Metatranscriptomics reveals unique microbial small RNAs in the ocean's water column

A mixed blessing of influent leachate microbes in downstream biotreatment systems of a full-scale landfill leachate treatment plant

In landfill leachate treatment plants (LLTPs), the microbiome plays a pivotal role in the decomposition of organic compounds, reduction in nutrient levels, and elimination of toxins. However, the effects of microbes in landfill leachate influents on downstream treatment systems remain poorly understood. To address this knowledge gap, we collected 23 metagenomic and 12 metatranscriptomic samples from landfill leachate and activated sludge from various treatment units in a full-scale LLTP. We successfully recovered 1,152 non-redundant metagenome-assembled genomes (MAGs), encompassing a wide taxonomic range, including 48 phyla, 95 classes, 166 orders, 247 families, 238 genera, and 1,152 species. More diverse microbes were observed in the influent leachate than in the downstream biotreatment systems, among which, an unprecedented ∼30 % of microbes with transcriptional expression migrated from the influent to the biological treatment units. Network analysis revealed that 399 shared MAGs across the four units exhibited high node centrality and degree, thus supporting enhanced interactions and increased stability of microbial communities. Functional reconstruction and genome characterization of MAGs indicated that these shared MAGs possessed greater capabilities for carbon, nitrogen, sulfur, and arsenic metabolism compared to non-shared MAGs. We further identified a novel species of Zixibacteria in the leachate influent with discrete lineages from those in other environments that accounted for up to 17 % of the abundance of the shared microbial community and exhibited notable metabolic versatility. Meanwhile, we presented groundbreaking evidence of the involvement of Zixibacteria-encoded genes in the production of harmful gas emissions, such as N2O and H2S, at the transcriptional level, thus suggesting that influent microbes may pose safety risks to downstream treatment systems. In summary, this study revealed the complex impact of the influent microbiome on LLTP and emphasizes the need to consider these microbial characteristics when designing treatment technologies and strategies for landfill leachate management.

Metatranscriptome revealed how carbon brush addition affected the fermentation of food wastewater in the low-temperature environment

Improving the anaerobic digestion (AD) performance in low-temperature environments has become a key factor in the development of waste treatment and resource recovery in cold regions. The utilization of external carriers to form a biofilm is the simplest and most practical way to enhance the psychrophilic AD performance in cold regions. In this study, the effect of carrier addition on the fermentation performance of low-temperature (15 ± 2 °C) food wastewater was investigated by forming biofilms with carbon brushes. The results showed that although the biofilm formation enhanced methane yields (15.24%), it also caused more accumulation of propionic acid (306.99-626.89 mg/L), and the concentration of acetic acid (86.78-254.71 mg/L) was relatively low. The microbial community revealed the highest abundance of the fermentative bacterium Firmicutes and the carbon brush carrier significantly increased its relative abundance (23.74%). Metatranscriptomic sequencing revealed that the abundance level of Clostridium, Bacteroides, Sedimentibacter and Pelotomaculum was the highest, reaching 80% in all groups. In addition, the abundance level of electroactive microorganisms in biofilms was higher, while the fermentation bacteria and methanogens were lower. This showed that biofilm can enrich more electroactive microorganisms, and granular sludge needs to enrich more fermentation bacteria and methanogens to ensure metabolic activity. Further studies have found that carbon metabolism had the highest activity (27.86%-30.39%) and H+-transporting ATPase (atp) was the most dominant functional enzyme (85.50%-86.65%) involved in electron transport in low-temperature fermentation of food wastewater. Interestingly, these expression levels of active granular sludge were higher than the biofilm formed by carbon brushes. Meanwhile, analysis of the methanogenic pathway found that active granular sludge tends to be directly metabolized to realize acetate to acetyl-CoA by acetyl-CoA synthetase (ACSS), while biofilms were not significantly different in the two metabolic pathways of acetate. These results deepen the understanding of treating low-temperature food wastewater.

RNAcode_Web - Convenient identification of evolutionary conserved protein coding regions

The differentiation of regions with coding potential from non-coding regions remains a key task in computational biology. Methods such as RNAcode that exploit patterns of sequence conservation for this task have a substantial advantage in classification accuracy in particular for short coding sequences, compared to methods that rely on a single input sequence. However, they require sequence alignments as input. Frequently, suitable multiple sequence alignments are not readily available and are tedious, and sometimes difficult to construct. We therefore introduce here a new web service that provides access to the well-known coding sequence detector RNAcode with minimal user overhead. It requires as input only a single target nucleotide sequence. The service automates the collection, selection, and preparation of homologous sequences from the NCBI database, as well as the construction of the multiple sequence alignment that are needed as input for RNAcode. The service automatizes the entire pre- and postprocessing and thus makes the investigation of specific genomic regions for previously unannotated coding regions, such as small peptides or additional introns, a simple task that is easily accessible to non-expert users. RNAcode_Web is accessible online at rnacode.bioinf.uni-leipzig.de.

Little reason to call them small noncoding RNAs

Hundreds of different species of small RNAs can populate a bacterial cell. This small transcriptome contains important information for the adaptation of cellular physiology to environmental changes. Underlying cellular networks involving small RNAs are RNA-RNA and RNA-protein interactions, which are often intertwined. In addition, small RNAs can function as mRNAs. In general, small RNAs are referred to as noncoding because very few are known to contain translated open reading frames. In this article, we intend to highlight that the number of small RNAs that fall within the set of translated RNAs is bound to increase. In addition, we aim to emphasize that the dynamics of the small transcriptome involve different functional codes, not just the genetic code. Therefore, since the role of small RNAs is always code-driven, we believe that there is little reason to continue calling them small noncoding RNAs.

A Reduction of Transcriptional Regulation in Aquatic Oligotrophic Microorganisms Enhances Fitness in Nutrient-Poor Environments

In this review, we consider the regulatory strategies of aquatic oligotrophs, microbial cells that are adapted to thrive under low-nutrient concentrations in oceans, lakes, and other aquatic ecosystems. Many reports have concluded that oligotrophs use less transcriptional regulation than copiotrophic cells, which are adapted to high nutrient concentrations and are far more common subjects for laboratory investigations of regulation. It is theorized that oligotrophs have retained alternate mechanisms of regulation, such as riboswitches, that provide shorter response times and smaller amplitude responses and require fewer cellular resources. We examine the accumulated evidence for distinctive regulatory strategies in oligotrophs. We explore differences in the selective pressures copiotrophs and oligotrophs encounter and ask why, although evolutionary history gives copiotrophs and oligotrophs access to the same regulatory mechanisms, they might exhibit distinctly different patterns in how these mechanisms are used. We discuss the implications of these findings for understanding broad patterns in the evolution of microbial regulatory networks and their relationships to environmental niche and life history strategy. We ask whether these observations, which have emerged from a decade of increased investigation of the cell biology of oligotrophs, might be relevant to recent discoveries of many microbial cell lineages in nature that share with oligotrophs the property of reduced genome size.

'Multi-omics' data integration: applications in probiotics studies

The concept of probiotics is witnessing increasing attention due to its benefits in influencing the host microbiome and the modulation of host immunity through the strengthening of the gut barrier and stimulation of antibodies. These benefits, combined with the need for improved nutraceuticals, have resulted in the extensive characterization of probiotics leading to an outburst of data generated using several 'omics' technologies. The recent development in system biology approaches to microbial science is paving the way for integrating data generated from different omics techniques for understanding the flow of molecular information from one 'omics' level to the other with clear information on regulatory features and phenotypes. The limitations and tendencies of a 'single omics' application to ignore the influence of other molecular processes justify the need for 'multi-omics' application in probiotics selections and understanding its action on the host. Different omics techniques, including genomics, transcriptomics, proteomics, metabolomics and lipidomics, used for studying probiotics and their influence on the host and the microbiome are discussed in this review. Furthermore, the rationale for 'multi-omics' and multi-omics data integration platforms supporting probiotics and microbiome analyses was also elucidated. This review showed that multi-omics application is useful in selecting probiotics and understanding their functions on the host microbiome. Hence, recommend a multi-omics approach for holistically understanding probiotics and the microbiome.

Microbial interactions enhanced environmental fitness and expanded ecological niches under dibutyl phthalate and cadmium co-contamination

Co-contamination of organic pollutants and heavy metals is universal in the natural environment. Dibutyl phthalate (DBP), a typical plasticizer, frequently coexists with cadmium (Cd) in nature. However, little attention has been given to the impacts of co-contamination by DBP and Cd on microbial communities or the responses of microbes. To address this, a microcosm experiment was conducted by supplying the exogenous DBP-degrading bacterium Glutamicibacter nicotianae ZM05 to investigate the interplay among DBP-Cd co-contamination, the exogenous DBP-degrading bacterium G. nicotianae ZM05, and indigenous microorganisms. To adapt to co-contamination stress, microbial communities adjust their diversity, interactions, and functions. The stability of the microbial community decreased under co-contamination, as evidenced by lower diversity, simpler network, and fewer ecological niches. Microbial interactions were strengthened, as evidenced by enriched pathways related to microbial communications. Meanwhile, interactions between microorganisms enhanced the environmental fitness of the exogenous DBP-degrading bacterium ZM05. Based on co-occurrence network prediction and coculture experiments, metabolic interactions between the non-DBP-degrading bacterium Cupriavidus metallidurans ZM16 and ZM05 were proven. Strain ZM16 utilized protocatechuic acid, a DBP downstream metabolite, to relieve acid inhibition and adsorbed Cd to relieve toxic stress. These findings help to explain the responses of bacterial and fungal communities to DBP-Cd co-contamination and provide new insights for the construction of degrading consortia for bioremediation.

Metatranscriptomics Unravel Composition, Drivers, and Functions of the Active Microorganisms in Light-Flavor Liquor Fermentation

The microbial community in the fermented pit determines the quantity and quality of light-flavor liquor. Genetic diversity and the potential functions of the microbial community are often analyzed by DNA-based omics sequencing. However, the features of the active microbial community have not been systematically studied. Here, metatranscriptomic analysis was performed to elucidate the active microbial composition, drivers, and their functions in light-flavor liquor fermentation. Bacterial genera, Lactobacillus, Streptococcus, Pediococcus, Thermotoga, and Faecalibacterium, and fungal genera, Saccharomyces, Talaromyces, Aspergillus, Clavispora, Rhizophagus, Cyberlindnera, and Wickerhamomyces, were the dominant active microorganisms during the fermentation process. Additionally, they dominated the three-stage fermentation successively. Redundancy analysis showed that pH, ethanol, moisture, and starch were the main driving forces of microbial succession. Among the genes for the respective carbohydrate-active enzyme families, those for the glycoside hydrolase family 23, the glycosyltransferase family 2, the carbohydrate-binding module family 50, the polysaccharide lyase family 4, the auxiliary activity family 1, and the carbohydrate esterase family 9 showed the highest expression level. Additionally, the highly expressed enzymes and their contributed microorganisms were found in the key KEGG pathways, including carbohydrate metabolism, energy metabolism, lipid metabolism, and amino acid metabolism. Based on these data, a functional model of carbohydrate hydrolysis, ethanol production, and flavor generation were proposed. Taken together, Saccharomyces, Lactobacillus, Wickerhamomyces, Pediococcus, Candida, and Faecalibacterium were suggested as the core active microorganisms. Overall, our findings provide new insights into the composition, drivers, and functions of the active microorganisms, which is crucial for improving the quality of light-flavor liquor. IMPORTANCE There is an urgent need for discovering the diversity and functions of the active microbial community in solid-state fermentation, especially in the pit of Chinese distilled liquor fermentation. Although the genetic composition of the microbial community has been clarified frequently by DNA-based sequencing, the composition and functions of the active microbial community have not been systematically revealed so far. Therefore, analysis of RNA-based data is crucial for discovering the functional microbial community. In this study, we employed metatranscriptomic analysis to elucidate the active microbial composition, successive drivers, and their functions in light-flavor liquor fermentation. The strategy can be broadly useful for discovering the active microbial community and exploring their functions in other types of flavor distilled liquor or other ecosystems. This study provides new insights into the understanding of the active microbial community composition and its functions.

Discrimination of Bacterial Community Structures among Healthy, Gingivitis, and Periodontitis Statuses through Integrated Metatranscriptomic and Network Analyses

Periodontal disease is an inflammatory condition caused by polymicrobial infection. The inflammation is initiated at the gingiva (gingivitis) and then extends to the alveolar bone, leading to tooth loss (periodontitis). Previous studies have shown differences in bacterial composition between periodontal healthy and diseased sites. However, bacterial metabolic activities during the health-to-periodontitis microbiome shift are still inadequately understood. This study was performed to investigate the bacterial characteristics of healthy, gingivitis, and periodontitis statuses through metatranscriptomic analysis. Subgingival plaque samples of healthy, gingivitis, and periodontitis sites in the same oral cavity were collected from 21 patients. Bacterial compositions were then determined based on 16S rRNA reads; taxonomic and functional profiles derived from genes based on mRNA reads were estimated. The results showed clear differences in bacterial compositions and functional profiles between healthy and periodontitis sites. Co-occurrence networks were constructed for each group by connecting two bacterial species if their mRNA abundances were positively correlated. The clustering coefficient values were 0.536 for healthy, 0.600 for gingivitis, and 0.371 for periodontitis sites; thus, network complexity increased during gingivitis development, whereas it decreased during progression to periodontitis. Taxa, including Eubacterium nodatum, Eubacterium saphenum, Filifactor alocis, and Fretibacterium fastidiosum, showed greater transcriptional activities than those of red complex bacteria, in conjunction with disease progression. These taxa were associated with periodontal disease progression, and the health-to-periodontitis microbiome shift was accompanied by alterations in bacterial network structure and complexity.

IMPORTANCE The characteristics of the periodontal microbiome influence clinical periodontal status. Gingivitis involves reversible gingival inflammation without alveolar bone resorption. In contrast, periodontitis is an irreversible disease characterized by inflammatory destruction in both soft and hard tissues. An imbalance of the microbiome is present in both gingivitis and periodontitis. However, differences in microbiomes and their functional activities in the healthy, gingivitis, and periodontitis statuses are still inadequately understood. Furthermore, some inflamed gingival statuses do not consistently cause attachment loss. In this study, metatranscriptomic analyses were used to investigate the specific bacterial composition and gene expression patterns of the microbiomes of the healthy, gingivitis, and periodontitis statuses. In addition, co-occurrence network analysis revealed that the gingivitis site included features of networks observed in both the healthy and periodontitis sites. These results provide transcriptomic evidence to support gingivitis as an intermediate state between the healthy and periodontitis statuses.

An Insight into Vaginal Microbiome Techniques

There is a unique microbial community in the female lower genital tract known as the vaginal microbiota, which varies in composition and density and provides significant benefits during pregnancy, reproductive cyclicity, healthy newborn delivery, protection from preterm birth, infections such as UTIs, bacterial vaginosis, and so on, and improves the efficacy of treatments for vaginal cancers. Methods: It is necessary to know how the vaginal microbiome is composed in order to make an accurate diagnosis of the diseases listed above. A microbiome’s members are difficult to classify, and the way microbial communities function and influence host–pathogen interactions are difficult to understand. More and more metagenomic studies are able to unravel such complexities due to advances in high-throughput sequencing and bioinformatics. When it comes to vaginal microbiota research, we’ll be looking at the use of modern techniques and strategies that can be used to investigate variations in vaginal microbiota in order to detect diseases earlier, better treat vaginal disorders, and boost women’s health. Discussion: The discussed techniques and strategies may improve the treatment of vaginal disorders and may be beneficial for women’s overall health.

High Transcriptional Activity and Diverse Functional Repertoires of Hundreds of Giant Viruses in a Coastal Marine System

Viruses belonging to the Nucleocytoviricota phylum are globally distributed and include members with notably large genomes and complex functional repertoires. Recent studies have shown that these viruses are particularly diverse and abundant in marine systems, but the magnitude of actively replicating Nucleocytoviricota present in ocean habitats remains unclear. In this study, we compiled a curated database of 2,431 Nucleocytoviricota genomes and used it to examine the gene expression of these viruses in a 2.5-day metatranscriptomic time-series from surface waters of the California Current. We identified 145 viral genomes with high levels of gene expression, including 90 Imitervirales and 49 Algavirales viruses. In addition to recovering high expression of core genes involved in information processing that are commonly expressed during viral infection, we also identified transcripts of diverse viral metabolic genes from pathways such as glycolysis, the TCA cycle, and the pentose phosphate pathway, suggesting that virus-mediated reprogramming of central carbon metabolism is common in oceanic surface waters. Surprisingly, we also identified viral transcripts with homology to actin, myosin, and kinesin domains, suggesting that viruses may use these gene products to manipulate host cytoskeletal dynamics during infection. We performed phylogenetic analysis on the virus-encoded myosin and kinesin proteins, which demonstrated that most belong to deep-branching viral clades, but that others appear to have been acquired from eukaryotes more recently. Our results highlight a remarkable diversity of active Nucleocytoviricota in a coastal marine system and underscore the complex functional repertoires expressed by these viruses during infection. IMPORTANCE The discovery of giant viruses has transformed our understanding of viral complexity. Although viruses have traditionally been viewed as filterable infectious agents that lack metabolism, giant viruses can reach sizes rivalling cellular lineages and possess genomes encoding central metabolic processes. Recent studies have shown that giant viruses are widespread in aquatic systems, but the activity of these viruses and the extent to which they reprogram host physiology in situ remains unclear. Here, we show that numerous giant viruses consistently express central metabolic enzymes in a coastal marine system, including components of glycolysis, the TCA cycle, and other pathways involved in nutrient homeostasis. Moreover, we found expression of several viral-encoded actin, myosin, and kinesin genes, indicating viral manipulation of the host cytoskeleton during infection. Our study reveals a high activity of giant viruses in a coastal marine system and indicates they are a diverse and underappreciated component of microbial diversity in the ocean.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.

Gut Microbiota in Liver Disease: What Do We Know and What Do We Not Know?

The gut and the liver have a bidirectional communication via the biliary system and the portal vein. The intestinal microbiota and microbial products play an important role for modulating liver diseases such as alcohol-associated liver disease, non-alcoholic fatty liver disease and steatohepatitis, and cholestatic liver diseases. Here, we review the role of the gut microbiota and its products for the pathogenesis and therapy of chronic liver diseases.

A Novel Freshwater to Marine Evolutionary Transition Revealed within Methylophilaceae Bacteria from the Arctic Ocean

Bacteria inhabiting polar oceans, particularly the Arctic Ocean, are less studied than those at lower latitudes. Discovering bacterial adaptations to Arctic Ocean conditions is essential for understanding responses to the accelerated environmental changes occurring in the North. The Methylophilaceae are emerging as a model for investigating the genomic basis of habitat adaptation, because related lineages are widely distributed across both freshwater and marine ecosystems. Here, we investigated Methylophilaceae diversity in the salinity-stratified surface waters of the Canada Basin, Arctic Ocean. In addition to a diversity of marine OM43 lineages, we report on the genomic characteristics and evolution of a previously undescribed Methylophilaceae clade (BS01) common to polar surface waters yet related to freshwater sediment Methylotenera species. BS01 is restricted to the lower-salinity surface waters, while OM43 is found throughout the halocline. An acidic proteome supports a marine lifestyle for BS01, but gene content shows increased metabolic versatility compared to OM43 and evidence for ongoing genome-streamlining. Phylogenetic reconstruction shows that BS01 colonized the pelagic ocean independently of OM43 via convergent evolution. Salinity adaptation and differences in one-carbon and nitrogen metabolism may play a role in niche differentiation between BS01 and OM43. In particular, urea utilization by BS01 is predicted to provide an ecological advantage over OM43 given the limited amount of inorganic nitrogen in the Canada Basin. These observations provide further evidence that the Arctic Ocean is inhabited by distinct bacterial groups and that at least one group (BS01) evolved via a freshwater to marine environmental transition.

What We Know So Far about the Metabolite-Mediated Microbiota-Intestinal Immunity Dialogue and How to Hear the Sound of This Crosstalk

Trillions of microorganisms, termed the "microbiota", reside in the mammalian gastrointestinal tract, and collectively participate in regulating the host phenotype. It is now clear that the gut microbiota, metabolites, and intestinal immune function are correlated, and that alterations of the complex and dynamic host-microbiota interactions can have deep consequences for host health. However, the mechanisms by which the immune system regulates the microbiota and by which the microbiota shapes host immunity are still not fully understood. This article discusses the contribution of metabolites in the crosstalk between gut microbiota and immune cells. The identification of key metabolites having a causal effect on immune responses and of the mechanisms involved can contribute to a deeper insight into host-microorganism relationships. This will allow a better understanding of the correlation between dysbiosis, microbial-based dysmetabolism, and pathogenesis, thus creating opportunities to develop microbiota-based therapeutics to improve human health. In particular, we systematically review the role of soluble and membrane-bound microbial metabolites in modulating host immunity in the gut, and of immune cells-derived metabolites affecting the microbiota, while discussing evidence of the bidirectional impact of this crosstalk. Furthermore, we discuss the potential strategies to hear the sound of such metabolite-mediated crosstalk.

Particulate Metabolites and Transcripts Reflect Diel Oscillations of Microbial Activity in the Surface Ocean

Light fuels photosynthesis and organic matter production by primary producers in the sunlit ocean. The quantity and quality of the organic matter produced influence community function, yet in situ measurements of metabolites, the products of cellular metabolism, over the diel cycle are lacking. We evaluated community-level biochemical consequences of oscillations of light in the North Pacific Subtropical Gyre by quantifying 79 metabolites in particulate organic matter from 15 m every 4 h over 8 days. Total particulate metabolite concentration peaked at dusk and represented up to 2% of total particulate organic carbon (POC). The concentrations of 55/79 (70%) individual metabolites exhibited significant 24-h periodicity, with daily fold changes from 1.6 to 12.8, often greater than those of POC and flow cytometry-resolvable biomass, which ranged from 1.2 to 2.8. Paired metatranscriptome analysis revealed the taxa involved in production and consumption of a subset of metabolites. Primary metabolites involved in anabolism and redox maintenance had significant 24-h periodicity and diverse organisms exhibited diel periodicity in transcript abundance associated with these metabolites. Compounds with osmotic properties displayed the largest oscillations in concentration, implying rapid turnover and supporting prior evidence of functions beyond cell turgor maintenance. The large daily oscillation of trehalose paired with metatranscriptome and culture data showed that trehalose is produced by the nitrogen-fixing cyanobacterium Crocosphaera, likely to store energy for nighttime metabolism. Together, paired measurements of particulate metabolites and transcripts resolve strategies that microbes use to manage daily energy and redox oscillations and highlight dynamic metabolites with cryptic roles in marine microbial ecosystems.IMPORTANCE Fueled by light, phytoplankton produce the organic matter that supports ocean ecosystems and carbon sequestration. Ocean change impacts microbial metabolism with repercussions for biogeochemical cycling. As the small molecule products of cellular metabolism, metabolites often change rapidly in response to environmental conditions and form the basis of energy and nutrient management and storage within cells. By pairing measurements of metabolites and gene expression in the stratified surface ocean, we reveal strategies of microbial energy management over the day-night cycle and hypothesize that oscillating metabolites are important substrates for dark respiration by phytoplankton. These high-resolution diel measurements of in situ metabolite concentrations form the basis for future work into the specific roles these compounds play in marine microbial communities.

Genome-enabled exploration of microbial ecology and evolution in the sea: a rising tide lifts all boats

As a young bacteriologist just launching my career during the early days of the 'microbial revolution' in the 1980s, I was fortunate to participate in some early discoveries, and collaborate in the development of cross-disciplinary methods now commonly referred to as "metagenomics". My early scientific career focused on applying phylogenetic and genomic approaches to characterize 'wild' bacteria, archaea and viruses in their natural habitats, with an emphasis on marine systems. These central interests have not changed very much for me over the past three decades, but knowledge, methodological advances and new theoretical perspectives about the microbial world certainly have. In this invited 'How we did it' perspective, I trace some of the trajectories of my lab's collective efforts over the years, including phylogenetic surveys of microbial assemblages in marine plankton and sediments, development of microbial community gene- and genome-enabled surveys, and application of genome-guided, cultivation-independent functional characterization of novel enzymes, pathways and their relationships to in situ biogeochemistry. Throughout this short review, I attempt to acknowledge, all the mentors, students, postdocs and collaborators who enabled this research. Inevitably, a brief autobiographical review like this cannot be fully comprehensive, so sincere apologies to any of my great colleagues who are not explicitly mentioned herein. I salute you all as well!

Metatranscriptomic analyses of the oral microbiome

Although the composition of the oral human microbiome is now well studied, regulation of genes within oral microbial communities remains mostly uncharacterized. Current concepts of periodontal disease and caries highlight the importance of oral biofilms and their role as etiological agents of those diseases. Currently, there is increased interest in exploring and characterizing changes in the composition and gene-expression profiles of oral microbial communities. These efforts aim to identify changes in functional activities that could explain the transition from health to disease and the reason for the chronicity of those infections. It is now clear that the functions of distinct species within the subgingival microbiota are intimately intertwined with the rest of the microbial community. This point highlights the relevance of examining the expression profile of specific species within the subgingival microbiota in the case of periodontal disease or caries lesions, in the context of the other members of the biofilm in vivo. Metatranscriptomic analysis of the oral community is the starting point for identifying environmental signals that modulate the shift in metabolism of the community from commensal to dysbiotic. These studies give a snapshot of the expression patterns of microbial communities and also allow us to determine triggers to diseases. For example, in the case of caries, studies have unveiled a potential new pathway of sugar metabolism, namely the use of sorbitol as an additional source of carbon by Streptococcus mutans; and in the case of periodontal disease, high levels of extracellular potassium could be a signal of disease. Longitudinal studies are needed to identify the real markers of the initial stages of caries and periodontal disease. More information on the gene-expression profiles of the host, along with the patterns from the microbiome, will lead to a clearer understanding of the modulation of health and disease. This review presents a summary of these initial studies, which have opened the door to a new understanding of the dynamics of the oral community during the dysbiotic process in the oral cavity.

Traversing the "Omic" landscape of microbial halotolerance for key molecular processes and new insights

Post-2005, the biology of the salt afflicted habitats is predominantly studied employing high throughput "Omic" approaches comprising metagenomics, transcriptomics, metatranscriptomics, metabolomics, and proteomics. Such "Omic-based" studies have deciphered the unfamiliar details about microbial salt-stress biology. The MAGs (Metagenome-assembled genomes) of uncultured halophilic microbial lineages such as Nanohaloarchaea and haloalkaliphilic members within CPR (Candidate Phyla Radiation) have been reconstructed from diverse hypersaline habitats. The study of MAGs of such uncultured halophilic microbial lineages has unveiled the genomic basis of salt stress tolerance in "yet to culture" microbial lineages. Furthermore, functional metagenomic approaches have been used to decipher the novel genes from uncultured microbes and their possible role in microbial salt-stress tolerance. The present review focuses on the new insights into microbial salt-stress biology gained through different "Omic" approaches. This review also summarizes the key molecular processes that underlie microbial salt-stress response, and their role in microbial salt-stress tolerance has been confirmed at more than one "Omic" levels.

Integration of absolute multi-omics reveals dynamic protein-to-RNA ratios and metabolic interplay within mixed-domain microbiomes

While the field of microbiology has adapted to the study of complex microbiomes via modern meta-omics techniques, we have not updated our basic knowledge regarding the quantitative levels of DNA, RNA and protein molecules within a microbial cell, which ultimately control cellular function. Here we report the temporal measurements of absolute RNA and protein levels per gene within a mixed bacterial-archaeal consortium. Our analysis of this data reveals an absolute protein-to-RNA ratio of 10²–10⁴ for bacterial populations and 10³–10⁵ for an archaeon, which is more comparable to Eukaryotic representatives’ humans and yeast. Furthermore, we use the linearity between the metaproteome and metatranscriptome over time to identify core functional guilds, hence using a fundamental biological feature (i.e., RNA/protein levels) to highlight phenotypical complementarity. Our findings show that upgrading multi-omic toolkits with traditional absolute measurements unlocks the scaling of core biological questions to dynamic and complex microbiomes, creating a deeper insight into inter-organismal relationships that drive the greater community function.

Here, the authors perform a temporal multi-omic analysis of a minimalistic cellulose-degrading and methane-producing consortium at the strain level and estimate protein-to-RNA ratios and RNA-protein dynamics of the community simultaneously over time.

Diverse nitrogen cycling pathways across a marine oxygen gradient indicate nitrogen loss coupled to chemoautotrophic activity

Genetic markers and geochemical assays of microbial nitrogen cycling processes, including autotrophic and heterotrophic denitrification, anammox, ammonia oxidation, and nitrite oxidation, were examined across the oxycline, suboxic, and anoxic zones of the Cariaco Basin, Venezuela. Ammonia and nitrite oxidation genes were expressed through the entire gradient. Transcripts associated with autotrophic and heterotrophic denitrifiers were mostly confined to the suboxic zone and below but were also present in particles in the oxycline. Anammox genes and transcripts were detected over a narrow depth range near the bottom of the suboxic zone and coincided with secondary NO₂ ^- maxima and available NH₄ ⁺ . Dissolved inorganic nitrogen (DIN) amendment incubations and comparisons between our sampling campaigns suggested that denitrifier activity may be closely coupled with NO₃ ^- availability. Expression of denitrification genes at depths of high rates of chemoautotrophic carbon fixation and phylogenetic analyses of nitrogen cycling genes and transcripts indicated a diverse array of denitrifiers, including chemoautotrophs capable of using NO₃ ^- to oxidize reduced sulfur species. Thus, results suggest that the Cariaco Basin nitrogen cycle is influenced by autotrophic carbon cycling in addition to organic matter oxidation and anammox.

Diversity and structure of prokaryotic communities within organic and conventional farming systems in central highlands of Kenya

Management practices such as tillage, crop rotation, irrigation, organic and inorganic inputs application are known to influence diversity and function of soil microbial populations. In this study, we investigated the effect of conventional versus organic farming systems at low and high input levels on structure and diversity of prokaryotic microbial communities. Soil samples were collected from the ongoing long-term farming system comparison trials established in 2007 at Chuka and Thika in Kenya. Physicochemical parameters for each sample were analyzed. Total DNA and RNA amplicons of variable region (V4-V7) of the 16S rRNA gene were generated on an Illumina platform using the manufacturer's instructions. Diversity indices and statistical analysis were done using QIIME2 and R packages, respectively. A total of 29,778,886 high quality reads were obtained and assigned to 16,176 OTUs at 97% genetic distance across both 16S rDNA and 16S rRNA cDNA datasets. The results pointed out a histrionic difference in OTUs based on 16S rDNA and 16S rRNA cDNA. Precisely, while 16S rDNA clustered by site, 16S rRNA cDNA clustered by farming systems. In both sites and systems, dominant phylotypes were affiliated to phylum Actinobacteria, Proteobacteria and Acidobacteria. Conventional farming systems showed a higher species richness and diversity compared to organic farming systems, whilst 16S rRNA cDNA datasets were similar. Physiochemical factors were associated differently depending on rRNA and rDNA. Soil pH, electrical conductivity, organic carbon, nitrogen, potassium, aluminium, zinc, iron, boron and micro-aggregates showed a significant influence on the observed microbial diversity. The observed higher species diversity in the conventional farming systems can be attributed to the integration of synthetic and organic agricultural inputs. These results show that the type of inputs used in a farming system not only affect the soil chemistry but also the microbial population dynamics and eventually the functional roles of these microbes.

Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data

MOTIVATION

Technological advances in meta-transcriptomics have enabled a deeper understanding of the structure and function of microbial communities. 'Total RNA' meta-transcriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this approach is the reconstruction of full-length taxonomic marker genes such as the small subunit ribosomal RNA. However, current tools for this purpose are mainly targeted towards analysis of amplicon and metagenomic data and thus lack the ability to handle the massive and complex datasets typically resulting from total RNA experiments.

RESULTS

In this work, we introduce MetaRib, a new tool for reconstructing ribosomal gene sequences from total RNA meta-transcriptomic data. MetaRib is based on the popular rRNA assembly program EMIRGE, together with several improvements. We address the challenge posed by large complex datasets by integrating sub-assembly, dereplication and mapping in an iterative approach, with additional post-processing steps. We applied the method to both simulated and real-world datasets. Our results show that MetaRib can deal with larger datasets and recover more rRNA genes, which achieve around 60 times speedup and higher F1 score compared to EMIRGE in simulated datasets. In the real-world dataset, it shows similar trends but recovers more contigs compared with a previous analysis based on random sub-sampling, while enabling the comparison of individual contig abundances across samples for the first time.

AVAILABILITY AND IMPLEMENTATION

The source code of MetaRib is freely available at https://github.com/yxxue/MetaRib.

CONTACT

yaxin.xue@uib.no or Inge.Jonassen@uib.no.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A minimum set of regulators to thrive in the ocean

Marine cyanobacteria of the genus Prochlorococcus thrive in high cell numbers throughout the euphotic zones of the world's subtropical and tropical oligotrophic oceans, making them some of the most ecologically relevant photosynthetic microorganisms on Earth. The ecological success of these free-living phototrophs suggests that they are equipped with a regulatory system competent to address many different stress situations. However, Prochlorococcus genomes are compact and streamlined, with the majority encoding only five different sigma factors, five to six two-component systems and eight types of other transcriptional regulators. Here, we summarize the existing information about the functions of these protein regulators, about transcriptomic responses to defined stress conditions, and discuss the current knowledge about riboswitches, RNA-based regulation and the roles of certain metabolites as co-regulators. We focus on the best-studied isolate, Prochlorococcus MED4, but extend to other strains and ecotypes when appropriate, and we include some information gained from metagenomic and metatranscriptomic analyses.

Regulatory Noncoding Small RNAs Are Diverse and Abundant in an Extremophilic Microbial Community

Regulatory small RNAs (sRNAs) play large-scale and essential roles in many cellular processes across all domains of life. Microbial sRNAs have been extensively studied in model organisms, but very little is known about the dynamics of sRNA synthesis and their roles in the natural environment. In this study, we discovered hundreds of intergenic (itsRNAs) and antisense (asRNAs) sRNAs expressed in an extremophilic microbial community inhabiting halite nodules (salt rocks) in the Atacama Desert. For this, we built SnapT, a new sRNA annotation pipeline that can be applied to any microbial community. We found asRNAs with expression levels negatively correlated with that of their overlapping putative target and itsRNAs that were conserved and significantly differentially expressed between 2 sampling time points. We demonstrated that we could perform target prediction and correlate expression levels between sRNAs and predicted target mRNAs at the community level. Functions of putative mRNA targets reflected the environmental challenges members of the halite communities were subjected to, including osmotic adjustments to a major rain event and competition for nutrients.IMPORTANCE Microorganisms in the natural world are found in communities, communicating and interacting with each other; therefore, it is essential that microbial regulatory mechanisms, such as gene regulation affected by small RNAs (sRNAs), be investigated at the community level. This work demonstrates that metatranscriptomic field experiments can link environmental variation with changes in RNA pools and have the potential to provide new insights into environmental sensing and responses in natural microbial communities through noncoding RNA-mediated gene regulation.

Advances and Challenges in Metatranscriptomic Analysis

Sequencing-based analyses of microbiomes have traditionally focused on addressing the question of community membership and profiling taxonomic abundance through amplicon sequencing of 16 rRNA genes. More recently, shotgun metagenomics, which involves the random sequencing of all genomic content of a microbiome, has dominated this arena due to advancements in sequencing technology throughput and capability to profile genes as well as microbiome membership. While these methods have revealed a great number of insights into a wide variety of microbiomes, both of these approaches only describe the presence of organisms or genes, and not whether they are active members of the microbiome. To obtain deeper insights into how a microbial community responds over time to their changing environmental conditions, microbiome scientists are beginning to employ large-scale metatranscriptomics approaches. Here, we present a comprehensive review on computational metatranscriptomics approaches to study microbial community transcriptomes. We review the major advancements in this burgeoning field, compare strengths and weaknesses to other microbiome analysis methods, list available tools and workflows, and describe use cases and limitations of this method. We envision that this field will continue to grow exponentially, as will the scope of projects (e.g. longitudinal studies of community transcriptional responses to perturbations over time) and the resulting data. This review will provide a list of options for computational analysis of these data and will highlight areas in need of development.

Microbial life under ice: Metagenome diversity and in situ activity of Verrucomicrobia in seasonally ice-covered Lakes

Northern lakes are ice-covered for a large part of the year, yet our understanding of microbial diversity and activity during winter lags behind that of the ice-free period. In this study, we investigated under-ice diversity and metabolism of Verrucomicrobia in seasonally ice-covered lakes in temperate and boreal regions of Quebec, Canada using 16S rRNA sequencing, metagenomics and metatranscriptomics. Verrucomicrobia, particularly the V1, V3 and V4 subdivisions, were abundant during ice-covered periods. A diversity of Verrucomicrobia genomes were reconstructed from Quebec lake metagenomes. Several genomes were associated with the ice-covered period and were represented in winter metatranscriptomes, supporting the notion that Verrucomicrobia are metabolically active under ice. Verrucomicrobia transcriptome analysis revealed a range of metabolisms potentially occurring under ice, including carbohydrate degradation, glycolate utilization, scavenging of chlorophyll degradation products, and urea use. Genes for aerobic sulfur and hydrogen oxidation were expressed, suggesting chemolithotrophy may be an adaptation to conditions where labile carbon may be limited. The expression of genes for flagella biosynthesis and chemotaxis was detected, suggesting Verrucomicrobia may be actively sensing and responding to winter nutrient pulses, such as phytoplankton blooms. These results increase our understanding on the diversity and metabolic processes occurring under ice in northern lakes ecosystems.© 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation

Matching metagenomic and/or metatranscriptomic data, currently often under-used, can be useful reference for metaproteomic tandem mass spectra (MS/MS) data analysis. Here we developed a software pipeline for identification of peptides and proteins from metaproteomic MS/MS data using proteins derived from matching metagenomic (and metatranscriptomic) data as the search database, based on two novel approaches Graph2Pro (published) and Var2Pep (new). Graph2Pro retains and uses uncertainties of metagenome assembly for reference-based MS/MS data analysis. Var2Pep considers the variations found in metagenomic/metatranscriptomic sequencing reads that are not retained in the assemblies (contigs). The new software pipeline provides one stop application of both tools, and it supports the use of metagenome assembly from commonly used assemblers including MegaHit and metaSPAdes. When tested on two collections of multi-omic microbiome data sets, our pipeline significantly improved the identification rate of the metaproteomic MS/MS spectra by about two folds, comparing to conventional contig- or read-based approaches (the Var2Pep alone identified 5.6% to 24.1% more unique peptides, depending on the data set). We also showed that identified variant peptides are important for functional profiling of microbiomes. All results suggested that it is important to take into consideration of the assembly uncertainties and genomic variants to facilitate metaproteomic MS/MS data interpretation.

Large Noncoding RNAs in Bacteria

Bacterial noncoding RNA (ncRNA) classes longer than 200 nucleotides are rare but are responsible for performing some of the most fundamental tasks in living cells. RNAs such as 16S and 23S rRNA, group I and group II introns, RNase P ribozymes, transfer-messenger RNAs, and coenzyme B₁₂ riboswitches are diverse in structure and accomplish biochemical functions that rival the activities of proteins. Over the last decade, a number of new classes of large ncRNAs have been uncovered in bacteria. A total of 21 classes with no established functions have been identified through the use of bioinformatics search strategies. Based on precedents for bacterial large ncRNAs performing sophisticated functions, it seems likely that some of these structured ncRNAs also will prove to carry out complex functions. Thus, determining their roles will provide a better understanding of fundamental biological processes. A few studies have produced data that provide clues to the purposes of some of these recently found classes, but the true functions of most classes remain mysterious.

Metatranscriptome analysis of the intestinal microorganisms in Pardosa pseudoannulata in response to cadmium stress

Cadmium (Cd) generates a variety of physiological and ecological toxicity to spiders. However, little is known about the effects of Cd on symbiotic bacteria of spiders. Metatranscriptomics is increasing our knowledge of microorganisms in environment. To better understand the impact of Cd on the symbiotic bacteria of spiders, we generated and compared the metatranscriptomes of the intestinal microorganisms of Pardosa pseudoannulata with and without Cd stress. The community structure of intestinal microorganisms in P. pseudoannulata was composed of 4 kingdoms, namely bacteria, viruses, eukaryotes and archaea, including 46 phyla, 97 classes, 184 orders, 339 families, 470 genera, and 598 species. The abundance of eukaryotes, bacteria and viruses was decreased by 0.14%, 1.22% and 2.52% respectively while the archaea was increased by 99.16% when under Cd stress. We identified 1519 differentially expressed genes (DEGs), including 770 up-regulated and 749 down-regulated genes. The results of KEGG annotation revealed that the expression of genes that are involved in the carbon metabolism, protein and amino acid metabolism and synthesis, glucose metabolism, oxidative phosphorylation, and glutathione metabolism were influenced by Cd. Collectively, these findings showed that Cd significantly impacted the community structure and expression of related functional genes of intestinal microorganisms in P. pseudoannulata.

A Retrospective Review of Microbiological Methods Applied in Studies Following the Deepwater Horizon Oil Spill

The Deepwater Horizon (DWH) oil spill in the Gulf of Mexico in 2010 resulted in serious damage to local marine and coastal environments. In addition to the physical removal and chemical dispersion of spilled oil, biodegradation by indigenous microorganisms was regarded as the most effective way for cleaning up residual oil. Different microbiological methods were applied to investigate the changes and responses of bacterial communities after the DWH oil spills. By summarizing and analyzing these microbiological methods, giving recommendations and proposing some methods that have not been used, this review aims to provide constructive guidelines for microbiological studies after environmental disasters, especially those involving organic pollutants.

A compendium of multi-omic sequence information from the Saanich Inlet water column

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters.

Capturing the genetic makeup of the active microbiome in situ

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and that have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions.

Metagenome Analysis: a Powerful Tool for Enzyme Bioprospecting

Microorganisms are found throughout every corner of nature, and vast number of microorganisms is difficult to cultivate by classical microbiological techniques. The advent of metagenomics has revolutionized the field of microbial biotechnology. Metagenomics allow the recovery of genetic material directly from environmental niches without any cultivation techniques. Currently, metagenomic tools are widely employed as powerful tools to isolate and identify enzymes with novel biocatalytic activities from the uncultivable component of microbial communities. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body and ocean water. This review article describes the state-of-the-art techniques and tools in metagenomics and discusses the potential of metagenomic approaches for the bioprospecting of industrial enzymes from various environmental samples. We also describe the unusual novel enzymes discovered via metagenomic approaches and discuss the future prospects for metagenome technologies.

Natural resource landscapes of a marine bacterium reveal distinct fitness-determining genes across the genome

Heterotrophic bacteria exploit diverse microhabitats in the ocean, from particles to transient gradients. Yet the degree to which genes and pathways can contribute to an organism's fitness on such complex and variable natural resource landscapes remains poorly understood. Here, we determine the gene-by-gene fitness of a generalist saprophytic marine bacterium (Vibrio sp. F13 9CS106) on complex resources derived from its natural habitats - copepods (Apocyclops royi) and brown algae (Fucus vesiculosus) - and as reference substrates, glucose and the polysaccharide alginate, derived from brown algal cell walls. We find that resource complexity strongly buffers fitness costs of mutations, and that anabolic rather than catabolic pathways are more stringently required, likely due to functional redundancy in the latter. Moreover, while carbohydrate-rich algae requires several synthesis pathways, protein-rich Apocyclops does not, suggesting this ancestral habitat for Vibrios is a replete medium with metabolically redundant substrates. We also identify a candidate fitness trade-off for algal colonization: deletion of mshA increases mutant fitness. Our results demonstrate that gene fitness depends on habitat composition, and suggest that this generalist uses distinct resources in different natural habitats. The results further indicate that substrate replete conditions may lead to relatively relaxed selection on catabolic genes.

Temperature Impacts on Soil Microbial Communities and Potential Implications for the Biodegradation of Turfgrass Pesticides

Maintaining healthy turfgrass often results in the use of pesticides to manage weed, insect, and disease pests. To identify and understand potential nontarget impacts of pesticide usage while still maintaining attractive and functional turfgrass sites, it is important to improve our understanding of how pesticides degrade in various environments throughout the growing season. Temperature heavily influences microbial community composition and activity, and the microbial community often heavily influences pesticide degradation in soil ecosystems. Pesticide transformation products generated through the action of soil microbial degradation networks can vary in their toxicity, with the potential result that a pesticide applied in the spring at 10°C could produce different transformation products with different toxicological impacts than the sample pesticide applied to the same site at 22°C. The objective of this review is to examine past research surrounding soil microbial activity related to pesticide degradation and provide a foundation for how the soil microbiome interacts with pesticides and how seasonal temperature variations may influence those interactions.

Comparative evaluation of rRNA depletion procedures for the improved analysis of bacterial biofilm and mixed pathogen culture transcriptomes

Global transcriptomic analysis via RNA-seq is often hampered by the high abundance of ribosomal (r)RNA in bacterial cells. To remove rRNA and enrich coding sequences, subtractive hybridization procedures have become the approach of choice prior to RNA-seq, with their efficiency varying in a manner dependent on sample type and composition. Yet, despite an increasing number of RNA-seq studies, comparative evaluation of bacterial rRNA depletion methods has remained limited. Moreover, no such study has utilized RNA derived from bacterial biofilms, which have potentially higher rRNA:mRNA ratios and higher rRNA carryover during RNA-seq analysis. Presently, we evaluated the efficiency of three subtractive hybridization-based kits in depleting rRNA from samples derived from biofilm, as well as planktonic cells of the opportunistic human pathogen Pseudomonas aeruginosa. Our results indicated different rRNA removal efficiency for the three procedures, with the Ribo-Zero kit yielding the highest degree of rRNA depletion, which translated into enhanced enrichment of non-rRNA transcripts and increased depth of RNA-seq coverage. The results indicated that, in addition to improving RNA-seq sensitivity, efficient rRNA removal enhanced detection of low abundance transcripts via qPCR. Finally, we demonstrate that the Ribo-Zero kit also exhibited the highest efficiency when P. aeruginosa/Staphylococcus aureus co-culture RNA samples were tested.

A Graph-Centric Approach for Metagenome-Guided Peptide and Protein Identification in Metaproteomics

Metaproteomic studies adopt the common bottom-up proteomics approach to investigate the protein composition and the dynamics of protein expression in microbial communities. When matched metagenomic and/or metatranscriptomic data of the microbial communities are available, metaproteomic data analyses often employ a metagenome-guided approach, in which complete or fragmental protein-coding genes are first directly predicted from metagenomic (and/or metatranscriptomic) sequences or from their assemblies, and the resulting protein sequences are then used as the reference database for peptide/protein identification from MS/MS spectra. This approach is often limited because protein coding genes predicted from metagenomes are incomplete and fragmental. In this paper, we present a graph-centric approach to improving metagenome-guided peptide and protein identification in metaproteomics. Our method exploits the de Bruijn graph structure reported by metagenome assembly algorithms to generate a comprehensive database of protein sequences encoded in the community. We tested our method using several public metaproteomic datasets with matched metagenomic and metatranscriptomic sequencing data acquired from complex microbial communities in a biological wastewater treatment plant. The results showed that many more peptides and proteins can be identified when assembly graphs were utilized, improving the characterization of the proteins expressed in the microbial communities. The additional proteins we identified contribute to the characterization of important pathways such as those involved in degradation of chemical hazards. Our tools are released as open-source software on github at https://github.com/COL-IU/Graph2Pro.

In recent years, meta-omic (including metatranscriptomic and metaproteomic) techniques have been adopted as complementary approaches to metagenomic sequencing to study functional characteristics and dynamics of microbial communities, aiming at a holistic understanding of a community to respond to the changes in the environment. Currently, metaproteomic data are largely analyzed using the bioinformatics tools originally designed in bottom-up proteomics. In particular, recent metaproteomic studies employed a metagenome-guided approach, in which complete or fragmental protein-coding genes were first predicted from metagenomic sequences (i.e., contigs or scaffolds), acquired from the matched community samples, and predicted protein sequences were then used in peptide identification. A key challenge of this approach is that the protein coding genes predicted from assembled metagenomic contigs can be incomplete and fragmented due to the complexity of metagenomic samples and the short reads length in metagenomic sequencing. To address this issue, in this paper, we present a graph-centric approach that exploits the de bruijn graph structure reported by metagenome assembly algorithms to improve metagenome-guided peptide and protein identification in metaproteomics. We show that our method can identify much more peptides and proteins, improving the characterization of the proteins expressed in the microbial communities.

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

mdRNA-Seq analysis of marine microbial communities from the northern Red Sea

Metatranscriptomic differential RNA-Seq (mdRNA-Seq) identifies the suite of active transcriptional start sites at single-nucleotide resolution through enrichment of primary transcript 5′ ends. Here we analyzed the microbial community at 45 m depth at Station A in the northern Gulf of Aqaba, Red Sea, during 500 m deep mixing in February 2012 using mdRNA-Seq and a parallel classical RNA-Seq approach. We identified promoters active in situ for five different pico-planktonic genera (the SAR11 clade of Alphaproteobacteria, Synechococcus of Cyanobacteria, Euryarchaeota, Thaumarchaeota, and Micromonas as an example for picoeukaryotic algae), showing the applicability of this approach to highly diverse microbial communities. 16S rDNA quantification revealed that 24% of the analyzed community were group II marine Euryarchaeota in which we identified a highly abundant non-coding RNA, Tan1, and detected very high expression of genes encoding intrinsically disordered proteins, as well as enzymes for the synthesis of specific B vitamins, extracellular peptidases, carbohydrate-active enzymes, and transport systems. These results highlight previously unknown functions of Euryarchaeota with community-wide relevance. The complementation of metatranscriptomic studies with mdRNA-Seq provides substantial additional information regarding transcriptional start sites, promoter activities, and the identification of non-coding RNAs.

Small RNAs expressed during dimethylsulfoniopropionate degradation by a model marine bacterium

The fate of the sulfur moiety of dimethylsulfoniopropionate (DMSP) depends on the 'bacterial switch', a regulatory point between two metabolic pathways with different biogeochemical endpoints. Studies have focused on transcriptional patterns of known genes to determine physiological and environmental factors affecting this switch, but post-transcriptional regulation has been under-studied. Here we use a model bacterium containing both pathways to look for transcription of non-coding regulatory small RNAs (sRNAs) during DMSP metabolism. RNA-seq analysis of Ruegeria pomeroyi DSS-3 grown with DMSP, metabolic intermediates of DMSP degradation (MMPA or acetate), or methionine revealed 182 putative sRNAs, with 46 showing differential expression during growth on DMSP. A knockout mutant constructed for an upregulated sRNA had a phenotype that differed in its use of the two degradation pathways. Because transcription patterns of many differentially expressed sRNAs were not correlated with the transcription of their putative target gene, their effects on DMSP degradation would not be observable in the transcriptome. Overall, our results indicate that sRNAs are crucial but largely cryptic actors in regulating DMSP metabolism in this model marine bacterium and potentially other bacterial groups involved in the surface ocean sulfur cycle.

Genomic and Transcriptomic Resolution of Organic Matter Utilization Among Deep-Sea Bacteria in Guaymas Basin Hydrothermal Plumes

Microbial chemosynthesis within deep-sea hydrothermal vent plumes is a regionally important source of organic carbon to the deep ocean. Although chemolithoautotrophs within hydrothermal plumes have attracted much attention, a gap remains in understanding the fate of organic carbon produced via chemosynthesis. In the present study, we conducted shotgun metagenomic and metatranscriptomic sequencing on samples from deep-sea hydrothermal vent plumes and surrounding background seawaters at Guaymas Basin (GB) in the Gulf of California. De novo assembly of metagenomic reads and binning by tetranucleotide signatures using emergent self-organizing maps (ESOM) revealed 66 partial and nearly complete bacterial genomes. These bacterial genomes belong to 10 different phyla: Actinobacteria, Bacteroidetes, Chloroflexi, Deferribacteres, Firmicutes, Gemmatimonadetes, Nitrospirae, Planctomycetes, Proteobacteria, Verrucomicrobia. Although several major transcriptionally active bacterial groups (Methylococcaceae, Methylomicrobium, SUP05, and SAR324) displayed methanotrophic and chemolithoautotrophic metabolisms, most other bacterial groups contain genes encoding extracellular peptidases and carbohydrate metabolizing enzymes with significantly higher transcripts in the plume than in background, indicating they are involved in degrading organic carbon derived from hydrothermal chemosynthesis. Among the most abundant and active heterotrophic bacteria in deep-sea hydrothermal plumes are Planctomycetes, which accounted for seven genomes with distinct functional and transcriptional activities. The Gemmatimonadetes and Verrucomicrobia also had abundant transcripts involved in organic carbon utilization. These results extend our knowledge of heterotrophic metabolism of bacterial communities in deep-sea hydrothermal plumes.

Use of Metatranscriptomics in Microbiome Research

The human intestinal microbiome is a microbial ecosystem that expresses as many as 100 times more genes than the human host, thereby constituting an important component of the human holobiome, which contributes to multiple health and disease processes. As most commensal species are difficult or impossible to culture, genomic characterization of microbiome composition and function, under various environmental conditions, comprises a central tool in understanding its roles in health and disease. The first decade of microbiome research was mainly characterized by usage of DNA sequencing-based 16S rDNA and shotgun metagenome sequencing, allowing for the elucidation of microbial composition and genome structure. Technological advances in RNA-seq have recently provided us with an ability to gain insight into the genes that are actively expressed in complex bacterial communities, enabling the elucidation of the functional changes that dictate the microbiome functions at given contexts, its interactions with the host, and functional alterations that accompany the conversion of a healthy microbiome toward a disease-driving configuration. Here, we highlight some of the key metatranscriptomics strategies that are implemented to determine microbiota gene expression and its regulation and discuss the advantages and potential challenges associated with these approaches.

Experimental Identification of Small Non-Coding RNAs in the Model Marine Bacterium Ruegeria pomeroyi DSS-3

In oligotrophic ocean waters where bacteria are often subjected to chronic nutrient limitation, community transcriptome sequencing has pointed to the presence of highly abundant small RNAs (sRNAs). The role of sRNAs in regulating response to nutrient stress was investigated in a model heterotrophic marine bacterium Ruegeria pomeroyi grown in continuous culture under carbon (C) and nitrogen (N) limitation. RNAseq analysis identified 99 putative sRNAs. Sixty-nine were cis-encoded and located antisense to a presumed target gene. Thirty were trans-encoded and initial target prediction was performed computationally. The most prevalent functional roles of genes anti-sense to the cis-sRNAs were transport, cell-cell interactions, signal transduction, and transcriptional regulation. Most sRNAs were transcribed equally under both C and N limitation, and may be involved in a general stress response. However, 14 were regulated differentially between the C and N treatments and may respond to specific nutrient limitations. A network analysis of the predicted target genes of the R. pomeroyi cis-sRNAs indicated that they average fewer connections than typical protein-encoding genes, and appear to be more important in peripheral or niche-defining functions encoded in the pan genome.

Plankton networks driving carbon export in the oligotrophic ocean

The biological carbon pump is the process by which CO₂ is transformed to organic carbon via photosynthesis, exported through sinking particles, and finally sequestered in the deep ocean. While the intensity of the pump correlates with plankton community composition, the underlying ecosystem structure driving the process remains largely uncharacterised. Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve our understanding of carbon export in the oligotrophic ocean. We show that specific plankton communities, from the surface and deep chlorophyll maximum, correlate with carbon export at 150 m and highlight unexpected taxa such as Radiolaria, alveolate parasites, as well as Synechococcus and their phages, as lineages most strongly associated with carbon export in the subtropical, nutrient-depleted, oligotrophic ocean. Additionally, we show that the relative abundance of just a few bacterial and viral genes can predict most of the variability in carbon export in these regions.

Metatranscriptomic analyses of plant cell wall polysaccharide degradation by microorganisms in the cow rumen

The bovine rumen represents a highly specialized bioreactor where plant cell wall polysaccharides (PCWPs) are efficiently deconstructed via numerous enzymes produced by resident microorganisms. Although a large number of fibrolytic genes from rumen microorganisms have been identified, it remains unclear how they are expressed in a coordinated manner to efficiently degrade PCWPs. In this study, we performed a metatranscriptomic analysis of the rumen microbiomes of adult Holstein cows fed a fiber diet and obtained a total of 1,107,083 high-quality non-rRNA reads with an average length of 483 nucleotides. Transcripts encoding glycoside hydrolases (GHs) and carbohydrate binding modules (CBMs) accounted for 1% and 0.1% of the total non-rRNAs, respectively. The majority (98%) of the putative cellulases belonged to four GH families (i.e., GH5, GH9, GH45, and GH48) and were primarily synthesized by Ruminococcus and Fibrobacter. Notably, transcripts for GH48 cellobiohydrolases were relatively abundant compared to the abundance of transcripts for other cellulases. Two-thirds of the putative hemicellulases were of the GH10, GH11, and GH26 types and were produced by members of the genera Ruminococcus, Prevotella, and Fibrobacter. Most (82%) predicted oligosaccharide-degrading enzymes were GH1, GH2, GH3, and GH43 proteins and were from a diverse group of microorganisms. Transcripts for CBM10 and dockerin, key components of the cellulosome, were also relatively abundant. Our results provide metatranscriptomic evidence in support of the notion that members of the genera Ruminococcus, Fibrobacter, and Prevotella are predominant PCWP degraders and point to the significant contribution of GH48 cellobiohydrolases and cellulosome-like structures to efficient PCWP degradation in the cow rumen.

Single-cell technologies in environmental omics

Environmental studies are primarily done by culturing isolated microorganisms or by amplifying and sequencing conserved genes. Difficulties understanding the complexity of large numbers of various microorganisms in an environment led to the development of techniques to enrich specific microorganisms for upstream analysis, ultimately leading to single-cell isolation and analyses. We discuss the significance of single-cell technologies in omics studies with focus on metagenomics and metatranscriptomics. We propose that by reducing sample heterogeneity using single-cell genomics, metaomic studies can be simplified.