Detection and identification of body fluid stains using antibody-nanoparticle conjugates

Nunzianda Frascione, Richard Thorogate, Barbara Daniel, Sue Jickells

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Body fluids are considered one of the most important evidence types in forensic casework. The presence and location of blood, semen and saliva can provide crucial information to investigators. Current practice relies on an accurate visual examination followed by the use of presumptive tests to determine the identity of the body fluid type.1,2 Further laboratory based tests are required to unequivocally confirm the identity of a stain.3 Body fluid stains can be difficult to detect with the naked eye, particularly on dark backgrounds and hence vital evidence may be overlooked. Current methods are fluid-type specific, with a separate, and different, test required for each body fluid.4-6 The laborious nature of such analysis and the impossibility of being carried out at the crime scene, leads to a delay in the investigation process that could prove detrimental to the solving of the case. Hence, there is a need for sensitive, specific and direct methods which can simultaneously detect, differentiate, and locate human fluids on items of forensic evidence. Here, we describe the preparation of functionalized iron oxide nanoparticles conjugated to antibodies specific to blood and saliva components and their use in detecting small traces against non-contrasting substrates including glass, ceramic tile, paper and black fabric. The advantage of our technique is that it can simultaneously detect blood and saliva and can spatially locate and differentiate these body fluid types. Most importantly, our technology, which exploits the superparamagnetic properties of iron oxide nanoparticles, works in situ with no need to remove the body fluid stains for testing and with no washing steps and does not interfere with downstream DNA profiling. Thus, our technology represents a novel and effective alternative to existing methods.

Original languageEnglish
Pages (from-to)508-512
Number of pages5
JournalThe Analyst
Volume137
Issue number2
Early online date25 Nov 2011
DOIs
Publication statusPublished - 21 Jan 2012

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