Modeling the Evolution of C₄ Photosynthesis

Abstract

The prediction and verification of adaptive trajectories on macroevolutionary timescales have rarely been achieved for complex biological systems. Employing a model linking biological information at multiple scales, Heckmann et al. simulate likely sequences of evolutionary changes from C₃ to C₄ photosynthesis biochemistry.

The evolution of C₄ photosynthesis enabled plants to colonize new environments and required a fundamental transition in the way CO₂ is concentrated and managed for carbon assimilation into sugars. Unlike C₃ photosynthesis, which takes place within a single cell type (mesophyll, M) and is most energetically efficient in temperate climates, C₄ photosynthesis maximizes efficiency in hot, dry climates by concentrating CO₂ in a second cell type (bundle sheath, BS) (Figure 1). To understand the evolution of photosynthesis, reconstructing a trajectory leading from C₃ to C₄ photosynthesis requires a multiscale, systems approach—a synthesis of biology on many scales, from biochemistry to physiology to phylogeny. In this issue of Cell, Heckmann et al. (2013) present a model that seeks to explain the evolution of C₄ photosynthesis by linking multiple disparate data types. They combine empirical biochemical dynamics, metabolic fluxes, and plant anatomical diversity into a model that predicts the evolution of C₄ photosynthesis and recapitulates the evolutionary trajectory alluded to by extant C₃-C₄ intermediate species across three genera (Flaveria, Panicum, and Moricandia). This cross-cutting model exemplifies a major goal of systems biology and will lead to a much deeper understanding of how evolution across fitness landscapes emerges as a consequence of myriad molecular-, biochemical-, and physiological-level processes. Moreover, this work reinforces the notion that greater command of properties underlying CO₂-efficient and high-yield C₄ photosynthesis is pivotal for improving agricultural productivity.

Figure 1. A Space Continuum Depicting the Orders of Magnitude Encompassed by the C4 Photosynthesis Evolution Model.

Evolution and adaptation are manifest at all spatial levels of scale. Biological information on all levels is complex, but the challenge comes with integrating across all levels of scale. To illustrate these scales, starting from the left, the RuBisCO molecule (Protein Data Bank: 1UZD) represents molecular-level processes. Next, biochemical and metabolic pathways are represented by M and BS cells from C₄ (top half) and C₃ (bottom half) plants. CO₂ is concentrated in the BS cells of C₄, but not C₃ plants. The third circle represents C₄ and C₃ leaf tissue structures; C₄ leaves have veins (white) surrounded by photosynthetic BS cells (green) and M cells (gray), whereas C₃ veins are surrounded by M cells with no photosynthetic BS cells. Finally, sugar cane (top) and wheat (bottom) are examples of C₄ and C₃ plants, respectively. As more information is integrated, complexity increases. Dark ovals where levels of scale overlap illustrate this increasing complexity. The span between dotted lines symbolizes the variability in C₃-C₄ evolutionary trajectories due to environmental selection pressures. The figure was drawn by Allison Kudla, PhD.

C₄ plants account for 25% of terrestrial photosynthesis (Edwards et al., 2010) and evolved to counteract the wasteful process of photorespiration in a high-O₂-containing atmosphere. C₄ plants evolved independently in more than 60 angiosperms from different ancestral C₃ plants to allow for a CO₂-concentrating mechanism at the active site of RuBisCO (ribulose1,5 bisphosphate carboxylase/oxygenase) and thus increase the carboxylation/oxygenation ratio. How and why C₄ photosynthesis evolved repeatedly are important but unanswered questions.

To answer these questions, the authors mapped the fitness landscape on which C₃-C₄ evolution took place by inserting fitness estimates into a population genetic framework and by exploring the probability distribution of evolutionary trajectories on a macroevolutionary timescale. Heckmann et al. (2013) demonstrate that C₄ evolution repeats itself in a predictable manner. Their model supports a previous hypothesis that biochemical changes in the evolution from C₃ to C₄ happen in modules; for instance, a photorespiratory pump is established, and the site of photorespiration shifts from the M to the BS cells, followed by a shift of RuBisCO to the BS (Sage et al., 2012). The model accounts for known properties of RuBisCO (activity, turnover), phosphoenol pyruvate carboxylase (PEPC) (activity, Michaelis-Menton constant), and the cell’s geometry and cell wall properties.

These modular changes toward C₄ photosynthesis do not appear to occur spontaneously in all plant lineages, which is reflected in the model. C₃ ancestors of C₄ plant lineages had a head start in the form of a pre-C₄ “potentiating anatomy.” This pre-C₄ morphology is characterized by reduced M cells, more prominent BS cells, and C₄ protein orthologs. Given that C4 evolution is historically contingent on this potentiating anatomy, the model predicts a constant evolutionary march from C₃, through C₃-C₄ intermediate, to C₄ photosynthesis phenotypes. This predicted evolutionary trajectory was further validated by experimental data from three genera of extant plants with C₃-C₄ intermediate photosynthesis.

Although the predictive power afforded by this model is impressive, it is equally remarkable to consider that a biological process like photosynthesis can be accurately reduced to six biochemical parameters (von Caemmerer, 2000). As with all models, this work relies on a number of key assumptions that also introduce important limitations. First, omitted biological details limit the relevance of the model for plants in real time. Many other processes govern CO₂ assimilation, including the availability of reducing equivalents from the light reactions, as well as overall growth conditions and sugar utilization rates following Calvin cycle reactions. PEPC limitation and Michaelis-Menten kinetics may not hold universally true. Second, the model is limited to the evolutionary states bounded by pre-C₄ C₃ photosynthesis and C₄ photosynthesis. These boundaries represent a small subset of the many lineages with evolved CO₂-concentrating mechanisms; unicellular algae acquired this trait before vascular plants evolved (Raven et al., 2008). Thus, the model cannot be extended to C₃ plants with different or no potentiating anatomy or to intermediate C₃-C₄ plants outside the genera examined here. Plant photosynthetic diversity dwarfs any model’s capacity to capture it, at least at this point in time. Third, and perhaps most importantly, environmental context is missing from this model. Adaptation resulting from environment-responsive physiology mediated by global regulatory networks and mutations is also lacking.

As an example of environmental ambivalence in the model, the parameters reflect conditions at a constant 25°C, despite the fact that the C₄ mode evolved to improve efficiency and CO₂ capture in hot, dry conditions. Interesting questions emerge, such as what climatic changes occurred during the many convergent C₄ evolutionary events? Could the environment select for additional fitnessenhancing mutations that would have changed the presented route through the fitness landscape? Are the C₃-C₄ intermediates actually “dead ends” in which a suddenly cooler environment made the increased energetic cost of pumping CO₂ into BS cells disadvantageous compared with C₃-like strategies? To further emphasize the criticality of environmental context, we note that the environment limits the possibility space of evolutionary trajectories just as potentiating anatomy and mutations do. Heckmann et al. (2013) discuss the importance of historical contingency and potentiating anatomy (or evolutionary head starts) for constraining evolutionary trajectories. A property largely explored in long-term evolution experiments with microbes, historical contingency is the environment-dependent accessibility of certain genotypes in a fitness landscape. These genotypes in the landscape are inaccessible unless one or more specific (potentiating) mutations arise in advance (Beaumont et al., 2009; Blount et al., 2008). Much like the potentiating pre-C₄ anatomy, these mutations increase the probability that a given genotype and phenotype will arise, even for complex phenotypes like photosynthesis or a novel metabolic regime (i.e., citrate synthesis). Evolution, however, is clearly dependent upon the environment. Environmental differences can thwart certain trajectories and render genotypes inaccessible, just as a lack of potentiating mutations can (Lindsey et al., 2013). This model thus leaves us with additional and exciting questions, such as in what environmental contexts has this trajectory prevailed? Would measured biochemical parameters in other C₃-C₄ intermediate plants recapitulate the model as Flaveria spp. have?

Despite its limitations, this study underscores how complex phenomena (e.g., evolution of a new carbon-concentrating strategy) can emerge from simple rules that influence biology at many levels of scale (Figure 1). The power in this approach lies in a model that links complex biological information spanning multiple scales (molecular, biochemical, morphological, and phylogenetic) to reveal an emerging pattern that is greater than the sum of the parts. Simplified models are the cornerstone of predicting dynamics of complex systems. Nonetheless, oversimplification and too many assumptions pave over the distinguishing ability of biological systems to adapt and respond to environmental change. Managing the tradeoff between model simplicity and completeness is a major challenge for systems biology, and we are confident that further iterations of this foundational model will enhance this balance.