The Optimized Workflow for Sample Preparation in LC-MS/MS-Based Urine Proteomics (original) (raw)
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PROTEOMICS, 2001
With an emphasis on obtaining a multitude of high quality tandem mass spectrometry spectra for protein identification, instrumental parameters are described for the liquid chromatography-tandem mass spectrometry analysis of trypsin digested unfractionated urine using a hybrid quadrupole-time-of-flight (Q-TOF) mass spectrometer. Precursor acquisition rates of up to 20 distinct precursors/minute in a single analysis were obtained through the use of parallel precursor selection (four precursors/survey period) and variable collision induced dissociation integration time (1 to 6 periods summed). Maximal exploitation of the gas phase fractionated ions was obtained through the use of narrow survey scans and iterative data-dependent analyses incorporating dynamic exclusion. The impact on data fidelity as a product of data-dependent selection of precursor ions from a dynamically excluded field is discussed with regards to sample complexity, precursor selection rates, survey scan range and facile chemical modifications. Operational and post-analysis strategies are presented to restore data confidence and reconcile the greatest number of matched spectra.
Journal of Proteome Research, 2013
Workflows in bottom-up proteomics have traditionally implemented the use of proteolysis during sample preparation; enzymatic digestion is most commonly performed using trypsin. This results in the hydrolysis of peptide bonds forming tryptic peptides, which can then be subjected to LC−MS/MS analysis. While the structure, specificity, and kinetics of trypsin are well characterized, a lack of consensus and understanding has remained regarding fundamental parameters critical to obtaining optimal data from a proteomics experiment. These include the type of trypsin used, pH during digestion, incubation temperature as well as enzyme-to-substrate ratio. Through the use of design of experiments (DOE), we optimized these parameters, resulting in deeper proteome coverage and a greater dynamic range of measurement. The knowledge gained from optimization of a discovery-based proteomics experiment was applied to targeted LC−MS/MS experiments using protein cleavage-isotope dilution mass spectrometry for absolute quantification. We demonstrated the importance of these digest parameters with respect to our limit of detection as well as our ability to acquire more accurate quantitative measurements. Additionally, we were able to quantitatively account for peptide decay observed in previous studies, caused by nonspecific activity of trypsin. The tryptic digest optimization described here has eliminated this previously observed peptide decay as well as provided a greater understanding and standardization for a common but critical sample treatment used across the field of proteomics.
Optimisation of urine sample preparation for shotgun proteomics
Open Chemistry, 2020
Urine reflects the renal function and urinary and kidney systems, but it may also reflect the presence of cancer in other parts of the body. Urine also has potential for providing prognostic information during therapeutic treatments thanks to non-invasive monitoring. A quick and reproducible protein purification procedure is essential to allow data comparison between proteomic studies in urine biomarker discovery. The article describes a simple, reproducible and cheap sample preparation procedure with a maximum protein yield (400 µg) obtained from only 10 mL of urine utilising cut-off filter desalting and digestion. The reported procedure removes yellowish background coloration residues and thus prevents the errors in spectrophotometric protein concentration determination. Different extraction solvents used in the presented procedure point to the possibility of partial elimination of abundant proteins (albumin and keratin family), as well as to the improvement of the sequence covera...
Preparation of urine samples for proteomic analysis
Methods in molecular biology (Clifton, N.J.), 2008
Reproducible procedures for the preparation of protein samples isolated from human urine are essential for meaningful proteomic analyses. Key applications are the discovery of novel proteins or their modifications in the human urine as well as protein biomarker discovery for diseases and drug treatments. The methodology presented here features experimental steps aimed at limiting protein losses because of organic solvent precipitation, effective separation of proteins from other compounds in the human urine and molecular weight-based enrichment of proteins in two distinct fractions. Urinary proteins are separated from cellular debris in the urine via centrifugation, concentrated with 5-kDa-cutoff membrane concentration devices and separated via size exclusion chromatography into fractions with a higher and a lower molecular weight than 30 kDa, respectively. A successive optional affinity removal step for highly abundant plasma proteins is described. Finally, buffer exchange steps us...
Analysis of the urine proteome via a combination of multi-dimensional approaches
PROTEOMICS, 2012
Urine is a biological fluid that is non-invasively and easily harvested, and exhibits high stability from the proteomics point of view. At the downside, the overall low protein content of urine as well as the presence of low-and high-abundance proteins underscores the need for protein enrichment. As a continuation of previous efforts towards the comprehensive characterization of the urine proteome, the current study targeted the mining of urine proteins through the combined application of different protein separation methodologies, specifically, liquid chromatography and preparative electrophoresis along with 1D gel electrophoresis and protein identification by mass spectrometry. In order to enhance comparison and integration of different experimental data sets, the ''standard'' urine sample developed within the European Kidney and Urine Proteomics (EuroKUP) COST Action, was employed. As a contribution to the existing knowledge, we focused on maintaining and providing information about experimental mass of the identified proteins as well as information pertaining to their relative abundance -as allowed by technical limitations -thus providing an initial view of different isoforms representation and facilitating their future characterization. The difficulties in comparing proteome mining data sets become once more evident, underscoring the need for adopting standardized ways for data reporting as well as for potential new approaches for data analysis involving a thorough investigation of received information at the peptide level.
Kidney International, 2004
Background. In the last few years there has been an increasing interest in exploring the human proteome. In particular, efforts have focused on developing strategies to generate reproducible protein maps of normal cells, tissues, and biologic fluids, from which studies can then compare protein expression between different groups (e.g., healthy individuals vs. those with a specific pathologic state).
Analytica Chimica Acta, 2006
Urine, a blood filtrate produced by the urinary system, is an ideal bio-sample and a rich source of biomarkers for diagnostic information. Many components in urine are useful in clinical diagnosis, and urinary proteins can be strong indication for many diseases such as proteinuria, kidney, bladder and urinary tract diseases. To enhance our understanding of urinary proteome, the urine proteins were prepared by different sample cleanup preparation methods and identified by nano-high performance liquid chromatography electrospray ionization tandem mass spectrometry followed by peptide fragmentation pattern. The experimental results demonstrated that a total of 2283 peptides, corresponding to 311 unique proteins, were identified from human urine samples, in which 104 proteins with higher confidence levels. The present study was designed to establish optimal techniques to create a proteomic map of normal urinary proteins. Also, a discussion of novel approaches to urine protein cleanup and constituents is given.
A Review on Mass Spectrometry: Its tools and data analysis for proteomics
2014
With advent of „The Human Genome Project‟ large-scale proteomics has rapidly come to dominate the post genomic age. The Protein Prediction is hard because of its complex structure. Data Analysis is the main issue while predicting the protein. The main problem in proteomics is to estimate the several proteins available in cell structure or tissue sample. Therefore, large scale proteomics technologies are required to measure physical connection of proteins in living organisms. Mass Spectrometry uses the technique to measure mass-to-charge ratio of ion. It‟s an evolving technique for characterization of proteins. A Mass Spectrometer can be more sensitive and specific, also complement with other LC detectors. Liquid Chromatography, unlike gas chromatography is a separation technique which helps to separate wide range of organic compounds from small molecular metabolites to peptides and proteins. This paper addresses the study of data analysis using mass Spectrometry. It also includes th...
Proteome science, 2007
Urine consists of a complex mixture of peptides and proteins and therefore is an interesting source of biomarkers. Because of its high throughput capacity SELDI-TOF-MS is a proteomics technology frequently used in biomarker studies. We compared the performance of seven SELDI protein chip types for profiling of urine using standard chip protocols. Performance was assessed by determining the number of detectable peaks and spot to spot variation for the seven array types and two different matrices: SPA and CHCA. A urine sample taken from one healthy volunteer was applied in eight-fold for each chip type/matrix combination. Data were analyzed for total number of detected peaks (S/N > 5). Spot to spot variation was determined by calculating the average CV of peak intensities. In addition, an inventory was made of detectable peaks with each chip and matrix type. Also the redundancy in peaks detected with the different chip/matrix combinations was determined. A total of 425 peaks (136 n...