Evaluation of antimicrobial susceptibility of <i>Escherichia coli </i>isolated from contaminated areas of Majengo slum in Meru County, Kenya

Jared Ombuya; Kennedy Gachoka; Naomi Mutea

doi:10.12688/f1000research.124121.1

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Research Article

Evaluation of antimicrobial susceptibility of Escherichia coli isolated from contaminated areas of Majengo slum in Meru County, Kenya

[version 1; peer review: awaiting peer review]

Jared Ombuya ¹, Kennedy Gachoka², Naomi Mutea³

PUBLISHED 04 Oct 2022

Author details Author details

¹ Meru University of Science and Technology, Meru, Kenya
² School of Applied Sciences, Meru University of Science & Technology, Meru, Kenya
³ School of Nursing, Meru University of Science and Technology, Meru, Kenya

Jared Ombuya
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Kennedy Gachoka
Roles: Supervision

Naomi Mutea
Roles: Supervision

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Background: Antimicrobial drug resistance is of great concern today. Infections by the antimicrobial resistant strains of Escherichia coli, including enteropathogenic as well as enterotoxigenic strains have been reported as a major cause of deaths, especially among young children in low- and middle-income countries. This has been augmented by antimicrobial misuse, over the counter availability and poor sanitation especially in low income areas.
This study aimed at characterizing antimicrobial resistant strains of Escherichia coli isolated from sanitation environments of the Majengo slum in Meru County, Kenya
Methods: A cross-sectional study was conducted on 61 samples from soil, water and drains swabs. These were tested against five antimicrobial drugs by the Kirby disk diffusion method.
Results: A total of 42 (69%) of the samples had Escherichia coli. These recorded antimicrobial drug susceptibility as follows: Out of the five antimicrobial agents used, ceftazidime 28 (66.67%) showed the highest sensitivity followed by ciprofloxacin 26 (61.90%) and imepenem 25 (59.52%) respectively. cefotaxime and cefoxitin showed least sensitivity at 14 (33.33%) and 13 (30.95%) respectively. In intermediate imepenem and ciprofloxacin were the highest with 12 (28.57%) followed by cefotaxime 10 (23.81%). The least intermediate was observed in ceftazidime and cefoxitin both at 7 (16.67%). The highest resistance was observed in cefoxitin 22 (52.38%), followed by cefotaxime at 18 (42.86%). Ciprofloxacin, imepenem and ceftazidime had the lowest resistance 4 (9.52%), 5 (11.91%) and 7 (16.67%) respectively. The p-value <0.05 was considered significant to the study.
Conclusions: This study showed that Escherichia coli isolated from Majengo is pathogenic and resistant to antibiotics. Detection of Escherichia coli poses a great risk in the spread of resistant strains in human. Proper sanitation and hygiene awareness practices should be provided through education to the residents of this area.

Keywords

E. coli, Susceptibility Testing, Antimicrobial Resistance, Multidrug Resistance, Ciprofloxacin, Ceftazidime, Cefotaxime, Imepenem, Cefoxitin

Corresponding author: Jared Ombuya

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2022 Ombuya J 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: Ombuya J, Gachoka K and Mutea N. Evaluation of antimicrobial susceptibility of Escherichia coli isolated from contaminated areas of Majengo slum in Meru County, Kenya [version 1; peer review: awaiting peer review]. F1000Research 2022, 11:1133 (https://doi.org/10.12688/f1000research.124121.1) First published: 04 Oct 2022, 11:1133 (https://doi.org/10.12688/f1000research.124121.1) Latest published: 12 Apr 2023, 11:1133 (https://doi.org/10.12688/f1000research.124121.3)

Introduction

Infectious organisms are currently the major cause of diseases worldwide. A number of newly recognized pathogens and strains are now emerging. These organisms have resulted in high morbidity and mortality globally.¹ The emergence of these pathogens has been attributed to microbial evolution, high mutations as the organisms try surviving in different environments as well as creation of new environments. This microbial evolution and high mutations has resulted to drug resistance, especially due to deposition of drug residues released in different environments, and more especially in areas with poor drainages and poor sanitation systems. As a result, there has evolved a need for surveillance and monitoring systems with emphasis on sanitation and water management. This will help curve the spread of emerging and re-emerging infectious diseases.

Human population growth currently has faced great challenges in accessing proper quality and quantity water resources. This has led to an increase in the number of water borne infectious diseases recently.² An estimated 30% of the bacterial population has been reported to be emerging because of wastewater, agricultural practices, and poor sanitation systems. Water management could act as a barrier to prevent the spread of pathogens. Prevention of pathogens could reduce environmental contamination, antibiotic misuse and eventually mutation of microorganisms.

In different environmental set ups, studies have indicated increased multidrug resistance strains which has led to increased mortality and morbidity resulting from exposure to infection causing organisms. Improved sanitation facilities is one of the most important interventions needed in order to stop the spread of resistant bacteria.³ A study on typhoid among young children,⁴ stressed the need for careful monitoring of antimicrobial resistance in a view to prevent increase of resistance strains and resultant infections to vulnerable communities.

Diarrheagenic E. coli has demonstrated a significant resistance to beta lactams antibiotics that are commonly prescribed,⁵ with contributing factors to diarrhea cases attributed to poor quality of foods, poor water systems, lack of proper hygiene often due to lack of water and poor sanitation. Studies have shown that human and animal waste are the main sources of contamination on the environment that hosts strains that are antimicrobial resistance.⁶ The study indicated that contamination resulted in formation of biofilms that supported bacterial resistance.

Methods

Ethical considerations

Approval to carry out the study was done by Meru University of Science and Technology MIRERC (Meru University Institutional Research and Ethics Review Committee). Approval Ref NO: MU/1/39/28 VOL.2(31). Date 17^th February 2022.

Study area

The study was conducted in the Majengo area, an informal settlement in Meru County within the Eastern region of Kenya. As with other slum areas, Majengo has congested households with poor sanitation and limited access to safe toilet facilities. It is located at Imenti North sub-county and Ntima west ward. River Kathita passes along the slum.

Study design and population

The study employed a cross-sectional study design with an aspect of laboratory analysis. Environmental samples were collected from water collection points, soils near latrines, and open drains in the Majengo area. Samples that were collected included water, soils, and swabs of open drains. The samples were then transported to the laboratory for analysis. The study did not involve households or interactions with residents of the Majengo area.

Sampling procedure

To identify sites for sample collection, the study utilized a stratified sampling scheme, where the Majengo area was stratified by its constituent villages using available maps. In each village, areas of sampling were randomly selected based on availability of the water collection points, soils near latrines, and open drains. The number of sampled areas or type of samples in each village was dependent on accessibility and spatial/temporal distribution of the sample types. The sampled areas were marked using Google map to pin sample collection points. Figure 1 shows sampled areas in the Majengo slum. The area was divided into two strata A and B as shown on the map.

Figure 1. Shows a map of the sampled areas in the Majengo slum. Maps data ©2022: Google, ©2022 CNES/Airbus, Maxar Technologies.

Sample size determination

To determine the required sample size, the following formula was used at a 95% confidence interval.⁷

n = \frac{{(z - score)}^{2} \times StdDev \times (1 - StdDev)}{{(marginal error)}^{2}}

n = \frac{(1.96) 2 \times 0.2 (1 - 0.2)}{0.05 \times 0.05}

Sample size = 61 samples

Sample processing

A 500 ml river water sample was collected into 500 ml sterile bottles by laying the bottle in water facing upstream. Tap water was collected into sterile 500 ml bottles. To do this, the individual tap was sterilized using a flamed alcohol cotton swab, a little water was allowed to flow, before getting collected into the sterile sample bottle. Approximately 10 g of soil samples were collected near toilets and dumping areas using a sterile spoon. In the swab collection, the cover was first untwisted to remove the swab and the sample collection was done by moving the swab in a clockwise circular motion. The swab was then returned aseptically into the vial containing transport media. It was labelled and packed in a cooler box containing an ice pack for transportation to the laboratory for analysis.

Samples preparation prior to the inoculation

Soil sample

A sample of soil weighing 1g was dissolved in sterile distilled water in a 250 ml conical flask.⁸ A serial dilution was performed up to 10⁵ for E. coli all dilutions were cultured into MacConkey agar (oxoid CM007) and incubated (Biobase) China at 37°C for 24 hours using microbiological standards of culturing. After this duration pink colonies of target organisms were sub cultured in Tryptone Bile Glucuronide (TBX) CM 0964 (Techno Pharmchem, India) to detect E. coli. Confirmation of E. coli was done on indole test.

Drain swabs

In the laboratory, drain swabs samples were cultured in MacConkey agar (Oxoid CM007) to isolate E. coli. The media was incubated at 37°C for 24 hours. After 24 hours’ growth pink colonies of E. coli in MacConkey agar (Oxoid CM007) were sub cultured in TBX to detect E. coli. Growth of green colonies was an indicator for the presence of E. coli.

Water analysis using most probable number method

The most probable number method was used to analyze water samples using MacConkey broth (Oxoid CM0505CM 0505) UK. Each bottle with sample was appropriately labelled. The water was mixed thoroughly by inverting the bottle several times. The cap of the bottle was removed and the mouth of the bottle flamed. The water samples were then inoculated by arranging the bottles in an incubator independently inside the incubator grill.⁹ After inoculation the bottles were incubated at 44°C for 24 hours and the samples were examined by observing the color change and gas formation. Table 1. shows water analysis set for untreated and treated water samples.

Table 1. Water analysis set for untreated and treated water samples.

Sample type	No. of bottles	Ml of broth	Strength of broth
Untreated water	1	50	Double
	5	10	Double
	5	5	Single
Treated water	1	50	Double
Treated water	5	10	Double

Microbiological identification of E. coli from the samples

In the laboratory, samples were cultured in MacConkey agar to isolate E. coli. The cultures were incubated at 37°C for 24 hours. After 24 hours’ growth of target organisms in MacConkey agar were sub cultured in TBX to detect E. coli. Growth of green colonies was an indicator for the presence of E. coli.

Biochemical identification of E. coli using Tryptone water

Isolates were subjected to biochemical identification using the indole test for E. coli. The test organism was inoculated in a bijou bottle containing 3 ml Tryptone water (Oxoid CM0087) UK and incubated at 37°C for 48 hours. The test for indole was done by adding one drop of Kovac’s reagent (Himedia) and the formation of a red ring within 10 minutes indicated presence of E. coli.

Gram staining technique

Gram staining is a technique used in differentiation of gram-positive and gram-negative bacteria. The technique is important since it helps in selecting the correct antibiotic during microbial sensitivity. A smear was prepared from the colonies to confirm if it was gram-negative rods using gram staining procedure. The procedure required gram stain reagents, slides, oil immersion and a microscope.

Colonies of the test organism were emulsified on a glass slide using a wire loop. A drop of normal saline was added to make a smear. The slide was allowed to air dry. The slides were passed through a flame to fix them. The smear was covered with crystal violet solution for 30 seconds. Then the smear was rapidly washed off to remove the excess stain. The smear was covered with Gram’s Iodine (Pro-Lab Diagnostics Netherland) for 30 seconds and washed off using tap water. The smear was decolorized by covering with acetone for a few seconds and washed off. The smear was then covered with a counter stain neutral red for 30 seconds. The smear was allowed to dry before being examined at power ×100 on a microscope (Olympus CX22). Presence of gram-negative rods confirmed the organism.

Antimicrobial susceptibility testing

Antimicrobial susceptibility testing was done using Mueller-Hinton Agar. Before inoculation of the organism to the Mueller-Hinton (CMO337 Oxoid) UK, single colonies were used to make 0.5 ml McFarland standard.¹⁰^,¹¹ Colony suspension was first prepared by picking single colonies and suspending them in a vial containing 1ml normal saline. The suspension was compared with McFarland’s standard in order to obtain the required concentration of the isolate. Using a sterile cotton swab, the isolate was picked and spread evenly on Mueller-Hinton agar. Once all the Mueller-Hinton agar was completely inoculated by suspension, antimicrobial discs were inserted on the swabbed Mueller-Hinton agar.¹² The discs were well spaced to prevent them from overlapping. They were pressed on the media to ensure complete contact. They were incubated for 24 hours at 37°C. After 24 hours of incubation, the susceptibility and resistance was determined by measuring the diameter of the zone of inhibition using Vernier Calipers. The measurement was recorded in millimeters. This enabled classification of isolates of E. coli as either sensitive, intermediate, or resistant.¹¹^,¹³ ATCC 25922 E. coli was used as a control organism during the study. The microbial agents used were as follows in their corresponding concentrations; imepenem (10 μg); ceftazidime (30 μg); cefotaxime (30 μg); cefoxitin (30 μg) and ciprofloxacin (5 μg).

Data analysis

Laboratory data was entered into Microsoft Excel v 2010 and analyzed using SPSS version 26.0. Descriptive analysis was done using Microsoft Excel. The analysis included, frequencies and graphs. Data was compared between each study strata and between each sample type using Kruskal-Wallis tests, between the two drugs using the Wilcoxon Signed Rank test and findings were presented as figures tables and graphs. A p-value of 0.05 or less was considered significant between comparison in susceptibility and resistance between the strata A and B.

Results

Antimicrobial susceptibility from both strata

A total of 42 isolates were tested for antimicrobial susceptibility in both strata. Out of these antimicrobials, 5 (50.48%) were susceptible, 5 (22.86%) were intermediate and 5 (26.67%) were resistant. Out of the five antimicrobial agents used, ceftazidime 28 (66.67%) showed the highest sensitivity followed by ciprofloxacin 26 (61.90%) and imepenem 25 (59.52%) respectively. cefotaxime and cefoxitin showed least sensitivity at 14 (33.33%) and 13 (30.95%) respectively. In intermediate imepenem and ciprofloxacin were the highest with 12 (28.57%) followed by cefotaxime 10 (23.81%). The least intermediate was observed in ceftazidime and cefoxitin both at 7 (16.67%). The highest resistance was observed in cefoxitin 22 (52.38%), followed by cefotaxime at 18 (42.86%). ciprofloxacin, imepenem and ceftazidime had the lowest resistance 4 (9.52%), 5 (11.91%) and 7 (16.67%) respectively. Figure 2 shows a bar plot of the percentages of susceptibility patterns of different drugs under classes of response to E. coli.

Figure 2. Shows a bar plot of the percentages of susceptibility patterns of different drugs under classes of response to E. coli in both strata.

IMP-imipenem; CAZ-ceftazidime; CXT-cefoxitin; CTX-cefotaxime; CIP-ciprofloxacin.

Antimicrobial susceptibility from drain swabs

A total of 16 isolates from drain swabs were tested for antimicrobial susceptibility. Out of these antimicrobials, 5 (61.25%) were susceptible to the microbial, 5 (23.75%) were intermediate and 5 (15%) were resistant. The highest resistance was shown to be cefotaxime 6 (33.34%), followed by cefoxitin at 4 (23.34%), while imipenem and ceftazidime were the least resistant at 2 (10%) respectively. ciprofloxacin was 0% resistant to the isolates tested. Table 2 shows antimicrobial susceptibility patterns from drain swabs in both strata. Out of the five drugs ceftazidime showed the highest susceptibility at 13 (85%) while imipenem followed at 13 (81.67%) respectively. ciprofloxacin was the highest in intermediate at 8 (46.67%) while imipenem and cefoxitin were the least intermediate at 2 (13.34%). Figure 3 shows antimicrobial susceptibility pattern from drain swabs.

Table 2. Antimicrobial susceptibility frequencies from drain swabs in both strata.

Antimicrobial	Sensitive	Intermediate	Resistant
Imipenem	13(81.67%)	2(13.34%)	1(10%)
Ceftazidime	13(85%)	2(20%)	1(10%)
Cefoxitin	10(63.34%)	2(13.34%)	4(23.34%)
Cefotaxime	5(35%)	5(31.67%)	6(33.34%)
Ciprofloxacin	8(53.33%)	8(46.67%)	0(0.00%)

Figure 3. Shows antimicrobial susceptibility pattern from drain swabs in both the strata.

IMP-imipenem; CAZ-ceftazidime; CXT-cefoxitin; CTX-cefotaxime; CIP-ciprofloxacin.

Antimicrobial susceptibility from soil isolates from both strata

A total of 23 samples of soil were tested for antimicrobial sensitivity using diffusion disc method of the five antimicrobials of which imepenem resistant were 4 (17.39%), 8 (34.78%) intermediate while 11 (48.83%) susceptible. Out of the five antimicrobials used in this study in ceftazidime resistant were 6 (26.09%), intermediate 5 (21.74%), susceptibility 12 (52.17%), cefoxitin resistant were 15 (65.22%), intermediate 5 (21.71%), susceptible 3 (13.04%), cefotaxime resistant were 9 (9.13%), intermediate 5 (21.74%), susceptible 9 (39.13%) and ciprofloxacin resistant were 4 (17.39%), intermediate 4 (17.39%), susceptible 15 (65. 22%). Table 3 shows E. coli antimicrobials susceptibility drug patterns from soil samples in both strata. In both strata ciprofloxacin showed the highest susceptibility at 65.22%, followed by ceftazidime at 52.17%, while cefoxitin showed the least susceptibility. Imepenem showed the highest intermediate of all the drugs. Cefoxitin showed the highest resistance. Figure 4 shows the comparison in susceptibility patterns of the samples.

Table 3. E. coli antimicrobials susceptibility drug patterns from soil samples in both strata.

	Sensitive	Intermediate	Resistant	Total	Sensitive	Intermediate	Resistant
Strata 1
Imipenem	7	2	0	9	77.78%	22.22%	0.00%
Ceftazidime	5	3	1	9	55.56%	33.33%	11.11%
Ceroxitin	2	1	6	9	22.22%	11.11%	66.67%
Cefotaxime	5	1	3	9	55.56%	11.11%	33.33%
Ciprofloxacin	6	2	1	9	66.67%	22.22%	11.11%
Strata 2
Imipenem	4	6	4	14	28.57%	42.86%	28.57%
Ceftazidime	7	2	5	14	50.00%	14.29%	35.71%
Ceroxitin	1	4	9	14	7.14%	28.57%	64.29%
Cefotaxime	4	4	6	14	28.57%	28.57%	42.86%
Ciprofloxacin	9	2	3	14	64.29%	14.29%	21.43%

Figure 4. Shows the comparison in susceptibility patterns of the soil samples in both strata.

IMP-imipenem; CAZ-ceftazidime; CXT-cefoxitin; CTX-cefotaxime; CIP-ciprofloxacin.

In the first strata, imepenem at 9 (77.78%) showed the highest susceptibility, followed by ciprofloxacin at 6 (66.67%) and cefoxitin was the least sensitive at 22.22%. Ceftazidime showed the highest intermediate at 33.33% while cefoxitin and cefotaxime were least intermediate. Cefoxitin showed the highest resistance while imepenem showed no resistant. In strata two ciprofloxacin 64.29% showed the highest susceptibility, followed by ceftazidime 50%. Cefoxitin showed highest resistance at 64.29%, followed by cefotaxime at 42.86%. Imepenem showed the highest intermediate of all the drugs.

Antimicrobial susceptibility for water samples

Out of the three water samples analyzed it was observed that, ceftazidime and Ciprofloxacin showed 100% sensitivity while imipenem showed the least sensitivity Figure 5 shows the comparisons in % between the drugs. The highest resistance was observed in both cefoxitin and cefotaxime at 100%. Imipenem was the most intermediate at 66.67%. Table 4 shows E. coli antimicrobials susceptibility drug patterns from water samples from strata 1 and 2.

Figure 5. Shows the comparisons in percentages between the drugs for water samples.

IMP-imipenem; CAZ-ceftazidime; CXT-cefoxitin; CTX-cefotaxime; CIP-ciprofloxacin.

Table 4. E. coli antimicrobials susceptibility of water samples.

Water	Sensitive	Intermediate	Resistant	Total	Sensitive	Intermediate	Resistant
Imipenem	1	2	0	3	33%	66.67%	0%
Ceftazidime	3	0	0	3	100%	0%	0%
Cefoxitin	0	0	3	3	0%	0%	100%
Cefotaxime	0	0	3	3	0%	0%	100%
Ciprofloxacin	3	0	0	3	100%	0%	0

Statistical comparison of resistance of the drugs using Kruskal-Wallis test and Wilcoxon Signed-Rank test

The resistance from this study was statistically significant since the p value=0.0005275354994284686 and the statistic=19.87938408896494. The p-value is less than 0.05, and so we reject the null hypothesis. This means that the resistance is not the same across the different drugs. To know which drug is more resistant, the Wilcoxon Signed-Rank test was used. This study found that cefoxitin and cefotaxime are statistically significant with a p-value 0.0156 which means they have highest resistance among the rest of the drugs. Table 5 shows p-values between compared drugs.

Table 5. p-values between compared drugs.

p-value	Ceftazidime	Cefoxitin	Cefotaxime	Ciprofloxacin
Imipenem	0.1088	0.0156	0.0156	0.7150
Ceftazidime		0.0156	0.0156	0.0679
Cefoxitin			0.2249	0.0156
Cefotaxime				0.0156

Table 6. Means and standard errors.

Drug	Mean±SE
Imipenem	23.809524±5.460448^a
Ceftazidime	19.440476±9.395252^a
Cefoxitin	9.333333±9.030211^b
Cefotaxime	23.452381±4.695007^b
Ciprofloxacin	21.547619±7.012888^a

Imipenem, ceftazidime and ciprofloxacin are not significant to this study since the p value is greater than p>0.05. This p-value correlates to what was found in a study conducted by¹⁴ who recorded a p-value of 0.36 towards E. coli.

Statistical analysis summary using plot box. Figure 6 shows a box plot showing summary of descriptive statistics of the means and standard errors of the antimicrobials.

Figure 6. Shows a box plot showing a summary of descriptive statistics of the means and standard errors of the individual drugs used.

Statistical comparison of sensitivity of the drugs using Kruskal-Wallis test and Wilcoxon Signed-Rank test

Sensitivity from this study was significant to the study since the p value=0.01171770477419787 between the strata. This means that the sensitivity was not the same across the different drugs. To know which drug is more sensitive, the Wilcoxon Signed-Rank test was performed. It was observed that, ciprofloxacin, ceftazidime and imipenem were the most sensitive drug with a p-value>0.05.

Table 7 shows the p-values of the antimicrobials in the study.

Table 7. p-values of the antimicrobials.

p-value	Ceftazidime	Cefoxitin	Cefotaxime	Ciprofloxcin
Imipenem	0.4630	0.0156	0.0277	0.9375
Ceftazidime		0.0156	0.0260	0.3454
Cefoxitin			0.9165	0.1158
Cefotaxime				0.0156

Discussion

Antimicrobial resistance patterns of E. coli from the study area

This study reported a range of multidrug resistance to E. coli from all the samples analyzed. Therefore, there is high chance that E. coli isolated from this study area emerges from the surrounding poor unhygienic conditions and inadequate sanitation facilities from the residents. This findings agrees with a study on contamination of street food in Burkina Faso that enteric organisms emerge from cross contamination.¹⁵ The same observation was recorded by.¹⁶ A study conducted on antimicrobial profile in Juja and Kibera found cefotaxime, ceftazidime and ciprofloxacin recorded a greater than 30% of antimicrobial resistance¹⁷ this result is much lower than the one reported in the current study that recorded 25% increase. A study conducted by¹⁸ observed that this increase in resistance is due to use in antibiotics in the treatment of diseases associated with poor unhygienic conditions. This study found the highest resistance on soil where it was it was noted that cefoxitin 65.22% an indication that soil was contaminated in this area. These findings correlate with study on urban informal settlement on antimicrobial resistance on the environment. It was noted from this study that less attention is being given on this contamination and pose a great risk to antimicrobial resistance.¹⁹ Another study noted that soil is a hotspot carrier of resistant genes.²⁰

The current study recorded 34% towards cefotaxime, imepenem10% and zero resistance to Ciprofloxacin. In a similar study,²¹ recorded 0% resistance to Ciprofloxacin and 1.68% to imipenem and 8.94% cefotaxime. This finding on cefotaxime and imepenem is much lower than the ones from the current study. However, both studies recorded 0% to ciprofloxacin. According to Ref. 22 multidrug resistance to E. coli was noted on cefotaxime at 79.7% resistance. A related study²³ recorded 93% resistance to E. coli. The current study recorded a lower figure of 42.86% resistance to cefotaxime.

The current study showed the least resistance towards ceftazidime (16.67%) which is much lower that the resistance obtained from²⁴ 100%.

Antimicrobial resistance from water samples

The current study showed 100% resistance to water samples analyzed during the study. This resistance is a likely indication that there is high contamination of wastewater that is in return used for home use by the residents. The current study only focused on river water samples passing through the study area and not water samples from the source area. This calls for a study in order to determine if there is contamination. The findings from the current study was higher by 20% from a related study conducted by Ref. 25 on antidrug resistance on Indian rivers. A study done by Ref. 26 while investigating resistance from water found that ceftazidime and ciprofloxacin had almost the same resistance; 1.7% and 1.8% respectively. These findings are higher than the current study which recorded 0% resistance on the drugs. According to Ref. 27, E. coli in wastewater plants was 60% resistant towards ciprofloxacin, which was higher than the current study at 0% resistance.

Conclusion

Antimicrobial resistance noted from this study will result in an increase of infections caused by treatment failure hence, high mortality rates.

Recommendations

Proper sanitation and hygiene awareness practices should be provided through education to the residents of this area. In the future, molecular methods should be used to look in more detail at the resistance genotype of the isolate from the study.

Author’s contribution

JO: Developed the concept, wrote the project proposal, collected the research data, analyzed the data, and wrote the thesis.

KG: Corrected the concept, provided necessary guidance, and corrections at the proposal writing, data analysis, and thesis writing.

NM: Corrected the concept, provided necessary guidance, and corrections at the proposal writing, data analysis, and thesis writing

Data availability

Underlying data

Figshare: EVALUATION OF ANTIMICROBIAL SUSCEPTIBILITY OF ESCHERICHIA COLI ISOLATED FROM CONTAMINATED AREAS OF MAJENGO SLUM IN MERU COUNTY, KENYA. https://doi.org/10.6084/m9.figshare.20325345.²⁸ This project contains the following underlying data:

• my data.xlsx (The data from this study represents data using measures of central tendency and the findings in percentages and bar graphs and statistical analysis involved using Kruskal Wallis and Wilcoxon from SPSS software.)

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

Acknowledgements

Many thanks to almighty God for enabling me throughout in doing this work. I thank everyone who supported me throughout this journey. In a special way I would like to thank my supervisors Dr. Kennedy Gachoka and Dr. Naomi K. Mutea for believing in me and guidance he has given me throughout this journey of research further with their authority allowed me to publish this work. I appreciate my mentor Dorothy Kagendo for guiding me in my work till the end.

I am very grateful to Sanitation Research Institute Director Dr Joy Riungu for the support in terms of laboratory reagents for carrying out the practical research.

I also offer my appreciations to chairman school of biological sciences for acceptance to use the biological laboratory in carrying out my study.

Many sincere appreciations to Mr. Sigido Mbogoh laboratory Technician Biological lab for laboratory for providing me with equipment and space to carry out the sample processing in the laboratory. Lastly I thank Mr Anampiu Kirimi for the guidance in carry out microbiology procedures during the study.

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11. Zelalem A, Abegaz K, Kebede A, et al.: Investigation on Salmonella enterica, Escherichia coli, and coliforms in beef from Ethiopian abattoirs: A potential risk of meat safety. Food Sci. Nutr. 2022(December 2021): 1–11.
12. monicah cheesbrough: monicah cheesbrough part 2.2006; 137–140 p.
13. Kahlmeter G, Giske CG, Kirn TJ, et al.: Point-counterpoint: Differences between the European Committee on Antimicrobial susceptibility testing and Clinical and Laboratory standards institute recommendations for reporting antimicrobial susceptibility results. J. Clin. Microbiol. 2019; 57(9). PubMed Abstract | Publisher Full Text
14. Maina J: Multiple-drug resistances gram-negative bacterial strains recoverable from food and environmental samples in kibera informal settlements Master of Science (Medical Microbiology) Jomo Kenyatta University of.2020.
15. Nikiema MEM, De La Gandara MP, Compaore KAM, et al.: Contamination of street food with multidrugresistant Salmonella, in Ouagadougou, Burkina Faso. PLoS One. 2021; 16(6 June 2021): 1–13. Publisher Full Text
16. Tahri L, Hafiane FZ, Fekhaoui M: Prevalence and antibiotic resistance of the Escherichia coli in the groundwater (Tadla-Morocco). Groundw. Sustain. Dev. 2021 May 1; 13: 100572. Publisher Full Text
17. Maina J, Ndung P, Muigai A, et al.: Antimicrobial Profiles of Selected Gram-Negative Bacteria Recoverable from Sewage and Sludge from Juja and Kibera Informal Settlements of the Larger Nairobi Metropolis.2019; 507–524.
18. Fleece ME, Nshama R, Walongo T, et al.: Longitudinal assessment of antibiotic resistance in fecal Escherichia coli in Tanzanian Children. Am. J. Trop. Med. Hyg. 2019; 100(5): 1110–1114. PubMed Abstract | Publisher Full Text
19. Iskandar K, Molinier L, Hallit S, et al.: Drivers of antibiotic resistance transmission in low-and middle-income countries from a “one health” perspective—a review. Antibiotics. 2020; 9(7): 1–23. Publisher Full Text
20. Samreen AI, Malak HA, Abulreesh HH: Environmental antimicrobial resistance and its drivers: a potential threat to public health. J Glob Antimicrob Resist. 2021; 27: 101–111. PubMed Abstract | Publisher Full Text
21. Divyashree M, Vijaya Kumar D, Ballamoole KK, et al.: Occurrence of antibiotic resistance among Gram negative bacteria isolated from effluents of fish processing plants in and around Mangalore. Int. J. Environ. Health Res. 2020; 30(6): 653–660.
22. Sonola VS, Katakweba AS, Misinzo G, et al.: Occurrence of Multi-Drug-Resistant Escherichia coli in. Antibiotics. 2021; 10(1137): 1–12.
23. Hope D, Ampaire L, Oyet C, et al.: Antimicrobial resistance in pathogenic aerobic bacteria causing surgical site infections in Mbarara regional referral hospital, Southwestern Uganda. Sci. Rep. 2019; 9(1): 1–10.
24. Ngene AC, Ohaegbu CG, Awom IE, et al.: High prevalence of multidrug resistant enterobacteriaceae isolated from wastewater and soil in Jos Metropolis, Plateau State, Nigeria.2021; 13(December): 22–29.
25. Bilal H, Khan MN, Rehman T, et al.: Antibiotic resistance in Pakistan: a systematic review of past decade. BMC Infect. Dis. 2021; 21(1): 1–19.
26. Mukami SN: phenotypic and molecular characterization of pathotypes, and antimicrobial resistance profiles of escherichia coli from food, water and livestock in selected informal settlements in nairobi.2021.
27. Praveenkumarreddy Y, Akiba M, Guruge KS, et al.: Occurrence of antimicrobial-resistant escherichia coli in sewage treatment plants of south India. J. Water Sanit. Hyg. Dev. 2020; 10(1): 48–55.
28. Ombuya J, Kennedy G, Naomi M: Evaluation of antimicrobial susceptibility of escherichia coli isolated from contaminated areas of majengo slum in meru county, kenya. figshare. [Dataset].2022. Publisher Full Text

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Version 3

VERSION 3 PUBLISHED 04 Oct 2022

Author details Author details

Jared Ombuya
Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Kennedy Gachoka
Roles: Supervision

Naomi Mutea
Roles: Supervision

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Article Versions (3)

version 3

Revised

Published: 12 Apr 2023, 11:1133

https://doi.org/10.12688/f1000research.124121.3

version 2

Revised

Published: 26 Jan 2023, 11:1133

https://doi.org/10.12688/f1000research.124121.2

version 1

Published: 04 Oct 2022, 11:1133

https://doi.org/10.12688/f1000research.124121.1

© 2022 Ombuya J 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.

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Ombuya J, Gachoka K and Mutea N. Evaluation of antimicrobial susceptibility of Escherichia coli isolated from contaminated areas of Majengo slum in Meru County, Kenya [version 1; peer review: awaiting peer review]. F1000Research 2022, 11:1133 (https://doi.org/10.12688/f1000research.124121.1)

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Version 1 04 Oct 22

Eman S. Ibrahim, National Research Centre, Dokki, Egypt
Benno H Ter Kuile, University of Amsterdam, Amsterdam, The Netherlands
Md. Abdus Sobur, Bangladesh Agricultural University, Mymensingh, Bangladesh; Provita Group, Mymensingh, Bangladesh
Abdennaceur Hassen, Research Center of Wastewater technologies, Technopark Borj Cedria, Tunisia

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4 Views

12 Sep 2024 | for Version 3

Abdennaceur Hassen, Research Center of Wastewater technologies, Technopark Borj Cedria, Soliman, Tunisia

4 Views Cite this report Responses(2)

Approved With Reservations

Main comments

As a whole, I find the article very interesting since it discusses a relevant topic, bacterial multidrug resistance, in a developed African country like Kenya, and a specific situation and environment. The study aimed to determine and provide crucial insights characterizing antimicrobial-resistant strains of Escherichia coli isolated from sanitation environments in the Majengo slum in Meru County, Kenya.

This statement is clear and concise. This subject is of considerable relevance in light of the importance of infections by antimicrobial-resistant Escherichia coli strains, such as enteropathogenic and enterotoxigenic strains. These strains of Escherichia coli have been reported worldwide as a major cause of death, especially among young children in low- and middle-income countries, like most African countries. This major cause of death has been exacerbated by antimicrobial misuse, over-the-counter availability, and poor sanitation, especially in low-income areas.

Additionally, I always recommend adding a graphical abstract to aid in understanding the study. The graphical abstract, sometimes not required and requested by the journal, gives added value. This helps the reader better understand the reality of the work.

On the other hand, the quality and presentation of the graphical abstract, in my opinion, is an excellent indicator concerning the research team. This is because it indicates the validity of their work, its seriousness, and its scientific rigor.

The paper is relatively short. It will be a relatively short paper. The manuscript is well-written in English and sometimes requires corrections and intervention. It would be helpful if you could provide me with a Doc manuscript so that I can assist the authors.

I summarize my main comments about this work:

Abstract
I find the abstract well-written, expressive, well-structured, and well-extended. I recommend removing Multidrug resistance since it has the same meaning as “antimicrobial resistance”, and adding “E. Isolates" instead of just “E. coli” and “sanitation environments”. These two keywords should be more indicative and precise concerning this investigation.

Introduction
A clear introduction to a topic that takes less than a page to introduce and explain the subject. It is nicely presented and properly defended which makes the topic and investigation useful. Furthermore, this introduction demonstrated the high relevance of the topic. I recommend some extension of this introduction considering the importance and abundance of the bibliography on this specific theme in the scientific literature. Of nearly all references cited, 27 references were not within the standards recommended by scientific journals of around 40 references; and once there is a small extension in the introduction, the number of references automatically increases a little. These references were almost all very recent since around 85% of the references were from 2021.

After the introduction, the main goals of this study are thoroughly introduced, well-cited, and structured. These goals are clearly expressed and written.

Materials and methods
All methodologies were well documented and described with all necessary monitoring, including microbiological and statistical tests. Although some corrections are needed to confirm the seriousness of the investigation. Regarding the sampling modality, it requires more explanation in terms of text restructuring. Gram staining technique description is not necessary since this technique is well-known and common.

Results and discussion
Results queues and text citations are useful and consistent. All results are well-cited, clearly explained, and defended. Concerning this defense, I noticed that the authors cited some very recent references beyond 2021 when defending their results.

Figures and tables
Although the illustrations are clear, clearly captioned, and well-made; however, Table 6 needs additional captions to aid in understanding and signifying the obtained values, ...etc.

Conclusion
As a conclusion, I think it is too short, so I think it needs some extension.

Decision
The work is well done, and consistent and deserves publication in a future issue with a correction. I mean English writing mainly. It is perfectly within the journal's scope.

Last, and for all the reasons mentioned above, I recommend the indexing of this work with a minor correction.

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?

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?

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Économie de l'eau, Hydrologie environnementale, Microbiologie, Antibiorésistance, Écologie environnementale et moléculaire, Écotoxicologie Processus de traitement de l’eau et de Filtration. Certification, normalisation et accréditation.

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4 Views

19 Jun 2023 | for Version 3

Md. Abdus Sobur, Microbiology and Hygiene, Bangladesh Agricultural University, Mymensingh, Mymensingh Division, Bangladesh; Poultry Diagnostic Lab, Provita Group, Mymensingh, Mymensingh Division, Bangladesh

4 Views Cite this report Responses(0)

Not Approved

The manuscript entitled "Evaluation of antimicrobial susceptibility of Escherichia coli isolated from contaminated areas of Majengo slum in Meru County, Kenya" has presented the prevalence of antibiotic resistance E. coli from soil, water and drains swabs in a poor sanitation area in Kenya. The topic has been chosen by the Authors has importance in One Health view point. However, the study design has some serous faults particularly, in statistical analysis. In addition, the whole manuscript requires major revisions in terms of scientific writing and sentence corrections. Over all the manuscript is not at the stage of indexing. Due to no line number, line wise correction is not possible. I have written the report based in section.

Abstract:
The Authors can write as E. coli after first use. The result section should be rewritten. The authors have mentioned the sensitive prevalence first, and then intermediate finally, the resistance pattern. They should write the resistance pattern first and then sensitive pattern if they feel sensitive pattern is important. No need to mention the intermediate pattern in abstract. To me, only resistance pattern is enough for abstract section. In conclusion, there is no indication in results and methods of abstract to say E. col as pathogenic and even no clue in the whole manuscript. What is the basis of this finding?

Keywords:
Why did the Authors use multidrug resistance as keywords when they have not identified multidrug resistance in their study?

Introduction:
As the background and justification of the study "introduction" section is not well written. The Authors have studied on E. coli in a particular area and they have mentioned the area as "contaminated" in the title. However, they have not indicated any linkage to be the area as contaminated. In addition, they have not described the area, people live there and their occupation which are important for E. coli contamination as well as antimicrobial resistance (AMR) relation. This information would help to formulate the justification of the study. It was mainly to convince the reader why the area is contaminated with AMR E. coli. Unfortunately, the justification of the study is absent here. Furthermore, there is no aim mentioned as well.

Methods:

Sample size determination:
Seems the reference (7) is not correct. On top of that, the Authors have not mentioned the meaning of the values they used in the formula. In addition, as per the equation no. of samples will be 246 not 61. The calculation is correct.

Sample processing:
How much tap water was collected? The Authors collected 500 ml river water in 500 ml bottle that is not a good practice. The bottle should be larger than the collection amount to prevent contamination.

Samples preparation prior to the inoculation:
Although the Authors are saying sample preparation prior to inoculation however, they have mentioned the culture procedures here as well. And they have written the microbial techniques separately bellow. No need to write separately as already mentioned. It was best to identify the E. coli by molecular technique.

Antimicrobial susceptibility testing:
Five antibiotics were selected among them, three were cephalosporin, one carbapenem (these four are B-lactams) and one Fluoroquinolones. Therefore, categorically only two types of antibiotics was selected. For this selection, it was best to identify ESBL among the E. coli isolates.

Data analysis:
Before doing any statistical analysis, maintaining minimum sample number (from population) should be followed otherwise statistical analysis get lower importance. In addition, comparing among antibiotics in this study is not useful as most of the antibiotics fall in the same group. Comparing among group will not be useful as well as one B-lactams have four antibiotics and Fluoroquinolones has only one antibiotics. Therefore, this analysis does not add any value to this study.

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

No
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?

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

No
Are all the source data underlying the results available to ensure full reproducibility?

No source data required
Are the conclusions drawn adequately supported by the results?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Antibiotic Resistance, Virulence, Veterinary Microbiology, Food Microbiology, Poultry Health, One Health

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Reviewer Report

8 Views

13 Jun 2023 | for Version 3

Benno H Ter Kuile, Swammerdam Institute of Life Sciences, University of Amsterdam, Amsterdam, North Holland, The Netherlands

8 Views Cite this report Responses(0)

Not Approved

This manuscript describes the level of resistance of Escherichia coli isolated from soil, water and drains swabs in a poor sanitation area in Kenya. The data are of interest as information about antimicrobial resistance in such environment is essential for a global OneHealth approach. While the data collection has been performed correctly, the data processing is substandard. A considerable revision of the results section will be needed.

The application of statistics is incorrect in many instances, but luckily often not required. I have looked up reference 7 on the sample size, but I could not find the equation the authors use. However, the final sample size (41 E. coli positive samples) is on the low side, but that does not invalidate the study. Tables 5 and 7 and figure 6 are useless, because antibiotics are not experimental groups, so the p-values are meaningless.

Throughout the study numbers are mentioned that are either incomprehensible, or don’t add up. In table 2, first two lines, the same numbers do not have the same percentages and they don’t add up to 100. Line 3: if 10 = 63.34%, then 2 cannot be 13.34 and if 2 is 13.34, then 4 cannot be 23.34. This is only one example, but throughout the manuscript numbers are flawed, don’t add up and simply don’t make sense.

A sentence like “Out of these antimicrobials, 5 (50.48%) were susceptible, 5 (22.86%) were intermediate and 5 (26.67%) were resistant.” is impossible to interpret. Antimicrobials are not susceptible, intermediate or resistant; microbes are or are not.

One final example: throughout the text the need for monitoring is stressed as a panacea against resistance. Monitoring may be helpful to find resistance hotspots and identify driving factors selecting for and spreading resistance, it will never be enough to solve the problem.

In conclusion, the data are useful, but the text is to be improved greatly for this manuscript to become a good article.

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

No
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?

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

No
Are all the source data underlying the results available to ensure full reproducibility?

No source data required
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Antimicrobial resistance

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4 Views

28 Apr 2023 | for Version 3

Eman S. Ibrahim, Department of Microbiology and Immunology, National Research Centre, Dokki, Egypt

4 Views Cite this report Responses(0)

Approved

The authors had covered all the amends required and there is no further comments to make.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Microbiology (bacteriology), Molecular biology, Nanotechnology

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22 Views

17 Feb 2023 | for Version 2

Eman S. Ibrahim, Department of Microbiology and Immunology, National Research Centre, Dokki, Egypt

22 Views Cite this report Responses(1)

Approved With Reservations

Dear respected colleagues,

I have read the manuscript entitled ‘Evaluation of antimicrobial susceptibility of Escherichia coli isolated from contaminated areas of Majengo slum in Meru County, Kenya ’ thoroughly.

The manuscript is discussing an interesting topic; Which is the danger of antibiotic resistance concerning E.coli and the linkage between antibiotic resistance and poor hygienic condition in rural areas and misuse of antibiotic treatment which in turn make it necessary to make antibiogram for choosing drug of choice before beginning treatment scheme. The work is clearly and accurately presented and cite the current literature.

The work is technically sound but the study design is partially appropriate as the study here made screening against only five antibiotic disc which is not enough to build on it a conclusion. Can you explain why was this antibiotic chosen over others?
Also why was genotypic identification of antibiotic resistant genes not taken?

In the conclusions found in the abstract section you mentioned that the isolated E.coli is pathogenic. What is your practical support for this information as you didn't make detection for virulence genes? So it is preferable to remove the word pathogenic.
The methods and statistical analysis and it's interpretation as well as result is well presented.

In discussion section concerning reference 15 this paper was discussing Salmonella isolates how are you comparing your result with this paper? It is preferable to remove it.

Conclusion section should include future scope of the study.

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?

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

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Microbiology (bacteriology), Molecular biology, Nanotechnology

Respond to this report

Responses (1)

Author Response

12 Apr 2023

jared ombuya, Meru University of Science and Technology, Meru, Kenya

The reason why I concluded that the organism is pathogenic is that I did serotyping of E coli strains and one strain was positive for the test

The reason for using the 5 antibiotics is that those are the commonly prescribed drugs in the health centers in the study area

Genotyping was not done as that could have quite expensive for me but that's the work to be done in my next level of study

The reference included for salmonella was mistakenly included hence will not appear in revised version

Conclusion will be amended accordingly as well in the revised version

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Competing Interests

No competing interests were disclosed.

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] 1. Health P: Future Emerging Issues in waterborne diseases and microbial agents.2012; 34–36.

[2] 2. Pedley S, Pond K: Emerging issues in water and infectious disease. World Health Organization;2003.

[3] 3. ReACT: Addressing the antibiotic resistance threat-the role of water, sanitation and hygiene.2018; 1–4.

[4] 4. Town G, Mohsin S, Aziz Q, et al.: Original article Burden of antibiotic resistance among children with typhoid in.2022; 3(1): 81–91.

[5] 5. Iseghohi MG, FA K: Escherichia Coli Encoding Extended-Spectrum Beta-Lactamases Isolated from Diarrheic Patients in Minna, Nigeria. Int. J. Biotechnol. 2021; 10(2): 52–68.

[6] 6. Haenni M, Dagot C, Chesneau O, et al.: Environmental contamination in a high-income country (France) by antibiotics, antibiotic-resistant bacteria, and antibiotic resistance genes: Status and possible causes. Environ. Int. 2022; 159(December 2021): 107047. PubMed Abstract | Publisher Full Text

[7] 7. Cochran WG: Cochran_1977_Sampling_Techniques__Third_Edition.pdf.1977; p. 448.

[8] 8. Amoafo OY, Malekar V, Jones E, et al.: Antibiotic resistance and phylogenetic profiling of Escherichia coli from dairy farm soils; organic versus conventional systems. Curr. Res. Microb. Sci. 2022; 3(July 2021): 100088.

[9] 9. Yeboah SIIK, Antwi-Agyei P, Domfeh MK: Drinking water quality and health risk assessment of intake and point-of-use water sources in Tano North Municipality, Ghana. J. Water Sanit. Hyg. Dev. 2022; 12(2): 157–167. Publisher Full Text

[10] 10. Ghabban H, Alnomasy SF, Almohammed H, et al.: Antibacterial, Cytotoxic, and Cellular Mechanisms of Green Synthesized Silver Nanoparticles against Some Cariogenic Bacteria (Streptococcus mutans and Actinomyces viscosus). J. Nanomater. 2022; 2022: 1–8. Publisher Full Text

[11] 11. Zelalem A, Abegaz K, Kebede A, et al.: Investigation on Salmonella enterica, Escherichia coli, and coliforms in beef from Ethiopian abattoirs: A potential risk of meat safety. Food Sci. Nutr. 2022(December 2021): 1–11.

[12] 12. monicah cheesbrough: monicah cheesbrough part 2.2006; 137–140 p.

[13] 13. Kahlmeter G, Giske CG, Kirn TJ, et al.: Point-counterpoint: Differences between the European Committee on Antimicrobial susceptibility testing and Clinical and Laboratory standards institute recommendations for reporting antimicrobial susceptibility results. J. Clin. Microbiol. 2019; 57(9). PubMed Abstract | Publisher Full Text

[14] 14. Maina J: Multiple-drug resistances gram-negative bacterial strains recoverable from food and environmental samples in kibera informal settlements Master of Science (Medical Microbiology) Jomo Kenyatta University of.2020.

[15] 15. Nikiema MEM, De La Gandara MP, Compaore KAM, et al.: Contamination of street food with multidrugresistant Salmonella, in Ouagadougou, Burkina Faso. PLoS One. 2021; 16(6 June 2021): 1–13. Publisher Full Text

[16] 16. Tahri L, Hafiane FZ, Fekhaoui M: Prevalence and antibiotic resistance of the Escherichia coli in the groundwater (Tadla-Morocco). Groundw. Sustain. Dev. 2021 May 1; 13: 100572. Publisher Full Text

[17] 17. Maina J, Ndung P, Muigai A, et al.: Antimicrobial Profiles of Selected Gram-Negative Bacteria Recoverable from Sewage and Sludge from Juja and Kibera Informal Settlements of the Larger Nairobi Metropolis.2019; 507–524.

[18] 18. Fleece ME, Nshama R, Walongo T, et al.: Longitudinal assessment of antibiotic resistance in fecal Escherichia coli in Tanzanian Children. Am. J. Trop. Med. Hyg. 2019; 100(5): 1110–1114. PubMed Abstract | Publisher Full Text

[19] 19. Iskandar K, Molinier L, Hallit S, et al.: Drivers of antibiotic resistance transmission in low-and middle-income countries from a “one health” perspective—a review. Antibiotics. 2020; 9(7): 1–23. Publisher Full Text

[20] 20. Samreen AI, Malak HA, Abulreesh HH: Environmental antimicrobial resistance and its drivers: a potential threat to public health. J Glob Antimicrob Resist. 2021; 27: 101–111. PubMed Abstract | Publisher Full Text

[21] 21. Divyashree M, Vijaya Kumar D, Ballamoole KK, et al.: Occurrence of antibiotic resistance among Gram negative bacteria isolated from effluents of fish processing plants in and around Mangalore. Int. J. Environ. Health Res. 2020; 30(6): 653–660.

[22] 22. Sonola VS, Katakweba AS, Misinzo G, et al.: Occurrence of Multi-Drug-Resistant Escherichia coli in. Antibiotics. 2021; 10(1137): 1–12.

[23] 23. Hope D, Ampaire L, Oyet C, et al.: Antimicrobial resistance in pathogenic aerobic bacteria causing surgical site infections in Mbarara regional referral hospital, Southwestern Uganda. Sci. Rep. 2019; 9(1): 1–10.

[24] 24. Ngene AC, Ohaegbu CG, Awom IE, et al.: High prevalence of multidrug resistant enterobacteriaceae isolated from wastewater and soil in Jos Metropolis, Plateau State, Nigeria.2021; 13(December): 22–29.

[25] 25. Bilal H, Khan MN, Rehman T, et al.: Antibiotic resistance in Pakistan: a systematic review of past decade. BMC Infect. Dis. 2021; 21(1): 1–19.

[26] 26. Mukami SN: phenotypic and molecular characterization of pathotypes, and antimicrobial resistance profiles of escherichia coli from food, water and livestock in selected informal settlements in nairobi.2021.

[27] 27. Praveenkumarreddy Y, Akiba M, Guruge KS, et al.: Occurrence of antimicrobial-resistant escherichia coli in sewage treatment plants of south India. J. Water Sanit. Hyg. Dev. 2020; 10(1): 48–55.

[28] 28. Ombuya J, Kennedy G, Naomi M: Evaluation of antimicrobial susceptibility of escherichia coli isolated from contaminated areas of majengo slum in meru county, kenya. figshare. [Dataset].2022. Publisher Full Text

Evaluation of antimicrobial susceptibility of Escherichia coli isolated from contaminated areas of Majengo slum in Meru County, Kenya

Abstract

Keywords

Introduction

Methods

Ethical considerations

Study area

Study design and population

Sampling procedure

Figure 1. Shows a map of the sampled areas in the Majengo slum. Maps data ©2022: Google, ©2022 CNES/Airbus, Maxar Technologies.

Sample size determination

Sample processing

Samples preparation prior to the inoculation

Water analysis using most probable number method

Table 1. Water analysis set for untreated and treated water samples.

Microbiological identification of E. coli from the samples

Biochemical identification of E. coli using Tryptone water

Gram staining technique

Antimicrobial susceptibility testing

Data analysis

Results

Antimicrobial susceptibility from both strata

Figure 2. Shows a bar plot of the percentages of susceptibility patterns of different drugs under classes of response to E. coli in both strata.

Antimicrobial susceptibility from drain swabs

Table 2. Antimicrobial susceptibility frequencies from drain swabs in both strata.

Figure 3. Shows antimicrobial susceptibility pattern from drain swabs in both the strata.

Antimicrobial susceptibility from soil isolates from both strata

Table 3. E. coli antimicrobials susceptibility drug patterns from soil samples in both strata.

Figure 4. Shows the comparison in susceptibility patterns of the soil samples in both strata.

Antimicrobial susceptibility for water samples

Figure 5. Shows the comparisons in percentages between the drugs for water samples.

Table 4. E. coli antimicrobials susceptibility of water samples.

Statistical comparison of resistance of the drugs using Kruskal-Wallis test and Wilcoxon Signed-Rank test

Table 5. p-values between compared drugs.

Table 6. Means and standard errors.

Figure 6. Shows a box plot showing a summary of descriptive statistics of the means and standard errors of the individual drugs used.

Statistical comparison of sensitivity of the drugs using Kruskal-Wallis test and Wilcoxon Signed-Rank test

Table 7. p-values of the antimicrobials.

Discussion

Antimicrobial resistance patterns of E. coli from the study area

Antimicrobial resistance from water samples

Conclusion

Recommendations

Author’s contribution

Data availability

Underlying data

Acknowledgements

References

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