Jorge Paula, Pérez-Pérez Martín, Pérez Rodríguez Gael, Fdez-Riverola Florentino, Pereira Maria Olívia, Lourenço Anália
CEB - Centre of Biological Engineering LIBRO - Laboratory of Research in Biofilms Rosário Oliveira, University of Minho, Braga, Portugal.
ESEI - Department of Computer Science, University of Vigo, Ourense, Spain.
Database (Oxford). 2016 Dec 26;2016. doi: 10.1093/database/baw143. Print 2016.
Considerable research efforts are being invested in the development of novel antimicrobial therapies effective against the growing number of multi-drug resistant pathogens. Notably, the combination of different agents is increasingly explored as means to exploit and improve individual agent actions while minimizing microorganism resistance. Although there are several databases on antimicrobial agents, scientific literature is the primary source of information on experimental antimicrobial combination testing. This work presents a semi-automated database curation workflow that supports the mining of scientific literature and enables the reconstruction of recently documented antimicrobial combinations. Currently, the database contains data on antimicrobial combinations that have been experimentally tested against Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes and Candida albicans, which are prominent pathogenic organisms and are well-known for their wide and growing resistance to conventional antimicrobials. Researchers are able to explore the experimental results for a single organism or across organisms. Likewise, researchers may look into indirect network associations and identify new potential combinations to be tested. The database is available without charges.Database URL: http://sing.ei.uvigo.es/antimicrobialCombination/.
目前，大量的研究工作都投入到了新型抗菌疗法的开发中，这些疗法要能有效对抗越来越多的多重耐药病原体。值得注意的是，越来越多的研究开始探索不同药物的组合，以此来利用和增强单个药物的作用，同时将微生物耐药性降至最低。虽然有几个关于抗菌药物的数据库，但科学文献仍是实验性抗菌药物联合测试信息的主要来源。这项工作提出了一种半自动数据库管理工作流程，该流程支持科学文献的挖掘，并能重建最近记录的抗菌药物组合。目前，该数据库包含了针对铜绿假单胞菌、金黄色葡萄球菌、大肠杆菌、单核细胞增生李斯特菌和白色念珠菌进行过实验测试的抗菌药物组合数据，这些都是重要的致病生物，并且以对传统抗菌药物广泛且不断增加的耐药性而闻名。研究人员能够探索针对单一生物体或跨生物体的实验结果。同样，研究人员可以研究间接的网络关联，并识别有待测试的新的潜在组合。该数据库免费提供。数据库网址：http://sing.ei.uvigo.es/antimicrobialCombination/
