Associations among wine grape microbiome, metabolome, and fermentation behavior suggest microbial contribution to regional wine characteristics

mBio

Volumn 7, Issue 3, 2016, Pages

  Bokulich, Nicholas A ^a,c   Collins, Thomas S ^a,d   Masarweh, Chad ^a   Allen, Greg ^b   Heymann, Hildegarde ^a   Ebeler, Susan E ^a   Millsa, David A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Far Niente and Nickel and Nickel Wineries   (United States)

^c NORTHERN ARIZONA UNIVERSITY   (United States)

^d WASHINGTON STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOGEOGRAPHY; CALIFORNIA; CHEMICAL COMPOSITION; CONTROLLED STUDY; FERMENTATION; FERMENTATION TECHNIQUE; FOOD QUALITY; GRAPE; LONGITUDINAL STUDY; MATHEMATICAL MODEL; METABOLITE; METABOLOME; MICROBIAL ACTIVITY; MICROBIAL CONSORTIUM; MICROBIAL DIVERSITY; MICROBIOME; NONHUMAN; PLANT MICROORGANISM INTERACTION; POPULATION ABUNDANCE; PRIORITY JOURNAL; PROCESS TECHNOLOGY; RANDOM FOREST; RED WINE; SPECIES RICHNESS; TERROIR; VINEYARD; WHITE WINE; ANALYSIS; BACTERIUM; CLASSIFICATION; FUNGUS; GROWTH, DEVELOPMENT AND AGING; METABOLISM; MICROBIOLOGY; MICROFLORA; VITIS; WINE;

BACTERIA; CALIFORNIA; FERMENTATION; FUNGI; LONGITUDINAL STUDIES; METABOLOME; MICROBIOTA; VITIS; WINE;

EID: 84979703559     PISSN: 21612129     EISSN: 21507511     Source Type: Journal    
DOI: 10.1128/mBio.00631-16     Document Type: Article

References (48)

1. Pereira GE, Gaudillere JP, van Leeuwen C, Hilbert G, Lavialle O, Maucourt M, Deborde C, Moing A, Rolin D. 2005. 1H NMR and chemometrics to characterize mature grape berries in four wine-growing areas in Bordeaux, France. J Agric Food Chem 53:6382-6389. http://dx.doi.org/10.1021/jf058058q.
2. Son HS, Hwang GS, Kim KM, Ahn HJ, Park WM, van den Berg F, Hong YS, Lee CH. 2009. Metabolic studies on geographical grapes and their wines using 1H NMR analysis coupled with multivariate statistics. J Agric Food Chem 57:1481-1490. http://dx.doi.org/10.1021/jf803388w.
3. López-Rituerto E, Savorani F, Avenoza A, Busto JH, Peregrina JM, Engelsen SB. 2012. Investigations of La Rioja terroir for wine production using 1H NMR metabolomics. J Agric Food Chem 60:3452-3461. http://dx.doi.org/10.1021/jf204361d.
4. Fischer U, Roth D, Christmann M. 1999. The impact of geographic origin, vintage, and wine estate on sensory properties of Vitis vinifera cv. Riesling wines. Food Qual Preference 10:281-288. http://dx.doi.org/10.1016/S0950-3293(99)00008-7.
5. Robinson AL, Adams DO, Boss PK, Heymann H, Solomon PS, Trengove RD. 2012. Influence of geographic origin on the sensory characteristics and wine composition of Vitis vinifera cv. Cabernet sauvignon wines from Australia. Am J Enol Vitic 63:467-476. http://dx.doi.org/10.5344/ajev.2012.12023.
6. Heymann H, Noble A. 1987. Descriptive analysis of commercial Cabernet sauvignon wines from California. Am J Enol Vitic 38:41-44.
7. Kontkanen D, Reynolds AG, Cliff MA, King M. 2005. Canadian terroir: sensory characterization of Bordeaux-style red wine varieties in the Niagara Peninsula. Food Res Int 38:417-425. http://dx.doi.org/10.1016/j.foodres.2004.10.010.
8. Van Leeuwen C, Seguin G. 2006. The concept of terroir in viticulture. J Wine Res 17:1-10. http://dx.doi.org/10.1080/09571260600633135.
9. Barata A, Malfeito-Ferreira M, Loureiro V. 2012. The microbial ecology of wine grape berries. Int J Food Microbiol 153:243-259. http://dx.doi.org/10.1016/j.ijfoodmicro.2011.11.025.
10. Bokulich NA, Thorngate JH, Richardson PM, Mills DA. 2014. Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate. Proc Natl Acad Sci U S A 111:E139-E148. http://dx.doi.org/10.1073/pnas.1317377110.
11. Taylor MW, Tsai P, Anfang N, Ross HA, Goddard MR. 2014. Pyrosequencing reveals regional differences in fruit-associated fungal communities. Environ Microbiol 16:2848-2858. http://dx.doi.org/10.1111/1462-2920.12456.
12. Gayevskiy V, Goddard MR. 2012. Geographic delineations of yeast communities and populations associated with vines and wines in New Zealand. ISME J 6:1281-1290. http://dx.doi.org/10.1038/ismej.2011.195.
13. Pinto C, Pinho D, Cardoso R, Custódio V, Fernandes J, Sousa S, Pinheiro M, Egas C, Gomes AC. 2015. Wine fermentation microbiome: a landscape from different Portuguese wine appellations. Front Microbiol 6:905. http://dx.doi.org/10.3389/fmicb.2015.00905.
14. Knight S, Klaere S, Fedrizzi B, Goddard MR. 2015. Regional microbial signatures positively correlate with differential wine phenotypes: evidence for a microbial aspect to terroir. Sci Rep 5:14233. http://dx.doi.org/10.1038/srep14233.
15. Swiegers JH, Bartowsky EJ, Henschke PA, Pretorius IS. 2005. Yeast and bacterial modulation of wine aroma and flavour. Aust J Grape Wine Res 11:139-173. http://dx.doi.org/10.1111/j.1755-0238.2005.tb00285.x.
16. Verginer M, Leitner E, Berg G. 2010. Production of volatile metabolites by grape-associated microorganisms. J Agric Food Chem 58:8344-8350. http://dx.doi.org/10.1021/jf100393w.
17. Bokulich NA, Joseph CM, Allen G, Benson AK, Mills DA. 2012. Next-generation sequencing reveals significant bacterial diversity of botrytized wine. PLoS One 7:e36357. http://dx.doi.org/10.1371/journal.pone.0036357.
18. Piao H, Hawley E, Kopf S, DeScenzo R, Sealock S, Henick-Kling T, Hess M. 2015. Insights into the bacterial community and its temporal succession during the fermentation of wine grapes. Front Microbiol 6:809. http://dx.doi.org/10.3389/fmicb.2015.00809.
19. Bokulich NA, Swadener M, Sakamoto K, Mills DA, Bisson LF. 2015. Sulfur dioxide treatment alters wine microbial diversity and fermentation progression in a dose-dependent fashion. Am J Enol Viticulture 66:73-79. http://dx.doi.org/10.5344/ajev.2014.14096.
20. Chatonnet P, Dubourdie D, Boidron J, Pons M. 1992. The origin of ethylphenols in wines. J Sci Food Agric 60:165-178. http://dx.doi.org/10.1002/jsfa.2740600205.
21. Alberto MR, Gómez-Cordovés C, Manca de Nadra MC. 2004. Metabolism of gallic acid and catechin by Lactobacillus hilgardii from wine. J Agric Food Chem 52:6465-6469. http://dx.doi.org/10.1021/jf049239f.
22. Rodríguez H, Curiel JA, Landete JM, de las Rivas B, López de Felipe F, Gómez-Cordovés C, Mancheño JM, Muñoz R. 2009. Food phenolics and lactic acid bacteria. Int J Food Microbiol 132:79-90. http://dx.doi.org/10.1016/j.ijfoodmicro.2009.03.025.
23. Escofier B, Pages J. 1990. Multiple factor analysis. Comput Stat Data Anal 18:121-140.
24. Breiman L. 2001. Random Forests. Mach Learn 45:5-32. http://dx.doi.org/10.1023/A:1010933404324.
25. Nisiotou AA, Rantsiou K, Iliopoulos V, Cocolin L, Nychas GJ. 2011. Bacterial species associated with sound and Botrytis-infected grapes from a Greek vineyard. Int J Food Microbiol 145:432-436. http://dx.doi.org/10.1016/j.ijfoodmicro.2011.01.017.
26. Bisson LF. 1999. Stuck and sluggish fermentations. Am J Enol Vitic 50: 107-119.
27. Fleet GH. 2003. Yeast interactions and wine flavour. Int J Food Microbiol 86:11-22. http://dx.doi.org/10.1016/s0168-1605(03)00245-9.
28. Bokulich NA, Bamforth CW. 2013. The microbiology of malting and brewing. Microbiol Mol Biol Rev 77:157-172. http://dx.doi.org/10.1128/MMBR.00060-12.
29. Priest FG, Cowbourne MA, Hough JS. 1974. Wort enterobacteria-review. J Inst Brew 80:342-356. http://dx.doi.org/10.1002/j.2050-0416.1974.tb03629.x.
30. Morrison-Whittle P, GoddardMR. 2015. Quantifying the relative roles of selective and neutral processes in defining eukaryotic microbial communities. ISME J 9:2003-2011. http://dx.doi.org/10.1038/ismej.2015.18.
31. Burns KN, Kluepfel DA, Strauss SL, Bokulich NA, Cantu D, Steenwerth KL. 2015. Vineyard soil bacterial diversity and composition revealed by 16S rRNA genes: differentiation by geographic features. Soil Biol Biochem 91:232-247. http://dx.doi.org/10.1038/ismej.2015.18.
32. Zarraonaindia I, Owens SM, Weisenhorn P, West K, Hampton-Marcell J, Lax S, Bokulich NA, Mills DA, Martin G, Taghavi S, van der Lelie D, Gilbert JA. 2015. The soil microbiome influences grapevine-associated microbiota. mBio 6:e02527-14. http://dx.doi.org/10.1128/nBio.02527-14.
33. Lucas PM, Claisse O, Lonvaud-Funel A. 2008. High frequency of histamine-producing bacteria in the enological environment and instability of the histidine decarboxylase production phenotype. Appl Environ Microbiol 74:811-817. http://dx.doi.org/10.1128/aem.01496-07.
34. Bokulich NA, Ohta M, Richardson PM, Mills DA. 2013. Monitoring seasonal changes in winery-resident microbiota. PLoS One 8:e66437. http://dx.doi.org/10.1371/journal.pone.0066437.
35. Bokulich NA, Mills DA. 2013. Improved selection of internal transcribed spacer-specific primers enables quantitative, ultra-high-throughput profiling of fungal communities. Appl Environ Microbiol 79:2519-2526. http://dx.doi.org/10.1128/AEM.03870-12.
36. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, Fierer N, Knight R. 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A 108:4516-4522. http://dx.doi.org/10.1073/pnas.1000080107.
37. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Gonzalez Pena AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. 2010. Qiime allows analysis of high-throughput community sequence data. Nat Methods 7:335-336. http://dx.doi.org/10.1038/nmeth.f.303.
38. Edgar RC. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460-2461. http://dx.doi.org/10.1093/bioinformatics/btq461.
39. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL. 2006. Greengenes, a chimerachecked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069-5072. http://dx.doi.org/10.1128/AEM.03006-05.
40. Abarenkov K, Henrik Nilsson R, Larsson K, Alexander IJ, Eberhardt U, Erland S, Høiland K, Kjøller R, Larsson E, Pennanen T, Sen R, Taylor AFS, Tedersoo L, Ursing BM, Vrålstad T, Liimatainen K, Peintner U, Kõljalg U. 2010. The UNITE database for molecular identification of fungi-recent updates and future perspectives. New Phytol 186:281-285. http://dx.doi.org/10.1111/j.1469-8137.2009.03160.x.
41. Wang Q, Garrity GM, Tiedje JM, Cole JR. 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261-5267. http://dx.doi.org/10.1128/AEM.00062-07.
42. Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R. 2010. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26:266-267. http://dx.doi.org/10.1093/bioinformatics/btp636.
43. Haas BJ, Gevers D, Earl AM, Feldgarden M, Ward DV, Giannoukos G, Ciulla D, Tabbaa D, Highlander SK, Sodergren E, Methé B, DeSantis TZ, Petrosino JF, Knight R, Birren BW. 2011. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 21:494-504. http://dx.doi.org/10.1101/gr.112730.110.
44. Price MN, Dehal PS, Arkin AP. 2010. FastTree 2-approximately maximum-likelihood trees for large alignments. PLoS One 5:e9490. http://dx.doi.org/10.1371/journal.pone.0009490.
45. Bokulich NA, Subramanian S, Faith JJ, Gevers D, Gordon JI, Knight R, Mills DA, Caporaso JG. 2013. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat Methods 10:57-59. http://dx.doi.org/10.1038/nmeth.2276.
46. Lozupone C, Knight R. 2005. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71: 8228-8235. http://dx.doi.org/10.1128/AEM.71.12.8228-8235.2005.
47. Anderson MJ. 2001. A new method for non-parametric multivariate analysis of variance. Aust Ecol 26:32-46. http://dx.doi.org/10.1046/j.1442-9993.2001.01070.x.
48. Le S, Josse J, Husson F. 2008. FactoMineR: an R package for multivariate analysis. J Stat Soft 25:1-18.