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

Glucose sensing in pancreatic β-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 β-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.

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.

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 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 collection invasiveness 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. Those 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 had 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 last five 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 a certain maturity. They are 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 performance, while quantile protein normalization provided worse results than those obtained with unnormalized data.

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.

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Drp1 phosphorylation at S600 promotes the phosphorylation at the S579 site

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Both Drp1 P-S600 and P-S579 are required for maximal mitochondrial fragmentation

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Drp1 S600A knockin mice are protected against diet-induced metabolic damage

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Drp1 phosphorylation controls brown adipose tissue thermogenic capacity in mice

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.

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.

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 β-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 β-cell. We summarize recent evidence showing that in pancreatic β-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 β-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 β-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.

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.

Glucose-dependent phosphorylation signaling pathways and crosstalk to mitochondrial respiration in insulin secreting cells

Background

Glucose is the main secretagogue of pancreatic beta-cells. Uptake and metabolism of the nutrient stimulates the beta-cell to release the blood glucose lowering hormone insulin. This metabolic activation is associated with a pronounced increase in mitochondrial respiration. Glucose stimulation also initiates a number of signal transduction pathways for the coordinated regulation of multiple biological processes required for insulin secretion.

Methods

Shotgun proteomics including TiO₂ enrichment of phosphorylated peptides followed by liquid chromatography tandem mass spectrometry on lysates from glucose-stimulated INS-1E cells was used to identify glucose regulated phosphorylated proteins and signal transduction pathways. Kinase substrate enrichment analysis (KSEA) was applied to identify key regulated kinases and phosphatases. Glucose-induced oxygen consumption was measured using a XF96 Seahorse instrument to reveal cross talk between glucose-regulated kinases and mitochondrial activation.

Results

Our kinetic analysis of substrate phosphorylation reveal the molecular mechanism leading to rapid activation of insulin biogenesis, vesicle trafficking, insulin granule exocytosis and cytoskeleton remodeling. Kinase-substrate enrichment identified upstream kinases and phosphatases and time-dependent activity changes during glucose stimulation. Activity trajectories of well-known glucose-regulated kinases and phosphatases are described. In addition, we predict activity changes in a number of kinases including NUAK1, not or only poorly studied in the context of the pancreatic beta-cell. Furthermore, we pharmacologically tested whether signaling pathways predicted by kinase-substrate enrichment analysis affected glucose-dependent acceleration of mitochondrial respiration. We find that phosphoinositide 3-kinase, Ca2+/calmodulin dependent protein kinase and protein kinase C contribute to short-term regulation of energy metabolism.

Conclusions

Our results provide a global view into the regulation of kinases and phosphatases in insulin secreting cells and suggest cross talk between glucose-induced signal transduction and mitochondrial activation.

Electronic supplementary material

The online version of this article (10.1186/s12964-019-0326-6) contains supplementary material, which is available to authorized users.

Mitochondrial lysine deacetylation promotes energy metabolism and calcium signaling in insulin-secreting cells

In pancreatic β-cells, mitochondria generate signals that promote insulin granule exocytosis. Here we study how lysine acetylation of mitochondrial proteins mechanistically affects metabolism-secretion coupling in insulin-secreting cells. Using mass spectrometry-based proteomics, we identified lysine acetylation sites in rat insulinoma cell line clone 1E cells. In cells lacking the mitochondrial lysine deacetylase sirtuin-3 (SIRT3), several matrix proteins are hyperacetylated. Disruption of the SIRT3 gene has a deleterious effect on mitochondrial energy metabolism and Ca²⁺ signaling. Under resting conditions, SIRT3 deficient cells are overactivated, which elevates the respiratory rate and enhances calcium signaling and basal insulin secretion. In response to glucose, the SIRT3 knockout cells are unable to mount a sustained cytosolic ATP response. Calcium signaling is strongly reduced and the respiratory response as well as insulin secretion are blunted. We propose mitochondrial protein lysine acetylation as a control mechanism in β-cell energy metabolism and Ca²⁺ signaling.-De Marchi, U., Galindo, A. N., Thevenet, J., Hermant, A., Bermont, F., Lassueur, S., Domingo, J. S., Kussmann, M., Dayon, L., Wiederkehr, A. Mitochondrial lysine deacetylation promotes energy metabolism and calcium signaling in insulin-secreting cells.

Obesity shows preserved plasma proteome in large independent clinical cohorts

Holistic human proteome maps are expected to complement comprehensive profile assessment of health and disease phenotypes. However, methodologies to analyze proteomes in human tissue or body fluid samples at relevant scale and performance are still limited in clinical research. Their deployment and demonstration in large enough human populations are even sparser. In the present study, we have characterized and compared the plasma proteomes of two large independent cohorts of obese and overweight individuals using shotgun mass spectrometry (MS)-based proteomics. Herein, we showed, in both populations from different continents of about 500 individuals each, the concordance of plasma protein MS measurements in terms of variability, gender-specificity, and age-relationship. Additionally, we replicated several known and new associations between proteins, clinical and molecular variables, such as insulin and glucose concentrations. In conclusion, our MS-based analyses of plasma samples from independent human cohorts proved the practical feasibility and efficiency of a large and unified discovery/replication approach in proteomics, which was also recently coined “rectangular” design.

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.

Mass spectrometry and DigiWest technology emphasize protein acetylation profile from Quisinostat-treated HuT78 CTCL cell line

Histone deacetylases (HDACs) are key enzymes involved in epigenetic modulation and were targeted by HDAC inhibitors (HDACis) for cancer treatment. The action of HDACis is not restricted to histones and also prevents deacetylation of other proteins, supporting their wide biological actions. The HuT78 cell line is recognized as a key tool to support and understand cutaneous T-cell lymphoma (CTCL) biology and was used as a predictive model since HDACi such as Vorinostat and Panobinostat have both demonstrated apoptotic activities in HuT78 cells and in primary blood CTCL cells. In this study, Quisinostat (JNJ-26481585) a novel second-generation HDACi with highest potency for HDAC1, was tested on HuT78 cell line. Quantitative mass spectrometry (MS)-based proteomics after acetylated-lysine peptide enrichment and a targeted antibody-based immunoassay (DigiWest) were used as complementary technologies to assess the modifications of the acetylated proteome. As expected, several acetylated lysines of histones were increased by the HDACi. Additional acetylated non-histone proteins were modulated after treatment with Quisinostat including the nucleolin (a major nucleolar protein), the replication protein A 70 kDa DNA-binding subunit, the phosphoglycerate kinase 1, the stress-70 protein, the proto-oncogene Myc and the serine hydroxymethyltransferase. A better knowledge of histone and non-histone acetylated protein profile after Quisinostat treatment can strongly support the understanding of non-clinical and clinical results of this HDACi. These technological tools can also help in designing new HDACis in a pharmaceutical drug discovery program.

SIGNIFICANCE

A better knowledge of histone and non-histone acetylated protein profile after HDAC inhibitors (HDACis) treatment can strongly support the understanding of non-clinical and clinical investigations in a pharmaceutical drug discovery program. Relative quantification using mass spectrometry -based proteomics after acetylated-lysine peptide enrichment and a targeted antibody-based immunoassay (DigiWest) are proposed as complementary technologies to assess the modifications of the acetylated proteome. Quisinostat (JNJ-26481585) a novel second-generation HDACi with highest potency for HDAC1 was better characterized in vitro in HuT78 cells to support and understand cutaneous T-cell lymphoma (CTCL) therapeutic research program.

Alzheimer disease pathology and the cerebrospinal fluid proteome

BACKGROUND

Altered proteome profiles have been reported in both postmortem brain tissues and body fluids of subjects with Alzheimer disease (AD), but their broad relationships with AD pathology, amyloid pathology, and tau-related neurodegeneration have not yet been fully explored. Using a robust automated MS-based proteomic biomarker discovery workflow, we measured cerebrospinal fluid (CSF) proteomes to explore their association with well-established markers of core AD pathology.

METHODS

Cross-sectional analysis was performed on CSF collected from 120 older community-dwelling adults with normal (n = 48) or impaired cognition (n = 72). LC-MS quantified hundreds of proteins in the CSF. CSF concentrations of β-amyloid 1-42 (Aβ1-42), tau, and tau phosphorylated at threonine 181 (P-tau181) were determined with immunoassays. First, we explored proteins relevant to biomarker-defined AD. Then, correlation analysis of CSF proteins with CSF markers of amyloid pathology, neuronal injury, and tau hyperphosphorylation (i.e., Aβ1-42, tau, P-tau181) was performed using Pearson's correlation coefficient and Bonferroni correction for multiple comparisons.

RESULTS

We quantified 790 proteins in CSF samples with MS. Four CSF proteins showed an association with CSF Aβ1-42 levels (p value ≤ 0.05 with correlation coefficient (R) ≥ 0.38). We identified 50 additional CSF proteins associated with CSF tau and 46 proteins associated with CSF P-tau181 (p value ≤ 0.05 with R ≥ 0.37). The majority of those proteins that showed such associations were brain-enriched proteins. Gene Ontology annotation revealed an enrichment for synaptic proteins and proteins originating from reelin-producing cells and the myelin sheath.

CONCLUSIONS

We used an MS-based proteomic workflow to profile the CSF proteome in relation to cerebral AD pathology. We report strong evidence of previously reported CSF proteins and several novel CSF proteins specifically associated with amyloid pathology or neuronal injury and tau hyperphosphorylation.

Insights into Islet Differentiation and Maturation through Proteomic Characterization of a Human iPSC-Derived Pancreatic Endocrine Model

PURPOSE

Great progresses have been made for generating in vitro pluripotent stem cell pancreatic β-like cells. However, the maturation stage of the cells still requires in vivo maturation to recreate the environmental niche. A deeper understanding of the factors promoting maturation of the cells is of great interest for clinical applications.

EXPERIMENTAL DESIGN

Label-free mass spectrometry based proteomic analysis is performed on samples from a longitudinal study of differentiation of human induced pluripotent stem cells toward glucose responsive insulin producing cells.

RESULTS

Proteome patterns correlate with specific transcription factor gene expression levels during in vitro differentiation, showing the relevance of the technology for identification of pancreatic-specific markers. The analysis of proteomes of the implanted cells in a longitudinal study shows that the neovascularization process linked to the extracellular matrix environment is time-dependent and conditions the proper maturation of the cells in β-like cells secreting insulin in response to glucose.

CONCLUSIONS AND CLINICAL RELEVANCE

Proteomic profiling is valuable to qualify and better understand in vivo maturation of progenitor cells toward β-cells. This is critical for future clinical trials where in vivo maturation still needs to be improved for robustness and effectiveness of cell therapy. Novel biomarkers for predicting the efficiency of maturation represents noninvasive monitoring tools for following efficiency of the implant.

Circadian and Feeding Rhythms Orchestrate the Diurnal Liver Acetylome

Lysine acetylation is involved in various biological processes and is considered a key reversible post-translational modification in the regulation of gene expression, enzyme activity, and subcellular localization. This post-translational modification is therefore highly relevant in the context of circadian biology, but its characterization on the proteome-wide scale and its circadian clock dependence are still poorly described. Here, we provide a comprehensive and rhythmic acetylome map of the mouse liver. Rhythmic acetylated proteins showed subcellular localization-specific phases that correlated with the related metabolites in the regulated pathways. Mitochondrial proteins were over-represented among the rhythmically acetylated proteins and were highly correlated with SIRT3-dependent deacetylation. SIRT3 activity being nicotinamide adenine dinucleotide (NAD)+ level-dependent, we show that NAD+ is orchestrated by both feeding rhythms and the circadian clock through the NAD+ salvage pathway but also via the nicotinamide riboside pathway. Hence, the diurnal acetylome relies on a functional circadian clock and affects important diurnal metabolic pathways in the mouse liver.

One-carbon metabolism, cognitive impairment and CSF measures of Alzheimer pathology: homocysteine and beyond

Background

Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults.

Methods

Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/β-Amyloid 1–42 peptide chain [Aβ_1–42] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status.

Results

The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aβ_1–42, tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine, glycine, methionine, SAH, SAM, serine, cysteine, and Hcy and reached a diagnostic accuracy of 87.5%. CSF SAH and 5-MTHF were associated with CSF tau and p-tau181. Plasma one-carbon metabolites were able to diagnose subjects with a positive CSF profile of AD pathology in APOE ε4 carriers.

Conclusions

We observed significant improvements in the prediction of cognitive impairment by adding one-carbon metabolites. This is partially explained by associations with CSF tau and p-tau181, suggesting a role for one-carbon metabolism in the aggregation of tau and neuronal injury. These metabolites may be particularly critical in APOE ε4 carriers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-017-0270-x) contains supplementary material, which is available to authorized users.

The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention

PURPOSE

The nutritional intervention program "DiOGenes" focuses on how obesity can be prevented and treated from a dietary perspective. We generated differential plasma proteome profiles in the DiOGenes cohort to identify proteins associated with weight loss and maintenance and explore their relation to body mass index, fat mass, insulin resistance, and sensitivity.

EXPERIMENTAL DESIGN

Relative protein quantification was obtained at baseline and after combined weight loss/maintenance phases using isobaric tagging and MS/MS. A Welch t-test determined proteins differentially present after intervention. Protein relationships with clinical variables were explored using univariate linear models, considering collection center, gender and age as confounding factors.

RESULTS

Four hundred and seventy three subjects were measured at baseline and end of the intervention; 39 proteins were longitudinally differential. Proteins with largest changes were sex hormone-binding globulin, adiponectin, C-reactive protein, calprotectin, serum amyloid A, and proteoglycan 4 (PRG4), whose association with obesity and weight loss is known. We identified new putative biomarkers for weight loss/maintenance. Correlation between PRG4 and proline-rich acidic protein 1 variation and Matsuda insulin sensitivity increment was showed.

CONCLUSION AND CLINICAL RELEVANCE

MS-based proteomic analysis of a large cohort of non-diabetic overweight and obese individuals concomitantly identified known and novel proteins associated with weight loss and maintenance.

ICP-MS/MS-Based Ionomics: A Validated Methodology to Investigate the Biological Variability of the Human Ionome

We here describe the development, validation and application of a quantitative methodology for the simultaneous determination of 29 elements in human serum using state-of-the-art inductively coupled plasma triple quadrupole mass spectrometry (ICP-MS/MS). This new methodology offers high-throughput elemental profiling using simple dilution of minimal quantity of serum samples. We report the outcomes of the validation procedure including limits of detection/quantification, linearity of calibration curves, precision, recovery and measurement uncertainty. ICP-MS/MS-based ionomics was used to analyze human serum of 120 older adults. Following a metabolomic data mining approach, the generated ionome profiles were subjected to principal component analysis revealing gender and age-specific differences. The ionome of female individuals was marked by higher levels of calcium, phosphorus, copper and copper to zinc ratio, while iron concentration was lower with respect to male subjects. Age was associated with lower concentrations of zinc. These findings were complemented with additional readouts to interpret micronutrient status including ceruloplasmin, ferritin and inorganic phosphate. Our data supports a gender-specific compartmentalization of the ionome that may reflect different bone remodelling in female individuals. Our ICP-MS/MS methodology enriches the panel of validated "Omics" approaches to study molecular relationships between the exposome and the ionome in relation with nutrition and health.

Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver

Diurnal oscillations of gene expression controlled by the circadian clock and its connected feeding rhythm enable organisms to coordinate their physiologies with daily environmental cycles. While available techniques yielded crucial insights into regulation at the transcriptional level, much less is known about temporally controlled functions within the nucleus and their regulation at the protein level. Here, we quantified the temporal nuclear accumulation of proteins and phosphoproteins from mouse liver by SILAC proteomics. We identified around 5,000 nuclear proteins, over 500 of which showed a diurnal accumulation. Parallel analysis of the nuclear phosphoproteome enabled the inference of the temporal activity of kinases accounting for rhythmic phosphorylation. Many identified rhythmic proteins were parts of nuclear complexes involved in transcriptional regulation, ribosome biogenesis, DNA repair, and the cell cycle and its potentially associated diurnal rhythm of hepatocyte polyploidy. Taken together, these findings provide unprecedented insights into the diurnal regulatory landscape of the mouse liver nucleus.

A Highly Automated Shotgun Proteomic Workflow: Clinical Scale and Robustness for Biomarker Discovery in Blood

With recent technological developments, protein biomarker discoveries directly from blood have regained interest due to elevated feasibility. Mass spectrometry (MS)-based proteomics can now characterize human plasma proteomes to a greater extent than has ever been possible before. Such deep proteome coverage comes, however, with important limitations in terms of analysis time which is a critical factor in the case of clinical studies. As a consequence, compromises still need to be made to balance the proteome coverage with realistic analysis time frame in clinical research. The analysis of a sufficient number of samples is compulsory to empower statistically robust candidate biomarker findings. We have, therefore, recently developed a scalable automated proteomic pipeline (ASAP²) to enable the proteomic analysis of large numbers of plasma and cerebrospinal fluid (CSF) samples, from dozens to a thousand of samples, with the latter number being currently processed in 15 weeks. A distinct characteristic of ASAP² relies on the possibility to prepare samples in a highly automated way, mostly using 96-well plates. We describe herein a sample preparation procedure for human plasma that includes internal standard spiking, abundant protein removal, buffer exchange, reduction, alkylation, tryptic digestion, isobaric labeling, pooling, and sample purification. Other key elements of the pipeline (i.e., study design, sample tracking, liquid chromatography (LC) tandem MS (MS/MS), data processing, and data analysis) are also highlighted.

Coordinated activation of mitochondrial respiration and exocytosis mediated by PKC signaling in pancreatic β cells

Mitochondria play a central role in pancreatic β-cell nutrient sensing by coupling their metabolism to plasma membrane excitability and insulin granule exocytosis. Whether non-nutrient secretagogues stimulate mitochondria as part of the molecular mechanism to promote insulin secretion is not known. Here, we show that PKC signaling, which is employed by many non-nutrient secretagogues, augments mitochondrial respiration in INS-1E (rat insulinoma cell line clone 1E) and human pancreatic β cells. The phorbol ester, phorbol 12-myristate 13-acetate, accelerates mitochondrial respiration at both resting and stimulatory glucose concentrations. A range of inhibitors of novel PKC isoforms prevent phorbol ester-induced respiration. Respiratory response was blocked by oligomycin that demonstrated PKC-dependent acceleration of mitochondrial ATP synthesis. Enhanced respiration was observed even when glycolysis was bypassed or fatty acid transport was blocked, which suggested that PKC regulates mitochondrial processes rather than upstream catabolic fluxes. A phosphoproteome study of phorbol ester-stimulated INS-1E cells maintained under resting (2.5 mM) glucose revealed a large number of phosphorylation sites that were altered during short-term activation of PKC signaling. The data set was enriched for proteins that are involved in gene expression, cytoskeleton remodeling, secretory vesicle transport, and exocytosis. Interactome analysis identified PKC, C-Raf, and ERK1/2 as the central phosphointeraction cluster. Prevention of ERK1/2 signaling by using a MEK1 inhibitor caused a marked decreased in phorbol 12-myristate 13-acetate-induced mitochondrial respiration. ERK1/2 signaling module therefore links PKC activation to downstream mitochondrial activation. We conclude that non-nutrient secretagogues act, in part, via PKC and downstream ERK1/2 signaling to stimulate mitochondrial energy production to compensate for energy expenditure that is linked to β-cell activation.-Santo-Domingo, J., Chareyron, I., Dayon, L., Galindo, A. N., Cominetti, O., Giménez, M. P. G., De Marchi, U., Canto, C., Kussmann, M., Wiederkehr, A. Coordinated activation of mitochondrial respiration and exocytosis mediated by PKC signaling in pancreatic β cells.

High-throughput and simultaneous quantitative analysis of homocysteine-methionine cycle metabolites and co-factors in blood plasma and cerebrospinal fluid by isotope dilution LC-MS/MS

The methionine cycle is a key pathway contributing to the regulation of human health, with well-established involvement in cardiovascular diseases and cognitive function. Changes in one-carbon cycle metabolites have also been associated with mild cognitive decline, vascular dementia, and Alzheimer's disease. Today, there is no single analytical method to monitor both metabolites and co-factors of the methionine cycle. To address this limitation, we here report for the first time a new method for the simultaneous quantitation of 17 metabolites in the methionine cycle, which are homocysteic acid, taurine, serine, cysteine, glycine, homocysteine, riboflavin, methionine, pyridoxine, cystathionine, pyridoxamine, S-adenosylhomocysteine, S-adenosylmethionine, betaine, choline, dimethylglycine, and 5-methyltetrahydrofolic acid. This multianalyte method, developed using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), provides a highly accurate and precise quantitation of these 17 metabolites for both plasma and cerebrospinal fluid metabolite monitoring. The method requires a simple sample preparation, which, combined with a short chromatographic run time, ensures a high sample throughput. This analytical strategy will thus provide a novel metabolomics approach to be employed in large-scale observational and intervention studies. We expect such a robust method to be particularly relevant for broad and deep molecular phenotyping of individuals in relation to their nutritional requirements, health monitoring, and disease risk management.

Proteomics of Cerebrospinal Fluid: Throughput and Robustness Using a Scalable Automated Analysis Pipeline for Biomarker Discovery

Cerebrospinal fluid (CSF) is a body fluid of high clinical relevance and an important source of potential biomarkers for brain-associated damages, such as traumatic brain injury and stroke, and for brain diseases, such as Alzheimer's and Parkinson's. Herein, we have implemented, evaluated, and validated a scalable automated proteomic pipeline (ASAP(2)) for the sample preparation and proteomic analysis of CSF, enabling increased throughput and robustness for biomarker discovery. Human CSF samples were depleted from abundant proteins and subjected to automated reduction, alkylation, protein digestion, tandem mass tag (TMT) 6-plex labeling, pooling, and sample cleanup in a 96-well-plate format before reversed-phase liquid chromatography tandem mass spectrometry (RP-LC MS/MS). We showed the impact on the CSF proteome coverage of applying the depletion of abundant proteins, which is usually performed on blood plasma or serum samples. Using ASAP(2) to analyze 96 identical CSF samples, we determined the analytical figures of merit of our shotgun proteomic approach regarding proteome coverage consistency (i.e., 387 proteins), quantitative accuracy, and individual protein variability. We demonstrated that, as for human plasma samples, ASAP(2) is efficient in analyzing large numbers of human CSF samples and is a valuable tool for biomarker discovery. The data has been deposited to the ProteomeXchange with identifier PXD003024.

Proteomics and circadian rhythms: it's all about signaling!

Proteomic technologies using MS offer new perspectives in circadian biology, in particular the possibility to study PTMs. To date, only very few studies have been carried out to decipher the rhythmicity of protein expression in mammals with large-scale proteomics. Although signaling has been shown to be of high relevance, comprehensive characterization studies of PTMs are even more rare. This review aims at describing the actual landscape of circadian proteomics and the opportunities and challenges appearing on the horizon. Emphasis was given to signaling processes for their role in metabolic health as regulated by circadian clocks and environmental factors. Those signaling processes are expected to be better and more deeply characterized in the coming years with proteomics.

General statistical modeling of data from protein relative expression isobaric tags

Quantitative comparison of the protein content of biological samples is a fundamental tool of research. The TMT and iTRAQ isobaric labeling technologies allow the comparison of 2, 4, 6, or 8 samples in one mass spectrometric analysis. Sound statistical models that scale with the most advanced mass spectrometry (MS) instruments are essential for their efficient use. Through the application of robust statistical methods, we developed models that capture variability from individual spectra to biological samples. Classical experimental designs with a distinct sample in each channel as well as the use of replicates in multiple channels are integrated into a single statistical framework. We have prepared complex test samples including controlled ratios ranging from 100:1 to 1:100 to characterize the performance of our method. We demonstrate its application to actual biological data sets originating from three different laboratories and MS platforms. Finally, test data and an R package, named isobar, which can read Mascot, Phenyx, and mzIdentML files, are made available. The isobar package can also be used as an independent software that requires very little or no R programming skills.