Mudappathi Rekha, Bharadwaj Vaishali, Liu Li
College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA.
bioRxiv. 2025 Jun 12:2025.06.09.658704. doi: 10.1101/2025.06.09.658704.
Intracellular protein transport (ICT) is a tightly regulated process that orchestrates protein localization and expression, ensuring proper cellular function. Dysregulated ICT can lead to aberrant expression of surface proteins involved in cell-cell communication, adhesion, and immune responses, contributing to disease progression and therapeutic resistance. Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) enables the simultaneous measurement of mRNA and surface protein levels in the same cell, providing a powerful opportunity to investigate the molecular mechanisms underlying surface protein regulation. In this study, we introduce a novel computational frame for Modeling Protein Expression and Transport (MPET) that evaluates the contribution of ICT activity to differential surface protein expression using CITE-seq data. MPET comprises three modules for identification of ICT-surface protein regulatory circuits across biological scales and their contributions to phenotypic variation. We applied MPET to analyze single-cell data from COVID-19 patients with varying disease severity. Our analysis revealed context-dependent recruitment of ICT genes and pervasive rewiring of ICT pathways throughout the course of disease progression. Notably, we found that even when the transcriptional levels of key immune response proteins remained stable, their expression on cell surface were significantly altered due to dysregulated ICT. MPET provides a valuable new tool for dissecting complex regulatory networks and offers mechanistic insight into post-transcriptional regulation of cell surface proteins in diseases.
细胞内蛋白质运输(ICT)是一个受到严格调控的过程,它协调蛋白质的定位和表达,确保细胞功能正常。ICT失调会导致参与细胞间通讯、黏附和免疫反应的表面蛋白异常表达,促进疾病进展和产生治疗抗性。通过测序对转录组和表位进行细胞索引(CITE-seq)能够在同一细胞中同时测量mRNA和表面蛋白水平,为研究表面蛋白调控的分子机制提供了强大的机会。在本研究中,我们引入了一种用于蛋白质表达和运输建模(MPET)的新型计算框架,该框架使用CITE-seq数据评估ICT活性对表面蛋白差异表达的贡献。MPET包含三个模块,用于识别跨生物尺度的ICT-表面蛋白调控回路及其对表型变异的贡献。我们应用MPET分析了不同疾病严重程度的COVID-19患者的单细胞数据。我们的分析揭示了在疾病进展过程中ICT基因的背景依赖性募集以及ICT通路的广泛重排。值得注意的是,我们发现即使关键免疫反应蛋白的转录水平保持稳定,由于ICT失调,它们在细胞表面的表达也会显著改变。MPET为剖析复杂的调控网络提供了一种有价值的新工具,并为疾病中细胞表面蛋白的转录后调控提供了机制性见解。