Literature DB >> 16345469

Liquid chromatographic determination of dipicolinic Acid from bacterial spores.

A D Warth1.   

Abstract

Dipicolinic acid was determined by reverse-phase liquid chromatography. Elution was with 0.2 M potassium phosphate, pH 1.8, containing 1.5% tert-amyl alcohol or higher concentrations of lower alcohols or acetonitrile. The normal analytical range was 50 to 1,000 muM, which is equivalent to 0.1 to 1 mg of spores per ml with a relative standard error of 2 to 4% and a detection limit of <100 pmol. Dipicolinic acid was fully extracted from spores by heating at pH 1.8 for 10 min at 100 degrees C. Sporulating cultures may be analyzed in less than 20 min without separation of cells from media. Liquid chromatography was also used to detect dipicolinic acid in more complex substrates, e.g., guinea pig feces containing Metabacterium polyspora spores and canned food. Dipicolinic acid could be detected in unspoiled canned salmon containing <10 added Bacillus cereus spores per g.

Entities:  

Year:  1979        PMID: 16345469      PMCID: PMC291239          DOI: 10.1128/aem.38.6.1029-1033.1979

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  7 in total

1.  [Short note on Metabacterium polyspora].

Authors:  C F ROBINOW
Journal:  Z Tropenmed Parasitol       Date:  1957-03

2.  Colorimetric assay for dipicolinic acid in bacterial spores.

Authors:  F W JANSSEN; A J LUND; L E ANDERSON
Journal:  Science       Date:  1958-01-03       Impact factor: 47.728

3.  Rapid determination of dipicolinic acid in the spores of Clostridium species by gas-liquid chromatography.

Authors:  M W Tabor; J MacGee; J W Holland
Journal:  Appl Environ Microbiol       Date:  1976-01       Impact factor: 4.792

4.  Molecular structure of the bacterial spore.

Authors:  A D Warth
Journal:  Adv Microb Physiol       Date:  1978       Impact factor: 3.517

5.  Relationship between the heat resistance of spores and the optimum and maximum growth temperatures of Bacillus species.

Authors:  A D Warth
Journal:  J Bacteriol       Date:  1978-06       Impact factor: 3.490

6.  Polarographic determination of dipicolinic acid in the presence of bacterial spores and vegetative cells.

Authors:  G S Porter; M W Brown; M R Brown
Journal:  Biochem J       Date:  1967-02       Impact factor: 3.857

7.  Study of calcium dipicolinate release during bacterial spore germination by using a new, sensitive assay for dipicolinate.

Authors:  I R Scott; D J Ellar
Journal:  J Bacteriol       Date:  1978-07       Impact factor: 3.490

  7 in total
  7 in total

1.  Distribution of calcium and other elements in cryosectioned Bacillus cereus T spores, determined by high-resolution scanning electron probe x-ray microanalysis.

Authors:  M Stewart; A P Somlyo; A V Somlyo; H Shuman; J A Lindsay; W G Murrell
Journal:  J Bacteriol       Date:  1980-07       Impact factor: 3.490

2.  Endophytic Paenibacillus amylolyticus KMCLE06 Extracted Dipicolinic Acid as Antibacterial Agent Derived via Dipicolinic Acid Synthetase Gene.

Authors:  Kanmani Anandan; Ravishankar Rai Vittal
Journal:  Curr Microbiol       Date:  2018-11-29       Impact factor: 2.188

3.  Involvement of the spore coat in germination of Bacillus cereus T spores.

Authors:  P M Kutima; P M Foegeding
Journal:  Appl Environ Microbiol       Date:  1987-01       Impact factor: 4.792

4.  Propagation by sporulation in the guinea pig symbiont Metabacterium polyspora.

Authors:  E R Angert; R M Losick
Journal:  Proc Natl Acad Sci U S A       Date:  1998-08-18       Impact factor: 11.205

5.  Characterization of two "Metabacterium" sp. from the gut of rodents. 2. Heteroxenic cultivation and proof of dipicolinic acid in "M. polyspora".

Authors:  S Stünkel; J Alves; I Kunstýr
Journal:  Folia Microbiol (Praha)       Date:  1993       Impact factor: 2.099

6.  Nanopore back titration analysis of dipicolinic acid.

Authors:  Yujing Han; Shuo Zhou; Liang Wang; Xiyun Guan
Journal:  Electrophoresis       Date:  2014-10-03       Impact factor: 3.535

7.  A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid identification of Bacillus spores and classification of Bacillus species.

Authors:  Elon Correa; Royston Goodacre
Journal:  BMC Bioinformatics       Date:  2011-01-26       Impact factor: 3.169

  7 in total

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