While early multicellular lineages necessarily started out as relatively simple groups of cells, little is known about how they became Darwinian entities capable of sustained multicellular evolution1,2,3. Here we investigate this with a multicellularity long-term evolution experiment, selecting for larger group size in the snowflake yeast (Saccharomyces cerevisiae) model system. Given the historical importance of oxygen limitation4, our ongoing experiment consists of three metabolic treatments5—anaerobic, obligately aerobic and mixotrophic yeast. After 600 rounds of selection, snowflake yeast in the anaerobic treatment group evolved to be macroscopic, becoming around 2 × 104 times larger (approximately mm scale) and about 104-fold more biophysically tough, while retaining a clonal multicellular life cycle. This occurred through biophysical adaptation—evolution of increasingly elongate cells that initially reduced the strain of cellular packing and then facilitated branch entanglements that enabled groups of cells to stay together even after many cellular bonds fracture. By contrast, snowflake yeast competing for low oxygen5 remained microscopic, evolving to be only around sixfold larger, underscoring the critical role of oxygen levels in the evolution of multicellular size. Together, this research provides unique insights into an ongoing evolutionary transition in individuality, showing how simple groups of cells overcome fundamental biophysical limitations through gradual, yet sustained, multicellular evolution.
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Underlying data used to generate figures and raw data are available at GitHub (https://github.com/ozanbozdag/de_novo_evolution_of_macroscopic_multicellularity). Raw Illumina sequencing reads are available at the NIH Sequence Read Archive under accession number PRJNA943273. All microscopy images used to generate data are archived in the Ratcliff laboratories Dropbox and are available on request.
Codes used in this study are available at GitHub (https://github.com/ozanbozdag/de_novo_evolution_of_macroscopic_multicellularity). Code for the simple 3D biophysical simulation are provided in Supplementary File 1; these simulations were adapted from ref. 35 (further information can be requested from T.C.D. or P.J.Y.).
Libby, E. & Rainey, P. B. A conceptual framework for the evolutionary origins of multicellularity. Phys. Biol. 10, 035001 (2013).
Michod, R. E. in The Evolution of Multicellularity (eds Herron M. D., Conlin P. L. & Ratcliff W. C.) 25–52 (CRC Press, 2022).
Buss, L. W. The Evolution of Individuality Vol. 796 (Princeton Univ. Press, 2014).
Knoll, A. H. The multiple origins of complex multicellularity. Ann. Rev. Earth Planet. Sci. 39, 217–239 (2011).
Bozdag, G. O., Libby, E., Pineau, R., Reinhard, C. T. & Ratcliff, W. C. Oxygen suppression of macroscopic multicellularity. Nat. Commun. 12, 2838 (2021).
Smukalla, S. et al. FLO1 is a variable green beard gene that drives biofilm-like cooperation in budding yeast. Cell 135, 726–737 (2008).
Tong, K., Bozdag, G. O. & Ratcliff, W. C. Selective drivers of simple multicellularity. Curr. Opin. Microbiol. 67, 102141 (2022).
Bonner, J. T. Perspective: the size‐complexity rule. Evolution 58, 1883–1890 (2004).
Willensdorfer, M. Organism size promotes the evolution of specialized cells in multicellular digital organisms. J. Evol. Biol. 21, 104–110 (2008).
Knoll, A. H. & Hewitt, D. in The Major Transitions in Evolution Revisited (eds Calcott B. & Sterelny K.) 251–270 (MIT Press, 2011).
Bonner, J. T. Why Size Matters: From Bacteria to Blue Whales (Princeton Univ. Press, 2011).
Boudaoud, A. An introduction to the mechanics of morphogenesis for plant biologists. Trends Plant Sci. 15, 353–360 (2010).
Jacobeen, S. et al. Cellular packing, mechanical stress and the evolution of multicellularity. Nat. Phys. 14, 286–290 (2018).
Boraas, M. E., Seale, D. B. & Boxhorn, J. E. Phagotrophy by a flagellate selects for colonial prey: a possible origin of multicellularity. Evol. Ecol. 12, 153–164 (1998).
Koschwanez, J. H., Foster, K. R. & Murray, A. W. Sucrose utilization in budding yeast as a model for the origin of undifferentiated multicellularity. PLoS Biol. 9, e1001122 (2011).
Herron, M. D. et al. De novo origins of multicellularity in response to predation. Sci. Rep. 9, 2328 (2019).
Westbrook, J. W. et al. What makes a leaf tough? Patterns of correlated evolution between leaf toughness traits and demographic rates among 197 shade-tolerant woody species in a neotropical forest. Am. Nat. 177, 800–811 (2011).
Prakash, V. N., Bull, M. S. & Prakash, M. Motility-induced fracture reveals a ductile-to-brittle crossover in a simple animal’s epithelia. Nat. Phys. 17, 504–511 (2021).
Ratcliff, W. C., Denison, R. F., Borrello, M. & Travisano, M. Experimental evolution of multicellularity. Proc. Natl Acad. Sci. USA 109, 1595–1600 (2012).
Lenski, R. E., Rose, M. R., Simpson, S. C. & Tadler, S. C. Long-term experimental evolution in Escherichia coli. I. Adaptation and divergence during 2,000 generations. Am. Nat. 138, 1315–1341 (1991).
Ratcliff, W. C., Fankhauser, J. D., Rogers, D. W., Greig, D. & Travisano, M. Origins of multicellular evolvability in snowflake yeast. Nat. Commun. 6, 6102 (2015).
Heinrich, E. C., Farzin, M., Klok, C. J. & Harrison, J. F. The effect of developmental stage on the sensitivity of cell and body size to hypoxia in Drosophila melanogaster. J. Exp. Biol. 214, 1419–1427 (2011).
Denk, W. & Horstmann, H. Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biol. 2, e329 (2004).
Edwards, C. E., Mai, D. J., Tang, S. & Olsen, B. D. Molecular anisotropy and rearrangement as mechanisms of toughness and extensibility in entangled physical gels. Phys. Rev. Mater. 4, 015602 (2020).
Brown, E., Nasto, A., Athanassiadis, A. G. & Jaeger, H. M. Strain stiffening in random packings of entangled granular chains. Phys. Rev. Lett. 108, 108302 (2012).
Raymer, D. M. & Smith, D. E. Spontaneous knotting of an agitated string. Proc. Natl Acad. Sci. USA 104, 16432–16437 (2007).
Wilhelm, J. & Frey, E. Elasticity of stiff polymer networks. Phys. Rev. Lett. 91, 108103 (2003).
Kim, J., Zhang, G., Shi, M. & Suo, Z. Fracture, fatigue, and friction of polymers in which entanglements greatly outnumber cross-links. Science 374, 212–216 (2021).
Tauber, J., Rovigatti, L., Dussi, S. & Van Der Gucht, J. Sharing the load: stress redistribution governs fracture of polymer double networks. Macromolecules 54, 8563–8574 (2021).
Sheu, Y.-J., Barral, Y. & Snyder, M. Polarized growth controls cell shape and bipolar bud site selection in Saccharomyces cerevisiae. Mol. Cell. Biol. 20, 5235–5247 (2000).
Watanabe, M., Watanabe, D., Nogami, S., Morishita, S. & Ohya, Y. Comprehensive and quantitative analysis of yeast deletion mutants defective in apical and isotropic bud growth. Curr. Genet. 55, 365–380 (2009).
Sopko, R. et al. Mapping pathways and phenotypes by systematic gene overexpression. Mol. Cell 21, 319–330 (2006).
Lee, D. H., Tamura, A., Arisaka, Y., Seo, J.-H. & Yui, N. Mechanically reinforced gelatin hydrogels by introducing slidable supramolecular cross-linkers. Polymers 11, 1787 (2019).
Gerhards, C. Effects of Type of Testing Equipment and Specimen Size on Toughness of Wood Vol. 97 (Forest Products Laboratory, 1968).
Jacobeen, S. et al. Geometry, packing, and evolutionary paths to increased multicellular size. Phys. Rev. E 97, 050401 (2018).
Okasha, S. Multilevel selection and the major transitions in evolution. Phil. Sci. 72, 1013–1025 (2005).
Graessley, W. W. The Entanglement Concept in Polymer Rheology (Springer, 1974).
Chen, W., Yu, H., Li, Q., Liu, Y. & Li, J. Ultralight and highly flexible aerogels with long cellulose I nanofibers. Soft Matter 7, 10360–10368 (2011).
Gravish, N., Franklin, S. V., Hu, D. L. & Goldman, D. I. Entangled granular media. Phys. Rev. Lett. 108, 208001 (2012).
Zou, L.-N., Cheng, X., Rivers, M. L., Jaeger, H. M. & Nagel, S. R. The packing of granular polymer chains. Science 326, 408–410 (2009).
Ozkan-Aydin, Y., Goldman, D. I. & Bhamla, M. S. Collective dynamics in entangled worm and robot blobs. Proc. Natl Acad. Sci. USA 118, e2010542118 (2021).
Nagy, L. G. in The Evolution of Multicellularity 279–300 (CRC Press, 2022).
Moore, D. Fungal Biology in the Origin and Emergence of Life (Cambridge Univ. Press, 2013).
García-Segovia, P., Andrés-Bello, A. & Martínez-Monzó, J. Rehydration of air-dried Shiitake mushroom (Lentinus edodes) caps: comparison of conventional and vacuum water immersion processes. LWT Food Sci. Technol. 44, 480–488 (2011).
Roth, R., Wagner, R. & Goodenough, U. Lichen 3. Outer layers. Algal Res. 56, 102332 (2021).
Yanni, D. et al. Topological constraints in early multicellularity favor reproductive division of labor. eLife 9, e54348 (2020).
Larson, B. T. et al. Biophysical principles of choanoflagellate self-organization. Proc. Natl Acad. Sci. USA 117, 1303–1311 (2020).
Hinkle, P. C., Kumar, M. A., Resetar, A. & Harris, D. L. Mechanistic stoichiometry of mitochondrial oxidative phosphorylation. Biochemistry 30, 3576–3582 (1991).
Raymond, J. & Segrè, D. The effect of oxygen on biochemical networks and the evolution of complex life. Science 311, 1764–1767 (2006).
Lewontin, R. C. The units of selection. Annu. Rev. Ecol. Syst. 1, 1–18 (1970).
Gietz, R. D. & Schiestl, R. H. High-efficiency yeast transformation using the LiAc/SS carrier DNA/PEG method. Nat. Protoc. 2, 31–34 (2007).
Deerinck, T. J. et al. High‐performance serial block‐face SEM of nonconductive biological samples enabled by focal gas injection‐based charge compensation. J. Microsc. 270, 142–149 (2018).
Ngo, H. T. & Yin, C. S. Luteimonas terrae sp. nov., isolated from rhizosphere soil of Radix ophiopogonis. Int. J. Syst. Evol. Microbiol. 66, 1920–1925 (2016).
Zamani-Dahaj, S. A. et al. Spontaneous emergence of multicellular heritability. Preprint at bioRxiv https://doi.org/10.1101/2021.07.19.452990 (2021).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://arxiv.org/abs/1303.3997 (2013).
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at https://arxiv.org/abs/1207.3907 (2012).
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Briefings Bioinform. 14, 178–192 (2013).
Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012).
Cherry, J. M. et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 40, D700–D705 (2012).
We thank J. T. Pentz for teaching us Illumina library preparation; S. Biliya at the High Throughput DNA Sequencing Core at Georgia Tech for sequencing the genomes of evolved strains; K. A. Boateng at Core Facilities at the Carl R. Woese Institute for Genomic Biology for the SEM imaging; S. Cao for helping with microscopy during the early stages of this project; and C. Orlic, L. Nagy, and all of the members of the Ratcliff group for comments on the manuscript. This work was supported by NIH grants R35-GM138030 to W.C.R. and R35-GM138354 to P.J.Y., Human Frontiers in Science Grant RGY0080/2020 to W.C.R., and a Packard Fellowship for Science and Engineering to W.C.R.
The authors declare no competing interests.
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Extended data figures and tables
Extended Data Fig. 1 Temporal dynamics of size evolution in each population and treatment group.
Data points show the weighted average radius of cluster size for the entire population. This was calculated by measuring the size of an average of 1150 snowflake yeast clusters per sample population (3 ancestors + 3 treatment groups x 5 replicate populations x 12 time points = 183 samples, all data is publicly available under the raw data file). Please see the Methods section for details on how weighted average radius was calculated.
Extended Data Fig. 2 Characterizing the life-cycle of the ancestral (microscopic) and evolved (macroscopic) snowflake yeast.
a, During the ~24-hour growth cycle, snowflake yeast compete for growth and reproduction in 10 mL of YPED (250 RPM at 30 °C). At the end of the growth phase, we select for larger group size via settling selection. While there is a theoretical maximum survival rate of 15% (that is, if all of the cells survived settling selection), we only transfer the bottom 50 µl of pellet biomass regardless of how many cells settle, creating an arms race that favours the fastest groups within the population. Our measurements of the number of cellular generations per day in Fig. 1a suggests about 3% of the cells survive from one day to the next on average. b, Both the microscopic (ancestral) and macroscopic (t600) snowflake yeast clusters have a life cycle, reproducing during the growth phase. c, Consistent with entanglement producing tough groups, macroscopic snowflake yeast release mostly microscopic propagules, possibly from branch tips at the exterior of the group, where the opportunity for entanglement is minimal. Despite the presence of many small propagules, most of the biomass in the population is contained within macroscopic clusters. The open circles represent the biomass-weighted mean size, which is the average sized group the mean cell finds itself in. A total of 14,313 clusters were analysed for the t0 time point, and 1,603 clusters were analysed for the t600 time point, across 0, 3, 6, 12, and 24-hour time points.
Extended Data Fig. 3 Cluster size and aspect ratio distribution.
a, Biomass distribution as a function of cluster size for the ancestral snowflake yeast (dotted line) and 600 day evolved populations of PA1-PA5. The ‘weighted mean size’ used in Figs. 1, 2 and 4 is the mean of the biomass distribution. b, Distribution of aspect ratios for ancestral and 600-day evolved populations of anaerobic snowflake yeast.
Extended Data Fig. 4 Cell shape is not substantially affected by location within macroscopic yeast.
a and b show cell volume and cell shape (aspect ratio) measured for 10 cells from the interior of a macroscopic cluster and 10 cells from the exterior of a cluster (measured in t600 macroscopic clusters). Average cell volume for exterior and interior are 110.8 µm3 and 113.1 µm3 (p = 0.88, t = 0.15 df = 17.55, Welch’s t-test), and average cell shape for exterior and interior are 2.9 and 2.8 (p = 0.51, t = 0.68, df = 14, Welch’s t-test). Individual measurements are marked as points, the mean and one standard deviation are indicated by the bar plot.
Extended Data Fig. 5 Parallel evolution of elongated cell shape across all five replicates of each PA population.
For each evolutionary time point and population, five different cells are shown (organized vertically from left to right: PA1 on the further left and PA5 on the further right in each box). Scale bar is 5 µm (under the ancestral cell). This is a more detailed version of the plot shown in Fig. 2c.
Extended Data Fig. 6 Macroscopic snowflake yeast are monoclonal, growing via permanent mother-daughter cellular bonds, not aggregation.
We co-cultured GFP and RFP-tagged genotypes of a macroscopic single strain isolate (PA2, strain ID: GOB1413-600) for 5 days, then imaged 70 clusters on a Nikon Ti-E. Shown are a composite of 11 individual clusters, which all remain entirely green or red. Individual clusters were compressed with a coverslip for imaging, resulting in their fragmentation into multiple modules. Scale bar (top-left) is 100 µm.
Extended Data Fig. 7 Quantifying entanglement via analysis of the topology and geometry of a snowflake yeast cluster.
a, We measured entanglement of individual components by fitting a convex hull around each component, and determining whether the other component overlaps with the space bounded by this convex hull. Here we just show the convex hull for the blue component, which overlaps with the red component. These components are thus part of the same entangled component. b, Using this approach, we identified the components within a sub-volume of a macroscopic snowflake yeast, and used a percolation analysis to examine the fraction of the biomass that is part of the same entangled component (coloured in red).
Extended Data Fig. 8 Cell stiffness and stress-strain curve.
a, Individual cells do not change their stiffness over 600 rounds of selection (average cell stiffness for the ancestor and t600 isolates are 0.019 and 0.020, respectively. p = 0.77, t = 0.31, df = 8, Welch’s unequal variances t-test). Single-cell stiffness values measured from atomic force microscopy (AFM) of individual cells. Error bars are one standard deviation. b, Macroscopic snowflake yeast fractured into small modules prior to compression do not show strain stiffening behaviour. Shown here is an AFM trajectory of cantilever deflection vs displacement for one t600 cluster that has been crushed into small, unentangled pieces.
Extended Data Fig. 9 Representative confocal images show chimeric clusters that are formed after growth in liquid culture followed by entanglement on agar plates.
a,b, Close-up view of clusters, highlighting the tangled red and green branches. Each frame is 139.64 x 139.64 x 34.50 µm in X, Y, and Z axes, respectively.
Extended Data Fig. 10 Dimensions of bud scars connecting cells in microscopic, ancestral (t0, grey) and macroscopic, evolved snowflake yeast clusters (PA2 t600, blue).
Macroscopic t600 yeast had 2.4x larger bud scar cross-sectional area (a; p < 0.001, t = 5.3, df = 24, t-test), 2.8x greater bud scar height (b; p < 0.001, t = 12.5, df = 24, t-test), resulting in bud scars with 5.8-fold greater volume (c; p < 0.001, t = 7.3, df = 24, t-test) than the microscopic ancestor. Error bars are one standard deviation. b, Histogram of pixel intensities for bud scars stained with chitin stain calcofluor white, isolated from ancestor (t0, microscopic) and t600 (macroscopic) bud scars. The t600 strain has a 27% higher mean fluorescence intensity, suggesting that they may have evolved moderately higher chitin density in the bud scar. c, The size differences in bud scars is readily visible. Shown are the side view of buds from the ancestor (left) and t600 evolved (right), imaged at the same microscope settings. The scale bar is 0.5 µm.
Supplementary File 1
Supplementary Table 1
A list of strain isolates, primers and plasmids used in the study.
Supplementary Video 1
Comparison of the ancestor and a population of macroscopic snowflake yeast (PA2 t600, on the right).
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Bozdag, G.O., Zamani-Dahaj, S.A., Day, T.C. et al. De novo evolution of macroscopic multicellularity. Nature 617, 747–754 (2023). https://doi.org/10.1038/s41586-023-06052-1
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