Consistent with its widespread use for fermentation, Saccharomyces cerevisiae, or “brewer's yeast” was detected in all beer samples at very high levels compared to other species (Figure 3), accounting for between 11% for the Orval and 99% of all sequencing reads for the Tempete. Most beers had about 90-97% of reads comming from Saccharomyces cerevisiae. More surprisingly, Saccharomyces mikatae, a species used in winemaking [Bellon JR, Schmid F, Capone DL, Dunn BL, Chambers PJ. Introducing a New Breed of Wine Yeast: Interspecific Hybridisation between a Commercial Saccharomyces cerevisiae Wine Yeast and Saccharomyces mikatae. Fairhead C, ed. PLoS ONE. 2013;8(4):e62053. doi:10.1371/journal.pone.0062053.] was also detected at high level in all samples (0.5% - 5%). Most brews were found to contain low to medium presence of various other yeast species, including Saccharomyces bayanus (used in winemaking and cider fermentation), Saccharomyces kudriavzevii and Saccharomyces pastorianus (used in lager), Saccharomyces eubayanus (a probable parent of Saccharomyces pastorianus), Brettanomyces bruxellensis (typically used for the production of the typical Belgian beer styles), Saccharomyces cariocanus and Saccharomyces paradoxus (two wild yeast species closely related to Saccharomyces cerevisiae). In addition, we observed that Brettanomyces bruxellensis was highly represented in the Orval beer and in the Chicha Beer Experimental with respectively 86% and 15% of the sequenced beer in these samples.
More interesting was the occurrence of non-conventional and wild yeast. For example, widespread were DNA reads associated to Kazachstania sp., a wild yeast of common occurrence in brines. Interestingly, one member of the family (K. servazzi) when pitched 24h before the ale yeast, gave significantly higher level of esters than the control beer and had a strong fruity and floral aroma [Gibson 2015, Poster presented at the
35th EBC (European Brewery Convention) Congress in Porto].
In 15 beers we measured traces of Alternaria sp., a field fungi present in the kernels of cereals that is also used in organic agriculture as natural herbicide for the control of weed. If the presence of Alternaria sp. in the malt may be an additional indication of its organic origin, Alternaria sp. proteins in the final product may cause beer gushing: the sudden release of foam after opening the bottle [Haikara 1980, Gushing induced by fungi. European Brewery Convention Monograph VI, Helsinki, Brauwelt-Verlag: Nürnberg, 1980, pp. 251–259].
The three beers in which we measured the highest ITS1 gene biodiversity were Waldbier 2014 “Black Pine” (an Austrian beer brewed using cones collected in the forest), 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.
The presence of some fungal DNA was restricted to a geographic area. For instance, DNA of Wickerhamomyces anomalus, a non-Saccharomyces wine yeast that contributes to wine aroma through the production of volatile compounds, was found in 5 Swiss beers (4 from Canton Wallis). Our small sample size cannot support a statistically significant association with a designated origin, and it is very possible that W. anomalus may be present in other beers as well.
Discussion and Perspectives
We believe that small, independent “craft” science can branch out from mainstream scientific research. Our choice to run BeerDeCoded independently and inside a citizen-science lab parallels what is happening in the brewing establishment. In 1978 there were 89 big, mainstream breweries in the US. In 2016, there are 5,301. Among them, 3,132 small, independent microbreweries represents 60% of the registered businesses (source: American Brewers Association
LINK). The phenomena of “craft” beer is expanding also in Europe and Asia. Supported by the favorable demand, one driver of this expansion is the awareness that brewing is attainable with limited resources. Individuals and small teams can brew good beer independently from the endorsement of important stakeholders. Our first dataset demonstrates that it is possible to execute complex molecular analyses on beer using limited resources, and with negligible support from traditional funding agencies and research institutions. Sustainable funding may be achieved by offering “craft science as service” to micro- and homebrewers.
Will molecular data be useful for the brewing industry? Microbreweries and homebrewers face sanitisation challenges. Information encoded in the beer DNA could help brewers to control the quality and the reproducibility of their processes, or to decide whether to use the final product for short term or long term storage based on an index of spoilage microbes. Other targeted analyses could help to validate procurement and to insure compliance if specific ingredients are declared on the label (i.e. is this yeast/hops/barley really what is declared?). Relevant data are accumulating. For instance, the full genome of 157 brewing yeast strains has been sequenced [Gallone 2016
Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts]
With untargeted molecular analyses, brewers could benchmark their production batches against known commercial beers and differentiate better in the brewing landscape. Major brands face losses due to counterfeiting and adulteration. In this context, molecular fingerprints could provide proof of authenticity for final products and for proprietary yeast strains.
With DNA sequencing costs dropping dramatically, and with the emergence of portable and low cost instrumentation, we believe that it is a favorable time to expand DNA analysis to novel fields, beer included. Still, BeerDeCoded remains a small “craft science” hub dedicated to Open Science. We invite researchers from other laboratories, microbreweries and citizen laboratories to build on our open data set, or to contribute additional data at their will.
Methods
Detailed methods are available on Github [link].
Beer sample preparation
The content in the beer bottle was mixed by inversion. 50 mL were transferred into a conical tube and centrifuged (5000 rpm, 20 min, 4 °C) to collect cells and precipitable material. Low fermentation beers (i.e. lager, pilsner) had a more unstable pellet compared to high fermentation beers (i.e. ales). The 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 removed and the pellet were stored at -20°C for future analyses. For DNA extraction, the ZR Fecal DNA MiniPrep Kit from Zymo Research (Catalog No. D6010) was used with minor modifications.
Quatity control for DNA extraction
The absorbance of the extracted DNA was measured at 230, 260 and 280 nm using a nanodrop instrument to ensure the DNA was free from protein and chemical contaminants.
PCR1: ITS amplification
To amplify yeast genomic DNA, we used the fungal hypervariable region ITS1 (internal transcribed spacer 1) as described [Bukolich 2015,
Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance] using the following primers: BITS (5′–CTACCTGCGGARGGATCA–3′) and B58S3 (5′–GAGATCCRTTGYTRAAAGTT–3′). Typical PCR reactions contained 5–100 ng DNA template. Amplicon size (500nt) was verified with gel electrophoresis and with a fragment analyser. ITS amplicon were purified from free primers and primer dimer species using AMPure XP beads following the manufacturer’s instructions. Dual indices and Illumina sequencing adapters were attached using the Nextera XT Index Kit following manufacturer’s instructions.
MiSeq Sequencing
MiSeq sequencing was performed using the MiSeq v3 reagent kit protocol. Briefly, we quantified the amplified DNA with a fluorimetric method that uses dsDNA binding dyes (Qubit). We diluted each DNA sample to 4 nM using 10 mM Tris pH 8.5 and pooled 5 uL of diluted DNA from each library. 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, we generated paired 2x 300bp reads that were exported as FASTq files.
Bioinformatics Analysis
We downloaded the curated set of ITS sequences from the Refseq database (https://www.ncbi.nlm.nih.gov/refseq/targetedloci/). We used these sequences to build an ITS index for the Burrows-Wheeler Aligner. We used BWA to map the reads of each beer from the fastq files to our ITS index. Then we sorted and indexed the bam files using samtools. Subsequently, we counted the number of ITS per beer and per species and we kept only the species where we found more than 10 reads.
Dataset content
The dataset contains the metagenetic 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.
Data and code statement
The raw data are stored in the SRA database in the bio project PRJNA388541
References
Author contributions
JS, LH and GR conceived the projects and communicated with the public. JS, NR and GR designed the experiments and carried out the research. JS, LH and GR wrote the manuscript.
Aknowledgements
The authors would like to thank Gabrielle Salanon for her help with sample extraction and analysis. Keith Harshman (Lausanne Genomic Technology Facility) for the access to the sequencing platform. Onecodex for the access to their metagenomic analysis tool.
Grant information
This project was funded by the 124 backers of the BeerDeCoded crowdfunding campaign that happened in June 2015. For a full list of backers, see [
LINK]. These funders played a significant role in the data collection as they sent their beer samples for analysis. All backers from the crowdfunding campaign were given a chance to participate in the study design and analysis, decision to publish, or the preparation of the manuscript.