Elad Noor

Design and analysis of synthetic carbon fixation pathways

Carbon fixation is the process by which CO2 is incorporated into organic compounds. In modern agriculture in which water, light, and nutrients can be abundant, carbon fixation could become a significant growth-limiting factor. Hence, increasing the fixation rate is of major importance in the road toward sustainability in food and energy production. There have been recent attempts to improve the rate and specificity of Rubisco, the carboxylating enzyme operating in the Calvin–Benson cycle; however, they have achieved only limited success. Nature employs several alternative carbon fixation pathways, which prompted us to ask whether more efficient novel synthetic cycles could be devised. Using the entire repertoire of approximately 5,000 metabolic enzymes known to occur in nature, we computationally identified alternative carbon fixation pathways that combine existing metabolic building blocks from various organisms. We compared the natural and synthetic pathways based on physicochemical criteria that include kinetics, energetics, and topology. Our study suggests that some of the proposed synthetic pathways could have significant quantitative advantages over their natural counterparts, such as the overall kinetic rate. One such cycle, which is predicted to be two to three times faster than the Calvin–Benson cycle, employs the most effective carboxylating enzyme, phosphoenolpyruvate carboxylase, using the core of the naturally evolved C4 cycle. Although implementing such alternative cycles presents daunting challenges related to expression levels, activity, stability, localization, and regulation, we believe our findings suggest exciting avenues of exploration in the grand challenge of enhancing food and renewable fuel production via metabolic engineering and synthetic biology.

Varying environments can speed up evolution

Simulations of biological evolution, in which computers are used to evolve systems toward a goal, often require many generations to achieve even simple goals. It is therefore of interest to look for generic ways, compatible with natural conditions, in which evolution in simulations can be speeded. Here, we study the impact of temporally varying goals on the speed of evolution, defined as the number of generations needed for an initially random population to achieve a given goal. Using computer simulations, we find that evolution toward goals that change over time can, in certain cases, dramatically speed up evolution compared with evolution toward a fixed goal. The highest speedup is found under modularly varying goals, in which goals change over time such that each new goal shares some of the subproblems with the previous goal. The speedup increases with the complexity of the goal: the harder the problem, the larger the speedup. Modularly varying goals seem to push populations away from local fitness maxima, and guide them toward evolvable and modular solutions. This study suggests that varying environments might significantly contribute to the speed of natural evolution. In addition, it suggests a way to accelerate optimization algorithms and improve evolutionary approaches in engineering.

eQuilibrator—the biochemical thermodynamics calculator

The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like ‘how much Gibbs energy is released by ATP hydrolysis at pH 5?’ are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use.

Glycolytic strategy as a tradeoff between energy yield and protein cost

Contrary to the textbook portrayal of glycolysis as a single pathway conserved across all domains of life, not all sugar-consuming organisms use the canonical Embden–Meyerhoff–Parnass (EMP) glycolytic pathway. Prokaryotic glucose metabolism is particularly diverse, including several alternative glycolytic pathways, the most common of which is the Entner–Doudoroff (ED) pathway. The prevalence of the ED pathway is puzzling as it produces only one ATP per glucose—half as much as the EMP pathway. We argue that the diversity of prokaryotic glucose metabolism may reflect a tradeoff between a pathway’s energy (ATP) yield and the amount of enzymatic protein required to catalyze pathway flux. We introduce methods for analyzing pathways in terms of thermodynamics and kinetics and show that the ED pathway is expected to require several-fold less enzymatic protein to achieve the same glucose conversion rate as the EMP pathway. Through genomic analysis, we further show that prokaryotes use different glycolytic pathways depending on their energy supply. Specifically, energy-deprived anaerobes overwhelmingly rely upon the higher ATP yield of the EMP pathway, whereas the ED pathway is common among facultative anaerobes and even more common among aerobes. In addition to demonstrating how protein costs can explain the use of alternative metabolic strategies, this study illustrates a direct connection between an organism’s environment and the thermodynamic and biochemical properties of the metabolic pathways it employs.

Cross-species analysis traces adaptation of Rubisco toward optimality in a low-dimensional landscape

Rubisco (D-ribulose 1,5-bisphosphate carboxylase/oxygenase), probably the most abundant protein in the biosphere, performs an essential part in the process of carbon fixation through photosynthesis, thus facilitating life on earth. Despite the significant effect that Rubisco has on the fitness of plants and other photosynthetic organisms, this enzyme is known to have a low catalytic rate and a tendency to confuse its substrate, carbon dioxide, with oxygen. This apparent inefficiency is puzzling and raises questions regarding the roles of evolution versus biochemical constraints in shaping Rubisco. Here we examine these questions by analyzing the measured kinetic parameters of Rubisco from various organisms living in various environments. The analysis presented here suggests that the evolution of Rubisco is confined to an effectively one-dimensional landscape, which is manifested in simple power law correlations between its kinetic parameters. Within this one-dimensional landscape, which may represent biochemical and structural constraints, Rubisco appears to be tuned to the intracellular environment in which it resides such that the net photosynthesis rate is nearly optimal. Our analysis indicates that the specificity of Rubisco is not the main determinant of its efficiency but rather the trade-off between the carboxylation velocity and CO2 affinity. As a result, the presence of oxygen has only a moderate effect on the optimal performance of Rubisco, which is determined mostly by the local CO2 concentration. Rubisco appears as an experimentally testable example for the evolution of proteins subject both to strong selection pressure and to biochemical constraints that strongly confine the evolutionary plasticity to a low-dimensional landscape.

Wheat hybridization and polyploidization results in deregulation of small RNAs.

Speciation via interspecific or intergeneric hybridization and polyploidization triggers genomic responses involving genetic and epigenetic alterations. Such modifications may be induced by small RNAs, which affect key cellular processes, including gene expression, chromatin structure, cytosine methylation and transposable element (TE) activity. To date, the role of small RNAs in the context of wide hybridization and polyploidization has received little attention. In this work, we performed high-throughput sequencing of small RNAs of parental, intergeneric hybrid, and allopolyploid plants that mimic the genomic changes occurring during bread wheat speciation. We found that the percentage of small RNAs corresponding to miRNAs increased with ploidy level, while the percentage of siRNAs corresponding to TEs decreased. The abundance of most miRNA species was similar to midparent values in the hybrid, with some deviations, as seen in overrepresentation of miR168, in the allopolyploid. In contrast, the number of siRNAs corresponding to TEs strongly decreased upon allopolyploidization, but not upon hybridization. The reduction in corresponding siRNAs, together with decreased CpG methylation, as shown here for the Veju element, represent hallmarks of TE activation. TE-siRNA downregulation in the allopolyploid may contribute to genome destabilization at the initial stages of speciation. This phenomenon is reminiscent of hybrid dysgenesis in Drosophila.

Rethinking glycolysis: on the biochemical logic of metabolic pathways

Metabolic pathways may seem arbitrary and unnecessarily complex. In many cases, a chemist might devise a simpler route for the biochemical transformation, so why has nature chosen such complex solutions? In this review, we distill lessons from a century of metabolic research and introduce new observations suggesting that the intricate structure of metabolic pathways can be explained by a small set of biochemical principles. Using glycolysis as an example, we demonstrate how three key biochemical constraints--thermodynamic favorability, availability of enzymatic mechanisms and the physicochemical properties of pathway intermediates--eliminate otherwise plausible metabolic strategies. Considering these constraints, glycolysis contains no unnecessary steps and represents one of the very few pathway structures that meet cellular demands. The analysis presented here can be applied to metabolic engineering efforts for the rational design of pathways that produce a desired product while satisfying biochemical constraints.

Central Carbon Metabolism as a Minimal Biochemical Walk between Precursors for Biomass and Energy

Central carbon metabolism uses a complex series of enzymatic steps to convert sugars into metabolic precursors. These precursors are then used to generate the entire biomass of the cell. Are there simplifying principles that can explain the structure of such metabolic networks? Here we address this question by studying central carbon metabolism in E. coli. We use all known classes of enzymes that work on carbohydrates to generate rules for converting compounds and for generating possible paths between compounds. We find that central carbon metabolism is built as a minimal walk between the 12 precursor metabolites that form the basis for biomass and one precursor essential for the positive net ATP balance in glycolysis: every pair of consecutive precursors in the network is connected by the minimal number of enzymatic steps. Similarly, input sugars are converted into precursors by the shortest possible enzymatic paths. This suggests an optimality principle for the structure of central carbon metabolism. The present approach may be used to study other metabolic networks and to design new minimal pathways.

A survey of carbon fixation pathways through a quantitative lens

While the reductive pentose phosphate cycle is responsible for the fixation of most of the carbon in the biosphere, it has several natural substitutes. In fact, due to the characterization of three new carbon fixation pathways in the last decade, the diversity of known metabolic solutions for autotrophic growth has doubled. In this review, the different pathways are analysed and compared according to various criteria, trying to connect each of the different metabolic alternatives to suitable environments or metabolic goals. The different roles of carbon fixation are discussed; in addition to sustaining autotrophic growth it can also be used for energy conservation and as an electron sink for the recycling of reduced electron carriers. Our main focus in this review is on thermodynamic and kinetic aspects, including thermodynamically challenging reactions, the ATP requirement of each pathway, energetic constraints on carbon fixation, and factors that are expected to limit the rate of the pathways. Finally, possible metabolic structures of yet unknown carbon fixation pathways are suggested and discussed.

Spanning high-dimensional expression space using ribosome-binding site combinatorics

Protein levels are a dominant factor shaping natural and synthetic biological systems. Although proper functioning of metabolic pathways relies on precise control of enzyme levels, the experimental ability to balance the levels of many genes in parallel is a major outstanding challenge. Here, we introduce a rapid and modular method to span the expression space of several proteins in parallel. By combinatorially pairing genes with a compact set of ribosome-binding sites, we modulate protein abundance by several orders of magnitude. We demonstrate our strategy by using a synthetic operon containing fluorescent proteins to span a 3D color space. Using the same approach, we modulate a recombinant carotenoid biosynthesis pathway in Escherichia coli to reveal a diversity of phenotypes, each characterized by a distinct carotenoid accumulation profile. In a single combinatorial assembly, we achieve a yield of the industrially valuable compound astaxanthin 4-fold higher than previously reported. The methodology presented here provides an efficient tool for exploring a high-dimensional expression space to locate desirable phenotypes.