Simultaneous quantification of multiple nucleic acid targets in complex rRNA mixtures using high density microarrays and nonspecific hybridization as a source of information.

To date, it has been problematic to accurately quantify multiple nucleic acid sequences, representing microbial targets, in multi-target mixtures using oligonucleotide microarrays, primarily due to nonspecific target binding (i.e., cross-hybridization). While some studies ignore the effects of nonspecific binding, other studies have developed approaches to minimize nonspecific binding, such as physical modeling to design highly specific probes, subtracting nonspecific signal using mismatch probes, and/or removing nonspecific duplexes by scanning through a range of wash stringencies. We have developed an alternative approach that, in contrast to previous approaches, uses nonspecific target binding as a source of information. Specifically, the new approach uses hybridization patterns (fingerprints) to quantify specific nucleic acid targets in complex target mixtures. We evaluated the approach by mixing together in vitro transcribed 28S rRNA targets at varying concentrations (up to 1.0 nM), and hybridizing the 24 mixtures to microarrays (n=3160 probes, in duplicate). Three independent Latin-square-designed experiments revealed accurate quantification of the targets. The regression between actual concentration of targets and those determined by the approach were highly positively correlated with high R(2) values (e.g., R(2)=0.90, n=6 targets; R(2)=0.84, n=8 targets; R(2)=0.82, n=10 targets).

An evaluation of the use of the LSU rRNA D1-D5 domain for DNA-based taxonomy of eukaryotic protists.

Diagnostic signature DNA sequences are important tools for the identification of species. There is an active debate in the literature on the choice of the best markers applicable for a broad range of organisms. Protists have seldom been included in these evaluations. Mitochondrial gene sequences are inappropriate for protists since several groups do not possess mitochondria. Here we studied the application of the large subunit (LSU) rRNA gene fragments (D1-D5) regarding their usefulness to discriminate between a wide range of heterotrophic nanoflagellates. Phylogenetic analyses based on the LSU rRNA fragments showed similar results compared to phylogenetic trees based on the small subunit (SSU) rRNA. The data set indicates the power of the use of the D1-D5 region as a marker for a DNA-based taxonomy. Our results, together with the available sequences in Genbank, form a comprehensive database for unicellular eukaryotes, especially heterotrophic flagellates. It is now possible to assign new sequences to the different groups of heterotrophic flagellates which we have tested for different closely related Cercomonas and Paracercomonas strains from groundwater.