Determining Allele-Specific Protein Expression (ASPE) Using a Novel Quantitative Concatamer Based Proteomics Method

Normal Alpha-1-Antitrypsin Variants Display in Serum Allele-Specific Protein Levels

Alpha-1-antitrypsin (A1AT or SERPINA1) has been proposed as a putative biomarker distinguishing healthy from diseased donors throughout several proteomics studies. However, the SERPINA1 gene displays high variability of frequent occurring genotypes among the general population. These different genotypes may affect A1AT expression and serum protein concentrations, and this is often not known, ignored, and/or not reported in serum proteomics studies. Here, we address allele-specific protein serum levels of A1AT in donors carrying the normal M variants of A1AT by measuring the proteoform profiles of purified A1AT from 81 serum samples, originating from 52 donors. When focusing on heterozygous donors, our data clearly reveal a statistically relevant difference in allele-specific protein serum levels of A1AT. In donors with genotype PI*M1VM1A, the experimentally observed ratio was approximately 1:1 (M1V/M1A, 1.00:0.96 ± 0.07, n = 17). For individuals with genotype PI*M1VM2, this ratio was 1:1.28 (M1V/M2, 1.00:1.31, ±0.19, n = 7). For genotypes PI*M1VM3 and PI*M1AM3, a significant higher amount of M3 was observed compared to the M1-subtypes (M1V/M3, 1.00:1.84 ± 0.35, n = 8; M1A/M3, 1.00:1.61 ± 0.33, n = 5). We argue that these observations are important and should be considered when analyzing serum A1AT levels before proposing A1AT as a putative serum biomarker.

Targeted Absolute Protein Quantification Using SILAC Internal Standard and Full-Length Protein Calibrators (TAQSI)

Mass spectrometry (MS)-based proteomics has been increasingly used for targeted absolute protein quantifications in both basic and clinical research. There is a great need to overcome some pitfalls of current MS-based targeted absolute protein quantification methods, such as high inter-assay variability and high cost associated with the use of synthesized isotopic peptides/proteins. Here we describe a targeted absolute protein quantification method utilizing SILAC internal standards and unlabeled full-length protein calibrators (TAQSI). The method has proven accurate, precise, reproducible, and cost-effective. Notably, the method is resistant to the variabilities caused by protein extraction and digestion. Moreover, it avoids measurement errors due to nonsynonymous mutations. This versatile method can be used for determining the absolute expressions of numerous proteins in various biological samples. As a proof-of-concept, this method was successfully applied to absolutely quantitate the protein expressions of carboxylesterase 1 (CES1) in human liver tissues.

Identification of regulatory variants of carboxylesterase 1 (CES1): A proof-of-concept study for the application of the Allele-Specific Protein Expression (ASPE) assay in identifying cis-acting regulatory genetic polymorphisms

It is challenging to study regulatory genetic variants as gene expression is affected by both genetic polymorphisms and non-genetic regulators. The mRNA allele-specific expression (ASE) assay has been increasingly used for the study of cis-acting regulatory variants because cis-acting variants affect gene expression in an allele-specific manner. However, poor correlations between mRNA and protein expressions were observed for many genes, highlighting the importance of studying gene expression regulation at the protein level. In the present study, we conducted a proof-of-concept study to utilize a recently developed allele-specific protein expression (ASPE) assay to identify the cis-acting regulatory variants of CES1 using a large set of human liver samples. The CES1 gene encodes for carboxylesterase 1 (CES1), the most abundant hepatic hydrolase in humans. Two cis-acting regulatory variants were found to be significantly associated with CES1 ASPE, CES1 protein expression, and its catalytic activity on enalapril hydrolysis in human livers. Compared to conventional gene expression-based approaches, ASPE demonstrated an improved statistical power to detect regulatory variants with small effect sizes since allelic protein expression ratios are less prone to the influence of non-genetic regulators (e.g., diseases and inducers). This study suggests that the ASPE approach is a powerful tool for identifying cis-regulatory variants.

A chromosome-level phased genome enabling allele-level studies in sweet orange: a case study on citrus Huanglongbing tolerance

Sweet orange originated from the introgressive hybridizations of pummelo and mandarin resulting in a highly heterozygous genome. How alleles from the two species cooperate in shaping sweet orange phenotypes under distinct circumstances is unknown. Here, we assembled a chromosome-level phased diploid Valencia sweet orange (DVS) genome with over 99.999% base accuracy and 99.2% gene annotation BUSCO completeness. DVS enables allele-level studies for sweet orange and other hybrids between pummelo and mandarin. We first configured an allele-aware transcriptomic profiling pipeline and applied it to 740 sweet orange transcriptomes. On average, 32.5% of genes have a significantly biased allelic expression in the transcriptomes. Different cultivars, transgenic lineages, tissues, development stages, and disease status all impacted allelic expressions and resulted in diversified allelic expression patterns in sweet orange, but particularly citrus Huanglongbing (HLB) shifted the allelic expression of hundreds of genes in leaves and calyx abscission zones. In addition, we detected allelic structural mutations in an HLB-tolerant mutant (T19) and a more sensitive mutant (T78) through long-read sequencing. The irradiation-induced structural mutations mostly involved double-strand breaks, while most spontaneous structural mutations were transposon insertions. In the mutants, most genes with significant allelic expression ratio alterations (≥1.5-fold) were directly affected by those structural mutations. In T19, alleles located at a translocated segment terminal were upregulated, including CsDnaJ, CsHSP17.4B, and CsCEBPZ. Their upregulation is inferred to keep phloem protein homeostasis under the stress from HLB and enable subsequent stress responses observed in T19. DVS will advance allelic level studies in citrus.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

Plasma Carboxylesterase 1 Predicts Methylphenidate Exposure: A Proof-of-Concept Study Using Plasma Protein Biomarker for Hepatic Drug Metabolism

Hepatic drug-metabolizing enzymes (DMEs) play critical roles in determining the pharmacokinetics and pharmacodynamics of numerous therapeutic agents. As such, noninvasive biomarkers capable of predicting DME expression in the liver have the potential to be used to personalize pharmacotherapy and improve drug treatment outcomes. In the present study, we quantified carboxylesterase 1 (CES1) protein concentrations in plasma samples collected during a methylphenidate pharmacokinetics study. CES1 is a prominent hepatic enzyme responsible for the metabolism of many medications containing small ester moieties, including methylphenidate. The results revealed a significant inverse correlation between plasma CES1 protein concentrations and the area under the concentration-time curves (AUCs) of plasma d-methylphenidate (P = 0.014, r = -0.617). In addition, when plasma CES1 protein levels were normalized to the plasma concentrations of 24 liver-enriched proteins to account for potential interindividual differences in hepatic protein release rate, the correlation was further improved (P = 0.003, r = -0.703), suggesting that plasma CES1 protein could explain ~ 50% of the variability in d-methylphenidate AUCs in the study participants. A physiologically-based pharmacokinetic modeling simulation revealed that the CES1-based individualized dosing strategy might significantly reduce d-methylphenidate exposure variability in pediatric patients relative to conventional trial and error fixed dosing regimens. This proof-of-concept study indicates that the plasma protein of a hepatic DME may serve as a biomarker for predicting its metabolic function and the pharmacokinetics of its substrate drugs.

Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection

Discovery of variant peptides such as a single amino acid variant (SAAV) in shotgun proteomics data is essential for personalized proteomics. Both the resolution of shotgun proteomics methods and the search engines have improved dramatically, allowing for confident identification of SAAV peptides. However, it is not yet known if these methods are truly successful in accurately identifying SAAV peptides without prior genomic information in the search database. We studied this in unprecedented detail by exploiting publicly available long-read RNA sequences and shotgun proteomics data from the gold standard reference cell line NA12878. Searching spectra from this cell line with the state-of-the-art open modification search engine ionbot against carefully curated search databases resulted in 96.7% false-positive SAAVs and an 85% lower true positive rate than searching with peptide search databases that incorporate prior genetic information. While adding genetic variants to the search database remains indispensable for correct peptide identification, inclusion of long-read RNA sequences in the search database contributes only 0.3% new peptide identifications. These findings reveal the differences in SAAV detection that result from various approaches, providing guidance to researchers studying SAAV peptides and developers of peptide spectrum identification tools.

Mass spectrometry-based abundance atlas of ABC transporters in human liver, gut, kidney, brain and skin

ABC transporters (ATP-binding cassette transporter) traffic drugs and their metabolites across membranes, making ABC transporter expression levels a key factor regulating local drug concentrations in different tissues and individuals. Yet, quantification of ABC transporters remains challenging because they are large and low-abundance transmembrane proteins. Here, we analysed 200 samples of crude and membrane-enriched fractions from human liver, kidney, intestine, brain microvessels and skin, by label-free quantitative mass spectrometry. We identified 32 (out of 48) ABC transporters: ABCD3 was the most abundant in liver, whereas ABCA8, ABCB2/TAP1 and ABCE1 were detected in all tissues. Interestingly, this atlas unveiled that ABCB2/TAP1 may have TAP2-independent functions in the brain and that biliary atresia (BA) and control livers have quite different ABC transporter profiles. We propose that meaningful biological information can be derived from a direct comparison of these data sets.

Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper

Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.

Absolute Quantitation of Drug-Metabolizing Cytochrome P450 Enzymes and Accessory Proteins in Dog Liver Microsomes Using Label-Free Standard-Free Analysis Reveals Interbreed Variability

Dogs are commonly used in human and veterinary pharmaceutical development. Physiologically based pharmacokinetic modeling using recombinant cytochrome P450 (CYP) enzymes requires accurate estimates of CYP abundance, particularly in liver. However, such estimates are currently available for only seven CYPs, which were determined in a limited number of livers from one dog breed (beagle). In this study, we used a label-free shotgun proteomics method to quantitate 11 CYPs (including four CYPs not previously measured), cytochrome P450 oxidoreductase, and cytochrome b5 in liver microsomes from 59 dogs representing four different breeds and mixed-breed dogs. Validation included showing correlation with CYP marker activities, immunoquantified protein, as well as CYP1A2 and CYP2C41 null allele genotypes. Abundance values largely agreed with those previously published. Average CYP abundance was highest (>120 pmol/mg protein) for CYP2D15 and CYP3A12; intermediate (40-89 pmol/mg) for CYP1A2, CYP2B11, CYP2E1, and CYP2C21; and lowest (<12 pmol/mg) for CYP2A13, CYP2A25, CYP2C41, CYP3A26, and CYP1A1. The CYP2C41 gene was detected in 12 of 58 (21%) livers. CYP2C41 protein abundance averaged 8.2 pmol/mg in those livers, and was highest (19 pmol/mg) in the only liver with two CYP2C41 gene copies. CYP1A2 protein was not detected in the only liver homozygous for the CYP1A2 stop codon mutation. Large breed-associated differences were observed for CYP2B11 (P < 0.0001; ANOVA) but not for other CYPs. Research hounds and Beagles had the highest CYP2B11 abundance; mixed-breed dogs and Chihuahua were intermediate; whereas greyhounds had the lowest abundance. These results provide the most comprehensive estimates to date of CYP abundance and variability in canine liver. SIGNIFICANCE STATEMENT: This work provides the most comprehensive quantitative analysis to date of the drug-metabolizing cytochrome P450 proteome in dogs that will serve as a valuable reference for physiologically based scaling and modeling used in drug development and research. This study also revealed high interindividual variation and dog breed-associated differences in drug-metabolizing cytochrome P450 expression that may be important for predicting drug disposition variability among a genetically diverse canine population.

Functional Study of Carboxylesterase 1 Protein Isoforms

Carboxylesterase 1 (CES1) is a primary human hepatic hydrolase involved in hydrolytic biotransformation of numerous medications. Considerable interindividual variability in CES1 expression and activity has been consistently reported. Four isoforms of the CES1 protein are produced by alternative splicing (AS). In the current study, the activity and expression of each CES1 isoform are examined using transfected cell lines, and CES1 isoform composition and its impact on CES1 activity in human livers are determined. In transfected cells, isoforms 3 and 4 show mRNA and protein expressions comparable to isoforms 1 and 2, but have significantly impaired activity when hydrolyzing enalapril and clopidogrel. In individual human liver samples, isoforms 1 and 2 are the major forms, contributing 73-90% of the total CES1 protein expression. In addition, the protein expression ratios of isoforms 1 and 2 to isoforms 3 and 4 are positively associated with CES1 activity in the liver, suggesting that CES1 isoform composition is a factor contributing to the variability in hepatic CES1 function. Further investigations of the regulation of CES1 AS would improve the understanding of CES1 variability and help develop a strategy to optimize the pharmacotherapy of many CES1 substrate medications.

Response to "Determining Allele-Specific Protein Expression (ASPE) Using a Novel Quantitative Concatamer Based Proteomics Method"

A recent publication in this journal reported the application of a targeted proteomic strategy using a quantitative concatemer (QconCAT) standard to the assessment of allele-specific expression of UGT2B15 claiming this methodology to be a "novel" approach ( J. Proteome Res. 2018, 17 (10), 3606-3612, DOI: 10.1021/acs.jproteome.8b00620). While the application is not common, the method was previously described and reported by our group in relation to the quantification of CYP2B6 alleles ( J. Proteome Res. 2013, 12 (12), 5934-5942, DOI: 10.1021/pr400279u) to assess the expression of a prevalent polymorphism in a Caucasian population.