A fast and reproducible method for albumin isolation and depletion from serum and cerebrospinal fluid

Proteomics-driven noninvasive screening of circulating serum protein panels for the early diagnosis of hepatocellular carcinoma

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.

Extrinsic and intrinsic preanalytical variables affecting liquid biopsy in cancer

Liquid biopsy, through isolation and analysis of disease-specific analytes, has evolved as a promising tool for safe and minimally invasive diagnosis and monitoring of tumors. It also has tremendous utility as a companion diagnostic allowing detection of biomarkers in a range of cancers (lung, breast, colon, ovarian, brain). However, clinical implementation and validation remains a challenge. Among other stages of development, preanalytical variables are critical in influencing the downstream cellular and molecular analysis of different analytes. Although considerable progress has been made to address these challenges, a comprehensive assessment of the impact on diagnostic parameters and consensus on standardized and optimized protocols is still lacking. Here, we summarize and critically evaluate key variables in the preanalytical stage, including study population selection, choice of biofluid, sample handling and collection, processing, and storage. There is an unmet need to develop and implement comprehensive preanalytical guidelines on the optimal practices and methodologies.

Understanding the extracellular vesicle surface for clinical molecular biology

Extracellular vesicles (EVs) are lipid-membrane enclosed nanoparticles that play significant roles in health and disease. EVs are abundant in body fluids and carry an array of molecules (proteins, lipids, nucleic acids and glycans) that reflect the identity and activity of their cell-of-origin. While the advent of high throughput omics technologies has allowed in-depth characterisation of EV compositions, how these molecular species are spatially distributed within EV structures is not well appreciated. This is particularly true of the EV surface where a plethora of molecules are reported to be both integral and peripherally associated to the EV membrane. This coronal layer or 'atmosphere' that surrounds the EV membrane contributes to a large, highly interactive and dynamic surface area that is responsible for facilitating EV interactions with the extracellular environment. The EV coronal layer harbours surface molecules that reflect the identity of parent cells, which is likely a highly valuable property in the context of diagnostic liquid biopsies. In this review, we describe the current understanding of the mechanical, electrostatic and molecular properties of the EV surface that offer significant biomarker potential and contribute to a highly dynamic interactome.

Proteome profiling of cerebrospinal fluid reveals biomarker candidates for Parkinson's disease

Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.

Identification of Cathepsin D as a Plasma Biomarker for Alzheimer's Disease

Although Alzheimer’s disease (AD) is the most common neurodegenerative disease, there are still no drugs available to treat or prevent AD effectively. Here, we examined changes in levels of selected proteins implicated in the pathogenesis of AD using plasma samples of control subjects and patients with cognition impairment. To precisely categorize the disease, fifty-six participants were examined with clinical cognitive tests, amyloid positron emission tomography (PET) scan, and white matter hyperintensities scored by magnetic resonance imaging. Plasma cathepsin D levels of the subjects were examined by immunoblotting and enzyme-linked immunosorbent assay (ELISA). Correlation of plasma cathepsin D levels with AD-related factors and clinical characteristics were examined by statistical analysis. By analyzing quantitative immunoblot and ELISA, we found that the plasma level of cathepsin D, a major lysosomal protease, was decreased in the group with amyloid plaque deposition at the brain compared to the control group. The level of plasma cathepsin D was negatively correlated with clinical dementia rating scale sum of boxes (CDR-SB) scores. In addition, our integrated multivariable logistic regression model suggests the high performance of plasma cathepsin D level for discriminating AD from non-AD. These results suggest that the plasma cathepsin D level could be developed as a diagnostic biomarker candidate for AD.

Efficient extraction of intact HSA-Aβ peptide complexes from sera: Toward albuminome biomarker identification

The performances of three commercial albumin extraction methods for the isolation of intact albumin-amyloid beta peptide (HSA-Aβ) complexes from serum were compared using different analytical approaches. To determine the extraction yield, the repeatability and the selectivity of the extraction procedures, a capillary electrophoresis coupled to UV detection method was developed. For the evaluation of the specificity and integrity of the extracted HSA-Aβ complexes, SDS-PAGE, hybrid and ultra-sensitive ELISA experiments were conducted. All the extraction methods showed different characteristics depending on their chemical binding affinities toward albumin. The ProteoExtract Albumin Depletion kit extracted albumin with a high repeatability but was not efficient for the extraction of intact HSA-Aβ complexes. The PureProteome Albumin magnetic beads showed a high specificity toward HSA thanks to the grafting of anti-HSA antibodies on their surface but tended to dissociate HSA from Aβ peptides. The Pierce Albumin depletion kit showed a high extraction yield, no selectivity towards the different albumin proteoforms and proved to be the most efficient method for the extraction of intact HSA-Aβ complexes from serum.

A Dual Workflow to Improve the Proteomic Coverage in Plasma Using Data-Independent Acquisition-MS

Plasma is one of the most important and common matrices for clinical chemistry and proteomic analyses. Data-independent acquisition (DIA) mass spectrometry has enabled the simultaneous quantitative analysis of hundreds of proteins in plasma samples in support population and disease studies. Depletion of the highest abundant proteins is a common tool to increase plasma proteome coverage, but this strategy can result in the nonspecific depletion of protein subsets with which proteins targeted for depletion interact, adversely affecting their analysis. Our work using an antibody-based depletion column revealed significant complementarity not only in the identification of the proteins derived from depleted and undepleted plasma, but importantly also in the extent to which different proteins can be reproducibly quantified in each fraction. We systematically defined four major quantitative parameters of increasing stringency in both the depleted plasma fraction and in undepleted plasma for 757 observed plasma proteins: Linearity cutoff r² > 0.8; lower limit of quantification (LLOQ); measurement range; limit of detection (LOD). We applied the results of our study to build a web-based tool, PlasmaPilot, that can serve as a protocol decision tree to determine whether the analysis of a specific protein warrants IgY14 mediated depletion.

Novel strategy using tryptic peptide immunoaffinity-based LC–MS/MS to quantify denosumab in monkey serum

Aim: Denosumab is a recombinant fully human IgG2 that has a high affinity and specificity for human RANKL. Commercially available RANKL labeled with an Fc fragment cannot be used to establish an indirect ELISA. To characterize denosumab pharmacokinetic a robust and accuracy method should be developed urgently. Results: In this study, an immunoaffinity enrichment method coupled with LC–MS/MS was established. The LC–MS/MS method acquired a linear range from 0.1 to 30 μg/ml. The intra- and inter-run precision (CV%) was within 11.5 and 10.5%, respectively. More importantly, the LC–MS/MS pharmacokinetic data were consistent with ELISA. Conclusion: This approach accelerated the quantification, reduced the costs and provided an alternative in case of lacking the special antigen to denosumab or a RANKL-biotinylated reagent.

Proteomic and network analysis of human serum albuminome by integrated use of quick crosslinking and two-step precipitation

Affinity- and chemical-based methods are usually employed to prepare human serum albuminome; however, these methods remain technically challenging. Herein, we report the development of a two-step precipitation (TSP) method by combined use of polyethylene glycol (PEG) and ethanol. PEG precipitation was newly applied to remove immunoglobulin G for albuminome preparation, which is simple, cost effective, efficient and compatible with downstream ethanol precipitation. Nonetheless, chemical extraction using TSP may disrupt weak and transient protein interactions with human serum albumin (HSA) leading to an incomplete albuminome. Accordingly, rapid fixation based on formaldehyde crosslinking (FC) was introduced into the TSP procedure. The developed FC-TSP method increased the number of identified proteins, probably by favouring real-time capture of weakly bound proteins in the albuminome. A total of 171 proteins excluding HSA were identified from the fraction obtained with FC-TSP. Further interaction network and cluster analyses revealed 125 HSA-interacting proteins and 14 highly-connected clusters. Compared with five previous studies, 55 new potential albuminome proteins including five direct and 50 indirect binders were only identified by our strategy and 12 were detected as common low-abundance proteins. Thus, this new strategy has the potential to effectively survey the human albuminome, especially low-abundance proteins of clinical interest.

Proteomic Substrate Identification for Membrane Proteases in the Brain

Cell-cell communication in the brain is controlled by multiple mechanisms, including proteolysis. Membrane-bound proteases generate signaling molecules from membrane-bound precursor proteins and control the length and function of cell surface membrane proteins. These proteases belong to different families, including members of the “a disintegrin and metalloprotease” (ADAM), the beta-site amyloid precursor protein cleaving enzymes (BACE), membrane-type matrix metalloproteases (MT-MMP) and rhomboids. Some of these proteases, in particular ADAM10 and BACE1 have been shown to be essential not only for the correct development of the mammalian brain, but also for myelination and maintaining neuronal connections in the adult nervous system. Additionally, these proteases are considered as drug targets for brain diseases, including Alzheimer’s disease (AD), schizophrenia and cancer. Despite their biomedical relevance, the molecular functions of these proteases in the brain have not been explored in much detail, as little was known about their substrates. This has changed with the recent development of novel proteomic methods which allow to identify substrates of membrane-bound proteases from cultured cells, primary neurons and other primary brain cells and even in vivo from minute amounts of mouse cerebrospinal fluid (CSF). This review summarizes the recent advances and highlights the strengths of the individual proteomic methods. Finally, using the example of the Alzheimer-related proteases BACE1, ADAM10 and γ-secretase, as well as ADAM17 and signal peptide peptidase like 3 (SPPL3), we illustrate how substrate identification with novel methods is instrumental in elucidating broad physiological functions of these proteases in the brain and other organs.

Proteomics of pediatric heart failure: from traditional biomarkers to new discovery strategies

Heart failure in children is a complex clinical syndrome with multiple aetiologies. The underlying disorders that lead to heart failure in children differ significantly from those in adults. Some clinical biomarkers for heart failure status and prognosis appear to be useful in both age groups. This review outlines the use and the present status of biomarkers for heart failure in paediatric cardiology. Furthermore, clinical scenarios in which development of new biomarkers might address management or prognosis are discussed. Finally, strategies for proteomic discovery of novel biomarkers and application to practice are described.

High-abundant protein depletion strategies applied on dog cerebrospinal fluid and evaluated by high-resolution mass spectrometry

As the number of fully sequenced animal genomes and the performance of advanced mass spectrometry-based proteomics techniques are continuously improving, there is now a great opportunity to increase the knowledge of various animal proteomes. This research area is further stimulated by a growing interest from veterinary medicine and the pharmaceutical industry. Cerebrospinal fluid (CSF) is a good source for better understanding of diseases related to the central nervous system, both in humans and other animals.

In this study, four high-abundant protein depletion columns, developed for human or rat serum, were evaluated for dog CSF. For the analysis, a shotgun proteomics approach, based on nanoLC-LTQ Orbitrap MS/MS, was applied. All the selected approaches were shown to deplete dog CSF with different success. It was demonstrated that the columns significantly improved the coverage of the detected dog CSF proteome. An antibody-based column showed the best performance, in terms of efficiency, repeatability and the number of proteins detected in the sample. In total 983 proteins were detected. Of those, 801 proteins were stated as uncharacterized in the UniProt database. To the best of our knowledge, this is the so far largest number of proteins reported for dog CSF in one single study.

We evaluated four high-abundant protein depletion kits on dog CSF.

High abundant depletion kit developed for humans/rats can be used for dog CSF.

Protein depletion of dog CSF gives extended coverage of the CSF proteome.

In total, 983 dog proteins were identified in this study.

Coupling enrichment methods with proteomics for understanding and treating disease

Owing to recent advances in proteomics analytical methods and bioinformatics capabilities there is a growing trend toward using these capabilities for the development of drugs to treat human disease, including target and drug evaluation, understanding mechanisms of drug action, and biomarker discovery. Currently, the genetic sequences of many major organisms are available, which have helped greatly in characterizing proteomes in model animal systems and humans. Through proteomics, global profiles of different disease states can be characterized (e.g. changes in types and relative levels as well as changes in PTMs such as glycosylation or phosphorylation). Although intracellular proteomics can provide a broad overview of physiology of cells and tissues, it has been difficult to quantify the low abundance proteins which can be important for understanding the diseased states and treatment progression. For this reason, there is increasing interest in coupling comparative proteomics methods with subcellular fractionation and enrichment techniques for membranes, nucleus, phosphoproteome, glycoproteome as well as low abundance serum proteins. In this review, we will provide examples of where the utilization of different proteomics-coupled enrichment techniques has aided target and biomarker discovery, understanding the drug targeting mechanism, and mAb discovery. Taken together, these improvements will help to provide a better understanding of the pathophysiology of various diseases including cancer, autoimmunity, inflammation, cardiovascular disease, and neurological conditions, and in the design and development of better medicines for treating these afflictions.

Liquid phase based separation systems for depletion, prefractionation, and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis-An update covering the period 2011-2014

This review article expands on the previous one (S. Selvaraju and Z. El Rassi, Electrophoresis 2012, 33, 74-88) by reviewing pertinent literature in the period extending from early 2011 to present. As the previous review article, the present one is concerned with proteomic sample preparation (e.g., depletion of high-abundance proteins, reduction of the protein dynamic concentration range, enrichment of a particular subproteome), and the subsequent chromatographic and/or electrophoretic prefractionation prior to peptide separation and identification by LC-MS/MS. This review article, however, is distinguished from its earlier version by expanding on capturing/enriching subphosphoproteomes by immobilized metal affinity chromatography and metal oxide affinity chromatography. Seventy-seven papers published in the period extending from mid-2011 to the present have been reviewed. By no means this review article is exhaustive, given the fact that its aim is to give a concise treatment of the latest developments in the field.

Removal of albumin and immunoglobulins from canine cerebrospinal fluid using depletion kits: a feasibility study

BACKGROUND

Highly abundant proteins in biological fluids such as serum or cerebrospinal fluid (CSF) can hinder the detection of proteins in lower abundance, e.g., potential biomarkers. Commercial products are available for the depletion of albumin and immunoglobulins (Igs), although most of these kits have not been validated for dog samples. The present study therefore examines the use of different types of depletion kits for dog CSF.

FINDINGS

Three kits, with different mechanisms for the depletion of albumin and Igs, were tested with dog CSF specimens. One product significantly decreased the amount of albumin; with all kits, IgG was less efficiently removed than albumin. Mass spectrometry of the fractions eluted from the depletion columns revealed considerable co-depletion of other CSF proteins.

CONCLUSIONS

A commercially available depletion kit was identified which depletes albumin and (to a lower extent) immunoglobulins from dog CSF. However, the limited efficacy and the concomitant loss of other proteins from the sample should be taken into account when using this product.

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.

Fast fixing and comprehensive identification to help improve real-time ligands discovery based on formaldehyde crosslinking, immunoprecipitation and SDS-PAGE separation

Background

Fast Fixation is necessary to study real-time protein-protein interactions under physiological conditions. Fast formaldehyde cross-linking can fix transient and weak protein interactions, thereby reducing the number of false negatives but producing great complexity. To reduce this complexity, immunoaffinity purification can Fish out complexes that include particular target proteins, but affinity-based co-purification has a limited capacity to eliminate nonspecific binding to beads and/or antibodies. To Filter out these complexes, SDS-PAGE is used to disrupt non-covalent bonds, thereby eliminating uncross-linked complexes and simultaneously providing molecular weight information for identification.

Results

We described a 4 F strategy to help improve real-time ligands discovery based on formaldehyde crosslinking, immunoprecipitation and SDS-PAGE separation: Fast Fix, Fish, and Filter, using albumin interactome as an example. The use of gel excision without staining makes this strategy comprehensive and sensitive. The target protein must be identified in the same slice as its ligands. The ligands must be identified in slices for the experimental group but not in the corresponding control slices. Only proteins that appear in the range of molecular weights equal to or greater than the sum of the proteins’ theoretical molecular weights, together with the target, are considered ligands. In this study, 5 s of cross-linking with 10% formaldehyde was achieved in human blood. The use of this strategy identified 35 ligands for albumin. Comparison with four major previous studies of the albuminome revealed that 68.57% of the 35 ligands identified in our study were identified in these other studies.

Conclusions

Fast cross-linking was achieved. The 4 F strategy can be used to identify real-time in situ interactions without prior intervention and to comprehensively identify ligands of particular target proteins with fewer false positives.