Introduction

MicroRNAs (miRNAs) are phylogenetically conserved, small non-coding RNAs (∼22 nucleotides) characterized by distinct expression and biogenesis criteria [1,]. MicroRNAs modulate the expression of genes through post-transcriptional effects on target mRNA stability and translational efficiency in both plants and animals. Microarray expression profiling can be used to determine if specific miRNAs are present in different cell types, stages of development, and disease states [2,]. To generate accurate and reproducible expression profiles using microarrays, it is critical that the labeling method effectively label all miRNA species in the sample regardless of specific sequence or structure.

Due to the small size of miRNAs and the lack of a common sequence tag (e.g. a poly(A) tail), specialized labeling methods are required to achieve consistent and representative labeling. To date, the prominent commercially available miRNA labeling methods are enzyme-based and involve the addition of nucleotides to the 3′ end of purified miRNAs. E. coli poly(A) polymerase I is used to catalyze the addition of approximately 20–50 nucleotides to the miRNA resulting in a total length between 40 and 70 nucleotides. Next, the extended miRNA is purified and fluorescent labels are attached through a direct chemical linkage to enzyme incorporated modified nucleotides or, is hybridized to a tag sequence that is linked to fluorophores. In contrast, the Label IT chemical labeling method facilitates the covalent attachment of fluorescent labels directly onto nucleic acids without an enzyme dependent step.

The goal of this study was to determine if miRNA expression profiles (using microarrays) are affected by the type of miRNA labeling method used. Three different miRNA labeling methods were directly compared for their ability to detect differentially expressed miRNAs from two different tissue sources (mouse brain and mouse heart). To validate the miRNA expression in these tissues, quantitative RT-PCR and published northern blot data were used to confirm and corroborate the miRNA profiles.

Materials and Methods

miRNA-enriched RNA isolation

MicroRNA-enriched samples were prepared from heart and brain tissue from adult ICR mice (Harlan Laboratories, Indianapolis, IN, USA) using the mirVana™ miRNA Isolation Kit (Ambion, Austin, TX, USA).

miRNA labeling and hybridization

MicroRNA-enriched samples were chemically labeled via alkylation (Label IT miRNA Labeling Kit, Mirus Bio Corporation, Madison, WI, USA) or enzymatically labeled with the mirVana miRNA Labeling Kit (Ambion) or the NCode miRNA Labeling System (Invitrogen, Carlsbad, CA, USA). Labeled miRNAs were then hybridized to NCode™ MultiSpecies miRNA microarray slides (Invitrogen). Cy™3 and Cy™5 fluorophores were detected when the Label IT chemical or mirVana enzymatic method was used. Alexa Fluor® 3 and Alexa Fluor® 5 were detected when the NCode enzymatic labeling system was used. To increase the stringency of our data analysis, a “dye swap” setup was used for each hybridization experiment performed. Each brain and heart miRNA-enriched sample was labeled for detection with each of the provided fluorophores before determining relative expression (e.g. heart with Cy5, brain with Cy3, and vice versa).

Sequences of RNA oligonucleotides used for spike-in and labeling experiments were determined using miRBase Sequence Database (http://microrna.sanger.ac.uk/sequences) [3,4,5,].

The labeling density (pmol fluorophore per µg RNA) generated by the Label IT labeling method was estimated using spectrophotometric (Beckman DU 530, Beckman Coulter, Fullerton, CA, USA) measurements and the molar extinction coefficient (ε), 150,000 M⁻¹ cm⁻¹, for the Cy3 fluorophore. The λ_max for Cy3 was 550 nm. RNA molar concentration was determined using absorbance at 260 nm and the calculated molecular weight and extinction coefficient for each RNA oligonucleotide.

Image analysis and data processing

Microarray data was obtained using the Axon GenePix 4000B scanner (Molecular Devices, Sunnyvale, CA, USA) for image acquisition and associated GenePix Pro 5.0 software for signal measurement. Photomultiplier tube measurements (PMTs), or laser intensities, for each hybridization slide were adjusted so that the highest expressing miRNAs (brightest features) exhibited measurements at the top of the signal linear range. Each of the data sets used was filtered using signal-to-noise criteria and the demonstration of differential expression for the given miRNA based on log₂ calculations of heart:brain signal ratios. Quality data was defined to have signal greater than the average signal of the array negative controls in the relevant channel plus 1.5 standard deviations of the negative control signal. Measurements below this signal cutoff were recorded as “Not Detected”. Signal measurements from either channel for brain or heart labeled samples were averaged before calculating heart/brain ratios and log₂ transformation for each miRNA. Differentially expressed miRNAs were required to have a calculated log₂(heart signal/brain signal) greater than 1 or less than −1 to represent greater than two fold differential expression between the two tissues. To fulfill the “dye swap” requirement, log transformed expression ratios were required to switch sign (e.g. from 3 to −3) when samples were detected using the opposite pairing, ensuring consistent differential expression regardless of which dye or method was used to label the samples.