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Semi-quantitative method for streptococci magnetic detection in raw milk

  • Carla Duarte
  • , Tiago Costa
  • , Carla Carneiro
  • , Rita Soares
  • , Andrei Jitariu
  • , Susana Cardoso
  • , Moisés Piedade
  • , Ricardo Bexiga
  • , Paulo Freitas

Resultado de pesquisa: ???type-name??????researchoutput.researchoutputtypes.contributiontojournal.article???revisão de pares

33 Citações (Scopus)

Resumo

Bovine mastitis is the most costly disease for dairy farmers and the most frequent reason for the use of antibiotics in dairy cattle; thus, control measures to detect and prevent mastitis are crucial for dairy farm sustainability. The aim of this study was to develop and validate a sensitive method to magnetically detect Streptococcus agalactiae (a Group B streptococci) and Streptococcus uberis in raw milk samples. Mastitic milk samples were collected aseptically from 44 cows with subclinical mastitis, from 11 Portuguese dairy farms. Forty-six quarter milk samples were selected based on bacterial identification by conventional microbiology. All samples were submitted to PCR analysis. In parallel, these milk samples were mixed with a solution combining specific antibodies and magnetic nanoparticles, to be analyzed using a lab-on-a-chip magnetoresistive cytometer, with microfluidic sample handling. This paper describes a point of care methodology used for detection of bacteria, including analysis of false positive/negative results. This immunological recognition was able to detect bacterial presence in samples spiked above 100 cfu/mL, independently of antibody and targeted bacteria used in this work. Using PCR as a reference, this method correctly identified 73% of positive samples for streptococci species with an anti-S. agalactiae antibody, and 41% of positive samples for an anti-GB streptococci antibody.

Idioma original???core.languages.en_GB???
Número do artigo19
RevistaBiosensors
Volume6
Número de emissão2
DOIs
Estado da publicação???researchoutput.status.published??? - 27 abr. 2016
Publicado externamenteSim

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