Assessing protein sequencing in human single hair shafts of decreasing lengths

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.

A human identification system for hair shaft using RNA polymorphism

Hair is one of the common pieces of evidence at crime scenes, with abundant mitochondrial DNA but limited nuclear DNA in its shaft. It also helps to narrow the investigation scope to maternal lineage but fails to provide unique individual information. We assumed that RNA in hair shafts would be an alternative resource used to perform human identification based on the facts that (1) RNA retains the polymorphic information; (2) the multi-copy of RNA in a cell resists degradation as compared to the one-copy of nuclear DNA. In this study, we explored the potential of RNA polymorphism in hair shafts for forensic individual identification. A SNaPshot typing system was constructed using 18 SNPs located on 11 genes (ABCA13, AHNAK, EXPH5, KMT2D, KRT35, PPP1R15A, RBM33, S100A5, TBC1D4, TMC5, TRPV2). The RNA typing system was evaluated for sensitivity, species specificity, and feasibility for aged hair samples. Hair samples from a Shanxi population in China were used for the population study of the system. The detection limit of the assay was 2 ng RNA. The CDP of these 11 genes was 0.999969 in the Shanxi population. We also identified the concordance of the RNA and DNA typing results. In summary, we developed an RNA typing method to perform human identification from hair shafts, which performed as accurately as nuclear DNA typing. Our method provides a potential basis for solving the human identification problem from hair shafts, as well as other biological materials that lack nuclear DNA.

DNA and protein analyses of hair in forensic genetics

Hair is one of the most common pieces of biological evidence found at a crime scene and plays an essential role in forensic investigation. Hairs, especially non-follicular hairs, are usually found at various crime scenes, either by natural shedding or by forcible shedding. However, the genetic material in hairs is usually highly degraded, which makes forensic analysis difficult. As a result, the value of hair has not been fully exploited in forensic investigations and trials. In recent years, with advances in molecular biology, forensic analysis of hair has achieved remarkable strides and provided crucial clues in numerous cases. This article reviews recent developments in DNA and protein analysis of hair and attempts to provide a comprehensive solution to improve forensic hair analysis.

The Enrichment of Specific Hair Follicle-Associated Cell Populations in Plucked Hairs Offers an Opportunity to Study Gene Expression Underlying Hair Traits

Gene expression differences can assist in characterizing important underlying genetic mechanisms between different phenotypic traits. However, when population-dense tissues are studied, the signals from scarce populations are diluted. Therefore, appropriately choosing a sample collection method that enriches a particular type of effector cells might yield more specific results. To address this issue, we performed a polyA-selected RNA-seq experiment of domestic horse (Equus ferus caballus) plucked-hair samples and skin biopsies. Then, we layered the horse gene abundance results against cell type-specific marker genes generated from a scRNA-seq supported with spatial mapping of laboratory mouse (Mus musculus) skin to identify the captured populations. The hair-plucking and skin-biopsy sample-collection methods yielded comparable quality and quantity of RNA-seq results. Keratin-related genes, such as KRT84 and KRT75, were among the genes that showed higher abundance in plucked hairs, while genes involved in cellular processes and enzymatic activities, such as MGST1, had higher abundance in skin biopsies. We found an enrichment of hair-follicle keratinocytes in plucked hairs, but detected an enrichment of other populations, including epidermis keratinocytes, in skin biopsies. In mammalian models, biopsies are often the method of choice for a plethora of gene expression studies and to our knowledge, this is a novel study that compares the cell-type enrichment between the non-invasive hair-plucking and the invasive skin-biopsy sample-collection methods. Here, we show that the non-invasive and ethically uncontroversial plucked-hair method is recommended depending on the research question. In conclusion, our study will allow downstream -omics approaches to better understand integumentary conditions in both health and disease in horses as well as other mammals.

Alternative LC-MS/MS Platforms and Data Acquisition Strategies for Proteomic Genotyping of Human Hair Shafts

Protein is a major component of all biological evidence. Proteomic genotyping is the use of genetically variant peptides (GVPs) that contain single-amino-acid polymorphisms to infer the genotype of matching nonsynonymous single-nucleotide polymorphisms for the individual from whom the protein sample originated. This can be used to statistically associate an individual to evidence found at a crime scene. The utility of the inferred genotype increases as the detection of GVPs increases, which is the direct result of technology transfer to mass spectrometry platforms typically available. Digests of single (2 cm) human hair shafts from three European and two African subjects were analyzed using data-dependent acquisition on a Q-Exactive Plus Hybrid Quadrupole-Orbitrap system, data-independent acquisition and a variant of parallel reaction monitoring (PRM) on an Orbitrap Fusion Lumos Tribrid system, and multiple reaction monitoring (MRM) on an Agilent 6495 triple quadrupole system. In our hands, average GVP detection from a selected panel of 24 GVPs increased from 6.5 ± 1.1 and 3.1 ± 0.8 using data-dependent and -independent acquisition to 9.5 ± 0.7 and 11.7 ± 1.7 using PRM and MRM (p < 0.05), respectively. PRM resulted in a 1.3-fold increase in detection sensitivity, and MRM resulted in a 1.6-fold increase in detection sensitivity. This increase in biomarker detection has a functional impact on the statistical association of a protein sample and an individual. Increased biomarker sensitivity, using Markov Chain Monte Carlo modeling, produced a median-estimated random match probability of over 1 in 10 trillion from a single hair using targeted proteomics. For PRM and MRM, detected GVPs were validated by the inclusion of stable isotope-labeled peptides in each sample, which served also as a detection trigger. This research accomplishes two aims: the demonstration of utility for alternative analytical platforms in proteomic genotyping and the establishment of validation methods for the evaluation of inferred genotypes.

Visualizing shed skin cells in fingerprint residue using dark-field microscopy

This proof-of-concept study shows that dark-field microscopy provides sufficient contrast for cell visualization in fingerprints with high sebum content. Although the application is limited to smooth surfaces that do not scatter light, such as polyethylene terephthalate (PET), it was able to measure the number of cells deposited within a fingerprint residue and the reduction in cell transfer with repeated skin contact. On a PET surface, at roughly 5 N of contact force, a typical finger transfers several hundred cells onto the surface. Over subsequent finger contacts onto a clean PET surface, this number decreased exponentially until a steady state was reached, which is characterized by the transfer of (78 ± 36) cells or (0.46 ± 0.21) cells/mm² when normalized for fingerprint area. High uncertainty in cell transfer was due to: the highly variable nature of a human finger (where the number of loose cells varies from person to person and from day to day depending on what they touch) and difficulties in controlling the contact force and finger movement such as twisting during deposition (where twisting of the finger can expose a new patch of skin to the substrate, increasing the number of cell transfer). Plasma etching was also explored as an effective way to validate dark-field microscopy for cell counting. Although limited to inorganic substrates due to etching effects, exposing the fingerprint for less than 10 min can remove a majority of the sebum while keeping the cells intact for a before-and-after comparison using light microscopy.