Time-regulated transcripts with the potential to modulate human pluripotent stem cell-derived cardiomyocyte differentiation

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art_MUNOZ_Timeregulated_transcripts_with_the_potential_to_modulate_human_2022.PDF (8.88 MB)
Citações na Scopus
2
Tipo de produção
article
Data de publicação
2022
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
BMC
Autores
MUNOZ, Juan J. A. M.
DARIOLLI, Rafael
SOBIE, Eric A.
Citação
STEM CELL RESEARCH & THERAPY, v.13, n.1, article ID 437, 27p, 2022
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Background Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) are a promising disease model, even though hiPSC-CMs cultured for extended periods display an undifferentiated transcriptional landscape. MiRNA-target gene interactions contribute to fine-tuning the genetic program governing cardiac maturation and may uncover critical pathways to be targeted. Methods We analyzed a hiPSC-CM public dataset to identify time-regulated miRNA-target gene interactions based on three logical steps of filtering. We validated this process in silico using 14 human and mouse public datasets, and further confirmed the findings by sampling seven time points over a 30-day protocol with a hiPSC-CM clone developed in our laboratory. We then added miRNA mimics from the top eight miRNAs candidates in three cell clones in two different moments of cardiac specification and maturation to assess their impact on differentiation characteristics including proliferation, sarcomere structure, contractility, and calcium handling. Results We uncovered 324 interactions among 29 differentially expressed genes and 51 miRNAs from 20,543 transcripts through 120 days of hiPSC-CM differentiation and selected 16 genes and 25 miRNAs based on the inverse pattern of expression (Pearson R-values < - 0.5) and consistency in different datasets. We validated 16 inverse interactions among eight genes and 12 miRNAs (Person R-values < - 0.5) during hiPSC-CMs differentiation and used miRNAs mimics to verify proliferation, structural and functional features related to maturation. We also demonstrated that miR-124 affects Ca2+ handling altering features associated with hiPSC-CMs maturation. Conclusion We uncovered time-regulated transcripts influencing pathways affecting cardiac differentiation/maturation axis and showed that the top-scoring miRNAs indeed affect primarily structural features highlighting their role in the hiPSC-CM maturation.
Palavras-chave
Cardiac differentiation, hiPSC-CM, Time-dependent regulated transcripts, miRNA
URI
https://observatorio.fm.usp.br/handle/OPI/49170
Referências
  1. Babiarz JE, 2012, STEM CELLS DEV, V21, P1956, DOI 10.1089/scd.2011.0357
  2. Bedada FB, 2014, STEM CELL REP, V3, P594, DOI 10.1016/j.stemcr.2014.07.012
  3. Bers DM, 2002, NATURE, V415, P198, DOI 10.1038/415198a
  4. Biagi D, 2021, J PERS MED, V11, DOI 10.3390/jpm11050374
  5. BOUVAGNET P, 1987, CIRC RES, V61, P329, DOI 10.1161/01.RES.61.3.329
  6. Burridge PW, 2012, CELL STEM CELL, V10, P16, DOI 10.1016/j.stem.2011.12.013
  7. Cai BZ, 2012, STEM CELLS, V30, P1746, DOI 10.1002/stem.1154
  8. Carpenter AE, 2006, GENOME BIOL, V7, DOI 10.1186/gb-2006-7-10-r100
  9. Chen A, 2014, STEM CELL RES THER, V5, DOI 10.1186/scrt401
  10. Churko JM, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-07333-4
  11. Condrat CE, 2020, CELLS-BASEL, V9, DOI 10.3390/cells9020276
  12. Cordes KR, 2009, CIRC RES, V104, P724, DOI 10.1161/CIRCRESAHA.108.192872
  13. Crestani T, 2020, BIOCHEM BIOPH RES CO, V533, P376, DOI 10.1016/j.bbrc.2020.09.021
  14. Dai DF, 2017, STEM CELLS INT, V2017, DOI 10.1155/2017/5153625
  15. Dariolli R, 2021, FRONT PHYSIOL, V12, DOI 10.3389/fphys.2021.624185
  16. Lima IMD, 2019, STEM CELL RES THER, V10, DOI 10.1186/s13287-019-1318-6
  17. Ding HM, 2021, MOL MED REP, V23, DOI 10.3892/mmr.2021.11961
  18. Eulalio A, 2012, NATURE, V492, P376, DOI 10.1038/nature11739
  19. Ford SJ, 2012, J PHYSIOL-LONDON, V590, P6047, DOI 10.1113/jphysiol.2012.240085
  20. Garate X, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-26156-3
  21. Gerbin KA, 2021, CELL SYST, V12, P670, DOI 10.1016/j.cels.2021.05.001
  22. Gomes AV, 2004, J BIOL CHEM, V279, P49579, DOI 10.1074/jbc.M407340200
  23. Grancharova T, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-94732-1
  24. Guo YX, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2008861118
  25. Guo YX, 2020, CIRC RES, V126, P1086, DOI 10.1161/CIRCRESAHA.119.315862
  26. Guo YX, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-06347-2
  27. Hinson JT, 2015, SCIENCE, V349, P982, DOI 10.1126/science.aaa5458
  28. Hom JR, 2011, DEV CELL, V21, P469, DOI 10.1016/j.devcel.2011.08.008
  29. Homan T, 2021, BIOINFORMATICS, V37, P4209, DOI 10.1093/bioinformatics/btab400
  30. Hwang HS, 2015, J MOL CELL CARDIOL, V85, P79, DOI 10.1016/j.yjmcc.2015.05.003
  31. Jiao SJ, 2017, CELL BIOSCI, V7, DOI 10.1186/s13578-017-0194-y
  32. Karbassi E, 2020, NAT REV CARDIOL, V17, P341, DOI 10.1038/s41569-019-0331-x
  33. Kerr CM, 2021, INT J MOL SCI, V22, P8482, DOI 10.3390/ijms22168482
  34. Kleinsorge Mandy, 2020, STAR Protoc, V1, P100026, DOI 10.1016/j.xpro.2020.100026
  35. Kolanowski TJ, 2017, INT J CARDIOL, V241, P379, DOI 10.1016/j.ijcard.2017.03.099
  36. Kuppusamy KT, 2015, P NATL ACAD SCI USA, V112, pE2785, DOI 10.1073/pnas.1424042112
  37. Leitolis A, 2019, FRONT CELL DEV BIOL, V7, DOI 10.3389/fcell.2019.00164
  38. Li SS, 2018, STEM CELL REP, V10, P808, DOI 10.1016/j.stemcr.2018.01.013
  39. Li YZ, 2016, SCI REP-UK, V6, DOI 10.1038/srep38815
  40. Lian XJ, 2012, P NATL ACAD SCI USA, V109, pE1848, DOI 10.1073/pnas.1200250109
  41. Lin Yongshun, 2020, STAR Protoc, V1, DOI 10.1016/j.xpro.2020.100015
  42. LOPASCHUK G D, 1991, American Journal of Physiology, V261, pH1698
  43. Lopaschuk GD, 2010, PHYSIOL REV, V90, P207, DOI 10.1152/physrev.00015.2009
  44. Lopez CA, 2021, SCI REP-UK, V11, DOI 10.1038/s41598-021-87186-y
  45. Lundy SD, 2013, STEM CELLS DEV, V22, P1991, DOI 10.1089/scd.2012.0490
  46. Luo XJ, 2020, FRONT CELL DEV BIOL, V8, DOI 10.3389/fcell.2020.00772
  47. Maas Renee G C, 2021, STAR Protoc, V2, P100334, DOI 10.1016/j.xpro.2021.100334
  48. MacLennan DH, 2003, NAT REV MOL CELL BIO, V4, P566, DOI 10.1038/nrm1151
  49. McGeary SE, 2019, SCIENCE, V366, P1470, DOI 10.1126/science.aav1741
  50. Nicolescu RC, 2019, FRONT PEDIATR, V6, DOI 10.3389/fped.2018.00424
  51. Oliveira NC de A, 2022, CLIN SCI
  52. Ong SB, 2018, EXPERT OPIN THER TAR, V22, P247, DOI 10.1080/14728222.2018.1439015
  53. Redd MA, 2019, NAT COMMUN, V10, DOI 10.1038/s41467-019-08388-7
  54. Robertson C, 2013, STEM CELLS, V31, P829, DOI 10.1002/stem.1331
  55. Romagnuolo R, 2019, STEM CELL REP, V12, P967, DOI 10.1016/j.stemcr.2019.04.005
  56. Ronaldson-Bouchard K, 2018, NATURE, V556, P239, DOI 10.1038/s41586-018-0016-3
  57. SASSE S, 1993, CIRC RES, V72, P932, DOI 10.1161/01.RES.72.5.932
  58. Scalzo Sergio, 2021, Cell Rep Methods, V1, P100044, DOI 10.1016/j.crmeth.2021.100044
  59. Schindelin J, 2012, NAT METHODS, V9, P676, DOI [10.1038/nmeth.2019, 10.1038/NMETH.2019]
  60. Sharma A, 2018, SCI REP-UK, V8, DOI 10.1038/s41598-018-24954-3
  61. Shirdel EA, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0017429
  62. Somers A, 2010, STEM CELLS, V28, P1728, DOI 10.1002/stem.495
  63. Talkhabi M, 2016, LIFE SCI, V145, P98, DOI 10.1016/j.lfs.2015.12.023
  64. Tian Y, 2015, SCI TRANSL MED, V7, DOI 10.1126/scitranslmed.3010841
  65. Tokar T, 2018, NUCLEIC ACIDS RES, V46, pD360, DOI 10.1093/nar/gkx1144
  66. Vilchez D, 2007, NAT NEUROSCI, V10, P1407, DOI 10.1038/nn1998
  67. Xu F, 2019, CLIN SCI, V133, P1387, DOI 10.1042/CS20190099
  68. Yang XL, 2014, CIRC RES, V114, P511, DOI 10.1161/CIRCRESAHA.114.300558
  69. Zhou SS, 2018, ACTA PHARMACOL SIN, V39, P1073, DOI 10.1038/aps.2018.30

Coleções
Artigos e Materiais de Revistas Científicas - FM/MCP
Artigos e Materiais de Revistas Científicas - HC/InCor
Artigos e Materiais de Revistas Científicas - LIM/13