Rocket-miR, a translational launchpad for miRNA-based antimicrobial drug development

Abstract

ABSTRACTDeveloping software tools that leverage biological data sets to accelerate drug discovery is an important aspect of bioinformatic research. Here, we present a novel example: a web application called Rocket-miR that applies an existing bioinformatic algorithm (IntaRNA) to predict cross-species miRNA-mRNA interactions and identify human miRNAs with potential antimicrobial activity against antibiotic-resistant bacterial infections. Rocket-miR is the logical extension of our prior finding that human miRNA let-7b-5p impairs the ability of the ubiquitous opportunistic pathogen Pseudomonas aeruginosa to form biofilms and resist the bactericidal effect of β-lactam antibiotics. Rocket-miR’s point and click interface enables researchers without programming expertise to predict additional human-miRNA-pathogen interactions. Identified miRNAs can be developed into novel antimicrobials effective against the 24 clinically relevant pathogens, implicated in diseases of the lung, gut, and other organs, that are included in the application. The paper incorporates three case studies contributed by microbiologists that study human pathogens to demonstrate the usefulness and usability of the application. Rocket-miR is accessible at the following link: http://scangeo.dartmouth.edu/RocketmiR/.IMPORTANCEAntimicrobial-resistant infections contribute to millions of deaths worldwide every year. In particular, the group of bacteria collectively known as ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter sp.) pathogens are of considerable medical concern due to their virulence and exceptional ability to develop antibiotic resistance. New kinds of antimicrobial therapies are urgently needed to treat patients for whom existing antibiotics are ineffective. The Rocket-miR application predicts targets of human miRNAs in bacterial and fungal pathogens, rapidly identifying candidate miRNA-based antimicrobials. The application’s target audience are microbiologists that have the laboratory resources to test the application’s predictions. The Rocket-miR application currently supports 24 recognized human pathogens that are relevant to numerous diseases including cystic fibrosis, chronic obstructive pulmonary disease (COPD), urinary tract infections, and pneumonia. Furthermore, the application code was designed to be easily extendible to other human pathogens that commonly cause hospital-acquired infections.

Keywords

• cystic fibrosis
• bioinformatics
• miRNA
• CF pathogens
• antimicrobial agents
• host-pathogen interactions