Publications by authors named "Andrey V Lisitsa"

30 Publications

  • Page 1 of 1

Does Proteomic Mirror Reflect Clinical Characteristics of Obesity?

J Pers Med 2021 Jan 21;11(2). Epub 2021 Jan 21.

Institute of Biomedical Chemistry, Pogodinskaya Street 10/8, 119121 Moscow, Russia.

Obesity is a frightening chronic disease, which has tripled since 1975. It is not expected to slow down staying one of the leading cases of preventable death and resulting in an increased clinical and economic burden. Poor lifestyle choices and excessive intake of "cheap calories" are major contributors to obesity, triggering type 2 diabetes, cardiovascular diseases, and other comorbidities. Understanding the molecular mechanisms responsible for development of obesity is essential as it might result in the introducing of anti-obesity targets and early-stage obesity biomarkers, allowing the distinction between metabolic syndromes. The complex nature of this disease, coupled with the phenomenon of metabolically healthy obesity, inspired us to perform data-centric, hypothesis-generating pilot research, aimed to find correlations between parameters of classic clinical blood tests and proteomic profiles of 104 lean and obese subjects. As the result, we assembled patterns of proteins, which presence or absence allows predicting the weight of the patient fairly well. We believe that such proteomic patterns with high prediction power should facilitate the translation of potential candidates into biomarkers of clinical use for early-stage stratification of obesity therapy.
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http://dx.doi.org/10.3390/jpm11020064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912072PMC
January 2021

Proteomic Analysis of Chr 18 Proteins Using 2D Fractionation.

J Proteome Res 2020 12 17;19(12):4901-4906. Epub 2020 Nov 17.

Institute of Biomedical Chemistry, Pogodinskaya 10, Moscow 119121, Russia.

One of the main goals of the Chromosome-Centric Human Proteome Project (C-HPP) is detection of "missing proteins" (PE2-PE4). Using the UPS2 (Universal proteomics standard 2) set as a model to simulate the range of protein concentrations in the cell, we have previously shown that 2D fractionation enables the detection of more than 95% of UPS2 proteins in a complex biological mixture. In this study, we propose a novel experimental workflow for protein detection during the analysis of biological samples. This approach is extremely important in the context of the C-HPP and the neXt-MP50 Challenge, which can be solved by increasing the sensitivity and the coverage of the proteome encoded by a particular human chromosome. In this study, we used 2D fractionation for in-depth analysis of the proteins encoded by human chromosome 18 (Chr 18) in the HepG2 cell line. Use of 2D fractionation increased the sensitivity of the SRM SIS method by 1.3-fold (68 and 88 proteins were identified by 1D fractionation and 2D fractionation, respectively) and the shotgun MS/MS method by 2.5-fold (21 and 53 proteins encoded by Chr 18 were detected by 1D fractionation and 2D fractionation, respectively). The results of all experiments indicate that 111 proteins encoded by human Chr 18 have been identified; this list includes 42% of the Chr 18 protein-coding genes and 67% of the Chr 18 transcriptome species (Illumina RNaseq) in the HepG2 cell line obtained using a single sample. Corresponding mRNAs were not registered for 13 of the detected proteins. The combination of 2D fractionation technology with SRM SIS and shotgun mass spectrometric analysis did not achieve full coverage, i.e., identification of at least one protein product for each of the 265 protein-coding genes of the selected chromosome. To further increase the sensitivity of the method, we plan to use 5-10 crude synthetic peptides for each protein to identify the proteins and select one of the peptides based on the obtained mass spectra for the synthesis of an isotopically labeled standard for subsequent quantitative analysis. Data are available via ProteomeXchange with the identifier PXD019263.
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http://dx.doi.org/10.1021/acs.jproteome.0c00856DOI Listing
December 2020

Revelation of Proteomic Indicators for Colorectal Cancer in Initial Stages of Development.

Molecules 2020 Jan 31;25(3). Epub 2020 Jan 31.

V.N. Orekhovich Institute of Biomedical Chemistry, 119121 Moscow, Russia.

Colorectal cancer (CRC) at a current clinical level is still hardly diagnosed, especially with regard to nascent tumors, which are typically asymptotic. Searching for reliable biomarkers of early diagnosis is an extremely essential task. Identification of specific post-translational modifications (PTM) may also significantly improve net benefits and tailor the process of CRC recognition. We examined depleted plasma samples obtained from 41 healthy volunteers and 28 patients with CRC at different stages to conduct comparative proteome-scaled analysis. The main goal of the study was to establish a constellation of protein markers in combination with their PTMs and semi-quantitative ratios that may support and realize the distinction of CRC until the disease has a poor clinical manifestation. Proteomic analysis revealed 119 and 166 proteins for patients in stages I-II and III-IV, correspondingly. Plenty of proteins (44 proteins) reflected conditions of the immune response, lipid metabolism, and response to stress, but only a small portion of them were significant ( < 0.01) for distinguishing stages I-II of CRC. Among them, some cytokines (Clusterin (CLU), C4b-binding protein (C4BP), and CD59 glycoprotein (CD59), etc.) were the most prominent and the lectin pathway was specifically enhanced in patients with CRC. Significant alterations in Inter-alpha-trypsin inhibitor heavy chains (ITIH1, ITIH2, ITIH3, and ITIH4) levels were also observed due to their implication in tumor growth and the malignancy process. Other markers (Alpha-1-acid glycoprotein 2 (ORM2), Alpha-1B-glycoprotein (A1BG), Haptoglobin (HP), and Leucine-rich alpha-2-glycoprotein (LRG1), etc.) were found to create an ambiguous core involved in cancer development but also to exactly promote tumor progression in the early stages. Additionally, we identified post-translational modifications, which according to the literature are associated with the development of colorectal cancer, including kininogen 1 protein (T327-p), alpha-2-HS-glycoprotein (S138-p) and newly identified PTMs, i.e., vitamin D-binding protein (K75-ac and K370-ac) and plasma protease C1 inhibitor (Y294-p), which may also contribute and negatively impact on CRC progression. The contribution of cytokines and proteins of the extracellular matrix is the most significant factor in CRC development in the early stages. This can be concluded since tumor growth is tightly associated with chronic aseptic inflammation and concatenated malignancy related to loss of extracellular matrix stability. Due attention should be paid to Apolipoprotein E (APOE), Apolipoprotein C1 (APOC1), and Apolipoprotein B-100 (APOB) because of their impact on the malfunction of DNA repair and their capability to regulate mTOR and PI3K pathways. The contribution of the observed PTMs is still equivocal, but a significant decrease in the likelihood between modified and native proteins was not detected confidently.
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http://dx.doi.org/10.3390/molecules25030619DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036866PMC
January 2020

The "Missing" Proteome: Undetected Proteins, Not-Translated Transcripts, and Untranscribed Genes.

J Proteome Res 2019 12 18;18(12):4273-4276. Epub 2019 Oct 18.

Institute of Biomedical Chemistry , 119121 Moscow , Russia.

The Chromosome-centric Human Proteome Project aims at characterizing the expression of proteins encoded in each chromosome at the tissue, cell, and subcellular levels. The proteomic profiling of a particular tissue or cell line commonly results in a substantial portion of proteins that are not observed (the "missing" proteome). The concurrent transcriptome profiling of the analyzed tissue/cells samples may help define the set of untranscribed genes in a given type of tissue or cell, thus narrowing the size of the "missing" proteome and allowing us to focus on defining the reasons behind undetected proteins, namely, whether they are technical (insufficient sensitivity of protein detection) or biological (correspond to not-translated transcripts). We believe that the quantitative polymerase chain reaction (qPCR) can provide an efficient approach to studying low-abundant transcripts related to undetected proteins due to its high sensitivity and the possibility of ensuring the specificity of detection via the simple Sanger sequencing of PCR products. Here we illustrated the feasibility of such an approach on a set of low-abundant transcripts. Although inapplicable to the analysis of whole transcriptome, qPCR can successfully be utilized to profile a limited cohort of transcripts encoded on a particular chromosome, as we previously demonstrated for human chromosome 18.
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http://dx.doi.org/10.1021/acs.jproteome.9b00383DOI Listing
December 2019

Challenges of the Human Proteome Project: 10-Year Experience of the Russian Consortium.

J Proteome Res 2019 12 28;18(12):4206-4214. Epub 2019 Oct 28.

Institute of Biomedical Chemistry , Moscow 119435 , Russia.

This manuscript collects all the efforts of the Russian Consortium, bottlenecks revealed in the course of the C-HPP realization, and ways of their overcoming. One of the main bottlenecks in the C-HPP is the insufficient sensitivity of proteomic technologies, hampering the detection of low- and ultralow-copy number proteins forming the "dark part" of the human proteome. In the frame of MP-Challenge, to increase proteome coverage we suggest an experimental workflow based on a combination of shotgun technology and selected reaction monitoring with two-dimensional alkaline fractionation. Further, to detect proteins that cannot be identified by such technologies, nanotechnologies such as combined atomic force microscopy with molecular fishing and/or nanowire detection may be useful. These technologies provide a powerful tool for single molecule analysis, by analogy with nanopore sequencing during genome analysis. To systematically analyze the functional features of some proteins (CP50 Challenge), we created a mathematical model that predicts the number of proteins differing in amino acid sequence: proteoforms. According to our data, we should expect about 100 000 different proteoforms in the liver tissue and a little more in the HepG2 cell line. The variety of proteins forming the whole human proteome significantly exceeds these results due to post-translational modifications (PTMs). As PTMs determine the functional specificity of the protein, we propose using a combination of gene-centric transcriptome-proteomic analysis with preliminary fractionation by two-dimensional electrophoresis to identify chemically modified proteoforms. Despite the complexity of the proposed solutions, such integrative approaches could be fruitful for MP50 and CP50 Challenges in the framework of the C-HPP.
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http://dx.doi.org/10.1021/acs.jproteome.9b00358DOI Listing
December 2019

Metabolomic diagnostics and human digital image.

Per Med 2019 03 15;16(2):133-144. Epub 2019 Feb 15.

Department of Proteomics & Mass Spectrometry, Institute of Biomedical Chemistry, Pogodinskaya st 10, 119121, Moscow, Russia.

The existing clinical laboratory practice has limitations in terms of specificity and sensitivity of diagnosis, making the introduction of new methods in medicine more topical. Application of 'omics' technologies, especially metabolomics, allows overcoming these limitations. The composition of blood metabolites reflects the physical state of an organism at the molecular level. The analysis of blood metabolome can serve as effective means of diagnosis, implementation of which in healthcare is timely and relevant. This paper demonstrates the versatility of metabolomic diagnostics, its applicability to various diseases. We discussed the standard of human digital image, which includes the metabolomic data sufficient to make an accurate assessment of general health and carry out precision diagnostics of a wide range of diseases.
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http://dx.doi.org/10.2217/pme-2018-0066DOI Listing
March 2019

200+ Protein Concentrations in Healthy Human Blood Plasma: Targeted Quantitative SRM SIS Screening of Chromosomes 18, 13, Y, and the Mitochondrial Chromosome Encoded Proteome.

J Proteome Res 2019 01 11;18(1):120-129. Epub 2018 Dec 11.

Institute of Biomedical Chemistry , Moscow 119435 , Russia.

This work continues the series of the quantitative measurements of the proteins encoded by different chromosomes in the blood plasma of a healthy person. Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards (SRM SIS) and a gene-centric approach, which is the basis for the implementation of the international Chromosome-centric Human Proteome Project (C-HPP), were applied for the quantitative measurement of proteins in human blood plasma. Analyses were carried out in the frame of C-HPP for each protein-coding gene of the four human chromosomes: 18, 13, Y, and mitochondrial. Concentrations of proteins encoded by 667 genes were measured in 54 blood plasma samples of the volunteers, whose health conditions were consistent with requirements for astronauts. The gene list included 276, 329, 47, and 15 genes of chromosomes 18, 13, Y, and the mitochondrial chromosome, respectively. This paper does not make claims about the detection of missing proteins. Only 205 proteins (30.7%) were detected in the samples. Of them, 84, 106, 10, and 5 belonged to chromosomes 18, 13, and Y and the mitochondrial chromosome, respectively. Each detected protein was found in at least one of the samples analyzed. The SRM SIS raw data are available in the ProteomeXchange repository (PXD004374, PASS01192).
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http://dx.doi.org/10.1021/acs.jproteome.8b00391DOI Listing
January 2019

Increased Sensitivity of Mass Spectrometry by Alkaline Two-Dimensional Liquid Chromatography: Deep Cover of the Human Proteome in Gene-Centric Mode.

J Proteome Res 2018 12 19;17(12):4258-4266. Epub 2018 Nov 19.

Institute of Biomedical Chemistry, RAS , Moscow , Russia.

Currently, great interest is paid to the identification of "missing" proteins that have not been detected in any biological material at the protein level (PE1). In this paper, using the Universal Proteomic Standard sets 1 and 2 (UPS1 and UPS2, respectively) as an example, we characterized mass spectrometric approaches from the point of view of sensitivity (Sn), specificity (Sp), and accuracy (Ac). The aim of the paper was to show the utility of a mass spectra approach for protein detection. This sets consists of 48 high-purity human proteins without single aminoacid polymorphism (SAP) or post translational modification (PTM). The UPS1 set consists of the same 48 proteins at 5 pmols each, and in UPS2, proteins were grouped into 5 groups in accordance with their molar concentration, ranging from 10 to 10 M. Single peptides from the 92% and 96% of all sets of proteins could be detected in a pure solution of UPS2 and UPS1, respectively, by selected reaction monitoring with stable isotope-labeled standards (SRM-SIS). We also found that, in the presence of a biological matrix such as Escherichia coli extract or human blood plasma (HBP), SRM-SIS makes it possible to detect from 63% to 79% of proteins in the UPS2 set (sensitivity) with the highest specificity (∼100%) and an accuracy of 80% by increasing the sensitivity of shotgun and selected reaction monitoring combined with a stable-isotope-labeled peptide standard (SRM-SIS technology) by fractionating samples using reverse-phase liquid chromatography under alkaline conditions (2D-LC_alk). It is shown that this technique of sample fractionation allows the SRM-SIS to detect 98% of the single peptides from the proteins present in the pure solution of UPS2 (47 out of 48 proteins). When the extracts of E. coli or Pichia pastoris are added as biological matrixes to the UPS2, 46, and 45 out of 48 proteins (∼95%) can be detected, respectively, using the SRM-SIS combined with 2D-LC_alk. The combination of the 2D-LC_alk SRM-SIS and shotgun technologies allows us to increase the sensitivity up to 100% in the case of the proteins of the UPS2 set. The usage of that technology can be a solution for identifying the so-called "missing" proteins and, eventually, creating the deep proteome of a particular chromosome of tissue or organs. Experimental data have been deposited in the PeptideAtlas SRM Experiment Library with the dataset identifier PASS01192 and the PRIDE repository with the dataset identifier PXD007643.
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http://dx.doi.org/10.1021/acs.jproteome.8b00754DOI Listing
December 2018

The Gene-Centric Content Management System and Its Application for Cognitive Proteomics.

Proteomes 2018 Feb 23;6(1). Epub 2018 Feb 23.

Orekhovich Institute of Biomedical Chemistry, Moscow 119191, Russia.

The Human Proteome Project is moving into the next phase of creating and/or reconsidering the functional annotations of proteins using the chromosome-centric paradigm. This challenge cannot be solved exclusively using automated means, but rather requires human intelligence for interpreting the combined data. To foster the integration between human cognition and post-genome array a number of specific tools were recently developed, among them CAPER, GenomewidePDB, and The Proteome Browser (TPB). For the purpose of tackling the task of protein functional annotating the Gene-Centric Content Management System (GenoCMS) was expanded with new features. The goal was to enable bioinformaticans to develop self-made applications and to position these applets within the generalized informational canvas supported by GenoCMS. We report the results of GenoCMS-enabled integration of the concordant informational flows in the chromosome-centric framework of the human chromosome 18 project. The workflow described in the article can be scaled to other human chromosomes, and also supplemented with new tracks created by the user. The GenoCMS is an example of a project-oriented informational system, which are important for public data sharing.
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http://dx.doi.org/10.3390/proteomes6010012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874771PMC
February 2018

Quantitative assessment of betamethasone dual-acting formulation in urine of patients with rheumatoid arthritis and ankylosing spondylitis after single-dose intramuscular administration and its application to long-term pharmacokinetic study.

J Pharm Biomed Anal 2018 Feb 6;149:278-289. Epub 2017 Nov 6.

V. N. Orekhovich Research Institute of Biomedical Chemistry, 10 Pogodinskaya str. bld. 8, 119121 Moscow, Russian Federation.

Quantitative evaluation and assessment of pharmacokinetic parameters of Diprospan (suspension for injection 7mg/mL (2mg+5mg/mL) of betamethasone) were performed in urine samples taken from patients with rheumatoid arthritis or ankylosing spondylitis for 28days after systemic intramuscular administration in routine clinical practice in an open-comparative prospective cohort study. The maximum betamethasone concentration was reached at day 4 of the follow-up; in some cases, β-phase of elimination of the drug was appeared at day 14 or at day 21 of the follow-up. The deferred β-phase elimination was likely a consequence of the physiological characteristics of the patients or of the influence of non-steroidal agents. The half-life of betamethasone was 8.5days. The elimination rate constant was 2.49h-1; the mean clearance was 4.72L/d. The recommended frequency of the drug administration to its complete elimination was estimated up to 48days. Mann-Whitney test showed no significant differences in pharmacokinetic characteristics between male and female subjects. The prolonged elimination phase was observed in patients with deviations in their body mass index, continual treatment by diclofenac and nimesulide or, possibly, after consuming an alcohol. The study was recorded in Clinical Trials open source with identifier NCT03119454.
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http://dx.doi.org/10.1016/j.jpba.2017.11.021DOI Listing
February 2018

Why Are the Correlations between mRNA and Protein Levels so Low among the 275 Predicted Protein-Coding Genes on Human Chromosome 18?

J Proteome Res 2017 12 27;16(12):4311-4318. Epub 2017 Oct 27.

Institute of Biomedical Chemistry RAS , 119121 Moscow, Russia.

In this work targeted (selected reaction monitoring, SRM, PASSEL: PASS00697) and panoramic (shotgun LC-MS/MS, PRIDE: PXD00244) mass-spectrometric methods as well as transcriptomic analysis of the same samples using RNA-Seq and PCR methods (SRA experiment IDs: SRX341198, SRX267708, SRX395473, SRX390071) were applied for quantification of chromosome 18 encoded transcripts and proteins in human liver and HepG2 cells. The obtained data was used for the estimation of quantitative mRNA-protein ratios for the 275 genes of the selected chromosome in the selected tissues. The impact of methodological limitations of existing analytical proteomic methods on gene-specific mRNA-protein ratios and possible ways of overcoming these limitations for detection of missing proteins are also discussed.
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http://dx.doi.org/10.1021/acs.jproteome.7b00348DOI Listing
December 2017

Post-translational modifications of FDA-approved plasma biomarkers in glioblastoma samples.

PLoS One 2017 11;12(5):e0177427. Epub 2017 May 11.

V.-N. Orekhovich Research Institute of Biomedical Chemistry, Moscow, Russia.

Liquid chromatography-tandem mass spectrometry was used to analyze plasma proteins of volunteers (control) and patients with glioblastoma multiform (GBM). A database search was pre-set with a variable post-translational modification (PTM): phosphorylation, acetylation or ubiquitination. There were no significant differences between the control and the GBM groups regarding the number of protein identifications, sequence coverage or number of PTMs. However, in GBM plasma, we unambiguously observed a decreased fraction in post-translationally modified peptides identified with high quality. The disease-specific PTM patterns were extracted and mapped to the set of FDA-approved plasma protein markers. Decreases of 46% and 24% in the number of acetylated and ubiquitinated peptides, respectively, were observed in the GBM samples. Significance of capturing disease-associated patterns of protein modifications was envisaged.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177427PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5426747PMC
September 2017

State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells.

J Proteome Res 2016 11 29;15(11):4030-4038. Epub 2016 Aug 29.

Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia.

A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC-MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC-MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (R ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015-2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126 .
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http://dx.doi.org/10.1021/acs.jproteome.6b00380DOI Listing
November 2016

Targeted Quantitative Screening of Chromosome 18 Encoded Proteome in Plasma Samples of Astronaut Candidates.

J Proteome Res 2016 11 22;15(11):4039-4046. Epub 2016 Aug 22.

Institute of Biomedical Chemistry , 119121, Moscow, Russia.

This work was aimed at estimating the concentrations of proteins encoded by human chromosome 18 (Chr 18) in plasma samples of 54 healthy male volunteers (aged 20-47). These young persons have been certified by the medical evaluation board as healthy subjects ready for space flight training. Over 260 stable isotope-labeled peptide standards (SIS) were synthesized to perform the measurements of proteins encoded by Chr 18. Selected reaction monitoring (SRM) with SIS allowed an estimate of the levels of 84 of 276 proteins encoded by Chr 18. These proteins were quantified in whole and depleted plasma samples. Concentration of the proteins detected varied from 10 M (transthyretin, P02766) to 10 M (P4-ATPase, O43861). A minor part of the proteins (mostly representing intracellular proteins) was characterized by extremely high inter individual variations. The results provide a background for studies of a potential biomarker in plasma among proteins encoded by Chr 18. The SRM raw data are available in ProteomeXchange repository (PXD004374).
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http://dx.doi.org/10.1021/acs.jproteome.6b00384DOI Listing
November 2016

The Size of the Human Proteome: The Width and Depth.

Int J Anal Chem 2016 19;2016:7436849. Epub 2016 May 19.

Institute of Biomedical Chemistry, Moscow 119121, Russia.

This work discusses bioinformatics and experimental approaches to explore the human proteome, a constellation of proteins expressed in different tissues and organs. As the human proteome is not a static entity, it seems necessary to estimate the number of different protein species (proteoforms) and measure the number of copies of the same protein in a specific tissue. Here, meta-analysis of neXtProt knowledge base is proposed for theoretical prediction of the number of different proteoforms that arise from alternative splicing (AS), single amino acid polymorphisms (SAPs), and posttranslational modifications (PTMs). Three possible cases are considered: (1) PTMs and SAPs appear exclusively in the canonical sequences of proteins, but not in splice variants; (2) PTMs and SAPs can occur in both proteins encoded by canonical sequences and in splice variants; (3) all modification types (AS, SAP, and PTM) occur as independent events. Experimental validation of proteoforms is limited by the analytical sensitivity of proteomic technology. A bell-shaped distribution histogram was generated for proteins encoded by a single chromosome, with the estimation of copy numbers in plasma, liver, and HepG2 cell line. The proposed metabioinformatics approaches can be used for estimation of the number of different proteoforms for any group of protein-coding genes.
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http://dx.doi.org/10.1155/2016/7436849DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4889822PMC
June 2016

Plasma preparation to measure FDA-approved protein markers by selected reaction monitoring.

Clin Transl Med 2015 Dec 15;4(1):32. Epub 2015 Oct 15.

Orekhovich Institute of Biomedical Chemistry, Pogodinskaya str. 10/8, 119121, Moscow, Russia.

Background: The development of commercially available panels for human blood plasma screening via selected reaction monitoring (SRM) offers reliable, cost-efficient and highly-standardized discovery and validation of protein biomarkers. However, protein detection by SRM can be hampered by interfering peptide fragment ions. To estimate the influence of interference on protein detection, we performed different types of sample preparation and implemented SRM measurements for well-characterized protein targets approved by the US Food and Drug Administration.

Methods: We used the PlasmaDeepDive™ SRM assay from BiognoSYS AG for absolute quantification of 18 proteins in 19 samples of human plasma using three different protocols for sample preparation. SRM measurements were performed using iRT standards for retention time normalization and isotopically-labeled reference peptides for absolute quantification. SpectroDive™ software was used for automated detection of reliable peak groups.

Results: Fourteen targeted proteins were quantitatively measured in more than half of the samples. Depletion of highly-abundant plasma proteins and peptide fraction clean-up on centrifuge plates resulted in detection of all 18 targeted proteins in femtomolar to picomolar concentrations.

Conclusions: It was shown that commercially designed SRM kits are suitable for SRM detection of well-established plasma/serum biomarkers.
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http://dx.doi.org/10.1186/s40169-015-0071-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607682PMC
December 2015

Combination of virtual and experimental 2DE together with ESI LC-MS/MS gives a clearer view about proteomes of human cells and plasma.

Electrophoresis 2016 Jan 6;37(2):302-9. Epub 2015 Nov 6.

Orekhovich Institute of Biomedical Chemistry of Russian Academy of Medical Sciences, Moscow, Russia.

Virtual and experimental 2DE coupled with ESI LC-MS/MS was introduced to obtain better representation of the information about human proteome. The proteins from HEPG2 cells and human blood plasma were run by 2DE. After staining and protein spot identification by MALDI-TOF MS, the protein maps were generated. The experimental physicochemical parameters (pI/Mw) of the proteoforms further detected by ESI LC-MS/MS in these spots were obtained. Next, the theoretical pI and Mw of identified proteins were calculated using program Compute pI/Mw (http://web.expasy.org/compute_pi/pi_tool-doc.html). Accordingly, the relationship between theoretical and experimental parameters was analyzed, and the correlation plots were built. Additionally, virtual/experimental information about different protein species/proteoforms from the same genes was extracted. As it was revealed from the plots, the major proteoforms detected in HepG2 cell line have pI/Mw parameters similar to theoretical values. In opposite, the minor protein species have mainly very different from theoretical pI and Mw parameters. A similar situation was observed in plasma in much higher degree. It means that minor protein species are heavily modified in cell and even more in plasma proteome.
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http://dx.doi.org/10.1002/elps.201500382DOI Listing
January 2016

One-dimensional proteomic profiling of Danio rerio embryo vitellogenin to estimate quantum dot toxicity.

Proteome Sci 2015 2;13:17. Epub 2015 May 2.

Orekhovich Institute of Biomedical Chemistry, 119121, Pogodinskaya St. 10, Moscow, Russia.

Background: Vitellogenin (Vtg) is the major egg yolk protein (YP) in most oviparous species and may be useful as an indicator in ecotoxicological testing at the biochemical level. In this study, we obtained detailed information about the Vtgs of Danio rerio embryos by cutting SDS-PAGE gel lanes into thin slices, and analyzing them slice-by-slice with (MALDI-TOF) mass spectrometry.

Results: We conducted three proteomic analyses, comparing embryonic Danio rerio Vtg cleavage products after exposure for 48 h to CdSecore/ZnSshell quantum dots (QDs), after exposure to a mixture of the components used for quantum dot synthesis (MCS-QDs), and in untreated embryos. The Vtg mass spectrometric profiles of the QDs-treated embryos differed from those of the unexposed or MCS-QDs-treated embryos.

Conclusion: This study demonstrates the possible utility of Vtg profiling in D. rerio embryos as a sensitive diagnostic tool to estimate nanoparticle toxicity.
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http://dx.doi.org/10.1186/s12953-015-0072-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4426544PMC
May 2015

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

J Proteome Res 2014 Dec 21;13(12):5551-60. Epub 2014 Oct 21.

Orekhovich Institute of Biomedical Chemistry , 119121, Moscow, Russia.

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.
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http://dx.doi.org/10.1021/pr500531xDOI Listing
December 2014

Applying of hierarchical clustering to analysis of protein patterns in the human cancer-associated liver.

PLoS One 2014 1;9(8):e103950. Epub 2014 Aug 1.

V. N. Orekhovich Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, Russia; Postgen Tech LLC, Moscow, Russia.

Background: There are two ways that statistical methods can learn from biomedical data. One way is to learn classifiers to identify diseases and to predict outcomes using the training dataset with established diagnosis for each sample. When the training dataset is not available the task can be to mine for presence of meaningful groups (clusters) of samples and to explore underlying data structure (unsupervised learning).

Results: We investigated the proteomic profiles of the cytosolic fraction of human liver samples using two-dimensional electrophoresis (2DE). Samples were resected upon surgical treatment of hepatic metastases in colorectal cancer. Unsupervised hierarchical clustering of 2DE gel images (n = 18) revealed a pair of clusters, containing 11 and 7 samples. Previously we used the same specimens to measure biochemical profiles based on cytochrome P450-dependent enzymatic activities and also found that samples were clearly divided into two well-separated groups by cluster analysis. It turned out that groups by enzyme activity almost perfectly match to the groups identified from proteomic data. Of the 271 reproducible spots on our 2DE gels, we selected 15 to distinguish the human liver cytosolic clusters. Using MALDI-TOF peptide mass fingerprinting, we identified 12 proteins for the selected spots, including known cancer-associated species.

Conclusions/significance: Our results highlight the importance of hierarchical cluster analysis of proteomic data, and showed concordance between results of biochemical and proteomic approaches. Grouping of the human liver samples and/or patients into differing clusters may provide insights into possible molecular mechanism of drug metabolism and creates a rationale for personalized treatment.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0103950PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118999PMC
November 2015

Chromosome 18 transcriptoproteome of liver tissue and HepG2 cells and targeted proteome mapping in depleted plasma: update 2013.

J Proteome Res 2014 Jan 13;13(1):183-90. Epub 2013 Dec 13.

Orekhovich Institute of Biomedical Chemistry of the Russian Academy of Medical Sciences , 10 Pogodinskaya Street, Moscow 119121, Russia.

We report the results obtained in 2012-2013 by the Russian Consortium for the Chromosome-centric Human Proteome Project (C-HPP). The main scope of this work was the transcriptome profiling of genes on human chromosome 18 (Chr 18), as well as their encoded proteome, from three types of biomaterials: liver tissue, the hepatocellular carcinoma-derived cell line HepG2, and blood plasma. The transcriptome profiling for liver tissue was independently performed using two RNaseq platforms (SOLiD and Illumina) and also by droplet digital PCR (ddPCR) and quantitative RT-PCR. The proteome profiling of Chr 18 was accomplished by quantitatively measuring protein copy numbers in the three types of biomaterial (the lowest protein concentration measured was 10(-13) M) using selected reaction monitoring (SRM). In total, protein copy numbers were estimated for 228 master proteins, including quantitative data on 164 proteins in plasma, 171 in the HepG2 cell line, and 186 in liver tissue. Most proteins were present in plasma at 10(8) copies/μL, while the median abundance was 10(4) and 10(5) protein copies per cell in HepG2 cells and liver tissue, respectively. In summary, for liver tissue and HepG2 cells a "transcriptoproteome" was produced that reflects the relationship between transcript and protein copy numbers of the genes on Chr 18. The quantitative data acquired by RNaseq, PCR, and SRM were uploaded into the "Update_2013" data set of our knowledgebase (www.kb18.ru) and investigated for linear correlations.
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http://dx.doi.org/10.1021/pr400883xDOI Listing
January 2014

Tissue-specific alternative splicing analysis reveals the diversity of chromosome 18 transcriptome.

J Proteome Res 2014 Jan 9;13(1):173-82. Epub 2013 Dec 9.

I. I. Mechnikov Institute of Vaccines and Sera of the Russian Academy of Medical Sciences , 5A, Maly Kazenny per., 105064 Moscow, Russia.

The Chromosome-centric Human Proteome Project (C-HPP) is aimed to identify the variety of protein products and transcripts of the number of chromosomes. The Russian part of C-HPP is devoted to the study of the human chromosome 18. Using widely accepted Tophat and SpliceGrapher, a tool for accurate splice sites and alternative mRNA isoforms prediction, we performed the extensive mining of the splice variants of chromosome 18 transcripts and encoded protein products in liver, brain, lung, kidney, blood, testis, derma, and skeletal muscles. About 6.1 billion of the reads represented by 450 billion of the bases have been analyzed. The relative frequencies of splice events as well as gene expression profiles in normal tissues are evaluated. Using ExPASy PROSITE, the novel features and possible functional sites of previously unknown splice variants were highlighted. A set of unique proteotypic peptides enabling the identification of novel alternative protein species using mass-spectrometry is constructed. The revealed data will be integrated into the gene-centric knowledgebase of the Russian part of C-HPP available at http://kb18.ru and http://www.splicing.zz.mu/.
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http://dx.doi.org/10.1021/pr400808uDOI Listing
January 2014

2DE-based approach for estimation of number of protein species in a cell.

Electrophoresis 2014 Mar 23;35(6):895-900. Epub 2013 Dec 23.

Department of Proteomic Research and Mass Spectrometry, V.N. Orekhovich, Institute of Biomedical Chemistry, Moscow, Russia; Department of Molecular and Radiation Biophysics, B.P. Konstantinov, Petersburg Nuclear Physics Institute, Gatchina, Leningrad District, Russia.

Insufficient sensitivity of methods for detection of proteins at a single molecule level does not yet allow obtaining the whole image of human proteome. But to go further, we need at least to know the proteome size, or how many different protein species compose this proteome. This is the task that could be at least partially realized by the method described in this article. The approach used in our study is based on detection of protein spots in 2DE after staining by protein dyes with various sensitivities. As the different protein spots contain different protein species, counting the spots opens a way for estimation of number of protein species. The function representing the dependence of the number of protein spots on sensitivity or LOD of protein dyes was generated. And extrapolation of this function curve to theoretical point of the maximum sensitivity (detection of a single smallest polypeptide) allowed to counting the number of different molecules (polypeptide species) at the concentration level of a single polypeptide per proteome. Using this approach, it was estimated that the minimal numbers of protein species for model objects, Escherichia coli and Pirococcus furiosus, are 6200 and 3400, respectively. We expect a single human cell (HepG2) to contain minimum 70 000 protein species.
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http://dx.doi.org/10.1002/elps.201300525DOI Listing
March 2014

Gene-centric content management system.

Biochim Biophys Acta 2014 Jan 27;1844(1 Pt A):77-81. Epub 2013 Aug 27.

Orekhovich Institute of Biomedical Chemistry of the Russian Academy of Medical Sciences (RAMS), Russia. Electronic address:

The Human Proteome Project (HPP) was started two years ago and the international consortia have elaborated a number of informational resources to harbor the HPP data. Selected informational resources are currently used to elaborate the HPP baseline metrics, which were introduced to estimate future contribution of HPP to the knowledge domain. We developed a Web-based tool Gene-centric Content Management System (GenoCMS) for comparing public resources to proprietary results by using the representation of proteins as color-coded catalog. Within our CMS, the features of protein-coding genes are uploaded from the public domain and then appended by additional features derived from original experimental workflows. We describe the heat-map/traffic light representation of our proteomic experiments as the background of data taken from NeXtProt, MS/MS repositories, the Human Protein Atlas and the RNAseqAtlas. The system presented at www.kb18.ru comprises a collaborative knowledge base for annotating the gene sets and disseminating these annotations through the Web. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.
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http://dx.doi.org/10.1016/j.bbapap.2013.08.006DOI Listing
January 2014

Highly sensitive detection of human cardiac myoglobin using a reverse sandwich immunoassay with a gold nanoparticle-enhanced surface plasmon resonance biosensor.

Anal Chim Acta 2013 Jan 12;759:105-9. Epub 2012 Nov 12.

IBMC RAMS, Pogodinskaya Street, 10, 119121 Moscow, Russian Federation.

A highly sensitive reverse sandwich immunoassay for the detection of human cardiac myoglobin (cMb) in serum was designed utilizing a gold nanoparticle (AuNP)-enhanced surface plasmon resonance (SPR) biosensor. First, a monoclonal anti-cMb antibody (Mab1) was covalently immobilized on the sensor surface. AuNPs were covalently conjugated to the second monoclonal anti-cMb antibody (Mab2) to form an immuno-gold reagent (Mab2-AuNP). The reverse sandwich immunoassay consists of two steps: (1) mixing the serum sample with Mab2-AuNP and incubation for the formation of cMb/Mab2-AuNP complexes and (2) sample injection over the sensor surface and evaluation of the Mab1/cMb/Mab2-AuNP complex formation, with the subsequent calculation of the cMb concentration in the serum. The biosensor signal was amplified approximately 30-fold compared with the direct reaction of cMb with Mab1 on the sensor surface. The limit of detection of cMb in a human blood serum sample was found to be as low as 10 pM (approx. 0.18 ng mL(-1)), and the inter-assay coefficient of variation was less than 3%. Thus, the developed SPR-based reverse sandwich immunoassay has a sensitivity that is sufficient to measure cMb across a wide range of normal and pathological concentrations, allowing an adequate estimation of the disease severity and the monitoring of treatment.
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http://dx.doi.org/10.1016/j.aca.2012.10.053DOI Listing
January 2013

Chromosome 18 transcriptome profiling and targeted proteome mapping in depleted plasma, liver tissue and HepG2 cells.

J Proteome Res 2013 Jan 20;12(1):123-34. Epub 2012 Dec 20.

Orekhovich Institute of Biomedical Chemistry of the Russian Academy of Medical Sciences, Russia.

The final goal of the Russian part of the Chromosome-centric Human Proteome Project (C-HPP) was established as the analysis of the chromosome 18 (Chr 18) protein complement in plasma, liver tissue and HepG2 cells with the sensitivity of 10(-18) M. Using SRM, we have recently targeted 277 Chr 18 proteins in plasma, liver, and HepG2 cells. On the basis of the results of the survey, the SRM assays were drafted for 250 proteins: 41 proteins were found only in the liver tissue, 82 proteins were specifically detected in depleted plasma, and 127 proteins were mapped in both samples. The targeted analysis of HepG2 cells was carried out for 49 proteins; 41 of them were successfully registered using ordinary SRM and 5 additional proteins were registered using a combination of irreversible binding of proteins on CN-Br Sepharose 4B with SRM. Transcriptome profiling of HepG2 cells performed by RNAseq and RT-PCR has shown a significant correlation (r = 0.78) for 42 gene transcripts. A pilot affinity-based interactome analysis was performed for cytochrome b5 using analytical and preparative optical biosensor fishing followed by MS analysis of the fished proteins. All of the data on the proteome complement of the Chr 18 have been integrated into our gene-centric knowledgebase ( www.kb18.ru ).
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http://dx.doi.org/10.1021/pr300821nDOI Listing
January 2013

Producing a one-dimensional proteomic map for human liver cytochromes p450.

Methods Mol Biol 2012 ;909:63-82

Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, Russia.

In this chapter we explore the inducible cytochrome P450 (CYP) forms as an example of membrane proteins analysis that relies on sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) fractionation with subsequent mass spectrometric (MS) identification. The approach involves cutting an SDS-PAGE gel lane into thin slices and identifying proteins in each slice by MS with the aim of obtaining detailed information on proteins of interest. A one-dimensional proteomic map showing the distribution of selected CYP isoforms across 40 slices was constructed using mass spectra obtained from each slice. Our protocol proved to be efficient enough to obtain a comprehensive profile of drug-metabolizing enzymes in the human liver. In addition to human tissues, the approach described should be applicable to the characterization of membrane proteins in other eukaryotic species.
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http://dx.doi.org/10.1007/978-1-61779-959-4_5DOI Listing
December 2012

Computational approach to characterization of human liver drug-metabolizing enzymes.

Eur J Pharm Sci 2010 Oct 3;41(2):305-11. Epub 2010 Jul 3.

V.N. Orekhovich Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Pogodinskaya St., Moscow, Russia.

Cytochromes P450 are the key enzymes for activating and inactivating many drugs; individual expression levels of CYPs may play a crucial role in drug safety and drug efficacy. Statistical comparison of biochemical profiles of 23 human liver microsomes have been used to characterize human liver samples. The profile included 12 parameters, namely activity of NADPH-cytochrome P450 reductase, cytochrome P450 content and cytochrome P450-dependent monooxygenase activities with marker substrates. Unsupervised statistical methods including cluster analysis and principal component analysis revealed with very high confidence the presence of two groups. Difference between the groups was explained by peculiarities of reductase activity and cytochrome P450 enzyme activities with 7-ethoxyresorufin, 7-methoxyresorufin, 7-methoxycoumarin, 7-benzyloxyresorufin and 7-benzyloxyquinoline. Results of biochemical assays coupled with multidimensional data analysis can be further used for targeted proteomic profiling of microsome oxidation mechanisms.
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http://dx.doi.org/10.1016/j.ejps.2010.06.014DOI Listing
October 2010

Application of slicing of one-dimensional gels with subsequent slice-by-slice mass spectrometry for the proteomic profiling of human liver cytochromes P450.

J Proteome Res 2010 Jan;9(1):95-103

Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, Russia.

Sequential thin slicing of one-dimensional electrophoresis gels followed by slice-by-slice mass spectrometry to allow protein identification was used to produce a proteomic map for cytochromes P450. Parallel MALDI-TOF-MS and LC-MS/MS analyses were performed. Combination of the two MS methods increased the quality of protein identification. We have proposed an efficient approach to obtain a comprehensive profile of drug-metabolizing enzymes in the liver that can be used to differentiate between polymorphic variants of cytochromes P450.
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http://dx.doi.org/10.1021/pr900262zDOI Listing
January 2010

Protein-protein interactions as new targets for drug design: virtual and experimental approaches.

J Bioinform Comput Biol 2007 Apr;5(2B):579-92

V.N.Orechovich Institute of Biomedical Chemistry RAMS, Pogodinskaya str. 10, Moscow, 119121, Russia.

Protein-protein and protein-ligand interactions play a central role in biochemical reactions, and understanding these processes is an important task in different fields of biomedical science and drug discovery. Proteins often work in complex assemblies of several macromolecules and small ligands. The structural and functional description of protein-protein interactions (PPI) is very important for basic-, as well as applied research. The interface areas of protein complexes have unique structure and properties, so PPI represent prospective targets for a new generation of drugs. One of the key targets of PPI inhibitors are oligomeric enzymes. This report shows interactive links between virtual and experimental approaches in a total pipeline "from gene to drug" and using Surface Plasmon Resonance technology for experimentally assessing PPI. Our research is conducted on two oligomeric enzymes -- HIV-1 protease (HIVp) (homo-dimer) and bacterial L-asparaginase (homo-tetramer). Using methods of molecular modeling and computational alanine scanning we obtained structural and functional description of PPI in these two enzymes. We also presented a real example of application of integral approach in searching inhibitors of HIVp dimerization -- from virtual database mining up to experimental testing of lead compounds.
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http://dx.doi.org/10.1142/s0219720007002825DOI Listing
April 2007
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