LAITOR4HPC: A text mining pipeline based on HPC for building interaction networks

Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context

At the heart of the cellular machinery through the regulation of cellular functions, protein-protein interactions (PPIs) have a significant role. PPIs can be analyzed with network approaches. Construction of a PPI network requires prediction of the interactions. All PPIs form a network. Different biases such as lack of data, recurrence of information, and false interactions make the network unstable. Integrated strategies allow solving these different challenges. These approaches have shown encouraging results for the understanding of molecular mechanisms, drug action mechanisms, and identification of target genes. In order to give more importance to an interaction, it is evaluated by different confidence scores. These scores allow the filtration of the network and thus facilitate the representation of the network, essential steps to the identification and understanding of molecular mechanisms. In this review, we will discuss the main computational methods for predicting PPI, including ones confirming an interaction as well as the integration of PPIs into a network, and we will discuss visualization of these complex data.

Cassava (Manihot esculenta) defensins: Prospection, structural analysis and tissue-specific expression under biotic/abiotic stresses

Defensins are a prominent family of antimicrobial peptides. They play sophisticated roles in the defense against pathogens in all living organisms, but few works address their expression under different conditions and plant tissues. The present work prospected defensins of Manihot esculenta Crantz, popularly known as cassava. Five defensin candidates (MeDefs) were retrieved from the genome sequences and characterized. Considering chromosome distribution, only MeDef1 and 2 occupy adjacent positions in the same chromosome arm. All 3D structures had antiparallel ß-sheets, an α-helix, and amphipathic residues distributed throughout the peptides with a predominance of cationic surface charge. MeDefs expression was validated by RT-qPCR, including two stress types (biotic: fungus Macrophomina pseudophaseolina, and abiotic: mechanical injury) and a combination of both stresses (fungus+injury) in three different tissues (root, stem, and leaf). For this purpose, ten reference genes (RGs) were tested, and three were chosen to characterize MeDef expression. MeDef3 was up-regulated at roots in all stress situations tested. MeDef1 and MeDef5 were induced in leaves under biotic and abiotic stresses, but not in both stress types simultaneously. Only MeDef2 was down-regulated in the stem tissue also with biotic/abiotic combined stresses. These results indicate that although defensins are known to be responsive to pathogen infection, they may act as preformed defense or, still, have tissue or stress specificities. Aspects of their structure, stability and evolution are also discussed.