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Boyang Zhang

Publications and source records attributed to Boyang Zhang.

2 recordsLinked to original sources

Pangenome of Streptomyces sampsonii and Relatives Highlights Horizontal Gene Transfer and Secondary Metabolism in Environmental Adaptation and Ecological Significance.

Streptomyces sampsonii is a promising biocontrol bacterium, but its genomic basis of adaptation and secondary metabolism remains unclear. Here, we present a chromosome-level genome assembly of S. sampsonii (7.20 Mb, 6015 protein-coding genes) and perform comparative analyses with 95 related Streptomyces species. Phylogenomic and synteny analyses revealed its closest relationship with S. albidoflavus, while extensive structural variations distinguished more distant lineages. Pangenome analysis uncovered 84,178 gene clusters, with pan_shell and pan_cloud genes predominantly enriched in xenobiotic biodegradation, metabolism, and antibiotic biosynthesis, highlighting their roles in ecological adaptation and biocontrol potential. Biosynthetic gene cluster (BGC) analysis identified numerous NRPS, PKS, and terpene pathways, many of which belong to pan_shell and pan_cloud regions, suggesting dynamic evolutionary origins. We further detected 66,260 horizontally transferred (HGT) genes, including 438 in BGCs, underscoring HGT as a major driver of metabolic innovation. Together, these findings provide novel insights into the genomic diversity, adaptive capacity, and secondary metabolic potential of S. sampsonii and its close relatives.

BGCs

Novel Predictive Spatial Biomarker in Non-Small Cell Lung Carcinoma: The Diversity of Niches Unlocking Treatment Sensitivity (DONUTS).

Probabilistic spatial modelling techniques developed on large-scale tumor-immune Atlases (~35M individually mapped cells; 50,000 high power fields) were used to characterize predictive features of treatment-responsive lung cancer. We identified CD8+FoxP3+ cell density as a robust pre-treatment biomarker for outcomes across disease stages and therapy types. In parallel, single-cell RNAseq studies of CD8+FoxP3+ T-cells revealed an activated, early effector phenotype, substantiating an anti-tumor role, and contrasting with CD4+FoxP3+ T-regulatory cells. A spatial biomarker was developed using an empirical probabilistic model to define the immediate cell neighbors or niche surrounding CD8+FoxP3+ cells and proximity to the tumor-stromal boundary. The resultant 'Diversity of Niches Unlocking Treatment Sensitivity (DONUTS)' are more prevalent than the CD8+FoxP3+ cells themselves, mitigating sampling error in small biopsies. Further, the DONUTS only require four markers, are additive to PD-L1, and associate with tertiary lymphoid structure counts. Taken together, the DONUTS represent a next-generation predictive biomarker poised for clinical implementation.

AstroPath