Interactions between species and environments from incomplete information

There are two contradictory aspects of the adaptive process in evolution. The first is that species must optimally increase their own fitness in a given environment. The second is that species must maintain their variation to be ready to respond to changing environments. In a strict sense, these two aspects might consider to be mutually exclusive. If species are optimally adapted, then the variation in the species that is suboptimal decreases and vice versa. To resolve this dilemma, species must find a balance between optimal adaptation and robust adaptation. Finding the balance between these processes requires both the local and global complete, static information. However, the balance between the processes must be dynamic. In this study, we propose a model that illustrates dynamic negotiation between the global and local information using lattice theory. The dynamic negotiation between these two levels results in an overestimate of fitness for each species. The overestimation of fitness in our model represents the multiplicity of fitness which is sometimes discussed as the exaptation. We show that species in our model demonstrate the power law of the lifespan distribution and 1/f fluctuation for the adaptive process. Our model allows for a balance between optimal adaptation and robust adaptation without any arbitrary parameters.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

PRASA: An integrated web server that analyzes protein interaction types

This work presents the Protein Association Analyzer (PRASA) (http://zoro.ee.ncku.edu.tw/prasa/) that predicts protein interactions as well as interaction types. Protein interactions are essential to most biological functions. The existence of diverse interaction types, such as physically contacted or functionally related interactions, makes protein interactions complex. Different interaction types are distinct and should not be confused. However, most existing tools focus on a specific interaction type or mix different interaction types. This work collected 7234058 associations with experimentally verified interaction types from five databases and compiled individual probabilistic models for different interaction types. The PRASA result page shows predicted associations and their related references by interaction type. Experimental results demonstrate the performance difference when distinguishing between different interaction types. The PRASA provides a centralized and organized platform for easy browsing, downloading and comparing of interaction types, which helps reveal insights into the complex roles that proteins play in organisms.     

Testing attachment point theory: diatom attachment on microtextured polyimide biomimics

Abstract

This paper explores diatom attachment to a range of laser etched polyimide surfaces to directly test ‘attachment point theory’. Static bioassays were conducted on microtextured polyimide surfaces using four diatom species, Fallacia carpentariae, Nitzschia cf. paleacea, Amphora sp. and Navicula jeffreyi with cell sizes ranging from 1 – 14 μm. The microtextured polyimides were modelled from natural fouling resistant bivalve surfaces and had wavelengths above, below and at the same scale as the diatom cell sizes. Diatoms attached in significantly higher numbers to treatments where the numbers of attachment points was highest. The lowest diatom attachment occurred where cells were slightly larger than the microtexture wavelength, resulting in only two theoretical points of attachment. The results support attachment point theory and highlight the need to address larval/cell size in relation to the number of attachment points on a surface. Further studies examining a range of microtexture scales are needed to apply attachment point theory to a suite of fouling organisms and to develop structured surfaces to control the attachment and development of fouling communities.     

The CQ ratio of surface energy components influences adhesion and removal of fouling bacteria

The interaction energy between bacteria and substrata with different surface energies was modelled by the extended DLVO (Derjaguin, Landau, Verwey and Overbeek) theory. The modeling results revealed that the interaction energy has a strong correlation with the CQ (Chen and Qi) ratio, which is defined as the ratio of the Lifshitz–van der Waals (LW) apolar to the electron donor surface energy components of substrata. Both modeling and experimental results with different bacteria including P. fluorescens, Cobetia marina and Vibrio alginolyticus demonstrated that if the LW surface energy of bacteria is larger than that of water, which is the case for most bacteria, the number of adhered bacteria decreases with a decreasing CQ ratio while bacterial removal rate increases with a decreasing CQ ratio. However, if the LW surface energy of bacteria is less than that of water, the opposite results are obtained. The CQ ratio gives a clear direction for the design of anti-biofouling and biofouling-release coatings through surface modification.     

Catalytic activity of iron phthalocyanine for the oxidation of thiocyanate and L-cysteine anchored on Au(111) clusters

ABSTRACT

We studied the oxidation reactions of thiocyanate and L-cysteine on iron phthalocyanine (FePc) coupled via a bridging ligand of the 4-mercatopyridine (4MP) type to a gold cluster (Au₂₆), aiming to simulate a modified gold electrode. Theoretical models have been used based on the framework of density functional theory. Several mechanistic pathways are explored for the study of these reactions, finding that the most favorable mechanism involves an electron transfer process as the rate-determining step. Along the process, the ability of the gold cluster to act as an electron acceptor facilitating the reactions was detected. In addition, the proposed models presented a correlation between the energy obtained for the rate-determining step of the reaction and the experimental oxidation potentials of the thiocyanate and L-cysteine.     

Electroosmotic Flow in Nanoscale Parallel-plate Channels: Molecular Simulation Study and Comparison with Classical Poisson–Boltzmann Theory

Molecular dynamics simulations have been carried out for simple electrolyte systems to study the electrokinetically driven osmotic flow in parallel-plate channels of widths ～10–120?nm. The results are compared with the classical theory predictions based on the solution to the Poisson–Boltzmann equation. We find that despite some of the limitations in the Poisson–Boltzmann equation, such as assumption of the Boltzmann distribution for the ions, the classical theory captures the general trend of the variations of the osmotic flow with channel width, as characterized by the mobility of the fluid in channels between ～10 and 120?nm at moderate to low ion concentration. At moderate concentration (corresponding to relatively low surface potential), the classical theory is almost quantitative. The theory and simulation show more disagreement at low concentration, primarily caused by the high surface potential where the assumption of Boltzmann distribution becomes inaccurate. We discuss the limitations of the Poisson–Boltzmann equation as applied to the nanoscale channels.