Affinity depletion of plasma and serum for mass spectrometry-based proteome analysis

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

Proteome Analysis of Serum Purified Using Solanum tuberosum and Lycopersicon esculentum Lectins

Serum and plasma exhibit a broad dynamic range of protein concentrations, posing challenges for proteome analysis. Various technologies have been developed to reduce this complexity, including high-abundance depletion methods utilizing antibody columns, extracellular vesicle enrichment techniques, and trace protein enrichment using nanobead cocktails. Here, we employed lectins to address this, thereby extending the scope of biomarker discovery in serum or plasma using a novel approach. We enriched serum proteins using 37 different lectins and subjected them to LC-MS/MS analysis with data-independent acquisition. Solanum tuberosum lectin (STL) and Lycopersicon esculentum lectin (LEL) enabled the detection of more serum proteins than the other lectins. STL and LEL bind to N-acetylglucosamine oligomers, emphasizing the significance of capturing these oligomer-binding proteins when analyzing serum trace proteins. Combining STL and LEL proved more effective than using them separately, allowing us to identify over 3000 proteins from serum through single-shot proteome analysis. We applied the STL/LEL trace-protein enrichment method to the sera of systemic lupus erythematosus model mice. This revealed differences in >1300 proteins between the systemic lupus erythematosus model and control mouse sera, underscoring the utility of this method for biomarker discovery.

Mass spectrometry as a lens into molecular human nutrition and health

Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.

Plasma proteomic signature of major depressive episode in the elderly

Depression is a complex and multifactorial disease, affecting about 6.5% of the elderly population in what is referred to as late-life depression (LLD). Despite its public health relevance, there is still limited information about the molecular mechanisms of LLD. We analyzed the blood plasma of 50 older adults, 19 with LLD and 31 controls, through untargeted mass spectrometry, and used systems biology tools to identify biochemical pathways and biological processes dysregulated in the disease. We found 96 differentially expressed proteins between LLD patients and control individuals. Using elastic-net regression, we generated a panel of 75 proteins that comprises a potential model for determining the molecular signature of LLD. We also showed that biological pathways related to vesicle-mediated transport and voltage-dependent calcium channels may be dysregulated in LLD. These data can help to build an understanding of the molecular basis of LLD, offering an integrated view of the biomolecular alterations that occur in this disorder. SIGNIFICANCE: Major depressive disorder in the elderly, called late-life depression (LLD), is a common and disabling disorder, with recent prevalence estimates of 6.5% in the general population. Despite the public health relevance, there is still limited information about the molecular mechanisms of LLD. The findings in this paper shed light on LLD heterogeneous biological mechanisms. We uncovered a potential novel biomolecular signature for LLD and biological pathways related to this condition which can be targets for the development of novel interventions for prevention, early diagnosis, and treatment of LLD.

Proteomics Landscape of Alzheimer's Disease

Alzheimer’s disease (AD) is the most prevalent form of dementia, and the numbers of AD patients are expected to increase as human life expectancy improves. Deposition of β-amyloid protein (Aβ) in the extracellular matrix and intracellular neurofibrillary tangles are molecular hallmarks of the disease. Since the precise pathophysiology of AD has not been elucidated yet, effective treatment is not available. Thus, understanding the disease pathology, as well as identification and development of valid biomarkers, is imperative for early diagnosis as well as for monitoring disease progression and therapeutic responses. Keeping this goal in mind several studies using quantitative proteomics platform have been carried out on both clinical specimens including the brain, cerebrospinal fluid (CSF), plasma and on animal models of AD. In this review, we summarize the mass spectrometry (MS)-based proteomics studies on AD and discuss the discovery as well as validation stages in brief to identify candidate biomarkers.

Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis

Multiple sclerosis (MS) is a neuroinflammatory disorder characterized by autoimmune-mediated inflammatory lesions in CNS leading to myelin damage and axonal loss. MS is a heterogenous disease with variable and unpredictable disease course. Due to its complex nature, MS is difficult to diagnose and responses to specific treatments may vary between individuals. Therefore, there is an indisputable need for biomarkers for early diagnosis, prediction of disease exacerbations, monitoring the progression of disease, and for measuring responses to therapy. Genomic and proteomic studies have sought to understand the molecular basis of MS and find biomarker candidates. Advances in next-generation sequencing and mass-spectrometry techniques have yielded an unprecedented amount of genomic and proteomic data; yet, translation of the results into the clinic has been underwhelming. This has prompted the development of novel data science techniques for exploring these large datasets to identify biologically relevant relationships and ultimately point towards useful biomarkers. Herein we discuss optimization of omics study designs, advances in the generation of omics data, and systems biology approaches aimed at improving biomarker discovery and translation to the clinic for MS.

Paper-based cascade cationic isotachophoresis: Multiplex detection of cardiac markers

Paper-based analytical devices (PADs) are widely used in point-of-care testing (POCT) as they are cost-effective, simple and straightforward. However, poor sensitivity hinders their use in detecting diseases with low abundance biomarkers. The poor detection limit of PADs is mainly attributed to the low concentration of analytes, and the complexity of biological fluid, leading to insufficient interactions between analytes and capture antibodies. This study aims to overcome these difficulties by developing a paper-based cationic isotachophoresis (ITP) approach for simultaneously detecting pico-molar levels of two essential cardiac protein markers: acidic troponin T (cTnT) and basic troponin I (cTnI) spiked into human serum samples. The approach utilizes 3-aminopropyltrimethoxysilane (APTMS) treated glass fiber papers with decreasing cross-sectional area assembled on a 3D printed cartridge device. Our results showed that in the presence of cTnT monoclonal antibody (mAb), fluorescently labeled cTnI and cTnT could be effectively enriched in cationic ITP. Each individual target was captured subsequently by a test line in the detection zone where the capture mAb was immobilized. Detailed analysis suggests that the technology is capable of simultaneous on-board depletion of abundant plasma proteins and enrichment of cTnI/cTnT by ~1300-fold with a sensitivity of 0.6 pmol/L for cTnT and a sensitivity of 1.5 pmol/L for cTnI in less than 6 min. The results demonstrate the potential of this technology for rapid, ultra-sensitive and cost-effective analysis of multiplex protein markers in clinical serum samples at point of care.

In-Depth Proteomic Analysis of Human Bronchoalveolar Lavage Fluid toward the Biomarker Discovery for Lung Cancers

PURPOSE

Lung cancer is among the most common cancers. Bronchoalveolar lavage fluid (BALF) can be easily obtained from patients with lung cancers. The aim is to develop a novel proteomic method of the molecule-based sensitive detection of biomarkers from BALF.

EXPERIMENTAL DESIGN

BALF samples are collected from segmental bronchus of 14 patients with lung cancers from Kyung Hee University Hospital. First, BALF proteome is depleted using a depletion column, and then peptides are prepared from the enriched low abundant proteins and fractionated by high pH reverse phase liquid chromatography prior to LC-MS/MS. Data are available via ProteomeXchange with identifier PXD012645.

RESULTS

A novel method is developed for in-depth proteomic analysis of BALF by combining antibody-based depletion of high abundant proteins from BALF with high pH peptide fractionation. Peptides are analyzed on a high resolution Orbitrap Fusion mass spectrometer. MaxQuant search result in the identification of 4615 protein groups mapped to 4534 genes.

CONCLUSIONS AND CLINICAL RELEVANCE

It is found that the method outperformed conventional BALF proteomic methods and it is believed that this method will facilitate the biomarker research for lung cancer. In addition, it is shown that BALF will be a great source of biomarkers of lung diseases.

Challenges in application of Raman spectroscopy to biology and materials

Raman spectroscopy has become an essential tool for chemists, physicists, biologists and materials scientists. In this article, we present the challenges in unravelling the molecule-specific Raman spectral signatures of different biomolecules like proteins, nucleic acids, lipids and carbohydrates based on the review of our work and the current trends in these areas. We also show how Raman spectroscopy can be used to probe the secondary and tertiary structural changes occurring during thermal denaturation of protein and lysozyme as well as more complex biological systems like bacteria. Complex biological systems like tissues, cells, blood serum etc. are also made up of such biomolecules. Using mice liver and blood serum, it is shown that different tissues yield their unique signature Raman spectra, owing to a difference in the relative composition of the biomolecules. Additionally, recent progress in Raman spectroscopy for diagnosing a multitude of diseases ranging from cancer to infection is also presented. The second part of this article focuses on applications of Raman spectroscopy to materials. As a first example, Raman spectroscopy of a melt cast explosives formulation was carried out to monitor the changes in the peaks which indicates the potential of this technique for remote process monitoring. The second example presents various modern methods of Raman spectroscopy such as spatially offset Raman spectroscopy (SORS), reflection, transmission and universal multiple angle Raman spectroscopy (UMARS) to study layered materials. Studies on chemicals/layered materials hidden in non-metallic containers using the above variants are presented. Using suitable examples, it is shown how a specific excitation or collection geometry can yield different information about the location of materials. Additionally, it is shown that UMARS imaging can also be used as an effective tool to obtain layer specific information of materials located at depths beyond a few centimeters.

This paper reviews various facets of Raman spectroscopy. This encompasses biomolecule fingerprinting and conformational analysis, discrimination of healthy vs. diseased states, depth-specific information of materials and 3D Raman imaging.

Identification of M. tuberculosis antigens in the sera of tuberculosis patients using biomimetic affinity chromatography in conjunction with ESI-CID-MS/MS

The profiling of abnormally-expressed proteins in host cells using mass spectrometry (MS) analysis is a classical approach for screening disease-associated biomarkers in clinical diagnosis. However, few pathogen-specific antigens can currently be detected in serum using this proteomic approach, since these are very low-abundant proteins that are easily masked by host high-abundant proteins. Identification of pathogen-specific antigens in the sera of tuberculosis patients is crucial for the clinical diagnosis of this infectious disease, especially in immune-compromised patients. In the present study, two biomimetic affinity chromatography (BiAC) media, At-23 and A115-94, were selected from a library of BiAC media and used to selectively fractionate Albumin and Immunoglobulin from sera, respectively, prior to MS analyses. Each fraction was collected and screened against the proteomic database of M. tuberculosis complex. Three antigens, FbpA, FbpB and BfrB, were identified with two distinct peptides in BiAC-fractionated sera from tuberculosis patients, which were confirmed by Western blotting. Moreover, the identification of pathogen-specific antigens in sera by BiAC in conjunction with ESI-CID-MS/MS represents a promising strategy for the discovery of disease-associated biomarkers in other diseases.

Depletion of Highly Abundant Proteins of the Human Blood Plasma: Applications in Proteomics Studies of Psychiatric Disorders

Psychiatric disorders are complex diseases involving exogenous and endogenous factors. Biomarkers for diagnosis or prediction of successful treatment are not existent. In addition, the molecular basis of these diseases is still poorly understood. Blood plasma represents the most complex proteome as it contains subproteomes from several body tissues. However, the high abundance of some little proteins can obscure the analysis of hundreds of low abundance proteins, which are potential biomarkers. Therefore, removal of these high abundance proteins is pivotal in any proteomic study of plasma. Here, we present a method of depleting these proteins using immunoaffinity liquid chromatography.

Identifying Biomarker Candidates in the Blood Plasma or Serum Proteome

Brain disorders are among the most complex and difficult to understand of human disorders in terms of pathophysiology and etiology. Differently from other human diseases such as cancer, which uses biomarkers in clinical practice, there are no prognostic and diagnostic biomarkers available for psychiatric disorders. Those associated with the likelihood of a successful medication are also not existent, impairing treatment strategies. Proteomics is a suitable tool for identifying such biomarkers to be validated and further implemented in the clinic. Here we present a protocol for the proteome analyses of blood plasma and serum collected in vivo, aiming for the discovery of potential biomarkers and the comprehension of the molecular bases of diseases and treatments.

Molecular serum signature of treatment resistant depression

RATIONALE

A substantial number of patients suffering from major depressive disorder (MDD) do not respond to multiple trials of anti-depressants, develop a chronic course of disease and become treatment resistant. Most of the studies investigating molecular changes in treatment-resistant depression (TRD) have only examined a limited number of molecules and genes. Consequently, biomarkers associated with TRD are still lacking.

OBJECTIVES

This study aimed to use recently advanced high-throughput proteomic platforms to identify peripheral biomarkers of TRD defined by two staging models, the Thase and Rush staging model (TRM) and the Maudsley Staging Model (MSM).

METHODS

Serum collected from an inpatient cohort of 65 individuals suffering from MDD was analysed using two different mass spectrometric-based platforms, label-free liquid chromatography mass spectrometry (LC-MS(E)) and selective reaction monitoring (SRM), as well as a multiplex bead based assay.

RESULTS

In the LC-MS(E) analysis, proteins involved in the acute phase response and complement activation and coagulation were significantly different between the staging groups in both models. In the multiplex bead-based assay analysis TNF-α levels (log(odds) = -4.95, p = 0.045) were significantly different in the TRM comparison. Using SRM, significant changes of three apolipoproteins A-I (β = 0.029, p = 0.035), M (β = -0.017, p = 0.009) and F (β = -0.031, p = 0.024) were associated with the TRM but not the MSM.

CONCLUSION

Overall, our findings suggest that proteins, which are involved in immune and complement activation, may represent potential biomarkers that could be used by clinicians to identify high-risk patients. Nevertheless, given that the molecular changes between the staging groups were subtle, the results need to be interpreted cautiously.

Optimizing Human Bile Preparation for Two-Dimensional Gel Electrophoresis

Aims. Bile is an important body fluid which assists in the digestion of fat and excretion of endogenous and exogenous compounds. In the present study, an improved sample preparation for human bile was established. Methods and Material. The method involved acetone precipitation followed by protein extraction using commercially available 2D Clean-Up kit. The effectiveness was evaluated by 2-dimensional electrophoresis (2DE) profiling quality, including number of protein spots and spot distribution. Results. The total protein of bile fluid in benign biliary disorders was 0.797 ± 0.465 μg/μL. The sample preparation method using acetone precipitation first followed by 2D Clean-Up kit protein extraction resulted in better quality of 2DE gel images in terms of resolution as compared with other sample preparation methods. Using this protocol, we obtained approximately 558 protein spots on the gel images and with better protein spots presentation of haptoglobin, serum albumin, serotransferrin, and transthyretin. Conclusions. Protein samples of bile prepared using acetone precipitation followed by 2D Clean-Up kit exhibited high protein resolution and significant protein profile. This optimized protein preparation protocol can effectively concentrate bile proteins, remove abundant proteins and debris, and yield clear presentation of nonabundant proteins and its isoforms on 2-dimensional electrophoresis gel images.

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

Human biofluids, especially blood plasma or serum, hold great potential as the sources of candidate biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge for detecting promising low-abundance proteins. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high- and moderate-abundance proteins, thus enabling much more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomic applications in human biofluids. The limitations and future perspectives of immunoaffinity separation methods are also discussed.

Biological pathways modulated by antipsychotics in the blood plasma of schizophrenia patients and their association to a clinical response

Proteomics is a valuable tool to unravel molecular mechanisms involved in human disorders. Considering the mediocre effectiveness of antipsychotics, which are the main class of drug used to treat schizophrenia, we analyzed a cohort of 58 schizophrenia patients who had blood collected before and after 6 weeks of antipsychotic treatment using a shotgun mass spectrometry proteomic profiling approach. Our aim was to unravel molecular pathways involved with an effective drug response. The results showed that all patients had essentially the same biochemical pathways triggered Independent of the antipsychotic response outcome. However, we observed that these pathways were regulated in different directions in blood samples from those who responded well to antipsychotics, compared with those who had a poorer outcome. These data are novel, timely and may help to guide new research efforts in the design of new treatments or medications for schizophrenia based on biologically relevant pathways.

Deciphering the biochemistry and identifying biomarkers to multiple sclerosis

Multiple sclerosis is an idiopathic demyelinating disease of the CNS. Despite being extensively studied during the last decades, many molecular aspects of the disease are still to be elucidated. Moreover, biomarkers for treatment and early diagnosis are major issues to be tackled. In this edition of Kroksveen et al. (Proteomics 2015, 15, 3361-3369) present biomarker candidates for the early detection of multiple sclerosis. Despite the need for validation in larger sets of samples, this dataset contributes to resolve open questions associated to multiple sclerosis.

Body fluid biomarkers in multiple sclerosis: how far we have come and how they could affect the clinic now and in the future

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system, which affects over 2.5 million people worldwide. Although MS has been extensively studied, many challenges still remain in regards to treatment, diagnosis and prognosis. Typically, prognosis and individual responses to treatment are evaluated by clinical tests such as the expanded disability status scale, MRI and presence of oligoclonal bands in the cerebrospinal fluid. However, none of these measures correlates strongly with treatment efficacy or disease progression across heterogeneous patient populations and subtypes of MS. Numerous studies over the past decades have attempted to identify sensitive and specific biomarkers for diagnosis, prognosis and treatment efficacy of MS. The objective of this article is to review and discuss the current literature on body fluid biomarkers in MS, including research on potential biomarker candidates in the areas of miRNA, mRNA, lipids and proteins.

Ten years of proteomics in multiple sclerosis

Multiple sclerosis, which is the most common cause of chronic neurological disability in young adults, is an inflammatory, demyelinating, and neurodegenerative disease of the CNS, which leads to the formation of multiple foci of demyelinated lesions in the white matter. The diagnosis is based currently on magnetic resonance image and evidence of dissemination in time and space. However, this could be facilitated if biomarkers were available to rule out other disorders with similar symptoms as well as to avoid cerebrospinal fluid analysis, which requires an invasive collection. Additionally, the molecular mechanisms of the disease are not completely elucidated, especially those related to the neurodegenerative aspects of the disease. The identification of biomarker candidates and molecular mechanisms of multiple sclerosis may be approached by proteomics. In the last 10 years, proteomic techniques have been applied in different biological samples (CNS tissue, cerebrospinal fluid, and blood) from multiple sclerosis patients and in its experimental model. In this review, we summarize these data, presenting their value to the current knowledge of the disease mechanisms, as well as their importance in identifying biomarkers or treatment targets.

Proteomic changes in serum of first onset, antidepressant drug-naïve major depression patients

Major depressive disorder (MDD) is a complex and multi-factorial disorder. Although genetic factors and other molecular aspects of MDD have been widely studied, the underlying pathological mechanisms are still mostly unknown. We sought to investigate the pathophysiology of MDD by identifying and characterising serum molecular differences and their correlation to symptom severity in first onset, antidepressant drug-naïve MDD patients. We performed an exploratory molecular profiling study on serum samples of MDD patients and controls using multiplex immunoassay and label-free liquid chromatography mass spectrometry in data independent mode (LC-MSE). We included two independent cohorts of first onset, antidepressant drug-naïve MDD patients (n = 23 and 15) and matched controls (n = 42 and 21) in our study in order to validate the results. The main outcome included the following list of circulatory molecules changing and/or correlating to symptom severity: angiotensin-converting enzyme, acute phase proteins (e.g. ferritin and serotransferrin), brain-derived neurotrophic factor, complement component C4-B, cortisol, cytokines (e.g. macrophage migration inhibitory factor and interleukin-16), extracellular newly identified receptor for advanced glycosylation end products-binding protein, growth hormone and superoxide dismutase-1. This study provides evidence of an increased pro-inflammatory and oxidative stress response, followed by a hyperactivation of the HPA-axis in the acute stages of first onset MDD, as well as a dysregulation in growth factor pathways. These findings help to elucidate MDD related pathways in more detail and further studies may lead to identification of novel drug targets, including components of the inflammatory and oxidative stress response.

Microwave & magnetic (M2) proteomics reveals CNS-specific protein expression waves that precede clinical symptoms of experimental autoimmune encephalomyelitis

Central nervous system-specific proteins (CSPs), transported across the damaged blood-brain-barrier (BBB) to cerebrospinal fluid (CSF) and blood (serum), might be promising diagnostic, prognostic and predictive protein biomarkers of disease in individual multiple sclerosis (MS) patients because they are not expected to be present at appreciable levels in the circulation of healthy subjects. We hypothesized that microwave &magnetic (M(2)) proteomics of CSPs in brain tissue might be an effective means to prioritize putative CSP biomarkers for future immunoassays in serum. To test this hypothesis, we used M(2) proteomics to longitudinally assess CSP expression in brain tissue from mice during experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. Confirmation of central nervous system (CNS)-infiltrating inflammatory cell response and CSP expression in serum was achieved with cytokine ELISPOT and ELISA immunoassays, respectively, for selected CSPs. M(2) proteomics (and ELISA) revealed characteristic CSP expression waves, including synapsin-1 and α-II-spectrin, which peaked at day 7 in brain tissue (and serum) and preceded clinical EAE symptoms that began at day 10 and peaked at day 20. Moreover, M(2) proteomics supports the concept that relatively few CNS-infiltrating inflammatory cells can have a disproportionally large impact on CSP expression prior to clinical manifestation of EAE.

Applications of low-flow LC–SRM for the analysis of large molecules in pharmaceutical R&D

Although ligand-binding assays are frequently employed to measure large molecules, the use of LC–SRM assays is increasingly popular due to the inherent selectivity advantage and the ability to operate without exquisitely selective antibodies. Until recently LC–SRM assays have been unable to compete with ligand-binding assays in terms of sensitivity. However, the use of low-flow chromatography prior to mass spectrometry has played a crucial role in increasing the sensitivity of LC–SRM platforms and enabling measurements of large molecules that had previously been unmeasurable. In this article, we highlight some technical advances, describe strategies for employing low-flow chromatography, and review recent literature that describes implementation of low-flow LC–SRM to support large-molecule analysis in pharmaceutical R&D.