Typing of Campylobacter jejuni isolated from poultry on the basis of flaA-RFLP by various restriction enzymes

Abstract

RFLP analysis of the flagellin ( fla A) gene was compared using three different restriction endonucleases i.e Dde I, Hinf I and Dpn II to determine the genetic diversity among 43 Campylobacter jejuni isolates of poultry origin from the same geographical area. fla A gene was amplified in all the isolates and RFLP analysis showed variations. Dde -based RFLP was found most efficient in discriminating C. jejuni isolates by generating 15 different Dde -RFLP patterns with discriminatory index (D.I) of 0.9258 whereas Dpn II produced seven Dpn -RFLP patterns (D.I .= 0.8427). While Hinf I enzyme produced only six Hin f-RFLP patterns (D.I .= 0.6977). The discrimination of Dpn -RFLP was comparable to discrimination given by Dde -RFLP analysis, which is generally used to study fla A gene RFLP.

Detection, characterization, and persistence of Campylobacter hepaticus, the cause of spotty liver disease in layer hens

“…Restriction fragment length polymorphism ( RFLP ) has been used extensively for the genomic characterization of C. jejuni ( Yadav et al, 2018 ; Zhang et al, 2018 ). While RFLP is not comparable to whole genome sequencing because of its reliance on a single (albeit hypervariable) gene, it is useful from an ease-of use perspective to conduct genomic comparisons where a requirement for large numbers of analyses may preclude the use of whole genome sequencing analysis.…”

Campylobacter jejuni and other emerging Campylobacteraceae in retail beef liver – an underestimated potential source?

“…2018; Yadav et al . 2018). Next, a representative strain of each RFLP pattern was randomly selected for characterization by MLST, following protocols described by Dingle et al .…”

“…A screening of the C. jejuni genotypes was performed by as previously described (Nachamkin et al 1993). The profiles were then analysed with BioNumerics software version 7Á0 (Applied Maths, Belgium), using the Dice coefficient and the unweighted pair group method with arithmetic mean (UPGMA) algorithm, with a genetic similarity cut-off value of 85%, in accordance with previous studies (Ghorbanalizadgan et al 2016;An et al 2018;Yadav et al 2018). Next, a representative strain of each RFLP pattern was randomly selected for characterization by MLST, following protocols described by Dingle et al (2001).…”