Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome.

Ocean microbial communities strongly influence the biogeochemistry, food webs, and climate of our planet. Despite recent advances in understanding their taxonomic and genomic compositions, little is known about how their transcriptomes vary globally. Here, we present a dataset of 187 metatranscriptomes and 370 metagenomes from 126 globally distributed sampling stations and establish a resource of 47 million genes to study community-level transcriptomes across depth layers from pole-to-pole. We examine gene expression changes and community turnover as the underlying mechanisms shaping community transcriptomes along these axes of environmental variation and show how their individual contributions differ for multiple biogeochemically relevant processes. Furthermore, we find the relative contribution of gene expression changes to be significantly lower in polar than in non-polar waters and hypothesize that in polar regions, alterations in community activity in response to ocean warming will be driven more strongly by changes in organismal composition than by gene regulatory mechanisms. VIDEO ABSTRACT.

Microbiota-dependent activation of the myeloid calcineurin-NFAT pathway inhibits B7H3- and B7H4-dependent anti-tumor immunity in colorectal cancer.

Bacterial sensing by intestinal tumor cells contributes to tumor growth through cell-intrinsic activation of the calcineurin-NFAT axis, but the role of this pathway in other intestinal cells remains unclear. Here, we found that myeloid-specific deletion of calcineurin in mice activated protective CD8+ T cell responses and inhibited colorectal cancer (CRC) growth. Microbial sensing by myeloid cells promoted calcineurin- and NFAT-dependent interleukin 6 (IL-6) release, expression of the co-inhibitory molecules B7H3 and B7H4 by tumor cells, and inhibition of CD8+ T cell-dependent anti-tumor immunity. Accordingly, targeting members of this pathway activated protective CD8+ T cell responses and inhibited primary and metastatic CRC growth. B7H3 and B7H4 were expressed by the majority of human primary CRCs and metastases, which was associated with low numbers of tumor-infiltrating CD8+ T cells and poor survival. Therefore, a microbiota-, calcineurin-, and B7H3/B7H4-dependent pathway controls anti-tumor immunity, revealing additional targets for immune checkpoint inhibition in microsatellite-stable CRC.

Bacterial retrons encode phage-defending tripartite toxin-antitoxin systems.

Retrons are prokaryotic genetic retroelements encoding a reverse transcriptase that produces multi-copy single-stranded DNA1 (msDNA). Despite decades of research on the biosynthesis of msDNA2, the function and physiological roles of retrons have remained unknown. Here we show that Retron-Sen2 of Salmonella enterica serovar Typhimurium encodes an accessory toxin protein, STM14_4640, which we renamed as RcaT. RcaT is neutralized by the reverse transcriptase-msDNA antitoxin complex, and becomes active upon perturbation of msDNA biosynthesis. The reverse transcriptase is required for binding to RcaT, and the msDNA is required for the antitoxin activity. The highly prevalent RcaT-containing retron family constitutes a new type of tripartite DNA-containing toxin-antitoxin system. To understand the physiological roles of such toxin-antitoxin systems, we developed toxin activation-inhibition conjugation (TAC-TIC), a high-throughput reverse genetics approach that identifies the molecular triggers and blockers of toxin-antitoxin systems. By applying TAC-TIC to Retron-Sen2, we identified multiple trigger and blocker proteins of phage origin. We demonstrate that phage-related triggers directly modify the msDNA, thereby activating RcaT and inhibiting bacterial growth. By contrast, prophage proteins circumvent retrons by directly blocking RcaT. Consistently, retron toxin-antitoxin systems act as abortive infection anti-phage defence systems, in line with recent reports3,4. Thus, RcaT retrons are tripartite DNA-regulated toxin-antitoxin systems, which use the reverse transcriptase-msDNA complex both as an antitoxin and as a sensor of phage protein activities.

Biosynthetic potential of the global ocean microbiome.

Natural microbial communities are phylogenetically and metabolically diverse. In addition to underexplored organismal groups1, this diversity encompasses a rich discovery potential for ecologically and biotechnologically relevant enzymes and biochemical compounds2,3. However, studying this diversity to identify genomic pathways for the synthesis of such compounds4 and assigning them to their respective hosts remains challenging. The biosynthetic potential of microorganisms in the open ocean remains largely uncharted owing to limitations in the analysis of genome-resolved data at the global scale. Here we investigated the diversity and novelty of biosynthetic gene clusters in the ocean by integrating around 10,000 microbial genomes from cultivated and single cells with more than 25,000 newly reconstructed draft genomes from more than 1,000 seawater samples. These efforts revealed approximately 40,000 putative mostly new biosynthetic gene clusters, several of which were found in previously unsuspected phylogenetic groups. Among these groups, we identified a lineage rich in biosynthetic gene clusters ('Candidatus Eudoremicrobiaceae') that belongs to an uncultivated bacterial phylum and includes some of the most biosynthetically diverse microorganisms in this environment. From these, we characterized the phospeptin and pythonamide pathways, revealing cases of unusual bioactive compound structure and enzymology, respectively. Together, this research demonstrates how microbiomics-driven strategies can enable the investigation of previously undescribed enzymes and natural products in underexplored microbial groups and environments.

Unravelling the collateral damage of antibiotics on gut bacteria.

Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease1. Despite this well-known collateral damage, the activity spectrum of different antibiotic classes on gut bacteria remains poorly characterized. Here we characterize further 144 antibiotics from a previous screen of more than 1,000 drugs on 38 representative human gut microbiome species2. Antibiotic classes exhibited distinct inhibition spectra, including generation dependence for quinolones and phylogeny independence for ß-lactams. Macrolides and tetracyclines, both prototypic bacteriostatic protein synthesis inhibitors, inhibited nearly all commensals tested but also killed several species. Killed bacteria were more readily eliminated from in vitro communities than those inhibited. This species-specific killing activity challenges the long-standing distinction between bactericidal and bacteriostatic antibiotic classes and provides a possible explanation for the strong effect of macrolides on animal3-5 and human6,7 gut microbiomes. To mitigate this collateral damage of macrolides and tetracyclines, we screened for drugs that specifically antagonized the antibiotic activity against abundant Bacteroides species but not against relevant pathogens. Such antidotes selectively protected Bacteroides species from erythromycin treatment in human-stool-derived communities and gnotobiotic mice. These findings illluminate the activity spectra of antibiotics in commensal bacteria and suggest strategies to circumvent their adverse effects on the gut microbiota.

Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO.

Factor analysis is a widely used method for dimensionality reduction in genome biology, with applications from personalized health to single-cell biology. Existing factor analysis models assume independence of the observed samples, an assumption that fails in spatio-temporal profiling studies. Here we present MEFISTO, a flexible and versatile toolbox for modeling high-dimensional data when spatial or temporal dependencies between the samples are known. MEFISTO maintains the established benefits of factor analysis for multimodal data, but enables the performance of spatio-temporally informed dimensionality reduction, interpolation, and separation of smooth from non-smooth patterns of variation. Moreover, MEFISTO can integrate multiple related datasets by simultaneously identifying and aligning the underlying patterns of variation in a data-driven manner. To illustrate MEFISTO, we apply the model to different datasets with spatial or temporal resolution, including an evolutionary atlas of organ development, a longitudinal microbiome study, a single-cell multi-omics atlas of mouse gastrulation and spatially resolved transcriptomics.

proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes.

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.

PyHMMER: a Python library binding to HMMER for efficient sequence analysis.

SUMMARY: PyHMMER provides Python integration of the popular profile Hidden Markov Model software HMMER via Cython bindings. This allows the annotation of protein sequences with profile HMMs and building new ones directly with Python. PyHMMER increases flexibility of use, allowing creating queries directly from Python code, launching searches, and obtaining results without I/O, or accessing previously unavailable statistics like uncorrected P-values. A new parallelization model greatly improves performance when running multithreaded searches, while producing the exact same results as HMMER. AVAILABILITY AND IMPLEMENTATION: PyHMMER supports all modern Python versions (Python 3.6+) and similar platforms as HMMER (x86 or PowerPC UNIX systems). Pre-compiled packages are released via PyPI (https://pypi.org/project/pyhmmer/) and Bioconda (https://anaconda.org/bioconda/pyhmmer). The PyHMMER source code is available under the terms of the open-source MIT licence and hosted on GitHub (https://github.com/althonos/pyhmmer); its documentation is available on ReadTheDocs (https://pyhmmer.readthedocs.io).

Extensive impact of non-antibiotic drugs on human gut bacteria.

A few commonly used non-antibiotic drugs have recently been associated with changes in gut microbiome composition, but the extent of this phenomenon is unknown. Here, we screened more than 1,000 marketed drugs against 40 representative gut bacterial strains, and found that 24% of the drugs with human targets, including members of all therapeutic classes, inhibited the growth of at least one strain in vitro. Particular classes, such as the chemically diverse antipsychotics, were overrepresented in this group. The effects of human-targeted drugs on gut bacteria are reflected on their antibiotic-like side effects in humans and are concordant with existing human cohort studies. Susceptibility to antibiotics and human-targeted drugs correlates across bacterial species, suggesting common resistance mechanisms, which we verified for some drugs. The potential risk of non-antibiotics promoting antibiotic resistance warrants further exploration. Our results provide a resource for future research on drug-microbiome interactions, opening new paths for side effect control and drug repurposing, and broadening our view of antibiotic resistance.

A faecal microbiota signature with high specificity for pancreatic cancer.

BACKGROUND: Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression. OBJECTIVE: To explore the faecal and salivary microbiota as potential diagnostic biomarkers. METHODS: We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase. RESULTS: Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation. CONCLUSION: Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Depression and fatigue in active IBD from a microbiome perspective-a Bayesian approach to faecal metagenomics.

BACKGROUND: Extraintestinal symptoms are common in inflammatory bowel diseases (IBD) and include depression and fatigue. These are highly prevalent especially in active disease, potentially due to inflammation-mediated changes in the microbiota-gut-brain axis. The aim of this study was to investigate the associations between structural and functional microbiota characteristics and severity of fatigue and depressive symptoms in patients with active IBD. METHODS: We included clinical data of 62 prospectively enrolled patients with IBD in an active disease state. Patients supplied stool samples and completed the questionnaires regarding depression and fatigue symptoms. Based on taxonomic and functional metagenomic profiles of faecal gut microbiota, we used Bayesian statistics to investigate the associative networks and triangle motifs between bacterial genera, functional modules and symptom severity of self-reported fatigue and depression. RESULTS: Associations with moderate to strong evidence were found for 3 genera (Odoribacter, Anaerotruncus and Alistipes) and 3 functional modules (pectin, glycosaminoglycan and central carbohydrate metabolism) with regard to depression and for 4 genera (Intestinimonas, Anaerotruncus, Eubacterium and Clostridiales g.i.s) and 2 functional modules implicating amino acid and central carbohydrate metabolism with regard to fatigue. CONCLUSIONS: This study provides the first evidence of association triplets between microbiota composition, function and extraintestinal symptoms in active IBD. Depression and fatigue were associated with lower abundances of short-chain fatty acid producers and distinct pathways implicating glycan, carbohydrate and amino acid metabolism. Our results suggest that microbiota-directed therapeutic approaches may reduce fatigue and depression in IBD and should be investigated in future research.

proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes.

Microbiology depends on the availability of annotated microbial genomes for many applications. Comparative genomics approaches have been a major advance, but consistent and accurate annotations of genomes can be hard to obtain. In addition, newer concepts such as the pan-genome concept are still being implemented to help answer biological questions. Hence, we present proGenomes2, which provides 87 920 high-quality genomes in a user-friendly and interactive manner. Genome sequences and annotations can be retrieved individually or by taxonomic clade. Every genome in the database has been assigned to a species cluster and most genomes could be accurately assigned to one or multiple habitats. In addition, general functional annotations and specific annotations of antibiotic resistance genes and single nucleotide variants are provided. In short, proGenomes2 provides threefold more genomes, enhanced habitat annotations, updated taxonomic and functional annotation and improved linkage to the NCBI BioSample database. The database is available at http://progenomes.embl.de/.

The gut microbiome in solid organ transplantation.

Despite ground-breaking advances in allogeneic transplantation, allograft rejection and immunosuppressant-specific complications remain a major challenge in transplant medicine. Growing evidence suggests the human gut microbiome as a potential contributor to transplant outcome and patient health. After breakthrough findings in haematopoietic stem cell transplantation (HSCT), the relevance of the microbiome in solid organ transplantation (SOT) is becoming increasingly clear. Here, we review the role of the microbiome in SOT focusing on its significance for transplant-associated complications such as allograft rejection and infections, and highlight its potential impact on immunosuppressive treatment. Moreover, we shed light on the emerging role of the microbiome as a diagnostic biomarker and therapeutic target and discuss current microbial intervention strategies. In addition, this review includes some practical considerations in designing clinical microbiome trials and offers some advice for the interpretation of the resulting data. Further investigation of the gut microbiome harbours countless clinical application possibilities and holds great promise of having a lasting impact on transplant medicine.

Subspecies in the global human gut microbiome.

Population genomics of prokaryotes has been studied in depth in only a small number of primarily pathogenic bacteria, as genome sequences of isolates of diverse origin are lacking for most species. Here, we conducted a large-scale survey of population structure in prevalent human gut microbial species, sampled from their natural environment, with a culture-independent metagenomic approach. We examined the variation landscape of 71 species in 2,144 human fecal metagenomes and found that in 44 of these, accounting for 72% of the total assigned microbial abundance, single-nucleotide variation clearly indicates the existence of sub-populations (here termed subspecies). A single subspecies (per species) usually dominates within each host, as expected from ecological theory. At the global scale, geographic distributions of subspecies differ between phyla, with Firmicutes subspecies being significantly more geographically restricted. To investigate the functional significance of the delineated subspecies, we identified genes that consistently distinguish them in a manner that is independent of reference genomes. We further associated these subspecies-specific genes with properties of the microbial community and the host. For example, two of the three Eubacterium rectale subspecies consistently harbor an accessory pro-inflammatory flagellum operon that is associated with lower gut community diversity, higher host BMI, and higher blood fasting insulin levels. Using an additional 676 human oral samples, we further demonstrate the existence of niche specialized subspecies in the different parts of the oral cavity. Taken together, we provide evidence for subspecies in the majority of abundant gut prokaryotes, leading to a better functional and ecological understanding of the human gut microbiome in conjunction with its host.

CART-a chemical annotation retrieval toolkit.

MOTIVATION: Data on bioactivities of drug-like chemicals are rapidly accumulating in public repositories, creating new opportunities for research in computational systems pharmacology. However, integrative analysis of these data sets is difficult due to prevailing ambiguity between chemical names and identifiers and a lack of cross-references between databases. RESULTS: To address this challenge, we have developed CART, a Chemical Annotation Retrieval Toolkit. As a key functionality, it matches an input list of chemical names into a comprehensive reference space to assign unambiguous chemical identifiers. In this unified space, bioactivity annotations can be easily retrieved from databases covering a wide variety of chemical effects on biological systems. Subsequently, CART can determine annotations enriched in the input set of chemicals and display these in tabular format and interactive network visualizations, thereby facilitating integrative analysis of chemical bioactivity data. AVAILABILITY AND IMPLEMENTATION: CART is available as a Galaxy web service (cart.embl.de). Source code and an easy-to-install command line tool can also be obtained from the web site. CONTACT: bork@embl.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOCAT2: a metagenomic assembly, annotation and profiling framework.

UNLABELLED: MOCAT2 is a software pipeline for metagenomic sequence assembly and gene prediction with novel features for taxonomic and functional abundance profiling. The automated generation and efficient annotation of non-redundant reference catalogs by propagating pre-computed assignments from 18 databases covering various functional categories allows for fast and comprehensive functional characterization of metagenomes. AVAILABILITY AND IMPLEMENTATION: MOCAT2 is implemented in Perl 5 and Python 2.7, designed for 64-bit UNIX systems and offers support for high-performance computer usage via LSF, PBS or SGE queuing systems; source code is freely available under the GPL3 license at http://mocat.embl.de CONTACT: : bork@embl.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Accurate and universal delineation of prokaryotic species.

The exponentially increasing number of sequenced genomes necessitates fast, accurate, universally applicable and automated approaches for the delineation of prokaryotic species. We developed specI (species identification tool; http://www.bork.embl.de/software/specI/), a method to group organisms into species clusters based on 40 universal, single-copy phylogenetic marker genes. Applied to 3,496 prokaryotic genomes, specI identified 1,753 species clusters. Of 314 discrepancies with a widely used taxonomic classification, >62% were resolved by literature support.

Metagenomic species profiling using universal phylogenetic marker genes.

To quantify known and unknown microorganisms at species-level resolution using shotgun sequencing data, we developed a method that establishes metagenomic operational taxonomic units (mOTUs) based on single-copy phylogenetic marker genes. Applied to 252 human fecal samples, the method revealed that on average 43% of the species abundance and 58% of the richness cannot be captured by current reference genome-based methods. An implementation of the method is available at http://www.bork.embl.de/software/mOTU/.

Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis.

We present Oqtans, an open-source workbench for quantitative transcriptome analysis, that is integrated in Galaxy. Its distinguishing features include customizable computational workflows and a modular pipeline architecture that facilitates comparative assessment of tool and data quality. Oqtans integrates an assortment of machine learning-powered tools into Galaxy, which show superior or equal performance to state-of-the-art tools. Implemented tools comprise a complete transcriptome analysis workflow: short-read alignment, transcript identification/quantification and differential expression analysis. Oqtans and Galaxy facilitate persistent storage, data exchange and documentation of intermediate results and analysis workflows. We illustrate how Oqtans aids the interpretation of data from different experiments in easy to understand use cases. Users can easily create their own workflows and extend Oqtans by integrating specific tools. Oqtans is available as (i) a cloud machine image with a demo instance at cloud.oqtans.org, (ii) a public Galaxy instance at galaxy.cbio.mskcc.org, (iii) a git repository containing all installed software (oqtans.org/git); most of which is also available from (iv) the Galaxy Toolshed and (v) a share string to use along with Galaxy CloudMan.

Potential of fecal microbiota for early-stage detection of colorectal cancer.

Several bacterial species have been implicated in the development of colorectal carcinoma (CRC), but CRC-associated changes of fecal microbiota and their potential for cancer screening remain to be explored. Here, we used metagenomic sequencing of fecal samples to identify taxonomic markers that distinguished CRC patients from tumor-free controls in a study population of 156 participants. Accuracy of metagenomic CRC detection was similar to the standard fecal occult blood test (FOBT) and when both approaches were combined, sensitivity improved > 45% relative to the FOBT, while maintaining its specificity. Accuracy of metagenomic CRC detection did not differ significantly between early- and late-stage cancer and could be validated in independent patient and control populations (N = 335) from different countries. CRC-associated changes in the fecal microbiome at least partially reflected microbial community composition at the tumor itself, indicating that observed gene pool differences may reveal tumor-related host-microbe interactions. Indeed, we deduced a metabolic shift from fiber degradation in controls to utilization of host carbohydrates and amino acids in CRC patients, accompanied by an increase of lipopolysaccharide metabolism.