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 \cite{Gallone_2016}.
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
Beer sample preparation
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 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. For DNA extraction, the ZR Fecal DNA MiniPrep kit (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 other contaminants.
PCR1: ITS amplification
To amplify yeast genomic DNA, we used the fungal hypervariable region ITS1 (internal transcribed spacer 1) as previously described \cite{Bokulich_2015} 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 using gel electrophoresis and with a fragment analyser. ITS amplicon were purified from free primers and primer dimers using AMPure 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).
Sequencing
MiSeq sequencing was performed using the MiSeq v3 reagent kit protocol (Illumina). Briefly, the amplified DNA was quantified using a fluorimetric method based on dsDNA 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.
Bioinformatics Analysis
The curated set of ITS sequences from the Refseq database (
https://www.ncbi.nlm.nih.gov/refseq/targetedloci/) was used to build an ITS index for the Burrows-Wheeler Aligner (BWA)
\cite{Li_2009}. The BWA was used to map the reads of each beer from the fastq files to our ITS index. The bam files were sorted and indexed using samtools. Subsequently, the number of ITS per beer and per species were counted and only the species where we found more than 10 reads were kept.
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
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 the following people for their invaluable help: 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 a sequencing platform; Bioinformatics platform Onecodex for providing access to their metagenomic analysis tool; UniverCité and InArTiS for their in kind support to the Hackuarium association and Rachel Aronoff for her critical edition of the manuscript.
Grant information
This project was crowdfunded thank to the support the 124 backers of the BeerDeCoded campaign that took place in June 2015. For a full list of backers, see [
LINK]. These funders also played a significant role in the data collection as they sent 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.
Copyright: © 2017 Sobel J et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence (
CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
Competing interests: GR is a shareholder of SwissDeCode, a company selling to food manufacturers point-of-need DNA tests for food safety and compliance.