Biology subjects

Blazier, A.

Publications and source records attributed to Blazier, A..

3 recordsLinked to original sources

bioRxiv2025

Maintenance of chronic neuroinflammation in multiple sclerosis via interferon signaling and CD8 T cell-mediated cytotoxicity

Chronic neuroinflammation and neurodegeneration are critical but unresolved drivers of disability accumulation in progressive multiple sclerosis (MS). Chronic active white matter lesions (CAL), identifiable radiologically as paramagnetic rim lesions (PRL), indicate progression-relevant chronic neuroinflammation. Using single-cell transcriptomics (scRNAseq) and T-cell receptor sequencing (scTCR-seq), we profiled cerebrospinal fluid (CSF) and blood immune cells of 34 radiologically characterized adults with MS (17 untreated, 6 treated with B-cell-depletion) and 5 healthy controls. Coupled with proteomics, we found PRL-associated enrichment of interferon (IFN) signaling and upregulation of TCR signaling in CSF and blood. This was accompanied by clonal expansion of CD8+ T effector memory (TEM) cells, with the highly expanded clonal cells exhibiting T helper type 1 (TH1) and cytotoxic profiles. Validating the cytotoxic immune profile in blood using flow cytometry, we identified a cellular correlate of PRL exhibiting features of CD8+ TEMRA cells. Despite B-cell depletion, PRL-associated neuroinflammation, driven by myeloid activation and CD8+ T-cell cytotoxicity, persisted. Serum and CSF proteomic networks showed PRL-pertinent signatures, including networks unaffected by B-cell depletion. Using in silico perturbation, we nominated therapeutic targets, including MYD88, TNF, MYC, TYK2, JAK2, and BTK, for alleviating chronic neuroinflammation in MS. Our findings highlight mechanisms of chronic neuroinflammation in MS and point to potential biomarkers for monitoring disease progression.

immunology↗

bioRxiv2024

Glial state changes and neuroinflammatory RIPK1 signaling are a key feature of ALS pathogenesis

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that causes motor neuron loss in the brain and spinal cord. Neuroinflammation driven by activated microglia and astrocytes is prominent in ALS, but an understanding of cell state dynamics and which pathways contribute to the disease remains unclear. Single nucleus RNA sequencing of ALS spinal cords demonstrated striking changes in glial cell states, including increased expression of inflammatory and glial activation markers. Many of these signals converged on RIPK1 and the necroptotic cell death pathway. Activation of the necroptosis pathway in ALS spinal cords was confirmed in a large bulk RNA sequencing dataset and at the protein level. Blocking RIPK1 kinase activity delayed symptom onset and motor impairment and modulated glial responses in SOD1G93A mice. We used a human iPSC-derived motor neuron, astrocyte, and microglia tri-culture system to identify potential biomarkers secreted upon RIPK1 activation, inhibited pharmacologically in vitro, and modulated in the CSF of people with ALS treated with a RIPK1 inhibitor. These data reveal ALS-enriched glial populations associated with inflammation and suggest a deleterious role for neuroinflammatory signaling in ALS pathogenesis.

neuroscience↗

bioRxiv2018

Reconciling high-throughput gene essentiality data with metabolic network reconstructions

The identification of genes essential for bacterial growth and survival represents a promising strategy for the discovery of antimicrobial targets. Essential genes can be identified on a genome-scale using transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification of both condition-independent and condition-dependent essential genes. To illustrate the scope of these challenges, we perform a large-scale comparison of multiple published Pseudomonas aeruginosa gene essentiality datasets, revealing substantial differences between the screens. We then contextualize essentiality using genome-scale metabolic network reconstructions and demonstrate the utility of this approach in providing functional explanations for essentiality and reconciling differences between screens. Genome-scale metabolic network reconstructions also enable a high-throughput, quantitative analysis to assess the impact of media conditions on the identification of condition-independent essential genes. Our computational model-driven analysis provides mechanistic insight into essentiality and contributes novel insights for design of future gene essentiality screens and the identification of core metabolic processes.\n\nAuthor SummaryWith the rise of antibiotic resistance, there is a growing need to discover new therapeutic targets to treat bacterial infections. One attractive strategy is to target genes that are essential for growth and survival. Essential genes can be identified with transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification and analysis of essential genes. We performed a large-scale comparison of multiple gene essentiality screens of the microbial pathogen Pseudomonas aeruginosa. We implemented a computational model-driven approach to provide functional explanations for essentiality and reconcile differences between screens. The integration of computational modeling with high-throughput experimental screens may enable the identification of drug targets with high-confidence and provide greater understanding for the development of novel therapeutic strategies.

systems biology↗