Identification of Bacteria by Computer: General Aspects and Perspectives

Lapage, S. P.; Bascomb, Shoshana; Willcox, W. R.; Curtis, Michael

doi:10.1099/00221287-77-2-273

Cited by 164 publications

(74 citation statements)

References 6 publications

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“…After various tests it was suggested and the features agreed with the description of B. subtilis in Bergey's Manual of Systematic Bacteriology [13]. It was also identified as B. subtilis with 99.9% identity by API 50 CHB [14,22] and was also characterized and identified by using a bioinformatics tool PIB (Probabilistic Identification of Bacteria) [15] that suggests the organism was B. subtilis (ID=0.9760). B. subtilis was cultured in nutrient broth and incubated in Psychrotherm IncubatorShaker at 37°C for 22-24 hours until the absorbance of growing culture reached 1.5-1.8.…”

Section: Methodsmentioning

confidence: 99%

Protease activity of extracellular enzyme produced by B. subtilis isolated from soil

Alam¹,

Uddin²,

Rahman³

et al. 2017

IJEAB

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Section: Methodsmentioning

confidence: 99%

Protease activity of extracellular enzyme produced by B. subtilis isolated from soil

Alam¹,

Uddin²,

Rahman³

et al. 2017

IJEAB

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“…This technique is based on a conditional probability model and was used by Dybowski & Franklin (1968) to identify enterobacteria. S. P. Lapage and colleagues further developed the method to its most common implementation in a series of reports Lapage et al, 1973; and used it to create a discrimination procedure for strains of Gramnegative, aerobic, rod-shaped bacteria. Wayne et al (1984) used these developments to derive a diagnostic probability matrix, which they used to classify slowly growing Mycobacterium species based on biochemical test results.…”

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confidence: 99%

Computer-assisted pattern recognition model for the identification of slowly growing mycobacteria including Mycobacterium tuberculosis

Plikaytis

Shinnick

1992

Journal of General Microbiology

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We present a computerized pattern recognition model used to speciate mycobacteria based on their restriction fragment length polymorphism (RFLP) banding patterns. DNA fragment migration distances were normalized to minimize lane-to-lane variability of band location both within and among gels through the inclusion of two internal size standards in each sample. The computer model used a library of normalized RFLP patterns derived from samples of known origin to create a probability matrix which was then used to classify the RFLP patterns from samples of unknown origin. The probability matrix contained the proportion of bands that fell within defined migration distance windows for each species in the library of reference samples. These proportions were then used to compute the likelihood that the banding pattern of an unknown sample corresponded to that of each species represented in the probability matrix. As a test of this process, we developed an automated, computer-assisted model for the identification of Mycobacterium species based on their normalized RFLP banding patterns. The probability matrix contained values for the M. tuberculosis complex, M. avium, M. intraceffufare, M. kansasii and M. gordonae species. Thirty-nine independent strains of known origin, not included in the probability matrix, were used to test the accuracy of the method in classifying unknowns: 37 of 39 (94.9%) were classified correctly. An additional set of 16 strains of known origin representing species not included in the model were tested to gauge the robustness of the probability matrix. Every sample was correctly identified as an outlier, i.e. a member of a species not included in the original matrix. This strategy may be readily adapted to other chromatographic and electrophoretic systems that generate peak profiles or banding patterns.

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“…It also lists the biochemical tests that are incompatible with the taxon chosen as the best biochemical fit. It is based on the "normalized likelihood" method of Lapage et al (9,10,14). STRAIN MATCHER does a "strain by strain" analysis and compares the test strain to over 11,000 individual strains in the database.…”

Section: Methodsmentioning

confidence: 99%

First Case of Septicemia Due to a Strain Belonging to Enteric Group 58 ( Enterobacteriaceae ) and Its Designation as Averyella dalhousiensis gen. nov., sp. nov., Based on Analysis of Strains from 20 Additional Cases

et al. 2005

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When enteric group 58 was first described as a distinct new group of Enterobacteriaceae in 1985, there were only five known human isolates: four from wounds and one from feces. In 1996, we investigated the first blood isolate of enteric group 58, a case of sepsis in a 33-year-old woman receiving total parenteral nutrition. Fifteen additional clinical isolates have since been identified at CDC, including several recognized from a collection of “unidentified” strains dating back to 1973. All strains were characterized with a standard set of 49 biochemical tests used for Enterobacteriaceae , and the results were analyzed to determine phenotypic relatedness and best taxonomic fit. Antibiograms were determined as a taxonomic tool. Original identifications provided by submitting laboratories encompassed a wide variety of Enterobacteriaceae , including 14 species in eight genera, the most common being Enterobacter spp., Salmonella spp., Serratia spp., Kluyvera spp., or Escherichia spp. Enteric group 58 strains have been most frequently isolated from traumatic injuries, fractures, and wounds and rarely from feces. Defining its clinical significance and distinguishing infection from colonization requires further study, but our case report indicates that serious systemic infection can occur. The vernacular name enteric group 58 was used from 1985 to 2004. In this paper, we formally name it Averyella dalhousiensis gen. nov., sp. nov., on the basis of its unique phenotype and its unique 16S rRNA gene sequence. These data indicate that enteric group 58 is not closely related to any of the existing genera or species of Enterobacteriaceae . The type strain is designated CDC9501-97, and a phenotypic definition is given based on all 21 strains.

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Identification of Bacteria by Computer: General Aspects and Perspectives

Cited by 164 publications

References 6 publications

Protease activity of extracellular enzyme produced by B. subtilis isolated from soil

Protease activity of extracellular enzyme produced by B. subtilis isolated from soil

Computer-assisted pattern recognition model for the identification of slowly growing mycobacteria including Mycobacterium tuberculosis

First Case of Septicemia Due to a Strain Belonging to Enteric Group 58 ( Enterobacteriaceae ) and Its Designation as Averyella dalhousiensis gen. nov., sp. nov., Based on Analysis of Strains from 20 Additional Cases

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