A hybrid DNA extraction method for the qualitative and quantitative assessment of bacterial communities from poultry production samples.

نویسندگان

  • Michael J Rothrock
  • Kelli L Hiett
  • John Gamble
  • Andrew C Caudill
  • Kellie M Cicconi-Hogan
  • J Gregory Caporaso
چکیده

The efficacy of DNA extraction protocols can be highly dependent upon both the type of sample being investigated and the types of downstream analyses performed. Considering that the use of new bacterial community analysis techniques (e.g., microbiomics, metagenomics) is becoming more prevalent in the agricultural and environmental sciences and many environmental samples within these disciplines can be physiochemically and microbiologically unique (e.g., fecal and litter/bedding samples from the poultry production spectrum), appropriate and effective DNA extraction methods need to be carefully chosen. Therefore, a novel semi-automated hybrid DNA extraction method was developed specifically for use with environmental poultry production samples. This method is a combination of the two major types of DNA extraction: mechanical and enzymatic. A two-step intense mechanical homogenization step (using bead-beating specifically formulated for environmental samples) was added to the beginning of the "gold standard" enzymatic DNA extraction method for fecal samples to enhance the removal of bacteria and DNA from the sample matrix and improve the recovery of Gram-positive bacterial community members. Once the enzymatic extraction portion of the hybrid method was initiated, the remaining purification process was automated using a robotic workstation to increase sample throughput and decrease sample processing error. In comparison to the strict mechanical and enzymatic DNA extraction methods, this novel hybrid method provided the best overall combined performance when considering quantitative (using 16S rRNA qPCR) and qualitative (using microbiomics) estimates of the total bacterial communities when processing poultry feces and litter samples.

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عنوان ژورنال:
  • Journal of visualized experiments : JoVE

دوره 94  شماره 

صفحات  -

تاریخ انتشار 2014