Extracted Ion Chromatograms Research Articles

Gcxgclab: An R Package for Two-Dimensional Gas Chromatography Preprocessing and Analysis.

Comprehensive two-dimensional gas chromatography (GC×GC) is an established technique capable of chromatographically separating thousands of analytes in complex matrices. When coupled with highly sensitive detectors such as a high-resolution mass spectrometer, these instruments produce large multidimensional data sets. A prevailing challenge for GC×GC users is efficient data handling and analysis. Although commercial software packages exist for GC×GC data analysis, these platforms are typically optimized for low-throughput qualitative data interpretation utilizing desktop computer systems. Additionally, commercial GC×GC data processing packages offer little flexibility to explore custom or novel data processing concepts. In this work, an open-source R package, called "gcxgclab", was developed as an alternative data processing package for GC×GC users and offers data preprocessing and analysis functions including baseline correction, smoothing, phase shift, peak detection, peak alignment, extracted ion chromatogram, mass spectra extraction, mass defect analysis, and targeted and nontargeted analysis. This package was designed to be customizable and allows for batch data processing on desktops or high-performance computing systems to increase the throughput. gcxgclab is available for free on the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/gcxgclab/index.html.

Gábor Transform-Based Antibody Quantitation in Serum: An Interlaboratory Liquid Chromatography/High-Resolution Mass Spectrometry Investigation.

Therapeutic monoclonal antibodies (t-mAbs) are crucial for treating various conditions, including cancers and autoimmune disorders. Accurate quantitation and pharmacokinetic monitoring of t-mAbs in serum are essential, but current methods like ligand binding assays (LBAs) and bottom-up peptide liquid chromatography-tandem mass spectrometry (LC-MS/MS) can lack the sensitivity and specificity needed to meet clinical demands. Emerging techniques using high-resolution mass spectrometry (HRMS) in top-down and middle-up approaches offer improved ability to accurately quantify mAb proteoforms apart from degradation products by keeping the sample proteins intact or minimizing digestion. This study describes the first use of Gábor transform (GT)-based iFAMS Quant+ software to quantify a t-mAb (vedolizumab) from ∼400 samples using an Agilent 6545XT AdvanceBio Q-TOF at the University of Oregon. These results are compared to a previously validated laboratory-developed test (LDT) from Mayo Clinic utilizing a Thermo Q Exactive Plus Orbitrap. The Mayo method used conventional extracted ion chromatograms (XICs) of select charge states for quantitation, while the iFAMS Quant+ method utilized GT-based charge state deconvolution, background subtraction, and signal integration. Calibration and quality control (QC) analyses and Passing-Bablok regression of 351 subject samples demonstrated excellent agreement between the two methods. The iFAMS Quant+ workflow exhibited unique advantages for characterizing interferents and analyte signal anomalies due to its deconvolution-based approach.

Metabolic profiling of triptophenolide in rat plasma, urine, bile and faeces after intragastric administration

Triptophenolide, a major diterpenoid extracted from Tripterygium wilfordii Hook. f., has been reported to possess significant anti-tumour, anti-androgen and anti-inflammatory activities. However, the metabolic fate of triptophenolide remains unknown. Therefore, this study focused on the metabolic profiling of triptophenolide in rat plasma, urine, bile and faeces following intragastric administration. An ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry with combination of extracted ion chromatogram strategy based on 71 typical metabolic reactions was established to comprehensively profile the metabolites of triptophenolide. This strategy allowed for the identification of 17 metabolites from the biosamples. Reduction, oxidation, glucuronide conjugation, and hydroxylation were considered as its main metabolic pathways in vivo. The present study will be greatly helpful for the further pharmacological studies on triptophenolide and would provide valuable information for its clinical application.

An Efficient Integrated Strategy for Comprehensive Metabolite Profiling of Sakurasosaponin from Aegiceras corniculatum in Rats.

Sakurasosaponin, a primary bioactive saponin from Aegiceras corniculatum, shows potential as an anti-cancer agent. However, there is a lack of information on its in vivo metabolism. This study aims to profile the in vivo metabolites of sakurasosaponin in rat feces, urine, and plasma after oral administration. An efficient strategy using ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry was developed, which combined metabolic prediction, multiple mass defects filtering, and highresolution extracted ion chromatograms for rapid and systematic analysis. Firstly, a theoretical list of metabolites for sakurasosaponin was developed. This was done by considering the metabolic pathways of saponins. Next, the multiple mass defects filtering method was employed to identify potential metabolites in feces and urine, using the unique metabolites of sakurasosaponin as multiple mass defects filtering templates. Subsequently, a high-resolution extracted ion chromatogram was used to quickly determine the metabolites in rat plasma post-identification in feces and urine. Lastly, the analysis of accurate mass, typical neutral loss, and diagnostic ion of the candidate metabolites was carried out to confirm their structural elucidation, and metabolic pathways of sakurasosaponin in vivo were also proposed. In total, 30 metabolites were provisionally identified in feces, urine, and plasma. Analysis of metabolic pathways revealed isomerization, deglycosylation, oxidation, hydroxylation, sulfate conjugation, glucuronide conjugation, and other related reactions as the primary biotransformation reactions of sakurasosaponin in vivo. The findings demonstrate that the designed research strategy effectively minimizes matrix interference, prevents the omission of low-concentration metabolites, and serves as a foundation for the discovery of active metabolites of sakurasosaponin.

On the utility of the extracted ion chromatograms for assigning the conjugation sites and side reactions in bioconjugates synthesized by the maleimide-thiol chemistry

Maleimide-thiol chemistry is widely used in the synthesis of protein–protein conjugate vaccines. In this reaction, thiol and maleimide groups, either in the carrier protein or in the antigen molecules, are linked via a thiosuccinimide linker. The assignment of the conjugation sites is key and is usually done by LC-MS/MS analysis of the conjugate proteolytic digestion, resulting in a very complex mixture of linear peptides and cross-linked peptide pairs. During proteolysis, the thiosuccinimide linker is converted to its hydrolyzed and transcyclized forms. The set of MS/MS spectra assigned to cross-linked peptide pairs contains valuable information about the conjugation sites that must be validated using objective criteria for more reliable assignment. The extracted ion chromatograms (XICs) have not previously been considered for these validation purposes. In the LC-MS/MS analysis, linear peptides eluted with a single-peak XIC pattern, while the cross-linked peptide pairs with a transcyclized linker (consisting of a mixture of diastereomers) eluted with a two-peak XIC pattern in 68–100 % of cases. Cross-linked peptide pairs with the hydrolyzed linker were detected with a multi-peak XIC pattern consisting of two, three and four peaks in 77 %, 15 % and 8 % of cases, respectively. The four-peak XIC pattern corresponds to cross-linked peptide pairs with two positional isomers of the hydrolyzed linker containing a mixture of diastereomers. Tandem digestions increased the analytical value of the XICs by converting the large and hydrophobic cross-linked peptide pairs, that show a single-peak XIC pattern, to more hydrophilic species eluting in multi-peak XIC patterns. XICs are easily obtained in any LC-MS/MS analysis, contain valuable information about conjugation sites and side reaction detection, and are worthy of routine inclusion in bioconjugate characterization.

Gábor Transform-Based Signal Isolation, Rapid Deconvolution, and Quantitation of Intact Protein Ions with Mass Spectrometry.

High-resolution mass spectrometry (HRMS) is a powerful technique for the characterization and quantitation of complex biological mixtures, with several applications including clinical monitoring and tissue imaging. However, these medical and pharmaceutical applications are pushing the analytical limits of modern HRMS techniques, requiring either further development in instrumentation or data processing methods. Here, we demonstrate new developments in the interactive Fourier-transform analysis for mass spectrometry (iFAMS) software including the first application of Gábor transform (GT) to protein quantitation. Newly added automation tools detect signals from minimal user input and apply thresholds for signal selection, deconvolution, and baseline correction to improve the objectivity and reproducibility of deconvolution. Additional tools were added to improve the deconvolution of highly complex or congested mass spectra and are demonstrated here for the first time. The "Gábor Slicer" enables the user to explore trends in the Gábor spectrogram with instantaneous ion mass estimates accurate to 10 Da. The charge adjuster allows for easy visual confirmation of accurate charge state assignments and quick adjustment if necessary. Deconvolution refinement utilizes a second GT of isotopically resolved data to remove common deconvolution artifacts. To assess the quality of deconvolution from iFAMS, several comparisons are made to deconvolutions using other algorithms such as UniDec and an implementation of MaxEnt in Agilent MassHunter BioConfirm. Lastly, the newly added batch processing and quantitation capabilities of iFAMS are demonstrated and compared to a common extracted ion chromatogram approach.

QPeaks: A Linear Regression-Based Asymmetric Peak Model for Parameter-Free Automatized Detection and Characterization of Chromatographic Peaks in Non-Target Screening Data.

We present qPeaks (quality peaks), a novel, user-parameter-free algorithm for peak detection and peak characterization applicable to chromatographic data. The algorithm is based on a linearizable regression model that analyzes asymmetric peaks and estimates the specific uncertainties associated with the peak regression parameters. The uncertainties of the parameters are used to derive a data quality score DQSpeak, rendering low reliability results more transparent during processing and allowing for the prioritization of generated features. High DQSpeak chromatographic peaks have a lower chance of being classified as false-positive and show higher repeatability over multiple measurements. The high efficiency of the algorithm makes it particularly useful for application within processing routines of nontarget screening through chromatography coupled with high-resolution mass spectrometry. qPeaks is integrated into the qAlgorithms nontarget screening processing toolbox and appends a parameter-free chromatographic peak detection and characterization step to it. With qAlgorithms, now high-resolution mass spectra are centroided using the qCentroids algorithms, centroids are clustered to form extracted ion chromatograms (EICs) with the qBinning algorithm, and chromatographic peaks are found on the generated EICs with qPeaks. However, all tools from qAlgorithms can also be used independently.

An XIC-Centric Strategy for Improved Identification and Quantification in Proteomic Data Analyses.

Reproducibility is a "proteomic dream" yet to be fully realized. A typical data analysis workflow utilizing extracted ion chromatograms (XICs) often treats the information path from identification to quantification as a one-way street. Here, we propose an XIC-centric approach in which the data flow is bidirectional: identifications are used to derive XICs whose information is in turn applied to validate the identifications. In this study, we employed liquid chromatography-mass spectrometry data from glycoprotein and human hair samples to illustrate the XIC-centric concept. At the core of this approach was XIC-based monoisotope repicking. Taking advantage of the intensity information for all detected isotopes across the whole range of an XIC peak significantly improved the accuracy and uncovered misidentifications originating from monoisotope assignment mistakes. It could also rescue non-top-ranked glycopeptide hits. Identification of glycopeptides is particularly susceptible to precursor mass errors for their low abundances, large masses, and glycans differing by 1 or 2 Da easily confused as isotopes. In addition, the XIC-centric strategy significantly reduced the problem of one XIC peak associated with multiple unique identifications, a source of quantitative irreproducibility. Taken together, the proposed approach can lead to improved identification and quantification accuracy and, ultimately, enhanced reproducibility in proteomic data analyses.

A LC-MS-based serum pharmacochemistry approach to reveal the compatibility features of mutual promotion/assistance herb pairs in Xijiao Dihuang decoction

Xijiao Dihuang decoction (XDT), a famous formula, was usually used to improve the prognosis of patients with blood-heat and blood-stasis syndrome-related diseases. There were some mutual promotion and mutual assistance herb pairs in XDT. However, the exact functions of these herb pairs in the compatibility of XDT were not elucidated due to the lack of appropriate methodologies. Based on the theory of serum pharmacochemistry, a systematic method was established for the qualitative and quantitative analysis of characteristic components in the extracts and drug-containing plasma samples of XDT and its relational mutual promotion/assistance herb pairs. For qualitative analysis, 85 characteristic components were identified using the liquid chromatography with triple time-of-flight mass/mass spectrometry (LC-Triple QTOF-MS/MS) based on the mass defect filtering, product ion filtering, neutral loss filtering and isotope pattern filtering techniques. For quantitative detection, a relative quantitation assay using an extract ion chromatogram (EIC) of the full scan MS experiment was validated and employed to assess the quantity of the 85 identified compounds in the test samples of single herb, herb pairs and XDT. The results of multivariate statistical analyses indicated that both the assistant and guide herbs could improve the solubilization of active compounds from the sovereign and minister herbs in XDT in vitro, might change the trans-membrane transportation, and regulate metabolism in vivo. The methods used in present study might be also valuable for the investigation of multiple components from other classic TCM formulas for the purpose of compatibility feature study.

Application of advanced high resolution mass spectrometric techniques for the analysis of losartan potassium regarding known and unknown impurities

Recalls of medicinal products can cause supply bottlenecks. This is often due to the findings of unexpected impurities that pose a health risk to patients. A recent example is losartan potassium which was contaminated with azido-impurities. The choice of the analytical method determines which substances can be detected and thus controlled. In this study a combination of an untargeted screening approach for impurities and a targeted evaluation of high-resolution mass spectrometry data was applied to search for impurities not described so far, leaving out a precise quantification. Six losartan potassium samples were studied regarding known and unknown impurities and hence highlight the applicability and capability of the approach. For separation a Zorbax RR StableBond C18 column (3.0 ×100 mm, particle size of 3.5 µm, pore size of 80 Å), a gradient elution and an electrospray ionization in positive and negative mode for mass spectrometric detection was used. An information-dependent acquisition method was applied for the measurement of losartan potassium samples. The untargeted data evaluation using general unknown comparative screening revealed the presence of N-methyl-2-pyrrolidone (NMP) and another impurity from synthesis. The identity of NMP was corroborated by a spiking experiment and the amount was estimated by means of standard addition. A targeted data evaluation by generating extracted ion chromatograms resulted in finding of four additional impurities. Combined approaches like this are needed to detect and respond to changes in the quality of drugs precociously.

Absolute Quantification of Human Serum Albumin Isoforms by Internal Calibration Based on a Top-Down LC-MS Approach.

Well-characterized biomarkers using reliable quantitative methods are essential for the management of various pathologies such as diabetes, kidney, and liver diseases. Human serum albumin (HSA) isoforms are gaining interest as biomarkers of advanced liver pathologies. In view of the structural alterations observed for HSA, insights into its isoforms are required to establish them as reliable biomarkers. Therefore, a robust absolute quantification method seems necessary. In this study, we developed and validated a far more advanced top-down liquid chromatography-mass spectrometry (LC-MS) method for the absolute quantification of HSA isoforms, using myoglobin (Mb) as an internal standard for quantification and for mass recalibration. Two different quantification approaches were investigated based on peak integration from the deconvoluted spectrum and extracted ion chromatogram (XIC). The protein mixture human serum albumin/myoglobin eluted in well-shaped separated peaks. Mb allowed a systematic mass recalibration for every sample, resulting in extremely low mass deviations compared to conventional deconvolution-based methods. In total, eight HSA isoforms of interest were quantified. Specific-isoform calibration curves showing good linearity were obtained by using the deconvoluted peaks. Noticeably, the HSA ionization behavior appeared to be isoform-dependent, suggesting that the use of an enriched isoform solution as a calibration standard for absolute quantification studies of HSA isoforms is necessary. Good repeatability, reproducibility, and accuracy were observed, with better sensitivity for samples with low albumin concentrations compared to routine biochemical assays. With a relatively simple workflow, the application of this method for absolute quantification shows great potential, especially for HSA isoform studies in a clinical context, where a high-throughput method and sensitivity are needed.

OPEs-ID: A software for non-targeted screening of organophosphate esters based on liquid chromatography-high-resolution mass spectrometry

Organophosphate esters (OPEs) are widely used as flame retardants and plasticizers, presenting a potential threat to the environment and human health. To date, no automatic software exists for the nontargeted screening of OPEs. In this study, OPEs-ID, a user-friendly software, was developed for the identification of OPEs using liquid chromatography-high-resolution mass spectrometry. The main workflow of OPEs-ID included fragments-dependent precursor ion screening, elemental composition determination, extracted ion chromatograms (EIC) comparison, and molecular structure identification via MetFrag strategy. A mixture of 17 OPE standards was identified with an identification rate of 100% by OPEs-ID. OPEs-ID demonstrated a rate of 94.1% for correctly ranking within the top 1 candidate in a local database (41.2% in PubChem) for the 17 OPE standards, which remarkably improved the identification when compared to conventional in silico fragmentation algorithms. Using a pooled airborne fine particle sample (PM2.5), OPEs-ID could automatically retrieve 22 valid molecules with structure candidates. The detection frequencies of 9 newly identified OPEs were between 13% and 100% in the 32 PM2.5 samples. Their semi-quantification concentrations were comparable to those of some traditional OPEs. Overall, OPEs-ID offers a powerful tool to significantly enrich our understanding of the OPEs present in the environment.

Combination of in silico prediction and convolutional neural network framework for targeted screening of metabolites from LC-HRMS fingerprints: A case study of “Pericarpium Citri Reticulatae - FructusAurantii”

In this study, a novel approach is introduced, merging in silico prediction with a Convolutional Neural Network (CNN) framework for the targeted screening of in vivo metabolites in Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) fingerprints. Initially, three predictive tools, supplemented by literature, identify potential metabolites for target prototypes derived from Traditional Chinese Medicines (TCMs) or functional foods. Subsequently, a CNN is developed to minimize false positives from CWT-based peak detection. The Extracted Ion Chromatogram (EIC) peaks are then annotated using MS-FINDER across three levels of confidence. This methodology focuses on analyzing the metabolic fingerprints of rats administered with "Pericarpium Citri Reticulatae - Fructus Aurantii" (PCR-FA). Consequently, 384 peaks in positive mode and 282 in negative mode were identified as true peaks of probable metabolites. By contrasting these with “blank serum” data, EIC peaks of adequate intensity were chosen for MS/MS fragment analysis. Ultimately, 14 prototypes (including flavonoids and lactones) and 40 metabolites were precisely linked to their corresponding EIC peaks, thereby providing deeper insight into the pharmacological mechanism. This innovative strategy markedly enhances the chemical coverage in the targeted screening of LC-HRMS metabolic fingerprints.

Quality evaluation of Angelica Sinensis Radix dispensing granules by integrating microvascular activity and chemical analysis

Ethnopharmacological relevanceAs a new form of crude slices of traditional Chinese medicine (TCM), traditional Chinese medicine dispensing granules (TCMDGs) have been used for clinical formula. It is necessary to evaluate whether the chemical composition and biological activity are consistent among the different batches. Angelica Sinensis Radix (ASR), the root of Angelica sinensis (Oliv.) Diels, is one of the most frequently used medicinal materials in gynecology, senile and cardiovascular diseases. In this paper, the quality of TCMDGs is examined taking the Angelica Sinensis Radix dispensing granules (ASRDGs) as a typical case. Aim of the studyIn this study, integrating bioequivalence and chemical analysis was used to evaluate the quality of dispensing granules taking ASRDGs as a typical case. Materials and methodsAccording to the clinical efficacy of ASR, the intestinal absorption liquid of ASRDGs (IAL-ASRDGs) in 15 batches prepared by the everted gut sac (EGS) method was used to evaluate its effects of vasodilatation on isolated vascular rings. Then, the chemical profiling analysis of IAL-ASRDGs from the 15 batches was carried out by ultra-high performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS). The components in IAL-ASRDGs were identified using mass spectrometry data and the obtained reference standards. Pearson correlation analysis was further performed for the selection of quality control markers based on the extracted ion chromatograms of the identified compounds and vasodilatory activities of different batches of IAL-ASRDGs. Moreover, the selected chemical components in ASRDGs were further verified by vasodilatory activities and quantitatively analyzed by ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-QQQ-MS). ResultsThe IAL-ASRDGs showed favorable vasodilatory activities. There were significant differences among the 15 batches. The ranges of maximum vasodilation rate (%) and EC50 were 69.33 ± 7.16 to 19.52 ± 5.05 and 0.07–25.58 g raw materials/mL, respectively. A total of 46 compounds in IAL-ASRDGs were identified based on accurate mass measurements, fragmentation behavior and the reference standards. Among them, 8 compounds including butylidenephthalide, butylphthalide and senkyunolide A showed positive correlation with vasodilatory effect of IAL-ASRDGs. The 8 compounds were further verified, showing obvious vasodilatory activities. The content of the 8 compounds also showed some differences in 15 batches of ASRDGs. Among them, the content of ferulic acid, senkyunolide I and senkyunolide H varied the most in different batches of ASRDGs. By Pearson correlation analysis, the total content of senkyunolides (senkyunolide A, senkyunolide I and senkyunolide H) in ASRDGs was found to reflect the vasodilatory activity of ASRDGs mostly. ConclusionThis study provides new strategies for the quality assessment by bioequivalence and explore the chemical quality control markers for ASRDGs.

Metabolic profiling of Qi-Yu-San-Long decoction in rat feces by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry combined with a post-targeted screening strategy.

Research into traditional Chinese medicine metabolism in feces is one of the key avenues to understanding the fate of traditional Chinese medicines in vivo. In this study, we used ultraperformance liquid chromatography-quadrupole time-of-flight MS in combination with a post-targeted screening strategy to identify the prototype components and metabolites in rat feces after oral administration. Based on our group's previous research, the component database of Qi-Yu-San-Long decoction (QYSLD) was established. Prototype components were screened from the fecal samples based on summarized chromatographic and MS behaviors. According to the chemical structure characteristics of related compounds, the possible metabolic pathways were inferred, and the metabolites related to QYSLD were predicted. We extracted ion chromatograms by predicting the m/z values of metabolite excimer ions and identified related metabolites based on their retention time and fragmentation behavior. A total of 93 QYSLD-related xenobiotics were confirmed or tentatively identified in rat fecal samples, and the results indicated that the main metabolic pathways of QYSLD were hydrolysis, deglycosylation, oxidation, reduction, decarboxylation, methylation and acetylation. This study presents a rapid method for identifying the prototype components and metabolites, and offers valuable insights into the biotransformation profiling of QYSLD in rat feces.

Degradation of polysorbate investigated by a high-performance liquid chromatography multi-detector system with charged aerosol and mass detection

Polysorbate 80 is widely used as a formulation component in biopharmaceutical drug products. Recent studies have shown that polysorbate 80 is readily degraded either through direct or indirect means. The degradation of polysorbate 80 causes a concern for the long-term stability of biopharmaceutical drug product, as the breakdown products of polysorbate 80 have been shown to cause adverse effects, such as formation of sub-visible and visible particles and mAb aggregation. Understanding the path and extent of degradation is of a paramount importance for the formulator during formulation development. A multi-detector HPLC system using charged aerosol and mass detection was developed and optimized for the characterization of polysorbate 80 standards. The system included a post-column make-up flow, i.e. an inverse gradient, that enabled constant eluent composition at the detectors. The inverse gradient eliminated the main source of variability for the charged aerosol detector response, thereby enabling the calculation of the mass balance between polysorbate components with different degrees of esterification. Extracted ion chromatograms of the mass detector combined with their respective retention times were used to qualitatively characterize the polysorbate samples down to the individual components. The system was applied to study the degradation of several polysorbate standards which occurred by enzymatic digestion or long-term storage. The system provided detailed information on the mechanism of degradation without the need for additional orthogonal analytical techniques.

QBinning: Data Quality-Based Algorithm for Automized Ion Chromatogram Extraction from High-Resolution Mass Spectrometry.

Due to the complexity and volume of data generated through non-target screening (NTS) using chromatographic couplings with high-resolution mass spectrometry, automized processing routines are necessary. The processing routines usually consist of many individual steps that are user-parameter-dependent and, thus, require labor-intensive optimization. Additionally, the effect of variations in raw data quality on the processing results is unclear and not fully understood. Within this work, we present qBinning, a novel algorithm for constructing extracted ion chromatograms (EICs) based on statistical principles and, thus, without the need to set user parameters. Furthermore, we give the user feedback on the specific qualities of the generated EICs using a scoring system (DQSbin). The DQSbin measures reliability as it correlates with the probability of correct classification of masses into EICs and the degree of overlap between different EIC construction algorithms. This work is a big step forward in understanding the behavior of NTS data and increasing the overall transparency in the results of NTS.

LC-MS fingerprint and multi-indicator components analysis of classical formula Gualou Xiebai Banxia Decoction

This study developed an optimal pre-processing technique for the reference substance of the classic formula Gualou Xiebai Banxia Decoction(GXBD) and established a comprehensive quality control method for GXBD reference substance to provide a reference for its overall quality evaluation. The authors prepared 15 batches of GXBD samples and innovatively used the extracted ion chromatogram under the base peak chromatogram mode to establish a liquid chromatography-mass spectrometry(LC-MS) fingerprint, identify characteristic peaks, and perform quantitative analysis of indicator components. The yield of the 15 batches of GXBD samples ranged from 50.28% to 76.20%. In the positive ion mode, 12 common characteristic peaks were detected in the LC-MS fingerprint, and the structures of five common peaks were identified by comparison with reference standards. The similarity between the fingerprint profiles of different batches of samples and the reference fingerprint profile ranged from 0.920 to 0.984. Finally, liquid chromatography-triple quadrupole mass spectrometry(LC-QQQ/MS) in multiple reaction monitoring(MRM) mode was used to determine the content of eight indicator components in GXBD, including loliolide, chrysoeriol, rutin, cucurbitacin D, macrostemonoside Ⅰ, 25S-timosaponin B Ⅱ, 25R-timosaponin B Ⅱ, and peptide proline-tryptophan-valine-proline-glycine(PWVPG). The method established in this study can reduce matrix interference in the compound, and it has good accuracy, stability, and practical value. It effectively reflects the quality attributes of GXBD samples and can be used for the comprehensive quality control of GXBD.

Highly automatic and universal approach for pure ion chromatogram construction from liquid chromatography-mass spectrometry data using deep learning

Feature extraction is the most fundamental step when analyzing liquid chromatography-mass spectrometry (LC-MS) datasets. However, traditional methods require optimal parameter selections and re-optimization for different datasets, thus hindering efficient and objective large-scale data analysis. Pure ion chromatogram (PIC) is widely used because it avoids the peak splitting problem of the extracted ion chromatogram (EIC) and regions of interest (ROIs). Here, we developed a deep learning-based pure ion chromatogram method (DeepPIC) to find PICs using a customized U-Net from centroid mode data of LC-MS directly and automatically. A model was trained, validated, and tested on the Arabidopsis thaliana dataset with 200 input-label pairs. DeepPIC was integrated into KPIC2. The combination enables the entire processing pipeline from raw data to discriminant models for metabolomics datasets. The KPIC2 with DeepPIC was compared against other competing methods (XCMS, FeatureFinderMetabo, and peakonly) on the MM48, simulated MM48, and quantitative datasets. These comparisons showed that DeepPIC outperforms XCMS, FeatureFinderMetabo, and peakonly in recall rates and correlation with sample concentrations. Five datasets of different instruments and samples were used to evaluate the quality of PICs and the universal applicability of DeepPIC, and 95.12% of the found PICs could precisely match their manually labeled PICs. Therefore, KPIC2+DeepPIC is an automatic, practical, and off-the-shelf method to extract features from raw data directly, exceeding traditional methods with careful parameter tuning. It is publicly available at https://github.com/yuxuanliao/DeepPIC.

Hybrid liquid chromatography high resolution and accuracy mass spectrometry approach for quantification of antibody-drug conjugates at the intact protein level in biological samples

Preclinical in vivo and in vitro characterization of Antibody-Drug Conjugates (ADCs) involves the development of several bioanalytical methods to address many drug exposure questions. The current pharma industry approach requires at least three different assays that must be run, i.e., total antibody (mAb), conjugated payload or conjugated mAb, and free payload assays. Herein we present analytical performances of a quantitative hybrid Ligand Binding/Liquid Chromatography High Resolution and Accuracy Mass Spectrometry (LB/LCHRAM) method that can condense much of the necessary bioanalytical information in one method. The method includes an immuno-capture step, and it detects whole ADC molecules. It was applied to plasma mouse samples and showed reliable bioanalytical performance according to full method validation standards. Quantitation using extracted ion chromatograms and deconvoluted mass peaks was evaluated. The limit of quantitation resulted in 0.5ng of protein on column with a linear dynamic range spanning from 0.5 to 10μg/mL. Moreover, lower drug-to-antibody ratio (DAR) ADC species can be simultaneously detected, also enabling qualitative characterization of in vivo ADC conjugation.