570 Biowissenschaften; Biologie
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All's well that ends well
(2012)
The transition from cell proliferation to cell expansion is critical for determining leaf size. Andriankaja et al. (2012) demonstrate that in leaves of dicotyledonous plants, a basal proliferation zone is maintained for several days before abruptly disappearing, and that chloroplast differentiation is required to trigger the onset of cell expansion.
The size of plant organs, such as leaves and flowers, is determined by an interaction of genotype and environmental influences. Organ growth occurs through the two successive processes of cell proliferation followed by cell expansion. A number of genes influencing either or both of these processes and thus contributing to the control of final organ size have been identified in the last decade. Although the overall picture of the genetic regulation of organ size remains fragmentary, two transcription factor/microRNA-based genetic pathways are emerging in the control of cell proliferation. However, despite this progress, fundamental questions remain unanswered, such as the problem of how the size of a growing organ could be monitored to determine the appropriate time for terminating growth. While genetic analysis will undoubtedly continue to advance our knowledge about size control in plants, a deeper understanding of this and other basic questions will require including advanced live-imaging and mathematical modeling, as impressively demonstrated by some recent examples. This should ultimately allow the comparison of the mechanisms underlying size control in plants and in animals to extract common principles and lineage-specific solutions.
Dynamic regulatory on/off minimization for biological systems under internal temporal perturbations
(2012)
Background: Flux balance analysis (FBA) together with its extension, dynamic FBA, have proven instrumental for analyzing the robustness and dynamics of metabolic networks by employing only the stoichiometry of the included reactions coupled with adequately chosen objective function. In addition, under the assumption of minimization of metabolic adjustment, dynamic FBA has recently been employed to analyze the transition between metabolic states.
Results: Here, we propose a suite of novel methods for analyzing the dynamics of (internally perturbed) metabolic networks and for quantifying their robustness with limited knowledge of kinetic parameters. Following the biochemically meaningful premise that metabolite concentrations exhibit smooth temporal changes, the proposed methods rely on minimizing the significant fluctuations of metabolic profiles to predict the time-resolved metabolic state, characterized by both fluxes and concentrations. By conducting a comparative analysis with a kinetic model of the Calvin-Benson cycle and a model of plant carbohydrate metabolism, we demonstrate that the principle of regulatory on/off minimization coupled with dynamic FBA can accurately predict the changes in metabolic states.
Conclusions: Our methods outperform the existing dynamic FBA-based modeling alternatives, and could help in revealing the mechanisms for maintaining robustness of dynamic processes in metabolic networks over time.
F2C2
(2012)
Background: Flux coupling analysis (FCA) has become a useful tool in the constraint-based analysis of genome-scale metabolic networks. FCA allows detecting dependencies between reaction fluxes of metabolic networks at steady-state. On the one hand, this can help in the curation of reconstructed metabolic networks by verifying whether the coupling between reactions is in agreement with the experimental findings. On the other hand, FCA can aid in defining intervention strategies to knock out target reactions.
Results: We present a new method F2C2 for FCA, which is orders of magnitude faster than previous approaches. As a consequence, FCA of genome-scale metabolic networks can now be performed in a routine manner.
Conclusions: We propose F2C2 as a fast tool for the computation of flux coupling in genome-scale metabolic networks. F2C2 is freely available for non-commercial use at https://sourceforge.net/projects/f2c2/files/.
Flux-P
(2012)
Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via 13C-based metabolic flux analysis, a model-based interpretation of stable carbon isotope patterns in intermediates of metabolism. Existing software such as FiatFlux, OpenFLUX or 13CFLUX supports experts in this complex analysis, but requires several steps that have to be carried out manually, hence restricting the use of this software for data interpretation to a rather small number of experiments. In this paper, we present Flux-P as an approach to automate and standardize 13C-based metabolic flux analysis, using the Bio-jETI workflow framework. Exemplarily based on the FiatFlux software, it demonstrates how services can be created that carry out the different analysis steps autonomously and how these can subsequently be assembled into software workflows that perform automated, high-throughput intracellular flux analysis of high quality and reproducibility. Besides significant acceleration and standardization of the data analysis, the agile workflow-based realization supports flexible changes of the analysis workflows on the user level, making it easy to perform custom analyses.
The distinctness of, and overlap between, pea genotypes held in several Pisum germplasm collections has been used to determine their relatedness and to test previous ideas about the genetic diversity of Pisum. Our characterisation of genetic diversity among 4,538 Pisum accessions held in 7 European Genebanks has identified sources of novel genetic variation, and both reinforces and refines previous interpretations of the overall structure of genetic diversity in Pisum. Molecular marker analysis was based upon the presence/absence of polymorphism of retrotransposon insertions scored by a high-throughput microarray and SSAP approaches. We conclude that the diversity of Pisum constitutes a broad continuum, with graded differentiation into sub-populations which display various degrees of distinctness. The most distinct genetic groups correspond to the named taxa while the cultivars and landraces of Pisum sativum can be divided into two broad types, one of which is strongly enriched for modern cultivars. The addition of germplasm sets from six European Genebanks, chosen to represent high diversity, to a single collection previously studied with these markers resulted in modest additions to the overall diversity observed, suggesting that the great majority of the total genetic diversity collected for the Pisum genus has now been described. Two interesting sources of novel genetic variation have been identified. Finally, we have proposed reference sets of core accessions with a range of sample sizes to represent Pisum diversity for the future study and exploitation by researchers and breeders.