Shirley – Aug 30th, 2017 – Scientists from Pacific Northwest National Laboratory team recently developed a new open-source software which named Informed-Proteomics. Details being released in Nature Methods, it presents a middle method by comparing with the commonly used top-down proteomics package.
Biomembrane-based proteomics analysis methods can be separated as Bottom-up and Top-down. Top-Down Proteomics, retaining valuable information about post-translational modifications analysis, isotypes and proteolytic processes. With the advances in instrument and sample processing solutions, there are more top-down LC-MS/MS data settings. Top-down mass spectrometry is more complex than traditional bottom-up data. New algorithms and software tools are needed to determine protein morphological recognition and quantification. All these lead to the development of informed-proteomics, which consists of LC-MS feature search algorithm, database search algorithm and interactive result viewer.
Currently, the study of intact proteins has a potential advantage as it can retain the type and location for post-translational modifications analysis of the molecule. However, protein was digested into peptides prior to mass spectrometry in bottom-up proteomics. Although top-down proteomics committed to analyze intact molecules, it is obviously more complicated from a technical point. Payne, one of the authors for this study, said that researchers are still working to develop effective and streamlined methods to solve all the steps from sample preparation and separation to mass spectrometry to back-end informatics.
Humans have about 20,000 protein-coding genes, and each of these 20,000 proteins may contain multiple post-translational modifications and various positions in a variety of combinations, regardless of splice variants and other genetic modifications. Payne noted, the search space will be more than 10 billion proteins. While the continuous improvement of the front-end will help inform the work by improving the quality of data, top-down data analysis still is an essentially challenging business. Researchers for this top-down proteomics have to know how to balance this challenge which may produce more identification, but miss more unknown or unexpected proteoforms.
Except for Informed-Profeomics, there are also several popular top-down programs, such as the ProSightPC software developed by Northwestern University’s Neil Kelleher. ProSightPC can identify an unknown quality modification on a given protein or peptide. This modification may be caused by the loss of a small peptide, homologous substitutions, post-translational modifications, or artificial defects due to sample pretreatment, and do not need to figure out in advance what the modification is. About this software, Payne and his team wrote in the book, ‘restricts the search space to a limited set of proteoforms in a ‘proteome warehouse’, a curated collection derived from known PTMs, splice variants, and single-nucleotide variants.’ The software supports blind search so that researchers can identify unexpected protein forms, but also increase the chance of false positive identification. None of these softwares is perfect, but scientist can take advance of them to find the balance. For further study, if a researcher concerns about the phosphorylation analysis service, then software can be used to place where the potential phosphosite is, not just searching around the places where the modifications might be. As Panye introduced, the informed-proteomics software fits between open and closed researches, the graph-based approach to searching that takes advantage of the fact that many proteoforms only in the placement of that modification instead of what modification is present.
“Whether you place a lysine methylation on lysine number one or on lysine number five, those two proteoforms are similar,” he said. “They might have divergent paths [in terms of the placement], but loss of the components of them are the same. So, if you have a protein which has 10 different placements for [a modification], the graph [method] allows you to explore all of those at one time, as opposed to a separate computation of events, and that gives us some real efficiency savings.”
Panye thinks the results you want to get from this software will be driven by your biological questions. By citing the example of an analysis of patient-derived xenograft (PDX) breast tumors, what their team really interested in the common mutations that are associated with cancer dysfunction, so phosphorylation or methylation or acetylation.
Except for the searching method, the Informed-Proteomics package also includes an LC-MS feature-finding algorithm. It can improve feature detection by aggregating signals in different charge states and across LC elution times. Besides, there is a new set of visualization tools to help verify the results manually.
The object for Proteomics is all the proteins in the body, and the final goal is to find the regular pattern for composition and activity. And Top-Down Proteomics package is another promising strategy for protein identification, analysis, sequence analysis and post-translational modification characterization. We can expect further clinical application based on this proteomics analysis methods.
PTMs refer to the covalent and generally enzymatic modification of proteins during or after protein biosynthesis. It denotes changes in the polypeptide chain as a result of adding distinct chemical moieties to amino acid residues. PTMs are the foundation of governing intricate cellular process, such as cell division, growth, differentiation, signaling and regulation. Also, PTMs are involved in many cellular processes including the maintenance of protein structure and integrity, regulation of metabolism & defense processes, cellular recognition and morphology changes. Consequently, analysis of protein post-translational modifications, including the modification categories and modified sites, is particularly important for study of cell biology and disease diagnostics and prevention.
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