From annotated genomes to metabolic flux models and kinetic parameter fitting

Significant advances in system-level modeling of cellular behavior can be achieved based on constraints derived from genomic information and on optimality hypotheses. For steady-state models of metabolic networks, mass conservation and reaction stoichiometry impose linear constraints on metabolic fluxes. Different objectives, such as maximization of growth rate or minimization of flux distance from a reference state, can be tested in different organisms and conditions. In particular, we have suggested that the metabolic properties of mutant bacterial strains are best described by an algorithm that performs a minimization of metabolic adjustment (MOMA) upon gene deletion. The increasing availability of many annotated genomes paves the way for a systematic application of these flux balance methods to a large variety of organisms. However, such a high throughput goal crucially depends on our capacity to build metabolic flux models in a fully automated fashion. Here we describe a pipeline for generating models from annotated genomes and discuss the current obstacles to full automation. In addition, we propose a framework for the integration of flux modeling results and high throughput proteomic data, which can potentially help in the inference of whole-cell kinetic parameters.     

From genomes to systems

A report on the 2nd Conference of the Consortium for Post-Genome Science (CPGS) 'Genomes to Systems', Manchester, UK, 1-3 September 2004.     

In silico prediction of proteins related to xyloglucan fucosyltransferases in Solanaceae genomes

Two independent studies have shown that the cell wall of pollen tubes from tobacco and tomato species contained fucosylated xyloglucan (XyG). These findings are intriguing as many reports have shown that XyG of somatic cells of these species is not fucosylated but instead is arabinosylated. In order to produce fucosylated XyG, plants must express a functional galactoside α-2-fucosyltransferase. Here, using a bioinformatics approach, we show that several candidate genes coding for XyG fucosyltransferases are present in the genome of coffee and several Solanaceae species including tomato, tobacco, potato, eggplant and pepper. BLAST and protein alignments with the 2 well-characterized XyG fucosyltransferases from Arabidopsis thaliana and Pisum sativum revealed that at least 6 proteins from different Solanaceae species and from coffee displayed the 3 conserved motifs required for XyG fucosyltransferase activity.     

From metabolic to metabolomic NMR spectroscopy of apoptotic cells

Over the past 10–15 years, nuclear magnetic resonance (NMR) spectroscopy has been employed to study metabolic events accompanying programmed cell death (apoptosis). The early studies were characterized by experiments focusing on specific metabolic parameters obtained by analyzing a limited number of biochemical compounds, e.g. selected metabolic species involved in the Krebs cycle, in energy metabolism, in phospholipid synthesis and degradation, or in mobile-lipid accumulation. However, during the past few years metabolic NMR spectroscopy has begun to refocus towards more comprehensive analyses of tissue metabolites detectable in NMR spectra. This review describes some requirements needed for the development of an integrated, metabolomic concept for NMR spectroscopy investigations of apoptotic cells, and presents recent studies approaching this goal. Metabolomic NMR spectroscopy allows one not only to distinguish between cells that are sensitive to apoptosis induction and resistant cells, but also, in conjunction with measurements of complementary biological parameters, to follow the temporal evolution of the apoptotic process and to analyze mechanisms of apoptosis resistance.     

In silico insights into the symbiotic nitrogen fixation in Sinorhizobium meliloti via metabolic reconstruction

Background

Sinorhizobium meliloti is a soil bacterium, known for its capability to establish symbiotic nitrogen fixation (SNF) with leguminous plants such as alfalfa. S. meliloti 1021 is the most extensively studied strain to understand the mechanism of SNF and further to study the legume-microbe interaction. In order to provide insight into the metabolic characteristics underlying the SNF mechanism of S. meliloti 1021, there is an increasing demand to reconstruct a metabolic network for the stage of SNF in S. meliloti 1021.

Results

Through an iterative reconstruction process, a metabolic network during the stage of SNF in S. meliloti 1021 was presented, named as iHZ565, which accounts for 565 genes, 503 internal reactions, and 522 metabolites. Subjected to a novelly defined objective function, the in silico predicted flux distribution was highly consistent with the in vivo evidences reported previously, which proves the robustness of the model. Based on the model, refinement of genome annotation of S. meliloti 1021 was performed and 15 genes were re-annotated properly. There were 19.8% (112) of the 565 metabolic genes included in iHZ565 predicted to be essential for efficient SNF in bacteroids under the in silico microaerobic and nutrient sharing condition.

Conclusions

As the first metabolic network during the stage of SNF in S. meliloti 1021, the manually curated model iHZ565 provides an overview of the major metabolic properties of the SNF bioprocess in S. meliloti 1021. The predicted SNF-required essential genes will facilitate understanding of the key functions in SNF and help identify key genes and design experiments for further validation. The model iHZ565 can be used as a knowledge-based framework for better understanding the symbiotic relationship between rhizobia and legumes, ultimately, uncovering the mechanism of nitrogen fixation in bacteroids and providing new strategies to efficiently improve biological nitrogen fixation.     

Using in silico predicted ancestral genomes to improve the efficiency of paleogenome reconstruction

Paleogenomics is the nascent discipline concerned with sequencing and analysis of genome‐scale information from historic, ancient, and even extinct samples. While once inconceivable due to the challenges of DNA damage, contamination, and the technical limitations of PCR‐based Sanger sequencing, following the dawn of the second‐generation sequencing revolution, it has rapidly become a reality. However, a significant challenge facing ancient DNA studies on extinct species is the lack of closely related reference genomes against which to map the sequencing reads from ancient samples. Although bioinformatic efforts to improve the assemblies have focused mainly in mapping algorithms, in this article we explore the potential of an alternative approach, namely using reconstructed ancestral genome as reference for mapping DNA sequences of ancient samples. Specifically, we present a preliminary proof of concept for a general framework and demonstrate how under certain evolutionary divergence thresholds, considerable mapping improvements can be easily obtained.     

In silico analysis of SSRs in mitochondrial genomes of plants

Simple sequence repeats (SSRs) or microsatellites constitute a countable portion of genomes. However, the significance of SSRs in organelle genomes has not been completely understood. The availability of organelle genome sequences allows us to understand the organization of SSRs in their genic and intergenic regions. In the current study we surveyed the patterns of SSRs in mitochondrial genomes of different taxa of plants. A total of 16 mitochondrial genomes, from algae to angiosperms, have been considered to analyze the pattern of simple sequence repeats present in them. Based on study, the mononucleotide repeats of A/T were found to be more prevalent in mitochondrial genomes over other repeat types. The dinucleotides repeats, TA/AT, were the second most numerous, whereas tri-, tetra-, and pentanucleotide repeats were in less number and present in intronic or intergenic portions only. Mononucleotide repeats prevailed in protein-coding exonic portions of all organisms. These results indicates that microsatellite pattern in mitochondrial genomes is different from nuclear genomes and also focuses on organization and diversity at SSR locuses in mitochondrial genomes. This is the novel report of microsatellite polymorphism in plant mitochondrion on whole genome level.     

Exploring the genomes: From Arabidopsis to crops

Model systems have played a crucial role for understanding biological processes at genetic, molecular and systems levels. Arabidopsis thaliana is one of the best studied model species for higher plants. Large genomic resources and mutant collections made Arabidopsis an excellent source for functional and comparative genomics. Rice and Brachypodium have a great potential to become model systems for grasses. Given the agronomic importance of grass crops, it is an attractive strategy to apply knowledge from Arabidopsis to grasses. Despite many efforts successful reports are sparse. Knowledge transfer should generally work best between orthologous genes that share functionality and a common ancestor. In higher plants, however, recent genome projects revealed an active and rapid evolution of genome structure, which challenges the concept of one-to-one orthologous mates between two species. In this study, we estimated on the example of protein families that are involved in redox related processes, the impact of gene expansions on the success rate for a knowledge transfer from Arabidopsis to the grass species rice, sorghum and Brachypodium. The sparse synteny between dicot and monocot plants due to frequent rearrangements, translocations and gene losses strongly impairs and reduces the number of orthologs detectable by positional conservation. To address the limitations of sparse synteny and expanded gene families, we applied for the detection of orthologs in this study orthoMCL, a sequence-based approach that allows to group closely related paralogs into one orthologous gene cluster. For a total of 49 out of 170 Arabidopsis genes we could identify conserved copy numbers between the dicot model and the grass annotations whereas approximately one third (34.7%, 59 genes) of the selected Arabidopsis genes lack an assignment to any of the grass genome annotations. The remaining 62 Arabidopsis genes represent groups that are considerably biased in their copy numbers between Arabidopsis and all or most of the three grass genomes.     

From in silico to in spectro kinetics of respiratory complex I

An enzyme's activity is the consequence of its structure. The stochastic approach we developed to study the functioning of the respiratory complexes is based upon their 3D structure and their physical and chemical properties. Consequently it should predict their kinetic properties. In this paper we compare the predictions of our stochastic model derived for the complex I with a number of experiments performed with a large range of complex I substrates and products. A good fit was found between the experiments and the prediction of our stochastic approach. We show that, due to the spatial separation of the two half redox reactions (NADH/NAD and Q/QH(2)), the kinetics cannot necessarily obey a simple mechanism (ordered or ping-pong for instance). A plateau in the kinetics is observed at high substrates concentrations, well evidenced in the double reciprocal plots, which is explained by the limiting rate of quinone reduction as compared with the oxidation of NADH at the other end of complex I. Moreover, we show that the set of the seven redox reactions in between the two half redox reactions (NADH/NAD and Q/QH(2)) acts as an electron buffer. An inhibition of complex I activity by quinone is observed at high concentration of this molecule, which cannot be explained by a simple stochastic model based on the known structure. We hypothesize that the distance between the catalytic site close to N2 (iron/sulfur redox center that transfers electrons to quinone) and the membrane forces the quinone/quinol to take several positions in between these sites. We represent these possible positions by an extra site necessarily occupied by the quinone/quinol molecules on their way to the redox site. With this hypothesis, we are able to fit the kinetic experiments over a large range of substrates and products concentrations. The slow rate constants derived for the transition between the two sites could be an indication of a conformational change of the enzyme during the quinone/quinol movement. This article is part of a Special Issue entitled: 17th European Bioenergetics Conference (EBEC 2012).     

From sequence to structure to networks

A report on the 7th European Conference on Computational Biology (ECCB), Cagliari, Italy, 22-26 September 2008.     

Uncovering metabolic pathways relevant to phenotypic traits of microbial genomes

Identifying the biochemical basis of microbial phenotypes is a main objective of comparative genomics. Here we present a novel method using multivariate machine learning techniques for comparing automatically derived metabolic reconstructions of sequenced genomes on a large scale. Applying our method to 266 genomes directly led to testable hypotheses such as the link between the potential of microorganisms to cause periodontal disease and their ability to degrade histidine, a link also supported by clinical studies.