Amine-reactive neutron-encoded labels for highly plexed proteomic quantitation.
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ABSTRACT:
SUBMITTER: Hebert AS
PROVIDER: S-EPMC3820946 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We assemble a versatile molecular scaffold from simple building blocks to create binary and multiplexed stable isotope reagents for quantitative mass spectrometry. Termed Protected Amine Labels (PAL), these reagents offer multiple analytical figures of merit including, (1) robust targeting of peptide N-termini and lysyl side chains, (2) optimal mass spectrometry ionization efficiency through regeneration of primary amines on labeled peptides, (3) an amino acid-based mass tag that incorporates heavy isotopes of carbon, nitrogen, and oxygen to ensure matched physicochemical and MS/MS fragmentation behavior among labeled peptides, and (4) a molecularly efficient architecture, in which the majority of hetero-atom centers can be used to synthesize a variety of nominal mass and sub-Da isotopologue stable isotope reagents. We demonstrate the performance of these reagents in well-established strategies whereby up to four channels of peptide isotopomers, each separated by 4 Da, are quantified in MS-level scans with accuracies comparable to current commercial reagents. In addition, we utilize the PAL scaffold to create isotopologue reagents in which labeled peptide analogs differ in mass based on the binding energy in carbon and nitrogen nuclei, thereby allowing quantification based on MS or MS/MS spectra. We demonstrate accurate quantification for reagents that support 6-plex labeling and propose extension of this scheme to 9-channels based on a similar PAL scaffold. Finally, we provide exemplar data that extend the application of isotopologe-based quantification reagents to medium resolution, quadrupole time-of-flight mass spectrometers.
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Project description:Metabolic labeling of cells using heavy amino acids is most commonly used for relative quantitation; however, partner mass shifts also detail the number of heavy amino acids contained within the precursor species. Here, we use a recently developed metabolic labeling technique, NeuCode (neutron encoding) stable isotope labeling with amino acids in cell culture (SILAC), which produces precursor partners spaced ~40 mDa apart to enable amino acid counting. We implement large scale counting of amino acids through a program, "Amino Acid Counter", which determines the most likely combination of amino acids within a precursor based on NeuCode SILAC partner spacing and filters candidate peptide sequences during a database search using this information. Counting the number of lysine residues for precursors selected for MS/MS decreases the median number of candidate sequences from 44 to 14 as compared to an accurate mass search alone (20 ppm). Furthermore, the ability to co-isolate and fragment NeuCode SILAC partners enables counting of lysines in product ions, and when the information is used, the median number of candidates is reduced to 7. We then demonstrate counting leucine in addition to lysine results in a 6-fold decrease in search space, 43 to 7, when compared to an accurate mass search. We use this scheme to analyze a nanoLC-MS/MS experiment and demonstrate that accurate mass plus lysine and leucine counting reduces the number of candidate sequences to one for ~20% of all precursors selected, demonstrating an ability to identify precursors without MS/MS analysis.
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Project description:We describe a protein quantification method called neutron encoding that exploits the subtle mass differences caused by nuclear binding energy variation in stable isotopes. These mass differences are synthetically encoded into amino acids and incorporated into yeast and mouse proteins via metabolic labeling. Mass spectrometry analysis with high mass resolution (>200,000) reveals the isotopologue-embedded peptide signals, permitting quantification. Neutron encoding will enable highly multiplexed proteome analysis with excellent dynamic range and accuracy.
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Project description:The ability to acquire highly accurate quantitative data is an increasingly important part of any proteomics experiment, whether shotgun or top-down approaches are used. We recently developed a quantitation strategy for peptides based on neutron encoding, or NeuCode SILAC, which uses closely spaced heavy isotope-labeled amino acids and high-resolution mass spectrometry to provide quantitative data. We reasoned that the strategy would also be applicable to intact proteins and could enable robust, multiplexed quantitation for top-down experiments. We used yeast lysate labeled with either (13)C6(15)N2-lysine or (2)H8-lysine, isotopologues of lysine that are spaced 36 mDa apart. Proteins having such close spacing cannot be distinguished during a medium resolution scan, but upon acquiring a high-resolution scan, the two forms of the protein with each amino acid are resolved and the quantitative information revealed. An additional benefit NeuCode SILAC provides for top down is that the spacing of the isotope peaks indicates the number of lysines present in the protein, information that aids in identification. We used NeuCode SILAC to quantify several hundred isotope distributions, manually identify and quantify proteins from 1:1, 3:1, and 5:1 mixed ratios, and demonstrate MS(2)-based quantitation using ETD.
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Project description:We describe a chemical tag for duplex proteome quantification using neutron encoding (NeuCode). The method utilizes the straightforward, efficient, and inexpensive carbamylation reaction. We demonstrate the utility of NeuCode carbamylation by accurately measuring quantitative ratios from tagged yeast lysates mixed in known ratios and by applying this method to quantify differential protein expression in mice fed a either control or high-fat diet.
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Project description:We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, (13)C6(15)N2 and (2)H8, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ~50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo(+) resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.
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Project description:Enzymes that facilitate the local deposition of electron dense reaction products have been widely used as labels in electron microscopy (EM) for the identification of synaptic contacts in neural tissue. Peroxidases, in particular, can efficiently metabolize 3,3'-diaminobenzidine tetrahydrochloride hydrate (DAB) to produce precipitates with high contrast under EM following heavy metal staining, and can be genetically encoded to facilitate the labeling of specific cell-types or organelles. Nevertheless, the peroxidase/DAB method has so far not been reported to work in a multiplexed manner in combination with 3D volume EM techniques (e.g. Serial blockface electron microscopy, SBEM; Focused ion beam electron microscopy, FIBSEM) that are favored for the large-scale ultrastructural assessment of synaptic architecture However, a recently described peroxidase with enhanced enzymatic activity (dAPEX2) can efficienty deposit EM-visible DAB products in thick tissue without detergent treatment opening the possibility for the multiplex labeling of genetically defined cell-types in combination with volume EM methods. Here we demonstrate that multiplexed dAPEX2/DAB tagging is compatible with both FIBSEM and SBEM volume EM approaches and use them to map long-range genetically identified synaptic inputs from the anterior cingulate cortex to the periaqueductal gray in the mouse brain.
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