Unipept in 2024: Expanding Metaproteomics Analysis with Support for Missed Cleavages and Semitryptic and Nontryptic Peptides.

IF 3.8 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Journal of Proteome Research Pub Date : 2025-01-10 DOI:10.1021/acs.jproteome.4c00848

Tibo Vande Moortele, Bram Devlaminck, Simon Van de Vyver, Tim Van Den Bossche, Lennart Martens, Peter Dawyndt, Bart Mesuere, Pieter Verschaffelt

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引用次数: 0

Abstract

Unipept, a pioneering software tool in metaproteomics, has significantly advanced the analysis of complex ecosystems by facilitating both taxonomic and functional insights from environmental samples. From the onset, Unipept's capabilities focused on tryptic peptides, utilizing the predictability and consistency of trypsin digestion to efficiently construct a protein reference database. However, the evolving landscape of proteomics and emerging fields like immunopeptidomics necessitate a more versatile approach that extends beyond the analysis of tryptic peptides. In this article, we present a significant update to the underlying index structure of Unipept, which is now powered by a Sparse Suffix Array index. This advancement enables the analysis of semitryptic peptides, peptides with missed cleavages, and nontryptic peptides such as those encountered in other research fields such as immunopeptidomics (e.g., MHC- and HLA-peptides). This new index benefits all tools in the Unipept ecosystem such as the web application, desktop tool, application programming interface (API), and command line interface. A benchmark study highlights significantly improved performance in handling missed cleavages, preserving the same level of accuracy.

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Unipept在2024年：扩展宏蛋白质组学分析，支持遗漏的切割和半胱氨酸和非胱氨酸肽。

Unipept是b宏蛋白质组学领域的一个开创性软件工具，通过促进环境样本的分类和功能洞察，显著推进了复杂生态系统的分析。从一开始，Unipept的能力就集中在胰蛋白酶上，利用胰蛋白酶消化的可预测性和一致性来有效地构建蛋白质参考数据库。然而，蛋白质组学和免疫肽组学等新兴领域的发展需要一种超越色氨酸肽分析的更通用的方法。在本文中，我们将对Unipept的底层索引结构进行重大更新，该结构现在由一个稀疏后缀数组索引提供支持。这一进步使得半胰蛋白酶、缺失切割肽和非胰蛋白酶的分析成为可能，如在免疫肽组学等其他研究领域（如MHC-和hla -肽）中遇到的那些。这个新的索引有利于Unipept生态系统中的所有工具，如web应用程序、桌面工具、应用程序编程接口（API）和命令行接口。一项基准研究突出了在处理遗漏的解理方面显着提高的性能，保持了相同水平的准确性。

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

Journal of Proteome Research 生物-生化研究方法

CiteScore

9.00

自引率

4.50%

发文量

251

审稿时长

3 months

期刊介绍： Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".