IL-17RA-signaling in Lgr5+ intestinal stem cells induces expression of transcription factor ATOH1 to promote secretory cell lineage commitment.

The Th17 cell-lineage-defining cytokine IL-17A contributes to host defense and inflammatory disease by coordinating multicellular immune responses. The IL-17 receptor (IL-17RA) is expressed by diverse intestinal cell types, and therapies targeting IL-17A induce adverse intestinal events, suggesting additional tissue-specific functions. Here, we used multiple conditional deletion models to identify a role for IL-17A in secretory epithelial cell differentiation in the gut. Paneth, tuft, goblet, and enteroendocrine cell numbers were dependent on IL-17A-mediated induction of the transcription factor ATOH1 in Lgr5+ intestinal epithelial stem cells. Although dispensable at steady state, IL-17RA signaling in ATOH1+ cells was required to regenerate secretory cells following injury. Finally, IL-17A stimulation of human-derived intestinal organoids that were locked into a cystic immature state induced ATOH1 expression and rescued secretory cell differentiation. Our data suggest that the cross talk between immune cells and stem cells regulates secretory cell lineage commitment and the integrity of the mucosa.

Comparative meta-omics for identifying pathogens associated with prosthetic joint infection.

Prosthetic joint infections (PJI) are economically and personally costly, and their incidence has been increasing in the United States. Herein, we compared 16S rRNA amplicon sequencing (16S), shotgun metagenomics (MG) and metatranscriptomics (MT) in identifying pathogens causing PJI. Samples were collected from 30 patients, including 10 patients undergoing revision arthroplasty for infection, 10 patients receiving revision for aseptic failure, and 10 patients undergoing primary total joint arthroplasty. Synovial fluid and peripheral blood samples from the patients were obtained at time of surgery. Analysis revealed distinct microbial communities between primary, aseptic, and infected samples using MG, MT, (PERMANOVA p = 0.001), and 16S sequencing (PERMANOVA p < 0.01). MG and MT had higher concordance with culture (83%) compared to 0% concordance of 16S results. Supervised learning methods revealed MT datasets most clearly differentiated infected, primary, and aseptic sample groups. MT data also revealed more antibiotic resistance genes, with improved concordance results compared to MG. These data suggest that a differential and underlying microbial ecology exists within uninfected and infected joints. This study represents the first application of RNA-based sequencing (MT). Further work on larger cohorts will provide opportunities to employ deep learning approaches to improve accuracy, predictive power, and clinical utility.

Arsenic disturbs the gut microbiome of individuals in a disadvantaged community in Nepal.

Arsenic is ubiquitous in nature, highly toxic, and is particularly abundant in Southern Asia. While many studies have focused on areas like Bangladesh and West Bengal, India, disadvantaged regions within Nepal have also suffered from arsenic contamination levels, with wells and other water sources possessing arsenic contamination over the recommended WHO and EPA limit of 10 µg/L, some wells reporting levels as high as 500 µg/L. Despite the region's pronounced arsenic concentrations within community water sources, few investigations have been conducted to understand the impact of arsenic contamination on host gut microbiota health. This study aims to examine differential arsenic exposure on the gut microbiome structure within two disadvantaged communities in southern Nepal. Fecal samples (n = 42) were collected from members of the Mahuawa (n = 20) and Ghanashyampur (n = 22) communities in southern Nepal. The 16S rRNA gene was amplified from fecal samples using Illumina-tag PCR and subject to high-throughput sequencing to generate the bacterial community structure of each sample. Bioinformatics analysis and multivariate statistics were conducted to identify if specific fecal bacterial assemblages and predicted functions were correlated with urine arsenic concentration. Our results revealed unique assemblages of arsenic volatilizing and pathogenic bacteria positively correlated with increased arsenic concentration in individuals within the two respective communities. Additionally, we observed that commensal gut bacteria negatively correlated with increased arsenic concentration in the two respective communities. Our study has revealed that arsenic poses a broader human health risk than was previously known. It is influential in shaping the gut microbiome through its enrichment of arsenic volatilizing and pathogenic bacteria and subsequent depletion of gut commensals. This aspect of arsenic has the potential to debilitate healthy humans by contributing to disorders like heart and liver cancers and diabetes, and it has already been shown to contribute to serious diseases and disorders, including skin lesions, gangrene and several types of skin, renal, lung, and liver cancers in disadvantaged areas of the world like Nepal.