This study evaluated the utility of defined substrate methodology (DSM) for the enumeration of indicator bacteria in wastewater applications. Two commercial products, Colilert and Enterolert systems (Idexx Laboratories, Westbrook, Maine), were evaluated for variation, false-positive results, and method correlation in both surface waters and treated wastewater effluent. The DSM tests performed as well or better than the traditional methodology. The Colilert total coliform test was also evaluated for its utility in estimating fecal coliforms by incubation at 44.5 Ϯ 0.2°C. The modified DSM total coliform test correlated well to membrane filtration (Pearson correlation coefficient 0.8) for two different sample groups, demonstrating its utility as a screening tool to estimate fecal coliform densities. Water Environ. Res., 74, 131 (2002).

In this study we examined the recovery of Cryptosporidium parvum and Giardia duodenalis from matrices containing various concentrations of dissolved iron. The organisms were recovered by using the immunomagnetic separation-immunofluorescent assay method, and the levels of recovery were compared to the dissolved iron concentrations. The levels of recovery of C. parvum decreased sharply at dissolved iron concentrations greater than 4 mg/liter, while the levels of recovery of G. duodenalis decreased sharply at concentrations greater than 40 mg/liter.

One of the most difficult challenges in the analysis of environmental samples is to separate the organism of interest from a sample that is high in background debris. Immunomagnetic separation (IMS) is one technique that has been developed to accomplish this in a rapid and reliable assay. Immunomagnetic separation (or biomagnetic separation) involves a superparamag-netic, monodispersed, polystyrene microsphere that is coated with a specific ligand. When added to a heterogeneous target suspension, the microspheres bind to the desired target. Using a powerful magnet, the microsphere-target complex is then removed from the suspension. Many different targets of interest can be isolated with this technique, including fungal/bacterial cells or spores, protozoan parasites, cellular and subcellular material, proteins, and nucleic acid products. This wide range of application makes IMS one of the most versatile techniques available for the purification of target products from heterogeneous sample matrices.

Indicator bacteria are the most common way of assessing biological water quality. Indicator bacteria are bacteria that can predict the presence of pathogenic organisms. To be a successful indicator, the following criteria must be met: Indicator bacteria must be easy to cultivate in the laboratory using simple, cost‐effective procedures. Indicator bacteria must be present in high enough concentrations to be readily detectable in a manageable sample volume. Indicator bacteria must effectively predict the risk of illness from exposure to the waterborne pathogens present in contaminated water.

Wastewater Laboratory Managers, Quality Assurance Officers, and analysts are aware of the requirements to analyze quality control (QC) samples as part of each analytical batch. Method blanks, laboratory control samples, matrix spikes, matrix spike duplicates, sample duplicates, surrogates, and other QC testing are mandated by most approved methods or state/national laboratory accreditation standards. Many wastewater laboratory professionals lack a clear understanding of how to apply the QC results to the analytical data for each analytical batch, or how to qualify the batch data based on the results of the batch QC samples. Appropriate data qualifiers are critical to understanding the limitations on the use of the data for compliance purposes.Training on the proper use and application of QC data can provide wastewater professionals with the background necessary to understand the relationship between QC testing and the resultant batch data associated with it. Once this critical relationship is understood, wastewater professionals are more likely to understand the need for QC testing, are able to appropriately qualify data associated with QC failures, and are able to accurately represent the quality of the data to the end-user.