Nirujogi, Raja Sekhar

Abstract Molecular profiling of human primary cell types is essential for understanding human biology. We present a transcriptome and proteome map of 28 primary human cell types. Three major clusters of epithelial, endothelial, and mesenchymal cell types were observed in both the transcriptome and proteome levels along with the discovery of cell type enriched molecules including GRAP and C1orf116. The epithelial cell specific protein C1orf116 was further validated using immunohistochemistry across various human tissues. An exhaustive protein database search considering 39 post-translational modifications (PTMs) revealed novel insights into the PTM landscape including identification of understudied PTMs such as serine O-acetylation and histidine methylation. This also enabled comprehensive characterization of proteins with diverse PTMs. Interestingly, an unexpectedly higher frequency of dioxidation on tryptophan compared to methionine led to the identification of oxidative mitochondria complex subunit proteins. Further, a search strategy accounting for alternative translational start sites, splice junctions and translational readthrough refined genome annotation using proteomic evidence. For example, peptides from translational readthrough including extended sequence of LDHB and MDH1 were detected representing the first peptide-level evidence of these protein readthrough isoforms. Our comprehensive transcriptome and proteome data revealed cell type-specific molecular cues and heterogeneity, offering new insights into disease mechanisms often overlooked by tissue proteomics.

Abstract A data-independent acquisition (DIA) approach is being increasingly adopted as a promising strategy for identification and quantitation of proteomes. As most DIA data sets are acquired with wide isolation windows, highly complex MS/MS spectra are generated, which negatively impacts obtaining peptide information through classical protein database searches. Therefore, the analysis of DIA data mainly relies on the evidence of the existence of peptides from prebuilt spectral libraries. Consequently, one major weakness of this method is that it does not account for peptides that are not included in the spectral library, precluding the use of DIA for discovery studies. Here, we present a strategy termed Precursor ion And Small Slice-DIA (PASS-DIA) in which MS/MS spectra are acquired with small isolation windows (slices) and MS/MS spectra are interpreted with accurately determined precursor ion masses. This method enables the direct application of conventional spectrum-centric analysis pipelines for peptide identification and precursor ion-based quantitation. The performance of PASS-DIA was observed to be superior to both data-dependent acquisition (DDA) and conventional DIA experiments with 69 and 48% additional protein identifications, respectively. Application of PASS-DIA for the analysis of post-translationally modified peptides again highlighted its superior performance in characterizing phosphopeptides (77% more), N-terminal acetylated peptides (56% more), and N-glycopeptides (83% more) as compared to DDA alone. Finally, the use of PASS-DIA to characterize a rare proteome of human fallopian tube organoids enabled 34% additional protein identifications than DDA alone and revealed biologically relevant pathways including low abundance proteins. Overall, PASS-DIA is a novel DIA approach for use as a discovery tool that outperforms both conventional DDA and DIA experiments to provide additional protein information. We believe that the PASS-DIA method is an important strategy for discovery-type studies when deeper proteome characterization is required.

Abstract Understanding the molecular profile of every human cell type is essential for understanding its role in normal physiology and disease. Technological advancements in DNA sequencing, mass spectrometry, and computational methods allow us to carry out multiomics analyses although such approaches are not routine yet. Human umbilical vein endothelial cells (HUVECs) are a widely used model system to study pathological and physiological processes associated with the cardiovascular system. In this study, next‐generation sequencing and high‐resolution mass spectrometry to profile the transcriptome and proteome of primary HUVECs is employed. Analysis of 145 million paired‐end reads from next‐generation sequencing confirmed expression of 12 186 protein‐coding genes (FPKM ≥0.1), 439 novel long non‐coding RNAs, and revealed 6089 novel isoforms that were not annotated in GENCODE. Proteomics analysis identifies 6477 proteins including confirmation of N ‐termini for 1091 proteins, isoforms for 149 proteins, and 1034 phosphosites. A database search to specifically identify other post‐translational modifications provide evidence for a number of modification sites on 117 proteins which include ubiquitylation, lysine acetylation, and mono‐, di‐ and tri‐methylation events. Evidence for 11 “missing proteins,” which are proteins for which there was insufficient or no protein level evidence, is provided. Peptides supporting missing protein and novel events are validated by comparison of MS/MS fragmentation patterns with synthetic peptides. Finally, 245 variant peptides derived from 207 expressed proteins in addition to alternate translational start sites for seven proteins and evidence for novel proteoforms for five proteins resulting from alternative splicing are identified. Overall, it is believed that the integrated approach employed in this study is widely applicable to study any primary cell type for deeper molecular characterization.