In saezlab/OmnipathR: OmniPath web service client and more

Introduction

The COSMOS PKN is a combination of the following datasets:

Genome-scale metabolic model (GEM) from Chalmers Sysbio (Wang et al., 2021.)
Network of chemical-protein interactions from STITCH (http://stitch.embl.de/)
Protein-protein interactions from Omnipath (Türei et al., 2021)

Building the PKN is possible in by calling the cosmos_pkn() function that we present in the last section. First let's take a closer look at each resource.

library(OmnipathR)

Chalmers Sysbio GEM

The Chalmers Sysbio group provides genome scale models of metabolism (GEMs) for various organisms: human, mouse, rat, fish, fly and worm. These models are available as Matlab files, which contain reaction data, stoichiometry matrix and identifier translation data.

The raw contents of the Matlab file can be loaded by chalmers_gem_raw(). This results in a convoluted structure of nested lists and arrays:

ch_raw <- chalmers_gem_raw()

Another function, chalmers_gem() processes the above structure into a data frame of reactions, also keeping the stoichiometry matrix and including the identifier translation data:

ch_processed <- chalmers_gem()
names(ch_processed)

The identifier translation tables are available by separate functions, chalmers_gem_metabolites() and chalmers_gem_reactions() for metabolite and reaction (and enzyme) identifiers, respectively. These return simple data frames.

ch_met <- chalmers_gem_metabolites()

ch_met

The metabolite identifier translation available here is also integrated into the package's translation service, available by the translate_ids and other functions.

translate_ids('MAM00001', 'metabolicatlas', 'recon3d', chalmers = TRUE)

Finally, the chalmers_gem_network() function uses all above data to compile a network binary chemical-protein interactions. By default Metabolic Atlas identifiers are used for the metabolites and Ensembl Gene IDs for the enzymes. These can be tranlated to the desired identifiers using the metabolite_ids and protein_ids arguments. Translation to multiple identifers is possible. The ri or record_id column in case of the Chalmers GEM represent the reaction ID, a unique identifier of the original reaction. One reaction yields many binary interactions as it consists of a number of gene products, reactants and products. The column ci means "complex ID", it is a unique identifier of groups of enzymes required together to carry out the reaction. The column reverse indicates if the row is derived from the reversed version of a reversible reaction. The column transporter signals reactions where the same metabolite occures both on reactant and product side, these are assumed to be transport reactions. In the Chalmers GEM the reactions are also assigned to compartments, these are encoded by single letter codes in the comp column. In the original data the compartment codes are postfixes of the metabolite IDs, here we move them into a separate column, leaving the Metabolic Atlas IDs clean and usable.

ch <- chalmers_gem_network()

ch

STITCH enzyme-metabolite interactions

STITCH is a large compendium of binary interactions between proteins and chemicals. Some of these are derived from metabolic reactions. Various attributes such as mode of action, effect sign and scores are assigned to each link. The datasets are available by organism, stored in "actions" and "links" tables, available by the stitch_actions() and stitch_links() functions, respectively. STITCH supports a broad variety of organisms, please refer to their website at (https://stitch.embl.de/).

sta <- stitch_actions()

sta

stl <- stitch_links()

stl

stitch_network() combines the actions and links data frames, filters by confidence scores, removes the prefixes from identifiers and translates them to the desired ID types. STITCH prefixes Ensembl Protein IDs with the NCBI Taxonomy ID, while PubChem CIDs with CID plus a lowercase letter "s" or "m", meaning stereo specific or merged stereoisomers, respectively. These prefixes are removed by default by the stitch_remove_prefixes() function. Effect signs (1 = activation, -1 = inhibition) and combined scores are aslo included in the data frame. Similarly to Chalmers GEM, translation of chemical and protein identifiers is available. The record_id column uniquely identifies the original records. Multiple rows with the same record_id are due to one-to-many identifier translation.

st <- stitch_network()

st

OmniPath signaling network

All parameters supported by the OmniPath web service (omnipath()) can be passed to omnipath_for_cosmos(), enabling precise control over the resources, interaction types and other options when preparing the signaling network from OmniPath. By default the "omnipath" dataset is included which contains high confidence, literature curated, causal protein-protein interactions. For human, mouse and rat, orthology translated data is retrieved from the web service, while for other organisms translation by orthologous gene pairs is carried out client side.

op <- omnipath_for_cosmos()

op

Complete build

Building the complete COSMOS PKN is done by cosmos_pkn(). All the resources above can be customized by arguments passed to this function. With all downloads and processing the build might take 30-40 minutes. Data is cached at various levels of processing, shortening processing times. With all data downloaded and HMDB ID translation data preprocessed, the build takes 3-4 minutes; the complete PKN is also saved in the cache, if this is available, loading it takes only a few seconds.

pkn <- cosmos_pkn()

pkn

The record_id column identifies the original records within each resource. If one record_id yields multiple records in the final data frame, it is the result of one-to-many ID translation or other processing steps. Before use, it is recommended to select one pair of ID type columns (by combining the preferred ones) and perform distinct by the identifier columns and sign. After the common columns, resource specific columns are labeled with the resource name; after these columns, molecule type and side specific identifer columns are named after the ID type and the side of the interaction ("source" vs. "target").