Biology subjects

Ao, J.

Publications and source records attributed to Ao, J..

3 recordsLinked to original sources

bioRxiv2025

Mid-Infrared Photothermal Imaging of Fatty Acid Desaturation Reaction in Cancer Cells

Direct visualization of metabolic conversions within living systems is essential for understanding metabolic activities yet challenging due to the absence of reaction-specific reporters and the limited sensitivity of current imaging modalities. Herein, we report an approach to monitor fatty acids (FAs) desaturation, primarily catalyzed by stearoyl-CoA desaturase, in cancer cells using deuterium (D)-labeled palmitic acid (PA-d31) as the reaction-specific reporter and mid-infrared photothermal (MIP) microscopy as the bond-selective imaging modality. The desaturation of PA-d31 produced a peak at 2246 cm-1 in the cell-silent region, corresponding to the stretching vibration of unsaturated C-D bonds (D-C=C-D) in unsaturated fatty acids. Penalized least squares fitting was employed to remove water background for enhancing the visibility of this peak. Our study revealed heterogeneous spatial distributions of both saturated FAs and their desaturated metabolites within lipid droplet pools in cancer cells. Furthermore, we observed an increase in fatty acid unsaturation level in OVCAR5 cells under cisplatin-induced stress. By directly visualizing fatty acid desaturation, this study offers new insights into fatty acid metabolism and opens avenues for evaluating new therapeutic strategies targeting fatty acid metabolism.

biochemistry↗

bioRxiv2025

QuickProt: A Fast and Accurate Homology-Based Protein Annotation Tool for Non-Model Organism Genomes

Despite the increasing number of genomes, the annotation of protein-coding genes is still lacking. In some genomes where transcriptome data is not available, various tools have been developed to annotate genes based on homologous proteins, but each tool has its limitations. Here, we propose quickprot, a user-friendly command-line tool that constructs a set of redundancy-free gene models from the target genome based on the homologous protein sequences of a set of closely related species. We tested its applicability in stonefish, and the results showed that it has high accuracy and runs faster than existing tools. This low-cost, high-precision annotation method is expected to become a useful tool for genome annotation, which will contribute to the research of comparative genomics. The software is implemented in Python and licensed under the MIT License. The source code, documentation, and tutorials can be obtained at https://github.com/thecgs/quickprot.

bioinformatics↗

bioRxiv2024

Single-cell profiling reveals the intratumor heterogeneity and immunosuppressive microenvironment in cervical adenocarcinoma

BackgroundCervical adenocarcinoma (ADC) is more aggressive compared to other types of cervical cancer (CC), such as squamous cell carcinoma (SCC). The tumor immune microenvironment (TIME) and tumor heterogeneity are recognized as pivotal factors in cancer progression and therapy. However, the disparities in TIME and heterogeneity between ADC and SCC are poorly understood. MethodsWe performed single-cell RNA sequencing on 11 samples of ADC tumor tissues, with other 4 SCC samples served as controls. The immunochemistry and multiplexed immunofluorescence were conducted to validate our findings. ResultsCompared to SCC, ADC exhibited unique enrichments in several sub-clusters of epithelial cells with elevated stemness and hyper-malignant features, including the Epi_10_CYSTM1 cluster. ADC displayed a highly immunosuppressive environment characterized by the enrichment of regulatory T cells (Tregs) and tumor-promoting neutrophils. The Epi_10_CYSTM1 cluster recruits Tregs via ALCAM-CD6 signaling, while Tregs reciprocally induce stemness in the Epi_10_CYSTM1 cluster through TGF{beta} signaling. Importantly, our study revealed that the Epi_10_CYSTM1 cluster could serve as a valuable predictor of lymph node metastasis for CC patients. ConclusionsThis study highlights the significance of ADC-specific cell clusters in establishing a highly immunosuppressive microenvironment, ultimately contributing to the heightened aggressiveness and poorer prognosis of ADC compared to SCC.

cancer biology↗