Biology subjects

You, K.

Publications and source records attributed to You, K..

7 recordsLinked to original sources

bioRxiv2025

BOGO: A Proteome-Wide Gene Overexpression Platform for Discovering Rational Cancer Combination Therapies

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/673780v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@19d5d7dorg.highwire.dtl.DTLVardef@64f7eborg.highwire.dtl.DTLVardef@d08b75org.highwire.dtl.DTLVardef@173c448_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG Cancer drug resistance remains a major barrier to durable treatment success, often leading to relapse despite advances in precision oncology. While combination therapies are being increasingly investigated, such as chemotherapy with small molecule inhibitors, predicting drug response and identifying rational drug combinations based on resistance mechanisms remain major challenges. Therefore, a proteome-wide, single-gene overexpression screening platform is essential for guiding rational therapy selection. Here, we present BOGO (Bxb1-landing pad human ORFeome-integrated system for a proteome-wide Gene Overexpression), a robust, scalable, and reproducible screening platform that enables single-copy, site-specific integration and overexpression of [~]19,000 human open across cancer cell models. Using BOGO, we identified drug-specific response drivers for 16 chemotherapeutic agents and integrated clinical datasets to uncover proliferation and resistance-associated genes with prognostic potential. Drug response similarity networks revealed both shared and unique mechanisms, highlighting key pathways such as autophagy, apoptosis, and Wnt signaling, and notable resistance-associated genes including BCL2, POLD2, and TRADD. In particular, we proposed a synergistic combination of the BCL2 family inhibitor ABT-263 (Navitoclax(R)) and the DNA analog TAS-102 (Lonsurf(R)), which revealed that lysosomal modulation is a key mechanism driving DNA analog resistance. This combination therapy selectively enhanced cytotoxicity in colorectal and pancreatic cancer cells in vitro, and demonstrated therapeutic benefit in vivo in both cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Together, these findings establish BOGO as a powerful gene overexpression perturbation platform for systematically identifying chemoresistance and chemosensitization drivers, and for discovering rational combination therapies. Its scalability and reproducibility position BOGO as a broadly applicable tool for functional genomics and therapeutic discovery beyond cancer resistance.

systems biology↗

bioRxiv2025

X-Atlas/Orion: Genome-wide Perturb-seq Datasets via a Scalable Fix-Cryopreserve Platform for Training Dose-Dependent Biological Foundation Models

The rapid expansion of massively parallel sequencing technologies has enabled the development of foundation models to uncover novel biological findings. While these have the potential to significantly accelerate scientific discoveries by creating AI-driven virtual cell models, their progress has been greatly limited by the lack of large-scale high-quality perturbation data, which remains constrained due to scalability bottlenecks and assay variability. Here, we introduce "Fix-Cryopreserve-ScRNAseq" (FiCS) Perturb-seq, an industrialized platform for scalable Perturb-seq data generation. We demonstrate that FiCS Perturb-seq exhibits high sensitivity and low batch effects, effectively capturing perturbation-induced transcriptomic changes and recapitulating known biological pathways and protein complexes. In addition, we release X-Atlas: Orion edition (X-Atlas/Orion), the largest publicly available Perturb-seq atlas. This atlas, generated from two genome-wide FiCS Perturb-seq experiments targeting all human protein-coding genes, comprises eight million cells deeply sequenced to over 16,000 unique molecular identifiers (UMIs) per cell. Furthermore, we show that single guide RNA (sgRNA) abundance can serve as a proxy for gene knockdown (KD) efficacy. Leveraging the deep sequencing and substantial cell numbers per perturbation, we also show that stratification by sgRNA expression can reveal dose-dependent genetic effects. Taken together, we demonstrate that FiCS Perturb-seq is an efficient and scalable platform for high-throughput Perturb-seq screens. Through the release of X-Atlas/Orion, we highlight the potential of FiCS Perturb-seq to address current scalability and variability challenges in data generation, advance foundation model development that incorporates gene-dosage effects, and accelerate biological discoveries.

genomics↗

bioRxiv2025

Effects of Exercise and Konjac on Lipid Metabolism and Mechanism in Obese Rats

ObjectiveTo study the effects of exercise and konjac on body weight and lipid metabolism in obese rats, and the possible mechanism of exercise combined with konjac on body weight and lipid metabolism. MethodsFifty male Sprague Dawley rats were randomly divided into 5 groups. After six weeks of intervention, blood lipid, body weight, liver weight, inflammatory factors, oxidative stress markers and proteins were measured. ResultsWeight and liver weight in HFD group were significantly higher (P<0.05, P<0.01) than those in CON group. Compared with HFD group, blood lipid index in intervention group were significantly decreased; The levels of MDA (P<0.01, P<0.05, P<0.05) and SOD (P<0.05) in intervention group were significantly decreased; the GSH levels in HAE group and HKE group were significantly increased(P<0.01, P<0.05); the levels of IL-6, TNF-, and leptin in HAE group (P<0.05, P<0.05, P<0.01) and HKE group (P<0.01, P<0.01, P<0.05) were significantly decreased; ApoA5 in intervention group was significantly increased (P<0.01), SREBP-1c and LXR was significantly decreased (P<0.01). ConclusionKonjac or exercise alone can improve the lipid metabolism, and the comprehensive effect is better. The mechanism of regulating lipid metabolism may be related to the expression of LXR, SREBP-1c and ApoA5.

biochemistry↗

bioRxiv2021

Serum Amyloid A promotes Acetaminophen-induced liverinjury by damaging sinusoidal endothelial cell and exacerbating platelet aggregation in liver

BackgroundAcetaminophen (APAP) is the most commonly used non-prescription antipyretic and analgesic drugs. Overuse of APAP can cause hepatotoxicity. Liver sinusoidal endothelial cells (LSECs) damage is an important early event in APAP-induced liver injury. Serum amyloid A (SAA) is an acute phase protein that mainly produced by hepatocytes, and promotes endothelial dysfunction via a pro-inflammatory and pro-thrombotic effect in atherosclerosis and renal disease. However, the role of SAA in APAP-induced liver injury remains unclear. MethodsIn this study, we used neutralizing antibody (anti-SAA) or antagonistic small peptide derived from sequence of human SAA1/2 (SAA-pep) to block the functional activity of Saa1/2 in mouse serum. Immunohistochemistry staining, Evans blue and platelet adhesion assays were performed to examine the liver damage, the integrity of sinusoidal endothelium and platelets accumulation in APAP-induce liver injury. ResultsOur study showed that in the early stage of APAP-induced acute liver injury in mice, the intrahepatic and serum Saa1/2 levels were significantly increased within 24 hours, and then gradually reduced to normal level from 3 days. Neutralization of Saa1/2 by antibodies or peptides effectively prevented the destruction of hepatic sinusoids, reduced the intrahepatic hemorrhage and platelet accumulation in liver, as well as increased the survival rate of mice treated with lethal dose of APAP. In vitro experiments showed that Saa1/2 aggravated LSECs death induced by APAP. Moreover, Saa1/2 promoted platelets adhesion on LSECs via Tlr2/Vcam-1 axis. ConclusionOur findings suggest that Saa1/2 promotes APAP-induced liver injury by damaged LSECs and exacerbated platelets aggregation. This study provides a potential target for intervention of acute liver injury/failure caused by hepatotoxic drugs such as APAP.

pharmacology and toxicology↗

bioRxiv2020

Quantifying liquid-liquid phase separation property of chromatin under physiological conditions using Hi-MS and Hi-C

BackgroundLiquid-liquid phase separation (LLPS) is an important organizing principle for biomolecular condensation and chromosome compartmentalization. However, while many proteins have been reported to undergo LLPS, quantitative and global analysis of chromatin LLPS property remains absent. ResultsHere, by combing chromatin associated protein pull-down, quantitative proteomics and 1,6-hexanediol treatment, we developed Hi-MS and defined anti-1,6-HD index of chromatin-associated proteins (AICAP) to quantitative measurement of LLPS property of chromatin-associated proteins in their endogenous state and physiological abundance. The AICAP values were verified by previously reported experiments and were reproducible across different MS platforms. Moreover, the AICAP values were highly correlate with protein functions. Proteins act in active/regulatory biological process often exhibit low AICAP values, while proteins act in structural and repressed biological process often exhibit high AICAP values. We further revealed that chromatin organization changes more in compartment A than B, and the changes in chromatin organization at various levels, including compartments, TADs and loops are highly correlated to the LLPS properties of their neighbor nuclear condensates. ConclusionsOur work provided the first global quantitative measurement of LLPS properties of chromatin-associated proteins and higher-order chromatin structure, and demonstrate that the active/regulatory chromatin components, both protein (trans) and DNA (cis), exhibit more hydrophobicity-dependent LLPS properties than the repressed/structural chromatin components.

cell biology↗

bioRxiv2019

Deep-learning enables proteome-scale identification of phase-separated protein candidates from immunofluorescence images

Intrinsically disordered region (IDR) analysis has been widely used in the screening of phase-separated proteins. However, the precise sequences determining phase separation remain unclear. Furthermore, a large number of phase-separated proteins that exhibit relatively low IDR content remain uncharacterized. Phase-separated proteins appear as spherical droplet structures in immunofluorescence (IF) images, which renders them distinguishable from non-phase-separated proteins. Here, we transformed the problem of phase-separated protein recognition into a binary classification problem of image recognition. In addition, we established a method named IDeepPhase to identify IF images with spherical droplet structures based on convolutional neural networks. Using IDeepPhase on proteome-scale IF images from the Human Protein Atlas database, we generated a comprehensive list of phase-separated candidates which displayed spherical droplet structures in IF images, allowing nomination of proteins, antibodies and cell lines for subsequent phase separation study.

bioinformatics↗

bioRxiv2018

AQ-seq: Accurate quantification of microRNAs and their variants

MicroRNAs (miRNAs) modulate diverse biological and pathological processes via post-transcriptional gene silencing. High-throughput small RNA sequencing (sRNA-seq) has been widely adopted to investigate the functions and regulatory mechanisms of miRNAs. However, accurate quantification has been limited owing to the severe ligation bias in conventional sRNA-seq methods. Here we present a high-throughput protocol, termed AQ-seq (accurate quantification by sequencing), that utilizes adapters with terminal degenerate sequences and a high concentration of polyethylene glycol (PEG), which removes the ligation bias during library preparation. By accurately measuring miRNAs and their variants (known as isomiRs), we identify alternatively processed miRNAs and correct the 5' end usage and strand preference that have been misannotated. We also uncover highly modified miRNAs that are uridylated and adenylated. Taken together, AQ-seq reveals the complexity of the miRNA isoform landscape, allowing us to refine miRNA annotation and to advance our understanding of miRNA regulation. Furthermore, AQ-seq can be adopted to improve other ligation-based sequencing methods including crosslinking-immunoprecipitation-sequencing (CLIP-seq) and ribosome profiling (Ribo-seq).

molecular biology↗