Proteomics-Compatible Fourier Transform Isotopic Ratio Mass Spectrometry of Polypeptides.

Measuring the relative abundances of heavy stable isotopes of the elements C, H, N, and O in proteins is of interest in environmental science, archeology, zoology, medicine, and other fields. The isotopic abundance measurements of the fine structure of immonium ions with ultrahigh resolution mass spectrometry obtained in gas-phase fragmentation of polypeptides have previously uncovered anomalous deuterium enrichment in (hydroxy)proline of bone collagen in marine mammals. Here, we provide a detailed description and validation of this approach and demonstrate per mil-range precision of isotopic ratio measurements in aliphatic residues from proteins and cell lysates. The analysis consists of proteomics-type experiment demanding sub-microgram amounts of a protein sample and providing concomitantly protein sequence data allowing one to verify sample purity and establish its identity. A novel software tool protein amino acid-resolved isotopic ratio mass spectrometry (PAIR-MS) is presented for extracting isotopic ratio data from the raw data files acquired on an Orbitrap mass spectrometer.

Abnormal (Hydroxy)proline Deuterium Content Redefines Hydrogen Chemical Mass.

Analyzing the δ2H values in individual amino acids of proteins extracted from vertebrates, we unexpectedly found in some samples, notably bone collagen from seals, more than twice as much deuterium in proline and hydroxyproline residues than in seawater. This corresponds to at least 4 times higher δ2H than in any previously reported biogenic sample. We ruled out diet as a plausible mechanism for such anomalous enrichment. This finding puts into question the old adage that "you are what you eat".

A Tale of Two Tails: Efficient Profiling of Protein Degraders by Specific Functional and Target Engagement Readouts.

Targeted protein degradation represents an area of great interest, potentially offering improvements with respect to dosing, side effects, drug resistance, and reaching "undruggable" proteins compared with traditional small-molecule therapeutics. A major challenge in the design and characterization of degraders acting as molecular glues is that binding of the molecule to the protein of interest (PoI) is not needed for efficient and selective protein degradation; instead, one needs to understand the interaction with the responsible ligase. Similarly, for proteasome targeting chimeras (PROTACs), understanding the binding characteristics of the PoI alone is not sufficient. Therefore, simultaneously assessing the binding to both PoI and the E3 ligase as well as the resulting degradation profile is of great value. The cellular thermal shift assay (CETSA) is an unbiased cell-based method, designed to investigate the interaction of compounds with their cellular protein targets by measuring compound-induced changes in protein thermal stability. In combination with mass spectrometry (MS), CETSA can simultaneously evaluate compound-induced changes in the stability of thousands of proteins. We have used CETSA MS to profile a number of protein degraders, including molecular glues (e.g., immunomodulatory drugs) and PROTACs, to understand mode of action and to deconvolute off-target effects in intact cells. Within the same experiment, we were able to monitor both target engagement by observing changes in protein thermal stability as well as efficacy by simultaneous assessment of protein abundances. This allowed us to correlate target engagement (i.e., binding to the PoI and ligases) and functional readout (i.e., degrader induced protein degradation).

Proteogenomics of Adenosine-to-Inosine RNA Editing in the Fruit Fly.

Adenosine-to-inosine RNA editing is one of the most common types of RNA editing, a posttranscriptional modification made by special enzymes. We present a proteomic study on this phenomenon for Drosophila melanogaster. Three proteome data sets were used in the study: two taken from public repository and the third one obtained here. A customized protein sequence database was generated using results of genome-wide adenosine-to-inosine RNA studies and applied for identifying the edited proteins. The total number of 68 edited peptides belonging to 59 proteins was identified in all data sets. Eight of them being shared between the whole insect, head, and brain proteomes. Seven edited sites belonging to synaptic vesicle and membrane trafficking proteins were selected for validation by orthogonal analysis by Multiple Reaction Monitoring. Five editing events in cpx, Syx1A, Cadps, CG4587, and EndoA were validated in fruit fly brain tissue at the proteome level using isotopically labeled standards. Ratios of unedited-to-edited proteoforms varied from 35:1 ( Syx1A) to 1:2 ( EndoA). Lys-137 to Glu editing of endophilin A may have functional consequences for its interaction to membrane. The work demonstrates the feasibility to identify the RNA editing event at the proteome level using shotgun proteomics and customized edited protein database.

Proteogenomics of Malignant Melanoma Cell Lines: The Effect of Stringency of Exome Data Filtering on Variant Peptide Identification in Shotgun Proteomics.

The identification of genetically encoded variants at the proteome level is an important problem in cancer proteogenomics. The generation of customized protein databases from DNA or RNA sequencing data is a crucial stage of the identification workflow. Genomic data filtering applied at this stage may significantly modify variant search results, yet its effect is generally left out of the scope of proteogenomic studies. In this work, we focused on this impact using data of exome sequencing and LC-MS/MS analyses of six replicates for eight melanoma cell lines processed by a proteogenomics workflow. The main objectives were identifying variant peptides and revealing the role of the genomic data filtering in the variant identification. A series of six confidence thresholds for single nucleotide polymorphisms and indels from the exome data were applied to generate customized sequence databases of different stringency. In the searches against unfiltered databases, between 100 and 160 variant peptides were identified for each of the cell lines using X!Tandem and MS-GF+ search engines. The recovery rate for variant peptides was ∼1%, which is approximately three times lower than that of the wild-type peptides. Using unfiltered genomic databases for variant searches resulted in higher sensitivity and selectivity of the proteogenomic workflow and positively affected the ability to distinguish the cell lines based on variant peptide signatures.

How well can morphology assess cell death modality? A proteomics study.

While the focus of attempts to classify cell death programs has finally shifted in 2010s from microscopy-based morphological characteristics to biochemical assays, more recent discoveries have put the underlying assumptions of many such assays under severe stress, mostly because of the limited specificity of the assays. On the other hand, proteomics can quantitatively measure the abundances of thousands of proteins in a single experiment. Thus proteomics could develop a modern alternative to both semiquantitative morphology assessment as well as single-molecule biochemical assays. Here we tested this hypothesis by analyzing the proteomes of cells dying after been treated with various chemical agents. The most striking finding is that, for a multivariate model based on the proteome changes in three cells lines, the regulation patterns of the 200-500 most abundant proteins typically attributed to household type more accurately reflect that of the proteins directly interacting with the drug than any other protein subset grouped by common function or biological process, including cell death. This is in broad agreement with the 'rigid cell death mechanics' model where drug action mechanism and morphological changes caused by it are bijectively linked. This finding, if confirmed, will open way for a broad use of proteomics in death modality assessment.

Methionine to isothreonine conversion as a source of false discovery identifications of genetically encoded variants in proteogenomics.

Searching deep proteome data for 9 NCI-60 cancer cell lines obtained earlier by Moghaddas Gholami et al. (Cell Reports, 2013) against a database from cancer genomes returned a variant tryptic peptide fragment 57-72 of molecular chaperone HSC70, in which methionine residue at 61 position is replaced by threonine, or isothreonine (homoserine), residue. However, no traces of the corresponding genetic alteration were found in the cell line genomes reported by Abaan et al. (Cancer Research, 2013). Studying on the background of this modification led us to conclude that a conversion of methionine into isothreonine resulted from iodoacetamide treatment of the probe during a sample preparation step. We found that up to 10% of methionine containing peptides experienced the above conversion for the datasets under study. The artifact was confirmed by model experiment with bovine albumin, where three of four methionine residues were partly converted to isothreonine by conventional iodoacetamide treatment. This experimental side reaction has to be taken into account when searching for genetically encoded peptide variants in the proteogenomics studies. BIOLOGICAL SIGNIFICANCE: A lot of effort is currently put into proteogenomics of cancer. Studies detect non-synonymous cancer mutations at protein level by search of high-throughput LC-MS/MS data against customized genomic databases. In such studies, much attention is paid to potential false positive identifications. Here we describe one possible cause of such false identifications, an artifact of sample preparation which mimics methionine to threonine nucleic acid-encoded variant. The methionine to isothreonine conversion should be taken into consideration for correct interpretation of proteogenomic data.

Exome-driven characterization of the cancer cell lines at the proteome level: the NCI-60 case study.

Cancer genome deviates significantly from the reference human genome, and thus a search against standard genome databases in cancer cell proteomics fails to identify cancer-specific protein variants. The goal of this Article is to combine high-throughput exome data [Abaan et al. Cancer Res. 2013] and shotgun proteomics analysis [Modhaddas Gholami et al. Cell Rep. 2013] for cancer cell lines from NCI-60 panel to demonstrate further that the cell lines can be effectively recognized using identified variant peptides. To achieve this goal, we generated a database containing mutant protein sequences of NCI-60 panel of cell lines. The proteome data were searched using Mascot and X!Tandem search engines against databases of both reference and mutant protein sequences. The identification quality was further controlled by calculating a fraction of variant peptides encoded by the own exome sequence for each cell line. We found that up to 92.2% peptides identified by both search engines are encoded by the own exome. Further, we used the identified variant peptides for cell line recognition. The results of the study demonstrate that proteome data supported by exome sequence information can be effectively used for distinguishing between different types of cancer cell lines.

Detection of viral proteins in human cells lines by xeno-proteomics: elimination of the last valid excuse for not testing every cellular proteome dataset for viral proteins.

Cell cultures used routinely in proteomic experiments may contain proteins from other species because of infection, transfection or just contamination. Since infection or contamination may affect the results of a biological experiment, it is important to test the samples for the presence of "alien" proteins. Usually cells are tested only for the most common infections, and most of the existing tests are targeting specific contaminations. Here we describe a three-step procedure for reliable untargeted detection of viral proteins using proteomics data, and recommend this or similar procedure to be applied to every proteomics dataset submitted for publication.