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Quantitative Detection of Low-Abundance Transcripts at Single-Cell Level in Human Epidermal Keratinocytes by Digital Droplet Reverse Transcription-Polymerase Chain Reaction

  • Frédéric Auvré
  • Julien Coutier
  • Michèle T. Martin
  • Nicolas O. Fortunel
Protocol
Part of the Methods in Molecular Biology book series

Abstract

Genetic and epigenetic characterization of the large cellular diversity observed within tissues is essential to understanding the molecular networks that ensure the regulation of homeostasis, repair, and regeneration, but also pathophysiological processes. Skin is composed of multiple cell lineages and is therefore fully concerned by this complexity. Even within one particular lineage, such as epidermal keratinocytes, different immaturity statuses or differentiation stages are represented, which are still incompletely characterized. Accordingly, there is presently great demand for methods and technologies enabling molecular investigation at single-cell level. Also, most current methods used to analyze gene expression at RNA level, such as RT-qPCR, do not directly provide quantitative data, but rather comparative ratios between two conditions. A second important need in skin biology is thus to determine the number of RNA molecules in a given cell sample. Here, we describe a workflow that we have set up to meet these specific needs, by means of transcript quantification in cellular micro-samples using flow cytometry sorting and reverse transcription-digital droplet polymerase chain reaction. As a proof-of-principle, the workflow was tested for the detection of transcription factor transcripts expressed at low levels in keratinocyte precursor cells. A linear correlation was found between quantification values and keratinocyte input numbers in a low quantity range from 40 cells to 1 cell. Interpretable signals were repeatedly obtained from single-cell samples corresponding to estimated expression levels as low as 10–20 transcript copies per keratinocyte or less. The present workflow may have broad applications for the detection and quantification of low-abundance nucleic acid species in single cells, opening up perspectives for the study of cell-to-cell genetic and molecular heterogeneity. Interestingly, the process described here does not require internal references such as house-keeping gene expression, as it is initiated with defined cell numbers, precisely sorted by flow cytometry.

Keywords

ddPCR Keratinocytes Low-abundance nucleic acids Single-cell level Transcript quantification 

Notes

Acknowledgments

We thank Genopole® (Evry, France), and particularly Julien Picot, who provided support for equipment and infrastructure. This work was supported by grants from: CEA and INSERM (UMR967) and the Délégation Générale de l’Armement (DGA) grants; FUI-AAP13 and the Conseil Général de l’Essonne within the STEMSAFE grant; and EURATOM (RISK-IR, FP7, grant 323267). Julien Coutier received a CEA-DGA thesis fellowship grant.

References

  1. 1.
    Li A, Simmons PJ, Kaur P (1998) Identification and isolation of candidate human keratinocyte stem cells based on cell surface phenotype. Proc Natl Acad Sci U S A 95:3902–3907Google Scholar
  2. 2.
    Fortunel NO, Hatzfeld JA, Rosemary PA, Ferraris C, Monier MN, Haydont V, Longuet J, Brethon B, Lim B, Castiel I, Schmidt R, Hatzfeld A (2003) Long-term expansion of human functional epidermal precursor cells: promotion of extensive amplification by low TGF-beta1 concentrations. J Cell Sci 116:4043–4052Google Scholar
  3. 3.
    Larderet G, Fortunel NO, Vaigot P, Cegalerba M, Maltère P, Zobiri O, Gidrol X, Waksman G, Martin MT (2006) Human side population keratinocytes exhibit long-term proliferative potential and a specific gene expression profile and can form a pluristratified epidermis. Stem Cells 24:965–974Google Scholar
  4. 4.
    Rachidi W, Harfourche G, Lemaitre G, Amiot F, Vaigot P, Martin MT (2007) Sensing radiosensitivity of human epidermal stem cells. Radiother Oncol 83:267–276Google Scholar
  5. 5.
    Harfouche G, Vaigot P, Rachidi W, Rigaud O, Moratille S, Marie M, Lemaitre G, Fortunel NO, Martin MT (2010) Fibroblast growth factor type 2 signaling is critical for DNA repair in human keratinocyte stem cells. Stem Cells 28:1639–1648Google Scholar
  6. 6.
    Fortunel NO, Cadio E, Vaigot P, Chadli L, Moratille S, Bouet S, Roméo PH, Martin MT (2010) Exploration of the functional hierarchy of the basal layer of human epidermis at the single-cell level using parallel clonal microcultures of keratinocytes. Exp Dermatol 19:387–392Google Scholar
  7. 7.
    Fortunel NO, Vaigot P, Cadio E, Martin MT (2010) Functional investigations of keratinocyte stem cells and progenitors at a single-cell level using multiparallel clonal microcultures. Methods Mol Biol 585:13–23Google Scholar
  8. 8.
    Chadli L, Cadio E, Vaigot P, Martin MT, Fortunel NO (2013) Monitoring the cycling activity of cultured human keratinocytes using a CFSE-based dye tracking approach. Methods Mol Biol 989:83–97Google Scholar
  9. 9.
    Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, Bright IJ, Lucero MY, Hiddessen AL, Legler TC, Kitano TK, Hodel MR, Petersen JF, Wyatt PW, Steenblock ER, Shah PH, Bousse LJ, Troup CB, Mellen JC, Wittmann DK, Erndt NG, Cauley TH, Koehler RT, So AP, Dube S, Rose KA, Montesclaros L, Wang S, Stumbo DP, Hodges SP, Romine S, Milanovich FP, White HE, Regan JF, Karlin-Neumann GA, Hindson CM, Saxonov S, Colston BW (2011) High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 83:8604–8610Google Scholar
  10. 10.
    Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR (2012) Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal Chem 84:1003–1011Google Scholar
  11. 11.
    Kretz M, Siprashvili Z, Chu C, Webster DE, Zehnder A, Qu K, Lee CS, Flockhart RJ, Groff AF, Chow J, Johnston D, Kim GE, Spitale RC, Flynn RA, Zheng GX, Aiyer S, Raj A, Rinn JL, Chang HY, Khavari PA (2013) Control of somatic tissue differentiation by the long non-coding RNA TINCR. Nature 493:231–235Google Scholar
  12. 12.
    Nagosa S, Leesch F, Putin D, Bhattacharya S, Altshuler A, Serror L, Amitai-Lange A, Nasser W, Aberdam E, Rouleau M, Tattikota SG, Poy MN, Aberdam D, Shalom-Feuerstein R (2017) microRNA-184 induces a commitment switch to epidermal differentiation. Stem Cell Reports 9:1991–2004Google Scholar
  13. 13.
    Fortunel NO, Otu HH, Ng HH, Chen J, Mu X, Chevassut T, Li X, Joseph M, Bailey C, Hatzfeld JA, Hatzfeld A, Usta F, Vega VB, Long PM, Libermann TA, Lim B (2003) Comment on “‘Stemness’: transcriptional profiling of embryonic and adult stem cells” and “a stem cell molecular signature”. Science 302:393Google Scholar
  14. 14.
    Arvia R, Sollai M, Pierucci F, Urso C, Massi D, Zakrzewska K (2017) Droplet digital PCR (ddPCR) vs quantitative real-time PCR (qPCR) approach for detection and quantification of Merkel cell polyomavirus (MCPyV) DNA in formalin fixed paraffin embedded (FFPE) cutaneous biopsies. J Virol Methods 246:15–20Google Scholar
  15. 15.
    Hurlin PJ, Quéva C, Koskinen PJ, Steingrímsson E, Ayer DE, Copeland NG, Jenkins NA, Eisenman RN (1995) Mad3 and Mad4: novel Max-interacting transcriptional repressors that suppress c-myc dependent transformation and are expressed during neural and epidermal differentiation. EMBO J 14:5646–5659Google Scholar
  16. 16.
    Sur I (2009) Krüppel-like factors 4 and 5: unity in diversity. Curr Genomics 10:594–603Google Scholar
  17. 17.
    Fortunel NO, Chadli L, Bourreau E, Cadio E, Vaigot P, Marie M, Deshayes N, Rathman-Josserand M, Leclaire J, Martin MT (2011) Cellular adhesion on collagen: a simple method to select human basal keratinocytes which preserves their high growth capacity. Eur J Dermatol 21(Suppl 2):12–20Google Scholar
  18. 18.
    Mine S, Fortunel NO, Pageon H, Asselineau D (2008) Aging alters functionally human dermal papillary fibroblasts but not reticular fibroblasts: a new view of skin morphogenesis and aging. PLoS One 3:e4066Google Scholar

Copyright information

© Springer Science+Business Media New York 2018

Authors and Affiliations

  • Frédéric Auvré
    • 1
    • 2
    • 3
    • 4
  • Julien Coutier
    • 1
    • 2
    • 3
    • 4
  • Michèle T. Martin
    • 1
    • 2
    • 3
    • 4
  • Nicolas O. Fortunel
    • 1
    • 2
    • 3
    • 4
  1. 1.Laboratoire de Génomique et Radiobiologie de la Kératinopoïèse, CEA/DRF/IBFJ/IRCMEvryFrance
  2. 2.INSERM U967Fontenay-aux-RosesFrance
  3. 3.Université Paris-DiderotParis 7France
  4. 4.Université Paris-SaclayParis 11France

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