A MS data search method for improved 15N‐labeled protein identification

Quantitative proteomics using stable isotope labeling strategies combined with MS is an important tool for biomarker discovery. Methods involving stable isotope metabolic labeling result in optimal quantitative accuracy, since they allow the immediate combination of two or more samples. Unfortunately, stable isotope incorporation rates in metabolic labeling experiments using mammalian organisms usually do not reach 100%. As a consequence, protein identifications in ¹⁵N database searches have poor success rates. We report on a strategy that significantly improves the number of ¹⁵N‐labeled protein identifications and results in a more comprehensive and accurate relative peptide quantification workflow.     

The 15N isotope effect in Escherichia coli: A neutron can make the difference

Several techniques based on stable isotope labeling are used for quantitative MS. These include stable isotope metabolic labeling methods for cells in culture as well as live organisms with the assumption that the stable isotope has no effect on the proteome. Here, we investigate the ¹⁵N isotope effect on Escherichia coli cultures that were grown in either unlabeled (¹⁴N) or ¹⁵N‐labeled media by LC‐ESI‐MS/MS‐based relative protein quantification. Consistent protein expression level differences and altered growth rates were observed between ¹⁴N and ¹⁵N‐labeled cultures. Furthermore, targeted metabolite analyses revealed altered metabolite levels between ¹⁴N and ¹⁵N‐labeled bacteria. Our data demonstrate for the first time that the introduction of the ¹⁵N isotope affects protein and metabolite levels in E. coli and underline the importance of implementing controls for unbiased protein quantification using stable isotope labeling techniques.     

Determining synthesis rates of individual proteins in zebrafish (Danio rerio) with low levels of a stable isotope labelled amino acid

The zebrafish is a powerful model organism for the analysis of human cardiovascular development and disease. Understanding these processes at the protein level not only requires changes in protein concentration to be determined but also the rate at which these changes occur on a protein‐by‐protein basis. The ability to measure protein synthesis and degradation rates on a proteome‐wide scale, using stable isotope labelling in conjunction with mass spectrometry is now a well‐established experimental approach. With the advent of more selective and sensitive mass spectrometers, it is possible to accurately measure lower levels of stable isotope incorporation, even when sample is limited. In order to challenge the sensitivity of this approach, we successfully determined the synthesis rates of over 600 proteins from the cardiac muscle of the zebrafish using a diet where either 30% or 50% of the L‐leucine was replaced with a stable isotope labelled analogue ([²H₇]L‐leucine]. It was possible to extract sufficient protein from individual zebrafish hearts to determine the incorporation rate of the label into hundreds of proteins simultaneously, with the two labelling regimens showing a good correlation of synthesis rates.     

Aging alters the metabolic flux signature of the ER‐unfolded protein response in vivo in mice

Age is a risk factor for numerous diseases, including neurodegenerative diseases, cancers, and diabetes. Loss of protein homeostasis is a central hallmark of aging. Activation of the endoplasmic reticulum unfolded protein response (UPR^ER) includes changes in protein translation and membrane lipid synthesis. Using stable isotope labeling, a flux “signature” of the UPR^ER in vivo in mouse liver was developed by inducing ER stress with tunicamycin and measuring rates of both proteome‐wide translation and de novo lipogenesis. Several changes in protein synthesis across ontologies were noted with age, including a more dramatic suppression of translation under ER stress in aged mice as compared with young mice. Binding immunoglobulin protein (BiP) synthesis rates and mRNA levels were increased more in aged than young mice. De novo lipogenesis rates decreased under ER stress conditions in aged mice, including both triglyceride and phospholipid fractions. In young mice, a significant reduction was seen only in the triglyceride fraction. These data indicate that aged mice have an exaggerated metabolic flux response to ER stress, which may indicate that aging renders the UPR^ER less effective in resolving proteotoxic stress.     

Characterization of global yeast quantitative proteome data generated from the wild-type and glucose repression saccharomyces cerevisiae strains: the comparison of two quantitative methods

The quantitative proteomic analysis of complex protein mixtures is emerging as a technically challenging but viable systems-level approach for studying cellular function. This study presents a large-scale comparative analysis of protein abundances from yeast protein lysates derived from both wild-type yeast and yeast strains lacking key components of the Snf1 kinase complex. Four different strains were grown under well-controlled chemostat conditions. Multidimensional protein identification technology followed by quantitation using either spectral counting or stable isotope labeling approaches was used to identify relative changes in the protein expression levels between the strains. A total of 2388 proteins were relatively quantified, and more than 350 proteins were found to have significantly different expression levels between the two strains of comparison when using the stable isotope labeling strategy. The stable isotope labeling based quantitative approach was found to be highly reproducible among biological replicates when complex protein mixtures containing small expression changes were analyzed. Where poor correlation between stable isotope labeling and spectral counting was found, the major reason behind the discrepancy was the lack of reproducible sampling for proteins with low spectral counts. The functional categorization of the relative protein expression differences that occur in Snf1-deficient strains uncovers a wide range of biological processes regulated by this important cellular kinase.     

Recent advancements in mass spectrometry–based tools to investigate newly synthesized proteins

Tight regulation of protein translation drives the proteome to undergo changes under influence of extracellular or intracellular signals. Despite mass spectrometry–based proteomics being an excellent method to study differences in protein abundance in complex proteomes, analyzing minute or rapid changes in protein synthesis and abundance remains challenging. Therefore, several dedicated techniques to directly detect and quantify newly synthesized proteins have been developed, notably puromycin-based, bio-orthogonal noncanonical amino acid tagging–based, and stable isotope labeling by amino acids in cell culture–based methods, combined with mass spectrometry. These techniques have enabled the investigation of perturbations, stress, or stimuli on protein synthesis. Improvements of these methods are still necessary to overcome various remaining limitations. Recent improvements include enhanced enrichment approaches and combinations with various stable isotope labeling techniques, which allow for more accurate analysis and comparison between conditions on shorter timeframes and in more challenging systems. Here, we aim to review the current state in this field.     

Systematic analysis of protein pools, isoforms, and modifications affecting turnover and subcellular localization

In higher eukaryotes many genes encode protein isoforms whose properties and biological roles are often poorly characterized. Here we describe systematic approaches for detection of either distinct isoforms, or separate pools of the same isoform, with differential biological properties. Using information from ion intensities we have estimated protein abundance levels and using rates of change in stable isotope labeling with amino acids in cell culture isotope ratios we measured turnover rates and subcellular distribution for the HeLa cell proteome. Protein isoforms were detected using three data analysis strategies that evaluate differences between stable isotope labeling with amino acids in cell culture isotope ratios for specific groups of peptides within the total set of peptides assigned to a protein. The candidate approach compares stable isotope labeling with amino acids in cell culture isotope ratios for predicted isoform-specific peptides, with ratio values for peptides shared by all the isoforms. The rule of thirds approach compares the mean isotope ratio values for all peptides in each of three equal segments along the linear length of the protein, assessing differences between segment values. The three in a row approach compares mean isotope ratio values for each sequential group of three adjacent peptides, assessing differences with the mean value for all peptides assigned to the protein. Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices. The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides. Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.     

OPP Labeling Enables Total Protein Synthesis Quantification in CHO Production Cell Lines at the Single‐Cell Level

Accurate measurement of global and specific protein synthesis rates is becoming increasingly important, especially in the context of biotechnological applications such as process modeling or selection of production cell clones. While quantification of total protein translation across whole cell populations is easily achieved, methods that are capable of tracking population dynamics at the single‐cell level are still lacking. To address this need, we apply O‐propargyl‐puromycin (OPP) labeling to assess total protein synthesis in single recombinant Chinese hamster ovary (CHO) cells by flow cytometry. Thereby we demonstrate that global protein translation rates slightly increase with progression through the cell cycle during exponential growth. Stable CHO cell lines producing recombinant protein display similar levels of total protein synthesis as their parental CHO host cell line. Global protein translation does not correlate with intracellular product content of three model proteins, but the host cell line with high transient productivity has a higher OPP signal. This indicates that production cell lines with increased overall protein synthesis capacity can be identified by our method at the single‐cell level. In conclusion, OPP‐labeling allows rapid and reproducible assessment of global protein synthesis in single CHO cells, and can be multiplexed with DNA staining or any type of immunolabeling of specific proteins or markers for organelles.     

Metabolic labeling of proteins for proteomics

Realization of the advantages of stable isotope labeling for proteomics has emerged gradually. However, many stable isotope label approaches rely on labeling in vitro using complex and sometimes expensive reagents. This review discusses strategies for labeling protein in vivo through metabolic incorporation of label into protein. This approach has many advantages, is particularly suited to single cells grown in culture (prokaryotic or eukaryotic), but is nonetheless subject to a number of complicating factors that must be controlled so that meaningful experiments can be conducted. Confounding issues include the metabolic lability of the amino acid precursor, incomplete labeling, and the role of protein turnover in labeling kinetics. All of these are controllable, provided that appropriate precautions are adopted.     

In-depth quantitative cardiac proteomics combining electron transfer dissociation and the metalloendopeptidase Lys-N with the SILAC mouse

In quantitative proteomics stable isotope labeling has progressed from cultured cells toward the total incorporation of labeled atoms or amino acids into whole multicellular organisms. For instance, the recently introduced (13)C(6)-lysine labeled SILAC mouse allows accurate comparison of protein expression directly in tissue. In this model, only lysine, but not arginine, residues are isotope labeled, as the latter may cause complications to the quantification by in vivo conversion of arginine to proline. The sole labeling of lysines discourages the use of trypsin, as not all peptides will be quantifiable. Therefore, in the initial work Lys-C was used for digestion. Here, we demonstrate that the lysine-directed protease metalloendopeptidase Lys-N is an excellent alternative. As lysine directed peptides generally yield longer and higher charged peptides, alongside the more traditional collision induced dissociation we also implemented electron transfer dissociation in a quantitative stable isotope labeling with amino acid in cell culture workflow for the first time. The utility of these two complementary approaches is highlighted by investigating the differences in protein expression between the left and right ventricle of a mouse heart. Using Lys-N and electron transfer dissociation yielded coverage to a depth of 3749 proteins, which is similar as earlier investigations into the murine heart proteome. In addition, this strategy yields quantitative information on ～ 2000 proteins with a median coverage of four peptides per protein in a single strong cation exchange-liquid chromatography-MS experiment, revealing that the left and right ventricle proteomes are very similar qualitatively as well as quantitatively.     

Cryopreservation of embryonic stem cell‐derived multicellular neural aggregates labeled with micron‐sized particles of iron oxide for magnetic resonance imaging

Magnetic resonance imaging (MRI) provides an effective approach to track labeled pluripotent stem cell (PSC)‐derived neural progenitor cells (NPCs) for neurological disorder treatments after cell labeling with a contrast agent, such as an iron oxide derivative. Cryopreservation of pre‐labeled neural cells, especially in three‐dimensional (3D) structure, can provide a uniform cell population and preserve the stem cell niche for the subsequent applications. In this study, the effects of cryopreservation on PSC‐derived multicellular NPC aggregates labeled with micron‐sized particles of iron oxide (MPIO) were investigated. These NPC aggregates were labeled prior to cryopreservation because labeling thawed cells can be limited by inefficient intracellular uptake, variations in labeling efficiency, and increased culture time before use, minimizing their translation to clinical settings. The results indicated that intracellular MPIO incorporation was retained after cryopreservation (70–80% labeling efficiency), and MPIO labeling had little adverse effects on cell recovery, proliferation, cytotoxicity and neural lineage commitment post‐cryopreservation. MRI analysis showed comparable detectability for the MPIO‐labeled cells before and after cryopreservation indicated by T₂ and T₂* relaxation rates. Cryopreserving MPIO‐labeled 3D multicellular NPC aggregates can be applied in in vivo cell tracking studies and lead to more rapid translation from preservation to clinical implementation. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:510–521, 2015     

Find Pairs: The Module for Protein Quantification of the PeakQuant Software Suite

Abstract Accurate quantification of proteins is one of the major tasks in current proteomics research. To address this issue, a wide range of stable isotope labeling techniques have been developed, allowing one to quantitatively study thousands of proteins by means of mass spectrometry. In this article, the FindPairs module of the PeakQuant software suite is detailed. It facilitates the automatic determination of protein abundance ratios based on the automated analysis of stable isotope-coded mass spectrometric data. Furthermore, it implements statistical methods to determine outliers due to biological as well as technical variance of proteome data obtained in replicate experiments. This provides an important means to evaluate the significance in obtained protein expression data. For demonstrating the high applicability of FindPairs, we focused on the quantitative analysis of proteome data acquired in (14)N/(15)N labeling experiments. We further provide a comprehensive overview of the features of the FindPairs software, and compare these with existing quantification packages. The software presented here supports a wide range of proteomics applications, allowing one to quantitatively assess data derived from different stable isotope labeling approaches, such as (14)N/(15)N labeling, SILAC, and iTRAQ. The software is publicly available at http://www.medizinisches-proteom-center.de/software and free for academic use.     

Advances in quantitative proteomics via stable isotope tagging and mass spectrometry

The high-throughput identification and accurate quantification of proteins are essential components of proteomic strategies for studying cellular functions and processes. Techniques that are largely based on stable isotope protein or peptide labeling and automated tandem mass spectrometry are increasingly being applied in quantitative proteomic studies. Over the past year, significant progress has been made toward improving and diversifying these technologies with respect to the methods for stable isotope labeling, process automation and data processing and analysis. Advances in stable isotope protein labeling and recent biological studies that used stable isotope based quantitative proteomics techniques are reviewed.     

Stable isotope labeling of protein by Kluyveromyces lactis for NMR study

Stable isotope labeling for proteins of interest is an important technique in structural analyses of proteins by NMR spectroscopy. Escherichia coli is one of the most useful protein expression systems for stable isotope labeling because of its high-level protein expression and low costs for isotope-labeling. However, for the expression of proteins with numerous disulfide-bonds and/or post-translational modifications, E. coli systems are not necessarily appropriate. Instead, eukaryotic cells, such as yeast Pichia pastoris, have great potential for successful production of these proteins. The hemiascomycete yeast Kluyveromyces lactis is superior to the methylotrophic yeast P. pastoris in some respects: simple and rapid transformation, good reproducibility of protein expression induction and easy scale-up of culture. In the present study, we established a protein expression system using K. lactis, which enabled the preparation of labeled proteins using glucose and ammonium chloride as a stable isotope source.     

Combination of online enzyme digestion with stable isotope labeling for high‐throughput quantitative proteome analysis

Various enzyme reactors and online enzyme digestion strategies have been developed in recent years. These reactors greatly enhanced the detection sensitivity and proteome coverage in qualitative proteomics. However, these devices have higher rates of miscleavage in protein digestion. Therefore, we investigated the effect of online enzyme digestion on the quantification accuracy of quantitative proteomics using chemical or metabolic isotope labeling approaches. The incomplete digestion would introduce some unexpected variations in comparative quantification when the samples are digested and then chemically isotope labeled in different aliquots. Even when identical protein aliquots are processed on these devices using post‐digestion chemical isotope labeling and the CVs of the ratios controlled to less than 50% in replicate analyses, about 10% of the quantified proteins have a ratio greater than two‐fold, whereas in theory the ratio is 1:1. Interestingly, the incomplete digestion with enzyme reactor is not a problem when metabolic isotope labeling samples were processed because the proteins are isotopically labeled in vivo prior to their simultaneous digestion within the reactor. Our results also demonstrated that both high quantification accuracy and high proteome coverage can be achieved in comparative proteome quantification using online enzyme digestion even when a limited amount of metabolic isotope labeling samples is used (1683 proteins comparatively quantified from 10⁵ Hela cells).     

Turnover of the human proteome: determination of protein intracellular stability by dynamic SILAC

The proteome of any system is a dynamic entity, such that the intracellular concentration of a protein is dictated by the relative rates of synthesis and degradation. In this work, we have analyzed time-dependent changes in the incorporation of a stable amino acid resolved precursor, a protocol we refer to as "dynamic SILAC", using 1-D gel separation followed by in-gel digestion and LC-MS/MS analyses to profile the intracellular stability of almost 600 proteins from human A549 adenocarcinoma cells, requiring multiple measures of the extent of labeling with stable isotope labeled amino acids in a classic label-chase experiment. As turnover rates are acquired, a profile can be built up that allows exploration of the 'dynamic proteome' and of putative features that predispose a protein to a high or a low rate of turnover. Moreover, measurement of the turnover rate of individual components of supramolecular complexes provides a unique insight in processes of protein complex assembly and turnover.     

Accumulation of “Old Proteins” and the Critical Need for MS‐based Protein Turnover Measurements in Aging and Longevity

Aging and age‐related diseases are accompanied by proteome remodeling and progressive declines in cellular machinery required to maintain protein homeostasis (proteostasis), such as autophagy, ubiquitin‐mediated degradation, and protein synthesis. While many studies have focused on capturing changes in proteostasis, the identification of proteins that evade these cellular processes has recently emerged as an approach to studying the aging proteome. With advances in proteomic technology, it is possible to monitor protein half‐lives and protein turnover at the level of individual proteins in vivo. For large‐scale studies, these technologies typically include the use of stable isotope labeling coupled with MS and comprehensive assessment of protein turnover rates. Protein turnover studies have revealed groups of highly relevant long‐lived proteins (LLPs), such as the nuclear pore complexes, extracellular matrix proteins, and protein aggregates. Here, the role of LLPs during aging and age‐related diseases and the methods used to identify and quantify their changes are reviewed. The methods available to conduct studies of protein turnover, used in combination with traditional proteomic methods, will enable the field to perform studies in a systems biology context, as changes in proteostasis may not be revealed in studies that solely measure differential protein abundances.     

A review of quantitative methods for proteomic studies

An overview is provided of six strategies for relative or absolute quantitation of protein abundances that are widely used in proteomic studies. Strengths and limitations are discussed. Four of these involve stable isotope labeling and isotope ratio measurements by mass spectrometry. In another, mass spectra are used to deconvolute overlapping peptide HPLC peaks to provide relative quantitation based on peak areas. The sixth provides relative abundances of proteins based on 2-D gel arrays. It should be noted that these strategies measure peptide and protein abundances, and cannot directly assess changes in regulation or expression.