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dc.contributor.authorFantini, Men
dc.contributor.authorPandolfini, Lucaen
dc.contributor.authorLisi, Sen
dc.contributor.authorChirichella, Men
dc.contributor.authorArisi, Ien
dc.contributor.authorTerrigno, Men
dc.contributor.authorGoracci, Men
dc.contributor.authorCremisi, Fen
dc.contributor.authorCattaneo, Aen
dc.date.accessioned2017-08-18T10:21:23Z
dc.date.available2017-08-18T10:21:23Z
dc.date.issued2017-05-15en
dc.identifier.issn1932-6203
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/266611
dc.description.abstractAntibody libraries are important resources to derive antibodies to be used for a wide range of applications, from structural and functional studies to intracellular protein interference studies to developing new diagnostics and therapeutics. Whatever the goal, the key parameter for an antibody library is its complexity (also known as diversity), i.e. the number of distinct elements in the collection, which directly reflects the probability of finding in the library an antibody against a given antigen, of sufficiently high affinity. Quantitative evaluation of antibody library complexity and quality has been for a long time inadequately addressed, due to the high similarity and length of the sequences of the library. Complexity was usually inferred by the transformation efficiency and tested either by fingerprinting and/or sequencing of a few hundred random library elements. Inferring complexity from such a small sampling is, however, very rudimental and gives limited information about the real diversity, because complexity does not scale linearly with sample size. Next-generation sequencing (NGS) has opened new ways to tackle the antibody library complexity quality assessment. However, much remains to be done to fully exploit the potential of NGS for the quantitative analysis of antibody repertoires and to overcome current limitations. To obtain a more reliable antibody library complexity estimate here we show a new, PCR-free, NGS approach to sequence antibody libraries on Illumina platform, coupled to a new bioinformatic analysis and software (Diversity Estimator of Antibody Library, DEAL) that allows to reliably estimate the complexity, taking in consideration the sequencing error.
dc.description.sponsorshipFunded by European Union Seventh Framework Program [grant No. 604102 A.C.] (Human Brain Project). https://www.humanbrainproject.eu/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
dc.languageengen
dc.language.isoenen
dc.publisherPublic Library of Science (PLoS)
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleAssessment of antibody library diversity through next generation sequencing and technical error compensationen
dc.typeArticle
prism.endingPagee0177574
prism.issueIdentifier5en
prism.publicationDate2017en
prism.publicationNamePLoS ONEen
prism.startingPagee0177574
prism.volume12en
dc.identifier.doi10.17863/CAM.12716
dcterms.dateAccepted2017-04-28en
rioxxterms.versionofrecord10.1371/journal.pone.0177574en
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2017-05-15en
dc.contributor.orcidPandolfini, Luca [0000-0003-1444-8167]
dc.identifier.eissn1932-6203
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idEC FP7 FET FLAGSHIP (604102)
cam.issuedOnline2017-05-15en


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International