Biomedical subjects

Zhenmin Liu

Publications and source records attributed to Zhenmin Liu.

2 recordsLinked to original sources

PubMed2026

Chromosome-Scale Genome Analysis Reveals Locus-Specific Disruption of the Citrinin-Associated Region in a Furu-Derived Monascus ruber Strain BC20.

Monascus species are widely used in traditional fermented foods for pigment and flavor formation, but citrinin contamination remains a major safety concern that limits broader food applications. Therefore, this study aimed to evaluate the citrinin risk of a furu-derived Monascus ruber strain, BC20, by integrating phenotypic screening across food-relevant matrices with genome-resolved analysis. After 14 days of cultivation across eight matrices, including fungal media as well as dairy-, cereal-, and bran-based substrates, citrinin was not detected by immunoaffinity cleanup combined with HPLC-FLD (LOD, 4 μg/kg; LOQ, 12 μg/kg). To investigate the genetic basis of this phenotype, we generated a chromosome-scale genome assembly for BC20 and conducted comparative analyses across a total of 19 Monascus genomes. ANI analysis and phylogenomic inference consistently placed BC20 within the ruber-pilosus clade. Comparative synteny analysis showed that the citrinin-associated locus in BC20 no longer retained an intact cluster configuration but instead exhibited a remnant-locus architecture, and similar patterns were also observed in several related genomes from the same clade. By contrast, the monacolin K (mk) locus remained syntenically conserved in BC20, supporting locus-specific structural disturbance rather than assembly-derived pseudo-absence. Additionally, its antifungal susceptibility was determined. Overall, BC20 represents a M. ruber candidate strain with undetectable citrinin, and this study provides a practical analytical framework for citrinin risk screening in food-related Monascus isolates.

biosynthetic gene cluster↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗