Toward protein engineering for phytoremediation: possibilities and challenges

The combination of rational protein engineering and directed evolution techniques allow for the redesign of enzymes with tailored properties for use in environmental remediation. This review summarizes current molecular methods for either altering or improving protein function and highlights examples of how these methods can address bioremediation problems. Although much of the protein engineering applied to environmental clean-up employs microbial systems, there is great potential for and significant challenges to translating these approaches to plant systems for phytoremediation purposes. Protein engineering technologies combined with genomic information and metabolic engineering strategies hold promise for the design of plants and microbes to remediate organic and inorganic pollutants.     

药用植物分子农场研究进展

植物分子农场可以利用植物生产具有药物用途的重组蛋白或者次生代谢化合物,应用广泛。随着对动植物中具有药物用途的代谢途径的深入解析,代谢途径中关键限速酶或调控蛋白的功能不断被明确,如何选择植物分子农场的底盘植物和遗传改造途径等问题,特别是如何协同提高植物制药产量与品质一直是植物分子农场体系建立中面临的关键科学问题。综述了药用的植物分子农场的最新研究进展,着重介绍了底盘植物的选择与药用植物分子农场的构建策略,以期为提高分子农场应用效果提供有力的科技支撑。     

New algorithms and an in silico benchmark for computational enzyme design

The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.     

Structure-driven protein engineering for production of valuable natural products

Proteins are the most frequently used biocatalysts, and their structures determine their functions. Modifying the functions of proteins on the basis of their structures lies at the heart of protein engineering, opening a new horizon for metabolic engineering by efficiently generating stable enzymes. Many attempts at classical metabolic engineering have focused on improving specific metabolic fluxes and producing more valuable natural products by increasing gene expression levels and enzyme concentrations. However, most naturally occurring enzymes show limitations, and such limitations have hindered practical applications. Here we review recent advances in protein engineering in synthetic biology, chemoenzymatic synthesis, and plant metabolic engineering and describe opportunities for designing and constructing novel enzymes or proteins with desirable properties to obtain more active natural products.     

Computational protein design: engineering molecular diversity, nonnatural enzymes, nonbiological cofactor complexes, and membrane proteins

Computational and theoretical methods are advancing protein design as a means to create and investigate proteins. Such efforts further our capacity to control, design and understand biomolecular structure, sequence and function. Herein, the focus is on some recent applications that involve using theoretical and computational methods to guide the design of protein sequence ensembles, new enzymes, proteins with novel cofactors, and membrane proteins.     

Directed evolution of (betaalpha)(8)-barrel enzymes

Natural molecular evolution supplies us with manifold examples of protein engineering. The imitation of these natural processes in the design of new enzymes has led to surprising and insightful results. Well-suited for design by evolutionary methods are enzymes with the common and versatile (betaalpha)(8)-barrel fold. Studies of enzyme stability, folding and design as well as the evolution of (betaalpha)(8)-barrel enzymes are discussed.     

Redesigning metabolic networks using mathematical programming

The design of new generation bioprocessing plants is increasingly dependent on the design of process-compatible microorganisms. The latter, whether through genetic or physiological manipulations, can be greatly assisted by metabolic engineering. An emerging powerful tool in metabolic engineering research is computer-assisted cell design using mathematical programming. In this work, the problem of optimizing cellular metabolic networks has been formulated as a Mixed Integer Nonlinear Programming (MINLP) model. The model can assist genetic engineers to identify which cellular enzymes should be modified, and the new levels of activity required to produce an optimal network. Results are presented from the tricarboxylic acid cycle in Dictyostelium discoideum. Copyright 1998 John Wiley & Sons, Inc.     

Using genome-context data to identify specific types of functional associations in pathway/genome databases

BACKGROUND: Hundreds of genes lacking homology to any protein of known function are sequenced every day. Genome-context methods have proved useful in providing clues about functional annotations for many proteins. However, genome-context methods detect many biological types of functional associations, and do not identify which type of functional association they have found. RESULTS: We have developed two new genome-context-based algorithms. Algorithm 1 extends our previous algorithm for identifying missing enzymes in predicted metabolic pathways (pathway holes) to use genome-context features. The new algorithm has significantly improved scope because it can now be applied to pathway reactions to which sequence similarity methods cannot be applied due to an absence of known sequences for enzymes catalyzing the reaction in other organisms. The new method identifies at least one known enzyme in the top ten hits for 58% of EcoCyc reactions that lack enzyme sequences in other organisms. Surprisingly, the addition of genome-context features does not improve the accuracy of the algorithm when sequences for the enzyme do exist in other organisms. Algorithm 2 uses genome-context methods to predict three distinct types of functional relationships between pairs of proteins: pairs that occur in the same protein complex, the same pathway, or the same operon. This algorithm performs with varying degrees of accuracy on each type of relationship, and performs best in predicting pathway and protein complex relationships.     

Methods for discovery and characterization of cellulolytic enzymes from insects

Abstract Cellulosic ethanol has been identified as a crucial biofuel resource due to its sustainability and abundance of cellulose feedstocks. However, current methods to obtain glucose from lignocellulosic biomass are ineffective due to recalcitrance of plant biomass. Insects have evolved endogenous and symbiotic enzymes to efficiently use lignocellulosic material as a source of metabolic glucose. Even though traditional biochemical methods have been used to identify and characterize these enzymes, the advancement of genomic and proteomic research tools are expected to allow new insights into insect digestion of cellulose. This information is highly relevant to the design of improved industrial processes of biofuel production and to identify potential new targets for development of insecticides. This review describes the diverse methodologies used to detect, quantify, purify, clone and express cellulolytic enzymes from insects, as well as their advantages and limitations.     

In vitro prototyping of limonene biosynthesis using cell-free protein synthesis

Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. We anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.     

Discovery of novel pathways for carbohydrate metabolism

Closing the gap between the increasing availability of complete genome sequences and the discovery of novel enzymes in novel metabolic pathways is a significant challenge. Here, we review recent examples of assignment of in vitro enzymatic activities and in vivo metabolic functions to uncharacterized proteins, with a focus on enzymes and metabolic pathways involved in the catabolism and biosynthesis of monosaccharides and polysaccharides. The most effective approaches are based on analyses of sequence-function space in protein families that provide clues for the predictions of the functions of the uncharacterized enzymes. As summarized in this Opinion, this approach allows the discovery of the catabolism of new molecules, new pathways for common molecules, and new enzymatic chemistries.     

From molecular engineering to process engineering: development of high-throughput screening methods in enzyme directed evolution

With increasing concerns in sustainable development, biocatalysis has been recognized as a competitive alternative to traditional chemical routes in the past decades. As nature’s biocatalysts, enzymes are able to catalyze a broad range of chemical transformations, not only with mild reaction conditions but also with high activity and selectivity. However, the insufficient activity or enantioselectivity of natural enzymes toward non-natural substrates limits their industrial application, while directed evolution provides a potent solution to this problem, thanks to its independence on detailed knowledge about the relationship between sequence, structure, and mechanism/function of the enzymes. A proper high-throughput screening (HTS) method is the key to successful and efficient directed evolution. In recent years, huge varieties of HTS methods have been developed for rapid evaluation of mutant libraries, ranging from in vitro screening to in vivo selection, from indicator addition to multi-enzyme system construction, and from plate screening to computation- or machine-assisted screening. Recently, there is a tendency to integrate directed evolution with metabolic engineering in biosynthesis, using metabolites as HTS indicators, which implies that directed evolution has transformed from molecular engineering to process engineering. This paper aims to provide an overview of HTS methods categorized based on the reaction principles or types by summarizing related studies published in recent years including the work from our group, to discuss assay design strategies and typical examples of HTS methods, and to share our understanding on HTS method development for directed evolution of enzymes involved in specific catalytic reactions or metabolic pathways.

     

Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours

Despite the current wealth of sequencing data, one‐third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome‐scale metabolic models with these new sequence–function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction.     

基于图论和约束优化的异源代谢途径设计方法及应用

构建高产高附加值产品的微生物细胞工厂是代谢工程的研究目标之一,设计高效的产品合成途径是实现这一目标的重要方式.不同微生物底盘因其代谢能力有所差异,故而可以利用的底物和生产的产品范围有限.为了扩大其生产能力,需要进行代谢途径从无到有的设计.传统代谢工程基于经验进行异源途径设计的方式低效且无法确保结果的全面性,而系统生物学...     

Directed evolution strategies for improved enzymatic performance

The engineering of enzymes with altered activity, specificity and stability, using directed evolution techniques that mimic evolution on a laboratory timescale, is now well established. However, the general acceptance of these methods as a route to new biocatalysts for organic synthesis requires further improvement of the methods for both ease-of-use and also for obtaining more significant changes in enzyme properties than is currently possible. Recent advances in library design, and methods of random mutagenesis, combined with new screening and selection tools, continue to push forward the potential of directed evolution. For example, protein engineers are now beginning to apply the vast body of knowledge and understanding of protein structure and function, to the design of focussed directed evolution libraries, with striking results compared to the previously favoured random mutagenesis and recombination of entire genes. Significant progress in computational design techniques which mimic the experimental process of library screening is also now enabling searches of much greater regions of sequence-space for those catalytic reactions that are broadly understood and, therefore, possible to model.     

酶分子设计常用策略和进展

酶分子的生物学功能很大程度上是由其三维空间结构和所处溶剂环境共同决定的。因此,优化酶分子的结构性质以及探索其性质最优的溶剂环境是改善酶分子功能以及进行理性设计的一个可行途径。从实际应用的角度来看,分子设计方法可以为酶工程提供一种有效的解决方案。目前,酶分子设计有两个重要的研究方向,包括提高酶分子的催化活力和优化其稳定性。同时,对酶分子设计方法的研究也有助于对蛋白质生物学机理的探索。在近些年的学术界酶分子设计案例中,生物信息学方法得到广泛的应用。本文系统地总结基于生物信息学的酶分子设计方法的背景、策略和一些经典案例。