Fluorescent Sensor Arrays Can Predict and Quantify the Composition of Multicomponent Bacterial Samples.
3-hydroxyflavone
ESIPT
discriminant analysis
machine learning
multiparametric sensing
pathogenic bacteria
pattern analysis
Journal
Frontiers in chemistry
ISSN: 2296-2646
Titre abrégé: Front Chem
Pays: Switzerland
ID NLM: 101627988
Informations de publication
Date de publication:
2019
2019
Historique:
received:
15
11
2019
accepted:
17
12
2019
entrez:
4
2
2020
pubmed:
6
2
2020
medline:
6
2
2020
Statut:
epublish
Résumé
Fast and reliable identification of infectious disease agents is among the most important challenges for the healthcare system. The discrimination of individual components of mixed infections represents a particularly difficult task. In the current study we further expand the functionality of a ratiometric sensor array technology based on small-molecule environmentally-sensitive organic dyes, which can be successfully applied for the analysis of mixed bacterial samples. Using pattern recognition methods and data from pure bacterial species, we demonstrate that this approach can be used to quantify the composition of mixtures, as well as to predict their components with the accuracy of ~80% without the need to acquire additional reference data. The described approach significantly expands the functionality of sensor arrays and provides important insights into data processing for the analysis of other complex samples.
Identifiants
pubmed: 32010667
doi: 10.3389/fchem.2019.00916
pmc: PMC6974461
doi:
Types de publication
Journal Article
Langues
eng
Pagination
916Subventions
Organisme : NIAID NIH HHS
ID : P01 AI083211
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR027940
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB027662
Pays : United States
Organisme : NIGMS NIH HHS
ID : P30 GM127200
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA036727
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR017846
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20 GM103480
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI125589
Pays : United States
Informations de copyright
Copyright © 2020 Svechkarev, Sadykov, Houser, Bayles and Mohs.
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