Data-independent Acquisition Mode Research Articles

Enhancing coverage of annotated compounds in traditional Chinese medicine formulas: Integrating MSE and Fast-DDA molecular network with AntDAS—Case study of Xiao Jian Zhong Tang

The chemical characterisation of traditional Chinese medicine formulas (TCMFs) using mass spectrometry poses notable challenges owing to their complex and diverse chemical compositions. While acquisition modes such as data-dependent acquisition (DDA) and data-independent acquisition (DIA) offer new insights, DDA's tendency to overlook low-abundance ions and DIA's complicated data processing, particularly in matching MS1 and MS2 information, limit the effective annotation of valuable compounds in TCMFs. Herein, we present a new integrated strategy to enhance the coverage of annotated compounds in TCMFs, using Xiao Jian Zhong Tang (XJZ) as a case study. First, we characterised the components of XJZ through UNIFI software in Fast-DDA and DIA modes. We then summarised the diagnostic ions and substituent information of the identified compounds based on the Fast-DDA data, integrating molecular networks and AntDAS to predict unknown components and uncover potential components. Ultimately, we characterised a total of 785 components in XJZ, including 43 that were unique to XJZ when compared to the individual herbs involved. The presence of these new components may result from the recombination of substituents during compatibility. In conclusion, this new integrated strategy facilitates more in-depth characterisation of components in TCMFs, providing a new direction for exploring the compatibility principles among TCMFs.

Integration WGCNA with LC-MS data for evaluating the processing status and transformation rules of Ligustri Lucidi Fructus: A novel strategy for evaluating the processing technology of traditional Chinese medicines

Ligustri Lucidi Fructus (LLF) is a traditional Chinese medicine (TCM) to treat hepatopathy and osteopathy. Wine-processed LLF (WLLF) was much more widely used than raw LLF (RLLF) in clinical practice, however, there is no consensus on processing time. To investigate the processing status of WLLF and transformation rules during processing, a UHPLC-Q-Orbitrap-MS method combined with data-independent acquisition (DIA) mode was firstly established and 227 compounds were identified or tentatively identified. Subsequently, a novel strategy using integration weighted gene co-expression network analysis (WGCNA) with LC-MS data was proposed. A total of 73 differential metabolites were screened out between RLLF and WLLF (wine steaming for 18 h). Meanwhile, the concentration of 11 differential compounds for WLLF was quantified. Finally, correlations between compounds were analyzed by WGCNA and the top five compounds negatively correlated with salidroside were validated, revealing that G13, specnuezhenide, oleuropein, acteoside, and neonuzhenide could be transformed into salidroside and its analogues during processing, respectively. The results indicated that our proposed strategy could be effectively employed to evaluate the processing status of TCMs.

Retinal Proteome Profiling of Inherited Retinal Degeneration Across Three Different Mouse Models Suggests Common Drug Targets in Retinitis Pigmentosa

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with invivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

B-146 Unlocking the potential of large-cohort proteomics studies with the Orbitrap Astral mass platform

Abstract Background Large-cohort proteomics analysis using mass spectrometry is a powerful approach to discover and validate new biomarkers. In combination with clinical data and computational analysis, large-cohort proteomics study brings opportunities in improving early diagnosis, refining patient stratification, and predicting/monitoring treatment response. Yet, to achieve meaningful biological insights in large-cohort studies, robust, reproducible, and comprehensive proteome profiling in a high-throughput manner still remains challenging. Here, we use a high-resolution accurate mass (HRAM) Oribtrap Astral platform to enable high-quality and robust protein quantification across thousands of LC-MS/MS analyses. With a throughput of 100 samples/day, we can reproducibly profile ∼9000 proteins from human cell line and ∼800 proteins from undepleted plasma across multiple instruments and more than 10 consecutive days in a 24/7 operation mode. Methods Experiments were performed on multiple Orbitrap Astral mass spectrometers with and without FAIMS Pro interface. Chromatographic separations were performed using a trap/elute method on Vanquish Neo system at a 11-minute gradient and a flow rate of 1ul/min, resulting in a throughput of 100 samples/day. Undepleted plasma digest was analyzed in a 24/7 mode for > 1000 injections on each LC-MS/MS setup. In addition, HeLa digest as quality control (QC) was analyzed every 12hours. The Oribtrap Astral platform was operated in data-independent acquisition (DIA) mode using a full scan with m/z 380-980, and DIA MS/MS scans with an isolation window of 2Th. Resulting DIA raw files were automatically transferred and processed using Chimerys in a beta version of Proteome Discoverer software. Results Multiple LC-MS/MS systems were operated in DIA mode either with or without FAIMS Pro device in a 24/7 operation mode at a throughput of 100SPD. Undepleted plasma digest was analyzed with >1000 injections on each LC-MS/MS setup. To monitor the baseline performance, HeLa digest served as QC were analyzed periodically every 12 hours with 3 technical replicates each time. To effectively manage and analyze these thousands of data files generated, we developed an automated data transfer and analysis pipeline. Automatically, the resulting DIA raw data files were immediately transferred to a server, then processed by state-of-the-art intelligent search algorithm Chimerys. Benefiting from the ultra-high scan speed of up to 200Hz on the Orbitrap Astral mass spectrometer, a much narrower isolation window width of 2Th was applied in the DIA method, comparing to 10-20Th on the classic DIA method. As a result, ∼9000 proteins from HeLa digest and ∼800 proteins from undepleted plasma digest were identified within only a 11-minutes gradient, respectively. More than 80% of the plasma proteins were reproducibly identified and quantified from all the runs on each LC-MS/MS setup, indicating a great reproducibility from run-to-run longitudinally. Stable and robust peptide quantitation was observed by extracting peptides with high, medium, and low abundant across the runs. Importantly, QC showed no performance degradation throughout the entire study, indicating high robustness of the entire LC-MS/MS setup. Conclusions Orbitrap Astral mass platform can comprehensively analyze the proteome of >1000s of sample robustly and reproducibly in a high-throughput manner, addressing the needs in large-cohort studies.

Pharmaceutical metabolite identification in lettuce (Lactuca sativa) and earthworms (Eisenia fetida) using liquid chromatography coupled to high-resolution mass spectrometry and in silico spectral library.

Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and anin silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

Exploring methandienone metabolites generated via homogenized camel liver: Advancements for anti-doping applications through High Resolution-Liquid Chromatography Mass Spectrometry analysis.

Anabolic steroids, also known as anabolic-androgenic steroids (AAS), encompass steroidal androgens such as testosterone, as well as synthetic counterparts with similar structures and effects. The misuse of AAS has increased over the years, leading to ethical and welfare concerns in sports. The World Anti-Doping Agency (WADA) and the International Federation for Equestrian Sports (FEI) have banned AAS in relevant sports. Methandienone is one of the most identified anabolic androgenic steroids in sports drug testing, Therefore, reliable detection methods are crucial for effective doping control and maintaining the integrity of the sports. This study explores the use of homogenized camel liver for detecting methandienone metabolites in camels. The biotransformation pathways of methandienone in homogenized camel liver tissues are analyzed using Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) to identify and characterize the phase I and phase II metabolites. Chromatographic separation was achieved using a Thermo-Hypersil C18 column. The study has identified 11 methandienone metabolites (M1-M11), this includes 10 phase I and one phase II metabolite. A glucuronic acid conjugate of methandienone was observed in this study, but no sulfonic acid conjugations were found. The metabolites and their possible chemical structures, along with their fragmentation patterns are confirmed using MSMS (MS2) experiments in data-independent acquisition (DIA) mode. These findings serve as a vital tool for the rapid detection of methandienone, combating its illicit use in camel racing. Comprehensive screenings covering both the parent drug and its metabolites are recommended to improve detection accuracy and ensure regulatory compliance in sports doping. Future research should explore methandienone's metabolite profile in administered camel samples.

Proteomic Analysis Identifies Dysregulated Proteins in Albuminuria: A South African Pilot Study.

Albuminuria may precede decreases in the glomerular filtration rate (GFR) and both tests are insensitive predictors of early stages of kidney disease. Our aim was to characterise the urinary proteome in black African individuals with albuminuria and well-preserved GFR from South Africa. This case-controlled study compared the urinary proteomes of 52 normoalbuminuric (urine albumin: creatinine ratio (uACR) < 3 mg/mmol) and 56 albuminuric (uACR ≥ 3 mg/mmol) adults of black African ethnicity. Urine proteins were precipitated, reduced, alkylated, digested, and analysed using an Evosep One LC (Evosep Biosystems, Odense, Denmark) coupled to a Sciex 5600 Triple-TOF (Sciex, Framingham, MA, USA) in data-independent acquisition mode. The data were searched on SpectronautTM 15. Differentially abundant proteins (DAPs) were filtered to include those with a ≥2.25-fold change and a false discovery rate ≤ 1%. Receiver-operating characteristic curves were used to assess the discriminating abilities of proteins of interest. Pathway analysis was performed using Enrichr software. As expected, the albuminuric group had higher uACR (7.9 vs. 0.55 mg/mmol, p < 0.001). The median eGFR (mL/min/1.73 m2) showed no difference between the groups (111 vs. 114, p = 0.707). We identified 80 DAPs in the albuminuria group compared to the normoalbuminuria group, of which 59 proteins were increased while 21 proteins were decreased in abundance. We found 12 urinary proteins with an AUC > 0.8 and a p < 0.001 in the multivariate analysis. Furthermore, an 80-protein model was developed that showed a high AUC ˃ 0.907 and a predictive accuracy of 91.3% between the two groups. Pathway analysis found that the DAPs were involved in insulin growth factor (IGF) functions, innate immunity, platelet degranulation, and extracellular matrix organization. In albuminuric individuals with a well-preserved eGFR, pathways involved in preventing the release and uptake of IGF by insulin growth factor binding protein were significantly enriched. These proteins are indicative of a homeostatic imbalance in a variety of cellular processes underlying renal dysfunction and are implicated in chronic kidney disease.

Capillary zone electrophoresis-tandem mass spectrometry for in-depth proteomics analysis via data-independent acquisition.

A capillary zone electrophoresis (CZE) system was coupled to an Orbitrap mass spectrometer operating in a data-independent acquisition (DIA) mode for in-depth proteomics analysis. The performance of this CZE-DIA-MS system was systemically evaluated and optimized under different operating conditions. The performance of the fully optimized CZE-DIA-MS system was subsequently compared to the one by using the same CZE-MS system operating in a data-dependent acquisition (DDA) mode. The experimental results show that the numbers of identified peptides and proteins acquired in the DIA mode are much higher than the ones acquired in the DDA mode, especially with the small sample loading amount. Specifically, the numbers of identified peptides and proteins acquired in the DIA mode are 1.8-fold and 2-fold higher than the ones acquired in the DDA mode by using 12.5 ng Hela digests. The proteins identified in the DIA mode also cover almost all the proteins identified in the DDA mode. In addition, a potential cancer biomarker protein, carbohydrate antigen 125, undetected in the DDA mode, can be easily identified in the DIA mode even with 12.5 ng Hela digests. The performance of the CZE-DIA-MS system for in-depth proteomics analysis with a limited sample amount has been fully demonstrated for the first time through this study.

An Inflection Point in High-Throughput Proteomics with Orbitrap Astral: Analysis of Biofluids, Cells, and Tissues.

This Technical Note presents a comprehensive proteomics workflow for the new combination of Orbitrap and Astral mass analyzers across biofluids, cells, and tissues. Central to our workflow is the integration of Adaptive Focused Acoustics (AFA) technology for cells and tissue lysis to ensure robust and reproducible sample preparation in a high-throughput manner. Furthermore, we automated the detergent-compatible single-pot, solid-phase-enhanced sample Preparation (SP3) method for protein digestion. The synergy of these advanced methodologies facilitates a robust and high-throughput approach for cell and tissue analysis, an important consideration in translational research. This work disseminates our platform workflow, analyzes the effectiveness, demonstrates the reproducibility of the results, and highlights the potential of these technologies in biomarker discovery and disease pathology. For cells and tissues (heart, liver, lung, and intestine) proteomics analysis by data-independent acquisition mode, identifications exceeding 10,000 proteins can be achieved with a 24 min active gradient. In 200 ng injections of HeLa digest across multiple gradients, an average of more than 80% of proteins have a CV less than 20%, and a 45 min run covers ∼90% of the expressed proteome. This complete workflow allows for large swaths of the proteome to be identified and is compatible with diverse sample types.

Screening and validation of therapeutic targets for chronic sinusitis with nasal polyps based on proteomics

Objective: To identify potential therapeutic targets of chronic sinusitis with nasal polyps (CRSwNP) through proteomics screening of and verify its effectiveness experimentally. Methods: The nasal tissue samples were collected from patients undergoing surgical treatment in the Department of Otorhinolaryngology, Head and Neck Surgery in Yuhuangding Hospital of Yantai from June 2010 to December 2021, including 69 patients with CRSwNP and 39 patients in the control group. Tissue samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-independent acquisition (DIA) mode to find differentially expressed proteins. Bioinformatics tools were employed to analyze the functions of differentially expressed proteins. The expression of hematopoietic cell kinase (HCK) in nasal tissues of patients with CRSwNP was further confirmed by qPCR and western blot. The mouse model of CRSwNP was established and treated with HCK inhibitor. The levels of inflammatory factors IgE, IL-4 and IL-5 in serum of CRSwNP mice, both treated and untreated with HCK inhibitors, were detected by enzyme-linked immunosorbent assay (ELISA) across different experimental groups. The experimental data were analyzed by Graphpad Prism 9 software. Results: DIA analysis identified 1 850 differential proteins, including 760 up-regulated proteins and 1 090 down-regulated proteins. Weighted correlation network analysis (WGCNA) correlation analysis of phenotypic data such as cell count and CT score with the results of genomics indemnified 575 proteins of MEBrown module which intersected with 35 kinases further screened from 1 850 differential proteins, yielding eight protein kinases: HCK, SYK, PDK2, FGR, PRKCB, ROR1, CAMK1 and GRK6. qPCR showed that the expression of HCK in CRSwNP was significantly higher than that in the control group (P<0.05). Further experiments in mice confirmed that the secretion of IgE, IL-4 and IL-5 in the serum of CRSwNP group was significantly higher than the control group (all P<0.05), indicating successful model establishment. The intervention of HCK significantly decreased the secretion of IgE, IL-4 and IL-5 in serum of mice (all P<0.05). Conclusion: The HCK inhibitor can reduce the inflammatory index of mice with CRSwNP, and HCK is a potential therapeutic target of CRSwNP.

LC-MS analysis of polar and highly polar organic pollutants in Barcelona urban groundwater using orthogonal LC separation modes.

Groundwater samples may contain thousands of organic pollutants from infiltration of surface water, sewer leakages, and to a minor extent from public water supply network losses. Polar (0 < log D < - 2.0) and very polar substances (log D < - 2.0) have been largely beyond the scope of applied analytical methodologies in environmental monitoring because of challenges related to their extraction from the sample and subsequent chromatographic separation. In this study, we developed an analytical workflow for 96 pollutants covering a broad polarity range, including pharmaceuticals, industrial chemicals, and artificial sweeteners, potentially seeping through the soil in urban areas. The Besos aquifer located at the Northern-eastern edge of the city of Barcelona was chosen as a study area due to the deterioration of the quality of the aquifers over the past years and the proven presence of numerous pollutants. The methodology consisted of vacuum-assisted evaporation (VAE) followed by chromatographic separation of the sample on two columns with orthogonal retention mechanisms, namely, an HSS T3 column (modified C18) and a BEH amide column (HILIC). The analytes were detected by high-resolution mass spectrometry on a Q Exactive Orbitrap system in data-independent acquisition mode. Taking into consideration the retention as well as the peak shape, a Quality Score (QS) was assigned for each analyte to evaluate the quality of each chromatographic peak of each compound. While 67 compounds, including 19 polar and 48 moderately polar, were satisfactorily retained on an HSS T3, 29 compounds, including 14 highly polar, 14 polar, and one moderately polar, were analyzed in the BEH amide column. The optimized methodology was applied for the analysis of 89 out of 96 validated contaminants with satisfactory recoveries in samples collected from seven wells, providing low LODs (0.02 to 0.45ng L-1) and LOQs (0.06 to 1.34ng L-1). A number of highly polar and polar compounds not previously reported to occur in GW, including artificial sweeteners, pharmaceuticals, and industrial chemicals, were detected at concentrations as high as few g L-1.

Bone Proteomics Method Optimization for Forensic Investigations.

The application of proteomic analysis to forensic skeletal remains has gained significant interest in improving biological and chronological estimations in medico-legal investigations. To enhance the applicability of these analyses to forensic casework, it is crucial to maximize throughput and proteome recovery while minimizing interoperator variability and laboratory-induced post-translational protein modifications (PTMs). This work compared different workflows for extracting, purifying, and analyzing bone proteins using liquid chromatography with tandem mass spectrometry (LC-MS)/MS including an in-StageTip protocol previously optimized for forensic applications and two protocols using novel suspension-trap technology (S-Trap) and different lysis solutions. This study also compared data-dependent acquisition (DDA) with data-independent acquisition (DIA). By testing all of the workflows on 30 human cortical tibiae samples, S-Trap workflows resulted in increased proteome recovery with both lysis solutions tested and in decreased levels of induced deamidations, and the DIA mode resulted in greater sensitivity and window of identification for the identification of lower-abundance proteins, especially when open-source software was utilized for data processing in both modes. The newly developed S-Trap protocol is, therefore, suitable for forensic bone proteomic workflows and, particularly when paired with DIA mode, can offer improved proteomic outcomes and increased reproducibility, showcasing its potential in forensic proteomics and contributing to achieving standardization in bone proteomic analyses for forensic applications.

The One Hour Human Proteome

We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS1 scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.

Combinatory data-independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities.

Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra-performance liquid chromatography-high-resolution mass spectrometry in data-independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high-throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.

Discovering Novel Organophosphorus Compounds in Wastewater Treatment Plant Effluents through Suspect Screening and Nontarget Analysis.

Limited knowledge on the structure of emerging organophosphorus compounds (OPCs) hampers our comprehensive understanding of their environmental occurrence and potential risks. Through suspect and nontarget screening, combining data-dependent acquisition, data-independent acquisition, and parallel reaction monitoring modes, we identified 60 OPCs (17 traditional and 43 emerging compounds) in effluents of 14 wastewater treatment plants (WWTPs) in Beijing and Qinghai, China. These OPCs comprise 26 organophosphate triesters, 17 organophosphate diesters, 6 organophosphonates, 7 organothiophosphate esters, and 4 other OPCs. Notably, 14 suspect OPCs were newly identified in WWTP effluents, and 16 nontarget OPCs were newly discovered in environmental matrices. Specifically, the cyclic phosphonate, (5-ethyl-2-methyl-1,3,2-dioxaphosphorinan-5-yl)methyl dimethyl phosphonate P-oxide (PMMMPn), consistently appeared in all WWTP effluents, with semiquantitative concentrations ranging from 44.4 to 282 ng/L. Its analogue, di-PMMMPn, presented in 93% of wastewater samples. Compositional differences between the WWTP effluents of two cities were mainly attributed to emerging OPCs. Hazard and ecological risk assessment underscored the substantial contribution of chlorinated organophosphate esters and organothiophosphate esters to overall risks of OPCs in WWTP effluents. This study provides the most comprehensive OPC profiles in WWTP effluents to date, highlighting the need for further research on their occurrence, fate, and risks, particularly for chlorinated OPCs.

Proteomic study of left ventricle and cortex in rats after myocardial infarction

Myocardial infarction (MI) induces neuroinflammation indirectly, chronic neuroinflammation may cause neurodegenerative diseases. Changes in the proteomics of heart and brain tissue after MI may shed new light on the mechanisms involved in neuroinflammation. This study explored brain and heart protein changes after MI with a data-independent acquisition (DIA) mode proteomics approach. Permanent ligation of the left anterior descending coronary artery (LAD) was performed in the heart of rats, and the immunofluorescence of microglia in the brain cortex was performed at 1d, 3d, 5d, and 7d after MI to detect the neuroinflammation. Then proteomics was accomplished to obtain the vital proteins in the heart and brain post-MI. The results show that the number of microglia was significantly increased in the Model-1d group, the Model-3d group, the Model-5d group, and the Model-7d group compared to the Sham group. Various proteins were obtained through DIA proteomics. Linking to key targets of brain disease, 14 proteins were obtained in the brain cortex. Among them, elongation of very long chain fatty acids protein 5 (ELOVL5) and ATP-binding cassette subfamily G member 4 (ABCG4) were verified through western blotting (WB). The results of WB were consistent with the proteomics results. Therefore, these proteins may be related to the pathogenesis of neuroinflammation after MI.

Data independent acquisition reveals in-depth serum proteome changes in uremic pruritus.

Introduction: Uremic pruritus (UP) is a prevalent symptom in patients suffering from uremia, yet its underlying etiology and mechanisms remain incompletely elucidated. Given the significant incidence of UP, identifying specific alterations in proteins present in the blood of UP patients could offer insights into the potential biological pathways associated with UP and facilitate the exploration of biomarkers. Methods: In this study, we employed LC-MS/MS-based data-independent acquisition (DIA) mode to analyze serum samples obtained from 54 UP patients categorized as DKD-UP, HN-UP, and GN-UP (n = 18 for each subgroup), along with 18 uremic patients without pruritus (Negative) and 18 CKD patients without pruritus (CKD). Through DIA mode analysis, a total of 7075 peptides and 959 proteins were quantified. Within these, we identified four upregulated and 13 downregulated Differentially Expressed Proteins (DEPs) in DKD-UP versus Negative, five upregulated and 22 downregulated DEPs in HN-UP versus Negative, and three upregulated and 23 downregulated DEPs in GN-UP versus Negative. Furthermore, we conducted an intersection analysis of the DEPs across these three comparison groups to derive a set of common DEPs (COMP). Subsequently, a total of 67 common DEPs were identified in the three UP groups when compared to the CKD group, with 40 DEPs showing upregulation and 27 DEPs displaying downregulation. Results: Following Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analyses, we observed that the DEPs distinguishing UP from CKD were primarily associated with mitochondrial function (MT-CYB, PRDX2, TOMM22), inflammation (CD59, CSF1), renal injury (WFDC2), and neural function (CAP1, VGF). Discussion: Our findings contribute to a potential molecular comprehension of UP pathogenesis, shedding light on the identification of these DEPs as plausible biomarkers for UP.

Extending the Coverage of Lys-C/Trypsin-Based Bottom-up Proteomics by Cysteine S-Aminoethylation.

To improve the coverage in bottom-up proteomics, S-aminoethylation of cysteine residues (AE-Cys) was carried out with 2-bromoethylamine, followed by cleavage with lysyl endopeptidase (Lys-C) or Lys-C/trypsin. A model study with bovine serum albumin showed that the C-terminal side of AE-Cys was successfully cleaved by Lys-C. The frequency of side reactions at amino acids other than Cys was less than that in the case of carbamidomethylation of Cys with iodoacetamide. Proteomic analysis of A549 cell extracts in the data-dependent acquisition mode after AE-Cys modification afforded a greater number of identified protein groups, especially membrane proteins. In addition, label-free quantification of proteins in mouse nonsmall cell lung cancer (NSCLC) tissue in the data-independent acquisition mode after AE-Cys modification showed improved NSCLC pathway coverage and greater reproducibility. Furthermore, the AE-Cys method could identify an epidermal growth factor receptor peptide containing the T790 M mutation site, a well-established lung-cancer-related mutation site that has evaded conventional bottom-up methods. Finally, AE-Cys was found to fully mimic Lys in terms of collision-induced dissociation fragmentation, ion mobility separation, and cleavage by Lys-C/trypsin, except for sulfoxide formation during sample preparation.

Identification of polar organic chemicals in the aquatic foodweb: Combining high-resolution mass spectrometry and trend analysis

Environmental risk assessment of chemical contaminants requires prioritizing of substances taken up by biota as it is a starting point for potential adverse effects. Although knowledge about the occurrence of known chemical pollutants in aquatic organisms has significantly improved during the last decade, there is still a poor understanding for a broad range of more polar compounds. To tackle this issue, we proposed an approach that identifies bioaccumulative and biomagnifiable polar chemicals using liquid chromatography coupled with electrospray ionization to high resolution tandem mass spectrometry (LC-HRMS/MS) and combine it with trend analysis using hierarchical clustering. As a proof-of-concept, this approach was implemented on various organisms and compartments (sediment, litter leaves, periphytic biofilm, invertebrates and fish) collected from a small urban river. HRMS/MS data measured via data-independent acquisition mode were retrospectively analysed using two analytical strategies: (1) retrospective target and (2) suspect/non-target screening. In the retrospective target analysis, 56 of 361 substances spanning a broad range of contaminant classes were detected (i.e. 26 in fish, 18 in macroinvertebrates, 28 in leaves, 29 in periphyton and 32 in sediments, with only 7 common to all compartments), among which 49 could be quantified using reference standards. The suspect screening approach based on two suspect lists (in-house, Norman SusDat) led to the confirmation of 5 compounds with standards (three xenobiotics at level 1 and two lipids at level 2) and tentative identification of seven industrial or natural chemicals at level 2 and 3 through a mass spectra library match. Overall, this proof-of-concept study provided a more comprehensive picture of the exposure of biota to emerging contaminants (i.e., the internal chemical exposome) and potential bioaccumulation or biomagnification of polar compounds along the trophic chain.

Improved quantification of carbonyl sub-metabolome by liquid chromatography mass spectrometry using a fragment controlled multiplexed isotopic tag

BackgroundCarbonyl-containing metabolites are a class of key intermediate in metabolism, which has potentials to be biomarkers. Since their poor ionization, derivatization reagents, such as dansylhydrazine, are usually used to improve the sensitivity and/or to facilitate quantification. However, most current carbonyl derivatization reagents only have two channels, one is isotopically labeled and the other one is non-labeled. To quantify more samples in a run and using data-independent acquisition (DIA) mode to get comprehensive and unbiased mass fragmentation, we proposed a fragment-controlled isotopic tag, called DiMe-FP-NHNH2 (FP) which has five channels: Δ0, Δ3, Δ6, Δ9, and Δ12, thus up to 5 samples can be analyzed in a run. ResultsThe most important improvement is that the FP tag can produce multiple characteristic signals in tandem mass, diagnostic ions and neutral losses, which helps to selectively detect aldehydes/ketones for targeted and untargeted analysis. To exhibit all capabilities of the FP tag, we mimicked an untargeted metabolomics experiment, which comprises two steps. First, discovery step, using Data-Independent Analysis (SWATH-MS) and the labeling of two channels (Δ0 and Δ3), we picked out aldehyde/ketone from the pooled urine samples based on three characteristic signals, including isotope patterns, diagnostic ions, and neutral losses. Second, five-plex quantification, relative and absolute quantification were achieved in a single LC-MS analysis. Notably, because of different nominal masses, the FP tag can be used on any low or high resolution mass spectrometers. SignificanceThe benefits and performance of the FP tag are demonstrated by the analysis of urine samples collected from patients from a prostate cancer study, in which more than a thousand features were found based on MS1 fingerprint, but only around 120 aldehyde/ketone candidates were confirmed with characteristic signals and nine of which were quantified showing significant differences from healthy and reference urine samples.