Abstract
The control of antibody specificity plays pivotal roles in key technological fields such as diagnostics and therapeutics. During the development of immunoassays (IAs) for the biosensing of pathogens in food matrices, we have found a way to rationalize and control the specificity of polyclonal antibodies (sera) for a complex analytical target (the Salmonella genus), in terms of number of analytes (Salmonella species) and potential cross-reactivity with similar analytes (other bacteria strains). Indeed, the biosensing of Salmonella required the development of sera and serum mixtures displaying homogeneous specificity for a large set of strains showing broad biochemical variety (54 Salmonella serovars tested in this study), which partially overlaps with the molecular features of other class of bacteria (like specific serogroups of E. coli). To achieve a trade-off between specificity harmonisation and maximization, we have developed a strategy based on the conversion of the specificity profiles of individual sera in to numerical descriptors, which allow predicting the capacity of serum mixtures to detect multiple bacteria strains. This approach does not imply laborious purification steps and results advantageous for process scaling-up, and may help in the customization of the specificity profiles of antibodies needed for diagnostic and therapeutic applications such as multi-analyte detection and recombinant antibody engineering, respectively.
Highlights
The control of antibody specificity plays pivotal roles in key technological fields such as diagnostics and therapeutics
The general workflow of this study is based on the four stages of development summarized in Scheme 1, such as: a) sera production and their characterization; b) The use of different descriptors to rank the sera; c) Specificity harmonization of serum mixtures; and d) Serum mixtures optimization, in terms of number of sera and fine tuning of the specificity profiles
The rationale is to exploit rabbits immune repertoires to generate a library of reagents, and to verify which one of the following scenarios is the most suitable to address the problem of custom specificity profiles generation: [1] use of individual sera obtained upon immunization against multiple strains; [2] use of multiple sera obtained by immunization against individual strains: or [3] combinations between sera belonging to the two aforementioned categories, where elements from [1] will serve as a “base” and elements from [2] as further constituents for finer specificity tuning against selected strains
Summary
The control of antibody specificity plays pivotal roles in key technological fields such as diagnostics and therapeutics. To achieve a trade-off between specificity harmonisation and maximization, we have developed a strategy based on the conversion of the specificity profiles of individual sera in to numerical descriptors, which allow predicting the capacity of serum mixtures to detect multiple bacteria strains This approach does not imply laborious purification steps and results advantageous for process scaling-up, and may help in the customization of the specificity profiles of antibodies needed for diagnostic and therapeutic applications such as multi-analyte detection and recombinant antibody engineering, respectively. The possibility of modulating Abs sensitivity and specificity upon mixing multiple constituents was long ago explored by Ehrlich et al, which were able to strongly increase the analytical sensitivity of ELISAs against the human chorionic gonadotropin14 In their studies, different monoclonal antibodies (mAbs) were mixed, resulting in cooperation to form circular complexes between mAbs and antigen, and sensitivity and specificity enhancement. These and other studies paved the way for the concept of using oligoclonal antibodies (oAbs, mixtures of selected mAbs), which are nowadays commercialized for diagnostic applications (e.g. oligoclonal anti-species labelled antibodies), and under consideration for therapeutic applications (e.g. oligoclonal mAbs/ recombinant pAbs mixtures)
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