Bioinformatics computation of metabolic models from sequenced genomes

Abstract

In the early days of the human genome project (HGP), during the late 1980s and early 1990s, there was skepticism that the genome project would produce biologically meaningful information. The reality is that bioinformatics has allowed us to extract far more biology from sequenced genomes than any published predictions in the early 1990s. Thanks to the efforts of many researchers in several subfields of bioinformatics, we can now process a sequenced genome through a series of computations to produce a quantitative metabolic flux model. Thus, surprisingly, bioinformatics has achieved what might have been held up as a holy grail of the field, before the goal was even articulated.

Developing computational biology at meridian 23° E, and a little eastwards

“…On the fundamental research front, we are actively working on a number of projects, including phylogenetic profiling [ 2 ], metabolic pathway analysis [ 3 ], ancestral state reconstructions [ 4 ] and radiation exposomics [ 5 ]—which are briefly presented below.…”

“…Thanks to the vast amounts of genomic data obtained over the past 20 years, a wide range of efficient algorithms and well-established methods and workflows, we are now able to process a sequenced genome through a series of computational steps to produce a quantitative metabolic flux model [ 3 ]. These steps produce a steady-state model, with constant concentrations and balanced fluxes of reactants and products; these reactions are expressed as a set of constraint equations and submitted to linear optimization in order to maximize biomass production [ 3 ]. This computational technique, while still in development, allows massive experiments on a genome scale for the design or modification of organisms for biotechnology and bioengineering.…”

Population FBA predicts metabolic phenotypes in yeast

“…By imposing constraints on the flux allowable through certain reactions (such as substrate uptake reactions, or reactions catalyzed by mutated, knocked-out, or low-copy number enzymes), different environments, genetic perturbations, or gene expression states can be modeled. The use of FBA and related techniques has grown to include a large user-base that actively contributes to the development of both methods and models, and metabolic reconstructions now exist for a variety of model organisms ranging from bacteria and yeast up through humans [ 11 – 15 ]. A particularly vibrant area of research in the field has been the use of large -omics data sets to constrain models in ways that reflect the influence of the cell’s regulatory machinery.…”