•The patient with an SLC6A1 mutation, typically linked to disorders like epilepsy and autism, exhibited symptoms consistent with schizophrenia and bipolar disorder.•The patient's polygenic risk score ...was aligned with both schizophrenia and bipolar disorder, despite no family history of psychiatric disorders.•The study contributed to ongoing discussion of the importance of GABAergic processes in schizophrenia's etiology.
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.
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.
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.
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.
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.
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•Met to iso-Thr conversion not encoded in genome was detected in proteome data.•Peptides with Thr and iso-Thr differ in their CID and HCD fragmentation patterns.•Met conversion to iso-Thr occurs during incubation with iodoacetamide at 95°C.•Iso-Thr variant can be detected for up to 10% of methionine-containing peptides.•Met to iso-Thr conversion has been experimentally proven using model protein.
Control of the crystallization front profile is of great importance for various aspects of bulk SiC crystal growth by physical vapor transport. The structural defect density, doping uniformity, and ...polytype stability are largely dependent on the profile evolution. In this paper, we consider the binary crystal growth from the multicomponent vapor and suggest a model of facet formation. The model is based on the microscopic consideration of the crystal growth by step-flow mechanism, with the step density dependent on the local front orientation with respect to the close-packed crystal planes. The growth kinetics employs the Burton–Cabrera–Frank approach extended to binary crystals and a multicomponent vapor. The model was implemented into the “Virtual Reactor” code and used to simulate the faceting during growth of the free-spreading bulk SiC crystals. The computations are compared with observations, providing a reasonable agreement between the theory and experiment. The developed approach can be readily extended to other materials grown from the vapor.
Studies of the photostimulated aggregation of ultradispersoidal Ag particles into fractal clusters observed in colloidal solutions irradiated by different types of pulsed and continuous-wave lasers ...and by non-monochromatic light are described. A photoaggregation mechanism is suggested, on the basis of mutual opposite charging of different-sized particles due to the equalization of their size-dependent Fermi energies in a conducting medium.
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