Microbiome-Based Stain Analyses in Crime Scenes

Forensic Microbiology: When, Where and How

Forensic microbiology is a relatively new discipline, born in part thanks to the development of advanced methodologies for the detection, identification and characterization of microorganisms, and also in relation to the growing impact of infectious diseases of iatrogenic origin. Indeed, the increased application of medical practices, such as transplants, which require immunosuppressive treatments, and the growing demand for prosthetic installations, associated with an increasing threat of antimicrobial resistance, have led to a rise in the number of infections of iatrogenic origin, which entails important medico-legal issues. On the other hand, the possibility of detecting minimal amounts of microorganisms, even in the form of residual traces (e.g., their nucleic acids), and of obtaining gene and genomic sequences at contained costs, has made it possible to ask new questions of whether cases of death or illness might have a microbiological origin, with the possibility of also tracing the origin of the microorganisms involved and reconstructing the chain of contagion. In addition to the more obvious applications, such as those mentioned above related to the origin of iatrogenic infections, or to possible cases of infections not properly diagnosed and treated, a less obvious application of forensic microbiology concerns its use in cases of violence or violent death, where the characterization of the microorganisms can contribute to the reconstruction of the case. Finally, paleomicrobiology, e.g., the reconstruction and characterization of microorganisms in historical or even archaeological remnants, can be considered as a sister discipline of forensic microbiology. In this article, we will review these different aspects and applications of forensic microbiology.

Response of salivary microbiome to temporal, environmental, and surface characteristics under in vitro exposure

The microbiome of saliva stains deposited at crime scenes and in everyday settings is valuable for forensic investigations and environmental ecology. However, the dynamics and applications of microbial communities in these saliva stains have not been fully explored. In this study, we analyzed saliva samples that were exposed to indoor conditions for up to 1 year and to different carriers (cotton, sterile absorbent cotton swab, woolen, dacron) in both indoor and outdoor environments for 1 month using high-throughput sequencing. The analysis of microbial composition and Mfuzz clustering showed that the salivary flora, specifically Streptococcus (cluster7), which was associated with microbial contamination, remained stable over short periods of time. However, prolonged exposure led to significant differences due to the invasion of environmental bacteria such as Pseudomonas and Achromobacter. The growth and colonization of environmental flora were promoted by humidity. The neutral model predictions indicated that the assembly of salivary microbial communities in outdoor environments was significantly influenced by stochastic processes, with environmental characteristics having a greater impact on community change compared to surface characteristics. By incorporating data from previous studies on fecal and vaginal secretion microbiology, we developed RF and XGBoost classification models that achieved high accuracy (>98 %) and AUC (>0.8). Additionally, a RF regression model was created to determine the time since deposition (TsD) of the stains. Time inference models yielded a mean absolute error (MAE) of 7.1 days for stains exposed for 1 year and 14.2 h for stains exposed for 14 days. These findings enhance our understanding of the changes in the microbiome of saliva stains over time, in different environments, and on different surfaces. They also have potential applications in assessing potential microbial contamination, identifying body fluids, and inferring the time of deposition.

Mass spectrometry-based proteomic analysis of biological stains identifies body fluids specific markers

The identification of biological stains and their tissue resource is an important part of forensic research. Current methods suffer from several limitations including poor sensitivity and specificity, trace samples, and sample destruction. In this study, we profiled the proteomes of menstrual blood, peripheral blood, saliva, semen, and vaginal fluid with mass spectrometry technology. Tissue-enhanced and tissue-specific proteins of each group have been proposed as potential biomarkers. These candidate proteins were further annotated and screened through the combination with the Human Protein Atlas database. Our data not only validates the protein biomarkers reported in previous studies but also identifies novel candidate biomarkers for human body fluids. These candidates lay the foundation for the development of rapid and specific forensic examination methods.

Recent omics advances in hair aging biology and hair biomarkers analysis

Aging is a complex natural process that leads to a decline in physiological functions, which is visible in signs such as hair graying, thinning, and loss. Although hair graying is characterized by a loss of pigment in the hair shaft, the underlying mechanism of age-associated hair graying is not fully understood. Hair graying and loss can have a significant impact on an individual's self-esteem and self-confidence, potentially leading to mental health problems such as depression and anxiety. Omics technologies, which have applications beyond clinical medicine, have led to the discovery of candidate hair biomarkers and may provide insight into the complex biology of hair aging and identify targets for effective therapies. This review provides an up-to-date overview of recent omics discoveries, including age-associated alterations of proteins and metabolites in the hair shaft and follicle, and highlights the significance of hair aging and graying biomarker discoveries. The decline in hair follicle stem cell activity with aging decreased the regeneration capacity of hair follicles. Cellular senescence, oxidative damage and altered extracellular matrix of hair follicle constituents characterized hair follicle and hair shaft aging and graying. The review attempts to correlate the impact of endogenous and exogenous factors on hair aging. We close by discussing the main challenges and limitations of the field, defining major open questions and offering an outlook for future research.

The Future Is Now: Unraveling the Expanding Potential of Human (Necro)Microbiome in Forensic Investigations

The relevance of postmortem microbiological examinations has been controversial for decades, but the boom in advanced sequencing techniques over the last decade is increasingly demonstrating their usefulness, namely for the estimation of the postmortem interval. This comprehensive review aims to present the current knowledge about the human postmortem microbiome (the necrobiome), highlighting the main factors influencing this complex process and discussing the principal applications in the field of forensic sciences. Several limitations still hindering the implementation of forensic microbiology, such as small-scale studies, the lack of a universal/harmonized workflow for DNA extraction and sequencing technology, variability in the human microbiome, and limited access to human cadavers, are discussed. Future research in the field should focus on identifying stable biomarkers within the dominant Bacillota and Pseudomonadota phyla, which are prevalent during postmortem periods and for which standardization, method consolidation, and establishment of a forensic microbial bank are crucial for consistency and comparability. Given the complexity of identifying unique postmortem microbial signatures for robust databases, a promising future approach may involve deepening our understanding of specific bacterial species/strains that can serve as reliable postmortem interval indicators during the process of body decomposition. Microorganisms might have the potential to complement routine forensic tests in judicial processes, requiring robust investigations and machine-learning models to bridge knowledge gaps and adhere to Locard's principle of trace evidence.