Practical 2

Building a model from MetaCyc

Our aim is to construct a model of the Entner-Doudoroff pathway of glycolysis in the natural ethanol-fermenting organism Zymomonas mobilis. If time permits, we will later use this as a basis to explore whether the substrate range of this organism could be expanded by metabolic engineering. For some background to this, you can find two articles here and here.

For this, we will use the ScrumPy module PyoCyc to extract the required reaction equations from a local copy of the MetaCyc database, starting from a list of the enzyme EC numbers. We will write the reactions into a ScrumPy file, which can then be loaded into ScrumPy and investigated. Of course, this automatically-generated model will not immediately work, for reasons such as different identifiers being used for the same metabolite in different reactions. In addition, the reaction list will contain reactions that will not take place in connection with the Entner-Doudoroff pathway because their substrates are not available in the cell.

Your task is to get the model to work so there is a viable route from glucose to ethanol, and to condense it so that only relevant reactions are present.

Step 1

Download, by right-clicking on its link, the ScrumPy file Zymomonas.spy and save it in the directory you are going to use for this exercise.
Open the model file with ScrumPy. Note that there are some generic components of the model here that we are giving you as a starting point:
1. An Include directive that is currently commented out but which will be needed to incorporate the reactions you are going to find.
2. A statement that WATER and PROTONS are regarded as external, freely-available species. Balancing every last PROTON is hard, so we're not going to struggle with that yet.
3. A set of transporter definitions that state that glucose (GLC), ethanol (ETOH) and carbon dioxide can exchange between the metabolism and the environment.
4. Two reaction definitions that cannot be retrieved from their EC numbers in the MetaCyc data files, even though they are present.

Step 2

Open PyoCyc and load the MetaCyc database by typing the following in your ScrumPy window:
```
from Bioinf import PyoCyc
db = PyoCyc.Organism()
```
Note that though you've loaded the generic MetaCyc, you could in principal load any BioCyc format organism database.

Copy this list of EC numbers for the Entner-Doudoroff pathway:

ecs=['EC-2.7.1.2', 'EC-3.1.1.31', 'EC-4.2.1.12', 'EC-4.1.2.14','EC-1.1.1.44',  'EC-1.2.1.12', 'EC-2.7.2.3', 'EC-5.4.2.11', 'EC-4.2.1.11', 'EC-2.7.1.40', 'EC-4.1.1.1', 'EC-1.1.1.1']

You can see the set of reactions associated with each EC number with the following code:
```
for e in ecs:
        for r in db[e]:
                print e, "\n", r.AsScrumPy()
```
Here, each EC number in turn is used as a key, e into the database, which returns a set of reaction records. The method AsScrumPy formats the record as required for the input file.
You need to generate an input file though, so enter the following:
```
spy=open("ZmED.spy","w")
spy.write('# Entner Duodoroff pathway\n')
for e in ecs:
    str = "# " + e +"\n"
    for r in db[e]:
            spy.write(str)
            spy.write(r.AsScrumPy())

spy.close()
```
- After opening the file, ZmED.spy, the first write statement puts an identifying comment in. Then for each EC number, a comment is inserted giving the EC number, since this often doesn't appear in the reaction name.

Step 3

Un-comment the Include directive in the Zymomonas.spy file to load your ZmED.spy and recompile the model using the drop-down ScrumPy menu option. Find out if there is a potential pathway through it by calculating the null space of the stoichiometry matrix:
```
ns = m.sm.NullSpace()
ns
```
- Two windows should now be open, one for Zymomonas.spy and one for ZmED.spy. However, the null space is empty, in other words the system defined by this model cannot support a stead-state flux in any of its reactions.
The common possibilities for the lack of a viable route where there should be one are either missing reactions, or, when all the reactions are present, inconsistencies in metabolite definitions break the connectivity. Looking for dangling (orphan) metabolites can point to both of these issues:
```
m.sm.OrphanMets()
```
If the network connectivity is being broken by inconsistent metabolite naming, edit ZmED.spy, save it, and recompile the model. Then check the null space and orphan metabolites again.
Once you get one or more null space vectors, you can compute the elementary modes of the model and the stoichiometry of their overall reaction to check whether you have the exected conversion of glucose to ethanol.
The model can now be reduced by removing reactions that will always be dead. Calculate the enzyme subsets of the model; all the dead reactions will be in the "dead" subset. Rather than deleting the reactions immediately, remove them from the model by placing a comment marker, "#", at the start of each line belonging to an unwanted reaction. Recompile the model and check that you have not broken the network.
How many reactions are left in ZmED.spy when you have inactivated all the dead ones?

Step 4

Time permitting, go to the next part.