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Shotgun protein sequencing with meta-contig assembly

机译:散弹枪装配的Shotgun蛋白测序

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Full-length de novo sequencing from tandem mass (MS/MS) spectra of unknown proteins such as antibodies or proteins from organisms with unsequenced genomes remains a challenging open problem. Conventional algorithms designed to individually sequence each MS/MS spectrum are limited by incomplete peptide fragmentation or low signal to noise ratios and tend to result in short de novo sequences at low sequencing accuracy. Our shotgun protein sequencing (SPS) approach was developed to ameliorate these limitations by first finding groups of unidentified spectra from the same peptides (contigs) and then deriving a consensus de novo sequence for each assembled set of spectra (contig sequences). But whereas SPS enables much more accurate reconstruction of de novo sequences longer than can be recovered from individual MS/MS spectra, it still requires error-tolerant matching to homologous proteins to group smaller contig sequences into full-length protein sequences, thus limiting its effectiveness on sequences from poorly annotated proteins. Using low and high resolution CID and high resolution HCD MS/MS spectra, we address this limitation with a Meta-SPS algorithm designed to overlap and further assemble SPS contigs into Meta-SPS de novo contig sequences extending as long as 100 amino acids at over 97% accuracy without requiring any knowledge of homologous protein sequences. We demonstrate Meta-SPS using distinct MS/MS data sets obtained with separate enzymatic digestions and discuss how the remaining de novo sequencing limitations relate to MS/MS acquisition settings.
机译:从未知蛋白质(例如抗体或基因组未测序的生物体的蛋白质)的串联质谱(MS / MS)质谱图进行全长从头测序仍然是一个充满挑战的开放性问题。被设计为单独对每个MS / MS谱进行单独测序的常规算法受到不完整的肽片段化或信噪比低的限制,并且倾向于以低测序精度导致短的从头测序序列。我们开发了shot弹枪蛋白质测序(SPS)方法,以通过首先从相同的肽段(重叠群)中找到未鉴定的光谱组,然后为每个组装的光谱集(重叠群序列)推导出一致的从头序列来改善这些局限性。但是,尽管SPS能够比从单个MS / MS光谱中恢复更长的时间来重新构建从头序列,但仍然需要与同源蛋白进行容错匹配才能将较小的重叠群序列分组为全长蛋白序列,从而限制了其有效性来自注释不良的蛋白质的序列。使用低分辨率和高分辨率CID以及高分辨率HCD MS / MS光谱,我们通过设计成重叠并进一步将SPS重叠群合成为Meta-SPS de novo重叠群序列的Meta-SPS算法解决了这一局限,该序列延伸超过100个氨基酸无需任何同源蛋白序列知识即可达到97%的准确性。我们使用不同的MS / MS数据集(通过单独的酶切消化)演示Meta-SPS,并讨论剩余的从头测序的局限性如何与MS / MS采集设置相关。

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