Prokaryotic transcriptomics: a new view on regulation, physiology and pathogenicity

An improved bacterial mRNA enrichment strategy in dual RNA sequencing to unveil the dynamics of plant-bacterial interactions

BACKGROUND

Dual RNA sequencing is a powerful tool that enables a comprehensive understanding of the molecular dynamics underlying plant-microbe interactions. RNA sequencing (RNA-seq) poses technical hurdles in the transcriptional analysis of plant-bacterial interactions, especially in bacterial transcriptomics, owing to the presence of abundant ribosomal RNA (rRNA), which potentially limits the coverage of essential transcripts. Therefore, to achieve cost-effective and comprehensive sequencing of the bacterial transcriptome, it is imperative to devise efficient methods for eliminating rRNA and enhancing the proportion of bacterial mRNA. In this study, we modified a strand-specific dual RNA-seq method with the goal of enriching the proportion of bacterial mRNA in the bacteria-infected plant samples. The enriched method involved the sequential separation of plant mRNA by poly A selection and rRNA removal for bacterial mRNA enrichment followed by strand specific RNA-seq library preparation steps. We assessed the efficiency of the enriched method in comparison to the conventional method by employing various plant-bacterial interactions, including both host and non-host resistance interactions with pathogenic bacteria, as well as an interaction with a beneficial rhizosphere associated bacteria using pepper and tomato plants respectively.

RESULTS

In all cases of plant-bacterial interactions examined, an increase in mapping efficiency was observed with the enriched method although it produced a lower read count. Especially in the compatible interaction with Xanthmonas campestris pv. Vesicatoria race 3 (Xcv3), the enriched method enhanced the mapping ratio of Xcv3-infected pepper samples to its own genome (15.09%; 1.45-fold increase) and the CDS (8.92%; 1.49-fold increase). The enriched method consistently displayed a greater number of differentially expressed genes (DEGs) than the conventional RNA-seq method at all fold change threshold levels investigated, notably during the early stages of Xcv3 infection in peppers. The Gene Ontology (GO) enrichment analysis revealed that the DEGs were predominantly enriched in proteolysis, kinase, serine type endopeptidase and heme binding activities.

CONCLUSION

The enriched method demonstrated in this study will serve as a suitable alternative to the existing RNA-seq method to enrich bacterial mRNA and provide novel insights into the intricate transcriptomic alterations within the plant-bacterial interplay.

Temporal development and potential interactions between the gut microbiome and resistome in early childhood

Antimicrobial resistance-associated infections have become a major threat to global health. The gut microbiome serves as a major reservoir of bacteria with antibiotic resistance genes; whereas, the temporal development of gut resistome during early childhood and the factors influencing it remain unclear. Moreover, the potential interactions between gut microbiome and resistome still need to be further explored. In this study, we found that antibiotic treatment led to destabilization of the gut microbiome and resistome structural communities, exhibiting a greater impact on the resistome than on the microbiome. The composition of the gut resistome at various developmental stages was influenced by the abundance and richness of different core microbes. First exposure to antibiotics led to a dramatic increase in the number of opportunistic pathogens carrying multidrug efflux pump encoding genes. Multiple factors could influence the gut microbiome and resistome formation. The data may provide new insights into early-life research.IMPORTANCEIn recent years, the irrational or inappropriate use of antibiotics, an important life-saving medical intervention, has led to the emergence and increase of drug-resistant and even multidrug-resistant bacteria. It remains unclear how antibiotic exposure affects various developmental stages of early childhood and how gut core microbes under antibiotic exposure affect the structural composition of the gut resistome. In this study, we focused on early antibiotic exposure and analyzed these questions in detail using samples from infants at various developmental stages. The significance of our research is to elucidate the impact of early antibiotic exposure on the dynamic patterns of the gut resistome in children and to provide new insights for early-life studies.

Transcriptome analysis reveals the underlying mechanism for over-accumulation of alkaline protease in Bacillus licheniformis

AIMS

Bacillus licheniformis AQ is an industrial strain with high production of alkaline protease (AprE), which has great industrial application value. However, how to regulate the production of AprE in the process of industrial fermentation is still not completely clear. Therefore, it is important to understand the metabolic process of AprE production in the industrial fermentation medium.

METHODS AND RESULTS

In this study, transcriptome sequencing of the whole fermentation course was performed to explore the synthesis and regulation mechanism of AprE in B. licheniformis AQ. During the fermentation process, the AprE got continuously accumulated, reaching a peak of 42 020 U/mL at the fermentation endpoint (48 h). Meanwhile, the highly expressed genes were observed. Compared with the fermentation endpoint, there were 61 genes in the intersection of differentially expressed genes, functioning as catabolic processes, peptidases and inhibitors, chaperones, and folding catalysts. Furthermore, the protein-protein interactions network of AprE was constructed.

CONCLUSION

This study provides important transcriptome information for B. licheniformis AQ and potential molecular targets for further improving the production of AprE.

Leptospira transcriptome sequencing using long-read technology reveals unannotated transcripts and potential polyadenylation of RNA molecules

IMPORTANCE

Leptospirosis, caused by the spirochete bacteria Leptospira, is a zoonotic disease of humans and animals, accounting for over 1 million annual human cases and over 60,000 deaths. We have characterized operon transcriptional units, identified novel RNA coding regions, and reported evidence of potential posttranscriptional polyadenylation in the Leptospira transcriptomes for the first time using Oxford Nanopore Technology RNA sequencing protocols. The newly identified RNA coding regions and operon transcriptional units were detected only in the pathogenic Leptospira transcriptomes, suggesting their significance in virulence-related functions. This article integrates bioinformatics, infectious diseases, microbiology, molecular biology, veterinary sciences, and public health. Given the current knowledge gap in the regulation of leptospiral pathogenicity, our findings offer valuable insights to researchers studying leptospiral pathogenicity and provide both a basis and a tool for researchers focusing on prokaryotic molecular studies for the understanding of RNA compositions and prokaryotic polyadenylation for their organisms of interest.

Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq

Bacteria colonize almost all parts of the human body and can differ significantly. However, the population level transcriptomics measurements can only describe the average bacteria population behaviors, ignoring the heterogeneity among bacteria. Here, we report a droplet-based high-throughput single-microbe RNA-seq assay (smRandom-seq), using random primers for in situ cDNA generation, droplets for single-microbe barcoding, and CRISPR-based rRNA depletion for mRNA enrichment. smRandom-seq showed a high species specificity (99%), a minor doublet rate (1.6%), a reduced rRNA percentage (32%), and a sensitive gene detection (a median of ~1000 genes per single E. coli). Furthermore, smRandom-seq successfully captured transcriptome changes of thousands of individual E. coli and discovered a few antibiotic resistant subpopulations displaying distinct gene expression patterns of SOS response and metabolic pathways in E. coli population upon antibiotic stress. smRandom-seq provides a high-throughput single-microbe transcriptome profiling tool that will facilitate future discoveries in microbial resistance, persistence, microbe-host interaction, and microbiome research.

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

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

Longitudinal Changes in Milk Microorganisms in the First Two Months of Lactation of Primiparous and Multiparous Cows

The present experiment was carried out to analyze the longitudinal changes in milk microorganisms. For this purpose, milk samples were collected from 12 healthy cows (n = 96; six primiparous cows and six multiparous cows) at eight different time points. The characteristics and variations in microbial composition were analyzed by 16S rRNA gene high-throughput sequencing. In the primiparous group, higher and more stable alpha diversity was observed in transitional and mature milk compared with the colostrum, with no significant difference in alpha diversity at each time point in the multiparous group. Proteobacteria, Firmicutes, Bacteroidota, and Actinobacteriota were the most dominant phyla, and Pseudomonas, UCG-005, Acinetobacter, Vibrio, Lactobacillus, Bacteroides, Serratia, Staphylococcus, and Glutamicibacter were the most dominant genera in both primiparous and multiparous cow milk. Some typically gut-associated microbes, such as Bacteroides, UCG-005, and Rikenellaceae_RC9_gut_group, etc., were enriched in the two groups. Biomarker taxa with the day in time (DIM) were identified by a random forest algorithm, with Staphylococcus showing the highest degree of interpretation, and the difference in milk microbiota between the two groups was mainly reflected in 0 d-15 d. Additionally, network analysis suggested that there were bacteria associated with the total protein content in milk. Collectively, our results disclosed the longitudinal changes in the milk microbiota of primiparous and multiparous cows, providing further evidence in dairy microbiology.

Overexpression of mcr-1 disrupts cell envelope synthesis and causes the dysregulation of carbon metabolism, redox balance and nucleic acids

Rapid dissemination of plasmid-borne polymyxin resistance mcr-1 genes threatens the efficacy of polymyxins. Acquisition of mcr-1 imposes a fitness cost on bacteria. The identification of the molecular mechanisms underpinning this fitness cost will help in the development of adjunctive antimicrobial therapies that target polymyxin-resistant Gram-negative pathogens. We employed phenotypic assays and transcriptomics to investigate the impact of mcr-1 expression on membrane characteristics and transcriptomic responses in E. coli TOP10 carrying the empty vector pBAD (TOP10+pBAD) and harboring pBAD-mcr-1 (TOP10+pBAD-mcr-1). The overexpression of mcr-1 increased outer membrane permeability and caused membrane depolarization, reflective of the transcriptomic results that showed downregulation of multiple genes involved in lipopolysaccharide core and O-antigen biosynthesis. Overexpression of mcr-1 also caused considerable gene expression changes in pathways involving carbohydrate metabolism (phosphotransferase system, pentose phosphate pathway, and pantothenate and coenzyme A biosynthesis), ABC transporters and intracellular responses to stress, especially those associated with oxidative and nucleic acid damage. Expression of mcr-1 also triggered the production of reactive oxygen species. Collectively, these findings indicate that overexpression of mcr-1 results in persistent transcriptomic changes that primarily involve disruption to cell envelope synthesis via the reduction of LPS modifications, as well as dysregulation of carbon metabolism, redox balance and nucleic acids. These consequences of expression dysregulation may act as the main factors that impose a fitness cost with mcr-1 expression.

Expressions of resistome is linked to the key functions and stability of active rumen microbiome

BACKGROUND

The resistome describes the array of antibiotic resistant genes (ARGs) present within a microbial community. Recent research has documented the resistome in the rumen of ruminants and revealed that the type and abundance of ARGs could be affected by diet and/or antibiotic treatment. However, most of these studies only assessed ARGs using metagenomics, and expression of the resistome and its biological function within the microbiome remains largely unexplored.

RESULTS

We characterized the pools of ARGs (resistome) and their activities in the rumen of 48 beef cattle belonging to three breeds (Angus, Charolais, Kinsella composite hybrid), using shotgun metagenomics and metatranscriptomics. Sixty (including 20 plasmid-associated) ARGs were expressed which accounted for about 30% of the total number of ARGs (187) identified in metagenomic datasets, with tetW and mefA exhibiting the highest level of expression. In addition, the bacterial hosts of 17 expressed ARGs were identified. The active resistome was less diverse in Kinsella composite hybrid than Angus, however, expression of ARGs did not differ among breeds. Although not associated with feed efficiency, the total abundance of expressed ARGs was positively correlated with metabolic pathways and 'attenuation values' (a measurement of stability) of the active rumen microbiome, suggesting that ARGs expression influences the stability and functionality of the rumen microbiome. Moreover, Ruminococcus spp., Prevotella ruminicola, Muribaculaceae spp. and Collinsella aerofaciens were all identified as hosts of expressed ARGs, possibly promoting the dominance of these carbohydrate degraders within the rumen microbiome.

CONCLUSIONS

Findings from this study provide new insight into the active rumen resistome in vivo, which may inform strategies to limit the spread of ubiquitously found ARGs from the rumen to the broader environment without negatively impacting the key functional outcomes of the rumen microbiome.

Integrated metagenomic and metatranscriptomic analysis reveals actively expressed antibiotic resistomes in the plastisphere

The plastisphere is viewed as a reservoir for the antibiotic resistome in water environments and may pose health concerns. However, the expression profiles of the resistome in the plastisphere are largely unknown. Here, we profiled the occurrence, abundance, and transcriptional level of antibiotic resistance genes (ARGs), plasmid associated ARGs, microbial composition and ARG bacterial hosts in the plastisphere and urban river water using 16S rRNA gene sequencing, metagenomic sequencing, and metatranscriptomic sequencing methods. A total of 173 ARGs conferring resistance to 24 major classes of antibiotics commonly prescribed to humans and animals were detected in the plastisphere. Of these, 75 genes were observed with transcriptional activity, indicating that the antibiotic resistome in the plastisphere was not only present, but also actively expressed. Human pathogens belonging to family Enterobacteriaceae were identified as bacterial hosts of ARGs in the plastisphere. The opportunistic and multidrug resistant human pathogen Enterobacter cloacae was found to actively express tetG and confer tetracycline resistance to the plastisphere. Furthermore, 39 genes were identified as "plasmid associated ARGs" in the plastisphere, displaying a higher proportion of transcript abundance compared with water. The above results suggest that the plastisphere is a hotspot for antibiotic resistome acquisition, expression, and dissemination.

Can polymer-degrading microorganisms solve the bottleneck of plastics' environmental challenges?

Increasing world population and industrial activities have enhanced anthropogenic pollution, plastic pollution being especially alarming. So, plastics should be recycled and/or make them biodegradable. Chemical and physical remediating methods are usually energy consuming and costly. In addition, they are not ecofriendly and usually produce toxic byproducts. Bioremediation is a proper option as it is cost-efficient and environmentally friendly. Plastic production and consumption are increasing daily, and, as a consequence, more microorganisms are exposed to these nonbiodegradable polymers. Therefore, investigating new efficient microorganisms and increasing the knowledge about their biology can pave the way for efficient and feasible plastic bioremediation processes. In this sense, omics, systems biology and bioinformatics are three important fields to analyze the biodegradation pathways in microorganisms. Based on the above-mentioned technologies, researchers can engineer microorganisms with specific desired properties to make bioremediation more efficient.

Vibrio splendidus virulence to Apostichopus japonicus is mediated by hppD through glutamate metabolism and flagellum assembly

Vibrio splendidus is the main opportunistic pathogen that causes skin ulcer syndrome in Apostichopus japonicus. hppDIn the present study, mutant V. splendidus with an in-frame deletion of hppDV.s. (MTVs) was constructed. The median lethal doses of wild-type V. splendidus (WTVs) and MTVs were 5.129 × 10⁶ and 2.606 × 10¹⁰ CFU mL⁻¹, respectively. RNA-Seq was performed using WTVs and MTVs cells at different growth stages to explore the mechanisms of the pathogenesis mediated by hppDV.s. Gene Ontology analysis showed that the expression levels of 105 genes involved in amino acid metabolism and protein binding were remarkably different between MTVs and WTVs. Kyoto Encyclopedia of Genes and Genomes analysis showed that the pathways of glutamate metabolism and flagellum assembly involved in biofilm formation and swarming motility were suppressed in MTVs. Correspondingly, the swarming motility, biofilm formation and colonisation of MTVs were remarkably decreased compared with those of WTVs. The results showed that 4-hppD catalyses tyrosine into fumarate, which could enhance glutamate metabolism and ATP production; promote flagellum assembly through the TCA cycle and lead to higher swarming, biofilm formation and colonisation abilities, to contribute to the pathogenesis of V. splendidus.

Bacterial Transcriptional Regulators: A Road Map for Functional, Structural, and Biophysical Characterization

The different niches through which bacteria move during their life cycle require a fast response to the many environmental queues they encounter. The sensing of these stimuli and their correct response is driven primarily by transcriptional regulators. This kind of protein is involved in sensing a wide array of chemical species, a process that ultimately leads to the regulation of gene transcription. The allosteric-coupling mechanism of sensing and regulation is a central aspect of biological systems and has become an important field of research during the last decades. In this review, we summarize the state-of-the-art techniques applied to unravel these complex mechanisms. We introduce a roadmap that may serve for experimental design, depending on the answers we seek and the initial information we have about the system of study. We also provide information on databases containing available structural information on each family of transcriptional regulators. Finally, we discuss the recent results of research about the allosteric mechanisms of sensing and regulation involving many transcriptional regulators of interest, highlighting multipronged strategies and novel experimental techniques. The aim of the experiments discussed here was to provide a better understanding at a molecular level of how bacteria adapt to the different environmental threats they face.

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.

Athermal, Chemically Triggered Release of RNA from Thioester Nucleic Acids

An athermal approach to mRNA enrichment from total RNA using a self-immolative thioester linked nucleic acids (TENA) is described. Oligo(thymine) (oT) TENA has a six-atom spacing between bases which allowed TENA to selectively base-pair with polyadenine RNA. As a result of the neutral backbone of TENA and the hydrophobicity of the octanethiol end group, oT TENA is water insoluble and efficiently pulled down 93±2 % of EGFP mRNA at a concentration of 10 ng μL^-1 . Self-immolative degradation of TENA upon ambient temperature exposure to nucleophilic buffer components (Tris, DTT) allowed recovery of 55±27 ng of mRNA from 3.1 μg of total RNA, which was not statistically different from the amount recovered using Dynabeads® mRNA DIRECT Kit (89±24 ng). Gene expression as measured by RT-qPCR was comparable for both enrichment methods, suggesting that the mild conditions required for enrichment of mRNA using oT TENA are compatible with RT-qPCR and other downstream molecular biology applications.

Dual RNA-Seq of Trunk Kidneys Extracted From Channel Catfish Infected With Yersinia ruckeri Reveals Novel Insights Into Host-Pathogen Interactions

Host-pathogen intectarions are complex, involving large dynamic changes in gene expression through the process of infection. These interactions are essential for understanding anti-infective immunity as well as pathogenesis. In this study, the host-pathogen interaction was analyzed using a model of acute infection where channel catfish were infected with Yersinia ruckeri. The infected fish showed signs of body surface hyperemia as well as hyperemia and swelling in the trunk kidney. Double RNA sequencing was performed on trunk kidneys extracted from infected channel catfish and transcriptome data was compared with data from uninfected trunk kidneys. Results revealed that the host-pathogen interaction was dynamically regulated and that the host-pathogen transcriptome fluctuated during infection. More specifically, these data revealed that the expression levels of immune genes involved in Cytokine-cytokine receptor interactions, the NF-kappa B signaling pathway, the JAK-STAT signaling pathway, Toll-like receptor signaling and other immune-related pathways were significantly upregulated. Y. ruckeri mainly promote pathogenesis through the flagellum gene fliC in channel catfish. The weighted gene co-expression network analysis (WGCNA) R package was used to reveal that the infection of catfish is closely related to metabolic pathways. This study contributes to the understanding of the host-pathogen interaction between channel catfish and Y. ruckeri, more specifically how catfish respond to infection through a transcriptional perspective and how this infection leads to enteric red mouth disease (ERM) in these fish.

Assessing the involvement of the placental microbiome and virome in preeclampsia using non coding RNA sequencing

OBJECTIVES

Preeclampsia is a dangerous pregnancy complication. The source of preeclampsia is unknown, though the placenta is believed to have a central role in its pathogenesis. An association between maternal infection and preeclampsia has been demonstrated, yet the involvement of the placental microbiome in the etiology of preeclampsia has not been determined. In this study, we examined whether preeclampsia is associated with an imbalanced microorganism composition in the placenta.

METHODS

To this end, we developed a novel method for the identification of bacteria/viruses based on sequencing of small non-coding RNA, which increases the microorganism-to-host ratio, this being a major challenge in microbiome methods. We validated the method on various infected tissues and demonstrated its efficiency in detecting microorganisms in samples with extremely low bacterial/viral biomass. We then applied the method to placenta specimens from preeclamptic and healthy pregnancies. Since the placenta is a remarkably large and heterogeneous organ, we explored the bacterial and viral RNA at each of 15 distinct locations.

RESULTS

Bacterial RNA was detected at all locations and was consistent with previous studies of the placental microbiome, though without significant differences between the preeclampsia and control groups. Nevertheless, the bacterial RNA composition differed significantly between various areas of the placenta. Viral RNA was detected in extremely low quantities, below the threshold of significance, thus viral abundance could not be determined.

CONCLUSIONS

Our results suggest that the bacterial and viral abundance in the placenta may have only limited involvement in the pathogenesis of preeclampsia. The evidence of a heterogenic bacterial RNA composition in the various placental locations warrants further investigation to capture the true nature of the placental microbiome.

Characterization of the Chimeric PriB-SSBc Protein

PriB is a primosomal protein required for the replication fork restart in bacteria. Although PriB shares structural similarity with SSB, they bind ssDNA differently. SSB consists of an N-terminal ssDNA-binding/oligomerization domain (SSBn) and a flexible C-terminal protein–protein interaction domain (SSBc). Apparently, the largest difference in structure between PriB and SSB is the lack of SSBc in PriB. In this study, we produced the chimeric PriB-SSBc protein in which Klebsiella pneumoniae PriB (KpPriB) was fused with SSBc of K. pneumoniae SSB (KpSSB) to characterize the possible SSBc effects on PriB function. The crystal structure of KpSSB was solved at a resolution of 2.3 Å (PDB entry 7F2N) and revealed a novel 114-GGRQ-117 motif in SSBc that pre-occupies and interacts with the ssDNA-binding sites (Asn14, Lys74, and Gln77) in SSBn. As compared with the ssDNA-binding properties of KpPriB, KpSSB, and PriB-SSBc, we observed that SSBc could significantly enhance the ssDNA-binding affinity of PriB, change the binding behavior, and further stimulate the PriA activity (an initiator protein in the pre-primosomal step of DNA replication), but not the oligomerization state, of PriB. Based on these experimental results, we discuss reasons why the properties of PriB can be retrofitted when fusing with SSBc.

Specific and Global RNA Regulators in Pseudomonas aeruginosa

Pseudomonas aeruginosa (Pae) is an opportunistic pathogen showing a high intrinsic resistance to a wide variety of antibiotics. It causes nosocomial infections that are particularly detrimental to immunocompromised individuals and to patients suffering from cystic fibrosis. We provide a snapshot on regulatory RNAs of Pae that impact on metabolism, pathogenicity and antibiotic susceptibility. Different experimental approaches such as in silico predictions, co-purification with the RNA chaperone Hfq as well as high-throughput RNA sequencing identified several hundreds of regulatory RNA candidates in Pae. Notwithstanding, using in vitro and in vivo assays, the function of only a few has been revealed. Here, we focus on well-characterized small base-pairing RNAs, regulating specific target genes as well as on larger protein-binding RNAs that sequester and thereby modulate the activity of translational repressors. As the latter impact large gene networks governing metabolism, acute or chronic infections, these protein-binding RNAs in conjunction with their cognate proteins are regarded as global post-transcriptional regulators.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

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

Transcriptional response to prolonged perchlorate exposure in the methanogen Methanosarcina barkeri and implications for Martian habitability

Observations of trace methane (CH₄) in the Martian atmosphere are significant to the astrobiology community given the overwhelming contribution of biological methanogenesis to atmospheric CH₄ on Earth. Previous studies have shown that methanogenic Archaea can generate CH₄ when incubated with perchlorates, highly oxidizing chaotropic salts which have been found across the Martian surface. However, the regulatory mechanisms behind this remain completely unexplored. In this study we performed comparative transcriptomics on the methanogen Methanosarcina barkeri, which was incubated at 30˚C and 0˚C with 10-20 mM calcium-, magnesium-, or sodium perchlorate. Consistent with prior studies, we observed decreased CH₄ production and apparent perchlorate reduction, with the latter process proceeding by heretofore essentially unknown mechanisms. Transcriptomic responses of M. barkeri to perchlorates include up-regulation of osmoprotectant transporters and selection against redox-sensitive amino acids. Increased expression of methylamine methanogenesis genes suggest competition for H₂ with perchlorate reduction, which we propose is catalyzed by up-regulated molybdenum-containing enzymes and maintained by siphoning diffused H₂ from energy-conserving hydrogenases. Methanogenesis regulatory patterns suggest Mars' freezing temperatures alone pose greater constraints to CH₄ production than perchlorates. These findings increase our understanding of methanogen survival in extreme environments and confers continued consideration of a potential biological contribution to Martian CH₄.

PhyloPrimer: a taxon-specific oligonucleotide design platform

Many environmental and biomedical biomonitoring and detection studies aim to explore the presence of specific organisms or gene functionalities in microbiome samples. In such cases, when the study hypotheses can be answered with the exploration of a small number of genes, a targeted PCR-approach is appropriate. However, due to the complexity of environmental microbial communities, the design of specific primers is challenging and can lead to non-specific results. We designed PhyloPrimer, the first user-friendly platform to semi-automate the design of taxon-specific oligos (i.e., PCR primers) for a gene of interest. The main strength of PhyloPrimer is the ability to retrieve and align GenBank gene sequences matching the user’s input, and to explore their relationships through an online dynamic tree. PhyloPrimer then designs oligos specific to the gene sequences selected from the tree and uses the tree non-selected sequences to look for and maximize oligo differences between targeted and non-targeted sequences, therefore increasing oligo taxon-specificity (positive/negative consensus approach). Designed oligos are then checked for the presence of secondary structure with the nearest-neighbor (NN) calculation and the presence of off-target matches with in silico PCR tests, also processing oligos with degenerate bases. Whilst the main function of PhyloPrimer is the design of taxon-specific oligos (down to the species level), the software can also be used for designing oligos to target a gene without any taxonomic specificity, for designing oligos from preselected sequences and for checking predesigned oligos. We validated the pipeline on four commercially available microbial mock communities using PhyloPrimer to design genus- and species-specific primers for the detection of Streptococcus species in the mock communities. The software performed well on these mock microbial communities and can be found at https://www.cerealsdb.uk.net/cerealgenomics/phyloprimer.

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.

Generation of Genetic Tools for Gauging Multiple-Gene Expression at the Single-Cell Level

Key microbial processes in many bacterial species are heterogeneously expressed in single cells of bacterial populations. However, the paucity of adequate molecular tools for live, real-time monitoring of multiple-gene expression at the single-cell level has limited the understanding of phenotypic heterogeneity. To investigate phenotypic heterogeneity in the ubiquitous opportunistic pathogen Pseudomonas aeruginosa, a genetic tool that allows gauging multiple-gene expression at the single-cell level has been generated. This tool, named pRGC, consists of a promoter-probe vector for transcriptional fusions that carries three reporter genes coding for the fluorescent proteins mCherry, green fluorescent protein (GFP), and cyan fluorescent protein (CFP). The pRGC vector has been characterized and validated via single-cell gene expression analysis of both constitutive and iron-regulated promoters, showing clear discrimination of the three fluorescence signals in single cells of a P. aeruginosa population without the need for image processing for spectral cross talk correction. In addition, two pRGC variants have been generated for either (i) integration of the reporter gene cassette into a single neutral site of P. aeruginosa chromosome that is suitable for long-term experiments in the absence of antibiotic selection or (ii) replication in bacterial genera other than Pseudomonas The easy-to-use genetic tools generated in this study will allow rapid and cost-effective investigation of multiple-gene expression in populations of environmental and pathogenic bacteria, hopefully advancing the understanding of microbial phenotypic heterogeneity.IMPORTANCE Within a bacterial population, single cells can differently express some genes, even though they are genetically identical and experience the same chemical and physical stimuli. This phenomenon, known as phenotypic heterogeneity, is mainly driven by gene expression noise and results in the emergence of bacterial subpopulations with distinct phenotypes. The analysis of gene expression at the single-cell level has shown that phenotypic heterogeneity is associated with key bacterial processes, including competence, sporulation, and persistence. In this study, new genetic tools have been generated that allow easy cloning of up to three promoters upstream of distinct fluorescent genes, making it possible to gauge multiple-gene expression at the single-cell level by fluorescence microscopy without the need for advanced image-processing procedures. A proof of concept has been provided by investigating iron uptake and iron storage gene expression in response to iron availability in P. aeruginosa.

Extensive Reannotation of the Genome of the Model Streptomycete Streptomyces lividans TK24 Based on Transcriptome and Proteome Information

Streptomyces lividans TK24 is a relevant Gram-positive soil inhabiting bacterium and one of the model organisms of the genus Streptomyces. It is known for its potential to produce secondary metabolites, antibiotics, and other industrially relevant products. S. lividans TK24 is the plasmid-free derivative of S. lividans 66 and a close genetic relative of the strain Streptomyces coelicolor A3(2). In this study, we used transcriptome and proteome data to improve the annotation of the S. lividans TK24 genome. The RNA-seq data of primary 5'-ends of transcripts were used to determine transcription start sites (TSS) in the genome. We identified 5,424 TSS, of which 4,664 were assigned to annotated CDS and ncRNAs, 687 to antisense transcripts distributed between 606 CDS and their UTRs, 67 to tRNAs, and 108 to novel transcripts and CDS. Using the TSS data, the promoter regions and their motifs were analyzed in detail, revealing a conserved -10 (TAnnnT) and a weakly conserved -35 region (nTGACn). The analysis of the 5' untranslated region (UTRs) of S. lividans TK24 revealed 17% leaderless transcripts. Several cis-regulatory elements, like riboswitches or attenuator structures could be detected in the 5'-UTRs. The S. lividans TK24 transcriptome contains at least 929 operons. The genome harbors 27 secondary metabolite gene clusters of which 26 could be shown to be transcribed under at least one of the applied conditions. Comparison of the reannotated genome with that of the strain Streptomyces coelicolor A3(2) revealed a high degree of similarity. This study presents an extensive reannotation of the S. lividans TK24 genome based on transcriptome and proteome analyses. The analysis of TSS data revealed insights into the promoter structure, 5'-UTRs, cis-regulatory elements, attenuator structures and novel transcripts, like small RNAs. Finally, the repertoire of secondary metabolite gene clusters was examined. These data provide a basis for future studies regarding gene characterization, transcriptional regulatory networks, and usage as a secondary metabolite producing strain.

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.

Metabolic RNA labeling for probing RNA dynamics in bacteria

Metabolic labeling of RNAs with noncanonical nucleosides that are chemically active, followed by chemoselective conjugation with imaging probes or enrichment tags, has emerged as a powerful method for studying RNA transcription and degradation in eukaryotes. However, metabolic RNA labeling is not applicable for prokaryotes, in which the complexity and distinctness of gene regulation largely remain to be explored. Here, we report 2'-deoxy-2'-azidoguanosine (AzG) as a noncanonical nucleoside compatible with metabolic labeling of bacterial RNAs. With AzG, we develop AIR-seq (azidonucleoside-incorporated RNA sequencing), which enables genome-wide analysis of transcription upon heat stress in Escherichia coli. Furthermore, AIR-seq coupled with pulse-chase labeling allows for global analysis of bacterial RNA degradation. Finally, we demonstrate that RNAs of mouse gut microbiotas can be metabolically labeled with AzG in living animals. The AzG-enabled metabolic RNA labeling should find broad applications in studying RNA biology in various bacterial species.

RNA-Seq-Based Transcriptomic Analysis of Saccharopolyspora spinosa Revealed the Critical Function of PEP Phosphonomutase in the Replenishment Pathway

Spinosyns, the secondary metabolites produced by Saccharopolyspora spinosa, are the active ingredients in a family of novel biological insecticides. Although the complete genome sequence of S. spinosa has been published, the transcriptome of S. spinosa remains poorly characterized. In this study, high-throughput RNA sequencing (RNA-seq) technology was applied to dissect the transcriptome of S. spinosa. Through transcriptomic analysis of different periods of S. spinosa growth, we found large numbers of differentially expressed genes and classified them according to their different functions. Based on the RNA-seq data, the CRISPR-Cas9 method was used to knock out the PEP phosphonomutase gene (orf 06952-4171). The yield of spinosyns A and D in S. spinosa-ΔPEP was 178.91 mg/L and 42.72 mg/L, which was 2.14-fold and 1.76-fold higher than that in the wild type (83.51 and 24.34 mg/L), respectively. The analysis of the mutant strains also verified the validity of the transcriptome data. The deletion of the PEP phosphonomutase gene leads to an increase in pyruvate content and affects the biosynthesis of spinosad. The replenishment of phosphoenol pyruvate in S. spinosa provides the substrate for the production of spinosad. We envision that these transcriptomic analysis results will contribute to the further study of secondary metabolites in actinomycetes.

An RNA biology perspective on species-specific programmable RNA antibiotics

Our body is colonized by a vast array of bacteria the sum of which forms our microbiota. The gut alone harbors >1,000 bacterial species. An understanding of their individual or synergistic contributions to human health and disease demands means to interfere with their functions on the species level. Most of the currently available antibiotics are broad-spectrum, thus too unspecific for a selective depletion of a single species of interest from the microbiota. Programmable RNA antibiotics in the form of short antisense oligonucleotides (ASOs) promise to achieve precision manipulation of bacterial communities. These ASOs are coupled to small peptides that carry them inside the bacteria to silence mRNAs of essential genes, for example, to target antibiotic-resistant pathogens as an alternative to standard antibiotics. There is already proof-of-principle with diverse bacteria, but many open questions remain with respect to true species specificity, potential off-targeting, choice of peptides for delivery, bacterial resistance mechanisms and the host response. While there is unlikely a one-fits-all solution for all microbiome species, I will discuss how recent progress in bacterial RNA biology may help to accelerate the development of programmable RNA antibiotics for microbiome editing and other applications.

Transcriptome based functional identification and application of regulator AbrB on alkaline protease synthesis in Bacillus licheniformis 2709

Bacillus licheniformis 2709 is the major alkaline protease producer, which has great potential value of industrial application, but how the high-producer can be regulated rationally is still not completely understood. It's meaningful to understand the metabolic processes during alkaline protease production in industrial fermentation medium. Here, we collected the transcription database at various enzyme-producing stages (preliminary stage, stable phase and decline phase) to specifically research the synthesized and regulatory mechanism of alkaline protease in B. licheniformis. The RNA-sequencing analysis showed differential expression of numerous genes related to several processes, among which genes correlated with regulators were concerned, especially the major differential gene abrB on enzyme (AprE) synthesis was investigated. It was further verified that AbrB is a repressor of AprE by plasmid-mediated over-expression due to the severely descending enzyme activity (11,300 U/mL to 2695 U/mL), but interestingly it is indispensable for alkaline protease production because the enzyme activity of the null abrB mutant was just about 2279 U/mL. Thus, we investigated the aprE transcription by eliminating the theoretical binding site (TGGAA) of AbrB protein predicated by computational strategy, which significantly improved the enzyme activity by 1.21-fold and gene transcription level by 1.77-fold in the mid-log phase at a cultivation time of 18 h. Taken together, it is of great significance to improve the production strategy, control the metabolic process and oriented engineering by rational molecular modification of regulatory network based on the high throughput sequencing and computational prediction.

Advances and challenges in single-cell RNA-seq of microbial communities

Microbes have developed complex strategies to respond to their environment and escape the immune system by individualizing their behavior. While single-cell RNA sequencing has become instrumental for studying mammalian cells, its use with fungi, protozoa and bacteria is still in its infancy. In this review, we highlight the major progress towards mapping the molecular states of microbes at the single-cell level using genome-wide transcriptomics and describe how these technologies can be extended to probe thousands of species at high throughput. We envision that mammalian and microbial single-cell profiling could soon be integrated for the study of microbial communities in health and disease.

Analysis of the Composition and Functions of the Microbiome in Diabetic Foot Osteomyelitis Based on 16S rRNA and Metagenome Sequencing Technology

Metagenome sequencing has not been used in infected bone specimens. This prospective observational study explored the microbiome and its function in patients with diabetic foot osteomyelitis (DFO) and posttraumatic foot osteomyelitis (PFO) based on 16S rRNA sequencing and metagenome sequencing technologies. Spearman analysis was used to explore the correlation between dominant species and clinical indicators of patients with DFO. High-throughput sequencing showed that all the specimens were polymicrobial. The microbial diversity was significantly higher in the DFO group than in the PFO group. Firmicutes, Prevotellaceae, and Prevotella were the most abundant microbes in the DFO group. The most abundant microbes in the PFO group were Proteobacteria, Halomonadaceae, and Halomonas Prevotella denticola, Prevotella jejuni, and Prevotella fusca had positive correlation with the duration of diabetic foot infection (DFI_d). Proteus vulgaris was positively correlated with the infection index, while Bacteroides fragilis was negatively correlated. The microbial functional genes were more abundant in the DFO group than in the PFO group. Metagenome sequencing is feasible for the analysis of the microbiome in infected bone specimens. Gram-negative bacteria and anaerobes are dominant in DFO.

The Open Challenge of in vitro Modeling Complex and Multi-Microbial Communities in Three-Dimensional Niches

The comprehension of the underlying mechanisms of the interactions within microbial communities represents a major challenge to be faced to control their outcome. Joint efforts of in vitro, in vivo and ecological models are crucial to controlling human health, including chronic infections. In a broader perspective, considering that polymicrobial communities are ubiquitous in nature, the understanding of these mechanisms is the groundwork to control and modulate bacterial response to any environmental condition. The reduction of the complex nature of communities of microorganisms to a single bacterial strain could not suffice to recapitulate the in vivo situation observed in mammals. Furthermore, some bacteria can adapt to various physiological or arduous environments embedding themselves in three-dimensional matrices, secluding from the external environment. Considering the increasing awareness that dynamic complex and dynamic population of microorganisms (microbiota), inhabiting different apparatuses, regulate different health states and protect against pathogen infections in a fragile and dynamic equilibrium, we underline the need to produce models to mimic the three-dimensional niches in which bacteria, and microorganisms in general, self-organize within a microbial consortium, strive and compete. This review mainly focuses, as a case study, to lung pathology-related dysbiosis and life-threatening diseases such as cystic fibrosis and bronchiectasis, where the co-presence of different bacteria and the altered 3D-environment, can be considered as worst-cases for chronic polymicrobial infections. We illustrate the state-of-art strategies used to study biofilms and bacterial niches in chronic infections, and multispecies ecological competition. Although far from the rendering of the 3D-environments and the polymicrobial nature of the infections, they represent the starting point to face their complexity. The increase of knowledge respect to the above aspects could positively affect the actual healthcare scenario. Indeed, infections are becoming a serious threat, due to the increasing bacterial resistance and the slow release of novel antibiotics on the market.

Novel insights into host-pathogen interactions of large yellow croakers ( Larimichthys crocea) and pathogenic bacterium Pseudomonas plecoglossicida using time-resolved dual RNA-seq of infected spleens

Host-pathogen interactions are highly complex, involving large dynamic changes in gene expression during infection. These interactions are fundamental to understanding anti-infection immunity of hosts, as well as the pathogenesis of pathogens. For bacterial pathogens interacting with animal hosts, time-resolved dual RNA-seq of infected tissue is difficult to perform due to low pathogen load in infected tissue. In this study, an acute infection model of Larimichthys crocea infected by Pseudomonas plecoglossicida was established. The spleens of infected fish exhibited typical symptoms, with a maximum bacterial load at two days post-injection (dpi). Time-resolved dual RNA-seq of infected spleens was successfully applied to study host-pathogen interactions between L. crocea and P. plecoglossicida. The spleens of infected L. crocea were subjected to dual RNA-seq, and transcriptome data were compared with those of noninfected spleens or in vitro cultured bacteria. Results showed that pathogen-host interactions were highly dynamically regulated, with corresponding fluctuations in host and pathogen transcriptomes during infection. The expression levels of many immunogenes involved in cytokine-cytokine receptor, Toll-like receptor signaling, and other immune-related pathways were significantly up-regulated during the infection period. Furthermore, metabolic processes and the use of oxygen in L. crocea were strongly affected by P. plecoglossicida infection. The WGCNA results showed that the metabolic process was strongly related to the entire immune process. For P. plecoglossicida, the expression levels of motility-related genes and flagellum assembly-related genes were significantly up-regulated. The results of this study may help to elucidate the interactions between L. crocea and P. plecoglossicida.

Interplay between Regulatory RNAs and Signal Transduction Systems during Bacterial Infection

The ability of pathogenic bacteria to stably infect the host depends on their capacity to respond and adapt to the host environment and on the efficiency of their defensive mechanisms. Bacterial envelope provides a physical barrier protecting against environmental threats. It also constitutes an important sensory interface where numerous sensing systems are located. Signal transduction systems include Two-Component Systems (TCSs) and alternative sigma factors. These systems are able to sense and respond to the ever-changing environment inside the host, altering the bacterial transcriptome to mitigate the impact of the stress. The regulatory networks associated with signal transduction systems comprise small regulatory RNAs (sRNAs) that can be directly involved in the expression of virulence factors. The aim of this review is to describe the importance of TCS- and alternative sigma factor-associated sRNAs in human pathogens during infection. The currently available genome-wide approaches for studies of TCS-regulated sRNAs will be discussed. The differences in the signal transduction mediated by TCSs between bacteria and higher eukaryotes and the specificity of regulatory RNAs for their targets make them appealing targets for discovery of new strategies to fight against multi-resistant bacteria.

Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to Listeria monocytogenes

Automatic de novo identification of the main regulons of a bacterium from genome and transcriptome data remains a challenge. To address this task, we propose a statistical model that can use information on exact positions of the transcription start sites and condition-dependent expression profiles. The central idea of this model is to improve the probabilistic representation of the promoter DNA sequences by incorporating covariates summarizing expression profiles (e.g. coordinates in projection spaces or hierarchical clustering trees). A dedicated trans-dimensional Markov chain Monte Carlo algorithm adjusts the width and palindromic properties of the corresponding position-weight matrices, the number of parameters to describe exact position relative to the transcription start site, and chooses the expression covariates relevant for each motif. All parameters are estimated simultaneously, for many motifs and many expression covariates. The method is applied to a dataset of transcription start sites and expression profiles available for Listeria monocytogenes. The results validate the approach and provide a new global view of the transcription regulatory network of this important pathogen. Remarkably, a previously unreported motif is found in promoter regions of ribosomal protein genes, suggesting a role in the regulation of growth.

Genome-Wide Transcription Start Site Mapping and Promoter Assignments to a Sigma Factor in the Human Enteropathogen Clostridioides difficile

The emerging human enteropathogen Clostridioides difficile is the main cause of diarrhea associated with antibiotherapy. Regulatory pathways underlying the adaptive responses remain understudied and the global view of C. difficile promoter structure is still missing. In the genome of C. difficile 630, 22 genes encoding sigma factors are present suggesting a complex pattern of transcription in this bacterium. We present here the first transcriptional map of the C. difficile genome resulting from the identification of transcriptional start sites (TSS), promoter motifs and operon structures. By 5′-end RNA-seq approach, we mapped more than 1000 TSS upstream of genes. In addition to these primary TSS, this analysis revealed complex structure of transcriptional units such as alternative and internal promoters, potential RNA processing events and 5′ untranslated regions. By following an in silico iterative strategy that used as an input previously published consensus sequences and transcriptomic analysis, we identified candidate promoters upstream of most of protein-coding and non-coding RNAs genes. This strategy also led to refine consensus sequences of promoters recognized by major sigma factors of C. difficile. Detailed analysis focuses on the transcription in the pathogenicity locus and regulatory genes, as well as regulons of transition phase and sporulation sigma factors as important components of C. difficile regulatory network governing toxin gene expression and spore formation. Among the still uncharacterized regulons of the major sigma factors of C. difficile, we defined the SigL regulon by combining transcriptome and in silico analyses. We showed that the SigL regulon is largely involved in amino-acid degradation, a metabolism crucial for C. difficile gut colonization. Finally, we combined our TSS mapping, in silico identification of promoters and RNA-seq data to improve gene annotation and to suggest operon organization in C. difficile. These data will considerably improve our knowledge of global regulatory circuits controlling gene expression in C. difficile and will serve as a useful rich resource for scientific community both for the detailed analysis of specific genes and systems biology studies.

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.

Construction of a High-Expression System in Bacillus through Transcriptomic Profiling and Promoter Engineering

Bacillus subtilis is an ideal host for secretion and expression of foreign proteins. The promoter is one of the most important elements to facilitate the high-level production of recombinant protein. To expand the repertoire of strong promoters for biotechnological applications in Bacillus species, 14 highly transcribed genes based on transcriptome profiling of B. pumilus BA06 were selected and evaluated for their promoter strength in B. subtilis. Consequently, a strong promoter P₂₀₆₉ was obtained, which could drive the genes encoding alkaline protease (aprE) and green fluorescent protein (GFP) to express more efficiency by an increase of 3.65-fold and 18.40-fold in comparison with the control promoter (P_aprE), respectively. Further, promoter engineering was applied to P₂₀₆₉, leading to a mutation promoter (P_2069M) that could increase GFP expression by 3.67-fold over the wild-type promoter (P₂₀₆₉). Moreover, the IPTG-inducible expression systems were constructed using the lac operon based on the strong promoters of P₂₀₆₉ and P_2069M, which could work well both in B. subtilis and B. pumilus. In this study, highly efficient expression system for Bacillus was constructed based on transcriptome data and promoter engineering, which provide not only a new option for recombinant expression in B. subtilis, but also novel genetic tool for B. pumilus.

Methodologies for Transcript Profiling Using Long-Read Technologies

RNA sequencing using next-generation sequencing technologies (NGS) is currently the standard approach for gene expression profiling, particularly for large-scale high-throughput studies. NGS technologies comprise high throughput, cost efficient short-read RNA-Seq, while emerging single molecule, long-read RNA-Seq technologies have enabled new approaches to study the transcriptome and its function. The emerging single molecule, long-read technologies are currently commercially available by Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), while new methodologies based on short-read sequencing approaches are also being developed in order to provide long range single molecule level information-for example, the ones represented by the 10x Genomics linked read methodology. The shift toward long-read sequencing technologies for transcriptome characterization is based on current increases in throughput and decreases in cost, making these attractive for de novo transcriptome assembly, isoform expression quantification, and in-depth RNA species analysis. These types of analyses were challenging with standard short sequencing approaches, due to the complex nature of the transcriptome, which consists of variable lengths of transcripts and multiple alternatively spliced isoforms for most genes, as well as the high sequence similarity of highly abundant species of RNA, such as rRNAs. Here we aim to focus on single molecule level sequencing technologies and single-cell technologies that, combined with perturbation tools, allow the analysis of complete RNA species, whether short or long, at high resolution. In parallel, these tools have opened new ways in understanding gene functions at the tissue, network, and pathway levels, as well as their detailed functional characterization. Analysis of the epi-transcriptome, including RNA methylation and modification and the effects of such modifications on biological systems is now enabled through direct RNA sequencing instead of classical indirect approaches. However, many difficulties and challenges remain, such as methodologies to generate full-length RNA or cDNA libraries from all different species of RNAs, not only poly-A containing transcripts, and the identification of allele-specific transcripts due to current error rates of single molecule technologies, while the bioinformatics analysis on long-read data for accurate identification of 5' and 3' UTRs is still in development.

DOOR: a prokaryotic operon database for genome analyses and functional inference

The rapid accumulation of fully sequenced prokaryotic genomes provides unprecedented information for biological studies of bacterial and archaeal organisms in a systematic manner. Operons are the basic functional units for conducting such studies. Here, we review an operon database DOOR (the Database of prOkaryotic OpeRons) that we have previously developed and continue to update. Currently, the database contains 6 975 454 computationally predicted operons in 2072 complete genomes. In addition, the database also contains the following information: (i) transcriptional units for 24 genomes derived using publicly available transcriptomic data; (ii) orthologous gene mapping across genomes; (iii) 6408 cis-regulatory motifs for transcriptional factors of some operons for 203 genomes; (iv) 3 456 718 Rho-independent terminators for 2072 genomes; as well as (v) a suite of tools in support of applications of the predicted operons. In this review, we will explain how such data are computationally derived and demonstrate how they can be used to derive a wide range of higher-level information needed for systems biology studies to tackle complex and fundamental biology questions.

Riboregulation in Nitrogen-Fixing Endosymbiotic Bacteria

Small non-coding RNAs (sRNAs) are ubiquitous components of bacterial adaptive regulatory networks underlying stress responses and chronic intracellular infection of eukaryotic hosts. Thus, sRNA-mediated regulation of gene expression is expected to play a major role in the establishment of mutualistic root nodule endosymbiosis between nitrogen-fixing rhizobia and legume plants. However, knowledge about this level of genetic regulation in this group of plant-interacting bacteria is still rather scarce. Here, we review insights into the rhizobial non-coding transcriptome and sRNA-mediated post-transcriptional regulation of symbiotic relevant traits such as nutrient uptake, cell cycle, quorum sensing, or nodule development. We provide details about the transcriptional control and protein-assisted activity mechanisms of the functionally characterized sRNAs involved in these processes. Finally, we discuss the forthcoming research on riboregulation in legume symbionts.

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

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

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

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

Characterization and potential mechanisms of highly antibiotic tolerant VBNC Escherichia coli induced by low level chlorination

Escherichia coli is an important pathogenic indicator in drinking water. Viable but non-culturable (VBNC) E. coli induced by low level chlorination was found to have higher antibiotic tolerance. The emerging of VBNC bacteria in drinking water systems is posing challenges to the control of bio-safety. It is necessary to study the underlying mechanisms of VBNC state E. coli under actual residual chlorine condition of drinking water pipe network. In this study, we investigated the changes of morphology and gene expressions that might present such state. The results indicated that the size of VBNC E. coli was not remarkably changed or recovered culturability under favorable environmental conditions. Results from transcriptomic analysis revealed that the regulated genes related to fimbrial-like adhesin protein, putative periplasmic pilin chaperone, regulators of the transcriptional regulation, antibiotic resistance genes and stress-induced genes, rendering VBNC cells more tolerant to adverse environmental conditions. In total of 16 genes were significantly up-regulated under the VBNC state, including three genes encoding toxic protein (ygeG, ibsD, shoB), indicating that VBNC E. coil was still a threat to human. The work is of great relevance in the context of better understanding this poorly understood physiological state.

Evaluating the genome and resistome of extensively drug-resistant Klebsiella pneumoniae using native DNA and RNA Nanopore sequencing

BACKGROUND

Klebsiella pneumoniae frequently harbours multidrug resistance, and current diagnostics struggle to rapidly identify appropriate antibiotics to treat these bacterial infections. The MinION device can sequence native DNA and RNA in real time, providing an opportunity to compare the utility of DNA and RNA for prediction of antibiotic susceptibility. However, the effectiveness of bacterial direct RNA sequencing and base-calling has not previously been investigated. This study interrogated the genome and transcriptome of 4 extensively drug-resistant (XDR) K. pneumoniae clinical isolates; however, further antimicrobial susceptibility testing identified 3 isolates as pandrug-resistant (PDR).

RESULTS

The majority of acquired resistance (≥75%) resided on plasmids including several megaplasmids (≥100 kb). DNA sequencing detected most resistance genes (≥70%) within 2 hours of sequencing. Neural network-based base-calling of direct RNA achieved up to 86% identity rate, although ≤23% of reads could be aligned. Direct RNA sequencing (with ∼6 times slower pore translocation) was able to identify (within 10 hours) ≥35% of resistance genes, including those associated with resistance to aminoglycosides, β-lactams, trimethoprim, and sulphonamide and also quinolones, rifampicin, fosfomycin, and phenicol in some isolates. Direct RNA sequencing also identified the presence of operons containing up to 3 resistance genes. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (≥2-fold) and the pmrHFIJKLM operon (≥8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to quantitative real-time PCR across 11 resistance genes.

CONCLUSION

Overall, MinION sequencing rapidly detected the XDR/PDR K. pneumoniae resistome, and direct RNA sequencing provided accurate estimation of expression levels of these genes.

Effect of the luxI/R gene on AHL-signaling molecules and QS regulatory mechanism in Hafnia alvei H4

Hafnia alvei H4 is a bacterium subject to regulation by a N-acyl-l-homoserine lactone (AHL)-mediated quorum sensing system and is closely related to the corruption of instant sea cucumber. Studying the effect of Hafnia alvei H4 quorum sensing regulatory genes on AHLs is necessary for the quality and preservation of instant sea cucumber. In this study, the draft genome of H. alvei H4, which comprises a single chromosome of 4,687,151 bp, was sequenced and analyzed and the types of AHLs were analyzed employing thin-layer chromatography (TLC) and high resolution triple quadrupole liquid chromatography/mass spectrometry (LC/MS). Then the wild-type strain of H. alvei H4 and the luxI/R double mutant (ΔluxIR) were compared by transcriptome sequencing (RNA-seq). The results indicate that the incomplete genome sequence revealed the presence of one quorum-sensing (QS) gene set, designated as lasI/expR. Three major AHLs, N-hexanoyl-l-homoserine lactone (C6-HSL), N-butyryl-l-homoserine lactone (C4-HSL), and N-(3-oxo-octanoyl)-l-homoserine lactone (3-oxo-C8-HSL) were found, with C6-HSL being the most abundant. C6-HSL was not detected in the culture of the luxI mutant (ΔluxI) and higher levels of C4-HSL was found in the culture of the luxR mutant (ΔluxR), which suggested that the luxR gene may have a positive effect on C4-HSL production. It was also found that AHL and QS genes are closely related in the absence of luxIR double deletion. The results of this study can further elucidate at the genetic level that luxI and luxR genes are involved in the regulation of AHL.