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Lynch, R.

Publications and source records attributed to Lynch, R..

7 recordsLinked to original sources

A cis-encoded RNA interaction controls sub-operonic spoVG expression in Staphylococcus aureus

Bacterial operons enable co-transcription of multiple genes, yet post-transcriptional mechanisms permitting differential regulation of individual genes within a polycistronic transcript remains incompletely understood. We demonstrate that a cis-encoded RNA-RNA interaction within the bicistronic yabJ-spoVG transcript forms an RNase III substrate that represses the transcription factor SpoVG in Staphylococcus aureus. Disruption of the cis-encoded regulation elevated monocistronic spoVG expression, reduced biofilm formation and cell wall peptidoglycan thickness, and increased sensitivity to cell wall-targeting antimicrobials in clinical vancomycin-intermediate S. aureus, consistent with phenotypes observed in an independent SpoVG overexpression strain. These findings uncover a previously undescribed mode of cis-regulatory control within a polycistronic operon and establish regulatory mRNA-mRNA interactions as a mechanism for sub-operonic gene regulation.

microbiology↗

Predicting viral sensitivity to antibodies using genetic sequences and antibody similarities

For genetically variable pathogens such as human immunodeficiency virus (HIV)-1, individual viral isolates can differ dramatically in their sensitivity to antibodies. The ability to predict which viruses will be sensitive and which will be resistant to a specific antibody could aid in the design of antibody therapies and help illuminate resistance evolution. Due to the enormous number of possible combinations, it is not possible to experimentally measure neutralization values for all pairs of viruses and antibodies. Here, we developed a simple and interpretable method called grouped neutralization learning (GNL) to predict neutralization values by leveraging viral genetic sequences and similarities in neutralization profiles between antibodies. Our method compares favorably to state-of-the-art approaches and is robust to model parameter assumptions. GNL can predict neutralization values for viruses with no observed data, an essential capability for evaluating novel viral strains. We also demonstrate that GNL can successfully transfer knowledge between independent data sets, allowing rapid estimates of viral sensitivity based on prior knowledge.

immunology↗

The Updated Mouse Universal Genotyping Array Bioinformatic Pipeline Improves Genetic QC in Laboratory Mice

The MiniMUGA genotyping array is a popular tool for genetic QC of laboratory mice and genotyping of samples from most types of experimental crosses involving laboratory strains, particularly for reduced complexity crosses. The content of the production version of the MiniMUGA array is fixed; however, there is the opportunity to improve arrays performance and the associated reports usefulness by leveraging thousands of samples genotyped since the initial description of MiniMUGA in 2020. Here we report our efforts to update and improve marker annotation, increase the number and the reliability of the consensus genotypes for inbred strains and increase the number of constructs that can reliably be detected with MiniMUGA. In addition, we have implemented key changes in the informatics pipeline to identify and quantify the contribution of specific genetic backgrounds to the makeup of a given sample, remove arbitrary thresholds, include the Y Chromosome and mitochondrial genome in the ideogram, and improve robust detection of the presence of commercially available substrains based on diagnostic alleles. Finally, we have made changes to the layout of the report, to simplify the interpretation and completeness of the analysis and added a table summarizing the ideogram. We believe that these changes will be of general interest to the mouse research community and will be instrumental in our goal of improving the rigor and reproducibility of mouse-based biomedical research.

genetics↗

Genome-Wide Association Study Reveals Influence of Cell-specific Gene Networks on Soybean Root System Architecture

Root system architecture (RSA) describes the shape and arrangement of a plants roots in the soil including the angle, rate of growth, and type of individual roots, which facilitates the uptake of nutrients and water. In crop improvement efforts, RSA has been less well studied due to the technical challenges associated with phenotyping roots as well as a focus on above-ground traits such as yield. We developed a gel-based root phenotyping system called RADICYL (Root Architecture 3D Cylinder), which is a non-invasive, high-throughput approach that enabled us to measure 15 RSA traits. We leveraged RADICYL to perform a comprehensive genome-wide association study (GWAS) with a panel of 371 diverse soybean elite lines, cultivars, landraces, and closely related species to identify gene networks underlying RSA. We identified 54 significant single nucleotide polymorphisms (SNPs) in our GWAS, some of which were shared across multiple RSA traits while others were specific to a given trait. We generated a single cell atlas of the soybean root using single nuclei RNA sequencing (snRNAseq) to explore the associated genes in the context of root tissues. Using gene co-expression network (GCN) analyses applied to RNA-seq of soybean root tissues, we identified network-level associations of genes predominantly expressed in endodermis with root width, and of those expressed in metaphloem with lateral root length. Our results suggest that pathways active in the endodermis and metaphloem cell-types influence soybean root system architecture.

plant biology↗

A Multitrait Locus Regulates Sarbecovirus Pathogenesis

Infectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to SARS-CoV disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse Chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6 that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2 and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species.

microbiology↗

Elucidating Mechanisms of Tolerance to Salmonella Typhimurium Across Long-Term Infections Using the Collaborative Cross

Understanding the molecular mechanisms underlying resistance and tolerance to pathogen infection may present the opportunity to develop novel interventions. Resistance is the absence of clinical disease with low pathogen burden, while tolerance is minimal clinical disease in the face of high pathogen burden. Salmonella is a worldwide health concern. We studied 18 strains of Collaborative Cross mice that survive acute Salmonella Typhimurium (STm) infections. We infected these strains orally and monitored them for three weeks post-infection. Five strains cleared STm by the end of the experiment (resistant), while 6 strains maintained a bacterial load and survived to the end of the experiment (tolerant). The remaining 7 strains survived longer than 7 days but succumbed to infection before the end of the study period and were called "delayed susceptible" to differentiate them from strains that do not survive to day 7 (susceptible). Tolerant strains were colonized in Peyers patches, mesenteric lymph node, spleen and liver, while resistant strains had significantly reduced bacterial colonization. Tolerant strains had lower pre-infection core body temperatures than both delayed susceptible and resistant strains and had disrupted circadian patterns of body temperature post-infection sooner than resistant strains. Tolerant strains had higher circulating total white blood cells than resistant strains, driven by increased numbers of neutrophils. Tolerant strains had more severe tissue damage and higher circulating levels of MCP-1 and IFN-{gamma}, but lower levels of ENA-78 than resistant strains. QTL analysis revealed 1 significant association and 6 suggestive associations. RNA-seq analysis identified 22 genes that are differentially regulated in tolerant versus resistant animals that overlapped with the QTLs we identified and allowed us to identify the top 5 canonical pathways. Fibrinogen genes (Fga, Fgb, and Fgg) were found across the QTL, RNA, and top canonical pathways making them the best candidate genes for differentiating tolerance and resistance. Author SummaryAn infected host can respond in multiple ways to bacterial infection including resistance and tolerance. Resistance is a decrease in pathogen load, while in tolerance mild clinical signs are present despite high pathogen load. We infected a collection of 18 strains of genetically diverse mice with Salmonella Typhimurium for up to three weeks. Five strains were resistant, 6 strains were tolerant, and the remaining 7 strains survived an intermediate amount of time ("delayed susceptible"). Tolerant strains maintained bacterial load across several organs, while resistant strains reduced bacterial load. Tolerant strains had the lowest pre-infection core body temperatures and the most rapid disruption in circadian patterns of body temperature post-infection. Tolerant strains had higher circulating neutrophils, higher circulating levels of MCP-1 and IFN-{gamma}, but lower levels of ENA-78 than resistant strains, in addition to more severe tissue damage than resistant strains. QTL analysis revealed multiple associated regions, and gene expression analysis identified 22 genes that are differentially regulated in tolerant versus resistant animals in these regions. Fibrinogen genes (Fga, Fgb, and Fgg) were found across the QTL, RNA, and top canonical pathways making them the best candidate genes for differentiating tolerance and resistance.

genetics↗

Genetic background influences survival of infections with Salmonella enterica serovar Typhimurium in the Collaborative Cross

Salmonella infections typically cause self-limiting gastroenteritis, but in some individuals these bacteria can spread systemically and cause disseminated disease. Salmonella Typhimurium (STm), which causes severe systemic disease in most inbred mice, has been used as a model for disseminated disease. To screen for new infection phenotypes across a range of host genetics, we orally infected 32 Collaborative Cross (CC) mouse strains with STm and monitored their disease progression for seven days by telemetry. Our data revealed a broad range of phenotypes across CC strains in many parameters including survival, bacterial colonization, tissue damage, complete blood counts (CBC), and serum cytokines. Eighteen CC strains survived to day 7, while fourteen susceptible strains succumbed to infection before day 7. Several CC strains had sex differences in survival and colonization. Surviving strains had lower pre-infection baseline temperatures and were less active during their daily active period. Core body temperature disruptions were detected earlier after STm infection than activity disruptions, making temperature a better detector of illness. All CC strains had STm in spleen and liver, but susceptible strains were more highly colonized. Tissue damage was weakly negatively correlated to survival. We identified loci associated with survival on Chromosomes (Chr) 1, 2, 4, 7. Polymorphisms in Ncf2 and Slc11a1, known to reduce survival in mice after STm infections, are located in the Chr 1 interval, and the Chr 7 association overlaps with a previously identified QTL peak called Ses2. We identified two new genetic regions on Chr 2 and 4 associated with susceptibility to STm infection. Our data reveal the diversity of responses to STm infection across a range of host genetics and identified new candidate regions for survival of STm infection. Author SummarySalmonella Typhimurium (STm) infections typically cause self-limiting diarrheal symptoms, but in some individuals, the bacteria can spread throughout the body and cause life-threatening infection. We used a population of genetically different mice (Collaborative Cross) to identify their range of responses to STm infection. We identified a broad range of outcomes across these different mice, including a group of mice susceptible to lethal infection and a group that survived our 7 day study. We found that mice that survived STm infection had a cooler core body temperature before infection than susceptible mice, while remaining active. Thus, body temperature, rather than activity, appears to be a better predictor of poor outcomes after STm infection. We identified several regions of the mouse genome that are associated with outcome after STm infection. One of these regions, mouse Chromosome (Chr) 1 has genes that are already known to influence susceptibility to STm infection. Two other regions that we identified to influence survival after STm infection, located on mouse Chr 2 and 4, are novel and contain numerous genes of interest that may be linked to susceptibility. Our work defines the utility of exploring how host genetic diversity influences infection outcomes with bacterial pathogens.

genetics↗