Studying bacterial transcriptomes using RNA-seq

Essential genes for Haemophilus parainfluenzae survival and biofilm growth

Haemophilus parainfluenzae (Hp) is a Gram-negative, highly prevalent, and abundant commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the supragingival plaque biofilm. Little is known about how Hp interacts with its neighbors in healthy biofilms nor its mechanisms of pathogenesis as an opportunistic pathogen. To address this, we identified the essential genome and conditionally essential genes in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain (Hp 392) and oral isolate EL1 (Hp EL1), we show that the essential genomes of Hp 392 and Hp EL1 are composed of 395 (20%) and 384 (19%) genes, respectively. The core essential genome, consisting of 341 (17%) essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains. RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo habitat. This library presents a valuable tool for investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.IMPORTANCEHaemophilus parainfluenzae is a highly abundant human commensal microbe, present in most healthy individuals where it colonizes the mouth. H. parainfluenzae correlates with good oral health and may play a role in preservation of healthy host status. Also, H. parainfluenzae can cause opportunistic infections outside of the oral cavity. To date, little is known about how H. parainfluenzae colonizes the human host, despite being such a frequent and abundant part of our human microbiome. Here, we demonstrate the creation and use of a powerful tool, a TnSeq library, used to identify genes necessary for both the outright growth of this organism and also genes conditionally essential for growth in varying oxygen status which it can encounter in the human host. This tool and these data serve as a foundation for further study of this relatively unknown organism that may play a role in preserving human health.

Deciphering nutritional stress responses via knowledge-enriched transcriptomics for microbial engineering

Understanding diverse bacterial nutritional requirements and responses is foundational in microbial research and biotechnology. In this study, we employed knowledge-enriched transcriptomic analytics to decipher complex stress responses of Vibrio natriegens to supplied nutrients, aiming to enhance microbial engineering efforts. We computed 64 independently modulated gene sets that comprise a quantitative basis for transcriptome dynamics across a comprehensive transcriptomics dataset containing a broad array of nutrient conditions. Our approach led to the i) identification of novel transporter systems for diverse substrates, ii) a detailed understanding of how trace elements affect metabolism and growth, and iii) extensive characterization of nutrient-induced stress responses, including osmotic stress, low glycolytic flux, proteostasis, and altered protein expression. By clarifying the relationship between the acetate-associated regulon and glycolytic flux status of various nutrients, we have showcased its vital role in directing optimal carbon source selection. Our findings offer deep insights into the transcriptional landscape of bacterial nutrition and underscore its significance in tailoring strain engineering strategies, thereby facilitating the development of more efficient and robust microbial systems for biotechnological applications.

Artificial Intelligence and Computational Biology in Gene Therapy: A Review

One of the trending fields in almost all areas of science and technology is artificial intelligence. Computational biology and artificial intelligence can help gene therapy in many steps including: gene identification, gene editing, vector design, development of new macromolecules and modeling of gene delivery. There are various tools used by computational biology and artificial intelligence in this field, such as genomics, transcriptomic and proteomics data analysis, machine learning algorithms and molecular interaction studies. These tools can introduce new gene targets, novel vectors, optimized experiment conditions, predict the outcomes and suggest the best solutions to avoid undesired immune responses following gene therapy treatment.

Genome-wide annotation of transcript boundaries using bacterial Rend-seq datasets

Accurate annotation to single-nucleotide resolution of the transcribed regions in genomes is key to optimally analyse RNA-seq data, understand regulatory events and for the design of experiments. However, currently most genome annotations provided by GenBank generally lack information about untranslated regions. Additionally, information regarding genomic locations of non-coding RNAs, such as sRNAs, or anti-sense RNAs is frequently missing. To provide such information, diverse RNA-seq technologies, such as Rend-seq, have been developed and applied to many bacterial species. However, incorporating this vast amount of information into annotation files has been limited and is bioinformatically challenging, resulting in UTRs and other non-coding elements being overlooked or misrepresented. To overcome this problem, we present pyRAP (python Rend-seq Annotation Pipeline), a software package that analyses Rend-seq datasets to accurately resolve transcript boundaries genome-wide. We report the use of pyRAP to find novel transcripts, transcript isoforms, and RNase-dependent sRNA processing events. In Bacillus subtilis we uncovered 63 novel transcripts and provide genomic coordinates with single-nucleotide resolution for 2218 5'UTRs, 1864 3'UTRs and 161 non-coding RNAs. In Escherichia coli, we report 117 novel transcripts, 2429 5'UTRs, 1619 3'UTRs and 91 non-coding RNAs, and in Staphylococcus aureus, 16 novel transcripts, 664 5'UTRs, 696 3'UTRs, and 81 non-coding RNAs. Finally, we use pyRAP to produce updated annotation files for B. subtilis 168, E. coli K-12 MG1655, and S. aureus 8325 for use in the wider microbial genomics research community.

Essential genes for Haemophilus parainfluenzae survival and biofilm growth

Haemophilus parainfluenzae ( Hp ) is a Gram-negative, pleomorphic rod, highly prevalent and abundant as a commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the tongue dorsum, keratinized gingiva, and the supragingival plaque biofilm. As a member of the HACEK group, Hp is also known to cause infective endocarditis. Additionally, case reports have identified Hp as the causative agent of meningitis, septic arthritis, chronic osteomyelitis, septicemia, and a variety of other infectious diseases. Little is known about how Hp interacts with its neighbors in the healthy biofilm nor about its mechanisms of pathogenesis as an extraoral opportunistic pathogen. To address these unknowns, we identified the essential genomes of two Hp strains and the conditionally essential genes for their growth in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain ( Hp 392) and a commensal oral isolate EL1 ( Hp EL1), we show that the essential genome of Hp 392 and Hp EL1 is composed of 395 and 384 genes, respectively. The core essential genome, consisting of 341 essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains of Hp . Additionally, RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic biofilm survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo oral habitat. Further, the creation of this library presents a valuable tool for further investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.

Bacterial therapies at the interface of synthetic biology and nanomedicine

Bacteria are emerging as living drugs to treat a broad range of disease indications. However, the inherent advantages of these replicating and immunostimulatory therapies also carry the potential for toxicity. Advances in synthetic biology and the integration of nanomedicine can address this challenge through the engineering of controllable systems that regulate spatial and temporal activation for improved safety and efficacy. Here, we review recent progress in nanobiotechnology-driven engineering of bacteria-based therapies, highlighting limitations and opportunities that will facilitate clinical translation.

Precision run-on sequencing (PRO-seq) for microbiome transcriptomics

Bacteria respond to environmental stimuli through precise regulation of transcription initiation and elongation. Bulk RNA sequencing primarily characterizes mature transcripts, so to identify actively transcribed loci we need to capture RNA polymerase (RNAP) complexed with nascent RNA. However, such capture methods have only previously been applied to culturable, genetically tractable organisms such as E. coli and B. subtilis. Here we apply precision run-on sequencing (PRO-seq) to profile nascent transcription in cultured E. coli and diverse uncultured bacteria. We demonstrate that PRO-seq can characterize the transcription of small, structured, or post-transcriptionally modified RNAs, which are often absent from bulk RNA-seq libraries. Applying PRO-seq to the human microbiome highlights taxon-specific RNAP pause motifs and pause-site distributions across non-coding RNA loci that reflect structure-coincident pausing. We also uncover concurrent transcription and cleavage of CRISPR guide RNAs and transfer RNAs. We demonstrate the utility of PRO-seq for exploring transcriptional dynamics in diverse microbial communities.

Profiling of Microbial Landscape in Lung of Chronic Obstructive Pulmonary Disease Patients Using RNA Sequencing

Purpose

The aim of the study was to use RNA sequencing (RNA-seq) data of lung from chronic obstructive pulmonary disease (COPD) patients to identify the bacteria that are most commonly detected. Additionally, the study sought to investigate the differences in these infections between normal lung tissues and those affected by COPD.

Patients and Methods

We re-analyzed RNA-seq data of lung from 99 COPD patients and 93 non-COPD smokers to determine the extent to which the metagenomes differed between the two groups and to assess the reliability of the metagenomes. We used unmapped reads in the RNA-seq data that were not aligned to the human reference genome to identify more common infections in COPD patients.

Results

We identified 18 bacteria that exhibited significant differences between the COPD and non-COPD smoker groups. Among these, Yersinia enterocolitica was found to be more than 30% more abundant in COPD. Additionally, we observed difference in detection rate based on smoking history. To ensure the accuracy of our findings and distinguish them from false positives, we double-check the metagenomic profile using Basic Local Alignment Search Tool (BLAST). We were able to identify and remove specific species that might have been misclassified as other species in Kraken2 but were actually Staphylococcus aureus, as identified by BLAST analysis.

Conclusion

This study highlighted the method of using unmapped reads, which were not typically used in sequencing data, to identify microorganisms present in patients with lung diseases such as COPD. This method expanded our understanding of the microbial landscape in COPD and provided insights into the potential role of microorganisms in disease development and progression.

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.

Mechanobiology as a tool for addressing the genotype-to-phenotype problem in microbiology

The central hypothesis of the genotype-phenotype relationship is that the phenotype of a developing organism (i.e., its set of observable attributes) depends on its genome and the environment. However, as we learn more about the genetics and biochemistry of living systems, our understanding does not fully extend to the complex multiscale nature of how cells move, interact, and organize; this gap in understanding is referred to as the genotype-to-phenotype problem. The physics of soft matter sets the background on which living organisms evolved, and the cell environment is a strong determinant of cell phenotype. This inevitably leads to challenges as the full function of many genes, and the diversity of cellular behaviors cannot be assessed without wide screens of environmental conditions. Cellular mechanobiology is an emerging field that provides methodologies to understand how cells integrate chemical and physical environmental stress and signals, and how they are transduced to control cell function. Biofilm forming bacteria represent an attractive model because they are fast growing, genetically malleable and can display sophisticated self-organizing developmental behaviors similar to those found in higher organisms. Here, we propose mechanobiology as a new area of study in prokaryotic systems and describe its potential for unveiling new links between an organism's genome and phenome.

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.

Pleomorphic Variants of Borreliella (syn. Borrelia) burgdorferi Express Evolutionary Distinct Transcriptomes

Borreliella (syn. Borrelia) burgdorferi is a spirochete bacterium that causes tick-borne Lyme disease. Along its lifecycle B. burgdorferi develops several pleomorphic forms with unclear biological and medical relevance. Surprisingly, these morphotypes have never been compared at the global transcriptome level. To fill this void, we grew B. burgdorferi spirochete, round body, bleb, and biofilm-dominated cultures and recovered their transcriptomes by RNAseq profiling. We found that round bodies share similar expression profiles with spirochetes, despite their morphological differences. This sharply contrasts to blebs and biofilms that showed unique transcriptomes, profoundly distinct from spirochetes and round bodies. To better characterize differentially expressed genes in non-spirochete morphotypes, we performed functional, positional, and evolutionary enrichment analyses. Our results suggest that spirochete to round body transition relies on the delicate regulation of a relatively small number of highly conserved genes, which are located on the main chromosome and involved in translation. In contrast, spirochete to bleb or biofilm transition includes substantial reshaping of transcription profiles towards plasmids-residing and evolutionary young genes, which originated in the ancestor of Borreliaceae. Despite their abundance the function of these Borreliaceae-specific genes is largely unknown. However, many known Lyme disease virulence genes implicated in immune evasion and tissue adhesion originated in this evolutionary period. Taken together, these regularities point to the possibility that bleb and biofilm morphotypes might be important in the dissemination and persistence of B. burgdorferi inside the mammalian host. On the other hand, they prioritize the large pool of unstudied Borreliaceae-specific genes for functional characterization because this subset likely contains undiscovered Lyme disease pathogenesis genes.

Profiling of bacterial transcriptome from ultra-low input with MiniBac-seq

There is a lack of appropriate methods for preparing bacterial RNA-seq library with ultra-low amount of RNA. To address this issue, we developed miniBac-seq, a strand-specific method for high-quality library construction from sub-nanogram of total RNA, which is 100-fold lower than the current benchmark kit and dramatically reduces preparation cost ($28 + $15 × samples). We further demonstrated the high sensitivity of miniBac-seq via detecting more than 500 genes from amount of total RNA equivalent to that of a single bacterial cell. Finally, we profiled the transcriptome of growth-arrested bacteria in isogenic culture of Escherichia coli. This subpopulation of bacteria is generally low in abundance but is a potent reservoir of antibiotic persistence, and their gene expression has been largely unknown due to technical limitations. Using miniBac-seq, we identified potential molecular driver towards arrested growth as well as antibiotic tolerance. Our method thus expands the capacity to quantify bacterial transcriptome in situ, which is useful to the understanding of bacterial physiology and regulation in their native contexts.

Arginine Catabolism and Polyamine Biosynthesis Pathway Disparities Within Francisella tularensis Subpopulations

Francisella tularensis is a highly infectious zoonotic pathogen with as few as 10 organisms causing tularemia, a disease that is fatal if untreated. Although F. tularensis subspecies tularensis (type A) and subspecies holarctica (type B) share over 99.5% average nucleotide identity, notable differences exist in genomic organization and pathogenicity. The type A clade has been further divided into subtypes A.I and A.II, with A.I strains being recognized as some of the most virulent bacterial pathogens known. In this study, we report on major disparities that exist between the F. tularensis subpopulations in arginine catabolism and subsequent polyamine biosynthesis. The genes involved in these pathways include the speHEA and aguAB operons, along with metK. In the hypervirulent F. tularensis A.I clade, such as the A.I prototype strain SCHU S4, these genes were found to be intact and highly transcribed. In contrast, both subtype A.II and type B strains have a truncated speA gene, while the type B clade also has a disrupted aguA and truncated aguB. Ablation of the chromosomal speE gene that encodes a spermidine synthase reduced subtype A.I SCHU S4 growth rate, whereas the growth rate of type B LVS was enhanced. These results demonstrate that spermine synthase SpeE promotes faster replication in the F. tularensis A.I clade, whereas type B strains do not rely on this enzyme for in vitro fitness. Our ongoing studies on amino acid and polyamine flux within hypervirulent A.I strains should provide a better understanding of the factors that contribute to F. tularensis pathogenicity.

Microbial Consortia and Mixed Plastic Waste: Pangenomic Analysis Reveals Potential for Degradation of Multiple Plastic Types via Previously Identified PET Degrading Bacteria

The global utilization of single-use, non-biodegradable plastics, such as bottles made of polyethylene terephthalate (PET), has contributed to catastrophic levels of plastic pollution. Fortunately, microbial communities are adapting to assimilate plastic waste. Previously, our work showed a full consortium of five bacteria capable of synergistically degrading PET. Using omics approaches, we identified the key genes implicated in PET degradation within the consortium's pangenome and transcriptome. This analysis led to the discovery of a novel PETase, EstB, which has been observed to hydrolyze the oligomer BHET and the polymer PET. Besides the genes implicated in PET degradation, many other biodegradation genes were discovered. Over 200 plastic and plasticizer degradation-related genes were discovered through the Plastic Microbial Biodegradation Database (PMBD). Diverse carbon source utilization was observed by a microbial community-based assay, which, paired with an abundant number of plastic- and plasticizer-degrading enzymes, indicates a promising possibility for mixed plastic degradation. Using RNAseq differential analysis, several genes were predicted to be involved in PET degradation, including aldehyde dehydrogenases and several classes of hydrolases. Active transcription of PET monomer metabolism was also observed, including the generation of polyhydroxyalkanoate (PHA)/polyhydroxybutyrate (PHB) biopolymers. These results present an exciting opportunity for the bio-recycling of mixed plastic waste with upcycling potential.

Transcriptomics Reveals How Minocycline-Colistin Synergy Overcomes Antibiotic Resistance in Multidrug-Resistant Klebsiella pneumoniae

Multidrug-resistant Gram-negative bacteria are a rapidly growing public health threat, and the development of novel antimicrobials has failed to keep pace with their emergence. Synergistic combinations of individually ineffective drugs present a potential solution, yet little is understood about the mechanisms of most such combinations. Here, we show that the combination of colistin (polymyxin E) and minocycline has a high rate of synergy against colistin-resistant and minocycline-intermediate or -resistant strains of Klebsiella pneumoniae. Furthermore, using transcriptome sequencing (RNA-Seq), we characterized the transcriptional profiles of these strains when treated with the drugs individually and in combination. We found a striking similarity between the transcriptional profiles of bacteria treated with the combination of colistin and minocycline at individually subinhibitory concentrations and those of the same isolates treated with minocycline alone. We observed a similar pattern with the combination of polymyxin B nonapeptide (a polymyxin B analogue that lacks intrinsic antimicrobial activity) and minocycline. We also found that genes involved in polymyxin resistance and peptidoglycan biosynthesis showed significant differential gene expression in the different treatment conditions, suggesting possible mechanisms for the antibacterial activity observed in the combination. These findings suggest that the synergistic activity of this combination against bacteria resistant to each drug alone involves sublethal outer membrane disruption by colistin, which permits increased intracellular accumulation of minocycline.

Nanopore sequencing of RNA and cDNA molecules in Escherichia coli

High-throughput sequencing dramatically changed our view of transcriptome architectures and allowed for ground-breaking discoveries in RNA biology. Recently, sequencing of full-length transcripts based on the single-molecule sequencing platform from Oxford Nanopore Technologies (ONT) was introduced and is widely used to sequence eukaryotic and viral RNAs. However, experimental approaches implementing this technique for prokaryotic transcriptomes remain scarce. Here, we present an experimental and bioinformatic workflow for ONT RNA-seq in the bacterial model organism Escherichia coli, which can be applied to any microorganism. Our study highlights critical steps of library preparation and computational analysis and compares the results to gold standards in the field. Furthermore, we comprehensively evaluate the applicability and advantages of different ONT-based RNA sequencing protocols, including direct RNA, direct cDNA, and PCR-cDNA. We find that (PCR)-cDNA-seq offers improved yield and accuracy compared to direct RNA sequencing. Notably, (PCR)-cDNA-seq is suitable for quantitative measurements and can be readily used for simultaneous and accurate detection of transcript 5' and 3' boundaries, analysis of transcriptional units, and transcriptional heterogeneity. In summary, based on our comprehensive study, we show nanopore RNA-seq to be a ready-to-use tool allowing rapid, cost-effective, and accurate annotation of multiple transcriptomic features. Thereby nanopore RNA-seq holds the potential to become a valuable alternative method for RNA analysis in prokaryotes.

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.

“Omics” Technologies - What Have They Told Us About Uropathogenic Escherichia coli Fitness and Virulence During Urinary Tract Infection?

Uropathogenic Escherichia coli (UPEC) is the main etiological agent of urinary tract infection (UTI), a widespread infectious disease of great impact on human health. This is further emphasized by the rapidly increase in antimicrobial resistance in UPEC, which compromises UTI treatment. UPEC biology is highly complex since uropathogens must adopt extracellular and intracellular lifestyles and adapt to different niches in the host. In this context, the implementation of forefront ‘omics’ technologies has provided substantial insight into the understanding of UPEC pathogenesis, which has opened the doors for new therapeutics and prophylactics discovery programs. Thus, ‘omics’ technologies applied to studies of UPEC during UTI, or in models of UTI, have revealed extensive lists of factors that are important for the ability of UPEC to cause disease. The multitude of large ‘omics’ datasets that have been generated calls for scrutinized analysis of specific factors that may be of interest for further development of novel treatment strategies. In this review, we describe main UPEC determinants involved in UTI as estimated by ‘omics’ studies, and we compare prediction of factors across the different ‘omics’ technologies, with a focus on those that have been confirmed to be relevant under UTI-related conditions. We also discuss current challenges and future perspectives regarding analysis of data to provide an overview and better understanding of UPEC mechanisms involved in pathogenesis which should assist in the selection of target sites for future prophylaxis and treatment.

Nitrogen source as a modulator of the metabolic activity of Pedobacter lusitanus NL19: a transcriptomic approach

Secondary metabolites (SMs) are compounds with relevant biological activities. Their production under laboratory conditions, especially in broth, is still challenging. An example is the pedopeptins, which are nonribosomal peptides active against some bacteria listed by the WHO for which new antibiotics are urgently needed. Their biosynthesis is inhibited by high concentrations of peptone from casein (PC) in tryptic soy broth (TSB), and we applied a RNA-seq approach to identify Pedobacter lusitanus NL19 cellular pathways modulated by this condition. Results were validated by qPCR and revealed 261 differentially expressed genes (DEGs), 46.3% of them with a predicted biological function. Specifically, high concentration of PC significantly repressed the de novo biosynthesis of biotin (- 60X) and the production of nonribosomal peptide synthetases (NRPS) of pedopeptins (about - 14X), but no effect was observed on the expression of other NRPS. Transcription of a L-Dap synthesis operon that includes a protein with a σ⁷⁰-like domain was also reduced (about - 7X). High concentrations of PC led to a significant overexpression of MFS and RND efflux pumps and a ferrous iron uptake system, suggesting the redirection of cell machinery to export compounds such as amino acids, sugars and metal divalent cations, alongside with a slight increase of iron import. KEY POINTS: • Higher concentrations of phosphate sources highly repress many operons • High concentrations of peptone from casein (PC) cause biotin's operon repression • High concentrations of PC downregulate the production of peptides of unknown function.

Transcriptome Analysis of Rat Lungs Exposed to Moxa Smoke after Acute Toxicity Testing

The increasing use of moxibustion has led to a debate concerning the safety of this treatment in human patients. Inhalation of cigarette smoke induces lung inflammation and granulomas, the proliferation of alveolar epithelial cells, and other toxic effects; therefore, it is important to assess the influence of inhaled moxa smoke on the lungs. In the present study, a novel poisoning cabinet was designed and used to assess the acute toxicity of moxa smoke in rats. We evaluated pathological changes in rat lung tissue and analyzed differentially expressed genes (DEGs) using RNA-seq and transcriptomic analyses. Our results show that the maximum tolerable dose of moxa smoke was 290.036 g/m³ and LC50 was 537.65 g/m³. Compared with that of the control group, the degree of inflammatory cell infiltration in the lung tissues of group A rats (all dead group) was increased, while that in group E rats (all live group) remained unchanged. GO and KEGG enrichment analyses showed that the DEGs implicated in cell components, binding, and cancer were significantly enriched in the experimental groups compared with the profile of the control group. The expressions of MAFF, HSPA1B, HSPA1A, AOC1, and MX2 determined using quantitative real-time PCR were similar to those determined using RNA-seq, confirming the reliability of RNA-seq data. Overall, our results provide a basis for future evaluations of moxibustion safety and the development of moxibustion-based technology.

Transcriptomic analysis of Streptococcus agalactiae periprosthetic joint infection

Although Streptococcus agalactiae periprosthetic joint infection (PJI) is not as prevalent as staphylococcal PJI, invasive S. agalactiae infection is not uncommon. Here, RNA-seq was used to perform transcriptomic analysis of S. agalactiae PJI using fluid derived from sonication of explanted arthroplasties of subjects with S. agalactiae PJI, with results compared to those of S. agalactiae strain NEM316 grown in vitro. A total of 227 genes with outlier expression were found (164 upregulated and 63 downregulated) between PJI sonicate fluid and in vitro conditions. Functional enrichment analysis showed genes involved in mobilome and inorganic ion transport and metabolism to be most enriched. Genes involved in nickel, copper, and zinc transport, were upregulated. Among known virulence factors, cyl operon genes, encoding β-hemolysin/cytolysin, were consistently highly expressed in PJI versus in vitro. The data presented provide insight into S. agalactiae PJI pathogenesis and may be a resource for identification of novel PJI therapeutics or vaccines against invasive S. agalactiae infections.

Myxobacterial Genomics and Post-Genomics: A Review of Genome Biology, Genome Sequences and Related 'Omics Studies

Myxobacteria are fascinating and complex microbes. They prey upon other members of the soil microbiome by secreting antimicrobial proteins and metabolites, and will undergo multicellular development if starved. The genome sequence of the model myxobacterium Myxococcus xanthus DK1622 was published in 2006 and 15 years later, 163 myxobacterial genome sequences have now been made public. This explosion in genomic data has enabled comparative genomics analyses to be performed across the taxon, providing important insights into myxobacterial gene conservation and evolution. The availability of myxobacterial genome sequences has allowed system-wide functional genomic investigations into entire classes of genes. It has also enabled post-genomic technologies to be applied to myxobacteria, including transcriptome analyses (microarrays and RNA-seq), proteome studies (gel-based and gel-free), investigations into protein–DNA interactions (ChIP-seq) and metabolism. Here, we review myxobacterial genome sequencing, and summarise the insights into myxobacterial biology that have emerged as a result. We also outline the application of functional genomics and post-genomic approaches in myxobacterial research, highlighting important findings to emerge from seminal studies. The review also provides a comprehensive guide to the genomic datasets available in mid-2021 for myxobacteria (including 24 genomes that we have sequenced and which are described here for the first time).

Identification of Novel lncRNA and Differentially Expressed Genes (DEGs) of Testicular Tissues among Cattle, Yak, and Cattle-Yak Associated with Male Infertility

Simple Summary

Cattle-yak is an excellent hybrid of male cattle and female yak, which has many more outstanding production traits, such as better adaptability to high altitudes and better meat quality. However, the male sterility of cattle-yak restricts the utilization of superior heterosis. Few studies have focused on the comprehensive analysis of cattle-yak and its parents, in order to find factors on infertility of the cattle-yak. This study comprehensively analyzed the mRNA and lncRNA expression profiles of testicular tissue samples of cattle, yak, and cattle-yak by RNA-seq technology, and identified some differentially expressed genes that may be related to male sterility of cattle-yak, in order to provide a theoretical basis for solving the problem of breeding work.

Abstract

Cattle-yak is an excellent hybrid of cattle and yak; they are characterized by better meat quality and stronger adaptability of harsh environments than their parents. However, male sterility of cattle-yak lay restraints on the transmission of heterosis. In this study, next generation sequence technology was performed to profile the testicular tissues transcriptome (lncRNA and mRNA) of cattle, yak, and cattle-yak. We analyzed the features and functions of significant differentially expressed genes among the three breeds. There are 9 DE lncRNAs and 46 DE mRNAs with comparisons of cattle, yak, and cattle-yak. Among them, the upregulated targeting genes, such as IGF1 and VGLL3 of cattle-yak lncRNA, may be related to the derangement of spermatocyte maturation and cell proliferation. Similarly, we found that the LDOC1 gene, which is related to the process of cellular apoptosis, is overexpressed in cattle-yak. GO enrichment analysis demonstrated that the cattle-yak is lacking the regulation of fertilization (GO: 0009566), spermatogenesis process (GO: 0007283), male gamete generation process (GO: 0048232), sexual reproduction (GO: 0019953), and multi-organism reproductive process (GO: 0044703), such processes may play important and positive roles in spermatogenesis and fertilization. Furthermore, the KEGG enrichment analysis showed that the upregulated DEGs of cattle-yak most enriched in Apoptosis (ko04210) and Hippo signaling pathway (ko04390), may lead to excessively dead of cell and inhibit cell growth, resulting in obstruction of meiosis and spermatogenesis processes. This study will enable us to deeper understand the mechanism of male cattle-yak infertility.

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.

The Quorum Sensing Auto-Inducer 2 (AI-2) Stimulates Nitrogen Fixation and Favors Ethanol Production over Biomass Accumulation in Zymomonas mobilis

Autoinducer 2 (or AI-2) is one of the molecules used by bacteria to trigger the Quorum Sensing (QS) response, which activates expression of genes involved in a series of alternative mechanisms, when cells reach high population densities (including bioluminescence, motility, biofilm formation, stress resistance, and production of public goods, or pathogenicity factors, among others). Contrary to most autoinducers, AI-2 can induce QS responses in both Gram-negative and Gram-positive bacteria, and has been suggested to constitute a trans-specific system of bacterial communication, capable of affecting even bacteria that cannot produce this autoinducer. In this work, we demonstrate that the ethanologenic Gram-negative bacterium Zymomonas mobilis (a non-AI-2 producer) responds to exogenous AI-2 by modulating expression of genes involved in mechanisms typically associated with QS in other bacteria, such as motility, DNA repair, and nitrogen fixation. Interestingly, the metabolism of AI-2-induced Z. mobilis cells seems to favor ethanol production over biomass accumulation, probably as an adaptation to the high-energy demand of N₂ fixation. This opens the possibility of employing AI-2 during the industrial production of second-generation ethanol, as a way to boost N₂ fixation by these bacteria, which could reduce costs associated with the use of nitrogen-based fertilizers, without compromising ethanol production in industrial plants.

Next-generation microbiology: from comparative genomics to gene function

Microbiology is at a turning point in its 120-year history. Widespread next-generation sequencing has revealed genetic complexity among bacteria that could hardly have been imagined by pioneers such as Pasteur, Escherich and Koch. This data cascade brings enormous potential to improve our understanding of individual bacterial cells and the genetic basis of phenotype variation. However, this revolution in data science cannot replace established microbiology practices, presenting the challenge of how to integrate these new techniques. Contrasting comparative and functional genomic approaches, we evoke molecular microbiology theory and established practice to present a conceptual framework and practical roadmap for next-generation microbiology.

BSGatlas: a unified Bacillus subtilis genome and transcriptome annotation atlas with enhanced information access

A large part of our current understanding of gene regulation in Gram-positive bacteria is based on Bacillus subtilis, as it is one of the most well studied bacterial model systems. The rapid growth in data concerning its molecular and genomic biology is distributed across multiple annotation resources. Consequently, the interpretation of data from further B. subtilis experiments becomes increasingly challenging in both low- and large-scale analyses. Additionally, B. subtilis annotation of structured RNA and non-coding RNA (ncRNA), as well as the operon structure, is still lagging behind the annotation of the coding sequences. To address these challenges, we created the B. subtilis genome atlas, BSGatlas, which integrates and unifies multiple existing annotation resources. Compared to any of the individual resources, the BSGatlas contains twice as many ncRNAs, while improving the positional annotation for 70 % of the ncRNAs. Furthermore, we combined known transcription start and termination sites with lists of known co-transcribed gene sets to create a comprehensive transcript map. The combination with transcription start/termination site annotations resulted in 717 new sets of co-transcribed genes and 5335 untranslated regions (UTRs). In comparison to existing resources, the number of 5' and 3' UTRs increased nearly fivefold, and the number of internal UTRs doubled. The transcript map is organized in 2266 operons, which provides transcriptional annotation for 92 % of all genes in the genome compared to the at most 82 % by previous resources. We predicted an off-target-aware genome-wide library of CRISPR-Cas9 guide RNAs, which we also linked to polycistronic operons. We provide the BSGatlas in multiple forms: as a website (https://rth.dk/resources/bsgatlas/), an annotation hub for display in the UCSC genome browser, supplementary tables and standardized GFF3 format, which can be used in large scale -omics studies. By complementing existing resources, the BSGatlas supports analyses of the B. subtilis genome and its molecular biology with respect to not only non-coding genes but also genome-wide transcriptional relationships of all genes.

Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification

RNA sequencing (RNA-seq) has matured into a reliable and low-cost assay for transcriptome profiling and has been deployed across a range of systems. The computational tool space for the analysis of RNA-seq data has kept pace with advances in sequencing. Yet tool development has largely centered around the human transcriptome. While eukaryotic and prokaryotic transcriptomes are similar, key differences in transcribed units limit the transfer of wet-lab and computational tools between the two domains. The article by M. Chung, R. S. Adkins, J. S. A. Mattick, K. R. Bradwell, et al. (mSystems 6:e00917-20, 2021, https://doi.org/10.1128/mSystems.00917-20), demonstrates that integrating prokaryote-specific strategies into existing RNA-seq analyses improves read quantification. Unlike in eukaryotes, polycistronic transcripts derived from operons lead to sequencing reads that span multiple neighboring genes. Chung et al. introduce FADU, a software tool that performs a correction for such reads and thereby improves read quantification and biological interpretation of prokaryotic RNA sequencing.

Coupled Transcriptomics for Differential Expression Analysis and Determination of Transcription Start Sites: Design and Bioinformatics

The term coupled transcriptomics is coined to describe a design of an RNA-seq experiment intended for both differential expression analysis and genome-wide determination of the transcription start sites (TSS). The minimal requirements for the first analysis are two experimental conditions with at least two biological replicates enabling statistical tests. The second analysis involves the bioinformatics comparison of the data generated from a control RNA-seq library with another library enriched in primary transcripts using Terminator^™ 5'-phosphate-dependent exonuclease, in an experiment denominated differential RNA-seq (dRNA-seq). Usually, dRNA-seq is carried out with specific protocols for library construction, different of those used for common differential expression analysis. Our experimental design allows to use the same data for both analyses, reducing the number of libraries to be generated and sequenced. This is a guide for designing a coupled transcriptomics experiment and for the subsequent bioinformatics procedures. The proposed methods can be applied to the detection and study of small RNA genes.

Systems and synthetic biology to elucidate secondary metabolite biosynthetic gene clusters encoded in Streptomyces genomes

Covering: 2010 to 2020 Over the last few decades, Streptomyces have been extensively investigated for their ability to produce diverse bioactive secondary metabolites. Recent advances in Streptomyces research have been largely supported by improvements in high-throughput technology 'omics'. From genomics, numerous secondary metabolite biosynthetic gene clusters were predicted, increasing their genomic potential for novel bioactive compound discovery. Additional omics, including transcriptomics, translatomics, interactomics, proteomics and metabolomics, have been applied to obtain a system-level understanding spanning entire bioprocesses of Streptomyces, revealing highly interconnected and multi-layered regulatory networks for secondary metabolism. The comprehensive understanding derived from this systematic information accelerates the rational engineering of Streptomyces to enhance secondary metabolite production, integrated with the exploitation of the highly efficient 'Design-Build-Test-Learn' cycle in synthetic biology. In this review, we describe the current status of omics applications in Streptomyces research to better understand the organism and exploit its genetic potential for higher production of valuable secondary metabolites and novel secondary metabolite discovery.

A Review of Current and Emerging Approaches for Water Pollution Monitoring

The aquatic ecosystem is continuously threatened by the infiltration and discharge of anthropogenic wastewaters. This issue requires the unending improvement of monitoring systems to become more comprehensive and specific to targeted pollutants. This review intended to elucidate the overall aspects explored by researchers in developing better water pollution monitoring tools in recent years. The discussion is encircled around three main elements that have been extensively used as the basis for the development of monitoring methods, namely the dissolved compounds, bacterial indicator, and nucleic acids. The latest technologies applied in wastewater and surface water mapped from these key players were reviewed and categorized into physicochemical and compound characterizations, biomonitoring, and molecular approaches in taxonomical and functional analyses. Overall, researchers are continuously rallying to enhance the detection of causal source for water pollution through either conventional or mostly advanced approaches focusing on spectrometry, high-throughput sequencing, and flow cytometry technology among others. From this review’s perspective, each pollution evaluation technology has its own advantages and it would be beneficial for several aspects of pollutants assessments to be combined and established as a complementary package for better aquatic environmental management in the long run.

Gene Networks Underlying the Resistance of Bifidobacterium longum to Inflammatory Factors

As permanent residents of the normal gut microbiota, bifidobacteria have evolved to adapt to the host’s immune response whose priority is to eliminate pathogenic agents. The mechanisms that ensure the survival of commensals during inflammation and maintain the stability of the core component of the normal gut microbiota in such conditions remain poorly understood. We propose a new in vitro approach to study the mechanisms of resistance to immune response factors based on high-throughput sequencing followed by transcriptome analysis. This approach allowed us to detect differentially expressed genes associated with inflammation. In this study, we demonstrated that the presence of the pro-inflammatory cytokines IL-6 and TNFα to the growth medium of the B. longum subsp. longum GT15 strain changes the latter’s growth rate insignificantly while affecting the expression of certain genes. We identified these genes and performed a COG and a KEGG pathway enrichment analysis. Using phylogenetic profiling we predicted the operons of genes whose expression was triggered by the cytokines TNFα and IL-6 in vitro. By mapping the transcription start points, we experimentally validated the predicted operons. Thus, in this study, we predicted the genes involved in a putative signaling pathway underlying the mechanisms of resistance to inflammatory factors in bifidobacteria. Since bifidobacteria are a major component of the human intestinal microbiota exhibiting pronounced anti-inflammatory properties, this study is of great practical and scientific relevance.

PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region

Bacterial small-RNA (sRNA) sequences are functional RNAs, which play an important role in regulating the expression of a diverse class of genes. It is thus critical to identify such sRNA sequences and their probable mRNA targets. Here, we discuss new procedures to identify and characterize sRNA and their targets via the introduction of an integrated online platform 'PresRAT'. PresRAT uses the primary and secondary structural attributes of sRNA sequences to predict sRNA from a given sequence or bacterial genome. PresRAT also finds probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrates on the identification of the probable sRNA-mRNA binding regions. Using PresRAT, we have identified a total of 66,209 potential sRNA sequences from 292 bacterial genomes and 2247 potential targets from 13 bacterial genomes. We have also implemented a protocol to build and refine 3D models of sRNA and sRNA-mRNA duplex regions and generated 3D models of 50 known sRNAs and 81 sRNA-mRNA duplexes using this platform. Along with the server part, PresRAT also contains a database section, which enlists the predicted sRNA sequences, sRNA targets, and their corresponding 3D models with structural dynamics information.

Overexpression of PLIN1 Promotes Lipid Metabolism in Bovine Adipocytes

Perilipin 1 (PLIN1) is a protein encoded by the PLIN1 gene in eukaryotes. PLIN1 is a member of the PAT protein family, a family of proteins related to lipid droplet (LD) surface proteins. PLIN1 phosphorylation plays a vital role during fat metabolism of adipose tissue lipolysis and fat storage in adipocytes. However, to further explore the regulation of the PLIN1 gene on the proliferation, differentiation and lipid metabolism of bovine adipocytes. In this study, the mRNA expression of PLIN1, at day six, was the highest during bovine adipocyte differentiation. Moreover, PLIN1 can promote the proliferation and differentiation of preadipocytes in cattle. On the sixth day, after transfection with, and overexpression of, the PLIN1 gene in bovine preadipocytes via adenovirus, cell samples were collected, and transcriptome sequencing was performed. A total of 1923 differentially expressed genes were detected. Through GO and KEGG pathway analysis, the differentially expressed genes were established to be mainly enriched in the AMPK, Wnt, and PPAR signaling pathways related to fat proliferation and differentiation. In conclusion, at the transcriptional level, PLIN1 plays an important role in regulating fat proliferation and metabolism. Additionally, the sequencing results screened new differentially expressed genes related to fat metabolism, providing theoretical support for molecular breeding of Qinchuan beef cattle.

Combined Transcriptome Sequencing of Mycoplasma hyopneumoniae and Infected Pig Lung Tissue Reveals Up-Regulation of Bacterial F1-Like ATPase and Down-Regulation of the P102 Cilium Adhesin in vivo

Mycoplasma hyopneumoniae (M. hyopneumoniae) causes enzootic pneumonia in pigs but it is still largely unknown which host-pathogen interactions enable persistent infection and cause disease. In this study, we analyzed the host and bacterial transcriptomes during infection using RNA sequencing. Comparison of the transcriptome of lung lesion tissue from infected pigs with lung tissue from non-infected animals, identified 424 differentially expressed genes (FDR < 0.01 and fold change > 1.5LOG2). These genes were part of the following major pathways of the immune system: interleukin signaling (type 4, 10, 13, and 18), regulation of Toll-like receptors by endogenous ligand and activation of C3 and C5 in the complement system. Besides analyzing the lung transcriptome, a sampling protocol was developed to obtain enough bacterial mRNA from infected lung tissue for RNA sequencing. This was done by flushing infected lobes in the lung, and subsequently enriching for bacterial RNA. On average, 2.2 million bacterial reads were obtained per biological replicate to analyze the bacterial in vivo transcriptome. We compared the in vivo bacterial transcriptome with the transcriptome of bacteria grown in vitro and identified 22 up-regulated and 30 down-regulated genes (FDR < 0.01 and fold change > 2LOG2). Six out of seven genes in the operon encoding the mycoplasma specific F1-like ATPase (MHP_RS02445-MHP_RS02475) and all genes in the operon MHP_RS01965-MHP_RS01990 with functions related to nucleotide metabolism, spermidine transport and glycerol-3-phoshate transport were up-regulated in vivo. Down-regulated in vivo were genes related to glycerol uptake, cilium adhesion (P102), cell division and myo-inositol metabolism. In addition to providing a novel method to isolate bacterial mRNA from infected lung, this study provided insights into changes in gene expression during infection, which could help development of novel treatment strategies against enzootic pneumonia caused by M. hyopneumoniae.

Improved bacterial RNA-seq by Cas9-based depletion of ribosomal RNA reads

A major challenge for RNA-seq analysis of gene expression is to achieve sufficient coverage of informative nonribosomal transcripts. In eukaryotic samples, this is typically achieved by selective oligo(dT)-priming of messenger RNAs to exclude ribosomal RNA (rRNA) during cDNA synthesis. However, this strategy is not compatible with prokaryotes in which functional transcripts are generally not polyadenylated. To overcome this, we adopted DASH (depletion of abundant sequences by hybridization), initially developed for eukaryotic cells, to improve both the sensitivity and depth of bacterial RNA-seq. DASH uses the Cas9 nuclease to remove unwanted cDNA sequences prior to library amplification. We report the design, evaluation, and optimization of DASH experiments for standard bacterial short-read sequencing approaches, including software for automated guide RNA (gRNA) design for Cas9-mediated cleavage in bacterial rDNA sequences. Using these gRNA pools, we effectively removed rRNA reads (56%-86%) in RNA-seq libraries from two different model bacteria, the Gram-negative pathogen Salmonella enterica and the anaerobic gut commensal Bacteroides thetaiotaomicron DASH works robustly, even with subnanogram amounts of input RNA. Its efficiency, high sensitivity, ease of implementation, and low cost (∼$5 per sample) render DASH an attractive alternative to rRNA removal protocols, in particular for material-constrained studies where conventional ribodepletion techniques fail.

Small Noncoding RNA CjNC110 Influences Motility, Autoagglutination, AI-2 Localization, Hydrogen Peroxide Sensitivity, and Chicken Colonization in Campylobacter jejuni

Small noncoding RNAs (ncRNAs) are involved in many important physiological functions in pathogenic microorganisms. Previous studies have identified the presence of noncoding RNAs in the major zoonotic pathogen Campylobacter jejuni; however, few have been functionally characterized to date. CjNC110 is a conserved ncRNA in C. jejuni, located downstream of the luxS gene, which is responsible for the production of the quorum sensing molecule autoinducer-2 (AI-2). In this study, we utilized strand specific high-throughput RNAseq to identify potential targets or interactive partners of CjNC110 in a sheep abortion clone of C. jejuni These data were then utilized to focus further phenotypic evaluation of the role of CjNC110 in motility, autoagglutination, quorum sensing, hydrogen peroxide sensitivity, and chicken colonization in C. jejuni Inactivation of the CjNC110 ncRNA led to a statistically significant decrease in autoagglutination ability as well as increased motility and hydrogen peroxide sensitivity compared to the wild-type. Extracellular AI-2 detection was decreased in ΔCjNC110; however, intracellular AI-2 accumulation was significantly increased, suggesting a key role of CjNC110 in modulating the transport of AI-2. Notably, ΔCjNC110 also showed a decreased ability to colonize chickens. Complementation of CjNC110 restored all phenotypic changes back to wild-type levels. The collective results of the phenotypic and transcriptomic changes observed in our data provide valuable insights into the pathobiology of C. jejuni sheep abortion clone and strongly suggest that CjNC110 plays an important role in the regulation of energy taxis, flagellar glycosylation, cellular communication via quorum sensing, oxidative stress tolerance, and chicken colonization in this important zoonotic pathogen.

Distinct transcriptome signatures of Helicobacter suis and Helicobacter heilmannii strains upon adherence to human gastric epithelial cells

The porcine Helicobacter suis and canine-feline H. heilmannii are gastric Helicobacter species with zoonotic potential. However, little is known about the pathogenesis of human infections with these Helicobacter species. To gain more insight into the interactions of both zoonotic Helicobacter species with human gastric epithelial cells, we investigated bacterial genes that are differentially expressed in a H. suis and H. heilmannii strain after adhesion to the human gastric epithelial cell line MKN7. In vitro Helicobacter-MKN7 binding assays were performed to obtain bacterial RNA for sequencing analysis. H. suis and H. heilmannii bacteria attached to the gastric epithelial cells (i.e. cases) as well as unbound bacteria (i.e. controls) were isolated, after which prokaryotic RNA was purified and sequenced. Differentially expressed genes were identified using the DESeq2 package and SARTools pipeline in R. A list of 134 (83 up-regulated and 51 down-regulated) and 143 (60 up-regulated and 83 down-regulated) differentially expressed genes (p_adj ≤ 0.01; fold change ≥ 2) were identified for the adherent H. suis and H. heilmannii strains, respectively. According to BLASTp analyses, only 2 genes were commonly up-regulated and 4 genes commonly down-regulated in both pathogens. Differentially expressed genes of the H. suis and H. heilmannii strains belonged to multiple functional classes, indicating that adhesion of both strains to human gastric epithelial cells evokes pleiotropic adaptive responses. Our results suggest that distinct pathways are involved in human gastric colonization of H. suis and H. heilmannii. Further research is needed to elucidate the clinical significance of these findings.

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.

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.

Valine-Induced Isoleucine Starvation in Escherichia coli K-12 Studied by Spike-In Normalized RNA Sequencing

Escherichia coli cells respond to a period of famine by globally reorganizing their gene expression. The changes are known as the stringent response, which is orchestrated by the alarmone ppGpp that binds directly to RNA polymerase. The resulting changes in gene expression are particularly well studied in the case of amino acid starvation. We used deep RNA sequencing in combination with spike-in cells to measure global changes in the transcriptome after valine-induced isoleucine starvation of a standard E. coli K12 strain. Owing to the whole-cell spike-in method that eliminates variations in RNA extraction efficiency between samples, we show that ribosomal RNA levels are reduced during isoleucine starvation and we quantify how the change in cellular RNA content affects estimates of gene regulation. Specifically, we show that standard data normalization relying on sample sequencing depth underestimates the number of down-regulated genes in the stringent response and overestimates the number of up-regulated genes by approximately 40%. The whole-cell spike-in method also made it possible to quantify how rapidly the pool of total messenger RNA (mRNA) decreases upon amino acid starvation. A principal component analysis showed that the first two components together described 69% of the variability of the data, underlining that large and highly coordinated regulons are at play in the stringent response. The induction of starvation by sudden addition of high valine concentrations provoked prominent regulatory responses outside of the expected ppGpp, RpoS, and Lrp regulons. This underlines the notion that with the high resolution possible in deep RNA sequencing analysis, any different starvation method (e.g., nitrogen-deprivation, removal of an amino acid from an auxotroph strain, or valine addition to E. coli K12 strains) will produce measurable variations in the stress response produced by the cells to cope with the specific treatment.

De novo transcriptome analysis of halotolerant bacterium Staphylococcus sp. strain P-TSB-70 isolated from East coast of India: In search of salt stress tolerant genes

In the present study, we identified salt stress tolerant genes from the marine bacterium Staphylococcus sp. strain P-TSB-70 through transcriptome sequencing. In favour of whole-genome transcriptome profiling of Staphylococcus sp. strain P-TSB-70 (GenBank Accn. No. KP117091) which tolerated upto 20% NaCl stress, the strain was cultured in the laboratory condition with 20% NaCl stress. Transcriptome analyses were performed by SOLiD4.0 sequencing technology from which 10280 and 9612 transcripts for control and treated, respectively, were obtained. The coverage per base (CPB) statistics were analyzed for both the samples. Gene ontology (GO) analysis has been categorized at varied graph levels based on three primary ontology studies viz. cellular components, biological processes, and molecular functions. The KEGG analysis of the assembled transcripts using KAAS showed presumed components of metabolic pathways which perhaps implicated in diverse metabolic pathways responsible for salt tolerance viz. glycolysis/gluconeogenesis, oxidative phosphorylation, glutathione metabolism, etc. further involving in salt tolerance. Overall, 90 salt stress tolerant genes were identified as of 186 salt-related transcripts. Several genes have been found executing normally in the TCA cycle pathway, integral membrane proteins, generation of the osmoprotectants, enzymatic pathway associated with salt tolerance. Recognized genes fit diverse groups of salt stress genes viz. abc transporter, betaine, sodium antiporter, sodium symporter, trehalose, ectoine, and choline, that belong to different families of genes involved in the pathway of salt stress. The control sample of the bacterium showed elevated high proportion of transcript contigs (29%) while upto 20% salt stress treated sample of the bacterium showed a higher percentage of transcript contigs (31.28%). A total of 1,288 and 1,133 transcript contigs were measured entirely as novel transcript contigs in both control and treated samples, respectively. The structure and function of 10 significant salt stress tolerant genes of Staphylococcus sp. have been analyzed in this study. The information acquired in the present study possibly used to recognize and clone the salt stress tolerant genes and support in developing the salt stress-tolerant plant varieties to expand the agricultural productivity in the saline system.

RNA-Seq Analysis Identifies Differentially Expressed Genes Insubcutaneous Adipose Tissuein Qaidamford Cattle, Cattle-Yak, and Angus Cattle

Simple Summary

Fat content is an important factor affecting beef quality. Therefore, the screening and identification of differentially expressed genes in adipose tissue between different breeds (Qaidamford cattle, hybrid cattle-yak, and Angus cattle) by RNA high-throughput sequencing can provide useful information to the beef cattle industry. The aim of this work was to identify candidate genes of adipose tissue for future beef breeding efforts. Comparative analysis revealed a significant difference between hybrid cattle and Angus, but the difference between hybrid cattle varieties (cattle-yak vs. Qaidamford cattle) was not significant. Gene ontology (GO) and KEGG pathway enrichment analysis indicated that some differentially expressed genes are involved in lipid metabolism-related biological processes and signaling pathways associated with cell metabolism, such as extracellular matrix (ECM)-receptor interaction and the PI3K-Akt signal pathway. The expression levels of some of the identified genes were further verified by reverse transcription quantitative polymerase chain reaction (RT-qPCR). These data will be helpful for further investigations of meat quality and breeding efforts for different cattle breeds.

Abstract

In the beef industry, fat tissue is closely related to meat quality. In this study, high-throughput RNA sequencing was utilized for adipose tissue transcriptome analysis between cattle-yak, Qaidamford cattle, and Angus cattle. The screening and identification of differentially expressed genes (DEGs) between different breeds of cattle would facilitate cattle breeding. Compared to Angus cattle adipose tissue, a total of 4167 DEGs were identified in cattle-yak adipose tissue and 3269 DEGs were identified in Qaidamford cattle adipose tissue. Considering cattle-yak as a control group, 154 DEGs were identified in Qaidamford cattle adipose tissue. GO analysis indicated the significant enrichment of some DEGs related to lipid metabolism. The KEGG pathway database was also used to map DEGs and revealed that most annotated genes were involved in ECM-receptor interaction and the PI3K-Akt signal pathway, which are closely related to cell metabolism. Eight selected DEGs related to adipose tissue development or metabolism were verified by RT-qPCR, indicating the reliability of the RNA-seq data. The results of this comparative transcriptome analysis of adipose tissue and screening DEGs suggest several candidates for further investigations of meat quality in different cattle breeds.

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.

Sequencing-based methods and resources to study antimicrobial resistance

Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.

Preparation of Vibrio cholerae Samples for RNA-seq Analysis

Massively parallel cDNA sequencing (RNA-seq) is a powerful tool for providing an unbiased approach to assess transcript abundance under a variety of conditions. In comparison to microarrays, this technique provides increased resolution and sensitivity and the ability to identify rare transcripts and sRNAs. Here, we describe the sample preparation (based on Illumina technology) used for transcriptomic analysis of V. cholerae cDNA libraries. We describe the entire process from RNA isolation through to the generation of barcoded cDNA libraries ready for sequencing.

Antibiotic Discovery: Where Have We Come from, Where Do We Go?

Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.