Microbiome-based body site of origin classification of forensically relevant blood traces

Forensic Microbiology: When, Where and How

Forensic microbiology is a relatively new discipline, born in part thanks to the development of advanced methodologies for the detection, identification and characterization of microorganisms, and also in relation to the growing impact of infectious diseases of iatrogenic origin. Indeed, the increased application of medical practices, such as transplants, which require immunosuppressive treatments, and the growing demand for prosthetic installations, associated with an increasing threat of antimicrobial resistance, have led to a rise in the number of infections of iatrogenic origin, which entails important medico-legal issues. On the other hand, the possibility of detecting minimal amounts of microorganisms, even in the form of residual traces (e.g., their nucleic acids), and of obtaining gene and genomic sequences at contained costs, has made it possible to ask new questions of whether cases of death or illness might have a microbiological origin, with the possibility of also tracing the origin of the microorganisms involved and reconstructing the chain of contagion. In addition to the more obvious applications, such as those mentioned above related to the origin of iatrogenic infections, or to possible cases of infections not properly diagnosed and treated, a less obvious application of forensic microbiology concerns its use in cases of violence or violent death, where the characterization of the microorganisms can contribute to the reconstruction of the case. Finally, paleomicrobiology, e.g., the reconstruction and characterization of microorganisms in historical or even archaeological remnants, can be considered as a sister discipline of forensic microbiology. In this article, we will review these different aspects and applications of forensic microbiology.

Integrative lncRNA, circRNA, and mRNA analysis reveals expression profiles of six forensic body fluids/tissue

RNAs have attracted much attention in forensic body fluid/tissue identification (BFID) due to their tissue-specific expression characteristics. Among RNAs, long RNAs (e.g., mRNA) have a higher probability of containing more polymorphic sites that can be used to assign the specific donor of the body fluid/tissue. However, few studies have characterized their overall profiles in forensic science. In this study, we sequenced the transcriptomes of 30 samples from venous blood, menstrual blood, semen, saliva, vaginal secretion, and skin tissue, obtaining a comprehensive picture of mRNA, lncRNA, and circRNA profiles. A total of 90,305 mRNAs, 102,906 lncRNAs (including 19,549 novel lncRNAs), and 40,204 circRNAs were detected. RNA type distribution, length distribution, and expression distribution were presented according to their annotation and expression level, and many novel body fluid/tissue-specific RNA markers were identified. Furthermore, the cognate relations among the three RNAs were analyzed according to gene annotations. Finally, SNPs and InDels from RNA transcripts were genotyped, and 21,611 multi-SNP and 4,471 multi-InDel transcriptomic microhaplotypes (tMHs) were identified. These results provide a comprehensive understanding of transcriptome profiles, which could provide new avenues for tracing the origin of the body fluid/tissue and identifying an individual.

Body fluids should be identified before estimating the time since deposition (TsD) in microbiome-based stain analyses for forensics

Identification and the time since deposition (TsD) estimation of body fluid stains from a crime scene could provide valuable information for solving the cases and are always difficult for forensics. Microbial characteristics were considered as a promising biomarker to address the issues. However, changes in the microbiota may damage the specific characteristics of body fluids. Correspondingly, incorrect body fluid identification may result in inaccurate TsD estimation. The mutual influence is not well understood and limited the codetection. In the current study, saliva, semen, vaginal secretion, and menstrual blood samples were exposed to indoor conditions and collected at eight time points (from fresh to 30 days). High-throughput sequencing based on the 16S rRNA gene was performed to characterize the microbial communities. The results showed that a longer TsD could decrease the discrimination of different body fluid stains. However, the accuracies of identification still reached a quite high value even without knowing the TsD. Correspondingly, the mean absolute error (MAE) of TsD estimation significantly increased without distinguishing the types of body fluids. The predictive TsD of menstrual blood reached a quite low MAE (1.54 ± 0.39 d). In comparison, those of saliva (6.57 ± 1.17 d), semen (6.48 ± 1.33 d), and vaginal secretion (5.35 ± 1.11 d) needed to be further improved. The great effect of individual differences on these stains limited the TsD estimation accuracy. Overall, microbial characteristics allow for codetection of body fluid identification and TsD estimation, and body fluids should be identified before estimating TsD in microbiome-based stain analyses.IMPORTANCEEmerged evidences suggest microbial characteristics could be considered a promising tool for identification and time since deposition (TsD) estimation of body fluid stains. However, the two issues should be studied together due to a potential mutual influence. The current study provides the first evidence to understand the mutual influence and determines an optimal process for codetection of identification and TsD estimation for unknown stains for forensics. In addition, we involved aged stains into our study for identification of body fluid stains, rather than only using fresh stains like previous studies. This increased the predictive accuracy. We have preliminary verified that individual differences in microbiotas limited the predictive accuracy of TsD estimation for saliva, semen, and vaginal secretion. Microbial characteristics could provide an accurate TsD estimation for menstrual blood. Our study benefits the comprehensive understanding of microbiome-based stain analyses as an essential addition to previous studies.

Evaluation of the Microbiome Identification of Forensically Relevant Biological Fluids: A Pilot Study

In forensic sciences, body fluids, or biological traces, are a major source of information, and their identification can play a decisive role in criminal investigations. Currently, the nature of biological fluids is assessed using immunological, physico-chemical, mRNA and epigenetic methods, but these have limits in terms of sensitivity and specificity. The emergence of next-generation sequencing technologies offers new opportunities to identify the nature of body fluids by determining bacterial communities. The aim of this pilot study was to assess whether analysis of the bacterial communities in isolated and mixed biological fluids could reflect the situation observed in real forensics labs. Several samples commonly encountered in forensic sciences were tested from healthy volunteers: saliva, vaginal fluid, blood, semen and skin swabs. These samples were analyzed alone or in combination in a ratio of 1:1. Sequencing was performed on the Ion Gene StudioTM S5 automated sequencer. Fluids tested alone revealed a typical bacterial signature with specific bacterial orders, enabling formal identification of the fluid of interest, despite inter-individual variations. However, in biological fluid mixtures, the predominance of some bacterial microbiomes inhibited interpretation. Oral and vaginal microbiomes were clearly preponderant, and the relative abundance of their bacterial communities and/or the presence of common species between samples made it impossible to detect bacterial orders or genera from other fluids, although they were distinguishable from one another. However, using the beta diversity, salivary fluids were identified and could be distinguished from fluids in combination. While this method of fluid identification is promising, further analyses are required to consolidate the protocol and ensure reliability.

Alterations in microbiome of COVID-19 patients and its impact on forensic investigations

The human microbiome is vital for maintaining human health and has garnered substantial attention in recent years, particularly in the context of the coronavirus disease 2019 (COVID-19) outbreak. Studies have underscored significant alterations in the microbiome of COVID-19 patients across various body niches, including the gut, respiratory tract, oral cavity, skin, and vagina. These changes manifest as shifts in microbiota composition, characterized by an increase in opportunistic pathogens and a decrease in beneficial commensal bacteria. Such microbiome transformations may play a pivotal role in influencing the course and severity of COVID-19, potentially contributing to the inflammatory response. This ongoing relationship between COVID-19 and the human microbiome serves as a compelling subject of research, underscoring the necessity for further investigations into the underlying mechanisms and their implications for patient health. Additionally, these alterations in the microbiome may have significant ramifications for forensic investigations, given the microbiome's potential in establishing individual characteristics. Consequently, changes in the microbiome could introduce a level of complexity into forensic determinations. As research progresses, a more profound understanding of the human microbiome within the context of COVID-19 may offer valuable insights into disease prevention, treatment strategies, and its potential applications in forensic science. Consequently, this paper aims to provide an overarching review of microbiome alterations due to COVID-19 and the associated impact on forensic applications, bridging the gap between the altered microbiome of COVID-19 patients and the challenges forensic investigations may encounter when analyzing this microbiome as a forensic biomarker.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

[Use of microbiological data for the purposes of forensic medical examination]

The study objective was to describe the formation of forensic microbiological examination as an analysis of a new type, defined as the detection and registration of reliably measured environmental and physiological changes within the microbial community of corpse in order to substantiate the possibility of using microbiological parameters to establish the prescription of death coming. It has been determined that the knowledge of the patterns of interaction of a human and his corpse with endogenous and exogenous flora provides the basis for solving a number of traditional and new application-oriented expert tasks and the allocation of such a variety of forensic examination as forensic microbiological examination. Endogenous and exogenous human flora and its interaction with living and dead biological tissues are the objects of this kind of examination, and the dynamic patterns of such interaction are the subject of study. One of the initial relevant tasks of forensic microbiological examination consists in development of methods, adequate for the expert task to be solved, choice of the research «target», «models» for comparative analysis and medium, adequate for task in hand, as well as certification of these methods and standardization of assessment criteria for the obtained results.

The Future Is Now: Unraveling the Expanding Potential of Human (Necro)Microbiome in Forensic Investigations

The relevance of postmortem microbiological examinations has been controversial for decades, but the boom in advanced sequencing techniques over the last decade is increasingly demonstrating their usefulness, namely for the estimation of the postmortem interval. This comprehensive review aims to present the current knowledge about the human postmortem microbiome (the necrobiome), highlighting the main factors influencing this complex process and discussing the principal applications in the field of forensic sciences. Several limitations still hindering the implementation of forensic microbiology, such as small-scale studies, the lack of a universal/harmonized workflow for DNA extraction and sequencing technology, variability in the human microbiome, and limited access to human cadavers, are discussed. Future research in the field should focus on identifying stable biomarkers within the dominant Bacillota and Pseudomonadota phyla, which are prevalent during postmortem periods and for which standardization, method consolidation, and establishment of a forensic microbial bank are crucial for consistency and comparability. Given the complexity of identifying unique postmortem microbial signatures for robust databases, a promising future approach may involve deepening our understanding of specific bacterial species/strains that can serve as reliable postmortem interval indicators during the process of body decomposition. Microorganisms might have the potential to complement routine forensic tests in judicial processes, requiring robust investigations and machine-learning models to bridge knowledge gaps and adhere to Locard's principle of trace evidence.

Applications of microbiology to different forensic scenarios - A narrative review

In contrast to other forensic disciplines, forensic microbiology is still too often considered a "side activity" and is not able to make a real and concrete contribution to forensic investigations. Indeed, the various application aspects of this discipline still remain a niche activity and, as a result, microbiological investigations are often omitted or only approximated, in part due to poor report in the literature. However, in certain situations, forensic microbiology can prove to be extremely effective, if not crucial, when all other disciplines fail. Precisely because microorganisms can represent forensic evidence, in this narrative review all the major pathological forensic applications described in the literature have been presented. The goal of our review is to highlight the versatility and transversality of microbiology in forensic science and to provide a comprehensive source of literature to refer to when needed.

Development and application of a multiplex PCR system for forensic salivary identification

In forensics, accurate identification of the origin of body fluids is essential for reconstructing a crime scene or presenting strong evidence in court. Microorganisms have demonstrated great potential in body fluid identification. We developed a multiplex PCR system for forensic salivary identification, which contains five types of bacteria:Streptococcus salivarius, Neisseria subflava, Streptococcus. mutans, Bacteroides thetaiotaomicron, and Bacteroides. uniformis. And the validated studies were carried out following the validation guidelines for DNA analysis methods developed by the Scientific Working Group on DNA Analysis Methods (SWGDAM), which included tests for sensitivity, species specificity, repeatability, stability, and mixed samples, trace samples, case samples, and a population study. Our result depicted that the lowest detection limit of the system was 0.01 ng template DNA. Moreover, the corresponding bacteria can still be detected when the amount of saliva input is low to 0.1 μL for DNA extraction. In addition, the target bacteria were not detected in the DNA of human, seven common animals, and seven bacteria DNA and in nine other body fluid samples (skin, semen, blood, menstrual blood, nasal mucus, sweat, tears, urine, and vaginal secretions). Six common inhibitors such as indigo, EDTA, hemoglobin, calcium ions, alcohol and humic acid were well tolerated by the system. What is more, the salivary identification system recognized the saliva component in all mixed samples and simulated case samples. Among 400 unrelated individuals from the Chinese Han population analyzed by this novel system, the detection rates of N. subflava, S. salivarius, and S. mutans were 97.75%, 70.75%, and 19.75%, respectively, with 100% identification of saliva. In conclusion, the salivary identification system has good sensitivity, specificity, stability, and accuracy, which can be a new effective tool for saliva identification.

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.

Trends in forensic microbiology: From classical methods to deep learning

Forensic microbiology has been widely used in the diagnosis of causes and manner of death, identification of individuals, detection of crime locations, and estimation of postmortem interval. However, the traditional method, microbial culture, has low efficiency, high consumption, and a low degree of quantitative analysis. With the development of high-throughput sequencing technology, advanced bioinformatics, and fast-evolving artificial intelligence, numerous machine learning models, such as RF, SVM, ANN, DNN, regression, PLS, ANOSIM, and ANOVA, have been established with the advancement of the microbiome and metagenomic studies. Recently, deep learning models, including the convolutional neural network (CNN) model and CNN-derived models, improve the accuracy of forensic prognosis using object detection techniques in microorganism image analysis. This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep learning (DL) based on microbial genome sequencing and microbial images, and provided a future outlook on forensic microbiology.

Advances in microbial metagenomics and artificial intelligence analysis in forensic identification

Microorganisms, which are widely distributed in nature and human body, show unique application value in forensic identification. Recent advances in high-throughput sequencing technology and significant reductions in analysis costs have markedly promoted the development of forensic microbiology and metagenomics. The rapid progression of artificial intelligence (AI) methods and computational approaches has shown their unique application value in forensics and their potential to address relevant forensic questions. Here, we summarize the current status of microbial metagenomics and AI analysis in forensic microbiology, including postmortem interval inference, individual identification, geolocation, and tissue/fluid identification.

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.

A Comprehensive Characterization of Small RNA Profiles by Massively Parallel Sequencing in Six Forensic Body Fluids/Tissue

Body fluids/tissue identification (BFID) is an essential procedure in forensic practice, and RNA profiling has become one of the most important methods. Small non-coding RNAs, being expressed in high copy numbers and resistant to degradation, have great potential in BFID but have not been comprehensively characterized in common forensic stains. In this study, the miRNA, piRNA, snoRNA, and snRNA were sequenced in 30 forensic relevant samples (menstrual blood, saliva, semen, skin, venous blood, and vaginal secretion) using the BGI platform. Based on small RNA profiles, relative specific markers (RSM) and absolute specific markers (ASM) were defined, which can be used to identify a specific body fluid/tissue out of two or six, respectively. A total of 5204 small RNAs were discovered including 1394 miRNAs (including 236 novel miRNA), 3157 piRNAs, 636 snoRNAs, and 17 snRNAs. RSMs for 15 pairwise body fluid/tissue groups were discovered by differential RNA analysis. In addition, 90 ASMs that were specifically expressed in a certain type of body fluid/tissue were screened, among them, snoRNAs were reported first in forensic genetics. In brief, our study deepened the understanding of small RNA profiles in forensic stains and offered potential BFID markers that can be applied in different forensic scenarios.

Prediction of Smoking Habits From Class-Imbalanced Saliva Microbiome Data Using Data Augmentation and Machine Learning

Human microbiome research is moving from characterization and association studies to translational applications in medical research, clinical diagnostics, and others. One of these applications is the prediction of human traits, where machine learning (ML) methods are often employed, but face practical challenges. Class imbalance in available microbiome data is one of the major problems, which, if unaccounted for, leads to spurious prediction accuracies and limits the classifier's generalization. Here, we investigated the predictability of smoking habits from class-imbalanced saliva microbiome data by combining data augmentation techniques to account for class imbalance with ML methods for prediction. We collected publicly available saliva 16S rRNA gene sequencing data and smoking habit metadata demonstrating a serious class imbalance problem, i.e., 175 current vs. 1,070 non-current smokers. Three data augmentation techniques (synthetic minority over-sampling technique, adaptive synthetic, and tree-based associative data augmentation) were applied together with seven ML methods: logistic regression, k-nearest neighbors, support vector machine with linear and radial kernels, decision trees, random forest, and extreme gradient boosting. K-fold nested cross-validation was used with the different augmented data types and baseline non-augmented data to validate the prediction outcome. Combining data augmentation with ML generally outperformed baseline methods in our dataset. The final prediction model combined tree-based associative data augmentation and support vector machine with linear kernel, and achieved a classification performance expressed as Matthews correlation coefficient of 0.36 and AUC of 0.81. Our method successfully addresses the problem of class imbalance in microbiome data for reliable prediction of smoking habits.

Individual Identification with Short Tandem Repeat Analysis and Collection of Secondary Information Using Microbiome Analysis

Forensic investigation is important to analyze evidence and facilitate the search for key individuals, such as suspects and victims in a criminal case. The forensic use of genomic DNA has increased with the development of DNA sequencing technology, thereby enabling additional analysis during criminal investigations when additional legal evidence is required. In this study, we used next-generation sequencing to facilitate the generation of complementary data in order to analyze human evidence obtained through short tandem repeat (STR) analysis. We examined the applicability and potential of analyzing microbial genome communities. Microbiological supplementation information was confirmed for two of four failed STR samples. Additionally, the accuracy of the gargle sample was confirmed to be as high as 100% and was highly likely to be classified as a body fluid sample. Our experimental method confirmed that anthropological and microbiological evidence can be obtained by performing two experiments with one extraction. We discuss the advantages and disadvantages of using these techniques, explore prospects in the forensic field, and highlight suggestions for future research.

Analysis of Microbial Communities: An Emerging Tool in Forensic Sciences

The objective of forensic sciences is to find clues in a crime scene in order to reconstruct the scenario. Classical samples include DNA or fingerprints, but both have inherent limitations and can be uninformative. Another type of sample has emerged recently in the form of the microbiome. Supported by the Human Microbiome Project, the characteristics of the microbial communities provide real potential in forensics. They are highly specific and can be used to differentiate and classify the originating body site of a human biological trace. Skin microbiota is also highly specific and different between individuals, leading to its possibility as an identification tool. By extension, the possibilities of the microbial communities to be deposited on everyday objects has also been explored. Other uses include the determination of the post-mortem interval or the analysis of soil communities. One challenge is that the microbiome changes over time and can be influenced by many environmental and lifestyle factors. This review offers an overview of the main methods and applications to demonstrate the benefit of the microbiome to provide forensically relevant information.

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.

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

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.

Assessing time dependent changes in microbial composition of biological crime scene traces using microbial RNA markers

Current body fluid identification methods do not reveal any information about the time since deposition (TsD) of biological traces, even though determining the age of traces could be crucial for the investigative process. To determine the utility of microbial RNA markers for TsD estimation, we examined RNA sequencing data from five forensically relevant body fluids (blood, menstrual blood, saliva, semen, and vaginal secretion) over seven time points, ranging from fresh to 1.5 years. One set of samples was stored indoors while another was exposed to outdoor conditions. In outdoor samples, we observed a consistent compositional shift, occurring after 4 weeks: this shift was characterized by an overall increase in non-human eukaryotic RNA and an overall decrease in prokaryotic RNA. In depth analyses showed a high fraction of tree, grass and fungal signatures, which are characteristic for the environment the samples were exposed to. When examining the prokaryotic fraction in more detail, three bacterial phyla were found to exhibit the largest changes in abundance, namely Actinobacteria, Proteobacteria and Firmicutes. More detailed analyses at the order level were done using a Lasso regression analysis to find a predictive subset of bacterial taxa. We found 26 bacterial orders to be indicative of sample age. Indoor samples did not reveal such a clear compositional change at the domain level: eukaryotic and prokaryotic abundance remained relatively stable across the assessed time period. Nonetheless, a Lasso regression analysis identified 32 bacterial orders exhibiting clear changes over time, enabling the prediction of TsD. For both indoor and outdoor samples, a larger number (around 60%) of the bacterial orders identified as indicative of TsD are part of the Actinobacteria, Proteobacteria and Firmicutes. In summary, we found that the observed changes across time are not primarily due to changes associated with body fluid specific bacteria but mostly due to accumulation of bacteria from the environment. Orders of these environmental bacteria could be evaluated for TsD prediction, considering the location and environment of the crime scene. However, further studies are needed to verify these findings, determine the applicability across samples, replicates, donors, and other variables, and also to further assess the effect of different seasons and locations on the samples.

Animal Forensic Genetics

Animal forensic genetics, where the focus is on non-human species, is broadly divided in two: domestic species and wildlife. When traces of a domestic species are relevant to a forensic investigation the question of species identification is less important, as the material comes from either a dog or a cat for instance, but more relevant may be the identification of the actual pet. Identification of a specific animal draws on similar methods to those used in human identification by using microsatellite markers. The use of cat short tandem repeats to link a cat hair to a particular cat paved the way for similar identification of dogs. Wildlife forensic science is becoming accepted as a recognised discipline. There is growing acceptance that the illegal trade in wildlife is having devasting effects on the numbers of iconic species. Loci on the mitochondrial genome are used to identify the most likely species present. Sequencing the whole locus may not be needed if specific bases can be targeted. There can be benefits of increased sensitivity using mitochondrial loci for species testing, but occasionally there is an issue if hybrids are present. The use of massively parallel DNA sequencing has a role in the identification of the ingredients of traditional medicines where studies found protected species to be present, and a potential role in future species assignments. Non-human animal forensic testing can play a key role in investigations provided that it is performed to the same standards as all other DNA profiling processes.

Challenges in Human Skin Microbial Profiling for Forensic Science: A Review

The human microbiome is comprised of the microbes that live on and within an individual, as well as immediately surrounding them. Microbial profiling may have forensic utility in the identification or association of individuals with criminal activities, using microbial signatures derived from a personal microbiome. This review highlights some important aspects of recent studies, many of which have revealed issues involving the effect of contamination of microbial samples from both technical and environmental sources and their impacts on microbiome research and the potential forensic applications of microbial profiling. It is imperative that these challenges be discussed and evaluated within a forensic context to better understand the future directions and potential applications of microbial profiling for human identification. It is necessary that the limitations identified be resolved prior to the adoption of microbial profiling, or, at a minimum, acknowledged by those applying this new approach.