↓ Skip to main content

Discrimination between some Mycoplasma spp. and Acholeplasma laidlawii in bovine milk using high resolution melting curve analysis

Overview of attention for article published in BMC Research Notes, February 2018
Altmetric Badge

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
24 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Discrimination between some Mycoplasma spp. and Acholeplasma laidlawii in bovine milk using high resolution melting curve analysis
Published in
BMC Research Notes, February 2018
DOI 10.1186/s13104-018-3223-y
Pubmed ID
Authors

Abd Al-Bar Al-Farha, Kiro Petrovski, Razi Jozani, Andrew Hoare, Farhid Hemmatzadeh

Abstract

This study aimed to provide a rapid, accurate and cost-effective diagnostic real time polymerase chain reaction-high resolution melting curve assay (PCR-HRM) to identify and distinguish between four different mycoplasmas and Acholeplasma laidlawii isolated at cow-level from a single commercial dairy farm in South Australia. One set of genus-level universal primers was designed targeting the 16S ribosomal RNA gene. Real time PCR-HRM analysis was able to identify and distinguish between five different mollicutes, namely A. laidlawii, M. arginini, M. bovirhinis, M. bovis and uncultured Mycoplasma. Results were confirmed through sequencing. Our developed assay provides rapid and accurate screening for Mycoplasma mastitis detection.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 21%
Student > Ph. D. Student 5 21%
Other 2 8%
Student > Bachelor 1 4%
Professor 1 4%
Other 0 0%
Unknown 10 42%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 5 21%
Agricultural and Biological Sciences 5 21%
Biochemistry, Genetics and Molecular Biology 2 8%
Medicine and Dentistry 1 4%
Engineering 1 4%
Other 0 0%
Unknown 10 42%