A mitochondrial DNA microarray has been developed to detect animal contamination in Canadian watershed samples. The results confirm that the mitochondrial microarray method could accurately detect the dominant animals present in water samples.
Fecal pollution monitoring in water quality assessments is of great significance for public health, as the major source of waterborne pathogens is related to the large number of pathogenic microorganisms associated with fecal material.
A Canadian research collaboration has developed a mitochondrial-based microarray (mitoArray) for rapid identification of the presence of 28 animals and one family (cervidae) potentially implicated in fecal pollution in mixed activity watersheds.
Oligonucleotide probes for genus or subfamily-level identification were targeted within the 12S rRNA–Val tRNA–16S rRNA region in the mitochondrial genome.
This region, called MI-50, was selected based on three criteria: the ability to be amplified by universal primers, that these universal primer sequences are present in most commercial and domestic animals of interest in source tracking, and that sufficient sequence variation exists within this region to meet the minimal requirements for microarray probe discrimination.
To quantify the overall level of mitochondrial DNA (mtDNA) in samples, a quantitative-PCR (Q-PCR) universal primer pair was also developed.
Probe validation was performed using DNA extracted from animal tissues and, for many cases, animal-specific fecal samples. To reduce the amplification of potentially interfering fish mtDNA sequences during the MI-50 enrichment step, a clamping PCR method was designed using a fish-specific peptide nucleic acid.
DNA extracted from 19 water samples were subjected to both array and independent PCR analyses.
The results confirm that the mitochondrial microarray method could accurately detect the dominant animals present in water samples. This emphasises the potential for this methodology in the parallel scanning of a large variety of animals normally monitored in fecal source tracking.
Water Research, Volume 47, Issue 1, 1 January 2013, Pages 16–30.
