Jan. 1, 2016 - Dec. 31, 2017Award Number
Center for Produce SafetyAmount Awarded
Kelly R. Bright, Ph.D
University of Arizona
Luisa A. Ikner, Ph.D., University of ArizonaResources
The methods used to detect E. coli were developed for drinking water and are known to produce high levels of false-positive and false-negative results when used for irrigation waters. Therefore, growers are required to make decisions about water quality/safety based on inaccurate tests. Our project goal is to identify microorganisms which may be used as novel indicators of the presence of pathogens (not just fecal contamination) in irrigation waters to allow the produce
industry to make more accurate risk-based assessments to determine when it is safe to irrigate crops. Our specific objectives are the following: 1) We will examine irrigation water to determine the levels of fecal indicator and pathogenic bacterial/viral species by existing cultural and/or molecular methods; 2) We will determine the composition (presence and relative abundance) of the entire bacterial, protozoan, and fungal communities found in irrigation water using “nextgeneration”
sequencing; 3) We will identify groups or specific species whose presence correlate well (presence/absence and relative abundance) with the occurrence of foodborne pathogens in irrigation waters. The use of more meaningful indicator species will provide growers with more accurate information upon which to optimize their irrigation practices to minimize the risk of contamination of produce by foodborne pathogens.
The methods used by the produce industry to detect fecal indicator organisms in irrigation waters utilize techniques developed for drinking water and may not be appropriate for determining the risk of contamination of crops. The EPA’s recreational bathing water standard of 126 E. coli/100 ml has been used as a risk threshold for irrigation waters, for which there is no scientific or statistically relevant basis; there is evidence that standard E. coli tests are inaccurate (high false + results) when used with irrigation waters. “Next-generation” DNA sequencing can be used as an inexpensive and powerful method to identify the composition (presence and relative abundance) of the entire prokaryotic (bacterial) and eukaryotic (e.g., protozoan) microbial communities in irrigation waters. Such information can be used to correlate the presence of foodborne pathogens with either shifts in the community makeup (from that of un-impacted waters) or with the presence of specific species (i.e., potential indicator organisms).
We will collect 100 samples in triplicate (total of 300 samples to be evaluated) from ten disparate irrigation water canals in Yuma, AZ over two fresh produce growing seasons (October- March) and two summers (non-growing) seasons. Each sample will be evaluated using Colilert® for the detection of total coliforms and E. coli. In addition, we will perform a series of enrichment/selective procedures to culture and isolate E. coli and Salmonella with confirmation via biochemical testing. The E. coli isolates will be examined using polymerase chain reaction (PCR) assays for the presence of the shiga toxin genes, stx1 and stx2. An additional volume of irrigation water will be concentrated and examined for the presence of pepper mild mottle virus and Aichiviruses (using quantitative PCR), which are known to be present in high numbers in waters with fecal contamination, in addition to the enteroviruses (a group of viral pathogens commonly found in feces).
Samples will be amplified using a PCR assay targeted to the conserved 16S and 18S rRNA genes that are found in all bacteria and protozoa, respectively. The PCR products will be purified and sequenced using the Illumina MiSeq sequencing platform and the species present will be identified by comparison to sequences in published databases. A comparison of the microbial communities between samples that are positive and negative for the presence of pathogens (both culturally and via next generation sequencing) will be conducted and analyzed (using specialized software such as Mothur) to identify groups of organisms or specific species whose presence correlate well (both presence/absence and relative abundance) with the occurrence of foodborne pathogens. The presence of pathogens or shifts in the microbial communities will also be compared to other water quality characteristics and potential impacts (e.g., rainfall, human and animal influences). This work should result in the identification of species which may be used as novel indicators of the presence of pathogens rather than just fecal contamination of irrigation waters and will allow the fresh produce industry to makerisk-based assessments of water quality and help to determine when it is safe to irrigate fields.