Biology subjects

Segata, N.

Publications and source records attributed to Segata, N..

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bioRxiv2020

Strengthening The Organizing and Reporting of Microbiome Studies (STORMS)

BackgroundHuman microbiome research is a growing field with the potential for improving our understanding and treatment of diseases and other conditions. The field is interdisciplinary, making concise organization and reporting of results across different styles of epidemiology, biology, bioinformatics, translational medicine, and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. MethodsA multidisciplinary group of microbiome epidemiology researchers reviewed elements of available reporting guidelines for observational and genetic studies and adapted these for application to culture-independent human microbiome studies. New reporting elements were developed for laboratory, bioinformatic, and statistical analyses tailored to microbiome studies, and other parts of these checklists were streamlined to keep reporting manageable. ResultsSTORMS is a 17-item checklist for reporting on human microbiome studies, organized into six sections covering typical sections of a scientific publication, presented as a table with space for author-provided details and intended for inclusion in supplementary materials. ConclusionsSTORMS provides guidance for authors and standardization for interdisciplinary microbiome studies, facilitating complete and concise reporting and augments information extraction for downstream applications. AvailabilityThe STORMS checklist is available as a versioned spreadsheet from https://www.stormsmicrobiome.org/.

genomics↗

bioRxiv2019

The signal and the noise - characteristics of antisense RNA in complex microbial communities

High-throughput sequencing has allowed unprecedented insight into the composition and function of complex microbial communities. With the onset of metatranscriptomics, it is now possible to interrogate the transcriptome of multiple organisms simultaneously to get an overview of the gene expression of the entire community. Studies have successfully used metatranscriptomics to identify and describe relationships between gene expression levels and community characteristics. However, metatranscriptomic datasets contain a rich suite of additional information which is just beginning to be explored. In this minireview we discuss the different computational strategies for handling antisense expression in metatranscriptomic samples and highlight their potentially detrimental effects on downstream analysis and interpretation. We also surveyed the antisense transcriptome of multiple genomes and metagenome-assembled genomes (MAGs) from five different datasets and found high variability in the level of antisense transcription for individual species which were consistent across samples. Importantly, we tested the hypothesis that antisense transcription is primarily the product of transcriptional noise and found mixed support, suggesting that the total observed antisense RNA in complex communities arises from a compounded effect of both random, biological and technical factors. Antisense transcription can provide a rich set of information, from technical details about data quality to novel insight into the biology of complex microbial communities.\n\nKey pointsO_LISeveral fundamentally different approaches are used to handle antisense RNA\nC_LIO_LIPrevalence of antisense RNA is highly variable between communities, genomes, and genes.\nC_LIO_LIAntisense RNA is likely an opaque mixture of technical, biological and random effects\nC_LI

microbiology↗

bioRxiv2019

A unified sequence catalogue of over 280,000 genomes obtained from the human gut microbiome

Comprehensive reference data is essential for accurate taxonomic and functional characterization of the human gut microbiome. Here we present the Unified Human Gastrointestinal Genome (UHGG) collection, a resource combining 286,997 genomes representing 4,644 prokaryotic species from the human gut. These genomes contain over 625 million protein sequences used to generate the Unified Human Gastrointestinal Protein (UHGP) catalogue, a collection that more than doubles the number of gut protein clusters over the Integrated Gene Catalogue. We find that a large portion of the human gut microbiome remains to be fully explored, with over 70% of the UHGG species lacking cultured representatives, and 40% of the UHGP missing meaningful functional annotations. Intra-species genomic variation analyses revealed a large reservoir of accessory genes and single-nucleotide variants, many of which were specific to individual human populations. These freely available genomic resources should greatly facilitate investigations into the human gut microbiome.

microbiology↗

bioRxiv2019

Distinct polysaccharide growth profiles of human intestinal Prevotella copri isolates

The gut-dwelling Prevotella copri, the most prevalent Prevotella species in human gut, have been associated with diet as well as disease, but our understanding of their diversity and functional roles remains rudimentary, as studies have been limited to 16S and metagenomic surveys and experiments using a single type strain. Here, we describe the genomic diversity of 83 P. copri isolates from 11 donors. We demonstrate that genomically distinct isolates, which can be categorized into different P. copri complex clades, utilize defined sets of plant polysaccharides that can be predicted in part from their genomes and from metagenomic data. This study thus reveals both genomic and functional differences in polysaccharide utilization between several novel human intestinal P. copri strains.

microbiology↗

bioRxiv2019

The personalized temporal dynamics of microbiome in the airways of cystic fibrosis patients

Although the cystic fibrosis (CF) lung microbiome has been characterized in several studies, little is still known about the functions harboured by those bacteria, and how they change with disease status and antibiotic treatment. The aim of this study was to investigate the taxonomic and functional temporal dynamics of airways microbiome in a cohort of CF patients. Multiple sputum samples were collected over 15 months from 22 patients with chronic P. aeruginosa infection, for a total of 79 samples. DNA extracted from samples was subjected to shotgun metagenomic sequencing allowing either strain-level taxonomic profiling and assessment of the functional metagenomic repertoire. High inter-patient taxonomic heterogeneity was found with short-term compositional changes during exacerbations and following antibiotic treatment. Each patient exhibited distinct sputum microbial communities at the taxonomic level, and strain-specific colonization of traditional CF pathogens, including P. aeruginosa, and emerging pathogens. Sputum microbiome was found to be extraordinarily resilient following antibiotic treatment, with rapid recovery of taxa and metagenome-associated gene functions. In particular, a large core set of genes, including antibiotic resistance genes, were shared across patients despite observed differences in clinical status or antibiotic treatment, and constantly detected in the lung microbiome of all subjects independently from known antibiotic exposure, suggesting an overall microbiome-associated functions stability despite taxonomic fluctuations of the communities. IMPORTANCEWhile the dynamics of CF sputum microbial composition were highly patient-specific, the overall sputum metagenome composition was stable, showing a high resilience along time and antibiotic exposure. The high degree of redundancy in the CF lung microbiome could testifies ecological aspects connected to the disease that were never considered so far, as the large core-set of genes shared between patients despite observed differences in clinical status or antibiotic treatment. Investigations on the actual functionality (e.g. by metatranscriptomics) of the identified core-set of genes could provide clues on genetic function of the microbiome to be targeted in future therapeutic treatments.

microbiology↗

bioRxiv2019

The Prevotella copri complex comprises four distinct clades that are underrepresented in Westernised populations

Prevotella copri is a common inhabitant of the human gut. Interest in P. copri has gathered pace due to conflicting reports on whether it is beneficial or detrimental to health. In a cross-continent meta-analysis exploiting >6,500 available metagenomes supported by new isolate sequencing and recovery of high-quality genomes from metagenomes, we obtained >1,000 P. copri genomes. This 100-fold increase over existing isolate genomes allowed the genetic and global population structure of P. copri to be explored at an unprecedented depth. We demonstrate P. copri is not a monotypic species, but encompasses four distinct clades (>10% inter-clade vs. <4% intra-clade average single nucleotide variants) for which we propose the name P. copri complex, comprising clades A, B, C and D. We show the complex is near ubiquitous in non-Westernised populations (95.4% versus 29.6% in Westernised populations), where all four clades are typically co-present within an individual (61.6% of the cases), in contrast to Westernised populations (4.6%). Genomic analysis of the complex reveals substantial and complementary functional diversity, including the potential for utilisation of complex carbohydrates, suggestive that multi-generational dietary modifications may be a driver for the reduced P. copri prevalence in Westernised populations. Analysis of ancient stool microbiomes highlights a similar pattern of P. copri presence consistent with modern non-Westernised populations, allowing us to estimate the time of clade delineation to pre-date human migratory waves out of Africa. Our analysis reveals P. copri to be far more diverse than previously appreciated and this diversity appears to be underrepresented in Western-lifestyle populations.

microbiology↗

bioRxiv2018

Tobacco exposure associated with oral microbiota oxygen utilization in the New York City Health and Nutrition Examination Study

PurposeThe effect of tobacco exposure on the oral microbiome has not been established. MethodsWe performed amplicon sequencing of the 16S ribosomal RNA gene V4 variable region to estimate bacterial community characteristics in 259 oral rinse samples, selected based on self-reported smoking and serum cotinine levels, from the 2013-14 New York City Health and Nutrition Examination Study. We identified differentially abundant operational taxonomic units (OTUs) by primary and secondhand tobacco exposure, and employed "microbe set enrichment analysis" to assess shifts in microbial oxygen utilization. ResultsCigarette smoking was associated with depletion of aerobic OTUs (Enrichment Score test statistic ES = -0.75, p = 0.002) with a minority (29%) of aerobic OTUs enriched in current smokers compared to never smokers. Consistent shifts in the microbiota were observed for current cigarette smokers as for non-smokers with secondhand exposure as measured by serum cotinine levels. Differential abundance findings were similar in crude and adjusted analyses. ConclusionResults support a plausible link between tobacco exposure and shifts in the oral microbiome at the population level through three lines of evidence: 1) a shift in microbiota oxygen utilization associated with primary tobacco smoke exposure, 2) consistency of abundance fold-changes associated with current smoking and shifts along the gradient of secondhand smoke exposure among non-smokers, and 3) consistency after adjusting for a priori hypothesized confounders. HighlightsO_LICigarette smoke was associated with microbial anaerobiosis in oral rinse specimens C_LIO_LIThe microbiome shifts associated with smoking and secondhand exposure were correlated C_LIO_LIShifts in oral bacterial oxygen utilization may mediate smoking and health outcomes C_LIO_LIWe propose "microbe set enrichment analysis" for interpreting shifts in the microbiome C_LI

epidemiology↗

bioRxiv2018

HMP16SData: Efficient Access to the Human Microbiome Project through Bioconductor

Phase 1 of the NIH Human Microbiome Project (HMP) investigated 18 body subsites of 239 healthy American adults, to produce the first comprehensive reference for the composition and variation of the \"healthy\" human microbiome. Publicly-available data sets from amplicon sequencing of two 16S rRNA variable regions, with extensive controlled-access participant data, provide a reference for ongoing microbiome studies. However, utilization of these data sets can be hindered by the complex bioinformatic steps required to access, import, decrypt, and merge the various components in formats suitable for ecological and statistical analysis. The HMP16SData package provides count data for both 16S variable regions, integrated with phylogeny, taxonomy, public participant data, and controlled participant data for authorized researchers, using standard integrative Bioconductor data objects. By removing bioinformatic hurdles of data access and management, HMP16SData enables epidemiologists with only basic R skills to quickly analyze HMP data.

bioinformatics↗

bioRxiv2017

Sociodemographic patterning in the oral microbiome of a diverse sample of New Yorkers

11.1 PurposeVariations in the oral microbiome are potentially implicated in social inequalities in oral disease, cancers, and metabolic disease. We describe sociodemographic variation of oral microbiomes in a diverse sample.\n\n1.2 MethodsWe performed 16S rRNA sequencing on mouthwash specimens in a subsample (n=282) of the 2013-14 population-based New York City Health and Nutrition Examination Study (NYC-HANES). We examined differential abundance of 216 operational taxonomic units (OTUs), and alpha and beta diversity by age, sex, income, education, nativity, and race/ethnicity. For comparison, we also examined differential abundance by diet, smoking status, and oral health behaviors.\n\n1.3 Results69 OTUs were differentially abundant by any sociodemographic variable (false discovery rate < 0.01), including 27 by race/ethnicity, 21 by family income, 19 by education, three by sex. We also found 49 differentially abundant by smoking status, 23 by diet, 12 by oral health behaviors. Genera differing for multiple sociodemographic characteristics included Lactobacillus, Prevotella, Porphyromonas, Fusobacterium.\n\n1.4 ConclusionsWe identified oral microbiome variation consistent with health inequalities, with more taxa differing by race/ethnicity than diet, and more by SES variables than oral health behaviors. Investigation is warranted into possible mediating effects of the oral microbiome in social disparities in oral, metabolic and cancers.\n\nHighlightsO_LIMost microbiome studies to date have had minimal sociodemographic variability, limiting what is known about associations of social factors and the microbiome.\nC_LIO_LIWe examined the oral microbiome in a population-based sample of New Yorkers with wide sociodemographic variation.\nC_LIO_LINumerous taxa were differentially abundant by race/ethnicity, income, education, marital status, and nativity.\nC_LIO_LIFrequently differentially abundant taxa include Porphyromonas, Fusobacterium, Streptococcus, and Prevotella, which are associated with oral and systemic disease.\nC_LIO_LIMediation of health disparities by microbial factors may represent an important intervention site to reduce health disparities, and should be explored in prospective studies.\nC_LI

epidemiology↗

bioRxiv2017

Accessible, curated metagenomic data through ExperimentHub

We present curatedMetagenomicData, a Bioconductor and command-line interface to thousands of metagenomic profiles from the Human Microbiome Project and other publicly available datasets, and ExperimentHub, a platform for convenient cloud-based distribution of data to the R desktop. The resource provides standardized per-participant metadata linked to bacterial, fungal, archaeal, and viral taxonomic abundances, as well as quantitative metabolic functional profiles. The datasets can be immediately analyzed in R or other software with a minimum of bioinformatic expertise and no preprocessing of data. We demonstrate identification of taxonomic/functional correlations, an investigation of gut \"enterotypes\", and a comparison of the accuracy of disease classification from different data types. These documented analyses can be reproduced efficiently on a laptop, without the barriers of working with large-scale, raw sequencing data. The building and expansion of curatedMetagenomicData is based entirely on open source software and pipelines, to facilitate the addition of new microbiome datasets and methods.

bioinformatics↗

bioRxiv2016

Studying vertical microbiome transmission from mothers to infants by strain-level metagenomic profiling

The gut microbiome starts to be shaped in the first days of life and continues to increase its diversity during the first months. Several investigations are assessing the link between the configuration of the infant gut microbiome and infant health, but a comprehensive strain-level assessment of vertically transmitted microbes from mother to infant is still missing. We longitudinally collected fecal and breast milk samples from multiple mother-infant pairs during the first year of life, and applied shotgun metagenomic sequencing followed by strain-level profiling. We observed several specific strains including those from Bifidobacterium bifidum, Coprococcus comes, and Ruminococcus bromii, that were present in samples from the same mother-infant pair, while being clearly distinct from those carried by other pairs, which is indicative of vertical transmission. We further applied metatranscriptomics to study the in vivo expression of vertically transmitted microbes, for example Bacteroides vulgatus and Bifidobacterium spp., thus suggesting that transmitted strains are functionally active in the two rather different environments of the adult and infant guts. By combining longitudinal microbiome sampling and newly developed computational tools for strain-level microbiome analysis, we showed that it is possible to track vertical transmission of members of the microbiome from mother to infants and characterize their transcriptional activity. Our work poses the basis for surveying at larger scale the sources of microbial diversity in the infants and starts associating these transmissions with the subsequent longer-term development of a healthy or dysbiotic microbiome.\n\nImportanceEarly infant exposure is important in the acquisition and ultimate development of a healthy infant microbiome. There is increasing support that the maternal microbial reservoir is a key route of microbial transmission, yet much is inferred from the observation of shared species in mother and infant. Common species, per se, does not necessarily equate vertical transmission as species exhibit considerable strain heterogeneity and it is therefore imperative to identify shared strains. We demonstrate here the potential of shotgun metagenomics and strain-level resolution to identify vertical transmission events via the maternal source. Combined with a metatranscriptomic approach, we show the potential not only to identify and track the fate of microbes in the early infant microbiome but also identify the metabolically active members. These approaches will ultimately provide important insights into the acquisition, development and community dynamics of the infant microbiome.

microbiology↗