Progress in prokaryotic transcriptomics

Comprehensive toxicological, metabolomic, and transcriptomic analysis of the biodegradation and adaptation mechanism by Achromobacter xylosoxidans SL-6 to diuron

Biodegradation was considered a promising and environmentally friendly method for treating environmental pollution caused by diuron. However, the mechanisms of biodegradation of diuron required further research. In this study, the degradation process of diuron by Achromobacter xylosoxidans SL-6 was systematically investigated. The results suggested that the antioxidant system of strain SL-6 was activated by adding diuron, thereby alleviating their oxidative stress response. In addition, degradation product analysis showed that diuron in strain SL-6 was mainly degraded by urea bridge cleavage, dehalogenation, deamination, and ring opening, and finally cis, cis-muconic acid was generated. The combined analysis of metabolomics and transcriptomics revealed the biodegradation and adaptation mechanism of strain SL-6 to diuron. Metabolomics analysis showed that after the strain SL-6 was exposed to diuron, metabolic pathways such as tricarboxylic acid cycle (cis, cis-muconic acid), glutathione metabolism (oxidized glutathione), and urea cycle (arginine) were reprogrammed in the cells. Furthermore, diuron could induce the production of membrane transport proteins in strain SL-6 cells and overexpress antioxidant enzyme genes, finally ultimately promoting the up-regulation of genes encoding amide hydrolases and dioxygenases, which was revealed by transcriptomics studies. This work enriched the biodegradation mechanism of phenylurea herbicides and provided guidance for the removal of diuron residues in the environment and promoting agriculture sustainable development.

The Rising Role of Omics and Meta-Omics in Table Olive Research

Table olives are often the result of fermentation, a process where microorganisms transform raw materials into the final product. The microbial community can significantly impact the organoleptic characteristics and safety of table olives, and it is influenced by various factors, including the processing methods. Traditional culture-dependent techniques capture only a fraction of table olives' intricate microbiota, prompting a shift toward culture-independent methods to address this knowledge gap. This review explores recent advances in table olive research through omics and meta-omics approaches. Genomic analysis of microorganisms isolated from table olives has revealed multiple genes linked to technological and probiotic attributes. An increasing number of studies concern metagenomics and metabolomics analyses of table olives. The former offers comprehensive insights into microbial diversity and function, while the latter identifies aroma and flavor determinants. Although proteomics and transcriptomics studies remain limited in the field, they have the potential to reveal deeper layers of table olives' microbiome composition and functionality. Despite the challenges associated with implementing multi-omics approaches, such as the reliance on advanced bioinformatics tools and computational resources, they hold the promise of groundbreaking advances in table olive processing technology.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

Reaching unreachables: Obstacles and successes of microbial cultivation and their reasons

In terms of the number and diversity of living units, the prokaryotic empire is the most represented form of life on Earth, and yet it is still to a significant degree shrouded in darkness. This microbial "dark matter" hides a great deal of potential in terms of phylogenetically or metabolically diverse microorganisms, and thus it is important to acquire them in pure culture. However, do we know what microorganisms really need for their growth, and what the obstacles are to the cultivation of previously unidentified taxa? Here we review common and sometimes unexpected requirements of environmental microorganisms, especially soil-harbored bacteria, needed for their replication and cultivation. These requirements include resuscitation stimuli, physical and chemical factors aiding cultivation, growth factors, and co-cultivation in a laboratory and natural microbial neighborhood.

Understanding human health through metatranscriptomics

Metatranscriptomics has revolutionized our ability to explore and understand transcriptional programs in microbial communities. Moreover, it has enabled us to gain deeper and more specific insight into the microbial activities in human gut, respiratory, oral, and vaginal communities. Perhaps the most important contribution of metatranscriptomics arises, however, from the analyses of disease-associated communities. We review the advantages and disadvantages of metatranscriptomics analyses in understanding human health and disease. We focus on human tissues low in microbial biomass and conditions associated with dysbiotic microbiota. We conclude that a more widespread use of metatranscriptomics and increased knowledge on microbe activities will uncover critical interactions between microbes and host in human health and provide diagnostic basis for culturing-independent, direct functional pathogen identification.

Rapid and accurate identification of ribosomal RNA sequences via deep learning

Advances in transcriptomic and translatomic techniques enable in-depth studies of RNA activity profiles and RNA-based regulatory mechanisms. Ribosomal RNA (rRNA) sequences are highly abundant among cellular RNA, but if the target sequences do not include polyadenylation, these cannot be easily removed in library preparation, requiring their post-hoc removal with computational techniques to accelerate and improve downstream analyses. Here, we describe RiboDetector, a novel software based on a Bi-directional Long Short-Term Memory (BiLSTM) neural network, which rapidly and accurately identifies rRNA reads from transcriptomic, metagenomic, metatranscriptomic, noncoding RNA, and ribosome profiling sequence data. Compared with state-of-the-art approaches, RiboDetector produced at least six times fewer misclassifications on the benchmark datasets. Importantly, the few false positives of RiboDetector were not enriched in certain Gene Ontology (GO) terms, suggesting a low bias for downstream functional profiling. RiboDetector also demonstrated a remarkable generalizability for detecting novel rRNA sequences that are divergent from the training data with sequence identities of <90%. On a personal computer, RiboDetector processed 40M reads in less than 6 min, which was ∼50 times faster in GPU mode and ∼15 times in CPU mode than other methods. RiboDetector is available under a GPL v3.0 license at https://github.com/hzi-bifo/RiboDetector.

Transcriptome Analysis of Komagataeibacter europaeus CGMCC 20445 Responses to Different Acidity Levels During Acetic Acid Fermentation

In the industrial production of high-acidity vinegar, the initial ethanol and acetic acid concentrations are limiting factors that will affect acetic acid fermentation. In this study, Komagataeibacter europaeus CGMCC 20445 was used for acetic acid shake flask fermentation at an initial ethanol concentration of 4.3% (v/v). We conducted transcriptome analysis of K. europaeus CGMCC 20445 samples under different acidity conditions to elucidate the changes in differentially expressed genes throughout the fermentation process. We also analyzed the expression of genes associated with acid-resistance mechanisms. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the differentially expressed genes were enriched in ribosomes, citrate cycle, butanoate metabolism, oxidative phosphorylation, pentose phosphate, and the fatty acid biosynthetic pathways. In addition, this study found that K. europaeus CGMCC 20445 regulates the gene expression levels of cell envelope proteins and stress-responsive proteins to adapt to the gradual increase in acidity during acetic acid fermentation. This study improved the understanding of the acid resistance mechanism of K. europaeus and provided relevant reference information for the further genetic engineering of this bacterium.

Innovations in CAZyme gene diversity and its modification for biorefinery applications

For sustainable growth, concept of biorefineries as recourse to the "fossil derived" energy source is important. Here, the Carbohydrate Active enZymes (CAZymes) play decisive role in generation of biofuels and related sugar-based products utilizing lignocellulose as a carbon source. Given their industrial significance, extensive studies on the evolution of CAZymes have been carried out. Various bacterial and fungal organisms have been scrutinized for the development of CAZymes, where advance techniques for strain enhancement such as CRISPR and analysis of specific expression systems have been deployed. Specific Omic-based techniques along with protein engineering have been adopted to unearth novel CAZymes and improve applicability of existing enzymes. In-Silico computational research and functional annotation of new CAZymes to synergy experiments are being carried out to devise cocktails of enzymes for use in biorefineries. Thus, with the establishment of these technologies, increased diversity of CAZymes with broad span of functions and applications is seen.

Dynamic insights on transcription initiation and RNA processing during bacterial adaptation

Transcription initiation and RNA processing govern gene expression and enable bacterial adaptation by reshaping the RNA landscape. The aim of this study was to simultaneously observe these two fundamental processes in a transcriptome responding to an environmental signal. A controlled σ^E system in E. coli was coupled to our previously described tagRNA-seq method to yield process kinetics information. Changes in transcription initiation frequencies (TIF) and RNA processing frequencies (PF) were followed using 5' RNA tags. Changes in TIF showed a binary increased/decreased pattern that alternated between transcriptionally activated and repressed promoters, providing the bacterial population with transcriptional oscillation. PF variation fell into three categories of cleavage activity: (i) constant and independent of RNA levels, (ii) increased once RNA has accumulated, and (iii) positively correlated to changes in TIF. This work provides a comprehensive and dynamic view of major events leading to transcriptomic reshaping during bacterial adaptation. It unveils an interplay between transcription initiation and the activity of specific RNA cleavage sites. This study utilized a well-known genetic system to analyze fundamental processes and can serve as a blueprint for comprehensive studies that exploit the RNA metabolism to decipher and understand bacterial gene expression control.

Metagenomics for broad and improved parasite detection: a proof-of-concept study using swine faecal samples

Efficient and reliable identification of emerging pathogens is crucial for the design and implementation of timely and proportionate control strategies. This is difficult if the pathogen is so far unknown or only distantly related with known pathogens. Diagnostic metagenomics - an undirected, broad and sensitive method for the efficient identification of pathogens - was frequently used for virus and bacteria detection, but seldom applied to parasite identification. Here, metagenomics datasets prepared from swine faeces using an unbiased sample processing approach with RNA serving as starting material were re-analysed with respect to parasite detection. The taxonomic identification tool RIEMS, used for initial detection, provided basic hints on potential pathogens contained in the datasets. The suspected parasites/intestinal protists (Blastocystis, Entamoeba, Iodamoeba, Neobalantidium, Tetratrichomonas) were verified using subsequently applied reference mapping analyses on the base of rRNA sequences. Nearly full-length gene sequences could be extracted from the RNA-derived datasets. In the case of Blastocystis, subtyping was possible with subtype (ST)15 discovered for the first known time in swine faeces. Using RIEMS, some of the suspected candidates turned out to be false-positives caused by the poor status of sequences in publicly available databases. Altogether, 11 different species/STs of parasites/intestinal protists were detected in 34 out of 41 datasets extracted from metagenomics data. The approach operates without any primer bias that typically hampers the analysis of amplicon-based approaches, and allows the detection and taxonomic classification including subtyping of protist and metazoan endobionts (parasites, commensals or mutualists) based on an abundant biomarker, the 18S rRNA. The generic nature of the approach also allows evaluation of interdependencies that induce mutualistic or pathogenic effects that are often not clear for many intestinal protists and perhaps other parasites. Thus, metagenomics has the potential for generic pathogen identification beyond the characterisation of viruses and bacteria when starting from RNA instead of DNA.

RNAseq analysis of α-proteobacterium Gluconobacter oxydans 621H

Background

The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole transcriptomes were sequenced to identify expressed genes and operon structures.

Results

Sequencing of primary transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis-regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313).

Conclusions

This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans. The corrections of start codons further improve the high quality genome reference and support future proteome analysis.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4415-x) contains supplementary material, which is available to authorized users.

Transcriptomic analysis of Ehrlichia ruminantium during the developmental stages in bovine and tick cell culture

The use of bioinformatics tools to search for possible vaccine candidates has been successful in recent years. In an attempt to search for additional vaccine candidates or improve the current heartwater vaccine design, a genome-wide transcriptional profile of E. ruminantium (Welgevonden strain) replicating in bovine endothelial cells (BA886) and Ixodes scapularis embryonic tick cells (IDE8) was performed. The RNA was collected from the infective extracellular form, the elementary bodies (EBs) and vegetative intracellular form, reticulate bodies (RBs) and was used for transcriptome sequencing. Several genes previously implicated with adhesion, attachment and pathogenicity were exclusively up-regulated in the EBs from bovine and tick cells. Similarly, genes involved in adaptation or survival of E. ruminantium in the host cells were up-regulated in the RBs from bovine cells. Thus, it was concluded that those genes expressed in the EBs might be important for infection of mammalian and tick host cells and these may be targets for both cell and humoral mediated immune responses. Alternatively, those exclusively expressed in the RBs may be important for survival in the host cells. Exported or secreted proteins exclusively expressed at this stage are ideal targets for the stimulation of cytotoxic T-lymphocyte (CTL) immune responses in the host.

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.

RNA-seq based transcriptomic analysis of single bacterial cells

Gene-expression heterogeneity among individual cells determines the fate of a bacterial population. Here we report the first bacterial single-cell RNA sequencing (RNA-seq), BaSiC RNA-seq, a method integrating RNA isolation, cDNA synthesis and amplification, and RNA-seq analysis of the whole transcriptome of single cyanobacterium Synechocystis sp. PCC 6803 cells which typically contain approximately 5-7 femtogram total RNA per cell. We applied the method to 3 Synechocystis single cells at 24 h and 3 single cells at 72 h after nitrogen-starvation stress treatment, as well as their bulk-cell controls under the same conditions, to determine the heterogeneity upon environmental stress. With 82-98% and 31-48% of all putative Synechocystis genes identified in single cells of 24 and 72 h, respectively, the results demonstrated that the method could achieve good identification of the transcripts in single bacterial cells. In addition, the preliminary results from nitrogen-starved cells also showed a possible increasing gene-expression heterogeneity from 24 h to 72 h after nitrogen starvation stress. Moreover, preliminary analysis of single-cell transcriptomic datasets revealed that genes from the "Mobile elements" functional category have the most significant increase of gene-expression heterogeneity upon stress, which was further confirmed by single-cell RT-qPCR analysis of gene expression in 24 randomly selected cells.

DNA and RNA Extraction and Quantitative Real-Time PCR-Based Assays for Biogas Biocenoses in an Interlaboratory Comparison

Five institutional partners participated in an interlaboratory comparison of nucleic acid extraction, RNA preservation and quantitative Real-Time PCR (qPCR) based assays for biogas biocenoses derived from different grass silage digesting laboratory and pilot scale fermenters. A kit format DNA extraction system based on physical and chemical lysis with excellent extraction efficiency yielded highly reproducible results among the partners and clearly outperformed a traditional CTAB/chloroform/isoamylalcohol based method. Analytical purpose, sample texture, consistency and upstream pretreatment steps determine the modifications that should be applied to achieve maximum efficiency in the trade-off between extract purity and nucleic acid recovery rate. RNA extraction was much more variable, and the destination of the extract determines the method to be used. RNA stabilization with quaternary ammonium salts was an as satisfactory approach as flash freezing in liquid N₂. Due to co-eluted impurities, spectrophotometry proved to be of limited value for nucleic acid qualification and quantification in extracts obtained with the kit, and picoGreen^® based quantification was more trustworthy. Absorbance at 230 nm can be extremely high in the presence of certain chaotropic guanidine salts, but guanidinium isothiocyanate does not affect (q)PCR. Absolute quantification by qPCR requires application of a reliable internal standard for which correct PCR efficiency and Y-intercept values are important and must be reported.

Interactions between closely related bacterial strains are revealed by deep transcriptome sequencing

Comparative genomics, metagenomics, and single-cell technologies have shown that populations of microbial species encompass assemblages of closely related strains. This raises the question of whether individual bacterial lineages respond to the presence of their close relatives by modifying their gene expression or, instead, whether assemblages simply act as the arithmetic addition of their individual components. Here, we took advantage of transcriptome sequencing to address this question. For this, we analyzed the transcriptomes of two closely related strains of the extremely halophilic bacterium Salinibacter ruber grown axenically and in coculture. These organisms dominate bacterial assemblages in hypersaline environments worldwide. The strains used here cooccurred in the natural environment and are 100% identical in their 16S rRNA genes, and each strain harbors an accessory genome representing 10% of its complete genome. Overall, transcriptomic patterns from pure cultures were very similar for both strains. Expression was detected along practically the whole genome albeit with some genes at low levels. A subset of genes was very highly expressed in both strains, including genes coding for the light-driven proton pump xanthorhodopsin, genes involved in the stress response, and genes coding for transcriptional regulators. Expression differences between pure cultures affected mainly genes involved in environmental sensing. When the strains were grown in coculture, there was a modest but significant change in their individual transcription patterns compared to those in pure culture. Each strain sensed the presence of the other and responded in a specific manner, which points to fine intraspecific transcriptomic modulation.

Experimental approaches to phenotypic diversity in infection

Microbial infections are burdening human health, even after the advent of antibiotics, vaccines and hygiene. Thus, infection biology has aimed at the molecular understanding of the pathogen-host interaction. This has revealed key virulence factors, host cell signaling pathways and immune responses. However, our understanding of the infection process is still incomplete. Recent evidence suggests that phenotypic diversity can have important consequences for the infection process. Diversity arises from the formation of distinct subpopulations of pathogen cells (with distinct virulence factor expression patterns) and host cells (with distinct response capacities). For technical reasons, such phenotypic diversity has often been overlooked. We are highlighting several striking examples and discuss the experimental approaches available for analyzing the different subpopulations. Single cell reporters and approaches from systems biology do hold much promise.

Dual 3'Seq using deepSuperSAGE uncovers transcriptomes of interacting Salmonella enterica Typhimurium and human host cells

Background

The interaction of eukaryotic host and prokaryotic pathogen cells is linked to specific changes in the cellular proteome, and consequently to infection-related gene expression patterns of the involved cells. To simultaneously assess the transcriptomes of both organisms during their interaction we developed dual 3’Seq, a tag-based sequencing protocol that allows for exact quantification of differentially expressed transcripts in interacting pro- and eukaryotic cells without prior fixation or physical disruption of the interaction.

Results

Human epithelial cells were infected with Salmonella enterica Typhimurium as a model system for invasion of the intestinal epithelium, and the transcriptional response of the infected host cells together with the differential expression of invading and intracellular pathogen cells was determined by dual 3’Seq coupled with the next-generation sequencing-based transcriptome profiling technique deepSuperSAGE (deep Serial Analysis of Gene Expression). Annotation to reference transcriptomes comprising the operon structure of the employed S. enterica Typhimurium strain allowed for in silico separation of the interacting cells including quantification of polycistronic RNAs. Eighty-nine percent of the known loci are found to be transcribed in prokaryotic cells prior or subsequent to infection of the host, while 75% of all protein-coding loci are represented in the polyadenylated transcriptomes of human host cells.

Conclusions

Dual 3’Seq was alternatively coupled to MACE (Massive Analysis of cDNA ends) to assess the advantages and drawbacks of a library preparation procedure that allows for sequencing of longer fragments. Additionally, the identified expression patterns of both organisms were validated by qRT-PCR using three independent biological replicates, which confirmed that RELB along with NFKB1 and NFKB2 are involved in the initial immune response of epithelial cells after infection with S. enterica Typhimurium.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1489-1) contains supplementary material, which is available to authorized users.

Comparative transcriptomic analysis reveals novel genes and regulatory mechanisms of Tetragenococcus halophilus in response to salt stress

Tetragenococcus halophilus, a moderately halophilic Gram-positive bacterium, was isolated from Chinese style soy sauce. This species is a valuable resource for investigating salt tolerance mechanisms and improving salinity resistance in microorganisms. RNA-seq was used to sequence T. halophilus samples treated with 0 M (T1), 1 M (T2), and 3.5 M NaCl (T3). Comparative transcriptomic analyses of the different treatments were performed using gene ontology and Kyoto encyclopedia of genes and genome. The comparison of T1 and T2 by RNA-seq revealed that genes involved in transcription, translation, membrane system, and division were highly up-regulated under optimum salt condition. The comparison of T2 and T3 showed that genes related to heat shock proteins or the ATP-binding cassette transport systems were significantly up-regulated under maximum-salt condition. In addition, a considerable proportion of the significantly differently expressed genes identified in this study are novel. These data provide a crucial resource that may determine specific responses to salt stress in T. halophilus.

READemption-a tool for the computational analysis of deep-sequencing-based transcriptome data

RNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. To draw biological conclusions based on RNA-Seq data, several steps, some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes and RNA immunoprecipitated with proteins, not only from bacteria but also from eukaryotes and archaea.

AVAILABILITY AND IMPLEMENTATION

READemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).

High-throughput sequencing for the study of bacterial pathogen biology

A revolution in sequencing technologies in recent years has led to dramatically increased throughput and reduced cost of bacterial genome sequencing. An increasing number of applications of the new technologies are providing broad insights into bacterial evolution, epidemiology, and pathogenesis. For example, the capacity to sequence large numbers of bacterial isolates is enabling high resolution phylogenetic analyses of bacterial populations leading to greatly enhanced understanding of the emergence, adaptation, and transmission of pathogenic clones. In addition, RNA-seq offers improved quantification and resolution for transcriptomic analysis, and the combination of high-throughput sequencing with transposon mutagenesis is a powerful approach for the identification of bacterial determinants required for survival in vivo. In this concise review we provide selected examples of how high throughput sequencing is being applied to understand the biology of bacterial pathogens, and discuss future technological advances likely to have a profound impact on the field.

Understanding Anaplasmataceae pathogenesis using "Omics" approaches

This paper examines how "Omics" approaches improve our understanding of Anaplasmataceae pathogenesis, through a global and integrative strategy to identify genes and proteins involved in biochemical pathways key for pathogen-host-vector interactions. The Anaplasmataceae family comprises obligate intracellular bacteria mainly transmitted by arthropods. These bacteria are responsible for major human and animal endemic and emerging infectious diseases with important economic and public health impacts. In order to improve disease control strategies, it is essential to better understand their pathogenesis. Our work focused on four Anaplasmataceae, which cause important animal, human and zoonotic diseases: Anaplasma marginale, A. phagocytophilum, Ehrlichia chaffeensis, and E. ruminantium. Wolbachia spp. an endosymbiont of arthropods was also included in this review as a model of a non-pathogenic Anaplasmataceae. A gap analysis on "Omics" approaches on Anaplasmataceae was performed, which highlighted a lack of studies on the genes and proteins involved in the infection of hosts and vectors. Furthermore, most of the studies have been done on the pathogen itself, mainly on infectious free-living forms and rarely on intracellular forms. In order to perform a transcriptomic analysis of the intracellular stage of development, researchers developed methods to enrich bacterial transcripts from infected cells. These methods are described in this paper. Bacterial genes encoding outer membrane proteins, post-translational modifications, eukaryotic repeated motif proteins, proteins involved in osmotic and oxidative stress and hypothetical proteins have been identified to play a key role in Anaplasmataceae pathogenesis. Further investigations on the function of these outer membrane proteins and hypothetical proteins will be essential to confirm their role in the pathogenesis. Our work underlines the need for further studies in this domain and on host and vector responses to infection.

A model system for studying the transcriptomic and physiological changes associated with mammalian host-adaptation by Leptospira interrogans serovar Copenhageni

Leptospirosis, an emerging zoonotic disease with worldwide distribution, is caused by spirochetes belonging to the genus Leptospira. More than 500,000 cases of severe leptospirosis are reported annually, with >10% of these being fatal. Leptospires can survive for weeks in suitably moist conditions before encountering a new host. Reservoir hosts, typically rodents, exhibit little to no signs of disease but shed large numbers of organisms in their urine. Transmission occurs when mucosal surfaces or abraded skin come into contact with infected urine or urine-contaminated water or soil. In humans, leptospires can cause a variety of clinical manifestations, ranging from asymptomatic or mild fever to severe icteric (Weil's) disease and pulmonary haemorrhage. Currently, little is known about how Leptospira persist within a reservoir host. Prior in vitro studies have suggested that leptospires alter their transcriptomic and proteomic profiles in response to environmental signals encountered during mammalian infection. However, no study has examined gene expression by leptospires within a mammalian host-adapted state. To obtain a more faithful representation of how leptospires respond to host-derived signals, we used RNA-Seq to compare the transcriptome of L. interrogans cultivated within dialysis membrane chambers (DMCs) implanted into the peritoneal cavities of rats with that of organisms grown in vitro. In addition to determining the relative expression levels of “core” housekeeping genes under both growth conditions, we identified 166 genes that are differentially-expressed by L. interrogans in vivo. Our analyses highlight physiological aspects of host adaptation by leptospires relating to heme uptake and utilization. We also identified 11 novel non-coding transcripts that are candidate small regulatory RNAs. The DMC model provides a facile system for studying the transcriptional and antigenic changes associated with mammalian host-adaption, selection of targets for mutagenesis, and the identification of previously unrecognized virulence determinants.

Leptospirosis, a global disease caused by the unusual bacterium Leptospira, is transmitted from animals to humans. Pathogenic species of Leptospira are excreted in urine from infected animals and can continue to survive in suitable environments before coming into contact with a new reservoir or accidental host. Leptospires have an inherent ability to survive a wide range of conditions encountered in nature during transmission and within mammals. However, we know very little about the regulatory pathways and gene products that promote mammalian host adaptation and enable leptospires to establish infection. In this study, we used a novel system whereby leptospires are cultivated in dialysis membrane chambers implanted into the peritoneal cavities of rats to compare the gene expression profiles of mammalian host-adapted and in vitro-cultivated organisms. In addition to providing a facile system for studying the transcriptional and physiologic changes leptospires undergo during mammalian infection, our data provide a rational basis for selecting new targets for mutagenesis.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

BACKGROUND

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads.

RESULTS

To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases.

CONCLUSIONS

As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Gene regulation by CcpA and catabolite repression explored by RNA-Seq in Streptococcus mutans

A bacterial transcriptome of the primary etiological agent of human dental caries, Streptococcus mutans, is described here using deep RNA sequencing. Differential expression profiles of the transcriptome in the context of carbohydrate source, and of the presence or absence of the catabolite control protein CcpA, revealed good agreement with previously-published DNA microarrays. In addition, RNA-seq considerably expanded the repertoire of DNA sequences that showed statistically-significant changes in expression as a function of the presence of CcpA and growth carbohydrate. Novel mRNAs and small RNAs were identified, some of which were differentially expressed in conditions tested in this study, suggesting that the function of the S. mutans CcpA protein and the influence of carbohydrate sources has a more substantial impact on gene regulation than previously appreciated. Likewise, the data reveal that the mechanisms underlying prioritization of carbohydrate utilization are more diverse than what is currently understood. Collectively, this study demonstrates the validity of RNA-seq as a potentially more-powerful alternative to DNA microarrays in studying gene regulation in S. mutans because of the capacity of this approach to yield a more precise landscape of transcriptomic changes in response to specific mutations and growth conditions.

Proteomic analysis of an unculturable bacterial endosymbiont (Blochmannia) reveals high abundance of chaperonins and biosynthetic enzymes

Many insect groups have coevolved with bacterial endosymbionts that live within specialized host cells. As a salient example, ants in the tribe Camponotini rely on Blochmannia, an intracellular bacterial mutualist that synthesizes amino acids and recycles nitrogen for the host. We performed a shotgun, label-free, LC/MS/MS quantitative proteomic analysis to investigate the proteome of Blochmannia associated with Camponotus chromaiodes. We identified more than 330 Blochmannia proteins, or 54% coverage of the predicted proteome, as well as 244 Camponotus proteins. Using the average intensity of the top 3 "best flier" peptides along with spiking of a surrogate standard at a known concentration, we estimated the concentration (fmol/μg) of those proteins with confident identification. The estimated dynamic range of Blochmannia protein abundance spanned 3 orders of magnitude and covered diverse functional categories, with particularly high representation of metabolism, information transfer, and chaperones. GroEL, the most abundant protein, totaled 6% of Blochmannia protein abundance. Biosynthesis of essential amino acids, fatty acids, and nucleotides, and sulfate assimilation had disproportionately high coverage in the proteome, further supporting a nutritional role of the symbiosis. This first quantitative proteomic analysis of an ant endosymbiont illustrates a promising approach to study the functional basis of intimate symbioses.

Stable isotope probing in the metagenomics era: a bridge towards improved bioremediation

Microbial biodegradation and biotransformation reactions are essential to most bioremediation processes, yet the specific organisms, genes, and mechanisms involved are often not well understood. Stable isotope probing (SIP) enables researchers to directly link microbial metabolic capability to phylogenetic and metagenomic information within a community context by tracking isotopically labeled substances into phylogenetically and functionally informative biomarkers. SIP is thus applicable as a tool for the identification of active members of the microbial community and associated genes integral to the community functional potential, such as biodegradative processes. The rapid evolution of SIP over the last decade and integration with metagenomics provide researchers with a much deeper insight into potential biodegradative genes, processes, and applications, thereby enabling an improved mechanistic understanding that can facilitate advances in the field of bioremediation.

Genome-enabled perspectives on the composition, evolution, and expression of virulence determinants in bacterial plant pathogens

Genome sequence analyses of bacterial plant pathogens are revealing important insights into the molecular determinants of pathogenicity and, through transcript characterization, responses to environmental conditions, evidence for small RNAs, and validation of uncharacterized genes. Genome comparison sheds further light on the processes impacting pathogen evolution and differences in gene repertoire among isolates contributing to niche specialization. Information derived from pathogen genome analysis is providing tools for use in diagnosis and interference with host-pathogen interactions for the purpose of disease control. However, the existing information infrastructure fails to adequately integrate the increasing numbers of sequence data sets, bioinformatic analyses, and experimental characterization, as required for effective systems-level analysis. Enhanced standardization of data formats at the point of publication is proposed as a possible solution.