Skip to main content
SpringerLink
Log in

Cell Reprogramming Preserving Epigenetic Age: Advantages and Limitations

  • REVIEW
  • Published:
Biochemistry (Moscow) Aims and scope Submit manuscript

Abstract

Our understanding of cell aging advanced significantly since the discovery of this phenomenon by Hayflick and Moorhead in 1961. In addition to the well-known shortening of telomeric regions of chromosomes, cell aging is closely associated with changes of the DNA methylation profile. Establishing, maintaining, or reversing epigenetic age of a cell is central to the technology of cell reprogramming. Two distinct approaches – iPSC- and transdifferentiation-based cell reprogramming – affect differently epigenetic age of the cells. The iPSC-based reprogramming protocols are generally believed to result in the reversion of DNA methylation profiles towards less differentiated states, while the original methylation profiles are preserved in the direct trans-differentiation protocols. Clearly, in order to develop adequate model of CNS pathologies, one has to have thorough understanding of the biological roles of DNA methylation in the development, maintenance of functional activity, tissue and cell diversity, restructuring of neural networks during learning, as well as in aging-associated neuronal decline. Direct cell reprogramming is an excellent alternative and a valuable supplement to the iPSC-based technologies both as a source of mature cells for modeling of neurodegenerative diseases, and as a novel powerful strategy for in vivo cell replacement therapy. Further advancement of the regenerative and personalized medicine will strongly depend on optimization of the production of patient-specific autologous cells involving alternative approaches of direct and indirect cell reprogramming that take into account epigenetic age of the starting cell material.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

5mC:

5-methylcytosine

Ascl1:

Achaete-scute homolog 1

BAM:

Brn2/Ascl1/Myt1L

Brn2:

POU domain, class 3, transcription factor 2

CH:

dinucleotide, where H = adenine (A), cytosine (C), or thymine (T)

CpG:

5′ cytosine-phosphate-guanine-3′ dinucleotide

ESCs:

embryonic stem cells

FUS:

Fused in Sarcoma

H3K27me3:

histone H3 tri-methylated at lysine 27

H3K4me3:

histone H3 tri-methylated at lysine 4 residue

hmC:

hydroxymethylcytosine

hmCG:

hydroxymethylcytosine-guanine dinucleotide

iPSCs:

induced pluripotent stem cells

Myt1L:

Myelin transcription factor 1-like protein

mCH:

methylated dinucleotide, where H = adenine (A), cytosine (C), or thymine (T)

NeuroD1:

neuronal differentiation

Ngn2:

neurogenin-2

REST:

RE1-silencing transcription factor

ROS:

reactive oxygen species

TF:

transcription factor

TL:

telomere length

References

  1. Dong, X., Milholland, B., and Vijg, J. (2016) Evidence for a limit to human lifespan, Nature, 538, 257-259, doi: https://doi.org/10.1038/nature19793 .

    Article  CAS  PubMed  Google Scholar 

  2. López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., and Kroemer, G. (2013) The hallmarks of aging, Cell, 153, 1194-217, doi: https://doi.org/10.1016/j.cell.2013.05.039 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimes, T. L., et al. (2018) An epigenetic biomarker of aging for lifespan and healthspan, Aging (Albany NY), 10, 573-591, doi: https://doi.org/10.18632/aging.101414 .

    Article  Google Scholar 

  4. Levine, M. E., Hosgood, H. D., Chen, B., Absher, D., Assimes, T., and Horvath, S. (2015) DNA methylation age of blood predicts future onset of lung cancer in the women’s health initiative, Aging (Albany NY), 7, 690-700, doi: https://doi.org/10.18632/aging.100809 .

    Article  CAS  Google Scholar 

  5. Horvath, S., and Levine, A. J. (2015) HIV-1 infection accelerates age according to the epigenetic clock, J. Infect. Dis., 212, 1563-1573, doi: https://doi.org/10.1093/infdis/jiv277 .

    Article  PubMed  PubMed Central  Google Scholar 

  6. Jylhävä, J., Pedersen, N. L., and Hägg, S. (2017) Biological age predictors, EBioMedicine, 21, 29-36, doi: https://doi.org/10.1016/j.ebiom.2017.03.046 .

    Article  PubMed  PubMed Central  Google Scholar 

  7. Gladyshev, T. V., and Gladyshev, V. N. (2016) A disease or not a disease? Aging as a pathology, Trends Mol. Med., 22, 995-996, doi: https://doi.org/10.1016/j.molmed.2016.09.009 .

    Article  PubMed  PubMed Central  Google Scholar 

  8. Takahashi, K., Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., and Yamanaka, S. (2007) Induction of pluripotent stem cells from adult human fibroblasts by defined factors, Cell, 131, 861-872, doi: https://doi.org/10.1016/j.cell.2007.11.019 .

    Article  CAS  PubMed  Google Scholar 

  9. Mertens, J., Marchetto, M. C., Bardy, C., and Gage, F. H. (2016) Evaluating cell reprogramming, differentiation and conversion technologies in neuroscience, Nat. Rev. Neurosci., 17, 424-437, doi: https://doi.org/10.1038/nrn.2016.46 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Böhnke, L., Traxler, L., Herdy, J. R., and Mertens, J. (2018) Human neurons to model aging: a dish best served old, Drug Discov. Today Dis. Models, 27, 43-49, doi: https://doi.org/10.1016/j.ddmod.2019.01.001 .

    Article  PubMed  Google Scholar 

  11. Traxler, L., Edenhofer, F., and Mertens, J. (2019) Next-generation disease modeling with direct conversion: a new path to old neurons, FEBS Lett., 593, 3316‐3337, doi: https://doi.org/10.1002/1873-3468.13678 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Mertens, J., Reid, D., Lau, S., Kim, Y., and Gage, F. H. (2018) Aging in a dish: iPSC-derived and directly induced neurons for studying brain aging and age-related neurodegenerative diseases, Annu. Rev. Genet., 52, 271-293, doi: https://doi.org/10.1146/annurev-genet-120417-031534 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hayflick, L. (1965) The limited in vitro lifetime of human diploid cell strains, Exp. Cell Res., 37, 614-636, doi: https://doi.org/10.1016/0014-4827(65)90211-9 .

    Article  CAS  PubMed  Google Scholar 

  14. Fang, E. F., Scheibye-Knudsen, M., Chua, K. F., Mattson, M. P., Croteau, D. L., and Bohr, V. A. (2016) Nuclear DNA damage signalling to mitochondria in aging, Nat. Rev. Mol. Cell Biol., 17, 308-321, doi: https://doi.org/10.1038/nrm.2016.14 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Chung, H. Y., Cesari, M., Anton, S., Marzetti, E., Giovannini, S., Seo, A. Y., Carter, C., Yu, B. P., and Leeuwenburgh, C. (2009) Molecular inflammation: underpinnings of aging and age-related diseases, Aging Res. Rev., 8, 18-30, doi: https://doi.org/10.1016/j.arr.2008.07.002 .

    Article  CAS  Google Scholar 

  16. Khan, S. S., Singer, B. D., Vaughan, D. E. (2017) Molecular and physiological manifestations and measurement of aging in humans, Aging Cell, 16, 624-633, doi: https://doi.org/10.1111/acel.12601 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Malaquin, N., Martinez, A., and Rodier, F. (2016) Keeping the senescence secretome under control: molecular reins on the senescence-associated secretory phenotype, Exp. Gerontol., 82, 39-49, doi: https://doi.org/10.1016/j.exger.2016.05.010 .

    Article  CAS  PubMed  Google Scholar 

  18. Horvath, S. (2013) DNA methylation age of human tissues and cell types, Genome Biol., 14, R115, doi: https://doi.org/10.1186/gb-2013-14-10-r115 .

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bell, C. G., Lowe, R., Adams, P. D., Baccarelli, A. A., Beck, S., et al. (2019) DNA methylation aging clocks: challenges and recommendations, Genome Biol., 20, 249, doi: https://doi.org/10.1186/s13059-019-1824-y .

    Article  PubMed  PubMed Central  Google Scholar 

  20. Johnson, T. E. (2006) Recent results: biomarkers of aging, Exp. Gerontol., 41, 1243-1246, doi: https://doi.org/10.1016/j.exger.2006.09.006 .

    Article  CAS  PubMed  Google Scholar 

  21. Butler, R. N., Sprott, R., Warner, H., Bland, J., Feuers, R., Forster, M., Fillit, H., Harman, S. M., Hewitt, M., Hyman, M., Johnson, K., Kligman, E., McClearn, G., Nelson, J., Richardson, A., Sonntag, W., Weindruch, R., and Wolf, N. (2004) Biomarkers of aging: from primitive organisms to humans, J. Gerontol. A Biol. Sci. Med. Sci., 59, B560-B567, doi: https://doi.org/10.1093/gerona/59.6.b560 .

    Article  PubMed  Google Scholar 

  22. Hayflick, L., and Moorhead, P. S. (1961) The serial cultivation of human diploid cell strains, Exp. Cell Res., 25, 585-621, doi: https://doi.org/10.1016/0014-4827(61)90192-6 .

    Article  CAS  PubMed  Google Scholar 

  23. Palm, W., and de Lange, T. (2008) How shelterin protects mammalian telomeres, Annu. Rev. Genet., 42, 301-334, doi: https://doi.org/10.1146/annurev.genet.41.110306.130350 .

    Article  CAS  PubMed  Google Scholar 

  24. Von Zglinicki, T., and Martin-Ruiz, C. M. (2005) Telomeres as biomarkers for aging and age-related diseases, Curr. Mol. Med., 5, 197-203, doi: https://doi.org/10.2174/1566524053586545 .

    Article  CAS  PubMed  Google Scholar 

  25. Mather, K. A., Jorm, A. F., Parslow, R. A., and Christensen, H. (2011) Is telomere length a biomarker of aging? J. Gerontol. A Biol. Sci. Med. Sci., 66, 202-213, doi: https://doi.org/10.1093/gerona/glq180 .

    Article  CAS  PubMed  Google Scholar 

  26. Lu, A. T., Seeboth, A., Tsai, P. C., Sun, D., Quach, A., et al. (2019) DNA methylation-based estimator of telomere length, Aging (Albany NY), 11, 5895-5923, doi: https://doi.org/10.18632/aging.102173 .

    Article  CAS  Google Scholar 

  27. Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., et al. (2009) Human DNA methylomes at base resolution show widespread epigenomic differences, Nature, 462, 315-322, doi: https://doi.org/10.1038/nature08514 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Stadler, M. B., Murr, R., Burger, L., Ivanek, R., Lienert, F., et al. (2011) DNA-binding factors shape the mouse methylome at distal regulatory regions, Nature, 480, 490-495, doi: https://doi.org/10.1038/nature10716 .

    Article  CAS  PubMed  Google Scholar 

  29. Schultz, M. D., He, Y., Whitaker, J. W., Hariharan, M., Mukamel, E. A., et al. (2015) Human body epigenome maps reveal noncanonical DNA methylation variation, Nature, 523, 212-216, doi: https://doi.org/10.1038/nature14465 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Whyte, W. A., Orlando, D. A., Hnisz, D., Abraham, B. J., Lin, C. Y., Kagey, M. H., Rahl, P. B., Lee, T. I., and Young, R. A. (2013) Master transcription factors and mediator establish super-enhancers at key cell identity genes, Cell, 153, 307-319, doi: https://doi.org/10.1016/j.cell.2013.03.035 .

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  31. He, Y., Hariharan, M., Gorkin, D. U., Dickel, D. E., Luo, C., Castanon, R. G., et al. (2017) Spatiotemporal DNA methylome dynamics of the developing mammalian fetus, bioRxiv, doi: https://doi.org/10.1101/166744 .

  32. Woodcock, D. M., Crowther, P. J., and Diver, W. P. (1987) The majority of methylated deoxycytidines in human DNA are not in the CpG dinucleotide, Biochem. Biophys. Res. Commun., 145, 888-894, doi: https://doi.org/10.1016/0006-291x(87)91048-5 .

    Article  CAS  PubMed  Google Scholar 

  33. Lister, R., Mukamel, E. A., Nery, J. R., Urich, M., Puddifoot, C. A., et al. (2013) Global epigenomic reconfiguration during mammalian brain development, Science, 341, 1237905, doi: https://doi.org/10.1126/science.1237905 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kolb, B., Mychasiuk, R., Muhammad, A., Li, Y., Frost, D. O., and Gibb, R. (2012) Experience and the developing prefrontal cortex, Proc. Natl. Acad. Sci. USA, 109 Suppl. 2, 17186-17193, doi: https://doi.org/10.1073/pnas.1121251109 .

    Article  PubMed  Google Scholar 

  35. Mellén, M., Ayata, P., Dewell, S., Kriaucionis, S., and Heintz, N. (2012) MeCP2 binds to 5hmC enriched within active genes and accessible chromatin in the nervous system, Cell, 151, 1417-1430, doi: https://doi.org/10.1016/j.cell.2012.11.022 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Li, H., Radford, J. C., Ragusa, M. J., Shea, K. L., McKercher, S. R., et al. (2008) Transcription factor MEF2C influences neural stem/progenitor cell differentiation and maturation in vivo, Proc. Natl. Acad. Sci. USA, 105, 9397-9402, doi: https://doi.org/10.1073/pnas.0802876105 .

    Article  PubMed  PubMed Central  Google Scholar 

  37. Akhtar, M. W., Kim, M. S., Adachi, M., Morris, M. J., Qi, X., Richardson, J. A., Bassel-Duby, R., Olson, E. N., Kavalali, E. T., and Monteggia, L. M. (2012) In vivo analysis of MEF2 transcription factors in synapse regulation and neuronal survival, PLoS One, 7, e34863, doi: https://doi.org/10.1371/journal.pone.0034863 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Fraga, M. F., and Esteller, M. (2007) Epigenetics and aging: the targets and the marks, Trends Genet., 23, 413-418, doi: https://doi.org/10.1016/j.tig.2007.05.008 .

    Article  CAS  PubMed  Google Scholar 

  39. Teschendorff, A. E., Menon, U., Gentry-Maharaj, A., Ramus, S. J., Weisenberger, D. J., et al. (2010) Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer, Genome Res., 20, 440-446, doi: https://doi.org/10.1101/gr.103606.109 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., et al. (2013) Genome-wide methylation profiles reveal quantitative views of human aging rates, Mol. Cell, 49, 359-367, doi: https://doi.org/10.1016/j.molcel.2012.10.016 .

    Article  CAS  PubMed  Google Scholar 

  41. Field, A. E., Robertson, N. A., Wang, T., Havas, A., Ideker, T., and Adams, P. D. (2018) DNA methylation clocks in aging: categories, causes, and consequences, Mol. Cell, 71, 882-895, doi: https://doi.org/10.1016/j.molcel.2018.08.008 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Sehl, M. E., Henry, J. E., Storniolo, A. M., Ganz, P. A., and Horvath, S. (2017) DNA methylation age is elevated in breast tissue of healthy women, Breast Cancer Res. Treat., 164, 209-219, doi: https://doi.org/10.1007/s10549-017-4218-4 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Binder, A. M., Corvalan, C., Mericq, V., Pereira, A., Santos, J. L., Horvath, S., Shepherd, J., and Michels, K. B. (2018) Faster ticking rate of the epigenetic clock is associated with faster pubertal development in girls, Epigenetics, 13, 85-94, doi: https://doi.org/10.1080/15592294.2017.1414127 .

    Article  PubMed  PubMed Central  Google Scholar 

  44. Horvath, S., and Raj, K. (2018) DNA methylation-based biomarkers and the epigenetic clock theory of aging, Nat. Rev. Genet., 19, 371-384, doi: https://doi.org/10.1038/s41576-018-0004-3 .

    Article  CAS  PubMed  Google Scholar 

  45. Lu, A. T., Quach, A., Wilson, J. G., Reiner, A. P., Aviv, A., Raj, K., Hou, L., Baccarelli, A. A., Li, Y., Stewart, J. D., Whitsel, E. A., Assimes, T. L., Ferrucci, L., and Horvath, S. (2019) DNA methylation GrimAge strongly predicts lifespan and healthspan, Aging (Albany NY), 11, 303-327, doi: https://doi.org/10.18632/aging.101684 .

    Article  CAS  Google Scholar 

  46. Booth, L. N., and Brunet, A. (2016) The aging epigenome, Mol. Cell, 62, 728-744, doi: https://doi.org/10.1016/j.molcel.2016.05.013 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Rose, N. R., and Klose, R. J. (2014) Understanding the relationship between DNA methylation and histone lysine methylation, Biochim. Biophys. Acta, 1839, 1362-1372, doi: https://doi.org/10.1016/j.bbagrm.2014.02.007 .

    Article  CAS  PubMed  Google Scholar 

  48. Reddington, J. P., Perricone, S. M., Nestor, C. E., Reichmann, J., Youngson, N. A., et al. (2013) Redistribution of H3K27me3 upon DNA hypomethylation results in de-repression of Polycomb target genes, Genome Biol., 14, R25, doi: https://doi.org/10.1186/gb-2013-14-3-r25 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Berger, S. L., and Sassone-Corsi, P. (2016) Metabolic signaling to chromatin, Cold Spring Harb. Perspect. Biol., 8, a019463, doi: https://doi.org/10.1101/cshperspect.a019463 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Niccoli, T., and Partridge, L. (2012) Aging as a risk factor for disease, Curr. Biol., 22, R741-52, doi: https://doi.org/10.1016/j.cub.2012.07.024 .

    Article  CAS  PubMed  Google Scholar 

  51. Ahlfors, J. E., Azimi, A., El-Ayoubi, R., Velumian, A., Vonderwalde, I., Boscher, C., Mihai, O., Mani, S., Samoilova, M., Khazaei, M., Fehlings, M. G., and Morshead, C. M. (2019) Examining the fundamental biology of a novel population of directly reprogrammed human neural precursor cells, Stem Cell Res. Ther., 10, 166, doi: https://doi.org/10.1186/s13287-019-1255-4 .

    Article  PubMed  PubMed Central  Google Scholar 

  52. Bellin, M., Marchetto, M. C., Gage, F. H., and Mummery, C. L. (2012) Induced pluripotent stem cells: the new patient? Nat. Rev. Mol. Cell Biol., 13, 713-726, doi: https://doi.org/10.1038/nrm3448 .

    Article  CAS  PubMed  Google Scholar 

  53. Lancaster, M. A., and Knoblich, J. A. (2014) Organogenesis in a dish: modeling development and disease using organoid technologies, Science, 345, 1247125, doi: https://doi.org/10.1126/science.1247125 .

    Article  CAS  PubMed  Google Scholar 

  54. Götz, M., Nakafuku, M., and Petrik, D. (2016) Neurogenesis in the developing and adult brain – similarities and key differences, Cold Spring Harb. Perspect. Biol., 8, a018853, doi: https://doi.org/10.1101/cshperspect.a018853 .

    Article  PubMed  PubMed Central  Google Scholar 

  55. Scheffler, B., Walton, N. M., Lin, D. D., Goetz, A. K., Enikolopov, G., Roper, S. N., and Steindler, D. A. (2005) Phenotypic and functional characterization of adult brain neuropoiesis, Proc. Natl. Acad. Sci. USA, 102, 9353-9358, doi: https://doi.org/10.1073/pnas.0503965102 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Madabhushi, R., Gao, F., Pfenning, A. R., Pan, L., Yamakawa, S., et al. (2015) Activity-induced DNA breaks govern the expression of neuronal early-response genes, Cell, 161, 1592-1605, doi: https://doi.org/10.1016/j.cell.2015.05.032 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. D’Angelo, M. A., Raices, M., Panowski, S. H., and Hetzer, M. W. (2009) Age-dependent deterioration of nuclear pore complexes causes a loss of nuclear integrity in postmitotic cells, Cell, 13, 284-295, doi: https://doi.org/10.1016/j.cell.2008.11.037 .

    Article  CAS  Google Scholar 

  58. Marchetto, M. C., Brennand, K. J., Boyer, L. F., and Gage, F. H. (2011) Induced pluripotent stem cells (iPSCs) and neurological disease modeling: progress and promises, Hum. Mol. Genet., 20, R109-R115, doi: https://doi.org/10.1093/hmg/ddr336 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lafaille, F. G., Pessach, I. M., Zhang, S. Y., Ciancanelli, M. J., Herman, M., et al. (2012) Impaired intrinsic immunity to HSV-1 in human iPSC-derived TLR3-deficient CNS cells, Nature, 491, 769-773, doi: https://doi.org/10.1038/nature11583 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Lee, G., Papapetrou, E. P., Kim, H., Chambers, S. M., Tomishima, M. J., et al. (2009) Modelling pathogenesis and treatment of familial dysautonomia using patient-specific iPSCs, Nature, 461, 402-406, doi: https://doi.org/10.1038/nature08320 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. De Boni, L., Gasparoni, G., Haubenreich, C., Tierling, S., Schmitt, I., Peitz, M., Koch, P., Walter, J., Wüllner, U., and Brüstle, O. (2018) DNA methylation alterations in iPSC- and hESC-derived neurons: potential implications for neurological disease modeling, Clin. Epigenetics, 10, 13, doi: https://doi.org/10.1186/s13148-018-0440-0 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Rando, T. A., and Chang, H. Y. (2012) Aging, rejuvenation, and epigenetic reprogramming: resetting the aging clock, Cell, 148, 46-57, doi: https://doi.org/10.1016/j.cell.2012.01.003 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Olova, N., Simpson, D. J., Marioni, R. E., and Chandra, T. (2019) Partial reprogramming induces a steady decline in epigenetic age before loss of somatic identity, Aging Cell, 18, e12877, doi: https://doi.org/10.1111/acel.12877 .

    Article  CAS  PubMed  Google Scholar 

  64. Ocampo, A., Reddy, P., Martinez-Redondo, P., Platero-Luengo, A., Hatanaka, F., et al. (2016) In vivo amelioration of age-associated hallmarks by partial reprogramming, Cell, 167, 1719-1733.e12, doi: https://doi.org/10.1016/j.cell.2016.11.052 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Sheng, C., Jungverdorben, J., Wiethoff, H., Lin, Q., Flitsch, L. J., Eckert, D., et al. (2018) A stably self-renewing adult blood-derived induced neural stem cell exhibiting patternability and epigenetic rejuvenation, Nat. Commun., 9, 4047, doi: https://doi.org/10.1038/s41467-018-06398-5 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Marion, R. M., Strati, K., Li, H., Tejera, A., Schoeftner, S., Ortega, S., Serrano, M., and Blasco, M. A. (2009) Telomeres acquire embryonic stem cell characteristics in induced pluripotent stem cells, Cell Stem Cell, 4, 141-154, doi: https://doi.org/10.1016/j.stem.2008.12.010 .

    Article  CAS  PubMed  Google Scholar 

  67. Suhr, S. T., Chang, E. A., Rodriguez, R. M., Wang, K., Ross, P. J., Beyhan, Z., Murthy, S., and Cibelli, J. B. (2009) Telomere dynamics in human cells reprogrammed to pluripotency, PLoS One, 4, e8124, doi: https://doi.org/10.1371/journal.pone.0008124 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Suhr, S. T., Chang, E. A., Tjong, J., Alcasid, N., Perkins, G. A., Goissis, M. D., Ellisman, M. H., Perez, G. I., and Cibelli, J. B. (2010) Mitochondrial rejuvenation after induced pluripotency, PLoS One, 5, e14095, doi: https://doi.org/10.1371/journal.pone.0014095 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Prigione, A., Hossini, A. M., Lichtner, B., Serin, A., Fauler, B., Megges, M., Lurz, R., Lehrach, H., Makrantonaki, E., Zouboulis, C. C., and Adjaye, J. (2011) Mitochondrial-associated cell death mechanisms are reset to an embryonic-like state in aged donor-derived iPS cells harboring chromosomal aberrations, PLoS One, 6, e27352, doi: https://doi.org/10.1371/journal.pone.0027352 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Nekrasov, E. D., Vigont, V. A., Klyushnikov, S. A., Lebedeva, O. S., Vassina, E. M., et al. (2016) Manifestation of Huntington’s disease pathology in human induced pluripotent stem cell-derived neurons, Mol. Neurodegener., 11, 27, doi: https://doi.org/10.1186/s13024-016-0092-5 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Koch, P., Breuer, P., Peitz, M., Jungverdorben, J., Kesavan, J., et al. (2011) Excitation-induced ataxin-3 aggregation in neurons from patients with Machado–Joseph disease, Nature, 480, 543-546, doi: https://doi.org/10.1038/nature10671 .

    Article  CAS  PubMed  Google Scholar 

  72. Duan, L., Bhattacharyya, B. J., Belmadani, A., Pan, L., Miller, R. J., and Kessler, J. A. (2014) Stem cell derived basal forebrain cholinergic neurons from Alzheimer’s disease patients are more susceptible to cell death, Mol. Neurodegener., 9, 3, doi: https://doi.org/10.1186/1750-1326-9-3 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Yagi, T., Ito, D., Okada, Y., Akamatsu, W., Nihei, Y., Yoshizaki, T., Yamanaka, S., Okano, H., and Suzuki, N. (2011) Modeling familial Alzheimer’s disease with induced pluripotent stem cells, Hum. Mol. Genet., 20, 4530-4539, doi: https://doi.org/10.1093/hmg/ddr394 .

    Article  CAS  PubMed  Google Scholar 

  74. Miller, J. D., Ganat, Y. M., Kishinevsky, S., Bowman, R. L., Liu, B., et al. (2013) Human iPSC-based modeling of late-onset disease via progerin-induced aging, Cell Stem Cell, 13, 691-705, doi: https://doi.org/10.1016/j.stem.2013.11.006 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Davis, R. L., Weintraub, H., and Lassar, A. B. (1987) Expression of a single transfected cDNA converts fibroblasts to myoblasts, Cell, 51, 987-1000, doi: https://doi.org/10.1016/0092-8674(87)90585-x .

    Article  CAS  PubMed  Google Scholar 

  76. Huang, P., Zhang, L., Gao, Y., He, Z., Yao, D., et al. (2014) Direct reprogramming of human fibroblasts to functional and expandable hepatocytes, Cell Stem Cell, 14, 370-384, doi: https://doi.org/10.1016/j.stem.2014.01.003 .

    Article  CAS  PubMed  Google Scholar 

  77. Ieda, M., Fu, J. D., Delgado-Olguin, P., Vedantham, V., Hayashi, Y., Bruneau, B. G., and Srivastava, D. (2010) Direct reprogramming of fibroblasts into functional cardiomyocytes by defined factors, Cell, 142, 375-386, doi: https://doi.org/10.1016/j.cell.2010.07.002 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Laiosa, C. V., Stadtfeld, M., Xie, H., de Andres-Aguayo, L., and Graf, T. (2006) Reprogramming of committed T cell progenitors to macrophages and dendritic cells by C/EBP alpha and PU.1 transcription factors, Immunity, 25, 731-744, doi: https://doi.org/10.1016/j.immuni.2006.09.011 .

    Article  CAS  PubMed  Google Scholar 

  79. Vierbuchen, T., Ostermeier, A., Pang, Z. P., Kokubu, Y., Südhof, T. C., and Wernig, M. (2010) Direct conversion of fibroblasts to functional neurons by defined factors, Nature, 463, 1035-1041, doi: https://doi.org/10.1038/nature08797 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Zhu, S., Russ, H. A., Wang, X., Zhang, M., Ma, T., Xu, T., Tang, S., Hebrok, M., and Ding, S. (2016) Human pancreatic beta-like cells converted from fibroblasts, Nat. Commun., 7, 10080, doi: https://doi.org/10.1038/ncomms10080 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Pang, Z. P., Yang, N., Vierbuchen, T., Ostermeier, A., Fuentes, D. R., Yang, T. Q., Citri, A., Sebastiano, V., Marro, S., Südhofm, T. C., and Wernig, M. (2011) Induction of human neuronal cells by defined transcription factors, Nature, 476, 220-223, doi: https://doi.org/10.1038/nature10202 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Mollinari, C., Zhao, J., Lupacchini, L., Garaci, E., Merlo, D., and Pei, G. (2018) Transdifferentiation: a new promise for neurodegenerative diseases, Cell Death Dis., 9, 830, doi: https://doi.org/10.1038/s41419-018-0891-4 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Wapinski, O. L., Vierbuchen, T., Qu, K., Lee, Q. Y., Chanda, S., et al. (2013) Hierarchical mechanisms for direct reprogramming of fibroblasts to neurons, Cell, 155, 621-635, doi: https://doi.org/10.1016/j.cell.2013.09.028 .

    Article  CAS  PubMed  Google Scholar 

  84. Chronis, C., Fiziev, P., Papp, B., Butz, S., Bonora, G., Sabri, S., Ernst, J., and Plath, K. (2017) Cooperative binding of transcription factors orchestrates reprogramming, Cell, 168, 442-459.e20, doi: https://doi.org/10.1016/j.cell.2016.12.016 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Fu, K., Chronis, C., Soufi, A., Bonora, G., Edwards, M., Smale, S. T., Zaret, K. S., Plath, K., and Pellegrini, M. (2018) Comparison of reprogramming factor targets reveals both species-specific and conserved mechanisms in early iPSC reprogramming, BMC Genomics, 19, 956, doi: https://doi.org/10.1186/s12864-018-5326-1 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Liu, M. L., Zang, T., Zou, Y., Chang, J. C., Gibson, J. R., Huber, K. M., and Zhang, C. L. (2013) Small molecules enable neurogenin 2 to efficiently convert human fibroblasts into cholinergic neurons, Nat. Commun., 4, 2183, doi: https://doi.org/10.1038/ncomms3183 .

    Article  CAS  PubMed  Google Scholar 

  87. Matsuda, T., Irie, T., Katsurabayashi, S., Hayashi, Y., Nagai, T., Hamazaki, N., Adefuin, A. M. D., Miura, F., Ito, T., Kimura, H., Shirahige, K., Takeda, T., Iwasaki, K., Imamura, T., and Nakashima, K. (2019) Pioneer factor NeuroD1 rearranges transcriptional and epigenetic profiles to execute microglia-neuron conversion, Neuron, 101, 472-485.e7, doi: https://doi.org/10.1016/j.neuron.2018.12.010 .

    Article  CAS  PubMed  Google Scholar 

  88. Iwafuchi-Doi, M., and Zaret, K. S. (2014) Pioneer transcription factors in cell reprogramming, Genes Dev., 28, 2679-2692, doi: https://doi.org/10.1101/gad.253443.114 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Wapinski, O. L., Lee, Q. Y., Chen, A. C., Li, R., Corces, M. R., et al. (2017) Rapid chromatin switch in the direct reprogramming of fibroblasts to neurons, Cell Rep., 20, 3236-3247, doi: https://doi.org/10.1016/j.celrep.2017.09.011 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Ladewig, J., Mertens, J., Kesavan, J., Doerr, J., Poppe, D., Glaue, F., Herms, S., Wernet, P., Kögler, G., Müller, F.-J., Koch, P., and Brüstle, O. (2012) Small molecules enable highly efficient neuronal conversion of human fibroblasts, Nat. Methods, 9, 575-578, doi: https://doi.org/10.1038/nmeth.1972 .

    Article  CAS  PubMed  Google Scholar 

  91. Zhao, J., He, H., Zhou, K., Ren, Y., Shi, Z., Wu, Z., Wang, Y., Lu, Y., and Jiao, J. (2012) Neuronal transcription factors induce conversion of human glioma cells to neurons and inhibit tumorigenesis, PLoS One, 7, e41506, doi: https://doi.org/10.1371/journal.pone.0041506 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Samoilova, E. M., Kalsin, V. A., Kushnir, N. M., Chistyakov, D. A., Troitskiy, A. V., and Baklaushev, V. P. (2018) Adult neural stem cells: basic research and production strategies for neurorestorative therapy, Stem Cells Int., 2018, 4835491, doi: https://doi.org/10.1155/2018/4835491 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Samoilova, E. M., Revkova, V. A., Brovkina, O. I., Kalsin, V. A., Melnikov, P. A., et al. (2019) Chemical reprogramming of somatic cells in neural direction: myth or reality? Bull. Exp. Biol. Med., 167, 546-555, doi: https://doi.org/10.1007/s10517-019-04570-5 .

    Article  CAS  PubMed  Google Scholar 

  94. Wu, H., and Zhang, Y. (2014) Reversing DNA methylation: mechanisms, genomics, and biological functions, Cell, 156, 45-68, doi: https://doi.org/10.1016/j.cell.2013.12.019 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Luo, C., Lee, Q. Y., Wapinski, O., Castanon, R., Nery, J. R., Mall, M., Kareta, M. S., Cullen, S. M., Goodell, M. A., Chang, H. Y., Wernig, M., and Ecker, J. R. (2019) Global DNA methylation remodeling during direct reprogramming of fibroblasts to neurons, eLife, 8, e40197, doi: https://doi.org/10.7554/eLife.40197 .

    Article  PubMed  PubMed Central  Google Scholar 

  96. Mertens, J., Paquola, A., Ku, M., Hatch, E., Böhnke, L., et al. (2015) Directly reprogrammed human neurons retain aging-associated transcriptomic signatures and reveal age-related nucleocytoplasmic defects, Cell Stem Cell, 17, 705-718, doi: https://doi.org/10.1016/j.stem.2015.09.001 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Yoo, A. S., Sun, A. X., Li, L., Shcheglovitov, A., Portmann, T., Li, Y., Lee-Messer, C., Dolmetsch, R. E., Tsien, R. W., and Crabtree, G. R. (2011) MicroRNA-mediated conversion of human fibroblasts to neurons, Nature, 476, 228-231, doi: https://doi.org/10.1038/nature10323 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Huh, C. J., Zhang, B., Victor, M. B., Dahiya, S., Batista, L. F., Horvath, S., and Yoo, A. S. (2016) Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts, eLife, 5, e18648, doi: https://doi.org/10.7554/eLife.18648 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Stroud, H., Su, S. C., Hrvatin, S., Greben, A. W., Renthal, W., Boxer, L. D., Nagy, M. A., Hochbaum, D. R., Kinde, B., Gabel, H. W., and Greenberg, M. E. (2017) Early-life gene expression in neurons modulates lasting epigenetic states, Cell, 171, 1151-1164.e16, doi: https://doi.org/10.1016/j.cell.2017.09.047 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Iwamoto, K., Bundo, M., Ueda, J., Oldham, M. C., Ukai, W., Hashimoto, E., Saito, T., Geschwind, D. H., and Kato, T. (2011) Neurons show distinctive DNA methylation profile and higher interindividual variations compared with non-neurons, Genome Res., 21, 688-696, doi: https://doi.org/10.1101/gr.112755.110 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Nicholas, C. R., Chen, J., Tang, Y., Southwell, D. G., Chalmers, N., et al. (2013) Functional maturation of hPSC-derived forebrain interneurons requires an extended timeline and mimics human neural development, Cell Stem Cell, 12, 573-586, doi: https://doi.org/10.1016/j.stem.2013.04.005 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Victor, M. B., Richner, M., Olsen, H. E., Lee, S. W., Monteys, A. M., Ma, C., Huh, C. J., Zhang, B., Davidson, B. L., Yang, X. W., and Yoo, A. S. (2018) Striatal neurons directly converted from Huntington’s disease patient fibroblasts recapitulate age-associated disease phenotypes, Nat. Neurosci., 21, 341-352, doi: https://doi.org/10.1038/s41593-018-0075-7 .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Schafer, S. T., Paquola, A., Stern, S., Gosselin, D., Ku, M., et al. (2019) Pathological priming causes developmental gene network heterochronicity in autistic subject-derived neurons, Nat. Neurosci., 22, 243-255, doi: https://doi.org/10.1038/s41593-018-0295-x .

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

The work was supported by the Russian Foundation for Basic Research (project no. 19-115-50396).

Author information

Authors and Affiliations

  1. Federal Research Clinical Center, FMBA of Russia, 115682, Moscow, Russia

    E. M. Samoylova & V. P. Baklaushev

Authors
  1. E. M. Samoylova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. P. Baklaushev
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E. M. Samoylova.

Ethics declarations

The authors declare no conflict of interest in financial or any other sphere. This article does not contain any studies with human participants or animals performed by any of the authors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Samoylova, E.M., Baklaushev, V.P. Cell Reprogramming Preserving Epigenetic Age: Advantages and Limitations. Biochemistry Moscow 85, 1035–1047 (2020). https://doi.org/10.1134/S0006297920090047

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0006297920090047

Keywords

Search

Navigation