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The role of mitochondrial energetics in the origin and diversification of eukaryotes

Abstract

The origin of eukaryotic cell size and complexity is often thought to have required an energy excess supplied by mitochondria. Recent observations show energy demands to scale continuously with cell volume, suggesting that eukaryotes do not have higher energetic capacity. However, respiratory membrane area scales superlinearly with the cell surface area. Furthermore, the consequences of the contrasting genomic architectures between prokaryotes and eukaryotes have not been precisely quantified. Here, we investigated (1) the factors that affect the volumes at which prokaryotes become surface area-constrained, (2) the amount of energy divested to DNA due to contrasting genomic architectures and (3) the costs and benefits of respiring symbionts. Our analyses suggest that prokaryotes are not surface area-constrained at volumes of 100‒103 µm3, the genomic architecture of extant eukaryotes is only slightly advantageous at genomes sizes of 106‒107 base pairs and a larger host cell may have derived a greater advantage (lower cost) from harbouring ATP-producing symbionts. This suggests that eukaryotes first evolved without the need for mitochondria since these ranges hypothetically encompass the last eukaryotic common ancestor and its relatives. Our analyses also show that larger and faster-dividing prokaryotes would have a shortage of respiratory membrane area and divest more energy into DNA. Thus, we argue that although mitochondria may not have been required by the first eukaryotes, eukaryote diversification was ultimately dependent on mitochondria.

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Fig. 1: Three different possibilities for energetic scaling across cell volume for prokaryotes and eukaryotes.
Fig. 2: Cell volumes, genome sizes and gene numbers for prokaryotes and eukaryotes.
Fig. 3: Factors that affect the volumes at which mitochondrion-less cells become constrained by their surface.
Fig. 4: Graphical representation of contrasting genomic architectures in prokaryotes and eukaryotes.
Fig. 5: The impact of genomic architecture on energy allocation in cells.
Fig. 6: Costs and benefits of harbouring ATP-exporting respiring symbionts.

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Data availability

All data are available in the Supplementary Information and Source Data Fig. 2. Source data are provided with this paper.

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Acknowledgements

We thank M. Lynch for comments on an early draft of this manuscript. S.A.M.-G. is supported by an EMBO Postdoctoral Fellowship (ALTF 21-2020). P.E.S. is supported by the Moore–Simons Project on the Origin of the Eukaryotic Cell, Simons Foundation 735927 (https://doi.org/10.46714/735927), the National Institutes of Health, R35-GM122566-01 and the National Science Foundation, DBI-2119963.

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P.S. and S.A.M.-G. conceptualized the study and devised the methodology. They carried out the validation, formal analysis and investigation, curated the data, wrote the original manuscript draft, reviewed and edited it, and visualized the data.

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Correspondence to Paul E. Schavemaker or Sergio A. Muñoz-Gómez.

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Nature Ecology and Evolution thanks István Zachar and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Comparing the results of metabolic rate calculations to data.

The blue points are empirically determined metabolic rates for various prokaryotic and eukaryotic species, obtained from Chiyomaru and Takemoto (2020) (units were converted by assuming that 1 mol ATP releases 50 kJ of energy). The red points are metabolic rates calculated with: \(R = \left( {f_d\alpha V^{0.97}/t_d} \right) + \beta V^{0.88}\), with the values for cell volumes and cell division times, for both prokaryotes and eukaryotes, obtained from Lynch and Marinov (2015). The solid line is a fit to the data: y = 2.0 × 105 x1, and the dashed line is a fit to the calculated points: y = 4.4 × 105 x0.85.

Extended Data Fig. 2 The shape factor (\({{{\boldsymbol{S}}}}\)) as a function of the ratio between cell length and width.

When this ratio is one, the cell is a sphere, and when this ratio is < 1 or >1, the cell is flattened into an oblate or prolate spheroid, respectively. The shape factor is calculated from Eq. S17.

Extended Data Fig. 3 Prediction of the mitochondrial inner membrane surface area.

a. The inner mitochondrial surface area as a function of cell surface area. Empirically determined inner mitochondrial membrane areas were obtained from Lynch and Marinov (2017) (blue points). The inner mitochondrial membrane area was calculated (red points) with: \((\left( {f_d\alpha V^{0.97}/t_d} \right) + \beta V^{0.88})/r \times A_r \times 2.5\), using cell volumes and cell division times for eukaryotic species obtained from Lynch and Marinov (2015). The factor 2.5 was included to account for the lipids that support the membrane (Lindén et al., 2012). Note that for the calculation it is assumed that the inner mitochondrial membrane only houses respiratory proteins. The solid line is a fit to the data: y = 0.40 x1.30. The dashed line is a fit to the model: y = 0.030 x1.32. Here, the value of \(A_r\) is the one for E. coli, which is listed in Table S1. b. As for A except that the value of \(A_r\) used for the model calculations, which is dependent on both cross-sectional surface areas and stoichiometries of respiratory enzymes, is taken from a eukaryote (bovine) (Schlame, 2021), yielding a closer correspondence between data and model.

Extended Data Fig. 4 The effect of varying mitochondrial genome copy number, mitochondrial genome size, and cell division times on the eukaryotic advantage over prokaryotes.

Plots are generated from Eqs. 46 with \(V_{gserv}\) = 1 µm3 and \(f_{mt}\) = 0.044. a, b. Varying mitochondrial genome number and size. For the blue lines, \(L_{mtDNA} =\) 104 bp and \(n_{mtDNA} =\) 1 per µm3 of mitochondrial volume. For the red lines \(L_{mtDNA} =\) 7×104 bp and \(n_{mtDNA} =\) 100 per µm3 of mitochondrial volume. Cell division time, \(t_d\) = 0. In some cases, red and blue overlap. a. For the dotted lines \(L_{prok} = L_{euk} =\) 108, for the dashed lines \(L_{prok} = L_{euk} =\) 107, and for the solid lines \(L_{prok} = L_{euk} =\) 106. b. For the dotted lines V = 106 µm3, for the dashed lines V = 103 µm3, and for the solid lines V = 1.1 µm3. c, d. Varying cell division time, \(t_d\). For all lines \(L_{mtDNA}\) = 104 bp and \(n_{mtDNA}\) = 1 per µm3. For the blue lines \(t_d\) = 0, for the red lines \(t_d\) = 10 h, and for the black lines \(t_d\) = 100 h. c. For the dotted lines \(L_{prok} = L_{euk} =\) 108, for the dashed lines \(L_{prok} = L_{euk} =\) 107, and for the solid lines \(L_{prok} = L_{euk} =\) 106. d. For the dotted lines V = 106 µm3, for the dashed lines V = 103 µm3, and for the solid lines V = 1.1 µm3.

Extended Data Fig. 5 The amount of cellular ATP that remains after DNA synthesis in prokaryotes and either modern or ancestral eukaryotes.

Plots are generated from Eqs. 5 and 7 with \(V_{gserv} =\) 1 µm3, \(L_{prok} =\) 107 bp, and \(f_{mt} = 0.3\). a. Amount of ATP left after DNA synthesis for prokaryotes and modern eukaryotes with a small mitochondrial genome size (\(L_{mtDNA} =\) 7×104 bp) and volume fraction (\(f_{mt} = 0.044\)), a main (nuclear) genome that does not scale with cell volume, and a low mitochondrial genome copy number per unit volume (\(n_{mtDNA} =\) 1). b. As above but with \(n_{mtDNA} =\) 10. c. Amount of ATP left after DNA synthesis for prokaryotes and ancestral proto-eukaryotes with a large mitochondrial genome size (\(L_{mtDNA} =\) 107 bp) and volume fraction (\(f_{mt} = 0.3\)), a main (nuclear) genome that does not scale with cell volume, and a low mitochondrial genome copy number per unit volume (\(n_{mtDNA} =\) 1); this model and parameter set best reflect an ancestral eukaryote as predicted by some mitochondrion-late scenarios. d. As above but with \(n_{mtDNA} =\) 3. e. Amount of ATP left after DNA synthesis for prokaryotes and ancestral eukaryotes with a large mitochondrial genome size (\(L_{mtDNA} =\) 107 bp) and volume fraction (\(f_{mt} = 0.3\)), a main genome size that scales with cell volume, and a low mitochondrial genome copy number per unit volume (\(n_{mtDNA} =\) 1); this model and parameter set best reflect an ancestral eukaryotes as predicted by mitochondrion-early scenarios. f. As above but with \(n_{mtDNA} =\) 3.

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Source Data Fig. 2

Database of cell volume, genome sizes and gene numbers for prokaryotes and eukaryotes.

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Schavemaker, P.E., Muñoz-Gómez, S.A. The role of mitochondrial energetics in the origin and diversification of eukaryotes. Nat Ecol Evol 6, 1307–1317 (2022). https://doi.org/10.1038/s41559-022-01833-9

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