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  1. Article ; Online: Does Proteomic Mirror Reflect Clinical Characteristics of Obesity?

    Olga I. Kiseleva / Viktoriia A. Arzumanian / Ekaterina V. Poverennaya / Mikhail A. Pyatnitskiy / Ekaterina V. Ilgisonis / Victor G. Zgoda / Oksana A. Plotnikova / Khaider K. Sharafetdinov / Andrey V. Lisitsa / Victor A. Tutelyan / Dmitry B. Nikityuk / Alexander I. Archakov / Elena A. Ponomarenko

    Journal of Personalized Medicine, Vol 11, Iss 2, p

    2021  Volume 64

    Abstract: Obesity is a frightening chronic disease, which has tripled since 1975. It is not expected to slow down staying one of the leading cases of preventable death and resulting in an increased clinical and economic burden. Poor lifestyle choices and excessive ...

    Abstract Obesity is a frightening chronic disease, which has tripled since 1975. It is not expected to slow down staying one of the leading cases of preventable death and resulting in an increased clinical and economic burden. Poor lifestyle choices and excessive intake of “cheap calories” are major contributors to obesity, triggering type 2 diabetes, cardiovascular diseases, and other comorbidities. Understanding the molecular mechanisms responsible for development of obesity is essential as it might result in the introducing of anti-obesity targets and early-stage obesity biomarkers, allowing the distinction between metabolic syndromes. The complex nature of this disease, coupled with the phenomenon of metabolically healthy obesity, inspired us to perform data-centric, hypothesis-generating pilot research, aimed to find correlations between parameters of classic clinical blood tests and proteomic profiles of 104 lean and obese subjects. As the result, we assembled patterns of proteins, which presence or absence allows predicting the weight of the patient fairly well. We believe that such proteomic patterns with high prediction power should facilitate the translation of potential candidates into biomarkers of clinical use for early-stage stratification of obesity therapy.
    Keywords obesity ; BMI ; blood tests ; proteomics ; mass spectrometry ; Medicine ; R
    Subject code 610 ; 616
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Multiomic Profiling Identified EGF Receptor Signaling as a Potential Inhibitor of Type I Interferon Response in Models of Oncolytic Therapy by Vesicular Stomatitis Virus

    Anastasia S. Nikitina / Anastasia V. Lipatova / Anton O. Goncharov / Anna A. Kliuchnikova / Mikhail A. Pyatnitskiy / Ksenia G. Kuznetsova / Azzam Hamad / Pavel O. Vorobyev / Olga N. Alekseeva / Marah Mahmoud / Yasmin Shakiba / Ksenia S. Anufrieva / Georgy P. Arapidi / Mark V. Ivanov / Irina A. Tarasova / Mikhail V. Gorshkov / Peter M. Chumakov / Sergei A. Moshkovskii

    International Journal of Molecular Sciences, Vol 23, Iss 5244, p

    2022  Volume 5244

    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 ... ...

    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.
    Keywords oncolytic virus ; vesicular stomatitis virus ; glioblastoma ; osteosarcoma ; type I interferon ; epidermal growth factor receptor ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Novel approach to meta-analysis of microarray datasets reveals muscle remodeling-related drug targets and biomarkers in Duchenne muscular dystrophy.

    Ekaterina Kotelnikova / Maria A Shkrob / Mikhail A Pyatnitskiy / Alessandra Ferlini / Nikolai Daraselia

    PLoS Computational Biology, Vol 8, Iss 2, p e

    2012  Volume 1002365

    Abstract: Elucidation of new biomarkers and potential drug targets from high-throughput profiling data is a challenging task due to a limited number of available biological samples and questionable reproducibility of differential changes in cross-dataset ... ...

    Abstract Elucidation of new biomarkers and potential drug targets from high-throughput profiling data is a challenging task due to a limited number of available biological samples and questionable reproducibility of differential changes in cross-dataset comparisons. In this paper we propose a novel computational approach for drug and biomarkers discovery using comprehensive analysis of multiple expression profiling datasets.The new method relies on aggregation of individual profiling experiments combined with leave-one-dataset-out validation approach. Aggregated datasets were studied using Sub-Network Enrichment Analysis algorithm (SNEA) to find consistent statistically significant key regulators within the global literature-extracted expression regulation network. These regulators were linked to the consistent differentially expressed genes.We have applied our approach to several publicly available human muscle gene expression profiling datasets related to Duchenne muscular dystrophy (DMD). In order to detect both enhanced and repressed processes we considered up- and down-regulated genes separately. Applying the proposed approach to the regulators search we discovered the disturbance in the activity of several muscle-related transcription factors (e.g. MYOG and MYOD1), regulators of inflammation, regeneration, and fibrosis. Almost all SNEA-derived regulators of down-regulated genes (e.g. AMPK, TORC2, PPARGC1A) correspond to a single common pathway important for fast-to-slow twitch fiber type transition. We hypothesize that this process can affect the severity of DMD symptoms, making corresponding regulators and downstream genes valuable candidates for being potential drug targets and exploratory biomarkers.
    Keywords Biology (General) ; QH301-705.5
    Subject code 006
    Language English
    Publishing date 2012-02-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Post-translational modifications of FDA-approved plasma biomarkers in glioblastoma samples.

    Natalia A Petushkova / Victor G Zgoda / Mikhail A Pyatnitskiy / Olesya V Larina / Nadezhda B Teryaeva / Alexander A Potapov / Andrey V Lisitsa

    PLoS ONE, Vol 12, Iss 5, p e

    2017  Volume 0177427

    Abstract: Liquid chromatography-tandem mass spectrometry was used to analyze plasma proteins of volunteers (control) and patients with glioblastoma multiform (GBM). A database search was pre-set with a variable post-translational modification (PTM): ... ...

    Abstract Liquid chromatography-tandem mass spectrometry was used to analyze plasma proteins of volunteers (control) and patients with glioblastoma multiform (GBM). A database search was pre-set with a variable post-translational modification (PTM): phosphorylation, acetylation or ubiquitination. There were no significant differences between the control and the GBM groups regarding the number of protein identifications, sequence coverage or number of PTMs. However, in GBM plasma, we unambiguously observed a decreased fraction in post-translationally modified peptides identified with high quality. The disease-specific PTM patterns were extracted and mapped to the set of FDA-approved plasma protein markers. Decreases of 46% and 24% in the number of acetylated and ubiquitinated peptides, respectively, were observed in the GBM samples. Significance of capturing disease-associated patterns of protein modifications was envisaged.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: The Size of the Human Proteome

    Elena A. Ponomarenko / Ekaterina V. Poverennaya / Ekaterina V. Ilgisonis / Mikhail A. Pyatnitskiy / Arthur T. Kopylov / Victor G. Zgoda / Andrey V. Lisitsa / Alexander I. Archakov

    International Journal of Analytical Chemistry, Vol

    The Width and Depth

    2016  Volume 2016

    Abstract: This work discusses bioinformatics and experimental approaches to explore the human proteome, a constellation of proteins expressed in different tissues and organs. As the human proteome is not a static entity, it seems necessary to estimate the number ... ...

    Abstract This work discusses bioinformatics and experimental approaches to explore the human proteome, a constellation of proteins expressed in different tissues and organs. As the human proteome is not a static entity, it seems necessary to estimate the number of different protein species (proteoforms) and measure the number of copies of the same protein in a specific tissue. Here, meta-analysis of neXtProt knowledge base is proposed for theoretical prediction of the number of different proteoforms that arise from alternative splicing (AS), single amino acid polymorphisms (SAPs), and posttranslational modifications (PTMs). Three possible cases are considered: (1) PTMs and SAPs appear exclusively in the canonical sequences of proteins, but not in splice variants; (2) PTMs and SAPs can occur in both proteins encoded by canonical sequences and in splice variants; (3) all modification types (AS, SAP, and PTM) occur as independent events. Experimental validation of proteoforms is limited by the analytical sensitivity of proteomic technology. A bell-shaped distribution histogram was generated for proteins encoded by a single chromosome, with the estimation of copy numbers in plasma, liver, and HepG2 cell line. The proposed metabioinformatics approaches can be used for estimation of the number of different proteoforms for any group of protein-coding genes.
    Keywords Analytical chemistry ; QD71-142
    Subject code 612
    Language English
    Publishing date 2016-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Applying of hierarchical clustering to analysis of protein patterns in the human cancer-associated liver.

    Natalia A Petushkova / Mikhail A Pyatnitskiy / Vladislav A Rudenko / Olesya V Larina / Oxana P Trifonova / Julya S Kisrieva / Natalia F Samenkova / Galina P Kuznetsova / Irina I Karuzina / Andrey V Lisitsa

    PLoS ONE, Vol 9, Iss 8, p e

    2014  Volume 103950

    Abstract: Background There are two ways that statistical methods can learn from biomedical data. One way is to learn classifiers to identify diseases and to predict outcomes using the training dataset with established diagnosis for each sample. When the training ... ...

    Abstract Background There are two ways that statistical methods can learn from biomedical data. One way is to learn classifiers to identify diseases and to predict outcomes using the training dataset with established diagnosis for each sample. When the training dataset is not available the task can be to mine for presence of meaningful groups (clusters) of samples and to explore underlying data structure (unsupervised learning). Results We investigated the proteomic profiles of the cytosolic fraction of human liver samples using two-dimensional electrophoresis (2DE). Samples were resected upon surgical treatment of hepatic metastases in colorectal cancer. Unsupervised hierarchical clustering of 2DE gel images (n = 18) revealed a pair of clusters, containing 11 and 7 samples. Previously we used the same specimens to measure biochemical profiles based on cytochrome P450-dependent enzymatic activities and also found that samples were clearly divided into two well-separated groups by cluster analysis. It turned out that groups by enzyme activity almost perfectly match to the groups identified from proteomic data. Of the 271 reproducible spots on our 2DE gels, we selected 15 to distinguish the human liver cytosolic clusters. Using MALDI-TOF peptide mass fingerprinting, we identified 12 proteins for the selected spots, including known cancer-associated species. Conclusions/significance Our results highlight the importance of hierarchical cluster analysis of proteomic data, and showed concordance between results of biochemical and proteomic approaches. Grouping of the human liver samples and/or patients into differing clusters may provide insights into possible molecular mechanism of drug metabolism and creates a rationale for personalized treatment.
    Keywords Medicine ; R ; Science ; Q
    Subject code 004
    Language English
    Publishing date 2014-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Proteogenomics of Malignant Melanoma Cell Lines: The Effect of Stringency of Exome Data Filtering on Variant Peptide Identification in Shotgun Proteomics

    Lobas, Anna A / Alexey L. Chernobrovkin / Anna A. Kliuchnikova / Dmitry S. Karpov / Elena Y. Lyssuk / Elizaveta M. Solovyeva / Irina Y. Ilina / Ksenia G. Kuznetsova / Mark V. Ivanov / Mikhail A. Pyatnitskiy / Mikhail V. Gorshkov / Olga E. Voronko / Roman A. Zubarev / Sergei A. Moshkovskii / Sergey S. Larin

    Journal of proteome research. 2018 Apr. 05, v. 17, no. 5

    2018  

    Abstract: The identification of genetically encoded variants at the proteome level is an important problem in cancer proteogenomics. The generation of customized protein databases from DNA or RNA sequencing data is a crucial stage of the identification workflow. ... ...

    Abstract The identification of genetically encoded variants at the proteome level is an important problem in cancer proteogenomics. The generation of customized protein databases from DNA or RNA sequencing data is a crucial stage of the identification workflow. Genomic data filtering applied at this stage may significantly modify variant search results, yet its effect is generally left out of the scope of proteogenomic studies. In this work, we focused on this impact using data of exome sequencing and LC–MS/MS analyses of six replicates for eight melanoma cell lines processed by a proteogenomics workflow. The main objectives were identifying variant peptides and revealing the role of the genomic data filtering in the variant identification. A series of six confidence thresholds for single nucleotide polymorphisms and indels from the exome data were applied to generate customized sequence databases of different stringency. In the searches against unfiltered databases, between 100 and 160 variant peptides were identified for each of the cell lines using X!Tandem and MS-GF+ search engines. The recovery rate for variant peptides was ∼1%, which is approximately three times lower than that of the wild-type peptides. Using unfiltered genomic databases for variant searches resulted in higher sensitivity and selectivity of the proteogenomic workflow and positively affected the ability to distinguish the cell lines based on variant peptide signatures.
    Keywords cell lines ; DNA ; genetic databases ; genomics ; liquid chromatography ; melanoma ; peptides ; proteome ; proteomics ; sequence analysis ; single nucleotide polymorphism ; tandem mass spectrometry
    Language English
    Dates of publication 2018-0405
    Size p. 1801-1811.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 2078618-9
    ISSN 1535-3907 ; 1535-3893
    ISSN (online) 1535-3907
    ISSN 1535-3893
    DOI 10.1021/acs.jproteome.7b00841
    Database NAL-Catalogue (AGRICOLA)

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  8. Article: Methionine to isothreonine conversion as a source of false discovery identifications of genetically encoded variants in proteogenomics

    Chernobrovkin, Alexey L / Alexander A. Moysa / Alexander I. Archakov / Alexander V. Veselovsky / Arthur T. Kopylov / Dmitry S. Karpov / Irina Y. Ilina / Ksenia G. Kuznetsova / Maria A. Karpova / Mark V. Ivanov / Mikhail A. Pyatnitskiy / Mikhail V. Gorshkov / Sergei A. Moshkovskii / Victor G. Zgoda

    Journal of proteomics. 2015 Apr. 29, v. 120

    2015  

    Abstract: Searching deep proteome data for 9 NCI-60 cancer cell lines obtained earlier by Moghaddas Gholami et al. (Cell Reports, 2013) against a database from cancer genomes returned a variant tryptic peptide fragment 57-72 of molecular chaperone HSC70, in which ... ...

    Abstract Searching deep proteome data for 9 NCI-60 cancer cell lines obtained earlier by Moghaddas Gholami et al. (Cell Reports, 2013) against a database from cancer genomes returned a variant tryptic peptide fragment 57-72 of molecular chaperone HSC70, in which methionine residue at 61 position is replaced by threonine, or isothreonine (homoserine), residue. However, no traces of the corresponding genetic alteration were found in the cell line genomes reported by Abaan et al. (Cancer Research, 2013). Studying on the background of this modification led us to conclude that a conversion of methionine into isothreonine resulted from iodoacetamide treatment of the probe during a sample preparation step. We found that up to 10% of methionine containing peptides experienced the above conversion for the datasets under study. The artifact was confirmed by model experiment with bovine albumin, where three of four methionine residues were partly converted to isothreonine by conventional iodoacetamide treatment. This experimental side reaction has to be taken into account when searching for genetically encoded peptide variants in the proteogenomics studies.A lot of effort is currently put into proteogenomics of cancer. Studies detect non-synonymous cancer mutations at protein level by search of high-throughput LC–MS/MS data against customized genomic databases. In such studies, much attention is paid to potential false positive identifications. Here we describe one possible cause of such false identifications, an artifact of sample preparation which mimics methionine to threonine nucleic acid-encoded variant. The methionine to isothreonine conversion should be taken into consideration for correct interpretation of proteogenomic data.
    Keywords albumins ; cattle ; data collection ; genetic databases ; genome ; homoserine ; methionine ; molecular chaperones ; mutation ; neoplasms ; peptides ; proteome ; threonine
    Language English
    Dates of publication 2015-0429
    Size p. 169-178.
    Publishing place Elsevier B.V.
    Document type Article
    ZDB-ID 2400835-7
    ISSN 1876-7737 ; 1874-3919
    ISSN (online) 1876-7737
    ISSN 1874-3919
    DOI 10.1016/j.jprot.2015.03.003
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