(156d) Development of a Biosensor for Cryptosporidium in Drinking Water

Cryptosporidium
parvum is a challenge for drinking
water utilities as it is resistant to common disinfectants and has a very low
infectious oocyst dose (in the range of 10-1000 oocysts for healthy persons and
as low as 10-100 for immunocompromised individuals). Additionally, Cryptosporidium
parvum has been listed by the CDC as a Class B bioterrorism agent.  Current
Cryptosporidium detection methods are expensive, slow, and plagued with
low and variable recovery rates.  This research couples a ‘sandwich immunoassay'
with Surface Enhanced Raman Spectroscopy (SERS) for the capture and
quantification of Cryptosporidium parvum oocysts in finished drinking
waters. Although common in biological analyses, little work has been done on
the employment of sandwich immunoassays for the detection of pathogens in drinking
waters. SERS is gaining popularity for low level detection techniques as it can
detect picomole (10^-12 M) to femtomole (10^-15 M)
concentrations of organic compounds in the presence of gold and silver colloids. Specifically, this assay employs a polycarbonate
filter membrane functionalized with anti-Cryptosporidium parvum IgG
antibodies.  Poly-L-lysine acts as spacer on the surface of the membrane and
activation by glutaraldehyde creates a reactive layer that binds with the
antibodies to create an anti-Cryptosporidium surface.  Water samples
containing Cryptosporidium parvum oocyst are filtered through the
membrane and are captured by the antibodies.  The membrane is exposed to a
solution of fluorescent dye-labeled immunogold.  The immunogold consists of 12
nm gold nanoparticles with anti-Cryptosporidium parvum antibodies
adsorbed and fluorescent dyes covalently bound to the gold nanoparticle surface. 
Excess immunogold is washed away and the membrane filter surface is analyzed
with Raman Spectroscopy.  The results of several optimization studies (i.e.
varying Raman dyes, varying filter pore sizes, varying specific anti-Cryptosporidium
antibodies) will be presented.  Also, the potential for expanding this assay to
a multi-pathogen detection method will be addressed.