Bioinformatics analysis of microRNA and putative target genes in bovine mammary tissue infected with Streptococcus uberis

MicroRNA (miRNA) are small single-stranded noncoding RNA with important roles in regulating innate immunity in nonruminants via transcriptional and posttranscriptional mechanisms. Mastitis causes significant losses in the dairy industry and a wealth of large-scale mRNA expression data from mammary t...

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Veröffentlicht in:Journal of dairy science 2012-11, Vol.95 (11), p.6397-6408
Hauptverfasser: Naeem, A, Zhong, K, Moisá, S.J, Drackley, J.K, Moyes, K.M, Loor, J.J
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container_end_page 6408
container_issue 11
container_start_page 6397
container_title Journal of dairy science
container_volume 95
creator Naeem, A
Zhong, K
Moisá, S.J
Drackley, J.K
Moyes, K.M
Loor, J.J
description MicroRNA (miRNA) are small single-stranded noncoding RNA with important roles in regulating innate immunity in nonruminants via transcriptional and posttranscriptional mechanisms. Mastitis causes significant losses in the dairy industry and a wealth of large-scale mRNA expression data from mammary tissue have provided fundamental insights into the tissue adaptations to pathogens. We studied the expression of 14 miRNA (miR-10a, -15b, -16a, -17, -21, -31, -145, -146a, -146b, -155, -181a, -205, -221, and -223) associated with regulation of innate immunity and mammary epithelial cell function in tissue challenged with Streptococcus uberis. Those data, along with microarray expression of 2,102 differentially expressed genes, were used for bioinformatics analysis to uncover putative target genes and the most affected biological pathways and functions. Three miRNA (181a, 16, and 31) were downregulated approximately 3- to 5-fold and miR-223 was upregulated approximately 2.5-fold in infected versus healthy tissue. Among differentially expressed genes due to infection, bioinformatics analysis revealed that the studied miRNA share in the regulation of a large number of metabolic (SCD, CD36, GPAM, and FASN), immune/oxidative stress (TNF, IL6, IL10, SOD2, LYZ, and TLR4), and cellular proliferation/differentiation (FOS and CASP4) target genes. This level of complex regulation was underscored by the coordinate effect revealed by bioinformatics on various cellular pathways within the Kyoto Encyclopedia of Genes and Genomes database. Most pathways associated with “cellular processes,” “organismal systems,” and “diseases” were activated by putative target genes of miR-31and miR-16a, with an overlapping activation of “immune system” and “signal transduction.” A pronounced effect and activation of miR-31 target genes was observed within “folding, sorting, and degradation,” “cell growth and death,” and “cell communication” pathways, whereas a marked inhibition of “lipid metabolism” occurred. Putative targets of miR-181a had a strong effect on FcγR-mediated phagocytosis, toll-like receptor signaling, and antigen processing and presentation, which were activated during intramammary infections. The targets of both miR-31 and miR-223 had an inhibitory effect on “lipid metabolism.” Overall, the combined analyses indicated that changes in mammary tissue immune, metabolic, and cell growth-related signaling pathways during infection might have been mediated in part through effects of
doi_str_mv 10.3168/jds.2011-5173
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Mastitis causes significant losses in the dairy industry and a wealth of large-scale mRNA expression data from mammary tissue have provided fundamental insights into the tissue adaptations to pathogens. We studied the expression of 14 miRNA (miR-10a, -15b, -16a, -17, -21, -31, -145, -146a, -146b, -155, -181a, -205, -221, and -223) associated with regulation of innate immunity and mammary epithelial cell function in tissue challenged with Streptococcus uberis. Those data, along with microarray expression of 2,102 differentially expressed genes, were used for bioinformatics analysis to uncover putative target genes and the most affected biological pathways and functions. Three miRNA (181a, 16, and 31) were downregulated approximately 3- to 5-fold and miR-223 was upregulated approximately 2.5-fold in infected versus healthy tissue. Among differentially expressed genes due to infection, bioinformatics analysis revealed that the studied miRNA share in the regulation of a large number of metabolic (SCD, CD36, GPAM, and FASN), immune/oxidative stress (TNF, IL6, IL10, SOD2, LYZ, and TLR4), and cellular proliferation/differentiation (FOS and CASP4) target genes. This level of complex regulation was underscored by the coordinate effect revealed by bioinformatics on various cellular pathways within the Kyoto Encyclopedia of Genes and Genomes database. Most pathways associated with “cellular processes,” “organismal systems,” and “diseases” were activated by putative target genes of miR-31and miR-16a, with an overlapping activation of “immune system” and “signal transduction.” A pronounced effect and activation of miR-31 target genes was observed within “folding, sorting, and degradation,” “cell growth and death,” and “cell communication” pathways, whereas a marked inhibition of “lipid metabolism” occurred. Putative targets of miR-181a had a strong effect on FcγR-mediated phagocytosis, toll-like receptor signaling, and antigen processing and presentation, which were activated during intramammary infections. The targets of both miR-31 and miR-223 had an inhibitory effect on “lipid metabolism.” Overall, the combined analyses indicated that changes in mammary tissue immune, metabolic, and cell growth-related signaling pathways during infection might have been mediated in part through effects of miRNA on gene transcription. Differential expression of miRNA supports the view from nonruminant cells/tissues that certain miRNA might be essential for the tissue’s adaptive response to infection.</description><identifier>ISSN: 0022-0302</identifier><identifier>EISSN: 1525-3198</identifier><identifier>DOI: 10.3168/jds.2011-5173</identifier><identifier>PMID: 22959936</identifier><identifier>CODEN: JDSCAE</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>Animal productions ; Animals ; antigens ; bioinformatics ; Biological and medical sciences ; Cattle ; cell growth ; cell proliferation ; Computational Biology ; dairy industry ; epithelial cells ; Female ; Food industries ; Fundamental and applied biological sciences. Psychology ; gene expression ; gene expression regulation ; Gene Expression Regulation - genetics ; genes ; Genes - genetics ; immune system ; Immunity, Innate - genetics ; interleukin-10 ; interleukin-6 ; lipid metabolism ; mammary glands ; Mammary Glands, Animal - metabolism ; Mammary Glands, Animal - microbiology ; mastitis ; Mastitis, Bovine - genetics ; Mastitis, Bovine - microbiology ; messenger RNA ; microarray technology ; microRNA ; MicroRNAs - analysis ; MicroRNAs - genetics ; Milk and cheese industries. Ice creams ; monogastric livestock ; non-coding RNA ; oxidative stress ; Oxidative Stress - genetics ; pathogens ; phagocytosis ; Real-Time Polymerase Chain Reaction - veterinary ; signal transduction ; sorting ; Streptococcal Infections - genetics ; Streptococcal Infections - metabolism ; Streptococcal Infections - microbiology ; Streptococcal Infections - veterinary ; Streptococcus ; Streptococcus uberis ; Terrestrial animal productions ; transcription (genetics) ; tumor necrosis factors ; Vertebrates</subject><ispartof>Journal of dairy science, 2012-11, Vol.95 (11), p.6397-6408</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-d3bf7e973d8d64f6ce0b5258c656e96ac880ddf315270a001ee942448f88ef643</citedby><cites>FETCH-LOGICAL-c386t-d3bf7e973d8d64f6ce0b5258c656e96ac880ddf315270a001ee942448f88ef643</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=26471334$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22959936$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Naeem, A</creatorcontrib><creatorcontrib>Zhong, K</creatorcontrib><creatorcontrib>Moisá, S.J</creatorcontrib><creatorcontrib>Drackley, J.K</creatorcontrib><creatorcontrib>Moyes, K.M</creatorcontrib><creatorcontrib>Loor, J.J</creatorcontrib><title>Bioinformatics analysis of microRNA and putative target genes in bovine mammary tissue infected with Streptococcus uberis</title><title>Journal of dairy science</title><addtitle>J Dairy Sci</addtitle><description>MicroRNA (miRNA) are small single-stranded noncoding RNA with important roles in regulating innate immunity in nonruminants via transcriptional and posttranscriptional mechanisms. Mastitis causes significant losses in the dairy industry and a wealth of large-scale mRNA expression data from mammary tissue have provided fundamental insights into the tissue adaptations to pathogens. We studied the expression of 14 miRNA (miR-10a, -15b, -16a, -17, -21, -31, -145, -146a, -146b, -155, -181a, -205, -221, and -223) associated with regulation of innate immunity and mammary epithelial cell function in tissue challenged with Streptococcus uberis. Those data, along with microarray expression of 2,102 differentially expressed genes, were used for bioinformatics analysis to uncover putative target genes and the most affected biological pathways and functions. Three miRNA (181a, 16, and 31) were downregulated approximately 3- to 5-fold and miR-223 was upregulated approximately 2.5-fold in infected versus healthy tissue. Among differentially expressed genes due to infection, bioinformatics analysis revealed that the studied miRNA share in the regulation of a large number of metabolic (SCD, CD36, GPAM, and FASN), immune/oxidative stress (TNF, IL6, IL10, SOD2, LYZ, and TLR4), and cellular proliferation/differentiation (FOS and CASP4) target genes. This level of complex regulation was underscored by the coordinate effect revealed by bioinformatics on various cellular pathways within the Kyoto Encyclopedia of Genes and Genomes database. Most pathways associated with “cellular processes,” “organismal systems,” and “diseases” were activated by putative target genes of miR-31and miR-16a, with an overlapping activation of “immune system” and “signal transduction.” A pronounced effect and activation of miR-31 target genes was observed within “folding, sorting, and degradation,” “cell growth and death,” and “cell communication” pathways, whereas a marked inhibition of “lipid metabolism” occurred. Putative targets of miR-181a had a strong effect on FcγR-mediated phagocytosis, toll-like receptor signaling, and antigen processing and presentation, which were activated during intramammary infections. The targets of both miR-31 and miR-223 had an inhibitory effect on “lipid metabolism.” Overall, the combined analyses indicated that changes in mammary tissue immune, metabolic, and cell growth-related signaling pathways during infection might have been mediated in part through effects of miRNA on gene transcription. Differential expression of miRNA supports the view from nonruminant cells/tissues that certain miRNA might be essential for the tissue’s adaptive response to infection.</description><subject>Animal productions</subject><subject>Animals</subject><subject>antigens</subject><subject>bioinformatics</subject><subject>Biological and medical sciences</subject><subject>Cattle</subject><subject>cell growth</subject><subject>cell proliferation</subject><subject>Computational Biology</subject><subject>dairy industry</subject><subject>epithelial cells</subject><subject>Female</subject><subject>Food industries</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>gene expression</subject><subject>gene expression regulation</subject><subject>Gene Expression Regulation - genetics</subject><subject>genes</subject><subject>Genes - genetics</subject><subject>immune system</subject><subject>Immunity, Innate - genetics</subject><subject>interleukin-10</subject><subject>interleukin-6</subject><subject>lipid metabolism</subject><subject>mammary glands</subject><subject>Mammary Glands, Animal - metabolism</subject><subject>Mammary Glands, Animal - microbiology</subject><subject>mastitis</subject><subject>Mastitis, Bovine - genetics</subject><subject>Mastitis, Bovine - microbiology</subject><subject>messenger RNA</subject><subject>microarray technology</subject><subject>microRNA</subject><subject>MicroRNAs - analysis</subject><subject>MicroRNAs - genetics</subject><subject>Milk and cheese industries. Ice creams</subject><subject>monogastric livestock</subject><subject>non-coding RNA</subject><subject>oxidative stress</subject><subject>Oxidative Stress - genetics</subject><subject>pathogens</subject><subject>phagocytosis</subject><subject>Real-Time Polymerase Chain Reaction - veterinary</subject><subject>signal transduction</subject><subject>sorting</subject><subject>Streptococcal Infections - genetics</subject><subject>Streptococcal Infections - metabolism</subject><subject>Streptococcal Infections - microbiology</subject><subject>Streptococcal Infections - veterinary</subject><subject>Streptococcus</subject><subject>Streptococcus uberis</subject><subject>Terrestrial animal productions</subject><subject>transcription (genetics)</subject><subject>tumor necrosis factors</subject><subject>Vertebrates</subject><issn>0022-0302</issn><issn>1525-3198</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpFkU1v1DAQhi0EosvCkSv4gsQlrT8SxzmWii-pohKlZ8txxourJF48Tqv99zjahZ6ssR_NzPuYkLecnUuu9MX9gOeCcV41vJXPyIY3oqkk7_RzsmFMiIpJJs7IK8T7UnLBmpfkTIiu6TqpNuTwKcQw-5gmm4NDamc7HjAgjZ5OwaX488dluRzofsmFeACabdpBpjuYAWmYaR8fwgx0stNk04HmgLhAefDgMgz0MeTf9DYn2OfoonML0qWHFPA1eeHtiPDmdG7J3ZfPv66-Vdc3X79fXV5XTmqVq0H2voWulYMeVO2VA9aXiNqpRkGnrNOaDYOXJXfLLGMcoKtFXWuvNXhVyy35eOy7T_HPApjNFNDBONoZ4oKGc163rOmKvi2pjmjJjZjAm30KayrDmVltm2LbrLbNarvw706tl36C4T_9T28BPpwAi86OPtnZBXziVN1yKdcd3x85b6Oxu2LH3N2WOQ0rf6ZLNvkXKrWS-Q</recordid><startdate>20121101</startdate><enddate>20121101</enddate><creator>Naeem, A</creator><creator>Zhong, K</creator><creator>Moisá, S.J</creator><creator>Drackley, J.K</creator><creator>Moyes, K.M</creator><creator>Loor, J.J</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><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>7X8</scope></search><sort><creationdate>20121101</creationdate><title>Bioinformatics analysis of microRNA and putative target genes in bovine mammary tissue infected with Streptococcus uberis</title><author>Naeem, A ; Zhong, K ; Moisá, S.J ; Drackley, J.K ; Moyes, K.M ; Loor, J.J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-d3bf7e973d8d64f6ce0b5258c656e96ac880ddf315270a001ee942448f88ef643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Animal productions</topic><topic>Animals</topic><topic>antigens</topic><topic>bioinformatics</topic><topic>Biological and medical sciences</topic><topic>Cattle</topic><topic>cell growth</topic><topic>cell proliferation</topic><topic>Computational Biology</topic><topic>dairy industry</topic><topic>epithelial cells</topic><topic>Female</topic><topic>Food industries</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>gene expression</topic><topic>gene expression regulation</topic><topic>Gene Expression Regulation - genetics</topic><topic>genes</topic><topic>Genes - genetics</topic><topic>immune system</topic><topic>Immunity, Innate - genetics</topic><topic>interleukin-10</topic><topic>interleukin-6</topic><topic>lipid metabolism</topic><topic>mammary glands</topic><topic>Mammary Glands, Animal - metabolism</topic><topic>Mammary Glands, Animal - microbiology</topic><topic>mastitis</topic><topic>Mastitis, Bovine - genetics</topic><topic>Mastitis, Bovine - microbiology</topic><topic>messenger RNA</topic><topic>microarray technology</topic><topic>microRNA</topic><topic>MicroRNAs - analysis</topic><topic>MicroRNAs - genetics</topic><topic>Milk and cheese industries. Ice creams</topic><topic>monogastric livestock</topic><topic>non-coding RNA</topic><topic>oxidative stress</topic><topic>Oxidative Stress - genetics</topic><topic>pathogens</topic><topic>phagocytosis</topic><topic>Real-Time Polymerase Chain Reaction - veterinary</topic><topic>signal transduction</topic><topic>sorting</topic><topic>Streptococcal Infections - genetics</topic><topic>Streptococcal Infections - metabolism</topic><topic>Streptococcal Infections - microbiology</topic><topic>Streptococcal Infections - veterinary</topic><topic>Streptococcus</topic><topic>Streptococcus uberis</topic><topic>Terrestrial animal productions</topic><topic>transcription (genetics)</topic><topic>tumor necrosis factors</topic><topic>Vertebrates</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Naeem, A</creatorcontrib><creatorcontrib>Zhong, K</creatorcontrib><creatorcontrib>Moisá, S.J</creatorcontrib><creatorcontrib>Drackley, J.K</creatorcontrib><creatorcontrib>Moyes, K.M</creatorcontrib><creatorcontrib>Loor, J.J</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of dairy science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Naeem, A</au><au>Zhong, K</au><au>Moisá, S.J</au><au>Drackley, J.K</au><au>Moyes, K.M</au><au>Loor, J.J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bioinformatics analysis of microRNA and putative target genes in bovine mammary tissue infected with Streptococcus uberis</atitle><jtitle>Journal of dairy science</jtitle><addtitle>J Dairy Sci</addtitle><date>2012-11-01</date><risdate>2012</risdate><volume>95</volume><issue>11</issue><spage>6397</spage><epage>6408</epage><pages>6397-6408</pages><issn>0022-0302</issn><eissn>1525-3198</eissn><coden>JDSCAE</coden><abstract>MicroRNA (miRNA) are small single-stranded noncoding RNA with important roles in regulating innate immunity in nonruminants via transcriptional and posttranscriptional mechanisms. Mastitis causes significant losses in the dairy industry and a wealth of large-scale mRNA expression data from mammary tissue have provided fundamental insights into the tissue adaptations to pathogens. We studied the expression of 14 miRNA (miR-10a, -15b, -16a, -17, -21, -31, -145, -146a, -146b, -155, -181a, -205, -221, and -223) associated with regulation of innate immunity and mammary epithelial cell function in tissue challenged with Streptococcus uberis. Those data, along with microarray expression of 2,102 differentially expressed genes, were used for bioinformatics analysis to uncover putative target genes and the most affected biological pathways and functions. Three miRNA (181a, 16, and 31) were downregulated approximately 3- to 5-fold and miR-223 was upregulated approximately 2.5-fold in infected versus healthy tissue. Among differentially expressed genes due to infection, bioinformatics analysis revealed that the studied miRNA share in the regulation of a large number of metabolic (SCD, CD36, GPAM, and FASN), immune/oxidative stress (TNF, IL6, IL10, SOD2, LYZ, and TLR4), and cellular proliferation/differentiation (FOS and CASP4) target genes. This level of complex regulation was underscored by the coordinate effect revealed by bioinformatics on various cellular pathways within the Kyoto Encyclopedia of Genes and Genomes database. Most pathways associated with “cellular processes,” “organismal systems,” and “diseases” were activated by putative target genes of miR-31and miR-16a, with an overlapping activation of “immune system” and “signal transduction.” A pronounced effect and activation of miR-31 target genes was observed within “folding, sorting, and degradation,” “cell growth and death,” and “cell communication” pathways, whereas a marked inhibition of “lipid metabolism” occurred. Putative targets of miR-181a had a strong effect on FcγR-mediated phagocytosis, toll-like receptor signaling, and antigen processing and presentation, which were activated during intramammary infections. The targets of both miR-31 and miR-223 had an inhibitory effect on “lipid metabolism.” Overall, the combined analyses indicated that changes in mammary tissue immune, metabolic, and cell growth-related signaling pathways during infection might have been mediated in part through effects of miRNA on gene transcription. Differential expression of miRNA supports the view from nonruminant cells/tissues that certain miRNA might be essential for the tissue’s adaptive response to infection.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>22959936</pmid><doi>10.3168/jds.2011-5173</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record>
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source MEDLINE; Elsevier ScienceDirect Journals Complete; EZB Electronic Journals Library
subjects Animal productions
Animals
antigens
bioinformatics
Biological and medical sciences
Cattle
cell growth
cell proliferation
Computational Biology
dairy industry
epithelial cells
Female
Food industries
Fundamental and applied biological sciences. Psychology
gene expression
gene expression regulation
Gene Expression Regulation - genetics
genes
Genes - genetics
immune system
Immunity, Innate - genetics
interleukin-10
interleukin-6
lipid metabolism
mammary glands
Mammary Glands, Animal - metabolism
Mammary Glands, Animal - microbiology
mastitis
Mastitis, Bovine - genetics
Mastitis, Bovine - microbiology
messenger RNA
microarray technology
microRNA
MicroRNAs - analysis
MicroRNAs - genetics
Milk and cheese industries. Ice creams
monogastric livestock
non-coding RNA
oxidative stress
Oxidative Stress - genetics
pathogens
phagocytosis
Real-Time Polymerase Chain Reaction - veterinary
signal transduction
sorting
Streptococcal Infections - genetics
Streptococcal Infections - metabolism
Streptococcal Infections - microbiology
Streptococcal Infections - veterinary
Streptococcus
Streptococcus uberis
Terrestrial animal productions
transcription (genetics)
tumor necrosis factors
Vertebrates
title Bioinformatics analysis of microRNA and putative target genes in bovine mammary tissue infected with Streptococcus uberis
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