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Dose finding in the Ames Salmonella assay.

N N Khromov-Borisov1, J N Picada, J A Henriques

  • 1Departamento de Biofísica e Centro de Biotecnologia, Universidade Federal do Rio Grande do Sul, 91501-970, Porto Alegre, RS, Brazil. nikita@dna.cbiot.ufrgs.br

Mutation Research
|September 28, 2000
PubMed
Summary

This study introduces statistical methods for identifying the lowest effective dose (LED) in mutagenicity assays, accounting for discrete data like bacterial colony counts. These methods improve dose-finding accuracy in genotoxicity testing.

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Area of Science:

  • Toxicology
  • Genetics
  • Statistical Modeling

Background:

  • Current mutagenicity potency measures often rely on 'rate' calculations, potentially overlooking discrete response data.
  • Statistical 'dose finding' methods exist but frequently ignore the discrete nature of biological responses, such as plate counts in mutagenicity assays.

Purpose of the Study:

  • To propose and evaluate statistical procedures for determining threshold dose/concentration values (e.g., lowest effective dose - LED) that accommodate discrete response data.
  • To address limitations in existing dose-finding methods for mutagenicity studies, particularly those using the Ames Salmonella assay.

Main Methods:

  • Two statistical procedures are presented for dose finding when plate counts follow a Poisson distribution: stepwise collapsing of counts and confidence limits for the mutation induction factor (MIF).

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  • A non-parametric visual estimation method for LED is described for cases with non-overlapping dose and control counts.

    • Main Results:

    • The proposed methods are demonstrated to be applicable and valid using datasets on the mutagenicity of harmine and an apomorphine oxidation product.
    • The study highlights the importance of considering the discrete nature of response data in dose-finding for mutagenicity assessments.

    Conclusions:

    • The developed statistical approaches offer improved accuracy for determining lowest effective dose (LED) in mutagenicity testing by handling discrete count data.
    • These methods provide robust alternatives to rate-based potency measures, enhancing the reliability of genotoxicity assessments.