Genomic Engineering Group / InteLAB
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Tuesday, 14 July 2020
Systems Biology
Systems biology is a fast growing subject that is currently being reshaped after whole-genome data is becoming available. SB projects are now aiming to reconstruct full organism metabolic networks, based on genomics, metabolomics and fluxomics tools. In our laboratory we are currently interested in the study of small (sub-nets) metabolic-regulatory networks, using some basic models to advance our understanding on how to put together metabolism and gene expression regulation.

  • Bioinformatics  ( 3 items )

    Bioinformatics and computational biology present a set of tools and techniques useful to solve biologial problems usually on the molecular level. Post-genome bioinformatics makes extensive use of genomic information (from sequenced genomes), mostly to compare two or more sequences (of nucleotides or amino acids), in order to find similarities and differences. Based on such comparisons, homologies may be assigned, and functional correlations may be attributed.It is a bioinformatics dogma that sequence correlations are associated with functional correlations. More interesting, structural similarities are usually associated with functional properties, thus providing evidence of biological activity.In our group we extensively use comparative genomics to study regulatory proteins and enzyme functions. In particular, we are interested in transcription factor binding sites (located in non-coding regions of the DNA) and polymerization sites of bacterial enzymes. Other tools have been used to characterize full metabolic (genome-wide) pathways and to find gene structure (operons and regulations).

  • Metabolic Engineering  ( 3 items )

    Metabolic engineering is referred to as the directed improvement of cellular properties through the modification of specific biochemical reactions or the introduction of new ones, with the use of recombinant DNA technology.

    Metabolic flux analysis (MFA) is the determination and study of metabolic fluxes either in vivo or in silico. The result is a flux map that shows the flux distribution over the metabolic network. The analysis is based on a mathematical model and in finding its solution. The resulting linear system of algebraic equations represents the stoichiometry of the corresponding set of biochemical reactions.

  • Regulatory Networks  ( 1 items )

    A central issue of post-genomic studies is to understand (and eventually control) how gene expression is regulated. Gene expression at a particular time and space is a delicate balance that obeys well established biochemical, i.e., physico-chemical rules, in a dynamic fashion, sustained away but not far from thermodynamic equilibrium conditions. Although genome-wide genetic circuitry is important in the establishment of how genes are expressed in response to environmental and internal variations (Remember: genes are commonly expressed in groups, or waves, also in response to internal gradients), state-of-the-art does not yet allow extensively study of more than a few genes interacting simultaneously. Typically, genes are expressed continuously, but on-off approaches are usually good enough to support biological hypothesis. We have used Petri net methodology to study regulatory-metabolic networks, in conjunction with logistic (discrete) models. As to our knowledge this was the first time Petri nets were used to study regulatory+metabolic networks. A case study modeling tryptophan biosynthesis in E. coli has been used to successfully test the methodology.

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