Directed evolution of potent neutralizing nanobodies against SARS-CoV-2 using CDR-swapping mutagenesis

Abstract

There is widespread interest in facile methods for generating potent neutralizing antibodies, nanobodies, and other affinity proteins against SARS-CoV-2 and related viruses to address current and future pandemics. While isolating antibodies from animals and humans are proven approaches, these methods are limited to the affinities, specificities, and functional activities of antibodies generated by the immune system. Here we report a surprisingly simple directed evolution method for generating nanobodies with high affinities and neutralization activities against SARS-CoV-2. We demonstrate that complementarity-determining region swapping between low-affinity lead nanobodies, which we discovered unintentionally but find is simple to implement systematically, results in matured nanobodies with unusually large increases in affinity. Importantly, the matured nanobodies potently neutralize both SARS-CoV-2 pseudovirus and live virus, and possess drug-like biophysical properties. We expect that our methods will improve in vitro nanobody discovery and accelerate the generation of potent neutralizing nanobodies against diverse coronaviruses.

Keywords: ACE2; COVID-19; RBD; affinity; maturation; nanobody; neutralization; receptor-binding domain; spike; yeast.

Graphical abstract

Figure 1

Summary of the discovery and affinity maturation of nanobodies against the spike protein of SARS-CoV-2 A synthetic nanobody library displayed on yeast was screened against the receptor-binding domain (RBD), spike (S1) protein, and spike protein trimer of SARS-CoV-2 by MACS and FACS. Two lead clones (KA1 and KC3) were identified and affinity matured using error-prone PCR. The sublibraries were screened against the S1 protein by FACS to isolate nanobody variants (KA1.ep1, KC3.ep3, and KC3.ep5) with superior binding activity relative to a potent neutralizing nanobody generated via immunization (Ty1).

Figure 2

Affinity-matured nanobodies possess a combination of CDRs from the two lead clones (A) Affinity maturation of lead nanobodies KA1 and KC3 via error-prone PCR results in nanobody variants that possess one CDR from each lead nanobody (CDR2 [red] from KA1 and CDR3 [blue] from KC3) in addition to one CDR (CDR1 [green]) that differs by only a single mutation. (B) Nanobody sequences (Kabat numbering) for the three affinity-matured variants. Residues that are different from KA1.ep1 are indicated with an amino acid letter.

Figure 3

Affinity-matured nanobodies potently neutralize SARS-CoV-2 pseudovirus and live virus (A) Neutralization results for nanobodies as bivalent Fc-fusion proteins (KA1, KC3, KA1.ep1, KC3.ep3, KC3.ep5, and Ty1) and an antibody (CB6) for inhibiting pseudovirus infectivity in a luciferase-based, HEK293T reporter cell line. Pseudovirus particles were preincubated with antibodies and added to reporter cells, and luciferase signal was measured after 48 h. (B) Neutralization results for nanobodies as bivalent Fc-fusion proteins (KC3.ep3, Ty1) and antibodies (CB6) for inhibiting live virus infection of VeroE6 cells. Nanobody and antibody dilutions were tested in eight replicate wells each. After cells were incubated with virus and nanobodies or antibody for 3 days, the cells were examined microscopically for visible cytopathic effect. Wells with any degree of visible, virus-induced cytopathic effect were scored as positive for infection. In (A), the data are averages of four or five repeats, and the error bars are standard deviations. In (B), the data are averages of two to four repeats, and the error bars are standard deviations.

Figure 4

Potent neutralizing nanobodies display high monovalent and bivalent affinities for the SARS-CoV-2 receptor-binding domain (A) Monovalent binding of nanobodies displayed on the surface of yeast to biotinylated SARS-CoV-2 receptor-binding domain. (B) Bivalent binding of nanobodies (Fc-fusion proteins) and antibodies (IgGs) to biotinylated SARS-CoV-2 receptor-binding domain immobilized on magnetic beads. The results are averages from three independent experiments, and the error bars are standard deviations.

Figure 5

Affinity-matured nanobody recognizes an epitope in the receptor-binding domain that overlaps with epitopes recognized by ACE2 and other potent SARS-CoV-2 neutralizing nanobodies and antibodies Bivalent nanobodies (KC3.ep3, VHH-72, and Ty1), antibodies (S309, CR3022, CB6, and C119) and ACE2 were preincubated with biotinylated receptor-binding domain of SARS-CoV-2 (5 nM) over a range of nanobody, antibody, and ACE2 concentrations, and then the mixtures were added to yeast cells displaying monovalent KC3.ep3. The percentage bound receptor-binding domain is reported relative to the amount bound in the absence of preblocking. The results are averages from three independent repeats, and the error bars are standard deviations.

Figure 6

Affinity-matured nanobodies display high stability and specificity (A) Melting temperatures of bivalent nanobodies and antibodies evaluated via differential scanning fluorimetry. (B) Non-specific binding of bivalent nanobodies and antibodies (immobilized on magnetic beads) was evaluated via incubation with biotinylated soluble membrane proteins from CHO cells and detection of non-specific binding via flow cytometry. Control antibodies with high (emibetuzumab) and low (elotuzumab) non-specific binding were also evaluated for comparison. The two control antibodies are not identical to the actual drugs, as they have the variable regions of the actual drugs and a common IgG1 framework. In (A) and (B), the results are averages from three independent repeats, and the error bars are standard deviations.

Figure 7

Nanobodies with nanomolar monovalent affinities can be generated via CDR-swapping mutagenesis without the need for lead clone identification and subsequent affinity maturation Nanobodies were selected from a non-immune library with (KA1.ep1, K7.13, K7.19) or without (KC3, KA1, KC1) CDR-swapping mutagenesis, and the selected clones were evaluated in terms of their monovalent binding affinities for the SARS-CoV-2 receptor-binding domain. The results are averages from two independent experiments, and the error bars are standard deviations.