Identification of vaginal fluid, saliva, and feces using microbial signatures in a Han Chinese population

Abstract

In recent years, forensic scientists have focused on the discrimination of body fluids using microbial signatures. In this study, we performed PCR-based detection of microbial signatures of vaginal fluid, saliva, and feces in a Han Chinese population. We investigated the 16S rRNA genes of Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus jensenii, Lactobacillus iners, and Atopobium vaginae in vaginal fluid, the 16S rRNA and the glucosyltransferase enzyme genes of Streptococcus salivarius and Streptococcus mutans in saliva, and the 16S rRNA genes of Enterococcus species, the RNA polymerase β-subunit gene of Bacteroides uniformis and Bacteroides vulgatus, and the α-1-6 mannanase gene of Bacteroides thetaiotaomicron in feces. As a result, the detection proportions of L. crispatus, L. gasseri, L. jensenii, L. iners, and A. vaginae were 15/16, 5/16, 8/16, 14/16, and 3/16 in 16 vaginal fluid donors, respectively. L. crispatus and L. jensenii were specifically detected in vaginal fluid; L. gasseri, L. iners, and A. vaginae were also detected in non-vaginal fluid. S. salivarius and S. mutans were not specifically detected in saliva. The detection proportions of Enterococcus species, B. uniformis, B. vulgatus, and B. thetaiotaomicron in 16 feces samples were 16/16, 12/16, 15/16, and 11/16, respectively. B. uniformis and B. thetaiotaomicron were specifically detected in feces. In addition, DNA samples prepared for the identification of body fluid can also be used for individual identification by short tandem repeat typing. The mean detection sensitivities of L. crispatus and L. jensenii were 0.362 and 0.249 pg/uL, respectively. In conclusion, L. crispatus, L. jensenii, B. uniformis, and B. thetaiotaomicron can be used as effective markers for forensic identification of vaginal fluid and feces.

Keywords: Bacteria; Body fluid identification; Feces; Forensic science; Han Chinese; Saliva; Vaginal fluid.