A Metataxonomic Approach Could Be Considered for Cattle Clinical Mastitis Diagnostics



Oultram, Joanne WH, Ganda, Erika K, Boulding, Sarah C, Bicalho, Rodrigo C and Oikonomou, Georgios
(2017) A Metataxonomic Approach Could Be Considered for Cattle Clinical Mastitis Diagnostics. FRONTIERS IN VETERINARY SCIENCE, 4 (MAR). 36-.

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Abstract

Mastitis is one of the most costly diseases affecting the dairy industry, and identification of the causative microorganism(s) is essential. Here, we report the use of next-generation sequencing of bacterial 16S rRNA genes for clinical mastitis diagnosis. We used 65 paired milk samples, collected from the mastitic and a contralateral healthy quarter of mastitic dairy cattle to evaluate the technique as a potential alternative to bacterial culture or targeted PCR. One large commercial dairy farm was used, with one trained veterinarian collecting the milk samples. The 16S rRNA genes were individually amplified and sequenced using the MiSeq platform. The MiSeq Reporter was used in order to analyze the obtained sequences. Cattle were categorized according to whether or not 1 of the 10 most abundant bacterial genera in the mastitic quarter exhibited an increase in relative abundance between the healthy and mastitic quarters equal to, or exceeding, twofold. We suggest that this increase in relative abundance is indicative of the genus being a causative mastitis pathogen. Well-known mastitis-causing pathogens such as <i>Streptococcus uberis</i> and <i>Staphylococcus</i> spp. were identified in most cattle. We were able to diagnose 53 out of the 65 studied cases and identify potential new mastitis pathogens such as <i>Sneathia sanguinegens</i> and <i>Listeria innocua</i>, which are difficult to identify by bacterial culture because of their fastidious nature.

Item Type: Article
Uncontrolled Keywords: metataxonomics, mastitis, cattle, diagnostics, sequencing
Depositing User: Symplectic Admin
Date Deposited: 01 Mar 2017 09:51
Last Modified: 19 Jan 2023 07:15
DOI: 10.3389/fvets.2017.00036
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3006114