Exploring the role of the human microbiome in forensic identification: opportunities and challenges.

Forensic microbiology is rapidly emerging as a novel tool for human identification. The human microbiome, comprising diverse microbial communities including fungi, bacteria, protozoa, and viruses, is unique to each individual, offering a new dimension to forensic investigations. While traditional identification methods primarily rely on DNA profiling and fingerprint analysis, they face limitations when complete DNA or fingerprints profiles are unattainable or degraded. In this context, the microbial signatures of the human skin microbiome present a promising alternative due to their resilience to environmental stresses and individual-specific composition. This review explores the potential of microbiome analysis in forensic human identification, evaluating its applications, advantages, limitations, and future prospects. The uniqueness of an individual's microbial community, particularly the skin microbiota, can provide distinctive biological markers for identification purposes, while technological advancements like 16 S rRNA sequencing and metagenomic shotgun sequencing are enhancing the specificity of microbial identification, enabling detailed analysis of these complex ecological communities. Despite these promising findings, current research has not yet achieved a level of identification probability that could establish microbial analysis as a stand-alone evidence tool. Therefore, it is presently considered ancillary to traditional methods, contributing to a more comprehensive biological profile of individuals.

Artificial intelligence-driven microbiome data analysis for estimation of postmortem interval and crime location.

Microbial communities, demonstrating dynamic changes in cadavers and the surroundings, provide invaluable insights for forensic investigations. Conventional methodologies for microbiome sequencing data analysis face obstacles due to subjectivity and inefficiency. Artificial Intelligence (AI) presents an efficient and accurate tool, with the ability to autonomously process and analyze high-throughput data, and assimilate multi-omics data, encompassing metagenomics, transcriptomics, and proteomics. This facilitates accurate and efficient estimation of the postmortem interval (PMI), detection of crime location, and elucidation of microbial functionalities. This review presents an overview of microorganisms from cadavers and crime scenes, emphasizes the importance of microbiome, and summarizes the application of AI in high-throughput microbiome data processing in forensic microbiology.

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.

Thanatomicrobiome in forensic medicine.

The circumstances of death and the estimation of the post-mortem interval (PMI) are often a great challenge for scientific and judicial investigators, especially when some time has elapsed since death. Several techniques are used; nevertheless, each presents its own limitations. In the quest for new techniques that are more reliable or at least complementary to those existing and sometimes less expensive, researchers have in recent years turned toward exploring the dynamics of the different microbial communities of a corpse according to their different stages of decomposition. This article summarizes the various works done in the field and shows the different sources of microorganisms in the different parts of the human corpse and their potential interest in the field of forensic medicine.

Feature selection with a genetic algorithm can help improve the distinguishing power of microbiota information in monozygotic twins' identification.

Introduction: Personal identification of monozygotic twins (MZT) has been challenging in forensic genetics. Previous research has demonstrated that microbial markers have potential value due to their specificity and long-term stability. However, those studies would use the complete information of detected microbial communities, and low-value species would limit the performance of previous models. Methods: To address this issue, we collected 80 saliva samples from 10 pairs of MZTs at four different time points and used 16s rRNA V3-V4 region sequencing to obtain microbiota information. The data formed 280 inner-individual (Self) or MZT sample pairs, divided into four groups based on the individual relationship and time interval, and then randomly divided into training and testing sets with an 8:2 ratio. We built 12 identification models based on the time interval ( ≤ 1 year or ≥ 2 months), data basis (Amplicon sequence variants, ASVs or Operational taxonomic unit, OTUs), and distance parameter selection (Jaccard distance, Bray-Curist distance, or Hellinger distance) and then improved their identification power through genetic algorithm processes. The best combination of databases with distance parameters was selected as the final model for the two types of time intervals. Bayes theory was introduced to provide a numerical indicator of the evidence's effectiveness in practical cases. Results: From the 80 saliva samples, 369 OTUs and 1130 ASVs were detected. After the feature selection process, ASV-Jaccard distance models were selected as the final models for the two types of time intervals. For short interval samples, the final model can completely distinguish MZT pairs from Self ones in both training and test sets. Discussion: Our findings support the microbiota solution to the challenging MZT identification problem and highlight the importance of feature selection in improving model performance.

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.

Palynology and mycology as biological evidence in a homicide case.

Criminal cases are studied from several disciplines to link a suspect with a criminal act. In this case, a man was reported missing in a coastal area in Buenos Aires Province, Argentina. The victim's relatives pointed to a possible suspect, and the local police carried out the investigation. We contributed to this research by applying palynological and mycological techniques. Palynomorphs and fungal spores offer valuable trace evidence, as they can be easily transferred between objects and crime scenes due to their minute size and persist on them for a long time. The victim was found 25 days later, lying on sandy soil, which partially covered the body, 35 km from where the suspect was arrested. Comparative samples were collected from the crime scene and the suspect's home and belongings (clothes, footwear, and seized vehicle). The palynological associations obtained from the crime scene and the defendant's belongings were dominated by diatoms and acritarchs (Acantomorphitae), all elements of marine origin, and a high CFU number of Bipolaris cynodontis, which allowed the defendant's clothing to be related to the place of corpse discovery. Soil from the defendant's home had an entirely continental composition, and the fungal biota was characteristic of prairie areas which were different from those of the crime scene.

Trends in forensic microbiology: From classical methods to deep learning.

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

Preliminary exploratory research on the application value of oral and intestinal meta-genomics in predicting subjects' occupations-A case study of the distinction between students and migrant workers.

Background: In the field of forensic science, accurately determining occupation of an individual can greatly assist in resolving cases such as criminal investigations or disaster victim identifications. However, estimating occupation can be challenging due to the intricate relationship between occupation and various factors, including gender, age, living environment, health status, medication use, and lifestyle habits such as alcohol consumption and smoking. All of these factors can impact the composition of oral or gut microbial community of an individual. Methods and results: In this study, we collected saliva and feces samples from individuals representing different occupational sectors, specifically students and manual laborers. We then performed metagenomic sequencing on the DNA extracted from these samples to obtain data that could be analyzed for taxonomic and functional annotations in five different databases. The correlation between occupation with microbial information was assisted from the perspective of α and ß diversity, showing that individuals belonging to the two occupations hold significantly different oral and gut microbial communities, and that this correlation is basically not affected by gender, drinking, and smoking in our datasets. Finally, random forest (RF) models were built with recursive feature elimination (RFE) processes. Models with 100% accuracy in both training and testing sets were constructed based on three species in saliva samples or on a single pathway annotated by the KEGG database in fecal samples, namely, "ko04145" or Phagosome. Conclusion: Although this study may have limited representativeness due to its small sample size, it provides preliminary evidence of the potential of using microbiome information for occupational inference.

The role of microorganisms in the biotransformation of psychoactive substances and its forensic relevance: a critical interdisciplinary review.

Microorganisms are widespread on the planet being able to adapt, persist, and grow in diverse environments, either rich in nutrient sources or under harsh conditions. The comprehension of the interaction between microorganisms and drugs is relevant for forensic toxicology and forensic chemistry, elucidating potential pathways of microbial metabolism and their implications. Considering the described scenario, this paper aims to provide a comprehensive and critical review of the state of the art of interactions amongst microorganisms and common drugs of abuse. Additionally, other drugs of forensic interest are briefly discussed. This paper outlines the importance of this area of investigation, covering the intersections between forensic microbiology, forensic chemistry, and forensic toxicology applied to drugs of abuse, and it also highlights research potentialities. Key points: Microorganisms are widespread on the planet and grow in a myriad of environments.Microorganisms can often be found in matrices of forensic interest.Drugs can be metabolized or produced (e.g. ethanol) by microorganisms.

The devil is in the details: Variable impacts of season, BMI, sampling site temperature, and presence of insects on the post-mortem microbiome.

Background: Post-mortem microbial communities are increasingly investigated as proxy evidence for a variety of factors of interest in forensic science. The reported predictive power of the microbial community to determine aspects of the individual's post-mortem history (e.g., the post-mortem interval) varies substantially among published research. This observed variation is partially driven by the local environment or the individual themselves. In the current study, we investigated the impact of BMI, sex, insect activity, season, repeat sampling, decomposition time, and temperature on the microbial community sampled from donated human remains in San Marcos, TX using a high-throughput gene-fragment metabarcoding approach. Materials and methods: In the current study, we investigated the impact of BMI, sex, insect activity, season, repeat sampling, decomposition time, and temperature on the microbial community sampled from donated human remains in San Marcos, TX using a high-throughput gene-fragment metabarcoding approach. Results: We found that season, temperature at the sampling site, BMI, and sex had a significant effect on the post-mortem microbiome, the presence of insects has a homogenizing influence on the total bacterial community, and that community consistency from repeat sampling decreases as the decomposition process progresses. Moreover, we demonstrate the importance of temperature at the site of sampling on the abundance of important diagnostic taxa. Conclusion: The results of this study suggest that while the bacterial community or specific bacterial species may prove to be useful for forensic applications, a clearer understanding of the mechanisms underpinning microbial decomposition will greatly increase the utility of microbial evidence in forensic casework.

Advances in microbial metagenomics and artificial intelligence analysis in forensic identification.

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

Estudio mediante técnicas moleculares del tanatomicrobioma intestinal en la estimación del intervalo post mortem temprano empleando un modelo de ratón / Early post mortem interval estimation in a mouse model using molecular analyses of the gut thanatomicrobiome

Introducción: en la actualidad, la falta de métodos cuantitativos fiables ha llevado a distintas líneas de investigación a buscar un modelo que prediga el intervalo post mortem (IPM). El tanatomicrobioma, presente desde el momento de la muerte, parece sufrir cambios predecibles y que siguen una correlación con el IPM.Materiales y métodosse ha analizado experimentalmente el comportamiento del tanatomicrobioma en la región del intestino delgado posterior y del colon ascendente durante las primeras 24 h de descomposición en Mus musculus. Para ello, se ha llevado a cabo una aproximación molecular basada en el análisis del gen ribosomal 16S (ARNr 16S) mediante electroforesis en gel con gradiente desnaturalizante (DGGE) y, seguidamente un análisis de la alfa y beta diversidad.Resultadoslos resultados basados en el análisis de los índices de diversidad ecológica reflejaron cambios estadísticamente significativos antes de las 12 h, y un descenso de la diversidad a partir de esas 12 h postmortem, siendo este estadísticamente significativo en las 2 regiones intestinales analizadas. Por otro lado, el estudio comparativo de las comunidades microbianas mostró que cambian estructurada y diferenciablemente desde el momento de la muerte, alejándose en similitud de las mostradas en vida (IPM 0 h).Discusiónestos resultados coinciden con el descenso de la diversidad sugerido a largo plazo por distintos autores. Sin embargo, en las condiciones del estudio, se ha visto que este descenso no se inicia hasta las 12 h. Conclusión como conclusión, se han podido establecer, según los cambios en la diversidad bacteriana, fases de la dinámica bacteriana durante la descomposición que podrían ayudar a mejorar los modelos de correlación microbiana para la estimación del IPM. (AU)

Introduction: Currently, the lack of reliable quantitative methods has led different research lines to find a model that predicts the postmortem interval (PMI). The thanatomicrobiome, present from the moment of death, has been shown to change in predictable ways, allowing a correlation with PMI.Materials and methodsIn this study, the shifts of the thanatomicrobiome in the region of the posterior small intestine and the ascending colon in Mus musculus during the first 24 hrs of decomposition have been analyzed experimentally. For this purpose, a molecular approach based on the analysis of the 16S ribosomal gene (16S rRNA) and a denaturing gradient gel electrophoresis (DGGE) was adopted, followed by analyses of the ecological diversity indices Alpha and beta diversity.ResultsThe results based on the analysis of the ecological diversity indices reflected statistically significant changes before 12 hrs, and a decrease in diversity after 12 hrs postmortem, this being statistically significant in the two intestinal regions analyzed. Moreover, the comparative study of microbial communities indicated distinct and structured changes from the moment of death, with shifts in the degree of similarity from the composition detected in life (PMI 0 hrs).DiscussionThese results agree with other studies demonstrating a decrease in microbial diversity. However, under the conditions of the study, this decrease does not begin until 12 hrs after death. Conclusions: In conclusion, by examining the dynamics of bacterial diversity our study has identified phases during decomposition that could help to improve microbial correlation models for PMI estimation. (AU)

[Ecological aspects of postmortem microbiome and possibility of their use in forensic practice]. / Ekologicheskie aspekty posmertnogo mikrobioma i vozmozhnost' ikh ispol'zovaniya v praktike sudebno-meditsinskoi ekspertizy.

Through experimental reproduction of the decomposition process using the cadaver of rabbit Oryctolagus sp., the dynamics of cadaver microflora was studied; the dominant bacterial taxa were isolated in pure culture and identified; their ecological and trophic profiles and biodiversity were described based on the values of Simpson and Menchinic ecological indices. The dependence of cadaver rotting and skeletonization rate on the taxonomic profile of microorganisms, decomposition period, and abiotic environmental factors (temperature, acidity, soil moisture) was demonstrated. The data obtained contribute to justifying the use of microbiological methods in forensic practice. To establish objective causality patterns of microbial transformation of organic matter in nature, further targeted study of ecological patterns of cadaveric microflora is necessary.

Revisión sobre las nuevas perspectivas de datación cadavérica desde el necrobioma / Review of cadaveric dating methods and new perspectives from the necrobiome

Hoy en día existen numerosas estrategias desde un punto de vista científico que ayudan a esclarecer los casos forenses, entre ellas la datación cadavérica. La ausencia de métodos fiables cuantitativos para estimar el intervalo post mortem explica el incremento de nuevas líneas de investigación prometedoras con dicha finalidad. Tras la aparición de las nuevas técnicas de secuenciación masiva y bioinformáticas, surge también el estudio del necrobioma como un área novedosa y poco estudiada dentro de las ciencias forenses, que se ha llegado a denominar «microbiología forense». En esta revisión se realiza un breve recorrido por las técnicas y procedimientos existentes de datación cadavérica, centrándose en la utilidad del tanatomicrobioma, o conjunto de microorganismos presentes en el momento de la muerte, que podría ser un método prometedor para la estimación del intervalo post mortem en el futuro. (AU)

Nowadays there are numerous scientific strategies that helping to clarify forensic cases, including time since death. The absence of reliable quantitative methods to estimate the post-mortem interval explains the increase in promising new lines of research for this purpose. After the appearance of the new techniques of massive sequencing and bioinformatics, also arises the study of the necrobiome through a new and little studied area within the forensic sciences, Forensic Microbiology. In this review, a tour of the existing techniques and procedures of cadaveric dating is made, which includes new cutting-edge techniques in different areas of knowledge and also mentions the utilities of Forensic Microbiology, where the thanatomicrobiome, present from the moment of death, according to recent studies, points to be a promising method for estimating the post-mortem interval in the future. (AU)

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 analyses. The aim of our review is to present significant achievements of selected studies on the thanatomicrobiome (micro-organisms found in the body, organs and fluids after death) and epinecrotic community (micro-organisms 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 micro-organisms 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 micro-organisms 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.

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.

Forensic evaluation of two nucleic acid extraction systems and validation of a RT-qPCR protocol for identification of SARS-CoV-2 in post-mortem nasopharyngeal swabs.

The COVID-19 outbreak has represented a challenge for the international scientific community and particularly for forensic sciences. The lack of Coronavirus post-mortem testing led the National Institute of Toxicology and Forensic Sciences (INTCF) from Spain to verify the performance and utility of a quantitative reverse transcription PCR (RT-qPCR) clinical diagnosis protocol for SARS-CoV-2 detection (TaqPath™ COVID-19 CE-IVD RT-PCR Kit), to shed light on the cause of death (COD) in potentially COVID-19 cases in judicial autopsies. Two different RNA extraction methods were also tested (EZ1® DSP Virus Kit on the EZ1® Advanced XL robot versus MagMAX™ Viral/Pathogen Nucleic Acid Isolation Kit) regarding extraction efficiency, precision and contamination. RT-qPCR was evaluated for precision, specificity, limit of detection and concordance. Both the automated and the manual RNA extraction procedures showed good efficiency, but the automated virus extraction by bio-robot produced more reproducible results than the manual extraction. The SARS-CoV-2 RT-qPCR assay showed high sensitivity with a detection limit up to 10 copies/reaction and high specificity, as no cross-reactivity was detected between any of the 12 different RNA viruses tested, including three types of coronaviruses (SARS-CoV, NL63 and 229E). Reproducibility and repeatability of the studied method as well as concordance with other SARS-CoV-2 molecular detection protocols were also demonstrated.

Human Bone Proteomes before and after Decomposition: Investigating the Effects of Biological Variation and Taphonomic Alteration on Bone Protein Profiles and the Implications for Forensic Proteomics.

Bone proteomic studies using animal proxies and skeletonized human remains have delivered encouraging results in the search for potential biomarkers for precise and accurate post-mortem interval (PMI) and the age-at-death (AAD) estimation in medico-legal investigations. The development of forensic proteomics for PMI and AAD estimation is in critical need of research on human remains throughout decomposition, as currently the effects of both inter-individual biological differences and taphonomic alteration on the survival of human bone protein profiles are unclear. This study investigated the human bone proteome in four human body donors studied throughout decomposition outdoors. The effects of ageing phenomena (in vivo and post-mortem) and intrinsic and extrinsic variables on the variety and abundancy of the bone proteome were assessed. Results indicate that taphonomic and biological variables play a significant role in the survival of proteins in bone. Our findings suggest that inter-individual and inter-skeletal differences in bone mineral density (BMD) are important variables affecting the survival of proteins. Specific proteins survive better within the mineral matrix due to their mineral-binding properties. The mineral matrix likely also protects these proteins by restricting the movement of decomposer microbes. New potential biomarkers for PMI estimation and AAD estimation were identified. Future development of forensic bone proteomics should include standard measurement of BMD and target a combination of different biomarkers.