Directed evolution of antibody fragments with monovalent femtomolar antigen-binding affinity

Cancer therapy with antibodies

The greatest challenge in cancer therapy is to eradicate cancer cells with minimal damage to normal cells. Targeted therapy has been developed to meet that challenge, showing a substantially increased therapeutic index compared with conventional cancer therapies. Antibodies are important members of the family of targeted therapeutic agents because of their extraordinarily high specificity to the target antigens. Therapeutic antibodies use a range of mechanisms that directly or indirectly kill the cancer cells. Early antibodies were developed to directly antagonize targets on cancer cells. This was followed by advancements in linker technologies that allowed the production of antibody-drug conjugates (ADCs) that guide cytotoxic payloads to the cancer cells. Improvement in our understanding of the biology of T cells led to the production of immune checkpoint-inhibiting antibodies that indirectly kill the cancer cells through activation of the T cells. Even more recently, bispecific antibodies were synthetically designed to redirect the T cells of a patient to kill the cancer cells. In this Review, we summarize the different approaches used by therapeutic antibodies to target cancer cells. We discuss their mechanisms of action, the structural basis for target specificity, clinical applications and the ongoing research to improve efficacy and reduce toxicity.

Development of a new affinity maturation protocol for the construction of an internalizing anti-nucleolin antibody library

Over the last decades, monoclonal antibodies have substantially improved the treatment of several conditions. The continuous search for novel therapeutic targets and improvements in antibody's structure, demands for a constant optimization of their development. In this regard, modulation of an antibody's affinity to its target has been largely explored and culminated in the discovery and optimization of a variety of molecules. It involves the creation of antibody libraries and selection against the target of interest. In this work, we aimed at developing a novel protocol to be used for the affinity maturation of an antibody previously developed by our group. An antibody library was constructed using an in vivo random mutagenesis approach that, to our knowledge, has not been used before for antibody development. Then, a cell-based phage display selection protocol was designed to allow the fast and simple screening of antibody clones capable of being internalized by target cells. Next generation sequencing coupled with computer analysis provided an extensive characterization of the created library and post-selection pool, that can be used as a guide for future antibody development. With a single selection step, an enrichment in the mutated antibody library, given by a decrease in almost 50% in sequence diversity, was achieved, and structural information useful in the study of the antibody-target interaction in the future was obtained.

Mechanical force determines chimeric antigen receptor microclustering and signaling

Chimeric antigen receptor (CAR) T cells are activated to trigger the lytic machinery after antigen engagement, and this has been successfully applied clinically as therapy. The mechanism by which antigen binding leads to the initiation of CAR signaling remains poorly understood. Here, we used a set of short double-stranded DNA (dsDNA) tethers with mechanical forces ranging from ∼12 to ∼51 pN to manipulate the mechanical force of antigen tether and decouple the microclustering and signaling events. Our results revealed that antigen-binding-induced CAR microclustering and signaling are mechanical force dependent. Additionally, the mechanical force delivered to the antigen tether by the CAR for microclustering is generated by autonomous cell contractility. Mechanistically, the mechanical-force-induced strong adhesion and CAR diffusion confinement led to CAR microclustering. Moreover, cytotoxicity may have a lower mechanical force threshold than cytokine generation. Collectively, these results support a model of mechanical-force-induced CAR microclustering for signaling.

Identification of a potent PCNA-p15-interaction inhibitor by autodisplay-based peptide library screening

Proliferating cell nuclear antigen (PCNA) is an essential factor for DNA metabolism. The influence of PCNA on DNA replication and repair, combined with the high expression rate of PCNA in various tumours renders PCNA a promising target for cancer therapy. In this context, an autodisplay-based screening method was developed to identify peptidic PCNA interaction inhibitors. A 12-mer randomized peptide library consisting of 2.54 × 106 colony-forming units was constructed and displayed at the surface of Escherichia coli BL21 (DE3) cells by autodisplay. Cells exhibiting an enhanced binding to fluorescent mScarlet-I-PCNA were enriched in four sorting rounds by flow cytometry. This led to the discovery of five peptide variants with affinity to mScarlet-I-PCNA. Among these, P3 (TCPLRWITHDHP) exhibited the highest binding signal. Subsequent flow cytometric analysis revealed a dissociation constant of 0.62 μM for PCNA-P3 interaction. Furthermore, the inhibition of PCNA interactions was investigated using p15, a PIP-box containing protein involved in DNA replication and repair. P3 inhibited the PCNA-p1551-70 interaction with a half maximal inhibitory activity of 16.2 μM, characterizing P3 as a potent inhibitor of the PCNA-p15 interaction.

Rationalizing diverse binding mechanisms to the same protein fold: insights for ligand recognition and biosensor design

The engineering of novel protein-ligand binding interactions, particularly for complex drug-like molecules, is an unsolved problem which could enable many practical applications of protein biosensors. In this work, we analyzed two engineer ed biosensors, derived from the plant hormone sensor PYR1, to recognize either the agrochemical mandipropamid or the synthetic cannabinoid WIN55,212-2. Using a combination of quantitative deep mutational scanning experiments and molecular dynamics simulations, we demonstrated that mutations at common positions can promote protein-ligand shape complementarity and revealed prominent differences in the electrostatic networks needed to complement diverse ligands. MD simulations indicate that both PYR1 protein-ligand complexes bind a single conformer of their target ligand that is close to the lowest free energy conformer. Computational design using a fixed conformer and rigid body orientation led to new WIN55,212-2 sensors with nanomolar limits of detection. This work reveals mechanisms by which the versatile PYR1 biosensor scaffold can bind diverse ligands. This work also provides computational methods to sample realistic ligand conformers and rigid body alignments that simplify the computational design of biosensors for novel ligands of interest.

Engineering the ADDobody protein scaffold for generation of high-avidity ADDomer super-binders

Adenovirus-derived nanoparticles (ADDomer) comprise 60 copies of adenovirus penton base protein (PBP). ADDomer is thermostable, rendering the storage, transport, and deployment of ADDomer-based therapeutics independent of a cold chain. To expand the scope of ADDomers for new applications, we engineered ADDobodies, representing PBP crown domain, genetically separated from PBP multimerization domain. We inserted heterologous sequences into hyper-variable loops, resulting in monomeric, thermostable ADDobodies expressed at high yields in Escherichia coli. The X-ray structure of an ADDobody prototype validated our design. ADDobodies can be used in ribosome display experiments to select a specific binder against a target, with an enrichment factor of ∼104-fold per round. ADDobodies can be re-converted into ADDomers by genetically reconnecting the selected ADDobody with the PBP multimerization domain from a different species, giving rise to a multivalent nanoparticle, called Chimera, confirmed by a 2.2 Å electron cryo-microscopy structure. Chimera comprises 60 binding sites, resulting in ultra-high, picomolar avidity to the target.

Synthetic development of a broadly neutralizing antibody against snake venom long-chain α-neurotoxins

Snakebite envenoming is a major global public health concern for which improved therapies are urgently needed. The antigenic diversity present in snake venom toxins from various species presents a considerable challenge to the development of a universal antivenom. Here, we used a synthetic human antibody library to find and develop an antibody that neutralizes long-chain three-finger α-neurotoxins produced by numerous medically relevant snakes. Our antibody bound diverse toxin variants with high affinity, blocked toxin binding to the nicotinic acetylcholine receptor in vitro, and protected mice from lethal venom challenge. Structural analysis of the antibody-toxin complex revealed a binding mode that mimics the receptor-toxin interaction. The overall workflow presented is generalizable for the development of antibodies that target conserved epitopes among antigenically diverse targets, and it offers a promising framework for the creation of a monoclonal antibody-based universal antivenom to treat snakebite envenoming.

Advancing Antibody Engineering through Synthetic Evolution and Machine Learning

Abs are versatile molecules with the potential to achieve exceptional binding to target Ags, while also possessing biophysical properties suitable for therapeutic drug development. Protein display and directed evolution systems have transformed synthetic Ab discovery, engineering, and optimization, vastly expanding the number of Ab clones able to be experimentally screened for binding. Moreover, the burgeoning integration of high-throughput screening, deep sequencing, and machine learning has further augmented in vitro Ab optimization, promising to accelerate the design process and massively expand the Ab sequence space interrogated. In this Brief Review, we discuss the experimental and computational tools employed in synthetic Ab engineering and optimization. We also explore the therapeutic challenges posed by developing Abs for infectious diseases, and the prospects for leveraging machine learning-guided protein engineering to prospectively design Abs resistant to viral escape.

A Directed Evolution Protocol for Engineering Minimal Transcription Factors, Based on CIS Display

Directed evolution is an efficient strategy for obtaining desired biomolecules. Since the 1990s, the emergence of display techniques has enabled high-throughput screening of functional proteins. However, classical methods require library construction by plasmid cloning and are limited by transformation efficiencies, typically limiting library sizes to ~106-107 variants. More recently, in vitro techniques have emerged that avoid cloning, allowing library sizes of >1012 members. One of these, CIS display, is a DNA-based display technique which allows high-throughput selection of biomolecules in vitro. CIS display creates the genotype-phenotype link required for selection by a DNA replication initiator protein, RepA, that binds exclusively to the template from which it has been expressed. This method has been successfully used to evolve new protein-protein interactions but has not been used before to select DNA-binding proteins, which are major components in mammalian synthetic biology. In this chapter, we describe a directed evolution method using CIS display to efficiently select functional DNA-binding proteins from pools of nonbinding proteins. The method is illustrated by enriching the minimal transcription factor Cro from a low starting frequency (1 in 109). This protocol is also applicable to engineering other DNA-binding proteins or transcription factors from combinatorial libraries.

ACIDES: on-line monitoring of forward genetic screens for protein engineering

Forward genetic screens of mutated variants are a versatile strategy for protein engineering and investigation, which has been successfully applied to various studies like directed evolution (DE) and deep mutational scanning (DMS). While next-generation sequencing can track millions of variants during the screening rounds, the vast and noisy nature of the sequencing data impedes the estimation of the performance of individual variants. Here, we propose ACIDES that combines statistical inference and in-silico simulations to improve performance estimation in the library selection process by attributing accurate statistical scores to individual variants. We tested ACIDES first on a random-peptide-insertion experiment and then on multiple public datasets from DE and DMS studies. ACIDES allows experimentalists to reliably estimate variant performance on the fly and can aid protein engineering and research pipelines in a range of applications, including gene therapy.

A Rapid Antibody Enhancement Platform in Saccharomyces cerevisiae Using an Improved, Diversifying CRISPR Base Editor

The yeast Saccharomyces cerevisiae is commonly used to interrogate and screen protein variants and to perform directed evolution studies to develop proteins with enhanced features. While several techniques have been described that help enable the use of yeast for directed evolution, there remains a need to increase their speed and ease of use. Here we present yDBE, a yeast diversifying base editor that functions in vivo and employs a CRISPR-dCas9-directed cytidine deaminase base editor to diversify DNA in a targeted, rapid, and high-breadth manner. To develop yDBE, we enhanced the mutation rate of an initial base editor by employing improved deaminase variants and characterizing several scaffolded guide constructs. We then demonstrate the ability of the yDBE platform to improve the affinity of a displayed antibody scFv, rapidly generating diversified libraries and isolating improved binders via cell sorting. By performing high-throughput sequencing analysis of the high-activity yDBE, we show that it enables a mutation rate of 2.13 × 10-4 substitutions/bp/generation over a window of 100 bp. As yDBE functions entirely in vivo and can be easily programmed to diversify nearly any such window of DNA, we posit that it can be a powerful tool for facilitating a variety of directed evolution experiments.

Quantification of evolved DNA-editing enzymes at scale with DEQSeq

We introduce DEQSeq, a nanopore sequencing approach that rationalizes the selection of favorable genome editing enzymes from directed molecular evolution experiments. With the ability to capture full-length sequences, editing efficiencies, and specificities from thousands of evolved enzymes simultaneously, DEQSeq streamlines the process of identifying the most valuable variants for further study and application. We apply DEQSeq to evolved libraries of Cas12f-ABEs and designer-recombinases, identifying variants with improved properties for future applications. Our results demonstrate that DEQSeq is a powerful tool for accelerating enzyme discovery and advancing genome editing research.

Structure and Dynamics Guiding Design of Antibody Therapeutics and Vaccines

Antibodies and other new antibody-like formats have emerged as one of the most rapidly growing classes of biotherapeutic proteins. Understanding the structural features that drive antibody function and, consequently, their molecular recognition is critical for engineering antibodies. Here, we present the structural architecture of conventional IgG antibodies alongside other formats. We emphasize the importance of considering antibodies as conformational ensembles in solution instead of focusing on single-static structures because their functions and properties are strongly governed by their dynamic nature. Thus, in this review, we provide an overview of the unique structural and dynamic characteristics of antibodies with respect to their antigen recognition, biophysical properties, and effector functions. We highlight the numerous technical advances in antibody structure prediction and design, enabled by the vast number of experimentally determined high-quality structures recorded with cryo-EM, NMR, and X-ray crystallography. Lastly, we assess antibody and vaccine design strategies in the context of structure and dynamics.

Universal redirection of CAR T cells against solid tumours via membrane-inserted ligands for the CAR

The effectiveness of chimaeric antigen receptor (CAR) T cell therapies for solid tumours is hindered by difficulties in the selection of an effective target antigen, owing to the heterogeneous expression of tumour antigens and to target antigen expression in healthy tissues. Here we show that T cells with a CAR specific for fluorescein isothiocyanate (FITC) can be directed against solid tumours via the intratumoural administration of a FITC-conjugated lipid-poly(ethylene)-glycol amphiphile that inserts itself into cell membranes. In syngeneic and human tumour xenografts in mice, 'amphiphile tagging' of tumour cells drove tumour regression via the proliferation and accumulation of FITC-specific CAR T cells in the tumours. In syngeneic tumours, the therapy induced the infiltration of host T cells, elicited endogenous tumour-specific T cell priming and led to activity against distal untreated tumours and to protection against tumour rechallenge. Membrane-inserting ligands for specific CARs may facilitate the development of adoptive cell therapies that work independently of antigen expression and of tissue of origin.

Protein engineering via sequence-performance mapping

Discovery and evolution of new and improved proteins has empowered molecular therapeutics, diagnostics, and industrial biotechnology. Discovery and evolution both require efficient screens and effective libraries, although they differ in their challenges because of the absence or presence, respectively, of an initial protein variant with the desired function. A host of high-throughput technologies-experimental and computational-enable efficient screens to identify performant protein variants. In partnership, an informed search of sequence space is needed to overcome the immensity, sparsity, and complexity of the sequence-performance landscape. Early in the historical trajectory of protein engineering, these elements aligned with distinct approaches to identify the most performant sequence: selection from large, randomized combinatorial libraries versus rational computational design. Substantial advances have now emerged from the synergy of these perspectives. Rational design of combinatorial libraries aids the experimental search of sequence space, and high-throughput, high-integrity experimental data inform computational design. At the core of the collaborative interface, efficient protein characterization (rather than mere selection of optimal variants) maps sequence-performance landscapes. Such quantitative maps elucidate the complex relationships between protein sequence and performance-e.g., binding, catalytic efficiency, biological activity, and developability-thereby advancing fundamental protein science and facilitating protein discovery and evolution.

Tozorakimab (MEDI3506): an anti-IL-33 antibody that inhibits IL-33 signalling via ST2 and RAGE/EGFR to reduce inflammation and epithelial dysfunction

Interleukin (IL)-33 is a broad-acting alarmin cytokine that can drive inflammatory responses following tissue damage or infection and is a promising target for treatment of inflammatory disease. Here, we describe the identification of tozorakimab (MEDI3506), a potent, human anti-IL-33 monoclonal antibody, which can inhibit reduced IL-33 (IL-33red) and oxidized IL-33 (IL-33ox) activities through distinct serum-stimulated 2 (ST2) and receptor for advanced glycation end products/epidermal growth factor receptor (RAGE/EGFR complex) signalling pathways. We hypothesized that a therapeutic antibody would require an affinity higher than that of ST2 for IL-33, with an association rate greater than 107 M-1 s-1, to effectively neutralize IL-33 following rapid release from damaged tissue. An innovative antibody generation campaign identified tozorakimab, an antibody with a femtomolar affinity for IL-33red and a fast association rate (8.5 × 107 M-1 s-1), which was comparable to soluble ST2. Tozorakimab potently inhibited ST2-dependent inflammatory responses driven by IL-33 in primary human cells and in a murine model of lung epithelial injury. Additionally, tozorakimab prevented the oxidation of IL-33 and its activity via the RAGE/EGFR signalling pathway, thus increasing in vitro epithelial cell migration and repair. Tozorakimab is a novel therapeutic agent with a dual mechanism of action that blocks IL-33red and IL-33ox signalling, offering potential to reduce inflammation and epithelial dysfunction in human disease.

Genotype-phenotype landscapes for immune-pathogen coevolution

Our immune systems constantly coevolve with the pathogens that challenge them, as pathogens adapt to evade our defense responses, with our immune repertoires shifting in turn. These coevolutionary dynamics take place across a vast and high-dimensional landscape of potential pathogen and immune receptor sequence variants. Mapping the relationship between these genotypes and the phenotypes that determine immune-pathogen interactions is crucial for understanding, predicting, and controlling disease. Here, we review recent developments applying high-throughput methods to create large libraries of immune receptor and pathogen protein sequence variants and measure relevant phenotypes. We describe several approaches that probe different regions of the high-dimensional sequence space and comment on how combinations of these methods may offer novel insight into immune-pathogen coevolution.

Imaging the Alternatively Spliced D Domain of Tenascin C in a Preclinical Model of Inflammatory Bowel Disease

PURPOSE

To image colon-expressed alternatively spliced D domain of tenascin C in preclinical colitis models using near infrared (NIR)-labeled targeted molecular imaging agents.

PROCEDURES

A human IgG1 with nanomolar binding affinity specific to the alternatively spliced D domain of tenascin C was generated. Immunohistochemistry identified disease-specific expression of this extracellular matrix protein in the colon of mice given dextran sulfate sodium in the drinking water. The antibody reagent was labeled with the NIR fluorophore IRDye 800CW via amine chemistry and intravenously dosed to evaluate in vivo targeting specificity. Increasing doses of imaging agent were given to estimate the saturating dose.

RESULTS

The NIR-labeled proteins successfully targeted colonic lesions in a murine model of colitis. Co-administration of a molar excess competing unlabeled dose reduced normalized uptake in diseased colon by > 70%. Near infrared ex vivo images of colon resected from diseased animals showed saturation at doses exceeding 1 nmol and was confirmed with additional quantitative ex vivo biodistribution. Cellular-level specificity and protein stability were assessed via microscopy.

CONCLUSIONS

Our imaging data suggest the alternatively spliced D domain of tenascin C is a promising target for delivery-based applications in inflammatory bowel diseases.

Immune cells use active tugging forces to distinguish affinity and accelerate evolution

Cells are known to exert forces to sense their physical surroundings for guidance of motion and fate decisions. Here, we propose that cells might do mechanical work to drive their own evolution, taking inspiration from the adaptive immune system. Growing evidence indicates that immune B cells-capable of rapid Darwinian evolution-use cytoskeletal forces to actively extract antigens from other cells' surfaces. To elucidate the evolutionary significance of force usage, we develop a theory of tug-of-war antigen extraction that maps receptor binding characteristics to clonal reproductive fitness, revealing physical determinants of selection strength. This framework unifies mechanosensing and affinity-discrimination capabilities of evolving cells: Pulling against stiff antigen tethers enhances discrimination stringency at the expense of absolute extraction. As a consequence, active force usage can accelerate adaptation but may also cause extinction of cell populations, resulting in an optimal range of pulling strength that matches molecular rupture forces observed in cells. Our work suggests that nonequilibrium, physical extraction of environmental signals can make biological systems more evolvable at a moderate energy cost.

Development of a human antibody fragment cross-neutralizing scorpion toxins

Previously, it was demonstrated that from the single chain fragment variable (scFv) 3F it is possible to generate variants capable of neutralizing the Cn2 and Css2 toxins, as well as their respective venoms (Centruroides noxius and Centruroides suffusus). Despite this success, it has not been easy to modify the recognition of this family of scFvs toward other dangerous scorpion toxins. The analysis of toxin-scFv interactions and in vitro maturation strategies allowed us to propose a new maturation pathway for scFv 3F to broaden recognition toward other Mexican scorpion toxins. From maturation processes against toxins CeII9 from C. elegans and Ct1a from C. tecomanus, the scFv RAS27 was developed. This scFv showed an increased affinity and cross-reactivity for at least 9 different toxins while maintaining recognition for its original target, the Cn2 toxin. In addition, it was confirmed that it can neutralize at least three different toxins. These results constitute an important advance since it was possible to improve the cross-reactivity and neutralizing capacity of the scFv 3F family of antibodies.

Titrating Avidity of Yeast-Displayed Proteins Using a Transcriptional Regulator

Yeast surface display is a valuable tool for protein engineering and directed evolution; however, significant variability in the copy number (i.e., avidity) of displayed variants on the yeast cell wall complicates screening and selection campaigns. Here, we report an engineered titratable display platform that modulates the avidity of Aga2-fusion proteins on the yeast cell wall dependent on the concentration of the anhydrotetracycline (aTc) inducer. Our design is based on a genomic Aga1 gene copy and an episomal Aga2-fusion construct both under the control of an aTc-dependent transcriptional regulator that enables stoichiometric and titratable expression, secretion, and display of Aga2-fusion proteins. We demonstrate tunable display levels over 2-3 orders of magnitude for various model proteins, including glucose oxidase enzyme variants, mechanostable dockerin-binding domains, and anti-PDL1 affibody domains. By regulating the copy number of displayed proteins, we demonstrate the effects of titratable avidity levels on several specific phenotypic activities, including enzyme activity and cell adhesion to surfaces under shear flow. Finally, we show that titrating down the display level allows yeast-based binding affinity measurements to be performed in a regime that avoids ligand depletion effects while maintaining small sample volumes, avoiding a well-known artifact in yeast-based binding assays. The ability to titrate the multivalency of proteins on the yeast cell wall through simple inducer control will benefit protein engineering and directed evolution methodology relying on yeast display for broad classes of therapeutic and diagnostic proteins of interest.

High-throughput saturation mutagenesis generates a high-affinity antibody against SARS-CoV-2 variants using protein surface display assay on a human cell

As new mutations continue to emerge, the ability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus to evade the human immune system and neutralizing antibodies remains a huge challenge for vaccine development and antibody research. The majority of neutralizing antibodies have reduced or lost activity against SARS-CoV-2 variants. In this study, we reported a novel protein surface display system on a mammalian cell for obtaining a higher-affinity antibody in high-throughput manner. Using a saturation mutagenesis strategy through integrating microarray-based oligonucleotide synthesis and single-cell screening assay, we generated a group of new antibodies against diverse prevalent SARS-CoV-2 variants through high-throughput screening the human antibody REGN10987 within 2 weeks. The affinity of those optimized antibodies to seven prevalent mutants was greatly improved, and the EC50 values were no higher than 5 ng/mL. These results demonstrate the robustness of our screening system in the rapid generation of an antibody with higher affinity against a new SARS-CoV-2 variant, and provides a potential application to other protein molecular interactions.

Facile One-Step Generation of Camelid VHH and Avian scFv Libraries for Phage Display by Golden Gate Cloning

Since its development in the 1980s, the Nobel Prize-awarded phage display technology has been one of the most commonly used in vitro selection technologies for the discovery of therapeutic and diagnostic antibodies. Besides the importance of selection strategy, one key component of the successful isolation of highly specific recombinant antibodies is the construction of high-quality phage display libraries. However, previous cloning protocols relied on a tedious multistep process with subsequent cloning steps for the introduction of first heavy and then light chain variable genetic antibody fragments (VH and VL). This resulted in reduced cloning efficiency, higher frequency of missing VH or VL sequences, as well as truncated antibody fragments. With the emergence of Golden Gate Cloning (GGC) for the generation of antibody libraries, the possibility of more facile library cloning has arisen. Here, we describe a streamlined one-step GGC strategy for the generation of camelid heavy chain only variable phage display libraries as well as the simultaneous introduction of heavy chain and light chain variable regions from the chicken into a scFv phage display vector.

Structural, functional, and physiological properties of anti-(4-hydroxy-3-nitrophenyl)acetyl antibodies during the course of affinity maturation

Structural and functional analyses of antibodies in the affinity maturation pathway can help us understand the molecular mechanisms of protein recognition. Using one of the haptens, (4-hydroxy-3-nitrophenyl)acetyl (NP), various monoclonal antibodies have been obtained, either at the early or late stage of immunization. The variable regions of monoclonal antibodies and their site-directed mutants can also be obtained as single-chain Fv (scFv) antibodies. The change in antigen-binding affinity and avidity of matured-type antibodies from germline-type antibodies could be evaluated based on binding kinetics and thermodynamics, proposing the antigen recognition mode. Crystal structures of a germline-type antibody, N1G9, and a matured-type antibody, C6, in complex with NP were determined, revealing different antigen-binding mode at atomic resolution. Notably, the Tyr to Gly mutation at the 95th residue of the heavy chain is critical for changing the configuration of complementarity determining region 3, which is involved in antigen binding. Furthermore, thermal stability analyses of scFv antibodies have revealed trade-off between antigen-binding affinity and thermal stability in the antigen-unbound state. To increase affinity, the stability of the variable region may be decreased, possibly due to protein architecture. The high stability of germline-type antibodies and the low stability of matured-type antibodies, which increase upon antigen binding, can be explained by the stability of antibodies required at the respective stages of immunization.

Single-Chain Fragment Variable: Recent Progress in Cancer Diagnosis and Therapy

Simple Summary

Recombinant antibody fragments have shown remarkable potential as diagnostic and therapeutic tools in the fight against cancer. The single-chain fragment variable (scFv) that contains the complete antigen-binding domains of a whole antibody, has several advantages such as a high specificity and affinity for antigens, a low immunogenicity, and the proven ability to penetrate tumor tissues and diffuse. This review provides an overview of the current studies on the principle, generation, and applications of scFvs, particularly in the diagnosis and therapy of cancer, and underscores their potential use in clinical trials.

Abstract

Cancer remains a public health problem worldwide. Although conventional therapies have led to some excellent outcomes, some patients fail to respond to treatment, they have few therapeutic alternatives and a poor survival prognosis. Several strategies have been proposed to overcome this issue. The most recent approach is immunotherapy, particularly the use of recombinant antibodies and their derivatives, such as the single-chain fragment variable (scFv) containing the complete antigen-binding domains of a whole antibody that successfully targets tumor cells. This review describes the recent progress made with scFvs as a cancer diagnostic and therapeutic tool, with an emphasis on preclinical approaches and their potential use in clinical trials.

Enhancing bioreactor arrays for automated measurements and reactive control with ReacSight

Small-scale, low-cost bioreactors provide exquisite control of environmental parameters of microbial cultures over long durations. Their use is gaining popularity in quantitative systems and synthetic biology. However, existing setups are limited in their measurement capabilities. Here, we present ReacSight, a strategy to enhance bioreactor arrays for automated measurements and reactive experiment control. ReacSight leverages low-cost pipetting robots for sample collection, handling and loading, and provides a flexible instrument control architecture. We showcase ReacSight capabilities on three applications in yeast. First, we demonstrate real-time optogenetic control of gene expression. Second, we explore the impact of nutrient scarcity on fitness and cellular stress using competition assays. Third, we perform dynamic control of the composition of a two-strain consortium. We combine custom or chi.bio reactors with automated cytometry. To further illustrate ReacSight's genericity, we use it to enhance plate-readers with pipetting capabilities and perform repeated antibiotic treatments on a bacterial clinical isolate.

Ig-VAE: Generative modeling of protein structure by direct 3D coordinate generation

While deep learning models have seen increasing applications in protein science, few have been implemented for protein backbone generation—an important task in structure-based problems such as active site and interface design. We present a new approach to building class-specific backbones, using a variational auto-encoder to directly generate the 3D coordinates of immunoglobulins. Our model is torsion- and distance-aware, learns a high-resolution embedding of the dataset, and generates novel, high-quality structures compatible with existing design tools. We show that the Ig-VAE can be used with Rosetta to create a computational model of a SARS-CoV2-RBD binder via latent space sampling. We further demonstrate that the model’s generative prior is a powerful tool for guiding computational protein design, motivating a new paradigm under which backbone design is solved as constrained optimization problem in the latent space of a generative model.

Many essential biochemical processes are governed by protein-protein interactions (PPIs), and our ability to make binding proteins that modulate PPIs is crucial to the creation of therapeutics and the study of cell-signaling. One critical aspect of PPI design is to capture protein conformational flexibility. Deep generative models are a class of mathematical models that are able to synthesize novel data from a finite set of training examples. Here, we make advances in computational protein design methodology by developing a deep generative model that creates protein backbones adopting the immunoglobulin fold, which is found in natural binding proteins such as antibodies. While generative models have been powerful in tasks such as image generation, using them to create proteins has remained a challenge. We solve this problem with a new model that allows for the direct generation of novel 3D molecules and show that they are of high chemical accuracy. Generated structures work well with existing protein design methods such as Rosetta, providing access to a large collection of novel immunoglobulin structures. Finally, we present a new protein design framework, called “generative design,” that shows how deep generative models such as ours can be applied to virtually any protein design problem.

Arming Immune Cell Therapeutics with Polymeric Prodrugs

Engineered immune cells are an exciting therapeutic modality, which survey and attack tumors. Backpacking strategies exploit cell targeting capabilities for delivery of drugs to combat tumors and their immune-suppressive environments. Here, a new platform for arming cell therapeutics through dual receptor and polymeric prodrug engineering is developed. Macrophage and T cell therapeutics are engineered to express a bioorthogonal single chain variable fragment receptor. The receptor binds a fluorescein ligand that directs cell loading with ligand-tagged polymeric prodrugs, termed "drugamers." The fluorescein ligand facilitates stable binding of drugamer to engineered macrophages over 10 days with 80% surface retention. Drugamers also incorporate prodrug monomers of the phosphoinositide-3-kinase inhibitor, PI-103. The extended release of PI-103 from the drugamer sustains antiproliferative activity against a glioblastoma cell line compared to the parent drug. The versatility and modularity of this cell arming system is demonstrated by loading T cells with a second fluorescein-drugamer. This drugamer incorporates a small molecule estrogen analog, CMP8, which stabilizes a degron-tagged transgene to provide temporal regulation of protein activity in engineered T cells. These results demonstrate that this bioorthogonal receptor and drugamer system can be used to arm multiple immune cell classes with both antitumor and transgene-activating small molecule prodrugs.

What Digital Immunoassays Can Learn from Ambient Analyte Theory: A Perspective

Immunoassays are important tools for clinical diagnosis as well as environmental and food analysis because they enable highly sensitive and quantitative measurements of analyte concentrations. In the 1980s, Roger Ekins suggested to improve the sensitivity of immunoassays by employing microspot assays, which are carried out under ambient analyte conditions and do not change the bulk analyte concentration of a sample during a measurement. More recently, the measurement of single analyte molecules has additionally attracted wide research interest. Although the ability to detect a single analyte molecule is not synonymous with the highest analytical sensitivity, single-molecule detection makes new routes accessible to avoiding background noise. This perspective follows the development of solid-phase immunoassays from the design of label techniques to single-molecule (digital) assays against the backdrop of Ekins's fundamental work on immunoassay theory. The essential aspects of both ambient analyte and digital assay approaches are presented as a guideline to finding a balance between the speed, sensitivity, and precision of immunoassays.

Human Antibodies for Viral Infections

Antibodies have been used to prevent or treat viral infections since the nineteenth century, but the full potential to use passive immunization for infectious diseases has yet to be realized. The advent of efficient methods for isolating broad and potently neutralizing human monoclonal antibodies is enabling us to develop antibodies with unprecedented activities. The discovery of IgG Fc region modifications that extend antibody half-life in humans to three months or more suggests that antibodies could become the principal tool with which we manage future viral epidemics. Antibodies for members of most virus families that cause severe disease in humans have been isolated, and many of them are in clinical development, an area that has accelerated during the effort to prevent or treat COVID-19 (coronavirus disease 2019). Broad and potently neutralizing antibodies are also important research reagents for identification of protective epitopes that can be engineered into active vaccines through structure-based reverse vaccinology. Expected final online publication date for the Annual Review of Immunology, Volume 40 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

An affinity threshold for maximum efficacy in anti-PD-1 immunotherapy

Monoclonal antibodies targeting the programmed cell death protein 1 (PD-1) remain the most prevalent cancer immunotherapy both as a monotherapy and in combination with additional therapies. Despite the extensive success of anti-PD-1 monoclonal antibodies in the clinic, the experimental relationship between binding affinity and functional potency for anti-PD-1 antibodies in vivo has not been reported. Anti-PD-1 antibodies with higher and lower affinity than nivolumab or pembrolizumab are entering the clinic and show varied preclinical efficacy. Here, we explore the role of broad-ranging affinity variation within a single lineage in a syngeneic immunocompetent mouse model. By developing a panel of murine anti-PD-1 antibodies with varying affinity (ranging from K_D = 20 pM – 15 nM), we find that there is a threshold affinity required for maximum efficacy at a given dose in the treatment of the MC38 adenocarcinoma model with anti-PD-1 immunotherapy. Physiologically based pharmacokinetic modeling complements interpretation of the experimental results and highlights the direct relationship between dose, affinity, and PD-1 target saturation in the tumor.

Kinetic Competition Screening of Yeast-Displayed Libraries for Isolating High Affinity Binders

Yeast surface display is a robust platform for obtaining binders with high affinity. Kinetic competition screening is an effective method for maturing the affinity of binders with strong starting affinities, or when dissociation kinetics are a key consideration for the protein of interest. In this chapter, we describe detailed protocols for setting up and performing a kinetic competition screen. The duration of competition is determined based on the dissociation rate constant of the parental clone measured on the yeast surface. This methodology was successfully used to improve the affinity of a viral double-stranded RNA binding protein with starting affinity in the sub-nanomolar range.

Identification of Brain ECM Binding Variable Lymphocyte Receptors Using Yeast Surface Display

Extracellular matrix (ECM) is a rich mixture of proteins and glycans secreted by cells. This includes typical ECM structures such as collagen and heparin as well as glycosylated, secreted proteins such as growth factors and peptidases. Certain components of ECM are ubiquitous among all tissue; however, each biological tissue also displays unique variations that can be identified using biopanning techniques. Here we describe using a variable lymphocyte receptor (VLR) yeast surface display library to identify selective binders to brain ECM by combining ECM biopanning with a rapid ELISA-based screen using clonal VLRs isolated directly from the yeast surface. Finally, potential ECM-binding candidates can be verified by immunostaining murine brain sections with VLRs released from the yeast surface. These methods provide a framework for the identification of tissue-selective ECM-binding VLRs using yeast surface display techniques and could easily be adapted for other binding scaffolds or ECM from other tissues.

Yeast Surface Display: New Opportunities for a Time-Tested Protein Engineering System

Yeast surface display has proven to be a powerful tool for the discovery of antibodies and other novel binding proteins and for engineering the affinity and selectivity of existing proteins for their targets. In the decades since the first demonstrations of the approach, the range of yeast display applications has greatly expanded to include many different protein targets and has grown to encompass methods for rapid protein characterization. Here, we briefly summarize the development of yeast display methodologies and highlight several selected examples of recent applications to timely and challenging protein engineering and characterization problems.

Recent Advances Toward Engineering Glycoproteins Using Modified Yeast Display Platforms

Yeast are capable recombinant protein expression hosts that provide eukaryotic posttranslational modifications such as disulfide bond formation and N-glycosylation. This property has been used to create surface display libraries for protein engineering; however, yeast surface display (YSD) with common laboratory strains has limitations in terms of diversifying glycoproteins due to the incorporation of high levels of mannose residues which often obscure important epitopes and are immunogenic in humans. Developing new strains for efficient and appropriate display will require combining existing technologies to permit efficient glycoprotein engineering. Foundational efforts generating knockout strains lacking characteristic hypermannosylation reactions exhibited morphological defects and poor growth. Later strains with "humanized" N-glycosylation machinery surmounted these limitations by targeting a small suite of glycosylhydrolase and glycosyltransferase enzymes from other taxa to the endoplasmic reticulum and Golgi. Advanced yeast strains also provide key modifications at the glycan termini that are essential for the full function of many glycoproteins. Here we review progress toward glycoprotein engineering when glycosylation is required for full function using advanced yeast expression platforms and the suitability of each for YSD of glycoproteins.

Affinity and Stability Analysis of Yeast Displayed Proteins

Yeast surface display is a powerful protein engineering technology that is extensively used to improve various properties of proteins, including affinity, specificity, and stability or even to add novel functions (usually ligand binding). Apart from its robustness and versatility as an engineering tool, yeast display offers a further critical advantage: Once the selection campaign is finished, usually resulting in an oligoclonal pool, these enriched protein variants can be analyzed individually on the surface of yeast without the need for any sub-cloning, soluble expression, and purification. Here, we provide detailed protocols for determining both the affinity and the thermal stability of yeast displayed proteins. In addition, we discuss the advantages, challenges, and potential pitfalls associated with affinity and stability analysis using yeast surface display.

Yeast Display Guided Selection of pH-Dependent Binders

pH-dependent antigen binding has proven useful in engineering next-generation therapeutics specifically via antibody recycling technology. This technology allows for half-life extension, thereby lowering the amount and frequency of dosing of therapeutics. Cell sorting, coupled with display techniques, has been used extensively for the selection of high-affinity binders. Herein, we describe a cell sorting methodology utilizing yeast surface display for selection of binding proteins with strong binding at physiological pH and weak to no binding at acidic pH. This methodology can be readily applied to engineer proteins and/or antibodies that do not have pH-dependent binding or for selection of de novo pH-dependent binders using library-based methods.

Simultaneous affinity maturation and developability enhancement using natural liability-free CDRs

Affinity maturation is often a necessary step for the development of potent therapeutic molecules. Many different diversification strategies have been used for antibody affinity maturation, including error-prone PCR, chain shuffling, and targeted complementary-determining region (CDR) mutation. Although effective, they can negatively impact antibody stability or alter epitope recognition. Moreover, they do not address the presence of sequence liabilities, such as glycosylation, asparagine deamidation, aspartate isomerization, aggregation motifs, and others. Such liabilities, if present or inadvertently introduced, can potentially create the need for new rounds of engineering, or even abolish the value of the antibody as a therapeutic molecule. Here, we demonstrate a sequence agnostic method to improve antibody affinities, while simultaneously eliminating sequence liabilities and retaining the same epitope binding as the parental antibody. This was carried out using a defined collection of natural CDRs as the diversity source, purged of sequence liabilities, and matched to the antibody germline gene family. These CDRs were inserted into the lead molecule in one or two sites at a time (LCDR1-2, LCDR3, HCDR1-2) while retaining the HCDR3 and framework regions unchanged. The final analysis of 92 clones revealed 81 unique variants, with each of 24 tested variants having the same epitope specificity as the parental molecule. Of these, the average affinity improved by over 100 times (to 96 pM), and the best affinity improvement was 231-fold (to 32 pM).

Lateral Flow Assays in Infectious Disease Diagnosis

Background

Lateral flow immunoassays are widely used as diagnostic tests in many applications in human and other diagnostic areas. Assays for human applications have been commercially available since the 1980s and initially were primarily used to identify pregnancy by measuring human chorionic gonadotropin in urine and serum/plasma.

Content

The first infectious disease lateral flow assays were commercialized in the late 1980s identifying the presence of Group A Streptococcus pyogenes collected with throat swabs; innumerable other applications followed in the intervening decades. The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) pandemic has brought a vast number of new assays for which emergency use authorization (EUA) has been requested in the USA. These assays have been designed for detection of the antibody response to an infection and viral antigens in respiratory samples. In view of the onslaught of new tests, this review will focus on the use of rapid lateral flow immunoassays for infectious diseases. Principles of lateral flow assays and approaches to the production of high-sensitivity point-of-care assays are presented. Market trends, customer requirements, and future directions of lateral flow assay technology and its applications in the infectious disease diagnostic space are discussed.

Summary

Lateral flow immunoassays play an important role in infectious disease diagnostics. Advancements in technology have led to improved performance of these assays and acceptance by professional users. With the advent of the SARS-CoV-2 pandemic, the market has reached new levels requiring hundreds of millions of tests per year for professional and even home use.

Development of a potent high-affinity human therapeutic antibody via novel application of recombination signal sequence-based affinity maturation

Therapeutic antibody development requires discovery of an antibody molecule with desired specificities and drug-like properties. For toxicological studies, a therapeutic antibody must bind the ortholog antigen with a similar affinity to the human target to enable relevant dosing regimens, and antibodies falling short of this affinity design goal may not progress as therapeutic leads. Herein, we report the novel use of mammalian recombination signal sequence (RSS)–directed recombination for complementarity-determining region–targeted protein engineering combined with mammalian display to close the species affinity gap of human interleukin (IL)-13 antibody 731. This fully human antibody has not progressed as a therapeutic in part because of a 400-fold species affinity gap. Using this nonhypothesis-driven affinity maturation method, we generated multiple antibody variants with improved IL-13 affinity, including the highest affinity antibody reported to date (34 fM). Resolution of a cocrystal structure of the optimized antibody with the cynomolgus monkey (or nonhuman primate) IL-13 protein revealed that the RSS-derived mutations introduced multiple successive amino-acid substitutions resulting in a de novo formation of a π–π stacking–based protein–protein interaction between the affinity-matured antibody heavy chain and helix C on IL-13, as well as an introduction of an interface-distant residue, which enhanced the light chain–binding affinity to target. These mutations synergized binding of heavy and light chains to the target protein, resulting in a remarkably tight interaction, and providing a proof of concept for a new method of protein engineering, based on synergizing a mammalian display platform with novel RSS-mediated library generation.

Reconstruction of evolving gene variants and fitness from short sequencing reads

Directed evolution can generate proteins with tailor-made activities. However, full-length genotypes, their frequencies and fitnesses are difficult to measure for evolving gene-length biomolecules using most high-throughput DNA sequencing methods, as short read lengths can lose mutation linkages in haplotypes. Here we present Evoracle, a machine learning method that accurately reconstructs full-length genotypes (R² = 0.94) and fitness using short-read data from directed evolution experiments, with substantial improvements over related methods. We validate Evoracle on phage-assisted continuous evolution (PACE) and phage-assisted non-continuous evolution (PANCE) of adenine base editors and OrthoRep evolution of drug-resistant enzymes. Evoracle retains strong performance (R² = 0.86) on data with complete linkage loss between neighboring nucleotides and large measurement noise, such as pooled Sanger sequencing data (~US$10 per timepoint), and broadens the accessibility of training machine learning models on gene variant fitnesses. Evoracle can also identify high-fitness variants, including low-frequency 'rising stars', well before they are identifiable from consensus mutations.

Computational maturation of a single-domain antibody against Aβ42 aggregation

The expansion of structural databases and the increase in computing power are enabling approaches for antibody discovery based on computational design. It has already been shown that it is possible to use this approach to generate antibodies for specific epitopes on challenging targets. Here we describe an application of this procedure for antibody maturation through the computational design of mutational variants of increased potency. We illustrate this procedure in the case of a single-domain antibody targeting an epitope in the N-terminal region of Aβ42, a peptide whose aggregation is closely associated with Alzheimer's disease. We show that this approach enables the generation of an antibody variant with over 200-fold increased potency against the primary nucleation process in Aβ42 aggregation. Our results thus demonstrate that potentiated antibody variants can be obtained by computational maturation.

A computational maturation method enables the generation of an antibody variant with over 200-fold increased potency against the primary nucleation process in Aβ42 aggregation.

Directing evolution of novel ligands by mRNA display

mRNA display is a powerful biological display platform for the directed evolution of proteins and peptides. mRNA display libraries covalently link the displayed peptide or protein (phenotype) with the encoding genetic information (genotype) through the biochemical activity of the small molecule puromycin. Selection for peptide/protein function is followed by amplification of the linked genetic material and generation of a library enriched in functional sequences. Iterative selection cycles are then performed until the desired level of function is achieved, at which time the identity of candidate peptides can be obtained by sequencing the genetic material. The purpose of this review is to discuss the development of mRNA display technology since its inception in 1997 and to comprehensively review its use in the selection of novel peptides and proteins. We begin with an overview of the biochemical mechanism of mRNA display and its variants with a particular focus on its advantages and disadvantages relative to other biological display technologies. We then discuss the importance of scaffold choice in mRNA display selections and review the results of selection experiments with biological (e.g., fibronectin) and linear peptide library architectures. We then explore recent progress in the development of "drug-like" peptides by mRNA display through the post-translational covalent macrocyclization and incorporation of non-proteogenic functionalities. We conclude with an examination of enabling technologies that increase the speed of selection experiments, enhance the information obtained in post-selection sequence analysis, and facilitate high-throughput characterization of lead compounds. We hope to provide the reader with a comprehensive view of current state and future trajectory of mRNA display and its broad utility as a peptide and protein design tool.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Intranasal gene therapy to prevent infection by SARS-CoV-2 variants

SARS-CoV-2 variants have emerged with enhanced pathogenicity and transmissibility, and escape from pre-existing immunity, suggesting first-generation vaccines and monoclonal antibodies may now be less effective. Here we present an approach for preventing clinical sequelae and the spread of SARS-CoV-2 variants. First, we affinity matured an angiotensin-converting enzyme 2 (ACE2) decoy protein, achieving 1000-fold binding improvements that extend across a wide range of SARS-CoV-2 variants and distantly related, ACE2-dependent coronaviruses. Next, we demonstrated the expression of this decoy in proximal airway when delivered via intranasal administration of an AAV vector. This intervention significantly diminished clinical and pathologic consequences of SARS-CoV-2 challenge in a mouse model and achieved therapeutic levels of decoy expression at the surface of proximal airways when delivered intranasally to nonhuman primates. Importantly, this long-lasting, passive protection approach is applicable in vulnerable populations such as the elderly and immune-compromised that do not respond well to traditional vaccination. This approach could be useful in combating COVID-19 surges caused by SARS-CoV-2 variants and should be considered as a countermeasure to future pandemics caused by one of the many pre-emergent, ACE2-dependent CoVs that are poised for zoonosis.

Affinity maturation of antibodies by combinatorial codon mutagenesis versus error-prone PCR

IN VITRO

affinity maturation of therapeutic monoclonal antibodies is commonly applied to achieve desired properties, such as improved binding kinetics and affinity. Currently there are no universally accepted protocols for generation of variegated antibody libraries or selection thereof. Here, we performed affinity maturation using a yeast-based single-chain variable fragment (scFv) expression system to compare two mutagenesis methods: random mutagenesis across the entire V(D)J region by error-prone PCR, and a novel combinatorial mutagenesis process limited to the complementarity-determining regions (CDRs). We applied both methods of mutagenesis to four human antibodies against well-known immuno-oncology target proteins. Detailed sequence analysis showed an even mutational distribution across the entire length of the scFv for the error-prone PCR method and an almost exclusive targeting of the CDRs for the combinatorial method. Though there were distinct mutagenesis profiles for each target antibody and mutagenesis method, we found that both methods improved scFv affinity with similar efficiency. When a subset of the affinity-matured antibodies was expressed as full-length immunoglobulin, the measured affinity constants were mostly comparable to those of the respective scFv, but the full-length antibodies were inferior to their scFv counterparts for one of the targets. Furthermore, we found that improved affinity for the full-length antibody did not always translate into enhanced binding to cell-surface expressed antigen or improved immune checkpoint blocking ability, suggesting that screening with full-length antibody or antigen-binding fragment formats might be advantageous and the subject of a future study.

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

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.

Towards an engineering theory of evolution

Biological technologies are fundamentally unlike any other because biology evolves. Bioengineering therefore requires novel design methodologies with evolution at their core. Knowledge about evolution is currently applied to the design of biosystems ad hoc. Unless we have an engineering theory of evolution, we will neither be able to meet evolution's potential as an engineering tool, nor understand or limit its unintended consequences for our biological designs. Here, we propose the evotype as a helpful concept for engineering the evolutionary potential of biosystems, or other self-adaptive technologies, potentially beyond the realm of biology.

Challenges for design of aggregation-resistant variants of granulocyte colony-stimulating factor

Non-native protein aggregation is a long-standing issue in pharmaceutical biotechnology. A rational design approach was used in order to identify variants of recombinant human granulocyte colony-stimulating factor (rhG-CSF) with lower aggregation propensity at solution conditions that are typical of commercial formulation. The approach used aggregation-prone-region (APR) predictors to select single amino acid substitutions that were predicted to decrease intrinsic aggregation propensity (IAP). The results of static light scattering temperature-ramps and chemical unfolding experiments demonstrated that none of the selected variants exhibited improved aggregation resistance, and the apparent conformational stability of each variant was lower than that of WT. Aggregation studies under partly denaturing conditions suggested that the IAP of at least one variant remained unaltered. Overall, this study highlights a general challenge in designing aggregation resistance for proteins, due to the need to accurately predict both APRs and conformational stability.