Short-Term Stable Isotope Probing of Proteins Reveals Taxa Incorporating Inorganic Carbon in a Hot Spring Microbial Mat.

The upper green layer of the chlorophototrophic microbial mats associated with the alkaline siliceous hot springs of Yellowstone National Park consists of oxygenic cyanobacteria (Synechococcus spp.), anoxygenic Roseiflexus spp., and several other anoxygenic chlorophototrophs. Synechococcus spp. are believed to be the main fixers of inorganic carbon (Ci), but some evidence suggests that Roseiflexus spp. also contribute to inorganic carbon fixation during low-light, anoxic morning periods. Contributions of other phototrophic taxa have not been investigated. In order to follow the pathway of Ci incorporation into different taxa, mat samples were incubated with [13C]bicarbonate for 3 h during the early-morning, low-light anoxic period. Extracted proteins were treated with trypsin and analyzed by mass spectrometry, leading to peptide identifications and peptide isotopic profile signatures containing evidence of 13C label incorporation. A total of 25,483 peptides, corresponding to 7,221 proteins, were identified from spectral features and associated with mat taxa by comparison to metagenomic assembly sequences. A total of 1,417 peptides, derived from 720 proteins, were detectably labeled with 13C. Most 13C-labeled peptides were derived from proteins of Synechococcus spp. and Roseiflexus spp. Chaperones and proteins of carbohydrate metabolism were most abundantly labeled. Proteins involved in photosynthesis, Ci fixation, and N2 fixation were also labeled in Synechococcus spp. Importantly, most proteins of the 3-hydroxypropionate bi-cycle for Ci fixation in Roseiflexus spp. were labeled, establishing that members of this taxocene contribute to Ci fixation. Other taxa showed much lower [13C]bicarbonate incorporation.IMPORTANCE Yellowstone hot spring mats have been studied as natural models for understanding microbial community ecology and as modern analogs of stromatolites, the earliest community fossils on Earth. Stable-isotope probing of proteins (Pro-SIP) permitted short-term interrogation of the taxa that are involved in the important process of light-driven Ci fixation in this highly active community and will be useful in linking other metabolic processes to mat taxa. Here, evidence is presented that Roseiflexus spp., which use the 3-hydroxypropionate bi-cycle, are active in Ci fixation. Because this pathway imparts a lower degree of selection of isotopically heavy Ci than does the Calvin-Benson-Bassham cycle, the results suggest a mechanism to explain why the natural abundance of 13C in mat biomass is greater than expected if only the latter pathway were involved. Understanding how mat community members influence the 13C/12C ratios of mat biomass will help geochemists interpret the 13C/12C ratios of organic carbon in the fossil record.

An algorithm to correct saturated mass spectrometry ion abundances for enhanced quantitation and mass accuracy in omic studies.

The mass accuracy and peak intensity of ions detected by mass spectrometry (MS) measurements are essential to facilitate compound identification and quantitation. However, high concentration species can yield erroneous results if their ion intensities reach beyond the limits of the detection system, leading to distorted and non-ideal detector response (e.g. saturation), and largely precluding the calculation of accurate m/z and intensity values. Here we present an open source computational method to correct peaks above a defined intensity (saturated) threshold determined by the MS instrumentation such as the analog-to-digital converters or time-to-digital converters used in conjunction with time-of-flight MS. In this method, the isotopic envelope for each observed ion above the saturation threshold is compared to its expected theoretical isotopic distribution. The most intense isotopic peak for which saturation does not occur is then utilized to re-calculate the precursor m/z and correct the intensity, resulting in both higher mass accuracy and greater dynamic range. The benefits of this approach were evaluated with proteomic and lipidomic datasets of varying complexities. After correcting the high concentration species, reduced mass errors and enhanced dynamic range were observed for both simple and complex omic samples. Specifically, the mass error dropped by more than 50% in most cases for highly saturated species and dynamic range increased by 1-2 orders of magnitude for peptides in a blood serum sample.

Identification of Salmonella Typhimurium Deubiquitinase SseL Substrates by Immunoaffinity Enrichment and Quantitative Proteomic Analysis.

Ubiquitination is a key protein post-translational modification that regulates many important cellular pathways and whose levels are regulated by equilibrium between the activities of ubiquitin ligases and deubiquitinases. Here, we present a method to identify specific deubiquitinase substrates based on treatment of cell lysates with recombinant enzymes, immunoaffinity purification, and global quantitative proteomic analysis. As a model system to identify substrates, we used a virulence-related deubiquitinase, SseL, secreted by Salmonella enterica serovar Typhimurium into host cells. Using this approach, two SseL substrates were identified in the RAW 264.7 murine macrophage-like cell line, S100A6 and heterogeneous nuclear ribonuclear protein K, in addition to the previously reported K63-linked ubiquitin chains. These substrates were further validated by a combination of enzymatic and binding assays. This method can be used for the systematic identification of substrates of deubiquitinases from other organisms and applied to study their functions in physiology and disease.

An Optimized Informatics Pipeline for Mass Spectrometry-Based Peptidomics.

The comprehensive MS analysis of the peptidome, the intracellular and intercellular products of protein degradation, has the potential to provide novel insights on endogenous proteolytic processing and its utility in disease diagnosis and prognosis. Along with the advances in MS instrumentation and related platforms, a plethora of proteomics data analysis tools have been applied for direct use in peptidomics; however, an evaluation of the currently available informatics pipelines for peptidomics data analysis has yet to be reported. In this study, we began by evaluating the results of several popular MS/MS database search engines, including MS-GF+, SEQUEST, and MS-Align+, for peptidomics data analysis, followed by identification and label-free quantification using the well-established accurate mass and time (AMT) tag and newly developed informed quantification (IQ) approaches, both based on direct LC-MS analysis. Our results demonstrated that MS-GF+ outperformed both SEQUEST and MS-Align+ in identifying peptidome peptides. Using a database established from MS-GF+ peptide identifications, both the AMT tag and IQ approaches provided significantly deeper peptidome coverage and less missing data for each individual data set than the MS/MS methods, while achieving robust label-free quantification. Besides having an excellent correlation with the AMT tag quantification results, IQ also provided slightly higher peptidome coverage. Taken together, we propose an optimized informatics pipeline combining MS-GF+ for initial database searching with IQ (or AMT tag) approaches for identification and label-free quantification for high-throughput, comprehensive, and quantitative peptidomics analysis. Graphical Abstract ᅟ.

Comprehensive quantitative analysis of ovarian and breast cancer tumor peptidomes.

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high-throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with postexcision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics and provides insights not readily obtainable from such approaches.

GlyQ-IQ: glycomics quintavariate-informed quantification with high-performance computing and GlycoGrid 4D visualization.

Glycomics quintavariate-informed quantification (GlyQ-IQ) is a biologically guided glycomics analysis tool for identifying N-glycans in liquid chromatography-mass spectrometry (LC-MS) data. Glycomics LC-MS data sets have convoluted extracted ion chromatograms that are challenging to deconvolve with existing software tools. LC deconvolution into constituent pieces is critical in glycomics data sets because chromatographic peaks correspond to different intact glycan structural isomers. The biological targeted analysis approach offers several key advantages to traditional LC-MS data processing. A priori glycan information about the individual target's elemental composition allows for improved sensitivity by utilizing the exact isotope profile information to focus chromatogram generation and LC peak fitting on the isotopic species having the highest intensity. Glycan target annotation utilizes glycan family relationships and in source fragmentation in addition to high specificity feature LC-MS detection to improve the specificity of the analysis. The GlyQ-IQ software was developed in this work and evaluated in the context of profiling the N-glycan compositions from human serum LC-MS data sets. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad human serum N-glycan profile from a high resolution nanoelectrospray-liquid chromatography-tandem mass spectrometry (nESI-LC-MS/MS) data set. A total of 156 glycan compositions and 640 glycan isomers were detected from a single sample. Over 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high-resolution mass spectra.

Automated data extraction from in situ protein-stable isotope probing studies.

Protein-stable isotope probing (protein-SIP) has strong potential for revealing key metabolizing taxa in complex microbial communities. While most protein-SIP work to date has been performed under controlled laboratory conditions to allow extensive isotope labeling of the target organism(s), a key application will be in situ studies of microbial communities for short periods of time under natural conditions that result in small degrees of partial labeling. One hurdle restricting large-scale in situ protein-SIP studies is the lack of algorithms and software for automated data processing of the massive data sets resulting from such studies. In response, we developed Stable Isotope Probing Protein Extraction Resources software (SIPPER) and applied it for large-scale extraction and visualization of data from short-term (3 h) protein-SIP experiments performed in situ on phototrophic bacterial mats isolated from Yellowstone National Park. Several metrics incorporated into the software allow it to support exhaustive analysis of the complex composite isotopic envelope observed as a result of low amounts of partial label incorporation. SIPPER also enables the detection of labeled molecular species without the need for any prior identification.

Advancing the high throughput identification of liver fibrosis protein signatures using multiplexed ion mobility spectrometry.

Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is a crucial direction for the field of medicine. While MS-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new instrumental platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry separations with liquid chromatography and MS to dramatically increase measurement sensitivity and throughput, further enabling future high throughput MS-based clinical applications. An initial application of the liquid chromatography--ion mobility spectrometry-MS platform analyzing blood serum samples from 60 postliver transplant patients with recurrent fibrosis progression and 60 nontransplant patients illustrates its potential utility for disease characterization.

LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets.

MOTIVATION: The addition of ion mobility spectrometry to liquid chromatography-mass spectrometry experiments requires new, or updated, software tools to facilitate data processing. RESULTS: We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension. AVAILABILITY: LC-IMS-MS Feature Finder is available as a command-line tool for download at http://omics.pnl.gov/software/LC-IMS-MS_Feature_Finder.php. The Microsoft.NET Framework 4.0 is required to run the software. All other dependencies are included with the software package. Usage of this software is limited to non-profit research to use (see README). CONTACT: rds@pnnl.gov. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Increasing Confidence of LC-MS Identifications by Utilizing Ion Mobility Spectrometry.

Ion mobility spectrometry in conjunction with liquid chromatography separations and mass spectrometry offers a range of new possibilities for analyzing complex biological samples. To fully utilize the information obtained from these three measurement dimensions, informatics tools based on the accurate mass and time tag methodology were modified to incorporate ion mobility spectrometry drift times for peptides observed in human serum. In this work a reference human serum database was created for 12,139 peptides and populated with the monoisotopic mass, liquid chromatography normalized elution time, and ion mobility spectrometry drift time(s) for each. We demonstrate that the use of three dimensions for peak matching during the peptide identification process resulted in an increased numbers of identifications and a lower false discovery rate relative to only using the mass and normalized elution time dimensions.

GlycReSoft: a software package for automated recognition of glycans from LC/MS data.

Glycosylation modifies the physicochemical properties and protein binding functions of glycoconjugates. These modifications are biosynthesized in the endoplasmic reticulum and Golgi apparatus by a series of enzymatic transformations that are under complex control. As a result, mature glycans on a given site are heterogeneous mixtures of glycoforms. This gives rise to a spectrum of adhesive properties that strongly influences interactions with binding partners and resultant biological effects. In order to understand the roles glycosylation plays in normal and disease processes, efficient structural analysis tools are necessary. In the field of glycomics, liquid chromatography/mass spectrometry (LC/MS) is used to profile the glycans present in a given sample. This technology enables comparison of glycan compositions and abundances among different biological samples, i.e. normal versus disease, normal versus mutant, etc. Manual analysis of the glycan profiling LC/MS data is extremely time-consuming and efficient software tools are needed to eliminate this bottleneck. In this work, we have developed a tool to computationally model LC/MS data to enable efficient profiling of glycans. Using LC/MS data deconvoluted by Decon2LS/DeconTools, we built a list of unique neutral masses corresponding to candidate glycan compositions summarized over their various charge states, adducts and range of elution times. Our work aims to provide confident identification of true compounds in complex data sets that are not amenable to manual interpretation. This capability is an essential part of glycomics work flows. We demonstrate this tool, GlycReSoft, using an LC/MS dataset on tissue derived heparan sulfate oligosaccharides. The software, code and a test data set are publically archived under an open source license.

Improving N-glycan coverage using HPLC-MS with electrospray ionization at subambient pressure.

Human serum glycan profiling with mass spectrometry (MS) has been employed to study several disease conditions and is demonstrating promise in, for example, clinical biomarker discovery. However, the low glycan ionization efficiency and the large dynamic range of glycan concentrations in human sera can hinder comprehensive profiling. In particular, large glycans are problematic because they are present at low concentrations and are prone to fragmentation. Here we show that, following liquid chromatographic separation on graphite columns, subambient pressure ionization with nanoelectrospray (SPIN)-MS can expand the serum glycome profile in comparison with the conventional atmospheric pressure electrospray ionization (ESI)-MS with a heated capillary inlet. Notably, the ions generated by the SPIN interface were observed at higher charge states for approximately half of the annotated glycans. Out of a total of 130 detected glycans, 34 were only detected with the SPIN-MS, resulting in improved coverage of glycan families as well as of glycans with larger numbers of labile monosaccharides.

A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics.

Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

Integrated post-experiment monoisotopic mass refinement: an integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

Accurate assignment of monoisotopic precursor masses to tandem mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor mass refinement. This combined method, "integrated post-experiment monoisotopic mass refinement" (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex high-throughput proteomics data.

High-resolution desorption electrospray ionization mass spectrometry for chemical characterization of organic aerosols.

Characterization of the chemical composition and chemical transformations of secondary organic aerosol (SOA) is both a major challenge and the area of greatest uncertainty in current aerosol research. This study presents the first application of desorption electrospray ionization combined with high-resolution mass spectrometry (DESI-MS) for detailed chemical characterization and studies of chemical aging of organic aerosol (OA) samples collected on Teflon substrates. DESI-MS offers unique advantages both for detailed characterization of chemically labile components in OA that cannot be detected using traditional electrospray ionization mass spectrometry (ESI-MS) and for studying chemical aging of OA. DESI-MS enables rapid characterization of OA samples collected on substrates by eliminating the sample preparation stage. In addition, it enables detection and structural characterization of chemically labile molecules in OA samples by minimizing the residence time of analyte in the solvent. In this study, DESI-MS and tandem mass spectrometry experiments (MS/MS) were used to examine chemical aging of SOA produced by the ozonolysis of limonene (LSOA) in the presence of gaseous ammonia. Exposure of LSOA to ammonia resulted in measurable changes in the optical properties of the sample observed using ultraviolet (UV)-visible spectroscopy. High-resolution DESI-MS analysis demonstrated that chemical aging results in formation of highly conjugated nitrogen-containing species that are most likely responsible for light-absorbing properties of the aged LSOA. Detailed analysis of the experimental data allowed us to identify several key aging reactions, including the transformation of carbonyls to imines, intramolecular dimerization of imines with other carbonyl compounds in SOA, and intermolecular cyclization of imines. This study presents an important step toward understanding the formation of light-absorbing OA (brown carbon) in the atmosphere.

Surrogate H/D detection strategy for protein conformational analysis using MS/MS data.

Amide hydrogen/deuterium exchange (H/DX) measurements by mass spectrometry provide a powerful tool for probing the structure and dynamics of proteins. In order to extend such measurements to complex multiprotein systems, new methods for delivering higher sensitivity and sequence coverage are required. In this study, we investigated the utility of tandem mass spectrometry (MS/MS) for providing an alternative to the conventional MS mode of operation applied to bottom-up H/DX experiments. Specifically, we aimed to determine whether differential deuteration measurements of collisionally induced dissociation (CID)-generated product ions can serve as effective surrogates for their corresponding intact peptide, thus providing an additional dimension for analysis. Replicate deuterium measurements of calmodulin (in its apo and holo forms) were obtained from peptic digests in both the MS and MS/MS domains and studied as a function of % deuteration, fragment ion selection, and contaminant level. We show that successful acquisition of MS/MS data for deuterated peptides requires controlled expansion of the isotopic envelope by limiting the range of deuterium label applied in the exchange-in reaction (< or = 50%) and that automation of ion selection via data-dependent acquisition is ultimately dependent upon peak detection algorithms. Upon full transmission of the isotopic envelope, fragment data demonstrate that all ions, with the exception of neutral loss fragment ions, return deuteration ratios reflecting the apo/holo transition that are in general agreement with values obtained from the corresponding precursor ions. The agreement is limited primarily by the ion statistics for each fragment, as the base peak in the MS/MS spectra provided the best correlation regardless of its m/z. We highlight that the freedom to select the base peak as a surrogate for the precursor ion derives from extensive H/D scrambling inducible under conventional CID conditions. When spectral interference prohibits conventional H/DX-MS measurements, we further show that the surrogate approach recovers accurate and precise per-peptide deuteration levels. Thus, a generalized strategy is presented in which CID-based automated H/DX-MS/MS acquisition can be used to extend measurements to complex protein systems, exceeding the peptide capacity of conventional H/DX-MS alone.

Hydra: software for tailored processing of H/D exchange data from MS or tandem MS analyses.

BACKGROUND: Hydrogen/deuterium exchange mass spectrometry (H/DX-MS) experiments implemented to characterize protein interaction and protein folding generate large quantities of data. Organizing, processing and visualizing data requires an automated solution, particularly when accommodating new tandem mass spectrometry modes for H/DX measurement. We sought to develop software that offers flexibility in defining workflows so as to support exploratory treatments of H/DX-MS data, with a particular focus on the analysis of very large protein systems and the mining of tandem mass spectrometry data. RESULTS: We present a software package ("Hydra") that supports both traditional and exploratory treatments of H/DX-MS data. Hydra's software architecture tolerates flexible data analysis procedures by allowing the addition of new algorithms without significant change to the underlying code base. Convenient user interfaces ease the organization of raw data files and input of peptide data. After executing a user-defined workflow, extracted deuterium incorporation values can be visualized in tabular and graphical formats. Hydra also automates the extraction and visualization of deuterium distribution values. Manual validation and assessment of results is aided by an interface that aligns extracted ion chromatograms and mass spectra, while providing a means of rapidly reprocessing the data following manual adjustment. A unique feature of Hydra is the automated processing of tandem mass spectrometry data, demonstrated on a large test data set in which 40,000 deuterium incorporation values were extracted from replicate analysis of approximately 1000 fragment ions in one hour using a typical PC. CONCLUSION: The customizable workflows and user-friendly interfaces of Hydra removes a significant bottleneck in processing and visualizing H/DX-MS data and helps the researcher spend more time executing new experiments and interpreting results. This increased efficiency will encourage the analysis of larger protein systems. The ability to accommodate the tandem MS dimension supports alternative data collection and analysis strategies, as well as higher resolution localization of deuteration where permitted by the fragmentation mechanism.

Structural mass spectrometry of the alpha beta-tubulin dimer supports a revised model of microtubule assembly.

The molecular basis of microtubule lattice instability derives from the hydrolysis of GTP to GDP in the lattice-bound state of alphabeta-tubulin. While this has been appreciated for many years, there is ongoing debate over the molecular basis of this instability and the possible role of altered nucleotide occupancy in the induction of a conformational change in tubulin. The debate has organized around seemingly contradictory models. The allosteric model invokes nucleotide-dependent states of curvature in the free tubulin dimer, such that hydrolysis leads to pronounced bending and thus disruption of the lattice. The more recent lattice model describes a predominant role for the lattice in straightening free dimers that are curved regardless of their nucleotide state. In this model, lattice-bound GTP-tubulin provides the necessary force to straighten an incoming dimer. Interestingly, there is evidence for both models. The enduring nature of this debate stems from a lack of high-resolution data on the free dimer. In this study, we have prepared alphabeta-tubulin samples at high dilution and characterized the nature of nucleotide-induced conformational stability using bottom-up hydrogen/deuterium exchange mass spectrometry (H/DX-MS) coupled with isothermal urea denaturation experiments. These experiments were accompanied by molecular dynamics simulations of the free dimer. We demonstrate an intermediate state unique to GDP-tubulin, suggestive of the curved colchicine-stabilized structure at the intradimer interface but show that intradimer flexibility is an important property of the free dimer regardless of nucleotide occupancy. Our results indicate that the assembly properties of the free dimer may be better described on the basis of this flexibility. A blended model of assembly emerges in which free-dimer allosteric effects retain importance, in an assembly process dominated by lattice-induced effects.

Integrating accelerated tryptic digestion into proteomics workflows.

An accelerated protein digestion procedure is described that features a microscale trypsin cartridge operated under aqueous-organic conditions. High sequence coverage digestions obtained in seconds with small amounts of enzyme are possible with the approach, which also supports online integration of digestion with reversed-phase protein separation. The construction and operation of effective digestor cartridges for rapid sample processing are described. For workflows involving chromatographic protein separation an easily assembled fluidic system is presented, which inserts the digestion step after column-based separation. Successful integration requires dynamic effluent titration immediately prior to transmission through the digestor. This is achieved through the co-ordination of the column gradient system with an inverse gradient system to produce steady pH and organic solvent levels. System assembly and operation sufficient for achieving digestion and identification of subnanogram levels of protein are described.

Restraining expansion of the peak envelope in H/D exchange-MS and its application in detecting perturbations of protein structure/dynamics.

Hydrogen/deuterium exchange (H/DX) mass spectrometry (MS) is increasingly applied to problems in protein structural biology in order to map protein dynamics and identify sites of interactions. In theory, an MS-based readout of deuterium label incorporation can overcome the concentration, size, purity, and complexity limitations inherent in NMR-based measurements of exchange; however, in practice, these advantages are reduced due to spectral interference and dilution of the sample in deuterium oxide (D 2O). In this study, we demonstrate that popular H/DX labeling strategies aggravate the interference problem and that significant recovery of spectral capacity may be achieved with a "minimalist" strategy. Simulations of peptide deuteration justify large reductions in the level of D 2O used in labeling experiments, as well as reduced numbers of peaks used in making relative labeling measurements between biochemical states of a protein. To demonstrate the utility of a minimalist approach, calmodulin was interrogated in a bottom-up H/DX-MS workflow, and sensitivity to the addition of Ca (2+) as a structural perturbation was measured as a function of % D 2O and the number of peaks used in quantitating deuteration level. It is shown that high sensitivity to change is preserved with deuteration levels of 5.0 +/- 1.1 (apo-CaM) and 1.4 +/- 1.3% (holo-CaM) using 10% D 2O in the labeling experiment. Further, only two peaks of a peptide peak distribution are needed to sensitively monitor changes in protein structure, dynamics, or both.