Quantification of changing Pseudomonas aeruginosa sodA, htpX and mt gene abundance in response to trace metal toxicity: a potential in situ biomarker of environmental health.

NJ Bouskill, EP Barnhart, TS Galloway, RD Handy, TE Ford

Research output: Contribution to journalArticlepeer-review

Abstract

Sediment-dwelling prokaryotes play a vital role in determining the fate and speciation of metals, yet are also susceptible to the biological effects of trace metals. In this article, optimized DNA extraction and purification techniques and species-specific primers are used to assess the genetic incidence and abundance of metal detoxification and general stress genes of Pseudomonas aeruginosa to complement chemical analysis in inferring the severity of metal-contaminated sites along the Clark Fork River, Montana. Results show the highest incidence of candidate genes related to bacterial stress at the most polluted site, while multiple regression analysis demonstrated significant correlations (P<0.05, r(2)=0.9) between in situ metal concentrations (As, Cu and Zn), total gene incidence, and the incidence of metal detoxification genes. Furthermore, principal components plotting the incidence of genes related to metal resistance show clear separation of sites giving clear clusters on the basis of contamination. Quantification of three genes (sodA, htpX and mt) from surveyed sites found significantly higher (anova, P<0.05) copy numbers at the more contaminated sites compared with reference sites. The development of rapid microbial biomarker tools represents a significant advance in the field of environmental biomonitoring and the prediction of metal bioavailability.
Original languageEnglish
Pages (from-to)276-286
Number of pages0
JournalFEMS Microbiol Ecol
Volume60
Issue number2
DOIs
Publication statusPublished - May 2007

Keywords

  • Arsenic
  • Bacterial Proteins
  • Copper
  • Environmental Health
  • Environmental Monitoring
  • Gene Dosage
  • Genes
  • Bacterial
  • Geography
  • Geologic Sediments
  • Humans
  • Metals
  • Heavy
  • Montana
  • Principal Component Analysis
  • Pseudomonas aeruginosa
  • Regression Analysis
  • Superoxide Dismutase
  • Zinc

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