Quantification of peptide m/z distributions from 13C-labeled cultures with high-resolution mass spectrometry.
ABSTRACT: Isotopic labeling studies of primary metabolism frequently utilize GC/MS to quantify (13)C in protein-hydrolyzed amino acids. During processing some amino acids are degraded, which reduces the size of the measurement set. The advent of high-resolution mass spectrometers provides a tool to assess molecular masses of peptides with great precision and accuracy and computationally infer information about labeling in amino acids. Amino acids that are isotopically labeled during metabolism result in labeled peptides that contain spatial and temporal information that is associated with the biosynthetic origin of the protein. The quantification of isotopic labeling in peptides can therefore provide an assessment of amino acid metabolism that is specific to subcellular, cellular, or temporal conditions. A high-resolution orbital trap was used to quantify isotope labeling in peptides that were obtained from unlabeled and isotopically labeled soybean embryos and Escherichia coli cultures. Standard deviations were determined by estimating the multinomial variance associated with each element of the m/z distribution. Using the estimated variance, quantification of the m/z distribution across multiple scans was achieved by a nonlinear fitting approach. Observed m/z distributions of uniformly labeled E. coli peptides indicated no significant differences between observed and simulated m/z distributions. Alternatively, amino acid m/z distributions obtained from GC/MS were convolved to simulate peptide m/z distributions but resulted in distinct profiles due to the production of protein prior to isotopic labeling. The results indicate that peptide mass isotopologue measurements faithfully represent mass distributions, are suitable for quantification of isotope-labeling-based studies, and provide additional information over existing methods.
Project description:Stable incorporation of labeled amino acids in cell culture is a simple approach to label proteins in vivo for mass spectrometric quantification. Full incorporation of isotopically heavy amino acids facilitates accurate quantification of proteins from different cultures, yet analysis methods for determination of incorporation are cumbersome and time-consuming. We present QTIPS, Quantification by Total Identified Peptides for SILAC, a straightforward, accurate method to determine the level of heavy amino acid incorporation throughout a population of peptides detected by mass spectrometry. Using QTIPS, we show that the incorporation of heavy amino acids in baker's yeast is unaffected by the use of prototrophic strains, indicating that auxotrophy is not a requirement for SILAC experiments in this organism. This method has general utility for multiple applications where isotopic labeling is used for quantification in mass spectrometry.
Project description:The relative quantification of proteins is one of the major techniques used to elucidate physiological reactions. Because it allows one to avoid artifacts due to chemical labeling, the metabolic introduction of heavy isotopes into proteins and peptides is the preferred method for relative quantification. For eukaryotic cells, stable isotope labeling by amino acids in cell culture (SILAC) has become the gold standard and can be readily applied in a vast number of scenarios. In the microbial realm, with its highly versatile metabolic capabilities, SILAC is often not feasible, and the use of other (13)C or (15)N labeled substrates might not be practical. Here, the incorporation of heavy sulfur isotopes is shown to be a useful alternative. We introduce (34)S stable isotope labeling of amino acids for quantification and the corresponding tools required for spectra extraction and disintegration of the isotopic overlaps caused by the small mass shift. As proof of principle, we investigated the proteomic changes related to naphthalene degradation in P. fluorescens ATCC 17483 and uncovered a specific oxidative-stress-like response.
Project description: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.
Project description:Stable isotope labeling by essential nutrients in cell culture (SILEC) was recently developed to generate isotopically labeled coenzyme A (CoA) and short-chain acyl-CoA thioesters. This was accomplished by modifying the widely used technique of stable isotope labeling by amino acids in cell culture to include [(13)C(3)(15)N]-pantothenate (vitamin B(5)), a CoA precursor, instead of the isotopically labeled amino acids. The lack of a de novo pantothenate synthesis pathway allowed for efficient and near-complete labeling of the measured CoA species. This protocol provides a step-by-step approach for generating stable isotope-labeled short-chain acyl-CoA internal standards in mammalian and insect cells as well as instructions on how to use them in stable isotope dilution mass spectrometric-based analyses. Troubleshooting guidelines, as well as a list of unlabeled and labeled CoA species, are also included. This protocol represents a prototype for generating stable isotope internal standards from labeled essential nutrients such as pantothenate. The generation and use of SILEC standards takes approximately 2-3 weeks.
Project description:We have developed a complete system for the isotopic labeling, fractionation, and automated quantification of differentially expressed peptides that significantly facilitates candidate biomarker discovery. We describe a new stable mass tagging reagent pair, (12)C(6)- and (13)C(6)-phenyl isocyanate (PIC), that offers significant advantages over currently available tags. Peptides are labeled predominantly at their amino termini and exhibit elution profiles that are independent of label isotope. Importantly, PIC-labeled peptides have unique neutral-mass losses upon CID fragmentation that enable charge state and label isotope identification and, thereby, decouple the sequence identification from the quantification of candidate biomarkers. To exploit these properties, we have coupled peptide fractionation protocols with a Thermo LTQ-XL LC-MS(2) data acquisition strategy and a suite of automated spectrum analysis software that identifies quantitative differences between labeled samples. This approach, dubbed the PICquant platform, is independent of protein sequence identification and excludes unlabeled peptides that otherwise confound biomarker discovery. Application of the PICquant platform to a set of complex clinical samples showed that the system allows rapid identification of peptides that are differentially expressed between control and patient groups.
Project description:Stable isotope labeling is widely used to encode and quantify proteins in mass-spectrometry-based proteomics. We compared metabolic labeling with stable isotope labeling by amino acids in cell culture (SILAC) and chemical labeling by stable isotope dimethyl labeling and find that they have comparable accuracy and quantitative dynamic range in unfractionated proteome analyses and affinity pull-down experiments. Analyzing SILAC- and dimethyl-labeled samples together in single liquid chromatography-mass spectrometric analyses minimizes differences under analytical conditions, allowing comparisons of quantitative errors introduced during sample processing. We find that SILAC is more reproducible than dimethyl labeling. Because proteins from metabolically labeled populations can be combined before proteolytic digestion, SILAC is particularly suited to studies with extensive sample processing, such as fractionation and enrichment of peptides with post-translational modifications. We compared both methods in pull-down experiments using a kinase inhibitor, dasatinib, and tagged GRB2-SH2 protein as affinity baits. We describe a StageTip dimethyl-labeling protocol that we applied to in-solution and in-gel protein digests. Comparing the impact of post-digest isotopic labeling on quantitative accuracy, we demonstrate how specific experimental designs can benefit most from metabolic labeling approaches like SILAC and situations where chemical labeling by stable isotope-dimethyl labeling can be a practical alternative.
Project description:Stable isotope dilution mass spectrometry (MS) represents the gold standard for quantification of endogenously formed cellular metabolites. Although coenzyme A (CoA) and acyl-CoA thioester derivatives are central players in numerous metabolic pathways, the lack of a commercially available isotopically labeled CoA limits the development of rigorous MS-based methods. In this study, we adapted stable isotope labeling by amino acids in cell culture (SILAC) methodology to biosynthetically generate stable isotope labeled CoA and thioester analogues for use as internal standards in liquid chromatography/multiple reaction monitoring mass spectrometry (LC/MRM-MS) assays. This was accomplished by incubating murine hepatocytes (Hepa 1c1c7) in media in which pantothenate (a precursor of CoA) was replaced with [(13)C(3)(15)N(1)]-pantothenate. Efficient incorporation into various CoA species was optimized to >99% [(13)C(3)(15)N(1)]-pantothenate after three passages of the murine cells in culture. Charcoal-dextran-stripped fetal bovine serum (FBS) was found to be more efficient for serum supplementation than dialyzed or undialyzed FBS, due to lower contaminating unlabeled pantothenate content. Stable isotope labeled CoA species were extracted and utilized as internal standards for CoA thioester analysis in cell culture models. This methodology of stable isotope labeling by essential nutrients in cell culture (SILEC) can serve as a paradigm for using vitamins and other essential nutrients to generate stable isotope standards that cannot be readily synthesized.
Project description:Phenotype in multicellular organisms is the consequence of dynamic metabolic events that occur in a spatially dependent fashion. This spatial and temporal complexity presents challenges for investigating metabolism; creating a need for improved methods that effectively probe biochemical events such as amino acid biosynthesis. Isotopic labeling can provide a temporal-spatial recording of metabolic events through, for example, the description of enriched amino acids in the protein pool. Proteins are therefore an important readout of metabolism and can be assessed with modern mass spectrometers. We compared the measurement of isotopic labeling in MS2 spectra obtained from tandem mass spectrometry under either higher energy collision dissociation (HCD) or collision induced dissociation (CID) at varied energy levels. Developing soybean embryos cultured with or without 13C-labeled substrates, and Escherichia coli MG1655 enriched by feeding 7% uniformly labeled glucose served as a source of biological material for protein evaluation. CID with low energies resulted in a disproportionate amount of heavier isotopologues remaining in the precursor isotopic distribution. HCD resulted in fewer quantifiable products; however deviation from predicted distributions were small relative to the CID-based comparisons. Fragment ions have the potential to provide information on the labeling of amino acids in peptides, but our results indicate that without further development the use of this readout in quantitative methods such as metabolic flux analysis is limited.
Project description:Stable heavy-isotope labeling is commonly used in quantitative proteomics. Several common techniques incorporate deuterium (2 H) as the heavy isotopic label using reductive amination with formaldehyde. Compared with alternatives, dimethyl labeling reagents are inexpensive and the labeling chemistry is simple and rapid. However, the substitution of hydrogen by deuterium can introduce subtle changes in peptides' polarities, leading to a shift in chromatographic retention times between deuterated and nondeuterated peptides that can lead to quantification deviations. Capillary zone electrophoresis has emerged as a complementary separation for ESI-MS-based proteomics, including targeted and quantitative approaches. The extent to which the deuterium isotope effect impacts CZE-based proteomics, which separates peptides based on their S/N ratios, has not been investigated. To address this issue, CZE was used to analyze dimethyl labeled E. coli tryptic digests in 100 min single-shot analyses. The median migration time shift was 0.1 s for light versus heavy labeled peptides, which is 2.5% of the peak width. For comparison, nUHPLC-ESI-MS/MS was used to analyze the same sample. In UPLC, deuterated peptides tended to elute earlier than nondeuterated peptides, with a retention shift of 3 s for light versus heavy labeled peptides, which is roughly half the peak width. This shift in separation time did not have a significant effect on quantitation for either method for equal mixing ratios of the light-intermediate-heavy isotope labeled samples.
Project description:Isobaric peptide termini labeling (IPTL) is an attractive protein quantification method because it provides more accurate and reliable quantification information than traditional isobaric labeling methods (e.g., TMT and iTRAQ) by making use of the entire fragment-ion series instead of only a single reporter ion. The multiplexing capacity of published IPTL implementations is, however, limited to three. Here, we present a selective maleylation-directed isobaric peptide termini labeling (SMD-IPTL) approach for quantitative proteomics of LysC protein digestion. SMD-IPTL extends the multiplexing capacity to 4-plex with the potential for higher levels of multiplexing using commercially available 13C/15N labeled amino acids. SMD-IPTL is achieved in a one-pot reaction in three consecutive steps: (1) selective maleylation at the N-terminus; (2) labeling at the ?-NH2 group of the C-terminal Lys with isotopically labeled acetyl-alanine; (3) thiol Michael addition of an isotopically labeled acetyl-cysteine at the maleylated N-terminus. The isobarically labeled peptides are fragmented into sets of b- and y-ion clusters upon LC-MS/MS, which convey not only sequence information but also quantitative information for every labeling channel and avoid the issue of ratio distortion observed with reporter-ion-based approaches. We demonstrate the SMD-IPTL approach with a 4-plex labeled sample of bovine serum albumin (BSA) and yeast lysates mixed at different ratios. With the use of SMD-IPTL for labeling and a narrow precursor isolation window of 0.8 Th with an offset of -0.2 Th, accurate ratios were measured across a 10-fold mixing range of BSA in a background of yeast proteome. With the yeast proteins mixed at ratios of 1:5:1:5, BSA was detected at ratios of 0.94:2.46:4.70:9.92 when spiked at 1:2:5:10 ratios with an average standard deviation of peptide ratios of 0.34.