Graves’ Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves’ disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson’s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.

Background Improving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods. Results We combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10–70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice. Conclusions Collectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans.

Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. While wastewater monitoring has been implemented to mitigate outbreak risk in universities and residential settings, its effectiveness in community K-12 sites is unknown. We implemented a wastewater and surface monitoring system to detect SARS-CoV-2 in nine elementary schools in San Diego County. Ninety-three percent of identified cases were associated with either a positive wastewater or surface sample; 67% were associated with a positive wastewater sample, and 40% were associated with a positive surface sample. The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Passive environmental surveillance can complement approaches that require individual consent, particularly in communities with limited access and/or high rates of testing hesitancy.