The fractional contributions of elementary modes to the metabolism of Escherichia coli and their estimation from reaction entropies

The metabolism of a cell can be viewed as a weighted sum of elementary modes. Due to the multiplicity of modes the identification of the individual weights represents a non-trivial problem. To enable the determination of weighting factors we have identified and implemented two gene deletions in combination with defined growth conditions that limit the metabolism from 4374 original elementary modes to 24 elementary modes for a non-PHB synthesizing control and 40 modes for a PHB synthesizing strain. These remaining modes can be further grouped into five families that have the same overall stoichiometry. Thus, the complexity of the problem is significantly reduced, and weighting factors for each family of modes could be determined from the measurement of accumulation rates of metabolites. Moreover, it is shown that individual weights are inversely correlated with the entropy generated by the operation of the used pathways defined in elementary modes. This suggests that evolution developed cellular regulatory patterns that permit diversity of pathways while favoring efficient pathways with low entropy generation. Furthermore, such correlation provides a rational way of estimating metabolic fluxes based on the thermodynamic properties of elementary modes. This is demonstrated with an example in which experimentally determined, intracellular fluxes are shown to be highly correlated with fluxes computed based on elementary modes and reaction entropies. The analysis suggests that the set of elementary modes can be interpreted analogous to a metabolic ensemble of quantum states of a macroscopic system.     

Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism

Elementary mode analysis is a useful metabolic pathway analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering.     

<Emphasis Type="Italic">mab-31</Emphasis> and the TGF-β pathway act in the ray lineage to pattern <Emphasis Type="Italic">C. elegans</Emphasis>male sensory rays

Background  

C. elegans TGF-β-like Sma/Mab signaling pathway regulates both body size and sensory ray patterning. Most of the components in this pathway were initially identified by genetic screens based on the small body phenotype, and many of these mutants display sensory ray patterning defect. At the cellular level, little is known about how and where these components work although ray structural cell has been implicated as one of the targets. Based on the specific ray patterning abnormality, we aim to identify by RNAi approach additional components that function specifically in the ray lineage to elucidate the regulatory role of TGF-β signaling in ray differentiation.     

Design, construction and performance of the most efficient biomass producing E. coli bacterium

Inverse metabolic engineering based on elementary mode analysis was applied to maximize the biomass yield of Escherchia coli MG1655. Elementary mode analysis was previously employed to identify among 1691 possible pathways for cell growth the most efficient pathway with maximum biomass yield. The metabolic network analysis predicted that deletion of only 6 genes reduces the number of possible elementary modes to the most efficient pathway. We have constructed a strain containing these gene deletions and we evaluated its properties in batch and in chemostat growth experiments. The results show that the theoretical predictions are closely matched by the properties of the designed strain.     

A scaffold for the Chinese hamster genome

Chinese hamster ovary (CHO) cells are a prevalent tool in biological research and are among the most widely used host cell lines for production of recombinant therapeutic proteins. While research in other organisms has been revolutionized through the development of DNA sequence-based tools, the lack of comparable genomic resources for the Chinese hamster has impeded similar work in CHO cell lines. A comparative genomics approach, based upon the completely sequenced mouse genome, can facilitate genomic work in this important organism. Using chromosome synteny to define regions of conserved linkage between Chinese hamster and mouse chromosomes, a working scaffold for the Chinese hamster genome has been developed. Mapping CHO and Chinese hamster sequences to the mouse genome creates direct access to relevant information in public databases. Additionally, mapping gene expression data onto a chromosome scaffold affords the ability to interpret information in a genomic context, potentially revealing important structural and regulatory features in the Chinese hamster genome. Further development of this genomic scaffold will provide opportunities to use biomolecular tools for research in CHO cell lines today and will be an asset to future efforts to sequence the Chinese hamster genome.