| Topic(s): Small Molecule > Tox / TDM / Endocrine |
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Poster Presentation Poster #2c Attended on Thursday at 12:15
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 Prostate Cancer: Are Male Testosterone Assays Fit For Purpose?
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James Hawley (Presenter) Wythenshawe Hospital >> NO POSTER PDF SUBMITTED
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| BACKGROUND: Androgen-deprivation therapy (ADT) is recommended to treat advanced prostate cancer. Evidence suggests that lowering testosterone concentrations below 0.7 nmol/L (20 ng/dL) improves patient survival and reduces disease progression. To date, limited work has been undertaken to assess the performance of testosterone assays in this concentration range in males receiving ADT therapy.
DESIGN: Surplus serum from males taking ADT was obtained prior to disposal from a tertiary cancer centre. Samples were anonymised and distributed to collaborating laboratories for testosterone analysis by 5 routine assays. Simultaneously, we collaborated with UK NEQAS to arrange a small survey to assess how male prostate cancer samples are processed in the UK.
RESULTS: The UK NEQAS survey indicated that 4/64 laboratories in the UK routinely refer samples for LC-MS/MS analysis in ADT patients. We observed considerable variation across routine immunoassay platforms compared to LC-MS/MS. All routine immunoassays displayed a mean positive bias, this ranged from 0.12 to 0.75 nmol/L (3.5 to 21.6 ng/dL).
SUMMARY: Despite the clinical importance of suppressing testosterone in ADT, our results suggest this is a cohort of patients that is often overlooked. The performance of many routine immunoassays in this low nanomolar range is sub-optimal for these patients. |
| Topic(s): Other -omics > Lipidomics |
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Poster Presentation Poster #5a Attended on Wednesday at 09:15
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 Quantitative LC-MS/MS Assay for Ceramides in Plasma and Serum: Development, Validation, and Performance Evaluation
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Amol Bajaj (Presenter) ARUP
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| BACKGROUND: Ceramides have emerged as novel diagnostic and prognostic biomarkers for cardiovascular disease (CVD), providing additional risk prediction beyond traditional lipid measures. Several studies have highlighted their potential utility as biomarkers for insulin resistance, type 2 diabetes mellitus, severity of coronary artery disease, atherosclerosis, dyslipidemia, malignancies, and neuroinflammation. We developed a quantitative LC-MS/MS method to measure Cer 16:0, Cer 18:0, Cer 24:0, and Cer 24:1 in plasma and serum and evaluated the method’s performance. METHODS: Aliquots of human plasma or serum samples (40 µL) were mixed with stable isotope-labeled internal standard (IS, deuterium labeled analogs of each ceramide, 40 µL), water (100 µL) and methyl tert-butyl ether (MTBE, 400 µL). The tubes were vortexed for 20 min, and then centrifuged for 5 min at 16,000 g. The supernatants were transferred to autosampler vials, and the samples were analyzed using a 6475 LC-MS/MS, equipped with a 1290 series HPLC (Agilent). Chromatographic separation was performed using a CSH C18 column (1.7 µm, 5 cm, 100 Å, 2.1 mm ID, Waters). Quantification was performed using a six-point calibration curve (0.02–2 µmol/L for Cer 16:0 and Cer 18:0; 0.2–20 µmol/L for Cer 24:0 and Cer 24:1), monitoring two mass transitions per analyte and IS. The injection volume was 5 µL, and data acquisition was performed in positive ion mode. Evaluation of the method’s performance included assessment of precision, sensitivity, linearity, accuracy, specificity, matrix effects, dilution integrity, carryover, robustness, and correlation with validated methods performed by other laboratories. Blood collection tube types, stability, and the adsorptive losses of ceramides during the sample preparation were also evaluated. All studies with samples from human subjects were approved by the Institutional Review Board of the University of Utah (Salt Lake City, UT). RESULTS: We developed and evaluated analytical performance of a method for quantifying four ceramides in plasma and serum samples by LC-MS/MS. The issues related to poor retention of Cer 16:0 and Cer 18:0, and adsorptive losses of ceramides were addressed with sample preparation methods and chromatographic separation. A CSH C18 column (Waters) provided the best HPLC performance. In a sample preparation method involving solvent extraction, evaporation, and reconstitution, a variation in the slopes of the calibration curves was observed using calibrators prepared in a Mass Spec Gold Serum (Golden West Diagnostics) matrix and those prepared in a pool of patient samples. However, when the evaporation and the reconstitution steps were omitted, and the extracts were directly injected for instrumental analysis, the variation in the slopes of the regression lines were comparable, suggesting adsorptive losses of the ceramide during evaporation and reconstitution steps of sample preparation. The assay demonstrated a total imprecision (CV) of <2-8.0% across the analytical measurement range for all the analytes included in the assay. In experiments on the evaluation of the methods’ accuracy, the observed concentrations agreed with the expected concentrations within 10% (imprecision among the replicates <5%). Slopes of linear regression lines (R2) for the agreement between the expected and the observed concentrations were 0.99 (0.996), 0.99 (0.995), 0.99 (0.995) and 0.99 (0.995) for Cer 16:0, Cer 18:0, Cer 24:0, and Cer 24:1, respectively. The lower limit of detection (LOD) was 0.01 µmol/L for Cer 16:0 and Cer 18:0, and 0.1 µmol/L for Cer 24:0 and Cer 24:1. The signal-to-noise ratio at the LOQ for the transitions of all the analytes was ≥10. Over 600 neat patient samples (serum and plasma) have been analyzed by the assay; no peaks in the vicinity of the peaks of the analytes and the ISs were observed in the mass transitions used in the assay. Overestimation of the ceramide concentrations was observed in hemolyzed or lipemic samples, containing >300 mg/dL or >225 mg/dL of hemoglobin or intralipid, respectively. No carryover was observed after injection of samples containing 4 µmol/L for Cer 16:0 and Cer 18:0, and 40 µmol/L for Cer 24:0 and Cer 24:1. The method was compared to a validated LC-MS/MS method of another laboratory using NIST material (Metabolites in Frozen Human Plasma, SRM 1950) and patient plasma or serum pools (n=6). Median (range) for percent agreement between the developed method and the comparative method were: 132 (117-143)%, 152 (149-156)%, 101 (97-103)% and 93 (82-99)%; the R2 values for the linear regression curves were 0.978, 0.999, 0.994 and 0.987, for Cer 16:0, Cer 18:0, Cer 24:0 and Cer 24:1, respectively. Ceramide concentrations from serum (red top), EDTA plasma, and lithium heparin plasma were comparable, showing agreement within 15%. CONCLUSION: An LC-MS/MS method was developed for quantifying Cer 16:0, Cer 18:0, Cer 24:0, and Cer 24:1 in plasma and serum samples. The method demonstrated reliable analytical performance with adequate precision, accuracy, and robustness. We observed reasonably good inter-laboratory agreement in the measured ceramide concentrations. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine > Cases in Clinical Analysis |
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Poster Presentation Poster #5c Attended on Thursday at 12:15
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LC-MS/MS Analysis of Bromazolam and Its Metabolites in Clinical Specimens from a San Francisco Patient Cohort
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Hannah Lusk (Presenter)  University of California San Francisco
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| INTRODUCTION: Benzodiazepines are central nervous system (CNS) depressants commonly used to treat anxiety, insomnia, seizures, and muscle spasms. Sedative effects induce relaxation and reduce anxiety but can also cause side effects such as drowsiness, altered mental status, dizziness, respiratory depression, and bradycardia. Due to their anxiolytic properties, benzodiazepines are frequently misused and carry a high risk of overdose, particularly when combined with other depressants. While several FDA-approved benzodiazepines, including alprazolam, lorazepam, and diazepam, are legally available by prescription in the United States, the illicit drug supply increasingly contains non-FDA-approved designer benzodiazepines. These compounds pose a significant public health concern due to their highly variable potency and poorly characterized pharmacokinetic profiles, increasing the risk of unintentional overdose. Bromazolam is one such designer benzodiazepine. Our laboratory conducts biosurveillance in San Francisco (SF) using a comprehensive mass spectrometry (MS)-based drug testing method, which has detected a recent rise in bromazolam-positive cases. In 2024, we identified 19 positive cases compared to 4 in 2023. To date, limited data exist on bromazolam’s pharmacokinetics, with only one study evaluating its metabolism using in vitro pooled human liver S9 fractions and in vivo analysis of serum and urine from two patients. To address this knowledge gap, we analyzed remnant serum and urine samples from SF patients to quantify bromazolam and characterize its metabolites. This study provides real-world data on bromazolam exposure and metabolism, offering insights into its pharmacokinetics and potential health risks. OBJECTIVES: The objective of this study is to characterize the metabolism of bromazolam in patient urine and serum samples. By analyzing bromazolam and its metabolites in real clinical samples, we aim to improve our understanding of its major metabolic pathways, thereby supporting toxicological and forensic investigations. METHODS: Ten remnant serum and 18 remnant urine samples were collected following a positive bromazolam result from our clinically validated comprehensive drug test using untargeted LC-QTOF-MS. Chromatographic separation was achieved with a C-18 column using a 10-minute gradient (2%-100% organic). Samples were analyzed on a SCIEX ZenoTOF® 7600 in positive mode with a TOF-MS survey scan and SWATH-triggered acquisition of high-resolution product ion spectra. Urine metabolites were identified through untargeted analysis. Serum concentrations of bromazolam and alpha-hydroxy bromazolam were quantified using 13 calibrators, a double blank, a blank, and four quality controls, all prepared in drug-free human serum to cover a dynamic range from 0.1 ng/mL to 1 µg/mL. Bromazolam-D5, at a concentration of 100 ng/mL, served as the internal standard. Quantification was performed using multiple reaction monitoring (MRM) on a SCIEX 4500 triple quadrupole MS. Chromatographic separation was carried out with a C-18 column using a 2-minute gradient (2%-100% organic). Sample preparation involved protein precipitation, centrifugation, evaporation under a steady stream of nitrogen gas, and reconstitution in the initial mobile phase. Data analysis was performed using PeakView software, and quantification was conducted using MultiQuant software. RESULTS: Bromazolam, bromazolam glucuronide, and hydroxy-bromazolam glucuronide were detected in all urine specimens analyzed using LC-QTOF-MS. Other metabolites identified in the original study that used human liver S9 fractions in vitro were not detected. Hydroxy-bromazolam glucuronide was the predominant metabolite, with an area under the curve (AUC) an average of 40% higher than the bromazolam peak. The ratios of bromazolam glucuronide and hydroxy-bromazolam glucuronide to bromazolam varied across samples, suggesting inter-individual differences in metabolic clearance. Concentrations in serum samples covered the calibration range and varied significantly between patients. IRB-approval was recently obtained to allow for medical chart review of positive bromazolam cases to evaluate if clinical symptoms and outcomes are associated with serum concentrations. CONCLUSIONS: The consistent detection of bromazolam glucuronide metabolites in patient urine samples underscores the significance of phase II metabolism in bromazolam clearance. In several samples, bromazolam was detected at lower levels than glucuronidated metabolites, indicating that failing to screen for these metabolites may lead to an underestimation of bromazolam-positive urine. This suggests that hydrolyzing samples before MS analysis or directly monitoring the glucuronide metabolite could extend the detection window and improve sensitivity. Variability in metabolite-to-parent drug ratios highlights inter-individual differences that may impact bromazolam’s pharmacologic effects. However, correlating bromazolam concentrations in serum with clinical symptoms is challenging due to poly-drug exposure, which complicates the attribution of symptoms to bromazolam versus other substances. Notably, no published clinical cases of bromazolam exist, with current literature primarily focusing on postmortem analyses. Our findings enhance the understanding of bromazolam pharmacokinetics, confirming its glucuronidation and metabolism to hydroxy-bromazolam. |
| Topic(s): Small Molecule > Lipidomics > Precision Medicine |
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Poster Presentation Poster #6d Attended on Thursday at 14:30
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Development of a Specific LC-MS/MS Method for the Quantification of Brain Cholesterol Metabolites in Neurodevelopmental Disorders
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Sophie Bouhour (Presenter) University of Sherbrooke >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: Several neurodevelopmental disorders, including Smith-Lemli-Opitz syndrome, Fragile X syndrome, and autism spectrum disorders, are associated with impairments in peripheral and cerebral cholesterol homeostasis. Oxidized derivatives of brain cholesterol, known as oxysterols, are promising biomarkers due to their ability to cross the blood-brain barrier. The quantification of these oxysterols in plasma offers a non-invasive approach to assess cerebral cholesterol homeostasis in these disorders. However, their low plasma concentrations and their structural similarities present significant analytical challenges, with only a few methods available for their simultaneous analysis. OBJECTIVE: This study aims to develop and validate a sensitive and specific method using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the analysis of 18 compounds: 5 cholesterol precursors, 5 auto-oxidized oxysterols, and 8 enzyme-derived oxysterols. METHODS: The LC-MS/MS method was developed using an Acquity UPLC system coupled with a Xevo TQ-S micro mass spectrometer (Waters). The ionization source was electrospray ionization in positive mode. Stable deuterium-labeled analogs were used as internal standards for each compound.
RESULTS: The dynamic Multiple Reaction Monitoring (MRM) acquisition mode was employed. Specific transitions were designated for the 18 oxysterols and their respective internal standards. A preliminary isocratic separation of oxysterols was obtained using a C8-silica column at 62.5% acetonitrile with 0.1% formic acid (B) and 37.5% HPLC-grade water with 0.1% formic acid at a flow rate of 0.3 mL/min. This initial step was followed by a linear gradient from 62.5% to 98% acetonitrile in order to enhance the separation of the most hydrophobic compounds. This chromatography setup provided an initial resolution of the 18 oxysterols, with a total run time of 17.5 minutes. This preliminary method demonstrated linearity between 5 and 1450 nM for 17 oxysterols in pure standards solutions, with limits of quantification of 1 nM for 10 compounds and 5 nM for the remaining 7 oxysterols. CONCLUSION: Mass spectrometry, ionization, and chromatographic separation parameters will be further optimized. The method validation will be performed according to Clinical & Laboratory Standards Institute (CLSI) C62 guidelines. Oxysterols will then be quantified in individuals with neurodevelopmental disorders. In the long term, this method will be implemented in clinical laboratories to support potential diagnostic applications and prognostic monitoring of cholesterol-related neurodevelopmental disorders. |
| Topic(s): Spatialomics > Spatialomics : Procedure and Validation > Spatialomics : Pathology and Biomarkers |
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Poster Presentation Poster #7d Attended on Thursday at 14:30
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HistoProbe: A Dual-Mode Thermally Assisted Microfluidic Platform for Rapid, Solvent-Minimal Mass Spectrometry Analysis of FFPE Tissues
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Malek Hassan (Presenter) Queen's University
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| INTRODUCTION: Formalin-fixed paraffin-embedded (FFPE) tissues are essential clinical resources, yet conventional deparaffinization methods are slow, laborious, and environmentally unfriendly, relying heavily on toxic solvents. Addressing these limitations, we introduce HistoProbe, a novel microfluidic platform enabling rapid, localized, and minimally solvent-dependent analysis and imaging of FFPE tissues by mass spectrometry (MS). METHODS: HistoProbe integrates a modified liquid microjunction surface sampling probe (LMJ-SSP) with precise thermal regulation adapted from 3D printer hardware. The platform operates in two distinct modes: Online and Offline. Online-HistoProbe enables direct metabolite extraction and real-time analysis from FFPE tissue sections at elevated temperatures (~60 °C) without any prior sample preparation or deparaffinization. It functions as a standalone tool by interfacing directly with the electrospray ionization (ESI) source of the mass spectrometer, offering a plug-and-play solution for rapid FFPE tissue analysis. Offline-HistoProbe enables targeted thermal deparaffinization using reduced volumes of solvents (i.e., ethyl acetate, toluene, or xylene) at controlled temperatures (up to 75 °C). This mode drastically lowers solvent usage compared to standard protocols while maintaining compatibility with high-resolution imaging. Both modes were coupled with desorption electrospray ionization mass spectrometry (DESI-MS) for metabolic profiling and hyperspectral molecular imaging. Data were analyzed using principal component analysis (PCA) for dimensionality reduction and unsupervised clustering of metabolic features. RESULTS: Optimization studies demonstrated that Online-HistoProbe eliminated the need for sample preparation and solvent use, reducing total analysis time to approximately 17 minutes per sample and enabling high-throughput analysis exceeding 80 samples per day. The practical spatial resolution of the online mode was approximately 1 millimeter, suitable for rapid tissue screening and metabolic profiling. Offline-HistoProbe, optimized with ethyl acetate at 75 °C, achieved comparable or superior metabolite recovery to traditional xylene-based deparaffinization, while reducing solvent consumption by over 99.5%. It supported a practical spatial resolution of 50–100 micrometers, allowing fine-grained molecular imaging. Both modes reliably distinguished neoplastic from non-neoplastic regions in melanoma FFPE tissues and enabled annotation of key biomolecules, including fatty acids, phosphatidylinositols, and oxidized lipids relevant to cancer metabolism. CONCLUSION: HistoProbe represents a significant advancement in mass spectrometry-based histopathology, combining speed, analytical precision, automation, and sustainability. Its dual-mode functionality addresses clinical demands by offering high-throughput direct analysis (Online mode) and high-resolution molecular imaging (Offline mode). HistoProbe substantially reduces solvent consumption, sample preparation time, and environmental impact, demonstrating immense potential for clinical diagnostics, biomarker discovery, and rapid intraoperative tissue assessments. |
| Topic(s): Other -omics > Data Analytics |
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Poster Presentation Poster #9b Attended on Wednesday at 12:15
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Metabolic Profiling of Tissues for Biomarker Discovery in Breast Cancer
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Valdis Gunnarsdottir Thormar (Presenter) University of Iceland >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: Breast cancer (BC) is the most prevalent cancer worldwide and the second leading cause of cancer-related deaths in women. Challenges relating to timely detection and the heterogeneous nature of BC complicate treatment strategies and influence patient outcomes. Conventional X-ray mammography screening, commonly used, exhibits limited sensitivity, particularly in young women with dense breast tissue, and lacks specificity for accurate BC diagnosis. Advanced diagnostic techniques that better characterize the disease enable more personalized treatment approaches, which improves prognosis. OBJECTIVE(S): This study aims to reveal associations between metabolites, lipids, and BC-related parameters, thereby facilitating the discovery of BC-specific biomarkers. METHODS: In this study, we use a metabolic fingerprinting method for analyzing fresh frozen (FF) tissue samples and archived formalin-fixed and paraffin-embedded (FFPE) tissue microarray (TMA) samples, on a well-defined Icelandic BC study cohort. Additionally, targeted and untargeted metabolomics analyses, covering both metabolites and lipids, have been performed on plasma samples from a subset of the same study cohort using LC-MS and NMR. The comprehensive metabolomics profiling of tissue was performed using desorption electrospray ionization mass spectrometry imagining (DESI-MSI) on TMAs from 222 BC patients and 30 normal tissues for diagnostic purposes. Advanced machine learning techniques for predictive modeling will be applied to the data. By combining the analysis of metabolites and lipids with various BC-related parameters, we aim to explore underlying associations in the data. Both univariate and multivariate methods will be applied, as each provides distinct information about the data structure. Unsupervised algorithms like PCA, t-SNE, and UMAP will be used to visualize and elucidate data patterns, whilst supervised algorithms such as Gradient Descent, SVM, and Random Forest, including ensemble learning techniques, will be deployed to build robust classifiers. Feature selection methods will be implemented to help identify biomarkers and regulate model complexity. To ensure model reliability and generalizability, rigorous cross-validation and data partitioning into training, testing, and validation sets are conducted. Partitioning and cross-validation allow for the robust evaluation of how well the models perform on new, unseen data. RESULTS: DESI-MSI has shown the ability to distinguish between tumor and normal breast tissues based on their metabolomics profiles. Additionally, the results showed that despite formalin fixation and paraffin embedding on the tissue, enough information could be obtained to characterize the tissue. To confirm and expand upon these findings, the DESI-MSI data is being pre-processed again according to a new pipeline, effectively increasing the number of detectable metabolites in FFPE BC tissue and lipids in FF BC tissues. CONCLUSION: In this ongoing research, we investigate the correlations between BC subtypes, relevant patient characteristics, and their metabolomic profiles, aiming at a holistic view of the biomolecular changes associated with BC. Ultimately, to identify novel biomarkers. |
| Topic(s): Other -omics > Lipidomics |
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Poster Presentation Poster #10d Attended on Thursday at 14:30
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MALDI MSI and Lipidomics Reveal Lipid Release in Ovarian Cancer Models
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Carlismari Grundmann (Presenter) University of California - Santa Cruz
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| INTRODUCTION: Ovarian cancer is the deadliest gynecologic malignancy, with high-grade serous carcinoma (HGSC) accounting for ~70% of cases. HGSC originates in the fallopian tube epithelium and metastasizes to the ovaries and omentum. We have found that epinephrine enhances lipid release from omental adipocytes, creating a pro-metastatic microenvironment. Using mass spectrometry imaging (MSI) of 3D co-cultures of HGSC cells, murine omental tissues, and adipocyte spheroids, alongside LC-MS(/MS) lipidomic profiling and invasion assays, we investigated this metabolic crosstalk. Our findings suggest that epinephrine acts as an autocrine signal in the tumor microenvironment to enhance lipid release, fostering HGSC invasion and disease progression. Understanding these interactions offers insight into tumor-microenvironment dynamics and could guide the development of targeted therapies to inhibit HGSC metastasis. METHODS: A 3D co-culture system in agarose was optimized to study interactions between murine omental tissues, adipocytes, and murine oviductal epithelial (MOE) cells. MALDI MSI was performed using a Bruker timsTOF flex mass spectrometer with a 50-micron spatial resolution in positive reflectron mode. A 50:50 CHCA:DHB matrix was applied using an HTX TMSprayer, enabling prioritization of lipid signals intensified in cancer-omentum/adipocyte interactions. For lipidomic profiling, LC-MS(/MS) analysis was performed in reverse-phase using both positive and negative ionization modes to identify differentially expressed lipids in adipocyte-conditioned media treated with a β-adrenergic receptor agonist (epinephrine) or antagonist (propranolol). These conditioned media were also used to evaluate cell behaviors, including proliferation, migration, and invasion. RESULTS: MSI data revealed that epinephrine is produced in 3D co-cultures involving HGSC cells, omental tissues, and adipocyte spheroids. Epinephrine-treated adipocyte-conditioned media significantly enhanced HGSC cell invasion, demonstrating the pro-metastatic effects of β-adrenergic signaling. Conversely, propranolol, a β-adrenergic receptor antagonist, effectively inhibited these effects by blocking endogenous epinephrine action. After optimizing lipid extraction strategies for adipocyte-conditioned media, LC-MS/MS data acquired in both ionization modes were analyzed to classify lipid subclasses and their relative abundance across treatments. Visualization tools such as Volcano Plots and Molecular Networks were used to interpret the data, leveraging Cytoscape for network analysis and LinexWorkflow for lipid metabolic pathway mapping. Lipidomic profiling revealed an increased release of specific lipid classes under epinephrine treatment, particularly glycerolipids and sterols, such as MG O-6:0 and ST 26:6. These findings suggest that β-adrenergic receptor activation enhances omental lipolysis, potentially contributing to metabolic reprogramming within the tumor microenvironment. This reprogramming may create a lipid-rich niche that supports HGSC progression. Furthermore, MALDI MSI provided spatially resolved confirmation of lipid accumulation at tumor-omentum interfaces within the 3D co-culture system. These localized lipid enrichments further support the hypothesis that metabolic crosstalk mediated by β-adrenergic signaling plays a pivotal role in facilitating tumor invasion and metastasis. CONCLUSION: Our findings highlight the role of epinephrine in modulating lipid dynamics within the HGSC tumor microenvironment. By integrating MALDI MSI and lipidomics, we reveal how β-adrenergic signaling enhances omental lipolysis, creating a pro-metastatic lipid-rich niche. These insights could guide the development of therapeutic strategies targeting metabolic vulnerabilities in HGSC. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine |
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Poster Presentation Poster #13a Attended on Wednesday at 09:15
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Development and Validation of a Sensitive UPLC-QToF Method for Vancomycin, Ceftazidime, and Ceftriaxone in Cerebrospinal Fluid and Serum
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Chao Sun (Presenter) University of Southern California, Children's Hospital of Los Angeles
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| INTRODUCTION: Vancomycin, ceftazidime, and ceftriaxone are antibiotics commonly used to treat central nervous system infections. We developed a sensitive liquid chromatography- quadrupole Time-of-Flight (UPLC-QToF) method that simultaneously measures these antibiotics in cerebrospinal fluid (CSF) and serum. This method will be used to analyze specimens to study the pharmacokinetics and blood-brain barrier penetration of these antibiotics. Additionally, it will aid in dosage optimization to minimize toxicity while maximizing therapeutic efficacy for patients with central nervous system infections. METHODS: CSF or serum was mixed with isotope-labeled internal standards and extracted using a 96-well Strata-X-C (Phenomenex) solid-phase extraction plate. The dried eluate was reconstituted with 75 µL of solvent and analyzed using a Xevo G3 QToF mass spectrometer (Waters) with an ACQUITY™ BEH C18 (1.7 µm, 2.1 × 50 mm) column (Waters). Accuracy was assessed using spike-recovery studies with CSF or synthetic serum. The analytical measurement range (AMR) was determined by spiking antibiotics into CSF or synthetic serum to generate seven specimens with increasing concentrations. Precision (repeatability and reproducibility) was assessed using quality control materials. Matrix effect was evaluated by comparing post-spiked extracted samples with neat antibiotic solutions (without solid-phase extraction). RESULTS: Linear regression was used to build the calibration curve. In both CSF and serum, the method demonstrated linearity for all antibiotics over a range of 0.1–10 µg/mL, with r² > 0.99. Repeatability and reproducibility were <10% CV. Minimum carryover was observed for both CSF and serum samples. Spike-recovery studies demonstrated recoveries of 89%–119% in serum samples and 91%–105% in CSF samples. Minimal matrix effect was observed in both serum and CSF samples. CONCLUSION: We have developed and validated a sensitive and rapid LC-QToF method for the simultaneous measurement of vancomycin, ceftazidime, and ceftriaxone in both serum and CSF. |
| Topic(s): Proteomics > Data Analytics > Metabolomics |
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Poster Presentation Poster #13b Attended on Wednesday at 12:15
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Integrating Targeted Proteomics and Clinical Data for Early-Stage Breast Cancer Biomarker Discovery in Human Plasma
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Kristrun Yr Holm (Presenter) University of Iceland >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: Breast cancer (BC) is the most prevalent cancer in women and ranks as the second leading cause of cancer-related deaths. Fortunately, the prognosis of BC is good when detected at an early stage, however, sensitive diagnostic tools for early detection of BC are vital for improving survival rates. Blood-based biomarkers may offer an alternative minimally invasive strategy to improve BC screening, with better sensitivity than the routinely used X-ray mammography. OBJECTIVES: The objective of this study is to discover protein biomarkers in human plasma samples for early breast cancer diagnosis, with an emphasis on clinical variables. METHODS: An absolute quantification of 131 proteins was performed on 270 well-defined Icelandic biobank-based plasma samples, 135 BC patients, and 135 healthy controls by UPLC-MRM-MS assay. This Icelandic study cohort is well-defined with respect to BC subtypes, clinicopathological variables and BRCA germline mutations. Among the BC patients, 33% were from BRAC2 999del5 mutation carriers. The absolute quantification of the proteins was conducted using a PeptiQuantTM protein human kit, which contains synthetic light peptides and matching heavy peptides as an internal standard for each protein. Sample preparation prior to analysis was fully automated using the liquid handling robot coupled with a solid-phase extraction (SPE) unit, where plasma samples were proteolytically cleaved with trypsin, internal standards were added, and the samples concentrated by SPE. Peak area data was generated using Skyline Quantitative Analysis software (v22.2.0.351). Further data analysis was conducted using RStudio (v4.2.2), and SIMCA Pro 17 software was used for statistical analysis, multivariate data analysis, and machine learning.
RESULTS: The targeted proteomics assay was successfully implemented for the absolute quantification of 131 proteins in human plasma samples with precision and accuracy for calibration standards and quality controls within 20% relative standard deviation. Out of the 131 proteins, 98 were quantifiable in the Icelandic bio-bank plasma samples, surpassing the lower limit of quantification. The samples were analyzed in eight batches, each containing matched pairs of cases and controls. Following data acquisition, the data was normalized, and minimal batch effects were corrected, ensuring accurate comparisons across all samples in downstream analysis. Considering the heterogeneous nature of BC, incorporating BC subtype, BRCA status, and clinicopathological variables such as tumor size, histological grade, and age appear to be important for assessing variations in protein concentrations. We detected several proteins that were significantly upregulated in BC cases, particularly in those with positive nodal metastasis, large tumors, and high histological grade. Other plasma proteins were found to be significantly downregulated in the Luminal B, triple-negative BC, HER-2 subtypes. Notably, two proteins were significantly downregulated in BRCA2 BC cases compared to both paired healthy controls and paired non-carrier BC patients, suggesting their potential as biomarkers for this specific mutation. CONCLUSIONS: Targeted proteomics using UPLC-MRM-MS demonstrates the potential for discovering and quantifying protein biomarkers in human plasma that could aid in the early detection of breast cancer, particularly in BRCA2 mutation carriers and subtypes such as Luminal B, triple-negative, and HER-2. |
| Topic(s): Proteomics > Metabolomics |
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Poster Presentation Poster #13c Attended on Thursday at 12:15
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Plasma Metabolomic and Proteomic Profiling of Anxious Dogs by HPLC-MS/MS: A Case-Control Study
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Claudia Gaither (Presenter) Faculté de médecine vétérinaire, Université de Montréal
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| INTRODUCTION: The prevalence of anxiety disorders in dogs highlights the need for novel/better diagnostics, prediction of treatment success, and treatment progress monitoring that can be achieved using innovative MS-based analyses. Behavioral problems affect up to 85% of dogs, with many stemming from underlying anxiety disorders. Some of the most common anxiety-related behavioral problems are separation anxiety, generalized anxiety, aggression, and compulsive behaviors. Although MS has been used for some disease profiling experiments in dogs and other species, it is usually overlooked in the veterinary and animal science fields, particularly in the animal behavior and psychiatry disciplines. Thus, here we investigate plasma proteomic and metabolomic differences between a group of anxious dogs and a group of non-anxious dogs. METHODS: Venous blood was collected, and plasma generated at the Faculté de médecine vétérinaire, Université de Montréal. Ten control and ten patient dogs underwent behavioral evaluations by a board-certified veterinary behaviorist and either diagnosed with an anxiety disorder or confirmed lack thereof, respectively. Samples were prepared for proteomic and metabolomic analyses by in-solution enzymatic digestion and solvent extraction of metabolites, respectively, for untargeted HPLC-MS/MS. Label-free quantitative MS data were acquired using a Vanquish Flex UHPLC, and an Evosep One system, both interfaced to a Q Exactive Plus Orbitrap MS (Thermo). Data were analyzed using Proteome Discoverer 2.2 or Compound Discoverer 2.1 (Thermo). Plasma protein and metabolite differences between the groups were assessed based on fold changes and t-tests (p-value ≤ 0.05). RESULTS: A total of 49 proteins had statistically significantly different plasma levels between anxious and non-anxious/control dogs, as determined by two-tailed student t-tests (p-value ≤ 0.05). Among the differential proteins were Apolipoproteins A-II, C-I and C-IV, involved in the packaging, transporting, and metabolizing of lipids, including cholesterol. Cholesterol is the precursor for cortisol, a well-studied biomarker for stress that leads to various physiological effects, including the flight or fight response. Other proteins found to be at different levels between the two groups were Fibrinogen Beta and Gamma chains, Serine Protease Inhibitors and Coagulation Factor XII, which are part of the blood coagulation cascade. These higher levels could be a result from cortisol production resulting in dysfunctional coagulation and excess clot formation. Finally, Complement Factors I and D, complement components C5, C6, C8A, and Complement Component 4 Binding Protein (C4BP) were differential and are involved in the complement system cascade, part of the innate immune response. The activation of C3 and C5 convertases is regulated by C4BP, and its differential expression could result in dysfunctional regulation of such enzymes, leading to increased or continuous inflammation.
Preliminary metabolomics results also show plasma profile differences between the two groups of dogs. Some of the metabolites that appear to be higher in the anxious dogs include phenylalanine, creatine, certain bile acids and certain fatty acids. In humans, higher levels of phenylalanine, a precursor to catecholamine neurotransmitters, are linked to anxiety. Bile acids can directly bind to brain receptors through the blood-brain barrier and their signaling may induce anxiety. Long chain saturated fatty acids are linked to anxiety-like behavior in mice and other fatty acids promote inflammation. Finally, metabolites like adenosine were lower in the anxious dogs, compared to controls. Low adenosine in humans can decrease sleep quality thus resulting in anxiety and depression. CONCLUSION: To our knowledge, this is the first unbiased/comprehensive clinical in-depth metabolomic/proteomic profiling of plasma from dogs with anxiety disorders. On the proteomics side, there are three main pathways that appear differential between the control and anxious dogs: those involved in lipid metabolism, the coagulation cascade, and the complement system. On the metabolomics side, phenylalanine, creatine, certain bile acids and certain fatty acids were found to be differential. Targeted assays will need to be developed for the validation of our findings and bring the field a step closer to elucidating the pathophysiology of anxiety. |
| Topic(s): Other -omics > Metabolomics > Precision Medicine |
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Poster Presentation Poster #16b Attended on Wednesday at 12:15
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 A Scalable and Accessible Workflow for Metabolic Flux Analysis in Human Cells
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Anna Weiser (Presenter) ETH Zurich
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| INTRODUCTION: Metabolic dysregulation is a hallmark of diseases including cancer, cardiovascular disease, and diabetes. A quantitative understanding of how metabolism is altered in these conditions is critical for therapeutic development. Metabolic flux analysis, which examines the rate at which metabolites flow through biochemical pathways, offers deep insights into metabolic activity and regulation. Stable isotope tracing experiments remain the most optimal method for dynamic measurement of metabolic processes. When combined with holistic computational models, they also offer a powerful tool for the prediction and validation of clinical interventions. In order to guide co-clinical applications robust and easy to use solutions are urgently needed. OBJECTIVES: Here we aim to create an easy-to-use toolkit for quantitative 13C metabolic flux analysis in human cells, for use by clinicians and researchers investigating metabolic activity, drug action, and potential resistance mechanisms. By lowering the technical barrier to flux analysis, we aim to provide a practical tool for interpreting metabolic dynamics beyond metabolite abundance. To this end, we have developed a comprehensive and user-friendly workflow that integrates liquid chromatography-mass spectrometry and stable isotope tracer analysis with machine learning-driven flux inference using Bayesian neural networks. Currently the workflow supports the design of isotope tracer experiments, exploratory data analysis, and probabilistic flux inference, with a focus on key flux ratios in human central carbon metabolism. METHODS: Cell Culture and Isotope Labeling: Human cancer cell lines including adult leukemia (HAP1), pediatric osteosarcoma (HOS), and neuroblastoma (SKNBE2), were cultured under standard conditions and treated with three targeted metabolic inhibitors: (1) 2-deoxyglucose (2DG): glycolysis inhibitor; (2) 6-aminonicotinamide (6AN): oxidative pentose phosphate pathway inhibitor (PPP); (3) CB-839 (CB): glutaminase inhibitor (glutaminolysis). Cells were incubated with the stable isotope-labeled tracer [1,2-13C]-glucose to focus on glycolysis and PPP, and prepared for LC-MS analysis using a simple solvent extraction and centrifugation to obtain a final extract of approximately 250k cells in 300 µL 1:4 (v/v) water/acetonitrile. Metabolite Profiling: We developed a semi-targeted high-resolution HILIC-LC-MS method specifically focused on central carbon metabolites, enabling sufficient separation within a timeframe appropriate for clinical translation. Calibration curves were obtained using non-enriched QC samples, enabling quantification in the presence of sample matrix in the approximate range of 5 nM - 0.1 mM of extracted sample for most compounds. As full scan acquisitions on Orbitrap instruments often have observably biased isotope ratios, semi-targeted MS1 acquisition windows were incorporated for more accurate quantification of the relevant compounds. Data were preprocessed and analyzed in R prior to downstream analysis and modelling. Flux Inference Framework: Fluxes were inferred using a simulation-based approach that couples 13C-metabolic flux analysis with Bayesian neural networks in Python. The inference workflow consists of: (1) atom-resolved metabolic network modeling (EMU-based), (2) simulation of expected isotopologue patterns for candidate flux distributions, (3) training of a Bayesian neural network to map observed data to posterior flux ratios, incorporating uncertainty. This architecture enables rapid, interpretable, and probabilistically grounded flux inference across different flux ratios. RESULTS: To optimize tracer selection for flux inference, Bayesian neural networks were trained on synthetic datasets simulating isotope labeling patterns under different tracer conditions. This yielded design-of-experiment maps that guide users in selecting the most informative tracers for specific regions of metabolism. For example, [1,2-13C]-glucose was optimal for resolving fluxes between glycolysis and the oxidative pentose phosphate pathway, while [U-13C]-pyruvate and [3-13C]-glutamine provided complementary information on anaplerotic versus oxidative TCA cycle activity. The selection focused on five flux ratios covering upper glycolysis, PPP, pyruvate utilization regarding TCA cycle, serine biosynthesis, and glutaminolysis, each chosen to inform on flux partitioning in central carbon metabolism. For biological validation, our workflow was applied to the three cancer cell lines described above using [1,2-13C]-glucose to specifically probe the flux split between glycolysis and PPP. Key findings include: (1) 6AN treatment significantly increased glycolytic flux relative to PPP in HAP1 and HOS, indicating compensatory rerouting under PPP inhibition. (2) SKNBE2 displayed a non-significant trend in the same direction. (3) 2DG, unexpectedly, increased glycolytic flux relative to PPP in HOS and SKNBE2. (4) CB-839 consistently increased relative PPP flux across all cell lines, potentially reflecting enhanced NADPH production under glutaminolysis-inhibition. CONCLUSION: Our workflow offers a streamlined approach for integrating isotope tracing, high-resolution metabolomics, and Bayesian neural networks to infer pathway activity. The initial application to three cancer cell lines illustrates the potential of this approach to detect drug-induced metabolic rewiring and to capture context-specific metabolic adaptations. While the method shows promise for accessible and interpretable flux analysis, further validation with additional tracers and experimental systems is needed. These early results support its future use in mechanistic studies, biomarker exploration, and therapeutic profiling. With continued development, this workflow may contribute to broader adoption of metabolic flux analysis in biomedical research. |
| Topic(s): Small Molecule > Metabolomics > Various OTHER |
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Poster Presentation Poster #18c Attended on Thursday at 12:15
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The Fibroid Secretome Possesses Distinct Metabolomic Features Compared to Adjacent and Control Myometrium
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Beth Harrison (Presenter) University of Liverpool
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| INTRODUCTION: The most common gynaecological condition and indication for hysterectomy worldwide is uterine leiomyomas (fibroids). Despite this, the pathophysiology of the condition remains poorly understood. Metabolomic analysis of the fibroid secretome offers novel mechanistic insight and potential identification of a future therapeutic target to reduce the heavy, irregular menstrual bleeding, chronic pelvic pain and infertility associated with the disease. OBJECTIVES: Identify significant differences in secreted metabolite abundances between fibroids, control myometrium and adjacent myometrium with future promise of better mechanistic understanding of disease and non-hormonal therapeutic targets. METHODS: Fresh surgical fibroid or myometrial samples were placed into basal DMEM medium with primocin and incubated for 24 hours. The resultant conditioned media was rendered acellular by centrifugation (4000 rpm, 4°C, 10 min). Deproteinised media containing deuterated internal standards were analysed using the 1290 Infinity II liquid chromatography system coupled to a 6550-quadrupole time-of-flight mass spectrometry (Agilent, UK). Prior to the analysis of study samples, optimal injection and reconstitution volumes were established. Data scaling by total protein concentration (BCA assay) and total metabolite abundance were compared. Ethical approval was obtained for the collection and usage of samples (LWRTB REC: ethical approval 19/WA/0271 and INTERPRET REC: approval 19/SC/0449). Raw data was processed using the Agilent MassHunter software suite and Metaboanalyst (Version 6.0). Features were extracted using ±10 ppm theoretical accurate mass and ±0.3 mins retention time window and were filtered based on their frequency (>70%) and variability across quality control samples (CV <30%). An accurate mass, retention time database containing 469 intermediary metabolites (Mw 72-785) was used to facilitate compound identification. Subsequent multivariant analysis using ANOVA (p<0.05 adjusted for FDR), univariant analysis using fold change and two paired t-test (FC 1.2, p<0.05 adjusted for FDR), and analysis of clinicodemographic variables was conducted following data pre-processing. Temporal profiling of the secretome was achieved by comparing time intervals collected and significant metabolite abundances. Iterative MS/MS was performed to aid in metabolite identification.
RESULTS: 129 samples from 48 patients were included in the final study, 19 samples from 2 patients were used for temporal profiling over 17, 24 and 50 h. Optimisation experiments showed that a 5 µL injection and a 50 µL reconstitution volume were superior. Covariate metadata analysis was performed to assess the contribution of fibroid subtype (by anatomical location), BMI (normal, overweight and obese), ethnicity (Caucasian, Black, Asian), pre-operative haemoglobin (<120 g/L Hb defined as anaemic), hormonal agents, menstrual phase, menopausal status (pre and post) and parity had on metabolite abundances. No demographic data demonstrated distinct metabolic profiles in either polarity. For targeted secretome analysis, 141 and 121 features were matched in positive and negative polarities respectively using an in-house metabolite database (level 1 identification). Of these matched features, 42(25 positive and 29 negative respectively, with duplicates accounted for), showed a significant change in metabolite abundance across univariant t-test (p<0.05) and multivariant ANOVA (p<0.05) analysis. For univariate analysis, most of the differences in metabolite abundances were shown between fibroid and control myometrium ((13 significant metabolites in positive and 20 in negative (blank contribution<5%)), where metabolite abundance was increased in fibroids relative to control (FC >1.2, no scaling). Most significant metabolites included amino acids and derivatives (including L-proline, L-ornithine, D-alanine), energy metabolism intermediates (including succinic acid, isocitrate, and malic acid), carbohydrates and derivatives (including glycerol, gluconic acid, and raffinose), and nucleotide metabolites (including hypoxanthine, inosine, and uracil). For untargeted secretome analysis, 5000 features in positive and negative polarities were matched by RT and accurate mass. 2950 positive and 2094 negative features remained after filtering by QC frequency and sample variation. Of these, 252 positive and 335 negative features showed a significant change in metabolite abundance across univariant t-test (p<0.05) and multivariant ANOVA (p<0.05) analysis. For univariate analysis, most of the differences in metabolite abundances were shown between fibroid and control myometrium ((166 significant metabolites in positive and 31 in negative (blank contribution<5%)), where metabolite abundance was increased in fibroid relative to control (FC >1.2, no scaling). Raw data was manually interrogated to assess metabolite peak quality and abundance of the precursor ion, and of which, 35 positive and 101 negative features were confirmed. Metabolite identification is ongoing, including targeted MS/MS experiments to identify unknown significant features.
CONCLUSION: This is the first study to demonstrate metabolomic differences in the secretome of fibroids compared to both control myometrium and adjacent myometrium using LC-QTOF-MS. We have shown that there are 48 metabolites with significant differences in abundance, that have been named and identified using RT and accurate mass from a reliable database. We have shown that metadata did not correlate with these metabolite differences. Further work is required to name and identify the significant metabolites found using the untargeted workflow, and to perform metabolite enrichment/pathway analysis to understand the biological significance in terms of pathophysiology and as a therapeutic target. |
| Topic(s): Small Molecule > Precision Medicine > Assays Leveraging Technology |
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Poster Presentation Poster #19a Attended on Wednesday at 09:15
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Development and Validation of a UPLC-MS/MS Method for Analyzing Drugs Commonly Used in Children with Attention-Deficit/Hyperactivity Disorder in Urine
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Ching-Mei Chen (Presenter) Chang Gung Medical Foundation
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| INTRODUCTION: Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurobehavioral disorder, particularly among school-age children. This condition not only impacts children's daily lives and learning but may also persist into adolescence and adulthood. In Taiwan, the prevalence of ADHD is approximately 9%. The primary medications currently used to treat ADHD include central nervous system stimulants, such as methylphenidate, and norepinephrine reuptake inhibitors, such as atomoxetine. Additionally, because individuals with ADHD often experience manic symptoms, doctors may prescribe aripiprazole, a serotonin 5-HT2A receptor antagonist. While these medications are effective, they can also lead to various psychiatric side effects. Furthermore, individual differences in drug metabolism necessitate precise dosage adjustments to achieve optimal therapeutic effects while minimizing adverse reactions, particularly in the vulnerable populations of children and adolescents. These medications typically have a short half-life and are primarily excreted in the urine as metabolites. OBJECTIVE(S): The objective of this study is to develop a rapid and non-invasive method for determining the concentrations of methylphenidate, atomoxetine, aripiprazole, and their metabolites in urine. Furthermore, the study aims to compare the consistency between individual plasma drug concentrations and their corresponding metabolite concentrations with urine drug concentrations. METHODS: 100 μL of urine was treated with glucuronidase and subjected to HLB solid-phase extraction. The urine was then directly analyzed using UPLC-MS/MS quantification. The three drugs and their metabolites were detected via electrospray ionization in positive mode, and the analytes were monitored in multiple reaction monitoring mode. The total analysis time for each sample was 3.5 minutes. RESULTS: We conducted method validation in accordance with the CLSI C62-A guidelines, establishing a detection limit of 1 ng/mL. The standard curve demonstrated linearity within a concentration range of 1-1000 ng/mL, with a linear correlation coefficient exceeding 0.999. Intra-batch and inter-batch imprecision were assessed using quality control samples, yielding values of less than 2.9% (n = 40) and 5.2% (n = 40), respectively. Accuracy was evaluated through recovery studies, with average recoveries for the six analytes ranging from 96.6% to 103.7%. This method exhibited no ion suppression or enhancement phenomena, and the presence of proteinuria and hematuria in samples did not impact the test results. Additionally, we analyzed the concentrations of three drugs and their metabolites in plasma and urine samples from 417 ADHD patients, confirming significant differences in drug concentrations among individuals receiving the same dosage. CONCLUSION: This study established an accurate, simple, and non-invasive UPLC-MS/MS method for the quantitative detection of ADHD medications in urine. It also demonstrated the significance of monitoring ADHD medication concentrations for personalized treatment and dosage adjustments, ensuring that each patient receives optimal treatment outcomes. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine |
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Poster Presentation Poster #19d Attended on Thursday at 14:30
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Development of Novel LC-MS/MS Psychoactive Panel (including Xylazine and Medetomidine) for Investigation of Prevalence in New Haven, CT Region
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Jill Kodger (Presenter) Yale University
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| INTRODUCTION: Novel psychoactive substances are synthetic compounds designed to mimic the effects of commonly misused illicit drugs. This study aims to develop a method for detecting and quantifying emerging veterinary anesthetics, kratom, synthetic opioids, synthetic cannabinoids, and synthetic benzodiazepines. The inclusion of veterinary drugs in this study is driven by the increasing prevalence of xylazine and medetomidine in patients with polydrug abuse. Kratom, used by approximately 0.7% of the U.S. population, is often consumed by individuals with opioid use disorder or polydrug abuse, and kratom-related deaths are frequently linked to polydrug use. The rise of synthetic opioids, particularly fentanyl, has contributed to what is now recognized as the "fourth wave" of the opioid epidemic, highlighting the urgent need for effective testing methods for these substances. Synthetic cannabinoids, often referred to as "bath salts," are synthetic stimulants chemically related to the khat plant and are commonly used in vapes. These compounds have been found in overdose victims and are increasingly involved in toxicological cases. There has been an uptick in novel psychoactive drug use, particularly veterinary drugs, in New Haven and surrounding areas, prompting our efforts to quantify this in our polydrug user population for surveillance purposes. METHODS: Urine (150uL) and internal standard (150uL at 200 ng/mL), were combined in micro centrifuge tube, vortexed, and centrifuged and poured into sample vials. 2uL of the resulting solution was injected onto an Acquity HSS T3 column (Waters; 1.8um, 2.1 x 50mm) with an Acquity UPLC H33 T3 VanGuard pre-column (Waters; 1.8um) coupled to a Xevo TQD(Waters). The mass spectrometer was operated in positive ion mode. Quantification was based on peak area ratios of xylazine (m/z 221.19>89.90) to xylazine D6 (m/z 227.18>89.94), 7-OH mitragynine (m/z 415.32>190.02), mitragynine (m/z 399.25 >174.14) , Gabapentin (m/z 172.03 >54.90) to gabapentin 13C3( m/z 175.17> 140.17), metonitazene (m/z 383.25 > 100.07) to metonitazene 13C6( m/z 175.17> 140.17), etonitazene (m/z 397.25>100.01) to etonitazene 13C6 (m/z 403.30 > 99.95) and medetomidine (m/z 201.13 > 94.94) to medetomidine 13C-D3 (205.13 > 98.93). RESULTS: A seven minute gradient of 50-100% mobile phase B was sufficient to separate all compounds using water +0.1% formic acid (FA) (mobile phase A) and methanol +0.1% FA (mobile phase B). The analytical measureable range (AMR) was within %CV <20% and had a recovery between 80-120%. AMR was 5 to 1000 ng/mL for all analytes except gabapentin, which was 20-1000 ng/mL. No significant carryover was observed up to a concentration of 200 ng/mL for all analytes. In a small sampling of 48 patients in our polydrug user population we found around 2.1% prevalence of medetomidine, 27.1 % prevalence of xylazine and 33.3% prevalence of gabapentin. CONCLUSION: In conclusion, novel psychoactive substances are detectable in our polydrug user population in the New Haven area, with xylazine being the most common, followed by medetomidine. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine |
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Poster Presentation Poster #21a Attended on Wednesday at 09:15
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To Free or Not to Free? An LC-MS/MS-Based Method Modification to Validate Clinical Performance of Bioavailable Testosterone Measurement
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Chelsea Swartchick (Presenter) Mayo Clinic >> NO POSTER PDF SUBMITTED
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| INTRODUCTION Measurement of total testosterone is an invaluable method for assessing an individual’s androgen status. This assay is often performed in conjunction with free testosterone measurement, which should encompass approximately 1 to 2% of the total testosterone concentration. However, measurement of free testosterone is influenced by abnormalities in both the concentration and/or function of sex hormone binding globulin (SHBG), the primary transport and regulatory protein for testosterone, along with albumin, the most abundant plasma protein. Therefore, analysis of bioavailable testosterone, which accounts for both free and testosterone loosely bound to albumin, is a more reliable representation of an individual’s true testosterone status. Recently, our bioavailable testosterone assay underwent a method modification to enhance calibrator storage and quality, which required subsequent validation to confirm adequate clinical performance. It has been shown that a strong correlation exists between bioavailable and free testosterone. As such clinical performance was validated by investigating the concordance between the reference interval (RI) flags (low, normal, or high) obtained using the modified BAT method and the RI flags from validated LC-MS/MS total and free testosterone assays. METHODS Residual serum samples (n = 65) from patients with recent (< 2 weeks) total and free testosterone measurements were used, where 23 were from women and 42 were obtained from men. Reference interval flags were categorized as high, normal, or low as determined being above, within, or below established reference intervals, respectively. There were 14 specimens classified as high, 36 as normal, and 15 as low, by both their total and free testosterone measurements. Bioavailable testosterone sample preparation involved the differential precipitation of testosterone-bound SHBG with ammonium sulfate. All non-SHBG bound testosterone remained in the supernatant, which subsequently was spiked with internal standard, carbon-13 labeled testosterone. Liquid-liquid extraction was performed, and the resulting isolate was derivatized before being quantified by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). All 65 bioavailable testosterone results were then categorized as either high, normal, or low according to the RI dependent on the patient’s sex and age. Flags from the bioavailable testosterone assay and flags from the free/testosterone measurements were evaluated for agreement. Serum SHBG was quantified using a chemiluminescent sandwich immunoassay. Serum albumin concentration was determined using a colorimetric method using the absorbance at 570 nm. RESULTS 59 of the 65 (90.7%) samples were correctly categorized with a RI flag as either low, normal, or high by both the free/total testosterone assays and the modified bioavailable testosterone method. The 6 samples that had discrepant flags required further investigation in which serum SHBG and albumin concentrations were evaluated. Of the discordant samples, 4 had elevated free and total testosterone, but normal bioavailable testosterone. Follow-up of this group demonstrated high SHBG concentrations. Elevated SHBG would expectedly bind more testosterone and decrease the bioavailable testosterone concentration, which provides a rationale of the normal categorization in this population. In a similar manner, one sample had a slightly elevated free and total testosterone, but normal bioavailable testosterone. The SHBG concentration of this sample was nearing the upper limit of normal, which follows the same principle as above where the bioavailable testosterone would be flagged as normal. The remaining discrepant sample had normal free and total testosterone, but elevated bioavailable testosterone. This specimen had an SHBG at the lower end of normal and an albumin at the higher end of normal. As there is less SHBG to bind testosterone and more albumin, an elevated bioavailable testosterone is appropriate. CONCLUSION Clinicians often prefer bioavailable testosterone as it more closely resembles the total bioactive testosterone in circulation when compared to free testosterone. Validation to ensure clinical accuracy of our bioavailable testosterone method modification involved a comparison of the reference interval flags between this method and verified free and total testosterone flags. In theory, samples that flag normal by both free and total testosterone assays should flag similarly with the bioavailable assay. We observed concordance in 90.7% of our samples, while the remaining 9.3% specimens had abnormal SHBG and/or albumin levels that were reflected appropriately in bioavailable testosterone RI flagging. In summary, our method modification performs clinically and can reflect the true testosterone status within a patient. |
| Topic(s): Spatialomics > Lipidomics > Spatialomics : Procedure and Validation |
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Poster Presentation Poster #21d Attended on Thursday at 14:30
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Mass Spectrometry Imaging of the Gut Microbiome
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Samarth Ganjoo (Presenter) University of Montreal
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| INTRODUCTION: The gastrointestinal microbiota is the largest microbial community within mammals. It is estimated that the human gut contains more than 100 trillion bacterial cells. This represents a diverse and complex array of amphiphilic membrane lipid structures spatially distributed along the gut. A multitude of these lipids have been shown to mediate host-microbe interactions, which are essential for maintaining the symbiotic relationship between the mammalian and bacterial cells. Understanding their spatial distribution in the gut can help identify the role of bacterial lipids on host biology, which remains unclear to date. This study focuses on the detection of lipid signals of bacterial origin by MALDI MSI to spatially resolve the microbiome biofilms across the intestine. METHOD: Fresh intestine harvested from mice was straightened and frozen on dry ice. 0.5-1 cm segments from different regions across the length of the intestine were cut and embedded in 10% CMC or NEG-50 embedding media. 10 μm thick transversal sections were cut at -16°C using a cryostat and mounted on ITO-coated glass slides. When dried, the sections were coated by sublimation (Shimadzu iMLayer) with 1,5-diaminonaphthalene (DAN) or 2,5-Dihydroxybenzoic acid (DHB) matrix. In addition to this, matrix spray deposition (HTX TM sprayer) was also employed in scenarios where MS/MS fragmentation was performed using lithium bromide (LiBr) salt with the MALDI matrices. Dual polarity MALDI MSI data was acquired from serial sections using a Shimadzu MALDI iMScope QT in the 400-1000 m/z range with 10 µm pixel size, 100 shots per pixel at a 5 kHz laser repetition rate. Lipid identification was performed by MALDI MS/MS directly from the sections. RESULTS: The preliminary high-resolution images of different intestinal regions produced an array of lipid signals, accounting to >500-600 unique spectral peaks per tissue section. Spatial segmentation analysis with spatially aware nearest shrunken centroid clustering and gaussian mixture models (GMM) highlighted numerous lipid signals clearly differentiating the intestine wall from the lumen. The segmentation varied across the length of the small intestine as well, portraying changes in the lipid localization in the tubular structure. A thorough library search using exact mass narrowed down our search list for lipid signals that may originate from bacterial cells around or within the gut lumen region. This is for example the case for m/z 603.5320 ([M+H]+; DG35:4), 796.5850 ([M+H]+; PC37:4), 771.5182 ([M-H]-; PG36:3), and 883.5977 ([M-H]-; PG44:3) all formally identified by MS/MS. These lipid species have been reported in literature to be preferentially expressed within bacteria. Several bacterial lipid gradients were also detected along the length of the intestine, presumably showing the localization of different bacteria. This is for example the case for PG36:3 with intensities increasing ~50% moving from jejunum to ileum in the small intestine. In addition to bacterial lipid detection, gradients for certain mammalian lipids were also observed across the length of the small intestine, which may be a consequence of lipid transfer from bacterial cells to the mammalian host cells as a metabolic pathway for immunomodulation. This is for example the case for SM34:1; O2 observed in high abundance around the jejunum section when compared to ileum or duodenum of the intestine, accompanied by a spatial localization shift to only one side of the intestine around the ileum region. This trend is indicative not only of lipid uptake by mammalian cells, but also of bacteria distribution from which this specific lipid may originate. Other interesting lipid trends are being investigated, with observations of phosphatidyl serine (PS) and phosphatidyl inositol (PI) lipids in the lumen regions of the tissues. These lipids are abundantly present in the gut and have been previously reported to play an important role in modulating the microbiome and its integrity. Work is also being done to assess bacterial-specific metabolite distributions within the gut to further characterize the various bacterial populations and the relationship with their host. CONCLUSION: Based on our findings, bacterial lipid signals as well as bacteria affected modulations in the lipids can be detected and mapped by MALDI-MSI from gut tissue sections. Additionally, a sub-population of lipids demonstrates intestine segment specific relative abundances and (or) distributions. These findings are hypothesized to be linked to certain lipid metabolic pathways that may be involved in immunomodulation, signaling, inflammation, etc. These findings and ongoing investigations will help us to better resolve the ongoing challenge of understanding the host-bacteria symbiosis. |
| Topic(s): Proteomics > Proteomics > Tox / TDM / Endocrine |
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Poster Presentation Poster #22b Attended on Wednesday at 12:15
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Protein Corona Formation and Cellular Effects of Multi-Walled Carbon Nanotubes Based on Pre-Coated Bovine Serum Albumin Concentration
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Jin Gyeong Son (Presenter) KRISS >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: The formation of a protein corona (PC) on nanomaterials upon exposure to biological environments significantly influences their cellular interactions and biocompatibility. Multi-walled carbon nanotubes (MWCNTs) have been widely studied for biomedical applications; however, their cellular effects vary depending on surface modifications. In this study, we investigate how pre-coating MWCNTs with different concentrations of bovine serum albumin (BSA) affects PC composition and cellular responses in A549 lung epithelial cells. OBJECTIVES: This study aims to (i) determine how BSA pre-coating concentration influences PC composition on MWCNTs, (ii) analyze secondary structural changes in adsorbed proteins, and (iii) evaluate the impact of these modifications on cellular uptake and intracellular signaling pathways. METHODS: MWCNTs were pre-incubated with varying concentrations of BSA (0, 1, 5, and 10 mg/mL) to form stabilized PC layers. Spectroscopic (circular dichroism, Fourier-transform infrared) and mass spectrometric (nanoLC-ESI-MS/MS) analyses were performed to characterize protein structures and compositions. Cellular uptake was quantified using optical absorption measurements, and proteomic analysis was conducted to assess intracellular responses in A549 cells. RESULTS: BSA pre-coating influenced both PC composition and secondary protein structures. Higher BSA concentrations (≥5 mg/mL) led to increased α-helix content and reduced cellular uptake of MWCNTs. Proteomic analysis revealed differential regulation of ribosomal and oxidative phosphorylation pathways at low BSA concentrations, whereas higher concentrations primarily affected mRNA surveillance pathways. These findings suggest that the protein corona composition dictates cellular interactions more than the intrinsic properties of MWCNTs. CONCLUSION: Pre-coating MWCNTs with BSA alters protein corona formation and downstream cellular responses in a concentration-dependent manner. Our results highlight the importance of surface modifications in nanomaterial biocompatibility and provide insights for designing safer nanocarrier systems. |
| Topic(s): Small Molecule > Metabolomics |
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Poster Presentation Poster #22d Attended on Thursday at 14:30
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Boronic Acid Mass Tags for the Specific Detection and Imaging of Diol Compounds
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Justine Gatein (Presenter) Université de Montréal
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| INTRODUCTION The advancement of on-tissue chemical derivatization techniques for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) of endogenous metabolites in tissues has attracted significant interest due to their benefits in enhancing detection sensitivity and ionization efficiency for poorly ionizable or/and low-abundance metabolites. Among these, glucose was found of high interest because of its implication in numerous diseases. The boron group of boronic acids exhibits high reactivity with compounds containing a diol function. Chemical derivatization enables the selective targeting of diols while enhancing the sensitivity and specificity of the method while reducing background noise, leading to more precise and reliable analysis. METHODS A new boronic acid containing a positively charged amine function was developed to compensate for the low ionization efficiency of compounds and enhance their detection in MSI. The analyte to tag ratio that allows for a complete reaction in solution and detection yield was first optimized. For MALDI MS of the 4-hydroxyestrone adduct, the best matrix was 9-aminoacridine (9AA) and it was 2′,6′-dihydroxyacetophenone (DHA) for the glucose adduct. For glucose, using brain homogenates, an optimized solution of 5mg/ml of boronic acid in 50% methanol was used to determine the best on-tissue reaction. Spray deposition parameters were then optimized for the boronic acid tag and DHA matrix. MALDI MSI was subsequently performed in the positive ion mode. Since the boron group has an easily recognizable isotopic signature, it is possible to more precisely identify the adducts that have reacted with the tag, in addition to confirming their identification by exact mass. For direct MALDI MSI glucose detection, N-(1-naphthyl) ethylenediamine dinitrate (NEDC) matrix was also spray deposited on all sections. MALDI MSI was then performed in the negative ion mode. RESULTS Boronic acid reactivity was initially tested in solution using several diol standards including 4-hydroxyestrone, ascorbic acid and several hexoses. In particular, we were able to successfully derivatize glucose in solution. After optimizing the reaction conditions (tag quantity, solvent, etc.), several matrices including 9AA, 1,5-dihydroxybenzoic acid, 1,5-diaminonaphthalene and DHA, were tested using the dry droplet method. For MALDI MSI, the tag and the matrix spray deposition method then were optimized. Thin tissue sections from mouse brain homogenates and different mouse organs were analyzed using the optimized methods using a Shimadzu MALDI iMScopeQT system. For glucose, the results were compared with MALDI MSI methods previously reported in the literature. Glucose was successfully detected in liver, kidney, testis and brain tissue sections (12 µm thick) by MALDI MSI at a spatial resolution of 25 µm using NEDC as matrix ([glucose + Cl]⁻, m/z = 215.032) and after on-tissue chemical derivatization with boronic acid ([glucose-boronic ac]+, m/z = 401.1868) using DHA as matrix with a mass accuracy ~1ppm. For liver and testis, glucose was homogenously detected across the sections. For brain, in all cases glucose was successfully detected predominantly in the gray matter. This distribution is consistent with that previously described in the literature, as the gray matter is the site of intense metabolic activity. For kidney, glucose was mostly detected in the medulla, which is again consistent with that previously described in the literature. However, when comparing glucose signal intensities between the ([glucose + Cl]⁻ NEDC produced ions and the ([glucose-boronic ac]+ ions, for brain, on-tissue chemical derivatization proved to be more sensitive by ~600-fold, while for liver, testis and kidney tissue, the detection improvements were ~800-fold, ~200-fold and ~70-fold, respectively. CONCLUSION As glucose metabolism is severely altered in many diseases, the development of MSI-based analytical methods is necessary to better understand local metabolism and potentially identify new therapeutic targets to increase treatment efficiency. By providing spatially resolved metabolic information, these methods offer valuable insights into disease-specific metabolic reprogramming and may contribute to the development of more effective, targeted therapeutic interventions. |
| Topic(s): Other -omics > Metabolomics > Metabolomics |
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Poster Presentation Poster #25c Attended on Thursday at 12:15
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Chemical Metabolomics – Innovative Chemical Biology Approaches to Investigate Gut Microbiome Metabolism
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Wawrzyniec Haberek (Presenter) Uppsala University
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| INTRODUCTION: The metabolism of the gut microbiota plays a critical role in shaping human physiology. Disruptions in this metabolic network have been associated with the onset and progression of various diseases. Despite its significance, the metabolic interactions between host and microbiome remain underexplored. Mass spectrometry (MS) is the gold standard for analyzing microbiome-derived metabolites due to its ability to resolve complex biological matrices such as plasma, feces, and urine. Profiling microbial metabolites holds promise for the discovery of novel bioactive compounds, disease biomarkers, and deeper insights into pathophysiological mechanisms. OBJECTIVES: A major limitation in MS-based metabolomics is the poor ionization efficiency of certain metabolite classes. This challenge underlines the need for new methodologies that enhance detection and broaden metabolite coverage. Our objective is to develop innovative chemical biology tools capable of identifying previously undetectable metabolites. METHODS: We have developed a suite of chemoselective probes tailored to derivatize specific functional groups of metabolites. These probes are combined with 13C/12C isotope labeling, enabling accurate quantification and comparative analysis. This platform, termed quantitative Sensitive CHEmoselective MetAbolomics (quant-SCHEMA), incorporates magnetic bead-assisted extraction for targeted isolation of metabolite classes. The method is compatible with various biological sample types and significantly enhances MS sensitivity, enabling detection of metabolites at attomole levels. RESULTS: Our chemoselective strategies enable the targeted analysis of several metabolite classes, including carbonyls, thiols, amines, and carboxylic acids. Using these tools, we confirmed the presence of clinically relevant, microbiota-derived metabolites in human samples. In a dietary intervention study involving 156 samples, we identified four novel food-derived biomarkers. These findings validate the robustness of our approach. We are now integrating quant-SCHEMA with standard metabolomics workflows in neuroscience, microbiome research, and biomarker discovery. CONCLUSION: We have successfully developed and implemented a powerful set of chemoselective tools for exploring host–microbiome metabolic interactions. To date, our work has led to the identification of over 300 previously unknown metabolites, the majority of which originate from gut microbial metabolism. Current efforts focus on characterizing the biological activity and functional roles of these newly discovered compounds RERERENCES: (1) Lin W et al., Angew. Chem. Int. Ed. 2021, 60, 23232. (2) Kaur A et al., Chem. Sci. 2023, 14, 5291. (3) Garg N et al., Angew. Chem. Int. Ed. 2018, 57, 13805. (4) Lin W et al., Chem. Commun. 2023, 59, 5843. (5) Conway L. P. et al., Chem. Commun. 2019, 55, 9080. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine > Tox / TDM / Endocrine |
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Poster Presentation Poster #26b Attended on Wednesday at 12:15
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LC-MS/MS Method Development and Validation for Quantification of Steroids in Serum
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Younus Mohammad (Presenter) Canterbury Health Laboratories >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: An accurate, precise and rapid measurement of steroids is crucial in diagnosis, monitoring and providing personalised treatment for many disorders, such as Cushing’s syndrome, Addison’s disease and congenital adrenal hyperplasia. Compared to traditional immunoassays LC-MS/MS provide more specificity, sensitivity and accuracy in measuring very low levels of steroids. OBJECTIVE: The aim of present work was to develop a simple LC-MS/MS method for the simultaneous quantification of eight steroid hormones: aldosterone, cortisol, 11-deoxycortisol, 21-deoxycortisol, androstenedione, 17-hydroxypregnenolone, testosterone, 17-hydroxyprogesterone, and dihydrotestosterone (DHT). METHODS: Supported liquid extraction was used for sample preparation. Chromatographic separation was achieved on a Cortecs premier C18 column, and 0.05 mM ammonium fluoride in water (+ 2% v/v methanol) and 0.05 mM ammonium fluoride in methanol (+2% v/v water) were employed as mobiles phase solvents. The analytes were detected on Water TQ-XS system, aldosterone was assessed in negative mode and all other analytes were assessed in positive mode. Chrome system calibrators and quality control samples (panel 1 and panel 2) were used. The method was validated for selectivity, sensitivity, accuracy, precision, recovery studies, effect of matrix and dilution integrity. The method also used quality assurance samples for external comparison and was compared against an external laboratory (Pathology Queensland, Australia). RESULTS: The analytical run was less than 10 mins. The validation results were found to be within acceptable limits, accuracy <15% compared to reference samples and % CV <10%. Passing-Bablok regression analysis for the method comparison study was within acceptable limits. CONCLUSIONS: The method can be a useful tool in determination of steroids in both clinical and scientific laboratory research. |
| Topic(s): Small Molecule > Spatialomics > none |
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Poster Presentation Poster #26c Attended on Thursday at 12:15
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Spatial Multi-Omics Using DESI Imaging-Guided Laser Microdissection for LC-MS/MS Proteomics
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Brittannie Willis (Presenter) Imperial College London
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| INTRODUCTION: Glioblastoma (GBM) is a highly aggressive and treatment-resistant brain cancer with a poor prognosis, presenting significant challenges to effective treatment despite interventions including surgery, radiation, and chemotherapy. The tumour's genetic mutations and immune microenvironment contribute to treatment resistance, further complicating therapeutic strategies. To improve clinical outcomes, it is critical to understand GBM's molecular heterogeneity in response to treatment and explore innovative metabolic therapeutic strategies, such as arginine deprivation. To understand drug responses in GBM, it is essential to consider the spatial context of proteins and metabolites within the tumour and its microenvironment. A powerful approach is the ability to capture metabolomic and proteomic data from the same tissue section. Mass spectrometry imaging (MSI) techniques, such as matrix-assisted laser desorption/ionisation (MALDI-MSI) and desorption electrospray ionisation mass spectrometry imaging (DESI-MSI), are valuable tools for metabolomic and lipidomic analyses. However, they do not provide the same depth of proteomic coverage as liquid chromatography-tandem mass spectrometry (LC-MS/MS). Furthermore, spatial multi-omics approaches often face challenges, such as poor protein recovery due to laser ablation or interference from embedding matrices, leading to biases in spatial representation. Additionally, many workflows often require consecutive tissue sections, which introduces variability and may cause loss of spatial context. To address these limitations, we have developed a spatially resolved multi-omics pipeline that integrates DESI-MSI for metabolomic imaging with LC-MS/MS-based quantitative proteomics from a single tissue section. OBJECTIVE: To develop a spatially resolved multi-omics pipeline that integrates DESI imaging-guided laser microdissection with LC-MS/MS proteomics, enabling enhanced molecular profiling from a single tissue section while preserving spatial context. METHODS: Fresh-frozen mouse brain tissue was sectioned at 8 μm thickness and analysed using DESI-MSI on a XEVO-G2-XS-QTOF mass spectrometer (Waters) to acquire spatial metabolomic profiles. Data were acquired in both positive and negative ion modes, with a spatial resolution of 50–100 μm. Data processing was performed using an in-house MATLAB pipeline for spectral preprocessing and peak picking. Regions of interest (ROIs) were identified based on high metabolomic intensities and resected using laser microdissection (Leica LMD7). Proteins from these resected ROIs were extracted, digested using trypsin, and analysed via LC-MS/MS on a ZenoTOF 7600 mass spectrometer (SCIEX). Peptides were separated using a 2.6 μm Kinetex XB-C18 100 Column, 150 × 0.3 mm (Phenomenex). Both DESI-MSI and LC-MS/MS conditions were optimised to maximise protein recovery while preserving spatial integrity. Database searching was performed using DIA-NN (version 1.8.1) and FragPipe (version 21.1) for protein identification and quantification. RESULTS: Our pipeline successfully combines spatial metabolomics and proteomics, preserving sample integrity and enhancing reproducibility. Over 1,100 proteins were identified with high sensitivity and spatial resolution within 10 × 10 μm ROIs, enabling detailed and comprehensive molecular profiling. By eliminating the need for consecutive tissue sections, variability was minimised, allowing for direct comparisons between metabolic and proteomic data. Additionally, optimised DESI-MSI conditions ensured maximal protein recovery, supporting accurate downstream analyses and a deeper understanding of molecular processes. CONCLUSION: In conclusion, we demonstrate the basis for a spatially resolved multi-omics workflow that integrates DESI-MSI and LC-MS/MS, enabling high-resolution mapping of both metabolites and proteins from a single tissue section. This approach overcomes the limitations of traditional methods by maximising data extraction while maintaining the spatial resolution, making it particularly advantageous for studies involving rare or limited clinical samples. Using mouse brain tissue as a model, we highlight the potential of our pipeline to uncover detailed differences in tissue composition through region-specific molecular profiling. This method offers a robust, quantitative approach for tissue profiling, with strong potential for advancing our understanding of therapy response and biomarker discovery. Our approach enables relative quantification by scaling spatial signals against a bulk reference channel and has demonstrated sensitivity in detecting 10 × 10 µm ROIs, ensuring robust and reproducible results. We believe that this workflow has the potential for widespread application in both research and clinical settings, facilitating the broader adoption of spatial multi-omics across diverse tissue types and disease models. |
| Topic(s): Proteomics > Proteomics |
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Poster Presentation Poster #33a Attended on Wednesday at 09:15
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Profiling Cysteine Phosphorylation via Mass Spectrometry
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Luba Mahbub (Presenter) McGill University
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| INTRODUCTION: Cysteine phosphorylation in proteins plays a regulatory role in signaling but remains underrepresented in phosphoproteomics due to its transient and chemically labile nature. Phosphatases of regenerating liver (PRLs) are cystine-based phosphatases that form a stable phosphocysteine intermediate during catalysis, which can accumulate endogenously in cells. All three human PRL isoforms are involved in cell growth and magnesium homeostasis and are frequently associated with cancer metastasis. Although both their catalytic and non-catalytic functions have been implicated in promoting metastasis, the underlying mechanism remains poorly understood. Quantifying phosphocysteine levels in cells and tissues may provide insight into their role in tumor progression. OBJECTIVES: The absence of PRL isoform-specific antibodies, combined with the acid- and heat-labile nature of phosphocysteine, has limited its characterization in biological systems. This study aims to establish a derivatization-based mass spectrometry workflow for the quantitative detection of PRL cysteine phosphorylation. A broader goal is to determine whether other cellular proteins also harbor stable cysteine phosphorylation. METHODS: Cell lysates or purified protein samples were first denatured, and free cysteine residues were reduced and alkylated to prevent nonspecific labeling. Phosphocysteine was then hydrolyzed by controlled heating, converting it to reactive thiols. The newly exposed thiols were selectively labeled with maleimide-based reagents. Labeled proteins were enriched using affinity purification, followed by tryptic digestion. Phosphocysteine-derived peptides were identified and quantified by mass spectrometry. RESULTS: A robust workflow was developed for detecting cysteine phosphorylation in recombinant PRLs under denaturing conditions. Denaturation in guanidine hydrochloride rendered the phosphocysteine intermediate more resistant to premature hydrolysis, enabling its preservation throughout the initial steps of the workflow. Following thermal hydrolysis, selective labeling of phosphocysteine-derived cysteines was achieved using biotin-maleimide. Labeled peptides from recombinant PRL2 expressed in E. coli were reliably detected by both MALDI-TOF and LC-MS/MS. NeutrAvidin-based enrichment of biotinylated proteins significantly enhanced detection sensitivity, allowing confident identification of modified peptides over background. Systematic optimization of reduction, alkylation, and labeling steps minimized nonspecific reactivity and improved recovery of phosphocysteine-derived peptides. CONCLUSION: This workflow offers a reliable, MS-compatible approach for the selective detection of cysteine phosphorylation in PRLs and is adaptable to other phosphocysteine-containing proteins. Future work will apply this strategy to mammalian cells and tissues to evaluate phosphocysteine levels in PRLs and explore their contribution to metastatic cancer. |
| Topic(s): Other -omics > Tox / TDM / Endocrine |
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Poster Presentation Poster #33d Attended on Thursday at 14:30
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Performance Evaluation of Reflex Tg-MS testing in TgAb-positive Samples: A Retrospective Concordance Analysis with Immunoassay
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Preejith Vachali (Presenter) Cleveland Clinic
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| BACKGROUND: Thyroglobulin (Tg) is an essential biomarker for monitoring differentiated thyroid cancer. However, the presence of Tg antibodies (TgAb) can interfere with Tg measurements obtained by immunoassays. To address this, reflex testing using a mass spectrometry-based Tg assay (Tg-MS) is employed when TgAb levels exceed a defined threshold. But recent literature findings have raised concerns regarding the validity of using a fixed TgAb threshold to trigger reflex MS testing (1). Expert recommendations now suggest that MS test may not be needed if Tg is <0.1 µg/L with no evidence of structural disease (1). This study assesses the analytical agreement and correlation between Tg-MS (LC-MS/MS) and the initial Beckman Tg immunoassay in TgAb-positive samples.
OBJECTIVE: To determine if reflex testing with the Tg- MS assay is necessary in TgAb-positive samples by evaluating its concordance with the initial Beckman Tg immunoassay, and whether strong agreement between the two methods supports limiting or omitting reflex testing in certain clinical scenarios. METHODS: Consecutive tests from March 2023 to February 2025 included 484 unique patients, and 928 total of Tg measurements. Tg values were assessed using two assays: an initial Beckman Tg immunoassay for all samples, with reflex Tg-MS testing conducted only for those with elevated TgAb (>4 IU/mL). Analytical focus was placed on values ≥0.5 ng/mL due to differences in detection thresholds (Beckman: ≥0.1 ng/mL, Tg-MS: ≥0.5 ng/mL). Tg values were categorized as <1, 1–2, and >2 ng/mL based on clinical cut-offs. Descriptive statistics were applied to demographic and assay data, using medians and interquartile ranges for non-normally distributed continuous variables, and frequencies and percentages for categorical variables. Non-normality was confirmed for both Tg assays, and log transformations failed to achieve normalization. Spear-man correlation analysis was performed to assess the strength and direction of association be-tween assays. To handle repeated measures, rank-transformed values were analyzed using the rmcorr package in R to produce within-subject correlation coefficients. Concordance correlation coefficient (CCC) was calculated based on a mixed-effects Poisson regression model incorporating random intercepts for patient ID, assay type, and their interaction, as per Tsai and Lin’s method (2) for non-normal distributions. The delta method was used to estimate 95% confidence intervals (CI). All analyses were conducted using SAS 9.4 and R version 4.3. RESULTS: The patient cohort had a median age of 57 years (IQR: 42–69), with 80.1% female. Across all 928 observations, the median Beckman Tg was 0.1 ng/mL and Tg-MS was 0.5 ng/mL. When restricted to values ≥0.5 ng/mL, Beckman Tg also had a median of 0.5 ng/mL, indicating baseline alignment with Tg-MS. The median absolute difference between assay values was 0.0 ng/mL, confirming minimal deviation. Among 624 observations with Beckman Tg levels <0.5 ng/mL, 93.7% also had Tg-MS below this threshold. Conversely, of the 262 observations with Beckman Tg >0.5 ng/mL, 95.8% showed corresponding Tg-MS values >0.5 ng/mL. The Spearman correlation coefficient between Tg-MS and Beckman Tg was 0.60 (95% CI: 0.53–0.65, p<0.001), indicating moderate positive correlation. The CCC was 0.98 (95% CI: 0.96–1.00, p<0.001), reflecting very strong agreement. The discrepancy between correlation and concordance is attributed to the non-linear relationship between values, suggesting that although trends are only moderately aligned, individual test values are nearly identical. Among the 484 unique patients, 57.2% had a single Tg measurements, while the remainder had multiple Tg measurements over time, enabling robust within-subject repeated measures correlation analysis. CONCLUSIONS: This analysis demonstrates a very high level of concordance between Tg-MS and Beckman Tg assays in TgAb-positive samples. While Tg-MS is currently performed reflexively when Tg anti-bodies are elevated, the strong agreement observed raises the question of whether reflex testing is always needed. In cases where Beckman Tg and Tg-MS values align closely, it may be reasonable to reconsider the routine necessity of reflex testing, particularly in settings where assay agreement is reliably high. However, further prospective testing and validation would be required before modifying clinical protocols. REFERENCES: 1. Giovanella L., et al., hsTg&TgAb Consensus Working Group. Thyroglobulin and thyroglobulin antibody: an updated clinical and laboratory expert consensus. Eur J Endocrinol, 2023 189(2): R11-R27. 2. Miao-yu T and Chao-Chun L., Concordance correlation coefficients estimated by variance components for longitudinal normal and Poisson data. Comput Stat and Data An, 2018. 121 p. 57-70. |
| Topic(s): Other -omics > Breath Analysis and VOC |
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Poster Presentation Poster #34a Attended on Wednesday at 09:15
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Breath VOC Profiling for Pre-Diabetes and Type 2 Diabetes Using TD-GC-TOF-MS: A South Asian Cross-Sectional Study
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Trenton Stewart (Presenter) Warwick University
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| INTRODUCTION: Type 2 diabetes mellitus (T2DM) is an escalating global health concern, with over 463 million people affected worldwide as of 2019 — a number projected to reach 700 million by 2045. In Nepal, the burden is rising rapidly, with recent estimates suggesting that approximately 10% of the adult population now lives with T2DM. Factors such as urbanization, changing diets, sedentary lifestyles, and limited access to preventive care are contributing to the steep rise in prevalence across South Asia. Current diagnostic strategies—such as fasting blood glucose and HbA1c tests—require blood sampling and are often underutilized in low-resource settings due to infrastructure, cost, and patient discomfort. These methods also fail to detect early metabolic changes before clinical thresholds are crossed. Exhaled breath contains volatile organic compounds (VOCs) that reflect underlying metabolic processes, and several studies have shown altered VOC profiles in individuals with diabetes. Acetone, for example, was first identified in diabetic breath as early as the 19th century and remains one of the most studied VOCs linked to glucose metabolism. Breath analysis represents a non-invasive, painless, and potentially real-time method of screening for metabolic disease. This study aims to evaluate the utility of breath VOC profiling for detecting pre-diabetes and T2DM in a South Asian cohort, using thermal desorption–gas chromatography–time-of-flight mass spectrometry (TD-GC-TOF-MS). The goal is to support the development of a portable, clinically relevant, and cost-effective diagnostic tool suitable for widespread screening in resource-constrained settings. METHODS: This cross-sectional validation study is set to recruit 240 participants from clinical sites in Nepal, including 80 healthy controls, 80 individuals with pre-diabetes, and 80 individuals with T2DM. This study is ensuring statistical power through a sample size calculation with a 95% confidence and accounting for 5% type 1 errors alongside the 50% prevalence, a total of 146 participants would be required. At least 73 diabetic participants and 73 controls would need to be recruited to ensure the power of the sensitivity and specificity of the study. Each participant will provide two exhaled breath samples, one fasting and one postprandial, collected using a BIO-VOC2 breath sampler. For each sampling, five full exhalations will be overlaid onto a single thermal desorption (TD) tube to enhance compound detection. After collection, TD tubes will be sealed and stored in a cooler at 4 °C, then transported under refrigerated conditions to the Biomedical Sensors Laboratory at the University of Warwick (UK) for analysis. Breath VOC samples were analysed using a TD-GC-TOF-MS system. Chromatographic peaks were deconvoluted and integrated using Chrome Compare™ software. The resulting VOC data were analysed using multivariate statistical analysis and machine learning (ML) techniques to identify compound features capable of differentiating between glycaemic and healthy classifications. ML models included Random Forest, XGboost, and Logistic Regression. Feature selection was based on the Mann–Whitney U test, with Benjamini–Hochberg false discovery rate (FDR-BH) correction applied to control for multiple comparisons. Ethical approval for this study was granted by the Nepal Health Research Council (NHRC), reference number 3833, and the Manmohan Memorial Medical College Research Committee (MMMC-RC), reference number 1471079180. Written informed consent was obtained from all participants prior to enrolment. RESULTS: Preliminary multivariate analysis was conducted on a subset of 132 participants: 51 healthy controls, 35 individuals with pre-diabetes, and 46 individuals with T2DM. These preliminary analyses revealed several VOCs with statistically significant differences between glycaemic classifications. In the Healthy vs pre-diabetic group, Longifolene achieved significance after multiple testing correction (adjusted p = 0.028). In the pre-diabetic vs T2DM group, Nonadecane (adjusted p = 0.017), Octadecane (p = 0.019), and Silanediol, dimethyl- (p = 0.025) also remained significant following FDR correction. While no VOCs reached statistical significance in the Healthy vs Diabetic group after FDR correction, several compounds showed strong combined p-values in other comparisons. Notably, Cyclohexane (corrected p = 0.061) in the Healthy vs pre-diabetic group and 2-Pentanone (corrected p = 0.073) in the pre-diabetic vs T2DM group demonstrated significant raw and combined p-values. As these are preliminary results, it is expected further discriminatory markers may be identified as the further data is collected. CONCLUSION: Preliminary results from this validation study indicate that breath VOC profiling using TD-GC-TOF-MS can differentiate between glycaemic states in a South Asian population. Several compounds, including Longifolene, Nonadecane, and Octadecane, showed statistically significant differentiation between classification groups. These preliminary findings support the potential of breath analysis as a non-invasive, low-burden tool for early identification of individuals at risk of pre-diabetes and type 2 diabetes, particularly in resource-limited settings. As data collection continues, it is anticipated that further discriminatory markers will be identified, strengthening the clinical utility of this approach. |
| Topic(s): Proteomics > Proteomics > none |
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Poster Presentation Poster #34b Attended on Wednesday at 12:15
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Development of a Ready-To-Use Evotip-Based Workflow for Plasma Protein Quantification
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Elodie Logerot (Presenter) Segal Cancer Proteomics Centre, Jewish General Hospital
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| INTRODUCTION: Accurate and reproducible quantification of plasma proteins poses a significant challenge to mass spectrometry-based proteomics due to its high dynamic range and inherent matrix complexity. Highly abundant proteins can mask the detection of biologically relevant, low-abundance species, and matrix effects and batch-to-batch variability further complicate quantitative analyses. As part of the SysQuan project, we use stable isotope-labeled mouse plasma (SILAC) as an internal standard for absolute quantification, which helps us address these limitations and improve consistency between workflows. Our goal is to develop an innovative, solution that will streamline plasma proteomics and enable its routine use in clinical and research environments. OBJECTIVE: The long-term goal is to create Evotips preloaded with SILAC mouse plasma, which will enable the direct addition and subsequent digestion of human plasma samples for quantification. This system is designed to be a robust tool for absolute protein quantification in clinical and research applications. METHODS: Currently, method development and optimization are based on human plasma samples. A "one-pot" digestion strategy is employed directly on Evotips to ensure compatibility with high-throughput workflows. This digestion protocol eliminates transfer steps and reduces sample handling errors by sequentially adding denaturation, reduction, alkylation, and digestion reagents directly onto the Evotip. Resulting digests were analyzed using an Evosep One LC system coupled with a timsTOF HT mass spectrometer operating in DIA-PASEF mode. Data were analyzed using a spectral library generated from fractionated, depleted and non-depleted plasma, and identification was performed using DIA-NN. RESULTS: On average, 450 proteins and 3,500 peptides were consistently identified in all technical replicates per sample. The workflow demonstrated high reproducibility, with coefficients of variation below 15% between replicate analyses. Notably, 91% of the proteins identified using the conventional S-Trap-based workflow were recovered during the "one-pot" digestion on Evotips. This significant overlap underscores the analytical depth of the streamlined protocol while significantly reducing processing times and preparation steps. Furthermore, around 75% of the peptides detected using the Evotip approach overlap with those included in the SysQuan panel (i.e., lysine-containing and shared between mouse and human), underlining the method's compatibility with absolute quantification pipelines. These initial results validate the digestion strategy on Evotips and support its integration into SILAC-based quantification workflows, including MRM or PRM-PASEF methods developed on a triple quadrupole mass spectrometer such as the Agilent 6495D or timsTOF HT as part of the SysQuan project. CONCLUSION: We present a reproducible and simplified method for plasma proteome analysis using Evotips that yields promising results in terms of protein and peptide coverage. The next phase of this project will implement SILAC mouse plasma on the Evotips to serve as a protein-level internal standard, which will enable robust quantification. The ability to integrate an internal standard directly into the Evotip format paves the way for standardized, plasma quantification solutions, with potential applications in translational research and routine workflows. REFERENCES: Ye, Z., Sabatier, P., Martin-Gonzalez, J. et al. One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes. Nat Commun 15, 2474 (2024). https://doi.org/10.1038/s41467-024-46777-9. |
| Topic(s): Spatialomics > Spatialomics : Pathology and Biomarkers > Metabolomics |
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Poster Presentation Poster #35c Attended on Thursday at 12:15
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Identifying ‘DESI’red Prognostic Features of Human Ductal Carcinoma In Situ and Invasive Ductal Carcinoma using Spatialomics
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Natasha Iaboni (Presenter) Queen's University
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| INTRODUCTION: Breast cancer is the leading cause of new cancer cases and second leading contributor to cancer-related deaths among Canadian women. In 2024, ~30,500 Canadian women were diagnosed with breast cancer, and >5500 women died of breast cancer related complications. Between 20-25% of all breast cancer cases diagnosed were classified as ductal carcinoma in situ (DCIS), a form of breast cancer that presents as an abnormal epithelial cell population contained within the breast ducts. While DCIS is non-invasive, it may act as a precursor to invasive ductal carcinoma (IDC) by growing through the ducts and invading surrounding tissue. Women diagnosed with DCIS face challenging treatment decisions due to our current inability to predict the risk of DCIS tumour invasiveness or DCIS recurrence. Due to these knowledge gaps, many women are over treated with aggressive therapies, leading to physical and mental distress, surgical comorbidities and an overall lower quality of life. Our lab is interested in the peroxisome proliferator-activated receptor γ (PPARγ), a key nuclear transcriptional regulator of lipid and sugar metabolism, and known to stop the growth and spread of breast tumours. Activation of PPARγ signaling via endogenous fatty acids and anti-inflammatory prostaglandins suppresses breast tumour progression via many putative signaling pathways, which are often cell and context specific. PPARγ-dependent protective pathways may include increasing expression of tumour suppressor genes such as BRCA1 or PTEN, decreasing inflammatory pathways by downregulating COX-2, and/or promoting apoptosis-related genes, all leading to decreased growth and spread of breast tumours. Notably, a report of increased PPARγ expression was associated with lower grade DCIS versus invasive breast cancer samples, suggesting PPARγ may normally act to reduce the invasive progression of DCIS. It remains unknown if loss of PPARγ signaling, common in some forms of aggressive breast tumours, plays a role in the transition from DCIS to IDC. OBJECTIVE: To address these clinical challenges, the primary objective of this study is to define the metabolomic profiles of human ex vivo DCIS and IDC tumours to enrich the pathological prognostic information available at time of diagnosis. METHODS: Formalin fixed and paraffin embedded (FFPE) human ex vivo DCIS/IDC tumour samples (n=8 DCIS, n=16 DCIS/IDC, n=10 IDC, n=34 total)) were obtained from the Kingston Health Sciences Centre. Sections of FFPE tissues were deparaffinized and then assessed using desorption electrospray ionization-mass spectrometry imaging (DESI), over a spectrum of m/z 50-1200 in negative ionization scanning mode, using a spatial resolution of 100um. The DESI-analyzed slides were then stained and annotated by a pathologist for DCIS, IDC, and non-tumour pathological regions. Of the n=34 FFPE samples, n=17 had additional corresponding tissues that were embedded in OCT and DESI assessed to serve as a direct comparison to the analytes detected via FFPE. The pathologist-guided annotations and DESI 2D heatmaps were then meticulously overlaid with one another using the imaging analysis SlicerMSI software MassVision. Regions of Interest (ROI’s) composed of nine 100X100um pixels were plotted in each pathological zone per slide and merged to form one mean spectra per ROI. A total of n=38,757 ROI’s were selected across 5 pathological zones. Supervised machine learning was conducted along with binary statistical analysis to identify highly significant (p<0.001) ions that had a Log2 fold change >1.5 between DCIS and IDC pathological regions. To complement the metabolomic expression profiles, the samples were assessed using immunohistochemistry (IHC) to obtain an H-Score (intensity x percent positivity) of specified protein expression. RESULTS: Notable ions significantly elevated in FFPE IDC versus DCIS tissues included 6 different omega-6 fatty acids such as Linolenic acid (m/z 279.2303), Arachidonic acid (m/z 303.2301) and Docosatetraenoic acid (m/z 331.2600). Omega-6 fatty acids are involved in the production of pro-inflammatory molecules such as pro-tumorigenic prostaglandins (PGs) from arachidonic acid metabolism, which promote invasiveness, progression and immunosuppression. In contrast, we observed the anti-inflammatory PG 15-Deoxy-d-12,14-PGJ2 (m/z 315.11) was significantly increased in FFPE DCIS versus IDC tissue. Interestingly, 15d-PGJ2 is also a natural ligand of PPARγ, and reported to induce apoptosis and decrease oxidative stress via PPARγ activation. The samples were then stained for PPARγ using IHC to define PPARγ expression within DCIS, IDC and surrounding benign tissues. Our data suggest a significant increase in PPARγ expression both within benign glands and ducts, and in DCIS versus IDC. PPARγ expression was not significantly different when comparing benign glands and ducts to DCIS. Within our cohort, there were no significant differences between intermediate versus high DCIS grades or moderate versus high IDC grades. CONCLUSION: This data suggests the significant increased expression of 15d-PGJ2 and PPARγ within DCIS versus IDC samples may aid in revealing the aggressive potential of these tumours and as well as further our understanding of those patients who are at risk for progression. Taken together, our findings also suggest a decrease in PPARγ expression correlates to progression from DCIS to IDC. Validating these expression profiles will allow us to provide pathologists with potential prognostic targets that may be routinely used to help optimize clinical treatment decision-making for DCIS patients. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine > Lipidomics |
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Poster Presentation Poster #43a Attended on Wednesday at 09:15
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Reducing False-Positive Phosphatidylethanol (PEth) Quantification in Alcohol Testing via Isobaric Lipidome Analysis and Interference Correction
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Ching-Hua Lee (Presenter) National Taiwan University
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| INTRODUCTION: Phosphatidylethanol (PEth) is a widely used biomarker for alcohol consumption in clinical and forensic settings. A consensus establishes that a blood PEth(16:0/18:1) concentration >20 ng/mL strongly indicates alcohol use. However, studies show that single drinking events with blood alcohol concentrations (BAC) of 0.3–0.5 g/kg or daily consumption of ~16 g ethanol for three months typically do not result in median PEth levels exceeding 20 ng/mL in collected post-drinking. For stricter monitoring of alcohol consumption in patients with alcohol-related liver disease (ALD) or those awaiting liver transplantation – where stringent alcohol control is critical - lowering the cutoff for PEth using LC-MS/MS is necessary. However, reducing the cutoff often increases false-positive results, potentially causing patient conflicts or delaying surgeries. Given that PEth is biosynthesized only in the presence of ethanol, we hypothesize that co-eluting phospholipid isobars in commonly used LC-MS/MS configurations contribute to false positives and inaccurate quantification. In this study, we apply a lipidomics approach to identify interference sources and optimize PEth analysis strategy to lower the cutoff concentration without compromising specificity. METHODS: Fifteen participants were enrolled: six with no alcohol consumption history in recent months and nine who self-reported past drinking habits. Three pooled samples were analyzed: (1) pool blank (n=6), (2) pool drinker (n=9), and (3) pool-QC (1:1 mix of pools 1 and 2). Lipidomics analysis of whole blood was performed using an Agilent 6545XT QTOF with iterative data-dependent analysis (DDA). Agilent 6460 and 6495 QQQ instruments, operating in different scan modes, identified interference sources to complement QTOF data. Multiple reaction monitoring (MRM) was used to develop quantitative methods for PEth homologues and interfering lipids. Whole blood samples (50 μL) were extracted using a modified Folch method. Lipid separation was performed using an Agilent Eclipse Plus C18 RRHD and a Phenomenex Kinetex C8 column. Mobile phase and gradient settings were evaluated to investigate relative retention time (RT) shifts between PEth and lipid isobars. PEth identification criteria included: (1) mass accuracy <20 ppm by HRMS and (2) retention time alignment with PEth(16:0/18:1) synthetic standard and equivalent carbon number (ECN) estimation. RESULTS: We identified 11 PEth homologues and their interfering lipid isobars, which follow specific co-elution patterns: PEth(X:Y) co-elutes with PS(X+2:Y) and PA(X+2:Y+1), where X and Y represent the total carbon number and double bonds on the acyl chain, respectively. For instance, PEth(16:0/18:1) (m/z 701) is affected by in-source fragmentation (ISF) of PS(18:0_18:1) (m/z 788→701) and PA(36:2) isomers (m/z 699), including PA(18:1_18:1), PA(18:0_18:2), and PA(16:0_20:3). These interferences persist across various LC settings and are influenced by skimmer voltage and elution conditions. To evaluate the impact of ISF from PS(18:0_18:1) on PEth(16:0/18:1) quantification, we used an the optimal skimmer voltage (170–190 V), determined with a synthetic standard. This resulted in ~3% ISF, leading to overestimation of MRM 701→281 to 40 ppb in pool blank samples under LC conditions with adequate separation (RT 5.3 min), demonstrating that ISF causes significant false-positive quantification. Further evaluate the interferences other than ISF, we used an Agilent 6495 QQQ with an ion funnel to minimum ISF (< 0.5%) from PS(18:0_18:1). Pool blank spiked with 20 ppb PEth(16:0/18:1) yielded quantification result of 22 ppb (MRM 701→255) and 25 ppb (MRM 701→281) with adequate separation. Based on co-elution patterns and quantification results, we selected MRM 701→255 as the final quantifier to minimize interferences. However, high-throughput LC settings (RT 1.8 min) increased the quantification result to 24.7 ppb for MRM 701→255 due to compressed lipid elution times, causing co-elution of FA(16:0) fragments from multiple sources. Further investigating the interferences suggested that lipids generating MRM 700→255 contribute approximately 24% of the [M+1] isotope to MRM 701→255. By mathematically subtracting isotopic interference yielded a final concentration with > 90 % accuracy. The optimized PEth quantification strategy - MRM 701→255 transition with isotope correction - enabled cutoff level to be lowered to 5 ppb with high specificity. CONCLUSION: Using a QTOF iterative-DDA lipidomics approach combined with QQQ instruments and various scan modes, we identified interference sources for PEth(16:0/18:1) analysis and developed an analytical strategy to minimize interference and improve quantification accuracy. These adjustments enable a lower PEth cutoff without compromising specificity, enhancing the reliability of alcohol consumption monitoring for ALD and liver transplant patients. |
| Topic(s): Proteomics > Assays Leveraging Technology |
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Poster Presentation Poster #43d Attended on Thursday at 14:30
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NexProQ: Multiplexed Quantitation of 500+ Proteins in Whole Blood and Dried Blood Spots Using PRM-PASEF and TMTpro
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Laleh Ebrahimi Ghahnavieh (Presenter) McGill University / Jewish General Hospital
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| INTRODUCTION: Quantitative proteomics in clinical samples have remained constrained by limited multiplexing capacity, high reagent costs, and low sample throughput. To address these limitations, we developed NexProQ, a novel platform combining TMTpro multiplexing with PRM-PASEF acquisition on the timsTOF HT. This approach enables us simultaneous absolute quantitation of over 500 protein targets in whole blood (WB) and dried blood spot (DBS) samples in a single run. METHODS: Proteotypic peptides were selected from 500+ clinically relevant targets and synthesized as unlabeled NAT standards. Internal calibration curves were prepared using TMT-pro 18-plex labels and peptide dilutions (spanning 1000× to 1× of the lower limit of quantitation (LLOQ)) mixture to reach five-point internal calibration curves. Then multiplexed with plasma and DBS digests preloaded onto EvoTips. Peptides analysis has been done at 30SPD using PRM-PASEF, and assay performance was assessed in terms of linearity, limits detection, intra-assay reproducibility, and matrix effects. RESULTS: Assay linearity was robust across most targets (R² > 0.98), with median LLOQs of 0.1–0.5 fmol on-column. Utilizing non-adjacent TMTpro reporter ions boosts quantitation reproducibility and decreases interference due to isotopic overlap. Most targets' intra-assay CVs are below 5%, hence quantitation is reproducible across different protein concentrations and sample types. Comparison across platforms illustrates the higher mass accuracy and consistency of reporter ion intensities on the QE+, while PRM-PASEF enables superior throughput. The strong concordance for high-abundance proteins has done by validating 274-peptide panel against reference MRM data. CONCLUSION: NexProQ offers significant escalating for scalability and accessibility of clinical proteomics. Its capacity to quantify hundreds of proteins across multiple samples within minutes supports its advantages in biomarker discovery, clinical validation, and large-cohort screening studies. This study paves the way for population-scale proteomic screening with performance exceeding current antibody- or aptamer-based methods. Commercial kit development is in progress to support standardization across labs. |
| Topic(s): Small Molecule > Metabolomics |
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Poster Presentation Poster #44a Attended on Wednesday at 09:15
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Urinary Metabolomics to Identify Diagnostic Biomarkers of Delirium: A Pilot Study
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Zaineb Hamoodi (Presenter) McMaster University
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| INTRODUCTION: Delirium is a condition characterized by fluctuating changes in cognitive function, attention, memory, and consciousness. Delirium is not known to be caused by one specific factor; rather, it is the balance between predisposing factors such as age, cognitive impairment, and comorbidities, as well as precipitating factors such as polypharmacy, infection, and surgery. Therefore, the rates of delirium in older adults who undergo anesthesia and surgery are especially high, with rates varying depending on the type of surgery that is performed. For example, patients who undergo hip fracture repair surgery develop post-operative delirium up to 53% of the time(1). Despite its frequency, delirium is often missed and underdiagnosed in clinical settings, leading to greater risk for injuries, mortality and prolonged hospitalization with persistent symptoms after hospital discharge. Current strategies for detecting delirium rely on subjective measures, where nurses and clinicians must observe changes in the cognitive function of their patients, with delirium assessed via the Confusion Assessment Method (CAM). Alternatively, urinary biomarkers for early detection of delirium may offer a more objective and less biased approach for risk assessment and/or diagnosis of vulnerable patients. OBJECTIVE: This project aims to apply metabolomics to identify a panel of urinary biomarkers that enable the prognosis and/or diagnosis of delirium onset in older patients following hip surgery using capillary electrophoresis-mass spectrometry (CE-MS). METHODS: In this pilot study, 56 urine samples from 9 patients (8 females, 1 male; mean age: 89; 2 total CAM+ patients) who underwent hip fracture repair surgery were collected over a period of 1 month along with the administration of a CAM assessment. The urine samples were analyzed using multisegment injection-CE-MS (MSI-CE-MS) to measure polar/ionic metabolites in both positive and negative mode. A targeted metabolomic approach was used using an authenticated list of known urinary metabolites, where their integrated peaks were normalized to an internal standard and hydration status adjusted for creatinine. After removing redundant, unreliable, and spurious signals, the data was analyzed using a partial least-squares-discriminant analysis (PLS-DA) model to rank urinary metabolites associated with CAM-positive delirium patients. Also, a receiver operating characteristic (ROC) curve was applied to identify a urinary metabolite ratio that differentiated delirium from delirium-free patients after hip surgery. RESULTS: The PLS-DA model showed that there was good separation between CAM-positive and CAM-negative patients. Two high ranking urinary metabolites (VIP score > 1.8) in this model were putatively identified as uric acid and phenylalanine. A ratiometric ROC curve using uric acid and phenylalanine was determined to provide the optimal discrimination between CAM-positive delirium patients to CAM-negative controls with an area under the curve (AUC) of 0.947 (p < 0.001). DISCUSSION: Changes in large neutral amino acids has often been implicated in the pathophysiology of delirium. For example, phenylalanine has been shown to be increased in serum in patients who developed post-operative delirium(2). In our urine samples, we observed a similar trend, with phenylalanine increased in CAM-positive patients. Additionally, lower uric acid in serum has been shown to be a risk factor for post-operative delirium in older patients(3). Similarly, our results also showed that lower uric acid correlated with a CAM-positive assessment. To further support these results, a ROC curve highlighted that a ratio of these two metabolites showed good discrimination between patients who developed delirium and patients who did not develop delirium. In conclusion, the results from this pilot study indicate that a panel of urinary metabolites may serve as non-invasive biomarkers for the diagnosis of delirium in older patients following hip surgery. To further validate these preliminary findings, a multi-centre clinical study is currently underway to recruit a larger patient population with repeat urine samples collected during hospitalization to allow for greater study power. REFERENCES: (1) Cerejeira, J.; Mukaetova-Ladinska, E. B. A Clinical Update on Delirium: From Early Recognition to Effective Management. Nurs. Res. Pract. 2011, 2011, 1–12. https://doi.org/10.1155/2011/875196. (2) Guo, Y.; Zhang, Y.; Jia, P.; Wang, W.; Zhou, Q.; Sun, L.; Zhao, A.; Zhang, X.; Wang, X.; Li, Y.; Zhang, J.; Jiang, W. Preoperative Serum Metabolites Are Associated With Postoperative Delirium in Elderly Hip-Fracture Patients. J. Gerontol. Ser. A 2017, 72 (12), 1689–1696. https://doi.org/10.1093/gerona/glx001. (3) Xu, L.; Lyu, W.; Wei, P.; Zheng, Q.; Li, C.; Zhang, Z.; Li, J. Lower Preoperative Serum Uric Acid Level May Be a Risk Factor for Postoperative Delirium in Older Patients Undergoing Hip Fracture Surgery: A Matched Retrospective Case-Control Study. BMC Anesthesiol. 2022, 22 (1). https://doi.org/10.1186/s12871-022-01824-0. |
| Topic(s): Small Molecule > Spatialomics > Microbiology |
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Poster Presentation Poster #45b Attended on Wednesday at 12:15
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Leveraging MALDI-MSI for Studying Spatial Molecular Mechanisms Involved in Vibrio cholerae Biofilm Formation.
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Ethan Older (Presenter) University of California Santa Cruz
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| INTRODUCTION: Cholera is an infection of the small intestine caused by pathogenic strains of the bacterium Vibrio cholerae and is characterized by severe diarrhea and rapid dehydration, left untreated, the mortality rates are 50-60% (1,2). In 2025, the World Health Organization (WHO) recorded 37,500 cholera cases and 2,400 deaths across 26 endemic countries. However, WHO estimates that the number of officially reported cases represents only 5-10% of the actual number of cases (3). The V. cholerae infection cycle relies on biofilm formation and dispersal. V. cholerae biofilm formation is controlled by QS molecules including cholerae autoinducer-1 (CAI-1), autoinducer-2 (AI-2) and 3,5-dimethyl-pyrazin-ol (DPO) which suppress biofilm formation through the repression of the critical transcriptional activator vpsT (4). The second messenger cyclic dimeric guanosine monophosphate (c-di-GMP) has also been found to bind to VpsT, activating multiple genes involved in biofilm formation (4,5). Interestingly, certain members of the human gut microbiome have been found to modulate V. cholerae infection through microbial metabolites (6,7). However, the identities of these metabolites, and the mechanisms by which they regulate V. cholerae biofilms remain unknown. We hypothesize that some of these unknown metabolites may be leveraged as a mechanism to modulate cholera infection, providing a potential treatment or preventative factor. OBJECTIVE(S): Probe the spatial distribution of excreted and intracellular V. cholerae metabolites during biofilm formation using Expansion Mass Spectrometry (ExMS). METHODS: V. cholerae microcolonies will be grown on solid media alone and imaged. Microcolonies will also be grown on functionalized hydrogels and physically expanded for analysis by Expansion Mass Spectrometry (ExMS). We have recently developed ExMS for use with human high grade serous ovarian cancer cell lines by applying an ionically crosslinked alginate and covalently crosslinked polyacrylamide to create double-crosslinked hydrogels capable of 20x stretch. These chemically inert materials require surface functionalization for 2D microcolony attachment. We have systematically optimized a procedure for attachment using Sulfo-SANPAH, a water-soluble heterobifunctional crosslinker. Surface adhesion is essential for cells to endure the physical stress of stretching and prevents premature detachment. A mechanically engineered platform will be used to equibiaxially stretch hydrogels with attached cells, enhancing expansion factors before MALDI-MSI, while maintaining cell viability and structural integrity. A MALDI matrix will be applied using an HTX-TMSprayer and MALDI-MSI will be performed using a Bruker timsTOF flex mass spectrometer with a 50 µm spatial resolution in positive and negative mode. The detection of microbial metabolites will be optimized by tuning experimental conditions including matrix composition, sample preparation, and MALDI parameters. RESULTS: Previous work in the Sanchez lab has enabled the label-free detection of c-di-GMP, the second messenger involved in regulating biofilm formation, in microbial colony biofilms using MALDI-MSI (8). We expect that MALDI-MSI of V. cholerae microcolony growth will reveal longitudinal metabolite production patterns that can be used to delineate stages of biofilm development. For example, increased c-di-GMP production during early microcolony growth facilitates expansion of V. cholerae cell populations and extracellular matrix production leading to biofilm formation. In addition to c-di-GMP, the production of QS molecules (i.e., CAI-1, AI-2, and DPO) also control V. cholerae biofilm formation. We will correlate these signals with stages in the V. cholerae life cycle to develop a baseline model for V. cholerae biofilm formation. We will also develop and optimize an LC-based method for rapid and quantitative validation of V. cholerae metabolites. Using this method, we will analyze a cohort of intestinal samples from V. cholerae-infected and uninfected mice to prioritize additional infection-relevant signals. DISCUSSION: This work is envisioned to spatially map V. cholerae metabolite production during the natural progression from microcolony to biofilm. While these experiments will focus on the detection of c-di-GMP and the known QS molecules, the data generated provide the unique ability for the untargeted discovery of additional exogenous microbial metabolites that affect V. cholerae biofilm regulation. Investigation of these metabolites may then reveal a factor that can be leveraged to prevent cholera disease through control of V. cholerae biofilms. REFERENCES: 1. Charles, R. C. & Ryan, E. T. Cholera in the 21st century. Curr. Opin. Infect. Dis. 24, 472 (2011). 2. Sack, D. A., Sack, R. B., Nair, G. B. & Siddique, A. Cholera. The Lancet 363, 223–233 (2004). 3. Ali, M. et al. The global burden of cholera. Bull. World Health Organ. 90, 209–218 (2012). 4. Papenfort, K. et al. A Vibrio cholerae autoinducer-receptor pair that controls biofilm formation. Nat. Chem. Biol. 13, 551–557 (2017). 5. Krasteva, P. V. et al. Vibrio cholerae VpsT Regulates Matrix Production and Motility by Directly Sensing Cyclic di-GMP. Science 327, 866–868 (2010). 6. You, J. S. et al. Commensal-derived metabolites govern Vibrio cholerae pathogenesis in host intestine. Microbiome 7, 132 (2019). 7. Pauer, H. et al. Bioactive small molecules produced by the human gut microbiome modulate Vibrio cholerae sessile and planktonic lifestyles. Gut Microbes 13, 1918993 (2021). 8. McCaughey, C. S. et al. A label-free approach for relative spatial quantitation of c-di-GMP in microbial biofilms. Anal. Chem. 96, 8308–8316 (2024). |
| Topic(s): Proteomics > Proteomics |
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Poster Presentation Poster #45c Attended on Thursday at 12:15
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Discovering Arginylation Substrates by ATE1-Based Arginylation Profiling with Bottom-Up and Top-Down Proteomics
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Richard Searfoss (Presenter) Washington University School of Medicine >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: Arginylation is a PTM installed by ATE1 to signal a protein for degradation by the N-degron pathway. Knockout of the ATE1 enzyme is embryonic lethal due to various cardiac defects including thinned myocardium and cardiac contractility deficiencies, however the exact mechanism of how this occurs is still unknown. Arginylation is also implicated as a regulator of aSyn folding and function, preventing aggregation as a potential mechanism in the prevention of synucleinopathies. Other roles for arginylation include protein secretion, notably serum albumin, and B-actin subcellular translocation. This modification most commonly occurs on the N-terminus of substrates, but studies show it can be installed on aspartic and glutamic acid side chains as well. Study of arginylation is challenging due to the low abundance of the modification, aspecific antibodies, and the difficulty of distinguishing a PTM from a missed cleavage. initial qualitative proteomics studies have identified two small sets of candidates (43 and 19 proteins) potentially equipped with N-term and mid-chain arginylation, respectively. These results indicate that arginylation serves as a biological regulator of protein function and thus raises the question of how many proteins/sites are arginylated and what their functions are. We have recently developed an ABAP strategy for the discovery of arginylation sites with both bottom-up and top-down proteomics. This method takes advantage of isotopically labeled arginine to validate the N-terminal installation of the arginyl modification by ATE1 both in vitro and in vivo. METHODS: Peptides, peptide mixtures, proteins, cell proteomes, patient heart and brain tissue, and mouse tissues (lung, heart, and brain) were arginylated by ATE1 assay. The enzyme assay was successfully reconstituted including two key enzymes involved in the protein arginylation: RARS1 and ATE1. RARS1 charged the tRNA for arginine with either R0 or isotopically labeled R10 in solution, and ATE1 used this newly charged Arg-tRNA to label substrates. To incorporate isotopic Arg into proteomes, lysates from biological samples were used as ribosome-inactive conditions. Labeled proteomes were mixed, digested, and fractionated for proteomics analysis in data-dependent acquisition mode. For top-down proteomics, the platform was developed using calreticulin as a working standard as a known substrate of ATE1 arginylation. This protein was subjected to arginylation in vitro, in vivo, and on-bead during pull-down. Other individual protein standards were labeled with the same ATE1 assay. Labeled proteins were kept separately or in mixtures and analyzed in MRMHR mode to target specific charge states. Data was analyzed with a custom software “ArginylomePlot” for bottom-up and ProSight for top-down. RESULTS: In bottom-up proteomics, we first established the workflow using peptide (e.g.: standard peptide) and proteome-wide peptides (e.g.: HEK293T digest) as a proof-of-concept, then applied the technology to protein (e.g.: CALR) and whole proteomes (including iPSC cells, iPSC cardiac fibroblasts, iPSC cardiac myocytes, HEK293T, various cancer cells, patient heart, and patient brains) for arginylation discovery. As a result, a large catalog of unbiased arginylation sites (>200) has been established from various cell and tissue samples. Representative sites were validated and followed up for their biological pathways. In top-down proteomics analyses, analysis showed clear presence of two features with the 156 Da mass shift between WT and arginylated proteoforms visible following the application of the ATE1 assay. Calreticulin was readily arginylated and quantitatively determined to be an efficient target of this assay is various experiments. Further experiments validating substrates identified in bottom-up experiments demonstrated similar findings, with N-terminal arginylation reproducibly reconstituted. DISCUSSION: Arginylation is an essential PTM as demonstrated by the embryonic lethality of the knockout of ATE1. Given its wide role in diseases from cardiac disease, circulatory protein secretion, and aSyn folding and aggregation, understanding this PTM is crucial from a basic sciences and diagnostics perspective. Our work has generated the largest arginylation site library so far and established a series of arginylation assays (in vitro, in-bacteria, ex vivo, and in vivo) for functional validation. Arginylation profiling revealed new protein N-termini, thus opening new frontiers in protease cleavage. Further, we demonstrated the first ever experiment studying arginylation using top-down proteomics. This work could serve as the technological foundation for studying the functions of this essential PTM, and it will have a long-lasting impact on the arginylation field by opening new biochemical and biological frontiers. Further, given the observed arginylation across a diverse set of proteomes, including cancer cell lines and real patient samples, we believe there could be deep relevance to clinical pathologies that are not yet known where clinical mass spectrometry would excel. |
| Topic(s): Other -omics > Metabolomics > Lipidomics |
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Poster Presentation Poster #51c Attended on Thursday at 12:15
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A Comprehensive LC-MS Exposomics Assay for Quantitative Analysis of Serum and Urine
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Rupasri Mandal (Presenter) University of Alberta
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| INTRODUCTION: Exposomics, the study of environmental exposures, life style, diet and their effects on health, and metabolomics, the analysis of small molecules (metabolites) in biological samples, are increasingly used together to understand how environmental and other factors influence human health. Metabolomics can provide insights into the impact of environmental exposures on metabolic processes, helping to identify potential biomarkers and mechanisms of disease. OBJECTIVE: In this quest, we have developed a custom made, comprehensive, quantitative LC-MS/MS-based assay for targeted exposomic (environmental and diet) compounds analysis of biospeimens such as serum and urine. This assay allows for the identification and quantification of up to 265 exposomic compounds. METHODS: Our method uses a reverse phase LC-MS/MS in both positive and negative ionization modes to separate metabolites. It combines the derivatization and extraction of analytes, and the selective mass-spectrometric detection using multiple reaction monitoring (MRM) pairs. Two separate panels involving two different precolumn derivatization reactions were developed for this assay: Panel A - Phenylisothiocyanate (PITC) derivatization targeting amine-containing compounds and Panel B - 3-nitrophenylhydrazine (3-NPH) derivatization targeting keto- and carboxyl-containing compounds. Isotopically-labeled internal standards are used for metabolite quantification. Calibration of metabolite concentration ranges in both panels was adjusted for different biofluid types. For panel A, a 96 deep-well plate with a filter plate attached via sealing tape, containing the required reagents and solvents, was used to prepare the plate assay. The first 14 wells of each plate are used for calibration and quality control purposes. For all metabolites, except organic acids, samples are first thawed on ice and then vortexed and centrifuged at 13,000x g. 10 µL of each sample are loaded onto the center of the filter on the upper 96-well plate and dried in a stream of nitrogen. Subsequently, PITC is added for derivatization. After incubation, the filter spots are dried again using an evaporator. Extraction of the metabolites is then achieved by adding 300 µL of extraction solvent. The extracts are obtained by centrifugation into the lower 96-deep well plate, followed by a dilution step with MS running solvent. For organic acid analysis (panel B), 90 µL of ice-cold methanol is added to 30 µL of each sample for overnight protein precipitation. The sample is centrifuged at 13000x g for 20 min. 50 µL of supernatant was loaded into the center of wells of a 96-deep well plate, followed by the addition of NPH. After incubation for 2h, isotope-labeled internal standards, BHT stabilizer and water are added before LC-MS injection. Mass spectrometric analysis was performed on Sciex 5500 QTrap® tandem MS instrument equipped with an Agilent 1290 series UHPLC system. The samples are delivered to the MS by a standard LC method. Data analysis was done using Analyst 1.6.2. Calibration regression, accuracy and precision of QC standards, and spiked recovery of each targeted metabolite were used for method validation. RESULTS: This custom assay can be used for the targeted identification and quantification of up to 265 metabolites across 16 chemical classes including amino acids and derivatives, biogenic amines, acylcarnitines, organic acids, fatty acids, nucleotides/nucleosides, bile acids, uremic toxins, parabens, plasticizers, pharmaceutical intermediates and other exoposomic compounds. The accuracy of QC standards with 3 different concentration levels are in the range of 80% to 120% with satisfactory precision values of less than 20%. The recovery rates of spiked serum, urine and fecal extract samples with three different concentration levels are in the range of 80% to 120% with satisfactory precision values of less than 20%. CONCLUSIONS: We have developed a comprehensive, sensitive, high-throughput, low-volume, quantitative targeted LC-MS/MS assay for the analysis of up to 265 exposomic compounds, across 16 chemical classes for serum and urine samples. Only 40 µL of a given sample are required for the entire analysis. We have adapted this assay into a 96-well plate format to enable high-throughput analysis. |
| Topic(s): Small Molecule > Metabolomics > Lipidomics |
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Poster Presentation Poster #52d Attended on Thursday at 14:30
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Newborn Screening for X-linked Adrenoleukodystrophy: Method Development and Validation of LC-MS/MS assay for Lysophosphatidylcholine Quantification
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Kandeepan Karthigesu (Presenter) McMaster University
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| BACKGROUND: X-linked adrenoleukodystrophy (X-ALD), due to pathogenic variants of the ABCD1 gene, is the most common peroxisomal disorder and affects 1:17000 births. Among the several forms, the childhood cerebral ALD (CCALD) is the most severe and fatal at the age of 4-8 years in males. CCALD presents with adrenal insufficiency and aggressive inflammatory demyelination. Treatment by bone marrow transplantation is effective, but must be done before onset of clinical neurological symptoms. Hence, early diagnosis is crucial in a clinical setting. Inclusion of X-ALD for newborn screening (NBS) in Canada has been limited due to a lack of validated analytical methods. This study aimed to clinically validate C20:0 to C26:0 lysophosphatidylcholines (LPCs) using liquid chromatography (LC) MS/MS and to implement it as a second-tier test for CCALD screening in Ontario. METHODS: Screen positive samples from the first-tier method under flow injection analysis (FIA) MS/MS were subjected to C20:0-LPC, C22:0-LPC, C24:0-LPC, and C26:0-LPC measurements using LC-MS/MS. To achieve this, various mobile phases, gradients, columns, internal standards, and MS parameters were evaluated to optimize the method. Analysis was conducted using a Waters Xevo-TQS micro MS/MS instrument coupled to a Waters ACQUITY H class plus UPLC binary solvent LC system. An ACQUITY Premier BEH C8 VanGuard FIT Column, 1.7 µm, 2.1 mm x 50 mm, with a matching 5 mm guard column was employed. Underivatized analytes and stable isotope internal standards were monitored in positive electrospray ionization (ESI+) mode by multiple reaction monitoring (MRM), using the same quantification or qualification product ions for all species (M/Z 104.1 and 184.1, respectively) with the following precursor ions: 552.4 (C20:0-LPC), 580.4 (C22:0-LPC), 608.5 (C24:0- LPC), 636.5 (C26:0-LPC), 556.4 (C20:0-d4-LPC), 586.4 (C22:0-13C6-LPC), 614.5 (C24:0-13C6-LPC), and 642.5 (C26:0-13C6-LPC). Dried blood spot (DBS) samples used as calibrators, quality controls, and blank filter paper during validation were sourced in-house and from the U.S. Centers for Disease Control and Prevention (CDC). RESULTS: Sample elution of DBS shaking at 600 rpm and 28°C with 100% methanol showed good recovery. The mobile phases A1 and B1 comprising water/acetonitrile (50/50, v/v) and methanol/acetonitrile (50/50, v/v), respectively, with 5 mM ammonium acetate, at a flow rate of 0.4 mL/min with gradient elution starting at 85% A1, showed the best chromatographic separation. MS parameters were optimized, including cone voltage 26 V, collision energy of 30 V, and capillary voltage of 4.25 kV. Method validation demonstrated good linearity ranging from 0.1 to 8.0 μM with an R-squared value greater than 0.99 for all LPCs. The limit of detection (LOD) for C20:0 LPC, C22:0 LPC, C24:0 LPC, and C26:0 LPC was 0.035, 0.008, 0.012, and 0.018 μM, respectively. The between-day precision of C20:0, C22:0, C24:0, and C26:0-LPCs were 6.3%, 11.9%, 9.2%, and 7.0%, respectively. Two-way ANOVA followed by multiple comparisons using Tukey’s HSD (Day 0 vs. Day 5; storage temperatures: 80°C, -20°C, 4°C, 25°C, and 45°C) revealed no significant differences in the concentration of C26:0 LPC extracted from DBS. CONCLUSION: We developed and validated an LC-MS/MS method for quantitation of C20:0, C22:0, C24:0 and C26:0 LPCs for CCALD second-tier NBS testing, with implementation anticipated in 2025. |
| Topic(s): Small Molecule > Tox / TDM / Endocrine > Various OTHER |
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Poster Presentation Poster #54c Attended on Thursday at 12:15
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Automated Liquid Chromatography Tandem Mass Spectrometry Analysis of Phosphatidylethanol (PEth)
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Spencer Seely (Presenter) University of California, San Diego >> NO POSTER PDF SUBMITTED
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| INTRODUCTION: Alcohol Abuse Disorder (AUD) or excessive ethanol consumption is detrimental to human health. Questionnaires regarding consumption can be inaccurate for the identification of at-risk patients. Indirect biomarkers, such as ethyl glucuronide (EtG) and ethyl sulfate (EtS), have short half-lives, limiting their effectiveness in the determination of chronic abuse. Phosphatidylethanols (PEths), phospholipids conjugated to ethanol, are biomarkers of ethanol use and are detectable 2-4 weeks post-consumption. Most recent published procedures for PEth analysis require time-consuming and complex extraction protocols. We describe an LC-MS/MS laboratory developed test (LDT) which employs a simple extraction process that can be performed manually or with an automated liquid handler to reduce overall turnaround time. METHODS: The measurement of two PEth homologues: 16:0/18:1 (POPEth) and 16:0/18:2 (PLPEth) was performed by isotope dilution LC-MS/MS in clinical whole blood specimens. Samples were extracted using an automated liquid handler using 0.1 M zinc sulfate solution and 50:50 acetonitrile: isopropanol. Extracts were vortexed for 5 minutes, followed by centrifugation at 2000 RCF for 5 minutes. Supernatants were collected and directly injected for analysis by LC-MS/MS. A retrospective analysis of 1847 patient results was performed to identify trends in the two measured homologues. RESSULTS: The analytical measurement range (AMR) for both POPEth and PLPEth was determined as 10 - 1,500 ng/mL, with strong linearity observed across the measure range (R2 >0.995). Calibrator and quality control biases were found to be within 15% of correlated values from an external reference laboratory. Biases were observed for the measurement of POPEth in a subset of externally correlated patient specimens. Isotope dilution studies were performed to assign the appropriate quantifier ion transition to resolve an unknown interferant. Retrospective patient data was used to evaluate PLPEth concentrations relative to established POPEth reference ranges; revealing similar ranges. The PLPEth:POPEth ratio was evaluated and found to be statistically higher in patients with light consumption (10-20 ng/mL POPEth) compared to moderate (20-200 ng/mL POPEth, p-value <0.0001), and heavy (>200 ng/mL POPEth, p-value= 0.0014) consumption; revealing additional utility for the measurement of PLPEth. CONCLUSION: This development of and LC-MS/MS LDT enables the accurate measure of PEth and compares well to external reference laboratory results. Reduction in turnaround time provides more actionable information for clinicians treating alcohol abuse and preventing organ damage during transplantation. More investigation is needed to establish reference ranges for PLPEth, which can provide additional insights to monitoring alcohol consumption and abuse. |