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Updated: May 22, 2026
A Simple Method for Automated Solid Phase Extraction of Water Samples for Immunological Analysis of Small Pollutants
Published on: January 1, 2016
Automated dead-end ultrafiltration of large volume water samples to enable detection of low-level targets and reduce
S D Leskinen1, E A Kearns, W L Jones
1Department of Cell Biology, Microbiology and Molecular Biology, University of South Florida, Tampa, FL 33620-7115, USA. leskinen@usf.edu
Aims:
A Portable Multi-use Automated Concentration System (PMACS) concentrates micro-organisms from large volumes of water through automated dead-end ultrafiltration and backflushing. The ability to detect microbial targets from ground, surface and cooling tower waters collected using standard methods was compared with samples from the PMACS in this study.
Methods And Results:
PMACS (100 l) and standard grab samples (100-500 ml) were collected from sites in Florida and South Carolina, USA. Samples were analysed for the presence of faecal indicator bacteria (FIB; ground and surface water) or Legionella pneumophila (Lp; cooling tower water). FIB were enumerated by growth on selective media following membrane filtration or in IDEXX defined substrate media. Lp cells were detected by direct fluorescence immunoassay using FITC-labelled monoclonal antibodies targeting serogroups 1, 2, 4 and 6. FIB were found in PMACS samples from ground and surface waters when their concentrations were below detection limits in grab samples. The concentrations of Lp in cooling tower samples collected over 5 months were more consistent in PMACS samples than grab samples.
Conclusions:
These data demonstrate that PMACS concentration is advantageous for water monitoring. FIB were detected in PMACS samples when their concentrations were below the detection limits of the standard methods used. PMACS processing provided more representative samples of cooling tower waters reducing sample variability during long-term monitoring.
Significance And Impact Of The Study:
This study highlights the utility of PMACS processing for enhanced monitoring of water for low-level microbial targets and for reducing sample variability in long-term monitoring programmes.
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