Search bioRxiv⌕ Search

Biology subjects

Mar, J.

Publications and source records attributed to Mar, J..

3 recordsLinked to original sources

Astrocyte Store-Released Calcium Modulates Visual Cortex Synapse Development and Circuit Function.

Astrocytes, a major class of glial cells, are critical regulators of synapse development during early postnatal life. While dysregulation of this process is implicated in numerous neurological disorders, the precise mechanisms by which astrocytes guide synapse formation and maturation remain poorly understood. A central signaling pathway for astrocytes is the dynamic fluctuation of intracellular calcium (Ca2+), which can arise from various sources and modulate a wide range of downstream effects. A key astrocytic mechanism for integrating neuronal signals is the release of Ca2+ from endoplasmic reticulum stores mediated by the IP3 Receptor Type 2 (IP3R2). Although defects in this signaling pathway have been mainly linked to adult brain dysfunction, its role in shaping synaptic development, a period when astrocyte-neuronal communication is established, is largely unknown. Here, we investigated the role of IP3R2-mediated Ca2+ signaling in astrocyte-dependent regulation of synapse development in the mouse visual cortex. Using a combination of histological, molecular, and circuit-level approaches, we found that loss of astrocytic IP3R2 leads to significant deficits in the maturation of glutamatergic but not GABAergic synapses. These synaptic disruptions were accompanied by attenuated visually evoked neuronal activation and impaired behavioral responses to visual threat stimuli. We further show that astrocytic morphological complexity is diminished in the absence of IP3R2, suggesting that store-released Ca2+ is required for both the structural and functional maturation of astrocyte-neuron interactions. Our findings establish a critical role for astrocytic IP3R2-mediated Ca2+ signaling in shaping excitatory circuit development and the emergence of visually driven behaviors.

neuroscience↗

The shape of gene expression distributions matter: how incorporating distribution shape improves the interpretation of cancer transcriptomic data

In genomics, we often impose the assumption that gene expression data follows a specific distribution. However, rarely do we stop to question this assumption or consider its applicability to all genes in the transcriptome. Our study investigated the prevalence of genes with expression distributions that are non-Normal in three different tumor types from the Cancer Genome Atlas (TCGA). Surprisingly, less than 50% of all genes were Normally-distributed, with other distributions including Gamma, Bimodal, Cauchy, and Lognormal were represented. Relevant information about cancer biology was captured by the genes with non-Normal gene expression. When used for classification, the set of non-Normal genes were able to discriminate between cancer patients with poor versus good survival status. Our results highlight the value of studying a genes distribution shape to model heterogeneity of transcriptomic data. These insights would have been overlooked when using standard approaches that assume all genes follow the same type of distribution in a patient cohort.

bioinformatics↗

A novel approach to modeling transcriptional heterogeneity identifies the oncogene candidate CBX2 in invasive breast carcinoma

Oncogenes promote the development of and serve as therapeutic targets against subsets of cancers. Here, a new statistical approach that captures transcriptional heterogeneity in tumor and adjacent normal (i.e. tumor-free) mRNA expression profiles was developed to identify oncogene candidates that were overexpressed in a subset of breast tumors. Intronic DNA methylation was strongly associated with the overexpression of chromobox 2 (CBX2), an oncogene candidate that was identified using our method but not through prior analytical approaches. CBX2 overexpression in breast tumors was associated with the upregulation of genes involved in cell cycle progression and is associated with poorer 5-year survival. The predicted function of CBX2 was confirmed in vitro providing the first experimental evidence that CBX2 promotes breast cancer cell growth. Modeling mRNA expression heterogeneity in tumors is a novel powerful approach with the potential to uncover therapeutic targets that benefit subsets of cancer patients.

systems biology↗