Grantee Research Project Results
Automated Human Fecal Pollution Detection
EPA Contract Number: EPD05036Title: Automated Human Fecal Pollution Detection
Investigators: U'Ren, Jack
Small Business: Saigene Corporation
EPA Contact: Richards, April
Phase: I
Project Period: March 1, 2005 through August 31, 2005
Project Amount: $70,000
RFA: Small Business Innovation Research (SBIR) - Phase I (2005) RFA Text | Recipients Lists
Research Category: Small Business Innovation Research (SBIR) , Watersheds , SBIR - Water and Wastewater
Description:
More than 2 million children worldwide die each year from enteric waterborne diseases caused by fecal pollution. Diseases such as typhoid fever, cholera, and hepatitis A all are transmitted by fecal contaminated water. Consequently, public health departments have set strict standards for the quantity of coliform bacteria allowed in the water. These standards are: (1) for drinking water, less than 1 coliform per 100 mL of water; (2) for unfiltered drinking water from watersheds, 50/100 mL, (3) for shellfish-growing waters, 70/100 mL; and (4) for swimming water, 200/100 mL. Coliforms represent a group of aerobic, gram-negative, nonsporulating bacilli, most of which are Escherichia coli. Most E. coli strains are not pathogenic, but represent an indication of fecal contamination and therefore the possible presence of other more harmful fecal pathogens.
Because of the requirement to detect very low levels of these bacteria (1 per 100 mL of water), rapid automated detection is very difficult. Culture techniques take 24 hours and the more rapid DNA amplification techniques still require DNA purification and the use of unstable enzymes and nucleotides as well as elaborate instrumentation, all of which are difficult and expensive to automate. In this research project, Saigene Corporation will develop an automated biosensor capable of detecting low levels of fecal microorganisms without the need for bacterial culture or DNA amplification techniques. The biosensor should be sensitive enough to detect fecal microorganisms at a level of 1 coliform cell per 100 mL of water within 30 minutes. The sensing element will be reusable to allow for long-term, unattended, cost-effective analysis. The sensor also should distinguish human from farm livestock sources of fecal pollution.
The final product is envisioned as an automated buoy placed in drinking water inlet sources, swimming waters, and shellfish or other aquaculture growing waters. The buoy will report fecal microorganism levels at set time intervals by remote telemetry communication. Sampling times may be remotely adjusted based on rainfall that can cause excessive runoff that might increase fecal pollution by overwhelming the handling capacity of sewage treatment facilities. A nonbuoy-based portable version of the instrument also will be developed. This portable instrument can be used to analyze water samples onsite. Backtracking bacterial levels to their source can locate the point source of the pollution. Then, site-specific remedial action can be implemented.
Supplemental Keywords:
small business, SBIR, human fecal pollution detection, wastewater, waterborne disease, contaminated water, coliform bacteria, Escherichia coli, E. coli, fecal contamination, biosensor, drinking water, EPA, RFA, Scientific Discipline, Ecosystem Protection/Environmental Exposure & Risk, Environmental Chemistry, Analytical Chemistry, Monitoring/Modeling, Environmental Monitoring, aquatic ecosystem, Cholera, drinking water, human exposue, recreational water quality, community water quality information system, fecal coliform, fecal pathogens, disease detection, public health alerts, enteric pathogensProgress and Final Reports:
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.