Biology subjects

Barquist, L.

Publications and source records attributed to Barquist, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Genome-scale TraDIS reveals dynamic and conserved fitness requirements of Salmonella Typhimurium across sequential host niches during porcine infection

Non-typhoidal salmonellosis remains a major global cause of foodborne gastrointestinal disease, with pigs representing an important reservoir of Salmonella enterica serovar Typhimurium. The emergence of host-adapted, multidrug-resistant lineages has further reinforced the need to understand the genetic basis of bacterial persistence and pathogenicity within physiologically relevant hosts. Here, we applied transposon-directed insertion sequencing (TraDIS) to systematically define the genetic requirements of a highly host-adapted, multidrug-resistant S. Typhimurium DT104 isolate across sequential host niches during porcine infection. A high-density transposon mutant library ([~]1.2 million mutants) was subjected to in vivo selection in the ileal mucosa and mesenteric lymph nodes, as well as ex vivo infection of primary porcine neutrophils. Across all conditions, we identified 1,813 conditionally essential genes, revealing strong niche-specific fitness signatures and a progressive increase in selective stringency along the infection route. Ileal colonization was primarily driven by determinants of invasion, motility and lipopolysaccharide biosynthesis. In contrast, survival within neutrophils depended on resistance to antimicrobial stresses and extensive metabolic rewiring, whereas persistence in lymph nodes required a broader functional repertoire integrating virulence, motility, envelope remodelling and metabolic adaptation, including bacterial microcompartment-associated pathways. Despite this marked heterogeneity, we identified a conserved porcine host-conditioned essential genome, comprising core invasion functions, RNA metabolism and genome maintenance pathways, and central metabolism. Notably, the outer membrane lipid asymmetry system Mla and the twin-arginine translocation (Tat) pathway emerged as conserved bottlenecks for in vivo fitness across all host-associated environments. Together, these findings establish a hierarchical model of S. Typhimurium adaptation during porcine infection and provide a systems-level view of tissue-specific and conserved genetic requirements underpinning persistence in a major zoonotic reservoir.

microbiology↗

bioRxiv2025

High levels of antisense transcription from numerous genes in the obligate intracellular bacterium Orientia tsutsugamushi.

Orientia tsutsugamushi (Ot) is a cytoplasmic, Gram-negative, obligate intracellular bacterium that causes the human disease scrub typhus. It has a highly repetitive genome whereby approximately 50% is composed of multiple copies of a proliferated integrative and conjugative element, the Rickettsial amplified Genetic Element (RAGE). Previous RNA sequencing analysis revealed a high level of antisense transcription in Ot, particularly from RAGE-encoded genes, with 18% of all genes having a sense:antisense ratio <1 and 5% with a ratio <0.1. In our current study, we have confirmed the earlier RNA sequencing findings via PCR-based methods and established that this antisense transcription is a consistent feature across eight distinct Ot strains. Furthermore, we have utilized PCR to monitor differences in sense and antisense expression between intracellular and extracellular bacteria. Our findings lend weight to the hypothesis that antisense transcription in Ot is a regulated mechanism, possibly playing a crucial role in the pathogens lifecycle during infection.

microbiology↗

bioRxiv2025

Comparative Dual RNA-Seq Analysis of Eight Orientia tsutsugamushi Strains in Endothelial Cells Reveals Regulatory Patterns in Bacterial and Host Pathways During Infection

Orientia tsutsugamushi is an obligate intracellular bacterium that causes the mite-borne human disease scrub typhus. The species is characterised by having many strains that differ in their ability to cause disease in murine infection models and in human patients. The genomes of a diverse set of Orientia tsutsugamushi strains have recently been analysed in detail, revealing broadly similar gene content with genomes differing primarily in synteny and in the composition of a large arsenal of predicted secreted effector proteins. Given the similarity in gene content, here we asked whether the observed differences in virulence were driven by genome-wide differences in gene expression of bacterial genes, and differences in the ensuing response of infected host cells. To explore this, we carried out a dual RNA sequencing analysis of eight diverse strains of Orientia tsutsugamushi grown in cultured human endothelial cells. An overall analysis found no clear patterns in the bacterial or host gene expression patterns that correlate with the ability to cause disease. We found that all strains induce a strong type 1 interferon response in endothelial cells, but that within that broad response each strain has a unique fingerprint of induced genes likely leading to different disease outcomes when combined with a complex immune system in vivo. We compared expression levels of orthologous genes between different strains and identified some bacterial pathways with constant expression levels whilst others were more variable, leading to the identification of specific pathways under tight transcriptional control during cellular infection. Together our data show that inter-strain differences in virulence are not defined by expression levels of any one set of bacterial or host genes and also reveal insights into transcriptional regulation of different pathways in Orientia tsutsugamushi.

microbiology↗

bioRxiv2025

Stress-Induced Iron-Sulfur Cluster Damage as a Conserved Trigger of the Stringent Response

Pathogenic bacteria rely on the stringent response to adapt to the complex and fluctuating conditions encountered within the host. However, the mechanisms by which the stringent response senses host-induced stress remain poorly understood. Here, we identify iron-sulfur (Fe-S) cluster damage as a conserved trigger of the stringent response in major Gram-negative pathogens, including Salmonella enterica, Enterobacter cloacae, and Klebsiella pneumoniae. We demonstrate that Fe-S cluster disruption--caused by oxidative stress or metal imbalance--restricts the intracellular pools of sulfur-containing and branched-chain amino acids, thereby activating the ribosome-associated (p)ppGpp synthetase RelA. Furthermore, we show that iron availability governs recovery from Fe-S cluster damage, modulating the dynamics of the stringent response. Finally, we emphasize the dual role of (p)ppGpp in transcriptional regulation, enhancing bacterial fitness during Fe-S cluster stress while simultaneously promoting virulence by upregulating the SPI-2 type III secretion system. Together, these findings uncover a conserved mechanism by which pathogenic bacteria integrate metabolic stress into adaptive gene regulation and virulence, positioning Fe-S cluster integrity as a pivotal node linking environmental sensing to transcriptional control during infection.

microbiology↗

bioRxiv2025

The pcnB gene sustains Shigella flexneri virulence

The enteropathogen Shigella flexneri employs a Type Three Secretion System (T3SS) to colonize intestinal epithelial cells. Genes encoding the T3SS are located on a large IncFII virulence plasmid, pINV. T3SS expression comes at the expense of slowed Shigella growth and is therefore strictly controlled by both transcriptional and post-transcriptional mechanisms. Following up on a recent genome-wide screen, we here show that the chromosomal gene pcnB, encoding the poly-A polymerase I (PAP-I), slows Shigella growth at 37{degrees}C, while at the same time promotes early colonization of a human epithelial enteroid model. Proteomic profiling revealed that pcnB drives global increase of the Shigella T3SS virulence program. Accordingly, pcnB sustains pINV replication to a level optimal for Shigella virulence. This is achieved through increased degradation of the antisense RNA CopA, involved in plasmid replication control. The pcnB effect on pINV replication was found to also ensure longer-term intraepithelial expansion of Shigella following human intestinal epithelium invasion. Our findings exemplify how an optimal pINV level is necessary for the execution of Shigellas infection cycle. AUTHOR SUMMARYBacterial infections represent a major global threat. Understanding the genetic determinants promoting infections is crucial to overcome this threat. Shigella is an intracellular bacterial pathogen that invades and disseminates in the intestinal epithelium, causing bacillary dysentery in humans. Shigellas ability to cause disease relies on the delivery of effector proteins into the host cells through an injection machinery, with most of the genes involved in this process located on a large virulence plasmid. Here we show that the chromosomal gene pcnB sustains an optimal virulence plasmid level. This is crucial for Shigella to maximize virulence protein expression and thereby efficiently invade, replicate and spread within the intestinal epithelium.

microbiology↗

bioRxiv2025

An antisense oligomer conjugate with unpredicted bactericidal activity against Fusobacterium nucleatum

Fusobacteria are commensal members of the oral microbiome that can spread from their primary niche and colonize distal sites in the human body. Their enrichment in colorectal and breast cancer tissue has been associated with tumor growth, metastasis, and chemotherapeutic resistance. The use of non-selective antibiotics to remove fusobacteria impairs tumor progression, but prolonged application risks side effects such as gastrointestinal problems and dysbiosis. Species-specific antisense antibiotics based on peptide nucleic acid (PNA) have shown efficacy in many Gram-negative species, suggesting that antisense PNAs may also enable a tailored depletion of fusobacteria. Here, we have investigated the antibacterial potential of cell-penetrating peptide (CPP)-PNA conjugates targeting the mRNA of putative essential genes in Fusobacterium nucleatum. Unexpectedly, we observed no growth inhibition with any of the target-specific PNAs, but identified a non-targeting control CPP-PNA (FUS79, (RXR)4XB-GACATAATTGT) as a potent growth inhibitor of F. nucleatum. Our data suggest that the CPP and specific sequence features of FUS79 are responsible for its activity, rather than an antisense effect. Interestingly, FUS79 also inhibits the growth of five additional fusobacterial strains but not of F. nucleatum ssp. vincentii (FNV). RNA-seq analysis indicates that FUS79 induces a membrane stress response in a vulnerable F. nucleatum strain but not in FNV. Collectively, our attempt at developing antisense antibiotics for fusobacteria discovers a potent growth inhibitor, whose bactericidal effect appears independent of target-specific mRNA inhibition. IMPORTANCEEnrichment of F. nucleatum at cancer sites is associated with increased tumor growth and metastasis. Antibiotic treatment to remove the bacteria was shown to change the course of cancer progression. Here we explore first steps to establish peptide nucleic acids (PNAs) as specific antisense antibiotics, thereby laying the foundation for further development of antisense technology in fusobacteria. While the CPP-PNA FUS79 was initially designed as a control, we observed that the compound was bactericidal for specific fusobacterial strains. Our results suggest that FUS79 might be able to selectively deplete fusobacterial strains from bacterial communities, offering a new perspective on fusobacterial removal at the tumor site.

microbiology↗

bioRxiv2025

Biased sampling confounds machine learning prediction of antimicrobial resistance

Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for the surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR and identify resistance determinants. However, bacterial populations are highly structured and sampling is biased towards human disease isolates, meaning samples and derived features are not independent. This is rarely considered in applications of ML to AMR. Here, we demonstrate the confounding effects of sample structure by analyzing over 24,000 whole genome sequences and AMR phenotypes from five diverse pathogens, using pathological training data where resistance is confounded with phylogeny. We show resulting ML models perform poorly, and increasing the training sample size fails to rescue performance. A comprehensive analysis of 6,740 models identifies species- and drug-specific effects on model accuracy. We provide concrete recommendations for evaluating future ML approaches to AMR.

bioinformatics↗

bioRxiv2024

A systematic identification of resistance determinants to antisense antibiotics suggests adaptation strategies dependent on the delivery peptide

The rise of antimicrobial resistance (AMR) among human pathogenic microbes is a serious threat to global health, calling for the development of novel treatment strategies. Antibiotics based on programmable antisense oligomers (asobiotics) offer an attractive solution to the "arms-race", as their specificity can be quickly updated and tailored to target resistant bacteria. In order to understand the genetic architecture of resistance to asobiotics, we employed laboratory evolution assays to identify mutations that decrease susceptibility to antisense peptide nucleic acid (PNA) against four major gram-negative pathogens: Escherichia coli, Klebsiella pneumoniae, Salmonella enterica, and Pseudomonas aeruginosa. We observed that the reduction in susceptibility upon asobiotics treatment was dependent on the specific cell penetrating peptide (CPP) being conjugated to the PNAs, suggesting that reduced uptake is a common adaptation strategy only against the (KFF)3-K CPP. We in fact observed that sbmA was frequently mutated in all tested species when treated with (KFF)3-K conjugated PNAs. We further identified mutations related to translation, peptide transport and cell envelope, which provide new hypotheses on cellular response to CPP-PNAs conjugates. Furthermore, for (RXR)4XB-acpP we observed a modest increase in resistance only when mutations in the PNA binding site were induced, which could easily be bypassed by changing the PNA sequence. These findings indicate that the specific identity of the CPP used plays a key role in determining its robustness against the evolution of resistance, and that laboratory evolution can illuminate the remaining gaps in our knowledge on the mechanisms of action of asobiotics.

microbiology↗

bioRxiv2023

The RNA-binding protein RbpB is a central regulator of polysaccharide utilization in gut Bacteroides

Paramount to human health, symbiotic bacteria in the gastrointestinal tract rely on the breakdown of complex polysaccharides to thrive in this sugar-deprived environment. Gut Bacteroides are metabolic generalists and deploy dozens of polysaccharide utilization loci (PULs) to forage diverse dietary and host-derived glycans. The expression of the multi-protein PUL complexes is tightly regulated at the transcriptional level. However, how PULs are orchestrated at translational level in response to the fluctuating levels of their cognate substrates is unknown. Here, we identify the RNA-binding protein RbpB and a family of noncoding RNAs as key players in post-transcriptional PUL regulation. Ablation of RbpB in Bacteroides thetaiotaomicron displays compromised colonization in the mouse gut in a host diet-dependent manner. Current dogma holds that individual PULs are regulated by dedicated transcriptional regulators. We demonstrate that RbpB acts as a global RNA binder that directly interacts with several hundred cellular transcripts. This includes a paralogous noncoding RNA family comprised of 14 members, the FopS (family of paralogous sRNAs) cluster. Through a series of in-vitro and in-vivo assays, we reveal that FopS sRNAs repress the translation of a SusC-like glycan transporter when substrates are limited--an effect antagonized by RbpB. Together, this study implicates RNA-coordinated metabolic control as an important, yet previously overlooked, factor contributing to the in-vivo fitness of predominant microbiota species in dynamic nutrient landscapes.

microbiology↗

bioRxiv2023

A cell-free transcription-translation pipeline for recreating methylation patterns boosts DNA transformation in bacteria

The bacterial world offers diverse strains for understanding medical and environmental processes and for engineering synthetic-biology chasses. However, genetically manipulating these strains has faced a long-standing bottleneck: how to efficiently transform DNA. Here we report IMPRINT, a generalized, rapid and scalable approach based on cell-free transcription-translation (TXTL) systems to overcome DNA restriction, a prominent barrier to transformation. IMPRINT utilizes TXTL to express DNA methyltransferases from the bacterial hosts restriction-modification systems. The expressed methyltransferases then methylate DNA in vitro to match the host DNAs methylation pattern, circumventing restriction and enhancing transformation. With IMPRINT, we efficiently multiplex methylation by diverse DNA methyltransferases and enhance plasmid transformation in gram-negative and gram-positive bacteria. We also developed a high-throughput pipeline that identifies the most consequential methyltransferases, and we apply IMPRINT to facilitate a library screen for translational rules in a hard-to-transform Bifidobacterium. Overall, IMPRINT can enhance DNA transformation, enabling use of increasingly sophisticated genetic manipulation tools across the bacterial world.

synthetic biology↗

bioRxiv2023

A side-by-side comparison of peptide-delivered antisense antibiotics employing different nucleotide mimics

Antisense oligomer (ASO)-based antibiotics that target mRNAs of essential bacterial genes have great potential for counteracting antimicrobial resistance and for precision microbiome editing. To date, the development of such antisense antibiotics has primarily focused on using phosphorodiamidate morpholino (PMO) and peptide nucleic acid (PNA) backbones, largely ignoring the growing number of chemical modalities that have spurred the success of ASO-based human therapy. Here, we directly compare the activities of seven chemically distinct 10mer ASOs, all designed to target the essential gene acpP upon delivery with a KFF-peptide carrier into Salmonella. Our systematic analysis of PNA, PMO, phosphorothioate-modified DNA (PTO), 2-methylated RNA (RNA-OMe), 2-methoxyethylated RNA (RNA-MOE), 2-fluorinated RNA (RNA-F) and 2-4-locked RNA (LNA) is based on a variety of in vitro and in vivo methods to evaluate ASO uptake, target pairing and inhibition of bacterial growth. Our data show that only PNA and PMO are efficiently delivered by the KFF peptide into Salmonella to inhibit bacterial growth. Nevertheless, the strong target binding affinity and in vitro translational repression activity of LNA and RNA-MOE make them promising modalities for antisense antibiotics that will require the identification of an effective carrier.

microbiology↗

bioRxiv2023

A method to correct for local alterations in DNA copy number that bias functional genomics assays applied to antibiotic-treated bacteria

Functional genomics techniques, such as transposon insertion sequencing and RNA sequencing, are key to studying relative differences in mutant fitness or gene expression under selective conditions. However, certain stress conditions, mutations, or antibiotics can directly interfere with DNA synthesis, resulting in systematic changes in local DNA copy number along the chromosome. This can lead to artefacts in sequencing-based functional genomics data when comparing antibiotic treatment to an unstressed control, with relative differences in gene-wise read counts being the result of alterations in chromosomal replication dynamics rather than selection or direct gene regulation. We term this artefact chromosomal location bias and implement a principled statistical approach to correct for it by calculating local normalization factors along the chromosome. These normalization factors are then directly incorporated in statistical analyses using standard RNA-sequencing analysis methods without modifying the read counts themselves, preserving important information about the mean-variance relationship in the data. We illustrate the utility of this approach by generating and analysing a ciprofloxacin-treated transposon insertion sequencing dataset in Escherichia coli as a case study. We show that ciprofloxacin treatment generates chromosomal location bias in the resulting data, and we further demonstrate that failing to correct for this bias leads to false predictions of mutant drug sensitivity as measured by minimum inhibitory concentrations. We have developed an R package and user-friendly graphical Shiny application, ChromoCorrect, that detects and corrects for chromosomal bias in read count data, enabling the application of functional genomics technologies to the study of antibiotic stress. IMPORTANCEAltered gene dosage due to changes in DNA replication has been observed under a variety of stresses with a variety of experimental techniques. However, the implications of changes in gene dosage for sequencing-based functional genomics assays are rarely considered. We present a statistically principled approach to correcting for the effect of changes in gene dosage, enabling testing for differences in the fitness effects or regulation of individual genes in the presence of confounding differences in DNA copy number. We show that failing to correct for these effects can lead to incorrect predictions of resistance phenotype when applying functional genomics assays to investigate antibiotic stress, and we provide a user-friendly application to detect and correct for changes in DNA copy number.

genomics↗

bioRxiv2023

Improved RNA stability estimation through Bayesian modeling reveals most bacterial transcripts have sub-minute half-lives

RNA decay is a crucial mechanism for regulating gene expression in response to environmental stresses. In bacteria, RNA-binding proteins (RBPs) are known to be involved in post-transcriptional regulation, but their global impact on RNA half-lives has not been extensively studied. To shed light on the role of the major RBPs ProQ and CspC/E in maintaining RNA stability, we performed RNA sequencing of Salmonella enterica over a time course following treatment with the transcription initiation inhibitor rifampicin (RIF-seq) in the presence and absence of these RBPs. We developed a hierarchical Bayesian model that corrects for confounding factors in rifampicin RNA stability assays and enables us to identify differentially decaying transcripts transcriptome-wide. Our analysis revealed that the median RNA half-life in Salmonella in early stationary phase is less than 1 minute, a third of previous estimates. We found that over half of the 500 most long-lived transcripts are bound by at least one major RBP, suggesting a general role for RBPs in shaping the transcriptome. Integrating differential stability estimates with CLIP-seq revealed that approximately 30% of transcripts with ProQ binding sites and more than 40% with CspC/E binding sites in coding or 3 untranslated regions decay differentially in the absence of the respective RBP. Analysis of differentially destabilized transcripts identified a role for ProQ in the oxidative stress response. Our findings provide new insights into post-transcriptional regulation by ProQ and CspC/E, and the importance of RBPs in regulating gene expression. Significance StatementTogether with transcription and translation, RNA decay is one of the major processes governing protein production. Here, we have developed a new statistical approach that corrects for confounding effects when estimating RNA decay rates from RNA-seq in bacteria. Our more accurate decay rate estimates indicate that Salmonella transcripts have half-lives about three times shorter than previously thought. This approach allowed us to measure the effects of RNA-binding proteins (RBPs) on decay rates, identifying large cohorts of transcripts with changes in stability following RBP deletion and conditions where post-transcriptional regulation affects survival. Our method should lead to a reevaluation of RNA stability estimates across diverse bacteria and new insights into the role of RBPs in shaping the transcriptome.

microbiology↗

bioRxiv2023

Ribosome profiling reveals the fine-tuned response of Escherichia coli to mild and severe acid stress

The ability to respond to acidic environments is crucial for neutralophilic bacteria. Escherichia coli has a well-characterized regulatory network that triggers a multitude of defense mechanisms to counteract excess of protons. Nevertheless, systemic studies of the transcriptional and translational reprogramming of E. coli to different degrees of acid stress have not yet been performed. Here, we used ribosome profiling and RNA sequencing to compare the response of E. coli (pH 7.6) to sudden mild (pH 5.8) and severe near-lethal acid stress (pH 4.4) conditions that mimic passage through the gastrointestinal tract. We uncovered new differentially regulated genes and pathways, key transcriptional regulators, and 18 novel acid-induced candidate sORFs. By using machine learning leveraging large compendia of publicly available E. coli expression data, we were able to distinguish between the response to acid stress and general stress. These results expand the acid resistance network and provide new insights into the fine-tuned response of E. coli to mild and severe acid stress.

microbiology↗

bioRxiv2023

Network depth affects inference of gene sets from bacterial transcriptomes using denoising autoencoders

The increasing number of publicly available bacterial gene expression data sets provides an unprecedented resource for the study of gene regulation in diverse conditions, but emphasizes the need for self-supervised methods for the automated generation of new hypotheses. One approach for inferring coordinated regulation from bacterial expression data is through the use of neural networks known as denoising autoencoders (DAEs), which encode large datasets in a reduced bottleneck layer. We have generalized this application of DAEs to include deep networks and explore the effects of network architecture on gene set inference using deep learning. We developed a DAE-based pipeline to extract gene sets from a large compendium of transcriptomic data in Escherichia coli, independently of the DAE network parameters and architecture. We validate our method by identifying many of the inferred gene sets with known pathways in E. coli, and have subsequently used this pipeline to explore how the choice of network architecture impacts gene sets recovery. We find that increasing network depth leads the DAEs to explain gene expression in terms of fewer, more concisely defined gene sets, and that adjusting the network compression results in a trade-off between generalizability and overall biological inference. Finally, leveraging our understanding of the impact of DAE architecture choices on gene set inference, we apply our pipeline to an independent uropathogenic E. coli dataset collected directly from infected patients to identify genes which are uniquely induced during human colonization.

bioinformatics↗

bioRxiv2023

An integrated transcriptomics-functional genomics approach reveals a small RNA that modulates Bacteroides thetaiotaomicron sensitivity to tetracyclines

Gene expression plasticity allows bacteria to adapt to diverse environments, tie their metabolism to available nutrients, and cope with stress. This is particularly relevant in a niche as dynamic and hostile as the human intestinal tract, yet transcriptional networks remain largely unknown in gut Bacteroides spp. Here, we map transcriptional units and profile their expression levels in Bacteroides thetaiotaomicron over a suite of 15 defined experimental conditions that are relevant in vivo, such as variation of temperature, pH, and oxygen tension, exposure to antibiotic stress, and growth on simple carbohydrates or on host mucin-derived glycans. Thereby, we infer stress- and carbon source-specific transcriptional regulons, including conditional expression of capsular polysaccharides and polysaccharide utilization loci, and expand the annotation of small regulatory RNAs (sRNAs) in this organism. Integrating this comprehensive expression atlas with transposon mutant fitness data, we identify conditionally important sRNAs. One example is MasB, whose inactivation led to increased bacterial tolerance of tetracyclines. Using MS2 affinity purification coupled with RNA sequencing, we predict targets of this sRNA and discuss their potential role in the context of the MasB-associated phenotype. Together, this transcriptomic compendium in combination with functional sRNA genomics--publicly available through a new iteration of the Theta-Base web browser (www.helmholtz-hiri.de/en/datasets/bacteroides-v2)--constitutes a valuable resource for the microbiome and sRNA research communities alike.

molecular biology↗

bioRxiv2022

Improved bacterial single-cell RNA-seq through automated MATQ-seq and Cas9-based removal of rRNA reads

Bulk RNA-sequencing technologies have provided invaluable insights into host and bacterial gene expression and associated regulatory networks. Nevertheless, the majority of these approaches report average expression across cell populations, hiding the true underlying expression patterns that are often heterogeneous in nature. Due to technical advances, single-cell transcriptomics in bacteria has recently become reality, allowing exploration of these heterogeneous populations, which are often the result of environmental changes and stressors. In this work, we have improved our previously published bacterial single-cell RNA-sequencing protocol that is based on MATQ-seq, achieving a higher throughput through the integration of automation. We also selected a more efficient reverse transcriptase, which led to reduced cell loss and higher workflow robustness. Moreover, we successfully implemented a Cas9-based ribosomal RNA depletion protocol into the MATQ-seq workflow. Applying our improved protocol on a large set of single Salmonella cells sampled over growth revealed improved gene coverage and a higher gene detection limit compared to our original protocol and allowed us to detect the expression of small regulatory RNAs, such as GcvB or CsrB at a single-cell level. In addition, we confirmed previously described phenotypic heterogeneity in Salmonella in regards to expression of pathogenicity-associated genes. Overall, the low percentage of cell loss and high gene detection limit makes the improved MATQ-seq protocol particularly well suited for studies with limited input material, such as analysis of small bacterial populations in host niches or intracellular bacteria. IMPORTANCEGene expression heterogeneity among isogenic bacteria is linked to clinically-relevant scenarios, like biofilm formation and antibiotic tolerance. The recent development of bacterial single-cell RNA-sequencing (scRNA-seq) enables the study of cell-to-cell variability in bacterial populations and the mechanisms underlying these phenomena. Here, we report a scRNA-seq workflow based on MATQ-seq with increased robustness, reduced cell loss, improved transcript capture rate, and gene coverage. Use of a more efficient reverse transcriptase and the integration of a ribosomal RNA depletion step, which can be adapted to other bacterial single-cell workflows, was instrumental for these improvements. Applying the protocol to the foodborne-pathogen Salmonella, we confirmed transcriptional heterogeneity across and within different growth phases and demonstrated that our workflow captures small regulatory RNAs on the single-cell level. Due to low cell loss and high transcript capture rates, this protocol is uniquely suited for experimental settings in which the starting material is limited, such as infected tissues.

microbiology↗

bioRxiv2022

Grad-seq analysis of Enterococcus faecalis and Enterococcus faecium provides a global view of RNA and protein complexes in these two opportunistic pathogens

Enterococcus faecalis and Enterococcus faecium are major nosocomial pathogens. Despite their relevance to public health and their role in the development of bacterial antibiotic resistance, relatively little is known about gene regulation in these species. RNA-protein complexes serve crucial functions in all cellular processes associated with gene expression, including post-transcriptional control mediated by small regulatory RNAs (sRNAs). Here, we present a new resource for the study of enterococcal RNA biology, employing the Grad-seq technique to comprehensively predict complexes formed by RNA and proteins in E. faecalis V583 and E. faecium AUS0004. Analysis of the generated global RNA and protein sedimentation profiles led to the identification of RNA-protein complexes and putative novel sRNAs. Validating our data sets, we observe well-established cellular RNA-protein complexes such as the 6S RNA-RNA polymerase complex, suggesting that 6S RNA-mediated global control of transcription is conserved in enterococci. Focusing on the largely uncharacterized RNA-binding protein KhpB, we use the RIP-seq technique to predict that KhpB interacts with sRNAs, tRNAs, and untranslated regions of mRNAs, and might be involved in the processing of specific tRNAs. Collectively, these datasets provide departure points for in-depth studies of the cellular interactome of enterococci that should facilitate functional discovery in these and related Gram-positive species. Our data are available to the community through a user-friendly Grad-seq browser that allows interactive searches of the sedimentation profiles (https://resources.helmholtz-hiri.de/gradseqef/).

microbiology↗