A bacterial signature-based method for the identification of seven forensically relevant human body fluids.

Detection and identification of body fluids plays a crucial role in criminal investigation, as it provides information on the source of the DNA as well as corroborative evidence regarding the crime committed, scene, and/or association with persons of interest. Historically, forensic serological methods have been chemical, immunological, catalytic, spectroscopic, and/or microscopic in nature. However, most of these methods are presumptive, with few robust confirmatory exceptions. In recent years several new molecular methods (mRNA, miRNA, DNA methylation, etc.) have been proposed; although promising, these methods require high quality human DNA or RNA. Additional steps are required in RNA based methods. Additionally, RNA based methods cannot be used for old cases where only DNA extracts remain to sample from. In this study, a novel non-human DNA (microbiome) based method was developed for the identification of the majority of forensically relevant human biological samples. Eight hundred and twelve (n = 812) biological samples (semen, vaginal fluid, menstrual blood, saliva, feces, urine, and blood) were collected and preserved using methods commonly used in forensic laboratories for evidence collection. Variable region four (V4) of 16 S ribosomal DNA (16 S rDNA) was amplified using a dual-indexing strategy and then sequenced on the MiSeq FGx sequencing platform using the MiSeq Reagent Kit v2 (500 cycles) and following the manufacturer's protocol. Machine learning prediction models were used to assess the classification accuracy of the newly developed method. As there was no significant difference in bacterial communities between vaginal fluid, menstrual blood, and female urine, these were combined as female intimate samples. Except in urine, the bacterial structures associated with male and female body fluid samples were not significantly different from one another. The newly developed method accurately identified human body fluid samples with an overall accuracy of more than 88%. This newly developed bacterial signature-based method is fast (no additional steps are needed as the same DNA can be used for both body fluid identification and STR typing), efficient (consume less sample as a single test can identify all major body fluids), sensitive (needs only 5 pg of bacterial DNA), accurate, and can be easily added into a forensic high throughput sequencing (HTS) panel.

An accurate bacterial DNA quantification assay for HTS library preparation of human biological samples.

Sequencing and classification of microbial taxa within forensically relevant biological fluids has the potential for applications in the forensic science and biomedical fields. The quantity of bacterial DNA from human samples is currently estimated based on quantity of total DNA isolated. This method can miscalculate bacterial DNA quantity due to the mixed nature of the sample, and consequently library preparation is often unreliable. We developed an assay that can accurately and specifically quantify bacterial DNA within a mixed sample for reliable 16S ribosomal DNA (16S rDNA) library preparation and high throughput sequencing (HTS). A qPCR method was optimized using universal 16S rDNA primers, and a commercially available bacterial community DNA standard was used to develop a precise standard curve. Following qPCR optimization, 16S rDNA libraries from saliva, vaginal and menstrual secretions, urine, and fecal matter were amplified and evaluated at various DNA concentrations; successful HTS data were generated with as low as 20 pg of bacterial DNA. Changes in bacterial DNA quantity did not impact observed relative abundances of major bacterial taxa, but relative abundance changes of minor taxa were observed. Accurate quantification of microbial DNA resulted in consistent, successful library preparations for HTS analysis.