Search PubMedSearch

Biomedical subjects

Xiaolei Yu

Publications and source records attributed to Xiaolei Yu.

2 recordsLinked to original sources

Comprehensive analysis of synonymous codon usage bias and evolutionary dynamics in the chloroplast genomes of eight Coptis species.

Coptis is a medically important genus renowned for producing valuable isoquinoline alkaloids. Although its chloroplast genomes encode key components for photosynthesis and plastid gene expression, the evolutionary constraints acting on their coding sequences and synonymous codon usage remain poorly resolved. Here, we combined a transparent taxon-level sampling strategy with comparative analyses of chloroplast CDSs from eight Coptis taxa. We quantified nucleotide composition, relative synonymous codon usage, effective number of codons, neutrality and PR2 patterns, and correspondence analysis, and then integrated these results with a core-CDS distance analysis and gene-wise pairwise dN/dS estimates. The chloroplast genomes showed a conserved AT-rich composition, especially at the third codon position (GC3 approximately 30.3-30.8%), with a consistent GC1 > GC2 > GC3 trend. Thirty preferred codons were detected, 28 ending in A/T, and eleven optimal codons were shared across the genus. The core-CDS distance analysis recovered a close relationship between C. chinensis and C. chinensis var. brevisepala, whereas most coding genes showed dN/dS values below one, consistent with pervasive purifying constraint. Across 48 consistently filtered CDSs, GC3s was negatively associated with mean dN (Spearman rho = -0.404, P = 0.00439) and CAI was positively associated with mean dN (rho = 0.303, P = 0.0361), whereas the remaining associations were not significant (all P > = 0.0972). These results extend codon-usage analysis by linking synonymous-site composition to coding-sequence evolution within Coptis, while providing a hypothesis-generating resource for future plastid engineering studies.

Genome, Chloroplast

Decoding mechanoregulation in immunological synapses using biomimetic artificial cells.

Mechanical force-driven signaling has emerged as a key regulator of cell-cell interactions (CCIs), which can enhance immune cell function. However, current biochemical approaches for studying CCIs offer minimal direct control over cellular bulk phenotypes, while synthetic biomaterial systems fail to mimic the dynamic complexity of cells. Here we introduce kpiCells, a biomaterial-based platform that uses a biomimetic membrane-endoplasmic architecture to enable finely tuned phenocopying of cellular states via modular mechanical, chemical and topographical inputs. We demonstrate that kpiCells can engage in physiological CCIs and reproduce critical subcellular features. In T cell systems, kpiCells enable integrated interrogation of afferent mechanosensing pathways and efferent force-exertion pathways, and support measurement of piconewton-scale forces at individual T cell antigen receptors as well as single cell-cell force fingerprints that define activation thresholds. This work establishes kpiCells as a bionic model that enables synthetic material design with the level of functional complexity approaching living cell systems.

Artificial Cells