Efficient and robust RNA-seq process for cultured bacteria and complex community transcriptomes

MinION Sequencing of colorectal cancer tumour microbiomes-A comparison with amplicon-based and RNA-Sequencing

BACKGROUND

Recent evidence suggests a role for the gut microbiome in the development and progression of many diseases and many studies have been carried out to analyse the microbiome using a variety of methods. In this study, we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples.

METHODS

DNA and RNA were extracted from 11 colorectal tumour samples. 16S rRNA amplicon sequencing and MinION sequencing was carried out using genomic DNA, and RNA-Sequencing for meta-transcriptomic analysis. Non-human MinION and RNA-Sequencing reads, and 16S rRNA amplicon sequencing reads were taxonomically classified using a database built from available RefSeq bacterial and archaeal genomes and a k-mer based algorithm in Kraken2. Concordance between the three platforms at different taxonomic levels was tested on a per-sample basis using Spearman's rank correlation.

RESULTS

The average number of reads per sample using RNA-Sequencing was greater than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. Taxonomic assignment using 16S sequencing was less reliable beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect greater numbers of phyla and genera in the same samples, compared to 16S sequencing. Bacterial species associated with colorectal cancer, Fusobacterium nucleatum, Parvimonas micra, Bacteroides fragilis and Porphyromonas gingivalis, were detectable using MinION, RNA-Sequencing and 16S rRNA amplicon sequencing data.

CONCLUSIONS

Long-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a cost-effective tool for rapid microbiome sequencing in a clinical setting.

Scalable and cost-effective ribonuclease-based rRNA depletion for transcriptomics

Bacterial RNA sequencing (RNA-seq) is a powerful approach for quantitatively delineating the global transcriptional profiles of microbes in order to gain deeper understanding of their physiology and function. Cost-effective bacterial RNA-seq requires efficient physical removal of ribosomal RNA (rRNA), which otherwise dominates transcriptomic reads. However, current methods to effectively deplete rRNA of diverse non-model bacterial species are lacking. Here, we describe a probe and ribonuclease based strategy for bacterial rRNA removal. We implemented the method using either chemically synthesized oligonucleotides or amplicon-based single-stranded DNA probes and validated the technique on three novel gut microbiota isolates from three distinct phyla. We further showed that different probe sets can be used on closely related species. We provide a detailed methods protocol, probe sets for >5000 common microbes from RefSeq, and an online tool to generate custom probe libraries. This approach lays the groundwork for large-scale and cost-effective bacterial transcriptomics studies.

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.

Reference databases are essential for studies on host-microbiota interactions. Here, the authors present the construction of VIRGO, a human vaginal non-redundant gene catalog, which represents a comprehensive resource for taxonomic and functional profiling of vaginal microbiomes from metagenomic and metatranscriptomic datasets.

The Signal and the Noise: Characteristics of Antisense RNA in Complex Microbial Communities

This study systematically evaluated the global patterns of microbial antisense expression across various environments and provides a bird’s-eye view of general patterns observed across data sets, which can provide guidelines in our understanding of antisense expression as well as interpretation of metatranscriptomic data in general. This analysis highlights that in some environments, antisense expression from microbial communities can dominate over regular gene expression. We explored some potential drivers of antisense transcription, but more importantly, this study serves as a starting point, highlighting topics for future research and providing guidelines to include antisense expression in generic bioinformatic pipelines for metatranscriptomic data.

High-throughput sequencing has allowed unprecedented insight into the composition and function of complex microbial communities. With metatranscriptomics, it is possible to interrogate the transcriptomes of multiple organisms simultaneously to get an overview of the gene expression of the entire community. Studies have successfully used metatranscriptomics to identify and describe relationships between gene expression levels and community characteristics. However, metatranscriptomic data sets contain a rich suite of additional information that is just beginning to be explored. Here, we focus on antisense expression in metatranscriptomics, discuss the different computational strategies for handling it, and highlight the strengths but also potentially detrimental effects on downstream analysis and interpretation. We also analyzed the antisense transcriptomes of multiple genomes and metagenome-assembled genomes (MAGs) from five different data sets and found high variability in the levels of antisense transcription for individual species, which were consistent across samples. Importantly, we challenged the conceptual framework that antisense transcription is primarily the product of transcriptional noise and found mixed support, suggesting that the total observed antisense RNA in complex communities arises from the combined effect of unknown biological and technical factors. Antisense transcription can be highly informative, including technical details about data quality and novel insight into the biology of complex microbial communities.

IMPORTANCE This study systematically evaluated the global patterns of microbial antisense expression across various environments and provides a bird’s-eye view of general patterns observed across data sets, which can provide guidelines in our understanding of antisense expression as well as interpretation of metatranscriptomic data in general. This analysis highlights that in some environments, antisense expression from microbial communities can dominate over regular gene expression. We explored some potential drivers of antisense transcription, but more importantly, this study serves as a starting point, highlighting topics for future research and providing guidelines to include antisense expression in generic bioinformatic pipelines for metatranscriptomic data.

The era of 'omics' technologies in the study of microbiologically influenced corrosion

Efforts to elucidate the relationships between microorganisms and metal corrosion were mainly directed to understanding the formation of biofilm structures grown on corroded surfaces. The emergence of high throughput DNA sequencing techniques has helped in the description of microbial species involved directly and indirectly in the corrosion processes of alloys. Coupled with sequencing from environmental samples, other methodologies such as metatranscriptome, metaproteomics and metabolomics have allowed a new horizon to be opened on the understanding of the role of corrosive microbial biofilm. Several groups of bacteria and archaea were identified, showing the dominance of Proteobacteria in several samples analyzed and members of groups that previously received less attention, such as Firmicutes and Bacteroidetes. Our research also shows that metagenomic studies describe the presence of various Archaea domain thermophilic and methanogenic groups associated with metal corrosion. Thus, opening the prospect of describing new microbial groups as possible participants in this current global concern.

Development and Preliminary Validation of a Feasible Procedure for Isolating RNA from Fiber-Adherent Bacteria in Human Stool

BACKGROUND Intestinal bacterial communities are not homogenous throughout the gastrointestinal tract. Human research on the gut microbiome often neglects intra-intestinal variability by relying on a single measurement from stool samples. One source of complexity is the adherence to undigested, residual fiber. Currently, no procedure exists to extract RNA from distinct bacterial subpopulations in stool samples. MATERIAL AND METHODS A serial centrifugation procedure was developed in which bacterial RNA could be extracted from distinct stool-fractions - fiber-adherent and non-fiber-adherent bacteria. To test whether the separation procedure yielded distinct bacterial subpopulations, a set of RT-qPCR assays were developed for a fiber-adherent bacterial species, Bifidobacterium adolescentis, then a within-subject repeated-measures study was conducted with 3 human subjects undergoing 4 dietary regimens. At each timepoint, between-fraction differences in gene expression were evaluated. RESULTS The RNA isolation procedure was able to isolate intact RNA in 20 of 24 samples in the fiber-adherent fraction. PurB and sdh were identified as suitable reference genes for B. adolescentis RT-qPCR assays. When subjects were provided a high resistant starch diet, bacterial fractions exhibited different expression of the trp operon (p=0.031). CONCLUSIONS Our study provides human gut microbiome researchers a novel tool for evaluating functional characteristics of bacterial subpopulations in human stool. Moreover, these experiments provide modest support for the existence of a functionally unique fiber-adherent subpopulation of B. adolescentis. Until a more thorough evaluation of the adherent and non-adherent fraction can be performed, researchers should be cautious when generalizing functional data derived solely from unfractionated stool samples.

Amino acid based de Bruijn graph algorithm for identifying complete coding genes from metagenomic and metatranscriptomic short reads

Metagenomic studies, greatly promoted by the fast development of next-generation sequencing (NGS) technologies, uncover complex structures of microbial communities and their interactions with environment. As the majority of microbes lack information of genome sequences, it is essential to assemble prokaryotic genomes ab initio aiming to retrieve complete coding genes from various metabolic pathways. The complex nature of microbial composition and the burden of handling a vast amount of metagenomic data, bring great challenges to the development of effective and efficient bioinformatic tools. Here we present a protein assembler (MetaPA), based on de Bruijn graph searching on oligopeptide spaces and can be applied on both metagenomic and metatranscriptomic sequencing data. When public homologous protein sequences are involved to guide the assembling procedures, MetaPA assembles 85% of total proteins in complete sequences with high precision of 83% on real high-throughput sequencing datasets. Application of MetaPA on metatranscriptomic data successfully identifies the majority of actively transcribed genes validated in related studies. The results suggest that MetaPA has a good potential in both metagenomic and metatranscriptomic studies to characterize the composition and abundance of microbiota.

Spatiotemporal Organization of the E. coli Transcriptome: Translation Independence and Engagement in Regulation

RNA localization in eukaryotes is a mechanism to regulate transcripts fate. Conversely, bacterial transcripts were not assumed to be specifically localized. We previously demonstrated that E. coli mRNAs may localize to where their products localize in a translation-independent manner, thus challenging the transcription-translation coupling extent. However, the scope of RNA localization in bacteria remained unknown. Here, we report the distribution of the E. coli transcriptome between the membrane, cytoplasm, and poles by combining cell fractionation with deep-sequencing (Rloc-seq). Our results reveal asymmetric RNA distribution on a transcriptome-wide scale, significantly correlating with proteome localization and prevalence of translation-independent RNA localization. The poles are enriched with stress-related mRNAs and small RNAs, the latter becoming further enriched upon stress in an Hfq-dependent manner. Genome organization may play a role in localizing membrane protein-encoding transcripts. Our results show an unexpected level of intricacy in bacterial transcriptome organization and highlight the poles as hubs for regulation.

mRNA extraction of Xanthomonas fragariae in strawberry and validation of reference genes for the RT-qPCR for study of bacterial gene expression

This is the first study which describes a unique procedure of isolating of high-quality, intact RNA from strawberry leaves of Xanthomonas fragariae, three most suitable reference genes, crucial for the normalization of RT-qPCR data for this pathogen and accurate expression analysis of target genes. In our study, various mathematic algorithms: NormFinder geNorm, BestKeeper, the delta CT method, RefFinder were adopted for validation of most stable reference genes from nine candidate genes (ffh, glyA, gyrA, gyrB, proC, pykA, recA, rpoB, rpoD). The analyses allowing to select three most suitable pioneer reference genes, gyrB, ffh, and pykA, that we recommend for the normalization of RT-qPCR data and for the study of the expression of target genes in Xf. Moreover, their combination as references allowed for an accurate expression analysis and computation of the fold change of the flhF and iroN2 genes in Xf. These two genes are important for the success of the colonization of plant tissue and pathogenicity and sequences of primers designed to study these genes, are presented.

Bioinformatic analysis of bacteria and host cell dual RNA-sequencing experiments

Bacterial pathogens subvert host cells by manipulating cellular pathways for survival and replication; in turn, host cells respond to the invading pathogen through cascading changes in gene expression. Deciphering these complex temporal and spatial dynamics to identify novel bacterial virulence factors or host response pathways is crucial for improved diagnostics and therapeutics. Dual RNA sequencing (dRNA-Seq) has recently been developed to simultaneously capture host and bacterial transcriptomes from an infected cell. This approach builds on the high sensitivity and resolution of RNA sequencing technology and is applicable to any bacteria that interact with eukaryotic cells, encompassing parasitic, commensal or mutualistic lifestyles. Several laboratory protocols have been presented that outline the collection, extraction and sequencing of total RNA for dRNA-Seq experiments, but there is relatively little guidance available for the detailed bioinformatic analyses required. This protocol outlines a typical dRNA-Seq experiment, based on a Chlamydia trachomatis-infected host cell, with a detailed description of the necessary bioinformatic analyses with currently available software tools.

The Landscape of Circular RNA in Cancer

Circular RNAs (circRNAs) are an intriguing class of RNA due to their covalently closed structure, high stability, and implicated roles in gene regulation. Here, we used an exome capture RNA sequencing protocol to detect and characterize circRNAs across >2,000 cancer samples. When compared against Ribo-Zero and RNase R, capture sequencing significantly enhanced the enrichment of circRNAs and preserved accurate circular-to-linear ratios. Using capture sequencing, we built the most comprehensive catalog of circRNA species to date: MiOncoCirc, the first database to be composed primarily of circRNAs directly detected in tumor tissues. Using MiOncoCirc, we identified candidate circRNAs to serve as biomarkers for prostate cancer and were able to detect circRNAs in urine. We further detected a novel class of circular transcripts, termed read-through circRNAs, that involved exons originating from different genes. MiOncoCirc will serve as a valuable resource for the development of circRNAs as diagnostic or therapeutic targets across cancer types.

Comparative metagenomic and metatranscriptomic analyses reveal the breed effect on the rumen microbiome and its associations with feed efficiency in beef cattle

BACKGROUND

Microorganisms are responsible for fermentation within the rumen and have been reported to contribute to the variation in feed efficiency of cattle. However, to what extent the breed affects the rumen microbiome and its association with host feed efficiency is unknown. Here, rumen microbiomes of beef cattle (n = 48) from three breeds (Angus, Charolais, Kinsella composite hybrid) with high and low feed efficiency were explored using metagenomics and metatranscriptomics, aiming to identify differences between functional potentials and activities of same rumen microbiomes and to evaluate the effects of host breed and feed efficiency on the rumen microbiome.

RESULTS

Rumen metagenomes were more closely clustered together and thus more conserved among individuals than metatranscriptomes, suggesting that inter-individual functional variations at the RNA level were higher than those at the DNA level. However, while mRNA enrichment significantly increased the sequencing depth of mRNA and generated similar functional profiles to total RNA-based metatranscriptomics, it led to biased abundance estimation of several transcripts. We observed divergent rumen microbial composition (metatranscriptomic level) and functional potentials (metagenomic level) among three breeds, but differences in functional activity (metatranscriptomic level) were less apparent. Differential rumen microbial features (e.g., taxa, diversity indices, functional categories, and genes) were detected between cattle with high and low feed efficiency, and most of them were breed-specific.

CONCLUSIONS

Metatranscriptomes represent real-time functional activities of microbiomes and have the potential to better associate rumen microorganisms with host performances compared to metagenomics. As total RNA-based metatranscriptomics seem to avoid potential biases caused by mRNA enrichment and allow simultaneous use of rRNA for generation of compositional profiles, we suggest their use for linking the rumen microbiome with host phenotypes in future studies. However, if exploration of specific lowly expressed genes is desired, mRNA enrichment is recommended as it will enhance the resolution of mRNA. Finally, the differential microbial features observed between efficient and inefficient steers tended to be specific to breeds, suggesting that interactions between host breed genotype and the rumen microbiome contribute to the variations in feed efficiency observed. These breed-associated differences represent an opportunity to engineer specific rumen microbiomes through selective breeding of the hosts.

Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection

Nearly all infectious agents contain DNA or RNA genomes, making sequencing an attractive approach for pathogen detection. The cost of high-throughput or next-generation sequencing has been reduced by several orders of magnitude since its advent in 2004, and it has emerged as an enabling technological platform for the detection and taxonomic characterization of microorganisms in clinical samples from patients. This review focuses on the application of untargeted metagenomic next-generation sequencing to the clinical diagnosis of infectious diseases, particularly in areas in which conventional diagnostic approaches have limitations. The review covers ( a) next-generation sequencing technologies and common platforms, ( b) next-generation sequencing assay workflows in the clinical microbiology laboratory, ( c) bioinformatics analysis of metagenomic next-generation sequencing data, ( d) validation and use of metagenomic next-generation sequencing for diagnosing infectious diseases, and ( e) significant case reports and studies in this area. Next-generation sequencing is a new technology that has the promise to enhance our ability to diagnose, interrogate, and track infectious diseases.

Comparative evaluation of cDNA library construction approaches for RNA-Seq analysis from low RNA-content human specimens

With the emergence of RNA sequencing technologies, metatranscriptomic studies are rapidly gaining attention as they simultaneously provide insight into gene expression profiles and therefore disease association pathways of microbial pathogens and their hosts. This approach, therefore, holds promise for applicability in infectious disease diagnostics. A challenge of this approach in the clinical setting is the low amount and quality of RNA, especially microbial RNA in most clinically-infected specimens. Here, we compared two commercially available stranded cDNA library preparation kits, the NuGEN Ovation SoLo RNA-Seq System and the Illumina TruSeq Stranded Total RNA, using RNA extracted from synovial and sonicate fluids from a subject with periprosthetic joint infection. The Ovation SoLo RNA-Seq System provided more useful transcriptomic data for the infecting bacterium, whereas the TruSeq Stranded Total RNA kit provided more useful human transcriptomic data.

Fecal Host Transcriptomics for Non-Invasive Human Mucosal Immune Profiling: Proof of Concept in Clostridium Difficile Infection

Background:

Host factors play an important role in pathogenesis and disease outcome in Clostridium difficile infection (CDI), and characterization of these responses could uncover potential host biomarkers to complement existing microbe-based diagnostics.

Methods:

We extracted RNA from fecal samples of patients with CDI and profiled human mRNA using amplicon-based next-generation sequencing (NGS). We compared the fecal host mRNA transcript expression profiles of patients with CDI to controls with non-CDI diarrhea.

Results:

We found that the ratio of human actin gamma 1 (ACTG1) to 16S ribosomal RNA (rRNA) was highly correlated with NGS quality as measured by percentage of reads on target. Patients with CDI could be differentiated from those with non-CDI diarrhea based on their fecal mRNA expression profiles using principal component analysis. Among the most differentially expressed genes were ones related to immune response (IL23A, IL34) and actin-cytoskeleton function (TNNT1, MYL4, SMTN, MYBPC3, all adjusted P-values < 1 x 10^-3).

Conclusions:

In this proof-of-concept study, we used host fecal transcriptomics for non-invasive profiling of the mucosal immune response in CDI. We identified differentially expressed genes with biological plausibility based on animal and cell culture models. This demonstrates the potential of fecal transcriptomics to uncover host-based biomarkers for enteric infections.

Concerted Metabolic Shifts Give New Insights Into the Syntrophic Mechanism Between Propionate-Fermenting Pelotomaculum thermopropionicum and Hydrogenotrophic Methanocella conradii

Microbial syntrophy is a thermodynamically-based cooperation between microbial partners that share the small amounts of free energy for anaerobic growth. To gain insights into the mechanism by which syntrophic microorganisms coordinate their metabolism, we constructed cocultures of propionate-oxidizing Pelotomaculum thermopropionicum and hydrogenotrophic Methanocella conradii and compared them to monocultures. Transcriptome analysis was performed on these cultures using strand-specific mRNA sequencing (RNA-Seq). The results showed that in coculture both P. thermopropionicum and M. conradii significantly upregulated the expression of genes involved in catabolism but downregulated those for anabolic biosynthesis. Specifically, genes coding for the methylmalonyl-CoA pathway in P. thermopropionicum and key genes for methanogenesis in M. conradii were substantially upregulated in coculture compared to monoculture. The putative flavin-based electron bifurcation/confurcation systems in both organisms were also upregulated in coculture. Formate dehydrogenase encoding genes in both organisms were markedly upregulated, indicating that formate was produced and utilized by P. thermopropionicum and M. conradii, respectively. The inhibition of syntrophic activity by formate and 2-bromoethanesulphonate (2-BES) but not H₂/CO₂ also suggested that formate production was used by P. thermopropionicum for the recycling of intracellular redox mediators. Finally, flagellum-induced signal transduction and amino acids exchange was upregulated for syntrophic interactions. Together, our study suggests that syntrophic organisms employ multiple strategies including global metabolic shift, utilization of electron bifurcation/confurcation and employing formate as an alternate electron carrier to optimize their metabolisms for syntrophic growth.

Heterotroph Interactions Alter Prochlorococcus Transcriptome Dynamics during Extended Periods of Darkness

Microbes evolve within complex ecological communities where biotic interactions impact both individual cells and the environment as a whole. Here we examine how cellular regulation in the marine cyanobacterium Prochlorococcus is influenced by a heterotrophic bacterium, Alteromonas macleodii, under different light conditions. We monitored the transcriptome of Prochlorococcus, grown either alone or in coculture, across a diel light:dark cycle and under the stress of extended darkness-a condition that cells would experience when mixed below the ocean's euphotic zone. More Prochlorococcus transcripts exhibited 24-h periodic oscillations in coculture than in pure culture, both over the normal diel cycle and after the shift to extended darkness. This demonstrates that biotic interactions, and not just light, can affect timing mechanisms in Prochlorococcus, which lacks a self-sustaining circadian oscillator. The transcriptomes of replicate pure cultures of Prochlorococcus lost their synchrony within 5 h of extended darkness and reflected changes in stress responses and metabolic functions consistent with growth cessation. In contrast, when grown with Alteromonas, replicate Prochlorococcus transcriptomes tracked each other for at least 13 h in the dark and showed signs of continued biosynthetic and metabolic activity. The transcriptome patterns suggest that the heterotroph may be providing energy or essential biosynthetic substrates to Prochlorococcus in the form of organic compounds, sustaining this autotroph when it is deprived of solar energy. Our findings reveal conditions where mixotrophic metabolism may benefit marine cyanobacteria and highlight new impacts of community interactions on basic Prochlorococcus cellular processes. IMPORTANCEProchlorococcus is the most abundant photosynthetic organism on the planet. These cells play a central role in the physiology of surrounding heterotrophs by supplying them with fixed organic carbon. It is becoming increasingly clear, however, that interactions with heterotrophs can affect autotrophs as well. Here we show that such interactions have a marked impact on the response of Prochlorococcus to the stress of extended periods of darkness, as reflected in transcriptional dynamics. These data suggest that diel transcriptional rhythms within Prochlorococcus, which are generally considered to be strictly under the control of light quantity, quality, and timing, can also be influenced by biotic interactions. Together, these findings provide new insights into the importance of microbial interactions on Prochlorococcus physiology and reveal conditions where heterotroph-derived compounds may support autotrophs-contrary to the canonical autotroph-to-heterotroph trophic paradigm.

A global regulatory system links virulence and antibiotic resistance to envelope homeostasis in Acinetobacter baumannii

The nosocomial pathogen Acinetobacter baumannii is a significant threat due to its ability to cause infections refractory to a broad range of antibiotic treatments. We show here that a highly conserved sensory-transduction system, BfmRS, mediates the coordinate development of both enhanced virulence and resistance in this microorganism. Hyperactive alleles of BfmRS conferred increased protection from serum complement killing and allowed lethal systemic disease in mice. BfmRS also augmented resistance and tolerance against an expansive set of antibiotics, including dramatic protection from β-lactam toxicity. Through transcriptome profiling, we showed that BfmRS governs these phenotypes through global transcriptional regulation of a post-exponential-phase-like program of gene expression, a key feature of which is modulation of envelope biogenesis and defense pathways. BfmRS activity defended against cell-wall lesions through both β-lactamase-dependent and -independent mechanisms, with the latter being connected to control of lytic transglycosylase production and proper coordination of morphogenesis and division. In addition, hypersensitivity of bfmRS knockouts could be suppressed by unlinked mutations restoring a short, rod cell morphology, indicating that regulation of drug resistance, pathogenicity, and envelope morphogenesis are intimately linked by this central regulatory system in A. baumannii. This work demonstrates that BfmRS controls a global regulatory network coupling cellular physiology to the ability to cause invasive, drug-resistant infections.

Infections with the hospital-acquired bacterium Acinetobacter baumannii are highly difficult to treat. The pathogen has evolved multiple lines of defense against antimicrobial stress, including a barrier-forming cell envelope as well as control systems that respond to antimicrobial stresses by enhancing antibiotic resistance and virulence. Here, we uncovered the role of a key stress-response system, BfmRS, in controlling the transition of A. baumannii to a state of heightened resistance and virulence. We show that BfmRS enhances pathogenicity in mammalian hosts, and augments the ability to grow in the presence of diverse antibiotics and tolerate transient, high-level antibiotic exposures. Connected to these effects is the ability of BfmRS to globally reprogram gene expression and control multiple pathways that build, protect, and shape the cell envelope. Moreover, we determined that resistance-enhancing mutations bypassing the need for BfmRS also modulate envelope- and morphology-associated pathways, further linking control of physiology with resistance in A. baumannii. This work uncovers a global control circuit that shifts cellular physiology in ways that promote hospital-associated disease, and points to inhibition of this circuit as a potential strategy for disarming the pathogen.

Characterization of Human Salivary Extracellular RNA by Next-generation Sequencing

BACKGROUND

It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential.

METHODS

We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated.

RESULTS

The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%).

CONCLUSIONS

Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies.

RUMINANT NUTRITION SYMPOSIUM: Tiny but mighty: the role of the rumen microbes in livestock production

The microbes inhabiting the rumen convert low-quality, fibrous, plant material into useable energy for the host ruminant. Consisting of bacteria, protozoa, fungi, archaea, and viruses, the rumen microbiome composes a sophisticated network of symbiosis essential to maintenance, immune function, and overall production efficiency of the host ruminant. Robert Hungate laid the foundation for rumen microbiome research. This area of research has expanded immensely with advances in methodology and technology that have not only improved the ability to describe microbes in taxonomic and density terms but also characterize populations of microbes, their functions, and their interactions with each other and the host. The interplay between the rumen microbiome and the host contributes to variation in many phenotypic traits expressed by the host animal. A better understanding of how the rumen microbiome influences host health and performance may lead to novel strategies and treatments for trait improvement. Furthermore, elucidation of maternal, genetic, and environmental factors that influence rumen microbiome establishment and development may provide novel insights into possible mechanisms for manipulating the rumen microbial composition to enhance long-term host health and performance. The potential for these tiny but mighty rumen microbes to play a role in improving livestock production is appreciated despite being relatively obscure.

RNA Sequencing and Analysis in Microorganisms for Metabolic Network Reconstruction

There is a strict interplay between metabolic networks and transcriptional regulation in bacteria; indeed, the transcriptome regulation, affecting the expression of large gene sets, can be used to predict the likely "on" or "off" state of metabolic genes as a function of environmental factors. Up to date, many bacterial transcriptomes have been studied by RNAseq, hundreds of experiments have been performed, and Giga bases of sequences have been produced. All this transcriptional information could potentially be integrated into metabolic networks in order to obtain a more comprehensive view of their regulation and to increase their prediction power.To get high-quality transcriptomic data, to be integrated into metabolic networks, it is paramount to clearly know how to produce highly informative RNA sequencing libraries and how to manage RNA sequencing data.In this chapter, we will get across the main steps of an RNAseq experiment: from removal of ribosomal RNAs, to strand-specific library preparation, till data analysis and integration. We will try to share our experience and know-how, to give you a precise protocol to follow, and some useful recommendations or tips and tricks to adopt in order to go straightforward toward a successful RNAseq experiment.

Experimental design and quantitative analysis of microbial community multiomics

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

A Laboratory Methodology for Dual RNA-Sequencing of Bacteria and their Host Cells In Vitro

Dual RNA-Sequencing leverages established next-generation sequencing (NGS)-enabled RNA-Seq approaches to measure genome-wide transcriptional changes of both an infecting bacteria and host cells. By simultaneously investigating both organisms from the same biological sample, dual RNA-Seq can provide unique insight into bacterial infection processes and reciprocal host responses at once. However, the difficulties involved in handling both prokaryotic and eukaryotic material require distinct, optimized procedures. We previously developed and applied dual RNA-Seq to measure prokaryotic and eukaryotic expression profiles of human cells infected with bacteria, using in vitro Chlamydia-infected epithelial cells as proof of principle. Here we provide a detailed laboratory protocol for in vitro dual RNA-Seq that is readily adaptable to any host-bacteria system of interest.

Optimization of a metatranscriptomic approach to study the lignocellulolytic potential of the higher termite gut microbiome

Background

Thanks to specific adaptations developed over millions of years, the efficiency of lignin, cellulose and hemicellulose decomposition of higher termite symbiotic system exceeds that of many other lignocellulose utilizing environments. Especially, the examination of its symbiotic microbes should reveal interesting carbohydrate-active enzymes, which are of primary interest for the industry. Previous metatranscriptomic reports (high-throughput mRNA sequencing) highlight the high representation and overexpression of cellulose and hemicelluloses degrading genes in the termite hindgut digestomes, indicating the potential of this technology in search for new enzymes. Nevertheless, several factors associated with the material sampling and library preparation steps make the metatranscriptomic studies of termite gut prokaryotic symbionts challenging.

Methods

In this study, we first examined the influence of the sampling strategy, including the whole termite gut and luminal fluid, on the diversity and the metatranscriptomic profiles of the higher termite gut symbiotic bacteria. Secondly, we evaluated different commercially available kits combined in two library preparative pipelines for the best bacterial mRNA enrichment strategy.

Results

We showed that the sampling strategy did not significantly impact the generated results, both in terms of the representation of the microbes and their transcriptomic profiles. Nevertheless collecting luminal fluid reduces the co-amplification of unwanted RNA species of host origin. Furthermore, for the four studied higher termite species, the library preparative pipeline employing Ribo-Zero Gold rRNA Removal Kit “Epidemiology” in combination with Poly(A) Purist MAG kit resulted in a more efficient rRNA and poly-A-mRNAdepletion (up to 98.44% rRNA removed) than the pipeline utilizing MICROBExpress and MICROBEnrich kits. High correlation of both Ribo-Zero and MICROBExpresse depleted gene expression profiles with total non-depleted RNA-seq data has been shown for all studied samples, indicating no systematic skewing of the studied pipelines.

Conclusions

We have extensively evaluated the impact of the sampling strategy and library preparation steps on the metatranscriptomic profiles of the higher termite gut symbiotic bacteria. The presented methodological approach has great potential to enhance metatranscriptomic studies of the higher termite intestinal flora and to unravel novel carbohydrate-active enzymes.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4076-9) contains supplementary material, which is available to authorized users.

Gut Microbiota, Inflammation, and Colorectal Cancer

Colorectal cancer is the second-leading cause of cancer-related deaths in the United States and fourth-leading cause of cancer-related deaths worldwide. While cancer is largely considered to be a disease of genetic and environmental factors, increasing evidence has demonstrated a role for the microbiota (the microorganisms associated with the human body) in shaping inflammatory environments and promoting tumor growth and spread. Herein, we discuss both human data from meta'omics analyses and data from mechanistic studies in cell culture and animal models that support specific bacterial agents as potentiators of tumorigenesis-including Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, and colibactin-producing Escherichia coli. Further, we consider how microbes can be used in diagnosing colorectal cancer and manipulating the tumor environment to encourage better patient outcomes in response to immunotherapy treatments.

Deep sequencing approaches for the analysis of prokaryotic transcriptional boundaries and dynamics

The identification of the protein-coding regions of a genome is straightforward due to the universality of start and stop codons. However, the boundaries of the transcribed regions, conditional operon structures, non-coding RNAs and the dynamics of transcription, such as pausing of elongation, are non-trivial to identify, even in the comparatively simple genomes of prokaryotes. Traditional methods for the study of these areas, such as tiling arrays, are noisy, labour-intensive and lack the resolution required for densely-packed bacterial genomes. Recently, deep sequencing has become increasingly popular for the study of the transcriptome due to its lower costs, higher accuracy and single nucleotide resolution. These methods have revolutionised our understanding of prokaryotic transcriptional dynamics. Here, we review the deep sequencing and data analysis techniques that are available for the study of transcription in prokaryotes, and discuss the bioinformatic considerations of these analyses.

Low-cell-number, single-tube amplification (STA) of total RNA revealed transcriptome changes from pluripotency to endothelium

Background

In addition to messenger RNA (mRNA), noncoding RNAs (ncRNAs) are essential components in cellular machineries for translation and splicing. Besides their housekeeping functions, ncRNAs are involved in cell type-specific regulation of translation, mRNA stability, genome structure, and accessibility. To have a comprehensive understanding of the identities and functions of different cell types, a method to comprehensively quantify both mRNA and ncRNA in a sensitive manner is highly desirable.

Methods

Here we tried to develop a system capable of concurrently profiling both mRNA and ncRNA by polyadenylating RNA in samples before reverse transcription. The sensitivity of the system was maximized by avoiding purification from cell lysis to amplified cDNA and by optimizing the buffer conditions. The single-tube amplification (STA) system was applied to single to 100 cells of 293T cells, human pluripotent stem cells (hPSCs) and their differentiated endothelial progenies to validate its quantitative power and sensitivity by qPCR and high-throughput sequencing.

Results

Using microRNA (miRNA) as an example, we showed that complementary DNA (cDNA) from ncRNAs could be amplified and specifically detected from a few cells within a single tube. The sensitivity of the system was maximized by avoiding purification from cell lysis to amplified cDNA and by optimizing the buffer conditions. With 100 human embryonic stem cells (hESCs) and their differentiated endothelial cells as input for high-throughput sequencing, the single-tube amplification (STA) system revealed both well-known and other miRNAs selectively enriched in each cell type. The selective enrichment of the miRNAs was further verified by qPCR with 293FT cells and a human induced pluripotent stem cell (hiPSC) line. In addition, the detection of other non-miRNA transcripts indicated that the STA target was not limited to miRNA, but extended to other ncRNAs and mRNAs as well. Finally, the STA system was capable of detecting miRNA and mRNA expression down to single cells, albeit with some loss of sensitivity and power.

Conclusions

Overall, STA offered a simple and sensitive way to concurrently quantify both mRNA and ncRNA expression in low-cell-number samples for both qPCR and high-throughput sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-017-0359-5) contains supplementary material, which is available to authorized users.

Expression of eukaryotic-like protein in the microbiome of sponges

Eukaryotic-like proteins (ELPs) are classes of proteins that are found in prokaryotes, but have a likely evolutionary origin in eukaryotes. ELPs have been postulated to mediate host-microbiome interactions. Recent work has discovered that prokaryotic symbionts of sponges contain abundant and diverse genes for ELPs, which could modulate interactions with their filter-feeding and phagocytic host. However, the extent to which these ELP genes are actually used and expressed by the symbionts is poorly understood. Here, we use metatranscriptomics to investigate ELP expression in the microbiomes of three different sponges (Cymbastella concentrica, Scopalina sp. and Tedania anhelens). We developed a workflow with optimized rRNA removal and in silico subtraction of host sequences to obtain a reliable symbiont metatranscriptome. This showed that between 1.3% and 2.3% of all symbiont transcripts contain genes for ELPs. Two classes of ELPs (cadherin and tetratricopeptide repeats) were abundantly expressed in the C. concentrica and Scopalina sp. microbiomes, while ankyrin repeat ELPs were predominant in the T. anhelens metatranscriptome. Comparison with transcripts that do not encode ELPs indicated a constitutive expression of ELPs across a range of bacterial and archaeal symbionts. Expressed ELPs also contained domains involved in protein secretion and/or were co-expressed with proteins involved in extracellular transport. This suggests these ELPs are likely exported, which could allow for direct interaction with the sponge. Our study shows that ELP genes in sponge symbionts represent actively expressed functions that could mediate molecular interaction between symbiosis partners.

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.

Studying Vertical Microbiome Transmission from Mothers to Infants by Strain-Level Metagenomic Profiling

The gut microbiome becomes shaped in the first days of life and continues to increase its diversity during the first months. Links between the configuration of the infant gut microbiome and infant health are being shown, but a comprehensive strain-level assessment of microbes vertically transmitted from mother to infant is still missing. We collected fecal and breast milk samples from multiple mother-infant pairs during the first year of life and applied shotgun metagenomic sequencing followed by computational strain-level profiling. We observed that several specific strains, including those of Bifidobacterium bifidum, Coprococcus comes, and Ruminococcus bromii, were present in samples from the same mother-infant pair, while being clearly distinct from those carried by other pairs, which is indicative of vertical transmission. We further applied metatranscriptomics to study the in vivo gene expression of vertically transmitted microbes and found that transmitted strains of Bacteroides and Bifidobacterium species were transcriptionally active in the guts of both adult and infant. By combining longitudinal microbiome sampling and newly developed computational tools for strain-level microbiome analysis, we demonstrated that it is possible to track the vertical transmission of microbial strains from mother to infants and to characterize their transcriptional activity. Our work provides the foundation for larger-scale surveys to identify the routes of vertical microbial transmission and its influence on postinfancy microbiome development. IMPORTANCE Early infant exposure is important in the acquisition and ultimate development of a healthy infant microbiome. There is increasing support for the idea that the maternal microbial reservoir is a key route of microbial transmission, and yet much is inferred from the observation of shared species in mother and infant. The presence of common species, per se, does not necessarily equate to vertical transmission, as species exhibit considerable strain heterogeneity. It is therefore imperative to assess whether shared microbes belong to the same genetic variant (i.e., strain) to support the hypothesis of vertical transmission. Here we demonstrate the potential of shotgun metagenomics and strain-level profiling to identify vertical transmission events. Combining these data with metatranscriptomics, we show that it is possible not only to identify and track the fate of microbes in the early infant microbiome but also to investigate the actively transcribing members of the community. These approaches will ultimately provide important insights into the acquisition, development, and community dynamics of the infant microbiome.

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.

Microbial Ecology: Where are we now?

Conventional microbiological methods have been readily taken over by newer molecular techniques due to the ease of use, reproducibility, sensitivity and speed of working with nucleic acids. These tools allow high throughput analysis of complex and diverse microbial communities, such as those in soil, freshwater, saltwater, or the microbiota living in collaboration with a host organism (plant, mouse, human, etc). For instance, these methods have been robustly used for characterizing the plant (rhizosphere), animal and human microbiome specifically the complex intestinal microbiota. The human body has been referred to as the Superorganism since microbial genes are more numerous than the number of human genes and are essential to the health of the host. In this review we provide an overview of the Next Generation tools currently available to study microbial ecology, along with their limitations and advantages.

A Sample-to-Sequence Protocol for Genus Targeted Transcriptomic Profiling: Application to Marine Synechococcus

Recent studies using whole community metagenomic and metatranscriptomic approaches are revealing important new insights into the functional potential and activity of natural marine microbial communities. Here, we complement these approaches by describing a complete ocean sample-to-sequence protocol, specifically designed to target a single bacterial genus for purposes of both DNA and RNA profiling using fluorescence activated cell sorting (FACS). The importance of defining and understanding the effects of a sampling protocol are critical if we are to gain meaningful data from environmental surveys. Rigorous pipeline trials with a cultured isolate, Synechococcus sp. BL107 demonstrate that water filtration has a well-defined but limited impact on the transcriptomic profile of this organism, whilst sample storage and multiple rounds of cell sorting have almost no effect on the resulting RNA sequence profile. Attractively, the means to replicate the sampling strategy is within the budget and expertise of most researchers.

Gene Expression Patterns during Light and Dark Infection of Prochlorococcus by Cyanophage

Cyanophage infecting the marine cyanobacteria Prochlorococcus and Synechococcus require light and host photosystem activity for optimal reproduction. Many cyanophages encode multiple photosynthetic electron transport (PET) proteins, which are presumed to maintain electron flow and produce ATP and NADPH for nucleotide biosynthesis and phage genome replication. However, evidence suggests phage augment NADPH production via the pentose phosphate pathway (PPP), thus calling into question the need for NADPH production by PET. Genes implicated in cyclic PET have since been identified in cyanophage genomes. It remains an open question which mode of PET, cyclic or linear, predominates in infected cyanobacteria, and thus whether the balance is towards producing ATP or NADPH. We sequenced transcriptomes of a cyanophage (P-HM2) and its host (Prochlorococcus MED4) throughout infection in the light or in the dark, and analyzed these data in the context of phage replication and metabolite measurements. Infection was robust in the light, but phage were not produced in the dark. Host gene transcripts encoding high-light inducible proteins and two terminal oxidases (plastoquinol terminal oxidase and cytochrome c oxidase)-implicated in protecting the photosynthetic membrane from light stress-were the most enriched in light but not dark infection. Among the most diminished transcripts in both light and dark infection was ferredoxin-NADP+ reductase (FNR), which uses the electron acceptor NADP+ to generate NADPH in linear photosynthesis. The phage gene for CP12, which putatively inhibits the Calvin cycle enzyme that receives NADPH from FNR, was highly expressed in light infection. Therefore, both PET production of NADPH and its consumption by carbon fixation are putatively repressed during phage infection in light. Transcriptomic evidence is thus consistent with cyclic photophosphorylation using oxygen as the terminal electron acceptor as the dominant mode of PET under infection, with ATP from PET and NADPH from the PPP producing the energy and reducing equivalents for phage nucleotide biosynthesis and replication.

Strand-specific RNA-seq analysis of the Lactobacillus delbrueckii subsp. bulgaricus transcriptome

Lactobacillus delbrueckii subsp. bulgaricus 2038 (Lb. bulgaricus 2038) is an industrial bacterium that is used as a starter for dairy products. We proposed several hypotheses concerning its industrial features previously. Here, we utilized RNA-seq to explore the transcriptome of Lb. bulgaricus 2038 from four different growth phases under whey conditions. The most abundantly expressed genes in the four stages were mainly involved in translation (for the logarithmic stage), glycolysis (for control/lag stages), lactic acid production (all the four stages), and 10-formyl tetrahydrofolate production (for the stationary stage). The high expression of genes like d-lactate dehydrogenase was thought as a result of energy production, and consistent expression of EPS synthesis genes, the restriction-modification (RM) system and the CRISPR/Cas system were validated for explaining the advantage of this strain in yoghurt production. Several postulations, like NADPH production through GapN bypass, converting aspartate into carbon-skeleton intermediates, and formate production through degrading GTP, were proved not working under these culture conditions. The high expression of helicase genes and co-expressed amino acids/oligopeptides transporting proteins indicated that the helicase might mediate the strain obtaining nitrogen source from the environment. The transport system of Lb. bulgaricus 2038 was found to be regulated by antisense RNA, hinting the potential application of non-coding RNA in regulating lactic acid bacteria (LAB) gene expression. Our study has primarily uncovered Lb. bulgaricus 2038 transcriptome, which could gain a better understanding of the regulation system in Lb. bulgaricus and promote its industrial application.

SAMSA: a comprehensive metatranscriptome analysis pipeline

BACKGROUND

Although metatranscriptomics-the study of diverse microbial population activity based on RNA-seq data-is rapidly growing in popularity, there are limited options for biologists to analyze this type of data. Current approaches for processing metatranscriptomes rely on restricted databases and a dedicated computing cluster, or metagenome-based approaches that have not been fully evaluated for processing metatranscriptomic datasets. We created a new bioinformatics pipeline, designed specifically for metatranscriptome dataset analysis, which runs in conjunction with Metagenome-RAST (MG-RAST) servers. Designed for use by researchers with relatively little bioinformatics experience, SAMSA offers a breakdown of metatranscriptome transcription activity levels by organism or transcript function, and is fully open source. We used this new tool to evaluate best practices for sequencing stool metatranscriptomes.

RESULTS

Working with the MG-RAST annotation server, we constructed the Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) software package, a complete pipeline for the analysis of gut microbiome data. SAMSA can summarize and evaluate raw annotation results, identifying abundant species and significant functional differences between metatranscriptomes. Using pilot data and simulated subsets, we determined experimental requirements for fecal gut metatranscriptomes. Sequences need to be either long reads (longer than 100 bp) or joined paired-end reads. Each sample needs 40-50 million raw sequences, which can be expected to yield the 5-10 million annotated reads necessary for accurate abundance measures. We also demonstrated that ribosomal RNA depletion does not equally deplete ribosomes from all species within a sample, and remaining rRNA sequences should be discarded. Using publicly available metatranscriptome data in which rRNA was not depleted, we were able to demonstrate that overall organism transcriptional activity can be measured using mRNA counts. We were also able to detect significant differences between control and experimental groups in both organism transcriptional activity and specific cellular functions.

CONCLUSIONS

By making this new pipeline publicly available, we have created a powerful new tool for metatranscriptomics research, offering a new method for greater insight into the activity of diverse microbial communities. We further recommend that stool metatranscriptomes be ribodepleted and sequenced in a 100 bp paired end format with a minimum of 40 million reads per sample.

Avoidance of stochastic RNA interactions can be harnessed to control protein expression levels in bacteria and archaea

A critical assumption of gene expression analysis is that mRNA abundances broadly correlate with protein abundance, but these two are often imperfectly correlated. Some of the discrepancy can be accounted for by two important mRNA features: codon usage and mRNA secondary structure. We present a new global factor, called mRNA:ncRNA avoidance, and provide evidence that avoidance increases translational efficiency. We also demonstrate a strong selection for the avoidance of stochastic mRNA:ncRNA interactions across prokaryotes, and that these have a greater impact on protein abundance than mRNA structure or codon usage. By generating synonymously variant green fluorescent protein (GFP) mRNAs with different potential for mRNA:ncRNA interactions, we demonstrate that GFP levels correlate well with interaction avoidance. Therefore, taking stochastic mRNA:ncRNA interactions into account enables precise modulation of protein abundance.

DOI:http://dx.doi.org/10.7554/eLife.13479.001

Many genes carry information for making proteins. To make a protein, a working copy of the information stored in DNA is first copied into a molecule of messenger RNA. These RNA messages are then interpreted by the ribosome, the molecular machine that makes proteins. Many messages are produced from each gene, and each message can be read multiple times. Thus, it should follow that the number of messages produced dictates the number of proteins made. However, this is not the case and the number of proteins produced cannot be completely predicted from knowing the number of messenger RNAs.

Cells control how much of a given protein they produce through interactions between the messenger RNAs and other regulatory RNAs. The regulatory RNAs bind directly to a message and impede protein production. Because there are millions of RNAs in a cell, these interactions have evolved to be highly specific. Nevertheless, it seems inevitable that messenger RNAs would encounter other RNAs too, which could short-circuit gene regulation and lead to less protein being produced.

Umu et al. have now asked if such short-circuit events are selected against during evolution. Computational tools were used to predict the strength of binding between the RNAs found in the dominant forms of microbial life on Earth: the bacteria and the archaea. This approach revealed that the majority of messenger RNAs bind more weakly to the most common RNA molecules found in cells than would be expected by chance. Weakened binding should prevent the RNA molecules from becoming tangled with each other and ensure that protein levels are not perturbed by unintended interactions between highly expressed messages and other RNAs.

To test this hypothesis further, Umu et al. generated versions of the gene for a green fluorescent protein that differed only in how well their messenger RNAs could avoid interacting with the most abundant RNAs in E. coli cells. Those messengers that were designed to avoid interacting with other RNAs yielded far more protein than those that were not. The findings show that taking this kind of avoidance into account can improve predictions about how much protein will be produced and should therefore make it easier to control protein production in experimental systems.

Finally, the messenger RNAs of some bacteria do not show such clear avoidance. However, these bacteria have a more complex internal cell structure. This finding hints at an alternative means for avoiding short-circuiting events that could be used by more complicated cells, such of those of animals and plants, which also contain much larger numbers of RNAs.

DOI:http://dx.doi.org/10.7554/eLife.13479.002

Studying the Human Microbiota

There are a range of methodologies available to study the human microbiota, ranging from traditional approaches such as culturing through to state-of-the-art developments in next generation DNA sequencing technologies. The advent of molecular techniques in particular has opened up tremendous new avenues for research, and has galvanised interest in the study of our microbial inhabitants. Given the dazzling array of available options, however, it is important to understand the inherent advantages and limitations of each technique so that the best approach can be employed to address the particular research objective. In this chapter we cover some of the most widely used current techniques in human microbiota research and highlight the particular strengths and caveats associated with each approach.

Stool microbiome reveals diverse bacterial ureases as confounders of oral urea breath testing for Helicobacter pylori and Mycobacterium tuberculosis in Bamako, Mali

Detection of bacterial urease activity has been utilized successfully to diagnose Helicobacter pylori (H. pylori). While Mycobacterium tuberculosis (M. tuberculosis) also possesses an active urease, it is unknown whether detection of mycobacterial urease activity by oral urease breath test (UBT) can be exploited as a rapid point of care biomarker for tuberculosis (TB) in humans. We enrolled 34 individuals newly diagnosed with pulmonary TB and 46 healthy subjects in Bamako, Mali and performed oral UBT, mycobacterial sputum culture and H. pylori testing. Oral UBT had a sensitivity and specificity (95% CI) of 70% (46-88%) and 11% (3-26%), respectively, to diagnose culture-confirmed M. tuberculosis disease among patients without H. pylori, and 100% sensitivity (69-100%) and 11% specificity (3-26%) to diagnose H. pylori among patients without pulmonary TB. Stool microbiome analysis of controls without TB or H. pylori but with positive oral UBT detected high levels of non-H. pylori urease producing organisms, which likely explains the low specificity of oral UBT in this setting and in other reports of oral UBT studies in Africa.

On the study of microbial transcriptomes using second- and third-generation sequencing technologies

Second-generation sequencing technologies transformed the study of microbial transcriptomes. They helped reveal the transcription start sites and antisense transcripts of microbial species, improving the microbial genome annotation. Quantification of genome-wide gene expression levels allowed for functional studies of microbial research. Ever-evolving sequencing technologies are reshaping approaches to studying microbial transcriptomes. Recently, Oxford Nanopore Technologies delivered a sequencing platform called MinION, a third-generation sequencing technology, to the research community. We expect it to be the next sequencing technology that enables breakthroughs in life science fields. The studies of microbial transcriptomes will be no exception. In this paper, we review microbial transcriptomics studies using second- generation sequencing technology. We also discuss the prospect of microbial transcriptomics studies with thirdgeneration sequencing.

Lessons from Digestive-Tract Symbioses Between Bacteria and Invertebrates

In most animals, digestive tracts harbor the greatest number of bacteria in the animal that contribute to its health: by aiding in the digestion of nutrients, provisioning essential nutrients and protecting against colonization by pathogens. Invertebrates have been used to enhance our understanding of metabolic processes and microbe-host interactions owing to experimental advantages. This review describes how advances in DNA sequencing technologies have dramatically altered how researchers investigate microbe-host interactions, including 16S rRNA gene surveys, metagenome experiments, and metatranscriptome studies. Advantages and challenges of each of these approaches are described herein. Hypotheses generated through omics studies can be directly tested using site-directed mutagenesis, and findings from transposon studies and site-directed experiments are presented. Finally, unique structural aspects of invertebrate digestive tracts that contribute to symbiont specificity are presented. The combination of omics approaches with genetics and microscopy allows researchers to move beyond correlations to identify conserved mechanisms of microbe-host interactions.

Characterization of CRISPR RNA transcription by exploiting stranded metatranscriptomic data

CRISPR-Cas systems are bacterial adaptive immune systems, each typically composed of a locus of cas genes and a CRISPR array of spacers flanked by repeats. Processed transcripts of CRISPR arrays (crRNAs) play important roles in the interference process mediated by these systems, guiding targeted immunity. Here we developed computational approaches that allow us to characterize the expression of many CRISPRs in their natural environments, using community RNA-seq (metatranscriptomic) data. By exploiting public human gut metatranscriptomic data sets, we studied the expression of 56 repeat-sequence types of CRISPRs, revealing that most CRISPRs are transcribed in one direction (producing crRNAs). In rarer cases, including a type II system associated with Bacteroides fragilis, CRISPRs are transcribed in both directions. Type III CRISPR-Cas systems were found in the microbiomes, but metatranscriptomic reads were barely found for their CRISPRs. We observed individual-level variation of the crRNA transcription, and an even greater transcription of a CRISPR from the antisense strand than the crRNA strand in one sample. The orientations of CRISPR expression implicated by metatranscriptomic data are largely in agreement with prior predictions for CRISPRs, with exceptions. Our study shows the promise of exploiting community RNA-seq data for investigating the transcription of CRISPR-Cas systems.

A next generation sequencing-based method to study the intra-host genetic diversity of norovirus in patients with acute and chronic infection

Background

Immunocompromised individuals with chronic norovirus (NoV) infection and elderly patients are hypothesized to be reservoirs where NoV might accumulate mutations and evolve into pandemic strains. Next generation sequencing (NGS) methods can monitor the intra-host diversity of NoV and its evolution but low abundance of viral RNA results in sub-optimal efficiency. In this study, we: 1) established a next generation sequencing-based method for NoV using bacterial rRNA depletion as a viral RNA enrichment strategy, and 2) measured the intra-host genetic diversity of NoV in specimens of patients with acute NoV infection (n = 4) and in longitudinal specimens of an immunocompromised patient with chronic NoV infection (n = 2).

Results

A single Illumina MiSeq dataset resulted in near full-length genome sequences for 5 out of 6 multiplexed samples. Experimental depletion of bacterial rRNA in stool RNA provided up to 1.9 % of NoV reads. The intra-host viral population in patients with acute NoV infection was homogenous and no single nucleotide variants (SNVs) were detected. In contrast, the NoV population from the immunocompromised patient was highly diverse and accumulated SNVs over time (51 SNVs in the first sample and 122 SNVs in the second sample collected 4 months later). The percentages of SNVs causing non-synonymous mutations were 27.5 % and 20.5 % for the first and second samples, respectively. The majority of non-synonymous mutations occurred, in increasing order of frequency, in p22, the major capsid (VP1) and minor capsid (VP2) genes.

Conclusions

The results provide data useful for the selection and improvement of NoV RNA enrichment strategies for NGS. Whole genome analysis using next generation sequencing confirmed that the within-host population of NoV in an immunocompromised individual with chronic NoV infection was more diverse compared to that in individuals with acute infection. We also observed an accumulation of non-synonymous mutations at the minor capsid gene that has not been reported in previous studies and might have a role in NoV adaptation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2831-y) contains supplementary material, which is available to authorized users.

Precise Identification of Genome-Wide Transcription Start Sites in Bacteria by 5'-Rapid Amplification of cDNA Ends (5'-RACE)

Transcription start sites are commonly used to locate promoter elements in bacterial genomes. TSS were previously studied one gene at a time, often through 5'-rapid amplification of cDNA ends (5'-RACE). This technique has now been adapted for high-throughput sequencing and can be used to precisely identify TSS in a genome-wide fashion for practically any bacterium, which greatly contributes to our understanding of gene regulatory networks in microorganisms.

Torn apart and reunited: impact of a heterotroph on the transcriptome of Prochlorococcus

Microbial interactions, whether direct or indirect, profoundly affect the physiology of individual cells and ultimately have the potential to shape the biogeochemistry of the Earth. For example, the growth of Prochlorococcus, the numerically dominant cyanobacterium in the oceans, can be improved by the activity of co-occurring heterotrophs. This effect has been largely attributed to the role of heterotrophs in detoxifying reactive oxygen species that Prochlorococcus, which lacks catalase, cannot. Here, we explore this phenomenon further by examining how the entire transcriptome of Prochlorococcus NATL2A changes in the presence of a naturally co-occurring heterotroph, Alteromonas macleodii MIT1002, with which it was co-cultured for years, separated and then reunited. Significant changes in the Prochlorococcus transcriptome were evident within 6 h of initiating co-culture, with groups of transcripts changing in different temporal waves. Many transcriptional changes persisted throughout the 48 h experiment, suggesting that the presence of the heterotroph affected a stable shift in Prochlorococcus physiology. These initial transcriptome changes largely corresponded to reduced stress conditions for Prochlorococcus, as inferred from the depletion of transcripts encoding DNA repair enzymes and many members of the 'high light inducible' family of stress-response proteins. Later, notable changes were seen in transcripts encoding components of the photosynthetic apparatus (particularly, an increase in PSI subunits and chlorophyll synthesis enzymes), ribosomal proteins and biosynthetic enzymes, suggesting that the introduction of the heterotroph may have induced increased production of reduced carbon compounds for export. Changes in secretion-related proteins and transporters also highlight the potential for metabolic exchange between the two strains.