A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spect...

https://pubs.acs.org/doi/pdfplus/10.1021/pr101065j?src=recsys

Andromeda: a peptide search engine integrated into the MaxQuant environment

The quantification of differences between two or more physiological states of a biological system is among the most important but also most challenging technical tasks in proteomics. In addition to the classical methods of differential protein gel or blot staining by dyes and fluorophores, mass-spectrometry-based quantification methods have gained increasing popularity over the past five years. Most of these methods employ differential stable isotope labeling to create a specific mass tag that can be recognized by a mass spectrometer and at the same time provide the basis for quantification. These mass tags can be introduced into proteins or peptides (i) metabolically, (ii) by chemical means, (iii) enzymatically, or (iv) provided by spiked synthetic peptide standards. In contrast, label-free quantification approaches aim to correlate the mass spectrometric signal of intact proteolytic peptides or the number of peptide sequencing events with the relative or absolute protein quantity directly. In this review, we critically examine the more commonly used quantitative mass spectrometry methods for their individual merits and discuss challenges in arriving at meaningful interpretations of quantitative proteomic data.

/pdf/quantitative-mass-spectrometry-in-proteomics-a-critical-510v02gycj.pdf

Quantitative mass spectrometry in proteomics: a critical review

Absolute Quantification of Proteins by LCMSE A Virtue of Parallel ms Acquisition

According to Genome Sequencing Project statistics (http://www.ncbi.nlm.nih.gov/genomes/static/gpstat.html), as of Feb 16, 2012, complete gene sequences have become available for 2816 viruses, 1117 prokaryotes, and 36 eukaryotes.1–2 The availability of full genome sequences has greatly facilitated biological research in many fields, and has greatly contributed to the growth of proteomics.

Proteins are important because they are the direct bio-functional molecules in the living organisms. The term “proteomics” was coined from merging “protein” and “genomics” in the 1990s.3–4 As a post-genomic discipline, proteomics encompasses efforts to identify and quantify all the proteins of a proteome, including expression, cellular localization, interactions, post-translational modifications (PTMs), and turnover as a function of time, space and cell type, thus making the full investigation of a proteome more challenging than sequencing a genome. There are possibly 100,000 protein forms encoded by the approximate 20,235 genes of the human genome,5 and determining the explicit function of each form will be a challenge.

The progress of proteomics has been driven by the development of new technologies for peptide/protein separation, mass spectrometry analysis, isotope labeling for quantification, and bioinformatics data analysis. Mass spectrometry has emerged as a core tool for large-scale protein analysis. In the past decade, there has been a rapid advance in the resolution, mass accuracy, sensitivity and scan rate of mass spectrometers used to analyze proteins. In addition, hybrid mass analyzers have been introduced recently (e.g. Linear Ion Trap-Orbitrap series6–7) which have significantly improved proteomic analysis.

“Bottom-up” protein analysis refers to the characterization of proteins by analysis of peptides released from the protein through proteolysis. When bottom-up is performed on a mixture of proteins it is called shotgun proteomics,8–10 a name coined by the Yates lab because of its analogy to shotgun genomic sequencing.11 Shotgun proteomics provides an indirect measurement of proteins through peptides derived from proteolytic digestion of intact proteins. In a typical shotgun proteomics experiment, the peptide mixture is fractionated and subjected to LC-MS/MS analysis. Peptide identification is achieved by comparing the tandem mass spectra derived from peptide fragmentation with theoretical tandem mass spectra generated from in silico digestion of a protein database. Protein inference is accomplished by assigning peptide sequences to proteins. Because peptides can be either uniquely assigned to a single protein or shared by more than one protein, the identified proteins may be further scored and grouped based on their peptides. In contrast, another strategy, termed ‘top-down’ proteomics, is used to characterize intact proteins (Figure 1). The top-down approach has some potential advantages for PTM and protein isoform determination and has achieved notable success. Intact proteins have been measured up to 200 kDa,12 and a large scale study has identified more than 1,000 proteins by multi-dimensional separations from complex samples.13 However, the top-down method has significant limitations compared with shotgun proteomics due to difficulties with protein fractionation, protein ionization and fragmentation in the gas phase. By relying on the analysis of peptides, which are more easily fractionated, ionized and fragmented, shotgun proteomics can be more universally adopted for protein analysis. In fact, a hybrid of bottom-up and top-down methodologies and instrumentation has been introduced as middle-down proteomics.14 Essentially, middle-down proteomics analyzes larger peptide fragments than bottom-up proteomics, minimizing peptide redundancy between proteins. Additionally the large peptide fragments yield similar advantages as top-down proteomics, such as gaining further insight into post-translational modifications, without the analytical challenges of analyzing intact proteins. Shotgun proteomics has become a workhorse for the analysis of proteins and their modifications and will be increasingly combined with top-down methods in the future.



Figure 1

Proteomic strategies: bottom-up vs. top-down vs. middle-down. The bottom-up approach analyzes proteolytic peptides. The top-down method measures the intact proteins. The middle-down strategy analyzes larger peptides resulted from limited digestion or ...



In the past decade shotgun proteomics has been widely used by biologists for many different research experiments, advancing biological discoveries. Some applications include, but are not limited to, proteome profiling, protein quantification, protein modification, and protein-protein interaction. There have been several reviews nicely summarizing mass spectrometry history,15 protein quantification with mass spectrometry,16 its biological applications,5,17–26 and many recent advances in methodology.27–32 In this review, we try to provide a full and updated survey of shotgun proteomics, including the fundamental techniques and applications that laid the foundation along with those developed and greatly improved in the past several years.

Protein Analysis by Shotgun/Bottom-up Proteomics

Two-dimensional liquid chromatography is often used to reduce the proteomic sample complexity prior to tandem mass spectrometry analysis. The 2D-LC performance depends on the peak capacity in both chromatographic dimensions, and separation orthogonality. The peak capacity and selectivity of many LC modes for peptides is not well known, and mathematical characterization for orthogonality is underdeveloped. Consequently, it is difficult to estimate the performance of 2D-LC for peptide separation. The goal of this paper was to investigate a selectivity of common LC modes and to identify the 2D-LC systems with a useful orthogonality. A geometric approach for orthogonality description was developed and applied for estimation of a practical peak 2D-LC capacity. Selected LC modes including various RP, SCX, SEC, and HILIC were combined in 2D-LC setups. SCX-RP, HILIC-RP, and RP-RP 2D systems were found to provide suitable orthogonality. The RP-RP system (employing significantly different pH in both RP separation dimensions) had the highest practical peak capacity of 2D-LC systems investigated.

Orthogonality of separation in two-dimensional liquid chromatography.

Current methodologies for protein quantitation include 2-dimensional gel electrophoresis techniques, metabolic labeling, and stable isotope labeling methods to name only a few. The current literature illustrates both pros and cons for each of the previously mentioned methodologies. Keeping with the teachings of William of Ockham, “with all things being equal the simplest solution tends to be correct”, a simple LC/MS based methodology is presented that allows relative changes in abundance of proteins in highly complex mixtures to be determined. Utilizing a reproducible chromatographic separations system along with the high mass resolution and mass accuracy of an orthogonal time-of-flight mass spectrometer, the quantitative comparison of tens of thousands of ions emanating from identically prepared control and experimental samples can be made. Using this configuration, we can determine the change in relative abundance of a small number of ions between the two conditions solely by accurate mass and retention...

Quantitative proteomic analysis by accurate mass retention time pairs.

Tautomeric equilibria in 2-hydroxypyridine and in cytosine. An assessment of density functional methods, including gradient corrections

Hydration free energies of nucleic acid bases using an ab initio continuum model

We describe a probabilistic peptide fragmentation model for use in protein databank searching and de novo sequencing of electrospray tandem mass spectrometry data. A probabilistic framework for tuning of the model using a range of well-characterized samples are introduced. We present preliminary results of our tuning efforts.

/pdf/probseq-a-fragmentation-model-for-interpretation-of-11ar4ac5au.pdf

Phillip Young

Papers

Quantitative proteomic analysis by accurate mass retention time pairs.

Tautomeric equilibria in 2-hydroxypyridine and in cytosine. An assessment of density functional methods, including gradient corrections

Hydration free energies of nucleic acid bases using an ab initio continuum model

ProbSeq—A Fragmentation Model for Interpretation of Electrospray Tandem Mass Spectrometry Data

ProbSeq - a fragmentation model for interpretation of electrospray tandem mass spectrometry data : Proteins and Signals