Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/340335
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampLima, Maíra Fasciotti Pinto-
dc.contributor.authorunicampEberlin, Marcos Nogueira-
dc.typeArtigopt_BR
dc.titleInvestigating the potential of ion mobility-mass spectrometry for microalgae biomass characterizationpt_BR
dc.contributor.authorFasciotti, Maira-
dc.contributor.authorSouza, Gustavo H. M. F.-
dc.contributor.authorAstarita, Giuseppe-
dc.contributor.authorCosta, Ingrid C. R.-
dc.contributor.authorMonteiro, Thays. V. C.-
dc.contributor.authorTeixeira, Claudia M. L. L.-
dc.contributor.authorEberlin, Marcos N.-
dc.contributor.authorSarpal, Amarijt S.-
dc.subjectLipídeospt_BR
dc.subject.otherlanguageLipidspt_BR
dc.description.abstractAlgae biomass is formed by an extremely complex set of metabolites, and its molecular characterization has been very challenging. We report the characterization of microalgae extracts via traveling wave ion mobility-mass spectrometry (TWIM-MS) by two different analysis strategies. First, the extracts were analyzed by direct infusion electrospray ionization (ESI) with no previous chromatographic separation (DI-ESI-TVVIM-MS). Second, the samples were screened for metabolites and lipids using an untargeted high-throughput method that employs ultrahigh-performance liquid chromatography (UHPLC) using data-independent analysis (DIA) MSE (UHPLC-HDMSE). Sixteen different microalgae biomasses were evaluated by both strategies. DI-ESI-TWIM-MS was able, via distinct drift times, to set apart different classes of metabolites, with the differences in the profiles of each microalga readily evident. With the UHPLC-HDMSE approach, 1251 different compounds were putatively annotated across 16 samples with 210 classified as lipids. From the normalized abundance for each annotated compound category, a detailed profiling in terms of metabolites, lipids, and lipid classes of each sample was performed. The reported workflow represents a powerful tool to determine the most suitable biotechnological applications for a given alga type and may allow for real-time monitoring of the algae composition distribution as a function of growth conditions, feedstocks, and the like. The determination of collision cross section results in improved confidence in the identification of triacylglycerols in samples, highly applicable to biofuels production. The two analysis strategies explored in this work offer powerful tools for the biomass industry by aiding in the identification of ideal strains and culture conditions for a specific application, saving analysis time and facilitating identification of a large number of constituents at oncept_BR
dc.relation.ispartofAnalytical chemistrypt_BR
dc.relation.ispartofabbreviationAnal. chem.pt_BR
dc.publisher.cityWashington, DCpt_BR
dc.publisher.countryEstados Unidospt_BR
dc.publisherAmerican Chemical Societypt_BR
dc.date.issued2019-
dc.date.monthofcirculationJulypt_BR
dc.language.isoengpt_BR
dc.description.volume91pt_BR
dc.description.issuenumber14pt_BR
dc.description.firstpage9266pt_BR
dc.description.lastpage9276pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn0003-2700pt_BR
dc.identifier.eissn1520-6882pt_BR
dc.identifier.doi10.1021/acs.analchem.9b02172pt_BR
dc.identifier.urlhttps://pubs.acs.org/doi/10.1021/acs.analchem.9b02172pt_BR
dc.description.sponsorshipCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQpt_BR
dc.description.sponsorshipFINANCIADORA DE ESTUDOS E PROJETOS - FINEPpt_BR
dc.description.sponsorshipFUNDAÇÃO CARLOS CHAGAS FILHO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIRO - FAPERJpt_BR
dc.description.sponsorshipFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPpt_BR
dc.description.sponsordocumentnumbernão tempt_BR
dc.description.sponsordocumentnumbernão tempt_BR
dc.description.sponsordocumentnumbernão tempt_BR
dc.description.sponsordocumentnumbernão tempt_BR
dc.date.available2020-05-07T15:55:10Z-
dc.date.accessioned2020-05-07T15:55:10Z-
dc.description.provenanceSubmitted by Mariana Aparecida Azevedo (mary1@unicamp.br) on 2020-05-07T15:55:10Z No. of bitstreams: 0. Added 1 bitstream(s) on 2020-08-27T19:16:41Z : No. of bitstreams: 1 000476567700072.pdf: 7237272 bytes, checksum: ba1f6b5b6aad3fea506948a307a42741 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-05-07T15:55:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2019en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/340335-
dc.contributor.departmentsem informaçãopt_BR
dc.contributor.departmentDepartamento de Química Orgânicapt_BR
dc.contributor.unidadeInstituto de Químicapt_BR
dc.contributor.unidadeInstituto de Químicapt_BR
dc.subject.keywordMass spectrometrypt_BR
dc.subject.keywordMetabolismpt_BR
dc.subject.keywordIonspt_BR
dc.subject.keywordBiomasspt_BR
dc.identifier.source000476567700072pt_BR
dc.creator.orcidsem informaçãopt_BR
dc.creator.orcid0000-0003-4868-0618pt_BR
dc.type.formArtigopt_BR
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