Biology subjects

Petroff, M. G.

Publications and source records attributed to Petroff, M. G..

3 recordsLinked to original sources

bioRxiv2025

Autoimmune regulator deficiency causes sterile epididymitis and impacts male fertility through disruption of inorganic physiology

Autoimmune regulator (AIRE), a transcription factor expressed by medullary thymic epithelial cells, is required for shaping the self-antigen tolerant T cell receptor repertoire. Humans with mutations in AIRE suffer from Autoimmune Polyglandular Syndrome Type 1 (APS-1). Among many symptoms, men with APS-1 commonly experience testicular insufficiency and infertility, but the mechanisms causing infertility are unknown. Using an Aire-deficient mouse model, we demonstrate that male subfertility is caused by sterile epididymitis characterized by immune cell infiltration and extensive fibrosis. In addition, we reveal that the presence of autoreactive immune cells and inflammation in epididymides of Aire-deficient mice are required for iron (Fe) deposition in the interstitium, which is brought on by macrophages. We further demonstrate that male subfertility is associated with a decrease in metals zinc (Zn), copper (Cu), and selenium (Se) which serve as cofactors in several antioxidant enzymes. We also show increase in DNA damage of epididymal sperm of Aire-/- animals as a key contributing factor to subfertility. The absence of Aire results in autoimmune attack of the epididymis leading to fibrosis, Fe deposition, and Cu, Zn and Se imbalance, ultimately resulting in sperm DNA damage and subfertility. These results highlight the requirement of Aire to promote immune tolerance throughout the epididymis, disruption of which causes an imbalance of inorganic elements with resulting consequence on male fertility. Key pointsBreakdown of epididymal self-tolerance promotes disruption of inorganic elements. Autoimmunity causes interstitial fibrosis resulting in sperm DNA damage and subfertility. Elevated interstitial iron and macrophages contribute to fibrosis.

pathology↗

bioRxiv2022

Group B streptococcal membrane vesicles induce proinflammatory cytokine production and are sensed in an NLRP3 inflammasome-dependent mechanism in human macrophages

Group B Streptococcus (GBS) is a major cause of fetal and neonatal mortality worldwide. Many of the adverse effects associated with invasive GBS are associated with inflammation that leads to chorioamnionitis, preterm birth, sepsis, and meningitis; therefore, understanding bacterial factors that promote inflammation is of critical importance. Membrane vesicles (MVs), which are produced by many pathogenic and non-pathogenic bacteria, may modulate host inflammatory responses. In mice, GBS MVs injected intra-amniotically can induce preterm birth and fetal death. Although it is known that GBS MVs induce large-scale leukocyte recruitment into infected tissues, the immune effectors driving these responses are unclear. Here, we hypothesized that macrophages respond to GBS-derived MVs by producing proinflammatory cytokines and are recognized through one or more pattern recognition receptors. We show that THP-1 macrophage-like cells produce high levels of neutrophil- and monocyte-specific chemokines in response to MVs derived from different clinical isolates of GBS. Interleukin (IL)-1{beta} was significantly upregulated in response to MVs, which was independent of NF-kB signaling but dependent on both caspase-1 and NLRP3. These data indicate that MVs contain one or more pathogen-associated molecular patterns that can be sensed by the immune system. Furthermore, this study identifies the NLRP3 inflammasome as a novel sensor of GBS MVs. Our data additionally indicate that MVs may serve as immune effectors that can be targeted for immunotherapeutics, particularly given that similar responses were observed across this subset of GBS isolates.

immunology↗

bioRxiv2018

Visualizing murine placental extracellular vesicle data with tidyNano: a computational framework for analyzing and visualizing nanoparticle data in R

Extracellular vesicles (EVs) are increasingly recognized as important mediators of intercellular communication, and in mammals are generally classified as ~50-150nm exosomes, ~100-1000nm microvesicles, and apoptotic bodies, each arising as a result of different biological processes. EVs carry protein, lipids, and nucleic acids within the circulation, to target cells whereupon they mediate physiological changes. Due to their small size, quantification and characterization by conventional microscopy is not possible. However, nanoparticle tracking analysis (NTA) has provided a method to determine the fluid concentration and size of extracellular vesicles and other nanoparticles. While NTA provides statistical summaries of samples in an experiment, a recurring difficulty is the organization, manipulation, and management of raw particle count data because of the large size of datasets, and resultant vulnerability to user error. To address these limitations, we developed tidyNano, an R package that provides functions to import, clean, and quickly summarize raw NanoSight (Malvern Panalytical) data for efficient calculation of statistics and visualization. Here, we provide a framework for importing raw nanoparticle data and provide functions to facilitate rapid and efficient analysis, visualization and calculation of summary statistics. tidyNano was used to analyze murine plasma extracellular vesicles across gestation by aggregating and summarizing samples based on technical, biological and gestational parameters. In addition, we developed shinySIGHT, a Shiny web application that allows for interactive exploration and visualization of EV data. Using this package, we analyzed data generated from 36 samples of EV derived from the plasma of mice across gestation.\n\nPeripheral EV concentration increased linearly across pregnancy, with trending increases as early as gestation day (GD) 5.5 and significant rises at GD14.5, and 17.5 relative to EV concentrations in nonpregnant females. Thus, the data highlight the utility of the mouse as a model of EV biology in pregnancy. Further, the package provides a mechanism for seamless analysis of EV data generated by NanoSight. Importantly, this package provides a straightforward framework by which diverse types of large datasets can be simply and efficiently analyzed. tidyNano and shinySIGHT are freely available under the MIT license and is hosted on GitHub (https://nguyens7.github.io/tidyNano/).

cell biology↗