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Book ; Online: Data Mining in Medical and Biological Research

Giannopoulou, Eugenia G.

2008

Keywords	Biotechnology
Size	1 electronic resource (332 pages)
Publisher	IntechOpen
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT021050106
ISBN	9789535164036 ; 9535164031
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article: The crosstalk between MYC and mTORC1 during osteoclastogenesis.

Bae, Seyeon / Oh, Brian / Tsai, Jefferson / Park, Peter Sang Uk / Greenblatt, Matthew Blake / Giannopoulou, Eugenia G / Park-Min, Kyung-Hyun

Frontiers in cell and developmental biology

2022 Volume 10, Page(s) 920683

Abstract: Osteoclasts are bone-resorbing cells that undergo extensive changes in morphology throughout their differentiation. Altered osteoclast differentiation and activity lead to changes in pathological bone resorption. The mammalian target of rapamycin (mTOR) ... ...

Abstract	Osteoclasts are bone-resorbing cells that undergo extensive changes in morphology throughout their differentiation. Altered osteoclast differentiation and activity lead to changes in pathological bone resorption. The mammalian target of rapamycin (mTOR) is a kinase, and aberrant mTOR complex 1 (mTORC1) signaling is associated with altered bone homeostasis. The activation of mTORC1 is biphasically regulated during osteoclastogenesis; however, the mechanism behind mTORC1-mediated regulation of osteoclastogenesis and bone resorption is incompletely understood. Here, we found that MYC coordinates the dynamic regulation of mTORC1 activation during osteoclastogenesis. MYC-deficiency blocked the early activation of mTORC1 and also reversed the decreased activity of mTORC1 at the late stage of osteoclastogenesis. The suppression of mTORC1 activity by rapamycin in mature osteoclasts enhances bone resorption activity despite the indispensable role of high mTORC1 activation in osteoclast formation in both mouse and human cells. Mechanistically, MYC induces Growth arrest and DNA damage-inducible protein (GADD34) expression and suppresses mTORC1 activity at the late phase of osteoclastogenesis. Taken together, our findings identify a MYC-GADD34 axis as an upstream regulator of dynamic mTORC1 activation in osteoclastogenesis and highlight the interplay between MYC and mTORC1 pathways in determining osteoclast activity.
Language	English
Publishing date	2022-08-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2737824-X
ISSN	2296-634X
ISSN	2296-634X
DOI	10.3389/fcell.2022.920683
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The crosstalk between MYC and mTORC1 during osteoclastogenesis

Seyeon Bae / Brian Oh / Jefferson Tsai / Peter Sang Uk Park / Matthew Blake Greenblatt / Eugenia G. Giannopoulou / Kyung-Hyun Park-Min

Frontiers in Cell and Developmental Biology, Vol

2022 Volume 10

Abstract	Osteoclasts are bone-resorbing cells that undergo extensive changes in morphology throughout their differentiation. Altered osteoclast differentiation and activity lead to changes in pathological bone resorption. The mammalian target of rapamycin (mTOR) is a kinase, and aberrant mTOR complex 1 (mTORC1) signaling is associated with altered bone homeostasis. The activation of mTORC1 is biphasically regulated during osteoclastogenesis; however, the mechanism behind mTORC1-mediated regulation of osteoclastogenesis and bone resorption is incompletely understood. Here, we found that MYC coordinates the dynamic regulation of mTORC1 activation during osteoclastogenesis. MYC-deficiency blocked the early activation of mTORC1 and also reversed the decreased activity of mTORC1 at the late stage of osteoclastogenesis. The suppression of mTORC1 activity by rapamycin in mature osteoclasts enhances bone resorption activity despite the indispensable role of high mTORC1 activation in osteoclast formation in both mouse and human cells. Mechanistically, MYC induces Growth arrest and DNA damage-inducible protein (GADD34) expression and suppresses mTORC1 activity at the late phase of osteoclastogenesis. Taken together, our findings identify a MYC-GADD34 axis as an upstream regulator of dynamic mTORC1 activation in osteoclastogenesis and highlight the interplay between MYC and mTORC1 pathways in determining osteoclast activity.
Keywords	MYC (c-myc) ; GADD34 (PPP1R15A) ; osteoclast (OC) ; mTORC1 (mechanistic target of rapamycin complex 1) ; bone resorption ; Biology (General) ; QH301-705.5
Subject code	500
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Hypoxia-Sensitive COMMD1 Integrates Signaling and Cellular Metabolism in Human Macrophages and Suppresses Osteoclastogenesis.

Murata, Koichi / Fang, Celestia / Terao, Chikashi / Giannopoulou, Eugenia G / Lee, Ye Ji / Lee, Min Joon / Mun, Se-Hwan / Bae, Seyeon / Qiao, Yu / Yuan, Ruoxi / Furu, Moritoshi / Ito, Hiromu / Ohmura, Koichiro / Matsuda, Shuichi / Mimori, Tsuneyo / Matsuda, Fumihiko / Park-Min, Kyung-Hyun / Ivashkiv, Lionel B

Immunity

2022 Volume 55, Issue 11, Page(s) 2209

Language	English
Publishing date	2022-11-06
Publishing country	United States
Document type	Published Erratum
ZDB-ID	1217235-2
ISSN	1097-4180 ; 1074-7613
ISSN (online)	1097-4180
ISSN	1074-7613
DOI	10.1016/j.immuni.2022.10.007
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Article ; Online: Inferring chromatin-bound protein complexes from genome-wide binding assays.

Giannopoulou, Eugenia G / Elemento, Olivier

Genome research

2013 Volume 23, Issue 8, Page(s) 1295–1306

Abstract: Genome-wide binding assays can determine where individual transcription factors bind in the genome. However, these factors rarely bind chromatin alone, but instead frequently bind to cis-regulatory elements (CREs) together with other factors thus forming ...

Abstract	Genome-wide binding assays can determine where individual transcription factors bind in the genome. However, these factors rarely bind chromatin alone, but instead frequently bind to cis-regulatory elements (CREs) together with other factors thus forming protein complexes. Currently there are no integrative analytical approaches that can predict which complexes are formed on chromatin. Here, we describe a computational methodology to systematically capture protein complexes and infer their impact on gene expression. We applied our method to three human cell types, identified thousands of CREs, inferred known and undescribed complexes recruited to these CREs, and determined the role of the complexes as activators or repressors. Importantly, we found that the predicted complexes have a higher number of physical interactions between their members than expected by chance. Our work provides a mechanism for developing hypotheses about gene regulation via binding partners, and deciphering the interplay between combinatorial binding and gene expression.
MeSH term(s)	Chromatin/metabolism ; Chromatin Immunoprecipitation ; Cluster Analysis ; Computational Biology ; Gene Expression Regulation ; Genome, Human ; Humans ; Models, Genetic ; Protein Binding ; Regulatory Sequences, Nucleic Acid ; Sequence Analysis, DNA ; Transcription Factors/metabolism
Chemical Substances	Chromatin ; Transcription Factors
Language	English
Publishing date	2013-04-03
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1284872-4
ISSN	1549-5469 ; 1088-9051 ; 1054-9803
ISSN (online)	1549-5469
ISSN	1088-9051 ; 1054-9803
DOI	10.1101/gr.149419.112
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Article ; Online: Use of RNA sequencing to evaluate rheumatic disease patients.

Giannopoulou, Eugenia G / Elemento, Olivier / Ivashkiv, Lionel B

Arthritis research & therapy

2015 Volume 17, Page(s) 167

Abstract: Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale ... ...

Abstract	Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale in a particular cell, tissue or organ. Microarray analysis has led to gene signatures that differentiate rheumatic diseases, and stages of a disease, as well as response to treatments. Nowadays, however, with the advent of next-generation sequencing methods, massive parallel sequencing of RNA tends to be the technology of choice for gene expression profiling, due to several advantages over microarrays, as well as for the detection of non-coding transcripts and alternative splicing events. In this review, we describe how RNA sequencing enables unbiased interrogation of the abundance and complexity of the transcriptome, and present a typical experimental workflow and bioinformatics tools that are often used for RNA sequencing analysis. We also discuss different uses of this next-generation sequencing technology to evaluate rheumatic disease patients and investigate the pathogenesis of rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, juvenile idiopathic arthritis and Sjögren's syndrome.
MeSH term(s)	Gene Expression Profiling/methods ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Rheumatic Diseases/genetics ; Sequence Analysis, RNA/methods
Language	English
Publishing date	2015-07-01
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2107602-9
ISSN	1478-6362 ; 1478-6354
ISSN (online)	1478-6362
ISSN	1478-6354
DOI	10.1186/s13075-015-0677-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: An integrated ChIP-seq analysis platform with customizable workflows.

Giannopoulou, Eugenia G / Elemento, Olivier

BMC bioinformatics

2011 Volume 12, Page(s) 277

Abstract: Background: Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification ... ...

Abstract	Background: Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks. Results: To address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset. Conclusions: ChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.
MeSH term(s)	Chromatin Immunoprecipitation/methods ; Chromosome Mapping ; Enhancer Elements, Genetic ; High-Throughput Nucleotide Sequencing/methods ; Histone Code ; Humans ; Jurkat Cells ; Proto-Oncogene Protein c-ets-1/metabolism ; Software ; Workflow
Chemical Substances	ETS1 protein, human ; Proto-Oncogene Protein c-ets-1
Language	English
Publishing date	2011-07-07
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/1471-2105-12-277
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: An integrated ChIP-seq analysis platform with customizable workflows

Giannopoulou Eugenia G / Elemento Olivier

BMC Bioinformatics, Vol 12, Iss 1, p

2011 Volume 277

Abstract: Abstract Background Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the ... ...

Abstract	Abstract Background Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks. Results To address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset. Conclusions ChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
Subject code	000
Language	English
Publishing date	2011-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Visualizing meta-features in proteomic maps.

Giannopoulou, Eugenia G / Lepouras, George / Manolakos, Elias S

BMC bioinformatics

2011 Volume 12, Page(s) 308

Abstract: Background: The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the ... ...

Abstract	Background: The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the identified proteins through their association with interaction networks, biological pathways, analysis of the effect of post-translational modifications, and other protein-related information. Results: In this paper, we present an integrative visualization methodology that allows combining experimentally produced proteomic features with protein meta-features, typically coming from meta-analysis tools and databases, in synthetic Proteomic Feature Maps. Using three proteomics analysis scenarios, we show that the proposed visualization approach is effective in filtering, navigating and interacting with the proteomics data in order to address visually challenging biological questions. The novelty of our approach lies in the ease of integration of any user-defined proteomic features in easy-to-comprehend visual representations that resemble the familiar 2D-gel images, and can be adapted to the user's needs. The main capabilities of the developed VIP software, which implements the presented visualization methodology, are also highlighted and discussed. Conclusions: By using this visualization and the associated VIP software, researchers can explore a complex heterogeneous proteomics dataset from different perspectives in order to address visually important biological queries and formulate new hypotheses for further investigation. VIP is freely available at http://pelopas.uop.gr/~egian/VIP/index.html.
MeSH term(s)	Mass Spectrometry/methods ; Phosphorylation ; Protein Processing, Post-Translational ; Proteins/chemistry ; Proteomics/methods ; Software
Chemical Substances	Proteins
Language	English
Publishing date	2011-07-28
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/1471-2105-12-308
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Visualizing Meta-Features in Proteomic Maps

Lepouras George / Giannopoulou Eugenia G / Manolakos Elias S

BMC Bioinformatics, Vol 12, Iss 1, p

2011 Volume 308

Abstract: Abstract Background The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role ... ...

Abstract	Abstract Background The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the identified proteins through their association with interaction networks, biological pathways, analysis of the effect of post-translational modifications, and other protein-related information. Results In this paper, we present an integrative visualization methodology that allows combining experimentally produced proteomic features with protein meta-features, typically coming from meta-analysis tools and databases, in synthetic Proteomic Feature Maps. Using three proteomics analysis scenarios, we show that the proposed visualization approach is effective in filtering, navigating and interacting with the proteomics data in order to address visually challenging biological questions. The novelty of our approach lies in the ease of integration of any user-defined proteomic features in easy-to-comprehend visual representations that resemble the familiar 2D-gel images, and can be adapted to the user's needs. The main capabilities of the developed VIP software, which implements the presented visualization methodology, are also highlighted and discussed. Conclusions By using this visualization and the associated VIP software, researchers can explore a complex heterogeneous proteomics dataset from different perspectives in order to address visually important biological queries and formulate new hypotheses for further investigation. VIP is freely available at http://pelopas.uop.gr/~egian/VIP/index.html .
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
Subject code	612
Language	English
Publishing date	2011-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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