Enhanced Discovery of Alternative Proteins (AltProts) in Mouse Cardiac Development Using Data-Independent Acquisition (DIA) Proteomics

Abstract

Alternative proteins (AltProts) are a class of proteins encoded by DNA sequences previously classified as noncoding. Despite their historically being overlooked, recent studies have highlighted their widespread presence and distinctive biological roles. So far, direct detection of AltProt has been relying on data-dependent acquisition (DDA) mass spectrometry (MS). However, data-independent acquisition (DIA) MS, a method that is rapidly gaining popularity for the analysis of canonical proteins, has seen limited application in AltProt research, largely due to the complexities involved in constructing DIA libraries. In this study, we present a novel DIA workflow that leverages a fragmentation spectra predictor for the efficient construction of DIA libraries, significantly enhancing the detection of AltProts. Our method achieved a 2-fold increase in the identification of AltProts and a 50% reduction in missing values compared to DDA. We conducted a comprehensive comparison of four AltProt databases, four DIA-library construction strategies, and three analytical software tools to establish an optimal workflow for AltProt analysis. Utilizing this workflow, we investigated the mouse heart development process and identified over 50 AltProts with differential expression between embryonic and adult heart tissues. Over 30 unannotated mouse AltProts were validated, including ASDURF, which played a crucial role in cardiac development. Our findings not only provide a practical workflow for MS-based AltProt analysis but also reveal novel AltProts with potential significance in biological functions.