Highlights
- •A series of dried blood mixtures containing as many as five individuals were analyzed.
- •Contributor cell populations were labeled with antibody probes and separated into two fractions.
- •DNA profiles from each fraction could be interpreted manually or using probabilistic modeling.
- •This approach can increase probative value of mixture evidence by associating many of the contributors to the sample.
Abstract
Forensic samples comprised of cell populations from multiple contributors often yield
DNA profiles that can be extremely challenging to interpret. This frequently results
in decreased statistical strength of an individual’s association to the mixture and
the loss of probative data. The purpose of this study was to test a front-end cell
separation workflow on complex mixtures containing as many as five contributors. Our
approach involved selectively labelling certain cell populations in dried whole blood
mixture samples with fluorescently labeled antibody probe targeting the HLA-A*02 allele,
separating the mixture using Fluorescence Activated Cell Sorting (FACS) into two fractions
that are enriched in A*02 positive and A*02 negative cells, and then generating DNA
profiles for each fraction. We then tested whether antibody labelling and cell sorting
effectively reduced the complexity of the original cell mixture by analyzing STR profiles
quantitatively using the probabilistic modeling software, TrueAllele® Casework. Results showed that antibody labelling and FACS separation of target populations
yielded simplified STR profiles that could be more easily interpreted using conventional
procedures. Additionally, TrueAllele® analysis of STR profiles from sorted cell fractions increased statistical strength
for the association of most of the original contributors interpreted from the original
mixtures.
Keywords
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Article info
Publication history
Published online: July 15, 2018
Accepted:
July 2,
2018
Received in revised form:
June 26,
2018
Received:
February 22,
2018
Identification
Copyright
© 2018 Elsevier B.V. All rights reserved.
