Hybrid dynamic/static method for large-scale simulation of metabolism

BACKGROUND: Many computer studies have employed either dynamic simulation or metabolic flux analysis (MFA) to predict the behaviour of biochemical pathways. Dynamic simulation determines the time evolution of pathway properties in response to environmental changes, whereas MFA provides only a snapshot of pathway properties within a particular set of environmental conditions. However, owing to the large amount of kinetic data required for dynamic simulation, MFA, which requires less information, has been used to manipulate large-scale pathways to determine metabolic outcomes. RESULTS: Here we describe a simulation method based on cooperation between kinetics-based dynamic models and MFA-based static models. This hybrid method enables quasi-dynamic simulations of large-scale metabolic pathways, while drastically reducing the number of kinetics assays needed for dynamic simulations. The dynamic behaviour of metabolic pathways predicted by our method is almost identical to that determined by dynamic kinetic simulation. CONCLUSION: The discrepancies between the dynamic and the hybrid models were sufficiently small to prove that an MFA-based static module is capable of performing dynamic simulations as accurately as kinetic models. Our hybrid method reduces the number of biochemical experiments required for dynamic models of large-scale metabolic pathways by replacing suitable enzyme reactions with a static module

Manipulation of Topological States and Bulk Band Gap Using Natural Heterostructures of a Topological Insulator

We have performed angle-resolved photoemission spectroscopy on (PbSe)5(Bi2Se3)3m, which forms a natural multilayer heterostructure consisting of a topological insulator (TI) and an ordinary insulator. For m = 2, we observed a gapped Dirac-cone state within the bulk-band gap, suggesting that the topological interface states are effectively encapsulated by block layers; furthermore, it was found that the quantum confinement effect of the band dispersions of Bi2Se3 layers enhances the effective bulk-band gap to 0.5 eV, the largest ever observed in TIs. In addition, we found that the system is no longer in the topological phase at m = 1, pointing to a topological phase transition between m = 1 and 2. These results demonstrate that utilization of naturally-occurring heterostructures is a new promising strategy for realizing exotic quantum phenomena and device applications of TIs.Comment: 5 pages, 5 figure

Unexpected Dirac-Node Arc in the Topological Line-Node Semimetal HfSiS

We have performed angle-resolved photoemission spectroscopy on HfSiS, which has been predicted to be a topological line-node semimetal with square Si lattice. We found a quasi-two-dimensional Fermi surface hosting bulk nodal lines, alongside the surface states at the Brillouin-zone corner exhibiting a sizable Rashba splitting and band-mass renormalization due to many-body interactions. Most notably, we discovered an unexpected Dirac-like dispersion extending one-dimensionally in k space - the Dirac-node arc - near the bulk node at the zone diagonal. These novel Dirac states reside on the surface and could be related to hybridizations of bulk states, but currently we have no explanation for its origin. This discovery poses an intriguing challenge to the theoretical understanding of topological line-node semimetals.Comment: 5 pages, 4 figures (paper proper) + 2 pages, figures (supplemental material

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles

BACKGROUND: In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. RESULTS: The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. CONCLUSION: The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles