Quantitative proteomics
Quantitative proteomics is an
Quantification using spectrophotometry
The concentration of a certain protein in a sample may be determined using spectrophotometric procedures.
Quantification using two dimensional electrophoresis
Two-dimensional gel electrophoresis (2-DE) represents one of the main technologies for quantitative proteomics with advantages and disadvantages. 2-DE provides information about the protein quantity, charge, and mass of the intact protein. It has limitations for the analysis of proteins larger than 150 kDa or smaller than 5kDa and low solubility proteins. Quantitative MS has higher sensitivity but does not provide information about the intact protein.
Classical 2-DE based on post-electrophoretic dye staining has limitations: at least three technical replicates are required to verify the reproducibility.[citation needed] Difference gel electrophoresis (DIGE) uses fluorescence-based labeling of the proteins prior to separation has increased the precision of quantification as well as the sensitivity in the protein detection.[citation needed] Therefore, DIGE represents the current main approach for the 2-DE based study of proteomes.[citation needed]
Quantification using mass spectrometry
Mass spectrometry (MS) represents one of the main technologies for quantitative proteomics with advantages and disadvantages.[4] Quantitative MS has higher sensitivity but can provide only limited information about the intact protein. Quantitative MS has been used for both discovery and targeted proteomic analysis to understand global proteomic dynamics in populations of cells (bulk analysis)[9] or in individual cells (single-cell analysis).[10][11]
Early approaches developed in the 1990s applied isotope-coded affinity tags (ICAT), which uses two reagents with heavy and light isotopes, respectively, and a biotin affinity tag to modify cysteine containing peptides. This technology has been used to label whole Saccharomyces cerevisiae cells,[12] and, in conjunction with mass spectrometry, helped lay the foundation of quantitative proteomics. This approach has been superseded by isobaric mass tags,[9] which are also used for single-cell protein analysis.[13]
Relative and absolute quantification
Mass spectrometry is not inherently quantitative because of differences in the ionization efficiency and/or detectability of the many peptides in a given sample, which has sparked the development of methods to determine relative and absolute abundance of proteins in samples.[3][4] The intensity of a peak in a mass spectrum is not a good indicator of the amount of the analyte in the sample, although differences in peak intensity of the same analyte between multiple samples accurately reflect relative differences in its abundance.
Stable isotope labeling in mass spectrometry
Stable isotope labels
An approach for relative quantification that is more costly and time-consuming, though less sensitive to experimental bias than label-free quantification, entails labeling the samples with
Absolute proteomic quantification using isotopic peptides entails spiking known concentrations of synthetic, heavy
Relative quantification methods include
Absolute quantification is performed using selected reaction monitoring (SRM).
Metal-coded tags
Metal-coded tags (MeCAT) method is based on chemical labeling, but rather than using stable isotopes, different lanthanide ions in macrocyclic complexes are used. The quantitative information comes from inductively coupled plasma MS measurements of the labeled peptides. MeCAT can be used in combination with elemental mass spectrometry
Mass spectrometers have a limited capacity to detect low-abundance peptides in samples with a high dynamic range. The limited duty cycle of mass spectrometers also restricts the collision rate, resulting in an undersampling.[15] Sample preparation protocols represent sources of experimental bias.
Stable isotope labeling with amino acids in cell culture
Stable isotope labeling with amino acids in cell culture (
Traditionally the level of multiplexing in SILAC was limited due to the number of SILAC isotopes available. Recently, a new technique called NeuCode SILAC,[16] has augmented the level of multiplexing achievable with metabolic labeling (up to 4). The NeuCode amino acid method is similar to SILAC but differs in that the labeling only utilizes heavy amino acids. The use of only heavy amino acids eliminates the need for 100% incorporation of amino acids needed for SILAC. The increased multiplexing capability of NeuCode amino acids is from the use of mass defects from extra neutrons in the stable isotopes. These small mass differences however need to be resolved on high resolution mass spectrometers.
One of the main benefits of SILAC is the level of quantitation bias from processing errors is low because heavy and light samples are combined before sample preparation for MS analysis. SILAC and NeuCode SILAC are excellent techniques for detecting small changes in protein levels or post-translational modifications between experimental groups.
Isobaric labeling
Isobaric mass tags (tandem mass tags) are tags that have identical mass and chemical properties that allow heavy and light isotopologues to co-elute together. All mass tags consist of a mass reporter that has a unique number of 13C substitutions, a mass normalizer that has a unique mass that balances the mass of the tag to make all the tags equal in mass and a reactive moiety that crosslinks to the peptides. These tags are designed to cleave at a specific linker region upon high-energy CID, yielding different-sized tags that are then quantitated by LC-MS/MS. Protein or peptide samples prepared from cells, tissues or biological fluids are labeled in parallel with the isobaric mass tags and combined for analysis. Protein quantitation is accomplished by comparing the intensities of the reporter ions in the MS/MS spectra. Three types of tandem mass tags are available with different reactivity: (1) reactive NHS ester which provides high-efficiency, amine-specific labeling (TMTduplex, TMTsixplex, TMT10plex and TMT11plex), (2) reactive iodacetyl function group which labels sulfhydryl-(-SH) groups (iodoTMT) and (3) reactive alkoxyamine functional group which provides covalent labeling of carbonyl-containing compounds (aminoxyTMT).
A key benefit of isobaric labeling over other quantification techniques (e.g. SILAC, ICAT, Label-free) is the increased multiplex capabilities and thus increased throughput potential. The ability to combine and analyze several samples simultaneously in one LC-MS run eliminates the need to analyze multiple data sets and eliminates run-to-run variation. Multiplexing reduces sample processing variability, improves specificity by quantifying the proteins from each condition simultaneously, and reduces turnaround time for multiple samples. The current available isobaric chemical tags facilitate the simultaneous analysis of up to 11 experimental samples.
Label-free quantification in mass spectrometry
One approach for relative quantification is to separately analyze samples by MS and compare the spectra to determine peptide abundance in one sample relative to another, as in label-free strategies. It is generally accepted, that while label-free quantification is the least accurate of the quantification paradigms, it is also inexpensive and reliable when put under heavy statistical validation. There are two different methods of quantification in label-free quantitative proteomics: AUC (area under the curve) and spectral counting.
Methods of label-free quantification
AUC is a method by which for a given peptide spectrum in an LC-MS run, the area under the spectral peak is calculated. AUC peak measurements are linearly proportional to the concentration of protein in a given analyte mixture. Quantification is achieved through ion counts, the measurement of the amount of an ion at a specific retention time.[17] Discretion is required for the standardization of the raw data.[18] High-resolution spectrometer can alleviate problems that arise when trying to make data reproducible, however much of the work regarding normalizing data can be done through software such as OpenMS, and MassView.[19]
Spectral counting involves counting the spectra of an identified protein and then standardizing using some form of normalization.[20] Typically this is done with an abundant peptide mass selection (MS) that is then fragmented and then MS/MS spectra are counted.[17] Multiple samplings of the protein peak is required for accurate estimation of the protein abundance because of the complex physiochemical nature of peptides. Thus, optimization for MS/MS experiments is a constant concern. One alternative to get around this problems is use a data independent technique that cycles between high and low collision energies. Thus a large survey of all possible precursor and product ions is collected. This is limited, however, by the mass spectrometry software's ability to recognize and match peptide patterns of associations between the precursor and product ions.
Applications
Biomedical applications
Quantitative proteomics has distinct applications in the medical field. Especially in the fields of drug and biomarker discovery. LC-MS/MS techniques have started to over take more traditional methods like the western blot and ELISA due to the cumbersome nature of labeling different and separating proteins using these methods and the more global analysis of protein quantification. Mass spectrometry methods are more sensitive to difference in protein structure like post-translational modification and thus can quantify differing modifications to proteins. Quantitative proteomics can circumvent these issues, only needing sequence information to be performed. It can be applied on a global proteome level, or on specifically isolating binding partners in pull-down or affinity purification experiments.[4][22] Disadvantages, however, in sensitivity and analysis time must be kept in consideration.[23]
Drug discovery
Quantitative proteomics has the largest applications in the protein target identification, protein target validation, and toxicity profiling of drug discovery.[24] Drug discovery has been used to investigate protein-protein interaction and, more recently, drug-small molecule interactions, a field of study called chemoproteomics. Thus, it has shown great promise in monitoring side-effects of small drug-like molecules and understanding the efficacy and therapeutic effect of one drug target over another.[25][26] One of the more typical methodologies for absolute protein quantification in drug discovery is the use of LC-MS/MS with multiple reaction monitoring (MRM). The mass spectrometry is typically done by a triple quadrupole MS.[24]
See also
References
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