Mullengaines3103

Throughout a 24-h period, the small intestine (SI) is exposed to diurnally varying food- and microbiome-derived antigenic burdens but maintains a strict immune homeostasis, which when perturbed in genetically susceptible individuals, may lead to Crohn disease. Herein, we demonstrate that dietary content and rhythmicity regulate the diurnally shifting SI epithelial cell (SIEC) transcriptional landscape through modulation of the SI microbiome. We exemplify this concept with SIEC major histocompatibility complex (MHC) class II, which is diurnally modulated by distinct mucosal-adherent SI commensals, while supporting downstream diurnal activity of intra-epithelial IL-10+ lymphocytes regulating the SI barrier function. Disruption of this diurnally regulated diet-microbiome-MHC class II-IL-10-epithelial barrier axis by circadian clock disarrangement, alterations in feeding time or content, or epithelial-specific MHC class II depletion leads to an extensive microbial product influx, driving Crohn-like enteritis. Collectively, we highlight nutritional features that modulate SI microbiome, immunity, and barrier function and identify dietary, epithelial, and immune checkpoints along this axis to be potentially exploitable in future Crohn disease interventions.The enteric nervous system (ENS) coordinates diverse functions in the intestine but has eluded comprehensive molecular characterization because of the rarity and diversity of cells. Here we develop two methods to profile the ENS of adult mice and humans at single-cell resolution RAISIN RNA-seq for profiling intact nuclei with ribosome-bound mRNA and MIRACL-seq for label-free enrichment of rare cell types by droplet-based profiling. Eloxatin The 1,187,535 nuclei in our mouse atlas include 5,068 neurons from the ileum and colon, revealing extraordinary neuron diversity. We highlight circadian expression changes in enteric neurons, show that disease-related genes are dysregulated with aging, and identify differences between the ileum and proximal/distal colon. In humans, we profile 436,202 nuclei, recovering 1,445 neurons, and identify conserved and species-specific transcriptional programs and putative neuro-epithelial, neuro-stromal, and neuro-immune interactions. The human ENS expresses risk genes for neuropathic, inflammatory, and extra-intestinal diseases, suggesting neuronal contributions to disease.Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗5501 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10-31) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10-47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗5501. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.The contribution of gene-by-environment (GxE) interactions for many human traits and diseases is poorly characterized. We propose a Bayesian whole-genome regression model for joint modeling of main genetic effects and GxE interactions in large-scale datasets, such as the UK Biobank, where many environmental variables have been measured. The method is called LEMMA (Linear Environment Mixed Model Analysis) and estimates a linear combination of environmental variables, called an environmental score (ES), that interacts with genetic markers throughout the genome. The ES provides a readily interpretable way to examine the combined effect of many environmental variables. The ES can be used both to estimate the proportion of phenotypic variance attributable to GxE effects and to test for GxE effects at genetic variants across the genome. GxE effects can induce heteroskedasticity in quantitative traits, and LEMMA accounts for this by using robust standard error estimates when testing for GxE effects. When applied to body mass index, systolic blood pressure, diastolic blood pressure, and pulse pressure in the UK Biobank, we estimate that 9.3%, 3.9%, 1.6%, and 12.5%, respectively, of phenotypic variance is explained by GxE interactions and that low-frequency variants explain most of this variance. We also identify three loci that interact with the estimated environmental scores (-log10p>7.3).Innovations in organoid-based models of human tissues have made them an exciting experimental platform for studying development and disease. However, these models require systematic benchmarking against primary tissue to establish their value. We discuss key parameters that impact the utility of organoid models, primarily focusing on cerebral organoids as examples.COVID-19 has unfortunately halted lab work, conferences, and in-person networking, which is especially detrimental to researchers just starting their labs. Through social media and our reviewer networks, we met some early-career stem cell investigators impacted by the closures. Here, they introduce themselves and their research to our readers.Lineage tracing and single-cell sequencing methods have been used independently to profile fate outcomes or molecular phenotypes, respectively. Weinreb et al. (2020) and Pei et al. (2020) (the latter in this issue of Cell Stem Cell) advance the shared principle that a simultaneous accounting of clonal and transcriptional trajectories provides critical new insights into organization and decision-making in hematopoiesis.