Functional roles of slow enzyme conformational changes in network dynamics

Development of CRISPR/Cas9-Mediated Saccharomyces cerevisiae Strains for the Cell-Surface Display of a Novel Fusion Acid-Alkaline Phytase

Phytases enhance phosphorus bioavailability in animal feed, but their limited reusability hinders their application. To overcome this, Saccharomyces cerevisiae was engineered to display a fusion phytase combining acid and alkaline phytases on its cell surface by using CRISPR/Cas9. The enzyme was anchored via the α-agglutinin-GPI system in two marker-free strains, BY4743::GAP-mGEB and BY4743::GAP-aGEB, employing MFα and Aga2p signal peptides, respectively. Both strains exhibited robust surface activity across a broad pH range, retaining >50% relative activity between pH 1.0 and 7.0, with dual optima at pH 2.0 and 5.0-6.0. Kinetic analysis revealed a Km of 0.377-0.989 mM and a kcat of 0.014-0.019 μmol/min/mg wet-cell weight, with the Aga2p strain showing the highest efficiency. The fusion phytase exhibited ∼ 3.5-4 times higher activity than the single acid phytase. These strains effectively degraded phytate in soybean, corn flour, and rice bran, demonstrating a sustainable approach for improving phosphorus utilization in animal feed.

Construction and enzymatic characterization of a monomeric variant of dimeric amylosucrase from Deinococcus geothermalis

Amylosucrase (ASase; E.C. 2.4.1.4), a member of glycoside hydrolase family 13 (GH13), produces α-1,4-glucans and sucrose isomers using sucrose as its sole substrate. This study identifies and characterizes the dimeric structure of ASase from Deinococcus geothermalis (DgAS), highlighting essential amino acid residues for maintaining the dimeric state. The monomeric form, DgAS R30A, exhibited a higher affinity for sucrose compared to the wild-type (WT), especially during the formation of the ASase-glucose intermediate complex and subsequent hydrolysis. Notably, DgAS R30A produced a higher proportion of α-glucans with a degree of polymerization (DP) of ≤20 and fewer α-glucans with a DP of ≥31. This suggested that the reduced surface area of the oligosaccharide binding site in the monomeric form led to decreased binding of longer-chain maltooligosaccharides, favoring the formation of shorter DP α-glucans. Kinetic analysis revealed significantly lower Michaelis constants (Km) for DgAS R30A's total and hydrolysis activities, with the overall performance (kcat/Km) values for DgAS R30A exceeded those of the WT at all sucrose concentrations. Here, we report the first high-resolution homodimeric DgAS structure, revealing conserved active site residues and a unique dimerization interface. This study enhances our understanding of the molecular factors influencing the oligomeric state and enzyme activities.

Physicochemical Perspective of Biological Heterogeneity

The vast majority of chemical processes that govern our lives occur within living cells. At the core of every life process, such as gene expression or metabolism, are chemical reactions that follow the fundamental laws of chemical kinetics and thermodynamics. Understanding these reactions and the factors that govern them is particularly important for the life sciences. The physicochemical environment inside cells, which can vary between cells and organisms, significantly impacts various biochemical reactions and increases the extent of population heterogeneity. This paper discusses using physical chemistry approaches for biological studies, including methods for studying reactions inside cells and monitoring their conditions. The potential for development in this field and possible new research areas are highlighted. By applying physical chemistry methodology to biochemistry in vivo, we may gain new insights into biology, potentially leading to new ways of controlling biochemical reactions.

The mechanistic insights into different aspects of promiscuity in metalloenzymes

Enzymes are nature's ultimate machinery to catalyze complex reactions. Though enzymes are evolved to catalyze specific reactions, they also show significant promiscuity in reactions and substrate selection. Metalloenzymes contain a metal ion or metal cofactor in their active site, which is crucial in their catalytic activity. Depending on the metal and its coordination environment, the metal ion or cofactor may function as a Lewis acid or base and a redox center and thus can catalyze a plethora of natural reactions. In fact, the versatility in the oxidation state of the metal ions provides metalloenzymes with a high level of catalytic adaptability and promiscuity. In this chapter, we discuss different aspects of promiscuity in metalloenzymes by using several recent experimental and theoretical works as case studies. We start our discussion by introducing the concept of promiscuity and then we delve into the mechanistic insight into promiscuity at the molecular level.

A Novel Cooperative Metallo-β-Lactamase Fold Metallohydrolase from Pathogen Vibrio vulnificus Exhibits β-Lactam Antibiotic-Degrading Activities

Vibrio vulnificus is a pathogen that accounts for one of the highest mortality rates and is responsible for most reported seafood-related illnesses and deaths worldwide. Owing to the threats of pathogens with β-lactamase activity, it is important to identify and characterize β-lactamases with clinical significance. In this study, the protein sequence of the metallo-β-lactamase (MBL) fold metallohydrolase from V. vulnificus (designated Vmh) was analyzed, and its oligomeric state, β-lactamase activity, and metal binding ability were determined. BLASTp analysis indicated that the V. vulnificus Vmh protein showed no significant sequence identity with any experimentally identified Ambler class B MBLs or enzymes containing the MBL protein fold; it was also predicted to have a signal peptide of 19 amino acids at its N terminus and an MBL protein fold from amino acid residues 23 to 216. Recombinant V. vulnificus Vmh protein was overexpressed and purified. Analytical ultracentrifugation and electrospray ionization-mass spectrometry (MS) data demonstrated its monomeric state in an aqueous solution. Recombinant V. vulnificus Vmh protein showed broad degrading activities against β-lactam antibiotics, such as penicillins, cephalosporins, and imipenems, with k_cat/K_m values ranging from 6.23 × 10² to 1.02 × 10⁴ M^-1 s^-1. The kinetic reactions of this enzyme exhibited sigmoidal behavior, suggesting the possibility of cooperativity. Zinc ions were required for the enzyme activity, which was abolished by adding the metal chelator EDTA. Inductively coupled plasma-MS indicated that this enzyme might bind two zinc ions per molecule as a cofactor.

Fluctuation theory of immune response: A statistical mechanical approach to understand pathogen induced T-cell population dynamics

In this period of intense interest in human immunity, we attempt here to quantify the immune response against pathogen invasion through T-cell population dynamics. Borrowing concepts from equilibrium statistical mechanics, we introduce a new description of the immune response function (IMRF) in terms of fluctuations in the population number of relevant biological cells (effector and regulatory T-cells). We use a coarse-grained chemical reaction network model (CG-CRNM) to calculate the number fluctuations and show that the response function derived as such can, indeed, capture the crossover observed in a T-cell driven immune response. We employ the network model to learn the effect of vitamin-D as an immunomodulator. We solve our CG-CRNM using a stochastic Gillespie algorithm. Depending on the effector T-cell concentration, we can classify immune regulation regimes into three categories: weak, strong, and moderate. The IMRF is found to behave differently in these three regimes. A damped cross-regulatory behavior found in the dynamics of effector and regulatory T-cell concentration in the diseased states correlates well with the same found in a cohort of patients with specific malignancies and autoimmune diseases. Importantly, the crossover from the weakly regulated steady state to the other (the strongly regulated) is accompanied by a divergence-like growth in the fluctuation of both the effector and the regulatory T-cell concentration, characteristic of a dynamic phase transition. We believe such steady-state IMRF analyses could help not only to phase-separate different immune stages but also aid in the valuable connection between autoimmunity, optimal vitamin-D, and consequences of immunosuppressive stress and malignancy.

Extensions to Michaelis-Menten Kinetics for Single Parameters

Biochemical transformation kinetics is based on the formation of enzyme-substrate complexes. We developed a robust scheme based on unit productions of enzymes and reactants in cyclic events to comply with mass action law to form enzyme-substrate complexes. The developed formalism supports a successful application of Michaelis-Menten kinetics in all biochemical transformations of single parameters. It is an essential tool to overcome some challenging healthcare and environmental issues. In developing the formalism, we defined the substrate [S]= [Product]3/4 and rate of reaction based on rate and time perspectives. It allowed us to develop two quadratic equations. The first, represents a body entity that gave a useful relationship of enzyme E = 2S0.33, and the second nutrients/feed, each giving [Enzymes] and [Enzyme-substrate complexes], simulating rate of reaction, [substrate], and their differentials. By combining [Enzymes] and [Enzyme-substrate complexes] values, this quadratic equation derives a Michaelis-Menten hyperbolic function. Interestingly, we can derive the proportionate rate of reaction and [Enzymes] values of the quadratics resulting in another Michaelis-Menten hyperbolic. What is clear from these results is that between these two hyperbolic functions, in-competitive inhibitions exist, indicating metabolic activities and growth in terms of energy levels. We validated these biochemical transformations with examples applicable to day to day life.

Molecular pathways for antigenic peptide generation by ER aminopeptidase 1

Endoplasmic Reticulum aminopeptidase 1 (ERAP1) is an intracellular enzyme that can generate or destroy potential peptide ligands for MHC class I molecules. ERAP1 activity influences the cell-surface immunopeptidome and epitope immunodominance patterns but in complex and poorly understood manners. Two main distinct pathways have been proposed to account for ERAP1's effects on the nature and quantity of MHCI-bound peptides: i) ERAP1 trims peptides in solution, generating the correct length for binding to MHCI or overtrimming peptides so that they are too short to bind, and ii) ERAP1 trims peptides while they are partially bound onto MHCI in manner that leaves the peptide amino terminus accessible. For both pathways, once an appropriate length peptide is generated it could bind conventionally to MHCI, competing with further trimming by ERAP1. The two pathways, although not necessarily mutually exclusive, provide distinct vantage points for understanding of the rules behind the generation of the immunopeptidome. Resolution of the mechanistic details of ERAP1-mediated antigenic peptide generation can have important consequences for pharmacological efforts to regulate the immunopeptidome for therapeutic applications, and for understanding association of ERAP1 alleles with susceptibility to autoimmune disease and cancer. We review current evidence in support of these two pathways and discuss their relative importance and potential complementarity.

Structure, function, and mechanism of proline utilization A (PutA)

Proline has important roles in multiple biological processes such as cellular bioenergetics, cell growth, oxidative and osmotic stress response, protein folding and stability, and redox signaling. The proline catabolic pathway, which forms glutamate, enables organisms to utilize proline as a carbon, nitrogen, and energy source. FAD-dependent proline dehydrogenase (PRODH) and NAD⁺-dependent glutamate semialdehyde dehydrogenase (GSALDH) convert proline to glutamate in two sequential oxidative steps. Depletion of PRODH and GSALDH in humans leads to hyperprolinemia, which is associated with mental disorders such as schizophrenia. Also, some pathogens require proline catabolism for virulence. A unique aspect of proline catabolism is the multifunctional proline utilization A (PutA) enzyme found in Gram-negative bacteria. PutA is a large (>1000 residues) bifunctional enzyme that combines PRODH and GSALDH activities into one polypeptide chain. In addition, some PutAs function as a DNA-binding transcriptional repressor of proline utilization genes. This review describes several attributes of PutA that make it a remarkable flavoenzyme: (1) diversity of oligomeric state and quaternary structure; (2) substrate channeling and enzyme hysteresis; (3) DNA-binding activity and transcriptional repressor function; and (4) flavin redox dependent changes in subcellular location and function in response to proline (functional switching).

Calcium Oscillation Frequency-Sensitive Gene Regulation and Homeostatic Compensation in Pancreatic β-Cells

Pancreatic islet [Formula: see text]-cells are electrically excitable cells that secrete insulin in an oscillatory fashion when the blood glucose concentration is at a stimulatory level. Insulin oscillations are the result of cytosolic [Formula: see text] oscillations that accompany bursting electrical activity of [Formula: see text]-cells and are physiologically important. ATP-sensitive [Formula: see text] channels (K(ATP) channels) play the key role in setting the overall activity of the cell and in driving bursting, by coupling cell metabolism to the membrane potential. In humans, when there is a defect in K(ATP) channel function, [Formula: see text]-cells fail to respond appropriately to changes in the blood glucose level, and electrical and [Formula: see text] oscillations are lost. However, mice compensate for K(ATP) channel defects in islet [Formula: see text]-cells by employing alternative mechanisms to maintain electrical and [Formula: see text] oscillations. In a recent study, we showed that in mice islets in which K(ATP) channels are genetically knocked out another [Formula: see text] current, provided by inward-rectifying [Formula: see text] channels, is increased. With mathematical modeling, we demonstrated that a sufficient upregulation in these channels can account for the paradoxical electrical bursting and [Formula: see text] oscillations observed in these [Formula: see text]-cells. However, the question of determining the correct level of upregulation that is necessary for this compensation remained unanswered, and this question motivates the current study. [Formula: see text] is a well-known regulator of gene expression, and several examples have been shown of genes that are sensitive to the frequency of the [Formula: see text] signal. In this mathematical modeling study, we demonstrate that a [Formula: see text] oscillation frequency-sensitive gene transcription network can adjust the gene expression level of a compensating [Formula: see text] channel so as to rescue electrical bursting and [Formula: see text] oscillations in a model [Formula: see text]-cell in which the key K(ATP) current is removed. This is done without the prescription of a target [Formula: see text] level, but evolves naturally as a consequence of the feedback between the [Formula: see text]-dependent enzymes and the cell's electrical activity. More generally, the study indicates how [Formula: see text] can provide the link between gene expression and cellular electrical activity that promotes wild-type behavior in a cell following gene knockout.

Decoding Single Molecule Time Traces with Dynamic Disorder

Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed. Here we report a new algorithm—Variational Bayes-double chain Markov model (VB-DCMM)—to analyze single molecule time trajectories that display dynamic disorder. The proposed analysis employing VB-DCMM allows us to detect the presence of dynamic disorder, if any, in each trajectory, identify the number of internal states, and estimate transition rates between the internal states as well as the rates of conformational transition within each internal state. Applying VB-DCMM algorithm to single molecule FRET data of H-DNA in 100 mM-Na⁺ solution, followed by data clustering, we show that at least 6 kinetic paths linking 4 distinct internal states are required to correctly interpret the duplex-triplex transitions of H-DNA.

We have developed a new algorithm to better decode single molecule data with dynamic disorder. Our new algorithm, which represents a substantial improvement over other methodologies, can detect the presence of dynamic disorder in each trajectory and quantify the kinetic characteristics of underlying energy landscape. As a model system, we applied our algorithm to the single molecule FRET time traces of H-DNA. While duplex-triplex transitions of H-DNA are conventionally interpreted in terms of two-state kinetics, slowly varying dynamic patterns corresponding to hidden internal states can also be identified from the individual time traces. Our algorithm reveals that at least 4 distinct internal states are required to correctly interpret the data.

Hysteresis and positive cooperativity as possible regulatory mechanisms of Trypanosoma cruzi hexokinase activity

In Trypanosoma cruzi, the causal agent of Chagas disease, the first six or seven steps of glycolysis are compartmentalized in glycosomes, which are authentic but specialized peroxisomes. Hexokinase (HK), the first enzyme in the glycolytic pathway, has been an important research object, particularly as a potential drug target. Here we present the results of a specific kinetics study of the native HK from T. cruzi epimastigotes; a sigmoidal behavior was apparent when the velocity of the reaction was determined as a function of the concentration of its substrates, glucose and ATP. This behavior was only observed at low enzyme concentration, while at high concentration classical Michaelis-Menten kinetics was displayed. The progress curve of the enzyme's activity displays a lag phase of which the length is dependent on the protein concentration, suggesting that HK is a hysteretic enzyme. The hysteretic behavior may be attributed to slow changes in the conformation of T. cruzi HK as a response to variations of glucose and ATP concentrations in the glycosomal matrix. Variations in HK's substrate concentrations within the glycosomes may be due to variations in the trypanosome's environment. The hysteretic and cooperative behavior of the enzyme may be a form of regulation by which the parasite can more readily adapt to these environmental changes, occurring within each of its hosts, or during the early phase of transition to a new host.

Comparative genome sequencing reveals genomic signature of extreme desiccation tolerance in the anhydrobiotic midge

Anhydrobiosis represents an extreme example of tolerance adaptation to water loss, where an organism can survive in an ametabolic state until water returns. Here we report the first comparative analysis examining the genomic background of extreme desiccation tolerance, which is exclusively found in larvae of the only anhydrobiotic insect, Polypedilum vanderplanki. We compare the genomes of P. vanderplanki and a congeneric desiccation-sensitive midge P. nubifer. We determine that the genome of the anhydrobiotic species specifically contains clusters of multi-copy genes with products that act as molecular shields. In addition, the genome possesses several groups of genes with high similarity to known protective proteins. However, these genes are located in distinct paralogous clusters in the genome apart from the classical orthologues of the corresponding genes shared by both chironomids and other insects. The transcripts of these clustered paralogues contribute to a large majority of the mRNA pool in the desiccating larvae and most likely define successful anhydrobiosis. Comparison of expression patterns of orthologues between two chironomid species provides evidence for the existence of desiccation-specific gene expression systems in P. vanderplanki.

The African chironomid midge, Polypedilum vanderplanki, is able to withstand extreme desiccation. Here the authors sequence the genomes of a desiccation-tolerant and desiccation-sensitive species of chironomid midge and pinpoint genes that may have a role in conferring resistance to desiccation.

A stochastic chemical dynamic approach to correlate autoimmunity and optimal vitamin-D range

Motivated by several recent experimental observations that vitamin-D could interact with antigen presenting cells (APCs) and T-lymphocyte cells (T-cells) to promote and to regulate different stages of immune response, we developed a coarse grained but general kinetic model in an attempt to capture the role of vitamin-D in immunomodulatory responses. Our kinetic model, developed using the ideas of chemical network theory, leads to a system of nine coupled equations that we solve both by direct and by stochastic (Gillespie) methods. Both the analyses consistently provide detail information on the dependence of immune response to the variation of critical rate parameters. We find that although vitamin-D plays a negligible role in the initial immune response, it exerts a profound influence in the long term, especially in helping the system to achieve a new, stable steady state. The study explores the role of vitamin-D in preserving an observed bistability in the phase diagram (spanned by system parameters) of immune regulation, thus allowing the response to tolerate a wide range of pathogenic stimulation which could help in resisting autoimmune diseases. We also study how vitamin-D affects the time dependent population of dendritic cells that connect between innate and adaptive immune responses. Variations in dose dependent response of anti-inflammatory and pro-inflammatory T-cell populations to vitamin-D correlate well with recent experimental results. Our kinetic model allows for an estimation of the range of optimum level of vitamin-D required for smooth functioning of the immune system and for control of both hyper-regulation and inflammation. Most importantly, the present study reveals that an overdose or toxic level of vitamin-D or any steroid analogue could give rise to too large a tolerant response, leading to an inefficacy in adaptive immune function.

A coarse-grained elastic network atom contact model and its use in the simulation of protein dynamics and the prediction of the effect of mutations

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cα-only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations.

Evidence for hysteretic substrate channeling in the proline dehydrogenase and Δ1-pyrroline-5-carboxylate dehydrogenase coupled reaction of proline utilization A (PutA)

PutA (proline utilization A) is a large bifunctional flavoenzyme with proline dehydrogenase (PRODH) and Δ(1)-pyrroline-5-carboxylate dehydrogenase (P5CDH) domains that catalyze the oxidation of l-proline to l-glutamate in two successive reactions. In the PRODH active site, proline undergoes a two-electron oxidation to Δ(1)-pyrroline-5-carboxlylate, and the FAD cofactor is reduced. In the P5CDH active site, l-glutamate-γ-semialdehyde (the hydrolyzed form of Δ(1)-pyrroline-5-carboxylate) undergoes a two-electron oxidation in which a hydride is transferred to NAD(+)-producing NADH and glutamate. Here we report the first kinetic model for the overall PRODH-P5CDH reaction of a PutA enzyme. Global analysis of steady-state and transient kinetic data for the PRODH, P5CDH, and coupled PRODH-P5CDH reactions was used to test various models describing the conversion of proline to glutamate by Escherichia coli PutA. The coupled PRODH-P5CDH activity of PutA is best described by a mechanism in which the intermediate is not released into the bulk medium, i.e., substrate channeling. Unexpectedly, single-turnover kinetic experiments of the coupled PRODH-P5CDH reaction revealed that the rate of NADH formation is 20-fold slower than the steady-state turnover number for the overall reaction, implying that catalytic cycling speeds up throughput. We show that the limiting rate constant observed for NADH formation in the first turnover increases by almost 40-fold after multiple turnovers, achieving half of the steady-state value after 15 turnovers. These results suggest that EcPutA achieves an activated channeling state during the approach to steady state and is thus a new example of a hysteretic enzyme. Potential underlying causes of activation of channeling are discussed.