A database of mass spectrometric assays for the yeast proteome

Proteomics, 2009

Precise and accurate protein quantification is critical to many areas of proteomics. Antibody-based approaches are costly and time-consuming to develop, consequently, there is considerable interest in alternative quantitative methods that are versatile and can be implemented without the considerable delays associated with antibody development and characterization. Approaches based on MS have therefore attracted considerable attention and are now frequently touted as the most practical and powerful of all options. Nevertheless, there are serious limitations associated with quantifying a protein based on tandem mass analysis of one or two peptides generated by either chemical or enzymatic cleavage. In an accompanying Viewpoint article, Molloy and coworkers point out that selectivity is not necessarily guaranteed despite the power of SRM. Here we address an additional concern that can also compromise specificity. In complex mammalian systems, multiple proteins can serve as precursors of a single peptide and consequently, depending on the peptide(s) selected, protein levels may be significantly under- or overestimated.

Molecular & Cellular Proteomics, 2011

Proteomics is gradually complementing large shotgun qualitative studies with hypothesis-driven quantitative experiments. Targeted analyses performed on triple quadrupole instruments in selected reaction monitoring (SRM) mode are characterized by a high degree of selectivity and low limit of detection; however the concurrent analysis of multiple analytes occurs at the expense of sensitivity due to reduced dwell time and/or selectivity due to limitation to a few transitions. A new data acquisition paradigm is presented, in which SRM is performed in two ways to simultaneously quantify and confirm the identity of the targeted peptides. A first set of primary transitions is continuously monitored during a predetermined elution time window to precisely quantify each peptide. In addition, a set of six to eight transitions are acquired in a data dependent event, triggered when all the primary transitions exceed a preset threshold.

Molecular & Cellular Proteomics, 2012

For many research questions in modern molecular and systems biology, information about absolute protein quantities is imperative. This information includes, for example, kinetic modeling of processes, protein turnover determinations, stoichiometric investigations of protein complexes, or quantitative comparisons of different proteins within one sample or across samples. To date, the vast majority of proteomic studies are limited to providing relative quantitative comparisons of protein levels between limited numbers of samples. Here we describe and demonstrate the utility of a targeting MS technique for the estimation of absolute protein abundance in unlabeled and nonfractionated cell lysates. The method is based on selected reaction monitoring (SRM) mass spectrometry and the "best flyer" hypothesis, which assumes that the specific MS signal intensity of the most intense tryptic peptides per protein is approximately constant throughout a whole proteome. SRM-targeted best flyer peptides were selected for each protein from the peptide precursor ion signal intensities from directed MS data. The most intense transitions per peptide were selected from full MS/MS scans of crude synthetic analogs. We used Monte Carlo cross-validation to systematically investigate the accuracy of the technique as a function of the number of measured best flyer peptides and the number of SRM transitions per peptide. We found that a linear model based on the two most intense transitions of the three best flying peptides per proteins (TopPep3/TopTra2) generated optimal results with a cross-correlated mean fold error of 1.8 and a squared Pearson coefficient R(2) of 0.88. Applying the optimized model to lysates of the microbe Leptospira interrogans, we detected significant protein abundance changes of 39 target proteins upon antibiotic treatment, which correlate well with literature values. The described method is generally applicable and exploits the inherent performance advantages of SRM, such as high sensitivity, selectivity, reproducibility, and dynamic range, and estimates absolute protein concentrations of selected proteins at minimized costs.

Methods In Molecular Biology, 2009

Proteomics may be defined as the systematic analysis of proteins expressed in a given organism (Electrophoresis 16:1090(Electrophoresis 16: -1094(Electrophoresis 16: , 1995. Important technical innovations in mass spectrometry (MS), protein identification methods, and database annotation, over the past decade, now make it possible to routinely identify thousands of proteins in complex biological samples (Nature 422:198-207, 2003). However, to gain new insights regarding fundamental biological questions, accurate protein quantification is also required. In this chapter, we present methods for the biochemical separation of different cellular compartments, two-dimensional chromatographic separation of the constituent peptide populations, and the recently published Spectral Counting Strategy , a label-free MS-based protein quantification technology (

Journal of Proteome Research, 2009

Selected reaction monitoring (SRM) is a powerful tandem mass spectrometry method that can be used to monitor target peptides within a complex protein digest. The specificity and sensitivity of the approach, as well as its capability to multiplex the measurement of many analytes in parallel, has made it a technology of particular promise for hypothesis driven proteomics. An underappreciated step in the development of an assay to measure many peptides in parallel is the time and effort necessary to establish a usable assay. Here we report the use of shotgun proteomics data to expedite the selection of SRM transitions for target peptides of interest. The use of tandem mass spectrometry data acquired on an LTQ ion trap mass spectrometer can accurately predict which fragment ions will produce the greatest signal in an SRM assay using a triple quadrupole mass spectrometer. Furthermore, we present a scoring routine that can compare the targeted SRM chromatogram data with an MS/MS spectrum acquired by data-dependent acquisition and stored in a library. This scoring routine is invaluable in determining which signal in the chromatogram from a complex mixture best represents the target peptide. These algorithmic developments have been implemented in a software package that is available from the authors upon request.

Nature Methods, 2005

Researchers have several options when designing proteomics experiments. Primary among these are choices of experimental method, instrumentation and spectral interpretation software. To evaluate these choices on a proteome scale, we compared triplicate measurements of the yeast proteome by liquid chromatography tandem mass spectrometry (LC-MS/MS) using linear ion trap (LTQ) and hybrid quadrupole time-of-flight (QqTOF; QSTAR) mass spectrometers. Acquired MS/MS spectra were interpreted with Mascot and SEQUEST algorithms with and without the requirement that all returned peptides be tryptic. Using a composite target decoy database strategy, we selected scoring criteria yielding 1% estimated false positive identifications at maximum sensitivity for all data sets, allowing reasonable comparisons between them. These comparisons indicate that Mascot and SEQUEST yield similar results for LTQacquired spectra but less so for QSTAR spectra. Furthermore, low reproducibility between replicate data acquisitions made on one or both instrument platforms can be exploited to increase sensitivity and confidence in large-scale protein identifications.

Molecular & Cellular Proteomics, 2008

LC-MS/MS has emerged as the method of choice for the identification and quantification of protein sample mixtures. For very complex samples such as complete proteomes, the most commonly used LC-MS/MS method, data-dependent acquisition (DDA) precursor selection, is of limited utility. The limited scan speed of current mass spectrometers along with the highly redundant selection of the most intense precursor ions generates a bias in the pool of identified proteins toward those of higher abundance. A directed LC-MS/MS approach that alleviates the limitations of DDA precursor ion selection by decoupling peak detection and sequencing of selected precursor ions is presented. In the first stage of the strategy, all detectable peptide ion signals are extracted from high resolution LC-MS feature maps or aligned sets of feature maps. The selected features or a subset thereof are subsequently sequenced in sequential, non-redundant directed LC-MS/MS experiments, and the MS/MS data are mapped back to the original LC-MS feature map in a fully automated manner. The strategy, implemented on an LTQ-FT MS platform, allowed the specific sequencing of 2,000 features per analysis and enabled the identification of more than 1,600 phosphorylation sites using a single reversed phase separation dimension without the need for time-consuming prefractionation steps. Compared with conventional DDA LC-MS/MS experiments, a substantially higher number of peptides could be identified from a sample, and this increase was more pronounced for low intensity precursor ions. Molecular & Cellular Proteomics 7:2138 -2150, 2008.

2012

The study of proteins has been a key element in biomedicine and biotechnology because of their important role in cell functions or enzymatic activity. Cells are the basic unit of living organisms, which are governed by a vast range of chemical reactions. These chemical reactions must be highly regulated in order to achieve homeostasis. Proteins are polymeric molecules that have taken on the evolutionary process the role, along with other factors, of control these chemical reactions. Learning how proteins interact and control their up and down regulations can teach us how living cells regulate their functions, as well as the cause of certain anomalies that occur in different diseases where proteins are involved. Mass spectrometry (MS) is an analytical widely used technique to study the protein content inside the cells as a biomarker point, which describes dysfunctions in diseases and increases knowledge of how proteins are working. All the methodologies involved in these descriptions are integrated in the field called Proteomics.

Journal of Mass Spectrometry, 2007

field have been possible owing to novel MS instrumentation, experimental strategies, and bioinformatics tools. Today it is possible to identify and determine relative expression levels of thousands of proteins in a biological system by MS analysis of peptides produced by proteolytic digestion. In some situations, however, the precise characterization of a particular peptide species in a very complex peptide mixture is needed. While single-fragment ion-based scanning modes such as selected ion reaction monitoring (SIRM) or consecutive reaction monitoring (CRM) may be highly sensitive, they do not produce MS/MS information and their actual specificity must be determined in advance, a prerequisite that is not usually met in a basic research context. In such cases, the MS detector may be programmed to perform continuous MS/MS spectra on the peptide ion of interest in order to obtain structural information. This selected MS/MS ion monitoring (SMIM) mode has a number of advantages that are fully exploited by MS detectors that, like the linear ion trap, are characterized by high scanning speeds. In this work, we show some applications of this technique in the context of biological studies. These results were obtained by selecting an appropriate combination of scans according to the purpose of each one of these research scenarios.

Nature Methods, 2009

In spite of these favorable properties, SRM has not been broadly used in proteomics, and SRM-based studies have mostly focused on small numbers of proteins . The effort required to develop a high-quality SRM assay for a protein has prevented the broader application of this technology. Assay development involves first the validation of the assay to confirm that it selectively monitors the analyte of interest and, second, optimization of the assay to maximize its sensitivity 8 . Optimization is achieved by determining the most suitable SRM transitions for each target peptide, along with other associated liquid chromatography (LC)-MS parameters, and is a lengthy and iterative process. Assay validation typically relies on the acquisition of full-scan MS/MS spectra for the targeted peptide on the same MS platform that will be used to deploy the assay, that is, a QQQ instrument. Acquisition of reliable MS/MS spectra of peptides in biological samples is strongly compromised by complex backgrounds that obscure the fragmentation pattern and limit the dynamic range, thus making the validation of transitions for low-abundance peptides extremely challenging. Additionally, MS/MS spectra acquisition on QQQ instruments is slow compared to fast scanning mass spectrometers such as linear ion traps. This creates the paradoxical situation that highly sensitive SRM assays have to be developed and validated by a method that has a substantially lower sensitivity and dynamic range than the SRM assay itself, which has prevented the routine development of SRM assays for low-abundance proteins.