Root and soil microbial communities constitute the below-ground plant microbiome, are drivers of nutrient cycling, and affect plant productivity. However, our understanding of their spatiotemporal patterns is confounded by exogenous factors that covary spatially, such as changes in host plant species, climate, and edaphic factors. These spatiotemporal patterns likely differ across microbiome domains (bacteria and fungi) and niches (root vs. soil). To capture spatial patterns at a regional scale, we sampled the below-ground microbiome of switchgrass monocultures of five sites spanning >3 degrees of latitude within the Great Lakes region. To capture temporal patterns, we sampled the below-ground microbiome across the growing season within a single site. We compared the strength of spatiotemporal factors to nitrogen addition determining the major drivers in our perennial cropping system. All microbial communities were most strongly structured by sampling site, though collection date also had strong effects; in contrast, nitrogen addition had little to no effect on communities. Though all microbial communities were found to have significant spatiotemporal patterns, the structure of bacterial communities was better explained by spatiotemporal factors than fungal communities, which appeared more structured by stochastic processes. Root communities, especially bacterial, were more temporally structured than soil communities which were more spatially structured, both across and within sampling sites. These differential responses of bacterial and fungal communities to spatiotemporal factors likely alter interactions and assembly of the plant microbiome.

The process of fermenting tofu extends thousands of years. Despite a resurgent interest in microbial communities and fermented foods, little knowledge exists concerning microbial diversity of communities of fermented ‘hairy’ tofu known in China as Mao tofu. We used high-throughput metagenomic sequencing of the ITS, LSU and 16S rDNA marker genes to disentangle the Mao tofu fungal and bacterial community composition and diversity across the four most important markets in the Yunnan region of China. We show that hairy tofu in this region consists of around 170 fungal and 365 bacterial taxa. Significant differences in community structure were found between markets and niches. Machine learning random forest models were able to accurately classify both market and niche of sample origin. An over-abundance of yeast taxa were detected, and Geotrichum were the most abundant fungal taxa, followed by Torulaspora, Trichosporon, and Pichia. Mucor (Mucormycota) was also abundant in the LSU data and especially in the outside niche (rind), which consists of the visible ‘hairy’ mycelium. The majority of the bacterial OTUs belonged to Proteobacteria, Firmicutes, and Bacteroidota, with Acinetobacter, Lactobacillus, Sphingobacterium and Flavobacterium the most abundant members. Of interest, putative fungal pathogens of plants (e.g. Cercospora, Diaporthe, Fusarium) and animal (e.g. Metarhizium, Entomomortierella, Pyxidiophora, Candida, Clavispora), as well as bacterial (e.g. Legionella) pathogens, were detected. Non-target eukaryotic taxa detected in by LSU amplicon sequencing included soybean (Glycine max), Protozoa, Metazoa (e.g. Nematoda and Platyhelminthes), Rhizaria and Chromista, providing evidence of additional biocomplexity and diversity in the tofu microbiome.