PNA-based microbial pathogen identification and resistance marker detection: an accurate, isothermal rapid assay based on genome-specific features.
With the rapidly growing availability of the entire genome sequences of microbial pathogens, there is unmet need for increasingly sensitive systems to monitor the gene-specific markers for diagnosis of bacteremia that enables an earlier detection of causative agent and determination of drug resistance. To address these challenges, a novel FISH-type genomic sequence-based molecular technique is proposed that can identify bacteria and simultaneously detect antibiotic resistance markers for rapid and accurate testing of pathogens. The approach is based on a synergistic combination of advanced Peptide Nucleic Acid (PNA)-based technology and signal-enhancing Rolling Circle Amplification (RCA) reaction to achieve a highly specific and sensitive assay. A specific PNA-DNA construct serves as an exceedingly selective and very effective biomarker, while RCA enhances detection sensitivity and provide with a highly multiplexed assay system. Distinct-color fluorescent decorator probes are used to identify about 20-nucleotide-long signature sequences in bacterial genomic DNA and/or key genetic markers of drug resistance in order to identify and characterize various pathogens. The technique's potential and its utility for clinical diagnostics are illustrated by identification of S. aureus with simultaneous discrimination of methicillin-sensitive (MSSA) versus methicillin-resistant (MRSA) strains. Overall these promising results hint to the adoption of PNA-based rapid sensitive detection for diagnosis of other clinically relevant organisms. Thereby, new assay enables significantly earlier administration of appropriate antimicrobial therapy and may, thus have a positive impact on the outcome of the patient.
Smolina
Irina
I
Center for Advanced Biotechnology and Department of Biomedical Engineering, Boston University, 36 Cummington St., Boston, MA 02215, USA.
Miller
Nancy S
NS
Frank-Kamenetskii
Maxim
M