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Microbiomes are ubiquitous and are found in the ocean, the soil, and in/on other living organisms. Changes in the microbiome can impact the health of the environmental niche in which they reside. In order to learn more about these communities, different approaches based on data from multiple omics have been pursued. Metagenomics produces a taxonomical profile of the sample, metatranscriptomics helps us to obtain a functional profile, and metabolomics completes the picture by determining which byproducts are being released into the environment. Although each approach provides valuable information separately, we show that, when combined, they paint a more comprehensive picture. We conclude with a review of network-based approaches as applied to integrative studies, which we believe holds the key to in-depth understanding of microbiomes.

Viruses are an understudied component of plant microbiomes. Identifying viruses that are shared between individual plants, or members of the “core virome”, could reveal stable viral populations with the potential to modulate the composition and function of the microbiome. Here, we examined the virome associated with Sphagnum mosses, a keystone species that has direct influence over the fate of peatland carbon stores. We analyzed bulk metagenomes and metatranscriptomes generated from Sphagnum field samples collected over a ten-month period to identify virus-like sequences shared among plants. Individual Sphagnum samples harbored distinct DNA and RNA viromes where only a small percentage (< 1%) of the total number of identified viral contigs were shared among all samples. Based on taxonomic classification, the shared viral contigs represent bacterial viruses, or phage (Caudoviricetes), as well as viruses of eukaryotes, namely nucleocytoplasmic large DNA viruses (Nucleocytoviricota) and RNA viruses (Riboviria). We linked the shared phage-like contigs to viral regions within sequenced genomes of bacterial taxa that are members of the Sphagnum core microbiome, suggesting that these contigs represent temperate phage or degraded prophage. The putative nucleocytoplasmic large DNA viruses and RNA viruses were phylogenetically diverse and showed sequence similarity to viruses associated with a broad range of hosts and environmental sources. The identification of shared viral contigs suggested that, despite the compositional heterogeneity between samples, Sphagnum mosses may harbor a core virome. Future work validating the presence of the core virome is warranted as it may aid in understanding how persistent viruses impact microbiome ecology and symbiont evolution within this climatically relevant keystone species.

Bacterial secondary metabolites are a major source of antibiotics and other bioactive compounds. In microbial communities, these molecules can mediate interspecies interactions and responses to environmental change. Despite the importance of secondary metabolites in human health and microbial ecology, little is known about their roles and regulation in the context of multispecies communities. In a simplified model of the rhizosphere composed of Bacillus cereus, Flavobacterium johnsoniae, and Pseudomonas koreensis, we show that the dynamics of secondary metabolism depend on community species composition and interspecies interactions. Comparative metatranscriptomics and metametabolomics reveal that the abundance of transcripts of biosynthetic gene clusters (BGCs) and metabolomic molecular features differ between monocultures or dual cultures and a tripartite community. In both two- and three-member cocultures, P. koreensis modified expression of BGCs for zwittermicin, petrobactin, and other secondary metabolites in B. cereus and F. johnsoniae, whereas the BGC transcriptional response to the community in P. koreensis itself was minimal. Pairwise and tripartite cocultures with P. koreensis displayed unique molecular features that appear to be derivatives of lokisin, suggesting metabolic handoffs between species. Deleting the BGC for koreenceine, another P. koreensis metabolite, altered transcript and metabolite profiles across the community, including substantial up-regulation of the petrobactin and bacillibactin BGCs in B. cereus, suggesting that koreenceine represses siderophore production. Results from this model community show that bacterial BGC expression and chemical output depend on the identity and biosynthetic capacity of coculture partners, suggesting community composition and microbiome interactions may shape the regulation of secondary metabolism in nature.

The 24-h cycle of light and darkness governs daily rhythms of complex behaviors across all domains of life. Intracellular photoreceptors sense specific wavelengths of light that can reset the internal circadian clock and/or elicit distinct phenotypic responses. In the surface ocean, microbial communities additionally modulate nonrhythmic changes in light quality and quantity as they are mixed to different depths. Here, we show that eukaryotic plankton in the North Pacific Subtropical Gyre transcribe genes encoding light-sensitive proteins that may serve as light-activated transcription factors, elicit light-driven electrical/chemical cascades, or initiate secondary messenger-signaling cascades. Overall, the protistan community relies on blue light-sensitive photoreceptors of the cryptochrome/photolyase family, and proteins containing the Light-Oxygen-Voltage (LOV) domain. The greatest diversification occurred within Haptophyta and photosynthetic stramenopiles where the LOV domain was combined with different DNA-binding domains and secondary signal-transduction motifs. Flagellated protists utilize green-light sensory rhodopsins and blue-light helmchromes, potentially underlying phototactic/photophobic and other behaviors toward specific wavelengths of light. Photoreceptors such as phytochromes appear to play minor roles in the North Pacific Subtropical Gyre. Transcript abundance of environmental light-sensitive protein-encoding genes that display diel patterns are found to primarily peak at dawn. The exceptions are the LOV-domain transcription factors with peaks in transcript abundances at different times and putative phototaxis photoreceptors transcribed throughout the day. Together, these data illustrate the diversity of light-sensitive proteins that may allow disparate groups of protists to respond to light and potentially synchronize patterns of growth, division, and mortality within the dynamic ocean environment.

As global temperatures rise, large amounts of carbon sequestered in permafrost are becoming available for microbial degradation. Accurate prediction of carbon gas emissions from thawing permafrost is limited by our understanding of these microbial communities. Here we use metagenomic sequencing of 214 samples from a permafrost thaw gradient to recover 1,529 metagenome-assembled genomes, including many from phyla with poor genomic representation. These genomes reflect the diversity of this complex ecosystem, with genus-level representatives for more than sixty per cent of the community. Meta-omic analysis revealed key populations involved in the degradation of organic matter, including bacteria whose genomes encode a previously undescribed fungal pathway for xylose degradation. Microbial and geochemical data highlight lineages that correlate with the production of greenhouse gases and indicate novel syntrophic relationships. Our findings link changing biogeochemistry to specific microbial lineages involved in carbon processing, and provide key information for predicting the effects of climate change on permafrost systems. Analysis of more than 1,500 microbial genomes sheds light on the processing of carbon released as permafrost thaws.

The Human Microbiome Project (HMP) aided in understanding the role of microbial communities and the influence of collective genetic material (the 'microbiome') in human health and disease. With the evolution of new sequencing technologies, researchers can now investigate the microbiome and map its influence on human health. Advances in bioinformatics methods for next-generation sequencing (NGS) data analysis have helped researchers to gain an in-depth knowledge about the taxonomic and genetic composition of microbial communities. Metagenomic-based methods have been the most commonly used approaches for microbiome analysis; however, it primarily extracts information about taxonomic composition and genetic potential of the microbiome under study, lacking quantification of the gene products (RNA and proteins). Conversely, metatranscriptomics, the study of a microbial community's RNA expression, can reveal the dynamic gene expression of individual microbial populations and the community as a whole, ultimately providing information about the active pathways in the microbiome.  In order to address the analysis of NGS data, the ASaiM analysis framework was previously developed and made available via the Galaxy platform. Although developed for both metagenomics and metatranscriptomics, the original publication demonstrated the use of ASaiM only for metagenomics, while thorough testing for metatranscriptomics data was lacking.  In the current study, we have focused on validating and optimizing the tools within ASaiM for metatranscriptomics data. As a result, we deliver a robust workflow that will enable researchers to understand dynamic functional response of the microbiome in a wide variety of metatranscriptomics studies. This improved and optimized ASaiM-metatranscriptomics (ASaiM-MT) workflow is publicly available via the ASaiM framework, documented and supported with training material so that users can interrogate and characterize metatranscriptomic data, as part of larger meta-omic studies of microbiomes.

Lignocellulosic residues are low-cost abundant feedstocks that can be used for industrial applications. However, their recalcitrance currently makes lignocellulose use limited. In natural environments, microbial communities can completely deconstruct lignocellulose by synergistic action of a set of enzymes and proteins. Microbial degradation of lignin by fungi, important lignin degraders in nature, has been intensively studied. More recently, bacteria have also been described as able to break down lignin, and to have a central role in recycling this plant polymer. Nevertheless, bacterial deconstruction of lignin has not been fully elucidated yet. Direct analysis of environmental samples using metagenomics, metatranscriptomics, and metaproteomics approaches is a powerful strategy to describe/discover enzymes, metabolic pathways, and microorganisms involved in lignin breakdown. Indeed, the use of these complementary techniques leads to a better understanding of the composition, function, and dynamics of microbial communities involved in lignin deconstruction. We focus on omics approaches and their contribution to the discovery of new enzymes and reactions that impact the development of lignin-based bioprocesses.

Background As the global population continues to grow, competition for resources between humans and livestock has been intensifying. Increasing milk protein production and improving feed efficiency are becoming increasingly important to meet the demand for high-quality dairy protein. In a previous study, we found that milk protein yield in dairy cows was associated with the rumen microbiome. The objective of this study was to elucidate the potential microbial features that underpins feed efficiency in dairy cows using metagenomics, metatranscriptomics, and metabolomics. Results Comparison of metagenomic and metatranscriptomic data revealed that the latter was a better approach to uncover the associations between rumen microbial functions and host performance. Co-occurrence network analysis of the rumen microbiome revealed differential microbial interaction patterns between the animals with different feed efficiency, with high-efficiency animals having more and stronger associations than low-efficiency animals. In the rumen of high-efficiency animals, Selenomonas and members of the Succinivibrionaceae family positively interacted with each other, functioning as keystone members due to their essential ecological functions and active carbohydrate metabolic functions. At the metabolic level, analysis using random forest machine learning suggested that six ruminal metabolites (all derived from carbohydrates) could be used as metabolic markers that can potentially differentiate efficient and inefficient microbiomes, with an accuracy of prediction of 95.06%. Conclusions The results of the current study provided new insights into the new ruminal microbial features associated with feed efficiency in dairy cows, which may improve the ability to select animals for better performance in the dairy industry. The fundamental knowledge will also inform future interventions to improve feed efficiency in dairy cows. 2fNfKsiaKwf1Ab-9aEYLYC Video Abstract.

Nearly all organisms are hosts to multiple viruses that collectively appear to be the most abundant biological entities in the biosphere. With recent advances in metagenomics and metatranscriptomics, the known diversity of viruses substantially expanded. Comparative analysis of these viruses using advanced computational methods culminated in the reconstruction of the evolution of major groups of viruses and enabled the construction of a virus megataxonomy, which has been formally adopted by the International Committee on Taxonomy of Viruses. This comprehensive taxonomy consists of six virus realms, which are aspired to be monophyletic and assembled based on the conservation of hallmark proteins involved in capsid structure formation or genome replication. The viruses in different major taxa substantially differ in host range and accordingly in ecological niches. In this review article, we outline the latest developments in virus megataxonomy and the recent discoveries that will likely lead to reassessment of some major taxa, in particular, split of three of the current six realms into two or more independent realms. We then discuss the correspondence between virus taxonomy and the distribution of viruses among hosts and ecological niches, as well as the abundance of viruses versus cells in different habitats. The distribution of viruses across environments appears to be primarily determined by the host ranges, i.e. the virome is shaped by the composition of the biome in a given habitat, which itself is affected by abiotic factors.