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Biomedical subjects

Xiang Wang

Publications and source records attributed to Xiang Wang.

9 recordsLinked to original sources

Comprehensive multi-post-translational modifications profiling reveals age-associated remodeling in skeletal muscle.

Sarcopenia, characterized by the progressive loss of skeletal muscle mass and function, is a major hallmark of aging. Post-translational modifications (PTMs) play essential roles in regulating protein activity and cellular homeostasis; however, how multiple PTMs are remodeled during skeletal muscle aging remains incompletely characterized. Here, we performed comprehensive multi-layered proteomic profiling of skeletal muscle from young (3-month-old) and aged (24-month-old) mice, systematically quantifying the global proteome together with five major PTMs: acetylation, phosphorylation, N-glycosylation, O-glycosylation, and ubiquitination. In total, we identified 5 337 proteins and mapped thousands of PTM sites, generating an integrated atlas of age-associated proteomic and PTM remodeling in skeletal muscle. Pathway enrichment analyses revealed distinct modification-specific patterns: acetylation and phosphorylation were predominantly associated with metabolic and mitochondrial-related pathways; N-glycosylation was enriched in immune- and secretory pathway-related processes; O-glycosylation was associated with muscle contraction-related pathways; and ubiquitination was preferentially linked to cytoskeletal organization in muscle cells. Correlation analyses further uncovered diverse association patterns among different PTMs across protein- and modification-level datasets. Phosphorylation and ubiquitination exhibited consistent positive associations, whereas acetylation and ubiquitination showed both inverse and concordant co-variation patterns across subsets of proteins. Phosphorylation and O-glycosylation displayed heterogeneous association patterns across different proteins, and acetylation and phosphorylation demonstrated positive correlations with distinct age-associated directional changes across protein subsets. Together, these results provide a comprehensive, multi-dimensional view of age-associated remodeling of the skeletal muscle proteome and multiple PTM layers, offering a valuable resource for understanding molecular alterations accompanying muscle aging and sarcopenia.

Animals

Genomic and functional characterization of sugar transporters reveals potential roles in sugar accumulation in a modern sugarcane cultivar.

Sugarcane (Saccharum spp.) is a globally important sugar crop whose productivity depends on efficient sugar transport from source to sink organs. However, systematic identification and functional characterization of sugar transporters (STs) in sugarcane cultivars remain limited. Here, we identified 190 non-redundant ST genes in sugarcane cultivar Guitang 42 (GT42) and phylogenetically classified them into nine groups within the Monosaccharide Transporter (MST), Sucrose Transporter (SUT), and Sugars Will Eventually be Exported Transporters (SWEET) families. Comparative evolutionary analysis revealed significant lineage-specific expansions in the PMT, STP subfamilies, and SWEET families compared to diploid and wild relatives, likely driven by polyploidization and intensive selection for sugar yield. Transcriptomic profiling across tissues and internode elongation stages demonstrated marked tissue-specific and developmental expression patterns. Yeast complementation assays confirmed the transport activity of candidate MSTs, SUTs and SWEETs, with confocal microscopy verifying their distinct subcellular localization at the plasma membrane, tonoplast, or endoplasmic reticulum. Furthermore, transient overexpression of several candidate transporters (ScSWEET4-T2, ScSWEET15, and ScTST4-T1) in Nicotiana benthamiana modulated soluble sugar accumulation, and their expression in sugarcane protoplasts activated key sugar-responsive marker genes (ScGPT2 and ScWIP4). Together, our study establishes a systematic genomic framework and identifies candidate functional transporters that govern sugar partitioning and storage, providing valuable genetic targets for molecular breeding and quality enhancement in sugarcane.

Functional characterization

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3

EprX associates with concurrent shifts in antimicrobial resistance and virulence in clinical bloodstream E. coli: a putative adaptive node for bacterial fitness.

Bloodstream infections (BSIs) caused by E. coli represent a growing global threat, driven by escalating antimicrobial resistance (AMR) and sustained virulence. However, the regulatory mechanisms linking these two phenotypes remain poorly understood. Here, we identify EprX, a previously uncharacterized YjbI-type pentapeptide repeat protein (PRP), a locus that our data suggest may influence metabolic and transcriptional profiles in clinical BSI E. coli isolates. Genomic screening of 85 clinical BSI strains reveals that eprX is present in 21.2% of isolates, often within distinct genomic contexts suggestive of mobile acquisition. Using λ-Red recombineering, we constructed eprX knockout mutants. Loss of eprX is associated with altered antimicrobial resistance profiles, increasing susceptibility to gentamicin, ciprofloxacin, and levofloxacin. This phenotype is consistent with upregulation of outer membrane porin genes (ompC, ompF) and downregulation of multidrug efflux pump genes (macB, mdtC, emrB) and two-component regulatory system genes. eprX deficiency also appears to correlate with attenuated virulence in our assays, as evidenced by improved survival of Galleria mellonella larvae (65-95% at 72 h post-infection vs. 40-60% for wild-type strains) and reduced adhesion to and invasion of human HeLa cells. Transcriptomic profiling reveals that eprX carriage is associated with broad, coordinated shifts in the expression of genes involved in LPS transport (lptG/lptF), type ;II secretion system components (gspD/gspE/gspF), autotransporter adhesins (ag43), and flagellar assembly, suggesting potential disruptions in outer-membrane integrity, biofilm formation, and virulence programs. Our data suggests that eprX is a genetic locus whose presence correlates with concurrent shifts in resistance maintenance and virulence traits, representing a putative adaptive node within the E. coli fitness landscape.

Animals

Effects of Time-Based and Distance-Based Repeated Sprint Training on Physical and Physiological Adaptations in Collegiate Basketball Players.

PURPOSE: This study aimed to compare the effects of time-based (TB) and distance-based (DB) repeated-sprint training (RST) on athletic performance adaptations in collegiate basketball players during preseason and to examine whether the 2 training prescriptions produce different levels of homogeneity in the magnitude of individual adaptations. METHODS: Thirty young male basketball players (age = 21.3 [1.4]&#xa0;y) were randomly and equally assigned to 3 groups (n = 10): DB-RST, TB-RST, and an active control group. Participants completed a 7-week RST program performed 3 times per week, consisting of 4 sets of 4 to 9 repetitions per session. The DB-RST group completed each sprint by covering a fixed 35-m distance, whereas the TB-RST group performed each sprint maximally for a fixed 5-second duration. Performance assessments including countermovement vertical jump, 20-m sprint, Illinois change-of-direction speed, reactive strength index, Wingate anaerobic power, and cardiorespiratory fitness were conducted before and after the 7-week training period. RESULTS: Both training groups demonstrated significant performance improvements over the 7-week intervention and relative to the control group (P < .05). Similar gains were observed in the magnitude of adaptations in the countermovement vertical jump, 20-m sprint, Illinois change-of-direction speed, and reactive strength index for the DB-RST and TB-RST groups. Interestingly, the TB-RST group showed more gains than the DB-RST in the magnitude of adaptations in the peak and mean power outputs, as well as cardiorespiratory fitness. Moreover, the TB-RST group showed lower intersubject variability in adaptive responses across the measured performance outcomes following the training intervention. CONCLUSION: Our findings indicate that RST effectively enhances the performance of basketball players, and that implementing a TB-RST protocol is more effective than a DB-RST approach for producing greater adaptations in physiological variables-specifically anaerobic power output and cardiorespiratory fitness-over the 7-week preseason period.

Humans

Biallelic Variants in ATP1A4 Are Associated with Oligoasthenoteratozoospermia and Male Infertility.

Male infertility, often caused by structural and functional sperm defects, remains genetically unexplained in a substantial proportion of cases. ATP1A4 encodes a testis-specific isoform of the Na+, K+-ATPase, a membrane enzyme crucial for maintaining cellular ionic homeostasis. Previous studies on Atp1a4 knockout mice have demonstrated severe defects in sperm motility and flagellar architecture; however, the contribution of ATP1A4 variants to human male reproduction remains to be elucidated. In this study, we identified compound biallelic variants in ATP1A4, a missense variant (c.2578&#x2009;T>A, p.Tyr860Asn) and a frameshift variant (c.2582del, p.Gly861Aspfs*5), in a patient presenting with severe oligoasthenoteratozoospermia. Both variants markedly affected ATP1A4 protein expression. Morphological analyses revealed coiled and folded flagella, disrupted mitochondrial sheaths, and irregular head morphology in the patient's spermatozoa. Expression profiling revealed that ATP1A4 was highly enriched in post-meiotic spermatids and localized along the entire flagellum of mature sperm in both humans and mice, indicating a critical role in flagellar assembly and structural integrity. Notably, intracytoplasmic sperm injection (ICSI) in this patient resulted in low fertilization efficiency and failed implantation, suggesting a potential adverse impact of ATP1A4 deficiency on sperm functional competence beyond motility. These findings broaden the genetic spectrum of oligoasthenoteratozoospermia and highlight ATP1A4 as a potential gene associated with human male infertility.

Male

Macrophage LRRK2 hyperactivity impairs autophagy and induces Paneth cell dysfunction.

LRRK2 polymorphisms (G2019S/N2081D) that increase susceptibility to Parkinson's disease and Crohn's disease (CD) lead to LRRK2 kinase hyperactivity and suppress autophagy. This connection suggests that LRRK2 kinase inhibition, a therapeutic strategy being explored for Parkinson's disease, may also benefit patients with CD. Paneth cell homeostasis is tightly regulated by autophagy, and their dysfunction is a precursor to gut inflammation in CD. Here, we found that patients with CD and mice carrying hyperactive LRRK2 polymorphisms developed Paneth cell dysfunction. We also found that LRRK2 kinase can be activated in the context of interactions between genes (genetic autophagy deficiency) and the environment (cigarette smoking). Unexpectedly, lamina propria immune cells were the main intestinal cell types that express LRRK2, instead of Paneth cells as previously suggested. We showed that LRRK2-mediated pro-inflammatory cytokine release from phagocytes impaired Paneth cell function, which was rescued by LRRK2 kinase inhibition through activation of autophagy. Together, these data suggest that LRRK2 kinase inhibitors maintain Paneth cell homeostasis by restoring autophagy and may represent a therapeutic strategy for CD.

Leucine-Rich Repeat Serine-Threonine Protein Kinas

Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods.

BACKGROUND: Alternative splicing (AS) plays critical roles in generating protein diversity and complexity. Dysregulation of AS underlies the initiation and progression of tumors. Machine learning approaches have emerged as efficient tools to identify promising biomarkers. It is meaningful to explore pivotal AS events (ASEs) to deepen understanding and improve prognostic assessments of lung adenocarcinoma (LUAD) via machine learning algorithms. METHOD: RNA sequencing data and AS data were extracted from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using several machine learning methods, we identified 24 pairs of LUAD-related ASEs implicated in splicing switches and a random forest-based classifiers for identifying lymph node metastasis (LNM) consisting of 12 ASEs. Furthermore, we identified key prognosis-related ASEs and established a 16-ASE-based prognostic model to predict overall survival for LUAD patients using Cox regression model, random survival forest analysis, and forward selection model. Bioinformatics analyses were also applied to identify underlying mechanisms and associated upstream splicing factors (SFs). RESULTS: Each pair of ASEs was spliced from the same parent gene, and exhibited perfect inverse intrapair correlation (correlation coefficient&#x2009;=&#x2009;-&#x2009;1). The 12-ASE-based classifier showed robust ability to evaluate LNM status of LUAD patients with the area under the receiver operating characteristic (ROC) curve (AUC) more than 0.7 in fivefold cross-validation. The prognostic model performed well at 1, 3, 5, and 10&#xa0;years in both the training cohort and internal test cohort. Univariate and multivariate Cox regression indicated the prognostic model could be used as an independent prognostic factor for patients with LUAD. Further analysis revealed correlations between the prognostic model and American Joint Committee on Cancer stage, T stage, N stage, and living status. The splicing network constructed of survival-related SFs and ASEs depicts regulatory relationships between them. CONCLUSION: In summary, our study provides insight into LUAD researches and managements based on these AS biomarkers.

Adenocarcinoma of Lung