Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
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Rapid and highly sensitive LAMP-CRISPR/Cas12a-based identification of bovine mastitis milk samples contaminated by Escherichia coli

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Автор
Shaizadinova, Aisha
Amanzholova, Meruyert
Kirillov, Saveliy
Bulashev, Aitbay
Abeldenov, Sailau
Дата
2023-12
Редактор
Journal of Agriculture and Food Research
ISSN
2666-1543
Аннотации
Mastitis is a prevalent disease affecting dairy cows, leading to significant economic losses in the dairy industry. Conventional diagnostic methods such as microbiology and PCR are expensive and time-consuming, emphasizing the need for alternative diagnostic approaches. The field of novel diagnostics is expanding rapidly due to the application of a modern molecular detection methods based on the CRISPR/Cas system. This system functions by targeting specific genetic sequences of the pathogen, including Escherichia coli, and detects the presence of the pathogen by employing a CRISPR RNA that complements the pathogen’s genetic sequence and a Cas12a enzyme that cleaves the particular DNA sequence. In this paper, we present a novel pathogen detection technology that combines the loop-mediated isothermal amplification (LAMP) reaction and Cas12a collateral activity. We have successfully developed a rapid and precise method for identifying E.coli genomic DNA using the LAMP-Cas12a technology, which exhibits high analytical sensitivity within an hour, detecting as low as 1.3 × 101 copies of target DNA. This technology also has the ability to differentiate E. coli from other prevalent mastitis pathogens such as Staphylococcus aureus and Streptococcus agalactiae. Furthermore, we employed a novel MbCas12a nuclease, which demonstrated excellent diagnostic performance in our study when identifying E.coli isolates isolated from bovine mastitis milk samples. The development of such new methods has the potential to expand agricultural tools for use in point-of-care (POC) diagnostics.
URI
http://rep.enu.kz/handle/enu/16082
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1-s2.0-S2666154323002284-main.pdf (5.668Mb)
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  • Agricultural and Biological Sciences[187]
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