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Chapter 2 : Assumptions and Limitations Associated with Microbial Source Tracking Methods

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Assumptions and Limitations Associated with Microbial Source Tracking Methods, Page 1 of 2

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Abstract:

This chapter provides a critical evaluation of microbial source tracking (MST) methods, including an analysis of the current expectations of MST tools. The ultimate goal of all microbial source tracking studies is to link fecal contamination with its host source, whether contamination is a concern in water or food. Characteristics considered desirable for an “ideal” MST tool are presented in the chapter, followed by a discussion of the assumptions made about tools currently used, research studies that have addressed these assumptions, and known limitations of the tools. Host specificity of commensal and mutualistic microflora of the gastrointestinal (GI) tract may, however, be the exception rather than the rule, particularly among the culturable fraction of the inhabitants of the GI tract. MST methods as related to food are also concerned with direct detection and tracking of the source of food-borne pathogens, some of which are zoonotic and are easily transmitted from animal hosts to humans. An MST tool that is adopted for beach water quality monitoring, total maximum daily load (TMDL) assessment, and food quality programs throughout the United States should meet the assumptions listed in the chapter. Several studies on the distribution of species/pattern/markers (SPMs) in primary versus secondary habitats noted distinct differences in the populations.

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2

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Figure 1

Examples of some SPMs currently used in MST. (A) Horizontal fluorophore-enhanced rep-PCR patterns of isolates. Each vertical lane represents one pattern. (B) Ribotype pattern of one isolate. (C) Ribotype patterns of isolates. (D) Carbon source utilization pattern of one isolate. (E) Specific genetic marker of amplified by PCR of DNA. MW, molecular weight.

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2
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Image of Figure 2
Figure 2

BOX-PCR subtyping of spp. isolated from a lift station (central sewer) shows diversity of enterococci.

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2
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Figure 3

Accumulation curves showing (A) the number of unique BOX-PCR subtypes of spp. as a function of sampling effort in various types of water and (B) the number of unique BOX-PCR subtypes of and spp. as a function of sampling effort in a storm water system. For Siesta Key samples the accumulation curves from several sites in a storm drain system were averaged: storm pipe water, beach water, ditch water, and vault water. Sampling 1 occurred during a rain event, while sampling 2 was dry. The Myakka River samples represent a relatively unimpacted site in a state park. Accumulation curves were averaged from the following samples: storm pipe water, vault water, ditch water, ditch sediment, beach water, and beach sediment. Sampling 1 occurred during a rain event, while sampling 2 was dry.

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2
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Image of Figure 4
Figure 4

Accumulation curve showing the number of unique BOX-PCR subtypes of spp. as a function of sampling effort in Gulf of Mexico beach sediments.

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2
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Tables

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Table 1

Examples of source identifiers and SPMs used in MST studies, with example references

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2
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Table 2

Characteristics of an ideal source identifier (SI) compared to those of a useful SI

Citation: Harwood V. 2007. Assumptions and Limitations Associated with Microbial Source Tracking Methods, p 33-64. In Santo Domingo J, Sadowsky M, Doyle M (ed), Microbial Source Tracking. ASM Press, Washington, DC. doi: 10.1128/9781555815769.ch2

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