Modular microfluidic system fabricated in thermoplastics for the strain-specific detection of bacterial pathogens.

Abstract

The recent outbreaks of a lethal E. coli strain in Germany have aroused renewed interest in developing rapid, specific and accurate systems for detecting and characterizing bacterial pathogens in suspected contaminated food and/or water supplies. To address this need, we have designed, fabricated and tested an integrated modular-based microfluidic system and the accompanying assay for the strain-specific identification of bacterial pathogens. The system can carry out the entire molecular processing pipeline in a single disposable fluidic cartridge and detect single nucleotide variations in selected genes to allow for the identification of the bacterial species, even its strain with high specificity. The unique aspect of this fluidic cartridge is its modular format with task-specific modules interconnected to a fluidic motherboard to permit the selection of the target material. In addition, to minimize the amount of finishing steps for assembling the fluidic cartridge, many of the functional components were produced during the polymer molding step used to create the fluidic network. The operation of the cartridge was provided by electronic, mechanical, optical and hydraulic controls located off-chip and packaged into a small footprint instrument (1 ft(3)). The fluidic cartridge was capable of performing cell enrichment, cell lysis, solid-phase extraction (SPE) of genomic DNA, continuous flow (CF) PCR, CF ligase detection reaction (LDR) and universal DNA array readout. The cartridge was comprised of modules situated on a fluidic motherboard; the motherboard was made from polycarbonate, PC, and used for cell lysis, SPE, CF PCR and CF LDR. The modules were task-specific units and performed universal zip-code array readout or affinity enrichment of the target cells with both made from poly(methylmethacrylate), PMMA. Two genes, uidA and sipB/C, were used to discriminate between E. coli and Salmonella, and evaluated as a model system. Results showed that the fluidic system could successfully identify bacteria in <40 min with minimal operator intervention and perform strain identification, even from a mixed population with the target of a minority. We further demonstrated the ability to analyze the E. coli O157:H7 strain from a waste-water sample using enrichment followed by genotyping.