马蛋白质图谱突显实验性 LPS 诱导关节炎期间滑膜液蛋白质组的动态变化

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-12 DOI:10.1021/acs.jproteome.4c0012510.1021/acs.jproteome.4c00125
Louise Bundgaard*, Filip Årman, Emma Åhrman, Marie Walters, Ulrich auf dem Keller, Johan Malmström and Stine Jacobsen, 
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引用次数: 0

摘要

在人类蛋白质组学研究中,人们一直在努力将大量的质谱碎片离子谱收集起来,形成庞大的光谱库(SL),作为数据独立采集(DIA)分析的资源。目前,在马的研究中仍缺少此类举措。在此,我们基于对 75 份马匹组织和体液样本的数据独立采集分析,展示了一个大规模的马匹光谱库,其中包括 6394 个典型蛋白质和 89,329 个独特的肽段。通过SL,可以对相同样本进行基于DIA-MS的大规模定量分析,生成定量马蛋白质分布图谱,从而推断不同器官和体液中的优势蛋白质。数据挖掘揭示了在特定类型的组织或体液中唯一鉴定出的 163 种蛋白质,作为确定组织特异性或组织类型特异性蛋白质的起点。我们通过强调实验性脂多糖诱发关节炎期间马滑膜液样本中蛋白质组的动态变化来展示 SL。模糊 c-means 聚类分析将 SERPINB1、ATRN、NGAL、LTF、MMP1 和 LBP 确定为关节炎症的假定生物标记物。该研究为今后采用 DIA-MS 进行马研究提供了可扩展的资源。
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An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis

In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.

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CiteScore
7.20
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4.30%
发文量
567
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