Microbiome Tools for Forensic Science

Massively parallel sequencing is unlocking the potential of environmental trace evidence

Massively parallel sequencing (MPS) has revolutionised the field of genomics enabling substantial advances in human DNA profiling. Further, the advent of MPS now allows biological signatures to be obtained from complex DNA mixtures and trace amounts of low biomass samples. Environmental samples serve as ideal forms of contact trace evidence as detection at a scene can establish a link between a suspect, location and victim. Many studies have applied MPS technology to characterise the biodiversity within high biomass environmental samples (such as soil and water) to address questions related to ecology, conservation, climate change and human health. However, translation of these tools to forensic science remains in its infancy, due in part to the merging of traditional forensic ecology practices with unfamiliar DNA technologies and complex datasets. In addition, people and objects also carry low biomass environmental signals which have recently been shown to reflect a specific individual or location. The sensitivity, and reducing cost, of MPS is now unlocking the power of both high and low biomass environmental DNA (eDNA) samples as useful sources of genetic information in forensic science. This paper discusses the potential of eDNA to forensic science by reviewing the most explored applications that are leading the integration of this technology into the field. We introduce novel areas of forensic ecology that could also benefit from these tools with a focus on linking a suspect to a scene or establishing provenance of an unknown sample and discuss the current limitations and validation recommendations to achieve translation of eDNA into casework.

Skin Microbiome Analysis for Forensic Human Identification: What Do We Know So Far?

Microbiome research is a highly transdisciplinary field with a wide range of applications and methods for studying it, involving different computational approaches and models. The fact that different people host radically different microbiota highlights forensic perspectives in understanding what leads to this variation and what regulates it, in order to effectively use microbes as forensic evidence. This narrative review provides an overview of some of the main scientific works so far produced, focusing on the potentiality of using skin microbiome profiling for human identification in forensics. This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The examined literature clearly ascertains that skin microbial communities, although personalized, vary systematically across body sites and time, with intrapersonal differences over time smaller than interpersonal ones, showing such a high degree of spatial and temporal variability that the degree and nature of this variability can constitute in itself an important parameter useful in distinguishing individuals from one another. Even making the effort to organically synthesize all results achieved until now, it is quite evident that these results are still the pieces of a puzzle, which is not yet complete.

Potential bacterial biomarkers for insect colonization in forensic cases: preliminary quantitative data on Wohlfahrtiimonas chitiniclastica and Ignatzschineria indica dynamics

For the last decades, forensic microbiology became an emerging complementary tool in criminalistics. Although the insect-microbe interactions regarding pathogen transmission were extensively studied, only scarce information is available on bacterial transfer from necrophagous insects to host tissues. Our data provides the first report on the occurrence of Wohlfahrtiimonas chitiniclastica and Ignatzschineria indica in Lucilia illustris Meigen, 1826 (Diptera: Calliphoridae), and the quantitative dynamics of the two bacterial species along the insect life-stages and transfer to beef and pork host tissues using qPCR gyrase b specific primers. The content of both bacterial species increased along the insect life stages. W. chitiniclastica was detected in all developmental stages independent of the feeding substrate. I. indica was measurable with 10² gene copies ng⁻¹ DNA threshold starting from the third instar larvae when feeding on beef, and from the egg stage with a 10²× higher representation when using the pork substrate. The transfer of bacterial species to both tissues occurred after 3 colonization days except for I. indica that was visible in beef liver only during day 5. Considering the utilization of pork tissues as human analogues, these quantitative microbial dynamics data provides first insect-specific bacterial candidates as potential colonization biomarkers in forensic investigations.

Transfer of skin microbiota between two dissimilar autologous microenvironments: A pilot study

Dysbiosis of skin microbiota is associated with several inflammatory skin conditions, including atopic dermatitis, acne, and hidradenitis suppurativa. There is a surge of interest by clinicians and the lay public to explore targeted bacteriotherapy to treat these dermatologic conditions. To date, skin microbiota transplantation studies have focused on moving single, enriched strains of bacteria to target sites rather than a whole community. In this prospective pilot study, we examined the feasibility of transferring unenriched skin microbiota communities between two anatomical sites of the same host. We enrolled four healthy volunteers (median age: 28 [range: 24, 36] years; 2 [50%] female) who underwent collection and transfer of skin microbiota from the forearm to the back unidirectionally. Using culture methods and 16S rRNA V1-V3 deep sequencing, we compared baseline and mixed ("transplant") communities, at T = 0 and T = 24 hours. Our ability to detect movement from one site to the other relied on the inherent diversity of the microenvironment of the antecubital fossa relative to the less diverse back. Comparing bacterial species present in the arm and mixed ("transplant") communities that were absent from the baseline back, we saw evidence of transfer of a partial DNA signature; our methods limit conclusions regarding the viability of transferred organisms. We conclude that unenriched transfer of whole cutaneous microbiota is challenging, but our simple technique, intended to move viable skin organisms from one site to another, is worthy of further investigation.

Evaluating Bioinformatic Pipeline Performance for Forensic Microbiome Analysis*,†,‡

Microbial communities have potential evidential utility for forensic applications. However, bioinformatic analysis of high-throughput sequencing data varies widely among laboratories. These differences can potentially affect microbial community composition and downstream analyses. To illustrate the importance of standardizing methodology, we compared analyses of postmortem microbiome samples using several bioinformatic pipelines, varying minimum library size or minimum number of sequences per sample, and sample size. Using the same input sequence data, we found that three open-source bioinformatic pipelines, MG-RAST, mothur, and QIIME2, had significant differences in relative abundance, alpha-diversity, and beta-diversity, despite the same input data. Increasing minimum library size and sample size increased the number of low-abundant and infrequent taxa detected. Our results show that bioinformatic pipeline and parameter choice affect results in important ways. Given the growing potential application of forensic microbiology to the criminal justice system, continued research on standardizing computational methodology will be important for downstream applications.

Consistent and correctable bias in metagenomic sequencing experiments

Marker-gene and metagenomic sequencing have profoundly expanded our ability to measure biological communities. But the measurements they provide differ from the truth, often dramatically, because these experiments are biased toward detecting some taxa over others. This experimental bias makes the taxon or gene abundances measured by different protocols quantitatively incomparable and can lead to spurious biological conclusions. We propose a mathematical model for how bias distorts community measurements based on the properties of real experiments. We validate this model with 16S rRNA gene and shotgun metagenomics data from defined bacterial communities. Our model better fits the experimental data despite being simpler than previous models. We illustrate how our model can be used to evaluate protocols, to understand the effect of bias on downstream statistical analyses, and to measure and correct bias given suitable calibration controls. These results illuminate new avenues toward truly quantitative and reproducible metagenomics measurements.

Consistent and correctable bias in metagenomic sequencing experiments

Marker-gene and metagenomic sequencing have profoundly expanded our ability to measure biological communities. But the measurements they provide differ from the truth, often dramatically, because these experiments are biased toward detecting some taxa over others. This experimental bias makes the taxon or gene abundances measured by different protocols quantitatively incomparable and can lead to spurious biological conclusions. We propose a mathematical model for how bias distorts community measurements based on the properties of real experiments. We validate this model with 16S rRNA gene and shotgun metagenomics data from defined bacterial communities. Our model better fits the experimental data despite being simpler than previous models. We illustrate how our model can be used to evaluate protocols, to understand the effect of bias on downstream statistical analyses, and to measure and correct bias given suitable calibration controls. These results illuminate new avenues toward truly quantitative and reproducible metagenomics measurements.

Volatile Organic Compound Profiling from Postmortem Microbes using Gas Chromatography-Mass Spectrometry

Volatile organic compounds (VOCs) are by-products of cadaveric decomposition and are responsible for the odor associated with decomposing remains. The direct link between VOC production and individual postmortem microbes has not been well characterized experimentally. The purpose of this study was to profile VOCs released from three postmortem bacterial isolates (Bacillus subtilis, Ignatzschineria indica, I. ureiclastica) using solid-phase microextraction arrow (SPME Arrow) and gas chromatography-mass spectrometry (GC-MS). Species were inoculated in headspace vials on Standard Nutrient Agar and monitored over 5 days at 24°C. Each species exhibited a different VOC profile that included common decomposition VOCs. VOCs exhibited upward or downward temporal trends over time. Ignatzschineria indica produced a large amount of dimethyldisulfide. Other compounds of interest included alcohols, aldehydes, aromatics, and ketones. This provides foundational data to link decomposition odor with specific postmortem microbes to improve understanding of underlying mechanisms for decomposition VOC production.

A 1H NMR metabolomic approach for the estimation of the time since death using aqueous humour: an animal model

INTRODUCTION

The estimation of the time since death, or post-mortem interval (PMI), still remains a main conundrum in forensic science. Several approaches have been so far proposed from either a qualitative or a quantitative point of view, but they still lack reliability and robustness. Recently, metabolomics has shown to be a potential tool to investigate the time-related post-mortem metabolite modifications in animal models.

OBJECTIVES

Here we propose, for the first time, the use of a ¹H NMR metabolomic approach for the estimation of PMI from aqueous humour (AH) in an ovine model.

METHODS

AH samples were collected at different times after death (from 118 to 1429 min). ¹H NMR experiments were performed and spectral data analysed by multivariate statistical tools.

RESULTS

A multivariate calibration model was built to estimate PMI on the basis of the metabolite content of the samples. The model was validated with an independent test set, obtaining a prediction error of 59 min for PMI < 500 min, 104 min for PMI from 500 to 1000 min, and 118 min for PMI > 1000 min. Moreover, the metabolomic approach suggested a picture of the mechanisms underlying the post-mortem biological modifications, highlighting the role played by taurine, choline, and succinate.

CONCLUSION

The time-related modifications of the ¹H NMR AH metabolomic profile seem to be encouraging in addressing the issue of a reproducible and robust model to be employed for the estimation of the time since death.

Experimental evaluation on the applicability of necrobiome analysis in forensic veterinary science

Despite the wide usage of animals as models in forensic studies, the investigations of fundamental legal questions involving domesticated and nondomesticated animals were always given marginal attention compared to “human forensic,” and only recently the interest in the discipline is increasing. Our research focuses on the effect of the fur coat on the activity and development of microbial decomposers. In order to test this variable never assessed before, rabbit carcasses were used and results show that: (i) distinct and significant temporal changes in terms of metabolic activity and taxa distribution can be tracked over the decomposition process; (ii) the richness and the diversity of the bacterial communities does not significantly vary over time, but it does not mean that the species Operational Taxonomic Units (OTUs) do not change; (iii) the presence/absence of the fur on the carcasses does not significantly affect either the bacterial communities’ functional activity or the diversity intra‐ and intercommunity, neither at phylum nor at family resolution; (iv) the functional activity and the ecological diversity of the bacterial communities are significantly affected by the body region, while the relative abundance is not. Obtained data confirm previous observations and provide new insight in the Forensic Veterinary field in terms of equally using them in order to derive a statistical model for the PMI estimation. As a future perspective, a contribution to the Forensic Entomology approach will be given in legal investigations when domestic or wild animals are involved, regardless of the presence of a hair layer.

Trace Evidence Potential in Postmortem Skin Microbiomes: From Death Scene to Morgue

Microbes can be used effectively as trace evidence, at least in research settings. However, it is unknown whether skin microbiomes change prior to autopsy and, if so, whether these changes interfere with linking objects to decedents. The current study included microbiomes from 16 scenes of death in the City and County of Honolulu and tested whether objects at the scenes can be linked to individual decedents. Postmortem skin microbiomes were stable during repeated sampling up to 60 h postmortem and were similar to microbiomes of an antemortem population. Objects could be traced to decedents approximately 75% of the time, with smoking pipes and medical devices being especially accurate (100% match), house and car keys being poor (0%), and other objects like phones intermediate (~80%). These results show that microbes from objects at death scenes can be matched to individual decedents, opening up a new method of establishing associations and identifications.

Characterizing forensically important insect and microbial community colonization patterns in buried remains

During violent criminal actions in which the perpetrator disposes of the victim's remains by burial, the analysis of insects and bacterial colonization patterns could be necessary for postmortem interval (PMI) estimation. Our research aimed to assess the decomposition process of buried rat carcasses from shallow graves (40 cm), the diversity and dynamics of insects and bacteria throughout the decomposition stages, and the environmental parameters' influence on these variations. The results provide further insight on decomposition in soil and contribute to a broader understanding of the factors involved in decomposition by qualitatively and quantitatively analysing the decomposer community (bacteria and insects). Additionally, two bacterial taxa, Enterococcus faecalis and Clostridium paraputrificum that were investigated for the first time as PMI indicators using quantitative polymerase chain reaction (qPCR) showed differential abundance over time, promising data for PMI estimation. The current study on the decomposition of buried rat carcasses in a natural environment will strengthen the current knowledge on decomposed remains from shallow graves and represents an effort to quantify insect and bacterial taxa as PMI estimators.

Microbial forensics: new breakthroughs and future prospects

Recent advances in genetic data generation, through massive parallel sequencing (MPS), storage and analysis have fostered significant progresses in microbial forensics (or forensic microbiology). Initial applications in circumstances of biocrime, bioterrorism and epidemiology are now accompanied by the prospect of using microorganisms (i) as ancillary evidence in criminal cases; (ii) to clarify causes of death (e.g., drownings, toxicology, hospital-acquired infections, sudden infant death and shaken baby syndromes); (iii) to assist human identification (skin, hair and body fluid microbiomes); (iv) for geolocation (soil microbiome); and (v) to estimate postmortem interval (thanatomicrobiome and epinecrotic microbial community). When compared with classical microbiological methods, MPS offers a diverse range of advantages and alternative possibilities. However, prior to its implementation in the forensic context, critical efforts concerning the elaboration of standards and guidelines consolidated by the creation of robust and comprehensive reference databases must be undertaken.

Temporal dynamics of microbiota before and after host death

The habitats that animals, humans and plants provide for microbial communities are inevitably transient, changing drastically when these hosts die. Because microbes associated with living hosts are ensured prime access to the deceased host’s organic matter, it is feasible that opportunistic, adaptable lifestyles are widespread among host-associated microbes. Here we investigate the temporal dynamics of microbiota by starving to death a host—the planktonic Crustacean Daphnia magna—and tracking the changes in its microbial community as it approaches death, dies and decomposes. Along with obligate host-associated microbes that vanished after the host’s death and decomposers that appeared after the host’s death, we also detected microbes with opportunistic lifestyles, seemingly capable of exploiting the host even before its death. We suggest that the period around host death plays an important role for host–microbiota ecology and for the evolution of hosts and their microbes.

Future Technologies

Microbiome analysis of environmental samples may represent the next frontier in environmental microbial forensics. Next-generation sequencing technologies significantly increased the available genetic data that could be used as evidentiary material. It is not clear, however, whether the microbiome can scale across institutions using forensic-based evidence due to the data resource requirements and the associated costs of maintaining these databases. A successful microbiome study is impacted by the quality of the information gathered and the steps in sample processing and data analysis. To ascertain the validity of methods and the results obtained, there needs to be a stringent procedure to validate the methods and ensure that the results are comparable and reproducible, not only within the laboratory but also between laboratories conducting similar research. Of primary importance for meaningful microbiome studies is an experimental design that leads to carefully executed, controlled, and reproducible studies. The microbiome literature contains a fair share of anecdotal descriptions of microbial community composition and "diagnostic" relative abundance of the taxa therein. These studies are now being supplemented by experimental designs that feature repeated measurements, error estimates, correlations of microbiota with covariates, and increasingly sophisticated statistical tests that enhance the robustness of data analysis and study conclusions. It is imperative to be careful, especially when carrying out attribution studies, to be fully aware of the possible biases included in a specific sample being analyzed.

Creating a 3D microbial and chemical snapshot of a human habitat

One of the goals of forensic science is to identify individuals and their lifestyle by analyzing the trace signatures left behind in built environments. Here, microbiome and metabolomic methods were used to see how its occupants used an office and to also gain insights into the lifestyle characteristics such as diet, medications, and personal care products of the occupants. 3D molecular cartography, a molecular visualization technology, was used in combination with mass spectrometry and microbial inventories to highlight human-environmental interactions. Molecular signatures were correlated with the individuals as well as their interactions with this indoor environment. There are person-specific chemical and microbial signatures associated with this environment that directly relate who had touched objects such as computers, computer mice, cell phones, desk phone, table or desks. By combining molecular and microbial investigation forensic strategies, this study offers novel insights to investigators who value the reconstructing of human lifestyle and characterization of human environmental interaction.

Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models

Death investigations often include an effort to establish the postmortem interval (PMI) in cases in which the time of death is uncertain. The postmortem interval can lead to the identification of the deceased and the validation of witness statements and suspect alibis. Recent research has demonstrated that microbes provide an accurate clock that starts at death and relies on ecological change in the microbial communities that normally inhabit a body and its surrounding environment. Here, we explore how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head), gene markers (16S ribosomal RNA (rRNA), 18S rRNA, internal transcribed spacer regions (ITS)), and taxonomic levels (sequence variants, species, genus, etc.). We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using gravesoil and skin data using the 16S rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.

Transmission of Airborne Bacteria across Built Environments and Its Measurement Standards: A Review

Human health is influenced by various factors including microorganisms present in built environments where people spend most of their lives (approximately 90%). It is therefore necessary to monitor and control indoor airborne microbes for occupational safety and public health. Most studies concerning airborne microorganisms have focused on fungi, with scant data available concerning bacteria. The present review considers papers published from 2010 to 2017 approximately and factors affecting properties of indoor airborne bacteria (communities and concentration) with respect to temporal perspective and to multiscale interaction viewpoint. From a temporal perspective, bacterial concentrations in built environments change depending on numbers of human occupancy, while properties of bacterial communities tend to remain stable. Similarly, the bacteria found in social and community spaces such as offices, classrooms and hospitals are mainly associated with human occupancy. Other major sources of indoor airborne bacteria are (i) outdoor environments, and (ii) the building materials themselves. Indoor bacterial communities and concentrations are varied with varying interferences by outdoor environment. Airborne bacteria from the outdoor environment enter an indoor space through open doors and windows, while indoor bacteria are simultaneously released to the outer environment. Outdoor bacterial communities and their concentrations are also affected by geographical factors such as types of land use and their spatial distribution. The bacteria found in built environments therefore originate from any of the natural and man-made surroundings around humans. Therefore, to better understand the factors influencing bacterial concentrations and communities in built environments, we should study all the environments that humans contact as a single ecosystem. In this review, we propose the establishment of a standard procedure for assessing properties of indoor airborne bacteria using four factors: temperature, relative humidity (RH), air exchange rate, and occupant density, as a minimum requirement. We also summarize the relevant legislation by country. Choice of factors to measure remain controversial are discussed.

Bioelectrical Impedance as a Technique for Estimating Postmortem Interval,

Estimation of postmortem interval (PMI) is a critical component of death investigation. A cadaver can be hypothesized to be a resistor-capacitor (RC) circuit the impedance (Z) of which changes in a quantifiable manner as the cadaver decomposes. This hypothesis was tested using bioelectrical impedance analysis (BIA) equipment to apply a current with a fixed amplitude at a single frequency to four cadavers over time and measuring two components of Z, resistance (R) and reactance (X_c ). Quadratic regression analysis between Z and accumulated degree days (ADD) showed a statistically significant parabolic relationship. The parabolic relationship poses an initial challenge to the use of the method, and additional research is needed to address this issue. However, the results of the reported research support the hypothesis that Z measured using BIA has a relationship to PMI.

Elucidation of complexity and prediction of interactions in microbial communities

Microorganisms engage in complex interactions with other members of the microbial community, higher organisms as well as their environment. However, determining the exact nature of these interactions can be challenging due to the large number of members in these communities and the manifold of interactions they can engage in. Various omic data, such as 16S rRNA gene sequencing, shotgun metagenomics, metatranscriptomics, metaproteomics and metabolomics, have been deployed to unravel the community structure, interactions and resulting community dynamics in situ. Interpretation of these multi-omic data often requires advanced computational methods. Modelling approaches are powerful tools to integrate, contextualize and interpret experimental data, thus shedding light on the underlying processes shaping the microbiome. Here, we review current methods and approaches, both experimental and computational, to elucidate interactions in microbial communities and to predict their responses to perturbations.