Estimating the Time Since Deposition of Saliva Stains With a Targeted Bacterial DNA Approach: A Proof-of-Principle Study

Focus on studying the effects of different exposure durations on the microbial structures and characteristics of three types of body fluids

BACKGROUND

Body fluid traceability inferences can provide important clues to the investigation of forensic cases. Microbiome has been proven to be well applied in forensic body fluid traceability studies. Most of the specimens at crime scenes are often exposed to the external environment when collected, so it is extremely important to exploring the structure characteristics of microbial communities of body fluid samples under different exposure durations for tracing the origin of body fluids based on microorganisms.

METHODS

Full-length 16S rRNA sequencing technology and multiple data analysis methods were used to explore the microbial changes in three types of body fluid samples at five different exposure time points.

RESULTS

With increasing exposure time, the Proteobacteria abundance gradually increased in the negative control and body fluid samples, and the Bacteroidetes and Firmicutes abundance decreased gradually, but the relative abundance of dominant genera in each body fluid remained dynamically stable. The microbial community structures of those samples from the same individual at different exposure durations were similar, and there were no significant differences in the microbial community structures among the different exposure time points. LEfSe and random forest analyses were applied to screen stable and differential microbial markers among body fluids, such as Streptococcus thermophilus, Streptococcus pneumoniae and Haemophilus parainfluenzae in saliva; Lactobacillus iners and Streptococcus agalactiae in vaginal fluid.

CONCLUSIONS

There were no significant differences in microbial community structures of the three types of body fluid samples exposed to the environment for various time periods, although the relative abundance of some microbes in these samples would change. The exposed samples could still be traced back to their source of the body fluid samples using the microbial community structures.

Spitting in the wind?-The challenges of RNA sequencing for biomarker discovery from saliva

Forensic trace contextualization, i.e., assessing information beyond who deposited a biological stain, has become an issue of great and steadily growing importance in forensic genetic casework and research. The human transcriptome encodes a wide variety of information and thus has received increasing interest for the identification of biomarkers for different aspects of forensic trace contextualization over the past years. Massively parallel sequencing of reverse-transcribed RNA ("RNA sequencing") has emerged as the gold standard technology to characterize the transcriptome in its entirety and identify RNA markers showing significant expression differences not only between different forensically relevant body fluids but also within a single body fluid between forensically relevant conditions of interest. Here, we analyze the quality and composition of four RNA sequencing datasets (whole transcriptome as well as miRNA sequencing) from two different research projects (the RNAgE project and the TrACES project), aiming at identifying contextualizing forensic biomarker from the forensically relevant body fluid saliva. We describe and characterize challenges of RNA sequencing of saliva samples arising from the presence of oral bacteria, the heterogeneity of sample composition, and the confounding factor of degradation. Based on these observations, we formulate recommendations that might help to improve RNA biomarker discovery from the challenging but forensically relevant body fluid saliva.

Multi-omics integration strategy in the post-mortem interval of forensic science

Estimates of post-mortem interval (PMI), which often serve as pivotal evidence in forensic contexts, are fundamentally based on assessments of variability among diverse molecular markers (including proteins and metabolites), their correlations, and their temporal changes in post-mortem organisms. Nevertheless, the present approach to estimating the PMI is not comprehensive and exhibits poor performance. We developed an innovative approach that integrates multi-omics and artificial intelligence, using multimolecular, multimarker, and multidimensional information to accurately describe the intricate biological processes that occur after death, ultimately enabling inference of the PMI. Called the multi-omics stacking model (MOSM), it combines metabolomics, protein microarray electrophoresis, and fourier transform-infrared spectroscopy data. It shows improved prediction accuracy of the PMI, which is urgently needed in the forensic field. It achieved an accuracy of 0.93, generalized area under the receiver operating characteristic curve of 0.98, and minimum mean absolute error of 0.07. The MOSM integration framework not only considers multiple markers but also incorporates machine-learning models with distinct algorithmic principles. The diversity of biological mechanisms and algorithmic models further ensures the generalizability and robustness of PMI estimation.

Transcriptomic changes and prediction of time since deposition of blood stains

In forensics, it is important to determine the time since deposition (TSD) of bloodstains, one of the most common types of biological evidence in criminal cases. However, no effective TSD inference methods have been established despite extensive attempts in forensic science. Our study investigated the changes in the blood transcriptome over time, and we found that degradation could be divided into four stages (days 0-2, 4-14, 21-56, and 84-168) at 4 °C. A random forest prediction model based on these transcriptional changes was trained on experimental samples and tested in separate test samples. This model was able to successfully predict TSD (area under the curve [AUC] = 0.995, precision = 1, and recall = 1). Thus, this proof-of-concept pilot study has practical significance for assessing physical evidence. Meanwhile, 11 upregulated and 13 downregulated transcripts were identified as potential time-marker transcripts, laying a foundation for further development of TSD analysis methods in forensic science and crime scene investigation.

Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood

In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.

Preliminary assessment of three quantitative approaches for estimating time-since-deposition from autofluorescence and morphological profiles of cell populations from forensic biological samples

Determining when DNA recovered from a crime scene transferred from its biological source, i.e., a sample's 'time-since-deposition' (TSD), can provide critical context for biological evidence. Yet, there remains no analytical techniques for TSD that are validated for forensic casework. In this study, we investigate whether morphological and autofluorescence measurements of forensically-relevant cell populations generated with Imaging Flow Cytometry (IFC) can be used to predict the TSD of 'touch' or trace biological samples. To this end, three different prediction frameworks for estimating the number of day(s) for TSD were evaluated: the elastic net, gradient boosting machines (GBM), and generalized linear mixed model (GLMM) LASSO. Additionally, we transformed these continuous predictions into a series of binary classifiers to evaluate the potential utility for forensic casework. Results showed that GBM and GLMM-LASSO showed the highest accuracy, with mean absolute error estimates in a hold-out test set of 29 and 21 days, respectively. Binary classifiers for these models correctly binned 94-96% and 98-99% of the age estimates as over/under 7 or 180 days, respectively. This suggests that predicted TSD using IFC measurements coupled to one or, possibly, a combination binary classification decision rules, may provide probative information for trace biological samples encountered during forensic casework.

Quantitative PCR analysis of bloodstains of different ages

An accurate method to estimate the age of a stain or the time since deposition (TsD) would represent an important tool in police investigations for evaluating the true relevance of a stain. In this study, two laboratories reproduced an mRNA-based method for TsD estimation published by another group. The qPCR-based assay includes four transcripts (B2M, LGALS2, CLC, and S100A12) and showed preferential degradation of the 5' end over the 3' end. In this study, the blood-specific marker ALAS2 was added to examine whether it would show the same degradation pattern. Based on our qPCR data several elastic net models with different penalty combinations were created, using training data from the two laboratories separately and combined. Each model was then used to estimate the age of bloodstains from two independent test sets each laboratory had prepared. The elastic net model built on both datasets with training samples up to 320 days old displayed the best prediction performance across all test samples (MAD=18.9 days). There was a substantial difference in the prediction performance for the two laboratories: Restricting TsD to up to 100 days for test data, one laboratory obtained an MAD of 2.0 days when trained on its own data, whereas the other laboratory obtained an MAD of 15 days.

The Oral Microbiome for Geographic Origin: An Italian Study

The human oral microbiome has primarily been studied in clinical settings and for medical purposes. More recently, oral microbial research has been incorporated into other areas of study. In forensics, research has aimed to exploit the variation in composition of the oral microbiome to answer forensic relevant topics, such as human identification and geographical provenience. Several studies have focused on the use of microbiome for continental, national, or ethnic origin evaluations. However, it is not clear how the microbiome varies between similar ethnic populations across different regions in a country. We report here a comparison of the oral microbiomes of individuals living in two regions of Italy - Lombardy and Piedmont. Oral samples were obtained by swabbing the donors' oral mucosa, and the V4 region of the 16S rRNA gene was sequenced from the extracted microbial DNA. Additionally, we compared the oral and the skin microbiome from a subset of these individuals, to provide an understanding of which anatomical region may provide more robust results that can be useful for forensic human identification. Initial analysis of the oral microbiota revealed the presence of a core oral microbiome, consisting of nine taxa shared across all oral samples, as well as unique donor characterising taxa in 31 out of 50 samples. We also identified a trend between the abundance of Proteobacteria and Bacteroidota and the smoking habits, and of Spirochaetota and Synergistota and the age of the enrolled participants. Whilst no significant differences were observed in the oral microbial diversity of individuals from Lombardy or Piedmont, we identified two bacterial families - Corynebacteriaceae and Actinomycetaceae - that showed abundance trends between the two regions. Comparative analysis of the skin and oral microbiota showed significant differences in the alpha (p = 0.0011) and beta (Pr(>F)= 9.999e-05) diversities. Analysis of skin and oral samples from the same donor further revealed that the skin microbiome contained more unique donor characterising taxa than the oral one. Overall, this study demonstrates that whilst the oral microbiome of individuals from the same country and of similar ethnicity are largely similar, there may be donor characterising taxa that might be useful for identification purposes. Furthermore, the bacterial signatures associated with certain lifestyles could provide useful information for investigative purposes. Finally, additional studies are required, the skin microbiome may be a better discriminant for human identification than the oral one.

Microbes in fingerprints: A source for dating crime evidence?

Interest in the human microbiome has grown in recent years because of increasing applications to biomedicine and forensic science. However, the potential for dating evidence at a crime scene based upon time-dependent changes in microbial signatures has not been established, despite a relatively straightforward scientific process for isolating the microbiome. We hypothesize that modifications in microbial diversity, abundance, and succession can provide estimates of the time a surface was touched for investigative purposes. In this proof-of-concept research, the sequencing and analysis of the 16 S rRNA gene from microbes present in fresh and aged latent fingerprints deposited by three donors with pre- and post-washed hands is reported. The stability of major microbial phyla is confirmed while the dynamics of less abundant groups is described up to 21 days post-deposition. Most importantly, a phylum is suggested as the source for possible biological markers to date fingerprints: Deinococcus-Thermus.

Microbiome-Based Stain Analyses in Crime Scenes

Recent advances in next-generation sequencing technologies (NGS) coupled with machine learning have demonstrated the potential of microbiome-based analyses in applied areas such as clinical diagnostics and forensic sciences. Particularly in forensics, microbial markers in biological stains left at a crime scene can provide valuable information for the reconstruction of crime scene cases, as they contain information on bodily origin, the time since deposition, and donor(s) of the stain. Importantly, microbiome-based analyses provide a complementary or an alternative approach to current methods when these are limited or not feasible. Despite the promising results from recent research, microbiome-based stain analyses are not yet employed in routine casework. In this review, we highlight the two main gaps that need to be addressed before we can successfully integrate microbiome-based analyses in applied areas with a special focus on forensic casework: one is a comprehensive assessment of the method's strengths and limitations, and the other is the establishment of a standard operating procedure. For the latter, we provide a roadmap highlighting key decision steps and offering laboratory and bioinformatic workflow recommendations, while also delineating those aspects that require further testing. Our goal is to ultimately facilitate the streamlining of microbiome-based analyses within the existing forensic framework to provide alternate lines of evidence, thereby improving the quality of investigations.

Optimization of DNA extraction and sampling methods for successful forensic microbiome analyses of the skin and saliva

Microbiome studies have contributed to many fields, such as healthcare and medicine; however, these studies are relatively limited in forensics. Microbiome analyses can provide information, such as geolocation and ancestry information, when short tandem repeat (STR) profiling fails. In this study, methods for DNA extraction and sampling from the skin and saliva were optimized for the construction of a Korean Forensic Microbiome Database (KFMD). DNA yields were estimated using four DNA extraction kits, including two automated kits (Maxwell® FSC DNA IQ™ Casework Kit and PrepFiler™ Forensic DNA Extraction Kit, updated) and two manual kits (QIAamp DNA Mini Kit and QIAamp DNA Micro Kit) commonly used in forensic DNA profiling laboratories. Next-generation sequencing of the 16S rRNA V4 region was performed to analyze microbial communities in samples. The Bacterial Transport Swab with Liquid Media (NobleBio), two cotton swabs (PoongSung and Puritan), and nylon-flocked swabs (NobleBio and COPAN) were tested for DNA recovery. The PrepFiler and Maxwell kits showed the highest yields of 3.884 ng/μL and 23.767 ng/μL from the scalp and saliva, respectively. With respect to DNA recovery, nylon-flocked swabs performed better than cotton swabs. The relative abundances of taxa sorted by DNA extraction kits were similar contributions; however, with significant differences in community composition between scalp and saliva samples. Lawsonella and Veillonella were the most abundant genera in the two sample types. Thus, the Maxwell® FSC DNA IQ™ Casework Kit and nylon-flocked swab (NobleBio) were optimal for DNA extraction and collection in microbiome analyses.

Whole-genome sequencing of artificial single-nucleotide variants induced by DNA degradation in biological crime scene traces

The aim of this study was to identify artificial single-nucleotide variants (SNVs) in degraded trace DNA samples. In a preliminary study, blood samples were stored for up to 120 days and whole-genome sequencing was performed using the Snakemake workflow dna-seq-gatk-variant-calling to identify positions that vary between the time point 0 sample and the aged samples. In a follow-up study on blood and saliva samples stored under humid and dry conditions, potential marker candidates for the estimation of the age of a blood stain (= time since deposition) were identified. Both studies show that a general decrease in the mean fragment size of the libraries over time was observed, presumably due to the formation of abasic sites during DNA degradation which are more susceptible to strand breaks by mechanical shearing of DNA. Unsurprisingly, an increase in the number of failed genotype calls (no coverage) was detected over time. Both studies indicated the presence of artificial SNVs with the majority of changes happening at guanine and cytosine positions. This confirms previous studies and can be explained by depurination through hydrolytic attacks which more likely deplete guanine while deamination leads to cytosine to thymine variants. Even complete genotype switches from homozygote 0/0 genotypes to the opposite 1/1 genotypes were observed. While positions with such drastic changes might provide suitable candidate markers for estimating short-term time since deposition (TsD), 11 markers were identified which show a slower gradual change of the relative abundance of the artificial variant in both blood and saliva samples, irrespective of storage conditions.

Recent advances in forensic biology and forensic DNA typing: INTERPOL review 2019-2022

This review paper covers the forensic-relevant literature in biological sciences from 2019 to 2022 as a part of the 20th INTERPOL International Forensic Science Managers Symposium. Topics reviewed include rapid DNA testing, using law enforcement DNA databases plus investigative genetic genealogy DNA databases along with privacy/ethical issues, forensic biology and body fluid identification, DNA extraction and typing methods, mixture interpretation involving probabilistic genotyping software (PGS), DNA transfer and activity-level evaluations, next-generation sequencing (NGS), DNA phenotyping, lineage markers (Y-chromosome, mitochondrial DNA, X-chromosome), new markers and approaches (microhaplotypes, proteomics, and microbial DNA), kinship analysis and human identification with disaster victim identification (DVI), and non-human DNA testing including wildlife forensics. Available books and review articles are summarized as well as 70 guidance documents to assist in quality control that were published in the past three years by various groups within the United States and around the world.

Application of Microbiome in Forensics

Recent advances in next-generation sequencing technology and improvements in bioinformatics have expanded the scope of microbiome analysis as a forensic tool. Microbiome research is concerned with the study of the compositional profile and diversity of microbial flora as well as the interactions between microbes, hosts, and the environment. It has opened up many new possibilities for forensic analysis. In this review, we discuss various applications of microbiomes in forensics, including identification of individuals, geolocation inference, post-mortem interval (PMI) estimation, and others.

Determination of the Time since Deposition of Blood Traces Utilizing a Liquid Chromatography-Mass Spectrometry-Based Proteomics Approach

Knowledge about when a bloodstain was deposited at a crime scene can be of critical value in forensic investigation. A donor of a genetically identified bloodstain could be linked to a suspected time frame and the crime scene itself. Determination of the time since deposition (TsD) has been extensively studied before but has yet to reach maturity. We therefore conducted a proof-of-principle study to study time- and storage-dependent changes of the proteomes of dried blood stains. A bottom-up proteomics approach was employed, and high-resolution liquid-chromatography-mass-spectrometry (HR-LC-MS) and data-independent acquisition (DIA) were used to analyze samples aged over a 2 month period and two different storage conditions. In multivariate analysis, samples showed distinct clustering according to their TsD in both principal component analysis (PCA) and in partial least square discriminant analysis (PLS DA). The storage condition alters sample aging and yields different separation-driving peptides in hierarchical clustering and in TsD marker peptide selection. Certain peptides and amino acid modifications were identified and further assessed for their applicability in assessing passed TsD. A prediction model based on data resampling (Jackknife) was applied, and prediction values for selected peptide ratios were created. Depending on storage conditions and actual sample age, mean prediction performances ranges in between 70 and 130% for the majority of peptides and time points. This places this study as a first in investigating LC-MS based bottom-up proteomics approaches for TsD determination.

Estimating the time since deposition (TsD) in saliva stains using temporal changes in microbial markers

Determining the time since deposition (TsD) of traces could be helpful in the investigation of criminal offenses. However, there are no reliable markers and models available for the inference of short-term TsD. The goal of this study was to investigate the potential of the succession pattern of human salivary microbial communities to serve as an efficiency TsD prediction tool in the resolution of the forensic cases. Saliva stains exposed to indoor conditions up to 20 days were collected and analyzed by 16S rRNA profiling using high-throughput sequencing technique. Noticeable differences in microbial composition were observed between different time points, and the indoor exposure time of saliva stains were inversely correlated with alpha diversity estimates across the measured time period. The sequencing results were used to identify TsD-dependent bacterial indicators to regress a generalized random forest model, resulting in a mean absolute deviation (MAD) of 1.41 days. Furthermore, a simplified TsD predictive model was also developed utilizing Enhydrobacter, Paenisporosarcina, and Janthinobacterium by quantitative PCR (qPCR) with a MAD of 1.32 days, and then forensic practice assessment were also performed by using mock samples with a MAD of 3.53 days. In conclusion, this study revealed significant changes in salivary microbial abundance as the prolongation of TsD. It demonstrated that the microbial biomarkers could be invoked as a "clock" for TsD estimation in human dried saliva stains.

Integrating the human microbiome in the forensic toolkit: Current bottlenecks and future solutions

Over the last few years, advances in massively parallel sequencing technologies (also referred to next generation sequencing) and bioinformatics analysis tools have boosted our knowledge on the human microbiome. Such insights have brought new perspectives and possibilities to apply human microbiome analysis in many areas, particularly in medicine. In the forensic field, the use of microbial DNA obtained from human materials is still in its infancy but has been suggested as a potential alternative in situations when other human (non-microbial) approaches present limitations. More specifically, DNA analysis of a wide variety of microorganisms that live in and on the human body offers promises to answer various forensically relevant questions, such as post-mortem interval estimation, individual identification, and tissue/body fluid identification, among others. However, human microbiome analysis currently faces significant challenges that need to be considered and overcome via future forensically oriented human microbiome research to provide the necessary solutions. In this perspective article, we discuss the most relevant biological, technical and data-related issues and propose future solutions that will pave the way towards the integration of human microbiome analysis in the forensic toolkit.

On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime

Body fluid and body tissue identification are important in forensic science as they can provide key evidence in a criminal investigation and may assist the court in reaching conclusions. Establishing a link between identifying the fluid or tissue and the DNA profile adds further weight to this evidence. Many forensic laboratories retain techniques for the identification of biological fluids that have been widely used for some time. More recently, many different biomarkers and technologies have been proposed for identification of body fluids and tissues of forensic relevance some of which are now used in forensic casework. Here, we summarize the role of body fluid/ tissue identification in the evaluation of forensic evidence, describe how such evidence is detected at the crime scene and in the laboratory, elaborate different technologies available to do this, and reflect real life experiences. We explain how, by including this information, crucial links can be made to aid in the investigation and solution of crime.