Electron Capture in Spin-Trap Capped Peptides. An Experimental Example of Ergodic Dissociation in Peptide Cation-Radicals

Electron capture dissociation was studied with tetradecapeptides and pentadecapeptides that were capped at N-termini with a 2-(4′-carboxypyrid-2′-yl)-4-carboxamide group (pepy), e.g., pepy-AEQLLQEEQLLQEL-NH2, pepy-AQEFGEQGQKALKQL-NH2, and pepy-AQEGSEQAQKFFKQL-NH2. Doubly and triply protonated peptide cations underwent efficient electron capture in the ion-cyclotron resonance cell to yield charge-reduced species. However, the electron capture was not accompanied by backbone dissociations. When the peptide ions were preheated by absorption of infrared photons close to the dissociation threshold, subsequent electron capture triggered ion dissociations near the remote C-terminus forming mainly (b11-14 + 1)+· fragment ions that were analogous to those produced by infrared multiphoton dissociation alone. Ab initio calculations indicated that the N-1 and N-1′ positions in the pepy moiety had topical gas-phase basicities (GB = 923 kJ mol−1) that were greater than those of backbone amide groups. Hence, pepy was a likely protonation site in the doubly and triply charged ions. Electron capture in the protonated pepy moiety produced the ground electronic state of the charge-reduced cation-radical with a topical recombination energy, RE = 5.43-5.46 eV, which was greater than that of protonated peptide residues. The hydrogen atom in the charge-reduced pepy moiety was bound by >160 kJ mol−1, which exceeded the hydrogen atom affinity of the backbone amide groups (21–41 kJ mol−1). Thus, the pepy moiety functioned as a stable electron and hydrogen atom trap that did not trigger radical-type dissociations in the peptide backbone that are typical of ECD. Instead, the internal energy gained by electron capture was redistributed over the peptide moiety, and when combined with additional IR excitation, induced proton-driven ion dissociations which occurred at sites that were remote from the site of electron capture. This example of a spin-remote fragmentation provided the first clear-cut experimental example of an ergodic dissociation upon ECD

Identifying and Tracking Proteins Through the Marine Water Column: Insights Into the Inputs and Preservation Mechanisms of Protein in Sediments

Proteins generated during primary production represent an important fraction of marine organic nitrogen and carbon, and have the potential to provide organism-specific information in the environment. The Bering Sea is a highly productive system dominated by seasonal blooms and was used as a model system for algal proteins to be tracked through the water column and incorporated into detrital sedimentary material. Samples of suspended and sinking particles were collected at multiple depths along with surface sediments on the continental shelf and deeper basin of the Bering Sea. Modified standard proteomic preparations were used in conjunction with high pressure liquid chromatography-tandem mass spectrometry to identify the suite of proteins present and monitor changes in their distribution. In surface waters 207 proteins were identified, decreasing through the water column to 52 proteins identified in post-bloom shelf surface sediments and 24 proteins in deeper (3490 m) basin sediments. The vast majority of identified proteins in all samples were diatom in origin, reflecting their dominant contribution of biomass during the spring bloom. Identified proteins were predominantly from metabolic, binding/structural, and transport-related protein groups. Significant linear correlations were observed between the number of proteins identified and the concentration of total hydrolysable amino acids normalized to carbon and nitrogen. Organelle-bound, transmembrane, photosynthetic, and other proteins involved in light harvesting were preferentially retained during recycling. These findings suggest that organelle and membrane protection represent important mechanisms that enhance the preservation of protein during transport and incorporation into sediments

Diatom Proteomics Reveals Unique Acclimation Strategies to Mitigate Fe Limitation

Phytoplankton growth rates are limited by the supply of iron (Fe) in approximately one third of the open ocean, with major implications for carbon dioxide sequestration and carbon (C) biogeochemistry. To date, understanding how alteration of Fe supply changes phytoplankton physiology has focused on traditional metrics such as growth rate, elemental composition, and biophysical measurements such as photosynthetic competence (Fv/Fm). Researchers have subsequently employed transcriptomics to probe relationships between changes in Fe supply and phytoplankton physiology. Recently, studies have investigated longer-term (i.e. following acclimation) responses of phytoplankton to various Fe conditions. In the present study, the coastal diatom, Thalassiosira pseudonana, was acclimated (10 generations) to either low or high Fe conditions, i.e. Fe-limiting and Fe-replete. Quantitative proteomics and a newly developed proteomic profiling technique that identifies low abundance proteins were employed to examine the full complement of expressed proteins and consequently the metabolic pathways utilized by the diatom under the two Fe conditions. A total of 1850 proteins were confidently identified, nearly tripling previous identifications made from differential expression in diatoms. Given sufficient time to acclimate to Fe limitation, T. pseudonana up-regulates proteins involved in pathways associated with intracellular protein recycling, thereby decreasing dependence on extracellular nitrogen (N), C and Fe. The relative increase in the abundance of photorespiration and pentose phosphate pathway proteins reveal novel metabolic shifts, which create substrates that could support other well-established physiological responses, such as heavily silicified frustules observed for Fe-limited diatoms. Here, we discovered that proteins and hence pathways observed to be down-regulated in short-term Fe starvation studies are constitutively expressed when T. pseudonana is acclimated (i.e., nitrate and nitrite transporters, Photosystem II and Photosystem I complexes). Acclimation of the diatom to the desired Fe conditions and the comprehensive proteomic approach provides a more robust interpretation of this dynamic proteome than previous studies.This work was supported by National Science Foundation grants OCE1233014 (BLN) and the Office of Polar Programs Postdoctoral Fellowship grant 0444148 (BLN). DRG was supported by National Institutes of Health 5P30ES007033-10. AH and MTM were supported by Natural Sciences and Engineering Research Council of Canada. RFS and PWB were supported by the New Zealand Royal Society Marsden Fund and the Ministry of Science. This work is supported in part by the University of Washington's Proteomics Computer Resource Centre (UWPR95794). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Trends in Sample Preparation for Proteome Analysis

Sample preparation is a key step in proteomics, however there is no consensus in the community about the standard method for preparation of proteins from clinical samples like tissues or biofluids. In this chapter, we will discuss some important steps in sample preparation used for bottom-up proteome profiling with mass spectrometry (MS). Specifically, tissues, which are an important source of biological information, are of interest because of their availability. Tissues are most often stored as fresh frozen (FF) or formalin-fixed paraffin-embedded (FFPE). While FF tissues are more readily available, paraffin embedding has historically been routinely used for tissue preservation. However, formaldehyde induced crosslinks during FFPE tissue preservation present a challenge to the protocols used for protein retrieval. Moreover, in our view, an important aspect to consider is also the amount of material available at the start of a protocol since this is directly related to the choice of protocol in order to minimize sample loss and maximize detection of peptides by MS. This “MS sensitivity” is of special importance when working with patient samples that are unique and often available in limited amounts making optimization of methods to analyze the proteins therein important given that their molecular information can be used in a patients’ diagnosis and treatment

Protein Recycling in Bering Sea Algal Incubations

Protein present in phytoplankton represents a large fraction of the organic nitrogen and carbon transported from its synthesis in surface waters to marine sediments. Yet relatively little is known about the longevity of identifiable protein in situ, or the potential modifications to proteins that occur during bloom termination, protein recycling and degradation. To address this knowledge gap, diatom-dominated phytoplankton was collected during the Bering Sea spring blooms of 2009 and 2010, and incubated under darkness in separate shipboard degradation experiments spanning 11 and 53 d, respectively. In each experiment, the protein distribution was monited over time using shotgun proteomics, along with total hydrolyzable amino acids (THAAs), total protein, particulate organic carbon (POC) and nitrogen (PN), and bacterial cell abundance. Identifiable proteins, total protein and THAAs were rapidly lost during the first 5 d of enclosure in darkness in both incubations. Thereafter the loss rate was slower, and it declined further after 22 d. The initial loss of identifiable biosynthetic, glycolysis, metabolism and translation proteins after 12 h may represent shutdown of cellular activity among algal cells. Additional peptides with glycan modifications were identified in early incubation time points, suggesting that such protein modifications could be used as a marker for internal recycling processes and possibly cell death. Protein recycling was not uniform, with a subset of algal proteins including fucoxanthin chlorophyll binding proteins and RuBisCO identified after 53 d of degradation. Non-metric multidimensional scaling was used to compare the incubations with previous environmental results. The results confirmed recent observations that some fraction of algal proteins can survive water column recycling and undergo transport to marine sediments, thus contributing organic nitrogen to the benthos

Comparison of a Label-Free Quantitative Proteomic Method Based on Peptide Ion Current Area to the Isotope Coded Affinity Tag Method

Recently, several research groups have published methods for the determination of proteomic expression profiling by mass spectrometry without the use of exogenously added stable isotopes or stable isotope dilution theory. These so-called label-free, methods have the advantage of allowing data on each sample to be acquired independently from all other samples to which they can later be compared in silico for the purpose of measuring changes in protein expression between various biological states. We developed label free software based on direct measurement of peptide ion current area (PICA) and compared it to two other methods, a simpler label free method known as spectral counting and the isotope coded affinity tag (ICAT) method. Data analysis by these methods of a standard mixture containing proteins of known, but varying, concentrations showed that they performed similarly with a mean squared error of 0.09. Additionally, complex bacterial protein mixtures spiked with known concentrations of standard proteins were analyzed using the PICA label-free method. These results indicated that the PICA method detected all levels of standard spiked proteins at the 90% confidence level in this complex biological sample. This finding confirms that label-free methods, based on direct measurement of the area under a single ion current trace, performed as well as the standard ICAT method. Given the fact that the label-free methods provide ease in experimental design well beyond pair-wise comparison, label-free methods such as our PICA method are well suited for proteomic expression profiling of large numbers of samples as is needed in clinical analysis

Resistant potato starch supplementation reduces serum histamine levels in healthy adults with links to attenuated intestinal permeability

Histamine from our diet or gut microbes can trigger gastrointestinal disturbances, and resistant potato starch (RPS) has previously been shown to alleviate these symptoms while increasing levels of health-associated bacteria such as Akkermansia through unknown mechanisms. Post hoc exploratory metabolomic analysis of serum amino acid, amine, and carnitine metabolites in participants consuming 3.5 g/day RPS or placebo (n = 48) was performed using liquid chromatography-mass spectrometry to determine whether RPS positively influences histamine metabolism and related parameters. Histamine levels were significantly reduced by RPS treatment, but histamine-degrading enzyme products were unaffected by RPS. RPS also reduced histamine-secreting Haemophilus and Lactobacillus. Further, metabolites associated with intestinal permeability, including 5-hydroxylysine, acetylspermidine, and short- and medium-chain carnitines ratios, were significantly reduced by RPS treatment, suggesting decreased serum histamine might be related to enhanced gut barrier function. These metabolomic findings expand the value of supplementing the diet with RPS

Evaluation of Electrophoretic Protein Extraction and Database-Driven Protein Identification from Marine Sediments

Intact proteins comprise a major component of organic carbon and nitrogen produced globally and are likely an important fraction of organic matter in sediments and soils. Extracting the protein component from sediments and soils for mass spectral characterization and identification represents a substantial challenge given the range of products and functionalities present in the complex matrix. Multiple forms of gel electrophoresis were evaluated as a means of enhancing recovery of sedimentary protein before proteomic characterization and compared with a direct enzymatic digestion of proteins in sediments. Resulting tryptic peptides were analyzed using shotgun proteomics and tandem mass spectra were evaluated with SEQUEST. Multiple databases were then evaluated to examine the ability to confidently identify proteins from environmental samples. Following evaluation of electrophoretic extraction of proteins from sediments, the recovery of an experimentally added standard protein (BSA) from older (\u3e1 ky) sediments was optimized. Protein extraction from sediments via direct electrophoresis of a slurry mixture and the specified extraction buffer resulted in the greatest number of confident protein identifications and highest sequence coverage of the BSA standard. Searching tandem mass spectral data against larger databases with a higher diversity of proteomes did not yield a greater number of, or more confidence in, protein identifications. Regardless of the protein database used, identified peptides correlated to proteins with the same function across taxa. This suggests that while determining taxonomic-level information remains a challenge in samples with unknown mixed species, it is possible to confidently assign the function of the identified protein

WaveletQuant, an improved quantification software based on wavelet signal threshold de-noising for labeled quantitative proteomic analysis

<p>Abstract</p> <p>Background</p> <p>Quantitative proteomics technologies have been developed to comprehensively identify and quantify proteins in two or more complex samples. Quantitative proteomics based on differential stable isotope labeling is one of the proteomics quantification technologies. Mass spectrometric data generated for peptide quantification are often noisy, and peak detection and definition require various smoothing filters to remove noise in order to achieve accurate peptide quantification. Many traditional smoothing filters, such as the moving average filter, Savitzky-Golay filter and Gaussian filter, have been used to reduce noise in MS peaks. However, limitations of these filtering approaches often result in inaccurate peptide quantification. Here we present the WaveletQuant program, based on wavelet theory, for better or alternative MS-based proteomic quantification.</p> <p>Results</p> <p>We developed a novel discrete wavelet transform (DWT) and a 'Spatial Adaptive Algorithm' to remove noise and to identify true peaks. We programmed and compiled WaveletQuant using Visual C++ 2005 Express Edition. We then incorporated the WaveletQuant program in the <b>Trans-Proteomic Pipeline (TPP)</b>, a commonly used open source proteomics analysis pipeline.</p> <p>Conclusions</p> <p>We showed that WaveletQuant was able to quantify more proteins and to quantify them more accurately than the ASAPRatio, a program that performs quantification in the TPP pipeline, first using known mixed ratios of yeast extracts and then using a data set from ovarian cancer cell lysates. The program and its documentation can be downloaded from our website at <url>http://systemsbiozju.org/data/WaveletQuant</url>.</p