A flexible mathematical model platform for studying branching networks: experimentally validated using the model actinomycete, Streptomyces coelicolor

Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium Streptomyces as a model we have developed a flexible mathematical model platform for the study of branched biological networks. Streptomyces fo...

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Published inPloS one Vol. 8; no. 2; p. e54316
Main Authors Nieminen, Leena, Webb, Steven, Smith, Margaret C M, Hoskisson, Paul A
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 18.02.2013
Public Library of Science (PLoS)
Subjects
Algorithms
Angiogenesis
Antibiotics
Biology
Cell division
Computer Simulation
Cues
Environment
Fermentation
Hyphae
Liquid culture
Mathematical analysis
Mathematical models
Mathematics
Medicine
Metabolism
Metabolites
Microorganisms
Microscopy
Models, Molecular
Morphology
Networks
Ordinary differential equations
Oxygen Consumption
Pharmacy
Reproducibility of Results
Soil dynamics
Soil microorganisms
Streptomyces
Streptomyces coelicolor
Streptomyces coelicolor - growth & development
Streptomyces coelicolor - physiology
Studies
Tips
Velocity
Online AccessGet full text

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Abstract Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium Streptomyces as a model we have developed a flexible mathematical model platform for the study of branched biological networks. Streptomyces form large aggregates in liquid culture that can impair industrial antibiotic fermentations. Understanding the features of these could aid improvement of such processes. The model requires relatively few experimental values for parameterisation, yet delivers realistic simulations of Streptomyces pellet and is able to predict features, such as the density of hyphae, the number of growing tips and the location of antibiotic production within a pellet in response to pellet size and external nutrient supply. The model is scalable and will find utility in a range of branched biological networks such as angiogenesis, plant root growth and fungal hyphal networks.
AbstractList Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium Streptomyces as a model we have developed a flexible mathematical model platform for the study of branched biological networks. Streptomyces form large aggregates in liquid culture that can impair industrial antibiotic fermentations. Understanding the features of these could aid improvement of such processes. The model requires relatively few experimental values for parameterisation, yet delivers realistic simulations of Streptomyces pellet and is able to predict features, such as the density of hyphae, the number of growing tips and the location of antibiotic production within a pellet in response to pellet size and external nutrient supply. The model is scalable and will find utility in a range of branched biological networks such as angiogenesis, plant root growth and fungal hyphal networks.
Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium Streptomyces as a model we have developed a flexible mathematical model platform for the study of branched biological networks. Streptomyces form large aggregates in liquid culture that can impair industrial antibiotic fermentations. Understanding the features of these could aid improvement of such processes. The model requires relatively few experimental values for parameterisation, yet delivers realistic simulations of Streptomyces pellet and is able to predict features, such as the density of hyphae, the number of growing tips and the location of antibiotic production within a pellet in response to pellet size and external nutrient supply. The model is scalable and will find utility in a range of branched biological networks such as angiogenesis, plant root growth and fungal hyphal networks.
Audience Academic
Author Smith, Margaret C M
Hoskisson, Paul A
Webb, Steven
Nieminen, Leena
AuthorAffiliation 4 Department of Biology, University of York, York, United Kingdom
Vanderbilt University Medical Center, United States of America
1 Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
2 Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom
3 MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, United Kingdom
AuthorAffiliation_xml – name: 4 Department of Biology, University of York, York, United Kingdom
– name: 1 Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
– name: 3 MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, United Kingdom
– name: 2 Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom
– name: Vanderbilt University Medical Center, United States of America
Author_xml – sequence: 1
  givenname: Leena
  surname: Nieminen
  fullname: Nieminen, Leena
  organization: Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
– sequence: 2
  givenname: Steven
  surname: Webb
  fullname: Webb, Steven
– sequence: 3
  givenname: Margaret C M
  surname: Smith
  fullname: Smith, Margaret C M
– sequence: 4
  givenname: Paul A
  surname: Hoskisson
  fullname: Hoskisson, Paul A
BackLink https://www.ncbi.nlm.nih.gov/pubmed/23441147$$D View this record in MEDLINE/PubMed
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2013 Hoskisson et al 2013 Hoskisson et al
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Conceived and designed the experiments: PAH LN SW MS. Performed the experiments: LN SW PAH. Analyzed the data: LN SW PAH. Contributed reagents/materials/analysis tools: LN PAH SW. Wrote the paper: PAH LN SW MS.
Competing Interests: The authors have declared that no competing interests exist.
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Snippet Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium...
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StartPage e54316
SubjectTerms Algorithms
Angiogenesis
Antibiotics
Biology
Cell division
Computer Simulation
Cues
Environment
Fermentation
Hyphae
Liquid culture
Mathematical analysis
Mathematical models
Mathematics
Medicine
Metabolism
Metabolites
Microorganisms
Microscopy
Models, Molecular
Morphology
Networks
Ordinary differential equations
Oxygen Consumption
Pharmacy
Reproducibility of Results
Soil dynamics
Soil microorganisms
Streptomyces
Streptomyces coelicolor
Streptomyces coelicolor - growth & development
Streptomyces coelicolor - physiology
Studies
Tips
Velocity
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Title A flexible mathematical model platform for studying branching networks: experimentally validated using the model actinomycete, Streptomyces coelicolor
URI https://www.ncbi.nlm.nih.gov/pubmed/23441147
https://www.proquest.com/docview/1330885770
https://search.proquest.com/docview/1312849790
https://pubmed.ncbi.nlm.nih.gov/PMC3575473
https://doaj.org/article/e6ee5cd1cc3d4153b006b401f41ba744
http://dx.doi.org/10.1371/journal.pone.0054316
Volume 8
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