![]() These peptides are afterwards inspected by liquid chromatography coupled to mass spectrometry, where they are separated by C18 chromatography in a first step. This technique is aimed at identifying proteins in complex mixtures using HPLC in combination with MS/MS.Ī shotgun proteomics workflow starts with the extraction of the proteins to be studied, from a tissue or cell, followed by the digestion step using a digestive enzyme, commonly trypsin, which generates a group of peptides. ![]() ![]() Over recent years, shotgun proteomics has made tremendous progress and has become the most comprehensive and versatile tool for studying proteins in a large scale. Mostly, a workflow of shotgun proteomics is a whole process of mass spectrometry data analysis aiming to address a biological question. The present research tries to revisit and implement a workflow for identifying proteins from tandem mass spectrometry data to complement findings from an existing study addressing the pathophysiology of SUI. While earlier studies have identified the serum proteomic profile in patients with SUI using database search engines, these findings raise a number of questions, including the issue of sensitivity and specificity. Some of these markers, however, were found to be nonspecific or did not affect the pathophysiology, while others showed no association with SUI. The etiology of SUI is still not completely known, although several studies have suggested that serum and tissue proteins can be bioindicators for SUI. SUI has become a widespread disease that affects profoundly the quality of life worldwide. Other risk factors influencing the occurrence of SUI include age, delivery mode, concomitant diabetes mellitus, hereditary factors, ethnicity, neurological illnesses, obesity, Parkinson’s disease, parity, recurrent urinary tract infections, and pregnancy. Age, parity, and family history are other risk factors that have been previously noted. One of the major contributors to stress incontinence is estrogen deficiency, which is thought to increase the chances of leakage by lowering muscle pressure around the urethra. In women, physical changes can also contribute to stress incontinence, including pregnancy, vaginal deliveries, and menopause. This type of urinary incontinence causes sudden spurts of leaked urine when someone coughs, laughs, or sneezes, or with straining and exertion. Stress Urinary Incontinence (SUI) is caused by weakened pelvic floor muscles or a weakened urethral sphincter leading to urine leaks whenever there is sudden physical pressure applied to the abdomen or bladder. This workflow was developed to encourage proteomic researchers to adopt MS-based techniques for accurate analysis and to promote MS as a routine tool to the clinical cohorts. The approach was also sensitive and accurately identified a set of protein that was shown to be markers for categories of diseases associated with the pathophysiology of SUI. Our results suggest that a combination of MS-GF+ and COMET represents the best sensitivity-specificity trade-off, outperforming all other tested combinations. We also compare the relative performance of each combination. We demonstrate how using the combined approach together with high-performance computing techniques can surmount the challenges of complex analyses and extended computing time. We apply our workflow to an existing study addressing the pathophysiology of SUI. Here, we describe our designed and developed workflow for protein identification from tandem mass spectrometry that uses multiple search engines. Therefore, it is critical to have a sensitive and specific analytical approach to identify markers that have been associated with protective and deleterious associations in disease. Although some studies pointed markers that can be bioindicators for SUI, these findings raise the issue of sensitivity and specificity. The pathophysiology of Stress Urinary Incontinence (SUI), caused by a damaged pelvic floor, has become a boundless disease altering the quality of life worldwide. Mass spectrometry (MS) has been applied across several clinical disciplines. Given the considerable time and effort spent in analysis, it is self-evident for a researcher to aspire for rigorous computational analysis and a more confident and accurate peptide/protein identification. A critical stage of shotgun proteomics is database search, a process which attempts to match the experimental spectra to the theoretical one.
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