# test_basic¶

Perform basic tests on an instance of cobra.Model.

## Module Contents¶

test_basic.test_model_id_presence(model)[source]

Expect that the model has an identifier.

The MIRIAM guidelines require a model to be identified via an ID. Further, the ID will be displayed on the memote snapshot report, which helps to distinguish the output clearly.

Implementation: Check if the cobra.Model object has a non-empty “id” attribute, this value is parsed from the “id” attribute of the <model> tag in the SBML file e.g. <model fbc:strict=”true” id=”iJO1366”>.

test_basic.test_genes_presence(model)[source]

Expect that at least one gene is defined in the model.

A metabolic model can still be a useful tool without any genes, however there are certain methods which rely on the presence of genes and, more importantly, the corresponding gene-protein-reaction rules. This test requires that there is at least one gene defined.

Implementation: Check if the cobra.Model object has non-empty “genes” attribute, this list is populated from the list of fbc:listOfGeneProducts which should contain at least one fbc:geneProduct.

test_basic.test_reactions_presence(model)[source]

Expect that at least one reaction is defined in the model.

To be useful a metabolic model should consist at least of a few reactions. This test simply checks if there are more than zero reactions.

Implementation: Check if the cobra.Model object has non-empty “reactions” attribute, this list is populated from the list of sbml:listOfReactions which should contain at least one sbml:reaction.

test_basic.test_metabolites_presence(model)[source]

Expect that at least one metabolite is defined in the model.

To be useful a metabolic model should consist at least of a few metabolites that are converted by reactions. This test simply checks if there are more than zero metabolites.

Implementation: Check if the cobra.Model object has non-empty “metabolites” attribute, this list is populated from the list of sbml:listOfSpecies which should contain at least one sbml:species.

test_basic.test_metabolites_formula_presence(model)[source]

Expect all metabolites to have a formula.

To be able to ensure that reactions are mass-balanced, all model metabolites ought to be provided with a chemical formula. Since it may be difficult to obtain formulas for certain metabolites this test serves as a mere report. Models can still be stoichiometrically consistent even when chemical formulas are not defined for each metabolite.

Implementation: Check if each cobra.Metabolite has a non-empty “formula” attribute. This attribute is set by the parser if there is an fbc:chemicalFormula attribute for the corresponding species in the SBML.

test_basic.test_metabolites_charge_presence(model)[source]

Expect all metabolites to have charge information.

To be able to ensure that reactions are charge-balanced, all model metabolites ought to be provided with a charge. Since it may be difficult to obtain charges for certain metabolites this test serves as a mere report. Models can still be stoichiometrically consistent even when charge information is not defined for each metabolite.

Implementation: Check if each cobra.Metabolite has a non-empty “charge” attribute. This attribute is set by the parser if there is an fbc:charge attribute for the corresponding species in the SBML.

test_basic.test_gene_protein_reaction_rule_presence(model)[source]

Expect all non-exchange reactions to have a GPR rule.

Gene-Protein-Reaction rules express which gene has what function. The presence of this annotation is important to justify the existence of reactions in the model, and is required to conduct in silico gene deletion studies. However, reactions without GPR may also be valid: Spontaneous reactions, or known reactions with yet undiscovered genes likely lack GPR.

Implementation: Check if each cobra.Reaction has a non-empty “gene_reaction_rule” attribute, which is set by the parser if there is an fbc:geneProductAssociation defined for the corresponding reaction in the SBML.

test_basic.test_ngam_presence(model)[source]

Expect a single non growth-associated maintenance reaction.

The Non-Growth Associated Maintenance reaction (NGAM) is an ATP-hydrolysis reaction added to metabolic models to represent energy expenses that the cell invests in continuous processes independent of the growth rate. Memote tries to infer this reaction from a list of buzzwords, and the stoichiometry and components of a simple ATP-hydrolysis reaction.

Implementation: From the list of all reactions that convert ATP to ADP select the reactions that match the irreversible reaction “ATP + H2O -> ADP + HO4P + H+”, whose metabolites are situated within the main model compartment. The main model compartment is assumed to be the cytosol, yet, if that cannot be identified, it is assumed to be the compartment with the most metabolites. The resulting list of reactions is then filtered further by attempting to match the reaction name with any of the following buzzwords (‘maintenance’, ‘atpm’, ‘requirement’, ‘ngam’, ‘non-growth’, ‘associated’). If this is possible only the filtered reactions are returned, if not the list is returned as is.

test_basic.test_metabolic_coverage(model)[source]

Expect a model to have a metabolic coverage >= 1.

The degree of metabolic coverage indicates the modeling detail of a given reconstruction calculated by dividing the total amount of reactions by the amount of genes. Models with a ‘high level of modeling detail have ratios >1, and models with a low level of detail have ratios <1. This difference arises as models with basic or intermediate levels of detail are assumed to include many reactions in which several gene products and their enzymatic transformations are ‘lumped’.

Implementation: Divides the amount reactions by the amount of genes. Raises an error if the model does not contain either reactions or genes.

test_basic.test_compartments_presence(model)[source]

Expect that two or more compartments are defined in the model.

While simplified metabolic models may be perfectly viable, generally across the tree of life organisms contain at least one distinct compartment: the cytosol or cytoplasm. In the case of prokaryotes there is usually a periplasm, and eurkaryotes are more complex. In addition to the internal compartment, a metabolic model also reflects the extracellular environment i.e. the medium/ metabolic context in which the modelled cells grow. Hence, in total, at least two compartments can be expected from a metabolic model.

Implementation: Check if the cobra.Model object has a non-empty “compartments” attribute, this list is populated from the list of sbml:listOfCompartments which should contain at least two sbml:compartment elements.

test_basic.test_protein_complex_presence(model)[source]

Expect that more than one enzyme complex is present in the model.

Based on the gene-protein-reaction (GPR) rules, it is possible to infer whether a reaction is catalyzed by a single gene product, isozymes or by a heteromeric protein complex. This test checks that at least one such heteromeric protein complex is defined in any GPR of the model. For S. cerevisiae it could be shown that “essential proteins tend to [cluster] together in essential complexes” (https://doi.org/10.1074%2Fmcp.M800490-MCP200).

This might also be a relevant metric for other organisms.

Implementation: Identify GPRs which contain at least one logical AND that combines two different gene products.

test_basic.test_find_pure_metabolic_reactions(model)[source]

Expect at least one pure metabolic reaction to be defined in the model.

If a reaction is neither a transport reaction, a biomass reaction nor a boundary reaction, it is counted as a purely metabolic reaction. This test requires the presence of metabolite formula to be able to identify transport reactions. This test is passed when the model contains at least one purely metabolic reaction i.e. a conversion of one metabolite into another.

Implementation: From the list of all reactions, those that are boundary, transport and biomass reactions are removed and the remainder assumed to be pure metabolic reactions. Boundary reactions are identified using the attribute cobra.Model.boundary. Please read the description of “Transport Reactions” and “Biomass Reaction Identified” to learn how they are identified.

test_basic.test_find_constrained_pure_metabolic_reactions(model)[source]

Expect zero or more purely metabolic reactions to have fixed constraints.

If a reaction is neither a transport reaction, a biomass reaction nor a boundary reaction, it is counted as a purely metabolic reaction. This test requires the presence of metabolite formula to be able to identify transport reactions. This test simply reports the number of purely metabolic reactions that have fixed constraints and does not have any mandatory ‘pass’ criteria.

Implementation: From the pool of pure metabolic reactions identify reactions which are constrained to values other than the model’s minimal or maximal possible bounds.

test_basic.test_find_transport_reactions(model)[source]

Expect >= 1 transport reactions are present in the model.

Cellular metabolism in any organism usually involves the transport of metabolites across a lipid bi-layer. This test reports how many of these reactions, which transports metabolites from one compartment to another, are present in the model, as at least one transport reaction must be present for cells to take up nutrients and/or excrete waste.

Implementation: A transport reaction is defined as follows: 1. It contains metabolites from at least 2 compartments and 2. at least 1 metabolite undergoes no chemical reaction, i.e., the formula and/or annotation stays the same on both sides of the equation.

A notable exception is transport via PTS, which also contains the following restriction: 3. The transported metabolite(s) are transported into a compartment through the exchange of a phosphate.

An example of transport via PTS would be pep(c) + glucose(e) -> glucose-6-phosphate(c) + pyr(c)

Reactions similar to transport via PTS (referred to as “modified transport reactions”) follow a similar pattern: A(x) + B-R(y) -> A-R(y) + B(y)

Such modified transport reactions can be detected, but only when the formula is defined for all metabolites in a particular reaction. If this is not the case, transport reactions are identified through annotations, which cannot detect modified transport reactions.

test_basic.test_find_constrained_transport_reactions(model)[source]

Expect zero or more transport reactions to have fixed constraints.

Cellular metabolism in any organism usually involves the transport of metabolites across a lipid bi-layer. Hence, this test reports how many of these reactions, which transports metabolites from one compartment to another, have fixed constraints. This test does not have any mandatory ‘pass’ criteria.

Implementation: Please refer to “Transport Reactions” for details on how memote identifies transport reactions. From the pool of transport reactions identify reactions which are constrained to values other than the model’s median lower and upper bounds.

test_basic.test_transport_reaction_gpr_presence(model)[source]

Expect a small fraction of transport reactions not to have a GPR rule.

As it is hard to identify the exact transport processes within a cell, transport reactions are often added purely for modeling purposes. Highlighting where assumptions have been made versus where there is proof may help direct the efforts to improve transport and transport energetics of the tested metabolic model. However, transport reactions without GPR may also be valid: Diffusion, or known reactions with yet undiscovered genes likely lack GPR.

Implementation: Check which cobra.Reactions classified as transport reactions have a non-empty “gene_reaction_rule” attribute.

test_basic.test_find_reversible_oxygen_reactions(model)[source]

Expect zero or more oxygen-containing reactions to be reversible.

The directionality of oxygen-producing/-consuming reactions affects the model’s ability to grow anaerobically i.e. create faux-anaerobic organisms. This test reports how many of these oxygen-containing reactions are reversible. This test does not have any mandatory ‘pass’ criteria.

Implementation: First, find the metabolite representing atmospheric oxygen in the model on the basis of an internal mapping table or by specifically looking for the formula “O2”. Then, find all reactions that produce or consume oxygen and report those that are reversible.

test_basic.test_find_unique_metabolites(model)[source]

Expect there to be less metabolites when removing compartment tag.

Metabolites may be transported into different compartments, which means that in a compartimentalized model the number of metabolites may be much higher than in a model with no compartments. This test counts only one occurrence of each metabolite and returns this as the number of unique metabolites. The test expects that the model is compartimentalized, and thus, that the number of unique metabolites is generally lower than the total number of metabolites.

Implementation: Reduce the list of metabolites to a unique set by removing the compartment tag. The cobrapy SBML parser adds compartment tags to each metabolite ID.

test_basic.test_find_duplicate_metabolites_in_compartments(model)[source]

Expect there to be zero duplicate metabolites in the same compartments.

The main reason for having this test is to help cleaning up merged models or models from automated reconstruction pipelines as these are prone to having identical metabolites from different namespaces (hence different IDs). This test therefore expects that every metabolite in any particular compartment has unique inchikey values.

Implementation: Identifies duplicate metabolites in each compartment by determining if any two metabolites have identical InChI-key annotations. For instance, this function would find compounds with IDs ATP1 and ATP2 in the cytosolic compartment, with both having the same InChI annotations.

test_basic.test_find_reactions_with_partially_identical_annotations(model)[source]

Expect there to be zero duplicate reactions.

Identify reactions in a pairwise manner that are annotated with identical database references. This does not take into account a reaction’s directionality or compartment.

The main reason for having this test is to help cleaning up merged models or models from automated reconstruction pipelines as these are prone to having identical reactions with identifiers from different namespaces. It could also be useful to identify a ‘type’ of reaction that occurs in several compartments.

Implementation:

Identify duplicate reactions globally by checking if any two metabolic reactions have the same entries in their annotation attributes. The heuristic looks at annotations with the keys “metanetx.reaction”, “kegg.reaction”, “brenda”, “rhea”, “biocyc”, “bigg.reaction” only.

test_basic.test_find_duplicate_reactions(model)[source]

Expect there to be zero duplicate reactions.

Identify reactions in a pairwise manner that use the same set of metabolites including potentially duplicate metabolites. Moreover, it will take a reaction’s directionality and compartment into account.

The main reason for having this test is to help cleaning up merged models or models from automated reconstruction pipelines as these are prone to having identical reactions with identifiers from different namespaces.

Implementation:

Compare reactions in a pairwise manner. For each reaction, the metabolite annotations are checked for a description of the structure (via InChI and InChIKey).If they exist, substrates and products as well as the stoichiometries of any reaction pair are compared. Only reactions where the substrates, products, stoichiometry and reversibility are identical are considered to be duplicates. This test will not be able to identify duplicate reactions if there are no structure annotations. Further, it will report reactions with differing bounds as equal if they otherwise match the above conditions.

test_basic.test_find_reactions_with_identical_genes(model)[source]

Expect there to be zero duplicate reactions.

Identify reactions in a pairwise manner that use identical sets of genes. It does not take into account a reaction’s directionality, compartment, metabolites or annotations.

The main reason for having this test is to help cleaning up merged models or models from automated reconstruction pipelines as these are prone to having identical reactions with identifiers from different namespaces.

Implementation:

Compare reactions in a pairwise manner and group reactions whose genes are identical. Skip reactions with missing genes.

test_basic.test_find_medium_metabolites(model)[source]

Expect zero or more metabolites to be set as medium.

This test checks all boundary reactions in the model that permit flux towards creating a metabolite, and reports those metabolites. This test does not have any mandatory ‘pass’ criteria.

Implementation: Identify the metabolite IDs of each reaction in the method cobra.Model.medium. Model.medium returns exchange reactions whose bounds permit the uptake of metabolites.