Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice.

Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between typically developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD or TD controls into germ-free mice and reveal that colonization with ASD microbiota is sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and modulates neuronal excitability in the brain. We propose that the gut microbiota regulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.

Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases.

Inflammatory bowel diseases, which include Crohn's disease and ulcerative colitis, affect several million individuals worldwide. Crohn's disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study's infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi'omics Database ( http://ibdmdb.org ), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases.

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Uncovering Hidden Members and Functions of the Soil Microbiome Using De Novo Metaproteomics.

Metaproteomics has been increasingly utilized for high-throughput characterization of proteins in complex environments and has been demonstrated to provide insights into microbial composition and functional roles. However, significant challenges remain in metaproteomic data analysis, including creation of a sample-specific protein sequence database. A well-matched database is a requirement for successful metaproteomics analysis, and the accuracy and sensitivity of PSM identification algorithms suffer when the database is incomplete or contains extraneous sequences. When matched DNA sequencing data of the sample is unavailable or incomplete, creating the proteome database that accurately represents the organisms in the sample is a challenge. Here, we leverage a de novo peptide sequencing approach to identify the sample composition directly from metaproteomic data. First, we created a deep learning model, Kaiko, to predict the peptide sequences from mass spectrometry data and trained it on 5 million peptide-spectrum matches from 55 phylogenetically diverse bacteria. After training, Kaiko successfully identified organisms from soil isolates and synthetic communities directly from proteomics data. Finally, we created a pipeline for metaproteome database generation using Kaiko. We tested the pipeline on native soils collected in Kansas, showing that the de novo sequencing model can be employed as an alternative and complementary method to construct the sample-specific protein database instead of relying on (un)matched metagenomes. Our pipeline identified all highly abundant taxa from 16S rRNA sequencing of the soil samples and uncovered several additional species which were strongly represented only in proteomic data.

Microbiome-wide association studies link dynamic microbial consortia to disease.

Rapid advances in DNA sequencing, metabolomics, proteomics and computational tools are dramatically increasing access to the microbiome and identification of its links with disease. In particular, time-series studies and multiple molecular perspectives are facilitating microbiome-wide association studies, which are analogous to genome-wide association studies. Early findings point to actionable outcomes of microbiome-wide association studies, although their clinical application has yet to be approved. An appreciation of the complexity of interactions among the microbiome and the host's diet, chemistry and health, as well as determining the frequency of observations that are needed to capture and integrate this dynamic interface, is paramount for developing precision diagnostics and therapies that are based on the microbiome.

Activity-Based Protein Profiling of Chitin Catabolism.

The microbial catabolism of chitin, an abundant and ubiquitous environmental organic polymer, is a fundamental cog in terrestrial and aquatic carbon and nitrogen cycles. Despite the importance of this critical bio-geochemical function, there is a limited understanding of the synergy between the various hydrolytic and accessory enzymes involved in chitin catabolism. To address this deficit, we synthesized activity-based probes (ABPs) designed to target active chitinolytic enzymes by modifying the chitin subunits N-acetyl glucosamine and chitotriose. The ABPs were used to determine the active complement of chitinolytic enzymes produced over time by the soil bacterium Cellvibrio japonicus treated with various C substrates. We demonstrate the utility of these ABPs in determining the synergy between various enzymes involved in chitin catabolism. The strategy can be used to gain molecular-level insights that can be used to better understand microbial roles in soil bio-geochemical cycling in the face of a changing climate.

Multi-omics of permafrost, active layer and thermokarst bog soil microbiomes.

Over 20% of Earth's terrestrial surface is underlain by permafrost with vast stores of carbon that, once thawed, may represent the largest future transfer of carbon from the biosphere to the atmosphere. This process is largely dependent on microbial responses, but we know little about microbial activity in intact, let alone in thawing, permafrost. Molecular approaches have recently revealed the identities and functional gene composition of microorganisms in some permafrost soils and a rapid shift in functional gene composition during short-term thaw experiments. However, the fate of permafrost carbon depends on climatic, hydrological and microbial responses to thaw at decadal scales. Here we use the combination of several molecular 'omics' approaches to determine the phylogenetic composition of the microbial communities, including several draft genomes of novel species, their functional potential and activity in soils representing different states of thaw: intact permafrost, seasonally thawed active layer and thermokarst bog. The multi-omics strategy reveals a good correlation of process rates to omics data for dominant processes, such as methanogenesis in the bog, as well as novel survival strategies for potentially active microbes in permafrost.

The gut mycobiota of rural and urban individuals is shaped by geography.

BACKGROUND: Understanding the structure and drivers of gut microbiota remains a major ecological endeavour. Recent studies have shown that several factors including diet, lifestyle and geography may substantially shape the human gut microbiota. However, most of these studies have focused on the more abundant bacterial component and comparatively less is known regarding fungi in the human gut. This knowledge deficit is especially true for rural and urban African populations. Therefore, we assessed the structure and drivers of rural and urban gut mycobiota. RESULTS: Our participants (n = 100) were balanced by geography and sex. The mycobiota of these geographically separated cohorts was characterized using amplicon analysis of the Internal Transcribed Spacer (ITS) gene. We further assessed biomarker species specific to rural and urban cohorts. In addition to phyla which have been shown to be ubiquitous constituents of gut microbiota, Pichia were key constituents of the mycobiota. We found that geographic location was a major driver of gut mycobiota. Other factors such as smoking where also determined gut mycobiota albeit to a lower extent, as explained by the small proportion of total variation. Linear discriminant and the linear discriminant analysis effect size analysis revealed several distinct urban and rural biomarkers. CONCLUSIONS: Together, our analysis reveals distinct community structure in urban and rural South African individuals. Geography was shown to be a key driver of rural and urban gut mycobiota.

Diverse tumour susceptibility in Collaborative Cross mice: identification of a new mouse model for human gastric tumourigenesis.

OBJECTIVE: The Collaborative Cross (CC) is a mouse population model with diverse and reproducible genetic backgrounds used to identify novel disease models and genes that contribute to human disease. Since spontaneous tumour susceptibility in CC mice remains unexplored, we assessed tumour incidence and spectrum. DESIGN: We monitored 293 mice from 18 CC strains for tumour development. Genetic association analysis and RNA sequencing were used to identify susceptibility loci and candidate genes. We analysed genomes of patients with gastric cancer to evaluate the relevance of genes identified in the CC mouse model and measured the expression levels of ISG15 by immunohistochemical staining using a gastric adenocarcinoma tissue microarray. Association of gene expression with overall survival (OS) was assessed by Kaplan-Meier analysis. RESULTS: CC mice displayed a wide range in the incidence and types of spontaneous tumours. More than 40% of CC036 mice developed gastric tumours within 1 year. Genetic association analysis identified Nfκb1 as a candidate susceptibility gene, while RNA sequencing analysis of non-tumour gastric tissues from CC036 mice showed significantly higher expression of inflammatory response genes. In human gastric cancers, the majority of human orthologues of the 166 mouse genes were preferentially altered by amplification or deletion and were significantly associated with OS. Higher expression of the CC036 inflammatory response gene signature is associated with poor OS. Finally, ISG15 protein is elevated in gastric adenocarcinomas and correlated with shortened patient OS. CONCLUSIONS: CC strains exhibit tremendous variation in tumour susceptibility, and we present CC036 as a spontaneous laboratory mouse model for studying human gastric tumourigenesis.

A Probe-Enabled Approach for the Selective Isolation and Characterization of Functionally Active Subpopulations in the Gut Microbiome.

Commensal microorganisms in the mammalian gut play important roles in host health and physiology, but a central challenge remains in achieving a detailed mechanistic understanding of specific microbial contributions to host biochemistry. New function-based approaches are needed that analyze gut microbial function at the molecular level by coupling detection and measurements of in situ biochemical activity with identification of the responsible microbes and enzymes. We developed a platform employing ß-glucuronidase selective activity-based probes to detect, isolate, and identify microbial subpopulations in the gut responsible for this xenobiotic metabolism. We find that metabolic activity of gut microbiota can be plastic and that between individuals and during perturbation, phylogenetically disparate populations can provide ß-glucuronidase activity. Our work links biochemical activity with molecular-scale resolution without relying on genomic inference.

Ion Mobility Spectrometry and the Omics: Distinguishing Isomers, Molecular Classes and Contaminant Ions in Complex Samples.

Ion mobility spectrometry (IMS) is a widely used analytical technique providing rapid gas phase separations. IMS alone is useful, but its coupling with mass spectrometry (IMS-MS) and various front-end separation techniques has greatly increased the molecular information achievable from different omic analyses. IMS-MS analyses are specifically gaining attention for improving metabolomic, lipidomic, glycomic, proteomic and exposomic analyses by increasing measurement sensitivity (e.g. S/N ratio), reducing the detection limit, and amplifying peak capacity. Numerous studies including national security-related analyses, disease screenings and environmental evaluations are illustrating that IMS-MS is able to extract information not possible with MS alone. Furthermore, IMS-MS has shown great utility in salvaging molecular information for low abundance molecules of interest when high concentration contaminant ions are present in the sample by reducing detector suppression. This review highlights how IMS-MS is currently being used in omic analyses to distinguish structurally similar molecules, isomers, molecular classes and contaminant ions.

Disentangling the complexity of permafrost soil by using high resolution profiling of microbial community composition, key functions and respiration rates.

Thawing permafrost can stimulate microbial activity, leading to faster decomposition of formerly preserved organic matter and CO2 release. Detailed knowledge about the vertical distribution of the responsible microbial community that is changing with increasing soil depth is limited. In this study, we determined the microbial community composition from cores sampled in a high Arctic heath at Svalbard, Norway; spanning from the active layer (AL) into the permafrost layer (PL). A special aim has been on identifying a layer of recently thawed soil, the transition zone (TZ), which might provide new insights into the fate of thawing permafrost. A unique sampling strategy allowed us to observe a diverse and gradually shifting microbial community in the AL, a Bacteroidetes dominated community in the TZ and throughout the PL, a community strongly dominated by a single Actinobacteria family (Intrasporangiaceae). The contrasting abundances of these two taxa caused a community difference of about 60%, just within 3 cm from TZ to PL. We incubated subsamples at about 5°C and measured highest CO2 production rates under aerobic incubations, yet contrasting for five different layers and correlating to the microbial community composition. This high resolution strategy provides new insights on how microbial communities are structured in permafrost and a better understanding of how they respond to thaw.

Metagenomic Insights into the Degradation of Resistant Starch by Human Gut Microbiota.

Several studies monitoring alterations in the community structure upon resistant starch (RS) interventions are available, although comprehensive function-based analyses are lacking. Recently, a multiomics approach based on 16S rRNA gene sequencing, metaproteomics, and metabolomics on fecal samples from individuals subjected to high and low doses of type 2 RS (RS2; 48 g and 3 g/2,500 kcal, respectively, daily for 2 weeks) in a crossover intervention experiment was performed. In the present study, we did pathway-based metagenomic analyses on samples from a subset of individuals (n = 12) from that study to obtain additional detailed insights into the functional structure at high resolution during RS2 intervention. A mechanistic framework based on obtained results is proposed where primary degradation was governed by Firmicutes, with Ruminococcus bromii as a major taxon involved, providing fermentation substrates and increased acetate concentrations for the growth of various major butyrate producers exhibiting the enzyme butyryl-coenzyme A (CoA):acetate CoA-transferase. H2-scavenging sulfite reducers and acetogens concurrently increased. Individual responses of gut microbiota were noted, where seven of the 12 participants displayed all features of the outlined pattern, whereas four individuals showed mixed behavior and one subject was unresponsive. Intervention order did not affect the outcome, emphasizing a constant substrate supply for maintaining specific functional communities.IMPORTANCE Manipulation of gut microbiota is increasingly recognized as a promising approach to reduce various noncommunicable diseases, such as obesity and type 2 diabetes. Specific dietary supplements, including resistant starches (RS), are often a focus, yet comprehensive insights into functional responses of microbiota are largely lacking. Furthermore, unresponsiveness in certain individuals is poorly understood. Our data indicate that distinct parts of microbiota work jointly to degrade RS and successively form health-promoting fermentation end products. It highlights the need to consider both primary degraders and specific more-downstream-acting bacterial groups in order to achieve desired intervention outcomes. The gained insights will assist the design of personalized treatment strategies based on an individual's microbiota.

Metagenomic Analysis of Subtidal Sediments from Polar and Subpolar Coastal Environments Highlights the Relevance of Anaerobic Hydrocarbon Degradation Processes.

In this work, we analyzed the community structure and metabolic potential of sediment microbial communities in high-latitude coastal environments subjected to low to moderate levels of chronic pollution. Subtidal sediments from four low-energy inlets located in polar and subpolar regions from both Hemispheres were analyzed using large-scale 16S rRNA gene and metagenomic sequencing. Communities showed high diversity (Shannon's index 6.8 to 10.2), with distinct phylogenetic structures (<40% shared taxa at the Phylum level among regions) but similar metabolic potential in terms of sequences assigned to KOs. Environmental factors (mainly salinity, temperature, and in less extent organic pollution) were drivers of both phylogenetic and functional traits. Bacterial taxa correlating with hydrocarbon pollution included families of anaerobic or facultative anaerobic lifestyle, such as Desulfuromonadaceae, Geobacteraceae, and Rhodocyclaceae. In accordance, biomarker genes for anaerobic hydrocarbon degradation (bamA, ebdA, bcrA, and bssA) were prevalent, only outnumbered by alkB, and their sequences were taxonomically binned to the same bacterial groups. BssA-assigned metagenomic sequences showed an extremely wide diversity distributed all along the phylogeny known for this gene, including bssA sensu stricto, nmsA, assA, and other clusters from poorly or not yet described variants. This work increases our understanding of microbial community patterns in cold coastal sediments, and highlights the relevance of anaerobic hydrocarbon degradation processes in subtidal environments.

Diversity, stability and resilience of the human gut microbiota.

Trillions of microbes inhabit the human intestine, forming a complex ecological community that influences normal physiology and susceptibility to disease through its collective metabolic activities and host interactions. Understanding the factors that underlie changes in the composition and function of the gut microbiota will aid in the design of therapies that target it. This goal is formidable. The gut microbiota is immensely diverse, varies between individuals and can fluctuate over time - especially during disease and early development. Viewing the microbiota from an ecological perspective could provide insight into how to promote health by targeting this microbial community in clinical treatments.

Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains.

Microbes hold the key to life. They hold the secrets to our past (as the descendants of the earliest forms of life) and the prospects for our future (as we mine their genes for solutions to some of the planet's most pressing problems, from global warming to antibiotic resistance). However, the piecemeal approach that has defined efforts to study microbial genetic diversity for over 20 years and in over 30,000 genome projects risks squandering that promise. These efforts have covered less than 20% of the diversity of the cultured archaeal and bacterial species, which represent just 15% of the overall known prokaryotic diversity. Here we call for the funding of a systematic effort to produce a comprehensive genomic catalog of all cultured Bacteria and Archaea by sequencing, where available, the type strain of each species with a validly published name (currently∼11,000). This effort will provide an unprecedented level of coverage of our planet's genetic diversity, allow for the large-scale discovery of novel genes and functions, and lead to an improved understanding of microbial evolution and function in the environment.

Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw.

Permafrost contains an estimated 1672 Pg carbon (C), an amount roughly equivalent to the total currently contained within land plants and the atmosphere. This reservoir of C is vulnerable to decomposition as rising global temperatures cause the permafrost to thaw. During thaw, trapped organic matter may become more accessible for microbial degradation and result in greenhouse gas emissions. Despite recent advances in the use of molecular tools to study permafrost microbial communities, their response to thaw remains unclear. Here we use deep metagenomic sequencing to determine the impact of thaw on microbial phylogenetic and functional genes, and relate these data to measurements of methane emissions. Metagenomics, the direct sequencing of DNA from the environment, allows the examination of whole biochemical pathways and associated processes, as opposed to individual pieces of the metabolic puzzle. Our metagenome analyses reveal that during transition from a frozen to a thawed state there are rapid shifts in many microbial, phylogenetic and functional gene abundances and pathways. After one week of incubation at 5 °C, permafrost metagenomes converge to be more similar to each other than while they are frozen. We find that multiple genes involved in cycling of C and nitrogen shift rapidly during thaw. We also construct the first draft genome from a complex soil metagenome, which corresponds to a novel methanogen. Methane previously accumulated in permafrost is released during thaw and subsequently consumed by methanotrophic bacteria. Together these data point towards the importance of rapid cycling of methane and nitrogen in thawing permafrost.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach.

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.

Tackling soil diversity with the assembly of large, complex metagenomes.

The large volumes of sequencing data required to sample deeply the microbial communities of complex environments pose new challenges to sequence analysis. De novo metagenomic assembly effectively reduces the total amount of data to be analyzed but requires substantial computational resources. We combine two preassembly filtering approaches--digital normalization and partitioning--to generate previously intractable large metagenome assemblies. Using a human-gut mock community dataset, we demonstrate that these methods result in assemblies nearly identical to assemblies from unprocessed data. We then assemble two large soil metagenomes totaling 398 billion bp (equivalent to 88,000 Escherichia coli genomes) from matched Iowa corn and native prairie soils. The resulting assembled contigs could be used to identify molecular interactions and reaction networks of known metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes Orthology database. Nonetheless, more than 60% of predicted proteins in assemblies could not be annotated against known databases. Many of these unknown proteins were abundant in both corn and prairie soils, highlighting the benefits of assembly for the discovery and characterization of novelty in soil biodiversity. Moreover, 80% of the sequencing data could not be assembled because of low coverage, suggesting that considerably more sequencing data are needed to characterize the functional content of soil.