Peptidome analysis of cerebrospinal fluid by LC-MALDI MS

Profiling Human Cerebrospinal Fluid (CSF) Endogenous Peptidome in Alzheimer's Disease

Human cerebrospinal fluid (CSF) is a rich source for central nervous system (CNS)-related disease biomarker discovery due to its direct interchange with the extracellular fluid of the CNS. Though extensive proteome-level profiling has been conducted for CSF, studies targeting at its endogenous peptidome is still limited. It is more difficult to include the post-translational modifications (PTMs) characterization of the peptidome in the mass spectrometry (MS) analysis because of their low abundance and the challenge of data interpretation. In this chapter, we present a peptidomic workflow that combines molecular weight cut-off (MWCO) separation, electron-transfer and higher-energy collision dissociation (EThcD) fragmentation, and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides including both N-glycosylation and O-glycosylation and other common peptide PTMs. The method has been successfully adopted to analyze CSF samples from healthy donors, mild cognitive impairment (MCI), and Alzheimer's disease (AD) patients to provide a landscape of peptidome in different disease states.

Identification of Central Nervous System Oncologic Disease Biomarkers in EVs from Cerebrospinal Fluid (CSF) of Pediatric Patients: A Pilot Neuro-Proteomic Study

Cerebrospinal fluid (CSF) is a biochemical-clinical window into the brain. Unfortunately, its wide dynamic range, low protein concentration, and small sample quantity significantly limit the possibility of using it routinely. Extraventricular drainage (EVD) of CSF allows us to solve quantitative problems and to study the biological role of extracellular vesicles (EVs). In this study, we implemented bioinformatic analysis of our previous data of EVD of CSF and its EVs obtained from congenital hydrocephalus with the aim of identifying a comprehensive list of potential tumor and non-tumor biomarkers of central nervous system diseases. Among all proteins identified, those enriched in EVs are associated with synapses, synaptosomes, and nervous system diseases including gliomas, embryonal tumors, and epilepsy. Among these EV-enriched proteins, given the broad consensus present in the recent scientific literature, we validated syntaxin-binding protein 1 (STXBP1) as a marker of malignancy in EVD of CSF and its EVs from patients with pilocytic astrocytoma and medulloblastoma. Our results show that STXBP1 is negatively enriched in EVs compared to non-tumor diseases and its downregulation correlates with adverse outcomes. Further experiments are needed to validate this and other EV markers in the blood of pediatric patients for translational medicine applications.

In-Depth Site-Specific O-Glycosylation Analysis of Glycoproteins and Endogenous Peptides in Cerebrospinal Fluid (CSF) from Healthy Individuals, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD) Patients

Site-specific O-glycoproteome mapping in complex biological systems provides a molecular basis for understanding the structure-function relationships of glycoproteins and their roles in physiological and pathological processes. Previous O-glycoproteome analysis in cerebrospinal fluid (CSF) focused on sialylated glycoforms, while missing information on other glycosylation types. In order to achieve an unbiased O-glycosylation profile, we developed an integrated strategy combining universal boronic acid enrichment, high-pH fractionation, and electron-transfer and higher-energy collision dissociation (EThcD) for enhanced intact O-glycopeptide analysis. We applied this strategy to analyze the O-glycoproteome in CSF, resulting in the identification of 308 O-glycopeptides from 110 O-glycoproteins, covering both sialylated and nonsialylated glycoforms. To our knowledge, this is the largest data set of O-glycoproteins and O-glycosites reported for CSF to date. We also developed a peptidomics workflow that utilized the EThcD and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides, including N-glycosylation, O-glycosylation, and other common peptide PTMs. Interestingly, among the 1411 endogenous peptides identified, 89 were O-glycosylated, and only one N-glycosylated peptide was found, indicating that CSF endogenous peptides were predominantly O-glycosylated. Analyses of the O-glycoproteome and endogenous peptidome PTMs were also conducted in the CSF of MCI and AD patients to provide a landscape of glycosylation patterns in different disease states. Our results showed a decreasing trend in fucosylation and an increasing trend of endogenous peptide O-glycosylation, which may play an important role in AD progression.

Weighted Gene Co-Expression Network Analysis and Support Vector Machine Learning in the Proteomic Profiling of Cerebrospinal Fluid from Extraventricular Drainage in Child Medulloblastoma

Medulloblastoma (MB) is the most common pediatric malignant central nervous system tumor. Overall survival in MB depends on treatment tuning. There is aneed for biomarkers of residual disease and recurrence. We analyzed the proteome of waste cerebrospinal fluid (CSF) from extraventricular drainage (EVD) from six children bearing various subtypes of MB and six controls needing EVD insertion for unrelated causes. Samples included total CSF, microvesicles, exosomes, and proteins captured by combinatorial peptide ligand library (CPLL). Liquid chromatography-coupled tandem mass spectrometry proteomics identified 3560 proteins in CSF from control and MB patients, 2412 (67.7%) of which were overlapping, and 346 (9.7%) and 805 (22.6%) were exclusive. Multidimensional scaling analysis discriminated samples. The weighted gene co-expression network analysis (WGCNA) identified those modules functionally associated with the samples. A ranked core of 192 proteins allowed distinguishing between control and MB samples. Machine learning highlighted long-chain fatty acid transport protein 4 (SLC27A4) and laminin B-type (LMNB1) as proteins that maximized the discrimination between control and MB samples. Machine learning WGCNA and support vector machine learning were able to distinguish between MB versus non-tumor/hemorrhagic controls. The two potential protein biomarkers for the discrimination between control and MB may guide therapy and predict recurrences, improving the MB patients' quality of life.

Peptidomic Approaches and Observations in Neurodegenerative Diseases

Mass spectrometry (MS), with its immense technological developments over the last two decades, has emerged as an unavoidable technique in analyzing biomolecules such as proteins and peptides. Its multiplexing capability and explorative approach make it a valuable tool for analyzing complex clinical samples concerning biomarker research and investigating pathophysiological mechanisms. Peptides regulate various biological processes, and several of them play a critical role in many disease-related pathological conditions. One important example in neurodegenerative diseases is the accumulation of amyloid-beta peptides (Aβ) in the brain of Alzheimer’s disease (AD) patients. When investigating brain function and brain-related pathologies, such as neurodegenerative diseases, cerebrospinal fluid (CSF) represents the most suitable sample because of its direct contact with the brain. In this review, we evaluate publications applying peptidomics analysis to CSF samples, focusing on neurodegenerative diseases. We describe the methodology of peptidomics analysis and give an overview of the achievements of CSF peptidomics over the years. Finally, publications reporting peptides regulated in AD are discussed.

Extraction, Isolation and Identification of Low Molecular Weight Peptides in Human Milk

Human milk contains numerous free low molecular weight peptides (LMWPs), which may play an important role in infant health and growth. The bioactivities of LMWPs are determined by their structures, especially the amino acid sequences. In the present study, 81 human milk samples were collected and purified by cation-exchange solid-phase extraction (SPE). Ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used for the separation and detection of free LMWPs in human milk. A total of 56 LMWPs were identified and quantified. These LMWPs were mainly derived from 3 regions of β-casein, which were the amino acid fragments of 16–40, 85–110, and 205–226. The predominant LMWPs were RETIESLSSSEESITEYK, RETIESLSSSEESITEYKQKVEKVK, ETIESLSSSEESITEYK, TQPLAPVHNPIS, and QPLAPVHNPISV with molecular weights of 2247.9573, 2860.2437, 2091.8591, 1372.7666, and 1271.7212, respectively. The results indicated that the technique based on SPE and UPLC-QTOF-MS might greatly facilitate the analysis of LMWPs in human milk.

Peptidomics and Capillary Electrophoresis

Peptides play a crucial role in many vitally important functions of living organisms. The goal of peptidomics is the identification of the "peptidome," the whole peptide content of a cell, organ, tissue, body fluid, or organism. In peptidomic or proteomic studies, capillary electrophoresis (CE) is an alternative technique for liquid chromatography. It is a highly efficient and fast separation method requiring extremely low amounts of sample. In peptidomic approaches, CE is commonly combined with mass spectrometric (MS) detection. Most often, CE is coupled with electrospray ionization MS and less frequently with matrix-assisted laser desorption/ionization MS. CE-MS has been employed in numerous studies dealing with determination of peptide biomarkers in different body fluids for various diseases, or in food peptidomic research for the analysis and identification of peptides with special biological activities. In addition to the above topics, sample preparation techniques commonly applied in peptidomics before CE separation and possibilities for peptide identification and quantification by CE-MS or CE-MS/MS methods are discussed in this chapter.

A CD10-OGP Membrane Peptolytic Signaling Axis in Fibroblasts Regulates Lipid Metabolism of Cancer Stem Cells via SCD1

Carcinoma-associated fibroblasts (CAFs) consist of heterogeneous subpopulations that play a critical role in the dynamics of the tumor microenvironment. The extracellular signals of CAFs have been attributed to the extracellular matrix, cytokines, cell surface checkpoints, and exosomes. In the present study, it is demonstrated that the CD10 transmembrane hydrolase expressed on a subset of CAFs supports tumor stemness and induces chemoresistance. Mechanistically, CD10 degenerates an antitumoral peptide termed osteogenic growth peptide (OGP). OGP restrains the expression of rate-limiting desaturase SCD1 and inhibits lipid desaturation, which is required for cancer stem cells (CSCs). Targeting CD10 significantly improves the efficacy of chemotherapy in vivo. Clinically, CD10-OGP signals are associated with the response to neoadjuvant chemotherapy in patients with breast cancer. The collective data suggest that a nexus between the niche and lipid metabolism in CSCs is a promising therapeutic target for breast cancer.

Method development and characterisation of the low-molecular-weight peptidome of human wound fluids

The normal wound healing process is characterised by proteolytic events, whereas infection results in dysfunctional activations by endogenous and bacterial proteases. Peptides, downstream reporters of these proteolytic actions, could therefore serve as a promising tool for diagnosis of wounds. Using mass-spectrometry analyses, we here for the first time characterise the peptidome of human wound fluids. Sterile post-surgical wound fluids were found to contain a high degree of peptides in comparison to human plasma. Analyses of the peptidome from uninfected healing wounds and Staphylococcus aureus -infected wounds identify unique peptide patterns of various proteins, including coagulation and complement factors, proteases, and antiproteinases. Together, the work defines a workflow for analysis of peptides derived from wound fluids and demonstrates a proof-of-concept that such fluids can be used for analysis of qualitative differences of peptide patterns from larger patient cohorts, providing potential biomarkers for wound healing and infection.

Exploring the Potential of Neuroproteomics in Alzheimer's Disease

Alzheimer's disease (AD) is progressive brain amyloidosis that damages brain regions associated with memory, thinking, behavioral and social skills. Neuropathologically, AD is characterized by intraneuronal hyperphosphorylated tau inclusions as neurofibrillary tangles (NFTs), and buildup of extracellular amyloid-beta (Aβ) peptide as senile plaques. Several biomarker tests capturing these pathologies have been developed. However, for the full clinical expression of the neurodegenerative events of AD, there exist other central molecular pathways. In terms of understanding the unidentified underlying processes for the progression and development of AD, a complete comprehension of the structure and composition of atypical aggregation of proteins is essential. Presently, to aid the prognosis, diagnosis, detection, and development of drug targets in AD, neuroproteomics is elected as one of the leading essential tools for the efficient exploratory discovery of prospective biomarker candidates estimated to play a crucial role. Therefore, the aim of this review is to present the role of neuroproteomics to analyze the complexity of AD.

Peptidomic profiling of cerebrospinal fluid from patients with intracranial saccular aneurysms

Intracranial saccular aneurysms (ISA) represent 90%-95% of all intracranial aneurysm cases, characterizing abnormal pockets at arterial branch points. Ruptures lead to subarachnoid hemorrhages (SAH) and poor prognoses. We applied mass spectrometry-based peptidomics to investigate the peptidome of twelve cerebrospinal fluid (CSF) samples collected from eleven patients diagnosed with ISA. For peptide profile analyses, participants were classified into: 1) ruptured intracranial saccular aneurysms (RIA), 2) unruptured intracranial saccular aneurysms (UIA), and late-ruptured intracranial saccular aneurysms (LRIA). Altogether, a total of 2199 peptides were detected by both Mascot and Peaks software, from which 484 (22.0%) were unique peptides. All unique peptides presented conserved chains, domains, regions of protein modulation and/or post-translational modification sites related to human diseases. Gene Ontology (GO) analyses of peptide precursor proteins showed that 42% are involved in binding, 56% in cellular anatomical entities, and 39% in intercellular signaling molecules. Unique peptides identified in patients diagnosed with RIA have a larger molecular weight and a distinctive developmental process compared to UIA and LRIA (P ≤ 0.05). Continued investigations will allow the characterization of the biological and clinical significance of the peptides identified in the present study, as well as identify prototypes for peptide-based pharmacological therapies to treat ISA. SIGNIFICANCE.

Potential biomarkers of childhood brain tumor identified by proteomics of cerebrospinal fluid from extraventricular drainage (EVD)

Brain tumors are the most common solid tumors in childhood. There is the need for biomarkers of residual disease, therapy response and recurrence. Cerebrospinal fluid (CSF) is a source of brain tumor biomarkers. We analyzed the proteome of waste CSF from extraventricular drainage (EVD) from 29 children bearing different brain tumors and 17 controls needing EVD insertion for unrelated causes. 1598 and 1526 proteins were identified by liquid chromatography-coupled tandem mass spectrometry proteomics in CSF control and brain tumor patients, respectively, 263 and 191 proteins being exclusive of either condition. Bioinformatic analysis revealed promising protein biomarkers for the discrimination between control and tumor (TATA-binding protein-associated factor 15 and S100 protein B). Moreover, Thymosin beta-4 (TMSB4X) and CD109, and 14.3.3 and HSP90 alpha could discriminate among other brain tumors and low-grade gliomas plus glyoneuronal tumors/pilocytic astrocytoma, or embryonal tumors/medulloblastoma. Biomarkers were validated by ELISA assay. Our method was able to distinguish among brain tumor vs non-tumor/hemorrhagic conditions (controls) and to differentiate two large classes of brain tumors. Further prospective studies may assess whether the biomarkers proposed by our discovery approach can be identified in other bodily fluids, therefore less invasively, and are useful to guide therapy and predict recurrences.

Peptidome analysis of cerebrospinal fluid in neonates with hypoxic-ischemic brain damage

Hypoxic-ischemic brain injury (HIBD) causes neonatal death and serious neurological disability; however, there are currently no promising therapies for it excepting cooling. Therefore, in this study, we used peptidome analysis to identify differentially expressed peptides in cerebrospinal fluid (CSF) of neonates with HIBD or controls, which may give a foundation for finding new promising drugs of neonatal HIBD. CSF samples were collected from neonates with HIBD (n = 4) or controls (n = 4). ITRAQ LC-MS/MS was used to identify differentially expressed peptides between two groups. A total of 35 differentially expressed peptides from 25 precursor proteins were identified. The 2671.5 Da peptide (HSQFIGYPITLFVEKER), one of the down-regulated peptides in neonatal HIBD, is a fragment of heat shock protein 90-alpha (HSP90α/HSP90AA1). Results of bioinformatics analysis showed that HSP90α/HSP90AA1 was located in the protein-protein interaction (PPI) network hub and was involved in the NOD-LIKE receptor (NLR) signaling pathway. This peptide, we named it Hypoxic-Ischemic Brain Damage Associated Peptide (HIBDAP), is a hydrophilic peptide with high stability and has a long half-life of 3.5 h in mammalian reticulocytes. It was demonstrated that TAT-HIBDAP could successfully enter PC12 cells and further into the nucleus. After HIBDAP pretreatment and 6 h of OGD treatment, low concentrations of HIBDAP increased the survival rate of cells, except 40 μM had a toxic effect. Safe concentrations of HIBDAP reduced pyroptosis of PC12 cells under OGD, except 20 μM had no effect, by suppressing expressions of NLRP3, ASC and Caspase-1 except NLRP1. The results of our study identified the characterization and expression profiles of peptides in CSF of neonatal HIBD. Several meaningful peptides such as HIBDAP may play significant roles in neonatal HIBD and provide new therapeutic targets for neonatal HIBD.

Collagen analysis with mass spectrometry

Mass spectrometry-based techniques can be applied to investigate collagen with respect to identification, quantification, supramolecular organization, and various post-translational modifications. The continuous interest in collagen research has led to a shift from techniques to analyze the physical characteristics of collagen to methods to study collagen abundance and modifications. In this review, we illustrate the potential of mass spectrometry for in-depth analyses of collagen.

Peptidomics Approaches for the Identification of Bioactive Molecules from Diaphorina citri

Huanglongbing (HLB), a deadly citrus disease, is primarily associated with Candidatus Liberibacter asiaticus (CLas) and spread by the hemipteran insect Diaphorina citri. Control strategies to combat HLB are urgently needed. In this work, we developed and compared workflows for the extraction of the D. citri peptidome, a dynamic set of polypeptides produced by proteolysis and other cellular processes. High-resolution mass spectrometry revealed bias among methods reflecting the physiochemical properties of the peptides: while TCA/acetone-based methods resulted in enrichment of C-terminally amidated peptides, a modification characteristic of bioactive peptides, larger peptides were overrepresented in the aqueous phase of chloroform/methanol extracts, possibly indicative of reduced co-analytical degradation during sample preparation. Parallel reaction monitoring (PRM) was used to validate the structure and upregulation of peptides derived from hemocyanin, a D. citri immune system protein, in insects reared on healthy and CLas-infected trees. Mining of the data sets also revealed 122 candidate neuropeptides, including PK/PBAN family neuropeptides and kinins, biostable analogs of which have known insecticidal properties. Taken together, this information yields new, in-depth insights into peptidomics methodology. Additionally, the putative neuropeptides identified may lead to psyllid mortality if applied to or expressed in citrus, consequently blocking the spread of HLB disease in citrus groves.

Changes in Synaptic Proteins Precede Neurodegeneration Markers in Preclinical Alzheimer's Disease Cerebrospinal Fluid

A biomarker of synapse loss, an early event in Alzheimer's disease (AD) pathophysiology that precedes neuronal death and symptom onset, would be a much-needed prognostic biomarker. With direct access to the brain interstitial fluid, the cerebrospinal fluid (CSF) is a potential source of synapse-derived proteins. In this study, we aimed to identify and validate novel CSF biomarkers of synapse loss in AD. Discovery: Combining shotgun proteomics of the CSF with an exhaustive search of the literature and public databases, we identified 251 synaptic proteins, from which we selected 22 for further study. Verification: Twelve proteins were discarded because of poor detection by Selected Reaction Monitoring (SRM). We confirmed the specific expression of 9 of the remaining proteins (Calsynytenin-1, GluR2, GluR4, Neurexin-2A, Neurexin-3A, Neuroligin-2, Syntaxin-1B, Thy-1, Vamp-2) at the human synapse using Array Tomography microscopy and biochemical fractionation methods. Exploration: Using SRM, we monitored these 9 synaptic proteins (20 peptides) in a cohort of CSF from cognitively normal controls and subjects in the pre-clinical and clinical AD stages (n = 80). Compared with controls, peptides from 8 proteins were elevated 1.3 to 1.6-fold (p < 0.04) in prodromal AD patients. Validation: Elevated levels of a GluR4 peptide at the prodromal stage were replicated (1.3-fold, p = 0.04) in an independent cohort (n = 60). Moreover, 7 proteins were reduced at preclinical stage 1 (0.6 to 0.8-fold, p < 0.04), a finding that was replicated (0.7 to 0.8-fold, p < 0.05) for 6 proteins in a third cohort (n = 38). In a cross-cohort meta-analysis, 6 synaptic proteins (Calsyntenin-1, GluR4, Neurexin-2A, Neurexin-3A, Syntaxin-1B and Thy-1) were reduced 0.8-fold (p < 0.05) in preclinical AD, changes that precede clinical symptoms and CSF markers of neurodegeneration. Therefore, these proteins could have clinical value for assessing disease progression, especially in preclinical stages of AD.

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.

Levels of ADAM10 are reduced in Alzheimer's disease CSF

Background

The disintegrin metalloproteinase 10 (ADAM10) is the main α-secretase acting in the non-amyloidogenic processing of the amyloid precursor protein. This study assesses whether ADAM10 is present in cerebrospinal fluid (CSF), and whether it has potential as a biomarker for Alzheimer’s disease (AD).

Methods

ADAM10 was characterized in human CSF samples by immunoprecipitation and western blotting using antibodies specific for different domains of the protein and by ultracentrifugation in sucrose density gradients. Samples from AD patients (n = 20) and age-matched non-AD controls (n = 20) were characterized for classical CSF biomarkers, Aβ42, T-tau, or P-tau by ELISA, and assayed for soluble ADAM10 levels by western blotting.

Results

We found that ADAM10 is present in human CSF as several distinct species: an immature form retaining the prodomain (proADAM10; ~ 80 kDa), a mature unprocessed full-length form (ADAM10f; ~ 55 kDa), and a truncated large soluble form released from the membrane (sADAM10; ~ 50 kDa). Fractionation by ultracentrifugation on sucrose density gradients showed that the ADAM10f and sADAM10 species form large complexes. Immunoblotting revealed a significant decrease in ADAM10f and sADAM10 in AD CSF compared to control CSF, while proADAM10 levels remained unaltered.

Conclusions

Several forms of ADAM10 are present in CSF, mainly assembled as high-molecular weight complexes. The determination of the levels of mature forms of CSF-ADAM10 may be useful as a biomarker for AD.

Electronic supplementary material

The online version of this article (10.1186/s12974-018-1255-9) contains supplementary material, which is available to authorized users.

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

Peptidome analysis of human milk from women delivering macrosomic fetuses reveals multiple means of protection for infants

Breastfeeding is associated with a lower incidence of obesity, diabetes, and cardiovascular disease later in life. While macrosomic infants have a higher risk of developing obesity and other metabolic disorders. Breast milk may contain special nutrients to meet the different growth needs of different infants. Whether mothers make breast milk different to meet the requirement of macrosomic infants is still unknown. Here, we conducted a comparison between mothers delivering macrosomic and non-macrosomic infants in colostrum endogenous peptides. More than 400 peptides, originating from at least 34 protein precursors, were identified by Liquid Chromatography/Mass Spectrometry (LC/MS). Out of these, 29 peptides found to be significant differently expressed (|fold change| ≥ 3, P < 0.01). Blastp analysis revealed 41 peptides may have established biological activities, which exhibit immunomodulating, antibacterial action, antioxidation, opioid agonist and antihypertensive activity. Furthermore, we found that peptide located at β-Casein 24-38 AA has antimicrobial effect against E. coli, Y. enterocolitica and S. aureus. While, κ-Casein 89-109 AA-derived peptide plays as a regulator of preadipocyte proliferation. The profile of endogenous peptides from macrosomic term infants is different from non-macrosomic terms. This different peptide expression potentially has specific physiological function to benefit macrosomic infants. Finally, we believe that our research is a meaningfull finding which may add to the understanding of milk peptide physiological action.

Evolving Relevance of Neuroproteomics in Alzheimer's Disease

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

EndoProteoFASP as a Tool to Unveil the Peptidome-Protease Profile: Application to Salivary Diagnostics

In the quest to fully comprehend the proteolytic events leading to the generation of the salivary peptidome, we have developed a method for the sequential elution of salivary peptides throughout progressive endogenous proteolysis. By screening the time-dependent changes in the salivary peptidome we can predict the activity pattern of salivary proteases responsible for such peptide fingerprint and identify susceptible protein targets. Herein, we describe a step-by-step tutorial based on a filter-aided sample preparation (FASP) method, taking advantage of the endogenous salivary proteases armamentarium (endoProteoFASP), to produce new peptides from the salivary proteins, adding to those present in the sample at the time of collection. In this protocol, the different sets of peptides retrieved after sample elution are identified following a liquid chromatography-tandem mass spectrometry approach. The likelihood of a large set of endogenous proteases (collected from several public sources) to be responsible for the generation of such peptides can be predicted by the analysis of the cleavage site specificity by Proteasix ( http://proteasix.cs.man.ac.uk /) algorithm. The attained peptidome-protease profile can be useful to elucidate the peptidome dynamics and the proteolytic events underpinning pathophysiological phenomena taking place locally within the oral cavity. This may help clinicians to diagnose oral pathologies and develop preventive therapeutic plans.

Origins, Technological Development, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources mainly by HPLC and mass spectrometry. Mass spectrometry allows the detection of a multitude of single peptides in complex mixtures. The term first appeared in full papers in the year 2001, after over 100 years of peptide research with a main focus on one or a few specific peptides. Within the last 15 years, this new field has grown to over 1200 publications. Mass spectrometry techniques, in combination with other analytical methods, were developed for the fast and comprehensive analysis of peptides in proteomics and specifically adjusted to implement peptidomics technologies. Although peptidomics is closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. The development of peptidomics is described, including the most important implementations for its technological basis. Different strategies are covered which are applied to several important applications, such as neuropeptidomics and discovery of bioactive peptides or biomarkers. This overview includes links to all other chapters in the book as well as recent developments of separation, mass spectrometric, and data processing technologies. Additionally, some new applications in food and plant peptidomics as well as immunopeptidomics are introduced.

Sample Preparation for Endopeptidomic Analysis in Human Cerebrospinal Fluid

This protocol describes a method developed to identify endogenous peptides in human cerebrospinal fluid (CSF). For this purpose, a previously developed method based on molecular weight cut-off (MWCO) filtration and mass spectrometric analysis was combined with an offline high-pH reverse phase HPLC pre-fractionation step. Secretion into CSF is the main pathway for removal of molecules shed by cells of the central nervous system. Thus, many processes in the central nervous system are reflected in the CSF, rendering it a valuable diagnostic fluid. CSF has a complex composition, containing proteins that span a concentration range of 8 - 9 orders of magnitude. Besides proteins, previous studies have also demonstrated the presence of a large number of endogenous peptides. While less extensively studied than proteins, these may also hold potential interest as biomarkers. Endogenous peptides were separated from the CSF protein content through MWCO filtration. By removing a majority of the protein content from the sample, it is possible to increase the sample volume studied and thereby also the total amount of the endogenous peptides. The complexity of the filtrated peptide mixture was addressed by including a reverse phase (RP) HPLC pre-fractionation step at alkaline pH prior to LC-MS analysis. The fractionation was combined with a simple concatenation scheme where 60 fractions were pooled into 12, analysis time consumption could thereby be reduced while still largely avoiding co-elution. Automated peptide identification was performed by using three different peptide/protein identification software programs and subsequently combining the results. The different programs were complementary rather than comparable with less than 15% of the identifications overlapped between the three.

Exploiting the human peptidome for novel antimicrobial and anticancer agents

Infectious diseases and cancers are leading causes of death and pose major challenges to public health. The human peptidome encompasses millions of compounds that display an enormous structural and functional diversity and represents an excellent source for the discovery of endogenous agents with antimicrobial and/or anticancer activity. Here, we discuss how to exploit the human peptidome for novel antimicrobial and anticancer agents through the generation of peptide libraries from human body fluids and tissues and stepwise purification of bioactive compounds.

Expanding the cerebrospinal fluid endopeptidome

Biomarkers of neurodegenerative disorders are needed to assist in diagnosis, to monitor disease progression and therapeutic interventions, and to provide insight into disease mechanisms. One route to identify such biomarkers is by proteomic and peptidomic analysis of cerebrospinal fluid (CSF). In the current study, we performed an in-depth analysis of the human CSF endopeptidome to establish an inventory that may serve as a basis for future targeted biomarker studies. High-pH RP HPLC was employed for off-line sample prefractionation followed by low-pH nano-LC-MS analysis. Different software programs and scoring algorithms for peptide identification were employed and compared. A total of 18 031 endogenous peptides were identified at a FDR of 1%, increasing the number of known endogenous CSF peptides 10-fold compared to previous studies. The peptides were derived from 2 053 proteins of which more than 60 have been linked to neurodegeneration. Notably, among the findings were six peptides derived from microtubule-associated protein tau, three of which span the diagnostically interesting threonine-181 (Tau-F isoform). Also, 213 peptides from amyloid precursor protein were identified, 58 of which were partially or completely within the sequence of amyloid β 1-40/42, as well as 109 peptides from apolipoprotein E, spanning sequences that discriminate between the E2/E3/E4 isoforms of the protein.

Ultrasensitive Measurement of Ca2+ Influx into Lipid Vesicles Induced by Protein Aggregates

To quantify and characterize the potentially toxic protein aggregates associated with neurodegenerative diseases, a high‐throughput assay based on measuring the extent of aggregate‐induced Ca²⁺ entry into individual lipid vesicles has been developed. This approach was implemented by tethering vesicles containing a Ca²⁺ sensitive fluorescent dye to a passivated surface and measuring changes in the fluorescence as a result of membrane disruption using total internal reflection microscopy. Picomolar concentrations of Aβ42 oligomers could be observed to induce Ca²⁺ influx, which could be inhibited by the addition of a naturally occurring chaperone and a nanobody designed to bind to the Aβ peptide. We show that the assay can be used to study aggregates from other proteins, such as α‐synuclein, and to probe the effects of complex biofluids, such as cerebrospinal fluid, and thus has wide applicability.

Sample-dependent diagnostic accuracy of prostaglandin D synthase in cerebrospinal fluid leak

BACKGROUND

Prostaglandin D2 synthase, commonly known as β-trace protein (βTP), is an excellent biomarker for the assessment of cerebrospinal fluid (CSF) leaks. Despite being widely used, the limits for the diagnostic values of βTP are not well established to date, and currently suggested cut-off values in literature range from 0.25 to 6.0mg/L. Sample-specific and more accurate thresholds are a current need.

METHODS

A retrospective observational study, performed in a tertiary-care hospital, between January 2006 and January 2014. A total of 74 patients were included, with a definitive diagnosis after initial leak suspicion and at least one determination of βTP using a nephelometry-based assay. A total of 46 CSF samples were included in the control group. Samples were obtained from nasal secretions, ear secretions or spinal surgical injury, directly using sterile Eppendorf tubes. The analysis of 3 different cut-off values was performed and the receiver operating curve (ROC) analyses were calculated.

RESULTS

Initial diagnostic suspicion was confirmed in 51% of cases, most of which were of postoperative origin (51%) and traumatic (26%). The βTP median concentration in different samples was significantly higher in the presence of cerebrospinal fluid fistula, regardless of sample type (22.0mg/L vs. 0.24mg/L, 95% confidence interval: 19.0-30.8 vs. 0.08-0.40; p<0.001). Data from contingency tables show 100% sensitivity and specificity, depending on sample type and the cut-off value used: for rhinorrhea and otorrhea samples, the most appropriate it was 0.7mg/L, while values >2.0mg/L could be used for spine postoperative fluid leakage samples.

CONCLUSIONS

The cut off value for βTP in the diagnosis and follow-up of cerebrospinal fluid leaks should be modified depending on the type of secretion (sample type), for a better diagnostic accuracy.

Proteomics and peptidomics: moving toward precision medicine in urological malignancies

Urological malignancies are a major cause of morbidity and mortality worldwide. Advances in early detection, diagnosis, prognosis and prediction of treatment response can significantly improve patient care. Proteomic and peptidomic profiling studies are at the center of kidney, prostate and bladder cancer biomarker discovery and have shown great promise for improved clinical assessment. Mass spectrometry (MS) is the most widely employed method for proteomic and peptidomic analyses. A number of MS platforms have been developed to facilitate accurate identification of clinically relevant markers in various complex biological samples including tissue, urine and blood. Furthermore, protein profiling studies have been instrumental in the successful introduction of several diagnostic multimarker tests into the clinic. In this review, we will provide a brief overview of high-throughput technologies for protein and peptide based biomarker discovery. We will also examine the current state of kidney, prostate and bladder cancer biomarker research as well as review the journey toward successful clinical implementation.

The Pathogenesis of the Demyelinating Form of Guillain-Barre Syndrome (GBS): Proteo-peptidomic and Immunological Profiling of Physiological Fluids

Acute inflammatory demyelinating polyneuropathy (AIDP) - the main form of Guillain-Barre syndrome-is a rare and severe disorder of the peripheral nervous system with an unknown etiology. One of the hallmarks of the AIDP pathogenesis is a significantly elevated cerebrospinal fluid (CSF) protein level. In this paper CSF peptidome and proteome in AIDP were analyzed and compared with multiple sclerosis and control patients. A total protein concentration increase was shown to be because of even changes in all proteins rather than some specific response, supporting the hypothesis of protein leakage from blood through the blood-nerve barrier. The elevated CSF protein level in AIDP was complemented by activization of protein degradation and much higher peptidome diversity. Because of the studies of the acute motor axonal form, Guillain-Barre syndrome as a whole is thought to be associated with autoimmune response against neurospecific molecules. Thus, in AIDP, autoantibodies against cell adhesion proteins localized at Ranvier's nodes were suggested as possible targets in AIDP. Indeed, AIDP CSF peptidome analysis revealed cell adhesion proteins degradation, however no reliable dependence on the corresponding autoantibodies levels was found. Proteome analysis revealed overrepresentation of Gene Ontology groups related to responses to bacteria and virus infections, which were earlier suggested as possible AIDP triggers. Immunoglobulin blood serum analysis against most common neuronal viruses did not reveal any specific pathogen; however, AIDP patients were more immunopositive in average and often had polyinfections. Cytokine analysis of both AIDP CSF and blood did not show a systemic adaptive immune response or general inflammation, whereas innate immunity cytokines were up-regulated. To supplement the widely-accepted though still unproven autoimmunity-based AIDP mechanism we propose a hypothesis of the primary peripheral nervous system damaging initiated as an innate immunity-associated local inflammation following neurotropic viruses egress, whereas the autoantibody production might be an optional complementary secondary process.

A single dose of the γ-secretase inhibitor semagacestat alters the cerebrospinal fluid peptidome in humans

BACKGROUND

In Alzheimer's disease, beta-amyloid peptides in the brain aggregate into toxic oligomers and plaques, a process which is associated with neuronal degeneration, memory loss, and cognitive decline. One therapeutic strategy is to decrease the production of potentially toxic beta-amyloid species by the use of inhibitors or modulators of the enzymes that produce beta-amyloid from amyloid precursor protein (APP). The failures of several such drug candidates by lack of effect or undesired side-effects underscore the importance to monitor the drug effects in the brain on a molecular level. Here we evaluate if peptidomic analysis in cerebrospinal fluid (CSF) can be used for this purpose.

METHODS

Fifteen human healthy volunteers, divided into three groups, received a single dose of placebo or either 140 mg or 280 mg of the γ-secretase inhibitor semagacestat (LY450139). Endogenous peptides in CSF, sampled prior to administration of the drug and at six subsequent time points, were analyzed by liquid chromatography coupled to mass spectrometry, using isobaric labeling based on the tandem mass tag approach for relative quantification.

RESULTS

Out of 302 reproducibly detected peptides, 11 were affected by the treatment. Among these, one was derived from APP and one from amyloid precursor-like protein 1. Nine peptides were derived from proteins that may not be γ-secretase substrates per se, but that are regulated in a γ-secretase-dependent manner.

CONCLUSIONS

These results indicate that a CSF peptidomic approach may be a valuable tool both to verify target engagement and to identify other pharmacodynamic effects of the drug. Data are available via ProteomeXchange with identifier PXD003075.

TRIAL REGISTRATION

NCT00765115 , registered 30/09/2008.

APLP1 as a cerebrospinal fluid biomarker for γ-secretase modulator treatment

INTRODUCTION

Alzheimer's disease brains are characterized by extracellular plaques containing the aggregated amyloid β42 (Aβ42) peptide and intraneuronal tangles containing hyperphosphorylated tau. Aβ42 is produced by sequential processing of the amyloid precursor protein (APP) by β-secretase followed by γ-secretase. Substantial efforts have been put into developing pharmaceuticals preventing the production or increasing the clearance of Aβ42. However, treatments inhibiting γ-secretase have proven disappointing due to off-target effects. To circumvent these effects, γ-secretase modulators (GSMs) have been developed, which rather than inhibiting γ-secretase shift its preference into producing less aggregation-prone shorter Aβ peptides. Belonging to the same family of proteins as APP, amyloid-like protein 1 (APLP1) is also a substrate for γ-secretase. Herein we investigated whether the GSM E2012 affects APLP1 processing in the central nervous system by measuring APLP1 peptide levels in cerebrospinal fluid (CSF) before and after E2012 treatment in dogs.

METHODS

An in-house monoclonal APLP1 antibody, AP1, was produced and utilized for immunopurification of APLP1 from human and dog CSF in a hybrid immuno-affinity mass spectrometric method. Seven dogs received a single dose of 20 or 80 mg/kg of E2012 in a randomized cross-over design and CSF was collected prior to and 4, 8 and 24 hours after dosing.

RESULTS

We have identified 14 CSF APLP1 peptides in humans and 12 CSF APLP1 peptides in dogs. Of these, seven were reproducibly detectable in dogs who received E2012. We found a dose-dependent relative increase of the CSF peptides APLP1β17, 1β18 and 1β28 accompanied with a decrease of 1β25 and 1β27 in response to E2012 treatment. All peptides reverted to baseline over the time of sample collection.

CONCLUSION

We show an in vivo effect of the GSM E2012 on the processing of APLP1 which is measurable in CSF. These data suggest that APLP1 peptides may be used as biomarkers to monitor drug effects of GSMs on γ-secretase processing in clinical trials. However, this requires further investigation in larger cohorts, including studies in man.

Neuroproteomic profiling of human body fluids

Analysis of protein expression and abundance provides a possibility to extend the current knowledge on disease-associated processes and pathways. The human brain is a complex organ and dysfunction or damage can give rise to a variety of neurological diseases. Although many proteins potentially reflecting disease progress are originating from brain, the scarce availability of human tissue material has lead to utilization of body fluids such as cerebrospinal fluid and blood in disease-related research. Within the most common neurological disorders, much effort has been spent on studying the role of a few hallmark proteins in disease pathogenesis but despite extensive investigation, the signatures they provide seem insufficient to fully understand and predict disease progress. In order to expand the view the field of neuroproteomics has lately emerged alongside developing technologies, such as affinity proteomics and mass spectrometry, for multiplexed and high-throughput protein profiling. Here, we provide an overview of how such technologies have been applied to study neurological disease and we also discuss some important considerations concerning discovery of disease-associated profiles.

Neutral polymers as coatings for high resolution electrophoretic separation of Aβ peptides on glass microchips

This study reports a comparison of the performances of two neutral polymers, poly ethylene-oxide (PEO) and poly(dimethylacrylamide-co-allyl glycidyl ether) (EpDMA), in glass microchips to achieve zone electrophoresis separation of several truncated forms of beta amyloid (Aβ) peptides, sharing very similar structures. The peptides were derivatized by FluoProbes 488 NHS to allow their fluorescence detection. Two protocols based either on PEO or EpDMA led to good pH stabilities in addition to a significant reduction of the electroosmotic flow. These two polymer coatings allowed repeatable analyses and high resolution for the simultaneous analysis of three Aβ peptides, Aβ 1-38, Aβ 1-40 and Aβ 1-42, considered as potential biomarkers of Alzheimer's disease. A recovery study showed that EpDMA was superior in reducing the adsorption of the Aβ peptides on the coated inner wall. Finally, the separation method relying on the EpDMA coated microchips was validated as linear using a calibration curve and the LOD was estimated to be close to 200 nM. Despite very short migration distances, different N-terminal or C-terminal truncated Aβ peptides, corresponding to promising biomarker combinations for the future diagnostic, were fully resolved. The method was successfully applied to detect these peptides in spiked cerebrospinal fluid and has provided a first achievement towards the development of a microsystem that would integrate preconcentration and separation steps.

Peptidomics for the discovery and characterization of neuropeptides and hormones

The discovery of neuropeptides as signaling molecules with paracrine or hormonal regulatory functions has led to trailblazing advances in physiology and fostered the characterization of numerous neuropeptide-binding G protein-coupled receptors (GPCRs) as potential drug targets. The impact on human health has been tremendous: approximately 30% of commercial drugs act via the GPCR pathway. However, about 25% of the GPCRs encoded by the mammalian genome still lack their pharmacological identity. Searching for the orphan GPCR endogenous ligands that are likely to be neuropeptides has proved to be a formidable task. Here we describe the mass spectrometry (MS)-based technologies and experimental strategies that have been successful in achieving high-throughput characterization of endogenous peptides in nervous and endocrine systems.

Current peptidomics: applications, purification, identification, quantification, and functional analysis

Peptidomics is an emerging field branching from proteomics that targets endogenously produced protein fragments. Endogenous peptides are often functional within the body-and can be both beneficial and detrimental. This review covers the use of peptidomics in understanding digestion, and identifying functional peptides and biomarkers. Various techniques for peptide and glycopeptide extraction, both at analytical and preparative scales, and available options for peptide detection with MS are discussed. Current algorithms for peptide sequence determination, and both analytical and computational techniques for quantification are compared. Techniques for statistical analysis, sequence mapping, enzyme prediction, and peptide function, and structure prediction are explored.

Explorative and targeted neuroproteomics in Alzheimer's disease

Alzheimer's disease (AD) is a progressive brain amyloidosis that injures brain regions involved in memory consolidation and other higher brain functions. Neuropathologically, the disease is characterized by accumulation of a 42 amino acid peptide called amyloid β (Aβ42) in extracellular senile plaques, intraneuronal inclusions of hyperphosphorylated tau protein in neurofibrillary tangles, and neuronal and axonal degeneration and loss. Biomarker assays capturing these pathologies have been developed for use on cerebrospinal fluid samples but there are additional molecular pathways that most likely contribute to the neurodegeneration and full clinical expression of AD. One way of learning more about AD pathogenesis is to identify novel biomarkers for these pathways and examine them in longitudinal studies of patients in different stages of the disease. Here, we discuss targeted proteomic approaches to study AD and AD-related pathologies in closer detail and explorative approaches to discover novel pathways that may contribute to the disease. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology.

Spatial neuroproteomics using imaging mass spectrometry

The nervous system constitutes arguably the most complicated and least understood cellular network in the human body. This consequently manifests itself in the fact that the molecular bases of neurodegenerative diseases remain unknown. The limited understanding of neurobiological mechanisms relates directly to the lack of appropriate bioanalytical technologies that allow highly resolved, sensitive, specific and comprehensive molecular imaging in complex biological matrices. Imaging mass spectrometry (IMS) is an emerging technique for molecular imaging. The technique is characterized by its high chemical specificity allowing comprehensive, spatial protein and peptide profiling in situ. Imaging MS represents therefore a powerful approach for investigation of spatio-temporal protein and peptide regulations in CNS derived tissue and cells. This review aims to provide a concise overview of major developments and applications concerning imaging mass spectrometry based protein and peptide profiling in neurobiological and biomedical research. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Esophageal cancer-related gene-4 (ECRG4) interactions with the innate immunity receptor complex

OBJECTIVE AND DESIGN

The human c2orf40 gene encodes a tumor suppressor gene called esophageal cancer-related gene-4 (ECRG4) with pro- and anti-inflammatory activities that depend on cell surface processing. Here, we investigated its physical and functional association with the innate immunity receptor complex.

METHODS

Interactions between ECRG4 and the innate immunity receptor complex were assessed by flow cytometry, immunohistochemistry, confocal microscopy, and co-immunoprecipitation. Phage display was used for ligand targeting to cells that overexpress the TLR4-MD2-CD14.

RESULTS

Immunoprecipitation and immunohistochemical studies demonstrate a physical interaction between ECRG4 and TLR4-MD2-CD14 on human granulocytes. Flow cytometry shows ECRG4 on the cell surface of a subset of CD14(+) and CD16(+) leukocytes. In a cohort of trauma patients, the C-terminal 16 amino acid domain of ECRG4 (ECRG4(133-148)) appears to be processed and shed, presumably at a thrombin-like consensus sequence. Phage targeting this putative ligand shows that this peptide sequence internalizes into cells through the TLR4/CD14/MD2 complex, but modulates inflammation through non-canonical, NFκB signal transduction.

CONCLUSIONS

ECRG4 is present on the surface of human monocytes and granulocytes. Its interaction with the human innate immunity receptor complex supports a role for cell surface activation of ECRG4 during inflammation and implicates this receptor in its mechanism of action.

Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

BACKGROUND

Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current cancer biomarkers make early cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as “peptidomics,” represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for cancer diagnostics applications.

CONTENT

Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate.

SUMMARY

Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as cancer biomarkers.

Deciphering the peptidome of urine from ovarian cancer patients and healthy controls

Background

Ovarian cancer (OvCa) is the most lethal gynecological malignancy. The emergence of high-throughput technologies, such as mass spectrometry, has allowed for a paradigm shift in the way we search for novel biomarkers. Urine-based peptidomic profiling is a novel approach that may result in the discovery of noninvasive biomarkers for diagnosing patients with OvCa. In this study, the peptidome of urine from 6 ovarian cancer patients and 6 healthy controls was deciphered.

Results

Urine samples underwent ultrafiltration and the filtrate was subjected to solid phase extraction, followed by fractionation using strong cation exchange chromatography. These fractions were analyzed using an Orbitrap mass spectrometer. Over 4600 unique endogenous urine peptides arising from 713 proteins were catalogued, representing the largest urine peptidome reported to date. Each specimen was processed in triplicate and reproducibility at the protein (69-76%) and peptide (58-63%) levels were noted. More importantly, over 3100 unique peptides were detected solely in OvCa specimens. One such promising biomarker was leucine-rich alpha-2-glycoprotein (LRG1), where multiple peptides were found in all urines from OvCa patients, but only one peptide was found in one healthy control urine sample.

Conclusions

Mining the urine peptidome may yield highly promising novel OvCa biomarkers.

Intrathecal delivery of protein therapeutics to the brain: a critical reassessment

Disorders of the central nervous system (CNS), including stroke, neurodegenerative diseases, and brain tumors, are the world's leading causes of disability. Delivery of drugs to the CNS is complicated by the blood-brain barriers that protect the brain from the unregulated leakage and entry of substances, including proteins, from the blood. Yet proteins represent one of the most promising classes of therapeutics for the treatment of CNS diseases. Many strategies for overcoming these obstacles are in development, but the relatively straightforward approach of bypassing these barriers through direct intrathecal administration has been largely overlooked. Originally discounted because of its lack of usefulness for delivering small, lipid-soluble drugs to the brain, the intrathecal route has emerged as a useful, in some cases perhaps the ideal, route of administration for certain therapeutic protein and targeted disease combinations. Here, we review blood-brain barrier functions and cerebrospinal fluid dynamics and their relevance to drug delivery via the intrathecal route, discuss animal and human studies that have investigated intrathecal delivery of protein therapeutics, and outline several characteristics of protein therapeutics that can allow them to be successfully delivered intrathecally.

The Roots of Autism and ADHD Twin Study in Sweden (RATSS)

Neurodevelopmental disorders affect a substantial minority of the general population. Their origins are still largely unknown, but a complex interplay of genetic and environmental factors causing disturbances of the central nervous system's maturation and a variety of higher cognitive skills is presumed. Only limited research of rather small sample size and narrow scope has been conducted in neurodevelopmental disorders using a twin-differences design. The Roots of Autism and ADHD Twin Study in Sweden (RATSS) is an ongoing project targeting monozygotic twins discordant for categorical or dimensional autistic and inattentive/hyperactive-impulsive phenotypes as well as other neurodevelopmental disorders, and typically developing twin controls. Included pairs are 9 years of age or older, and comprehensively assessed for psychopathology, medical history, neuropsychology, and dysmorphology, as well as structural, functional, and molecular brain imaging. Specimens are collected for induced pluripotent (iPS) and neuroepithelial stem cells, genetic, gut bacteria, protein-/monoamine, and electron microscopy analyses. RATSS's objective is to generate a launch pad for novel surveys to understand the complexity of genotype-environment-phenotype interactions in autism spectrum disorder and attention-deficit hyperactivity disorder (ADHD). By October 2013, RATSS had collected data from 55 twin pairs, among them 10 monozygotic pairs discordant for autism spectrum disorder, seven for ADHD, and four for other neurodevelopmental disorders. This article describes the design, recruitment, data collection, measures, collected pairs' characteristics, as well as ongoing and planned analyses in RATSS. Potential gains of the study comprise the identification of environmentally mediated biomarkers, the emergence of candidates for drug development, translational modeling, and new leads for prevention of incapacitating outcomes.

Proteomics and metabolomics in inflammatory bowel disease

Genome-wide studies in inflammatory bowel disease (IBD) have allowed us to understand Crohn's disease and ulcerative colitis as forms of related autoinflammatory disorders that arise from a multitude of pathogenic origins. Proteomics and metabolomics are the offspring of genomics that possess unprecedented possibilities to characterize unknown pathogenic pathways. It has been about a decade since proteomics was first applied to IBD, and 5 years for metabolomics. These techniques have yielded novel and potentially important findings, but turning these results into beneficial patient outcomes remains challenging. This review recounts the history and context of clinical IBD developments before and after proteomics and metabolomics IBD in this field, discusses the challenges in consolidating high complexity data with physiological understanding, and provides an outlook on the emerging principles that will help interface the bioanalytical laboratory with IBD prognosis.