Kinetics of Allosteric Inhibition of Single Enzyme by Product Molecules

A minimal kinetic model for the interpretation of complex catalysis in single enzyme molecules

Multi-exponential waiting-time distribution and randomness parameter greater than unity ascribe dynamic disorder in single-enzyme catalysis corroborated to the interplay of transforming conformers [English et al., Nat. Chem. Biol., 2006, 2, 87]. The associated multi-state model of enzymatic turnovers with statically heterogeneous catalytic rates misdescribes the non-linear uprising of the randomness parameter from unity in relation to the attributes of the fall-offs of the waiting-time distribution at different substrate concentrations. To resolve this crucial issue, we first employ a comprehensive stochastic reaction scenario and further rationalize and work out the minimal indispensable dynamic-disorder model that ensures the foregoing relationship upon comparison with the data. We elucidate that specific disregard for the transition rate coefficients in the multi-state model on account of the especially slow conformational transitions is the underlying reason for not achieving interrelation between the observables.

Isolation and functional verification of an aspartate aminotransferase gene from Neoporphyra haitanensis

BACKGROUND

Neoporphyra haitanensis is a commercial laver species in China. Aspartic acid is an important flavor amino acid, and aspartate aminotransferase (AAT) is a crucial enzyme in its biosynthesis. In this study, we cloned one AAT gene (NhAAT) from the red alga N. haitanensis and investigated its sequence structure, transcriptional expression and enzymatic characteristics. The purpose of our research is to obtain a functional AAT responsible for the biosynthesis of aspartic acid from red seaweeds, which has the potential to influence the flavor of N. haitanensis.

RESULTS

Sequence analysis showed that NhAAT contains a conserved domain of Aminotran_1_2, which belongs to the transaminase superfamily. The secondary structure of NhAAT is dominated by α-helix. The results of enzymatic characterization illustrated that the NhAAT has highest catalytic activity at 45 °C and pH 7.5 in both forward and reverse reactions. The calculated K_m values of NhAAT was 5.67 and 6.16 mM for L-glutamic acid and L-aspartic acid, respectively. Quantitative analysis showed that the NhAAT expression of N. haitanensis collected in late harvest (Dec) was 4.5 times that of N. haitanensis collected in early harvest (Oct), while the aspartic acid content of N. haitanensis collected in late harvest (Dec) was 1.2 times that of N. haitanensis collected in early harvest (Oct).

CONCLUSION

The results of enzyme kinetics indicated that NhAAT prefers to catalyze the reaction in the direction of aspartic acid production. Moreover, the trend of NhAAT expression level was consistent with that of aspartic acid content in N. haitanensis in different harvest periods. Our research is helpful to understand the accumulation and regulation of amino acids in N. haitanensis in different habitats and the taste difference of N. haitanensis in different harvest periods.

Kinetics of Initial Charge Separation in the Photosynthetic Reaction Centers of Rhodobacter sphaeroides

A stochastic kinetic study of the initial electron transfer reaction in the reaction centers of wild-type and different mutants of photosynthetic bacterium Rhodobacter sphaeroides is suggested. The present approach to the disorder-driven complex kinetics skilfully offers an alternative to the earlier dynamic analyses. Exploiting a rational description of the reaction coordinate, effected by the relaxation of the surrounding protein environment, the measured kinetics were reproduced quantitatively. Notably, comparisons of the extracted relative free energies of electron transfer for the selected mutants and the available independent electrochemical estimates show exact agreement in some cases.

Glutamate Dehydrogenase Functions in Glutamic Acid Metabolism and Stress Resistance in Pyropia haitanensis

Pyropia haitanensis is an important laver species in China. Its quality traits are closely related to the content of glutamic acid. Glutamate dehydrogenase (GDH) is a crucial enzyme in the glutamic acid metabolism. In this study, two GDH genes from P. haitanensis, PhGDH1 and PhGDH2, were cloned and successfully expressed in Escherichia coli. The in vitro enzyme activity assay demonstrated that the catalytic activity of PhGDHs is mainly in the direction of ammonium assimilation. The measured Km values of PhGDH1 for NADH, (NH4)2SO4, and α-oxoglutarate were 0.12, 4.99, and 0.16 mM, respectively, while the corresponding Km values of PhGDH2 were 0.02, 3.98, and 0.104 mM, respectively. Site-directed mutagenesis results showed that Gly193 and Thr361 were important catalytic residues for PhGDH2. Moreover, expression levels of both PhGDHs were significantly increased under abiotic stresses. These results suggest that PhGDHs can convert α-oxoglutarate to glutamic acid, and enhance the flavor and stress resistance of P. haitanensis.

A Revisit to Turnover Kinetics of Individual Escherichia coli β-Galactosidase Molecules

Single-molecule experiments on β-galactosidase from Escherichia coli that catalyzes the hydrolysis of resorufin-β-d-galactopyranoside revealed important observations like fluctuating catalytic rate, memory effects arising from temporal correlations between the enzymatic turnovers and nonexponential waiting time distributions. The root cause of the observed results is intrinsic fluctuations among the different conformers of the active species, during the course of the reaction, thereby imparting dynamic disorder in the system under investigation. Originally, a multistate stochastic kinetic theory was employed that, despite satisfying the measured waiting time distributions and the mean waiting times at different substrate concentrations, yields a constant estimate of the randomness parameter. Inevitably, this manifests a strong disagreement with the substrate-concentration-dependent time variations of the said distribution, which at the same time misinterprets the measured magnitudes of the randomness parameter at lower concentrations. Here, we suggest a dual approach to the single-enzyme reaction, independently, making important improvements over the parent study and the recently suggested two-state stochastic analyses followed by quantitative rationalization of the experimental data. In the first case, an off-pathway mechanism satisfied the Michaelis-Menten equation under the circumstance of prevailing disorder while tested against the single-molecule data. However, recovery of randomness data in the lower-concentration regime, albeit primarily marks a significant refinement, a qualitative agreement at the growing concentrations seems to be reasoned by an account of switching among the limited numbers of discrete conformers. Consequently, in the second case, we circumvented the conventional way of approaching the enzyme catalysis and mapped the dynamics of structural transitions of the biocatalyst with the temporal fluctuations of the spatial distance between the different locations along a coarse-grained polymer chain. Exploiting a general mechanism for dynamic disorder, a reaction-diffusion formalism yielded an analytical expression for the waiting time distribution of the enzymatic turnovers, from which the mean waiting time and the randomness parameter were readily determined. Application of our results to the findings of the experiment on single β-galactosidase shows a quantitative agreement in each case. This soundly validates the usefulness of accounting for a more rigorous microscopic description pertinent to the conformational multiplicity in rationalizing the real-time data over the routine state-based sketch of the reaction system.