Metatranscriptomic Datasets Research Articles

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

BackgroundOceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean’s interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth.ResultsWe leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins.ConclusionsCombining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes.AbL6i64VtV696aBPsu8M5wVideo abstract

DiTing: A Pipeline to Infer and Compare Biogeochemical Pathways From Metagenomic and Metatranscriptomic Data.

Metagenomics and metatranscriptomics are powerful methods to uncover key micro-organisms and processes driving biogeochemical cycling in natural ecosystems. Databases dedicated to depicting biogeochemical pathways (for example, metabolism of dimethylsulfoniopropionate (DMSP), which is an abundant organosulfur compound) from metagenomic/metatranscriptomic data are rarely seen. Additionally, a recognized normalization model to estimate the relative abundance and environmental importance of pathways from metagenomic and metatranscriptomic data has not been organized to date. These limitations impact the ability to accurately relate key microbial-driven biogeochemical processes to differences in environmental conditions. Thus, an easy-to-use, specialized tool that infers and visually compares the potential for biogeochemical processes, including DMSP cycling, is urgently required. To solve these issues, we developed DiTing, a tool wrapper to infer and compare biogeochemical pathways among a set of given metagenomic or metatranscriptomic reads in one step, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and a manually created DMSP cycling gene database. Accurate and specific formulae for over 100 pathways were developed to calculate their relative abundance. Output reports detail the relative abundance of biogeochemical pathways in both text and graphical format. DiTing was applied to simulated metagenomic data and resulted in consistent genetic features of simulated benchmark genomic data. Subsequently, when applied to natural metagenomic and metatranscriptomic data from hydrothermal vents and the Tara Ocean project, the functional profiles predicted by DiTing were correlated with environmental condition changes. DiTing can now be confidently applied to wider metagenomic and metatranscriptomic datasets, and it is available at https://github.com/xuechunxu/DiTing.

Pipeline for Analyzing Activity of Metabolic Pathways in Planktonic Communities Using Metatranscriptomic Data.

In this article, we present our novel pipeline for analysis of metabolic activity using a microbial community's metatranscriptome sequence data set for validation. Our method is based on expectation-maximization (EM) algorithm and provides enzyme expression and pathway activity levels. Further expanding our analysis, we consider individual enzymatic activity and compute enzyme participation coefficients to approximate the metabolic pathway activity more accurately. We apply our EM pathways pipeline to a metatranscriptomic data set of a plankton community from surface waters of the Northern Gulf of Mexico. The data set consists of RNA-seq data and respective environmental parameters, which were sampled at two depths, six times a day over multiple 24-hour cycles. Furthermore, we discuss microbial dependence on day-night cycle within our findings based on a three-way correlation of the enzyme expression during antipodal times-midnight and noon. We show that the enzyme participation levels strongly affect the metabolic activity estimates: that is, marginal and multiple linear regression of enzymatic and metabolic pathway activity correlated significantly with the recorded environmental parameters. Our analysis statistically validates that EM-based methods produce meaningful results, as our method confirms statistically significant dependence of metabolic pathway activity on the environmental parameters, such as salinity, temperature, brightness, and a few others.

Sulfoquinovose is a select nutrient of prominent bacteria and a source of hydrogen sulfide in the human gut

Responses of the microbiota to diet are highly personalized but mechanistically not well understood because many metabolic capabilities and interactions of human gut microorganisms are unknown. Here we show that sulfoquinovose (SQ), a sulfonated monosaccharide omnipresent in green vegetables, is a selective yet relevant substrate for few but ubiquitous bacteria in the human gut. In human feces and in defined co-culture, Eubacterium rectale and Bilophila wadsworthia used recently identified pathways to cooperatively catabolize SQ with 2,3-dihydroxypropane-1-sulfonate as a transient intermediate to hydrogen sulfide (H2S), a key intestinal metabolite with disparate effects on host health. SQ-degradation capability is encoded in almost half of E. rectale genomes but otherwise sparsely distributed among microbial species in the human intestine. However, re-analysis of fecal metatranscriptome datasets of four human cohorts showed that SQ degradation (mostly from E. rectale and Faecalibacterium prausnitzii) and H2S production (mostly from B. wadsworthia) pathways were expressed abundantly across various health states, demonstrating that these microbial functions are core attributes of the human gut. The discovery of green-diet-derived SQ as an exclusive microbial nutrient and an additional source of H2S in the human gut highlights the role of individual dietary compounds and organosulfur metabolism on microbial activity and has implications for precision editing of the gut microbiota by dietary and prebiotic interventions.

Animalcules: interactive microbiome analytics and visualization in R

BackgroundMicrobial communities that live in and on the human body play a vital role in health and disease. Recent advances in sequencing technologies have enabled the study of microbial communities at unprecedented resolution. However, these advances in data generation have presented novel challenges to researchers attempting to analyze and visualize these data.ResultsTo address some of these challenges, we have developed animalcules, an easy-to-use interactive microbiome analysis toolkit for 16S rRNA sequencing data, shotgun DNA metagenomics data, and RNA-based metatranscriptomics profiling data. This toolkit combines novel and existing analytics, visualization methods, and machine learning models. For example, the toolkit features traditional microbiome analyses such as alpha/beta diversity and differential abundance analysis, combined with new methods for biomarker identification are. In addition, animalcules provides interactive and dynamic figures that enable users to understand their data and discover new insights. animalcules can be used as a standalone command-line R package or users can explore their data with the accompanying interactive R Shiny interface.ConclusionsWe present animalcules, an R package for interactive microbiome analysis through either an interactive interface facilitated by R Shiny or various command-line functions. It is the first microbiome analysis toolkit that supports the analysis of all 16S rRNA, DNA-based shotgun metagenomics, and RNA-sequencing based metatranscriptomics datasets. animalcules can be freely downloaded from GitHub at https://github.com/compbiomed/animalcules or installed through Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/animalcules.html.C6TN5sLkpWMyzjfpfLhNCdVideo abstract

Molecular analyses of the gill symbiosis of the bathymodiolin mussel Gigantidas platifrons.

SummaryAlthough the deep-sea bathymodiolin mussels have been intensively studied as a model of animal-bacteria symbiosis, it remains challenging to assess the host-symbiont interactions due to the complexity of the symbiotic tissue—the gill. Using cold-seep mussel Gigantidas platifrons as a model, we isolated the symbiont harboring bacteriocytes and profiled the transcriptomes of the three major parts of the symbiosis—the gill, the bacteriocyte, and the symbiont. This breakdown of the complex symbiotic tissue allowed us to characterize the host-symbiont interactions further. Our data showed that the gill's non-symbiotic parts play crucial roles in maintaining and protecting the symbiosis; the bacteriocytes supply the symbiont with metabolites, control symbiont population, and shelter the symbiont from phage infection; the symbiont dedicates to the methane oxidation and energy production. This study demonstrates that the bathymodiolin symbiosis interacts at the tissue, cellular, and molecular level, maintaining high efficiency and harmonic chemosynthetic micro niche.

EXPLORING THE METABOLICALLY ACTIVE RUMEN MICROBIOTA AND ITS FIBROLYTIC POTENTIAL IN CROSSBRED CATTLE FED ON FIBROUS DIET THROUGH METATRANSCRIPTOMICS

The rumen wharves conglomerate of symbiotic fibrolytic microflora with the potential to produce repertoire of carbohydrate-active enzymes to elicit the degradation of recalcitrant plant lignocellulosic complex into simpler forms that can be utilized by the host. A metatranscriptomics approach was adopted to explore the metabolically active microbiota and the transcripts involved in the deconstruction of lignocellulose in Indian crossbred cattle rumen. The experimental animals were fed with mixed diet for a period of twenty-one days and the total RNA was isolated from the rumen digesta using a modified total RNA extraction protocol. After mRNA enrichment, the cDNA libraries were subjected to sequencing under Illumina HiSeq platform and generated about 2.89 GB of raw sequences. The contig assembly was accomplished using two different tools and the redundant sequences were removed before further processing. A total of 133,930 orfs were predicted from the assembled contigs using MetaGeneMark tool and the taxonomic affiliation of orfs were achieved using MEGAN 6.0 Community Edition. A total of 17 bacterial, 5 eukaryotic and 1 archaeal phylum were identified from rumen metatranscriptomic dataset. Phylum Bacteroidetes were acknowledged as the most abundant and metabolically active rumen bacterial populations in cattle rumen with 36,414 orfs corresponding to it, followed by Firmicutes with 6,349 orfs. Further, MEGAN annotation of metatranscriptomic data at species level revealed that Prevotella brevis and Prevotella ruminicola as the most metabolically active bacterial populations representing 4,022 and 2,725 orfs each. The functional annotation of metatranscriptomic data using COG database revealed that a large number of transcripts (~16%) were corresponding to translation, ribosomal structure and biogenesis and carbohydrate transport and metabolism (15%). dbCAN annotation of rumen metatranscriptomic data identified and classified 5,267 transcripts belonging to 168 CAZyme families (GH-52%, GT-26%, CBM-14%, CE-6%, PL-2% and AA-0%). The microbial community analysis of the CAZyme encoding transcripts using M5NR database revealed that a significant proportion of CAZymes were contributed by genera Prevotella (37%) and Bacteroides (21%). The cattle rumen microbiome metatranscriptome analysis presented in this study facilitated the detection of large number of transcripts encoding diverse CAZymes that actively take part in the hydrolysis of plant lignocellulose complex that may be useful for improving livestock and biofuel generation.

Proteome specialization of anaerobic fungi during ruminal degradation of recalcitrant plant fiber

The rumen harbors a complex microbial mixture of archaea, bacteria, protozoa, and fungi that efficiently breakdown plant biomass and its complex dietary carbohydrates into soluble sugars that can be fermented and subsequently converted into metabolites and nutrients utilized by the host animal. While rumen bacterial populations have been well documented, only a fraction of the rumen eukarya are taxonomically and functionally characterized, despite the recognition that they contribute to the cellulolytic phenotype of the rumen microbiota. To investigate how anaerobic fungi actively engage in digestion of recalcitrant fiber that is resistant to degradation, we resolved genome-centric metaproteome and metatranscriptome datasets generated from switchgrass samples incubated for 48 h in nylon bags within the rumen of cannulated dairy cows. Across a gene catalog covering anaerobic rumen bacteria, fungi and viruses, a significant portion of the detected proteins originated from fungal populations. Intriguingly, the carbohydrate-active enzyme (CAZyme) profile suggested a domain-specific functional specialization, with bacterial populations primarily engaged in the degradation of hemicelluloses, whereas fungi were inferred to target recalcitrant cellulose structures via the detection of a number of endo- and exo-acting enzymes belonging to the glycoside hydrolase (GH) family 5, 6, 8, and 48. Notably, members of the GH48 family were amongst the highest abundant CAZymes and detected representatives from this family also included dockerin domains that are associated with fungal cellulosomes. A eukaryote-selected metatranscriptome further reinforced the contribution of uncultured fungi in the ruminal degradation of recalcitrant fibers. These findings elucidate the intricate networks of in situ recalcitrant fiber deconstruction, and importantly, suggest that the anaerobic rumen fungi contribute a specific set of CAZymes that complement the enzyme repertoire provided by the specialized plant cell wall degrading rumen bacteria.

Development of Microbiome Biobanks – Challenges and Opportunities

The microbiome research field is rapidly evolving, but the required biobanking infrastructure is currently fragmented and not prepared for the biobanking of microbiomes. The rapid advancement of technologies requires an urgent assessment of how biobanks can underpin research by preserving microbiome samples and their functional potential.

Metatranscriptomic analysis of modified atmosphere packaged poultry meat enables prediction of Brochothrix thermosphacta and Carnobacterium divergens in situ metabolism.

In this study, in situ-expressed metabolic routes of Brochothrix (B.) thermosphacta and Carnobacterium (C.) divergens were evaluated based on a metatranscriptomic dataset from bacteria growing on MAP chicken meat (O2/CO2; N2/CO2). Both species exhibited no (C. divergens) or minor transcription regulation (B. thermosphacta) within their main metabolic routes in response to different atmospheres. Both employ pathways related to glucose and ribose. Gluconeogenesis from lipid-borne glycerol is active in the progressing lack of carbohydrates. Pyruvate fates in both species comprise lactate, ethanol, acetate, CO2, formate, C4-compounds and H2O2 (only B. thermosphacta). Both species express genes for a minimal aerobic respiratory chain, but do not possess the genetic setting for a functional citric acid cycle. While products of carbohydrate and glycerol metabolism display mild to medium sensorial off-characteristics, predicted end products of their amino acid metabolism comprise, e.g., isobutyrate and isovalerate (B. thermosphacta) or cadaverine and tyramine (C. divergens) as potent spoilage compounds.

A framework for the computational prediction and analysis of non-coding RNAs in microbial environmental populations and their experimental validation

Small regulatory RNAs and antisense RNAs play important roles in the regulation of gene expression in bacteria but are underexplored, especially in natural populations. While environmentally relevant microbes often are not amenable to genetic manipulation or cannot be cultivated in the laboratory, extensive metagenomic and metatranscriptomic datasets for these organisms might be available. Hence, dedicated workflows for specific analyses are needed to fully benefit from this information. Here, we identified abundant sRNAs from oceanic environmental populations of the ecologically important primary producer Prochlorococcus starting from a metatranscriptomic differential RNA-Seq (mdRNA-Seq) dataset. We tracked their homologs in laboratory isolates, and we provide a framework for their further detailed characterization. Several of the experimentally validated sRNAs responded to ecologically relevant changes in cultivation conditions. The expression of the here newly discovered sRNA Yfr28 was highly stimulated in low-nitrogen conditions. Its predicted top targets include mRNAs encoding cell division proteins, a sigma factor, and several enzymes and transporters, suggesting a pivotal role of Yfr28 in the coordination of primary metabolism and cell division. A cis-encoded antisense RNA was identified as a possible positive regulator of atpF encoding subunit b’ of the ATP synthase complex. The presented workflow will also be useful for other environmentally relevant microorganisms for which experimental validation abilities are frequently limiting although there is wealth of sequence information available.

Comparative Metatranscriptomics of Periodontitis Supports a Common Polymicrobial Shift in Metabolic Function and Identifies Novel Putative Disease-Associated ncRNAs.

Periodontitis is an inflammatory disease that deteriorates bone supporting teeth afflicting ∼743 million people worldwide. Bacterial communities associated with disease have been classified into red, orange, purple, blue, green, and yellow complexes based on their roles in the periodontal pocket. Previous metagenomic and metatranscriptomics analyses suggest a common shift in metabolic signatures in disease vs. healthy communities with up-regulated processes including pyruvate fermentation, histidine degradation, amino acid metabolism, TonB-dependent receptors. In this work, we examine existing metatranscriptome datasets to identify the commonly differentially expressed transcripts and potential underlying RNA regulatory mechanisms behind the metabolic shifts. Raw RNA-seq reads from three studies (including 49 healthy and 48 periodontitis samples) were assembled into transcripts de novo. Analyses revealed 859 differentially expressed (DE) transcripts, 675 more- and 174 less-expressed. Only ∼20% of the DE transcripts originate from the pathogenic red/orange complexes, and ∼50% originate from organisms unaffiliated with a complex. Comparison of expression profiles revealed variations among disease samples; while specific metabolic processes are commonly up-regulated, the underlying organisms are diverse both within and across disease associated communities. Surveying DE transcripts for known ncRNAs from the Rfam database identified a large number of tRNAs and tmRNAs as well as riboswitches (FMN, glycine, lysine, and SAM) in more prevalent transcripts and the cobalamin riboswitch in both more and less prevalent transcripts. In silico discovery identified many putative ncRNAs in DE transcripts. We report 15 such putative ncRNAs having promising covariation in the predicted secondary structure and interesting genomic context. Seven of these are antisense of ribosomal proteins that are novel and may involve maintaining ribosomal protein stoichiometry during the disease associated metabolic shift. Our findings describe the role of organisms previously unaffiliated with disease and identify the commonality in progression of disease across three metatranscriptomic studies. We find that although the communities are diverse between individuals, the switch in metabolic signatures characteristic of disease is typically achieved through the contributions of several community members. Furthermore, we identify many ncRNAs (both known and putative) which may facilitate the metabolic shifts associated with periodontitis.

Activity and Metabolic Versatility of Complete Ammonia Oxidizers in Full-Scale Wastewater Treatment Systems.

The recent discovery of complete ammonia oxidizers (comammox) contradicts the paradigm that chemolithoautotrophic nitrification is always catalyzed by two different microorganisms. However, our knowledge of the survival strategies of comammox in complex ecosystems, such as full-scale wastewater treatment plants (WWTPs), remains limited. Analyses of genomes and in situ transcriptomes of four comammox organisms from two full-scale WWTPs revealed that comammox were active and showed a surprisingly high metabolic versatility. A gene cluster for the utilization of urea and a gene encoding cyanase suggest that comammox may use diverse organic nitrogen compounds in addition to free ammonia as the substrates. The comammox organisms also encoded the genomic potential for multiple alternative energy metabolisms, including respiration with hydrogen, formate, and sulfite as electron donors. Pathways for the biosynthesis and degradation of polyphosphate, glycogen, and polyhydroxyalkanoates as intracellular storage compounds likely help comammox survive unfavorable conditions and facilitate switches between lifestyles in fluctuating environments. One of the comammox strains acquired from the anaerobic tank encoded and transcribed genes involved in homoacetate fermentation or in the utilization of exogenous acetate, both pathways being unexpected in a nitrifying bacterium. Surprisingly, this strain also encoded a respiratory nitrate reductase which has not yet been found in any other Nitrospira genome and might confer a selective advantage to this strain over other Nitrospira strains in anoxic conditions.IMPORTANCE The discovery of comammox in the genus Nitrospira changes our perception of nitrification. However, genomes of comammox organisms have not been acquired from full-scale WWTPs, and very little is known about their survival strategies and potential metabolisms in complex wastewater treatment systems. Here, four comammox metagenome-assembled genomes and metatranscriptomic data sets were retrieved from two full-scale WWTPs. Their impressive and-among nitrifiers-unsurpassed ecophysiological versatility could make comammox Nitrospira an interesting target for optimizing nitrification in current and future bioreactor configurations.

Metatranscriptomic Profiling Reveals the Effect of Breed on Active Rumen Eukaryotic Composition in Beef Cattle With Varied Feed Efficiency.

Exploring the compositional characteristics of rumen eukaryotic community can expand our understanding of their role in rumen function and feed efficiency. In this study, we applied metatranscriptomics to characterize the active rumen eukaryotic community (protozoa and fungi) in beef cattle (n = 48) of three breeds [Angus (AN), Charolais (CH), and Kinsella Composite (KC)] and with divergent residual feed intake (RFI). The composition of active rumen eukaryotic microbiota was evaluated based on enriched 18S rRNAs from the metatranscriptomic datasets. At the phylum level, a total of four protozoal taxa (Ciliophora, Parabasalia, unclassified SAR, and unclassified Alveolata), six fungal taxa (Neocallimastigomycota, Basidiomycota, unclassified Fungi, Mucoromycota, Ascomycota, and Chytridiomycota), and one sister group of kingdom Fungi (unclassified Opisthokonta) were detected with relative abundances higher than 0.01% and in at least 50% of animals within each breed. Among these, Ciliophora, Parabasalia, unclassified Opisthokonta, and Neocallimastigomycota were the top four active eukaryotic phyla. At the genus level, a total of 8 ciliated protozoa, 5 flagellated protozoa, 5 anaerobic fungi, and 10 aerobic fungi taxa were detected, with unclassified Trichostomatia, Tetratrichomonas, unclassified Neocallimastigaceae, and Pleurotus being the most predominant taxa of ciliated protozoa, flagellated protozoa, anaerobic fungi, and aerobic fungi, respectively. Differential abundance analysis revealed that breed had a significant effect on the phylogenetic lineages of rumen eukaryotes, and seven fungal taxa were more abundant (linear discriminant analysis score > 2 with P < 0.05) in the rumen of KC steers than in the rumen of AN and CH steers. Although principal coordinate analysis (PCoA) revealed that the ruminal active eukaryotic profiles were not distinguishable between high- and low-RFI groups, the diversity indices, including Faith’s phylogenetic diversity (PD), observed operational taxonomic units (OTUs), and Shannon index of rumen eukaryotes were higher in low-RFI steers than those in high-RFI steers. Meanwhile, the abundance of genus Entodinium and the kingdom Fungi was higher in low-RFI steers than that in high-RFI steers. This information on active rumen eukaryotic microbiota and identified differential abundance of taxa between high- and low-RFI animals suggests the possibility of improving feed efficiency through altering rumen eukaryotic microbiota.

A comprehensive non-redundant gene catalog reveals extensive within-community intraspecies diversity in the human vagina

Analysis of metagenomic and metatranscriptomic data is complicated and typically requires extensive computational resources. Leveraging a curated reference database of genes encoded by members of the target microbiome can make these analyses more tractable. In this study, we assemble a comprehensive human vaginal non-redundant gene catalog (VIRGO) that includes 0.95 million non-redundant genes. The gene catalog is functionally and taxonomically annotated. We also construct a vaginal orthologous groups (VOG) from VIRGO. The gene-centric design of VIRGO and VOG provides an easily accessible tool to comprehensively characterize the structure and function of vaginal metagenome and metatranscriptome datasets. To highlight the utility of VIRGO, we analyze 1,507 additional vaginal metagenomes, and identify a high degree of intraspecies diversity within and across vaginal microbiota. VIRGO offers a convenient reference database and toolkit that will facilitate a more in-depth understanding of the role of vaginal microorganisms in women’s health and reproductive outcomes.

Can rumen bacteria communicate to each other?

BackgroundThe rumen contains a myriad of microbes whose primary role is to degrade and ferment dietary nutrients, which then provide the host with energy and nutrients. Rumen microbes commonly attach to ingested plant materials and form biofilms for effective plant degradation. Quorum sensing (QS) is a well-recognised form of bacterial communication in most biofilm communities, with homoserine lactone (AHL)-based QS commonly being used by Gram-negative bacteria alone and AI-2 Lux-based QS communication being used to communicate across Gram-negative and Gram-positive bacteria. However, bacterial cell to cell communication in the rumen is poorly understood. In this study, rumen bacterial genomes from the Hungate collection and Genbank were prospected for QS-related genes. To check that the discovered QS genes are actually expressed in the rumen, we investigated expression levels in rumen metatranscriptome datasets.ResultsA total of 448 rumen bacterial genomes from the Hungate collection and Genbank, comprised of 311 Gram-positive, 136 Gram-negative and 1 Gram stain variable bacterium, were analysed. Abundance and distribution of AHL and AI-2 signalling genes showed that only one species (Citrobacter sp. NLAE-zl-C269) of a Gram-negative bacteria appeared to possess an AHL synthase gene, while the Lux-based genes (AI-2 QS) were identified in both Gram-positive and Gram-positive bacteria (191 genomes representing 38.2% of total genomes). Of these 192 genomes, 139 are from Gram-positive bactreetteria and 53 from Gram-negative bacteria. We also found that the genera Butyrivibrio, Prevotella, Ruminococcus and Pseudobutyrivibrio, which are well known as the most abundant bacterial genera in the rumen, possessed the most lux-based AI-2 QS genes. Gene expression levels within the metatranscriptome dataset showed that Prevotella, in particular, expressed high levels of LuxS synthase suggesting that this genus plays an important role in QS within the rumen.ConclusionThis is the most comprehensive study of QS in the rumen microbiome to date. This study shows that AI-2-based QS is rife in the rumen. These results allow a greater understanding on plant-microbe interactions in the rumen.

Expansion of known ssRNA phage genomes: From tens to over a thousand.

The first sequenced genome was that of the 3569-nucleotide single-stranded RNA (ssRNA) bacteriophage MS2. Despite the recent accumulation of vast amounts of DNA and RNA sequence data, only 12 representative ssRNA phage genome sequences are available from the NCBI Genome database (June 2019). The difficulty in detecting RNA phages in metagenomic datasets raises questions as to their abundance, taxonomic structure, and ecological importance. In this study, we iteratively applied profile hidden Markov models to detect conserved ssRNA phage proteins in 82 publicly available metatranscriptomic datasets generated from activated sludge and aquatic environments. We identified 15,611 nonredundant ssRNA phage sequences, including 1015 near-complete genomes. This expansion in the number of known sequences enabled us to complete a phylogenetic assessment of both sequences identified in this study and known ssRNA phage genomes. Our expansion of these viruses from two environments suggests that they have been overlooked within microbiome studies.

Design of targeted primers based on 16S rRNA sequences in meta-transcriptomic datasets and identification of a novel taxonomic group in the Asgard archaea

BackgroundAmplification of small subunit (SSU) rRNA genes with universal primers is a common method used to assess microbial populations in various environmental samples. However, owing to limitations in coverage of these universal primers, some microorganisms remain unidentified. The present study aimed to establish a method for amplifying nearly full-length SSU rRNA gene sequences of previously unidentified prokaryotes, using newly designed targeted primers via primer evaluation in meta-transcriptomic datasets.MethodsPrimer binding regions of universal primer 8F/Arch21F for bacteria or archaea were used for primer evaluation of SSU rRNA sequences in meta-transcriptomic datasets. Furthermore, targeted forward primers were designed based on SSU rRNA reads from unclassified groups unmatched with the universal primer 8F/Arch21F, and these primers were used to amplify nearly full-length special SSU rRNA gene sequences along with universal reverse primer 1492R. Similarity and phylogenetic analysis were used to confirm their novel status.ResultsUsing this method, we identified unclassified SSU rRNA sequences that were not matched with universal primer 8F and Arch21F. A new group within the Asgard superphylum was amplified by the newly designed specific primer based on these unclassified SSU rRNA sequences by using mudflat samples.ConclusionWe showed that using specific primers designed based on universal primer evaluation from meta-transcriptomic datasets, identification of novel taxonomic groups from a specific environment is possible.

A new lineage of segmented RNA viruses infecting animals.

Metagenomic sequencing has revolutionised our knowledge of virus diversity, with new virus sequences being reported faster than ever before. However, virus discovery from metagenomic sequencing usually depends on detectable homology: without a sufficiently close relative, so-called ‘dark’ virus sequences remain unrecognisable. An alternative approach is to use virus-identification methods that do not depend on detecting homology, such as virus recognition by host antiviral immunity. For example, virus-derived small RNAs have previously been used to propose ‘dark’ virus sequences associated with the Drosophilidae (Diptera). Here, we combine published Drosophila data with a comprehensive search of transcriptomic sequences and selected meta-transcriptomic datasets to identify a completely new lineage of segmented positive-sense single-stranded RNA viruses that we provisionally refer to as the Quenyaviruses. Each of the five segments contains a single open reading frame, with most encoding proteins showing no detectable similarity to characterised viruses, and one sharing a small number of residues with the RNA-dependent RNA polymerases of single- and double-stranded RNA viruses. Using these sequences, we identify close relatives in approximately 20 arthropods, including insects, crustaceans, spiders, and a myriapod. Using a more conserved sequence from the putative polymerase, we further identify relatives in meta-transcriptomic datasets from gut, gill, and lung tissues of vertebrates, reflecting infections of vertebrates or of their associated parasites. Our data illustrate the utility of small RNAs to detect viruses with limited sequence conservation, and provide robust evidence for a new deeply divergent and phylogenetically distinct RNA virus lineage.

Occurrence and expression of genes encoding methyl-compound production in rumen bacteria

BackgroundDigestive processes in the rumen lead to the release of methyl-compounds, mainly methanol and methylamines, which are used by methyltrophic methanogens to form methane, an important agricultural greenhouse gas. Methylamines are produced from plant phosphatidylcholine degradation, by choline trimethylamine lyase, while methanol comes from demethoxylation of dietary pectins via pectin methylesterase activity. We have screened rumen metagenomic and metatranscriptomic datasets, metagenome assembled genomes, and the Hungate1000 genomes to identify organisms capable of producing methyl-compounds. We also describe the enrichment of pectin-degrading and methane-forming microbes from sheep rumen contents and the analysis of their genomes via metagenomic assembly.ResultsScreens of metagenomic data using the protein domains of choline trimethylamine lyase (CutC), and activator protein (CutD) found good matches only to Olsenella umbonata and to Caecibacter, while the Hungate1000 genomes and metagenome assembled genomes from the cattle rumen found bacteria within the phyla Actinobacteria, Firmicutes and Proteobacteria. The cutC and cutD genes clustered with genes that encode structural components of bacterial microcompartment proteins. Prevotella was the dominant genus encoding pectin methyl esterases, with smaller numbers of sequences identified from other fibre-degrading rumen bacteria. Some large pectin methyl esterases (> 2100 aa) were found to be encoded in Butyrivibrio genomes. The pectin-utilising, methane-producing consortium was composed of (i) a putative pectin-degrading bacterium (phylum Tenericutes, class Mollicutes), (ii) a galacturonate-using Sphaerochaeta sp. predicted to produce acetate, lactate, and ethanol, and (iii) a methylotrophic methanogen, Methanosphaera sp., with the ability to form methane via a primary ethanol-dependent, hydrogen-independent, methanogenesis pathway.ConclusionsThe main bacteria that produce methyl-compounds have been identified in ruminants. Their enzymatic activities can now be targeted with the aim of finding ways to reduce the supply of methyl-compound substrates to methanogens, and thereby limit methylotrophic methanogenesis in the rumen.