Data-Independent Acquisition and Label-Free Quantification for Quantitative Proteomics Analysis of Human Cerebrospinal Fluid.

This article presents a practical guide to mass spectrometry-based data-independent acquisition and label-free quantification for proteomics analysis applied to cerebrospinal fluid, offering a robust and scalable approach to probing the proteomic composition of the central nervous system. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Cerebrospinal fluid sample collection and preparation for mass spectrometry analysis Basic Protocol 2: Mass spectrometry sample analysis with data-independent acquisition Support Protocol: Data-dependent mass spectrometry and spectral library construction Basic Protocol 3: Analysis of mass spectrometry data.

Mass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition.

The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N,N-dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS2) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.

Quantitative Measurement of Intrathecally Synthesized Proteins in Mice.

Cerebrospinal fluid (CSF), a fluid found in the brain and the spinal cord, is of great importance to both basic and clinical science. The analysis of the CSF protein composition delivers crucial information in basic neuroscience research as well as neurological diseases. One caveat is that proteins measured in CSF may derive from both intrathecal synthesis and transudation from serum, and protein analysis of CSF can only determine the sum of these two components. To discriminate between protein transudation from the blood and intrathecally produced proteins in animal models as well as in humans, CSF protein profiling measurements using conventional protein analysis tools must include the calculation of the albumin CSF/serum quotient (Qalbumin), a marker of the integrity of the blood-brain interface (BBI), and the protein index (Qprotein/Qalbumin), an estimate of intrathecal protein synthesis. This protocol illustrates the entire procedure, from CSF and blood collection to quotients and indices calculations, for the quantitative measurement of intrathecal protein synthesis and BBI impairment in mouse models of neurological disorders.

CSF Sample Preparation for Data-Independent Acquisition.

To study changes in neurological diseases and to identify disease-related mechanisms or biomarkers for diagnosis, cerebrospinal fluid (CSF) is frequently used for proteomic-based discovery. In the last years, development and application of mass spectrometry (MS) techniques have made essential contributions to proteomic studies including protein identification as well as quantification. Until recently, biomarker discovery studies were performed through bottom-up proteomics utilizing data-dependent acquisition. However, drawbacks like stochastic selection of precursor ions cause the exclusion of low-abundant ions from fragmentation as well as from data analysis leading to technical variances among different samples and result in inconsistent data sets. In contrast, data-independent acquisition (DIA) enables almost complete and reproducible quantitative analysis gaining more and more interest as a method for reliable MS-based protein quantification. Besides the utilization of a proper analysis platform, a prerequisite for biomarker studies is the selection of suitable samples and sample processing strategies. Especially for CSF, blood contamination has tremendous impact on the quantitative analysis. In addition, complex processing methods such as protein or peptide fractionation prior to MS analysis can lead to variabilities that affect the reliability of the quantitative results. Here we present methods to evaluate in a first step the CSF quality in regard to blood contamination for the subsequent MS-based sample preparation and finally a DIA method for the analysis of CSF.

Sample Fractionation Techniques for CSF Peptide Spectral Library Generation.

Data-independent acquisition (DIA) is becoming more prominent as a method for comprehensive proteomic analysis of clinical samples due to its ability to acquire essentially all fragment ion spectra in a single LC-ESI-MS/MS experiment. Since the direct correlation between a precursor and its fragment ions is lost when acquiring all ions in a defined m/z range, one data analysis strategy is using so-called peptide spectral libraries. These are usually generated by measuring similar biological samples in data-dependent (DDA) mode. The peptide spectral library content is a major limitation for the successful identification from DIA data. This is because a fragment ion spectrum from the sample can only be matched, and thus identified, when it is present in the peptide spectral library. In order to enhance peptide spectral library size, the sample for generating the peptide spectral library can be subjected to extended separation strategies prior to DDA. These strategies are of special relevance for biological samples containing a few very high-abundant proteins, such as CSF, as they enlarge the identification of low-abundant proteins. In instances of CSF separation, suitable methods include the 1D SDS-PAGE of proteins and high-pH reversed-phase peptide fractionation. Both methods are based on different protein/peptide characteristics, are complementary with one another, and are inexpensive and easy to establish. Ideally, DDA spectra from samples generated with both methods combine to achieve a comprehensive spectral library.

Application of 2D-DIGE and iTRAQ Workflows to Analyze CSF in Gliomas.

Proteomics is an indispensable tool for disease biomarker discovery. It is widely used for the analysis of biological fluids such as cerebrospinal fluid (CSF), blood, and saliva, which further aids in our understanding of disease incidence and progression. CSF is often the biospecimen of choice in case of intracranial tumors, as rapid changes in the tumor microenvironment can be easily assessed due to its close proximity to the brain. On the contrary studies comprising of serum or plasma samples do not truly reflect the underlying molecular alterations due to the presence of protective blood-brain barrier. We have described in here the detailed workflows for two advanced proteomics techniques, namely, 2D-DIGE (two-dimensional difference in-gel electrophoresis) and iTRAQ (isobaric tag for relative and absolute quantitation), for CSF analysis. Both of these techniques are very sensitive and widely used for quantitative proteomics analysis.

Peptidomic Workflow Applied to Cerebrospinal Fluid Analysis.

Proteo-peptidomic profiling of biofluids is used to identify disease biomarkers and to study molecular mechanisms of pathology development. Previously, we studied changes in cerebrospinal fluid (CSF) and blood plasma associated with Guillain-Barre syndrome (GBS)-a rare and severe disorder of the peripheral nervous system with an unknown etiology. Here, we describe the workflow for the analysis of endogenous peptides from CSF. The procedure covers sample preparation, liquid chromatography-mass spectrometry (LC-MS) analysis, and bioinformatics analysis and allows identification of more than 1100 peptides from 181 protein groups in ~3 h from a single CSF sample derived from non-neurological, non-oncological patients.

Quantitative Evaluation of Different Protein Fractions of Cerebrospinal Fluid Using 18O Labeling.

Molecular analysis of cerebrospinal fluid (CSF) provides comprehensive information on physiological and pathological processes related to the brain. In particular, proteomic studies give insights into the pathogenesis of many brain diseases which still pose diagnostic and therapeutic challenges. The identification of reliable biomarkers is an important step to meet these challenges. Mass spectrometry is an essential proteomic tool, not only for highly sensitive identification of proteins and posttranslational modifications, but also for their reliable quantification. Here, 18O labeling of tryptic peptides was employed to qualitative and quantitative analyses of protein fractions obtained by depletion of highly abundant proteins from cerebrospinal fluid. It was found that the execution of the investigated depletion protocols may cause the loss of potential protein biomarkers of neurological diseases.

A Versatile Workflow for Cerebrospinal Fluid Proteomic Analysis with Mass Spectrometry: A Matter of Choice between Deep Coverage and Sample Throughput.

Human cerebrospinal fluid (CSF) is a sample of choice in the study of brain disorders. This biological fluid circulates in the brain and the spinal cord and contains tissue-specific proteins, indicative of health and disease conditions. Despite its potential as a valid source of biological markers, CSF remains largely understudied as compared to blood, in particular due to its more invasive way of sampling.Challenges remain when performing proteomic analysis in clinical research studies. State-of-the-art mass spectrometry (MS) enables deep characterization of the human proteome. But some technical limitations are cardinal to be addressed, such as the capacity to routinely analyze large cohorts of samples. Importantly, a trade-off still needs to be made between the proteome coverage depth and the number of measured samples. In this context, we developed a scalable automated proteomic pipeline for the analysis of CSF. Because of its versatility, this workflow can be adapted to accommodate proteome coverage and/or sample throughput. It allows us to prepare and quantitatively analyze hundreds to thousands of CSF samples; it can also allow identification of more than 3000 proteins in a CSF sample when coupled with isoelectric focusing fractionation.In this chapter, we describe an end-to-end pipeline for the proteomic analysis of CSF. The main steps of the sample preparation comprise spiking of a standard, protein digestion, isobaric labeling, and purification; these are performed in a 96-well plate format enabling automation. Depending on the targeted depth of the CSF proteome, optional analytical steps can be included, such as the removal of abundant proteins and sample pre-fractionation. Liquid chromatography tandem MS as well as data processing and analysis complete the pipeline.

SWATH Mass Spectrometry Applied to Cerebrospinal Fluid Differential Proteomics: Establishment of a Sample-Specific Method.

Mass spectrometry (MS) has become the gold standard method for proteomics by allowing the simultaneous identification and/or quantification of thousands of proteins of a given sample. Over time, mass spectrometry has evolved into newer quantitative approaches with increased sensitivity and accuracy, such as the sequential windows acquisition of all theoretical fragment-ion spectra (SWATH)-MS approach. Moreover, in the past few years, some improvements were made in the SWATH-acquisition algorithm, allowing the design of sample-customized acquisition methods by adjusting the Q1 windows' width in order to reduce it in the most populated m/z regions. This customization results in an increase in the specificity and a reduction in the interferences, ultimately leading to an improvement in the amount of quantitative data extracted to eventually increase the proteome coverage. These improvements are especially relevant for clinical neuroproteomics, which is mainly based on the analysis of circulatory biofluids, in particular the cerebrospinal fluid (CSF) due to its close connection with the brain.In the present chapter, a detailed description of the methodologies necessary to perform a whole-proteome relative quantification of CSF samples by SWATH-MS is presented, starting with the isolation of the protein fraction, its preparation for MS analysis, with all the necessary information for the design of a SWATH-MS method specific for each sample batch, and finally providing different methodologies for the analysis of the quantitative data obtained.

Top-Down Proteomics Applied to Human Cerebrospinal Fluid.

Cerebrospinal fluid (CSF) is the fluid of choice to study pathologies and disorders of the central nervous system (CNS). Its composition, especially its proteins and peptides, holds the promise that it may reflect the pathological state of an individual. Traditionally, proteins and peptides in CSF have been analyzed using bottom-up proteomics technologies in the search of high proteome coverage. However, the limited protein sequence coverage of this technology means that information regarding post-translational modifications (PTMs) and alternative splice variants is lost. As an alternative technology, top-down proteomics offers low to medium proteome coverage, but high protein coverage enabling almost a full characterization of the proteins' primary structure. This allows us to precisely identify distinct molecular forms of proteins (proteoforms) as well as naturally occurring bioactive peptide fragments, which could be of critical biological relevance and would otherwise remain undetected with a classical proteomics approach.Here, we describe various strategies including sample preparation protocols, off-line intact protein prefractionation, and LC-MS/MS methods together with data analysis pipelines to analyze cerebrospinal fluid (CSF) by top-down proteomics. However, there is not a unique or standardized method and the selection of the top-down strategy will depend on the exact goal of the study. Here, we describe various top-down proteomics methods that enable rapid protein characterization and may be an excellent companion analytical workflow in the search for new protein biomarkers in neurodegenerative diseases.

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.

Untargeted Metabolomics Relative Quantification by SWATH Mass Spectrometry Applied to Cerebrospinal Fluid.

Cerebrospinal fluid (CSF) has been considered the key source for the search of biomarkers, in particular for neurological diseases, such as Alzheimer's and Parkinson's disease, since it reflects the state of the central nervous system (CNS). Finding biomarkers in the earliest stages of neurodegenerative diseases has become imperative, since, at the moment, there are no drugs that can reverse these pathological processes. Untargeted metabolomics analysis by liquid chromatography combined with SWATH-MS relative quantification is an emerging approach to search for potential biomarkers. In this chapter, we describe a method for untargeted metabolomics analysis of CSF samples that can also be used in parallel to a proteomics approach. The analysis is focused on the SWATH acquisition mode, where beyond precursor's relative quantification, the information of the MS/MS relative quantification is also used to help in the search of new potential biomarkers.

Essential Features and Use Cases of the Cerebrospinal Fluid Proteome Resource (CSF-PR).

Every year, a large number of published studies present biomarkers for various neurological disorders. Many of these studies are based on mass spectrometry proteomics data and describe comparison of the abundance of proteins in cerebrospinal fluid between two or more disease groups. As the number of such studies is growing, it is no longer straightforward to obtain an overview of which specific proteins are increased or decreased between the numerous relevant diseases and their many subcategories, or to see the larger picture or trends between related diseases. To alleviate this situation, we therefore mined the literature for mass spectrometry-based proteomics studies including quantitative protein data from cerebrospinal fluid of patients with multiple sclerosis, Alzheimer's disease, and Parkinson's disease and organized the extracted data in the Cerebrospinal Fluid Proteome Resource (CSF-PR). CSF-PR is freely available online at http://probe.uib.no/csf-pr , is highly interactive, and allows for easy navigation, visualization, and export of the published scientific data. This chapter will guide the user through some of the most important features of the tool and show examples of the suggested use cases.

Plasmatic Signature of Disease by Differential Scanning Calorimetry (DSC).

Differential scanning calorimetry (DSC) has been used for several decades to characterize thermal stability of macromolecules such as proteins and DNA. It allows to determine the denaturation temperature and enthalpy of individual domains of proteins, thus giving new insights into their domain organization and ligand interaction. Over the past decade, it has been shown that this technique can also be used to study biofluids such as plasma or cerebrospinal fluid to obtain denaturation profiles. An increasing number of studies demonstrated that such profiles obtained from patients were significantly different from profiles obtained using biofluids of healthy individuals. This opens interesting perspectives for new diagnostics and monitoring tools for a large number of diseases. Nevertheless, the extensive studies of plasma samples from patients with different pathologies as well as the development of standardized methods of data analysis are necessary to reach the promising diagnostic potential of this methodology. Using plasma samples from healthy individuals and glioblastoma patients, we outline the steps necessary to obtain a plasmatic calorimetric profile with VP-DSC instrument and describe a cluster analysis of obtained data.

Survival associated with cerebrospinal fluid analysis in downer adult dairy cows: A retrospective study (2006-2014).

BACKGROUND: Threshold values for total nucleated cell count (TNCC) and protein concentration in cerebrospinal fluid (CSF) of downer dairy cows suggestive of a spinal cord lesion were recently published. OBJECTIVES: Determine short- and long-term survival of downer cows that underwent CSF analysis using the reported threshold values. Evaluate the prognostic value of these threshold values to predict short- and long-term survival. ANIMALS: Two hundred and fourteen downer adult dairy cows that underwent CSF analysis during hospitalization at the Centre Hospitalier Universitaire Vétérinaire (CHUV) of the Université de Montréal. METHODS: Retrospective study. Medical records of downer adult dairy cows presented to the hospital between January 2006 and October 2014 for which CSF analysis results were available were studied. Short-term (discharge from hospital) and long-term (completion of lactation) survival were determined and compared in accordance with CSF TNCC and protein concentration, using a Chi-square test. RESULTS: Cows with CSF TNCC and/or protein concentration above the threshold values had a significantly lower short-term survival rate (P = .02). The odds of nonsurvival of cows with one or both CSF values above the threshold values was 2.16 times higher than the odds for cows with values under the threshold values. CSF TNCC >4.5 cells/µL had sensitivity and specificity of 17.3% (95% CI: 10.7%-25.7%) and 92.3% (95% CI: 85.4%-96.6%), respectively, for predicting short-term nonsurvival. CSF protein concentration >0.39 g/L had sensitivity and specificity of 20.9% (95% CI: 13.7%-29.7%) and 91.4% (95% CI: 84.2%-96.0%), respectively. CONCLUSIONS: CSF analysis above threshold values used in this study is associated with increased odds of short-term nonsurvival.

Relapsing-Remitting Multiple Sclerosis diagnosis from cerebrospinal fluids via Fourier transform infrared spectroscopy coupled with multivariate analysis.

Multiple sclerosis (MS) is a chronic, progressive, inflammatory and degenerative disease of central nervous system. Here, we aimed to develop a method for differential diagnosis of Relapsing-Remitting MS (RRMS) and clinically isolated syndrome (CIS) patients, as well as to identify CIS patients who will progress to RRMS, from cerebrospinal fluid (CSF) by infrared (IR) spectroscopy and multivariate analysis. Spectral analyses demonstrated significant differences in the molecular contents, especially in the lipids and Z conformation of DNA of CSF from CIS, CIS to RRMS transformed (TCIS) and RRMS groups. These changes enables the discrimination of diseased groups and controls (individuals with no neurological disease) from each other using hierarchical cluster and principal component analysis. Some CIS samples were consistently clustered in RRMS class, which may indicate that these CIS patients potentially will transform to RRMS over time. Z-DNA band at 795 cm-1 that is existent only in diseased groups and significant increase in carbonyl amount, decrease in amideI/amide II and lipid/protein ratios observed only for RRMS groups can be used as diagnostic biomarkers. The results of the present study shed light on the early diagnosis of RRMS by IR spectroscopy complemented with multivariate analysis tools.

Biochemical analysis of cerebrospinal fluid in the laboratories of deployed medical treatment facilities: are Multistix 10 SG strip and iSTAT useful?

INTRODUCTION: During military deployment, the diagnosis and the management of acute bacterial meningitis can be problematic, as deployed Medical Treatment Facilities (MTFs) often have a limited laboratory diagnostic capability. However, French Role 2 and 3 MTFs have point-of-care (POC) testing to perform urinary (Multistix 10 SG strip) and blood (iSTAT handheld analyser) biochemical testing mentioned in AMedP8.5. The purpose of this study was to compare the accuracy of this urine test strip and of the iSTAT CHEM8 and CG4 cartridges with a standard hospital bench top analyser in order to determine if these POC devices have a potential role in the biochemical analysis of cerebrospinal fluid (CSF protein, CSF glucose and CSF lactate, respectively). METHODS: Agreement between the index methods and the reference methods (suitable kits on the Cobas 6 000 System) was evaluated by parallel testing of 30 CSF samples by both techniques. For CSF protein, agreement between the strip and the reference method was evaluated determining the κ coefficient. For CSF glucose and CSF lactate subgroups, least squares linear regressions were calculated and Bland-Altman analyses were performed. RESULTS: The Multistix 10 SG strip can be used to make a semiquantitative determination of CSF protein. A good agreement between the strip and the reference method was observed (κ coefficient: 0.93 (IC95 0.82 to 1)). This strip is thus well adapted to demonstrate an elevation of CSF protein level as observed in acute bacterial meningitis. The iSTAT CHEM8 and CG4+ cartridges correlated well with the reference methods for the determination of CSF glucose and CSF lactate, respectively (r2>0.98) but exhibited a negative bias (∼ -7% and ∼ -15%, respectively). CONCLUSIONS: The combined use of the Multistix 10 SG strip and of the iSTAT system appears to be an attractive solution for the biochemical investigation of CSF in medical treatment facilities with limited laboratory diagnostic capability.

Insights into the human brain proteome: Disclosing the biological meaning of protein networks in cerebrospinal fluid.

Cerebrospinal fluid (CSF) is an excellent source of biological information regarding the nervous system, once it is in close contact and accurately reflects alterations in this system. Several studies have analyzed differential protein profiles of CSF samples between healthy and diseased human subjects. However, the pathophysiological mechanisms and how CSF proteins relate to diseases are still poorly known. By applying bioinformatics tools, we attempted to provide new insights on the biological and functional meaning of proteomics data envisioning the identification of putative disease biomarkers. Bioinformatics analysis of data retrieved from 99 mass spectrometry (MS)-based studies on CSF profiling highlighted 1985 differentially expressed proteins across 49 diseases. A large percentage of the modulated proteins originate from exosome vesicles, and the majority are involved in either neuronal cell growth, development, maturation, migration, or neurotransmitter-mediated cellular communication. Nevertheless, some diseases present a unique CSF proteome profile, which were critically analyzed in the present study. For instance, 48 proteins were found exclusively upregulated in the CSF of patients with Alzheimer's disease and are mainly involved in steroid esterification and protein activation cascade processes. A higher number of exclusively upregulated proteins were found in the CSF of patients with multiple sclerosis (76 proteins) and with bacterial meningitis (70 proteins). Whereas in multiple sclerosis, these proteins are mostly involved in the regulation of RNA metabolism and apoptosis, in bacterial meningitis the exclusively upregulated proteins participate in inflammation and antibacterial humoral response, reflecting disease pathogenesis. The exploration of the contribution of exclusively upregulated proteins to disease pathogenesis will certainly help to envision potential biomarkers in the CSF for the clinical management of nervous system diseases.