Metabolic Labeling of Proteins for Proteomics

A Method for Rigorously Selective Capture and Simultaneous Fluorescent Labeling of N-Terminal Glycine Peptides

Although chemical methods for the selective derivatization of amino acid (AA) side chains in peptides and proteins are available, selective N-terminal labeling is challenging, especially for glycine, which has no side chain at the α-carbon position. We report here a double activation at glycine's α-methylene group that allows this AA to be differentiated from the other 19 AAs. A condensation reaction of dibenzoylmethane with glycine results in the formation of an imine, and subsequent tautomerization is followed by intramolecular cyclization, leading to the formation of a fluorescent pyrrole ring. Additionally, the approach exhibits compatibility with AAs possessing reactive side chains. Further, the method allows for selective pull-down assays of N-terminal glycine peptides from mixtures without prior knowledge of the N-terminal peptide distribution.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies

In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.

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.

Label-Free Physical Techniques and Methodologies for Proteins Detection in Microfluidic Biosensor Structures

Proteins in biological fluids (blood, urine, cerebrospinal fluid) are important biomarkers of various pathological conditions. Protein biomarkers detection and quantification have been proven to be an indispensable diagnostic tool in clinical practice. There is a growing tendency towards using portable diagnostic biosensor devices for point-of-care (POC) analysis based on microfluidic technology as an alternative to conventional laboratory protein assays. In contrast to universally accepted analytical methods involving protein labeling, label-free approaches often allow the development of biosensors with minimal requirements for sample preparation by omitting expensive labelling reagents. The aim of the present work is to review the variety of physical label-free techniques of protein detection and characterization which are suitable for application in micro-fluidic structures and analyze the technological and material aspects of label-free biosensors that implement these methods. The most widely used optical and impedance spectroscopy techniques: absorption, fluorescence, surface plasmon resonance, Raman scattering, and interferometry, as well as new trends in photonics are reviewed. The challenges of materials selection, surfaces tailoring in microfluidic structures, and enhancement of the sensitivity and miniaturization of biosensor systems are discussed. The review provides an overview for current advances and future trends in microfluidics integrated technologies for label-free protein biomarkers detection and discusses existing challenges and a way towards novel solutions.

Spatial Stable Isotopic Labeling by Amino Acids in Cell Culture: Pulse-Chase Labeling of Three-Dimensional Multicellular Spheroids for Global Proteome Analysis

Three-dimensional cell cultures, or spheroids, are important model systems for cancer research because they recapitulate chemical and phenotypic aspects of in vivo tumors. Spheroids develop radially symmetric chemical gradients, resulting in distinct cellular populations. Stable isotopic labeling by amino acids in cell culture (SILAC) is a well-established approach to quantify protein expression and has previously been used in a pulse-chase format to evaluate temporal changes. In this article, we demonstrate that distinct isotopic signatures can be introduced into discrete spatial cellular populations, effectively tracking proteins to original locations in the spheroid, using a platform that we refer to as spatial SILAC. Spheroid populations were grown with light, medium, and heavy isotopic media, and the concentric shells of cells were harvested by serial trypsinization. Proteins were quantitatively analyzed by ultraperformance liquid chromatography-tandem mass spectrometry. The isotopic signatures correlated with the spatial location and the isotope position do not significantly impact the proteome of each individual layer. Spatial SILAC can be used to examine the proteomic changes in the different layers of the spheroid and to identify protein biomarkers throughout the structure. We show that SILAC labels can be discretely pulsed to discrete positions, without altering the spheroid's proteome, promising future combined pharmacodynamic and pharmacokinetic studies.

Protein Labeling and Crosslinking by Covalent Aptamers

We developed a new approach to selectively modify native proteins in their biological environment using electrophilic covalent aptamers. These aptamers are generated through introduction of a proximity-driven electrophile at specific nucleotide sites. Using thrombin as a proof-of-concept, we demonstrate that covalent aptamers can selectively transfer a variety of functional handles and/or irreversibly crosslink to the target protein. This approach offers broad programmability and high target specificity. Furthermore, it addresses issues common to aptamers such as instability towards endogenous nucleases and residence times during target engagement. Covalent aptamers are new tools that enable specific protein modification and sensitive protein detection. Moreover, they provide prolonged, nuclease-resistant enzyme inhibition.

Revealing mechanisms of mating plug function under sexual selection

Promiscuous mating by females leads to competition between males for fertilization success. When fertilization is internal, this means that rival males’ sperm must compete within the female reproductive tract to reach the eggs. Males of diverse species deposit a mating plug during copulation, which is hypothesized to assist in the race for fertilization following multiple mating. Here, we tested this by using stable isotope labeling to discriminate the ejaculates of competing male voles in direct competition. This revealed that the mating plug simultaneously inhibits the sperm of rival males while promoting transport of a male’s own sperm, both of which are beneficial in the competition for fertilizations.

Mating plugs are produced by many sexually reproducing animals and are hypothesized to promote male fertilization success under promiscuous mating. However, tests of this hypothesis have been constrained by an inability to discriminate ejaculates of different males in direct competition. Here, we use stable isotope labeling in vivo and proteomics to achieve this in a promiscuous rodent, Myodes glareolus. We show that, although the first male’s plug is usually dislodged, it can be retained throughout the second male’s copulation. Retained plugs did not completely block rival sperm but did significantly limit their numbers. Differences in the number of each male’s sperm progressing through the female reproductive tract were also explained by natural variation in the size of mating plugs and reproductive accessory glands from which major plug proteins originate. Relative sperm numbers in turn predicted the relative fertilization success of rival males. Our application of stable isotopes to label ejaculates resolves a longstanding debate by revealing how rodent mating plugs promote fertilization success under competitive conditions. This approach opens new opportunities to reveal cryptic mechanisms of postcopulatory sexual selection among diverse animal taxa.

Using Genetic Code Expansion for Protein Biochemical Studies

Protein identification has gone beyond simply using protein/peptide tags and labeling canonical amino acids. Genetic code expansion has allowed residue- or site-specific incorporation of non-canonical amino acids into proteins. By taking advantage of the unique properties of non-canonical amino acids, we can identify spatiotemporal-specific protein states within living cells. Insertion of more than one non-canonical amino acid allows for selective labeling that can aid in the identification of weak or transient protein-protein interactions. This review will discuss recent studies applying genetic code expansion for protein labeling and identifying protein-protein interactions and offer considerations for future work in expanding genetic code expansion methods.

Discovery of Half-life of Circulating Hepatitis B Surface Antigen in Patients With Chronic Hepatitis B Infection Using Heavy Water Labeling

In a pilot study, heavy water labeling was used to determine hepatitis B surface antigen (HBsAg) turnover rates in chronic hepatitis B (CHB) patients. The mean (standard deviation) half-life of HBsAg in blood was 6.7 (5.5) days, which reflects recent production in the liver and supports strategies aimed at reducing HBsAg production in CHB patients.

Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases

Accurate, reliable, and objective biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and related age-associated neurodegenerative disorders are urgently needed to assist in both diagnosis, particularly at early stages, and monitoring of disease progression. Technological advancements in protein detection platforms over the last few decades have resulted in a plethora of reported molecular biomarker candidates for both AD and PD; however, very few of these candidates are developed beyond the discovery phase of the biomarker development pipeline, a reflection of the current bottleneck within the field. In this review, the expanded use of selected reaction monitoring (SRM) targeted mass spectrometry will be discussed in detail as a platform for systematic verification of large panels of protein biomarker candidates prior to costly validation testing. We also advocate for the coupling of discovery-based proteomics with modern targeted MS-based approaches (e.g., SRM) within a single study in future workflows to expedite biomarker development and validation for AD and PD. It is our hope that improving the efficiency within the biomarker development process by use of an SRM pipeline may ultimately hasten the development of biomarkers that both decrease misdiagnosis of AD and PD and ultimately lead to detection at early stages of disease and objective assessment of disease progression. This article is part of the special issue "Proteomics".

A Metabolic Labeling Strategy for Relative Protein Quantification in Clostridioides difficile

Clostridioides difficile (formerly Clostridium difficile) is a Gram-positive, anaerobe, spore-forming pathogen, which causes drug-induced diseases in hospitals worldwide. A detailed analysis of the proteome may provide new targets for drug development or therapeutic strategies to combat this pathogen. The application of metabolic labeling (ML) would allow for accurate quantification of significant differences in protein abundance, even in the case of very small changes. Additionally, it would be possible to perform more accurate studies of the membrane or surface proteomes, which usually require elaborated sample preparation. Such studies are therefore prone to higher standard deviations during the quantification. The implementation of ML strategies for C. difficile is complicated due to the lack in arginine and lysine auxotrophy as well as the Stickland dominated metabolism of this anaerobic pathogen. Hence, quantitative proteome analyses could only be carried out by label free or chemical labeling methods so far. In this paper, a ML approach for C. difficile is described. A cultivation procedure with 15N-labeled media for strain 630Δerm was established achieving an incorporation rate higher than 97%. In a proof-of-principle experiment, the performance of the ML approach in C. difficile was tested. The proteome data of the cytosolic subproteome of C. difficile cells grown in complex medium as well as two minimal media in the late exponential and early stationary growth phase obtained via ML were compared with two label free relative quantification approaches (NSAF and LFQ). The numbers of identified proteins were comparable within the three approaches, whereas the number of quantified proteins were between 1,110 (ML) and 1,861 (LFQ) proteins. A hierarchical clustering showed clearly separated clusters for the different conditions and a small tree height with ML approach. Furthermore, it was shown that the quantification based on ML revealed significant altered proteins with small fold changes compared to the label free approaches. The quantification based on ML was accurate, reproducible, and even more sensitive compared to label free quantification strategies.

Protein Turnover Measurements in Human Serum by Serial Immunoaffinity LC-MS/MS

BACKGROUND

The half-life of target proteins is frequently an important parameter in mechanistic pharmacokinetic and pharmacodynamic (PK/PD) modeling of biotherapeutics. Clinical studies for accurate measurement of physiologically relevant protein turnover can reduce the uncertainty in PK/PD model-based predictions, for example, of the therapeutic dose and dosing regimen in first-in-human clinical trials.

METHODS

We used a targeted mass spectrometry work flow based on serial immunoaffinity enrichment ofmultiple human serum proteins from a [5,5,5-2H3]-L-leucine tracer pulse-chase study in healthy volunteers. To confirm the reproducibility of turnover measurements from serial immunoaffinity enrichment, multiple aliquots from the same sample set were subjected to protein turnover analysis in varying order. Tracer incorporation was measured by multiple–reaction-monitoring mass spectrometry and target turnover was calculated using a four-compartment pharmacokinetic model.

RESULTS

Five proteins of clinical or therapeutic relevance including soluble tumor necrosis factor receptor superfamily member 12A, tissue factor pathway inhibitor, soluble interleukin 1 receptor like 1, soluble mucosal addressin cell adhesion molecule 1, and muscle-specific creatine kinase were sequentially subjected to turnover analysis from the same human serum sample. Calculated half-lives ranged from 5–15 h; however, no tracer incorporation was observed for mucosal addressin cell adhesion molecule 1.

CONCLUSIONS

The utility of clinical pulse-chase studies to investigate protein turnover can be extended by serial immunoaffinity enrichment of target proteins. Turnover analysis from serum and subsequently from remaining supernatants provided analytical sensitivity and reproducibility for multiple human target proteins in the same sample set, irrespective of the order of analysis.

Clickable Cubosomes for Antibody-Free Drug Targeting and Imaging Applications

The combination of copper-free click chemistry with metabolic labeling offers new opportunities in drug delivery. The objective of this study was to determine whether cubosomes functionalized with azide or dibenzocyclooctyne (DBCO) groups are able to undergo copper-free click chemistry with a strained cyclooctyne or azide, respectively. Phytantriol-based cubosomes were functionalized using phospholipids bearing an azide or DBCO group. The modified cubosome dispersions were characterized using dynamic light scattering, cryo-TEM, and small-angle X-ray scattering. The efficiency of "clickability" was assessed by reacting the cubosomes with a complementary dye and determining bound and unbound dye via size exclusion chromatography. The clickable cubosomes reacted specifically and efficiently with a click-Cy5 dye with minor changes to the size, shape, and structure of the cubosomes. This indicates that cubosomes can retain their unique internal structure while participating in copper-free click chemistry. This proof of concept study paves the way for the use of copper-free click chemistry and metabolic labeling with cubosomes for targeted drug delivery and imaging.

RElative QUantitation Inferred by Evaluating Mixtures (REQUIEM)

Motivated by the lack of easily implementable and generally applicable strategies to increase and assess data accuracy, we devised a novel label-free approach, termed REQUIEM, to address challenges in relative quantitation. For comparing the relative amounts of analytes in two samples, a mixture is prepared from aliquots of the samples, and the samples and the mixture are analyzed in parallel according to the intended workflow. Processing of the resulting data using the REQUIEM algorithm yields unbiased analyte fold-changes and associated statistics, allowing several types of errors to be diagnosed or eliminated. Extensive simulations and analysis of carefully prepared standard samples demonstrated the rigorous foundations of REQUIEM. We applied REQUIEM to several real-world analytical techniques and workflows, notably to tandem mass spectrometry analysis by using isomeric oligosaccharides as test analytes. We conclude that REQUIEM can reveal inaccuracies in the data that are difficult to identify by using traditional approaches.

Strategies in relative and absolute quantitative mass spectrometry based proteomics

Quantitative mass spectrometry approaches are used for absolute and relative quantification in global proteome studies. To date, relative and absolute quantification techniques are available that differ in quantification accuracy, proteome coverage, complexity and robustness. This review focuses on most common relative or absolute quantification strategies exemplified by three experimental studies. A label-free relative quantification approach was performed for the investigation of the membrane proteome of sensory cilia to the depth of olfactory receptors in Mus musculus. A SILAC-based relative quantification approach was successfully applied for the identification of core components and transient interactors of the peroxisomal importomer in Saccharomyces cerevisiae. Furthermore, AQUA using stable isotopes was exemplified to unraveling the prenylome influenced by novel prenyltransferase inhibitors. Characteristic enrichment and fragmentation strategies for a robust quantification of the prenylome are also summarized.

Experimental and Study Design Considerations for Uncovering Oncometabolites

Metabolomics as a field has gained attention due to its potential for biomarker discovery, namely because it directly reflects disease phenotype and is the downstream effect of posttranslational modifications. The field provides a "top-down," integrated view of biochemistry in complex organisms, as opposed to the traditional "bottom-up" approach that aims to analyze networks of interactions between genes, proteins and metabolites. It also allows for the detection of thousands of endogenous metabolites in various clinical biospecimens in a high-throughput manner, including tissue and biofluids such as blood and urine. Of note, because biological fluid samples can be collected relatively easily, the time-dependent fluctuations of metabolites can be readily studied in detail.In this chapter, we aim to provide an overview of (1) analytical methods that are currently employed in the field, and (2) study design concepts that should be considered prior to conducting high-throughput metabolomics studies. While widely applicable, the concepts presented here are namely applicable to high-throughput untargeted studies that aim to search for metabolite biomarkers that are associated with a particular human disease.

Retrieving Quantitative Information of Histone PTMs by Mass Spectrometry

Posttranslational modifications (PTMs) of histones are one of the main research interests in the rapidly growing field of epigenetics. Accurate and precise quantification of these highly complex histone PTMs is critical for understanding the histone code and the biological significance behind it. It nonetheless remains a major analytical challenge. Mass spectrometry (MS) has been proven as a robust tool in retrieving quantitative information of histone PTMs, and a variety of MS-based quantitative strategies have been successfully developed and employed in basic research as well as clinical studies. In this chapter, we provide an overview for quantitative analysis of histone PTMs, often highly flexible and case dependent, as a primer for future experimental designs.

Combining Click Chemistry-Based Proteomics With Dox-Inducible Gene Expression

Inactivating mutations in single genes can trigger, prevent, promote, or alleviate diseases. Identifying such disease-related genes is a main pillar of medical research. Since proteins play a crucial role in mediating these effects, their impact on the diseased cells' proteome including posttranslational modifications has to be elucidated for a detailed understanding of the role of these genes in the disease process. In complex disorders, like cancer, several genes contribute to the disease process, thereby hampering the assignment of a proteomic change to the corresponding causative gene. To enable comprehensive screening for the impact of inactivation of a gene, e.g., loss of a tumor suppressor in cancer, on the cellular proteome, we present a strategy based on combination of three technologies that is recombinase-mediated cassette exchange, click chemistry, and mass spectrometry. The methodology is exemplified by the analysis of the proteomic changes induced by the loss of a tumor suppressor gene in colorectal cancer cells. To demonstrate the applicability to screen for posttranslational modification changes, we also describe the analysis of protein glycosylation changes caused by the tumor suppressor inactivation. In principle, this strategy can be applied to analyze the effects of any gene of interest on protein expression as well as posttranslational modification by glycosylation. Moreover adaptation of the strategy to an appropriate cell culture model has the potential for application on a broad range of diseases where the disease-promoting mutations have been identified.

Rapid enzyme regeneration results in the striking catalytic longevity of an engineered, single species, biocatalytic biofilm

BACKGROUND

Engineering of single-species biofilms for enzymatic generation of fine chemicals is attractive. We have recently demonstrated the utility of an engineered Escherichia coli biofilm as a platform for synthesis of 5-halotryptophan. E. coli PHL644, expressing a recombinant tryptophan synthase, was employed to generate a biofilm. Its rapid deposition, and instigation of biofilm formation, was enforced by employing a spin-down method. The biofilm presents a large three-dimensional surface area, excellent for biocatalysis. The catalytic longevity of the engineered biofilm is striking, and we had postulated that this was likely to largely result from protection conferred to recombinant enzymes by biofilm's extracellular matrix. SILAC (stable isotopic labelled amino acids in cell cultures), and in particular dynamic SILAC, in which pulses of different isotopically labelled amino acids are administered to cells over a time course, has been used to follow the fate of proteins. To explore within our spin coated biofilm, whether the recombinant enzyme's longevity might be in part due to its regeneration, we introduced pulses of isotopically labelled lysine and phenylalanine into medium overlaying the biofilm and followed their incorporation over the course of biofilm development.

RESULTS

Through SILAC analysis, we reveal that constant and complete regeneration of recombinant enzymes occurs within spin coated biofilms. The striking catalytic longevity within the biofilm results from more than just simple protection of active enzyme by the biofilm and its associated extracellular matrix. The replenishment of recombinant enzyme is likely to contribute significantly to the catalytic longevity observed for the engineered biofilm system.

CONCLUSIONS

Here we provide the first evidence of a recombinant enzyme's regeneration in an engineered biofilm. The recombinant enzyme was constantly replenished over time as evidenced by dynamic SILAC, which suggests that the engineered E. coli biofilms are highly metabolically active, having a not inconsiderable energetic demand. The constant renewal of recombinant enzyme highlights the attractive possibility of utilising this biofilm system as a dynamic platform into which enzymes of interest can be introduced in a "plug-and-play" fashion and potentially be controlled through promoter switching for production of a series of desired fine chemicals.

A simplified calculation procedure for mass isotopomer distribution analysis (MIDA) based on multiple linear regression

We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two ¹³ C atoms (¹³ C₂ -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of ¹³ C₂ -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% ¹³ C₂ -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd.

Comparing the Diagnostic Classification Accuracy of iTRAQ, Peak-Area, Spectral-Counting, and emPAI Methods for Relative Quantification in Expression Proteomics

Diagnostic classification accuracy is critical in expression proteomics to ensure that as many true differences as possible are identified with acceptable false-positive rates. We present a comparison of the diagnostic accuracy of iTRAQ with three label-free methods, peak area, spectral counting, and emPAI, for relative quantification using a spiked proteome standard. We provide the first validation of emPAI for intersample relative quantification and find clear differences among the four quantification approaches that could be considered when designing an experiment. Spectral counting was observed to perform surprisingly well in all regards. Peak area performed best for smaller fold differences and was shown to be capable of discerning a 1.1-fold difference with acceptable specificity and sensitivity. The performance of iTRAQ was dramatically worse than the label-free methods with low abundance proteins. Using the iTRAQ data set for validation, we also demonstrate a novel iTRAQ analysis regime that avoids the use of ratios in significance testing and outperforms a common commercial alternative.

Proteome Dynamics: Tissue Variation in the Kinetics of Proteostasis in Intact Animals

Understanding the role of protein turnover in the maintenance of proteostasis requires accurate measurements of the rates of replacement of proteins in complex systems, such as intact animals. Moreover, any investigation of allometric scaling of protein turnover is likely to include species for which fully annotated proteomes are not available. We have used dietary administration of stable isotope labeled lysine to assess protein turnover rates for proteins from four tissues in the bank vole, Myodes glareolus. The annotated genome for this species is not available, so protein identification was attained through cross-species matching to the mouse. For proteins for which confident identifications were derived, the pattern of lysine incorporation over 40 days was used to define the rate of synthesis of individual proteins in the four tissues. The data were heavily filtered to retain a very high quality dataset of turnover rates for 1088 proteins. Comparative analysis of the four tissues revealed different median rates of degradation (kidney: 0.099 days⁻¹; liver 0.136 days⁻¹; heart, 0.054 days⁻¹, and skeletal muscle, 0.035 days⁻¹). These data were compared with protein degradation rates from other studies on intact animals or from cells in culture and indicate that both cell type and analytical methodology may contribute to variance in turnover data between different studies. These differences were not only due to tissue-specific proteins but were reflected in gene products common to all tissues. All data are available via ProteomeXchange with identifier PXD002054.

Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants

Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.

A new method to measure muscle protein synthesis in humans by endogenously introduced d9-leucine and using blood for precursor enrichment determination

Enrichment from the easily accessible blood amino acid pool is commonly used as precursor enrichment to calculate rates of muscle protein fractional synthesis in relevant human studies in lieu of the less accessible muscle fluid amino acid pool. However, the accuracy of this approach depends largely on the extent to which there is low discrepancy in free amino acid enrichment between blood and muscle. Steady-state gradient (i.e., ratio) of amino acid enrichment between blood and muscle fluid in the basal state and in response to amino acid infusion were determined in five healthy subjects, and in association with two separate tracers: d9-leucine, introduced endogenously by the metabolism of d10-leucine (i.e., l-[2,3,3,4,5,5,5,6,6,6-(2)H10]leucine) infused in blood, and (13)C6-phenylalanine introduced/infused in blood. The blood-to-muscle fluid amino acid enrichment ratio was lower (P < 0.05) for d9-leucine compared to (13)C6-phenylalanine both before (1.5 ± 0.1 vs. 2.5 ± 0.1) and during (1.1 ± 0.1 vs. 1.2 ± 0.1) amino acid infusion. Importantly, the decrease in this ratio in association with the amino acid infusion was considerably less for the d9-leucine than the (13)C6-phenylalanine (-0.38 ± 0.03 vs. -1.29 ± 0.07; P < 0.05). In conclusion, blood d9-leucine enrichment introduced endogenously by intravenous infusion of d10-leucine provides a closer estimate of the muscle fluid amino acid enrichment, and its associated changes, than blood phenylalanine enrichment to calculate rates of muscle protein synthesis in humans.

A novel method for determination of the (15) N isotopic composition of Rubisco in wheat plants exposed to elevated atmospheric carbon dioxide

Although ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) is mostly known as a key enzyme involved in CO2 assimilation during the Calvin cycle, comparatively little is known about its role as a pool of nitrogen storage in leaves. For this purpose, we developed a protocol to purify Rubisco that enables later analysis of its (15) N isotope composition (δ(15) N) at the natural abundance and (15) N-labeled plants. In order to test the utility of this protocol, durum wheat (Triticum durum var. Sula) exposed to an elevated CO2 concentration (700 vs 400 µmol mol(-1) ) was labeled with K(15) NO3 (enriched at 2 atom %) during the ear development period. The developed protocol proves to be selective, simple, cost effective and reproducible. The study reveals that (15) N labeling was different in total organic matter, total soluble protein and the Rubisco fraction. The obtained data suggest that photosynthetic acclimation in wheat is caused by Rubisco depletion. This depletion may be linked to preferential nitrogen remobilization from Rubisco toward grain filling.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

Overview of peptide and protein analysis by mass spectrometry

Mass spectrometry is an indispensable tool for peptide and protein analysis owing to its speed, sensitivity, and versatility. It can be used to determine amino acid sequences of peptides, and to characterize a wide variety of post-translational modifications such as phosphorylation and glycosylation. Mass spectrometry can also be used to determine absolute and relative protein quantities, and can identify and quantify thousands of proteins from complex samples, which makes it an extremely powerful tool for systems biology studies. The main goals of this unit are to familiarize peptide and protein chemists and biologists with the types of mass spectrometers that are appropriate for the majority of their analytical needs, to describe the kinds of experiments that can be performed with these instruments on a routine basis, and to discuss the kinds of information that these experiments provide.

Protein turnover on the scale of the proteome

Protein turnover is a neglected dimension in postgenomic studies, defining the dynamics of changes in protein expression and forging a link between transcriptome, proteome and metabolome. Recent advances in postgenomic technologies have led to the development of new proteomic techniques to measure protein turnover on a proteome-wide scale. These methods are driven by stable isotope metabolic labeling of cells in culture or in intact animals. This review considers the merits and difficulties of different methods that allow access to proteome dynamics.

Alternative fusion protein strategies to express recalcitrant QconCAT proteins for quantitative proteomics of human drug metabolizing enzymes and transporters

QconCAT is a tool for quantitative proteomics, consisting of an artificial protein, expressed from an artificial gene, made up of a concatenated string of proteotypic peptides selected from the proteins under study. Isotopically labeled QconCAT (usually containing (13)C6-arginine and (13)C6-lysine) provides a standard for each proteotypic peptide included in its sequence. In practice, some QconCAT proteins fail to express at sufficient levels for the purpose of quantitative analysis. Two complementary methods are presented to express recalcitrant QconCAT proteins intended to quantify human hepatic enzymes and transporters.

Electrostatic control of peptide side-chain reactivity using amphiphilic homopolymer-based supramolecular assemblies

Supramolecular assemblies formed by amphiphilic homopolymers with negatively charged groups in the hydrophilic segment have been designed to enable high labeling selectivity toward reactive side chain functional groups in peptides. The negatively charged interiors of the supramolecular assemblies are found to block the reactivity of protonated amines that would otherwise be reactive in aqueous solution, while maintaining the reactivity of nonprotonated amines. Simple changes to the pH of the assemblies' interiors allow control over the reactivity of different functional groups in a manner that is dependent on the pKa of a given peptide functional group. The labeling studies carried out in positively charged supramolecular assemblies and free buffer solution show that, even when the amine is protonated, labeling selectivity exists only when complementary electrostatic interactions are present, thereby demonstrating the electrostatically controlled nature of these reactions.

Proteomics in uveal melanoma

Uveal melanoma is the most common primary intraocular malignancy in adults, with an incidence of 5-7 per million per year. It is associated with the development of metastasis in about 50% of cases, and 40% of patients with uveal melanoma die of metastatic disease despite successful treatment of the primary tumour. The survival rates at 5, 10 and 15 years are 65%, 50% and 45% respectively. Unlike progress made in many other areas of cancer, uveal melanoma is still poorly understood and survival rates have remained similar over the past 25 years. Recently, advances made in molecular genetics have improved our understanding of this disease and stratification of patients into low risk and high risk for developing metastasis. However, only a limited number of studies have been performed using proteomic methods. This review will give an overview of various proteomic technologies currently employed in life sciences research, and discuss proteomic studies of uveal melanoma.

A proteomic approach to identify seminal plasma proteins in roosters (Gallus gallus domesticus)

Considering the interest in avian semen processing and storage, the objective of this study was to identify the domestic fowl seminal plasma proteins using two-dimensional gel electrophoresis (2-DE) and mass spectrometry MS/MS. For three times in a 4-month period, seminal plasma was obtained from semen collected from four local male chickens (Gallus gallus domesticus) and prepared for two-dimensional polyacrylamide gel electrophoresis. A total of 83 spots were detected across all gels and analyzed by MALDI-TOF/TOF. Among these spots, 17 have been successfully identified. The most intensely stained spots were recognized as serum albumin, ovotransferrin, alpha-enolase, fatty acid binding protein, thioredoxin, trypsin inhibitor CITI-1 and gallinacin-9. From these proteins, two are characteristic of avian seminal plasma, the ovotransferrin and gallinacin-9, and one is specific of the Gallus species, the chicken trypsin inhibitor CITI-1.

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

Quantification of histone modifications using ¹⁵N metabolic labeling

Mass spectrometry has made major contributions to recent discoveries in the field of epigenetics, particularly in the characterization of the myriad post-translational modifications (PTMs) of histones which are technically challenging to analyze. These new developments have further aroused great interest in development of robust, new mass spectrometric methods to quantitatively study the dynamics of histone modifications. This review covers quantitative analysis of histone PTMs and discuss an ¹⁵N metabolic labeling procedure for quantifying histone PTMs applied to the analysis of methyltransferase knockouts in the model organism, Tetrahymena thermophila.

Glycocapture-based proteomics for secretome analysis

Protein glycosylation represents the most abundant extracellular posttranslational modification in multicellular organisms. These glycoproteins unequivocally comprise the major biomolecules involved in extracellular processes, such as growth factors, signaling proteins for cellular communication, enzymes, and proteases for on- and off-site processing. It is now known that altered protein glycosylation is a hallmark event in many different pathologies. Glycoproteins are found mostly in the so-called secretome, which comprises classically and nonclassically secreted proteins and protein fragments that are released from the cell surface through ectodomain shedding. Due to biological complexity and technical difficulty, comparably few studies have taken an in-depth investigation of cellular secretomes using system-wide approaches. The cellular secretomes are considered to be a valuable source of therapeutic targets and novel biomarkers. It is not surprising that many existing biomarkers, including biomarkers for breast, ovarian, prostate, and colorectal cancers are glycoproteins. Focused analysis of secreted glycoproteins could thus provide valuable information for early disease diagnosis, and surveillance. Furthermore, since most secreted proteins are glycosylated and glycosylation predominantly targets secreted proteins, the glycan/sugar moiety itself can be used as a chemical "handle" for the targeted analysis of cellular secretomes, thereby reducing sample complexity and allowing detection of low abundance proteins in proteomic workflows. This review will focus on various glycoprotein enrichment strategies that facilitate proteomics-based technologies for the quantitative analysis of cell secretomes and cell surface proteomes.

Addressing the current bottlenecks of metabolomics: Isotopic Ratio Outlier Analysis™, an isotopic-labeling technique for accurate biochemical profiling

Metabolomics or biochemical profiling is a fast emerging science; however, there are still many associated bottlenecks to overcome before measurements will be considered robust. Advances in MS resolution and sensitivity, ultra pressure LC-MS, ESI, and isotopic approaches such as flux analysis and stable-isotope dilution, have made it easier to quantitate biochemicals. The digitization of mass spectrometers has simplified informatic aspects. However, issues of analytical variability, ion suppression and metabolite identification still plague metabolomics investigators. These hurdles need to be overcome for accurate metabolite quantitation not only for in vitro systems, but for complex matrices such as biofluids and tissues, before it is possible to routinely identify biomarkers that are associated with the early prediction and diagnosis of diseases. In this report, we describe a novel isotopic-labeling method that uses the creation of distinct biochemical signatures to eliminate current bottlenecks and enable accurate metabolic profiling.

The application of quantification techniques in proteomics for biomedical research

The systematic analysis of biological processes requires an understanding of the quantitative expression patterns of proteins, their interacting partners and their subcellular localization. This information was formerly difficult to accrue as the relative quantification of proteins relied on antibody-based methods and other approaches with low throughput. The advent of soft ionization techniques in mass spectrometry plus advances in separation technologies has aligned protein systems biology with messenger RNA, DNA, and microarray technologies to provide data on systems as opposed to singular protein entities. Another aspect of quantitative proteomics that increases its importance for the coming few years is the significant technical developments underway both for high pressure liquid chromatography and mass spectrum devices. Hence, robustness, reproducibility and mass accuracy are still improving with every new generation of instruments. Nonetheless, the methods employed require validation and comparison to design fit for purpose experiments in advanced protein analyses. This review considers the newly developed systematic protein investigation methods and their value from the standpoint that relative or absolute protein quantification is required de rigueur in biomedical research.

Qualitative and quantitative screening of amino acids in plant tissues

The comprehensive analysis of metabolites (metabolomics) and expressed proteins (proteomics) in any given biological system forms the center of modern efforts to define the critical functions of biological systems. Because amino acids play important roles in primary and secondary metabolic pathways as well as serving as the building blocks of proteins, they have been important targets for efforts at metabolic profiling. Amino acids have been analyzed using a number of procedures, including separation by high performance liquid chromatography (HPLC), gas chromatography (GC), liquid chromatography (LC), and capillary electrophoresis (CE). Mass spectrometry (MS) remains the primary analytical and detection system for metabolic profiling, including amino acid analysis, due to its accuracy and the information content obtained by such analyses, which facilitates the identification and measurement of large numbers of biomolecules. MS methods also add the capability of monitoring isotope distributions of molecules for metabolic flux analysis. Here we describe a GC-MS method that is suitable for analysis of amino acids in sub-milligram quantities of fresh plant material and that is easily adapted to high-throughput screening approaches.

Quantitative proteomics reveals that the specific methyltransferases Txr1p and Ezl2p differentially affect the mono-, di- and trimethylation states of histone H3 lysine 27 (H3K27)

Nuclear DNA in eukaryotic cells is assembled into the hierarchical chromatin structure via a process that is dynamically affected by the combinatorial set of post-translational modifications (PTMs) of histones in a dynamic manner responsive to physiological and environmental changes. The precise quantification of these complex modifications is challenging. Here we present a robust MS-based quantitative proteomics method for studying histone PTMs using (15)N metabolically labeled histones as the internal reference. Using this approach, we identified Tetrahymena trithorax related 1 (Txr1p) as a histone methyltransferase in Tetrahymena thermophila and characterized the relationships of the Txr1p and Ezl2p methyltransferases to histone H3 modification. We identified 32 PTMs in more than 60 tryptic peptides from histone H3 of the ciliate model organism Tetrahymena thermophila, and we quantified them (average coefficient of variation: 13%). We examined perturbations to histone modification patterns in two knockout strains of SET-domain-containing histone methyltransferases (HMT). Knockout of TXR1 led to progressively decreased mono-, di-, and tri-methylation of H3K27 and apparent reduced monomethylation of H3K36 in vivo. In contrast, EZL2 knockout resulted in dramatic reductions in both di- and tri-methylation of H3K27 in vivo, whereas the levels of monomethylation of H3K27 increased significantly. This buildup of monomethyl H3K27 is consistent with its role as a substrate for Ezl2p. These results were validated via immunoblotting using modification site-specific antibodies. Taken together, our studies define Txr1p as an H3K27 monomethylation-specific HMT that facilitates the buildup of H3K27 di- and trimethylation by the canonical H3K27-specific HMT, Ezl2p. Our studies also delineate some of the interdependences between various H3 modifications, as compensatory increases in monomethylation at H3K4, H3K23, and H3K56 were also observed for both TXR1 and ELZ2 mutants.

Proteome dynamics: revisiting turnover with a global perspective

Although bulk protein turnover has been measured with the use of stable isotope labeled tracers for over half a century, it is only recently that the same approach has become applicable to the level of the proteome, permitting analysis of the turnover of many proteins instead of single proteins or an aggregated protein pool. The optimal experimental design for turnover studies is dependent on the nature of the biological system under study, which dictates the choice of precursor label, protein pool sampling strategy, and treatment of data. In this review we discuss different approaches and, in particular, explore how complexity in experimental design and data processing increases as we shift from unicellular to multicellular systems, in particular animals.

Isotopic labeling-assisted metabolomics using LC-MS

Metabolomics has emerged as the latest of the so-called “omics” disciplines and has great potential to provide deeper understanding of fundamental biochemical processes at the biological system level. Among recent technological developments, LC–HRMS enables determination of hundreds to thousands of metabolites over a wide range of concentrations and has developed into one of the most powerful techniques in non-targeted metabolomics. The analysis of mixtures of in-vivo-stable isotopic-labeled samples or reference substances with un-labeled samples leads to specific LC–MS data patterns which can be systematically exploited in practically all data-processing steps. This includes recognition of true metabolite-derived analytical features in highly complex LC–MS data and characterization of the global biochemical composition of biological samples. In addition, stable-isotopic labeling can be used for more accurate quantification (via internal standardization) and identification of compounds in different organisms.