JoVE Logo

Zaloguj się

Aby wyświetlić tę treść, wymagana jest subskrypcja JoVE. Zaloguj się lub rozpocznij bezpłatny okres próbny.

W tym Artykule

  • Podsumowanie
  • Streszczenie
  • Wprowadzenie
  • Protokół
  • Wyniki
  • Dyskusje
  • Ujawnienia
  • Podziękowania
  • Materiały
  • Odniesienia
  • Przedruki i uprawnienia

Podsumowanie

DNA methylation is capable of maintaining stable levels of gene expression as well as allowing for dynamic changes in gene expression in response to a variety of stimuli. We detail techniques that allow the study of gene-specific changes in DNA methylation and the effect of these changes on gene expression.

Streszczenie

DNA methylation serves to regulate gene expression through the covalent attachment of a methyl group onto the C5 position of a cytosine in a cytosine-guanine dinucleotide. While DNA methylation provides long-lasting and stable changes in gene expression, patterns and levels of DNA methylation are also subject to change based on a variety of signals and stimuli. As such, DNA methylation functions as a powerful and dynamic regulator of gene expression. The study of neuroepigenetics has revealed a variety of physiological and pathological states that are associated with both global and gene-specific changes in DNA methylation. Specifically, striking correlations between changes in gene expression and DNA methylation exist in neuropsychiatric and neurodegenerative disorders, during synaptic plasticity, and following CNS injury. However, as the field of neuroepigenetics continues to expand its understanding of the role of DNA methylation in CNS physiology, delineating causal relationships in regards to changes in gene expression and DNA methylation are essential. Moreover, in regards to the larger field of neuroscience, the presence of vast region and cell-specific differences requires techniques that address these variances when studying the transcriptome, proteome, and epigenome. Here we describe FACS sorting of cortical astrocytes that allows for subsequent examination of a both RNA transcription and DNA methylation. Furthermore, we detail a technique to examine DNA methylation, methylation sensitive high resolution melt analysis (MS-HRMA) as well as a luciferase promoter assay. Through the use of these combined techniques one is able to not only explore correlative changes between DNA methylation and gene expression, but also directly assess if changes in the DNA methylation status of a given gene region are sufficient to affect transcriptional activity.

Wprowadzenie

Epigenetics is the study of chemical modifications that can affect the transcriptional activity of the genome. Essentially, without a change in the DNA sequence, epigenetic modifications such as DNA methylation, histone acetylation, and histone methylation are sufficient to reversibly alter patterns of gene expression 1. DNA methylation, a potent regulator of gene expression, is the most well characterized epigenetic modification. DNA methylation is the covalent attachment of methyl groups on the C5 position of a cytosine, typically the cytosine of a cytosine-guanine dinucleotide, also known as a CpG site. Areas that contain a high density of CpG sites are known as CpG islands (CGIs). CGIs are frequently associated with transcriptional start sites (TSS) and gene promoters 1-3. Thus, while changes in DNA methylation at CGIs are not always concomitant with changes in cellular expression or function, changes in DNA methylation at CGIs can exert powerful regulation on transcriptional activity 2.

Historically, DNA methylation was observed to be essential in embryogenesis, imprinting, and development, with little changes in the levels of DNA methylation occurring in post-mitotic cells (with the exception of alterations in cancer-related genes) 4,5. However, the field of neuroepigenetics has highlighted an important non-developmental role for DNA methylation. Specifically, cognitive epigenetics has redefined DNA methylation as a highly plastic mechanism integral in mediating both the transcriptional activation and repression of genes essential for the process of learning and memory 6. Apart from cognitive epigenetics, studies modeling ischemic injury and neuropathic pain characterize DNA methylation as a labile mechanism that responds rapidly to a variety of CNS insults 7-9. In regards to astrocytes, several lines of evidence suggest DNA methylation plays an important role in astrogliogenesis. Fan et al., found that conditional KO of DNMT1 in neural progenitor cells (NPCs) resulted in precocious development of astrocytes concordant with a global state of hypomethylation 10. Additionally, Perisic et al., concluded differential levels of DNA methylation of the GLT-1 promoter mediated differential levels of expression of the glutamate transporter in the cortex and cerebellum, emphasizing a role in DNA methylation in establishing brain-region specific patterns of astrocytic gene expression 11. Overall, numerous studies underscore the dynamic and labile nature of DNA methylation in the CNS as environment, drugs, and injury have all been shown to change DNA methylation and often, gene expression 4,9. Together, these neuroepigenetic studies point to DNA methylation as a feasible therapeutic target with the potential to mitigate a variety of CNS pathologies.

As the field of epigenetics expands its understanding of the role of DNA methylation in neurodevelopment and disease, the challenge of moving DNA methylation towards a therapeutic target is performing not only correlative, but causative studies that define specific gene targets and sites. Additionally, surveying changes in DNA methylation specific to brain region and cell type remains an ongoing and time worthy challenge unique to the field of neuroepigenetics. This protocol utilizes a variety of techniques including fluorescence-activated cell sorting (FACS) of astrocytes, methylation-sensitive high resolution melt analysis (MS-HRM), and a methylation luciferase assay to investigate the DNA methylation status of KCNJ10, a gene that encodes for Kir4.1. Kir4.1 is a glial specific potassium channel that demonstrates both brain region and cell specific patterns of expression in the CNS 12-16. Kir4.1 expression increases moving from rostral to caudal CNS regions, with the highest expression occurring in the spinal cord 15. Although the channel is expressed in ependymal cells, oligodendrocytes and their precursor cells, Kir4.1 is predominantly expressed in astrocytes and thought to be essential for maintaining homeostatic levels of potassium as well as supporting glutamate uptake by setting the astrocytic resting membrane potential at a hyperpolarized -80mV 12,16-19. Importantly, the expression of Kir4.1 is non-static both during development and following multiple forms of CNS injury 20-25. We wished to examine the epigenetic regulation of this channel, specifically in astrocytes during development. The techniques utilized offer gene-specific and targeted CpG site analyses that provide causal evidence for a role of DNA methylation in regulating KCNJ10 gene expression. These techniques can be applied to other genes.

Access restricted. Please log in or start a trial to view this content.

Protokół

All animals were handled in accordance with the National Institutes of Health guidelines. The Animal Care and Use Committee at the University of Alabama at Birmingham approved animal use.

1. Obtaining RNA and DNA from an Enriched Astrocytic Population using Fluorescent Activated Cell Sorting (FACS) of Astrocytes from Whole Brain Tissue

  1. Sedate animal with CO2 for 1 min and then rapidly decapitate. Dissect cortices as described in Albuquerque et al.,26; it is not necessary to remove meninges.
    Note: Transgenic rats expressing eGFP under the S100β (an astrocyte marker) promoter were generated by Itakura et al.27 and utilized for FACS sorting of astrocytes.
  2. Prepare whole brain homogenate using a papain dissociation kit under non-sterile conditions according to manufacturer’s protocol. Heat-activate papain at 37 °C in water bath for 10 min. Note: Papain solution is provided by manufacturer and contains L-cysteine and EDTA (See Table of Materials).
    1. Cut or dremel a hole into the top of a 50 ml conical tube to allow tubing carrying 95%O2:5% CO2 to be fed into a closed conical tube (Figure 1A). Place dissected cortices in 10mm culture dish containing dissociation media (MEM supplemented with 20mM glucose and penicillin/streptomycin (500 U/ml) and equilibrated to 95%O2:5% CO2) and use a clean razor blade to mince tissue into 1 x 1 mm2 pieces.
  3. Transfer tissue using 10 ml manual pipetman to 50 ml conical tube containing papain solution. Allow tissue to settle to bottom of transfer pipette before discharging to minimize the amount of dissociation media carried over. Keep papain solution equilibrated to 95%O2:5% CO2 via surface gas exchange for the duration of the incubation. Do not bubble papain solution. Incubate tissue for 20 min in 37 °C water bath.
  4. Following incubation in papain solution, triturate tissue 10 times with a 10 ml transfer pipette at slow speed. Centrifuge cloudy cell suspension at 1,000 x g for 5 min at RT.
    1. Equilibrate DNase/albumin inhibitor solution (provided by manufacturer) via surface gas exchange and re-suspend pelleted cells in 3 ml of DNase/albumin inhibitor solution. Prepare commercial discontinuous density gradient following manufacturer instructions.
  5. Spin discontinuous density gradient at 1,000 x g for 6 min. Isolate dissociated cells from the bottom of tube by sucking bottom pellet using a pipette.
  6. Re-suspend dissociated cells in 2-3 ml of DPBS with 0.02% bovine serum albumin and 1 mg/ml DNase or preferred HEPES buffered culture media. Pass through 40 µm filter before FACS (Figure 2A). Keep cells on ice until sorting.
    1. Perform FACS28.
    2. Pellet cells in 1.5 ml centrifuge tubes at 2,000 x g for 5 min at 4 °C.
      Note: Pelleted astrocytes can be utilized immediately or kept in -80 °C until DNA extraction.
  7. Extract RNA and DNA using preferred isolation method 2930. Assess RNA and DNA concentration and quality via spectrophotometer and bioanalyzer 31.
    Note: Utilize only high quality RNA and DNA in subsequent steps, 260/280=2.0-2.2 and 1.8-1.9, respectively. Bioanalyzer analysis is essential to assess for RNA degradation or DNA fragmentation. RNA or DNA can be utilized immediately or stored in -80 °C or -20 °C, respectively for subsequent studies.

2. Assessing DNA Methylation Status of a Gene using Methylation-sensitive High Resolution Melt Analysis (MS-HRMA)

  1. Enter gene sequence of interest into preferred online methylation mapping software to identify any CpG islands in gene of interest 32.
    1. Design primers against bisulfite converted DNA sequence33 and amplify using preferred DNA polymerase according to manufacturer’s protocol. Verify amplified product size by running a 1% agarose DNA gel at 100 V for 45 min. Store primers at stock concentration of 20 µM in -20 °C.
  2. Bisulfite convert 500-1,000 ng of DNA of each sample and methylated DNA standards ranging from 0-100% from the same animal species 34. Elute samples to provide a concentration of 20 ng/µl. Verify concentration of bisulfite converted DNA via spectrophotometer 31.
  3. Setup 20 µl reactions for MS-HRM amplification using preferred DNA polymerase and primers at 5 µM concentration according to Table 1 and 2. Run all samples, including FACS DNA and methylated standards, in triplicate.
  4. Depending on analysis software, set pre- and post- start and stop parameters around the transitions of the melt curve. Set pre-melt start and pre-melt stop parameters so the difference between the two is 0.2 – 0.5 °C. Set post-melt start and post-melt stop similarly. Extract peak temperature difference data for each sample.
  5. Using percent methylated standards (y-value) and their corresponding average peak temperature differences (x-value) generate a linear regression equation (Figure 3A-B, Table 3-4). Use this linear regression equation to estimate methylation status of unknown samples 35.

3. Assessing Hyper-methylated Promoter Activity via Use of Luciferase Assay

  1. Identify CpG islands of target gene (Step 2.1). PCR amplify regions of interest 36 and clone upstream of the luc2 Firefly luciferase reporter gene to produce CpG-island-luc2 plasmids 37.
  2. Linearize 30 µg of CpG-island-luc2 plasmid via restriction enzyme digestion 38. Verify sites for restriction digest and avoid double cuts using preferred cutter software 38. Heat-inactivate enzymes at appropriate temperature and duration following digestion according to manufacturer’s protocol. Minimal loss of DNA occurs during the linearization step.
  3. Methylate linearized plasmids using CpG methylase (M.Sssl) O/N at 30 °C or leave untreated following manufacturer protocol except for the following adjustments.
  4. Perform 50 µl reactions.
  5. Use 5 units of CpG methylase to methylate 700 ng of linearized plasmid.
  6. Run reactions O/N for 13-19 hr.
  7. Following CpG methylase reaction, perform DNA cleanup using standard, commercially available silica-gel membrane clean up kit according to manufacturer’s protocol. Significant losses of DNA occur following CpG methylase reaction, 30-60% loss.
  8. Verify methylation of plasmids via an Hpa II restriction digest.
  9. Take 1 µg of methylated or non-methylated DNA and restriction digest with Hpa II for 1 hr at 37 °C. Use 5-10 units of Hpa II for each µg DNA. Following Hpa II digestion, perform DNA cleanup using preferred, commercially available silica-gel membrane clean up kit. Run both CpG methylated and non-methylated plasmids on a 1% agarose DNA gel in TAE or TBE buffer at 100 V for 45 min for visualization (Figure 4B).
  10. Subject both methylated and non-methylated plasmids to double digestion with appropriate restriction enzymes to release full-length luc 2 (vector) and CpG island (insert) fragments 38. Perform double digestion O/N at appropriate temperature and heat-inactivate enzymes following digestion according to manufacturer’s protocol. Minimal loss of DNA concentration occurs during double restriction digest.
  11. Run double digested plasmids on 1% DNA agarose gel at 100 V for 1 hr to allow for separation of vector and insert (Figure 4C). Caution. Wearing protective UV face shield, place DNA gel on a tabletop black light to visualize bands. Based on size, excise methylated and non-methylated insert and non-methylated vector using a clean surgical blade.
  12. Gel extract DNA using saturated phenol, pH 6.6. Briefly, weigh DNA gel containing vector or insert. Use 100 µl of phenol per 0.1 gram of DNA gel. Homogenize DNA gel in phenol using glass dounce homogenizer.
  13. Add chloroform (using 1/5 of phenol volume) and shake samples for 20 sec. Incubate samples at RT for 2-3 min. Centrifuge for 15 min at max speed (16.1 x 1,000 x g) at 4 °C.
  14. Remove aqueous solution and add 0.1X volume of 3 M sodium acetate and 2.5X volume of ethanol. Incubate samples for 1 hr at -80 °C. Following incubation, remove ethanol and re-suspend DNA in 30 µl of preferred buffer. Significant loss of DNA occurs following isolation of inserts and vectors, 30-50% loss.
  15. Re-ligate methylated and non-methylated inserts to non-methylated vector using T4 DNA ligase 38. Use a 1:4 ratio of vector to insert for ligation reactions. Setup reaction according to manufacturer instructions. Use a total volume of 50 µl for reactions and incubate O/N at -20 °C or on ice with lid over ice bucket.
  16. Following ligation, perform DNA cleanup using preferred, commercially available silica-gel membrane clean up kit. Significant loss of DNA occur following ligation reaction, an approximate 30-50% loss of DNA. Verify re-ligation by running on 1% agarose DNA gel at 100 V for 45 min and assess concentration of re-ligated plasmids (Figure 4D).
  17. Transfect methylated or non-methylated plasmids into D54 cells using a commercial transfection reagent according to manufacturer’s protocol. Seed D54 cells onto 12-well plate at a 0.14 x 106 cells/well.
  18. Following 24 hr, transfect cells with equal concentrations of either (1) non-methyated CpG-luc2 plasmid + Renilla or other control luciferase vector or (2) methylated CpG-luc2 plasmid + Renilla or other control luciferase vector.
  19. Allow cells to transfect for 24 hr before performing dual luciferase assay. Perform assay according to manufacturer instructions. Perform readings using a luminometer. Read each well in triplicate.
  20. Calculate ratio of Firefly luciferase activity to Renilla or other control luciferase activity. Normalize methylated Firefly:control luciferase activity to non-methylated Firefly:control luciferase activity by dividing methylated luciferase activity by non-methylated luciferase activity

Access restricted. Please log in or start a trial to view this content.

Wyniki

An enriched population of astrocytes was acquired via FACS sorting of eGFP-S100β transgenic animals 27. Due to decreasing quality of cells and molecular molecules isolated from animals older than postnatal day 50 (p50), animals aged p0-p40 are optimal for such experiments. Cortical tissue was used for these experiments. Cortices from two to six animals were pooled together. FACS was performed at UAB Comprehensive Flow Cytometry Core facility. Sorting was performed on Becton Dickinson FacsAria II. eGFP exc...

Access restricted. Please log in or start a trial to view this content.

Dyskusje

This protocol describes the isolation of an enriched population of astrocytes via FACS as well as a variety of techniques that allow for both correlative and causative studies between DNA methylation and gene expression. These techniques, used in isolation or in combination, are particularly useful for laboratories that work with tissue of high cellular heterogeneity or are interested in the DNA methylation status of a particular gene or gene region versus global DNA methylation changes. One relatively unique challenge i...

Access restricted. Please log in or start a trial to view this content.

Ujawnienia

The authors have no disclosures.

Podziękowania

This work was supported by R01NS075062-01A1. FACS sorting performed at UAB Comprehensive Flow Cytometry Core facility (P30 AR048311, P30 A1027767). Dr. Scott Philips from the UAB Neurobiology Core facility and Dr. Susan Nozell from UAB CDIB assisted with technical aspects of the luciferase assay.

Access restricted. Please log in or start a trial to view this content.

Materiały

NameCompanyCatalog NumberComments
Papain Dissociation SystemWorthington Biochemical CorporationLK003150
AllPrep DNA/RNA Mini KitQiagen80204
Methyl PrimerApplied Biosystemsonlinesoftware to localize CpG Islands
EZ DNA methylation KitZymo ResearchD5001
Rat Premixed Calibration StandardEpiGenDx80-8060R-Premix
CpG Methylase (M.Sssl)Zymo ResearchE2010
QIAquick Gel Extraction QIagen28704Used for gel extraction and DNA cleanup
Restriction enzymesNew England BioLabs
NEB cutterNew England BioLabsonlineverify restriction digest sites
Dual Luciferase Reporter Assay SystemPromegaE1910
Luc2 vector, pGL4.10PromegaE6651
renilla vector, pGL4.74PromegaE2241
TD-20/20 LuminometerTurner Designs
Lipofectamine LTX and Plus ReagentLife TechnologiesA12621
Phenol, saturated pH 6.6/6.9Fisher ScientificBP 17501-100
Nanodrop 2000/2000c SpectrophtometerThermoScientific
MeltDoctor Master MixLife Technologies4415440
High Resolution Melt (HRM) Software v2.0Life Technologies4397808
AB SDS software v2.3Life Technologiesonline
AB High Resolution Melting Getting Started Guide Life Technologiesonline
AB 7900HT Fast Real-Time SystemLife Technologies

Odniesienia

  1. Bird, A. DNA methylation patterns and epigenetic memory. Genes Dev. 16 (1), 6-21 (2002).
  2. Deaton, A. M., Bird, A. CpG islands and the regulation of transcription. Genes Dev. 25, 1010-1022 (2011).
  3. Lorincz, M. C., Dickerson, D. R., Schmitt, M. Intragenic DNA methylation alters chromatin structure and elongation efficiency in mammalian cells. Nat Struct. Mol Biol. 11 (11), 1068-1075 (2004).
  4. Moore, L. D., Le, T. DNA methylation and its basic function. Neuropsychopharmacol. 38, 23-38 (2013).
  5. Santos, K. F., Mazzola, T. N. The prima donna of epigenetics: the regulation of gene expression by DNA methylation. Braz.J.Med.Biol.Res. 38 (10), 1531-1541 (2005).
  6. Day, J. J., Sweatt, J. D. Cognitive neuroepigenetics: a role for epigenetic mechanisms in learning and memory. Neurobiol. Learn.Mem. 96, 2-12 (2011).
  7. Denk, F., McMahon, S. B. Chronic pain: emerging evidence for the involvement of epigenetics. Neuron. 73, 435-444 (2012).
  8. Endres, M., et al. DNA methyltransferase contributes to delayed ischemic brain injury. J. Neuroscience. 20 (9), 3175-3181 (2000).
  9. Qureshi, I. A., Mehler, M. F. Emerging role of epigenetics in stroke: part 1: DNA methylation and chromatin modifications. Arch.Neurol. 67, 1316-1322 (2010).
  10. Tian, R., et al. disease mutant glial fibrillary acidic protein compromises glutamate transport in astrocytes. J Neuropathol. Exp Neurol. 69, 335-345 (2010).
  11. Perisic, T., Holsboer, F., Rein, T. The CpG island shore of the GLT-1 gene acts as a methylation-sensitive enhancer. Glia. 60 (9), 1345-1355 (2012).
  12. Olsen, M. L., Higashimori, H., Campbell, S. L., Hablitz, J. J. Functional expression of Kir4.1 channels in spinal cord astrocytes. Glia. 53 (5), 516-528 (2006).
  13. Poopalasundaram, S., et al. Glial heterogeneity in expression of the inwardly rectifying K+ channel, Kir4.1, in adult rat CNS. Glia. 30, 362-372 (2000).
  14. Hibino, H., Fujita, A., Iwai, K., Yamada, M. Differential assembly of inwardly rectifying K+ channel subunits. Kir4.1 and Kir5.1, in brain astrocytes. 279, 44065-44073 (2004).
  15. Nwaobi, S. E., Lin, E., Peramsetty, S. R. DNA methylation functions as a critical regulator of Kir4.1 expression during CNS development. Glia. 62 (3), 411-427 (2014).
  16. Li, L., Head, V. Identification of an inward rectifier potassium channel gene expressed in mouse cortical astrocytes. Glia. 33, 57-71 (2001).
  17. Kucheryavykh, Y. V., et al. Downregulation of Kir4.1 inward rectifying potassium channel subunits by RNAi impairs potassium transfer and glutamate uptake by cultured cortical astrocytes. Glia. 55 (3), 274-281 (2007).
  18. Djukic, B., Casper, K. B., Philpot, B. D., Chin, L. S. Conditional knock-out of Kir4.1 leads to glial membrane depolarization, inhibition of potassium and glutamate uptake, and enhanced short-term synaptic potentiation. J. Neuroscience. 27, 11354-11365 (2007).
  19. Fujita, A., et al. Clustering of Kir4.1 at specialized compartments of the lateral membrane in ependymal cells of rat brain. Cell Tissue Res. 359 (2), 627-634 (2015).
  20. MacFarlane, S. N., Sontheimer, H. Electrophysiological changes that accompany reactive gliosis in vitro. J Neuroscience. 17 (19), 7316-7329 (1997).
  21. Ambrosio, R., Maris, D. O., Grady, M. S., Winn, H. R. Impaired K(+) homeostasis and altered electrophysiological properties of post-traumatic hippocampal glia. J. Neuroscience. 19 (18), 8152-8162 (1999).
  22. Anderova, M., et al. Voltage-dependent potassium currents in hypertrophied rat astrocytes after a cortical stab wound. Glia. 48 (4), 311-326 (2004).
  23. Olsen, M. L., Campbell, S. C., McFerrin, M. B., Floyd, C. L. Spinal cord injury causes a wide-spread, persistent loss of Kir4.1 and glutamate transporter 1: benefit of 17 beta-oestradiol treatment. Brain. 133, 1013-1025 (2010).
  24. Koller, H., Schroeter, M., Jander, S., Stoll, G. Time course of inwardly rectifying K(+) current reduction in glial cells surrounding ischemic brain lesions. Brain Res. 872, 1-2 (2000).
  25. Bordey, A., Lyons, S. A., Hablitz, J. J. Electrophysiological characteristics of reactive astrocytes in experimental cortical dysplasia. J Neurophysiol. 85 (4), 1719-1731 (2001).
  26. Albuquerque, C., Joseph, D. J., Choudhury, P. plating, and maintenance of cortical astrocyte cultures. 8, Cold Spring. 10-1101 (2009).
  27. Itakura, E., et al. Generation of transgenic rats expressing green fluorescent protein in S-100beta-producing pituitary folliculo-stellate cells and brain astrocytes. Endocrinology. 148, 1518-1523 (2007).
  28. Foo, L. C. Purification of astrocytes from transgenic rodents by fluorescence-activated cell sorting. Cold Spring Harb.Protoc. 2013, 551-560 (2013).
  29. Smith, C., Otto, P., Bitner, R. A silica membrane-based method for the isolation of genomic DNA from tissues and cultured cells. CSH. Protoc. 2006, 2006-201 (2006).
  30. Sambrook, J., Russell, D. W. A Single-step Method for the Simultaneous Preparation. of DNA, RNA, and Protein from Cells and. 1, 2006-201 (2006).
  31. Barbas, C. F., Burton, D. R., Scott, J. K. Quantitation of DNA and. , (2007).
  32. Zhao, Z., Han, L. CpG islands: algorithms and applications in methylation studies. Biochem. Biophys. Res. Commun. 382, 643-645 (2009).
  33. Srivastava, G. P., Guo, J., Shi, H. PRIMEGENS-v2: genome-wide primer design for analyzing DNA methylation patterns of CpG islands. Bioinformatics. 24, 1837-1842 (2008).
  34. Patterson, K., Molloy, L., Qu, W. DNA methylation: bisulphite modification and analysis. J.Vis.Exp.(56), doi:3170 [pii];10.3791/3170. , (2011).
  35. Drummond, G. B., Vowler, S. L. Categorized or continuous? Strength of an association-and linear regression. Adv.Physiol Educ. 36, 89-92 (2012).
  36. Sambrook, J., Russell, D. W. The basic polymerase chain reaction. CSH.Protoc. 1, (2006).
  37. Arpa, P. Strategies for cloning PCR products. Cold Spring Harb.Protoc. 8, (2009).
  38. Makovets, S. Basic DNA electrophoresis in molecular cloning: a comprehensive guide for beginners. Methods Mol.Biol. 1054, 11-43 (2013).
  39. Cahoy, J. D., et al. A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function. J Neuroscience. 28, 264-278 (2008).
  40. Maldonado, P. P., Velez-Fort, M., Levavasseur, F. Oligodendrocyte precursor cells are accurate sensors of local K+ in mature gray matter. J Neuroscience. 33, 2432-2442 (2013).
  41. Kalsi, A. S., Greenwood, K., Wilkin, G. Kir4.1 expression by astrocytes and oligodendrocytes in CNS white matter: a developmental study in the rat optic nerve. J.Anat. 204, 475-485 (2004).
  42. Higashi, K., et al. An inwardly rectifying K(+) channel, Kir4.1, expressed in astrocytes surrounds synapses and blood vessels in brain. Am.J.Physiol Cell Physiol. 281 (3), (2001).
  43. Olsen, M. L., Higashimori, H., Campbell, S. L., Hablitz, J. J. Functional expression of Kir4.1 channels in spinal cord astrocytes. Glia. 53 (5), 516-528 (2006).
  44. Neusch, C., Rozengurt, N., Jacobs, R. E., Lester, H. A. Kir4.1 Potassium Channel Subunit Is Crucial for Oligodendrocyte Development and In Vivo Myelination. J. Neuroscience. 21 (15), 5429-5438 (2001).
  45. Kofuji, P., et al. Genetic Inactivation of an Inwardly Rectifying Potassium Channel (Kir4.1 Subunit) in Mice: Phenotypic Impact in Retina. J. Neuroscience. 20 (15), 5733-5740 (2000).
  46. Kofuji, P., Connors, N. C. Molecular substrates of potassium spatial buffering in glial cells. Mol.Neurobiol. 28, 195-208 (2003).
  47. Nwaobi, S. E., Lin, E., Peramsetty, S. R. DNA methylation functions as a critical regulator of Kir4.1 expression during CNS development. Glia. 62 (3), 411-427 (2014).
  48. Wojdacz, T. K., Dobrovic, A. Methylation-sensitive high-resolution melting. Nat.Protoc. 3, 1903-1908 (2008).
  49. Wojdacz, T. K., Dobrovic, A. Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation. Nucleic Acids Res. 35, 10-1093 (2007).
  50. Laird, P. W. Principles and challenges of genomewide DNA methylation analysis. Nat.Rev.Genet. 11, 191-203 (2010).

Access restricted. Please log in or start a trial to view this content.

Przedruki i uprawnienia

Zapytaj o uprawnienia na użycie tekstu lub obrazów z tego artykułu JoVE

Zapytaj o uprawnienia

Przeglądaj więcej artyków

Keywords DNA MethylationGene ExpressionTranscriptional ActivityAstrocytesKCNJ10 Kir4 1NeuroepigeneticsFACS SortingMS HRMALuciferase Promoter AssayNeuropsychiatric DisordersNeurodegenerative DisordersSynaptic PlasticityCNS InjuryTranscriptomeProteomeEpigenome

This article has been published

Video Coming Soon

JoVE Logo

Prywatność

Warunki Korzystania

Zasady

Badania

Edukacja

O JoVE

Copyright © 2025 MyJoVE Corporation. Wszelkie prawa zastrzeżone