Manimozhiyan Arumugam

A human gut microbial gene catalogue established by metagenomic sequencing

To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ∼150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively.

Enterotypes of the human gut microbiome

Our knowledge of species and functional composition of the human gut microbiome is rapidly increasing, but it is still based on very few cohorts and little is known about variation across the world. By combining 22 newly sequenced faecal metagenomes of individuals from four countries with previously published data sets, here we identify three robust clusters (referred to as enterotypes hereafter) that are not nation or continent specific. We also confirmed the enterotypes in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous. This indicates further the existence of a limited number of well-balanced host–microbial symbiotic states that might respond differently to diet and drug intake. The enterotypes are mostly driven by species composition, but abundant molecular functions are not necessarily provided by abundant species, highlighting the importance of a functional analysis to understand microbial communities. Although individual host properties such as body mass index, age, or gender cannot explain the observed enterotypes, data-driven marker genes or functional modules can be identified for each of these host properties. For example, twelve genes significantly correlate with age and three functional modules with the body mass index, hinting at a diagnostic potential of microbial markers.

Richness of human gut microbiome correlates with metabolic markers

We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.

An integrated catalog of reference genes in the human gut microbiome

Many analyses of the human gut microbiome depend on a catalog of reference genes. Existing catalogs for the human gut microbiome are based on samples from single cohorts or on reference genomes or protein sequences, which limits coverage of global microbiome diversity. Here we combined 249 newly sequenced samples of the Metagenomics of the Human Intestinal Tract (MetaHit) project with 1,018 previously sequenced samples to create a cohort from three continents that is at least threefold larger than cohorts used for previous gene catalogs. From this we established the integrated gene catalog (IGC) comprising 9,879,896 genes. The catalog includes close-to-complete sets of genes for most gut microbes, which are also of considerably higher quality than in previous catalogs. Analyses of a group of samples from Chinese and Danish individuals using the catalog revealed country-specific gut microbial signatures. This expanded catalog should facilitate quantitative characterization of metagenomic, metatranscriptomic and metaproteomic data from the gut microbiome to understand its variation across populations in human health and disease.

Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota

Citing this paper Please note that where the full-text provided on Kings Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publishers definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publishers website for any subsequent corrections.In recent years, several associations between common chronic human disorders and altered gut microbiome composition and function have been reported. In most of these reports, treatment regimens were not controlled for and conclusions could thus be confounded by the effects of various drugs on the microbiota, which may obscure microbial causes, protective factors or diagnostically relevant signals. Our study addresses disease and drug signatures in the human gut microbiome of type 2 diabetes mellitus (T2D). Two previous quantitative gut metagenomics studies of T2D patients that were unstratified for treatment yielded divergent conclusions regarding its associated gut microbial dysbiosis. Here we show, using 784 available human gut metagenomes, how antidiabetic medication confounds these results, and analyse in detail the effects of the most widely used antidiabetic drug metformin. We provide support for microbial mediation of the therapeutic effects of metformin through short-chain fatty acid production, as well as for potential microbiota-mediated mechanisms behind known intestinal adverse effects in the form of a relative increase in abundance of Escherichia species. Controlling for metformin treatment, we report a unified signature of gut microbiome shifts in T2D with a depletion of butyrate-producing taxa. These in turn cause functional microbiome shifts, in part alleviated by metformin-induced changes. Overall, the present study emphasizes the need to disentangle gut microbiota signatures of specific human diseases from those of medication.

Genomic variation landscape of the human gut microbiome

Whereas large-scale efforts have rapidly advanced the understanding and practical impact of human genomic variation, the practical impact of variation is largely unexplored in the human microbiome. We therefore developed a framework for metagenomic variation analysis and applied it to 252 faecal metagenomes of 207 individuals from Europe and North America. Using 7.4 billion reads aligned to 101 reference species, we detected 10.3 million single nucleotide polymorphisms (SNPs), 107,991 short insertions/deletions, and 1,051 structural variants. The average ratio of non-synonymous to synonymous polymorphism rates of 0.11 was more variable between gut microbial species than across human hosts. Subjects sampled at varying time intervals exhibited individuality and temporal stability of SNP variation patterns, despite considerable composition changes of their gut microbiota. This indicates that individual-specific strains are not easily replaced and that an individual might have a unique metagenomic genotype, which may be exploitable for personalized diet or drug intake.

Transcriptome Complexity in a Genome-Reduced Bacterium

Simply Mycoplasma The bacterium Mycoplasma pneumoniae, a human pathogen, has a genome of reduced size and is one of the simplest organisms that can reproduce outside of host cells. As such, it represents an excellent model organism in which to attempt a systems-level understanding of its biological organization. Now three papers provide a comprehensive and quantitative analysis of the proteome, the metabolic network, and the transcriptome of M. pneumoniae (see the Perspective by Ochman and Raghavan). Anticipating what might be possible in the future for more complex organisms, Kühner et al. (p. 1235) combine analysis of protein interactions by mass spectrometry with extensive structural information on M. pneumoniae proteins to reveal how proteins work together as molecular machines and map their organization within the cell by electron tomography. The manageable genome size of M. pneumoniae allowed Yus et al. (p. 1263) to map the metabolic network of the organism manually and validate it experimentally. Analysis of the network aided development of a minimal medium in which the bacterium could be cultured. Finally, G‡ell et al. (p. 1268) applied state-of-the-art sequencing techniques to reveal that this “simple” organism makes extensive use of noncoding RNAs and has exon- and intron-like structure within transcriptional operons that allows complex gene regulation resembling that of eukaryotes. Sequencing of a tiny bacterium’s RNA reveals many noncoding RNAs and complex gene regulation reminiscent of eukaryotes. To study basic principles of transcriptome organization in bacteria, we analyzed one of the smallest self-replicating organisms, Mycoplasma pneumoniae. We combined strand-specific tiling arrays, complemented by transcriptome sequencing, with more than 252 spotted arrays. We detected 117 previously undescribed, mostly noncoding transcripts, 89 of them in antisense configuration to known genes. We identified 341 operons, of which 139 are polycistronic; almost half of the latter show decaying expression in a staircase-like manner. Under various conditions, operons could be divided into 447 smaller transcriptional units, resulting in many alternative transcripts. Frequent antisense transcripts, alternative transcripts, and multiple regulators per gene imply a highly dynamic transcriptome, more similar to that of eukaryotes than previously thought.

Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes.

Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.

The human small intestinal microbiota is driven by rapid uptake and conversion of simple carbohydrates

The human gastrointestinal tract (GI tract) harbors a complex community of microbes. The microbiota composition varies between different locations in the GI tract, but most studies focus on the fecal microbiota, and that inhabiting the colonic mucosa. Consequently, little is known about the microbiota at other parts of the GI tract, which is especially true for the small intestine because of its limited accessibility. Here we deduce an ecological model of the microbiota composition and function in the small intestine, using complementing culture-independent approaches. Phylogenetic microarray analyses demonstrated that microbiota compositions that are typically found in effluent samples from ileostomists (subjects without a colon) can also be encountered in the small intestine of healthy individuals. Phylogenetic mapping of small intestinal metagenome of three different ileostomy effluent samples from a single individual indicated that Streptococcus sp., Escherichia coli, Clostridium sp. and high G+C organisms are most abundant in the small intestine. The compositions of these populations fluctuated in time and correlated to the short-chain fatty acids profiles that were determined in parallel. Comparative functional analysis with fecal metagenomes identified functions that are overrepresented in the small intestine, including simple carbohydrate transport phosphotransferase systems (PTS), central metabolism and biotin production. Moreover, metatranscriptome analysis supported high level in-situ expression of PTS and carbohydrate metabolic genes, especially those belonging to Streptococcus sp. Overall, our findings suggest that rapid uptake and fermentation of available carbohydrates contribute to maintaining the microbiota in the human small intestine.

Human gut microbes impact host serum metabolome and insulin sensitivity

Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin-resistant individuals is characterized by increased levels of branched-chain amino acids (BCAAs), which correlate with a gut microbiome that has an enriched biosynthetic potential for BCAAs and is deprived of genes encoding bacterial inward transporters for these amino acids. Prevotella copri and Bacteroides vulgatus are identified as the main species driving the association between biosynthesis of BCAAs and insulin resistance, and in mice we demonstrate that P. copri can induce insulin resistance, aggravate glucose intolerance and augment circulating levels of BCAAs. Our findings suggest that microbial targets may have the potential to diminish insulin resistance and reduce the incidence of common metabolic and cardiovascular disorders.