Department of Mathematical Modelling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Mol Cell Proteomics. 2013 Jul;12(7):1780-90. doi: 10.1074/mcp.M113.027540. Epub 2013 Feb 21.
An increasing number of studies involve integrative analysis of gene and protein expression data, taking advantage of new technologies such as next-generation transcriptome sequencing and highly sensitive mass spectrometry (MS) instrumentation. Recently, a strategy, termed ribosome profiling (or RIBO-seq), based on deep sequencing of ribosome-protected mRNA fragments, indirectly monitoring protein synthesis, has been described. We devised a proteogenomic approach constructing a custom protein sequence search space, built from both Swiss-Prot- and RIBO-seq-derived translation products, applicable for MS/MS spectrum identification. To record the impact of using the constructed deep proteome database, we performed two alternative MS-based proteomic strategies as follows: (i) a regular shotgun proteomic and (ii) an N-terminal combined fractional diagonal chromatography (COFRADIC) approach. Although the former technique gives an overall assessment on the protein and peptide level, the latter technique, specifically enabling the isolation of N-terminal peptides, is very appropriate in validating the RIBO-seq-derived (alternative) translation initiation site profile. We demonstrate that this proteogenomic approach increases the overall protein identification rate 2.5% (e.g. new protein products, new protein splice variants, single nucleotide polymorphism variant proteins, and N-terminally extended forms of known proteins) as compared with only searching UniProtKB-SwissProt. Furthermore, using this custom database, identification of N-terminal COFRADIC data resulted in detection of 16 alternative start sites giving rise to N-terminally extended protein variants besides the identification of four translated upstream ORFs. Notably, the characterization of these new translation products revealed the use of multiple near-cognate (non-AUG) start codons. As deep sequencing techniques are becoming more standard, less expensive, and widespread, we anticipate that mRNA sequencing and especially custom-tailored RIBO-seq will become indispensable in the MS-based protein or peptide identification process. The underlying mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000124.
越来越多的研究涉及基因和蛋白质表达数据的综合分析，利用下一代转录组测序和高灵敏度质谱（MS）仪器等新技术。最近，一种基于核糖体保护的 mRNA 片段深度测序的策略，即核糖体图谱（或 RIBO-seq），间接监测蛋白质合成，已被描述。我们设计了一种蛋白质基因组学方法，构建了一个定制的蛋白质序列搜索空间，由瑞士Prot 和 RIBO-seq 衍生的翻译产物构建，适用于 MS/MS 谱鉴定。为了记录使用构建的深度蛋白质组数据库的影响，我们采用了两种替代的基于 MS 的蛋白质组学策略，如下所示：（i）常规的Shotgun 蛋白质组学和（ii）N 端联合分数对角色谱（COFRADIC）方法。虽然前者技术可以在蛋白质和肽水平上进行全面评估，但后者技术，特别是能够分离 N 端肽，非常适合验证 RIBO-seq 衍生的（替代）翻译起始位点谱。我们证明，与仅搜索 UniProtKB-SwissProt 相比，这种蛋白质基因组学方法可将整体蛋白质鉴定率提高 2.5%（例如新的蛋白质产物、新的蛋白质剪接变体、单核苷酸多态性变体蛋白和已知蛋白质的 N 端延伸形式）。此外，使用此定制数据库，对 N 端 COFRADIC 数据的鉴定导致了除鉴定四个翻译的上游 ORF 之外，还检测到 16 个导致 N 端延伸的蛋白质变体的替代起始位点。值得注意的是，这些新翻译产物的特征表明使用了多个近同（非 AUG）起始密码子。随着深度测序技术变得越来越标准、更便宜和广泛，我们预计 mRNA 测序，特别是定制的 RIBO-seq，将成为基于 MS 的蛋白质或肽鉴定过程中不可或缺的一部分。基础质谱蛋白质组学数据已被存入 ProteomeXchange 联盟，数据集标识符为 PXD000124。
