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Background Inflammatory bowel disease (IBD) patients experience recurrent episodes of intestinal inflammation and often follow an unpredictable disease course. Mucosal colonization with adherent-invasive Escherichia coli (AIEC) are believed to perpetuate intestinal inflammation. However, it remains unclear if the 24-year-old AIEC in vitro definition fully predicts mucosal colonization in vivo. To fill this gap, we have developed a novel molecular barcoding approach to distinguish strain variants in the gut and have integrated this approach to explore mucosal colonization of distinct patient-derived E. coli isolates in gnotobiotic mouse models of colitis. Results Germ-free inflammation-susceptible interleukin-10-deficient ( Il10 −/− ) and inflammation-resistant WT mice were colonized with a consortium of AIEC and non-AIEC strains, then given a murine fecal transplant to provide niche competition. E. coli strains isolated from human intestinal tissue were each marked with a unique molecular barcode that permits identification and quantification by barcode-targeted sequencing. 16S rRNA sequencing was used to evaluate the microbiome response to E. coli colonization. Our data reveal that specific AIEC and non-AIEC strains reproducibly colonize the intestinal mucosa of WT and Il10 −/− mice. These E. coli expand in Il10 −/− mice during inflammation and induce compositional dysbiosis to the microbiome in an inflammation-dependent manner. In turn, specific microbes co-evolve in inflamed mice, potentially diversifying E. coli colonization patterns. We observed no selectivity in E. coli colonization patterns in the fecal contents, indicating minimal selective pressure in this niche from host-microbe and interbacterial interactions. Because select AIEC and non-AIEC strains colonize the mucosa, this suggests the in vitro AIEC definition may not fully predict in vivo colonization potential. Further comparison of seven E. coli genomes pinpointed unique genomic features contained only in highly colonizing strains (two AIEC and two non-AIEC). Those colonization-associated features may convey metabolic advantages (e.g., iron acquisition and carbohydrate consumption) to promote efficient mucosal colonization. Conclusions Our findings establish the in vivo mucosal colonizer, not necessarily AIEC, as a principal dysbiosis driver through crosstalk with host and associated microbes. Furthermore, we highlight the utility of high-throughput screens to decode the in vivo colonization dynamics of patient-derived bacteria in murine models. 6LG4zbnj4e64eDS25av5eP Video Abstract

Germ-free (GF) mice, which are depleted of their resident microbiota, are the gold standard for exploring the role of the microbiome in health and disease; however, they are of limited value in the study of human-specific pathogens because they do not support their replication. Here, we develop GF mice systemically reconstituted with human immune cells and use them to evaluate the role of the resident microbiome in the acquisition, replication and pathogenesis of two human-specific pathogens, Epstein–Barr virus (EBV) and human immunodeficiency virus (HIV). Comparison with conventional (CV) humanized mice showed that resident microbiota enhance the establishment of EBV infection and EBV-induced tumorigenesis and increase mucosal HIV acquisition and replication. HIV RNA levels were higher in plasma and tissues of CV humanized mice compared with GF humanized mice. The frequency of CCR5 + CD4 + T cells throughout the intestine was also higher in CV humanized mice, indicating that resident microbiota govern levels of HIV target cells. Thus, resident microbiota promote the acquisition and pathogenesis of two clinically relevant human-specific pathogens. Resident microbiota contribute to HIV and EBV infection in a germ-free humanized mouse model.

As one of Beth Palmer's many close friends, I would like to thank the Citizen for its interest in her story.

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann-Whitney = 1.46×10-5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

The advent of COVID-19 was associated with an upsurge of \"warmlines,\" or telephone lines staffed by non-clinicians that provide non-crisis mental health support. This paper describes a state-funded warmline initiative that was part of a public health approach to mitigating the harms of COVID-19 among people living with mental illness.

Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants. We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes. We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant. Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

OBJECTIVE: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. RESEARCH DESIGN AND METHODS: Via meta-analysis of data from 14 cohorts comprising ~48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. RESULTS: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. CONCLUSIONS: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

OBJECTIVE--Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for [beta]-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants. RESEARCH DESIGN AND METHODS--We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes. RESULTS--We observed a significant association of total zinc intake with lower fasting glucose levels ([beta]-coefficient [+ or -] SE per 1 mg/day of zinc intake: -0.0012 [+ or -] 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC3OA8 rs11558471 variant on fasting glucose levels (p-coefficient [+ or -] SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 [+ or -] 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant. CONCLUSIONS--Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels. Diabetes 60:2407-2416, 2011