A novel concept combining experimental and mathematical analysis for the identification of unknown interspecies effects in a mixed culture.

Bacteria in natural habitats only occur in consortia together with various other species. Characterization of bacterial species, however, is normally done by laboratory testing of pure isolates. Any interactions that might appear during growth in mixed-culture are obviously missed by this approach. Existing experimental studies mainly focus on two-species mixed cultures with species specifically chosen for their known growth characteristics, and their anticipated interactions. Various theoretical mathematical studies dealing with mixed cultures and possible interspecies effects exist, but often models cannot be validated due to a lack of experimental data. Here, we present a concept for the identification of interspecies effects in mixed cultures with arbitrary and unknown single-species properties. Model structure and parameters were inferred from single-species experiments for the reproduction of mixed-culture experiments by simulation. A mixed culture consisting of the three-species Pseudomonas aeruginosa, Burkholderia cepacia, and Staphylococcus aureus served as a model system. For species-specific enumeration a quantitative terminal restriction length polymorphism (qT-RFLP) assay was used. Based on models fitted to single-species cultivations, the outcome of mixed-culture experiments was predicted. Deviations of simulation results and experimental findings were then used to design additional single-cell experiments, to modify the corresponding growth kinetics, and to update model parameters. Eventually, the resulting mixed-culture dynamics was predicted and compared again to experimental results. During this iterative cycle, it became evident that the observed coexistence of P. aeruginosa and B. cepacia in mixed-culture chemostat experiments cannot be explained on the basis of glucose as the only substrate. After extension of growth kinetics, that is, for use of amino acids as secondary substrates, mixed-culture simulations represented the experimental findings very well. According to the model structure, as motivated by single-species experiments, the growth of P. aeruginosa and B. cepacia on glucose and amino acids could be assumed to be independent of each other. In contrast, both substrates are taken up simultaneously by S. aureus.

Characterization of a three bacteria mixed culture in a chemostat: evaluation and application of a quantitative terminal-restriction fragment length polymorphism (T-RFLP) analysis for absolute and species specific cell enumeration.

Growth dynamics of Pseudomonas aeruginosa, Burkholderia cepacia, and Staphylococcus aureus in a batch and chemostat, were investigated as a laboratory model system for persistent infections in cystic fibrosis. Most species-specific enumeration methods for mixed cultures are laborious or only qualitative, and therefore impede generation of quantitative data required for validation of mathematical models. Here, a quantitative T-RFLP method was evaluated and applied for specific and absolute cell number enumerations. The method was tested to be unbiased by quantitative sample composition and allowed reproducible enumerations of mixed cultures. For assay validation, samples of defined concentration containing one, two or three species were quantified. Logarithmically transformed absolute cell numbers of single-species dilutions were linear within a lower working range of 10(4)-10(6) cfu/mL (species-dependent) and an upper working range of 10(10) cfu/mL. Quantifications of single species (10(6)-10(10) cfu/mL) spiked with one or two other species agreed well with single species controls. Differences between slopes of first order linear regression of spiked and pure dilution series were insignificant. Coefficient of variation of defined mixed replicates was maximum 4.39%, of a three-species chemostat it was maximum 1.76%. T-RFLP monitoring of pure cultures in parallel shake flasks and of a three-species mixed chemostat gave very consistent results. Coexistence of at least two species after a time period equivalent to more than 33 volume exchanges was found. This result was not predicted from pure cultures clearly indicating the need for quantitative mixed culture experiments to better understand microbial growth dynamics and for mathematical model validation.

Coexistence in the chemostat as a result of metabolic by-products.

Classical chemostat models assume that competition is purely exploitative and mediated via a common, limiting and single resource. However, in laboratory experiments with pathogens related to the genetic disease Cystic Fibrosis, species specific properties of production, inhibition and consumption of a metabolic by-product, acetate, were found. These assumptions were implemented into a mathematical chemostat model which consists of four nonlinear ordinary differential equations describing two species competing for one limiting nutrient in an open system. We derive classical chemostat results and find that our basic model supports the competitive exclusion principle, the bistability of the system as well as stable coexistence. The analytical results are illustrated by numerical simulations performed with experimentally measured parameter values. As a variant of our basic model, mimicking testing of antibiotics for therapeutic treatments in mixed cultures instead of pure ones, we consider the introduction of a lethal inhibitor, which cannot be eliminated by one of the species and is selective for the stronger competitor. We discuss our theoretical results in relation to our experimental model system and find that simulations coincide with the qualitative behavior of the experimental result in the case where the metabolic by-product serves as a second carbon source for one of the species, but not the producer.