Biology subjects

Ishihama, Y.

Publications and source records attributed to Ishihama, Y..

4 recordsLinked to original sources

bioRxiv2020

Peak identification and quantification by proteomic mass spectrogram decomposition

Recent advances in liquid chromatography/mass spectrometry (LC/MS) technology have notably improved the sensitivity, resolution, and speed of proteome analysis, resulting in increasing demand for more sophisticated algorithms to interpret complex mass spectrograms. Here, we propose a novel statistical method that we call proteomic mass spectrogram decomposition (ProtMSD) for joint identification and quantification of peptides and proteins. Given the proteomic mass spectrogram and the reference mass spectra of all possible peptide ions associated with proteins as a dictionary, our method directly estimates the temporal intensity curves of those peptide ions, i.e., the chromatograms, under a group sparsity constraint without using the conventional careful pre-processing (e.g., thresholding and peak picking). We show that the accuracy of protein identification was significantly improved by using the protein-peptide hierarchical relationships, the isotopic distribution profiles and predicted retention times of peptide ions and the pre-learned mass spectra of noise. In the analysis of E. coli cell lysate, our ProtMSD showed excellent agreement (3277 peptide ions (94.79%) and 493 proteins (98.21%)) with the conventional cascading approach to identification and quantification based on Mascot and Skyline. This is the first attempt to use a matrix decomposition technique as a tool for LC/MS-based joint proteome identification and quantification.

bioinformatics↗

bioRxiv2020

Effect of Phosphorylation on the Collision Cross Sections of Peptide Ions in Ion Mobility Spectrometry

The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups.

biochemistry↗

bioRxiv2020

Proximity Labeling-assisted Identification of Endogenous Kinase Substrates

Mass spectrometry-based phosphoproteomics can identify more than 10,000 phosphorylated sites in a single experiment. But, despite the fact that enormous phosphosite information has been accumulated in public repositories, protein kinase-substrate relationships remain largely unknown. Here, we describe a method to identify endogenous substrates of kinases by means of proximity labeling. We used a proximity-dependent biotin identification approach, called BioID, in combination with kinase-perturbed phosphoproteomics profiling and phosphorylation sequence motifs derived from in vitro kinase assay to find molecules that interact with a target kinase, that show altered phosphorylation in response to kinase perturbation, and that are directly phosphorylated by the kinase in vitro; i.e., endogenous kinase substrates. Application of this methodology to casein kinase 2 (CK2) and protein kinase A (PKA) identified 33 and 52 putative substrates, respectively. We also show that known cancer-associated missense mutations near phosphosites of substrates affect phosphorylation by CK2 or PKA, and thus might alter downstream signaling in cancer cells bearing these mutations. This study extends our knowledge of kinase-substrate networks by proposing a new large-scale approach to identify endogenous substrates of kinases.

molecular biology↗

bioRxiv2020

Quantitative nascent proteome profiling by dual pulse labeling with O-propargyl-puromycin and stable isotope labeled amino acids

Monitoring translational regulation in response to environmental signals is crucial for understanding cellular proteostasis. However, only limited approaches are currently available for quantifying acute changes in protein synthesis induced by stimuli. Recently, a clickable puromycin analog, O-propargyl-puromycin (OPP), was developed and applied to label the C-termini of nascent polypeptide chains (NPCs). Following affinity purification via a click reaction, OPP allows for a proteomic analysis of NPCs. Despite its advantage, the affinity purification of NPCs using magnetic beads or resins inherently suffers from significant non-specific protein binding, which hinders accurate quantification of the nascent proteins. To address this issue, we employed dual pulse labeling of NPCs with both OPP and stable isotope labeled amino acids to distinguish bona fide NPCs from non-specific proteins, thereby enabling the accurate quantitative profiling of NPCs. We applied this method to dissecting the transcription-coupled translation responses and quantified ~3,000 nascent proteins. We found that the translation of a subset of ribosomal proteins (e.g., RPSA, RPLP0) as well as signaling proteins (e.g., BCAR3, EFNA1, DUSP1) was significantly repressed by transcription inhibition. Together, the present method provides an accurate and broadly applicable nascent proteome profiling for many biological applications at the level of translation.

biochemistry↗