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Proteomics is the large-scale study of proteins. Proteins are vital macromolecules of all living organisms, with many functions such as the formation of structural fibers of muscle tissue, enzymatic digestion of food, or synthesis and replication of DNA. In addition, other kinds of proteins include antibodies that protect an organism from infection, and hormones that send important signals throughout the body.
Peptide mass fingerprinting (PMF), also known as protein fingerprinting, is an analytical technique for protein identification in which the unknown protein of interest is first cleaved into smaller peptides, whose absolute masses can be accurately measured with a mass spectrometer such as MALDI-TOF or ESI-TOF. The method was developed in 1993 by several groups independently. The peptide masses are compared to either a database containing known protein sequences or even the genome. This is achieved by using computer programs that translate the known genome of the organism into proteins, then theoretically cut the proteins into peptides, and calculate the absolute masses of the peptides from each protein. They then compare the masses of the peptides of the unknown protein to the theoretical peptide masses of each protein encoded in the genome. The results are statistically analyzed to find the best match.
Rudolf Aebersold is a Swiss biologist, regarded as a pioneer in the fields of proteomics and systems biology. He has primarily researched techniques for measuring proteins in complex samples, in many cases via mass spectrometry. Ruedi Aebersold is a professor of Systems biology at the Institute of Molecular Systems Biology (IMSB) in ETH Zurich. He was one of the founders of the Institute for Systems Biology in Seattle, Washington, United States where he previously had a research group.
Mascot is a software search engine that uses mass spectrometry data to identify proteins from peptide sequence databases. Mascot is widely used by research facilities around the world. Mascot uses a probabilistic scoring algorithm for protein identification that was adapted from the MOWSE algorithm. Mascot is freely available to use on the website of Matrix Science. A license is required for in-house use where more features can be incorporated.
Protein mass spectrometry refers to the application of mass spectrometry to the study of proteins. Mass spectrometry is an important method for the accurate mass determination and characterization of proteins, and a variety of methods and instrumentations have been developed for its many uses. Its applications include the identification of proteins and their post-translational modifications, the elucidation of protein complexes, their subunits and functional interactions, as well as the global measurement of proteins in proteomics. It can also be used to localize proteins to the various organelles, and determine the interactions between different proteins as well as with membrane lipids.
Shotgun proteomics refers to the use of bottom-up proteomics techniques in identifying proteins in complex mixtures using a combination of high performance liquid chromatography combined with mass spectrometry. The name is derived from shotgun sequencing of DNA which is itself named after the rapidly expanding, quasi-random firing pattern of a shotgun. The most common method of shotgun proteomics starts with the proteins in the mixture being digested and the resulting peptides are separated by liquid chromatography. Tandem mass spectrometry is then used to identify the peptides.
Bottom-up proteomics is a common method to identify proteins and characterize their amino acid sequences and post-translational modifications by proteolytic digestion of proteins prior to analysis by mass spectrometry. The major alternative workflow used in proteomics is called top-down proteomics where intact proteins are purified prior to digestion and/or fragmentation either within the mass spectrometer or by 2D electrophoresis. Essentially, bottom-up proteomics is a relatively simple and reliable means of determining the protein make-up of a given sample of cells, tissues, etc.
Quantitative proteomics is an analytical chemistry technique for determining the amount of proteins in a sample. The methods for protein identification are identical to those used in general proteomics, but include quantification as an additional dimension. Rather than just providing lists of proteins identified in a certain sample, quantitative proteomics yields information about the physiological differences between two biological samples. For example, this approach can be used to compare samples from healthy and diseased patients. Quantitative proteomics is mainly performed by two-dimensional gel electrophoresis (2-DE), preparative native PAGE, or mass spectrometry (MS). However, a recent developed method of quantitative dot blot (QDB) analysis is able to measure both the absolute and relative quantity of an individual proteins in the sample in high throughput format, thus open a new direction for proteomic research. In contrast to 2-DE, which requires MS for the downstream protein identification, MS technology can identify and quantify the changes.
Isobaric tags for relative and absolute quantitation (iTRAQ) is an isobaric labeling method used in quantitative proteomics by tandem mass spectrometry to determine the amount of proteins from different sources in a single experiment. It uses stable isotope labeled molecules that can be covalent bonded to the N-terminus and side chain amines of proteins.
Label-free quantification is a method in mass spectrometry that aims to determine the relative amount of proteins in two or more biological samples. Unlike other methods for protein quantification, label-free quantification does not use a stable isotope containing compound to chemically bind to and thus label the protein.
An isotope-coded affinity tag (ICAT) is an in-vitro isotopic labeling method used for quantitative proteomics by mass spectrometry that uses chemical labeling reagents. These chemical probes consist of three elements: a reactive group for labeling an amino acid side chain, an isotopically coded linker, and a tag for the affinity isolation of labeled proteins/peptides. The samples are combined and then separated through chromatography, then sent through a mass spectrometer to determine the mass-to-charge ratio between the proteins. Only cysteine containing peptides can be analysed. Since only cysteine containing peptides are analysed, often the post translational modification is lost.
OpenMS is an open-source project for data analysis and processing in mass spectrometry and is released under the 3-clause BSD licence. It supports most common operating systems including Microsoft Windows, MacOS and Linux.
A peptide spectral library is a curated, annotated and non-redundant collection/database of LC-MS/MS peptide spectra. One essential utility of a peptide spectral library is to serve as consensus templates supporting the identification of peptides and proteins based on the correlation between the templates with experimental spectra.
Proteogenomics is a field of biological research that utilizes a combination of proteomics, genomics, and transcriptomics to aid in the discovery and identification of peptides. Proteogenomics is used to identify new peptides by comparing MS/MS spectra against a protein database that has been derived from genomic and transcriptomic information. Proteogenomics often refers to studies that use proteomic information, often derived from mass spectrometry, to improve gene annotations. The utilization of both proteomics and genomics data alongside advances in the availability and power of spectrographic and chromatographic technology led to the emergence of proteogenomics as its own field in 2004.
In bio-informatics, a peptide-mass fingerprint or peptide-mass map is a mass spectrum of a mixture of peptides that comes from a digested protein being analyzed. The mass spectrum serves as a fingerprint in the sense that it is a pattern that can serve to identify the protein. The method for forming a peptide-mass fingerprint, developed in 1993, consists of isolating a protein, breaking it down into individual peptides, and determining the masses of the peptides through some form of mass spectrometry. Once formed, a peptide-mass fingerprint can be used to search in databases for related protein or even genomic sequences, making it a powerful tool for annotation of protein-coding genes.
Systematic Protein Investigative Research Environment (SPIRE) provides web-based experiment-specific mass spectrometry (MS) proteomics analysis in order to identify proteins and peptides, and label-free expression and relative expression analyses. SPIRE provides a web-interface and generates results in both interactive and simple data formats.
MassMatrix is a mass spectrometry data analysis software that uses a statistical model to achieve increased mass accuracy over other database search algorithms. This search engine is set apart from others dues to its ability to provide extremely efficient judgement between true and false positives for high mass accuracy data that has been obtained from present day mass spectrometer instruments. It is useful for identifying disulphide bonds in tandem mass spectrometry data. This search engine is set apart from others due to its ability to provide extremely efficient judgement between true and false positives for high mass accuracy data that has been obtained from present day mass spectrometer instruments.
In mass spectrometry, data-independent acquisition (DIA) is a method of molecular structure determination in which all ions within a selected m/z range are fragmented and analyzed in a second stage of tandem mass spectrometry. Tandem mass spectra are acquired either by fragmenting all ions that enter the mass spectrometer at a given time or by sequentially isolating and fragmenting ranges of m/z. DIA is an alternative to data-dependent acquisition (DDA) where a fixed number of precursor ions are selected and analyzed by tandem mass spectrometry.
Ancient proteins are complex mixtures and the term palaeoproteomics is used to characterise the study of proteomes in the past. Ancients proteins have been recovered from a wide range of archaeological materials, including bones, teeth, eggshells, leathers, parchments, ceramics, painting binders and well-preserved soft tissues like gut intestines. These preserved proteins have provided valuable information about taxonomic identification, evolution history (phylogeny), diet, health, disease, technology and social dynamics in the past.
References
- ↑ TPP 5.0.0 Release is Available
- ↑ Software:PeptideProphet - SPCTools
- ↑ Software:ProteinProphet - SPCTools
- ↑ Keller, A; Nesvizhskii, A; Kolker, E; Aebersold, R. (2002). "Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search". Anal Chem. 74 (20): 5383–5392. doi:10.1021/ac025747h. PMID 12403597.
- ↑ Choi, Hyungwon; Ghosh, Debashis; Nesvizhskii, Alexey I. (2008). "Statistical Validation of Peptide Identifications in Large-Scale Proteomics Using the Target-Decoy Database Search Strategy and Flexible Mixture Modeling" (PDF). Journal of Proteome Research. 7 (1): 286–292. doi:10.1021/pr7006818. ISSN 1535-3893. PMID 18078310.
- ↑ Nesvizhskii AI, Keller A, Kolker E, Aebersold R. (2003) "A statistical model for identifying proteins by tandem mass spectrometry." Anal Chem 75:4646-58
- ↑ Reiter, L.; Claassen, M.; Schrimpf, SP.; Jovanovic, M.; Schmidt, A.; Buhmann, JM.; Hengartner, MO.; Aebersold, R. (Nov 2009). "Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry". Mol Cell Proteomics. 8 (11): 2405–17. doi: 10.1074/mcp.M900317-MCP200 . PMC 2773710 . PMID 19608599.
- ↑ Software:SpectraST - SPCTools