The "most wanted" taxa from the human microbiome for whole genome sequencing

Eubacterium album sp. nov., a butyrate-producing bacterium isolated from faeces of a healthy human

An oval to rod-shaped, Gram-stain-positive, strictly anaerobic bacterium, designated LFL-14T, was isolated from the faeces of a healthy Chinese woman. Cells of the strain were non-spore-forming, grew optimally at 37 °C (growth range 30-45 °C) and pH 7.0 (growth range 6.0-9.0) under anaerobic conditions in the liquid modified Gifu anaerobic medium (mGAM). The result of 16S rRNA gene-based analysis indicated that LFL-14T shared an identity of 94.7 0% with Eubacterium ventriosum ATCC 27560T, indicating LFL-14T represented a novel taxon. The results of genome-based analysis revealed that the average nucleotide identity (ANI), the digital DNA-DNA hybridisation (dDDH) and average amino acid identity (AAI) between LFL-14T and its phylogenetically closest neighbour, Eubacterium ventriosum ATCC 27560T, were 77.0 %, 24.6 and 70.9 %, respectively, indicating that LFL-14T represents a novel species of the genus Eubacterium. The genome size of LFL-14T was 2.92 Mbp and the DNA G+C content was 33.14 mol%. We analysed the distribution of the genome of LFL-14T in cohorts of healthy individuals, type 2 diabetes patients (T2D) and patients with non-alcoholic fatty liver disease (NAFLD). We found that its abundance was higher in the T2D cohort, but it had a low average abundance of less than 0.2 % in all three cohorts. The percentages of frequency of occurrence in the T2D, healthy and NAFLD cohorts were 48.87 %, 16.72 % and 13.10 % respectively. The major cellular fatty acids of LFL-14T were C16 : 0 (34.4 %), C17 : 0 2-OH (21.4 %) and C14 : 0 (11.7 %). Additionally, the strain contained diphosphatidylglycerol (DPG) and phosphatidylethanolamine (PE), as well as unidentified phospholipids and unidentified glycolipids. The glucose fermentation products of LFL-14T were acetate and butyrate. In summary, On the basis of its chemotaxonomic, phenotypic, phylogenetic and phylogenomic properties, strain LFL-14T (= CGMCC 1.18005T = KCTC 25580T) is identified as representing a novel species of the genus Eubacterium, for which the name Eubacterium album sp. nov. is proposed.

Advances in Culturomics Research on the Human Gut Microbiome: Optimizing Medium Composition and Culture Techniques for Enhanced Microbial Discovery

Despite considerable advancements achieved using next-generation sequencing technologies in exploring microbial diversity, several species of the gut microbiome remain unknown. In this transformative era, culturomics has risen to prominence as a pivotal approach in unveiling realms of microbial diversity that were previously deemed inaccessible. Utilizing innovative strategies to optimize growth and culture medium composition, scientists have successfully cultured hard-to-cultivate microbes. This progress has fostered the discovery and understanding of elusive microbial entities, highlighting their essential role in human health and disease paradigms. In this review, we emphasize the importance of culturomics research on the gut microbiome and provide new theories and insights for expanding microbial diversity via the optimization of cultivation conditions.

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

BACKGROUND

Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible.

RESULTS

Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets.

CONCLUSIONS

Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Double emulsions as a high-throughput enrichment and isolation platform for slower-growing microbes

Our understanding of in situ microbial physiology is primarily based on physiological characterization of fast-growing and readily-isolatable microbes. Microbial enrichments to obtain novel isolates with slower growth rates or physiologies adapted to low nutrient environments are plagued by intrinsic biases for fastest-growing species when using standard laboratory isolation protocols. New cultivation tools to minimize these biases and enrich for less well-studied taxa are needed. In this study, we developed a high-throughput bacterial enrichment platform based on single cell encapsulation and growth within double emulsions (GrowMiDE). We showed that GrowMiDE can cultivate many different microorganisms and enrich for underrepresented taxa that are never observed in traditional batch enrichments. For example, preventing dominance of the enrichment by fast-growing microbes due to nutrient privatization within the double emulsion droplets allowed cultivation of slower-growing Negativicutes and Methanobacteria from stool samples in rich media enrichment cultures. In competition experiments between growth rate and growth yield specialist strains, GrowMiDE enrichments prevented competition for shared nutrient pools and enriched for slower-growing but more efficient strains. Finally, we demonstrated the compatibility of GrowMiDE with commercial fluorescence-activated cell sorting (FACS) to obtain isolates from GrowMiDE enrichments. Together, GrowMiDE + DE-FACS is a promising new high-throughput enrichment platform that can be easily applied to diverse microbial enrichments or screens.

Metabolite profiling of human-originated Lachnospiraceae at the strain level

The human gastrointestinal (GI) tract harbors diverse microbes, and the family Lachnospiraceae is one of the most abundant and widely occurring bacterial groups in the human GI tract. Beneficial and adverse effects of the Lachnospiraceae on host health were reported, but the diversities at species/strain levels as well as their metabolites of Lachnospiraceae have been, so far, not well documented. In the present study, we report on the collection of 77 human-originated Lachnospiraceae species (please refer hLchsp, https://hgmb.nmdc.cn/subject/lachnospiraceae) and the in vitro metabolite profiles of 110 Lachnospiraceae strains (https://hgmb.nmdc.cn/subject/lachnospiraceae/metabolites). The Lachnospiraceae strains in hLchsp produced 242 metabolites of 17 categories. The larger categories were alcohols (89), ketones (35), pyrazines (29), short (C2-C5), and long (C > 5) chain acids (31), phenols (14), aldehydes (14), and other 30 compounds. Among them, 22 metabolites were aromatic compounds. The well-known beneficial gut microbial metabolite, butyric acid, was generally produced by many Lachnospiraceae strains, and Agathobacter rectalis strain Lach-101 and Coprococcus comes strain NSJ-173 were the top 2 butyric acid producers, as 331.5 and 310.9 mg/L of butyric acids were produced in vitro, respectively. Further analysis of the publicly available cohort-based volatile-metabolomic data sets of human feces revealed that over 30% of the prevailing volatile metabolites were covered by Lachnospiraceae metabolites identified in this study. This study provides Lachnospiraceae strain resources together with their metabolic profiles for future studies on host-microbe interactions and developments of novel probiotics or biotherapies.

Precise strategies for selecting probiotic bacteria in treatment of intestinal bacterial dysfunctional diseases

Abundant microbiota resides in the organs of the body, which utilize the nutrition and form a reciprocal relationship with the host. The composition of these microbiota changes under different pathological conditions, particularly in response to stress and digestive diseases, making the microbial composition and health of the hosts body interdependent. Probiotics are living microorganisms that have demonstrated beneficial effects on physical health and as such are used as supplements to ameliorate symptoms of various digestive diseases by optimizing microbial composition of the gut and restore digestive balance. However, the supplementary effect does not achieve the expected result. Therefore, a targeted screening strategy on probiotic bacteria is crucial, owing to the presence of several bacterial strains. Core bacteria work effectively in maintaining microbiological homeostasis and stabilization in the gastrointestinal tract. Some of the core bacteria can be inherited and acquired from maternal pregnancy and delivery; others can be acquired from contact with the mother, feces, and the environment. Knowing the genera and functions of the core bacteria could be vital in the isolation and selection of probiotic bacteria for supplementation. In addition, other supporting strains of probiotic bacteria are also needed. A comprehensive strategy for mining both core and supporting bacteria before its clinical use is needed. Using metagenomics or other methods of estimation to discern the typically differentiated strains of bacteria is another important strategy to treat dysbiosis. Hence, these two factors are significant to carry out targeted isolation and selection of the functional strains to compose the resulting probiotic preparation for application in both research and clinical use. In conclusion, precise probiotic supplementation, by screening abundant strains of bacteria and isolating specific probiotic strains, could rapidly establish the core microbiota needed to confer resilience, particularly in bacterial dysfunctional diseases. This approach can help identify distinct bacteria which can be used to improve supplementation therapies.

Strain level and comprehensive microbiome analysis in inflammatory bowel disease via multi-technology meta-analysis identifies key bacterial influencers of disease

Objective

Inflammatory bowel disease (IBD) is a heterogenous disease in which the microbiome has been shown to play an important role. However, the precise homeostatic or pathological functions played by bacteria remain unclear. Most published studies report taxa-disease associations based on single-technology analysis of a single cohort, potentially biasing results to one clinical protocol, cohort, and molecular analysis technology. To begin to address this key question, precise identification of the bacteria implicated in IBD across cohorts is necessary.

Methods

We sought to take advantage of the numerous and diverse studies characterizing the microbiome in IBD to develop a multi-technology meta-analysis (MTMA) as a platform for aggregation of independently generated datasets, irrespective of DNA-profiling technique, in order to uncover the consistent microbial modulators of disease. We report the largest strain-level survey of IBD, integrating microbiome profiles from 3,407 samples from 21 datasets spanning 15 cohorts, three of which are presented for the first time in the current study, characterized using three DNA-profiling technologies, mapping all nucleotide data against known, culturable strain reference data.

Results

We identify several novel IBD associations with culturable strains that have so far remained elusive, including two genome-sequenced but uncharacterized Lachnospiraceae strains consistently decreased in both the gut luminal and mucosal contents of patients with IBD, and demonstrate that these strains are correlated with inflammation-related pathways that are known mechanisms targeted for treatment. Furthermore, comparative MTMA at the species versus strain level reveals that not all significant strain associations resulted in a corresponding species-level significance and conversely significant species associations are not always re-captured at the strain level.

Conclusion

We propose MTMA for uncovering experimentally testable strain-disease associations that, as demonstrated here, are beneficial in discovering mechanisms underpinning microbiome impact on disease or novel targets for therapeutic interventions.

Culturomics, a potential approach paving the way toward bacteriotherapy

The human microbiota has been extensively studied over the past decade to describe its role in health and diseases. Numerous studies showed the presence of bacterial imbalance in a variety of human health conditions, suggesting great potential for the development of bacteriotherapies. Identifying mechanisms involving the human microbiota has been very challenging due to the complex data generated by molecular approaches and the limited number of organisms isolated by culture and described. This review summarizes the efforts done to describe the human microbiota through culturomics and the advancements in culturing the organisms residing at different body sites.

Anaerobic single-cell dispensing facilitates the cultivation of human gut bacteria

Cultivation via classical agar plate (CAP) approaches is widely used to study microbial communities, but they are time-consuming. An alternative approach is the application of single-cell dispensing (SCD), which allows high-throughput, label-free sorting of microscopic particles. We aimed to develop a new anaerobic SCD workflow to cultivate human gut bacteria and compared it with CAP using faecal communities on three rich culture media. We found that the SCD approach significantly decreased the experimental time to obtain pure cultures from 17 ± 4 to 5 ± 0 days, while the isolate diversity and relative abundance coverage were comparable for both approaches. We further tested the total captured fraction by sequencing the sorted bacteria directly after growth as bulk biomass from 2400 dispensed single cells without downstream identification of individual strains. In this approach, the cultured fraction increased from 35.2% to 52.2% for SCD, highlighting the potential for deeper cultivation projects from single samples. SCD-based cultivation also captured species not detected by sequencing (16 ± 5 per sample, including seven novel taxa). From this work, 82 human gut bacterial species across five phyla (Actinobacteriota, Bacteroidota, Desulfobacterota, Firmicutes and Proteobacteria) and 24 families were obtained, including the first cultured member of 11 novel genera and 10 novel species that were fully characterized taxonomically.

Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank

BACKGROUND

In gut microbiome studies, the cultured gut microbial resource plays essential roles, such as helping to unravel gut microbial functions and host-microbe interactions. Although several major studies have been performed to elucidate the cultured human gut microbiota, up to 70% of the Unified Human Gastrointestinal Genome species have not been cultured to date. Large-scale gut microbial isolation and identification as well as availability to the public are imperative for gut microbial studies and further characterizing human gut microbial functions.

RESULTS

In this study, we constructed a human Gut Microbial Biobank (hGMB; homepage: hgmb.nmdc.cn ) through the cultivation of 10,558 isolates from 31 sample mixtures of 239 fresh fecal samples from healthy Chinese volunteers, and deposited 1170 strains representing 400 different species in culture collections of the International Depository Authority for long-term preservation and public access worldwide. Following the rules of the International Code of Nomenclature of Prokaryotes, 102 new species were characterized and denominated, while 28 new genera and 3 new families were proposed. hGMB represented over 80% of the common and dominant human gut microbial genera and species characterized from global human gut 16S rRNA gene amplicon data (n = 11,647) and cultured 24 "most-wanted" and "medium priority" taxa proposed by the Human Microbiome Project. We in total sequenced 115 genomes representing 102 novel taxa and 13 previously known species. Further in silico analysis revealed that the newly sequenced hGMB genomes represented 22 previously uncultured species in the Unified Human Gastrointestinal Genome (UHGG) and contributed 24 representatives of potentially "dark taxa" that had not been discovered by UHGG. The nonredundant gene catalogs generated from the hGMB genomes covered over 50% of the functionally known genes (KEGG orthologs) in the largest global human gut gene catalogs and approximately 10% of the "most wanted" functionally unknown proteins in the FUnkFams database.

CONCLUSIONS

A publicly accessible human Gut Microbial Biobank (hGMB) was established that contained 1170 strains and represents 400 human gut microbial species. hGMB expands the gut microbial resources and genomic repository by adding 102 novel species, 28 new genera, 3 new families, and 115 new genomes of human gut microbes. Video abstract.

Automated analysis of genomic sequences facilitates high-throughput and comprehensive description of bacteria

The study of microbial communities is hampered by the large fraction of still unknown bacteria. However, many of these species have been isolated, yet lack a validly published name or description. The validation of names for novel bacteria requires that the uniqueness of those taxa is demonstrated and their properties are described. The accepted format for this is the protologue, which can be time-consuming to create. Hence, many research fields in microbiology and biotechnology will greatly benefit from new approaches that reduce the workload and harmonise the generation of protologues.We have developed Protologger, a bioinformatic tool that automatically generates all the necessary readouts for writing a detailed protologue. By producing multiple taxonomic outputs, functional features and ecological analysis using the 16S rRNA gene and genome sequences from a single species, the time needed to gather the information for describing novel taxa is substantially reduced. The usefulness of Protologger was demonstrated by using three published isolate collections to describe 34 novel taxa, encompassing 17 novel species and 17 novel genera, including the automatic generation of ecologically and functionally relevant names. We also highlight the need to utilise multiple taxonomic delineation methods, as while inconsistencies between each method occur, a combined approach provides robust placement. Protologger is open source; all scripts and datasets are available, along with a webserver at www.protologger.de.

Extensive microbial diversity within the chicken gut microbiome revealed by metagenomics and culture

BACKGROUND

The chicken is the most abundant food animal in the world. However, despite its importance, the chicken gut microbiome remains largely undefined. Here, we exploit culture-independent and culture-dependent approaches to reveal extensive taxonomic diversity within this complex microbial community.

RESULTS

We performed metagenomic sequencing of fifty chicken faecal samples from two breeds and analysed these, alongside all (n = 582) relevant publicly available chicken metagenomes, to cluster over 20 million non-redundant genes and to construct over 5,500 metagenome-assembled bacterial genomes. In addition, we recovered nearly 600 bacteriophage genomes. This represents the most comprehensive view of taxonomic diversity within the chicken gut microbiome to date, encompassing hundreds of novel candidate bacterial genera and species. To provide a stable, clear and memorable nomenclature for novel species, we devised a scalable combinatorial system for the creation of hundreds of well-formed Latin binomials. We cultured and genome-sequenced bacterial isolates from chicken faeces, documenting over forty novel species, together with three species from the genus Escherichia, including the newly named species Escherichia whittamii.

CONCLUSIONS

Our metagenomic and culture-based analyses provide new insights into the bacterial, archaeal and bacteriophage components of the chicken gut microbiome. The resulting datasets expand the known diversity of the chicken gut microbiome and provide a key resource for future high-resolution taxonomic and functional studies on the chicken gut microbiome.

Innovations to culturing the uncultured microbial majority

Despite the surge of microbial genome data, experimental testing is important to confirm inferences about the cell biology, ecological roles and evolution of microorganisms. As the majority of archaeal and bacterial diversity remains uncultured and poorly characterized, culturing is a priority. The growing interest in and need for efficient cultivation strategies has led to many rapid methodological and technological advances. In this Review, we discuss common barriers that can hamper the isolation and culturing of novel microorganisms and review emerging, innovative methods for targeted or high-throughput cultivation. We also highlight recent examples of successful cultivation of novel archaea and bacteria, and suggest key microorganisms for future cultivation attempts.

Recent advances in culture-based gut microbiome research

Gut microbes affect the physiology of their hosts. Studying their diversity and functions is thus of utmost importance as it will open new avenues towards the discovery of new biomolecules and the treatment of diseases. Gut microbiome research is currently boosted by the unification of metagenomics, which has dominated the field in the last two decades, and cultivation, which is experiencing a renaissance. Each of these approaches has advantages and drawbacks that can be overcome if used synergistically. In this brief article, we summarize recent literature and own studies on the cultivation of gut microbes, provide a succinct status quo of cultured fractions and collections of isolates, and give short opinions on challenges and next steps to take.

Deep Learning for Integrated Analysis of Insulin Resistance with Multi-Omics Data

Technological advances in next-generation sequencing (NGS) have made it possible to uncover extensive and dynamic alterations in diverse molecular components and biological pathways across healthy and diseased conditions. Large amounts of multi-omics data originating from emerging NGS experiments require feature engineering, which is a crucial step in the process of predictive modeling. The underlying relationship among multi-omics features in terms of insulin resistance is not well understood. In this study, using the multi-omics data of type II diabetes from the Integrative Human Microbiome Project, from 10,783 features, we conducted a data analytic approach to elucidate the relationship between insulin resistance and multi-omics features, including microbiome data. To better explain the impact of microbiome features on insulin classification, we used a developed deep neural network interpretation algorithm for each microbiome feature’s contribution to the discriminative model output in the samples.

Revealing the in vivo growth and division patterns of mouse gut bacteria

Current techniques for studying gut microbiota are unable to answer some important microbiology questions, like how different bacteria grow and divide in the gut. We propose a method that integrates the use of sequential d-amino acid-based in vivo metabolic labeling with fluorescence in situ hybridization (FISH), for characterizing the growth and division patterns of gut bacteria. After sequentially administering two d-amino acid-based probes containing different fluorophores to mice by gavage, the resulting dual-labeled peptidoglycans provide temporal information on cell wall synthesis of gut bacteria. Following taxonomic identification with FISH probes, the growth and division patterns of the corresponding bacterial taxa, including species that cannot be cultured separately in vitro, are revealed. Our method offers a facile yet powerful tool for investigating the in vivo growth dynamics of the bacterial gut microbiota, which will advance our understanding of bacterial cytology and facilitate elucidation of the basic microbiology of this gut "dark matter."

Strategies and advancements in human microbiome description and the importance of culturomics

The human microbiota gained a big interest among the scientific community with numerous studies being performed to better understand its role in health and diseases. Even with all the success achieved in studying the bacterial populations at the different body sites and its interaction among each other and with the host, some links remain missing and might have therapeutic benefits. In this review, we summarize the main means used for bacterial identification, human microbiota description and the role of culturomics in leading the way towards the development of new bacterio-therapeutic approaches.

Evaluation of computational methods for human microbiome analysis using simulated data

BACKGROUND

Our understanding of the composition, function, and health implications of human microbiota has been advanced by high-throughput sequencing and the development of new genomic analyses. However, trade-offs among alternative strategies for the acquisition and analysis of sequence data remain understudied.

METHODS

We assessed eight popular taxonomic profiling pipelines; MetaPhlAn2, metaMix, PathoScope 2.0, Sigma, Kraken, ConStrains, Centrifuge and Taxator-tk, against a battery of metagenomic datasets simulated from real data. The metagenomic datasets were modeled on 426 complete or permanent draft genomes stored in the Human Oral Microbiome Database and were designed to simulate various experimental conditions, both in the design of a putative experiment; read length (75-1,000 bp reads), sequence depth (100K-10M), and in metagenomic composition; number of species present (10, 100, 426), species distribution. The sensitivity and specificity of each of the pipelines under various scenarios were measured. We also estimated the relative root mean square error and average relative error to assess the abundance estimates produced by different methods. Additional datasets were generated for five of the pipelines to simulate the presence within a metagenome of an unreferenced species, closely related to other referenced species. Additional datasets were also generated in order to measure computational time on datasets of ever-increasing sequencing depth (up to 6 × 107).

RESULTS

Testing of eight pipelines against 144 simulated metagenomic datasets initially produced 1,104 discrete results. Pipelines using a marker gene strategy; MetaPhlAn2 and ConStrains, were overall less sensitive, than other pipelines; with the notable exception of Taxator-tk. This difference in sensitivity was largely made up in terms of runtime, significantly lower than more sensitive pipelines that rely on whole-genome alignments such as PathoScope2.0. However, pipelines that used strategies to speed-up alignment between genomic references and metagenomic reads, such as kmerization, were able to combine both high sensitivity and low run time, as is the case with Kraken and Centrifuge. Absent species genomes in the database mostly led to assignment of reads to the most closely related species available in all pipelines. Our results therefore suggest that taxonomic profilers that use kmerization have largely superseded those that use gene markers, coupling low run times with high sensitivity and specificity. Taxonomic profilers using more time-consuming read reassignment, such as PathoScope 2.0, provided the most sensitive profiles under common metagenomic sequencing scenarios. All the results described and discussed in this paper can be visualized using the dedicated R Shiny application (https://github.com/microgenomics/HumanMicrobiomeAnalysis). All of our datasets, pipelines and results are made available through the GitHub repository for future benchmarking.

Droplet-based high-throughput cultivation for accurate screening of antibiotic resistant gut microbes

Traditional cultivation approaches in microbiology are labor-intensive, low-throughput, and yield biased sampling of environmental microbes due to ecological and evolutionary factors. New strategies are needed for ample representation of rare taxa and slow-growers that are often outcompeted by fast-growers in cultivation experiments. Here we describe a microfluidic platform that anaerobically isolates and cultivates microbial cells in millions of picoliter droplets and automatically sorts them based on colony density to enhance slow-growing organisms. We applied our strategy to a fecal microbiota transplant (FMT) donor stool using multiple growth media, and found significant increase in taxonomic richness and larger representation of rare and clinically relevant taxa among droplet-grown cells compared to conventional plates. Furthermore, screening the FMT donor stool for antibiotic resistance revealed 21 populations that evaded detection in plate-based assessment of antibiotic resistance. Our method improves cultivation-based surveys of diverse microbiomes to gain deeper insights into microbial functioning and lifestyles.

MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data

Motivation

Analysis toolkits for shotgun metagenomic data achieve strain-level characterization of complex microbial communities by capturing intra-species gene content variation. Yet, these tools are hampered by the extent of reference genomes that are far from covering all microbial variability, as many species are still not sequenced or have only few strains available. Binning co-abundant genes obtained from de novo assembly is a powerful reference-free technique to discover and reconstitute gene repertoire of microbial species. While current methods accurately identify species core parts, they miss many accessory genes or split them into small gene groups that remain unassociated to core clusters.

Results

We introduce MSPminer, a computationally efficient software tool that reconstitutes Metagenomic Species Pan-genomes (MSPs) by binning co-abundant genes across metagenomic samples. MSPminer relies on a new robust measure of proportionality coupled with an empirical classifier to group and distinguish not only species core genes but accessory genes also. Applied to a large scale metagenomic dataset, MSPminer successfully delineates in a few hours the gene repertoires of 1661 microbial species with similar specificity and higher sensitivity than existing tools. The taxonomic annotation of MSPs reveals microorganisms hitherto unknown and brings coherence in the nomenclature of the species of the human gut microbiota. The provided MSPs can be readily used for taxonomic profiling and biomarkers discovery in human gut metagenomic samples. In addition, MSPminer can be applied on gene count tables from other ecosystems to perform similar analyses.

Availability and implementation

The binary is freely available for non-commercial users at www.enterome.com/downloads.

Supplementary information

Supplementary data are available at Bioinformatics online.

Isolation and characterization of diverse microbial representatives from the human skin microbiome

BACKGROUND

The skin micro-environment varies across the body, but all sites are host to microorganisms that can impact skin health. Some of these organisms are true commensals which colonize a unique niche on the skin, while open exposure of the skin to the environment also results in the transient presence of diverse microbes with unknown influences on skin health. Culture-based studies of skin microbiota suggest that skin microbes can affect skin properties, immune responses, pathogen growth, and wound healing.

RESULTS

In this work, we greatly expanded the diversity of available commensal organisms by collecting > 800 organisms from 3 body sites of 17 individuals. Our collection includes > 30 bacterial genera and 14 fungal genera, with Staphylococcus and Micrococcus as the most prevalent isolates. We characterized a subset of skin isolates for the utilization of carbon compounds found on the skin surface. We observed that members of the skin microbiota have the capacity to metabolize amino acids, steroids, lipids, and sugars, as well as compounds originating from personal care products.

CONCLUSIONS

This collection is a resource that will support skin microbiome research with the potential for discovery of novel small molecules, development of novel therapeutics, and insight into the metabolic activities of the skin microbiota. We believe this unique resource will inform skin microbiome management to benefit skin health. Video abstract.

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

Improving Characterization of Understudied Human Microbiomes Using Targeted Phylogenetics

Whole-genome bacterial sequences are required to better understand microbial functions, niche-specific bacterial metabolism, and disease states. Although genomic sequences are available for many of the human-associated bacteria from commonly tested body habitats (e.g., feces), as few as 13% of bacterium-derived reads from other sites such as the skin map to known bacterial genomes. To facilitate a better characterization of metagenomic shotgun reads from underrepresented body sites, we collected over 10,000 bacterial isolates originating from 14 human body habitats, identified novel taxonomic groups based on full-length 16S rRNA gene sequences, clustered the sequences to ensure that no individual taxonomic group was overselected for sequencing, prioritized bacteria from underrepresented body sites (such as skin and respiratory and urinary tracts), and sequenced and assembled genomes for 665 new bacterial strains. Here, we show that addition of these genomes improved read mapping rates of Human Microbiome Project (HMP) metagenomic samples by nearly 30% for the previously underrepresented phylum Fusobacteria, and 27.5% of the novel genomes generated here had high representation in at least one of the tested HMP samples, compared to 12.5% of the sequences in the public databases, indicating an enrichment of useful novel genomic sequences resulting from the prioritization procedure. As our understanding of the human microbiome continues to improve and to enter the realm of therapy developments, targeted approaches such as this to improve genomic databases will increase in importance from both an academic and a clinical perspective.IMPORTANCE The human microbiome plays a critically important role in health and disease, but current understanding of the mechanisms underlying the interactions between the varying microbiome and the different host environments is lacking. Having access to a database of fully sequenced bacterial genomes provides invaluable insights into microbial functions, but currently sequenced genomes for the human microbiome have largely come from a limited number of body sites (primarily feces), while other sites such as the skin, respiratory tract, and urinary tract are underrepresented, resulting in as little as 13% of bacterium-derived reads mapping to known bacterial genomes. Here, we sequenced and assembled 665 new bacterial genomes, prioritized from a larger database to select underrepresented body sites and bacterial taxa in the existing databases. As a result, we substantially improve mapping rates for samples from the Human Microbiome Project and provide an important contribution to human bacterial genomic databases for future studies.

A library of human gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome research

Our understanding of how the gut microbiome interacts with its human host has been restrained by limited access to longitudinal datasets to examine stability and dynamics, and by having only a few isolates to test mechanistic hypotheses. Here, we present the Broad Institute-OpenBiome Microbiome Library (BIO-ML), a comprehensive collection of 7,758 gut bacterial isolates paired with 3,632 genome sequences and longitudinal multi-omics data. We show that microbial species maintain stable population sizes within and across humans and that commonly used 'omics' survey methods are more reliable when using averages over multiple days of sampling. Variation of gut metabolites within people over time is associated with amino acid levels, and differences across people are associated with differences in bile acids. Finally, we show that genomic diversification can be used to infer eco-evolutionary dynamics and in vivo selection pressures for strains within individuals. The BIO-ML is a unique resource designed to enable hypothesis-driven microbiome research.

The Integrative Human Microbiome Project

The NIH Human Microbiome Project (HMP) has been carried out over ten years and two phases to provide resources, methods, and discoveries that link interactions between humans and their microbiomes to health-related outcomes. The recently completed second phase, the Integrative Human Microbiome Project, comprised studies of dynamic changes in the microbiome and host under three conditions: pregnancy and preterm birth; inflammatory bowel diseases; and stressors that affect individuals with prediabetes. The associated research begins to elucidate mechanisms of host-microbiome interactions under these conditions, provides unique data resources (at the HMP Data Coordination Center), and represents a paradigm for future multi-omic studies of the human microbiome.

The Integrative Human Microbiome Project

The NIH Human Microbiome Project (HMP) has been carried out over ten years and two phases to provide resources, methods, and discoveries that link interactions between humans and their microbiomes to health-related outcomes. The recently completed second phase, the Integrative Human Microbiome Project, comprised studies of dynamic changes in the microbiome and host under three conditions: pregnancy and preterm birth; inflammatory bowel diseases; and stressors that affect individuals with prediabetes. The associated research begins to elucidate mechanisms of host-microbiome interactions under these conditions, provides unique data resources (at the HMP Data Coordination Center), and represents a paradigm for future multi-omic studies of the human microbiome.

Microbiome Analytics of the Gut Microbiota in Patients With Juvenile Idiopathic Arthritis: A Longitudinal Observational Cohort Study

Objective

To assess the composition of gut microbiota in Italian and Dutch patients with juvenile idiopathic arthritis (JIA) at baseline, with inactive disease, and with persistent activity compared to healthy controls.

Methods

In a multicenter, prospective, observational cohort study, fecal samples were collected at baseline from 78 Italian and 21 Dutch treatment‐naive JIA patients with <6 months of disease duration and compared to 107 geographically matched samples from healthy children. Forty‐four follow‐up samples from patients with inactive disease and 25 follow‐up samples from patients with persistent activity were analyzed. Gut microbiota composition was determined by 16S ribosomal RNA–based metagenomics. Alpha‐ and β‐diversity were computed, and log ratios of relative abundance were compared between patients and healthy controls using random forest models and logistic regression.

Results

Baseline samples from Italian patients showed reduced richness compared to healthy controls (P < 0.001). Random forest models distinguished between Italian patient baseline samples and healthy controls and suggested differences between Dutch patient samples and healthy controls (areas under the curve >0.99 and 0.71, respectively). The operational taxonomic units (OTUs) of Erysipelotrichaceae (increased in patients), Allobaculum (decreased in patients), and Faecalibacterium prausnitzii (increased in patients) showed different relative abundance in Italian patient baseline samples compared to controls after controlling for multiple comparisons. Some OTUs differed between Dutch patient samples and healthy controls, but no evidence remained after controlling for multiple comparisons. No differences were found in paired analysis between Italian patient baseline and inactive disease samples.

Conclusion

Our findings show evidence for dysbiosis in JIA patients. Only patient/control status, age, and geographic origin appear to be drivers of the microbiota profiles, regardless of disease activity stage, inflammation, and markers of autoimmunity.

New insights from uncultivated genomes of the global human gut microbiome

The genome sequences of many species of the human gut microbiome remain unknown, largely owing to challenges in cultivating microorganisms under laboratory conditions. Here we address this problem by reconstructing 60,664 draft prokaryotic genomes from 3,810 faecal metagenomes, from geographically and phenotypically diverse humans. These genomes provide reference points for 2,058 newly identified species-level operational taxonomic units (OTUs), which represents a 50% increase over the previously known phylogenetic diversity of sequenced gut bacteria. On average, the newly identified OTUs comprise 33% of richness and 28% of species abundance per individual, and are enriched in humans from rural populations. A meta-analysis of clinical gut-microbiome studies pinpointed numerous disease associations for the newly identified OTUs, which have the potential to improve predictive models. Finally, our analysis revealed that uncultured gut species have undergone genome reduction that has resulted in the loss of certain biosynthetic pathways, which may offer clues for improving cultivation strategies in the future.

A review of 10 years of human microbiome research activities at the US National Institutes of Health, Fiscal Years 2007-2016

The National Institutes of Health (NIH) is the primary federal government agency for biomedical research in the USA. NIH provides extensive support for human microbiome research with 21 of 27 NIH Institutes and Centers (ICs) currently funding this area through their extramural research programs. This analysis of the NIH extramural portfolio in human microbiome research briefly reviews the early history of this field at NIH, summarizes the program objectives and the resources developed in the recently completed 10-year (fiscal years 2007-2016) $215 M Human Microbiome Project (HMP) program, evaluates the scope and range of the $728 M NIH investment in extramural human microbiome research activities outside of the HMP over fiscal years 2012-2016, and highlights some specific areas of research which emerged from this investment. This analysis closes with a few comments on the technical needs and knowledge gaps which remain for this field to be able to advance over the next decade and for the outcomes of this research to be able to progress to microbiome-based interventions for treating disease and supporting health.

Bello González T, Zoetendal EG, van Passel MWJ, Smidt H. High throughput cultivation-based screening on porous aluminum oxide chips allows targeted isolation of antibiotic resistant human gut bacteria

The emergence of bacterial pathogens that are resistant to clinical antibiotics poses an increasing risk to human health. An important reservoir from which bacterial pathogens can acquire resistance is the human gut microbiota. However, thus far, a substantial fraction of the gut microbiota remains uncultivated and has been little-studied with respect to its resistance reservoir-function. Here, we aimed to isolate yet uncultivated resistant gut bacteria by a targeted approach. Therefore, faecal samples from 20 intensive care patients who had received the prophylactic antibiotic treatment selective digestive decontamination (SDD), i.e. tobramycin, polymyxin E, amphotericin B and cefotaxime, were inoculated anaerobically on porous aluminium oxide chips placed on top of poor and rich agar media, including media supplemented with the SDD antibiotics. Biomass growing on the chips was analysed by 16S rRNA gene amplicon sequencing, showing large inter-individual differences in bacterial cultivability, and enrichment of a range of taxonomically diverse operational taxonomic units (OTUs). Furthermore, growth of Ruminococcaceae (2 OTUs), Enterobacteriaceae (6 OTUs) and Lachnospiraceae (4 OTUs) was significantly inhibited by the SDD antibiotics. Strains belonging to 16 OTUs were candidates for cultivation to pure culture as they shared ≤95% sequence identity with the closest type strain and had a relative abundance of ≥2%. Six of these OTUs were detected on media containing SDD antibiotics, and as such were prime candidates to be studied regarding antibiotic resistance. One of these six OTUs was obtained in pure culture using targeted isolation. This novel strain was resistant to the antibiotics metrodinazole and imipenem. It was initially classified as member of the Ruminococcaceae, though later it was found to share 99% nucleotide identity with the recently published Sellimonas intestinalis BR72T. In conclusion, we show that high-throughput cultivation-based screening of microbial communities can guide targeted isolation of bacteria that serve as reservoirs of antibiotic resistance.

New Insights into Human Nostril Microbiome from the Expanded Human Oral Microbiome Database (eHOMD): a Resource for the Microbiome of the Human Aerodigestive Tract

The expanded Human Oral Microbiome Database (eHOMD) is a comprehensive microbiome database for sites along the human aerodigestive tract that revealed new insights into the nostril microbiome. The eHOMD provides well-curated 16S rRNA gene reference sequences linked to available genomes and enables assignment of species-level taxonomy to most next-generation sequences derived from diverse aerodigestive tract sites, including the nasal passages, sinuses, throat, esophagus, and mouth. Using minimum entropy decomposition coupled with the RDP Classifier and our eHOMD V1-V3 training set, we reanalyzed 16S rRNA V1-V3 sequences from the nostrils of 210 Human Microbiome Project participants at the species level, revealing four key insights. First, we discovered that Lawsonella clevelandensis, a recently named bacterium, and Neisseriaceae [G-1] HMT-174, a previously unrecognized bacterium, are common in adult nostrils. Second, just 19 species accounted for 90% of the total sequences from all participants. Third, 1 of these 19 species belonged to a currently uncultivated genus. Fourth, for 94% of the participants, 2 to 10 species constituted 90% of their sequences, indicating that the nostril microbiome may be represented by limited consortia. These insights highlight the strengths of the nostril microbiome as a model system for studying interspecies interactions and microbiome function. Also, in this cohort, three common nasal species (Dolosigranulum pigrum and two Corynebacterium species) showed positive differential abundance when the pathobiont Staphylococcus aureus was absent, generating hypotheses regarding colonization resistance. By facilitating species-level taxonomic assignment to microbes from the human aerodigestive tract, the eHOMD is a vital resource enhancing clinical relevance of microbiome studies. IMPORTANCE The eHOMD (http://www.ehomd.org) is a valuable resource for researchers, from basic to clinical, who study the microbiomes and the individual microbes in body sites in the human aerodigestive tract, which includes the nasal passages, sinuses, throat, esophagus, and mouth, and the lower respiratory tract, in health and disease. The eHOMD is an actively curated, web-based, open-access resource. eHOMD provides the following: (i) species-level taxonomy based on grouping 16S rRNA gene sequences at 98.5% identity, (ii) a systematic naming scheme for unnamed and/or uncultivated microbial taxa, (iii) reference genomes to facilitate metagenomic, metatranscriptomic, and proteomic studies and (iv) convenient cross-links to other databases (e.g., PubMed and Entrez). By facilitating the assignment of species names to sequences, the eHOMD is a vital resource for enhancing the clinical relevance of 16S rRNA gene-based microbiome studies, as well as metagenomic studies.

The human gut pan-microbiome presents a compositional core formed by discrete phylogenetic units

The complex community of microbes living in the human gut plays an important role in host wellbeing. However, defining a ‘healthy’ gut microbiome in terms of composition has remained an elusive task, despite its anticipated medical and scientific importance. In this regard, a central question has been if there is a ‘core’ microbiome consisting of bacterial groups common to all healthy humans. Recent studies have been able to define a compositional core in human gut microbiome datasets in terms of taxonomic assignments. However, the description of the core microbiome in terms of taxonomic assignments may not be adequate when considering subsequent analyses and applications. Through the implementation of a dynamic clustering approach in the meta-analyisis of comprehensive 16S rRNA marker gene datasets, this study found that the human gut pan-microbiome presents a preeminent compositional core comprised of discrete units of varying phylogenetic depth present in all individuals studied. Since both microbial traits and ecological coherence show signs of phylogenetic conservation, this outcome provides a new conceptual framework in the study of the ecosystem, as well as important practical considerations which should be taken into account in future research.

The contribution of culturomics to the repertoire of isolated human bacterial and archaeal species

After a decade of research and metagenomic analyses, our knowledge of the human microbiota appears to have reached a plateau despite promising results. In many studies, culture has proven to be essential in describing new prokaryotic species and filling metagenomic gaps. In 2015, only 2172 different prokaryotic species were reported to have been isolated at least once from the human body as pathogens or commensals. In this review, we update the previous repertoire by reporting the different species isolated from the human body to date, increasing it by 28% to reach a total of 2776 species associated with human beings. They have been classified into 11 different phyla, mostly the Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. Finally, culturomics contributed up to 66.2% towards updating this repertoire by reporting 400 species, of which 288 were novel. This demonstrates the need to continue the culturing work, which seems essential in order to decipher the hidden human microbial content.

Novel human microbe-disease associations inference based on network consistency projection

Increasing evidence shows that microbes are closely related to various human diseases. Obtaining a comprehensive and detailed understanding of the relationships between microbes and diseases would not only be beneficial to disease prevention, diagnosis and prognosis, but also would lead to the discovery of new drugs. However, because of a lack of data, little effort has been made to predict novel microbe-disease associations. To date, few methods have been proposed to solve the problem. In this study, we developed a new computational model based on network consistency projection to infer novel human microbe-disease associations (NCPHMDA) by integrating Gaussian interaction profile kernel similarity of microbes and diseases, and symptom-based disease similarity. NCPHMDA is a non-parametric and global network based model that combines microbe space projection and disease space projection to achieve the final prediction. Experimental results demonstrated that the integrated space projection of microbes and diseases, and symptom-based disease similarity played roles in the model performance. Cross validation frameworks and case studies further illustrated the superior predictive performance over other methods.

The First Microbial Colonizers of the Human Gut: Composition, Activities, and Health Implications of the Infant Gut Microbiota

The human gut microbiota is engaged in multiple interactions affecting host health during the host's entire life span. Microbes colonize the neonatal gut immediately following birth. The establishment and interactive development of this early gut microbiota are believed to be (at least partially) driven and modulated by specific compounds present in human milk. It has been shown that certain genomes of infant gut commensals, in particular those of bifidobacterial species, are genetically adapted to utilize specific glycans of this human secretory fluid, thus representing a very intriguing example of host-microbe coevolution, where both partners are believed to benefit. In recent years, various metagenomic studies have tried to dissect the composition and functionality of the infant gut microbiome and to explore the distribution across the different ecological niches of the infant gut biogeography of the corresponding microbial consortia, including those corresponding to bacteria and viruses, in healthy and ill subjects. Such analyses have linked certain features of the microbiota/microbiome, such as reduced diversity or aberrant composition, to intestinal illnesses in infants or disease states that are manifested at later stages of life, including asthma, inflammatory bowel disease, and metabolic disorders. Thus, a growing number of studies have reported on how the early human gut microbiota composition/development may affect risk factors related to adult health conditions. This concept has fueled the development of strategies to shape the infant microbiota composition based on various functional food products. In this review, we describe the infant microbiota, the mechanisms that drive its establishment and composition, and how microbial consortia may be molded by natural or artificial interventions. Finally, we discuss the relevance of key microbial players of the infant gut microbiota, in particular bifidobacteria, with respect to their role in health and disease.

A Robust Framework for Microbial Archaeology

Microbial archaeology is flourishing in the era of high-throughput sequencing, revealing the agents behind devastating historical plagues, identifying the cryptic movements of pathogens in prehistory, and reconstructing the ancestral microbiota of humans. Here, we introduce the fundamental concepts and theoretical framework of the discipline, then discuss applied methodologies for pathogen identification and microbiome characterization from archaeological samples. We give special attention to the process of identifying, validating, and authenticating ancient microbes using high-throughput DNA sequencing data. Finally, we outline standards and precautions to guide future research in the field.

The impact of immigration on microbial community composition in full-scale anaerobic digesters

Anaerobic digestion is widely applied to treat organic waste at wastewater treatment plants. Characterisation of the underlying microbiology represents a source of information to develop strategies for improved operation. Hence, we investigated microbial communities of thirty-two full-scale anaerobic digesters over a six-year period using 16S rRNA gene amplicon sequencing. Sampling of the sludge fed into these systems revealed that several of the most abundant populations were likely inactive and immigrating with the influent. This observation indicates that a failure to consider immigration will interfere with correlation analysis and give an inaccurate picture of the growing microbial community. Furthermore, several abundant OTUs could not be classified to genus level with commonly applied taxonomies, making inference of their function unreliable and comparison to other studies problematic. As such, the existing MiDAS taxonomy was updated to include these abundant phylotypes. The communities of individual digesters surveyed were remarkably similar - with only 300 OTUs representing 80% of the total reads across all plants, and 15% of these identified as non-growing and possibly inactive immigrating microbes. By identifying abundant and growing taxa in anaerobic digestion, this study paves the way for targeted characterisation of the process-important organisms towards an in-depth understanding of the microbiology.

More than just a gut feeling: constraint-based genome-scale metabolic models for predicting functions of human intestinal microbes

The human gut is colonized with a myriad of microbes, with substantial interpersonal variation. This complex ecosystem is an integral part of the gastrointestinal tract and plays a major role in the maintenance of homeostasis. Its dysfunction has been correlated to a wide array of diseases, but the understanding of causal mechanisms is hampered by the limited amount of cultured microbes, poor understanding of phenotypes, and the limited knowledge about interspecies interactions. Genome-scale metabolic models (GEMs) have been used in many different fields, ranging from metabolic engineering to the prediction of interspecies interactions. We provide showcase examples for the application of GEMs for gut microbes and focus on (i) the prediction of minimal, synthetic, or defined media; (ii) the prediction of possible functions and phenotypes; and (iii) the prediction of interspecies interactions. All three applications are key in understanding the role of individual species in the gut ecosystem as well as the role of the microbiota as a whole. Using GEMs in the described fashions has led to designs of minimal growth media, an increased understanding of microbial phenotypes and their influence on the host immune system, and dietary interventions to improve human health. Ultimately, an increased understanding of the gut ecosystem will enable targeted interventions in gut microbial composition to restore homeostasis and appropriate host-microbe crosstalk.

The multi-omics promise in context: from sequence to microbial isolate

The numbers and diversity of microbes in ecosystems within and around us is unmatched, yet most of these microorganisms remain recalcitrant to in vitro cultivation. Various high-throughput molecular techniques, collectively termed multi-omics, provide insights into the genomic structure and metabolic potential as well as activity of complex microbial communities. Nonetheless, pure or defined cultures are needed to (1) decipher microbial physiology and thus test multi-omics-based ecological hypotheses, (2) curate and improve database annotations and (3) realize novel applications in biotechnology. Cultivation thus provides context. In turn, we here argue that multi-omics information awaits integration into the development of novel cultivation strategies. This can build the foundation for a new era of omics information-guided microbial cultivation technology and reduce the inherent trial-and-error search space. This review discusses how information that can be extracted from multi-omics data can be applied for the cultivation of hitherto uncultured microorganisms. Furthermore, we summarize groundbreaking studies that successfully translated information derived from multi-omics into specific media formulations, screening techniques and selective enrichments in order to obtain novel targeted microbial isolates. By integrating these examples, we conclude with a proposed workflow to facilitate future omics-aided cultivation strategies that are inspired by the microbial complexity of the environment.

Toward Accurate and Quantitative Comparative Metagenomics

Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized.

Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium

Protection against enteric infections, also termed colonization resistance, results from mutualistic interactions of the host and its indigenous microbes. The gut microbiota of humans and mice is highly diverse and it is therefore challenging to assign specific properties to its individual members. Here, we have used a collection of murine bacterial strains and a modular design approach to create a minimal bacterial community that, once established in germ-free mice, provided colonization resistance against the human enteric pathogen Salmonella enterica serovar Typhimurium (S. Tm). Initially, a community of 12 strains, termed Oligo-Mouse-Microbiota (Oligo-MM¹²), representing members of the major bacterial phyla in the murine gut, was selected. This community was stable over consecutive mouse generations and provided colonization resistance against S. Tm infection, albeit not to the degree of a conventional complex microbiota. Comparative (meta)genome analyses identified functions represented in a conventional microbiome but absent from the Oligo-MM¹². By genome-informed design, we created an improved version of the Oligo-MM community harbouring three facultative anaerobic bacteria from the mouse intestinal bacterial collection (miBC) that provided conventional-like colonization resistance. In conclusion, we have established a highly versatile experimental system that showed efficacy in an enteric infection model. Thus, in combination with exhaustive bacterial strain collections and systems-based approaches, genome-guided design can be used to generate insights into microbe-microbe and microbe-host interactions for the investigation of ecological and disease-relevant mechanisms in the intestine.

Exploring and Understanding the Biochemical Diversity of the Human Microbiota

Recent studies have illuminated a remarkable diversity and abundance of microbes living on and within the human body. While we are beginning to appreciate associations of certain bacteria and genes with particular host physiological states, considerable information is lacking about the relevant functional activities of the human microbiota. The human gut microbiome encodes tremendous potential for the biosynthesis and transformation of compounds that are important for both microbial and host physiology. Implementation of chemical knowledge and techniques will be required to improve our understanding of the biochemical diversity of the human microbiota. Such efforts include the characterization of novel microbial enzymes and pathways, isolation of microbial natural products, and development of tools to modulate biochemical functions of the gut microbiota. Ultimately, a molecular understanding of gut microbial activities will be critical for elucidating and manipulating these organisms' contributions to human health and disease.

Expansion of Microbial Forensics

Microbial forensics has been defined as the discipline of applying scientific methods to the analysis of evidence related to bioterrorism, biocrimes, hoaxes, or the accidental release of a biological agent or toxin for attribution purposes. Over the past 15 years, technology, particularly massively parallel sequencing, and bioinformatics advances now allow the characterization of microorganisms for a variety of human forensic applications, such as human identification, body fluid characterization, postmortem interval estimation, and biocrimes involving tracking of infectious agents. Thus, microbial forensics should be more broadly described as the discipline of applying scientific methods to the analysis of microbial evidence in criminal and civil cases for investigative purposes.