Profiling the Bacterial Community of Fermenting Traminette Grapes during Wine Production using Metagenomic Amplicon Sequencing
Summary
Here, we present a protocol to describe amplicon metagenomic for determining the bacterial community of Traminette grapes, fermenting grapes, and final wine.
Abstract
Advances in sequencing technology and the relatively easy access to the use of bioinformatics tools to profile microbial community structures have facilitated a better understanding of both culturable and non-culturable microbes in grapes and wine. During industrial fermentation, microbes, known and unknown, are often responsible for product development and off-flavor. Therefore, profiling the bacteria from grape to wine can enable an easy understanding of in situ microbial dynamics. In this study, the bacteria of Traminette grapes must undergoing fermentation, and the final wine were subjected to DNA extraction that yielded 15 ng/µL to 87 ng/µL. The 16S amplicon of the hypervariable region of the V4 region was sequenced, relatively abundant bacteria consisting of phyla Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, Fusobacteriota and followed by the Verrucomicrobiota, Halobacterota, Desulfobacterota, Myxococcota, and Acidobacteriota. A Venn diagram analysis of the shared unique operational taxonomic units (OTU) revealed that 15 bacteria phyla were common to both grape must, fermenting stage, and final wine. Phyla that were not previously reported were detected using the 16S amplicon sequencing, as well as genera such as Enterobacteriaceae and Lactobacillaceae. Variation in the organic nutrient use in wine and its impact on bacteria was tested; Traminette R tank containing Fermaid O and Traminette L stimulated with Stimula Sauvignon blanc + Fermaid O. Alpha diversity using the Kruskal-Wallis test determined the degree of evenness. The beta diversity indicated a shift in the bacteria at the fermentation stage for the two treatments, and the final wine bacteria looked similar. The study confirmed that 16S amplicon sequencing can be used to monitor bacteria changes during wine production to support quality and better utilization of grape bacteria during wine production.
Introduction
Traminette grape is characterized by production of superior wine quality, in addition to appreciable yield and partial resistance to several fungal infections1,2,3. The natural fermentation of grapes relies on associated microorganisms, wine production environment, and fermentation vessels4,5. Oftentimes, many wineries rely on wild yeast and bacteria for fermentation, production of alcohol, esters, aroma, and flavor development6.
The goal of this study is to examine the bacterial composition of grapes and monitor their dynamics during fermentation. Although, the modern use of starter cultures such as Saccharomyces cerevisiae for primary fermentation, where alcohol is produced, is common to different wine styles7. In addition, secondary fermentation, where malic acid is decarboxylated by Oenococcus oeni to lactic acid, improves the organoleptic and taste profile of the wine and reduces the acidity of wine8,9. With the recent advances in the use of culture-independent methods, it is now possible to determine different microbes associated with the wine grape and the species that are transferred to must and participate in the fermentation at different times up to the final product10.
The roles and dynamics of wild bacteria from different grapes transferred to the must during wine fermentation are poorly understood. The taxonomy of many of these bacteria is not even known, or their phenotypic properties are uncharacterized. This makes their application in coculture fermentation still poorly underutilized. However, microbiological culture-based analysis has been used to determine the bacterial population associated with grapes and wine10. It is widely known that selective culture plating is tedious, prone to contamination, has a low reproducibility, and output can be doubtful; it also misses bacterial species whose growth requirements are unknown. Previous studies indicate that culture-independent, 16S rRNA gene-based methodologies offer a more dependable and cost-effective approach to characterizing complex microbial communities11. For example, sequencing the hypervariable regions of the 16S rRNA gene has been successfully employed to study bacteria in grapes leaves, berries, and wine12,13,14. Studies have shown that the use of either 16S rRNA metabarcoding or whole metagenomic sequencing is suitable for microbiome studies15. There is emerging information about the possible linkage of bacterial diversity to their metabolic attributes during wine production, which could help in the determination of oenological properties and terroir16.
The need to maximize the advantages of the metagenomic tools using next-generation sequencing (NGS) to study the grape and wine microbial ecology has been emphasized16,17. Also, the use of culture-independent methods based on high throughput sequencing to profile microbial diversity of the food and fermentation ecosystem has become very relevant and valuable to many laboratories and is recommended for industrial use18,19. It provides an advantage of detection and taxonomic profiling of the present microbial populations and the contribution of environmental microbes, their relative abundance, and alpha and beta diversity20. The sequencing of the variable region of the 16S region has become an important gene of choice and has been used during different microbial ecological studies.
While many studies focus on fungi, especially yeast, during wine fermentation21, this study reported the 16S amplicon sequencing and bioinformatic tools used to study the bacteria during Traminette grapes fermentation for wine production.
Protocol
Representative Results
Discussion
The protocol of metagenomics starts from the sampling of the grape must, and when yeast was added to the must, the fermenting wine and final wine samples. This was followed by duplicate DNA extraction that was successfully extracted from these samples. The quantities obtained varied in concentration from 15 ng/ µL to 87 ng/ µL. This shows that the DNA extraction protocol is effective for metagenomic studies of wine. Although the quality of the DNA at A260/A280 varies, this may be attributed to different paramet…
Disclosures
The authors have nothing to disclose.
Acknowledgements
Funding from the Appalachian State University Research Council (URC) grant and CAPES Print Travel fellowship that supported the visit of FAO to Universidade de São Paulo, Ribeirão Preto – São Paulo, Brazil, are gratefully acknowledged. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. ECPDM is grateful for the CAPES Print Travel grant that supported her visit to Appalachian State University. ECPDM is a research fellow 2 from the Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brasil (CNPq).
Materials
| Agarose gel | Promega, Madison, WI USA | V3121 | Electrophoresis |
| FastPrep DNA spinKit for soil | MP Biomedicals, Solon, OH USA | 116560-200 | DNA extraction |
| FastQC software | Babraham Institute, United Kingdom | Bioinformatics | |
| Fermaid O | Scott Laboratory, Petaluma, CA USA | Fermentation | |
| High-Fidelity PCR Master Mix | New England Biolabs, USA | F630S | Polymerase chain reaction for sequencing |
| NEBNext Ultra | New England Biolabs, USA | NEB #E7103 | DNA Library Prep |
| NEBNext Ultra II DNA Library Prep Kit | Illumina, San Diego, CA USA | DNA sequencing | |
| NovaSeq Control Software (NVCS) | Illumina, San Diego, CA USA | DNA sequencing | |
| Novaseq6000 platform | Illumina, San Diego, CA USA | DNA sequencing | |
| QuiBit | Thermoscientific, Waltham, MA, USA | DNA quantification | |
| Quickdrop spectrophotometer | Molecular device, San Jose, CA, USA | DNA quantification | |
| Sodium Phosphate | Sigma Aldrich | 342483 | DNA extraction buffer |
| Stimula Sauvignon Blanc | Scott Laboratory, Petaluma, CA USA | Fermentation |
References
- Skinkis, P. A., Bordelon, B. P., Wood, K. V. Comparison of monoterpene constituents in traminette, gewürztraminer, and riesling winegrapes. American Journal of Enology and Viticulture. 59, 440-445 (2008).
- Bordelon, B. P., Skinkis, P. A., Howard, P. H. Impact of training system on vine performance and fruit composition of Traminette. American Journal of Enology and Viticulture. 59, 39-46 (2008).
- Reisch, B. I., et al. . Traminette’ Grape. New York Food and Life Science Bulletin. , (1996).
- Clemente-Jimenez, J. M., Mingorance-Cazorla, L., Martı́nez-Rodrı́guez, S., Las Heras-Vázquez, F. J., Rodrı́guez-Vico, F. Molecular characterization and oenological properties of wine yeasts isolated during spontaneous fermentation of six varieties of grape must. Food Microbiology. 21, 149-155 (2004).
- Attila, K. &. #. 1. 9. 5. ;., Kluz, M. Natural microflora of wine grape berries. Journal of Microbiology, Biotechnology and Food Sciences. 4 (special issue 1), 32-36 (2015).
- Swiegers, J. H., Bartowsky, E. J., Henschke, P. A., Pretorius, I. S. Yeast and bacterial modulation of wine aroma and flavor in Microbial modulation of wine aroma and flavour. Australian Journal of Grape and Wine Research. 11 (2), 139-173 (2008).
- Alonso-del-Real, J., Pérez-Torrado, R., Querol, A., Barrio, E. Dominance of wine Saccharomyces cerevisiae strains over S. kudriavzevii in industrial fermentation competitions is related to an acceleration of nutrient uptake and utilization. Environmental Microbiology. 21 (5), 1627-1644 (2019).
- Virdis, C., Sumby, K., Bartowsky, E., Jiranek, V. Lactic acid bacteria in wine: Technological advances and evaluation of their functional role. Frontiers in Microbiology. 11, 3192 (2021).
- Burns, T. R., Osborne, J. P. Impact of malolactic fermentation on the color and color stability of Pinot noir and Merlot Wine. American Journal of Enology and Viticulture. 64, 370-377 (2013).
- Piao, H., et al. Insights into the bacterial community and its temporal succession during the fermentation of wine grapes. Frontier of Microbiology. 6, 809 (2015).
- Figdor, D., Gukabivale, K. Survival against the odds: Microbiology of root canals associated with post-treatment disease Endodontic Topics. 18, 62-77 (2011).
- Bokulich, N. A., Joseph, C. M. L., Greg Allen, G., Benson, A. K., Mills, D. A. Next-generation sequencing reveals significant bacterial diversity of botrytized wine. Plos ONE. 7 (5), e36357 (2012).
- Berbegal, C., et al. A metagenomic-based approach for the characterization of bacterial diversity associated with spontaneous malolactic fermentations in wine. International Journal of Molecular Science. 20, 3980 (2019).
- Leveau, J. H., Tech, J. J. Grapevine microbiomics: bacterial diversity on grape leaves and berries revealed by high-throughput sequence analysis of 16S rRNA amplicons. International Symposium on Biological Control of Postharvest Diseases: Challenges and Opportunities. 905, 31-42 (2010).
- Rubiola, S., Macori, G., Civera, T., Fanning, S., Mitchell, M., Chiesa, F. Comparison between full-length 16s RNA metabarcoding and whole metagenome sequencing suggests the use of either is suitable for large-scale microbiome studies. Foodborne Pathogens and Disease. 19, 495-504 (2022).
- Bokulich, N. A., et al. Associations among wine grape microbiome, metabolome, and fermentation behavior suggest microbial contribution to regional wine characteristics. Mbio. 7 (3), e00631-e00716 (2016).
- Siren, K., et al. Multi-omics and potential applications in wine production. Current Opinion in Biotechnology. 56, 172-178 (2019).
- Kidd, S. P., Bastian, S. E. P., Eisenhofer, R., Welsh, B. L. Monitoring the viable grapevine microbiome to enhance the quality of wild wines. Microbiology Australia. 44 (1), 13-17 (2023).
- Lorenz, P., Eck, J. Metagenomics and industrial applications. Nature Reviews Microbiology. 3, 510-516 (2005).
- Tosi, E., Azzolini, M., Guzzo, F., Zapparoli, G. Evidence of different fermentation behaviours of two indigenous strains of Saccharomyces cerevisiae and Saccharomyces uvarum isolated from Amarone wine. Journal of Applied Microbiology. 107 (1), 210-218 (2009).
- Stefanini, I., Cavalier, D. Metagenomic approaches to investigate the contribution of the vineyard environment to the quality of wine fermentation: potentials and difficulties. Frontiers in Microbiology. 9, 991 (2018).
- Caporaso, J. G., et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods. 5, 335-336 (2010).
- Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., Holmes, S. P. DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods. 13, 581-583 (2016).
- Quast, C., et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research. 41 (Database issue), D590-D596 (2013).
- Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecology. 26 (1), 32-46 (2001).
- Bolyen, E., et al. interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology. 37, 852-857 (2019).
- Fadiji, A. E., Babalola, O. O. Metagenomics methods for the study of plant-associated microbial communities: A review. Journal of Microbiological Methods. 170, 105860 (2020).
- van Hijum, S. A., Vaughan, E. E., Vogel, R. F. Application of state-of-art sequencing technologies to indigenous food fermentations. Current Opinion in Biotechnology. 24, 178-186 (2013).
- Víquez-R, L., Fleischer, R., Wilhelm, K., Tschapka, M., Sommer, S. Jumping the green wall: The use of PNA-DNA clamps to enhance microbiome sampling depth in wildlife microbiome research. Ecology and Evolution. 10 (20), 11779-11786 (2020).
- Bukin, Y. S., Galachyants, P., Yu, I. V., Morozov, S. V., Bukin, A. S., Zakharenko, T. I., Zemskaya, The effect of 16S rRNA region choice on bacterial community metabarcoding results. Scientific Data. 6, 190007 (2019).
