Reducing mutational bias in random protein libraries

Deep mutational scanning and CRISPR-engineered viruses: tools for evolutionary and functional genomics studies

Recent advancements in synthetic biology and sequencing technologies have revolutionized the ability to manipulate viral genomes with unparalleled precision. This review focuses on two powerful methodologies: deep mutational scanning and CRISPR-based genome editing, that enable comprehensive mutagenesis and detailed functional characterization of viral proteins. These approaches have significantly deepened our understanding of the molecular determinants driving viral evolution and adaptation. Furthermore, we discuss how these advances provide transformative insights for future vaccine development and therapeutic strategies.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here we establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Accelerating enzyme discovery and engineering with high-throughput screening

Covering: up to August 2024Enzymes play an essential role in synthesizing value-added chemicals with high specificity and selectivity. Since enzymes utilize substrates derived from renewable resources, biocatalysis offers a pathway to an efficient bioeconomy with reduced environmental footprint. However, enzymes have evolved over millions of years to meet the needs of their host organisms, which often do not align with industrial requirements. As a result, enzymes frequently need to be tailored for specific industrial applications. Combining enzyme engineering with high-throughput screening has emerged as a key approach for developing novel biocatalysts, but several challenges are yet to be addressed. In this review, we explore emergent strategies and methods for isolating, creating, and characterizing enzymes optimized for bioproduction. We discuss fundamental approaches to discovering and generating enzyme variants and identifying those best suited for specific applications. Additionally, we cover techniques for creating libraries using automated systems and highlight innovative high-throughput screening methods that have been successfully employed to develop novel biocatalysts for natural product synthesis.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Preclinical Anticipation of On- and Off-Target Resistance Mechanisms to Anti-Cancer Drugs: A Systematic Review

The advent of targeted therapies has led to tremendous improvements in treatment options and their outcomes in the field of oncology. Yet, many cancers outsmart precision drugs by developing on-target or off-target resistance mechanisms. Gaining the ability to resist treatment is the rule rather than the exception in tumors, and it remains a major healthcare challenge to achieve long-lasting remission in most cancer patients. Here, we discuss emerging strategies that take advantage of innovative high-throughput screening technologies to anticipate on- and off-target resistance mechanisms before they occur in treated cancer patients. We divide the methods into non-systematic approaches, such as random mutagenesis or long-term drug treatment, and systematic approaches, relying on the clustered regularly interspaced short palindromic repeats (CRISPR) system, saturated mutagenesis, or computational methods. All these new developments, especially genome-wide CRISPR-based screening platforms, have significantly accelerated the processes for identification of the mechanisms responsible for cancer drug resistance and opened up new avenues for future treatments.

Deep mutational scanning: A versatile tool in systematically mapping genotypes to phenotypes

Unveiling how genetic variations lead to phenotypic variations is one of the key questions in evolutionary biology, genetics, and biomedical research. Deep mutational scanning (DMS) technology has allowed the mapping of tens of thousands of genetic variations to phenotypic variations efficiently and economically. Since its first systematic introduction about a decade ago, we have witnessed the use of deep mutational scanning in many research areas leading to scientific breakthroughs. Also, the methods in each step of deep mutational scanning have become much more versatile thanks to the oligo-synthesizing technology, high-throughput phenotyping methods and deep sequencing technology. However, each specific possible step of deep mutational scanning has its pros and cons, and some limitations still await further technological development. Here, we discuss recent scientific accomplishments achieved through the deep mutational scanning and describe widely used methods in each step of deep mutational scanning. We also compare these different methods and analyze their advantages and disadvantages, providing insight into how to design a deep mutational scanning study that best suits the aims of the readers' projects.

Construction and application of an efficient dual-base editing platform for Bacillus subtilis evolution employing programmable base conversion

The functionally evolved bacterial chassis is of great importance to manufacture a group of assorted high value-added chemicals, from small molecules to biologically active macromolecules. However, the current evolution frameworks are less efficienct in generating in vivo genomic diversification because of insufficient tunability, rendering limited evolution spacing for chassis. Here, an engineered genomic diversification platform (CRISPR-ABE8e-CDA-nCas9) leveraging a programmable dual-deaminases base editor was fabricated for rapidly evolving bacterial chassis. The dual-base editor was constructed by reprogramming the CRISPR array, nCas9, and cytidine and adenosine deaminase, enabling single or multiple base conversion at the genomic scale by simultaneous C-to-T and A-to-G conversion in vivo. Employing titration of the Cas-deaminase fusion protein, the platform enabled editing any pre-defined genomic loci with tunable conversion efficiency and editable window, generating a repertoire of mutants with highly diversified genomic sequences. Leveraging the genomic diversification platform, we successfully evolved the nisin-resistant capability of Bacillus subtilis through directed evolution of the subunit of lantibiotic ATP-binding cassette. Therefore, our work provides a portable and programmable genomic diversification platform, which is promising to expedite the fabrication of high-performance and robust bacterial chassis used in the development of biomanufacturing and biopharmaceuticals.

Optimized Loopable Translation as a Platform for the Synthesis of Repetitive Proteins

The expression of long proteins with repetitive amino acid sequences often presents a challenge in recombinant systems. To overcome this obstacle, we report a genetic construct that circularizes mRNA in vivo by rearranging the topology of a group I self-splicing intron from T4 bacteriophage, thereby enabling "loopable" translation. Using a fluorescence-based assay to probe the translational efficiency of circularized mRNAs, we identify several conditions that optimize protein expression from this system. Our data suggested that translation of circularized mRNAs could be limited primarily by the rate of ribosomal initiation; therefore, using a modified error-prone PCR method, we generated a library that concentrated mutations into the initiation region of circularized mRNA and discovered mutants that generated markedly higher expression levels. Combining our rational improvements with those discovered through directed evolution, we report a loopable translator that achieves protein expression levels within 1.5-fold of the levels of standard vectorial translation. In summary, our work demonstrates loopable translation as a promising platform for the creation of large peptide chains, with potential utility in the development of novel protein materials.

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.

An error prone PCR method for small amplicons

Error-prone PCR (epPCR) is a commonly employed approach in molecular biology, especially in directed evolution, to generate libraries of DNA molecules with broad mutational spectrums. Though commonly applied to mutagenize protein coding sequences of several hundreds or thousands of basepairs, we found that commonly used protocols were not suitable for small (<100 bp) amplicons. Here we report a modified error-prone PCR protocol utilizing a Touchdown approach and employing only commercially available components, that should be broadly useful for the researcher interested in concentrating mutations into a small region of plasmid DNA. It will also be useful for achieving very high mutational loads on a standard-sized amplicon.

Applications of Deep Mutational Scanning in Virology

Several recently developed high-throughput techniques have changed the field of molecular virology. For example, proteomics studies reveal complete interactomes of a viral protein, genome-wide CRISPR knockout and activation screens probe the importance of every single human gene in aiding or fighting a virus, and ChIP-seq experiments reveal genome-wide epigenetic changes in response to infection. Deep mutational scanning is a relatively novel form of protein science which allows the in-depth functional analysis of every nucleotide within a viral gene or genome, revealing regions of importance, flexibility, and mutational potential. In this review, we discuss the application of this technique to RNA viruses including members of the Flaviviridae family, Influenza A Virus and Severe Acute Respiratory Syndrome Coronavirus 2. We also briefly discuss the reverse genetics systems which allow for analysis of viral replication cycles, next-generation sequencing technologies and the bioinformatics tools that facilitate this research.

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Understanding the genetic regulatory code governing gene expression is an important challenge in molecular biology. However, how individual coding and non-coding regions of the gene regulatory structure interact and contribute to mRNA expression levels remains unclear. Here we apply deep learning on over 20,000 mRNA datasets to examine the genetic regulatory code controlling mRNA abundance in 7 model organisms ranging from bacteria to Human. In all organisms, we can predict mRNA abundance directly from DNA sequence, with up to 82% of the variation of transcript levels encoded in the gene regulatory structure. By searching for DNA regulatory motifs across the gene regulatory structure, we discover that motif interactions could explain the whole dynamic range of mRNA levels. Co-evolution across coding and non-coding regions suggests that it is not single motifs or regions, but the entire gene regulatory structure and specific combination of regulatory elements that define gene expression levels.

Increased surface charge in the protein chaperone Spy enhances its anti-aggregation activity

Chaperones are essential components of the protein homeostasis network. There is a growing interest in optimizing chaperone function, but exactly how to achieve this aim is unclear. Here, using a model chaperone, the bacterial protein Spy, we demonstrate that substitutions that alter the electrostatic potential of Spy's concave, client-binding surface enhance Spy's anti-aggregation activity. We show that this strategy is more efficient than one that enhances the hydrophobicity of Spy's surface. Our findings thus challenge the traditional notion that hydrophobic interactions are the major driving forces that guide chaperone-substrate binding. Kinetic data revealed that both charge- and hydrophobicity-enhanced Spy variants release clients more slowly, resulting in a greater "holdase" activity. However, increasing short-range hydrophobic interactions deleteriously affected Spy's ability to capture substrates, thus reducing its in vitro chaperone activity toward fast-aggregating substrates. Our strategy in chaperone surface engineering therefore sought to fine-tune the different molecular forces involved in chaperone-substrate interactions rather than focusing on enhancing hydrophobic interactions. These results improve our understanding of the mechanistic basis of chaperone-client interactions and illustrate how protein surface-based mutational strategies can facilitate the rational improvement of molecular chaperones.

Evolving a Peptide: Library Platforms and Diversification Strategies

Peptides are widely used in pharmaceutical industry as active pharmaceutical ingredients, versatile tools in drug discovery, and for drug delivery. They find themselves at the crossroads of small molecules and proteins, possessing favorable tissue penetration and the capability to engage into specific and high-affinity interactions with endogenous receptors. One of the commonly employed approaches in peptide discovery and design is to screen combinatorial libraries, comprising a myriad of peptide variants of either chemical or biological origin. In this review, we focus mainly on recombinant peptide libraries, discussing different platforms for their display or expression, and various diversification strategies for library design. We take a look at well-established technologies as well as new developments and future directions.

A Phage-Assisted Continuous Selection Approach for Deep Mutational Scanning of Protein-Protein Interactions

Protein-protein interactions (PPIs) are critical for organizing molecules in a cell and mediating signaling pathways. Dysregulation of PPIs is often a key driver of disease. To better understand the biophysical basis of such disease processes-and to potentially target them-it is critical to understand the molecular determinants of PPIs. Deep mutational scanning (DMS) facilitates the acquisition of large amounts of biochemical data by coupling selection with high throughput sequencing (HTS). The challenging and labor-intensive design and optimization of a relevant selection platform for DMS, however, limits the use of powerful directed evolution and selection approaches. To address this limitation, we designed a versatile new phage-assisted continuous selection (PACS) system using our previously reported proximity-dependent split RNA polymerase (RNAP) biosensors, with the aim of greatly simplifying and streamlining the design of a new selection platform for PPIs. After characterization and validation using the model KRAS/RAF PPI, we generated a library of RAF variants and subjected them to PACS and DMS. Our HTS data revealed positions along the binding interface that are both tolerant and intolerant to mutations, as well as which substitutions are tolerated at each position. Critically, the "functional scores" obtained from enrichment data through continuous selection for individual variants correlated with K_D values measured in vitro, indicating that biochemical data can be extrapolated from sequencing using our new system. Due to the plug and play nature of RNAP biosensors, this method can likely be extended to a variety of other PPIs. More broadly, this, and other methods under development support the continued development of evolutionary and high-throughput approaches to address biochemical problems, moving toward a more comprehensive understanding of sequence-function relationships in proteins.

Antibody discovery and engineering by enhanced CRISPR-Cas9 integration of variable gene cassette libraries in mammalian cells

Antibody engineering in mammalian cells offers the important advantage of expression and screening of libraries in their native conformation, increasing the likelihood of generating candidates with more favorable molecular properties. Major advances in cellular engineering enabled by CRISPR-Cas9 genome editing have made it possible to expand the use of mammalian cells in biotechnological applications. Here, we describe an antibody engineering and screening approach where complete variable light (V_L) and heavy (V_H) chain cassette libraries are stably integrated into the genome of hybridoma cells by enhanced Cas9-driven homology-directed repair (HDR), resulting in their surface display and secretion. By developing an improved HDR donor format that utilizes in situ linearization, we are able to achieve >15-fold improvement of genomic integration, resulting in a screening workflow that only requires a simple plasmid electroporation. This proved suitable for different applications in antibody discovery and engineering. By integrating and screening an immune library obtained from the variable gene repertoire of an immunized mouse, we could isolate a diverse panel of >40 unique antigen-binding variants. Additionally, we successfully performed affinity maturation by directed evolution screening of an antibody library based on random mutagenesis, leading to the isolation of several clones with affinities in the picomolar range.

Modern methods for laboratory diversification of biomolecules

Genetic variation fuels Darwinian evolution, yet spontaneous mutation rates are maintained at low levels to ensure cellular viability. Low mutation rates preclude the exhaustive exploration of sequence space for protein evolution and genome engineering applications, prompting scientists to develop methods for efficient and targeted diversification of nucleic acid sequences. Directed evolution of biomolecules relies upon the generation of unbiased genetic diversity to discover variants with desirable properties, whereas genome-engineering applications require selective modifications on a genomic scale with minimal off-targets. Here, we review the current toolkit of mutagenesis strategies employed in directed evolution and genome engineering. These state-of-the-art methods enable facile modifications and improvements of single genes, multicomponent pathways, and whole genomes for basic and applied research, while simultaneously paving the way for genome editing therapeutic interventions.

Library Generation and Auxotrophic Selection Assays in Escherichia coli and Thermus thermophilus

The selection of optimized enzymes from gene libraries is important, both for basic and applied research. Here, we first describe the generation of plasmid-borne libraries using error-prone PCR and highly competent Escherichia coli cells. We then provide protocols for the use of these libraries for auxotrophic selection assays with E. coli and the extremely thermophilic bacterium Thermus thermophilus as hosts.

High Throughput Random Mutagenesis and Single Molecule Real Time Sequencing of the Muscle Nicotinic Acetylcholine Receptor

High throughput random mutagenesis is a powerful tool to identify which residues are important for the function of a protein, and gain insight into its structure-function relation. The human muscle nicotinic acetylcholine receptor was used to test whether this technique previously used for monomeric receptors can be applied to a pentameric ligand-gated ion channel. A mutant library for the α1 subunit of the channel was generated by error-prone PCR, and full length sequences of all 2816 mutants were retrieved using single molecule real time sequencing. Each α1 mutant was co-transfected with wildtype β1, δ, and ε subunits, and the channel function characterized by an ion flux assay. To test whether the strategy could map the structure-function relation of this receptor, we attempted to identify mutations that conferred resistance to competitive antagonists. Mutant hits were defined as receptors that responded to the nicotinic agonist epibatidine, but were not inhibited by either α-bungarotoxin or tubocurarine. Eight α1 subunit mutant hits were identified, six of which contained mutations at position Y233 or V275 in the transmembrane domain. Three single point mutations (Y233N, Y233H, and V275M) were studied further, and found to enhance the potencies of five channel agonists tested. This suggests that the mutations made the channel resistant to the antagonists, not by impairing antagonist binding, but rather by producing a gain-of-function phenotype, e.g. increased agonist sensitivity. Our data show that random high throughput mutagenesis is applicable to multimeric proteins to discover novel functional mutants, and outlines the benefits of using single molecule real time sequencing with regards to quality control of the mutant library as well as downstream mutant data interpretation.

Methods for the directed evolution of proteins

Directed evolution has proved to be an effective strategy for improving or altering the activity of biomolecules for industrial, research and therapeutic applications. The evolution of proteins in the laboratory requires methods for generating genetic diversity and for identifying protein variants with desired properties. This Review describes some of the tools used to diversify genes, as well as informative examples of screening and selection methods that identify or isolate evolved proteins. We highlight recent cases in which directed evolution generated enzymatic activities and substrate specificities not known to exist in nature.

Conformation-dependent epitopes recognized by prion protein antibodies probed using mutational scanning and deep sequencing

Prion diseases are caused by a structural rearrangement of the cellular prion protein, PrP(C), into a disease-associated conformation, PrP(Sc), which may be distinguished from one another using conformation-specific antibodies. We used mutational scanning by cell-surface display to screen 1341 PrP single point mutants for attenuated interaction with four anti-PrP antibodies, including several with conformational specificity. Single-molecule real-time gene sequencing was used to quantify enrichment of mutants, returning 26,000 high-quality full-length reads for each screened population on average. Relative enrichment of mutants correlated to the magnitude of the change in binding affinity. Mutations that diminished binding of the antibody ICSM18 represented the core of contact residues in the published crystal structure of its complex. A similarly located binding site was identified for D18, comprising discontinuous residues in helix 1 of PrP, brought into close proximity to one another only when the alpha helix is intact. The specificity of these antibodies for the normal form of PrP likely arises from loss of this conformational feature after conversion to the disease-associated form. Intriguingly, 6H4 binding was found to depend on interaction with the same residues, among others, suggesting that its ability to recognize both forms of PrP depends on a structural rearrangement of the antigen. The application of mutational scanning and deep sequencing provides residue-level resolution of positions in the protein-protein interaction interface that are critical for binding, as well as a quantitative measure of the impact of mutations on binding affinity.

High throughput mutagenesis for identification of residues regulating human prostacyclin (hIP) receptor expression and function

The human prostacyclin receptor (hIP receptor) is a seven-transmembrane G protein-coupled receptor (GPCR) that plays a critical role in vascular smooth muscle relaxation and platelet aggregation. hIP receptor dysfunction has been implicated in numerous cardiovascular abnormalities, including myocardial infarction, hypertension, thrombosis and atherosclerosis. Genomic sequencing has discovered several genetic variations in the PTGIR gene coding for hIP receptor, however, its structure-function relationship has not been sufficiently explored. Here we set out to investigate the applicability of high throughput random mutagenesis to study the structure-function relationship of hIP receptor. While chemical mutagenesis was not suitable to generate a mutagenesis library with sufficient coverage, our data demonstrate error-prone PCR (epPCR) mediated mutagenesis as a valuable method for the unbiased screening of residues regulating hIP receptor function and expression. Here we describe the generation and functional characterization of an epPCR derived mutagenesis library compromising >4000 mutants of the hIP receptor. We introduce next generation sequencing as a useful tool to validate the quality of mutagenesis libraries by providing information about the coverage, mutation rate and mutational bias. We identified 18 mutants of the hIP receptor that were expressed at the cell surface, but demonstrated impaired receptor function. A total of 38 non-synonymous mutations were identified within the coding region of the hIP receptor, mapping to 36 distinct residues, including several mutations previously reported to affect the signaling of the hIP receptor. Thus, our data demonstrates epPCR mediated random mutagenesis as a valuable and practical method to study the structure-function relationship of GPCRs.

Probabilistic methods in directed evolution: library size, mutation rate, and diversity

Directed evolution has emerged as an important tool for engineering proteins with improved or novel properties. Because of their inherent reliance on randomness, directed evolution protocols are amenable to probabilistic modeling and analysis. This chapter summarizes and reviews in a nonmathematical way some of the probabilistic works related to directed evolution, with particular focus on three of the most widely used methods: saturation mutagenesis, error-prone PCR, and in vitro recombination. The ultimate aim is to provide the reader with practical information to guide the planning and design of directed evolution studies. Importantly, the applications and locations of freely available computational resources to assist with this process are described in detail.

Directed evolution of G-protein-coupled receptors for high functional expression and detergent stability

G-protein-coupled receptors (GPCRs) are cell-surface receptors exhibiting a key role in cellular signal transduction processes, thus making them pharmacologically highly relevant target proteins. However, the molecular mechanisms driving receptor activation by ligand binding and signal transduction are poorly understood, since as integral membrane proteins, most GPCRs are very challenging for functional and structural studies. The biophysical properties of natural GPCRs, usually required by the cell in only low amounts, support their functionality in the lipid bilayer but are insufficient for high-level recombinant overexpression and stability in detergent solution. Current structural information about GPCRs is thus limited to a subset of GPCRs with either intrinsically favorable or properly improved biophysical behavior. Recently, directed protein evolution techniques for functional expression and detergent stability have been developed to increase the accessibility of GPCRs for functional and structural studies. Directed evolution does not rely on any preconceived notion of what might be limiting biophysical properties. By random mutagenesis combined with a high-throughput screening and selection system, directed protein evolution has the power to efficiently isolate rare phenotypes and thus contribute to the elucidation of the stability-determining factors, in addition to solving the practical problem of creating stable GPCRs. In the current chapter, protocols for generation of genetic diversity within GPCRs and selection are provided and discussed.

MAP(2.0)3D: a sequence/structure based server for protein engineering

The Mutagenesis Assistant Program (MAP) is a web-based tool to provide statistical analyses of the mutational biases of directed evolution experiments on amino acid substitution patterns. MAP analysis assists protein engineers in the benchmarking of random mutagenesis methods that generate single nucleotide mutations in a codon. Herein, we describe a completely renewed and improved version of the MAP server, the MAP(2.0)3D server, which correlates the generated amino acid substitution patterns to the structural information of the target protein. This correlation aids in the selection of a more suitable random mutagenesis method with specific biases on amino acid substitution patterns. In particular, the new server represents MAP indicators on secondary and tertiary structure and correlates them to specific structural components such as hydrogen bonds, hydrophobic contacts, salt bridges, solvent accessibility, and crystallographic B-factors. Three model proteins (D-amino oxidase, phytase, and N-acetylneuraminic acid aldolase) are used to illustrate the novel capability of the server. MAP(2.0)3D server is available publicly at http://map.jacobs-university.de/map3d.html.

Mechanistic and structural insights into the regioselectivity of an acyl-CoA fatty acid desaturase via directed molecular evolution

Membrane-bound fatty acid desaturases and related enzymes play a pivotal role in the biosynthesis of unsaturated and various unusual fatty acids. Structural insights into the remarkable catalytic diversity and wide range of substrate specificities of this class of enzymes remain limited due to the lack of a crystal structure. To investigate the structural basis of the double bond positioning (regioselectivity) of the desaturation reaction in more detail, we relied on a combination of directed evolution in vitro and a powerful yeast complementation assay to screen for Δx regioselectivity. After two selection rounds, variants of the bifunctional Δ12/Δ9-desaturase from the house cricket (Acheta domesticus) exhibited increased Δ9-desaturation activity on shorter chain fatty acids. This change in specificity was the result of as few as three mutations, some of them near the putative active site. Subsequent analysis of individual substitutions revealed an important role of residue Phe-52 in facilitating Δ9-desaturation of shorter chain acyl substrates and allowed for the redesign of the cricket Δ12/Δ9-desaturase into a 16:0-specific Δ9-desaturase. Our results demonstrate that a minimal number of mutations can have a profound impact on the regioselectivity of acyl-CoA fatty acid desaturases and include the first biochemical data supporting the acyl-CoA acyl carrier specificity of a desaturase able to carry out Δ12-desaturation.

Role of the F1 region in the Escherichia coli aerotaxis receptor Aer

In Escherichia coli, the aerotaxis receptor Aer is an atypical receptor because it senses intracellular redox potential. The Aer sensor is a cytoplasmic, N-terminal PAS domain that is tethered to the membrane by a 47-residue F1 linker. Here we investigated the function, topology, and orientation of F1 by employing random mutagenesis, cysteine scanning, and disulfide cross-linking. No native residue was obligatory for function, most deleterious substitutions had radically different side chain properties, and all F1 mutants but one were functionally rescued by the chemoreceptor Tar. Cross-linking studies were consistent with the predicted α-helical structure in the N-terminal F1 region and demonstrated trigonal interactions among the F1 linkers from three Aer monomers, presumably within trimer-of-dimer units, as well as binary interactions between subunits. Using heterodimer analyses, we also demonstrated the importance of arginine residues near the membrane interface, which may properly anchor the Aer protein in the membrane. By incorporating these data into a homology model of Aer, we developed a model for the orientation of the Aer F1 and PAS regions in an Aer lattice that is compatible with the known dimensions of the chemoreceptor lattice. We propose that the F1 region facilitates the orientation of PAS and HAMP domains during folding and thereby promotes the stability of the PAS and HAMP domains in Aer.

Gain-of-function mutations cluster in distinct regions associated with the signalling pathway in the PAS domain of the aerotaxis receptor, Aer

The Aer receptor monitors internal energy (redox) levels in Escherichia coli with an FAD-containing PAS domain. Here, we randomly mutagenized the region encoding residues 14-119 of the PAS domain and found 72 aerotaxis-defective mutants, 24 of which were gain-of-function, signal-on mutants. The mutations were mapped onto an Aer homology model based on the structure of the PAS-FAD domain in NifL from Azotobacter vinlandii. Signal-on lesions clustered in the FAD binding pocket, the beta-scaffolding and in the N-cap loop. We suggest that the signal-on lesions mimic the 'signal-on' state of the PAS domain, and therefore may be markers for the signal-in and signal-out regions of this domain. We propose that the reduction of FAD rearranges the FAD binding pocket in a way that repositions the beta-scaffolding and the N-cap loop. The resulting conformational changes are likely to be conveyed directly to the HAMP domain, and on to the kinase control module. In support of this hypothesis, we demonstrated disulphide band formation between cysteines substituted at residues N98C or I114C in the PAS beta-scaffold and residue Q248C in the HAMP AS-2 helix.

Enzyme engineering for enantioselectivity: from trial-and-error to rational design?

The availability of tailored enzymes is crucial for the implementation of biocatalysis in organic chemistry. Enantioselectivity is one key parameter defining the usefulness of an enzyme and, therefore, the competitiveness of the corresponding industrial process. Hence, identification of enzymes with high enantioselectivity in the desired transformation is important. Currently, this is achieved by screening collections and libraries comprising natural or man-made diversity for the desired trait. Recently, a variety of improved methods have been developed to generate and screen this diversity more efficiently. Here, we present and discuss the most important advances in both library generation and screening. We also evaluate future trends, such as moving from random evolution to more rational.

Critical evaluation of random mutagenesis by error-prone polymerase chain reaction protocols, Escherichia coli mutator strain, and hydroxylamine treatment

Random mutagenesis methods constitute a valuable protein modification toolbox with applications ranging from protein engineering to directed protein evolution studies. Although a variety of techniques are currently available, the field is lacking studies that would directly compare the performance parameters and operational range of different methods. In this study, we have scrutinized several of the most commonly used random mutagenesis techniques by critically evaluating popular error-prone polymerase chain reaction (PCR) protocols as well as hydroxylamine and a mutator Escherichia coli strain mutagenesis methods. Relative mutation frequencies were analyzed using a reporter plasmid that allowed direct comparison of the methods. Error-prone PCR methods yielded the highest mutation rates and the widest operational ranges, whereas the chemical and biological methods generated a low level of mutations and exhibited a narrow range of operation. The repertoire of transitions versus transversions varied among the methods, suggesting the use of a combination of methods for high-diversity full-scale mutagenesis. Using the parameters defined in this study, the evaluated mutagenesis methods can be used for controlled mutagenesis, where the intended average frequency of induced mutations can be adjusted to a desirable level.

Predicting protein evolution in vitro by phage escape technology

The relationship between host and pathogen is inherently dynamic at the genetic level. A plethora of host defensive systems have evolved to counteract and/or eliminate invading pathogens. These strategies exert selection pressure upon the pathogen, leading to the emergence of mechanisms to combat the host including immune evasion and resistance. Consequently, effective control of rapidly evolving diseases is contingent on the ability to predict pathogen evolution prior to the emergence of resistant phenotypes. Highlighted in this article is a bacteriophage-based technology capable of screening hundreds of millions of binding events simultaneously at single molecule resolution, thus providing an in vitro mimetic of protein evolution. This technology, termed phage escape, can be utilized to model the evolution of proteins in the presence of antibodies or other selective pressure, providing a predictive solution to the coevolution of antigens and the immune system. Foresight into the evolutionary path of an antigen and subsequent neutralization strategies can facilitate more efficacious vaccination formulation and have important implications in the treatment of a range of evolving diseases, including viral infections and cancer.

A new recombinant protein expression system for high-throughput screening in the yeast Yarrowia lipolytica

Development of a high-throughput eukaryotic screening procedure is important to increase success in obtaining improved enzymes through directed enzyme evolution. This procedure was developed for the yeast Yarrowia lipolytica which becomes the second eukaryotic host for this purpose. The extracellular lipase Lip2 was used as expressed enzyme but this system will be easily adjusted for other enzymes. We adapted and optimized the protocol for protein expression by Y. lipolytica in 96-well microplates. Yeast transformation efficiency and expression cassette insertion were increased by constructing a strain containing a zeta docking platform for targeted integration into the genome. The coefficient of variance of the full process was reduced from 36.3% to 18.9%. The main part of the variability (11.7%) arises from the specific lipase enzyme assay whereas the coefficient of variance concerning transformation, growth and expression steps represents only 7.2%. The rate of clone with no activity was reduced from 5.8% to 0.2%. Both transformation efficiency and variability are then compatible with high-throughput screening in the yeast Y. lipolytica.

Genetic selection for critical residues in ribonucleases

Homologous mammalian proteins were subjected to an exhaustive search for residues that are critical to their structure/function. Error-prone polymerase chain reactions were used to generate random mutations in the genes of bovine pancreatic ribonuclease (RNase A) and human angiogenin, and a genetic selection based on the intrinsic cytotoxicity of ribonucleolytic activity was used to isolate inactive variants. Twenty-three of the 124 residues in RNase A were found to be intolerant to substitution with at least one particular amino acid. Twenty-nine of the 123 residues in angiogenin were likewise intolerant. In both RNase A and angiogenin, only six residues appeared to be wholly intolerant to substitution: two histidine residues involved in general acid/base catalysis and four cysteine residues that form two disulfide bonds. With few exceptions, the remaining critical residues were buried in the hydrophobic core of the proteins. Most of these residues were found to tolerate only conservative substitutions. The importance of a particular residue as revealed by this genetic selection correlated with its sequence conservation, though several non-conserved residues were found to be critical for protein structure/function. Despite voluminous research on RNase A, the importance of many residues identified herein was unknown, and those can now serve as targets for future work. Moreover, a comparison of the critical residues in RNase A and human angiogenin, which share only 35% amino acid sequence identity, provides a unique perspective on the molecular evolution of the RNase A superfamily, as well as an impetus for applying this methodology to other ribonucleases.

Strategies and computational tools for improving randomized protein libraries

In the last decade, directed evolution has become a routine approach for engineering proteins with novel or altered properties. Concurrently, a trend away from purely 'blind' randomization strategies and towards more 'semi-rational' approaches has also become apparent. In this review, we discuss ways in which structural information and predictive computational tools are playing an increasingly important role in guiding the design of randomized libraries: web servers such as ConSurf-HSSP and SCHEMA allow the prediction of sites to target for producing functional variants, while algorithms such as GLUE, PEDEL and DRIVeR are useful for estimating library completeness and diversity. In addition, we review recent methodological developments that facilitate the construction of unbiased libraries, which are inherently more diverse than biased libraries and therefore more likely to yield improved variants.

A computer program for the estimation of protein and nucleic acid sequence diversity in random point mutagenesis libraries

A computer program for the generation and analysis of in silico random point mutagenesis libraries is described. The program operates by mutagenizing an input nucleic acid sequence according to mutation parameters specified by the user for each sequence position and type of point mutation. The program can mimic almost any type of random mutagenesis library, including those produced via error-prone PCR (ep-PCR), mutator Escherichia coli strains, chemical mutagenesis, and doped or random oligonucleotide synthesis. The program analyzes the generated nucleic acid sequences and/or the associated protein library to produce several estimates of library diversity (number of unique sequences, point mutations, and single point mutants) and the rate of saturation of these diversities during experimental screening or selection of clones. This information allows one to select the optimal screen size for a given mutagenesis library, necessary to efficiently obtain a certain coverage of the sequence-space. The program also reports the abundance of each specific protein mutation at each sequence position, which is useful as a measure of the level and type of mutation bias in the library. Alternatively, one can use the program to evaluate the relative merits of preexisting libraries, or to examine various hypothetical mutation schemes to determine the optimal method for creating a library that serves the screen/selection of interest. Simulated libraries of at least 10⁹ sequences are accessible by the numerical algorithm with currently available personal computers; an analytical algorithm is also available which can rapidly calculate a subset of the numerical statistics in libraries of arbitrarily large size. A multi-type double-strand stochastic model of ep-PCR is developed in an appendix to demonstrate the applicability of the algorithm to amplifying mutagenesis procedures. Estimators of DNA polymerase mutation-type-specific error rates are derived using the model. Analyses of an alpha-synuclein ep-PCR library and NNS synthetic oligonucleotide libraries are given as examples.