Depletion Of High-abundance Proteins Research Articles

B-157 High Resolution Liquid Chromatography - Mass Spectrometry (LC-MS) For Rapid, High-Throughput Clinical Testing of β2-Transferrin in Human Nasal Secretions

Abstract Background Leakage of Cerebrospinal Fluid (CSF) can result from trauma, lacerations, and surgery, and if untreated can result in potentially life-threatening meningitis. CSF leaks can be diagnosed through the detection of β2-Transferrin (β2-Tf) from nasal secretions via gel electrophoresis. β2-Tf is a uniquely glycosylated proteoform of Transferrin found primarily in CSF, which can be distinguished from the most abundant Transferrin proteoform (β1-Tf) by its altered electrophoretic mobility. However, gel-based detection of β2-Tf requires hours of labor and has low specificity due to the numerous alternative glycoforms of Transferrin. Higher-throughput assays are thus desirable for improved patient care. Recently, our group applied High-Resolution Mass Spectrometry (HR-MS) coupled to Microprobe In-Emitter Elution (MPIE) to discriminate Transferrin isoforms. This method successfully resolved β2- from β1-Tf in nasal secretions derived from patient samples with suspected CSF leakage, but has relatively low sample-to-sample throughput. Herein, we describe a novel approach utilizing Liquid Chromatography Mass Spectrometry (LC-MS) to rapidly profile Transferrin glycoforms from patient nasal secretion samples. Furthermore, we explore solutions to address significant blood contamination in nasal secretions, which may otherwise interfere with this approach. Furthermore, we explore solutions to address significant blood contamination in some nasal secretions, which may otherwise interfere with this approach. Methods Our approach consists of two primary steps: 1) Sample processing and high abundance protein depletion via commercial filtration and depletion columns. 2) LC-MS analysis of the resulting extract to resolve Transferrin glycoforms by retention time and m/z. This approach retains the high specificity of the previously demonstrated MPIE-MS method, but takes advantage of existing high-throughput liquid chromatography platforms to reduce the sample-to-sample analysis time. Secretion samples were analyzed using a Vanquish HPLC system coupled to a Q-Exactive Plus Mass Spectrometer (ThermoFisher). Broadband mass spectra were collected (FWHM resolution of 17,500 at 200 m/z), and the deconvoluted average masses were used to identify Transferrin glycoforms. Results Our approach was benchmarked using remnant nasal secretion samples from patients with known CSF leakage. Examining 9 samples, the resulting ESI spectra revealed peaks at 79,554 Da and 78,008 Da, consistent with β1-Tf (Pred. MW (Average): 79,554.71 Da) and β2-Tf (Pred. MW (Average): 78,008.35 Da) within ∼10 ppm mass accuracy. The 79.5 kD peak was observed in all samples, while the 78 kD peak was observed in 7 of 9 samples. Samples with missing β2-Tf were marked by significant blood contamination. Genetic variants (2/9 samples) resulted in mass shifts for both β1- and β2-Tf variants, but Transferrin glycoforms identifiable due to the preserved mass shift between the β1- and β2-Tf peaks (∼1546.4 Da). An optimized LC-MS gradient enables rapid (∼10 minute) sample-to-sample injection times. Samples with blood contamination represent an additional challenge for identification of β2-Tf, owing to ion suppression from blood-derived β1-Tf. We have developed enrichment and depletion methods to increase the sensitivity for β2-Tf in blood contaminated samples, and anticipate that these approaches will reduce or eliminate this challenge. Conclusions Our approach enables high-throughput, MS-based measurement of Transferrin glycoforms (i.e. β1- and β2-Tf) from clinical nasal secretion samples for the first time.

The Low-Abundance Plasma Proteome Reveals Differentially Abundant Proteins Associated with Breast Implant Capsular Contracture: A Pilot Study.

Capsular contracture (CC) is one of the most common postoperative complications associated with breast implant-associated infections. The mechanisms that lead to CC remain poorly understood. Plasma is an ideal biospecimen for early proteomics biomarker discovery. However, as high-abundance proteins mask signals from low-abundance proteins, identifying novel or specific proteins as biomarkers for a particular disease has been hampered. Here, we employed depletion of high-abundance plasma proteins followed by Tandem Mass Tag (TMT)-based quantitative proteomics to compare 10 healthy control patients against 10 breast implant CC patients. A total of 450 proteins were identified from these samples. Among them, 16 proteins were significantly differentially expressed in which 5 proteins were upregulated and 11 downregulated in breast implant CC patients compared to healthy controls. Gene Ontology enrichment analysis revealed that proteins related to cell, cellular processes and catalytic activity were highest in the cellular component, biological process, and molecular function categories, respectively. Further, pathway analysis revealed that inflammatory responses, focal adhesion, platelet activation, and complement and coagulation cascades were enriched pathways. The differentially abundant proteins from TMT-based quantitative proteomics have the potential to provide important information for future mechanistic studies and in the development of breast implant CC biomarkers.

Applications of high performance liquid chromatography-mass spectrometry in proteomics

Proteomics profiling plays an important role in biomedical studies. Proteomics studies are much more complicated than genome research, mainly because of the complexity and diversity of proteomic samples. High performance liquid chromatography-mass spectrometry (HPLC-MS) is a fundamental tool in proteomics research owing to its high speed, resolution, and sensitivity. Proteomics research targets from the peptides and individual proteins to larger protein complexes, the molecular weight of which gradually increases, leading to sustained increases in structural and compositional complexity and alterations in molecular properties. Therefore, the selection of various separation strategies and stationary-phase parameters is crucial when dealing with the different targets in proteomics research for in-depth proteomics analysis. This article provides an overview of commonly used chromatographic-separation strategies in the laboratory, including reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), hydrophobic interaction chromatography (HIC), ion-exchange chromatography (IEC), and size-exclusion chromatography (SEC), as well as their applications and selectivity in the context of various biomacromolecules. At present, no single chromatographic or electrophoretic technology features the peak capacity required to resolve such complex mixtures into individual components. Multidimensional liquid chromatography (MDLC), which combines different orthogonal separation modes with MS, plays an important role in proteomics research. In the MDLC strategy, IEC, together with RPLC, remains the most widely used separation mode in proteomics analysis; other chromatographic methods are also frequently used for peptide/protein fractionation. MDLC technologies and their applications in a variety of proteomics analyses have undergone great development. Two strategies in MDLC separation systems are mainly used in proteomics profiling: the "bottom-up" approach and the "top-down" approach. The "shotgun" method is a typical "bottom-up" strategy that is based on the RPLC or MDLC separation of whole-protein-sample digests coupled with MS; it is an excellent technique for identifying a large number of proteins. "Top-down" analysis is based on the separation of intact proteins and provides their detailed molecular information; thus, this technique may be advantageous for analyzing the post-translational modifications (PTMs) of proteins. In this paper, the "bottom-up" "top-down" and protein-protein interaction (PPI) analyses of proteome samples are briefly reviewed. The diverse combinations of different chromatographic modes used to set up MDLC systems are described, and compatibility issues between mobile phases and analytes, between mobile phases and MS, and between mobile phases in different separation modes in multidimensional chromatography are analyzed. Novel developments in MDLC techniques, such as high-abundance protein depletion and chromatography arrays, are further discussed. In this review, the solutions proposed by researchers when encountering compatibility issues are emphasized. Moreover, the applications of HPLC-MS combined with various sample pretreatment methods in the study of exosomal and single-cell proteomics are examined. During exosome isolation, the combined use of ultracentrifugation and SEC can yield exosomes of higher purity. The use of SEC with ultra-large-pore-size packing materials (200 nm) enables the isolation of exosomal subgroups, and proteomics studies have revealed significant differences in protein composition and function between these subgroups. In the field of single-cell proteomics, researchers have addressed challenges related to reducing sample processing volumes, preventing sample loss, and avoiding contamination during sample preparation. Innovative methods and improvements, such as the utilization of capillaries for sample processing and microchips as platforms to minimize the contact area of the droplets, have been proposed. The integration of these techniques with HPLC-MS shows some progress. In summary, this article focuses on the recent advances in HPLC-MS technology for proteomics analysis and provides a comprehensive reference for future research in the field of proteomics.

Enhancing biomarker detection in human serum for lung cancer diagnosis: Aqueous biphasic systems for simultaneous depletion of high-abundance proteins and efficient extraction of CYFRA 21–1

Analysing biomarkers in human serum could be used as an effective and less invasive approach for the diagnosis of lung cancer; however, biomarker detection reliability is highly limited due to matrix effects. Herein, aqueous biphasic systems (ABS) are studied as platforms for human serum pretreatment, allowing the simultaneous depletion of high abundant proteins and biomarker extraction. By using ABS varying the polyethylene glycol (PEG) molecular weight between 400 and 6000 g·mol−1 and adopting phosphate buffer as the other phase-forming component, the depletion of the high abundance serum proteins immunoglobulin G (IgG) and human serum albumin (HSA) is induced at the ABS interphase, through precipitation, forming a three-phase partitioning system (ABS-TPP). Maximum depletion efficiencies of 99 % for IgG and 70 % for HSA were achieved in one step using PEG 1500-based ABS-TPP. On the other hand, lung cancer biomarkers, such as CYFRA 21–1, are extracted to the PEG-rich phase of the same ABS-TPP with recovery yields of 91 %. This work shows that a proper selection of the PEG molecular weight in the ABS composition leads to the efficient depletion of high-abundance proteins and extraction of cancer biomarkers from human serum, in a single step, confirming the potential of ABS for sample pretreatment to improve biomarker analysis.

SDS-page of magnetic isolated fraction from plasma of buffalo calves after depletion of high abundance proteins

SDS-page of magnetic isolated fraction from plasma of buffalo calves after depletion of high abundance proteins

Identification of Plasma Biomarkers from Rheumatoid Arthritis Patients Using an Optimized Sequential Window Acquisition of All THeoretical Mass Spectra (SWATH) Proteomics Workflow.

Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.

Tailored pretreatment of serum samples and biomarker extraction afforded by ionic liquids as constituents of aqueous biphasic systems

Prostate cancer serum biomarkers, such as the U.S. Food and Drug Administration (FDA)-approved prostate specific antigen (PSA), are valuable markers of diagnosis, response to treatment and disease progression. Despite the expected benefits of using PSA to better manage the mortality and morbidity associated to prostate cancer, sample complexity and interference within analysis make its quantification in serum a high-cost and strenuous assignment. Here, we make use of the simple preparation, water-rich environment, and selectivity of aqueous biphasic systems (ABS) to develop alternative serum pretreatment strategies. A set of ammonium- and phosphonium-based ionic liquids (ILs) were used as either main phase-forming agents in IL-salt ABS or as adjuvants in polymer-salt ABS, allowing to explore the IL designer solvent nature and versatile role in ABS formation and performance. Serum pretreatment efficiency was evaluated by the capacity of each ABS to simultaneously deplete high abundance serum proteins (immunoglobulin G, IgG, and human serum albumin, HSA) at the systems’ interphase (thus, generating a three-phase partitioning system – ABS-TPP) and extract PSA to a single ABS phase. Regardless of the ABS typology under appraisal (IL-salt or polymer-salt-IL), the proper design of the IL structure is critical for both the ability to deplete high abundance serum proteins and extract PSA. The results demonstrate that, in addition to the proper choice of the ABS typology, a careful adjustment of the IL hydrophobicity is key to achieve the simultaneous depletion of high-abundance proteins and complete PSA extraction in a single step, creating new approaches for PSA analysis and its application in diagnosis/prognosis.

An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples

BackgroundClinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers.ResultsWe have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC–MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1–5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies.ConclusionsOverall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Strategies to Enrich, Identify, and Characterize Glycoproteome in Blood Plasma Using Liquid Chromatography High-Resolution Mass Spectrometry.

Blood and blood-derived components such as plasma and serum are considered as excellent resources that can be utilized to understand the biology of higher eukaryotic organisms including human beings. In research and clinical studies, blood plasma and serum are used to monitor health conditions, progression, and severity of diseases. Many of the disease-related studies utilize plasma and serum due to their disease relevance and accessibility as they can be collected from patients and healthy donors through minimally invasive approaches. Despite its significance, the unique proteome composition, complexity, wide dynamic range, and heterogeneity of the plasma proteins highlight critical factors that challenge the existing analytical technologies. Depletion of high abundant proteins is one among the accepted methods that can simplify the plasma proteome complexity; however, collateral loss of critical proteins should be anticipated. Selective protein enrichment seems to be a better alternative to depletion. Glycosylation of proteins is a dominant posttranslational modification known for its biological as well as diagnostic and therapeutic potential. Most of the reported therapeutic targets for diagnosis and monitoring are found to be glycosylated. In this chapter, a protocol for selective and reproducible enrichment of glycoproteins from blood plasma followed by identification through liquid chromatography high-resolution mass spectrometry has been documented.

High-Throughput and In-Depth Proteomic Profiling of 5 μL Plasma and Serum Using TMTpro 16-Plex.

High-throughput and in-depth proteomic analysis of plasma and serum samples remains challenging due to the presence of multiple high-abundance proteins. Here, we provide a detailed protocol for proteomic analysis of serum and plasma specimens using a high-abundance protein depletion kit and TMTpro 16-plex reagents. This method requires only 5μL serum or plasma, identifying and quantifying about 1000 proteins. A batch of 16 samples can be processed in 36h. On average, each sample consumes about 1.5h of mass spectrometer instrument time. Overall, our method can identify proteins across six orders of magnitude with high reproducibility (CV<20%) using a shorter instrument time and less sample volume compared to existing methods. Thus, the method is suitable to be applied to large-scale proteomic studies.

Differentially Expressed Proteins in Transfusion-Dependent Thalassemia (TDT) and Their Role in Tdt Disease Severity

Introduction: The management of transfusion-dependent thalassemia (TDT) has seen essential improvements; however, still several challenges to controlling the incidence worldwide. Limitations of available current treatment modalities in resource-limited countries are the driving force to investigate the novel diagnostic and therapeutic options for better clinical management of these patients. Proteomics may be a potential technique to identify novel biomarkers of disease severity and understand the pathophysiological mechanisms of TDT, as proven in many other diseases. Understanding the inter-relationships of proteins affected by the disease process, such as oxidative stress in TDT patients, can help to elucidate the mechanisms involved in the disease pathophysiology. However, plasma proteome profile studies in TDT are limited. This study aimed to investigate the differentially expressed proteins (novel proteins) in serum from TDT to understand the pathophysiology of TDT and determine their role in TDT severity by performing quantitative serum proteomics profiling. Methods: The sample size was calculated based on the sensitivity and specificity of the protein biomarkers identified in the pilot study. A total of 64 patients were included in this study. A serum sample was collected from 32 TDT patients and 32 non-thalassemia controls. Before the serum samples could be processed for label-free quantification using the liquid chromatography-mass spectrometry/mass spectrometry (LCMS/MS) approach, high abundance proteins such as serum albumin and immunoglobulins were depleted using Pierce™ Albumin/IgG Removal Kit (Thermo Fisher Scientific, USA.) according to the manufacturer's protocols. The protein content in samples after depletion of high abundance proteins was determined using the Bradford assay using the protocol recommended by the manufacturer protocol (BioRad, USA). Each protein sample was prepared for LC-MS/MS analysis using EasyPep™ Mini MS Sample Prep Kit (Thermo Fisher Scientific, USA). Analysis of sera was performed on the Agilent 6560C ion mobility Q-TOF LC/MS system (Agilent, USA). To validate the LCMS/MS results, ELISA was done. Differentially regulated proteins with p-value <0.05 were identified from the dataset and uploaded to online databases PANTHER to classify and identify the proteins' functions. The functional gene ontology (GO) annotation of the identified protein in terms of molecular function, biological process, and cellular component was evaluated using this curated biological database. The statistically significant expressed proteins were submitted to STRING, and a combined score of >0.4 (medium confidence) was considered experimentally validated and statistically significant interactions between proteins. The cluster with the largest number of proteins with strong connections was identified for the pathway enrichment analysis. The identified protein cluster from the STRING database was uploaded to the KEGG online database to acquire the enriched pathway. Results: 51 dysregulated proteins were found between cases and controls (Table). However, only 13 showed statistically significant differential expression (p <0.05) with a fold change >1, and mostly were downregulated. Gene ontology functional annotation analysis showed these proteins were involved in molecular functions, mainly catalytic activities (37%), followed by molecular function regulation (15%). The biological processes primarily involved the cellular (35.5%) and metabolic processes (32.3%). The pathway analysis showed that these proteins were involved mainly in hemostasis. In KEGG pathway analysis, the proteins were involved primarily in fat digestion and absorption and vitamin digestion & absorption. Conclusion: We elucidated the possible biological processes modulated by oxidative stress using the differentially expressed novel proteins and the associated pathways using comprehensive molecular and biocomputational analysis. Interestingly, most of the differentially expressed proteins in this study have not been yet reported in previous studies to be modulated by oxidative stress in TDT patients. Therefore, the identified dysregulated proteins can serve as a potential biomarker to monitor a patient's condition, determine the effect, need for blood transfusion, and help develop novel prognostic and diagnostic methods. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Proteomic Profile Analysis of Synovial Fluid in Patients With Anterior Cruciate Ligament Tears

Background: Anterior cruciate ligament (ACL) tears are associated with posttraumatic osteoarthritis, but the early biological changes that initiate joint degeneration after this injury are not well characterized. ACL tears typically result in effusion in the knee, which may provide insight into the initial response of the joint to injuries. Hypothesis: Patient- and injury-specific factors are associated with the proteomics of synovial fluid in knees with ACL tears. Study Design: Descriptive laboratory study. Methods: Synovial fluid was collected from 105 patients (38 male, 67 female) with an acute traumatic ACL tear. Patient- and injury-specific factors such as age, sex, body mass index, time from injury, presence/absence of concomitant meniscal tears, and location of concomitant bone bruises (if present) were recorded. The protein concentration of synovial fluid was measured, followed by benchmarking of samples for multi-affinity high-abundance protein depletion. An isotropically labeled high-resolution nano-liquid chromatography with tandem mass spectrometry–based proteomic approach was used to determine the synovial fluid protein profile. Data were processed, quality controlled, and analyzed computationally for each patient and injury factor. Results: The proteomics of synovial fluid from ACL tears was associated with patient sex, injury pattern, and location of bone bruises but not with patient age, body mass index, or time from injury. Knees with an isolated ACL tear had higher glutathione peroxidase 1 (GPX1) and plastin 3 levels than knees with an ACL tear and meniscal tear. A bone bruise on the lateral femoral condyle was associated with elevated leptin and glucose-6-phosphate dehydrogenase (G6PD) levels. A bone bruise on the lateral tibial plateau was associated with decreased GPX1 levels. Male patients had higher matrix metalloproteinase 9 and lower G6PD levels than female patients. Conclusion: Patient sex, injury pattern, and bone bruise location were important determinants of the proteomic profile of effusion resulting from ACL tears. Clinical Relevance: Longitudinal follow-ups to see if and how proteomic differences relate to clinical outcomes and mechanistic studies to assess the role that specific proteins play in the joint are warranted. Ultimately, these investigations could lead to better approaches to predict clinical outcomes and identify possible interventions to optimize outcomes in these patients.

The plasma proteome of rheumatic patients reveals differences in fingerprint based on the cardiovascular history

Background and Aims : The risk of cardiovascular diseases in patients with a rheumatic background is much higher compared to the normal population. Still, it’s etiology is not fully understood. In this study the plasma proteome of patients with a rheumatic background were compared with a group of patients who on top of their rheumatic background suffered from a cardiovascular event (CVE).Methods: The cohort consisted of a rheumatic patient control group (n=10) and a patient group (n=10) with a CVE history. Samples were collected 1 year prior to the CVE and 3-6 months after the CVE. Patients were matched with controls based on age, sex and medication use. Depletion of high abundant plasma proteins (TOP-14) was followed by “bottom up” shotgun proteomics using LC-MS/MS. Rstudio was used for normalization assessment and the relative changes in protein/peptide abundance were investigated using Perseus for comparison between the groups.Results: Principle component analysis (PCA) demonstrated a difference in overall protein and peptide signature between the control group and the CVE group. A total of 282 proteins determined this potential difference. Within the CVE group PCA revealed a more comparable signature before and after the CVE. Nevertheless, still 59 proteins demonstrated significant difference in relative abundancy within the CVE group.Conclusions: Here we demonstrated the existence of potential differences in the plasma proteome of rheumatic patient’s who suffered from a CVE. This signature may already exist prior to a CVE. This gives rise to further investigation of potential risk markers which may predict a relative risk for a CVE in rheumatic diseases. Background and Aims : The risk of cardiovascular diseases in patients with a rheumatic background is much higher compared to the normal population. Still, it’s etiology is not fully understood. In this study the plasma proteome of patients with a rheumatic background were compared with a group of patients who on top of their rheumatic background suffered from a cardiovascular event (CVE). Methods: The cohort consisted of a rheumatic patient control group (n=10) and a patient group (n=10) with a CVE history. Samples were collected 1 year prior to the CVE and 3-6 months after the CVE. Patients were matched with controls based on age, sex and medication use. Depletion of high abundant plasma proteins (TOP-14) was followed by “bottom up” shotgun proteomics using LC-MS/MS. Rstudio was used for normalization assessment and the relative changes in protein/peptide abundance were investigated using Perseus for comparison between the groups. Results: Principle component analysis (PCA) demonstrated a difference in overall protein and peptide signature between the control group and the CVE group. A total of 282 proteins determined this potential difference. Within the CVE group PCA revealed a more comparable signature before and after the CVE. Nevertheless, still 59 proteins demonstrated significant difference in relative abundancy within the CVE group. Conclusions: Here we demonstrated the existence of potential differences in the plasma proteome of rheumatic patient’s who suffered from a CVE. This signature may already exist prior to a CVE. This gives rise to further investigation of potential risk markers which may predict a relative risk for a CVE in rheumatic diseases.

Comparing Efficiency of Lysis Buffer Solutions and Sample Preparation Methods for Liquid Chromatography-Mass Spectrometry Analysis of Human Cells and Plasma.

The use of a proper sample processing methodology for maximum proteome coverage and high-quality quantitative data is an important choice to make before initiating a liquid chromatography–mass spectrometry (LC–MS)-based proteomics study. Popular sample processing workflows for proteomics involve in-solution proteome digestion and single-pot, solid-phase-enhanced sample preparation (SP3). We tested them on both HeLa cells and human plasma samples, using lysis buffers containing SDS, or guanidinium hydrochloride. We also studied the effect of using commercially available depletion mini spin columns before SP3, to increase proteome coverage in human plasma samples. Our results show that the SP3 protocol, using either buffer, achieves the highest number of quantified proteins in both the HeLa cells and plasma samples. Moreover, the use of depletion mini spin columns before SP3 results in a two-fold increase of quantified plasma proteins. With additional fractionation, we quantified nearly 1400 proteins, and examined lower-abundance proteins involved in neurodegenerative pathways and mitochondrial metabolism. Therefore, we recommend the use of the SP3 methodology for biological sample processing, including those after depletion of high-abundance plasma proteins.

Study of Glutathione S-transferase-P1 in cancer blood plasma after extraction by affinity magnetic nanoparticles and monitoring by MALDI-TOF, IM-Q-TOF and LC-ESI-Q-TOF MS

Glutathione S-transferase P1 (GST-P1) is considered as a detoxification enzyme and can be upregulated in several cancers. Therefore, qualification and/or quantification of GST-P1 in biological fluids can be noteworthy in cancer diagnostic and/or prognostic methods. Whereas costly immunoassays methods are routinely used for clinical analysis, long analysis time per sample is still considered as their disadvantages. To create a fast, efficient, and economical GST-P1 qualification and/or quantification technique, we developed an affinity magnetic nanoparticle-MS method. In proposed method there is no need for any pretreatment for reducing the complexity of sample and depletion of high abundant proteins that are used in routinely immunoassays methods. After enrichment of GST-P1 from blood plasma samples by affinity magnetic nanoparticle (without any pretreatment), the final eluent was analyzed using MALDI-TOF, IM-Q-TOF and LC-ESI-Q-TOF MS. For the first time this study demonstrates the suitability of affinity magnetic nanoparticle-MS method for qualification/quantification of GST-P1 from acute lymphoblastic leukemia blood plasma samples with the limit-of-detection 0.0094 ppm in less than 5 h. Our finding showed that in these blood plasma samples the level of GST-P1 can be up to six times more than healthy children.

Trichloroacetic Acid/Acetone Precipitation Method to Optimize Canine Synovial Fluid for One and Two-Dimensional Gel Electrophoresis Studies

The challenge associated with the use of synovial fluid for osteoarthritic proteome studies is the optimization step, which involves the depletion of high abundant proteins from the samples. The objective of this study was to develop a cost efficient and effective method to remove albumin from canine synovial fluid for proteome studies. Pooled synovial fluid samples were obtained from clinically healthy dogs (n=5), with no radiographic features of osteoarthritis. The acetone precipitation method and 10% w/v of trichloroacetic acid/acetone were chosen to deplete the albumin from canine synovial fluid and the outcome from the different methods were compared using one dimensional and two-dimensional gel electrophoresis studies. The results showed that the 10% w/v TCA/acetone precipitation method removed highly abundant proteins from synovial fluid for gel electrophoresis studies compared to the acetone precipitation method. The 10% w/v TCA/acetone precipitation method provides an effective method to remove albumin from the synovial fluid using gel electrophoresis, especially two-dimensional gel electrophoresis. The accessibility and cost of TCA and acetone make this method of precipitation a simple and cost-effective technique in preparing a canine synovial fluid for two-dimensional gel electrophoresis analysis.

Evaluation of Spin Columns for Human Plasma Depletion to Facilitate MS-Based Proteomics Analysis of Plasma.

High abundant protein depletion is a common strategy applied to increase analytical depth in global plasma proteomics experiment setups. The standard strategies for depletion of the highest abundant proteins currently rely on multiple-use HPLC columns or multiple-use spin columns. Here we evaluate the performance of single-use spin columns for plasma depletion and show that the single-use spin reduces handling time by allowing parallelization and is easily adapted to a nonspecialized lab environment without reducing the high plasma proteome coverage and reproducibility. In addition, we evaluate the effect of viral heat inactivation on the plasma proteome, an additional step in the plasma preparation workflow that allows the sample preparation of SARS-Cov2-infected samples to be performed in a BSL3 laboratory, and report the advantage of performing the heat inactivation postdepletion. We further show the possibility of expanding the use of the depletion column cross-species to macaque plasma samples. In conclusion, we report that single-use spin columns for high abundant protein depletion meet the requirements for reproducibly in in-depth plasma proteomics and can be applied on a common animal model while also reducing the sample handling time.

Integrated proteomic sample preparation with combination of on-line high-abundance protein depletion, denaturation, reduction, desalting and digestion to achieve high throughput plasma proteome quantification

In this study, we developed an integrated plasma proteome sample preparation system, by which high-abundance proteins from human plasma were first depleted by immunoaffinity column, followed by on-line middle and low-abundance proteins denaturation, reduction, desalting and tryptic digestion. To evaluate the performance of such a system, 20 μL plasma was processed automatically, followed by 1-h gradient liquid chromatography-mass spectrometry analysis (LC-MS). Compared to conventional in-solution protocols, not only the sample preparation time could be shortened from 20 h to 20 min, but also the number of identified proteins were greatly increased by 1.4–2.0 times. Such an integrated system allows us to process 36 human plasma samples per day, with more than 300 proteins and 52 FDA approved disease markers per sample being identified. With combination of such an integrated sample preparation system with label-free single-shot LC-MS/MS, the human plasma proteins could be quantified across more than 6 orders of magnitude of abundance range with high reproducibility (Pearson R = 0.99, n = 9). In addition, the relative quantification of human plasma samples from diabetic retinopathy patients and diabetic patients demonstrated the feasibility of our developed workflow for clinic plasma proteome profiling. All these results demonstrated that our developed integrated plasma proteome sample preparation system would provide a new tool for high throughput biomarker discovery.

Extending the Depth of Human Plasma Proteome Coverage Using Simple Fractionation Techniques.

Human plasma is one of the most widely used tissues in clinical analysis, and plasma-based biomarkers are used for monitoring patient health status and/or response to medical treatment to avoid unnecessary invasive biopsy. Data-driven plasma proteomics has suffered from a lack of throughput and detection sensitivity, largely due to the complexity of the plasma proteome and in particular the enormous quantitative dynamic range, estimated to be between 9 and 13 orders of magnitude between the lowest and the highest abundance protein. A major challenge is to identify workflows that can achieve depth of plasma proteome coverage while minimizing the complexity of the sample workup and maximizing the sample throughput. In this study, we have performed intensive depletion of high-abundant plasma proteins or enrichment of low-abundant proteins using the Agilent multiple affinity removal liquid chromatography (LC) column-Human 6 (Hu6), the Agilent multiple affinity removal LC column-Human 14 (Hu14), and ProteoMiner followed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS PAGE) and C18 prefractionation techniques. We compared the performance of each of these fractionation approaches to identify the method that satisfies requirements for analysis of clinical samples and to include good plasma proteome coverage in combination with reasonable sample output. In this study, we report that one-dimensional (1D) gel-based prefractionation allows parallel sample processing and no loss of proteome coverage, compared with serial chromatographic separation, and significantly accelerates analysis time, particularly important for large clinical projects. Furthermore, we show that a variety of methodologies can achieve similarly high plasma proteome coverage, allowing flexibility in method selection based on project-specific needs. These considerations are important in the effort to accelerate plasma proteomics research so as to provide efficient, reliable, and accurate diagnoses, population-based health screening, clinical research studies, and other clinical work.

Abstract 2854: Multi-omic considerations: Exploring LBgard blood tubes for proteomic analysis

Abstract Expanding the number of -omic (genomic, proteomic, etc.) analyte classes, a single blood draw will serve to increase the scientific value of that sample by affording additional multi-variant analyses. The detection and monitoring of many chronic diseases and cancers requires multi-factorial/multi-analyte measurement. Specialized blood collection tubes (e.g., liquid biopsy tubes) are routinely used in the development of minimally invasive methods to monitor key cancer biomarkers in blood. The suitability of plasma isolated from liquid biopsy blood tubes for quantitative proteomics studies needs further exploration. Herein we performed proteomic analyses of whole blood collected and stored in LBgard Blood Tubes. In this study, matched blood samples from 3 healthy donors were collected in LBgard Blood Tubes and K3EDTA (EDTA) tubes, which is the standard blood collection tube used for plasma proteomic analyzes. Blood collected in LBgard Blood Tubes was stored for either 5 days or 7 days at ambient temperature. Following high-abundant plasma protein depletion, plasma proteins were analyzed in quantitative discovery proteomics by liquid chromatography tandem-mass spectrometry (TMT-LC-MS/MS). Over 800 unique proteins were identified by mass spectrometry in the plasma samples analyzed. Of those, &amp;gt;90% were found to be of similar abundance between EDTA Day 0 plasma samples and plasma isolated from whole blood collected in LBgard Blood Tubes. After storage of the LBgard Blood Tube samples for up to 7 days at ambient temperature, &amp;gt;85% of the proteins demonstrated similar abundance in both stored LBgard Blood samples and EDTA tube samples processed immediately after collection. Samples were also evaluated via ELISA to quantify the levels of proteins known to be cancer related. LBgard Blood Tubes prevented changes in the plasma concentrations of several protein biomarkers known to be sensitive to preanalytical variability in samples stored for 5 days at ambient temperature as compared to samples stored in EDTA tubes under the same conditions. Utilizing tandem-mass tag spectrometry and immunoassay methodologies, we have determined the compatibility of LBgard Blood Tube for determining proteomic profiles of blood samples. Additionally, blood collected in LBgard Blood Tubes was shown to have consistent concentrations of protein after storing the collected blood sample for several days, with enhanced protein detection as compared to EDTA tubes. Citation Format: Jacob M. Vasquez, Joel Desharnais. Multi-omic considerations: Exploring LBgard blood tubes for proteomic analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2854.