Top-down mass spectrometry of native proteoforms and their complexes: A community study

The combination of native electrospray ionisation with top-down fragmentation in mass spectrometry allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and co-factors. While this approach is powerful, both native mass spectrometry and top-down mass spectrometry are not yet well standardised, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics (CTDP) initiated a study to develop and test protocols for native mass spectrometry combined with top-down fragmentation of proteins and protein complexes across eleven instruments in nine laboratories. The outcomes are summarised in this report to provide robust benchmarks and a valuable entry point for the scientific community.

High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip

Global quantification of protein abundances in single cells could provide direct information on cellular phenotypes and complement transcriptomics measurements. However, single-cell proteomics is still immature and confronts many technical challenges. Herein we describe a nested nanoPOTS (N2) chip to improve protein recovery, operation robustness, and processing throughput for isobaric-labeling-based scProteomics workflow. The N2 chip reduces reaction volume to <30 nL and increases capacity to >240 single cells on a single microchip. The tandem mass tag (TMT) pooling step is simplified by adding a microliter droplet on the nested nanowells to combine labeled single-cell samples. In the analysis of ~100 individual cells from three different cell lines, we demonstrate that the N2 chip-based scProteomics platform can robustly quantify ~1500 proteins and reveal membrane protein markers. Our analyses also reveal low protein abundance variations, suggesting the single-cell proteome profiles are highly stable for the cells cultured under identical conditions.

Cell-Type-Specific Proteomics Analysis of a Small Number of Plant Cells by Integrating Laser Capture Microdissection with a Nanodroplet Sample Processing Platform

Plant organs and tissues contain multiple cell types, which are well organized in 3-dimensional structure to efficiently perform physiological functions such as homeostasis and response to environmental perturbation and pathogen infection. It is critically important to perform molecular measurements at the cell-type-specific level to discover mechanisms and unique features of cell populations that govern differentiation and respond to external perturbations. Although mass spectrometry-based proteomics has been demonstrated as an enabling discovery tool for studying plant physiology, conventional approaches require millions of cells to generate robust biological conclusions. Such requirements mask the cell-to-cell heterogeneities and limit the comprehensive profiling of plant proteins at spatially resolved and cell-type-specific resolutions. This article describes a recently developed proteomics workflow for studying a small number of plant cells by integrating laser capture microdissection, microfluidic nanodroplet-based sample preparation, and ultrasensitive liquid chromatography-mass spectrometry. Using poplar as a model tree species, we provide detailed protocols, including plant leaf and root tissue harvest, sample preparation, cryosectioning, laser microdissection, protein digestion, mass spectrometry measurement, and data analysis. We show that the workflow enables the precise identification and quantification of thousands of proteins from hundreds of isolated plant root and leaf cells. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Plant tissue fixation and embedding Support Protocol 1: Preparation of 2.5% CMC solution Support Protocol 2: Slow freezing of CMC blocks to avoid crack development in the block Basic Protocol 2: Preparation of cryosections Alternate Protocol: Using a vacuum manifold to dehydrate the cryosection slides (primarily for root tissues) Basic Protocol 3: Laser capture microdissection of specific types of plant cells Basic Protocol 4: Nanodroplet-based sample preparation for ultrasensitive proteomic analysis Support Protocol 3: Fabrication of nanowell chips Basic Protocol 5: Liquid chromatography and mass spectrometry.

Mapping Influenza-Induced Posttranslational Modifications on Histones from CD8+ T Cells

T cell function is determined by transcriptional networks that are regulated by epigenetic programming via posttranslational modifications (PTMs) to histone proteins and DNA. Bottom-up mass spectrometry (MS) can identify histone PTMs, whereas intact protein analysis by MS can detect species missed by bottom-up approaches. We used a novel approach of online two-dimensional liquid chromatography-tandem MS with high-resolution reversed-phase liquid chromatography (RPLC), alternating electron transfer dissociation (ETD) and collision-induced dissociation (CID) on precursor ions to maximize fragmentation of uniquely modified species. The first online RPLC separation sorted histone families, then RPLC or weak cation exchange hydrophilic interaction liquid chromatography (WCX-HILIC) separated species heavily clad in PTMs. Tentative identifications were assigned by matching proteoform masses to predicted theoretical masses that were verified with tandem MS. We used this innovative approach for histone-intact protein PTM mapping (HiPTMap) to identify and quantify proteoforms purified from CD8 T cells after in vivo influenza infection. Activation significantly altered PTMs following influenza infection, histone maps changed as T cells migrated to the site of infection, and T cells responding to secondary infections had significantly more transcription enhancing modifications. Thus, HiPTMap identified and quantified proteoforms and determined changes in CD8 T cell histone PTMs over the course of infection.

Storage Conditions of Human Kidney Tissue Sections Affect Spatial Lipidomics Analysis Reproducibility

Lipids often are labile, unstable, and tend to degrade overtime, so it is of the upmost importance to study these molecules in their most native state. We sought to understand the optimal storage conditions for spatial lipidomic analysis of human kidney tissue sections. Specifically, we evaluated human kidney tissue sections on several different days throughout the span of a week using our established protocol for elucidating lipids using high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We studied kidney tissue sections stored under five different conditions: open stored at -80 °C, vacuumed sealed and stored at -80 °C, with matrix preapplied before storage at -80 °C, under a nitrogen atmosphere and stored at -80 °C, and at room temperature in a desiccator. Results were compared to data obtained from kidney tissue sections that were prepared and analyzed immediately after cryosectioning. Data was processed using METASPACE. After a week of storage, the sections stored at room temperature showed the largest amount of lipid degradation, while sections stored under nitrogen and at -80 °C retained the greatest number of overlapping annotations in relation to freshly cut tissue. Overall, we found that molecular degradation of the tissue sections was unavoidable over time, regardless of storage conditions, but storing tissue sections in an inert gas at low temperatures can curtail molecular degradation within tissue sections.

Dynamic metabolic reprogramming in dendritic cells: An early response to influenza infection that is essential for effector function

Infection with the influenza virus triggers an innate immune response that initiates the adaptive response to halt viral replication and spread. However, the metabolic response fueling the molecular mechanisms underlying changes in innate immune cell homeostasis remain undefined. Although influenza increases parasitized cell metabolism, it does not productively replicate in dendritic cells. To dissect these mechanisms, we compared the metabolism of dendritic cells to that of those infected with active and inactive influenza A virus and those treated with toll-like receptor agonists. Using quantitative mass spectrometry, pulse chase substrate utilization assays and metabolic flux measurements, we found global metabolic changes in dendritic cells 17 hours post infection, including significant changes in carbon commitment via glycolysis and glutaminolysis, as well as mitochondrial respiration. Influenza infection of dendritic cells led to a metabolic phenotype distinct from that induced by TLR agonists, with significant resilience in terms of metabolic plasticity. We identified c-Myc as one transcription factor modulating this response. Restriction of c-Myc activity or mitochondrial substrates significantly changed the immune functions of dendritic cells, such as reducing motility and T cell activation. Transcriptome analysis of inflammatory dendritic cells isolated following influenza infection showed similar metabolic reprogramming occurs in vivo. Thus, early in the infection process, dendritic cells respond with global metabolic restructuring, that is present in inflammatory lung dendritic cells after infection, and this is important for effector function. These findings suggest metabolic switching in dendritic cells plays a vital role in initiating the immune response to influenza infection.

Dendritic cells are critical in mounting an effective immune response to influenza infection by initiating the immune response to influenza and activating the adaptive response to mediate viral clearance and manifest immune memory for protection against subsequent infections. We found dendritic cells undergo a profound metabolic shift after infection. They alter the concentration and location of hundreds of proteins, including c-Myc, facilitating a shift to a highly glycolytic phenotype that is also flexible in terms of fueling respiration. Nonetheless, we found limiting access to specific metabolic pathways or substrates diminished key immune functions. We previously described an immediate, fixed hypermetabolic state in infected respiratory epithelial cells. Here we present data indicating the metabolic response of dendritic cells is increased yet flexible, distinct from what we previously showed for epithelial cells. Additionally, we demonstrate dendritic cells tailor their metabolic response to the pathogen or TLR stimulus. This metabolic reprogramming occurs rapidly in vitro and is sustained in inflammatory dendritic cells in vivo for at least 9 days following influenza infection. These studies introduce the possibility of modulating the immune response to viral infection using customized metabolic therapy to enhance or diminish the function of specific cells.

Proteome specialization of anaerobic fungi during ruminal degradation of recalcitrant plant fiber

The rumen harbors a complex microbial mixture of archaea, bacteria, protozoa, and fungi that efficiently breakdown plant biomass and its complex dietary carbohydrates into soluble sugars that can be fermented and subsequently converted into metabolites and nutrients utilized by the host animal. While rumen bacterial populations have been well documented, only a fraction of the rumen eukarya are taxonomically and functionally characterized, despite the recognition that they contribute to the cellulolytic phenotype of the rumen microbiota. To investigate how anaerobic fungi actively engage in digestion of recalcitrant fiber that is resistant to degradation, we resolved genome-centric metaproteome and metatranscriptome datasets generated from switchgrass samples incubated for 48 h in nylon bags within the rumen of cannulated dairy cows. Across a gene catalog covering anaerobic rumen bacteria, fungi and viruses, a significant portion of the detected proteins originated from fungal populations. Intriguingly, the carbohydrate-active enzyme (CAZyme) profile suggested a domain-specific functional specialization, with bacterial populations primarily engaged in the degradation of hemicelluloses, whereas fungi were inferred to target recalcitrant cellulose structures via the detection of a number of endo- and exo-acting enzymes belonging to the glycoside hydrolase (GH) family 5, 6, 8, and 48. Notably, members of the GH48 family were amongst the highest abundant CAZymes and detected representatives from this family also included dockerin domains that are associated with fungal cellulosomes. A eukaryote-selected metatranscriptome further reinforced the contribution of uncultured fungi in the ruminal degradation of recalcitrant fibers. These findings elucidate the intricate networks of in situ recalcitrant fiber deconstruction, and importantly, suggest that the anaerobic rumen fungi contribute a specific set of CAZymes that complement the enzyme repertoire provided by the specialized plant cell wall degrading rumen bacteria.

Abstract 2856: An intelligent boosting to amplify signal with isobaric labeling (iBASIL) strategy for precise quantitative single-cell proteomics analysis

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection (e.g., our recent boosting to amplify signal with isobaric labeling (BASIL) approach) has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have systematically evaluated and optimized the BASIL approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of single cells. This improved, intelligent BASIL (iBASIL) approach enables comprehensive and quantitative single-cell proteomics analysis by carefully controlling the boosting-to-sample ratio and optimizing MS automatic gain control and ion injection time settings. Using standard LC-MS platforms, iBASIL enabled precise quantification of 800-1,200 proteins from single FACS-isolated cells (depending on the cell type). Moreover, coupling iBASIL to nanoscale fractionation enabled identification of &gt;3,000 proteins and reliable quantification of &gt;2,000 proteins while readily separating single cells from 3 different acute myeloid leukemia cell lines. We believe iBASIL has broad utility for comprehensive and precise quantitative single-cell proteomics for systems biology and biomedical research, as well as for comprehensive proteomic analysis of size-limited clinical specimens that cannot be readily accessed by regular proteomics platforms. It also has the potential to be adapted for phosphoproteome analysis of as few as 100 cells.

Citation Format: Chia-Feng Tsai, Rui Zhao, Ronald Moore, Sarah Williams, Kendall Schultz, Paul Piehowski, Ljiljana Pasa-Tolic, Karin Rodland, Richard Smith, Tujin Shi, Ying Zhu, Ying Zhu, Tao Liu. An intelligent boosting to amplify signal with isobaric labeling (iBASIL) strategy for precise quantitative single-cell proteomics analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2856.

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform

Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.

Siderophore profiling of co-habitating soil bacteria by ultra-high resolution mass spectrometry

Calcareous soil microbes complete for scarce iron by synthesizing diverse suites of siderophores detectable by ultra-high resolution mass spectrometry.

ProForma: A Standard Proteoform Notation

The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Targeting Metabolic Reprogramming by Influenza Infection for Therapeutic Intervention

Influenza is a worldwide health and financial burden posing a significant risk to the immune-compromised, obese, diabetic, elderly, and pediatric populations. We identified increases in glucose metabolism in the lungs of pediatric patients infected with respiratory pathogens. Using quantitative mass spectrometry, we found metabolic changes occurring after influenza infection in primary human respiratory cells and validated infection-associated increases in c-Myc, glycolysis, and glutaminolysis. We confirmed these findings with a metabolic drug screen that identified the PI3K/mTOR inhibitor BEZ235 as a regulator of infectious virus production. BEZ235 treatment ablated the transient induction of c-Myc, restored PI3K/mTOR pathway homeostasis measured by 4E-BP1 and p85 phosphorylation, and reversed infection-induced changes in metabolism. Importantly, BEZ235 reduced infectious progeny but had no effect on the early stages of viral replication. BEZ235 significantly increased survival in mice, while reducing viral titer. We show metabolic reprogramming of host cells by influenza virus exposes targets for therapeutic intervention.

A compendium of multi-omic sequence information from the Saanich Inlet water column

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters.

Informed-Proteomics: open-source software package for top-down proteomics

Top-down proteomics, the analysis of intact proteins in their endogenous form, preserves valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down liquid chromatography-tandem MS (LC-MS/MS) data sets is rapidly increasing on account of advances in instrumentation and sample-processing protocols. However, top-down mass spectra are substantially more complex than conventional bottom-up data. New algorithms and software tools for confident proteoform identification and quantification are needed. Here we present Informed-Proteomics, an open-source software suite for top-down proteomics analysis that consists of an LC-MS feature-finding algorithm, a database search algorithm, and an interactive results viewer. We compare our tool with several other popular tools using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.

Quantitative cardiac phosphoproteomics profiling during ischemia-reperfusion in an immature swine model

Ischemia-reperfusion (I/R) results in altered metabolic and molecular responses, and phosphorylation is one of the most noted regulatory mechanisms mediating signaling mechanisms during physiological stresses. To expand our knowledge of the potential phosphoproteomic changes in the myocardium during I/R, we used Isobaric Tags for Relative and Absolute Quantitation-based analyses in left ventricular samples obtained from porcine hearts under control or I/R conditions. The data are available via ProteomeXchange with identifier PXD006066. We identified 1,896 phosphopeptides within left ventricular control and I/R porcine samples. Significant differential phosphorylation between control and I/R groups was discovered in 111 phosphopeptides from 86 proteins. Analysis of the phosphopeptides using Motif-x identified five motifs: (..R..S..), (..SP..), (..S.S..), (..S…S..), and (..S.T..). Semiquantitative immunoblots confirmed site location and directional changes in phosphorylation for phospholamban and pyruvate dehydrogenase E1, two proteins known to be altered by I/R and identified by this study. Novel phosphorylation sites associated with I/R were also identified. Functional characterization of the phosphopeptides identified by our methodology could expand our understanding of the signaling mechanisms involved during I/R damage in the heart as well as identify new areas to target therapeutic strategies.NEW & NOTEWORTHY We used Isobaric Tags for Relative and Absolute Quantitation technology to investigate the phosphoproteomic changes that occur in cardiac tissue under ischemia-reperfusion conditions. The results of this study provide an extensive catalog of phosphoproteins, both predicted and novel, associated with ischemia-reperfusion, thereby identifying new pathways for investigation.

Host-influenza proteomics leads to metabolic drug repurposing that reduces viral burden while significantly improving survival after lethal infection (TECH2P.917)

A retrospective survey of pediatric patients infected with respiratory pathogens identified increases in glucose metabolism in the lungs of several individuals. After viral infection the host cell mounts an energetic and resource intensive antiviral response, while the virus exploits the host to generate progeny. Using absolute quantification with Host-Influenza Proteomics (HIP) we sought to characterize changes in host cell homeostasis that contribute to these competing processes. Like in the patients, we found gross metabolic changes occurring after influenza infection in primary human respiratory cells as well as dendritic cells. This new metabolic phenotype is distinct from immune activation and involves increases in glycolysis and glutaminolysis, decreased fatty acid β-oxidation concomitant to non-canonical TCA activity. Based on these findings we developed a metabolic drug repurposing screen in human bronchial epithelial cells and high-throughput viral tittering system. We screened over 160 metabolic substrates and small molecules to identify responsive prophylactic and therapeutic pathways (e.g. lipid and glucose metabolism respectively). One compound known to alter glucose sensitivity, NVP-BEZ235, reduced viral titers and significantly increased survival in vivo after lethal influenza challenge. Human PET scans followed by HIP analysis elucidated a unique metabolic signature in influenza-infection exposing targets for therapeutic intervention.

Application of printed circuit board technology to FT-ICR MS analyzer cell construction and prototyping

Although Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) remains the mass spectrometry platform that provides the highest levels of performance for mass accuracy and resolving power, there is room for improvement in analyzer cell design as the ideal quadrupolar trapping potential has yet to be generated for a broadband MS experiment. To this end, analyzer cell designs have improved since the field's inception, yet few research groups participate in this area because of the high cost of instrumentation efforts. As a step towards reducing this barrier to participation and allowing for more designs to be physically tested, we introduce a method of FT-ICR analyzer cell prototyping utilizing printed circuit boards at modest vacuum conditions. This method allows for inexpensive devices to be readily fabricated and tested over short intervals and should open the field to laboratories lacking or unable to access high performance machine shop facilities because of the required financial investment.

Automated genome mining of ribosomal peptide natural products

Ribosomally synthesized and posttranslationally modified peptides (RiPPs), especially from microbial sources, are a large group of bioactive natural products that are a promising source of new (bio)chemistry and bioactivity.1 In light of exponentially increasing microbial genome databases and improved mass spectrometry (MS)-based metabolomic platforms, there is a need for computational tools that connect natural product genotypes predicted from microbial genome sequences with their corresponding chemotypes from metabolomic data sets. Here, we introduce RiPPquest, a tandem mass spectrometry database search tool for identification of microbial RiPPs, and apply it to lanthipeptide discovery. RiPPquest uses genomics to limit search space to the vicinity of RiPP biosynthetic genes and proteomics to analyze extensive peptide modifications and compute p-values of peptide-spectrum matches (PSMs). We highlight RiPPquest by connecting multiple RiPPs from extracts of Streptomyces to their gene clusters and by the discovery of a new class III lanthipeptide, informatipeptin, from Streptomyces viridochromogenes DSM 40736 to reflect that it is a natural product that was discovered by mass spectrometry based genome mining using algorithmic tools rather than manual inspection of mass spectrometry data and genetic information. The presented tool is available at cyclo.ucsd.edu.

Molecular tools for investigating microbial community structure and function in oxygen-deficient marine waters

Water column oxygen (O2)-deficiency shapes food-web structure by progressively directing nutrients and energy away from higher trophic levels into microbial community metabolism resulting in fixed nitrogen loss and greenhouse gas production. Although respiratory O2 consumption during organic matter degradation is a natural outcome of a productive surface ocean, global-warming-induced stratification intensifies this process leading to oxygen minimum zone (OMZ) expansion. Here, we describe useful tools for detection and quantification of potential key microbial players and processes in OMZ community metabolism including quantitative polymerase chain reaction primers targeting Marine Group I Thaumarchaeota, SUP05, Arctic96BD-19, and SAR324 small-subunit ribosomal RNA genes and protein extraction methods from OMZ waters compatible with high-resolution mass spectrometry for profiling microbial community structure and functional dynamics.

In vitro transcription activities of Pol IV, Pol V, and RDR2 reveal coupling of Pol IV and RDR2 for dsRNA synthesis in plant RNA silencing

In Arabidopsis, RNA-dependent DNA methylation and transcriptional silencing involves three nuclear RNA polymerases that are biochemically undefined: the presumptive DNA-dependent RNA polymerases Pol IV and Pol V and the putative RNA-dependent RNA polymerase RDR2. Here we demonstrate their RNA polymerase activities in vitro. Unlike Pol II, Pols IV and V require an RNA primer, are insensitive to α-amanitin, and differ in their ability to displace the nontemplate DNA strand during transcription. Biogenesis of 24 nt small interfering RNAs (siRNAs), which guide cytosine methylation to corresponding sequences, requires both Pol IV and RDR2, which physically associate in vivo. Whereas Pol IV does not require RDR2 for activity, RDR2 is nonfunctional in the absence of associated Pol IV. These results suggest that the physical and mechanistic coupling of Pol IV and RDR2 results in the channeled synthesis of double-stranded precursors for 24 nt siRNA biogenesis.

Identification of soybean proteins from a single cell type: the root hair

Root hairs (RH) are a terminally differentiated single cell type, mainly involved in water and nutrient uptake from the soil. The soybean RH cell represents an excellent model for the study of single cell systems biology. In this study, we identified 5702 proteins, with at least two peptides, from soybean RH using an accurate mass and time tag approach, establishing a comprehensive proteome reference map of this single cell type. We also showed that trypsin is the most appropriate enzyme for soybean proteomic studies by performing an in silico digestion of the soybean proteome using different proteases. Although the majority of proteins identified in this study are involved in basal metabolism, the function of others are more related to RH formation/function and include proteins involved in nutrient uptake (transporters) or vesicular trafficking (cytoskeleton and ras-associated binding proteins). Interestingly, some of these proteins appear to be specifically detected in RH and constitute promising candidates for further studies to elucidate unique features of this single-cell model.

Genes for the major structural components of Thermotogales species' togas revealed by proteomic and evolutionary analyses of OmpA and OmpB homologs

The unifying structural characteristic of members of the bacterial order Thermotogales is their toga, an unusual cell envelope that includes a loose-fitting sheath around each cell. Only two toga-associated structural proteins have been purified and characterized in Thermotoga maritima: the anchor protein OmpA1 (or Ompα) and the porin OmpB (or Ompβ). The gene encoding OmpA1 (ompA1) was cloned and sequenced and later assigned to TM0477 in the genome sequence, but because no peptide sequence was available for OmpB, its gene (ompB) was not annotated. We identified six porin candidates in the genome sequence of T. maritima. Of these candidates, only one, encoded by TM0476, has all the characteristics reported for OmpB and characteristics expected of a porin including predominant β-sheet structure, a carboxy terminus porin anchoring motif, and a porin-specific amino acid composition. We highly enriched a toga fraction of cells for OmpB by sucrose gradient centrifugation and hydroxyapatite chromatography and analyzed it by LC/MS/MS. We found that the only porin candidate that it contained was the TM0476 product. This cell fraction also had β-sheet character as determined by circular dichroism, consistent with its enrichment for OmpB. We conclude that TM0476 encodes OmpB. A phylogenetic analysis of OmpB found orthologs encoded in syntenic locations in the genomes of all but two Thermotogales species. Those without orthologs have putative isofunctional genes in their place. Phylogenetic analyses of OmpA1 revealed that each species of the Thermotogales has one or two OmpA homologs. T. maritima has two OmpA homologs, encoded by ompA1 (TM0477) and ompA2 (TM1729), both of which were found in the toga protein-enriched cell extracts. These annotations of the genes encoding toga structural proteins will guide future examinations of the structure and function of this unusual lineage-defining cell sheath.

Dengue virus infection perturbs lipid homeostasis in infected mosquito cells

Dengue virus causes ∼50-100 million infections per year and thus is considered one of the most aggressive arthropod-borne human pathogen worldwide. During its replication, dengue virus induces dramatic alterations in the intracellular membranes of infected cells. This phenomenon is observed both in human and vector-derived cells. Using high-resolution mass spectrometry of mosquito cells, we show that this membrane remodeling is directly linked to a unique lipid repertoire induced by dengue virus infection. Specifically, 15% of the metabolites detected were significantly different between DENV infected and uninfected cells while 85% of the metabolites detected were significantly different in isolated replication complex membranes. Furthermore, we demonstrate that intracellular lipid redistribution induced by the inhibition of fatty acid synthase, the rate-limiting enzyme in lipid biosynthesis, is sufficient for cell survival but is inhibitory to dengue virus replication. Lipids that have the capacity to destabilize and change the curvature of membranes as well as lipids that change the permeability of membranes are enriched in dengue virus infected cells. Several sphingolipids and other bioactive signaling molecules that are involved in controlling membrane fusion, fission, and trafficking as well as molecules that influence cytoskeletal reorganization are also up regulated during dengue infection. These observations shed light on the emerging role of lipids in shaping the membrane and protein environments during viral infections and suggest membrane-organizing principles that may influence virus-induced intracellular membrane architecture.

Novel quantitative proteomic analysis of influenza infected dendritic cells reveals a previously unappreciated immune modulatory protein and infection induced differential expression of DC proteins, with unexpectedly high membrane protein dynamics. (110.24)

Airway dendritic cells (DC) initiate the immune response (IR) to respiratory pathogens (e.g.influenza). DC respond by releasing cytokines and presenting antigen to T cells, which activate on encountering the MCHI/peptide complex. This DC-T cell interaction dictates the IR to a given pathogen. Given that antigen presentation couples the innate and adaptive immune responses, a better understanding of these processes is vital to basic immune research and to therapeutic and vaccine development. To elucidate the underlying mechanisms of these processes we elected to identify DC proteins and quantify their changes in abundance using 18O labeling and LTQ-Orbit-trap-MS. Presuming the import of membrane protein dynamics on DCs, we developed a high pressure trypsinization technique to denature and digest insoluble proteins. We identified &gt;1500 DC proteins, 20% of which change in abundance (i.e. ≥ 2 fold) early in infection. Unexpectedly this method detected infection induced changes in membrane proteins exceeding soluble protein dynamics. Analysis of these preliminary data indicates major shifts in DC metabolic and antigen processing and presentation pathways occur as a result of infection. Network analysis resulted in the identification of two critical modulator proteins; one of these was NFκB, a well known modulator of the immune response and another protein previously unidentified as an IR modulator. Together these data revealed new and important aspects of the immune response.

Site-specific proteomics approach for study protein S-nitrosylation

Here we present a novel and robust method for the identification of protein S-nitrosylation sites in complex protein mixtures. The approach utilizes the cysteinyl affinity resin to selectively enrich S-nitrosylated peptides reduced by ascorbate followed by nanoscale liquid chromatography tandem mass spectrometry. Two alkylation agents with different added masses were employed to differentiate the S-nitrosylation sites from the non-S-nitrosylation sites. We applied this approach to MDA-MB-231 cells treated with Angeli's salt, a nitric oxide donor that has been shown to inhibit breast tumor growth and angiogenesis. A total of 162 S-nitrosylation sites were identified and an S-nitrosylation motif was revealed in our study. The 162 sites are significantly more than the number reported by previous methods, demonstrating the efficiency of our approach. Our approach will further facilitate the functional study of protein S-nitrosylation in cellular processes and may reveal new therapeutic targets.

HCMV pUS28 initiates pro-migratory signaling via activation of Pyk2 kinase

Background

Human Cytomegalovirus (HCMV) has been implicated in the acceleration of vascular disease and chronic allograft rejection. Recently, the virus has been associated with glioblastoma and other tumors. We have previously shown that the HCMV-encoded chemokine receptor pUS28 mediates smooth muscle cell (SMC) and macrophage motility and this activity has been implicated in the acceleration of vascular disease. pUS28 induced SMC migration involves the activation of the protein tyrosine kinases (PTKs) Src and Focal adhesion kinase as well as the small GTPase RhoA. The PTK Pyk2 has been shown to play a role in cellular migration and formation of cancer, especially glioblastoma. The role of Pyk2 in pUS28 signaling and migration are unknown.

Methods

In the current study, we examined the involvement of the PTK Pyk2 in pUS28-induced cellular motility. We utilized in vitro migration of SMC to determine the requirements for Pyk2 in pUS28 pro-migratory signaling. We performed biochemical analysis of Pyk2 signaling in response to pUS28 activation to determine the mechanisms involved in pUS28 migration. We performed mass spectrometric analysis of Pyk2 complexes to identify novel Pyk2 binding partners.

Results

Expression of a mutant form of Pyk2 lacking the autophosphorylation site (Tyr-402) blocks pUS28-mediated SMC migration in response to CCL5, while the kinase-inactive Pyk2 mutant failed to elicit the same negative effect on migration. pUS28 stimulation with CCL5 results in ligand-dependent and calcium-dependent phosphorylation of Pyk2 Tyr-402 and induced the formation of an active Pyk2 kinase complex containing several novel Pyk2 binding proteins. Expression of the autophosphorylation null mutant Pyk2 F402Y did not abrogate the formation of an active Pyk2 kinase complex, but instead prevented pUS28-mediated activation of RhoA. Additionally, pUS28 activated RhoA via Pyk2 in the U373 glioblastoma cells. Interestingly, the Pyk2 kinase complex in U373 contained several proteins known to participate in glioma tumorigenesis.

Conclusions

These findings represent the first demonstration that pUS28 signals through Pyk2 and that this PTK participates in pUS28-mediated cellular motility via activation of RhoA. Furthermore, these results provide a potential mechanistic link between HCMV-pUS28 and glioblastoma cell activation.

Platelet proteome changes associated with diabetes and during platelet storage for transfusion

Human platelets play a key role in hemostasis and thrombosis and have recently emerged as key regulators of inflammation. Platelets stored for transfusion produce pro-thrombotic and pro-inflammatory mediators implicated in adverse transfusion reactions. Correspondingly, these mediators are central players in pathological conditions including cardiovascular disease, the major cause of death in diabetics. In view of this, a mass spectrometry based proteomics study was performed on platelets collected from healthy and type-2 diabetics stored for transfusion. Strikingly, our innovative and sensitive proteomic approach identified 122 proteins that were either up- or down-regulated in type-2 diabetics relative to nondiabetic controls and 117 proteins whose abundances changed during a 5-day storage period. Notably, our studies are the first to characterize the proteome of platelets from diabetics before and after storage for transfusion. These identified differences allow us to formulate new hypotheses and experimentation to improve clinical outcomes by targeting "high risk platelets" that render platelet transfusion less effective or even unsafe.

Optimization of proteomic sample preparation procedures for comprehensive protein characterization of pathogenic systems

Mass spectrometry-based proteomics is a powerful analytical tool for investigating pathogens and their interactions within a host. The sensitivity of such analyses provides broad proteome characterization, but the sample-handling procedures must first be optimized to ensure compatibility with the technique and to maximize the dynamic range of detection. The decision-making process for determining optimal growth conditions, preparation methods, sample analysis methods, and data analysis techniques in our laboratory is discussed herein with consideration of the balance in sensitivity, specificity, and biomass losses during analysis of host-pathogen systems.

A data-mining scheme for identifying peptide structural motifs responsible for different MS/MS fragmentation intensity patterns

Although tandem mass spectrometry (MS/MS) has become an integral part of proteomics, intensity patterns in MS/MS spectra are rarely weighted heavily in most widely used algorithms because they are not yet fully understood. Here a knowledge mining approach is demonstrated to discover fragmentation intensity patterns and elucidate the chemical factors behind such patterns. Fragmentation intensity information from 28 330 ion trap peptide MS/MS spectra of different charge states and sequences went through unsupervised clustering using a penalized K-means algorithm. Without any prior chemistry assumptions, four clusters with distinctive fragmentation patterns were obtained. A decision tree was generated to investigate peptide sequence motif and charge state status that caused these fragmentation patterns. This data-mining scheme is generally applicable for any large data sets. It bypasses the common prior knowledge constraints and reports on the overall peptide fragmentation behavior. It improves the understanding of gas-phase peptide dissociation and provides a foundation for new or improved protein identification algorithms.

Statistical characterization of the charge state and residue dependence of low-energy CID peptide dissociation patterns

Data mining was performed on 28 330 unique peptide tandem mass spectra for which sequences were assigned with high confidence. By dividing the spectra into different sets based on structural features and charge states of the corresponding peptides, chemical interactions involved in promoting specific cleavage patterns in gas-phase peptides were characterized. Pairwise fragmentation maps describing cleavages at all Xxx-Zzz residue combinations for b and y ions reveal that the difference in basicity between Arg and Lys results in different dissociation patterns for singly charged Arg- and Lys-ending tryptic peptides. While one dominant protonation form (proton localized) exists for Arg-ending peptides, a heterogeneous population of different protonated forms or more facile interconversion of protonated forms (proton partially mobile) exists for Lys-ending peptides. Cleavage C-terminal to acidic residues dominates spectra from singly charged peptides that have a localized proton and cleavage N-terminal to Pro dominates those that have a mobile or partially mobile proton. When Pro is absent from peptides that have a mobile or partially mobile proton, cleavage at each peptide bond becomes much more prominent. Whether the above patterns can be found in b ions, y ions, or both depends on the location of the proton holder(s) in multiply protonated peptides. Enhanced cleavages C-terminal to branched aliphatic residues (Ile, Val, Leu) are observed in both b and y ions from peptides that have a mobile proton, as well as in y ions from peptides that have a partially mobile proton; enhanced cleavages N-terminal to these residues are observed in b ions from peptides that have a partially mobile proton. Statistical tools have been designed to visualize the fragmentation maps and measure the similarity between them. The pairwise cleavage patterns observed expand our knowledge of peptide gas-phase fragmentation behaviors and may be useful in algorithm development that employs improved models to predict fragment ion intensities.

Preferential recognition of a microbial metabolite by human V 2V 2 T cells

Human Vgamma2Vdelta2 T cells are stimulated by prenyl pyrophosphates, such as isopentenyl pyrophosphate (IPP), and play important roles in mediating immunity against microbial pathogens and have potent anti-tumor activity. (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMBPP) has been identified as a metabolite in the 2-C-methyl-D-erythritol-4 phosphate (MEP) pathway for isoprenoid biosynthesis that is used by many bacteria and protozoan parasites. We find that HMBPP is the major Vgamma2Vdelta2 T-cell antigen for many bacteria, including Mycobacterium tuberculosis, Yersinia enterocolitica and Escherichia coli. HMBPP was a 30 000-fold more potent antigen than IPP. Using mutant bacteria, we show that bacterial antigen levels for Vgamma2Vdelta2 T cells are controlled by MEP pathway enzymes and find no evidence for the production of 3-formyl-1-butyl pyrophosphate. Moreover, HMBPP reactivity required only germ line-encoded Vgamma2Vdelta2 TCR elements and is present at birth. Importantly, we show that bacterial HMBPP levels correlated with their ability to expand Vgamma2Vdelta2 T cells in vivo upon engraftment into severe combined immunodeficiency-beige mice. Thus, the production of HMBPP by a microbial-specific isoprenoid pathway plays a major role in determining whether bacteria will stimulate Vgamma2Vdelta2 T cells in vivo. This preferential stimulation by a common microbial isoprenoid metabolite allows Vgamma2Vdelta2 T cells to respond to a broad array of pathogens using this pathway.

Structural studies of Vgamma2Vdelta2 T cell phosphoantigens

Human gammadelta T cells containing the Vgamma2Vdelta2 (Vgamma9Vdelta2) T cell receptor are stimulated by a broad variety of small, phosphorus-containing antigenic molecules called phosphoantigens. The structures of several species present in both Mycobacteria (TUBags1-4) and in Escherichia coli have been reported to contain a formyl-alkyl diphosphate core. Here we report the synthesis of the lead member of the series, 3-formyl-1-butyl diphosphate. This compound has low activity for gammadelta T cell stimulation, unlike its highly active isomer (E)-4-hydroxy-3-methyl-but-2-enyl diphosphate, necessitating a revision of the structure of TUBag1. Likewise, the structure of the species identified as the pentyl analog (TUBag 2) is revised to 6-phosphogluconate. These results indicate that neither TUBag1 nor the m/e 275 species proposed for TUBag2 are 3-formyl-1-alkyl diphosphates, leading to the conclusion that none of the natural phosphoantigens (TUBags1-4) possess the structures reported previously.

Using size exclusion chromatography-RPLC and RPLC-CIEF as two-dimensional separation strategies for protein profiling

Bottom-up proteomics (analyzing peptides that result from protein digestion) has demonstrated capability for broad proteome coverage and good throughput. However, due to incomplete sequence coverage, this approach is not ideally suited to the study of modified proteins. The modification complement of a protein can best be elucidated by analyzing the intact protein. 2-DE, typically coupled with the analysis of peptides that result from in-gel digestion, is the most frequently applied protein separation technique in MS-based proteomics. As an alternative, numerous column-based liquid phase techniques, which are generally more amenable to automation, are being investigated. In this work, the combination of size-exclusion chromatography (SEC) fractionation with RPLC-Fourier-transform ion cyclotron resonance (FTICR)-MS is compared with the combination of RPLC fractionation with CIEF-FTICR-MS for the analysis of the Shewanella oneidensis proteome. SEC-RPLC-FTICR-MS allowed the detection of 297 proteins, as opposed to 166 using RPLC-CIEF-FTICR-MS, indicating that approaches based on LC-MS provide better coverage. However, there were significant differences in the sets of proteins detected and both approaches provide a basis for accurately quantifying changes in protein and modified protein abundances.

Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations

The gamma-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms, approximately 40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized "hypothetical" genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 2-5; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome.

Identification of proteins in human cytomegalovirus (HCMV) particles: the HCMV proteome

Human cytomegalovirus (HCMV), a member of the herpesvirus family, is a large complex enveloped virus composed of both viral and cellular gene products. While the sequence of the HCMV genome has been known for over a decade, the full set of viral and cellular proteins that compose the HCMV virion are unknown. To approach this problem we have utilized gel-free two-dimensional capillary liquid chromatography-tandem mass spectrometry (MS/MS) and Fourier transform ion cyclotron resonance MS to identify and determine the relative abundances of viral and cellular proteins in purified HCMV AD169 virions and dense bodies. Analysis of the proteins from purified HCMV virion preparations has indicated that the particle contains significantly more viral proteins than previously known. In this study, we identified 71 HCMV-encoded proteins that included 12 proteins encoded by known viral open reading frames (ORFs) previously not associated with virions and 12 proteins from novel viral ORFs. Analysis of the relative abundance of HCMV proteins indicated that the predominant virion protein was the pp65 tegument protein and that gM rather than gB was the most abundant glycoprotein. We have also identified over 70 host cellular proteins in HCMV virions, which include cellular structural proteins, enzymes, and chaperones. In addition, analysis of HCMV dense bodies indicated that these viral particles are composed of 29 viral proteins with a reduced quantity of cellular proteins in comparison to HCMV virions. This study provides the first comprehensive quantitative analysis of the viral and cellular proteins that compose infectious particles of a large complex virus.

Dissociation Behavior of Doubly-Charged Tryptic Peptides: Correlation of Gas-Phase Cleavage Abundance with Ramachandran Plots

Analysis of fragmentation patterns from 5654 unique doubly charged tryptic peptides is obtained. Great variability of average relative abundance of bond cleavage is found between different amino acid combinations. There exist similarities as well as differences between b and y ions. Strong enhancement or suppression of cleavage gives insight into possible chemical interactions at reactive conformations formed by preferred phi-psi angles.

Suppression of the lower charge state ions in the external accumulation RF multipole with a reduced trapping DC potential

Radio frequency (RF) multipoles are increasingly used in mass spectrometry as two-dimensional ion traps for ion accumulation and preselection. It was reported recently that ions having lower charge states, in particular singly charged ions, can be efficiently removed from such an ion trap when reduced DC trapping voltages are applied. This procedure can be useful for removing singly charged species contributing chemical noise to mass spectra of complex biomolecular samples, e.g., solvent contaminants in LC-MS or relatively low MW ampholytes in CIEF-MS experiments. We consider a physical mechanism and derive relationships that provide a quantitative description for the low charge state ejection phenomenon. Experimental conditions for the efficient discrimination against lower charge states are evaluated. Initial experimental observations reported are in agreement with the theoretical treatment.

The use of accurate mass tags for high-throughput microbial proteomics

We describe and review progress towards a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements for microbial systems based upon the use of polypeptide accurate mass tags (AMTs) produced by global protein enzymatic digestions. The two-stage strategy exploits high accuracy mass measurements using Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate polypeptide AMTs for a specific organism, from potential mass tags tentatively identified using tandem mass spectrometry (MS/MS), providing the basis for subsequent measurements without the need for routine MS/MS. A high-resolution capillary liquid chromatography separation combined with high sensitivity, and high-resolution accurate FTICR measurements is shown to be capable of characterizing polypeptide mixtures of more than 10(5) components, sufficient for broad protein identification using AMTs. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, and the capability for stable-isotope labeling methods for precise relative protein abundance measurements. The strategy has been initially evaluated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Additional developments, including the use of multiplexed-MS/MS capabilities and methods for dynamic range expansion of proteome measurements that promise to further extend the quality of proteomics measurements, are also described.

Enrichment of integral membrane proteins for proteomic analysis using liquid chromatography-tandem mass spectrometry

An increasing number of proteomic strategies rely on liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect and identify constituent peptides of enzymatically digested proteins obtained from various organisms and cell types. However, sample preparation methods for isolating membrane proteins typically involve the use of detergents and chaotropes that often interfere with chromatographic separation and/or electrospray ionization. To address this problem, a sample preparation method combining carbonate extraction, surfactant-free organic solvent-assisted solubilization, and proteolysis was developed and demonstrated to target the membrane subproteome of Deinococcus radiodurans. Out of 503 proteins identified, 135 were recognized as hydrophobic on the basis of their calculated hydropathy values (GRAVY index), corresponding to coverage of 15% of the predicted hydrophobic proteome. Using the PSORT algorithm, 53 of the proteins identified were classified as integral outer membrane proteins and 215 were classified as integral cytoplasmic membrane proteins. All identified integral cytoplasmic membrane proteins had from 1 to 16 mapped transmembrane domains (TMDs), and 65% of those containing four or more mapped TMDs were identified by at least one hydrophobic membrane spanning peptide. The extensive coverage of the membrane subproteome (24%) by identification of highly hydrophobic proteins containing multiple TMDs validates the efficacy of the described sample preparation technique to isolate and solubilize hydrophobic integral membrane proteins from complex protein mixtures.

An accurate mass tag strategy for quantitative and high-throughput proteome measurements

We describe and demonstrate a global strategy that extends the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements based upon the use of peptide "accurate mass tags" (AMTs) produced by global protein enzymatic digestion. The two-stage strategy exploits Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry to validate peptide AMTs for a specific organism, tissue or cell type from "potential mass tags" identified using conventional tandem mass spectrometry (MS/MS) methods, providing greater confidence in identifications as well as the basis for subsequent measurements without the need for MS/MS, and thus with greater sensitivity and increased throughput. A single high resolution capillary liquid chromatography separation combined with high sensitivity, high resolution and accurate FT-ICR measurements has been shown capable of characterizing peptide mixtures of significantly more than 10(5) components with mass accuracies of < 1 ppm, sufficient for broad protein identification using AMTs. Other attractions of the approach include the broad and relatively unbiased proteome coverage, the capability for exploiting stable isotope labeling methods to realize high precision for relative protein abundance measurements, and the projected potential for study of mammalian proteomes when combined with additional sample fractionation. Using this strategy, in our first application we have been able to identify AMTs for >60% of the potentially expressed proteins in the organism Deinococcus radiodurans.

Obtaining more accurate Fourier transform ion cyclotron resonance mass measurements without internal standards using multiply charged ions

Space-charge effects produce frequency shifts in Fourier transform ion cyclotron resonance (FTICR) mass spectrometry and correction for these shifts is necessary for obtaining accurate mass measurements. We report a novel method for obtaining accurate mass calibration to correct for space-charge induced mass shifts without the requirement for internal calibrants. The new approach is particularly well suited for electrospray ionization-FTICR mass spectra that contain multiple charge states of the same molecular species. This method, deconvolution of Coulombic affected linearity (DeCAL), is described and presented with several examples demonstrating the increased mass measurement accuracy obtained. DeCAL provides the basis for more routinely obtaining higher mass accuracy measurements in conjunction with chromatographic separations for complex mixture analysis, and obviates the need for internal calibration in many applications.

Accurate mass multiplexed tandem mass spectrometry for high-throughput polypeptide identification from mixtures

We report a new tandem mass spectrometric approach for the improved identification of polypeptides from mixtures (e.g., using genomic databases). The approach involves the dissociation of several species simultaneously in a single experiment and provides both increased speed and sensitivity. The data analysis makes use of the known fragmentation pathways for polypeptides and highly accurate mass measurements for both the set of parent polypeptides and their fragments. The accurate mass information makes it possible to attribute most fragments to a specific parent species. We provide an initial demonstration of this multiplexed tandem MS approach using an FTICR mass spectrometer with a mixture of seven polypeptides dissociated using infrared irradiation from a CO2 laser. The peptides were added to, and then successfully identified from, the largest genomic database yet available (C. elegans), which is equivalent in complexity to that for a specific differentiated mammalian cell type. Additionally, since only a few enzymatic fragments are necessary to unambiguously identify a protein from an appropriate database, it is anticipated that the multiplexed MS/MS method will allow the more rapid identification of complex protein mixtures with on-line separation of their enzymatically produced polypeptides.

Protein identification with a single accurate mass of a cysteine-containing peptide and constrained database searching

A method for rapid and unambiguous identification of proteins by sequence database searching using the accurate mass of a single peptide and specific sequence constraints is described. Peptide masses were measured using electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry to an accuracy of 1 ppm. The presence of a cysteine residue within a peptide sequence was used as a database searching constraint to reduce the number of potential database hits. Cysteine-containing peptides were detected within a mixture of peptides by incorporating chlorine into a general alkylating reagent specific for cysteine residues. Secondary search constraints included the specificity of the protease used for protein digestion and the molecular mass of the protein estimated by gel electrophoresis. The natural isotopic distribution of chlorine encoded the cysteine-containing peptide with a distinctive isotopic pattern that allowed automatic screening of mass spectra. The method is demonstrated for a peptide standard and unknown proteins from a yeast lysate using all 6118 possible yeast open reading frames as a database. As judged by calculation of codon bias, low-abundance proteins were identified from the yeast lysate using this new method but not by traditional methods such as tandem mass spectrometry via data-dependent acquisition or mass mapping.

Egg-laying hormone peptides in the aplysiidae family

The neuropeptidergic bag cells of the marine mollusc Aplysia californica are involved in the egg-laying behavior of the animal. These neurosecretory cells synthesize an egg-laying hormone (ELH) precursor protein, yielding multiple bioactive peptides, including ELH, several bag cell peptides (BCP) and acidic peptide (AP). While immunohistochemical studies have involved a number of species, homologous peptides have been biochemically characterized in relatively few Aplysiidae species. In this study, a combination of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS) and electrospray ionization Fourier transform ion cyclotron resonance MS is used to characterize and compare the ELH peptides from related opisthobranch molluscs including Aplysia vaccaria and Phyllaplysia taylori. The peptide profiles of bag cells from these two Aplysiidae species are similar to that of A. californica bag cells. In an effort to characterize further several of these peptides, peptides from multiple groups of cells of each species were extracted, and microbore liquid chromatography was used to separate and isolate them. Several MS-based sequencing approaches are applied to obtain the primary structures of bag cell peptides and ELH. Our studies reveal that (α)-BCPs are 100 % conserved across all species studied. In addition, the complete sequences of (ε)-BCP and ELH of A. vaccaria were determined. They show a high degree of homology to their counterparts in A. californica, with only a few amino acid residue substitutions.