Vibrio parahaemolyticus


Vibrio parahaemolyticus, Vp, is one of many naturally-occurring Vibrio species that are important in maintaining the balance of nutrients in the marine environment. They help decompose wastes in the ocean and especially chitin, which comprises the exoskeletin of marine invertebrates such as crabs; chitin is the second most abundant biopolymer on Earth, after cellulose. Unfortunately, some of these marine bacteria, including Vp, are filtered during the feeding process and high densities of Vp can occur naturally in oysters. Because an oyster feeds by filtering seawater, it can accumulate enough Vp to cause illness in a vulnerable consumer who eats uncooked or undercooked oysters. Densities of these naturally occurring bacteria vary throughout the year in the marine environment, but they tend to be highest in warmer months when water temperatures are highest. The higher the water temperature, the higher the densities of Vp in the water, and potentially, in oysters. However, the "old wives tale" that oysters are safe to eat when harvested during months with "r" in their name is not true; in southern states such as the Gulf of Mexico states often maintain infective doses of Vp throughout the year. Additional information about Vp can be found at the FDA Food Safety web site.

Predicting Risk


Variations in density drive research efforts to accurately predict high Vp densities that could pose health risks to at-risk individuals who eat raw oysters. The Food and Drug Administration (FDA) has developed an experimental prediction model that uses temperature and salinity to estimate Vp densities and the associated risk to consumers.

The University of Southern Mississippi Gulf Coast Research Laboratory (GCRL) launched a collaboration in 2003 with federal and state agencies to take the model's use a step further. GCRL researchers are experimenting with satellite data on water temperature and other environmental factors for use in the FDA experimental prediction model.

Funded by the National Oceanic and Atmospheric Administration's Oceans and Human Health Initiative, the breakthrough project initially used sea surface temperature (SST) data that are already available from satellites. In 2009, salinity data were added to improve the predictive capability of the maps. More recently, the Naational Science Foundation (NSF) and the National Aeronautics and Space Administration (NASA) have funded this project. The project now determines how well these remotely sensed data (NASA funding) match data collected from boats on site in oyster-harvesting waters (NSF funding).

The ultimate goal of the project is to provide a rigorous real-time monitoring of Vp via the maps on this web site.

Remote Sensing


Remote sensing data used in Vp risk prediction is acquired by the scientists at the Gulf Coast Geospatial Center (GCGC) from NASA's MODerate resolution Imaging Spectroradiometer (MODIS) satellite sensor onboard the Aqua satellite. These data go through three steps in order to be used in Vp risk prediction. First, the amount of the sun's energy (in the form of waves of light) from the waters in the Gulf of Mexico is measured by the MODIS sensor.



Second, four different wavelengths of light measured by MODIS are used in algorithms to estimate sea surface temperature (SST) and salinity. The algorithm for estimating SST uses two measurements of the thermal, or heat energy (in the form of light waves), that radiates from the ocean's surface. The algorithm for estimating salinity uses measurements of two wavelengths of light that are strongly influenced by the amount of suspended (or organic material) and dissolved material (also known as colored dissolved organic material, or CDOM) in the water. Normally, the higher these CDOM measurements are the lower the salinity readings will be, as they are found in higher concentrations near shore where freshwater rivers bring them into the estuaries.

        

The latest SST, Salinity and Vibrio at Harvest imagery. Click the images for the full resolution geotiff. View the images in GIS Mapserver


In the third step, GCGC scientists apply the algorithm products generated by MODIS data as inputs to algorithms provided by the FDA to estimate densities of Vp. The density map is created with the following algorithm:

average log(Vp/g) = -2.05 + 0.097*SST + 0.2*SAL - 0.0055*SAL2


The results are illustrated by creating maps that use a color scale from blue (lowest readings) to red (highest readings). These color scales represent the readings of SST, salinity, and estimated Vp densities that have been generated using MODIS data.

Ground Referencing


Use of remote sensing data must include ground referencing - making certain the algorithm products from the MODIS sensor data significantly match the data someone on a boat at the oyster collection sites can measure with a thermometer or salinometer, and in the laboratory with infected oysters collected at that location. Once scientists find the degree of correlation between the two data collection methods, they can determine the reliability of predictions that are based on remotely sensed data. This process is called "ground truthing".

Steps in Ground Referencing:



Further Information


Further information on this project are available in the following documents. Additional scientific information about Vp can be found in the "Bad Bugs" manual published by FDA. The Vp page in the "Bad Bugs Book" is under revision, so please note that the infective dose is not 1,000,000 cells but rather will be changed to a lower number (FDA, personal communication).



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Research Article: