Water quality specialist use MST to apportion fecal microbes to their host animals. By doing so, it is hoped that effective management and mitigation efforts can be designed to reduce fecal flora in surface waters. In addition, being able to identify primary sources of fecal contamination may help to refine estimates of the human health risk posed by various sources of fecal contamination.

Many potential markers and methods have been proposed for MST. These have been broadly classified as library-dependent and library-independent methods. Library dependent methods rely on collecting a large number of microbes from specific sources. The microbes are then characterized phenotypically (e.g., antimicrobial resistance analysis) or based on nucleic acid markers (e.g., ribotyping) to develop a library of characteristics that are correlated with the originating host animals. These patterns can be used to derive a classification function that is then used to putatively identify the host animals from which the fecal flora originated. Challenges for library dependent methods include the need to construct a large library before any work can proceed. In addition, because traits such as ribotypes are unlikely to reflect evolutionarily selected traits, correlations between these markers and host animals are unlikely to be spatially and temporally stable. Thus, libraries may require periodic “updates” In addition libraries and classification functions may not be readily available to all practitioners. 

Library-independent methods require markers for microbes or genes that are specific to a given animal. Assuming these markers are functionally linked to the host animals, then the markers should be spatially and temporally stable. Challenges include the ability to identify suitable markers. Both library-dependent and library-independent methods require thorough validation.

Regardless of the method that is chosen for MST, there are two basic assumptions for these methods to work: 

1. Host-specificity exists and is detectable.
2. The proportion of any given marker is constant in the environment.
   1. No differential loss.
   2. No significant environmental replication.

   3. No significant environmental reservoirs.

DNA microarrays can be used both as a tool for library dependent and library independent MST. In the former case, a microarray is constructed from known or random gene fragments and the array is then used to “fingerprint” fecal isolates much like other nucleic acid based methods. This data is then used to construct a classification function. This approach can include hundreds to thousands of discreet markers, although the total number of probes used in the classification function should be less than 1/10^th the number of isolates used to construct the classification function. An alternative method employs a mixed-genome microarray (links) to capture some of the natural diversity between flora collected from specific hosts. Once a large number of host specific isolates are characterized, it is possible to identify probes that are closely correlated with specific hosts. These probes can be retrieved and sequenced to identify the specific gene fragments. Subsequently, low density microarrays, suspension arrays, or real-time PCR assays can be constructed for these markers. The principle advantage of the microarray is that a large number of discreet markers can be screened for genes that are required for the bacterium to reside in the host gut.

In our study we constructed a mixed-genome Enterococcus microarray. The array (4,320 probes) was constructed from DNA pooled from >40 isolates of Enterococcus from each of five host species (human, elk/deer, cow, dog, and waterfowl). In a preliminary analysis (January 2004) we hybridized DNA from 83 Enterococcus isolates to the array to produce >350,000 data points. From this data we constructed a library-dependent classification function (using DFA) that was capable of correctly identifying 98% of the host animals when 19 probes were used in the equation. When the analysis was limited to a more statistically appropriate number of probes (n=8), 76% of the original isolates were correctly classified. Analysis of probe specificity demonstrated the potential for a number of host specific markers for humans (n>100), cows (n>100), elk/deer (n=23), dogs (n=4) and waterfowl (n=3). Additional hybridizations are underway to identify more markers and further validate potential markers for MST.

Co-investigators: Dr. Marilyn Soule (msoule@vetmed.wsu.edu), Dr. Frank Loge (floge@wsu.edu), and Dr. John Gay (jgay@vetmed.wsu.edu).

Technical assistance is provided by Melissa Oatley, Melissa Krug, and Stacey LaFrentz.

Funding

We gratefully acknowledge funding support from USDA-NRI-CSREES and the Agricultural Animal Health Program, College of Veterinary Medicine, Pullman, WA.

Home  |   Description  |   Personnel   |   Publications  |   Funding  |  Pathogen Detection  |   Other Links