A Tale of Two Isomerases: Compact versus Extended Active Sites in Ketosteroid Isomerase and Phosphoglucose Isomerase

Dynamic interchange between two protonation states is characteristic of active sites of cholinesterases

Cholinesterases are well-known and widely studied enzymes crucial to human health and involved in neurology, Alzheimer's, and lipid metabolism. The protonation pattern of active sites of cholinesterases influences all the chemical processes within, including reaction, covalent inhibition by nerve agents, and reactivation. Despite its significance, our comprehension of the fine structure of cholinesterases remains limited. In this study, we employed enhanced-sampling quantum-mechanical/molecular-mechanical calculations to show that cholinesterases predominantly operate as dynamic mixtures of two protonation states. The proton transfer between two non-catalytic glutamate residues follows the Grotthuss mechanism facilitated by a mediator water molecule. We show that this uncovered complexity of active sites presents a challenge for classical molecular dynamics simulations and calls for special treatment. The calculated proton transfer barrier of 1.65 kcal/mol initiates a discussion on the potential existence of two coupled low-barrier hydrogen bonds in the inhibited form of butyrylcholinesterase. These findings expand our understanding of structural features expressed by highly evolved enzymes and guide future advances in cholinesterase-related protein and drug design studies.

Revisiting the Roles of Catalytic Residues in Human Ornithine Transcarbamylase

Human ornithine transcarbamylase (hOTC) is a mitochondrial transferase protein involved in the urea cycle and is crucial for the conversion of toxic ammonia to urea. Structural analysis coupled with kinetic studies of Escherichia coli, rat, bovine, and other transferase proteins has identified residues that play key roles in substrate recognition and conformational changes but has not provided direct evidence for all of the active residues involved in OTC function. Here, computational methods were used to predict the likely active residues of hOTC; the function of these residues was then probed with site-directed mutagenesis and biochemical characterization. This process identified previously reported active residues, as well as distal residues that contribute to activity. Mutation of active site residue D263 resulted in a substantial loss of activity without a decrease in protein stability, suggesting a key catalytic role for this residue. Mutation of predicted second-layer residues H302, K307, and E310 resulted in significant decreases in enzymatic activity relative to that of wild-type (WT) hOTC with respect to l-ornithine. The mutation of fourth-layer residue H107 to produce the hOTC H107N variant resulted in a 66-fold decrease in catalytic efficiency relative to that of WT hOTC with respect to carbamoyl phosphate and a substantial loss of thermal stability. Further investigation identified H107 and to a lesser extent E98Q as key residues involved in maintaining the hOTC quaternary structure. This work biochemically demonstrates the importance of D263 in hOTC catalytic activity and shows that residues remote from the active site also play key roles in activity.

MAHOMES II: A webserver for predicting if a metal binding site is enzymatic

Recent advances have enabled high-quality computationally generated structures for proteins with no solved crystal structures. However, protein function data remains largely limited to experimental methods and homology mapping. Since structure determines function, it is natural that methods capable of using computationally generated structures for functional annotations need to be advanced. Our laboratory recently developed a method to distinguish between metalloenzyme and nonenzyme sites. Here we report improvements to this method by upgrading our physicochemical features to alleviate the need for structures with sub-angstrom precision and using machine learning to reduce training data labeling error. Our improved classifier identifies protein bound metal sites as enzymatic or nonenzymatic with 94% precision and 92% recall. We demonstrate that both adjustments increased predictive performance and reliability on sites with sub-angstrom variations. We constructed a set of predicted metalloprotein structures with no solved crystal structures and no detectable homology to our training data. Our model had an accuracy of 90%-97.5% depending on the quality of the predicted structures included in our test. Finally, we found the physicochemical trends that drove this model's successful performance were local protein density, second shell ionizable residue burial, and the pocket's accessibility to the site. We anticipate that our model's ability to correctly identify catalytic metal sites could enable identification of new enzymatic mechanisms and improve de novo metalloenzyme design success rates.

MAHOMES II: A webserver for predicting if a metal binding site is enzymatic

Recent advances have enabled high-quality computationally generated structures for proteins with no solved crystal structures. However, protein function data remains largely limited to experimental methods and homology mapping. Since structure determines function, it is natural that methods capable of using computationally generated structures for functional annotations need to be advanced. Our laboratory recently developed a method to distinguish between metalloenzyme and non-enzyme sites. Here we report improvements to this method by upgrading our physicochemical features to alleviate the need for structures with sub-angstrom precision and using machine learning to reduce training data labeling error. Our improved classifier identifies protein bound metal sites as enzymatic or non-enzymatic with 94% precision and 92% recall. We demonstrate that both adjustments increased predictive performance and reliability on sites with sub-angstrom variations. We constructed a set of predicted metalloprotein structures with no solved crystal structures and no detectable homology to our training data. Our model had an accuracy of 90 - 97.5% depending on the quality of the predicted structures included in our test. Finally, we found the physicochemical trends that drove this model's successful performance were local protein density, second shell ionizable residue burial, and the pocket's accessibility to the site. We anticipate that our model's ability to correctly identify catalytic metal sites could enable identification of new enzymatic mechanisms and improve de novo metalloenzyme design success rates.

Significance statement

Identification of enzyme active sites on proteins with unsolved crystallographic structures can accelerate discovery of novel biochemical reactions, which can impact healthcare, industrial processes, and environmental remediation. Our lab has developed an ML tool for predicting sites on computationally generated protein structures as enzymatic and non-enzymatic. We have made our tool available on a webserver, allowing the scientific community to rapidly search previously unknown protein function space.

Phosphoglucose Isomerase Is Important for Aspergillus fumigatus Cell Wall Biogenesis

Aspergillus fumigatus is a devastating opportunistic fungal pathogen causing hundreds of thousands of deaths every year. Phosphoglucose isomerase (PGI) is a glycolytic enzyme that converts glucose-6-phosphate to fructose-6-phosphate, a key precursor of fungal cell wall biosynthesis. Here, we demonstrate that the growth of A. fumigatus is repressed by the deletion of pgi, which can be rescued by glucose and fructose supplementation in a 1:10 ratio. Even under these optimized growth conditions, the Δpgi mutant exhibits severe cell wall defects, retarded development, and attenuated virulence in Caenorhabditis elegans and Galleria mellonella infection models. To facilitate exploitation of A. fumigatus PGI as an antifungal target, we determined its crystal structure, revealing potential avenues for developing inhibitors, which could potentially be used as adjunctive therapy in combination with other systemic antifungals. IMPORTANCE Aspergillus fumigatus is an opportunistic fungal pathogen causing deadly infections in immunocompromised patients. Enzymes essential for fungal survival and cell wall biosynthesis are considered potential drug targets against A. fumigatus. PGI catalyzes the second step of the glycolysis pathway, linking glycolysis and the pentose phosphate pathway. As such, PGI has been widely considered as a target for metabolic regulation and therefore a therapeutic target against hypoxia-related diseases. Our study here reveals that PGI is important for A. fumigatus survival and exhibit pleiotropic functions, including development, cell wall glucan biosynthesis, and virulence. We also solved the crystal structure of PGI, thus providing the genetic and structural groundwork for the exploitation of PGI as a potential antifungal target.

Electrostatic fingerprints of catalytically active amino acids in enzymes

The computed electrostatic and proton transfer properties are studied for 20 enzymes that represent all six major enzyme commission classes and a variety of different folds. The properties of aspartate, glutamate, and lysine residues that have been previously experimentally determined to be catalytically active are reported. The catalytic aspartate and glutamate residues studied here are strongly coupled to at least one other aspartate or glutamate residue and often to multiple other carboxylate residues with intrinsic pK_a differences less than 1 pH unit. Sometimes these catalytic acidic residues are also coupled to a histidine residue, such that the intrinsic pK_a of the acidic residue is higher than that of the histidine. All catalytic lysine residues studied here are strongly coupled to tyrosine or cysteine residues, wherein the intrinsic pK_a of the anion-forming residue is higher than that of the lysine. Some catalytic lysines are also coupled to other lysines with intrinsic pK_a differences within 1 pH unit. Some evidence of the possible types of interactions that facilitate nucleophilicity is discussed. The interactions reported here provide important clues about how side chain functional groups that are weak Brønsted acids or bases for the free amino acid in solution can achieve catalytic potency and become strong acids, bases or nucleophiles in the enzymatic environment.

pH Effects and Cooperativity among Key Titratable Residues for Escherichia coli Glycinamide Ribonucleotide Transformylase

Human glycinamide ribonucleotide transformylase (GAR Tfase) is a regulatory enzyme in the de novo purine biosynthesis pathway that has been extensively studied as an anticancer target. To some extent, inhibition of GAR Tfase selectively targets cancer cells over normal cells and inhibits purine formation and DNA replication. In this study, we investigated E. coli GAR Tfase, which shares high sequence similarity with the human GAR Tfase, and most functional residues are conserved. Herein, we aim to predict the pH-activity curve through a computational approach. We carried out pH-replica exchange molecular dynamics (pH-REMD) simulations to investigate pH-dependent functions such as structural changes, ligand binding, and catalytic activity. To compute the pH-activity curve, we identified the catalytic residues in specific protonation states, referred to as the catalytic competent protonation states (CCPS), which maintain the structure, keep ligands bound, and facilitate catalysis. Our computed population of CCPS with respect to pH matches well with the experimental pH-activity curve. To compute the microscopic pK_a values in the catalytically active conformation, we devised a thermodynamic model that considers the coupling between protonation states of CCPS residues and conformational states. These results allow us to correctly identify the general acid and base catalysts and interpret the pH-activity curve at an atomistic level.

Amino acid interactions that facilitate enzyme catalysis

Interactions in enzymes between catalytic and neighboring amino acids and how these interactions facilitate catalysis are examined. In examples from both natural and designed enzymes, it is shown that increases in catalytic rates may be achieved through elongation of the buffer range of the catalytic residues; such perturbations in the protonation equilibria are, in turn, achieved through enhanced coupling of the protonation equilibria of the active ionizable residues with those of other ionizable residues. The strongest coupling between protonation states for a pair of residues that deprotonate to form an anion (or a pair that accept a proton to form a cation) is achieved when the difference in the intrinsic pK_as of the two residues is approximately within 1 pH unit. Thus, catalytic aspartates and glutamates are often coupled to nearby acidic residues. For an anion-forming residue coupled to a cation-forming residue, the elongated buffer range is achieved when the intrinsic pK_a of the anion-forming residue is higher than the intrinsic pK_a of the (conjugate acid of the) cation-forming residue. Therefore, the high pK_a, anion-forming residues tyrosine and cysteine make good coupling partners for catalytic lysine residues. For the anion-cation pairs, the optimum difference in intrinsic pK_as is a function of the energy of interaction between the residues. For the energy of interaction ε expressed in units of (ln 10)RT, the optimum difference in intrinsic pK_as is within ∼1 pH unit of ε.

Analysis of electrostatic coupling throughout the laboratory evolution of a designed retroaldolase

The roles of local interactions in the laboratory evolution of a highly active, computationally designed retroaldolase (RA) are examined. Partial Order Optimum Likelihood (POOL) is used to identify catalytically important amino acid interactions in several RA95 enzyme variants. The series RA95.5, RA95.5–5, RA95.5–8, and RA95.5–8F, representing progress along an evolutionary trajectory with increasing activity, is examined. Computed measures of coupling between charged states of residues show that, as evolution proceeds and higher activities are achieved, electrostatic coupling between the biochemically active amino acids and other residues is increased. In silico residue scanning suggests multiple coupling partners for the catalytic lysine K83. The effects of two predicted partners, Y51 and E85, are tested using site‐directed mutagenesis and kinetic analysis of the variants Y51F and E85Q. The Y51F variants show decreases in k_cat relative to wild type, with the greatest losses observed for the more evolved constructs; they also exhibit significant decreases in k_cat/K_M across the series. Only modest decreases in k_cat/K_M are observed for the E85Q variants with little effect on k_cat. Computed metrics of the degree of coupling between protonation states rise significantly as evolution proceeds and catalytic turnover rate increases. Specifically, the charge state of the catalytic lysine K83 becomes more strongly coupled to those of other amino acids as the enzyme evolves to a better catalyst.

Burkholderia ubonensis High-Level Tetracycline Resistance Is Due to Efflux Pump Synergy Involving a Novel TetA(64) Resistance Determinant

Burkholderia ubonensis, a nonpathogenic soil bacterium belonging to the Burkholderia cepacia complex (Bcc), is highly resistant to some clinically significant antibiotics. The concern is that B. ubonensis may serve as a resistance reservoir for Bcc or B. pseudomallei complex (Bpc) organisms that are opportunistic human pathogens. Using a B. ubonensis strain highly resistant to tetracycline (MIC, ≥256 µg/ml), we identified and characterized tetA(64) that encodes a novel tetracycline-specific efflux pump of the major facilitator superfamily. TetA(64) and associated TetR(64) regulator expression are induced by tetracyclines. Although TetA(64) is the primary tetracycline and doxycycline resistance determinant, maximum tetracycline and doxycycline resistance requires synergy between TetA(64) and the nonspecific AmrAB-OprA resistance nodulation cell division efflux pump. TetA(64) does not efflux minocycline, tigecycline, and eravacycline. Comprehensive screening of genome sequences showed that TetA(64) is unequally distributed in the Bcc and absent from the Bpc. It is present in some major cystic fibrosis pathogens, like Burkholderia cenocepacia, but absent from others like Burkholderia multivorans The tetR(64)-tetA(64) genes are located in a region of chromosome 1 that is highly conserved in Burkholderia sp. Because there is no evidence for transposition, the tetR(64)-tetA(64) genes may have been acquired by homologous recombination after horizontal gene transfer. Although Burkholderia species contain a resident multicomponent efflux pump that allows them to respond to tetracyclines up to a certain concentration, the acquisition of the single-component TetA(64) by some species likely provides the synergy that these bacteria need to defend against high tetracycline concentrations in niche environments.

Probing remote residues important for catalysis in Escherichia coli ornithine transcarbamoylase

Understanding how enzymes achieve their tremendous catalytic power is a major question in biochemistry. Greater understanding is also needed for enzyme engineering applications. In many cases, enzyme efficiency and specificity depend on residues not in direct contact with the substrate, termed remote residues. This work focuses on Escherichia coli ornithine transcarbamoylase (OTC), which plays a central role in amino acid metabolism. OTC has been reported to undergo an induced-fit conformational change upon binding its first substrate, carbamoyl phosphate (CP), and several residues important for activity have been identified. Using computational methods based on the computed chemical properties from theoretical titration curves, sequence-based scores derived from evolutionary history, and protein surface topology, residues important for catalytic activity were predicted. The roles of these residues in OTC activity were tested by constructing mutations at predicted positions, followed by steady-state kinetics assays and substrate binding studies with the variants. First-layer mutations R57A and D231A, second-layer mutation H272L, and third-layer mutation E299Q, result in 57- to 450-fold reductions in k_cat/K_M with respect to CP and 44- to 580-fold reductions with respect to ornithine. Second-layer mutations D140N and Y160S also reduce activity with respect to ornithine. Most variants had decreased stability relative to wild-type OTC, with variants H272L, H272N, and E299Q having the greatest decreases. Variants H272L, E299Q, and R57A also show compromised CP binding. In addition to direct effects on catalytic activity, effects on overall protein stability and substrate binding were observed that reveal the intricacies of how these residues contribute to catalysis.

Energy Metabolism in Cancer: The Roles of STAT3 and STAT5 in the Regulation of Metabolism-Related Genes

A central characteristic of many types of cancer is altered energy metabolism processes such as enhanced glucose uptake and glycolysis and decreased oxidative metabolism. The regulation of energy metabolism is an elaborate process involving regulatory proteins such as HIF (pro-metastatic protein), which reduces oxidative metabolism, and some other proteins such as tumour suppressors that promote oxidative phosphorylation. In recent years, it has been demonstrated that signal transducer and activator of transcription (STAT) proteins play a pivotal role in metabolism regulation. STAT3 and STAT5 are essential regulators of cytokine- or growth factor-induced cell survival and proliferation, as well as the crosstalk between STAT signalling and oxidative metabolism. Several reports suggest that the constitutive activation of STAT proteins promotes glycolysis through the transcriptional activation of hypoxia-inducible factors and therefore, the alteration of mitochondrial activity. It seems that STAT proteins function as an integrative centre for different growth and survival signals for energy and respiratory metabolism. This review summarises the functions of STAT3 and STAT5 in the regulation of some metabolism-related genes and the importance of oxygen in the tumour microenvironment to regulate cell metabolism, particularly in the metabolic pathways that are involved in energy production in cancer cells.

Evaluating the catalytic importance of a conserved Glu97 residue in triosephosphate isomerase

Investigating enzyme activity is central to our understanding of biological function, and the design of biocatalysts continues to find applications in synthesis. While a role for active site residues can be proposed based on structure and mechanism, our understanding of the catalytic importance for residues surrounding the active site is less well understood. In triosephosphate isomerase (TIM), Glu97 is situated adjacent to the active site and is found in essentially all sequences. Prior studies reported mutation of Glu97 to Asp and Gln in TIM from Plasmodium falciparum (PfTIM) led to a 100- and 4000-fold decrease in activity, respectively, while the E97D mutation in TIM from Gallus gallus (cTIM) had no effect on activity. To investigate further the question of how mutations in essentially superimposable structures give different effects, we mutated E97 in TIM from Trypanosoma brucei brucei (TbbTIM), Saccharomyces cerevisiae (yTIM), and human (hTIM). The E97D, E97A, and E97Q mutations led to a ∼three-tenfold decrease in activity, a modest effect compared to the 10²-10³-fold effect in PfTIM. CD and fluorescence studies showed the overall structures for the mutants were essentially unchanged. Structural analysis shows that several residues surrounding E97 differ between PfTIM and TIM from the other organisms, and rearrangements or mispositioning of residues in PfTIM may lead to the different rate effects. The results illustrate the interplay of active site and surrounding residues in affecting catalysis and highlight that understanding of the role of residues surrounding the active site may aid in the incorporation of favorable or avoidance of unfavorable interactions when designing enzymes.

Characterization of equine GST A3-3 as a steroid isomerase

Glutathione transferases (GSTs) comprise a superfamily of enzymes prominently involved in detoxication by making toxic electrophiles more polar and therefore more easily excretable. However some GSTs have developed alternative functions. Thus, a member of the Alpha class GSTs in pig and human tissues is involved in steroid hormone biosynthesis, catalyzing the obligatory double-bond isomerization of Δ⁵-androstene-3,17-dione to Δ⁴-androstene-3,17-dione and of Δ⁵-pregnene-3,20-dione to Δ⁴-pregnene-3,20-dione on the biosynthetic pathways to testosterone and progesterone. The human GST A3-3 is the most efficient steroid double-bond isomerase known so far in mammals. The current work extends discoveries of GST enzymes that act in the steroidogenic pathways in large mammals. The mRNA encoding the steroid isomerase GST A3-3 was cloned from testis of the horse (Equus ferus caballus). The concentrations of GSTA3 mRNA were highest in hormone-producing organs such as ovary, testis and adrenal gland. EcaGST A3-3 produced in E. coli has been characterized and shown to have highly efficient steroid double-bond isomerase activity, exceeding its activities with conventional GST substrates. The enzyme now ranks as one of the most efficient steroid isomerases known in mammals and approaches the activity of the bacterial ketosteroid isomerase, one of the most efficient enzymes of all categories known today. The high efficiency and the tissue distribution of EcaGST A3-3 support the view that the enzyme plays a physiologically significant role in the biosynthesis of steroid hormones.

In vitro evolution of an l-amino acid deaminase active on l-1-naphthylalanine

l-Amino acid deaminase from Proteus myxofaciens (PmaLAAD) is a promising biocatalyst for enantioselective biocatalysis that can be exploited to produce optically pure d-amino acids or α-keto acids.

Electric Fields and Enzyme Catalysis

What happens inside an enzyme's active site to allow slow and difficult chemical reactions to occur so rapidly? This question has occupied biochemists' attention for a long time. Computer models of increasing sophistication have predicted an important role for electrostatic interactions in enzymatic reactions, yet this hypothesis has proved vexingly difficult to test experimentally. Recent experiments utilizing the vibrational Stark effect make it possible to measure the electric field a substrate molecule experiences when bound inside its enzyme's active site. These experiments have provided compelling evidence supporting a major electrostatic contribution to enzymatic catalysis. Here, we review these results and develop a simple model for electrostatic catalysis that enables us to incorporate disparate concepts introduced by many investigators to describe how enzymes work into a more unified framework stressing the importance of electric fields at the active site.

Contrasting patterns of nucleotide polymorphism suggest different selective regimes within different parts of the PgiC1 gene in Festuca ovina L

Background

Phosphoglucose isomerase (PGI, EC 5.3.1.9) is an essential metabolic enzyme in all eukaryotes. An earlier study of the PgiC1 gene, which encodes cytosolic PGI in the grass Festuca ovina L., revealed a marked difference in the levels of nucleotide polymorphism between the 5’ and 3’ portions of the gene.

Methods

In the present study, we characterized the sequence polymorphism in F. ovina PgiC1 in more detail and examined possible explanations for the non-uniform pattern of nucleotide polymorphism across the gene.

Results

Our study confirms that the two portions of the PgiC1 gene show substantially different levels of DNA polymorphism and also suggests that the peptide encoded by the 3’ portion of PgiC1 is functionally and structurally more important than that encoded by the 5’ portion. Although there was some evidence of purifying selection (d_N/d_S test) on the 5’ portion of the gene, the signature of purifying selection was considerably stronger on the 3’ portion of the gene (d_N/d_S and McDonald–Kreitman tests). Several tests support the action of balancing selection within the 5’ portion of the gene. Wall’s B and Q tests were significant only for the 5’ portion of the gene. There were also marked peaks of nucleotide diversity, Tajima’s D and the d_N/d_S ratio at or around a PgiC1 codon site (within the 5’ portion of the gene) that a previous study had suggested was subject to positive diversifying selection.

Conclusions

Our results suggest that the two portions of the gene have been subject to different selective regimes. Purifying selection appears to have been the main force contributing to the relatively low level of polymorphism within the 3’ portion of the sequence. In contrast, it is possible that balancing selection has contributed to the maintenance of the polymorphism within the 5’ portion of the gene.

Electronic supplementary material

The online version of this article (doi:10.1186/s41065-017-0032-6) contains supplementary material, which is available to authorized users.

iTRAQ-based quantitative proteome revealed metabolic changes of Flammulina velutipes mycelia in response to cold stress

Temperature is one of the pivotal factors influencing mycelium growth and fruit-body formation of Flammulina velutipes. To gain insights into hyphae growth and fruit-body formation events and facilitate the identification of potential stage-specific biomarker candidates, we investigated the proteome response of F. velutipes mycelia to cold stresses using iTRAQ-coupled two-dimensional liquid chromatography tandem mass spectrometry (2D LC-MS/MS) technique. Among 1198 proteins identified with high confidence, a total of 63 displayed altered expression level after cold stress treatments. In-depth data analysis reveals that differentially expressed proteins were involved in a variety of cellular processes, particularly metabolic processes. Among the 31 up-regulated proteins, 24 (77.42%) were associated with 22 specific KEGG pathways. These up-regulated proteins could possibly serve as potential biomarkers to study the molecular mechanisms of F. velutipes mycelia response to cold stresses. These data of the proteins might provide valuable evidences to better understand the molecular mechanisms of mycelium resistance to cold stress and fruit-body formation in fungi.

BIOLOGICAL SIGNIFICANCE

Low-temperature is one of the pivotal factors in some Flammulina velutipes industrial processes influencing mycelium growth, inducing primordia and controlling fruit-body development. Preliminary study has indicated that effectively regulating cultivation could augment the yield by controlling optimal cold stress level on mycelia. However, we are still far from understanding the molecular and physiological mechanisms of adaptation of these fungi at cold stress. In the present study, the experiments reported above were undertaken to investigate chronological changes of protein expression during F. velutipes mycelia in response to cold stress by using iTRAQ-coupled 2D LC-MS/MS technique. This result would provide new insights to the underlying mycelium growth and fruit-body formation mechanisms of basidiomycetes under cold stress.

Genome and metagenome analyses reveal adaptive evolution of the host and interaction with the gut microbiota in the goose

The goose is an economically important waterfowl that exhibits unique characteristics and abilities, such as liver fat deposition and fibre digestion. Here, we report de novo whole-genome assemblies for the goose and swan goose and describe the evolutionary relationships among 7 bird species, including domestic and wild geese, which diverged approximately 3.4~6.3 million years ago (Mya). In contrast to chickens as a proximal species, the expanded and rapidly evolving genes found in the goose genome are mainly involved in metabolism, including energy, amino acid and carbohydrate metabolism. Further integrated analysis of the host genome and gut metagenome indicated that the most widely shared functional enrichment of genes occurs for functions such as glycolysis/gluconeogenesis, starch and sucrose metabolism, propanoate metabolism and the citrate cycle. We speculate that the unique physiological abilities of geese benefit from the adaptive evolution of the host genome and symbiotic interactions with gut microbes.

The 3-D Structural Basis for the Pgi Genotypic Differences in the Performance of the Butterfly Melitaea cinxia at Different Temperatures

Although genotype-by-environment interaction has long been used to unveil the genetic variation that affects Darwinian fitness, the mechanisms underlying the interaction usually remain unknown. Genetic variation at the dimeric glycolytic enzyme phosphoglucoisomerase (Pgi) has been observed to interact with temperature to explain the variation in the individual performance of the butterfly Melitaea cinxia. At relatively high temperature, individuals with Pgi-non-f genotypes generally surpass those with Pgi-f genotypes, while the opposite applies at relatively low temperature. In this study, we did protein structure predictions and BlastP homology searches with the aim to understand the structural basis for this temperature-dependent difference in the performance of M. cinxia. Our results show that, at amino acid (AA) site 372, one of the two sites that distinguish Pgi-f (the translated polypeptide of the Pgi-f allele) from Pgi-non-f (the translated polypeptide of the Pgi-non-f allele), the Pgi-non-f-related residue strengthens an electrostatic attraction between a pair of residues (Glu373-Lys472) that are from different monomers, compared to the Pgi-f-related residue. Further, BlastP searches of animal protein sequences reveal a dramatic excess of electrostatically attractive combinations of the residues at the Pgi AA sites equivalent to sites 373 and 472 in M. cinxia. This suggests that factors enhancing the inter-monomer interaction between these two sites, and therefore helping the tight association of two Pgi monomers, are favourable. Our homology-modelling results also show that, at the second AA site that distinguishes Pgi-f from Pgi-non-f in M. cinxia, the Pgi-non-f-related residue is more entropy-favourable (leading to higher structural stability) than the Pgi-f-related residue. To sum up, this study suggests a higher structural stability of the protein products of the Pgi-non-f genotypes than those of the Pgi-f genotypes, which may explain why individuals carrying Pgi-non-f genotypes outperform those carrying Pgi-f genotypes at stressful high temerature.

Model-Based Design of Biochemical Microreactors

Mathematical modeling of biochemical pathways is an important resource in Synthetic Biology, as the predictive power of simulating synthetic pathways represents an important step in the design of synthetic metabolons. In this paper, we are concerned with the mathematical modeling, simulation, and optimization of metabolic processes in biochemical microreactors able to carry out enzymatic reactions and to exchange metabolites with their surrounding medium. The results of the reported modeling approach are incorporated in the design of the first microreactor prototypes that are under construction. These microreactors consist of compartments separated by membranes carrying specific transporters for the input of substrates and export of products. Inside the compartments of the reactor multienzyme complexes assembled on nano-beads by peptide adapters are used to carry out metabolic reactions. The spatially resolved mathematical model describing the ongoing processes consists of a system of diffusion equations together with boundary and initial conditions. The boundary conditions model the exchange of metabolites with the neighboring compartments and the reactions at the surface of the nano-beads carrying the multienzyme complexes. Efficient and accurate approaches for numerical simulation of the mathematical model and for optimal design of the microreactor are developed. As a proof-of-concept scenario, a synthetic pathway for the conversion of sucrose to glucose-6-phosphate (G6P) was chosen. In this context, the mathematical model is employed to compute the spatio-temporal distributions of the metabolite concentrations, as well as application relevant quantities like the outflow rate of G6P. These computations are performed for different scenarios, where the number of beads as well as their loading capacity are varied. The computed metabolite distributions show spatial patterns, which differ for different experimental arrangements. Furthermore, the total output of G6P increases for scenarios where microcompartimentation of enzymes occurs. These results show that spatially resolved models are needed in the description of the conversion processes. Finally, the enzyme stoichiometry on the nano-beads is determined, which maximizes the production of glucose-6-phosphate.

Evidence for Positive Selection within the PgiC1 Locus in the Grass Festuca ovina

The dimeric metabolic enzyme phosphoglucose isomerase (PGI, EC 5.3.1.9) plays an essential role in energy production. In the grass Festuca ovina, field surveys of enzyme variation suggest that genetic variation at cytosolic PGI (PGIC) may be adaptively important. In the present study, we investigated the molecular basis of the potential adaptive significance of PGIC in F. ovina by analyzing cDNA sequence variation within the PgiC1 gene. Two, complementary, types of selection test both identified PGIC1 codon (amino acid) sites 200 and 173 as candidate targets of positive selection. Both candidate sites involve charge-changing amino acid polymorphisms. On the homology-modeled F. ovina PGIC1 3-D protein structure, the two candidate sites are located on the edge of either the inter-monomer boundary or the inter-domain cleft; examination of the homology-modeled PGIC1 structure suggests that the amino acid changes at the two candidate sites are likely to influence the inter-monomer interaction or the domain-domain packing. Biochemical studies in humans have shown that mutations at several amino acid sites that are located close to the candidate sites in F. ovina, at the inter-monomer boundary or the inter-domain cleft, can significantly change the stability and/or kinetic properties of the PGI enzyme. Molecular evolutionary studies in a wide range of other organisms suggest that PGI amino acid sites with similar locations to those of the candidate sites in F. ovina may be the targets of positive/balancing selection. Candidate sites 200 and 173 are the only sites that appear to discriminate between the two most common PGIC enzyme electromorphs in F. ovina: earlier studies suggest that these electromorphs are implicated in local adaptation to different grassland microhabitats. Our results suggest that PGIC1 sites 200 and 173 are under positive selection in F. ovina.

Prediction of distal residue participation in enzyme catalysis

A scoring method for the prediction of catalytically important residues in enzyme structures is presented and used to examine the participation of distal residues in enzyme catalysis. Scores are based on the Partial Order Optimum Likelihood (POOL) machine learning method, using computed electrostatic properties, surface geometric features, and information obtained from the phylogenetic tree as input features. Predictions of distal residue participation in catalysis are compared with experimental kinetics data from the literature on variants of the featured enzymes; some additional kinetics measurements are reported for variants of Pseudomonas putida nitrile hydratase (ppNH) and for Escherichia coli alkaline phosphatase (AP). The multilayer active sites of P. putida nitrile hydratase and of human phosphoglucose isomerase are predicted by the POOL log ZP scores, as is the single-layer active site of P. putida ketosteroid isomerase. The log ZP score cutoff utilized here results in over-prediction of distal residue involvement in E. coli alkaline phosphatase. While fewer experimental data points are available for P. putida mandelate racemase and for human carbonic anhydrase II, the POOL log ZP scores properly predict the previously reported participation of distal residues.

Experimental and computational mutagenesis to investigate the positioning of a general base within an enzyme active site

The positioning of catalytic groups within proteins plays an important role in enzyme catalysis, and here we investigate the positioning of the general base in the enzyme ketosteroid isomerase (KSI). The oxygen atoms of Asp38, the general base in KSI, were previously shown to be involved in anion–aromatic interactions with two neighboring Phe residues. Here we ask whether those interactions are sufficient, within the overall protein architecture, to position Asp38 for catalysis or whether the side chains that pack against Asp38 and/or the residues of the structured loop that is capped by Asp38 are necessary to achieve optimal positioning for catalysis. To test positioning, we mutated each of the aforementioned residues, alone and in combinations, in a background with the native Asp general base and in a D38E mutant background, as Glu at position 38 was previously shown to be mispositioned for general base catalysis. These double-mutant cycles reveal positioning effects as large as 10³-fold, indicating that structural features in addition to the overall protein architecture and the Phe residues neighboring the carboxylate oxygen atoms play roles in positioning. X-ray crystallography and molecular dynamics simulations suggest that the functional effects arise from both restricting dynamic fluctuations and disfavoring potential mispositioned states. Whereas it may have been anticipated that multiple interactions would be necessary for optimal general base positioning, the energetic contributions from positioning and the nonadditive nature of these interactions are not revealed by structural inspection and require functional dissection. Recognizing the extent, type, and energetic interconnectivity of interactions that contribute to positioning catalytic groups has implications for enzyme evolution and may help reveal the nature and extent of interactions required to design enzymes that rival those found in biology.

Effects of non-catalytic, distal amino acid residues on activity of E. coli DinB (DNA polymerase IV)

DinB is one of two Y family polymerases in E. coli and is involved in copying damaged DNA. DinB is specialized to bypass deoxyguanosine adducts that occur at the N(2) position, with its cognate lesion being the furfuryl adduct. Active site residues have been identified that make contact with the substrate and carry out deoxynucleotide triphosphate (dNTP) addition to the growing DNA strand. In DNA polymerases, these include negatively charged aspartate and glutamate residues (D8, D103, and E104 in E. coli DNA polymerase IV DinB). These residues position the essential magnesium ions correctly to facilitate nucleophilic attack by the primer hydroxyl group on the α-phosphate group of the incoming dNTP. To study the contribution of DinB residues to lesion bypass, the computational methods THEMATICS and POOL were employed. These methods correctly predict the known active site residues, as well as other residues known to be important for activity. In addition, these methods predict other residues involved in substrate binding as well as more remote residues. DinB variants with mutations at the predicted positions were constructed and assayed for bypass of the N(2) -furfuryl-dG lesion. We find a wide range of effects of predicted residues, including some mutations that abolish damage bypass. Moreover, most of the DinB variants constructed are unable to carry out the extension step of lesion bypass. The use of computational prediction methods represents another tool that will lead to a more complete understanding of translesion DNA synthesis.

Expression and knockdown analysis of glucose phosphate isomerase in chicken primordial germ cells

Glucose is an important monosaccharide required to generate energy in all cells. After entry into cells, glucose is phosphorylated to glucose-6-phosphate and then transformed into glycogen or metabolized to produce energy. Glucose phosphate isomerase (GPI) catalyzes the reversible isomerization of glucose-6-phosphate and fructose-6-phosphate. Without GPI activity or fructose-6-phosphate, many steps of glucose metabolism would not occur. The requirement for GPI activity for normal functioning of primordial germ cells (PGCs) needs to be identified. In this study, we first examined the expression of chicken GPI during early embryonic development and germ cell development. GPI expression was strongly and ubiquitously detected in chicken early embryos and embryonic tissues at Embryonic Day 6.5 (E6.5). Continuous GPI expression was detected in PGCs and germ cells of both sexes during gonadal development. Specifically, GPI expression was stronger in male germ cells than in female germ cells during embryonic development and the majority of post-hatching development. Then, we used siRNA-1499 to knock down GPI expression in PGCs. siRNA-1499 caused an 85% knockdown in GPI, and PGC proliferation was also affected 48 h after transfection. We further examined the knockdown effects on 28 genes related to the glycolysis/gluconeogenesis pathway and the endogenous glucose level in chicken PGCs. Among genes related to glycolysis/gluconeogenesis, 20 genes showed approximately 3-fold lower expression, 4 showed approximately 10-fold lower, and 2 showed approximately 100-fold lower expression in knockdown PGCs. The endogenous glucose level was significantly reduced in knockdown PGCs. We conclude that the GPI gene is crucial for maintaining glycolysis and supplying energy to developing PGCs.

POOL server: machine learning application for functional site prediction in proteins

Summary: We present an automated web server for partial order optimum likelihood (POOL), a machine learning application that combines computed electrostatic and geometric information for high-performance prediction of catalytic residues from 3D structures. Input features consist of THEMATICS electrostatics data and pocket information from ConCavity. THEMATICS measures deviation from typical, sigmoidal titration behavior to identify functionally important residues and ConCavity identifies binding pockets by analyzing the surface geometry of protein structures. Both THEMATICS and ConCavity (structure only) do not require the query protein to have any sequence or structure similarity to other proteins. Hence, POOL is applicable to proteins with novel folds and engineered proteins. As an additional option for cases where sequence homologues are available, users can include evolutionary information from INTREPID for enhanced accuracy in site prediction.

Availability: The web site is free and open to all users with no login requirements at http://www.pool.neu.edu.

Contact:m.ondrechen@neu.edu

Supplementary Information:Supplementary data are available at Bioinformatics online.