Integration of enzyme activities into metabolic flux distributions by elementary mode analysis
In systems biology, network-based pathway analysis facilitates understanding or designing metabolic systems and enables prediction of metabolic flux distributions. Network-based flux analysis requires considering not only pathway architectures but also the proteome or transcriptome to predict flux distributions, because recombinant microbes significantly change the distribution of gene expressions. The current problem is how to integrate such heterogeneous data to build a network-based model. The ECF model is a non-mechanistic and static model to link an enzyme activity profile to a metabolic flux distribution by introducing the power-law formula into EMA, suggesting that the change in an enzyme profile rather reflects the change in the flux distribution. The ECF model is highly applicable to the central metabolism in knockout mutants of E. coli and B. subtilis.
Source: BMC Systems Biology 2007,1:31 doi:10.1186/1752 -0509-1-31
Protein Interaction Network Analysis Reveals the Function of Tumor Suppressor
Elucidation of the cellular signaling pathways that contribute to cancer development often begins with the identification of a gene mutated in human tumors. Complementary biochemical approaches become especially important when the sequence of the newly identified gene provides few clues as to its function. Major et al. used analysis of protein interaction networks to define the function of WTX, a tumor suppressor gene found very recently to be mutated in an inherited kidney cancer called Wilms tumor. The WTX protein forms a complex with several proteins in the WNT signaling cascade, including 
-catenin, AXIN1, -TrCP2 (-transducin repeat-containing protein 2), and APC (adenomatous polyposis coli) and antagonizes WNT signaling by promoting -catenin degradation.
Source: Science, Volume 316, Number 5827, Issue of 18 May 2007
Signal Convergence in Plants
Plastids, including plant chloroplasts, are built and operated largely under the control of the nuclear genome. Largely, but not exclusively, plastids carry their own residual genome and can talk back when things go awry. Koussevitzky et al. now show that several signaling pathways that carry news of disaster from the plastid to the nucleus actually converge into one signaling pathway before the news emerges from the chloroplast. Thus, the nucleus receives a coherent report that integrates several aspects of chloroplast function. Gun1 protein is identified as a key integrator within the chloroplast, and ABI4 as a key transcription factor within the nucleus that responds to the news by altering gene transcription.
Source: Science, Volume 316, Number 5825, Issue of 04 May 2007
Global Reconstruction of the Human Metabolic Network
Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype–phenotype relationships. Duarte etal. in University of California have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein they describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Their comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology.
Source: PNAS | February 6, 2007 | vol. 104 | no. 6 | 1777-1782
The gene and the genon concept
'Gene' has become a vague and ill-defined concept. To set the stage for mathematical analysis of gene storage and expression, we return to the original concept of the gene as a function encoded in the genome, basis of genetic analysis, that is a polypeptide or other functional product. The additional information needed to express a gene is contained within each mRNA as an ensemble of signals, added to or superimposed onto the coding sequence. To designate this programme, the term 'genon' had been introduced. Individual genons are contained in the pre-mRNA forming a pre-genon. A genomic domain contains a proto-genon, with the signals of transcription activation in addition to the pre-genon in the transcripts. Some contain several mRNAs and hence genons, to be singled out by RNA processing and differential splicing. The programme in the genon in cis is implemented by corresponding factors of protein or RNA nature contained in the transgenon of the cell or organism. The gene, the cis programme contained in the individual domain and transcript, and the trans programme of factors, can be analysed by information theory.
Source:Molecular Systems Biology 3 Article number:87 doi:10.1038/msb4100123
Systems Biology at the Single-Molecule Level
The goal of single-molecule research is to produce a movie of the cell. Biochemistry and biophysics done in the test tube already provide an understanding of the dynamic behavior of molecules; from these studies, what goes on in cells, minute by minute or even second by second, can be inferred. Ultimately, however, the goal is to film single molecules in single cells, focusing in closely enough not only to observe spatial and temporal characteristics but also to decipher molecular mechanisms. We're not there yet, but recent advances in single-molecule techniques bring us tantalizingly close to a molecule-scale movie of cellular life. Discover more at http://www.sciencemag.org/sciext/singlemolecules/#section_in-stke
From genes to functional classes in the study of biological systems
With the popularisation of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed. FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.
