Biology subjects

CHEN, Y.

Publications and source records attributed to CHEN, Y..

5 recordsLinked to original sources

bioRxiv2026

Ybx1 Deficiency Causes ROS-Driven IBD-Like Intestinal Inflammation and Postnatal Lethality

Y box-binding protein 1 (YB-1; Ybx1/ybx1) is essential for zebrafish development. Maternal ybx1-/- mutants exhibited embryonic lethality, whereas zygotic mutants (Zybx1-/-) showed high postnatal mortality between 10 and 20 dpf, although a small fraction survived to adulthood. Western blot and immunohistochemical analysis revealed strong, transient expression of Ybx1 in intestinal enterocytes from 3 to 5 days post-fertilization (dpf), followed by rapid ubiquitin-mediated degradation at 6 dpf, coinciding with defective intestinal development and compromised gut homeostasis. RNA-seq analysis identified elevated reactive oxygen species (ROS) and upregulation of matrix metalloproteinases mmp9 and mmp13a in Zybx1-/- larvae. Antioxidant treatment with ascorbic acid rescued postnatal lethality and alleviated intestinal defects, whereas prooxidant exposure exacerbated them. Pharmacological inhibition of Mmp9 or Mmp13a similarly prevented lethality, highlighting a ROS-MMP axis driving tissue damage. By 30 dpf, surviving mutants exhibited progressive intestinal impairment and severe pathology. These findings demonstrate that Ybx1 deficiency triggers ROS-dependent intestinal inflammation, MMP-mediated gut damage, and postnatal lethality, establishing Ybx1-deficient zebrafish as a robust model for studying inflammatory bowel disease (IBD)-like intestinal disorders.

developmental biology↗

bioRxiv2025

Modulation of signal response by small RNAs through feed-forward loops

In response to environmental changes, bacteria have evolved sophisticated regulatory networks that incorporate small RNAs (sRNAs) and transcription factors (TFs) to fine-tune cellular physiology. Both sRNAs and TFs modulate gene expression, but the former function via post-transcriptional mechanisms, while the latter act at the transcriptional level. However, it remains unclear why both regulatory layers are conserved through evolution, rather than one being sufficient. Here, we experimentally identified that CRP, a global regulator, regulates 25 small RNAs (sRNAs) in Escherichia coli. Interestingly, CRP also controls 80% of the target genes of these sRNAs. This architecture led us to identify 34 novel sRNA-mediated feed-forward loops (sFFLs)--circuits where CRP regulates both an sRNA and its target--within the CRP regulon. Quantitative PCR analysis of 16 such sFFLs revealed that each type possesses a distinct cAMP dose-response profile, suggesting that different sFFL structures embody unique regulatory logic. Specifically, coherent and incoherent type 3 and 4 sFFLs exhibit broader dynamic ranges in their dose-response compared to open-loop controls. Coherent and incoherent type 1 and 2 sFFLs appear more energy-efficient. Altogether, we propose that sRNAs cooperate with TFs through sFFLs to optimize both the energy efficiency and the diversity of signal response profiles. Therefore, sRNAs serve as critical components integrating transcriptional and post-transcriptional networks across diverse cellular pathways.

systems biology↗

bioRxiv2025

Sirtuin 3 with rs11607019 regulates gene expression in 293 cells

BackgroundSIRT3 is a NAD+ dependent deacetylase located in mitochondria and plays a critical role in various biological processes such as aging and cancer. Recent GWAS analyses have identified an intronic SNP, rs11607019, that significantly influences platelet function. MethodsTo investigate the genome-wide transcriptional effects of this variant, we performed site-directed mutagenesis experiments. ResultsOur results demonstrate that rs11607019 upregulates GABRE, COL12A1, PLEKHG4B, and SERF1B, while downregulating APOBEC3G in 293 cells, without cell tumor mutational burden karyotype phenotype. ConclusionThese findings suggest that rs11607019 is a strong candidate locus for blood cell phenotyping and may warrant further investigation in relation to kidney-related diseases in latent populations.

cell biology↗

bioRxiv2023

Robust and Accurate Doublet Detection of Single-Cell Sequencing Data via Maximizing Area Under Precision-Recall Curve

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity by offering detailed profiles of individual cells within diverse specimens. However, due to the limitations of sequencing technology, two or more cells may be captured in the same droplet and share the same barcode. These incidents, termed doublets or multiplets, can lead to artifacts in single-cell data analysis. While explicit experimental design can mitigate these issues with the help of auxiliary cell markers, computationally annotating doublets has a broad impact on analyzing the existing public single-cell data and reduces potential experimental costs. Considering that doublets form only a minor fraction of the total dataset, we argue that current doublet detection methods, primarily focused on optimizing classification accuracy, might be inefficient in performing well on the inherently imbalanced data in the area under the precision-recall curve (AUPRC) metric. To address this, we introduce RADO (Robust and Accurate DOublet detection) - an algorithm designed to annotate doublets by maximizing the AUPRC, effectively tackling the imbalance challenge. Benchmarked on 18 public datasets, RADO outperforms other methods in terms of doublet score and achieves similar performance to the current best methods in doublet calling. Furthermore, beyond its application in single-cell RNA-seq data, we demonstrate RADOs adaptability to single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data, where it outperforms other scATAC-seq doublet detection methods. RADOs open-source implementation is available at: https://github.com/poseidonchan/RADO.

bioinformatics↗

bioRxiv2018

Different obesity phenotypes correlated with the PI3K-AKT signaling pathway in tree shrews

ObjectiveTo identify the meaningful co-expressed gene network in mRNA extracted from adipose tissue representing different obesity phenotypes in a new tree shrew model. Furthermore, to locate the potential drug target based on analyzing the possible pathways and hub genes responsible for obesity.\n\nMethodsTen tree shrews were selected from F1 populations and divided into 3 groups based on their Lees index for mRNA sequencing. We identified clusters of highly correlated genes (modules) by weighted gene co-expression network analysis (WGCNA).\n\nResultsThree modules were strongly correlated with not less than one obesity phenotype (associations ranging from -0.94 to 0.85, P < 0.01). The ribosome, lysosome and ubiquitin-mediated proteolysis pathways were the most enriched pathways of the blue (including 481 genes), brown (389 genes) and turquoise (1781 genes) modules, respectively. The hub genes were determined, including UBA52 in the blue module, AKT1 in the brown module and LRRK2 in the turquoise module.\n\nConclusionsWe characterized different obesity phenotypes in tree shrews for the first time. The most represented gene AKT1 indicated the vital role of the PI3K-AKT pathway through interactions with downstream pathways and differentially expressed genes (DEGs). The work will help provide new insight into the prevention and treatment strategies of obesity.

genetics↗