A New Workflow to Generate Monoclonal Antibodies against Microorganisms

Markus Göthel,Katja Hanack,Anja Schlör,Katrin Messerschmidt,Martin Listek,Anja Hönow

doi:10.3390/app11209359

Abstract

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 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.

Highlights

The sorted hybridoma cells were seeded in 96-well plates (Greiner bio-one) and cultivated under 6% CO2 at 37 ◦ C and 95% humidity in RPMI full-growth medium supplemented with 10% fetal calf serum (FCS), 2 mM glutamine, 50 μM ß-mercaptoethanol, and
To generate Monoclonal antibodies (mAbs) specific for living bacteria in food or drinking water, the potential target proteins need to be localized on the cell surface
A flow cytometry approach is a useful and sensitive alternative to screen for potential binders due to its ability to gate on whole bacteria and identify mAbs that bind on cell surface-related targets [20]

Summary

Introduction

Monoclonal antibodies (mAbs) are highly versatile biomolecules used manifold in analytical and diagnostic systems for the detection of targets ranging from low molecular weight substances to whole microorganisms [1,2,3]. In addition to the complexity of pathogens, the generation of specific mAbs is limited by the complex procedure of inducing strain-specific immune responses and the laborious selection of desired hybridoma cell lines [5]. With this objective, we performed an initial proof of concept study by combining bioinformatic epitope prediction with novel immunization and selection tools to identify antibody candidates that can discriminate E

Methods

Results

Conclusion