Biomedical subjects

Xue Zhang

Publications and source records attributed to Xue Zhang.

3 recordsLinked to original sources

PubMed2026

Ancient DNA unveils distinctive ancestries in the Bronze and Iron Ages of East Tianshan.

The East Tianshan Mountains occupy a key corridor between Central and East Asia, but their population history remains poorly understood. Here we report genome-wide data from 135 ancient individuals from 11 archaeological sites. We identify a previously unrecognized Bronze Age admixture between populations related to Yellow River millet farmers and steppe pastoralists associated with the Chemurchek culture. In contrast, we find little genetic contribution from contemporaneous middle-to-late Bronze Age steppe pastoralists, despite their eastward expansion across the Eurasian Steppe. By the Iron Age, regional populations had become more heterogeneous, incorporating additional eastern and steppe-related sources while retaining variable contributions from Early Bronze Age groups. These results reveal sustained demographic interactions in eastern Central Asia nearly 1800 years preceding the establishment of the historic Silk Road.

DNA, Ancient↗

PubMed2026

Genomic insights into low-level rifampicin resistance mediated by borderline rpoB mutations in Mycobacterium tuberculosis: prevalence and phylogeny in Northeast China.

The emergence of low-level rifampicin (RIF) resistance in Mycobacterium tuberculosis poses a challenge to tuberculosis (TB) control, as it often leads to discordance between genotypic resistance detected by molecular assays (e.g., Xpert MTB/RIF) and phenotypic susceptibility in conventional drug susceptibility testing (DST). In this study, we performed whole-genome sequencing (WGS) on 17 clinical isolates from Changchun, Northeast China, which exhibited such discordance. All isolates harbored functional borderline mutations in the rpoB RRDR region, predominantly Leu452Pro and Leu430Pro (29% each), followed by His445Asn (18%). RIF minimum inhibitory concentration (MIC) values ranged from ≤0.25 to 1.0 mg/L, confirming low-level resistance. Notably, 53% (9/17) of the isolates were co-resistant to fluoroquinolones and 24% (4/17) to isoniazid (INH). According to WHO classification, 59% (10/17) were pre-extensively drug-resistant TB (Pre-XDR-TB) or multidrug-resistant TB (MDR-TB). Phylogenetic analysis revealed that 94% (16/17) belonged to the East Asian Beijing lineage (Lineage 2.2.1), with no evidence of recent local transmission. These findings underscore the complexity of low-level RIF resistance and its frequent association with broader drug resistance in a dominant lineage, highlighting the need for integrating MIC and WGS into diagnostic algorithms to guide appropriate treatment and surveillance.IMPORTANCEThe accurate detection of RIF resistance is critical for the management of TB, yet standard phenotypic methods often fail to identify strains with low-level resistance conferred by borderline rpoB mutations. This study provides the first genomic characterization of such discordant isolates in Northeast China, revealing a high prevalence of co-resistance to other key drugs and a strong association with the locally dominant Beijing lineage. The findings emphasize that reliance on phenotypic DST alone may lead to underestimation of drug resistance and inappropriate treatment, potentially contributing to the emergence and spread of Pre-XDR-TB and MDR-TB. Incorporating MIC determination and WGS into routine diagnostics could enhance detection, inform tailored therapy, and improve surveillance of these clinically significant strains.

Mycobacterium tuberculosis↗

PubMed2025

TRAIT: A Comprehensive Database for T-cell Receptor-antigen Interactions.

Comprehensive and integrated resources on interactions between T-cell receptors (TCRs) and antigens are still lacking for adoptive T-cell-based immunotherapies, highlighting a significant gap that must be addressed to fully understand the mechanisms of antigen recognition by T cells. In this study, we present the T-cell receptor-antigen interaction database (TRAIT), a comprehensive database that profiles the interactions between TCRs and antigens. TRAIT stands out due to its comprehensive description of TCR-antigen interactions by integrating sequences, structures, and affinities. It provides millions of experimentally validated TCR-antigen pairs, resulting in an exhaustive landscape of antigen-specific TCRs. Notably, TRAIT emphasizes single-cell omics as a major reliable data source for TCR-antigen interactions and includes millions of reliable non-interactive TCRs. Additionally, it thoroughly demonstrates the interactions between mutations of TCRs and antigens, thereby benefiting affinity optimization of engineered TCRs as well as vaccine design. TCRs on clinical trials are innovatively provided. With the significant efforts made toward elucidating the complex interactions between TCRs and antigens, TRAIT is expected to ultimately contribute superior algorithms and substantial advancements in the field of T-cell-based immunotherapies. TRAIT is freely accessible at https://pgx.zju.edu.cn/traitdb.

Receptors, Antigen, T-Cell↗