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

Carotenoids in Health as Studied by Omics-Related Endpoints

Carotenoids have been associated with risk reduction for several chronic diseases, including the association of their dietary intake/circulating levels with reduced incidence of obesity, type 2 diabetes, certain types of cancer, and even lower total mortality. In addition to some carotenoids constituting vitamin A precursors, they are implicated in potential antioxidant effects and pathways related to inflammation and oxidative stress, including transcription factors such as nuclear factor κB and nuclear factor erythroid 2-related factor 2. Carotenoids and metabolites may also interact with nuclear receptors, mainly retinoic acid receptor/retinoid X receptor and peroxisome proliferator-activated receptors, which play a role in the immune system and cellular differentiation. Therefore, a large number of downstream targets are likely influenced by carotenoids, including but not limited to genes and proteins implicated in oxidative stress and inflammation, antioxidation, and cellular differentiation processes. Furthermore, recent studies also propose an association between carotenoid intake and gut microbiota. While all these endpoints could be individually assessed, a more complete/integrative way to determine a multitude of health-related aspects of carotenoids includes (multi)omics-related techniques, especially transcriptomics, proteomics, lipidomics, and metabolomics, as well as metagenomics, measured in a variety of biospecimens including plasma, urine, stool, white blood cells, or other tissue cellular extracts. In this review, we highlight the use of omics technologies to assess health-related effects of carotenoids in mammalian organisms and models.

Root-Knot-Nematode-Encoded CEPs Increase Nitrogen Assimilation

C-terminally encoded peptides (CEPs) are plant developmental signals that regulate growth and adaptive responses to nitrogen stress conditions. These small signal peptides are common to all vascular plants, and intriguingly have been characterized in some plant parasitic nematodes. Here, we sought to discover the breadth of root-knot nematode (RKN)-encoded CEP-like peptides and define the potential roles of these signals in the plant-nematode interaction, focusing on peptide activity altering plant root phenotypes and nitrogen uptake and assimilation. A comprehensive bioinformatic screen identified 61 CEP-like sequences encoded within the genomes of six root-knot nematode (RKN; Meloidogyne spp.) species. Exogenous application of an RKN CEP-like peptide altered A. thaliana and M. truncatula root phenotypes including reduced lateral root number in M. truncatula and inhibited primary root length in A. thaliana. To define the role of RKN CEP-like peptides, we applied exogenous RKN CEP and demonstrated increases in plant nitrogen uptake through the upregulation of nitrate transporter gene expression in roots and increased 15N/14N in nematode-formed root galls. Further, we also identified enhanced nematode metabolic processes following CEP application. These results support a model of parasite-induced changes in host metabolism and inform endogenous pathways to regulate plant nitrogen assimilation.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

Heavy water metabolic labeling followed by liquid chromatography coupled with mass spectrometry is a powerful high throughput technique for measuring the turnover rates of individual proteins in vivo. The turnover rate is obtained from the exponential decay modeling of the depletion of the monoisotopic relative isotope abundance. We provide theoretical formulas for the time course dynamics of six mass isotopomers and use the formulas to introduce a method that utilizes partial isotope profiles, only two mass isotopomers, to compute protein turnover rate. The use of partial isotope profiles alleviates the interferences from co-eluting contaminants in complex proteome mixtures and improves the accuracy of the estimation of label enrichment. In five different datasets, the technique consistently doubles the number of peptides with high goodness-of-fit characteristics of the turnover rate model. We also introduce a software tool, d2ome+, which automates the protein turnover estimation from partial isotope profiles.

Determining and interpreting protein lifetimes in mammalian tissues

The orchestration of protein production and degradation, and the regulation of protein lifetimes, play a central role in the majority of biological processes. Recent advances in proteomics have enabled the estimation of protein half-lives for thousands of proteins in vivo. What is the utility of these measurements, and how can they be leveraged to interpret the proteome changes occurring during development, aging, and disease? This opinion article summarizes leading technical approaches and highlights their strengths and weaknesses. We also disambiguate frequently used terminology, illustrate recent mechanistic insights, and provide guidance for interpreting and validating protein turnover measurements. Overall, protein lifetimes, coupled to estimates of protein levels, are essential for obtaining a deep understanding of mammalian biology and the basic processes defining life itself.

Efficiency of Protein Renewal Is Limited by Feed Intake and Not by Protein Lifetime in Aging Caenorhabditis elegans

Protein turnover maintains the proteome's functional integrity. Here, protein turnover efficiency over time in wild-type Caenorhabditis elegans was assessed using inverse [¹⁵N]-pulse labeling up to 7 days after the egg-laying phase at 20 °C. Isotopic analysis of some abundant proteins was executed favoring data quality over quantity for mathematical modeling. Surprisingly, isotopic enrichment over time reached an upper limit showing an apparent cessation of protein renewal well before death, with protein fractions inaccessible to turnover ranging from 14 to 83%. For life span modulation, worms were raised at different temperatures after egg laying. Mathematical modeling of isotopic enrichment points either to a slowdown of protein turnover or to an increasing protein fraction resistant to turnover with time. Most notably, the estimated time points of protein turnover cessation from our mathematical model were highly correlated with the observed median life span. Thrashing and pumping rates over time were linearly correlated with isotopic enrichment, therefore linking protein/tracer intake to protein turnover rate and protein life span. If confirmed, life span extension is possible by optimizing protein turnover rate through modulating protein intake in C. elegans and possibly other organisms. While proteome maintenance benefits from a high protein turnover rate, protein turnover is fundamentally energy-intensive, where oxidative stress contributes to damage that it is supposed to repair.

Advances in stable isotope labeling: dynamic labeling for spatial and temporal proteomic analysis

The field of proteomics is continually improving, requiring the development of new quantitative methods. Stable isotope labeling in cell culture (SILAC) is a metabolic labeling technique originating in the early 2000s. By incorporating isotopically labeled amino acids into the media used for cell culture, unlabeled versus labeled cells can be differentiated by the mass spectrometer. Traditional SILAC labeling has been expanded to pulsed applications allowing for a new quantitative dimension of proteomics - temporal analysis. The complete introduction of Heavy SILAC labeling chased with surplus unlabeled medium mimics traditional pulse-chase experiments and allows for the loss of heavy signal to track proteomic changes over time. In a similar fashion, pulsed SILAC (pSILAC) monitors the initial incorporation of a heavy label across a period of time, which allows for the rate of protein label integration to be assessed. These innovative techniques have aided in inspiring numerous SILAC-based temporal and spatial labeling applications, including super SILAC, spike-in SILAC, spatial SILAC, and a revival in label multiplexing. This review reflects upon the evolution of SILAC and the pulsed SILAC application, introduces advances in SILAC labeling, and proposes future perspectives for this novel and exciting field.

Long-lived mitochondrial proteins and why they exist

Intracellular long-lived proteins (LLPs) provide structural support for several highly stable protein complexes and assemblies that play essential roles in ensuring cellular homeostasis and function. Recently, mitochondrial long-lived proteins (mt-LLPs) were discovered within inner mitochondria membranes (IMMs) and cristae invagination in tissues with old postmitotic cells. This observation is at odds with the fact that mitochondria are highly dynamic organelles that are continually remodeled through processes of fission, fusion, biogenesis, and multiple quality control pathways. In this opinion article, we propose that a subset of the mitochondrial proteome persists over long time frames and these mt-LLPs provide key structural support for the lifelong maintenance of mitochondrial structure.

Protein turnover models for LC-MS data of heavy water metabolic labeling

Protein turnover is vital for cellular functioning and is often associated with the pathophysiology of a variety of diseases. Metabolic labeling with heavy water followed by liquid chromatography coupled to mass spectrometry is a powerful tool to study in vivo protein turnover in high throughput and large scale. Heavy water is a cost-effective and easy to use labeling agent. It labels all nonessential amino acids. Due to its toxicity in high concentrations (20% or higher), small enrichments (8% or smaller) of heavy water are used with most organisms. The low concentration results in incomplete labeling of peptides/proteins. Therefore, the data processing is more challenging and requires accurate quantification of labeled and unlabeled forms of a peptide from overlapping mass isotopomer distributions. The work describes the bioinformatics aspects of the analysis of heavy water labeled mass spectral data, available software tools and current challenges and opportunities.

Quantitative Proteomics Using Isobaric Labeling: A Practical Guide

In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in biological samples. Although its multiplexing capacity and flexibility make this a valuable technology for addressing various biological questions, its quantitative accuracy and precision still pose significant challenges to the reliability of its quantification results. Here, we give a detailed overview of the different kinds of isobaric mass tags and the advantages and disadvantages of the isobaric labeling method. We also discuss which precautions should be taken at each step of the isobaric labeling workflow, to obtain reliable quantification results in large-scale quantitative proteomics experiments. In the last section, we discuss the broad applications of the isobaric labeling technology in biological and clinical studies, with an emphasis on thermal proteome profiling and proteogenomics.

Using stable isotope labeling to advance our understanding of Alzheimer's disease etiology and pathology

Stable isotope labeling with mass spectrometry (MS)-based proteomic analysis has become a powerful strategy to assess protein steady-state levels, protein turnover, and protein localization. Applying these analyses platforms to neurodegenerative disorders may uncover new aspects of the etiology of these devastating diseases. Recently, stable isotopes-MS has been used to investigate early pathological mechanisms of Alzheimer's disease (AD) with mouse models of AD-like pathology. In this review, we summarize these stable isotope-MS experimental designs and the recent application in the context of AD pathology. We also describe our current efforts aimed at using nuclear magnetic resonance (NMR) analysis of stable isotope-labeled amyloid fibrils from AD mouse model brains. Collectively, these methodologies offer new opportunities to study proteome changes in AD and other neurodegenerative diseases by elucidating mechanisms to target for treatment and prevention.

Complement and Coagulation Cascades are Potentially Involved in Dopaminergic Neurodegeneration in α-Synuclein-Based Mouse Models of Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder that results in motor dysfunction and, eventually, cognitive impairment. α-Synuclein protein is known as a central protein to the pathophysiology of PD, but the underlying pathological mechanism still remains to be elucidated. In an effort to understand how α-synuclein underlies the pathology of PD, various PD mouse models with α-synuclein overexpression have been developed. However, systemic analysis of the brain proteome of those mouse models is lacking. In this study, we established two mouse models of PD by injecting α-synuclein preformed fibrils (PFF) or by inducing overexpression of human A53T α-synuclein to investigate common pathways in the two different types of the PD mouse models. For more accurate quantification of mouse brain proteome, the proteins were quantified using the method of stable isotope labeling with amino acids in mammals . We identified a total of 8355 proteins from the two mouse models; ∼6800 and ∼7200 proteins from α-synuclein PFF-injected mice and human A53T α-synuclein transgenic mice, respectively. Through pathway analysis of the differentially expressed proteins common to both PD mouse models, it was discovered that the complement and coagulation cascade pathways were enriched in the PD mice compared to control animals. Notably, a validation study demonstrated that complement component 3 (C3)-positive astrocytes were increased in the ventral midbrain of the intrastriatal α-synuclein PFF-injected mice and C3 secreted from astrocytes could induce the degeneration of dopaminergic neurons. This is the first study that highlights the significance of the complement and coagulation pathways in the pathogenesis of PD through proteome analyses with two sophisticated mouse models of PD.

Using Heavy Mass Isotopomers for Protein Turnover in Heavy Water Metabolic Labeling

Metabolic labeling followed by LC-MS-based proteomics is a powerful tool to study proteome dynamics in high-throughput experiments both in vivo and in vitro. High mass resolution and accuracy allow differentiation in isotope profiles and the quantification of partially labeled peptide species. Metabolic labeling duration introduces a time domain in which the gradual incorporation of labeled isotopes is recorded. Different stable isotopes are used for labeling. Labeling with heavy water has advantages because it is cost-effective and easy to use. The protein degradation rate constant has been modeled using exponential decay models for the relative abundances of mass isotopomers. The recently developed closed-form equations were applied to study the analytic behavior of the heavy mass isotopomers in the time domain of metabolic labeling. The predictions from the closed-form equations are compared with the practices that have been used to extract degradation rate constants from the time-course profiles of heavy mass isotopomers. It is shown that all mass isotopomers, except for the monoisotope, require data transformations to obtain the exponential depletion, which serves as a basis for the rate constant model. Heavy mass isotopomers may be preferable choices for modeling high-mass peptides or peptides with a high number of labeling sites. The results are also applicable to stable isotope labeling with other atom-based labeling agents.

Using protein turnover to expand the applications of transcriptomics

RNA expression and protein abundance are often at odds when measured in parallel, raising questions about the functional implications of transcriptomics data. Here, we present the concept of persistence, which attempts to address this challenge by combining protein half-life data with RNA expression into a single metric that approximates protein abundance. The longer a protein's half-life, the more influence it can have on its surroundings. This data offers a valuable opportunity to gain deeper insight into the functional meaning of transcriptome changes. We demonstrate the application of persistence using schizophrenia (SCZ) datasets, where it greatly improved our ability to predict protein abundance from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight offered by transcriptomics data, and extended application of this concept could advance numerous research fields.

Quantitative Mass Spectrometry-Based Proteomics: An Overview

In recent decades, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review actual strategies and problems of the methods for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

System-wide molecular dynamics of endothelial dysfunction in Gram-negative sepsis

Background

Inflammation affecting whole organism vascular networks plays a central role in the progression and establishment of several human diseases, including Gram-negative sepsis. Although the molecular mechanisms that control inflammation of specific vascular beds have been partially defined, knowledge lacks on the impact of these on the molecular dynamics of whole organism vascular beds. In this study, we have generated an in vivo model by coupling administration of lipopolysaccharide with stable isotope labeling in mammals to mimic vascular beds inflammation in Gram-negative sepsis and to evaluate its effects on the proteome molecular dynamics. Proteome molecular dynamics of individual vascular layers (glycocalyx (GC), endothelial cells (EC), and smooth muscle cells (SMC)) were then evaluated by coupling differential systemic decellularization in vivo with unbiased systems biology proteomics.

Results

Our data confirmed the presence of sepsis-induced disruption of the glycocalyx, and we show for the first time the downregulation of essential molecular maintenance processes in endothelial cells affecting this apical vascular coating. Similarly, a novel catabolic phenotype was identified in the newly synthesized EC proteomes that involved the impairment of protein synthesis, which affected multiple cellular mechanisms, including oxidative stress, the immune system, and exacerbated EC-specific protein turnover. In addition, several endogenous molecular protective mechanisms involving the synthesis of novel antithrombotic and anti-inflammatory proteins were also identified as active in EC. The molecular dynamics of smooth muscle cells in whole organism vascular beds revealed similar patterns of impairment as those identified in EC, although this was observed to a lesser extent. Furthermore, the dynamics of protein posttranslational modifications showed disease-specific phosphorylation sites in the EC proteomes.

Conclusions

Together, the novel findings reported here provide a broader picture of the molecular dynamics that take place in whole organism vascular beds in Gram-negative sepsis inflammation. Similarly, the obtained data can pave the way for future therapeutic strategies aimed at intervening in specific protein synthesis mechanisms of the vascular unit during acute inflammatory processes.

Quantitative In Vivo Proteomics of Metformin Response in Liver Reveals AMPK-Dependent and -Independent Signaling Networks

Metformin is the front-line treatment for type 2 diabetes worldwide. It acts via effects on glucose and lipid metabolism in metabolic tissues, leading to enhanced insulin sensitivity. Despite significant effort, the molecular basis for metformin response remains poorly understood, with a limited number of specific biochemical pathways studied to date. To broaden our understanding of hepatic metformin response, we combine phospho-protein enrichment in tissue from genetically engineered mice with a quantitative proteomics platform to enable the discovery and quantification of basophilic kinase substrates in vivo. We define proteins whose binding to 14-3-3 are acutely regulated by metformin treatment and/or loss of the serine/threonine kinase, LKB1. Inducible binding of 250 proteins following metformin treatment is observed, 44% of which proteins bind in a manner requiring LKB1. Beyond AMPK, metformin activates protein kinase D and MAPKAPK2 in an LKB1-independent manner, revealing additional kinases that may mediate aspects of metformin response. Deeper analysis uncovered substrates of AMPK in endocytosis and calcium homeostasis.

Mass Spectrometry Techniques: Principles and Practices for Quantitative Proteomics

In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable of quantitatively comparing many thousands of proteins obtained from cells and organisms.

The Journey Is the Reward, a Taoist Proverb: John B. Fenn Award for Distinguished Contribution in Mass Spectrometry Lecture

This account provided by John Yates describes his incredible path as a scientist, emphasizing key decisions along the way that shaped his career and led to his landmark contributions to the field of mass spectrometry. Although perhaps best known is the development of the SEQUEST algorithm for automated interpretation of tandem mass spectra of peptides, John's achievements have spanned the field of proteomics and had major impact on the ability to address and solve significant biological problems.

Phosphoproteomics Profiling to Identify Altered Signaling Pathways and Kinase-Targeted Cancer Therapies

Phosphorylation is one of the most extensively studied posttranslational modifications (PTM), which regulates cellular functions like cell growth, differentiation, apoptosis, and cell signaling. Kinase families cover a wide number of oncoproteins and are strongly associated with cancer. Identification of driver kinases is an intense area of cancer research. Thus, kinases serve as the potential target to improve the efficacy of targeted therapies. Mass spectrometry-based phosphoproteomic approach has paved the way to the identification of a large number of altered phosphorylation events in proteins and signaling cascades that may lead to oncogenic processes in a cell. Alterations in signaling pathways result in the activation of oncogenic processes predominantly regulated by kinases and phosphatases. Therefore, drugs such as kinase inhibitors, which target dysregulated pathways, represent a promising area for cancer therapy.

Absolute Quantitation of Oxidizable Peptides by Coulometric Mass Spectrometry

Quantitation methods for peptides using mass spectrometry have advanced rapidly. These methods rely on using standard and/or isotope-labeled peptides, which might be difficult or expensive to synthesize. To tackle this challenge, we present a new approach for absolute quantitation without the use of standards or calibration curves based on coulometry combined with mass spectrometry (MS). In this approach, which we call coulometric mass spectrometry (CMS), the mass spectrum of a target peptide containing one or more tyrosine residues is recorded before and after undergoing electrochemical oxidation. We record the total integrated oxidation current from the electrochemical measurement, which according to the Faraday's Law of coulometry, provides the number of moles of oxidized peptide. The ion intensity ratio of the target peptide before and after oxidation provides an excellent estimate of the fraction of the peptide that has been oxidized, from which the total amount of peptide is calculated. The striking strength of CMS is that it needs no standard peptide, but CMS does require the peptide to contain a known number of oxidizable groups. To illustrate the power of this method, we analyzed various tyrosine-containing peptides such as GGYR, DRVY, oxytocin, [Arg⁸]-vasotocin and angiotensinogen 1-14 with a quantification error ranging from - 7.5 to + 2.4%. This approach is also applicable to quantifying phosphopeptides and could be useful in proteomics research.

A New Quantification Method Using Electrochemical Mass Spectrometry

Mass spectrometry-based quantification method has advanced rapidly. In general, the methods for accurate quantification rely on the use of authentic target compounds or isotope-labeled compounds as standards, which might be not available or difficult to synthesize. To tackle this grand challenge, this paper presents a novel approach, based on electrochemistry (EC) combined with mass spectrometry (MS). In this approach, a target compound is allowed to undergo electrochemical oxidation and then subject to MS analysis. The oxidation current recorded from electrochemistry (EC) measurement provides information about the amount of the oxidized analyte, based on the Faraday's Law. On the other hand, the oxidation reaction yield can be determined from the analyte MS signal changes upon electrolysis. Therefore, the total amount of analyte can be determined. In combination with liquid chromatography (LC), the method can be applicable to mixture analysis. The striking strength of such a method for quantitation is that neither standard compound nor calibration curve is required. Various analyte molecules such as dopamine, norepinephrine, and rutin as well as peptide glutathione in low quantity were successfully quantified using our method with the quantification error ranging from - 2.6 to + 4.6%. Analyte in a complicated matrix (e.g., uric acid in urine) was also accurately measured. Graphical Abstract.

Trends in the Design of New Isobaric Labeling Reagents for Quantitative Proteomics

Modern mass spectrometry is one of the most frequently used methods of quantitative proteomics, enabling determination of the amount of peptides in a sample. Although mass spectrometry is not inherently a quantitative method due to differences in the ionization efficiency of various analytes, the application of isotope-coded labeling allows relative quantification of proteins and proteins. Over the past decade, a new method for derivatization of tryptic peptides using isobaric labels has been proposed. The labels consist of reporter and balanced groups. They have the same molecular weights and chemical properties, but differ in the distribution of stable heavy isotopes. These tags are designed in such a way that during high energy collision induced dissociation (CID) by tandem mass spectrometry, the isobaric tag is fragmented in the specific linker region, yielding reporter ions with different masses. The mass shifts among the reporter groups are compensated by the balancing groups so that the overall mass is the same for all forms of the reagent. Samples of peptides are labeled with the isobaric mass tags in parallel and combined for analysis. Quantification of individual peptides is achieved by comparing the intensity of reporter ions in the tandem mass (MS/MS) spectra. Isobaric markers have found a wide range of potential applications in proteomics. However, the currently available isobaric labeling reagents have some drawbacks, such as high cost of production, insufficient selectivity of the derivatization, and relatively limited enhancement of sensitivity of the analysis. Therefore, efforts have been devoted to the development of new isobaric markers with increased usability. The search for new isobaric markers is focused on developing a more selective method of introducing a tag into a peptide molecule, increasing the multiplexicity of markers, lowering the cost of synthesis, and increasing the sensitivity of measurement by using ionization tags containing quaternary ammonium salts. Here, the trends in the design of new isobaric labeling reagents for quantitative proteomics isobaric derivatization strategies in proteomics are reviewed, with a particular emphasis on isobaric ionization tags. The presented review focused on different types of isobaric reagents used in quantitative proteomics, their chemistry, and advantages offer by their application.

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 increases 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.

A Guide to Mass Spectrometry-Based Quantitative Proteomics

Proteomics has become an attractive science in the postgenomic era, given its capacity to identify up to thousands of molecules in a single, complex sample and quantify them in an absolute and/or relative manner. The use of these techniques enables understanding of cellular and molecular mechanisms of diseases and other biological conditions, as well as identification and screening of protein biomarkers. Here we provide a straightforward, up-to-date compilation and comparison of the main quantitation techniques used in comparative proteomics such as in vitro and in vivo stable isotope labeling and label-free techniques. Additionally, this chapter includes common methods for data acquisition in proteomics and some appropriate methods for data processing. This compilation can serve as a reference for scientists who are new to, or already familiar with, quantitative proteomics.

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.

Induction of the Immunoproteasome Subunit Lmp7 Links Proteostasis and Immunity in α-Synuclein Aggregation Disorders

Accumulation of aggregated α-synuclein into Lewy bodies is thought to contribute to the onset and progression of dopaminergic neuron degeneration in Parkinson's disease (PD) and related disorders. Although protein aggregation is associated with perturbation of proteostasis, how α-synuclein aggregation affects the brain proteome and signaling remains uncertain. In a mouse model of α-synuclein aggregation, 6% of 6215 proteins and 1.6% of 8183 phosphopeptides changed in abundance, indicating conservation of proteostasis and phosphorylation signaling. The proteomic analysis confirmed changes in abundance of proteins that regulate dopamine synthesis and transport, synaptic activity and integrity, and unearthed changes in mRNA binding, processing and protein translation. Phosphorylation signaling changes centered on axonal and synaptic cytoskeletal organization and structural integrity. Proteostatic responses included a significant increase in the levels of Lmp7, a component of the immunoproteasome. Increased Lmp7 levels and activity were also quantified in postmortem human brains with PD and dementia with Lewy bodies. Functionally, the immunoproteasome degrades α-synuclein aggregates and generates potentially antigenic peptides. Expression and activity of the immunoproteasome may represent testable targets to induce adaptive responses that maintain proteome integrity and modulate immune responses in protein aggregation disorders.

Quantitative Comparison of Proteomes Using SILAC

Stable isotope labeling by amino acids in cell culture (SILAC) has become very popular as a quantitative proteomic method since it was firstly introduced by Matthias Mann's group in 2002. It is a metabolic labeling strategy in which isotope-labeled amino acids are metabolically incorporated in vivo into proteins during translation. After natural (light) or heavy amino acid incorporation, differentially labeled samples are mixed immediately after cell lysis and before any further processing, which minimizes quantitative errors caused by handling different samples in parallel. In this unit, we describe protocols for basic duplex SILAC, triplex SILAC for use in nondividing cells such as neurons, and for measuring amounts of newly synthesized proteins. © 2018 by John Wiley & Sons, Inc.

Selective permeability of mouse blood-aqueous barrier as determined by 15N-heavy isotope tracing and mass spectrometry

The blood-aqueous barrier plays a key role in regulating aqueous humor homeostasis by selectively restricting passage of proteins into the eye. The kinetics of aqueous flow are traditionally measured using artificial markers; however, these marker molecules do not address the barrier's selective permeability to plasma proteins. Here we applied stable isotope labeling of all serum proteins with nitrogen-15 (¹⁵N) atoms. Following systemic injection of this "heavy" serum in mice, the ¹⁵N-to-endogenous nitrogen-14 (¹⁴N) ratio of each protein in aqueous was measured by mass spectrometry. By monitoring the kinetic changes in these ratios, we determined the permeability profiles of hundreds of serum proteins. Meanwhile, we subjected one of the eyes to neoangiogenic wound healing by inflicting injury to the corneal limbus and compared the ¹⁵N proteomes between the normal eyes and the recovering eyes at 2 weeks after injury. In the injured eye, we detected markedly enhanced permeability to inhibitory complement regulator proteins, such as Cfh, Cfhr, Cfb, Cfi, Cfd, and Vtn. Many of the proteins in this group are implicated in age-related macular degeneration associated with leakage of the blood-retinal barrier due to inflammation. To rule out the possibility that the observed leakage was due simply to physical damage of the blood vessels, we separately created a neovascularization model using an alkali burn of the avascular cornea. In this latter model, elevated levels of Cfh and Cfb were evident. These findings suggest that ocular neovascularization is associated with enhanced permeability to serum complement regulators.

EpiProfile 2.0: A Computational Platform for Processing Epi-Proteomics Mass Spectrometry Data

Epigenetics has become a fundamental scientific discipline with various implications for biology and medicine. Epigenetic marks, mostly DNA methylation and histone post-translational modifications (PTMs), play important roles in chromatin structure and function. Accurate quantification of these marks is an ongoing challenge due to the variety of modifications and their wide dynamic range of abundance. Here we present EpiProfile 2.0, an extended version of our 2015 software (v1.0), for accurate quantification of histone peptides based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. EpiProfile 2.0 is now optimized for data-independent acquisition through the use of precursor and fragment extracted ion chromatography to accurately determine the chromatographic profile and to discriminate isobaric forms of peptides. The software uses an intelligent retention time prediction trained on the analyzed samples to enable accurate peak detection. EpiProfile 2.0 supports label-free and isotopic labeling, different organisms, known sequence mutations in diseases, different derivatization strategies, and unusual PTMs (such as acyl-derived modifications). In summary, EpiProfile 2.0 is a universal and accurate platform for the quantification of histone marks via LC-MS/MS. Being the first software of its kind, we anticipate that EpiProfile 2.0 will play a fundamental role in epigenetic studies relevant to biology and translational medicine. EpiProfile is freely available at https://github.com/zfyuan/EpiProfile2.0_Family .

Identification of long-lived synaptic proteins by proteomic analysis of synaptosome protein turnover

Memory formation is believed to result from changes in synapse strength and structure. While memories may persist for the lifetime of an organism, the proteins and lipids that make up synapses undergo constant turnover with lifetimes from minutes to days. The molecular basis for memory maintenance may rely on a subset of long-lived proteins (LLPs). While it is known that LLPs exist, whether such proteins are present at synapses is unknown. We performed an unbiased screen using metabolic pulse-chase labeling in vivo in mice and in vitro in cultured neurons combined with quantitative proteomics. We identified synaptic LLPs with half-lives of several months or longer. Proteins in synaptic fractions generally exhibited longer lifetimes than proteins in cytosolic fractions. Protein turnover was sensitive to pharmacological manipulations of activity in neuronal cultures or in mice exposed to an enriched environment. We show that synapses contain LLPs that may underlie stabile long-lasting changes in synaptic structure and function.

Increased Degradation Rates in the Components of the Mitochondrial Oxidative Phosphorylation Chain in the Cerebellum of Old Mice

Brain structures differ in the magnitude of age-related neuron loss with the cerebellum being more affected. An underlying cause could be an age-related decline in mitochondrial bioenergetics. Successful aging of mitochondria reflects a balanced turnover of proteins involved in mitochondrial biogenesis and mitophagy. Thus, an imbalance in mitochondrial turnover can contribute to the diminution of cellular function seen during aging. Mitochondrial biogenesis and mitophagy are mediated by a set of proteins including MFN1, MFN2, OPA1, DRP1, FIS1 as well as DMN1l and DNM1, all of which are required for mitochondrial fission. Using N15 labeling, we report that the turnover rates for DMN1l and FIS1 go in opposite directions in the cerebellum of 22-month-old C57BL6j mice as compared to 3-month-old mice. Previous studies have reported decreased turnover rates for the mitochondrial respiratory complexes of aged rodents. In contrast, we found increased turnover rates for mitochondrial proteins of the oxidative phosphorylation chain in the aged mice as compared to young mice. Furthermore, the turnover rate of the components that are most affected by aging –complex III components (ubiquinol cytochrome C oxidoreductase) and complex IV components (cytochrome C oxidase)– was significantly increased in the senescent cerebellum. However, the turnover rates of proteins involved in mitophagy (i.e., the proteasomal and lysosomal degradation of damaged mitochondria) were not significantly altered with age. Overall, our results suggest that an age-related imbalance in the turnover rates of proteins involved in mitochondrial biogenesis and mitophagy (DMN1l, FIS1) in conjunction with an age-related imbalance in the turnover rates of proteins of the complexes III and IV of the electron transfer chain, might impair cerebellar mitochondrial bioenergetics in old mice.

Poisson Model To Generate Isotope Distribution for Biomolecules

We introduce a simplified computational algorithm for computing isotope distributions (relative abundances and masses) of biomolecules. The algorithm is based on Poisson approximation to binomial and multinomial distributions. It leads to a small number of arithmetic operations to compute isotope distributions of molecules. The approach uses three embedded loops to compute the isotope distributions, as compared with the eight embedded loops in exact calculations. The speed improvement is about 3-fold compared to the fast Fourier transformation-based isotope calculations, often termed as ultrafast isotope calculation. The approach naturally incorporates the determination of the masses of each molecular isotopomer. It is applicable to high mass accuracy and resolution mass spectrometry data. The application to tryptic peptides in a UniProt protein database revealed that the mass accuracy of the computed isotopomers is better than 1 ppm. Even better mass accuracy (below 1 ppm) is achievable when the method is paired with the exact calculations, which we term a hybrid approach. The algorithms have been implemented in a freely available C/C++ code.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Historical and contemporary stable isotope tracer approaches to studying mammalian protein metabolism

Over a century ago, Frederick Soddy provided the first evidence for the existence of isotopes; elements that occupy the same position in the periodic table are essentially chemically identical but differ in mass due to a different number of neutrons within the atomic nucleus. Allied to the discovery of isotopes was the development of some of the first forms of mass spectrometers, driven forward by the Nobel laureates JJ Thomson and FW Aston, enabling the accurate separation, identification, and quantification of the relative abundance of these isotopes. As a result, within a few years, the number of known isotopes both stable and radioactive had greatly increased and there are now over 300 stable or radioisotopes presently known. Unknown at the time, however, was the potential utility of these isotopes within biological disciplines, it was soon discovered that these stable isotopes, particularly those of carbon (13 C), nitrogen (15 N), oxygen (18 O), and hydrogen (2 H) could be chemically introduced into organic compounds, such as fatty acids, amino acids, and sugars, and used to "trace" the metabolic fate of these compounds within biological systems. From this important breakthrough, the age of the isotope tracer was born. Over the following 80 yrs, stable isotopes would become a vital tool in not only the biological sciences, but also areas as diverse as forensics, geology, and art. This progress has been almost exclusively driven through the development of new and innovative mass spectrometry equipment from IRMS to GC-MS to LC-MS, which has allowed for the accurate quantitation of isotopic abundance within samples of complex matrices. This historical review details the development of stable isotope tracers as metabolic tools, with particular reference to their use in monitoring protein metabolism, highlighting the unique array of tools that are now available for the investigation of protein metabolism in vivo at a whole body down to a single protein level. Importantly, it will detail how this development has been closely aligned to the technological development within the area of mass spectrometry. Without the dedicated development provided by these mass spectrometrists over the past century, the use of stable isotope tracers within the field of protein metabolism would not be as widely applied as it is today, this relationship will no doubt continue to flourish in the future and stable isotope tracers will maintain their importance as a tool within the biological sciences for many years to come. © 2016 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc. Mass Spec Rev.

Amyloid Accumulation Drives Proteome-wide Alterations in Mouse Models of Alzheimer's Disease-like Pathology

Amyloid beta (Aβ) peptides impair multiple cellular pathways and play a causative role in Alzheimer's disease (AD) pathology, but how the brain proteome is remodeled by this process is unknown. To identify protein networks associated with AD-like pathology, we performed global quantitative proteomic analysis in three mouse models at young and old ages. Our analysis revealed a robust increase in Apolipoprotein E (ApoE) levels in nearly all brain regions with increased Aβ levels. Taken together with prior findings on ApoE driving Aβ accumulation, this analysis points to a pathological dysregulation of the ApoE-Aβ axis. We also found dysregulation of protein networks involved in excitatory synaptic transmission. Analysis of the AMPA receptor (AMPAR) complex revealed specific loss of TARPγ-2, a key AMPAR-trafficking protein. Expression of TARPγ-2 in hAPP transgenic mice restored AMPA currents. This proteomic database represents a resource for the identification of protein alterations responsible for AD.

Mass Defect-Based Dimethyl Pyrimidinyl Ornithine (DiPyrO) Tags for Multiplex Quantitative Proteomics

We have developed a novel amine-reactive mass defect-based chemical tag, dimethyl pyrimidinyl ornithine (DiPyrO), that is compact in size, is suitable for various biological samples, and enables highly multiplexed quantification of peptides at the MS1 level without increasing mass spectral complexity. The DiPyrO tag structure incorporates heavy isotopes in a variety of configurations to impart as much as 45.3 mDa or as little as 5.8 mDa per tag between labeled peptides. Notably, peptides containing lysine are labeled with two tags, doubling the imparted mass defect to up to 90.6 mDa for the duplex tags and effectively reducing the resolving power requirement compared to previously reported mass defect-based quantification approaches. This permits current and previous generation LTQ-Orbitrap platforms to perform confident quantitative analyses of two DiPyrO-labeled samples at 100K resolving power, whereas 3-plex and 6-plex quantifications are possible at 240K and 480K resolving powers, respectively. In this work, we discuss the design and synthesis of the DiPyrO tag, characterize its effect on labeled proteome analysis by nanoLC-MS2, and demonstrate proof-of-principle applications of the duplex and triplex tags for quantitative proteomics using high-resolution MS acquisition on the Orbitrap Elite and Orbitrap Fusion Lumos.

Predicting the protein half-life in tissue from its cellular properties

Protein half-life is an important feature of protein homeostasis (proteostasis). The increasing number of in vivo and in vitro studies using high throughput proteomics provide estimates of the protein half-lives in tissues and cells. However, protein half-lives in cells and tissues are different. Due to the resource requirements for researching tissues, more data is available from cellular studies than tissues. We have designed a multivariate linear model for predicting protein half-life in tissue from its cellular properties. Inputs to the model are cellular half-life, abundance, intrinsically disordered sequences, and transcriptional and translational rates. Before the modeling, we determined substructures in the data using the relative distance from the regression line of the protein half-lives in tissues and cells, identifying three separate clusters. The model was trained on and applied to predict protein half-lives from murine liver, brain and heart tissues. In each tissue type we observed similar prediction patterns of protein half-lives. We found that the model provides the best results when there is a strong correlation between tissue and cell culture protein half-lives. Additionally, we clustered the protein half-lives to determine variations in correlation coefficients between the protein half-lives in the tissue versus in cell culture. The clusters identify strongly and weakly correlated protein half-lives, further improves the overall prediction and identifies sub groupings which exhibit specific characteristics. The model described herein, is generalizable to other data sets and has been implemented in a freely available R code.

Quantitative proteomics in lung cancer

Lung cancer is the most common cause of cancer-related death worldwide, less than 7% of patients survive 10 years following diagnosis across all stages of lung cancer. Late stage of diagnosis and lack of effective and personalized medicine reflect the need for a better understanding of the mechanisms that underlie lung cancer progression. Quantitative proteomics provides the relative different protein abundance in normal and cancer patients which offers the information for molecular interactions, signaling pathways, and biomarker identification. Here we introduce both theoretical and practical applications in the use of quantitative proteomics approaches, with principles of current technologies and methodologies including gel-based, label free, stable isotope labeling as well as targeted proteomics. Predictive markers of drug resistance, candidate biomarkers for diagnosis, and prognostic markers in lung cancer have also been discovered and analyzed by quantitative proteomic analysis. Moreover, construction of protein networks enables to provide an opportunity to interpret disease pathway and improve our understanding in cancer therapeutic strategies, allowing the discovery of molecular markers and new therapeutic targets for lung cancer.

Metabolic in Vivo Labeling Highlights Differences of Metabolically Active Microbes from the Mucosal Gastrointestinal Microbiome between High-Fat and Normal Chow Diet

The gastrointestinal microbiota in the gut interacts metabolically and immunologically with the host tissue in the contact zone of the mucus layer. For understanding the details of these interactions and especially their dynamics it is crucial to identify the metabolically active subset of the microbiome. This became possible by the development of stable isotope probing techniques, which have only sparsely been applied to microbiome research. We applied the in vivo stable isotope approach using ¹⁵N-labeled diet with subsequent identification of metabolically active bacterial species. Four-week old male Sprague-Dawley rats were randomly assigned to chow diet (CD, n =15) and high-fat diet (HFD, n =15). After 11 weeks, three animals from each group were sacrificed for baseline characterization of anthropometric and metabolic obesity. The remaining animals were exposed to either a ¹⁵N-labeled (n =9) or a ¹⁴N-unlabeled experimental diet (n =3). Three rats from each cohort (HFD and CD) were sacrificed at 12, 24, and 72 h. The remaining three animals from each cohort, which received the ¹⁴N-unlabeled diet, were sacrificed after 72 h. The colon was harvested and divided into three equal sections (proximal, medial, and distal), and the mucus layer of each specimen was sampled by scraping. We identified the active subset in an HFD model of obesity in comparison with lean controls rats using metaproteomics. In addition, all samples were investigated by 16S rRNA amplicon gene sequencing. The active microbiome of the HFD group showed an increase in bacterial taxa for Verrucomicrobia and Desulfovibrionaceae. In contrast with no significant changes in alpha diversity, time- and localization-dependent effects in beta-diversity were clearly observed. In terms of enzymatic functions the HFD group showed strong affected metabolic pathways such as energy production and carbohydrate metabolism. In vivo isotope labeling combined with metaproteomics provides a valuable method to distinguish the active from the non-active bacterial phylogenetic groups that are relevant for microbiota-host interaction. For morbid obesity such analysis may provide potentially new strategies for targeted pre- or probiotic treatments.

Glial fibrillary acidic protein exhibits altered turnover kinetics in a mouse model of Alexander disease

Mutations in the astrocyte-specific intermediate filament glial fibrillary acidic protein (GFAP) lead to the rare and fatal disorder, Alexander disease (AxD). A prominent feature of the disease is aberrant accumulation of GFAP. It has been proposed that this accumulation occurs because of an increase in gene transcription coupled with impaired proteasomal degradation, yet this hypothesis remains untested. We therefore sought to directly investigate GFAP turnover in a mouse model of AxD that is heterozygous for a disease-causing point mutation (Gfap^R236H/+) (and thus expresses both wild-type and mutant protein). Stable isotope labeling by amino acids in cell culture, using primary cortical astrocytes, indicated that the in vitro half-lives of total GFAP in astrocytes from wild-type and mutant mice were similar at ∼3-4 days. Surprisingly, results obtained with stable isotope labeling of mammals revealed that, in vivo, the half-life of GFAP in mutant mice (15.4 ± 0.5 days) was much shorter than that in wild-type mice (27.5 ± 1.6 days). These unexpected in vivo data are most consistent with a model in which synthesis and degradation are both increased. Our work reveals that an AxD-causing mutation alters GFAP turnover kinetics in vivo and provides an essential foundation for future studies aimed at preventing or reducing the accumulation of GFAP. In particular, these data suggest that elimination of GFAP might be possible and occurs more quickly than previously surmised.

Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease

Tandem mass spectrometry based shotgun proteomics of distal gut microbiomes is exceedingly difficult due to the inherent complexity and taxonomic diversity of the samples. We introduce two new methodologies to improve metaproteomic studies of microbiome samples. These methods include the stable isotope labeling in mammals to permit protein quantitation across two mouse cohorts as well as the application of activity-based probes to enrich and analyze both host and microbial proteins with specific functionalities. We used these technologies to study the microbiota from the adoptive T cell transfer mouse model of inflammatory bowel disease (IBD) and compare these samples to an isogenic control, thereby limiting genetic and environmental variables that influence microbiome composition. The data generated highlight quantitative alterations in both host and microbial proteins due to intestinal inflammation and corroborates the observed phylogenetic changes in bacteria that accompany IBD in humans and mouse models. The combination of isotope labeling with shotgun proteomics resulted in the total identification of 4434 protein clusters expressed in the microbial proteomic environment, 276 of which demonstrated differential abundance between control and IBD mice. Notably, application of a novel cysteine-reactive probe uncovered several microbial proteases and hydrolases overrepresented in the IBD mice. Implementation of these methods demonstrated that substantial insights into the identity and dysregulation of host and microbial proteins altered in IBD can be accomplished and can be used in the interrogation of other microbiome-related diseases.

A timeline of stable isotopes and mass spectrometry in the life sciences

This review retraces the role of stable isotopes and mass spectrometry in the life sciences. The timeline is divided into four segments covering the years 1920-1950, 1950-1980, 1980-2000, and 2000 until today. For each period methodic progress and typical applications are discussed. Application of stable isotopes is driven by improvements of mass spectrometry, chromatography, and related fields in sensitivity, mass accuracy, structural specificity, complex sample handling ability, data output, and data evaluation. We currently experience the vision of omics-type analyses, that is, the comprehensive identification and quantification of a complete compound class within one or a few analytical runs. This development is driven by stable isotopes without competition by radioisotopes. In metabolic studies as classic field of isotopic tracer experiments, stable isotopes and radioisotopes were competing solutions, with stable isotopes as the long-term junior partner. Since the 1990s the number of metabolic studies with radioisotopes decreases, whereas stable isotope studies retain their slow but stable upward tendency. Unique fields of stable isotopes are metabolic tests in newborns, metabolic experiments in healthy controls, newborn screening for inborn errors, quantification of drugs and drug metabolites in doping control, natural isotope fractionation in geology, ecology, food authentication, or doping control, and more recently the field of quantitative omics-type analyses. There, cells or whole organisms are systematically labeled with stable isotopes to study proteomic differences or specific responses to stimuli or genetic manipulation. The duo of stable isotopes and mass spectrometry will probably continue to grow in the life sciences, since it delivers reference-quality quantitative data with molecular specificity, often combined with informative isotope effects. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:58-85, 2017.

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

NeuCode Proteomics Reveals Bap1 Regulation of Metabolism

We introduce neutron-encoded (NeuCode) amino acid labeling of mice as a strategy for multiplexed proteomic analysis in vivo. Using NeuCode, we characterize an inducible knockout mouse model of Bap1, a tumor suppressor and deubiquitinase whose in vivo roles outside of cancer are not well established. NeuCode proteomics revealed altered metabolic pathways following Bap1 deletion, including profound elevation of cholesterol biosynthetic machinery coincident with reduced expression of gluconeogenic and lipid homeostasis proteins in liver. Bap1 loss increased pancreatitis biomarkers and reduced expression of mitochondrial proteins. These alterations accompany a metabolic remodeling with hypoglycemia, hypercholesterolemia, hepatic lipid loss, and acinar cell degeneration. Liver-specific Bap1 null mice present with fully penetrant perinatal lethality, severe hypoglycemia, and hepatic lipid deficiency. This work reveals Bap1 as a metabolic regulator in liver and pancreas, and it establishes NeuCode as a reliable proteomic method for deciphering in vivo biology.