Impact of omega-3 fatty acids on hypertriglyceridemia, lipidomics, and gut microbiome in patients with type 2 diabetes.

BACKGROUND: Fish oil (FO), a mixture of omega-3 fatty acids mainly comprising docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), has been recommended for patients with type 2 diabetes (T2D) and hypertriglyceridemia. However, its effects on lipidomic profiles and gut microbiota and the factors influencing triglyceride (TG) reduction remain unclear. METHODS: We conducted a 12-week, randomized, double-blind, placebo-controlled trial in 309 Chinese patients with T2D with hypertriglyceridemia (ClinicalTrials.gov: NCT03120299). Participants were randomly assigned (1:1) to receive either 4 g FO or corn oil for 12 weeks. The primary outcome was changes in serum TGs and the lipidomic profile, and the secondary outcome included changes in the gut microbiome and other metabolic variables. FINDINGS: The FO group had significantly better TG reduction (mean [95% confidence interval (CI)]: -1.51 [-2.01, -1.01] mmol/L) compared to the corn oil group (-0.66 [-1.15, -0.16] mmol/L, p = 0.02). FO significantly altered the serum lipid profile by reducing low-unsaturated TG species and increasing those containing DHA or EPA. FO had minor effects on gut microbiota, while baseline microbial features predicted the TG response to FO better than phenotypic or lipidomic features, potentially mediated by specific lipid metabolites. A total of 9 lipid metabolites significantly mediated the link between 4 baseline microbial variables and the TG response to FO supplementation. CONCLUSIONS: Our findings demonstrate differential impacts of omega-3 fatty acids on lipidomic and microbial profiles in T2D and highlight the importance of baseline gut microbiota characteristics in predicting the TG-lowering efficacy of FO. FUNDING: This study was funded by the National Nature Science Foundation.

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption.

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

Deciphering unique and shared interactions between the human gut microbiota and oral antidiabetic drugs.

The administration of oral antidiabetic drugs (OADs) to patients with type 2 diabetes elicits distinct and shared changes in the gut microbiota, with acarbose and berberine exhibiting greater impacts on the gut microbiota than metformin, vildagliptin, and glipizide. The baseline gut microbiota strongly associates with treatment responses of OADs.

Divergent age-associated and metabolism-associated gut microbiome signatures modulate cardiovascular disease risk.

Insight into associations between the gut microbiome with metabolism and aging is crucial for tailoring interventions to promote healthy longevity. In a discovery cohort of 10,207 individuals aged 40-93 years, we used 21 metabolic parameters to classify individuals into five clusters, termed metabolic multimorbidity clusters (MCs), that represent different metabolic subphenotypes. Compared to the cluster classified as metabolically healthy (MC1), clusters classified as 'obesity-related mixed' (MC4) and 'hyperglycemia' (MC5) exhibited an increased 11.1-year cardiovascular disease (CVD) risk by 75% (multivariable-adjusted hazard ratio (HR): 1.75, 95% confidence interval (CI): 1.43-2.14) and by 117% (2.17, 1.72-2.74), respectively. These associations were replicated in a second cohort of 9,061 individuals with a 10.0-year follow-up. Based on analysis of 4,491 shotgun fecal metagenomes from the discovery cohort, we found that gut microbial composition was associated with both MCs and age. Next, using 55 age-specific microbial species to capture biological age, we developed a gut microbial age (MA) metric, which was validated in four external cohorts comprising 4,425 metagenomic samples. Among individuals aged 60 years or older, the increased CVD risk associated with MC4 or MC5, as compared to MC1, MC2 or MC3, was exacerbated in individuals with high MA but diminished in individuals with low MA, independent of age, sex and other lifestyle and dietary factors. This pattern, in which younger MA appears to counteract the CVD risk attributable to metabolic dysfunction, implies a modulating role of MA in cardiovascular health for metabolically unhealthy older people.

Consistent signatures in the human gut microbiome of old- and young-onset colorectal cancer.

The incidence of young-onset colorectal cancer (yCRC) has been increasing in recent decades, but little is known about the gut microbiome of these patients. Most studies have focused on old-onset CRC (oCRC), and it remains unclear whether CRC signatures derived from old patients are valid in young patients. To address this, we assembled the largest yCRC gut metagenomes to date from two independent cohorts and found that the CRC microbiome had limited association with age across adulthood. Differential analysis revealed that well-known CRC-associated taxa, such as Clostridium symbiosum, Peptostreptococcus stomatis, Parvimonas micra and Hungatella hathewayi were significantly enriched (false discovery rate <0.05) in both old- and young-onset patients. Similar strain-level patterns of Fusobacterium nucleatum, Bacteroides fragilis and Escherichia coli were observed for oCRC and yCRC. Almost all oCRC-associated metagenomic pathways had directionally concordant changes in young patients. Importantly, CRC-associated virulence factors (fadA, bft) were enriched in both oCRC and yCRC compared to their respective controls. Moreover, the microbiome-based classification model had similar predication accuracy for CRC status in old- and young-onset patients, underscoring the consistency of microbial signatures across different age groups.

Cushing Syndrome Is Associated With Gut Microbial Dysbiosis and Cortisol-Degrading Bacteria.

CONTEXT: Cushing syndrome (CS) is a severe endocrine disease characterized by excessive secretion of cortisol with multiple metabolic disorders. While gut microbial dysbiosis plays a vital role in metabolic disorders, the role of gut microbiota in CS remains unclear. OBJECTIVE: The objective of this work is to examine the alteration of gut microbiota in patients with CS. METHODS: We performed shotgun metagenomic sequencing of fecal samples from 78 patients with CS and 78 healthy controls matched for age and body mass index. Furthermore, we verify the cortisol degradation capacity of Ruminococcus gnavus in vitro and identify the potential metabolite by LC-MC/MS. RESULTS: We observed significant differences in microbial composition between CS and controls in both sexes, with CS showing reduced Bacteroidetes (Bacteroides vulgatus) and elevated Firmicutes (Erysipelotrichaceae_bacterium_6_1_45) and Proteobacteria (Enterobacter cloacae). Despite distinct causes of hypercortisolism in ACTH-dependent and ACTH-independent CS, we found no significant differences in metabolic profiles or gut microbiota between the 2 subgroups. Furthermore, we identified a group of gut species, including R. gnavus, that were positively correlated with cortisol levels in CS. These bacteria were found to harbor cortisol-degrading desAB genes and were consistently enriched in CS. Moreover, we demonstrated the efficient capacity of R. gnavus to degrade cortisol to 11-oxygenated androgens in vitro. CONCLUSION: This study provides evidence of gut microbial dysbiosis in patients with CS and identifies a group of CS-enriched bacteria capable of degrading cortisol. These findings highlight the potential role of gut microbiota in regulating host steroid hormone levels, and consequently host health.

Effects of Lifetime Exposures to Environmental Contaminants on the Adult Gut Microbiome.

Emerging experimental evidence indicates that toxicant-induced alterations in gut microbiota composition and activity may affect host homeostasis. However, data from human studies are scarce; to our knowledge, no previous studies have quantified the association of lifetime exposure to environmental chemicals, across multiple time points, with the composition of the adult gut microbiome. Here we studied 124 individuals born in the Faroe Islands in 1986-1987 who were followed approximately every seven years from birth through age 28 years. Organochlorine compounds, including polychlorinated biphenyls (PCBs) and pesticides, perfluoroalkyl substances (PFAS), and mercury (Hg), were measured in cord blood and longitudinally in participants' blood. At age 28, the gut microbiome was assessed using shotgun metagenomic sequencing. Historical contaminant exposures had little direct effect on the adult gut microbiome, while a small number of fastidious anaerobes were weakly linked to recent PFAS/PFOS exposures at age 28. In this cohort, our findings suggest no lasting effects of early life exposures on adult gut microbial composition, but proximal exposures may contribute to gut microbiome alterations. The methods developed and used for this investigation may help in future identification of small but lasting impacts of environmental toxicant exposure on the gut microbiome.

Metagenomic analysis reveals crosstalk between gut microbiota and glucose-lowering drugs targeting the gastrointestinal tract in Chinese patients with type 2 diabetes: a 6 month, two-arm randomised trial.

AIMS/HYPOTHESIS: The use of oral glucose-lowering drugs, particularly those designed to target the gut ecosystem, is often observed in association with altered gut microbial composition or functional capacity in individuals with type 2 diabetes. The gut microbiota, in turn, plays crucial roles in the modulation of drug efficacy. We aimed to assess the impacts of acarbose and vildagliptin on human gut microbiota and the relationships between pre-treatment gut microbiota and therapeutic responses. METHODS: This was a randomised, open-labelled, two-arm trial in treatment-naive type 2 diabetes patients conducted in Beijing between December 2016 and December 2017. One hundred participants with overweight/obesity and newly diagnosed type 2 diabetes were recruited from the Pinggu Hospital and randomly assigned to the acarbose (n=50) or vildagliptin (n=50) group using sealed envelopes. The treatment period was 6 months. Blood, faecal samples and visceral fat data from computed tomography images were collected before and after treatments to measure therapeutic outcomes and gut microbiota. Metagenomic datasets from a previous type 2 diabetes cohort receiving acarbose or glipizide for 3 months were downloaded and processed. Statistical analyses were applied to identify the treatment-related changes in clinical variables, gut microbiota and associations. RESULTS: Ninety-two participants were analysed. After 6 months of acarbose (n=44) or vildagliptin (n=48) monotherapy, both groups achieved significant reductions in HbA1c (from 60 to 46 mmol/mol [from 7.65% to 6.40%] in the acarbose group and from 59 to 44 mmol/mol [from 7.55% to 6.20%] in the vildagliptin group) and visceral fat areas (all adjusted p values for pre-post comparisons <0.05). Both arms showed drug-specific and shared changes in relative abundances of multiple gut microbial species and pathways, especially the common reductions in Bacteroidetes species. Three months and 6 months of acarbose-induced changes in microbial composition were highly similar in type 2 diabetes patients from the two independent studies. Vildagliptin treatment significantly enhanced fasting active glucagon-like peptide-1 (GLP-1) levels. Baseline gut microbiota, rather than baseline GLP-1 levels, were strongly associated with GLP-1 response to vildagliptin, and to a lesser extent with GLP-1 response to acarbose. CONCLUSIONS/INTERPRETATION: This study reveals common microbial responses in type 2 diabetes patients treated with two glucose-lowering drugs targeting the gut differently and acceptable performance of baseline gut microbiota in classifying individuals with different GLP-1 responses to vildagliptin. Our findings highlight bidirectional interactions between gut microbiota and glucose-lowering drugs. TRIAL REGISTRATION: ClinicalTrials.gov NCT02999841 FUNDING: National Key Research and Development Project: 2016YFC1304901.

Distinct Functional Metagenomic Markers Predict the Responsiveness to Anti-PD-1 Therapy in Chinese Non-Small Cell Lung Cancer Patients.

Background: Programmed death 1 (PD-1) and the ligand of PD-1 (PD-L1) are central targets for immune-checkpoint therapy (ICT) blocking immune evasion-related pathways elicited by tumor cells. A number of PD-1 inhibitors have been developed, but the efficacy of these inhibitors varies considerably and is typically below 50%. The efficacy of ICT has been shown to be dependent on the gut microbiota, and experiments using mouse models have even demonstrated that modulation of the gut microbiota may improve efficacy of ICT. Methods: We followed a Han Chinese cohort of 85 advanced non-small cell lung cancer (NSCLC) patients, who received anti-PD-1 antibodies. Tumor biopsies were collected before treatment initiation for whole exon sequencing and variant detection. Fecal samples collected biweekly during the period of anti-PD-1 antibody administration were used for metagenomic sequencing. We established gut microbiome abundance profiles for identification of significant associations between specific microbial taxa, potential functionality, and treatment responses. A prediction model based on random forest was trained using selected markers discriminating between the different response groups. Results: NSCLC patients treated with antibiotics exhibited the shortest survival time. Low level of tumor-mutation burden and high expression level of HLA-E significantly reduced progression-free survival. We identified metagenomic species and functional pathways that differed in abundance in relation to responses to ICT. Data on differential enrichment of taxa and predicted microbial functions in NSCLC patients responding or non-responding to ICT allowed the establishment of random forest algorithm-adopted models robustly predicting the probability of whether or not a given patient would benefit from ICT. Conclusions: Overall, our results identified links between gut microbial composition and immunotherapy efficacy in Chinese NSCLC patients indicating the potential for such analyses to predict outcome prior to ICT.

Combined berberine and probiotic treatment as an effective regimen for improving postprandial hyperlipidemia in type 2 diabetes patients: a double blinded placebo controlled randomized study.

Non-fasting lipidemia (nFL), mainly contributed by postprandial lipidemia (PL), has recently been recognized as an important cardiovascular disease (CVD) risk as fasting lipidemia (FL). PL serves as a common feature of dyslipidemia in Type 2 Diabetes (T2D), albeit effective therapies targeting on PL were limited. In this study, we aimed to evaluate whether the therapy combining probiotics (Prob) and berberine (BBR), a proven antidiabetic and hypolipidemic regimen via altering gut microbiome, could effectively reduce PL in T2D and to explore the underlying mechanism. Blood PL (120 min after taking 100 g standard carbohydrate meal) was examined in 365 participants with T2D from the Probiotics and BBR on the Efficacy and Change of Gut Microbiota in Patients with Newly Diagnosed Type 2 Diabetes (PREMOTE study), a random, placebo-controlled, and multicenter clinical trial. Prob+BBR was superior to BBR or Prob alone in improving postprandial total cholesterol (pTC) and low-density lipoprotein cholesterol (pLDLc) levels with decrement of multiple species of postprandial lipidomic metabolites after 3 months follow-up. This effect was linked to the changes of fecal Bifidobacterium breve level responding to BBR alone or Prob+BBR treatment. Four fadD genes encoding long-chain acyl-CoA synthetase were identified in the genome of this B. breve strain, and transcriptionally activated by BBR. In vitro BBR treatment further decreased the concentration of FFA in the culture medium of B. breve compared to vehicle. Thus, the activation of fadD by BBR could enhance FFA import and mobilization in B. breve and diliminish the intraluminal lipids for absorption to mediate the effect of Prob+BBR on PL. Our study confirmed that BBR and Prob (B. breve) could exert a synergistic hypolipidemic effect on PL, acting as a gut lipid sink to achieve better lipidemia and CVD risk control in T2D.

Network of Interactions Between Gut Microbiome, Host Biomarkers, and Urine Metabolome in Carotid Atherosclerosis.

Comprehensive analyses of multi-omics data may provide insights into interactions between different biological layers concerning distinct clinical features. We integrated data on the gut microbiota, blood parameters and urine metabolites of treatment-naive individuals presenting a wide range of metabolic disease phenotypes to delineate clinically meaningful associations. Trans-omics correlation networks revealed that candidate gut microbial biomarkers and urine metabolite feature were covaried with distinct clinical phenotypes. Integration of the gut microbiome, the urine metabolome and the phenome revealed that variations in one of these three systems correlated with changes in the other two. In a specific note about clinical parameters of liver function, we identified Eubacteriumeligens, Faecalibacteriumprausnitzii and Ruminococcuslactaris to be associated with a healthy liver function, whereas Clostridium bolteae, Tyzzerellanexills, Ruminococcusgnavus, Blautiahansenii, and Atopobiumparvulum were associated with blood biomarkers for liver diseases. Variations in these microbiota features paralleled changes in specific urine metabolites. Network modeling yielded two core clusters including one large gut microbe-urine metabolite close-knit cluster and one triangular cluster composed of a gut microbe-blood-urine network, demonstrating close inter-system crosstalk especially between the gut microbiome and the urine metabolome. Distinct clinical phenotypes are manifested in both the gut microbiome and the urine metabolome, and inter-domain connectivity takes the form of high-dimensional networks. Such networks may further our understanding of complex biological systems, and may provide a basis for identifying biomarkers for diseases. Deciphering the complexity of human physiology and disease requires a holistic and trans-omics approach integrating multi-layer data sets, including the gut microbiome and profiles of biological fluids. By studying the gut microbiome on carotid atherosclerosis, we identified microbial features associated with clinical parameters, and we observed that groups of urine metabolites correlated with groups of clinical parameters. Combining the three data sets, we revealed correlations of entities across the three systems, suggesting that physiological changes are reflected in each of the omics. Our findings provided insights into the interactive network between the gut microbiome, blood clinical parameters and the urine metabolome concerning physiological variations, and showed the promise of trans-omics study for biomarker discovery.

Characterization of respiratory microbial dysbiosis in hospitalized COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, the microbial composition of the respiratory tract and other infected tissues as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Between 27 January and 26 February 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients in Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. We identified distinct signatures of microbial dysbiosis among severely ill COVID-19 patients on broad spectrum antimicrobial therapy. Co-detection of other human respiratory viruses (including human alphaherpesvirus 1, rhinovirus B, and human orthopneumovirus) was demonstrated in 30.8% (4/13) of the severely ill patients, but not in any of the mildly affected patients. Notably, the predominant respiratory microbial taxa of severely ill patients were Burkholderia cepacia complex (BCC), Staphylococcus epidermidis, or Mycoplasma spp. (including M. hominis and M. orale). The presence of the former two bacterial taxa was also confirmed by clinical cultures of respiratory specimens (expectorated sputum or nasal secretions) in 23.1% (3/13) of the severe cases. Finally, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes was demonstrated in one severely ill patient, which might accelerate his disease deterioration and death occurring one month after ICU admission. Our findings point to SARS-CoV-2-related microbial dysbiosis and various antibiotic-resistant respiratory microbes/pathogens in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking strategies are needed to prevent the spread of antimicrobial resistance, improve the treatment regimen and clinical outcomes of hospitalized, severely ill COVID-19 patients.

Global Landscape of Clostridioides Difficile Phylogeography, Antibiotic Susceptibility, and Toxin Polymorphisms by Post-Hoc Whole-Genome Sequencing from the MODIFY I/II Studies.

INTRODUCTION: Clostridioides (Clostridium) difficile infection, the leading cause of healthcare-associated diarrhea, represents a significant burden on global healthcare systems. Despite being a global issue, information on C. difficile from a global perspective is lacking. The aim of this study is to model the global phylogeography of clinical C. difficile. METHODS: Using samples collected from the MODIFY I and II studies (NCT01241552, NCT01513239), we performed whole-genome sequencing of 1501 clinical isolates including 37 novel sequence types (STs), representing the largest worldwide collection to date. RESULTS: Our data showed ribotypes, multi-locus sequence typing clades, and whole-genome phylogeny were in good accordance. The clinical C. difficile genome was found to be more conserved than previously reported (61% core genes), and modest recombination rates of 1.4-5.0 were observed across clades. We observed a significant continent distribution preference among five C. difficile clades (Benjamini-Hochberg corrected Fisher's exact test P < 0.01); moreover, weak association between geographic and genetic distance among ribotypes suggested sources beyond healthcare-related transmission. Markedly different trends of antibiotic susceptibility among lineages and regions were identified, and three novel mutations (in pyridoxamine 5'-phosphate oxidase family protein: Tyr130Ser, Tyr130Cys, and a promoter SNP) associated with metronidazole-reduced susceptibility were discovered on a nim-related gene and its promotor by genome-wide association study. Toxin gene polymorphisms were shown to vary within and between prevalent ribotypes, and novel severe mutations were found on the tcdC toxin regulator protein. CONCLUSION: Our systematic characterization of a global set of clinical trial C. difficile isolates from infected individuals demonstrated the complexity of the genetic makeup of this pathogenic organism. The geographic variability of clades, variability in toxin genes, and mutations associated with antibiotic susceptibility indicate a highly complex interaction of C. difficile between host and environment. This dataset will provide a useful resource for validation of findings and future research of C. difficile.

Population Bottlenecks and Intra-host Evolution During Human-to-Human Transmission of SARS-CoV-2.

The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions.

A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases.

The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological, and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top two loci explaining 11% of the Prevotella-Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Our two-stage metagenome genome-wide association studies on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.

Intra-host variation and evolutionary dynamics of SARS-CoV-2 populations in COVID-19 patients.

BACKGROUND: Since early February 2021, the causative agent of COVID-19, SARS-CoV-2, has infected over 104 million people with more than 2 million deaths according to official reports. The key to understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of mutation and evolution of this virus at both inter- and intra-host levels. However, despite quite a few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and their evolutionary dynamics remain mostly unknown. METHODS: Using high-throughput sequencing of metatranscriptomic and hybrid captured libraries, we characterized consensus genomes and intra-host single nucleotide variations (iSNVs) of serial samples collected from eight patients with COVID-19. The distribution of iSNVs along the SARS-CoV-2 genome was analyzed and co-occurring iSNVs among COVID-19 patients were identified. We also compared the evolutionary dynamics of SARS-CoV-2 population in the respiratory tract (RT) and gastrointestinal tract (GIT). RESULTS: The 32 consensus genomes revealed the co-existence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in a single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparing allele frequencies of the iSNVs revealed a clear genetic differentiation between intra-host populations from the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events during intra-host migrations. Compared to RT populations, the GIT populations showed a better maintenance and rapid development of viral genetic diversity following the suspected intra-host bottlenecks. CONCLUSIONS: Our findings here illustrate the intra-host bottlenecks and evolutionary dynamics of SARS-CoV-2 in different anatomic sites and may provide new insights to understand the virus-host interactions of coronaviruses and other RNA viruses.

An Expanded Gene Catalog of Mouse Gut Metagenomes.

High-quality and comprehensive reference gene catalogs are essential for metagenomic research. The rather low diversity of samples used to construct existing catalogs of the mouse gut metagenome limits the numbers of identified genes in existing catalogs. We therefore established an expanded catalog of genes in the mouse gut metagenome (EMGC) containing >5.8 million genes by integrating 88 newly sequenced samples, 86 mouse gut-related bacterial genomes, and 3 existing gene catalogs. EMGC increases the number of nonredundant genes by more than 1 million genes compared to the so-far most extensive catalog. More than 60% of the genes in EMGC were assigned to Bacteria, with 54.20% being assigned to a phylum and 35.33% to a genus, while 30.39% were annotated at the KEGG orthology level. Nine hundred two metagenomic species (MGS) assigned to 122 taxa are identified based on the EMGC. The EMGC-based analysis of samples from groups of mice originating from different animal providers, housing laboratories, and genetic strains substantiated that diet is a major contributor to differences in composition and functional potential of the gut microbiota irrespective of differences in environment and genetic background. We envisage that EMGC will serve as a valuable reference data set for future metagenomic studies in mice.IMPORTANCE We established an expanded gene catalog of the mouse gut metagenome not only to increase the sample size compared to that in existing catalogs but also to provide a more comprehensive reference data set of the mouse gut microbiome for bioinformatic analysis. The expanded gene catalog comprises more than 5.8 million unique genes, as well as a wide range of taxonomic and functional information. Particularly, the analysis of metagenomic species with the expanded gene catalog reveals a great novelty of mouse gut-inhabiting microbial species. We envisage that the expanded gene catalog of the mouse gut metagenome will serve as a valuable bioinformatic resource for future gut metagenomic studies in mice.

Sex- and age-related trajectories of the adult human gut microbiota shared across populations of different ethnicities.

Lifelong sex- and age-related trajectories of the human gut microbiota remain largely unexplored. Using metagenomics, we derived the gut microbial composition of 2,338 adults (26-76 years) from a Han Chinese population-based cohort where metabolic health, hormone levels and aspects of their lifestyles were also recorded. In this cohort, and in three independent cohorts distributed across China, Israel and the Netherlands, we observed sex differences in the gut microbial composition and a shared age-related decrease in sex-dependent differences in gut microbiota. Compared to men, the gut microbiota of premenopausal women exhibited higher microbial diversity and higher abundances of multiple species known to have beneficial effects on host metabolism. We also found consistent sex-independent, age-related gut microbial characteristics across all populations, with the presence of members of the oral microbiota being the strongest indicator of older chronological age. Our findings highlight the existence of sex- and age-related trajectories in the human gut microbiota that are shared between populations of different ethnicities and emphasize the pivotal links between sex hormones, gut microbiota and host metabolism.

Gut microbiome-related effects of berberine and probiotics on type 2 diabetes (the PREMOTE study).

Human gut microbiome is a promising target for managing type 2 diabetes (T2D). Measures altering gut microbiota like oral intake of probiotics or berberine (BBR), a bacteriostatic agent, merit metabolic homoeostasis. We hence conducted a randomized, double-blind, placebo-controlled trial with newly diagnosed T2D patients from 20 centres in China. Four-hundred-nine eligible participants were enroled, randomly assigned (1:1:1:1) and completed a 12-week treatment of either BBR-alone, probiotics+BBR, probiotics-alone, or placebo, after a one-week run-in of gentamycin pretreatment. The changes in glycated haemoglobin, as the primary outcome, in the probiotics+BBR (least-squares mean [95% CI], -1.04[-1.19, -0.89]%) and BBR-alone group (-0.99[-1.16, -0.83]%) were significantly greater than that in the placebo and probiotics-alone groups (-0.59[-0.75, -0.44]%, -0.53[-0.68, -0.37]%, P < 0.001). BBR treatment induced more gastrointestinal side effects. Further metagenomics and metabolomic studies found that the hypoglycaemic effect of BBR is mediated by the inhibition of DCA biotransformation by Ruminococcus bromii. Therefore, our study reports a human microbial related mechanism underlying the antidiabetic effect of BBR on T2D. (Clinicaltrial.gov Identifier: NCT02861261).

Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples.

BACKGROUND: COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. METHODS: We applied a novel multiplex PCR amplicon (amplicon)-based and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. RESULTS: We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. CONCLUSIONS: This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses.