1 Introduction

The gradual and progressive loss of neuronal structure and function, and ultimately neuronal death, is a common characteristic of neurodegenerative disorders, and eventually leads to nervous system dysfunction. Distinct cognitive, behavioral, and motor symptoms, characteristic of a specific disorder, become manifest as neurodegeneration progresses, reflecting the brain region and neuronal type affected and the extent of damage. Changes associated with neurodegeneration at the cellular level, such as neurite retraction, synaptic dysfunction, and axonal transport defects, typically precede neuronal loss [1]. These changes are manifestations of deregulated biochemical pathways, and may result in imbalanced metabolite levels and biomolecule leakage in intercellular space or unconventional secretions, including shedding vesicles (or ectosomes) [2].

Incorporation of molecular markers in the diagnostic process could aid detection of early changes, prior to extensive neuronal loss, as early as the presymptomatic stages of the disorder, thus enabling improved patient stratification for targeted drug development . Such biomarkers should be sufficiently sensitive and specific to distinguish AD from other disorders with overlapping symptoms, especially at early disease stages, and thus provide window of opportunity for therapeutic intervention and contribute to improved patient outcomes. They could also serve as a tool to assess disease stage and monitor disease progression. Easily accessible biosamples collected by non- or minimally invasive procedures, simple methodology with short processing time to generate results, and low overall cost would avail such tool to population screening, which would not be feasible with other modalities, like novel neuroimaging approaches.

Non-coding (nc)RNAs have a crucial role in the entire spectrum of cellular processes, from development and differentiation to homeostatic maintenance, and have been implicated in different diseases. Micro-RNAs (miRNAs) are a family of ncRNA molecules that were first described in 1993. Long miRNA transcripts, known as pri-miRNA, are enzymatically processed into the mature form (~22 nucleotides); these short RNA molecules accomplish posttranscriptional gene silencing by binding complementary sequences at the 3’UTR of target mRNAs, leading to mRNA degradation or translation inhibition (reviewed in [3]). Multiple mRNAs may be targets of a specific miRNA and several miRNAs may target a specific mRNA. Around 2600 human mature miRNAs have been characterized (miRBase release 21) [4].

The majority of miRNA profiling studies focus on solid tissues, but due to their high stability, miRNAs released by peripheral tissues are detectable in blood and blood components, like serum and plasma. MiRNAs are also detectable in other biofluids, such as cerebrospinal fluid (CSF) , urine, and saliva [5,6,7]. The potential of circulating miRNAs as biomarkers in blood or blood components was indicated by studies examining patients with various malignancies [8, 9]. Boeri and colleagues demonstrated that circulating miRNAs could be used to predict disease in samples taken from lung cancer patients, several years before the onset of disease [10]. Another study reported lower expression of two miRNAs in saliva from oral squamous cell carcinoma patients compared to healthy individuals [11]. Keller et al. analyzed blood samples from patients diagnosed with one of 14 diseases, which included different cancers and autoimmune conditions, and found that over 100 miRNAs were deregulated for each disease; they were able to predict the disease in nearly 7 out of 10 patients being studied [12].

The early advances in the study of miRNA as noninvasive biomarkers in cancer inspired their study for other conditions, including AD. Several deregulated miRNAs in brain, CSF, and blood have been associated with AD and other brain disorders (reviewed in [13] and [1]).

Interestingly, changes in miRNA concentrations in a bodily fluid and in an organ involved in pathology are not always concordant and sometimes change in opposite directions. For instance, serum hsa-miR-501-3p levels were downregulated in AD patients, its lower levels significantly correlating with lower Mini-Mental State Examination scores, but it was upregulated in the postmortem brains of the same donors [14]. Although miRNA expression may be discordant between biofluid and affected tissue, and irrespective of whether changes in expression are causal or consequential to the pathological process, discovery of novel miRNA biomarkers would improve patient stratification and targeted drug development .

Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies, such as narrow-assay-focus and high-sample-throughput (e.g., reverse transcription-quantitative PCR; RT-qPCR), and broad-assay-focus and low-sample-throughput techniques (e.g., sequencing and microarrays). In a recent study, 12 commercially available platforms for analysis of miRNA expression were systematically compared, and platform performance was assessed for reproducibility, sensitivity, accuracy, specificity, and concordance of differential expression. Two miRNA sequencing platforms, three miRNA hybridization platforms, and seven RT-qPCR platforms were included in the assessment. Each method had its strengths and weaknesses, and researchers can refer to those findings to guide their selection according to the aims of their project.[15] While broad assay focus techniques are useful in identifying promising candidates in a small number of samples, focused analysis of specific candidates (assays) in a large number of samples is better served by a technology such as RT-qPCR. RT-qPCR is characterized by an overall high sensitivity, especially prominent when working with samples with low RNA quantity, which is of particular importance when miRNA expression is studied in body fluids. The advent of microfluidic-based qPCR platforms, such as the Fluidigm BioMark HD System, can yield as many as 9216 datapoints in one qPCR experiment (e.g., if using a 96 × 96 chip); it has the capacity for high-sample-throughput but minimal RNA requirements.

The miScript qPCR System has more than 2400 validated human miRNA assays and allows the flexibility to study any subset of these. It uses a poly-A universal reverse transcription (RT) step, followed by oligo-dT priming. Universal RT is less complicated and quicker than target-specific RT alternatives, and allows greater flexibility for downstream analysis of the whole miRNome as compared to a multiplex reaction which is confined to the number of assays included in the RT step. Internal controls such as the miRNA reverse transcription control (miRTC), which is added in the RT Mix, and the positive PCR control (PPC), which is dispensed on pre-spotted PCR Arrays, are typical of this platform and allow evaluation of important stages of the procedure.

A detailed account of a three-step workflow for multi-well plates pre-spotted with qPCR primer assays, which includes quality checkpoints after each step: (1) RT and quality control of the RT product by evaluation of miRTC levels, (2) preamplification and evaluation of the preamplified miRTC product, and (3) qPCR assessment of spike-in controls miRTC and PPC, together with miRNAs of interest; a discussion of important considerations regarding RNA quantity; as well as explanations of the most suitable normalization procedure have previously been covered in another volume of this series [16]. Here, I present the protocol for users of the Fluidigm BioMark HD System [17].

2 Materials

The following materials and reagents are required for this protocol:

  • 96-well plate containing assays in solution.

  • 20× DNA Binding Dye Sample Loading Reagent.

  • 8-strip PCR tubes.

  • Low EDTA-TE buffer (0.1 mM EDTA).

  • RT2 Microfluidics qPCR Reagent System.

3 Method

3.1 Protocol Overview

In this protocol, cDNA synthesis is performed using the RT2 Microfluidics qPCR Reagent System. Next, preamplification is performed using the RT2 PreAMP Pathway Primer Mix Format H. Finally, real-time PCR is performed using RT2 Profiler PCR Array Format H in combination with Microfluidics qPCR Master Mix (contains EvaGreen).

3.2 Considerations of RNA Amount to Be Used

The RT2 Microfluidics qPCR System yields results with as little as 10 ng or as much as 1 μg total RNA per well reaction. However, the optimal amount of starting material depends on the relative abundance of the transcripts of interest. Lower abundance transcripts require more RNA; higher abundance transcripts require less RNA . Greater amounts of input RNA yield greater number of positive calls; that is, genes expressed in the linear dynamic range of the method.

Important: Use a consistent amount of total RNA for all samples in a single experiment to be characterized and compared.

3.3 Procedure

3.3.1 cDNA Synthesis Using the RT2 Microfluidics qPCR Reagent System

  1. 1.

    Thaw Buffer GE2 and BC4 Solution (RT master mix). Mix each solution by flicking the tubes. Centrifuge briefly to collect residual liquid from the sides of the tubes and then store on ice.

  2. 2.

    Prepare the genomic DNA elimination mix for each RNA sample in one well of a 96-well plate according to Table 1.

  3. 3.

    Incubate the genomic DNA elimination mix for 5 min at 37 °C, then place immediately on ice for at least 1 min.

  4. 4.

    Add 6 μL BC4 Solution to each well, mix by carefully pipetting up and down (can be done with a multi-channel pipette). Centrifuge briefly to collect residual liquid from the sides of the tubes.

  5. 5.

    Program a thermal cycler for a single cycle as follows: 42 °C for 60 min, 95 °C for 5 min, 4 °C hold. Place the 96-well plate in the cycler and run the program (see Note 1 ).

  6. 6.

    Place the reactions on ice and proceed with the preamplification protocol (see Note 2 ).

Table 1 Genomic DNA elimination mix
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3.3.2 Preamplification Using RT2 PreAMP Primer Mix Format H

  1. 1.

    Thaw RT2 PreAMP Primer Mix and RT2 PreAMP PCR Mastermix (PA-30) on ice. Mix each solution by flicking the tubes. Centrifuge briefly to collect residual liquid from the sides of the tubes and then store on ice.

  2. 2.

    Prepare preamplification mix according to Table 2.

  3. 3.

    Pipet 8 μL preamplification mix into each well of an empty 96-well plate.

  4. 4.

    Add 2 μL of first-strand cDNA from each well of the 96-well plate in step 6 to each well of the 96-well plate in step 9 using an 8-channel pipette (see Note 3 ).

  5. 5.

    Mix by carefully pipetting up and down and spin briefly.

  6. 6.

    Program the real-time cycler according to Table 3. Place the 96-well plate in the real-time cycler and start the program.

  7. 7.

    When cycling is finished, take the plate from the real-time cycler and place on ice.

  8. 8.

    Add 1 μL Side Reaction Reducer to each well. Mix gently by pipetting up and down and spin briefly.

  9. 9.

    Incubate at 37 °C for 15 min followed by heat inactivation at 95 °C for 5 min.

  10. 10.

    Add 44 μL low EDTA–TE buffer (0.1 mM EDTA) to each well (see Note 4 ).

  11. 11.

    Place on ice prior to real-time PCR, or store at −15 to −30 °C.

Table 2 Preamplification mix
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Table 3 Cycling conditions for preamplification
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3.3.3 Sample Mix Preparation

  1. 1.

    Prepare a sample mix according to Table 4.

  2. 2.

    Pipette 53 μL (96.96 Dynamic Array) or 26 μL (48.48 Dynamic Array) sample mix into each tube of an 8-strip PCR tube.

  3. 3.

    Using an 8-channel pipette, transfer 4 μL sample mix into each well of an empty 96-well plate (for the 48.48 Dynamic Array, use only half of the 96-well plate).

  4. 4.

    Add 2 μL of each preamplified sample from step 17 to a well of the 96-well plate containing the sample mix (see Note 5 ).

  5. 5.

    Cover the plate with plate sealer. Mix and spin briefly.

  6. 6.

    Label the plate as “sample.”

Table 4 Sample mix
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3.3.4 Assay Mix Preparation

  1. 1.

    Remove the RT2 Profiler PCR Array Format H from −15 to −30 °C. Thaw for 10 min at room temperature (15–25 °C). Briefly vortex and spin the plate to bring the contents to the bottom of the wells.

  2. 2.

    Mark the caps of the RT2 Profiler PCR Array so that they can be replaced in the original order. Remove the caps.

  3. 3.

    Pipet 45 μL 2× Assay Loading Reagent (provided by Fluidigm) into each tube of an 8-strip PCR tube.

  4. 4.

    Transfer 3 μL 2× Assay Loading Reagent from the 8-strip tube into each well of an empty 96-well plate (see Notes 6 and 7 ).

  5. 5.

    Transfer 3 μL from each well of the RT2 Profiler PCR Array to the corresponding well of the 96-well plate from step 27.

  6. 6.

    Cover the plate with a plate sealer. Mix by vortexing and spin briefly.

  7. 7.

    Label this plate as “assay.”

3.3.5 Priming and Loading the Fluidigm BioMark HD Dynamic Array

  1. 1.

    Peel the blue protective film from the underside of the BioMark Chip. Place the BioMark Dynamic Array into the IFC Controller.

  2. 2.

    Prime the Dynamic Array using standard Fluidigm protocols.

  3. 3.

    Using an 8-channel pipette, aliquot 5 μL from each well of the “sample” plate into appropriate sample inlets on the BioMark Dynamic Array (loading wells on the right side of the chip).

  4. 4.

    Using an 8-channel pipette, aliquot 5 μL from each well of the “assay” plate into appropriate assay inlets on the BioMark Dynamic Array (loading wells on the left side of the chip).

  5. 5.

    Using the IFC Controller HX (96.96 Dynamic Arrays) or the IFC Controller MX (48.48 Dynamic Arrays), run the Load Mix (136×) Script for 96.96 IFCs or the Load Mix (113×) Script for 48.48 IFCs.

  6. 6.

    Remove the BioMark Dynamic Array from the IFC Controller.

  7. 7.

    Remove any dust particles from the BioMark Chip surface.

3.3.6 Running the BioMark Dynamic Array IFC

  1. 1.

    Double-click the “Data Collection Software” icon to launch the software.

  2. 2.

    Click “Start a New Run,” place the chip into the reader, and click “Load.”

  3. 3.

    Verify chip barcode and chip type, choose project settings (if applicable), and click “Next.”

  4. 4.

    Chip run file: Select “New” or “Predefined,” browse to a file location for data storage, and click “Next.”

  5. 5.

    For “Application, Reference, Probes,” select the following: (a) “Application Type: Gene Expression,” (b) “Passive Reference: ROX,” (c) “Select Assay: single probe,” (d) “Select probe type: EvaGreen.” Click “Next.”

  6. 6.

    Click “Browse” to find thermal protocol file “GE 96×96 Standard v1.pcl.” or “GE 48x48 Standard v1.pcl” (see Note 8 ).

  7. 7.

    Change the thermal protocol file to the conditions in Table 5.

  8. 8.

    Confirm that “Auto Exposure” is selected and click “Next.”

  9. 9.

    Verify the Dynamic Array run information and click “Start Run.”

Table 5 Cycling conditions for Fluidigm BioMark 96.96 Dynamic Array IFCs
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4 Notes

  1. 1.

    This is the reverse transcription step.

  2. 2.

    Reactions can be stored in a −15 to −30 °C freezer at this point.

  3. 3.

    The remaining first-strand cDNA can be stored for use in future experiments.

  4. 4.

    This is a fivefold dilution (11 μL preamplification mix +44 μL buffer). This dilution can be optimized if desired. (Undiluted cDNA can be used for qPCR if needed.)

  5. 5.

    Preamplified sample can be transferred using an 8-channel pipette.

  6. 6.

    This step can be performed using an 8-channel pipette.

  7. 7.

    For a 96.96 Dynamic Array, all 96 assays can be used at one time. When using a 48.48 Dynamic Array, only 48 assays can be used at once. A second 48.48 Dynamic Array must be run to utilize all 96 assays.

  8. 8.

    A 96.96-specific protocol or 48.48-specific protocol must be used depending on the Dynamic Array type.