Once a genome has been annotated with functional roles, we can determine what chemical reactions those roles implement. For example, in B. subtilis, we annotated a gene with the functional role "Pyruvate kinase (EC 2.7.1.40)" or "Enolase". This, of course, maps directly to a reaction, converting Phosphoenolpyruvate into Pyruvate and generating one ATP in the process. Other reaction assignments are, of course, more difficult, requiring the presence of multiple genes to form enzyme complexes. Additionally, since chemically many reactions can proceed in either direction we must determine which directions are implemented by the organism.

You can manually edit your model, adding or removing reactions and changing reaction directionality, by uploading a new model file through the Model View page. See Model View Tutorial Part 6.

In the near future we hope to add the ability to add and remove reactions directly through the SEED website. Additionally, we will allow users to switch between different biomass objective functions and formulate new objective functions.

In Model View we allow you to model growth of your organism on different media conditions. These predictions are made using Flux balance analysis.

What does this entail? We start with a model, which is the network of metabolic and transport reactions an organism an perform and a biomass objective function, and add a media formulation, just a list of compounds and their concentrations. Then we use linear optimization techniques to solve for that biomass objective function. If we are able to solve the problem and produce biomass, we get a list of "fluxes" through reactions that tell us which parts of the cell's metabolism are being used.

You can run flux balance using the Model View pages. See Part 5 of the Model View Tutorial for details.

In the near future we will allow users to upload growth phenotype data. In it's basic form, this is simply whether or not an organism grew on a specific media.

Adding to this, we hope to allow for an number of complex phenotypes:

1. Phenotype of growth of organism strains where genes have been added or removed.
2. Gene-level microarray expression data on organisms and strains.

With these simple and complex phenotypes, hope to allow users to track how closely their models fit to observed results, allowing users to modify the organism model until predictions and observed phenotypes converge.

• Part 1
• Part 2
• Part 3
  

Once we have determined which reactions are implemented by an organism's annotated genes, we can construct the initial model: this is essentially a stoichiometric matrix and a biomass objective function, essentially the parts list that a cell needs to produce the biomass it needs to grow.

However, in most cases this model is not yet functional. If we attempt to grow it on complete media, i.e. LB, it will fail to produce all the parts needed for the biomass function. This is where model gap-filling comes in. We insert candidate transport and standard reactions until the cell successfully grows on complete media. These reactions are clearly labeled in the initial model. In the Model View Tutorial, you can search for gap-filled reactions in the Reaction table.

See Using Model View for details on viewing your initial model.

!Accessing your model from the RAST page