MELISA Institute has first-level technology for the conservation, identification and subsequent analysis of research samples for proteomics and genomics studies. In this framework, a fundamental part of the work of our Corporation is the processing -through bioinformatics tools- of a large amount of biological data generated in our laboratory, thus obtaining clear and concise information.
After processing the samples received from our clients, we deliver a detailed personalized report with the results of the identification and quantification of the proteome or genome, depending on the case.
At MELISA Institute, we constantly update our processes to maintain the highest quality standards. In this first edition of MELISA’s Experts, our Bioinformatics Engineer, Guillermo Nourdin, MSc, explains the advances of our institution in Data Independent Acquisition (DIA) for protein identification through mass spectrometry.
Data Independent Acquisition (DIA) in Mass Spectrometry
In proteomics, the main objective is to identify and quantify the proteins contained in a sample of interest. For these reason, mass spectrometry is a useful tool for these purposes.
Our expert defines Data Independent Acquisition as “an approach to obtaining data in mass spectrometry (MS)”. A strategy capable of focusing on all ion precursors within a m/z range (windows) determined by the mass spectrometer -in our case Bruker's timsTOF Pro-.
In the next stage, the ions are fragmented by a collision-induced dissociation system (CID), a system that consists in the fragmentation of the ions in a gas phase, where they are accelerated by applying an electric potential, increasing their kinetic energy, to then let them collide with neutral molecules (nitrogen). This collision results in a bond break and the fragmentation of the ions into smaller fragments. These fragments are analyzed in the first mass filter (MS1), which in the case of the timsTOF Pro is a quadrupole analyzer, which is capable of detecting and isolating the resulting ions, to later be analyzed in a second mass analyzer (MS2) composed of a TOF (Time of Flight) analyzer.
Our Bioinformatics Engineer explains that, in contrast to other methods, this type of strategy differs from data-dependent acquisition (DDA) in that only the most abundant ions (fixed number of ions) pass through the first mass filter, to then be fractionated into smaller ions, isolated and identified in the second mass analyzer.
The advantage of DIA-based strategies is the ability to identify all precursors in the initial stage, making the technique highly reproducible, in addition to its ability to identify and quantify samples of complex mixtures in a more dynamic range, allowing the application of this technique in comparative research studies.
Pros and Cons
Although the advantages of this technique are high, it still has some problems to solve, such as the adaptation or creation of new software tools involved in the analysis of DIA data that are capable of calculating correct false positive rates in the results.
However, -in Guillermo Nourdin’s opinion- this type of innovation in data acquisition has a promising future, as more and more researchers around the world are working on new bioinformatics techniques to address the issue, thus increasing their performance, accuracy and Protein identification for research purposes.
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