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Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture. Significance Although metabolic interactions have long been implicated in the assembly of microbial communities, their general prevalence has remained largely unknown. In this study, we systematically survey, by using a metabolic modeling approach, the extent of resource competition and metabolic cross-feeding in over 800 microbial communities from diverse habitats. We show that interspecies metabolic exchanges are widespread in natural communities, and that such exchanges can provide group advantage under nutrient-poor conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence. The presented methodology and mechanistic insights have broad implications for understanding compositional variation in natural communities as well as for facilitating the design of synthetic microbial communities.

Inappropriate antimicrobial usage is a key driver of antimicrobial resistance (AMR). Low- and middle-income countries (LMICs) are disproportionately burdened by AMR and young children are especially vulnerable to infections with AMR-bearing pathogens. The impact of antibiotics on the microbiome, selection, persistence, and horizontal spread of AMR genes is insufficiently characterized and understood in children in LMICs. This systematic review aims to collate and evaluate the available literature describing the impact of antibiotics on the infant gut microbiome and resistome in LMICs. In this systematic review, we searched the online databases MEDLINE (1946 to 28 January 2023), EMBASE (1947 to 28 January 2023), SCOPUS (1945 to 29 January 2023), WHO Global Index Medicus (searched up to 29 January 2023), and SciELO (searched up to 29 January 2023). A total of 4,369 articles were retrieved across the databases. Duplicates were removed resulting in 2,748 unique articles. Screening by title and abstract excluded 2,666 articles, 92 articles were assessed based on the full text, and 10 studies met the eligibility criteria that included human studies conducted in LMICs among children below the age of 2 that reported gut microbiome composition and/or resistome composition (AMR genes) following antibiotic usage. The included studies were all randomized control trials (RCTs) and were assessed for risk of bias using the Cochrane risk-of-bias for randomized studies tool. Overall, antibiotics reduced gut microbiome diversity and increased antibiotic-specific resistance gene abundance in antibiotic treatment groups as compared to the placebo. The most widely tested antibiotic was azithromycin that decreased the diversity of the gut microbiome and significantly increased macrolide resistance as early as 5 days posttreatment. A major limitation of this study was paucity of available studies that cover this subject area. Specifically, the range of antibiotics assessed did not include the most commonly used antibiotics in LMIC populations. In this study, we observed that antibiotics significantly reduce the diversity and alter the composition of the infant gut microbiome in LMICs, while concomitantly selecting for resistance genes whose persistence can last for months following treatment. Considerable heterogeneity in study methodology, timing and duration of sampling, and sequencing methodology in currently available research limit insights into antibiotic impacts on the microbiome and resistome in children in LMICs. More research is urgently needed to fill this gap in order to better understand whether antibiotic-driven reductions in microbiome diversity and selection of AMR genes place LMIC children at risk for adverse health outcomes, including infections with AMR-bearing pathogens.

Genomes are critical units in microbiology, yet ascertaining quality in prokaryotic genome assemblies remains a formidable challenge. We present GUNC (the Genome UNClutterer), a tool that accurately detects and quantifies genome chimerism based on the lineage homogeneity of individual contigs using a genome’s full complement of genes. GUNC complements existing approaches by targeting previously underdetected types of contamination: we conservatively estimate that 5.7% of genomes in GenBank, 5.2% in RefSeq, and 15–30% of pre-filtered “high-quality” metagenome-assembled genomes in recent studies are undetected chimeras. GUNC provides a fast and robust tool to substantially improve prokaryotic genome quality.

The specI software automatically and highly accurately delineates and assigns bacterial species based on a set of universal marker genes that it extracts from sequenced genomes. 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.

Gene content differences in human gut microbes can lead to inter-individual phenotypic variations such as digestive capacity. It is unclear whether gene content variation is caused by differences in microbial species composition or by the presence of different strains of the same species; the extent of gene content variation in the latter is unknown. Unlike pan-genome studies of cultivable strains, the use of metagenomic data can provide an unbiased view of structural variation of gut bacterial strains by measuring them in their natural habitats, the gut of each individual in this case, representing native boundaries between gut bacterial populations. We analyzed publicly available metagenomic data from fecal samples to characterize inter-individual variation in gut bacterial species. A comparison of 11 abundant gut bacterial species showed that the gene content of strains from the same species differed, on average, by 13% between individuals. This number is based on gene deletions only and represents a lower limit, yet the variation is already in a similar range as observed between completely sequenced strains of cultivable species. We show that accessory genes that differ considerably between individuals can encode important functions, such as polysaccharide utilization and capsular polysaccharide synthesis loci. Metagenomics can yield insights into gene content variation of strains in complex communities, which cannot be predicted by phylogenetic marker genes alone. The large degree of inter-individual variability in gene content implies that strain resolution must be considered in order to fully assess the functional potential of an individual's human gut microbiome.

Metagenomic sequencing has greatly improved our ability to profile the composition of environmental and host-associated microbial communities. However, the dependency of most methods on reference genomes, which are currently unavailable for a substantial fraction of microbial species, introduces estimation biases. We present an updated and functionally extended tool based on universal (i.e., reference-independent), phylogenetic marker gene (MG)-based operational taxonomic units (mOTUs) enabling the profiling of >7700 microbial species. As more than 30% of them could not previously be quantified at this taxonomic resolution, relative abundance estimates based on mOTUs are more accurate compared to other methods. As a new feature, we show that mOTUs, which are based on essential housekeeping genes, are demonstrably well-suited for quantification of basal transcriptional activity of community members. Furthermore, single nucleotide variation profiles estimated using mOTUs reflect those from whole genomes, which allows for comparing microbial strain populations (e.g., across different human body sites). Metagenomic analysis based on universal phylogenetic marker gene (MG)-based operational taxonomic units (mOTUs) is a useful strategy, especially for microbial species without reference genomes. Here, the authors develop mOTUs2, an updated and functionally extended profiling tool for microbial abundance, activity and population profiling.

Giant viruses are remarkable for their large genomes, often rivaling those of small bacteria, and for having genes thought exclusive to cellular life. Most isolated to date infect nonmarine protists, leaving their strategies and prevalence in marine environments largely unknown. Using eukaryotic single-cell metagenomics in the Pacific, we discovered a Mimiviridae lineage of giant viruses, which infects choanoflagellates, widespread protistan predators related to metazoans. The ChoanoVirus genomes are the largest yet from pelagic ecosystems, with 442 of 862 predicted proteins lacking known homologs. They are enriched in enzymes formodifying organic compounds, including degradation of chitin, an abundant polysaccharide in oceans, and they encode 3 divergent type-1 rhodopsins (VirR) with distinct evolutionary histories from those that capture sunlight in cellular organisms. One (VirRDTS) is similar to the only other putative rhodopsin from a virus (PgV) with a known host (a marine alga). Unlike the algal virus, ChoanoViruses encode the entire pigment biosynthesis pathway and cleavage enzyme for producing the required chromophore, retinal. We demonstrate that the rhodopsin shared by ChoanoViruses and PgV binds retinal and pumps protons. Moreover, our 1.65-Å resolved VirRDTS crystal structure and mutational analyses exposed differences from previously characterized type-1 rhodopsins, all of which come from cellular organisms. Multiple VirR types are present in metagenomes from across surface oceans, where they are correlated with and nearly as abundant as a canonical marker gene from Mimiviridae . Our findings indicate that light-dependent energy transfer systems are likely common components of giant viruses of photosynthetic and phagotrophic unicellular marine eukaryotes.

Due to the complexity of the protocols and a limited knowledge of the nature of microbial communities, simulating metagenomic sequences plays an important role in testing the performance of existing tools and data analysis methods with metagenomic data. We developed metagenomic read simulators with platform-specific (Sanger, pyrosequencing, Illumina) base-error models, and simulated metagenomes of differing community complexities. We first evaluated the effect of rigorous quality control on Illumina data. Although quality filtering removed a large proportion of the data, it greatly improved the accuracy and contig lengths of resulting assemblies. We then compared the quality-trimmed Illumina assemblies to those from Sanger and pyrosequencing. For the simple community (10 genomes) all sequencing technologies assembled a similar amount and accurately represented the expected functional composition. For the more complex community (100 genomes) Illumina produced the best assemblies and more correctly resembled the expected functional composition. For the most complex community (400 genomes) there was very little assembly of reads from any sequencing technology. However, due to the longer read length the Sanger reads still represented the overall functional composition reasonably well. We further examined the effect of scaffolding of contigs using paired-end Illumina reads. It dramatically increased contig lengths of the simple community and yielded minor improvements to the more complex communities. Although the increase in contig length was accompanied by increased chimericity, it resulted in more complete genes and a better characterization of the functional repertoire. The metagenomic simulators developed for this research are freely available.

Nearly all iron dissolved in the ocean is complexed by strong organic ligands of unknown composition. The effect of ligand composition on microbial iron acquisition is poorly understood, but amendment experiments using model ligands show they can facilitate or impede iron uptake depending on their identity. Here we show that siderophores, organic compounds synthesized by microbes to facilitate iron uptake, are a dynamic component of the marine ligand pool in the eastern tropical Pacific Ocean. Siderophore concentrations in iron-deficient waters averaged 9 pM, up to fivefold higher than in iron-rich coastal and nutrient-depleted oligotrophic waters, and were dominated by amphibactins, amphiphilic siderophores with cell membrane affinity. Phylogenetic analysis of amphibactin biosynthetic genes suggests that the ability to produce amphibactins has transferred horizontally across multiple Gammaproteobacteria, potentially driven by pressures to compete for iron. In coastal and oligotrophic regions of the eastern Pacific Ocean, amphibactins were replaced with lower concentrations (1–2 pM) of hydrophilic ferrioxamine siderophores. Our results suggest that organic ligand composition changes across the surface ocean in response to environmental pressures. Hydrophilic siderophores are predominantly found across regions of the ocean where iron is not expected to be the limiting nutrient for the microbial community at large. However, in regions with intense competition for iron, some microbes optimize iron acquisition by producing siderophores that minimize diffusive losses to the environment. These siderophores affect iron bioavailability and thus may be an important component of the marine iron cycle.

Whereas large-scale efforts have rapidly advanced the understanding and practical impact of human genomic variation, the practical impact of variation is largely unexplored in the human microbiome. We therefore developed a framework for metagenomic variation analysis and applied it to 252 faecal metagenomes of 207 individuals from Europe and North America. Using 7.4 billion reads aligned to 101 reference species, we detected 10.3 million single nucleotide polymorphisms (SNPs), 107,991 short insertions/deletions, and 1,051 structural variants. The average ratio of non-synonymous to synonymous polymorphism rates of 0.11 was more variable between gut microbial species than across human hosts. Subjects sampled at varying time intervals exhibited individuality and temporal stability of SNP variation patterns, despite considerable composition changes of their gut microbiota. This indicates that individual-specific strains are not easily replaced and that an individual might have a unique metagenomic genotype, which may be exploitable for personalized diet or drug intake. A framework for metagenomic variation analysis to explore variation in the human microbiome is developed; the study describes SNPs, short indels and structural variants in 252 faecal metagenomes of 207 individuals from Europe and North America. Gene variation in human gut microbes A collaboration between members of the European MetaHIT and American NIH Human Microbiome projects has led to the development of a framework for metagenomic variation analysis, which is used to analyse single nucleotide polymorphisms, short indels and structural variants in 252 faecal metagenomes of 207 individuals from Europe and North America. Variation patterns suggest that individuals might have unique metagenomic genotypes that could provide data relevant to personalized dietary or drug choices.