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

YesHuman 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.The Technology Commercialization Innovation Program (Contracts #121668, #132043) of the Utah Governors Office of Commercial Development, the Scholarship Activitie

A case for “StopGo”: Reprogramming translation to augment codon meaning of GGN by promoting unconventional termination (Stop) after addition of glycine and then allowing continued translation (Go)

When a eukaryotic mRNA sequence specifying an amino acid motif known as 2A is directly followed by a proline codon, two nonoverlapping proteins are synthesized. From earlier work, the second protein is known to start with this proline codon and is not created by proteolysis. Here we identify the C-terminal amino acid of an upstream 2A-encoded product from Perina nuda picorna-like virus that is glycine specified by the last codon of the 2A-encoding sequence. This is an example of recoding where 2A promotes unconventional termination after decoding of the glycine codon and continued translation beginning with the 3′ adjacent proline codon

Rqc2p and 60S ribosomal subunits mediate mRNA-independent elongation of nascent chains

In Eukarya, stalled translation induces 40S dissociation and recruitment of the ribosome quality control complex (RQC) to the 60S subunit, which mediates nascent chain degradation. Here we report cryo-electron microscopy structures revealing that the RQC components Rqc2p (YPL009C/Tae2) and Ltn1p (YMR247C/Rkr1) bind to the 60S subunit at sites exposed after 40S dissociation, placing the Ltn1p RING (Really Interesting New Gene) domain near the exit channel and Rqc2p over the P-site transfer RNA (tRNA). We further demonstrate that Rqc2p recruits alanine- and threonine-charged tRNA to the A site and directs the elongation of nascent chains independently of mRNA or 40S subunits. Our work uncovers an unexpected mechanism of protein synthesis, in which a protein--not an mRNA--determines tRNA recruitment and the tagging of nascent chains with carboxy-terminal Ala and Thr extensions ("CAT tails")

Evaluating changes in firefighter urinary metabolomes after structural fires: an untargeted, high resolution approach

Abstract Firefighters have elevated rates of urinary tract cancers and other adverse health outcomes, which may be attributable to environmental occupational exposures. Untargeted metabolomics was applied to characterize this suite of environmental exposures and biological changes in response to occupational firefighting. 200 urine samples from 100 firefighters collected at baseline and two to four hours post-fire were analyzed using untargeted liquid-chromatography and high-resolution mass spectrometry. Changes in metabolite abundance after a fire were estimated with fixed effects linear regression, with false discovery rate (FDR) adjustment. Partial least squares discriminant analysis (PLS-DA) was also used, and variable important projection (VIP) scores were extracted. Systemic changes were evaluated using pathway enrichment for highly discriminating metabolites. Metabolome-wide-association-study (MWAS) identified 268 metabolites associated with firefighting activity at FDR q < 0.05. Of these, 20 were annotated with high confidence, including the amino acids taurine, proline, and betaine; the indoles kynurenic acid and indole-3-acetic acid; the known uremic toxins trimethylamine n-oxide and hippuric acid; and the hormone 7a-hydroxytestosterone. Partial least squares discriminant analysis (PLS-DA) additionally implicated choline, cortisol, and other hormones. Significant pathways included metabolism of urea cycle/amino group, alanine and aspartate, aspartate and asparagine, vitamin b3 (nicotinate and nicotinamide), and arginine and proline. Firefighters show a broad metabolic response to fires, including altered excretion of indole compounds and uremic toxins. Implicated pathways and features, particularly uremic toxins, may be important regulators of firefighter’s increased risk for urinary tract cancers

Imputed nsSNP profile probabilities in European and African populations.

<p><b>A</b>) The probability of an overall individual nsSNP profile in the population (Pr(profile|population)) was estimated by determining the probability of detected nsSNP alleles, or allele combination, in each gene (Pr(nsSNP gene profile|population)), and then using the product rule to multiply these probabilities together (Pr(overall profile|population)). <b>B</b>) The probability of overall imputed nsSNP profiles occurring in the European population (Pr(profile|EUR population)) was calculated using imputed nsSNP alleles from individuals in the two European-American cohorts (EA1 and EA2) and the product rule. Values are presented as a logarithm (log₁₀(Pr(profile|EUR population))). Confidence intervals (90% CI) are estimated using parametric bootstrapping. <b>C</b>) The overall imputed nsSNP profile probability in the African population was also calculated (Pr(profile|AFR population)) and plotted versus the probability of the profile occurring in the European population (Pr(profile|EUR population)). Confidence intervals (90% CI) were estimated using parametric bootstrapping. In addition to European–American subjects (red), imputed nsSNP profile probabilities were also estimated from proteomic datasets derived from an African-American (green) and Kenyan (blue) cohort. The line of equal profile probability in the European and African population is indicated (dotted line). <b>D</b>) The likelihood of hair samples coming from a European relative to African genetic background was calculated as the ratio of overall imputed nsSNP profile probabilities in the European and African populations (EUR/AFR = Pr(profile|EUR population)/Pr(profile|AFR population)); European-American subjects (red), African-American subjects (green), and Kenyan subjects (blue) are indicated.</p

Comparison of probability estimates based on imputed nsSNPs and mitochondrial DNA haplotype.

<p>The mitochondrial DNA haplotype and subgroup from one of the European-American cohorts (EA2, n = 15) were classified, compared to a database of subjects from an American sample population (Utah, n = 9,372), and the logarithm of haplotype probability was calculated (log₁₀(Pr(mtDNA haplotype|Utah population)), black bars). Genetically variant peptides containing single amino acid polymorphisms were identified in the hair shaft proteomic datasets of the same subjects, an overall profile of imputed nsSNP loci determined, and logarithm of the probability of each profile occurring in the European population was calculated as described in the Materials and Methods section (log₁₀(Pr(imputed nsSNP profile|EUR population)), red bars). Confidence intervals (90% CI) were estimated using parametric bootstrapping. Each measure is represented using the same axis (log₁₀(Pr(profile|population))).</p