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The combined use of multiple omics allows to study complex interrelated biological processes in their entirety. We applied a combination of metabolomics, lipidomics and proteomics to human bones to investigate their combined potential to estimate time elapsed since death (i.e., the postmortem interval [PMI]). This ‘ForensOMICS’ approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors before their placement at the Forensic Anthropology Research Facility owned by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219-790-834-872days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic, and proteomic profiles from the pre- and post-placement bone samples. The three omics blocks were investigated independently by univariate and multivariate analyses, followed by Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers describing postmortem changes and discriminating the individuals based on their PMI. The resulting model showed that pre-placement metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement ones. Metabolites in the pre-placement samples suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules with an excellent potential for PMI estimation, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different postmortem stability, in the future we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by using proteins.

DNA sequencing has revolutionised our understanding of archaic humans during the Middle and Upper Palaeolithic. Unfortunately, while many Palaeolithic sites contain large numbers of bones, the majority of these lack the diagnostic features necessary for traditional morphological identification. As a result the recovery of Pleistocene-age human remains is extremely rare. To circumvent this problem we have applied a method of collagen fingerprinting to more than 2000 fragmented bones from the site of Denisova Cave, Russia, in order to facilitate the discovery of human remains. As a result of our analysis a single hominin bone (Denisova 11) was identified, supported through in-depth peptide sequencing analysis and found to carry mitochondrial DNA of the Neandertal type. Subsequent radiocarbon dating revealed the bone to be >50,000 years old. Here we demonstrate the huge potential collagen fingerprinting has for identifying hominin remains in highly fragmentary archaeological assemblages, improving the resources available for wider studies into human evolution.

Previous dating of the Vi-207 and Vi-208 Neanderthal remains from Vindija Cave (Croatia) led to the suggestion that Neanderthals survived there as recently as 28,000–29,000 B.P. Subsequent dating yielded older dates, interpreted as ages of at least ∼32,500 B.P. We have redated these same specimens using an approach based on the extraction of the amino acid hydroxyproline, using preparative high-performance liquid chromatography (Prep-HPLC). This method is more efficient in eliminating modern contamination in the bone collagen. The revised dates are older than 40,000 B.P., suggesting the Vindija Neanderthals did not live more recently than others across Europe, and probably predate the arrival of anatomically modern humans in Eastern Europe. We applied zooarchaeology by mass spectrometry (ZooMS) to find additional hominin remains. We identified one bone that is Neanderthal, based on its mitochondrial DNA, and dated it directly to 46,200 ± 1,500 B.P. We also attempted to date six early Upper Paleolithic bone points from stratigraphic units G₁, Fd/d+G₁ and Fd/d, Fd. One bone artifact gave a date of 29,500 ± 400 B.P., while the remainder yielded no collagen. We additionally dated animal bone samples from units G₁ and G₁–G₃. These dates suggest a co-occurrence of early Upper Paleolithic osseous artifacts, particularly split-based points, alongside the remains of Neanderthals is a result of postdepositional mixing, rather than an association between the two groups, although more work is required to show this definitively.

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.

The study of post-mortem changes is a crucial component of forensic investigation. Human forensic taphonomic facilities (HFTFs) are the only institutions allowing the design and execution of controlled human decomposition experiments. When bodies are skeletonized, bones are normally stored in skeletal collections and used for anthropological studies. However, HFTFs apply chemical and/or thermal treatments to the remains prior bone long-term storage. These treatments are believed to alter heavily the original biochemical and molecular signature of bone material. The present study aims to evaluate the effect of these procedures on the bone metabolome and lipidome by using an animal bone model. Three intact bovine tibiae were processed using three protocols routinely applied at HFTFs, and their three counterparts were used as non-treated controls. Bone powder samples were subjected to biphasic extraction and both metabolites and lipids were analysed via liquid chromatography tandem mass-spectrometry. Results showed severe reductions in the abundances of both metabolites and lipids, and the presence of contamination introduced by cleaning agents. Despite the preliminary nature of the study, we demonstrated that the biochemical profile of bone is heavily affected by the maceration procedures. Ideally, these treatments should be avoided, or replaced by minimally invasive procedures agreed across HFTFs.

•P-M bacterial colonisation study with non-culture genomic and proteomic techniques.•First to identify Vibrionaceae as abundant on decomposing pork using T-RFLP.•Strain level identifications could be obtained through proteomic analysis. Bacteria are considered one of the major driving forces of the mammalian decomposition process and have only recently been recognised as forensic tools. At this point, little is known about their potential use as ‘post-mortem clocks’. This study aimed to establish the proof of concept for using bacterial identification as post-mortem interval (PMI) indicators, using a multi-omics approach. Pieces of pork were placed in the University’s outdoor facility and surface swabs were taken at regular intervals up to 60 days. Terminal restriction fragment length polymorphism (T-RFLP) of the 16S rDNA was used to identify bacterial taxa. It succeeded in detecting two out of three key contributors involved in decomposition and represents the first study to reveal Vibrionaceae as abundant on decomposing pork. However, a high fraction of present bacterial taxa could not be identified by T-RFLP. Proteomic analyses were also performed at selected time points, and they partially succeeded in the identification of precise strains, subspecies and species of bacteria that colonized the body after different PMIs. T-RFLP is incapable of reliably and fully identifying bacterial taxa, whereas proteomics could help in the identification of specific strains of bacteria. Nevertheless, microbial identification by next generation sequencing might be used as PMI clock in future investigations and in conjunction with information provided by forensic entomologists. To the best of our knowledge, this work represents the first attempt to find a cheaper and easily accessible, culture-independent alternative to high-throughput techniques to establish a ‘microbial clock’, in combination with proteomic strategies to address this issue.

Considering the growing importance of microbiome analyses in forensics for identifying individuals, this study explores the transfer of the skin microbiome onto clothing, its persistence on fabrics over time, and its transferability from the environment and between different garments. Furthermore, this project compares three specific QIAGEN microbiome extraction kits to test their extraction efficiency on fabric samples. Additionally, this study aims to check if these extracts contain human DNA, providing a chance to obtain more information from the same evidence for personal identification. The results obtained show: (1) variations in the skin microbiome between the volunteers, potentially due to their different sex; (2) differences in microbial composition between worn and unworn clothing; (3) the influence of the environment on the microbial signature of unworn clothing; (4) the potential use of certain phyla as biomarkers to differentiate between worn and unworn garments, even over extended periods; (5) a tendency towards extraction biases in the QIAampMP® DNA microbiome kit among the three tested ones; and (6) none of the extraction kits allow for the typing of human genetic profiles suitable for comparison. In conclusion, our study offers supplementary insights into the potential utility of time-transferred microbiome analysis on garments for forensic applications.

One of the most debated topics in forensic anthropology and archaeology is the estimation of the time elapsed since death and the biological age of the body from skeletonised bodies, or fragments of them. Usually, standard analytical and morphological approaches tend to suffer from weaknesses, highly relying on the expertise of the forensic scientists and on their subjective interpretation of the macroscopic and microscopic bone features to draw conclusions. In order to improve the accuracy and the objectivity of these estimations, biomolecular approaches seem to be the most promising way to address the problem. Between all the biomolecules available to conduct this type of studies, proteins are the ones able to survive longest in biological tissues through the decomposition process. Furthermore, they also convey several modifications which can be related with ageing phenomena both in vivo and post-mortem, with protein deamidation being the most commonly occurring in forensic and in archaeological contexts. All these features make proteins an interesting target for new applications in forensic sciences, with the potential to become new biomarkers for biological and geological age estimations. The research presented here applied proteomic methods to experimental forensic and archaeological bones and teeth to investigate how the decomposition process and the environmental conditions impact the proteins degradation and modification, and evaluated also the effects that the decomposition of a body may have on the surrounding burial environment using a metagenomic approach to evaluate changes within the soil microbial community. Results showed that proteomic analyses on bones can provide interesting information about the ageing phenomena in forensic and archaeological scenarios; in particular, the new potential biomarkers proposed here may become in future a molecular support to the estimation of post-mortem interval and age-at-death, improving the ability of scientists to find the truth behind complicated forensic contexts.

The combined use of multiple omics methods to answer complex system biology questions is growing in biological and medical sciences, as the importance of studying interrelated biological processes in their entirety is increasingly recognized. We applied a combination of metabolomics, lipidomics and proteomics to human bone to investigate the potential of this multi-omics approach to estimate the time elapsed since death (i.e., the post-mortem interval, PMI). This \"ForensOMICS\" approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors in a fresh stage of decomposition before placement of the bodies to decompose outdoors at the human taphonomy facility managed by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219, 790, 834 and 872 days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic and proteomic profiles from the pre- and post-placement bone samples. Multivariate analysis was used to investigate the three omics blocks by means of Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers that could effectively describe post-mortem changes and classify the individuals based on their PMI. The resulting model showed that pre-placement bone metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement profiles. Metabolites associated with the pre-placement samples, suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules from the three groups that show excellent potential for estimation of the PMI, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different post-mortem stability, in future studies we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by including more stable proteins. Competing Interest Statement The authors have declared no competing interest.

What happens to a dead body in an extremely cold environment? Decomposition in cold environments Our study took place in Grand Forks, North Dakota, one of the coldest cities in the United States, where winters are characterized by temperatures that can drop to -40 degrees Fahrenheit (-40 degrees Celsius) and high winds that can reach up to 31 miles per hour (50 kilometers per hour). [...]the body cools much faster in cold conditions, which can skew estimates based on body temperature.