• Journal of Microbiology
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• 제44권6호
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• pp.600-606
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• 2006

Spore forming actinobacteria (sporoactinobacteria) isolated from soils with an acidic pH in Pinus thunbergii forests and coal mine waste were subjected to taxonomic characterization. For the isolation of acidophilic actinobacteria, acidified starch casein agar (pH adjusted to 4-5) was used. The numbers of actinobacteria growing in acidic media were between $3.2{\times}10^4$ and $8.0{\times}10^6$ CFU/g soil. Forty three acidophilic actinobacterial strains were isolated and their 16S rDNA sequences were determined. The isolates were divided into eight distinctive phylogenetic clusters within the variation encompassed by the family Streptomycetaceae. Four clusters among them were assigned to the genus Streptacidiphilus, whereas the remaining four were assigned to Streptomyces. The clusters belonging to either Streptomyces or Streptacidiphilus did not form a monophyletic clade. The growth pH profiles indicated that the representative isolates grew best between pH 5 and 6. It is evident from this study that acidity has played a critical role in the differentiation of the family Streptomycetaceae, and also that different mechanisms might have resulted in the evolution of two groups, Streptacidiphilus (strict acidophiles) and neutrotolerant acidophilic Streptomyces. The effect of geographic separation was clearly seen among the Streptacidiphilus isolates, which may be a key factor in speciation of the genus.

• Journal of Microbiology
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• 제33권2호
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• pp.95-102
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• 1995

A probability identification matrix of acidophilic Streptomyces was constructed. The phenetic data of the strains were derived from numerical classification described by Seong et al. The minimum number of diagnostic characters was determined using computer programs for calculation of different separation indices. The resulting matrix consisted of 25 clusters versus 53 characters. Theoretical evaluation of this matrix was achieved by estimating the chuster overlap and the identification scores for the Hypothetical Median Organisms (HMO) and for the representatives of each cluster. Cluster overlap was found to be relatively small. Identification scores for the HMO and the randomly selected representatives of each cluster were satisfactory. The matrix was assessed practically by applying the matrix to the identification of unknown isolates. Of the unknown isolates, 71.9% were clearly identified to one of eight clusters. The numerical classification data was also used to design a selective isolation medium for antibiotic-producing organisms. Four chemical substances including 2 antibiotics were determined by the DLACHAR program as diagnostic for the isolation of target organisms which have antimicrobial activity against Micrococcus luteus. It was possible to detect the increased rate of selective isolation on the synthesized medium. Theresults show that the numerical phenetic data can be applied to a variety of purposes, such as construction of identification matrix and selective isolation medium for acidophilic antinomycetes.