Development of an in silico method for the identification of subcomplexes involved in the biogenesis of multiprotein complexes in Saccharomyces cerevisiae

Mitochondrial citrate transporters Ctp1-Yhm2 and respiratory chain: A coordinated functional connection in Saccharomyces cerevisiae metabolism

The mitochondrial inner membrane contains some hydrophobic proteins that mediate the exchange of metabolites between the mitochondrial matrix and the cytosol. Ctp1 and Yhm2 are two carrier proteins in the yeast Saccharomyces cerevisiae responsible for the transport of citrate, a tricarboxylate involved in several metabolic pathways. Since these proteins also contribute to respiratory metabolism, in this study we investigated for the first time whether changes in citrate transport can affect the structural organization and functional properties of respiratory complexes. Through experiments in yeast mutant cells in which the gene encoding Ctp1 or Yhm2 was deleted, we found that in the absence of either mitochondrial citrate transporter, mitochondrial respiration was impaired. Structural analysis of the respiratory complexes III and IV revealed different expression levels of the catalytic and supernumerary subunits in the Δctp1 and Δyhm2 strains. In addition, Δyhm2 mitochondria appeared to be more sensitive than Δctp1 to the oxidative damage. Our results provide the first evidence for a coordinated modulation of mitochondrial citrate transport and respiratory chain activity in S. cerevisiae metabolism.

APPINetwork: an R package for building and computational analysis of protein-protein interaction networks

Background

Protein-protein interactions (PPIs) are essential to almost every process in a cell. Analysis of PPI networks gives insights into the functional relationships among proteins and may reveal important hub proteins and sub-networks corresponding to functional modules. Several good tools have been developed for PPI network analysis but they have certain limitations. Most tools are suited for studying PPI in only a small number of model species, and do not allow second-order networks to be built, or offer relevant functions for their analysis. To overcome these limitations, we have developed APPINetwork (Analysis of Protein-protein Interaction Networks). The aim was to produce a generic and user-friendly package for building and analyzing a PPI network involving proteins of interest from any species as long they are stored in a database.

Methods

APPINetwork is an open-source R package. It can be downloaded and installed on the collaborative development platform GitLab (https://forgemia.inra.fr/GNet/appinetwork). A graphical user interface facilitates its use. Graphical windows, buttons, and scroll bars allow the user to select or enter an organism name, choose data files and network parameters or methods dedicated to network analysis. All functions are implemented in R, except for the script identifying all proteins involved in the same biological process (developed in C) and the scripts formatting the BioGRID data file and generating the IDs correspondence file (implemented in Python 3). PPI information comes from private resources or different public databases (such as IntAct, BioGRID, and iRefIndex). The package can be deployed on Linux and macOS operating systems (OS). Deployment on Windows is possible but it requires the prior installation of Rtools and Python 3.

Results

APPINetwork allows the user to build a PPI network from selected public databases and add their own PPI data. In this network, the proteins have unique identifiers resulting from the standardization of the different identifiers specific to each database. In addition to the construction of the first-order network, APPINetwork offers the possibility of building a second-order network centered on the proteins of interest (proteins known for their role in the biological process studied or subunits of a complex protein) and provides the number and type of experiments that have highlighted each PPI, as well as references to articles containing experimental evidence.

Conclusion

More than a tool for PPI network building, APPINetwork enables the analysis of the resultant network, by searching either for the community of proteins involved in the same biological process or for the assembly intermediates of a protein complex. Results of these analyses are provided in easily exportable files. Examples files and a user manual describing each step of the process come with the package.