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 β 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.

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.

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.

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.

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.

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.

[Ecological aspects of postmortem microbiome and possibility of their use in forensic practice]

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.

Individual Identification with Short Tandem Repeat Analysis and Collection of Secondary Information Using Microbiome Analysis

Forensic investigation is important to analyze evidence and facilitate the search for key individuals, such as suspects and victims in a criminal case. The forensic use of genomic DNA has increased with the development of DNA sequencing technology, thereby enabling additional analysis during criminal investigations when additional legal evidence is required. In this study, we used next-generation sequencing to facilitate the generation of complementary data in order to analyze human evidence obtained through short tandem repeat (STR) analysis. We examined the applicability and potential of analyzing microbial genome communities. Microbiological supplementation information was confirmed for two of four failed STR samples. Additionally, the accuracy of the gargle sample was confirmed to be as high as 100% and was highly likely to be classified as a body fluid sample. Our experimental method confirmed that anthropological and microbiological evidence can be obtained by performing two experiments with one extraction. We discuss the advantages and disadvantages of using these techniques, explore prospects in the forensic field, and highlight suggestions for future research.

Microbial traces and their role in forensic science

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

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.

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.

Forensic Applications of Microbiomics: A Review

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

Dysbiosis in the Dead: Human Postmortem Microbiome Beta-Dispersion as an Indicator of Manner and Cause of Death

The postmortem microbiome plays an important functional role in host decomposition after death. Postmortem microbiome community successional patterns are specific to body site, with a significant shift in composition 48 h after death. While the postmortem microbiome has important forensic applications for postmortem interval estimation, it also has the potential to aid in manner of death (MOD) and cause of death (COD) determination as a reflection of antemortem health status. To further explore this association, we tested beta-dispersion, or the variability of microbiomes within the context of the “Anna Karenina Principle” (AKP). The foundational principle of AKP is that stressors affect microbiomes in unpredictable ways, which increases community beta-dispersion. We hypothesized that cases with identified M/CODs would have differential community beta-dispersion that reflected antemortem conditions, specifically that cardiovascular disease and/or natural deaths would have higher beta-dispersion compared to other deaths (e.g., accidents, drug-related deaths). Using a published microbiome data set of 188 postmortem cases (five body sites per case) collected during routine autopsy in Wayne County (Detroit), MI, we modeled beta-dispersion to test for M/COD associations a priori. Logistic regression models of beta-dispersion and case demographic data were used to classify M/COD. We demonstrated that beta-dispersion, along with case demographic data, could distinguish among M/COD – especially cardiovascular disease and drug related deaths, which were correctly classified in 79% of cases. Binary logistic regression models had higher correct classifications than multinomial logistic regression models, but changing the defined microbial community (e.g., full vs. non-core communities) used to calculate beta-dispersion overall did not improve model classification or M/COD. Furthermore, we tested our analytic approach on a case study that predicted suicides from other deaths, as well as distinguishing MOD (e.g., homicides vs. suicides) within COD (e.g., gunshot wound). We propose an analytical workflow that combines postmortem microbiome indicator taxa, beta-dispersion, and case demographic data for predicting MOD and COD classifications. Overall, we provide further evidence the postmortem microbiome is linked to the host’s antemortem health condition(s), while also demonstrating the potential utility of including beta-dispersion (a non-taxon dependent approach) coupled with case demographic data for death determination.

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.

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.

Molecular Tracing to Find Source of Protracted Invasive Listeriosis Outbreak, Southern Germany, 2012-2016

We investigated 543 Listeria monocytogenes isolates from food having a temporal and spatial distribution compatible with that of the invasive listeriosis outbreak occurring 2012–2016 in southern Germany. Using forensic microbiology, we identified several products from 1 manufacturer contaminated with the outbreak genotype. Continuous molecular surveillance of food isolates could prevent such outbreaks.

Validation of real-time PCR assays for bioforensic detection of model plant pathogens

The U.S. agricultural sector is vulnerable to intentionally introduced microbial threats because of its wide and open distribution and economic importance. To investigate such events, forensically valid assays for plant pathogen detection are needed. In this work, real-time PCR assays were developed for three model plant pathogens: Pseudomonas syringae pathovar tomato, Xylella fastidiosa, and Wheat streak mosaic virus. Validation included determination of the linearity and range, limit of detection, sensitivity, specificity, and exclusivity of each assay. Additionally, positive control plasmids, distinguishable from native signature by restriction enzyme digestion, were developed to support forensic application of the assays. Each assay displayed linear amplification of target nucleic acid, detected 100 fg or less of target nucleic acid, and was specific to its target pathogen. Results obtained with these model pathogens provide the framework for development and validation of similar assays for other plant pathogens of high consequence.

Particularities regarding the etiology of sepsis in forensic services

If in clinical practice definitive diagnostic criteria had been established, after death sepsis is often difficult to diagnose, especially if a site of origin is not found or if no clinical data are available. This article will analyze the etiology of sepsis in a medical-legal service with emphasis on the differences in diagnosing it in clinical and forensic environments. A total of 78 cases of sepsis cases diagnosed or confirmed at the autopsy were selected. The etiological agent was determined either during the hospitalization or by postmortem bacteriology. A high prevalence of Gram-negative sepsis was found, especially multidrug-resistant micro-organisms. Most frequent etiological agents were Acinetobacter baumannii, Escherichia coli, Enterobacter, Enterococcus, Pseudomonas, and Klebsiella. Polymicrobial sepsis is much more frequent than in nonforensic cases. In legal medicine, the prevalence of Gram-negative sepsis is much higher than in nonforensic autopsies, and the point of origin is shifted toward the skin and the gastrointestinal system.