Advances in the directed evolution of proteins

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Programmable synthetic receptors: the next-generation of cell and gene therapies

Cell and gene therapies hold tremendous promise for treating a range of difficult-to-treat diseases. However, concerns over the safety and efficacy require to be further addressed in order to realize their full potential. Synthetic receptors, a synthetic biology tool that can precisely control the function of therapeutic cells and genetic modules, have been rapidly developed and applied as a powerful solution. Delicately designed and engineered, they can be applied to finetune the therapeutic activities, i.e., to regulate production of dosed, bioactive payloads by sensing and processing user-defined signals or biomarkers. This review provides an overview of diverse synthetic receptor systems being used to reprogram therapeutic cells and their wide applications in biomedical research. With a special focus on four synthetic receptor systems at the forefront, including chimeric antigen receptors (CARs) and synthetic Notch (synNotch) receptors, we address the generalized strategies to design, construct and improve synthetic receptors. Meanwhile, we also highlight the expanding landscape of therapeutic applications of the synthetic receptor systems as well as current challenges in their clinical translation.

Designing Multivalent and Multispecific Biologics

In the era of precision medicine, multivalent and multispecific therapeutics present a promising approach for targeted disease intervention. These therapeutics are designed to interact with multiple targets simultaneously, promising enhanced efficacy, reduced side effects, and resilience against drug resistance. We dissect the principles guiding the design of multivalent biologics, highlighting challenges and strategies that must be considered to maximize therapeutic effect. Engineerable elements in multivalent and multispecific biologic design-domain affinities, valency, and spatial presentation-must be considered in the context of the molecular targets as well as the balance of important properties such as target avidity and specificity. We illuminate recent applications of these principles in designing protein and cell therapies and identify exciting future directions in this field, underscored by advances in biomolecular and cellular engineering and computational approaches. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering , Volume 15 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

MBE: model-based enrichment estimation and prediction for differential sequencing data

Characterizing differences in sequences between two conditions, such as with and without drug exposure, using high-throughput sequencing data is a prevalent problem involving quantifying changes in sequence abundances, and predicting such differences for unobserved sequences. A key shortcoming of current approaches is their extremely limited ability to share information across related but non-identical reads. Consequently, they cannot use sequencing data effectively, nor be directly applied in many settings of interest. We introduce model-based enrichment (MBE) to overcome this shortcoming. We evaluate MBE using both simulated and real data. Overall, MBE improves accuracy compared to current differential analysis methods.

The Wild-Type tRNA Adenosine Deaminase Enzyme TadA Is Capable of Sequence-Specific DNA Base Editing

Base editors are genome editing tools that enable site-specific base conversions through the chemical modification of nucleobases in DNA. Adenine base editors (ABEs) convert A ⋅ T to G ⋅ C base pairs in DNA by using an adenosine deaminase enzyme to modify target adenosines to inosine intermediates. Due to the lack of a naturally occurring adenosine deaminase that can modify DNA, ABEs were evolved from a tRNA-deaminating enzyme, TadA. Previous experiments with an ABE comprising a wild-type (wt) TadA showed no detectable activity on DNA, and directed evolution was therefore required to enable this enzyme to accept DNA as a substrate. Here we show that wtTadA can perform base editing in DNA in both bacterial and mammalian cells, with a strict sequence motif requirement of TAC. We leveraged this discovery to optimize a reporter assay to detect base editing levels as low as 0.01 %. Finally, we used this assay along with molecular dynamics simulations of full ABE:DNA complexes to better understand how the sequence recognition of mutant TadA variants change as they accumulate mutations to better edit DNA substrates.

Comparative biochemical characterization of mammalian-derived CYP11A1s with cholesterol side-chain cleavage activities

Steroid drugs, the second largest class of pharmaceuticals after antibiotics, have shown significant anti-inflammatory, anti-allergic, and endocrine-regulating effects. A group of cytochrome P450 enzymes, namely, CYP11A1 isoenzymes from different organisms are capable of converting cholesterol into pregnenolone, which is a pivotal reaction in both steroid metabolism and (bio)synthetic network of steroid products. However, the low activity of CYP11A1s greatly restricts the industrial application of these cholesterol side-chain cleavage enzymes. Herein, we investigate ten CYP11A1 enzymes of different origins and in vitro characterize two CYP11A1s with a relatively higher expression level from Capra hircus and Sus scrofa, together with the CYP11A1s from Homo sapiens and Bos taurus as references. Towards five selected sterol substrates with different side chain structures, S. scrofa CYP11A1 displays relatively higher activities. Through redox partners combination screening, we reveal the optimal redox partner pair of S. scrofa adrenodoxin and C. hircus adrenodoxin reductase. Moreover, the semi-rational mutagenesis for the active sites and substrate entrance channels of human and bovine CYP11A1s is performed based on comparative analysis of their crystal structures. The mutant mBtCYP11A1-Q377A derived from mature B. taurus CYP11A1 shows a 1.46 times higher activity than the wild type enzyme. These results not only demonstrate the tunability of the highly conserved CYP11A1 isoenzymes, but also lay a foundation for the following engineering efforts on these industrially relevant P450 enzymes.

The Role of Quorum Sensing Molecules in Bacterial-Plant Interactions

Quorum sensing (QS) is a system of communication of bacterial cells by means of chemical signals called autoinducers, which modulate the behavior of entire populations of Gram-negative and Gram-positive bacteria. Three classes of signaling molecules have been recognized, Al-1, Al-2, Al-3, whose functions are slightly different. However, the phenomenon of quorum sensing is not only concerned with the interactions between bacteria, but the whole spectrum of interspecies interactions. A growing number of research results confirm the important role of QS molecules in the growth stimulation and defense responses in plants. Although many of the details concerning the signaling metabolites of the rhizosphere microflora and plant host are still unknown, Al-1 compounds should be considered as important components of bacterial-plant interactions, leading to the stimulation of plant growth and the biological control of phytopathogens. The use of class 1 autoinducers in plants to induce beneficial activity may be a practical solution to improve plant productivity under field conditions. In addition, researchers are also interested in tools that offer the possibility of regulating the activity of autoinducers by means of degrading enzymes or specific inhibitors (QSI). Current knowledge of QS and QSI provides an excellent foundation for the application of research to biopreparations in agriculture, containing a consortia of AHL-producing bacteria and QS inhibitors and limiting the growth of phytopathogenic organisms.

Directed Evolution of Laccase for Improved Thermal Stability Facilitated by Droplet-Based Microfluidic Screening System

Laccases are attractive biocatalysts for industry due to their broad substrate spectrum, the use of oxygen as final electron acceptor, and water as the sole byproduct. Increasing efforts have been devoted to the engineering of laccases to improve their properties. The droplet-based microfluidic screening (DMFS) technology can accelerate the screening procedure and probe the large sequence space. In this study, a DMFS system including a heating step and picoinjection was used to sort large laccase libraries, yielding 12 variants with enhanced thermotolerance. All the obtained amino acid substitutions are distributed on the surface of the laccase. Interestingly, recombination of three identified substitutions of Asp to Asn on the surface resulted in the best variant M20, exhibiting 24.0-fold higher remaining activity at 58.8 °C and 1.9-3.4-fold higher remaining activity after incubation in organic solvents solution (20% (v/v) methanol and ethanol) and ionic liquid solution (20% (v/v) 1-ethyl-3-methylimidazolium ethyl sulfate) for 12 h. Furthermore, molecular dynamic simulations revealed that the recombination of the three beneficial substitutions, Asp98Asn, Asp474Asn, and Asp340Asn on the surface introduced more hydrogen bonds compared to the wild type, which made M20 more thermostable. This study highlighted the importance of the DMFS system for an efficient identification of beneficial long-distance amino acid substitutions.

Enhancement of solubility of recombinant alcohol dehydrogenase from Rhodococcus ruber using predictive tool

Solubility is one of key factors influencing the heterologous production of recombinant proteins in biotechnology. Among many aggregation-prone proteins, alcohol dehydrogenase (ADH-A) from Rhodococcus ruber (in this work abbreviated RrADH) shows a great potential in processes involved in the biotransformation of natural compounds. As ADH-A is a potentially high value asset in industrial biotransformation processes, improvement of its solubility would be of major commercial benefit. Predictive tools and in silico analysis provide a fast means for improving protein properties, for selecting appropriate changes, and ultimately for saving costs. We have therefore focused on enhancement of the solubility of RrADH using an online accesible predictive tool Aggrescan 3D 2.0. Selected mutations were introduced into the protein amino acid sequence by using site-directed PCR. This led to a 17% increase in the protein solubility of RrADHmut1 and a 98% increase for RrADHmut2. Moreover, the basic kinetics of the enzyme reaction were positively affected, further optimizing the overall performance of the production process.

Protposer: the web server that readily proposes protein stabilizing mutations with high PPV

Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here Protposer, a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, Protposer uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, Protposer analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When Protposer is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, Protposer largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. Protposer is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at http://webapps.bifi.es/the-protposer.

Cell-Free Synthesis of Human Endothelin Receptors and Its Application to Ribosome Display

Engineering G-protein-coupled receptors (GPCRs) for improved stability or altered function is of great interest, as GPCRs consist of the largest protein family, are involved in many important signaling pathways, and thus, are one of the major drug targets. Here, we report the development of a high-throughput screening method for GPCRs using a reconstituted in vitro transcription-translation (IVTT) system. Human endothelin receptor type-B (ETBR), a class A GPCR that binds endothelin-1 (ET-1), a 21-residue peptide hormone, was synthesized in the presence of nanodisc (ND) composed of a phospholipid, 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (POPG). The ET-1 binding of ETBR was significantly reduced or was undetectable when other phospholipids were used for ND preparation. However, when functional ETBR purified from Sf9 cells was reconstituted into NDs, ET-1 binding was observed with two different phospholipids tested, including POPG. These results suggest that POPG likely supports the folding of ETBR into its functional form in the IVTT system. Using the same conditions as ETBR, whose three-dimensional structure has been solved, human endothelin receptor type-A (ETAR), whose three-dimensional structure remains unsolved, was also synthesized in its functional form. By adding POPG-ND to the IVTT system, both ETAR and ETBR were successfully subjected to ribosome display, a method of in vitro directed evolution that facilitates the screening of up to 10¹² mutants. Finally, using a mock library, we showed that ribosome display can be applied for gene screening of ETBR, suggesting that high-throughput screening and directed evolution of GPCRs is possible in vitro.

Engineering a Fluorescent Protein Color Switch Using Entropy-Driven β-Strand Exchange

Protein conformational switches are widely used in biosensing. They are often composed of an input domain (which binds a target ligand) fused to an output domain (which generates an optical readout). A central challenge in designing such switches is to develop mechanisms for coupling the input and output signals via conformational changes. Here, we create a biosensor in which binding-induced folding of the input domain drives a conformational shift in the output domain that results in a sixfold green-to-yellow ratiometric fluorescence change in vitro and a 35-fold intensiometric fluorescence increase in cultured cells. The input domain consists of circularly permuted FK506 binding protein (cpFKBP) that folds upon binding its target ligand (FK506 or rapamycin). cpFKBP folding induces the output domain, an engineered green fluorescent protein (GFP) variant, to replace one of its β-strands (containing T203 and specifying green fluorescence) with a duplicate β-strand (containing Y203 and specifying yellow fluorescence) in an intramolecular exchange reaction. This mechanism employs the loop-closure entropy principle, embodied by the folding of the partially disordered cpFKBP domain, to couple ligand binding to the GFP color shift. This study highlights the high-energy barriers present in GFP folding which cause β-strand exchange to be slow and are also likely responsible for the shift from the β-strand exchange mechanism in vitro to ligand-induced chromophore maturation in cells. The proof-of-concept design has the advantages of full genetic encodability and potential for modularity. The latter attribute is enabled by the natural coupling of binding and folding and circular permutation of the input domain, which theoretically allows different binding domains to be compatible for insertion into the GFP surface loop.

Directed Evolution of a Nonheme Diiron N-oxygenase AzoC for Improving Its Catalytic Efficiency toward Nitrogen Heterocycle Substrates

The azoxy compounds with an intriguing chemical bond [-N=N⁺(-O⁻)-] are known to have broad applications in many industries. Our previous work revealed that a nonheme diiron N-oxygenase AzoC catalyzed the oxidization of amino-group to its nitroso analogue in the formation of azoxy bond in azoxymycins biosynthesis. However, except for the reported pyridine alkaloid azoxy compounds, most azoxy bonds of nitrogen heterocycles have not been biosynthesized so far, and the substrate scope of AzoC is limited to p-aminobenzene-type compounds. Therefore, it is very meaningful to use AzoC to realize the biosynthesis of azoxy nitrogen heterocycles compounds. In this work, we further studied the catalytic potential of AzoC toward nitrogen heterocycle substrates including 5-aminopyrimidine and 5-aminopyridine compounds to form new azoxy compounds through directed evolution. We constructed a double mutant L101I/Q104R via molecular engineering with improved catalytic efficiency toward 2-methoxypyrimidin-5-amine. These mutations also proved to be beneficial for N-oxygenation of methyl 5-aminopyrimidine-2-carboxylate. The structural analysis showed that relatively shorter distance between the substrate and the diiron center and amino acid residues of the active center may be responsible for the improvement of catalytic efficiency in L101I/Q104R. Our results provide a molecular basis for broadening the AzoC catalytic activity and its application in the biosynthesis of azoxy six-membered nitrogen catenation compounds.

PacBio sequencing output increased through uniform and directional fivefold concatenation

Advances in sequencing technology have allowed researchers to sequence DNA with greater ease and at decreasing costs. Main developments have focused on either sequencing many short sequences or fewer large sequences. Methods for sequencing mid-sized sequences of 600-5,000 bp are currently less efficient. For example, the PacBio Sequel I system yields ~ 100,000-300,000 reads with an accuracy per base pair of 90-99%. We sought to sequence several DNA populations of ~ 870 bp in length with a sequencing accuracy of 99% and to the greatest depth possible. We optimised a simple, robust method to concatenate genes of ~ 870 bp five times and then sequenced the resulting DNA of ~ 5,000 bp by PacBioSMRT long-read sequencing. Our method improved upon previously published concatenation attempts, leading to a greater sequencing depth, high-quality reads and limited sample preparation at little expense. We applied this efficient concatenation protocol to sequence nine DNA populations from a protein engineering study. The improved method is accompanied by a simple and user-friendly analysis pipeline, DeCatCounter, to sequence medium-length sequences efficiently at one-fifth of the cost.

Hinge-shift mechanism as a protein design principle for the evolution of β-lactamases from substrate promiscuity to specificity

TEM-1 β-lactamase degrades β-lactam antibiotics with a strong preference for penicillins. Sequence reconstruction studies indicate that it evolved from ancestral enzymes that degraded a variety of β-lactam antibiotics with moderate efficiency. This generalist to specialist conversion involved more than 100 mutational changes, but conserved fold and catalytic residues, suggesting a role for dynamics in enzyme evolution. Here, we develop a conformational dynamics computational approach to rationally mold a protein flexibility profile on the basis of a hinge-shift mechanism. By deliberately weighting and altering the conformational dynamics of a putative Precambrian β-lactamase, we engineer enzyme specificity that mimics the modern TEM-1 β-lactamase with only 21 amino acid replacements. Our conformational dynamics design thus re-enacts the evolutionary process and provides a rational allosteric approach for manipulating function while conserving the enzyme active site.

De novo proteins from random sequences through in vitro evolution

Natural proteins are the result of billions of years of evolution. The earliest predecessors of today's proteins are believed to have emerged from random polypeptides. While we have no means to determine how this process exactly happened, there is great interest in understanding how it reasonably could have happened. We are reviewing how researchers have utilized in vitro selection and molecular evolution methods to investigate plausible scenarios for the emergence of early functional proteins. The studies range from analyzing general properties and structural features of unevolved random polypeptides to isolating de novo proteins with specific functions from synthetic randomized sequence libraries or generating novel proteins by combining evolution with rational design. While the results are exciting, more work is needed to fully unravel the mechanisms that seeded protein-dominated biology.

Peptides and pseudopeptide ligands: a powerful toolbox for the affinity purification of current and next-generation biotherapeutics

Following the consolidation of therapeutic proteins in the fight against cancer, autoimmune, and neurodegenerative diseases, recent advancements in biochemistry and biotechnology have introduced a host of next-generation biotherapeutics, such as CRISPR-Cas nucleases, stem and car-T cells, and viral vectors for gene therapy. With these drugs entering the clinical pipeline, a new challenge lies ahead: how to manufacture large quantities of high-purity biotherapeutics that meet the growing demand by clinics and biotech companies worldwide. The protein ligands employed by the industry are inadequate to confront this challenge: while featuring high binding affinity and selectivity, these ligands require laborious engineering and expensive manufacturing, are prone to biochemical degradation, and pose safety concerns related to their bacterial origin. Peptides and pseudopeptides make excellent candidates to form a new cohort of ligands for the purification of next-generation biotherapeutics. Peptide-based ligands feature excellent target biorecognition, low or no toxicity and immunogenicity, and can be manufactured affordably at large scale. This work presents a comprehensive and systematic review of the literature on peptide-based ligands and their use in the affinity purification of established and upcoming biological drugs. A comparative analysis is first presented on peptide engineering principles, the development of ligands targeting different biomolecular targets, and the promises and challenges connected to the industrial implementation of peptide ligands. The reviewed literature is organized in (i) conventional (α-)peptides targeting antibodies and other therapeutic proteins, gene therapy products, and therapeutic cells; (ii) cyclic peptides and pseudo-peptides for protein purification and capture of viral and bacterial pathogens; and (iii) the forefront of peptide mimetics, such as β-/γ-peptides, peptoids, foldamers, and stimuli-responsive peptides for advanced processing of biologics.

Enhancing promiscuous chemistries of a Schiff-base forming enzyme by divergent evolution

Directed evolution has emerged as a powerful technique for the rapid tailoring of enzymes toward particular synthetic demands, spawning a number of enzymes capable of complex chemical transformations. During random mutagenesis of a protein, changes in fitness must be assayed in order to quantify and understand the relative effect a given mutation has, and the assay employed must be carefully chosen to report directly on the transformation of interest. Here, we describe a series of medium-throughput screening techniques that have been utilized for the evolution and engineering of an artificial carboligase, RA95.5-8, resulting in improvement of catalytic efficiency of a number of promiscuous chemistries. The methods make use of common analytical chemistry equipment and low-cost materials, and may help inspire development of novel screening workflows for related transformations.

Smart stimuli-responsive biopolymeric nanomedicines for targeted therapy of solid tumors

Solid tumors form a permissive microenvironment with irregular features, including high pressured tumor interstitial fluid with acidic pH, co-adaptation of cancer cells with other cells like the immune system cells, abnormal metabolism and anomalous overexpression of various pieces of molecular machinery. The functional expressions of several oncomarkers in different solid tumors have led to the development of targeted drug-delivery systems (DDSs). As a new class of DDSs, stimuli-responsive nanomedicines (SRNMs) have been developed using advanced nanobiomaterials such as biopolymers that show excellent biocompatibility with low inherent immunogenicity. In this review, we aim to overview different types of SRNMs, present deep insights into the stimuli-responsive biopolymers and discuss the most up-to-date progress in the design and development of SRNMs used as advanced DDSs for targeted therapy of cancer.

Rozhkova A, N. Zorov I, Korotkova O, P. Sinitsyn A, Schwaneberg U, D. Davari M. Engineering Robust Cellulases for Tailored Lignocellulosic Degradation Cocktails

Lignocellulosic biomass is a most promising feedstock in the production of second-generation biofuels. Efficient degradation of lignocellulosic biomass requires a synergistic action of several cellulases and hemicellulases. Cellulases depolymerize cellulose, the main polymer of the lignocellulosic biomass, to its building blocks. The production of cellulase cocktails has been widely explored, however, there are still some main challenges that enzymes need to overcome in order to develop a sustainable production of bioethanol. The main challenges include low activity, product inhibition, and the need to perform fine-tuning of a cellulase cocktail for each type of biomass. Protein engineering and directed evolution are powerful technologies to improve enzyme properties such as increased activity, decreased product inhibition, increased thermal stability, improved performance in non-conventional media, and pH stability, which will lead to a production of more efficient cocktails. In this review, we focus on recent advances in cellulase cocktail production, its current challenges, protein engineering as an efficient strategy to engineer cellulases, and our view on future prospects in the generation of tailored cellulases for biofuel production.

In Vitro Selection of Peptides and Proteins-Advantages of mRNA Display

mRNA display is a robust in vitro selection technique that allows the selection of peptides and proteins with desired functions from libraries of trillions of variants. mRNA display relies upon a covalent linkage between a protein and its encoding mRNA molecule; the power of the technique stems from the stability of this link, and the large degree of control over experimental conditions afforded to the researcher. This article describes the major advantages that make mRNA display the method of choice among comparable in vivo and in vitro methods, including cell-surface display, phage display, and ribosomal display. We also describe innovative techniques that harness mRNA display for directed evolution, protein engineering, and drug discovery.

Computer-Assisted Recombination (CompassR) Teaches us How to Recombine Beneficial Substitutions from Directed Evolution Campaigns

A main remaining challenge in protein engineering is how to recombine beneficial substitutions. Systematic recombination studies show that poorly performing variants are usually obtained after recombination of 3 to 4 beneficial substitutions. This limits researchers in exploiting nature's potential in generating better enzymes. The Computer-assisted Recombination (CompassR) strategy provides a selection guide for beneficial substitutions that can be recombined to gradually improve enzyme performance by analysis of the relative free energy of folding (ΔΔGfold ). The performance of CompassR was evaluated by analysis of 84 recombinants located on 13 positions of Bacillus subtilis lipase A. The finally obtained variant F17S/V54K/D64N/D91E had a 2.7-fold improved specific activity in 18.3 % (v/v) 1-butyl-3-methylimidazolium chloride ([BMIM][Cl]). In essence, the deducted CompassR rule allows recombination of beneficial substitutions in an iterative manner and empowers researchers to generate better enzymes in a time-efficient manner.

Learning the pattern of epistasis linking genotype and phenotype in a protein

Understanding the pattern of epistasis-the non-independence of mutations-is critical for relating genotype and phenotype. However, the combinatorial complexity of potential epistatic interactions has severely limited the analysis of this problem. Using new mutational approaches, we report a comprehensive experimental study of all 2¹³ mutants that link two phenotypically distinct variants of the Entacmaea quadricolor fluorescent protein-an opportunity to examine epistasis up to the 13^th order. The data show the existence of many high-order epistatic interactions between mutations, but also reveal extraordinary sparsity, enabling novel experimental and computational strategies for learning the relevant epistasis. We demonstrate that such information, in turn, can be used to accurately predict phenotypes in practical situations where the number of measurements is limited. Finally, we show how the observed epistasis shapes the solution space of single-mutation trajectories between the parental fluorescent proteins, informative about the protein's evolutionary potential. This work provides conceptual and experimental strategies to profoundly characterize epistasis in a protein, relevant to both natural and laboratory evolution.

Key Genetic Parameters for Population Management

Population management has the primary task of maximizing the long-term competitiveness of a breed. Breeds compete with each other for being able to supply consumer demands at low costs and also for funds from conservation programs. The competition for consumer preference is won by breeds with high genetic gain for total merit who maintained a sufficiently high genetic diversity, whereas the competition for funds is won by breeds with high conservation value. The conservation value of a breed could be improved by increasing its contribution to the gene pool of the species. This may include the recovery of its original genetic background and the maintenance of a high genetic diversity at native haplotype segments. The primary objective of a breeding program depends on the genetic state of the population and its intended usage. In this paper, we review the key genetic parameters that are relevant for population management, compare the methods for estimating them, derive the formulas for predicting their value at a future time, and clarify their usage in various types of breeding programs that differ in their main objectives. These key parameters are kinships, native kinships, breeding values, Mendelian sampling variances, native contributions, and mutational effects. Population management currently experiences a transition from using pedigree-based estimates to marker-based estimates, which improves the accuracies of these estimates and thereby increases response to selection. In addition, improved measures of the factors that determine the competitiveness of a breed and utilize auxiliary parameters, such as Mendelian sampling variances, mutational effects, and native kinships, enable to improve further upon historic recommendations for genetic population management.

Network analysis of dynamically important residues in protein structures mediating ligand-binding conformational changes

According to the generalized conformational selection model, ligand binding involves the co-existence of at least two conformers with different ligand-affinities in a dynamical equilibrium. Conformational transitions between them should be guaranteed by intramolecular vibrational dynamics associated to each conformation. These motions are, therefore, related to the biological function of a protein. Positions whose mutations are found to alter these vibrations the most can be defined as key positions, that is, dynamically important residues that mediate the ligand-binding conformational change. In a previous study, we have shown that these positions are evolutionarily conserved. They correspond to buried aliphatic residues mostly localized in regular structured regions of the protein like β-sheets and α-helices. In the present paper, we perform a network analysis of these key positions for a large dataset of paired protein structures in the ligand-free and ligand-bound form. We observe that networks of interactions between these key positions present larger and more integrated networks with faster transmission of the information. Besides, networks of residues result that are robust to conformational changes. Our results reveal that the conformational diversity of proteins seems to be guaranteed by a network of strongly interconnected key positions rather than individual residues.

Recent Advances in Droplet-based Microfluidic Technologies for Biochemistry and Molecular Biology

Recently, droplet-based microfluidic systems have been widely used in various biochemical and molecular biological assays. Since this platform technique allows manipulation of large amounts of data and also provides absolute accuracy in comparison to conventional bioanalytical approaches, over the last decade a range of basic biochemical and molecular biological operations have been transferred to drop-based microfluidic formats. In this review, we introduce recent advances and examples of droplet-based microfluidic techniques that have been applied in biochemistry and molecular biology research including genomics, proteomics and cellomics. Their advantages and weaknesses in various applications are also comprehensively discussed here. The purpose of this review is to provide a new point of view and current status in droplet-based microfluidics to biochemists and molecular biologists. We hope that this review will accelerate communications between researchers who are working in droplet-based microfluidics, biochemistry and molecular biology.

Distant Non-Obvious Mutations Influence the Activity of a Hyperthermophilic Pyrococcus furiosus Phosphoglucose Isomerase

The cupin-type phosphoglucose isomerase (PfPGI) from the hyperthermophilic archaeon Pyrococcus furiosus catalyzes the reversible isomerization of glucose-6-phosphate to fructose-6-phosphate. We investigated PfPGI using protein-engineering bioinformatics tools to select functionally-important residues based on correlated mutation analyses. A pair of amino acids in the periphery of PfPGI was found to be the dominant co-evolving mutation. The position of these selected residues was found to be non-obvious to conventional protein engineering methods. We designed a small smart library of variants by substituting the co-evolved pair and screened their biochemical activity, which revealed their functional relevance. Four mutants were further selected from the library for purification, measurement of their specific activity, crystal structure determination, and metal cofactor coordination analysis. Though the mutant structures and metal cofactor coordination were strikingly similar, variations in their activity correlated with their fine-tuned dynamics and solvent access regulation. Alternative, small smart libraries for enzyme optimization are suggested by our approach, which is able to identify non-obvious yet beneficial mutations.

Activity Improvement and Vital Amino Acid Identification on the Marine-Derived Quorum Quenching Enzyme MomL by Protein Engineering

MomL is a marine-derived quorum-quenching (QQ) lactonase which can degrade various N-acyl homoserine lactones (AHLs). Intentional modification of MomL may lead to a highly efficient QQ enzyme with broad application potential. In this study, we used a rapid and efficient method combining error-prone polymerase chain reaction (epPCR), high-throughput screening and site-directed mutagenesis to identify highly active MomL mutants. In this way, we obtained two candidate mutants, MomL_I144V and MomL_V149A. These two mutants exhibited enhanced activities and blocked the production of pathogenic factors of Pectobacterium carotovorum subsp. carotovorum (Pcc). Besides, seven amino acids which are vital for MomL enzyme activity were identified. Substitutions of these amino acids (E238G/K205E/L254R) in MomL led to almost complete loss of its QQ activity. We then tested the effect of MomL and its mutants on Pcc-infected Chinese cabbage. The results indicated that MomL and its mutants (MomL_L254R, MomL_I144V, MomL_V149A) significantly decreased the pathogenicity of Pcc. This study provides an efficient method for QQ enzyme modification and gives us new clues for further investigation on the catalytic mechanism of QQ lactonase.

Consensus sequence design as a general strategy to create hyperstable, biologically active proteins

Consensus sequence design offers a promising strategy for designing proteins of high stability while retaining biological activity since it draws upon an evolutionary history in which residues important for both stability and function are likely to be conserved. Although there have been several reports of successful consensus design of individual targets, it is unclear from these anecdotal studies how often this approach succeeds and how often it fails. Here, we attempt to assess generality by designing consensus sequences for a set of six protein families with a range of chain lengths, structures, and activities. We characterize the resulting consensus proteins for stability, structure, and biological activities in an unbiased way. We find that all six consensus proteins adopt cooperatively folded structures in solution. Strikingly, four of six of these consensus proteins show increased thermodynamic stability over naturally occurring homologs. Each consensus protein tested for function maintained at least partial biological activity. Although peptide binding affinity by a consensus-designed SH3 is rather low, K _m values for consensus enzymes are similar to values from extant homologs. Although consensus enzymes are slower than extant homologs at low temperature, they are faster than some thermophilic enzymes at high temperature. An analysis of sequence properties shows consensus proteins to be enriched in charged residues, and rarified in uncharged polar residues. Sequence differences between consensus and extant homologs are predominantly located at weakly conserved surface residues, highlighting the importance of these residues in the success of the consensus strategy.

Assessing Interactions between Helical Aromatic Oligoamide Foldamers and Protein Surfaces: A Tethering Approach

Helically folded aromatic foldamers may constitute suitable candidates for the ab initio design of ligands for protein surfaces. As preliminary steps toward the exploration of this hypothesis, a tethering approach was developed to detect interactions between a protein and a foldamer by confining the former at the surface of the latter. Cysteine mutants of two therapeutically relevant enzymes, CypA and IL4, were produced. Two series of ten foldamers were synthesized bearing different proteinogenic side chains and either a long or a short linker functionalized with an activated disulfide. Disulfide exchange between the mutated cysteines and the activated disulfides yielded 20 foldamer-IL4 and 20 foldamer-CypA adducts. Effectiveness of the reaction was demonstrated by LC-MS, by MS analysis after proteolytic digestion, and by 2D NMR. Circular dichroism then revealed diastereoselective interactions between the proteins and the foldamers confined at their surface which resulted in a preferred handedness of the foldamer helix. Helix sense bias occurred sometimes with both the short and the long linkers and sometimes with only one of them. In a few cases, helix handedness preference is found to be close to quantitative. These cases constitute valid candidates for structural elucidation of the interactions involved.

Biochemical characterization of three new α-olefin-producing P450 fatty acid decarboxylases with a halophilic property

BACKGROUND

The CYP152 family member OleT_JE from Jeotgalicoccus sp. ATCC 8456 has been well-known to catalyze the unusual one-step decarboxylation of free fatty acids towards the formation of terminal alkenes. Efforts to tune up its decarboxylation activity for better production of biological alkenes have been extensively explored via approaches such as site-directed mutagenesis and electron source engineering, but with limited success. To gain more insights into the decarboxylation mechanism and reaction bifurcation (decarboxylation versus hydroxylation), we turned to an alternative approach to explore the natural CYP152 resources for a better variety of enzyme candidates.

RESULTS

We biochemically characterized three new P450 fatty acid decarboxylases including OleT_JH, OleT_SQ and OleT_SA, with respect to their substrate specificity, steady-state kinetics, and salt effects. These enzymes all act as an OleT_JE-like fatty acid decarboxylase being able to decarboxylate a range of straight-chain saturated fatty acids (C₈-C₂₀) to various degrees. Site-directed mutagenesis analysis to the lower activity P450 enzyme OleT_SA revealed a number of key amino acid residues within the substrate-binding pocket (T47F, I177L, V319A and L405I) that are important for delicate substrate positioning of different chain-length fatty acids and thus the decarboxylation versus hydroxylation chemoselectivity, in particular for the mid-chain fatty acids (C₈-C₁₂). In addition, the three new decarboxylases exhibited optimal catalytic activity and stability at a salt concentration of 0.5 M, and were thus classified as moderate halophilic enzymes.

CONCLUSION

The P450 fatty acid decarboxylases OleT_JE, OleT_JH, OleT_SQ and OleT_SA belong to a novel group of moderate halophilic P450 enzymes. OleT_JH from Jeotgalicoccus halophilus shows the decarboxylation activity, kinetic parameters, as well as salt tolerance and stability that are comparable to OleT_JE. Site-directed mutagenesis of several key amino acid residues near substrate-binding pocket provides important guidance for further engineering of these P450 fatty acid decarboxylases that hold promising application potential for production of α-olefin biohydrocarbons.

Extensive libraries of gene truncation variants generated by in vitro transposition

The detailed analysis of the impact of deletions on proteins or nucleic acids can reveal important functional regions and lead to variants with improved macromolecular properties. We present a method to generate large libraries of mutants with deletions of varying length that are randomly distributed throughout a given gene. This technique facilitates the identification of crucial sequence regions in nucleic acids or proteins. The approach utilizes in vitro transposition to generate 5΄ and 3΄ fragment sub-libraries of a given gene, which are then randomly recombined to yield a final library comprising both terminal and internal deletions. The method is easy to implement and can generate libraries in three to four days. We used this approach to produce a library of >9000 random deletion mutants of an artificial RNA ligase enzyme representing 32% of all possible deletions. The quality of the library was assessed by next-generation sequencing and detailed bioinformatics analysis. Finally, we subjected this library to in vitro selection and obtained fully functional variants with deletions of up to 18 amino acids of the parental enzyme that had been 95 amino acids in length.

Directed Evolution of Glycopeptides Using mRNA Display

Directed evolution is a useful method for the discovery of nucleic acids, peptides, or proteins that have desired binding abilities or functions. Because of the abundance and importance of glycosylation in nature, directed evolution of glycopeptides and glycoproteins is also highly desirable. However, common directed evolution platforms such as phage-, yeast-, or mammalian-cell display are limited for these applications by several factors. Glycan structure at each glycosylation site is not genetically encoded, and yeast and mammalian cells produce a heterogeneous mixture of glycoforms at each site on the protein. Although yeast, mammalian and Escherichia coli cells can be engineered to produce a homogenous glycoform at all glycosylation sites, there are just a few specific glycan structures that can readily be accessed in this manner. Recently, we reported a novel system for the directed evolution of glycopeptide libraries, which could in principle be decorated with any desired glycan. Our method combines in vitro peptide selection by mRNA display with unnatural amino acid incorporation and chemical attachment of synthetic oligosaccharides. Here, we provide an updated and optimized protocol for this method, which is designed to create glycopeptide mRNA display libraries containing ~1013 sequences and select them for target binding. The target described here is the HIV broadly neutralizing monoclonal antibody 2G12; 2G12 binds to cluster of high-mannose oligosaccharides on the HIV envelope glycoprotein gp120; and glycopeptides that mimic this epitope may be useful in HIV vaccine applications. This method is expected to be readily applicable for other types of glycans and targets of interest in glycobiology.

Selection platforms for directed evolution in synthetic biology

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code.

Flexible Proteins at the Origin of Life

Almost all modern proteins possess well-defined, relatively rigid scaffolds that provide structural preorganization for desired functions. Such scaffolds require the sufficient length of a polypeptide chain and extensive evolutionary optimization. How ancestral proteins attained functionality, even though they were most likely markedly smaller than their contemporary descendants, remains a major, unresolved question in the origin of life. On the basis of evidence from experiments and computer simulations, we argue that at least some of the earliest water-soluble and membrane proteins were markedly more flexible than their modern counterparts. As an example, we consider a small, evolved in vitro ligase, based on a novel architecture that may be the archetype of primordial enzymes. The protein does not contain a hydrophobic core or conventional elements of the secondary structure characteristic of modern water-soluble proteins, but instead is built of a flexible, catalytic loop supported by a small hydrophilic core containing zinc atoms. It appears that disorder in the polypeptide chain imparts robustness to mutations in the protein core. Simple ion channels, likely the earliest membrane protein assemblies, could also be quite flexible, but still retain their functionality, again in contrast to their modern descendants. This is demonstrated in the example of antiamoebin, which can serve as a useful model of small peptides forming ancestral ion channels. Common features of the earliest, functional protein architectures discussed here include not only their flexibility, but also a low level of evolutionary optimization and heterogeneity in amino acid composition and, possibly, the type of peptide bonds in the protein backbone.

Engineering High Affinity Protein-Protein Interactions Using a High-Throughput Microcapillary Array Platform

Affinity maturation of protein-protein interactions requires iterative rounds of protein library generation and high-throughput screening to identify variants that bind with increased affinity to a target of interest. We recently developed a multipurpose protein engineering platform, termed μSCALE (Microcapillary Single Cell Analysis and Laser Extraction). This technology enables high-throughput screening of libraries of millions of cell-expressing protein variants based on their binding properties or functional activity. Here, we demonstrate the first use of the μSCALE platform for affinity maturation of a protein-protein binding interaction. In this proof-of-concept study, we engineered an extracellular domain of the Axl receptor tyrosine kinase to bind tighter to its ligand Gas6. Within 2 weeks, two iterative rounds of library generation and screening resulted in engineered Axl variants with a 50-fold decrease in kinetic dissociation rate, highlighting the use of μSCALE as a new tool for directed evolution.

Extending enzyme molecular recognition with an expanded amino acid alphabet

Natural enzymes are constructed from the 20 proteogenic amino acids, which may then require posttranslational modification or the recruitment of coenzymes or metal ions to achieve catalytic function. Here, we demonstrate that expansion of the alphabet of amino acids can also enable the properties of enzymes to be extended. A chemical mutagenesis strategy allowed a wide range of noncanonical amino acids to be systematically incorporated throughout an active site to alter enzymic substrate specificity. Specifically, 13 different noncanonical side chains were incorporated at 12 different positions within the active site of N-acetylneuraminic acid lyase (NAL), and the resulting chemically modified enzymes were screened for activity with a range of aldehyde substrates. A modified enzyme containing a 2,3-dihydroxypropyl cysteine at position 190 was identified that had significantly increased activity for the aldol reaction of erythrose with pyruvate compared with the wild-type enzyme. Kinetic investigation of a saturation library of the canonical amino acids at the same position showed that this increased activity was not achievable with any of the 20 proteogenic amino acids. Structural and modeling studies revealed that the unique shape and functionality of the noncanonical side chain enabled the active site to be remodeled to enable more efficient stabilization of the transition state of the reaction. The ability to exploit an expanded amino acid alphabet can thus heighten the ambitions of protein engineers wishing to develop enzymes with new catalytic properties.

The Framework of Computational Protein Design

Computational protein design (CPD) has established itself as a leading field in basic and applied science with a strong coupling between the two. Proteins are computationally designed from the level of amino acids to the level of a functional protein complex. Design targets range from increased thermo- (or other) stability to specific requested reactions such as protein-protein binding, enzymatic reactions, or nanotechnology applications. The design scheme may encompass small regions of the proteins or the entire protein. In either case, the design may aim at the side-chains or at the full backbone conformation. Herein, the main framework for the process is outlined highlighting key elements in the CPD iterative cycle. These include the very definition of CPD, the diverse goals of CPD, components of the CPD protocol, methods for searching sequence and structure space, scoring functions, and augmenting the CPD with other optimization tools. Taken together, this chapter aims to introduce the framework of CPD.

Emerging Strategies for Developing Next-Generation Protein Therapeutics for Cancer Treatment

Protein-based therapeutics have been revolutionizing the oncology space since they first appeared in the clinic two decades ago. Unlike traditional small-molecule chemotherapeutics, protein biologics promote active targeting of cancer cells by binding to cell-surface receptors and other markers specifically associated with or overexpressed on tumors versus healthy tissue. While the first approved cancer biologics were monoclonal antibodies, the burgeoning field of protein engineering is spawning research on an expanded range of protein formats and modifications that allow tuning of properties such as target-binding affinity, serum half-life, stability, and immunogenicity. In this review we highlight some of these strategies and provide examples of modified and engineered proteins under development as preclinical and clinical-stage drug candidates for the treatment of cancer.