Abstract
Information on the time when a stain was deposited at a crime scene can be valuable in forensic investigations. It can link a DNA-identified stain donor with a crime or provide a post-mortem interval estimation in cases with cadavers. The available methods for estimating stain deposition time have limitations of different types and magnitudes. In this proof-of-principle study we investigated for the first time the use of microbial DNA for this purpose in human saliva stains. First, we identified the most abundant and frequent bacterial species in saliva using publicly available 16S rRNA gene next generation sequencing (NGS) data from 1,848 samples. Next, we assessed time-dependent changes in 15 identified species using de-novo 16S rRNA gene NGS in the saliva stains of two individuals exposed to indoor conditions for up to 1 year. We selected four bacterial species, i.e., Fusobacterium periodonticum, Haemophilus parainfluenzae, Veillonella dispar, and Veillonella parvula showing significant time-dependent changes and developed a 4-plex qPCR assay for their targeted analysis. Then, we analyzed the saliva stains of 15 individuals exposed to indoor conditions for up to 1 month. Bacterial counts generally increased with time and explained 54.9% of the variation (p = <2.2E–16). Time since deposition explained ≥86.5% and ≥88.9% of the variation in each individual and species, respectively (p = <2.2E–16). Finally, based on sample duplicates we built and tested multiple linear regression models for predicting the stain deposition time at an individual level, resulting in an average mean absolute error (MAE) of 5 days (ranging 3.3–7.8 days). Overall, the deposition time of 181 (81.5%) stains was correctly predicted within 1 week. Prediction models were also assessed in stains exposed to similar conditions up to 1 month 7 months later, resulting in an average MAE of 8.8 days (ranging 3.9–16.9 days). Our proof-of-principle study suggests the potential of the DNA profiling of human commensal bacteria as a method of estimating saliva stains time since deposition in the forensic scenario, which may be expanded to other forensically relevant tissues. The study considers practical applications of this novel approach, but various forensic developmental validation and implementation criteria will need to be met in more dedicated studies in the future.
Highlights
In routine forensic investigations, DNA profiling based on short tandem repeats (STRs) is the gold standard for identifying the individuals who left a biological sample at the crime scene (Butler, 2004)
We aimed to design a suitable 4-plex qPCR assay based on TaqMan probe technology that would allow for the simultaneous analysis of all four selected bacterial species using species-specific primers that target single-copy genes
In the American Gut Project (AGP) study, R. mucilaginosa was the most abundant species accounting for 10.7% (3,305,923) of the reads, whereas P. salivae was the least abundant accounting for 0.47% (146,083) of the reads
Summary
In routine forensic investigations, DNA profiling based on short tandem repeats (STRs) is the gold standard for identifying the individuals who left a biological sample at the crime scene (Butler, 2004). One important additional piece of information, which can be crucial to solving a case, is knowledge of the time frame when the person identified by DNA-based profiling left the biological stain at the scene. Knowing the time since deposition of a crime scene stain can help the police assess the alibis of suspects or provide investigative information to search for the right suspect. When multiple biological traces belonging to different donors are found at a scene, information on their time since deposition may help investigators select the ones with the highest investigative value for further analysis, in cases where the time of the crime is known. In crime scenes involving (parts of) a corpse, estimation of the time since deposition of the stains found around/on the body can serve as an additional method for determining the time since death, i.e., post-mortem interval (PMI)
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