Biology subjects

Hsieh, Y.-J.

Publications and source records attributed to Hsieh, Y.-J..

5 recordsLinked to original sources

bioRxiv2026

HSPB8 regulates CTP synthase filaments to couple nucleotide metabolism and autophagy in tumors

Metabolic adaptation and proteostasis are essential for tumor survival under nutrient stress, yet how these processes are mechanistically integrated remains unclear. Here, we identify CTP synthase (CTPS) filament dynamics as a regulatory nexus linking nucleotide metabolism to autophagic flux. Under glutamine deprivation--a hallmark of poorly vascularized solid tumors--CTPS undergoes polymerization into filamentous assemblies that exhibit reduced enzymatic activity. We demonstrate that filament formation is driven by intracellular asparagine availability and stabilized by the accumulation of misfolded proteins. Using APEX2-based proximity labeling and proteomics, we identify the small heat shock protein HSPB8 as a filament-associated regulator. HSPB8, acting within the chaperone-assisted selective autophagy (CASA) pathway, antagonizes CTPS polymerization by promoting clearance of misfolded proteins, thereby restoring soluble, catalytically active CTPS. Filament disassembly increases CTP production and enhances synthesis of autophagy-related phospholipids, including phosphatidylinositol and phosphatidylethanolamine, resulting in accelerated autophagic flux. Cells expressing filament-deficient CTPS mutants display elevated autophagosome formation and increased LC3-II accumulation upon lysosomal blockade, confirming enhanced flux. In vivo, disruption of CTPS filament assembly impairs xenograft tumor growth and is associated with excessive autophagy. Analysis of TCGA datasets further reveals that high CTPS and low HSPB8 expression correlate with poor patient survival across multiple cancers. Collectively, our findings establish CTPS filament dynamics as a proteostasis-sensitive metabolic switch that coordinates nucleotide biosynthesis with autophagy, revealing a previously unrecognized vulnerability in tumors adapting to nutrient limitation.

cell biology↗

bioRxiv2023

Engineering Nanomolar Potent Protein-based Inhibitors for Papain-like Protease Guided by Residue Correlation Network

Identifying critical residues in protein-protein binding and efficiently designing stable and specific protein binders is challenging. In addition to direct contacts in a protein-protein binding interface, our study employs computation modeling to reveal the essential network of residue interaction and dihedral angle correlation critical in protein-protein recognition. We propose that mutating residues regions exhibited highly correlated motions within the interaction network can efficiently optimize protein-protein interactions to create tight and selective protein binders. We validated our strategy using ubiquitin (Ub) and MERS coronaviral papain-like protease (PLpro) complexes, where Ub is one central player in many cellular functions and PLpro is an antiviral drug target. Our designed UbV with 3 mutated residues resulted in a [~]3,500-fold increase in functional inhibition, compared with the wild-type Ub. Further optimization by incorporating 2 more residues within the network, the 5-point mutant achieved a KD of 1.5 nM and IC50 of 9.7 nM. The modification led to a 27,500-fold and 5,500-fold enhancements in affinity and potency, respectively, as well as improved selectivity, without destabilizing the UbV structure. Our study highlights residue correlation and interaction networks in protein-protein interaction, introduces an effective approach to design high affinity protein binders for cell biology and future therapeutics solutions.

biophysics↗

bioRxiv2022

A Hybrid Learning Method with High Specificity for Excluding Non-chromosome Objects Problem

BackgroundFor automated analysis of metaphase chromosome images, the chromosome objects on the images need to be segmented in advance. However, the segmentation results often contain a lot of non-chromosome objects in the images. Hence, elimination of non-chromosome objects is an essential process in automated chromosome image analysis. This study aims to exclude non-chromosome objects and preserve as many chromosomes as possible. In this paper, we propose a hybrid deep learning method to exclude non-chromosome objects from metaphase chromosome images. MethodThe proposed method consists of two phases. In the first phase, two classification results are obtained from feature-based and image-based convolutional neural networks (CNN) separately (the feature-based CNN uses the features of the images as input; the image-based CNN uses the images as input directly). In the second phase, the prediction results from the above two CNNs are combined and resent to another CNN to obtain final classification results. ResultsThe proposed method uses 18,757 non-chromosome objects and 43,398 chromosomes (including single and multiple overlapped chromosomes) from 1038 chromosome images to evaluate the performance. The experimental results show that the proposed method can detect and exclude 99.61% (18,683/18,757) of the non-chromosome objects and preserve 99.95% (43,375/43,398) of the chromosomes for further analysis. ConclusionsThe proposed method has a high effectiveness on excluding non-chromosome objects and could be used as a preprocessing procedure for chromosome image analysis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/511091v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1183f1forg.highwire.dtl.DTLVardef@d84d69org.highwire.dtl.DTLVardef@c23122org.highwire.dtl.DTLVardef@127e4e9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic AbstractC_FLOATNO C_FIG

bioinformatics↗

bioRxiv2020

A Newly Identified Role for IL-22 in Bladder Immunity

Bacterial and parasitic urinary tract infections(UTI) affect many, but our understanding of associated immunity remains poor. Prior work indicates interleukin-22(IL-22) is a key cytokine during infection of other epithelia. We hypothesized IL-22 is crucial during UTI. IL-22-null(KO) and wild-type(wt) mice underwent bladder wall injection with S. haematobium eggs or transurethral infection with uropathogenic E. coli UTI89. IL-22 and its soluble binding protein, IL-22BP, were increased in the bladder after S. haematobium egg injection. Genes typically induced by IL-22(CXCL2, REG3G[antimicrobial defense protein]], S100A8, S100A9, and Areg) were expressed at higher levels following S. haematobium egg injection. IL-22 stimulation of bladder tissue induced REG3B expression. IL-22 receptor alpha-1 expression was detectable in the urothelium by immunofluorescence and qPCR. Injection of S. haematobium eggs into IL-22-KO vs wt mice triggered differential expression of genes related to transferase activity(transferring alkyl or aryl groups) and epithelial cell development. Numerous uroplakin genes were downregulated in egg-injected, IL-22-KO mice versus their wt counterparts. These decreases in uroplakin expression suggest that, as in the gut, IL-22 is important for replenishing the epithelium during infection-related injury. Following transurethral infection with UTI89, IL-22-KO mice had lower bacterial counts in their urine, bladder, and kidneys. Giving stabilized IL-22 cytokine (IL-22-Fc) to UTI89-infected mice led to higher kidney bacterial counts and increased morbidity. Our data suggest that IL-22 is indeed important in urinary tract immunity, and may interfere with clearance of bacteria from the urinary tract, potentially through its role in maintenance of mature urothelium.

immunology↗

bioRxiv2018

Profiling of urine bacterial DNA to identify an oncobiome in a mouse model of bladder cancer

IntroductionRecurrent urinary tract infections have been linked to increased risk of bladder cancer, suggesting a potential role of the urinary microbiome in bladder cancer pathogenesis.\n\nObjectiveCompare the urinary microbiomes in mice with and without bladder.\n\nMethodsLongitudinal study of mice exposed to a dilute bladder-specific carcinogen (0.05% n-butyl-n-(4-hydroxybutyl) nitrosamine, BBN mice, n=10), and control mice (n=10). Urine was sampled monthly from individual mice for 4 months. Microbial DNA was extracted from the urine, and the V4 region of the 16S rRNA gene sequenced. Animals were sacrificed and their bladders harvested for histopathology. Bladder sections were graded by a blinded pathologist. The composition and diversity of the urinary microbiome were compared between the BBN and control mice. Metabolic pathway analysis was completed using PICRUST.\n\nResultsBladder histology in the BBN group showed normal tissue with inflammation (BBN-normal, n=5), precancerous pathologies, (BBN-precancerous, n=3), and invasive cancer (BBN-cancer, n=2). Alpha diversity did not differ between the mice exposed to BBN and the control mice at any timepoint. There were no differences in the urinary microbiomes between the BBN and control mice at baseline. At month 4, mice exposed to BBN had higher proportion of both Gardnerella and Bifidobacterium compared to control mice. There were no differences in proportions of specific bacteria between either the BBN-precancer or BBN-cancer and controls at month 4. However, the BBN-normal mice had higher proportions of Gardnerella, Haemophilus, Bifidobacterium, and Ureaplasma Actinobaculum, and lower proportions of Actinomyces, compared to control mice at month 4. Functional pathway analysis demonstrated increases in genes related to purine metabolism, phosphotransferase systems, peptidases, protein folding, and bacterial toxins in the BBN-mice compared to control mice at month 4.\n\nConclusionMice exposed to 4 months of BBN, a bladder-specific carcinogen, have distinct urine microbial profiles compared to control mice.

cancer biology↗