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Article ; Online: Identification of Potential Therapeutic Targets on the Level of DNA/mRNAs, Proteins and Metabolites: A Systematic Mapping Review of Scientific Texts' Fragments from Open Targets.

Pogodin, Pavel V / Kiseleva, Olga I / Ilgisonis, Ekaterina V

2023 Volume 45, Issue 4, Page(s) 3406–3418

Abstract: Database records contain useful information, which is readily available, but, unfortunately, limited compared to the source (publications). Our study reviewed the text fragments supporting the association between the biological macromolecules and ... ...

Abstract	Database records contain useful information, which is readily available, but, unfortunately, limited compared to the source (publications). Our study reviewed the text fragments supporting the association between the biological macromolecules and diseases from Open Targets to map them on the biological level of study (DNA/RNA, proteins, metabolites). We screened records using a dictionary containing terms related to the selected levels of study, reviewed 600 hits manually and used machine learning to classify 31,260 text fragments. Our results indicate that association studies between diseases and macromolecules conducted on the level of DNA and RNA prevail, followed by the studies on the level of proteins and metabolites. We conclude that there is a clear need to translate the knowledge from the DNA/RNA level to the evidence on the level of proteins and metabolites. Since genes and their transcripts rarely act in the cell by themselves, more direct evidence may be of greater value for basic and applied research.
Language	English
Publishing date	2023-04-13
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2000024-8
ISSN	1467-3045 ; 1467-3037
ISSN (online)	1467-3045
ISSN	1467-3037
DOI	10.3390/cimb45040223
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Evolution of Protein Functional Annotation: Text Mining Study.

Ilgisonis, Ekaterina V / Pogodin, Pavel V / Kiseleva, Olga I / Tarbeeva, Svetlana N / Ponomarenko, Elena A

Journal of personalized medicine

2022 Volume 12, Issue 3

Abstract: Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of ... ...

Abstract	Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. However, the neXt-CP50 Challenge is more complicated than the missing-protein challenge: the approaches and methods for solving the problem are clear, but neither the concept of protein function nor specific experimental and/or bioinformatics protocols have been standardized to address it. We proposed using a retrospective analysis of the key HPP repository, the neXtProt database, to identify the most frequently used experimental and bioinformatic methods for analyzing protein functions, and the dynamics of accumulation of functional annotations. It has been shown that the dynamics of the increase in the number of proteins with known functions are greater than the progress made in the experimental confirmation of the existence of questionable proteins in the framework of the missing-protein challenge. At the same time, the functional annotation is based on the guilty-by-association postulate, according to which, based on large-scale experiments on API-MS and Y2H, proteins with unknown functions are most likely mapped through "handshakes" to biochemical processes.
Language	English
Publishing date	2022-03-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662248-8
ISSN	2075-4426
ISSN	2075-4426
DOI	10.3390/jpm12030479
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Article: How to catch trends using MeSH terms analysis?

Ilgisonis, Ekaterina V / Pyatnitskiy, Mikhail A / Tarbeeva, Svetlana N / Aldushin, Artem A / Ponomarenko, Elena A

Scientometrics

2022 Volume 127, Issue 4, Page(s) 1953–1967

Abstract: The paper describes a scheme for the comparative analysis of the sets of Pubmed publications. The proposed analysis is based on the comparison of the frequencies of occurrence of keywords-MeSH terms. The purpose of the analysis is to identify MeSH terms ... ...

Abstract	The paper describes a scheme for the comparative analysis of the sets of Pubmed publications. The proposed analysis is based on the comparison of the frequencies of occurrence of keywords-MeSH terms. The purpose of the analysis is to identify MeSH terms that characterize research areas specific to each group of articles, as well as to identify trends-topics on which the number of published works has changed significantly in recent years. The proposed approach was tested by comparing a set of medical publications and a group of articles in the field of personalized medicine. We analyzed about 700 thousand abstracts published in the period 2009-2021 and indexed them with MeSH terms. Topics with increasing research interest have been identified both in the field of medicine in general and specific to personalized medicine. Retrospective analysis of the keywords frequency of occurrence changes has shown the shift of the scientific priorities in this area over the past 10 years. The revealed patterns can be used to predict the relevance and significance of the scientific work direction in the horizon of 3-5 years. The proposed analysis can be scaled in the future for a larger number of groups of publications, as well as adjusted by introducing filters at the stage of sampling (scientific centers, journals, availability of full texts, etc.) or selecting a list of keywords (frequency threshold, use of qualifiers, category of generalizations). Supplementary information: The online version contains supplementary material available at 10.1007/s11192-022-04292-y.
Language	English
Publishing date	2022-02-21
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	435652-4
ISSN	0138-9130
ISSN	0138-9130
DOI	10.1007/s11192-022-04292-y
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Article: The Expectation and Reality of the HepG2 Core Metabolic Profile.

Kiseleva, Olga I / Kurbatov, Ilya Y / Arzumanian, Viktoriia A / Ilgisonis, Ekaterina V / Zakharov, Svyatoslav V / Poverennaya, Ekaterina V

Metabolites

2023 Volume 13, Issue 8

Abstract: To represent the composition of small molecules circulating in HepG2 cells and the formation of the "core" of characteristic metabolites that often attract researchers' attention, we conducted a meta-analysis of 56 datasets obtained through metabolomic ... ...

Abstract	To represent the composition of small molecules circulating in HepG2 cells and the formation of the "core" of characteristic metabolites that often attract researchers' attention, we conducted a meta-analysis of 56 datasets obtained through metabolomic profiling via mass spectrometry and NMR. We highlighted the 288 most commonly studied compounds of diverse chemical nature and analyzed metabolic processes involving these small molecules. Building a complete map of the metabolome of a cell, which encompasses the diversity of possible impacts on it, is a severe challenge for the scientific community, which is faced not only with natural limitations of experimental technologies, but also with the absence of transparent and widely accepted standards for processing and presenting the obtained metabolomic data. Formulating our research design, we aimed to reveal metabolites crucial to the Hepg2 cell line, regardless of all chemical and/or physical impact factors. Unfortunately, the existing paradigm of data policy leads to a streetlight effect. When analyzing and reporting only target metabolites of interest, the community ignores the changes in the metabolomic landscape that hide many molecular secrets.
Language	English
Publishing date	2023-08-03
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2662251-8
ISSN	2218-1989
ISSN	2218-1989
DOI	10.3390/metabo13080908
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Article: Multiomics Picture of Obesity in Young Adults.

Kiseleva, Olga I / Pyatnitskiy, Mikhail A / Arzumanian, Viktoriia A / Kurbatov, Ilya Y / Ilinsky, Valery V / Ilgisonis, Ekaterina V / Plotnikova, Oksana A / Sharafetdinov, Khaider K / Tutelyan, Victor A / Nikityuk, Dmitry B / Ponomarenko, Elena A / Poverennaya, Ekaterina V

Biology

2024 Volume 13, Issue 4

Abstract: Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes ... ...

Abstract	Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC-MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC-MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m
Language	English
Publishing date	2024-04-18
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2661517-4
ISSN	2079-7737
ISSN	2079-7737
DOI	10.3390/biology13040272
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Article ; Online: Deep proteomic dataset of human liver samples obtained by two-dimensional sample fractionation coupled with tandem mass spectrometry.

Vavilov, Nikita E / Ilgisonis, Ekaterina V / Lisitsa, Andrey V / Ponomarenko, Elena A / Farafonova, Tatiana E / Tikhonova, Olga V / Zgoda, Victor G / Archakov, Alexander I

Data in brief

2022 Volume 42, Page(s) 108055

Abstract: The data was acquired from 3 normal human liver tissues by LC-MS methods. The tissue liver samples from male subjects post mortem were obtained from ILSBio LLC (https://bioivt.com/). Liver tissue was frozen in liquid nitrogen, transported and shipped on ... ...

Abstract	The data was acquired from 3 normal human liver tissues by LC-MS methods. The tissue liver samples from male subjects post mortem were obtained from ILSBio LLC (https://bioivt.com/). Liver tissue was frozen in liquid nitrogen, transported and shipped on dry ice. The proteins were extracted and purified followed up by trypsin hydrolysis. The peptide mixture was aliquoted and analyzed by different LC-MS approaches: one-dimensional shotgun LC-MS, two-dimensional LC-MS, two-dimensional SRM SIS (Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards). The Shotgun assay resulted in a qualitative in-depth human liver proteome, and a semi-quantitative iBAQ (intensity-based absolute quantification) value was calculated to show the relative protein content of the sample. Absolute quantitative concentrations of proteins encoded by human chromosome 18 using SRM SIS were obtained.
Language	English
Publishing date	2022-03-12
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2786545-9
ISSN	2352-3409 ; 2352-3409
ISSN (online)	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2022.108055
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Article ; Online: Exploring Dynamic Metabolome of the HepG2 Cell Line: Rise and Fall.

Kiseleva, Olga I / Kurbatov, Ilya Yu / Arzumanian, Viktoriia A / Ilgisonis, Ekaterina V / Vakhrushev, Igor V / Lupatov, Alexey Yu / Ponomarenko, Elena A / Poverennaya, Ekaterina V

Cells

2022 Volume 11, Issue 22

Abstract: Both biological and technical variations can discredit the reliability of obtained data in omics studies. In this technical note, we investigated the effect of prolonged cultivation of the HepG2 hepatoma cell line on its metabolomic profile. Using the GC ...

Abstract	Both biological and technical variations can discredit the reliability of obtained data in omics studies. In this technical note, we investigated the effect of prolonged cultivation of the HepG2 hepatoma cell line on its metabolomic profile. Using the GC × GC-MS approach, we determined the degree of metabolic variability across HepG2 cells cultured in uniform conditions for 0, 5, 10, 15, and 20 days. Post-processing of obtained data revealed substantial changes in relative abundances of 110 metabolites among HepG2 samples under investigation. Our findings have implications for interpreting metabolomic results obtained from immortal cells, especially in longitudinal studies. There are still plenty of unanswered questions regarding metabolomics variability and many potential areas for future targeted and panoramic research. However, we suggest that the metabolome of cell lines is unstable and may undergo significant transformation over time, even if the culture conditions remain the same. Considering metabolomics variability on a relatively long-term basis, careful experimentation with particular attention to control samples is required to ensure reproducibility and relevance of the research results when testing both fundamentally and practically significant hypotheses.
MeSH term(s)	Humans ; Reproducibility of Results ; Hep G2 Cells ; Metabolome ; Metabolomics/methods ; Gas Chromatography-Mass Spectrometry/methods
Language	English
Publishing date	2022-11-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2661518-6
ISSN	2073-4409 ; 2073-4409
ISSN (online)	2073-4409
ISSN	2073-4409
DOI	10.3390/cells11223548
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Article ; Online: Metabolomic Markers for Predicting Preeclampsia in the First Trimester of Pregnancy: A Retrospective Study.

Ilgisonis, Ekaterina V / Shalina, Raisa / Kasum-Zade, Nigyar / Burkova, Kristina G / Trifonova, Oxana P / Maslov, Dmitry L / Kaysheva, Anna L / Markin, Sergey S

Molecules (Basel, Switzerland)

2022 Volume 27, Issue 8

Abstract: We sought to identify the characteristic metabolite profile of blood plasma samples obtained from patients with preeclampsia. Direct high-resolution mass spectrometry was used to analyze samples from 79 pregnant women, 34 of whom had preeclampsia. We ... ...

Abstract	We sought to identify the characteristic metabolite profile of blood plasma samples obtained from patients with preeclampsia. Direct high-resolution mass spectrometry was used to analyze samples from 79 pregnant women, 34 of whom had preeclampsia. We performed a comparative analysis of the metabolite profiles and found that they differed between pregnant women with and without preeclampsia. Lipids and sugars were identified as components of the metabolite profile that are likely to be associated with the development of preeclampsia. While PE was established only in the third trimester, a set of metabolites specific for the third trimester, including 2-(acetylamino)-1,5-anhydro-2-deoxy-4-O-b-D-galactopyranosyl-D-arabino-Hex-1-enitol, N-Acetyl-D-glucosaminyldiphosphodolichol, Cer(d18:0/20:0), and allolithocholic acid, was already traced in the first trimester. These components are also likely involved in lipid metabolism disorders and the development of oxidative stress.
MeSH term(s)	Biomarkers ; Female ; Humans ; Metabolomics/methods ; Pre-Eclampsia/diagnosis ; Pregnancy ; Pregnancy Trimester, First ; Retrospective Studies
Chemical Substances	Biomarkers
Language	English
Publishing date	2022-04-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules27082475
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Article: Deep proteomic dataset of human liver samples obtained by two-dimensional sample fractionation coupled with tandem mass spectrometry

Vavilov, Nikita E. / Ilgisonis, Ekaterina V. / Lisitsa, Andrey V. / Ponomarenko, Elena A. / Farafonova, Tatiana E. / Tikhonova, Olga V. / Zgoda, Victor G. / Archakov, Alexander I.

Data in Brief. 2022 June, v. 42

2022

Abstract	The data was acquired from 3 normal human liver tissues by LC-MS methods. The tissue liver samples from male subjects post mortem were obtained from ILSBio LLC (https://bioivt.com/). Liver tissue was frozen in liquid nitrogen, transported and shipped on dry ice. The proteins were extracted and purified followed up by trypsin hydrolysis. The peptide mixture was aliquoted and analyzed by different LC-MS approaches: one-dimensional shotgun LC-MS, two-dimensional LC-MS, two-dimensional SRM SIS (Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards). The Shotgun assay resulted in a qualitative in-depth human liver proteome, and a semi-quantitative iBAQ (intensity-based absolute quantification) value was calculated to show the relative protein content of the sample. Absolute quantitative concentrations of proteins encoded by human chromosome 18 using SRM SIS were obtained.
Keywords	chromosomes ; data collection ; dry ice ; fractionation ; humans ; hydrolysis ; isotope labeling ; liquid nitrogen ; liver ; males ; peptides ; protein content ; proteome ; proteomics ; tandem mass spectrometry ; trypsin
Language	English
Dates of publication	2022-06
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	2786545-9
ISSN	2352-3409
ISSN	2352-3409
DOI	10.1016/j.dib.2022.108055
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Analysis of Single Biomacromolecules and Viruses: Is It a Myth or Reality?

Pleshakova, Tatyana O / Ivanov, Yuri D / Valueva, Anastasia A / Shumyantseva, Victoria V / Ilgisonis, Ekaterina V / Ponomarenko, Elena A / Lisitsa, Andrey V / Chekhonin, Vladimir P / Archakov, Alexander I

International journal of molecular sciences

2023 Volume 24, Issue 3

Abstract: The beginning of the twenty-first century witnessed novel breakthrough research directions in the life sciences, such as genomics, transcriptomics, translatomics, proteomics, metabolomics, and bioinformatics. A newly developed single-molecule approach ... ...

Abstract	The beginning of the twenty-first century witnessed novel breakthrough research directions in the life sciences, such as genomics, transcriptomics, translatomics, proteomics, metabolomics, and bioinformatics. A newly developed single-molecule approach addresses the physical and chemical properties and the functional activity of single (individual) biomacromolecules and viral particles. Within the alternative approach, the combination of "single-molecule approaches" is opposed to "omics approaches". This new approach is fundamentally unique in terms of its research object (a single biomacromolecule). Most studies are currently performed using postgenomic technologies that allow the properties of several hundreds of millions or even billions of biomacromolecules to be analyzed. This paper discusses the relevance and theoretical, methodological, and practical issues related to the development potential of a single-molecule approach using methods based on molecular detectors.
MeSH term(s)	Genomics/methods ; Proteomics/methods ; Computational Biology ; Metabolomics/methods ; Viruses
Language	English
Publishing date	2023-01-18
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms24031877
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