Volatilomics-Based Microbiome Evaluation of Fermented Dairy by Prototypic Headspace-Gas Chromatography–High-Temperature Ion Mobility Spectrometry (HS-GC-HTIMS) and Non-Negative Matrix Factorization (NNMF)

dc.contributor.authorCapitain, Charlotte C.
dc.contributor.authorNejati, Fatemeh
dc.contributor.authorZischka, Martin
dc.contributor.authorBerzak, Markus
dc.contributor.authorJunne, Stefan
dc.contributor.authorNeubauer, Peter
dc.contributor.authorWeller, Philipp
dc.date.accessioned2022-04-14T11:47:00Z
dc.date.available2022-04-14T11:47:00Z
dc.date.issued2022-03-28
dc.date.updated2022-04-08T14:02:22Z
dc.description.abstractFermented foods, such as yogurt and kefir, contain a versatile spectrum of volatile organic compounds (VOCs), including ethanol, acetic acid, ethyl acetate, and diacetyl. To overcome the challenge of overlapping peaks regarding these key compounds, the drift tube temperature was raised in a prototypic high-temperature ion mobility spectrometer (HTIMS). This HS-GC-HTIMS was used for the volatilomic profiling of 33 traditional kefir, 13 commercial kefir, and 15 commercial yogurt samples. Pattern recognition techniques, including principal component analysis (PCA) and NNMF, in combination with non-targeted screening, revealed distinct differences between traditional and commercial kefir while showing strong similarities between commercial kefir and yogurt. Classification of fermented dairy samples into commercial yogurt, commercial kefir, traditional mild kefir, and traditional tangy kefir was also possible for both PCA- and NNMF-based models, obtaining cross-validation (CV) error rates of 0% for PCA-LDA, PCA-kNN (k = 5), and NNMF-kNN (k = 5) and 3.3% for PCA-SVM and NNMF-LDA. Through back projection of NNMF loadings, characteristic substances were identified, indicating a mild flavor composition of commercial samples, with high concentrations of buttery-flavored diacetyl. In contrast, traditional kefir showed a diverse VOC profile with high amounts of flavorful alcohols (including ethanol and methyl-1-butanol), esters (including ethyl acetate and 3-methylbutyl acetate), and aldehydes. For validation of the results and deeper understanding, qPCR sequencing was used to evaluate the microbial consortia, confirming the microbial associations between commercial kefir and commercial yogurt and reinforcing the differences between traditional and commercial kefir. The diverse flavor profile of traditional kefir primarily results from the yeast consortium, while commercial kefir and yogurt is primarily, but not exclusively, produced through bacterial fermentation. The flavor profile of fermented dairy products may be used to directly evaluate the microbial consortium using HS-GC-HTIMS analysis.en
dc.identifier.eissn2218-1989
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/16744
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-15522
dc.language.isoenen
dc.rightsLicensee 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/).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc570 Biowissenschaften; Biologiede
dc.subject.othergas chromatography–ion mobility spectroscopyen
dc.subject.othervolatile organic compoundsen
dc.subject.otherhigh-temperature ion mobility spectrometryen
dc.subject.othernon-targeted screening using machine learningen
dc.subject.othernon-negative matrix factorizationen
dc.subject.otherdairy fermentationen
dc.subject.othertraditional and commercial kefiren
dc.subject.otherquantitative polymerase chain reactionen
dc.titleVolatilomics-Based Microbiome Evaluation of Fermented Dairy by Prototypic Headspace-Gas Chromatography–High-Temperature Ion Mobility Spectrometry (HS-GC-HTIMS) and Non-Negative Matrix Factorization (NNMF)en
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber299en
dcterms.bibliographicCitation.doi10.3390/metabo12040299en
dcterms.bibliographicCitation.issue4en
dcterms.bibliographicCitation.journaltitleMetabolitesen
dcterms.bibliographicCitation.originalpublishernameMDPIen
dcterms.bibliographicCitation.originalpublisherplaceBaselen
dcterms.bibliographicCitation.volume12en
tub.accessrights.dnbfreeen
tub.affiliationFak. 3 Prozesswissenschaften>Inst. Biotechnologie>FG Bioverfahrenstechnikde
tub.affiliation.facultyFak. 3 Prozesswissenschaftende
tub.affiliation.groupFG Bioverfahrenstechnikde
tub.affiliation.instituteInst. Biotechnologiede
tub.publisher.universityorinstitutionTechnische Universität Berlinen
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