In-depth exploration of cerebrospinal fluid by combining peptide ligand library treatment and label-free protein quantification

Cerebrospinal Fluid Proteome Map Reveals Molecular Signatures of Reversible Cerebral Vasoconstriction Syndrome

Reversible cerebral vasoconstriction syndrome (RCVS) is a complex neurovascular disorder characterized by repetitive thunderclap headaches and reversible cerebral vasoconstriction. The pathophysiological mechanism of this mysterious syndrome remains underexplored and there is no clinically available molecular biomarker. To provide insight into the pathogenesis of RCVS, this study reported the first landscape of dysregulated proteome of cerebrospinal fluid (CSF) in patients with RCVS (n  =  21) compared to the age- and sex-matched controls (n  =  20) using data-independent acquisition mass spectrometry. Protein-protein interaction and functional enrichment analysis were employed to construct functional protein networks using the RCVS proteome. An RCVS-CSF proteome library resource of 1054 proteins was established, which illuminated large groups of upregulated proteins enriched in the brain and blood-brain barrier (BBB). Personalized RCVS-CSF proteomic profiles from 17 RCVS patients and 20 controls reveal proteomic changes involving the complement system, adhesion molecules, and extracellular matrix, which may contribute to the disruption of BBB and dysregulation of neurovascular units. Moreover, an additional validation cohort validated a panel of biomarker candidates and a two-protein signature predicted by machine learning model to discriminate RCVS patients from controls with an area under the curve of 0.997. This study reveals the first RCVS proteome and a potential pathogenetic mechanism of BBB and neurovascular unit dysfunction. It also nominates potential biomarker candidates that are mechanistically plausible for RCVS, which may offer potential diagnostic and therapeutic opportunities beyond the clinical manifestations.

Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a clinically and biologically heterogenous disease with currently unpredictable progression and relapse. After the development and success of neurofilament as a cerebrospinal fluid (CSF) biomarker, there is reinvigorated interest in identifying other markers of or contributors to disease. The objective of this study is to probe the predictive potential of a panel of brain-enriched proteins on MS disease progression and subtype.

METHODS

This study includes 40 individuals with MS and 14 headache controls. The MS cohort consists of 20 relapsing remitting (RR) and 20 primary progressive (PP) patients. The CSF of all individuals was analyzed for 63 brain enriched proteins using a method of liquid-chromatography tandem mass spectrometry. Wilcoxon rank sum test, Kruskal-Wallis one-way ANOVA, logistic regression, and Pearson correlation were used to refine the list of candidates by comparing relative protein concentrations as well as relation to known imaging and molecular biomarkers.

RESULTS

We report 30 proteins with some relevance to disease, clinical subtype, or severity. Strikingly, we observed widespread protein depletion in the disease CSF as compared to control. We identified numerous markers of relapsing disease, including KLK6 (kallikrein 6, OR = 0.367, p < 0.05), which may be driven by active disease as defined by MRI enhancing lesions. Other oligodendrocyte-enriched proteins also appeared at reduced levels in relapsing disease, namely CNDP1 (carnosine dipeptidase 1), LINGO1 (leucine rich repeat and Immunoglobin-like domain-containing protein 1), MAG (myelin associated glycoprotein), and MOG (myelin oligodendrocyte glycoprotein). Finally, we identified three proteins-CNDP1, APLP1 (amyloid beta precursor like protein 1), and OLFM1 (olfactomedin 1)-that were statistically different in relapsing vs. progressive disease raising the potential for use as an early biomarker to discriminate clinical subtype.

CONCLUSIONS

We illustrate the utility of targeted mass spectrometry in generating potential targets for future biomarker studies and highlight reductions in brain-enriched proteins as markers of the relapsing remitting disease stage.

Neuronal autoantibodies in the cerebrospinal fluid of 148 patients with schizophrenia and 151 healthy controls

Schizophrenia is a syndrome with multiple etiologies, one of which is the potential for an autoimmune disease of the brain such as N-methyl-d-aspartate receptor (NMDAR) encephalitis, which can induce psychosis resembling schizophrenia. Here, we examined anti-neuronal autoantibodies related to psychosis using both cell- (CBA) and tissue-based assays (TBA) in the cerebrospinal fluid (CSF) of patients with chronic schizophrenia and control participants. First, we screened for the antibodies against leucine-rich glioma-inactivated 1 (LGI1), γ-aminobutyric acid B receptor (GABABR), dipeptidyl aminopeptidase-like protein 6 (DPPX), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR1/R2), and contactin-associated protein-like 2 (CASPR2) in 148 patients with schizophrenia. No antibodies were detected. Next, we performed CBA for NMDAR antibodies in 148 patients with schizophrenia and 151 age- and sex-matched controls. Although we detected relatively weak immunoreactivity for NMDAR in the CSFs of two patients with schizophrenia and three controls, no samples were positive when strict criteria were applied. For TBA in the rat hippocampus and cerebellum, we detected positive signals in the CSFs of 13 patients with schizophrenia and eight controls. Positive samples were analyzed for paraneoplastic syndrome and antinuclear antibodies using immunoblotting. The CSFs of nine patients and six controls were positive for dense fine speckle 70 (DFS70) antibodies. Additionally, antibodies against centromere protein (CENP)-A and CENP-B were detected in patients with schizophrenia. Our results suggest that autoantibodies against NMDAR, LG1, GABABR, DPPX, AMPAR1/R2, and CASPR2 are not associated with the pathogenesis of chronic schizophrenia. Moreover, we emphasize the importance of considering the effect of anti-DFS70 antibodies when analyzing autoantibodies in CSF samples. Conclusively, we obtained no evidence suggesting that the most frequent neuronal autoantibodies in the CSF play a role in the pathogenesis of schizophrenia, even in our sample.

Microglia and complement mediate early corticostriatal synapse loss and cognitive dysfunction in Huntington's disease

Huntington's disease (HD) is a devastating monogenic neurodegenerative disease characterized by early, selective pathology in the basal ganglia despite the ubiquitous expression of mutant huntingtin. The molecular mechanisms underlying this region-specific neuronal degeneration and how these relate to the development of early cognitive phenotypes are poorly understood. Here we show that there is selective loss of synaptic connections between the cortex and striatum in postmortem tissue from patients with HD that is associated with the increased activation and localization of complement proteins, innate immune molecules, to these synaptic elements. We also found that levels of these secreted innate immune molecules are elevated in the cerebrospinal fluid of premanifest HD patients and correlate with established measures of disease burden.In preclinical genetic models of HD, we show that complement proteins mediate the selective elimination of corticostriatal synapses at an early stage in disease pathogenesis, marking them for removal by microglia, the brain's resident macrophage population. This process requires mutant huntingtin to be expressed in both cortical and striatal neurons. Inhibition of this complement-dependent elimination mechanism through administration of a therapeutically relevant C1q function-blocking antibody or genetic ablation of a complement receptor on microglia prevented synapse loss, increased excitatory input to the striatum and rescued the early development of visual discrimination learning and cognitive flexibility deficits in these models. Together, our findings implicate microglia and the complement cascade in the selective, early degeneration of corticostriatal synapses and the development of cognitive deficits in presymptomatic HD; they also provide new preclinical data to support complement as a therapeutic target for early intervention.

Beyond the amyloid hypothesis: how current research implicates autoimmunity in Alzheimer's disease pathogenesis

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

Cerebrospinal fluid camk2a levels at baseline predict long-term progression in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) remains a highly unpredictable disease. Many hope that fluid biomarkers may contribute to better stratification of disease, aiding the personalisation of treatment decisions, ultimately improving patient outcomes.

OBJECTIVE

The objective of this study was to evaluate the predictive value of CSF brain-specific proteins from early in the disease course of MS on long term clinical outcomes.

METHODS

In this study, 34 MS patients had their CSF collected and stored within 5 years of disease onset and were then followed clinically for at least 15 years. CSF concentrations of 64 brain-specific proteins were analyzed in the 34 patient CSF, as well as 19 age and sex-matched controls, using a targeted liquid-chromatography tandem mass spectrometry approach.

RESULTS

We identified six CSF brain-specific proteins that significantly differentiated MS from controls (p < 0.05) and nine proteins that could predict disease course over the next decade. CAMK2A emerged as a biomarker candidate that could discriminate between MS and controls and could predict long-term disease progression.

CONCLUSION

Targeted approaches to identify and quantify biomarkers associated with MS in the CSF may inform on long term MS outcomes. CAMK2A may be one of several candidates, warranting further exploration.

DIGE Analysis of ProteoMiner™ Fractionated Serum/Plasma Samples

The discovery of clinically relevant biomarkers using gel-based proteomics has proven extremely challenging, principally because of the large dynamic range of protein abundances in biofluids such as blood and the fact that only a small number of proteins constitute the vast majority of total blood protein mass. Various separation, depletion, enrichment, and quantitative developments coupled with improvements in gel-based protein quantification technologies, specifically fluorescence two-dimensional difference gel electrophoresis (2D-DIGE), have contributed to significant improvements in the detection and identification of lower abundance proteins. One of these enrichment technologies, ProteoMiner, is the focus of this chapter. The ProteoMiner technology utilizes hexapeptide bead library with huge diversity to bind and enrich low-abundance proteins but at the same time suppresses the concentration of high-abundance proteins in subsequent analysis.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Combinatorial peptides: A library that continuously probes low-abundance proteins

After a decade of experimental applications, it is the objective of this review to make a point on combinatorial peptide ligand libraries dedicated to low-abundance proteins from animals to plants and to microorganism proteomics. It is, thus, at the light of the recent technical developments and applications that we will examine the state of the art, its usage within the scientific community, and its openness to unexplored fields. The improvements of the methodology and its implementation in connection with analytical determinations of combinatorial peptide ligand library (CPLL)-treated samples are extensively reviewed and commented upon. Relevant examples covering few critical aspects describe the performance of the technology. Finally, a reflection on the technological future is attempted in particular by involving new concepts adapted to the limited availability of certain biological samples.

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.

Profiling of Cerebrospinal Fluid Lipids and Their Relationship with Plasma Lipids in Healthy Humans

Lipidomics provides an overview of lipid profiles in biological systems. Although blood is commonly used for lipid profiling, cerebrospinal fluid (CSF) is more suitable for exploring lipid homeostasis in brain diseases. However, whether an individual’s background affects the CSF lipid profile remains unclear, and the association between CSF and plasma lipid profiles in heathy individuals has not yet been defined. Herein, lipidomics approaches were employed to analyze CSF and plasma samples obtained from 114 healthy Japanese subjects. Results showed that the global lipid profiles differed significantly between CSF and plasma, with only 13 of 114 lipids found to be significantly correlated between the two matrices. Additionally, the CSF total protein content was the primary factor associated with CSF lipids. In the CSF, the levels of major lipids, namely, phosphatidylcholines, sphingomyelins, and cholesterolesters, correlated with CSF total protein levels. These findings indicate that CSF lipidomics can be applied to explore changes in lipid homeostasis in patients with brain diseases.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including β-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment.

METHOD

We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (n = 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time.

RESULTS

Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discriminate between individuals with AD and non-AD cognitive impairment as well as Tau/β-amyloid ratio. Notably, SMOC1 levels in postmortem brain are highly correlated with AD pathology even in the preclinical stage of disease, indicating that CSF SMOC1 levels reflect underlying brain pathology specific for AD.

CONCLUSION

Collectively these findings highlight the utility of targeted MS approaches to quantify biomarkers associated with AD that could be used for monitoring disease progression, stratifying patients for clinical trials and measuring therapeutic response.

Potential Plasticity of the Mannoprotein Repertoire Associated to Mycobacterium tuberculosis Virulence Unveiled by Mass Spectrometry-Based Glycoproteomics

To date, Mycobacterium tuberculosis (Mtb) remains the world’s greatest infectious killer. The rise of multidrug-resistant strains stresses the need to identify new therapeutic targets to fight the epidemic. We previously demonstrated that bacterial protein-O-mannosylation is crucial for Mtb infectiousness, renewing the interest of the bacterial-secreted mannoproteins as potential drug-targetable virulence factors. The difficulty of inventorying the mannoprotein repertoire expressed by Mtb led us to design a stringent multi-step workflow for the reliable identification of glycosylated peptides by large-scale mass spectrometry-based proteomics. Applied to the differential analyses of glycoproteins secreted by the wild-type Mtb strain—and by its derived mutant invalidated for the protein-O-mannosylating enzyme PMTub—this approach led to the identification of not only most already known mannoproteins, but also of yet-unknown mannosylated proteins. In addition, analysis of the glycoproteome expressed by the isogenic recombinant Mtb strain overexpressing the PMTub gene revealed an unexpected mannosylation of proteins, with predicted or demonstrated functions in Mtb growth and interaction with the host cell. Since in parallel, a transient increased expression of the PMTub gene has been observed in the wild-type bacilli when infecting macrophages, our results strongly suggest that the Mtb mannoproteome may undergo adaptive regulation during infection of the host cells. Overall, our results provide deeper insights into the complexity of the repertoire of mannosylated proteins expressed by Mtb, and open the way to novel opportunities to search for still-unexploited potential therapeutic targets.

Characterization of Postprandial Effects on CSF Metabolomics: A Pilot Study with Parallel Comparison to Plasma

Cerebrospinal fluid (CSF) metabolites reflect biochemical diffusion/export from the brain and possibly serve as biomarkers related to brain disease severity, pathophysiology, and therapeutic efficacy/toxicity. Metabolomic studies using blood matrices have demonstrated interindividual and preanalytical variation of blood metabolites, whereas those of CSF metabolites remain unclear. In this study, we aimed to delineate the postprandial effects on CSF metabolites because fasting of patients with brain-related disorders is challenging. We collected pre- and postprandial (1.5, 3, and 6 h) plasma and CSF from nine healthy subjects. Using a mass-spectrometry-based global metabolomics approach, 150 and 130 hydrophilic metabolites and 263 and 340 lipids were detected in CSF and plasma, respectively. Principal component analysis of CSF hydrophilic metabolites and lipids primarily classified individual subjects at any time point, suggesting that the postprandial effects had a lower impact than interindividual variations on CSF metabolites. Individually, less than 10% of the CSF metabolites were putatively altered by postprandial effects (with either significant differences or over 2-fold changes, but not both) at any time point. Thus, global CSF metabolite levels are not directly associated with food intake, and except for several putatively altered CSF metabolites, postprandial effects are not a major concern when applying CSF metabolomics to screen biomarkers.

Low-abundance plant protein enrichment with peptide libraries to enlarge proteome coverage and related applications

In plant tissues proteins are present in low amounts but in a very large number. To this peculiar situation many complex foreign components render protein extraction and purification very difficult. In the last several years interesting technologies have been described to improve the technical situation to the point that some methodologies allow reaching very low-abundance proteins and minor allergens. Among enrichment methods the one documented in this report is based on combinatorial peptide ligand libraries (CPLLs) that emerged in the last decade by contributing to largely improve the knowledge in plant proteomics. It is the aim of this review to describe how this technology allows detecting low-abundance proteins from various plant tissues and to report the dynamics of the proteome components in response to environmental changes and biotic attacks. Typical documented examples with the description of their scientific interest are reported. The described technical approach and selected applications are considered as one of the most advanced approaches for plant proteomics investigations with possibilities not only to enlarge the knowledge of plant proteomes but also to discover novel allergens as well as plant biomarkers subsequent to stressful situations.

Affinity depletion versus relative protein enrichment: a side-by-side comparison of two major strategies for increasing human cerebrospinal fluid proteome coverage

Cerebrospinal fluid (CSF) is in direct contact with the central nervous system. This makes human CSF an attractive source of potential biomarkers for neurologic diseases. Similarly to blood plasma, proteomic analysis of CSF is complicated by a high dynamic range of individual protein concentrations and by the presence of several highly abundant proteins. To deal with the abundant human CSF proteins, methods developed for blood plasma/serum are routinely used. Multiple affinity removal systems and protein enrichment of less abundant proteins using a combinatorial peptide ligand library are among the most frequent approaches. However, their relative impact on CSF proteome coverage has never been evaluated side-by-side in a single study. Therefore, we explored the effect of CSF depletion using MARS 14 cartridge and ProteoMiner ligand library on the number of CSF proteins identified in subsequent LC–MS/MS analysis. LC–MS/MS analysis of crude (non-treated) CSF provided roughly 500 identified proteins. Depletion of CSF by MARS 14 cartridge increased the number of identifications to nearly 800, while treatment of CSF using ProteoMiner enabled identification of 600 proteins. To explore the potential losses of CSF proteins during the depletion process, we also analyzed the “waste” fractions generated by both methods, i.e., proteins retained by the MARS 14 cartridge, and the molecules present in the flow-through fraction from ProteoMiner. More than 250 proteins were bound to MARS 14 cartridge, 100 of those were not identified in the corresponding depleted CSF. Similarly, analysis of the waste fraction in ProteoMiner workflow provided almost 70 unique proteins not found in the CSF depleted by the ligand library. Both depletion strategies significantly increased the number of identified CSF proteins compared to crude CSF. However, MARS 14 depletion provided a markedly higher number of identified proteins (773) compared to ProteoMiner (611). Further, we showed that CSF proteins are lost due to co-depletion (MARS 14) or exclusion (ProteoMiner) during the depletion process. This suggests that the routinely discarded “waste” fractions contain proteins of potential interest and should be included in CSF biomarker studies.

Deployment of Label-Free Quantitative Olfactory Proteomics to Detect Cerebrospinal Fluid Biomarker Candidates in Synucleinopathies

Nowadays, diagnosis of neurodegenerative disorders is mainly based on neuroimaging and clinical symptoms, although postmortem neuropathological confirmation remains the gold standard diagnostic technique. Therefore, cerebrospinal fluid (CSF) proteome is considered a valuable molecular repository for diagnosing and targeting the neurodegenerative process. It is well known that olfactory dysfunction is among the earliest features of synucleinopathies such as Parkinson's disease (PD). Consequently, we consider that the application of tissue proteomics in primary olfactory structures is an ideal approach to explore early pathophysiological changes, detecting olfactory proteins that might be tested in CSF as potential biomarkers. Data mining of mass spectrometry-generated datasets has revealed that 30% of the olfactory bulb (OB) proteome is also localized in CSF. In this chapter, we describe a method that utilizes label-free quantitative proteomics and computational analysis to characterize human OB proteomes and potential cerebrospinal fluid (CSF) biomarkers associated with neurodegenerative syndromes. For that, we applied peptide fractionation methods, followed by tandem mass spectrometry (nanoLC-MS/MS), in silico analysis, and semi-quantitative orthogonal techniques in OB derived from PD subjects. After obtaining the differential OB proteome across Lewy-type alpha-synucleinopathy (LTS) stages and further validating the method, this workflow was applied to probe changes in NEGR1 (neuronal growth regulator 1) and GNPDA2 (glucosamine-6-phosphate deaminase 2) protein levels in CSF derived from parkinsonian subjects with respect to controls, observing an inverse correlation between both proteins and α-synuclein, the principal component analysis of Lewy pathology.

Deep Dive on the Proteome of Human Cerebrospinal Fluid: A Valuable Data Resource for Biomarker Discovery and Missing Protein Identification

Cerebrospinal fluid (CSF) is a body fluid of choice for biomarker studies of brain disorders but remains relatively under-studied compared with other biological fluids such as plasma, partly due to the more invasive means of its sample collection. The present study establishes an in-depth CSF proteome through the analysis of a unique CSF sample from a pool of donors. After immunoaffinity depletion, the CSF sample was fractionated using off-gel electrophoresis and analyzed with liquid chromatography tandem mass spectrometry (MS) using the latest generation of hybrid Orbitrap mass spectrometers. The shotgun proteomic analysis allowed the identification of 20 689 peptides mapping on 3379 proteins. To the best of our knowledge, the obtained data set constitutes the largest CSF proteome published so far. Among the CSF proteins identified, 34% correspond to genes whose transcripts are highly expressed in brain according to the Human Protein Atlas. The principal Alzheimer's disease biomarkers (e.g., tau protein, amyloid-β, apolipoprotein E, and neurogranin) were detected. Importantly, our data set significantly contributes to the Chromosome-centric Human Proteome Project (C-HPP), and 12 proteins considered as missing are proposed for validation in accordance with the HPP guidelines. Of these 12 proteins, 8 proteins are based on 2 to 6 uniquely mapping peptides from this CSF analysis, and 4 match a new peptide with a "stranded" single peptide in PeptideAtlas from previous CSF studies. The MS proteomic data are available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD009646.

DIGE Analysis of ProteoMinerTM Fractionated Serum/Plasma Samples

The discovery of clinically relevant biomarkers using gel-based proteomics has proven extremely challenging, principally because of the large dynamic range of protein abundances in biofluids such as blood and the fact that only a small number of proteins constitute the vast majority of total blood protein mass. Various separation, depletion, enrichment, and quantitative developments coupled with improvements in gel-based protein quantification technologies, specifically difference gel electrophoresis (DIGE), have contributed to significant improvements in the detection and identification of lower abundance proteins. One of these enrichment technologies, Proteominer, will be the focus of this chapter. The Proteominer technology a utilizes hexapeptide bead library with huge diversity to bind and enrich low-abundance proteins but at the same time suppressing the concentration of high-abundance proteins in subsequent analysis.

Evidence for a Role of Nerve Injury in Painful Intervertebral Disc Degeneration: A Cross-Sectional Proteomic Analysis of Human Cerebrospinal Fluid

Intervertebral disc degeneration (DD) is a cause of low back pain (LBP) in some individuals. However, although >30% of adults have DD, LBP only develops in a subset of individuals. To gain insight into the mechanisms underlying nonpainful versus painful DD, human cerebrospinal fluid (CSF) was examined using differential expression shotgun proteomic techniques comparing healthy control participants, subjects with nonpainful DD, and patients with painful DD scheduled for spinal fusion surgery. Eighty-eight proteins were detected, 27 of which were differentially expressed. Proteins associated with DD tended to be related to inflammation (eg, cystatin C) regardless of pain status. In contrast, most differentially expressed proteins in DD-associated chronic LBP patients were linked to nerve injury (eg, hemopexin). Cystatin C and hemopexin were selected for further examination using enzyme-linked immunosorbent assay in a larger cohort. While cystatin C correlated with DD severity but not pain or disability, hemopexin correlated with pain intensity, physical disability, and DD severity. This study shows that CSF can be used to study mechanisms underlying painful DD in humans, and suggests that while painful DD is associated with nerve injury, inflammation itself is not sufficient to develop LBP.

PERSPECTIVE

CSF was examined for differential protein expression in healthy control participants, pain-free adults with asymptomatic intervertebral DD, and LBP patients with painful intervertebral DD. While DD was related to inflammation regardless of pain status, painful degeneration was associated with markers linked to nerve injury.

Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods

This data article describes a controlled, spiked proteomic dataset for which the “ground truth” of variant proteins is known. It is based on the LC-MS analysis of samples composed of a fixed background of yeast lysate and different spiked amounts of the UPS1 mixture of 48 recombinant proteins. It can be used to objectively evaluate bioinformatic pipelines for label-free quantitative analysis, and their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. More specifically, it can be useful for tuning software tools parameters, but also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. The raw MS files can be downloaded from ProteomeXchange with identifier PXD001819. Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1]. The experimental design used here for data processing takes advantage of the different spike levels introduced in the samples composing the dataset, and processed data are merged in a single file to facilitate the evaluation and illustration of software tools results for the detection of variant proteins with different absolute expression levels and fold change values.

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.

New insights into the human brain proteome: Protein expression profiling of deep brain stimulation target areas

Deep brain stimulation (DBS) is a neurosurgical procedure that provides therapeutic benefits for movement and affective disorders. The nucleus basalis of Meynert (NBM) and substantia nigra (SN) are considered target areas to apply DBS. Even though the degeneration of NBM and SN underlies the cognitive decline observed in neurological diseases, the protein knowledge derived from both areas is scarce. We have characterized the proteome present in both subcortical brain areas using the Triple TOF 5600 mass spectrometer, identifying 2775 and 3469 proteoforms in NBM and SN respectively. Data mining of MS-generated proteomic data have revealed that: i) 675 proteins tend to localize to synaptic ending, ii) 61% of the global dataset is also present in human CSF and/or plasma, and iii) 894 proteins have not been previously identified in healthy brain by MS. The correlation of NBM and SN proteomic expression profiles with human brain transcriptome data available at Allen Brain Atlas has revealed protein evidence for 250 genes considered with brain-wide expression and 112 genes with region-specific expression in human brain. In addition, protein datasets have been classified according to their chromosomal origin, increasing the current proteome coverage in healthy human brain.

BIOLOGICAL SIGNIFICANCE

The nucleus basalis of Meynert and substantia nigra are brain areas of clinical interest to apply the deep brain stimulation (DBS) technology in neurosurgery. Our proteomic characterization has revealed 675 proteins involved in the regulation of synaptic transmission, electrical machinery, and neurotransmitter release in both DBS target areas. Moreover, 2599 identified proteins present capacity to be secreted to the CSF and plasma. Our data contribute to a further step towards the characterization of the anatomical atlas of the human brain proteome, detecting 652 proteins that are common between different basal ganglia structures. This article is part of a Special Issue entitled: HUPO 2014.

Accessing to the minor proteome of red blood cells through the influence of the nanoparticle surface properties on the corona composition

Nanoparticle (NP)-protein interactions in complex samples have not yet been clearly understood. Nevertheless, several studies demonstrated that NP's physicochemical features significantly impact on the protein corona composition. Taking advantage of the NP potential to harvest different subsets of proteins, we assessed for the first time the capacity of three kinds of superparamagnetic NPs to highlight the erythrocyte minor proteome. Using both qualitative and quantitative proteomics approaches, nano-liquid chromatography-tandem mass spectrometry allowed the identification of 893 different proteins, confirming the reproducible capacity of NPs to increase the number of identified proteins, through a reduction of the sample concentration range and the capture of specific proteins on the three different surfaces. These NP-specific protein signatures revealed significant differences in their isoelectric point and molecular weight. Moreover, this NP strategy offered a deeper access to the erythrocyte proteome highlighting several signaling pathways implicated in important erythrocyte functions. The automated potentiality, the reproducibility, and the low-consuming sample demonstrate the strong compatibility of our strategy for large-scale clinical studies and may become a standardized sample preparation in future erythrocyte-associated proteomics studies.

Toward defining the anatomo-proteomic puzzle of the human brain: An integrative analysis

The human brain is exceedingly complex, constituted by billions of neurons and trillions of synaptic connections that, in turn, define ∼900 neuroanatomical subdivisions in the adult brain (Hawrylycz et al. An anatomically comprehensive atlas of the human brain transcriptome. Nature 2012, 489, 391-399). The human brain transcriptome has revealed specific regional transcriptional signatures that are regulated in a spatiotemporal manner, increasing the complexity of the structural and molecular organization of this organ (Kang et al. Spatio-temporal transcriptome of the human brain. Nature 2011, 478, 483-489). During the last decade, neuroproteomics has emerged as a powerful approach to profile neural proteomes using shotgun-based MS, providing complementary information about protein content and function at a global level. Here, we revise recent proteome profiling studies performed in human brain, with special emphasis on proteome mapping of anatomical macrostructures, specific subcellular compartments, and cerebrospinal fluid. Moreover, we have performed an integrative functional analysis of the protein compilation derived from these large-scale human brain proteomic studies in order to obtain a comprehensive view of human brain biology. Finally, we also discuss the potential contribution of our meta-analysis to the Chromosome-centric Human Proteome Project initiative.

Deciphering preferential interactions within supramolecular protein complexes: the proteasome case

In eukaryotic cells, intracellular protein breakdown is mainly performed by the ubiquitin-proteasome system. Proteasomes are supramolecular protein complexes formed by the association of multiple sub-complexes and interacting proteins. Therefore, they exhibit a very high heterogeneity whose function is still not well understood. Here, using a newly developed method based on the combination of affinity purification and protein correlation profiling associated with high-resolution mass spectrometry, we comprehensively characterized proteasome heterogeneity and identified previously unknown preferential associations within proteasome sub-complexes. In particular, we showed for the first time that the two main proteasome subtypes, standard proteasome and immunoproteasome, interact with a different subset of important regulators. This trend was observed in very diverse human cell types and was confirmed by changing the relative proportions of both 20S proteasome forms using interferon-γ. The new method developed here constitutes an innovative and powerful strategy that could be broadly applied for unraveling the dynamic and heterogeneous nature of other biologically relevant supramolecular protein complexes.

TOM1 is a PI5P effector involved in the regulation of endosomal maturation

Phosphoinositides represent a major class of lipids specifically involved in the organisation of signaling cascades, maintenance of the identity of organelles and regulation of multiple intracellular trafficking steps. We previously described that phosphatidylinositol 5-monophosphate (PI5P), produced by the Shigella flexneri phosphatase IpgD, is implicated in the endosomal sorting of the EGFR. Here, we show that the adaptor protein TOM1 is a new PI5P direct binding partner. We identify the domain of TOM1 involved in this interaction and characterize the binding motif. Finally, we demonstrate that the recruitment of TOM1 by PI5P on signaling endosomes is responsible for the delay in EGFR degradation and fluid-phase bulk endocytosis. Taken together, our data strongly suggest that PI5P-enrichment in signaling endosomes prevents endosomal maturation through the recruitment of TOM1, and point out to a new function of PI5P in regulating discrete maturation steps in the endosomal system.

Sample treatment methods involving combinatorial peptide ligand libraries for improved proteomes analyses

If used in an optimized manner, the technology of combinatorial peptide solid-phase libraries can easily improve the analytical determinations of proteomes by several factors. The discovery of novel species and of early stage biomarkers becomes thus reachable with a simple sample treatment. This report describes the most important point to consider (overloading and full recovery) along with a minimum scientific background and gives then detailed recipes to laboratory technicians. Orientations for optional routes are also given according to the objective of the experimental investigations. This covers different approaches to capture proteins of very low abundance. Total protein harvestings to prevent partial losses are also described such as single exhaustive desorption and fractionated elutions for more detailed analyses. Documented results are also reported demonstrating the capability of the technology well beyond what is the common assumption.

Solid-phase extraction strategies to surmount body fluid sample complexity in high-throughput mass spectrometry-based proteomics

For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations.

Label-free quantitative urinary proteomics identifies the arginase pathway as a new player in congenital obstructive nephropathy

Obstructive nephropathy is a frequently encountered situation in newborns. In previous studies, the urinary peptidome has been analyzed for the identification of clinically useful biomarkers of obstructive nephropathy. However, the urinary proteome has not been explored yet and should allow additional insight into the pathophysiology of the disease. We have analyzed the urinary proteome of newborns (n = 5/group) with obstructive nephropathy using label free quantitative nanoLC-MS/MS allowing the identification and quantification of 970 urinary proteins. We next focused on proteins exclusively regulated in severe obstructive nephropathy and identified Arginase 1 as a potential candidate molecule involved in the development of obstructive nephropathy, located at the crossroad of pro- and antifibrotic pathways. The reduced urinary abundance of Arginase 1 in obstructive nephropathy was verified in independent clinical samples using both Western blot and MRM analysis. These data were confirmed in situ in kidneys obtained from a mouse obstructive nephropathy model. In addition, we also observed increased expression of Arginase 2 and increased total arginase activity in obstructed mouse kidneys. mRNA expression analysis of the related arginase pathways indicated that the pro-fibrotic arginase-related pathway is activated during obstructive nephropathy. Taken together we have identified a new actor in the development of obstructive nephropathy in newborns using quantitative urinary proteomics and shown its involvement in an in vivo model of disease. The present study demonstrates the relevance of such a quantitative urinary proteomics approach with clinical samples for a better understanding of the pathophysiology and for the discovery of potential therapeutic targets.

Microscale depletion of high abundance proteins in human biofluids using IgY14 immunoaffinity resin: analysis of human plasma and cerebrospinal fluid

Removal of highly abundant proteins in plasma is often carried out using immunoaffinity depletion to extend the dynamic range of measurements to lower abundance species. While commercial depletion columns are available for this purpose, they generally are not applicable to limited sample quantities (<20 μL) due to low yields stemming from losses caused by nonspecific binding to the column matrix and concentration of large eluent volumes. Additionally, the cost of the depletion media can be prohibitive for larger-scale studies. Modern LC-MS instrumentation provides the sensitivity necessary to scale-down depletion methods with minimal sacrifice to proteome coverage, which makes smaller volume depletion columns desirable for maximizing sample recovery when samples are limited, as well as for reducing the expense of large-scale studies. We characterized the performance of a 346 μL column volume microscale depletion system, using four different flow rates to determine the most effective depletion conditions for ∼6-μL injections of human plasma proteins and then evaluated depletion reproducibility at the optimum flow rate condition. Depletion of plasma using a commercial 10-mL depletion column served as the control. Results showed depletion efficiency of the microscale column increased as flow rate decreased, and that our microdepletion was reproducible. In an initial application, a 600-μL sample of human cerebrospinal fluid (CSF) pooled from multiple sclerosis patients was depleted and then analyzed using reversed phase liquid chromatography-mass spectrometry to demonstrate the utility of the system for this important biofluid where sample quantities are more commonly limited.

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.

Endoplasmic reticulum stress-activated transcription factor ATF6α requires the disulfide isomerase PDIA5 to modulate chemoresistance

ATF6α, a membrane-anchored transcription factor from the endoplasmic reticulum (ER) that modulates the cellular response to stress as an effector of the unfolded-protein response (UPR), is a key player in the development of tumors of different origin. ATF6α activation has been linked to oncogenic transformation and tumor maintenance; however, the mechanism(s) underlying this phenomenon remains elusive. Here, using a phenotypic small interfering RNA (siRNA) screening, we identified a novel role for ATF6α in chemoresistance and defined the protein disulfide isomerase A5 (PDIA5) as necessary for ATF6α activation upon ER stress. PDIA5 contributed to disulfide bond rearrangement in ATF6α under stress conditions, thereby leading to ATF6α export from the ER and activation of its target genes. Further analysis of the mechanism demonstrated that PDIA5 promotes ATF6α packaging into coat protein complex II (COPII) vesicles and that the PDIA5/ATF6α activation loop is essential to confer chemoresistance on cancer cells. Genetic and pharmacological inhibition of the PDIA5/ATF6α axis restored sensitivity to the drug treatment. This work defines the mechanisms underlying the role of ATF6α activation in carcinogenesis and chemoresistance; furthermore, it identifies PDIA5 as a key regulator ATF6α-mediated cellular functions in cancer.