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A New Workflow to Generate Monoclonal Antibodies against Microorganisms

  • Monoclonal antibodies are used worldwide as highly potent and efficient detection reagents for research and diagnostic applications. Nevertheless, the specific targeting of complex antigens such as whole microorganisms remains a challenge. To provide a comprehensive workflow, we combined bioinformatic analyses with novel immunization and selection tools to design monoclonal antibodies for the detection of whole microorganisms. In our initial study, we used the human pathogenic strain E. coli O157:H7 as a model target and identified 53 potential protein candidates by using reverse vaccinology methodology. Five different peptide epitopes were selected for immunization using epitope-engineered viral proteins. The identification of antibody-producing hybridomas was performed by using a novel screening technology based on transgenic fusion cell lines. Using an artificial cell surface receptor expressed by all hybridomas, the desired antigen-specific cells can be sorted fast and efficiently out of the fusion cell pool. Selected antibodyMonoclonal antibodies are used worldwide as highly potent and efficient detection reagents for research and diagnostic applications. Nevertheless, the specific targeting of complex antigens such as whole microorganisms remains a challenge. To provide a comprehensive workflow, we combined bioinformatic analyses with novel immunization and selection tools to design monoclonal antibodies for the detection of whole microorganisms. In our initial study, we used the human pathogenic strain E. coli O157:H7 as a model target and identified 53 potential protein candidates by using reverse vaccinology methodology. Five different peptide epitopes were selected for immunization using epitope-engineered viral proteins. The identification of antibody-producing hybridomas was performed by using a novel screening technology based on transgenic fusion cell lines. Using an artificial cell surface receptor expressed by all hybridomas, the desired antigen-specific cells can be sorted fast and efficiently out of the fusion cell pool. Selected antibody candidates were characterized and showed strong binding to the target strain E. coli O157:H7 with minor or no cross-reactivity to other relevant microorganisms such as Legionella pneumophila and Bacillus ssp. This approach could be useful as a highly efficient workflow for the generation of antibodies against microorganisms.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Markus GöthelORCiDGND, Martin ListekGND, Katrin MesserschmidtORCiDGND, Anja SchlörORCiD, Anja Hönow, Katja HanackORCiDGND
URN:urn:nbn:de:kobv:517-opus4-523341
DOI:https://doi.org/10.25932/publishup-52334
ISSN:1866-8372
Titel des übergeordneten Werks (Deutsch):Mathematisch-Naturwissenschaftliche Reihe
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1174)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:07.09.2021
Erscheinungsjahr:2021
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:20.10.2021
Freies Schlagwort / Tag:antibody producing cell selection; epitope prediction; hybridoma; monoclonal antibody
Ausgabe:20
Aufsatznummer:9359
Seitenanzahl:17
Quelle:Appl. Sci. 2021, 11(20), 9359; https://doi.org/10.3390/app11209359
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer Review:Referiert
Publikationsweg:Open Access / Green Open-Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
Externe Anmerkung:Bibliographieeintrag der Originalveröffentlichung/Quelle
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