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Sensitive detection of glucagon aggregation using amyloid fibril‐specific antibodies
dc.contributor.authorStimple, Samuel D.
dc.contributor.authorKalyoncu, Sibel
dc.contributor.authorDesai, Alec A.
dc.contributor.authorMogensen, Jesper E.
dc.contributor.authorSpang, Lotte T.
dc.contributor.authorAsgreen, Désirée J.
dc.contributor.authorStaby, Arne
dc.contributor.authorTessier, Peter M.
dc.date.accessioned2019-08-09T17:15:51Z
dc.date.availableWITHHELD_13_MONTHS
dc.date.available2019-08-09T17:15:51Z
dc.date.issued2019-08
dc.identifier.citationStimple, Samuel D.; Kalyoncu, Sibel; Desai, Alec A.; Mogensen, Jesper E.; Spang, Lotte T.; Asgreen, Désirée J. ; Staby, Arne; Tessier, Peter M. (2019). "Sensitive detection of glucagon aggregation using amyloid fibril‐specific antibodies." Biotechnology and Bioengineering 116(8): 1868-1877.
dc.identifier.issn0006-3592
dc.identifier.issn1097-0290
dc.identifier.urihttps://hdl.handle.net/2027.42/150615
dc.description.abstractSensitive detection of protein aggregates is important for evaluating the quality of biopharmaceuticals and detecting misfolded proteins in several neurodegenerative diseases. However, it is challenging to detect extremely low concentrations (<10 ppm) of aggregated protein in the presence of high concentrations of soluble protein. Glucagon, a peptide hormone used in the treatment of extreme hypoglycemia, is aggregation‐prone and forms amyloid fibrils. Detection of glucagon fibrils using conformation‐specific antibodies is an attractive approach for identifying such aggregates during process and formulation development. Therefore, we have used yeast surface display and magnetic‐activated cell sorting to sort single‐chain antibody libraries to identify antibody variants with high conformational specificity for glucagon fibrils. Notably, we find several high‐affinity antibodies that display excellent selectivity for glucagon fibrils, and we have integrated these antibodies into a sensitive immunoassay. Surprisingly, the sensitivity of our assay—which involves direct (nonantibody mediated) glucagon immobilization in microtiter plates—can be significantly enhanced by pretreating the microtiter plates with various types of globular proteins before glucagon immobilization. Moreover, increased total concentrations of glucagon peptide also significantly improve the sensitivity of our assay, which appears to be due to the strong seeding activity of immobilized fibrils at high glucagon concentrations. Our final assay is highly sensitive (fibril detection limit of ~0.5–1 ppm) and is >20 times more sensitive than detection using a conventional, amyloid‐specific fluorescent dye (Thioflavin T). We expect that this type of sensitive immunoassay can be readily integrated into the drug development process to improve the generation of safe and potent peptide therapeutics.Sensitive detection of protein aggregates is important for evaluating the quality of biopharmaceuticals and detecting misfolded proteins in several neurodegenerative diseases. However, it is challenging to detect extremely low concentrations (<10 ppm) of aggregated protein in the presence of high concentrations of soluble protein. Glucagon, a peptide hormone used in the treatment of extreme hypoglycemia, is aggregation‐prone and forms amyloid fibrils. Conformation‐specific antibodies were generated that recognize glucagon fibrils in a highly selective manner, and these antibodies were integrated into an ELISA method that is >20 times more sensitive than conventional methods for detecting glucagon fibrils.
dc.publisherWiley Periodicals, Inc.
dc.subject.otherprotein
dc.subject.otherantibody
dc.subject.otherconformation
dc.subject.otherdirected evolution
dc.subject.otheraggregate
dc.titleSensitive detection of glucagon aggregation using amyloid fibril‐specific antibodies
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelPublic Health
dc.subject.hlbsecondlevelBiological Chemistry
dc.subject.hlbsecondlevelEcology and Evolutionary Biology
dc.subject.hlbsecondlevelMathematics
dc.subject.hlbsecondlevelNatural Resources and Environment
dc.subject.hlbsecondlevelStatistics and Numeric Data
dc.subject.hlbtoplevelHealth Sciences
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/150615/1/bit26994_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/150615/2/bit26994.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/150615/3/bit26994-sup-0001-Supporting_Information__submission_.pdf
dc.identifier.doi10.1002/bit.26994
dc.identifier.sourceBiotechnology and Bioengineering
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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