Skyline (software)

Last updated
Skyline
Developer(s) Brendan X. MacLean et al.
Initial release17 February 2009;15 years ago (2009-02-17)
Stable release
21.2
Written in C#
Operating system Windows
Type Bioinformatics / Mass spectrometry software
License Apache license 2.0
Website Skyline Homepage

Skyline is an open source software for targeted proteomics [1] [2] and metabolomics [3] data analysis. It runs on Microsoft Windows and supports the raw data formats from multiple mass spectrometric vendors. It contains a graphical user interface to display chromatographic data for individual peptide or small molecule analytes.

Contents

Skyline supports multiple workflows including selected reaction monitoring (SRM) / multiple reaction monitoring (MRM), [4] parallel reaction monitoring (PRM), [5] [6] data-independent acquisition (DIA/SWATH) [7] and targeted data-dependent acquisition. [8]

See also

Related Research Articles

<span class="mw-page-title-main">Proteomics</span> Large-scale study of proteins

Proteomics is the large-scale study of proteins. Proteins are vital parts of 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.

<span class="mw-page-title-main">Tandem mass spectrometry</span> Type of mass spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is a technique in instrumental analysis where two or more stages of analysis using one or more mass analyzer are performed with an additional reaction step in between these analyses to increase their abilities to analyse chemical samples. A common use of tandem MS is the analysis of biomolecules, such as proteins and peptides.

<span class="mw-page-title-main">Metabolomics</span> Scientific study of chemical processes involving metabolites

Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.

<span class="mw-page-title-main">Stable isotope labeling by amino acids in cell culture</span>

Stable isotope labeling by/with amino acids in cell culture (SILAC) is a technique based on mass spectrometry that detects differences in protein abundance among samples using non-radioactive isotopic labeling. It is a popular method for quantitative proteomics.

<span class="mw-page-title-main">Ruedi Aebersold</span> Swiss biologist (born 1954)

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.

The Trans-Proteomic Pipeline (TPP) is an open-source data analysis software for proteomics developed at the Institute for Systems Biology (ISB) by the Ruedi Aebersold group under the Seattle Proteome Center. The TPP includes PeptideProphet, ProteinProphet, ASAPRatio, XPRESS and Libra.

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.

A tandem mass tag (TMT) is a chemical label that facilitates sample multiplexing in mass spectrometry (MS)-based quantification and identification of biological macromolecules such as proteins, peptides and nucleic acids. TMT belongs to a family of reagents referred to as isobaric mass tags which are a set of molecules with the same mass, but yield reporter ions of differing mass after fragmentation. The relative ratio of the measured reporter ions represents the relative abundance of the tagged molecule, although ion suppression has a detrimental effect on accuracy. Despite these complications, TMT-based proteomics has been shown to afford higher precision than Label-free quantification. In addition to aiding in protein quantification, TMT tags can also increase the detection sensitivity of certain highly hydrophilic analytes, such as phosphopeptides, in RPLC-MS analyses.

<span class="mw-page-title-main">Protein mass spectrometry</span> Application of mass spectrometry

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.

<span class="mw-page-title-main">Top-down proteomics</span>

Top-down proteomics is a method of protein identification that either uses an ion trapping mass spectrometer to store an isolated protein ion for mass measurement and tandem mass spectrometry (MS/MS) analysis or other protein purification methods such as two-dimensional gel electrophoresis in conjunction with MS/MS. Top-down proteomics is capable of identifying and quantitating unique proteoforms through the analysis of intact proteins. The name is derived from the similar approach to DNA sequencing. During mass spectrometry intact proteins are typically ionized by electrospray ionization and trapped in a Fourier transform ion cyclotron resonance, quadrupole ion trap or Orbitrap mass spectrometer. Fragmentation for tandem mass spectrometry is accomplished by electron-capture dissociation or electron-transfer dissociation. Effective fractionation is critical for sample handling before mass-spectrometry-based proteomics. Proteome analysis routinely involves digesting intact proteins followed by inferred protein identification using mass spectrometry (MS). Top-down MS (non-gel) proteomics interrogates protein structure through measurement of an intact mass followed by direct ion dissociation in the gas phase.

<span class="mw-page-title-main">Quantitative proteomics</span> Analytical chemistry technique

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.

<span class="mw-page-title-main">Isobaric tag for relative and absolute quantitation</span>

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.

<span class="mw-page-title-main">Capillary electrophoresis–mass spectrometry</span>

Capillary electrophoresis–mass spectrometry (CE–MS) is an analytical chemistry technique formed by the combination of the liquid separation process of capillary electrophoresis with mass spectrometry. CE–MS combines advantages of both CE and MS to provide high separation efficiency and molecular mass information in a single analysis. It has high resolving power and sensitivity, requires minimal volume and can analyze at high speed. Ions are typically formed by electrospray ionization, but they can also be formed by matrix-assisted laser desorption/ionization or other ionization techniques. It has applications in basic research in proteomics and quantitative analysis of biomolecules as well as in clinical medicine. Since its introduction in 1987, new developments and applications have made CE-MS a powerful separation and identification technique. Use of CE–MS has increased for protein and peptides analysis and other biomolecules. However, the development of online CE–MS is not without challenges. Understanding of CE, the interface setup, ionization technique and mass detection system is important to tackle problems while coupling capillary electrophoresis to mass spectrometry.

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.

<span class="mw-page-title-main">Selected reaction monitoring</span> Tandem mass spectrometry method

Selected reaction monitoring (SRM), also called multiple reaction monitoring (MRM), is a method used in tandem mass spectrometry in which an ion of a particular mass is selected in the first stage of a tandem mass spectrometer and an ion product of a fragmentation reaction of the precursor ions is selected in the second mass spectrometer stage for detection.

<span class="mw-page-title-main">Isobaric labeling</span>

Isobaric labeling is a mass spectrometry strategy used in quantitative proteomics. Peptides or proteins are labeled with chemical groups that have identical mass (isobaric), but vary in terms of distribution of heavy isotopes in their structure. These tags, commonly referred to as tandem mass tags, are designed so that the mass tag is cleaved at a specific linker region upon high-energy CID (HCD) during tandem mass spectrometry yielding reporter ions of different masses. The most common isobaric tags are amine-reactive tags. However, tags that react with cysteine residues and carbonyl groups have also been described. These amine-reactive groups go through N-hydroxysuccinimide (NHS) reactions, which are based around three types of functional groups. Isobaric labeling methods include tandem mass tags (TMT), isobaric tags for relative and absolute quantification (iTRAQ), mass differential tags for absolute and relative quantification, and dimethyl labeling. TMTs and iTRAQ methods are most common and developed of these methods. Tandem mass tags have a mass reporter region, a cleavable linker region, a mass normalization region, and a protein reactive group and have the same total mass.

<span class="mw-page-title-main">Single-cell analysis</span> Testbg biochemical processes and reactions in an individual cell

In the field of cellular biology, single-cell analysis and subcellular analysis is the study of genomics, transcriptomics, proteomics, metabolomics and cell–cell interactions at the single cell level. The concept of single-cell analysis originated in the 1970s. Before the discovery of heterogeneity, single-cell analysis mainly referred to the analysis or manipulation of an individual cell in a bulk population of cells at a particular condition using optical or electronic microscope. To date, due to the heterogeneity seen in both eukaryotic and prokaryotic cell populations, analyzing a single cell makes it possible to discover mechanisms not seen when studying a bulk population of cells. Technologies such as fluorescence-activated cell sorting (FACS) allow the precise isolation of selected single cells from complex samples, while high throughput single cell partitioning technologies, enable the simultaneous molecular analysis of hundreds or thousands of single unsorted cells; this is particularly useful for the analysis of transcriptome variation in genotypically identical cells, allowing the definition of otherwise undetectable cell subtypes. The development of new technologies is increasing our ability to analyze the genome and transcriptome of single cells, as well as to quantify their proteome and metabolome. Mass spectrometry techniques have become important analytical tools for proteomic and metabolomic analysis of single cells. Recent advances have enabled quantifying thousands of protein across hundreds of single cells, and thus make possible new types of analysis. In situ sequencing and fluorescence in situ hybridization (FISH) do not require that cells be isolated and are increasingly being used for analysis of tissues.

Stable isotope standards and capture by anti-peptide antibodies (SISCAPA) is a mass spectrometry method for measuring the amount of a protein in a biological sample.

References

  1. MacLean B, Tomazela DM, et al. (2010). "Skyline: an open source document editor for creating and analyzing targeted proteomics experiments". Bioinformatics. 26 (7): 966–8. doi:10.1093/bioinformatics/btq054. PMC   2844992 . PMID   20147306.
  2. Pino L, et al. (2017). "The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics". Mass Spectrometry Reviews. 39 (3): 229–244. doi:10.1002/mas.21540. PMC   5799042 . PMID   28691345.
  3. Adams K, et al. (2020). "Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics". Journal of Proteome Research. 19 (4): 1447–1458. doi:10.1021/acs.jproteome.9b00640. PMC   7127945 . PMID   31984744.
  4. Abbatiello S, et al. (2015). "Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma". Mol Cell Proteomics. 14 (9): 2357–74. doi: 10.1074/mcp.M114.047050 . PMC   4563721 . PMID   25693799.
  5. Sherrod S, et al. (2012). "Label-free quantitation of protein modifications by pseudo selected reaction monitoring with internal reference peptides". Journal of Proteome Research. 11 (6): 3467–79. doi:10.1021/pr201240a. PMC   3368409 . PMID   22559222.
  6. Schilling B, et al. (2015). "Multiplexed, Scheduled, High-Resolution Parallel Reaction Monitoring on a Full Scan QqTOF Instrument with Integrated Data-Dependent and Targeted Mass Spectrometric Workflows". Analytical Chemistry. 87 (20): 10222–9. doi:10.1021/acs.analchem.5b02983. PMC   5677521 . PMID   26398777.
  7. Navarro P, et al. (2016). "A multicenter study benchmarks software tools for label-free proteome quantification". Nature Biotechnology. 34 (11): 1130–1136. doi:10.1038/nbt.3685. PMC   5120688 . PMID   27701404.
  8. Schilling B, et al. (2012). "Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation". Mol Cell Proteomics. 11 (5): 202–214. doi: 10.1074/mcp.M112.017707 . PMC   3418851 . PMID   22454539.