Preliminary performance assessment of biotoxin detection for UWS applications using a MicroChemLab device.

Abstract

Issued by S andia N ational Laboratories, operated for the U nited States D epartment o f E nergy b y Sandia Corporation. NOTICE:This report was prepared as an account of work sponsored by an agency of the United States Government. N either t he U nited S tates Government, n or an y a gency t hereof, n or a ny o f their em ployees, n or an y o f t heir co ntractors, s ubcontractors, or t heir em ployees, make any warranty, e xpress or i mplied, or a ssume a ny l egal l iability or responsibility for t he a ccuracy, completeness, or us efulness of a ny i nformation, a pparatus, product, or pr ocess disclosed, or represent t hat i ts u se would n ot i nfringe p rivately o wned r ights. R eference h erein t o an y s pecific commercial p roduct, p rocess, o r s ervice b y t rade n ame, t rademark, m anufacturer, o r o therwise, does not ne cessarily c onstitute or i mply i ts e ndorsement, r ecommendation, or f avoring b y t he United States Government, any agency thereof, or any of their contractors or subcontractors. T he views and opinions expressed herein do not necessarily state or reflect those of the United States Government, any agency thereof, or any of their contractors.Printed i n the U nited S tates o f America. This r eport has b een r eproduced d irectly from t he b est available copy. AbstractIn a multiyear research agreement with Tenix Investments Pty. Ltd., Sandia has been developing field deployable technologies for detection of biotoxins in water supply systems. The unattended water s ensor or UWS e mploys m icrofluidic c hip ba sed gel e lectrophoresis f or m onitoring biological analytes in a small integrated sensor platform. This instrument collects, prepares, and analyzes w ater s amples i n an automated m anner. S ample an alysis i s d one u sing t he µChemLab TM analysis module. T his report uses analysis results of two datasets collected using the U WS t o es timate p erformance o f t he d evice. T he f irst d ataset i s m ade u p o f s amples containing ricin a t va rying c oncentrations a nd i s us ed f or a ssessing i nstrument r esponse a nd detection probability. The second dataset is comprised of analyses of water samples collected at a water utility which are used to assess the false positive probability. T he analyses of the two sets are used to estimate the Receiver Operating Characteristic or ROC curves for the device at one set of operational and detection algorithm parameters. For these parameters and based on a statistical estimate, the ricin probability of detection is about 0.9 at a concentration of 5 nM for a false positive probability of 1x10 -6 .-4- AcknowledgementsThis work was funded through a Cooperative Research and Development Agreement (CRADA) with Tenix and CH2M Hill. The authors gratefully acknowledge the cooperation of the Contra Costa W ater d istrict ( Alameda C ounty, C A) an d t he C ity o f Glendale W ater U tility (Glendale, AZ) f or a llowing te mporary in stallation o f U WS pr ototypes i n t heir r espective w ater pum ping stations. The authors a lso a ...