Deciphering "Immaturity-Stemness" in Human Epidermal Stem Cells at the Levels of Protein-Coding and Non-Coding Genomes: A Prospective Computational Approach
The epidermis hosts populations of epithelial stem cells endowed with well-documented renewal and regenerative functions. This tissue thus constitutes a model for exploring the molecular characteristics of stem cells, which remain to date partially characterized at the molecular level in human skin....
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| Veröffentlicht in: | International journal of molecular sciences 2024-03, Vol.25 (6), p.3353 |
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| creator | Vinasco-Sandoval, Tatiana Lemaître, Gilles Soularue, Pascal Martin, Michèle T Fortunel, Nicolas O |
| description | The epidermis hosts populations of epithelial stem cells endowed with well-documented renewal and regenerative functions. This tissue thus constitutes a model for exploring the molecular characteristics of stem cells, which remain to date partially characterized at the molecular level in human skin. Our group has investigated the regulatory functions of the KLF4/TGFB1 and the MAD4/MAX/MYC signaling pathways in the control of the immaturity-stemness versus differentiation fate of keratinocyte stem and precursor cells from human interfollicular epidermis. We described that down-modulation of either
or
/MAD4 using RNA interference tools promoted an augmented stemness cellular status; an effect which was associated with significant transcriptional changes, as assessed by RNA-sequencing. Here, we have implemented a computational approach aimed at integrating the level of the coding genome, comprising the transcripts encoding conventional proteins, and the non-coding genome, with a focus on long non-coding RNAs (lncRNAs). In addition, datasets of micro-RNAs (miRNAs) with validated functions were interrogated in view of identifying miRNAs that could make the link between protein-coding and non-coding transcripts. Putative regulons comprising both coding and long non-coding transcripts were built, which are expected to contain original pro-stemness candidate effectors available for functional validation approaches. In summary, interpretation of our basic functional data together with in silico biomodeling gave rise to a prospective picture of the complex constellation of transcripts regulating the keratinocyte stemness status. |
| doi_str_mv | 10.3390/ijms25063353 |
| format | Article |
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or
/MAD4 using RNA interference tools promoted an augmented stemness cellular status; an effect which was associated with significant transcriptional changes, as assessed by RNA-sequencing. Here, we have implemented a computational approach aimed at integrating the level of the coding genome, comprising the transcripts encoding conventional proteins, and the non-coding genome, with a focus on long non-coding RNAs (lncRNAs). In addition, datasets of micro-RNAs (miRNAs) with validated functions were interrogated in view of identifying miRNAs that could make the link between protein-coding and non-coding transcripts. Putative regulons comprising both coding and long non-coding transcripts were built, which are expected to contain original pro-stemness candidate effectors available for functional validation approaches. In summary, interpretation of our basic functional data together with in silico biomodeling gave rise to a prospective picture of the complex constellation of transcripts regulating the keratinocyte stemness status.</description><identifier>ISSN: 1422-0067</identifier><identifier>ISSN: 1661-6596</identifier><identifier>EISSN: 1422-0067</identifier><identifier>DOI: 10.3390/ijms25063353</identifier><identifier>PMID: 38542324</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Datasets ; Genetic transcription ; Genomes ; Genomics ; Humans ; Life Sciences ; MicroRNA ; MicroRNAs - metabolism ; Prospective Studies ; Proteins ; Proteins - metabolism ; Proto-Oncogene Proteins c-myc - metabolism ; RNA, Long Noncoding - genetics ; RNA, Long Noncoding - metabolism ; Signal Transduction ; Skin ; Stem cells ; Stem Cells - metabolism ; Transcription factors</subject><ispartof>International journal of molecular sciences, 2024-03, Vol.25 (6), p.3353</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Attribution - NonCommercial</rights><rights>2024 by the authors. 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c471t-1156f10edf4c50dbe756046ba605a1f4753001fd90b8da60b058b81ea065a10d3</cites><orcidid>0000-0003-0530-6466 ; 0000-0002-0189-0573 ; 0000-0002-0898-1582 ; 0000-0001-8702-247X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10970410/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10970410/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38542324$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-04517658$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Vinasco-Sandoval, Tatiana</creatorcontrib><creatorcontrib>Lemaître, Gilles</creatorcontrib><creatorcontrib>Soularue, Pascal</creatorcontrib><creatorcontrib>Martin, Michèle T</creatorcontrib><creatorcontrib>Fortunel, Nicolas O</creatorcontrib><title>Deciphering "Immaturity-Stemness" in Human Epidermal Stem Cells at the Levels of Protein-Coding and Non-Coding Genomes: A Prospective Computational Approach</title><title>International journal of molecular sciences</title><addtitle>Int J Mol Sci</addtitle><description>The epidermis hosts populations of epithelial stem cells endowed with well-documented renewal and regenerative functions. This tissue thus constitutes a model for exploring the molecular characteristics of stem cells, which remain to date partially characterized at the molecular level in human skin. Our group has investigated the regulatory functions of the KLF4/TGFB1 and the MAD4/MAX/MYC signaling pathways in the control of the immaturity-stemness versus differentiation fate of keratinocyte stem and precursor cells from human interfollicular epidermis. We described that down-modulation of either
or
/MAD4 using RNA interference tools promoted an augmented stemness cellular status; an effect which was associated with significant transcriptional changes, as assessed by RNA-sequencing. Here, we have implemented a computational approach aimed at integrating the level of the coding genome, comprising the transcripts encoding conventional proteins, and the non-coding genome, with a focus on long non-coding RNAs (lncRNAs). In addition, datasets of micro-RNAs (miRNAs) with validated functions were interrogated in view of identifying miRNAs that could make the link between protein-coding and non-coding transcripts. Putative regulons comprising both coding and long non-coding transcripts were built, which are expected to contain original pro-stemness candidate effectors available for functional validation approaches. 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Lemaître, Gilles ; Soularue, Pascal ; Martin, Michèle T ; Fortunel, Nicolas O</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c471t-1156f10edf4c50dbe756046ba605a1f4753001fd90b8da60b058b81ea065a10d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Datasets</topic><topic>Genetic transcription</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>MicroRNA</topic><topic>MicroRNAs - metabolism</topic><topic>Prospective Studies</topic><topic>Proteins</topic><topic>Proteins - metabolism</topic><topic>Proto-Oncogene Proteins c-myc - metabolism</topic><topic>RNA, Long Noncoding - genetics</topic><topic>RNA, Long Noncoding - metabolism</topic><topic>Signal Transduction</topic><topic>Skin</topic><topic>Stem cells</topic><topic>Stem Cells - metabolism</topic><topic>Transcription factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vinasco-Sandoval, Tatiana</creatorcontrib><creatorcontrib>Lemaître, Gilles</creatorcontrib><creatorcontrib>Soularue, Pascal</creatorcontrib><creatorcontrib>Martin, Michèle T</creatorcontrib><creatorcontrib>Fortunel, Nicolas O</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>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of molecular sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vinasco-Sandoval, Tatiana</au><au>Lemaître, Gilles</au><au>Soularue, Pascal</au><au>Martin, Michèle T</au><au>Fortunel, Nicolas O</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deciphering "Immaturity-Stemness" in Human Epidermal Stem Cells at the Levels of Protein-Coding and Non-Coding Genomes: A Prospective Computational Approach</atitle><jtitle>International journal of molecular sciences</jtitle><addtitle>Int J Mol Sci</addtitle><date>2024-03-15</date><risdate>2024</risdate><volume>25</volume><issue>6</issue><spage>3353</spage><pages>3353-</pages><issn>1422-0067</issn><issn>1661-6596</issn><eissn>1422-0067</eissn><abstract>The epidermis hosts populations of epithelial stem cells endowed with well-documented renewal and regenerative functions. This tissue thus constitutes a model for exploring the molecular characteristics of stem cells, which remain to date partially characterized at the molecular level in human skin. Our group has investigated the regulatory functions of the KLF4/TGFB1 and the MAD4/MAX/MYC signaling pathways in the control of the immaturity-stemness versus differentiation fate of keratinocyte stem and precursor cells from human interfollicular epidermis. We described that down-modulation of either
or
/MAD4 using RNA interference tools promoted an augmented stemness cellular status; an effect which was associated with significant transcriptional changes, as assessed by RNA-sequencing. Here, we have implemented a computational approach aimed at integrating the level of the coding genome, comprising the transcripts encoding conventional proteins, and the non-coding genome, with a focus on long non-coding RNAs (lncRNAs). In addition, datasets of micro-RNAs (miRNAs) with validated functions were interrogated in view of identifying miRNAs that could make the link between protein-coding and non-coding transcripts. Putative regulons comprising both coding and long non-coding transcripts were built, which are expected to contain original pro-stemness candidate effectors available for functional validation approaches. In summary, interpretation of our basic functional data together with in silico biomodeling gave rise to a prospective picture of the complex constellation of transcripts regulating the keratinocyte stemness status.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>38542324</pmid><doi>10.3390/ijms25063353</doi><orcidid>https://orcid.org/0000-0003-0530-6466</orcidid><orcidid>https://orcid.org/0000-0002-0189-0573</orcidid><orcidid>https://orcid.org/0000-0002-0898-1582</orcidid><orcidid>https://orcid.org/0000-0001-8702-247X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Datasets Genetic transcription Genomes Genomics Humans Life Sciences MicroRNA MicroRNAs - metabolism Prospective Studies Proteins Proteins - metabolism Proto-Oncogene Proteins c-myc - metabolism RNA, Long Noncoding - genetics RNA, Long Noncoding - metabolism Signal Transduction Skin Stem cells Stem Cells - metabolism Transcription factors |
| title | Deciphering "Immaturity-Stemness" in Human Epidermal Stem Cells at the Levels of Protein-Coding and Non-Coding Genomes: A Prospective Computational Approach |
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