Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya

Alex Kipnyargis; Eucharia Kenya; Fathiya Khamis; Romano Mwirichia

doi:10.12688/f1000research.134465.2

Home Browse Spatiotemporal structure and composition of the microbial communities...

ALL Metrics

Views

Downloads

Get PDF

Get XML

Export

▬

✚

Research Article

Revised

Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya

[version 2; peer review: 1 approved, 2 approved with reservations, 1 not approved]

Alex Kipnyargis ¹, Eucharia Kenya¹, Fathiya Khamis², Romano Mwirichia¹

PUBLISHED 17 May 2024

Author details Author details

¹ Department of Biological Sciences, University of Embu, Embu, Kenya
² Arthropod Pathology, International Centre of Insect Physiology and Ecology, Nairobi, Nairobi County, Kenya

Alex Kipnyargis
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Eucharia Kenya
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – Review & Editing

Fathiya Khamis
Roles: Conceptualization, Investigation, Methodology, Resources, Supervision, Visualization, Writing – Review & Editing

Romano Mwirichia
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Bioinformatics gateway.

Abstract

Background

Soda lakes are habitats characterized by haloalkaline conditions also known to host unique microbial communities. The water chemistry changes with seasons due to evaporative concentration or floods from the surrounding grounds. However, it is not yet clear if the change in physiochemical changes influences the spatiotemporal diversity and structure of microbial communities in these ecosystems.

Methods

Using 16S rRNA gene amplicon sequencing, we investigated the diversity and structure of microbial communities in water and brine samples taken from Lake Magadi between June and September 2018. Additionally, physicochemical parameters were also analyzed for every sampling site. Additionally, physicochemical parameters were also analyzed for every sampling site.

Results

The abundant bacterial phyla were Proteobacteria, Cyanobacteria, Bacteroidetes, Actinobacteria, Firmicutes, Verrumicrobia, Deinococcus-Thermus, Spirochaetes, and Chloroflexi. The Archaeal diversity was represented by phyla Euryachaeota, Crenarchaeota, Euryarchaeota, and Thaumarchaeota. The dominant bacterial species were: Euhalothece sp. (10.3%), Rhodobaca sp. (9.6%), Idiomarina sp. (5.8%), Rhodothermus sp. (3.0%), Roseinatronobacter sp. (2.4%), Nocardioides sp. (2.3%), Gracilimonas sp. (2.2%), and Halomonas sp. (2%). The dominant archaeal species included Halorubrum sp. (18.3%), Salinarchaeum sp. (5.3%), and Haloterrigena sp. (1.3%). The composition of bacteria was higher than that of archaea, while their richness and diversity varied widely across the sampling seasons. The α-diversity indices showed that high diversity was recorded in August, followed by September, June, and July in that order. The findings demonstrated that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) contributed majorly to the diversity observed in the microbial community. Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.

Conclusions

We provide insights into the relationships between microbial structure and geochemistry across various sampling sites in Lake Magadi.

Keywords

Soda lake, spatiotemporal, archaea, bacteria, physicochemical parameters, α-diversity, β-diversity

Corresponding author: Alex Kipnyargis

Competing interests: No competing interests were disclosed.

Grant information: This research was funded by the National Research Fund, Kenya (grant number NRF/1/MMC/470) to Romano Mwirichia.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2024 Kipnyargis A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Kipnyargis A, Kenya E, Khamis F and Mwirichia R. Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya [version 2; peer review: 1 approved, 2 approved with reservations, 1 not approved]. F1000Research 2024, 13:11 (https://doi.org/10.12688/f1000research.134465.2) First published: 03 Jan 2024, 13:11 (https://doi.org/10.12688/f1000research.134465.1) Latest published: 17 May 2024, 13:11 (https://doi.org/10.12688/f1000research.134465.2)

Revised Amendments from Version 1

This version contains the revisions that were suggested by the first reviewer.
Abstract: Multivariate analysis was used to explain the clustering of microbial communities. In this case, the results showed that concentrations of salts and alkalinity levels were responsible for the clustering of samples rather than the sampling time point.
Rather than using correlation analysis, the effects of water chemistry on the microbial structure were paraphrased to emphasize their influence.
Results: There was a reordering of data and figures to show results in chronological order. A few misleading sentences were also paraphrased as suggested by the reviewer.
Discussion: This section has been revised to depict the relationship of our findings with preexisting information on soda lakes. Those paragraphs that were seen as irrelevant to our results have been deleted.
Conclusion: The entire conclusion has been revised by me to better convey the important points about variety among sample locations and seasons as well as the influence of environmental conditions on the dynamics of microorganism populations in Lake Magadi. Your remarks were very beneficial.

See the authors' detailed response to the review by Marianne Haines

Introduction

Most living organisms are adapted to habitats characterized by moderate temperature (10–37°C), pH (of approximately 7), salinity (0.15–0.5 M NaCl), pressure (1 atm), and adequate supply of water (Aguilar et al., 1998; Antranikian et al., 2005). However, molecular techniques such as next-generation sequencing have revealed that diverse groups of organisms thrive even in biomes previously thought to be lifeless (Canganella & Wiegel, 2011; Rampelotto, 2013). Microbial communities in ecosystems such as the hypersaline lakes of the East African Rift Valley survive and thrive under one or several extreme conditions and are referred to as polyextremophiles (Sorokin et al., 2014a; Urbieta et al., 2015).

The distribution and diversity of microbial communities in hypersaline lakes are mainly affected by physicochemical parameters (Tazi et al., 2014). Lake Magadi is an example of an extreme habitat characterized by high concentrations of Na⁺, K⁺, CO₃^2–, Cl^–, HCO₃^–, and SiO_2, but low concentrations of Ca²⁺ and Mg²⁺ (Jones et al., 1998; Getenet et al., 2022). During the dry seasons, thermonatrite (Na₂CO₃.H₂O), and halite (NaCl) precipitate by evaporative concentration (Eugester, 1971, 1980). The lake is in a region with alternating wet and dry seasons. During the dry season, when ground temperatures exceed 40°С, there is extensive evaporation (Matagi, 2004; Muruga & Anyango, 2013). In addition, a white layer of soda covers the lake almost completely, and rainy days may result in flooding from the surrounding water entering the lake.

Despite the extreme conditions existing in the lake, it is a highly productive ecosystem with diverse microbial communities driving active nitrogen, carbon, and sulfur cycles (Jones et al., 1998; Sorokin et al., 2007). The high productivity is mainly driven by Arthrospira spp. and other cyanobacteria (Melack & Kilham, 1974; Oduor & Schagerl, 2007). Cyanobacteria in lake lagoons only form algal mats in these lakes during rainy seasons (Jones et al., 1998; Muruga & Anyango, 2013; Krenitz & Shagerl, 2016). Reports indicate that Ectothiorhodospira, an anoxygenic phototrophic halophilic bacterium, and eukaryotes such as diatomic and green algae also play an essential part in primary production (Matagi, 2004; Grant, 2006).

Many bacterial species have been isolated from extreme environments, and they frequently exhibit adaptations to optimal growth under the prevailing conditions (Krulwich et al., 2011; De Maayer et al., 2014; Sorokin et al., 2014b). Previously described isolates from Lake Magadi include the archaeal genera Natronobacterium and Natronococcus gen. nov. (Tindall et al., 1984) and Natronobacterium magadii, Natrialba magadii (Kamekura et al., 1997), bacterial species Spirochaeta alkalica sp. nov., Spirochaeta Africana (Zhilina et al., 1996), Tindallia magadiensis (Kevbrin et al., 1998), Halomonas magadii (Duckworth et al., 2000), Amphibacillus fermentum (renamed Pelagirhabdus fermentum) sp. nov., Amphibacillus tropicus, and Halonatronum saccharophilum (Zhilina et al., 2001), Methylonatrum kenyense (Sorokin et al., 2007), Euhalothece natronophila (Mikhodyuk et al., 2008) and Natranaerobaculum magadiense (Zavarzina et al., 2013). Edwin et al. (2019) recovered 11 isolates affiliated with the cyanobacterial orders Chroococcales, Oscillatoriales, Pleurocapsales, and Nostocales. Recent studies have reported isolates affiliated with the genus Bacillus, Alkalibacterium, Staphylococcus, Micrococcus, Halomonas, and Alkalilimnicola (Kiplimo et al., 2019; Kipnyargis et al., 2022). Orwa et al. (2020) recovered several fungal isolates affiliated with 18 different genera with Aspergillus, Penicillium, Cladosporium, Phorma, and Acremonium being dominant. Several studies have explored the microbial diversity in Lake Magadi using amplicons analysis targeting groups such as fungi (Kambura et al., 2016; Salano et al., 2017; Mwirichia, 2022) or bacteria (Kambura et al., 2016).

A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons. We hypothesized that microbial communities within the lake shift in response to changes in the water chemistry over time. We predict that the communities in the brines are different from those in the open lake water. In this study, we explored the spatiotemporal variation in the microbial community over four months at different sites in Lake Magadi using 16S rRNA gene sequencing.

Methods

Sampling site and sampling criteria

Sampling was done in hypersaline Lake Magadi, Kenya. It is located 1°43-2°00 S and 36°13-36°18E in an enclosed basin with an annual precipitation of 500 mm (Behr & Röhricht, 2000). Lake Magadi is a relatively shallow water body that is fed by various hot springs distributed along the edges of the lake. The inflows have an influence on the lake volume and the water chemistry. Water samples were collected from different points in the lake including spring, brine, and open waters. Samples were collected from these sites in June, July, August, and September 2018 and the dry season lasted for all the sampling months, with June marking the start of the season and September being the driest month. The coordinates of the sampling sites were: S1 (1.891380 S; 36.302632 E), S2 (1.895020 S; 36.299372 E), S3 (1.900988 S; 36.301307 E), S4 (1.908460 S; 36.301996 E), S5 (1.991601 S; 36.258904E), S6 (1.975517 S; 36.236564 E) and BR1 (1.887908 S; 36.300855 E) (Figure 1). S1 was composed of hot spring water, S2–S6 were composed of open waters, and BR1 was brine. Three sub-samples of 50 ml each were collected from each site and pooled into a composite sample. In addition, water samples for physicochemical analysis were collected. All samples were collected in sterile Conical Centrifuge tubes (Biologix, Shandong, China, Cat. No. 430829) and transported in a cool box.

Figure 1. Map of Lake Magadi showing the sampling sites.

Analysis of physicochemical parameters

Water temperature, pH, total dissolved solids (TDS), and salinity measurements were recorded in situ. Water temperature, TDS, and salinity were measured using a VWR phenomenal handheld Meter (VWR, Atlanta, GA, USA, Model CO 3100H), while pH was measured using a Hanna Combo pH meter (Hanna Instruments, Nusafalau, Romania, Model HI-98128). In this case, about 100 ml of sample water was put in a sterile 400 ml glass beaker (Marienfeld, Germany, Cat. No. BR91236). A pre-calibrated meter was dipped in the sample and the readings were recorded. Water samples for dissolved P, K⁺, NO₃^-, NH₄^-, Mg²⁺, Na^-, Fe^2-, Ca²⁺, SO₄^2-, Cl^-, and HCO₃^- measurements were collected in sterile 500ml bottles and stored in a cool box for transportation to Crop Nutrition Laboratory Services (CNLS), Nairobi where analysis was done. Cations such as Ca, Mg, K, Na, Mn, Fe, Cu, Mo, B, Zn, and S were analyzed using atomic absorption spectrometry (AAS). At the same time, anion analysis was carried out using mass spectrometry.

DNA extraction

Cell biomass for DNA extraction was obtained by centrifuging 50 ml of each water sample at 14,000 rpm for 20 minutes in an Eppendorf centrifuge (Eppendorf, Model 5415R, Cat. Z605212). The pellets were resuspended in 200 μl of a resuspension buffer (25% w/v sucrose (Sigma-Aldrich, Cat. No. S9378) in 50 mM Tris pH 8.5 (Sigma-Aldrich, Cat. No. 93352), and 50 mM EDTA; pH 8.0 (Sigma-Aldrich, Cat. No. 798681). To disrupt the cell wall of Gram positives, 2 μl of lysozyme (20 mg/ml) (Roche, Cat. No. 10837059001) and 10 μl of RNAse A (20 mg/ml) (Roche, Cat. No. 10109142001) were added and incubated at 37°C for 30 minutes. Cell lysis was achieved by the addition of 600 μl of a lysis buffer (1% SDS (Sigma-Aldrich, Cat. No. 8.17034) in 10 mM Tris pH 8.5 (Sigma-Aldrich) and 5 mM EDTA; pH 8.0 (Sigma-Aldrich). The samples were gently mixed with 10 μl of Proteinase K (20 mg/ml) (Sigma-Aldrich, Cat. No. 39450-01-6) and incubated at 65°C for 2 hours. DNA was recovered by adding an equal volume of chloroform (Sigma-Aldrich, Cat. No. C2432) followed by centrifugation at 13,200 rpm for 10 min at 4°C in an Eppendorf 5415R centrifuge. The aqueous layer was transferred into a new tube with 150 μl of sodium acetate (pH 5.2) (Sigma-Aldrich, Cat. No. S8750) and an equal volume of isopropyl alcohol (Sigma-Aldrich, Cat. No. 67-63-0). The contents were centrifuged at 13,200 rpm for 10 minutes and the DNA pellet was recovered by washing with 70% ethanol, air-dried for 15 minutes, and dissolved in 30 μl of nuclease-free water (Sigma-Aldrich, Cat. No. 7732-18-5). DNA quality was checked by running an aliquot of 2 μl in 1% agarose (Sigma-Aldrich, Cat. No. A9918) gel electrophoresis (Orwa et al., 2020).

Sequencing of the 16S rRNA amplicons

The V4 hypervariable region of the 16S rRNA genes was amplified using the universal primers for bacterial and archaeal primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) (Caporaso et al., 2012). Amplification was done using HotStarTaq Plus Master Mix Kit (Qiagen, USA) under the following cycling conditions: initial denaturation at 94°C for 3 minutes, followed by 35 cycles of denaturation at 94°C for 30 seconds, annealing at 53°C for 40 seconds and elongation at 72°C for 1 minute, after which a final elongation step at 72°C for 5 minutes was performed. Three independent PCR reactions were performed per sample and pooled in equimolar amounts. The PCR products were then checked in a 2% agarose gel. The sample was purified using calibrated Ampure XP beads (Beckman Coulter, Inc., IN, USA). DNA libraries were prepared using Illumina TruSeq DNA libraries (Illumina, Inc., San Diego, CA, United States) and sequencing was performed at MR DNA (Shallowater, TX, USA) on a MiSeq platform (2 × 300 bp) following the guidelines of the manufacturer (Illumina Inc.).

Sequence processing and taxonomic assignment

The Q25 sequence data derived from MiSeq sequencing was processed using the MR DNA ribosomal and functional gene analysis pipeline (MR DNA, Shallowater, TX). Sequences were depleted of primers, reads <250 bp, and ambiguous base calls were removed. The reads were quality-filtered using a maximum expected error threshold of 1.0. Sequences were further processed using VSEARCH v2.14 (Rognes et al., 2016). This included sorting and size-filtering of the paired reads to ≥300 bp (--sortbylength --minseqlength 300) and dereplication (--derep_fulllength). The sequences were then denoised and evaluated for potential chimeric sequences using UCHIME package v.11. (Edgar et al., 2011). Representative operational taxonomic units (OTUs) were picked de novo using VSEARCH v2.14 (Rognes et al., 2016), and assigned taxonomy using BLAST searches against the SILVA v132 rRNA reference database (Quast et al., 2012). A sequence identity cutoff of 97% was used to pick OTUs from the quality-filtered, denoised, non-chimeric sequences. Eukaryotic sequences were filtered from the dataset using the script filter_otu_table.py. in QIIME v1.90 (Caporaso et al., 2010b).

The Illumina raw reads for the 16S rRNA gene sequences were deposited in the Sequence Read Archive (SRA) of NCBI under the accession numbers PRJNA962270 (Kipnyargis et al., 2023b).

Microbial community analysis

Sequences with assigned taxonomy were aligned using PyNast (Caporaso et al., 2010a), and a phylogenetic tree was constructed using FastTree v2.1.7 (Price et al., 2010). The alpha diversity indices (Chao1, abundance-based coverage estimator (ACE), Simpson, Shannon, Fisher’s alpha, Pielou’s evenness, and Good’s coverage) were calculated with QIIME v1.90 (Caporaso et al., 2010) using alpha_rarefaction.py employing the same level of surveying effort (37,000 per sample based on the lowest sample count). All subsequent steps were analyzed in R software v4.2.0 (R Core Team, 2020) and RStudio v1.1.456 (RStudio Team, 2020). The results of all statistical tests were regarded as significant if p $\leq$ 0.05. To compare the (dis) similarity of OTU compositions between communities the OTU abundance table was standardized using decostand (method = “hellinger”). Hierarchical cluster analysis was performed using hclust in R software v4.2.0 (R Core Team, 2020) (method = “average”). The heatmap was created using JColorGrid v1.86 (Joachimiak et al., 2006).

The OTU network generated in QIIME was filtered using an edge cut-off of 0.001 and visualized in Cytoscape v3.9.1 (Otasek et al., 2019) in an “edge-weighted spring-embedded layout”. In this case, sampling sites were used as source nodes and bacterial families as target nodes. Redundancy analysis (RDA), based on Bray dissimilarity was used to test the correlation between the physicochemical parameters and the microbial community at the genus level. This was done using the Microeco package v0.15.0 (Liu et al., 2021) and plotted using the package Pheatmap in R.

To assess the beta diversity of microbial communities, a non-metric multidimensional scaling (NMDS) was performed using Bray-Curtis dissimilarities with the script compare_categories.py. test and weighted UniFrac distance matrix (Lozupone & Knight, 2005) as input using the Vegan package in R (Bray & Curtis, 1957; Oksanen, 2015).

Results

Physicochemical properties of the sampling sites

One of the objectives of this study was to investigate the change in water chemistry over time. It has been established that physicochemical factors play a critical role in shaping the structural composition of microbial communities in an ecosystem. Samples from site S1 (hot spring water) exhibited lower concentrations of the various ions and cations as compared to the other samples. The water temperature ranged from 27°C to 38.7°C (average 33.7°C). The pH of the water was alkaline, ranging from 9.8 (S6_June) to 11.5 (BR1_June) recording the highest pH value of 11.5. The major water cations were Na⁺ (10,300–160,000 ppm) and K⁺ (131–4,280 ppm), and the major anions were HCO₃⁻ (15,400–277,000ppm) and Cl⁻ (4,050–102,000 mg/L). Phosphorus levels ranged from 2.38–108 ppm, while magnesium and calcium levels were low, ranging from 0.02–16.1 and 0.05–127 ppm, respectively. The total dissolved solids (TDS) ranged from 27.1–153.5 ppm (Table 1).

Table 1. Physicochemical characteristics of the water samples collected from Lake Magadi.

TDS total dissolved solids, SAR sodium absorption ratio. The samples are denoted as S1 to S6, while BR1 represents the brine sample.

Sample	S1_June	S1_Sep	S2_June	S2_July	S2_Sep	S3_June	S3_July	S3_Aug	S3_Sep	S4_June	S4_July	S4_Aug	S4_Sep	S5_June	S5_July	S5_Aug	S5_Sep	S6_June	S6_July	S6_Aug	BR1_June	BR1_Sep
pH	10.5	10.4	10.6	10.2	10.7	10.5	10.5	11.3	10.4	10.5	10.5	11.1	10.9	10.2	9.9	10.3	10.2	10.3	9.8	10.4	11.5	11.2
Temp. (°C)	35.6	35.6	35.1	32.8	37.2	38.7	27	34.6	35.6	37.3	27	33.6	37.8	34.2	32.7	29.8	32.8	32.5	30.2	29.2	38.3	34.8
TDS (ppm)	27.1	27.1	137.6	143.9	145	114.1	135.4	139.2	153.5	110.7	134.6	139.8	143.3	46	45.7	45.7	42.9	104.9	118.1	83.9	136	134.8
P (ppm)	2.38	7.77	58.4	78	117	27.4	77.2	108	69.8	26.4	63.8	107	105	3.96	2.39	5.79	10.6	16.2	21.9	4.91	81.1	92.8
K (ppm)	131	365	2,300	2,700	4,280	1,220	2,430	3,300	2,560	1,130	1,960	3,270	2,370	201	190	280	378	697	697	513	3,410	3,210
NO₃ (ppm)	0.89	9.03	1.81	0.01	5.98	0.01	0.01	0.2	4.96	0.01	0.01	0.01	6.99	4.56	0.01	0.19	8.5	32	0.01	0.01	0.01	7.44
NH₄ (ppm)	0.02	0.69	0.072	0.2	0.98	0.017	0.082	0.013	0.53	0.033	0.01	0.056	0.86	0.076	0.076	1.04	1.52	0.01	0.16	0.59	0.47	0.79
Mg (ppm)	0.026	5.86	2.49	6.58	2.63	2.82	8.2	0.02	4.76	2.41	6.31	0.3	2.31	0.81	4.46	0.02	2.57	3.89	6.02	0.02	1.44	16.1
Mn (ppm)	0.06	0.01	0.045	0.066	0.01	0.076	0.23	0.01	0.019	0.15	0.13	0.11	0.01	0.01	0.01	0.01	0.01	0.24	0.74	0.15	0.028	0.53
S (ppm)	39.9	132	548	629	1010	324	708	958	710	304	585	973	949	97.2	90.7	71.4	182	213	271	178	845	974
Cu (ppm)	0.01	0.15	0.01	0.01	0.15	0.01	0.01	0.22	0.086	0.01	0.01	0.01	0.098	0.01	0.01	0.01	0.11	0.01	0.01	0.068	0.01	0.4
B (ppm)	6.8	14.6	103	126	197	55.7	126	184	116	52	108	184	169	13	12.4	11.2	20.4	37.8	43.6	28.2	147	160
Zn (ppm)	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.33	0.29
Na (ppm)	10,300	22,900	93,400	114,000	143,000	63,900	120,000	121,000	100,000	58,800	100,000	118,000	104,000	18,300	17,700	16,000	30,800	58,800	70,500	36,000	155,000	160,000
Fe (ppm)	2.79	0.53	0.01	1.34	0.01	2.13	9.63	0.91	0.92	2.42	3.17	1.59	0.17	0.25	2.5	0.01	0.25	4.1	14.7	3.82	0.86	0.49
Ca (ppm)	0.05	3.79	8.52	10.9	0.34	12	16.4	0.2	7.43	10.8	9.23	1.13	6.54	0.05	2.94	0.05	2.72	13.8	15.8	0.05	2.15	127
SO₄ (ppm)	120	395	1,640	1,880	3,030	971	2,120	2,870	2,130	911	1,750	2,920	2,840	291	272	214	545	638	812	533	2,530	2,920
Mo (ppm)	0.067	0.25	1.66	2.49	3.82	1.03	2.43	4.99	2.23	0.83	1.74	4.5	3.09	0.048	0.23	2.09	0.24	0.29	0.4	1.68	2.37	2.79
Cl (ppm)	4,050	3,720	52,300	77,400	102,000	30,700	72,300	99,800	74,200	30,200	60,500	93,100	62,500	7,910	8,620	7,680	6,740	24,100	32,500	16,700	93,500	99,000
NO₃N (ppm)	0.2	2.04	0.41	0.01	1.35	0.01	0.01	0.045	1.12	0.01	0.01	0.01	1.58	1.03	0.01	0.043	1.92	7.23	0.01	0.01	0.01	1.68
HCO₃ (ppm)	17,300	15,400	145,000	205,000	213,000	94,300	229,000	242,000	143,000	94,700	196,000	233,000	165,000	30,100	30,200	29,300	25,300	98,200	141,000	70,600	256,000	277,000
Si (ppm)	66.2	114	447	568	786	282	569	861	590	284	458	867	760	89.9	94.9	194	107	106	197	287	595	696
SiO₂ (ppm)	142	244	956	1,220	1,680	603	1,220	1,840	1,260	608	980	1,850	1,630	192	203	415	229	227	421	614	1,270	1,490
SAR (ppm)	9,310	1,720	7,230	6,730	18,200	4,310	6,040	69,000	7,050	4,210	6,220	25,500	8,900	4,290	1,520	15,300	3,220	3,600	3,830	34,400	20,100	3,550
CaCO₃ (ppm)	0.23	33.5	31.5	54.2	11.6	41.6	74.6	0.58	38.1	36.9	48.9	4.05	25.8	3.45	25.6	0.21	17.3	50.4	64.2	0.21	11.3	384

Sequence analysis and diversity studies

After quality filtering, denoising, and removal of potential chimeras and non-bacterial sequences, approximately 3,197,447 high-quality sequences with an average read length of 525 bp were obtained from the entire dataset. The number of sequences per sample varied from 37,406 (sample S5_Jun) to 285,085 (sample BR1_Sep) with an average value of 121,603 sequences. The number of OTUs per sample ranged from 852 (sample S3_July) to 2,024 (sample S5_Sep) (Table 2). Sequencing generated a total of 4,837 OTUs distributed in the domain Bacteria (3,802 OTUs) and Archaea (1,035 OTUs). Overall, most OTUs were found in the open waters samples of S5, while S4 had the least number of OTUs. The distribution of shared OTUs based on the month of sampling is shown in Extended data, Supplementary Figure 1 (Kipnyargis et al., 2023a).

Table 2. Number of sequences generated, OTUs, and diversity indices of 22 sampling sites in Lake Magadi.

OTUs, operational taxonomic units; ACE, abundance-based coverage estimator.

Sample	Number of Sequences	OTUS	Chao1	Ace	Simpson	Observed species	Shannon	Fisher alpha	Goods coverage
BR1_June	149,051	1,416	357.30	414.77	0.93	148	5.28	53.40	0.89
S1_June	191,597	1,089	171.50	175.11	0.93	89	4.63	25.63	0.94
S2_June	174,894	1,267	180.77	181.63	0.88	94	4.32	27.66	0.94
S3_June	139,647	1,513	251.65	319.48	0.94	131	5.15	44.51	0.91
S4_June	130,649	1,514	306.14	397.09	0.92	140	5.00	49.13	0.89
S5_June	37,406	1,221	363.23	452.68	0.96	209	6.16	92.00	0.85
S6_June	116,475	1,665	350.70	385.77	0.96	179	5.90	71.63	0.87
S2_July	177,773	1,259	301.33	300.15	0.91	98	4.49	29.32	0.92
S3_July	177,827	852	171.50	162.62	0.66	69	2.86	18.11	0.95
S4_July	156,660	1,167	166.62	189.02	0.90	87	4.31	24.84	0.94
S5_July	109,083	1,917	435.14	487.08	0.97	231	6.54	108.85	0.83
S6_July	103,156	1,149	181.32	192.37	0.86	106	4.19	32.76	0.93
S3_Aug	177,142	874	91.91	107.34	0.79	55	3.20	13.39	0.96
S4_Aug	172,666	934	175.86	143.57	0.84	70	3.70	18.46	0.95
S5_Aug	83,183	1,815	572.10	579.97	0.97	222	6.28	101.75	0.82
S6_Aug	64,022	1,732	497.95	457.95	0.98	200	6.57	85.59	0.86
BR1_Sep	285,085	1,710	323.50	356.33	0.95	178	5.75	71.00	0.88
S1_Sep	180,065	1,583	341.16	436.97	0.95	177	5.77	70.38	0.87
S2_Sep	170,143	1,114	184.23	213.10	0.89	90	4.34	26.03	0.94
S3_Sep	149,323	1,124	149.37	174.86	0.75	90	3.50	26.03	0.94
S4_Sep	151,058	956	185.17	135.22	0.80	68	3.26	17.76	0.95
S5_Sep	100,542	2,024	594.50	641.88	0.98	248	6.85	123.09	0.81

Alpha diversity studies

The values of the good’s coverage estimator ranged from 81% (S5_Sep) and 96% (S3_Aug) suggesting that the sequencing process captured a significant number of dominant communities. Within the open water samples (S2–S6), site 5 samples collected across the seasons had the highest alpha diversity indices suggesting that S5 had the highest species richness and diversity. S3_Aug samples (open waters) had the lowest alpha diversity indices. Within the hot spring samples (S1), S1 samples collected in September had the highest species richness and diversity. Within the brine samples (BR1), Br1 samples collected in September had the highest species diversity and richness (Table 2).

The alpha diversity indices showed that high microbial diversity was recorded in August, followed by September, June, and July in that order (Figure 2).

Figure 2. Alpha diversity plots of OTU richness among different sampling months.

Beta diversity studies

Beta diversity ordination based on Bray-Curtis dissimilarity showed that samples (except hot spring and brine samples) did not cluster based on the sampling site. Overall, all samples clustered together based on salinity and alkalinity, indicating the impact of these elements on the structure of the bacterial and archaeal communities (Figure 3; Table 1). The principal component (PCA) analysis showed that the first (PC1) and second (PC2) axes described 38.7% and 17.9% of the variance in microbial communities, respectively. Accordingly, samples were clustered into three distinct groups based on alkalinity and salinity. Low alkalinity and salinity samples (pH 9.8 – 10.5; 10,300 ppm – 70,500 ppm) formed cluster I with nine samples (S1_06, S1_09, S5_06, S5_09, S5_08, S5_07, S6_08, S6_06, and S6_07). Moderately alkaline and saline samples (pH 10.5 – 10.6; 63, 900 ppm – 100,000 ppm) formed cluster II with six samples (S3_06, S4_06, S2_06, S3_07, S2_07, and S4_07). Highly alkaline and saline samples (pH 10.7-11.5; >100,000 ppm) formed cluster III consisting of six samples (Br1_06; 155,000 ppm, Br1_09; 160,000 ppm, S4_09; 104,000 ppm, S2_09; 143,000 ppm, S3_08; 121,000 ppm, and S4_08; 118,000 ppm).

Figure 3. Principal component analysis (PCA) ordination of differences in microbial communities from sampling sites and sampling months.

Taxonomic composition and structure

The proportion of bacteria to archaea varied by season and sampling month (Figure 4). The results indicate that the archaeal population increased as the ion concentration increased while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1). In hot spring water (S1), archaea abundance was the lowest while bacterial abundance was the highest. Within open water samples (S2–S6), S4 had the highest abundance of archaea, while S5 had the highest proportion of bacteria. Within the brine (BR1), the archaea proportion was relatively higher than the bacterial communities. From June to September 2018, bacterial abundance decreased while archaeal abundance increased (Figure 4A).

Figure 4. Relative abundance and composition of the microbial community taxa based on sampling sites and month of sampling.

(A) The proportion of Domains bacteria and archaea across the sampling sites and months. (B) Relative abundance of the most popular bacterial and archaeal phyla across the sampling sites and the sampling months.

The bacterial reads were distributed across 25 phyla, 107 orders, 225 families, and 545 genera. The results revealed that the most abundant bacterial phyla across the sampling sites and the four months of sampling included Proteobacteria (35% of all the reads), Cyanobacteria (14.2%), Bacteroidetes (10.9%), Actinobacteria (5.2%), Firmicutes (2.7%), Verrumicrobia (1.1%). Deinococcus-Thermus (0.6%), Spirochaetes (0.4%), and Chloroflexi (0.1%) were detected in lower abundances (Figure 4B). At the genus level, the dominant bacterial genera (> 1% of all sequences across all samples) were Euhalothece (10.3%), Rhodobaca (9.6%), Idiomarina (5.8%), Rhodothermus (3.0%), Roseinatronobacter (2.4%), Nocardioides (2.3%), Gracilimonas (2.2%), Halomonas (2.0%), Lewinella (1.9%), Synechococcus (1.8%), Aliidiomarina (1.8%), Nitriliruptor (1.7%), Thioalkalivibrio (1.7%), Salinibacter (1.4%), Alkalimonas (1.25%), Chelatococcus (1.4%), and Rhodovulum (1.4%). Others included: Cytophaga (0.9%), Natronocella (0.9%), Thiohalomonas (0.9%), Euzebya (0.8%), Paracoccus (0.8%), and Luteolibacter (0.8%). The abundance of bacterial genera was higher in the sampling site S5 (25.3%) followed by S6 with 20.1%, S3 (14.5%), S1 and S4 with 12.8% each, and brine sample BR1 with 3.9% abundance in that order. In terms of the sampling month, June had the highest bacterial abundance with 39.5% followed by July (27%), September (16.8%), and August (16.2%) in that order.

The archaeal reads were affiliated to three phyla (Euryachaeota, Crenarchaeota, and Thaumarchaeota) (Figure 4B), 14 orders, 20 families, and 62 genera. The dominant Phylum was Euryachaeota (87% of all Archaeal samples), with its dominant genera (>1% of all sequences across all samples) being Halorubrum (18.3%), Salinarchaeum (5.4%), and Haloterrigena (1.3%). Other genera included Methanomassiliicoccus (0.6%), Palaeococcus (0.4%), Halovenus (0.3%), Thermococcus (0.3%), Haladaptatus (0.3%), Halorientalis (0.3%), Methanobrevibacter (0.2%), Natronomonas (0.2%), Halohasta (0.2%), Haloquadratum (0.1%), and Methanobacterium (0.1%). The abundance of archaeal genera was higher in S3 (27.2%) followed by brine site BR1 with 21.6% abundance. S1 and S6 had the least archaeal abundance with 0.08 and 0.8%, respectively. In terms of the sampling month, September had the highest archaeal abundance with 53% followed by August (23%), June (12.7%), and July (11.4%).

The bacterial species composition (>1%) included Euhalothece spp. (10.3%), Rhodobaca spp. (9.6%), Idiomarina spp. (5.8%), Rhodothermus spp. (3.0%), Roseinatronobacter spp. (2.4%), Nocardioides spp. (2.3%), Gracilimonas spp. (2.2%), Halomonas sp. (2%), Lewinella (1.9%), Synechococcus spp. (1.8%), Cyanobacterium spp. (1.8%), Aliidiomarina spp. (1.7%), Nitriliruptor spp. (1,7%), Thioalkalivibrio spp. (1.7%), Salinibacter spp. (1.4%), Alkalimonas spp. (1.2%), Chelatococcus spp. (1.1%), and Rhodovulum spp. (1.1%). The Euhalothece natrophila species were abundant in June, July, and August, except in sites S5 and S6 across all seasons. Rhodobaca bogoriensis was largely sampled in June and site S6 in July and August 2018. Idiomarina spp. were largely concentrated in June, particularly in sites S1 and S5, whereas Rhodovulum spp. were sampled across all seasons. Lewinella coherens were sampled in June mostly in sites S3 and S4. On the other hand, Halorubrum spp. (18.3%), Salinarchaeum spp. (5.3%), Haloterrigena spp. (1.3%), Methanomassiliicoccus spp. (0.7%), and Palaeococcus spp. (0.5%) were the major species in the Archaeal Domain. Idiomarina vacuolatum was sampled across all the sampling seasons but its abundance varied across the sampling sites. Halorubrum vacuolatum was mainly sampled in August (S1 and S2) and September (S3, S4, and S5). Salinarchaeum sp. was mainly sampled in September, while Haloterrigena spp. was sampled across the seasons and sites, though in low proportions. The top 30 most abundant species of bacteria and archaea are shown in Figure 5. Overall, Halorubrum spp. was the most abundant species sampled followed by Euhalothece spp. and Rhodobaca spp. (Extended data, Supplementary Figure 2 (Kipnyargis et al., 2023a)).

Figure 5. Read abundance (%) of the top 30 species across samples.

Microbial co-occurrence network analysis at the family level revealed that bacterial members of the family Cyclobacteriaceae, Burkholderiaceae, and Alteromonadaceae were unique to the S1 sampling site. Bacterial members of Halobacteroidaceae, Spirochaetaceae, halanaerobiaceae, and desulfohalobiaceae, as well as Archaeal members of Archaeoglobaceae and Methanobacteriaceae, were found exclusively in the S2 sampling site. Phyllobacteriaceae and Nostocaceae were unique to S3, while Alcanivoracaceae, Carnobacteriaceae, and Marinilabiliaceae bacteria were found in S5 only. Unique to S6 were the bacterial Puniceicoccaceae family. The highest number of co-shared families was found between S5 and S1 co-sharing eight families, whereas Bacilaceae and Natranaerobiaceae were found in S5 and S2, and S6 and S2 co-shared only one family (Pseudomonadaceae) (Figure 6).

Figure 6. Network analysis of microbial community at Family level based on sampling sites.

Samples marked with red squares indicate their exclusive site of isolation.

Physicochemical drivers of bacterial and archaeal community structure

Redundancy analysis (RDA) was used to assess the effect of water chemistry on microbial community structure in Lake Magadi. The results reveal that changes in the physicochemical parameters influenced the microbial communities in the lake (Extended data, Supplementary Table 2 (Kipnyargis et al., 2023a)). The RDA explained 62.2% and 17.2% of the variation in the first (RDA1) and the second (RDA2) axes, respectively (Figure 7).

Figure 7. Redundancy Analysis (RDA) ordination showing the relationships between the physicochemical factors and the dominant genera in Lake Magadi. Samples corresponding to their sampling month are indicated, while genera are written in red, and environmental variables are indicated by arrows. TDS corresponds to total dissolved solids.

The results demonstrated that temperature, pH, P, K, NO₃^-, and TDS significantly influenced the microbial community structure. Generally, members of genera Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece spp. had a wide range of adaptability. Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium, Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas spp. were least influenced by the tested physicochemical factors (Extended data, Supplementary Figure 3 (Kipnyargis et al., 2023a)). Notably, Halorubrum and Haloterrigena spp. were positively correlated with P and K (R² = 0.66, p < 0.001), but negatively correlated with Mn and CO₃^2-. pH and NH4⁺ appear to positively correlate with the structure of the members of the genus Salinarcheum (R² = 0.245; p < 0.004), but negatively correlated with NO₃^-. Members of Alkalimonas, Idiomarina, and Aliidiomarina spp. were positively correlated with NO₃^- (R² = 0.049, p < 0.210), but negatively correlated with all other tested parameters. Members of Nocardiodes, Rhodothermus, Salinarcheum, Salinibacter, and Euhalothece spp. were positively correlated with total dissolved solids (TDS), alkalinity, salinity, CO₃²⁺, and NH₄⁺ (R² = 0.606, p < 0.001), but negatively correlated with Mg²⁺, Mn, and NO₃^-. On the other hand, Mn, temperature CO₃^2-, and NH₄⁺ negatively affect the structure of Rhodobaca.

Discussion

We explored the structure and composition of microbial communities based on the seasonality and physicochemical parameters of Lake Magadi. The physicochemical parameters revealed high concentrations of sodium salts, HCO₃^-, SO₄^2-, pH values of 9.8–11.5, temperatures of 27–38°C, and low concentrations of Ca²⁺, Mg²⁺, and Cu²⁺. These findings were consistent with previous reports indicating that soda lakes are characterized by moderate to high temperatures, high concentrations of HCO₃⁻/CO₃²⁻, and reduced concentrations of Ca²⁺ and Mg²⁺ (Sorokin et al., 2014a; Vavourakis et al., 2018). However, total dissolved solids (TDS) ranged from 27 ppm (0.02g/L) to 143 ppm (0.143g/L), a situation that is lower than other soda lakes (Taher, 1999; Hosam et al., 2017; Pérez & Chebude, 2017). Sulfate concentration (120–3,030 ppm) was similar to most soda lakes in East Africa (Lameck et al., 2023), but higher than the concentration reported in Lake Lancago in Qinghai-Tibet (Wang et al., 2022). Comparatively lower sulfate concentrations have been reported from lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012) and Lake Hamra in Egypt (Mahmoud et al., 2024). The concentrations of the measured elements (except pH) were variable from site to site and fluctuated with time, indicating that the lake chemistry is constantly changing in its constituent elements. A high and stable pH recorded in Lake Magadi is due to high amounts of carbonates that maintain a constant pH in soda lake ecosystems (Simachew et al., 2016). It is postulated that Ca²⁺ and Mg²⁺ precipitate as insoluble carbonates due to high evaporation rates in these ecosystems. As a result, an alkaline brine with Na⁺, Cl⁻, and HCO₃⁻/CO₃²⁻ accumulates as main ions. The shift in CO₂/HCO₃⁻/CO₃²⁻ equilibrium towards CO₃²⁻, leads to the formation of a soda (Na₂CO₃) lake with pH values of over 10.0 (Grant and Jones, 2016).

A high number of OTUs was detected for the domain Bacteria with 3,802 OTUs while Archaea had 1,035 OTUs. Bacterial diversity was dominated by the phyla Proteobacteria (35% of all the reads), Cyanobacteria (14.2%), Bacteroidetes (10.9%), Actinobacteria (5.2%), Firmicutes (2.7%), Verrumicrobia (1.1%). On the other hand, Deinococcus-Thermus (0.6%), Spirochaetes (0.4%), and Chloroflexi (0.1%) were detected in lower abundances in Lake Magadi. Similar results have been shown from soda ecosystems such as Solar saltern in Tunisia (Menasria et al., 2019), lake Chott El Jerid (Abdallah et al., 2018), hot springs of Lake Magadi (Kambura et al., 2016), and lakes Sonachi, Magadi, Elmenteita, and Bogoria in Kenya (Mwirichia, 2022). Members of the phylum Proteobacteria were the most dominant group across all the time points and sampling sites. The role of members of Proteobacteria such as Burkholderiaceae is to decompose recalcitrant organic matter while others like Beijerinckiaceae fix atmospheric nitrogen (Li et al., 2012). The phylum Cyanobacteria, the major contributor to nitrogen fixation in soda lakes (Sorokin & Kuenen, 2005), was represented mainly by the Euhalothece spp. Euhalothece is a single-celled stenohaline cyanobacterium growing optimally at 7% (w/v) NaCl. They depict a morphological variability depending on the concentrations of NaCl and carbonates as well as the pH conditions (Mikhodyuk et al., 2008). The presence of Euhalothece in Lake Magadi is thus supported by high salts and carbonates (Table 1). Contrastingly, the results in other soda lakes have shown that Arthrospira spp. are the main photosynthetic agents driving primary productivity, with the seasonal occurrence of Cyanospira, Synechococcus, and Chroococcus to augment this process (Jones et al., 1998). Thirdly, members of the phylum Bacteroidetes were majorly represented by the genera Rhodothermus, Roseinatrobacter, Gracilimonas, Lewinella, and Cytophaga. Verrumicrobia was represented by Verrucomicrobium, Puniceicoccus, and Coraliomargarita. Bacteroidetes and Verrucomicrobia are known to thrive in high-nutrient environments where they play a role in the degradation of biopolymers such as cellulose and chitin (Newton et al., 2011). Interestingly, the presence of Bacteroidetes and Verrucomicrobia was often associated with the availability of Cyanobacteria across the sites and the sampling periods (Extended data, Supplementary Table 1 (Kipnyargis et al., 2023a)). Photosynthetic stages of cyanobacteria lead to a high rate of CO₂ and HCO₃^- consumption, and a consequent increase in pH (Almeida et al., 2011). As a result, nutrient release is enhanced from the sediments of the lake, hence acting as substrates for Bacteroidetes and Verrucomicrobia. Phylum Firmicutes (2.7% of all the reads) was represented by members of Class Clostridium (Clostridium, Halanaerobium, Natranaerobius, and Moorella sp.) and Bacilli (Alkalibacterium and Anoxybacillus sp.).

The archaeal community of the Lake Magadi microbiome was represented by three phyla, the Euryachaeota (25% of all the reads), Crenarchaeota (0.01%), and Thaumarchaeota (0.01%). Generally, archaea were more abundant in brine samples with Br1_June and Br1_Sept accounting for 24.5% of total archaea. Previous studies have indicated that archaea are more adapted to saline environments than bacteria (Mani et al., 2020). Euryachaeota was the most abundant phylum across the sites and the sampling seasons with 87% of all archaeal communities. Euryachaeota has well-adapted inhabitants of hypersaline environments where they play a critical role in ecosystem services such as carbon cycling by functioning as methanogens (Jiang et al., 2007; Vavourakis et al., 2016). Grant et al. (1999) first characterized this phylum in the alkaline saltern of Lake Magadi. The second most abundant group was Thaumarchaeota also known as ammonia-oxidizing agents (Andreote et al., 2018). In marine environments, their distribution along a salinity gradient has been linked to changes in location, salinity, and sediment depth (Webster et al., 2015). A one-time sampling of the Lake Magadi hot springs depicted a similar picture with Euryachaeota accounting for up to 28% abundance while Thaumarchaeota and Crenarchaeota were each 1% abundant (Kambura et al., 2016). Studies in other soda lakes that have detected members of the phylum Euryachaeota and Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota (Wang et al., 2022). However, explorations in Soda Lake in Salina Preta, Brazil, revealed the contrary where members of Thaumarchaeota were most abundant while Euryarchaeota was least abundant (Andreote et al., 2018). The most abundant archaeal genera belonged to Halorubrum (18.3%), Salinarchaeum (5.4%), and Haloterrigena (1.3%). Most of these microbes have their habitats in soda lakes and neutral saline environments (Feng et al., 2005; Mwatha & Grant, 2016; Minegishi et al., 2017; Zhao et al., 2020). Other haloalkaliphilic archaea related to genera Natronomonas, Natrialba, Natrococcus, Natronobacterium, Natronolimnobius, and Halorubrum, all of whom were detected in this study, have previously been isolated from brines of East African soda lakes and Inner Mongolian lakes where salinity values reach > 30%, and pH values of >10 (Grant and Sorokin, 2011). Overall, the results of this study reflect bacterial composition in many soda lakes around the world (Sorokin et al., 2014a; Kambura et al., 2016; Mani et al., 2020; Poyraz & Mutlu, 2020; Wang et al., 2022).

Co-occurrence network analysis demonstrates the interactions between microbial taxa, which can be symbiotic or competitive (He et al., 2019). At the family level revealed the presence of heterogenous microbial communities that co-occur in different sampling sites along the lake as well as others that were unique to a particular site, suggesting mutual interactions of these communities across the sites. For instance, Desulfobacteriaceae were unique to S2. Correspondingly, S2 had the highest concentration of both sulfur and sulfate ions (Table 1). This family, particularly Desulfonatronum, Desulfonatronospira, Desulfonatronovibrio, and Desulfohalophilus have been shown to thrive in anoxic parts of soda lakes acting as sulfate-reducing bacteria (SRB) through the oxidation of hydrogen and formate or direct disproportionation of sulfite of thiosulfate (Sorokin et al., 2011). Noteworthy, Thioalkalivibrio sp. was not significantly influenced by the physicochemical properties investigated. This suggests that these strains have devised adaptive mechanisms to thrive under the prevailing harsh conditions of Lake Magadi. Indeed, Thioalkalivibrio sp., which are sulfur-oxidizing bacteria (SOB), have been found to adapt well in soda lake ecosystems (Li et al., 2022). Unique to the S6 site were the members of the family Puniceicoccaceae which have also been described in four soda lakes of the Cariboo Plateau in Canada (Zorz et al., 2019). Cyclobacteriaceae retrieved from the S1 site have established habitats in diverse ecosystems like cold marine regions like algal/microbial mats, haloalkaline soda lakes, Antarctica, freshwater bodies, marine waters, marine sediments, mangroves, hot springs, and mud volcanoes (Rosenberg et al., 2014). Members of families Rhodobacteraceae and Cyclobacteriaceae have sulfate–oxidizing properties, whereas Burkholderiaceae (unique to S1) have adapted to different ecological niches and are involved in processes such as catabolism of aromatic compounds as well as nitrogen fixation (Pérez-Pantoja et al., 2012).

Alpha diversity studies revealed that samples in the open waters, particularly S5, had the highest species richness and diversity. However, open waters samples from S2–S4 depicted varying degrees of microbial diversity. While this could not be conclusively explained, it has been suggested that water waves affect the distribution and degradation of organic matter degradation and nutrient cycling, thereby influencing the composition diversity of microbes in water ecosystems (Zhu et al., 2018). Brine samples (BR1) in June and September had relatively high diversity and evenness indices. Despite high salinity and alkalinity in soda lake brine, the presence of high light intensity and dissolved CO₂ promotes the growth of photosynthetic microorganisms. Subsequently, these phototrophs generate large quantities of dissolved organic matter (DOM) which become substrates for sustaining the diverse microbial communities (Banda et al., 2020). Moreover, hot spring samples (S1) exhibited high Shannon and Simpson diversity indices, an indication of high microbial diversity. Research on Soda Lake hot springs revealed a highly active and diverse microbial community, suggesting the high plasticity of these organisms toward extreme environments (Dadheech et al., 2013; Kambura et al., 2016).

The principal component analysis revealed that compared with other samples, hot spring (S1) and brine (BR1) samples clustered according to their sites (cluster I and II, respectively) (Figure 3) . This indicates that hot spring and brine samples had distinct community similarities (Tao et al., 2019). However, samples appeared to cluster based on the changes in the salinity and alkalinity of the sampling sites from low to high salinity and alkalinity clusters. This is an indication that the impact of time point sampling on the community structure was limited. Previous studies have established that salinity is the primary selective force driving the distribution of beta diversity, whereas alkalinity influences microbial richness (Antony et al., 2013; Boros & Kolpakova, 2018; Banda et al., 2020). Moreover, extreme salinity and alkalinity confine the microbial communities to a few taxa highly adapted to the prevailing conditions (Oren, 2011).

In terms of water chemistry (Figure 7; Extended data, Supplementary Figure 3 (Kipnyargis et al., 2023a)), pH, temperature, PO₄^3-, K, and NO₃⁻, NH₄⁺, Mn, Na⁺, SO₄^2-, and TDS influenced the variation of microbial community composition in Lake Magadi. Salinity and alkalinity tend to influence the distribution of the microbial communities in the Soda Lake ecosystem. Specifically, members of genera Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of physicochemical adaptability. Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were least influenced by the tested physicochemical factors (Extended data, Supplementary Figure 3 (Kipnyargis et al., 2023a)). The archaeal genera Salinarchaeum and Halorubrum Halobellus, Halolamina, Methanobrevibacter, and Halorhabdus have been strongly associated with salinity and factors such as pH, Mg²⁺, Na⁺, K⁺, Ca²⁺, and SO₄^2– (Han et al., 2017). Nitrate appears to drive the structure of the members of the genera Aliidiomarina, Idiomarina, and Alkalimonas (Figure 4, Extended data Supplementary Figure 3 (Kipnyargis et al., 2023a)). Many strains of Alkalimonas have been isolated from Chahannor (China), Kulunda Steppe (Russia), and Elementaita (Kenya) soda lakes where they play a role in nitrate reduction and formation of H₂S (Ma et al., 2004; Vavourakis et al., 2016). However, in this study, sulfur was negatively correlated with Alkalimonas. The Aliidiomarina and Idiomarina belong to the family Idiomarinaceae and have also been described as nitrogen reducers but poor in carbohydrate utilization (Chiu et al., 2014).

Conclusion

Studies combining ecological, physiological, and taxonomic aspects have shown the remarkable diversity of halocaliaphiles in numerous saline and alkaline lakes. The current study determined the structure of the microbial communities in different sampling sites and time points in Lake Magadi and explored the influence of physicochemical parameters on the composition and diversity of these microorganisms. Our findings indicated that results revealed that in comparison to archaea, bacteria are much more diverse in this ecosystem. The bacterial community was dominated by the phyla Proteobacteria, Cyanobacteria, Bacteroidetes Actinobacteria, Firmicutes, and Verrumicrobia. On the other hand, archaea were majorly composed of Euryachaeota while Crenarchaeota, and Thaumarchaeota were found in the least abundance across the sampling seasons and sites. Species richness and diversity varied within open waters while samples from brine (Br_1) and hot spring (S1) revealed high diversity and evenness was recorded. Ordination studies indicated that samples clustered based on salinity and alkalinity rather than the sampling season. Water chemistry depicted high concentrations of sodium salts, HCO₃^-, SO₄^2-, pH values of 9.8–11.5, temperatures of 27–38°C, and low concentrations of Ca²⁺, Mg²⁺, and Cu²⁺. Temperature, pH, P, K, NO₃^-, and TDS significantly influenced the microbial community distribution in Lake Magadi. Our research highlights the composition and diversity of microbial communities across four successive dry months of soda Lake Magadi and the key physicochemical factors influencing them. We recommend future research focus on the functional profiles of samples during and after cyanobacterial blooms, including vertical profile stratification of Lake Magadi. The inclusion of sediment samples will also elucidate the taxonomic and functional profile of anoxic microbial communities.

Data availability

Underlying data

NCBI BioProject: Prokaryotic diversity within the hypersaline Lake Magadi in Kenya. Accession number: PRJNA962270. https://www.ncbi.nlm.nih.gov/bioproject/PRJNA962270/ (Kipnyargis et al., 2023b).

Extended data

Figshare: Structure and composition of the microbial communities in hypersaline Lake Magadi: Additional Materials. https://doi.org/10.6084/m9.figshare.22699456 (Kipnyargis et al., 2023a).

This project contains the following extended data:

• Supplementary Figure 1.png (The distribution of shared operational taxonomic units (OTUs) based on the month of sampling in Lake Magadi.)
• Supplementary Figure 2.png (Percentage read abundance of the top 20 species of the microbial communities collected from Lake Magadi.)
• Supplementary Figure 3.png (The influence of physicochemical parameters on the structure of microbial communities in Lake Magadi.)
• Supplementary Table 1.xlsx (Percentage abundance of bacterial and archaeal communities in Lake Magadi across the sampling months, broken down by phylum.)
• Supplementary Table 2.docx (Mantel test results of the effects of physicochemical factors on microbial structure and composition in Lake Magadi.)

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

References

Abdallah MB, Karray F, Kallel N, et al.: Abundance and diversity of prokaryotes in ephemeral hypersaline lake Chott El Jerid using Illumina Miseq sequencing, DGGE and qPCR assays. Extremophiles. 2018; 22: 811–823. PubMed Abstract | Publisher Full Text
Aguilar A, Ingemansson T, Magnien E: Extremophile microorganisms as cell factories: Support from the European Union. Extremophiles. 1998; 2(3): 367–373. PubMed Abstract | Publisher Full Text
Almeida TIR, Calijuri MC, Falco PB, et al.: Biogeochemical process and the diversity of Nhecolândia lakes, Brazil. An. Acad. Bras. Ciênc. 2011; 83:391–407. PubMed Abstract | Publisher Full Text
Andreote APD, Dini-Andreote F, Rigonato J, et al.: Contrasting the genetic patterns of microbial communities in soda lakes with and without cyanobacterial bloom. Front. Microbiol. 2018; 9(244): 1–13. PubMed Abstract | Publisher Full Text | Free Full Text
Antony CP, Kumaresan D, Hunger S, et al.: Microbiology of Lonar Lake and other soda lakes. ISME J. 2013; 7(3): 468–476. PubMed Abstract | Publisher Full Text | Free Full Text
Antranikian G, Vorgias CE, Bertoldo C: Extreme environments as a resource for microorganisms and novel biocatalysts. Adv. Biochem. Eng. Biotechnol. 2005; 96(8): 219–262. Publisher Full Text
Banda JF, Lu Y, Hao C, et al.: The Effects of Salinity and pH on Microbial Community Diversity and Distribution Pattern in the Brines of Soda Lakes in Badain Jaran Desert, China. Geomicrobiol. J. 2020; 37(1): 1–12. Publisher Full Text
Behr HJ, Röhricht C: Record of seismotectonic events in siliceous cyanobacterial sediments (Magadi cherts), Lake Magadi, Kenya. Int. J. Earth Sci. 2000; 89(2): 268–283. isi:000089932800007. Publisher Full Text
Boros E, Kolpakova M: A review of the defining chemical properties of soda lakes and pans: An assessment on a large geographic scale of Eurasian inland saline surface waters. PLoS One. 2018; 13(8): e0202205. PubMed Abstract | Publisher Full Text | Free Full Text
Boutaiba S, Hacene H, Bidle KA, et al.: Salt Lakes of the Algerian Sahara. J. Arid Environ. 2012; 75(10): 909–916. PubMed Abstract | Publisher Full Text | Free Full Text
Bray JR, Curtis JT: An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. 1957; 27(4): 325–349. Publisher Full Text
Canganella F, Wiegel J: Extremophiles: From abyssal to terrestrial ecosystems and possibly beyond. Naturwissenschaften. 2011; 98(4): 253–279. PubMed Abstract | Publisher Full Text
Caporaso JG, Bittinger K, Bushman FD, et al.: PyNAST: A flexible tool for aligning sequences to a template alignment. Bioinformatics. 2010a; 26(2): 266–267. PubMed Abstract | Publisher Full Text | Free Full Text
Caporaso JG, Kuczynski J, Stombaugh J, et al.: QIIME allows analysis of high-throughput community sequencing data. Nat. Methods. 2010b; 7(5): 335–336. PubMed Abstract | Publisher Full Text | Free Full Text
Caporaso JG, Lauber CL, Walters WA, et al.: Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012; 6(8): 1621–1624. PubMed Abstract | Publisher Full Text | Free Full Text
Chiu HH, Rogozin DY, Huang SP, et al.: Aliidiomarina shirensis sp. nov., a halophilic bacterium isolated from Shira Lake in Khakasia, southern Siberia, and a proposal to transfer Idiomarina maris to the genus Aliidiomarina. Int. J. Syst. Evol. Microbiol. 2014; 64(4): 1334–1339. Publisher Full Text
Dadheech PK, Glöckner G, Casper P, et al.: Cyanobacterial diversity in the hot spring, pelagic, and benthic habitats of a tropical soda lake. FEMS Microbiol. Ecol. 2013; 85(2):389–401. PubMed Abstract | Publisher Full Text
De Maayer P, Anderson D, Cary C, et al.: Some like it cold: Understanding the survival strategies of psychrophiles. EMBO Rep. 2014; 15(5): 508–517. PubMed Abstract | Publisher Full Text | Free Full Text
Duckworth AW, Grant WD, Jones BE, et al.: Halomonas magadii sp. nov., a new member of the genus Halomonas, isolated from a soda lake of the East African Rift Valley. Extremophiles. 2000; 4(1): 53–60. PubMed Abstract | Publisher Full Text
Edgar RC, Haas BJ, Clemente JC, et al.: UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011; 27(16): 2194–2200. PubMed Abstract | Publisher Full Text | Free Full Text
Edwin N, Akhwale JK, Mwirichia R: Phylogenetic and morphological diversity of culturable cyanobacteria from Lake Magadi in Kenya. Afr. J. Biol. Sci. 2019; 01(4): 24–31. Publisher Full Text
Eugester H: Origin and Deposition of Trona. Rocky Mt. Geol. 1971; 10(1): 49–55.
Eugster HP: Lake Magadi, Kenya, and its precursors. Dev. Sedimentol. 1980; 28(C): 195–232. Publisher Full Text
Feng J, Zhou P, Zhou YG, et al.: Halorubrum alkaliphilum sp. nov., a novel haloalkaliphile isolated from a soda lake in Xinjiang, China. Int. J. Syst. Evol. Microbiol. 2005; 55(1): 149–152. Publisher Full Text
Getenet M, García-Ruiz JM, Otálora F, et al.: A Comprehensive Methodology for Monitoring Evaporitic Mineral Precipitation and Hydrochemical Evolution of Saline Lakes: The Case of Lake Magadi Soda Brine (East African Rift Valley, Kenya). Cryst. Growth Des. 2022; 22(4): 2307–2317. PubMed Abstract | Publisher Full Text | Free Full Text
Ghori N, Michael JW, Andrew SW: Temporal microbial community dynamics within a unique acid saline lake. Front. Microbiol. 2021; 12: 649594. PubMed Abstract | Publisher Full Text | Free Full Text
Grant WD, Sorokin D: Distribution and Diversity of Soda Lake Alkaliphiles. Extremophiles Handbook. 2011; (July 2015): 28–54. Publisher Full Text
Grant WD, Jones BE: Soda lakes of East Africa. Soda Lakes of East Africa. 2016; 1–408. Publisher Full Text
Grant S, Grant WD, Jones BE, et al.: Novel archaeal phylotypes from an East African alkaline saltern. Extremophiles. 1999; 3(2): 139–145. PubMed Abstract | Publisher Full Text
Grant WD: Alkaline environments and biodiversity. Encyclopedia of Life Support Systems. 2006; 20.
Han R, Zhang X, Liu J, et al.: Microbial community structure and diversity within hypersaline Keke Salt Lake environments. Can. J. Microbiol. 2017; 63(11): 895–908. Publisher Full Text
He H, Fu L, Liu Q, et al.: Community Structure, Abundance and Potential Functions of Bacteria and Archaea in the Sansha Yongle Blue Hole, Xisha, South China Sea. Front. Microbiol. 2019; 10(2404): 1–16. PubMed Abstract | Publisher Full Text | Free Full Text
Hosam EE, Mohamad SAE-K, Mai AW: Biodiversity of uncultured bacteria in hypersaline lakes, Siwa oasis, Egypt, as determined by polymerase chain reaction and denaturing gradient gel electrophoresis (PCR-DGGE) of 16S rRNA gene phylotypes. Int. J. Genet. Mol. Biol. 2017; 9(2): 8–15. Publisher Full Text
Jiang H, Dong H, Yu B, et al.: Microbial response to salinity change in Lake Chaka, a hypersaline lake on Tibetan plateau. Environ. Microbiol. 2007; 9(10): 2603–2621. PubMed Abstract | Publisher Full Text
Joachimiak MP, Weisman JL, May BCH: JColorGrid: Software for the visualization of biological measurements. BMC Bioinformatics. 2006; 7: 1–5. PubMed Abstract | Publisher Full Text | Free Full Text
Jones BE, Grant WD, Duckworth AW, et al.: Microbial diversity of soda lakes. Extremophiles. 1998; 2: 191–200. Publisher Full Text
Kambura AK, Mwirichia RK, Kasili RW, et al.: Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya. BMC Microbiol. 2016; 16(1): 1–12. Publisher Full Text
Kamekura M, Dyall-smith ML, Upasani V, et al.: Diversity of Alkaliphilic Halobacteria: Proposals for Transfer of Na trono bacterium vacuola tum, Na trono ba cterium magadii, and Natronobacterium pharaonis to Halorubrum, Natrialba, and Natronomonas gen. nov., Respectively, as Halorubrum. Int. J. Syst. Bacteriol. 1997; 47(7): 853–857. PubMed Abstract | Publisher Full Text
Kevbrin VV, Zhilina TN, Rainey FA, et al.: Tindallia magadii gen. nov., sp. nov.: An alkaliphilic anaerobic ammonifier from Soda Lake Deposits. Curr. Microbiol. 1998; 37(2): 94–100. Publisher Full Text
Kiplimo D, Mugweru J, Kituyi S, et al.: Diversity of esterase and lipase producing haloalkaliphilic bacteria from Lake Magadi in Kenya. J. Basic Microbiol. 2019; 59(12): 1173–1184. PubMed Abstract | Publisher Full Text
Kipnyargis A, Eucharia K, Fathiya K, et al.: Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya: Extended data. Figshare. 2023a. Reference Source
Kipnyargis A, Mwirichia R, Eucharia K, et al.: ID 962270 - BioProject - NCBI.2023b. Reference Source
Kipnyargis A, Mwirichia R, Pfeiffer B, et al.: Complete Genome Sequence of Alkalihalobacillus sp. Strain LMS39, a Haloalkaliphilic Bacterium Isolated from a Hypersaline Lake. Microbiol. Resour. Announc. 2022; 11(7): e0032522. PubMed Abstract | Publisher Full Text | Free Full Text
Krenitz L, Shagerl M: Tiny and Tough: Microphytes of East African Soda Lakes.Schagerl M, editor. Soda Lakes of East Africa. Springer; 2016; pp. 149–177.
Krulwich TA, Sachs G, Padan E: Molecular aspects of bacterial pH sensing and homeostasis. Nat. Rev. Microbiol. 2011; 9(5): 330–343. PubMed Abstract | Publisher Full Text | Free Full Text
Lameck AS, Skutai J, Boros E: Review of chemical properties of inland soda and saline waters in East Africa (rift valley region). J. Hydrol.: Reg. Stud. 2023; 46:101323. Publisher Full Text
Li R, Khafipour E, Krause DO, et al.: Pyrosequencing Reveals the Influence of Organic and Conventional Farming Systems on Bacterial Communities. PLoS One. 2012; 7(12): e51897. PubMed Abstract | Publisher Full Text | Free Full Text
Li X, Yang M, Mu T, et al.: Composition and key-influencing factors of bacterial communities active in sulfur cycling of soda lake sediments. Arch. Microbiol. 2022; 204(6): 317–319. PubMed Abstract | Publisher Full Text
Liu C, Cui Y, Li X, et al.: Microeco: An R package for data mining in microbial community ecology. FEMS Microbiol. Ecol. 2021; 97(2): 1–9. Publisher Full Text
Lozupone C, Knight R: UniFrac: A new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 2005; 71(12): 8228–8235. PubMed Abstract | Publisher Full Text | Free Full Text
Ma Y, Xue Y, Grant WD, et al.: Alkalimonas amylolytica gen. nov., sp. nov., and Alkalimonas delamerensis gen. nov., sp. nov., novel alkaliphilic bacteria from soda lakes in China and East Africa. Extremophiles. 2004; 8(3): 193–200. PubMed Abstract | Publisher Full Text
Mahmoud AMA, Ali MHH, Abdelkarim MS, et al.: Chemical, biochemical, and bioactivity studies on some soda lakes, Wadi El-Natrun, Egypt. Environ. Monit. Assess. 2024; 196:436. PubMed Abstract | Publisher Full Text | Free Full Text
Mani K, Taib N, Hugoni M, et al.: Transient dynamics of archaea and bacteria in sediments and brine across a salinity gradient in a solar saltern of Goa, India. Front. Microbiol. 2020; 11(August): 1–19. PubMed Abstract | Publisher Full Text | Free Full Text
Matagi SV: A biodiversity assessment of the Flamingo Lakes of eastern Africa. J. Limnol. 2004; 5(1): 13–26. Publisher Full Text
Melack JM, Kilham P: Photosynthetic rates of phytoplankton in East African alkaline, saline lakes1. Limnol. Oceanogr. 1974; 19(5): 743–755. Publisher Full Text
Menasria T, Monteoliva-Sánchez M, Benammar L, et al.: Culturable halophilic bacteria inhabiting Algerian saline ecosystems: A source of promising features and potentialities. World J. Microbiol. Biotechnol. 2019; 35(9): 132. PubMed Abstract | Publisher Full Text
Mikhodyuk OS, Gerasimenko LM, Akimov VN, et al.: Ecophysiology and polymorphism of the unicellular extremely natronophilic cyanobacterium Euhalothece sp. Z-M001 from Lake Magadi. Microbiology. 2008; 77(6): 717–725. Publisher Full Text
Minegishi H, Enomoto S, Echigo A, et al.: Salinarchaeum chitinilyticum sp. Nov., a chitin-degrading haloarchaeon isolated from commercial salt. Int. J. Syst. Evol. Microbiol. 2017; 67(7): 2274–2278. PubMed Abstract | Publisher Full Text
Muruga B, Anyango B: A Survey of Extremophilic Bacteria in Lake Magadi, Kenya. Am. J. Mol. Cell. Biol. 2013; 2(1): 14–26.
Mwatha WE, Grant WD: Natronobacterium vacuolata sp. nov., a Haloalkaliphilic Archaeon Isolated from Lake Magadi, Kenya. Int. J. Syst. Bacteriol. 2016; 43(3): 401–404.
Mwirichia R: Amplicon-Based Analysis of the Fungal Diversity across Four Kenyan Soda Lakes. Scientifica. 2022; 2022: 1–9. PubMed Abstract | Publisher Full Text | Free Full Text
Newton RJ, Jones SE, Eiler A, et al.: A Guide to the Natural History of Freshwater Lake Bacteria. Microbiol. Mol. Biol. Rev. 2011; 75(1): 14–49. PubMed Abstract | Publisher Full Text | Free Full Text
Oduor SO, Schagerl M: Temporal trends of ion contents and nutrients in three Kenyan Rift Valley saline-alkaline lakes and their influence on phytoplankton biomass. Hydrobiologia. 2007; 584(1): 59–68. Publisher Full Text
Oksanen J: Vegan: an introduction to ordination. Management. 2015; 1: 1–10. Reference Source
Oren A: Thermodynamic limits to microbial life at high salt concentrations. Environ. Microbiol. 2011; 13(8): 1908–1923. PubMed Abstract | Publisher Full Text
Orwa P, Mugambi G, Wekesa V, et al.: Isolation of haloalkaliphilic fungi from Lake Magadi in Kenya. Heliyon. 2020; 6(1): e02823. PubMed Abstract | Publisher Full Text | Free Full Text
Otasek D, Morris JH, Bouças J, et al.: Cytoscape Automation: Empowering workflow-based network analysis. Genome Biol. 2019; 20(1): 115–185. PubMed Abstract | Publisher Full Text | Free Full Text
Pérez-Pantoja D, Donoso R, Agulló L, et al.: Genomic analysis of the potential for aromatic compounds biodegradation in Burkholderiales. Environ. Microbiol. 2012; 14(5): 1091–1117. Publisher Full Text
Pérez E, Chebude Y: Chemical Analysis of Gaet’ale, a Hypersaline Pond in Danakil Depression (Ethiopia): New Record for the Most Saline Water Body on Earth. Aquat. Geochem. 2017; 23(2): 109–117. Publisher Full Text
Poyraz N, Mutlu M: Characterization of Microbial Populations of Lake Van By 16S Metagenomics Study. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi - C Yaşam Bilimleri Ve Biyoteknoloji. 2020; 9(1): 80–88. Publisher Full Text
Price MN, Dehal PS, Arkin AP: FastTree 2 - Approximately maximum-likelihood trees for large alignments. PLoS One. 2010; 5(3): e9490. PubMed Abstract | Publisher Full Text | Free Full Text
Quast C, Pruesse E, Yilmaz P, et al.: The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2012; 41(D1): D590–D596. PubMed Abstract | Publisher Full Text | Free Full Text
R Core Team: R: A language and environment for statistical computing Vienna, Austria: R Foundation for Statistical Computing; 2020. https://www.r-project.org/
RStudio Team: RStudio: integrated development for R.PBC, Boston, MA: Rstudio Team; 2020. Reference Source
Rampelotto PH: Extremophiles and extreme environments. Life. 2013; 3(3): 482–485. PubMed Abstract | Publisher Full Text | Free Full Text
Rognes T, Flouri T, Nichols B, et al.: VSEARCH: A versatile open source tool for metagenomics. PeerJ. 2016; 4(10): e2584–e2522. PubMed Abstract | Publisher Full Text | Free Full Text
Rosenberg E, De Long EF, Lory S, et al.: The prokaryotes: Other major lineages of bacteria and the archaea. The Prokaryotes: Other Major Lineages of Bacteria and The Archaea. 2014; 43: 1–1028. Publisher Full Text
Salano OA, Makonde M, Kasili RW, et al.: Diversity and distribution of fungal communities within the hot springs of soda lakes in the Kenyan rift valley. Academicjournals. Org. 2017; 11(19): 764–775. Publisher Full Text
Simachew A, Lanzén A, Gessesse A, et al.: Prokaryotic Community Diversity Along an Increasing Salt Gradient in a Soda Ash Concentration Pond. Microb. Ecol. 2016; 71(2): 326–338. PubMed Abstract | Publisher Full Text
Sorokin DY, Panteleeva AN, Tourova TP, et al.: Natronoflexus pectinivorans gen. nov. sp. nov., an obligately anaerobic and alkaliphilic fermentative member of Bacteroidetes from soda lakes. Extremophiles. 2011; 15(6): 691–696. PubMed Abstract | Publisher Full Text | Free Full Text
Sorokin DY, Berben T, Melton ED, et al.: Microbial diversity and biogeochemical cycling in soda lakes. Extremophiles. 2014a; 18(5): 791–809. PubMed Abstract | Publisher Full Text | Free Full Text
Sorokin DY, Gumerov VM, Rakitin AL, et al.: Genome analysis of Chitinivibrio alkaliphilus gen. nov., sp. nov., a novel extremely haloalkaliphilic anaerobic chitinolytic bacterium from the candidate phylum Termite Group 3. Environ. Microbiol. 2014b; 16(6): 1549–1565. PubMed Abstract | Publisher Full Text
Sorokin DY, Kuenen JG: Chemolithotrophic haloalkaliphiles from soda lakes. FEMS Microbiol. Ecol. 2005; 52(3): 287–295. PubMed Abstract | Publisher Full Text
Sorokin DY, Trotsenko YA, Doronina NV, et al.: Methylohalomonas lacus gen. nov., sp. nov. and Methylonatrum kenyense gen. nov., sp. nov., methylotrophic gammaproteobacteria from hypersaline lakes. Int. J. Syst. Evol. Microbiol. 2007; 57(12): 2762–2769. PubMed Abstract | Publisher Full Text
Taher AG: Inland saline lakes of Wadi El Natrun depression, Egypt. Int. J. Salt Lake Res. 1999; 8(2): 149–170. Publisher Full Text
Tao X, Guo F, Zhou Q, et al.: Bacterial community mapping of the intestinal tract in acute pancreatitis rats based on 16S rDNA gene sequence analysis. RSC Adv. 2019; 9(9): 5025–5036. PubMed Abstract | Publisher Full Text | Free Full Text
Tazi L, Breakwell DP, Harker AR, et al.: Life in extreme environments: Microbial diversity in Great Salt Lake, Utah. Extremophiles. 2014; 18(3): 525–535. PubMed Abstract | Publisher Full Text
Tindall BJ, Ross HNM, Grant WD: Natronobacterium gen. nov. and Natronococcus gen. nov., Two New Genera of Haloalkaliphilic Archaebacteria. Syst. Appl. Microbiol. 1984; 5(1): 41–57. Publisher Full Text
Urbieta MS, Donati ER, Chan KG, et al.: Thermophiles in the genomic era: Biodiversity, science, and applications. Biotechnol. Adv. 2015; 33(6): 633–647. Publisher Full Text
Vavourakis CD, Andrei AS, Mehrshad M, et al.: A metagenomics roadmap to the uncultured genome diversity in hypersaline soda lake sediments. Microbiome. 2018; 6(1): 118–168. PubMed Abstract | Publisher Full Text | Free Full Text
Vavourakis CD, Ghai R, Rodriguez-Valera F, et al.: Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines. Front. Microbiol. 2016; 7(211): 1–18. Publisher Full Text
Wang M, Zhang X, Shu Z, et al.: Bacterial and archaeal communities within the alkaline soda Langaco Lake in the Qinghai-Tibet Plateau. Ann. Microbiol. 2022; 72(1): 1–15. Publisher Full Text
Webster G, O’Sullivan LA, Meng Y, et al.: Archaeal community diversity and abundance changes along a natural salinity gradient in estuarine sediments. FEMS Microbiol. Ecol. 2015; 91(2): 1–18. PubMed Abstract | Publisher Full Text | Free Full Text
Zavarzina DG, Zhilina TN, Kuznetsov BB, et al.: Natranaerobaculum magadiense gen. nov., sp. nov., an anaerobic, alkalithermophilic bacterium from soda lake sediment. Int. J. Syst. Evol. Microbiol. 2013; 63(PART 12): 4456–4461. PubMed Abstract | Publisher Full Text
Zhao D, Zhang S, Xue Q, et al.: Abundant Taxa and Favorable Pathways in the Microbiome of Soda-Saline Lakes in Inner Mongolia. Front. Microbiol. 2020; 11(July): 1–17. PubMed Abstract | Publisher Full Text | Free Full Text
Zhilina TN, Garnova ES, Tourova TP, et al.: Amphibacillus fermentum sp. nov. and Amphibacillus tropicus sp. nov., new alkaliphilic, facultatively anaerobic, saccharolytic bacilli from Lake Magadi. Microbiology. 2001; 70(6): 711–722. Publisher Full Text
Zhilina TN, Zavarzin GA, Rainey F, et al.: Spirochaeta alkalica sp. nov., Spirochaeta africana sp. nov., and Spirochaeta asiatica sp. nov., alkaliphilic anaerobes from the Continental Soda Lakes in Central Asia and the East African rift. Int. J. Syst. Bacteriol. 1996; 46(1): 305–312. PubMed Abstract | Publisher Full Text
Zhu P, Wang Y, Shi T, et al.: Intertidal zonation affects diversity and functional potentials of bacteria in surface sediments: A case study of the Golden Bay mangrove, China. Appl. Soil Ecol. 2018; 130(5): 159–168. Publisher Full Text
Zorz JK, Sharp C, Kleiner M, et al.: A shared core microbiome in soda lakes separated by large distances. Nat. Commun. 2019; 10(1): 4210–4230. PubMed Abstract | Publisher Full Text | Free Full Text

Comments on this article Comments (0)

Version 2

VERSION 2 PUBLISHED 03 Jan 2024

Author details Author details

¹ Department of Biological Sciences, University of Embu, Embu, Kenya
² Arthropod Pathology, International Centre of Insect Physiology and Ecology, Nairobi, Nairobi County, Kenya

Alex Kipnyargis
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Eucharia Kenya
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – Review & Editing

Fathiya Khamis
Roles: Conceptualization, Investigation, Methodology, Resources, Supervision, Visualization, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This research was funded by the National Research Fund, Kenya (grant number NRF/1/MMC/470) to Romano Mwirichia.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (2)

version 2

Revised

Published: 17 May 2024, 13:11

https://doi.org/10.12688/f1000research.134465.2

version 1

Published: 03 Jan 2024, 13:11

https://doi.org/10.12688/f1000research.134465.1

© 2024 Kipnyargis A et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download

Export To

metrics

	Views	Downloads
F1000Research	-	-
PubMed Central Data from PMC are received and updated monthly.	-	-

Citations

SEE MORE DETAILS

CITE

how to cite this article

Kipnyargis A, Kenya E, Khamis F and Mwirichia R. Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya [version 2; peer review: 1 approved, 2 approved with reservations, 1 not approved]. F1000Research 2024, 13:11 (https://doi.org/10.12688/f1000research.134465.2)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

track

receive updates on this article

Track an article to receive email alerts on any updates to this article.

Open Peer Review

Current Reviewer Status: ?

Key to Reviewer Statuses VIEW HIDE

ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

Version 2

VERSION 2

PUBLISHED 17 May 2024

Revised

Views

Reviewer Report 11 Nov 2024

Addis Simachew, Institute of Biotechnology Associate Professor of Microbial Ecology and Biotechnology, Addis Ababa University, Addis Ababa, Ethiopia

Approved with Reservations

https://doi.org/10.5256/f1000research.166004.r330095

I would like to thank the authors for conducting this nice work which fills a gap by assessing microbial communities structure in response to seasonality in Lake Magadi, Kenya, one of the soda lakes in the East African Rift Valley System.
General comments
The authors have attempted to assess the structure and composition of microbial communities in response to the seasonality and physicochemical parameters of Lake Magadi. Accordingly, the authors assessed the microbial communities structure and composition using three types of samples (hot spring water, open lake water and brine) of selected sampling sites in lake Magadi; sampled at four consecutive months (June to September of 2018). The key research question as pointed out by the authors was “how microbial diversity changes with the fluctuating physicochemical conditions with seasons, specifically wet/rainy and dry seasons?
In general, the manuscript needs major revision for acceptance due to the following major issues:
1.The sampling months were successive dry months, as described by the authors, it contradicts with the objective and hypothesis of the study. What does the authors mean by seasonality considering only dry months of the year?. The study was designed as stated by the authors, to investigate the effect of seasonality, i.e., the effect of dry and wet/rainy seasons on the microbial communities structure and composition. However, the study design did not include the rainy season of the area to answer the research question and test the research hypothesis. To this end, in the authors concluded that “our research highlights the composition and diversity of microbial communities across four successive dry months of soda Lake Magadi and the key physicochemical factors influencing them” in contradiction to the research objective and hypothesis.
2.The number of samples taken from each sample type were not proportional. Only a single composite sample was taken from the hot spring (S1) and brine (Br1), while five composite samples (S2-S6) were taken from the open lake water. The authors did not justify why such sampling scheme was employed. Unless justified the representativeness and the reliability of the data is questionable.
3.Three sample sites (S2, S3 and S4) were on the northern tip of the lake while the other two sample sites (S4 and S5) were on the southern tip of the lake (Figure 1). These sample sites were also around the shore of the lake while the large portion of the lake in the middle was not covered. The key question is that, are the sample sites representative to assess the lake microbial community? What was/were the reason/s to consider such sampling scheme?
4.The data for Br1-June, Br1-August, S1-June, S1-August and S2-August are not available. Then, how comparison is possible without having the full set of data for each sample site?
5.The temperature of the sample sites were in the range of 27^oC (S1-June and S4-July) to 38.7^oC (S3-June) while the maximum temperature the sample site considered as hot spring was 35.6^oC both in June and September which is less than to some of the other sample sites. What is/are the reason/s for considering the sampling site with low temperature value as hot spring?
6.There is a new bacterial classification system. In this new classification system, some phylum names are changed, Proteobacteria to Pseudomonata; Firmicutes to Baccilota etc. Hence, it would be better if the new classification systems is used.

Specific comments
Taxonomic composition and structure

Paragraph 1

1.The proportion of bacteria to archaea varied by season and sampling month (Figure 4)…
The sampling month represents the season. Then what do you mean by season and sampling month?
2. In hot spring water (S1), archaea abundance was the lowest while bacterial abundance was the highest
3.What was the proportion of archaeal abundance in these months? It would be clear if the percentage values are presented. What about for July and August?(sites 1, 4, and 5)
4.No such description of sites either in the method nor the result. Please make it consistent for the sake of understanding.
5. From June to September 2018, bacterial abundance decreased while archaeal abundance increased (Figure 4A)
6.It would be more informative if the proportion is described in percentage or in numerical.
The data in Figure 4A shows the microbial abundance at domain level along sampling sites. It would be more informative if the data were presented along months for a specific month. It is very difficult to conclude if the variations was due to month or site specific variations. Moreover, the data for some sampling sites is not complete. For instance, No data for S1 for July, August and the same is true for Br1.

Paragraph 3

7.S1 and S6 had the least archaeal abundance with 0.08 and 0.8%, respectively. In terms of the sampling month, September had the highest archaeal abundance with 53% followed by August (23%), June (12.7%), and July (11.4%)…

8.It would be appropriate if this information is included in paragraph 1.

Paragraph 4

9.The word “sampled” is used several times. It is better if other better word is used.
10.. (Kipnyargis et al., 2023a))…Why this citation?

Paragraph 5

11. Halobacteroidaceae, Spirochaetaceae, halanaerobiaceae, and desulfohalobiaceae…
halanaerobiaceae, and desulfohalobiaceae: start with capital letters

Paragraph 5

12.Generally, members of genera Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece spp. had a wide range of adaptability---
13.Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium, Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas spp. were least influenced by the tested physicochemical factors---The above statements are contradictory.
14.The first statement describes that members of the genera mentioned had a wide range of adaptability which implies that they are less influenced by the physicochemical parameters of the environments. The second statement also indicates the same for members of the microbial genera listed out. It needs attention of the authors.
…Mn and CO32-. pH and NH4+ …
The dot next to should be corrected
…. correlated with Mg2+, Mn, and NO3- …
Mn should be written in the ionic form as the other species
…On the other hand, Mn, temperature CO32-, and NH4+ …
The same comment as above

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Haloalkaliphilic Microbial Ecology and Biotechnology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

Report a concern

Respond or Comment

Views

Reviewer Report 23 Oct 2024

Cristiano Pedroso-Roussado, Universidade de Lisboa Instituto Superior Tecnico, Lisboa, Portugal

Approved with Reservations

https://doi.org/10.5256/f1000research.166004.r330100

I want to thank the authors for performing this work which represents a relevant microbial profile study for bacteria and archaea in Lake Magadi, Kenya.

General:
The work needs a whole revision for refine its text, and allow a more fluid narrative. The methods' section does not match with the results section. The discussion needs to have a more critical take on the findings. Key words does not reveal a clear picture of the work. Hence, I believe this work needs another round of revision before being fully accepted.

In detail:
INTRO
- Alpha-diversity is an index that speaks about diversity within samples and this seems not to be fully understood by the authors. The same for beta-diversity, that speaks about diversity between samples. A more critical take on these indexes is necessary.
. It is not clear the relevance of measuring TDS.
. Annotations are not correct: replace "ml" for "mL" and give a space for "X ºC".
- Is there any reference for the taxonomical update of Pelagirhabdus fermentum?
- What is a lake lagoon?
- What is the relevance of the isolates that Edwin et al (2019) and Orwa et al (2020) collected with the work you here introduce?

METHODS
- It is not clear how many water samples were collected nor at which depth. More details on the methods' section is necessary.
- Why do you justify the collection of 50 mL per sample instead of >5 L?
- How long did it take for traveling with samples? And at what temperature?

RESULTS
- You should not state the objective of the study in the results' section.
- Table 2 is showing all the results which is not a conventional way to show different variables (taxonomy vs diversity). I would prefer to see the sequencing QC as well.
. Does the figure 2 show the three different collection points combined (spring, brine, open waters)? It is needed more clarity for the space and time importance on the results.
- What does the proportion of bacteria to archaea tell us?
- It is not mentioned how did you perform the co-occurrence and redundancy analyses.
- Your study relates to the microbiota and not to the microbiome (Berg et al., (2020)(Ref-1))

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

References

1. Berg G, Rybakova D, Fischer D, Cernava T, et al.: Microbiome definition re-visited: old concepts and new challenges. Microbiome. 2020; 8 (1). Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Applied microbiology, microbiome analysis, next-generation sequencing, third-generation sequencing.

CITE

Report a concern

Respond or Comment

Views

Reviewer Report 17 Jun 2024

Marianne Haines, University of Calgary, Calgary, Alberta, Canada

Approved

https://doi.org/10.5256/f1000research.166004.r279828

Well done getting this all updated. The manuscript is in much better shape. I can see all the hard work you have put into it. Well done. There are a few minor things I would suggest amending and then that’s all from me. Good luck with all your future science – I hope it brings you much joy and remains inspiring. See below:

Abstract

Abstract: background

“However, it is not yet clear if the change in physiochemical changes influences the spatiotemporal diversity and structure of microbial communities in these ecosystems.” VS “The distribution and diversity of microbial communities in hypersaline lakes are mainly affected by physicochemical parameters (Tazi et al., 2014)” in the 2^nd paragraph of the Introduction. These two statements are contradictory. Perhaps you are trying to say that the influence of physiochemical parameters within a single lake have not been explored.

Abstract: methods

You have repeated a sentence twice

Abstract: results

The “composition” of Archaea cannot be higher. I think you mean the total abundance of Archaea was higher than that of Bacteria.
What is P+ ? Phosphorous? Why does it have a “+”?

Methods:

All these updates make this much better

Results

I still think Table 2 needs to define what an “observed species” is. Please refer to review 1 for more on this. Is it the number of unique species that were assigned?
“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10,300 ppm – 70,500 ppm) formed cluster I with nine samples (S1_06, S1_09, S5_06, S5_09, S5_08, S5_07, S6_08, S6_06, and S6_07). Moderately alkaline and saline samples (pH 10.5 – 10.6; 63, 900 ppm – 100,000 ppm)” – just need to remove the spacing between 63, and 900 to reader doesn’t get confused and think these are two separate numbers. My interpretation is that this is actually 63,900 ppm?
Still need to be more specific with this one “pH and NH4⁺ appear to positively correlate with the structure of the members of the genus Salinarcheum (R² = 0.245; p < 0.004), but negatively correlated with NO₃^-.” How does something positively correlate with the “structure of the members” – do you mean at increasing pH and ammonium concentrations more members of that genus were present? The subject of this sentence is “pH and NH4+” so as it is this sentence implies that pH and NH4+ were negatively correlated the nitrate. I don’t think that is what you mean, I think you mean that with increases in NO3- the presence and/or abundance of Salinarcheum was reduced. Is that it?

Discussion

This has come a long way, I can really see that you have now compared your results to others. Well done.

Conclusion

“halocaliaphiles” spelling
Much better conclusion

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: alkaline soda lake communities, alkaliphilic cyanobacteria

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

CITE

Report a concern

Respond or Comment

Version 1

VERSION 1

PUBLISHED 03 Jan 2024

Views

Reviewer Report 11 May 2024

Srijak Bhatnagar, Athabasca University, Athabasca, Alberta, Canada

Not Approved

https://doi.org/10.5256/f1000research.147523.r251335

Major Feedback:

Please run us statistical test on the alpha diversity values as it appears the August values could be very similar to June values statistical test is required to ensure the difference mentioned by the

Major Feedback:

Please run us statistical test on the alpha diversity values as it appears the August values could be very similar to June values statistical test is required to ensure the difference mentioned by the authors
Sequence analysis subsection under result, line 2: average read length is listed as 525bp The Amplicon expected from the primer mentioned should be around 300 and the length of my seek is also around 300bp. How is read length possible?
In various places site, S1 is described as a hot spring, but the temperature is shown as roughly around 35°C. How is this a hot spring?
Subsection taxonomic, composition, and structure: “Population increased due to evaporative iron concentration”. This is a causal statement, and no evidence of causation is shown in the study.
Figure 4B: the results mention Euryarcheota as the most abundant phylum. This is not evident from the figure. Either the legend is wrong, or the result is misinterpreted
Subsection physicochemical drivers: “TDS has a positive influence”. This is a subjective statement with no evidence provided. Unsure what positive influence here means.
Use of homonyms: Certain terms have a well-defined and established meaning and could cause confusion, please avoid them. For eg.,
- Figure 6:” exclusive site of isolation”. Isolation is a specific microbial technique, which was not employed in this study.
- DOM -> Dissolved Organic Matter, but in the manuscript used for Dead Organic Materials
The authors missed the opportunity to guide the discussion by focusing on the temporal changes in physicochemical factors driving the microbial community changes and then discussing possible reasons. The way the discussion is currently framed, it is a mix of results retelling and describing various taxa that were observed by other publications.

Minor Issues:

There is no mention of Phix filtering and sequence processing under methods
Typo in paragraph two of microbial community analysis, subsection Bray Curtis dissimilarity, written as Bray dissimilarity
Table 1: add the charge to the measured ions
Results first paragraph line 3: various ions and cations-> various ions or various anions and cations
Please mention the medium library size. It is more informative than the average size.
Incomplete sentence. beta diversity studies, subsection, line 2: samples better individual community similarity
Figure 3: Label the clusters as described in the results section
Figure 5: plastering of samples and taxa that here would be helpful and visualising the heat map while it’s understandable that samples are shown by month class based upon composition, should be able to substantiate some of the observations made by the authors.
Discussion: “The concentration of these elements” – >“The concentration of these ions”

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Bioinformatics, microbiomes, and environmental microbiology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

CITE

Report a concern

Respond or Comment

Views

Reviewer Report 01 Apr 2024

Marianne Haines, University of Calgary, Calgary, Alberta, Canada

Approved with Reservations

https://doi.org/10.5256/f1000research.147523.r251341

Summary
The authors sampled 7 sites representing spring, brine, and open waters in Lake Magadi, Kenya, over a 4-month period. Each sample underwent physiochemical testing and DNA extraction for amplicon sequencing and subsequent microbial community analysis. The authors thoroughly explore the composition of the microbial communities at each site and timepoint. Community composition is explored through standard taxon abundance measures and multiple diversity measures. Physiochemical drivers of the success (abundance) of different taxa are also evaluated. This work is valuable to microbial ecologists interested in extreme environments, notably, alkaline soda lakes.

Comments
Firstly, thank-you so much for your commitment to science. Well done! It takes a lot of work to get a manuscript to this stage. You have put together a very comprehensive analysis of your community data. Your results are stated very well and are nicely presented in figures. I really enjoyed the in-depth exploration of the community data. Overall, the manuscript is in good shape, although there are some places, particularly in the discussion and conclusion, where I think it requires some work.

Abstract

Add in that you did 16S AND analysed physiochemical properties in the methods

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”

“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Figure 1 – it is hard to see which sites are S3 and S4

Bit unnecessary to have the type of cool box.

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.
It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Results
There was an uneven distribution in sampling times, that needs to be mentioned. Why did this happen? How could it have influenced/biased your results?

Physicochemical properties of the sampling sites

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to explained.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Table 2 rows should be ordered by sample and then chronologically.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?
Figure 6: What a cool plot. This is a cool way to visualise data. I like it!
Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.
“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and timepoints pooled together? That should be clarified.
“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does structure of members mean?

Discussion
Where this manuscript needs attention is in the discussion. In general, discussion clarity and reasoning needs improvement. This is particularly evident when citing other literature. There were a few places I wasn’t sure what the authors meant and there are some repeated / missing words.

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake.Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: alkaline soda lake communities, alkaliphilic cyanobacteria

CITE

Report a concern

Author Response 20 Jun 2024

Alex Kipnyargis, Department of Biological Sciences, University of Embu, Embu, Kenya

20 Jun 2024

Author Response
- Add in that you did 16S AND analysed physiochemical properties in the methods
- Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the
... Continue reading
Add in that you did 16S AND analysed physiochemical properties in the methods

Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the diversity and structure of microbial communities in water and brine samples taken from Lake Magadi between June and September 2018. Physicochemical parameters were also analyzed for every sampling site.

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”

Response: The sentence “Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” is deleted completely.
The statement should now reads: "Multivariate analysis revealed that salinity and alkalinity were the major drivers of changes in the structure of microbial communities in Lake Magadi."

“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.

Response: The statement now reads “The findings demonstrated that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) contributed majorly to diversity observed in the microbial community."

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.

Response: "validly described" is replaced with "previously described"

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”

Response: Thank you.

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.

Response: "Illumina" will be deleted. It will now read: “In this study, we explored the spatiotemporal variation in the microbial community and physiochemical properties of the water over four months at different sites in Lake Magadi using 16S rRNA gene sequencing.”

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Response: The sentence after the GPRS coordinates describes the features of the sampling sites

Figure 1 – it is hard to see which sites are S3 and S4

Response: This has been corrected and a new map will be submitted

Bit unnecessary to have the type of cool box.

Response: This has been removed

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Response: No response since it is a comment.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.

Response: That sentence will now read: “The V4 hypervariable region of the 16S rRNA genes was amplified using the universal primers for bacteria and archaea 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′)”

It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Response: The dry season lasted for all of the sampling months, with June marking the start of the season and September being the driest month. This has been effected in the manuscript.

Results
There was an uneven distribution in sampling times, that needs to be mentioned. Why did this happen? How could it have influenced/biased your results?

Response: You are right. Uneven distribution in sampling sites was a result of:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.

Physicochemical properties of the sampling sites

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Response: This has been done as suggested.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to be explained.

Response:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.
However, the Good’s coverage (Table 2) ranged between 0.81–0.96, indicating that the sequencing depth was sufficient to cover most microbial species information and the sample size was sufficient to reflect the diversity differences among different communities.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Response: The assignment to genus level is a more confident way of taxonomic assignment while using 16S rRNA gene. Qiime would pick out the species identified in the OTUs, but we would not be confident to pick out species to difficulties surrounding 16S in resolving closely related species. We would probably remove that statement and recommend that future studies should consider the use of Amplified Sequence Variants (ASVs) to confidently assign species. The 00s in the “observed species” column have been removed.

Table 2 rows should be ordered by sample and then chronologically.

Response: This has been ordered accordingly.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Response: The word hot spring will be used consistently.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

Response: Figure 2 has been presented in chronological order.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

Response: This has been removed

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

Response: I have removed the key

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Response: You are right, I will rephrase this sentence.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Response: The spaces between the numbers have been removed and the numbers read appropriately. Numbers for high cluster have been inserted.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Response: A brief explanation of the clusters has been inserted in the figure caption.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Response: Good suggestion. I have paraphrased the sentence

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to the month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Response: The bars have been ordered according to sample and month.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?

Figure 6: What a cool plot. This is a cool way to visualise data. I like it!

Response: Thank you for the comment.

Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.

Response: This has been corrected

“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and time points pooled together? That should be clarified.

Response: This is a cumulative abundance based on all the time points and sites. The clarification has been effected in the manuscript.

“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Response: Yes, it is the abundance. I have changed this in the manuscript.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

Response: You are right. The sentence has been changed to read “The results demonstrated that temperature, CaCO₃, pH, P⁺, K⁺, NO₃^-, and TDS influenced the microbial community structure.”

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

Response: This has been corrected to capture the aspect of objectivity.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does the structure of members mean?

Response: Structure means how members of a particular microbial community distribute across seasons and sites.

Discussion

Where this manuscript needs attention is in the discussion. In general, discussion clarity and reasoning needs improvement. This is particularly evident when citing other literature. There were a few places I wasn’t sure what the authors meant and there are some repeated / missing words.

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

Response: More comparisons have been introduced in the manuscript to capture similar, higher, and lower concentrations of sulfates in soda lakes.

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

Response: Thank you. I have borrowed your words verbatim and the sentence reads well now.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

Response: That part has been paraphrased to explain the reason for high and stable pH. I felt that since pH was relatively stable across seasons and site, it is important to explain how this happens.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

Response: I agree. This paragraph has been entirely deleted.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

Response: Proteobacteria accounted for 35% of all the reads.

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

Response: I have supported this by a sentence reading: “The existence of Euhalothece in Lake Magadi is thus supported by high salts and carbonates (Table 1).”

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

Response: The sentence has been paraphrased to capture the contrasting aspect of Lake Magadi with other soda lakes.

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

Response: The entire paragraph does not discuss the results adequately and has been deleted

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

Response: The sentence has been enhanced to explain how photosynthetic cyanobacteria contribute towards the generation of substrates for Bacteroidetes and Verrumicrobia.

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

Response: The entire paragraph does not discuss the results adequately and has been deleted.

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

Response: The word “in” has been inserted appropriately. Thank you!

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

Response: This sentence has been paraphrased

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

Response: True. This has been deleted

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

Response: This has been changed to explain the reason for the effect.

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

Response: Structure has been replaced with diversity. The sentence has been paraphrased to capture the aspect of water waves and their effect on the distribution of nutrients. This could explain the variation in the diversity of microbes in water ecosystems.

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

Response: The sentence does not justify the diversity enough. I have introduced another theorem. “Despite high salinity and alkalinity in soda lake brine, the presence of high light intensity and dissolved CO₂ promotes the growth of photosynthetic microorganisms.
Subsequently, these phototrophs generate large quantities of dissolved organic matter (DOM) which become substrates for sustaining the diverse microbial communities (Banda 2020).”

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Response: I have rewritten the statement to capture the relationship of our findings with other studies on hot springs and the reason for such high diversity studies. Research on Soda Lake hot springs revealed a highly active and diverse microbial community, suggesting the high plasticity of these organisms toward extreme environments.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake. Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Response to conclusion section: I have rewritten the entire conclusion in a way that captures the conclusive elements of both diversity across seasons and sampling sites and the effects of the environmental factors on the population dynamics of microorganisms in Lake Magadi. Your comments were truly helpful.
Add in that you did 16S AND analysed physiochemical properties in the methods

Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the diversity and structure of microbial communities in water and brine samples taken from Lake Magadi between June and September 2018. Physicochemical parameters were also analyzed for every sampling site.

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”

Response: The sentence “Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” is deleted completely.
The statement should now reads: "Multivariate analysis revealed that salinity and alkalinity were the major drivers of changes in the structure of microbial communities in Lake Magadi."

“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.

Response: The statement now reads “The findings demonstrated that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) contributed majorly to diversity observed in the microbial community."

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.

Response: "validly described" is replaced with "previously described"

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”

Response: Thank you.

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.

Response: "Illumina" will be deleted. It will now read: “In this study, we explored the spatiotemporal variation in the microbial community and physiochemical properties of the water over four months at different sites in Lake Magadi using 16S rRNA gene sequencing.”

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Response: The sentence after the GPRS coordinates describes the features of the sampling sites

Figure 1 – it is hard to see which sites are S3 and S4

Response: This has been corrected and a new map will be submitted

Bit unnecessary to have the type of cool box.

Response: This has been removed

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Response: No response since it is a comment.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.

Response: That sentence will now read: “The V4 hypervariable region of the 16S rRNA genes was amplified using the universal primers for bacteria and archaea 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′)”

It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Response: The dry season lasted for all of the sampling months, with June marking the start of the season and September being the driest month. This has been effected in the manuscript.

Results
There was an uneven distribution in sampling times, that needs to be mentioned. Why did this happen? How could it have influenced/biased your results?

Response: You are right. Uneven distribution in sampling sites was a result of:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.

Physicochemical properties of the sampling sites

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Response: This has been done as suggested.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to be explained.

Response:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.
However, the Good’s coverage (Table 2) ranged between 0.81–0.96, indicating that the sequencing depth was sufficient to cover most microbial species information and the sample size was sufficient to reflect the diversity differences among different communities.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Response: The assignment to genus level is a more confident way of taxonomic assignment while using 16S rRNA gene. Qiime would pick out the species identified in the OTUs, but we would not be confident to pick out species to difficulties surrounding 16S in resolving closely related species. We would probably remove that statement and recommend that future studies should consider the use of Amplified Sequence Variants (ASVs) to confidently assign species. The 00s in the “observed species” column have been removed.

Table 2 rows should be ordered by sample and then chronologically.

Response: This has been ordered accordingly.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Response: The word hot spring will be used consistently.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

Response: Figure 2 has been presented in chronological order.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

Response: This has been removed

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

Response: I have removed the key

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Response: You are right, I will rephrase this sentence.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Response: The spaces between the numbers have been removed and the numbers read appropriately. Numbers for high cluster have been inserted.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Response: A brief explanation of the clusters has been inserted in the figure caption.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Response: Good suggestion. I have paraphrased the sentence

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to the month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Response: The bars have been ordered according to sample and month.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?

Figure 6: What a cool plot. This is a cool way to visualise data. I like it!

Response: Thank you for the comment.

Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.

Response: This has been corrected

“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and time points pooled together? That should be clarified.

Response: This is a cumulative abundance based on all the time points and sites. The clarification has been effected in the manuscript.

“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Response: Yes, it is the abundance. I have changed this in the manuscript.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

Response: You are right. The sentence has been changed to read “The results demonstrated that temperature, CaCO₃, pH, P⁺, K⁺, NO₃^-, and TDS influenced the microbial community structure.”

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

Response: This has been corrected to capture the aspect of objectivity.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does the structure of members mean?

Response: Structure means how members of a particular microbial community distribute across seasons and sites.

Discussion

Where this manuscript needs attention is in the discussion. In general, discussion clarity and reasoning needs improvement. This is particularly evident when citing other literature. There were a few places I wasn’t sure what the authors meant and there are some repeated / missing words.

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

Response: More comparisons have been introduced in the manuscript to capture similar, higher, and lower concentrations of sulfates in soda lakes.

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

Response: Thank you. I have borrowed your words verbatim and the sentence reads well now.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

Response: That part has been paraphrased to explain the reason for high and stable pH. I felt that since pH was relatively stable across seasons and site, it is important to explain how this happens.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

Response: I agree. This paragraph has been entirely deleted.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

Response: Proteobacteria accounted for 35% of all the reads.

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

Response: I have supported this by a sentence reading: “The existence of Euhalothece in Lake Magadi is thus supported by high salts and carbonates (Table 1).”

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

Response: The sentence has been paraphrased to capture the contrasting aspect of Lake Magadi with other soda lakes.

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

Response: The entire paragraph does not discuss the results adequately and has been deleted

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

Response: The sentence has been enhanced to explain how photosynthetic cyanobacteria contribute towards the generation of substrates for Bacteroidetes and Verrumicrobia.

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

Response: The entire paragraph does not discuss the results adequately and has been deleted.

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

Response: The word “in” has been inserted appropriately. Thank you!

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

Response: This sentence has been paraphrased

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

Response: True. This has been deleted

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

Response: This has been changed to explain the reason for the effect.

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

Response: Structure has been replaced with diversity. The sentence has been paraphrased to capture the aspect of water waves and their effect on the distribution of nutrients. This could explain the variation in the diversity of microbes in water ecosystems.

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

Response: The sentence does not justify the diversity enough. I have introduced another theorem. “Despite high salinity and alkalinity in soda lake brine, the presence of high light intensity and dissolved CO₂ promotes the growth of photosynthetic microorganisms.
Subsequently, these phototrophs generate large quantities of dissolved organic matter (DOM) which become substrates for sustaining the diverse microbial communities (Banda 2020).”

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Response: I have rewritten the statement to capture the relationship of our findings with other studies on hot springs and the reason for such high diversity studies. Research on Soda Lake hot springs revealed a highly active and diverse microbial community, suggesting the high plasticity of these organisms toward extreme environments.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake. Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Response to conclusion section: I have rewritten the entire conclusion in a way that captures the conclusive elements of both diversity across seasons and sampling sites and the effects of the environmental factors on the population dynamics of microorganisms in Lake Magadi. Your comments were truly helpful.
Competing Interests: No competing interests Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 20 Jun 2024

Alex Kipnyargis, Department of Biological Sciences, University of Embu, Embu, Kenya

20 Jun 2024

Author Response
- Add in that you did 16S AND analysed physiochemical properties in the methods
- Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the
... Continue reading
Add in that you did 16S AND analysed physiochemical properties in the methods

Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the diversity and structure of microbial communities in water and brine samples taken from Lake Magadi between June and September 2018. Physicochemical parameters were also analyzed for every sampling site.

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”

Response: The sentence “Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” is deleted completely.
The statement should now reads: "Multivariate analysis revealed that salinity and alkalinity were the major drivers of changes in the structure of microbial communities in Lake Magadi."

“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.

Response: The statement now reads “The findings demonstrated that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) contributed majorly to diversity observed in the microbial community."

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.

Response: "validly described" is replaced with "previously described"

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”

Response: Thank you.

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.

Response: "Illumina" will be deleted. It will now read: “In this study, we explored the spatiotemporal variation in the microbial community and physiochemical properties of the water over four months at different sites in Lake Magadi using 16S rRNA gene sequencing.”

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Response: The sentence after the GPRS coordinates describes the features of the sampling sites

Figure 1 – it is hard to see which sites are S3 and S4

Response: This has been corrected and a new map will be submitted

Bit unnecessary to have the type of cool box.

Response: This has been removed

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Response: No response since it is a comment.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.

Response: That sentence will now read: “The V4 hypervariable region of the 16S rRNA genes was amplified using the universal primers for bacteria and archaea 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′)”

It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Response: The dry season lasted for all of the sampling months, with June marking the start of the season and September being the driest month. This has been effected in the manuscript.

Results
There was an uneven distribution in sampling times, that needs to be mentioned. Why did this happen? How could it have influenced/biased your results?

Response: You are right. Uneven distribution in sampling sites was a result of:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.

Physicochemical properties of the sampling sites

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Response: This has been done as suggested.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to be explained.

Response:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.
However, the Good’s coverage (Table 2) ranged between 0.81–0.96, indicating that the sequencing depth was sufficient to cover most microbial species information and the sample size was sufficient to reflect the diversity differences among different communities.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Response: The assignment to genus level is a more confident way of taxonomic assignment while using 16S rRNA gene. Qiime would pick out the species identified in the OTUs, but we would not be confident to pick out species to difficulties surrounding 16S in resolving closely related species. We would probably remove that statement and recommend that future studies should consider the use of Amplified Sequence Variants (ASVs) to confidently assign species. The 00s in the “observed species” column have been removed.

Table 2 rows should be ordered by sample and then chronologically.

Response: This has been ordered accordingly.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Response: The word hot spring will be used consistently.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

Response: Figure 2 has been presented in chronological order.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

Response: This has been removed

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

Response: I have removed the key

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Response: You are right, I will rephrase this sentence.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Response: The spaces between the numbers have been removed and the numbers read appropriately. Numbers for high cluster have been inserted.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Response: A brief explanation of the clusters has been inserted in the figure caption.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Response: Good suggestion. I have paraphrased the sentence

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to the month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Response: The bars have been ordered according to sample and month.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?

Figure 6: What a cool plot. This is a cool way to visualise data. I like it!

Response: Thank you for the comment.

Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.

Response: This has been corrected

“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and time points pooled together? That should be clarified.

Response: This is a cumulative abundance based on all the time points and sites. The clarification has been effected in the manuscript.

“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Response: Yes, it is the abundance. I have changed this in the manuscript.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

Response: You are right. The sentence has been changed to read “The results demonstrated that temperature, CaCO₃, pH, P⁺, K⁺, NO₃^-, and TDS influenced the microbial community structure.”

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

Response: This has been corrected to capture the aspect of objectivity.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does the structure of members mean?

Response: Structure means how members of a particular microbial community distribute across seasons and sites.

Discussion

Where this manuscript needs attention is in the discussion. In general, discussion clarity and reasoning needs improvement. This is particularly evident when citing other literature. There were a few places I wasn’t sure what the authors meant and there are some repeated / missing words.

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

Response: More comparisons have been introduced in the manuscript to capture similar, higher, and lower concentrations of sulfates in soda lakes.

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

Response: Thank you. I have borrowed your words verbatim and the sentence reads well now.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

Response: That part has been paraphrased to explain the reason for high and stable pH. I felt that since pH was relatively stable across seasons and site, it is important to explain how this happens.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

Response: I agree. This paragraph has been entirely deleted.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

Response: Proteobacteria accounted for 35% of all the reads.

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

Response: I have supported this by a sentence reading: “The existence of Euhalothece in Lake Magadi is thus supported by high salts and carbonates (Table 1).”

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

Response: The sentence has been paraphrased to capture the contrasting aspect of Lake Magadi with other soda lakes.

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

Response: The entire paragraph does not discuss the results adequately and has been deleted

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

Response: The sentence has been enhanced to explain how photosynthetic cyanobacteria contribute towards the generation of substrates for Bacteroidetes and Verrumicrobia.

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

Response: The entire paragraph does not discuss the results adequately and has been deleted.

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

Response: The word “in” has been inserted appropriately. Thank you!

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

Response: This sentence has been paraphrased

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

Response: True. This has been deleted

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

Response: This has been changed to explain the reason for the effect.

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

Response: Structure has been replaced with diversity. The sentence has been paraphrased to capture the aspect of water waves and their effect on the distribution of nutrients. This could explain the variation in the diversity of microbes in water ecosystems.

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

Response: The sentence does not justify the diversity enough. I have introduced another theorem. “Despite high salinity and alkalinity in soda lake brine, the presence of high light intensity and dissolved CO₂ promotes the growth of photosynthetic microorganisms.
Subsequently, these phototrophs generate large quantities of dissolved organic matter (DOM) which become substrates for sustaining the diverse microbial communities (Banda 2020).”

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Response: I have rewritten the statement to capture the relationship of our findings with other studies on hot springs and the reason for such high diversity studies. Research on Soda Lake hot springs revealed a highly active and diverse microbial community, suggesting the high plasticity of these organisms toward extreme environments.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake. Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Response to conclusion section: I have rewritten the entire conclusion in a way that captures the conclusive elements of both diversity across seasons and sampling sites and the effects of the environmental factors on the population dynamics of microorganisms in Lake Magadi. Your comments were truly helpful.
Add in that you did 16S AND analysed physiochemical properties in the methods

Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the diversity and structure of microbial communities in water and brine samples taken from Lake Magadi between June and September 2018. Physicochemical parameters were also analyzed for every sampling site.

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”

Response: The sentence “Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” is deleted completely.
The statement should now reads: "Multivariate analysis revealed that salinity and alkalinity were the major drivers of changes in the structure of microbial communities in Lake Magadi."

“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.

Response: The statement now reads “The findings demonstrated that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) contributed majorly to diversity observed in the microbial community."

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.

Response: "validly described" is replaced with "previously described"

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”

Response: Thank you.

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.

Response: "Illumina" will be deleted. It will now read: “In this study, we explored the spatiotemporal variation in the microbial community and physiochemical properties of the water over four months at different sites in Lake Magadi using 16S rRNA gene sequencing.”

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Response: The sentence after the GPRS coordinates describes the features of the sampling sites

Figure 1 – it is hard to see which sites are S3 and S4

Response: This has been corrected and a new map will be submitted

Bit unnecessary to have the type of cool box.

Response: This has been removed

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Response: No response since it is a comment.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.

Response: That sentence will now read: “The V4 hypervariable region of the 16S rRNA genes was amplified using the universal primers for bacteria and archaea 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′)”

It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Response: The dry season lasted for all of the sampling months, with June marking the start of the season and September being the driest month. This has been effected in the manuscript.

Results
There was an uneven distribution in sampling times, that needs to be mentioned. Why did this happen? How could it have influenced/biased your results?

Response: You are right. Uneven distribution in sampling sites was a result of:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.

Physicochemical properties of the sampling sites

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Response: This has been done as suggested.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to be explained.

Response:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.
However, the Good’s coverage (Table 2) ranged between 0.81–0.96, indicating that the sequencing depth was sufficient to cover most microbial species information and the sample size was sufficient to reflect the diversity differences among different communities.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Response: The assignment to genus level is a more confident way of taxonomic assignment while using 16S rRNA gene. Qiime would pick out the species identified in the OTUs, but we would not be confident to pick out species to difficulties surrounding 16S in resolving closely related species. We would probably remove that statement and recommend that future studies should consider the use of Amplified Sequence Variants (ASVs) to confidently assign species. The 00s in the “observed species” column have been removed.

Table 2 rows should be ordered by sample and then chronologically.

Response: This has been ordered accordingly.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Response: The word hot spring will be used consistently.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

Response: Figure 2 has been presented in chronological order.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

Response: This has been removed

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

Response: I have removed the key

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Response: You are right, I will rephrase this sentence.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Response: The spaces between the numbers have been removed and the numbers read appropriately. Numbers for high cluster have been inserted.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Response: A brief explanation of the clusters has been inserted in the figure caption.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Response: Good suggestion. I have paraphrased the sentence

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to the month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Response: The bars have been ordered according to sample and month.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?

Figure 6: What a cool plot. This is a cool way to visualise data. I like it!

Response: Thank you for the comment.

Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.

Response: This has been corrected

“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and time points pooled together? That should be clarified.

Response: This is a cumulative abundance based on all the time points and sites. The clarification has been effected in the manuscript.

“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Response: Yes, it is the abundance. I have changed this in the manuscript.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

Response: You are right. The sentence has been changed to read “The results demonstrated that temperature, CaCO₃, pH, P⁺, K⁺, NO₃^-, and TDS influenced the microbial community structure.”

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

Response: This has been corrected to capture the aspect of objectivity.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does the structure of members mean?

Response: Structure means how members of a particular microbial community distribute across seasons and sites.

Discussion

Where this manuscript needs attention is in the discussion. In general, discussion clarity and reasoning needs improvement. This is particularly evident when citing other literature. There were a few places I wasn’t sure what the authors meant and there are some repeated / missing words.

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

Response: More comparisons have been introduced in the manuscript to capture similar, higher, and lower concentrations of sulfates in soda lakes.

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

Response: Thank you. I have borrowed your words verbatim and the sentence reads well now.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

Response: That part has been paraphrased to explain the reason for high and stable pH. I felt that since pH was relatively stable across seasons and site, it is important to explain how this happens.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

Response: I agree. This paragraph has been entirely deleted.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

Response: Proteobacteria accounted for 35% of all the reads.

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

Response: I have supported this by a sentence reading: “The existence of Euhalothece in Lake Magadi is thus supported by high salts and carbonates (Table 1).”

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

Response: The sentence has been paraphrased to capture the contrasting aspect of Lake Magadi with other soda lakes.

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

Response: The entire paragraph does not discuss the results adequately and has been deleted

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

Response: The sentence has been enhanced to explain how photosynthetic cyanobacteria contribute towards the generation of substrates for Bacteroidetes and Verrumicrobia.

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

Response: The entire paragraph does not discuss the results adequately and has been deleted.

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

Response: The word “in” has been inserted appropriately. Thank you!

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

Response: This sentence has been paraphrased

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

Response: True. This has been deleted

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

Response: This has been changed to explain the reason for the effect.

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

Response: Structure has been replaced with diversity. The sentence has been paraphrased to capture the aspect of water waves and their effect on the distribution of nutrients. This could explain the variation in the diversity of microbes in water ecosystems.

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

Response: The sentence does not justify the diversity enough. I have introduced another theorem. “Despite high salinity and alkalinity in soda lake brine, the presence of high light intensity and dissolved CO₂ promotes the growth of photosynthetic microorganisms.
Subsequently, these phototrophs generate large quantities of dissolved organic matter (DOM) which become substrates for sustaining the diverse microbial communities (Banda 2020).”

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Response: I have rewritten the statement to capture the relationship of our findings with other studies on hot springs and the reason for such high diversity studies. Research on Soda Lake hot springs revealed a highly active and diverse microbial community, suggesting the high plasticity of these organisms toward extreme environments.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake. Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Response to conclusion section: I have rewritten the entire conclusion in a way that captures the conclusive elements of both diversity across seasons and sampling sites and the effects of the environmental factors on the population dynamics of microorganisms in Lake Magadi. Your comments were truly helpful.
Competing Interests: No competing interests Close
Report a concern

Comments on this article Comments (0)

Version 2

VERSION 2 PUBLISHED 03 Jan 2024

Open Peer Review

Reviewer Status

Reviewer Reports

	Invited Reviewers
	1	2	3	4
Version 2 (revision) 17 May 24	read		read	read
Version 1 03 Jan 24	read	read

Marianne Haines, University of Calgary, Calgary, Canada
Srijak Bhatnagar, Athabasca University, Athabasca, Canada
Cristiano Pedroso-Roussado, Universidade de Lisboa Instituto Superior Tecnico, Lisboa, Portugal
Addis Simachew, Addis Ababa University, Addis Ababa, Ethiopia

Comments on this article

All Comments(0)

Add a comment

Browse by related subjects

Back to all reports

Reviewer Report

2 Views

11 Nov 2024 | for Version 2

Addis Simachew, Institute of Biotechnology Associate Professor of Microbial Ecology and Biotechnology, Addis Ababa University, Addis Ababa, Ethiopia

2 Views Cite this report Responses(0)

Approved With Reservations

Paragraph 1

Paragraph 3

Paragraph 4

9.The word “sampled” is used several times. It is better if other better word is used.
10.. (Kipnyargis et al., 2023a))…Why this citation?

Paragraph 5

11. Halobacteroidaceae, Spirochaetaceae, halanaerobiaceae, and desulfohalobiaceae…
halanaerobiaceae, and desulfohalobiaceae: start with capital letters

Paragraph 5

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Haloalkaliphilic Microbial Ecology and Biotechnology

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

2 Views

23 Oct 2024 | for Version 2

Cristiano Pedroso-Roussado, Universidade de Lisboa Instituto Superior Tecnico, Lisboa, Portugal

2 Views Cite this report Responses(0)

Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

References

1. Berg G, Rybakova D, Fischer D, Cernava T, et al.: Microbiome definition re-visited: old concepts and new challenges. Microbiome. 2020; 8 (1). Publisher Full Text

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Applied microbiology, microbiome analysis, next-generation sequencing, third-generation sequencing.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

11 Views

17 Jun 2024 | for Version 2

Marianne Haines, University of Calgary, Calgary, Alberta, Canada

11 Views Cite this report Responses(0)

Approved

“However, it is not yet clear if the change in physiochemical changes influences the spatiotemporal diversity and structure of microbial communities in these ecosystems.” VS “The distribution and diversity of microbial communities in hypersaline lakes are mainly affected by physicochemical parameters (Tazi et al., 2014)” in the 2^nd paragraph of the Introduction. These two statements are contradictory. Perhaps you are trying to say that the influence of physiochemical parameters within a single lake have not been explored.

Abstract: methods

You have repeated a sentence twice

Abstract: results

The “composition” of Archaea cannot be higher. I think you mean the total abundance of Archaea was higher than that of Bacteria.
What is P+ ? Phosphorous? Why does it have a “+”?

Methods:

All these updates make this much better

Results

I still think Table 2 needs to define what an “observed species” is. Please refer to review 1 for more on this. Is it the number of unique species that were assigned?
“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10,300 ppm – 70,500 ppm) formed cluster I with nine samples (S1_06, S1_09, S5_06, S5_09, S5_08, S5_07, S6_08, S6_06, and S6_07). Moderately alkaline and saline samples (pH 10.5 – 10.6; 63, 900 ppm – 100,000 ppm)” – just need to remove the spacing between 63, and 900 to reader doesn’t get confused and think these are two separate numbers. My interpretation is that this is actually 63,900 ppm?
Still need to be more specific with this one “pH and NH4⁺ appear to positively correlate with the structure of the members of the genus Salinarcheum (R² = 0.245; p < 0.004), but negatively correlated with NO₃^-.” How does something positively correlate with the “structure of the members” – do you mean at increasing pH and ammonium concentrations more members of that genus were present? The subject of this sentence is “pH and NH4+” so as it is this sentence implies that pH and NH4+ were negatively correlated the nitrate. I don’t think that is what you mean, I think you mean that with increases in NO3- the presence and/or abundance of Salinarcheum was reduced. Is that it?

Discussion

This has come a long way, I can really see that you have now compared your results to others. Well done.

Conclusion

“halocaliaphiles” spelling
Much better conclusion

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

alkaline soda lake communities, alkaliphilic cyanobacteria

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

11 Views

11 May 2024 | for Version 1

Srijak Bhatnagar, Athabasca University, Athabasca, Alberta, Canada

11 Views Cite this report Responses(0)

Not Approved

Major Feedback:

Please run us statistical test on the alpha diversity values as it appears the August values could be very similar to June values statistical test is required to ensure the difference mentioned by the authors
Sequence analysis subsection under result, line 2: average read length is listed as 525bp The Amplicon expected from the primer mentioned should be around 300 and the length of my seek is also around 300bp. How is read length possible?
In various places site, S1 is described as a hot spring, but the temperature is shown as roughly around 35°C. How is this a hot spring?
Subsection taxonomic, composition, and structure: “Population increased due to evaporative iron concentration”. This is a causal statement, and no evidence of causation is shown in the study.
Figure 4B: the results mention Euryarcheota as the most abundant phylum. This is not evident from the figure. Either the legend is wrong, or the result is misinterpreted
Subsection physicochemical drivers: “TDS has a positive influence”. This is a subjective statement with no evidence provided. Unsure what positive influence here means.
Use of homonyms: Certain terms have a well-defined and established meaning and could cause confusion, please avoid them. For eg.,
- Figure 6:” exclusive site of isolation”. Isolation is a specific microbial technique, which was not employed in this study.
- DOM -> Dissolved Organic Matter, but in the manuscript used for Dead Organic Materials
The authors missed the opportunity to guide the discussion by focusing on the temporal changes in physicochemical factors driving the microbial community changes and then discussing possible reasons. The way the discussion is currently framed, it is a mix of results retelling and describing various taxa that were observed by other publications.

Minor Issues:

There is no mention of Phix filtering and sequence processing under methods
Typo in paragraph two of microbial community analysis, subsection Bray Curtis dissimilarity, written as Bray dissimilarity
Table 1: add the charge to the measured ions
Results first paragraph line 3: various ions and cations-> various ions or various anions and cations
Please mention the medium library size. It is more informative than the average size.
Incomplete sentence. beta diversity studies, subsection, line 2: samples better individual community similarity
Figure 3: Label the clusters as described in the results section
Figure 5: plastering of samples and taxa that here would be helpful and visualising the heat map while it’s understandable that samples are shown by month class based upon composition, should be able to substantiate some of the observations made by the authors.
Discussion: “The concentration of these elements” – >“The concentration of these ions”

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Bioinformatics, microbiomes, and environmental microbiology

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

19 Views

01 Apr 2024 | for Version 1

Marianne Haines, University of Calgary, Calgary, Alberta, Canada

19 Views Cite this report Responses(1)

Approved With Reservations

Add in that you did 16S AND analysed physiochemical properties in the methods

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”

“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Figure 1 – it is hard to see which sites are S3 and S4

Bit unnecessary to have the type of cool box.

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.
It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to explained.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Table 2 rows should be ordered by sample and then chronologically.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?
Figure 6: What a cool plot. This is a cool way to visualise data. I like it!
Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.
“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and timepoints pooled together? That should be clarified.
“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does structure of members mean?

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake.Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

alkaline soda lake communities, alkaliphilic cyanobacteria

Respond to this report

Responses (1)

Author Response

20 Jun 2024

Alex Kipnyargis, Department of Biological Sciences, University of Embu, Embu, Kenya

Add in that you did 16S AND analysed physiochemical properties in the methods
Response: Methods (paraphrased): Using 16S rRNA gene amplicon sequencing, we investigated the diversity and structure of microbial communities in water and brine samples taken from Lake Magadi between June and September 2018. Physicochemical parameters were also analyzed for every sampling site.

“Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” Probably seasonality and site also impact diversity but they are masked by the stronger drivers of salinity and alkalinity. You could rephrase this to say salinity and alkalinity had a stronger or the most notable impact on beta diversity. Indeed you actually directly contradict this point in the last sentence: “Multivariate analysis revealed significant spatial and temporal effects on β-diversity and salinity and alkalinity were the major drivers of microbial composition in Lake Magadi.”
Response: The sentence “Furthermore, salinity and alkalinity affect β-diversity rather than the sampling site or seasonality.” is deleted completely.
The statement should now reads: "Multivariate analysis revealed that salinity and alkalinity were the major drivers of changes in the structure of microbial communities in Lake Magadi."
“The effects of physicochemical parameters on the microbial community structure showed that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) had a positive correlation with the microbial community structure” I don’t know what you mean by positive correlation on microbial community structure. Explain.
Response: The statement now reads “The findings demonstrated that temperature, pH, P+, K+, NO3 -, and total dissolved solids (TDS) contributed majorly to diversity observed in the microbial community."

Introduction

What do you mean by “validly described”, be more specific what your definition of valid descriptions are.
Response: "validly described" is replaced with "previously described"

This is stated really nicely, “A key ecological question is how microbial diversity changes with the fluctuating physicochemical conditions with seasons.”
Response: Thank you.

“In this study, we explored the spatiotemporal variation in the microbial community AND physiochemical properties of the water over four months at different sites in Lake Magadi using Illumina 16S sequencing.” 16S is more specific than the type of sequencing.
Response: "Illumina" will be deleted. It will now read: “In this study, we explored the spatiotemporal variation in the microbial community and physiochemical properties of the water over four months at different sites in Lake Magadi using 16S rRNA gene sequencing.”

Methods

The naming of samples makes it easy to distinguish brine from the other sample types but it is hard to know that S1 is the only spring.

Response: The sentence after the GPRS coordinates describes the features of the sampling sites

Figure 1 – it is hard to see which sites are S3 and S4

Response: This has been corrected and a new map will be submitted

Bit unnecessary to have the type of cool box.

Response: This has been removed

I haven’t done extensive diversity analysis of 16S data so I can’t comment on these methods.

Response: No response since it is a comment.

Should include some text that states that the primer is designed to capture both Bacteria and Archaea.

Response: That sentence will now read: “The V4 hypervariable region of the 16S rRNA genes was amplified using the universal primers for bacteria and archaea 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′)”

It would be helpful to state early on in the piece which seasons these months fall in to in Kenya. Are these warm or cool months, rainy or dry? Not all readers will know this immediately.

Response: The dry season lasted for all of the sampling months, with June marking the start of the season and September being the driest month. This has been effected in the manuscript.

Results
There was an uneven distribution in sampling times, that needs to be mentioned. Why did this happen? How could it have influenced/biased your results?

Response: You are right. Uneven distribution in sampling sites was a result of:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.

Physicochemical properties of the sampling sites

Table 1 needs units beside each metric in column 1 even though I see they are stated in the body of the text, one should be able to look at the Table without needing to seek clarification from the text.

Response: This has been done as suggested.

Why are there months missing for some of the samples? If data wasn’t collected for those months, how did that impact RDA which was used to test the correlation between physiochemical parameters and genera? Why these samples are missing and how the analysis overcame this needs to be explained.

Response:
1. S1 and Br_1 (hot spring and brine, respectively were only available in June and September).
2. The DNA extraction protocol did not yield sufficient DNA for sequencing in sample S2 for August 2018.
However, the Good’s coverage (Table 2) ranged between 0.81–0.96, indicating that the sequencing depth was sufficient to cover most microbial species information and the sample size was sufficient to reflect the diversity differences among different communities.

Sequence analysis and diversity studies

Table 2: What are “observed species”, you say that taxa were assigned to genus level, not to species level. Is this column actually talking about the number of different genera? This column should have the 00s removed.

Response: The assignment to genus level is a more confident way of taxonomic assignment while using 16S rRNA gene. Qiime would pick out the species identified in the OTUs, but we would not be confident to pick out species to difficulties surrounding 16S in resolving closely related species. We would probably remove that statement and recommend that future studies should consider the use of Amplified Sequence Variants (ASVs) to confidently assign species. The 00s in the “observed species” column have been removed.

Table 2 rows should be ordered by sample and then chronologically.

Response: This has been ordered accordingly.

Alpha diversity studies

This is the first time in the piece you have mentioned the spring is a hot spring. That needs to be updated in the methods.

Response: The word hot spring will be used consistently.

Figure 2 has the x axis categories in alphabetical order but I think from the perspective of the reader this should be presented chronologically. Seasonality usually has a profound impact on community structure, it would be nice to visualise easily if there are (or are not) diversity trends based on seasonality.

Response: Figure 2 has been presented in chronological order.

In Figure 2 legend, you state “Statistical significance was determined at p < 0.05” but I don’t see any indication of statistical significance conveyed on the graph so I don’t think this sentence is necessary.

Response: This has been removed

I like that you have presented the results from so many different measures of species diversity here. It is not necessary to do it for this work, but one way to simplify this type of graph (especially because all tests show similar trends) would be to normalise all values and then plot them on a single graph with box plot colours indicating the test type. At present, your coloured key here is unnecessary because you already have the months as categories in the x-axis.

Response: I have removed the key

“The alpha diversity indices showed that high microbial diversity was recorded in the month of August, followed by September, June, and July in that order (Figure 2).” I don’t think these results clearly show this, they are too variable and overlapping.

Response: You are right, I will rephrase this sentence.

Beta diversity studies

“Low alkalinity and salinity samples (pH 9.8 – 10.5; 10 ***what is this number?***, 300 ppm – 70,500 ppm).” Same thing with the 63 in the medium cluster, and then that number is missing in the high cluster.

Response: The spaces between the numbers have been removed and the numbers read appropriately. Numbers for high cluster have been inserted.

Figure 3 needs to tell me which clusters are which, preferably on top of the graph are in the legend. That’s cool that they cluster like that.

Response: A brief explanation of the clusters has been inserted in the figure caption.

Taxonomic composition and structure

“The results indicate that the archaeal population increased due to evaporative ion concentration while bacteria abundance was higher where the ion concentration was lower (sites 1, 4, and 5) (Table 1).” I don’t think you can conclude this from your results. You might say there is a trend and it could be because of ion concentration. This is a discussion point and shouldn’t be in the results section.

Response: Good suggestion. I have paraphrased the sentence

Figure 4: I am a bit confused with the alignment of different samples, why are there gaps between bars in some cases but not in others? I think 4A and 4B should have their samples aligned vertically according to the month and sample site. If there are gaps where one sample was completed for Bacteria and not for Archaea that’s fine, but the figure needs to simply explain why. Gaps between sample types makes in 4A but things go astray in 4B.

Response: The bars have been ordered according to sample and month.

Is the relative abundance on the y-axis of figure 4A based on read number? How was that calculated?
Figure 6: What a cool plot. This is a cool way to visualise data. I like it!

Response: Thank you for the comment.

Figure 7: In the legend, “Samples corresponding to their sampling month are indicated as indicated”. This is a bit of a clumsy sentence. Good news is the key is completely self-explanatory so you just delete it. You don’t need to explain TDS again, its common enough in the field and you already have described it in the methods.

Response: This has been corrected

“Notably, members of the phylum Proteobacteria were the most dominant group across all the sampling sites, accounting for 35% abundance.” Is this abundance based on all sample site and time points pooled together? That should be clarified.

Response: This is a cumulative abundance based on all the time points and sites. The clarification has been effected in the manuscript.

“Idiomarina vacuolatum was sampled across all the sampling seasons but varied in structure across the sampling sites.” Do you mean varied in abundance? Be as specific as you can when stating results.

Response: Yes, it is the abundance. I have changed this in the manuscript.

Physicochemical drivers of bacterial and archaeal community structure

“Overall, temperature, pH, P+, K+, NO3-, and TDS had a positive influence on the microbial community structure.” – what does this mean? What do you define as a positive influence?

Response: You are right. The sentence has been changed to read “The results demonstrated that temperature, CaCO₃, pH, P⁺, K⁺, NO₃^-, and TDS influenced the microbial community structure.”

“were adapted to fewer physiochemical factors” bold statement. Keep it more objective here? You could say that these species were not found in high concentrations of X, Y, Z.

Response: This has been corrected to capture the aspect of objectivity.

“pH appears to positively correlate with the structure of the members of the genus Salinarcheum”, what does the structure of members mean?

Response: Structure means how members of a particular microbial community distribute across seasons and sites.

Discussion

Where this manuscript needs attention is in the discussion. In general, discussion clarity and reasoning needs improvement. This is particularly evident when citing other literature. There were a few places I wasn’t sure what the authors meant and there are some repeated / missing words.

“Furthermore, sulfate concentration (39–958 ppm) was lower than that of lakes Sidi Ameur and Himalatt (Algeria) (Boutaiba et al., 2012).” This isn’t a meaningful reference to use here. I don’t understand why this single comparison (of 2 lakes in Algeria) is important to the discussion. Sulfate concentration varies quite a lot throughout soda lakes. Is this sulfate concentration low or high relative to soda lakes in general?

Response: More comparisons have been introduced in the manuscript to capture similar, higher, and lower concentrations of sulfates in soda lakes.

“The concentrations of these elements (except pH) were varied across the sampling months and sites, suggesting that the lake chemistry is constantly changing in its constituent elements” This isn’t a suggestion … you measured it. Instead you could say “measured elements were variable from site to site and fluctuated with time.

Response: Thank you. I have borrowed your words verbatim and the sentence reads well now.

“Hypersaline lakes are characterized by …” The remainder of this paragraph is not relevant to the discussion. It is either introduction material or should be deleted. It does not “discuss” your results.

Response: That part has been paraphrased to explain the reason for high and stable pH. I felt that since pH was relatively stable across seasons and site, it is important to explain how this happens.

“Under the extremes of salinity and alkalinity, microorganisms in soda …” This entire paragraph is also introduction material or should be deleted. It does not discuss the results.

Response: I agree. This paragraph has been entirely deleted.

“Notably, the phylum Proteobacteria was the most dominant group across all the sampling sites, accounting for 35% abundance.” Be specific about what the abundance means, it is 35% of all reads from all timepoints and samples sites were attributed to Proteobacteria?

Response: Proteobacteria accounted for 35% of all the reads.

“They were followed by the phylum Cyanobacteria (14.2%) represented mainly by the Euhalothece spp. Euhalothece is a single- celled stenohaline cyanobacterium that grow optimally at 7% (w/v) NaCl.” This is where you can compare to the salt concentration in your system – is it above or below this?

Response: I have supported this by a sentence reading: “The existence of Euhalothece in Lake Magadi is thus supported by high salts and carbonates (Table 1).”

It seems that Eulohaleaceae are the main bacterial phototrophs in your system. So the following discussion about Spirulina doesn’t make too much sense. You could say this is in contrast to many other soda lakes systems where Arthrospira dominates. Does Lake Magadi have more NaCl than other lakes, is that why Eulohaleaceae and not Arthrospira dominate? Have either of these two taxa been found to be common in the lake in other studies?

Response: The sentence has been paraphrased to capture the contrasting aspect of Lake Magadi with other soda lakes.

“Our findings showed a shift in bacterial composition throughout the sampling seasons where a high abundance of Actinobacteria and Proteobacteria was accompanied by a lower abundance of Actinobacteria.” How is Actinobacteria in high abundance and low abundance?

Response: The entire paragraph does not discuss the results adequately and has been deleted

“Interestingly, the presence of Bacteroidetes was often associated with the availability of Cyanobacteria across the sampling periods” Keep going here… why could this be the case?

Response: The sentence has been enhanced to explain how photosynthetic cyanobacteria contribute towards the generation of substrates for Bacteroidetes and Verrumicrobia.

“However, the abundance of Firmicutes, which possess diverse metabolic capacities and are resistant to oxygen limitations (Martiny et al., 2006) depicted an uneven behavior in relation to Actinobacterial composition.” What do you mean depicted an uneven behaviour?

Response: The entire paragraph does not discuss the results adequately and has been deleted.

“Grant et al. (1999) first characterized this phylum IN the alkaline saltern of Lake Magadi.”

Response: The word “in” has been inserted appropriately. Thank you!

“Their distribution along a salinity gradient in estuarine sediments may be linked to changes in location and/or salinity as well as gradient sediment depth (Webster et al., 2015).” I don’t understand what you mean here.

Response: This sentence has been paraphrased

“Crenarchaeota (Ghori et al., 2021), Crenarchaeota, Euryarchaeota, Woesearchaeota, and Pacearchaeota, Euryachaeota and Woesearchaeota (Wang et al., 2022).” Crenarcheaota and Woesearcheota are repeated in this.

Response: True. This has been deleted

“Remarkably, Thioalkalivibrio sp. was not significantly affected by the physicochemical properties investigated.” Yes! Good observation. But why? Tell me why it is remarkable or unexpected. E.g., “We had expected that Thioalkalivibrio would have responded positively to XYZ…

Response: This has been changed to explain the reason for the effect.

“However, open waters samples from S2–S4 depicted varying degrees of community structure and this could be due to variations in the intertidal water zones (Zhu et al., 2018).” Lacking specificity, what do you mean by community structure here, diversity / abundance / species type? What do you mean by variations in intertidal water zones? What type of variations?

Response: Structure has been replaced with diversity. The sentence has been paraphrased to capture the aspect of water waves and their effect on the distribution of nutrients. This could explain the variation in the diversity of microbes in water ecosystems.

“This phenomenon can be attributed to the maintenance of homogenous abundances by microbial communities during brine formation, hence resulting in higher biodiversity (Banda et al., 2020).” Homogenous abundances of each microbe as evaporation occurs? Why would this happen?

Response: The sentence does not justify the diversity enough. I have introduced another theorem. “Despite high salinity and alkalinity in soda lake brine, the presence of high light intensity and dissolved CO₂ promotes the growth of photosynthetic microorganisms.
Subsequently, these phototrophs generate large quantities of dissolved organic matter (DOM) which become substrates for sustaining the diverse microbial communities (Banda 2020).”

“Hot spring samples collected in September showed high species diversity indices.” Microbial samples from Lake Magadi hot springs were established to be stable and active (Kambura et al., 2016).” Relevance? Are high species diversity indices unusual in hot springs? Is it unusual to have a stable, active community? What does stable mean here? Similarly structured over time? Is that what is seen at S1? There are only two samples from S1 so that conclusion cannot be drawn anyway.

Response: I have rewritten the statement to capture the relationship of our findings with other studies on hot springs and the reason for such high diversity studies. Research on Soda Lake hot springs revealed a highly active and diverse microbial community, suggesting the high plasticity of these organisms toward extreme environments.

Conclusion

The conclusion needs some work. The clarity needs to be improved by being much more specific.

“The results depict a great deal of diversity in bacterial diversity as compared to archaea.” Consider rephrasing this.

“Salinity and alkalinity are the main drivers of the microbial community in the lake. Overall, members of Nocardiodes, Rhodothermus, Haloterrigena, Methanomasiliicoccus, Halorubrum, Palaeococcus, Nocardioides, Salinarcheum, Salinibacter, and Euhalothece had a wide range of adaptability.” Does this mean these members have a wide range of adaptability to salinity and alkalinity or are present in many sites?

“Conversely, Synechococcus, Thioalkalivibrio, Cyanobacterium spp., Rhodovulum, Lewinella, Idiomarina, Pseudidiomarina, Chelatococcus, Aliidiomarina, and Alkalimonas were affected by fewer physicochemical factors.” Does this also mean they had a wide range of adaptability? Or does this mean they weren’t positively correlated with particular nutrients?

“…have a positive correlation with microbial community structure.” What is a positive correlation with microbial community structure? How do they influence the community structure?

Response to conclusion section: I have rewritten the entire conclusion in a way that captures the conclusive elements of both diversity across seasons and sampling sites and the effects of the environmental factors on the population dynamics of microorganisms in Lake Magadi. Your comments were truly helpful.

View more View less

Competing Interests

No competing interests

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] Abdallah MB, Karray F, Kallel N, et al.: Abundance and diversity of prokaryotes in ephemeral hypersaline lake Chott El Jerid using Illumina Miseq sequencing, DGGE and qPCR assays. Extremophiles. 2018; 22: 811–823. PubMed Abstract | Publisher Full Text

[2] Aguilar A, Ingemansson T, Magnien E: Extremophile microorganisms as cell factories: Support from the European Union. Extremophiles. 1998; 2(3): 367–373. PubMed Abstract | Publisher Full Text

[3] Almeida TIR, Calijuri MC, Falco PB, et al.: Biogeochemical process and the diversity of Nhecolândia lakes, Brazil. An. Acad. Bras. Ciênc. 2011; 83:391–407. PubMed Abstract | Publisher Full Text

[4] Andreote APD, Dini-Andreote F, Rigonato J, et al.: Contrasting the genetic patterns of microbial communities in soda lakes with and without cyanobacterial bloom. Front. Microbiol. 2018; 9(244): 1–13. PubMed Abstract | Publisher Full Text | Free Full Text

[5] Antony CP, Kumaresan D, Hunger S, et al.: Microbiology of Lonar Lake and other soda lakes. ISME J. 2013; 7(3): 468–476. PubMed Abstract | Publisher Full Text | Free Full Text

[6] Antranikian G, Vorgias CE, Bertoldo C: Extreme environments as a resource for microorganisms and novel biocatalysts. Adv. Biochem. Eng. Biotechnol. 2005; 96(8): 219–262. Publisher Full Text

[7] Banda JF, Lu Y, Hao C, et al.: The Effects of Salinity and pH on Microbial Community Diversity and Distribution Pattern in the Brines of Soda Lakes in Badain Jaran Desert, China. Geomicrobiol. J. 2020; 37(1): 1–12. Publisher Full Text

[8] Behr HJ, Röhricht C: Record of seismotectonic events in siliceous cyanobacterial sediments (Magadi cherts), Lake Magadi, Kenya. Int. J. Earth Sci. 2000; 89(2): 268–283. isi:000089932800007. Publisher Full Text

[9] Boros E, Kolpakova M: A review of the defining chemical properties of soda lakes and pans: An assessment on a large geographic scale of Eurasian inland saline surface waters. PLoS One. 2018; 13(8): e0202205. PubMed Abstract | Publisher Full Text | Free Full Text

[10] Boutaiba S, Hacene H, Bidle KA, et al.: Salt Lakes of the Algerian Sahara. J. Arid Environ. 2012; 75(10): 909–916. PubMed Abstract | Publisher Full Text | Free Full Text

[11] Bray JR, Curtis JT: An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. 1957; 27(4): 325–349. Publisher Full Text

[12] Canganella F, Wiegel J: Extremophiles: From abyssal to terrestrial ecosystems and possibly beyond. Naturwissenschaften. 2011; 98(4): 253–279. PubMed Abstract | Publisher Full Text

[13] Caporaso JG, Bittinger K, Bushman FD, et al.: PyNAST: A flexible tool for aligning sequences to a template alignment. Bioinformatics. 2010a; 26(2): 266–267. PubMed Abstract | Publisher Full Text | Free Full Text

[14] Caporaso JG, Kuczynski J, Stombaugh J, et al.: QIIME allows analysis of high-throughput community sequencing data. Nat. Methods. 2010b; 7(5): 335–336. PubMed Abstract | Publisher Full Text | Free Full Text

[15] Caporaso JG, Lauber CL, Walters WA, et al.: Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012; 6(8): 1621–1624. PubMed Abstract | Publisher Full Text | Free Full Text

[16] Chiu HH, Rogozin DY, Huang SP, et al.: Aliidiomarina shirensis sp. nov., a halophilic bacterium isolated from Shira Lake in Khakasia, southern Siberia, and a proposal to transfer Idiomarina maris to the genus Aliidiomarina. Int. J. Syst. Evol. Microbiol. 2014; 64(4): 1334–1339. Publisher Full Text

[17] Dadheech PK, Glöckner G, Casper P, et al.: Cyanobacterial diversity in the hot spring, pelagic, and benthic habitats of a tropical soda lake. FEMS Microbiol. Ecol. 2013; 85(2):389–401. PubMed Abstract | Publisher Full Text

[18] De Maayer P, Anderson D, Cary C, et al.: Some like it cold: Understanding the survival strategies of psychrophiles. EMBO Rep. 2014; 15(5): 508–517. PubMed Abstract | Publisher Full Text | Free Full Text

[19] Duckworth AW, Grant WD, Jones BE, et al.: Halomonas magadii sp. nov., a new member of the genus Halomonas, isolated from a soda lake of the East African Rift Valley. Extremophiles. 2000; 4(1): 53–60. PubMed Abstract | Publisher Full Text

[20] Edgar RC, Haas BJ, Clemente JC, et al.: UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011; 27(16): 2194–2200. PubMed Abstract | Publisher Full Text | Free Full Text

[21] Edwin N, Akhwale JK, Mwirichia R: Phylogenetic and morphological diversity of culturable cyanobacteria from Lake Magadi in Kenya. Afr. J. Biol. Sci. 2019; 01(4): 24–31. Publisher Full Text

[22] Eugester H: Origin and Deposition of Trona. Rocky Mt. Geol. 1971; 10(1): 49–55.

[23] Eugster HP: Lake Magadi, Kenya, and its precursors. Dev. Sedimentol. 1980; 28(C): 195–232. Publisher Full Text

[24] Feng J, Zhou P, Zhou YG, et al.: Halorubrum alkaliphilum sp. nov., a novel haloalkaliphile isolated from a soda lake in Xinjiang, China. Int. J. Syst. Evol. Microbiol. 2005; 55(1): 149–152. Publisher Full Text

[25] Getenet M, García-Ruiz JM, Otálora F, et al.: A Comprehensive Methodology for Monitoring Evaporitic Mineral Precipitation and Hydrochemical Evolution of Saline Lakes: The Case of Lake Magadi Soda Brine (East African Rift Valley, Kenya). Cryst. Growth Des. 2022; 22(4): 2307–2317. PubMed Abstract | Publisher Full Text | Free Full Text

[26] Ghori N, Michael JW, Andrew SW: Temporal microbial community dynamics within a unique acid saline lake. Front. Microbiol. 2021; 12: 649594. PubMed Abstract | Publisher Full Text | Free Full Text

[27] Grant WD, Sorokin D: Distribution and Diversity of Soda Lake Alkaliphiles. Extremophiles Handbook. 2011; (July 2015): 28–54. Publisher Full Text

[28] Grant WD, Jones BE: Soda lakes of East Africa. Soda Lakes of East Africa. 2016; 1–408. Publisher Full Text

[29] Grant S, Grant WD, Jones BE, et al.: Novel archaeal phylotypes from an East African alkaline saltern. Extremophiles. 1999; 3(2): 139–145. PubMed Abstract | Publisher Full Text

[30] Grant WD: Alkaline environments and biodiversity. Encyclopedia of Life Support Systems. 2006; 20.

[31] Han R, Zhang X, Liu J, et al.: Microbial community structure and diversity within hypersaline Keke Salt Lake environments. Can. J. Microbiol. 2017; 63(11): 895–908. Publisher Full Text

[32] He H, Fu L, Liu Q, et al.: Community Structure, Abundance and Potential Functions of Bacteria and Archaea in the Sansha Yongle Blue Hole, Xisha, South China Sea. Front. Microbiol. 2019; 10(2404): 1–16. PubMed Abstract | Publisher Full Text | Free Full Text

[33] Hosam EE, Mohamad SAE-K, Mai AW: Biodiversity of uncultured bacteria in hypersaline lakes, Siwa oasis, Egypt, as determined by polymerase chain reaction and denaturing gradient gel electrophoresis (PCR-DGGE) of 16S rRNA gene phylotypes. Int. J. Genet. Mol. Biol. 2017; 9(2): 8–15. Publisher Full Text

[34] Jiang H, Dong H, Yu B, et al.: Microbial response to salinity change in Lake Chaka, a hypersaline lake on Tibetan plateau. Environ. Microbiol. 2007; 9(10): 2603–2621. PubMed Abstract | Publisher Full Text

[35] Joachimiak MP, Weisman JL, May BCH: JColorGrid: Software for the visualization of biological measurements. BMC Bioinformatics. 2006; 7: 1–5. PubMed Abstract | Publisher Full Text | Free Full Text

[36] Jones BE, Grant WD, Duckworth AW, et al.: Microbial diversity of soda lakes. Extremophiles. 1998; 2: 191–200. Publisher Full Text

[37] Kambura AK, Mwirichia RK, Kasili RW, et al.: Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya. BMC Microbiol. 2016; 16(1): 1–12. Publisher Full Text

[38] Kamekura M, Dyall-smith ML, Upasani V, et al.: Diversity of Alkaliphilic Halobacteria: Proposals for Transfer of Na trono bacterium vacuola tum, Na trono ba cterium magadii, and Natronobacterium pharaonis to Halorubrum, Natrialba, and Natronomonas gen. nov., Respectively, as Halorubrum. Int. J. Syst. Bacteriol. 1997; 47(7): 853–857. PubMed Abstract | Publisher Full Text

[39] Kevbrin VV, Zhilina TN, Rainey FA, et al.: Tindallia magadii gen. nov., sp. nov.: An alkaliphilic anaerobic ammonifier from Soda Lake Deposits. Curr. Microbiol. 1998; 37(2): 94–100. Publisher Full Text

[40] Kiplimo D, Mugweru J, Kituyi S, et al.: Diversity of esterase and lipase producing haloalkaliphilic bacteria from Lake Magadi in Kenya. J. Basic Microbiol. 2019; 59(12): 1173–1184. PubMed Abstract | Publisher Full Text

[41] Kipnyargis A, Eucharia K, Fathiya K, et al.: Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya: Extended data. Figshare. 2023a. Reference Source

[42] Kipnyargis A, Mwirichia R, Eucharia K, et al.: ID 962270 - BioProject - NCBI.2023b. Reference Source

[43] Kipnyargis A, Mwirichia R, Pfeiffer B, et al.: Complete Genome Sequence of Alkalihalobacillus sp. Strain LMS39, a Haloalkaliphilic Bacterium Isolated from a Hypersaline Lake. Microbiol. Resour. Announc. 2022; 11(7): e0032522. PubMed Abstract | Publisher Full Text | Free Full Text

[44] Krenitz L, Shagerl M: Tiny and Tough: Microphytes of East African Soda Lakes.Schagerl M, editor. Soda Lakes of East Africa. Springer; 2016; pp. 149–177.

[45] Krulwich TA, Sachs G, Padan E: Molecular aspects of bacterial pH sensing and homeostasis. Nat. Rev. Microbiol. 2011; 9(5): 330–343. PubMed Abstract | Publisher Full Text | Free Full Text

[46] Lameck AS, Skutai J, Boros E: Review of chemical properties of inland soda and saline waters in East Africa (rift valley region). J. Hydrol.: Reg. Stud. 2023; 46:101323. Publisher Full Text

[47] Li R, Khafipour E, Krause DO, et al.: Pyrosequencing Reveals the Influence of Organic and Conventional Farming Systems on Bacterial Communities. PLoS One. 2012; 7(12): e51897. PubMed Abstract | Publisher Full Text | Free Full Text

[48] Li X, Yang M, Mu T, et al.: Composition and key-influencing factors of bacterial communities active in sulfur cycling of soda lake sediments. Arch. Microbiol. 2022; 204(6): 317–319. PubMed Abstract | Publisher Full Text

[49] Liu C, Cui Y, Li X, et al.: Microeco: An R package for data mining in microbial community ecology. FEMS Microbiol. Ecol. 2021; 97(2): 1–9. Publisher Full Text

[50] Lozupone C, Knight R: UniFrac: A new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 2005; 71(12): 8228–8235. PubMed Abstract | Publisher Full Text | Free Full Text

[51] Ma Y, Xue Y, Grant WD, et al.: Alkalimonas amylolytica gen. nov., sp. nov., and Alkalimonas delamerensis gen. nov., sp. nov., novel alkaliphilic bacteria from soda lakes in China and East Africa. Extremophiles. 2004; 8(3): 193–200. PubMed Abstract | Publisher Full Text

[52] Mahmoud AMA, Ali MHH, Abdelkarim MS, et al.: Chemical, biochemical, and bioactivity studies on some soda lakes, Wadi El-Natrun, Egypt. Environ. Monit. Assess. 2024; 196:436. PubMed Abstract | Publisher Full Text | Free Full Text

[53] Mani K, Taib N, Hugoni M, et al.: Transient dynamics of archaea and bacteria in sediments and brine across a salinity gradient in a solar saltern of Goa, India. Front. Microbiol. 2020; 11(August): 1–19. PubMed Abstract | Publisher Full Text | Free Full Text

[54] Matagi SV: A biodiversity assessment of the Flamingo Lakes of eastern Africa. J. Limnol. 2004; 5(1): 13–26. Publisher Full Text

[55] Melack JM, Kilham P: Photosynthetic rates of phytoplankton in East African alkaline, saline lakes1. Limnol. Oceanogr. 1974; 19(5): 743–755. Publisher Full Text

[56] Menasria T, Monteoliva-Sánchez M, Benammar L, et al.: Culturable halophilic bacteria inhabiting Algerian saline ecosystems: A source of promising features and potentialities. World J. Microbiol. Biotechnol. 2019; 35(9): 132. PubMed Abstract | Publisher Full Text

[57] Mikhodyuk OS, Gerasimenko LM, Akimov VN, et al.: Ecophysiology and polymorphism of the unicellular extremely natronophilic cyanobacterium Euhalothece sp. Z-M001 from Lake Magadi. Microbiology. 2008; 77(6): 717–725. Publisher Full Text

[58] Minegishi H, Enomoto S, Echigo A, et al.: Salinarchaeum chitinilyticum sp. Nov., a chitin-degrading haloarchaeon isolated from commercial salt. Int. J. Syst. Evol. Microbiol. 2017; 67(7): 2274–2278. PubMed Abstract | Publisher Full Text

[59] Muruga B, Anyango B: A Survey of Extremophilic Bacteria in Lake Magadi, Kenya. Am. J. Mol. Cell. Biol. 2013; 2(1): 14–26.

[60] Mwatha WE, Grant WD: Natronobacterium vacuolata sp. nov., a Haloalkaliphilic Archaeon Isolated from Lake Magadi, Kenya. Int. J. Syst. Bacteriol. 2016; 43(3): 401–404.

[61] Mwirichia R: Amplicon-Based Analysis of the Fungal Diversity across Four Kenyan Soda Lakes. Scientifica. 2022; 2022: 1–9. PubMed Abstract | Publisher Full Text | Free Full Text

[62] Newton RJ, Jones SE, Eiler A, et al.: A Guide to the Natural History of Freshwater Lake Bacteria. Microbiol. Mol. Biol. Rev. 2011; 75(1): 14–49. PubMed Abstract | Publisher Full Text | Free Full Text

[63] Oduor SO, Schagerl M: Temporal trends of ion contents and nutrients in three Kenyan Rift Valley saline-alkaline lakes and their influence on phytoplankton biomass. Hydrobiologia. 2007; 584(1): 59–68. Publisher Full Text

[64] Oksanen J: Vegan: an introduction to ordination. Management. 2015; 1: 1–10. Reference Source

[65] Oren A: Thermodynamic limits to microbial life at high salt concentrations. Environ. Microbiol. 2011; 13(8): 1908–1923. PubMed Abstract | Publisher Full Text

[66] Orwa P, Mugambi G, Wekesa V, et al.: Isolation of haloalkaliphilic fungi from Lake Magadi in Kenya. Heliyon. 2020; 6(1): e02823. PubMed Abstract | Publisher Full Text | Free Full Text

[67] Otasek D, Morris JH, Bouças J, et al.: Cytoscape Automation: Empowering workflow-based network analysis. Genome Biol. 2019; 20(1): 115–185. PubMed Abstract | Publisher Full Text | Free Full Text

[68] Pérez-Pantoja D, Donoso R, Agulló L, et al.: Genomic analysis of the potential for aromatic compounds biodegradation in Burkholderiales. Environ. Microbiol. 2012; 14(5): 1091–1117. Publisher Full Text

[69] Pérez E, Chebude Y: Chemical Analysis of Gaet’ale, a Hypersaline Pond in Danakil Depression (Ethiopia): New Record for the Most Saline Water Body on Earth. Aquat. Geochem. 2017; 23(2): 109–117. Publisher Full Text

[70] Poyraz N, Mutlu M: Characterization of Microbial Populations of Lake Van By 16S Metagenomics Study. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi - C Yaşam Bilimleri Ve Biyoteknoloji. 2020; 9(1): 80–88. Publisher Full Text

[71] Price MN, Dehal PS, Arkin AP: FastTree 2 - Approximately maximum-likelihood trees for large alignments. PLoS One. 2010; 5(3): e9490. PubMed Abstract | Publisher Full Text | Free Full Text

[72] Quast C, Pruesse E, Yilmaz P, et al.: The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2012; 41(D1): D590–D596. PubMed Abstract | Publisher Full Text | Free Full Text

[73] R Core Team: R: A language and environment for statistical computing Vienna, Austria: R Foundation for Statistical Computing; 2020. https://www.r-project.org/

[74] RStudio Team: RStudio: integrated development for R.PBC, Boston, MA: Rstudio Team; 2020. Reference Source

[75] Rampelotto PH: Extremophiles and extreme environments. Life. 2013; 3(3): 482–485. PubMed Abstract | Publisher Full Text | Free Full Text

[76] Rognes T, Flouri T, Nichols B, et al.: VSEARCH: A versatile open source tool for metagenomics. PeerJ. 2016; 4(10): e2584–e2522. PubMed Abstract | Publisher Full Text | Free Full Text

[77] Rosenberg E, De Long EF, Lory S, et al.: The prokaryotes: Other major lineages of bacteria and the archaea. The Prokaryotes: Other Major Lineages of Bacteria and The Archaea. 2014; 43: 1–1028. Publisher Full Text

[78] Salano OA, Makonde M, Kasili RW, et al.: Diversity and distribution of fungal communities within the hot springs of soda lakes in the Kenyan rift valley. Academicjournals. Org. 2017; 11(19): 764–775. Publisher Full Text

[79] Simachew A, Lanzén A, Gessesse A, et al.: Prokaryotic Community Diversity Along an Increasing Salt Gradient in a Soda Ash Concentration Pond. Microb. Ecol. 2016; 71(2): 326–338. PubMed Abstract | Publisher Full Text

[80] Sorokin DY, Panteleeva AN, Tourova TP, et al.: Natronoflexus pectinivorans gen. nov. sp. nov., an obligately anaerobic and alkaliphilic fermentative member of Bacteroidetes from soda lakes. Extremophiles. 2011; 15(6): 691–696. PubMed Abstract | Publisher Full Text | Free Full Text

[81] Sorokin DY, Berben T, Melton ED, et al.: Microbial diversity and biogeochemical cycling in soda lakes. Extremophiles. 2014a; 18(5): 791–809. PubMed Abstract | Publisher Full Text | Free Full Text

[82] Sorokin DY, Gumerov VM, Rakitin AL, et al.: Genome analysis of Chitinivibrio alkaliphilus gen. nov., sp. nov., a novel extremely haloalkaliphilic anaerobic chitinolytic bacterium from the candidate phylum Termite Group 3. Environ. Microbiol. 2014b; 16(6): 1549–1565. PubMed Abstract | Publisher Full Text

[83] Sorokin DY, Kuenen JG: Chemolithotrophic haloalkaliphiles from soda lakes. FEMS Microbiol. Ecol. 2005; 52(3): 287–295. PubMed Abstract | Publisher Full Text

[84] Sorokin DY, Trotsenko YA, Doronina NV, et al.: Methylohalomonas lacus gen. nov., sp. nov. and Methylonatrum kenyense gen. nov., sp. nov., methylotrophic gammaproteobacteria from hypersaline lakes. Int. J. Syst. Evol. Microbiol. 2007; 57(12): 2762–2769. PubMed Abstract | Publisher Full Text

[85] Taher AG: Inland saline lakes of Wadi El Natrun depression, Egypt. Int. J. Salt Lake Res. 1999; 8(2): 149–170. Publisher Full Text

[86] Tao X, Guo F, Zhou Q, et al.: Bacterial community mapping of the intestinal tract in acute pancreatitis rats based on 16S rDNA gene sequence analysis. RSC Adv. 2019; 9(9): 5025–5036. PubMed Abstract | Publisher Full Text | Free Full Text

[87] Tazi L, Breakwell DP, Harker AR, et al.: Life in extreme environments: Microbial diversity in Great Salt Lake, Utah. Extremophiles. 2014; 18(3): 525–535. PubMed Abstract | Publisher Full Text

[88] Tindall BJ, Ross HNM, Grant WD: Natronobacterium gen. nov. and Natronococcus gen. nov., Two New Genera of Haloalkaliphilic Archaebacteria. Syst. Appl. Microbiol. 1984; 5(1): 41–57. Publisher Full Text

[89] Urbieta MS, Donati ER, Chan KG, et al.: Thermophiles in the genomic era: Biodiversity, science, and applications. Biotechnol. Adv. 2015; 33(6): 633–647. Publisher Full Text

[90] Vavourakis CD, Andrei AS, Mehrshad M, et al.: A metagenomics roadmap to the uncultured genome diversity in hypersaline soda lake sediments. Microbiome. 2018; 6(1): 118–168. PubMed Abstract | Publisher Full Text | Free Full Text

[91] Vavourakis CD, Ghai R, Rodriguez-Valera F, et al.: Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines. Front. Microbiol. 2016; 7(211): 1–18. Publisher Full Text

[92] Wang M, Zhang X, Shu Z, et al.: Bacterial and archaeal communities within the alkaline soda Langaco Lake in the Qinghai-Tibet Plateau. Ann. Microbiol. 2022; 72(1): 1–15. Publisher Full Text

[93] Webster G, O’Sullivan LA, Meng Y, et al.: Archaeal community diversity and abundance changes along a natural salinity gradient in estuarine sediments. FEMS Microbiol. Ecol. 2015; 91(2): 1–18. PubMed Abstract | Publisher Full Text | Free Full Text

[94] Zavarzina DG, Zhilina TN, Kuznetsov BB, et al.: Natranaerobaculum magadiense gen. nov., sp. nov., an anaerobic, alkalithermophilic bacterium from soda lake sediment. Int. J. Syst. Evol. Microbiol. 2013; 63(PART 12): 4456–4461. PubMed Abstract | Publisher Full Text

[95] Zhao D, Zhang S, Xue Q, et al.: Abundant Taxa and Favorable Pathways in the Microbiome of Soda-Saline Lakes in Inner Mongolia. Front. Microbiol. 2020; 11(July): 1–17. PubMed Abstract | Publisher Full Text | Free Full Text

[96] Zhilina TN, Garnova ES, Tourova TP, et al.: Amphibacillus fermentum sp. nov. and Amphibacillus tropicus sp. nov., new alkaliphilic, facultatively anaerobic, saccharolytic bacilli from Lake Magadi. Microbiology. 2001; 70(6): 711–722. Publisher Full Text

[97] Zhilina TN, Zavarzin GA, Rainey F, et al.: Spirochaeta alkalica sp. nov., Spirochaeta africana sp. nov., and Spirochaeta asiatica sp. nov., alkaliphilic anaerobes from the Continental Soda Lakes in Central Asia and the East African rift. Int. J. Syst. Bacteriol. 1996; 46(1): 305–312. PubMed Abstract | Publisher Full Text

[98] Zhu P, Wang Y, Shi T, et al.: Intertidal zonation affects diversity and functional potentials of bacteria in surface sediments: A case study of the Golden Bay mangrove, China. Appl. Soil Ecol. 2018; 130(5): 159–168. Publisher Full Text

[99] Zorz JK, Sharp C, Kleiner M, et al.: A shared core microbiome in soda lakes separated by large distances. Nat. Commun. 2019; 10(1): 4210–4230. PubMed Abstract | Publisher Full Text | Free Full Text

Spatiotemporal structure and composition of the microbial communities in hypersaline Lake Magadi, Kenya

Abstract

Background

Methods

Results

Conclusions

Keywords

Revised Amendments from Version 1

Introduction

Methods

Sampling site and sampling criteria

Figure 1. Map of Lake Magadi showing the sampling sites.

Analysis of physicochemical parameters

DNA extraction

Sequencing of the 16S rRNA amplicons

Sequence processing and taxonomic assignment

Microbial community analysis

Results

Physicochemical properties of the sampling sites

Table 1. Physicochemical characteristics of the water samples collected from Lake Magadi.

Sequence analysis and diversity studies

Table 2. Number of sequences generated, OTUs, and diversity indices of 22 sampling sites in Lake Magadi.

Alpha diversity studies

Figure 2. Alpha diversity plots of OTU richness among different sampling months.

Beta diversity studies

Figure 3. Principal component analysis (PCA) ordination of differences in microbial communities from sampling sites and sampling months.

Taxonomic composition and structure

Figure 4. Relative abundance and composition of the microbial community taxa based on sampling sites and month of sampling.

Figure 5. Read abundance (%) of the top 30 species across samples.

Figure 6. Network analysis of microbial community at Family level based on sampling sites.

Physicochemical drivers of bacterial and archaeal community structure

Discussion

Conclusion

Data availability

Underlying data

Extended data

References

Comments on this article Comments (0)

Open Peer Review

Comments on this article Comments (0)

Open Peer Review

Reviewer Status

Reviewer Reports

Comments on this article

Browse by related subjects

Competing Interests Policy

Stay Updated