Biology subjects

Sit, K.

Publications and source records attributed to Sit, K..

3 recordsLinked to original sources

bioRxiv2025

GDF15 regulates necroptotic cell death through direct interaction with RIPK3

Enhancing the immunogenicity of tumor cells is a major objective in cancer therapy, particularly for tumors with low immune cell infiltration scores. Inducing immunogenic forms of programmed cell death (PCD) offers a promising strategy to strengthen anti-tumor immunity and improve therapeutic outcomes. Necroptosis, a highly inflammatory form of regulated cell death triggered by TNF signaling, can elicit robust immune activation. However, its regulation in tumor cells remains incompletely understood, limiting its therapeutic exploitation. To investigate the protein-protein interactions that govern necroptotic cell death in tumor cells, we established a co-Immunoprecipitation - Mass Spectrometry (coIP-MS) workflow using RIPK3, the central effector kinase driving necroptosis in TNF-induced signaling, as bait. This unbiased proteomic approach enables the identification of candidate regulators directly associated with the necrosome complex components under active necroptotic conditions. Among identified candidates, TCOF1 and GDF15 emerged as previously unrecognized modulators, with functional knockout of either gene markedly enhancing necroptotic cell death in tumor cells. Reciprocal IP experiments confirmed a direct interaction between GDF15 and RIPK3, supporting its mechanistic role as a negative regulator that suppresses necroptotic signaling. Thus, our findings extend the function of GDF15 beyond its established role in inflammation, uncovering an additional layer of regulation at the level of cell-intrinsic death signaling. Collectively, our findings position GDF15 as a RIPK3-interacting "brake" on necroptotic cell death and highlight TCOF1 as an additional inhibitory node. Our study underscores the potential of targeting necroptosis-suppressive mechanisms to influence PCD outcomes in tumors and demonstrates the power of coIP-MS for mapping TNF-induced interactions to reveal actionable molecular targets for tumor sensitization.

cell biology↗

bioRxiv2022

Automated classification of estrous stage in rodents using deep learning

The rodent estrous cycle modulates a range of biological functions, from gene expression to behavior. The cycle is typically divided into four stages, each characterized by distinct hormone concentration profiles. Given the difficulty of repeatedly sampling plasma steroid hormones from rodents, the primary method for classifying estrous stage is by identifying vaginal epithelial cell types. However, manual classification of epithelial cell samples is time-intensive and variable, even amongst expert investigators. Here, we use a deep learning approach to achieve classification accuracy at expert levels in a matter of seconds. Due to the heterogeneity and breadth of our input dataset, our deep learning approach ("EstrousNet") is highly generalizable across rodent species, stains, and subjects. The EstrousNet algorithm exploits the temporal dimension of the hormonal cycle by fitting classifications to an archetypal estrous cycle, highlighting possible misclassifications and flagging anestrus phases (e.g., pseudopregnancy). EstrousNet allows for rapid estrous cycle staging, improving the ability of investigators to consider endocrine state in their rodent studies.

cell biology↗

bioRxiv2021

Inhibiting retinoic acid mitigates vision loss in a mouse model of retinal degeneration

In degenerative retinal disorders, rod and cone photoreceptors die, causing vision impairment and blindness. Downstream neurons survive but undergo morphological and physiological remodeling, with some retinal ganglion cells (RGC) exhibiting heightened spontaneous firing. Retinoic acid (RA) has been implicated as the key signaling molecule that induces RGC hyperactivity, obscuring RGC light responses and reducing light avoidance behaviors triggered by residual rods and cones. However, evidence that RA-dependent remodeling corrupts image-forming vision has been lacking. Here we show that disulfiram, an FDA-approved drug that inhibits RA synthesis, and BMS 493, an RA receptor (RAR) inhibitor, reduce RGC hyperactivity and augment image detection in visually impaired mice. Functional imaging of visual cortical neurons shows that disulfiram and BMS 493 sharpen orientation-tuning and strengthen response fidelity to naturalistic scenes. These findings establish a causal link between RA-induced retinal hyperactivity and vision impairment and define molecular targets and candidate drugs for boosting image-forming vision in retinal degeneration.

neuroscience↗