Characterizing the D-Amino Acid Position in Peptide Epimers by Using Higher-Energy Collisional Dissociation Tandem Mass Spectrometry: A Case Study of Liraglutide.

D-amino acid-containing peptides (DAACPs) occur in biological and artificial environments. Since the importance of DAACPs has been recognized, various mass spectrometry-based analytical approaches have been developed. However, the capability of higher-energy collisional dissociation (HCD) fragmentation to characterize DAACP sites has not been evaluated. In this study, we compared the normalized spectra intensity under different conditions of HCD and used liraglutide along with its DAACPs as examples. Our results indicated that the difference in the intensity of y ions between DAACPs and all-L liraglutide could not only distinguish them but also localize the sites of D-amino acids in the DAACPs. Our data demonstrate the potential of using HCD for the site characterization of DAACPs, which may have great impact in biological studies and peptide drug development.

Assessing the Similarity between Random Copolymer Drug Glatiramer Acetate by Using LC-MS Data Coupling with Hypothesis Testing.

The full characterization of nonbiological complex drugs (NBCDs) is not possible, but analytical approaches are of urgent need to evaluate the similarity between different lots and compare with their follow-up versions. Here, we propose a hypothesis testing-based approach to assess the similarity/difference between random amino acid copolymer drugs using liquid chromatography mass spectrometry (LC-MS) analysis. Two glatiramer acetate (GA) drugs, commercially available Copaxone and in-house synthesized SPT, and a negative control were digested by Lys-C and followed by HILIC-MS analysis. After retention time alignment and feature identification, 1627 features matched to m/z values in an elemental composition database were considered as derived from active drug ingredients. A hypothesis testing approach, the sum of squared deviations test, was developed to process high-dimensional data derived from LC-MS spectra. The feasibility of this approach was first demonstrated by testing 5 versus 5 lots of Copaxone and Copaxone versus SPT, which suggested a significant similarity by obtaining the estimated 95th percentile of the distribution of the estimator (ρ̂(95%)) at 0.0056 (p-value = 0.0026) and 0.0026 (p-value < 0.0001), respectively. In contrast, the ρ̂ was 0.036 (p-value = 1.00), while comparing Copaxone and the negative control, implying a lack of similarity. We further synthesized nine stable isotope-labeled peptides to validate the proposed amino acid sequences in the database, demonstrating the correctness in sequence identification. The quantitation variations in our analytical procedures were determined to be 6.8-7.7%. This approach was found to have a great potential for evaluating the similarity between generic NBCDs and listed reference drugs, as well as to monitor the lot-to-lot variation.

Identification of di-isononyl phthalate metabolites for exposure marker discovery using in vitro/in vivo metabolism and signal mining strategy with LC-MS data.

Di-isononyl phthalate esters (DINPs) are endocrine-disrupting chemicals and have replaced di(2-ethylhexyl) phthalate (DEHP) as the major plasticizer for poly(vinyl chloride) (PVC) products in recent years. Exposure marker discovery of DINPs is crucial, because of their high potential for human exposure and toxicity. Here, we propose an alternative approach for tracing signals derived from stable isotope-labeled precursors with varied labeling ratios to efficiently filter probable metabolite signals. The statistical process, which involves a signal mining algorithm with isotope tracing (SMAIT), has effectively filtered 13 probable DINP metabolite signals out of the 8867 peaks in the LC-MS data obtained from incubated stable isotope-labeled precursors with liver enzymes. Seven of the 13 probable metabolite signals were confirmed as DINP structure-related metabolites by preliminary MS/MS analyses. These 7 structure-related metabolite signals were validated as effective DINP exposure markers, using urine samples collected from DINP-administered rats without time-consuming comprehensive structure identification. We propose that the 7 identified possible DINP metabolite signals of m/z 279.1, 293.1, 305.1, 307.1, 321.1, 365.1, and 375.1 are potential markers for DINP exposure and should be investigated further. The integrated approach described here can efficiently, and systematically, filter probable metabolite signals from a complex LC-MS dataset for toxic exposure marker discovery. It is a relatively low-cost/rapid workflow for exposure marker discovery.

Associations between maternal phthalate exposure and cord sex hormones in human infants.

It has been speculated that maternal phthalate exposure may affect reproductive development in human newborns. However, the mechanism awaits further investigation. The aim is to evaluate the association between maternal phthalate exposure and cord sex steroid hormones in pregnant women and their newborns from the general population. A total of 155 maternal and infant pair were recruited and analyzed. Levels of urinary phthalate metabolites and sex steroid hormones were determined using liquid chromatography/electrospray tandem mass spectrometry (LC-ESI-MS/MS) and radioimmunoassay (RIA), respectively. No significant correlation was found between each steroid hormones and phthalate metabolites for male newborns, except MMP was marginally significantly correlated with E(2). After adjusting for maternal age, estradiol (E(2)) levels in cord serum from male newborns were not correlated with maternal urinary phthalate metabolites. In female newborns, the maternal urinary levels of mono-(2-ethylhexyl) phthalate (MEHP) and mono-(2-ethyl-5-hydroxyhexyl) phthalate (5OH-MEHP) were negatively correlated with the free testosterone (fT) and fT/E(2) levels in cord serum with Pearson correlation coefficients ranging between -0.24 and -0.29 (p<0.05). Additionally, after gestational age was adjusted, the maternal urinary level of DEHP was negatively correlated with the free testosterone (fT) and fT/E(2) levels in cord serum. We suggest that maternal exposure to phthalates may affect sex steroid hormones status in fetal and newborn stage.

Collection of in vivo-like liver cell secretome with alternative sample enrichment method using a hollow fiber bioreactor culture system combined with tangential flow filtration for secretomics analysis.

A hollow fiber bioreactor (HFB) culture system coupled with a tangential flow filtration (TFF) device was used for HepG2 cell secretome analysis. In order to reduce the loss of low-molecular-weight proteins, two new features, the hollow fiber with 0.1 µm pore size and a TFF device with a membrane of 1kDa molecular weight cutoff, were added to the system described previously. The HFB culture system and the conventional dish culture method for secretome collection were compared side by side. It was observed that only a small fraction of cells (<0.01%) were lysed in the HFB culture system, in contrast to the 2.73% in the conventional dish culture. A total of 111 proteins were identified in the collected conditioned medium (CM) by liquid chromatography-tandem mass spectrometry (LC-MS/MS) with this improved collection procedure. Many of these proteins reported to be biomarkers for liver-related diseases. About 16% of the identified proteins were smaller than 20kDa, demonstrating that the modified collection system had the ability to reduce the loss of low-molecular-weight proteins, in contrast to our previous collection system. The percentage increase of proteins classified as extracellular space or plasma membrane between the conventional dish culture and the HFB culture system was 40-60%. We believed that in vivo-like culture environments could support liver cells to improve protein secretion than conventional dish cultures. We suggest that the combination of the HFB culture system, TFF device, and LC-MS/MS analysis, would be an efficient procedure for the collection and characterization of in vivo-like cell secretome.

A statistical procedure to selectively detect metabolite signals in LC-MS data based on using variable isotope ratios.

The tracing of metabolite signals in LC-MS data using stable isotope-labeled compounds has been described in the literature. However, the filtering efficiency and confidence when mining metabolite signals in complex LC-MS datasets can be improved. Here, we propose an additional statistical procedure to increase the compound-derived signal mining efficiency. This method also provides a highly confident approach to screen out metabolite signals because the correlation of varying concentration ratios of native/stable isotope-labeled compounds and their instrumental response ratio is used. An in-house computational program [signal mining algorithm with isotope tracing (SMAIT)] was developed to perform the statistical procedure. To illustrate the SMAIT concept and its effectiveness for mining metabolite signals in LC-MS data, the plasticizer, di-(2-ethylhexyl) phthalate (DEHP), was used as an example. The statistical procedure effectively filtered 15 probable metabolite signals from 3617 peaks in the LC-MS data. These probable metabolite signals were considered structurally related to DEHP. Results obtained here suggest that the statistical procedure could be used to confidently facilitate the detection of probable metabolites from a compound-derived precursor presented in a complex LC-MS dataset.

Association between GST genetic polymorphism and dose-related production of urinary benzene metabolite markers, trans, trans-muconic acid and S-phenylmercapturic acid.

The urinary benzene metabolites, trans, trans-muconic acid (ttMA) and S-phenylmercapturic acid (SPMA), are widely used as benzene exposure biomarkers. The influence of the glutathione S-transferase (GST) genetic polymorphism on the excretion levels of urinary ttMA and/or SPMA has been investigated. The association between dose-related production of urinary benzene metabolites and benzene exposure level was also reported. However, the association between the dose-related productions of urinary benzene metabolites and GST genetic polymorphism was not described in the literature. The purpose of this study was to investigate the association between the GST genetic polymorphism and dose-related production of the two widely used biomarkers, urinary ttMA and SPMA. Seventy male workers in a chemical factory were measured for their benzene exposure levels and provided blood and urine specimens at the end of work-shift. The atmospheric benzene exposure levels of these workers were determined by passive samplers with gas chromatograph mass spectrometer. The urinary ttMA and SPMA levels were quantitated by an online dual-loop cleanup device with an electrospray ionization tandem mass spectrometer. The analyses of GST genotypes, including M(1), T(1), and P(1), were done using PCR. Mean (+/- SD) of benzene exposure levels in participants was 7.2 +/- 15 ppm. The ttMA and SPMA levels in the high benzene exposure group (> or =1 ppm) were higher than those in the low benzene exposure group (<1 ppm; P < 0.001). Among the GST genotypes investigated in this study, the results showed that only the GSTT1 genotype was related to the level and dose-related production of SPMA. Using SPMA for evaluating benzene exposure, the results suggest that the GSTT1 genetic polymorphism, especially in a comparison study between two populations with different GSTT1 genotype frequencies, should be considered. Additionally, the biological exposure index value of SPMA should be set based on the levels of subjects with GSTT1-deficient genotypes for protection of all subjects.

Evaluation of electrospray ionization and atmospheric pressure chemical ionization for simultaneous detection of estrone and its metabolites using high-performance liquid chromatography/tandem mass spectrometry.

The levels of estrogens and/or their metabolites play important roles in carcinogenesis, reproductive function, and sexual development during perinatal and adolescence periods. The main purpose of this report was to investigate the applicability of high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) with electrospray ionization (ESI) and/or atmospheric pressure chemical ionization (APCI) for simultaneous detection of estrone (E1) and its six metabolites. Both positive and negative ionization modes in ESI and APCI were used to evaluate the signal responses of seven target analytes. Among the seven target analytes, five analytes, E1, 16alpha-hydroxyestrone, 2-methoxyestrone, 4-methoxyestrone, and 2-hydroxyestrone-3-methyl, produced signals with the best signal-to-noise (S/N) ratios in positive APCI-MS/MS mode, while the other two analytes, 2-hydroxyestrone and 4-hydroxyestrone, yielded the best S/N ratios in negative ESI-MS/MS mode. Based on the results of the evaluation, HPLC-APCI-MS/MS with switching between positive and negative modes was recommended for simultaneous detection of E1 and its six metabolites. The proposed analytical scheme was successfully applied in the analysis of cell culture medium of Human liver carcinoma cells treated with varying amounts of 2,3,7,8-tetrachlorodibenzo-p-dioxin.

An electrospray ionization tandem mass spectrometry based system with an online dual-loop cleanup device for simultaneous quantitation of urinary benzene exposure biomarkers trans,trans-muconic acid and S-phenylmercapturic acid.

An electrospray ionization tandem mass spectrometry (ESI-MS/MS) system with an online dual-loop cleanup device was developed for simultaneous quantitation of the urinary benzene exposure biomarkers trans,trans-muconic acid (ttMA) and S-phenylmercapturic acid (SPMA). The cleanup device was constructed from an autosampler, two electrically operated two-position switching valves, a reversed-phase C18 trap cartridge, a 200-microL loop, and two solvent-delivery pumps. The device was interfaced directly with a triple-quadrupole mass spectrometer and fully controlled by computer software and hardware. Because isotope dilution by introducing 13C-labeled ttMA and SPMA as internal standards was employed, the precision of the analytical system was high (for ttMA, intra- and inter-day CV values ranged from 3.82-4.53%; for SPMA, 2.13-7.06%). The calibration curves obtained using human urine spiked with ttMA were linear from 15.6-4000 microg/L (R = 0.9998) and SPMA at concentrations from 0.78-200 microg/L (R = 0.9993). The method detection limit (MDL) for SPMA was 0.23 microg/L. The MDL of ttMA could not be determined accurately because of unavailability of an appropriate blank urine matrix, but was estimated to be lower than 7.43 microg/L. Without tedious manual sample cleanup procedures the analytical system is fully automated and is therefore useful for high-throughput simultaneous determination of urinary ttMA and SPMA. The sample throughput is roughly 100 samples per day. With the selectivity and the sensitivity provided by MS/MS detection, the analytical system can be used for large-scale monitoring of environmental or occupational exposure of humans to benzene.

Development and validation of an isotope-dilution electrospray ionization tandem mass spectrometry method with an on-line sample clean-up device for the quantitative analysis of the benzene exposure biomarker S-phenylmercapturic acid in human urine.

An isotope-dilution electrospray ionization tandem mass spectrometry (ESI-MS/MS) method with an on-line sample clean-up device, for the quantitative analysis of human urine for the benzene exposure biomarker S-phenylmercapturic acid (SPMA), was developed and validated. The sample clean-up system was constructed from an autosampler, a reversed-phase C18 trap cartridge, a two-position switching valve, and controlling computer software and hardware. The sample clean-up system was interfaced via 1/20 splitting to the ESI source of a triple-quadrupole mass spectrometer using negative ion mode and multiple reaction monitoring for SPMA and the isotope-labeled internal standard. A strategy was adopted to acquire pooled blank urine matrix and quality control samples spiked with standards. Validated procedures and data on method specificity, detection limits, standard curves, precision and recovery, sample storage stability, and inter-laboratory comparison are presented. The analytical system was fully automated. No tedious manual sample clean-up procedures are required. With the selectivity and the sensitivity provided by ESI-MS/MS detection, the analytical system can be used for high-throughput and accurate determination of SPMA levels in human urine samples, as a biomarker for environmental as well as occupational benzene exposure.

An online automatic sample cleanup system for the quantitative detection of the benzene exposure biomarker S-phenylmercapturic acid in human urine by electrospray ionization tandem mass spectrometry.

An online automatic sample cleanup system was developed for use with electrospray ionization tandem mass spectrometry (ESI-MS-MS) for the quantitative detection of the benzene exposure biomarker S-phenylmercapturic acid (S-PMA) in human urine. The sample clean-up system was constructed with an autosampling device, a reversed-phase C18 trap cartridge, a two-position switching valve, and controlling computer software and hardware. The sample cleanup system was interfaced directly with the ESI source of a triple-stage-quadrupole MS using multiple reaction monitoring of negative product ions derived from S-PMA and the internal standard as the detection mode. The calibration curve was linear using human urine spiked at concentrations from 0.23 to 100 mg/L S-PMA (R2 = 0.997). The detection limit of the analytical system for neat S-PMA standard solution was 0.04 microg/L, whereas the detection limit was estimated to be lower than 0.35 microg/L for a urine matrix containing trace amounts of S-PMA. Without tedious manual sample cleanup procedures, the analytical system is fully automatic and therefore useful for high-throughput urinary S-PMA determination. With the selectivity and the sensitivity provided by MS-MS detection, the analytical system can be used for high-throughput and accurate determination of S-PMA levels in human urinary samples as a biomarker for benzene exposure.