Modeling,simulation, and embryology

Summary A delightful book to get the whole picture of simulation applications in developmental biology and easily readable for those who would like to overlook the field in one quick sweep. If you would like to get a more detailed perspective, a great number of literature references provides this opportunity.     

Thermophilic bacterial leaching of manganese dioxide

Summary Thermophilic bacterial leaching of low-grade manganese oxide ore was, demonstrated at 50°C and 70°C. A static culture system was used with cane molasses as the nutrient source. By employing batch cultures, with an acid wash to redissolve adsorbed Mn²⁺ at completion of each batch, the bacterial reduction could be driven to completion.     

Modeling of biofilm reactors with consecutive reactions

Modeling of biofilm reactors has been carried out by several authors. Most of the models use first-order or zero-order kinetics, because of the simplicity of the solution of the mathematical problem. However, the reaction kinetics for many practical situations is a non-linear Monod kinetics, which requires numerical solutions. This paper deals with the modeling of biofilm reactors and effectiveness factor calculations for a biofilm particle with Monod kinetics and two consecutive reactions. The model is applied to biological denitrification in a fluidized bed bioreactor, in which the liquid phase is assumed to be in plug flow. Effectiveness factors of biofilm are numerically calculated by solving the system of ODES by orthogonal collocation. Axial concentration profiles of nitrate and nitrite species are calculated and compared with experimental results.     

Direct and indirect mechanisms in the bacterial leaching of covellite

Summary Bacterial leachings of sample of covellite using a strain of Thiobacillus ferrooxidans in 9 K medium with and without iron were made at several pulp densities. Rates of solubilization with and without iron correspond to total and to direct mechanism respectively. Orders of reaction (at each pulp density) for each mechanism at two temperatures were calculated.     

Analysis, evaluation, and optimization of kinetic parameters for performance appraisal and design of UASB reactors

Studies have been undertaken to explore the applicability of different kinetic models for the performance appraisal of upflow anaerobic sludge blanket (UASB) reactors treating wastewater in the range of 300-4000 mg COD/l. Three kinetic models namely, Monod, Grau second-order, and Haldane model are considered for the analysis. Both linear and nonlinear regressions have been performed to examine the best-fit among the kinetic models. In this process, five error analysis methods have been used to analyze the data. Apart from optimization of kinetic coefficients with minimization of associated errors, prediction of effluent COD has also been undertaken to verify the applicability of kinetic models. In both the cases, Grau second-order model is found to be the best class of fit for wide range of data sets in UASB reactor.     

Modeling, docking, and simulation of the major facilitator superfamily

X-ray structures are known for three members of the Major Facilitator Superfamily (MFS) of membrane transporter proteins, thus enabling the use of homology modeling to extrapolate to other MFS members. However, before employing such models for, e.g., mutational or docking studies, it is essential to develop a measure of their quality. To aid development of such metrics, two disparate MFS members (NupG and GLUT1) have been modeled. In addition, control models were created with shuffled sequences, to mimic poor quality homology models. These models and the template crystal structures have been examined in terms of both static and dynamic indicators of structural quality. Comparison of the behavior of modeled structures with the crystal structures in molecular dynamics simulations provided a metric for model quality. Docking of the inhibitor forskolin to GLUT1 and to a control model revealed significant differences, indicating that we may identify accurate models despite low sequence identity between target sequences and templates.     

Modeling,analysis and simulation of ant-based network routing protocols

Using the metaphor of swarm intelligence, ant-based routing protocols deploy control packets that behave like ants to discover and optimize routes between pairs of nodes. These ant-based routing protocols provide an elegant, scalable solution to the routing problem for both wired and mobile ad hoc networks. The routing problem is highly nonlinear because the control packets alter the local routing tables as they are routed through the network. We mathematically map the local rules by which the routing tables are altered to the dynamics of the entire networks. Using dynamical systems theory, we map local protocol rules to full network performance, which helps us understand the impact of protocol parameters on network performance. In this paper, we systematically derive and analyze global models for simple ant-based routing protocols using both pheromone deposition and evaporation. In particular, we develop a stochastic model by modeling the probability density of ants over the network. The model is validated by comparing equilibrium pheromone levels produced by the global analysis to results obtained from simulation studies. We use both a Matlab simulation with ideal communications and a QualNet simulation with realistic communication models. Using these analytic and computational methods, we map out a complete phase diagram of network behavior over a small multipath network. We show the existence of both stable and unstable (inaccessible) routing solutions having varying properties of efficiency and redundancy depending upon the routing parameters. Finally, we apply these techniques to a larger 50-node network and show that the design principles acquired from studying the small model network extend to larger networks.     

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

Background

Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members.

Results

Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate.

Conclusion

In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members.

     

Modeling bacterial growth responses

Summary The main steps of modeling bacterial growth responses are summarized and a new model for growth curves is shown. Its advantages are analyzed from some theoretical and practical points of view. The new model fits better and has more advantageous statistical properties than the Gompertz curve.     

Isolation,screening, and optimization of bacterial strains for novel transglutaminase production

Transglutaminases are a class of transferases known to form isopeptide bond between glutamine and lysine residues in a protein molecule. Increasing demand for transglutaminase in food and other industries and its low productivity have compelled researchers to isolate and screen micro-organisms with potential to produce it. In the present investigation around 200 isolates were screened for extracellular secretion of microbial transglutaminase (MTGase). Isolate B4 showed enzyme activity of 1.71?±?0.2?U/mL followed by isolate C2 which showed 1.61?±?0.17?U/mL activity, comparable with the activity of industrially used microbial strains. Biochemical analysis along with 16S r-RNA sequencing revealed these isolates (B4 and C2) to be Bacillus nakamurai and a variant of Bacillus subtilis, respectively. Amongst the various production media screened, a medium containing starch and peptone was found best for MTGase production. Correlation between growth, enzyme production, and sugar utilization was also studied and maximum enzyme production was obtained after 48 to 60?hr. Highest MTGase titer (3.95?±?0.03?U/mL for B4 and 2.65?±?0.17?U/mL for C2) was obtained by optimization of parameters. The enzyme was characterized for temperature and pH optima, pH and thermal stability, and effect of metal ions, suggesting its potential use in future applications.     

Modeling and estimating bacterial lag phase

A branching process model of a bacterial population with initial lag phase is developed. Approximations are established in order to facilitate parameter estimation. The validity of approximations and estimation procedures is tested with simulated data.     

Modeling, optimization, and computer control of the cephalosporin C fermentation process

In this study, a cephalosporin C producing strain, Cephalosporium acremonium (ATCC 36225), was chosen to determine the optimal conditions that maximize antibiotic production in a mixed substrate of glucose and sucrose. A model for cell growth and cephalosporin C production at different pH and temperature was developed and the associated parameters were evaluated experimentally. Pontryagin's maximum principle, in conjunction with the model, was used to predict the optimal temperature and pH control profiles to maximize the production of antibiotic.     

An arsenic(III)-oxidizing bacterial population: selection,characterization, and performance in reactors

AIMS: To select an autotrophic arsenic(III)-oxidizing population, named CASO1, and to evaluate the performance of the selected bacteria in reactors. METHODS AND RESULTS: An As(III)-containing medium without organic substrate was used to select CASO1 from a mining environment. As(III) oxidation was studied under batch and continuous conditions. The main organisms present in CASO1 were identified with molecular biology tools. CASO1 exhibited significant As(III)-oxidizing activity between pH 3 and 8. The optimum temperature was 25 degrees C. As(III) oxidation was still observed in the presence of 1000 mg l(-1) As(III). In continuous culture mode, the As(III) oxidation rate reached 160 mg l(-1) h(-1). The CASO1 consortium contains at least two organisms - strain b3, which is phylogenetically close to Ralstonia picketii, and strain b6, which is related to the genus Thiomonas. The divergence in 16S rDNA sequences between b6 and the closest related organism was 5.9%, suggesting that b6 may be a new species. CONCLUSIONS: High As(III)-oxidizing activity can be obtained without organic nutrient supply, using a bacterial population from a mining environment. SIGNIFICANCE AND IMPACT OF THE STUDY: The biological oxidation of arsenite by the CASO1 population is of particular interest for decontamination of arsenic-contaminated waste or groundwater.     

Modeling and optimization of fermentative hydrogen production

Biohydrogen is a sustainable energy resource due to its potentially higher efficiency of conversion to usable power, non-polluting nature and high energy density. The purpose of modeling and optimization is to improve, analyze and predict biohydrogen production. Biohydrogen production depends on a number of variables, including pH, temperature, substrate concentration and nutrient availability, among others. Mathematical modeling of several distinct processes such as kinetics of microbial growth and products formation, steady state behavior of organic substrate along with its utilization and inhibition have been presented. Present paper summarizes the experimental design methods used to investigate effects of various factors on fermentative hydrogen production, including one-factor-at-a-time design, full factorial and fractional factorial designs. Each design method is briefly outlined, followed by the introduction of its analysis. In addition, the applications of artificial neural network, genetic algorithm, principal component analysis and optimization process using desirability function have also been highlighted.     

Performance and bacterial compositions of aged refuse reactors treating mature landfill leachate

Aged landfill leachates become more refractory over time and difficulty to treat. Recently, aged refuse bioreactors show great promise in treating leachates. In this study, aged refuse bioreactors were constructed to simulate landfill leachate degradation process. The characteristics of leachate were: COD_cr, ∼2200 mg/L; BOD₅, ∼280 mg/L; total nitrogen, ∼2030 mg/L; and ammonia, ∼1900 mg/L. Results showed that bioreactor could remove leachate pollutants effectively at hydraulic loading of 20 L/m³ d. The removal rate reduced when hydraulic loading doubled or temperature lowered. Effluent recirculation could alleviate the temperature effect. Combining aged refuse and slag biofilters could treat leachate more efficiently. Pyrosequencing analysis indicated that bacteria from Pseudomonas, Lysobacter, Bacillus and δ-proteobacter, Flexibacteraceae were more abundant in the samples. The Shannon index decreased at lower temperature, while evenness and equitability increased with recirculation. We suggest that filter medium and temperature may be the main factors for shaping bacterial community structure.     

Production optimization for concentration and volume-limited fed-batch reactors in biochemical processes

Bioprocess and Biosystems Engineering - Since a very slight violation of constraint could cause process safety and product quality problems in biochemical processes, an adaptive approach of...