30 results on '"Elena A. Ponomarenko"'
Search Results
2. Methods of Computational Interactomics for Investigating Interactions of Human Proteoforms
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Elena A. Ponomarenko, O. I. Kiseleva, Andrew Ivanov, and E. V. Poverennaya
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Proteomics ,Proteome ,Computer science ,Protein species ,Computational Biology ,Single gene ,General Medicine ,Computational biology ,Biochemistry ,Protein–protein interaction ,Machine Learning ,Data Mining ,Humans ,Human genome ,Protein Interaction Maps ,Databases, Protein ,Organism - Abstract
Human genome contains ca. 20,000 protein-coding genes that could be translated into millions of unique protein species (proteoforms). Proteoforms coded by a. single gene often have different functions, which implies different protein partners. By interacting with each other, proteoforms create a. network reflecting the dynamics of cellular processes in an organism. Perturbations of protein-protein interactions change the network topology, which often triggers pathological processes. Studying proteoforms is a. relatively new research area in proteomics, and this is why there are comparatively few experimental studies on the interaction of proteoforms. Bioinformatics tools can facilitate such studies by providing valuable complementary information to the experimental data and, in particular, expanding the possibilities of the studies of proteoform interactions.
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- 2020
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3. The 'Missing' Proteome: Undetected Proteins, Not-Translated Transcripts, and Untranscribed Genes
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Sergey P. Radko, Andrey Lisitsa, Alexander I. Archakov, Ekaterina V. Poverennaya, Elena A. Ponomarenko, and L. K. Kurbatov
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Proteomics ,0301 basic medicine ,Proteome ,Computational biology ,Biology ,Polymerase Chain Reaction ,Biochemistry ,Transcriptome ,03 medical and health sciences ,symbols.namesake ,Chromosome 18 ,Human proteome project ,Chromosomes, Human ,Humans ,Gene ,Sanger sequencing ,030102 biochemistry & molecular biology ,Proteomic Profiling ,Gene Expression Profiling ,Hep G2 Cells ,General Chemistry ,Gene expression profiling ,030104 developmental biology ,symbols ,Chromosomes, Human, Pair 18 - Abstract
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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- 2019
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4. Challenges of the Human Proteome Project: 10-Year Experience of the Russian Consortium
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Victor G. Zgoda, Andrey Lisitsa, Arthur T. Kopylov, Elena A. Ponomarenko, Sergey N. Mazurenko, Alexander A. Makarov, Mikhail A. Pyatnitskii, Ekaterina V. Ilgisonis, Renad Z. Sagdeev, A. L. Aseev, Anatoly I. Grigoriev, Victor A. Bykov, Ekaterina V. Poverennaya, Olga I. Kiseleva, Alexander I. Archakov, Konstantin G. Skryabin, Vadim M. Govorun, Tatiana O. Pleshakova, Yuri D. Ivanov, Stanislav N. Naryzhny, and Vadim T. Ivanov
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Proteomics ,0301 basic medicine ,Spectrometry, Mass, Electrospray Ionization ,Proteome ,Computer science ,Functional features ,Biosensing Techniques ,Computational biology ,Microscopy, Atomic Force ,Sensitivity and Specificity ,Biochemistry ,Genome ,Russia ,Workflow ,03 medical and health sciences ,Tandem Mass Spectrometry ,Human proteome project ,Humans ,Nanotechnology ,Electrophoresis, Gel, Two-Dimensional ,030102 biochemistry & molecular biology ,Genome, Human ,Atomic force microscopy ,Proteins ,General Chemistry ,030104 developmental biology ,Hepg2 cells ,Nanopore sequencing ,Protein Processing, Post-Translational - Abstract
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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- 2019
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5. Гены «стахановцы» 18 хромосомы человека, отсутствующие белки и не охарактеризованные белки в ткани печени и клеточной линии HepG2
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George S. Krasnov, Anastasia V. Tsvetkova, Sergey S. Markin, Y.Y. Kiseleva, A. V. Lisitsa, Ekaterina V. Ilgisonis, Victor G. Zgoda, K.G. Ptitsyn, Olga S. Timoshenko, Svetlana A. Khmeleva, Ekaterina V. Poverennaya, Alexander I. Archakov, K.A. Deinichenko, I.V. Buromski, Olga I. Kiseleva, I. V. Vakhrushev, Sergey P. Radko, Elena A. Ponomarenko, V.V. Shapovalova, L. K. Kurbatov, and Mikhail A. Pyatnitskiy
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0303 health sciences ,NeXtProt ,030302 biochemistry & molecular biology ,RNA-Seq ,missing proteins ,proteotypic peptides ,RNA-seq ,Illumina ,Oxford Nanopore Technologies ,transcriptome ,C-HPP ,human proteome project ,General Medicine ,Computational biology ,Biology ,Proteomics ,Transcriptome ,03 medical and health sciences ,EXPERIMENTAL RESEARCH ,Complementary DNA ,Gene expression ,Proteome ,отсутствующие белки ,протеотипические пептиды ,РНК- секвенирование ,транскриптом ,проект протеом человека ,Gene ,030304 developmental biology - Abstract
Missing (MP) and functionally uncharacterized proteins (uPE1) comprise less than 5% of the total number of proteins encoded by human Chr18 genes. Within half a year, since the January 2020 version of NextProt, the number of entries in the MP+uPE1 datasets changed, mainly due to the achievements of antibody-based proteomics. Assuming that the proteome is closely related to the transcriptome scaffold, quantitative PCR, Illumina HiSeq, and Oxford Nanopore Technology were applied to characterize the liver samples of three male donors in comparison with the HepG2 cell line. The data mining of the Expression Atlas (EMBL-EBI) and the profiling of biopsy samples by using orthogonal methods of transcriptome analysis have shown that in HepG2 cells and the liver, the genes encoding functionally uncharacterized proteins (uPE1) are expressed as low as for the missing proteins (less than 1 copy per cell), except the selected cases of HSBP1L1, TMEM241, C18orf21, and KLHL14. The initial expectation that uPE1 genes might be expressed at higher levels than MP genes, was compromised by severe discrepancies in our semi-quantitative gene expression data and in public databanks. Such discrepancy forced us to revisit the transcriptome of Chr18, the target of the Russian C-HPP Consortium. Tanglegram of highly expressed genes and further correlation analysis have shown the severe dependencies on the mRNA extraction method and the analytical platform. Targeted gene expression analysis by quantitative PCR (qPCR) and high-throughput transcriptome profiling (Illumina HiSeq and ONT MinION) for the same set of samples from normal liver tissue and HepG2 cells revealed the detectable expression of 250+ (92%) protein-coding genes of Chr18 (at least one method). The expression of slightly more than 50% protein-coding genes was detected simultaneously by all three methods. Correlation analysis of the gene expression profiles showed that the grouping of the datasets depended almost equally on both the type of biological material and the experimental method, particularly cDNA/mRNA isolation and library preparation., Отсутствующие белки и функционально не охарактеризованные белки (в англоязычной литературе обозначенные как missing (MP) и functionally uncharacterized proteins (uPE1), соответственно) составляют менее 5% от общего числа белков, кодируемых генами 18 хромосомы человека. В течение полугода, начиная с января 2020 года, в версии NextProt выросло количество записей в наборах данных MP+uPE1. Подобные изменения обусловлены преимущественно достижениями протеомики на основе антител. В данной работе количественная ПЦР, технологии секвенирования Illumina HiSeq и Oxford Nanopore Technologies были применены для сравнительного анализа транскриптомного профиля образцов печени трех доноров мужского пола и клеточной линии HepG2. Анализ данных атласа экспрессии (Expression Atlas, EMBL-EBI) и полученных результатов по биологическим образцам с использованием ортогональных методов анализа транскриптома показал, что в клетках печени и HepG2 уровень экспрессии генов, кодирующих функционально не охарактеризованные белки (uPE1), находится на таком же низком уровне, как и в случае генов MP (в количестве менее 1 копии на клетку). Исключение составили несколько генов: HSBP1L1, TMEM241, C18orf21 и KLHL14. Согласно существенным расхождениям в ранее полученных полуколичественных данных по экспрессии генов и данным в открытых базах данных, изначально предполагалось, что экспрессия генов uPE1 может быть выше, чем генов MP. Подобное расхождение побудило обратиться к транскриптому 18 хромосомы человека, являющейся целевой для России в проекте «Протеом человека». Полученные результаты о наиболее экспрессируемых генах и дальнейший корреляционный анализ показал существование зависимости от метода экстракции мРНК и аналитической платформы. Анализ экспрессии целевых генов 18 хромосомы с применением количественной ПЦР (qPCR) и методов высокопроизводительного профилирования транскриптома (Illumina HiSeq и ONT MinION) для одинаковых наборов образцов нормальной ткани печени и клеточной линии HepG2 выявил более 250 (92%) белок-кодирующих генов, детектируемых хотя бы одним методом. Экспрессия более чем 50% белок-кодирующих генов была детектирована всеми тремя методами. Корреляционный анализ профилей экспрессии генов показал, что результаты «группируются» в зависимости от типа биологического материала и экспериментальных методов, в частности от способа подготовки библиотеки (выделения кДНК, мРНК). Зависимость от выбора способа биоинформатической обработки была отмечена в значительно меньшей степени.
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- 2021
6. Proteomic Analysis of Chr 18 Proteins Using 2D Fractionation
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Natalya A Shushkova, Sergey P. Radko, Victor G. Zgoda, Tatiana E. Farafonova, Elena A. Ponomarenko, A. V. Lisitsa, Konstantin N. Yarygin, O. V. Tikhonova, Ekaterina V. Ilgisonis, Svetlana E. Novikova, Nikita E. Vavilov, and Alexander I. Archakov
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0301 basic medicine ,Proteomics ,030102 biochemistry & molecular biology ,Proteome ,Chemistry ,Selected reaction monitoring ,Context (language use) ,Shotgun ,General Chemistry ,Computational biology ,Fractionation ,Biochemistry ,Transcriptome ,03 medical and health sciences ,030104 developmental biology ,Tandem Mass Spectrometry ,Human proteome project ,Chromosomes, Human ,Humans - Abstract
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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- 2020
7. Human Chr18: 'Stakhanovite' Genes, Missing and uPE1 Proteins in Liver Tissue and HepG2 Cells
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Ekaterina V. Ilgisonis, V.V. Shapovalova, I. V. Vakhrushev, Ekaterina V. Poverennaya, Sergey P. Radko, Olga I. Kiseleva, I.V. Buromski, Olga S. Timoshenko, Sergey S. Markin, George S. Krasnov, Andrey Lisitsa, Svetlana A. Khmeleva, K.G. Ptitsyn, Elena A. Ponomarenko, Victor G. Zgoda, L. K. Kurbatov, Alexander I. Archakov, Anastasia V. Tsvetkova, Mikhail A. Pyatnitskiy, and Y.Y. Kiseleva
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Transcriptome ,NeXtProt ,Complementary DNA ,Minion ,Proteome ,Gene expression ,Computational biology ,Biology ,Proteomics ,Gene - Abstract
Missing (MP) and functionally uncharacterized proteins (uPE1) comprise less than 5% of the total number of human Chr18 genes. Within half a year, since the January 2020 version of NextProt, the number of entries in the MP+uPE1 datasets has changed, mainly due to the achievements of antibody-based proteomics. Assuming that the proteome is closely related to the transcriptome scaffold, quantitative PCR, Illumina HiSeq, and Oxford Nanopore Technology were applied to characterize the liver samples of three male donors compared with the HepG2 cell line. The data mining of Expression Atlas (EMBL-EBI) and the profiling of our biospecimens using orthogonal methods of transcriptome analysis have shown that in HepG2 cells and the liver, the genes encoding functionally uncharacterized proteins (uPE1) are expressed as low as for the missing proteins (less than 1 copy per cell), except for selected cases of HSBP1L1, TMEM241, C18orf21, and KLHL14. The initial expectation that uPE1 genes might be expressed at higher levels than MP genes, was compromised by severe discrepancies in our semi-quantitative gene expression data and in public databanks. Such discrepancy forced us to revisit the transcriptome of Chr18, the target of Russian C-HPP Consortia. Tanglegram of highly expressed genes and further correlation analysis have shown the severe dependencies on the mRNA extraction method and analytical platform.Targeted gene expression analysis by quantitative PCR (qPCR) and high-throughput transcriptome profiling (Illumina HiSeq and ONT MinION) for the same set of samples from normal liver tissue and HepG2 cells revealed the detectable expression of 250+ (92%) protein-coding genes of Chr18 (at least one method). The expression of slightly more than 50% protein-coding genes was detected simultaneously by all three methods. Correlation analysis of the gene expression profiles showed that the grouping of the datasets depended almost equally on both the type of biological material and the experimental method, particularly cDNA/mRNA isolation and library preparation. The dependence on the choice of bioinformatics analysis pipeline was also noticeable but significantly less. Furthermore, the combination of Illumina HiSeq and ONT MinION sequencing to validate proteotypic peptides of missing and uPE1 proteins was performed for the heat-shock factor binding protein HSBP1L1 (missing protein, recently transferred to PE1 category) and uncharacterized protein C18orf21 (uPE1). We observed that a nonsynonymous SNP led to the loss of the site of trypsinolysis in HSBP1L1. The modified version of HSBP1L1 was included in the sequence database and searched against the MS/MS dataset from Kulak, Geyer & Mann (2017), but delivered no significant identification. Thus, HSBP1L1 is still missing for the MS-pillar of C-HPP, although its existence at the protein level has been confirmed.
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- 2020
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8. Increased Sensitivity of Mass Spectrometry by Alkaline Two-Dimensional Liquid Chromatography: Deep Cover of the Human Proteome in Gene-Centric Mode
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Svetlana Novikova, Arthur T. Kopylov, Victor G. Zgoda, Elena A. Ponomarenko, Ekaterina V. Ilgisonis, Ekaterina V. Poverennaya, Alexander I. Archakov, Tatiana E. Farafonova, Andrey Lisitsa, and O. V. Tikhonova
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0301 basic medicine ,Molar concentration ,Proteome ,Mass spectrometry ,Sensitivity and Specificity ,01 natural sciences ,Biochemistry ,Mass Spectrometry ,03 medical and health sciences ,Human proteome project ,Chromosomes, Human ,Humans ,Sensitivity (control systems) ,Gene ,Proteogenomics ,Chromatography, Reverse-Phase ,Chromatography ,Chemistry ,010401 analytical chemistry ,Selected reaction monitoring ,Proteins ,Reproducibility of Results ,General Chemistry ,0104 chemical sciences ,030104 developmental biology ,Mass spectrum ,Chromatography, Liquid - Abstract
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 10–11 to 10–6 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 standard...
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- 2018
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9. Relative Abundance of Proteins in Blood Plasma Samples from Patients with Chronic Cerebral Ischemia
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Alexander А. Izotov, Valeria Yu. Kudryavtseva, Alexander I. Archakov, N B Teryaeva, A. T. Kopylov, Alexander Potapov, Elena A. Ponomarenko, Olga I. Kiseleva, Sergei Morozov, and Anna L. Kaysheva
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Adult ,Male ,0301 basic medicine ,medicine.medical_specialty ,Adolescent ,Proteome ,Ischemia ,Mass spectrometry ,Proteomics ,Brain Ischemia ,Brain ischemia ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,0302 clinical medicine ,Internal medicine ,Blood plasma ,medicine ,Humans ,Innate immune system ,Chemistry ,General Medicine ,Middle Aged ,medicine.disease ,030104 developmental biology ,Endocrinology ,Female ,Biomarkers ,030217 neurology & neurosurgery ,Homeostasis - Abstract
A comparative protein profile analysis of 17 blood plasma samples from patients with ischemia and 20 samples from healthy volunteers was carried out using ultra-high resolution mass spectrometry. The analysis of measurements was performed using the proteomics search engine OMSSA. Normalized spectrum abundance factor (NSAF) in the biological samples was assessed using SearchGUI. The findings of mass spectrometry analysis of the protein composition of blood plasma samples demonstrate that the depleted samples are quite similar in protein composition and relative abundance of proteins. By comparing them with the control samples, we have found a small group of 44 proteins characteristic of the blood plasma samples from patients with chronic cerebral ischemia. These proteins contribute to the processes of homeostasis maintenance, including innate immune response unfolding, the response of a body to stress, and contribution to the blood clotting cascade.
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- 2018
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10. Prospects in studying the human proteome
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Ekaterina V. Ilgisonis, V. G. Zgoda, A. V. Lisitsa, Elena A. Ponomarenko, Alexander I. Archakov, Ekaterina V. Poverennaya, and A. T. Kopylov
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0301 basic medicine ,Cultural Studies ,03 medical and health sciences ,030104 developmental biology ,030102 biochemistry & molecular biology ,Political Science and International Relations ,Proteome ,Alternative splicing ,Protein species ,Human proteome project ,Computational biology ,Biology ,Cell biology - Abstract
Bioinformatic and experimental approaches to studying the human proteome, the totality of proteins of various tissues and organs, are considered. Since the proteome is dynamic, to determine its size, it is necessary to establish its width (the number of various protein species, proteoforms) and depth (the number of copies of each proteoform in a tissue). The quantity of proteoforms that form because of alternative splicing processes and the implementation of single-nucleotide alterations (single amino-acid polymorphisms and posttranslational modifications) at the proteomic level was predicted. Experimental confirmation of the presence of proteoforms is limited by the high analytical sensitivity of proteomic technologies. The metabioinformatic approaches proposed by the authors can be used to evaluate the number of proteoforms for any group of protein-coding genes.
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- 2017
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11. State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells
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Alexander V. Tyakht, Egor Prokhortchouk, O. V. Tikhonova, E. S. Kostrjukova, T E Farafonova, Ekaterina V. Ilgisonis, Alexey Y. Gorbachev, A. S. Sokolov, Arthur T. Kopylov, Elena A. Ponomarenko, Y.Y. Kiseleva, Andrey Lisitsa, Elena N. Ilina, I. V. Vakhrushev, Ekaterina V. Poverennaya, Alexander M. Mazur, Konstantin N. Yarygin, Vadim M. Govorun, Alexander I. Archakov, Victor G. Zgoda, Sergei A. Moshkovskii, Olga I. Kiseleva, Konstantin G. Skryabin, Sergey P. Radko, and Svetlana E. Novikova
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Proteomics ,0301 basic medicine ,Proteome ,RNA-Seq ,Shotgun ,Biology ,Biochemistry ,Transcriptome ,03 medical and health sciences ,Chromosome 18 ,Human proteome project ,Humans ,Digital polymerase chain reaction ,RNA, Messenger ,Databases, Protein ,030102 biochemistry & molecular biology ,Gene Expression Profiling ,Proteins ,Chromosome ,Hep G2 Cells ,General Chemistry ,Molecular biology ,030104 developmental biology ,Liver ,Chromosomes, Human, Pair 18 - Abstract
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
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- 2016
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12. Combination of virtual and experimental 2DE together with ESI LC-MS/MS gives a clearer view about proteomes of human cells and plasma
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Andrey Lisitsa, Maria A. Maynskova, Victor G. Zgoda, Alexander I. Archakov, Elena V. Khryapova, Stanislav N. Naryzhny, I. V. Vakhrushev, Svetlana E. Novikova, Natalia L. Ronzhina, O. V. Tikhonova, and Elena A. Ponomarenko
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0301 basic medicine ,Chemistry ,Clinical Biochemistry ,Esi lc ms ms ,Protein species ,Analytical chemistry ,Plasma ,Mass spectrometry ,Biochemistry ,Analytical Chemistry ,03 medical and health sciences ,030104 developmental biology ,Hepg2 cells ,Proteome ,Pi ,Human proteome project - Abstract
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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- 2015
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13. The Gene-Centric Content Management System and Its Application for Cognitive Proteomics
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Alexander V Shargunov, Andrey Lisitsa, Elena A. Ponomarenko, and Ekaterina V. Poverennaya
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0301 basic medicine ,Computer science ,Clinical Biochemistry ,data-enabled science ,lcsh:QR1-502 ,integrative biology ,Omics science ,Biochemistry ,knowledge base ,Human Proteome Project ,chromosome 18 ,Article ,lcsh:Microbiology ,Task (project management) ,03 medical and health sciences ,Structural Biology ,Human–computer interaction ,Human proteome project ,Molecular Biology ,business.industry ,Human intelligence ,Cognition ,Data sharing ,030104 developmental biology ,Workflow ,Knowledge base ,Proteome ,business - Abstract
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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- 2018
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14. [Multiomics study of HepG2 cell line proteome]
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A. V. Lisitsa, V. G. Zgoda, O. I. Kiseleva, Stanislav N. Naryzhny, Ekaterina V. Poverennaya, and Elena A. Ponomarenko
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0301 basic medicine ,Proteomics ,Proteome ,Sequence Analysis, RNA ,Single amino acid polymorphism ,Gene Expression Profiling ,Alternative splicing ,Single-nucleotide polymorphism ,General Medicine ,Computational biology ,Hep G2 Cells ,Biology ,Polymorphism, Single Nucleotide ,General Biochemistry, Genetics and Molecular Biology ,Transcriptome ,03 medical and health sciences ,Alternative Splicing ,030104 developmental biology ,Tandem Mass Spectrometry ,Hepg2 cells ,Posttranslational modification ,Humans ,Protein Processing, Post-Translational - Abstract
Current proteomic studies are generally focused on the most abundant proteoforms encoded by canonical nucleic sequences. Transcriptomic and proteomic data, accumulated in a variety of postgenome sources and coupled with state-of-art analytical technologies, allow to start the identification of aberrant (non-canonical) proteoforms. The main sources of aberrant proteoforms are alternative splicing, single nucleotide polymorphism, and post-translational modifications. The aim of this work was to estimate the heterogeneity of HepG2 proteome. We suggested multiomics approach, which combines transcriptomic (RNAseq) and proteomic (2DE-MS/MS) methods, as a promising strategy to explore the proteome.Na segodniashniĭ moment issledovaniia v oblasti proteomiki sosredotocheny v osnovnom vokrug naibolee predstavlennykh form belkov, zachastuiu kodiruemykh kanonicheskimi (neizmenennymi) nukleotidnymi posledovatel'nostiami. Nakoplennyĭ massiv transkriptomnykh i proteomnykh dannykh nariadu s vysokim urovnem sovremennykh tekhnologicheskikh vozmozhnosteĭ postgenomnykh issledovaniĭ pozvoliaet pristupit' k identifikatsii aberrantnykh form belkov. Dannaia rabota byla natselena na otsenku geterogennosti proteoma HepG2, voznikaiushcheĭ v rezul'tate realizatsii aberratsiĭ na belkovom urovne. V kachestve perspektivnogo instrumenta issledovaniia proteoma byl predlozhen kompleks transkriptomnykh (RNAseq) i proteomnykh (2DE i MS/MS) metodov.
- Published
- 2017
15. Why Are the Correlations between mRNA and Protein Levels so Low among the 275 Predicted Protein-Coding Genes on Human Chromosome 18?
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Elena A. Ponomarenko, Andrey Lisitsa, Ekaterina V. Poverennaya, Ekaterina V. Ilgisonis, Sergey P. Radko, Alexander I. Archakov, Victor G. Zgoda, and Arthur T. Kopylov
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0301 basic medicine ,Genetics ,Proteomics ,Chromosome ,Proteins ,Shotgun ,General Chemistry ,Hep G2 Cells ,Biology ,Biochemistry ,03 medical and health sciences ,030104 developmental biology ,MRNA Sequencing ,Real-time polymerase chain reaction ,Liver ,Chromosome 18 ,Proteome ,Human proteome project ,Humans ,RNA, Messenger ,Chromosomes, Human, Pair 18 ,Transcriptome ,Gene - Abstract
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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- 2017
16. 2DE-based approach for estimation of number of protein species in a cell
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Victor G. Zgoda, Elena A. Ponomarenko, Andrey Lisitsa, Stanislav N. Naryzhny, and Alexander I. Archakov
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Spots ,Clinical Biochemistry ,Cell ,Protein species ,Computational biology ,Human cell ,Biology ,medicine.disease_cause ,Biochemistry ,Molecular biology ,Analytical Chemistry ,medicine.anatomical_structure ,Proteome ,Human proteome project ,medicine ,Escherichia coli ,Function (biology) - Abstract
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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- 2013
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17. Chromosome 18 Transcriptoproteome of Liver Tissue and HepG2 Cells and Targeted Proteome Mapping in Depleted Plasma: Update 2013
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Elena A. Ponomarenko, L. K. Kurbatov, Egor B. Prokhortchouck, Ekaterina V. Ilgisonis, Valentina V. Averchuk, Y.Y. Kiseleva, Alexander A. Moisa, Sergey P. Radko, Sergei A. Moshkovskii, Alexander I. Archakov, P. A. Karalkin, O. V. Tikhonova, Konstantin N. Yarygin, Andrey Lisitsa, Victor G. Zgoda, E. S. Kostrjukova, Nadezhda A. Bogolubova, Konstantin G. Skryabin, I. V. Vakhrushev, K.G. Ptitsyn, Arthur T. Kopylov, Alexander V. Tyakht, Alexander M. Mazur, A. S. Sokolov, Elena N. Ilina, Alexey Y. Gorbachev, Dmitry G. Alexeev, Ekaterina V. Poverennaya, Vadim M. Govorun, Alexey D. Filimonov, and Svetlana E. Novikova
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Proteome ,Hep G2 Cells ,General Chemistry ,Biology ,Polymerase Chain Reaction ,Biochemistry ,Molecular biology ,Transcriptome ,Plasma ,MRNA Sequencing ,Liver ,Chromosome 18 ,Cell culture ,Human proteome project ,Humans ,Digital polymerase chain reaction ,Chromosomes, Human, Pair 18 ,Gene - Abstract
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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- 2013
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18. Targeted Quantitative Screening of Chromosome 18 Encoded Proteome in Plasma Samples of Astronaut Candidates
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Andrey Lisitsa, Alexander Moysa, Anatoly I. Grigoriev, Andrey A. Markin, Victor G. Zgoda, A. T. Kopylov, Svetlana E. Novikova, Alexander I. Archakov, Elena A. Ponomarenko, Sergei A. Moshkovskii, Ekaterina V. Ilgisonis, Maria G. Zavialova, and O. V. Tikhonova
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0301 basic medicine ,Adult ,Proteome ,Peptide ,Biology ,Biochemistry ,03 medical and health sciences ,Plasma ,Young Adult ,Chromosome 18 ,Humans ,Prealbumin ,chemistry.chemical_classification ,Adenosine Triphosphatases ,Plasma samples ,Selected reaction monitoring ,Healthy subjects ,Medical evaluation ,General Chemistry ,Middle Aged ,Molecular biology ,Healthy Volunteers ,Transthyretin ,030104 developmental biology ,chemistry ,biology.protein ,Astronauts ,Chromosomes, Human, Pair 18 - Abstract
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 10–6 M (transthyretin, P02766) to 10–11 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 Proteom...
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- 2016
19. Comparative Ranking of Human Chromosomes Based on Post-Genomic Data
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Andrey Lisitsa, Sergei A. Moshkovskii, Ekaterina V. Ilgisonis, Alexander I. Archakov, Mikhail A. Pyatnitskiy, Ekaterina V. Poverennaya, Elena A. Ponomarenko, and Alexey Chernobrovkin
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Computational biology ,Biology ,ENCODE ,computer.software_genre ,Biochemistry ,Transcriptome ,Open Reading Frames ,Resource (project management) ,Databases, Genetic ,Human Genome Project ,Genetics ,Human proteome project ,Chromosomes, Human ,Humans ,Relevance (information retrieval) ,Molecular Biology ,Internet ,Chromosome Mapping ,Computational Biology ,Genomics ,Ranking ,Proteome ,Molecular Medicine ,Human genome ,Data mining ,computer ,Biotechnology - Abstract
The goal of the Human Proteome Project (HPP) is to fully characterize the 21,000 human protein-coding genes with respect to the estimated two million proteins they encode. As such, the HPP aims to create a comprehensive, detailed resource to help elucidate protein functions and to advance medical treatment. Similarly to the Human Genome Project (HGP), the HPP chose a chromosome-centric approach, assigning different chromosomes to different countries. Here we introduce a scoring method for chromosome ranking based on several characteristics, including relevance to health problems, existing published knowledge, and current transcriptome and proteome coverage. The score of each chromosome was computed as a weighted combination of indexes reflecting the aforementioned characteristics. The approach is tailored to the chromosome-centric HPP (C-HPP), and is advantageous in that it takes into account currently available information. We ranked the human chromosomes using the proposed score, and observed that Chr Y, Chr 13, and Chr 18 were top-ranked, whereas the scores of Chr 19, Chr 11, and Chr 17 were comparatively low. For Chr 18, selected for the Russian part of C-HPP, about 25% of the encoded genes were associated with diseases, including cancers and neurodegenerative and psychiatric diseases, as well as type 1 diabetes and essential hypertension. This ranking approach could easily be adapted to prioritize research for other sets of genes, such as metabolic pathways and functional categories.
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- 2012
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20. Recent advances in proteomic profiling of human blood: clinical scope
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Andrey Lisitsa, Alexander I. Archakov, Victor G. Zgoda, and Elena A. Ponomarenko
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Proteomics ,Proteome ,Human blood ,Proteomic Profiling ,Gene Expression Profiling ,Selected reaction monitoring ,Computational biology ,Biology ,Mass spectrometry ,Biochemistry ,Molecular biology ,Mass Spectrometry ,Gene expression profiling ,Plasma ,Human proteome project ,Humans ,Chromosomes, Human, Pair 18 ,Molecular Biology - Abstract
A chromosome-centric approach in combination with targeted selected reaction monitoring-mass spectrometry analysis is one of the main approaches to study the human proteome. Measuring the size of the human plasma proteome includes both definition of all forms of proteins and quantitative measuring of the content of each protein form. The algorithm for measuring the proteome of canonical (master) proteins of chromosome 18 was created by combining a chromosome-centric approach and selected reaction monitoring-mass spectrometry. It can be scaled for all chromosomes to measure master proteins in the human blood plasma. Establishment of selected reaction monitoring-mass spectrometry diagnostic assays for quantitative measuring of the proteins associated with the development of diseases is a practical result.
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- 2015
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21. Gene-centric view on the human proteome project: The example of the Russian roadmap for chromosome 18
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S. O. Mazurenko, Elena A. Ponomarenko, Renad Z. Sagdeev, A. L. Aseev, Alexander Khlunov, Anatoly I. Grigoriev, Andrey Lisitsa, Vadim M. Govorun, Victor A. Bykov, Vadim T. Ivanov, Alexander A. Makarov, Konstantin G. Skryabin, and Alexander I. Archakov
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Proteomics ,Genetics ,Internet ,Proteome ,Alternative splicing ,Context (language use) ,Blood Proteins ,Computational biology ,Biology ,Sensitivity and Specificity ,Biochemistry ,Russia ,Chromosome 18 ,Human Genome Project ,Human proteome project ,Humans ,Coding region ,Chromosomes, Human, Pair 18 ,Molecular Biology ,Gene ,Biotechnology - Abstract
During the 2010 Human Proteome Organization Congress in Sydney, a gene-centric approach emerged as a feasible and tractable scaffold for assemblage of the Human Proteome Project. Bringing the gene-centric principle into practice, a roadmap for the 18th chromosome was drafted, postulating the limited sensitivity of analytical methods, as a serious bottleneck in proteomics. In the context of the sensitivity problem, we refer to the "copy number of protein molecules" as a measurable assessment of protein abundance. The roadmap is focused on the development of technology to attain the low- and ultralow -"copied" portion of the proteome. Roadmap merges the genomic, transcriptomic and proteomic levels to identify the majority of 285 proteins from 18th chromosome - master proteins. Master protein is the primary translation of the coding sequence and resembling at least one of the known isoforms, coded by the gene. The executive phase of the roadmap includes the expansion of the study of the master proteins with alternate splicing, single amino acid polymorphisms (SAPs) and post-translational modifications. In implementing the roadmap, Russian scientists are expecting to establish proteomic technologies for integrating MS and atomic force microscopy (AFM). These technologies are anticipated to unlock the value of new biomarkers at a detection limit of 10(-18) M, i.e. 1 protein copy per 1 μL of plasma. The roadmap plan is posted at www.proteome.ru/en/roadmap/ and a forum for discussion of the document is supported.
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- 2011
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22. Combination of virtual and experimental 2DE together with ESI LC-MS/MS gives a clearer view about proteomes of human cells and plasma
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Stanislav N, Naryzhny, Victor G, Zgoda, Maria A, Maynskova, Svetlana E, Novikova, Natalia L, Ronzhina, Igor V, Vakhrushev, Elena V, Khryapova, Andrey V, Lisitsa, Olga V, Tikhonova, Elena A, Ponomarenko, and Alexander I, Archakov
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Proteomics ,Spectrometry, Mass, Electrospray Ionization ,Proteome ,Tandem Mass Spectrometry ,Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ,Humans ,Electrophoresis, Gel, Two-Dimensional ,Blood Proteins ,Hep G2 Cells ,Chromatography, Liquid - Abstract
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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- 2015
23. [The Russian part of the human proteome project:first results and prospects]
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Ekaterina V. Ilgisonis, V. G. Zgoda, Ekaterina V. Poverennaya, A. T. Kopylov, Alexander I. Archakov, Elena A. Ponomarenko, and A. V. Lisitsa
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Pilot phase ,Proteomics ,Biomedical Research ,Proteome ,Computer science ,Gene Expression Profiling ,General Medicine ,Computational biology ,Mass spectrometric ,General Biochemistry, Genetics and Molecular Biology ,Mass Spectrometry ,Task (project management) ,Russia ,Protein content ,Liver ,Human proteome project ,Quantitative assessment ,Humans ,Chromosomes, Human, Pair 18 - Abstract
The article summarizes the achievements of the pilot phase (2010-2014) of the Russian part of the international project "Human Proteome" and identifies the directions for further work on the study of the human chromosome 18 proteome in the framework of the project main phase (2015-2022). The pilot phase of the project was focused on the detection of at least one protein for each chromosome 18 protein-coding gene in three types of the biological material. The application of mass spectrometric detection of proteins by the methods of multiple reactions monitoring (MRM) and gene-centric approach made it possible to detect 95% of master forms of proteins, for 60% of which the quantitative assessment of the protein content was obtained in at least one type of the biological material. The task of the main phase of the project is to measure the proteome size of healthy individuals, taking into account the modified protein forms, providing for both the bioinformatics prediction of the quantity of proteins types and the selective experimental measurement of single proteoforms. Since the ranges of protein concentrations corresponding to the normal physiological state have not been identified, the work of the main phase of the project is focused on the study of clinically healthy individuals. The absence of these data complicates significantly the interpretation of the patients' blood proteomic profiles and prevents creating diagnostic tests. In the long term prospect, implementation of the project envisages development of a diagnostic test system based on multiple reactions monitoring (MRM) for quantitative measurement of the protein forms associated with some diseases. Development of such test systems will allow predicting the extent of risk of different diseases, diagnosing a disease at its early stage and monitoring the effectiveness of the treatment.Stat'ia obobshchaet dostizheniia pilotnoĭ fazy (2010-2014 gg.) rossiĭskoĭ chasti mezhdunarodnogo proekta “Proteom cheloveka” i opredeliaet napravleniia dal'neĭshikh rabot po issledovaniiu proteoma, kodiruemogo genami khromosomy 18 cheloveka (2015-2022 gg.). Pilotnaia faza proekta byla sfokusirovana na detektirovanii kak minimum odnogo belka dlia kazhdogo belok-kodiruiushchego gena khromosomy 18 v trekh tipakh biologicheskogo materiala: plazme krovi, kletkakh pecheni i kletochnoĭ linii HepG2. Ispol'zovanie mass-spektrometricheskoĭ detektsii belkov metodom monitoringa mnozhestvennykh reaktsiĭ (MMR) i geno-tsentrichnogo podkhoda pozvolilo detektirovat' 95% masternykh (nemodifitsirovannykh belkov, soderzhashchikh kanonicheskie aminokislotnye posledovatel'nosti) form belkov, iz kotorykh dlia 60% poluchena otsenka kolichestvennogo soderzhaniia belka khotia by v odnom tipe biologicheskogo materi ala. Zadacheĭ osnovnoĭ fazy proekta iavliaetsia opredelenie razmerov proteoma zdorovogo cheloveka s uchetom modifitsirovannykh form belkov; ono predusmatrivaet kak bioinformaticheskoe predskazanie kolichestva vidov belkov, tak i vyborochnoe éksperimental'noe izmerenie otdel'nykh form. Raboty osnovnoĭ fazy proekta sfokusirovany na issledovanii zdorovogo (obsledovannogo) cheloveka, poskol'ku ne opredeleny diapazony kontsentratsiĭ belkov, sootvetstvuiushchie normal'nomu fiziologicheskomu sostoianiiu. Otsutstvie étikh dannykh sushchestvenno oslozhniaet interpretatsiiu proteomnykh profileĭ krovi patsientov, chto prepiatstvuet sozdaniiu diagnosticheskikh testov. V dolgosrochnoĭ perspektive realizatsiia proekta predusmatrivaet sozdanie na osnove MMR diagnosticheskoĭ test-sistemy dlia kolichestvennogo izmereniia form belkov, assotsiirovannykh s razvitiem zabolevaniĭ. Sozdanie podobnykh test-sistem pozvolit predskazyvat' ste pen' riska vozniknoveniia tekh ili inykh zabolevaniĭ, diagnostirovat' zabolevaniia na rannikh stadiiakh i provodit' monitoring éffektivnosti lecheniia.
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- 2015
24. Profiling proteoforms: promising follow-up of proteomics for biomarker discovery
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A. L. Chernobrovkin, Elena A. Ponomarenko, Andrey Lisitsa, Alexander I. Archakov, and Sergei A. Moshkovskii
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Proteomics ,Proteome ,Protein species ,Computational Biology ,Single gene ,Computational biology ,Biology ,Bioinformatics ,Biochemistry ,Alternative Splicing ,Targeted mass spectrometry ,Neoplasms ,Human proteome project ,Profiling (information science) ,Animals ,Humans ,Biomarker discovery ,Shotgun proteomics ,Molecular Biology ,Protein Processing, Post-Translational ,Biomarkers - Abstract
Today, proteomics usually compares clinical samples by use of bottom-up profiling with high resolution mass spectrometry, where all protein products of a single gene are considered as an integral whole. At the same time, proteomics of proteoforms, which considers the variety of protein species, offers the potential to discover valuable biomarkers. Proteoforms are protein species that arise as a consequence of genetic polymorphisms, alternative splicing, post-translational modifications and other less-explored molecular events. The comprehensive observation of proteoforms has been an exclusive privilege of top-down proteomics. Here, we review the possibilities of a bottom-up approach to address the microheterogeneity of the human proteome. Special focus is given to shotgun proteomics and structure-based bioinformatics as a source of hypothetical proteoforms, which can potentially be verified by targeted mass spectrometry to determine the relevance of proteoforms to diseases.
- Published
- 2014
25. 2DE-based approach for estimation of number of protein species in a cell
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Stanislav N, Naryzhny, Andrey V, Lisitsa, Victor G, Zgoda, Elena A, Ponomarenko, and Alexander I, Archakov
- Subjects
Proteomics ,Proteome ,Histocytochemistry ,Limit of Detection ,Escherichia coli ,Linear Models ,Humans ,Electrophoresis, Gel, Two-Dimensional ,Hep G2 Cells - Abstract
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.
- Published
- 2013
26. Chromosome 18 transcriptome profiling and targeted proteome mapping in depleted plasma, liver tissue and HepG2 cells
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Elena A. Ponomarenko, Aleksey D. Filimonov, L. K. Kurbatov, Sergey P. Radko, T E Farafonova, Ekaterina V. Ilgisonis, Andrew Ivanov, O. V. Tikhonova, Stanislav N. Naryzhny, Alexei Medvedev, Alexander A. Moisa, Dmitry G. Alexeev, Victor G. Zgoda, Y. V. Mezentsev, Nadezhda V. Pyndyk, Nadezhda A. Bogolyubova, A. L. Chernobrovkin, Elena N. Ilina, Ekaterina V. Poverennaya, Svetlana E. Novikova, Vadim M. Govorun, Sergei A. Moshkovskii, Andrey Lisitsa, Svetlana A. Khmeleva, Alexander I. Archakov, Arthur T. Kopylov, Alexander V. Tyakht, and E. S. Kostrjukova
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Proteome ,Genome, Human ,Gene Expression ,General Chemistry ,Blood Proteins ,Hep G2 Cells ,Biology ,Biochemistry ,Interactome ,Molecular biology ,Mass Spectrometry ,Sepharose ,Liver ,Chromosome 18 ,Hepg2 cells ,Human proteome project ,Transcriptome profiling ,Humans ,Chromosomes, Human, Pair 18 ,Databases, Protein ,Transcriptome ,Gene - Abstract
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 ).
- Published
- 2012
27. [Knowledge-based technologies in proteomics]
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Ekaterina V. Ilgisonis, Elena A. Ponomarenko, and Andrey Lisitsa
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Proteomics ,Exploit ,Computer science ,Knowledge Bases ,Information Storage and Retrieval ,Ontology (information science) ,Complex Mixtures ,Bioinformatics ,Biochemistry ,Mass Spectrometry ,Medical Subject Headings ,Knowledge extraction ,Controlled vocabulary ,Animals ,Humans ,Information Dissemination ,Organic Chemistry ,Computational Biology ,Proteins ,Data science ,ComputingMethodologies_PATTERNRECOGNITION ,Proteome ,DECIPHER ,PeptideAtlas ,Software - Abstract
Proteomic technologies enable one to identify thousands of proteins in biological samples. These data require appropriate means for storage, dissemination and analytical processing to decipher the new knowledge. Automatic processing of high-efficient experimental results is powered by the controlled vocabularies, such as Medical Subject Headings and GeneOntology. While ontology and vocabularies undergo constant evolution, it is necessary to provide centralized storage of proteomic data for further revision in accordance with the updated knowledge domain. Proteomic repositories like PRIDE, The Global Proteome Machine, PeptideAtlas, etc., are available to harbor the wealth of mass spectral data and appropriate protein identifications. The existing repositories facilitate the development of knowledge extraction technologies to compare the list of identified proteins with the GeneOntology annotations, Medical Subject Headings, metabolic and regulatory pathways. This paper reviews modern analytical tools that exploit the knowledge-based technologies for proteome research.
- Published
- 2011
28. [Selection of the peptide mass tolerance value for the protein identification with peptide mass fingerprinting]
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Oxana P. Trifonova, N. A. Petushkova, A. L. Chernobrovkin, Elena A. Ponomarenko, and A. V. Lisitsa
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Gel electrophoresis ,Chromatography ,Protein mass spectrometry ,Chemistry ,Organic Chemistry ,Mass spectrometry ,Tandem mass tag ,Biochemistry ,Peptide Mapping ,Mass Spectrometry ,Molecular Weight ,Peptide mass fingerprinting ,Data Interpretation, Statistical ,Proteome ,Mass spectrum ,Microsomes, Liver ,Humans ,Bottom-up proteomics ,Peptides ,Software - Abstract
Peptide mass fingerprinting (PMF) is widely used for protein identification while studying proteome via time-of-flight mass spectrometer or via 1D or 2D electrophoresis. Peptide mass tolerance indicating the fit of theoretical peptide mass to an experimental one signifcantly influences protein identification. The role of peptide mass tolerance could be estimated by counting the number of correctly identified proteins for the reference set of mass spectra. The reference set of 400 Ultraflex (Bruker Daltonics, Germany) protein mass spectra was obtained for liver microsomes slices hydrolyzed via 1D gel electrophoresis. Using a Mascot server for protein identification, the peptide mass tolerance value varied within 0.02–0.40 Da with a step of 0.01 Da. The number of identified proteins changed up to 10 times depending on the tolerance. The maximal number of identified proteins was reported for the tolerance value of 0.15 Da (120 ppm) known to be 1.5–2-fold higher than the recommended values for such a type of mass spectrometer. The software program PMFScan was developed to obtain the dependence between the number of identified proteins and the tolerance values.
- Published
- 2011
29. Proteomics of mouse liver microsomes: performance of different protein separation workflows for LC-MS/MS
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Andrei V. Lisitsa, Alexander I. Archakov, O. V. Tikhonova, Victor G. Zgoda, Sergei A. Moshkovskii, Arthur T. Kopylov, Stanislav A. Melnik, Timofey V. Andreewski, and Elena A. Ponomarenko
- Subjects
Male ,Proteomics ,Chromatography ,Protein digestion ,Complete protein ,Biology ,Biochemistry ,Mice ,Membrane protein ,Tandem Mass Spectrometry ,Proteome ,Protein purification ,Microsome ,Microsomes, Liver ,Animals ,Electrophoresis, Gel, Two-Dimensional ,Electrophoresis, Polyacrylamide Gel ,Ion trap ,Molecular Biology ,Chromatography, Liquid - Abstract
The mouse liver microsome proteome was investigated using ion trap MS combined with three separation workflows including SDS-PAGE followed by reverse-phase LC of in-gel protein digestions (519 proteins identified); 2-D LC of protein digestion (1410 proteins); whole protein separation on mRP heat-stable column followed by 2-D LC of protein digestions from each fraction (3-D LC; 3703 proteins). The higher number of proteins identified in the workflow corresponded to the lesser percentage of run-to-run reproducibility. Gel-based method yielded a number of predicted membrane proteins similar to LC-based workflows.
- Published
- 2009
30. Chromosome-centric approach to overcoming bottlenecks in the Human Proteome Project
- Author
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Arthur T. Kopylov, Alexey Chernobrovkin, Alexander I. Archakov, Stanislav N. Naryzhny, Victor G. Zgoda, Andrey Lisitsa, and Elena A. Ponomarenko
- Subjects
Proteome ,Operations research ,food and beverages ,Computational biology ,Biology ,Biochemistry ,Genome ,Bottleneck ,Cellular protein ,Chromosome (genetic algorithm) ,Limit of Detection ,Human proteome project ,Chromosomes, Human ,Humans ,Thermodynamics ,DECIPHER ,Human genome ,Molecular Biology - Abstract
The international Human Proteome Project (HPP), a logical continuation of the Human Genome Project, was launched on 23 September 2010 in Sydney, Australia. In accordance with the gene-centric approach, the goals of the HPP are to prepare an inventory of all human proteins and decipher the network of cellular protein interactions. The greater complexity of the proteome in comparison to the genome gives rise to three bottlenecks in the implementation of the HPP. The main bottleneck is the insufficient sensitivity of proteomic technologies, hampering the detection of proteins with low- and ultra-low copy numbers. The second bottleneck is related to poor reproducibility of proteomic methods and the lack of a so-called 'gold' standard. The last bottleneck is the dynamic nature of the proteome: its instability over time. The authors here discuss approaches to overcome these bottlenecks in order to improve the success of the HPP.
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