Adaptive evolutionary trajectories in complexity: Transitions between unicellularity and facultative differentiated multicellularity.

Hanna Isaksson, Peter Lind, Eric Libby
Author Information
  1. Hanna Isaksson: Department of Mathematics and Mathematical Statistics, Umeå University, Umeå 90187, Sweden. ORCID
  2. Peter Lind: IceLab, Umeå University, Umeå 90187, Sweden. ORCID
  3. Eric Libby: Department of Mathematics and Mathematical Statistics, Umeå University, Umeå 90187, Sweden. ORCID

Abstract

Multicellularity spans a wide gamut in terms of complexity, from simple clonal clusters of cells to large-scale organisms composed of differentiated cells and tissues. While recent experiments have demonstrated that simple forms of multicellularity can readily evolve in response to different selective pressures, it is unknown if continued exposure to those same selective pressures will result in the evolution of increased multicellular complexity. We use mathematical models to consider the adaptive trajectories of unicellular organisms exposed to periodic bouts of abiotic stress, such as drought or antibiotics. Populations can improve survival in response to the stress by evolving multicellularity or cell differentiation-or both; however, these responses have associated costs when the stress is absent. We define a parameter space of fitness-relevant traits and identify where multicellularity, differentiation, or their combination is fittest. We then study the effects of adaptation by allowing populations to fix mutations that improve their fitness. We find that while the same mutation can be beneficial to populations of different complexity, e.g., strict unicellularity or life cycles with stages of differentiated multicellularity, the magnitudes of their effects can differ and alter which is fittest. As a result, we observe adaptive trajectories that gain and lose complexity. We also show that the order of mutations, historical contingency, can cause some transitions to be permanent in the absence of neutral evolution. Ultimately, we find that continued exposure to a selective driver for multicellularity can either lead to increasing complexity or a return to unicellularity.

Keywords

References

  1. Proc Natl Acad Sci U S A. 2009 Mar 3;106(9):3254-8 [PMID: 19223580]
  2. Curr Opin Genet Dev. 2016 Aug;39:29-34 [PMID: 27318097]
  3. Chem Soc Rev. 2013 Jan 7;42(1):305-41 [PMID: 23023210]
  4. Dev Cell. 2004 Sep;7(3):313-25 [PMID: 15363407]
  5. Curr Biol. 2012 Jun 19;22(12):1123-7 [PMID: 22608512]
  6. Biol Rev Camb Philos Soc. 2013 Nov;88(4):844-61 [PMID: 23448295]
  7. mBio. 2023 Dec 19;14(6):e0263423 [PMID: 37982608]
  8. Biophys Rev (Melville). 2022 Jun;3(2):021305 [PMID: 35673523]
  9. Proc Natl Acad Sci U S A. 2012 Jan 31;109(5):1595-600 [PMID: 22307617]
  10. Microbiol Spectr. 2015 Apr;3(2):MB-0002-2014 [PMID: 26104716]
  11. Nat Ecol Evol. 2019 Aug;3(8):1197-1205 [PMID: 31285576]
  12. Science. 2014 Oct 24;346(6208):426-7 [PMID: 25342789]
  13. Curr Opin Microbiol. 2022 Jun;67:102141 [PMID: 35247708]
  14. Nat Rev Microbiol. 2014 Feb;12(2):115-24 [PMID: 24384602]
  15. Sci Rep. 2019 Feb 20;9(1):2328 [PMID: 30787483]
  16. Dev Cell. 2017 Oct 23;43(2):124-140 [PMID: 29065305]
  17. Science. 2004 Sep 10;305(5690):1622-5 [PMID: 15308767]
  18. Proc Natl Acad Sci U S A. 2012 Feb 7;109(6):E326-35 [PMID: 22308336]
  19. Proc Natl Acad Sci U S A. 2015 Mar 3;112(9):2776-81 [PMID: 25605926]
  20. Evolution. 2008 Feb;62(2):436-51 [PMID: 18031303]
  21. Genes (Basel). 2023 Apr 19;14(4): [PMID: 37107699]
  22. Curr Opin Microbiol. 2013 Oct;16(5):580-9 [PMID: 23880136]
  23. Nat Rev Microbiol. 2016 Nov;14(11):716-723 [PMID: 27640757]
  24. J R Soc Interface. 2015 Jan 6;12(102):20140982 [PMID: 25551152]
  25. Metab Eng. 2017 Jan;39:19-28 [PMID: 27815194]
  26. Microbiol Spectr. 2018 Jul;6(4): [PMID: 30051798]
  27. PLoS Comput Biol. 2023 Apr 21;19(4):e1010698 [PMID: 37083675]
  28. Evolution. 1996 Apr;50(2):477-492 [PMID: 28568940]
  29. Dev Biol. 2011 Sep 1;357(1):73-82 [PMID: 21699890]
  30. Genes Dev. 1998 Apr 1;12(7):1022-35 [PMID: 9531539]
  31. Glycobiology. 2003 Apr;13(4):17R-27R [PMID: 12626396]
  32. Commun Biol. 2023 Mar 16;6(1):275 [PMID: 36928386]
  33. Philos Trans R Soc Lond B Biol Sci. 2009 Oct 12;364(1531):2809-17 [PMID: 19720646]
  34. Science. 2003 Jul 18;301(5631):361-3 [PMID: 12869759]
  35. Cell Stress Chaperones. 2023 Sep;28(5):455-466 [PMID: 36441380]
  36. F1000Res. 2014 Jun 24;3:133 [PMID: 25309731]
  37. Proc Natl Acad Sci U S A. 2015 May 12;112(19):6122-7 [PMID: 25918381]
  38. Antimicrob Agents Chemother. 2004 Oct;48(10):3670-6 [PMID: 15388418]
  39. Nat Commun. 2013;4:2742 [PMID: 24193369]
  40. Proc Biol Sci. 2023 Sep 27;290(2007):20231055 [PMID: 37727086]
  41. Front Microbiol. 2018 May 29;9:1121 [PMID: 29896182]
  42. Front Plant Sci. 2017 Nov 20;8:1997 [PMID: 29209355]
  43. J Theor Biol. 2010 Jan 7;262(1):23-34 [PMID: 19761779]
  44. Nature. 2005 Aug 25;436(7054):1171-5 [PMID: 16121184]
  45. Nat Commun. 2015 Jan 20;6:6102 [PMID: 25600558]
  46. J Bacteriol. 1991 Jun;173(11):3318-33 [PMID: 1904430]
  47. Cells. 2019 Oct 23;8(11): [PMID: 31652831]
  48. Philos Trans R Soc Lond B Biol Sci. 2017 Dec 5;372(1735): [PMID: 29061893]
  49. Annu Rev Genet. 2008;42:235-51 [PMID: 18983257]
  50. Philos Trans R Soc Lond B Biol Sci. 2016 Aug 19;371(1701): [PMID: 27431522]
  51. Microb Cell Fact. 2011 Aug 30;10 Suppl 1:S14 [PMID: 21995592]
  52. Proc Natl Acad Sci U S A. 2022 May 3;119(18):e2116066119 [PMID: 35486699]
  53. Evolution. 2019 May;73(5):1001-1011 [PMID: 30953575]
  54. Proc Natl Acad Sci U S A. 2012 Aug 21;109(34):13686-91 [PMID: 22872867]
  55. Proc Biol Sci. 2011 Dec 7;278(1724):3574-83 [PMID: 21490013]
  56. PLoS Comput Biol. 2014 Sep 18;10(9):e1003803 [PMID: 25233196]
  57. Nature. 2000 Dec 21-28;408(6815):965-7 [PMID: 11140681]
  58. PLoS Comput Biol. 2012;8(4):e1002468 [PMID: 22511858]
  59. Nat Ecol Evol. 2023 Jun;7(6):889-902 [PMID: 37081145]
  60. Proc Biol Sci. 2002 Nov 22;269(1507):2357-62 [PMID: 12495504]
  61. PLoS Comput Biol. 2010 Jun 10;6(6):e1000805 [PMID: 20548941]
  62. Nat Rev Microbiol. 2017 Jul;15(7):385-396 [PMID: 28420885]
  63. Bioessays. 2020 May;42(5):e2000029 [PMID: 32163611]
  64. Curr Genet. 2020 Apr;66(2):313-318 [PMID: 31559453]
  65. Cell. 2014 Aug 28;158(5):1136-1147 [PMID: 25171413]
  66. Proc Natl Acad Sci U S A. 2015 Jul 21;112(29):9076-81 [PMID: 26150498]
  67. Integr Comp Biol. 2003 Feb;43(1):64-73 [PMID: 21680410]
  68. PLoS Biol. 2014 Dec 16;12(12):e1002023 [PMID: 25514332]
  69. Am Nat. 2019 Mar;193(3):409-423 [PMID: 30794447]
  70. Microbiol Mol Biol Rev. 2009 Jun;73(2):310-47 [PMID: 19487730]
  71. Mar Life Sci Technol. 2022 Aug 16;4(3):389-413 [PMID: 37073170]
  72. FEMS Microbiol Rev. 2016 Nov 1;40(6):831-854 [PMID: 28204529]
  73. Nat Rev Genet. 2017 Aug;18(8):498-512 [PMID: 28479598]
  74. Nature. 2009 Nov 5;462(7269):90-3 [PMID: 19890329]
  75. Am J Bot. 2014 Jan;101(1):6-25 [PMID: 24363320]
  76. Curr Genet. 2021 Dec;67(6):871-876 [PMID: 34114051]
  77. Bioessays. 2009 Jul;31(7):758-68 [PMID: 19472368]
  78. PLoS Biol. 2020 Mar 19;18(3):e3000642 [PMID: 32191693]
  79. Cell Calcium. 2015 Mar;57(3):166-73 [PMID: 25498309]
  80. Environ Mol Mutagen. 2017 Jun;58(5):235-263 [PMID: 28485537]
  81. Genetics. 2005 Apr;169(4):1807-14 [PMID: 15687275]
  82. Nat Rev Microbiol. 2013 Jul;11(7):443-54 [PMID: 23712352]
  83. Arch Environ Contam Toxicol. 2000 Feb;38(2):147-51 [PMID: 10629274]
  84. FEMS Microbiol Rev. 2019 Jul 1;43(4):389-400 [PMID: 30980074]
  85. Science. 1999 May 21;284(5418):1318-22 [PMID: 10334980]
  86. Curr Biol. 2018 Jan 22;28(2):262-267.e3 [PMID: 29337077]
  87. Nat Commun. 2023 Jun 15;14(1):3555 [PMID: 37322016]
  88. Nat Ecol Evol. 2024 May;8(5):1010-1020 [PMID: 38486107]
  89. Science. 2013 Dec 13;342(6164):1364-7 [PMID: 24231808]
  90. Mol Biol Evol. 2008 Oct;25(10):2109-18 [PMID: 18640994]
  91. Microbiol Res. 2023 Mar;268:127302 [PMID: 36640720]
  92. Elife. 2023 Oct 27;12: [PMID: 37889142]
  93. Curr Biol. 2020 Nov 2;30(21):4155-4164.e6 [PMID: 32888478]
  94. Nat Rev Microbiol. 2013 Jul;11(7):467-81 [PMID: 23748343]
  95. Ecol Evol. 2019 Jul 09;9(15):8509-8523 [PMID: 31410258]

Grants

  1. 2018-03630/Vetenskapsrådet (VR)

MeSH Term

Biological Evolution
Mutation
Cell Differentiation
Adaptation, Physiological
Models, Biological
Genetic Fitness
Stress, Physiological

Word Cloud

Created with Highcharts 10.0.0multicellularitycomplexitycandifferentiatedselectivetrajectoriesstressunicellularitysimplecellsorganismsresponsedifferentpressurescontinuedexposureresultevolutionadaptiveimprovedifferentiationfittesteffectsadaptationpopulationsmutationsfindMulticellularityspanswidegamuttermsclonalclusterslarge-scalecomposedtissuesrecentexperimentsdemonstratedformsreadilyevolveunknownwillincreasedmulticellularusemathematicalmodelsconsiderunicellularexposedperiodicboutsabioticdroughtantibioticsPopulationssurvivalevolvingcelldifferentiation-orhoweverresponsesassociatedcostsabsentdefineparameterspacefitness-relevanttraitsidentifycombinationstudyallowingfixfitnessmutationbeneficialegstrictlifecyclesstagesmagnitudesdifferalterobservegainlosealsoshoworderhistoricalcontingencycausetransitionspermanentabsenceneutralUltimatelydrivereitherleadincreasingreturnAdaptiveevolutionarycomplexity:Transitionsfacultative

Similar Articles

Cited By