Arsenic contamination of natural waters is a worldwide concern, as the drinking water supplies for large populations can have high concentrations of arsenic. Traditional techniques to detect arsenic in natural water samples can be costly and time-consuming; therefore, robust and inexpensive methods to detect arsenic in water are highly desirable. Additionally, methods for detecting arsenic in the field have been greatly sought after. This article focuses on the use of bacteria-based assays as an emerging method that is both robust and inexpensive for the detection of arsenic in groundwater both in the field and in the laboratory. The arsenic detection elements in bacteria-based bioassays are biosensor-reporter strains; genetically modified strains of, e.g., Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Rhodopseudomonas palustris. In response to the presence of arsenic, such bacteria produce a reporter protein, the amount or activity of which is measured in the bioassay. Some of these bacterial biosensor-reporters have been successfully utilized for comparative in-field analyses through the use of simple solution-based assays, but future methods may concentrate on miniaturization using fiberoptics or microfluidics platforms. Additionally, there are other potential emerging bioassays for the detection of arsenic in natural waters including nematodes and clams.

Arsenic and other pollutants are often present in trace amounts in drinking water in a number of countries. In aqueous solutions the sensitivity of arsenic-responsive bacterial bioreporters is far better than the performance of chemical field test kits. However, biological detection currently requires extensive handling and expensive fluorescence microscopy. We fabricated and tested microfluidic chips with fluorescent (GFP) E. coli bacteria that respond to arsenic. Measurement results of fluorescence intensity as function of arsenic concentration and exposure time are promising, showing a clear response to concentrations of 50 μg/l of arsenite.

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