This work was supported by grants from the NIH (5R01MH094705-04 and R01MH109665-01 to Z.J.H.), by the CSHL Robertson Neuroscience Fund (to Z.J.H.), and by a NARSAD Post-Doctoral Fellowship (to A.P.).

<ol><li>Macosko, E. Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Highly+Parallel+Genome-wide+Expression+Profiling+of+Individual+Cells+Using+Nanoliter+Droplets%5BTitle%5D)+AND+%22Cell%22%5BJournal%5D)">Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.</a> Cell. 161 (5), 1202-1214 (2015).</li>
<li>Klein, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Droplet+barcoding+for+single-cell+transcriptomics+applied+to+embryonic+stem+cells%5BTitle%5D)+AND+%22Cell%22%5BJournal%5D)">Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.</a> Cell. 161 (5), 1187-1201 (2015).</li>
<li>Xin, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Use+of+the+Fluidigm+C1+platform+for+RNA+sequencing+of+single+mouse+pancreatic+islet+cells%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Sciences+of+the+United+States+of+America%22%5BJournal%5D)">Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells.</a> Proceedings of the National Academy of Sciences of the United States of America. 113 (12), 3293-3298 (2016).</li>
<li>Gao, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Nanogrid+single-nucleus+RNA+sequencing+reveals+phenotypic+diversity+in+breast+cancer%5BTitle%5D)+AND+%22Nature+Communications%22%5BJournal%5D)">Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer.</a> Nature Communications. 8 (1), 228(2017).</li>
<li>Yuan, J., Sims, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((An+Automated+Microwell+Platform+for+Large-Scale+Single+Cell+RNA-Seq%5BTitle%5D)+AND+%22Scientific+Reports%22%5BJournal%5D)">An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq.</a> Scientific Reports. 6, 33883(2016).</li>
<li>Eberwine, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Analysis+of+gene+expression+in+single+live+neurons%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Sciences+of+the+United+States+of+America%22%5BJournal%5D)">Analysis of gene expression in single live neurons.</a> Proceedings of the National Academy of Sciences of the United States of America. 89 (7), 3010-3014 (1992).</li>
<li>Hashimshony, T., Wagner, F., Sher, N., Yanai, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((CEL-Seq%3A+Single-Cell+RNA-Seq+by+Multiplexed+Linear+Amplification%5BTitle%5D)+AND+%22Cell+Reports%22%5BJournal%5D)">CEL-Seq: Single-Cell RNA-Seq by Multiplexed Linear Amplification.</a> Cell Reports. 2 (3), 666-673 (2012).</li>
<li>Paul, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Transcriptional+Architecture+of+Synaptic+Communication+Delineates+GABAergic+Neuron+Identity%5BTitle%5D)+AND+%22Cell%22%5BJournal%5D)">Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity.</a> Cell. 171 (3), 522-539 (2017).</li>
<li>Zeisel, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cell+types+in+the+mouse+cortex+and+hippocampus+revealed+by+single-cell+RNA-seq%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq.</a> Science. 1934, (2015).</li>
<li>Tasic, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Adult+mouse+cortical+cell+taxonomy+revealed+by+single+cell+transcriptomics%5BTitle%5D)+AND+%22Nature+Neuroscience%22%5BJournal%5D)">Adult mouse cortical cell taxonomy revealed by single cell transcriptomics.</a> Nature Neuroscience. 19, 335-346 (2016).</li>
<li>Okaty, B. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multi-Scale+Molecular+Deconstruction+of+the+Serotonin+Neuron+System%5BTitle%5D)+AND+%22Neuron%22%5BJournal%5D)">Multi-Scale Molecular Deconstruction of the Serotonin Neuron System.</a> Neuron. 88 (4), 774-791 (2015).</li>
<li>Poulin, J. F., Tasic, B., Hjerling-Leffler, J., Trimarchi, J. M., Awatramani, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Disentangling+neural+cell+diversity+using+single-cell+transcriptomics%5BTitle%5D)+AND+%22Nature+Neuroscience%22%5BJournal%5D)">Disentangling neural cell diversity using single-cell transcriptomics.</a> Nature Neuroscience. 19 (9), 1131-1141 (2016).</li>
<li>Crow, M., Paul, A., Ballouz, S., Huang, Z. J., Gillis, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Exploiting+single-cell+expression+to+characterize+co-expression+replicability%5BTitle%5D)+AND+%22Genome+Biology%22%5BJournal%5D)">Exploiting single-cell expression to characterize co-expression replicability.</a> Genome Biology. 17, 101(2016).</li>
<li>Crow, M., Paul, A., Ballouz, S., Huang, Z. J., Gillis, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Characterizing+the+replicability+of+cell+types+defined+by+single+cell+RNA-sequencing+data+using+MetaNeighbor%5BTitle%5D)+AND+%22Nature+Communications%22%5BJournal%5D)">Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor.</a> Nature Communications. 9 (1), (2018).</li>
<li>Hrvatin, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+analysis+of+experience-dependent+transcriptomic+states+in+the+mouse+visual+cortex%5BTitle%5D)+AND+%22Nature+Neuroscience%22%5BJournal%5D)">Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex.</a> Nature Neuroscience. 21 (1), 120-129 (2018).</li>
</ol>

Authors declare that there are no competing financial interests.

The manual sorting protocol is suitable for a supervised RNA sequencing of neuron populations that are either sparsely labeled in the mice brain or are representing a rare cell population that is otherwise not feasible to study using current high-throughput cell sorting and amplification methods. Cells subjected to FACS usually undergo sheath and sample line pressures in the range of ~9&#8211;14 psi, depending on nozzle size and desired event rates. In addition, upon being ejected from the nozzle, the cells can land hard...

Single-cell RNA sequencing (RNA-seq) has transformed transcriptomic studies. While large-scale single-cell RNAseq can be performed using a variety of techniques, such as droplets1,2, microfluidics3, nanogrids4, and microwells5, most methods cannot sort defined cell types that express genetically encoded fluorophores. To isolate a select cell population, fluorescence-activated cell sorting (FACS) is often used to sort labeled cells in a single-cell mode. However, FACS has some restrictions and requires meticulous sample processing steps. First, a large number of input cells are typically needed (often several million cells per mL), with a significant fraction (&#62;15&#8211;20%) containing the labeled population. Second, cell preparations may require multiple rounds of density gradient centrifugation steps to remove glial fraction, debris, and cell clumps that might otherwise clog the nozzle or flow cell. Third, FACS usually employs staining and destaining steps for live/dead staining (e.g., 4&#8242;,6-diamidino-2-phenylindole (DAPI), propidium iodide (PI), and Cytotracker dyes), which take up additional time. Fourth, as a rule of thumb for two-color sorting (such as DAPI and green/red fluorescent protein (GFP/RFP)), usually two samples and one control are needed, requiring an unlabeled sample to be processed in addition to the desired mouse strain. Fifth, filtering is often performed multiple times before and during sample sorting to proactively prevent clogged sample lines in an FACS machine. Sixth, time must be allotted in most commonly used FACS setups to initialize and stabilize the fluid stream and perform droplet calibration. Seventh, control samples are typically run in sequence prior to the actual sample collection to set up compensation matrices, doublet rejection, setting gates, etc. Users either perform steps six and seven themselves ahead of time or require the assistance of a technician in parallel. Finally, post-FACS, there are often steps to ensure that only labeled single cells are present in each well; for example, by checking samples in a high-content screening setup such as a fast plate imager.
To circumvent the steps outlined above and facilitate a relatively quick, targeted sequencing of a small population of single fluorescently labeled neurons, we describe a manual sorting procedure followed by two rounds of a highly sensitive in vitro amplification protocol, called double in-vitro transcription with absolute counts sequencing (DIVA-Seq). The RNA amplification and cDNA library generation are adapted from Eberwine et al.6 and Hashimshony et al.7, with certain modifications to suit mouse interneurons that have smaller cellular volumes; furthermore, we have also found that it is equally useful for excitatory pyramidal neurons.

<table><tbody><tr><td>ERCC RNA Spike-In Control Mixes</td><td>Thermo Fisher</td><td>Cat# 4456740</td><td></td></tr><tr><td>SuperScript III</td><td>Thermo Fisher</td><td>Cat# 18080093</td><td></td></tr><tr><td>RNaseOUT Recombinant Ribonuclease Inhibitor</td><td>Thermo Fisher</td><td>Cat# 10777019</td><td></td></tr><tr><td>RNA fragmentation buffer</td><td>New England Biolabs</td><td>Cat# E6105S</td><td></td></tr><tr><td>RNA MinElute kit</td><td>Qiagen</td><td>Cat# 74204</td><td></td></tr><tr><td>Antarctic phosphatase</td><td>New England Biolabs</td><td>Cat# M0289</td><td></td></tr><tr><td>Poly nucleotide kinase</td><td>New England Biolabs</td><td>Cat# M0201</td><td></td></tr><tr><td>T4 RNA ligase2, truncated</td><td>New England Biolabs</td><td>Cat# M0242</td><td></td></tr><tr><td>Ampure Xp magnetic&amp;nbsp; beads</td><td>Beckman Coulter</td><td>Cat# A63880</td><td></td></tr><tr><td>SPRIselect size selection magnetic beads</td><td>Thermo Fisher</td><td>Cat# B23317</td><td></td></tr><tr><td>DL-AP5</td><td>Tocris</td><td>Cat# 0105</td><td></td></tr><tr><td>CNQX</td><td>Tocris</td><td>Cat# 1045</td><td></td></tr><tr><td>TTX</td><td>Tocris</td><td>Cat# 1078</td><td></td></tr><tr><td>Protease from Streptomyces griseus</td><td>Sigma-Aldrich</td><td>Cat# P5147</td><td></td></tr><tr><td>Message Amp II kit</td><td>Thermo Fisher</td><td>Cat# AM1751</td><td></td></tr><tr><td>Carbogen</td><td>Airgas</td><td>Cat# UN3156</td><td></td></tr><tr><td>Sylgard 184</td><td>Sigma-Aldrich</td><td>Cat# 761036</td><td></td></tr><tr><td>Illumina TrueSeq smallRNA kit</td><td>Illumina</td><td>Cat# RS-200-0012</td><td></td></tr><tr><td>Bioanalyzer RNA Pico chip</td><td>Agilent</td><td>Cat# 5067-1513</td><td></td></tr><tr><td>Bioanalyzer High Sensitvity DNA chip</td><td>Agilent</td><td>Cat# 5067-4626</td><td></td></tr><tr><td>Bioanalyzer 2100</td><td>Agilent</td><td></td><td></td></tr><tr><td>Dissection microscope with fluorescence and bright field illumination with DIC optics.&amp;nbsp; (Leica model MZ-16F).</td><td>Leica</td><td>Model MZ-16F</td><td></td></tr><tr><td>Glass microcapillary: Borosilicate capillary tubes 500/pk. OD= 1 mm, ID=0.58 mm, wall= 0.21 mm, Length= 150 mm.</td><td>Warner instruments</td><td>Model GC100-15, Order# 30-0017</td><td></td></tr><tr><td>Capillary pipette puller</td><td>Sutter Instruments Co</td><td>P-97</td><td></td></tr><tr><td>Vibratome</td><td>Thermo Microm</td><td>HM 650V</td><td></td></tr><tr><td>Vibratome tissue cooling unit</td><td>Thermo Microm</td><td>CU 65</td><td></td></tr></tbody></table>

single-cell rna sequencing of fluorescently labeled mouse neurons using manual sorting and double in vitro transcription with absolute counts sequencing (diva-seq)

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing platforms process all input cells indiscriminately. Sometimes, fluorescence-activated cell sorting (FACS) is used upstream to isolate a specifically labeled population of interest. A limitation of FACS is the need for high numbers of input cells with significantly labeled fractions, which is impractical for collecting and profiling rare or sparsely labeled neuron populations from the mouse brain. Here, we describe a method for manually collecting sparse fluorescently labeled single neurons from freshly dissociated mouse brain tissue. This process allows for capturing single-labeled neurons with high purity and subsequent integration with an in vitro transcription-based amplification protocol that preserves endogenous transcript ratios. We describe a double linear amplification method that uses unique molecule identifiers (UMIs) to generate individual mRNA counts. Two rounds of amplification results in a high degree of gene detection per single cell.

Using the protocol described above, GABAergic neurons were manually sorted (Figure 1) and RNA was amplified, then made into a cDNA library (Figure 2) and sequenced at high depth8. The amplified RNA (aRNA) products ranged between 200&#8211;4,000 bp in size, with a peak distribution slightly above 500 bp (Figure 3A). The bead-purified cDNA library was further size-restricted by ...

Watch this Scientific Journal Video about Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

This protocol describes the manual sorting procedure to isolate single fluorescently labeled neurons followed by in vitro transcription-based mRNA amplification for high-depth single-cell RNA sequencing.

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing (DIVA-Seq)

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing ...

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Research

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Neuroscience

9.4K Views.  Cold Spring Harbor Laboratory. This protocol describes the manual sorting procedure to isolate single fluorescently labeled neurons followed by in vitro transcription-based mRNA amplification for high-depth single-cell RNA sequencing.

Video: Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Production of RNA for Transcriptomic Analysis from Mouse Spinal Cord Motor Neuron Cell Bodies by Laser Capture Microdissection

Preparation of high-quality RNA from cells of interest is critical to precise and meaningful analysis of transcriptional differences among cell types or between the same cell type in health and disease or following pharmacologic treatments.&#160;In the spinal cord, such preparation from motor neurons, the target of interest in many neurologic and neurodegenerative diseases, is complicated by the fact that motor neurons represent &#60;10% of the total cell population.&#160;Laser capture microdissection (LMD) has been developed to address this problem.&#160;Here, we describe a protocol to quickly recover, freeze, and section mouse spinal cord to avoid RNA damage by endogenous and exogenous RNases, followed by staining with Azure B in 70% ethanol to identify the motor neurons while keeping endogenous RNase inhibited.&#160;LMD is then used to capture the stained neurons directly into guanidine thiocyanate lysis buffer, maintaining RNA integrity.&#160;Standard techniques are used to recover the total RNA and measure its integrity.&#160;This material can then be used for downstream analysis of the transcripts by RNA-seq and qRT-PCR.

High-quality total RNA has been prepared from cell bodies of mouse spinal cord motor neurons by laser capture microdissection after staining spinal cord sections with Azure B in 70% ethanol.&#160;Sufficient RNA (~40-60 ng) is recovered from 3,000-4,000 motor neurons to allow downstream RNA analysis by RNA-seq and qRT-PCR.

Preparation of high-quality RNA from cells of interest is critical to precise and meaningful analysis of transcriptional differences among cell types or ...

A Method to Target and Isolate Airway-innervating Sensory Neurons in Mice

Somatosensory nerves transduce thermal, mechanical, chemical, and noxious stimuli caused by both endogenous and environmental agents. The cell bodies of these afferent neurons are located within the sensory ganglia. Sensory ganglia innervate a specific organ or portion of the body. For instance, the dorsal root ganglia (DRG) are located in the vertebral column and extend processes throughout the body and limbs. The trigeminal ganglia are located in the skull and innervate the face, and upper airways. Vagal afferents of the nodose ganglia extend throughout the gut, heart, and lungs. The nodose neurons control a diverse array of functions such as: respiratory rate, airway irritation, and cough reflexes. Thus, to understand and manipulate their function, it is critical to identify and isolate airway specific neuronal sub-populations. In the mouse, the airways are exposed to a fluorescent tracer dye, Fast Blue, for retrograde tracing of airway-specific nodose neurons. The nodose ganglia are dissociated and fluorescence activated cell (FAC) sorting is used to collect dye positive cells. Next, high quality ribonucleic acid (RNA) is extracted from dye positive cells for next generation sequencing. Using this method airway specific neuronal gene expression is determined.

Organ specific sensory neurons are difficult to identify. Fast Blue tracing is used to identify nodose neurons innervating the airways for cell sorting. Sorted nodose neurons are used to extract high quality ribonucleic acid (RNA) for sequencing. Using this protocol, gene expression of airway specific neurons is determined.

Somatosensory nerves transduce thermal, mechanical, chemical, and noxious stimuli caused by both endogenous and environmental agents. The cell bodies of ...

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 ...

Reliable Identification of Living Dopaminergic Neurons in Midbrain Cultures Using RNA Sequencing and TH-promoter-driven eGFP Expression

In Parkinson&#39;s Disease (PD) there is widespread neuronal loss throughout the brain with pronounced degeneration of dopaminergic neurons in the SNc, leading to bradykinesia, rigidity, and tremor. The identification of living dopaminergic neurons in primary Ventral Mesencephalic (VM) cultures using a fluorescent marker provides an alternative way to study the selective vulnerability of these neurons without relying on the immunostaining of fixed cells. Here, we isolate, dissociate, and culture mouse VM neurons for 3 weeks. We then identify dopaminergic neurons in the cultures using eGFP fluorescence (driven by a Tyrosine Hydroxylase (TH) promoter). Individual neurons are harvested into microcentrifuge tubes using glass micropipettes. Next, we lyse the harvested cells, and conduct cDNA synthesis and transposon-mediated &#34;tagmentation&#34; to produce single cell RNA-Seq libraries1,2,3,4,5. After passing a quality-control check, single-cell libraries are sequenced and subsequent analysis is carried out to measure gene expression. We report transcriptome results for individual dopaminergic and GABAergic neurons isolated from midbrain cultures. We report that 100% of the live TH-eGFP cells that were harvested and sequenced were dopaminergic neurons. These techniques will have widespread applications in neuroscience and molecular biology.

In Parkinson&#39;s Disease (PD), Substantia Nigra (SNc) dopaminergic neurons degenerate, leading to motor dysfunction. Here we report a protocol for culturing ventral midbrain neurons from a mouse expressing eGFP driven by a Tyrosine Hydroxylase (TH) promoter sequence, harvesting individual fluorescent neurons from the cultures, and measuring their transcriptome using RNA-seq.

In Parkinson&#39;s Disease (PD) there is widespread neuronal loss throughout the brain with pronounced degeneration of dopaminergic neurons in the SNc, ...

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

The discovery of cell type-specific markers can provide insight into cellular function and the origins of cellular heterogeneity. With a recent push for the improved understanding of neuronal diversity, it is important to identify genes whose expression defines various subpopulations of cells. The retina serves as an excellent model for the study of central nervous system diversity, as it is composed of multiple major cell types. The study of each major class of cells has yielded genetic markers that facilitate the identification of these populations. However, multiple subtypes of cells exist within each of these major retinal cell classes, and few of these subtypes have known genetic markers, although many have been characterized by morphology or function. A knowledge of genetic markers for individual retinal subtypes would allow for the study and mapping of brain targets related to specific visual functions and may also lend insight into the gene networks that maintain cellular diversity. Current avenues used to identify the genetic markers of subtypes possess drawbacks, such as the classification of cell types following sequencing. This presents a challenge for data analysis and requires rigorous validation methods to ensure that clusters contain cells of the same function. We propose a technique for identifying the morphology and functionality of a cell prior to isolation and sequencing, which will allow for the easier identification of subtype-specific markers. This technique may be extended to non-neuronal cell types, as well as to rare populations of cells with minor variations. This protocol yields excellent-quality data, as many of the libraries have provided read depths greater than 20 million reads for single cells. This methodology overcomes many of the hurdles presented by Single-cell RNA-Seq and may be suitable for researchers aiming to profile cell types in a straightforward and highly efficient manner.

Here, we present a combinatorial approach for classifying neuronal cell types prior to isolation and for the subsequent characterization of single-cell transcriptomes. This protocol optimizes the preparation of samples for successful RNA Sequencing (RNA-Seq) and describes a methodology designed specifically for the enhanced understanding of cellular diversity.

The discovery of cell type-specific markers can provide insight into cellular function and the origins of cellular heterogeneity. With a recent push for ...

Isolation of Adult Spinal Cord Nuclei for Massively Parallel Single-nucleus RNA Sequencing

Probing an individual cell&#39;s gene expression enables the identification of cell type and cell state. Single-cell RNA sequencing has emerged as a powerful tool for studying transcriptional profiles of cells, particularly in heterogeneous tissues such as the central nervous system. However, dissociation methods required for single cell sequencing can lead to experimental changes in the gene expression and cell death. Furthermore, these methods are generally restricted to fresh tissue, thus limiting studies on archival and bio-bank material. Single nucleus RNA sequencing (snRNA-Seq) is an appealing alternative for transcriptional studies, given that it accurately identifies cell types, permits the study of tissue that is frozen or difficult to dissociate, and reduces dissociation-induced transcription. Here, we present a high-throughput protocol for rapid isolation of nuclei for downstream snRNA-Seq. This method enables isolation of nuclei from fresh or frozen spinal cord samples and can be combined with two massively parallel droplet encapsulation platforms.

Here, we present a protocol to rapidly isolate high-quality nuclei from the fresh or frozen tissue for downstream massively parallel RNA sequencing. We include detergent-mechanical and hypotonic-mechanical tissue disruption and cell lysis options, both of which can be used for isolation of nuclei.

Probing an individual cell&#39;s gene expression enables the identification of cell type and cell state. Single-cell RNA sequencing has emerged as a ...

Isolation of Region-specific Microglia from One Adult Mouse Brain Hemisphere for Deep Single-cell RNA Sequencing

As resident macrophages in the central nervous system, microglia actively control brain development and homeostasis, and their dysfunctions may drive human diseases. Considerable advances have been made to uncover the molecular signatures of homeostatic microglia as well as alterations of their gene expression in response to environmental stimuli. With the advent and maturation of single-cell genomic methodologies, it is increasingly recognized that heterogenous microglia may underlie the diverse roles they play in different developmental and pathological conditions. Further dissection of such heterogeneity can be achieved through efficient isolation of microglia from a given region of interest, followed by sensitive profiling of individual cells. Here, we provide a detailed protocol for the rapid isolation of microglia from different brain regions in a single adult mouse brain hemisphere. We also demonstrate how to use these sorted microglia for plate-based deep single-cell RNA sequencing. We discuss the adaptability of this method to other scenarios and provide guidelines for improving the system to accommodate large-scale studies.

We provide a protocol for isolation of microglia from different dissected regions of an adult mouse brain hemisphere, followed by semi-automated library preparation for deep single-cell RNA sequencing of full-length transcriptomes. This method will help to elucidate functional heterogeneity of microglia in health and disease.

As resident macrophages in the central nervous system, microglia actively control brain development and homeostasis, and their dysfunctions may drive ...

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 ...

Biology

Fluorescence-Activated Nuclei Negative Sorting of Neurons Combined with Single Nuclei RNA Sequencing to Study the Hippocampal Neurogenic Niche

Adult Hippocampal Neurogenesis (AHN), which consists of a lifelong maintenance of proliferative and quiescent neural stem cells (NSCs) within the sub-granular zone (SGZ) of the dentate gyrus (DG) and their differentiation from newly born neurons into granule cells in the granule cell layer, is well validated across numerous studies. Using genetically modified animals, particularly rodents, is a valuable tool to investigate signaling pathways regulating AHN and to study the role of each cell type that compose the hippocampal neurogenic niche. To address the latter, methods combining single nuclei isolation with next generation sequencing have had a significant impact in the field of AHN to identify gene signatures for each cell population. Further refinement of these techniques is however needed to phenotypically profile rarer cell populations within the DG. Here, we present a method that utilizes Fluorescence Activated Nuclei Sorting (FANS) to exclude most neuronal populations from a single nuclei suspension isolated from freshly dissected DG, by selecting unstained nuclei for the NeuN antigen, in order to perform single nuclei RNA sequencing (snRNA-seq). This method is a potential steppingstone to further investigate intercellular regulation of the AHN and to uncover novel cellular markers and mechanisms across species.

Presented here is a method to sequence single nuclei isolated from the mouse dentate gyrus that excludes most neurons through fluorescence-activated nuclei (FAN)-sorting. This approach generates high-quality expression profiles and facilitates the study of most other cell types represented in the niche, including scarce populations such as neural stem cells.

Adult Hippocampal Neurogenesis (AHN), which consists of a lifelong maintenance of proliferative and quiescent neural stem cells (NSCs) within the ...

Low-input Nucleus Isolation and Multiplexing with Barcoded Antibodies of Mouse Sympathetic Ganglia for Single-nucleus RNA Sequencing

The cardiac autonomic nervous system is crucial in controlling cardiac function, such as heart rate and cardiac contractility, and is divided into sympathetic and parasympathetic branches. Normally, there is a balance between these two branches to maintain homeostasis. However, cardiac disease states such as myocardial infarction, heart failure, and hypertension can induce the remodeling of cells involved in cardiac innervation, which is associated with an adverse clinical outcome.
Although there are vast amounts of data for the histological structure and function of the cardiac autonomic nervous system, its molecular biological architecture in health and disease is still enigmatic in many aspects. Novel technologies such as single-cell RNA sequencing (scRNA-seq) hold promise for the genetic characterization of tissues at single-cell resolution. However, the relatively large size of neurons may impede the standardized use of these techniques. Here, this protocol exploits droplet-based single-nucleus RNA sequencing (snRNA-seq), a method to characterize the biological architecture of cardiac sympathetic neurons in health and disease. A stepwise approach is demonstrated to perform snRNA-seq of the bilateral superior cervical (SCG) and stellate ganglia (StG) dissected from adult mice.
This method enables long-term sample preservation, maintaining an adequate RNA quality when samples from multiple individuals/experiments cannot be collected all at once within a short period of time. Barcoding the nuclei with hashtag oligos (HTOs) enables demultiplexing and the trace-back of distinct ganglionic samples post sequencing. Subsequent analyses revealed successful nuclei capture of neuronal, satellite glial, and endothelial cells of the sympathetic ganglia, as validated by snRNA-seq. In summary, this protocol provides a stepwise approach for snRNA-seq of sympathetic extrinsic cardiac ganglia, a method that has the potential for broader application in studies of the innervation of other organs and tissues.

This protocol describes the detailed, low-input sample preparation for single-nucleus sequencing, including the dissection of mouse superior cervical and stellate ganglia, cell dissociation, cryopreservation, nucleus isolation, and hashtag barcoding.