Comparative analysis of plasma affinity depletion methods: Impact on protein composition and phosphopeptide abundance in human plasma

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Pallaprolu Nikhil, Dande Aishwarya, Sameer Dhingra, Krishna Pandey, V. Ravichandiran, Ramalingam Peraman
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Abstract

Affinity-based protein depletion and TiO2 enrichment methods play a crucial role in detection of low-abundant proteins and phosphopeptides enrichment, respectively. Here, we assessed the effectiveness of HSA/IgG (HU2) and Human 7 (HU7) depletion methods and their impact on phosphopeptides coverage through comparative proteome analysis, utilizing in-solution digestion and nano-LC-Orbitrap mass spectrometry (MS). Our results demonstrated that both HU2 and HU7 affinity depletion significantly decreased high-abundant proteins by 1.5–7.8-fold (p < 0.001). A total of 1491 proteins were identified, with 48 proteins showing significant expression in the depleted groups. Notably, cadherin-13, neutrophil defensin 1, APM1, and desmoplakin variant protein were exclusively detected in the HU2/HU7-depleted groups. Furthermore, study on effect of depletion on phosphopeptides revealed an increase in tandem MS spectral counts with notable decrease (∼50%) in peptide spectrum matching in depleted groups, which was attributed to significant reduction in protein counts. Our post translation modification workflow for phosphoproteomics detected 42 phosphorylated peptides, corresponding to 12 phosphoproteins with unique peptide match ≥2 (high false discovery rates confidence). Among them, 10 phosphorylated proteins are highly expressed in depleted groups. Overall, these findings offer valuable insights in selection of protein depletion methods for comprehensive plasma proteomics analysis.

血浆亲和力耗竭方法的比较分析:对人体血浆中蛋白质组成和磷酸肽丰度的影响
基于亲和力的蛋白质耗竭和TiO2富集方法分别在检测低丰度蛋白质和富集磷酸肽方面发挥着重要作用。在此,我们利用溶液消化和纳米液相轨道质谱(MS)技术,通过比较蛋白质组分析,评估了HSA/IgG(HU2)和Human 7(HU7)去除方法的有效性及其对磷酸肽覆盖率的影响。我们的研究结果表明,HU2 和 HU7 亲和耗竭法都能使高丰度蛋白质显著减少 1.5-7.8 倍(p < 0.001)。共鉴定出 1491 个蛋白质,其中 48 个蛋白质在耗竭组中有显著表达。值得注意的是,在HU2/HU7耗竭组中只检测到了cadherin-13、嗜中性粒细胞防御素1、APM1和desmoplakin变体蛋白。此外,研究耗竭对磷酸肽的影响发现,在耗竭组中,串联质谱计数增加,肽谱匹配度明显下降(∼50%),这归因于蛋白质计数的显著减少。我们的磷酸化蛋白质组学翻译后修饰工作流程检测到 42 个磷酸化肽段,对应于 12 个磷酸化蛋白质,其唯一肽段匹配度≥2(高误发现率置信度)。其中,10 个磷酸化蛋白在耗竭组中高表达。总之,这些发现为选择蛋白质耗竭方法进行血浆蛋白质组学综合分析提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ELECTROPHORESIS
ELECTROPHORESIS 生物-分析化学
CiteScore
6.30
自引率
13.80%
发文量
244
审稿时长
1.9 months
期刊介绍: ELECTROPHORESIS is an international journal that publishes original manuscripts on all aspects of electrophoresis, and liquid phase separations (e.g., HPLC, micro- and nano-LC, UHPLC, micro- and nano-fluidics, liquid-phase micro-extractions, etc.). Topics include new or improved analytical and preparative methods, sample preparation, development of theory, and innovative applications of electrophoretic and liquid phase separations methods in the study of nucleic acids, proteins, carbohydrates natural products, pharmaceuticals, food analysis, environmental species and other compounds of importance to the life sciences. Papers in the areas of microfluidics and proteomics, which are not limited to electrophoresis-based methods, will also be accepted for publication. Contributions focused on hyphenated and omics techniques are also of interest. Proteomics is within the scope, if related to its fundamentals and new technical approaches. Proteomics applications are only considered in particular cases. Papers describing the application of standard electrophoretic methods will not be considered. Papers on nanoanalysis intended for publication in ELECTROPHORESIS should focus on one or more of the following topics: • Nanoscale electrokinetics and phenomena related to electric double layer and/or confinement in nano-sized geometry • Single cell and subcellular analysis • Nanosensors and ultrasensitive detection aspects (e.g., involving quantum dots, "nanoelectrodes" or nanospray MS) • Nanoscale/nanopore DNA sequencing (next generation sequencing) • Micro- and nanoscale sample preparation • Nanoparticles and cells analyses by dielectrophoresis • Separation-based analysis using nanoparticles, nanotubes and nanowires.
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