Immunodeficiency Promotes Adaptive Alterations of Host Gut Microbiome: An Observational Metagenomic Study in Mice.
TL;DR: Data regarding the red blood cell (RBC) concentration and serum IgA level during different stages of development support the concept of the microbiota alleviating the advancement of immune deficiency, which is called microbial compensation.
Abstract: The crosstalk between the gut microbiota and immune state of the host is an essential focus in academia and clinics. To explore the dynamic role of the microbiota in response to immune deficiency, we comprehensively assessed the microbiome of 90 mouse fecal samples, across three time points including two immunodeficiency models, namely severe combined immunodeficient (SCID) mice and non-obese diabetic SCID (NOD/SCID) mice, with BALB/cA as a control strain. Metagenomic analysis revealed a decrease in alpha diversity and the existence of a clear structural separation in the microbiota of immunodeficient mice. Although nuances exist between SCID and NOD/SCID mice, an increase in the protective microbiota, in particular Lactobacillus, contributed the most to the discrimination of immunodeficient and control mice. Further data regarding the red blood cell (RBC) concentration and serum IgA level during different stages of development support the concept of the microbiota alleviating the advancement of immune deficiency, which is called microbial compensation. Taken together, these results demonstrate the dynamic impact of immunodeficiency on the gut microbiota and the adaptive alteration of the microbiota that may influence the host state.
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TL;DR: The key factors that affect the formulation of a humanized mouse model representative of the human gut flora are reviewed and several approaches are proposed as to how researchers can effectively design such models for clinical relevance.
Abstract: Considerable evidence points to the critical role of the gut microbiota in physiology and disease. The administration of live microbes as a therapeutic modality is increasingly being considered. However, key questions such as how to identify candidate microorganisms and which preclinical models are relevant to recapitulate human microbiota remain largely unanswered. The establishment of a humanized gnotobiotic mouse model through the fecal microbiota transplantation of human feces into germ-free mice provides an innovative and powerful tool to mimic the human microbial system. However, numerous considerations are required in designing such a model, as various elements, ranging from the factors pertaining to human donors to the mouse genetic background, affect how microbes colonize the gut. Thus, it is critical to match the murine context to that of human donors to provide a continuous and faithful progression of human flora in mice. This is of even greater importance when the need for accuracy and reproducibility across global research groups are taken into account. Here, we review the key factors that affect the formulation of a humanized mouse model representative of the human gut flora and propose several approaches as to how researchers can effectively design such models for clinical relevance.
78 citations
TL;DR: In this article, Mendelian randomization (MR) was used to assess how genetically predicted systemic iron status affected T2D risk using a 2-sample MR analysis to obtain a causal estimate.
Abstract: CONTEXT Iron overload is a known risk factor for type 2 diabetes (T2D); however, iron overload and iron deficiency have both been associated with metabolic disorders in observational studies. OBJECTIVE Using mendelian randomization (MR), we assessed how genetically predicted systemic iron status affected T2D risk. METHODS A 2-sample MR analysis was used to obtain a causal estimate. We selected genetic variants strongly associated (P < 5 × 10-8) with 4 biomarkers of systemic iron status from a study involving 48 972 individuals performed by the Genetics of Iron Status consortium and applied these biomarkers to the T2D case-control study (74 124 cases and 824 006 controls) performed by the Diabetes Genetics Replication and Meta-analysis consortium. The simple median, weighted median, MR-Egger, MR analysis using mixture-model, weighted allele scores, and MR based on a Bayesian model averaging approaches were used for the sensitivity analysis. RESULTS Genetically instrumented serum iron (odds ratio [OR]: 1.07; 95% CI, 1.02-1.12), ferritin (OR: 1.19; 95% CI, 1.08-1.32), and transferrin saturation (OR: 1.06; 95% CI, 1.02-1.09) were positively associated with T2D. In contrast, genetically instrumented transferrin, a marker of reduced iron status, was inversely associated with T2D (OR: 0.91; 95% CI, 0.87-0.96). CONCLUSION Genetic evidence supports a causal link between increased systemic iron status and increased T2D risk. Further studies involving various ethnic backgrounds based on individual-level data and studies regarding the underlying mechanism are warranted for reducing the risk of T2D.
63 citations
TL;DR: The divergent role of two closely related cytokines, IL-12 and IL-23, in shaping immune responses is discussed and a better understanding of the immunological function of these cytokines is pivotal.
Abstract: In this review we discuss the divergent role of two closely related cytokines, IL-12 and IL-23, in shaping immune responses In light of current therapeutic developments using biologic agents to block these two pathways, a better understanding of the immunological function of these cytokines is pivotal
31 citations
TL;DR: In this paper, a metagenomic approach enabled the taxonomic and functional identification of the microbial community and associated genes detected in colorectal cancer specimens and the most remarkable differences between tumors and healthy tissue was the significant increase in the genus Fusobacterium in the former, in particular the species F. nucleatum, as well as Camplylobacter or Bacteroides fragilis, in accordance with previous studies of CRC.
Abstract: An increased risk of developing colorectal cancer (CRC) and other types of tumor is associated to Lynch syndrome (LS), an inherited condition caused by germline mutations in mismatch repair genes. We selected a cohort of LS patients that had developed CRC and had undergone surgical resection. Formalin-fixed paraffin embedded (FFPE) tissue blocks from matched colorectal and normal mucosa were used for genomic DNA extraction with a commercial kit and sequenced by high-throughput sequencing. A metagenomic approach enabled the taxonomic and functional identification of the microbial community and associated genes detected in the specimens. Slightly lower taxonomic diversity was observed in the tumor compared to the non-tumor tissue. Furthermore, the most remarkable differences between tumors and healthy tissue was the significant increase in the genus Fusobacterium in the former, in particular the species F. nucleatum, as well as Camplylobacter or Bacteroides fragilis, in accordance with previous studies of CRC. However, unlike prior studies, the present work is not based on directed detection by qPCR but instead uses a metagenomic approach to retrieve the whole bacterial community, and addresses the additional difficulty of using long-term stored FFPE samples.
20 citations
TL;DR: In this paper, the authors investigated the short-term association between ambient temperature and mental health hospitalizations in Bern, Switzerland, and found that the hospitalization risk increased linearly by 4.0% for every 10°C increase in mean daily temperature.
Abstract: Background Psychiatric disorders constitute a major public health concern that are associated with substantial health and socioeconomic burden. Psychiatric patients may be more vulnerable to high temperatures, which under current climate change projections will most likely increase the burden of this public health concern. Objective This study investigated the short-term association between ambient temperature and mental health hospitalizations in Bern, Switzerland. Methods Daily hospitalizations for mental disorders between 1973 and 2017 were collected from the University Hospital of Psychiatry and Psychotherapy in Bern. Population-weighted daily mean ambient temperatures were derived for the catchment area of the hospital from 2.3-km gridded weather maps. Conditional quasi-Poisson regression with distributed lag linear models were applied to assess the association up to three days after the exposure. Stratified analyses were conducted by age, sex, and subdiagnosis, and by subperiods (1973–1989 and 1990–2017). Additional subanalyses were performed to assess whether larger risks were found during the warm season or were due to heatwaves. Results The study included a total number of 88,996 hospitalizations. Overall, the hospitalization risk increased linearly by 4.0% (95% CI 2.0%, 7.0%) for every 10°C increase in mean daily temperature. No evidence of a nonlinear association or larger risks during the warm season or heatwaves was found. Similar estimates were found across for all sex and age categories, and larger risks were found for hospitalizations related to developmental disorders (29.0%; 95% CI 9.0%, 54.0%), schizophrenia (10.0%; 95% CI 4.0%, 15.0%), and for the later rather than the earlier period (5.0%; 95% CI 2.0%, 8.0% vs. 2.0%; 95% CI -3.0%, 8.0%). Conclusions Our findings suggest that increasing temperatures could negatively affect mental status in psychiatric patients. Specific public health policies are urgently needed to protect this vulnerable population from the effects of climate change.
15 citations
References
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TL;DR: An overview of the analysis pipeline and links to raw data and processed output from the runs with and without denoising are provided.
Abstract: Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.
28,911 citations
TL;DR: A new method for metagenomic biomarker discovery is described and validates by way of class comparison, tests of biological consistency and effect size estimation to address the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities.
Abstract: This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
9,057 citations
TL;DR: The results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.
Abstract: Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.
6,860 citations
"Immunodeficiency Promotes Adaptive ..." refers methods in this paper
...Microbial functions were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software (Langille et al., 2013)....
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TL;DR: MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance.
Abstract: Assessment and characterization of gut microbiota has become a major research area in human disease, including type 2 diabetes, the most prevalent endocrine disease worldwide. To carry out analysis on gut microbial content in patients with type 2 diabetes, we developed a protocol for a metagenome-wide association study (MGWAS) and undertook a two-stage MGWAS based on deep shotgun sequencing of the gut microbial DNA from 345 Chinese individuals. We identified and validated approximately 60,000 type-2-diabetes-associated markers and established the concept of a metagenomic linkage group, enabling taxonomic species-level analyses. MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance. An analysis of 23 additional individuals demonstrated that these gut microbial markers might be useful for classifying type 2 diabetes.
4,981 citations
TL;DR: The authors showed that colonisation of mice with a segmented filamentous bacterium (SFB) is sufficient to induce the appearance of CD4+ T helper cells that produce IL-17 and IL-22 (Th17 cells) in the lamina propria.
3,860 citations
"Immunodeficiency Promotes Adaptive ..." refers background in this paper
...Studies on segmented filamentous bacteria (SFB) revealed the role of the microbiota in Th17 cell induction, causing autoimmune arthritis in susceptible mice (Ivanov et al., 2009)....
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