Name: Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice (Video) | JoVE Journal
Uploaded: 2019-01-07T14:00:00.000+00:00
Duration: 7 min 7 s
Description: Learn to assess lung microRNA expression across the estrous cycle in ozone-exposed mice. This method reveals how hormonal fluctuations influence inflammatory gene regulation in female mice.

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5 minutes

This research was supported by grants from NIH K01HL133520 (PS) and K12HD055882 (PS). The authors thank Dr. Joanna Floros for the assistance with ozone exposure experiments.

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
<ol>
	<li>Properly restrain a female C57BL/6 mouse (8&#8211;9 weeks old) using the one-handed mouse restraint technique described in Machholz et al.10.</li>
	<li>Fill the sterile plastic pipette with 10 &#956;L of ultra-pure water.</li>
	<li>Introduce the tip of plastic pipette into the vagina.</li>
	<li>Gently flush the liquid 4&#8211;5 times to collect the sample.</li>
	<li>Place the final flush containing vaginal fluid on a glass slide.</li>
	<li>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.</li>
</ol>
2. Exposure to Ozone
<ol>
	<li>Place a maximum of 4 mice in two 1.2 L glass containers with wire mesh lids, and water ad libitum.</li>
	<li>Put one glass container in the ozone chamber and the other in the filtered air exposure chamber.</li>
	<li>Adjust the ozone concentration to 2 ppm and monitor ozone levels regularly. 
	NOTE: The ozone apparatus delivers a regulated airflow (&#62;30 air changes/h) with controlled temperature (25 &#176;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.</li>
	<li>Remove glass containers after 3 h of ozone/filtered air exposure. Return animals to cage with bedding, food, and water ad libitum.</li>
</ol>
3. Lung Collection
<ol>
	<li>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.</li>
	<li>Dampen the mouse skin with 70% ethanol.</li>
	<li>Make a 2 cm midline incision using an operating scissor and surgical tweezers to expose the vena cava.</li>
	<li>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.</li>
	<li>Use a surgical scissor to cut open the abdominal cavity and remove skin/upper muscle, moving upwards toward the ribs.</li>
	<li>Use a surgical scissor to puncture the diaphragm. 
	NOTE: Lungs will collapse away from the diaphragm.</li>
	<li>Cut away the ribcage using a surgical scissor to expose the heart and lungs.</li>
	<li>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.</li>
	<li>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.</li>
	<li>Close the tube lid and store the tissue at -80 &#176;C until use.</li>
</ol>
4. RNA Preparation
<ol>
	<li>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.</li>
	<li>Split the pulverized lungs and place into two 1.5 mL tubes (half lung each).</li>
	<li>Add 500 &#181;L of guanidinium thiocyanate per sample tube and mix.&#160; Homogenize each sample using 18 G, 21 G, and 23 G needles, respectively. 
	NOTE: Samples can be spiked with 5.6&#8201; x&#8201; 108&#160;copies of a small RNA spike-in control (from a different species) before proceeding with the extraction.</li>
	<li>Add 500 &#181;L of ethanol to each sample and vortex for 15 s.</li>
	<li>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.</li>
	<li>For DNase I treatment (in-column);
	<ol>
		<li>Add 400 &#181;L of RNA Wash Buffer and centrifuge at 12,000 x g for 1 min.</li>
		<li>In an RNase-free tube, add 5 &#181;L of DNase I and 75 &#181;L of 1x DNA digestion buffer and mix. Add the mix directly to the column matrix.</li>
		<li>Incubate at room temperature for 15 min.</li>
	</ol>
	</li>
	<li>Add 400 &#181;L 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.</li>
	<li>Add 700 &#181;L of RNA wash buffer to the column and centrifuge at 12,000 x g for 1 min. Discard the flow-through.</li>
	<li>Centrifuge at 12,000 x g for 2 min to remove remaining buffer. Transfer the column into an RNase-free tube.</li>
	<li>To elute RNA, add 35 &#181;L of DNase/RNase-free water directly to the column matrix and centrifuge at 12,000 x g for 1.5 min.</li>
	<li>Measure total RNA concentration (260 nm) and purity using a spectrophotometer. Follow instructions to perform RNA quantification in a 1.5 &#181;L 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 &#8220;pure&#8221; for RNA. Typical RNA concentration usually ranges between 750 and 2,500 ng/&#181;L.</li>
	<li>Store at -80 &#176;C.</li>
</ol>
5. miRNA Profiling
<ol>
	<li>To retro-transcribe small RNAs, use 200 ng of total RNA.
	<ol>
		<li>Prepare the reverse-transcription reaction mix on ice (total volume per reaction is 20 &#181;L). For each reaction, add 4 &#181;L of 5x buffer, 2 &#181;L of 10x nucleotides mix, 2 &#181;L of reverse transcriptase, and 2 &#181;L of RNase-free water. Mix all the components and aliquot in 600 &#181;L RNAse-free plastic tubes (10 &#181;L 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.</li>
		<li>Add the template RNA (200 ng in 10 &#181;L) 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.</li>
		<li>Incubate for 60 min at 37 &#176;C.</li>
		<li>Incubate for 5 min at 95 &#176;C and place the tubes on ice.</li>
		<li>Dilute the cDNA by adding 200 &#181;L of RNase-free water to each 20 &#181;L reverse-transcription reaction.</li>
	</ol>
	</li>
	<li>Perform real-time PCR using the Mouse Inflammatory Response and Autoimmunity miRNA PCR Array.
	<ol>
		<li>Prepare a reaction mix (total volume 1100 &#181;L): For each reaction, add 550 &#181;L of 2x PCR master mix, 110 &#181;L of 10x universal primer mix, 340 &#181;L of RNase-free water, and 340 &#181;L of template cDNA (diluted reaction from step 5.1.5).</li>
		<li>Add 10 &#181;L of reaction mix to each well of the pre-loaded miRNA PCR Array using a multichannel pipettor.</li>
		<li>Seal the miRNA PCR Array plate with optical adhesive film.</li>
		<li>Centrifuge the plate for 1 min at 1,000 x g at room temperature to remove bubbles.</li>
		<li>Program the real-time cycler, PCR initial activation step for 15 min at 95 &#176;C, 3-step cycling containing denaturation for 15 s at 94 &#176;C, annealing for 30 s at 55 &#176;C, and extension for 30 s at 70 &#176;C for 40 cycles number. 
		NOTE: Follow manufacturer&#8217;s cycling conditions instructions to set up the real-time cycler. Perform the dissociation curve step built into the real-time cycler software.</li>
		<li>Perform data analysis.</li>
	</ol>
	</li>
</ol>
6. Data Analysis
<ol>
	<li>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.</li>
	<li>Normalize Ct values to the average Ct of six miRNA housekeeping controls: SNORD61, SNORD68, SNORD72, SNORD95, SNORD96A, RNU6-2, using the following equation: 
	&#916;Ct = (Ct_Target &#8722; Ct_housekeeping)</li>
	<li>For fold change calculations, calculate &#916;&#916;Ct values using a specific sample as the control, using the relative expression equation12: 
	miRNA relative expression: 
	2-&#8710;&#8710;Ct, where - &#8710;&#8710;Ct = -[&#8710;Ct test - &#8710;Ct control] 
	NOTE: A fold change of 200 is considered as cutoff.</li>
	<li>Export fold change expression values to perform statistical analysis on R using the limma package in Bioconductor8.</li>
	<li>Correct for multiple comparisons using the Benjamini-Hochberg method13. 
	NOTE: &#160;A copy of the R script is available at: <a href="http://psilveyra.github.io/silveyralab/">http://psilveyra.github.io/silveyralab/</a>. Datasets and analyzed data are also available at the Gene Expression Omnibus under number GSE111667,&#160;https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111667.</li>
</ol>
7. Data Analysis: Functional Analysis Software
<ol>
	<li>Arrange the dataset. Include miRNAs with their respective expression log ratios and p-values. See Table 1 for specific dataset formatting.</li>
	<li>Open functional analysis software (version 01-10).</li>
	<li>Upload the dataset using the following format: File format: &#8220;Flexible Format&#8221;, Contains Column Header: &#8220;Yes&#8221;, Select Identifier type: &#8220;miRBase (mature)&#8221;, 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).</li>
	<li>Select &#8220;Infer Observations&#8221; and verify that the experimental group labeling is correct.</li>
	<li>Go to &#8220;Dataset Summary&#8221; to revise the total amount of mapped and unmapped miRNAs.</li>
	<li>Click on the &#8220;new&#8221; button at the top left of program. Select &#8220;New MicroRNA Target Filter&#8221; and upload a microRNA dataset.
	<ol>
		<li>Set Source to: TarBase, Ingenuity Experts Findings, miRecords.</li>
		<li>Set Confidence to: Experimentally observed or high (predicted).</li>
		<li>Select &#8220;Add Columns&#8221; to include a variety of biological information about the targets such as species, diseases, tissues, pathways and more.</li>
		<li>To focus on targets that have changed expression in the experiment, select &#8220;Add/ replace mRNA dataset&#8221;. Use &#8220;Expression Pairing&#8221; 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).</li>
	</ol>
	</li>
	<li>Click &#8220;Add to My Pathway&#8221; to send the filtered dataset to a pathway canvas and explore more biological relationships.</li>
	<li>Use Path Designer to create a publication-quality model of microRNA effects.</li>
	<li>An alternate option is to create a core analysis.
	<ol>
		<li>For core analysis type, select &#8220;Expression Analysis&#8221;.</li>
		<li>For measurement type, select &#8220;Expr Log Ratio&#8221;.</li>
		<li>Analysis Filter Summary: consider only molecules and/or relationships where: (species = mouse) AND (confidence = experimentally observed) AND (data sources = &#8220;Ingenuity Expert Findings&#8221;, &#8220;Ingenuity ExpertAssist Findings&#8221;, &#8220;miRecords&#8221;, &#8220;TarBase&#8221;, OR &#8220;TargetScan Human&#8221;).</li>
		<li>Select a cutoff of p-value = 0.05.</li>
		<li>Run the analysis. 
		NOTE: The report will include: canonical pathways, upstream regulators analysis, diseases and functions, regulator effects, networks, molecules and more.</li>
	</ol>
	</li>
</ol>

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<li>Umstead, T. M., Phelps, D. S., Wang, G., Floros, J., Tarkington, B. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In+vitro+exposure+of+proteins+to+ozone%5BTitle%5D)+AND+%22Toxicology+Mechanisms+and+Methods%22%5BJournal%5D)">In vitro exposure of proteins to ozone.</a> Toxicology Mechanisms and Methods. 12 (1), 1-16 (2002).</li>
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</ol>

The authors declare that they have no competing interests.

MicroRNA profiling is an advantageous technique for both disease diagnosis and mechanistic research. In this manuscript, we defined a protocol to evaluate the expression of miRNAs that are predicted to regulate inflammatory genes in the lungs of female mice exposed to ozone in different estrous cycle stages. Methods for the determination of the estrous cycle, such as the visual detection method, have been described16. However, these rely on one-time measurements, and therefore are unreliable. To a...

microRNAs (miRNAs) are short (19 to 25 nucleotides), naturally occurring, non-coding RNA molecules.Sequences of miRNAs are evolutionary conserved across species, suggesting the importance of miRNAs in regulating physiological functions1. microRNA expression profiling has been proven to be helpful for identifying miRNAs that are important in the regulation of a variety of processes, including the immune response, cell differentiation, developmental processes, and apoptosis2. More recently, miRNAs have been recognized for their potential use in disease diagnostics and therapeutics. For researchers studying mechanisms of gene regulation, measuring miRNA expression can enlighten systems-level models of regulatory processes, especially when miRNA information is merged with mRNA profiling and other genome-scale data3. On the other hand, miRNAs have also been shown to be more stable than mRNAs in a range of specimen types and are also measurable with greater sensitivity than proteins4. This has led to considerable interest in the development of miRNAs as biomarkers for diverse molecular diagnostic applications, including lung diseases.
In the lung, miRNAs play important roles in developmental processes and the maintenance of homeostasis. Moreover, their abnormal expression has been associated with the development and progression of various pulmonary diseases5. Inflammatory lung disease induced by air pollution has demonstrated greater severity and poorer prognosis in females, indicating that hormones and the estrous cycle can regulate lung innate immunity and miRNA expression in response to environmental challenges6. In this protocol, we use ozone exposure, which is a major component of air pollution, to induce a form of lung inflammation in female mice that occurs in the absence of adaptive immunity. By using ozone, we are inducing the development of airway hyperresponsiveness that is associated with airway epithelial cell damage and an increase in neutrophils and inflammatory mediators in proximal airways7. Currently, there are not well-described protocols to characterize and analyze miRNAs across the estrous cycle in ozone-exposed mice. 
Below, we describe a simple method to identify estrous cycle stages and miRNA expression in lung tissue of female mice exposed to ozone. We also address effective bioinformatics approaches to miRNA discovery and target identification, with an emphasis on computational biology. We analyze the microarray data using limma, an R/Bioconductor software that provides an integrated solution for analyzing data from gene expression experiments8. Analysis of PCR array data from limma has an advantage in terms of power over t-test based procedures when using small number of arrays/samples to compare expression. To comprehend the biological context of miRNA expression results, we then used the functional analysis software. In order to understand the mechanisms regulating transcriptional changes and to predict likely outcomes, the software combines miRNA-expression datasets and knowledge from the literature9. This is an advantage when compared with software that just look for statistical enrichment in overlapping to sets of miRNAs.

<table><tbody><tr><td>C57BL/6J mice</td><td>The Jackson Laboratory</td><td>000664</td><td>8 weeks old</td></tr><tr><td>UltraPure Water</td><td>Thermo Fisher Scientific</td><td>10813012</td><td></td></tr><tr><td>Sterile plastic pipette</td><td>Fisher Scientific</td><td>13-711-25</td><td>Capacity: 1.7 mL</td></tr><tr><td>Frosted Microscope Slides</td><td>Thermo Fisher Scientific</td><td>2951TS</td><td></td></tr><tr><td>Light microscope</td><td>Microscope World</td><td>MW3-H5</td><td>10x and 20x objective</td></tr><tr><td>Ketathesia- Ketamine HCl Injection USP</td><td>Henry Schein Animal Health</td><td>55853</td><td>90 mg/kg. Controlled drug.</td></tr><tr><td>Xylazine Sterile Solution</td><td>Lloyd Laboratories</td><td>139-236</td><td>10 mg/kg. Controlled Drug.</td></tr><tr><td>Ethanol</td><td>Fisher Scientific</td><td>BP2818100</td><td>Dilute to 70% ethanol with water.</td></tr><tr><td>21 G gauge needle</td><td>BD Biosciences</td><td>305165</td><td></td></tr><tr><td>Syringe</td><td>Fisher Scientific</td><td>329654</td><td>1 mL</td></tr><tr><td>Operating Scissors</td><td>World Precision Instruments</td><td>501221, 504613</td><td>14 cm, Sharp/Blunt, Curved and 9 cm, Straight, Fine Sharp Tip</td></tr><tr><td>Tweezer Kit</td><td>World Precision Instruments</td><td>504616</td><td></td></tr><tr><td>Spectrum&amp;nbsp;Bessman Tissue Pulverizers</td><td>Fisher Scientific</td><td>08-418-1</td><td>Capacity: 10 to 50 mg</td></tr><tr><td>RNase-free Microfuge Tubes</td><td>Thermo Fisher Scientific</td><td>AM12400</td><td>1.5 mL</td></tr><tr><td>TRIzol Reagent</td><td>Thermo Fisher Scientific</td><td>15596026</td><td></td></tr><tr><td>Direct-zol RNA MiniPrep Plus</td><td>Zymo Research</td><td>R2071</td><td></td></tr><tr><td>NanoDrop</td><td>Thermo Fisher Scientific</td><td>ND-ONE-W</td><td></td></tr><tr><td>miScript II RT kit</td><td>Qiagen</td><td>218161</td><td></td></tr><tr><td>Mouse Inflammatory Response &amp;amp; Autoimmunity miRNA PCR Array</td><td>Qiagen</td><td>MIMM-105Z</td><td></td></tr><tr><td>Thin-walled, DNase-free, RNase-free PCR tubes</td><td>Thermo Fisher Scientific</td><td>AM12225</td><td>for 20 &amp;mu;L reactions</td></tr><tr><td>miRNeasy Serum/Plasma Spike-in Control</td><td>Qiagen</td><td>219610</td><td></td></tr><tr><td>Microsoft Excel</td><td>Microsoft Corporation</td><td></td><td>https://office.microsoft.com/excel/</td></tr><tr><td>Ingenuity Pathway Analysis</td><td>Qiagen</td><td></td><td>https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis/</td></tr><tr><td>R Software</td><td>The R Foundation</td><td></td><td>https://www.r-project.org/</td></tr><tr><td>Thermal cycler or chilling/heating block</td><td>General Lab Supplier</td><td></td><td></td></tr><tr><td>Microcentrifuge</td><td>General Lab Supplier</td><td></td><td></td></tr><tr><td>Real-time PCR cycler</td><td>General Lab Supplier</td><td></td><td></td></tr><tr><td>Multichannel pipettor</td><td>General Lab Supplier</td><td></td><td></td></tr><tr><td>RNA wash buffer</td><td>Zymo Research</td><td>R1003-3-48</td><td>48 mL</td></tr><tr><td>DNA digestion buffer</td><td>Zymo Research</td><td>E1010-1-4</td><td>4 mL</td></tr><tr><td>RNA pre-wash buffer</td><td>Zymo Research</td><td>R1020-2-25</td><td>25 mL</td></tr><tr><td>Ultraviolet ozone analyzer</td><td>Teledyne API</td><td>Model T400</td><td>http://www.teledyne-api.com/products/oxygen-compound-instruments/t400</td></tr><tr><td>Mass flow controllers</td><td>Sierra Instruments Inc</td><td>Flobox 951/954</td><td>http://www.sierrainstruments.com/products/954p.html</td></tr></tbody></table>

lung microrna profiling across the estrous cycle in ozone-exposed mice

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

MicroRNA (miRNA) profiling has become of interest to researchers working in various research areas of biology and medicine. Current studies show a promising future of using miRNAs in the diagnosis and care of lung diseases. Here, we define a protocol for miRNA profiling to measure the relative abundance of a group of miRNAs predicted to regulate inflammatory genes in the lung tissue from of an ozone-induced airway inflammation mouse model. Because it has been shown that circulating sex hormone levels can affect the regulation of lung innate immunity in females, the purpose of this method is to describe an inflammatory miRNA profiling protocol in female mice, taking into consideration the estrous cycle stage of each animal at the time of ozone exposure. We also address applicable bioinformatics approaches to miRNA discovery and target identification methods using limma, an R/Bioconductor software, and functional analysis software to understand the biological context and pathways associated with differential miRNA expression.

The different cell types observed in smears are used to identify the mouse estrous cycle stage (Figure 1). These are identified by cell morphology. During proestrus, cells are almost exclusively clusters of round-shaped, well-formed nucleated epithelial cells (Figure 1A). When the mouse is in the estrus stage, cells are cornified squamous epithelial cells, present in densely packed clusters (Figure 1B</strong...

Here we describe a method to assess lung expression of miRNAs that are predicted to regulate inflammatory genes using mice exposed to ozone or filtered air at different stages of the estrous cycle.

MicroRNA (miRNA) profiling has become of interest to researchers working in various research areas of biology and medicine. Current studies show a ...

lung-microrna-profiling-across-the-estrous-cycle-in-ozone-exposed-mice

Research

JoVE Journal

Immunology and Infection

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Cell-Specific Paired Interrogation of the Mouse Ovarian Epigenome and Transcriptome

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Learn to assess lung microRNA expression across the estrous cycle in ozone-exposed mice. This method reveals how hormonal fluctuations influence inflammatory gene regulation in female mice.

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

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