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Updated: Oct 16, 2026

Colorimetric Paper-based Detection of Escherichia coli, Salmonella spp., and Listeria monocytogenes from Large Volumes of Agricultural Water
Published on: June 9, 2014
Colourimetric LAMP detection of Escherichia coli in bovine milk using a simplified DNA preparation method
Tewodros Fentahun Jember1,2, Mark Edward Westman3, Sameer Dinkar Pant1,4
1Faculty of Science and Health, School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, Wagga Wagga, Australia.
Abstract:
Escherichia coli (E. coli) is a common cause of bovine mastitis, and rapid detection from milk is important for timely disease management. However, molecular assays such as colourimetric loop-mediated isothermal amplification (LAMP) are often limited by laboratory-based DNA extraction. This study evaluated a simplified HotSHOT (HS) DNA preparation method for extracting E. coli DNA from bovine milk and assessed its compatibility with colourimetric LAMP and conventional PCR. Pasteurised bovine milk spiked with E. coli was used for analytical evaluation, and culture‑positive clinical milk samples were tested to assess diagnostic performance. The HS method was compared with five commercial DNA extraction kits and a direct boiling method without centrifugation. Performance was assessed using limit of detection (LOD) expressed as colony-forming units per millilitre. Using the HS method, the LOD was 7.9 × 10⁴ CFU/mL for LAMP and 7.9 × 10³ CFU/mL for PCR. PCR performance of the HS method was comparable to the QIAamp and Norgen commercial kits, while LAMP sensitivity was ten- to a hundred-fold lower than the best kit-based methods. Direct boiling showed markedly reduced sensitivity, with an LOD of 7.9 × 10⁸ CFU/mL. Among 17 culture-confirmed clinical mastitis milk samples positive for E. coli, LAMP detected 15 (88.2%) and PCR detected all 17 (100%). These results show that simplified DNA preparation can support molecular detection of E. coli in bovine milk and provide a practical basis for future development of field-deployable diagnostics in resource-constrained settings.

