Microbiome Tools for Forensic Science

Volatile organic compounds produced during postmortem processes can be linked via chromatographic profiles to individual postmortem bacterial species

Decomposition odor is produced during postmortem mammalian tissue breakdown by bacteria, insects, and intrinsic chemical processes. Past research has not thoroughly investigated which volatile organic compounds (VOCs) can be linked directly to individual bacterial species on decomposing remains. The purpose of this study was to profile the VOCs produced over time by individual species of bacteria using comprehensive two-dimensional gas chromatography (GC×GC) to expand our foundational knowledge of what each bacterial species contributes to decomposition odor. Five different species of bacteria (Bacillus subtilis, Ignatzschineria indica, Ignatzschineria ureiclastica, Curtobacterium luteum, and Vagococcus lutrae) were cultured on standard nutrient agar individually and monitored daily using solid phase microextraction arrow (SPME Arrow) and GC×GC in combination with quadrupole mass spectrometry (qMS) and flame ionization detection (FID). The GC×GC-qMS/FID approach was used to generate rich VOC profiles that represented the bacterial species' metabolic VOC production longitudinally. The data obtained from the chromatographic output was used to compare with a prior study using one-dimensional GC-qMS, and also between each of the five species to investigate the extent of overlap between species. No single VOC could be found in all five bacterial species investigated, and there was little overlap in the profile between species. To further visualize these differences, chromatographic peak data was investigated using two different ordination strategies, principal component analysis (PCA) and principal coordinate analysis (PCoA). The two ordination strategies were compared with each other using a Procrustes analysis. This was performed to understand differences in ordination strategies between the separation science community and chemical ecological community. Overall, ordination strategies were found to produce similar results, as evidenced by the correlation of PCA and PCoA in the Procrustes analysis. All analysis strategies yielded distinct VOC profiles for each species. Further study of additional species will support understanding of the holistic view of decomposition odor from a chemical ecology perspective, and further support our understanding of the production of decomposition odor that culminates from such a complex environment.

Estimating postmortem interval based on oral microbial community succession in rat cadavers

The accurate estimation of the postmortem interval has been one of the crucial issues to be solved in forensic research, and it is influenced by various factors in the process of decay. With the development of high-throughput sequencing technology, forensic microbiology has become the major hot topic in forensic science, which provides new research options for postmortem interval estimation. The oral microbial community is one of the most diverse of microbiomes, ranking as the second most abundant microbiota following the gastrointestinal tract. It is remarkable that oral microorganisms have a significant function in the decay process of cadavers. Therefore, we collected outdoor soil to simulate the death environment and focused on the relationship between oral microbial community succession and PMI in rats above the soil. In addition, linear regression models and random forest regression models were developed for the relationship between the relative abundance of oral microbes and PMI. We also identified a number of microorganisms that may be important to estimate PMI, including: Ignatzschineria, Morganella, Proteus, Lysinibacillus, Pseudomonas, Globicatella, Corynebacterium, Streptococcus, Rothia, Aerococcus, Staphylococcus, and so on.

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.

Decomposition in an extreme cold environment and associated microbiome-prediction model implications for the postmortem interval estimation

Introduction

The accurate estimation of postmortem interval (PMI), the time between death and discovery of the body, is crucial in forensic science investigations as it impacts legal outcomes. PMI estimation in extremely cold environments becomes susceptible to errors and misinterpretations, especially with prolonged PMIs. This study addresses the lack of data on decomposition in extreme cold by providing the first overview of decomposition in such settings. Moreover, it proposes the first postmortem microbiome prediction model for PMI estimation in cold environments, applicable even when the visual decomposition is halted.

Methods

The experiment was conducted on animal models in the second-coldest region in the United States, Grand Forks, North Dakota, and covered 23 weeks, including the winter months with temperatures as low as -39°C. Random Forest analysis models were developed to estimate the PMI based either uniquely on 16s rRNA gene microbial data derived from nasal swabs or based on both microbial data and measurable environmental parameters such as snow depth and outdoor temperatures, on a total of 393 samples.

Results

Among the six developed models, the best performing one was the complex model based on both internal and external swabs. It achieved a Mean Absolute Error (MAE) of 1.36 weeks and an R2 value of 0.91. On the other hand, the worst performing model was the minimal one that relied solely on external swabs. It had an MAE of 2.89 weeks and an R2 of 0.73. Furthermore, among the six developed models, the commonly identified predictors across at least five out of six models included the following genera: Psychrobacter (ASV1925 and ASV1929), Carnobacterium (ASV2872) and Pseudomonas (ASV1863).

Discussion

The outcome of this research provides the first microbial model able to predict PMI with an accuracy of 9.52 days over a six-month period of extreme winter conditions.

Symbiosis takes a front and center role in biology

All animals and plants likely require interactions with microbes, often in strong, persistent symbiotic associations. While the recognition of this phenomenon has been slow in coming, it will impact most, if not all, subdisciplines of biology.

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

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.

Recovery of microbial DNA by agar-containing solution from extremely low-biomass specimens including skin

Recovering a sufficient amount of microbial DNA from extremely low-biomass specimens, such as human skin, to investigate the community structure of the microbiome remains challenging. We developed a sampling solution containing agar to increase the abundance of recovered microbial DNA. Quantitative PCR targeting the 16S rRNA gene revealed a significant increase in the amount of microbial DNA recovered from the developed sampling solution compared with conventional solutions from extremely low-biomass skin sites such as the volar forearm and antecubital fossa. In addition, we confirmed that the developed sampling solution reduces the contamination rate of probable non-skin microbes compared to the conventional solutions, indicating that the enhanced recovery of microbial DNA was accompanied by a reduced relative abundance of contaminating microbes in the 16S rRNA gene amplicon sequencing data. In addition, agar was added to each step of the DNA extraction process, which improved the DNA extraction efficiency as a co-precipitant. Enzymatic lysis with agar yielded more microbial DNA than conventional kits, indicating that this method is effective for analyzing microbiomes of low-biomass specimens.

The uselessness of using salivary microbiota in forensic identification purposes of a person with recent antibiotic use

The detection of microbial flora changes in saliva samples because of antibiotic use through advanced molecular genetic analysis is important for forensic and clinical applications. This study aims to reveal the variability in the microbial structure of human saliva after antibiotic use with metagenomic analysis techniques from a forensic point of view. Within the scope of the study, saliva samples were collected from patients who were under the effect of regional anesthesia to be administered a standardized course of antibiotic therapy that lasted for a week. The analysis was conducted on 56 saliva samples from 14 individuals over four different time intervals. Isolation of the 16S rRNA region and PCR analysis were performed prior to sequence analysis to determine the microbiome structure of the samples at phylum, genus, and species levels. As expected, changes were observed in bacterial species found in saliva samples after administration of antibiotics and this was linked to the specific type of antibiotics that were administered. This change was statistically significant for Firmicutes, Spirochetes, and Verrucomicrobiota. Furthermore, although the oral microbiome tends to return to its former state at the phylum and genus level within a 4-week period after the start of antibiotic use, it is observed that the change, especially in some bacterial species, still continues. The findings of this study show that because of the inability of stabilization at species-level in a period of 4 weeks from the start of antibiotic use, it is not suitable to assess saliva samples at species-level for forensic identification.

Microbiology and postmortem interval: a systematic review

This systematic review aims to learn if and how it is possible to use the human microbiome to indicate the time elapsed after death. Articles were searched on the PubMed database using predefined data fields and keywords; reviews, systematic reviews, and meta-analyses were excluded. The final selection included 14 papers (out of 144). The results indicated that the microorganisms present in the cadaveric island succeed predictably over time, with markers between the stages of decomposition constituting a potential innovative tool for postmortem interval (PMI) estimation. The human microbiome has the potential to be used for PMI estimation and may present advantages as microbes are present in all seasons, in all habitats, including the most extreme ones, and because microbial communities respond predictably to environmental changes.

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.

Postmortem skin microbiome signatures associated with human cadavers within the first 12 h at the morgue

Introduction

Forensic microbiome studies expanded during the last decade, aiming to identify putative bacterial biomarkers to be used for the postmortem interval (PMI) estimation. Bacterial diversity and dynamics during decomposition are influenced by each individual's micro and macroenvironment, ante and postmortem conditions, varying across body sites and time. The skin, the largest organ of the human body, hosts a diverse microbial diversity, representing the first line of defense of a living individual. Targeting the investigation of the postmortem skin microbiome could help understanding the role of microbes during decomposition, and association with the ante and postmortem conditions.

Methods

The current study aimed to identify the postmortem skin microbiome signatures associated with eight human bodies, received at the Institute of Legal Medicine Iasi, Romania, during April and May 2021. A total of 162 samples (including triplicate) representing face and hands skin microbiome were investigated via Illumina MiSeq, upon arrival at the morgue (T0) and after 12 hours (T1).

Results

The taxonomic characteristics of the skin microbiota varied across different body sites. However, there were no significant differences in taxonomic profiles between collection time, T0 and T1, except for some dynamic changes in the abundance of dominant bacteria. Moreover, different microbial signatures have been associated with a specific cause of death, such as cardiovascular disease, while an elevated blood alcohol level could be associated with a decrease in bacterial richness and diversity.

Discussion

The places where the bodies were discovered seemed to play an important role in explaining the bacterial diversity composition. This study shows promising results towards finding common postmortem bacterial signatures associated with human cadavers within the first 12h at the morgue.

Forensic Microbiology in India: A missing piece in the puzzle of criminal investigation system

BACKGROUND

Forensic Microbiology is an emerging branch of science that has great potential to assist criminal investigations. Having said that, microbial analysis is not performed routinely during forensic investigations in India. This could be attributed to lack of specific training and lack of evidence-based standard protocol.

OBJECTIVES

The authors attempt to highlight the key areas in forensic microbiology that need to be explored in a developing nation like India.

CONTENT

Forensic microbiology could help in linking a person to a crime, determining the cause of death, estimating postmortem interval (PMI), etc. Additionally, applications are being developed by forensic microbiologists across the globe to investigate the coordinated and dynamic changes in microbial activity which occur after the death of a human host. Such evidence from the human postmortem microbiome can aid in criminal investigations and administration of justice. These recent advances and developments have the potential to transform the field of forensic microbiology in a developing country.

Exploring postmortem succession of rat intestinal microbiome for PMI based on machine learning algorithms and potential use for humans

The microbial communities may undergo a meaningful successional change during the progress of decay and decomposition that could aid in determining the post-mortem interval (PMI). However, there are still challenges to applying microbiome-based evidence in law enforcement practice. In this study, we attempted to investigate the principles governing microbial community succession during decomposition of rat and human corpse, and explore their potential use for PMI of human cadavers. A controlled experiment was conducted to characterize temporal changes in microbial communities associated with rat corpses as they decomposed for 30 days. Obvious differences of microbial community structures were observed among different stages of decomposition, especially between decomposition of 0-7d and 9-30d. Thus, a two-layer model for PMI prediction was developed based on the succession of bacteria by combining classification and regression models using machine learning algorithms. Our results achieved 90.48% accuracy for discriminating groups of PMI 0-7d and 9-30d, and yielded a mean absolute error of 0.580d within 7d decomposition and 3.165d within 9-30d decomposition. Furthermore, samples from human cadavers were collected to gain the common succession of microbial community between rats and humans. Based on the 44 shared genera of rats and humans, a two-layer model of PMI was rebuilt to be applied for PMI prediction of human cadavers. Accurate estimates indicated a reproducible succession of gut microbes across rats and humans. Together these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating PMI.

Toward Oral Thanatomicrobiology-An Overview of the Forensic Implications of Oral Microflora

Introduction

The oral cavity is home to numerous microorganisms including bacteria, fungi, and viruses which together form the oral microflora. It is the second most diverse microbial site in the human body after the gastrointestinal tract. Microbial degradation is a common phenomenon that occurs after death, with the early and advanced stages of decomposition being closely associated with oral microbial activity.

Methods

This article reviews the current state of knowledge on the role of the oral microflora in postmortem events, and highlights the growing importance of terms such as forensic microbiology and thanatomicrobiome. This article also discusses next-generation sequencing, metagenomic sequencing studies, and RNA sequencing to study the oral thanatomicrobiome and epinecrotic communities in forensic oral genetics.

Results

The indigenous microorganisms in the oral cavity are among the first to respond to the process of decomposition. DNA/RNA sequencing is a relatively simple, precise, and cost-effective method to estimate biological diversity during various stages of postmortem decomposition. The field of thanatomicrobiology is rapidly evolving into a key area in forensic research.

Conclusion

This article briefly narrates oral microflora and its implications in forensic odontology. The role of microbial activity in postmortem events is gaining importance in forensic research, and further studies are needed to fully understand the potential applications of advanced technology in the study of the oral thanatomicrobiome.

A bibliometric analysis of microbial forensics from 1984 to 2022: progress and research trends

Microbial forensics is a rapidly evolving discipline that has gained significant momentum in recent years. The study evaluated relevant results over the last four decades from 1984 to 2022 all over the world, aiming to analyze the growing trends and research orientations of microbial forensics. Using "microbial forensics" as the search topic in the Web of Science Core Collection, the systematic retrieval identified 579 documents relevant to the field and draw many statistical tables and maps to make the retrieval results visible. According to further bibliometric analysis, there are an increasing number of publications related to microbial forensics from the overall trend, with the highest number of publications recorded in 2021. In terms of the total number of articles, the USA and China were both the leading contributors to the field among 40 countries. The field has developed rapidly in recent years based on the development of next-generation sequencing. Over the course of its development, there are rich keywords in the research of scholars, which focus on diversity and identification. Moreover, despite the early hot topic being PCR (the use of PCR to probe microorganisms), in recent years, the topics, markers, and the potential application of microorganisms in forensic practice have become hot, which also indicates the future research directions of microbial forensic.

MPrESS: An R-Package for Accurately Predicting Power for Comparisons of 16S rRNA Microbiome Taxa Distributions including Simulation by Dirichlet Mixture Modeling

Deep sequencing has revealed that the 16S rRNA gene composition of the human microbiome can vary between populations. However, when existing data are insufficient to address the desired study questions due to limited sample sizes, Dirichlet mixture modeling (DMM) can simulate 16S rRNA gene predictions from experimental microbiome data. We examined the extent to which simulated 16S rRNA gene microbiome data can accurately reflect the diversity within that identified from experimental data and calculate the power. Even when experimental and simulated datasets differed by less than 10%, simulation by DMM consistently overestimates power, except when using only highly discriminating taxa. Admixtures of DMM with experimental data performed poorly compared to pure simulation and did not show the same correlation with experimental data p-value and power values. While multiple replications of random sampling remain the favored method of determining the power, when the estimated sample size required to achieve a certain power exceeds the sample number, then simulated samples based on DMM can be used. We introduce an R-Package, MPrESS, to assist in power calculation and sample size estimation for a 16S rRNA gene microbiome dataset to detect a difference between populations. MPrESS can be downloaded from GitHub.

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.

High-throughput sequencing to evaluate the effects of methamphetamine on the succession of the bacterial community to estimate the postmortem interval

In forensic medical examinations, estimating the postmortem interval (PMI) is an important factor. Methamphetamine (MA) is a synthetic stimulant that is commonly abused, and estimation of the PMI after MA abuse has become one of the main tasks in forensic investigation. Microorganisms play a vital role in carrion decomposition. Analysing the bacterial succession patterns can be used as a forensic tool to estimate the PMI. The present study aimed to analyse bacterial succession changes during the decomposition of MA to estimate the PMI. We analysed bacterial communities in rabbits treated with three different concentrations of MA (0, 22.5, and 90 mg/kg) under the natural conditions of 20 °C and 70% humidity by sequencing 16S rRNA gene amplicons using the Illumina MiSeq system. We obtained 2 374 209 high-quality sequences and 2 937 operational taxonomic units (OTUs). The relative abundances of the bacterial communities varied markedly in response to different MA concentrations. Interestingly, in response to the different concentrations of MA, Bacteroidetes became disparate in the rectum in the late PMI. Increased numbers of bacterial taxa were identified in the rectum and buccal cavity samples, except at the highest concentration of MA in the rectum samples when PMI was 0-h, than were present in live rabbits. Meanwhile, the PMI correlated significantly with bacterial succession at different taxonomic levels. Our results suggested that bacterial community succession could be used as a "microbial clock" to estimate the PMI in cases of MA-related death; however, further study is required to gain a deeper understanding of this concept.

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.

Microbial ecology of vertebrate decomposition in terrestrial ecosystems

Vertebrate decomposition results in an ephemeral disturbance of the surrounding environment. Microbial decomposers are recognized as key players in the breakdown of complex organic compounds, controlling carbon and nutrient fate in the ecosystem and potentially serving as indicators of time since death for forensic applications. As a result, there has been increasing attention on documenting the microbial communities associated with vertebrate decomposition, or the 'necrobiome'. These necrobiome studies differ in the vertebrate species, microhabitats (e.g. skin vs. soil), and geographic locations studied, but many are narrowly focused on the forensic application of microbial data, missing the larger opportunity to understand the ecology of these communities. To further our understanding of microbial dynamics during vertebrate decomposition and identify knowledge gaps, there is a need to assess the current works from an ecological systems perspective. In this review, we examine recent work pertaining to microbial community dynamics and succession during vertebrate (human and other mammals) decomposition in terrestrial ecosystems, through the lens of a microbial succession ecological framework. From this perspective, we describe three major microbial microhabitats (internal, external, and soil) in terms of their unique successional trajectories and identify three major knowledge gaps that remain to be addressed.

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.

Environmental DNA as an innovative technique to identify the origins of falsified antimalarial tablets-a pilot study of the pharmabiome

Falsified medicines are a major threat to global health. Antimalarial drugs have been particularly targeted by criminals. As DNA analysis has revolutionized forensic criminology, we hypothesized that these techniques could also be used to investigate the origins of falsified medicines. Medicines may contain diverse adventitious biological contamination, and the sealed nature of blister-packages may capture and preserve genetic signals from the manufacturing processes allowing identification of production source(s). We conducted a blinded pilot study to determine if such environmental DNA (eDNA) could be detected in eleven samples of falsified and genuine artesunate antimalarial tablets, collected in SE Asia, which could be indicative of origin. Massively Parallel Sequencing (MPS) was used to characterize microbial and eukaryote diversity. Two mitochondrial DNA analysis approaches were explored to detect the presence of human DNA. Trace eDNA from these low biomass samples demonstrated sample specific signals using two target markers. Significant differences in bacterial and eukaryote DNA community structures were observed between genuine and falsified tablets and between different packaging types of falsified artesunate. Human DNA, which was indicative of likely east Asian ancestry, was found in falsified tablets. This pilot study of the 'pharmabiome' shows the potential of environmental DNA as a powerful forensic tool to assist with the identification of the environments, and hence location and timing, of the source and manufacture of falsified medicines, establish links between seizures and complement existing tools to build a more complete picture of criminal trade routes. The finding of human DNA in tablets raises important ethical issues that need to be addressed.

Postmortem submersion interval estimation of cadavers recovered from freshwater based on gut microbial community succession

Microbial community succession during decomposition has been proven to be a useful tool for postmortem interval (PMI) estimation. Numerous studies have shown that the intestinal microbial community presented chronological changes after death and was stable in terrestrial corpses with different causes of death. However, the postmortem pattern of intestinal microbial community succession in cadavers retrieved from water remains unclear. For immersed corpses, the postmortem submersion interval (PMSI) is a useful indicator of PMI. To provide reliable estimates of PMSI in forensic investigations, we investigated the gut microbial community succession of corpses submersed in freshwater and explored its potential application in forensic investigation. In this study, the intestinal microbial community of mouse submersed in freshwater that died of drowning or CO2 asphyxia (i.e., postmortem submersion) were characterized by 16S rDNA amplification and high-throughput sequencing, followed by bioinformatic analyses. The results demonstrated that the chronological changes in intestinal bacterial communities were not different between the drowning and postmortem submersion groups. α-diversity decreased significantly within 14 days of decomposition in both groups, and the β-diversity bacterial community structure ordinated chronologically, inferring the functional pathway and phenotype. To estimate PMSI, a regression model was established by random forest (RF) algorithm based on the succession of postmortem microbiota. Furthermore, 15 genera, including Proteus, Enterococcus, and others, were selected as candidate biomarkers to set up a concise predicted model, which provided a prediction of PMSI [MAE (± SE) = 0.818 (± 0.165) d]. Overall, our present study provides evidence that intestinal microbial community succession would be a valuable marker to estimate the PMSI of corpses submerged in an aquatic habitat.

Microbial communities in the liver and brain are informative for postmortem submersion interval estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater

Introduction

Bodies recovered from water, especially in the late phase of decomposition, pose difficulties to the investigating authorities. Various methods have been proposed for postmortem submersion interval (PMSI) estimation and drowning identification, but some limitations remain. Many recent studies have proved the value of microbiota succession in viscera for postmortem interval estimation. Nevertheless, the visceral microbiota succession and its application for PMSI estimation and drowning identification require further investigation.

Methods

In the current study, mouse drowning and CO₂ asphyxia models were developed, and cadavers were immersed in freshwater for 0 to 14 days. Microbial communities in the liver and brain were characterized via 16S rDNA high-throughput sequencing.

Results

Only livers and brains collected from 5 to 14 days postmortem were qualified for sequencing. There was significant variation between microbiota from liver and brain. Differences in microbiota between the cadavers of mice that had drowned and those only subjected to postmortem submersion decreased over the PMSI. Significant successions in microbial communities were observed among the different subgroups within the late phase of the PMSI in livers and brains. Eighteen taxa in the liver which were mainly related to Clostridium_sensu_stricto and Aeromonas, and 26 taxa in the brain which were mainly belonged to Clostridium_sensu_stricto, Acetobacteroides, and Limnochorda, were selected as potential biomarkers for PMSI estimation based on a random forest algorithm. The PMSI estimation models established yielded accurate prediction results with mean absolute errors ± the standard error of 1.282 ± 0.189 d for the liver and 0.989 ± 0.237 d for the brain.

Conclusions

The present study provides novel information on visceral postmortem microbiota succession in corpses submerged in freshwater which sheds new light on PMSI estimation based on the liver and brain in forensic practice.

Post-Mortem Interval and Microbiome Analysis through 16S rRNA Analysis: A Systematic Review

The determination of the Post-Mortem Interval (PMI) is an issue that has always represented a challenge in the field of forensic science. Different innovative approaches, compared to the more traditional ones, have been tried over the years, without succeeding in being validated as successful methods for PMI estimation. In the last two decades, innovations in sequencing technologies have made it possible to generate large volumes of data, allowing all members of a bacterial community to be sequenced. The aim of this manuscript is to provide a review regarding new advances in PMI estimation through cadaveric microbiota identification using 16S rRNA sequencing, in order to correlate specific microbiome profiles obtained from different body sites to PMI. The systematic review was performed according to PRISMA guidelines. For this purpose, 800 studies were identified through database searching (Pubmed). Articles that dealt with PMI estimation in correlation with microbiome composition and contained data about species, body site of sampling, monitoring time and sequencing method were selected and ultimately a total of 25 studies were considered. The selected studies evaluated the contribution of the various body sites to determine PMI, based on microbiome sequencing, in human and animal models. The results of this systematic review highlighted that studies conducted on both animals and humans yielded results that were promising. In order to fully exploit the potential of the microbiome in the estimation of PMI, it would be desirable to identify standardized body sampling sites and specific sampling methods in order to align data obtained by different research groups.

Supervised Machine Learning Enables Geospatial Microbial Provenance

The recent increase in publicly available metagenomic datasets with geospatial metadata has made it possible to determine location-specific, microbial fingerprints from around the world. Such fingerprints can be useful for comparing microbial niches for environmental research, as well as for applications within forensic science and public health. To determine the regional specificity for environmental metagenomes, we examined 4305 shotgun-sequenced samples from the MetaSUB Consortium dataset-the most extensive public collection of urban microbiomes, spanning 60 different cities, 30 countries, and 6 continents. We were able to identify city-specific microbial fingerprints using supervised machine learning (SML) on the taxonomic classifications, and we also compared the performance of ten SML classifiers. We then further evaluated the five algorithms with the highest accuracy, with the city and continental accuracy ranging from 85-89% to 90-94%, respectively. Thereafter, we used these results to develop Cassandra, a random-forest-based classifier that identifies bioindicator species to aid in fingerprinting and can infer higher-order microbial interactions at each site. We further tested the Cassandra algorithm on the Tara Oceans dataset, the largest collection of marine-based microbial genomes, where it classified the oceanic sample locations with 83% accuracy. These results and code show the utility of SML methods and Cassandra to identify bioindicator species across both oceanic and urban environments, which can help guide ongoing efforts in biotracing, environmental monitoring, and microbial forensics (MF).

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.

Microbiota succession throughout life from the cradle to the grave

Associations between age and the human microbiota are robust and reproducible. The microbial composition at several body sites can predict human chronological age relatively accurately. Although it is largely unknown why specific microorganisms are more abundant at certain ages, human microbiota research has elucidated a series of microbial community transformations that occur between birth and death. In this Review, we explore microbial succession in the healthy human microbiota from the cradle to the grave. We discuss the stages from primary succession at birth, to disruptions by disease or antibiotic use, to microbial expansion at death. We address how these successions differ by body site and by domain (bacteria, fungi or viruses). We also review experimental tools that microbiota researchers use to conduct this work. Finally, we discuss future directions for studying the microbiota's relationship with age, including designing consistent, well-powered, longitudinal studies, performing robust statistical analyses and improving characterization of non-bacterial microorganisms.

[Estimation of time since death with the postmortem microbiome: a modern view and approaches to solving the problem]

The aim of the review is to summarize and update the data of modern studies devoted to determining the post-mortem interval (PMI) with the use of microorganisms, as well as disclosing prospects for further study in the presented direction. Estimating the time elapsed since death based on the postmortem microbiome has great potential for accurate determination of PMI, but all methods currently used have their limitations. The dynamics of changes in microbial communities due to the influence of many external and internal factors significantly complicates the process of interpreting the results. The change of microbial communities in the human corpse has shown promising results for the assessment of PMI, but to date there is no evidence of the repeatability of such a continuity in various geographic and ecological conditions. The question of conducting new, large-scale studies, taking in all the factors that could affect the posthumous microbiome, is becoming urgent.

Sperm hunting on optical microscope slides for forensic analysis with deep convolutional networks - a feasibility study

Microscopic sperm detection is an important task in sexual assault cases. In some instances, the samples contain no or only low amounts of semen. Therefore, the biological material is transferred onto a glass slide and needs to be manually scanned using an optical microscope. This work can be very time consuming, especially when no spermatozoa is present. In such a case, the result needs to be validated. In this article we show how convolutional neural networks can perform this task and how they can reduce the scanning time by locating the sperm cells on images taken under the microscope. For this purpose, we trained a VGG19 network and a VGG19 variation with 1942 images, some containing sperm cells and some not.

Microbial traces and their role in forensic science

Forensic microbiology, also known as the microbiology of death, is an emerging branch of science that is still underused in criminal investigations. Some of the cases might be difficult to solve with commonly-used forensic methods, and then they become an operational field for microbiological and mycological analysis. The aim of our review is to present significant achievements of selected studies on the thanatomicrobiome (microorganisms found in the body, organs and fluids after death) and epinecrotic community (microorganisms found on decaying corpses) that can be used in forensic sciences. Research carried out as a part of the forensic microbiology deals with the thanatomicrobiome and the necrobiome - communities of microorganisms that live inside and outside of a putrefying corpse. Change of species composition observed in each community is a valuable feature that gives a lot of information related to the crime. It is mainly used in the estimation of post-mortem interval (PMI). In some criminal investigations, such noticeable changes in the microbiome and mycobiome can determine the cause or the actual place of death. The microbial traces found at the crime scene can also provide clear evidence of guilt. Nowadays, identification of microorganisms isolated from the body or environment is based on metagenome analysis and 16S rRNA gene amplicon-based sequencing for bacteria and ITS rRNA gene amplicon-based sequencing for fungi. Cultivation methods are still in use and seem to be more accurate; however, they require much more time to achieve a final result, which is an unwanted feature in any criminal investigation.

Ancient Metagenomic Studies: Considerations for the Wider Scientific Community

Like modern metagenomics, ancient metagenomics is a highly data-rich discipline, with the added challenge that the DNA of interest is degraded and, depending on the sample type, in low abundance. This requires the application of specialized measures during molecular experiments and computational analyses. Furthermore, researchers often work with finite sample sizes, which impedes optimal experimental design and control of confounding factors, and with ethically sensitive samples necessitating the consideration of additional guidelines. In September 2020, early career researchers in the field of ancient metagenomics met (Standards, Precautions & Advances in Ancient Metagenomics 2 [SPAAM2] community meeting) to discuss the state of the field and how to address current challenges. Here, in an effort to bridge the gap between ancient and modern metagenomics, we highlight and reflect upon some common misconceptions, provide a brief overview of the challenges in our field, and point toward useful resources for potential reviewers and newcomers to the field.

Toward a Framework for Assessing Privacy Risks in Multi-Omic Research and Databases

While the accumulation and increased circulation of genomic data have captured much attention over the past decade, privacy risks raised by the diversification and integration of omics have been largely overlooked. In this paper, we propose the outline of a framework for assessing privacy risks in multi-omic research and databases. Following a comparison of privacy risks associated with genomic and epigenomic data, we dissect ten privacy risk-impacting omic data properties that affect either the risk of re-identification of research participants, or the sensitivity of the information potentially conveyed by biological data. We then propose a three-step approach for the assessment of privacy risks in the multi-omic era. Thus, we lay grounds for a data property-based, 'pan-omic' approach that moves away from genetic exceptionalism. We conclude by inviting our peers to refine these theoretical foundations, put them to the test in their respective fields, and translate our approach into practical guidance.

Usefulness of Microbiome for Forensic Geolocation: A Review

Forensic microbiomics is a promising tool for crime investigation. Geolocation, which connects an individual to a certain place or location by microbiota, has been fairly well studied in the literature, and several applications have been found. The aim of this review is to highlight the main findings in this field, including the current sample storage, DNA extraction, sequencing and data analysis techniques that are being used, and its potential applications in human trafficking and ancient DNA studies. Second, the challenges and limitations of forensic microbiomics and geolocation are emphasised, providing recommendations for the establishment of this tool in the forensic science community.

Microbiome Forensic Biobanking: A Step toward Microbial Profiling for Forensic Human Identification

In recent years many studies have highlighted the great potential of microbial analysis in human identification for forensic purposes, with important differences in microbial community composition and function across different people and locations, showing a certain degree of uncertainty. Therefore, further studies are necessary to enable forensic scientists to evaluate the risk of microbial transfer and recovery from various items and to further critically evaluate the suitability of current human DNA recovery protocols for human microbial profiling for identification purposes. While the establishment and development of microbiome research biobanks for clinical applications is already very structured, the development of studies on the applicability of microbiome biobanks for forensic purposes is still in its infancy. The creation of large population microbiome biobanks, specifically dedicated to forensic human identification, could be worthwhile. This could also be useful to increase the practical applications of forensic microbiology for identification purposes, given that this type of evidence is currently absent from most real casework investigations and judicial proceedings in courts.

Predicting the postmortem interval using human intestinal microbiome data and random forest algorithm

Gradual changes in microbial communities in a human body after death can be used to determine postmortem interval (PMI). In this study, gut microflora samples were collected from the vermiform appendix and the transverse colon of human cadavers with PMIs between 5 and 192 h. The results revealed that the appendix might be an excellent intestinal sampling site and the appendix flora had an inferred succession rule during human body decomposition. Firmicutes, Bacteroidetes, and their respective subclasses showed a predictable successionrule in relative abundance over time. A Random Forest regression model was developed to correlate human gut microbiota with PMI. We believe that our findings have increased the knowledge of the composition and abundance of the gut microbiota in human corpses, and suggest that the use of the human appendix microbial succession may be a potential method for forensic estimation of the time of death.

A walk on the dirt: soil microbial forensics from ecological theory to the crime lab

Forensics aims at using physical evidence to solve investigations with science-based principles, thus operating within a theoretical framework. This however is often rather weak, the exception being DNA-based human forensics that is well anchored in theory. Soil is a most commonly encountered, easily and unknowingly transferred evidence but it is seldom employed as soil analyses require extensive expertise. In contrast, comparative analyses of soil bacterial communities using nucleic acid technologies can efficiently and precisely locate the origin of forensic soil traces. However, this application is still in its infancy, and is very rarely used. We posit that understanding the theoretical bases and limitations of their uses is essential for soil microbial forensics to be judiciously implemented. Accordingly, we review the ecological theory and experimental evidence explaining differences between soil microbial communities, i.e. the generation of beta diversity, and propose to integrate a bottom-up approach of interactions at the microscale, reflecting historical contingencies with top-down mechanisms driven by the geographic template, providing a potential explanation as to why bacterial communities map according to soil types. Finally, we delimit the use of soil microbial forensics based on the present technologies and ecological knowledge, and propose possible venues to remove existing bottlenecks.

At the Interface of Life and Death: Post-mortem and Other Applications of Vaginal, Skin, and Salivary Microbiome Analysis in Forensics

Microbial forensics represents a promising tool to strengthen traditional forensic investigative methods and fill related knowledge gaps. Large-scale microbiome studies indicate that microbial fingerprinting can assist forensics in areas such as trace evidence, source tracking, geolocation, and circumstances of death. Nevertheless, the majority of forensic microbiome studies focus on soil and internal organ samples, whereas the microbiome of skin, mouth, and especially vaginal samples that are routinely collected in sexual assault and femicide cases remain underexplored. This review discusses the current and emerging insights into vaginal, skin, and salivary microbiome-modulating factors during life (e.g., lifestyle and health status) and after death (e.g., environmental influences and post-mortem interval) based on next-generation sequencing. We specifically highlight the key aspects of female reproductive tract, skin, and mouth microbiome samples relevant in forensics. To fill the current knowledge gaps, future research should focus on the degree to which the post-mortem succession rate and profiles of vaginal, skin, and saliva microbiota are sensitive to abiotic and biotic factors, presence or absence of oxygen and other gases, and the nutrient richness of the environment. Application of this microbiome-related knowledge could provide valuable complementary data to strengthen forensic cases, for example, to shed light on the circumstances surrounding death with (post-mortem) microbial fingerprinting. Overall, this review synthesizes the present knowledge and aims to provide a framework to adequately comprehend the hurdles and potential application of vaginal, skin, and salivary post-mortem microbiomes in forensic investigations.

"Touch microbiome" as a potential tool for forensic investigation: A pilot study

Human skin hosts a variety of microbes that can be transferred to surfaces ("touch microbiome"). These microorganisms can be considered as forensic markers similarly to "touch DNA". With this pilot study, we wanted to evaluate the transferability and persistence of the "touch microbiome" on a surface after the deposition of a fingerprint and its exposure for 30 days at room temperature. Eleven volunteers were enrolled in the study. Skin microbiome samples were collected by swabbing the palm of their hands; additionally, donors were asked to touch a glass microscope slide to deposit their fingerprints, that were then swabbed. Both human and microbial DNA was isolated and quantified. Amelogenin locus and 16 human STRs were amplified, whereas the V4 region of 16 S rRNA gene was sequenced using Illumina MiSeq platform. STR profiles were successfully typed for 5 out of 22 "touch DNA" samples, while a microbiome profile was obtained for 20 out of 22 "touch microbiome" samples. Six skin core microbiome taxa were identified, as well as unique donor characterizing taxa. These unique taxa may have relevance for personal identification studies and may be useful to provide forensic intelligence information also when "touch DNA" fails. Additional future studies including greater datasets, additional time points and a greater number of surfaces may clarify the applicability of "touch microbiome" studies to real forensic contexts.

Diurnal variation in the human skin microbiome affects accuracy of forensic microbiome matching

BACKGROUND

The human skin microbiome has been recently investigated as a potential forensic tool, as people leave traces of their potentially unique microbiomes on objects and surfaces with which they interact. In this metagenomic study of four people in Hong Kong, their homes, and public surfaces in their neighbourhoods, we investigated the stability and identifiability of these microbiota traces on a timescale of hours to days.

RESULTS

Using a Canberra distance-based method of comparing skin and surface microbiomes, we found that a person could be accurately matched to their household in 84% of tests and to their neighbourhood in 50% of tests, and that matching accuracy did not decay for household surfaces over the 10-day study period, although it did for public surfaces. The time of day at which a skin or surface sample was taken affected matching accuracy, and 160 species across all sites were found to have a significant variation in abundance between morning and evening samples. We hypothesised that daily routines drive a rhythm of daytime dispersal from the pooled public surface microbiome followed by normalisation of a person's microbiome by contact with their household microbial reservoir, and Dynamic Bayesian Networks (DBNs) supported dispersal from public surfaces to skin as the major dispersal route among all sites studied.

CONCLUSIONS

These results suggest that in addition to considering the decay of microbiota traces with time, diurnal patterns in microbiome exposure that contribute to the human skin microbiome assemblage must also be considered in developing this as a potential forensic method. Video Abstract.

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.

Microbiomes in forensic botany: a review

Fragments of botanical material can often be found at crime scenes (on live and dead bodies, or on incriminating objects) and can provide circumstantial evidence on various aspects of forensic investigations such as determining crime scene locations, times of death or possession of illegal species. Morphological and genetic analysis are the most commonly applied methods to analyze plant fragment evidence but are limited by their low capacity to differentiate between potential source locations, especially at local scales. Here, we review the current applications and limitations of current plant fragment analysis for forensic investigations and introduce the potential of microbiome analysis to complement the existing forensic plant fragment analysis toolkit. The potential for plant fragment provenance identification at geographic scales meaningful to forensic investigations warrants further investigation of the phyllosphere microbiome in this context. To that end we identify three key areas of future research: 1) Retrieval of microbial DNA of sufficient quality and quantity from botanical material; 2) Variability of the phyllosphere microbiome at different taxonomic and spatial scales, with explicit reference to assignment capacity; 3) Impacts on assignment capacity of time, seasonality and movement of fragments between locations. The development of robust microbiome analysis tools for forensic purposes in botanical material could increase the evidentiary value of the botanical evidence commonly encountered in casework, aiding in the identification of crime scene locations.

Machine learning applications in microbial ecology, human microbiome studies, and environmental monitoring

Advances in nucleic acid sequencing technology have enabled expansion of our ability to profile microbial diversity. These large datasets of taxonomic and functional diversity are key to better understanding microbial ecology. Machine learning has proven to be a useful approach for analyzing microbial community data and making predictions about outcomes including human and environmental health. Machine learning applied to microbial community profiles has been used to predict disease states in human health, environmental quality and presence of contamination in the environment, and as trace evidence in forensics. Machine learning has appeal as a powerful tool that can provide deep insights into microbial communities and identify patterns in microbial community data. However, often machine learning models can be used as black boxes to predict a specific outcome, with little understanding of how the models arrived at predictions. Complex machine learning algorithms often may value higher accuracy and performance at the sacrifice of interpretability. In order to leverage machine learning into more translational research related to the microbiome and strengthen our ability to extract meaningful biological information, it is important for models to be interpretable. Here we review current trends in machine learning applications in microbial ecology as well as some of the important challenges and opportunities for more broad application of machine learning to understanding microbial communities.

Forensic Applications of Microbiomics: A Review

The rise of microbiomics and metagenomics has been driven by advances in genomic sequencing technology, improved microbial sampling methods, and fast-evolving approaches in bioinformatics. Humans are a host to diverse microbial communities in and on their bodies, which continuously interact with and alter the surrounding environments. Since information relating to these interactions can be extracted by analyzing human and environmental microbial profiles, they have the potential to be relevant to forensics. In this review, we analyzed over 100 papers describing forensic microbiome applications with emphasis on geolocation, personal identification, trace evidence, manner and cause of death, and inference of the postmortem interval (PMI). We found that although the field is in its infancy, utilizing microbiome and metagenome signatures has the potential to enhance the forensic toolkit. However, many of the studies suffer from limited sample sizes and model accuracies, and unrealistic environmental settings, leaving the full potential of microbiomics to forensics unexplored. It is unlikely that the information that can currently be elucidated from microbiomics can be used by law enforcement. Nonetheless, the research to overcome these challenges is ongoing, and it is foreseeable that microbiome-based evidence could contribute to forensic investigations in the future.

Random forests for predicting species identity of forensically important blow flies (Diptera: Calliphoridae) and flesh flies (Diptera: Sarcophagidae) using geometric morphometric data: Proof of concept

Wing shape variation has been shown to be useful for delineating forensically important fly species in two Diptera families: Calliphoridae and Sarcophagidae. Compared to DNA-based identification, the cost of geometric morphometric data acquisition and analysis is relatively much lower because the tools required are basic, and stable softwares are available. However, to date, an explicit demonstration of using wing geometric morphometric data for species identity prediction in these two families remains lacking. Here, geometric morphometric data from 19 homologous landmarks on the left wing of males from seven species of Calliphoridae (n = 55), and eight species of Sarcophagidae (n = 40) were obtained and processed using Generalized Procrustes Analysis. Allometric effect was removed by regressing centroid size (in log₁₀ ) against the Procrustes coordinates. Subsequently, principal component analysis of the allometry-adjusted Procrustes variables was done, with the first 15 principal components used to train a random forests model for species prediction. Using a real test sample consisting of 33 male fly specimens collected around a human corpse at a crime scene, the estimated percentage of concordance between species identities predicted using the random forests model and those inferred using DNA-based identification was about 80.6% (approximate 95% confidence interval = [68.9%, 92.2%]). In contrast, baseline concordance using naive majority class prediction was 36.4%. The results provide proof of concept that geometric morphometric data has good potential to complement morphological and DNA-based identification of blow flies and flesh flies in forensic work.

Trimethylornithine Membrane Lipids: Discovered in Planctomycetes and Identified in Diverse Environments

Intact polar membrane lipids (IPLs) are the building blocks of all cell membranes. There is a wide range of phosphorus-free IPL structures, including amino acid containing IPLs, that can be taxonomically specific. Trimethylornithine membrane lipids (TMOs) were discovered in northern wetland Planctomycete species that were isolated and described in the last decade. The trimethylated terminal nitrogen moiety of the ornithine amino acid in the TMO structure gives the lipid a charged polar head group, similar to certain phospholipids. Since their discovery, TMOs have been identified in various other recently described northern latitude Planctomycete species, and in diverse environments including tundra soil, a boreal eutrophic lake, meso-oligotrophic lakes, and hot springs. The majority of environments or enrichment cultures in which TMOs have been observed include predominately heterotrophic microbial communities involved in the degradation of recalcitrant material and/or low oxygen methanogenic conditions at primarily northern latitudes. Other ecosystems occupied with microbial communities that possess similar metabolic pathways, such as tropical peatlands or coastal salt marshes, may include TMO producing Planctomycetes as well, further allowing these lipids to potentially be used to understand microbial community responses to environmental change in a wide range of systems. The occurrence of TMOs in hot springs indicates that these unique lipids could have broad environmental distribution with different specialized functions. Opportunities also exist to investigate the application of TMOs in microbiome studies, including forensic necrobiomes. Further environmental and microbiome lipidomics research involving TMOs will help reveal the evolution, functions, and applications of these unique membrane lipids.

The genital microbiome and its potential for detecting sexual assault

Since its inception, the Human Microbiome Project (HMP) has provided key discoveries that can be applied to forensics, in addition to those of obvious medical value. Whether for postmortem interval estimation, geolocation, or human identification, there are many applications of the microbiome as an investigative lead for forensic casework. The human skin microbiome has shown great potential for use in studies of transfer and human identification, however there has been little focus on the genital microbiome, in particular penile skin which differs from other body sites. Our preliminary data on both the penile and vaginal microbiome demonstrates potential value in cases of sexual assault. In this study we describe genital microbial signatures based on the analysis of five male and five female genital samples and compare these results to those from longitudinal studies. Selected taxa, e.g., Gardnerella, Lactobacilli, Finegoldia, Peptoniphilus, and Anaerococci, are shown to be candidate constituents of the genital microbiome that merit investigation for use in sexual assault casework.

Histological changes in human skin 32 days after death and the potential forensic significance

To observe the histological changes in human skin within 32 days after death to explore its potential significance in forensic practice. The intact full-thickness skin and subcutaneous tissue from the sternum of eight corpses were placed in an environment of 4–6 °C for 4 h, 6 h, 12 h, 18 h, 24 h, 36 h, 48 h, 60 h, 72 h, 84 h, 96 h, 6 d, 8 d, 10 d, 12 d, 16 d, 20 d, 24 d, 28 d, and 32 d. Then, the whole layer of the skin was stained with haematoxylin & eosin. The histological morphology of the epidermis, dermis and appendages (sweat glands, hair follicles, and sebaceous glands) was observed under an light microscope. The epithelial nucleus condensed at 24 h after death, and cell lysis was exhausted after 20 days. The post-mortem changes in the dermis occurred later than that of the epidermis (72 h), but after epidermal changes started, the change was more rapid. At 16 d, the layers had become homogenized. The epidermis and dermis had completely separated 24 d after death. The changes in the sweat glands appeared earlier (24 h) and disappeared later (32 days); the sebaceous glands and hair follicles began to undergo degenerative changes at 96 h after death, and at approximately 20 d, only their contour remained. There were individual and structural differences in the post-mortem histological changes in the skin. At 4–6 °C ambient temperature, some structures of the human skin still exist for a long time after death, and these structures can be used to identify the source of the tissue; post-mortem histological changes in the skin occur at specific times, which can be used to help infer the time of death. A comprehensive observation of changes in the skin composition/structure is required to comprehensively analyse possible death times.