Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning

Detalhes bibliográficos
Autor(a) principal: Ribeiro Da Cunha, Bernardo
Data de Publicação: 2021
Outros Autores: Fonseca, Luís P. P., Calado, Cecília
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.21/12742
Resumo: Este trabalho foi financiado pelo Concurso Anual para Projetos de Investigação, Desenvolvimento, Inovação e Criação Artística (IDI&CA) 2017 do Instituto Politécnico de Lisboa. Código de referência IPL/2017/DrugsPlatf/ISEL
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spelling Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learningAntibiotic discoveryFourier-transform infrared (FTIR) spectroscopyHigh-throughput screeningMechanism of action (MOA)Antimicrobial potencyEste trabalho foi financiado pelo Concurso Anual para Projetos de Investigação, Desenvolvimento, Inovação e Criação Artística (IDI&CA) 2017 do Instituto Politécnico de Lisboa. Código de referência IPL/2017/DrugsPlatf/ISELThe low rate of discovery and rapid spread of resistant pathogens have made antibiotic discovery a worldwide priority. In cell-based screening, the mechanism of action (MOA) is identified after antimicrobial activity. This increases rediscovery, impairs low potency candidate detection, and does not guide lead optimization. In this study, high-throughput Fourier-transform infrared (FTIR) spectroscopy was used to discriminate the MOA of 14 antibiotics at pathway, class, and individual antibiotic level. For that, the optimal combinations and parametrizations of spectral preprocessing were selected with cross-validated partial least squares discriminant analysis, to which various machine learning algorithms were applied. This coherently resulted in very good accuracies, independently of the algorithms, and at all levels of MOA. Particularly, an ensemble of subspace discriminants predicted the known pathway (98.6%), antibiotic classes (100%), and individual antibiotics (97.8%) with exceptional accuracy, and similar results were obtained for simulated novel MOA. Even at very low concentrations (1 mu g/mL) and growth inhibition (15%), over 70% pathway and class accuracy was achieved, suggesting FTIR spectroscopy can probe the grey chemical matter. Prediction of inhibitory effect was also examined, for which a squared exponential Gaussian process regression yielded a root mean square error of 0.33 and a R-2 of 0.92, indicating that metabolic alterations leading to growth inhibition are intrinsically reflected on FTIR spectra beyond cell density.SpringerRCIPLRibeiro Da Cunha, BernardoFonseca, Luís P. P.Calado, Cecília2021-02-01T13:00:58Z2021-01-142021-01-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/12742engCUNHA, Bernardo Ribeiro da; FONSECA, Luís P.; CALADO, Cecília – Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning. Applied Microbiology and Biotechnology. ISSN 0175-7598. Vol. 105, N.º 3 (2021), pp. 1269-12860175-759810.1007/s00253-021-11102-71432-0614metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T10:06:16Zoai:repositorio.ipl.pt:10400.21/12742Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:20:46.476570Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
title Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
spellingShingle Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
Ribeiro Da Cunha, Bernardo
Antibiotic discovery
Fourier-transform infrared (FTIR) spectroscopy
High-throughput screening
Mechanism of action (MOA)
Antimicrobial potency
title_short Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
title_full Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
title_fullStr Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
title_full_unstemmed Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
title_sort Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning
author Ribeiro Da Cunha, Bernardo
author_facet Ribeiro Da Cunha, Bernardo
Fonseca, Luís P. P.
Calado, Cecília
author_role author
author2 Fonseca, Luís P. P.
Calado, Cecília
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Ribeiro Da Cunha, Bernardo
Fonseca, Luís P. P.
Calado, Cecília
dc.subject.por.fl_str_mv Antibiotic discovery
Fourier-transform infrared (FTIR) spectroscopy
High-throughput screening
Mechanism of action (MOA)
Antimicrobial potency
topic Antibiotic discovery
Fourier-transform infrared (FTIR) spectroscopy
High-throughput screening
Mechanism of action (MOA)
Antimicrobial potency
description Este trabalho foi financiado pelo Concurso Anual para Projetos de Investigação, Desenvolvimento, Inovação e Criação Artística (IDI&CA) 2017 do Instituto Politécnico de Lisboa. Código de referência IPL/2017/DrugsPlatf/ISEL
publishDate 2021
dc.date.none.fl_str_mv 2021-02-01T13:00:58Z
2021-01-14
2021-01-14T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/12742
url http://hdl.handle.net/10400.21/12742
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv CUNHA, Bernardo Ribeiro da; FONSECA, Luís P.; CALADO, Cecília – Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning. Applied Microbiology and Biotechnology. ISSN 0175-7598. Vol. 105, N.º 3 (2021), pp. 1269-1286
0175-7598
10.1007/s00253-021-11102-7
1432-0614
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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