Source tracking

Abstract: Microbial source tracking (MST) includes a group of methodologies that are aimed at identifying, and in some cases quantifying, the dominant source(s) of fecal contamination in resource waters, including drinking, ground, recreational, and wildlife habitat waters. MST methods can be grouped into two major types. Library-dependent methods are culture based and rely on isolate-by-isolate typing of bacteria cultured from various fecal sources and from water samples These isolates are matched to their corresponding source categories by direct subtype matching (41, 70) or by statistical means (23, 37, 40, 41, 80, 83, 102). In contrast, library-independent methods frequently are based on sample-level detection of a specific, host-associated genetic marker in a DNA extract by PCR (6, 11, 26, 88). Analyses of certain chemicals associated with sewage, including fecal sterols (29, 30, 47), optical brighteners (29, 30, 68), and host mitochondrial DNA (67), have also been utilized for what can be more broadly termed fecal source tracking; however, in this review we compare the performance of only fecal source tracking studies in which the target(s) is microbial. Mounting pressure to determine the origin of nonpoint source fecal pollution, as exemplified by the U.S. Environmental Protection Agency's total maximum daily load program, has led to a steady increase in manuscript submissions and grant applications that include MST approaches. At the same time, resource managers concerned with water quality and regulatory pressures struggle with the choice of methodology in the face of requirements for immediate application. Although there has been significant progress in the MST field over the last 10 years, variability among performance measurements and validation approaches in laboratory and field studies has led to a body of literature that is very difficult to interpret, both for scientists and for end users (99). In this review, we first consider the development and validation of MST methods in a historical context to describe the lessons learned in early studies. Next, uniform performance characteristics are introduced to allow comparison of method performance across MST studies (Tables ​(Tables11 and ​and2),2), and this is followed by a discussion of considerations for field study design and implementation. TABLE 1. Performance statistics for tests in which results were based on isolate-by-isolate classification into the various known-source categoriesa TABLE 2. Performance statistics for tests in which MST methods were tested with reference samples to determine the ability or failure to detect the sole source of fecal contamination

Abstract: The impairment of water quality by faecal pollution is a global public health concern. Microbial source tracking methods help to identify faecal sources but the few recent quantitative microbial source tracking applications disregarded catchment hydrology and pollution dynamics. This quantitative microbial source tracking study, conducted in a large karstic spring catchment potentially influenced by humans and ruminant animals, was based on a tiered sampling approach: a 31-month water quality monitoring (Monitoring) covering seasonal hydrological dynamics and an investigation of flood events (Events) as periods of the strongest pollution. The detection of a ruminant-specific and a human-specific faecal Bacteroidetes marker by quantitative real-time PCR was complemented by standard microbiological and on-line hydrological parameters. Both quantitative microbial source tracking markers were detected in spring water during Monitoring and Events, with preponderance of the ruminant-specific marker. Applying multiparametric analysis of all data allowed linking the ruminant-specific marker to general faecal pollution indicators, especially during Events. Up to 80% of the variation of faecal indicator levels during Events could be explained by ruminant-specific marker levels proving the dominance of ruminant faecal sources in the catchment. Furthermore, soil was ruled out as a source of quantitative microbial source tracking markers. This study demonstrates the applicability of quantitative microbial source tracking methods and highlights the prerequisite of considering hydrological catchment dynamics in source tracking study design.

Abstract: This chapter uses the term microbial source tracking (MST) to collectively refer to a number of methods developed to specifically determine the sources of fecal contamination and/or fecal indicator bacteria in water, because the chapter focuses on the use of microbial-based assays, rather than analyzing for chemical compounds such as coprostanol or host animal genes (i.e., mitochondrial genes). The chapter outlines the scientific questions and regulatory needs that have led to the burgeoning growth of this area of environmental microbiology. A section discusses some of the new tools and approaches that can be used to examine environmental samples and how they can be used in tracking sources of fecal pollution. Nucleic acid microarrays can be used to screen for the presence of DNA or RNA (i.e., expression arrays) obtained from pure cultures or from complex microbial communities. The power of multilocus sequence typing (MLST) in combination with metagenomic sequencing data was illustrated in recent application in which the presence of Burkholderia-like bacteria was confirmed by comparing typing data with metagenomic sequences from the Sargasso Sea. A promising technology in source tracking and in microbial ecology in general, is called hierarchical oligonucleotide primer extension. This fingerprint technique uses combinations of hierarchical primers to target different bacteria within a phylogenetic group.

Abstract: A particle filtering (PF) approach is presented for performing sequential geoacoustic inversion of a complex ocean acoustic environment using a moving acoustic source. This approach treats both the environmental parameters [e.g., water column sound speed profile (SSP), water depth, sediment and bottom parameters] at the source location and the source parameters (e.g., source depth, range and speed) as unknown random variables that evolve as the source moves. This allows real-time updating of the environment and accurate tracking of the moving source. As a sequential Monte Carlo technique that operates on nonlinear systems with non-Gaussian probability densities, the PF is an ideal algorithm to perform tracking of environmental and source parameters, and their uncertainties via the evolving posterior probability densities. The approach is demonstrated on both simulated data in a shallow water environment with a sloping bottom and experimental data collected during the SWellEx-96 experiment.