Simulation of growth of a filamentous fungus in 3 dimensions

Lejeune, Robert; Baron, Gino V.

doi:10.1002/(sici)1097-0290(19970120)53:2<139::aid-bit3>3.0.co;2-p

Cited by 42 publications

(33 citation statements)

References 20 publications

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“…An initial model was based on diffusion–reaction of a hypothetical intracellular growth-limiting component (Yang et al 1992a); this model was later extended to include the diffusion of limiting substrates and fragmentation due to shear forces (Meyerhoff et al 1995). Basing growth on a tip extension rate depending on oxygen concentration, a similar model combined microscopic morphology with analysis of solute profiles along the pellet radius and the fractal dimension (Lejeune and Baron 1997). Macroscopic (fermentation) models focus instead on the effects of mass transport on growth and production in a reactor, providing e.g.…”

Section: State Of the Art In Growth Modeling Of Filamentous Microorgamentioning

confidence: 99%

“…Oxygen concentrations in concentric shells obtained with the three-dimensional model were subsequently compared with the radial (one-dimensional, 1D) oxygen profile obtained assuming spherical symmetry (Lejeune and Baron 1997). Obviously, the 3D model was computationally much more intensive than the 1D counterpart, but nevertheless resulted in a very similar oxygen concentration profile.…”

Section: Mathematical Model Descriptionmentioning

confidence: 99%

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Structured morphological modeling as a framework for rational strain design of Streptomyces species

Celler

Picioreanu

Loosdrecht

et al. 2012

Antonie van Leeuwenhoek

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Successful application of a computational model for rational design of industrial Streptomyces exploitation requires a better understanding of the relationship between morphology—dictated by microbial growth, branching, fragmentation and adhesion—and product formation. Here we review the state-of-the-art in modeling of growth and product formation by filamentous microorganisms and expand on existing models by combining a morphological and structural approach to realistically model and visualize a three-dimensional pellet. The objective is to provide a framework to study the effect of morphology and structure on natural product and enzyme formation and yield. Growth and development of the pellet occur via the processes of apical extension, branching and cross-wall formation. Oxygen is taken to be the limiting component, with the oxygen concentration at the tips regulating growth kinetics and the oxygen profile within the pellet affecting the probability of branching. Biological information regarding the processes of differentiation and branching in liquid cultures of the model organism Streptomyces coelicolor has been implemented. The model can be extended based on information gained in fermentation trials for different production strains, with the aim to provide a test drive for the fermentation process and to pre-assess the effect of different variables on productivity. This should aid in improving Streptomyces as a production platform in industrial biotechnology. Electronic supplementary material The online version of this article (doi:10.1007/s10482-012-9760-9) contains supplementary material, which is available to authorized users.

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Section: State Of the Art In Growth Modeling Of Filamentous Microorgamentioning

confidence: 99%

Section: Mathematical Model Descriptionmentioning

confidence: 99%

Structured morphological modeling as a framework for rational strain design of Streptomyces species

Celler

Picioreanu

Loosdrecht

et al. 2012

Antonie van Leeuwenhoek

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“…Knudsen & Stack [89] introduced the idea of a simulation model for hyphal growth of a fungal hyperparasite through soil and use of the model to predict the incidence of hyperparasitism of sclerotia of certain soilborne plant pathogens. Lejeune and Baron [90] and Lejeune et al [91] simulated the 3D growth of the filamentous fungus Trichoderma reesei, based on properties of mycelial growth (total hyphal length and total number of tips). Cross and Kenerley [92], using a combination of the Ratkowsky and Arrhenius equations, modeled colony growth of T. virens at different temperatures.…”

Section: Simulation Modeling Of Biocontrol Agent Performancementioning

confidence: 99%

Ecological Complexity and the Success of Fungal Biological Control Agents

Knudsen

Dandurand

2014

Advances in Agriculture

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Fungal biological control agents against plant pathogens, especially those in soil, operate within physically, biologically, and spatially complex systems by means of a variety of trophic and nontrophic interspecific interactions. However, the biocontrol agents themselves are also subject to the same types of interactions, which may reduce or in some cases enhance their efficacy against target plant pathogens. Characterization of these ecologically complex systems is challenging, but a number of tools are available to help unravel this complexity. Several of these tools are described here, including the use of molecular biology to generate biocontrol agents with useful marker genes and then to quantify these agents in natural systems, epifluorescence and confocal laser scanning microscopy to observe their presence and activity in situ, and spatial statistics and computer simulation modeling to evaluate and predict these activities in heterogeneous soil habitats.

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“…From this simulation, it is possible to extend a model describing the kinetics of hyphal extension and stochastic branching to three dimensions. This model could be used to simulate the formation of a pellet from one or more spores [38]. A population model has been used to analyze single hyphal growth and fragmentation in submerged cultures.…”

Section: Modeling In Fungal Morphologymentioning

confidence: 99%

Application of Actinobacterial and Fungal Morphology on the Design of Operating Strategies in Bioprocess Development

Panda

Rameshaiah²

2009

TOBIOTJ

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Various options in biotechnology have been exercised to produce industrially important metabolites from filamentous organisms. To select a suitable production strategy, the direct and indirect roles of morphological parameters in controlling bioprocess variables are observed. Some progress has been made in quantitation of morphology.Useful correlations have been reported in the literature in this avenue. Of course, some of the models, with proper modification, can be used to explain the morphological phenomena. This review is concerned with the application of morphological variables to correlate with bioprocess parameters for explaining optimal production strategy.

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Simulation of growth of a filamentous fungus in 3 dimensions

Cited by 42 publications

References 20 publications

Structured morphological modeling as a framework for rational strain design of Streptomyces species

Structured morphological modeling as a framework for rational strain design of Streptomyces species

Ecological Complexity and the Success of Fungal Biological Control Agents

Application of Actinobacterial and Fungal Morphology on the Design of Operating Strategies in Bioprocess Development

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