Biology subjects

Bobba, S.

Publications and source records attributed to Bobba, S..

4 recordsLinked to original sources

bioRxiv2025

Diverse infections transcriptionally reprogram the intestinal epithelium and epithelial-immune cell interactions

The distal small intestine plays vital roles in host physiology by regulating nutrient and fluid homeostasis. Despite being impacted in Crohns disease and a major target for a range of infections, we know relatively little about the complexity of cellular responses and cell-cell communication in the ileum during infection. Single cell and spatial transcriptomics have emerged as powerful technologies to study tissue heterogeneity in the gut, but these tools have focused on the large intestine, in part due to the accessibility of this tissue for biopsies and its importance in cancer. Here we present GutPath, an atlas of over 500,000 single cells with RNA and protein expression profiles for 91 cell states in the ileum across diverse infectious archetypes. We show that GutPath accurately captures established immune responses to infection while revealing pathogen-specific responses in enterocytes. To highlight the discovery potential of this atlas, we identify a novel enterocyte cell state present during Yersinia pseudotuberculosis infection that is spatially linked to bacterial load and tissue pathology. GutPath establishes a much-needed resource for the immunology community that will accelerate the study of the transcriptional diversity of cellular landscapes in the small intestine.

immunology↗

bioRxiv2025

TNF signaling maintains local restriction of bacterial founder populations in intestinal and systemic sites during oral Yersinia infection

Enteroinvasive bacterial pathogens are responsible for an enormous worldwide disease burden that critically affects the young and immunocompromised. Yersinia pseudotuberculosis is a Gram-negative enteric pathogen, closely related to the plague agent Y. pestis, that colonizes intestinal tissues, induces the formation of pyogranulomas along the intestinal tract, and disseminates to systemic organs following oral infection of experimental rodents. Prior studies proposed that systemic tissues were colonized by a pool of intestinal replicating bacteria distinct from populations within Peyers patches and mesenteric lymph nodes. Whether bacteria within intestinal pyogranulomas serve as the source for systemic dissemination, and the relationship between bacterial populations within different tissue sites is poorly defined. Moreover, the factors that regulate Yersinia colonization and dissemination are not well understood. Here, we demonstrate, using Sequence Tag-based Analysis of Microbial Populations in R (STAMPR), that remarkably small founder populations independently colonize intestinal and systemic tissues. Notably, intestinal pyogranulomas contain clonal populations of bacteria that are restricted and do not spread to other tissues. However, populations of Yersinia are shared among systemic organs and the blood, suggesting that systemic dissemination occurs via hematogenous spread. Finally, we demonstrate that TNF signaling is a key contributor to the bottlenecks limiting both tissue colonization and lymphatic dissemination of intestinal bacterial populations. Altogether, this study reveals previously undescribed aspects of infection dynamics of enteric bacterial pathogens. ImportanceBacterial escape from the intestine can lead to severe disease, including sepsis, organ damage, and death. However, the intestinal bacterial population dynamics governing the colonization of mucosal and systemic tissues and the intestinal sites that seed systemic spread are not clear. Yersinia pseudotuberculosis is a rodent and human intestinal pathogen closely related to the plague agent and provides a natural rodent-adapted model to study systemic bacterial dissemination. Our findings define the infection dynamics of enteric Yersinia and the impact of the innate immune system on Yersinia colonization of the intestine and systemic organs.

microbiology↗

bioRxiv2022

A nepenthesin insert allosterically controls catalysis in the malaria parasite protease plasmepsin V

Plasmepsin V (PM V) is a pepsin-like aspartic protease essential for growth of the malaria parasite Plasmodium falciparum. Previous work has shown PM V to be an ER-resident protease that processes parasite proteins destined for export into the host cell. Depletion or inhibition of the enzyme is lethal during asexual replication within red blood cells, as well as during the formation of sexual stage gametocytes. The structure of the P. vivax PM V has been characterized by x-ray crystallography, revealing a canonical pepsin fold punctuated by structural features uncommon to secretory aspartic proteases. Here we use parasite genetics to probe these structural features by attempting to rescue lethal PM V depletion with various mutant enzymes. We find an unusual nepenthesin 1-type insert to be essential for parasite growth and PM V activity. Mutagenesis of the nepenthesin insert suggests that both its amino acid sequence and one of the two disulfide bonds that undergird its structure are required for the nepenthesin inserts role in PM V function. Molecular dynamics simulations paired with Markov state modelling suggest that the nepenthesin insert allosterically controls PM V catalysis through multiple mechanisms.

microbiology↗

bioRxiv2018

A Pre-transplant Blood-based Lipid Signature for Prediction of Antibody-mediated Rejection in Kidney Transplant Patients

There is a lack of biomarkers for pre-kidney transplant immune risk stratification to avoid over- or under-immunosuppression, despite substantial advances in kidney transplant management. Since the circulating lipidome is integrally involved in various inflammatory process and pathophysiology of several immune response, we hypothesized that the lipidome may provide biomarkers that are helpful in the prediction of kidney rejection. Serial plasma samples collected over 1-year post-kidney transplant from a prospective, observational cohort of 45 adult Kidney Transplant [antibody-mediated rejection (AMR)=16; stable controls (SC) =29] patients, were assayed for 210 unique lipid metabolites by quantitative mass spectrometry. A stepwise regularized linear discriminant analysis (RLDA) was used to generate models of predictors of rejection and multivariate statistics was used to identify metabolic group differences. The RLDA models include lipids as well as of calculated panel reactive antibody (cPRA) and presence of significant donor-specific antibody (DSA) at the time of transplant. Analysis of lipids on day of transplant (T1) samples revealed a 7-lipid classifier (lysophosphatidylethanolamine and phosphatidylcholine species) which discriminated between AMR and SC with a misclassification rate of 8.9% [AUC = 0.95 (95% CI = 0.84-0.98), R2 = 0.63]. A clinical model using cPRA and DSA was inferior and produced a misclassification rate of 15.6% [AUC = 0.82 (95% CI = 0.69-0.93), R2 = 0.41]. A stepwise combined model using 4 lipid classifiers and DSA improved the AUC further to 0.98 (95% CI = 0.89-1.0, R2 = 0.83) with a misclassification of only 2.2%. Specific classes of lipids were lower in AMR compared with SC. Serial analysis of SC patients demonstrated metabolic changes between T1 and 6 months (T2) post-transplant, but not between 6 and 12 (T3) months post-transplant. There were no overtime changes in AMR patients. Analysis of SC T1 vs AMR T3 (that at time of AMR) showed sustained decreased levels of lipids in AMR at the time of rejection. These findings suggest that lack of anti-inflammatory polyunsaturated phospholipids differentiate SC from AMR pre-transplant and at the time of rejection, and a composite model using a 4-lipid classifier along with DSA could be used for prediction of antibody-mediated rejection before transplant. HighlightsO_LIDespite significant advancements in kidney transplant treatment and intensive clinical follow-up monitoring, all rejection events are unlikely to be recognized at the beginning. As a result, efforts have been made to identify new biomarkers for kidney rejection detection. C_LIO_LIWhile lipids are known to be potent mediators of inflammation, pro-resolving processes, and other cell signaling cascades, lipidomics can be applied to identify reliable biomarkers to monitor disease severity and may also allow prediction of kidney rejection. C_LIO_LIOur lipidomic study shows lipid profile changes between antibody-mediated rejection group and stable control group as a function of different time point, pre and post-kidney transplantation. Furthermore, our study demonstrates that combining lipid and clinical parameters allow prediction of rejection on the day of the transplant. C_LIO_LIThese findings have the potential to change the present paradigm of pre and post-transplant monitoring and management of these patients by implementing an evidence-based risk stratification technique, resulting in a substantial improvement in kidney transplant success. C_LI

biochemistry↗