Keywords
metagenomic, beer, citizen science, crowdfunding,
metagenomic, beer, citizen science, crowdfunding,
This new version is meant to answer the issues raised in the comments received from referees 1-3 (see also our responses to referees' reports). We added Table 1 and two references. Because the sensitivity of our analysis was changed, some fungal species that were initially described were not relevant anymore and have been removed from the main text and figures. All information related to version 1 is still available in the raw data and original files and figures are on the project GitHub repository.
See the authors' detailed response to the review by Bastian Greshake
See the authors' detailed response to the review by Kristoffer Krogerus
See the authors' detailed response to the review by Matthew L. Bochman
Beer is probably the world’s oldest and most widely consumed alcoholic beverage on the planet, with a worldwide production of nearly 2 billion hectolitres (2·10E11 litres) annually [The Barth Report, Hops 2015/2016], and, as DNA sequencing becomes increasingly cheap, whole genome sequencing and metagenomic analyses are being explored as tools to better understand brewing in particular, and food fermentation in general1. Complex microbial communities influence the wine- and cheesemaking process throughout2,3. Indeed, microbial communities contribute to nutritional and aromatic properties, as well as shelf life of the products. In the case of wine, microorganisms are present in the soil, on the grapes, and in the fermenter, being carried over from the vine to the must to the wine, and there is increasing evidence for the existence of an important microbial contribution to the notion of “terroir” (i.e regional environmental factors that affect the properties of the final product)4–7. One question that remains unanswered is whether there is such a thing as a “terroir” for beer.
Of particular interest is sour beers, such as lambic and gueuze, beverages produced without the controlled addition of known yeast cultivates. Instead, the wort is exposed to ambient air, allowing naturally occurring bacteria and yeasts to start the fermentation and leading to a production that is difficult to standardize. To our knowledge, three initiatives are currently exploring the role of the beer microbiome in the brewing process and how it shapes the characteristics of the final product. Using metagenomic analyses, Kevin Verstrepen and colleagues at KU Leuven, Belgium, study the production of lambic, a traditional Belgian beer produced by spontaneous fermentation [VIB project 35]. Similarly, Matthew Bochman and colleagues at Indiana University, USA, have recently published preliminary results showing how the microbial community evolved over the fermentation process, together with the relative abundance of the organic acids that give sour beer its characteristic taste8,9. Similarly, researchers at the University of Washington, USA, have studied open-fermentation beer and discovered a novel interspecific hybrid yeast10.
To investigate the microbial composition of a collection of commercial beers, we initiated BeerDeCoded in the context of Hackuarium, a Swiss not-for-profit organisation that supports unconventional research projects and promotes the public understanding of science. Members of the Hackuarium community are interested in participatory biology and want to promote interdisciplinary citizen research and innovation outside traditional institutions, using low-cost, simple and accessible technologies. The goal of the BeerDeCoded project is not only to broaden the scientific knowledge about beer, but also to improve the public understanding of issues related to personal genomics, food technology, and their role in society. With the release of this first data set, we built the proof of concept for a targeted metagenome analysis pipeline for beer samples that can be used in high schools, citizen science laboratories, craft breweries or industrial plants.
The content of each beer sample was mixed to homogeneity by inversing the bottle several times. 50 mL were transferred into a conical tube and centrifuged (5000 rpm, 20 min, 4°C) to collect cells and other precipitable material. Pellets were resuspended with 1 mL TE buffer (Tris 10 mM, EDTA 1 mM, pH 8.0) and transferred into 1.5 mL tubes. The samples were centrifuged (10000 rpm, 10 min, 4°C), the supernatant was removed and the pellet stored frozen (-20°C) until future analyses. The ZR Fecal DNA MiniPrep kit (Zymo Research) was used for DNA extraction with minor modifications to the original protocol11. Sludge pellets were used instead of the 50-100 mg of fecal material suggested by the manufacturer..
To ensure the DNA was free from proteins and other contaminants, the absorbance of DNA samples was measured at 230, 260 and 280 nm using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific).
Yeast genomic DNA was amplified using the fungal hypervariable region ITS1 (internal transcribed spacer 1) as previously described11 using the following primers: BITS (5’–CTACCTGCGGARGGATCA–3’) and B58S3 (5’– GAGATCCRTTGYTRAAAGTT–3’). Typical PCR reactions contained 5–100ng of DNA template. Amplicon size (500nt) was verified using gel electrophoresis and with a fragment analyser. ITS amplicons were purified using AM-Pure XP beads following the manufacturer’s instructions (Beckman Coulter). Dual indices and Illumina sequencing adapters were attached using the Nextera XT Index Kit following manufacturer’s instructions (Illumina).
MiSeq sequencing was performed using the MiSeq v3 reagent kit protocol (Illumina). Briefly, the amplified DNA was quantified using a fluorimetric method based on ds-DNA binding dyes (Qubit). Each DNA sample was diluted to 4 nM using 10 mM Tris pH 8.5 and 5 uL of diluted DNA from each library were pooled. In preparation for cluster generation and sequencing, 5 uL of the pooled final library was denatured with 5 uL of freshly diluted 0.2 N NaOH and combined with 30% PhiX control library to serve as an internal control for low-diversity libraries. After loading the samples on the MiSeq, paired 2x 300bp reads were generated and exported as FASTq files.
The curated set of ITS sequences from the Refseq database (Targeted Loci) was used to build an ITS index for the Burrows-Wheeler Aligner (BWA, version 0.7.13)12. The BWA was used with standards parameters to map the paired-end reads of each beer from the fastq files to our ITS index. The BAM files were sorted and indexed using samtools13. A quality control of the BAM files was performed using SAMstat (version 1.5)14. A read quality threshold above 3 (MAPQ score) was applied in order to remove low quality and non-unique mapping reads. Subsequently, the number of ITS per beer and per species were counted and only species with over 10 reads were taken into consideration. Visualization of the results were performed with R (version 3.4.0).
Over the month of June 2015, a total of 124 individuals contributed over 10,000 Euros to a crowdfunding campaign that provided financial resources for the first stage of the BeerDeCoded project. Reaching out to the public through this campaign also enabled crowdsourcing a collection of 120 beer samples from 20 countries. We have subsequently demonstrated that it is possible to extract DNA directly from bottled beer using low cost methodologies, typically available to citizen scientists (see Methods).
The internal transcribed spacer regions (ITS) of fungal species15 were then amplified and, after quality control, 39 samples were sent for DNA sequencing. These 39 commercial beers originated from 5 different countries: 30 were from Switzerland, five from Belgium, two from Italy, one from France and one from Austria. We obtained an average library size of 600K reads (min 350K, max 2400K see Table 1) with more than 99% of reads mapping to the ITS database per sample.
A total of 42 fungal species were identified, 24 of which were present only in a single brew. This high variety of wild yeasts in commercial beers was unexpected (Figure 1 A), with some brews containing traces of up to more than 10 different fungal species (Figure 1 B). The beer in which we measured the highest ITS diversity (19 fungal species) was Waldbier 2014 Schwarzkiefer, an Austrian beer brewed using pine cones collected in local forests. Two other beers contained more than 12 fungal species: La Nébuleuse Cumbres Rijkrallpa (a sour/wild ale beer made with cranberries and the fermented corn “Chicha”) and Chimay Red Cap, a Belgian trappist beer. Using hierarchical clustering, we built a proximity tree of the different beers (Figure 2).
(A) the number of beers containing the species (n=36) occurring in at least two samples. Species (n=52) present in only one sample were excluded for clarity. (B) represents the number of fungal species identified in each of the 39 bottled beers.
We applied the Ward’s method on the Euclidean distance computed on the log10 counts matrix.
Consistent with its widespread use for fermentation, brewer’s yeast (Saccharomyces cerevisiae) was detected in all beer samples, accounting for between 11% (Orval, an ale beer by Belgian Brasserie d’Orval) and 99% (Tempête, an ale from the Swiss brewery Docteur Gab’s) of all sequencing reads. In most samples, S. cerevisiae was present at very high levels (typically 90–97% of reads, Figure 3). More surprisingly, Saccharomyces mikatae, a species used in winemaking16 was also relatively abundant in all samples (0.5–5%). Interestingly, most brews were found to contain low to medium abundance of multiple other yeast species, including Saccharomyces kudriavzevii and Saccharomyces eubayanus (a probable parent of Saccharomyces pastorianus) and Brettanomyces bruxellensis (typically used for the production of the Belgian beers). Non-conventional, as well as wild yeast, such as Saccharomyces cariocanus and Saccharomyces paradoxus, two species closely related to Saccharomyces cerevisiae were also found. Another example is Kazachstania sp., a wild yeast of commonly found in brines17. The presence of this species may be of interest, as it was previously reported that adding the parent Kazachstania servazzi to the brewing process 24 hours before the ale yeast contributed to the production of high level of esters, producing a strong fruity and floral aroma18.
While a continuous process of market consolidation has lead to 5 companies controlling more than half of global beer production, there has been an explosion of craft industries over the past years, especially in Europe and North America. In 1978 there were 89 large industrial breweries in the USA. In 2016, there were 5,301, among them 3,132 small, independent microbreweries (American Brewers Association). There is a parallel with Hackuarium, an independent “craft” science initiative that has branched out from large institutional research institutes and provides an environment that allows scientists to explore topics that are rarely found in academia or industry. What is truly unique is the participation of individuals with no formal science training, and therefore the strong focus on citizen science and communication. With the BeerDeCoded project, we explored the potential of crowdfunding and crowdsourcing in engaging members of the general public in the production of scientific knowledge. We demonstrated that it is possible to execute complex molecular analyses on everyday products using limited resources and technical support from research institutions, and no financial support from traditional funding sources. The resulting dataset contains the ITS profile of 39 bottled beers from five different countries, revealing the low abundance but widespread presence of wild fungal species. It is a proof of concept that sequencing beer metagenomic information can be done, at least partly, with the help of the public. For the current analysis, we relied on high-throughput sequencing technology available to us through a partnership, a technology that may be out of reach for individuals working in non-traditional research environments. In the future, we would like to overcome this limitation, for example by providing a pipeline based on portable sequencing technologies, such as Oxford Nanopore’s minION instrument. Further analyses could also go as far as shedding light on the so-called biological ”dark matter” of the beer ecosystem19,20.
With the costs of DNA sequencing falling dramatically, and with the emergence of portable and user-friendly instrumentation, we believe that it is a favorable time to expand the application of DNA analysis to novel fields, including food and beverage. This industry is starting to explore the potential of genome sequencing to understand the contribution of various species to product characteristics. The sequencing of the full genome of 157 brewing yeast strains was, for example, recently reported21. Metagenomic analyses could also have important implications for the optimization and batch-to-batch reproducibility of the various fermentation processes, as well as quality control, traceability and authentication of the products. One hypothesis that could be investigated further in the future is whether the presence of a specific fungal species can be diagnostic for a unique geographic area. In our data set, the non Saccharomyces yeast that contributes to wine aroma through the production of volatile compounds, Wickerhamomyces anomalus, was found exclusively in five of the brews manufactured in Switzerland. The limited sample size, however, does not allow us to draw a statistically significant conclusion, and it remains to be seen if W. anomalus is present in beers from other locations as well. Due to inherent limitations of DNA sequencing, it is difficult to anticipate whether the microbes identified are likely to be having an impact on the fermentation process. However, based on the identification of strains present in brews with desired characteristics, controlled experiments in which the microbial composition of the brew is altered could allow us to investigate if the presence of specific microorganisms affects flavour22. The origin of each yeast species could also be investigated; i.e. whether they come with the ingredients or from the environment at the production site. Techniques to sample airborne DNA exist23. Furthermore, other protocols could also be used to catalogue plant DNA24, such as malt and hop varieties, and to map the bacterial diversity.
In order to standardize and simplify our pipeline, and facilitate the contribution of new data and their further analysis by individuals not involved in this initial study, we are in the process of developing a BeerDeCoded repository and a Galaxy instance25. This tool will enable any citizen scientist to carry out beer metagenomics and reproduce our analysis. In the meantime, we encourage researchers from other laboratories, microbreweries and citizen laboratories to further explore our data set, and invite them to consider contributing additional data in the future.
The dataset contains the metagenomic profiles for 39 beers. The data was obtained using a targeted approach based on the phylogenetic typing with internal transcribed spacers (ITS) of ribosomal sequences. All methods, quality control, processed tables, metadata and code are accessible at: https://github.com/beerdecoded/Beer_ITS_analysis. The raw data are stored in the SRA database in the bio project PRJNA388541
GR is the co-founder, CTO and a shareholder of SwissDeCode, a company selling point-of-need DNA tests to food manufacturers for food safety and compliance. JS, LH and NR declare no competing interests.
This project was crowdfunded thanks to the support of 124 contributors to the BeerDeCoded campaign that took place in June 2015. For a full list of backers, see the kickstarter project page. Some of these individuals played a role in data collection, as they provided the beer samples of their choice for analysis and participated in DNA extraction workshops.
The authors would like to thank the following people for their invaluable contributions: Vanessa Lorenzo (Hackuarium) and Alex Hantson (nativs.ch) for their help with the crowdfunding campaign; Gabrielle Salanon for her help with sample extraction and analysis; Keith Harshman (Lausanne Genomic Technology Facility, University of Lausanne) and Stéphane Bernard (Debiopharm International) for providing access to the sequencing platform; Onecodex for providing access to its metagenomic analysis tool; Vital-it high-performance computing centre of the Swiss Institute of Bioinformatics (SIB) for providing access to their analysis cluster; UniverCite and InArTiS for hosting the Hackuarium laboratory; Rachel Aronoff (Hackuarium) for her critical revisions of the manuscript; Patrick Roelli (Bioinformatics Core Facility, University of Lausanne) for the review of the code; Bérénice Batut (University of Freiburg) for the development of the Galaxy instance; Yan Amstein and the backers of the crowdfunding campaign for providing beer samples; all members of the Hackuarium community, past and present, for their contribution to such an inspiring environment.
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Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Fungal metagenomics & bioinformatics
References
1. Naumov GI, James SA, Naumova ES, Louis EJ, et al.: Three new species in the Saccharomyces sensu stricto complex: Saccharomyces cariocanus, Saccharomyces kudriavzevii and Saccharomyces mikatae.Int J Syst Evol Microbiol. 2000; 50 Pt 5: 1931-42 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Competing Interests: I also participated in a crowdfunding campaign to use next-gen enunciating to analyze beer samples (https://experiment.com/projects/mapping-the-sour-beer-microbiome).
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Are the datasets clearly presented in a useable and accessible format?
Yes
Competing Interests: No competing interests were disclosed.
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Are the datasets clearly presented in a useable and accessible format?
Yes
Competing Interests: I also participated in a crowdfunding campaign to use next-gen enunciating to analyze beer samples (https://experiment.com/projects/mapping-the-sour-beer-microbiome).
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Are the datasets clearly presented in a useable and accessible format?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Fungal metagenomics & bioinformatics
Alongside their report, reviewers assign a status to the article:
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Version 1 11 Sep 17 |
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Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
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