Quantitative bacterial transcriptomics with RNA-seq

Comparison of direct cDNA and PCR-cDNA Nanopore sequencing of RNA from Escherichia coli isolates

Whole-transcriptome (long-read) RNA sequencing (Oxford Nanopore Technologies, ONT) holds promise for reference-agnostic analysis of differential gene expression in pathogenic bacteria, including for antimicrobial resistance genes (ARGs). However, direct cDNA ONT sequencing requires large concentrations of polyadenylated mRNA, and amplification protocols may introduce technical bias. Here we evaluated the impact of direct cDNA- and cDNA PCR-based ONT sequencing on transcriptomic analysis of clinical Escherichia coli. Four E. coli bloodstream infection-associated isolates (n=2 biological replicates per isolate) were sequenced using the ONT Direct cDNA Sequencing SQK-DCS109 and PCR-cDNA Barcoding SQK-PCB111.24 kits. Biological and technical replicates were distributed over eight flow cells using 16 barcodes to minimize batch/barcoding bias. Reads were mapped to a transcript reference and transcript abundance was quantified after in silico depletion of low-abundance and rRNA genes. We found there were strong correlations between read counts using both kits and when restricting the analysis to include only ARGs. We highlighted that correlations were weaker for genes with a higher GC content. Read lengths were longer for the direct cDNA kit compared to the PCR-cDNA kit whereas total yield was higher for the PCR-cDNA kit. In this small but methodologically rigorous evaluation of biological and technical replicates of isolates sequenced with the direct cDNA and PCR-cDNA ONT sequencing kits, we demonstrated that PCR-based amplification substantially improves yield with largely unbiased assessment of core gene and ARG expression. However, users of PCR-based kits should be aware of a small risk of technical bias which appears greater for genes with an unusually high (>52%)/low (<44%) GC content.

Methods for studying microbial acid stress responses: from molecules to populations

The study of how micro-organisms detect and respond to different stresses has a long history of producing fundamental biological insights while being simultaneously of significance in many applied microbiological fields including infection, food and drink manufacture, and industrial and environmental biotechnology. This is well-illustrated by the large body of work on acid stress. Numerous different methods have been used to understand the impacts of low pH on growth and survival of micro-organisms, ranging from studies of single cells to large and heterogeneous populations, from the molecular or biophysical to the computational, and from well-understood model organisms to poorly defined and complex microbial consortia. Much is to be gained from an increased general awareness of these methods, and so the present review looks at examples of the different methods that have been used to study acid resistance, acid tolerance, and acid stress responses, and the insights they can lead to, as well as some of the problems involved in using them. We hope this will be of interest both within and well beyond the acid stress research community.

Decoding the molecular concerto: Toxicotranscriptomic evaluation of microplastic and nanoplastic impacts on aquatic organisms

The pervasive and steadily increasing presence of microplastics/nanoplastics (MPs/NPs) in aquatic environments has raised significant concerns regarding their potential adverse effects on aquatic organisms and their integration into trophic dynamics. This emerging issue has garnered the attention of (eco)toxicologists, promoting the utilization of toxicotranscriptomics to unravel the responses of aquatic organisms not only to MPs/NPs but also to a wide spectrum of environmental pollutants. This review aims to systematically explore the broad repertoire of predicted molecular responses by aquatic organisms, providing valuable intuitions into complex interactions between plastic pollutants and aquatic biota. By synthesizing the latest literature, present analysis sheds light on transcriptomic signatures like gene expression, interconnected pathways and overall molecular mechanisms influenced by various plasticizers. Harmful effects of these contaminants on key genes/protein transcripts associated with crucial pathways lead to abnormal immune response, metabolic response, neural response, apoptosis and DNA damage, growth, development, reproductive abnormalities, detoxification, and oxidative stress in aquatic organisms. However, unique challenge lies in enhancing the fingerprint of MPs/NPs, presenting complicated enigma that requires decoding their specific impact at molecular levels. The exploration endeavors, not only to consolidate existing knowledge, but also to identify critical gaps in understanding, push forward the frontiers of knowledge about transcriptomic signatures of plastic contaminants. Moreover, this appraisal emphasizes the imperative to monitor and mitigate the contamination of commercially important aquatic species by MPs/NPs, highlighting the pivotal role that regulatory frameworks must play in protecting all aquatic ecosystems. This commitment aligns with the broader goal of ensuring the sustainability of aquatic resources and the resilience of ecosystems facing the growing threat of plastic pollutants.

Elucidating the Mode of Action of Hybrid Nanoparticles of Cu/Zn Against Copper-Tolerant Xanthomonas euvesicatoria

The widespread presence of tolerance to copper in Xanthomonas species has resulted in the need to develop alternative approaches to control plant diseases caused by xanthomonads. In recent years, nanotechnological approaches have resulted in the identification of novel materials to control plant pathogens. With many metal-based nanomaterials having shown promise for disease control, an important question relates to the mode of action of these new materials. In this study, we used several approaches, such as scanning electron microscopy, propidium monoazide quantitative polymerase chain reaction, epifluorescence microscopy, and RNA sequencing to elucidate the mode of action of a Cu/Zn hybrid nanoparticle against copper-tolerant strains of Xanthomonas euvesicatoria. We demonstrate that Cu/Zn did not activate copper resistance genes (i.e., copA and copB) in the copper-tolerant bacterium but functioned by disrupting the bacterial cell structure and perturbing important biological processes such as cell respiration and chemical homeostasis.

Bacterial phenotypic heterogeneity through the lens of single-cell RNA sequencing

Bacterial transcription is not monolithic. Microbes exist in a wide variety of cell states that help them adapt to their environment, acquire and produce essential nutrients, and engage in both competition and cooperation with their neighbors. While we typically think of bacterial adaptation as a group behavior, where all cells respond in unison, there is often a mixture of phenotypic responses within a bacterial population, where distinct cell types arise. A primary phenomenon driving these distinct cell states is transcriptional heterogeneity. Given that bacterial mRNA transcripts are extremely short-lived compared to eukaryotes, their transcriptional state is closely associated with their physiology, and thus the transcriptome of a bacterial cell acts as a snapshot of the behavior of that bacterium. Therefore, the application of single-cell transcriptomics to microbial populations will provide novel insight into cellular differentiation and bacterial ecology. In this review, we provide an overview of transcriptional heterogeneity in microbial systems, discuss the findings already provided by single-cell approaches, and plot new avenues of inquiry in transcriptional regulation, cellular biology, and mechanisms of heterogeneity that are made possible when microbial communities are analyzed at single-cell resolution.

Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains

Foreign proteins are produced by introducing synthetic constructs into host bacteria for biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result in load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, and the synthetic system may suffer from suboptimal function. To help in the detection of bacterial load stress, we developed machine-learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered Escherichia coli strains.

Methodologies for bacterial ribonuclease characterization using RNA-seq

Bacteria adjust gene expression at the post-transcriptional level through an intricate network of small regulatory RNAs and RNA-binding proteins, including ribonucleases (RNases). RNases play an essential role in RNA metabolism, regulating RNA stability, decay, and activation. These enzymes exhibit species-specific effects on gene expression, bacterial physiology, and different strategies of target recognition. Recent advances in high-throughput RNA sequencing (RNA-seq) approaches have provided a better understanding of the roles and modes of action of bacterial RNases. Global studies aiming to identify direct targets of RNases have highlighted the diversity of RNase activity and RNA-based mechanisms of gene expression regulation. Here, we review recent RNA-seq approaches used to study bacterial RNases, with a focus on the methods for identifying direct RNase targets.

Antisense transcription and its roles in adaption to environmental stress in E. coli

It has been reported that a highly varying proportion (1% ∼ 93%) of genes in various prokaryotes have antisense RNA (asRNA) transcription. However, the extent of the pervasiveness of asRNA transcription in the well-studied E. coli K12 strain has thus far been an issue of debate. Furthermore, very little is known about the expression patterns and functions of asRNAs under various conditions. To fill these gaps, we determined the transcriptomes and proteomes of E. coli K12 at multiple time points in five culture conditions using strand-specific RNA-seq, differential RNA-seq, and quantitative mass spectrometry methods. To reduce artifacts of possible transcriptional noise, we identified asRNA using stringent criteria with biological replicate verification and transcription start sites (TSSs) information included. We identified a total of 660 asRNAs, which were generally short and largely condition-dependently transcribed. We found that the proportions of the genes which had asRNA transcription highly depended on the culture conditions and time points. We classified the transcriptional activities of the genes in six transcriptional modes according to their relative levels of asRNA to mRNA. Many genes changed their transcriptional modes at different time points of the culture conditions, and such transitions can be described in a well-defined manner. Intriguingly, the protein levels and mRNA levels of genes in the sense-only/sense-dominant mode were moderately correlated, but the same was not true for genes in the balanced/antisense-dominant mode, in which asRNAs were at a comparable or higher level to mRNAs. These observations were further validated by western blot on candidate genes, where an increase in asRNA transcription diminished gene expression in one case and enhanced it in another. These results suggest that asRNAs may directly or indirectly regulate translation by forming duplexes with cognate mRNAs. Thus, asRNAs may play an important role in the bacterium's responses to environmental changes during growth and adaption to different environments.

IMPORTANCE

The cis -antisense RNA (asRNA) is a type of understudied RNA molecules in prokaryotes, which is believed to be important in regulating gene expression. Our current understanding of asRNA is constrained by inconsistent reports about its identification and properties. These discrepancies are partially caused by a lack of sufficient samples, biological replicates, and culture conditions. This study aimed to overcome these disadvantages and identified 660 putative asRNAs using integrated information from strand-specific RNA-seq, differential RNA-seq, and mass spectrometry methods. In addition, we explored the relative expression between asRNAs and sense RNAs and investigated asRNA regulated transcriptional activity changes over different culture conditions and time points. Our work strongly suggests that asRNAs may play a crucial role in bacterium's responses to environmental changes during growth and adaption to different environments.

Transcriptional Profiles Analysis of COVID-19 and Malaria Patients Reveals Potential Biomarkers in Children

The clinical presentation overlap between malaria and COVID-19 poses special challenges for rapid diagnosis in febrile children. In this study, we collected RNA-seq data of children with malaria and COVID-19 infection from the public databases as raw data in fastq format paired end files. A group of six, five and two biological replicates of malaria, COVID-19 and healthy donors respectively were used for the study. We conducted differential gene expression analysis to visualize differences in the expression profiles. Using edgeR, we explored particularly gene expression levels in different phenotype groups and found that 1084 genes and 2495 genes were differentially expressed in the malaria samples and COVID-19 samples respectively when compared to healthy controls. The highly expressed gene in the COVID-19 group we found CD151 gene which is facilitates in T cell proliferation, while in the malaria group, among the highly expressed gene we identified GBP5 gene which involved in inflammatory response and response to bacterium. By comparing both malaria and COVID-19 infections, the overlap of 62 differentially expressed genes patterns were identified. Among them, three genes (ENSG00000234998, H2AC19 and TXNDC5) were highly upregulated in both infections. Strikingly, we observed 13 genes such as HBQ1, HBM, SLC7A5, SERINC2, ATP6V0C, ST6GALNAC4, RAD23A, PNPLA2, GAS2L1, TMEM86B, SLC6A8, UBALD1, RNF187 were downregulated in children with malaria and uniquely upregulated in children with COVID-19, thus may be further validated as potential biomarkers to delineate COVID-19 from malaria-related febrile infection. The hemoglobin complexes and lipid metabolism biological pathways are highly expressed in both infections. Our study provided new insights for further investigation of the biological pattern in hosts with malaria and COVID-19 coinfection.

What are housekeeping genes?

The concept of "housekeeping gene" has been used for four decades but remains loosely defined. Housekeeping genes are commonly described as "essential for cellular existence regardless of their specific function in the tissue or organism", and "stably expressed irrespective of tissue type, developmental stage, cell cycle state, or external signal". However, experimental support for the tenet that gene essentiality is linked to stable expression across cell types, conditions, and organisms has been limited. Here we use genome-scale functional genomic screens together with bulk and single-cell sequencing technologies to test this link and optimize a quantitative and experimentally validated definition of housekeeping gene. Using the optimized definition, we identify, characterize, and provide as resources, housekeeping gene lists extracted from several human datasets, and 10 other animal species that include primates, chicken, and C. elegans. We find that stably expressed genes are not necessarily essential, and that the individual genes that are essential and stably expressed can considerably differ across organisms; yet the pathways enriched among these genes are conserved. Further, the level of conservation of housekeeping genes across the analyzed organisms captures their taxonomic groups, showing evolutionary relevance for our definition. Therefore, we present a quantitative and experimentally supported definition of housekeeping genes that can contribute to better understanding of their unique biological and evolutionary characteristics.

Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens

While bacteria can be beneficial to our health, their deadly pathogenic potential has been an ever-present concern exacerbated by the emergence of drug-resistant strains. As such, there is a pressing urgency for an enhanced understanding of their gene function and regulation, which could mediate the development of novel antimicrobials. Transcriptomic analyses have been established as insightful and indispensable to the functional characterization of genes and identification of new biological pathways, but in the context of bacterial studies, they remain limited to species-specific datasets. To address this, we integrated the genomic and transcriptomic data of the 17 most notorious and researched bacterial pathogens, creating bacteria.guru, an interactive database that can identify, visualize, and compare gene expression profiles, coexpression networks, functionally enriched clusters, and gene families across species. Through illustrating antibiotic resistance mechanisms in P. aeruginosa, we demonstrate that bacteria.guru could potentially aid in discovering multi-faceted antibiotic targets and, overall, facilitate future bacterial research. AVAILABILITY: The database and coexpression networks are freely available from https://bacteria.guru/. Sample annotations can be found in the supplemental data.

The Complex Transcriptional Landscape of Magnetosome Gene Clusters in Magnetospirillum gryphiswaldense

Magnetosomes are complex membrane organelles synthesized by magnetotactic bacteria (MTB) for navigation in the Earth’s magnetic field. In the alphaproteobacterium Magnetospirillum gryphiswaldense, all steps of magnetosome formation are tightly controlled by >30 specific genes arranged in several gene clusters. However, the transcriptional organization of the magnetosome gene clusters has remained poorly understood. Here, by applying Cappable-seq and whole-transcriptome shotgun RNA sequencing, we show that mamGFDCop and feoAB1op are transcribed as single transcriptional units, whereas multiple transcription start sites (TSS) are present in mms6op, mamXYop, and the long (>16 kb) mamABop. Using a bioluminescence reporter assay and promoter knockouts, we demonstrate that most of the identified TSS originate from biologically meaningful promoters which mediate production of multiple transcripts and are functionally relevant for proper magnetosome biosynthesis. In addition, we identified a strong promoter in a large intergenic region within mamXYop, which likely drives transcription of a noncoding RNA important for gene expression in this operon. In summary, our data suggest a more complex transcriptional architecture of the magnetosome operons than previously recognized, which is largely conserved in other magnetotactic Magnetospirillum species and, thus, is likely fundamental for magnetosome biosynthesis in these organisms.

IMPORTANCE Magnetosomes have emerged as a model system to study prokaryotic organelles and a source of biocompatible magnetic nanoparticles for various biomedical applications. However, the lack of knowledge about the transcriptional organization of magnetosome gene clusters has severely impeded the engineering, manipulation, and transfer of this highly complex biosynthetic pathway into other organisms. Here, we provide a high-resolution image of the previously unappreciated transcriptional landscape of the magnetosome operons. Our findings are important for further unraveling the complex genetic framework of magnetosome biosynthesis. In addition, they will facilitate the rational reengineering of magnetic bacteria for improved bioproduction of tunable magnetic nanoparticles, as well as transplantation of magnetosome biosynthesis into foreign hosts by synthetic biology approaches. Overall, our study exemplifies how a genetically complex pathway is orchestrated at the transcriptional level to ensure the balanced expression of the numerous constituents required for the proper assembly of one of the most intricate prokaryotic organelles.

Mycoplasma genitalium and M. pneumoniae Regulate a Distinct Set of Protein-Coding Genes in Epithelial Cells

Mycoplasma genitalium and M. pneumoniae are two significant mycoplasmas that infect the urogenital and respiratory tracts of humans. Despite distinct tissue tropisms, they both have similar pathogenic mechanisms and infect/invade epithelial cells in the respective regions and persist within these cells. However, the pathogenic mechanisms of these species in terms of bacterium-host interactions are poorly understood. To gain insights on this, we infected HeLa cells independently with M. genitalium and M. pneumoniae and assessed gene expression by whole transcriptome sequencing (RNA-seq) approach. The results revealed that HeLa cells respond to M. genitalium and M. pneumoniae differently by regulating various protein-coding genes. Though there is a significant overlap between the genes regulated by these species, many of the differentially expressed genes were specific to each species. KEGG pathway and signaling network analyses revealed that the genes specific to M. genitalium are more related to cellular processes. In contrast, the genes specific to M. pneumoniae infection are correlated with immune response and inflammation, possibly suggesting that M. pneumoniae has some inherent ability to modulate host immune pathways.

Quantitative Control for Stoichiometric Protein Synthesis

Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Global transcriptome analysis of Stenotrophomonas maltophilia in response to growth at human body temperature

Stenotrophomonas maltophilia is a typical example of an environmental originated opportunistic human pathogen, which can thrive at different habitats including the human body and can cause a wide range of infections. It must cope with heat stress during transition from the environment to the human body as the physiological temperature of the human body (37 °C) is higher than environmental niches (22–30 °C). Interestingly, S. rhizophila a phylogenetic neighbour of S. maltophilia within genus Stenotrophomonas is unable to grow at 37 °C. Thus, it is crucial to understand how S. maltophilia is adapted to human body temperature, which could suggest its evolution as an opportunistic human pathogen. In this study, we have performed comparative transcriptome analysis of S. maltophilia grown at 28 and 37 °C as temperature representative for environmental niches and the human body, respectively. RNA-Seq analysis revealed several interesting findings showing alterations in gene-expression levels at 28 and 37 °C, which can play an important role during infection. We have observed downregulation of genes involved in cellular motility, energy production and metabolism, replication and repair whereas upregulation of VirB/D4 type IV secretion system, aerotaxis, cation diffusion facilitator family transporter and LacI family transcriptional regulators at 37 °C. Microscopy and plate assays corroborated altered expression of genes involved in motility. The results obtained enhance our understanding of the strategies employed by S. maltophilia during adaptation towards the human body.

The Genome of "Candidatus Liberibacter asiaticus" Is Highly Transcribed When Infecting the Gut of Diaphorina citri

The Asian citrus psyllid, Diaphorina citri, is the vector of the bacterium "Candidatus Liberibacter asiaticus" (Las), associated with the devastating, worldwide citrus disease huanglongbing. In order to explore the molecular interactions of this bacterium with D. citri during the vector acquisition process, cDNA libraries were sequenced on an Illumina platform, obtained from the gut of adult psyllids confined in healthy (H) and in Las-infected young shoots (Las) for different periods of times (I = 1/2 days, II = 3/4 days, and III = 5/6 days). In each sampling time, three biological replicates were collected, containing 100 guts each, totaling 18 libraries depleted in ribosomal RNA. Reads were quality-filtered and mapped against the Chinese JXGC Las strain and the Floridian strain UF506 for the analysis of the activity of Las genome and SC1, SC2, and type 3 (P-JXGC-3) prophages of the studied Las strain. Gene activity was considered only if reads of at least two replicates for each acquisition access period mapped against the selected genomes, which resulted in coverages of 44.4, 79.9, and 94.5% of the JXGC predicted coding sequences in Las I, Las II, and Las III, respectively. These genes indicate an active metabolism and increased expression according to the feeding time in the following functional categories: energy production, amino acid metabolism, signal translation, cell wall, and replication and repair of genetic material. Pilins were among the most highly expressed genes regardless of the acquisition time, while only a few genes from cluster I of flagella were not expressed. Furthermore, the prophage region had a greater coverage of reads for SC1 and P-JXGC-3 prophages and low coverage in SC2 and no indication of activity for the lysis cycle. This research presents the first descriptive analysis of Las transcriptome in the initial steps of the D. citri gut colonization, where 95% of Las genes were active.

An acquired acyltransferase promotes Klebsiella pneumoniae ST258 respiratory infection

Klebsiella pneumoniae ST258 is a human pathogen associated with poor outcomes worldwide. We identify a member of the acyltransferase superfamily 3 (atf3), enriched within the ST258 clade, that provides a major competitive advantage for the proliferation of these organisms in vivo. Comparison of a wild-type ST258 strain (KP35) and a Δatf3 isogenic mutant generated by CRISPR-Cas9 targeting reveals greater NADH:ubiquinone oxidoreductase transcription and ATP generation, fueled by increased glycolysis. The acquisition of atf3 induces changes in the bacterial acetylome, promoting lysine acetylation of multiple proteins involved in central metabolism, specifically Zwf (glucose-6 phosphate dehydrogenase). The atf3-mediated metabolic boost leads to greater consumption of glucose in the host airway and increased bacterial burden in the lung, independent of cytokine levels and immune cell recruitment. Acquisition of this acyltransferase enhances fitness of a K. pneumoniae ST258 isolate and may contribute to the success of this clonal complex as a healthcare-associated pathogen.

ProkSeq for complete analysis of RNA-Seq data from prokaryotes

Summary

Since its introduction, RNA-Seq technology has been used extensively in studies of pathogenic bacteria to identify and quantify differences in gene expression across multiple samples from bacteria exposed to different conditions. With some exceptions, tools for studying gene expression, determination of differential gene expression, downstream pathway analysis and normalization of data collected in extreme biological conditions is still lacking. Here, we describe ProkSeq, a user-friendly, fully automated RNA-Seq data analysis pipeline designed for prokaryotes. ProkSeq provides a wide variety of options for analysing differential expression, normalizing expression data and visualizing data and results.

Availability and implementation

ProkSeq is implemented in Python and is published under the MIT source license. The pipeline is available as a Docker container https://hub.docker.com/repository/docker/snandids/prokseq-v2.0, or can be used through Anaconda: https://anaconda.org/snandiDS/prokseq. The code is available on Github: https://github.com/snandiDS/prokseq and a detailed user documentation, including a manual and tutorial can be found at https://prokseqV20.readthedocs.io.

Supplementary information

Supplementary data are available at Bioinformatics online.

Efficient and cost-effective bacterial mRNA sequencing from low input samples through ribosomal RNA depletion

BACKGROUND

RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification.

RESULTS

EMBR-seq results in 90% of the sequenced RNA molecules from an E. coli culture deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq uses a single or a few oligonucleotides per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits for bacterial rRNA depletion, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA.

CONCLUSIONS

EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.

Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage

To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.

CrrB Positively Regulates High-Level Polymyxin Resistance and Virulence in Klebsiella pneumoniae

Polymyxin resistance (PR) threatens the treatment of carbapenem-resistant Klebsiella pneumoniae (CRKP) infections. PR frequently arises through chemical modification of the lipid A portion of lipopolysaccharide. Various mutations are implicated in PR, including in three two-component systems—CrrA/B, PmrA/B, and PhoP/Q—and the negative regulator MgrB. Few have been functionally validated. Therefore, here we adapt a CRISPR-Cas9 system to CRKP to elucidate how mutations in clinical CRKP isolates induce PR. We demonstrate that CrrB is a positive regulator of PR, and common clinical mutations lead to the addition of both 4-amino-4-deoxy-L-arabinose (L-Ara4N) and phosophethanolamine (pEtN) to lipid A, inducing notably higher polymyxin minimum inhibitory concentrations than mgrB disruption. Additionally, crrB mutations cause a significant virulence increase at a fitness cost, partially from activation of the pentose phosphate pathway. Our data demonstrate the importance of CrrB in high-level PR and establish important differences across crrB alleles in balancing resistance with fitness and virulence.

McConville et al. leverage CRISPR-Cas to demonstrate that mutations in crrB induce high-level polymyxin resistance in Klebsiella pneumoniae via the addition of L-Ara4N and pEtN to lipid A. CrrB mutations also increase virulence while conferring a fitness cost and alter carbon metabolism through activation of the pentose phosphate pathway.

Identification of the novel bacterial blight resistance gene Xa46(t) by mapping and expression analysis of the rice mutant H120

Rice bacterial leaf blight is caused by Xanthomonas oryzae pv. oryzae (Xoo) and produces substantial losses in rice yields. Resistance breeding is an effective method for controlling bacterial leaf blight disease. The mutant line H120 derived from the japonica line Lijiangxintuanheigu is resistant to all Chinese Xoo races. To identify and map the Xoo resistance gene(s) of H120, we examined the association between phenotypic and genotypic variations in two F₂ populations derived from crosses between H120/CO39 and H120/IR24. The segregation ratios of F₂ progeny consisted with the action of a single dominant resistance gene, which we named Xa46(t). Xa46(t) was mapped between the markers RM26981 and RM26984 within an approximately 65.34-kb region on chromosome 11. The 12 genes predicted within the target region included two candidate genes encoding the serine/threonine-protein kinase Doa (Loc_Os11g37540) and Calmodulin-2/3/5 (Loc_Os11g37550). Differential expression of H120 was analyzed by RNA-seq. Four genes in the Xa46(t) target region were differentially expressed after inoculation with Xoo. Mapping and expression data suggest that Loc_Os11g37540 allele is most likely to be Xa46(t). The sequence comparison of Xa23 allele between H120 and CBB23 indicated that the Xa46(t) gene is not identical to Xa23.

StanDep: Capturing transcriptomic variability improves context-specific metabolic models

Diverse algorithms can integrate transcriptomics with genome-scale metabolic models (GEMs) to build context-specific metabolic models. These algorithms require identification of a list of high confidence (core) reactions from transcriptomics, but parameters related to identification of core reactions, such as thresholding of expression profiles, can significantly change model content. Importantly, current thresholding approaches are burdened with setting singular arbitrary thresholds for all genes; thus, resulting in removal of enzymes needed in small amounts and even many housekeeping genes. Here, we describe StanDep, a novel heuristic method for using transcriptomics to identify core reactions prior to building context-specific metabolic models. StanDep clusters gene expression data based on their expression pattern across different contexts and determines thresholds for each cluster using data-dependent statistics, specifically standard deviation and mean. To demonstrate the use of StanDep, we built hundreds of models for the NCI-60 cancer cell lines. These models successfully increased the inclusion of housekeeping reactions, which are often lost in models built using standard thresholding approaches. Further, StanDep also provided a transcriptomic explanation for inclusion of lowly expressed reactions that were otherwise only supported by model extraction methods. Our study also provides novel insights into how cells may deal with context-specific and ubiquitous functions. StanDep, as a MATLAB toolbox, is available at https://github.com/LewisLabUCSD/StanDep.

A Simple, Cost-Effective, and Robust Method for rRNA Depletion in RNA-Sequencing Studies

The profiling of gene expression by RNA sequencing (RNA-seq) has enabled powerful studies of global transcriptional patterns in all organisms, including bacteria. Because the vast majority of RNA in bacteria is rRNA, it is standard practice to deplete the rRNA from a total RNA sample such that the reads in an RNA-seq experiment derive predominantly from mRNA. One of the most commonly used commercial kits for rRNA depletion, the Ribo-Zero kit from Illumina, was recently discontinued abruptly and for an extended period of time. Here, we report the development of a simple, cost-effective, and robust method for depleting rRNA that can be easily implemented by any lab or facility. We first developed an algorithm for designing biotinylated oligonucleotides that will hybridize tightly and specifically to the 23S, 16S, and 5S rRNAs from any species of interest. Precipitation of these oligonucleotides bound to rRNA by magnetic streptavidin-coated beads then depletes rRNA from a complex, total RNA sample such that ∼75 to 80% of reads in a typical RNA-seq experiment derive from mRNA. Importantly, we demonstrate a high correlation of RNA abundance or fold change measurements in RNA-seq experiments between our method and the Ribo-Zero kit. Complete details on the methodology are provided, including open-source software for designing oligonucleotides optimized for any bacterial species or community of interest.IMPORTANCE The ability to examine global patterns of gene expression in microbes through RNA sequencing has fundamentally transformed microbiology. However, RNA-seq depends critically on the removal of rRNA from total RNA samples. Otherwise, rRNA would comprise upward of 90% of the reads in a typical RNA-seq experiment, limiting the reads coming from mRNA or requiring high total read depth. A commonly used kit for rRNA subtraction from Illumina was recently unavailable for an extended period of time, disrupting routine rRNA depletion. Here, we report the development of a "do-it-yourself" kit for rapid, cost-effective, and robust depletion of rRNA from total RNA. We present an algorithm for designing biotinylated oligonucleotides that will hybridize to the rRNAs from a target set of species. We then demonstrate that the designed oligonucleotides enable sufficient rRNA depletion to produce RNA-seq data with 75 to 80% of reads coming from mRNA. The methodology presented should enable RNA-seq studies on any species or metagenomic sample of interest.

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.

Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations

BACKGROUND

Network inference is an important aim of systems biology. It enables the transformation of OMICs datasets into biological knowledge. It consists of reverse engineering gene regulatory networks from OMICs data, such as RNAseq or mass spectrometry-based proteomics data, through computational methods. This approach allows to identify signalling pathways involved in specific biological functions. The ability to infer causality in gene regulatory networks, in addition to correlation, is crucial for several modelling approaches and allows targeted control in biotechnology applications.

METHODS

We performed simulations according to the approximate Bayesian computation method, where the core model consisted of a steady-state simulation algorithm used to study gene regulatory networks in systems for which a limited level of details is available. The simulations outcome was compared to experimentally measured transcriptomics and proteomics data through approximate Bayesian computation.

RESULTS

The structure of small gene regulatory networks responsible for the regulation of biological functions involved in biomining were inferred from multi OMICs data of mixed bacterial cultures. Several causal inter- and intraspecies interactions were inferred between genes coding for proteins involved in the biomining process, such as heavy metal transport, DNA damage, replication and repair, and membrane biogenesis. The method also provided indications for the role of several uncharacterized proteins by the inferred connection in their network context.

CONCLUSIONS

The combination of fast algorithms with high-performance computing allowed the simulation of a multitude of gene regulatory networks and their comparison to experimentally measured OMICs data through approximate Bayesian computation, enabling the probabilistic inference of causality in gene regulatory networks of a multispecies bacterial system involved in biomining without need of single-cell or multiple perturbation experiments. This information can be used to influence biological functions and control specific processes in biotechnology applications.

Digitalizing heterologous gene expression in Gram-negative bacteria with a portable ON/OFF module

While prokaryotic promoters controlled by signal-responding regulators typically display a range of input/output ratios when exposed to cognate inducers, virtually no naturally occurring cases are known to have an OFF state of zero transcription-as ideally needed for synthetic circuits. To overcome this problem, we have modelled and implemented a simple digitalizer module that completely suppresses the basal level of otherwise strong promoters in such a way that expression in the absence of induction is entirely impeded. The circuit involves the interplay of a translation-inhibitory sRNA with the translational coupling of the gene of interest to a repressor such as LacI. The digitalizer module was validated with the strong inducible promoters Pm (induced by XylS in the presence of benzoate) and PalkB (induced by AlkS/dicyclopropyl ketone) and shown to perform effectively in both Escherichia coli and the soil bacterium Pseudomonas putida. The distinct expression architecture allowed cloning and conditional expression of, e.g. colicin E3, one molecule of which per cell suffices to kill the host bacterium. Revertants that escaped ColE3 killing were not found in hosts devoid of insertion sequences, suggesting that mobile elements are a major source of circuit inactivation in vivo.

Full-length RNA profiling reveals pervasive bidirectional transcription terminators in bacteria

The ability to determine full-length nucleotide composition of individual RNA molecules is essential for understanding the architecture and function of a transcriptome. However, experimental approaches capable of capturing the sequences of both 5' and 3' termini of the same transcript remain scarce. In the present study, simultaneous 5' and 3' end sequencing (SEnd-seq)-a high-throughput and unbiased method that simultaneously maps transcription start and termination sites with single-nucleotide resolution-is presented. Using this method, a comprehensive view of the Escherichia coli transcriptome was obtained, which displays an unexpected level of complexity. SEnd-seq notably expands the catalogue of transcription start sites and termination sites, defines unique transcription units and detects prevalent antisense RNA. Strikingly, the results of the present study unveil widespread overlapping bidirectional terminators located between opposing gene pairs. Furthermore, it has been shown that convergent transcription is a major contributor to highly efficient bidirectional termination both in vitro and in vivo. This finding highlights an underappreciated role of RNA polymerase conflicts in shaping transcript boundaries and suggests an evolutionary strategy for modulating transcriptional output by arranging gene orientation.

High-resolution analysis of the pneumococcal transcriptome under a wide range of infection-relevant conditions

Streptococcus pneumoniae is an opportunistic human pathogen that typically colonizes the nasopharyngeal passage and causes lethal disease in other host niches, such as the lung or the meninges. The expression and regulation of pneumococcal genes at different life-cycle stages, such as commensal or pathogenic, are not entirely understood. To chart the transcriptional responses of S. pneumoniae, we used RNA-seq to quantify the relative abundance of the transcriptome under 22 different infection-relevant conditions. The data demonstrated a high level of dynamic expression and, strikingly, all annotated pneumococcal genomic features were expressed in at least one of the studied conditions. By computing the correlation values of every pair of genes across all studied conditions, we created a co-expression matrix that provides valuable information on both operon structure and regulatory processes. The co-expression data are highly consistent with well-characterized operons and regulons, such as the PyrR, ComE and ComX regulons, and have allowed us to identify a new member of the competence regulon. Lastly, we created an interactive data center named PneumoExpress (https://veeninglab.com/pneumoexpress) that enables users to access the expression data as well as the co-expression matrix in an intuitive and efficient manner, providing a valuable resource to the pneumococcal research community.

Expanding the Vocabulary of Peptide Signals in Streptococcus mutans

Streptococci, including the dental pathogen Streptococcus mutans, undergo cell-to-cell signaling that is mediated by small peptides to control critical physiological functions such as adaptation to the environment, control of subpopulation behaviors and regulation of virulence factors. One such model pathway is the regulation of genetic competence, controlled by the ComRS signaling system and the peptide XIP. However, recent research in the characterization of this pathway has uncovered novel operons and peptides that are intertwined into its regulation. These discoveries, such as cell lysis playing a critical role in XIP release and importance of bacterial self-sensing during the signaling process, have caused us to reevaluate previous paradigms and shift our views on the true purpose of these signaling systems. The finding of new peptides such as the ComRS inhibitor XrpA and the peptides of the RcrRPQ operon also suggests there may be more peptides hidden in the genomes of streptococci that could play critical roles in the physiology of these organisms. In this review, we summarize the recent findings in S. mutans regarding the integration of other circuits into the ComRS signaling pathway, the true mode of XIP export, and how the RcrRPQ operon controls competence activation. We also look at how new technologies can be used to re-annotate the genome to find new open reading frames that encode peptide signals. Together, this summary of research will allow us to reconsider how we perceive these systems to behave and lead us to expand our vocabulary of peptide signals within the genus Streptococcus.

An integrative overview of genomic, transcriptomic and proteomic analyses in organohalide respiration research

Organohalide respiration (OHR) is a crucial process in the global halogen cycle and of interest for bioremediation. However, investigations on OHR are hampered by the restricted genetic accessibility and the poor growth yields of many organohalide-respiring bacteria (OHRB). Therefore, genomics, transcriptomics and proteomics are often used to investigate OHRB. In general, these gene expression studies are more useful when the data of the different 'omics' approaches are integrated and compared among a wide range of cultivation conditions and ideally involve several closely related OHRB. Despite the availability of a couple of proteomic and transcriptomic datasets dealing with OHRB, such approaches are currently not covered in reviews. Therefore, we here present an integrative and comparative overview of omics studies performed with the OHRB Sulfurospirillum multivorans, Dehalococcoides mccartyi, Desulfitobacterium spp. and Dehalobacter restrictus. Genes, transcripts, proteins and the regulatory and biochemical processes involved in OHR are discussed, and a comprehensive view on the unusual metabolism of D. mccartyi, which is one of the few bacteria possibly using a quinone-independent respiratory chain, is provided. Several 'omics'-derived theories on OHRB, e.g. the organohalide-respiratory chain, hydrogen metabolism, corrinoid biosynthesis or one-carbon metabolism are critically discussed on the basis of this integrative approach.

Adding function to the genome of African Salmonella Typhimurium ST313 strain D23580

Salmonella Typhimurium sequence type (ST) 313 causes invasive nontyphoidal Salmonella (iNTS) disease in sub-Saharan Africa, targeting susceptible HIV+, malarial, or malnourished individuals. An in-depth genomic comparison between the ST313 isolate D23580 and the well-characterized ST19 isolate 4/74 that causes gastroenteritis across the globe revealed extensive synteny. To understand how the 856 nucleotide variations generated phenotypic differences, we devised a large-scale experimental approach that involved the global gene expression analysis of strains D23580 and 4/74 grown in 16 infection-relevant growth conditions. Comparison of transcriptional patterns identified virulence and metabolic genes that were differentially expressed between D23580 versus 4/74, many of which were validated by proteomics. We also uncovered the S. Typhimurium D23580 and 4/74 genes that showed expression differences during infection of murine macrophages. Our comparative transcriptomic data are presented in a new enhanced version of the Salmonella expression compendium, SalComD23580: http://bioinf.gen.tcd.ie/cgi-bin/salcom_v2.pl. We discovered that the ablation of melibiose utilization was caused by three independent SNP mutations in D23580 that are shared across ST313 lineage 2, suggesting that the ability to catabolize this carbon source has been negatively selected during ST313 evolution. The data revealed a novel, to our knowledge, plasmid maintenance system involving a plasmid-encoded CysS cysteinyl-tRNA synthetase, highlighting the power of large-scale comparative multicondition analyses to pinpoint key phenotypic differences between bacterial pathovariants.

BAC-BROWSER: The Tool for Visualization and Analysis of Prokaryotic Genomes

Prokaryotes are actively studied objects in the scope of genomic regulation. Microbiologists need special tools for complex analysis of data to study and identification of regulatory mechanism in bacteria and archaea. We developed a tool BAC-BROWSER, specifically for visualization and analysis of small prokaryotic genomes. BAC-BROWSER provides tools for different types of analysis to study a wide set of regulatory mechanisms of prokaryotes: -transcriptional regulation by transcription factors (TFs), analysis of TFs, their targets, and binding sites.-other regulatory motifs, promoters, terminators and ribosome binding sites-transcriptional regulation by variation of operon structure, alternative starts or ends of transcription.-non-coding RNAs, antisense RNAs-RNA secondary structure, riboswitches-GC content, GC skew, codon usage BAC-browser incorporated free programs accelerating the verification of obtained results: primer design and oligocalculator, vector visualization, the tool for synthetic gene construction. The program is designed for Windows operating system and freely available for download in http://smdb.rcpcm.org/tools/index.html.

Evaluation of promoter sequences for the secretory production of a Clostridium thermocellum cellulase in Paenibacillus polymyxa

Due to their high secretion capacity, Gram-positive bacteria from the genus Bacillus are important expression hosts for the high-yield production of enzymes in industrial biotechnology; however, to date, strains from only few Bacillus species are used for enzyme production at industrial scale. Herein, we introduce Paenibacillus polymyxa DSM 292, a member of a different genus, as a novel host for secretory protein production. The model gene cel8A from Clostridium thermocellum was chosen as an easily detectable reporter gene with industrial relevance to demonstrate heterologous expression and secretion in P. polymyxa. The yield of the secreted cellulase Cel8A protein was increased by optimizing the expression medium and testing several promoter sequences in the expression plasmid pBACOV. Quantitative mass spectrometry was used to analyze the secretome in order to identify promising new promoter sequences from the P. polymyxa genome itself. The most abundantly secreted host proteins were identified, and the promoters regulating the expression of their corresponding genes were selected. Eleven promoter sequences were cloned and tested, including well-characterized promoters from Bacillus subtilis and Bacillus megaterium. The best result was achieved with the promoter for the hypothetical protein PPOLYM_03468 from P. polymyxa. In combination with the optimized expression medium, this promoter enabled the production of 5475 U/l of Cel8A, which represents a 6.2-fold increase compared to the reference promoter P_aprE. The set of promoters described in this work covers a broad range of promoter strengths useful for heterologous expression in the new host P. polymyxa.

Functional Transcriptomics for Bacterial Gene Detectives

Developments in transcriptomic technology and the availability of whole-genome-level expression profiles for many bacterial model organisms have accelerated the assignment of gene function. However, the deluge of transcriptomic data is making the analysis of gene expression a challenging task for biologists. Online resources for global bacterial gene expression analysis are not available for the majority of published data sets, impeding access and hindering data exploration. Here, we show the value of preexisting transcriptomic data sets for hypothesis generation. We describe the use of accessible online resources, such as SalComMac and SalComRegulon, to visualize and analyze expression profiles of coding genes and small RNAs. This approach arms a new generation of "gene detectives" with powerful new tools for understanding the transcriptional networks of Salmonella, a bacterium that has become an important model organism for the study of gene regulation. To demonstrate the value of integrating different online platforms, and to show the simplicity of the approach, we used well-characterized small RNAs that respond to envelope stress, oxidative stress, osmotic stress, or iron limitation as examples. We hope to provide impetus for the development of more online resources to allow the scientific community to work intuitively with transcriptomic data.

Transcriptomic analysis of longitudinal Burkholderia pseudomallei infecting the cystic fibrosis lung

The melioidosis bacterium, Burkholderia pseudomallei, is increasingly being recognised as a pathogen in patients with cystic fibrosis (CF). We have recently catalogued genome-wide variation of paired, isogenic B. pseudomallei isolates from seven Australasian CF cases, which were collected between 4 and 55 months apart. Here, we extend this investigation by documenting the transcriptomic changes in B. pseudomallei in five cases. Following growth in an artificial CF sputum medium, four of the five paired isolates exhibited significant differential gene expression (DE) that affected between 32 and 792 genes. The greatest number of DE events was observed between the strains from patient CF9, consistent with the hypermutator status of the latter strain, which is deficient in the DNA mismatch repair protein MutS. Two patient isolates harboured duplications that concomitantly increased expression of the β-lactamase-encoding gene penA, and a 35 kb deletion in another abolished expression of 29 genes. Convergent expression profiles in the chronically-adapted isolates identified two significantly downregulated and 17 significantly upregulated loci, including the resistance-nodulation-division (RND) efflux pump BpeEF-OprC, the quorum-sensing hhqABCDE operon, and a cyanide- and pyocyanin-insensitive cytochrome bd quinol oxidase. These convergent pathoadaptations lead to increased expression of pathways that may suppress competing bacterial and fungal pathogens, and that enhance survival in oxygen-restricted environments, the latter of which may render conventional antibiotics less effective in vivo. Treating chronically adapted B. pseudomallei infections with antibiotics designed to target anaerobic infections, such as the nitroimidazole class of antibiotics, may significantly improve pathogen eradication attempts by exploiting this Achilles heel.

Large Noncoding RNAs in Bacteria

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

Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes

In a conventional view of the prokaryotic genome organization, promoters precede operons and ribosome binding sites (RBSs) with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of precomputed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as noncanonical RBS patterns. To assess the accuracy of GeneMarkS-2, we used genes validated by COG (Clusters of Orthologous Groups) annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of ∼5000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts.

Requirement or exclusion of inverted repeat sequences with cruciform-forming potential in Escherichia coli revealed by genome-wide analyses

Inverted repeat (IR) sequences are DNA sequences that read the same from 5' to 3' in each strand. Some IRs can form cruciforms under the stress of negative supercoiling, and these IRs are widely found in genomes. However, their biological significance remains unclear. The aim of the current study is to explore this issue further. We constructed the first Escherichia coli genome-wide comprehensive map of IRs with cruciform-forming potential. Based on the map, we performed detailed and quantitative analyses. Here, we report that IRs with cruciform-forming potential are statistically enriched in the following five regions: the adjacent regions downstream of the stop codon-coding sites (referred to as the stop codons), on and around the positions corresponding to mRNA ends (referred to as the gene ends), ~ 20 to ~45 bp upstream of the start codon-coding sites (referred to as the start codons) within the 5'-UTR (untranslated region), ~ 25 to ~ 60 bp downstream of the start codons, and promoter regions. For the adjacent regions downstream of the stop codons and on and around the gene ends, most of the IRs with a repeat unit length of ≥ 8 bp and a spacer size of ≤ 8 bp were parts of the intrinsic terminators, regardless of the location, and presumably used for Rho-independent transcription termination. In contrast, fewer IRs were present in the small region preceding the start codons. In E. coli, IRs with cruciform-forming potential are actively placed or excluded in the regulatory regions for the initiation and termination of transcription and translation, indicating their deep involvement or influence in these processes.

Testing culture purity in prokaryotes: criteria and challenges

Reliance on pure cultures was introduced at the beginning of microbiology as a discipline and has remained significant although their adaptive properties are essentially dissimilar from those of mixed cultures and environmental populations. They are needed for (i) taxonomic identification; (ii) diagnostics of pathogens; (iii) virulence and pathogenicity studies; (iv) elucidation of metabolic properties; (v) testing sensitivity to antibiotics; (vi) full-length genome assembly; (vii) strain deposition in microbial collections; and (viii) description of new species with name validation. Depending on the specific task there are alternative claims for culture purity, i.e., when conventional criteria are satisfied or when looking deeper is necessary. Conventional proof (microscopic and plating controls) has a low resolution and depends on the observer's personal judgement. Phenotypic criteria alone cannot prove culture purity and should be complemented with genomic criteria. We consider the possible use of DNA high-throughput culture sequencing data to define criteria for only one genospecies, axenic state detection panel and only one genome. The second and third of these are preferable, although their resolving capacity (depth) is limited. Because minor contaminants may go undetected, even with deep sequencing, the reliably pure culture would be a clonal culture launched from a single cell or trichome (multicellular bacterium). Although this type of culture is associated with technical difficulties and cannot be employed on a large scale (the corresponding inoculums may have low chances of growth when transferred to solid media), it is hoped that the high-throughput culturing methods introduced by 'culturomics' will overcome this obstacle.

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.

Strand-specific transcriptomes of Enterohemorrhagic Escherichia coli in response to interactions with ground beef microbiota: interactions between microorganisms in raw meat

BACKGROUND

Enterohemorrhagic Escherichia coli (EHEC) are zoonotic agents associated with outbreaks worldwide. Growth of EHEC strains in ground beef could be inhibited by background microbiota that is present initially at levels greater than that of the pathogen E. coli. However, how the microbiota outcompetes the pathogenic bacteria is unknown. Our objective was to identify metabolic pathways of EHEC that were altered by natural microbiota in order to improve our understanding of the mechanisms controlling the growth and survival of EHECs in ground beef.

RESULTS

Based on 16S metagenomics analysis, we identified the microbial community structure in our beef samples which was an essential preliminary for subtractively analyzing the gene expression of the EHEC strains. Then, we applied strand-specific RNA-seq to investigate the effects of this microbiota on the global gene expression of EHEC O2621765 and O157EDL933 strains by comparison with their behavior in beef meat without microbiota. In strain O2621765, the expression of genes connected with nitrate metabolism and nitrite detoxification, DNA repair, iron and nickel acquisition and carbohydrate metabolism, and numerous genes involved in amino acid metabolism were down-regulated. Further, the observed repression of ftsL and murF, involved respectively in building the cytokinetic ring apparatus and in synthesizing the cytoplasmic precursor of cell wall peptidoglycan, might help to explain the microbiota's inhibitory effect on EHECs. For strain O157EDL933, the induced expression of the genes implicated in detoxification and the general stress response and the repressed expression of the peR gene, a gene negatively associated with the virulence phenotype, might be linked to the survival and virulence of O157:H7 in ground beef with microbiota.

CONCLUSION

In the present study, we show how RNA-Seq coupled with a 16S metagenomics analysis can be used to identify the effects of a complex microbial community on relevant functions of an individual microbe within it. These findings add to our understanding of the behavior of EHECs in ground beef. By measuring transcriptional responses of EHEC, we could identify putative targets which may be useful to develop new strategies to limit their shedding in ground meat thus reducing the risk of human illnesses.

Global survey of mRNA levels and decay rates of Chlamydia trachomatis trachoma and lymphogranuloma venereum biovars

Interpreting the intricate bacterial transcriptomics implies understanding the dynamic relationship established between de novo transcription and the degradation of transcripts. Here, we performed a comparative overview of gene expression levels and mRNA decay rates for different-biovar (trachoma and lymphogranuloma venereum) strains of the obligate intracellular bacterium Chlamydia trachomatis. By using RNA-sequencing to measure gene expression levels at mid developmental stage and mRNA decay rates upon rifampicin-based transcription blockage, we observed that: i) 60-70% of the top-50 expressed genes encode proteins with unknown function and proteins involved in "Translation, ribosomal structure and biogenesis" for all strains; ii) the expression ranking by genes' functional categories was in general concordant among different-biovar strains; iii) the median of the half-life time (t_1/2) values of transcripts were 15-17 min, indicating that the degree of transcripts' stability seems to correlate with the bacterial intracellular life-style, as these values are considerably higher than the ones observed in other studies for facultative intracellular and free-living bacteria; iv) transcript decay rates were highly heterogeneous within each C. trachomatis strain and did not correlate with steady-state expression levels; v) only at very few instances (essentially at gene functional category level) was possible to unveil dissimilarities potentially underlying phenotypic differences between biovars. In summary, the unveiled transcriptomic scenario, marked by a general lack of correlation between transcript production and degradation and a huge inter-transcript heterogeneity in decay rates, likely reflects the challenges underlying the unique biphasic developmental cycle of C. trachomatis and its intricate interactions with the human host, which probably exacerbate the complexity of the bacterial transcription regulation.

Identification of endoribonuclease specific cleavage positions reveals novel targets of RNase III in Streptococcus pyogenes

A better understanding of transcriptional and post-transcriptional regulation of gene expression in bacteria relies on studying their transcriptome. RNA sequencing methods are used not only to assess RNA abundance but also the exact boundaries of primary and processed transcripts. Here, we developed a method, called identification of specific cleavage position (ISCP), which enables the identification of direct endoribonuclease targets in vivo by comparing the 5΄ and 3΄ ends of processed transcripts between wild type and RNase deficient strains. To demonstrate the ISCP method, we used as a model the double-stranded specific RNase III in the human pathogen Streptococcus pyogenes. We mapped 92 specific cleavage positions (SCPs) among which, 48 were previously described and 44 are new, with the characteristic 2 nucleotides 3΄ overhang of RNase III. Most SCPs were located in untranslated regions of RNAs. We screened for RNase III targets using transcriptomic differential expression analysis (DEA) and compared those with the RNase III targets identified using the ISCP method. Our study shows that in S. pyogenes, under standard growth conditions, RNase III has a limited impact both on antisense transcripts and on global gene expression with the expression of most of the affected genes being downregulated in an RNase III deletion mutant.