Biology subjects

Parker, G. J.

Publications and source records attributed to Parker, G. J..

3 recordsLinked to original sources

bioRxiv2023

Blood-brain barrier water exchange measurements using contrast-enhanced ASL

A technique for quantifying regional blood-brain barrier (BBB) water exchange rates using contrast-enhanced arterial spin labelling (CE-ASL) is presented and evaluated in simulations and in vivo. The two-compartment ASL model describes the water exchange rate from blood to tissue, kb, but to estimate kb in practice it is necessary to separate the intra- and extravascular signals. This is challenging in standard ASL data owing to the small difference in T1 values. Here, a gadolinium-based contrast agent is used to increase this T1 difference and enable the signal components to be disentangled. The optimal post-contrast blood T1 [Formula] at 3T was determined in a sensitivity analysis, and the accuracy and precision of the method quantified using Monte Carlo simulations. Proof-of-concept data were acquired in six healthy volunteers (five female, age range 24 - 46 years). The sensitivity analysis identified the optimal [Formula] at 3T as 0.8 s. Simulations showed kb could be estimated in individual cortical regions with a relative error{epsilon} < 1% and coefficient of variation CoV = 30 %; however, a high dependence on blood T1 was also observed. In volunteer data, mean parameter values in grey matter were: arterial transit time tA = 1.15{+/-}0.49 s, cerebral blood flow f = 58.0{+/-}14.3 ml blood / min / 100 ml tissue, water exchange rate kb = 2.32 {+/-} 2.49 s-1. CE-ASL can provide regional BBB water exchange rate estimates; however, the clinical utility of the technique is dependent on the achievable accuracy of measured T1 values.

biophysics↗

bioRxiv2021

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 that contain single amino acid polymorphisms to infer the genotype of matching non-synonymous single nucleotide polymorphisms for the individual who originated the protein sample. 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 genetically variant peptides 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 on a Orbitrap Fusion Lumos Tribrid system, and multiple reaction monitoring on an Agilent 6495 triple quadrupole system. In our hands, average genetically variant peptide detection from a selected 24 genetically variant peptide panel 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 parallel reaction monitoring and multiple reaction monitoring (p < 0.05). Parallel reaction monitoring resulted in a 1.3-fold increase in detection sensitivity, and multiple reaction monitoring 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 parallel reaction monitoring and multiple reaction monitoring, detected genetically variant peptides 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. HighlightsO_LITest four mass spectrometry configurations to optimize detection of genetically variant peptides C_LIO_LITechnology transfer of proteomic genotyping assays C_LIO_LIImproved sensitivity results in higher level of forensic discrimination for human identification using multiple reaction monitoring C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/435505v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1001cfaorg.highwire.dtl.DTLVardef@6e8aa1org.highwire.dtl.DTLVardef@14f8076org.highwire.dtl.DTLVardef@7ad930_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

Peptide Ancestry Informative Markers in Uterine Neoplasms from Women of European, African and Asian Ancestry

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with molecular disease pathogenesis. Nonsynonymous single nucleotide polymorphisms (SNPs) encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis shows that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R2=0.9905). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues resulted in the quantitation of 62 pAIMs that correlate with self-described race and genotype-confirmed patient ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. These efforts describe a generalized set of markers for proteoancestry assessment that will further support studies investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

cancer biology↗