Biomedical subjects

Ping Xu

Publications and source records attributed to Ping Xu.

8 recordsLinked to original sources

PubMed2026

Non-coding RNA 7SK drives tumor resistance by coupling local oncogenic activation with global transcriptional repression.

The conserved non-coding RNA 7SK is a well-established global transcriptional repressor, yet its context-specific functions in cancer and therapy resistance remain paradoxical. Here, we resolve this paradox by uncovering a dual-axis mechanism through which 7SK drives colorectal cancer (CRC) resistance. By integrating single-cell multi-omics with functional assays, we demonstrate that 7SK not only selectively activates the JUN transcriptional network to fuel tumor proliferation but also reduces global transcriptional entropy to stabilize an immunosuppressive microenvironment and promote immune escape. This "local activation-global suppression" paradigm is conserved across multiple cancer types, positioning 7SK as a potential pan-cancer therapeutic target. Our findings reveal 7SK as a dynamic modulator that balances oncogene-specific transcription with global transcriptional suppression across cancers, providing a new framework for understanding and targeting ncRNA-mediated resistance.

Humans↗

PubMed2026

Integrative Proteomics and Ubiquitomics Reveal on-Targets and off-Targets of PROTAC dBET1.

Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that induce selective degradation of target proteins by hijacking the ubiquitin-proteasome system (UPS). Despite their transformative potential in eliminating disease-associated proteins, comprehensively identifying off-target degradation events remains technically challenging. Here, we employed an integrated proteomic and ubiquitinomic strategy to systematically profile the degradation landscape of the PROTAC molecule dBET1 in Jurkat T cells. By capturing the upstream ubiquitination events─which serve as earlier and more sensitive indicators than total protein abundance─our approach enabled the identification of previously overlooked off-target candidates. While dBET1 efficiently degraded its canonical BET family targets, our data also revealed the mitochondrial outer membrane protein VDAC1 as a putative off-target, evidenced by its depletion and increased multisite ubiquitination. Notably, our analysis framework enabled site-specific resolution of degradation events within BRD3, revealing preferential ubiquitination at functionally essential bromodomains, suggesting that degron-enriched regions may underlie domain-selective degradation. Additionally, dBET1 treatment was associated with mitochondrial depolarization and calcium homeostasis disruption, defects that we hypothesize may be functionally linked to the observed VDAC1 depletion. Together, this study demonstrates that integrating ubiquitomics provides a superior sensitivity layer for PROTAC safety assessment, capable of uncovering mechanism-based liabilities that escape conventional global proteomic screening.

Humans↗

PubMed2026

A Robust, Self-Digestion-Resistant LysN with Superior Activity and Cleavage Fidelity for Advanced Proteomic Workflows.

LysN is a valuable protease in proteomics because it cleaves peptide bonds N-terminal to lysine, generating peptides with physicochemical properties complementary to those produced by LysC and trypsin. However, the broader adoption of LysN in proteomic workflows has been limited by the lack of commercially available enzymes that combine high activity, low missed-cleavage rates, and sufficient stability under practical sample-processing conditions. Here, we report the recombinant production and proteomic characterization of a self-digestion-resistant and highly active LysN from Shewanella loihica (SL-LysN). Using terminomics, we mapped the mature N- and C-termini of the enzyme and established the primary structure of the active protease. We further developed a high-density fermentation, refolding, and purification workflow to obtain highly purified recombinant SL-LysN. Biochemical and proteomic benchmarking showed that SL-LysN displayed 3.3-fold higher specific activity than commercial LysN and reduced missed cleavages by approximately 80%. Notably, SL-LysN retained high activity in the presence of 8 M urea or 1% SDS and showed strong resistance to autolysis, indicating exceptional robustness for proteomic sample preparation. In complex mammalian proteome digests, SL-LysN achieved >95% cleavage specificity and a missed-cleavage rate of only 5.9%. These features address a long-standing bottleneck in N-terminal proteolysis and establish SL-LysN as a high-performance enzymatic tool for advanced proteomic workflows, including deep protein sequencing, quantitative proteomics, terminomics, de novo sequencing and analyses requiring efficient digestion under denaturing conditions.

Shewanella↗

PubMed2026

A genome-wide in vivo screen reveals fitness pathways required for streptococcal infective endocarditis.

Infective endocarditis (IE) is a life-threatening disease most often caused by blood-borne bacteria that infect previously damaged cardiac tissue. Despite the importance of this disease, the genetic basis for IE-associated fitness remains poorly defined. Here, we present the first genome-wide in vivo analysis of bacterial fitness in a vertebrate model of IE. We identified 146 genes in Streptococcus sanguinis required for IE fitness, the majority of which had not previously been linked to endocarditis. These determinants cluster into conserved metabolic, cell envelope, transport, and regulatory pathways, representing a vast reservoir of potential targets for novel antimicrobial intervention. A subset of these genes was examined in Streptococcus mutans; all were found to be essential for IE fitness in this distantly related oral species as well, suggesting broad conservation. Using experimental evolution, we further show that disruption of key fitness pathways triggers reproducible compensatory "bypass" mechanisms. Together, these findings provide a comprehensive, genome-wide map of the bacterial niche-requirements for streptococcal infective endocarditis.

Animals↗

PubMed2026

AI proteomics: from protein identification to virtual cells.

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and protein complexes; advancing spatial and perturbation proteomics; integrating multi-omics data; and, ultimately, enabling AI virtual cells. Finally, we call for global collaboration among data producers, data consumers and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics, laying the foundation for transformative advancements in proteomics driven by AI.

Proteomics↗

PubMed2025

Inferring cell trajectories of spatial transcriptomics via optimal transport analysis.

The integration of cell transcriptomics and spatial position to organize differentiation trajectories remains a challenge. Here, we introduce SpaTrack, which leverages optimal transport to reconcile both gene expression and spatial position from spatial transcriptomics into the transition costs, thereby reconstructing cell differentiation. SpaTrack can construct detailed spatial trajectories that reflect the differentiation topology and trace cell dynamics across multiple samples over temporal intervals. To capture the dynamic drivers of differentiation, SpaTrack models cell fate as a function of expression profiles influenced by transcription factors over time. By applying SpaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Diverse malignant lineages expanding within a primary tumor are uncovered. One lineage, characterized by upregulated epithelial mesenchymal transition, implants at the metastatic site and subsequently colonizes to form a secondary tumor. Overall, SpaTrack efficiently advances trajectory inference from spatial transcriptomics, providing valuable insights into differentiation processes.

Animals↗

PubMed2025

Phosphoproteomics delineates hepatocellular carcinoma subtypes and pinpoints therapeutic targets.

BACKGROUND AND AIMS: Only a minority of patients could benefit from systemic therapy owing to the high heterogeneity of HCC. Therefore, a deeper understanding of the pathogenesis of HCC is essential for precision therapy. Genomic and proteomic studies of HCC have enhanced our understanding of HCC. However, the phosphoproteomic characterization of HCC remains poorly understood. APPROACH AND RESULTS: We conducted an in-depth analysis of a clinical cohort of HCC using high-coverage phosphoproteomic. Effective therapeutic targets were validated using liver cancer cell lines and HCC patient-derived xenograft mouse models that correspond to the phosphoproteomic subtypes of HCC. Phosphoproteomic analysis classified HCC into 3 subtypes, A, B, and C, with increasing malignancy and correlation with clinical features, including patient prognosis, tumor staging, serum alpha-fetoprotein levels, tumor thrombus, and tumor size. Phosphoproteomic subtyping deeply reflected the biological characteristics and clinical features of patients with HCC. The profiles of HCC-dysregulated kinase activities inferred from the different phosphoproteomic subtypes consistently identify increased kinase activity related to cell proliferation. Subtype-C HCC patients showed the most significant dysregulation, indicating a potential therapeutic target. The corresponding drug, bosutinib, demonstrated efficacy in inhibiting the growth of subtype C tumors in liver cancer cell lines and HCC patient-derived xenograft mouse models representative of the phosphoproteomic HCC subtypes. CONCLUSIONS: Our study provides a comprehensive exploration of the phosphoproteomic landscape of HCC, establishing new subtypes that match clinical features and identifying potential therapeutic targets for the most malignant C subtype.

Carcinoma, Hepatocellular↗

PubMed2024

Super Enhanced Purification of Denatured-Refolded Ubiquitinated Proteins by ThUBD Revealed Ubiquitinome Dysfunction in Liver Fibrosis.

Ubiquitination is crucial for maintaining protein homeostasis and plays a vital role in diverse biological processes. Ubiquitinome profiling and quantification are of great scientific significance. Artificial ubiquitin-binding domains (UBDs) have been widely employed to capture ubiquitinated proteins. The success of this enrichment relies on recognizing native spatial structures of ubiquitin and ubiquitin chains by UBDs under native conditions. However, the use of native lysis conditions presents significant challenges, including insufficient protein extraction, heightened activity of deubiquitinating enzymes and proteasomes in removing the ubiquitin signal, and purification of a substantial number of contaminant proteins, all of which undermine the robustness and reproducibility of ubiquitinomics. In this study, we introduced a novel approach that combines denatured-refolded ubiquitinated sample preparation (DRUSP) with a tandem hybrid UBD for ubiquitinomic analysis. The samples were effectively extracted using strongly denatured buffers and subsequently refolded using filters. DRUSP yielded a significantly stronger ubiquitin signal, nearly three times greater than that of the Control method. Then, eight types of ubiquitin chains were quickly and accurately restored; therefore, they were recognized and enriched by tandem hybrid UBD with high efficiency and no biases. Compared with the Control method, DRUSP showed extremely high efficiency in enriching ubiquitinated proteins, improving overall ubiquitin signal enrichment by approximately 10-fold. Moreover, when combined with ubiquitin chain-specific UBDs, DRUSP had also been proven to be a versatile approach. This new method significantly enhanced the stability and reproducibility of ubiquitinomics research. Finally, DRUSP was successfully applied to deep ubiquitinome profiling of early mouse liver fibrosis with increased accuracy, revealing novel insights for liver fibrosis research.

Animals↗