Quantitative analysis and medium components optimizing for culturing a fastidious bacterium Christensenella minuta
bioRxiv(2019)
Abstract
is a heritable bacterium with controversial physiologies associating with both obesity and potential pathogenicity. Since this bacterium is fastidious to culture, it is hardly to well understand its biological feature. We develop a strategy for statistical analysis of this low abundant strain and optimize culture condition to make a significant improvement on its biomass and facilitate the researches about the metabolism and function of this bacterium. Basing on the fluorogenic quantitative technology, a quantitative approach was successfully constructed for by plotting t value from fluorescence quantitative PCR against the logarithm of concentration gradient of plasmids containing 16S rDNA of the strain. This method exhibited to have specificity on analyzing the strain biomass statistically. For improving the strain biomass, “komodo” predicted to optimize medium components and metabonomics analysis explored the catabolites addition effects on culture improvement. With the aid of Plackett-Burman and Box-Behnken in Design-Expert 8.0.6, the PB and response surface experiment were designed and analyzed from the single factor results. On the modified GAM medium, the strain concentration was found increasing markedly by 10 times. The addition of some amino acids, vitamins and inorganic salts has contributions for the strain multiplication, especially L-cysteine, VB6 and NaCl. The addition of 55 mg/L of L-cysteine, 20.5 mg/L VB6 and 55 g/L NaCl into the modified GAM medium increased the biomass by 3.59 times compared to the biomass on only modified GAM medium according to the response surface experiment. Through the newly constructed method, we successfully analyzed the amount of and obtained a novel medium to increase biomass significantly.
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Key words
<italic>Christensenella minuta</italic>,Fastidious bacterium,Statistical analysis,Fluorescence quantitative PCR,Medium components optimizing,Metabonomics analysis
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