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Integration of gas chromatography mass spectrometry methods for differentiating ricin preparation methods

Authors :
Jon H. Wahl
Kathryn C. Antolick
Karen L. Wahl
Christopher J. Ehrhardt
Heather A. Colburn
Kristin D. Victry
David S. Wunschel
Angela M. Melville
Source :
The Analyst. 137(9)
Publication Year :
2012

Abstract

The investigation of crimes involving chemical or biological agents is infrequent, but presents unique analytical challenges. The protein toxin ricin is encountered more frequently than other agents and is found in the seeds of Ricinus communis, commonly known as the castor plant. Typically, the toxin is extracted from castor seeds utilizing a variety of different recipes that result in varying purity of the toxin. Moreover, these various purification steps can also leave or differentially remove a variety of exogenous and endogenous residual components with the toxin that may indicate the type and number of purification steps involved. We have applied three gas chromatography – mass spectrometry (GC-MS) based analytical methods to measure the variation in seed carbohydrates and castor oil ricinoleic acid, as well as the presence of solvents used for purification. These methods were applied to the same samples prepared using four previously identified toxin preparation methods, starting from four varieties of castor seeds. The individual data sets for seed carbohydrate profiles, ricinoleic acid, or acetone amount each provided information capable of differentiating different types of toxin preparations across seed types. However, the integration of the data sets using multivariate factor analysis provided a clear distinction of all samples based on the preparation method, independent of the seed source. In particular, the abundance of mannose, arabinose, fucose, ricinoleic acid, and acetone were shown to be important differentiating factors. These complementary tools provide a more confident determination of the method of toxin preparation than would be possible using a single analytical method.

Details

ISSN :
13645528
Volume :
137
Issue :
9
Database :
OpenAIRE
Journal :
The Analyst
Accession number :
edsair.doi.dedup.....4797834875adfe3002dd9dcb2e492171