SLC25A46 promotes mitochondrial fission and mediates resistance to lipotoxic stress in INS-1E insulin-secreting cells.

Glucose sensing in pancreatic ß-cells depends on oxidative phosphorylation and mitochondria-derived signals that promote insulin secretion. Using mass spectrometry-based phosphoproteomics to search for downstream effectors of glucose-dependent signal transduction in INS-1E insulinoma cells, we identified the outer mitochondrial membrane protein SLC25A46. Under resting glucose concentrations, SLC25A46 was phosphorylated on a pair of threonine residues (T44/T45) and was dephosphorylated in response to glucose-induced Ca2+ signals. Overexpression of SLC25A46 in INS-1E cells caused complete mitochondrial fragmentation, resulting in a mild mitochondrial defect associated with lowered glucose-induced insulin secretion. In contrast, inactivation of the Slc25a46 gene resulted in dramatic mitochondrial hyperfusion, without affecting respiratory activity or insulin secretion. Consequently, SLC25A46 is not essential for metabolism-secretion coupling under normal nutrient conditions. Importantly, insulin-secreting cells lacking SLC25A46 had an exacerbated sensitivity to lipotoxic conditions, undergoing massive apoptosis when exposed to palmitate. Therefore, in addition to its role in mitochondrial dynamics, SLC25A46 plays a role in preventing mitochondria-induced apoptosis in INS-E cells exposed to nutrient stress. By protecting mitochondria, SLC25A46 might help to maintain ß-cell mass essential for blood glucose control.

Super-Resolution Mass Spectrometry Enables Rapid, Accurate, and Highly Multiplexed Proteomics at the MS2 Level.

In tandem mass spectrometry (MS2)-based multiplexed quantitative proteomics, the complement reporter ion approaches (TMTc and TMTproC) were developed to eliminate the ratio-compression problem of conventional MS2-level approaches. Resolving all high m/z complement reporter ions (∼6.32 mDa-spaced) requires mass resolution and scan speeds above the performance levels of OrbitrapTM instruments. Therefore, complement reporter ion quantification with TMT/TMTpro reagents is currently limited to 5 out of 11 (TMT) or 9 out of 18 (TMTpro) channels (∼1 Da spaced). We first demonstrate that a FusionTM LumosTM Orbitrap can resolve 6.32 mDa-spaced complement reporter ions with standard acquisition modes extended with 3 s transients. We then implemented a super-resolution mass spectrometry approach using the least-squares fitting (LSF) method for processing Orbitrap transients to achieve shotgun proteomics-compatible scan rates. The LSF performance resolves the 6.32 mDa doublets for all TMTproC channels in the standard mass range with transients as short as ∼108 ms (Orbitrap resolution setting of 50,000 at m/z 200). However, we observe a slight decrease in measurement precision compared to 1 Da spacing with the 108 ms transients. With 256 ms transients (resolution of 120,000 at m/z 200), coefficients of variation are essentially indistinguishable from 1 Da samples. We thus demonstrate the feasibility of highly multiplexed, accurate, and precise shotgun proteomics at the MS2 level.

Blood plasma protein profiles of neuropsychiatric symptoms and related cognitive decline in older people.

Neuropsychiatric symptoms (NPS) severely affect patients and their caregivers, and are associated with worse long-term outcomes. This study tested the hypothesis that altered protein levels in blood plasma could serve as biomarkers of NPS; and that altered protein levels are associated with persisting NPS and cognitive decline over time. We performed a cross-sectional and longitudinal study in older subjects with cognitive impairment and cognitively unimpaired in a memory clinic setting. NPS were recorded through the Neuropsychiatric Inventory Questionnaire (NPI-Q) while cognitive and functional impairment was assessed using the clinical dementia rating sum of boxes (CDR-SoB) score at baseline and follow-up visits. Shotgun proteomic analysis based on liquid chromatography-mass spectrometry was conducted in blood plasma samples, identifying 420 proteins. The presence of Alzheimer's Disease (AD) pathology was determined by cerebrospinal fluid biomarkers. Eighty-five subjects with a mean age of 70 (±7.4) years, 62% female and 54% with mild cognitive impairment or mild dementia were included. We found 15 plasma proteins with altered baseline levels in participants with NPS (NPI-Q score > 0). Adding those 15 proteins to a reference model based on clinical data (age, CDR-SoB) significantly improved the prediction of NPS (from receiver operating characteristic area under the curve [AUC] 0.75 to AUC 0.91, p = 0.004) with a specificity of 89% and a sensitivity of 74%. The identified proteins additionally predicted both persisting NPS and cognitive decline at follow-up visits. The observed associations were independent of the presence of AD pathology. Using proteomics, we identified a panel of specific blood proteins associated with current and future NPS, and related cognitive decline in older people. These findings show the potential of untargeted proteomics to identify blood-based biomarkers of pathological alterations relevant for NPS and related clinical disease progression.

The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease.

Beyond the core features of Alzheimer's disease (AD) pathology, i.e. amyloid pathology, tau-related neurodegeneration and microglia response, multiple other molecular alterations and pathway dysregulations have been observed in AD. Their inter-individual variations, complex interactions and relevance for clinical manifestation and disease progression remain poorly understood, however. Heterogeneity at both pathophysiological and clinical levels complicates diagnosis, prognosis, treatment and drug design and testing. High-throughput "omics" comprise unbiased and untargeted data-driven methods which allow the exploration of a wide spectrum of disease-related changes at different endophenotype levels without focussing a priori on specific molecular pathways or molecules. Crucially, new methodological and statistical advances now allow for the integrative analysis of data resulting from multiple and different omics methods. These multi-omics approaches offer the unique advantage of providing a more comprehensive characterisation of the AD endophenotype and to capture molecular signatures and interactions spanning various biological levels. These new insights can then help decipher disease mechanisms more deeply. In this review, we describe the different multi-omics tools and approaches currently available and how they have been applied in AD research so far. We discuss how multi-omics can be used to explore molecular alterations related to core features of the AD pathologies and how they interact with comorbid pathological alterations. We further discuss whether the identified pathophysiological changes are relevant for the clinical manifestation of AD, in terms of both cognitive impairment and neuropsychiatric symptoms, and for clinical disease progression over time. Finally, we address the opportunities for multi-omics approaches to help discover novel biomarkers for diagnosis and monitoring of relevant pathophysiological processes, along with personalised intervention strategies in AD.

Systemic and central nervous system neuroinflammatory signatures of neuropsychiatric symptoms and related cognitive decline in older people.

BACKGROUND: Neuroinflammation may contribute to psychiatric symptoms in older people, in particular in the context of Alzheimer's disease (AD). We sought to identify systemic and central nervous system (CNS) inflammatory alterations associated with neuropsychiatric symptoms (NPS); and to investigate their relationships with AD pathology and clinical disease progression. METHODS: We quantified a panel of 38 neuroinflammation and vascular injury markers in paired serum and cerebrospinal fluid (CSF) samples in a cohort of cognitively normal and impaired older subjects. We performed neuropsychiatric and cognitive evaluations and measured CSF biomarkers of AD pathology. Multivariate analysis determined serum and CSF neuroinflammatory alterations associated with NPS, considering cognitive status, AD pathology, and cognitive decline at follow-up visits. RESULTS: NPS were associated with distinct inflammatory profiles in serum, involving eotaxin-3, interleukin (IL)-6 and C-reactive protein (CRP); and in CSF, including soluble intracellular cell adhesion molecule-1 (sICAM-1), IL-8, 10-kDa interferon-γ-induced protein, and CRP. AD pathology interacted with CSF sICAM-1 in association with NPS. Presenting NPS was associated with subsequent cognitive decline which was mediated by CSF sICAM-1. CONCLUSIONS: Distinct systemic and CNS inflammatory processes are involved in the pathophysiology of NPS in older people. Neuroinflammation may explain the link between NPS and more rapid clinical disease progression.

Proteomics reveals unique plasma signatures in constitutional thinness.

PURPOSE: Studying the plasma proteome of control versus constitutionally thin (CT) individuals, exposed to overfeeding, may give insights into weight-gain management, providing relevant information to the clinical entity of weight-gain resistant CT, and discovering new markers for the condition. EXPERIMENTAL DESIGN: Untargeted protein relative quantification of 63 CT and normal-weight individuals was obtained in blood plasma at baseline, during and after an overfeeding challenge using mass spectrometry-based proteomics. RESULTS: The plasma proteome of CT subjects presented limited specificity with respect to controls at baseline. Yet, CT showed lower levels of inflammatory C-reactive protein and larger levels of protective insulin-like growth factor-binding protein 2. Differences were more marked during and after overfeeding. CT plasma proteome showed larger magnitude and significance in response, suggesting enhanced "resilience" and more rapid adaptation to changes. Four proteins behaved similarly between CT and controls, while five were regulated in opposite fashion. Ten proteins were differential during overfeeding in CT only (including increased fatty acid-binding protein and glyceraldehyde-3-phosphate dehydrogenase, and decreased apolipoprotein C-II and transferrin receptor protein 1). CONCLUSIONS AND CLINICAL RELEVANCE: This first proteomic profiling of a CT cohort reveals different plasma proteomes between CT subjects and controls in a longitudinal clinical trial. Our molecular observations further support that the resistance to weight gain in CT subjects appears predominantly biological. CLINICALTRIALS: gov Identifier: NCT02004821.

Proteomics of human biological fluids for biomarker discoveries: technical advances and recent applications.

INTRODUCTION: Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate invasive collection and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades, proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids. AREAS COVERED: We review proteomic technologies for the identification of biomarkers. These are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that has until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from the last 5 years in the Scopus database) using MS-based proteomics. EXPERT OPINION: While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached certain maturity. They are now better suited to discover innovative and robust biofluid biomarkers.

Assessing normalization methods in mass spectrometry-based proteome profiling of clinical samples.

BACKGROUND: Large-scale proteomic studies have to deal with unwanted variability, especially when samples originate from different centers and multiple analytical batches are needed. Such variability is typically added throughout all the steps of a clinical research study, from human biological sample collection and storage, sample preparation, spectral data acquisition, to peptide and protein quantification. In order to remove such diverse and unwanted variability, normalization of the protein data is performed. There have been already several published reviews comparing normalization methods in the -omics field, but reports focusing on proteomic data generated with mass spectrometry (MS) are much fewer. Additionally, most of these reports have only dealt with small datasets. RESULTS: As a case study, here we focused on the normalization of a large MS-based proteomic dataset obtained from an overweight and obese pan-European cohort, where different normalization methods were evaluated, namely: center standardize, quantile protein, quantile sample, global standardization, ComBat, median centering, mean centering, single standard and removal of unwanted variation (RUV); some of these are generic normalization methods while others have been specifically created to deal with genomic or metabolomic data. We checked how relationships between proteins and clinical variables (e.g., gender, levels of triglycerides or cholesterol) were improved after normalizing the data with the different methods. CONCLUSIONS: Some normalization methods were better adapted for this particular large-scale shotgun proteomic dataset of human plasma samples labeled with isobaric tags and analyzed with liquid chromatography-tandem MS. In particular, quantile sample normalization, RUV, mean and median centering showed very good performances, while quantile protein normalization provided worse results than those obtained with unnormalized data.

Cerebrospinal Fluid Proteome Alterations Associated with Neuropsychiatric Symptoms in Cognitive Decline and Alzheimer's Disease.

Although neuropsychiatric symptoms (NPS) are common and severely affect older people with cognitive decline, little is known about their underlying molecular mechanisms and relationships with Alzheimer's disease (AD). The aim of this study was to identify and characterize cerebrospinal fluid (CSF) proteome alterations related to NPS. In a longitudinally followed-up cohort of subjects with normal cognition and patients with cognitive impairment (MCI and mild dementia) from a memory clinic setting, we quantified a panel of 790 proteins in CSF using an untargeted shotgun proteomic workflow. Regression models and pathway enrichment analysis were used to investigate protein alterations related to NPS, and to explore relationships with AD pathology and cognitive decline at follow-up visits. Regression analysis selected 27 CSF proteins associated with NPS. These associations were independent of the presence of cerebral AD pathology (defined as CSF p-tau181/Aß1−42 > 0.0779, center cutoff). Gene ontology enrichment showed abundance alterations of proteins related to cell adhesion, immune response, and lipid metabolism, among others, in relation to NPS. Out of the selected proteins, three were associated with accelerated cognitive decline at follow-up visits after controlling for possible confounders. Specific CSF proteome alterations underlying NPS may both represent pathophysiological processes independent from AD and accelerate clinical disease progression.

Crosstalk between Drp1 phosphorylation sites during mitochondrial remodeling and their impact on metabolic adaptation.

Mitochondria constantly undergo fusion and fission events, referred as mitochondrial dynamics, which determine mitochondrial architecture and bioenergetics. Cultured cell studies demonstrate that mitochondrial dynamics are acutely regulated by phosphorylation of the mitochondrial fission orchestrator dynamin-related protein 1 (Drp1) at S579 or S600. However, the physiological impact and crosstalk of these phosphorylation sites is poorly understood. Here, we describe the functional interrelation between S579 and S600 phosphorylation sites in vivo and their role on mitochondrial remodeling. Mice carrying a homozygous Drp1 S600A knockin (Drp1 KI) mutation display larger mitochondria and enhanced lipid oxidation and respiratory capacities, granting improved glucose tolerance and thermogenic response upon high-fat feeding. Housing mice at thermoneutrality blunts these differences, suggesting a role for the brown adipose tissue in the protection of Drp1 KI mice against metabolic damage. Overall, we demonstrate crosstalk between Drp1 phosphorylation sites and provide evidence that their modulation could be used in the treatment and prevention of metabolic diseases.

An integrative multi-omics approach reveals new central nervous system pathway alterations in Alzheimer's disease.

BACKGROUND: Multiple pathophysiological processes have been described in Alzheimer's disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood. We hypothesize that specific molecular patterns indicating both known and yet unidentified pathway alterations are associated with distinct aspects of AD pathology. METHODS: We performed multi-level cerebrospinal fluid (CSF) omics in a well-characterized cohort of older adults with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analyzed at single-omic level with correlation and regression approaches. Multi-omics factor analysis was used to integrate all biological levels. Identified analytes were used to construct best predictive models of the presence of AD pathology and of cognitive decline with multifactorial regression analysis. Pathway enrichment analysis identified pathway alterations in AD. RESULTS: Multi-omics integration identified five major dimensions of heterogeneity explaining the variance within the cohort and differentially associated with AD. Further analysis exposed multiple interactions between single 'omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response, and extracellular matrix signaling pathways in association with AD. Finally, combinations of four molecules improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1). CONCLUSIONS: Applying an integrative multi-omics approach we report novel molecular and pathways alterations associated with AD pathology. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.

Proteomics of Human Milk: Definition of a Discovery Workflow for Clinical Research Studies.

Milk is a complex biological fluid composed mainly of water, carbohydrates, lipids, proteins, and diverse bioactive factors. Human milk represents a unique tailored source of nutrients that adapts during lactation to the specific needs of the developing infant. Proteins in milk have been studied for decades, and proteomics, peptidomics, and glycoproteomics are the main approaches previously deployed to decipher the proteome of human milk. In the present work, we aimed at implementing a highly automated pipeline for the proteomic analysis of human milk with liquid chromatography mass spectrometry (MS). Commercial human milk samples were used to evaluate and optimize workflows. Centrifugation for defatting milk samples was assessed before and after reduction, alkylation, and enzymatic digestion of proteins, without and with presence of surfactants. Skimmed milk samples were analyzed using isobaric labeling-based quantitative MS on an Orbitrap Tribrid mass spectrometer. Sample fractionation using isoelectric focusing was also evaluated to more deeply profile the human milk proteome. Finally, the most appropriate workflow was transferred to a liquid handling workstation for automated sample preparation. In conclusion, we have defined and describe herein an efficient highly automated proteomic workflow for human milk sample analysis. It is compatible with clinical research, possibly allowing the analysis of sufficiently large cohorts of samples.

Augmented mitochondrial energy metabolism is an early response to chronic glucose stress in human pancreatic beta cells.

AIMS/HYPOTHESIS: In islets from individuals with type 2 diabetes and in islets exposed to chronic elevated glucose, mitochondrial energy metabolism is impaired. Here, we studied early metabolic changes and mitochondrial adaptations in human beta cells during chronic glucose stress. METHODS: Respiration and cytosolic ATP changes were measured in human islet cell clusters after culture for 4 days in 11.1 mmol/l glucose. Metabolomics was applied to analyse intracellular metabolite changes as a result of glucose stress conditions. Alterations in beta cell function were followed using insulin secretion assays or cytosolic calcium signalling after expression of the calcium probe YC3.6 specifically in beta cells of islet clusters. RESULTS: At early stages of glucose stress, mitochondrial energy metabolism was augmented in contrast to the previously described mitochondrial dysfunction in beta cells from islets of diabetic donors. Following chronic glucose stress, mitochondrial respiration increased (by 52.4%, p < 0.001) and, as a consequence, the cytosolic ATP/ADP ratio in resting human pancreatic islet cells was elevated (by 27.8%, p < 0.05). Because of mitochondrial overactivation in the resting state, nutrient-induced beta cell activation was reduced. In addition, chronic glucose stress caused metabolic adaptations that resulted in the accumulation of intermediates of the glycolytic pathway, the pentose phosphate pathway and the TCA cycle; the most strongly augmented metabolite was glycerol 3-phosphate. The changes in metabolites observed are likely to be due to the inability of mitochondria to cope with continuous nutrient oversupply. To protect beta cells from chronic glucose stress, we inhibited mitochondrial pyruvate transport. Metabolite concentrations were partially normalised and the mitochondrial respiratory response to nutrients was markedly improved. Furthermore, stimulus-secretion coupling as assessed by cytosolic calcium signalling, was restored. CONCLUSION/INTERPRETATION: We propose that metabolic changes and associated mitochondrial overactivation are early adaptations to glucose stress, and may reflect what happens as a result of poor blood glucose control. Inhibition of mitochondrial pyruvate transport reduces mitochondrial nutrient overload and allows beta cells to recover from chronic glucose stress. Graphical abstract.

Exploration of human cerebrospinal fluid: A large proteome dataset revealed by trapped ion mobility time-of-flight mass spectrometry.

Cerebrospinal fluid (CSF) is a biofluid in direct contact with the brain and as such constitutes a sample of choice in neurological disorder research, including neurodegenerative diseases such as Alzheimer or Parkinson. Human CSF has still been less studied using proteomic technologies compared to other biological fluids such as blood plasma or serum. In this work, a pool of "normal" human CSF samples was analysed using a shotgun proteomic workflow that combined removal of highly abundant proteins by immunoaffinity depletion and isoelectric focussing fractionation of tryptic peptides to alleviate the complexity of the biofluid. The resulting 24 fractions were analysed using liquid chromatography coupled to a high-resolution and high-accuracy timsTOF Pro mass spectrometer. This state-of-the-art mass spectrometry-based proteomic workflow allowed the identification of 3'174 proteins in CSF. The dataset reported herein completes the pool of the most comprehensive human CSF proteomes obtained so far. An overview of the identified proteins is provided based on gene ontology annotation. Mass and tandem mass spectra are made available as a possible starting point for further studies exploring the human CSF proteome.

Progress and pitfalls of using isobaric mass tags for proteome profiling.

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

Protein Lysine Acetylation: Grease or Sand in the Gears of ß-Cell Mitochondria?

Mitochondria carry out many essential functions in metabolism. A central task is the oxidation of nutrients and the generation of ATP by oxidative phosphorylation. Mitochondrial metabolism needs to be tightly regulated for the cell to respond to changes in ATP demand and nutrient supply. Here, we review how protein lysine acetylation contributes to the regulation of mitochondrial metabolism in insulin target tissues and the insulin-secreting pancreatic ß-cell. We summarize recent evidence showing that in pancreatic ß-cells, lysine acetylation occurs on a large number of proteins involved in metabolism. Furthermore, we give a brief overview of the molecular mechanism that controls lysine acetylation dynamics. We propose that protein lysine acetylation is an important mechanism for the fine-tuning of mitochondrial activity in ß-cells during normal physiology. In contrast, nutrient oversupply, oxidative stress, or inhibition of the mitochondrial deacetylase SIRT3 leads to protein lysine hyperacetylation, which impairs mitochondrial function. By perturbing mitochondrial activity in ß-cells and insulin target tissues, protein lysine hyperacetylation may contribute to the development of type 2 diabetes.

Persistent low body weight in humans is associated with higher mitochondrial activity in white adipose tissue.

BACKGROUND: Constitutional thinness (CT) is a state of low but stable body weight (BMI ≤18 kg/m2). CT subjects have normal-range hormonal profiles and food intake but exhibit resistance to weight gain despite living in the modern world's obesogenic environment. OBJECTIVE: The goal of this study is to identify molecular mechanisms underlying this protective phenotype against weight gain. METHODS: We conducted a clinical overfeeding study on 30 CT subjects and 30 controls (BMI 20-25 kg/m2) matched for age and sex. We performed clinical and integrative molecular and transcriptomic analyses on white adipose and muscle tissues. RESULTS: Our results demonstrate that adipocytes were markedly smaller in CT individuals (mean ± SEM: 2174 ± 142 µm 2) compared with controls (3586 ± 216 µm2) (P < 0.01). The mitochondrial respiratory capacity was higher in CT adipose tissue, particularly at the level of complex II of the electron transport chain (2.2-fold increase; P < 0.01). This higher activity was paralleled by an increase in mitochondrial number (CT compared with control: 784 ± 27 compared with 675 ± 30 mitochondrial DNA molecules per cell; P < 0.05). No evidence for uncoupled respiration or "browning" of the white adipose tissue was found. In accordance with the mitochondrial differences, CT subjects had a distinct adipose transcriptomic profile [62 differentially expressed genes (false discovery rate of 0.1 and log fold change >0.75)], with many differentially expressed genes associating with positive metabolic outcomes. Pathway analyses revealed an increase in fatty acid oxidation ( P = 3 × 10-04) but also triglyceride biosynthesis (P = 3.6 × 10-04). No differential response to the overfeeding was observed in the 2 groups. CONCLUSIONS: The distinct molecular signature of the adipose tissue in CT individuals suggests the presence of augm ented futile lipid cycling, rather than mitochondrial uncoupling, as a way to increase energy expenditure in CT individuals. We propose that increased mitochondrial function in adipose tissue is an important mediator in sustaining the low body weight in CT individuals. This knowledge could ultimately allow more targeted approaches for weight management treatment strategies. This trial was registered at clinicaltrials.gov as NCT02004821.

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.

Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance.

Comprehensive, high throughput analysis of the plasma proteome has the potential to enable holistic analysis of the health state of an individual. Based on our own experience and the evaluation of recent large-scale plasma mass spectrometry (MS) based proteomic studies, we identified two outstanding challenges: slow and delicate nano-flow liquid chromatography (LC) and irreproducibility of identification of data-dependent acquisition (DDA). We determined an optimal solution reducing these limitations with robust capillary-flow data-independent acquisition (DIA) MS. This platform can measure 31 plasma proteomes per day. Using this setup, we acquired a large-scale plasma study of the diet, obesity and genes dietary (DiOGenes) comprising 1508 samples. Proving the robustness, the complete acquisition was achieved on a single analytical column. Totally, 565 proteins (459 identified with two or more peptide sequences) were profiled with 74% data set completeness. On average 408 proteins (5246 peptides) were identified per acquisition (319 proteins in 90% of all acquisitions). The workflow reproducibility was assessed using 34 quality control pools acquired at regular intervals, resulting in 92% data set completeness with CVs for protein measurements of 10.9%.The profiles of 20 apolipoproteins could be profiled revealing distinct changes. The weight loss and weight maintenance resulted in sustained effects on low-grade inflammation, as well as steroid hormone and lipid metabolism, indicating beneficial effects. Comparison to other large-scale plasma weight loss studies demonstrated high robustness and quality of biomarker candidates identified. Tracking of nonenzymatic glycation indicated a delayed, slight reduction of glycation in the weight maintenance phase. Using stable-isotope-references, we could directly and absolutely quantify 60 proteins in the DIA.In conclusion, we present herein the first large-scale plasma DIA study and one of the largest clinical research proteomic studies to date. Application of this fast and robust workflow has great potential to advance biomarker discovery in plasma.

Analyzing Cerebrospinal Fluid Proteomes to Characterize Central Nervous System Disorders: A Highly Automated Mass Spectrometry-Based Pipeline for Biomarker Discovery.

Over the past decade, liquid chromatography tandem mass spectrometry (LC MS/MS)-based workflows become standard for biomarker discovery in proteomics. These medium- to high-throughput (in terms of protein content) profiling approaches have been applied to clinical research. As a result, human proteomes have been characterized to a greater extent than ever before. However, proteomics in clinical research and biomarker discovery studies has generally been performed with small cohorts of subjects (or pooled samples from larger cohorts). This is problematic, as when aiming to identify novel biomarkers, small studies suffer from inherent and important limitations, as a result of the reduced biological diversity and representativity of human populations. Consequently, larger-scale proteomics will be key to delivering robust biomarker candidates and enabling translation to clinical practice.Cerebrospinal fluid (CSF) is a highly clinically relevant body fluid, and an important source of potential biomarkers for brain-associated damage, such as that induced by traumatic brain injury and stroke, and brain diseases, such as Alzheimer's disease and Parkinson's disease. We have developed a scalable automated proteomic pipeline (ASAP2) for biomarker discovery. This workflow is compatible with larger clinical research studies in terms of sample size, while still allowing several hundred proteins to be measured in CSF by MS. In this chapter, we describe the whole proteomic workflow to analyze human CSF. We further illustrate our protocol with some examples from an analysis of hundreds of human CSF samples, in the specific context of biomarker discovery to characterize central nervous system disorders.