Highlights
- •A novel method for the identification of saliva in forensic samples was developed.
- •The technique is based on the detection of oral bacteria by direct PCR and an ICS.
- •Using this method, the entire analysis process was performed simply and rapidly.
- •Oral bacteria were detected in most saliva swabs, but not in other body fluids.
- •Oral bacteria were detected in a sufficient number of mock forensic samples.
Abstract
In this paper, we describe the development of a novel method to detect oral bacteria
by combining direct polymerase chain reaction (direct PCR) with an immunochromatographic
strip (ICS), enabling the identification of saliva in forensic samples. Direct PCR
was first used to directly amplify specific oral bacterial sequences (from Streptococcus sanguinis and Streptococcus salivarius) from swab samples, circumventing the need for tedious sample preparation steps such
as cell lysis and DNA extraction and purification. The resultant amplicons were then
colorimetrically detected on an ICS, a much more convenient, cost-effective, and user-friendly
detection method than those currently available, thereby allowing the presence or
absence of the target oral bacteria to be determined with the naked eye. Moreover,
the entire analysis process was performed rapidly and with ease using this combination
of direct PCR amplification from swab samples and ICS-based amplicon detection. This
method successfully detected S. sanguinis and S. salivarius in most of the saliva swab samples tested, and returned negative results using blood,
semen, urine, and vaginal fluid swab samples. Furthermore, S. sanguinis and S. salivarius were detected in a large number of mock forensic samples using this technique, which
suggests that direct PCR and ICS-based detection of oral bacteria is sufficient to
demonstrate the presence of saliva. Thus, we believe that the proposed method could
be very useful for the identification of saliva in forensic applications.
Keywords
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Article info
Publication history
Published online: December 20, 2017
Accepted:
December 19,
2017
Received in revised form:
November 14,
2017
Received:
August 28,
2017
Identification
Copyright
© 2017 Elsevier B.V. All rights reserved.
