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  • Title: 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.
    Author: Schmidt JK, König B, Reichl U.
    Journal: Biotechnol Bioeng; 2007 Mar 01; 96(4):738-56. PubMed ID: 16937400.
    Abstract:
    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.
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