optimized co-extraction and quantification of dna from enteric pathogens in surface water samples near produce fields in california

optimized co-extraction and quantification of dna from enteric pathogens in surface water samples near produce fields in california

;Michael B. Cooley;Diana Carychao;Lisa Gorski
journal of magnetic resonance (san diego, calif : 1997) 2018 Vol. 9 pp. -
177
cooley2018frontiersoptimized

Abstract

Pathogen contamination of surface water is a health hazard in agricultural environments primarily due to the potential for contamination of crops. Furthermore, pathogen levels in surface water are often unreported or under reported due to difficulty with culture of the bacteria. The pathogens are often present, but require resuscitation, making quantification difficult. Frequently, this leads to the use of quantitative PCR targeted to genes unique to the pathogens. However, multiple pathogen types are commonly in the same water sample, both gram + and gram –, leading to problems with DNA extraction. With Shiga toxin-producing Escherichia coli (STEC), Salmonella enterica and Listeria monocytogenes as target, a method was optimized to co-extract all three and quantify the level of each using droplet digital PCR (ddPCR). Multiplexed target genes in STEC were virulence genes, shiga toxin 2 (stx2) and hemolysin (ehx). Likewise, multiplexed targets in Listeria and Salmonella were the virulence genes listeriolysin (hly) and invasion protein A (invA). Water samples were processed using microbiological techniques for each of the pathogens and duplicate water samples were quantified by ddPCR. A significant correlation was found between culture and ddPCR results indicating detection primarily of culturable cells by ddPCR. Average virulence gene levels were 923, 23 k, 69 and 152 copies per sample for stx2, ehx, hly and invA, respectively. Additionally, stx2, ehx and inv levels were significantly correlated (P < 0.05, R = 0.34) with generic E. coli MPN levels in the duplicate samples. Indirect quantification with ddPCR will improve understanding of prevalence of the pathogens and may reduce risks associated with contaminated surface water.

Citation

ID: 250917
Ref Key: cooley2018frontiersoptimized
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
250917
Unique Identifier:
10.3389/fmicb.2018.00448
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet