Ab initio reconstruction of metabolic pathways

We propose a new formulation for the problem of ab initio metabolic pathway reconstruction. Given a set of biochemical reactions together with their substrates and products, we consider the reactions as transfers of atoms between the chemical compounds and we look for successions of reactions transferring a maximal (or preset) number of atoms between a given source and sink compound. We state this problem as the one of finding a composition of partial injections that maximizes the image size. First, we study the theoretical complexity of this problem, state some related problems and then give a practical algorithm to solve them. Finally, we present two applications of this approach to the reconstruction of the tryptophan biosynthesis pathway and to the glycolysis.     

Metabolic network visualization eliminating node redundance and preserving metabolic pathways

Background  

The tools that are available to draw and to manipulate the representations of metabolism are usually restricted to metabolic pathways. This limitation becomes problematic when studying processes that span several pathways. The various attempts that have been made to draw genome-scale metabolic networks are confronted with two shortcomings: 1- they do not use contextual information which leads to dense, hard to interpret drawings, 2- they impose to fit to very constrained standards, which implies, in particular, duplicating nodes making topological analysis considerably more difficult.     

Caveat emptor: limitations of the automated reconstruction of metabolic pathways in Plasmodium

The functional reconstruction of metabolic pathways from an annotated genome is a tedious and demanding enterprise. Automation of this endeavor using bioinformatics algorithms could cope with the ever-increasing number of sequenced genomes and accelerate the process. Here, the manual reconstruction of metabolic pathways in the functional genomic database of Plasmodium falciparum--Malaria Parasite Metabolic Pathways--is described and compared with pathways generated automatically as they appear in PlasmoCyc, metaSHARK and the Kyoto Encyclopedia for Genes and Genomes. A critical evaluation of this comparison discloses that the automatic reconstruction of pathways generates manifold paths that need an expert manual verification to accept some and reject most others based on manually curated gene annotation.     

Global dynamic optimization approach to predict activation in metabolic pathways

Background

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been succesfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework.

Results

In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results.

Conclusions

The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.     

Glycerate 2-kinase of Thermotoga maritima and genomic reconstruction of related metabolic pathways

Members of a novel glycerate-2-kinase (GK-II) family were tentatively identified in a broad range of species, including eukaryotes and archaea and many bacteria that lack a canonical enzyme of the GarK (GK-I) family. The recently reported three-dimensional structure of GK-II from Thermotoga maritima (TM1585; PDB code 2b8n) revealed a new fold distinct from other known kinase families. Here, we verified the enzymatic activity of TM1585, assessed its kinetic characteristics, and used directed mutagenesis to confirm the essential role of the two active-site residues Lys-47 and Arg-325. The main objective of this study was to apply comparative genomics for the reconstruction of metabolic pathways associated with GK-II in all bacteria and, in particular, in T. maritima. Comparative analyses of ~400 bacterial genomes revealed a remarkable variety of pathways that lead to GK-II-driven utilization of glycerate via a glycolysis/gluconeogenesis route. In the case of T. maritima, a three-step serine degradation pathway was inferred based on the tentative identification of two additional enzymes, serine-pyruvate aminotransferase and hydroxypyruvate reductase (TM1400 and TM1401, respectively), that convert serine to glycerate via hydroxypyruvate. Both enzymatic activities were experimentally verified, and the entire pathway was validated by its in vitro reconstitution.     

In silico reconstruction of the amino acid metabolic pathways of Trypanosoma cruzi

Trypanosoma cruzi is the epidemiological agent of Chagas' disease, affecting most of Central and South America, constituting a significant health and socio-economic problem. The parasite has a metabolism largely based on the consumption of amino acids, which participate in a diversity of metabolic pathways, leading to many crucial compounds for the survival of this parasite. Study of its enzymes has the potential to disclose new therapeutic targets and foster the development of new drugs. In this study, we employed computational approaches to reconstruct in silico the amino acid metabolic pathways of T. cruzi, aiming to link genomic information with functional information. For that, protein sequences from 570 EC classes belonging to 25 different pathways in general amino acid metabolism were downloaded from KEGG. A subset of 471 EC classes had at least one sequence deposited. Clustering of the proteins belonging to each EC class was performed using a similarity-based approach implemented in the tool AnEnPi. Reconstruction of the metabolic pathways comprising the amino acid metabolism of T. cruzi was performed by analyzing the output of BLASTP, using as query the dataset of predicted proteins of T. cruzi against all sequences of each individual cluster. This approach allowed us to identify 764 T. cruzi proteins probably involved in the metabolism of amino acids as well as the identification of several putative cases of analogy. Furthermore, we were able to identify several enzymatic activities of T. cruzi that were not previously included in KEGG.     

Butanol production from renewable biomass: rediscovery of metabolic pathways and metabolic engineering

Biofuel from renewable biomass is one of the answers to help solve the problems associated with limited fossil resources and climate change. Butanol has superior liquid-fuel characteristics, with similar properties to gasoline, and thus, has the potential to be used as a substitute for gasoline. Clostridia are recognized as a good butanol producers and are employed in the industrial-scale production of solvents. Due to the difficulty of performing genetic manipulations on clostridia, however, strain improvement has been rather slow. Furthermore, complex metabolic characteristics of acidogenesis followed by solventogenesis in this strain have hampered the development of engineered clostridia strains with highly efficient and selective butanol-production capabilities. In recent years, the butanol-producing characteristics in clostridia have been further characterized and alternative pathways discovered. More recently, systems-level metabolic engineering approaches were taken to develop superior strains. Herein, we review recent discoveries of metabolic pathways for butanol production and the metabolic engineering strategies being developed.     

MarVis: a tool for clustering and visualization of metabolic biomarkers

Background

Gene set analysis based on Gene Ontology (GO) can be a promising method for the analysis of differential expression patterns. However, current studies that focus on individual GO terms have limited analytical power, because the complex structure of GO introduces strong dependencies among the terms, and some genes that are annotated to a GO term cannot be found by statistically significant enrichment.

Results

We proposed a method for enriching clustered GO terms based on semantic similarity, namely cluster enrichment analysis based on GO (CeaGO), to extend the individual term analysis method. Using an Affymetrix HGU95aV2 chip dataset with simulated gene sets, we illustrated that CeaGO was sensitive enough to detect moderate expression changes. When compared to parent-based individual term analysis methods, the results showed that CeaGO may provide more accurate differentiation of gene expression results. When used with two acute leukemia (ALL and ALL/AML) microarray expression datasets, CeaGO correctly identified specifically enriched GO groups that were overlooked by other individual test methods.

Conclusion

By applying CeaGO to both simulated and real microarray data, we showed that this approach could enhance the interpretation of microarray experiments. CeaGO is currently available at http://chgc.sh.cn/en/software/CeaGO/.     

MarVis: a tool for clustering and visualization of metabolic biomarkers

Background  

A central goal of experimental studies in systems biology is to identify meaningful markers that are hidden within a diffuse background of data originating from large-scale analytical intensity measurements as obtained from metabolomic experiments. Intensity-based clustering is an unsupervised approach to the identification of metabolic markers based on the grouping of similar intensity profiles. A major problem of this basic approach is that in general there is no prior information about an adequate number of biologically relevant clusters.     

Evolutionary optimization of metabolic pathways. Theoretical reconstruction of the stoichiometry of ATP and NADH producing systems

The structural design of ATP and NADH producing systems, such as glycolysis and the citric acid cycle (TCA), is analysed using optimization principles. It is assumed that these pathways combined with oxidative phosphorylation have reached, during their evolution, a high efficiency with respect to ATP production rates. On the basis of kinetic and thermodynamic principles, conclusions are derived concerning the optimal stoichiometry of such pathways. Extending previous investigations, both the concentrations of adenine nucleotides as well as nicotinamide adenine dinucleotides are considered variable quantities. This implies the consideration of the interaction of an ATP and NADH producing system, an ATP consuming system, a system coupling NADH consumption with ATP production and a system consuming NADH decoupled from ATP production. It is examined in what respect real metabolic pathways can be considered optimal by studying a large number of alternative pathways. The kinetics of the individual reactions are described by linear or bilinear functions of reactant concentrations. In this manner, the steady-state ATP production rate can be calculated for any possible ATP and NADH producing pathway. It is shown that most of the possible pathways result in a very low ATP production rate and that the very efficient pathways share common structural properties. Optimization with respect to the ATP production rate is performed by an evolutionary algorithm. The following results of our analysis are in close correspondence to the real design of glycolysis and the TCA cycle. (1) In all efficient pathways the ATP consuming reactions are located near the beginning. (2) In all efficient pathways NADH producing reactions as well as ATP producing reactions are located near the end. (3) The number of NADH molecules produced by the consumption of one energy-rich molecule (glucose) amounts to four in all efficient pathways. A distance measure and a measure for the internal ordering of reactions are introduced to study differences and similarities in the stoichiometries of metabolic pathways.     

The metabolic pathways of Acholeplasma and Mycoplasma: an overview

The metabolism of the Mollicutes Acholeplasma and Mycoplasma may be characterized as restricted, for example, by virtue of the apparent absence of cytochrome pigments. Some Mollicutes have lowered ECA values during their logarithmic growth phase, which we speculate may be related to insufficient substrate phosphorylation or insufficient ATP synthesis linked to glycolysis. We found that PEP is carboxylated by preparations of A. laidlawii, but not by other Mollicutes; thus in this organism oxaloacetate from PEP may be a link to other pathways. We found phosphoribosylpyrophosphate in A. laidlawii, which suggests that ribosylation of purines and pyrimidines occurs in Mollicutes other than M. mycoides.     

Glutamate metabolic pathways and retinal function

Glutamate is a major neurotransmitter in the CNS but is also a key metabolite intimately coupled to amino acid production/degradation. We consider the effect of inhibition of two key glutamate metabolic enzymes: glutamine synthetase (GS) and aspartate aminotransferase on retinal function assessed using the electroretinogram to consider photoreceptoral (a-wave) and post-receptoral (b-wave) amplitudes. Quantitative immunocytochemistry was used to assess amino acid levels within photoreceptors, ganglion and Müller cells secondary to GS inhibition. Intravitreal injections of methionine sulfoximine reduced GS immunoreactivity in the rat retina. Additionally, glutamate and its precursor aspartate was reduced in photoreceptors and ganglion cells, but elevated in Müller cells. This reduction in neuronal glutamate was consistent with a deficit in neurotransmission (−75% b-wave reduction). Exogenous glutamine supply completely restored the b-wave, whereas other amino acid substrates (lactate, pyruvate, α-ketoglutarate, and succinate) only partially restored the b-wave (16–20%). Inhibition of the aminotranferases using aminooxyacetic acid had no effect on retinal function. However, aminooxyacetic acid application after methionine sulfoximine further reduced the b-wave (from −75% to −92%). The above data suggest that de novo glutamate synthesis involving aspartate aminotransferase can partially sustain neurotransmission when glutamate recycling is impaired. We also show that altered glutamate homeostasis results in a greater change in amino acid distribution in ganglion cells compared with photoreceptors.     

Chromokinetics of metabolic pathways.

Some methods to study and intuitively understand steady-state flows in complicated metabolic pathways are discussed. For this purpose, a suitable decomposition of complex metabolic schemes into smaller subsystems is used. These independent subsystems are then interpreted as basic colors of a chromatic coloring scheme. The mixture of these basic colors allows an intuitive picture of how a steady state in a metabolic pathway can be understood. Furthermore, actions of drugs can be more easily investigated on this basis. An anaerobic variant of pyruvate metabolism in rat liver mitochondria is presented as a simple example. This experiment allows measurement of the percentage that each basic color contributes to the steady states resulting from different experimental conditions. Possible implementations of existing algorithms and rational design of new drugs are discussed. A MATHEMATICA program, based on a new algorithm for finding all basic colors of stoichiometric networks, is included.