Statin therapy is associated with lower prevalence of gut microbiota dysbiosis.

Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans1,2. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low microbial cell densities1,2, and its prevalence varies from 13% in a general population cohort to as high as 78% in patients with inflammatory bowel disease2. Reported changes in stool consistency3 and inflammation status4 during the progression towards obesity and metabolic comorbidities led us to propose that these developments might similarly correlate with an increased prevalence of the potentially dysbiotic Bact2 enterotype. Here, by exploring obesity-associated microbiota alterations in the quantitative faecal metagenomes of the cross-sectional MetaCardis Body Mass Index Spectrum cohort (n = 888), we identify statin therapy as a key covariate of microbiome diversification. By focusing on a subcohort of participants that are not medicated with statins, we find that the prevalence of Bact2 correlates with body mass index, increasing from 3.90% in lean or overweight participants to 17.73% in obese participants. Systemic inflammation levels in Bact2-enterotyped individuals are higher than predicted on the basis of their obesity status, indicative of Bact2 as a dysbiotic microbiome constellation. We also observe that obesity-associated microbiota dysbiosis is negatively associated with statin treatment, resulting in a lower Bact2 prevalence of 5.88% in statin-medicated obese participants. This finding is validated in both the accompanying MetaCardis cardiovascular disease dataset (n = 282) and the independent Flemish Gut Flora Project population cohort (n = 2,345). The potential benefits of statins in this context will require further evaluation in a prospective clinical trial to ascertain whether the effect is reproducible in a randomized population and before considering their application as microbiota-modulating therapeutics.

Impairment of gut microbial biotin metabolism and host biotin status in severe obesity: effect of biotin and prebiotic supplementation on improved metabolism.

OBJECTIVES: Gut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome's functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation. DESIGN: We performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice. RESULTS: Severe obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration. CONCLUSION: Strategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity. TRIAL REGISTRATION NUMBER: NCT02059538.

Major microbiota dysbiosis in severe obesity: fate after bariatric surgery.

OBJECTIVES: Decreased gut microbial gene richness (MGR) and compositional changes are associated with adverse metabolism in overweight or moderate obesity, but lack characterisation in severe obesity. Bariatric surgery (BS) improves metabolism and inflammation in severe obesity and is associated with gut microbiota modifications. Here, we characterised severe obesity-associated dysbiosis (ie, MGR, microbiota composition and functional characteristics) and assessed whether BS would rescue these changes. DESIGN: Sixty-one severely obese subjects, candidates for adjustable gastric banding (AGB, n=20) or Roux-en-Y-gastric bypass (RYGB, n=41), were enrolled. Twenty-four subjects were followed at 1, 3 and 12 months post-BS. Gut microbiota and serum metabolome were analysed using shotgun metagenomics and liquid chromatography mass spectrometry (LC-MS). Confirmation groups were included. RESULTS: Low gene richness (LGC) was present in 75% of patients and correlated with increased trunk-fat mass and comorbidities (type 2 diabetes, hypertension and severity). Seventy-eight metagenomic species were altered with LGC, among which 50% were associated with adverse body composition and metabolic phenotypes. Nine serum metabolites (including glutarate, 3-methoxyphenylacetic acid and L-histidine) and functional modules containing protein families involved in their metabolism were strongly associated with low MGR. BS increased MGR 1 year postsurgery, but most RYGB patients remained with low MGR 1 year post-BS, despite greater metabolic improvement than AGB patients. CONCLUSIONS: We identified major gut microbiota alterations in severe obesity, which include decreased MGR and related functional pathways linked with metabolic deteriorations. The lack of full rescue post-BS calls for additional strategies to improve the gut microbiota ecosystem and microbiome-host interactions in severe obesity. TRIAL REGISTRATION NUMBER: NCT01454232.

De novo profiling of RNA viruses in Anopheles malaria vector mosquitoes from forest ecological zones in Senegal and Cambodia.

BACKGROUND: Mosquitoes are colonized by a large but mostly uncharacterized natural virome of RNA viruses, and the composition and distribution of the natural RNA virome may influence the biology and immunity of Anopheles malaria vector populations. RESULTS: Anopheles mosquitoes were sampled in malaria endemic forest village sites in Senegal and Cambodia, including Anopheles funestus, Anopheles gambiae group sp., and Anopheles coustani in Senegal, and Anopheles hyrcanus group sp., Anopheles maculatus group sp., and Anopheles dirus in Cambodia. The most frequent mosquito species sampled at both study sites are human malaria vectors. Small and long RNA sequences were depleted of mosquito host sequences, de novo assembled and clustered to yield non-redundant contigs longer than 500 nucleotides. Analysis of the assemblies by sequence similarity to known virus families yielded 115 novel virus sequences, and evidence supports a functional status for at least 86 of the novel viral contigs. Important monophyletic virus clades in the Bunyavirales and Mononegavirales orders were found in these Anopheles from Africa and Asia. The remaining non-host RNA assemblies that were unclassified by sequence similarity to known viruses were clustered by small RNA profiles, and 39 high-quality independent contigs strongly matched a pattern of classic RNAi processing of viral replication intermediates, suggesting they are entirely undescribed viruses. One thousand five hundred sixty-six additional high-quality unclassified contigs matched a pattern consistent with Piwi-interacting RNAs (piRNAs), suggesting that strand-biased piRNAs are generated from the natural virome in Anopheles. To functionally query piRNA effect, we analyzed piRNA expression in Anopheles coluzzii after infection with O'nyong nyong virus (family Togaviridae), and identified two piRNAs that appear to display specifically altered abundance upon arbovirus infection. CONCLUSIONS: Anopheles vectors of human malaria in Africa and Asia are ubiquitously colonized by RNA viruses, some of which are monophyletic but clearly diverged from other arthropod viruses. The interplay between small RNA pathways, immunity, and the virome may represent part of the homeostatic mechanism maintaining virome members in a commensal or nonpathogenic state, and could potentially influence vector competence.

Correction to: De novo profiling of RNA viruses in Anopheles malaria vector mosquitoes from forest ecological zones in Senegal and Cambodia.

Following the publication of this article [1], the authors reported that the original shading in columns 3 and 4 of Table 3, which indicated the presence or absence of viruses in each library, had been removed during typesetting.

Akkermansia muciniphila abundance is lower in severe obesity, but its increased level after bariatric surgery is not associated with metabolic health improvement.

The gut bacterial species Akkermansia muciniphila is associated with a healthier clinical profile. The purpose of this study was to determine the association between A. muciniphila and glucose homeostasis in patients undergoing bariatric surgery (BS): gastric banding (GB) or Roux-en-Y gastric bypass (RYGB). This nonrandomized prospective study included 65 women with severe obesity. Longitudinal analysis included subjects for whom A. muciniphila data were available at follow-up [1, 3, and 12 mo; GB (n = 10) or RYGB (n = 11)]. Glucose homeostasis markers were measured under fasting conditions (glucose, insulin, and HbA1c) or during an oral glucose tolerance test. Fecal microbiota was analyzed using shotgun metagenomics, and A. muciniphila relative abundance was assessed with 16S rRNA quantitative PCR. A. muciniphila relative abundance was significantly lower in severe obesity [mean body mass index, 45.7 kg/m2 (SD 5.4)] than in moderate obesity [33.2 kg/m2 (SD 3.8)] but not associated with glucose homeostasis markers. A significant increase in A. muciniphila relative abundance after RYGB was not correlated with metabolic improvement. Baseline A. muciniphila abundance was correlated with bacterial gene richness and was highest in the high-richness Ruminococcaceae enterotype. A. muciniphila increased in relative abundance after BS in patients with low baseline A. muciniphila abundance, especially those with a Bacteroides type 2 enterotype classification. Although decreased in severe obesity, relative abundance of A. muciniphila was not associated with glucose homeostasis before or after BS. A certain level of A. muciniphila abundance might be required to observe a beneficial link to health. The severity of obesity and gut dysbiosis may partly explain the discrepancy with previous findings in less obese populations.

Elevated serum ceramides are linked with obesity-associated gut dysbiosis and impaired glucose metabolism.

INTRODUCTION: Low gut microbiome richness is associated with dyslipidemia and insulin resistance, and ceramides and other sphingolipids are implicated in the development of diabetes. OBJECTIVES: Determine whether circulating sphingolipids, particularly ceramides, are associated with alterations in the gut microbiome among obese patients with increased diabetes risk. METHODS: This was a cross-sectional and longitudinal retrospective analysis of a dietary/weight loss intervention. Fasted serum was collected from 49 participants (41 women) and analyzed by HPLC-MS/MS to quantify 45 sphingolipids. Shotgun metagenomic sequencing of stool was performed to profile the gut microbiome. RESULTS: Confirming the link to deteriorated glucose homeostasis, serum ceramides were positively correlated with fasting glucose, but inversely correlated with fasting and OGTT-derived measures of insulin sensitivity and ß-cell function. Significant associations with gut dysbiosis were demonstrated, with SM and ceramides being inversely correlated with gene richness. Ceramides with fatty acid chain lengths of 20-24 carbons were the most associated with low richness. Diet-induced weight loss, which improved gene richness, decreased most sphingolipids. Thirty-one MGS, mostly corresponding to unidentified bacteria species, were inversely correlated with ceramides, including a number of Bifidobacterium and Methanobrevibacter smithii. Higher ceramide levels were also associated with increased metagenomic modules for lipopolysaccharide synthesis and flagellan synthesis, two pathogen-associated molecular patterns, and decreased enrichment of genes involved in methanogenesis and bile acid metabolism. CONCLUSION: This study identifies an association between gut microbiota richness, ceramides, and diabetes risk in overweight/obese humans, and suggests that the gut microbiota may contribute to dysregulation of lipid metabolism in metabolic disorders.

Highly focused transcriptional response of Anopheles coluzzii to O'nyong nyong arbovirus during the primary midgut infection.

BACKGROUND: Anopheles mosquitoes are efficient vectors of human malaria, but it is unknown why they do not transmit viruses as well as Aedes and Culex mosquitoes. The only arbovirus known to be consistently transmitted by Anopheles mosquitoes is O'nyong nyong virus (ONNV, genus Alphavirus, family Togaviridae). The interaction of Anopheles mosquitoes with RNA viruses has been relatively unexamined. RESULTS: We transcriptionally profiled the African malaria vector, Anopheles coluzzii, infected with ONNV. Mosquitoes were fed on an infectious bloodmeal and were analyzed by Illumina RNAseq at 3 days post-bloodmeal during the primary virus infection of the midgut epithelium, before systemic dissemination. Virus infection triggers transcriptional regulation of just 30 host candidate genes. Most of the regulated candidate genes are novel, without known function. Of the known genes, a significant cluster includes candidates with predicted involvement in carbohydrate metabolism. Two candidate genes encoding leucine-rich repeat immune (LRIM) factors point to possible involvement of immune protein complexes in the mosquito antiviral response. The primary ONNV infection by bloodmeal shares little transcriptional response in common with ONNV infection by intrathoracic injection, nor with midgut infection by the malaria parasites, Plasmodium falciparum or P. berghei. Profiling of A. coluzzii microRNA (miRNA) identified 118 known miRNAs and 182 potential novel miRNA candidates, with just one miRNA regulated by ONNV infection. This miRNA was not regulated by other previously reported treatments, and may be virus specific. Coexpression analysis of miRNA abundance and messenger RNA expression revealed discrete clusters of genes regulated by Imd and JAK/STAT, immune signaling pathways that are protective against ONNV in the primary infection. CONCLUSIONS: ONNV infection of the A. coluzzii midgut triggers a remarkably limited gene regulation program of mostly novel candidate genes, which likely includes host genes deployed for antiviral defense, as well as genes manipulated by the virus to facilitate infection. Functional dissection of the ONNV-response candidate genes is expected to generate novel insight into the mechanisms of virus-vector interaction.

Updates in Rhea--a manually curated resource of biochemical reactions.

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive and non-redundant resource of expert-curated biochemical reactions described using species from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Rhea has been designed for the functional annotation of enzymes and the description of genome-scale metabolic networks, providing stoichiometrically balanced enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list and additional reactions), transport reactions and spontaneously occurring reactions. Rhea reactions are extensively curated with links to source literature and are mapped to other publicly available enzyme and pathway databases such as Reactome, BioCyc, KEGG and UniPathway, through manual curation and computational methods. Here we describe developments in Rhea since our last report in the 2012 database issue of Nucleic Acids Research. These include significant growth in the number of Rhea reactions and the inclusion of reactions involving complex macromolecules such as proteins, nucleic acids and other polymers that lie outside the scope of ChEBI. Together these developments will significantly increase the utility of Rhea as a tool for the description, analysis and reconciliation of genome-scale metabolic models.

The revisited genome of Pseudomonas putida KT2440 enlightens its value as a robust metabolic chassis.

By the time the complete genome sequence of the soil bacterium Pseudomonas putida KT2440 was published in 2002 (Nelson et al., ) this bacterium was considered a potential agent for environmental bioremediation of industrial waste and a good colonizer of the rhizosphere. However, neither the annotation tools available at that time nor the scarcely available omics data-let alone metabolic modeling and other nowadays common systems biology approaches-allowed them to anticipate the astonishing capacities that are encoded in the genetic complement of this unique microorganism. In this work we have adopted a suite of state-of-the-art genomic analysis tools to revisit the functional and metabolic information encoded in the chromosomal sequence of strain KT2440. We identified 242 new protein-coding genes and re-annotated the functions of 1548 genes, which are linked to almost 4900 PubMed references. Catabolic pathways for 92 compounds (carbon, nitrogen and phosphorus sources) that could not be accommodated by the previously constructed metabolic models were also predicted. The resulting examination not only accounts for some of the known stress tolerance traits known in P. putida but also recognizes the capacity of this bacterium to perform difficult redox reactions, thereby multiplying its value as a platform microorganism for industrial biotechnology.

MicroScope--an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data.

MicroScope is an integrated platform dedicated to both the methodical updating of microbial genome annotation and to comparative analysis. The resource provides data from completed and ongoing genome projects (automatic and expert annotations), together with data sources from post-genomic experiments (i.e. transcriptomics, mutant collections) allowing users to perfect and improve the understanding of gene functions. MicroScope (http://www.genoscope.cns.fr/agc/microscope) combines tools and graphical interfaces to analyse genomes and to perform the manual curation of gene annotations in a comparative context. Since its first publication in January 2006, the system (previously named MaGe for Magnifying Genomes) has been continuously extended both in terms of data content and analysis tools. The last update of MicroScope was published in 2009 in the Database journal. Today, the resource contains data for >1600 microbial genomes, of which ∼300 are manually curated and maintained by biologists (1200 personal accounts today). Expert annotations are continuously gathered in the MicroScope database (∼50 000 a year), contributing to the improvement of the quality of microbial genomes annotations. Improved data browsing and searching tools have been added, original tools useful in the context of expert annotation have been developed and integrated and the website has been significantly redesigned to be more user-friendly. Furthermore, in the context of the European project Microme (Framework Program 7 Collaborative Project), MicroScope is becoming a resource providing for the curation and analysis of both genomic and metabolic data. An increasing number of projects are related to the study of environmental bacterial (meta)genomes that are able to metabolize a large variety of chemical compounds that may be of high industrial interest.

Rhea--a manually curated resource of biochemical reactions.

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive resource of expert-curated biochemical reactions. Rhea provides a non-redundant set of chemical transformations for use in a broad spectrum of applications, including metabolic network reconstruction and pathway inference. Rhea includes enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list), transport reactions and spontaneously occurring reactions. Rhea reactions are described using chemical species from the Chemical Entities of Biological Interest ontology (ChEBI) and are stoichiometrically balanced for mass and charge. They are extensively manually curated with links to source literature and other public resources on metabolism including enzyme and pathway databases. This cross-referencing facilitates the mapping and reconciliation of common reactions and compounds between distinct resources, which is a common first step in the reconstruction of genome scale metabolic networks and models.

Deep learning methods in metagenomics: a review.

The ever-decreasing cost of sequencing and the growing potential applications of metagenomics have led to an unprecedented surge in data generation. One of the most prevalent applications of metagenomics is the study of microbial environments, such as the human gut. The gut microbiome plays a crucial role in human health, providing vital information for patient diagnosis and prognosis. However, analysing metagenomic data remains challenging due to several factors, including reference catalogues, sparsity and compositionality. Deep learning (DL) enables novel and promising approaches that complement state-of-the-art microbiome pipelines. DL-based methods can address almost all aspects of microbiome analysis, including novel pathogen detection, sequence classification, patient stratification and disease prediction. Beyond generating predictive models, a key aspect of these methods is also their interpretability. This article reviews DL approaches in metagenomics, including convolutional networks, autoencoders and attention-based models. These methods aggregate contextualized data and pave the way for improved patient care and a better understanding of the microbiome's key role in our health.

Oral histidine affects gut microbiota and MAIT cells improving glycemic control in type 2 diabetes patients.

Amino acids, metabolized by host cells as well as commensal gut bacteria, have signaling effects on host metabolism. Oral supplementation of the essential amino acid histidine has been shown to exert metabolic benefits. To investigate whether dietary histidine aids glycemic control, we performed a case-controlled parallel clinical intervention study in participants with type 2 diabetes (T2D) and healthy controls. Participants received oral histidine for seven weeks. After 2 weeks of histidine supplementation, the microbiome was depleted by antibiotics to determine the microbial contribution to histidine metabolism. We assessed glycemic control, immunophenotyping of peripheral blood mononucelar cells (PBMC), DNA methylation of PBMCs and fecal gut microbiota composition. Histidine improves several markers of glycemic control, including postprandial glucose levels with a concordant increase in the proportion of MAIT cells after two weeks of histidine supplementation. The increase in MAIT cells was associated with changes in gut microbial pathways such as riboflavin biosynthesis and epigenetic changes in the amino acid transporter SLC7A5. Associations between the microbiome and MAIT cells were replicated in the MetaCardis cohort. We propose a conceptual framework for how oral histidine may affect MAIT cells via altered gut microbiota composition and SLC7A5 expression in MAIT cells directly and thereby influencing glycemic control. Future studies should focus on the role of flavin biosynthesis intermediates and SLC7A5 modulation in MAIT cells to modulate glycemic control.

An updated metabolic view of the Bacillus subtilis 168 genome.

Continuous updating of the genome sequence of Bacillus subtilis, the model of the Firmicutes, is a basic requirement needed by the biology community. In this work new genomic objects have been included (toxin/antitoxin genes and small RNA genes) and the metabolic network has been entirely updated. The curated view of the validated metabolic pathways present in the organism as of 2012 shows several significant differences from pathways present in the other bacterial reference, Escherichia coli: variants in synthesis of cofactors (thiamine, biotin, bacillithiol), amino acids (lysine, methionine), branched-chain fatty acids, tRNA modification and RNA degradation. In this new version, gene products that are enzymes or transporters are explicitly linked to the biochemical reactions of the RHEA reaction resource (http://www.ebi.ac.uk/rhea/), while novel compound entries have been created in the database Chemical Entities of Biological Interest (http://www.ebi.ac.uk/chebi/). The newly annotated sequence is deposited at the International Nucleotide Sequence Data Collaboration with accession number AL009126.4.

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes), a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short). The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

Functional alterations and predictive capacity of gut microbiome in type 2 diabetes.

The gut microbiome plays a significant role in the development of Type 2 Diabetes Mellitus (T2DM), but the functional mechanisms behind this association merit deeper investigation. Here, we used the nanopore sequencing technology for metagenomic analyses to compare the gut microbiome of individuals with T2DM from the United Arab Emirates (n = 40) with that of control (n = 44). DMM enterotyping of the cohort resulted concordantly with previous results, in three dominant groups Bacteroides (K1), Firmicutes (K2), and Prevotella (K3) lineages. The diversity analysis revealed a high level of diversity in the Firmicutes group (K2) both in terms of species richness and evenness (Wilcoxon rank-sum test, p value < 0.05 vs. K1 and K3 groups), consistent with the Ruminococcus enterotype described in Western populations. Additionally, functional enrichment analyses of KEGG modules showed significant differences in abundance between individuals with T2DM and controls (FDR < 0.05). These differences include modules associated with the degradation of amino acids, such as arginine, the degradation of urea as well as those associated with homoacetogenesis. Prediction analysis with the Predomics approach suggested potential biomarkers for T2DM, including a balance between a depletion of Enterococcus faecium and Blautia lineages with an enrichment of Absiella spp or Eubacterium limosum in T2DM individuals, highlighting the potential of metagenomic analysis in predicting predisposition to diabetic cardiomyopathy in T2DM patients.

Protein supplementation changes gut microbial diversity and derived metabolites in subjects with type 2 diabetes.

High-protein diets are promoted for individuals with type 2 diabetes (T2D). However, effects of dietary protein interventions on (gut-derived) metabolites in T2D remains understudied. We therefore performed a multi-center, randomized-controlled, isocaloric protein intervention with 151 participants following either 12-week high-protein (HP; 30Energy %, N = 78) vs. low-protein (LP; 10 Energy%, N = 73) diet. Primary objectives were dietary effects on glycemic control which were determined via glycemic excursions, continuous glucose monitors and HbA1c. Secondary objectives were impact of diet on gut microbiota composition and -derived metabolites which were determined by shotgun-metagenomics and mass spectrometry. Analyses were performed using delta changes adjusting for center, baseline, and kidney function when appropriate. This study found that a short-term 12-week isocaloric protein modulation does not affect glycemic parameters or weight in metformin-treated T2D. However, the HP diet slightly worsened kidney function, increased alpha-diversity, and production of potentially harmful microbiota-dependent metabolites, which may affect host metabolism upon prolonged exposure.

Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide.

The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.

Whole-genome sequence of Stenotrophomonas maltophilia D457, a clinical isolate and a model strain.

Stenotrophomonas maltophilia is an opportunistic pathogen with an environmental origin, and it is an increasingly relevant cause of nosocomial infections. Here we present the whole-genome sequence of S. maltophilia strain D457, a clinical isolate that is being used as a model for studying antibiotic resistance in this bacterial species.