The work presented here was funded through NIH HLB U01 HL133360 awarded to JS and RV, NIDA R21 DA036372 awarded to JS and EVB, and T32 AA-007463 awarded to Jan Hoek in support of SJO&#39;S.

This study was carried out in accordance with the recommendations of Animal Care and Use Committee (IACUC) of Thomas Jefferson University and Drexel University College of Medicine. The protocol was approved by the Thomas Jefferson University and Drexel University College of Medicine IACUC.
1. Animal model
<ol>
	<li>Insert two 75 mg slow-release morphine sulfate pellets or two placebo pellets subcutaneously in adult male Sprague-Dawley rats.
	<ol>
		<li>Use a gown and gloves appropriately for minor sterile surgery. Shave the rat dorsum with clippers if necessary.</li>
		<li>Apply vet ointment to the animal&#39;s eyes. Anesthetize the rat with approximately 20 s of isoflurane inhalation. Anesthesia is confirmed by loss of consciousness.</li>
		<li>Make a midline incision in the rat dorsum with bead-sterilized blunt scissors and separate the dermis from the body wall with a bead-sterilized probe. Insert the pellets under the dermis with bead-sterilized forceps. Suture the incision closed with a sterile needle. 
		NOTE: The entire procedure takes about 5 min per rat. Fresh sterile gloves are used for each rat.</li>
		<li>Place the rat into an isolation cage for postsurgical recovery. Check for a heartbeat and regular respiratory rhythm. Observe the rat until consciousness is regained. Assess for postsurgical pain.</li>
		<li>Assess the rats 8 h postsurgery and every 12 h after for recovery and infection. Place rats in a cage with the rest of the cohort when they are fully recovered from surgery, about 24 h postsurgery.</li>
	</ol>
	</li>
	<li>Give an intraperitoneal naltrexone injection (75 mg/kg) to the G and the Withdrawal cohorts following 6 days of morphine exposure. 
	NOTE: There were four rat cohorts in this representative experiment (see Figure 1).</li>
</ol>
2. Sample harvesting
<ol>
	<li>Harvest the brain 6 days following the pellet insertion or 24 h following the naltrexone injection.
	<ol>
		<li>Place the animal in an isoflurane chamber for approximately 30 s or until loss of consciousness occurs, indicated by a lack of motion and decreased respiratory rate.</li>
		<li>Use a sharp guillotine to rapidly decapitate the animal.</li>
		<li>Dissect the brain out from the animal&#39;s skull.</li>
		<li>Use a sharp handheld razor to make the following gross incisions to the removed brain: First, slice off the cerebellum and discard. Second, separate the brainstem from the forebrain with a transverse incision. Third, hemisect the forebrain and/or brainstem with a midline sagittal incision.</li>
		<li>Place the forebrain and brainstem into a plastic tissue-embedding mold with 3-4 cm of Optimal Cutting Temperature compound (OCT) in the bottom of the mold. Cover the rest of the sample with OCT.</li>
		<li>Immediately place the plastic tissue-embedding mold with the sample covered with OCT into a bath containing dry ice and methanol. Do not let the methanol spill into the tissue-embedding mold. Keep the embedding mold with the brain sample in the methanol-ice bath until tissue collection is finished (~10-15 min maximum).</li>
		<li>Place the brain sample into a -80 &#176;C freezer as soon as possible.</li>
	</ol>
	</li>
	<li>Harvest the gut samples concurrently.
	<ol>
		<li>Following rapid decapitation, make a midline incision in the animal&#39;s abdomen with a scalpel.</li>
		<li>Find the cecum and sever its connection to the ascending colon.</li>
		<li>Squeeze the cecal contents into a 15 mL conical tube.</li>
		<li>Immediately place the conical tube on dry ice and put into a -80 &#176;C freezer as soon as possible. 
		NOTE: The small intestine contents can also be collected using the same methods as a negative control.</li>
	</ol>
	</li>
</ol>
3. Slicing
<ol>
	<li>Slice the hemisected rat forebrain using a cryostat.
	<ol>
		<li>Remove the plastic embedding mold with the forebrain from the -80 &#176;C freezer and place into a -20 &#176;C cryostat.</li>
		<li>Remove the OCT-embedded hemisected forebrain sample from the embedding mold. Use a razor to slice the corners of the plastic embedding mold vertically if necessary. Mount the forebrain for rostral to caudal coronal slicing on a cryostat chuck using OCT. 
		NOTE: Anatomic landmarks to identify the CeA include the optic tract and stria terminalis (Figure 2B). The optic tract branches from the optic chiasm and tracks dorsal-lateral as the brain is sliced rostral to caudal. When the optic tract has a morphology similar to what is seen in a rat brain atlas bregma -2.12 mm10, test slices may be viewed under a microscope. The optic tract and stria terminalis morphology can be checked in a rat brain atlas10 to identify the bregma and whether the CeA surrounds the stria terminals.</li>
		<li>Slice 10 &#181;m thick coronal sections from the hemisected forebrain rostral to caudal until sections containing the CeA are reached. 
		NOTE: The width and height of the sections are approximately 200 mm.</li>
		<li>Collect 10 &#181;m sections containing the CeA, or the preferred brain region, by thaw-mounting 10 &#181;m sections onto plain glass slides. Immediately place the glass slides onto a metal pan resting on dry ice. Put the slides with brain sections into a -80 &#176;C freezer as soon as possible. 
		NOTE: Multiple slices may be placed on the same slide. If using a different cell type stain for slices on the same slide, leave about 100 mm between slices so a hydrophobic pen can be used to separate cell type-specific antibody solutions on the slide. Leave about 20 mm from the edge of the slide on each side of the slice.</li>
	</ol>
	</li>
</ol>
4. Immunofluorescence staining
<ol>
	<li>Stain the forebrain sections for the brain cell of choice (e.g., neuron, microglia, astrocyte, etc.) using immunofluorescence.
	<ol>
		<li>Remove one or more slides with 10 &#181;m sections of the CeA from the -80 &#176;C freezer.</li>
		<li>Fix the slides with 75% ethanol for 30 s. Remove the excess liquid.</li>
		<li>Block the slices for 30 s with 2% bovine serum antigen (BSA) in 1x phosphate buffer saline (PBS). Wash 1x with PBS.</li>
		<li>Add a primary antibody solution to the slide for 2 min. Wash 1x with 2% BSA solution. 
		NOTE: The primary antibody solution is composed of 2% primary antibody, 1% RNase Out, and 96% of same BSA PBS solution for the blocking step above (step 4.1.3). The representative experiment used an anti-NeuN antibody, an anti-Cd11&#946; antibody, and an anti-GFAP antibody in the following quantities: 3 &#181;L of primary, 1.88 &#181;L of RNA inhibitor, and 145.12 &#181;L of BSA solution.</li>
		<li>Add the secondary antibody solution to the slide for 3 min. Wash 1x with PBS. 
		NOTE: The secondary antibody solution is composed of 1 &#181;L of goat anti-mouse 488 nm fluorescent tag (1:500), 2.5 &#181;L of RNA inhibitor, 1.3 &#181;L of DAPI (1:10,000), and 196.5 &#181;L of 2% BSA.</li>
	</ol>
	</li>
</ol>
5. Ethanol and xylene dehydration series
<ol>
	<li>Dip the slides into 75% ethanol for 30 s. Immediately after, dip the slides in 95% ethanol for 30 s. Immediately after, dip the slides into 100% ethanol for 30 s. Immediately after, dip the slides into a second container containing 100% ethanol for 30 s.</li>
	<li>Following the ethanol dehydration series, dip the slides into freshly poured xylene for 1 min. Immediately after, dip the slides into a second container of xylene for 4 min.</li>
	<li>Remove the slides from the xylene bath and let air dry in the dark for 5 min.</li>
	<li>Place the slides in a desiccator for 5 min to dry further.</li>
</ol>
6. Laser capture microdissection
<ol>
	<li>If stained, place the slide into the microscope and find the region of interest (CeA) using anatomic landmarks (i.e., the optic chiasm and stria terminalis).</li>
	<li>Use fluorescence to identify the stained cell type and its nucleus in the region of interest. Choose one cell or multiple cells if doing single cell pooled samples. Mark the cells of interest using LCM software.</li>
	<li>Place the LCM cap on top of the slice on the region of interest.</li>
	<li>Use test shots of an infrared (IR) laser to adjust the IR laser strength, size, and duration so that the LCM cap adhesive melts only over the area of the selected single cell. This ensures that no other cells will be collected other than the cells selected. 
	NOTE: In this representative experiment, 10 cell pools of the same cell type were used as a single sample to limit the cell-to-cell variability in gene expression between samples with the same treatment. However, this method can be used for true single cell experiments1,3.</li>
	<li>Select the individual cells to be collected for analysis using the LCM software tools (Figure 2C). Cells selected must be in the anatomic area of the CeA (or the brain region of choice) based on the rat brain atlas and the bregma10. Cells should be at least 3 &#181;m from the adjacent stained nuclei.</li>
	<li>Fire the IR laser to collect the identified single cells.</li>
	<li>Place the cap in the quality control (QC) station and view it to ensure that only the desired cells were selected. If other cells were mistakenly selected, an ultraviolet laser can be used to destroy the unwanted cells while the cap remains in the QC station.</li>
	<li>Take a photo of the tissue section from where the cell was collected to document its anatomic specificity. Record the distance of the slice from the bregma if appropriate using a rat brain atlas as a reference10.</li>
	<li>Remove the LCM cap from the QC station, attach the sample extraction device, and pipette 5.5 &#181;L of lysis buffer onto the sample. 
	NOTE: The lysis buffer solution consists of 0.5 &#181;L of lysis enhancer and 5 &#181;L of resuspension buffer.</li>
	<li>Fit the ExtracSure device onto a 0.5 mL microcentrifuge tube and place on a hotplate at 75 &#176;C for 15 min.</li>
	<li>Spin down the sample and lysis buffer for 30 s at low speed (0.01-0.02 x g) and place the collected sample into a -80 &#176;C freezer.</li>
</ol>
7. Single-cell microfluidic RT-qPCR
<ol>
	<li>Preamplification of single cell mRNA for 96.96 Dynamic Array Chip
	<ol>
		<li>Combine the forward and reverse mRNA qPCR gene primers for all the genes being assayed in a primer pool for preamplification (500 nM concentration each primer). For example, 1 &#181;L of 100 &#181;M primers in 80 &#181;L plus 120 &#181;L of DNA Suspension Buffer. 
		NOTE: The primer sequences used for the representative experiment can be found in O&#39;Sullivan et al.4.</li>
		<li>In a new 96 x 96 PCR plate, add 1 &#181;L of 5x VILO to each well.</li>
		<li>Remove LCM single cell samples from the samples stored at -80 &#176;C, let thaw briefly, centrifuge briefly at a low speed (0.01-0.02 x g), and add 5.5 &#181;L of the lysed single-cell sample to the PCR plate. Each sample is added to its own well.</li>
		<li>Place the PCR plate with the samples and VILO into the thermocycler and heat at 65 &#176;C for 1.5 min. Spin the plate for 1 min at 1,300 x g at 4 &#176;C and place the plate on ice.</li>
		<li>Add 0.15 &#181;L of 10x cDNA synthesis master mix, 0.12 &#181;L T4 Gene 32 protein, and 0.73 &#181;L of DNA suspension buffer to each well.</li>
		<li>Place the PCR plate into the thermocycler and run the following protocol: 25 &#176;C for 5 min, 50 &#176;C for 30 min, 55 &#176;C for 25 min, 60 &#176;C for 5 min, 70 &#176;C for 10 min, 4 &#176;C to end.</li>
		<li>Add 7.5 &#181;L of Taq polymerase master mix to each well.</li>
		<li>Add 1.5 &#181;L of the primer pool (see above) to each well.</li>
		<li>Place the PCR plate in the thermocycler and run the following preamplification protocol: 95 &#176;C for 10 min, followed by 22 cycles of 96 &#176;C for 5 sec, 60 &#176;C for 4 min.</li>
		<li>Add 0.6 &#181;L of exonuclease I reaction buffer 10x, 1.2 &#181;L exonuclease I, and 4.2 &#181;L of DNA suspension buffer to each well.</li>
		<li>Place the PCR plate in the thermocycler and run the following protocol: 37 &#176;C for 30 min, 80 &#176;C for 15 min.</li>
		<li>Add 54 &#181;L of TE buffer to each well. Spin the PCR plate at 1,300 x g at 5 min. Store at 4 &#176;C if immediately continuing to next step. Store at -20 &#176;C if waiting more than 12 h for next step.</li>
	</ol>
	</li>
	<li>Prepare the sample plate for the 96.96 Dynamic Array Chip.
	<ol>
		<li>In a new 96 well PCR plate, add 0.45 &#181;L of 20x DNA binding dye and 4.55 &#181;L of low ROX mastermix to each well.</li>
		<li>Add 3 &#181;L of preamplified sample to each well, spin the PCR plate at 1,300 x g, then put the plate on ice.</li>
	</ol>
	</li>
	<li>Prepare the assay plate for the 96.96 Dynamic Array Chip.
	<ol>
		<li>In a new 96 well PCR plate, add 3.75 &#181;L of 2x GE assay loading reagent and 1.25 &#181;L of DNA suspension buffer to each well.</li>
		<li>Add 2.5 &#181;L of 10 &#181;M qPCR primer to each corresponding well. Spin the PCR plate at 1,300 x g for 5 min.</li>
	</ol>
	</li>
	<li>Load and run the 96.96 Dynamic Array Chip.
	<ol>
		<li>Prime the chip with control line fluid.</li>
		<li>Place the chip in an IFC Controller HX and run the Prime (136X) script.</li>
		<li>Add 6 &#181;L of the sample from the PCR sample plate into the corresponding sample wells in the 96.96 Dynamic Array Chip.</li>
		<li>Add 6 &#181;L of the sample from the PCR assay plate into the corresponding assay wells in the 96.96 Dynamic Array Chip.</li>
		<li>Use needles to pop any air bubbles in the wells of the 96.96 Dynamic Array Chip.</li>
		<li>Place the 96.96 Dynamic Array Chip into the IFC Controller HX and run the Load Mix (136x) script.</li>
		<li>Remove the chip from the IFC Controller HX, peel off the protective sticker, and place the 96.96 Dynamic Array Chip into a microfluidic RT-qPCR platform. Run the GE Fast 96 x 96 PCR protocol (30 cycles). 
		NOTE: The RNA quality and validity of the results are assessed by multiple methods, including assay validation via gel electrophoresis, melting temperature curves, sample and assay replicates, and standard dilution series plots. Additionally, transcriptional findings can be validated by independent methods on brain hemisection including Western blot and immunofluorescence assays.</li>
	</ol>
	</li>
</ol>
8. Measuring the bacterial abundance with microfluidic RT-qPCR
<ol>
	<li>Extract the bacterial DNA following the directions of the stool DNA extraction kit.</li>
	<li>Estimate the bacterial DNA concentration using qPCR.</li>
	<li>Add the extracted bacterial DNA to a new PCR plate. Add 1 &#181;L of extracted bacterial DNA and 9 &#181;L of DNA Suspension buffer.</li>
	<li>Prepare the assay plate for the 48.48 Dynamic Array Chip (see steps 7.2.1-7.2.2)</li>
	<li>Prepare the sample plate for the 48.48 Dynamic Array Chip (see steps 7.3.1-7.3.2)
	<ol>
		<li>In a new 96 well PCR plate, add 0.45 &#181;L of 20x DNA binding dye and 4.55 &#181;L of low ROX mastermix to 48 wells.</li>
		<li>Add 3 &#181;L of the sample from the PCR plate containing the bacterial DNA to the 48 wells and spin down the PCR plate at 1,300 x g for 5 min. Store at 4 &#176;C.</li>
	</ol>
	</li>
	<li>Load and run the 48.48 Dynamic Array Chip (see steps 7.4.1-7.4.7).</li>
</ol>

<ol>
	<li>Park, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inputs+drive+cell+phenotype+variability.">Inputs drive cell phenotype variability.</a> Genome Research. 24, 930-941 (2014).</li><li>Park, J., Ogunnaike, B., Schwaber, J., Vadigepalli, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identifying+functional+gene+regulatory+network+phenotypes+underlying+single+cell+transcriptional+variability.">Identifying functional gene regulatory network phenotypes underlying single cell transcriptional variability.</a> Progress in Biophysics and Molecular Biology. 117, 87-98 (2015).</li><li>Park, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-Cell+Transcriptional+Analysis+Reveals+Novel+Neuronal+Phenotypes+and+Interaction+Networks+Involved+in+the+Central+Circadian+Clock.">Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock.</a> Frontiers in Neuroscience. 10, 481 (2016).</li><li>O'Sullivan, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-Cell+Glia+and+Neuron+Gene+Expression+in+the+Central+Amygdala+in+Opioid+Withdrawal+Suggests+Inflammation+With+Correlated+Gut+Dysbiosis.">Single-Cell Glia and Neuron Gene Expression in the Central Amygdala in Opioid Withdrawal Suggests Inflammation With Correlated Gut Dysbiosis.</a> Frontiers in Neuroscience. 13, 665 (2019).</li><li>Buettner, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+analysis+of+cell-to-cell+heterogeneity+in+single+cell+RNA-sequencing+data+reveals+hidden+subpopulations+of+cells.">Computational analysis of cell-to-cell heterogeneity in single cell RNA-sequencing data reveals hidden subpopulations of cells.</a> Nature Biotechnology. 33, 155-160 (2015).</li><li>Papalexi, E., Satija, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+RNA+sequencing+to+explore+immune+cell+heterogeneity.">Single-cell RNA sequencing to explore immune cell heterogeneity.</a> Nature Reviews Immunolology. 18, 35-45 (2018).</li><li>SEQC/MAQC-III Consortium. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comprehensive+assessment+of+RNA-seq+accuracy,+reproducibility+and+information+content+by+the+Sequencing+Quality+Control+Consortium.">A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium.</a> Nature Biotechnology. 32, 903-914 (2014).</li><li>Rowin, J., Xia, Y., Jung, B., Sun, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gut+inflammation+and+dysbiosis+in+human+motor+neuron+disease.">Gut inflammation and dysbiosis in human motor neuron disease.</a> Physiological Reports. 5, (2017).</li><li>Tamboli, C. P., Neut, C., Desreumaux, P., Colombel, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dysbiosis+in+inflammatory+bowel+disease.">Dysbiosis in inflammatory bowel disease.</a> Gut. 53, 1-4 (2004).</li><li>Paxinos, G., Watson, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Rat Brain in Stereotaxic Coordinates: Hard Cover Edition. , (2006).</li></ol>

The authors declare that they have no competing financial interests.

Single-cell biology has demonstrated the heterogeneity of cellular phenotypes and robustness of tissue function. These findings have provided insight into the organization of biological systems at both macro and micro scales. Here, we describe the combination of two methods, LCM and microfluidic qPCR, to obtain single-cell transcriptome measures that provide anatomic specificity and transcriptional accuracy at a relatively low cost (Figure 1). Our group takes a systems biology approach and o...

Measuring the gene expression profiles of single cells has demonstrated extensive phenotypic heterogeneity within a tissue. This complexity has complicated our understanding of the biological networks that govern tissue function. Our group and others have explored this phenomenon in many tissues and conditions1,2,3,4,5,6. These experiments not only suggest that regulation of gene expression networks underlie such heterogeneity, but also that single-cell resolution reveals a complexity in tissue function that tissue-level resolution fails to appreciate. Indeed, merely a small minority of cells may respond to a specific condition or challenge, but the impact of those cells on overall physiology may be substantial. Additionally, a system biology approach that applies multivariate methods to high dimensional datasets from multiple cell types and tissues can elucidate system-wide treatment effects.
We combine LCM and microfluidic RT-qPCR to obtain such datasets. We take this approach here in contrast to gathering single cells via fluorescence-activated cell sorting (FACS) and using RNA sequencing (RNA-seq) to measure their transcriptome. The advantage of LCM over FACS is that the exact anatomic specificity of single cells can be documented with LCM, relatively and absolutely. Further, while RNA-seq can measure more features that RT-qPCR, microfluidic RT-qPCR is less expensive and has a higher sensitivity and specificity7.
In this representative experiment, we investigated the effects of opioid dependence and naltrexone-precipitated opioid withdrawal on rat neuronal, microglia, and astrocyte gene expression in the central nucleus of the amygdala (CeA) and gut microflora abundance4. Four treatment groups were analyzed: 1) Placebo, 2) Morphine, 3) Naltrexone, and 4) Withdrawal (Figure 1). We found that opioid dependence did not substantially alter gene expression, but that opioid withdrawal induced the expression of inflammatory genes, Tnf in particular. Astrocytes were the most affected cell type. The gut microbiome was profoundly impacted by opioid withdrawal as indicated by a decrease in the Firmicutes to Bacteroides ratio, which is an established marker of gut dysbiosis8,9.

<table><tbody><tr><td>20X DNA Binding Dye</td><td>Fluidigm</td><td>100-7609</td><td>NA</td></tr><tr><td>2x GE Assay Loading Reagent</td><td>Fluidigm</td><td>85000802-R</td><td>NA</td></tr><tr><td>48.48 Dynamic Array IFC for Gene Expression</td><td>Fluidigm</td><td>BMK-M-48.48</td><td>NA</td></tr><tr><td>96.96 Dynamic Array IFC for Gene Expression</td><td>Fluidigm</td><td>BMK-M-96.96</td><td>NA</td></tr><tr><td>Anti-Cd11&amp;beta; Antibody</td><td>Genway Biotech</td><td>CCEC48</td><td>Microglia Stain</td></tr><tr><td>Anti-NeuN Antibody, clone A60</td><td>EMD Millipore</td><td>MAB377</td><td>Neuronal Stain</td></tr><tr><td>ArcturusXT Laser Capture Microdissection System</td><td>Arcturus</td><td>NA</td><td>NA</td></tr><tr><td>Biomark HD</td><td>Fluidigm</td><td>NA</td><td>RT-qPCR platform</td></tr><tr><td>Bovine Serum Antigen</td><td>Sigma-Aldrich</td><td>B4287</td><td></td></tr><tr><td>CapSure Macro LCM Caps</td><td>ThermoFisher Scientific</td><td>LCM0211</td><td>NA</td></tr><tr><td>CellDirect One-Step qRT-PCR Kit</td><td>ThermoFisher Scientific</td><td>11753500</td><td>Lysis buffer solution components</td></tr><tr><td>DAPI</td><td>ThermoFisher Scientific</td><td>62248</td><td>Nucleus Stain</td></tr><tr><td>DNA Suspension Buffer</td><td>TEKnova</td><td>T0221</td><td></td></tr><tr><td>Exonuclease I</td><td>New Englnad BioLabs, Inc.</td><td>M0293S</td><td>NA</td></tr><tr><td>ExtracSure Sample Extraction Device</td><td>ThermoFisher Scientific</td><td>LCM0208</td><td>NA</td></tr><tr><td>Fisherbrand Superfrost Plus Microscope Slides</td><td>ThermoFisher Scientific</td><td>22-037-246</td><td>Plain glass slides</td></tr><tr><td>GeneAmp Thin-Walled Reaction Tube</td><td>ThermoFisher Scientific</td><td>N8010611</td><td></td></tr><tr><td>GFAP Monoclonal Antibody</td><td>ThermoFisher Scientific</td><td>A-21294</td><td>Astrocyte Stain</td></tr><tr><td>Goat anti-Mouse IgG (H+L), Superclonal&amp;trade; Recombinant Secondary Antibody, Alexa Fluor 488</td><td>ThermoFisher Scientific</td><td>A28175</td><td>Seconadry Antibody</td></tr><tr><td>IFC Controller</td><td>Fluidigm</td><td>NA</td><td>NA</td></tr><tr><td>RNaseOut</td><td>ThermoFisher Scientific</td><td>10777019</td><td></td></tr><tr><td>SsoFast EvaGreen Supermix with Low Rox</td><td>Bio-Rad</td><td>PN 172-5211</td><td>Rox master mix</td></tr><tr><td>SuperScript VILO cDNA Synthesis Kit</td><td>ThermoFisher Scientific</td><td>11754250</td><td>Contains VILO and SuperScript</td></tr><tr><td>T4 Gene 32 Protein</td><td>New Englnad BioLabs, Inc.</td><td>M0300S</td><td>NA</td></tr><tr><td>TaqMan PreAmp Master Mix</td><td>ThermoFisher Scientific</td><td>4391128</td><td>NA</td></tr><tr><td>TE Buffer</td><td>TEKnova</td><td>T0225</td><td>NA</td></tr></tbody></table>

combining laser capture microdissection and microfluidic qpcr to analyze transcriptional profiles of single cells: a systems biology approach to opioid dependence

Profound transcriptional heterogeneity in anatomically adjacent single cells suggests that robust tissue functionality may be achieved by cellular phenotype diversity. Single-cell experiments investigating the network dynamics of biological systems demonstrate cellular and tissue responses to various conditions at biologically meaningful resolution. Herein, we explain our methods for gathering single cells from anatomically specific locations and accurately measuring a subset of their gene expression profiles. We combine laser capture microdissection (LCM) with microfluidic reverse transcription quantitative polymerase chain reactions (RT-qPCR). We also use this microfluidic RT-qPCR platform to measure the microbial abundance of gut contents.

The selection of the single cells was validated both visually and molecularly. Visually, cellular morphology was viewed before cell collection. Cells collected were then viewed at the QC station and the cellular nuclei stain (DAPI) overlapped with the single cell selection marker fluorescence. Figure 2A shows representative images of a slide with hemisected rat forebrain containing the CeA. Subsequent images (Figure 2</st...

Watch this Scientific Journal Video about Combining Laser Capture Microdissection and Microfluidic qPCR to Analyze Transcriptional Profiles of Single Cells: A Systems Biology Approach to Opioid Depend

Combining Laser Capture Microdissection and Microfluidic qPCR to Analyze Transcriptional Profiles of Single Cells: A Systems Biology Approach to Opioid Dependence

This protocol explains how to collect single neurons, microglia, and astrocytes from the central nucleus of the amygdala with high accuracy and anatomic specificity using laser capture microdissection. Additionally, we explain our use of microfluidic RT-qPCR to measure a subset of the transcriptome of these cells.

Profound transcriptional heterogeneity in anatomically adjacent single cells suggests that robust tissue functionality may be achieved by cellular ...

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5.2K Views.  Thomas Jefferson University. Dit is een zeer nauwkeurige en kosteneffectieve methode voor het begrijpen van genexpressie op het niveau van één cel. Het belangrijkste voordeel van deze techniek is dat we 96 monsters in één batch kunnen monteren. Dit hoge aantal monsters stelt ons in staat om cellulaire subfennotypes te identificeren met een anatomische specificiteit.De pijplijn van deze methode kan worden toegepast op elk biologisch probleem, elk systeem, elk weefsel, om te informeren naar de individuele cellul...

Video: Combining Laser Capture Microdissection and Microfluidic qPCR to Analyze Transcriptional Profiles of Single Cells: A Systems Biology Approach to Opioid Dependence

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience

The encoding of experiences in the brain and the consolidation of long-term memories depend on gene transcription. Identifying the function of specific genes in encoding experience is one of the main objectives of molecular neuroscience. Furthermore, the functional association of defined genes with specific behaviors has implications for understanding the basis of neuropsychiatric disorders. Induction of robust transcription programs has been observed in the brains of mice following various behavioral manipulations. While some genetic elements are utilized recurrently following different behavioral manipulations and in different brain nuclei, transcriptional programs are overall unique to the inducing stimuli and the structure in which they are studied1,2.
In this publication, a protocol is described for robust and comprehensive transcriptional profiling from brain nuclei of mice in response to behavioral manipulation. The protocol is demonstrated in the context of analysis of gene expression dynamics in the nucleus accumbens following acute cocaine experience. Subsequent to a defined in vivo experience, the target neural tissue is dissected; followed by RNA purification, reverse transcription and utilization of microfluidic arrays for comprehensive qPCR analysis of multiple target genes. This protocol is geared towards comprehensive analysis (addressing 50-500 genes) of limiting quantities of starting material, such as small brain samples or even single cells.
The protocol is most advantageous for parallel analysis of multiple samples (e.g. single cells, dynamic analysis following pharmaceutical, viral or behavioral perturbations). However, the protocol could also serve for the characterization and quality assurance of samples prior to whole-genome studies by microarrays or RNAseq, as well as validation of data obtained from whole-genome studies.

This manuscript describes a protocol that applies comprehensive profiling for analysis of transcriptional programs induced in specific brain nuclei of rodents following behavioral paradigms. Herein, this approach is illustrated in the context of profiling genes induced in the nucleus accumbens (NAc) of mice following acute cocaine exposure, utilizing microfluidic qPCR arrays.

The encoding of experiences in the brain and the consolidation of long-term memories depend on gene transcription. Identifying the function of specific ...

Behavior

Transcriptome Analysis of Single Cells

Many gene expression analysis techniques rely on material isolated from heterogeneous populations of cells from tissue homogenates or cells in culture.1,2,3 In the case of the brain, regions such as the hippocampus contain a complex arrangement of different cell types, each with distinct mRNA profiles. The ability to harvest single cells allows for a more in depth investigation into the molecular differences between and within cell populations. We describe a simple and rapid method for harvesting cells for further processing. Pipettes often used in electrophysiology are utilized to isolate (using aspiration) a cell of interest and conveniently deposit it into an Eppendorf tube for further processing with any number of molecular biology techniques. Our protocol can be modified for the harvest of dendrites from cell culture or even individual cells from acute slices.
We also describe the aRNA amplification method as a major downstream application of single cell isolations. This method was developed previously by our lab as an alternative to other gene expression analysis techniques such as reverse-transcription or real-time polymerase chain reaction (PCR).4,5,6,7,8 This technique provides for linear amplification of the polyadenylated RNA beginning with only femtograms of material and resulting in microgram amounts of antisense RNA. The linearly amplified material provides a more accurate estimation than PCR exponential amplification of the relative abundance of components of the transcriptome of the isolated cell. The basic procedure consists of two rounds of amplification. Briefly, a T7 RNA polymerase promoter site is incorporated into double stranded cDNA created from the mRNA transcripts. An overnight in vitro transcription (IVT) reaction is then performed in which T7 RNA polymerase produces many antisense transcripts from the double stranded cDNA. The second round repeats this process but with some technical differences since the starting material is antisense RNA. It is standard to repeat the second round, resulting in three rounds of amplification. Often, the third round in vitro transcription reaction is performed using biotinylated nucleoside triphosphates so that the antisense RNA produced can be hybridized and detected on a microarray.7,8

In this article we describe a simple method for the harvesting of single cells from rat primary neuronal cultures and subsequent transcriptome analysis using aRNA amplification. This approach is generalizable to any cell type.

Many gene expression analysis techniques rely on material isolated from heterogeneous populations of cells from tissue homogenates or cells in ...

Neuroscience

Laser Capture Microdissection of Enriched Populations of Neurons or Single Neurons for Gene Expression Analysis After Traumatic Brain Injury

Long-term cognitive disability after TBI is associated with injury-induced neurodegeneration in the hippocampus-a region in the medial temporal lobe that is critical for learning, memory and executive function.1,2 Hence our studies focus on gene expression analysis of specific neuronal populations in distinct subregions of the hippocampus. The technique of laser capture microdissection (LCM), introduced in 1996 by Emmert-Buck, et al.,3 has allowed for significant advances in gene expression analysis of single cells and enriched populations of cells from heterogeneous tissues such as the mammalian brain that contains thousands of functional cell types.4 We use LCM and a well established rat model of traumatic brain injury (TBI) to investigate the molecular mechanisms that underlie the pathogenesis of TBI. Following fluid-percussion TBI, brains are removed at pre-determined times post-injury, immediately frozen on dry ice, and prepared for sectioning in a cryostat. The rat brains can be embedded in OCT and sectioned immediately, or stored several months at -80 &deg;C before sectioning for laser capture microdissection. Additionally, we use LCM to study the effects of TBI on circadian rhythms. For this, we capture neurons from the suprachiasmatic nuclei that contain the master clock of the mammalian brain. Here, we demonstrate the use of LCM to obtain single identified neurons (injured and degenerating, Fluoro-Jade-positive, or uninjured, Fluoro-Jade-negative) and enriched populations of hippocampal neurons for subsequent gene expression analysis by real time PCR and/or whole-genome microarrays. These LCM-enabled studies have revealed that the selective vulnerability of anatomically distinct regions of the rat hippocampus are reflected in the different gene expression profiles of different populations of neurons obtained by LCM from these distinct regions. The results from our single-cell studies, where we compare the transcriptional profiles of dying and adjacent surviving hippocampal neurons, suggest the existence of a cell survival rheostat that regulates cell death and survival after TBI.

We describe how to use laser capture microdissection (LCM) to obtain enriched populations of hippocampal neurons or single neurons from frozen sections of the injured rat brain for subsequent gene expression analysis using quantitative real time PCR and/or whole-genome microarrays.

Long-term cognitive disability after TBI is associated with injury-induced neurodegeneration in the hippocampus-a region in the medial temporal lobe that ...

Laser Microdissection Applied to Gene Expression Profiling of Subset of Cells from the Drosophila Wing Disc

Heterogeneous nature of tissues has proven to be a limiting factor in the amount of information that can be generated from biological samples, compromising downstream analyses. Considering the complex and dynamic cellular associations existing within many tissues, in order to recapitulate the in vivo interactions thorough molecular analysis one must be able to analyze specific cell populations within their native context. Laser-mediated microdissection can achieve this goal, allowing unambiguous identification and successful harvest of cells of interest under direct microscopic visualization while maintaining molecular integrity. We have applied this technology to analyse gene expression within defined areas of the developing Drosophila wing disc, which represents an advantageous model system to study growth control, cell differentiation and organogenesis. Larval imaginal discs are precociously subdivided into anterior and posterior, dorsal and ventral compartments by lineage restriction boundaries. Making use of the inducible GAL4-UAS binary expression system, each of these compartments can be specifically labelled in transgenic flies expressing an UAS-GFP transgene under the control of the appropriate GAL4-driver construct. In the transgenic discs, gene expression profiling of discrete subsets of cells can precisely be determined after laser-mediated microdissection, using the fluorescent GFP signal to guide laser cut. 
Among the variety of downstream applications, we focused on RNA transcript profiling after localised RNA interference (RNAi). With the advent of RNAi technology, GFP labelling can be coupled with localised knockdown of a given gene, allowing to determinate the transcriptional response of a discrete cell population to the specific gene silencing. To validate this approach, we dissected equivalent areas of the disc from the posterior (labelled by GFP expression), and the anterior (unlabelled) compartment upon regional silencing in the P compartment of an otherwise ubiquitously expressed gene. RNA was extracted from microdissected silenced and unsilenced areas and comparative gene expression profiling determined by quantitative real-time RT-PCR. We show that this method can effectively be applied for accurate transcriptomics of subsets of cells within the Drosophila imaginal discs. Indeed, while massive disc preparation as source of RNA generally assumes cell homogeneity, it is well known that transcriptional expression can vary greatly within these structures in consequence of positional information. Using localized fluorescent GFP signal to guide laser cut, more accurate transcriptional analyses can be performed and profitably applied to disparate applications, including transcript profiling of distinct cell lineages within their native context.

Laser Microdissection Applied to Gene Expression Profiling of Subset of Cells from the Drosophila Wing Disc

Laser microdissection was applied to analyse gene expression profiling in specific compartments of Drosophila wing disc subjected to localised RNAi in vivo. RNA extracted from equivalent areas of silenced and unsilenced compartments was analysed by quantitative RT-PCR to determine comparative gene expression profiling within the context of native tissue microecology.

Heterogeneous nature of tissues has proven to be a limiting factor in the amount of information that can be generated from biological samples, ...

Biology

Olfactory Neurons Obtained through Nasal Biopsy Combined with Laser-Capture Microdissection: A Potential Approach to Study Treatment Response in Mental Disorders

Bipolar disorder (BD) is a severe neuropsychiatric disorder with poorly understood pathophysiology and typically treated with the mood stabilizer, lithium carbonate. Animal studies as well as human genetic studies indicate that lithium affects molecular targets that are involved in neuronal growth, survival and maturation, and notably molecules involved in Wnt signaling. Given the ethical challenge to obtaining brain biopsies for investigating dynamic molecular changes associated with lithium-response in the central nervous system (CNS), one may consider the use of neurons obtained from olfactory tissues to achieve this goal.The olfactory epithelium contains olfactory receptor neurons at different stages of development and glial-like supporting cells. This provides a unique opportunity to study dynamic changes in the CNS of patients with neuropsychiatric diseases, using olfactory tissue safely obtained from nasal biopsies. To overcome the drawback posed by substantial contamination of biopsied olfactory tissue with non-neuronal cells, a novel approach to obtain enriched neuronal cell populations was developed by combining nasal biopsies with laser-capture microdissection. In this study, a system for investigating treatment-associated dynamic molecular changes in neuronal tissue was developed and validated, using a small pilot sample of BD patients recruited for the study of the molecular mechanisms of lithium treatment response.

In this study, a novel platform to investigate intraneuronal molecular signatures of treatment response in bipolar disorder (BD) was developed and validated. Olfactory epithelium from BD patients was obtained through nasal biopsies. Then laser-capture microdissection was combined with Real Time RT PCR to investigate the molecular signature of lithium response in BD.

Bipolar disorder (BD) is a severe neuropsychiatric disorder with poorly understood pathophysiology and typically treated with the mood stabilizer, lithium ...

Laser Capture Microdissection - A Demonstration of the Isolation of Individual Dopamine Neurons and the Entire Ventral Tegmental Area

Laser capture microdissection (LCM) is used to isolate a concentrated population of individual cells or precise anatomical regions of tissue from tissue sections on a microscope slide. When combined with immunohistochemistry, LCM can be used to isolate individual cells types based on a specific protein marker. Here, the LCM technique is described for collecting a specific population of dopamine neurons directly labeled with&#160;tyrosine hydroxylase immunohistochemistry and for isolation of the dopamine neuron containing region of the ventral tegmental area using indirect tyrosine hydroxylase immunohistochemistry on a section adjacent to those used for LCM. An infrared (IR) capture laser is used to both dissect individual neurons as well as the ventral tegmental area off glass slides and onto an LCM cap for analysis. Complete dehydration of the tissue with 100% ethanol and xylene is critical. The combination of the IR capture laser and the ultraviolet (UV) cutting laser is used to isolate individual dopamine neurons or the ventral tegmental area when using PEN membrane slides. A PEN membrane slide has significant advantages over a glass slide as it offers better consistency in capturing and collecting cells, is faster collecting large pieces of tissue, is less reliant on dehydration and results in complete removal of the tissue from the slide. Although removal of large areas of tissue from a glass slide is feasible, it is considerably more time consuming and frequently leaves some residual tissue behind. Data shown here demonstrate that RNA of sufficient quantity and quality can be obtained using these procedures for quantitative PCR measurements. Although RNA and DNA are the most commonly isolated molecules from tissue and cells collected with LCM, isolation and measurement of microRNA, protein and epigenetic changes in DNA can also benefit from the enhanced anatomical and cellular resolution obtained using LCM.

The isolation of individual dopamine neurons or the ventral tegmental area with direct or indirect immunohistochemistry is demonstrated using laser capture microdissection. Parameters for isolation of tissue from a glass slide using an infrared laser and from membrane slides using the combination of an infrared and ultraviolet laser are discussed.

Laser capture microdissection (LCM) is used to isolate a concentrated population of individual cells or precise anatomical regions of tissue from tissue ...

Fluorescence Activated Cell Sorting (FACS) and Gene Expression Analysis of Fos-expressing Neurons from Fresh and Frozen Rat Brain Tissue

The study of neuroplasticity and molecular alterations in learned behaviors is switching from the study of whole brain regions to the study of specific sets of sparsely distributed activated neurons called neuronal ensembles that mediate learned associations. Fluorescence Activated Cell Sorting (FACS) has recently been optimized for adult rat brain tissue and allowed isolation of activated neurons using antibodies against the neuronal marker NeuN and Fos protein, a marker of strongly activated neurons. Until now, Fos-expressing neurons and other cell types were isolated from fresh tissue, which entailed long processing days and allowed very limited numbers of brain samples to be assessed after lengthy and complex behavioral procedures. Here we found that yields of Fos-expressing neurons and Fos mRNA from dorsal striatum were similar between freshly dissected tissue and tissue frozen at -80 &#186;C for 3 - 21 days. In addition, we confirmed the phenotype of the NeuN-positive and NeuN-negative sorted cells by assessing gene expression of neuronal (NeuN), astrocytic (GFAP), oligodendrocytic (Oligo2) and microgial (Iba1) markers, which indicates that frozen tissue can also be used for FACS isolation of glial cell types. Overall, it is possible to collect, dissect and freeze brain tissue for multiple FACS sessions. This maximizes the amount of data obtained from valuable animal subjects that have often undergone long and complex behavioral procedures.

Fluorescence Activated Cell Sorting FACS and Gene Expression Analysis of Fos-expressing Neurons from Fresh and Frozen Rat Brain Tissue

Here we present a Fluorescence Activated Cell Sorting (FACS) protocol to study molecular alterations in Fos-expressing neuronal ensembles from both fresh and frozen brain tissue. The use of frozen tissue allows FACS isolation of many brain areas over multiple sessions to maximize the use of valuable animal subjects.

The study of neuroplasticity and molecular alterations in learned behaviors is switching from the study of whole brain regions to the study of specific ...

RNA Isolation from Cell Specific Subpopulations Using Laser-capture Microdissection Combined with Rapid Immunolabeling

Laser capture microdissection (LCM) allows the isolation of specific cells from thin tissue sections with high spatial resolution. Effective LCM requires precise identification of cells subpopulations from a heterogeneous tissue. Identification of cells of interest for LCM is usually based on morphological criteria or on fluorescent protein reporters. The combination of LCM and rapid immunolabeling offers an alternative and efficient means to visualize specific cell types and to isolate them from surrounding tissue. High-quality RNA can then be extracted from a pure cell population and further processed for downstream applications, including RNA-sequencing, microarray or qRT-PCR. This approach has been previously performed and briefly described in few publications. The goal of this article is to illustrate how to perform rapid immunolabeling of a cell population while keeping RNA integrity, and how to isolate these specific cells using LCM. Herein, we illustrated this multi-step procedure by immunolabeling and capturing dopaminergic cells in brain tissue from one-day-old mice. We highlight key critical steps that deserve special consideration. This protocol can be adapted to a variety of tissues and cells of interest. Researchers from different fields will likely benefit from the demonstration of this approach.

Gene expression analysis of a subset of cells in a specific tissue represents a major challenge. This article describes how to isolate high-quality total RNA from a specific cell population by combining a rapid immunolabeling method with laser capture microdissection.

Laser capture microdissection (LCM) allows the isolation of specific cells from thin tissue sections with high spatial resolution. Effective LCM requires ...

Investigating Drivers of Antireward in Addiction Behavior with Anatomically Specific Single-Cell Gene Expression Methods

Increasing rates of addiction behavior have motivated mental health researchers and clinicians alike to understand antireward and recovery. This shift away from reward and commencement necessitates novel perspectives, paradigms, and hypotheses along with an expansion of the methods applied to investigate addiction. Here, we provide an example: A systems biology approach to investigate antireward that combines laser capture microdissection (LCM) and high-throughput microfluidic reverse transcription quantitative polymerase chain reactions (RT-qPCR). Gene expression network dynamics were measured and a key driver of neurovisceral dysregulation in alcohol and opioid withdrawal, neuroinflammation, was identified. This combination of technologies provides anatomic and phenotypic specificity at single-cell resolution with high-throughput sensitivity and specific gene expression measures yielding both hypothesis-generating datasets and mechanistic possibilities that generate opportunities for novel insights and treatments.

The combination of laser capture microdissection and microfluidic RT-qPCR provides anatomic and biotechnical specificity in measuring the transcriptome in single neurons and glia. Applying creative methods with a system's biology approach to psychiatric disease may lead to breakthroughs in understanding and treatment such as the neuroinflammation antireward hypothesis in addiction.

Increasing rates of addiction behavior have motivated mental health researchers and clinicians alike to understand antireward and recovery. This shift ...

Laser-assisted Microdissection (LAM) as a Tool for Transcriptional Profiling of Individual Cell Types

The understanding of developmental processes at the molecular level requires insights into transcriptional regulation, and thus the transcriptome, at the level of individual cell types. While the methods described here are generally applicable to a wide range of species and cell types, our research focuses on plant reproduction. Plant cultivation and seed production is of crucial importance for human and animal nutrition. A detailed understanding of the regulatory networks that govern the formation of the reproductive lineage (germline) and ultimately of seeds is a precondition for the targeted manipulation of plant reproduction. In particular, the engineering of apomixis (asexual reproduction through seeds) into crop plants promises great improvements, as it leads to the formation of clonal seeds that are genetically identical to the mother plant. Consequently, the cell types of the female germline are of major importance for the understanding and engineering of apomixis. However, as the corresponding cells are deeply embedded within the floral tissues, they are very difficult to access for experimental analyses, including cell-type specific transcriptomics. To overcome this limitation, sections of individual cells can be isolated by laser-assisted microdissection (LAM). While LAM in combination with transcriptional profiling allows the identification of genes and pathways active in any cell type with high specificity, establishing a suitable protocol can be challenging. Specifically, the quality of RNA obtained after LAM can be compromised, especially when small, single cells are targeted. To circumvent this problem, we have established a workflow for LAM that reproducibly results in high RNA quality that is well suitable for transcriptomics, as exemplified here by the isolation of cells of the female germline in apomictic Boechera. In this protocol, procedures are described for tissue preparation and LAM, also with regard to RNA extraction and quality control.

Laser-assisted Microdissection LAM as a Tool for Transcriptional Profiling of Individual Cell Types

Here we present a protocol for laser-assisted microdissection of specific plant cell types for transcriptional profiling. While the protocol is suitable for different species and cell types, the focus is on highly inaccessible cells of the female germline important for sexual and apomictic reproduction in the crucifer genus Boechera.

The understanding of developmental processes at the molecular level requires insights into transcriptional regulation, and thus the transcriptome, at the ...

Combining Laser Capture Microdissection and Microfluidic qPCR to Analyze Transcriptional Profiles of Single Cells: A Systems Biology Approach to Opioid Dependence

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