一个处理大规模巧合错误的处理 De Novo 抗体由自下而上的蛋白质组的测序
Douwe Schulte1, Joost Snijder1
1Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands.
Journal of proteome research
|June 27, 2024
概括
拼接软件 (v1.5) 从数据重建抗体序列,通过解决质量错误和模两可的残留物来提高准确性. 新功能增强了 de novo 序测序的兼容性和容错性.
科学领域:
- 蛋白质组学是指蛋白质组学.
- 免疫学 免疫学 免疫学
- 生物信息学是一种生物信息学.
背景情况:
- "自下而上的蛋白质组学"能够高精度地从多产品中确定抗体序列.
- 序列测序的准确性受到同位素残留物 (氨酸/异氨酸) 和模两可的碎片化谱的挑战.
- De novo序算法可能会产生错误,影响抗体序列重建.
研究的目的:
- 提交Stitch软件 (v1.5) 的更新,以改善从de novo的抗体序列重建.
- 使用蛋白质组学数据提高抗体测序的准确性和稳定性.
- 为了提高Stitch与各种数据处理管道的兼容性.
主要方法:
- 实现了一个基于质量的对齐算法来处理质量巧合错误.
- 引入了一个后处理步骤,用于使用w-ions来分配白/异白残留物.
- 集成了一种频谱查看器,用于直接评估序列分配.
- 扩展了输入兼容性,包括来自Casanovo,PEAKS,Novor.Cloud,pNovo和MaxNovo的数据.
主要成果:
- 更新后的Stitch (v1.5) 显示了对类级别测序错误的更好的耐受性.
- 基于质量的对齐有效地解释了序列测序中的质量巧合错误.
- 用二次碎片离子来增强异构体残留物 (I/L) 的分配.
- 更广泛的算法兼容性增加了Stitch在各种蛋白质组学工作流中的适用性.
结论:
- 史蒂奇 (v1.5) 提供了一种更强大,更准确的方法,可以从新数据中重建抗体序列.
- 软件增强提高了蛋白质组学中的抗体序列确定可靠性.
- 斯蒂奇增强的兼容性和耐错性使其在各种抗体发现和表征管道中更容易使用.
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