Human Hepatic Transporter Signature Peptides for Quantitative Targeted Absolute Proteomics: Selection, Digestion Efficiency, and Peptide Stability

PURPOSE

Quantitative targeted absolute proteomics (QTAP) quantifies proteins by measuring the signature peptides produced from target proteins by trypsin digestion. The selection of signature peptides is critical for reliable peptide quantification. The purpose of this study was to comprehensively assess the digestion efficiency and stability of tryptic peptides and to identify optimal signature peptides for human hepatic transporters and membrane marker proteins.

METHODS

The plasma membrane fraction of the human liver was digested at different time points and the peptides were comprehensively quantified using quantitative proteomics. Transporters and membrane markers were quantified using the signature peptides by QTAP.

RESULTS

Tryptic peptides were classified into clusters with low digestion efficiency, low stability, and high digestion efficiency and stability. Using the cluster information, we found that a proline residue next to the digestion site or the peptide position in or close to the transmembrane domains lowers digestion efficiency. A peptide containing cysteine at the N-terminus or arginine-glycine lowers peptide stability. Based on this information and the time course of peptide quantification, optimal signature peptides were identified for human hepatic transporters and membrane markers. The quantification of transporters with multiple signature peptides yielded consistent absolute values with less than 30% of coefficient variants in human liver microsomes and homogenates.

CONCLUSIONS

The signature peptides selected in the present study enabled the reliable quantification of human hepatic transporters. The QTAP protocol using these optimal signature peptides provides quantitative data on hepatic transporters usable for integrated pharmacokinetic studies.

Exercise-induced myokines downregulates the ACE2 level in bronchial epithelial cells: Implications for SARS-CoV-2 prevention

BACKGROUND

The Covid-19 pandemic has emerged as the leading public health challenge of our time (20th century). While vaccinations have finally blunted the death rate, concern has remained about more virulent forms highlighting the need for alternative approaches. Epidemiological studies indicate that physical activity has been shown to decrease the risk of infection of some respiratory viruses. Part of the salutary effects of exercise is believed to be through the elaboration of cytokines by contracting skeletal muscles (termed myokines). The objective of this study was to investigate whether exercise-induced myokines would mitigate the SARS-CoV-2 infectivity of the bronchial epithelium through modulating the SARS-CoV-2 Covid-19 receptor (angiotensin-converting enzyme 2 -ACE2) its priming enzyme, transmembrane serine protease 2 (TMPRSS2).

METHODS

We utilized a cell culture model of exercise to generate myokines by differentiating C2C12 cells into myotubules and inducing them to contract via low-frequency electric pulse stimulation. Condition media was concentrated via centrifugation and applied to human immortalized human bronchial epithelium cell line (6HBE14o) along with conditioned media from unstimulated myotubules as controls. Following exposure to myokines, the 16HBE14o cells were harvested and subjected to quantitative RT-PCR and Enzyme-Linked Immunosorbent Assay (ELISA) for assessment of mRNA and protein levels of ACE2 and TMPRSS2, respectively. Pilot proteomic data was performed with isotope barcoding and mass spectroscopy.

RESULTS

Quantitative Real-Time PCR of 16HBE14o with 48 h treated unstimulated vs. stimulated myokine treatment revealed a reduction of ACE2 and TMPRSS2 mRNA by 32% (p<2.69x10-5) and 41% (p<4.57x10-5), respectively. The high sensitivity of ELISAs showed downregulation of ACE2 and TMPRSS2 protein expression in 16HBE14o cells by 53% (p<0.01) and 32% (p<0.03) respectively with 48 h treated. For rigor, this work was replicated in the human lung cancer cell line A549, which mirrored the downregulation. Proteomic analysis showed dramatic alteration in myokine profile between contracted and uncontracted C2C12 tubules.

CONCLUSIONS

The current study explores a novel approach of a modified exercise cell culture system and uses ACE2 and TMPRSS2 as a surrogate marker of SARS-CoV-2 infectivity. In conclusion, we demonstrated biological data supporting exercise's protective effect against Covid-19. These further strengthen myokines' beneficial role as potential therapeutic targets against SARS-CoV-2 and similar viruses albeit these preliminary cell culture studies will require future validation in animal models.

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.

Data-independent acquisition (DIA): An emerging proteomics technology for analysis of drug-metabolizing enzymes and transporters

Data-independent acquisition (DIA) proteomics is a recently-developed global mass spectrometry (MS)-based proteomics strategy. In a DIA method, precursor ions are isolated into pre-defined isolation windows and fragmented; all fragmented ions in each window are then analyzed by a high-resolution mass spectrometer. DIA proteomics analysis is characterized by a broad protein coverage, high reproducibility, and accuracy, and its combination with advances in other techniques such as sample preparation and computational data analysis could lead to further improvements in assay performances. DIA technology has been increasingly utilized in various proteomics studies, including quantifying drug-metabolizing enzymes and transporters. Quantitative proteomics study of drug-metabolizing enzymes and transporters could lead to a better understanding of pharmacokinetics and pharmacodynamics and facilitate drug development. This review summarizes the application of DIA technology in proteomic analysis of drug-metabolizing enzymes and transporters.

Application of proteomics to understand maturation of drug metabolizing enzymes and transporters for the optimization of pediatric drug therapy

Drug disposition in children is different compared to adults. Growth and developmental change the processes involved in drug disposition and efficacy, including membrane transporters and drug metabolizing enzymes, but for many of these proteins, the exact changes have not been fully elucidated to date. Quantitative proteomics offers a solution to analyze many DME and DT proteins at once and can be performed with very small tissue samples, overcoming many of the challenges previously limiting research in this pediatric field. Liquid chromatography tandem mass spectrometry (LC-MS/MS) based methods for quantification of (membrane) proteins has evolved as a golden standard for proteomic analysis. The last years, big steps have been made in maturation studies of hepatic and renal drug transporters and drug metabolizing enzymes using this method. Protein and organ specific maturation patterns have been identified for the human liver and kidney, which aids pharmacological modelling and predicting drug dosing in the pediatric population. Further research should focus on other organs, like intestine and brain, as well as on innovative methods in which proteomics can be used to further overcome the limited access to pediatric tissues, including liquid biopsies and organoids. In this review there is aimed to provide an overview of available human pediatric proteomics data, discuss its challenges and provide guidance for future research.

Label-free quantitative proteomic analysis of serum extracellular vesicles differentiating patients of alcoholic and nonalcoholic fatty liver diseases

Alcoholic liver disease (ALD) and nonalcoholic fatty liver disease (NAFLD) are typically asymptomatic and slow-progressing but potentially fatal diseases that are common causes of liver cirrhosis and related complications. Exosomes are nano-sized extracellular vesicles that have been linked to various intercellular communication processes and can carry biological materials reflecting the state and severity of disease. In this study, shotgun proteomic analysis of the protein expression profiles of extracellular vesicles, including exosomes and microvesicles, enriched from human serum samples of 24 patients diagnosed with various fatty liver diseases was performed using liquid chromatography tandem mass spectrometry (LC-MS/MS) followed by protein identification and label-free quantification using the MaxQuant platform. A total of 329 proteins, including 190 previously reported exosome-specific proteins, were identified from four types of liver disease, where significant differences in protein expression were found in apolipoproteins, immunoglobulins, and other previously reported markers of liver disease. Principal component analysis of 61 proteins identified from MaxQuant analysis of the LC-MS/MS data provided a confident differentiation between ALD and NAFLD. SIGNIFICANCE: The current investigation revealed the difference among various types of liver disease using LC-MS/MS of exosomes enriched from human serum samples of 24 patients where the most significantly up-regulation proteins were alpha-2-macroglobulin for alcoholic hepatitis and apolipoprotein C3 for nonalcoholic fatty liver disease.

Proteomic Quantification of Changes in Abundance of Drug-Metabolizing Enzymes and Drug Transporters in Human Liver Cirrhosis: Different Methods, Similar Outcomes

Model-based assessment of the effects of liver disease on drug pharmacokinetics requires quantification of changes in enzymes and transporters responsible for drug metabolism and disposition. Different proteomic methods are currently used for protein quantification in tissues and in vitro systems, each with specific procedures and requirements. The outcome of quantitative proteomic assays using four different methods (one targeted and three label-free) applied to the same sample set was compared in this study. Three pooled cirrhotic liver microsomal samples corresponding to cirrhosis with nonalcoholic fatty liver disease, biliary disease, or cancer and a control microsomal pool were analyzed using quantification concatemer-based targeted proteomics, the total protein approach (TPA), high three ion intensity (Hi3) approach, and intensity-based absolute quantification (iBAQ) to determine the absolute and relative abundance in disease compared with control. The relative abundance data provided a "disease perturbation factor" (DPF) for each target protein. Absolute and relative abundances generated by standard-based label-free methods (iBAQ and Hi3) showed good agreement with targeted proteomics (limited bias and scatter), but TPA (standard-free method) overestimated absolute abundances by approximately 2-fold. The DPF was consistent between different proteomic methods but varied between enzymes and transporters, indicating discordance of effects of cirrhosis on various metabolism-related proteins. The DPF ranged from no change (e.g., for glucuronosyltransferase-1A6 in nonalcoholic fatty liver disease group) to less than 0.3 (e.g., carboxylesterases-1 in cirrhosis of biliary origin). SIGNIFICANCE STATEMENT: This study demonstrated that relative changes in enzymes and transporters (DPF) are independent of the quantitative proteomic methods used. Standard-based label-free methods, such as high three ion intensity (Hi3) and intensity-based absolute quantification (iBAQ) methods, were less biased and more precise than the total protein approach (TPA) when compared with targeted data. The DPF reconciled differences across proteomic methods observed with absolute levels. Using this approach, differences were revealed in the expression of enzymes/transporters in cirrhosis associated with different etiologies.

Dilemmas With Absolute Quantification of Pharmacologically Relevant Proteins Using Mass Spectrometry

Determination of abundances of proteins involved in uptake, distribution, metabolism and excretion of xenobiotics is a prerequisite to understand and predict elimination mechanisms in tissue. Mass spectrometry promises simple and accurate measurements of individual proteins in complex mixtures using isotopically labeled peptide standards. However, comparisons of measurements performed in different laboratories have shown considerable discrepancies in the data generated. Even when very similar approaches are compared, the results differ significantly. An alternative method of measuring protein titers is global proteomics. Depending on sample type, this allows quantification of hundreds to thousands of proteins in a single analysis. It enables system-wide insights by providing protein copy numbers and cell sizes. Regardless of differences, the workflows of both the labeled standard-based and the proteomic approach share several steps. Each can be critical. Selection of optimal techniques is the prerequisite for accurate and reproducible protein quantification.

Mass Spectrometry of Human Transporters

Transporters are key to understanding how an individual will respond to a particular dose of a drug. Two patients with similar systemic concentrations may have quite different local concentrations of a drug at the required site. The transporter profile of any individual depends upon a variety of genetic and environmental factors, including genotype, age, and diet status. Robust models (virtual patients) are therefore required and these models are data hungry. Necessary data include quantitative transporter profiles at the relevant organ. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) is currently the most powerful method available for obtaining this information. Challenges include sourcing the tissue, isolating the hydrophobic membrane-embedded transporter proteins, preparing the samples for MS (including proteolytic digestion), choosing appropriate quantification methodology, and optimizing the LC-MS/MS conditions. Great progress has been made with all of these, especially within the last few years, and is discussed here.

Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)-Based Proteomics of Drug-Metabolizing Enzymes and Transporters

Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics is a powerful tool for identifying and quantifying proteins in biological samples, outperforming conventional antibody-based methods in many aspects. LC-MS/MS-based proteomics studies have revealed the protein abundances of many drug-metabolizing enzymes and transporters (DMETs) in tissues relevant to drug metabolism and disposition. Previous studies have consistently demonstrated marked interindividual variability in DMET protein expression, suggesting that varied DMET function is an important contributing factor for interindividual variability in pharmacokinetics (PK) and pharmacodynamics (PD) of medications. Moreover, differential DMET expression profiles were observed across different species and in vitro models. Therefore, caution must be exercised when extrapolating animal and in vitro DMET proteomics findings to humans. In recent years, DMET proteomics has been increasingly utilized for the development of physiologically based pharmacokinetic models, and DMET proteins have also been proposed as biomarkers for prediction of the PK and PD of the corresponding substrate drugs. In sum, despite the existence of many challenges in the analytical technology and data analysis methods of LC-MS/MS-based proteomics, DMET proteomics holds great potential to advance our understanding of PK behavior at the individual level and to optimize treatment regimens via the DMET protein biomarker-guided precision pharmacotherapy.

Interpretation of Drug Interaction Using Systemic and Local Tissue Exposure Changes

Systemic exposure of a drug is generally associated with its pharmacodynamic (PD) effect (e.g., efficacy and toxicity). In this regard, the change in area under the plasma concentration-time curve (AUC) of a drug, representing its systemic exposure, has been mainly considered in evaluation of drug-drug interactions (DDIs). Besides the systemic exposure, the drug concentration in the tissues has emerged as a factor to alter the PD effects. In this review, the status of systemic exposure, and/or tissue exposure changes in DDIs, were discussed based on the recent reports dealing with transporters and/or metabolic enzymes mediating DDIs. Particularly, the tissue concentration in the intestine, liver and kidney were referred to as important factors of PK-based DDIs.

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.

Label-free absolute protein quantification with data-independent acquisition

Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIA-based label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides. SIGNIFICANCE: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.

From Endogenous Compounds as Biomarkers to Plasma-Derived Nanovesicles as Liquid Biopsy; Has the Golden Age of Translational Pharmacokinetics-Absorption, Distribution, Metabolism, Excretion-Drug-Drug Interaction Science Finally Arrived?

It is now established that a drug's pharmacokinetics (PK) absorption, distribution, metabolism, excretion (ADME) and drug-drug interaction (DDI) profile can be modulated by age, disease, and genotype. In order to facilitate subject phenotyping and clinical DDI assessment, therefore, various endogenous compounds (in plasma and urine) have been pursued as drug-metabolizing enzyme and transporter biomarkers. Compared with biomarkers, however, the topic of circulating extracellular vesicles as "liquid biopsy" has received little attention within the ADME community; most organs secrete nanovesicles (e.g., exosomes) into the blood that contain luminal "cargo" derived from the originating organ (proteins, messenger RNA, and microRNA). As such, ADME profiling of plasma exosomes could be leveraged to better define genotype-phenotype relationships and the study of ontogeny, disease, and complex DDIs. If methods to support the isolation of tissue-derived plasma exosomes are successfully developed and validated, it is envisioned that they will be used jointly with genotyping, biomarkers, and modeling tools to greatly progress translational PK-ADME-DDI science.

Drug Transporters in Xenobiotic Disposition and Pharmacokinetic Prediction

Drug transporters are widely expressed in organs and tissue barriers throughout human and animal bodies. Studies over the last two decades have identified various ATP-binding cassette and solute carrier transporters that play critical roles in the absorption, distribution, metabolism, and elimination of drugs and xenobiotics. This special section contains more than 20 original manuscripts and reviews that cover the most recent advances in the areas of drug transporter research, including the basic biology and function of transporters, expression of drug transporters in organ and tissue barriers, the mechanisms underlying regulation of transporter expression, transporter-mediated drug disposition in animal models, and the development and utilization of new technologies in drug transporter study, as well as pharmacokinetic modeling and simulation to assess transporter involvement in drug disposition and drug-drug interactions. We believe that the topics covered in this special section will advance our understanding of the roles of transporters in drug disposition, efficacy, and safety.

Multiple-Enzyme-Digestion Strategy Improves Accuracy and Sensitivity of Label- and Standard-Free Absolute Quantification to a Level That Is Achievable by Analysis with Stable Isotope-Labeled Standard Spiking

Quantification of individual proteins is an essential task in understanding biological processes. For example, determination of concentrations of proteins transporting and metabolizing xenobiotics is a prerequisite for drug disposition predictions in humans based on in vitro data. So far, this task has frequently been accomplished by targeted proteomics. This type of analyses requires preparation of stable isotope labeled standards for each protein of interest. The selection of appropriate standard peptides is usually tedious and the number of proteins that can be studied in a single experiment by these approaches is limited. In addition, incomplete digestion of proteins often affects the accuracy of the quantification. To circumvent these constrains in proteomic protein quantification, label- and standard-free approaches, such as "total protein approach" (TPA) have been proposed. Here we directly compare an approach using stable isotope labeled (SIL) standards and TPA for quantification of transporters and enzymes in human liver samples within the same LC-MS/MS runs. We show that TPA is a convenient alternative to SIL-based methods. Optimization of the sample preparation beyond commonly used single tryptic digestion, by adding consecutive cleavage steps, improves accuracy and reproducibility of the TPA method to a level, which is achievable by analysis using stable isotope-labeled standard spiking.

Interaction of soy isoflavones and their main metabolites with hOATP2B1 transporter

Membrane organic anion-transporting polypeptides (OATPs) are responsible for the drug transmembrane transport within the human body. The function of OATP2B1 transporter can be inhibited by various natural compounds. Despite increased research interest in soya as a part of human diet, the effect of its active components to interact with hOATP2B1 has not been elucidated in a complex extent. This in vitro study examined the inhibitory effect of main soy isoflavones (daidzin, daidzein, genistin, genistein, glycitin, glycitein, biochanin A, formononetin) and their metabolites formed in vivo (S-equol, O-desmethylangolensin) towards human OATP2B1 transporter. MDCKII cells overexpressing hOATP2B1 were employed to determine quantitative inhibitory parameters of the tested compounds and to analyze mechanism/s of the inhibitory interaction. The study showed that aglycones of soy isoflavones and the main biologically active metabolite S-equol were able to significantly inhibit hOATP2B1-mediated transport. The Ki values for most of aglycones range from 1 to 20 μM. In contrast, glucosides did not exhibit significant inhibitory effect. The kinetic analysis did not indicate a uniform type of inhibition towards the hOATP2B1 although predominant mechanism of inhibition seemed to be competitive. These findings may suggest that tested soy isoflavones and their metabolites might affect transport of xenobiotics including drugs across tissue barriers via hOATP2B1.

Quantification of Hepatic Organic Anion Transport Proteins OAT2 and OAT7 in Human Liver Tissue and Primary Hepatocytes

Organic anion transporter (OAT) 2 and OAT7 were recently shown to be involved in the hepatic uptake of drugs; however, there is limited understanding of the population variability in the expression of these transporters in liver. There is also a need to derive relative expression-based scaling factors (REFs) that can be used to bridge in vitro functional data to the in vivo drug disposition. To this end, we quantified OAT2 and OAT7 surrogate peptide abundance in a large number of human liver tissue samples ( n = 52), as well as several single-donor cryopreserved human hepatocyte lots ( n = 30) by a novel, validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. The average surrogate peptide expression of OAT2 and OAT7 in the liver samples was 1.52 ± 0.57 and 4.63 ± 1.58 fmol/μg membrane protein, respectively. While we noted statistically significant differences ( p < 0.05) in hepatocyte and liver tissue abundances for both OAT2 and OAT7, the differences were relatively small (1.8- and 1.5-fold difference in median values, respectively). Large interindividual variability was noted in the hepatic expression of OAT2 (16-fold in liver tissue and 23-fold in hepatocytes). OAT7, on the other hand, showed less interindividual variability (4-fold) in the livers, but high variability for the hepatocyte lots (27-fold). A significant positive correlation in OAT2 and OAT7 expression was observed, but expression levels were neither associated with age nor sex. In conclusion, our data suggest marked interindividual variability in the hepatic expression of OAT2/7, which may contribute to the pharmacokinetic variability of their substrates. Because both transporters were less abundant in hepatocytes than livers, a REF-based approach is recommended when scaling in vitro hepatocyte transport data to predict hepatic drug clearance and liver exposure of OAT2/7 substrates.