Users primarily interested in using cameo as a tool
for enumerating metabolic engineering strategies have access to cameo's advanced programming interface via cameo.api
that provides access to potential products (cameo.api.products
), host organisms (cameo.api.hosts
) and
a configurable design function (cameo.api.design
). Running cameo.api.design
requires only minimal input and will run the following workflow.
Import the advanced interface.
from cameo import api
Search by trivial name.
api.products.search('caffeine')
InChI | SMILES | charge | formula | mass | name | source | search_rank | |
---|---|---|---|---|---|---|---|---|
MNXM680 | InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)... | CN1C=NC2=C1C(=O)N(C)C(=O)N2C | 0 | C8H10N4O2 | 194.1906 | caffeine | chebi:27732 | 0 |
Search by ChEBI ID.
api.products.search('chebi:27732')
InChI | SMILES | charge | formula | mass | name | source | search_rank | |
---|---|---|---|---|---|---|---|---|
MNXM680 | InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)... | CN1C=NC2=C1C(=O)N(C)C(=O)N2C | 0 | C8H10N4O2 | 194.1906 | caffeine | chebi:27732 | 0 |
Currently the following host organisms and respective models are available in cameo. More hosts and models will be added in the future (please get in touch with us if you'd like to get a particular host organism included).
for host in api.hosts:
for model in host.models:
print(host.name, model.id)
Escherichia coli iJO1366 Saccharomyces cerevisiae iMM904
For demonstration purposes, we'll set a few options to limit the computational time. Also we'll create a multiprocessing view to take advantage of multicore CPUs (strain design algorithms will be run in parallel for individually predicted heterologous pathways).
from cameo.parallel import MultiprocessingView
mp_view = MultiprocessingView()
Limit the number of predicted heterlogous pathways to 4.
api.design.options.max_pathway_predictions = 4
Set a time limit of 30 minutes on individual heuristic optimizations.
api.design.options.heuristic_optimization_timeout = 30
report = api.design(product='vanillin', view=mp_view)
Id | Name | Formula |
---|---|---|
MNXM754 | vanillin | C8H8O3 |
equation | lower_bound | upper_bound | |
---|---|---|---|
MNXR5340 | H(+) + NADH + O2 + vanillate <=> H2O + 3,4-dih... | -1000 | 1000 |
MNXR5336 | 2.0 H(+) + NADH + vanillate <=> H2O + vanillin... | -1000 | 1000 |
MNXR2795 | S-adenosyl-L-methionine + glycine <=> H(+) + S... | -1000 | 1000 |
MNXR68718 | H2O + 3,4-dihydroxybenzoate <=> 3-dehydroshiki... | -1000 | 1000 |
Max flux: 4.29196
equation | lower_bound | upper_bound | |
---|---|---|---|
MNXR5340 | H(+) + NADH + O2 + vanillate <=> H2O + 3,4-dih... | -1000 | 1000 |
MNXR5336 | 2.0 H(+) + NADH + vanillate <=> H2O + vanillin... | -1000 | 1000 |
MNXR84169 | (6R)-5,10-methylenetetrahydrofolate + glycine ... | -1000 | 1000 |
MNXR68718 | H2O + 3,4-dihydroxybenzoate <=> 3-dehydroshiki... | -1000 | 1000 |
Max flux: 7.28363
equation | lower_bound | upper_bound | |
---|---|---|---|
MNXR5340 | H(+) + NADH + O2 + vanillate <=> H2O + 3,4-dih... | -1000 | 1000 |
MNXR5336 | 2.0 H(+) + NADH + vanillate <=> H2O + vanillin... | -1000 | 1000 |
MNXR68718 | H2O + 3,4-dihydroxybenzoate <=> 3-dehydroshiki... | -1000 | 1000 |
MNXR651 | 2.0 H(+) + NADH + formate <=> H2O + formaldehy... | -1000 | 1000 |
Max flux: 7.58479
equation | lower_bound | upper_bound | |
---|---|---|---|
MNXR5340 | H(+) + NADH + O2 + vanillate <=> H2O + 3,4-dih... | -1000 | 1000 |
MNXR5336 | 2.0 H(+) + NADH + vanillate <=> H2O + vanillin... | -1000 | 1000 |
MNXR230 | H(+) + 4-hydroxybenzoate + O2 + NADPH <=> H2O ... | -1000 | 1000 |
MNXR640 | methanol + NAD(+) <=> H(+) + NADH + formaldehyde | -1000 | 1000 |
This is the format of your plot grid: [ (1,1) x1,y1 ] [ (1,2) x2,y2 ] [ (2,1) x3,y3 ] [ (2,2) x4,y4 ]