Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America; Department of Consortium for Fibrosis Research & Translation, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America.
Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America.
J Mol Cell Cardiol. 2021 May;154:92-96. doi: 10.1016/j.yjmcc.2021.01.007. Epub 2021 Feb 5.
Alternative splicing is prevalent in the heart and implicated in many cardiovascular diseases, but not every alternative transcript is translated and detecting non-canonical isoforms at the protein level remains challenging. Here we show the use of a computation-assisted targeted proteomics workflow to detect protein alternative isoforms in the human heart. We build on a recent strategy to integrate deep RNA-seq and large-scale mass spectrometry data to identify candidate translated isoform peptides. A machine learning approach is then applied to predict their fragmentation patterns and design protein isoform-specific parallel reaction monitoring detection (PRM) assays. As proof-of-principle, we built PRM assays for 29 non-canonical isoform peptides and detected 22 peptides in a human heart lysate. The predictions-aided PRM assays closely mirrored synthetic peptide standards for non-canonical sequences. This approach may be useful for validating non-canonical protein identification and discovering functionally relevant isoforms in the heart.
选择性剪接在心脏中很普遍，与许多心血管疾病有关，但并非每个选择性转录本都被翻译，并且在蛋白质水平上检测非规范同工型仍然具有挑战性。在这里，我们展示了使用计算辅助靶向蛋白质组学工作流程来检测人类心脏中的蛋白质选择性同工型。我们基于最近的一种策略，整合深度 RNA-seq 和大规模质谱数据来识别候选翻译同工型肽。然后应用机器学习方法来预测它们的片段模式并设计蛋白质同工型特异性平行反应监测检测 (PRM) 测定法。作为原理验证，我们为 29 个非规范同工型肽构建了 PRM 测定法，并在人心脏裂解物中检测到 22 个肽。预测辅助的 PRM 测定法与非规范序列的合成肽标准非常吻合。这种方法可用于验证非规范蛋白质鉴定和发现心脏中具有功能相关性的同工型。
