Flux Control in Glycolysis Varies Across the Tree of Life

PEMPS: a phylogenetic software tool to model the evolution of metabolic pathways

BACKGROUND

Metabolic pathways support the enzyme flux that converts input chemicals into energy and cellular building blocks. With a constant rate of input, steady-state flux is achieved when metabolite concentrations and reaction rates remain constant over time. Individual genes undergo mutation, while selection acts on higher level functions of the pathway, such as steady-state flux where applicable. Modeling the evolution of metabolic pathways through mechanistic sets of ordinary differential equations is a piece of the genotype-phenotype map model for interpreting genetic variation and inter-specific differences. Such models can generate distinct compensatory changes and adaptive changes from directional selection, indicating single nucleotide polymorphisms and fixed differences that could affect phenotype. If used for inference, this would ultimately enable detection of selection on metabolic pathways as well as inference of ancestral states for metabolic pathway function.

RESULTS

A software tool for simulating the evolution of metabolic pathways based upon underlying biochemistry, phylogenetics, and evolutionary considerations is presented. The Python program, Phylogenetic Evolution of Metabolic Pathway Simulator (PEMPS), implements a mutation-selection framework to simulate the evolution of the pathway over a phylogeny by interfacing with COPASI to calculate the steady-state flux of the metabolic network, introducing mutations as alterations in parameter values according to a model, and calculating a fitness score and corresponding probability of fixation based on the change in steady-state flux value(s). Results from simulations are consistent with a priori expectations of fixation probabilities and systematic change in model parameters.

CONCLUSIONS

The PEMPS program simulates the evolution of a metabolic pathway with a mutation-selection modeling framework based on criteria like steady-state flux that is designed to work with SBML-formatted kinetic models, and Newick-formatted phylogenetic trees. The Python software is run on the Linux command line and is available at https://github.com/nmccloskey/PEMPS .

Empirical evidence for metabolic drift in plant and algal lipid biosynthesis pathways

Metabolic pathway drift has been formulated as a general principle to help in the interpretation of comparative analyses between biosynthesis pathways. Indeed, such analyses often indicate substantial differences, even in widespread pathways that are sometimes believed to be conserved. Here, our purpose is to check how much this interpretation fits to empirical data gathered in the field of plant and algal biosynthesis pathways. After examining several examples representative of the diversity of lipid biosynthesis pathways, we explain why it is important to compare closely related species to gain a better understanding of this phenomenon. Furthermore, this comparative approach brings us to the question of how much biotic interactions are responsible for shaping this metabolic plasticity. We end up introducing some model systems that may be promising for further exploration of this question.

A Retro-Aldol Reaction Prompted the Evolvability of a Phosphotransferase System for the Utilization of a Rare Sugar

The evolution of the bacterial phosphotransferase system (PTS) linked to glycolysis is dependent on the availability of naturally occurring sugars. Although bacteria exhibit sugar specificities based on carbon catabolite repression, the acquisition and evolvability of the cellular sugar preference under conditions that are suboptimal for growth (e.g., environments rich in a rare sugar) are poorly understood. Here, we generated Escherichia coli mutants via a retro-aldol reaction to obtain progeny that can utilize the rare sugar d-tagatose. We detected a minimal set of adaptive mutations in the d-fructose-specific PTS to render E. coli capable of d-tagatose utilization. These E. coli mutant strains lost the tight regulation of both the d-fructose and N-acetyl-galactosamine PTS following deletions in the binding site of the catabolite repressor/activator protein (Cra) upstream from the fruBKA operon and in the agaR gene, encoding the N-acetylgalactosamine (GalNAc) repressor, respectively. Acquired d-tagatose catabolic pathways then underwent fine-tuned adaptation via an additional mutation in 1-phosphofructose kinase to adjust metabolic fluxes. We determined the evolutionary trajectory at the molecular level, providing insights into the mechanism by which enteric bacteria evolved a substrate preference for the rare sugar d-tagatose. Furthermore, the engineered E. coli mutant strain could serve as an in vivo high-throughput screening platform for engineering non-phosphosugar isomerases to produce rare sugars. IMPORTANCE Microorganisms generate energy through glycolysis, which might have preceded a rapid burst of evolution, including the evolution of cellular respiration in the primordial biosphere. However, little is known about the evolvability of cellular sugar preferences. Here, we generated Escherichia coli mutants via a retro-aldol reaction to obtain progeny that can utilize the rare sugar d-tagatose. Consequently, we identified mutational hot spots and determined the evolutionary trajectory at the molecular level. This provided insights into the mechanism by which enteric bacteria evolved substrate preferences for various sugars, accounting for the widespread occurrence of these taxa. Furthermore, the adaptive laboratory evolution-induced cellular chassis could serve as an in vivo high-throughput screening platform for engineering tailor-made non-phosphorylated sugar isomerases to produce low-calorigenic rare sugars showing antidiabetic, antihyperglycemic, and antitumor activities.

The Memory Problem for Neutral Mutational Models of Evolution

Models for the evolution of various phenotypes are sometimes constructed with an assumption that mutational effects will be symmetrically distributed about a static mean. This model produces a memory effect that over long evolutionary times results in an expectation that randomized sequences underlying the genetic architecture of the trait will on average retain the ancestral phenotype. This expectation is unrealistic and also inconsistent with our current understanding of processes of molecular evolution.

A dual-function RNA balances carbon uptake and central metabolism in Vibrio cholerae

Bacterial small RNAs (sRNAs) are well known to modulate gene expression by base pairing with trans‐encoded transcripts and are typically non‐coding. However, several sRNAs have been reported to also contain an open reading frame and thus are considered dual‐function RNAs. In this study, we discovered a dual‐function RNA from Vibrio cholerae, called VcdRP, harboring a 29 amino acid small protein (VcdP), as well as a base‐pairing sequence. Using a forward genetic screen, we identified VcdRP as a repressor of cholera toxin production and link this phenotype to the inhibition of carbon transport by the base‐pairing segment of the regulator. By contrast, we demonstrate that the VcdP small protein acts downstream of carbon transport by binding to citrate synthase (GltA), the first enzyme of the citric acid cycle. Interaction of VcdP with GltA results in increased enzyme activity and together VcdR and VcdP reroute carbon metabolism. We further show that transcription of vcdRP is repressed by CRP allowing us to provide a model in which VcdRP employs two different molecular mechanisms to synchronize central metabolism in V. cholerae.

From OCR and ECAR to energy: Perspectives on the design and interpretation of bioenergetics studies

Biological energy transduction underlies all physiological phenomena in cells. The metabolic systems that support energy transduction have been of great interest due to their association with numerous pathologies including diabetes, cancer, rare genetic diseases, and aberrant cell death. Commercially available bioenergetics technologies (e.g., extracellular flux analysis, high-resolution respirometry, fluorescent dye kits, etc.) have made practical assessment of metabolic parameters widely accessible. This has facilitated an explosion in the number of studies exploring, in particular, the biological implications of oxygen consumption rate (OCR) and substrate level phosphorylation via glycolysis (i.e., via extracellular acidification rate (ECAR)). Though these technologies have demonstrated substantial utility and broad applicability to cell biology research, they are also susceptible to historical assumptions, experimental limitations, and other caveats that have led to premature and/or erroneous interpretations. This review enumerates various important considerations for designing and interpreting cellular and mitochondrial bioenergetics experiments, some common challenges and pitfalls in data interpretation, and some potential "next steps" to be taken that can address these highlighted challenges.

High-throughput insertional mutagenesis reveals novel targets for enhancing lipid accumulation in Nannochloropsis oceanica

The microalga Nannochloropsis oceanica is considered a promising platform for the sustainable production of high-value lipids and biofuel feedstocks. However, current lipid yields of N. oceanica are too low for economic feasibility. Gaining fundamental insights into the lipid metabolism of N. oceanica could open up various possibilities for the optimization of this species through genetic engineering. Therefore, the aim of this study was to discover novel genes associated with an elevated neutral lipid content. We constructed an insertional mutagenesis library of N. oceanica, selected high lipid mutants by five rounds of fluorescence-activated cell sorting, and identified disrupted genes using a novel implementation of a rapid genotyping procedure. One particularly promising mutant (HLM23) was disrupted in a putative APETALA2-like transcription factor gene. HLM23 showed a 40%-increased neutral lipid content, increased photosynthetic performance, and no growth impairment. Furthermore, transcriptome analysis revealed an upregulation of genes related to plastidial fatty acid biosynthesis, glycolysis and the Calvin-Benson-Bassham cycle in HLM23. Insights gained in this work can be used in future genetic engineering strategies for increased lipid productivity of Nannochloropsis.

Constructive Neutral Evolution 20 Years Later

Evolution has led to a great diversity that ranges from elegant simplicity to ornate complexity. Many complex features are often assumed to be more functional or adaptive than their simpler alternatives. However, in 1999, Arlin Stolzfus published a paper in the Journal of Molecular Evolution that outlined a framework in which complexity can arise through a series of non-adaptive steps. He called this framework Constructive Neutral Evolution (CNE). Despite its two-decade-old roots, many evolutionary biologists still appear to be unaware of this explanatory framework for the origins of complexity. In this perspective piece, we explain the theory of CNE and how it changes the order of events in narratives that describe the evolution of complexity. We also provide an extensive list of cellular features that may have become more complex through CNE. We end by discussing strategies to determine whether complexity arose through neutral or adaptive processes.

Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond

As both a computational and an experimental endeavor, ancestral sequence reconstruction remains a timely and important technique. Modern approaches to conduct ancestral sequence reconstruction for proteins are built upon a conceptual framework from journal founder Emile Zuckerkandl. On top of this, work on maximum likelihood phylogenetics published in Journal of Molecular Evolution in 1996 was one of the first approaches for generating maximum likelihood ancestral sequences of proteins. From its computational history, future model development needs as well as potential applications in areas as diverse as computational systems biology, molecular community ecology, infectious disease therapeutics and other biomedical applications, and biotechnology are discussed. From its past in this journal, there is a bright future for ancestral sequence reconstruction in the field of evolutionary biology.

Emerging Frontiers in the Study of Molecular Evolution

A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.

Metabolic Determinants of Enzyme Evolution in a Genome-Scale Bacterial Metabolic Network

Different genes and proteins evolve at very different rates. To identify the factors that explain these differences is an important aspect of research in molecular evolution. One such factor is the role a protein plays in a large molecular network. Here, we analyze the evolutionary rates of enzyme-coding genes in the genome-scale metabolic network of Escherichia coli to find the evolutionary constraints imposed by the structure and function of this complex metabolic system. Central and highly connected enzymes appear to evolve more slowly than less connected enzymes, but we find that they do so as a by-product of their high abundance, and not because of their position in the metabolic network. In contrast, enzymes catalyzing reactions with high metabolic flux-high substrate to product conversion rates-evolve slowly even after we account for their abundance. Moreover, enzymes catalyzing reactions that are difficult to by-pass through alternative pathways, such that they are essential in many different genetic backgrounds, also evolve more slowly. Our analyses show that an enzyme's role in the function of a metabolic network affects its evolution more than its place in the network's structure. They highlight the value of a system-level perspective for studies of molecular evolution.

Characterizing the roles of changing population size and selection on the evolution of flux control in metabolic pathways

Background

Understanding the genotype-phenotype map is fundamental to our understanding of genomes. Genes do not function independently, but rather as part of networks or pathways. In the case of metabolic pathways, flux through the pathway is an important next layer of biological organization up from the individual gene or protein. Flux control in metabolic pathways, reflecting the importance of mutation to individual enzyme genes, may be evolutionarily variable due to the role of mutation-selection-drift balance. The evolutionary stability of rate limiting steps and the patterns of inter-molecular co-evolution were evaluated in a simulated pathway with a system out of equilibrium due to fluctuating selection, population size, or positive directional selection, to contrast with those under stabilizing selection.

Results

Depending upon the underlying population genetic regime, fluctuating population size was found to increase the evolutionary stability of rate limiting steps in some scenarios. This result was linked to patterns of local adaptation of the population. Further, during positive directional selection, as with more complex mutational scenarios, an increase in the observation of inter-molecular co-evolution was observed.

Conclusions

Differences in patterns of evolution when systems are in and out of equilibrium, including during positive directional selection may lead to predictable differences in observed patterns for divergent evolutionary scenarios. In particular, this result might be harnessed to detect differences between compensatory processes and directional processes at the pathway level based upon evolutionary observations in individual proteins. Detecting functional shifts in pathways reflects an important milestone in predicting when changes in genotypes result in changes in phenotypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0962-7) contains supplementary material, which is available to authorized users.

Selection on metabolic pathway function in the presence of mutation-selection-drift balance leads to rate-limiting steps that are not evolutionarily stable

Background

While commonly assumed in the biochemistry community that the control of metabolic pathways is thought to be critical to cellular function, it is unclear if metabolic pathways generally have evolutionarily stable rate limiting (flux controlling) steps.

Results

A set of evolutionary simulations using a kinetic model of a metabolic pathway was performed under different conditions to evaluate the evolutionary stability of rate limiting steps. Simulations used combinations of selection for steady state flux, selection against the cost of molecular biosynthesis, and selection against the accumulation of high concentrations of a deleterious intermediate. Two mutational regimes were used, one with mutations that on average were neutral to molecular phenotype and a second with a preponderance of activity-destroying mutations. The evolutionary stability of rate limiting steps was low in all simulations with non-neutral mutational processes. Clustering of parameter co-evolution showed divergent inter-molecular evolutionary patterns under different evolutionary regimes.

Conclusions

This study provides a null model for pathway evolution when compensatory processes dominate with potential applications to predicting pathway functional change. This result also suggests a possible mechanism in which studies in statistical genetics that aim to associate a genotype to a phenotype assuming independent action of variants may be mis-specified through a mis-characterization of the link between individual gene function and pathway function. A better understanding of the genotype-phenotype map has potential applications in differentiating between compensatory changes and directional selection on pathways as well as detecting SNPs and fixed differences that might have phenotypic effects.

Reviewers

This article was reviewed by Arne Elofsson, David Ardell, and Shamil Sunyaev.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-016-0133-6) contains supplementary material, which is available to authorized users.