A library-on-library screen reveals the breadth expansion landscape of a broadly neutralizing betacoronavirus antibody.

Broadly neutralizing antibodies (bnAbs) typically evolve cross-reactivity breadth through acquiring somatic hypermutations. While evolution of breadth requires improvement of binding to multiple antigenic variants, most experimental evolution platforms select against only one antigenic variant at a time. In this study, a yeast display library-on-library approach was applied to delineate the affinity maturation of a betacoronavirus bnAb, S2P6, against 27 spike stem helix peptides in a single experiment. Our results revealed that the binding affinity landscape of S2P6 varies among different stem helix peptides. However, somatic hypermutations that confer general improvement in binding affinity across different stem helix peptides could also be identified. We further showed that a key somatic hypermutation for breadth expansion involves long-range interaction. Overall, our work not only provides a proof-of-concept for using a library-on-library approach to analyze the evolution of antibody breadth, but also has important implications for the development of broadly protective vaccines.

Evolution and synthetic biology.

Evolutionary observations have often served as an inspiration for biological design. Decoding of the central dogma of life at a molecular level and understanding of the cellular biochemistry have been elegantly used to engineer various synthetic biology applications, including building genetic circuits in vitro and in cells, building synthetic translational systems, and metabolic engineering in cells to biosynthesize and even bioproduce complex high-value molecules. Here, we review three broad areas of synthetic biology that are inspired by evolutionary observations: (i) combinatorial approaches toward cell-based biomolecular evolution, (ii) engineering interdependencies to establish microbial consortia, and (iii) synthetic immunology. In each of the areas, we will highlight the evolutionary premise that was central toward designing these platforms. These are only a subset of the examples where evolution and natural phenomena directly or indirectly serve as a powerful source of inspiration in shaping synthetic biology and biotechnology.

Characterization, Directed Evolution, and Targeting of DNA Virus-Encoded RNA Capping Enzymes Using Phenotypic Yeast Platforms.

The constant and the sudden emergence of zoonotic human and animal viruses is a significant threat to human health, the world economy, and the world food supply. This has necessitated the development of broad-spectrum therapeutic strategies to combat these emerging pathogens. Mechanisms that are essential for viral replication and propagation have been successfully targeted in the past to develop broad-spectrum therapeutics that can be readily repurposed to combat new zoonotic pathogens. Because of the importance of viral RNA capping enzymes to viral replication and pathogenesis, as well as their presence in both DNA and RNA viruses, these viral proteins have been a long-standing therapeutic target. Here, we use genome sequencing information and yeast-based platforms (YeRC0M) to identify, characterize, and target viral genome-encoded essential RNA capping enzymes from emerging strains of DNA viruses, i.e., Monkeypox virus and African Swine Fever Virus, which are a significant threat to human and domestic animal health. We first identified and biochemically characterized these viral RNA capping enzymes and their necessary protein domains. We observed significant differences in functional protein domains and organization for RNA capping enzymes from emerging DNA viruses in comparison to emerging RNA viruses. We also observed several differences in the biochemical properties of these viral RNA capping enzymes using our phenotypic yeast-based approaches (YeRC0M) as compared to the previous in vitro studies. Further, using directed evolution, we were able to identify inactivation and attenuation mutations in these essential viral RNA capping enzymes; these data could have implications on virus biocontainment as well as live attenuated vaccine development. We also developed methods that would facilitate high-throughput phenotypic screening to identify broad-spectrum inhibitors that selectively target viral RNA capping enzymes over host RNA capping enzymes. As demonstrated here, our approaches to identify, characterize, and target viral genome-encoded essential RNA capping enzymes are highly modular and can be readily adapted for targeting emerging viral pathogens as well as their variants that emerge in the future.

Biochemical Analysis Leads to Improved Orthogonal Bioluminescent Tools.

Engineered luciferase-luciferin pairs have expanded the number of cellular targets that can be visualized in tandem. While light production relies on selective processing of synthetic luciferins by mutant luciferases, little is known about the origin of selectivity. The development of new and improved pairs requires a better understanding of the structure-function relationship of bioluminescent probes. In this work, we report a biochemical approach to assessing and optimizing two popular bioluminescent pairs: Cashew/d-luc and Pecan/4'-BrLuc. Single mutants derived from Cashew and Pecan revealed key residues for selectivity and thermal stability. Stability was further improved through a rational addition of beneficial residues. In addition to providing increased stability, the known stabilizing mutations surprisingly also improved selectivity. The resultant improved pair of luciferases are >100-fold selective for their respective substrates and highly thermally stable. Collectively, this work highlights the importance of mechanistic insight for improving bioluminescent pairs and provides significantly improved Cashew and Pecan enzymes which should be immediately suitable for multicomponent imaging applications.

Synthetic Platforms for Characterizing and Targeting of SARS-CoV-2 Genome Capping Enzymes.

Essential viral enzymes have been successfully targeted to combat the diseases caused by emerging pathogenic RNA viruses (e.g., viral RNA-dependent RNA polymerase). Because of the conserved nature of such viral enzymes, therapeutics targeting these enzymes have the potential to be repurposed to combat emerging diseases, e.g., remdesivir, which was initially developed as a potential Ebola treatment, then was repurposed for COVID-19. Our efforts described in this study target another essential and highly conserved, but relatively less explored, step in RNA virus translation and replication, i.e., capping of the viral RNA genome. The viral genome cap structure disguises the genome of most RNA viruses to resemble the mRNA cap structure of their host and is essential for viral translation, propagation, and immune evasion. Here, we developed a synthetic, phenotypic yeast-based complementation platform (YeRC0M) for molecular characterization and targeting of SARS-CoV-2 genome-encoded RNA cap-0 (guanine-N7)-methyltransferase (N7-MTase) enzyme (nsp14). In YeRC0M, the lack of yeast mRNA capping N7-MTase in yeast, which is an essential gene in yeast, is complemented by the expression of functional viral N7-MTase or its variants. Using YeRC0M, we first identified important protein domains and amino acid residues that are essential for SARS-CoV-2 nsp14 N7-MTase activity. We also expanded YeRC0M to include key nsp14 variants observed in emerging variants of SARS-CoV-2 (e.g., delta variant of SARS-CoV-2 encodes nsp14 A394V and nsp14 P46L). We also combined YeRC0M with directed evolution to identify attenuation mutations in SARS-CoV-2 nsp14. Because of the high sequence similarity of nsp14 in emerging coronaviruses, these observations could have implications on live attenuated vaccine development strategies. These data taken together reveal key domains in SARS-CoV-2 nsp14 that can be targeted for therapeutic strategies. We also anticipate that these readily tractable phenotypic platforms can also be used for the identification of inhibitors of viral RNA capping enzymes as antivirals.

Multicomponent Bioluminescence Imaging with Naphthylamino Luciferins.

Bioluminescent tools have been used for decades to image processes in complex tissues and preclinical models. However, few distinct probes are available to probe multicellular interactions. We and others are addressing this limitation by engineering new luciferases that can selectively process synthetic luciferin analogues. In this work, we explored naphthylamino luciferins as orthogonal bioluminescent probes. Three analogues were prepared using an optimized synthetic route. The luciferins were found to be robust emitters with native luciferase in vitro and in cellulo. We further screened the analogues against libraries of luciferase mutants to identify unique enzyme-substrate pairs. The new probes can be used in conjunction with existing bioluminescent tools for multi-component imaging.

Statistical Coupling Analysis-Guided Library Design for the Discovery of Mutant Luciferases.

Directed evolution has proven to be an invaluable tool for protein engineering; however, there is still a need for developing new approaches to continue to improve the efficiency and efficacy of these methods. Here, we demonstrate a new method for library design that applies a previously developed bioinformatic method, Statistical Coupling Analysis (SCA). SCA uses homologous enzymes to identify amino acid positions that are mutable and functionally important and engage in synergistic interactions between amino acids. We use SCA to guide a library of the protein luciferase and demonstrate that, in a single round of selection, we can identify luciferase mutants with several valuable properties. Specifically, we identify luciferase mutants that possess both red-shifted emission spectra and improved stability relative to those of the wild-type enzyme. We also identify luciferase mutants that possess a >50-fold change in specificity for modified luciferins. To understand the mutational origin of these improved mutants, we demonstrate the role of mutations at N229, S239, and G246 in altered function. These studies show that SCA can be used to guide library design and rapidly identify synergistic amino acid mutations from a small library.