Profiling of the sORF-encoded peptides and discovery of their potential biological function using mass spectrometry

Abstract

The discovery of non-canonical proteins, such as small open reading frame-encoded peptides (sORF-encoded peptides, SEPs), alternative proteins (AltProts), and cryptic immunopeptides, has challenged the traditional boundaries of proteomics, revealing a hidden layer of the proteome. These biomolecules, often overlooked due to their small size, low abundance, and origins in genomic regions previously considered non-coding, challenge traditional proteomic paradigms. To overcome detection barriers, we developed advanced mass spectrometry-based approaches, integrating data-independent acquisition (DIA) proteomics, immunopeptidomics, and CRISPR-based functional screening. These methods, applied across three distinct studies corresponding to the core chapters of this thesis, provide novel insights into the biological roles of non-canonical proteins and establish robust tools for their characterization. First in Chapter 2, we optimized a DIA-based proteomics workflow to enhance AltProt detection in mouse cardiac development. Recognizing the limitations of conventional data-dependent acquisition, we employed computationally predicted spectral libraries to improve sensitivity, achieving a twofold increase in AltProt identifications with reduced missing values. Applied to embryonic and adult mouse heart tissues, this approach identified over 50 differentially expressed AltProts enriched in pathways linked to cellular differentiation. Through targeted validation using Western blotting and parallel reaction monitoring, we confirmed ASDURF, an upstream open reading frame (uORF)-derived protein, as a regulator of cardiomyocyte maturation, highlighting the developmental importance of AltProts and establishing a reliable pipeline for their study in other biological contexts. Next in Chapter 3, we addressed the challenges of identifying MHC-presented peptides from non-canonical sources by developing a Pseudo-DIA Library Search Strategy for immunopeptidomics. This method, combining unrestricted DIA searches with in silico predicted libraries, increased immunopeptide detection by up to 3.8-fold compared to standard approaches. In human cell lines, we identified cryptic peptides and neoantigens encoded by sORFs, assessing their immunogenic potential for personalized cancer immunotherapy. To facilitate broader adoption, we created a user-friendly graphical interface for generating spectral libraries from MSFragger outputs, validated across independent datasets. This work expands the scope of immunopeptidomics and supports the development of targeted cancer therapies. Finally in Chapter 4, we conducted a large-scale analysis of over 36,000 microproteins across 86 public mass spectrometry datasets, revealing their predominant origins in long non-coding RNAs and frequent proximity to oncogenes. Conservation analyses across 100 species indicated diverse evolutionary pressures, with mammalian-specific patterns suggesting adaptive roles. Using a CRISPR knockout library in three cancer cell lines, we demonstrated that several microproteins independently regulate proliferation, distinct from their associated canonical proteins, as evidenced by comparisons with public DepMap data. These findings position microproteins as potential therapeutic targets in oncology. Collectively, this thesis advances our understanding of the proteome's complexity by uncovering the functional roles of non-canonical proteins in development and disease. The methodologies developed provide practical tools for future studies, while the biological insights open new avenues for precision medicine and developmental biology research.