Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, ¹³C₆¹⁵N₂ and ²H₈, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo⁺ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.The ability to make de novo sequence identifications directly from tandem mass spectra has long been a holy grail of the proteomic community. Such a capability would wean the field from its reliance upon sequenced genome databases. Even for organisms with fully annotated genomes, events such as single nucleotide polymorphisms, alternative splicing, gene fusion, and a host of other genomic transformations can result in altered proteomes. These alterations can vary from cell to cell and individual to individual. Thus, one could argue that the most valuable proteomic information, the individual and cellular proteome variation from the genome, remains elusive (1). This problem has received considerable attention; that said, it is not easy to de novo correlate spectrum to sequence in a large-scale, automated fashion (2–6). Improvements in mass accuracy have helped, but routine, reliable de novo sequencing without database assistance is not standard (7–10).A primary means to facilitate de novo spectral interpretation is the simple annotation of m/z peaks in tandem mass spectra as either N- or C-terminal. We and others have investigated this seemingly simple first step. Real-world spectra, however, are complex. Difficulties often arise in determining the charge state of the fragment or in differentiating between fragment ions and peaks arising from neutral loss, internal fragmentation, or spectral noise, both electronic and chemical. Several strategies have focused on product ion annotation. These approaches have included manipulation of the N-terminus basicity combined with electron transfer dissociation (ETD)¹ (11–13). This approach can yield mostly N-terminal fragments for peptides having only two charges. However, it requires both ETD and the protease LysN. Other methods have used differential labeling of N- and C-terminal peptides to shift either one or the other product ion series, by either metabolic or chemical means (14–18). Metabolic incorporation of amino acids is an efficient method of introducing distinctive labels that eliminates in vitro labeling, but this method requires that the sample be amenable to cell culture (19, 20). Additionally, it may be difficult to achieve complete labeling in complex systems. Several other approaches used to introduce heavy isotopes onto one terminus have been investigated, including trypsin digestion in ¹⁸O water (21–23), differential isotopic esterification (24, 25), derivatization of the C-terminal carboxylate by p-bromophenethylamine (8, 26), N-terminal derivatization with sulfonic acid groups (27, 28), and formaldehyde labeling via reductive amination (29–31). These chemical modifications are introduced after cell lysis, often immediately prior to analysis. Although chemical labeling strategies can be used with a variety of samples, difficulties can arise from differences in labeling efficiency between samples, and often a clean-up step is required following labeling, which may lead to sample loss. No matter the labeling method, in this regime, the two precursors must be separately isolated, fragmented, and analyzed either together or separately. The recognition and selection of the broadly spaced doublet in real time also are necessary. These requirements have limited the utility of these approaches. Our own laboratory discovered that the c- and ^●z-type product ions generated from either electron capture dissociation or ETD have distinct chemical formulae and therefore can always be distinguished based on accurate mass alone (32). The problem with this approach is that extremely high mass accuracy (<500 ppb) is required in order to distinguish these product ion types above ∼600 Da in mass. Thus, the majority of the product ions within a spectrum cannot be readily mapped to either terminus with high confidence.Despite these difficulties, we assert that robust de novo sequencing methodology would benefit greatly from a simple method that could be used to distinguish N- and C-terminal product ions with high accuracy and precision. Ideally, the approach would work regardless of the choice of proteolytic enzyme or dissociation method. Recently, we described a new technology for protein quantification called neutron encoding (NeuCode) (33). NeuCode embeds millidalton mass differences into peptides and proteins by exploiting the mass defect induced by differences in the nuclear binding energies of the various stable isotopes of common elements such as C, N, H, and O. For example, consider the amino acid lysine, which has eight additional neutrons (+8 Da). One way to synthesize this amino acid is to add six ¹³C atoms and two ¹⁵N atoms (+8.0142 Da). Another isotopologue could be constructed by adding eight ²H atoms (+8.0502). These two isotopologues differ by only 36 mDa; peptide precursors containing both of these amino acids would appear as a single, unresolved precursor m/z peak at a mass resolving power of less than ∼100,000. However, under high resolving powers (i.e. greater than ∼100,000 at m/z 400), this doublet is resolved. We first developed this NeuCode concept in the context of metabolic labeling, akin to stable isotope labeling with amino acids in cell culture (SILAC), except that instead of the precursor partners being separated by 4 to 8 Da, they are separated by only 6 to 40 mDa. For quantitative purposes, NeuCode promises to deliver ultraplexed SILAC (>12) without increasing spectral complexity.We reasoned that the isotopologues of Lys that permit NeuCode SILAC would generate a distinct fingerprint on C-terminal product ions. Specifically, peptides that have been labeled with NeuCode SILAC and digested with LysC uniformly contain Lys at the C terminus. Upon MS/MS, all C-terminal product ions should present as doublets (with duplex NeuCode), whereas N-terminal products will be detected as a single m/z peak. The very close m/z spacing of the NeuCode SILAC partners will ensure that each partner is always co-isolated and that the signatures are visible only upon high-resolving-power mass analysis. Here we investigate the combination of NeuCode SILAC and high-resolving-power MS/MS analysis to allow the straightforward identification of C-terminal product ions.

Sample Preparation

Saccharomyces cerevisiae strain BY4741 Lys1Δ was grown in defined synthetic complete (SC, Sunrise Science, San Diego, CA) drop-out media with either heavy 6C¹³/2N¹⁵ lysine (+8.0142 Da, Cambridge Isotopes, Tewksbury, MA), or heavy 8D (+8.0502 Da, Cambridge Isotopes). Cells were propagated to a minimum of 10 doublings. At mid-log phase, cells were harvested via centrifugation at 3,000 × g for 3 min and then washed three times with chilled double distilled H₂O. Cell pellets were resuspended in 5 ml lysis buffer (50 mm Tris pH 8, 8 m urea, 75 mm sodium chloride, 100 mm sodium butyrate, 1 mm sodium orthovanadate, protease and phosphatase inhibitor tablet), and protein was extracted via glass bead milling (Retsch, Haan, Germany). Protein concentration was measured via BCA (Pierce). Cysteines in the yeast lysate were reduced with 5 m dithiothreitol at ambient temperature for 30 min, alkylated with 15 mm iodoacetamide in the dark at ambient temperature for 30 min, and then quenched with 5 mm dithiothreitol. 50 mm tris (pH 8.0) was used to dilute the urea concentration to 4 m. Proteins were digested with LysC (1:50 enzyme:protein ratio) at ambient temperature for 16 h. The digestion was quenched with TFA and desalted with a tC18 Sep-Pak (Waters, Etten-Leur, The Netherlands). Samples were prepared by mixing 6C¹³/2N¹⁵ (+8.0412 Da) and 8D (+8.0502 Da) labeled peptides in 1:1 ratios by mass. For strong cation exchange fractionation, peptides were dissolved in 400 μl of strong cation exchange buffer A (5 mm KH₂PO₄ and 30% acetonitrile; pH 2.65) and injected onto a polysulfoethylaspartamide column (9.4 mm × 200 mm; PolyLC) attached to a Surveyor LC quarternary pump (Thermo Electron, West Chester, PA) operating at 3 ml/min. Peptides were detected by photodiode array detector (Thermo Electron, West Chester, PA). Fractions were collected every 2 min starting at 10 min into the following gradient: 0–2 min at 100% buffer A, 2–5 min at 0%–15% buffer B (5 mm KH₂PO₄, 30% acetonitrile, and 350 mm KCl (pH 2.65)), and 5–35 min at 15%–100% buffer B. Buffer B was held at 100% for 10 min. Finally, the column was washed with buffer C (50 mm KH₂PO₄ and 500 mm KCl (pH 7.5)) and water before recalibration. Fractions were collected by hand every 2 to 3 min starting at 10 min into the gradient and were lyophilized and desalted with a tC18 Sep-Pak (Waters).

LC-MS/MS

Samples were loaded onto a 15-cm-long, 75-μm capillary column packed with 5 μm Magic C18 (Michrom, Auburn, CA) particles in mobile phase A (0.2% formic acid in water). Peptides were eluted with mobile phase B (0.2% formic acid in acetonitrile) over a 120-min gradient at a flow rate of 300 nl/min. Eluted peptides were analyzed by an Orbitrap Elite mass spectrometer. For the nonfractionated samples, mass spectrometer instrument methods comprised one MS¹ scan followed by data-dependent MS² scans of the five most intense precursors. A survey MS¹ scan was performed by the Orbitrap at 30,000 resolving power to identify precursors to sample for tandem mass spectrometry, and this was followed by an additional MS¹ scan at 480,000 resolving power (at m/z 400; actual mass resolving power of 470,700). Data-dependent tandem mass spectrometry was performed via beam-type collisional activated dissociation (HCD) in the Orbitrap at a resolving power of 15,000, 60,000, 120,000, or 240,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. For experiments comparing the duty cycle and resolving power required in order to distinguish y-ion doublets, MS¹ and MS² target ion accumulation values were set to 5 × 10⁵ and 5 × 10⁴, respectively. For all other experiments, MS¹ target accumulation values were set to 1 × 10⁶ and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 30 s for −0.55 m/z and +2.55 m/z of selected precursors. For ETD analysis, data-dependent top-five mass spectrometry was performed at a resolving power of 240,000 (m/z 400; actual MS² mass resolving power of 271,000) (34). ETD accumulation values were set to 1 × 10⁶ for MS¹ target accumulation and 4 × 10⁵ for MS² target accumulation. The fluoranthene reaction time was set to 100 ms. For the high-pH strong cation exchange fractions, data-dependent tandem mass spectrometry was performed via HCD at a resolving power of either 60,000 or 120,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. MS¹ targets were set to 1 × 10⁶, and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 45 s for −0.55 m/z and +2.55 m/z of selected precursors. Analysis by use of a wide isolation window was performed on an Orbitrap Fusion. MS¹ analysis was performed at 450,000 resolving power (m/z 200), and MS² analysis was performed at 120,000 resolving power (m/z 400). Data-dependent top-N mass spectrometry was performed, with precursors selected from sequential 25-Da windows. HCD was performed twice on the same precursor, first by use of a quadrupole isolation width of 0.7 m/z for peptide identification, and then using 25 m/z quadrupole isolation. Fragment ions were analyzed in the Orbitrap at a mass resolving power of 120,000 (m/z 400). MS¹ and MS² target accumulation values were set to 2 × 10⁵ and 5 × 10⁴, respectively.

Data Analysis

Thermo.raw files were converted to searchable DTA text files using the Coon OMSSA Proteomic Analysis Software Suite (COMPASS) (35). DTA files containing exclusively y-ions were generated using an in-house algorithm. DTA files were searched against the UniProt yeast database (version 132) with Lys-C specificity using the Open Mass Spectrometry Search Algorithm (OMSSA), version 2.1.9 (36). Methionine oxidation was searched as a variable modification. Cysteine carbamidomethylation and the mass shift imparted by the lysine isotopolgues were searched as fixed modifications. For MS² scans performed at a resolving power of 60,000, 120,000, or 240,000, a shift of +8.0142, representing the mass shift of the ¹³C₆¹⁵N₂ isotopologue, was searched. For MS² scans performed at 15,000 resolving power, the average shift of the ¹³C₆¹⁵N₂ and ⁸H₂ isotopologues (+8.0322) was searched. For all analyses, the precursor mass was obtained from the 480,000 MS scan. The precursor mass tolerance was defined as 50 ppm, and the fragment ion mass tolerance was set to 0.01 Da. A histogram of precursor mass error at different search tolerances is presented in supplemental Fig. S1. Using the COMPASS software suite, obtained search results were filtered to 1% FDR based on E-values. y-ion doublets were extracted from raw files using an in-house algorithm explained in the supplemental information. Briefly, an ensemble of three different machine learning models was used to score each MS/MS spectral peak for C-terminal product ion prediction. To train our ensemble learner to correctly distinguish C-terminal product ion peaks from N-terminal product ion peaks and noise peaks within our experimental MS/MS spectra, we generated a representative training set of spectral data. Instances used for training and test sets were peaks acquired only from MS/MS spectra associated with a peptide identification. Peaks with a signal-to-noise value of less than 5 were not used. Feature information for each training/testing instance was extracted from raw spectral data. Seven MS/MS spectral features were selected to generate training and test set data: (1) “has doublet” (evaluated as “true” only if a spectral peak could be found at the predicted m/z of the peak''s “heavy” partner), (2) “signal-to-noise” (discretized using a scale of 1–5 based on the peak''s signal-to-noise value), (3) “is isotope,” (4) “is neutral loss,” (5) “number of isotopes,” (6) “number of doublet isotopes,” and (7) “has neutral loss.”To evaluate NeuCode SILAC labeling for automated de novo sequencing, PepNovo⁺ (8) was benchmarked on y-ion predicted spectra. First, a set of identified spectra from 13,832 unique peptides (>7,400 per precursor charge 2–3) was produced to train PepNovo⁺ so it could learn features such as the relative peak height ranks of b/y-ions and the probability of noise at each mass interval. These training spectra were acquired under the 11 NeuCode yeast strong cation exchange fractions prepared as described above. Thermo raw files were converted into mzXML format using ProteoWizard v2.2.2828 (with peak-picking turned on) and identified by MS-GF⁺ v9358 (37) at a 1% spectrum-level FDR against the UniProt yeast database (plus isoforms), v20110729. A fixed modification of K⁺8.0142 was imposed along with variable modifications of oxidized Met and deamidated Asn/Gln. All MS/MS scans were searched with a 50-ppm precursor mass tolerance, the high-accuracy LTQ instrument setting, the HCD fragmentation setting, and one allowed missed Lys-C cleavage.Thermo.raw files were also converted into DTA spectra as before, except the in-house algorithm for selecting y-ion doublets was slightly altered to boost the peak height of predicted y-ions above that of other peaks (the cumulative peak height was equal to the sum of the monoisotopic doublet peaks, all isotopic doublet peaks, and two times the peak height of the base peak) and to convert their m/z to charge one. Remaining peaks not predicted to be y-ions were converted to charge one by a previously described MS/MS deconvolution tool (38). Deconvoluted DTA spectra that originated from identified MS/MS scans were then paired with the MSGF⁺ peptide IDs and passed to PepNovo⁺ for training. The resulting PepNovo⁺ scoring model lacked the rank-boosting component (39), which requires identified spectra from >100,000 unique peptides per precursor charge state and extensive modification of the PepNovo⁺ source code to train. Still, the model was sufficient to perform de novo peptide sequencing on the y-ion predicted spectra. PepNovo⁺ was also run on the raw MS/MS scans (mzXML spectra converted to MGF with all MS/MS peaks converted to charge one) by use of a previously trained HCD scoring model that also lacks the rank-boosting component (40). The following PepNovo⁺ parameters were set at all stages of training and benchmarking: fixed modification of K⁺8.0142; variable modifications of oxidized Met and deamidated Asn; 0.01-Da fragment mass tolerance; use of spectrum precursor charge; and use of spectrum precursor m/z.     

Ribose 5-Phosphate Isomerase B Knockdown Compromises Trypanosoma brucei Bloodstream Form Infectivity

Ribose 5-phosphate isomerase is an enzyme involved in the non-oxidative branch of the pentose phosphate pathway, and catalyzes the inter-conversion of D-ribose 5-phosphate and D-ribulose 5-phosphate. Trypanosomatids, including the agent of African sleeping sickness namely Trypanosoma brucei, have a type B ribose-5-phosphate isomerase. This enzyme is absent from humans, which have a structurally unrelated ribose 5-phosphate isomerase type A, and therefore has been proposed as an attractive drug target waiting further characterization. In this study, Trypanosoma brucei ribose 5-phosphate isomerase B showed in vitro isomerase activity. RNAi against this enzyme reduced parasites'' in vitro growth, and more importantly, bloodstream forms infectivity. Mice infected with induced RNAi clones exhibited lower parasitaemia and a prolonged survival compared to control mice. Phenotypic reversion was achieved by complementing induced RNAi clones with an ectopic copy of Trypanosoma cruzi gene. Our results present the first functional characterization of Trypanosoma brucei ribose 5-phosphate isomerase B, and show the relevance of an enzyme belonging to the non-oxidative branch of the pentose phosphate pathway in the context of Trypanosoma brucei infection.     

Crystal structure of Archaeoglobus fulgidus CTP:inositol-1-phosphate cytidylyltransferase, a key enzyme for di-myo-inositol-phosphate synthesis in (hyper)thermophiles

Many Archaea and Bacteria isolated from hot, marine environments accumulate di-myo-inositol-phosphate (DIP), primarily in response to heat stress. The biosynthesis of this compatible solute involves the activation of inositol to CDP-inositol via the action of a recently discovered CTP:inositol-1-phosphate cytidylyltransferase (IPCT) activity. In most cases, IPCT is part of a bifunctional enzyme comprising two domains: a cytoplasmic domain with IPCT activity and a membrane domain catalyzing the synthesis of di-myo-inositol-1,3′-phosphate-1′-phosphate from CDP-inositol and l-myo-inositol phosphate. Herein, we describe the first X-ray structure of the IPCT domain of the bifunctional enzyme from the hyperthermophilic archaeon Archaeoglobus fulgidus DSMZ 7324. The structure of the enzyme in the apo form was solved to a 1.9-Å resolution. The enzyme exhibited apparent K_m values of 0.9 and 0.6 mM for inositol-1-phosphate and CTP, respectively. The optimal temperature for catalysis was in the range 90 to 95°C, and the V_max determined at 90°C was 62.9 μmol · min⁻¹ · mg of protein⁻¹. The structure of IPCT is composed of a central seven-stranded mixed β-sheet, of which six β-strands are parallel, surrounded by six α-helices, a fold reminiscent of the dinucleotide-binding Rossmann fold. The enzyme shares structural homology with other pyrophosphorylases showing the canonical motif G-X-G-T-(R/S)-X₄-P-K. CTP, l-myo-inositol-1-phosphate, and CDP-inositol were docked into the catalytic site, which provided insights into the binding mode and high specificity of the enzyme for CTP. This work is an important step toward the final goal of understanding the full catalytic route for DIP synthesis in the native, bifunctional enzyme.     

The detection and attribution of extreme reductions in vegetation growth across the global land surface

Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite-derived vegetation index data and supporting tree-ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi-arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region- and biome-dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non-dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate-specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.     

Potential applications of stress solutes from extremophiles in protein folding diseases and healthcare

Protein misfolding, aggregation and deposition in the brain, in the form of amyloid, are implicated in the etiology of several neurodegenerative disorders, such as Alzheimer’s, Parkinson’s and prion diseases. Drugs available on the market reduce the symptoms, but they are not a cure. Therefore, it is urgent to identify promising targets and develop effective drugs. Preservation of protein native conformation and/or inhibition of protein aggregation seem pertinent targets for drug development. Several studies have shown that organic solutes, produced by extremophilic microorganisms in response to osmotic and/or heat stress, prevent denaturation and aggregation of model proteins. Among these stress solutes, mannosylglycerate, mannosylglyceramide, di-myo-inositol phosphate, diglycerol phosphate and ectoine are effective in preventing amyloid formation by Alzheimer’s Aβ peptide and/or α-synuclein in vitro. Moreover, mannosylglycerate is a potent inhibitor of Aβ and α-synuclein aggregation in living cells, and mannosylglyceramide and ectoine inhibit aggregation and reduce prion peptide-induced toxicity in human cells. This review focuses on the efficacy of stress solutes from hyper/thermophiles and ectoines to prevent amyloid formation in vitro and in vivo and their potential application in drug development against protein misfolding diseases. Current and envisaged applications of these extremolytes in neurodegenerative diseases and healthcare will also be addressed.     

Cognitive predictors of balance in Parkinson’s disease

Postural instability is one of the most incapacitating symptoms of Parkinson’s disease (PD) and appears to be related to cognitive deficits. This study aims to determine the cognitive factors that can predict deficits in static and dynamic balance in individuals with PD. A sociodemographic questionnaire characterized 52 individuals with PD for this work. The Trail Making Test, Rule Shift Cards Test, and Digit Span Test assessed the executive functions. The static balance was assessed using a plantar pressure platform, and dynamic balance was based on the Timed Up and Go Test. The results were statistically analysed using SPSS Statistics software through linear regression analysis. The results show that a statistically significant model based on cognitive outcomes was able to explain the variance of motor variables. Also, the explanatory value of the model tended to increase with the addition of individual and clinical variables, although the resulting model was not statistically significant The model explained 25–29% of the variability of the Timed Up and Go Test, while for the anteroposterior displacement it was 23–34%, and for the mediolateral displacement it was 24–39%. From the findings, we conclude that the cognitive performance, especially the executive functions, is a predictor of balance deficit in individuals with PD.     

Force-induced bidirectional stepping of cytoplasmic dynein

Cytoplasmic dynein is a minus-end-directed microtubule motor whose mechanism of movement remains poorly understood. Here, we use optical tweezers to examine the force-dependent stepping behavior of yeast cytoplasmic dynein. We find that dynein primarily advances in 8 nm increments but takes other sized steps (4-24 nm) as well. An opposing force induces more frequent backward stepping by dynein, and the motor walks backward toward the microtubule plus end at loads above its stall force of 7 pN. Remarkably, in the absence of ATP, dynein steps processively along microtubules under an external load, with less force required for minus-end- than for plus-end-directed movement. This nucleotide-independent walking reveals that force alone can drive repetitive microtubule detachment-attachment cycles of dynein's motor domains. These results suggest a model for how dynein's two motor domains coordinate their activities during normal processive motility and provide new clues for understanding dynein-based motility in living cells.     

The Disulfide Bond Arrangement in the Extracellular Domain of the Activin Type II Receptor

The initial step in the signaling cascade of the growth factor activin involves its binding to the extracellular domain of the activin type II receptor. This receptor domain contains 10 cysteine residues which are engaged in intramolecular disulfide bonds. To elucidate the structural framework of this domain we have characterized its disulfide-bonding pattern using an extracellular fragment of the receptor which binds activin A with high affinity. By combining proteolysis with mass spectroscopy and chemical sequence analysis, the disulfide connectivity was determined to be as follows: C1–C3, C2–C4, C5–C8, C6–C7, and C9–C10. A similar disulfide arrangement occurs in a family of snake toxins for which the three-dimensional structure is known.     

An assessment of the ultrasonic probe-based enhancement of protein cleavage with immobilized trypsin

The use of ultrasonic probe, in conjunction with immobilized trypsin, has been explored in this work for potential enhancement of protein digestion. Several solid supports commonly used to immobilize trypsin were subjected to different ultrasonication amplitudes and time in order to investigate their mechanical resistance to ultrasonic energy when provided by the ultrasonic probe. Glass beads and magnetic particles were found to remain intact in most conditions studied. It was found that immobilized trypsin cannot be reused after ultrasonication since the enzymatic activity was greatly diminished. For comparative purposes, vortex shaking was also explored for protein cleavage. Four standard proteins--bovine serum albumin, α-lactalbumin, carbonic anhydrase and ovalbumin--were successfully identified using peptide mass fingerprint, or peptide fragment fingerprint. In addition, the performance of the classical protein cleavage (overnight, 12 h) and the ultrasonic methods was found to be similar when the digestion of a complex proteome, human plasma, was assessed through 18-O quantification. The digestion yields found were 90-117% for the ultrasonic and 5-21% for the vortex when those methods were compared with the classical overnight digestion.     

<Emphasis Type="Italic">RNase</Emphasis>-Based Gametophytic Self-Incompatibility Evolution: Questioning the Hypothesis of Multiple Independent Recruitments of the <Emphasis Type="Italic">S</Emphasis>-Pollen Gene

Multiple independent recruitments of the S-pollen component (always an F-box gene) during RNase-based gametophytic self-incompatibility evolution have recently been suggested. Therefore, different mechanisms could be used to achieve the rejection of incompatible pollen in different plant families. This hypothesis is, however, mainly based on the interpretation of phylogenetic analyses, using a small number of divergent nucleotide sequences. In this work we show, based on a large collection of F-box S-like sequences, that the inferred relationship of F-box S-pollen and F-box S-like sequences is dependent on the sequence alignment software and phylogenetic method used. Thus, at present, it is not possible to address the phylogenetic relationship of F-box S-pollen and S-like sequences from different plant families. In Petunia and Malus/Pyrus the putative S-pollen gene(s) show(s) variability patterns different than expected for an S-pollen gene, raising the question of false identification. Here we show that in Petunia, the unexpected features of the putative S-pollen gene are not incompatible with this gene’s being the S-pollen gene. On the other hand, it is very unlikely that the Pyrus SFBB-gamma gene is involved in specificity determination. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.