Literature DB >> 10730939

A statistical model for assessing sample size for bacterial colony selection: a case study of Escherichia coli and avian cellulitis.

R S Singer1, W O Johnson, J S Jeffrey, R P Chin, T E Carpenter, E R Atwill, D C Hirsh.   

Abstract

A general problem for microbiologists is determining the number of phenotypically similar colonies growing on an agar plate that must be analyzed in order to be confident of identifying all of the different strains present in the sample. If a specified number of colonies is picked from a plate on which the number of unique strains of bacteria is unknown, assigning a probability of correctly identifying all of the strains present on the plate is not a simple task. With Escherichia coli of avian cellulitis origin as a case study, a statistical model was designed that would delineate sample sizes for efficient and consistent identification of all the strains of phenotypically similar bacteria in a clinical sample. This model enables the microbiologist to calculate the probability that all of the strains contained within the sample are correctly identified and to generate probability-based sample sizes for colony identification. The probability of cellulitis lesions containing a single strain of E. coli was 95.4%. If one E. coli strain is observed out of three colonies randomly selected from a future agar plate, the probability is 98.8% that only one strain is on the plate. These results are specific for this cellulitis E. coli scenario. For systems in which the number of bacterial strains per sample is variable, this model provides a quantitative means by which sample sizes can be determined.

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Year:  2000        PMID: 10730939     DOI: 10.1177/104063870001200203

Source DB:  PubMed          Journal:  J Vet Diagn Invest        ISSN: 1040-6387            Impact factor:   1.279


  6 in total

1.  Diversity, frequency, and persistence of Escherichia coli O157 strains from range cattle environments.

Authors:  David G Renter; Jan M Sargeant; Richard D Oberst; Mansour Samadpour
Journal:  Appl Environ Microbiol       Date:  2003-01       Impact factor: 4.792

2.  A model to estimate the optimal sample size for microbiological surveys.

Authors:  S F Altekruse; F Elvinger; Y Wang; K Ye
Journal:  Appl Environ Microbiol       Date:  2003-10       Impact factor: 4.792

3.  Assessing genetic heterogeneity within bacterial species isolated from gastrointestinal and environmental samples: how many isolates does it take?

Authors:  D Döpfer; W Buist; Y Soyer; M A Munoz; R N Zadoks; L Geue; B Engel
Journal:  Appl Environ Microbiol       Date:  2008-03-31       Impact factor: 4.792

Review 4.  Mastitis therapy and antimicrobial susceptibility: a multispecies review with a focus on antibiotic treatment of mastitis in dairy cattle.

Authors:  John Barlow
Journal:  J Mammary Gland Biol Neoplasia       Date:  2011-10-09       Impact factor: 2.673

5.  Assessment of Diversity of Antimicrobial Resistance Phenotypes and Genotypes of Mannheimia haemolytica Isolates From Bovine Nasopharyngeal Swabs.

Authors:  Hannah F Carter; Robert W Wills; Matthew A Scott; Alexis C Thompson; Randall S Singer; John Dustin Loy; Brandi B Karisch; William B Epperson; Amelia R Woolums
Journal:  Front Vet Sci       Date:  2022-05-11

6.  Salmonella spp. transmission in a vertically integrated poultry operation: Clustering and diversity analysis using phenotyping (serotyping, phage typing) and genotyping (MLVA).

Authors:  Helen Kathleen Crabb; Joanne Lee Allen; Joanne Maree Devlin; Simon Matthew Firestone; Colin Reginald Wilks; James Rudkin Gilkerson
Journal:  PLoS One       Date:  2018-07-19       Impact factor: 3.240

  6 in total

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