Search

Floodplain soils are vast reservoirs of organic carbon often attributed to anaerobic conditions that impose metabolic constraints on organic matter degradation. What remains elusive is how such metabolic constraints respond to dynamic flooding and drainage cycles characteristic of floodplain soils. Here we show that microbial depolymerization and respiration of organic compounds, two rate-limiting steps in decomposition, vary spatially and temporally with seasonal flooding of mountainous floodplain soils (Gothic, Colorado, USA). Combining metabolomics and -proteomics, we found a lower abundance of oxidative enzymes during flooding coincided with the accumulation of aromatic, high-molecular weight compounds, particularly in surface soils. In subsurface soils, we found that a lower oxidation state of carbon coincided with a greater abundance of chemically reduced, energetically less favorable low-molecular weight metabolites, irrespective of flooding condition. Our results suggest that seasonal flooding temporarily constrains oxidative depolymerization of larger, potentially plant-derived compounds in surface soils; in contrast, energetic constraints on microbial respiration persist in more reducing subsurface soils regardless of flooding. Our work underscores that the potential vulnerability of these distinct anaerobic carbon storage mechanisms to changing flooding dynamics should be considered, particularly as climate change shifts both the frequency and extent of flooding in floodplains globally.

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. We present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ∼5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

Characterization of the metabolic heterogeneity in cell populations requires the analysis of single cells. Most current methods in single-cell analysis rely on cell manipulation, potentially altering the abundance of metabolites in individual cells. A small sample volume and the chemical diversity of metabolites are additional challenges in single-cell metabolomics. Here, we describe the combination of fiber-based laser ablation electrospray ionization (f-LAESI) with 21 T Fourier transform ion cyclotron resonance mass spectrometry (21TFTICR-MS) for in situ single-cell metabolic profiling in plant tissue. Single plant cells infected by bacteria were selected and sampled directly from the tissue without cell manipulation through mid-infrared ablation with a fine optical fiber tip for ionization by f-LAESI. Ultrahigh performance 21T-FTICR-MS enabled the simultaneous capture of isotopic fine structures (IFSs) for 47 known and 11 unknown compounds, thus elucidating their elemental compositions from single cells and providing information on metabolic heterogeneity in the cell population.

van Krevelen diagrams (O/C vs H/C ratios of elemental formulas) have been widely used in studies to obtain an estimation of the main compound categories present in environmental samples. However, the limits defining a specific compound category based solely on O/C and H/C ratios of elemental formulas have never been accurately listed or proposed to classify metabolites in biological samples. Furthermore, while O/C vs H/C ratios of elemental formulas can provide an overview of the compound categories, such classification is inefficient because of the large overlap among different compound categories along both axes. We propose a more accurate compound classification for biological samples analyzed by high-resolution mass spectrometry based on an assessment of the C/H/O/N/P stoichiometric ratios of over 130 000 elemental formulas of compounds classified in 6 main categories: lipids, peptides, amino sugars, carbohydrates, nucleotides, and phytochemical compounds (oxy-aromatic compounds). Our multidimensional stoichiometric compound classification (MSCC) constraints showed a highly accurate categorization of elemental formulas to the main compound categories in biological samples with over 98% of accuracy representing a substantial improvement over any classification based on the classic van Krevelen diagram. This method represents a signficant step forward in environmental research, especially ecological stoichiometry and eco-metabolomics studies, by providing a novel and robust tool to improve our understanding of the ecosystem structure and function through the chemical characterization of biological samples.

Ultrahigh resolution mass spectrometry, such as Fourier transform ion cyclotron resonance mass spectrometry (FT ICR MS), can resolve thousands of molecular ions in complex organic matrices. A Compound Identification Algorithm (CIA) was previously developed for automated elemental formula assignment for natural organic matter (NOM). In this work, we describe software Formularity with a user-friendly interface for CIA function and newly developed search function Isotopic Pattern Algorithm (IPA). While CIA assigns elemental formulas for compounds containing C, H, O, N, S, and P, IPA is capable of assigning formulas for compounds containing other elements. We used halogenated organic compounds (HOC), a chemical class that is ubiquitous in nature as well as anthropogenic systems, as an example to demonstrate the capability of Formularity with IPA. A HOC standard mix was used to evaluate the identification confidence of IPA. Tap water and HOC spike in Suwannee River NOM were used to assess HOC identification in complex environmental samples. Strategies for reconciliation of CIA and IPA assignments were discussed. Software and sample databases with documentation are freely available.

Secondary organic aerosol (SOA), formed in the photooxidation of diesel fuel, biodiesel fuel, and 20% biodiesel fuel/80% diesel fuel mixture, are prepared under high-NO x conditions in the presence and absence of sulfur dioxide (SO 2 ), ammonia (NH 3 ), and relative humidity (RH). The composition of condensed-phase organic compounds in SOA is measured using several complementary techniques including aerosol mass spectrometry (AMS), high-resolution nanospray desorption electrospray ionization mass spectrometry (nano-DESI/HRMS), and ultrahigh resolution and mass accuracy 21T Fourier transform ion cyclotron resonance mass spectrometry (21T FT-ICR MS). Results demonstrate that sulfuric acid and condensed organosulfur species formed in photooxidation experiments with SO 2 are present in the SOA particles. Fewer organosulfur species are formed in the high humidity experiments, performed at RH 90%, in comparison with experiments done under dry conditions. There is a strong overlap of organosulfur species observed in this study with previous field and chamber studies of SOA. Many MS peaks of organosulfates (R-OS(O) 2 OH) previously designated as biogenic or of unknown origin in field studies might have originated from anthropogenic sources, such as photooxidation of hydrocarbons present in diesel and biodiesel fuel.

Various proteoforms may be generated from a single gene due to primary structure alterations (PSAs) such as genetic variations, alternative splicing, and post-translational modifications (PTMs). Top-down mass spectrometry is capable of analyzing intact proteins and identifying patterns of multiple PSAs, making it the method of choice for studying complex proteoforms. In top-down proteomics, proteoform identification is often performed by searching tandem mass spectra against a protein sequence database that contains only one reference protein sequence for each gene or transcript variant in a proteome. Because of the incompleteness of the protein database, an identified proteoform may contain unknown PSAs compared with the reference sequence. Proteoform characterization is to identify and localize PSAs in a proteoform. Although many software tools have been proposed for proteoform identification by top-down mass spectrometry, the characterization of proteoforms in identified proteoform-spectrum matches still relies mainly on manual annotation. We propose to use the Modification Identification Score (MIScore), which is based on Bayesian models, to automatically identify and localize PTMs in proteoforms. Experiments showed that the MIScore is accurate in identifying and localizing one or two modifications.

Wetlands attenuate the migration of many contaminants through a wide range of biogeochemical reactions. Recent research has shown that the rhizosphere, the zone near plant roots, in wetlands is especially effective at promoting contaminant attenuation. The objective of this study was to compare the soil organic matter (OM) composition and microbial communities of a rhizosphere soil (primarily an oxidized environment) to that of the bulk wetland soil (primarily a reduced environment). The rhizosphere had elevated C, N, Mn, and Fe concentrations and total bacteria, including Anaeromyxobacter, counts (as identified by qPCR). Furthermore, the rhizosphere contained several organic molecules that were not identified in the nonrhizosphere soil (54% of the >2200 ESI-FTICR-MS identified compounds). The rhizosphere OM molecules generally had (1) greater overall molecular weights, (2) less aromaticity, (3) more carboxylate and N-containing COO functional groups, and (4) a greater hydrophilic character. These latter two OM properties typically promote metal binding. This study showed for the first time that not only the amount but also the molecular characteristics of OM in the rhizosphere may in part be responsible for the enhanced immobilization of contaminants in wetlands. These finding have implications on the stewardship and long-term management of contaminated wetlands.

De novo sequencing of proteins and peptides is one of the most important problems in mass spectrometry-driven proteomics. A variety of methods have been developed to accomplish this task from a set of bottom-up tandem (MS/MS) mass spectra. However, a more recently emerged top-down technology, now gaining more and more popularity, opens new perspectives for protein analysis and characterization, implying a need for efficient algorithms to process this kind of MS/MS data. Here, we describe a method that allows for the retrieval, from a set of top-down MS/MS spectra, of long and accurate sequence fragments of the proteins contained in the sample. To this end, we outline a strategy for generating high-quality sequence tags from top-down spectra, and introduce the concept of a T-Bruijn graph by adapting to the case of tags the notion of an A-Bruijn graph widely used in genomics. The output of the proposed approach represents the set of amino acid strings spelled out by optimal paths in the connected components of a T-Bruijn graph. We illustrate its performance on top-down data sets acquired from carbonic anhydrase 2 (CAH2) and the Fab region of alemtuzumab.

Soil organic matter (SOM), a complex, heterogeneous mixture of above and belowground plant litter and animal and microbial residues at various degrees of decomposition, is a key reservoir for carbon (C) and nutrient biogeochemical cycling in soil based ecosystems. A limited understanding of the molecular composition of SOM limits the ability to routinely decipher chemical processes within soil and accurately predict how terrestrial carbon fluxes will respond to changing climatic conditions and land use. To elucidate the molecular-level structure of SOM, we selectively extracted a broad range of intact SOM compounds by a combination of different organic solvents from soils with a wide range of C content. Our use of electrospray ionization (ESI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) and a suite of solvents with varying polarity significantly expands the inventory of the types of organic molecules present in soils. Specifically, we found that hexane is selective for lipid-like compounds with very low O/C ratios (<0.1); water (H2O) was selective for carbohydrates with high O/C ratios; acetonitrile (ACN) preferentially extracts lignin, condensed structures, and tannin polyphenolic compounds with O/C > 0.5; methanol (MeOH) has higher selectivity toward compounds characterized with low O/C < 0.5; and hexane, MeOH, ACN, and H2O solvents increase the number and types of organic molecules extracted from soil for a broader range of chemically diverse soil types. Our study of SOM molecules by ESI FTICR MS revealed new insight into the molecular-level complexity of organics contained in soils. We present the first comparative study of the molecular composition of SOM from different ecosystems using ultra high-resolution mass spectrometry.

There are two approaches for de novo protein sequencing: Edman degradation and mass spectrometry (MS). Existing MS-based methods characterize a novel protein by assembling tandem mass spectra of overlapping peptides generated from multiple proteolytic digestions of the protein. Because each tandem mass spectrum covers only a short peptide of the target protein, the key to high coverage protein sequencing is to find spectral pairs from overlapping peptides in order to assemble tandem mass spectra to long ones. However, overlapping regions of peptides may be too short to be confidently identified. High-resolution mass spectrometers have become accessible to many laboratories. These mass spectrometers are capable of analyzing molecules of large mass values, boosting the development of top-down MS. Top-down tandem mass spectra cover whole proteins. However, top-down tandem mass spectra, even combined, rarely provide full ion fragmentation coverage of a protein. We propose an algorithm, TBNovo, for de novo protein sequencing by combining top-down and bottom-up MS. In TBNovo, a top-down tandem mass spectrum is utilized as a scaffold, and bottom-up tandem mass spectra are aligned to the scaffold to increase sequence coverage. Experiments on data sets of two proteins showed that TBNovo achieved high sequence coverage and high sequence accuracy.

Post-translational modifications (PTMs) play an important role in various biological processes through changing protein structure and function. Some ultramodified proteins (like histones) have multiple PTMs forming PTM patterns that define the functionality of a protein. While bottom-up mass spectrometry (MS) has been successful in identifying individual PTMs within short peptides, it is unable to identify PTM patterns spreading along entire proteins in a coordinated fashion. In contrast, top-down MS analyzes intact proteins and reveals PTM patterns along the entire proteins. However, while recent advances in instrumentation have made top-down MS accessible to many laboratories, most computational tools for top-down MS focus on proteins with few PTMs and are unable to identify complex PTM patterns. We propose a new algorithm, MS-Align-E, that identifies both expected and unexpected PTMs in ultramodified proteins. We demonstrate that MS-Align-E identifies many proteoforms of histone H4 and benchmark it against the currently accepted software tools.

MS dissociation methods, including collision induced dissociation (CID), high energy collision dissociation (HCD), and electron transfer dissociation (ETD), can each contribute distinct peptidome identifications using conventional peptide identification methods (Shen et al. J. Proteome Res. 2011), but such samples still pose significant informatics challenges. In this work, we explored utilization of high accuracy fragment ion mass measurements, in this case provided by Fourier transform MS/MS, to improve peptidome peptide data set size and consistency relative to conventional descriptive and probabilistic scoring methods. For example, we identified 20-40% more peptides than SEQUEST, Mascot, and MS&#95;GF scoring methods using high accuracy fragment ion information and the same false discovery rate (FDR) from CID, HCD, and ETD spectra. Identified species covered >90% of the collective identifications obtained using various conventional peptide identification methods, which significantly addresses the common issue of different data analysis methods generating different peptide data sets. Choice of peptide dissociation and high-precision measurement-based identification methods presently available for degradomic-peptidomic analyses needs to be based on the coverage and confidence (or specificity) afforded by the method, as well as practical issues (e.g., throughput). By using accurate fragment information, >1000 peptidome components can be identified from a single human blood plasma analysis with low peptide-level FDRs (e.g., 0.6%), providing an improved basis for investigating potential disease-related peptidome components.

We report on the effectiveness of CID, HCD, and ETD for LC-FT MS/MS analysis of peptides using a tandem linear ion trap-Orbitrap mass spectrometer. A range of software tools and analysis parameters were employed to explore the use of CID, HCD, and ETD to identify peptides (isolated from human blood plasma) without the use of specific "enzyme rules". In the evaluation of an FDR-controlled SEQUEST scoring method, the use of accurate masses for fragments increased the number of identified peptides (by ~50%) compared to the use of conventional low accuracy fragment mass information, and CID provided the largest contribution to the identified peptide data sets compared to HCD and ETD. The FDR-controlled Mascot scoring method provided significantly fewer peptide identifications than SEQUEST (by 1.3-2.3 fold) and CID, HCD, and ETD provided similar contributions to identified peptides. Evaluation of de novo sequencing and the UStags method for more intense fragment ions revealed that HCD afforded more contiguous residues (e.g., ≥ 7 amino acids) than either CID or ETD. Both the FDR-controlled SEQUEST and Mascot scoring methods provided peptide data sets that were affected by the decoy database used and mass tolerances applied (e.g., identical peptides between data sets could be limited to ~70%), while the UStags method provided the most consistent peptide data sets (>90% overlap). The m/z ranges in which CID, HCD, and ETD contributed the largest number of peptide identifications were substantially overlapping. This work suggests that the three peptide ion fragmentation methods are complementary and that maximizing the number of peptide identifications benefits significantly from a careful match with the informatics tools and methods applied. These results also suggest that the decoy strategy may inaccurately estimate identification FDRs.

Disulfide bonds are a form of post-translational modification that often determines protein structure(s) and function(s). In this work, we report a mass spectrometry method for identification of disulfides in degradation products of proteins, specifically endogenous peptides in the human blood plasma peptidome. LC-Fourier transform tandem mass spectrometry (FT MS/MS) was used for acquiring mass spectra that were de novo sequenced and then searched against the IPI human protein database. Through the use of unique sequence tags (UStags), we unambiguously correlated the spectra to specific database proteins. Examination of the UStags' prefix and/or suffix sequences that contain cysteine(s) in conjunction with sequences of the UStags-specified database proteins is shown to enable the unambigious determination of disulfide bonds. Using this method, we identified the intermolecular and intramolecular disulfides in human blood plasma peptidome peptides that have molecular weights of up to approximately 10 kDa.

Herein we describe a strategy for degradomic-peptidomic analyses. The human blood peptidome was isolated through application of AC/SEC, which enriched its components by >300-fold. The isolated peptidome components were separated by long column HRLC providing a peak capacity of approximately 300 for species having MWs of up to 20 kDa. The separated species were identified by the FT MS/MS-UStags sequencing method. We identified >200 peptidome components that originated from 29 protein substrates from the blood plasma of a single healthy person. The peptidome peptides identified had MWs range of 0.5-14 kDa and identifications were achieved with extremely low (near zero) false discovery rates through searching the IPI human protein database (approximately 70,000 entries). Some of the peptidome peptides identified have mutations and modifications such as acetylation, acetylhexosamine, amidation, cysteinylation, didehydro, oxidation, and pyro-glu. The capabilities described enable the global analysis of the peptidome peptides to identify degradome targets such as degradome proteases, proteases inhibitors, and other relevant substrates, the cleavage specificities for the degradation of individual substrates, as well as a potential basis for using the various extents of substrate degradation for diagnostic purposes.

Chemical cross-linking combined with mass spectrometry can be a powerful approach for the identification of protein-protein interactions and for providing constraints on protein structures. However, enrichment of cross-linked peptides is crucial to reduce sample complexity before mass spectrometric analysis. In addition compact cross-linkers are often preferred to provide short spacer lengths, surface accessibility to the protein complexes, and must have reasonable solubility under conditions where the native complex structure is stable. In this study, we present a novel compact cross-linker that contains two distinct features: (1) an alkyne tag and (2) a small molecule detection tag (NO(2)) to maintain reasonable solubility in water. The alkyne tag enables enrichment of the cross-linked peptides after proteolytic cleavage and coupling of an affinity tag using alkyne-azido click chemistry. Neutral loss of the small NO(2) moiety provides a secondary means of detecting cross-linked peptides in MS/MS analyses, providing additional confidence in peptide identifications. We show the labeling efficiency of this cross-linker, which we termed CLIP (click-enabled linker for interacting proteins) using ubiquitin. The enrichment capability of CLIP is demonstrated for cross-linked ubiquitin in highly complex E. coli cell lysates. Sequential collision-induced dissociation tandem mass spectrometry (CID-MS/MS) and electron transfer dissociation (ETD)-MS/MS of intercross-linked peptides (two peptides connected with a cross-linker) are also demonstrated for improved automated identification of cross-linked peptides.

The phosphorylation of any site on a given protein can affect its activity, degradation rate, ability to dock with other proteins or bind divalent cations, and/or its localization. These effects can operate within the same protein; in fact, multisite phosphorylation is a key mechanism for achieving signal integration in cells. Hence, knowing the overall phosphorylation signature of a protein is essential for understanding the "state" of a cell. However, current technologies to monitor the phosphorylation status of proteins are inefficient at determining the relative stoichiometries of phosphorylation at multiple sites. Here we report a new capability for comprehensive liquid chromatography mass spectrometry (LC/MS) analysis of intact phosphoproteins. The technology platform builds upon an integration of bottom-up and top-down approaches that is facilitated by intact protein reversed-phase (RP)LC concurrently coupled with Fourier transform ion cyclotron resonance (FTICR) MS and fraction collection. As the use of conventional RPLC systems for phosphopeptide identification has proven challenging due to the formation of metal ion complexes at various metal surfaces during LC/MS and ESI-MS analysis, we have developed a "metal-free" RPLC-ESI-MS platform for phosphoprotein characterization. This platform demonstrated a significant sensitivity enhancement for phosphorylated casein proteins enriched from a standard protein mixture and revealed the presence of over 20 casein isoforms arising from genetic variants with varying numbers of phosphorylation sites. The integrated workflow was also applied to an enriched yeast phosphoproteome to evaluate the feasibility of this strategy for characterizing complex biological systems and revealed approximately 16% of the detected yeast proteins to have multiple phosphorylation isoforms. The intact protein LC/MS platform for characterization of combinatorial post-translational modifications (PTMs), with special emphasis on multisite phosphorylation, holds great promise to significantly extend our understanding of the roles of multiple PTMs on signaling components that control the cellular responses to various stimuli.

Here, we report a new approach that integrates pulsed Q dissociation (PQD) and electron transfer dissociation (ETD) techniques for confident and quantitative identification of iTRAQ-labeled phosphopeptides. The use of isobaric tags for relative and absolute quantification enables a high-throughput quantification of peptides via reporter ion signals in the low m/z range of tandem mass spectra. PQD, a form of ion trap collision activated dissociation, allows for detection of low mass-to-charge fragment ions, and electron transfer dissociation is especially useful for sequencing peptides that contain post-translational modifications. Analysis of the phosphoproteome of human fibroblast cells using a sensitive linear ion trap mass spectrometer demonstrated that this hybrid approach improves both identification and quantification of phosphopeptides. ETD improved phosphopeptide identification, while PQD provides improved quantification of iTRAQ-labeled phosphopeptides.

We present an integrated top-down and bottom-up approach that is facilitated by concurrent liquid chromatography-mass spectrometry (LC-MS) analysis and fraction collection for comprehensive high-throughput intact protein profiling. The approach employs high-resolution, reversed-phase (RP) LC separations coupled on-line with a 12 T Fourier transform ion cyclotron resonance (FTICR) mass spectrometer to profile and tentatively identify modified proteins, using detected intact protein masses in conjunction with bare protein identifications from the bottom-up analysis of the corresponding LC fractions. Selected identifications are incorporated into a target ion list for subsequent off-line gas-phase fragmentation that uses an aliquot of the original fraction used for bottom-up analysis. In a proof-of-principle demonstration, this comprehensive strategy was applied to identify protein isoforms arising from various amino acid modifications (e.g., acetylation, phosphorylation) and genetic variants (e.g., single nucleotide polymorphisms, SNPs). This strategy overcomes major limitations of traditional bottom-up (e.g., inability to characterize multiple unexpected protein isoforms and genetic variants) and top-down (e.g., low throughput) approaches.

De novo sequencing is a spectrum analysis approach for mass spectrometry data to discover post-translational modifications in proteins; however, such an approach is still in its infancy and is still not widely applied to proteomic practices due to its limited reliability. In this work, we describe a de novo sequencing approach for the discovery of protein modifications based on identification of the proteome UStags (Shen, Y.; Tolić, N.; Hixson, K. K.; Purvine, S. O.; Pasa-Tolić, L.; Qian, W. J.; Adkins, J. N.; Moore, R. J.; Smith, R. D. Anal. Chem. 2008, 80, 1871-1882). The de novo information was obtained from Fourier-transform tandem mass spectrometry data for peptides and polypeptides from a yeast lysate, and the de novo sequences obtained were selected based on filter levels designed to provide a limited yet high quality subset of UStags. The DNA-predicted database protein sequences were then compared to the UStags, and the differences observed across or in the UStags (i.e., the UStags' prefix and suffix sequences and the UStags themselves) were used to infer possible sequence modifications. With this de novo-UStag approach, we uncovered some unexpected variances within several yeast protein sequences due to amino acid mutations and/or multiple modifications to the predicted protein sequences. To determine false discovery rates, two random (false) databases were independently used for sequence matching, and ~3% false discovery rates were estimated for the de novo-UStag approach. The factors affecting the reliability (e.g., existence of de novo sequencing noise residues and redundant sequences) and the sensitivity of the approach were investigated and described. The combined de novo-UStag approach complements the UStag method previously reported by enabling the discovery of new protein modifications.

Protein proteolytic degradation is an essential component to proper cell function and its life cycle. Here, we study the protein degradation in yeast Saccharomyces cerevisiae cells on a proteome-wide scale by detection of the intermediate peptides produced from the intracellular degradation of proteins using sequencing-based tandem mass spectrometry. By tracing the detected approximately 1100 peptides and their approximately 200 protein-substrate origins we obtain evidence for new insights into the proteome-wide protein-selective degradation in yeast cells. This evidence shows that the yeast cytoplasm is the largest pool for the degradation of proteins with both biochemical and geometric specificities, whereas the yeast nucleus seems to be a proteolysis-inert organelle under the condition studied. Yeast V-ATPase subunits appear to be degraded during their disassembly, and yeast mitochondrial proteins functioning as precursors, transport carriers, and gates are preferentially degraded. Ubiquitylation may be unnecessary for the proteasomal degradation of yeast cytoplasmic regulatory and enzyme proteins according to our observations. This study shows that the intracellular peptides are informational targets for directly probing the protein degradation-involved molecular mechanisms and cell biology processes.

Identifying proteins and their modification states and with known levels of confidence remains as a significant challenge for proteomics. Random or decoy peptide databases are increasingly being used to estimate the false discovery rate (FDR), e.g., from liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of tryptic digests. We show that this approach can significantly underestimate the FDR and describe an approach for more confident protein identifications that uses unique partial sequences derived from a combination of database searching and amino acid residue sequencing using high-accuracy MS/MS data. Applied to a Saccharomyces cerevisiae tryptic digest, the approach provided 3 132 confident peptide identifications ( approximately 5% modified in some fashion), covering 575 proteins with an estimated zero FDR. The conventional approach provided 3 359 peptide identifications and 656 proteins with 0.3% FDR based upon a decoy database analysis. However, the present approach revealed approximately 5% of the 3 359 identifications to be incorrect and many more as potentially ambiguous (e.g., due to not considering certain amino acid substitutions and modifications). In addition, 677 peptides and 39 proteins were identified that had been missed by conventional analysis, including nontryptic peptides, peptides with a variety of expected/unexpected chemical modifications, known/unknown post-translational modifications, single nucleotide polymorphisms or gene encoding errors, and multiple modifications of individual peptides.

We investigated the combination of weak anion exchange (WAX) fractionation and on-line reversed-phase liquid chromatography (RPLC) separation using a 12 T FTICR mass spectrometer for the detection of intact proteins from a Shewanella oneidensis MR-1 cell lysate. This work aimed at optimizing intact protein detection for profiling proteins at a level that incorporates their modification state. A total of 715 intact proteins were detected, and the combined results from the WAX fractions and the unfractionated cell lysate were aligned using LC-MS features to facilitate protein abundance measurements. Protein identifications and post-translational modifications were assigned for approximately 10% of the detected proteins by comparing intact protein mass measurements to proteins identified in peptide MS/MS analysis of an aliquot of the same fraction. Intact proteins were also detected for S. oneidensis lysates obtained from cells grown on 13C-, 15N-depleted media under aerobic and sub-oxic conditions. The strategy can be readily applied for measuring differential protein abundances and provides a platform for high-throughput selection of biologically relevant targets for further characterization.

In proteomics, effective methods are needed for identifying the relatively limited subset of proteins displaying significant changes in abundance between two samples. One way to accomplish this task is to target for identification by MS/MS only the "interesting" proteins based on the abundance ratio of isotopically labeled pairs of peptides. We have developed the software and hardware tools for online LC-FTICR MS/MS studies in which a set of initially unidentified peptides from a proteome analysis can be selected for identification based on their distinctive changes in abundance following a "perturbation". We report here the validation of this method using a mixture of standard proteins combined in different ratios after isotopic labeling. We also demonstrate the application of this method to the identification of Shewanella oneidensis peptides/proteins exhibiting differential abundance in suboxic versus aerobic cell cultures.

Ultrasensitive nanoscale proteomics approaches for characterizing proteins from complex proteomic samples of <50 ng of total mass are described. Protein identifications from 0.5 pg of whole proteome extracts were enabled by ultrahigh sensitivity (<75 zmol for individual proteins) achieved using high-efficiency (peak capacities of approximately 10(3)) 15-microm-i.d. capillary liquid chromatography separations (i.e., using nanoLC, approximately 20 nL/min mobile-phase flow rate at the optimal linear velocity of approximately 0.2 cm/s) coupled on-line with a micro-solid-phase sample extraction and a nanoscale electrospray ionization interface to a 11.4-T Fourier transform ion cyclotron resonance (FTICR) mass spectrometer (MS). Proteome measurement coverage improved as sample size was increased from as little as 0.5 pg of sample. It was found that a 2.5-ng sample provided 14% coverage of all annotated open reading frames for the microorganism Deinococcus radiodurans, consistent with previous results for a specific culture condition. The estimated detection dynamic range for detected proteins was 10(5)-10(6). An improved accurate mass and LC elution time two-dimensional data analysis methodology, used to both speed and increase the confidence of peptide/protein identifications, enabled identification of 872 proteins/run from a single 3-h nanoLC/FTICR MS analysis. The low-zeptomole-level sensitivity provides a basis for extending proteomics studies to smaller cell populations and potentially to a single mammalian cell. Application with ion trap MS/MS instrumentation allowed protein identification from 50 pg (total mass) of proteomic samples (i.e., approximately 100 times larger than FTICR MS), corresponding to a sensitivity of approximately 7 amol for individual proteins. Compared with single-stage FTICR measurements, ion trap MS/MS provided a much lower proteome measurement coverage and dynamic range for a given analysis time and sample quantity.

This work focuses on the development of a multidimensional electrokinetic-based separation/concentration platform coupled with electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR-MS) for achieving the high resolution and ultrasensitive analysis of complex protein/peptide mixtures. A microdialysis junction is employed as the interface for on-line combination of capillary isoelectric focusing (CIEF) with transient capillary isotachophoresis/zone electrophoresis (CITP/CZE) in an integrated platform. Besides the excellent resolving power afforded by both CIEF and CZE separations, the electrokinetic focusing/stacking effects of CIEF and CITP greatly enhance the dynamic range and detection sensitivity of MS for protein identification. The constructed multidimensional separation/concentration platform is demonstrated for the analysis of Shewanella oneidensis proteome, which has considerable implications toward the bioremediation of environmental pollutants. The electrokinetic-based platform offers the overall peak capacity comparable to those obtained using multidimensional chromatography systems, but with a much shorter run time and no need for column regeneration. Most importantly, a total of 1174 unique proteins, corresponding to 26.5% proteome coverage, are identified from the cytosolic fraction of S. oneidensis, while requiring <500 ng of proteolytic digest loaded in the CIEF capillary. The ultrasensitive capabilities of electrokinetic-based proteome approach are attributed to the concentration effect in CIEF, the electrokinetic stacking of CITP, the nanoscale peak volume in CZE, the "accurate mass tag" strategy for protein/peptide identification, and the high-sensitivity, high-resolution, and high-mass measurement accuracy of FTICR-MS.

In this work, we describe the application of a stable isotope amino acid (lysine) labeling in conjunction with data-dependent multiplexed tandem mass spectrometry (MS/MS) to facilitate the characterization and identification of peptides from proteomic (global protein) digests. Lysine auxotrophic yeast was grown in the presence of 13C-labeled or unlabeled lysine and combined after harvesting in equal proportions. Endoproteinase LysC digestion of the cytosolic fraction produced a global proteomic sample, consisting of heavy/light labeled peptide pairs. Then data-dependent multiplexed-MS/MS was applied to simultaneously select and dissociate only labeled peptide ion pairs. The approach allows differentiation between N-terminal (e.g., b-type ions) and C-terminal fragment ions (e.g., y-type ions) in resulting tandem mass spectra, as well as the capability of differentiation between near-isobaric glutamine and lysine residues. We also describe the utility of peptide composition and fragment information to support peptide identifications and examine the potential application of lysine labeling for differential quantitative protein analysis.

Tandem mass spectrometry (MS/MS) plays an important role in the unambiguous identification and structural elucidation of biomolecules. In contrast to conventional MS/MS approaches for protein identification where an individual polypeptide is sequentially selected and dissociated, a multiplexed-MS/MS approach increases throughput by selecting several peptides for simultaneous dissociation using either infrared multiphoton dissociation (IRMPD) or multiple frequency sustained off-resonance irradiation (SORI) collisionally induced dissociation (CID). The high mass measurement accuracy and resolution of FTICR combined with knowledge of peptide dissociation pathways allows the fragments arising from several different parent ions to be assigned. Herein we report the application of multiplexed-MS/MS coupled with on-line separations for the identification of peptides present in complex mixtures (i.e., whole cell lysate digests). Software was developed to enable "on-the-fly" data-dependent peak selection of a subset of polypeptides from each FTICR MS acquisition. In the subsequent MS/MS acquisitions, several coeluting peptides were fragmented simultaneously using either IRMPD or SORI-CID techniques. The utility of this approach has been demonstrated using a bovine serum albumin tryptic digest separated by capillary LC where multiple peptides were readily identified in single MS/MS acquisitions. We also present initial results from multiplexed-MS/MS analysis of a D. radiodurans whole cell digest to illustrate the utility of this approach for high-throughput analysis of a bacterial proteome.

We report on the design and application of a high-efficiency multiple-capillary liquid chromatography (LC) system for high-throughput proteome analysis. The multiple-capillary LC system using commercial LC pumps was operated at a pressure of 10,000 psi to deliver mobile phases through a novel passive feedback valve arrangement that permitted mobile-phase flow path switching and efficient sample introduction. The multiple-capillary LC system uses several serially connected dual-capillary column devices. The dual-capillary column approach eliminates the time delays for column regeneration (or equilibration) since one capillary column was used for a separation while the other was being washed. Several serially connected dual-capillary columns and electrospray ionization (ESI) sources were operated independently and can be used either for "backup" operation or for parallel operation with other mass spectrometers. This high-efficiency multiple-capillary LC system utilizes switching valves for all operations, enabling automated operation. The separation efficiency of the dual-capillary column arrangement, optimal capillary dimensions (column length and packed particle size), capillary regeneration conditions, and mobile-phase compositions and their compatibility with electrospray ionization were investigated. A high magnetic field (11.4 T) Fourier transform ion cyclotron resonance (FTICR) mass spectrometer was coupled on-line with this high-efficiency multiple-capillary LC system using an ESI interface. The capillary LC provided a peak capacity of approximately 650, and the 2-D capillary LC-FTICR analysis provided a combined resolving power of > 6 x 10(7) components. For yeast cytosolic tryptic digests > 100,000 polypeptides were detected, and approximately 1,000 proteins could be characterized from a single capillary LC-FTICR analysis using the high mass measurement accuracy (approximately 1 ppm) of FTICR, and likely more if LC retention time information were also exploited for peptide identification.