Youssef Darzi

Population-level analysis of gut microbiome variation

“Normal” for the gut microbiota For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities. Science, this issue pp. 560 and 565 Two large-scale studies in Western Europe establish environment-diet-microbe-host interactions. Fecal microbiome variation in the average, healthy population has remained under-investigated. Here, we analyzed two independent, extensively phenotyped cohorts: the Belgian Flemish Gut Flora Project (FGFP; discovery cohort; N = 1106) and the Dutch LifeLines-DEEP study (LLDeep; replication; N = 1135). Integration with global data sets (N combined = 3948) revealed a 14-genera core microbiota, but the 664 identified genera still underexplore total gut diversity. Sixty-nine clinical and questionnaire-based covariates were found associated to microbiota compositional variation with a 92% replication rate. Stool consistency showed the largest effect size, whereas medication explained largest total variance and interacted with other covariate-microbiota associations. Early-life events such as birth mode were not reflected in adult microbiota composition. Finally, we found that proposed disease marker genera associated to host covariates, urging inclusion of the latter in study design.

Integrated metagenomics/metaproteomics reveals human host microbiota signatures of Crohn's disease

Crohns disease (CD) is an inflammatory bowel disease of complex etiology, although dysbiosis of the gut microbiota has been implicated in chronic immune-mediated inflammation associated with CD. Here we combined shotgun metagenomic and metaproteomic approaches to identify potential functional signatures of CD in stool samples from six twin pairs that were either healthy, or that had CD in the ileum (ICD) or colon (CCD). Integration of these omics approaches revealed several genes, proteins, and pathways that primarily differentiated ICD from healthy subjects, including depletion of many proteins in ICD. In addition, the ICD phenotype was associated with alterations in bacterial carbohydrate metabolism, bacterial-host interactions, as well as human host-secreted enzymes. This eco-systems biology approach underscores the link between the gut microbiota and functional alterations in the pathophysiology of Crohns disease and aids in identification of novel diagnostic targets and disease specific biomarkers.

Determinants of community structure in the global plankton interactome

Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

Plankton networks driving carbon export in the oligotrophic ocean.

The biological carbon pump is the process by which CO2 is transformed to organic carbon via photosynthesis, exported through sinking particles, and finally sequestered in the deep ocean. While the intensity of the pump correlates with plankton community composition, the underlying ecosystem structure driving the process remains largely uncharacterized. Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve our understanding of carbon export in the oligotrophic ocean. We show that specific plankton communities, from the surface and deep chlorophyll maximum, correlate with carbon export at 150u2009m and highlight unexpected taxa such as Radiolaria and alveolate parasites, as well as Synechococcus and their phages, as lineages most strongly associated with carbon export in the subtropical, nutrient-depleted, oligotrophic ocean. Additionally, we show that the relative abundance of a few bacterial and viral genes can predict a significant fraction of the variability in carbon export in these regions.

Induction of Bone Loss by Pathobiont-Mediated Nod1 Signaling in the Oral Cavity

Periodontitis is a common disease that is characterized by resorption of the alveolar bone and mediated by commensal bacteria that trigger host immune responses and bone destruction through unidentified mechanisms. We report that Nod1, an innate intracellular host receptor for bacterial peptidoglycan-related molecules, is critical for commensal-induced periodontitis in a mouse model. Mice lacking Nod1 exhibit reduced bone resorption as well as impaired recruitment of neutrophils to gingival tissues and osteoclasts to the alveolar bone, which mediate tissue and bone destruction. Further analysis showed that accumulation of a Nod1-stimulating commensal bacterium, NI1060, at gingival sites was sufficient to induce neutrophil recruitment and bone resorption. Genomic sequencing revealed that NI1060 is a mouse-specific bacterium that is related to bacteria associated with the development of aggressive periodontitis in humans. These findings provide insight into commensal-host interactions contributing to periodontitis and identify a potential target for preventing this common oral disease.

Quantitative microbiome profiling links gut community variation to microbial load

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration. To enable genuine characterization of host–microbiota interactions, microbiome research must exchange ratios for counts. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn’s disease, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling).

Species–function relationships shape ecological properties of the human gut microbiome

Despite recent progress, the organization and ecological properties of the intestinal microbial ecosystem remain under-investigated. Here, using a manually curated metabolic module framework for (meta-)genomic data analysis, we studied species–function relationships in gut microbial genomes and microbiomes. Half of gut-associated species were found to be generalists regarding overall substrate preference, but we observed significant genus-level metabolic diversification linked to bacterial life strategies. Within each genus, metabolic consistency varied significantly, being low in Firmicutes genera and higher in Bacteroides. Differentiation of fermentable substrate degradation potential contributed to metagenomic functional repertoire variation between individuals, with different enterotypes showing distinct saccharolytic/proteolytic/lipolytic profiles. Finally, we found that module-derived functional redundancy was reduced in the low-richness Bacteroides enterotype, potentially indicating a decreased resilience to perturbation, in line with its frequent association to dysbiosis. These results provide insights into the complex structure of gut microbiome-encoded metabolic properties and emphasize the importance of functional and ecological assessment of gut microbiome variation in clinical studies.

Meta-omics in inflammatory bowel disease research: applications, challenges, and guidelines

Meta-omics [metagenomics, metatranscriptomics, and metaproteomics] are rapidly expanding our knowledge of the gut microbiota in health and disease. These technologies are increasingly used in inflammatory bowel disease [IBD] research. Yet, meta-omics data analysis, interpretation, and among-study comparison remain challenging. In this review we discuss the role these techniques are playing in IBD research, highlighting their strengths and limitations. We give guidelines on proper sample collection and preparation methods, and on performing the analyses and interpreting the results, reporting available user-friendly tools and pipelines.

Towards biome-specific analysis of meta-omics data

Microbial ecology has witnessed tremendous progress over the last decade empowered by meta-omics approaches and innovations in DNA/RNA sequencing as well as high-resolution mass spectrometry. In this climate, the rise of meta-omics projects (Raes, 2011) such as MetaHIT and the Human Microbiome Project, Tara Oceans, the Global Ocean Sampling Expedition and the Earth Microbiome Project aiming at unraveling the structure and function of specific microbiomes in different habitats was observed. Now that massive data generation is no longer science fiction, the bottleneck shifts to computational analysis (Falony et al., 2015).

The genomic sequence of the oral pathobiont strain NI1060 reveals unique strategies for bacterial competition and pathogenicity

Strain NI1060 is an oral bacterium responsible for periodontitis in a murine ligature-induced disease model. To better understand its pathogenicity, we have determined the complete sequence of its 2,553,982 bp genome. Although closely related to Pasteurella pneumotropica, a pneumonia-associated rodent commensal based on its 16S rRNA, the NI1060 genomic content suggests that they are different species thriving on different energy sources via alternative metabolic pathways. Genomic and phylogenetic analyses showed that strain NI1060 is distinct from the genera currently described in the family Pasteurellaceae, and is likely to represent a novel species. In addition, we found putative virulence genes involved in lipooligosaccharide synthesis, adhesins and bacteriotoxic proteins. These genes are potentially important for host adaption and for the induction of dysbiosis through bacterial competition and pathogenicity. Importantly, strain NI1060 strongly stimulates Nod1, an innate immune receptor, but is defective in two peptidoglycan recycling genes due to a frameshift mutation. The in-depth analysis of its genome thus provides critical insights for the development of NI1060 as a prime model system for infectious disease.