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Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients
The opportunistic pathogen Pseudomonas aeruginosa is often involved in airway infections of cystic fibrosis (CF) patients. It persists in the hostile CF lung environment, inducing chronic infections due to the production of several virulence factors. In this regard, the ability to form a biofilm pla...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145053/ https://www.ncbi.nlm.nih.gov/pubmed/35630332 http://dx.doi.org/10.3390/microorganisms10050887 |
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author | Artini, Marco Papa, Rosanna Sapienza, Filippo Božović, Mijat Vrenna, Gianluca Tuccio Guarna Assanti, Vanessa Sabatino, Manuela Garzoli, Stefania Fiscarelli, Ersilia Vita Ragno, Rino Selan, Laura |
author_facet | Artini, Marco Papa, Rosanna Sapienza, Filippo Božović, Mijat Vrenna, Gianluca Tuccio Guarna Assanti, Vanessa Sabatino, Manuela Garzoli, Stefania Fiscarelli, Ersilia Vita Ragno, Rino Selan, Laura |
author_sort | Artini, Marco |
collection | PubMed |
description | The opportunistic pathogen Pseudomonas aeruginosa is often involved in airway infections of cystic fibrosis (CF) patients. It persists in the hostile CF lung environment, inducing chronic infections due to the production of several virulence factors. In this regard, the ability to form a biofilm plays a pivotal role in CF airway colonization by P. aeruginosa. Bacterial virulence mitigation and bacterial cell adhesion hampering and/or biofilm reduced formation could represent a major target for the development of new therapeutic treatments for infection control. Essential oils (EOs) are being considered as a potential alternative in clinical settings for the prevention, treatment, and control of infections sustained by microbial biofilms. EOs are complex mixtures of different classes of organic compounds, usually used for the treatment of upper respiratory tract infections in traditional medicine. Recently, a wide series of EOs were investigated for their ability to modulate biofilm production by different pathogens comprising S. aureus, S. epidermidis, and P. aeruginosa strains. Machine learning (ML) algorithms were applied to develop classification models in order to suggest a possible antibiofilm action for each chemical component of the studied EOs. In the present study, we assessed the biofilm growth modulation exerted by 61 commercial EOs on a selected number of P. aeruginosa strains isolated from CF patients. Furthermore, ML has been used to shed light on the EO chemical components likely responsible for the positive or negative modulation of bacterial biofilm formation. |
format | Online Article Text |
id | pubmed-9145053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91450532022-05-29 Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients Artini, Marco Papa, Rosanna Sapienza, Filippo Božović, Mijat Vrenna, Gianluca Tuccio Guarna Assanti, Vanessa Sabatino, Manuela Garzoli, Stefania Fiscarelli, Ersilia Vita Ragno, Rino Selan, Laura Microorganisms Article The opportunistic pathogen Pseudomonas aeruginosa is often involved in airway infections of cystic fibrosis (CF) patients. It persists in the hostile CF lung environment, inducing chronic infections due to the production of several virulence factors. In this regard, the ability to form a biofilm plays a pivotal role in CF airway colonization by P. aeruginosa. Bacterial virulence mitigation and bacterial cell adhesion hampering and/or biofilm reduced formation could represent a major target for the development of new therapeutic treatments for infection control. Essential oils (EOs) are being considered as a potential alternative in clinical settings for the prevention, treatment, and control of infections sustained by microbial biofilms. EOs are complex mixtures of different classes of organic compounds, usually used for the treatment of upper respiratory tract infections in traditional medicine. Recently, a wide series of EOs were investigated for their ability to modulate biofilm production by different pathogens comprising S. aureus, S. epidermidis, and P. aeruginosa strains. Machine learning (ML) algorithms were applied to develop classification models in order to suggest a possible antibiofilm action for each chemical component of the studied EOs. In the present study, we assessed the biofilm growth modulation exerted by 61 commercial EOs on a selected number of P. aeruginosa strains isolated from CF patients. Furthermore, ML has been used to shed light on the EO chemical components likely responsible for the positive or negative modulation of bacterial biofilm formation. MDPI 2022-04-24 /pmc/articles/PMC9145053/ /pubmed/35630332 http://dx.doi.org/10.3390/microorganisms10050887 Text en © 2022 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 Artini, Marco Papa, Rosanna Sapienza, Filippo Božović, Mijat Vrenna, Gianluca Tuccio Guarna Assanti, Vanessa Sabatino, Manuela Garzoli, Stefania Fiscarelli, Ersilia Vita Ragno, Rino Selan, Laura Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients |
title | Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients |
title_full | Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients |
title_fullStr | Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients |
title_full_unstemmed | Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients |
title_short | Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on Pseudomonas aeruginosa Isolates from Cystic Fibrosis Patients |
title_sort | essential oils biofilm modulation activity and machine learning analysis on pseudomonas aeruginosa isolates from cystic fibrosis patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145053/ https://www.ncbi.nlm.nih.gov/pubmed/35630332 http://dx.doi.org/10.3390/microorganisms10050887 |
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