Reverse differentiation as a gene filtering tool in genome expression profiling of adipogenesis for fat marker gene selection and their analysis
During mesenchymal stem cell (MSC) conversion into adipocytes, the adipogenic cocktail consisting of insulin, dexamethasone, indomethacin and 3-isobutyl-1-methylxanthine not only induces adipogenic-specific but also genes for non-adipogenic processes. Therefore, not all significantly expressed genes...
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| description | During mesenchymal stem cell (MSC) conversion into adipocytes, the adipogenic cocktail consisting of insulin, dexamethasone, indomethacin and 3-isobutyl-1-methylxanthine not only induces adipogenic-specific but also genes for non-adipogenic processes. Therefore, not all significantly expressed genes represent adipogenic-specific marker genes. So, our aim was to filter only adipogenic-specific out of all expressed genes. We hypothesize that exclusively adipogenic-specific genes change their expression during adipogenesis, and reverse during dedifferentiation. Thus, MSC were adipogenic differentiated and dedifferentiated.
Adipogenesis and reverse adipogenesis was verified by Oil Red O staining and expression of PPARG and FABP4. Based on GeneChips, 991 genes were differentially expressed during adipogenesis and grouped in 4 clusters. According to bioinformatic analysis the relevance of genes with adipogenic-linked biological annotations, expression sites, molecular functions, signaling pathways and transcription factor binding sites was high in cluster 1, including all prominent adipogenic genes like ADIPOQ, C/EBPA, LPL, PPARG and FABP4, moderate in clusters 2-3, and negligible in cluster 4. During reversed adipogenesis, only 782 expressed genes (clusters 1-3) were reverted, including 597 genes not reported for adipogenesis before. We identified APCDD1, CHI3L1, RARRES1 and SEMA3G as potential adipogenic-specific genes.
The model system of adipogenesis linked to reverse adipogenesis allowed the filtration of 782 adipogenic-specific genes out of total 991 significantly expressed genes. Database analysis of adipogenic-specific biological annotations, transcription factors and signaling pathways further validated and valued our concept, because most of the filtered 782 genes showed affiliation to adipogenesis. Based on this approach, the selected and filtered genes would be potentially important for characterization of adipogenesis and monitoring of clinical translation for soft-tissue regeneration. Moreover, we report 4 new marker genes. |
| doi_str_mv | 10.1371/journal.pone.0069754 |
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Adipogenesis and reverse adipogenesis was verified by Oil Red O staining and expression of PPARG and FABP4. Based on GeneChips, 991 genes were differentially expressed during adipogenesis and grouped in 4 clusters. According to bioinformatic analysis the relevance of genes with adipogenic-linked biological annotations, expression sites, molecular functions, signaling pathways and transcription factor binding sites was high in cluster 1, including all prominent adipogenic genes like ADIPOQ, C/EBPA, LPL, PPARG and FABP4, moderate in clusters 2-3, and negligible in cluster 4. During reversed adipogenesis, only 782 expressed genes (clusters 1-3) were reverted, including 597 genes not reported for adipogenesis before. We identified APCDD1, CHI3L1, RARRES1 and SEMA3G as potential adipogenic-specific genes.
The model system of adipogenesis linked to reverse adipogenesis allowed the filtration of 782 adipogenic-specific genes out of total 991 significantly expressed genes. Database analysis of adipogenic-specific biological annotations, transcription factors and signaling pathways further validated and valued our concept, because most of the filtered 782 genes showed affiliation to adipogenesis. Based on this approach, the selected and filtered genes would be potentially important for characterization of adipogenesis and monitoring of clinical translation for soft-tissue regeneration. Moreover, we report 4 new marker genes.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0069754</identifier><identifier>PMID: 23922792</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adipocytes ; Adipogenesis ; Adipogenesis - genetics ; Adiposity - genetics ; Aged ; Alzheimer's disease ; Annotations ; Binding Sites ; Bioinformatics ; Biology ; Biomarkers - metabolism ; Bone marrow ; Cancer ; Cell Dedifferentiation - genetics ; Cell Differentiation - genetics ; Cell Separation ; Chitinase ; Cluster Analysis ; Dexamethasone ; Diabetes ; Filtration ; Gene expression ; Gene Expression Profiling ; Genes ; Genome, Human - genetics ; Genomes ; Genomics ; Humans ; Immunology ; Indomethacin ; Insulin ; Laboratories ; Lipids ; Mathematics ; Medical research ; Medicine ; Mesenchymal Stromal Cells - cytology ; Mesenchymal Stromal Cells - metabolism ; Mesenchyme ; Metabolism ; Middle Aged ; Models, Biological ; Peroxisome proliferator-activated receptors ; Proteins ; Regeneration ; Rheumatology ; Signal transduction ; Signal Transduction - genetics ; Signaling ; Stem cells ; Tissue engineering ; Transcription factors ; Transcription Factors - metabolism</subject><ispartof>PloS one, 2013-07, Vol.8 (7), p.e69754-e69754</ispartof><rights>2013 Ullah et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Ullah et al 2013 Ullah et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-3e74eab8553eeb3f70cce96bf7288f009c81ea3f85d773a6ffe73dd18ee1daf63</citedby><cites>FETCH-LOGICAL-c526t-3e74eab8553eeb3f70cce96bf7288f009c81ea3f85d773a6ffe73dd18ee1daf63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3724870/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3724870/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79472,79473</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23922792$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Gronthos, Stan</contributor><creatorcontrib>Ullah, Mujib</creatorcontrib><creatorcontrib>Stich, Stefan</creatorcontrib><creatorcontrib>Häupl, Thomas</creatorcontrib><creatorcontrib>Eucker, Jan</creatorcontrib><creatorcontrib>Sittinger, Michael</creatorcontrib><creatorcontrib>Ringe, Jochen</creatorcontrib><title>Reverse differentiation as a gene filtering tool in genome expression profiling of adipogenesis for fat marker gene selection and their analysis</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>During mesenchymal stem cell (MSC) conversion into adipocytes, the adipogenic cocktail consisting of insulin, dexamethasone, indomethacin and 3-isobutyl-1-methylxanthine not only induces adipogenic-specific but also genes for non-adipogenic processes. Therefore, not all significantly expressed genes represent adipogenic-specific marker genes. So, our aim was to filter only adipogenic-specific out of all expressed genes. We hypothesize that exclusively adipogenic-specific genes change their expression during adipogenesis, and reverse during dedifferentiation. Thus, MSC were adipogenic differentiated and dedifferentiated.
Adipogenesis and reverse adipogenesis was verified by Oil Red O staining and expression of PPARG and FABP4. Based on GeneChips, 991 genes were differentially expressed during adipogenesis and grouped in 4 clusters. According to bioinformatic analysis the relevance of genes with adipogenic-linked biological annotations, expression sites, molecular functions, signaling pathways and transcription factor binding sites was high in cluster 1, including all prominent adipogenic genes like ADIPOQ, C/EBPA, LPL, PPARG and FABP4, moderate in clusters 2-3, and negligible in cluster 4. During reversed adipogenesis, only 782 expressed genes (clusters 1-3) were reverted, including 597 genes not reported for adipogenesis before. We identified APCDD1, CHI3L1, RARRES1 and SEMA3G as potential adipogenic-specific genes.
The model system of adipogenesis linked to reverse adipogenesis allowed the filtration of 782 adipogenic-specific genes out of total 991 significantly expressed genes. Database analysis of adipogenic-specific biological annotations, transcription factors and signaling pathways further validated and valued our concept, because most of the filtered 782 genes showed affiliation to adipogenesis. Based on this approach, the selected and filtered genes would be potentially important for characterization of adipogenesis and monitoring of clinical translation for soft-tissue regeneration. Moreover, we report 4 new marker genes.</description><subject>Adipocytes</subject><subject>Adipogenesis</subject><subject>Adipogenesis - genetics</subject><subject>Adiposity - genetics</subject><subject>Aged</subject><subject>Alzheimer's disease</subject><subject>Annotations</subject><subject>Binding Sites</subject><subject>Bioinformatics</subject><subject>Biology</subject><subject>Biomarkers - metabolism</subject><subject>Bone marrow</subject><subject>Cancer</subject><subject>Cell Dedifferentiation - genetics</subject><subject>Cell Differentiation - genetics</subject><subject>Cell Separation</subject><subject>Chitinase</subject><subject>Cluster Analysis</subject><subject>Dexamethasone</subject><subject>Diabetes</subject><subject>Filtration</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Genes</subject><subject>Genome, Human - genetics</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Humans</subject><subject>Immunology</subject><subject>Indomethacin</subject><subject>Insulin</subject><subject>Laboratories</subject><subject>Lipids</subject><subject>Mathematics</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Mesenchymal Stromal Cells - cytology</subject><subject>Mesenchymal Stromal Cells - metabolism</subject><subject>Mesenchyme</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Models, Biological</subject><subject>Peroxisome proliferator-activated receptors</subject><subject>Proteins</subject><subject>Regeneration</subject><subject>Rheumatology</subject><subject>Signal transduction</subject><subject>Signal Transduction - genetics</subject><subject>Signaling</subject><subject>Stem cells</subject><subject>Tissue engineering</subject><subject>Transcription factors</subject><subject>Transcription Factors - metabolism</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNptUl1rFDEUHUSxtfoPRAO--LJrPmaSzItQitVCQRB9DtnkZps1m4zJbLH_wp_cjDMtrfiUy805595zOU3zmuA1YYJ82KVDjjqshxRhjTHvRdc-aY5Jz-iKU8yePqiPmhel7DDumOT8eXNEWU-p6Olx8-cbXEMugKx3DjLE0evRp4h0QRptIQJyPoyQfdyiMaWAfJzaaQ8Ifg8ZSpnQQ04VNmGSQ9r6IU3U4gtyKSOnR7TX-SfkWbFAADNPiRaNV-BzrXS4qYSXzTOnQ4FXy3vS_Dj_9P3sy-ry6-eLs9PLlekoH1cMRAt6I7uOAWyYE9gY6PnGCSqlw7g3koBmTnZWCKZ5NSeYtUQCEKsdZyfN21l3CKmo5ZhFkZZK0rKOdxVxMSNs0js1ZF8t3KikvfrbSHmrdB69CaCkAEuMtcZq0pIebwwQajEntA6jGletj8u0w2YP1tQ7Zx0eiT7-if5KbdO1YoK2UkwC7xeBnH4doIxq74uBEHSEdJj2JpK3vCWsQt_9A_2_u3ZGmZxKyeDulyFYTQG7Y6kpYGoJWKW9eWjknnSXKHYLp1TTpQ</recordid><startdate>20130726</startdate><enddate>20130726</enddate><creator>Ullah, Mujib</creator><creator>Stich, Stefan</creator><creator>Häupl, Thomas</creator><creator>Eucker, Jan</creator><creator>Sittinger, Michael</creator><creator>Ringe, Jochen</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20130726</creationdate><title>Reverse differentiation as a gene filtering tool in genome expression profiling of adipogenesis for fat marker gene selection and their analysis</title><author>Ullah, Mujib ; Stich, Stefan ; Häupl, Thomas ; Eucker, Jan ; Sittinger, Michael ; Ringe, Jochen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-3e74eab8553eeb3f70cce96bf7288f009c81ea3f85d773a6ffe73dd18ee1daf63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adipocytes</topic><topic>Adipogenesis</topic><topic>Adipogenesis - genetics</topic><topic>Adiposity - genetics</topic><topic>Aged</topic><topic>Alzheimer's disease</topic><topic>Annotations</topic><topic>Binding Sites</topic><topic>Bioinformatics</topic><topic>Biology</topic><topic>Biomarkers - metabolism</topic><topic>Bone marrow</topic><topic>Cancer</topic><topic>Cell Dedifferentiation - genetics</topic><topic>Cell Differentiation - genetics</topic><topic>Cell Separation</topic><topic>Chitinase</topic><topic>Cluster Analysis</topic><topic>Dexamethasone</topic><topic>Diabetes</topic><topic>Filtration</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Genes</topic><topic>Genome, Human - genetics</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Humans</topic><topic>Immunology</topic><topic>Indomethacin</topic><topic>Insulin</topic><topic>Laboratories</topic><topic>Lipids</topic><topic>Mathematics</topic><topic>Medical research</topic><topic>Medicine</topic><topic>Mesenchymal Stromal Cells - cytology</topic><topic>Mesenchymal Stromal Cells - metabolism</topic><topic>Mesenchyme</topic><topic>Metabolism</topic><topic>Middle Aged</topic><topic>Models, Biological</topic><topic>Peroxisome proliferator-activated receptors</topic><topic>Proteins</topic><topic>Regeneration</topic><topic>Rheumatology</topic><topic>Signal transduction</topic><topic>Signal Transduction - genetics</topic><topic>Signaling</topic><topic>Stem cells</topic><topic>Tissue engineering</topic><topic>Transcription factors</topic><topic>Transcription Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ullah, Mujib</creatorcontrib><creatorcontrib>Stich, Stefan</creatorcontrib><creatorcontrib>Häupl, Thomas</creatorcontrib><creatorcontrib>Eucker, Jan</creatorcontrib><creatorcontrib>Sittinger, Michael</creatorcontrib><creatorcontrib>Ringe, Jochen</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Therefore, not all significantly expressed genes represent adipogenic-specific marker genes. So, our aim was to filter only adipogenic-specific out of all expressed genes. We hypothesize that exclusively adipogenic-specific genes change their expression during adipogenesis, and reverse during dedifferentiation. Thus, MSC were adipogenic differentiated and dedifferentiated.
Adipogenesis and reverse adipogenesis was verified by Oil Red O staining and expression of PPARG and FABP4. Based on GeneChips, 991 genes were differentially expressed during adipogenesis and grouped in 4 clusters. According to bioinformatic analysis the relevance of genes with adipogenic-linked biological annotations, expression sites, molecular functions, signaling pathways and transcription factor binding sites was high in cluster 1, including all prominent adipogenic genes like ADIPOQ, C/EBPA, LPL, PPARG and FABP4, moderate in clusters 2-3, and negligible in cluster 4. During reversed adipogenesis, only 782 expressed genes (clusters 1-3) were reverted, including 597 genes not reported for adipogenesis before. We identified APCDD1, CHI3L1, RARRES1 and SEMA3G as potential adipogenic-specific genes.
The model system of adipogenesis linked to reverse adipogenesis allowed the filtration of 782 adipogenic-specific genes out of total 991 significantly expressed genes. Database analysis of adipogenic-specific biological annotations, transcription factors and signaling pathways further validated and valued our concept, because most of the filtered 782 genes showed affiliation to adipogenesis. Based on this approach, the selected and filtered genes would be potentially important for characterization of adipogenesis and monitoring of clinical translation for soft-tissue regeneration. Moreover, we report 4 new marker genes.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23922792</pmid><doi>10.1371/journal.pone.0069754</doi><oa>free_for_read</oa></addata></record> |
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| ispartof | PloS one, 2013-07, Vol.8 (7), p.e69754-e69754 |
| issn | 1932-6203 1932-6203 |
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| source | PLoS (Open access); MEDLINE; Full-Text Journals in Chemistry (Open access); DOAJ Directory of Open Access Journals; PubMed Central; EZB Electronic Journals Library |
| subjects | Adipocytes Adipogenesis Adipogenesis - genetics Adiposity - genetics Aged Alzheimer's disease Annotations Binding Sites Bioinformatics Biology Biomarkers - metabolism Bone marrow Cancer Cell Dedifferentiation - genetics Cell Differentiation - genetics Cell Separation Chitinase Cluster Analysis Dexamethasone Diabetes Filtration Gene expression Gene Expression Profiling Genes Genome, Human - genetics Genomes Genomics Humans Immunology Indomethacin Insulin Laboratories Lipids Mathematics Medical research Medicine Mesenchymal Stromal Cells - cytology Mesenchymal Stromal Cells - metabolism Mesenchyme Metabolism Middle Aged Models, Biological Peroxisome proliferator-activated receptors Proteins Regeneration Rheumatology Signal transduction Signal Transduction - genetics Signaling Stem cells Tissue engineering Transcription factors Transcription Factors - metabolism |
| title | Reverse differentiation as a gene filtering tool in genome expression profiling of adipogenesis for fat marker gene selection and their analysis |
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