Zhou, H.-L. | bioRxiv Science

bioRxiv2025

The denitrosylase SCoR2 controls cardioprotective metabolic reprogramming

Acute myocardial infarction (MI) is a leading cause of morbidity and mortality, and therapeutic options remain limited. Endogenously generated nitric oxide (NO) is highly cardioprotective, but protection is not replicated by nitroso-vasodilators (e.g., nitrates, nitroprusside) used in clinical practice, highlighting specificity in NO-based signaling and untapped therapeutic potential. Signaling by NO is mediated largely by S-nitrosylation, entailing specific enzymes that form and degrade S-nitrosothiols in proteins (SNO-proteins), termed nitrosylases and denitrosylases, respectively. SNO-CoA Reductase 2 (SCoR2; product of the Akr1a1 gene) is a recently discovered protein denitrosylase. Genetic variants in SCoR2 have been associated with cardiovascular disease, but its function is unknown. Here we show that mice lacking SCoR2/Akr1a1 exhibit robust protection in an animal model of MI. SCoR2 regulates ketolytic energy availability, antioxidant levels and polyol homeostasis via S-nitrosylation of key metabolic effectors. Human cardiomyopathy shows reduced SCoR2 expression and an S-nitrosylation signature of metabolic reprogramming, mirroring SCoR2-/- mice. Deletion of SCoR2 thus coordinately reprograms multiple metabolic pathways--ketone body utilization, glycolysis, pentose phosphate shunt and polyol metabolism--to limit infarct size, establishing SCoR2 as a novel regulator in the injured myocardium and a potential drug target. Impact statementMice lacking the denitrosylase enzyme SCoR2 demonstrate robust cardioprotection resulting from coordinate reprogramming of multiple metabolic pathways. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/642752v2_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@72bfbborg.highwire.dtl.DTLVardef@189cbc4org.highwire.dtl.DTLVardef@1a0cc51org.highwire.dtl.DTLVardef@1c61004_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2021

Chord: Identifying Doublets in Single-Cell RNA Sequencing Data by an Ensemble Machine Learning Algorithm

High-throughput single-cell RNA sequencing (scRNA-seq) is a popular method, but it is accompanied by doublet rate problems that disturb the downstream analysis. Several computational approaches have been developed to detect doublets. However, most of these methods have good performance in some datasets but lack stability in others; thus, it is difficult to regard a single method as the gold standard for each scenario, and it is a difficult and time-consuming task for researcher to choose the most appropriate software. To address these issues, we propose Chord which implements a machine learning algorithm that integrates multiple doublet detection methods. Chord had a higher accuracy and stability than the individual approaches on different datasets containing real and synthetic data. Moreover, Chord was designed with a modular architecture port, which has high flexibility and adaptability to the incorporation of any new tools. Chord is a general solution to the doublet detection problem.

bioinformatics↗