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Beyond mass spectrometry, the next step in proteomics

机译：超越质谱，蛋白质组学的下一步

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Proteins can be the root cause of a disease, and they can be used to cure it. The need to identify these critical actors was recognized early (1951) by Sanger; the first biopolymer sequenced was a peptide, insulin. With the advent of scalable, single-molecule DNA sequencing, genomics and transcriptomics have since propelled medicine through improved sensitivity and lower costs, but proteomics has lagged behind. Currently, proteomics relies mainly on mass spectrometry (MS), but instead of truly sequencing, it classifies a protein and typically requires about a billion copies of a protein to do it. Here, we offer a survey that illuminates a few alternatives with the brightest prospects for identifying whole proteins and displacing MS for sequencing them. These alternatives all boast sensitivity superior to MS and promise to be scalable and seem to be adaptable to bioinformatics tools for calling the sequence of amino acids that constitute a protein.
机译：蛋白质可以是疾病的根本原因，它们可用于治愈它。萨尔杰申请识别这些关键行动者的需要;第一个生物聚合物测序是肽，胰岛素。随着可扩展，单分子DNA测序，基因组学和转录组织的出现，由于通过改善敏感性和降低成本，因此可以推进药物，但蛋白质组学落后。目前，蛋白质组学主要依赖于质谱（MS），而不是真正排序，而不是真正测序，它归类蛋白质，通常需要大约十亿份蛋白质进行蛋白质。在这里，我们提供了一项调查，阐明了一些替代品，具有最明亮的前景，用于识别整个蛋白质和移位MS进行测序。这些替代方案都夸大敏感度优于MS，并承诺可扩展，似乎适应生物信息学工具，用于呼叫构成蛋白质的氨基酸序列。

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