Dual Transcriptomic Profiling of Host and Microbiota during Health and Disease in Pediatric Asthma
Publication Date
June 30, 2015
Journal
PLOS ONE
Authors
Marcos Pérez Losada, Eduardo Castro Nallar, Matthew L. Bendall, Robert J. Freishtat, et al
Volume
10
Issue
6
Pages
e0131819
DOI
https://dx.plos.org/10.1371/journal.pone.0131819
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0131819
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/26125632
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4488395
Europe PMC
http://europepmc.org/abstract/MED/26125632
Web of Science
000358151300057
Scopus
84938630531
Mendeley
http://www.mendeley.com/research/dual-transcriptomic-profiling-host-microbiota-during-health-disease-pediatric-asthma
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Mendeley | Further Information

{"title"=>"Dual transcriptomic profiling of host and microbiota during health and disease in pediatric asthma", "type"=>"journal", "authors"=>[{"first_name"=>"Marcos", "last_name"=>"Pérez-Losada", "scopus_author_id"=>"6602584301"}, {"first_name"=>"Eduardo", "last_name"=>"Castro-Nallar", "scopus_author_id"=>"54411924800"}, {"first_name"=>"Matthew L.", "last_name"=>"Bendall", "scopus_author_id"=>"35204612500"}, {"first_name"=>"Robert J.", "last_name"=>"Freishtat", "scopus_author_id"=>"6506843276"}, {"first_name"=>"Keith A.", "last_name"=>"Crandall", "scopus_author_id"=>"7006440923"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84938630531", "doi"=>"10.1371/journal.pone.0131819", "pui"=>"605481099", "pmid"=>"26125632", "scopus"=>"2-s2.0-84938630531", "issn"=>"19326203", "isbn"=>"10.1371/journal.pone.0131819"}, "id"=>"5d832a0c-b7a6-39ba-9220-14c8375e6529", "abstract"=>"BACKGROUND: High-throughput sequencing (HTS) analysis of microbial communities from the respiratory airways has heavily relied on the 16S rRNA gene. Given the intrinsic limitations of this approach, airway microbiome research has focused on assessing bacterial composition during health and disease, and its variation in relation to clinical and environmental factors, or other microbiomes. Consequently, very little effort has been dedicated to describing the functional characteristics of the airway microbiota and even less to explore the microbe-host interactions. Here we present a simultaneous assessment of microbiome and host functional diversity and host-microbe interactions from the same RNA-seq experiment, while accounting for variation in clinical metadata.\\n\\nMETHODS: Transcriptomic (host) and metatranscriptomic (microbiota) sequences from the nasal epithelium of 8 asthmatics and 6 healthy controls were separated in silico and mapped to available human and NCBI-NR protein reference databases. Human genes differentially expressed in asthmatics and controls were then used to infer upstream regulators involved in immune and inflammatory responses. Concomitantly, microbial genes were mapped to metabolic databases (COG, SEED, and KEGG) to infer microbial functions differentially expressed in asthmatics and controls. Finally, multivariate analysis was applied to find associations between microbiome characteristics and host upstream regulators while accounting for clinical variation.\\n\\nRESULTS AND DISCUSSION: Our study showed significant differences in the metabolism of microbiomes from asthmatic and non-asthmatic children for up to 25% of the functional properties tested. Enrichment analysis of 499 differentially expressed host genes for inflammatory and immune responses revealed 43 upstream regulators differentially activated in asthma. Microbial adhesion (virulence) and Proteobacteria abundance were significantly associated with variation in the expression of the upstream regulator IL1A; suggesting that microbiome characteristics modulate host inflammatory and immune systems during asthma.", "link"=>"http://www.mendeley.com/research/dual-transcriptomic-profiling-host-microbiota-during-health-disease-pediatric-asthma", "reader_count"=>103, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>22, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>39, "Student > Postgraduate"=>4, "Student > Master"=>13, "Other"=>5, "Student > Bachelor"=>4, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>22, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>39, "Student > Postgraduate"=>4, "Student > Master"=>13, "Other"=>5, "Student > Bachelor"=>4, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>3, "Unspecified"=>8, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>14, "Mathematics"=>1, "Medicine and Dentistry"=>19, "Agricultural and Biological Sciences"=>42, "Veterinary Science and Veterinary Medicine"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>1, "Immunology and Microbiology"=>12}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>19}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>12}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>42}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>14}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>8}, "Environmental Science"=>{"Environmental Science"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Colombia"=>1, "United States"=>5, "Thailand"=>1}, "group_count"=>7}

CrossRef

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/2156862"], "description"=>"<p>EEB plots for COG category 2 (A), SEED categories 1 to 3 (B–D) and KEGG categories 1 to 3 (E–G).</p>", "links"=>[], "tags"=>["airway microbiome research", "Dual Transcriptomic Profiling", "microbiome characteristics", "16 S rRNA gene", "asthmatic", "host", "hts", "regulator IL 1A", "cog", "kegg", "Human genes differentially", "variation", "analysis"], "article_id"=>1469288, "categories"=>["Uncategorised"], "users"=>["Marcos Pérez-Losada", "Eduardo Castro-Nallar", "Matthew L. Bendall", "Robert J. Freishtat", "Keith A. Crandall"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131819.g004", "stats"=>{"downloads"=>2, "page_views"=>72, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Extended_error_bar_EEB_plots_showing_functional_properties_differing_significantly_between_asthmatics_AS_and_controls_CL_with_an_effect_size_8805_1_/1469288", "title"=>"Extended error bar (EEB) plots showing functional properties differing significantly between asthmatics (AS) and controls (CL) with an effect size ≥1%.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-30 03:38:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/2156863"], "description"=>"<p><i>P</i> and <i>q</i> value tests for significance and correlation coefficients are shown.</p>", "links"=>[], "tags"=>["airway microbiome research", "Dual Transcriptomic Profiling", "microbiome characteristics", "16 S rRNA gene", "asthmatic", "host", "hts", "regulator IL 1A", "cog", "kegg", "Human genes differentially", "variation", "analysis"], "article_id"=>1469289, "categories"=>["Uncategorised"], "users"=>["Marcos Pérez-Losada", "Eduardo Castro-Nallar", "Matthew L. Bendall", "Robert J. Freishtat", "Keith A. Crandall"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0131819.g005", "stats"=>{"downloads"=>0, "page_views"=>155, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MaAsLin_scattergrams_showing_associations_between_the_microbial_functional_property_of_Adhesion_A_and_proportions_of_Proteobacteria_B_and_change_in_expression_of_the_host_gene_regulator_IL1A_/1469289", "title"=>"MaAsLin scattergrams showing associations between the microbial functional property of Adhesion (A) and proportions of Proteobacteria (B) and change in expression of the host gene regulator <i>IL1A</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-30 03:38:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/2156864", "https://ndownloader.figshare.com/files/2156865", "https://ndownloader.figshare.com/files/2156866"], "description"=>"<div><p>Background</p><p>High-throughput sequencing (HTS) analysis of microbial communities from the respiratory airways has heavily relied on the 16S rRNA gene. Given the intrinsic limitations of this approach, airway microbiome research has focused on assessing bacterial composition during health and disease, and its variation in relation to clinical and environmental factors, or other microbiomes. Consequently, very little effort has been dedicated to describing the functional characteristics of the airway microbiota and even less to explore the microbe-host interactions. Here we present a simultaneous assessment of microbiome and host functional diversity and host-microbe interactions from the same RNA-seq experiment, while accounting for variation in clinical metadata.</p><p>Methods</p><p>Transcriptomic (host) and metatranscriptomic (microbiota) sequences from the nasal epithelium of 8 asthmatics and 6 healthy controls were separated <i>in silico</i> and mapped to available human and NCBI-NR protein reference databases. Human genes differentially expressed in asthmatics and controls were then used to infer upstream regulators involved in immune and inflammatory responses. Concomitantly, microbial genes were mapped to metabolic databases (COG, SEED, and KEGG) to infer microbial functions differentially expressed in asthmatics and controls. Finally, multivariate analysis was applied to find associations between microbiome characteristics and host upstream regulators while accounting for clinical variation.</p><p>Results and Discussion</p><p>Our study showed significant differences in the metabolism of microbiomes from asthmatic and non-asthmatic children for up to 25% of the functional properties tested. Enrichment analysis of 499 differentially expressed host genes for inflammatory and immune responses revealed 43 upstream regulators differentially activated in asthma. Microbial adhesion (virulence) and Proteobacteria abundance were significantly associated with variation in the expression of the upstream regulator IL1A; suggesting that microbiome characteristics modulate host inflammatory and immune systems during asthma.</p></div>", "links"=>[], "tags"=>["airway microbiome research", "Dual Transcriptomic Profiling", "microbiome characteristics", "16 S rRNA gene", "asthmatic", "host", "hts", "regulator IL 1A", "cog", "kegg", "Human genes differentially", "variation", "analysis"], "article_id"=>1469290, "categories"=>["Uncategorised"], "users"=>["Marcos Pérez-Losada", "Eduardo Castro-Nallar", "Matthew L. Bendall", "Robert J. Freishtat", "Keith A. Crandall"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0131819.s001", "https://dx.doi.org/10.1371/journal.pone.0131819.s002", "https://dx.doi.org/10.1371/journal.pone.0131819.s003"], "stats"=>{"downloads"=>8, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dual_Transcriptomic_Profiling_of_Host_and_Microbiota_during_Health_and_Disease_in_Pediatric_Asthma_/1469290", "title"=>"Dual Transcriptomic Profiling of Host and Microbiota during Health and Disease in Pediatric Asthma", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-06-30 03:38:49"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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