Data-independent Acquisition Research Articles

Meta-Analysis and DIA-MS-Based Proteomic Investigation of COPD Patients and Asymptomatic Smokers in the Indian Population.

Chronic obstructive pulmonary disease (COPD) is India's second largest cause of death and is largely caused by smoking. Asymptomatic smokers develop COPD due to genetic, environmental, and molecular variables, making early screening crucial. Data-independent acquisition mass spectrometry (DIA-MS) based-proteomics offers an unbiased method to analyze proteomic profiles. This study is the first to use DIA-based proteomics to analyze individual serum samples from three distinct male cohorts: healthy individuals (n = 10), asymptomatic smokers (n = 10), and COPD patients (n = 10). This comprehensive approach identified 667 proteins with a 1% false discovery rate. Differentially expressed proteins included 40 in the normal versus asymptomatic comparison, 88 in the COPD versus normal comparison, and 40 in the COPD versus asymptomatic comparison. Among them, protein-associated genes such as PRDX6, ELANE, PRKCSH, PRTN3, and MNDA could help differentiate COPD from asymptomatic smokers, while ELANE, H3-3A, IGHE, SLC4A1, and SERPINA11 could differentiate COPD from healthy subjects. Pathway enrichment and protein-protein interaction analyses revealed significant alterations in hemostasis, immune system functions, fibrin clot formation, and post-translational protein modifications. Key proteins were validated using a parallel reaction monitoring assay. DIA data are available via ProteomeXchange with identifier PXD055242. Our findings reveal key protein classifiers in COPD patients, asymptomatic smokers, and healthy individuals, helping clinicians understand disease pathobiology and improve disease management and quality of life.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery.

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data-independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA-MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation based on 8- or 11-point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.

Data-independent acquisition proteomic analysis of the brain microvasculature in Alzheimer’s disease identifies major pathways of dysfunction and upregulation of cytoprotective responses

Brain microvascular dysfunction is an important feature of Alzheimer’s disease (AD). To better understand the brain microvascular molecular signatures of AD, we processed and analyzed isolated human brain microvessels by data-independent acquisition liquid chromatography with tandem mass spectrometry (DIA LC–MS/MS) to generate a quantitative dataset at the peptide and protein level. Brain microvessels were isolated from parietal cortex grey matter using protocols that preserve viability for downstream functional studies. Our cohort included 23 subjects with clinical and neuropathologic concordance for Alzheimer’s disease, and 21 age-matched controls. In our analysis, we identified 168 proteins whose abundance was significantly increased, and no proteins that were significantly decreased in AD. The most highly increased proteins included amyloid beta, tau, midkine, SPARC related modular calcium binding 1 (SMOC1), and fatty acid binding protein 7 (FABP7). Additionally, Gene Ontology (GO) enrichment analysis identified the enrichment of increased proteins involved in cellular detoxification and antioxidative responses. A systematic evaluation of protein functions using the UniProt database identified groupings into common functional themes including the regulation of cellular proliferation, cellular differentiation and survival, inflammation, extracellular matrix, cell stress responses, metabolism, coagulation and heme breakdown, protein degradation, cytoskeleton, subcellular trafficking, cell motility, and cell signaling. This suggests that AD brain microvessels exist in a stressed state of increased energy demand, and mount a compensatory response to ongoing oxidative and cellular damage that is associated with AD. We also used public RNAseq databases to identify cell-type enriched genes that were detected at the protein level and found no changes in abundance of these proteins between control and AD groups, indicating that changes in cellular composition of the isolated microvessels were minimal between AD and no-AD groups. Using public data, we additionally found that under half of the proteins that were significantly increased in AD microvessels had concordant changes in brain microvascular mRNA, implying substantial discordance between gene and protein levels. Together, our results offer novel insights into the molecular underpinnings of brain microvascular dysfunction in AD.

Phosphoproteomic analysis reveals the mechanisms of human umbilical cord mesenchymal stem cell-derived exosomes attenuate renal aging

Aging is a critical biological process, with particularly notable impacts on the kidneys. Exosomes derived from human umbilical cord mesenchymal stem cells (hUC-MSCs) are capable of transferring various bioactive molecules, which exhibit beneficial therapeutic effects on kidney diseases. This study demonstrates that exosomes derived from hUC-MSCs ameliorate cellular senescence in the kidneys of naturally aging mice. These exosomes reduce the protein expression of senescence markers and senescence-associated secretory phenotypes (SASP) leading to fewer DNA damage foci and increased expression of the proliferation indicator Ki67. During the aging process, many proteins undergo phosphorylation modifications. We utilized data-independent acquisition (DIA) phosphoproteomics to study kidneys of naturally aging mice and those treated with hUC-MSC-derived exosomes. We observed elevated phosphorylation levels of the differentially phosphorylated proteins, Lamin A/C, at Ser390 and Ser392 sites, which were subsequently verified by western blotting. Overall, this study provides a new molecular characterization of hUC-MSC-derived exosomes in mitigating cellular senescence in the kidneys. SignificanceDIA phosphoproteomics was employed to investigate phosphorylated proteins in the kidney tissues of naturally aging mice with hUCMSC-exos treated. The results demonstrated that the DIA technique detected a higher abundance of phosphorylated proteins. We identified 24 significantly differentially phosphorylated proteins, and found that the phosphorylation of specific Lamin A/C sites is crucial for preventing cellular senescence. This study will help to better reveal the related phosphorylated proteins involved in hUCMSC-exos intervention in the kidneys of naturally aging mice, providing a foundation for future research on specific phosphorylation sites of proteins as potential therapeutic targets for renal aging-related diseases.

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we developed Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models.

Simple and robust high-throughput serum proteomics workflow with low-microflow LC-MS/MS.

Clinical proteomics has substantially advanced in identifying and quantifying proteins from biofluids, such as blood, contributing to the discovery of biomarkers. The throughput and reproducibility of serum proteomics for large-scale clinical sample analyses require improvements. High-throughput analysis typically relies on automated equipment, which can be costly and has limited accessibility. In this study, we present a rapid, high-throughput workflow low-microflow LC-MS/MS method without automation. This workflow was optimized to minimize the preparation time and costs by omitting the depletion and desalting steps. The developed method was applied to data-independent acquisition (DIA) analysis of 235 samples, and it consistently yielded approximately 6000 peptides and 600 protein groups, including 33 FDA-approved biomarkers. Our results demonstrate that an 18-min DIA high-throughput workflow, assessed through intermittently collected quality control samples, ensures reproducibility and stability even with 2 µL of serum. It was successfully used to analyze serum samples from patients with diabetes having chronic kidney disease (CKD), and could identify five dysregulated proteins across various CKD stages.

Characterization of the Angiogenic and Proteomic Features of Circulating Exosomes in a Canine Mandibular Model of Distraction Osteogenesis.

Distraction osteogenesis (DO) represents a highly effective method for addressing significant bone defects; however, it necessitates a long treatment period. Exosomes are key mediators of intercellular communication. To investigate their role in the angiogenesis and osteogenesis of DO, we established a canine mandibular DO model with a bone defect (BD) group as the control. Higher levels of angiogenesis were observed in the regenerating tissue from the DO group compared to those from the BD group, accompanied by earlier osteogenesis. Proteomic analysis was performed on circulating exosomes at different phases of the DO using a data-independent acquisition method. Data are available via ProteomeXchange with the identifier PXD050531. The results indicated specific alterations in circulating exosome proteins at different phases of DO, reflecting the regenerative activities in the corresponding tissues. Notably, fibronectin 1 (FN1), thrombospondin 1 (THBS1), and transferrin receptor (TFRC) emerged as potential candidate proteins related to the angiogenic response in DO. Further cellular experiments validated the potential of DO-associated circulating exosomes to promote angiogenesis in endothelial cells. Collectively, these data reveal previously unknown mechanisms that may underlie the efficacy of DO and suggest that exosome-derived proteins may be useful as therapeutic targets for strategies designed to improve DO-related angiogenesis and bone regeneration.

Lipid and Corticosteroid Biomarkers Under the Influence of Bisphosphonates.

Detecting the use of bisphosphonates (BPs) in equine athletes is of interest to regulators and laboratories due to the threat to welfare issues for the potential to provide analgesic effects and manipulating bone structure. The detection of BPs in biological matrices is challenging due to erratic biological elimination and inconsistent analytical recoveries. Therefore, complementary approaches are needed to provide evidence of their misuse in racehorses. BPs have two sub-classes: nitrogenous and non-nitrogenous. This study investigated plasma elimination following administration of one example from each sub-class, together with changes in endogenous eicosanoid and corticosteroids. Zoledronic acid (ZA) and tiludronic acid (TA) were administered by IV infusion to 8 thoroughbred horses with an 11-month washout period between each administration. Sample preparation for quantification of BPs by liquid chromatography-tandem mass spectrometry (LC-MS/MS) utilised a two-step solid phase extraction (SPE) consisting of polymeric reversed-phase followed by weak anion exchange prior to derivatisation using trimethyl orthoacetate. Endogenous biomarkers were analysed after protein precipitation and SPE with polymeric reversed-phase prior to liquid chromatography-high resolution mass spectrometry (LC-HRMS) using data independent acquisition. The LC-MS/MS analysis showed ZA was undetectable after 8 h post-administration while TA was detected up to the final collection point of 28 days post-administration. The LC-HRMS analysis utilised targeted (i.e., prior inclusion list of compounds) approaches to monitor level changes of eicosanoid and corticosteroid biomarkers. Putative biomarkers were identified and now subject to validation for translation into routine sample analysis for improved retrospectivity to detecting BP misuse in equine plasma.

Mapping Nanoscale-To-Single-Cell Phosphoproteomic Landscape by Chip-DIA.

Protein phosphorylation plays a crucial role in regulating disease phenotypes and serves as a key target for drug development. Mapping nanoscale-to-single-cell samples can unravel the heterogeneity of cellular signaling events. However, it remains a formidable analytical challenge due to the low detectability, abundance, and stoichiometry of phosphorylation sites. Here, we present a Chip-DIA strategy,integratinga microfluidic-based phosphoproteomic chip (iPhosChip) with data-independent acquisition mass spectrometry (DIA-MS) for ultrasensitive nanoscale-to-single-cell phosphoproteomic profiling. The iPhosChip operates as an all-in-one station that accommodates both quantifiable cell capture/imaging and the entire phosphoproteomic workflow in a highly streamlined and multiplexed manner. Coupled with a sample size-comparable library-based DIA-MS strategy, Chip-DIA achieved ultra-high sensitivity, detecting 1076±158 to 15869±1898 phosphopeptides from 10±0 to 1013±4 cells, and revealed the first single-cell phosphoproteomic landscape comprising druggable sites and basal phosphorylation-mediated networks in lung cancer. Notably, the sensitivity and coverage enabled the illumination of heterogeneous cytoskeleton remodeling and cytokeratin signatures in patient-derived cells resistant to third-generation EGFR therapy, stratifying mixed-lineage adenocarcinoma-squamous cell carcinoma subtypes, and identifying alternative targeted therapy for late-stage patients. With flexibility in module design and functionalization, Chip-DIA can be adapted to other PTM-omics to explore dysregulated PTM landscapes, thereby guiding therapeutic strategies toward precision oncology.

Integrated strategy for high-confident global profiling of the histidine phosphoproteome

BackgroundHistidine phosphorylation (pHis) plays a key role in signal transduction in prokaryotes and regulates tumour initiation and progression in mammals. However, the pHis substrates and their functions are rarely known due to the lack of effective analytical strategies. ResultsHerein, we provide a strategy for unbiased enrichment and assignment of the pHis peptides. First, the entire procedure was designed under alkaline conditions to maintain the stability of the N–P bond of pHis and high-pH reverse-phase chromatography was used to efficiently separate the pHis peptides. Second, exploiting the coelution benefits of diethyl labelling, the ratios of light- and heavy-labelled peptides were accurately quantified, and the sites of phosphorylated histidine were assigned. Finally, Cu-IDA bead enrichment and data-independent acquisition mass spectrometry analysis were used to improve the coverage of the histidine phosphoproteome. With this novel strategy, 768 and 1125 potential pHis peptides were identified from lysates of E. coli and HeLa cells, respectively. And these values represent the highest coverage of the histidine phosphoproteome for both cell types. SignificanceThese data strongly support the presumption that pHis modifications are widely present in bacteria. The study provides an efficient strategy and can lead to a better understanding of pHis-modified substrates and their biological functions.

An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis.

In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.

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

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

Deep Spectral Library of Mice Retina for Myopia Research: Proteomics Dataset generated by SWATH and DIA-NN

The retina plays a crucial role in processing and decoding visual information, both in normal development and during myopia progression. Recent advancements have introduced a library-independent approach for data-independent acquisition (DIA) analyses. This study demonstrates deep proteome identification and quantification in individual mice retinas during myopia development, with an average of 6,263 ± 86 unique protein groups. We anticipate that the use of a predicted retinal-specific spectral library combined with the robust quantification achieved within this dataset will contribute to a better understanding of the proteome complexity. Furthermore, a comprehensive mice retinal-specific spectral library was generated, encompassing a total identification of 9,401 protein groups, 70,041 peptides, 95,339 precursors, and 761,868 transitions acquired using SWATH-MS acquisition on a ZenoTOF 7600 mass spectrometer. This dataset surpasses the spectral library generated through high-pH reversed-phase fractionation by data-dependent acquisition (DDA). The data is available via ProteomeXchange with the identifier PXD046983. It will also serve as an indispensable reference for investigations in myopia research and other retinal or neurological diseases.

Deep Proteome Analysis of Cerebrospinal Fluid from Pediatric Patients with Central Nervous System Cancer.

The cerebrospinal fluid (CSF) is a key matrix for discovery of biomarkers relevant for prognosis and the development of therapeutic targets in pediatric central nervous system malignancies. However, the wide range of protein concentrations and age-related differences in children makes such discoveries challenging. In addition, pediatric CSF samples are often sparse and first prioritized for clinical purposes. The present work focused on optimizing each step of the proteome analysis workflow to extract the most detailed proteome information possible from the limited CSF resources available for research purposes. The strategy included applying sequential ultracentrifugation to enrich for extracellular vesicles (EV) in addition to analysis of a small volume of raw CSF, which allowed quantification of 1351 proteins (+55% relative to raw CSF) from 400 μL CSF. When including a spectral library, a total of 2103 proteins (+240%) could be quantified. The workflow was optimized for CSF input volume, tryptic digestion method, gradient length, mass spectrometry data acquisition method and database search strategy to quantify as many proteins a possible. The fully optimized workflow included protein aggregation capture (PAC) digestion, paired with data-independent acquisition (DIA, 21 min gradient) and allowed 2989 unique proteins to be quantified from only 400 μL CSF, which is a 340% increase in proteins compared to analysis of a tryptic digest of raw CSF.

End-to-End Throughput Chemical Proteomics for Photoaffinity Labeling Target Engagement and Deconvolution.

Photoaffinity labeling (PAL) methodologies have proven to be instrumental for the unbiased deconvolution of protein-ligand binding events in physiologically relevant systems. However, like other chemical proteomic workflows, they are limited in many ways by time-intensive sample manipulations and data acquisition techniques. Here, we describe an approach to address this challenge through the innovation of a carboxylate bead-based protein cleanup procedure to remove excess small-molecule contaminants and couple it to plate-based, proteomic sample processing as a semiautomated solution. The analysis of samples via label-free, data-independent acquisition (DIA) techniques led to significant improvements on a workflow time per sample basis over current standard practices. Experiments utilizing three established PAL ligands with known targets, (+)-JQ-1, lenalidomide, and dasatinib, demonstrated the utility of having the flexibility to design experiments with a myriad of variables. Data revealed that this workflow can enable the confident identification and rank ordering of known and putative targets with outstanding protein signal-to-background enrichment sensitivity. This unified end-to-end throughput strategy for processing and analyzing these complex samples could greatly facilitate efficient drug discovery efforts and open up new opportunities in the chemical proteomics field.

Comparative proteomic analysis of regenerative mechanisms in mouse retina to identify markers for neuro-regeneration in glaucoma

The retina is part of the central nervous system (CNS). Neurons in the CNS and retinal ganglion cells lack the ability to regenerate axons spontaneously after injury. The intrinsic axonal growth regulators, their interaction and roles that enable or inhibit axon growth are still largely unknown. This study endeavored to characterize the molecular characteristics under neurodegenerative and regenerative conditions. Data-Independent Acquisition Mass Spectrometry was used to map the comprehensive proteome of the regenerative retina from 14-day-old mice (Reg-P14) and adult mice after lens injury (Reg-LI) both showing regrowing axons in vitro, untreated adult mice, and retina from adult mice subjected to two weeks of elevated intraocular pressure showing degeneration. A total of 5750 proteins were identified (false discovery rate < 1%). Proteins identified in both Reg-P14 and Reg-LI groups were correlated to thyroid hormone, Notch, Wnt, and VEGF signaling pathways. Common interactors comprising E1A binding protein P300 (EP300), CREB binding protein (CBP), calcium/calmodulin dependent protein kinase II alpha (CaMKIIα) and sirtuin 1 (SIRT1) were found in both Reg-P14 and Reg-LI retinas. Proteins identified in both regenerating and degenerative groups were correlated to thyroid hormone, Notch, mRNA surveillance and measles signaling pathways, along with PD-L1 expression and the PD-1 checkpoint pathway. Common interactors across regenerative and degenerative retinas comprising NF-kappa-B p65 subunit (RELA), RNA-binding protein with serine-rich domain 1 (RNPS1), EP300 and SIN3 transcription regulator family member A (SIN3A). The findings from our study provide the first mapping of regenerative mechanisms across postnatal, mature and degenerative mouse retinas, revealing potential biomarkers that could facilitate neuro-regeneration in glaucoma.

Identification of Potential Growth-Related Proteins in Chick Vitreous during Emmetropization Using SWATH-MS and Targeted-Based Proteomics (MRMHR).

The vitreous humor (VH) is a transparent gelatin-like substance that occupies two-thirds of the eyeball and undergoes the most significant changes during eye elongation. Quantitative proteomics on the normal growth period in the VH could provide new insights into understanding its progression mechanism in the early stages of myopia. In this study, a data-independent acquisition (SWATH-MS) was combined with targeted LC-ESI-MS/MS to identify and quantify the relative protein changes in the vitreous during the normal growth period (4, 7, 14, 21 and 28 days old) in the chick model. Chicks were raised under normal growing conditions (12/12 h Dark/light cycle) for 28 days, where ocular measurements, including refractive and biometric measurements, were performed on days 4 (baseline), 7, 14, 21 and 28 (n = 6 chicks at each time point). Extracted vitreous proteins from individual animals were digested and pooled into a left eye pool and a right pool at each time point for protein analysis. The vitreous proteome for chicks was generated using an information-dependent acquisition (IDA) method by combining injections from individual time points. Using individual pool samples, SWATH-MS was employed to quantify proteins between each time point. DEPs were subsequently confirmed in separate batches of animals individually on random eyes (n = 4) using MRMHR between day 7 and day 14. Refraction and vitreous chamber depth (VCD) were found to be significantly changed (p < 0.05, n = 6 at each time point) during the period. A comprehensive vitreous protein ion library was built with 1576 non-redundant proteins (22987 distinct peptides) identified at a 1% false discovery rate (FDR). A total of 12 up-regulated and 26 down-regulated proteins were found across all time points compared to day 7 using SWATH-MS. Several DEPs, such as alpha-fetoprotein, the cadherin family group, neurocan, and reelin, involved in structural and growth-related pathways, were validated for the first time using MRMHR under this experimental condition. This study provided the first comprehensive spectral library of the vitreous for chicks during normal growth as well as a list of potential growth-related protein biomarker candidates using SWATH-MS and MRMHR during the emmetropization period.

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

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

B-251 Comprehensive Proteomics Analysis Reveals an Exosomal Biomarker Signature Useful for Detection of Non-Small Cell Lung Cancer

Abstract Background Lung cancer is the second most commonly diagnosed lung cancer in the world, and Non-Small Cell Lung Cancer is the most prevalent subtype. Tissue biopsy is the gold standard for detecting lung cancer, but is highly invasive as it necessitates the extraction of a sample of tissue for histologic analysis. It also carries risks of bleeding and/or infection, and is inconvenient from a patient perspective. The development of a minimally invasive test, such as one utilizing a blood or urine sample, capable of providing accurate results for lung cancer detection and/or subtyping, would significantly enhance the clinical landscape and streamline patient care. Methods In this study we utilize A549 and H1299 human lung cancer cell lines, differing in cell type, location within the lung, and genetic composition (Kras &amp; p53 status), along with two additional cancer cell lines (HeLa/cervical cancer and SCBO/bladder cancer), as controls. Cell lysate and exosome proteomics data were obtained using data independent acquisition- liquid chromatography mass spectrometry (DIA-LCMS) and analyzed using ProteoDisco 2.0, a custom-designed software application in R. Raw mass spectra data was subject to quantile normalization to mitigate external, non-biological differences between the samples. Differential protein expression was performed and Student's t-test was used to identify significantly different proteins across the sample types. A correlation coefficient matrix and Principal Component Analysis were used to assess global differences, and hierarchical clustering and heat maps allowed for visualizing of specific groups of proteins that separated all sample types. Results Over 1000 proteins were identified in each of the exosome samples, and &amp;gt;7500 proteins were detected in the lysates. Correlation coefficient matrix and PCA demonstrate that exosomal protein profiles, relative to cell lysates, are better at differentiating between the two lung cancer cell lines and controls. Surprisingly, exosomal proteomic patterns are different for the two lung cancers, implicating activation of different signaling pathways. Specifically, hierarchical clustering identified protein clusters showing enrichment for multiple biological processes: H1299 cells manifest enrichment of apical junction proteins and in epithelial-mesenchymal transition (EMT) ontology, while A549 cell lines show enrichment in proteins involved in oxidative phosphorylation. This combination of functional pathways can be used as a biomarker signature to distinguish between these two lung cancer subtypes, and from controls. Conclusions A short list of exosomal proteins, comprising apical junction, EMT, and oxidative phosphorylation constituents can detect lung cancer and further distinguish between subtypes represented by A549 and H1299 lung cancer cells. This biomarker signature has potential for detecting and subtyping lung cancer, to allow for early detection of disease, development of personalized treatment strategies, and result in improved clinical outcomes for this deadly disease.

B-249 Assessing Targeted Mass Spectrometry Assay Performance for Putative Biomarker Proteins on a New Hybrid Nominal Mass Instrument

Abstract Background The development of targeted mass spectrometry-based proteomics assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to highly multi-analyte clinical studies. Targeted assays are currently unable to scale to thousands of peptide targets from hundreds of proteins, requiring extensive refinement down assays for the minimum useful analytes. Large parallel reaction monitoring (PRM) assays are now possible with a new hybrid nominal-mass instrument. The scale of assay is achievable with this instrument by using real-time alignment, while being sensitive and fast enough to handle many concurrent targets. To assess the performance of this new instrument we constructed a large scale PRM assay for proposed neurodegenerative disease marker proteins, and an assay for proteins associated with amyloid tissue typing. Methods To evaluate the performance of this instrument on proteins of interest in cerebrospinal fluid, we performed an analysis on a pool from individuals diagnosed as Alzheimer’s, Parkinson’s, or cognitively normal. A calibration curve of cerebrospinal fluid diluted into chicken serum at 14 dilutions and individual human cerebrospinal fluid were digested with a protein aggregation and capture based digestion protocol. CSF peptides were separated by 60 minute gradient on C18 IonOpticks column, and amyloid tissue peptides separated by 30 minute gradient on C18 PepMap column with a Vanquish Neo UHPLC and analyzed by data-independent acquisition (DIA) and PRM with a new hybrid nominal mass instrument designed for targeted tandem mass spectrometry (tMS2). Scheduled methods were generated using a Skyline external tool, transitions were refined to minimize interference and maximize the LLOQ. DIA data was searched, and data extracted and analyzed in Skyline. PRM data was extracted and quantified with Skyline; CSF calibration curve LLOQ is calculated by bilinear fit. Results For the large scale cerebrospinal fluid (CSF) assay the selection of protein targets was based on literature from neurodegenerative disease cohort studies. We target 1065 peptides from 104 proteins, including proteins currently measured by ELISA in clinical research, e.g.: APP, TAU, and APOE. Sensitivity and reproducibility of the assay is assessed using figures of merit from replicate matched-matrix calibration curves. Over 80% of proteins have at least one peptide with a LLOQ below 30% dilution in the matched matrix, and of all targeted peptides over 55% had a LLOQ below 30% dilution. To demonstrate the application of the real-time alignment on the new instrument we constructed an assay for samples where not every analyte is shared. An assay for amyloidosis associated proteins was constructed for a total of 180 peptides mapping to 52 proteins. This includes 11 proteins most commonly associated with amyloid deposition; APCS, APOA4, APOE, CLU, LECT2, IGKC, IGLC2/4/7, SAA1, TTR, and VTN. From the preliminary set of 12 previously typed samples we observe peptide abundances consistent with the assigned type. Conclusions This novel instrument provides a new approach for building large targeted mass spectrometry assays. We demonstrate the ability of the real-time alignment to adjust scheduled retention time windows, ensuring that chromatographic shifts do not lead to a loss of peptide detection and quantification.