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Research Article| Volume 14, P18-30, January 2015

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Facile semi-automated forensic body fluid identification by multiplex solution hybridization of NanoString® barcode probes to specific mRNA targets

Published:September 14, 2014DOI:https://doi.org/10.1016/j.fsigen.2014.09.005

      Highlights

      • Developed a multiplex digital gene expression method for body fluid identification.
      • Uses solution hybridization of color-coded NanoString® probes to 23 mRNA targets.
      • We devised a simple 5 min room temperature lysis protocol for RNA isolation.
      • Maximum likelihood algorithm to estimate body fluid quantities in a sample.
      • Use likelihood ratios to test for the presence of each body fluid in a sample.

      Abstract

      A DNA profile from the perpetrator does not reveal, per se, the circumstances by which it was transferred. Body fluid identification by mRNA profiling may allow extraction of contextual ‘activity level’ information from forensic samples. Here we describe the development of a prototype multiplex digital gene expression (DGE) method for forensic body fluid/tissue identification based upon solution hybridization of color-coded NanoString® probes to 23 mRNA targets. The method identifies peripheral blood, semen, saliva, vaginal secretions, menstrual blood and skin. We showed that a simple 5 min room temperature cellular lysis protocol gave equivalent results to standard RNA isolation from the same source material, greatly enhancing the ease-of-use of this method in forensic sample processing.
      We first describe a model for gene expression in a sample from a single body fluid and then extend that model to mixtures of body fluids. We then describe calculation of maximum likelihood estimates (MLEs) of body fluid quantities in a sample, and we describe the use of likelihood ratios to test for the presence of each body fluid in a sample. Known single source samples of blood, semen, vaginal secretions, menstrual blood and skin all demonstrated the expected tissue-specific gene expression for at least two of the chosen biomarkers. Saliva samples were more problematic, with their previously identified characteristic genes exhibiting poor specificity. Nonetheless the most specific saliva biomarker, HTN3, was expressed at a higher level in saliva than in any of the other tissues.
      Crucially, our algorithm produced zero false positives across this study's 89 unique samples. As a preliminary indication of the ability of the method to discern admixtures of body fluids, five mixtures were prepared. The identities of the component fluids were evident from the gene expression profiles of four of the five mixtures. Further optimization of the biomarker ‘CodeSet’ will be required before it can be used in casework, particularly with respect to increasing the signal-to-noise ratio of the saliva biomarkers. With suitable modifications, this simplified protocol with minimal hands on requirement should facilitate routine use of mRNA profiling in casework laboratories.

      Keywords

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