Biology subjects

Avican, K.

Publications and source records attributed to Avican, K..

11 recordsLinked to original sources

bioRxiv2026

High-throughput, single-cell-encoded colony imaging reveals infection-linked heterogeneity

Phenotypic heterogeneity within bacterial populations shapes adaptation, antibiotic tolerance, and infection dynamics, yet colony-level quantification remains difficult at scale and on dark/selective media. We present HeteroTyper, an automated, high-throughput time-lapse platform that measures colony phenotypes across >100 plates per run on both transparent and dark media. HeteroTyper includes a ready-to-use computational pipeline that can be deployed on common plate-imaging setups and across agar types, delivering appearance times as a proxy for lag times, growth trajectories, colony size, intensity, and morphology from routine image series. Automated counts closely matched manual counts, supporting accuracy and scalability. Using Yersinia pseudotuberculosis as a model, HeteroTyper resolves phenotypic heterogeneity in vitro, with early and late phases showing broader appearance time distributions than mid-log phases. It also reveals organ-specific heterogeneity in vivo, with mesenteric lymph node isolates displaying the broadest appearance time distributions compared to spleen and liver. Appearance time was negatively associated with final colony size and intensity, linking growth initiation to downstream colony outcomes. Together, these distribution-level measurements indicate that bacterial adaptation during infection is compartmentalized by tissue microenvironments and prior history, and establish HeteroTyper as a practical, generalizable route to quantify infection-relevant phenotypic diversity on solid media at routine, high throughput.

microbiology↗

bioRxiv2026

Sample-derived cDNA guides broad host RNA depletion for in vivo pathogen transcriptomics

RNA sequencing has transformed our understanding of host-microbe interactions, yet in vivo profiling of bacterial pathogenesis remains fundamentally limited by the dominance of host RNA. Traditional rRNA depletion strategies fail to eliminate the vast background of host messenger and non-coding RNAs, resulting in poor pathogen coverage and necessitating cost-prohibitive deep sequencing. Here, we present a sample-derived, cDNA-guided broad host RNA depletion methodology that selectively eliminates host transcripts directly from complex infected tissues. By utilizing reverse-transcribed host RNA to guide RNase H-mediated cleavage of host RNA:cDNA duplexes, this approach enriches bacterial transcripts over 14-fold without perturbing the physiological composition of the pathogen transcriptome. Crucially, our method preserves bacterial rRNA, establishing it as a highly valuable in vivo biomarker for quantifying microbial replication rates, viability, and entry into persister states. We demonstrate that this targeted depletion achieves fully saturated bacterial gene detection at a fraction of the traditional sequencing depth, fundamentally altering the economic and computational realities of in vivo transcriptomics.

molecular biology↗

bioRxiv2026

Bacterial Stress Responses Lower mRNA-Protein Level Correlations

Diverse bacterial pathogens have evolved complex regulatory mechanisms to adapt to various environmental stresses during infection. The uncertainty in mRNA-protein levels in response to environmental stressors complicates our understanding of bacterial physiology and their adaptation to stressful environments. To examine this issue, we have integrated transcriptomics and proteomics data on three human bacterial pathogens Salmonella enterica Typhimurium, Yersinia pseudotuberculosis, and Staphylococcus aureus under ten infection-relevant stress conditions. We observed positive correlations between mRNA and protein levels, which were decreased under different stress conditions. Essential genes exhibited higher expression levels with lower variation across the conditions and stronger mRNA-protein correlations compared to non-essential genes, highlighting their critical role in bacterial adaptability and survival. Moreover, we identified a substantial number of genes with stress-induced non-correlating mRNA-protein levels, especially under conditions triggering strong stress responses. Particularly this level was dramatically lowered for osmotic stress specific genes affected by impaired translational activity under osmotic stress. Our findings highlight the prevalence of non-correlating mRNA-protein levels and the potential role of post-translational modifications in modulating protein levels in response to environmental stressors during infection. This study provides a comprehensive framework for integrating transcriptomics and proteomics data and identifies potential gene products that might significantly impact the ability of diverse bacterial pathogens to adapt to hostile infection environments. Significance StatementUnderstanding how bacteria adapt to host environments is crucial for combating infections. We employed an integrative transcriptomics and proteomics approach to investigate mRNA-protein correlations in three clinically relevant pathogens under ten infection-relevant stress conditions. We identified genes whose mRNA-protein relationships are significantly disrupted by specific stressors. This study provides a deeper understanding of mRNA-protein level uncertainty, coupling it to stress responses known to trigger critical post-transcriptional and post-translational regulations. These findings help reveal novel mechanisms of bacterial adaptation and pathogenesis. By providing a comprehensive, multi-species dataset, this study serves as a foundational resource for infection biology, driving future advancements in understanding complex regulatory networks and identifying potential antimicrobial targets.

microbiology↗

bioRxiv2025

6S RNA facilitates bacterial virulence and adaptation at the epithelial barrier

Enteropathogenic bacteria must adapt dynamically to the complex gastrointestinal environment to successfully colonize host tissue and evade immune defenses. Using Yersinia pseudotuberculosis as a model, we performed in vivo spatial transcriptomics to investigate bacterial gene expression as it translocates from cecal lumen to associated lymphoid tissue in the mouse intestine. By optimizing bacterial RNA enrichment, we achieved near-complete transcriptome coverage and identified compartment-specific transcriptional profiles. Bacteria in lymphoid tissue exhibited elevated expression of virulence-associated type III secretion system (T3SS) genes and markers of increased replication, alongside a higher plasmid copy number. Oxygen availability emerged as an environmental cue for T3SS induction. Importantly, we discovered a role for the non-coding 6S RNA in accelerating virulence gene expression. Tissue-localized bacteria had significantly upregulated 6S RNA levels, and deletion of the ssrS gene encoding 6S RNA impaired T3SS gene expression and effector secretion. Further, spatial analyses of bacterial gene expression in foci of infected lymphoid tissue revealed heterogeneous expression patterns with significantly elevated expression of T3SS and 6S RNA in bacteria located close to surrounding phagocytes. Together these findings demonstrate that Y. pseudotuberculosis undergoes rapid transcriptional reprogramming upon epithelial barrier crossing coordinated by environmental sensing, where 6S RNA accelerates tissue colonization by promoting efficient expression of T3SS.

microbiology↗

bioRxiv2025

RfaH is Essential for Virulence and Adaptive Responses in Yersinia pseudotuberculosis Infection

We previously demonstrated that increased expression of the gene encoding transcriptional antiterminator RfaH during Yersinia pseudotuberculosis transcriptional reprogramming necessary for adapting to persistent infection. RfaH is known to regulate expression of the O-antigen biosynthesis operon in Y. pseudotuberculosis. In this study, we examined the role of RfaH in virulence, bacterial physiology under infection-relevant stress conditions, and determined the RfaH regulon in Y. pseudotuberculosis. We employed a mouse infection model and phenotypic assays to test RfaHs role in virulence and physiology, as well as RNA sequencing, including O-antigen biosynthesis-deficient strains. Our findings demonstrate that loss of rfaH significantly attenuates virulence, reducing the capacity of Y. pseudotuberculosis to establish persistent infection. RfaH expression is increased during the stationary growth phase and under various stress conditions, such as high osmolarity and temperature. Functional assays revealed that the{Delta} rfaH strain displayed defects in swimming and increased clumping, indicating altered surface properties affecting motility. Transcriptomic analysis showed that the absence of rfaH led to downregulation of genes involved in virulence besides O-antigen biosynthesis operon, suggesting RfaHs critical role in virulence and host adaptation. Notably, we identified a hypothetical non-coding RNA encoded within the 5-UTR of the O-antigen biosynthesis operon, which may regulate gene expression of the urease operon in Y. pseudotuberculosis. Collectively, our findings suggest that RfaH is essential for the virulence and adaptive capacity of Y. pseudotuberculosis to colonize the host. This study provides insights into regulatory mechanisms that facilitate bacterial survival in hostile environments and highlights the importance of RfaH and its regulatory targets in the pathogenesis of Y. pseudotuberculosis. Author SummaryFor bacterial pathogens to establish infection and persist in the host, they must adapt to harsh environments and fine-tune gene expression accordingly. The transcriptional antiterminator RfaH plays a pivotal role in regulating key genes essential for adaptation and virulence in Y. pseudotuberculosis. In this study, we explored the function of RfaH in bacterial physiology, stress responses, and infection dynamics. Using a mouse infection model, we found that loss of RfaH significantly reduced virulence and impaired the pathogens ability to establish persistent infection. Notably, RfaH expression increased under stress conditions, such as high osmolarity and temperature, underscoring its role in bacterial adaptation. On the other hand, the absence of RfaH led to motility defects and enhanced bacterial aggregation, suggesting alterations in surface properties. Transcriptomic analysis revealed that RfaH influences a broader set of genes beyond the O-antigen biosynthesis operon, including virulence factors critical for host adaptation. Additionally, we identified a potential non-coding RNA within the 5'-UTR of the O-antigen biosynthesis operon, which may regulate urease operon. Overall, our findings establish RfaH as a key regulator of Y. pseudotuberculosis virulence, shedding light on the molecular mechanisms that enable bacterial survival in challenging environments.

microbiology↗

bioRxiv2024

Bacterial protein function prediction via multimodal deep learning

Bacterial proteins are specialized with extensive functional diversity for survival in diverse and stressful environments. A significant portion of these proteins remains functionally uncharacterized, limiting our understanding of bacterial survival mechanisms. Hence, we developed Deep Expression STructure (DeepEST), a multimodal deep learning framework designed to accurately predict protein function in bacteria by assigning Gene Ontology (GO) terms. DeepEST comprises two modules: a multi-layer perceptron that takes gene expression and gene location as input features, and a protein structure-based predictor. Within DeepEST, we integrated these modules through a learnable weighted linear combination and introduced a novel masked loss function to fine-tune the structure-based predictor for bacterial species. These modeling choices are particularly well suited for bacteria due to the spatial organization of their circular genomes. Functionally related genes frequently co-localize and are co-transcribed within operons, allowing transcription dynamics to serve as crucial, condition-dependent regulatory signals. We show that DeepEST outperforms existing protein function prediction methods on a 25-species benchmark, relying solely on amino acid sequence or protein structure. Moreover, DeepEST predicts GO terms for unclassified hypothetical proteins across 25 human bacterial pathogens, facilitating the design of experimental setups for characterization studies. By combining expression, localization, and structure information in a unified deep learning framework, DeepEST bridges organism-specific data integration and structure-based transfer learning, providing a method tailored for bacterial protein function prediction in settings with structural and multi-condition expression data. AvailabilityAccompanying code and data can be found under https://github.com/BorgwardtLab/DeepEST.

bioinformatics↗

bioRxiv2022

A core transcriptional response for biofilm formation by Y. pseudotuberculosis

Previous transcriptional profiling of the enteropathogen Yersinia pseudotuberculosis during persistent stages of colonisation of mouse cecal lymphoid follicles indicated the possible involvement of biofilm in infection maintenance. Not much is known about the mechanisms responsible for biofilm formation by this pathogen, and most current knowledge is based on results of experiments conducted using the related Y. pestis pathogen that forms biofilm in the flea gut. In this study, we performed transcriptional profiling of Y. pseudotuberculosis in biofilms from different biofilm-inducing conditions, bile exposure, amino acid deprivation and in vivo mimicking conditions with and without oxygen. The comparison of differential expression of genes in biofilm versus planktonic bacteria showed a set of 54 core genes that were similarly regulated, independent of inducing condition. This set included many genes that were previously shown to be associated with biofilms, such as hutG, hsmF, hmsT and cpxP that were upreg-ulated and other genes such as hmsP and rfaH that were downregulated. There were also novel biofilm-associated genes, including genes encoding hypothetical proteins. To identify the genes involved in inducing biofilm formation, the gene expression of bacteria during an early initial phase when biofilm starts to form after induction by bile or amino acid depletion was determined. Comparisons of the resulting gene expression profiles with the profiles of non-induced bacteria incubated for the same period of time showed a set of core genes associated with early biofilm formation. This set included genes involved in quorum sensing, pili biogenesis and genes indicative of a potential metabolic shift involving nitrogen utilisation. Genes encoding components of sugar phosphotransferase systems were also up-regulated during biofilm induction. Assays of biofilm formation by bacteria deleted of some of these core genes showed that strains lacking hpr and luxS, which are known to be important for functional sugar phosphotransferase systems and quorum sensing, as well as glnL encoding a sensory histidine kinase were most negatively affected. Most of the deletion mutant strains tested were affected, but the effect was less severe, suggesting high levels of redundancy in the pathways involved in biofilm formation by this pathogen.

microbiology↗

bioRxiv2022

RpoN is required for a functional type III secretion system in Yersinia pseudotuberculosis

Pathogenic bacteria use a broad range of virulence factors to thrive within their host. Yersinia pseudotuberculosis, a gram-negative enteropathogen in humans, utilises a Type III secretion system to overcome the hosts innate immune response. A global regulator previously shown to be essential for virulence in Y. pseudotuberculosis is RpoN. We show here that a strain lacking RpoN has a severely reduced capacity to secrete Yop effectors. This strain has a substantially reduced expression of genes encoding structural components of the secretion apparatus, the ysc operons, while expression of genes encoding effectors and translocators is less affected. We show that RpoN regulates a complex network, where one part is suggested to contribute to inducing Type III secretion via the enhancer-binding protein GlrR/RpoN regulon. By analogy, during inducement of Type III secretion, RpoN has a positive effect on expression of the sigma factor RpoE, which also is known to act downstream of GlrR. Interestingly, we found putative RpoE binding sites upstream of the ysc operons, and also a partial rescue of Yop secretion in the rpoN mutant strain by overexpression of RpoE. Our findings suggest that the RpoN-mediated effect on expression of type III genes involves a sigma factor hierarchy, where RpoN via RpoE contributes to inducing Type III secretion.

molecular biology↗

bioRxiv2020

Spatiotemporal Variations in Growth Rate and Virulence Plasmid Copy Number during Yersinia pseudotuberculosis Infection

Pathogenic Yersinia spp. depend on the activity of a potent virulence plasmid-encoded ysc/yop type 3 secretion system (T3SS) to colonize hosts and cause disease. It was recently shown that Y. pseudotuberculosis up-regulates the virulence plasmid copy number (PCN) during infection and the resulting elevated gene dose of plasmid-encoded T3SS genes is essential for virulence. When and how this novel regulatory mechanism is deployed and regulates the replication of the virulence plasmid during infection is unknown. In the current study, we applied droplet digital PCR (ddPCR) to investigate the dynamics of Y. pseudotuberculosis virulence PCN variations and growth rates in infected mouse organs. We demonstrated that both PCN and growth varied in different tissues and over time throughout the course of infection, indicating that the bacteria adapted to discrete microenvironments during infection. The PCN was highest in Peyers Patches and caecum during the clonal invasive phase of the infection, while the fastest growth rates were found in the draining mesenteric lymph nodes. In deeper, systemic organs, the PCN was lower and more modest growth rates were recorded. Our study indicates that increased gene dosage of the plasmid-encoded T3SS genes is most important early in the infection during invasion of the host. The described ddPCR approach will greatly simplify analyses of PCN, growth dynamics, and bacterial loads in infected tissues, and will be readily applicable to other infection models. ImportanceStudying pathogenic bacteria proliferating inside infected hosts is challenging using traditional methods, especially the transit and reversible genetic events. The bacteria are effectively diluted by the overwhelming number of host cells present in infected tissues. Using an innovative droplet digital PCR (ddPCR) approach, we have determined the virulence plasmid copy number (PCN) variations and growth rates of Yersinia during the course of infection in a mouse model. Here, we show that both the virulence plasmid copy number and bacterial growth rates display spatiotemporal variations in mice during infection. We demonstrate that the peak-to-trough ratio can be used as a proxy for determining the growth rate of invasive bacterial pathogen during infection, and ddPCR as the method of choice for quantifying DNA in host-pathogen interaction context. This proof-of-concept ddPCR approach can be easily applied for any bacterial pathogens and any infection models, for analysis of PCN, growth dynamics and bacterial loads.

microbiology↗

bioRxiv2020

Genome-scale mapping reveals complex regulatory activities of RpoN in Yersinia pseudotuberculosis

RpoN, an alternative sigma factor commonly known as sigma 54, is implicated in persistent stages of Yersinia pseudotuberculosis infections in which genes associated with this regulator are upregulated. We here combined phenotypic and genomic assays to provide insight into its role and function in this pathogen. RpoN was found essential for Y. pseudotuberculosis virulence in mice, and in vitro functional assays showed that it controls biofilm formation and motility. Mapping genome-wide associations of Y. pseudotuberculosis RpoN using chromatin immunoprecipitation coupled with next-generation sequencing identified an RpoN-binding motif located at 103 inter- and intragenic sites on both sense and anti-sense strands. Deletion of rpoN had a large impact on gene expression, including down-regulation of genes encoding proteins involved in flagellar assembly, chemotaxis, and quorum sensing. There were also clear indications of cross talk with other sigma factors, together with indirect effects due to altered expression of other regulators. Matching differential gene expression with locations of the binding sites implicated around 130 genes or operons potentially activated or repressed by RpoN. Mutagenesis of selected intergenic binding sites confirmed both positive and negative regulatory effects of RpoN binding. Corresponding mutations of intragenic sense sites had less impact on associated gene expression. Surprisingly, mutating intragenic sites on the anti-sense strand commonly reduced expression of genes encoded by the corresponding sense strand. IMPORTANCEThe alternative sigma factor, RpoN ({sigma} 54), which is widely distributed in eubacteria have been implicated to control gene expression of importance for numerous functions including virulence. Proper responses to host environments are crucial for bacteria to establish infection and regulatory mechanisms involved are therefore of high interest for development of future therapeutics. Little is known about the function of RpoN in the intestinal pathogen Y. pseudotuberculosis and we therefore investigated its regulatory role in this pathogen. This regulator was indeed found to be critical for establishment of infection in mice, likely involving its requirement for motility and biofilm formation. The RpoN regulon involved both activating and suppressive effects on gene expression which could be confirmed with mutagenesis of identified binding sites. This is the first of its kind study of RpoN in Y. pseudotuberculosis revealing complex regulation of gene expression involving both productive and silent effects of its binding to DNA providing important information about RpoN regulation in enterobacteria.

microbiology↗

bioRxiv2020

RNA Atlas of Human Bacterial Pathogens Uncovers Stress Dynamics Linked to Infection

Despite being genetically diverse, bacterial pathogens can adapt to similar stressful environments in human host, but how this diversity allows them to achive this is yet not fully understood. Knowledge gained through comparative genomics is insufficient as it lacks the level of gene expression reflecting gene usage. To fill this gap, we investigated the transcriptome of 32 diverse bacterial pathogens under 11 host related stress conditions. We revealed that diverse bacterial pathogens have common responses to similar stresses to a certain extent but mostly employ their unique repertoire with intersections between different stress responses. We also identified universal stress responders which shed light on the nature of antimicrobial targets. In addition, we found that known and unknown putative novel ncRNAs comprised a significant proportion of the responses. All the data is collected in PATHOgenex atlas, providing ample opportunities to discover novel players critical for virulence and maintenance of infection.

microbiology↗