PubMed HealthSearch

Biomedical subjects

Tong Zhang

Publications and source records attributed to Tong Zhang.

5 recordsLinked to original sources

PRDX1 as a novel urinary biomarker for bladder cancer: Development of an integrated fiber optic sensing platform.

In this study, integrated proteomic and transcriptomic analyses identified peroxiredoxin 1 (PRDX1) as a novel urinary biomarker for bladder cancer (BC). PRDX1 was significantly upregulated in BC tissues and was associated with poorer overall survival. In vitro experiments further demonstrated that PRDX1 promotes malignant phenotypes of BC cells, including proliferation, migration, and invasion. Silencing PRDX1 in BC cells significantly reduced the invasiveness and proliferation ability.To address the clinical need for rapid and non-invasive detection, we developed an innovative optical fiber biosensor based on surface plasmon resonance (SPR) technology for the quantitative detection of urinary PRDX1. The biosensor exhibited excellent analytical performance, including high sensitivity (limit of detection: 0.06 ng/mL), a wide linear range (0-25 ng/mL), rapid response (∼14 s), as well as good stability and selectivity. In clinical validation involving 97 BC patients and 30 healthy controls, the biosensor demonstrated outstanding diagnostic performance, with an area under the receiver operating characteristic curve (AUC) of 0.91 and an overall diagnostic accuracy of 86.6%, outperforming conventional enzyme-linked immunosorbent assay (ELISA). Collectively, this study not only identifies PRDX1 as a promising biomarker for non-invasive diagnosis and prognostic evaluation of BC, but also establishes an efficient SPR-based optical fiber sensing platform, providing new insights into both clinical detection and the functional role of PRDX1 in BC progression.

Humans

Pilea: profiling bacterial growth dynamics from metagenomes with sketching.

BACKGROUND: Quantifying bacteria's growth rates is essential for understanding their ecological roles and for building predictive models in environmental and clinical settings. Peak-to-trough ratios (PTRs) derived from shotgun metagenomes offer a culture-independent proxy for in situ growth rates of bacterial species, yet their reliable computation remains challenging. RESULTS: We introduce Pilea ( https://github.com/xinehc/pilea ), an alignment-free, sketching-based method that incorporates statistical models for robust PTR estimation. Pilea achieves speed improvements over existing methods while also enhancing accuracy, as demonstrated on both simulated and real datasets. CONCLUSIONS: By scaling efficiently to comprehensive reference collections such as the Genome Taxonomy Database (GTDB), Pilea enables large-scale analyses of bacterial growth dynamics across biomes, unlocking new insights for ecological research. Video Abstract.

Bacteria

Methylation-based droplet digital polymerase chain reaction shows high concordance with chronic lymphocytic leukemia IGHV somatic mutation status.

OBJECTIVE: Somatic hypermutation at immunoglobulin heavy chain variable (IGHV) genes, an established prognostic and predictive biomarker for chronic lymphocytic leukemia (CLL), is assessed by gene sequencing. We developed a single methylation-specific droplet digital polymerase chain reaction (methyl-ddPCR) to predict IGHV status in patients with CLL. METHODS: The CLL methylation array and IGHV data from the International Cancer Genome Consortium (ICGC) were used for biomarker discovery. Top-ranked candidate regions were manually screened for PCR primer and probe binding sites. A single methyl-ddPCR was evaluated on an internal cohort of CLLs with mutated (M), unmutated (U), and inconclusive IGHV results originally determined by next-generation sequencing (NGS). RESULTS: Analysis of ICGC data identified array probe cg23844018 as a candidate for the PCR. The corresponding CpG site showed high methylation levels in U-CLL and lower levels in M-CLL. On the internal cohort, a single optimal cutoff correctly classified 104 of 115 U- and M-CLLs (90.4%; area under the curve = 0.96). The PCR data correlated with some prognostic fluorescence in situ hybridization and CLL subset groupings. Limited analysis suggests that the PCR may be able to stratify some patients with CLL who have inconclusive results on IGHV NGS testing. CONCLUSIONS: The methyl-ddPCR showed high concordance with CLL IGHV status in an internal cohort.

Humans

RabbitSketch: a high-performance sketching library for genome analysis.

SUMMARY: We present RabbitSketch, a highly optimized library of sketching algorithms such as MinHash, OrderMinHash, and HyperLogLog that can exploit the power of modern multi-core CPUs. It provides significant speedups compared to existing implementations, ranging from 2.30× to 49.55×, as well as flexible and easy-to-use interfaces for both Python and C++. As a result, the similarity analysis of 455GB genomic data can be completed in only 5 minutes using RabbitSketch with merely 20 lines of Python code. As a case study, we enhanced RabbitTClust by integrating RabbitSketch's Kssd algorithm, resulting in a 1.54× speedup with no loss in accuracy. AVAILABILITY AND IMPLEMENTATION: RabbitSketch is available at https://github.com/RabbitBio/RabbitSketch with an archived version at Zenodo: https://doi.org/10.5281/zenodo.14903962. Detailed API documentation is available at https://rabbitsketch.readthedocs.io/en/latest.

Software

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-Treated Pancreatic Beta Cells.

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse posttranslational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated β-cells. We observed a swift response in the global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-κB signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple colocalized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

Proteomics