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Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19
Gut microbiota (GM) modulation can be investigated as possible solution to enhance recovery after COVID-19. An open-label, single-center, single-arm, pilot, interventional study was performed by enrolling twenty patients recently recovered from COVID-19 to investigate the role of a mixed probiotic,...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10094838/ https://www.ncbi.nlm.nih.gov/pubmed/37047594 http://dx.doi.org/10.3390/ijms24076623 |
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author | Laterza, Lucrezia Putignani, Lorenza Settanni, Carlo Romano Petito, Valentina Varca, Simone De Maio, Flavio Macari, Gabriele Guarrasi, Valerio Gremese, Elisa Tolusso, Barbara Wlderk, Giulia Pirro, Maria Antonia Fanali, Caterina Scaldaferri, Franco Turchini, Laura Amatucci, Valeria Sanguinetti, Maurizio Gasbarrini, Antonio |
author_facet | Laterza, Lucrezia Putignani, Lorenza Settanni, Carlo Romano Petito, Valentina Varca, Simone De Maio, Flavio Macari, Gabriele Guarrasi, Valerio Gremese, Elisa Tolusso, Barbara Wlderk, Giulia Pirro, Maria Antonia Fanali, Caterina Scaldaferri, Franco Turchini, Laura Amatucci, Valeria Sanguinetti, Maurizio Gasbarrini, Antonio |
author_sort | Laterza, Lucrezia |
collection | PubMed |
description | Gut microbiota (GM) modulation can be investigated as possible solution to enhance recovery after COVID-19. An open-label, single-center, single-arm, pilot, interventional study was performed by enrolling twenty patients recently recovered from COVID-19 to investigate the role of a mixed probiotic, containing Lactobacilli, Bifidobacteria and Streptococcus thermophilus, on gastrointestinal symptoms, local and systemic inflammation, intestinal barrier integrity and GM profile. Gastrointestinal Symptom Rating Scale, cytokines, inflammatory, gut permeability, and integrity markers were evaluated before (T(0)) and after 8 weeks (T(1)) of probiotic supplementation. GM profiling was based on 16S-rRNA targeted-metagenomics and QIIME 2.0, LEfSe and PICRUSt computational algorithms. Multiple machine learning (ML) models were trained to classify GM at T(0) and T(1). A statistically significant reduction of IL-6 (p < 0.001), TNF-α (p < 0.001) and IL-12RA (p < 0.02), citrulline (p value < 0.001) was reported at T(1). GM global distribution and microbial biomarkers strictly reflected probiotic composition, with a general increase in Bifidobacteria at T(1). Twelve unique KEGG orthologs were associated only to T(0), including tetracycline resistance cassettes. ML classified the GM at T(1) with 100% score at phylum level. Bifidobacteriaceae and Bifidobacterium spp. inversely correlated to reduction of citrulline and inflammatory cytokines. Probiotic supplementation during post-COVID-19 may trigger anti-inflammatory effects though Bifidobacteria and related-metabolism enhancement. |
format | Online Article Text |
id | pubmed-10094838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100948382023-04-13 Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 Laterza, Lucrezia Putignani, Lorenza Settanni, Carlo Romano Petito, Valentina Varca, Simone De Maio, Flavio Macari, Gabriele Guarrasi, Valerio Gremese, Elisa Tolusso, Barbara Wlderk, Giulia Pirro, Maria Antonia Fanali, Caterina Scaldaferri, Franco Turchini, Laura Amatucci, Valeria Sanguinetti, Maurizio Gasbarrini, Antonio Int J Mol Sci Article Gut microbiota (GM) modulation can be investigated as possible solution to enhance recovery after COVID-19. An open-label, single-center, single-arm, pilot, interventional study was performed by enrolling twenty patients recently recovered from COVID-19 to investigate the role of a mixed probiotic, containing Lactobacilli, Bifidobacteria and Streptococcus thermophilus, on gastrointestinal symptoms, local and systemic inflammation, intestinal barrier integrity and GM profile. Gastrointestinal Symptom Rating Scale, cytokines, inflammatory, gut permeability, and integrity markers were evaluated before (T(0)) and after 8 weeks (T(1)) of probiotic supplementation. GM profiling was based on 16S-rRNA targeted-metagenomics and QIIME 2.0, LEfSe and PICRUSt computational algorithms. Multiple machine learning (ML) models were trained to classify GM at T(0) and T(1). A statistically significant reduction of IL-6 (p < 0.001), TNF-α (p < 0.001) and IL-12RA (p < 0.02), citrulline (p value < 0.001) was reported at T(1). GM global distribution and microbial biomarkers strictly reflected probiotic composition, with a general increase in Bifidobacteria at T(1). Twelve unique KEGG orthologs were associated only to T(0), including tetracycline resistance cassettes. ML classified the GM at T(1) with 100% score at phylum level. Bifidobacteriaceae and Bifidobacterium spp. inversely correlated to reduction of citrulline and inflammatory cytokines. Probiotic supplementation during post-COVID-19 may trigger anti-inflammatory effects though Bifidobacteria and related-metabolism enhancement. MDPI 2023-04-01 /pmc/articles/PMC10094838/ /pubmed/37047594 http://dx.doi.org/10.3390/ijms24076623 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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/). |
spellingShingle | Article Laterza, Lucrezia Putignani, Lorenza Settanni, Carlo Romano Petito, Valentina Varca, Simone De Maio, Flavio Macari, Gabriele Guarrasi, Valerio Gremese, Elisa Tolusso, Barbara Wlderk, Giulia Pirro, Maria Antonia Fanali, Caterina Scaldaferri, Franco Turchini, Laura Amatucci, Valeria Sanguinetti, Maurizio Gasbarrini, Antonio Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 |
title | Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 |
title_full | Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 |
title_fullStr | Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 |
title_full_unstemmed | Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 |
title_short | Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19 |
title_sort | ecology and machine learning-based classification models of gut microbiota and inflammatory markers may evaluate the effects of probiotic supplementation in patients recently recovered from covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10094838/ https://www.ncbi.nlm.nih.gov/pubmed/37047594 http://dx.doi.org/10.3390/ijms24076623 |
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