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arXiv · 1911.06950

Highly Sensitive and Label-free Digital Detection of Whole Cell E. coli with Interferometric Reflectance Imaging

Negin Zaraee·Fulya Ekiz kanik·Abdul Muyeed Bhuiya·Emily S. Gong·Matthew T. Geib·Nese Lortlar Ünlü·Ayca Yalcin Ozkumur·Julia R. Dupuis·M. Selim Ünlü
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Abstract

Bacterial infectious diseases are a major threat to human health. Timely and sensitive pathogenic bacteria detection is crucial in identifying the bacterial contaminations and preventing the spread of infectious diseases. Due to limitations of conventional bacteria detection techniques there have been concerted research efforts towards development of new biosensors. Biosensors offering label free, whole bacteria detection are highly desirable over those relying on label based or pathogenic molecular components detection. The major advantage is eliminating the additional time and cost required for labeling or extracting the desired bacterial components. Here, we demonstrate rapid, sensitive and label free E. coli detection utilizing interferometric reflectance imaging enhancement allowing for visualizing individual pathogens captured on the surface. Enabled by our ability to count individual bacteria on a large sensor surface, we demonstrate a limit of detection of 2.2 CFU/ml from a buffer solution with no sample preparation. To the best of our knowledge, this high level of sensitivity for whole E. coli detection is unprecedented in label free biosensing. The specificity of our biosensor is validated by comparing the response to target bacteria E. coli and non target bacteria S. aureus, K. pneumonia and P. aeruginosa. The biosensor performance in tap water also proves that its detection capability is unaffected by the sample complexity. Furthermore, our sensor platform provides high optical magnification imaging and thus validation of recorded detection events as the target bacteria based on morphological characterization. Therefore, our sensitive and label free detection method offers new perspectives for direct bacterial detection in real matrices and clinical samples.

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Negin Zaraee, Fulya Ekiz kanik, Abdul Muyeed Bhuiya, Emily S. Gong, Matthew T. Geib, Nese Lortlar Ünlü, Ayca Yalcin Ozkumur, Julia R. Dupuis, M. Selim Ünlü. 2019-11-16. Highly Sensitive and Label-free Digital Detection of Whole Cell E. coli with Interferometric Reflectance Imaging. https://doi.org/10.1016/j.bios.2020.112258

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