Scientists develop a high-throughput, cell-free screening platform for anti-SARS-CoV-2 antibody discovery

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Scientists from Northwestern University, USA, have recently developed a high-throughput automated screening platform to rapidly identify SARS-CoV-2 antibodies against severe acute respiratory syndrome. The study is now available at bioRxiv* Prepress server.

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Therapeutic monoclonal antibodies developed against the skeletal protein of SARS-CoV-2 have become a promising intervention for the treatment of patients with novel coronavirus 2019 (COVID-19). Similarly, antibodies produced in response to COVID-19 vaccines have been shown to be highly effective in preventing SARS-CoV-2 infection and symptomatic diseases. Besides therapeutic use, antibodies are widely used in immunoassays for rapid detection of viral antigens.

Screening platforms currently in use are used to identify Evolution directed antigen-specific antibodies or isolate clones from single B cells from individuals recovered from COVID-19 or infected animals. Isolation, evaluation and identification of the best candidate antibody requires a series of time-consuming and labor-intensive experiments, including cloning, transfection, cell-based protein expression, protein purification, and binding assessment. The duration of these procedures ranges from weeks to months. Furthermore, these procedures often show low efficacy in identifying potent neutralizing antibodies against SARS-CoV-2.

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In the current study, scientists developed an automated antibody discovery platform that combines cell-free protein synthesis with high-throughput protein-protein interaction assay.

High-throughput antibody discovery platform

The platform combines four major steps, including cell-free DNA assembly and amplification, cell-free protein synthesis, amplified and homogenous immunosorbent assay, and an automated workflow using robotic and sonic fluid handling. The cell-free protein synthesis systems used in the study can generate antibodies directly from linear DNA templates. Likewise, the immunoassay can rapidly characterize a protein-protein interaction without the need for protein purification.

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The platform takes only 24 hours to screen and distinguish hundreds of antibodies bound to a specific antigen. For functional validation, the scientists used this automated screening platform to test a panel of 120 previously identified antibodies that target the sparse protein of SARS-CoV-2.

High-throughput, cell-free antibody assay workflow. a, Schematic diagram of the steps involved in the cell-free antibody assay workflow. b, Schematic of an AlphaLISA screen for neutralizing antibodies by competition with ACE2 of SARS-CoV-2 RBD. c, Evaluation of commercial neutralizing antibodies (nAbs) in the AlphaLISA ACE2 competition screen (n = 3 independent replicates ± SEM). d, Comparison of the reported and measured efficacy of commercial neutralizing antibodies.

Detection of protein–protein interaction using a high-throughput antibody discovery platform

The binding capacity of candidate antibodies generated using the cell-free systems was assessed using a near-luminescent amplified amplified immunosorbent assay. The high-throughput screening method can distinguish protein-protein interactions directly from those of cell-free protein synthesis. In addition, the non-covalent method stabilizes proteins of interest on donor and acceptor beads, which produce a chemiluminescent signal upon interactions. Importantly, the technique can characterize direct antigen binding as well as competitive binding of specific epitopes.

Analysis of five commercially available antibodies revealed that this immunoassay can determine the ability of the antibodies to compete with angiotensin converting enzyme 2 (ACE2) for binding to the spike receptor-binding domain (RBD) of SARS-CoV-2. Additional tests with the heavy and light chains of the antigen-binding fragment revealed that the assay is very consistent in predicting antibody aggregation.

The efficacy of the immunoassay to characterize antibody binding was evaluated using distinct panels of antibodies known to bind spike trimmer or spike RBD or compete with ACE2 for RBD binding. These experiments included a set of 120 antibodies that had already been identified and tested.

The results revealed that the amplified and homogeneous luminescent proximity-associated immunosorbent assay is highly efficient in specifically detecting antibodies that bind to spike pruning segments, spike RBD, or compete with ACE2 for RBD binding.

Since more than 90% of neutralizing antibodies act by blocking the ACE2-RBD interaction, the study compared ACE2 competition with virus neutralization. The results revealed that the assay can consistently identify strong neutralizing antibodies through the ACE2 blocking mechanism. However, the assay showed low efficiency in characterizing the less potent neutralizing antibodies.

The performance of the cell-free antibody assay workflow was evaluated on neutralizing SARS-CoV-2 antibodies.  af, AlphaLISA data are presented as means for 3 independent replicates.  The dashed line indicates three standard deviations away from the background signal.  ab, a previously published antibody binding heatmap was measured using AlphaLISA to detect S trimer binding (log10 scale), RBD binding (log10 scale), and ACE2 competition (linear scale).  AlphaLISA data are presented as the average of three independent replicates.  The lowest neutralization IC value reported for comparison (log10 scale) is also plotted and X indicates no relevant data (Supplementary Table 2).  A heat map for binding of 36 diverse antibodies.  b, Heat map of binding of all 84 antibodies in Brouwer et al.  data set.  cd, equivalence plots comparing AlphaLISA to the 84 antibodies found in Brouwer et al.  Dataset versus published ELISA data.  The dashed line indicates three standard deviations away from the background.  c, S trimer binding.  d, RBD binding.  e, Comparison of binding data between S trimer and RBD AlphaLISA.  f, Equivalence plot comparing AlphaLISA ACE2 competition data for the 84 antibodies in Brouwer et al.  Dataset versus published pseudovirus neutralization data.  Antibodies that have been reported to compete with ACE2 by Brouwer et al.  In red color.

The performance of the cell-free antibody assay workflow was evaluated on neutralizing SARS-CoV-2 antibodies. af, AlphaLISA data are presented as means for 3 independent replicates. The dashed line indicates three standard deviations away from the background signal. ab, a previously published antibody binding heatmap was measured using AlphaLISA to detect S trimer binding (log10 scale), RBD binding (log10 scale), and ACE2 competition (linear scale). AlphaLISA data are presented as the average of three independent replicates. The lowest neutralization IC value reported for comparison (log10 scale) is also plotted and X indicates no relevant data (Supplementary Table 2). A heat map for binding of 36 diverse antibodies. b, Heat map of binding of all 84 antibodies in Brouwer et al. data set. cd, equivalence plots comparing AlphaLISA to the 84 antibodies found in Brouwer et al. Dataset versus published ELISA data. The dashed line indicates three standard deviations away from the background. c, S trimer binding. d, RBD binding. e, Comparison of binding data between S trimer and RBD AlphaLISA. f, Equivalence plot comparing AlphaLISA ACE2 competition data for the 84 antibodies in Brouwer et al. Dataset versus published pseudovirus neutralization data. Antibodies that have been reported to compete with ACE2 by Brouwer et al. In red color.

Study the importance

The study describes the development and validation of a high-throughput automated antibody discovery platform that uses cell-free assay and expression systems. The main advantage of the platform is fast response time and productivity. For example, a single researcher can characterize a group of 120 antibodies within 24 hours using this method.

Another important feature is the direct profiling of complex antibodies using cell-free extracts. This waives the need for protein purification procedures that are often the defining step in antibody screening.

As reported by the scientists, this high-throughput platform can be used for fast and easy identification of potent antibodies for therapeutic, diagnostic and other essential research applications.

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