Rule-based computing system for microbial interactions and communications: Evolution in virtual bacterial populations

Gregory, Richard I.; Saunders, Venetia A.; Saunders, J. R.

doi:10.1016/j.biosystems.2007.09.002

Cited by 8 publications

(9 citation statements)

References 14 publications

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“…patible plasmid(s). A collection of tagged bit strings ("tags") (see Gregory et al (2007)) make up the functional genome. Tags are abstract genes, a tag consists of a bit string and an assigned category or type.…”

Section: Cell Interactions and R Plasmid Transfer By Conjugationmentioning

confidence: 99%

“…The purpose of this study is to develop and validate an individual-based model (IbM), COSMIC-rules (see Gregory et al, 2006Gregory et al, , 2007, to simulate plasmid transfer events and incompatibility in bacterial populations. The IbM is used here to develop biologically-realistic simulations of plasmid transfer with predictive potential, for example in examining the spread of antibiotic resistance in clinically-important bacteria.…”

Section: Introductionmentioning

confidence: 99%

“…COSMIC-rules models three levels: the genome, the bacterial cell and the environment (for details see Gregory et al, 2007). The genome comprises genes or sets of genes, each represented by a discrete bit string.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Rule-based modelling of conjugative plasmid transfer and incompatibility

Gregory

Saunders

2008

Biosystems

Self Cite

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Section: Cell Interactions and R Plasmid Transfer By Conjugationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rule-based modelling of conjugative plasmid transfer and incompatibility

Gregory

Saunders

2008

Biosystems

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“…To our knowledge, there are no examples of the integration of interaction effects in such models to the level where they can be used to predict the performance of mixedculture fermentations. However, Gregory et al developed a computing system that allows the modeling of interactions and evolution in bacterial communities (60,61). This model includes several aspects, such as growth stimulatory interactions, antibiotic sensitivity, the occurrence of antibiotic-resistant mutants, and growth on nutrients derived from killed cells, in one model.…”

Section: Descriptive and Predictive Modeling In The Genomics Eramentioning

confidence: 99%

Unraveling Microbial Interactions in Food Fermentations: from Classical to Genomics Approaches

Sieuwerts

Bok

Hugenholtz

et al. 2008

Appl Environ Microbiol

266

178

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3Fermentation, the microbial degradation of organic compounds without net oxidation, is an important process in the global carbon cycle and is also exploited worldwide for the production and preservation of food. It is one of the oldest food-processing technologies known, with some records dating back to 6,000 B.C. (50). The link between food and microbiology was laid by Pasteur, who found that yeasts were responsible for alcoholic fermentation (106). Since that discovery, scientific and industrial interests in food microbiology started to grow and continue to increase today. The number of food products that rely on fermentation in one or more steps of their production is tremendous. They form an important constituent of the daily diet and rank among the most innovative product categories in the food industry.Most of the important microorganisms applied in the production of fermented foods have been studied for decades, yielding a wealth of information on their physiology and genetics in relation to product functionalities, such as the development of flavor, taste, and texture. The recent emergence of genomics has opened new avenues for the systematic analysis of microbial metabolism and the responses of microorganisms to their environment. Additionally, genomics has boosted research on important food microbes (22,90,93). Much of this research focuses on the performance of a single strain, including its interactions with the food matrix. However, food fermentations are typically carried out by mixed cultures consisting of multiple strains or species. Population dynamics play a crucial role in the performance of mixed-culture fermentations, and for many years, studies on mixed-culture food fermentations have focused on analyzing population dynamics using classical and molecular methods. Many of these studies are mainly descriptive, and relatively little is known about the mechanisms governing population dynamics in general and the molecular interactions that occur between the consortium members in particular. The availability of genome sequences for several species that are of industrial importance as well as technological advances in functional genomics enable new approaches to study food microbiology beyond the single species level and allow an integral analysis of the interactions and metabolic activity in mixed cultures.Here we review the current knowledge on important food fermentation processes, focusing on the bacterial interactions.In addition, we illustrate how genomics approaches may contribute to the elucidation of the interaction networks between microbes, including interactions with the food environment. This information may find application in the industry through rational optimization and increased control over mixed-culture fermentations.

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“…Therefore, in this study, a virtual computer-based system designed to study the evolution of a community of ribozyme-like agents is presented. The system is based on rules in a similar manner to some of the earlier computing systems that have treated the evolution of bacterial populations (Vlachos et al 2006;Gregory et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Dynamics of a Laterally Evolving Community of Ribozyme-Like Agents as Studied with a Rule-Based Computing System

Jalasvuori

Bamford

2009

Orig Life Evol Biosph

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The very early forms of life probably comprised ribozyme-like agents that were able to catalyze reactions and serve as templates for their own replication. The early evolution has also been suggested to occur mainly horizontally between proto-cells or inorganic compartments rather than vertically from parent cell to their dividing siblings. In order to study the evolutionary dynamics of such a community a rule-based computing system entitled as PrimordialEvo was developed. The system simulates a three dimensional matrix of compartments in which replicators, resource collectors and various other actors thrive. Horizontal movement between compartments may be due to genetically induced vesicle formation or random drift. Analysis of the simulation experiments suggests that active sharing of innovations between compartments is important for the overall reproductive success of life. The capability of natural selection to favor genes in the system was also tested, and, for example, the frequency of anti-parasites was observed to increase when parasites were allowed to emerge.

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Rule-based computing system for microbial interactions and communications: Evolution in virtual bacterial populations

Cited by 8 publications

References 14 publications

Rule-based modelling of conjugative plasmid transfer and incompatibility

Rule-based modelling of conjugative plasmid transfer and incompatibility

Unraveling Microbial Interactions in Food Fermentations: from Classical to Genomics Approaches

Dynamics of a Laterally Evolving Community of Ribozyme-Like Agents as Studied with a Rule-Based Computing System

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