Systematic Assessment of the Benefits and Caveats in Mining Microbial Post-Translational Modifications from Shotgun Proteomic Data: The Response of <i>Shewanella oneidensis</i> to Chromate Exposure

Microbes are known to regulate both gene expression and protein activity through the use of post-translational modifications (PTMs). Common PTMs involved in cellular signaling and gene control include methylations, acetylations, and phosphorylations, whereas oxidations have been implicated as an indicator of stress. Shewanella oneidensis MR-1 is a Gram-negative bacterium that demonstrates both respiratory versatility and the ability to sense and adapt to diverse environmental conditions. The data set used in this study consisted of tandem mass spectra derived from midlog phase aerobic cultures of S. oneidensis either native or shocked with 1 mM chromate [Cr(VI)]. In this study, three algorithms (DBDigger, Sequest, and InsPecT) were evaluated for their ability to scrutinize shotgun proteomic data for evidence of PTMs. The use of conservative scoring filters for peptides or proteins versus creating a subdatabase first from a nonmodification search was evaluated with DBDigger. The use of higher-scoring filters for peptide identifications was found to result in optimal identifications of PTM peptides with a 2% false discovery rate (FDR) for the total data set using the DBDigger algorithm. However, the FDR climbs to unacceptably high levels when only PTM peptides are considered. Sequest was evaluated as a method for confirming PTM peptides putatively identified using DBDigger; however, there was a low identification rate (∼25%) for the searched spectra. InsPecT was found to have a much lower, and thus more acceptable, FDR than DBDigger for PTM peptides. Comparisons between InsPecT and DBDigger were made with respect to both the FDR and PTM peptide identifications. As a demonstration of this approach, a number of S. oneidensis chemotaxis proteins as well as low-abundance signal transduction proteins were identified as being post-translationally modified in response to chromate challenge.已知微生物可通过翻译后修饰（post-translational modifications, PTMs）调控基因表达与蛋白质活性。参与细胞信号转导及基因调控的常见PTMs包括甲基化、乙酰化与磷酸化，而氧化修饰则被视作应激反应的指示标志物。奥奈达希瓦氏菌MR-1（Shewanella oneidensis MR-1）是一种革兰氏阴性菌，兼具呼吸代谢多样性与感知并适应多种环境条件的能力。本研究使用的数据集源自该菌对数生长中期需氧培养物的串联质谱谱图，样本分为野生型与经1 mM铬酸盐[Cr(VI)]胁迫两组。本研究评估了DBDigger、Sequest与InsPecT三种算法在鸟枪法蛋白质组学数据中筛选PTMs相关修饰证据的性能。针对DBDigger算法，本研究对比了两种分析策略：对肽段或蛋白质采用保守性评分过滤，与先通过非修饰搜索构建子数据库后再开展分析的策略。结果显示，使用DBDigger算法时，对肽段鉴定采用更高评分的过滤策略，可在全数据集下实现2%错误发现率（false discovery rate, FDR）的PTM肽段最优鉴定，但仅考虑PTM肽段时，FDR会升至不可接受的高水平。Sequest被用于验证通过DBDigger推定鉴定出的PTM肽段，但该算法对检索谱图的鉴定率仅约25%，相对偏低。InsPecT用于PTM肽段鉴定时的FDR远低于DBDigger，更符合实验要求。本研究同时从错误发现率与PTM肽段鉴定数两个维度，对比了InsPecT与DBDigger的性能。作为该分析流程的应用示例，本研究鉴定出多种奥奈达希瓦氏菌的趋化蛋白及低丰度信号转导蛋白，这些蛋白均在铬酸盐胁迫下发生了翻译后修饰。