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Application of SSCP to Identification of Resistance Mutations

  • Timothy D. McHugh
Part of the Methods in Molecular Medicine™ book series (MIMM, volume 48)

Abstract

There has been a significant increase in the number of genes associated with antibiotic resistance that have been described. For many antimicrobials all of the principal genes associated with their action have been identified (1). There is increasing interest in the epidemiological distribution of resistance mutations of these genes and research into their origin and routes of transmission. At the more fundamental level, there is interest in the impact of such mutations on the fitness/survivability of the pathogen (2). We have described the strategies for selection of mutants in the mycobacteria (3) and also a polymerase chain reaction-single-stranded conformational polymorphism (PCR-SSCP) approach to investigation of the distribution of such mutants. In this method PCR amplimers are denatured to form single-stranded nucleic acids and then submitted to gel electrophoresis to identify sequence polymorphisms. Sequencing of clones remains relatively expensive and time consuming for investigating a large number of isolates from clinical practice or strains from mutation experiments. This chapter outlines a method for screening large numbers of PCR amplimers, which can then inform rational selection for cloning and sequence analysis, or for identifying novel mutations for detailed sequence. Alternatively, this approach can be used for rapid screening where the SSCP profile relating to each mutation is already known.

Keywords

Sterile Deionized Water Drug Resistance Mutation Conformational Polymorphism Vertical Format Short Plate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Ramaswamy, S. and Musser, J. M. (1998) Molecular genetic basis of antimicrobial agent resistance in Mycobacterium tuberculosis: 1998 update. Tubercle Lung. Dis. 79, 3–29CrossRefGoogle Scholar
  2. 2.
    Gillespie, S. H. and McHugh, T. D. (1997) The biological cost of resistance. Trends Microbiol. 5, 337–339.PubMedCrossRefGoogle Scholar
  3. 3.
    Billington, O. J., McHugh, T. D. and Gillespie, S. H. (1999) The physiological cost of rifampin resistance induced in vitro in Mycobacterum tuberculosis. Antimicrob. Agents. Chemother. 43, 1866–1869.PubMedGoogle Scholar
  4. 4.
    Suzuki Y, Orita M, Shiraishi M, Hayashi K & Sekiya T. (1990) Detection of ras gene mutations in human lung cancers by single-strand conformation polymorphism analysis of polymerase chain reaction products. Oncogene 5, 1037–1043.PubMedGoogle Scholar
  5. 5.
    Rowe, P. S., Oudet, C. L., Francis, F., et al. (1997) Distribution of mutations in the PEX gene in families with X-linked hypophosphataemic rickets (HYP). Human. Mol. Gen. 6, 539–549.CrossRefGoogle Scholar
  6. 6.
    Telenti, A., Imboden, P., Marchesi, F., et al. (1993) Detection of rifampinresistance mutations in Mycobacterium tuberculosis. Lancet 341, 647–650.PubMedCrossRefGoogle Scholar
  7. 7.
    Orita, M., Iwahana, H., Kanazawa, H., Hayashi, K., and Sekiya, T. (1989) Detection of polymorphisms of human DNA by gel electrophoresis as single-strand conformation polymorphisms. Proc. Natl. Acad. Sci. 86, 2766–2770.PubMedCrossRefGoogle Scholar
  8. 8.
    Gillespie, S. H., McHugh, T. D., Ayes, H., Dickens, A., Estradiou, A., and Whiting, G. C. (1997) Allelic variation of the lytA gene of Streptococcus pneumoniae. Infect. Immun. 65, 3936–3938.PubMedGoogle Scholar
  9. 9.
    Hannan, M. M., McHugh, T. D., Billington, O., Gazzard, B., and Gillespie, S. H. (1997). Variation in pncA gene: molecular biology and clinical significance. Span. J. Chemoth. 10(Suppl. 2), 140.Google Scholar

Copyright information

© The Humana Press Inc., Totowa, NJ 2001

Authors and Affiliations

  • Timothy D. McHugh
    • 1
  1. 1.Department of Medical MicrobiologyRoyal Free and University College Medical School, Royal Free CampusLondonUK

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