In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks.
Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis.



Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous.



The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.
Department of General Biology, Instituto de Ciências Biológicas (ICB), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.|Institute of Biological Sciences, Federal University of Para, Belém, PA, Brazil.|Biotechnology Center (CBiotec), Federal University of Paraiba (UFPB), João Pessoa, Brazil.
Edson Luiz
EL
Folador
Department of General Biology, Instituto de Ciências Biológicas (ICB), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.|Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.
Paulo Vinícius Sanches Daltro
PV
de Carvalho
Department of General Biology, Instituto de Ciências Biológicas (ICB), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
Wanderson Marques
WM
Silva
Department of Biochemistry and Immunology, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
Rafaela Salgado
RS
Ferreira
Institute of Biological Sciences, Federal University of Para, Belém, PA, Brazil.
Artur
A
Silva
Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Tamilnadu, India.
Michael
M
Gromiha
Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
Preetam
P
Ghosh
Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, West Bengal, India.
Debmalya
D
Barh
Department of General Biology, Instituto de Ciências Biológicas (ICB), Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil.
Vasco
V
Azevedo
Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark. roettger@imada.sdu.dk.
Richard
R
Röttger
D001426:Bacterial Proteins / Q000378:metabolism*; D003198:Computer Simulation; D016925:Corynebacterium pseudotuberculosis / Q000378:metabolism*; D025941:Protein Interaction Mapping / Q000379:methods*
D001426:Bacterial Proteins
Corynebacterium pseudotuberculosis; Essential proteins; Protein-protein interaction network