Metabolic Labeling of Mammalian Organisms with Stable Isotopes for Quantitative Proteomic Analysis

Gaussian Process Modeling of Protein Turnover

We describe a stochastic model to compute in vivo protein turnover rate constants from stable-isotope labeling and high-throughput liquid chromatography-mass spectrometry experiments. We show that the often-used one- and two-compartment nonstochastic models allow explicit solutions from the corresponding stochastic differential equations. The resulting stochastic process is a Gaussian processes with Ornstein-Uhlenbeck covariance matrix. We applied the stochastic model to a large-scale data set from (15)N labeling and compared its performance metrics with those of the nonstochastic curve fitting. The comparison showed that for more than 99% of proteins, the stochastic model produced better fits to the experimental data (based on residual sum of squares). The model was used for extracting protein-decay rate constants from mouse brain (slow turnover) and liver (fast turnover) samples. We found that the most affected (compared to two-exponent curve fitting) results were those for liver proteins. The ratio of the median of degradation rate constants of liver proteins to those of brain proteins increased 4-fold in stochastic modeling compared to the two-exponent fitting. Stochastic modeling predicted stronger differences of protein turnover processes between mouse liver and brain than previously estimated. The model is independent of the labeling isotope. To show this, we also applied the model to protein turnover studied in induced heart failure in rats, in which metabolic labeling was achieved by administering heavy water. No changes in the model were necessary for adapting to heavy-water labeling. The approach has been implemented in a freely available R code.

Current Proteomic Methods to Investigate the Dynamics of Histone Turnover in the Central Nervous System

Characterizing the dynamic behavior of nucleosomes in the central nervous system is vital to our understanding of brain-specific chromatin-templated processes and their roles in transcriptional plasticity. Histone turnover-the complete loss of old, and replacement by new, nucleosomal histones-is one such phenomenon that has recently been shown to be critical for cell-type-specific transcription in brain, synaptic plasticity, and cognition. Such revelations that histones, long believed to static proteins in postmitotic cells, are highly dynamic in neurons were only possible owing to significant advances in analytical chemistry-based techniques, which now provide a platform for investigations of histone dynamics in both healthy and diseased tissues. Here, we discuss both past and present proteomic methods (eg, mass spectrometry, human "bomb pulse labeling") for investigating histone turnover in brain with the hope that such information may stimulate future investigations of both adaptive and aberrant forms of "neuroepigenetic" plasticity.

A Biologist's Field Guide to Multiplexed Quantitative Proteomics

High-throughput genomic and proteomic studies have generated near-comprehensive catalogs of biological constituents within many model systems. Nevertheless, static catalogs are often insufficient to fully describe the dynamic processes that drive biology. Quantitative proteomic techniques address this need by providing insight into closely related biological states such as the stages of a therapeutic response or cellular differentiation. The maturation of quantitative proteomics in recent years has brought about a variety of technologies, each with their own strengths and weaknesses. It can be difficult for those unfamiliar with this evolving landscape to match the experiment at hand with the best tool for the job. Here, we outline quantitative methods for proteomic mass spectrometry and discuss their benefits and weaknesses from the perspective of the biologist aiming to generate meaningful data and address mechanistic questions.

Reduced in vivo hepatic proteome replacement rates but not cell proliferation rates predict maximum lifespan extension in mice

Combating the social and economic consequences of a growing elderly population will require the identification of interventions that slow the development of age-related diseases. Preserved cellular homeostasis and delayed aging have been previously linked to reduced cell proliferation and protein synthesis rates. To determine whether changes in these processes may contribute to or predict delayed aging in mammals, we measured cell proliferation rates and the synthesis and replacement rates (RRs) of over a hundred hepatic proteins in vivo in three different mouse models of extended maximum lifespan (maxLS): Snell Dwarf, calorie-restricted (CR), and rapamycin (Rapa)-treated mice. Cell proliferation rates were not consistently reduced across the models. In contrast, reduced hepatic protein RRs (longer half-lives) were observed in all three models compared to controls. Intriguingly, the degree of mean hepatic protein RR reduction was significantly correlated with the degree of maxLS extension across the models and across different Rapa doses. Absolute rates of hepatic protein synthesis were reduced in Snell Dwarf and CR, but not Rapa-treated mice. Hepatic chaperone levels were unchanged or reduced and glutathione S-transferase synthesis was preserved or increased in all three models, suggesting a reduced demand for protein renewal, possibly due to reduced levels of unfolded or damaged proteins. These data demonstrate that maxLS extension in mammals is associated with improved hepatic proteome homeostasis, as reflected by a reduced demand for protein renewal, and that reduced hepatic protein RRs hold promise as an early biomarker and potential target for interventions that delay aging in mammals.

LG. Allocation of endogenous nutrients for reproduction in the lesser long-nosed bat ( Leptonycteris yerbabuenae ) in central Mexico

In contrast to birds, the contribution of body reserves to sustain reproductive activities of migratory bats has not being examined. We used C stable isotope analysis to track the importance of nutrients stored in body tissues of the lesser long-nosed bat ( Leptonycteris yerbabuenae ) in Central Mexico. The bat migrates seasonally between areas dominated by vegetation types with contrasting C stable isotope values: in spring–summer, it forages in cactus forests before commuting to dry and wet forests, where mating and births occur. We collected breath and whole blood from nonreproductive individuals in a cactus forest in spring–mid-summer, from mating individuals in an evergreen forest in mid-late summer, and from lactating females in winter in a tropical deciduous forest. We also collected hair and milk from lactating females and several tissues from naturally aborted fetus in late autumn. We tested the hypothesis that nutrient reserves accumulated in cactus forest contribute to the maintenance of adults when they commute to their reproductive grounds, to the construction of offspring tissues during pregnancy, and to the production of milk. The importance of energy stores accumulated in cactus forests to fuel oxidative metabolism was marginal for mating males but it was high for some mating females. Nutrient stores accumulated in cactus forests contributed to ~50% of synthesis of fetus tissues but their contribution for milk production was negligible. Female lesser long-nosed bats can be described as capital-income breeders in relation to the development of offspring during gestation and as incomer breeders in relation to lactation.

En contraste con las aves, la contribución de las reservas corporales para mantener las actividades reproductivas no ha sido evaluada en los murciélagos migratorios. En este estudio, usamos análisis de isótopos estables de C para reconstruir la importancia de los nutrientes almacenados en los tejidos del murciélago magueyero menor ( Leptonycteris yerbabuenae ) en el centro de México. Este murciélago migra estacionalmente entre áreas dominadas por tipos de vegetación con valores contrastantes de isótopos estables de C: la especie forrajea en bosques de cactáceas en primavera-verano antes de moverse a bosques secos y húmedos donde ocurren el apareamiento y los nacimientos. Se colectaron muestras de aliento y sangre entera de individuos no reproductivos en un bosque de cactáceas en primavera y mediados del verano, de individuos en etapa de apareamiento en un bosque húmedo a mediados y finales del verano, y de hembras lactantes en el invierno en un bosque seco tropical. Además, se colectaron muestras de pelo y leche de las hembras lactantes, y de varios tejidos de fetos a finales del otoño. Se probó la hipótesis de que las reservas de nutrientes acumuladas en el bosque de cactáceas contribuyen al mantenimiento de los adultos cuando se mueven a sus sitios de apareamiento, a la construcción de tejidos de las crías durante la preñez, y a la producción de leche. La importancia de las reservas de energía acumuladas en los bosques de cactáceas fue marginal para los machos y fue alta para algunas hembras durante el apareamiento. Los nutrientes acumulados en los bosques de cactáceas contribuyeron en hasta el 50% de la síntesis de tejidos de los fetos pero su contribución para la producción de leche fue de poca importancia. Las hembras de los murciélagos magueyeros menores siguen una estrategia reproductiva mixta de uso de reservas acumuladas y de nutrientes externos en relación al desarrollo de las crías durante la gestación, y una estrategia de uso de nutrientes externos en relación a la lactancia.

Proteomic Analysis of Protein Turnover by Metabolic Whole Rodent Pulse-Chase Isotopic Labeling and Shotgun Mass Spectrometry Analysis

The analysis of protein half-life and degradation dynamics has proven critically important to our understanding of a broad and diverse set of biological conditions ranging from cancer to neurodegeneration. Historically these protein turnover measures have been performed in cells by monitoring protein levels after "pulse" labeling of newly synthesized proteins and subsequent chase periods. Comparing the level of labeled protein remaining as a function of time to the initial level reveals the protein's half-life. In this method we provide a detailed description of the workflow required for the determination of protein turnover rates on a whole proteome scale in vivo. Our approach starts with the metabolic labeling of whole rodents by restricting all the nitrogen in their diet to exclusively nitrogen-15 in the form of spirulina algae. After near complete organismal labeling with nitrogen-15, the rodents are then switched to a normal nitrogen-14 rich diet for time periods of days to years. Tissues are harvested, the extracts are fractionated, and the proteins are digested to peptides. Peptides are separated by multidimensional liquid chromatography and analyzed by high resolution orbitrap mass spectrometry (MS). The nitrogen-15 containing proteins are then identified and measured by the bioinformatic proteome analysis tools Sequest, DTASelect2, and Census. In this way, our metabolic pulse-chase approach reveals in vivo protein decay rates proteome-wide.

Molecular and Cellular Mechanisms of Axonal Regeneration After Spinal Cord Injury

Following axotomy, a complex temporal and spatial coordination of molecular events enables regeneration of the peripheral nerve. In contrast, multiple intrinsic and extrinsic factors contribute to the general failure of axonal regeneration in the central nervous system. In this review, we examine the current understanding of differences in protein expression and post-translational modifications, activation of signaling networks, and environmental cues that may underlie the divergent regenerative capacity of central and peripheral axons. We also highlight key experimental strategies to enhance axonal regeneration via modulation of intraneuronal signaling networks and the extracellular milieu. Finally, we explore potential applications of proteomics to fill gaps in the current understanding of molecular mechanisms underlying regeneration, and to provide insight into the development of more effective approaches to promote axonal regeneration following injury to the nervous system.

Pulsed Azidohomoalanine Labeling in Mammals (PALM) Detects Changes in Liver-Specific LKB1 Knockout Mice

Quantification of proteomes by mass spectrometry has proven to be useful to study human pathology recapitulated in cellular or animal models of disease. Enriching and quantifying newly synthesized proteins (NSPs) at set time points by mass spectrometry has the potential to identify important early regulatory or expression changes associated with disease states or perturbations. NSP can be enriched from proteomes by employing pulsed introduction of the noncanonical amino acid, azidohomoalanine (AHA). We demonstrate that pulsed introduction of AHA in the feed of mice can label and identify NSP from multiple tissues. Furthermore, we quantitate differences in new protein expression resulting from CRE-LOX initiated knockout of LKB1 in mouse livers. Overall, the PALM strategy allows for the first time in vivo labeling of mouse tissues to differentiate protein synthesis rates at discrete time points.

Preparation of highly and generally enriched mammalian tissues for solid state NMR

An appreciable level of isotope labelling is essential for future NMR structure elucidation of mammalian biomaterials, which are either poorly expressed, or unexpressable, using micro-organisms. We present a detailed protocol for high level (13)C enrichment even in slow turnover murine biomaterials (fur keratin), using a customized diet supplemented with commercial labelled algal hydrolysate and formulated as a gel to minimize wastage, which female mice consumed during pregnancy and lactation. This procedure produced approximately eightfold higher fur keratin labelling in pups, exposed in utero and throughout life to label, than in adults exposed for the same period, showing both the effectiveness, and necessity, of this approach.

Fmr1 deficiency promotes age-dependent alterations in the cortical synaptic proteome

Fragile X syndrome (FXS) is an X-linked neurodevelopmental disorder characterized by severe intellectual disability and other symptoms including autism. Although caused by the silencing of a single gene, Fmr1 (fragile X mental retardation 1), the complexity of FXS pathogenesis is amplified because the encoded protein, FMRP, regulates the activity-dependent translation of numerous mRNAs. Although the mRNAs that associate with FMRP have been extensively studied, little is known regarding the proteins whose expression levels are altered, directly or indirectly, by loss of FMRP during brain development. Here we systematically measured protein expression in neocortical synaptic fractions from Fmr1 knockout (KO) and wild-type (WT) mice at both adolescent and adult stages. Although hundreds of proteins are up-regulated in the absence of FMRP in young mice, this up-regulation is largely diminished in adulthood. Up-regulated proteins included previously unidentified as well as known targets involved in synapse formation and function and brain development and others linked to intellectual disability and autism. Comparison with putative FMRP target mRNAs and autism susceptibility genes revealed substantial overlap, consistent with the idea that the autism endophenotype of FXS is due to a "multiple hit" effect of FMRP loss, particularly within the PSD95 interactome. Through studies of de novo protein synthesis in primary cortical neurons from KO and WT mice, we found that neurons lacking FMRP produce nascent proteins at higher rates, many of which are synaptic proteins and encoded by FMRP target mRNAs. Our results provide a greatly expanded view of protein changes in FXS and identify age-dependent effects of FMRP in shaping the neuronal proteome.

Monitoring host responses to the gut microbiota

The gastrointestinal (GI) ecosystem is increasingly understood to be a fundamental component of health, and has been identified as a new focal point for diagnosing, correcting and preventing countless disorders. Shotgun DNA sequencing has emerged as the dominant technology for determining the genetic and microbial composition of the gut microbiota. This technology has linked microbiota dysbioses to numerous GI diseases including inflammatory bowel disease, obesity and allergy, and to non-GI diseases like autism and depression. The importance of establishing causality in the deterioration of the host-microbiota relationship is well appreciated; however, discovery of candidate molecules and pathways that underlie mechanisms remains a major challenge. Targeted approaches, transcriptional assays, cytokine panels and imaging analyses, applied to animals, have yielded important insight into host responses to the microbiota. However, non-invasive, hypothesis-independent means of measuring host responses in humans are necessary to keep pace with similarly unbiased sequencing efforts that monitor microbes. Mass spectrometry-based proteomics has served this purpose in many other fields, but stool proteins exist in such diversity and dynamic range as to overwhelm conventional proteomics technologies. Focused analysis of host protein secretion into the gut lumen and monitoring proteome-level dynamics in stool provides a tractable route toward non-invasively evaluating dietary, microbial, surgical or pharmacological intervention efficacies. This review is intended to guide GI biologists and clinicians through the methods currently used to elucidate host responses in the gut, with a specific focus on mass spectrometry-based shotgun proteomics applied to the study of host protein dynamics within the GI ecosystem.

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.

Understanding the rules of the road: proteomic approaches to interrogate the blood brain barrier

The blood brain barrier (BBB) is often regarded as a passive barrier that protects brain parenchyma from toxic substances, circulating leukocytes, while allowing the passage of selected molecules. Recently, a combination of molecular profiling techniques have characterized the constituents of the BBB based on in vitro models using isolated endothelial cells and ex vivo models analyzing isolated blood vessels. Characterization of gene expression profiles that are specific to the endothelium of brain blood vessels, and the identification of proteins, cells and multi-cellular structure that comprise the BBB have led to a emerging consensus that the BBB is not, in and of itself, a simple barrier of specialized endothelial cells. Instead, regulation of transcytosis, permeability, and drug translocation into the central nervous system is now viewed as a collection of neurovascular units (NVUs) that, together, give the BBB its unique biological properties. We will review recent technology advancing the understanding of the molecular basis of the BBB with a focus on proteomic approaches.

Analysis of proteome dynamics in mice by isotopic labeling

Recent advances in mass spectrometry and in vivo isotopic labeling have enabled proteome-wide analyses of protein turnover in complex organisms. Here, we describe a protocol for analyzing protein turnover rates in mouse tissues by comprehensive (15)N labeling. The procedure involves the complete isotopic labeling of blue green algae (Spirulina platensis) with (15)N and utilizing it as a source of dietary nitrogen for mice. We outline a detailed protocol for in-house production of (15)N-labeled algae, labeling of mice, and analysis of isotope incorporation kinetics by mass spectrometry. The methodology can be adapted to analyze proteome dynamics in most murine tissues and may be particularly useful in the analysis of proteostatic disruptions in mouse models of disease.

Isobaric labeling-based relative quantification in shotgun proteomics

Mass spectrometry plays a key role in relative quantitative comparisons of proteins in order to understand their functional role in biological systems upon perturbation. In this review, we review studies that examine different aspects of isobaric labeling-based relative quantification for shotgun proteomic analysis. In particular, we focus on different types of isobaric reagents and their reaction chemistry (e.g., amine-, carbonyl-, and sulfhydryl-reactive). Various factors, such as ratio compression, reporter ion dynamic range, and others, cause an underestimation of changes in relative abundance of proteins across samples, undermining the ability of the isobaric labeling approach to be truly quantitative. These factors that affect quantification and the suggested combinations of experimental design and optimal data acquisition methods to increase the precision and accuracy of the measurements will be discussed. Finally, the extended application of isobaric labeling-based approach in hyperplexing strategy, targeted quantification, and phosphopeptide analysis are also examined.

Effect of an anti-depressant on mouse hippocampus protein turnover using MIMS

Although antidepressants have been used in the treatment of affective disorders for over fifty years, the precise mechanism of their action remains unknown. Treatment regimens are based by and large on empirical parameters and characterized by a trial and error scheme. A better understanding of the mechanisms involved in antidepressant drug response is of fundamental importance for the development of new compounds that have a higher success rate and specificity. In order to elucidate the molecular pathways involved in the action of antidepressants, we wish to identify brain areas, cell types, and organelles that are targeted by antidepressant treatment in mice. Multi-isotope Imaging Mass Spectrometry (MIMS) allows a quantitative approach to this analysis, allowing us to delineate antidepressant effect on protein synthesis in the brain at single cell and organelle resolution. In these experiments, we obtained a global analysis of protein turnover in the hippocampus dentate gyrus (DG) and in the Cornu Ammonis (CA) regions, together with a subcellular analysis in the granular cells and others.

Deep and precise quantification of the mouse synaptosomal proteome reveals substantial remodeling during postnatal maturation

During postnatal murine maturation, behavioral patterns emerge and become shaped by experience-dependent adaptations. During the same period, the morphology of dendritic spines, the morphological correlates of excitatory synapses, is known to change, and there is evidence of concurrent alterations of the synaptosomal protein machinery. To obtain comprehensive and quantitative insights in the developmental regulation of the proteome of synapses, we prepared cortical synaptosomal fractions from a total of 16 individual juvenile and adult mouse brains (age 3 or 8 weeks, respectively). We then applied peptide-based iTRAQ labeling (four pools of 4 animals) and high-resolution two-dimensional peptide fractionation (99 SCX fractions and 3 h reversed-phase gradients) using a hybrid CID-HCD acquisition method on a Velos Orbitrap mass spectrometer to identify a comprehensive set of synaptic proteins and to quantify changes in protein expression. We obtained a data set tracking expression levels of 3500 proteins mapping to 3427 NCBI GeneIDs during development with complete quantification data available for 3422 GeneIDs, which, to the best of our knowledge, constitutes the deepest coverage of the synaptosome proteome to date. The inclusion of biological replicates in a single mass spectrometry analysis demonstrated both high reproducibility of our synaptosome preparation method as well as high precision of our quantitative data (correlation coefficient R = 0.87 for the biological replicates). To evaluate the validity of our data, the developmental regulation of eight proteins identified in our analysis was confirmed independently using western blotting. A gene ontology analysis confirmed the synaptosomal nature of a large fraction of identified proteins. Of note, the set of the most strongly regulated proteins revealed candidates involved in neurological processes in health and disease states. This highlights the fact that developmentally regulated proteins can play additional roles in neurological disease processes. All data have been deposited to the ProteomeXchange with identifier PXD000552.

Recent advances in stable isotope labeling based techniques for proteome relative quantification

The large scale relative quantification of all proteins expressed in biological samples under different states is of great importance for discovering proteins with important biological functions, as well as screening disease related biomarkers and drug targets. Therefore, the accurate quantification of proteins at proteome level has become one of the key issues in protein science. Herein, the recent advances in stable isotope labeling based techniques for proteome relative quantification were reviewed, from the aspects of metabolic labeling, chemical labeling and enzyme-catalyzed labeling. Furthermore, the future research direction in this field was prospected.

Brain Proteome Changes Induced by Olfactory Learning in Drosophila

For more than 30 years, the study of learning and memory in Drosophila melanogaster (fruit fly) has used an olfactory learning paradigm and has resulted in the discovery of many genes involved in memory formation. By varying learning programs, the creation of different memory types can be achieved, from short-term memory formation to long-term. Previous studies in the fruit fly used gene mutation methods to identify genes involved in memory formation. Presumably, memory creation involves a combination of genes, pathways, and neural circuits. To examine memory formation at the protein level, a quantitative proteomic analysis was performed using olfactory learning and ¹⁵N-labeled fruit flies. Differences were observed in protein expression and relevant pathways between different learning programs. Our data showed major protein expression changes occurred between short-term memory (STM) and long-lasting memory, and only minor changes were found between long-term memory (LTM) and anesthesia-resistant memory (ARM).

Monitoring protein conformational changes and dynamics using stable-isotope labeling and mass spectrometry

An understanding of the mechanism accompanying functional conformational changes associated with protein activation has important implications for drug design. Here we describe a powerful method, conformational changes and dynamics using stable-isotope labeling and mass spectrometry (CDSiL-MS), which involves chemical labeling by isotope-coded forms of N-ethylmaleimide or succinic anhydride to site-specifically label the side chains of cysteines or lysines, respectively, in native proteins. Subsequent MS analysis allows the quantitative monitoring of reactivity of residues as a function of time, providing a measurement of the labeling kinetics and thereby enabling elucidation of conformational changes of proteins. We demonstrate the utility of this method using a model G protein-coupled receptor, the β2-adrenergic receptor, including experiments that characterize the functional conformational changes associated with activation of distinct signaling pathways induced by different β-adrenoceptor ligands. The procedure requires 5 d, and it can easily be adapted to systems in which soluble and detergent-solubilized membrane protein targets, which undergo function-dependent conformational changes, can be interrogated structurally to allow drug screening.

Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.

Dual mode action of mangiferin in mouse liver under high fat diet

Chronic over-nutrition is a major contributor to the spread of obesity and its related metabolic disorders. Development of therapeutics has been slow compared to the speedy increase in occurrence of these metabolic disorders. We have identified a natural compound, mangiferin (MGF) (a predominant component of the plants of Anemarrhena asphodeloides and Mangifera indica), that can protect against high fat diet (HFD) induced obesity, hyperglycemia, insulin resistance and hyperlipidemia in mice. However, the molecular mechanisms whereby MGF exerts these beneficial effects are unknown. To understand MGF mechanisms of action, we performed unbiased quantitative proteomic analysis of protein profiles in liver of mice fed with HFD utilizing 15N metabolically labeled liver proteins as internal standards. We found that out of 865 quantified proteins 87 of them were significantly differentially regulated by MGF. Among those 87 proteins, 50% of them are involved in two major processes, energy metabolism and biosynthesis of metabolites. Further classification indicated that MGF increased proteins important for mitochondrial biogenesis and oxidative activity including oxoglutarate dehydrogenase E1 (Dhtkd1) and cytochrome c oxidase subunit 6B1 (Cox6b1). Conversely, MGF reduced proteins critical for lipogenesis such as fatty acid stearoyl-CoA desaturase 1 (Scd1) and acetyl-CoA carboxylase 1 (Acac1). These mass spectrometry data were confirmed and validated by western blot assays. Together, data indicate that MGF upregulates proteins pivotal for mitochondrial bioenergetics and downregulates proteins controlling de novo lipogenesis. This novel mode of dual pharmacodynamic actions enables MGF to enhance energy expenditure and inhibit lipogenesis, and thereby correct HFD induced liver steatosis and prevent adiposity. This provides a molecular basis supporting development of MGF or its metabolites into therapeutics to treat metabolic disorders.

Quantitative proteomics in laser capture microdissected sleep nuclei from rat brain

The combination of stable isotope labeling of amino acids in mammals (SILAM) and laser capture microdissection (LCM) for selective proteomic analysis of the targeted tissues holds tremendous potential for refined characterization of proteome changes within complex tissues such as the brain. The authors have applied this approach to measure changes in relative protein abundance in ventral tegmental area (VTA) of the rat brain that correlate to pharmacological perturbations. Enriched ¹³C₆¹⁵N₂-lysine was introduced in vivo via diet. These animals were sacrificed during the middle of the 12-hour light period to extract isotopically “heavy” proteins, which were then used as a reference for extracts from dosed, unlabeled rats. Animals were administered an orexin peptide (Ox-B), an orexin receptor antagonist (ORA), or a mixture of both (Ox-B + ORA). All samples were obtained at same phase of the sleep cycle. Labeled-pair identification and differential quantitation provided protein identification and expression ratio data. Five proteins were found to exhibit decreased relative abundance after administration of an ORA, including α-synuclein and rat myelin basic protein. Conversely, six proteins showed increased relative abundance upon antagonist treatment, including 2’,3’-cyclic nucleotide 3’-phosphodiesterase.

Proteomic analysis of colorectal cancer: discovering novel biomarkers

Colorectal cancer is one of the most common cancers in the Western world. When detected at an early stage, the majority of cancers can be cured with current treatment modalities. However, most cancers present at an intermediate stage. The discovery of sensitive and specific biomarkers has the potential to improve preclinical diagnosis of primary and recurrent colorectal cancer, and holds the promise of prognostic and therapeutic application. Current biomarkers such as carcinoembryonic antigen lack sensitivity and specificity for general population screening. This review aims to highlight the role of current proteomic technologies in the discovery and validation of potential biomarkers with a view to translation to the clinic.

Proteomic approach to aging research

The scope of the current paper is to review existing and potential applications of proteomic analysis to aging research. The focus will lie on the unique opportunities of high-throughput studies for uncovering specific alterations in protein expression, protein complexes or protein modifications caused by biological aging. The result of such studies will outline aging phenotypes and potentially indicate pathways involved in the pathogenesis of age-associated disfunctions. Specific attention is paid to the illustrations of successful applications of proteomic technologies and potential applications of new proteomic concepts to biogerontological studies.

Technologies and Challenges in Proteomic Analysis of Protein S-acylation

Protein S-acylation (also called palmitoylation) is a pervasive post-translational modification that plays critical roles in regulating protein trafficking, localization, stability, activity, and complex formation. The past decade has witnessed tremendous advances in the study of protein S-acylation, largely owing to the development of novel S-acylproteomics technologies. In this review, we summarize current S-acylproteomics approaches, critically review published S-acylproteomics studies, and envision future directions for the burgeoning S-acylproteomics field. Emerging S-acylproteomics technologies promise to shed new light on this distinct post-translational modification and facilitate the discovery of new disease mechanisms, biomarkers, and therapeutic targets.

Proteomic approaches and identification of novel therapeutic targets for alcoholism

Recent studies have shown that gene regulation is far more complex than previously believed and does not completely explain changes at the protein level. Therefore, the direct study of the proteome, considerably different in both complexity and dynamicity to the genome/transcriptome, has provided unique insights to an increasing number of researchers. During the past decade, extraordinary advances in proteomic techniques have changed the way we can analyze the composition, regulation, and function of protein complexes and pathways underlying altered neurobiological conditions. When combined with complementary approaches, these advances provide the contextual information for decoding large data sets into meaningful biologically adaptive processes. Neuroproteomics offers potential breakthroughs in the field of alcohol research by leading to a deeper understanding of how alcohol globally affects protein structure, function, interactions, and networks. The wealth of information gained from these advances can help pinpoint relevant biomarkers for early diagnosis and improved prognosis of alcoholism and identify future pharmacological targets for the treatment of this addiction.

Stable isotope labeling by amino acids in cell culture (SILAC) for quantitative proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Mass spectrometry-based biomarkers in drug development

Advances in mass spectrometry, proteomics, protein bioanalytical approaches, and biochemistry have led to a rapid evolution and expansion in the area of mass spectrometry-based biomarker discovery and development. The last decade has also seen significant progress in establishing accepted definitions, guidelines, and criteria for the analytical validation, acceptance, and qualification of biomarkers. These advances have coincided with a decreased return on investment for pharmaceutical research and development and an increasing need for better early decision making tools. Empowering development teams with tools to measure a therapeutic interventions impact on disease state and progression, measure target engagement, and to confirm predicted pharmacodynamic effects is critical to efficient data-driven decision making. Appropriate implementation of a biomarker or a combination of biomarkers can enhance understanding of a drugs mechanism, facilitate effective translation from the preclinical to clinical space, enable early proof of concept and dose selection, and increase the efficiency of drug development. Here we will provide descriptions of the different classes of biomarkers that have utility in the drug development process as well as review specific, protein-centric, mass spectrometry-based approaches for the discovery of biomarkers and development of targeted assays to measure these markers in a selective and analytically precise manner.

Interrogation of in vivo protein-protein interactions using transgenic mouse models and stable isotope labeling

Methods in mass spectrometry have evolved in recent years, facilitating proteomic analyses that were previously beyond the limits of the technology. Transgenic mouse models, coupled with mass spectrometry proteomics, have served as valuable platform for elucidating the in vivo function of individual genes and proteins. Here we discuss the methods we have recently employed to characterize protein-protein interactions and posttranslational modifications in tagged knock-in mouse models. These methods can be broadly applied to other systems for various applications in both basic and translational science.

Stable isotope labeling in mammals (SILAM)

Analysis of animal models of disease is essential to the understanding of human disease and the identification of potential targets for clinical drugs. Global analysis of proteins by mass spectrometry is an important tool for these studies. Stable isotope labeling in mammals (SILAM) was developed to quantitate the proteomes of rodents using mass spectrometry. The crux of SILAM analysis is the complete labeling of all proteins in a rodent with heavy nitrogen ((15)N). These (15)N tissues are then employed as an internal standard for quantitative proteomics analysis using a high-resolution and mass-accuracy mass spectrometer.

The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.

The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.

A perspective on proteomics in cell biology

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Proteomic strategies facilitate system-wide analyses of protein complexes.

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Isotope labelling allows quantitative measurement of protein properties, not only their identification.

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There is a major need to organise effective community sharing of the proteomic data mountain.

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The integration of proteomic data with other online data repositories must be improved.

During the past 15 years mass spectrometry (MS)-based analyses have become established as the method of choice for direct protein identification and measurement. Owing to the remarkable improvements in the sensitivity and resolution of MS instruments, this technology has revolutionised the opportunities available for the system-wide characterisation of proteins, with wide applications across virtually the whole of cell biology. In this article we provide a perspective on the current state of the art and discuss how the future of cell biology research may benefit from further developments and applications in the field of MS and proteomics, highlighting the major challenges ahead for the community in organising the effective sharing and integration of the resulting data mountain.

Tracking brain palmitoylation change: predominance of glial change in a mouse model of Huntington's disease

Protein palmitoylation, a reversible lipid modification of proteins, is widely used in the nervous system, with dysregulated palmitoylation being implicated in a variety of neurological disorders. Described below is ABE/SILAM, a proteomic strategy that couples acyl-biotinyl exchange (ABE) purification of palmitoyl-proteins to whole animal stable isotope labeling (SILAM) to provide an accurate tracking of palmitoylation change within rodent disease models. As a first application, we have used ABE/SILAM to look at Huntington's disease (HD), profiling palmitoylation change in two HD-relevant mouse mutants: the transgenic HD model mouse YAC128 and the hypomorphic Hip14-gt mouse, which has sharply reduced expression for HIP14 (Zdhhc17), a palmitoyl-transferase implicated in the HD disease process. Rather than mapping to the degenerating neurons themselves, the biggest disease changes instead map to astrocytes and oligodendrocytes (i.e., the supporting glial cells).

Comparative and Quantitative Global Proteomics Approaches: An Overview

Proteomics became a key tool for the study of biological systems. The comparison between two different physiological states allows unravelling the cellular and molecular mechanisms involved in a biological process. Proteomics can confirm the presence of proteins suggested by their mRNA content and provides a direct measure of the quantity present in a cell. Global and targeted proteomics strategies can be applied. Targeted proteomics strategies limit the number of features that will be monitored and then optimise the methods to obtain the highest sensitivity and throughput for a huge amount of samples. The advantage of global proteomics strategies is that no hypothesis is required, other than a measurable difference in one or more protein species between the samples. Global proteomics methods attempt to separate quantify and identify all the proteins from a given sample. This review highlights only the different techniques of separation and quantification of proteins and peptides, in view of a comparative and quantitative global proteomics analysis. The in-gel and off-gel quantification of proteins will be discussed as well as the corresponding mass spectrometry technology. The overview is focused on the widespread techniques while keeping in mind that each approach is modular and often recovers the other.

Large precursor tolerance database search - a simple approach for estimation of the amount of spectra with precursor mass shifts in proteomic data

Mass measurement and precursor mass assignment are independent processes in proteomic data acquisition. Due to misassignments to C-13 peak, or for other reasons, extensive precursor mass shifts (i.e., deviations of the measured from calculated precursor neutral masses) in LC-MS/MS data obtained with the high-accuracy LTQ-Orbitrap mass spectrometers have been reported in previous studies. Although computational methods for post-acquisition reassignment to monoisotopic mass have been developed to curate the MS/MS spectra prior to database search, a simpler method for estimating the fraction of spectra with precursor mass shift so as to determine whether the data require curation remains desirable. Here, we provide the evidence that an easy approach, which applies a large precursor tolerance (2.1Da or higher) in SEQUEST search against a forward and decoy protein sequence database and then filters the data with PeptideProphet peptide identification probability (p≥0.9), could detect most of the MS/MS spectra containing inaccurate precursor masses. Furthermore, through the implementation of artificial mass shifts on 4000 randomly selected MS/MS spectra, which originally had accurate precursor mass assigned by the mass spectrometers, we demonstrated that the accuracy of the precursor mass has almost negligible influence on the efficacy and fidelity of peptide identification.

BIOLOGICAL SIGNIFICANCE

Integral precursor mass shift is a known problem and thus proteomic data should be handled and analyzed properly to avoid losing important protein identification and/or quantification information. A quick and easy approach for estimating the number of MS/MS spectra with inaccurate precursor mass assignments would be helpful for evaluating the performance of the instrument, determining whether the data requires curation prior to database search or should be searched with specific search parameter(s). Here we demonstrated most of the MS/MS spectra with inaccurate mass assignments (integral or non-integral changes) that could be easily identified by database search with large precursor tolerance windows.

Candidate serum biomarkers for early intestinal cancer using 15N metabolic labeling and quantitative proteomics in the ApcMin/+ mouse

Current screening procedures for colorectal cancer are imperfect and highly invasive and result in increased mortality rates due to low compliance. The goal of the experiments reported herein is to identify potential blood-based biomarkers indicative of early stage intestinal cancers using the ApcMin/+ mouse model of intestinal cancer as an experimental system. Serum proteins from tumor-bearing ApcMin/+ mice were quantitatively compared to tumor-free Apc+/+ wild-type mice via in anima metabolic labeling with 14N/15N-labeled Spirulina algae and an LTQ Orbitrap mass spectrometer. Out of 1116 total serum proteins quantified, this study identified 40 that were differentially expressed and correlated with the increase in intestinal neoplasms. A subset of these differentially expressed proteins underwent a secondary quantitative screen using selected reaction monitoring-mass spectrometry with stable isotope-labeled peptides. Using both quantitative techniques, we identified MGAM and COL1A1 as downregulated and ITIH3 and F5 as upregulated in serum. All but COL1A1 were similarly differentially expressed in the mRNA of neoplastic colonic tissues of ApcMin/+ mice compared to normal wild-type tissue. These differentially expressed proteins identified in the ApcMin/+ mouse model have provided a set of candidate biomarkers for future validation screens in humans.

Dynamic regulation of hepatic lipid droplet properties by diet

Cytoplasmic lipid droplets (CLD) are organelle-like structures that function in neutral lipid storage, transport and metabolism through the actions of specific surface-associated proteins. Although diet and metabolism influence hepatic CLD levels, how they affect CLD protein composition is largely unknown. We used non-biased, shotgun, proteomics in combination with metabolic analysis, quantitative immunoblotting, electron microscopy and confocal imaging to define the effects of low- and high-fat diets on CLD properties in fasted-refed mice. We found that the hepatic CLD proteome is distinct from that of CLD from other mammalian tissues, containing enzymes from multiple metabolic pathways. The hepatic CLD proteome is also differentially affected by dietary fat content and hepatic metabolic status. High fat feeding markedly increased the CLD surface density of perilipin-2, a critical regulator of hepatic neutral lipid storage, whereas it reduced CLD levels of betaine-homocysteine S-methyltransferase, an enzyme regulator of homocysteine levels linked to fatty liver disease and hepatocellular carcinoma. Collectively our data demonstrate that the hepatic CLD proteome is enriched in metabolic enzymes, and that it is qualitatively and quantitatively regulated by diet and metabolism. These findings implicate CLD in the regulation of hepatic metabolic processes, and suggest that their properties undergo reorganization in response to hepatic metabolic demands.

Recent advances in quantitative neuroproteomics

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

Profiling of diet-induced neuropeptide changes in rat brain by quantitative mass spectrometry

Neuropeptides are intercellular signal transmitters that play key roles in modulation of many behavioral and physiological processes. Neuropeptide signaling in several nuclei in the hypothalamus contributes to the control of food intake. Additionally, food intake regulation involves neuropeptide signaling in the reward circuitry in the striatum. Here, we analyze neuropeptides extracted from hypothalamus and striatum from rats in four differentially treated dietary groups including a high-fat/high-sucrose diet, mimicking diet-induced obesity. We employ high-resolution tandem mass spectrometry using higher-energy collision dissociation and electron transfer dissociation fragmentation for sensitive identification of more than 1700 unique endogenous peptides, including virtually all key neuropeptides known to be involved in food intake regulation. Label-free quantification of differential neuropeptide expression revealed comparable upregulation of orexigenic and anorexigenic neuropeptides in rats that were fed on a high-fat/high-sucrose diet.

Stable isotope labeling of mammals (SILAM) for in vivo quantitative proteomic analysis

Metabolic labeling of rodent proteins with ¹⁵N, a heavy stable isotope of nitrogen, provides an efficient way for relative quantitation of differentially expressed proteins. Here we describe a protocol for metabolic labeling of rats with an ¹⁵N-enriched spirulina diet. As a case study, we also demonstrate the application of ¹⁵N-enriched tissue as a common internal standard in quantitative analysis of differentially expressed proteins in neurodevelopment in rats at two different time points, postnatal day 1 and 45. We briefly discuss the bioinformatics tools, ProLucid and Census, which can easily be used in a sequential manner to identify and quantitate relative protein levels on a proteomic scale.