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dc.contributor.authorBuchanan, B.C.
dc.contributor.authorSafavinia, B.
dc.contributor.authorWu, L.
dc.contributor.authorYoon, J.-Y.
dc.date.accessioned2022-07-08T21:36:27Z
dc.date.available2022-07-08T21:36:27Z
dc.date.issued2022
dc.identifier.citationBuchanan, B. C., Safavinia, B., Wu, L., & Yoon, J.-Y. (2022). Smartphone-based autofluorescence imaging to detect bacterial species on laboratory surfaces. Analyst.
dc.identifier.issn0003-2654
dc.identifier.pmid35648102
dc.identifier.doi10.1039/d2an00358a
dc.identifier.urihttp://hdl.handle.net/10150/665324
dc.description.abstractThe potential of bacterial contamination is commonly seen in biological and clinical laboratory surfaces, creating a need to detect the presence of bacteria on a surface. Various bacterial species have been found to naturally exist on surfaces, including Escherichia coli, Salmonella Typhimurium, and Staphylococcus aureus that were investigated in this study. Bacterial presence was identified from laboratory surfaces using a smartphone and low-cost components without culturing or staining. Autofluorescence from bacteria was quantified using a 405 nm LED as an excitation light source. A low-cost acrylic film could isolate the autofluorescence emission. ImageJ was used to process and analyze the images and quantify the emitted autofluorescence signal. This imaging platform successfully detected the presence of all three bacterial species from the heavily used laboratory surfaces. A trend of decreasing fluorescence signal was observed with decreasing bacterial concentration, and the limit of detection was 104 CFU cm−2. It could also distinguish from tap water, protein (bovine serum albumin), and NaCl solutions. This preliminary work emphasizes the ability to detect autofluorescence signals of bacteria and non-microbial surface contaminants using a cost-effective and straightforward imaging platform. © 2022 The Royal Society of Chemistry
dc.language.isoen
dc.publisherRoyal Society of Chemistry
dc.rightsCopyright © 2022 The Author(s). This journal is copyright the Royal Society of Chemistry.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.titleSmartphone-based autofluorescence imaging to detect bacterial species on laboratory surfaces
dc.typeArticle
dc.typetext
dc.contributor.departmentDepartment of Biomedical Engineering, The University of Arizona
dc.identifier.journalAnalyst
dc.description.note12 month embargo; first published: 24 May 2022
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleAnalyst


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