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Abstract Cyanobacteria are globally occurring photosynthetic bacteria notable for their contribution to primary production and production of toxins which have detrimental ecosystem impacts. Furthermore, cyanobacteria can form mutualistic symbiotic relationships with a diverse set of eukaryotes, including land plants, aquatic plankton and fungi. Nevertheless, not all cyanobacteria are found in symbiotic associations suggesting symbiotic cyanobacteria have evolved specializations that facilitate host-interactions. Photosynthetic capabilities, nitrogen fixation, and the production of complex biochemicals are key functions provided by host-associated cyanobacterial symbionts. To explore if additional specializations are associated with such lifestyles in cyanobacteria, we have conducted comparative phylogenomics of molecular functions and of biosynthetic gene clusters (BGCs) in 984 cyanobacterial genomes. Cyanobacteria with host-associated and symbiotic lifestyles were concentrated in the family Nostocaceae, where eight monophyletic clades correspond to specific host taxa. In agreement with previous studies, symbionts are likely to provide fixed nitrogen to their eukaryotic partners, through multiple different nitrogen fixation pathways. Additionally, our analyses identified chitin metabolising pathways in cyanobacteria associated with specific host groups, while obligate symbionts had fewer BGCs. The conservation of molecular functions and BGCs between closely related symbiotic and free-living cyanobacteria suggests the potential for additional cyanobacteria to form symbiotic relationships than is currently known.

In lichen research, metagenomes are increasingly being used for evaluating symbiont composition and metabolic potential, but the overall content and limitations of these metagenomes have not been assessed. We reassembled over 400 publicly available metagenomes, generated metagenome-assembled genomes (MAGs), constructed phylogenomic trees, and mapped MAG occurrence and frequency across the data set. Ninety-seven percent of the 1,000 recovered MAGs were bacterial or the fungal symbiont that provides most cellular mass. Our mapping of recovered MAGs provides the most detailed survey to date of bacteria in lichens and shows that 4 family-level lineages from 2 phyla accounted for as many bacterial occurrences in lichens as all other 71 families from 16 phyla combined. Annotation of highly complete bacterial, fungal, and algal MAGs reveals functional profiles that suggest interdigitated vitamin prototrophies and auxotrophies, with most lichen fungi auxotrophic for biotin, most bacteria auxotrophic for thiamine and the few annotated algae with partial or complete pathways for both, suggesting a novel dimension of microbial cross-feeding in lichen symbioses. Contrary to longstanding hypotheses, we found no annotations consistent with nitrogen fixation in bacteria other than known cyanobacterial symbionts. Core lichen symbionts such as algae were recovered as MAGs in only a fraction of the lichen symbioses in which they are known to occur. However, the presence of these and other microbes could be detected at high frequency using small subunit rRNA analysis, including in many lichens in which they are not otherwise recognized to occur. The rate of MAG recovery correlates with sequencing depth, but is almost certainly influenced by biological attributes of organisms that affect the likelihood of DNA extraction, sequencing and successful assembly, including cellular abundance, ploidy and strain co-occurrence. Our results suggest that, though metagenomes are a powerful tool for surveying microbial occurrence, they are of limited use in assessing absence, and their interpretation should be guided by an awareness of the interacting effects of microbial community complexity and sequencing depth.

An extensive metagenomic analysis investigates the global distribution of antimicrobial resistance genes over different biomes, which are primarily influenced by host genera and environment rather than geographic or anthropogenic factors.

The study of viral communities has revealed the enormous diversity and impact these biological entities have on various ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterisation of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterisation of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities, a large metagenomics study, and a collection of publicly available viral genomic sequences from the human gut. The results showed that VIRify could identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an average accuracy of 86.6%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Finally, the use of VIRify led to a large expansion in the number of taxonomically classified human gut viral sequences and the improvement of outdated and shallow taxonomic classifications. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them.

Abstract Background The human intestinal microbiome is a complex community that contributes to host health and disease. In addition to normal microbiota, pathogens like carbapenem-resistant Enterobacteriaceae may be asymptomatically present. When these bacteria are present at very low levels, they are often undetectable in hospital surveillance cultures, known as occult or subclinical colonization. Through the receipt of antibiotics, these subclinical pathogens can increase to sufficiently high levels to become detectable, in a process called outgrowth. However, little is known about the interaction between gut microbiota and Enterobacteriaceae during occult colonization and outgrowth. Results We developed a clinically relevant mouse model for studying occult colonization. Conventional wild-type mice without antibiotic pre-treatment were exposed to Klebsiella pneumoniae but rapidly tested negative for colonization. This occult colonization was found to perturb the microbiome as detected by both 16S rRNA amplicon and shotgun metagenomic sequencing. Outgrowth of occult K. pneumoniae was induced either by a four-antibiotic cocktail or by individual receipt of ampicillin, vancomycin, or azithromycin, which all reduced overall microbial diversity. Notably, vancomycin was shown to trigger K. pneumoniae outgrowth in only a subset of exposed animals (outgrowth-susceptible). To identify factors that underlie outgrowth susceptibility, we analyzed microbiome-encoded gene functions and were able to classify outgrowth-susceptible microbiomes using pathways associated with mRNA stability. Lastly, an evolutionary approach illuminated the importance of xylose metabolism in K. pneumoniae colonization, supporting xylose abundance as a second susceptibility indicator. We showed that our model is generalizable to other pathogens, including carbapenem-resistant Escherichia coli and Enterobacter cloacae. Conclusions Our modeling of occult colonization and outgrowth could help the development of strategies to mitigate the risk of subsequent infection and transmission in medical facilities and the wider community. This study suggests that microbiota mRNA and small-molecule metabolites may be used to predict outgrowth-susceptibility. Video Abstract

Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.

Non-coding RNA function is poorly understood, partly due to the challenge of determining RNA secondary (2D) structure. Here, the authors present a framework for the reproducible prediction and visualization of the 2D structure of a wide array of RNAs, which enables linking RNA sequence to function.

Abstract Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

Abstract Microbial eukaryotes constitute a significant fraction of biodiversity and have recently gained more attention, but the recovery of high-quality metagenomic assembled eukaryotic genomes is limited by the current availability of tools. To help address this, we have developed EukCC, a tool for estimating the quality of eukaryotic genomes based on the automated dynamic selection of single copy marker gene sets. We demonstrate that our method outperforms current genome quality estimators, particularly for estimating contamination, and have applied EukCC to datasets derived from two different environments to enable the identification of novel eukaryote genomes, including one from the human skin.

Abstract Background The metabolic capacity, stress response and evolution of uncultured environmental Tenericutes have remained elusive, since previous studies have been largely focused on pathogenic species. In this study, we expanded analyses on Tenericutes lineages that inhabit various environments using a collection of 840 genomes. Results Several environmental lineages were discovered inhabiting the human gut, ground water, bioreactors and hypersaline lake and spanning the Haloplasmatales and Mycoplasmatales orders. A phylogenomics analysis of Bacilli and Tenericutes genomes revealed that some uncultured Tenericutes are affiliated with novel clades in Bacilli, such as RF39, RFN20 and ML615. Erysipelotrichales and two major gut lineages, RF39 and RFN20, were found to be neighboring clades of Mycoplasmatales. We detected habitat-specific functional patterns between the pathogenic, gut and the environmental Tenericutes, where genes involved in carbohydrate storage, carbon fixation, mutation repair, environmental response and amino acid cleavage are overrepresented in the genomes of environmental lineages, perhaps as a result of environmental adaptation. We hypothesize that the two major gut lineages, namely RF39 and RFN20, are probably acetate and hydrogen producers. Furthermore, deteriorating capacity of bactoprenol synthesis for cell wall peptidoglycan precursors secretion is a potential adaptive strategy employed by these lineages in response to the gut environment. Conclusions This study uncovers the characteristic functions of environmental Tenericutes and their relationships with Bacilli, which sheds new light onto the pathogenicity and evolutionary processes of Mycoplasmatales.

Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40–60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71 M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.

Abstract Background The emergence of antibiotic-resistant pathogens has created an urgent need for novel antimicrobial treatments. Advances in next-generation sequencing have opened new frontiers for discovery programmes for natural products allowing the exploitation of a larger fraction of the microbial community. Polyketide (PK) and non-ribosomal pepetide (NRP) natural products have been reported to be related to compounds with antimicrobial and anticancer activities. We report here a new culture-independent approach to explore bacterial biosynthetic diversity and determine bacterial phyla in the microbial community associated with PK and NRP diversity in selected soils. Results Through amplicon sequencing, we explored the microbial diversity (16S rRNA gene) of 13 soils from Antarctica, Africa, Europe and a Caribbean island and correlated this with the amplicon diversity of the adenylation (A) and ketosynthase (KS) domains within functional genes coding for non-ribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), which are involved in the production of NRP and PK, respectively. Mantel and Procrustes correlation analyses with microbial taxonomic data identified not only the well-studied phyla Actinobacteria and Proteobacteria, but also, interestingly, the less biotechnologically exploited phyla Verrucomicrobia and Bacteroidetes, as potential sources harbouring diverse A and KS domains. Some soils, notably that from Antarctica, provided evidence of endemic diversity, whilst others, such as those from Europe, clustered together. In particular, the majority of the domain reads from Antarctica remained unmatched to known sequences suggesting they could encode enzymes for potentially novel PK and NRP. Conclusions The approach presented here highlights potential sources of metabolic novelty in the environment which will be a useful precursor to metagenomic biosynthetic gene cluster mining for PKs and NRPs which could provide leads for new antimicrobial metabolites.

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.

Metagenomic and meta-barcode DNA sequencing has rapidly become a widely-used technique for investigating a range of questions, particularly related to health and environmental monitoring. There has also been a proliferation of bioinformatic tools for analysing metagenomic and amplicon datasets, which makes selecting adequate tools a significant challenge. A number of benchmark studies have been undertaken; however, these can present conflicting results. In order to address this issue we have applied a robust Z-score ranking procedure and a network meta-analysis method to identify software tools that are consistently accurate for mapping DNA sequences to taxonomic hierarchies. Based upon these results we have identified some tools and computational strategies that produce robust predictions.

Abstract The poultry red mite Dermanyssus gallinae is best known as a threat to the laying-hen industry; adversely affecting production and hen health and welfare throughout the globe, both directly and through its role as a disease vector. Nevertheless, D. gallinae is being increasingly implemented in dermatological complaints in non-avian hosts, suggesting that its significance may extend beyond poultry. The main objective of the current work was to review the potential of D. gallinae as a wider veterinary and medical threat. Results demonstrated that, as an avian mite, D. gallinae is unsurprisingly an occasional pest of pet birds. However, research also supports that these mites will feed from a range of other animals including: cats, dogs, rodents, rabbits, horses and man. We conclude that although reported cases of D. gallinae infesting mammals are relatively rare, when coupled with the reported genetic plasticity of this species and evidence of permanent infestations on non-avian hosts, potential for host-expansion may exist. The impact of, and mechanisms and risk factors for such expansion are discussed, and suggestions for further work made. Given the potential severity of any level of host-expansion in D. gallinae, we conclude that further research should be urgently conducted to confirm the full extent of the threat posed by D. gallinae to (non-avian) veterinary and medical sectors.

Metagenomics, the study of genetic material recovered directly from environmental samples, has the potential to provide insight into the structure and function of heterogeneous microbial communities. There has been an increased use of metagenomics to discover and understand the diverse biosynthetic capacities of marine microbes, thereby allowing them to be exploited for industrial, food, and health care products. This ELIXIR pilot action was motivated by the need to establish dedicated data resources and harmonized metagenomics pipelines for the marine domain, in order to enhance the exploration and exploitation of marine genetic resources. In this paper, we summarize some of the results from the ELIXIR pilot action “Marine metagenomics – towards user centric services”.

Abstract The use of synthetic pesticides and repellents to target pests of veterinary and medical significance is becoming increasingly problematic. One alternative approach employs the bioactive attributes of plant-derived products (PDPs). These are particularly attractive on the grounds of low mammalian toxicity, short environmental persistence and complex chemistries that should limit development of pest resistance against them. Several pesticides and repellents based on PDPs are already available, and in some cases widely utilised, in modern pest management. Many more have a long history of traditional use in poorer areas of the globe where access to synthetic pesticides is often limited. Preliminary studies support that PDPs could be more widely used to target numerous medical and veterinary pests, with modes of action often specific to invertebrates. Though their current and future potential appears significant, development and deployment of PDPs to target veterinary and medical pests is not without issue. Variable efficacy is widely recognised as a restraint to PDPs for pest control. Identifying and developing natural bioactive PDP components in place of chemically less-stable raw or 'whole’ products seems to be the most popular solution to this problem. A limited residual activity, often due to photosensitivity or high volatility, is a further drawback in some cases (though potentially advantageous in others). Nevertheless, encapsulation technologies and other slow-release mechanisms offer strong potential to improve residual activity where needed. The current review provides a summary of existing use and future potential of PDPs against ectoparasites of veterinary and medical significance. Four main types of PDP are considered (pyrethrum, neem, essential oils and plant extracts) for their pesticidal, growth regulating and repellent or deterrent properties. An overview of existing use and research for each is provided, with direction to more extensive reviews given in many sections. Sections to highlight potential issues, modes of action and emerging and future potential are also included.

The poultry red mite (PRM), Dermanyssus gallinae, is a hematophagous ectoparasite considered as the major pest in the egg-laying industry. Its pesticide-based control is only partially successful and requires the development of new control interventions such as vaccines. In this study, we follow a vaccinology approach to identify PRM candidate protective antigens. Based on proteomic data from fed and unfed nymph and adult mites, we selected a novel PRM protein, calumenin (Deg-CALU), which is tested as a vaccine candidate on an on-hen trial. Rhipicephalus microplus Subolesin (Rhm-SUB) was chosen as a positive control. Deg-CALU and Rhm-SUB reduced the mite oviposition by 35 and 44%, respectively. These results support Deg-CALU and Rhm-SUB as candidate protective antigens for the PRM control.

Cellular receptors usually contain a designated sensory domain that recognizes the signal. Per/Arnt/Sim (PAS) domains are ubiquitous sensors in thousands of species ranging from bacteria to humans. Although PAS domains were described as intracellular sensors, recent structural studies revealed PAS-like domains in extracytoplasmic regions in several transmembrane receptors. However, these structurally defined extracellular PAS-like domains do not match sequence-derived PAS domain models, and thus their distribution across the genomic landscape remains largely unknown. Here we show that structurally defined extracellular PAS-like domains belong to the Cache superfamily, which is homologous to, but distinct from the PAS superfamily. Our newly built computational models enabled identification of Cache domains in tens of thousands of signal transduction proteins including those from important pathogens and model organisms. Furthermore, we show that Cache domains comprise the dominant mode of extracellular sensing in prokaryotes.

Visualization systems for tracking proteins are standard experimental tools in most areas of biological research apart from protein purification. Here, we have sought to plug this gap by producing red and yellow visual tags using the heme-binding domain of mosquito cytochrome b5 and the flavin mononucleotide (FMN)-binding domain of human P450 reductase. Tests with colorless glutathione-S-transferase (GST) show them to be simple and effective tools for visually identifying correctly folded protein and tracking protein molecules through protein expression and purification. Furthermore, the characteristic absorbance signatures of the colored tags can be used to quantify protein concentrations directly, which allows purification to be linked to colorimetric detection. This technology, which we call Rainbow Tagging, facilitates expression and downstream processing of recombinant proteins, paving the way for the development of automated high-throughput protein expression systems.

We report the crystal structure solution of the Intracellular Protease Inhibitor (IPI) protein from Bacillus subtilis, which has been reported to be an inhibitor of the intracellular subtilisin Isp1 from the same organism. The structure of IPI is a variant of the all-beta, immunoglobulin (Ig) fold. It is possible that IPI is important for protein-protein interactions, of which inhibition of Isp1 is one. The intracellular nature of ISP is questioned, because an alternative ATG codon in the ipi gene would produce a protein with an N-terminal extension containing a signal peptide. It is possible that alternative initiation exists, producing either an intracellular inhibitor or a secreted form that may be associated with the cell surface. Homologues of the IPI protein from other species are multi-domain proteins, containing signal peptides and domains also associated with the bacterial cell-surface. The cysteine peptidase inhibitors chagasin and amoebiasin also have Ig-like folds, but their topology differs significantly from that of IPI, and they share no recent common ancestor. A model of IPI docked to Isp1 shows similarities to other subtilisin:inhibitor complexes, particularly where the inhibitor interacts with the peptidase active site.

Current models of schizophrenia and bipolar disorder implicate multiple genes, however their biological relationships remain elusive. To test the genetic role of glutamate receptors and their interacting scaffold proteins, the exons of ten glutamatergic 'hub' genes in 1304 individuals were re-sequenced in case and control samples. No significant difference in the overall number of non-synonymous single nucleotide polymorphisms (nsSNPs) was observed between cases and controls. However, cluster analysis of nsSNPs identified two exons encoding the cysteine-rich domain and first transmembrane helix of GRM1 as a risk locus with five mutations highly enriched within these domains. A new splice variant lacking the transmembrane GPCR domain of GRM1 was discovered in the human brain and the GRM1 mutation cluster could perturb the regulation of this variant. The predicted effect on individuals harbouring multiple mutations distributed in their ten hub genes was also examined. Diseased individuals possessed an increased load of deleteriousness from multiple concurrent rare and common coding variants. Together, these data suggest a disease model in which the interplay of compound genetic coding variants, distributed among glutamate receptors and their interacting proteins, contribute to the pathogenesis of schizophrenia and bipolar disorders.

The accelerating growth in the number of protein sequences taxes both the computational and manual resources needed to analyze them. One approach to dealing with this problem is to minimize the number of proteins subjected to such analysis in a way that minimizes loss of information. To this end we have developed a set of Representative Proteomes (RPs), each selected from a Representative Proteome Group (RPG) containing similar proteomes calculated based on co-membership in UniRef50 clusters. A Representative Proteome is the proteome that can best represent all the proteomes in its group in terms of the majority of the sequence space and information. RPs at 75%, 55%, 35% and 15% co-membership threshold (CMT) are provided to allow users to decrease or increase the granularity of the sequence space based on their requirements. We find that a CMT of 55% (RP55) most closely follows standard taxonomic classifications. Further analysis of this set reveals that sequence space is reduced by more than 80% relative to UniProtKB, while retaining both sequence diversity (over 95% of InterPro domains) and annotation information (93% of experimentally characterized proteins). All sets can be browsed and are available for sequence similarity searches and download at http://www.proteininformationresource.org/rps, while the set of 637 RPs determined using a 55% CMT are also available for text searches. Potential applications include sequence similarity searches, protein classification and targeted protein annotation and characterization.

Genome-wide associations have shown a lot of promise in dissecting the genetics of complex traits in humans with single variants, yet a large fraction of the genetic effects is still unaccounted for. Analyzing genetic interactions between variants (epistasis) is one of the potential ways forward. We investigated the abundance and functional impact of a specific type of epistasis, namely the interaction between regulatory and protein-coding variants. Using genotype and gene expression data from the 210 unrelated individuals of the original four HapMap populations, we have explored the combined effects of regulatory and protein-coding single nucleotide polymorphisms (SNPs). We predict that about 18% (1,502 out of 8,233 nsSNPs) of protein-coding variants are differentially expressed among individuals and demonstrate that regulatory variants can modify the functional effect of a coding variant in cis. Furthermore, we show that such interactions in cis can affect the expression of downstream targets of the gene containing the protein-coding SNP. In this way, a cis interaction between regulatory and protein-coding variants has a trans impact on gene expression. Given the abundance of both types of variants in human populations, we propose that joint consideration of regulatory and protein-coding variants may reveal additional genetic effects underlying complex traits and disease and may shed light on causes of differential penetrance of known disease variants.