{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T01:34:55Z","timestamp":1784252095717,"version":"3.55.0"},"reference-count":21,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T00:00:00Z","timestamp":1689811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The clinical manifestation of leptospirosis is often misdiagnosed as other febrile illnesses such as dengue. Therefore, there is an urgent need for a precise diagnostic tool at the field level to detect the pathogenic Leptospira\u00a0lipL32 gene at the molecular level for prompt therapeutic decisions. Quantitative polymerase chain reaction (qPCR) is widely used as the primary diagnostic tool, but its applicability is limited by high equipment cost and the lack of availability in every hospital, especially in rural areas where leptospirosis mainly occurs. Here, we report the development of a CRISPR dFnCas9-based quantitative lateral flow immunoassay to detect the lipL32 gene. The developed assay showed superior performance regarding the lowest detectable limit of 1 fg\/mL. The test is highly sensitive and selective, showing that leptospirosis diagnosis can be achieved with a low-cost lateral flow device.<\/jats:p>","DOI":"10.3390\/s23146544","type":"journal-article","created":{"date-parts":[[2023,7,20]],"date-time":"2023-07-20T05:42:01Z","timestamp":1689831721000},"page":"6544","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Lateral Flow Assay for the Detection of Leptospira\u00a0lipL32 Gene Using CRISPR Technology"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1045-7472","authenticated-orcid":false,"given":"Satheesh","family":"Natarajan","sequence":"first","affiliation":[{"name":"Healthcare Technology Innovation Centre, Indian Institute of Technology Madras, Chennai 600113, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jayaraj","family":"Joseph","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7821-7427","authenticated-orcid":false,"given":"Balamurugan","family":"Vinayagamurthy","sequence":"additional","affiliation":[{"name":"Indian Council of Agricultural Research-National Institute of Veterinary Epidemiology and Disease Informatics (ICAR-NIVEDI), Bangalore 560064, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6956-1146","authenticated-orcid":false,"given":"Pedro","family":"Estrela","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK"},{"name":"Centre for Bioengineering & Biomedical Technologies, University of Bath, Bath BA2 7AY, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Costa, F., Hagan, J.E., Calcagno, J., Kane, M., Torgerson, P., Martinez-Silveira, M.S., Stein, C., Abela-Ridder, B., and Ko, A.I. 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