Microarray assay was performed by LC Science Company. The microfluidic PicoArray reactor is made from silicon using standard microelectronic fabrication procedures. The reactor contains three topographical features: pico- reaction chambers, fluid microchannels, and inlet/outlet through holes. The chip contains 128 x 31 (total 3698) individual reaction chambers, each with an internal volume of 270 pl. The fluid microchannels are of a tapered shape that was derived from a fluid mechanical model to produce a uniform flow rate across all reaction chambers. This technology enables a high density of uniform spots. RNA extraction and analysis protocol: 5 µg total RNA sample isolated from untreated rabbit reticulocyte lysate (Promega), was size fractionated using a YM-100 Microcon centrifugal filter (Millipore) and the small RNAs (< 300 nt) isolated were 3’-extended with a poly(A) tail using poly(A) polymerase. An oligonucleotide tag was then ligated to the poly(A) tail for subsequent fluorescent dye staining. Hybridization was performed overnight on a µParaflo microfluidic chip using a micro-circulation pump (Atactic Technologies)9. On the microfluidic chip, each detection probe consisted of a chemically modified nucleotide coding segment complementary to target microRNA (from miRBase, http://microrna.sanger.ac.uk/sequences/) and a spacer segment of polyethylene glycol to extend the coding segment away from the substrate. The detection probes were made by in situ synthesis using PGR (photogenerated reagent) chemistry. The hybridization melting temperatures were balanced by chemical modifications of the detection probes. Hybridization used 100 µL 6xSSPE buffer (0.90 M NaCl, 60 mM Na2HPO4, 6 mM EDTA, pH 6.8) containing 25% formamide at 34 °C. After hybridization, detection was carried out by fluorescence labeling using tag-specific Cy3 and Cy5 dyes. Hybridization images were collected using a laser scanner (GenePix 4000B, Molecular Device) and digitized using Array-Pro image analysis software (Media Cybernetics). Data were analyzed by first subtracting the background and then normalizing the signals using a LOWESS filter10 (Locally-weighted Regression) and p-values of the t-test were calculated; differentially detected signals were those with less than 0.01 p-values.
