Evaluation and optimization of ion-current ratio measurements by selected-ion-monitoring mass spectrometry

A guide to precise measurements of isotope abundance by ESI-Orbitrap MS

Stable isotopes of carbon, hydrogen, nitrogen, oxygen and sulfur are widespread in nature. Nevertheless, their relative abundance is not the same everywhere. This is due to kinetic isotope effects in enzymes and other physical principles such as equilibrium thermodynamics. Variations in isotope ratios offer unique insights into environmental pollution, trophic relationships in ecology, metabolic disorders and Earth history including climate history. Although classical isotope ratio mass spectrometry (IRMS) techniques still struggle to access intramolecular information like site-specific isotope abundance, electrospray ionization-Orbitrap mass spectrometry can be used to achieve precise and accurate intramolecular quantification of isotopically substituted molecules ('isotopocules'). This protocol describes two procedures. In the first one, we provide a step-by-step beginner's guide for performing multi-elemental, intramolecular and site-specific stable isotope analysis in unlabeled polar solutes by direct infusion. Using a widely available calibration solution, isotopocules of trifluoroacetic acid and immonium ions from the model peptide MRFA are quantified. In the second approach, nitrate is used as a simple model for a flow injection routine that enables access to a diverse range of naturally occurring isotopic signatures in inorganic oxyanions. Each procedure takes 2-3 h to complete and requires expertise only in general mass spectrometry. The workflows use optimized Orbitrap IRMS data-extraction and -processing software and are transferable to various analytes amenable to soft ionization, including metabolites, peptides, drugs and environmental pollutants. Optimized mass spectrometry systems will enable intramolecular isotope research in many areas of biology.

A compositional data model to predict the isotope distribution for average peptides using a compositional spline model

We propose an updated approach for approximating the isotope distribution of average peptides given their monoisotopic mass. Our methodology involves in-silico cleavage of the entire UNIPROT database of human-reviewed proteins using Trypsin, generating a theoretical peptide dataset. The isotope distribution is computed using BRAIN. We apply a compositional data modelling strategy that utilizes an additive log-ratio transformation for the isotope probabilities followed by a penalized spline regression. Furthermore, due to the impact of the number of sulphur atoms on the course of the isotope distribution, we develop separate models for peptides containing zero up to five sulphur atoms. Additionally, we propose three methods to estimate the number of sulphur atoms based on an observed isotope distribution. The performance of the spline models and the sulphur prediction approaches is evaluated using a mean squared error and a modified Pearson's χ2 goodness-of-fit measure on an experimental UPS2 data set. Our analysis reveals that the variability in spectral accuracy, that is, the variability between MS1 scans, contributes more to the errors than the approximation of the theoretical isotope distribution by our proposed average peptide model. Moreover, we find that the accuracy of predicting the number of sulphur atoms based on the observed isotope distribution is limited by measurement accuracy.

Sampling the proteome by emerging single-molecule and mass spectrometry methods

Mammalian cells have about 30,000-fold more protein molecules than mRNA molecules, which has major implications in the development of proteomics technologies. We review strategies that have been helpful for counting billions of protein molecules by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome.

The isotope distribution: A rose with thorns

The isotope distribution, which reflects the number and probabilities of occurrence of different isotopologues of a molecule, can be theoretically calculated. With the current generation of (ultra)-high-resolution mass spectrometers, the isotope distribution of molecules can be measured with high sensitivity, resolution, and mass accuracy. However, the observed isotope distribution can differ substantially from the expected isotope distribution. Although differences between the observed and expected isotope distribution can complicate the analysis and interpretation of mass spectral data, they can be helpful in a number of specific applications. These applications include, yet are not limited to, the identification of peptides in proteomics, elucidation of the elemental composition of small organic molecules and metabolites, as well as wading through peaks in mass spectra of complex bioorganic mixtures such as petroleum and humus. In this review, we give a nonexhaustive overview of factors that have an impact on the observed isotope distribution, such as elemental isotope deviations, ion sampling, ion interactions, electronic noise and dephasing, centroiding, and apodization. These factors occur at different stages of obtaining the isotope distribution: during the collection of the sample, during the ionization and intake of a molecule in a mass spectrometer, during the mass separation and detection of ionized molecules, and during signal processing.

Comparison of Unit Resolution Versus High-Resolution Accurate Mass for Parallel Reaction Monitoring

Parallel reaction monitoring (PRM) is an increasingly popular alternative to selected reaction monitoring (SRM) for targeted proteomics. PRM's strengths over SRM are that it monitors all product ions in a single spectrum, thus eliminating the need to select interference-free product ions prior to data acquisition, and that it is most frequently performed on high-resolution instruments, such as quadrupole-orbitrap and quadrupole-time-of-flight instruments. Here, we show that the primary advantage of PRM is the ability to monitor all transitions in parallel and that high-resolution data are not necessary to obtain high-quality quantitative data. We run the same scheduled PRM assay, measuring 432 peptides from 126 plasma proteins, multiple times on an Orbitrap Eclipse Tribrid mass spectrometer, alternating separate liquid chromatography-tandem mass spectrometry runs between the high-resolution Orbitrap and the unit resolution linear ion trap for PRM. We find that both mass analyzers have similar technical precision and that the linear ion trap's superior sensitivity gives it better lower limits of quantitation for over 62% of peptides in the assay.

Highly Multiplex Targeted Proteomics Enabled by Real-Time Chromatographic Alignment

Targeted mass spectrometry methods produce high-quality quantitative data in terms of limits of detection and dynamic range, at the cost of a substantial compromise in throughput compared to methods such as data independent and data dependent acquisition. The logistical and experimental issues inherent to maintaining assays of even several hundred targets are significant. Prominent among these issues is the drift in analyte retention time as liquid chromatography (LC) columns wear, forcing targeted scheduling windows to be much larger than LC peak widths. If these problems could be solved, proteomics assays would be capable of targeting thousands of peptides in an hour-long experiment, enabling large cohort studies to be performed without sacrificing sensitivity and specificity. We describe a solution in the form of a new method for real-time chromatographic alignment and demonstrate its application to a 56 min LC-gradient HeLa digest assay with 1489 targets. The method is based on the periodic acquisition of untargeted survey scans in a reference experiment and alignment to those scans during subsequent experiments. We describe how the method enables narrower scheduled retention time windows to be used. The narrower scheduling windows enables more targets to be included in the assay or proportionally more time to be allocated to each target, improving the sensitivity. Finally, we point out how the procedure could be improved and how much additional target multiplexing could be gained in the future.

The Acinetobacter baumannii Mla system and glycerophospholipid transport to the outer membrane

The outer membrane (OM) of Gram-negative bacteria serves as a selective permeability barrier that allows entry of essential nutrients while excluding toxic compounds, including antibiotics. The OM is asymmetric and contains an outer leaflet of lipopolysaccharides (LPS) or lipooligosaccharides (LOS) and an inner leaflet of glycerophospholipids (GPL). We screened Acinetobacter baumannii transposon mutants and identified a number of mutants with OM defects, including an ABC transporter system homologous to the Mla system in E. coli. We further show that this opportunistic, antibiotic-resistant pathogen uses this multicomponent protein complex and ATP hydrolysis at the inner membrane to promote GPL export to the OM. The broad conservation of the Mla system in Gram-negative bacteria suggests the system may play a conserved role in OM biogenesis. The importance of the Mla system to Acinetobacter baumannii OM integrity and antibiotic sensitivity suggests that its components may serve as new antimicrobial therapeutic targets.

Systematic quantitative analysis of H2A and H2B variants by targeted proteomics

BACKGROUND

Histones organize DNA into chromatin through a variety of processes. Among them, a vast diversity of histone variants can be incorporated into chromatin and finely modulate its organization and functionality. Classically, the study of histone variants has largely relied on antibody-based assays. However, antibodies have a limited efficiency to discriminate between highly similar histone variants.

RESULTS

In this study, we established a mass spectrometry-based analysis to address this challenge. We developed a targeted proteomics method, using selected reaction monitoring or parallel reaction monitoring, to quantify a maximum number of histone variants in a single multiplexed assay, even when histones are present in a crude extract. This strategy was developed on H2A and H2B variants, using 55 peptides corresponding to 25 different histone sequences, among which a few differ by a single amino acid. The methodology was then applied to mouse testis extracts in which almost all histone variants are expressed. It confirmed the abundance profiles of several testis-specific histones during successive stages of spermatogenesis and the existence of predicted H2A.L.1 isoforms. This methodology was also used to explore the over-expression pattern of H2A.L.1 isoforms in a mouse model of male infertility.

CONCLUSIONS

Our results demonstrate that targeted proteomics is a powerful method to quantify highly similar histone variants and isoforms. The developed method can be easily transposed to the study of human histone variants, whose abundance can be deregulated in various diseases.

Effect of Error Propagation in Stable Isotope Tracer Studies: An Approach for Estimating Impact on Apparent Biochemical Flux

Stable isotope tracers are widely used to quantify metabolic rates, and yet a limited number of studies have considered the impact of analytical error on estimates of flux. For example, when estimating the contribution of de novo lipogenesis, one typically measures a minimum of four isotope ratios, i.e., the precursor and product labeling pre- and posttracer administration. This seemingly simple problem has 1 correct solution and 80 erroneous outcomes. In this report, we outline a methodology for evaluating the effect of error propagation on apparent physiological endpoints. We demonstrate examples of how to evaluate the influence of analytical error in case studies concerning lipid and protein synthesis; we have focused on (2)H2O as a tracer and contrast different mass spectrometry platforms including GC-quadrupole-MS, GC-pyrolysis-IRMS, LC-quadrupole-MS, and high-resolution FT-ICR-MS. The method outlined herein can be used to determine how to minimize variations in the apparent biology by altering the dose and/or the type of tracer. Likewise, one can facilitate biological studies by estimating the reduction in the noise of an outcome that is expected for a given increase in the number of replicate injections.

Comparison of data acquisition strategies on quadrupole ion trap instrumentation for shotgun proteomics

The most common data collection in shotgun proteomics is via data-dependent acquisition (DDA), a process driven by an automated instrument control routine that directs MS/MS acquisition from the highest abundant signals to the lowest. An alternative to DDA is data-independent acquisition (DIA), a process in which a specified range in m/z is fragmented without regard to prioritization of a precursor ion or its relative abundance in the mass spectrum, thus potentially offering a more comprehensive analysis of peptides than DDA. In this work, we evaluate both DDA and DIA on three different linear ion trap instruments: an LTQ, an LTQ modified with an electrodynamic ion funnel, and an LTQ Velos. These instruments represent both older (LTQ) and newer (LTQ Velos) ion trap designs (i.e., linear versus dual ion traps, respectively), and allow direct comparison of peptide identifications using both DDA and DIA analysis. Further, as the LTQ Velos has an enhanced "S-lens" ion guide to improve ion flux, we found it logical to determine if the former LTQ model could be leveraged by improving sensitivity by modifying with an electrodynamic ion guide of significantly different design to the S-lens. We find that the ion funnel enabled LTQ identifies more proteins in the insoluble fraction of a yeast lysate than the other two instruments in DIA mode, whereas the faster scanning LTQ Velos performs better in DDA mode. We explore reasons for these results, including differences in scan speed, source ion optics, and linear ion trap design.

Selected reaction monitoring applied to proteomics

Selected reaction monitoring (SRM) performed on triple quadrupole mass spectrometers has been the reference quantitative technique to analyze small molecules for several decades. It is now emerging in proteomics as the ideal tool to complement shotgun qualitative studies; targeted SRM quantitative analysis offers high selectivity, sensitivity and a wide dynamic range. However, SRM applied to proteomics presents singularities that distinguish it from small molecules analysis. This review is an overview of SRM technology and describes the specificities and the technical aspects of proteomics experiments. Ongoing developments aiming at increasing multiplexing capabilities of SRM are discussed; they dramatically improve its throughput and extend its field of application to directed or supervised discovery experiments.

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

Measurement of human surfactant protein-B turnover in vivo from tracheal aspirates using targeted proteomics

We describe a method to measure protein synthesis and catabolism in humans without prior purification and use the method to measure the turnover of surfactant protein-B (SP-B). SP-B, a lung-specific, hydrophobic protein essential for fetal-neonatal respiratory transition, is present in only picomolar quantities in tracheal aspirate samples and difficult to isolate for dynamic turnover studies using traditional in vivo tracer techniques. Using infusion of [5,5,5-(2)H(3)] leucine and a targeted proteomics method, we measured both the quantity and kinetics of SP-B tryptic peptides in tracheal aspirate samples of symptomatic newborn infants. The fractional synthetic rate (FSR) of SP-B measured using the most abundant proteolytic fragment, a 10 amino acid peptide from the carboxy-terminus of proSP-B (SPTGEWLPR), from the circulating leucine pool was 0.035 +/- 0.005 h(-1), and the fractional catabolic rate was 0.044 +/- 0.003 h(-1). This technique permits high-throughput and sensitive measurement of turnover of low abundance proteins with minimal sample preparation.

Computational analysis of quantitative proteomics data using stable isotope labeling

Over the last few years, new proteomics methods have been developed for making quantitative comparisons using stable isotope labeling. Although these methods have paved the way for quantitative proteomics, the analysis of these data is often the rate-limiting step. In fact, many analyzes are still carried out manually, which adds a level of subjectivity to the data that will vary between laboratories and even analysts. In this chapter, we have attempted to summarize several of the key steps necessary for an individual to automate the analysis of quantitative proteomics data. The approach is straightfoward to implement for an individual with moderate programming experience and used to process proteomics data in an objective manner.

Multi-Q: a fully automated tool for multiplexed protein quantitation

The iTRAQ labeling method combined with shotgun proteomic techniques represents a new dimension in multiplexed quantitation for relative protein expression measurement in different cell states. To expedite the analysis of vast amounts of spectral data, we present a fully automated software package, called Multi-Q, for multiplexed iTRAQ-based quantitation in protein profiling. Multi-Q is designed as a generic platform that can accommodate various input data formats from search engines and mass spectrometer manufacturers. To calculate peptide ratios, the software automatically processes iTRAQ's signature peaks, including peak detection, background subtraction, isotope correction, and normalization to remove systematic errors. Furthermore, Multi-Q allows users to define their own data-filtering thresholds based on semiempirical values or statistical models so that the computed results of fold changes in peptide ratios are statistically significant. This feature facilitates the use of Multi-Q with various instrument types with different dynamic ranges, which is an important aspect of iTRAQ analysis. The performance of Multi-Q is evaluated with a mixture of 10 standard proteins and human Jurkat T cells. The results are consistent with expected protein ratios and thus demonstrate the high accuracy, full automation, and high-throughput capability of Multi-Q as a large-scale quantitation proteomics tool. These features allow rapid interpretation of output from large proteomic datasets without the need for manual validation. Executable Multi-Q files are available on Windows platform at http://ms.iis.sinica.edu.tw/Multi-Q/.

Quantitative Comparison of Proteomic Data Quality between a 2D and 3D Quadrupole Ion Trap

A 2D ion trap has a greater ion trapping efficiency, greater ion capacity before observing space-charging effects, and a faster ion ejection rate than a traditional 3D ion trap mass spectrometer. These hardware improvements should result in a significant increase in protein identifications from complex mixtures analyzed using shotgun proteomics. In this study, we compare the quality and quantity of peptide identifications using data-dependent acquisition of tandem mass spectra of peptides between two commercially available ion trap mass spectrometers (an LTQ and an LCQ XP Max). We demonstrate that the increased trapping efficiency, increased ion capacity, and faster ion ejection rate of the LTQ results in greater than 5-fold more protein identifications, better identification of low-abundance proteins, and higher confidence protein identifications when compared with a LCQ XP Max.

Measurement of the Isotope Enrichment of Stable Isotope-Labeled Proteins Using High-Resolution Mass Spectra of Peptides

Stable isotope-enriched molecules are used as internal standards and as tracers of in vivo substrate metabolism. The accurate conversion of measured ratios in the mass spectrometer to mole ratios is complicated because a polyatomic molecule containing enriched atoms will result in a combinatorial distribution of isotopomers depending on the enrichment and number of "labeled" atoms. This effect could potentially cause a large error in the mole ratio measurement depending on which isotope peak or peaks were used to determine the ratio. We report a computational method that predicts isotope distributions over a range of enrichments and compares the predicted distributions to experimental peptide isotope distributions obtained by Fourier transform ion cyclotron resonance mass spectrometry. Our approach is accurate with measured enrichments within 1.5% of expected isotope distributions. The method is also precise with 4.9, 2.0, and 0.8% relative standard deviations for peptides containing 59, 79, and 99 atom % excess (15)N, respectively. The approach is automated making isotope enrichment calculations possible for thousands of peptides in a single muLC-FTICR-MS experiment.

A correlation algorithm for the automated quantitative analysis of shotgun proteomics data

Quantitative shotgun proteomic analyses are facilitated using chemical tags such as ICAT and metabolic labeling strategies with stable isotopes. The rapid high-throughput production of quantitative "shotgun" proteomic data necessitates the development of software to automatically convert mass spectrometry-derived data of peptides into relative protein abundances. We describe a computer program called RelEx, which uses a least-squares regression for the calculation of the peptide ion current ratios from the mass spectrometry-derived ion chromatograms. RelEx is tolerant of poor signal-to-noise data and can automatically discard nonusable chromatograms and outlier ratios. We apply a simple correction for systematic errors that improves the accuracy of the quantitative measurement by 32 +/- 4%. Our automated approach was validated using labeled mixtures composed of known molar ratios and demonstrated in a real sample by measuring the effect of osmotic stress on protein expression in Saccharomyces cerevisiae.

Metabolic Labeling of Mammalian Organisms with Stable Isotopes for Quantitative Proteomic Analysis

To quantify proteins on a global level from mammalian tissue, a method was developed to metabolically introduce 15N stable isotopes into the proteins of Rattus norvegicus for use as internal standards. The long-term metabolic labeling of rats with a diet enriched in 15N did not result in adverse health consequences. The average 15N amino acid enrichments reflected the relative turnover rates in the different tissues and ranged from 74.3 mpe in brain to 92.2 mpe in plasma. Using the 15N-enriched liver as a quantitative internal standard, changes in individual protein levels in response to cycloheximide treatment were measured for 310 proteins. These measurements revealed 127 proteins with altered protein level (p < 0.05). Most proteins with altered level have previously reported functions involving xenobiotic metabolism and protein-folding machinery of the endoplasmic reticulum. This approach is a powerful tool for the global quantitation of proteins, is capable of measuring proteome-wide changes in response to a drug, and will be useful for studying animal models of disease.