Proteomic genotyping of fingermark donors with genetically variant peptides

Starch treatment improves the salivary proteome for subject identification purposes

Identification of subjects, including perpetrators, is one of the most crucial goals of forensic science. Saliva is among the most common biological fluids found at crime scenes, containing identifiable components. DNA has been the most prominent identifier to date, but its analysis can be complex due to low DNA yields and issues preserving its integrity at the crime scene. Proteins are emerging as viable candidates for subject identification. Previous work has shown that the salivary proteome of the least-abundant proteins may be helpful for subject identification, but more optimized techniques are needed. Among them is removing the most abundant proteins, such as salivary α-amylase. Starch treatment of saliva samples elicited the removal of this enzyme and that of glycosylated, low-molecular-weight proteins, proteases, and immunoglobulins, resulting in a saliva proteome profile enriched with a subset of proteins, allowing a more reliable and nuanced subject identification.

Recent advances in forensic biology and forensic DNA typing: INTERPOL review 2019-2022

This review paper covers the forensic-relevant literature in biological sciences from 2019 to 2022 as a part of the 20th INTERPOL International Forensic Science Managers Symposium. Topics reviewed include rapid DNA testing, using law enforcement DNA databases plus investigative genetic genealogy DNA databases along with privacy/ethical issues, forensic biology and body fluid identification, DNA extraction and typing methods, mixture interpretation involving probabilistic genotyping software (PGS), DNA transfer and activity-level evaluations, next-generation sequencing (NGS), DNA phenotyping, lineage markers (Y-chromosome, mitochondrial DNA, X-chromosome), new markers and approaches (microhaplotypes, proteomics, and microbial DNA), kinship analysis and human identification with disaster victim identification (DVI), and non-human DNA testing including wildlife forensics. Available books and review articles are summarized as well as 70 guidance documents to assist in quality control that were published in the past three years by various groups within the United States and around the world.

Identifying individuals using proteomics: are we there yet?

Multi-omics approaches including proteomics analyses are becoming an integral component of precision medicine. As clinical proteomics studies gain momentum and their sensitivity increases, research on identifying individuals based on their proteomics data is here examined for risks and ethics-related issues. A great deal of work has already been done on this topic for DNA/RNA sequencing data, but it has yet to be widely studied in other omics fields. The current state-of-the-art for the identification of individuals based solely on proteomics data is explained. Protein sequence variation analysis approaches are covered in more detail, including the available analysis workflows and their limitations. We also outline some previous forensic and omics proteomics studies that are relevant for the identification of individuals. Following that, we discuss the risks of patient reidentification using other proteomics data types such as protein expression abundance and post-translational modification (PTM) profiles. In light of the potential identification of individuals through proteomics data, possible legal and ethical implications are becoming increasingly important in the field.

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.

Improving the visualization of fingermarks using multi-target immunolabeling

The development of fingermarks is an important step in visualizing ridge patterns for individualization purposes. Immunolabeling can be applied to fingermarks to selectively and sensitively detect antigens in fingermarks, and can be used as a developing method to visualize fingermarks. In this study we investigated single (the detection of one antigen) and multiple targeting approaches (the detection of multiple antigens simultaneously) to improve fingermark development. The detection of dermcidin, an antimicrobial peptide, was used as the gold standard to compare single and multi-target detection of keratins, albumin and/or dermcidin. Single detection of dermcidin and albumin mostly resulted in clear ridge details and/or pore detection, whereas the single keratin detection resulted in a poor visualization of the fingermarks. The multi-target approach in which both dermcidin and albumin were targeted, resulted in improved fingermark development compared to single dermcidin detection. Therefore, we recommend the use of multi-target detection consisting of anti-dermcidin and anti-albumin when using immunolabeling as fingermark development technique. Additionally, the optimized multi-target approach was tested as a pre- and post-development technique in combination with powder dusting and cyanoacrylate fuming. Immunolabeling has not been implemented yet in forensic case work, however we expect that immunolabeling can be used to redevelop poorly developed and/or smudged fingermarks in the nearby future. Currently, an ongoing pilot-study is being conducted in collaboration with the Dutch police.

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.

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.

Fractionation of DNA and protein from individual latent fingerprints for forensic analysis

Human touch samples represent a significant portion of forensic DNA casework. Yet, the generally low abundance of genetic material combined with the predominantly extracellular nature of DNA in these samples makes DNA-based forensic analysis exceptionally challenging. Human proteins present in these same touch samples offer an abundant and environmentally-robust alternative. Proteogenomic methods, using protein sequence variants arising from nonsynonymous DNA mutations, have recently been applied to forensic analysis and may represent a viable option looking forward. However, DNA analysis remains the gold standard and any proteomics-based methods would need to consider how DNA could be co-extracted from samples without significant loss. Herein, we describe a simple workflow for the collection, enrichment and fractionation of DNA and protein in latent fingerprint samples. This approach ensures that DNA collected from a latent fingerprint can be analyzed by traditional DNA casework methods, while protein can be proteolytically digested and analyzed via standard liquid chromatography-tandem mass spectrometry-based proteomics methods from the same touch sample. Sample collection from non-porous surfaces (i.e., glass) is performed through the application of an anionic surfactant over the fingermark. The sample is then split into separate DNA and protein fractions following centrifugation to enrich the protein fraction by pelleting skin cells. The results indicate that this workflow permits analysis of DNA within the sample, yet highlights the challenge posed by the trace nature of DNA in touch samples and the potential for DNA to degrade over time. Protein deposited in touch samples does not appear to share this limitation, with robust protein quantities collected across multiple human donors. The quantity and quality of protein remains robust regardless of fingerprint age. The proteomic content of these samples is consistent across individual donors and fingerprint age, supporting the future application of genetically variable peptide (GVP) analysis of touch samples for forensic identification.

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.