Dmitry S. Karpov

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.

PPLine: An Automated Pipeline for SNP, SAP, and Splice Variant Detection in the Context of Proteogenomics.

The fundamental mission of the Chromosome-Centric Human Proteome Project (C-HPP) is the research of human proteome diversity, including rare variants. Liver tissues, HepG2 cells, and plasma were selected as one of the major objects for C-HPP studies. The proteogenomic approach, a recently introduced technique, is a powerful method for predicting and validating proteoforms coming from alternative splicing, mutations, and transcript editing. We developed PPLine, a Python-based proteogenomic pipeline providing automated single-amino-acid polymorphism (SAP), indel, and alternative-spliced-variants discovery based on raw transcriptome and exome sequence data, single-nucleotide polymorphism (SNP) annotation and filtration, and the prediction of proteotypic peptides (available at https://sourceforge.net/projects/ppline). In this work, we performed deep transcriptome sequencing of HepG2 cells and liver tissues using two platforms: Illumina HiSeq and Applied Biosystems SOLiD. Using PPLine, we revealed 7756 SAP and indels for HepG2 cells and liver (including 659 variants nonannotated in dbSNP). We found 17 indels in transcripts associated with the translation of alternate reading frames (ARF) longer than 300 bp. The ARF products of two genes, SLMO1 and TMEM8A, demonstrate signatures of caspase-binding domain and Gcn5-related N-acetyltransferase. Alternative splicing analysis predicted novel proteoforms encoded by 203 (liver) and 475 (HepG2) genes according to both Illumina and SOLiD data. The results of the present work represent a basis for subsequent proteomic studies by the C-HPP consortium.

Human aqueous humor proteome in cataract, glaucoma, and pseudoexfoliation syndrome.

Twenty‐nine human aqueous humor samples from patients with eye diseases such as cataract and glaucoma with and without pseudoexfoliation syndrome were characterized by LC–high resolution MS analysis. In total, 269 protein groups were identified with 1% false discovery rate including 32 groups that were not reported previously for this biological fluid. Since the samples were analyzed individually, but not pooled, 36 proteins were identified in all samples, comprising the constitutive proteome of the fluid. The most dominant molecular function of aqueous humor proteins as determined by GO analysis is endopeptidase inhibitor activity. Label‐free protein quantification showed no significant difference between glaucoma and cataract aqueous humor proteomes. At the same time, we found decrease in the level of apolipoprotein D as a marker of the pseudoexfoliation syndrome. The data are available from ProteomeXchange repository (PXD002623).

Exome-based proteogenomics of HEK-293 human cell line: Coding genomic variants identified at the level of shotgun proteome.

Genomic and proteomic data were integrated into the proteogenomic workflow to identify coding genomic variants of Human Embryonic Kidney 293 (HEK‐293) cell line at the proteome level. Shotgun proteome data published by Geiger et al. (2012), Chick et al. (2015), and obtained in this work for HEK‐293 were searched against the customized genomic database generated using exome data published by Lin et al. (2014). Overall, 112 unique variants were identified at the proteome level out of ∼1200 coding variants annotated in the exome. Seven identified variants were shared between all the three considered proteomic datasets, and 27 variants were found in any two datasets. Some of the found variants belonged to widely known genomic polymorphisms originated from the germline, while the others were more likely resulting from somatic mutations. At least, eight of the proteins bearing amino acid variants were annotated as cancer‐related ones, including p53 tumor suppressor. In all the considered shotgun datasets, the variant peptides were at the ratio of 1:2.5 less likely being identified than the wild‐type ones compared with the corresponding theoretical peptides. This can be explained by the presence of the so‐called “passenger” mutations in the genes, which were never expressed in HEK‐293 cells. All MS data have been deposited in the ProteomeXchange with the dataset identifier PXD002613 (http://proteomecentral.proteomexchange.org/dataset/PXD002613).

Proteasome inhibition enhances resistance to DNA damage via upregulation of Rpn4-dependent DNA repair genes

The 26S proteasome is an ATP‐dependent multi‐subunit protease complex and the major regulator of intracellular protein turnover and quality control. However, its role in the DNA damage response is controversial. We addressed this question in yeast by disrupting the transcriptional regulation of the PRE1 proteasomal gene. The mutant strain has decreased proteasome activity and is hyper‐resistant to various DNA‐damaging agents. We found that Rpn4‐target genes MAG1, RAD23, and RAD52 are overexpressed in this strain due to Rpn4 stabilisation. These genes represent three different pathways of base excision, nucleotide excision and double strand break repair by homologous recombination (DSB‐HR). Consistently, the proteasome mutant displays increased DSB‐HR activity. Our data imply that the proteasome may have a negative role in DNA damage response.

The central domain of yeast transcription factor Rpn4 facilitates degradation of reporter protein in human cells

Despite high interest in the cellular degradation machinery and protein degradation signals (degrons), few degrons with universal activity along species have been identified. It has been shown that fusion of a target protein with a degradation signal from mammalian ornithine decarboxylase (ODC) induces fast proteasomal degradation of the chimera in both mammalian and yeast cells. However, no degrons from yeast‐encoded proteins capable to function in mammalian cells were identified so far. Here, we demonstrate that the yeast transcription factor Rpn4 undergoes fast proteasomal degradation and its central domain can destabilize green fluorescent protein and Alpha‐fetoprotein in human HEK 293T cells. Furthermore, we confirm the activity of this degron in yeast. Thus, the Rpn4 central domain is an effective interspecies degradation signal.

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.

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.

Functional analysis of Debaryomyces hansenii Rpn4 on a genetic background of Saccharomyces cerevisiae

Abstract The transcription factor ScRpn4 coordinates the expression of Saccharomyces cerevisiae proteasomal genes. ScRpn4 orthologues are found in a number of other Saccharomycetes yeasts. Their functions, however, have not yet been characterised experimentally in vivo. We expressed the Debaryomyces hansenii DEHA2D12848 gene encoding an ScRpn4 orthologue (DhRpn4), in an S. cerevisiae strain lacking RPN4. We showed that DhRpn4 activates transcription of proteasomal genes using ScRpn4 binding site and provides resistance to various stresses. The 43‐238 aa segment of DhRpn4 contains an unique portable transactivation domain. Similar to the ScRpn4 N‐terminus, this domain lacks a compact structure. Moreover, upon overexpression in D. hansenii, DhRpn4 upregulates protesomal genes. Thus, we show that DhRpn4 is the activator for proteasomal genes.