Biology subjects

Sohail, S.

Publications and source records attributed to Sohail, S..

4 recordsLinked to original sources

bioRxiv2026

ATP13A2 Loss of Function-Driven Polyamine Dysregulation Induces SAM Depletion and Epigenetic Astrocyte Toxicity

Aging is the strongest risk factor for neurodegeneration, yet how the human brain ages remains poorly understood. Loss-of-function (LOF) variants in ATP13A2 cause severe juvenile-onset Parkinsons disease, providing a window into the mechanisms that accelerate age-related neurodegeneration. ATP13A2-LOF causes lysosomal polyamine sequestration, but how this promotes pathogenesis remains unclear. We discovered that ATP13A2-LOF depletes cytosolic polyamines in astrocytes, triggering compensatory upregulation of de novo polyamine biosynthesis, which diverts S-adenosyl methionine (SAM) from DNA and histone methylation, leading to increased chromatin accessibility and epigenetic reprogramming of astrocytes into a neuroinflammatory state that releases neurotoxic cytokines that promote dopaminergic neuron death. In ATP13A2 knockout mice and human models, we find that genetic and pharmacological inhibition of SAM utilization in polyamine biosynthesis prevents astrocytic epigenetic reprogramming and promotes dopaminergic neuron survival. These findings reveal a direct link between polyamine metabolism, epigenetic dysfunction, and neurotoxic inflammation, uncovering new therapeutic opportunities in Parkinsons disease.

neuroscience↗

bioRxiv2026

Synthetic Immunological Niche Reveals Early Immune Dysregulationand Stratifies Therapeutic Response in Type 1 Diabetes

In Type 1 Diabetes (T1D), disease onset and response to immunotherapy vary widely among individuals, reflecting heterogeneous stage-specific immune dysregulation that remains undefined. To investigate this heterogeneity, we engineered a microporous polycaprolactone scaffold that forms a synthetic immunological niche (IN) upon subcutaneous implantation, enabling in vivo capture of systemic immune dysregulation. In non-obese diabetic (NOD) mice, longitudinal transcriptomic profiling of IN-infiltrating cells identified early-stage genes relatively enriched for myeloid cells, followed by progressive increases in T cell-associated dysregulation at later stages that distinguished T1D progressors from non-progressors. We derived an early-stage IN-based T1D gene signature capturing immune alterations. The signature stratified NOD progressors from non-progressors as early as 6 weeks of age and was conserved across human T1D datasets, distinguishing T1D from non-diabetic individuals in spleen and pancreatic lymph node samples, but not peripheral blood. Signature-based stratification further revealed enrichment of macrophage-associated TNF- pathways in NOD progressors, validated in human T1D islets. Given heterogeneous response to anti-TNF- therapy, IN profiling identified resistance-associated mechanisms and enabled derivation of a pathway score that prospectively distinguished treatment-sensitive from resistant mice prior to therapy, establishing the IN as a minimally invasive platform for detecting stage-wise immune dysregulation and stratifying immunotherapy response in T1D.

bioengineering↗

bioRxiv2025

Evidence for an indigenous female mouse urobiome

Mice have been used as a valuable model of understanding pathophysiological mechanisms of urinary tract infection for almost six decades. Mice offer many advantages including genetic manipulation to test the role of genes and mechanisms, the availability of germ-free mice, and similarities to humans in innate immune defenses and the strain-dependent presence of vesicoureteral reflux. However, like with humans, the mouse bladder urine above the urinary sphincter has generally been assumed to be sterile. Yet, given the presence of urobiomes in other mammals and the emerging role of the human urobiome in the defense of the urinary bladder and upper urinary tract, the existence of a mouse urobiome should be critically examined as indigenous microbiota may influence experimental results. To determine if an indigenous murine urobiome exists, we obtained expressed urine from two sets of female C57BL/6J mice during three different intervals using two different extraction and sequencing methods and analyzed them simultaneously by a single method. For one set, we also obtained urine by suprapubic aspiration, which we compared to the paired expressed urine samples. We conclude that an indigenous murine urobiome exists and that expressed urine contains post-urethral microbes.

microbiology↗

bioRxiv2022

Integrating current analyses of the breast cancer microbiome

Breast cancer is the second leading cause of cancer death for women in the US (American Cancer Society: About Breast Cancer, n.d.). Many cancer types have significant associations with their resident microbial communities - emerging evidence suggests that breast cancers also interact with the local tissue-associated microbiota. Studies have examined the relationship between breast cancer and its microbiome, however, the studies varied in their approaches used to evaluate these relationships. Microbiome research advances rapidly and analysis pipelines and databases are updated frequently. This dynamic environment makes inter-study comparisons and superficial evaluations challenging as no two studies are using the same standards for evaluation. Researchers have observed the microbiota of tumor tissue, surrounding normal sites, and healthy breast tissue from non-cancer individuals (Hieken et al., 2016; Urbaniak et al., 2016; Xuan et al., 2014), but they have not been able to translate their findings into information that can be used for breast cancer treatment or detection nor address what affect studying different variable regions has in their analysis. Within the majority of these studies, comparisons of the tumor tissue with adjacent normal tissue has revealed differences. This project will integrate all available studies related to breast cancer and the mammary microbiome to 1 reassess the original findings in light of advances in this rapidly progressing field and 2 incorporate all the data available as a large meta-analysis to identify general trends and specific differences across patient cohorts and studies.

bioinformatics↗