Author(s):
Jorge, Paula ; Pérez-Pérez, Martín ; Rodríguez, Gael Pérez ; Pereira, Maria Olívia ; Lourenço, Anália
Date: 2017
Persistent ID: https://hdl.handle.net/1822/47483
Origin: RepositóriUM - Universidade do Minho
Project/scholarship:
info:eu-repo/grantAgreement/FCT/5876/147337/PT;
info:eu-repo/grantAgreement/FCT/5876-PPCDTI/126270/PT
;
info:eu-repo/grantAgreement/FCT/COMPETE/126270/PT;
info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F88192%2F2012/PT;
Subject(s): Antimicrobial peptide combination; Bioinformatics; Network; Colistin; Polymyxin B; Nisin; Science & Technology
Description
Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.ijantimicag.2017.02.012.
Antimicrobial combinations involving antimicrobial peptides (AMPs) attract considerable attention within current antimicrobial and anti-resistance research. The objective of this study was to review the available scientific literature on the effects of antimicrobial combinations involving colistin (polymyxin E), polymyxin B and nisin, which are US Food and Drug Administration (FDA)-approved AMPs broadly tested against prominent multidrug-resistant pathogens. A bioinformatics approach based on literature mining and manual expert curation supported the reconstruction of experimental evidence on the potential of these AMP combinations, as described in the literature. Network analysis enabled further characterisation of the retrieved antimicrobial agents, targets and combinatory effects. This systematic analysis was able to output valuable information on the studies conducted on colistin, polymyxin B and nisin combinations. The reconstructed networks enable the traversal and browsing of a large number of agent combinations, providing comprehensive details on the organisms, modes of growth and methodologies used in the studies. Therefore, network analysis enables a bird's-eye view of current research trends as well as in-depth analysis of specific drugs, organisms and combinatory effects, according to particular user interests. The reconstructed knowledge networks are publicly accessible at http://sing-group.org/antimicrobialCombination/. Hopefully, this resource will help researchers to look into antimicrobial combinations more easily and systematically. User-customised queries may help to identify missing and less studied links and to generate new research hypotheses.
This work was supported by the Portuguese Foundation for Science and Technology(FCT)under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 [POCI01-0145-FEDER-006684] and BioTecNorte operation [NORTE-010145-FEDER-000004], funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte.The authors also acknowledge the support received from FCT and the European Community fund FEDER, through Program COMPETE, under the scope of the Project RECI/BBB-EBI/0179/2012 [FCOMP-01-0124-FEDER-027462],the[14VI05]Contract-Programme from the University of Vigo (Vigo, Spain), the INOU-16-05 project from the Provincial Council of Ourense, and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa [2012/273]. SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure. Finally, the authors acknowledge the PhD grant of Paula Jorge[Grant no. SFRH/BD/88192/2012],funded by FCT,thePhD grants of Martín Pérez-Pérez and Gael Pérez-Rodríguez, funded by the Xunta de Galicia and the University of Vigo, and the Research grant 2014 of Anália Lourenço by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID).
info:eu-repo/semantics/publishedVersion
