Scientists Develop High Throughput Cellless Screening Platform for Discovery of Anti-SARS-CoV-2 Antibodies

Scientists at Northwestern University in the United States recently developed a high-throughput automated screening platform to rapidly identify antibodies to coronavirus 2 (SARS-CoV-2) in severe acute respiratory syndrome. The study is currently available on the bioRxiv* preprint server.

Background

Therapeutic monoclonal antibodies developed against the SARS-CoV-2 spike protein have become a promising intervention to treat critically ill patients of the 2019 coronavirus (COVID-19). Likewise, antibodies generated in response to COVID-19 vaccines have shown great efficacy in preventing SARS-CoV-2 infection and symptomatic illnesses. Besides therapeutic use, antibodies are widely used in immunoassays for the rapid detection of viral antigens.

Screening platforms currently in use for the identification of antigen-specific antibodies use directed evolution or isolation of single B cell clones from individuals recovered by COVID-19 or from infected animals. . Isolation, evaluation and identification of the best antibody candidate requires a series of tedious and laborious experiments, including cloning, transfection, cell-based protein expression, protein purification and evaluation. of the link. The turnaround time for these procedures ranges from a few weeks to several months. In addition, these procedures often exhibit low efficiency in identifying potent neutralizing antibodies against SARS-CoV-2.

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

High throughput antibody discovery platform

The platform combines four main steps, including cell-free DNA assembly and amplification, cell-free protein synthesis, an amplified luminescent proximity homogeneous binding immunosorbent assay, and an automated workflow using robotic manipulation and acoustics of liquids. The cell-free protein synthesis systems used in the study can generate antibodies directly from linear DNA models. Likewise, the immunoassay can quickly characterize the protein-protein interaction without requiring protein purification.

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

A high throughput cell-free antibody screening workflow. a, Diagram of the steps involved in the cell-free antibody screening workflow. b, Schematic of the AlphaLISA screen for neutralizing antibodies by competition with ACE2 for SARS-CoV-2 RBD. c, Evaluation of Commercial Neutralizing Antibodies (nAbs) in the AlphaLISA ACE2 Competition Screen (n = 3 independent repeats ± SEM). d, Comparison of reported and measured potencies of commercial neutralizing antibodies.

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

The binding capacity of candidate antibodies generated using cell-free systems was assessed using the Amplified Luminescent Proximity Homogeneous Bound Immunosorbent Assay. This high throughput screening method can characterize protein-protein interactions directly from cell-free protein synthesis reactions. In addition, the method non-covalently immobilizes the proteins of interest on the donor and acceptor beads, which produce a chemiluminescent signal during the interactions. Importantly, the technique can characterize direct antibody-antigen binding as well as competitive binding for specific epitopes.

Analysis of five commercially available antibodies revealed that this immunoassay could determine the ability of the antibodies to compete with the human angiotensin converting enzyme 2 (ACE2) to bind to the receptor binding domain of SARS-CoV-2 peak (RBD). Further testing with heavy and light chains of the antigen binding fragment revealed that the test is very consistent in predicting antibody assembly.

The efficacy of the immunoassay to characterize antibody binding was further assessed using separate panels of antibodies known to bind to the trimer peak or the RBD tip or to compete with ACE2 for the. link to RBD. These experiments included a panel of 120 antibodies already identified and tested.

The results revealed that the immunosorbent assay homogeneously bound to amplified luminescent proximity is very effective in specifically detecting antibodies that bind to the trimer tip, tip RBD or compete with ACE2 for binding to RBD. .

Since more than 90% of neutralizing antibodies work by blocking the ACE2 – RBD interaction, the study compared ACE2 competition against virus neutralization. The results revealed that the test could consistently identify strong neutralizing antibodies through the ACE2 blocking mechanism. However, the test showed low efficiency in characterizing less potent neutralizing antibodies.

Cell-free antibody screening workflow performance evaluated on SARS-CoV-2 neutralizing antibodies.  af, AlphaLISA data are presented as the mean of 3 independent replicates.  A dotted line indicates three standard deviations of the background signal.  ab, Heatmap of previously published antibody binding 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 3 independent replicates.  The lowest reported neutralization IC50 value is also plotted for comparison (log10 scale) and an X indicates that no relevant data is available (Supplementary Table 2).  a Heatmap of the binding of 36 different antibodies.  b, Heatmap of the binding of all 84 antibodies in the Brouwer et al.  database.  cd, Parity plots comparing AlphaLISA to 84 antibodies in Brouwer et al.  dataset compared to published ELISA data.  A dotted line indicates three standard deviations from the background.  c, S trim binding.  d, RBD bond.  e, Comparison of S trimer and RBD AlphaLISA binding data.  f, Parity graph comparing AlphaLISA ACE2 competition data for the 84 antibodies in Brouwer et al.  dataset versus published pseudovirus neutralization data.  The antibodies which have been reported to compete with ACE2 by Brouwer et al.  are drawn in red.

Cell-free antibody screening workflow performance evaluated on SARS-CoV-2 neutralizing antibodies. af, AlphaLISA data are presented as the mean of 3 independent replicates. A dotted line indicates three standard deviations of the background signal. ab, Heatmap of previously published antibody binding 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 3 independent replicates. The lowest reported neutralization IC50 value is also plotted for comparison (log10 scale) and an X indicates that no relevant data is available (Supplementary Table 2). a Heatmap of the binding of 36 different antibodies. b, Heatmap of the binding of all 84 antibodies in the Brouwer et al. database. cd, Parity plots comparing AlphaLISA to 84 antibodies in Brouwer et al. dataset compared to published ELISA data. A dotted line indicates three standard deviations from the background. c, S trim binding. d, RBD bond. e, Comparison of S trimer and RBD AlphaLISA binding data. f, Parity graph comparing AlphaLISA ACE2 competition data for the 84 antibodies in Brouwer et al. dataset versus published pseudovirus neutralization data. The antibodies which have been reported to compete with ACE2 by Brouwer et al. are drawn in red.

Importance of the study

The study describes the development and validation of a high throughput automated antibody discovery platform that uses cell-free expression and screening systems. The main advantage of the platform is speed of execution and throughput. For example, a single researcher can characterize a panel of 120 antibodies in 24 hours using this method.

Another important advantage is the direct profiling of the antibodies synthesized using cell-free extracts. This eliminates the need for protein purification procedures which are often considered the limiting step in antibody screening.

As the scientists mentioned, this high throughput platform can be used for quick and easy identification of potent antibodies for therapeutic, diagnostic and other basic research applications.

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