Enhanced Proteomic Coverage in Tissue Microenvironment by Immune Cell Subtype Library-Assisted DIA-MS.

IF 6.1 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Molecular & Cellular Proteomics Pub Date : 2024-07-01 Epub Date: 2024-05-27 DOI:10.1016/j.mcpro.2024.100792
Jhih-Ci Yang, Tzi-Hui Hsu, Ciao-Syuan Chen, Jou-Hui Yu, Kuo-I Lin, Yu-Ju Chen
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Abstract

Immune cells that infiltrate the tumor microenvironment (TME) play crucial roles in shaping cancer development and influencing clinical outcomes and therapeutic responses. However, obtaining a comprehensive proteomic snapshot of tumor-infiltrating immunity in clinical specimens is often hindered by small sample amounts and a low proportion of immune infiltrating cells in the TME. To enable in-depth and highly sensitive profiling of microscale tissues, we established an immune cell-enriched library-assisted strategy for data-independent acquisition mass spectrometry (DIA-MS). Firstly, six immune cell subtype-specific spectral libraries were established from sorted cluster of differentiation markers, CD8+, CD4+ T lymphocytes, B lymphocytes, natural killer cells, dendritic cells, and macrophages in murine mesenteric lymph nodes (MLNs), covering 7815 protein groups with surface markers and immune cell-enriched proteins. The feasibility of microscale immune proteomic profiling was demonstrated on 1 μg tissue protein from the tumor of murine colorectal cancer (CRC) models using single-shot DIA; the immune cell-enriched library increased coverage to quantify 7419 proteins compared to directDIA analysis (6978 proteins). The enhancement enabled the mapping of 841 immune function-related proteins and exclusive identification of many low-abundance immune proteins, such as CD1D1, and CD244, demonstrating high sensitivity for immune landscape profiling. This approach was used to characterize the MLNs in CRC models, aiming to elucidate the mechanism underlying their involvement in cancer development within the TME. Even with a low percentage of immune cell infiltration (0.25-3%) in the tumor, our results illuminate downregulation in the adaptive immune signaling pathways (such as C-type lectin receptor signaling, and chemokine signaling), T cell receptor signaling, and Th1/Th2/Th17 cell differentiation, suggesting an immunosuppressive status in MLNs of CRC model. The DIA approach using the immune cell-enriched libraries showcased deep coverage and high sensitivity that can facilitate illumination of the immune proteomic landscape for microscale samples.

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免疫细胞亚型库辅助 DIA-MS 提高组织微环境的蛋白质组覆盖率
浸润肿瘤微环境(TME)的免疫细胞在塑造癌症发展、影响临床结果和治疗反应方面起着至关重要的作用。然而,在临床样本中获取肿瘤浸润免疫的全面蛋白质组快照往往受到样本量少和肿瘤微环境中免疫浸润细胞比例低的阻碍。为了对微量组织进行深入和高灵敏度的分析,我们建立了一种免疫细胞富集库辅助数据独立采集质谱(DIA-MS)的策略。首先,我们从小鼠肠系膜淋巴结(MLNs)中分拣出的CD8+、CD4+ T淋巴细胞、B淋巴细胞、自然杀伤细胞、树突状细胞和巨噬细胞建立了6个免疫细胞亚型特异性谱库,涵盖了7815个具有表面标志物和免疫细胞富集蛋白的蛋白质组。利用单次 DIA 对小鼠结直肠癌(CRC)模型肿瘤中的 1 μg 组织蛋白进行微尺度免疫蛋白质组分析的可行性得到了证实;与直接 DIA 分析(6978 个蛋白质)相比,免疫细胞富集库提高了覆盖率,量化了 7419 个蛋白质。通过增强,绘制了 841 个免疫功能相关蛋白的图谱,并独家鉴定了许多低丰度免疫蛋白,如 CD1D1 和 CD244,显示了免疫图谱分析的高灵敏度。我们采用这种方法描述了 CRC 模型中 MLNs 的特征,旨在阐明它们参与 TME 内癌症发展的机制。即使肿瘤中的免疫细胞浸润比例较低(0.25-3%),我们的结果也显示了适应性免疫信号通路(C 型凝集素受体信号转导、趋化因子信号转导等)、T 细胞受体信号转导和 Th1/Th2/Th17 细胞分化的下调,这表明 CRC 模型的 MLNs 存在免疫抑制状态。利用免疫细胞富集文库的DIA方法展示了其深度覆盖性和高灵敏度,有助于阐明微量样本的免疫蛋白质组图谱。
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来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
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