Search

The history of Earth’s carbon cycle reflects trends in atmospheric composition convolved with the evolution of photosynthesis. Fortunately, key parts of the carbon cycle have been recorded in the carbon isotope ratios of sedimentary rocks. The dominant model used to interpret this record as a proxy for ancient atmospheric CO 2 is based on carbon isotope fractionations of modern photoautotrophs, and longstanding questions remain about how their evolution might have impacted the record. Therefore, we measured both biomass (ε p ) and enzymatic (ε Rubisco ) carbon isotope fractionations of a cyanobacterial strain ( Synechococcus elongatus PCC 7942) solely expressing a putative ancestral Form 1B rubisco dating to ≫1 Ga. This strain, nicknamed ANC, grows in ambient pCO 2 and displays larger ε p values than WT, despite having a much smaller ε Rubisco (17.23 ± 0.61‰ vs. 25.18 ± 0.31‰, respectively). Surprisingly, ANC ε p exceeded ANC ε Rubisco in all conditions tested, contradicting prevailing models of cyanobacterial carbon isotope fractionation. Such models can be rectified by introducing additional isotopic fractionation associated with powered inorganic carbon uptake mechanisms present in Cyanobacteria, but this amendment hinders the ability to accurately estimate historical pCO 2 from geological data. Understanding the evolution of rubisco and the CO 2 concentrating mechanism is therefore critical for interpreting the carbon isotope record, and fluctuations in the record may reflect the evolving efficiency of carbon fixing metabolisms in addition to changes in atmospheric CO 2 .

Cyanobacteria rely on CO 2 -concentrating mechanisms (CCMs) to grow in today’s atmosphere (0.04% CO 2 ). These complex physiological adaptations require ≈15 genes to produce two types of protein complexes: inorganic carbon (Ci) transporters and 100+ nm carboxysome compartments that encapsulate rubisco with a carbonic anhydrase (CA) enzyme. Mutations disrupting any of these genes prohibit growth in ambient air. If any plausible ancestral form—i.e., lacking a single gene—cannot grow, how did the CCM evolve? Here, we test the hypothesis that evolution of the bacterial CCM was “catalyzed” by historically high CO 2 levels that decreased over geologic time. Using an E. coli reconstitution of a bacterial CCM, we constructed strains lacking one or more CCM components and evaluated their growth across CO 2 concentrations. We expected these experiments to demonstrate the importance of the carboxysome. Instead, we found that partial CCMs expressing CA or Ci uptake genes grew better than controls in intermediate CO 2 levels (≈1%) and observed similar phenotypes in two autotrophic bacteria, Halothiobacillus neapolitanus and Cupriavidus necator . To understand how CA and Ci uptake improve growth, we model autotrophy as colimited by CO 2 and HCO 3 − , as both are required to produce biomass. Our experiments and model delineated a viable trajectory for CCM evolution where decreasing atmospheric CO 2 induces an HCO 3 − deficiency that is alleviated by acquisition of CA or Ci uptake, thereby enabling the emergence of a modern CCM. This work underscores the importance of considering physiology and environmental context when studying the evolution of biological complexity.

From a metabolic perspective, molecular oxygen (O

Enzymes are well known for their catalytic abilities, some even reaching "catalytic perfection" in the sense that the reaction they catalyze has reached the physical bound of the diffusion rate. However, our growing understanding of enzyme superfamilies has revealed that only some share a catalytic chemistry while others share a substrate-handle binding motif, for example, for a particular phosphate group. This suggests that some families emerged through a "substrate-handle-binding-first" mechanism ("binding-first" for brevity) instead of "chemistry-first" and we are, therefore, left to wonder what the role of non-catalytic binders might have been during enzyme evolution. In the last of their eight seminal, back-to-back articles from 1976, John Albery and Jeremy Knowles addressed the question of enzyme evolution by arguing that the simplest mode of enzyme evolution is what they defined as "uniform binding" (parallel stabilization of all enzyme-bound states to the same degree). Indeed, we show that a uniform-binding proto-catalyst can accelerate a reaction, but only when catalysis is already present, that is, when the transition state is already stabilized to some degree. Thus, we sought an alternative explanation for the cases where substrate-handle-binding preceded any involvement of a catalyst. We find that evolutionary starting points that exhibit negative catalysis can redirect the reaction's course to a preferred product without need for rate acceleration or product release; that is, if they do not stabilize, or even destabilize, the transition state corresponding to an undesired product. Such a mechanism might explain the emergence of "binding-first" enzyme families like the aldolase superfamily.

The history of Earth’s carbon cycle reflects trends in atmospheric composition convolved with the evolution of photosynthesis. Fortunately, key parts of the carbon cycle have been recorded in the carbon isotope ratios of sedimentary rocks. The dominant model used to interpret this record as a proxy for ancient atmospheric CO2is based on carbon isotope fractionations of modern photoautotrophs, and longstanding questions remain about how their evolution might have impacted the record. We tested the intersection of environment and evolution by measuring both biomass (εp) and enzymatic (εRubisco) carbon isotope fractionations of a cyanobacterial strain (Synechococcus elongatusPCC 7942) solely expressing a putative ancestral Form 1B rubisco dating to ≫1 Ga. This strain, nicknamed ANC, grows in ambient pCO2and displays larger εpvalues than WT, despite having a much smaller εRubisco(17.23 ± 0.61‰ vs. 25.18 ± 0.31‰ respectively). Measuring both enzymatic and biomass fractionation revealed a surprising result—ANC εpexceeded ANC εRubiscoin all conditions tested, contradicting prevailing models of cyanobacterial carbon isotope fractionation. However, these models were corrected by accounting for cyanobacterial physiology, notably the CO2concentrating mechanism (CCM). Our model suggested that additional fractionating processes like powered inorganic carbon uptake systems contribute to εp, and this effect is exacerbated in ANC. Understanding the evolution of rubisco and the CCM is therefore critical for interpreting the carbon isotope record. Large fluctuations in that record may reflect the evolving efficiency of carbon fixing metabolisms in addition to changes in atmospheric CO2.Significance StatementEarth scientists rely on chemical fossils like the carbon isotope record to derive ancient atmospheric CO2concentrations, but interpretation of this record is calibrated using modern organisms. We tested this assumption by measuring the carbon isotope fractionation of a reconstructed ancestral rubisco enzyme (>1 billion years old)in vivoandin vitro. Our results contradicted prevailing models of carbon flow in Cyanobacteria, but our data could be rationalized if light-driven uptake of CO2is taken into account. Our study showed that the carbon isotope record tracks both the evolution of photosynthesis physiology as well as changes in atmospheric CO2, highlighting the value of considering both evolution and physiology for comparative biological approaches to understanding Earth’s history.

Cyanobacteria rely on CO2 concentrating mechanisms (CCMs) that depend on ≈15 genes to produce two protein complexes: an inorganic carbon (Ci) transporter and a 100+ nm carboxysome compartment that encapsulates rubisco with a carbonic anhydrase (CA) enzyme. Mutations disrupting CCM components prohibit growth in today’s atmosphere (0.04% CO2), indicating that CCMs evolved to cope with declining environmental CO2. Indeed, geochemical data and models indicate that atmospheric CO2 has been generally decreasing from high concentrations over the last ≈3.5 billion years. We used a synthetic reconstitution of a bacterial CCM in E. coli to study the co-evolution of CCMs with atmospheric CO2. We constructed strains expressing putative ancestors of modern CCMs — strains lacking one or more CCM components — and evaluated their growth in a variety of CO2 concentrations. Partial forms expressing CA or Ci uptake genes grew better than controls in intermediate CO2 levels (≈1%); we observed similar phenotypes in genetic studies of two autotrophic bacteria, H. neapolitanus and C. necator. To explain how partial CCMs improve growth, we advance a model of co-limitation of autotrophic growth by CO2 and HCO3-, as both are required to produce biomass. Our model and results delineated a viable trajectory for bacterial CCM evolution where decreasing atmospheric CO2 induces an HCO3- deficiency that is alleviated by acquisition of CAs or Ci uptake genes, thereby enabling the emergence of a modern CCM. This work underscores the importance of considering physiology and environmental context when studying the evolution of biological complexity.SignificanceThe greenhouse gas content of the ancient atmosphere is estimated using models and measurements of geochemical proxies. Some inferred high ancient CO2 levels using models of biological CO2 fixation to interpret the C isotopes found in preserved organic matter. Others argued that elevated CO2 could reconcile a faint young Sun with evidence for liquid water on Earth. We took a complementary “synthetic biological” approach to understanding the composition of the ancient atmosphere by studying present-day bacteria engineered to resemble ancient autotrophs. By showing that it is simpler to rationalize the emergence of modern bacterial autotrophs if CO2 was once high, these investigations provided independent evidence for the view that CO2 concentrations were significantly elevated in the atmosphere of early Earth.

Making sense of the metabolism of microbial communities is a daunting task. Using denitrification as a model metabolism, a new paper shows that the rate of denitrification can often be predicted from genome contents, and dynamical models can be composed to predict denitrification rates of communities of two to five species.