Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp.

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor's scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

Proteomic Characterization of Damaged Single Hairs Recovered after an Explosion for Protein-Based Human Identification.

Evidence recovery is challenging where an explosion has occurred. Though hair evidence may be sufficiently robust to be recovered at the site, forensic analysis underutilizes the matrix by relying on morphological analysis. Where DNA is compromised, particularly in hair, protein-based human identification presents a promising alternative. Detection of amino acid polymorphisms in hair proteins as genetically variant peptides (GVPs) permits the inference of individualizing single nucleotide polymorphisms for identification. However, an explosive blast may damage hair proteins and compromise GVP identification. This work assesses effects of an explosive blast on the hair proteome and GVP identification, investigates microscopy as a predictor of proteome profiling success in recovered hairs to improve analysis throughput, and quantifies discriminative power in damaged hairs. The proteomics dataset has been deposited into the ProteomeXchange Consortium (PXD017427). With the exception of degradation in keratins K75, K80, K40, and keratin-associated protein KAP10-11 as markers of hair cuticular damage, corroborated by scanning electron microscopic analysis, minimal hair proteome degradation following explosion allowed successful proteome profiling of single hairs regardless of morphological damage. Finally, GVP identification remained independent of explosion conditions, permitting similar discriminative power between exploded and undamaged hairs. These findings lend greater confidence to GVP analysis in one-inch hairs for forensic identification and provide information about hair protein localization.

Automated analysis of scanning electron microscopic images for assessment of hair surface damage.

Mechanical damage of hair can serve as an indicator of health status and its assessment relies on the measurement of morphological features via microscopic analysis, yet few studies have categorized the extent of damage sustained, and instead have depended on qualitative profiling based on the presence or absence of specific features. We describe the development and application of a novel quantitative measure for scoring hair surface damage in scanning electron microscopic (SEM) images without predefined features, and automation of image analysis for characterization of morphological hair damage after exposure to an explosive blast. Application of an automated normalization procedure for SEM images revealed features indicative of contact with materials in an explosive device and characteristic of heat damage, though many were similar to features from physical and chemical weathering. Assessment of hair damage with tailing factor, a measure of asymmetry in pixel brightness histograms and proxy for surface roughness, yielded 81% classification accuracy to an existing damage classification system, indicating good agreement between the two metrics. Further ability of the tailing factor to score features of hair damage reflecting explosion conditions demonstrates the broad applicability of the metric to assess damage to hairs containing a diverse set of morphological features.

Hair Proteome Variation at Different Body Locations on Genetically Variant Peptide Detection for Protein-Based Human Identification.

Human hair contains minimal intact nuclear DNA for human identification in forensic and archaeological applications. In contrast, proteins offer a pathway to exploit hair evidence for human identification owing to their persistence, abundance, and derivation from DNA. Individualizing single nucleotide polymorphisms (SNPs) are often conserved as single amino acid polymorphisms in genetically variant peptides (GVPs). Detection of GVP markers in the hair proteome via high-resolution tandem mass spectrometry permits inference of SNPs with known statistical probabilities. To adopt this approach for forensic investigations, hair proteomic variation and its effects on GVP identification must first be characterized. This research aimed to assess variation in single-inch head, arm, and pubic hair, and discover body location-invariant GVP markers to distinguish individuals. Comparison of protein profiles revealed greater body location-specific variation in keratin-associated proteins and intracellular proteins, allowing body location differentiation. However, robust GVP markers derive primarily from keratins that do not exhibit body location-specific differential expression, supporting GVP identification independence from hair proteomic variation at the various body locations. Further, pairwise comparisons of GVP profiles with 8 SNPs demonstrated greatest interindividual variation and high intraindividual consistency, enabling similar differentiative potential of individuals using single hairs irrespective of body location origin.

Combined DNA Typing and Protein Identification from Unfired Brass Cartridges,,.

Biological evidence analysis from contact traces is adversely affected by low quantity and quality of DNA. Proteins in these samples contain potentially individualizing information and may be particularly important for difficult surfaces such as brass, where DNA may yield incomplete profiles. In this study, touched unfired brass cartridges were sampled using dry tape or wet swabs and analyzed by separating DNA and protein from the same collected material, thus producing both genomic and proteomic information. DNA recovery was similar for both collection methods, with tape yielding an average of 1.36 ± 1.87 ng and swabs, 1.34 ± 3.04 ng. Analysis by mass spectrometry identified 95 proteins, with the two collection methods showing no significant difference (p = 0.76) in the average number of collected proteins: 44.5 ± 10.9, (tape) versus 47.9 ± 20.4 (swabs). Proteins can be collected from fingerprints at levels necessary to provide identifying information, thus expanding information obtained from challenging evidence.

Development of a Protein-based Human Identification Capability from a Single Hair.

Shed human hair (lacking root nuclear DNA) frequently contributes important information to forensic investigations involving human identification. Detection of genetic variation observed in amino acid sequences of hair proteins provides a new suite of identity markers that augment microscopic hair analysis and mitochondrial DNA sequencing. In this study, a new method that completely dissolves single hairs using a combination of heat, ultrasonication, and surfactants was developed. Dissolved proteins were digested and genetically variant peptide (GVP) profiles were obtained for single hairs (25 mm) via high-resolution nanoflow liquid chromatography-based mass spectrometry and a novel exome-driven bioinformatic approach. Overall, 6519 unique peptides were identified and a total of 57 GVPs were confirmed. Random match probabilities ranged between 2.6 × 10-2 and 6.0 × 10-9 . The new bioinformatic strategy and ability to analyze GVPs in forensically relevant samples sizes demonstrate applicability of this approach to distinguish individuals in forensic contexts.

Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome.

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects' DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European-American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.