Fungal and bacterial communities of ‘Pinot noir’ must: effects of vintage, growing region, climate, and basic must chemistry

Abstract

Background The geographic and temporal distributions of bacterial and fungal populations are poorly understood within the same wine grape cultivar. In this work, we describe the microbial composition from ‘Pinot noir’ must with respect to vintage, growing region, climate, and must chemistry across the states of California and Oregon, USA. Materials and Methods We sampled ‘Pinot noir’ clone 667 clusters from 15 vineyards existing in a latitudinal gradient spanning nearly 1,200 km in California and Oregon for two vintages (2016 and 2017). Regions included five American Viticultural Areas (AVA). In order from southern California to Oregon, these AVAs were Santa Barbara, Monterey, Sonoma, Mendocino, and Willamette Valley. Uninoculated grape musts were subjected to 16S rRNA gene and ITS-1 amplicon sequencing to assess composition of microbial communities. We also measured grape maturity metrics. Finally, to describe regions by precipitation and growing degree days, we queried the Parameter-elevation Regressions on Independent Slopes Model (PRISM) spatial climate dataset. Results Most of the dominant bacterial taxa in must samples were in the family Enterobacteriaceae, notably the lactic acid bacteria or the acetic acid bacteria groups, but some, like the betaproteobacterial genus Massilia, belonged to groups not commonly found in grape musts. Fungal communities were dominated by Hanseniaspora uvarum (Saccharomycetaceae). We detected relationships between covariates (e.g., vintage, precipitation during the growing season, pH, titratable acidity, and total soluble solids) and bacterial genera Gluconobacter and Tatumella in the family Enterobacteraceae, Sphingomonas (Sphingomonodaceae), Lactobacillus (Lactobacillaceae), and Massilia (Oxalobacteraceae), as well as fungal genera in Hanseniaspora, Kazachstania, Lachancea, Torulaspora in the family Saccharomycetaceae, as well as Alternaria (Pleosporaceae), Erysiphe (Erysiphaceae), and Udeniomyces (Cystofilobasidiaceae). Fungal community distances were significantly correlated with geographic distances, but this was not observed for bacterial communities. Climate varied across regions and vintages, with growing season precipitation ranging from 11 mm to 285 mm and growing degree days ranging from 1,245 to 1,846. Discussion We determined that (1) bacterial beta diversity is structured by growing season precipitation, (2) fungal beta diversity reflects growing season precipitation and growing degree days, and (3) microbial differential abundances of specific genera vary with vintage, growing season precipitation, and fruit maturity metrics. Further, the correlation between fungal community dissimilarities and geographic distance suggests dispersal limitation and the vineyard as a source for abundant fungal taxa. Contrasting this observation, the lack of correlation between bacterial community dissimilarity and geographic distance suggests that environmental filtering is shaping these communities.

Transcriptomics Provides a Genetic Signature of Vineyard Site and Offers Insight into Vintage-Independent Inoculated Fermentation Outcomes

“…S2), but these analyses lacked the ability to resolve whether the particular organisms detected belonged to the spoilage organism Botrytis cinerea or another species in the genus Botrytis. Through this work, must microbiome sequencing was extended to include the 2019 vintage, with results largely matching findings from previous vintages across these same vineyard sites (51). The observed microbial community composition was consistent with organisms previously shown to be present at the initial stages of the winemaking process (4,(16)(17)(18)52).…”

“…S1A in the supplemental material). As part of a larger study ( 49 – 51 ), in 2016, 2017, and 2019, microbiome samples for DNA isolation and ribosomal DNA amplicon sequencing were taken approximately 2 to 3 h prior to inoculation from four independent fermentations per vineyard site. In the 2017 and 2019 vintages, two primary fermentations from each site were also profiled using RNA sequencing approaches to perform eukaryotic gene expression analyses at multiple fermentation time points after inoculation with the wine yeast RC212.…”

“…DNA was extracted for amplicon sequencing and library preparation as described in references 51 and 69 . The UC Davis DNA Tech Core performed sequencing using Illumina MiSeq, producing 251-bp paired-end sequences.…”

Sources and Assembly of Microbial Communities in Vineyards as a Functional Component of Winegrowing

“…Vineyard microbiomes (both in the soil and directly associated with grapevines) are shaped by multiple interacting factors that make up a single location, including climate (i.e., precipitation and temperature gradients), geolocation, elevation, topography and slope, edaphic factors, and management practices for the soil and the grapevine (Barata et al, 2012b;Bokulich et al, 2014;Burns et al, 2015Burns et al, , 2016Jara et al, 2016;Portillo et al, 2016;Vitulo et al, 2019;Liu et al, 2020;Steenwerth et al, 2021). Microbial biodiversity in the soil, grapevine, and surrounding environments thus reflect effects of both environmental filtering and dispersal limitation (see Glossary), as detailed below.…”

“…Geographic distance is often a primary factor correlated with these differences, though it is unclear if it is merely a proxy for these other drivers (Burns et al, 2015;Miura et al, 2017). For example, microbiota in musts appear to correlate with vineyard and regional level climate and weather patterns (Bokulich et al, 2014;Reiter et al, 2021;Steenwerth et al, 2021), human activity, and human transport between vineyards in the case of S. cerevisiae (Goddard et al, 2010;Gayevskiy et al, 2016). Site, encompassing the specific environmental constraints of a single place (e.g., vineyard or block), is commonly the most explanatory variable in studies of microbiome assembly in other plants, suggesting that vineyard-specific microbiomes should not come as a surprise (Knief et al, 2010;Rastogi et al, 2012;Coleman-Derr et al, 2016;Wagner et al, 2016).…”