Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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
_version_ 1784716198742589440
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
work_keys_str_mv AT artinimarco essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT paparosanna essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT sapienzafilippo essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT bozovicmijat essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT vrennagianluca essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT tuccioguarnaassantivanessa essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT sabatinomanuela essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT garzolistefania essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT fiscarelliersiliavita essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT ragnorino essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients
AT selanlaura essentialoilsbiofilmmodulationactivityandmachinelearninganalysisonpseudomonasaeruginosaisolatesfromcysticfibrosispatients