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 (scRNA-seq) protocol that is based on multiple annealing and deoxycytidine (dC) tailing-based quantitative scRNA-seq (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 rRNA depletion protocol into the MATQ-seq workflow. Applying our improved protocol on a large set of single Salmonella cells sampled over different growth conditions 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 regard 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. IMPORTANCE Gene 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, and improved transcript capture rate and gene coverage. Use of a more efficient reverse transcriptase and the integration of an rRNA 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 at a 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.

FinO domain proteins such as ProQ of the model pathogen Salmonella enterica have emerged as a new class of major RNA-binding proteins in bacteria. ProQ has been shown to target hundreds of transcripts, including mRNAs from many virulence regions, but its role, if any, in bacterial pathogenesis has not been studied. Here, using a Dual RNA-seq approach to profile ProQ-dependent gene expression changes as Salmonella infects human cells, we reveal dysregulation of bacterial motility, chemotaxis, and virulence genes which is accompanied by altered MAPK (mitogen-activated protein kinase) signaling in the host. Comparison with the other major RNA chaperone in Salmonella, Hfq, reinforces the notion that these two global RNA-binding proteins work in parallel to ensure full virulence. Of newly discovered infection-associated ProQ-bound small noncoding RNAs (sRNAs), we show that the 3'UTR-derived sRNA STnc540 is capable of repressing an infection-induced magnesium transporter mRNA in a ProQ-dependent manner. Together, this comprehensive study uncovers the relevance of ProQ for Salmonella pathogenesis and highlights the importance of RNA-binding proteins in regulating bacterial virulence programs.IMPORTANCE The protein ProQ has recently been discovered as the centerpiece of a previously overlooked "third domain" of small RNA-mediated control of gene expression in bacteria. As in vitro work continues to reveal molecular mechanisms, it is also important to understand how ProQ affects the life cycle of bacterial pathogens as these pathogens infect eukaryotic cells. Here, we have determined how ProQ shapes Salmonella virulence and how the activities of this RNA-binding protein compare with those of Hfq, another central protein in RNA-based gene regulation in this and other bacteria. To this end, we apply global transcriptomics of pathogen and host cells during infection. In doing so, we reveal ProQ-dependent transcript changes in key virulence and host immune pathways. Moreover, we differentiate the roles of ProQ from those of Hfq during infection, for both coding and noncoding transcripts, and provide an important resource for those interested in ProQ-dependent small RNAs in enteric bacteria.

The Gram-negative rod-shaped bacterium Pseudomonas aeruginosa is not only a major cause of nosocomial infections but also serves as a model species of bacterial RNA biology. While its transcriptome architecture and posttranscriptional regulation through the RNA-binding proteins Hfq, RsmA, and RsmN have been studied in detail, global information about stable RNA-protein complexes in this human pathogen is currently lacking. Here, we implement gradient profiling by sequencing (Grad-seq) in exponentially growing P. aeruginosa cells to comprehensively predict RNA and protein complexes, based on glycerol gradient sedimentation profiles of >73% of all transcripts and ∼40% of all proteins. As to benchmarking, our global profiles readily reported complexes of stable RNAs of P. aeruginosa, including 6S RNA with RNA polymerase and associated product RNAs (pRNAs). We observe specific clusters of noncoding RNAs, which correlate with Hfq and RsmA/N, and provide a first hint that P. aeruginosa expresses a ProQ-like FinO domain-containing RNA-binding protein. To understand how biological stress may perturb cellular RNA/protein complexes, we performed Grad-seq after infection by the bacteriophage ΦKZ. This model phage, which has a well-defined transcription profile during host takeover, displayed efficient translational utilization of phage mRNAs and tRNAs, as evident from their increased cosedimentation with ribosomal subunits. Additionally, Grad-seq experimentally determines previously overlooked phage-encoded noncoding RNAs. Taken together, the Pseudomonas protein and RNA complex data provided here will pave the way to a better understanding of RNA-protein interactions during viral predation of the bacterial cell.IMPORTANCE Stable complexes by cellular proteins and RNA molecules lie at the heart of gene regulation and physiology in any bacterium of interest. It is therefore crucial to globally determine these complexes in order to identify and characterize new molecular players and regulation mechanisms. Pseudomonads harbor some of the largest genomes known in bacteria, encoding ∼5,500 different proteins. Here, we provide a first glimpse on which proteins and cellular transcripts form stable complexes in the human pathogen Pseudomonas aeruginosa We additionally performed this analysis with bacteria subjected to the important and frequently encountered biological stress of a bacteriophage infection. We identified several molecules with established roles in a variety of cellular pathways, which were affected by the phage and can now be explored for their role during phage infection. Most importantly, we observed strong colocalization of phage transcripts and host ribosomes, indicating the existence of specialized translation mechanisms during phage infection. All data are publicly available in an interactive and easy to use browser.

A major obstacle in infection biology is the limited ability to recapitulate human disease trajectories in traditional cell culture and animal models, which impedes the translation of basic research into clinics. Here, we introduce a three-dimensional (3D) intestinal tissue model to study human enteric infections at a level of detail that is not achieved by conventional two-dimensional monocultures. Our model comprises epithelial and endothelial layers, a primary intestinal collagen scaffold, and immune cells. Upon Salmonella infection, the model mimics human gastroenteritis, in that it restricts the pathogen to the epithelial compartment, an advantage over existing mouse models. Application of dual transcriptome sequencing to the Salmonella-infected model revealed the communication of epithelial, endothelial, monocytic, and natural killer cells among each other and with the pathogen. Our results suggest that Salmonella uses its type III secretion systems to manipulate STAT3-dependent inflammatory responses locally in the epithelium without accompanying alterations in the endothelial compartment. Our approach promises to reveal further human-specific infection strategies employed by Salmonella and other pathogens.IMPORTANCE Infection research routinely employs in vitro cell cultures or in vivo mouse models as surrogates of human hosts. Differences between murine and human immunity and the low level of complexity of traditional cell cultures, however, highlight the demand for alternative models that combine the in vivo-like properties of the human system with straightforward experimental perturbation. Here, we introduce a 3D tissue model comprising multiple cell types of the human intestinal barrier, a primary site of pathogen attack. During infection with the foodborne pathogen Salmonella enterica serovar Typhimurium, our model recapitulates human disease aspects, including pathogen restriction to the epithelial compartment, thereby deviating from the systemic infection in mice. Combination of our model with state-of-the-art genetics revealed Salmonella-mediated local manipulations of human immune responses, likely contributing to the establishment of the pathogen's infection niche. We propose the adoption of similar 3D tissue models to infection biology, to advance our understanding of molecular infection strategies employed by bacterial pathogens in their human host.