Co-Expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A
Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications. The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a rankin...
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| Veröffentlicht in: | IEEE/ACM transactions on computational biology and bioinformatics 2018-11, Vol.15 (6), p.2009-2016 |
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| creator | Mukund, Kavitha Ward, Samuel R. Lieber, Richard L. Subramaniam, Shankar |
| description | Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications. The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into five groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes-Dclk1 and Ostalpha-within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work. |
| doi_str_mv | 10.1109/TCBB.2017.2763949 |
| format | Article |
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The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into five groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes-Dclk1 and Ostalpha-within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.</description><identifier>ISSN: 1545-5963</identifier><identifier>EISSN: 1557-9964</identifier><identifier>DOI: 10.1109/TCBB.2017.2763949</identifier><identifier>PMID: 29053464</identifier><identifier>CODEN: ITCBCY</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Atrophy ; Bioinformatics ; Biomarkers ; botox ; Botulinum toxin type A ; clustering ; Clustering algorithms ; Co-expression networks ; Connectin ; Contraction ; Correlation ; cross sectional temporal data ; Data mining ; Data processing ; Extracellular matrix ; Functional analysis ; Gene expression ; gene ranking ; Genes ; Isoforms ; Metabolism ; muscle ; Muscles ; Myosin ; Network analysis ; Paralysis ; Proteins ; Real-time systems ; Recovery ; Skeletal muscle ; Therapeutic applications ; timecourse ; Transcription</subject><ispartof>IEEE/ACM transactions on computational biology and bioinformatics, 2018-11, Vol.15 (6), p.2009-2016</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c349t-1d599f77e4dedc65c1f7856f067649748308952ef41359d476228765aa05ff0b3</citedby><cites>FETCH-LOGICAL-c349t-1d599f77e4dedc65c1f7856f067649748308952ef41359d476228765aa05ff0b3</cites><orcidid>0000-0002-8059-4659 ; 0000-0002-3570-2315 ; 0000-0002-7203-4520 ; 0000-0002-4470-155X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8070322$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8070322$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29053464$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mukund, Kavitha</creatorcontrib><creatorcontrib>Ward, Samuel R.</creatorcontrib><creatorcontrib>Lieber, Richard L.</creatorcontrib><creatorcontrib>Subramaniam, Shankar</creatorcontrib><title>Co-Expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A</title><title>IEEE/ACM transactions on computational biology and bioinformatics</title><addtitle>TCBB</addtitle><addtitle>IEEE/ACM Trans Comput Biol Bioinform</addtitle><description>Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications. The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into five groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes-Dclk1 and Ostalpha-within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.</description><subject>Atrophy</subject><subject>Bioinformatics</subject><subject>Biomarkers</subject><subject>botox</subject><subject>Botulinum toxin type A</subject><subject>clustering</subject><subject>Clustering algorithms</subject><subject>Co-expression networks</subject><subject>Connectin</subject><subject>Contraction</subject><subject>Correlation</subject><subject>cross sectional temporal data</subject><subject>Data mining</subject><subject>Data processing</subject><subject>Extracellular matrix</subject><subject>Functional analysis</subject><subject>Gene expression</subject><subject>gene ranking</subject><subject>Genes</subject><subject>Isoforms</subject><subject>Metabolism</subject><subject>muscle</subject><subject>Muscles</subject><subject>Myosin</subject><subject>Network analysis</subject><subject>Paralysis</subject><subject>Proteins</subject><subject>Real-time systems</subject><subject>Recovery</subject><subject>Skeletal muscle</subject><subject>Therapeutic applications</subject><subject>timecourse</subject><subject>Transcription</subject><issn>1545-5963</issn><issn>1557-9964</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkE1LAzEQhoMoVqs_QARZ8OJla75nc2xL_YCigvUctruJ3dpuapLF9t-7pbUHTzMwz_syPAhdEdwjBKv7yXAw6FFMoEdBMsXVETojQkCqlOTH252LVCjJOug8hDnGlCvMT1GHKiwYl_wMvQ1dOlqvvAmhcnXyYuKP819Jf7XyLi9mSXTJe2zKTVV_JnFmkpG1poghcTYZuNgsqrpZtqnGu-jWVZ32L9CJzRfBXO5nF308jCbDp3T8-vg87I_TgnEVU1IKpSyA4aUpCykKYiET0mIJkivgGcOZEtRYTphQJQdJaQZS5DkW1uIp66K7XW_76HdjQtTLKhRmschr45qgiRIcA6PAW_T2Hzp3ja_b7zQlAhQVANBSZEcV3oXgjdUrXy1zv9EE661uvdWtt7r1Xnebudk3N9OlKQ-JP78tcL0DKmPM4ZxhwIxS9guz-IGh</recordid><startdate>201811</startdate><enddate>201811</enddate><creator>Mukund, Kavitha</creator><creator>Ward, Samuel R.</creator><creator>Lieber, Richard L.</creator><creator>Subramaniam, Shankar</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Academic</collection><jtitle>IEEE/ACM transactions on computational biology and bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mukund, Kavitha</au><au>Ward, Samuel R.</au><au>Lieber, Richard L.</au><au>Subramaniam, Shankar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Co-Expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A</atitle><jtitle>IEEE/ACM transactions on computational biology and bioinformatics</jtitle><stitle>TCBB</stitle><addtitle>IEEE/ACM Trans Comput Biol Bioinform</addtitle><date>2018-11</date><risdate>2018</risdate><volume>15</volume><issue>6</issue><spage>2009</spage><epage>2016</epage><pages>2009-2016</pages><issn>1545-5963</issn><eissn>1557-9964</eissn><coden>ITCBCY</coden><abstract>Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications. The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into five groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes-Dclk1 and Ostalpha-within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>29053464</pmid><doi>10.1109/TCBB.2017.2763949</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-8059-4659</orcidid><orcidid>https://orcid.org/0000-0002-3570-2315</orcidid><orcidid>https://orcid.org/0000-0002-7203-4520</orcidid><orcidid>https://orcid.org/0000-0002-4470-155X</orcidid></addata></record> |
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| subjects | Atrophy Bioinformatics Biomarkers botox Botulinum toxin type A clustering Clustering algorithms Co-expression networks Connectin Contraction Correlation cross sectional temporal data Data mining Data processing Extracellular matrix Functional analysis Gene expression gene ranking Genes Isoforms Metabolism muscle Muscles Myosin Network analysis Paralysis Proteins Real-time systems Recovery Skeletal muscle Therapeutic applications timecourse Transcription |
| title | Co-Expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A |
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