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从头测序肽段的串联质谱分析及其在蛋白质基因组学中的应用。

De Novo Sequencing of Peptides from Tandem Mass Spectra and Applications in Proteogenomics.

机构信息

Department of artificial intelligence and data engineering, Faculty of Engineering, Ankara University, Ankara, Turkey.

Medical Informatics and Bioinformatics, Institute for Measurement Engineering and Sensor Technology, Hochschule Ruhr West, University of Applied Sciences, Mülheim adR., Germany.

出版信息

Methods Mol Biol. 2025;2859:1-19. doi: 10.1007/978-1-0716-4152-1_1.

Abstract

The changes in protein expression are hallmarks of development and disease. Protein expression can be established qualitatively and quantitatively using mass spectrometry (MS). Samples are prepared, proteins extracted and then analyzed using MS and MS/MS. The resulting spectra need to be processed computationally to assign peptide spectrum match. Database searches employ sequence databases or spectral libraries for matching possible peptides with the measured spectra. This route is well established but fails when peptides are not found in sequence repositories. In this case, de novo sequencing of MS/MS spectra can be employed. Many computational algorithms that establish the peptide sequence from MS/MS spectrum alone are available. While de novo sequencing assigns a sequence to an MS/MS spectrum, this assignment can be used in further processes for genome annotation. For example, novel exons can be assigned, known exons can be extended, and splice sites can be validated at the protein level. We compiled an extensive list of such algorithms, grouped them, and discussed the selected approaches. We also provide a roadmap of how de novo sequencing can enter mainstream proteogenomic analysis. In the future, de novo predictions can be added to sample-specific protein databases, including RNA-seq translations. These enriched databases can then be used for proteogenomics studies with existing pipelines.

摘要

蛋白质表达的变化是发育和疾病的标志。可以使用质谱(MS)定性和定量地确定蛋白质表达。通过 MS 和 MS/MS 对样品进行预处理、提取蛋白质并进行分析。需要通过计算处理得到的光谱来分配肽谱匹配。数据库搜索使用序列数据库或光谱库将可能的肽与测量的光谱进行匹配。这种方法已经很成熟,但当肽在序列库中找不到时就会失败。在这种情况下,可以使用从头测序的 MS/MS 光谱。有许多可以从 MS/MS 光谱中单独建立肽序列的计算算法。虽然从头测序可以为 MS/MS 光谱分配一个序列,但该序列分配可用于基因组注释的进一步处理。例如,可以为 MS/MS 光谱分配新的外显子,扩展已知的外显子,并在蛋白质水平验证剪接位点。我们编译了一个广泛的此类算法列表,对其进行了分组,并讨论了所选方法。我们还提供了一个路线图,说明从头测序如何进入主流的蛋白质基因组分析。将来,可以将从头预测添加到特定于样本的蛋白质数据库中,包括 RNA-seq 翻译。然后,这些丰富的数据库可以与现有的管道一起用于蛋白质基因组学研究。

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