Biology subjects

Su, T.-P.

Publications and source records attributed to Su, T.-P..

3 recordsLinked to original sources

bioRxiv2025

Sigma-1 Receptor Promotes Glycolysis in Neuronal Systems by Suppressing GRIM19

Sigma-1 receptor (S1R) is a Ca2+ sensitive, ligand-operated receptor chaperone protein present on the endoplasmic reticulum (ER) membrane and more specifically at the mitochondria-associated ER membrane (MAM). Upon activation by ER calcium depletion or ligand binding, S1R can increase calcium efflux from the ER into the mitochondria by chaperoning IP3 receptor type3 (Ip3R3). Mitochondrial metabolism has an intricate relationship with glycolysis. Despite S1R affecting mitochondria, the relevance of S1R to glycolysis and its impact on the overall cellular energy metabolism is not known. This study utilizes wild-type (Wt) and S1R knockout (S1R KO) Neuro2a (N2a) cells and Wt and S1R KO mice for primary culture of cortical neurons studies and longitudinal in-vivo imaging. In this manuscript we describe the fundamental functions of S1R on glycolysis, mitochondrial activity and NAD+/NADH metabolism, keystone coenzymes essential for glycolysis and for mitochondrial activity. Both N2a cells and cortical neurons lacking S1R had reduced glycolytic activity, and increased mitochondria complex I protein GRIM19 but no change in mitochondrial oxygen consumption. Furthermore, we observed an increased NAD+/NADH ratio in S1R KO condition. Positron emission tomography revealed decreased [18F]fluorodeoxyglucose brain uptake in S1R KO mice. We observed that knocking down GRIM19 in S1R KO condition rescued the glycolysis deficit. Altogether, these data show for the first time that S1R modulates glycolysis and NAD metabolism in various neuronal systems. This new insight on the S1R function may lead to new therapeutic applications of S1R ligands where compromised glycolysis and cellular NAD+/NADH ratios occur such as aging and neurodegeneration.

cell biology↗

bioRxiv2025

p53-induced RNA-binding protein ZMAT3 inhibits transcription of a hexokinase to suppress mitochondrial respiration

The tumor suppressor p53 is a transcription factor that controls the expression of hundreds of genes. Emerging evidence indicates that the p53-induced RNA-binding protein ZMAT3 acts as a key splicing regulator that contributes to p53-dependent tumor suppression in vitro and in vivo. However, the mechanism by which ZMAT3 functions within the p53 pathway remains largely unclear. Here, we discovered a function of ZMAT3 in inhibiting transcription of HKDC1, a hexokinase that regulates glucose metabolism and mitochondrial respiration. Quantitative proteomics revealed HKDC1 as the most significantly upregulated protein in ZMAT3-depleted colorectal cancer cells. ZMAT3 depletion resulted in increased mitochondrial respiration, which was rescued by simultaneous depletion of HKDC1, suggesting that HKDC1 is a critical downstream effector of ZMAT3. Unexpectedly, ZMAT3 did not bind to HKDC1 RNA or DNA; however, proteomic analysis of the ZMAT3 interactome identified its interaction with the oncogenic transcription factor JUN. ZMAT3 depletion enhanced JUN binding to the HKDC1 locus, leading to increased HKDC1 transcription that was rescued upon JUN depletion, suggesting that JUN activates HKDC1 transcription in ZMAT3-depleted cells. Collectively, these findings uncover a mechanism by which ZMAT3 regulates transcription through JUN and demonstrate that HKDC1 is a key component of the ZMAT3-regulated transcriptome in the context of mitochondrial respiration regulation.

cancer biology↗

bioRxiv2025

Forecast Padding Enhances Accuracy and Robustness of EEG-Phase-Synchronized TMS

Closed-loop neuromodulation is a promising personalized treatment for various neuropsychiatric disor-ders, delivering precise stimuli based on real-time brain signals. However, its clinical potential is currently limited by technical challenges inherent in its real-time nature. This article addresses the primary technical challenges in EEG-Phase-Synchronized Transcranial Magnetic Stimulation (TMS), including poor stimulation accuracy and inefficient biomarker detection (correlated with deadlock). These challenges arise from the vulnerability of existing algorithms to filter edge effects. Inspired by predictive coding theory in neuroscience, we propose a novel signal padding method (forecast padding) to mitigate the filter edge effect. To properly quantify the improvements that forecast padding brings about in real-world systems, we introduce a novel delay-relevant validation framework and demonstrate its reliability using experimental data from a real system. Through this framework, we demonstrate that forecast padding significantly improves both stimulation accuracy and deadlock rate. Given the pervasive impact of filter edge effects in closed-loop neuromodulation and other signal processing domains, forecast padding shows broad application potential across various fields.

bioengineering↗