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Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature

2022-11-08Journal article Open access
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dc.contributor.authorFernandes, Ana Filipa
dc.contributor.authorGonçalves, Luís Gafeira
dc.contributor.authorBento, Maria
dc.contributor.authorAnjo, Sandra I.
dc.contributor.authorManadas, Bruno
dc.contributor.authorBarroso, Clara
dc.contributor.authorVillar, Miguel
dc.contributor.authorMacedo, Rita
dc.contributor.authorSimões, Maria João
dc.contributor.authorCoelho, Ana Varela
dc.date.accessioned2023-03-08T15:08:37Z
dc.date.available2023-03-08T15:08:37Z
dc.date.issued2022-11-08
dc.descriptionThis article belongs to the Special Issue Metabolomics in Health and Disease.pt_PT
dc.description.abstractTuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups-healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.pt_PT
dc.description.sponsorshipNew INDIGO Programme on Biotechnology-Human Health (INDIGO-DBT2-062), ERA NET Project supported by FCT. Partially supported by project PTDC/CVT-CVT/29510/2017 funded by Fundação para a Ciência a Tecnologia; Projects LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) and UID/Multi/04378/2019) funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI); by ONEIDA project (LISBOA-01-0145-FEDER-016417) co-funded by FEEI-”Fundos Europeus Estruturais e de Investimento” from “Programa Operacional Regional Lisboa 2020” and by national funds from Fundação para a Ciência e a Tecnologia. European Regional Development Fund (ERDF), through the COMPETE 2020—Operational Programme for Competitiveness and Internationalisation and Portuguese national funds via FCT—Fundação para a Ciência e a Tecnologia, I.P., under projects: POCI-01-0145-FEDER-007440 (ref. UIDB/04539/2020 and UIDP/04539/2020), and by The Na tional Mass Spectrometry Network (RNEM) under the contract POCI-01-0145-FEDER-402-022125 (ref.: ROTEIRO/0028/2013). Luis G Gonçalves was financed by an FCT contract according to DL57/2016, [SFRH/BPD/111100/2015].pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationInt J Mol Sci. 2022 Nov 8;23(22):13733. doi: 10.3390/ijms232213733.pt_PT
dc.identifier.doi10.3390/ijms232213733pt_PT
dc.identifier.issn1661-6596
dc.identifier.urihttp://hdl.handle.net/10400.18/8549
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationApplied Molecular Biosciences Unit
dc.relationCenter for Innovative Biomedicine and Biotechnology
dc.relationCenter for Innovative Biomedicine and Biotechnology
dc.relationCarboxydotrophs for alkane production: from CO/CO2 to fuel
dc.relation.publisherversionhttps://www.mdpi.com/1422-0067/23/22/13733pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectTuberculosispt_PT
dc.subjectDiagnosispt_PT
dc.subjectBiomarkerspt_PT
dc.subjectBlood Serumpt_PT
dc.subjectMass Spectrometrypt_PT
dc.subjectMultiomicspt_PT
dc.subjectInfecções Respiratóriaspt_PT
dc.titleMass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signaturept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleApplied Molecular Biosciences Unit
oaire.awardTitleCenter for Innovative Biomedicine and Biotechnology
oaire.awardTitleCenter for Innovative Biomedicine and Biotechnology
oaire.awardTitleCarboxydotrophs for alkane production: from CO/CO2 to fuel
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCVT-CVT%2F29510%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMulti%2F04378%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04539%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04539%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBPD%2F111100%2F2015/PT
oaire.citation.issue22pt_PT
oaire.citation.startPage13733pt_PT
oaire.citation.titleInternational Journal of Molecular Sciencespt_PT
oaire.citation.volume23pt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
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project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.embargofctAcesso de acordo com política editorial da revista.pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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