Protein variability in cerebrospinal fluid and its possible implications for neurological protein biomarker research.

Cerebrospinal fluid is investigated in biomarker studies for various neurological disorders of the central nervous system due to its proximity to the brain. Currently, only a limited number of biomarkers have been validated in independent studies. The high variability in the protein composition and protein abundance of cerebrospinal fluid between as well as within individuals might be an important reason for this phenomenon. To evaluate this possibility, we investigated the inter- and intraindividual variability in the cerebrospinal fluid proteome globally, with a specific focus on disease biomarkers described in the literature. Cerebrospinal fluid from a longitudinal study group including 12 healthy control subjects was analyzed by label-free quantification (LFQ) via LC-MS/MS. Data were quantified via MaxQuant. Then, the intra- and interindividual variability and the reference change value were calculated for every protein. We identified and quantified 791 proteins, and 216 of these proteins were abundant in all samples and were selected for further analysis. For these proteins, we found an interindividual coefficient of variation of up to 101.5% and an intraindividual coefficient of variation of up to 29.3%. Remarkably, these values were comparably high for both proteins that were published as disease biomarkers and other proteins. Our results support the hypothesis that natural variability greatly impacts cerebrospinal fluid protein biomarkers because high variability can lead to unreliable results. Thus, we suggest controlling the variability of each protein to distinguish between good and bad biomarker candidates, e.g., by utilizing reference change values to improve the process of evaluating potential biomarkers in future studies.

Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry.

Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.

Distinct metabolomic signature in cerebrospinal fluid in early parkinson's disease.

OBJECTIVE: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early-stage PD diagnosis. METHODS: By applying a non-targeted and mass spectrometry-driven approach, we investigated the CSF metabolome of 44 early-stage sporadic PD patients yet without treatment (DeNoPa cohort). We compared all detected metabolite levels with those measured in CSF of 43 age- and gender-matched healthy controls. After this analysis, we validated the results in an independent PD study cohort (Tübingen cohort). RESULTS: We identified that dehydroascorbic acid levels were significantly lower and fructose, mannose, and threonic acid levels were significantly higher (P < .05) in PD patients when compared with healthy controls. These changes reflect pathological oxidative stress responses, as well as protein glycation/glycosylation reactions in PD. Using a machine learning approach based on logistic regression, we successfully predicted the origin (PD patients vs healthy controls) in a second (n = 18) as well as in a third and completely independent validation set (n = 36). The biomarker signature is composed of the three markers-mannose, threonic acid, and fructose-and allows for sample classification with a sensitivity of 0.790 and a specificity of 0.800. CONCLUSION: We identified PD-specific metabolic changes in CSF that were associated with antioxidative stress response, glycation, and inflammation. Our results disentangle the complexity of the CSF metabolome to unravel metabolome changes related to early-stage PD. The detected biomarkers help understanding PD pathogenesis and can be applied as biomarkers to increase clinical diagnosis accuracy and patient care in early-stage PD. © 2017 International Parkinson and Movement Disorder Society.

Metabolic profiling of body fluids and multivariate data analysis.

Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC-MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC-MS measurement and guidelines for the subsequent data analysis. Advantages of this protocol include: •Robust and reproducible metabolomics results, taking into account pre-analytical variations that may occur during the sampling process•Small sample volume required•Rapid and cost-effective processing of biological samples•Logistic regression based determination of biomarker signatures for in-depth data analysis.

Proteomics of rimmed vacuoles define new risk allele in inclusion body myositis.

OBJECTIVE: Sporadic inclusion body myositis (sIBM) pathogenesis is unknown; however, rimmed vacuoles (RVs) are a constant feature. We propose to identify proteins that accumulate within RVs. METHODS: RVs and intact myofibers were laser microdissected from skeletal muscle of 18 sIBM patients and analyzed by a sensitive mass spectrometry approach using label-free spectral count-based relative protein quantification. Whole exome sequencing was performed on 62 sIBM patients. Immunofluorescence was performed on patient and mouse skeletal muscle. RESULTS: A total of 213 proteins were enriched by >1.5 -fold in RVs compared to controls and included proteins previously reported to accumulate in sIBM tissue or when mutated cause myopathies with RVs. Proteins associated with protein folding and autophagy were the largest group represented. One autophagic adaptor protein not previously identified in sIBM was FYCO1. Rare missense coding FYCO1 variants were present in 11.3% of sIBM patients compared with 2.6% of controls (p = 0.003). FYCO1 colocalized at RVs with autophagic proteins such as MAP1LC3 and SQSTM1 in sIBM and other RV myopathies. One FYCO1 variant protein had reduced colocalization with MAP1LC3 when expressed in mouse muscle. INTERPRETATION: This study used an unbiased proteomic approach to identify RV proteins in sIBM that included a novel protein involved in sIBM pathogenesis. FYCO1 accumulates at RVs, and rare missense variants in FYCO1 are overrepresented in sIBM patients. These FYCO1 variants may impair autophagic function, leading to RV formation in sIBM patient muscle. FYCO1 functionally connects autophagic and endocytic pathways, supporting the hypothesis that impaired endolysosomal degradation underlies the pathogenesis of sIBM. Ann Neurol 2017;81:227-239.

Low-bias phosphopeptide enrichment from scarce samples using plastic antibodies.

Phosphospecific enrichment techniques and mass spectrometry (MS) are essential tools for comprehending the cellular phosphoproteome. Here, we report a fast and simple approach for low sequence-bias phosphoserine (pS) peptide capture and enrichment that is compatible with low biological or clinical sample input. The approach exploits molecularly imprinted polymers (MIPs, "plastic antibodies") featuring tight neutral binding sites for pS or pY that are capable of cross-reacting with phosphopeptides of protein proteolytic digests. The versatility of the resulting method was demonstrated with small samples of whole-cell lysate from human embryonic kidney (HEK) 293T cells, human neuroblastoma SH-SY5Y cells, mouse brain or human cerebrospinal fluid (CSF). Following pre-fractionation of trypsinized proteins by strong cation exchange (SCX) chromatography, pS-MIP enrichment led to the identification of 924 phosphopeptides in the HEK 293T whole-cell lysate, exceeding the number identified by TiO2-based enrichment (230). Moreover, the phosphopeptides were extracted with low sequence bias and showed no evidence for the characteristic preference of TiO2 for acidic amino acids (aspartic and glutamic acid). Applying the method to human CSF led to the discovery of 47 phosphopeptides belonging to 24 proteins and revealed three previously unknown phosphorylation sites.

Amyloid-ß as a biomarker for Alzheimer's disease: quantification methods in body fluids.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, characterized by neuronal impairment leading to dramatic changes in brain. Amyloid-ß peptides and tau protein are the most promising biomarkers for AD. Cerebrospinal fluid and plasma are used to determine the concentration of these species. Since the pathological processes of AD start decades before the first symptoms, biomarkers may provide the possibility of early disease detection. The application of rapidly emerging technology, such as mass spectrometry, has opened new avenues to accelerate biomarker discovery, both for diagnostic as well as for prognostic purposes. This review summarizes AD biomarker studies with focus on amyloid-ß peptides in biological fluids and their quantification with immunoassays as well as the latest mass spectrometry-based methods.

Identification of a novel human LAP1 isoform that is regulated by protein phosphorylation.

Lamina associated polypeptide 1 (LAP1) is an integral protein of the inner nuclear membrane that is ubiquitously expressed. LAP1 binds to lamins and chromatin, probably contributing to the maintenance of the nuclear envelope architecture. Moreover, LAP1 also interacts with torsinA and emerin, proteins involved in DYT1 dystonia and X-linked Emery-Dreifuss muscular dystrophy disorder, respectively. Given its relevance to human pathological conditions, it is important to better understand the functional diversity of LAP1 proteins. In rat, the LAP1 gene (TOR1AIP1) undergoes alternative splicing to originate three LAP1 isoforms (LAP1A, B and C). However, it remains unclear if the same occurs with the human TOR1AIP1 gene, since only the LAP1B isoform had thus far been identified in human cells. In silico analysis suggested that, across different species, potential new LAP1 isoforms could be generated by alternative splicing. Using shRNA to induce LAP1 knockdown and HPLC-mass spectrometry analysis the presence of two isoforms in human cells was described and validated: LAP1B and LAP1C; the latter is putatively N-terminal truncated. LAP1B and LAP1C expression profiles appear to be dependent on the specific tissues analyzed and in cultured cells LAP1C was the major isoform detected. Moreover, LAP1B and LAP1C expression increased during neuronal maturation, suggesting that LAP1 is relevant in this process. Both isoforms were found to be post-translationally modified by phosphorylation and methionine oxidation and two LAP1B/LAP1C residues were shown to be dephosphorylated by PP1. This study permitted the identification of the novel human LAP1C isoform and partially unraveled the molecular basis of LAP1 regulation.

Internal ribosomal entry site (IRES) activity generates endogenous carboxyl-terminal domains of Cx43 and is responsive to hypoxic conditions.

Connexin43 (Cx43) is the most abundant gap junction protein in higher vertebrate organisms and has been shown to be involved in junctional and non-junctional functions. In addition to the expression of full-length Cx43, endogenously produced carboxyl-terminal segments of Cx43 have been described and have been suggested to be involved in manifold biological functions, such as hypoxic preconditioning and neuronal migration. Molecular aspects, however, behind the separate generation of carboxyl-terminal segments of Cx43 have remained elusive. Here we report on a mechanism that may play a key role in the separate production of these domains. First, stringent evidence derived from siRNA treatment and specific knockouts revealed significant loss of the low molecular weight fragments of Cx43. By applying a dicistronic vector strategy on transfected cell lines, we were able to identify putative IRES activity (nucleotides 442­637) in the coding region of Cx43, which resides upstream from the nucleotide sequence encoding the carboxyl terminus (nucleotides 637­1149). Functional responsiveness of the endogenous expression of Cx43 fragments to hypoxic/ischemic treatment was evaluated in in vitro and in vivo models, which led to a significant increase of the fastest migrating form (20 kDa) under conditions of metabolic deprivation. By nano-MS spectrometry, we achieved stringent evidence of the identity of the 20-kDa segment as part of the carboxyl-terminal domain of full-length Cx43. Our data prove the existence of endogenously expressed carboxyl-terminal domains, which may serve as valuable tools for further translational application in ischemic disorders.