It has been suggested that a deep memory of early life is hidden in the architecture of metabolic networks, whose reactions could have been catalyzed by small molecules or minerals before genetically encoded enzymes. A major challenge in unravelling these early steps is assessing the plausibility of a connected, thermodynamically consistent proto-metabolism under different geochemical conditions, which are still surrounded by high uncertainty. Here we combine network-based algorithms with physico-chemical constraints on chemical reaction networks to systematically show how different combinations of parameters (temperature, pH, redox potential and availability of molecular precursors) could have affected the evolution of a proto-metabolism. Our analysis of possible trajectories indicates that a subset of boundary conditions converges to an organo-sulfur-based proto-metabolic network fuelled by a thioester- and redox-driven variant of the reductive tricarboxylic acid cycle that is capable of producing lipids and keto acids. Surprisingly, environmental sources of fixed nitrogen and low-potential electron donors are not necessary for the earliest phases of biochemical evolution. We use one of these networks to build a steady-state dynamical metabolic model of a protocell, and find that different combinations of carbon sources and electron donors can support the continuous production of a minimal ancient ‘biomass’ composed of putative early biopolymers and fatty acids.
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All data presented in this paper have been deposited in a public repository and can be accessed at https://github.com/segrelab/BoundaryConditionsForAncientMetabolism.
All code presented in this paper can be accessed at https://github.com/segrelab/BoundaryConditionsForAncientMetabolism.
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We thank all members of the Segrè Laboratory for helpful discussions. We acknowledge support provided by the Directorates for Biological Sciences and Geosciences at the National Science Foundation and NASA (agreement nos. 80NSSC17K0295, 80NSSC17K0296 and 1724150) issued through the Astrobiology Programme of the Science Mission Directorate; the National Science Foundation (grant no. 1457695, NSFOCE-BSF 1635070); the Human Frontiers Science Programme (grant no. RGP0020/2016) and the Boston University Hariri Institute for Computing and Computational Science and Engineering.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Enzymes in thioester-driven protometabolism are depleted in nitrogenous compounds.
(a) We classified reactions in KEGG as being plausibly pre-enzymatic (PPE) reactions if they (i) could proceed spontaneously, (ii) were associated with enzymes that contain at-least one iron–sulfur cluster or (iii) were associated with an enzyme that relied on atleast one metal (Ni, Co, Cu, Mg, Mn, Mo, Zn, Fe, W) cofactor. (b) For all scenarios resulting in expansion of more than 100 metabolites (n = 144) we computed the fraction of PPE-reactions amongst the pre-ammonia reactions (x-axis) and post-ammonia reactions (y-axis). The frequency of PPE-reactions in the pre-ammonia reaction set was on average higher than the frequency of PPE-reactions in the post-ammonia reaction set (one-tailed Wilcoxon signed-rank test: P < 10-19). (c) We identified KEGG reactions that were dependent on at-least one of the following nitrogen-containing coenzymes: flavin, biotin, thiamine pyrophosphate (TPP) pyridoxal phosphate (PLP), haem, pterin or cobalamin. (d) We compute the fraction of pre- and post- ammonia reactions associated with nitrogen-containing coenzymes in the KEGG database, and found that a much higher proportion of post-ammonia reactions were dependent on these coenzymes relative to pre-ammonia reactions (one-tailed Wilcoxon signed-rank test: P < 10-24). (e) We parsed the catalytic active site database72 to find entries associated with pre and post-ammonia reactions, and compute the fraction of entries associated with amino acids with nitrogen-containing side-chains (Q,N,W,H,K,R). (f) For each scenario, the fraction of active sites with nitrogen-containing amino acids was significantly higher for post-ammonia reactions relative to pre-ammonia reactions one-tailed Wilcoxon signed-rank test: P < 10-24).
Extended Data Fig. 2 Enzymes catalyzing reactions before the addition of ammonia are not depleted in nitrogen-containing amino acids relative to enzymes added after ammonia.
To see if the amino acid biases in active sites of enzymes catalyzing reactions added to the network without ammonia (see Extended Data Fig. 1e, f) is confounded due to evolutionary selection for reduced nitrogen in these enzymes, we computed the fraction of nitrogen side-chains in enzymes in pre-ammonia reactions (x-axis) and in enzymes in post-ammonia reactions (y-axis). We found that enzymes in the pre-ammonia networks did not have significantly less nitrogen usage compared to enzymes in post-ammonia reactions (one-tailed Wilcoxon signed-rank test: P = 1).
(a) We grouped the n = 672 geochemical scenarios into whether a source of fixed carbon and thiols was provided in the seed set. We then plotted the empirical cumulative distributions for each group of scenarios. Notably, when thiols and fixed carbon are not supplied in the seed set, the networks are always below 100 metabolites, indicating that expansion is prohibited without either fixed carbon or thiols in the seed set. (b) We determined what geochemical parameters (x-axis) were essential for the production of important biomolecules (y-axis). For example, palmitate, a long-chain fatty acid, is producible only if thiols and reductant below 400 mV is provided in the seed set.
Extended Data Fig. 4 Network expansion with different combinations of carbon sources, thiols, generic reductants and generic oxidants.
We performed network expansion using a seed set with both a generic reductant at a fixed potential (x-axis) and a generic oxidant at a fixed potential (y-axis) with (a) no thiols or fixed carbon, (b) thiols and no fixed carbon, (c) no thiols and fixed carbon, and (d) both thiols and fixed carbon. The colour indicates the size (number of metabolites) in the final expanded network. Interestingly, a strong driving force provided by a strong oxidant ( > 0 mV) never sufficiently compensated for the weak driving force provided by a weak reductant ( > 0 mV), suggesting that oxidants have little influence on enabling expansion beyond 20 metabolites. The only conditions that led to an expansion that was greater than 20 metabolites with a weak electron donor was when the oxidant was also weak (-200 to -600 mV). We hypothesized that this was due to the ability of thiols or reduced carbon species to reduce the oxidant, enabling the production of a strong reductant. Indeed, when we removed all thiol to disulfide reactions using the generic redox system, expansion was blocked (inset).
Extended Data Fig. 5 Reduction potential of NAD(P)/FAD substitutes influences the size of expanded networks.
We plotted the size (number of metabolites, y-axis) of expanded networks as a function of reduction potential of NAD(P)/FAD substitutes (x-axis) for different physico-chemical conditions with (a) no fixed carbon or thiols, (b) fixed carbon and no thiols, (c) thiols and no fixed carbon, and (d) both fixed carbon and thiols. (e) We plot the range of physiologically feasible reduction potentials for classes of redox systems potentially relevant for early protometabolic systems, showing that dithiol/disulfide redox systems could potentially have enabled expansion under a variety of conditions.
(a) In extant biochemistry, keto acids are converted to amino acids using transamination or reductive amination reaction mechanisms, which are then polymerized using a phosphate or thioester-coupled mechanism to make polypeptides. (b) If prebiotic environments did not have a source of fixed nitrogen, then keto acids could have been reduced to -hydroxy acids, which could then be polymerized into polyesters either with4 or without55 thioester bond breaking.
Supporting information text.
Excel tables containing all the network expansion data used to generate Figs. 1–4 and Extended Data Figs. 1–5.
Cytoscape file containing the data for the interactive visualization of the network expansion and its variability.
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Goldford, J.E., Hartman, H., Marsland, R. et al. Environmental boundary conditions for the origin of life converge to an organo-sulfur metabolism. Nat Ecol Evol 3, 1715–1724 (2019). https://doi.org/10.1038/s41559-019-1018-8
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