NovoLign:通过序列比对进行元蛋白质组学研究。

IF 5.1 Q1 ECOLOGY ISME communications Pub Date : 2024-10-12 eCollection Date: 2024-01-01 DOI:10.1093/ismeco/ycae121
Hugo B C Kleikamp, Ramon van der Zwaan, Ramon van Valderen, Jitske M van Ede, Mario Pronk, Pim Schaasberg, Maximilienne T Allaart, Mark C M van Loosdrecht, Martin Pabst
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摘要

质谱和生物信息学方法的巨大进步已将蛋白质组学扩展到微生物生态学领域。元蛋白质组学数据常用的光谱注释方法依赖于数据库搜索,这需要从整个元基因组测序实验中获得特定样本数据库。然而,创建这些数据库既复杂又耗时,而且容易出错,有可能使实验结果和结论产生偏差。这就要求采用其他方法,以快速、正交的方式深入了解元蛋白组学数据。在这里,我们介绍了 NovoLign,它是一种从新元蛋白质组学管道,可对来自完整元蛋白质组学实验的从新序列进行序列比对。该管道可对复杂群落进行快速分类剖析,并评估通过数据库搜索获得的元蛋白质组学结果的分类覆盖范围。此外,NovoLign 管道还支持创建用于数据库搜索的参考序列数据库,以确保全面覆盖。我们使用广泛的硅学和实验数据(包括纯参考菌株、实验室增菌培养物、合成群落和环境微生物群落)评估了 NovoLign 管道的分类覆盖率和假阳性注释。总之,我们介绍的 NovoLign 是一种全新的元蛋白质组学管道,它利用大规模序列比对实现快速分类剖析、评估数据库搜索结果和创建参考序列数据库。NovoLign 管道可通过 https://github.com/hbckleikamp/NovoLign 公开获取。
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NovoLign: metaproteomics by sequence alignment.

Tremendous advances in mass spectrometric and bioinformatic approaches have expanded proteomics into the field of microbial ecology. The commonly used spectral annotation method for metaproteomics data relies on database searching, which requires sample-specific databases obtained from whole metagenome sequencing experiments. However, creating these databases is complex, time-consuming, and prone to errors, potentially biasing experimental outcomes and conclusions. This asks for alternative approaches that can provide rapid and orthogonal insights into metaproteomics data. Here, we present NovoLign, a de novo metaproteomics pipeline that performs sequence alignment of de novo sequences from complete metaproteomics experiments. The pipeline enables rapid taxonomic profiling of complex communities and evaluates the taxonomic coverage of metaproteomics outcomes obtained from database searches. Furthermore, the NovoLign pipeline supports the creation of reference sequence databases for database searching to ensure comprehensive coverage. We assessed the NovoLign pipeline for taxonomic coverage and false positive annotations using a wide range of in silico and experimental data, including pure reference strains, laboratory enrichment cultures, synthetic communities, and environmental microbial communities. In summary, we present NovoLign, a de novo metaproteomics pipeline that employs large-scale sequence alignment to enable rapid taxonomic profiling, evaluation of database searching outcomes, and the creation of reference sequence databases. The NovoLign pipeline is publicly available via: https://github.com/hbckleikamp/NovoLign.

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