Identification of Mycoplasmas using a fluorophore-free microarray and infrared chemical imaging (IRCI)

Microarray chip development using infrared imaging for the identification of catfish species

Several families of catfish species are extensively aquacultured around the world; however, only those from the family Ictaluridae can be labeled as catfish in the United States. Non-Ictalurid catfish species that are marketed as "catfish" in the USA are considered misbranded. Misbranding in general has led to an increased interest in developing deoxyribonucleic acid (DNA)-based methods such as DNA barcoding, polymerase chain reaction restriction fragment length polymorphism, and DNA microarrays with fluorescence detection for the identification of fish species. In this proof-of-concept study, DNA microarrays coupled with a newly developed mid-infrared imaging detection method were applied to the identification of seven species of catfish for the first time. Species-specific DNA probes targeting three regions per species of the cytochrome c oxidase 1 (barcoding) gene were developed and printed as microarrays on glass slides. Deoxyribonucleic acid targets labeled with biotin were hybridized to their complementary probes using a strategy that allowed the selective formation of a silver layer on hybridized spots needed for detection. Using this three-probe format, the seven species were all identified correctly, even when a limited number of false positive spots were observed. Raman spectroscopy was employed to further characterize the arrays.

Enhanced mid-infrared chemical imaging (IRCI) detection of DNA microarrays

We report on the optimization of a recently proposed mid-infrared chemical imaging (IRCI) detection method for the analysis of DNA microarrays. The improved protocol allowed for a ten-fold reduction in the time needed to generate a mosaic image of an entire microarray and the production of IR images with high contrast that would facilitate data analysis and interpretation. Advantages of using this protocol were evaluated by applying it to the analysis of four virulence genes in the genomes of 19 strains of the food bacterial pathogen Yersinia enterocolitica.