Optimizing a custom tiling microarray for low input detection and identification of unamplified virus targets

Abstract Viruses are major pathogens causing foodborne illnesses and are often present at low levels in foods, thus requiring sensitive techniques for their detection in contaminated foods. The lack of efficient culture methods for many foodborne viruses and the potential for multi-species viral contamination have driven investigation toward non-amplification based methods for virus detection and identification. A custom DNA microarray (FDA_EVIR) was assessed for its sensitivity in the detection and identification of low-input virus targets, human hepatitis A virus, norovirus, and coxsackievirus, individually and in combination. Modifications to sample processing were made to accommodate low input levels of unamplified virus targets, which included addition of carrier cDNA, RNase treatment, and optimization of DNase I-mediated target fragmentation. Amplification-free detection and identification of foodborne viruses were achieved in the range of 250–500 copies of virus RNA. Alternative data analysis methods were employed to distinguish the genotypes of the viruses particularly at lower levels of target input and the single probe-based analysis approach made it possible to identify a minority species in a multi-virus complex. The oligonucleotide array is shown to be a promising platform to detect foodborne viruses at low levels close to what are anticipated in food or environmental samples.