Influence of metabolic network structure and function on enzyme evolution

Background  

Most studies of molecular evolution are focused on individual genes and proteins. However, understanding the design principles and evolutionary properties of molecular networks requires a system-wide perspective. In the present work we connect molecular evolution on the gene level with system properties of a cellular metabolic network. In contrast to protein interaction networks, where several previous studies investigated the molecular evolution of proteins, metabolic networks have a relatively well-defined global function. The ability to consider fluxes in a metabolic network allows us to relate the functional role of each enzyme in a network to its rate of evolution.     

Crystal structure of yeast cytosine deaminase. Insights into enzyme mechanism and evolution

Yeast cytosine deaminase is an attractive candidate for anticancer gene therapy because it catalyzes the deamination of the prodrug 5-fluorocytosine to form 5-fluorouracil. We report here the crystal structure of the enzyme in complex with the inhibitor 2-hydroxypyrimidine at 1.6-A resolution. The protein forms a tightly packed dimer with an extensive interface of 1450 A2 per monomer. The inhibitor was converted into a hydrated adduct as a transition-state analog. The essential zinc ion is ligated by the 4-hydroxyl group of the inhibitor together with His62, Cys91, and Cys94 from the protein. The enzyme shares similar active-site architecture to cytidine deaminases and an unusually high structural homology to 5-aminoimidazole-4-carboxamide-ribonucleotide transformylase and thereby may define a new superfamily. The unique C-terminal tail is involved in substrate specificity and also functions as a gate controlling access to the active site. The complex structure reveals a closed conformation, suggesting that substrate binding seals the active-site entrance so that the catalytic groups are sequestered from solvent. A comparison of the crystal structures of the bacterial and fungal cytosine deaminases provides an elegant example of convergent evolution, where starting from unrelated ancestral proteins, the same metal-assisted deamination is achieved through opposite chiral intermediates within distinctly different active sites.     

Functional evolution of the yeast protein interaction network

Protein interactions are central to most biological processes. We investigated the dynamics of emergence of the protein interaction network of Saccharomyces cerevisiae by mapping origins of proteins on an evolutionary tree. We demonstrate that evolutionary periods are characterized by distinct connectivity levels of the emerging proteins. We found that the most-connected group of proteins dates to the eukaryotic radiation, and the more ancient group of pre-eukaryotic proteins is less connected. We show that functional classes have different average connectivity levels and that the time of emergence of these functional classes parallels the observed connectivity variation in evolution. We take these findings as evidence that the evolution of function might be the reason for the differences in connectivity throughout evolutionary time. We propose that the understanding of the mechanisms that generate the scale-free protein interaction network, and possibly other biological networks, requires consideration of protein function.     

Experimental evolution of the grain of metabolic specialization in yeast

Adaptation to any given environment may be accompanied by a cost in terms of reduced growth in the ancestral or some alternative environment. Ecologists explain the cost of adaptation through the concept of a trade‐off, by which gaining a new trait involves losing another trait. Two mechanisms have been invoked to explain the evolution of trade‐offs in ecological systems, mutational degradation, and functional interference. Mutational degradation occurs when a gene coding a specific trait is not under selection in the resident environment; therefore, it may be degraded through the accumulation of mutations that are neutral in the resident environment but deleterious in an alternative environment. Functional interference evolves if the gene or a set of genes have antagonistic effects in two or more ecologically different traits. Both mechanisms pertain to a situation where the selection and the alternative environments are ecologically different. To test this hypothesis, we conducted an experiment in which 12 experimental populations of wild yeast were each grown in a minimal medium supplemented with a single substrate. We chose 12 different carbon substrates that were metabolized through similar and different pathways in order to represent a wide range of ecological conditions. We found no evidence for trade‐offs between substrates on the same pathway. The indirect response of substrates on other pathways, however, was consistently negative, with little correlation between the direct and indirect responses. We conclude that the grain of specialization in this case is the metabolic pathway and that specialization appears to evolve through mutational degradation.     

基于酶约束的代谢网络模型研究进展及其应用

基因组尺度代谢网络模型已经成功地应用于指导代谢工程改造,但由于传统通量平衡分析法仅考虑化学计量学和反应方向约束,模拟得到的是理论最优结果,对一些现象如代谢溢流、底物层级利用等无法准确描述。近年来人们通过在代谢网络模型中引入新的蛋白量、热力学等约束发展了新的约束优化计算方法,可以更准确真实地模拟细胞在不同条件下的代谢行为。文中主要对近年来提出的多种酶约束模型进行评述,对酶约束引入的基本思路、酶约束的数学方程表示及优化目标设定、引入酶约束后对代谢通量计算结果的影响及酶约束模型在代谢工程菌种改造中的应用等进行了全面深入的介绍,并提出了已有各种方法存在的主要问题,展望了相关方法的未来发展方向。通过引入新的约束,代谢网络模型能够更精确模拟和预测细胞在环境和基因扰动下的代谢行为,为代谢工程菌种改造提供更准确可靠的指导。     

The evolution of enzyme specificity in the metabolic replicator model of prebiotic evolution

The chemical machinery of life must have been catalytic from the outset. Models of the chemical origins have attempted to explain the ecological mechanisms maintaining a minimum necessary diversity of prebiotic replicator enzymes, but little attention has been paid so far to the evolutionary initiation of that diversity. We propose a possible first step in this direction: based on our previous model of a surface-bound metabolic replicator system we try to explain how the adaptive specialization of enzymatic replicator populations might have led to more diverse and more efficient communities of cooperating replicators with two different enzyme activities. The key assumptions of the model are that mutations in the replicator population can lead towards a) both of the two different enzyme specificities in separate replicators: efficient "specialists" or b) a "generalist" replicator type with both enzyme specificities working at less efficiency, or c) a fast-replicating, non-enzymatic "parasite". We show that under realistic trade-off constraints on the phenotypic effects of these mutations the evolved replicator community will be usually composed of both types of specialists and of a limited abundance of parasites, provided that the replicators can slowly migrate on the mineral surface. It is only at very weak trade-offs that generalists take over in a phase-transition-like manner. The parasites do not seriously harm the system but can freely mutate, therefore they can be considered as pre-adaptations to later, useful functions that the metabolic system can adopt to increase its own fitness.     

Modularity in the evolution of yeast protein interaction network

Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution.     

Analysis of metabolic network based on conservation of molecular structure

Recent work has revealed much about chemical reactions inside hundreds of organisms as well as universal characteristics of metabolic networks, which shed light on the evolution of the networks. However, characteristics of individual metabolites have been neglected. For example, some carbohydrates have structures that are decomposed into small molecules by metabolic reactions, but coenzymes such as ATP are mostly preserved. Such differences in metabolite characteristics are important for understanding the universal characteristics of metabolic networks. To quantify the structure conservation of metabolites, we defined the "structure conservation index" (SCI) for each metabolite as the fraction of metabolite atoms restored to their original positions through metabolic reactions. As expected, coenzymes and coenzyme-like metabolites that have reaction loops in the network show a higher SCI. Using the index, we found that the sum of metabolic fluxes is negatively correlated with the structure preservation of metabolite. Also, we found that each reaction path around high SCI metabolites changes independently, while changes in reaction paths involving low SCI metabolites coincide through evolution processes. These correlations may provide a clue to universal properties of metabolic networks.     

Directed evolution to re-adapt a co-evolved network within an enzyme

We have previously used targeted active-site saturation mutagenesis to identify a number of transketolase single mutants that improved activity towards either glycolaldehyde (GA), or the non-natural substrate propionaldehyde (PA). Here, all attempts to recombine the singles into double mutants led to unexpected losses of specific activity towards both substrates. A typical trade-off occurred between soluble expression levels and specific activity for all single mutants, but many double mutants decreased both properties more severely suggesting a critical loss of protein stability or native folding. Statistical coupling analysis (SCA) of a large multiple sequence alignment revealed a network of nine co-evolved residues that affected all but one double mutant. Such networks maintain important functional properties such as activity, specificity, folding, stability, and solubility and may be rapidly disrupted by introducing one or more non-naturally occurring mutations. To identify variants of this network that would accept and improve upon our best D469 mutants for activity towards PA, we created a library of random single, double and triple mutants across seven of the co-evolved residues, combining our D469 variants with only naturally occurring mutations at the remaining sites. A triple mutant cluster at D469, E498 and R520 was found to behave synergistically for the specific activity towards PA. Protein expression was severely reduced by E498D and improved by R520Q, yet variants containing both mutations led to improved specific activity and enzyme expression, but with loss of solubility and the formation of inclusion bodies. D469S and R520Q combined synergistically to improve k_cat 20-fold for PA, more than for any previous transketolase mutant. R520Q also doubled the specific activity of the previously identified D469T to create our most active transketolase mutant to date. Our results show that recombining active-site mutants obtained by saturation mutagenesis can rapidly destabilise critical networks of co-evolved residues, whereas beneficial single mutants can be retained and improved upon by randomly recombining them with natural variants at other positions in the network.     

From network models to network responses: integration of thermodynamic and kinetic properties of yeast genome-scale metabolic networks

Many important problems in cell biology arise from the dense nonlinear interactions between functional modules. The importance of mathematical modelling and computer simulation in understanding cellular processes is now indisputable and widely appreciated. Genome-scale metabolic models have gained much popularity and utility in helping us to understand and test hypotheses about these complex networks. However, there are some caveats that come with the use and interpretation of different types of metabolic models, which we aim to highlight here. We discuss and illustrate how the integration of thermodynamic and kinetic properties of the yeast metabolic networks in network analyses can help in understanding and utilizing this organism more successfully in the areas of metabolic engineering, synthetic biology and disease treatment.     

Topological structure analysis of the protein-protein interaction network in budding yeast

Interaction detection methods have led to the discovery of thousands of interactions between proteins, and discerning relevance within large-scale data sets is important to present-day biology. Here, a spectral method derived from graph theory was introduced to uncover hidden topological structures (i.e. quasi-cliques and quasi-bipartites) of complicated protein-protein interaction networks. Our analyses suggest that these hidden topological structures consist of biologically relevant functional groups. This result motivates a new method to predict the function of uncharacterized proteins based on the classification of known proteins within topological structures. Using this spectral analysis method, 48 quasi-cliques and six quasi-bipartites were isolated from a network involving 11,855 interactions among 2617 proteins in budding yeast, and 76 uncharacterized proteins were assigned functions.     

Crystal structure of the yeast His6 enzyme suggests a reaction mechanism

The Saccharomyces cerevisiae His6 gene codes for the enzyme phosphoribosyl-5-amino-1-phosphoribosyl-4-imidazolecarboxamide isomerase, catalyzing the fourth step in histidine biosynthesis. To get an insight into the structure and function of this enzyme, we determined its X-ray structure at a resolution of 1.30 A using the anomalous diffraction signal of the protein's sulphur atoms at 1.77 A wavelength. His6 folds in an (alpha/beta)8 barrel similar to HisA, which performs the same function in bacteria and archaea. We found a citrate molecule from the buffer bound in a pocket near the expected position of the active site and used it to model the open form of the substrate (phosphoribulosyl moiety), which is a reaction intermediate. This model enables us to identify catalytic residues and to propose a reaction mechanism where two aspartates act as acid/base catalysts: Asp134 as a proton donor for ring opening, and Asp9 as a proton acceptor and donor during enolization of the aminoaldose. Asp9 is conserved in yeast His6 and bacterial or archaeal HisA sequences, and Asp134 has equivalents in both HisA and TrpF, but they occur at a different position in the protein sequence.     

Simultaneous optimization of enzyme activity and quaternary structure by directed evolution

Natural evolution has produced efficient enzymes of enormous structural diversity. We imitated this natural process in the laboratory to augment the efficiency of an engineered chorismate mutase with low activity and an unusual hexameric topology. By applying two rounds of DNA shuffling and genetic selection, we obtained a 400-fold more efficient enzyme, containing three non-active-site mutations. Detailed biophysical characterization of the evolved variant suggests that it exists predominantly as a trimer in solution, but is otherwise similarly stable as the parent hexamer. The dramatic structural and functional effects achieved by a small number of seemingly innocuous substitutions highlights the utility of directed evolution for modifying protein-protein interactions to produce novel quaternary states with optimized activities.     

Cooperative evolution in protein complexes of yeast from comparative analyses of its interaction network

A comparative analysis among Saccharomyces cerevisiae and the other four yeasts Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii, and Yarrowia lipolytica is presented. The broad evolutionary range spanned by the organisms allows to quantitatively demonstrate novel evolutionary effects in protein complexes. The evolution rates within cliques of interlinked proteins are found to bear strong multipoint correlations, witnessing a cooperative coevolution of complex subunits. The coevolution is found to be largely independent of the tendency of the subunits to have similar abundances.     

Location in the yeast hexokinase structure of residues related to the enzyme activity

Seven residues implicated as acting directly in substrate binding in yeast hexokinase B have been identified in the crystallographic structure by chemical sequencing. The cysteine which is regarded as a residue critically maintaining the active conformation of yeast hexokinase has been selectively labelled and likewise located in the structure. In some parts of the amino acid sequence predicted from the high-resolution electron density map it is found that alignments of chemically sequenced peptides can be made unambiguously; however, the extent of matching to the predicted sequence varies considerably along the chain.