Hernandez-Velazquez, R. | Search bioRxiv

bioRxiv2025

A tale of two vineyards: parsing site-specific differences in bacterial and fungal communities of wine grapes from proximal vineyards, and their changes during processing in a single winery

Wine is a microbial product, naturally transformed through fermentation by a consortium of fungi and bacteria that originate from the vineyard and the cellar, in addition to any microorganisms that are intentionally inoculated. Previous work has shown that grapevine-associated microbiota follow distinct biogeographic patterns, associated with climate and soil properties, and that even neighboring vineyards can harbor distinct microbial communities, but it is unclear whether these differences persist when controlling for variations in farming practices, cultivar, and climate, and whether site-specific microbial profiles change during processing in the winery. Here we investigated the bacterial and fungal microbiota of fruit pre- and post-harvest from two nearby vineyards planted to a single variety, geographically close to one another, and farmed the same way, and then processed in a single winery. These communities subtly changed during processing yet retained distinct site-specific signatures, indicating a partial contribution of the winery environment to the microbiota of grape must and juice pre-fermentation. We also profiled the microbiota of key microbial sources in the winery environment, including fruit flies and processing equipment, demonstrating that the microbiota at these sites reflect contact with plant material, harbor communities distinct from fruit, and appear to partially contribute to the fermentation assemblage, especially via the contribution of fermentative yeasts that are rare or missing in the vineyard environment. These results bolster previous reports of site-specific microbial signatures in winegrowing and make a first estimation of the changes to the grape-associated microbiome during early processing. ImportanceNative wine fermentations are driven by microbes carried over from the vineyard or introduced in the winery. In this study, we tracked the microbiome dynamics of wine fermentations from two Chardonnay vineyards planted in close proximity to examine the relative contribution of vineyard- and winery-resident microbiota on microbial succession during wine fermentation. By tracking microbial changes from vineyard to winery, we show that the winery environment, including processing equipment and fruit flies, contributes to the fermentation microbiome but does not override vineyard-specific microbial differences. These findings support the concept of microbial terroir and highlight the importance of vineyard microbiomes in shaping wine fermentation. This work advances our understanding of how microbial diversity influences wine production and provides insight into the ecological dynamics of fermentation. By identifying key microbial sources and their contributions, this study lays the groundwork for future microbiome research in viticulture and wine making.

microbiology↗

bioRxiv2025

MOSHPIT: accessible, reproducible metagenome data science on the QIIME 2 framework

Metagenome sequencing has revolutionized functional microbiome analysis across diverse ecosystems, but is fraught with technical hurdles. We introduce MOSHPIT (https://moshpit.readthedocs.io), software built on the QIIME 2 framework (Q2F) that integrates best-in-class CAMI2-validated metagenome tools with robust provenance tracking and multiple user interfaces, enabling streamlined, reproducible metagenome analysis for all expertise levels. By building on Q2F, MOSHPIT enhances scalability, interoperability, and reproducibility in complex workflows, democratizing and accelerating discovery at the frontiers of metagenomics.

bioinformatics↗

bioRxiv2020

Quantitative assessment of NCLDV-host interactions predicted by co-occurrence analyses

Nucleocytoplasmic DNA viruses (NCLDVs) are highly diverse and abundant in marine environments. However, knowledge of their hosts is limited because only a few NCLDVs have been isolated so far. Taking advantage of the recent large-scale marine metagenomics census, in silico host prediction approaches are expected to fill the gap and further expand our knowledge of virus-host relationships for unknown NCLDVs. In this study, we built co-occurrence networks of NCLDVs and eukaryotic taxa to predict virus-host interactions using Tara Oceans sequencing data. Using the positive likelihood ratio to assess the performance of host prediction for NCLDVs, we benchmarked several co-occurrence approaches and demonstrated an increase in the odds ratio of predicting true positive relationships four-fold compared with random host predictions. To further refine host predictions from high-dimensional co-occurrence networks, we developed a phylogeny-informed filtering method, Taxon Interaction Mapper, and showed it further improved the prediction performance by twelve-fold. Finally, we inferred virophage - NCLDV networks to corroborate that co-occurrence approaches are effective for predicting interacting partners of NCLDVs in marine environments. ImportanceNCLDVs can infect a wide range of eukaryotes although their life cycle is less dependent on hosts compared with other viruses. However, our understanding of NCLDV- host systems is highly limited because few of these viruses have been isolated so far. Co-occurrence information has been assumed to be useful to predict virus-host interactions. In this study, we quantitatively show the effectiveness of co-occurrence inference for NCLDV host prediction. We also improve the prediction performance with a phylogeny-guided method, which leads to a concise list of candidate host lineages for three NCLDV families. Our results underpin the usage of co-occurrence approach for metagenomic exploration of the ecology of this diverse group of viruses.

microbiology↗