High Resolution Time-of-Flight Mass Spectrometry Fingerprinting of Metabolites from Cecum and Distal Colon Contents of Rats Fed Resistant Starch

dc.contributor.author Anderson, Timothy
dc.contributor.author Jane, Jay-Lin
dc.contributor.author Birt, Diane
dc.contributor.author Ai, Yongfeng
dc.contributor.author Jones, Roger
dc.contributor.author Jane, Jay-lin
dc.contributor.author Zhao, Yinsheng
dc.contributor.author Houk, Robert
dc.contributor.author McClelland, John
dc.contributor.department Ames National Laboratory
dc.date 2018-02-15T12:41:34.000
dc.date.accessioned 2020-06-29T23:26:09Z
dc.date.available 2020-06-29T23:26:09Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2014
dc.date.embargo 2014-11-24
dc.date.issued 2014-01-01
dc.description.abstract <p>Time-of-flight mass spectrometry along with statistical analysis was utilized to study metabolic profiles among rats fed resistant starch (RS) diets. Fischer 344 rats were fed four starch diets consisting of 55 % (w/w, dbs) starch. A control starch diet consisting of corn starch was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. A subgroup received antibiotic treatment to determine if perturbations in the gut microbiome were long lasting. A second subgroup was treated with azoxymethane (AOM), a carcinogen. At the end of the 8-week study, cecal and distal colon content samples were collected from the sacrificed rats. Metabolites were extracted from cecal and distal colon samples into acetonitrile. The extracts were then analyzed on an accurate-mass time-of-flight mass spectrometer to obtain their metabolic profile. The data were analyzed using partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis utilized a training set and verification set to classify samples within diet and treatment groups. PLS-DA could reliably differentiate the diet treatments for both cecal and distal colon samples. The PLS-DA analyses of the antibiotic and no antibiotic-treated subgroups were well classified for cecal samples and modestly separated for distal colon samples. PLS-DA analysis had limited success separating distal colon samples for rats given AOM from those not treated; the cecal samples from AOM had very poor classification. Mass spectrometry profiling coupled with PLS-DA can readily classify metabolite differences among rats given RS diets.</p>
dc.description.comments <p>This is a manuscript of an article in <em>Analytical and Bioanalytical Chemistry</em> 406 (2014): 745. Posted with permission. The final publication is available at Springer via <a href="http://dx.doi.org/10.1007/s00216-013-7523-8" target="_blank">http://dx.doi.org/10.1007/s00216-013-7523-8</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/ameslab_pubs/240/
dc.identifier.articleid 1237
dc.identifier.contextkey 6390140
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ameslab_pubs/240
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/7791
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/ameslab_pubs/240/2014_Jones_HighResolution.pdf|||Fri Jan 14 22:52:17 UTC 2022
dc.source.uri 10.1007/s00216-013-7523-8
dc.subject.disciplines Biochemistry, Biophysics, and Structural Biology
dc.subject.disciplines Chemistry
dc.subject.disciplines Food Chemistry
dc.subject.disciplines Food Science
dc.subject.disciplines Mechanical Engineering
dc.subject.disciplines Nutrition
dc.subject.keywords resistant starch
dc.subject.keywords mass spectrometry
dc.subject.keywords metabolites
dc.subject.keywords PLS-DA
dc.title High Resolution Time-of-Flight Mass Spectrometry Fingerprinting of Metabolites from Cecum and Distal Colon Contents of Rats Fed Resistant Starch
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isAuthorOfPublication a56e515d-7fd9-4768-9f73-42a248e128b7
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relation.isAuthorOfPublication 72e25a81-2813-4101-9504-8f38266732b7
relation.isOrgUnitOfPublication 25913818-6714-4be5-89a6-f70c8facdf7e
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