<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>12</volume><submitter>Romani L</submitter><pubmed_abstract>This is the first study on gut microbiota (GM) in children affected by coronavirus disease 2019 (COVID-19). Stool samples from 88 patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and 95 healthy subjects were collected (admission: 3-7 days, discharge) to study GM profile by 16S rRNA gene sequencing and relationship to disease severity. The study group was divided in COVID-19 (68), Non-COVID-19 (16), and MIS-C (multisystem inflammatory syndrome in children) (4). Correlations among GM ecology, predicted functions, multiple machine learning (ML) models, and inflammatory response were provided for COVID-19 and Non-COVID-19 cohorts. The GM of COVID-19 cohort resulted as dysbiotic, with the lowest α-diversity compared with Non-COVID-19 and CTRLs and by a specific β-diversity. Its profile appeared enriched in &lt;i>Faecalibacterium&lt;/i>, &lt;i>Fusobacterium&lt;/i>, and &lt;i>Neisseria&lt;/i> and reduced in &lt;i>Bifidobacterium&lt;/i>, &lt;i>Blautia&lt;/i>, &lt;i>Ruminococcus&lt;/i>, &lt;i>Collinsella&lt;/i>, &lt;i>Coprococcus&lt;/i>, &lt;i>Eggerthella&lt;/i>, and &lt;i>Akkermansia&lt;/i>, compared with CTRLs (&lt;i>p &lt;&lt;/i> 0.05). All GM paired-comparisons disclosed comparable results through all time points. The comparison between COVID-19 and Non-COVID-19 cohorts highlighted a reduction of &lt;i>Abiotrophia&lt;/i> in the COVID-19 cohort (&lt;i>p&lt;/i> &lt; 0.05). The GM of MIS-C cohort was characterized by an increase of &lt;i>Veillonella&lt;/i>, &lt;i>Clostridium&lt;/i>, &lt;i>Dialister&lt;/i>, &lt;i>Ruminococcus&lt;/i>, and &lt;i>Streptococcus&lt;/i> and a decrease of &lt;i>Bifidobacterium&lt;/i>, &lt;i>Blautia&lt;/i>, &lt;i>Granulicatella&lt;/i>, and &lt;i>Prevotella&lt;/i>, compared with CTRLs. Stratifying for disease severity, the GM associated to "moderate" COVID-19 was characterized by lower α-diversity compared with "mild" and "asymptomatic" and by a GM profile deprived in &lt;i>Neisseria&lt;/i>, &lt;i>Lachnospira&lt;/i>, &lt;i>Streptococcus&lt;/i>, and &lt;i>Prevotella&lt;/i> and enriched in &lt;i>Dialister&lt;/i>, &lt;i>Acidaminococcus&lt;/i>, &lt;i>Oscillospora&lt;/i>, &lt;i>Ruminococcus&lt;/i>, &lt;i>Clostridium&lt;/i>, &lt;i>Alistipes&lt;/i>, and &lt;i>Bacteroides.&lt;/i> The ML models identified &lt;i>Staphylococcus&lt;/i>, &lt;i>Anaerostipes&lt;/i>, &lt;i>Faecalibacterium&lt;/i>, &lt;i>Dorea&lt;/i>, &lt;i>Dialister&lt;/i>, &lt;i>Streptococcus&lt;/i>, &lt;i>Roseburia&lt;/i>, &lt;i>Haemophilus&lt;/i>, &lt;i>Granulicatella&lt;/i>, &lt;i>Gemmiger&lt;/i>, &lt;i>Lachnospira&lt;/i>, &lt;i>Corynebacterium&lt;/i>, &lt;i>Prevotella&lt;/i>, &lt;i>Bilophila&lt;/i>, &lt;i>Phascolarctobacterium&lt;/i>, &lt;i>Oscillospira&lt;/i>, and &lt;i>Veillonella&lt;/i> as microbial markers of COVID-19. The KEGG ortholog (KO)-based prediction of GM functional profile highlighted 28 and 39 KO-associated pathways to COVID-19 and CTRLs, respectively. Finally, &lt;i>Bacteroides&lt;/i> and &lt;i>Sutterella&lt;/i> correlated with proinflammatory cytokines regardless disease severity. Unlike adult GM profiles, &lt;i>Faecalibacterium&lt;/i> was a specific marker of pediatric COVID-19 GM. The durable modification of patients' GM profile suggested a prompt GM quenching response to SARS-CoV-2 infection since the first symptoms. &lt;i>Faecalibacterium&lt;/i> and reduced fatty acid and amino acid degradation were proposed as specific COVID-19 disease traits, possibly associated to restrained severity of SARS-CoV-2-infected children. Altogether, this evidence provides a characterization of the pediatric COVID-19-related GM.</pubmed_abstract><journal>Frontiers in cellular and infection microbiology</journal><pagination>908492</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9304937</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>The Relationship Between Pediatric Gut Microbiota and SARS-CoV-2 Infection.</pubmed_title><pmcid>PMC9304937</pmcid><pubmed_authors>Macari G</pubmed_authors><pubmed_authors>Cutrera R</pubmed_authors><pubmed_authors>Villani A</pubmed_authors><pubmed_authors>Cursi L</pubmed_authors><pubmed_authors>Pansa P</pubmed_authors><pubmed_authors>De Luca M</pubmed_authors><pubmed_authors>Cotugno N</pubmed_authors><pubmed_authors>Manno EC</pubmed_authors><pubmed_authors>Rossi P</pubmed_authors><pubmed_authors>Carducci FC</pubmed_authors><pubmed_authors>Lancella L</pubmed_authors><pubmed_authors>Bernardi S</pubmed_authors><pubmed_authors>Zangari P</pubmed_authors><pubmed_authors>CACTUS Study Team</pubmed_authors><pubmed_authors>Gardini S</pubmed_authors><pubmed_authors>Ciofi Degli Atti M</pubmed_authors><pubmed_authors>Campana A</pubmed_authors><pubmed_authors>Putignani L</pubmed_authors><pubmed_authors>Palma P</pubmed_authors><pubmed_authors>D'Argenio P</pubmed_authors><pubmed_authors>Romani L</pubmed_authors><pubmed_authors>Del Chierico F</pubmed_authors><pubmed_authors>Guarrasi V</pubmed_authors><pubmed_authors>De Ioris MA</pubmed_authors><pubmed_authors>Ristori MV</pubmed_authors><pubmed_authors>Chiurchiu S</pubmed_authors><pubmed_authors>Finocchi A</pubmed_authors><pubmed_authors>Sessa L</pubmed_authors><pubmed_authors>D'Amore C</pubmed_authors><pubmed_authors>Pane S</pubmed_authors><pubmed_authors>Perno CF</pubmed_authors><pubmed_authors>Morrocchi E</pubmed_authors><pubmed_authors>Pascucci GR</pubmed_authors><pubmed_authors>Cancrini C</pubmed_authors></additional><is_claimable>false</is_claimable><name>The Relationship Between Pediatric Gut Microbiota and SARS-CoV-2 Infection.</name><description>This is the first study on gut microbiota (GM) in children affected by coronavirus disease 2019 (COVID-19). Stool samples from 88 patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and 95 healthy subjects were collected (admission: 3-7 days, discharge) to study GM profile by 16S rRNA gene sequencing and relationship to disease severity. The study group was divided in COVID-19 (68), Non-COVID-19 (16), and MIS-C (multisystem inflammatory syndrome in children) (4). Correlations among GM ecology, predicted functions, multiple machine learning (ML) models, and inflammatory response were provided for COVID-19 and Non-COVID-19 cohorts. The GM of COVID-19 cohort resulted as dysbiotic, with the lowest α-diversity compared with Non-COVID-19 and CTRLs and by a specific β-diversity. Its profile appeared enriched in &lt;i>Faecalibacterium&lt;/i>, &lt;i>Fusobacterium&lt;/i>, and &lt;i>Neisseria&lt;/i> and reduced in &lt;i>Bifidobacterium&lt;/i>, &lt;i>Blautia&lt;/i>, &lt;i>Ruminococcus&lt;/i>, &lt;i>Collinsella&lt;/i>, &lt;i>Coprococcus&lt;/i>, &lt;i>Eggerthella&lt;/i>, and &lt;i>Akkermansia&lt;/i>, compared with CTRLs (&lt;i>p &lt;&lt;/i> 0.05). All GM paired-comparisons disclosed comparable results through all time points. The comparison between COVID-19 and Non-COVID-19 cohorts highlighted a reduction of &lt;i>Abiotrophia&lt;/i> in the COVID-19 cohort (&lt;i>p&lt;/i> &lt; 0.05). The GM of MIS-C cohort was characterized by an increase of &lt;i>Veillonella&lt;/i>, &lt;i>Clostridium&lt;/i>, &lt;i>Dialister&lt;/i>, &lt;i>Ruminococcus&lt;/i>, and &lt;i>Streptococcus&lt;/i> and a decrease of &lt;i>Bifidobacterium&lt;/i>, &lt;i>Blautia&lt;/i>, &lt;i>Granulicatella&lt;/i>, and &lt;i>Prevotella&lt;/i>, compared with CTRLs. Stratifying for disease severity, the GM associated to "moderate" COVID-19 was characterized by lower α-diversity compared with "mild" and "asymptomatic" and by a GM profile deprived in &lt;i>Neisseria&lt;/i>, &lt;i>Lachnospira&lt;/i>, &lt;i>Streptococcus&lt;/i>, and &lt;i>Prevotella&lt;/i> and enriched in &lt;i>Dialister&lt;/i>, &lt;i>Acidaminococcus&lt;/i>, &lt;i>Oscillospora&lt;/i>, &lt;i>Ruminococcus&lt;/i>, &lt;i>Clostridium&lt;/i>, &lt;i>Alistipes&lt;/i>, and &lt;i>Bacteroides.&lt;/i> The ML models identified &lt;i>Staphylococcus&lt;/i>, &lt;i>Anaerostipes&lt;/i>, &lt;i>Faecalibacterium&lt;/i>, &lt;i>Dorea&lt;/i>, &lt;i>Dialister&lt;/i>, &lt;i>Streptococcus&lt;/i>, &lt;i>Roseburia&lt;/i>, &lt;i>Haemophilus&lt;/i>, &lt;i>Granulicatella&lt;/i>, &lt;i>Gemmiger&lt;/i>, &lt;i>Lachnospira&lt;/i>, &lt;i>Corynebacterium&lt;/i>, &lt;i>Prevotella&lt;/i>, &lt;i>Bilophila&lt;/i>, &lt;i>Phascolarctobacterium&lt;/i>, &lt;i>Oscillospira&lt;/i>, and &lt;i>Veillonella&lt;/i> as microbial markers of COVID-19. The KEGG ortholog (KO)-based prediction of GM functional profile highlighted 28 and 39 KO-associated pathways to COVID-19 and CTRLs, respectively. Finally, &lt;i>Bacteroides&lt;/i> and &lt;i>Sutterella&lt;/i> correlated with proinflammatory cytokines regardless disease severity. Unlike adult GM profiles, &lt;i>Faecalibacterium&lt;/i> was a specific marker of pediatric COVID-19 GM. The durable modification of patients' GM profile suggested a prompt GM quenching response to SARS-CoV-2 infection since the first symptoms. &lt;i>Faecalibacterium&lt;/i> and reduced fatty acid and amino acid degradation were proposed as specific COVID-19 disease traits, possibly associated to restrained severity of SARS-CoV-2-infected children. Altogether, this evidence provides a characterization of the pediatric COVID-19-related GM.</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2026-03-31T11:54:45.327Z</modification><creation>2025-02-19T02:44:28.042Z</creation></dates><accession>S-EPMC9304937</accession><cross_references><pubmed>35873161</pubmed><doi>10.3389/fcimb.2022.908492</doi></cross_references></HashMap>