Biology subjects

Hoover, C. A.

Publications and source records attributed to Hoover, C. A..

4 recordsLinked to original sources

bioRxiv2025

Genetic dissection of microglia cannibalism reveals an IL10 signaling axis controls microglia lifespan

The development of complex organs, like the brain, demands a robust system for tissue remodeling and cellular debris clearance. In the brain, this function is performed by microglia, which must clear diverse debris substrates, including that caused by cell death. Although the subsequent fate of these phagocytic microglia is a critical regulatory point that impacts whether the brain resolves a debris environment, the genetic mechanisms that control microglia fate after debris clearance remain mostly unknown. To address this, we conducted a large-scale CRISPR screen in zebrafish using a custom-built robotic confocal microscope. We selected candidate genes from a single-cell RNA sequencing dataset of embryonic mouse microglia. This screen identified several modulators of microglial lifespan and cannibalism that are enriched in mouse and zebrafish microglia, including interleukin-10 receptor beta (il10rb), a receptor subunit for the cytokine IL10. Perturbation of il10, il10rb, and downstream signaling molecules JAK/STAT in zebrafish reduced microglial death. Expression analysis in mouse and zebrafish confirmed that microglia express both il10 and il10rb. Given the established role of IL10 in lysosomal remodeling, we hypothesized that it regulates microglial survival through lysosomal acidification. While il10rb perturbation did not alter lysosome number or size, it caused a significant reduction in LysoTracker-positive lysosomes, indicating decreased lysosomal acidification. Inhibiting v-ATPase also reduced microglial death, reinforcing the link between lysosomal pH and cell fate. Our findings reveal a cytokine-regulated mechanism where lysosomal dynamics determine the survival of phagocytic microglia. We propose that a necroptosis-cannibalism process functions as a quality control mechanism for microglial turnover, which is critical for refining neuroimmune cell function in the brain.

neuroscience↗

bioRxiv2025

sox17 mutagenesis reveals microglia can be impacted by genetic maternal effects

Embryonic development is precisely shaped by maternal and zygotic factors. These maternal factors exert their influence through maternal effects, a phenomenon where an offsprings phenotype is determined, at least in part, by the mothers environment and genotype. While environmental maternal effects can cause phenotypes that present both early and later in life, genetic maternal effects generally induce phenotypes in the earliest embryonic stages. Here, we reveal a genetic maternal effect that influences the development of cells that arise after early embryogenesis, highlighting that specific cell types can be susceptible to late-onset genetic maternal effects. Using zebrafish to study microglia, the resident immune cells of the brain, we identified a mutation in sry-related HMG box gene-17 (sox17) that exhibits a maternal effect phenotype that presents as a reduction of microglia in the brain and precursors in the yolk sac. We demonstrate that sox17 is expressed in microglia and their yolk sac precursors and is maternally-loaded. We show that sox17 restoration via embryonic injection reverses the maternal effect on microglia and yolk sac cells in sox17 mutants. To identify additional genes interacting with sox17, we nominated genes from scRNA sequencing analysis of mouse embryonic microglia to perform a genetic screen using CRISPR mutagenesis and a custom-built robot that captures confocal images of the zebrafish brain in high-throughput. This screen identified f11r.1, gas6, and mpp1 as modifiers of microglia abundance in the embryonic brain, which we demonstrated are also expressed in zebrafish microglia. Transcriptional and mutant analyses with these new modifiers suggest that sox17 positively regulates mpp1 transcription. These results demonstrate that microglia are susceptible to genetic maternal effects, in addition to their known sensitivity to environmental maternal effects. Our findings reveal a late-onset phenotype associated with the maternal genotype, expanding the recognized impact of genetic maternal effects beyond initial embryo viability and into long-term vigor.

neuroscience↗

bioRxiv2020

Adenomatous Polyposis Coli Loss Controls Cell Cycle Regulators and Response to Paclitaxel

Adenomatous Polyposis Coli (APC) is lost in approximately 70% of sporadic breast cancers, with an inclination towards triple negative breast cancer (TNBC). TNBC is treated with traditional chemotherapy, such as paclitaxel (PTX); however, tumors often develop drug resistance. We previously created APC knockdown cells (APC shRNA1) using the human TNBC cells, MDA-MB-157, and showed that APC loss induces PTX resistance. To understand the mechanisms behind APC-mediated PTX response, we performed cell cycle analysis and analyzed cell cycle related proteins. Cell cycle analysis indicated increased G2/M population in PTX-treated APC shRNA1 cells compared to PTX-treated controls, suggesting that APC expression does not alter PTX-induced G2/M arrest. We further studied the subcellular localization of the G2/M transition proteins, cyclin B1 and CDK1. The APC shRNA1 cells had increased CDK1, which was preferentially localized to the cytoplasm, and increased CDK6. RNA-sequencing was performed to gain a global understanding of changes downstream of APC loss and identified a broad mis-regulation of cell cycle-related genes in APC shRNA1 cells. Our studies are the first to show an interaction between APC and taxane response in breast cancer. The implications include designing combination therapy to re-sensitize APC-mutant breast cancers to taxanes using the specific cell cycle alterations.

cancer biology↗

bioRxiv2017

MAGI: A Bayesian-like method for metabolite, annotation, and gene integration

Metabolomics is a widely used technology for obtaining direct measures of metabolic activities from diverse biological systems. However, ambiguous metabolite identifications are a common challenge and biochemical interpretation is often limited by incomplete and inaccurate genome-based predictions of enzyme activities (i.e. gene annotations). Metabolite, Annotation, and Gene Integration (MAGI) generates a metabolite-gene association score using a biochemical reaction network. This is calculated by a method that emphasizes consensus between metabolites and genes via biochemical reactions. To demonstrate the potential of this method, we applied MAGI to integrate sequence data and metabolomics data collected from Streptomyces coelicolor A3(2), an extensively characterized bacterium that produces diverse secondary metabolites. Our findings suggest that coupling metabolomics and genomics data by scoring consensus between the two increases the quality of both metabolite identifications and gene annotations in this organism. MAGI also made biochemical predictions for poorly annotated genes that were consistent with the extensive literature on this important organism. This limited analysis suggests that using metabolomics data has the potential to improve annotations in sequenced organisms and also provides testable hypotheses for specific biochemical functions. MAGI is freely available for academic use both as an online tool at https://magi.nersc.gov and with source code available at https://github.com/biorack/magi.

bioinformatics↗