Comparison of protein expression levels and proteomically-inferred genotypes using human hair from different body sites

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.

Profiling of hair proteome revealed individual demographics

Human hair is often found at crime scenes, persists for a long time, and is a valuable biological specimen in forensic investigations. Hair contains minimal intact nuclear DNA for the discrimination of individual identity. In such cases, proteomics evaluation of hair proteins could provide an attractive alternative for protein-based human identification. Therefore, this study adopted a proteomic approach to profile hair shafts from both males and females across different ethnic populations including Chinese, Indians, Malays, and Filipinos in their 20-80 s. First, hair proteins were extracted by different methods to adopt the most suitable protocol that produced the highest extraction efficiency based on most significant enrichment of keratins and keratin-associated proteins. Abundance of hair keratins including both types I and II, and keratin-associated proteins, estimated using label-free quantification, showed distinguishable profiles, and the possibilities of distinguishing individuals within each ethnic origin. Similarly, several protein candidates and their abundances could be used to distinguish sex and age of individuals. This study explored the possibility of utilizing hair proteomics phenotyping in forensic science to differentiate individuals across various ethnic groups, sex and age.

Protein Biomarkers for the Identification of Forensically Relevant Human Hair from Different Body Parts in Intimate Contact Cases

Correctly identifying the human hair anatomic location found at crime scenes can link biological sample donors with the actual crime event, thus providing significant insight into the crime scene reconstruction. Forensic proteomic studies on human hairs can facilitate the development of new biomarkers for hair identification while compensating for the limitations of the conventional morphologic hair comparison and DNA analysis. Herein, the LC-MS/MS platform was used to find differentially expressed protein biomarkers in hairs from different body sites. The findings indicated that a total of 296 protein biomarkers with statistically significant differences in body sites were initially identified, and hair samples from the scalp, pubic, and armpit parts were distinguished from each other, which were validated by multiple bioinformatic methods. Fewer differences in protein patterns between armpit and pubic hairs while larger differences between hair and armpit as well as pubic hairs provided reasonable evidence of sexual or close intimate contact in crimes. This study lays the foundation for the development of a more reliable strategy to distinguish human hairs of various body areas from Chinese and will also support microscopic hair comparison analysis and assist in the proper handling of legal proceedings in relative cases by judicial officers, deserving special attention and further in-depth investigation. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the iProX partner repository with the dataset identifier PXD038173.

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.

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.

Elucidation of familial relationships using hair shaft proteomics

This study examines the potential of hair shaft proteomic analysis to delineate genetic relatedness. Proteomic profiling and amino acid sequence analysis provide information for quantitative and statistically-based analysis of individualization and sample similarity. Protein expression levels are a function of cell-specific transcriptional and translational programs. These programs are greatly influenced by an individual's genetic background, and are therefore influenced by familial relatedness as well as ancestry and genetic disease. Proteomic profiles should therefore be more similar among related individuals than unrelated individuals. Likewise, profiles of genetically variant peptides that contain single amino acid polymorphisms, the result of non-synonymous SNP alleles, should behave similarly. The proteomically-inferred SNP alleles should also provide a basis for calculation of combined paternity and sibship indices. We test these hypotheses using matching proteomic and genetic datasets from a family of two adults and four siblings, one of which has a genetic condition that perturbs hair structure and properties. We demonstrate that related individuals, compared to those who are unrelated, have more similar proteomic profiles, profiles of genetically variant peptides and higher combined paternity indices and combined sibship indices. This study builds on previous analyses of hair shaft protein profiling and genetically variant peptide profiles in different real-world scenarios including different human hair shaft body locations and pigmentation status. It also validates the inclusion of proteomic information with other biomolecular substrates in forensic hair shaft analysis, including mitochondrial and nuclear DNA.

Forensic proteomics

Protein is a major component of all biological evidence, often the matrix that embeds other biomolecules such as polynucleotides, lipids, carbohydrates, and small molecules. The proteins in a sample reflect the transcriptional and translational program of the originating cell types. Because of this, proteins can be used to identify body fluids and tissues, as well as convey genetic information in the form of single amino acid polymorphisms, the result of non-synonymous SNPs. This review explores the application and potential of forensic proteomics. The historical role that protein analysis played in the development of forensic science is examined. This review details how innovations in proteomic mass spectrometry have addressed many of the historical limitations of forensic protein science, and how the application of forensic proteomics differs from proteomics in the life sciences. Two more developed applications of forensic proteomics are examined in detail: body fluid and tissue identification, and proteomic genotyping. The review then highlights developing areas of proteomics that have the potential to impact forensic science in the near future: fingermark analysis, species identification, peptide toxicology, proteomic sex estimation, and estimation of post-mortem intervals. Finally, the review highlights some of the newer innovations in proteomics that may drive further development of the field. In addition to potential impact, this review also attempts to evaluate the stage of each application in the development, validation and implementation process. This review is targeted at investigators who are interested in learning about proteomics in a forensic context and expanding the amount of information they can extract from biological evidence.

Proteomics in Forensic Analysis: Applications for Human Samples

Proteomics, the large-scale study of all proteins of an organism or system, is a powerful tool for studying biological systems. It can provide a holistic view of the physiological and biochemical states of given samples through identification and quantification of large numbers of peptides and proteins. In forensic science, proteomics can be used as a confirmatory and orthogonal technique for well-built genomic analyses. Proteomics is highly valuable in cases where nucleic acids are absent or degraded, such as hair and bone samples. It can be used to identify body fluids, ethnic group, gender, individual, and estimate post-mortem interval using bone, muscle, and decomposition fluid samples. Compared to genomic analysis, proteomics can provide a better global picture of a sample. It has been used in forensic science for a wide range of sample types and applications. In this review, we briefly introduce proteomic methods, including sample preparation techniques, data acquisition using liquid chromatography-tandem mass spectrometry, and data analysis using database search, spectral library search, and de novo sequencing. We also summarize recent applications in the past decade of proteomics in forensic science with a special focus on human samples, including hair, bone, body fluids, fingernail, muscle, brain, and fingermark, and address the challenges, considerations, and future developments of forensic proteomics.

Age-Related Changes in Hair Shaft Protein Profiling and Genetically Variant Peptides

Recent reports highlight possible improvements in individual identification using proteomic information from human hair evidence. These reports have stimulated investigation of parameters that affect the utility of proteomic information. In addition to variables already studied relating to processing technique and anatomic origin of hair shafts, an important variable is hair ageing. Present work focuses on the effect of age on protein profiling and analysis of genetically variant peptides (GVPs). Hair protein profiles may be affected by developmental and physiological changes with age of the donor, exposure to different environmental conditions and intrinsic processes, including during storage. First, to explore whether general trends were evident in the population at different ages, hair samples were analyzed from groups of different subjects in their 20's, 40's and 60's. No significant differences were seen as a function of age, but consistent differences were evident between European American and African American hair profiles. Second, samples collected from single individuals at different ages were analyzed. Mostly, these showed few protein expression level differences over periods of 10 years or less, but samples from subjects at 44 and 65 year intervals were distinctly different in profile. The results indicate that use of protein profiling for personal identification, if practical, would be limited to decadal time intervals. Moreover, batch effects were clearly evident in samples processed by different staff. To investigate the contribution of storage (at room temperature) in affecting the outcomes, the same proteomic digests were analyzed for GVPs. In samples stored over 10 years, GVPs were reduced in number in parallel with the yield of identified proteins and unique peptides. However, a very different picture emerged with respect to personal identification. Numbers of GVPs sufficed to distinguish individuals despite the age differences of the samples. As a practical matter, three hair samples per person provided nearly the maximal number obtained from 5 or 6 samples. The random match probability (where the log increased in proportion to the number of GVPs) reached as high as 1 in 10⁸. The data indicate that GVP results are dependent on the single nucleotide polymorphism profile of the donor genome, where environmental/processing factors affect only the yield, and thus are consistent despite the ages of the donors and samples and batchwise effects in processing. This conclusion is critical for application to casework where the samples may be in storage for long periods and used to match samples recently collected.

Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine

The increasing availability of high throughput proteomics data provides us with opportunities as well as posing new ethical challenges regarding data privacy and re-identifiability of participants. Moreover, the fact that proteomics represents a level between the genotype and the phenotype further exacerbates the situation, introducing dilemmas related to publicly available data, anonymization, ownership of information and incidental findings. In this paper, we try to differentiate proteomics from genomics data and cover the ethical challenges related to proteomics data sharing. Finally, we give an overview of the proposed solutions and the outlook for future studies.