Metabarcoding to investigate changes in soil microbial communities within forensic burial contexts

Searching for alternative high DNA-yielding bone types for DNA analysis of aged skeletal remains

The petrous bone contains significantly higher amounts of DNA than any other human bone. Because of highly destructive sampling and because it is not always part of the recovered remains, the need for alternative sources of DNA is important. To identify additional optimal bone types, petrous bones were compared to femurs, tali, and calcanei sampled from 66 adult skeletons from two distinct modern-era Christian cemeteries. An extraction method employing full demineralization was used to obtain DNA, real-time PCR quantification to ascertain DNA quantity and degradation, and a commercial forensic short tandem repeats (STR) PCR amplification kit to determine genetic profiles. Statistical analysis was performed to explore the differences in DNA yield, DNA degradation, and success of STR amplification. A systematic studies exploring intra-skeletal variability in DNA preservation including various excavation sites differing by time period and geographical position are rare, and the second part of the investigation was based on a comparison of both archaeological sites, which allowed us to compare the effect of different post-mortem intervals and environmental conditions on DNA preservation. The older burial site in Črnomelj was active between the 13th and 18th century, whereas the more recent Polje burial was in use from the 16th to 19th century, creating different temporal and geographical environments. Results for the Črnomelj burial site revealed that the petrous bone outperformed all other bone types studied, except the calcaneus. At the Polje archeological site calcanei, tali, and femurs yielded the same STR typing success as petrous bones. The results obtained highlight the importance of careful bone sample selection for DNA analysis of aged skeletal remains. In addition to petrous bones, calcanei were found to be an alternative source of DNA when older burial sites are investigated. When more recent burial sites are processed, calcanei, tali, and femurs should be sampled besides petrous bones, not only because they exhibited good performance, but also because of easier sampling and easier grinding in the case of trabecular bones. This study contributes valuable insights into the potential use of various skeletal types as a source of DNA for investigation of aged skeletal remains, and it offers practical implications for forensic and archaeological investigations.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Cutting edge tools in the field of soil microbiology

The study of the whole of the genetic material contained within the microbial populations found in a certain environment is made possible by metagenomics. This technique enables a thorough knowledge of the variety, function, and interactions of microbial communities that are notoriously difficult to research. Due to the limitations of conventional techniques such as culturing and PCR-based methodologies, soil microbiology is a particularly challenging field. Metagenomics has emerged as an effective technique for overcoming these obstacles and shedding light on the dynamic nature of the microbial communities in soil. This review focuses on the principle of metagenomics techniques, their potential applications and limitations in soil microbial diversity analysis. The effectiveness of target-based metagenomics in determining the function of individual genes and microorganisms in soil ecosystems is also highlighted. Targeted metagenomics, including high-throughput sequencing and stable-isotope probing, is essential for studying microbial taxa and genes in complex ecosystems. Shotgun metagenomics may reveal the diversity of soil bacteria, composition, and function impacted by land use and soil management. Sanger, Next Generation Sequencing, Illumina, and Ion Torrent sequencing revolutionise soil microbiome research. Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)'s third and fourth generation sequencing systems revolutionise long-read technology. GeoChip, clone libraries, metagenomics, and metabarcoding help comprehend soil microbial communities. The article indicates that metagenomics may improve environmental management and agriculture despite existing limitations.Metagenomics has revolutionised soil microbiology research by revealing the complete diversity, function, and interactions of microorganisms in soil. Metagenomics is anticipated to continue defining the future of soil microbiology research despite some limitations, such as the difficulty of locating the appropriate sequencing method for specific genes.

A preliminary study characterizing temporal changes in soil bacterial communities after dismembered bones were buried

Determining the burial time of skeletal remains is one of the most important issues of forensic medicine. We speculated that the microbiome of gravesoil may be a promising method to infer burial time by virtue of time-dependent. As we know, forensic scientists have established various models to predict the postmortem interval of a decedent based on the changes in body and soil microbiome communities. However, limited data are available on the burial time prediction for bones, especially dismembered bones. In this exploratory study, we initially conducted 16S rRNA amplicon high-throughput sequencing on the burial soil of 10 porcine femurs within a 120-day period and analyzed the changes in soil microbial communities. Compared with the control soil, a higher Shannon index in the microbial diversity of burial soil containing bones was observed. Correlation analysis identified 61 time-related bacterial families and the best subset selection method obtained best subset, containing Thermomonosporaceae, Clostridiaceae, 0319-A21, and Oxalobacteraceae, which were used to construct a simplified multiple linear regression model with a mean absolute error (MAE) of 56.69 accumulated degree day (ADD). An additional random forest model was established based on indicators for the minimum cross-validation error of Thermomonosporaceae, Clostridiaceae, 0319-A21, Oxalobacteraceae, and Syntrophobacteraceae, with an MAE of 55.65 ADD. The produced empirical data in this pilot study provided the evidence of feasibility that the microbial successional changes of burial soil will predict the burial time of dismembered bones and may also expand the current knowledge of the effects of bone burial on soil bacterial communities.

Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation

Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0-8Dvs. WPG 16-40D, p < 0.0001; WPS 0-16Dvs. WPS 24-40D, p = 0.003; SPG 0D vs. SPG 8-40D, p = 0.0005; and SPS 0D vs. SPS 8-40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI.

Inference of drowning sites using bacterial composition and random forest algorithm

Diagnosing the drowning site is a major challenge in forensic practice, particularly when corpses are recovered from flowing rivers. Recently, forensic experts have focused on aquatic microorganisms, including bacteria, which can enter the bloodstream during drowning and may proliferate in corpses. The emergence of 16S ribosomal RNA gene (16S rDNA) amplicon sequencing has provided a new method for analyzing bacterial composition and has facilitated the development of forensic microbiology. We propose that 16S rDNA amplicon sequencing could be a useful tool for inferring drowning sites. Our study found significant differences in bacterial composition in different regions of the Guangzhou section of the Pearl River, which led to differences in bacteria of drowned rabbit lungs at different drowning sites. Using the genus level of bacteria in the lung tissue of drowned rabbits, we constructed a random forest model that accurately predicted the drowning site in a test set with 100% accuracy. Furthermore, we discovered that bacterial species endemic to the water were not always present in the corresponding drowned lung tissue. Our findings demonstrate the potential of a random forest model based on bacterial genus and composition in drowned lung tissues for inferring drowning sites.

Predicting the Postmortem Interval Based on Gravesoil Microbiome Data and a Random Forest Model

The estimation of a postmortem interval (PMI) is particularly important for forensic investigations. The aim of this study was to assess the succession of bacterial communities associated with the decomposition of mouse cadavers and determine the most important biomarker taxa for estimating PMIs. High-throughput sequencing was used to investigate the bacterial communities of gravesoil samples with different PMIs, and a random forest model was used to identify biomarker taxa. Redundancy analysis was used to determine the significance of environmental factors that were related to bacterial communities. Our data showed that the relative abundance of Proteobacteria, Bacteroidetes and Firmicutes showed an increasing trend during decomposition, but that of Acidobacteria, Actinobacteria and Chloroflexi decreased. At the genus level, Pseudomonas was the most abundant bacterial group, showing a trend similar to that of Proteobacteria. Soil temperature, total nitrogen, NH₄⁺-N and NO₃^--N levels were significantly related to the relative abundance of bacterial communities. Random forest models could predict PMIs with a mean absolute error of 1.27 days within 36 days of decomposition and identified 18 important biomarker taxa, such as Sphingobacterium, Solirubrobacter and Pseudomonas. Our results highlighted that microbiome data combined with machine learning algorithms could provide accurate models for predicting PMIs in forensic science and provide a better understanding of decomposition processes.

Advances in artificial intelligence-based microbiome for PMI estimation

Postmortem interval (PMI) estimation has always been a major challenge in forensic science. Conventional methods for predicting PMI are based on postmortem phenomena, metabolite or biochemical changes, and insect succession. Because postmortem microbial succession follows a certain temporal regularity, the microbiome has been shown to be a potentially effective tool for PMI estimation in the last decade. Recently, artificial intelligence (AI) technologies shed new lights on forensic medicine through analyzing big data, establishing prediction models, assisting in decision-making, etc. With the application of next-generation sequencing (NGS) and AI techniques, it is possible for forensic practitioners to improve the dataset of microbial communities and obtain detailed information on the inventory of specific ecosystems, quantifications of community diversity, descriptions of their ecological function, and even their application in legal medicine. This review describes the postmortem succession of the microbiome in cadavers and their surroundings, and summarizes the application, advantages, problems, and future strategies of AI-based microbiome analysis for PMI estimation.

Post-Mortem Interval of Human Skeletal Remains Estimated with Handheld NIR Spectrometry

Estimating the post-mortem interval (PMI) of human skeletal remains is a critical issue of forensic analysis, with important limitations such as sample preparation and practicability. In this work, NIR spectroscopy (NIRONE® Sensor X; Spectral Engines, 61449, Germany) was applied to estimate the PMI of 104 human bone samples between 1 day and 2000 years. Reflectance data were repeatedly collected from eight independent spectrometers between 1950 and 1550 nm with a spectral resolution of 14 nm and a step size of 2 nm, each from the external and internal bone. An Artificial Neural Network was used to analyze the 66,560 distinct diagnostic spectra, and clearly distinguished between forensic and archaeological bone material: the classification accuracies for PMIs of 0−2 weeks, 2 weeks−6 months, 6 months−1 year, 1 year−10 years, and >100 years were 0.90, 0.94, 0.94, 0.93, and 1.00, respectively. PMI of archaeological bones could be determined with an accuracy of 100%, demonstrating the adequate predictive performance of the model. Applying a handheld NIR spectrometer to estimate the PMI of human skeletal remains is rapid and extends the repertoire of forensic analyses as a distinct, novel approach.

Microbial DNA in human nucleic acid extracts: Recoverability of the microbiome in DNA extracts stored frozen long-term and its potential and ethical implications for forensic investigation

Human DNA samples can remain unaltered for years and preserve important genetic information for forensic investigations. In fact, besides human genetic information, these extracts potentially contain additional valuable information: microbiome signatures. Forensic microbiology is rapidly becoming a significant tool for estimating post-mortem interval (PMI), and establishing cause of death and personal identity. To date, the possibility to recover unaltered microbiome signatures from human DNA extracts has not been proven. This study examines the microbiome signatures within human DNA extracts obtained from six cadavers with different PMIs, which were stored frozen for 5-16 years. Results demonstrated that the microbiome can be co-extracted with human DNA using forensic kits designed to extract the human host's DNA from different tissues and fluids during decomposition. We compared the microbial communities identified in these samples with microbial DNA recovered from two human cadavers donated to the Forensic Anthropology Center at Texas State University (FACTS) during multiple decomposition stages, to examine whether the microbial signatures recovered from "old" (up to 16 years) extracts are consistent with those identified in recently extracted microbial DNA samples. The V4 region of 16 S rRNA gene was amplified and sequenced using Illumina MiSeq for all DNA extracts. The results obtained from the human DNA extracts were compared with each other and with the microbial DNA from the FACTS samples. Overall, we found that the presence of specific microbial taxa depends on the decomposition stage, the type of tissue, and the depositional environment. We found no indications of contamination in the microbial signatures, or any alterations attributable to the long-term frozen storage of the extracts, demonstrating that older human DNA extracts are a reliable source of such microbial signatures. No shared Core Microbiome (CM) was identified amongst the total 18 samples, but we identified certain species in association with the different decomposition stages, offering potential for the use of microbial signatures co-extracted with human DNA samples for PMI estimation in future. Unveiling the new significance of older human DNA extracts brings with it important ethical-legal considerations. Currently, there are no shared legal frameworks governing the long-term storage and use of human DNA extracts obtained from crime scene evidence for additional research purposes. It is therefore important to create common protocols on the storage of biological material collected at crime scenes. We review existing legislation and guidelines, and identify some important limitations for the further development and application of forensic microbiomics.

Dynamics of insects, microorganisms and muscle mRNA on pig carcasses and their significances in estimating PMI

The accurate estimate of the postmortem interval (PMI) is of vital significance in the investigation of homicide cases. In this study, three pig carcasses were placed in the field to study the pattern of insect succession, the change of microorganisms and the degradation of muscle tissue RNA during the decomposition process. The results showed that insects could quickly colonize the carcasses and still exist on them until the end of the experiment (41 days). Their development and succession patterns are useful indicators for PMI estimation. The diversity of rectal microorganisms decreased with the decomposition time. In different decomposition periods, significant differences in the rectal and soil microbial composition and relative abundance were found, which could be used to estimate the PMI with an accuracy of 3-4 days. The RNA of muscle tissue was found to have a time-dependent relationship with the PMI. Ppia and Gapdh showed a linear upward trend within 10 h after the death, followed by a gradual downward trend from 10 to 240 h. The expression of β-actin gene showed a gradual downward trend during 0-240 h. This is the first study in China to analyze the changes of insects, muscle RNA and microorganisms on pig carcasses in the same natural environment, which provide basic data for the PMI estimation.

Estimation of the post-mortem interval of human skeletal remains using Raman spectroscopy and chemometrics

An important demand exists in the field of forensic analysis to objectively determine the post-mortem interval (PMI) when human skeletal remains are discovered. It is widely known that bones undergo different chemical and physical processes after death, mainly due to their interaction with the environment in which they are found, although it is not known exactly what these processes consist of. Multiple techniques have been used so far to follow up these and other post-mortem changes and thus establish the time elapsed since the individual's death, but they present important drawbacks in terms of reliability and accuracy. The aim of this research was to propose an analytical methodology capable of determining the PMI by using non-destructive Raman spectroscopy measurements of human skeletal remains. The recorded Raman spectra provided valuable and potentially useful information from which a multivariate study was performed by means of orthogonal partial least squares regression (OPLSR) in order to correlate the PMI with the detected spectral modifications. A collection of 53 real human skeletal remains with known PMI (15 years ≤ PMI ≤ 87 years) was analysed and used for building and validating the OPLS model. The PMI of 10 out of 14 validation samples could be determined with an accuracy error of less than 30%, demonstrating the adequate predictive performance of the OPLS model even in spite of the large inter-individual variability it handled. This opens up the possibility of applying the OPLS model in combination with non-destructive techniques to the determination of the PMI of human skeletal remains that have been buried in conditions similar or equal to those of cemetery niches and in a geographic location with a Mediterranean climate, which is an important achievement for forensic medicine and anthropology.

The Effect of Different Coverings on Total Body Score Development of Buried Carcasses

Background

Examination of post-mortem changes is one of the ways to assess decomposition process on buried bodies. Nonetheless, studies on such assessment are still lacking, especially on the effects of body coverings by different materials in burial conditions. The aim of this research is to study the effect of different types of covering towards decomposition on buried rabbit carcasses by using Total Body Score (TBS) system.

Methods

Twenty-seven rabbit carcasses were divided into: (i) No Clothing; (ii) Thick Clothing and (iii) Plastic Wrapping groups, and buried into individual shallow graves. One subject was exhumed from first to ninth post-burial week and assessed by using TBS system.

Results and Discussion

There are significant differences among TBS between different coverings while controlling the time factor, F (2, 23) = 4.80, P < 0.05, partial η² = 0.294. TBS score for Plastic Wrapping group is significantly lower than No Clothing group over times at α = 0.05, P < 0.05. The slightly delaying effect of thick clothing is caused by design of jacket, which allows arthropods access and microbial activity. Relatively strong delaying effect by plastic covering could be caused by impermeable property that caused accumulation of decompositional products and slow down the degradation.

Conclusion

In conclusion, TBS system is a potential tool in describing rate of decomposition for buried cases in Malaysia.

"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.

Bone Diagenesis in Short Timescales: Insights from an Exploratory Proteomic Analysis

The evaluation of bone diagenetic phenomena in archaeological timescales has a long history; however, little is known about the origins of the microbes driving bone diagenesis, nor about the extent of bone diagenesis in short timeframes-such as in forensic contexts. Previously, the analysis of non-collagenous proteins (NCPs) through bottom-up proteomics revealed the presence of potential biomarkers useful in estimating the post-mortem interval (PMI). However, there is still a great need for enhancing the understanding of the diagenetic processes taking place in forensic timeframes, and to clarify whether proteomic analyses can help to develop better models for estimating PMI reliably. To address these knowledge gaps, we designed an experiment based on whole rat carcasses, defleshed long rat bones, and excised but still-fleshed rat limbs, which were either buried in soil or exposed on a clean plastic surface, left to decompose for 28 weeks, and retrieved at different time intervals. This study aimed to assess differences in bone protein relative abundances for the various deposition modalities and intervals. We further evaluated the effects that extrinsic factors, autolysis, and gut and soil bacteria had on bone diagenesis via bottom-up proteomics. Results showed six proteins whose abundance was significantly different between samples subjected to either microbial decomposition (gut or soil bacteria) or to environmental factors. In particular, muscle- and calcium-binding proteins were found to be more prone to degradation by bacterial attack, whereas plasma and bone marrow proteins were more susceptible to exposure to extrinsic agents. Our results suggest that both gut and soil bacteria play key roles in bone diagenesis and protein decay in relatively short timescales, and that bone proteomics is a proficient resource with which to identify microbially-driven versus extrinsically-driven diagenesis.

A Combined Application of Molecular Microbial Ecology and Elemental Analyses Can Advance the Understanding of Decomposition Dynamics

Introducing animal carbon-source to soil initiates biochemical and microbial processes that lead to its decomposition and recycling, which subsequently cause successional shifts in soil microbial community. To investigate the use of soil microbial community to inform criminal investigation, this study was designed to mimic clandestine graves. It compared the decomposition of stillborn piglets (Sus scrofa domesticus), as human analogues, to oak (Quercus robur) leaf litter and soil-only controls outdoors for 720 days. Environmental and edaphic parameters were monitored and showed soil microbial community alignment with temperature seasonality, which highlighted the importance of this abiotic factor. Denaturing gradient gel electrophoresis (DGGE) data were used to calculate Hill numbers and diversity indices of the bacterial 16S rRNA community did not distinguish mammalian- from plant-based decomposition consistently during the first or second year of the study. In contrast, the fungal 18S rRNA community allowed clear differentiation between different treatments (beta diversity) throughout the 720-day experiment and suggested the moment of the decomposing mammalian skin rupture. 16S rRNA-based NGS facilitated the identification of e.g., Pirellulaceae, Acidobacteria ii1-15_order and Candidatus xiphinematobacter as Year 2 bacterial markers of gravesoil at family, order and species taxonomic levels, respectively, and confirmed the similarity of the calculated Hill diversity metrics with those derived from DGGE profiling. Parallel soil elemental composition was measured by portable X-ray Fluorescence where calcium profiles for the piglet-associated soils were distinct from those without carrion. Also, soil calcium content and PMI correlated positively during the first year then negatively during the second. This study is one of the first to apply a multidisciplinary approach based on molecular and physicochemical analytical techniques to assess decomposition. It highlights the recognised potential of using soil microbial community in forensic investigations and provides a proof-of-concept for the application of a combined molecular and elemental approach to further understand the dynamics of decomposition. In addition, it sets the scene for further research in different conditions based on Hill numbers metrics instead of the classic ecological indices for soil necrobiome richness, diversity and evenness.

Predicting the postmortem interval of burial cadavers based on microbial community succession

Previous studies have demonstrated that microbial community succession during the decomposition of cadavers could be used to estimate the postmortem interval (PMI). However, the vast majority of the existing studies focused on exposed cadavers. In fact, burial cadavers are common scenarios for forensic investigations. In this study, the microbial communities from gravesoil, rectum and skin of burial SD rat cadavers during decomposition were characterized using 16S rRNA gene high-throughput sequencing. We predicted PMI based on the microbial community succession. Obvious differences in microbial community structures were observed between different stages of decomposition. Later decay stages had a lower alpha diversity compared to earlier decay stages. Significant linear relationships between similarities of the microbial communities and postmortem intervals were observed, manifesting regular succession over the course of decomposition. Furthermore, we combined random forest models with postmortem microbial features to predict PMI. The model explained 86.83%, 84.55% and 81.67% of the variation in the microbial community, with a mean absolute error of 1.82, 2.06 and 2.13 days within 60 days of decomposition for gravesoil, rectum and skin of burial cadavers, respectively. Overall, our results suggested that postmortem microbial community data could serve as a potential forensic tool to estimate accurate PMI of burial cadavers.

Microbial analyses of blood spot surfaces collected from a laboratory and the bathroom of a female single-person household under different environmental conditions

Many people spend most of their time indoors, thereby exposing themselves to indoor environmental microbial communities that might interact with the human microbiota. These potential interactions have only been considered for personal identification; however, accumulating evidence indicates that these microbial interactions are potentially implicated with the identification of human interactions and location-specific factors including time and seasonal variations in the microbial community. To augment the potential of metagenomics-based forensic tools, we compared the composition of microbial communities in blood spot surfaces from healthy adults placed in different environments, such as in the bathroom of a female single-person household and on a laboratory, which were sampled across seasons and time points. The laboratory samples showed more changes in the bacterial community over time owing to the higher number of individuals using the laboratory, whereas the microbial communities in the bathroom samples remained relatively stable over time. Moreover, the two locations could be distinguished according to their specific bacterial community compositions. Variations were also observed related to changes in temperature and humidity, allowing for prediction of season-based microbial community. These findings offer a new perspective regarding the use of microbial community analysis in forensic science.

The applicability of forensic time since death estimation methods for buried bodies in advanced decomposition stages

Estimation of the postmortem interval in advanced postmortem stages is a challenging task. Although there are several approaches available for addressing postmortem changes of a (human) body or its environment (ecologically and/or biochemically), most are restricted to specific timeframes and/or individual and environmental conditions. It is well known, for instance, that buried bodies decompose in a remarkably different manner than on the ground surface. However, data on how established methods for PMI estimation perform under these conditions are scarce. It is important to understand whether and how postmortem changes are affected under burial conditions, if corrective factors could be conceived, or if methods have to be excluded for respective cases. We present the first multi-methodological assessment of human postmortem decomposition carried out on buried body donors in Europe, at the Amsterdam Research Initiative for Sub-surface Taphonomy and Anthropology (ARISTA) in the Netherlands. We used a multidisciplinary approach to investigate postmortem changes of morphology, skeletal muscle protein decomposition, presence of insects and other necrophilous animals as well as microbial communities (i.e., microbiomes) from August to November 2018 associated with two complete body exhumations and eight partial exhumations. Our results clearly display the current possibilities and limitations of methods for PMI estimation in buried remains and provide a baseline for future research and application.

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.

Soil Fungal Communities Investigated by Metabarcoding Within Simulated Forensic Burial Contexts

Decomposition of animal bodies in the burial environment plays a key role in the biochemistry of the soil, altering the balance of the local microbial populations present before the introduction of the carcass. Despite the growing number of studies on decomposition and soil bacterial populations, less is known on its effects on fungal communities. Shifts in the fungal populations at different post-mortem intervals (PMIs) could provide insights for PMI estimation and clarify the role that specific fungal taxa have at specific decomposition stages. In this study, we buried pig carcasses over a period of 1- to 6-months, and we sampled the soil in contact with each carcass at different PMIs. We performed metabarcoding analysis of the mycobiome targeting both the internal transcribed spacer (ITS) 1 and 2, to elucidate which one was more suitable for this purpose. Our results showed a decrease in the fungal taxonomic richness associated with increasing PMIs, and the alteration of the soil fungal signature even after 6 months post-burial, showing the inability of soil communities to restore their original composition within this timeframe. The results highlighted taxonomic trends associated with specific PMIs, such as the increase of the Mortierellomycota after 4- and 6-months and of Ascomycota particularly after 2 months, and the decrease of Basidiomycota from the first to the last time point. We have found a limited number of taxa specifically associated with the carrion and not present in the control soil, showing that the major contributors to the recorded changes are originated from the soil and were not introduced by the carrion. As this is the first study conducted on burial graves, it sets the baseline for additional studies to investigate the role of fungal communities on prolonged decomposition periods and to identify fungal biomarkers to improve the accuracy of PMI prediction for forensic applications.