1
|
Kalhor M, Lapin J, Picciani M, Wilhelm M. Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification. Mol Cell Proteomics 2024; 23:100798. [PMID: 38871251 PMCID: PMC11269915 DOI: 10.1016/j.mcpro.2024.100798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/26/2024] [Accepted: 06/09/2024] [Indexed: 06/15/2024] Open
Abstract
Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities, and future perspectives of this approach and its impact on mass spectrometry-based proteomics.
Collapse
Affiliation(s)
- Mostafa Kalhor
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Joel Lapin
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Mario Picciani
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Mathias Wilhelm
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Munich Data Science Institute, Technical University of Munich, Garching, Germany.
| |
Collapse
|
2
|
Ivanov MV, Garibova LA, Postoenko VI, Levitsky LI, Gorshkov MV. On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics. Proteomics 2024; 24:e2300090. [PMID: 37496303 DOI: 10.1002/pmic.202300090] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/05/2023] [Accepted: 07/18/2023] [Indexed: 07/28/2023]
Abstract
The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E. coli dataset demonstrating in a number of cases that erroneous data processing methods may lead to a low CV which has nothing to do with these methods' performances in quantitation.
Collapse
Affiliation(s)
- Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Leyla A Garibova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Valeriy I Postoenko
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| |
Collapse
|
3
|
Korolkova Y, Mikov A, Lobas A, Solovyeva E, Surin A, Andreev Y, Gorshkov M, Kozlov S. Venom-gland transcriptomics and venom proteomics of the Tibellus oblongus spider. Sci Data 2023; 10:820. [PMID: 37993463 PMCID: PMC10665394 DOI: 10.1038/s41597-023-02703-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 10/31/2023] [Indexed: 11/24/2023] Open
Abstract
The Tibellus oblongus spider is an active hunter that does not spin webs and remains highly underinvestigated in terms of the venom composition. Here, we describe venom glands transcriptome and venom proteome analysis for unveiling the polypeptide composition of Tibellus oblongus spider venom. The resulting EST database includes 1733 records, including 1263 nucleotide sequences with ORFs, of these 942 have been identified as toxin-coding. The database of peptide sequences was built based on of the transcriptomics results. It contains 217 new toxins, 212 of them were detected in the T. oblongus venom by the proteomics.
Collapse
Affiliation(s)
- Yuliya Korolkova
- Department of Molecular Neurobiology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 16/10 Miklukho-Maklay Str., 117997, Moscow, Russia.
| | - Alexander Mikov
- Scientific Research Institute for Systems Biology and Medicine, Scientific Driveway, 18, 117246, Moscow, Russia
| | - Anna Lobas
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, RAS, 38 Bld. 2, Leninsky Pr., 119334, Moscow, Russia
| | - Elizaveta Solovyeva
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, RAS, 38 Bld. 2, Leninsky Pr., 119334, Moscow, Russia
- Department of Molecular and Chemical Physics, Moscow Institute of Physics and Technology (National Research University), 9 Institutsky Per., 141700, Dolgoprudny, Russia
| | - Alexey Surin
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, RAS, 38 Bld. 2, Leninsky Pr., 119334, Moscow, Russia
| | - Yaroslav Andreev
- Department of Molecular Neurobiology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 16/10 Miklukho-Maklay Str., 117997, Moscow, Russia
- Moscow Institute of Molecular Medicine, Sechenov First Moscow State Medical University, 8 Bld. 2, Trubetskaya Str., 119991, Moscow, Russia
| | - Mikhail Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, RAS, 38 Bld. 2, Leninsky Pr., 119334, Moscow, Russia
| | - Sergey Kozlov
- Department of Molecular Neurobiology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, 16/10 Miklukho-Maklay Str., 117997, Moscow, Russia
| |
Collapse
|
4
|
Postoenko VI, Garibova LA, Levitsky LI, Bubis JA, Gorshkov MV, Ivanov MV. IQMMA: Efficient MS1 Intensity Extraction Pipeline Using Multiple Feature Detection Algorithms for DDA Proteomics. J Proteome Res 2023; 22:2827-2835. [PMID: 37579078 DOI: 10.1021/acs.jproteome.3c00075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
One of the key steps in data dependent acquisition (DDA) proteomics is detection of peptide isotopic clusters, also called "features", in MS1 spectra and matching them to MS/MS-based peptide identifications. A number of peptide feature detection tools became available in recent years, each relying on its own matching algorithm. Here, we provide an integrated solution, the intensity-based Quantitative Mix and Match Approach (IQMMA), which integrates a number of untargeted peptide feature detection algorithms and returns the most probable intensity values for the MS/MS-based identifications. IQMMA was tested using available proteomic data acquired for both well-characterized (ground truth) and real-world biological samples, including a mix of Yeast and E. coli digests spiked at different concentrations into the Human K562 digest used as a background, and a set of glioblastoma cell lines. Three open-source feature detection algorithms were integrated: Dinosaur, biosaur2, and OpenMS FeatureFinder. None of them was found optimal when applied individually to all the data sets employed in this work; however, their combined use in IQMMA improved efficiency of subsequent protein quantitation. The software implementing IQMMA is freely available at https://github.com/PostoenkoVI/IQMMA under Apache 2.0 license.
Collapse
Affiliation(s)
- Valeriy I Postoenko
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
- Moscow Institute of Physics and Technology, National Research University, G. Dolgoprudny, Institutsky Lane 9, Dolgoprudny 141701, Russia
| | - Leyla A Garibova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
- Moscow Institute of Physics and Technology, National Research University, G. Dolgoprudny, Institutsky Lane 9, Dolgoprudny 141701, Russia
| | - Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| | - Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| |
Collapse
|
5
|
Bakker R, Ellers J, Roelofs D, Vooijs R, Dijkstra T, van Gestel CAM, Hoedjes KM. Combining time-resolved transcriptomics and proteomics data for Adverse Outcome Pathway refinement in ecotoxicology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161740. [PMID: 36708843 DOI: 10.1016/j.scitotenv.2023.161740] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 01/14/2023] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Conventional Environmental Risk Assessment (ERA) of pesticide pollution is based on soil concentrations and apical endpoints, such as the reproduction of test organisms, but has traditionally disregarded information along the organismal response cascade leading to an adverse outcome. The Adverse Outcome Pathway (AOP) framework includes response information at any level of biological organization, providing opportunities to use intermediate responses as a predictive read-out for adverse outcomes instead. Transcriptomic and proteomic data can provide thousands of data points on the response to toxic exposure. Combining multiple omics data types is necessary for a comprehensive overview of the response cascade and, therefore, AOP development. However, it is unclear if transcript and protein responses are synchronized in time or time lagged. To understand if analysis of multi-omics data obtained at the same timepoint reveal one synchronized response cascade, we studied time-resolved shifts in gene transcript and protein abundance in the springtail Folsomia candida, a soil ecotoxicological model, after exposure to the neonicotinoid insecticide imidacloprid. We analyzed transcriptome and proteome data every 12 h up to 72 h after onset of exposure. The most pronounced shift in both transcript and protein abundances was observed after 48 h exposure. Moreover, cross-correlation analyses indicate that most genes displayed the highest correlation between transcript and protein abundances without a time-lag. This demonstrates that a combined analysis of transcriptomic and proteomic data from the same time-point can be used for AOP improvement. This data will promote the development of biomarkers for the presence of neonicotinoid insecticides or chemicals with a similar mechanism of action in soils.
Collapse
Affiliation(s)
- Ruben Bakker
- Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
| | - Jacintha Ellers
- Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
| | - Dick Roelofs
- Keygene N.V., Agro Business Park 90, 6708 PW Wageningen, the Netherlands
| | - Riet Vooijs
- Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
| | - Tjeerd Dijkstra
- Max Planck Institute for Developmental Biology, Max-Planck-Ring 25, D-72076 Tübingen, Germany
| | - Cornelis A M van Gestel
- Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
| | - Katja M Hoedjes
- Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands.
| |
Collapse
|
6
|
Yeast Ribonucleotide Reductase Is a Direct Target of the Proteasome and Provides Hyper Resistance to the Carcinogen 4-NQO. J Fungi (Basel) 2023; 9:jof9030351. [PMID: 36983519 PMCID: PMC10057556 DOI: 10.3390/jof9030351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/05/2023] [Accepted: 03/10/2023] [Indexed: 03/15/2023] Open
Abstract
Various external and internal factors damaging DNA constantly disrupt the stability of the genome. Cells use numerous dedicated DNA repair systems to detect damage and restore genomic integrity in a timely manner. Ribonucleotide reductase (RNR) is a key enzyme providing dNTPs for DNA repair. Molecular mechanisms of indirect regulation of yeast RNR activity are well understood, whereas little is known about its direct regulation. The study was aimed at elucidation of the proteasome-dependent mechanism of direct regulation of RNR subunits in Saccharomyces cerevisiae. Proteome analysis followed by Western blot, RT-PCR, and yeast plating analysis showed that upregulation of RNR by proteasome deregulation is associated with yeast hyper resistance to 4-nitroquinoline-1-oxide (4-NQO), a UV-mimetic DNA-damaging drug used in animal models to study oncogenesis. Inhibition of RNR or deletion of RNR regulatory proteins reverses the phenotype of yeast hyper resistance to 4-NQO. We have shown for the first time that the yeast Rnr1 subunit is a substrate of the proteasome, which suggests a common mechanism of RNR regulation in yeast and mammals.
Collapse
|
7
|
Kazakova EM, Solovyeva EM, Levitsky LI, Bubis JA, Emekeeva DD, Antonets AA, Nazarov AA, Gorshkov MV, Tarasova IA. Proteomics-based scoring of cellular response to stimuli for improved characterization of signaling pathway activity. Proteomics 2023; 23:e2200275. [PMID: 36478387 DOI: 10.1002/pmic.202200275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 11/04/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Abstract
Omics technologies focus on uncovering the complex nature of molecular mechanisms in cells and organisms, including biomarkers and drug targets discovery. Aiming at these tasks, we see that information extracted from omics data is still underused. In particular, characteristics of differentially regulated molecules can be combined in a single score to quantify the signaling pathway activity. Such a metric can be useful for comprehensive data interpretation to follow: (1) developing molecular responses in time; (2) potency of a drug on a certain cell culture; (3) ranking the signaling pathway activity in stimulated cells; and (4) integration of the omics data and assay-based measurements of cell viability, cytotoxicity, and proliferation. With recent advances in ultrafast mass spectrometry for quantitative proteomics allowing data collection in a few minutes, proteomics score for cellular response to stimuli can become a fast, accurate, and informative complement to bioassays. Here, we utilized an interquartile-based selection of differentially regulated features and a variety of schemes for quantifying cellular responses to come up with the quantitative metric for total cellular response and pathway activity. Validation was performed using antiproliferative and virus assays and label-free proteomics data collected for cancer cells subjected to drug stimulation.
Collapse
Affiliation(s)
- Elizaveta M Kazakova
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Elizaveta M Solovyeva
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Lev I Levitsky
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Julia A Bubis
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Daria D Emekeeva
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Anastasia A Antonets
- Department of Chemistry, M. V. Lomonosov Moscow State University, Moscow, Russia
| | - Alexey A Nazarov
- Department of Chemistry, M. V. Lomonosov Moscow State University, Moscow, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Irina A Tarasova
- V.L. Talrose Institute for Energy Problems of Chemical Physics, Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| |
Collapse
|
8
|
Nasaev SS, Kopeykina AS, Kuznetsova KG, Levitsky LI, Moshkovskii SA. Proteomic Analysis of Zebrafish Protein Recoding via mRNA Editing by ADAR Enzymes. BIOCHEMISTRY. BIOKHIMIIA 2022; 87:1301-1309. [PMID: 36509721 DOI: 10.1134/s0006297922110098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
RNA editing by adenosine deaminases of the ADAR family can lead to protein recoding, since inosine formed from adenosine in mRNA is complementary to cytosine; the resulting codon editing might introduce amino acid substitutions into translated proteins. Proteome recoding can have functional consequences which have been described in many animals including humans. Using protein recoding database derived from publicly available transcriptome data, we identified for the first time the recoding sites in the zebrafish shotgun proteomes. Out of more than a hundred predicted recoding events, ten substitutions were found in six used datasets. Seven of them were in the AMPA glutamate receptor subunits, whose recoding has been well described, and are conserved among vertebrates. Three sites were specific for zebrafish proteins and were found in the transmembrane receptors astrotactin 1 and neuregulin 3b (proteins involved in the neuronal adhesion and signaling) and in the rims2b gene product (presynaptic membrane protein participating in the neurotransmitter release), respectively. Further studies are needed to elucidate the role of recoding of the said three proteins in the zebrafish.
Collapse
Affiliation(s)
- Shamsudin S Nasaev
- Federal Research and Clinical Center of Physical-Chemical Medicine, Moscow, 119435, Russia.,Institute of Biomedical Chemistry, Moscow, 119121, Russia
| | - Anna S Kopeykina
- Pirogov Russian National Research Medical University, Moscow, 117997, Russia
| | | | - Lev I Levitsky
- Talrose Institute for Energy Problems of Chemical Physics, Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Sergei A Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, Moscow, 119435, Russia. .,Pirogov Russian National Research Medical University, Moscow, 117997, Russia
| |
Collapse
|
9
|
Solovyeva EM, Bubis JA, Tarasova IA, Lobas AA, Ivanov MV, Nazarov AA, Shutkov IA, Gorshkov MV. On the Feasibility of Using an Ultra-Fast DirectMS1 Method of Proteome-Wide Analysis for Searching Drug Targets in Chemical Proteomics. BIOCHEMISTRY. BIOKHIMIIA 2022; 87:1342-1353. [PMID: 36509723 DOI: 10.1134/s000629792211013x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Protein quantitation in tissue cells or physiological fluids based on liquid chromatography/mass spectrometry is one of the key sources of information on the mechanisms of cell functioning during chemotherapeutic treatment. Information on significant changes in protein expression upon treatment can be obtained by chemical proteomics and requires analysis of the cellular proteomes, as well as development of experimental and bioinformatic methods for identification of the drug targets. Low throughput of whole proteome analysis based on liquid chromatography and tandem mass spectrometry is one of the main factors limiting the scale of these studies. The method of direct mass spectrometric identification of proteins, DirectMS1, is one of the approaches developed in recent years allowing ultrafast proteome-wide analyses employing minute-scale gradients for separation of proteolytic mixtures. Aim of this work was evaluation of both possibilities and limitations of the method for identification of drug targets at the level of whole proteome and for revealing cellular processes activated by the treatment. Particularly, the available literature data on chemical proteomics obtained earlier for a large set of onco-pharmaceuticals using multiplex quantitative proteome profiling were analyzed. The results obtained were further compared with the proteome-wide data acquired by the DirectMS1 method using ultrashort separation gradients to evaluate efficiency of the method in identifying known drug targets. Using ovarian cancer cell line A2780 as an example, a whole-proteome comparison of two cell lysis techniques was performed, including the freeze-thaw lysis commonly employed in chemical proteomics and the one based on ultrasonication for cell disruption, which is the widely accepted as a standard in proteomic studies. Also, the proteome-wide profiling was performed using ultrafast DirectMS1 method for A2780 cell line treated with lonidamine, followed by gene ontology analyses to evaluate capabilities of the method in revealing regulation of proteins in the cellular processes associated with drug treatment.
Collapse
Affiliation(s)
- Elizaveta M Solovyeva
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Irina A Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Anna A Lobas
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Alexey A Nazarov
- Faculty of Chemistry, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Ilya A Shutkov
- Faculty of Chemistry, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia.
| |
Collapse
|
10
|
Ivanov MV, Bubis JA, Gorshkov V, Tarasova IA, Levitsky LI, Solovyeva EM, Lipatova AV, Kjeldsen F, Gorshkov MV. DirectMS1Quant: Ultrafast Quantitative Proteomics with MS/MS-Free Mass Spectrometry. Anal Chem 2022; 94:13068-13075. [PMID: 36094425 DOI: 10.1021/acs.analchem.2c02255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Recently, we presented the DirectMS1 method of ultrafast proteome-wide analysis based on minute-long LC gradients and MS1-only mass spectra acquisition. Currently, the method provides the depth of human cell proteome coverage of 2500 proteins at a 1% false discovery rate (FDR) when using 5 min LC gradients and 7.3 min runtime in total. While the standard MS/MS approaches provide 4000-5000 protein identifications within a couple of hours of instrumentation time, we advocate here that the higher number of identified proteins does not always translate into better quantitation quality of the proteome analysis. To further elaborate on this issue, we performed a one-on-one comparison of quantitation results obtained using DirectMS1 with three popular MS/MS-based quantitation methods: label-free (LFQ) and tandem mass tag quantitation (TMT), both based on data-dependent acquisition (DDA) and data-independent acquisition (DIA). For comparison, we performed a series of proteome-wide analyses of well-characterized (ground truth) and biologically relevant samples, including a mix of UPS1 proteins spiked at different concentrations into an Echerichia coli digest used as a background and a set of glioblastoma cell lines. MS1-only data was analyzed using a novel quantitation workflow called DirectMS1Quant developed in this work. The results obtained in this study demonstrated comparable quantitation efficiency of 5 min DirectMS1 with both TMT and DIA methods, yet the latter two utilized a 10-20-fold longer instrumentation time.
Collapse
Affiliation(s)
- Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vladimir Gorshkov
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark
| | - Irina A Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Elizaveta M Solovyeva
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Anastasiya V Lipatova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Frank Kjeldsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| |
Collapse
|
11
|
Kuznetsova KG, Zvonareva SS, Ziganshin R, Mekhova ES, Dgebuadze P, Yen DTH, Nguyen THT, Moshkovskii SA, Fedosov AE. Vexitoxins: conotoxin-like venom peptides from predatory gastropods of the genus Vexillum. Proc Biol Sci 2022; 289:20221152. [PMID: 35946162 PMCID: PMC9363990 DOI: 10.1098/rspb.2022.1152] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Venoms of predatory marine cone snails are intensely studied because of the biomedical applications of the neuropeptides that they contain, termed conotoxins. Meanwhile some gastropod lineages have independently acquired secretory glands strikingly similar to the venom gland of cone snails, suggesting that they possess similar venoms. Here we focus on the most diversified of these clades, the genus Vexillum. Based on the analysis of a multi-species proteo-transcriptomic dataset, we show that Vexillum species indeed produce complex venoms dominated by highly diversified short cysteine-rich peptides, vexitoxins. Vexitoxins possess the same precursor organization, display overlapping cysteine frameworks and share several common post-translational modifications with conotoxins. Some vexitoxins show sequence similarity to conotoxins and adopt similar domain conformations, including a pharmacologically relevant inhibitory cysteine knot motif. The Vexillum envenomation gland (gL) is a notably more recent evolutionary novelty than the conoidean venom gland. Thus, we hypothesize lower divergence between vexitoxin genes, and their ancestral 'somatic' counterparts compared to that in conotoxins, and we find support for this hypothesis in the evolution of the vexitoxin cluster V027. We use this example to discuss how future studies on vexitoxins can inform the origin of conotoxins, and how they may help to address outstanding questions in venom evolution.
Collapse
Affiliation(s)
- Ksenia G. Kuznetsova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Sofia S. Zvonareva
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninsky prospect, 33, Moscow 119071, Russia
| | - Rustam Ziganshin
- Institute of Bioorganic Chemistry, Russian Academy of Sciences, Miklukho-Maklaya street, 16/10, Moscow 117997, Russia
| | - Elena S. Mekhova
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninsky prospect, 33, Moscow 119071, Russia
| | - Polina Dgebuadze
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninsky prospect, 33, Moscow 119071, Russia
| | - Dinh T. H. Yen
- Russian-Vietnamese Tropical Research and Technology Center, Coastal Branch, 30 Nguyễn Thiện Thuật, Nha Trang, Vietnam
| | - Thanh H. T. Nguyen
- Russian-Vietnamese Tropical Research and Technology Center, Coastal Branch, 30 Nguyễn Thiện Thuật, Nha Trang, Vietnam
| | - Sergei A. Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| | - Alexander E. Fedosov
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninsky prospect, 33, Moscow 119071, Russia
| |
Collapse
|
12
|
Levitsky LI, Kuznetsova KG, Kliuchnikova AA, Ilina IY, Goncharov AO, Lobas AA, Ivanov MV, Lazarev VN, Ziganshin RH, Gorshkov MV, Moshkovskii SA. Validating Amino Acid Variants in Proteogenomics Using Sequence Coverage by Multiple Reads. J Proteome Res 2022; 21:1438-1448. [PMID: 35536917 DOI: 10.1021/acs.jproteome.2c00033] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Mass spectrometry-based proteome analysis implies matching the mass spectra of proteolytic peptides to amino acid sequences predicted from genomic sequences. Reliability of peptide variant identification in proteogenomic studies is often lacking. We propose a way to interpret shotgun proteomics results, specifically in the data-dependent acquisition mode, as protein sequence coverage by multiple reads as it is done in nucleic acid sequencing for calling of single nucleotide variants. Multiple reads for each sequence position could be provided by overlapping distinct peptides, thus confirming the presence of certain amino acid residues in the overlapping stretch with a lower false discovery rate. Overlapping distinct peptides originate from miscleaved tryptic peptides in combination with their properly cleaved counterparts and from peptides generated by multiple proteases after the same specimen is subject to parallel digestion and analyzed separately. We illustrate this approach using publicly available multiprotease data sets and our own data generated for the HEK-293 cell line digests obtained using trypsin, LysC, and GluC proteases. Totally, up to 30% of the whole proteome was covered by tryptic peptides with up to 7% covered twofold and more. The proteogenomic analysis of the HEK-293 cell line revealed 36 single amino acid variants, seven of which were supported by multiple reads.
Collapse
Affiliation(s)
- Lev I Levitsky
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Ksenia G Kuznetsova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Anna A Kliuchnikova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| | - Irina Y Ilina
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Anton O Goncharov
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| | - Anna A Lobas
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Mark V Ivanov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Vassili N Lazarev
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Moscow Institute of Physics and Technology (State University), 9, Institutskiy per., Dolgoprudny, Moscow Region 141701, Russia
| | - Rustam H Ziganshin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya, Moscow 117997, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Sergei A Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| |
Collapse
|
13
|
Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi. Curr Issues Mol Biol 2022; 44:2069-2088. [PMID: 35678669 PMCID: PMC9164042 DOI: 10.3390/cimb44050140] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/06/2022] [Accepted: 05/07/2022] [Indexed: 11/17/2022] Open
Abstract
An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed “1DE-gel concentration” method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC–MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.
Collapse
|
14
|
Multiomic Profiling Identified EGF Receptor Signaling as a Potential Inhibitor of Type I Interferon Response in Models of Oncolytic Therapy by Vesicular Stomatitis Virus. Int J Mol Sci 2022; 23:ijms23095244. [PMID: 35563635 PMCID: PMC9102229 DOI: 10.3390/ijms23095244] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/29/2022] [Accepted: 05/06/2022] [Indexed: 11/16/2022] Open
Abstract
Cancer cell lines responded differentially to type I interferon treatment in models of oncolytic therapy using vesicular stomatitis virus (VSV). Two opposite cases were considered in this study, glioblastoma DBTRG-05MG and osteosarcoma HOS cell lines exhibiting resistance and sensitivity to VSV after the treatment, respectively. Type I interferon responses were compared for these cell lines by integrative analysis of the transcriptome, proteome, and RNA editome to identify molecular factors determining differential effects observed. Adenosine-to-inosine RNA editing was equally induced in both cell lines. However, transcriptome analysis showed that the number of differentially expressed genes was much higher in DBTRG-05MG with a specific enrichment in inflammatory proteins. Further, it was found that two genes, EGFR and HER2, were overexpressed in HOS cells compared with DBTRG-05MG, supporting recent reports that EGF receptor signaling attenuates interferon responses via HER2 co-receptor activity. Accordingly, combined treatment of cells with EGF receptor inhibitors such as gefitinib and type I interferon increases the resistance of sensitive cell lines to VSV. Moreover, sensitive cell lines had increased levels of HER2 protein compared with non-sensitive DBTRG-05MG. Presumably, the level of this protein expression in tumor cells might be a predictive biomarker of their resistance to oncolytic viral therapy.
Collapse
|
15
|
Lipatova AV, Soboleva AV, Gorshkov VA, Bubis JA, Solovyeva EM, Krasnov GS, Kochetkov DV, Vorobyev PO, Ilina IY, Moshkovskii SA, Kjeldsen F, Gorshkov MV, Chumakov PM, Tarasova IA. Multi-Omics Analysis of Glioblastoma Cells' Sensitivity to Oncolytic Viruses. Cancers (Basel) 2021; 13:cancers13215268. [PMID: 34771433 PMCID: PMC8582528 DOI: 10.3390/cancers13215268] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/11/2021] [Accepted: 10/15/2021] [Indexed: 12/28/2022] Open
Abstract
Simple Summary This study aims to uncover the contribution of interferon-dependent antiviral mechanisms preserved in tumor cells to the resistance of glioblastoma multiforme cells to oncolytic viruses. To characterize the functionality of interferon signaling, we used omics profiling and titration-based measurements of cell sensitivity to a panel of viruses of diverse oncolytic potential. This study shows why patient-derived glioblastoma cultures can acquire increased resistance to oncolytic viruses in the presence of interferons and suggests an approach to ranking glioblastoma cells by the acquired resistance. Our findings are important for monitoring the oncolytic potential of viruses to overcome IFN-induced resistance of tumor cells and contribute to successful therapy. Abstract Oncolytic viruses have gained momentum in the last decades as a promising tool for cancer treatment. Despite the progress, only a fraction of patients show a positive response to viral therapy. One of the key variable factors contributing to therapy outcomes is interferon-dependent antiviral mechanisms in tumor cells. Here, we evaluated this factor using patient-derived glioblastoma multiforme (GBM) cultures. Cell response to the type I interferons’ (IFNs) stimulation was characterized at mRNA and protein levels. Omics analysis revealed that GBM cells overexpress interferon-stimulated genes (ISGs) and upregulate their proteins, similar to the normal cells. A conserved molecular pattern unambiguously differentiates between the preserved and defective responses. Comparing ISGs’ portraits with titration-based measurements of cell sensitivity to a panel of viruses, the “strength” of IFN-induced resistance acquired by GBM cells was ranked. The study demonstrates that suppressing a single ISG and encoding an essential antiviral protein, does not necessarily increase sensitivity to viruses. Conversely, silencing IFIT3 and PLSCR1 genes in tumor cells can negatively affect the internalization of vesicular stomatitis and Newcastle disease viruses. We present evidence of a complex relationship between the interferon response genes and other factors affecting the sensitivity of tumor cells to viruses.
Collapse
Affiliation(s)
- Anastasiya V. Lipatova
- V. A. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.V.L.); (A.V.S.); (G.S.K.); (D.V.K.); (P.O.V.)
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Alesya V. Soboleva
- V. A. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.V.L.); (A.V.S.); (G.S.K.); (D.V.K.); (P.O.V.)
| | - Vladimir A. Gorshkov
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark; (V.A.G.); (F.K.)
| | - Julia A. Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia; (J.A.B.); (E.M.S.); (M.V.G.)
| | - Elizaveta M. Solovyeva
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia; (J.A.B.); (E.M.S.); (M.V.G.)
| | - George S. Krasnov
- V. A. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.V.L.); (A.V.S.); (G.S.K.); (D.V.K.); (P.O.V.)
| | - Dmitry V. Kochetkov
- V. A. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.V.L.); (A.V.S.); (G.S.K.); (D.V.K.); (P.O.V.)
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Pavel O. Vorobyev
- V. A. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.V.L.); (A.V.S.); (G.S.K.); (D.V.K.); (P.O.V.)
| | - Irina Y. Ilina
- Federal Research and Clinical Center of Physical-Chemical Medicine, 119435 Moscow, Russia; (I.Y.I.); (S.A.M.)
| | - Sergei A. Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, 119435 Moscow, Russia; (I.Y.I.); (S.A.M.)
- Department of Biochemistry, Medico-Biological Faculty, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Frank Kjeldsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark; (V.A.G.); (F.K.)
| | - Mikhail V. Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia; (J.A.B.); (E.M.S.); (M.V.G.)
| | - Peter M. Chumakov
- V. A. Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (A.V.L.); (A.V.S.); (G.S.K.); (D.V.K.); (P.O.V.)
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
- Correspondence: (P.M.C.); (I.A.T.)
| | - Irina A. Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia; (J.A.B.); (E.M.S.); (M.V.G.)
- Correspondence: (P.M.C.); (I.A.T.)
| |
Collapse
|
16
|
Levitsky LI, Bubis JA, Gorshkov MV, Tarasova IA. AA_stat: Intelligent profiling of in vivo and in vitro modifications from open search results. J Proteomics 2021; 248:104350. [PMID: 34389500 DOI: 10.1016/j.jprot.2021.104350] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/21/2021] [Accepted: 08/04/2021] [Indexed: 11/18/2022]
Abstract
Characterization of post-translational modifications is among the most challenging tasks in tandem mass spectrometry-based proteomics which has yet to find an efficient solution. The ultra-tolerant (open) database search attempts to meet this challenge. However, interpretation of the mass shifts observed in open search still requires an effective and automated solution. We have previously introduced the AA_stat tool for analysis of amino acid frequencies at different mass shifts and generation of hypotheses on unaccounted in vitro modifications. Here, we report on the new version of AA_stat, which now complements amino acid frequency statistics with a number of new features: (1) MS/MS-based localization of mass shifts and localization scoring, including shifts which are the sum of modifications; (2) inferring fixed modifications to increase method sensitivity; (3) inferring monoisotopic peak assignment errors and variable modifications based on abundant mass shift localizations to increase the yield of closed search; (4) new mass calibration algorithm to account for partial systematic shifts; (5) interactive integration of all results and a rated list of possible mass shift interpretations. With these options, we improve interpretation of open search results and demonstrate the utility of AA_stat for profiling of abundant and rare amino acid modifications. AA_stat is implemented in Python as an open-source command-line tool available at https://github.com/SimpleNumber/aa_stat. SIGNIFICANCE: Mass spectrometry-based PTM characterization has a long history, yet most of the methods rely on a priori knowledge of modifications of interest and do not provide a whole proteome modification landscape in a blind manner. The open database search is an efficient attempt to address this challenge by identifying peptides with mass shifts corresponding to possible modifications. Then, interpreting these mass shifts is required. Therefore, development of bioinformatics software for post-processing of the open search results, which is capable of detection and accurate annotation of new or unexpected modifications, from characterization of sample preparation efficiency and quality control to discovery of rare post-translational modifications, is of high importance.
Collapse
Affiliation(s)
- Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Irina A Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia.
| |
Collapse
|
17
|
Gabdrakhmanov IT, Gorshkov MV, Tarasova IA. Proteomics of Cellular Response to Stress: Taking Control of False Positive Results. BIOCHEMISTRY (MOSCOW) 2021; 86:338-349. [PMID: 33838633 DOI: 10.1134/s0006297921030093] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
One of the main goals of quantitative proteomics is molecular profiling of cellular response to stress at the protein level. To perform this profiling, statistical analysis of experimental data involves multiple testing of a hypothesis about the equality of protein concentrations between the cells under normal and stress conditions. This analysis is then associated with the multiple testing problem dealing with the increased chance of obtaining false positive results. A number of solutions to this problem are known, yet, they may lead to the loss of potentially important biological information when applied with commonly accepted thresholds of statistical significance. Using the proteomic data obtained earlier for the yeast samples containing proteins at known concentrations and the biological models of early and late cellular responses to stress, we analyzed dependences of distributions of false positive and false negative rates on the protein fold changes and thresholds of statistical significance. Based on the analysis of the density of data points in the volcano plots, Benjamini-Hochberg method, and gene ontology analysis, visual approach for optimization of the statistical threshold and selection of the differentially regulated proteins has been suggested, which could be useful for researchers working in the field of quantitative proteomics.
Collapse
Affiliation(s)
| | - Mikhail V Gorshkov
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, 141701, Russia.,Talrose Institute for Energy Problems of Chemical Physics, Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Irina A Tarasova
- Talrose Institute for Energy Problems of Chemical Physics, Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia.
| |
Collapse
|
18
|
Ivanov MV, Solovyeva EM, Bubis JA, Gorshkov MV. Improving the Protein Inference from Bottom-Up Proteomic Data Using Identifications from MS1 Spectra. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:1258-1262. [PMID: 33900766 DOI: 10.1021/jasms.1c00061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Protein inference is one of the crucial steps in proteome characterization using a bottom-up approach. Multiple algorithms to solve the problem are focused on extensive analysis of shared peptides identified from fragmentation mass spectra (MS/MS). However, many protein homologues with a similar amino acid sequence typically have identical lists of identified peptides due to the problem of proteome undersampling in a bottom-up approach and, thus, cannot be distinguished by existing protein inference methods. Here, we propose the use of peptide feature information extracted from precursor mass spectra to assist in identification of proteins otherwise indistinguishable from MS/MS. The proposed method was integrated with a protein inference algorithm based on the parsimony principle and built-in in the postsearch utility Scavager. The results demonstrate increasing accuracy and efficiency of homologous protein identifications for the well characterized data sets including the one with known protein sequences from iPRG-2016 study.
Collapse
Affiliation(s)
- Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Building 2, Moscow 119334, Russia
| | - Elizaveta M Solovyeva
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Building 2, Moscow 119334, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Building 2, Moscow 119334, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Building 2, Moscow 119334, Russia
| |
Collapse
|
19
|
Liu Z, Ma A, Mathé E, Merling M, Ma Q, Liu B. Network analyses in microbiome based on high-throughput multi-omics data. Brief Bioinform 2021; 22:1639-1655. [PMID: 32047891 PMCID: PMC7986608 DOI: 10.1093/bib/bbaa005] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 01/07/2020] [Accepted: 01/08/2020] [Indexed: 02/06/2023] Open
Abstract
Together with various hosts and environments, ubiquitous microbes interact closely with each other forming an intertwined system or community. Of interest, shifts of the relationships between microbes and their hosts or environments are associated with critical diseases and ecological changes. While advances in high-throughput Omics technologies offer a great opportunity for understanding the structures and functions of microbiome, it is still challenging to analyse and interpret the omics data. Specifically, the heterogeneity and diversity of microbial communities, compounded with the large size of the datasets, impose a tremendous challenge to mechanistically elucidate the complex communities. Fortunately, network analyses provide an efficient way to tackle this problem, and several network approaches have been proposed to improve this understanding recently. Here, we systemically illustrate these network theories that have been used in biological and biomedical research. Then, we review existing network modelling methods of microbial studies at multiple layers from metagenomics to metabolomics and further to multi-omics. Lastly, we discuss the limitations of present studies and provide a perspective for further directions in support of the understanding of microbial communities.
Collapse
Affiliation(s)
- Zhaoqian Liu
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Anjun Ma
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Ewy Mathé
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Marlena Merling
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH 43210, USA
| | - Bingqiang Liu
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH 43210, USA
| |
Collapse
|
20
|
Ivanov MV, Bubis JA, Gorshkov V, Abdrakhimov DA, Kjeldsen F, Gorshkov MV. Boosting MS1-only Proteomics with Machine Learning Allows 2000 Protein Identifications in Single-Shot Human Proteome Analysis Using 5 min HPLC Gradient. J Proteome Res 2021; 20:1864-1873. [PMID: 33720732 DOI: 10.1021/acs.jproteome.0c00863] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Proteome-wide analyses rely on tandem mass spectrometry and the extensive separation of proteolytic mixtures. This imposes considerable instrumental time consumption, which is one of the main obstacles in the broader acceptance of proteomics in biomedical and clinical research. Recently, we presented a fast proteomic method termed DirectMS1 based on ultrashort LC gradients as well as MS1-only mass spectra acquisition and data processing. The method allows significant reduction of the proteome-wide analysis time to a few minutes at the depth of quantitative proteome coverage of 1000 proteins at 1% false discovery rate (FDR). In this work, to further increase the capabilities of the DirectMS1 method, we explored the opportunities presented by the recent progress in the machine-learning area and applied the LightGBM decision tree boosting algorithm to the scoring of peptide feature matches when processing MS1 spectra. Furthermore, we integrated the peptide feature identification algorithm of DirectMS1 with the recently introduced peptide retention time prediction utility, DeepLC. Additional approaches to improve the performance of the DirectMS1 method are discussed and demonstrated, such as using FAIMS for gas-phase ion separation. As a result of all improvements to DirectMS1, we succeeded in identifying more than 2000 proteins at 1% FDR from the HeLa cell line in a 5 min gradient LC-FAIMS/MS1 analysis. The data sets generated and analyzed during the current study have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD023977.
Collapse
Affiliation(s)
- Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
| | - Vladimir Gorshkov
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark
| | - Daniil A Abdrakhimov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia.,Moscow Institute of Physics and Technology, Institutsky lane 9, Dolgoprudny, Moscow Region 141700, Russia
| | - Frank Kjeldsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense M, Denmark
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
| |
Collapse
|
21
|
Abdrakhimov DA, Bubis JA, Gorshkov V, Kjeldsen F, Gorshkov MV, Ivanov MV. Biosaur: An open-source Python software for liquid chromatography-mass spectrometry peptide feature detection with ion mobility support. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2021:e9045. [PMID: 33450063 DOI: 10.1002/rcm.9045] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 12/20/2020] [Accepted: 01/04/2021] [Indexed: 06/12/2023]
Abstract
RATIONALE One of the important steps in initial data processing of peptide mass spectra is the detection of peptide features in full-range mass spectra. Ion mobility offers advantages over previous methods performing this detection by providing an additional structure-specific separation dimension. However, there is a lack of open-source software that utilizes these advantages and detects peptide features in mass spectra acquired along with ion mobility data using new instruments such as timsTOF and/or FAIMS-Orbitrap. METHODS Recently, a utility called Dinosaur was presented, which provides an efficient way for feature detection in peptide ion mass spectra. In this work we extended its functionality by developing Biosaur software to fully employ the additional information provided by ion mobility data. Biosaur was developed using the Python 3.8 programming language. RESULTS Biosaur supports the processing of data acquired using mass spectrometers with ion mobility capabilities, specifically timsTOF and FAIMS. In addition, it processes mass spectra obtained in negative ion mode and reports cosine correlation table for peptide features which is useful for differentiation between in-source fragments and semi-tryptic peptides. CONCLUSIONS Biosaur is a utility for detecting peptide features in liquid chromatography-mass spectra with ion mobility and negative ion supports. The software is distributed with an open-source APACHE 2.0 license and is freely available on Github: https://github.com/abdrakhimov1/Biosaur.
Collapse
Affiliation(s)
- Daniil A Abdrakhimov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow, 119334, Russia
- Moscow Institute of Physics and Technology, National Research University, G. Dolgoprudny, Institutsky Lane 9, Dolgoprudnyj, RU, 141701, Russia
| | - Julia A Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow, 119334, Russia
| | - Vladimir Gorshkov
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M, DK-5230, Denmark
| | - Frank Kjeldsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M, DK-5230, Denmark
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow, 119334, Russia
| | - Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow, 119334, Russia
| |
Collapse
|
22
|
Solovyeva EM, Moshkovskii SA, Gorshkov MV. Identification-Free Control over the Precursor Isotopic Mass Misassignment in Orbitrap-Based Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:218-224. [PMID: 33119294 DOI: 10.1021/jasms.0c00281] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Selection of a precursor ion from a peptide isotopic cluster to obtain a fragmentation mass spectrum is a crucial step in data-dependent proteome analysis. However, the monoisotopic mass assignment performed in this step is often an issue confronted by the data acquisition software of hybrid Orbitrap FTMS that is most widely used in proteomics. To address the problem, many data processing tools, such as raw data converters and search engines, have optional accounting for the precursor mass shift due to the isotopic error. These solutions require additional data preprocessing steps and lead to an increase in the search space, thus making the analysis longer and/or less reliable. In this work, we processed 100 Orbitrap-based LC-MS/MS runs from 10 publicly available data sets to examine the rate of precursor isotope misassignment. The effect from taking the isotope error into account during the search on the number of identified peptides varied in a wide range from 0 to 33%. Thus, it may be tempting to spend extra time before or during a search to account for the mass assignment issue. Alternatively, this effect can be predicted a priori using an identification-free metric, which can be a part of data quality control software. Based on the results obtained in this work, we propose such a metric be further added into the visual and intuitive quality control software, viQC, developed previously and available at https://github.com/lisavetasol/viQC. It takes about a minute to calculate and plot nine quality metrics, including the proposed one for typical proteome analysis.
Collapse
Affiliation(s)
- Elizaveta M Solovyeva
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region 141701, Russia
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| | - Sergei A Moshkovskii
- Pirogov Russian National Research Medical University, Moscow 117997, Russia
- Federal Research and Clinical Center of Physical-Chemical Medicine, Moscow 119435, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| |
Collapse
|
23
|
New Insectotoxin from Tibellus Oblongus Spider Venom Presents Novel Adaptation of ICK Fold. Toxins (Basel) 2021; 13:toxins13010029. [PMID: 33406803 PMCID: PMC7824768 DOI: 10.3390/toxins13010029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 12/21/2020] [Accepted: 12/30/2020] [Indexed: 11/17/2022] Open
Abstract
The Tibellus oblongus spider is an active predator that does not spin webs and remains poorly investigated in terms of venom composition. Here, we present a new toxin, named Tbo-IT2, predicted by cDNA analysis of venom glands transcriptome. The presence of Tbo-IT2 in the venom was confirmed by proteomic analyses using the LC-MS and MS/MS techniques. The distinctive features of Tbo-IT2 are the low similarity of primary structure with known animal toxins and the unusual motif of 10 cysteine residues distribution. Recombinant Tbo-IT2 (rTbo-IT2), produced in E. coli using the thioredoxin fusion protein strategy, was structurally and functionally studied. rTbo-IT2 showed insecticidal activity on larvae of the housefly Musca domestica (LD100 200 μg/g) and no activity on the panel of expressed neuronal receptors and ion channels. The spatial structure of the peptide was determined in a water solution by NMR spectroscopy. The Tbo-IT2 structure is a new example of evolutionary adaptation of a well-known inhibitor cystine knot (ICK) fold to 5 disulfide bonds configuration, which determines additional conformational stability and gives opportunities for insectotoxicity and probably some other interesting features.
Collapse
|
24
|
Kuznetsova KG, Levitsky LI, Pyatnitskiy MA, Ilina IY, Bubis JA, Solovyeva EM, Zgoda VG, Gorshkov MV, Moshkovskii SA. Cysteine alkylation methods in shotgun proteomics and their possible effects on methionine residues. J Proteomics 2020; 231:104022. [PMID: 33096305 DOI: 10.1016/j.jprot.2020.104022] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 10/06/2020] [Accepted: 10/15/2020] [Indexed: 01/06/2023]
Abstract
In order to optimize sample preparation for shotgun proteomics, we compared four cysteine alkylating agents: iodoacetamide, chloroacetamide, 4-vinylpyridine and methyl methanethiosulfonate, and estimated their effects on the results of proteome analysis. Because alkylation may result in methionine modification in vitro, proteomics data were searched for methionine to isothreonine conversions, which may mimic genomic methionine to threonine substitutions found in proteogenomic analyses. We found that chloroacetamide was superior to the other reagents in terms of the number of identified peptides and undesirable off-site reactions. Among the reagents evaluated, iodoacetamide increased the rate of methionine-to-isothreonine conversion, especially if the sample was prepared in gel. The presence of proline following methionine in a protein sequence increased the modification rate as well. Generally, the methionine-to-isothreonine conversion events were relatively rare, but should be taken into account in proteogenomic studies when searching for single nucleotide polymorphism events at the protein level. Additionally, we have evaluated other methionine modifications, such as oxidation and carbamidomethylation. We found that carbamidomethylation may affect up to 80% of peptides containing methionine under the condition of iodoacetamide alkylation. In this case, carbamidomethylation of methionine is more common than oxidation and should be accounted for as a variable modification during proteomic search. SIGNIFICANCE: One of the most trending questions in bottom-up proteomics is the depth of proteome profiling, in other words, the coverage of proteins by identified tryptic peptides. In proteogenomics, where the identification of a single peptide, e.g. bearing an amino acid substitution, may be of interest, high sequence coverage is especially important. Chemical modifications during sample preparation may mimic biologically significant coding mutations at the proteome level. A typical example of such modification is methionine to isothreonine conversion during alkylation, which mimics methionine to threonine substitution in protein sequences due to respective genomic mutations. Therefore, the studies on the proper selection of alkylating reagents which balance the cysteine alkylation efficiency and the extent of methionine conversion upon conventional proteomic sample preparation workflow are crucial for the outcome of proteogenomic analyses and should present a general interest for the proteomic community.
Collapse
Affiliation(s)
- Ksenia G Kuznetsova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.
| | - Lev I Levitsky
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Mikhail A Pyatnitskiy
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia; Institute of Biomedical Chemistry, 10, Pogodinskaya, Moscow 119121, Russia
| | - Irina Y Ilina
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Julia A Bubis
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Elizaveta M Solovyeva
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Victor G Zgoda
- Institute of Biomedical Chemistry, 10, Pogodinskaya, Moscow 119121, Russia; Skolkovo Institute of Science and Technology, 30, bld. 1, Bolshoy Boulevard, Moscow 121205, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Sergei A Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia; Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia.
| |
Collapse
|
25
|
Kliuchnikova AA, Goncharov AO, Levitsky LI, Pyatnitskiy MA, Novikova SE, Kuznetsova KG, Ivanov MV, Ilina IY, Farafonova TE, Zgoda VG, Gorshkov MV, Moshkovskii SA. Proteome-Wide Analysis of ADAR-Mediated Messenger RNA Editing during Fruit Fly Ontogeny. J Proteome Res 2020; 19:4046-4060. [PMID: 32866021 DOI: 10.1021/acs.jproteome.0c00347] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Adenosine-to-inosine RNA editing is an enzymatic post-transcriptional modification which modulates immunity and neural transmission in multicellular organisms. In particular, it involves editing of mRNA codons with the resulting amino acid substitutions. We identified such sites for developmental proteomes of Drosophila melanogaster at the protein level using available data for 15 stages of fruit fly development from egg to imago and 14 time points of embryogenesis. In total, 40 sites were obtained, each belonging to a unique protein, including four sites related to embryogenesis. The interactome analysis has revealed that the majority of the editing-recoded proteins were associated with synaptic vesicle trafficking and actomyosin organization. Quantitation data analysis suggested the existence of a phase-specific RNA editing regulation with yet unknown mechanisms. These findings supported the transcriptome analysis results, which showed that a burst in the RNA editing occurs during insect metamorphosis from pupa to imago. Finally, targeted proteomic analysis was performed to quantify editing-recoded and genomically encoded versions of five proteins in brains of larvae, pupae, and imago insects, which showed a clear tendency toward an increase in the editing rate for each of them. These results will allow a better understanding of the protein role in physiological effects of RNA editing.
Collapse
Affiliation(s)
- Anna A Kliuchnikova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| | - Anton O Goncharov
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Institute of Biomedical Chemistry, 10, Pogodinskaya, Moscow 119121, Russia
| | - Lev I Levitsky
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Mikhail A Pyatnitskiy
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Institute of Biomedical Chemistry, 10, Pogodinskaya, Moscow 119121, Russia
| | | | - Ksenia G Kuznetsova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Mark V Ivanov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Irina Y Ilina
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | | | - Victor G Zgoda
- Institute of Biomedical Chemistry, 10, Pogodinskaya, Moscow 119121, Russia.,Skolkovo Institute of Science and Technology, 30, bld. 1, Bolshoy Boulevard, Moscow 121205, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 1, Leninsky Prospect, Moscow 119334, Russia
| | - Sergei A Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| |
Collapse
|
26
|
Kurpe SR, Grishin SY, Surin AK, Selivanova OM, Fadeev RS, Dzhus YF, Gorbunova EY, Mustaeva LG, Azev VN, Galzitskaya OV. Antimicrobial and Amyloidogenic Activity of Peptides Synthesized on the Basis of the Ribosomal S1 Protein from Thermus Thermophilus. Int J Mol Sci 2020; 21:ijms21176382. [PMID: 32887478 PMCID: PMC7504387 DOI: 10.3390/ijms21176382] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 08/26/2020] [Accepted: 08/29/2020] [Indexed: 12/15/2022] Open
Abstract
Controlling the aggregation of vital bacterial proteins could be one of the new research directions and form the basis for the search and development of antibacterial drugs with targeted action. Such approach may be considered as an alternative one to antibiotics. Amyloidogenic regions can, like antibacterial peptides, interact with the "parent" protein, for example, ribosomal S1 protein (specific only for bacteria), and interfere with its functioning. The aim of the work was to search for peptides based on the ribosomal S1 protein from T. thermophilus, exhibiting both aggregation and antibacterial properties. The biological system of the response of Gram-negative bacteria T. thermophilus to the action of peptides was characterized. Among the seven studied peptides, designed based on the S1 protein sequence, the R23I (modified by the addition of HIV transcription factor fragment for bacterial cell penetration), R23T (modified), and V10I (unmodified) peptides have biological activity that inhibits the growth of T. thermophilus cells, that is, they have antimicrobial activity. But, only the R23I peptide had the most pronounced activity comparable with the commercial antibiotics. We have compared the proteome of peptide-treated and intact T. thermophilus cells. These important data indicate a decrease in the level of energy metabolism and anabolic processes, including the processes of biosynthesis of proteins and nucleic acids. Under the action of 20 and 50 μg/mL R23I, a decrease in the number of proteins in T. thermophilus cells was observed and S1 ribosomal protein was absent. The obtained results are important for understanding the mechanism of amyloidogenic peptides with antimicrobial activity and can be used to develop new and improved analogues.
Collapse
Affiliation(s)
- Stanislav R. Kurpe
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (S.R.K.); (S.Y.G.); (A.K.S.); (O.M.S.); (Y.F.D.)
| | - Sergei Yu. Grishin
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (S.R.K.); (S.Y.G.); (A.K.S.); (O.M.S.); (Y.F.D.)
| | - Alexey K. Surin
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (S.R.K.); (S.Y.G.); (A.K.S.); (O.M.S.); (Y.F.D.)
- The Branch of the Institute of Bioorganic Chemistry, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (E.Y.G.); (L.G.M.); (V.N.A.)
- State Research Center for Applied Microbiology and Biotechnology, 142279 Obolensk, Moscow Region, Russia
| | - Olga M. Selivanova
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (S.R.K.); (S.Y.G.); (A.K.S.); (O.M.S.); (Y.F.D.)
| | - Roman S. Fadeev
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russian;
| | - Ylyana F. Dzhus
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (S.R.K.); (S.Y.G.); (A.K.S.); (O.M.S.); (Y.F.D.)
| | - Elena Yu. Gorbunova
- The Branch of the Institute of Bioorganic Chemistry, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (E.Y.G.); (L.G.M.); (V.N.A.)
| | - Leila G. Mustaeva
- The Branch of the Institute of Bioorganic Chemistry, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (E.Y.G.); (L.G.M.); (V.N.A.)
| | - Vyacheslav N. Azev
- The Branch of the Institute of Bioorganic Chemistry, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (E.Y.G.); (L.G.M.); (V.N.A.)
| | - Oxana V. Galzitskaya
- Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia; (S.R.K.); (S.Y.G.); (A.K.S.); (O.M.S.); (Y.F.D.)
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russian;
- Correspondence:
| |
Collapse
|
27
|
Is It Possible to Find Needles in a Haystack? Meta-Analysis of 1000+ MS/MS Files Provided by the Russian Proteomic Consortium for Mining Missing Proteins. Proteomes 2020; 8:proteomes8020012. [PMID: 32456206 PMCID: PMC7356824 DOI: 10.3390/proteomes8020012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 05/18/2020] [Accepted: 05/19/2020] [Indexed: 12/04/2022] Open
Abstract
Despite direct or indirect efforts of the proteomic community, the fraction of blind spots on the protein map is still significant. Almost 11% of human genes encode missing proteins; the existence of which proteins is still in doubt. Apparently, proteomics has reached a stage when more attention and curiosity need to be exerted in the identification of every novel protein in order to expand the unusual types of biomaterials and/or conditions. It seems that we have exhausted the current conventional approaches to the discovery of missing proteins and may need to investigate alternatives. Here, we present an approach to deciphering missing proteins based on the use of non-standard methodological solutions and encompassing diverse MS/MS data, obtained for rare types of biological samples by members of the Russian Proteomic community in the last five years. These data were re-analyzed in a uniform manner by three search engines, which are part of the SearchGUI package. The study resulted in the identification of two missing and five uncertain proteins detected with two peptides. Moreover, 149 proteins were detected with a single proteotypic peptide. Finally, we analyzed the gene expression levels to suggest feasible targets for further validation of missing and uncertain protein observations, which will fully meet the requirements of the international consortium. The MS data are available on the ProteomeXchange platform (PXD014300).
Collapse
|
28
|
Ivanov MV, Bubis JA, Gorshkov V, Tarasova IA, Levitsky LI, Lobas AA, Solovyeva EM, Pridatchenko ML, Kjeldsen F, Gorshkov MV. DirectMS1: MS/MS-Free Identification of 1000 Proteins of Cellular Proteomes in 5 Minutes. Anal Chem 2020; 92:4326-4333. [DOI: 10.1021/acs.analchem.9b05095] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- Mark V. Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Julia A. Bubis
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vladimir Gorshkov
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M DK-5230, Denmark
| | - Irina A. Tarasova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Lev I. Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Anna A. Lobas
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Elizaveta M. Solovyeva
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Marina L. Pridatchenko
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Frank Kjeldsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M DK-5230, Denmark
| | - Mikhail V. Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
- Moscow Institute of Physics and Technology (State University), 141700 Dolgoprudny, Russia
| |
Collapse
|
29
|
Solovyeva EM, Lobas AA, Surin AK, Levitsky LI, Gorshkov VA, Gorshkov MV. viQC: Visual and Intuitive Quality Control for Mass Spectrometry-Based Proteome Analysis. JOURNAL OF ANALYTICAL CHEMISTRY 2019. [DOI: 10.1134/s1061934819140119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
30
|
Lisitsa AV, Petushkova NA, Levitsky LI, Zgoda VG, Larina OV, Kisrieva YS, Frankevich VE, Gamidov SI. Comparative Analysis of the Performаnce of Mascot and IdentiPy Algorithms on a Benchmark Dataset Obtained by Tandem Mass Spectrometry Analysis of Testicular Biopsies. Mol Biol 2019. [DOI: 10.1134/s0026893319010096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
31
|
Kuznetsova KG, Ivanov MV, Pyatnitskiy MA, Levitsky LI, Ilina IY, Chernobrovkin AL, Zubarev RA, Gorhskov MV, Moshkovskii SA. Brain Proteome of Drosophila melanogaster Is Enriched with Nuclear Proteins. BIOCHEMISTRY (MOSCOW) 2019; 84:71-78. [PMID: 30927528 DOI: 10.1134/s0006297919010097] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The brain proteome of Drosophila melanogaster was characterized by liquid chromatography/high-resolution mass spectrometry and compared to the earlier characterized Drosophila whole-body and head proteomes. Raw data for all the proteomes were processed in a similar manner. Approximately 4000 proteins were identified in the brain proteome that represented, as expected, the subsets of the head and body proteomes. However, after thorough data curation, we reliably identified 24 proteins unique for the brain proteome; 13 of them have never been detected before at the protein level. Fourteen of 24 identified proteins have been annotated as nuclear proteins. Comparison of three used datasets by label-free quantitation showed statistically significant enrichment of the brain proteome with nuclear proteins. Therefore, we recommend the use of isolated brain preparations in the studies of Drosophila nuclear proteins.
Collapse
Affiliation(s)
- K G Kuznetsova
- Institute of Biomedical Chemistry, Moscow, 119121, Russia
| | - M V Ivanov
- Institute of Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - M A Pyatnitskiy
- Institute of Biomedical Chemistry, Moscow, 119121, Russia.,Higher School of Economics, Moscow, 101000, Russia
| | - L I Levitsky
- Institute of Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - I Y Ilina
- Institute of Biomedical Chemistry, Moscow, 119121, Russia
| | | | - R A Zubarev
- Karolinska Institutet, Stockholm, SE-171 77, Sweden.,Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - M V Gorhskov
- Institute of Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - S A Moshkovskii
- Institute of Biomedical Chemistry, Moscow, 119121, Russia. .,Pirogov Russian National Research Medical University (RNRMU), Moscow, 117997, Russia
| |
Collapse
|
32
|
Klein J, Zaia J. psims - A Declarative Writer for mzML and mzIdentML for Python. Mol Cell Proteomics 2019; 18:571-575. [PMID: 30563850 PMCID: PMC6398200 DOI: 10.1074/mcp.rp118.001070] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 12/12/2018] [Indexed: 01/04/2023] Open
Abstract
mzML and mzIdentML are commonly used, powerful tools for representing mass spectrometry data and derived identification information. These formats are complex, requiring non-trivial logic to translate data into the appropriate representation. Most published implementations are tightly coupled to data structures. The most complete implementations are written in compiled languages that cannot expose the complete flexibility of the implementation to external programs or bindings. To our knowledge, there are no complete implementations for mzML or mzIdentML available to scripting languages like Python or R. We present psims, a library written in Python for writing mzML and mzIdentML. The library allows writing either XML format using built-in Python data structures. It includes a controlled vocabulary resolution system to simplify the encoding process and an identity tracking system to manage entity relationships. The source code is available at https://github.com/mobiusklein/psims, and through the Python Package Index as psims, licensed under the Apache 2 common license.
Collapse
Affiliation(s)
- Joshua Klein
- From the ‡Program for Bioinformatics, Boston University, Boston, Massachusetts 02215
| | - Joseph Zaia
- From the ‡Program for Bioinformatics, Boston University, Boston, Massachusetts 02215;
- §Department of Biochemistry, Boston University, Boston, Massachusetts 02118
| |
Collapse
|
33
|
Levitsky LI, Klein JA, Ivanov MV, Gorshkov MV. Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework. J Proteome Res 2019; 18:709-714. [PMID: 30576148 DOI: 10.1021/acs.jproteome.8b00717] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Many of the novel ideas that drive today's proteomic technologies are focused essentially on experimental or data-processing workflows. The latter are implemented and published in a number of ways, from custom scripts and programs, to projects built using general-purpose or specialized workflow engines; a large part of routine data processing is performed manually or with custom scripts that remain unpublished. Facilitating the development of reproducible data-processing workflows becomes essential for increasing the efficiency of proteomic research. To assist in overcoming the bioinformatics challenges in the daily practice of proteomic laboratories, 5 years ago we developed and announced Pyteomics, a freely available open-source library providing Python interfaces to proteomic data. We summarize the new functionality of Pyteomics developed during the time since its introduction.
Collapse
Affiliation(s)
- Lev I Levitsky
- Moscow Institute of Physics and Technology , Dolgoprudny, Moscow Region 141701 , Russia.,V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| | - Joshua A Klein
- Bioinformatics Program , Boston University , Boston , Massachusetts 02215 , United States
| | - Mark V Ivanov
- V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| |
Collapse
|
34
|
Balakireva AV, Deviatkin AA, Zgoda VG, Kartashov MI, Zhemchuzhina NS, Dzhavakhiya VG, Golovin AV, Zamyatnin AA. Proteomics Analysis Reveals That Caspase-Like and Metacaspase-Like Activities Are Dispensable for Activation of Proteases Involved in Early Response to Biotic Stress in Triticum aestivum L. Int J Mol Sci 2018; 19:ijms19123991. [PMID: 30544979 PMCID: PMC6320887 DOI: 10.3390/ijms19123991] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 12/04/2018] [Accepted: 12/08/2018] [Indexed: 12/15/2022] Open
Abstract
Plants, including Triticum aestivum L., are constantly attacked by various pathogens which induce immune responses. Immune processes in plants are tightly regulated by proteases from different families within their degradome. In this study, a wheat degradome was characterized. Using profile hidden Markov model (HMMer) algorithm and Pfam database, comprehensive analysis of the T. aestivum genome revealed a large number of proteases (1544 in total) belonging to the five major protease families: serine, cysteine, threonine, aspartic, and metallo-proteases. Mass-spectrometry analysis revealed a 30% difference between degradomes of distinct wheat cultivars (Khakasskaya and Darya), and infection by biotrophic (Puccinia recondita Rob. ex Desm f. sp. tritici) or necrotrophic (Stagonospora nodorum) pathogens induced drastic changes in the presence of proteolytic enzymes. This study shows that an early immune response to biotic stress is associated with the same core of proteases from the C1, C48, C65, M24, M41, S10, S9, S8, and A1 families. Further liquid chromatography-mass spectrometry (LC-MS) analysis of the detected protease-derived peptides revealed that infection by both pathogens enhances overall proteolytic activity in wheat cells and leads to activation of proteolytic cascades. Moreover, sites of proteolysis were identified within the proteases, which probably represent targets of autocatalytic activation, or hydrolysis by another protease within the proteolytic cascades. Although predicted substrates of metacaspase-like and caspase-like proteases were similar in biotrophic and necrotrophic infections, proteolytic activation of proteases was not found to be associated with metacaspase-like and caspase-like activities. These findings indicate that the response of T. aestivum to biotic stress is regulated by unique mechanisms.
Collapse
Affiliation(s)
- Anastasia V Balakireva
- Sechenov First Moscow State Medical University, Institute of Molecular Medicine, Trubetskaya str., 8, bld. 2, Moscow 119991, Russia.
| | - Andrei A Deviatkin
- Sechenov First Moscow State Medical University, Institute of Molecular Medicine, Trubetskaya str., 8, bld. 2, Moscow 119991, Russia.
| | - Victor G Zgoda
- Institute of Biomedical Chemistry, Pogodinskaya str., 10, bld. 8, Moscow 119121, Russia.
| | - Maxim I Kartashov
- All Russian Research Institute of Phytopathology, VNIIF, Bolshie Vyazemi, Odintsovsky distr., Moscow region 143050, Russia.
| | - Natalia S Zhemchuzhina
- All Russian Research Institute of Phytopathology, VNIIF, Bolshie Vyazemi, Odintsovsky distr., Moscow region 143050, Russia.
| | - Vitaly G Dzhavakhiya
- All Russian Research Institute of Phytopathology, VNIIF, Bolshie Vyazemi, Odintsovsky distr., Moscow region 143050, Russia.
| | - Andrey V Golovin
- Sechenov First Moscow State Medical University, Institute of Molecular Medicine, Trubetskaya str., 8, bld. 2, Moscow 119991, Russia.
- Faculty of Bioengineering and Bioinformatics, Moscow State University, Moscow 119992, Russia.
| | - Andrey A Zamyatnin
- Sechenov First Moscow State Medical University, Institute of Molecular Medicine, Trubetskaya str., 8, bld. 2, Moscow 119991, Russia.
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow 119992, Russia.
| |
Collapse
|
35
|
Kovalchik KA, Colborne S, Spencer SE, Sorensen PH, Chen DDY, Morin GB, Hughes CS. RawTools: Rapid and Dynamic Interrogation of Orbitrap Data Files for Mass Spectrometer System Management. J Proteome Res 2018; 18:700-708. [PMID: 30462513 DOI: 10.1021/acs.jproteome.8b00721] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Optimizing the quality of proteomics data collected from a mass spectrometer (MS) requires careful selection of acquisition parameters and proper assessment of instrument performance. Software tools capable of extracting a broad set of information from raw files, including meta, scan, quantification, and identification data, are needed to provide guidance for MS system management. In this work, direct extraction and utilization of these data is demonstrated using RawTools, a standalone tool for extracting meta and scan data directly from raw MS files generated on Thermo Orbitrap instruments. RawTools generates summarized and detailed plain text outputs after parsing individual raw files, including scan rates and durations, duty cycle characteristics, precursor and reporter ion quantification, and chromatography performance. RawTools also contains a diagnostic module that includes an optional "preview" database search for facilitating informed decision-making related to optimization of MS performance based on a variety of metrics. RawTools has been developed in C# and utilizes the Thermo RawFileReader library and thus can process raw MS files with high speed and high efficiency on all major operating systems (Windows, MacOS, Linux). To demonstrate the utility of RawTools, the extraction of meta and scan data from both individual and large collections of raw MS files was carried out to identify problematic characteristics of instrument performance. Taken together, the combined rich feature-set of RawTools with the capability for interrogation of MS and experiment performance makes this software a valuable tool for proteomics researchers.
Collapse
Affiliation(s)
- Kevin A Kovalchik
- Department of Chemistry , University of British Columbia , Vancouver , British Columbia V6T 1Z3 , Canada.,Canada's Michael Smith Genome Sciences Centre , British Columbia Cancer Agency , Vancouver , British Columbia V5Z 1L3 , Canada
| | - Shane Colborne
- Canada's Michael Smith Genome Sciences Centre , British Columbia Cancer Agency , Vancouver , British Columbia V5Z 1L3 , Canada
| | - Sandra Elizabeth Spencer
- Canada's Michael Smith Genome Sciences Centre , British Columbia Cancer Agency , Vancouver , British Columbia V5Z 1L3 , Canada
| | - Poul H Sorensen
- Department of Molecular Oncology , British Columbia Cancer Research Centre , Vancouver , British Columbia V5Z 1L3 , Canada
| | - David D Y Chen
- Department of Chemistry , University of British Columbia , Vancouver , British Columbia V6T 1Z3 , Canada
| | - Gregg B Morin
- Canada's Michael Smith Genome Sciences Centre , British Columbia Cancer Agency , Vancouver , British Columbia V5Z 1L3 , Canada.,Department of Medical Genetics , University of British Columbia , Vancouver , British Columbia V6T 1Z3 , Canada
| | - Christopher S Hughes
- Canada's Michael Smith Genome Sciences Centre , British Columbia Cancer Agency , Vancouver , British Columbia V5Z 1L3 , Canada.,Department of Molecular Oncology , British Columbia Cancer Research Centre , Vancouver , British Columbia V5Z 1L3 , Canada
| |
Collapse
|