Mass spectrometric analysis of peptides in brain neurosecretory cells and neurohemal organs in the adult blowfly,Protophormia terraenovae

Neuropeptides in neurosecretory cells of the pars intercerebralis (PI) and pars lateralis (PL) in the brain, and those in the corpus cardiacum–hypocerebral ganglion complex (CC-HG) and corpus allatum (CA) were examined by mass spectrometry and immunocytochemistry in adult females of the blowfly, Protophormia terraenovae. By using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and electrospray ionization quadrupole orthogonal acceleration time-of-flight mass spectrometry (ESI-Q-Tof MS) and MS/MS, 4 peptides (including myosuppressin and SIFamide) were detected in the PI, 12 peptides (including [Arg⁷]-corazonin and [Arg⁷]-corazonin^3–11) in the PL, 13 peptides (including myosuppressin, [Arg⁷]-corazonin and [Arg⁷]-corazonin^3–11) in the CC-HG, and 6 peptides in the CA. MALDI-TOF MS analysis of each tissue or organ was made in about 20 flies under diapause-inducing (LD 12:12 at 20 °C) and diapause-averting conditions (LD 18:6 at 25 °C). These molecular ion peaks did not distinctively differ between diapause-inducing and diapause-averting conditions. A peptide with an m/z value at 1395.1 was purified from 240 brains and the 2nd–10th amino acids were sequenced as –YRKPPFNGS–, corresponding to a partial sequence of SIFamide. Only two pairs of somata in the PI were immunoreactive to antisera against SIFamide, which were local neurons widely extending fibers throughout the brain neuropils.     

A Novel Spectral Annotation Strategy Streamlines Reporting of Mono-ADP-ribosylated Peptides Derived from Mouse Liver and Spleen in Response to IFN-γ

Mass-spectrometry-enabled ADP-ribosylation workflows are developing rapidly, providing researchers a variety of ADP-ribosylome enrichment strategies and mass spectrometric acquisition options. Despite the growth spurt in upstream technologies, systematic ADP-ribosyl (ADPr) peptide mass spectral annotation methods are lacking. HCD-dependent ADP-ribosylome studies are common, but the resulting MS2 spectra are complex, owing to a mixture of b/y-ions and the m/p-ion peaks representing one or more dissociation events of the ADPr moiety (m-ion) and peptide (p-ion). In particular, p-ions that dissociate further into one or more fragment ions can dominate HCD spectra but are not recognized by standard spectral annotation workflows. As a result, annotation strategies that are solely reliant upon the b/y-ions result in lower spectral scores that in turn reduce the number of reportable ADPr peptides. To improve the confidence of spectral assignments, we implemented an ADPr peptide annotation and scoring strategy. All MS2 spectra are scored for the ADPr m-ions, but once spectra are assigned as an ADPr peptide, they are further annotated and scored for the p-ions. We implemented this novel workflow to ADPr peptides enriched from the liver and spleen isolated from mice post 4 h exposure to systemic IFN-γ. HCD collision energy experiments were first performed on the Orbitrap Fusion Lumos and the Q Exactive, with notable ADPr peptide dissociation properties verified with CID (Lumos). The m-ion and p-ion series score distributions revealed that ADPr peptide dissociation properties vary markedly between instruments and within instrument collision energy settings, with consequences on ADPr peptide reporting and amino acid localization. Consequentially, we increased the number of reportable ADPr peptides by 25% (liver) and 17% (spleen) by validation and the inclusion of lower confidence ADPr peptide spectra. This systematic annotation strategy will streamline future reporting of ADPr peptides that have been sequenced using any HCD/CID-based method.     

A Novel Spectral Annotation Strategy Streamlines Reporting of Mono-ADP-ribosylated Peptides Derived from Mouse Liver and Spleen in Response to IFN-γ

Mass-spectrometry-enabled ADP-ribosylation workflows are developing rapidly, providing researchers a variety of ADP-ribosylome enrichment strategies and mass spectrometric acquisition options. Despite the growth spurt in upstream technologies, systematic ADP-ribosyl (ADPr) peptide mass spectral annotation methods are lacking. HCD-dependent ADP-ribosylome studies are common, but the resulting MS2 spectra are complex, owing to a mixture of b/y-ions and the m/p-ion peaks representing one or more dissociation events of the ADPr moiety (m-ion) and peptide (p-ion). In particular, p-ions that dissociate further into one or more fragment ions can dominate HCD spectra but are not recognized by standard spectral annotation workflows. As a result, annotation strategies that are solely reliant upon the b/y-ions result in lower spectral scores that in turn reduce the number of reportable ADPr peptides. To improve the confidence of spectral assignments, we implemented an ADPr peptide annotation and scoring strategy. All MS2 spectra are scored for the ADPr m-ions, but once spectra are assigned as an ADPr peptide, they are further annotated and scored for the p-ions. We implemented this novel workflow to ADPr peptides enriched from the liver and spleen isolated from mice post 4 h exposure to systemic IFN-γ. HCD collision energy experiments were first performed on the Orbitrap Fusion Lumos and the Q Exactive, with notable ADPr peptide dissociation properties verified with CID (Lumos). The m-ion and p-ion series score distributions revealed that ADPr peptide dissociation properties vary markedly between instruments and within instrument collision energy settings, with consequences on ADPr peptide reporting and amino acid localization. Consequentially, we increased the number of reportable ADPr peptides by 25% (liver) and 17% (spleen) by validation and the inclusion of lower confidence ADPr peptide spectra. This systematic annotation strategy will streamline future reporting of ADPr peptides that have been sequenced using any HCD/CID-based method.     

Mass spectrometric characterization of isoform variants of peanut (Arachis hypogaea) stem lectin (SL-I)

Matrix assisted laser desorption/ionization–time-of-flight (MALDI–TOF) mass spectrometric (MS) analysis of purified Arachis hypogaea stem lectin (SL-I) and its tryptic digests suggested it to be an isoformic glucose/mannose binding lectin. Two-dimensional gel electrophoresis of SL-I indicated six isoforms (A1–A6), which were confirmed by Western blotting and MALDI–TOF MS analysis. Comparative analysis of peptide mass spectra of the isoforms matched with A. hypogaea lectins with three different accession numbers (Q43376_ARAHY, Q43377_ARAHY, Q70DJ5_ARAHY). Tandem mass spectrometric (MS/MS) analysis of tryptic peptides revealed these to be isoformic variants with altered amino acid sequences. Among the peptides, the peptide T12 showed major variation. The ¹⁹⁹Val–Ser–Tyr–Asn²⁰² sequence in peptide T12 of A1 and A2 was replaced by ¹⁹⁹Leu–Ser–His–Glu²⁰² in A3 and A4 (T12′) while in A5 and A6 this sequence was ¹⁹⁹Val–Ser–Tyr–Val²⁰² (T12″). Peptide T1 showed the presence of ¹⁰Asn in the isoforms A1–A5 while in A6 this amino acid was replaced by ¹⁰Lys (T1′). Overall amino acid sequence as identified by MS/MS showed a high degree of similarity between A1, A2 and among A3, A4, A5. Carbohydrate binding domain and adenine binding site seem to be conserved.     

Improved liquid chromatography–tandem mass spectrometry method for the analysis of eptifibatide in human plasma

A rapid, selective and highly sensitive high performance liquid chromatography–tandem mass spectrometry method (LC–MS/MS) was developed and validated for the determination and pharmacokinetic investigation of eptifibatide in human plasma. Eptifibatide and the internal standard (IS), EPM-05, were extracted from plasma samples using solid phase extraction. Chromatographic separation was performed on a C₁₈ column at a flow rate of 0.5 mL/min. Detection of eptifibatide and the IS was achieved by tandem mass spectrometry with an electrospray ionization (ESI) interface in positive ion mode. Traditional multiple reaction monitoring (MRM) using the transition of m/z 832.6 → m/z 646.4 and m/z 931.6 → m/z 159.4 was performed to quantify eptifibatide and the IS, respectively. The calibration curves were linear over the range of 1–1000 ng/mL with the lower limit of quantitation validated at 1 ng/mL. The intra- and inter-day precisions were within 13.3%, while the accuracy was within ±7.6% of nominal values. The validated LC–MS/MS method was successfully applied for the evaluation of pharmacokinetic parameters of eptifibatide after intravenous (i.v.) administration of a 45 μg/kg bolus of eptifibatide to 8 healthy volunteers.     

Humoral Responses to Diverse Autoimmune Disease-Associated Antigens in Multiple Sclerosis

To compare frequencies of autoreactive antibody responses to endogenous disease-associated antigens in healthy controls (HC), relapsing and progressive MS and to assess their associations with clinical and MRI measures of MS disease progression.

Methods

The study analyzed 969 serum samples from 315 HC, 411 relapsing remitting MS (RR-MS), 128 secondary progressive MS (SP-MS), 33 primary progressive MS (PP-MS) and 82 patients with other neurological diseases for autoantibodies against two putative MS antigens CSF114(Glc) and KIR4.1a and KIR4.1b and against 24 key endogenous antigens linked to diseases such as vasculitis, systemic sclerosis, rheumatoid arthritis, Sjogren’s syndrome, systemic lupus erythematosus, polymyositis, scleroderma, polymyositis, dermatomyositis, mixed connective tissue disease and primary biliary cirrhosis. Associations with disability and MRI measures of lesional injury and neurodegeneration were assessed.

Results

The frequencies of anti-KIR4.1a and anti-KIR4.1b peptide IgG positivity were 9.8% and 11.4% in HC compared to 4.9% and 7.5% in RR-MS, 8.6% for both peptides in SP-MS and 6.1% for both peptides in PP-MS (p = 0.13 for KIR4.1a and p = 0.34 for KIR4.1b), respectively. Antibodies against CSF114(Glc), KIR4.1a and KIR4.1b peptides were not associated with MS compared to HC, or with MS disease progression. HLA DRB1*15:01 positivity and anti-Epstein Barr virus antibodies, which are MS risk factors, were not associated with these putative MS antibodies.

Conclusions

Antibody responses to KIR4.1a and KIR4.1b peptides are not increased in MS compared to HC nor associated with MS disease progression. The frequencies of the diverse autoreactive antibodies investigated are similar in MS and HC.     

EpiProfile Quantifies Histone Peptides With Modifications by Extracting Retention Time and Intensity in High-resolution Mass Spectra

Histone post-translational modifications contribute to chromatin function through their chemical properties which influence chromatin structure and their ability to recruit chromatin interacting proteins. Nanoflow liquid chromatography coupled with high resolution tandem mass spectrometry (nanoLC-MS/MS) has emerged as the most suitable technology for global histone modification analysis because of the high sensitivity and the high mass accuracy of this approach that provides confident identification. However, analysis of histones with this method is even more challenging because of the large number and variety of isobaric histone peptides and the high dynamic range of histone peptide abundances. Here, we introduce EpiProfile, a software tool that discriminates isobaric histone peptides using the distinguishing fragment ions in their tandem mass spectra and extracts the chromatographic area under the curve using previous knowledge about peptide retention time. The accuracy of EpiProfile was evaluated by analysis of mixtures containing different ratios of synthetic histone peptides. In addition to label-free quantification of histone peptides, EpiProfile is flexible and can quantify different types of isotopically labeled histone peptides. EpiProfile is unique in generating layouts (i.e. relative retention time) of histone peptides when compared with manual quantification of the data and other programs (such as Skyline), filling the need of an automatic and freely available tool to quantify labeled and non-labeled modified histone peptides. In summary, EpiProfile is a valuable nanoflow liquid chromatography coupled with high resolution tandem mass spectrometry-based quantification tool for histone peptides, which can also be adapted to analyze nonhistone protein samples.The nucleosome, the basic unit of chromatin, consists of 147 base pairs of DNA wrapped around histone proteins (H2A, H2B, H3, and H4). Histones play vital roles in chromatin, interacting with many signaling proteins and chromatin-structural proteins through various post-translational modifications (PTMs)¹ (1–3). There are numerous PTMs on histones, including methylation (mono - me1, di - me2, tri - me3), acetylation (ac), phosphorylation (ph), ubiquitination, and SUMOylation (4). Histone PTMs can affect chromatin function, and therefore influence processes such as gene accessibility, DNA repair and chromosome condensation. Moreover, histone PTMs cross-talk in a synergistic manner to fine-tune gene expression (5). Therefore, quantification of histone PTMs has become a high priority to investigate cell regulation and epigenetics (6).Traditionally, antibody-based methods (e.g. Western blot) have been used to analyze histone modifications (7), which have multiple disadvantages. First, antibodies are not available for every new PTM discovered. Second, PTMs on neighboring amino acids (e.g. H3K9me1–3 and H3S10ph) may prevent antibody binding, a phenomenon called epitope occlusion. Third, the quantification of PTMs via antibody-based methods is not sensitive to small differences (e.g. <twofold). Mass spectrometry (MS) has emerged as a sensitive and efficient technique to detect known and novel PTMs (8). The high mass accuracy and the high speed of modern mass spectrometers allow for sensitive, confident, and accurate peptide quantification when coupled with nanoflow liquid chromatography (nanoLC).NanoLC-MS/MS analysis of protein digests (i.e. bottom-up MS) is nowadays a mature and widely applied technology. Data-dependent acquisition is the most commonly adopted MS acquisition method to identify peptides via bottom-up MS (9–12), generating MS1 and MS2 spectra. Nevertheless, histone proteins are particularly challenging to analyze by using the generalized bottom-up workflow. As histones are rich with lysines and arginines, tryptic digest of histones generates short peptides that are difficult to be retained on C18 columns. To improve histone peptide retention, the unmodified and mono-methylated lysines and peptide N terminus can be selectively chemically propionylated (13–16), preventing tryptic digest after lysine to generate longer peptides. Moreover, peptide identification through traditional database searches leads to a large number of false positives, as allowing several dynamic modifications (e.g. me1/me2/me3, ac, ph) dramatically increases the number of molecular candidates and thus the possibility to achieve a false hit (12). Therefore, software tools that quantify histone peptides require additional data to correctly map a given peptide, such as previous knowledge of peptide retention time.Quantification of histone peptides is particularly challenging because of presence of isobaric peptides, near isobaric PTMs such as tri-methylation (42.047 Da) and acetylation (42.011 Da), and low abundant species. Previous knowledge about relative peptide retention time (RT) enables differentiation between species close in mass and therefore selection of the correct peak for integration of the area of the chromatographic peak (i.e. area under curve or AUC). However, determination of peptide RT might be difficult because of their low abundance though acid extraction was performed to purify histones. This problem can be solved by using isotopically labeled synthetic histone peptides (17), or data independent approaches (18). When using relative retention time information to assign peak identities, reproducible nanoLC is crucial, especially because some isobaric peptides co-elute. In this case, the MS acquisition method must perform targeted MS2 for the co-eluting isobaric peptides at the specific time that they elute. These species can be discriminated and quantified based on the intensity of fragment ions unique to each species. For instance, the peptides KacSTGGKAPR (H3K9ac) and KSTGGKacAPR (H3K14ac) have the same mass and overlap at the nanoLC elution (the full protein sequence of human canonical histone H3 and H4 are shown in Fig. 1A). Thus, the co-eluting isobaric peptides could not be quantified separately based on the MS1 signal, but the unique fragment ions present in MS2 spectra allow them to be quantified individually.Open in a separate windowFig. 1.Histones are a challenge for quantitative mass spectrometry analyses. A, Human histone H3.1 and H4 protein sequences. B, Spline fitting to calculate AUC: blue lines are the original peaks and pink lines are the fitted peaks. C, An example of isobaric PTM modified peptides. The above MS2 is matched with H3K18ac, and the same MS2 is also matched with H3K23ac below. D, The workflow of EpiProfile: inputting precursor m/z and charge state, extracting elution profiles, selecting the correct chromatographic peak, calculating AUC, and outputting quantification tables and figures.There have been few computational investigations attempting to solve the problem of quantifying co-eluting isobaric peptides. DiMaggio et al. used a mixed integer linear optimization (MILP) framework to quantify partially co-eluting isobaric histone peptides from electron transfer dissociation (ETD) spectra (19). The framework is comprised of two MILP models: (1) enumerating the entire space of the modified forms that satisfy a given peptide mass and (2) determining the relative composition of the modified forms in the spectrum. Another study by Guan et al. identified isobaric peptides by searching ETD MS/MS spectra for ions representing all possible configurations of modified peptides using a visual assistance program. The relative abundances of these species were estimated by using a nonnegative least squares procedure (20). Other quantification programs can also perform accurate peak picking, but are commonly not as suitable for heavily modified and isobaric histone peptides (e.g. Skyline) (21). These software programs are unable to provide the layouts of histone peptides (i.e. relative RTs) or discriminate all isobaric modified peptides, two tasks that are vital for full characterization of a histone sample.In this study, we developed a new quantification program named EpiProfile. EpiProfile extracts ion chromatography for known histone peptides by using previous knowledge about their elution profiles. Moreover, it discriminates and quantifies the isobaric histone peptides by resolving the linear equations listed with the peak heights of unique fragment ions between the two modification sites in the MS2 spectra (e.g. ions between H3K9ac and H3K14ac). We evaluated the accuracy of EpiProfile by mixing different ratios of synthetic histone peptides, and then tested EpiProfile by analyzing nanoLC-MS/MS data sets of the following samples: purified histones from HeLa cells, a synthetic histone peptide library, and histone peptides labeled during cell growth with ¹³C-labeled glucose media or stable isotope labeling by amino acids in cell culture (SILAC) (22). We compared EpiProfile to manual quantification of the data, and also with the openly available program Skyline. We found that manual quantification is obviously time-consuming and that Skyline cannot generate the layouts of histone peptides and cannot discriminate four or six-component isobaric peptides, a common occurrence in histone data. Moreover, EpiProfile is highly flexible, and thus it can be used to analyze various protein samples, including isotopically labeled peptides and nonhistone data sets.     

LC/MS evaluation of metabolism and membrane transport of bombesin peptides

Two bombsin peptides, GRPR agonist [Aca-QWAVGHLM-NH₂] and antagonist [fQWAVGHL-NHEthyl] were evaluated. We employed the highly sensitive Waters Q-Tof Premier MS coupled with a UPLC system to identify the metabolites produced by rat hepatocytes or PC-3 human prostate cancer cells; and we utilized the AB/MDS 4000 Q-Trap LC/MS/MS system with highly sensitive quantitative and qualitative performance, to quantitatively analyze the internalization of GRPR agonist and antagonist in PC-3 cells. The major metabolites of both GRPR agonist and antagonist were the result of peptide bond hydrolysis between W and A which was demonstrated by observation of the N-terminal fragment m/z 446 (Aca-QW-OH) for agonist and m/z 480 (fQW-OH) for antagonist. Both peptides were also hydrolyzed between A and V which formed peaks m/z 517 [Aca-QWA-OH] and m/z 555 (VGHLM-NH2) for the agonist and m/z 551 [fQWA-OH] and m/z 452 (VGHL-NHEthyl) for the antagonist. The peptide agonist also formed a unique metabolite that resulted from hydrolysis of the C-terminal amide. The antagonist showed significantly slower metabolism as compared to the agonist in both rat hepatocytes and PC-3 cells. The antagonist also showed significantly lower PC-3 cell internalization rate than that of the agonist. In conclusion, the metabolism profiles of both GRPR agonist and antagonist peptides were identified by LC/MS. The antagonist peptide was more stable than the agonist peptide in rat hepatocyte incubation. One major factor could be the hydrolysis-resistant C-terminal L-NHEthyl group compared with the unsubstituted amide of the agonist. Another factor could be different amino acid sequences of the agonist and antagonist that may also influence the enzymatic hydrolysis. The antagonist ligand is potentially more useful for receptor-targeted imaging due primarily to its higher metabolic stability.     

Metaproteogenomic analysis of a sulfate-reducing enrichment culture reveals genomic organization of key enzymes in the m-xylene degradation pathway and metabolic activity of proteobacteria

This study aimed to ascertain the functional and phylogenetic relationships within an m-xylene degrading sulfate-reducing enrichment culture, which had been maintained for several years in the laboratory with m-xylene as the sole source of carbon and energy. Previous studies indicated that a phylotype affiliated to the Desulfobacteraceae was the main m-xylene assimilating organism. In the present study, genes and gene products were identified by a metaproteogenomic approach using LC-MS/MS analysis of the microbial community, and 2426 peptides were identified from 576 proteins. In the metagenome of the community, gene clusters encoding enzymes involved in fumarate addition to a methyl moiety of m-xylene (nms, bss), as well as gene clusters coding for enzymes involved in modified beta-oxidation to (3-methyl)benzoyl-CoA (bns), were identified in two separate contigs. Additionally, gene clusters containing homologues to bam genes encoding benzoyl-CoA reductase (Bcr) class II, catalyzing the dearomatization of (3-methyl)benzoyl-CoA, were identified. Time-resolved protein stable isotope probing (protein-SIP) experiments using ¹³C-labeled m-xylene showed that the respective gene products were highly ¹³C-labeled. The present data suggested the identification of gene products that were similar to those involved in methylnaphthalene degradation even though the consortium was not capable of growing in the presence of naphthalene, methylnaphthalene or toluene as substrates. Thus, a novel branch of enzymes was found that was probably specific for anaerobic m-xylene degradation.     

Confirmation of spectinomycin in milk using ion-pair solid-phase extraction and liquid chromatography–electrospray ion trap mass spectrometry

A confirmation procedure is described for residues of spectinomycin in bovine milk. Spectinomycin is extracted from raw milk using ion-pair reversed-phase solid-phase extraction. The extracts are ion-pair chromatographed on a polymeric reversed-phase column and analyzed on a quadrupole ion trap mass spectrometer equipped with an electrospray interface. MS–MS data are acquired in the scan mode of product ions deriving from m/z 333, the protonated molecular ion. The estimated limit of confirmation is between 0.05 and 0.1 μg/ml. The procedure was validated with control milk, fortified milk (0.1–5.0 μg/ml), and milk from cows dosed with spectinomycin.     

A peptidomics study reveals the impressive antimicrobial peptide arsenal of the wax moth Galleria mellonella

The complete antimicrobial peptide repertoire of Galleria mellonella was investigated for the first time by LC/MS. Combining data from separate trypsin, Glu-C and Asp-N digests of immune hemolymph allowed detection of 18 known or putative G. mellonella antimicrobial peptides or proteins, namely lysozyme, moricin-like peptides (5), cecropins (2), gloverin, Gm proline-rich peptide 1, Gm proline-rich peptide 2, Gm anionic peptide 1 (P1-like), Gm anionic peptide 2, galiomicin, gallerimycin, inducible serine protease inhibitor 2, 6tox and heliocin-like peptide. Six of these were previously known only as nucleotide sequences, so this study provides the first evidence for expression of these genes. LC/MS data also provided insight into the expression and processing of the antimicrobial Gm proline-rich peptide 1. The gene for this peptide was isolated and shown to be unique to moths and to have an unusually long precursor region (495 bp). The precursor region contained other proline-rich peptides and LC/MS data suggested that these were being specifically processed and were present in hemolymph at very high levels. This study shows that G. mellonella can concurrently release an impressive array of at least 18 known or putative antimicrobial peptides from 10 families to defend itself against invading microbes.     

MS1 Peptide Ion Intensity Chromatograms in MS2 (SWATH) Data Independent Acquisitions. Improving Post Acquisition Analysis of Proteomic Experiments

Quantitative analysis of discovery-based proteomic workflows now relies on high-throughput large-scale methods for identification and quantitation of proteins and post-translational modifications. Advancements in label-free quantitative techniques, using either data-dependent or data-independent mass spectrometric acquisitions, have coincided with improved instrumentation featuring greater precision, increased mass accuracy, and faster scan speeds. We recently reported on a new quantitative method called MS1 Filtering (Schilling et al. (2012) Mol. Cell. Proteomics 11, 202–214) for processing data-independent MS1 ion intensity chromatograms from peptide analytes using the Skyline software platform. In contrast, data-independent acquisitions from MS2 scans, or SWATH, can quantify all fragment ion intensities when reference spectra are available. As each SWATH acquisition cycle typically contains an MS1 scan, these two independent label-free quantitative approaches can be acquired in a single experiment. Here, we have expanded the capability of Skyline to extract both MS1 and MS2 ion intensity chromatograms from a single SWATH data-independent acquisition in an Integrated Dual Scan Analysis approach. The performance of both MS1 and MS2 data was examined in simple and complex samples using standard concentration curves. Cases of interferences in MS1 and MS2 ion intensity data were assessed, as were the differentiation and quantitation of phosphopeptide isomers in MS2 scan data. In addition, we demonstrated an approach for optimization of SWATH m/z window sizes to reduce interferences using MS1 scans as a guide. Finally, a correlation analysis was performed on both MS1 and MS2 ion intensity data obtained from SWATH acquisitions on a complex mixture using a linear model that automatically removes signals containing interferences. This work demonstrates the practical advantages of properly acquiring and processing MS1 precursor data in addition to MS2 fragment ion intensity data in a data-independent acquisition (SWATH), and provides an approach to simultaneously obtain independent measurements of relative peptide abundance from a single experiment.Mass spectrometry is the leading technology for large-scale identification and quantitation of proteins and post-translational modifications (PTMs)¹ in biological systems (1, 2). Although several types of experimental designs are employed in such workflows, most large-scale applications use data-dependent acquisitions (DDA) where peptide precursors are first identified in the MS1 scan and one or more peaks are then selected for subsequent fragmentation to generate their corresponding MS2 spectra. In experiments using DDA, one can employ either chemical/metabolic labeling or label-free strategies for relative quantitation of peptides (and proteins) (3, 4). Depending on the type of labeling approach employed, i.e. metabolic labeling with SILAC or postmetabolic labeling with ICAT or isobaric tags such as iTRAQ or TMT, the relative quantitation of these peptides are made using either MS1 or MS2 ion intensity data (4–7). Label-free quantitative techniques have until recently been based entirely on integrated ion intensity measurements of precursors in the MS1 scan, or in the case of spectral counting the number of assigned MS2 spectra (3, 8, 9).Label-free approaches have recently generated more widespread interest (10–12), in part because of their adaptability to a wide range of proteomic workflows, including human samples that are not amenable to most metabolic labeling techniques, or where chemical labeling may be cost prohibitive and/or interfere with subsequent enrichment steps (11, 13). However the use of DDA for label-free quantitation is also susceptible to several limitations including insufficient reproducibility because of under-sampling, digestion efficiency, as well as misidentifications (14, 15). Moreover, low ion abundance may prohibit peptide selection, especially in complex samples (14). These limitations often present challenges in data analysis when making comparisons across samples, or when a peptide is sampled in only one of the study conditions.To address the challenges in obtaining more comprehensive sampling in MS1 space, Purvine et al. first demonstrated the ability to obtain sequence information from peptides fragmented across the entire m/z range using “shotgun or parallel collision-induced dissociation (CID)” on an orthogonal time of flight instrument (16). Shortly thereafter Venable et al. reported on a data independent acquisition methodology to limit the complexity of the MS2 scan by using a segmented approach for the sequential isolation and fragmentation of all peptides in a defined precursor window (e.g. 10 m/z) using an ion trap mass spectrometer (17). However, the proper implementation of this DIA technique suffered from technical limitations of instruments available at that time, including slow acquisition rates and low MS2 resolution that made systematic product ion extraction problematic. To alleviate the challenge of long duty cycles in DIAs, researchers at the Waters Corporation adopted an alternative approach by rapidly switching between low (MS1) and high energy (MS2) scans and then using proprietary software to align peptide precursor and fragment ion information to determine peptide sequences (18, 19). Recent mass spectrometry innovations in efficient high-speed scanning capabilities, together with high-resolution data acquisition of both MS1 and MS2 scans, and multiplexing of scan windows have overcome many of these limitations (10, 20, 21). Moreover, the simultaneous development of novel software solutions for extracting ion intensity chromatograms based on spectral libraries has enabled the use of DIA for large-scale label free quantitation of multiple peptide analytes (21, 22). In addition to targeting specific peptides from a previously generated peptide spectral library, the data can also be reexamined (i.e. post-acquisition) for additional peptides of interest as new reference data emerges. On the SCIEX TripleTOF 5600, a quadrupole orthogonal time-of-flight mass spectrometer, this technique has been optimized and extended to what is called ‘SWATH MS2′ based on a combination of new technical and software improvements (10, 22).In a DIA experiment a MS1 survey scan is carried out across the mass range followed by a SWATH MS2 acquisition series, however the cycle time of the MS1 scan is dramatically shortened compared with DDA type experiments. The Q1 quadrupole is set to transmit a wider window, typically Δ25 m/z, to the collision cell in incremental steps over the full mass range. Therefore the MS/MS spectra produced during a SWATH MS2 acquisition are of much greater complexity as the MS/MS spectra are a composite of all fragment ions produced from peptide analytes with molecular ions within the selected MS1 m/z window. The cycle of data independent MS1 survey scans and SWATH MS2 scans is repeated throughout the entire LC-MS acquisition. Fragment ion information contained in these SWATH MS2 spectra can be used to uniquely identify specific peptides by comparisons to reference spectra or spectral libraries. Moreover, ion intensities of these fragment ions can also be used for quantitation. Although MS2 typically increases selectivity and reduces the chemical noise often observed in MS1 scans, quantifying peptides from SWATH MS2 scans can be problematic because of the presence of interferences in one or more fragment ions or decreased ion intensity of MS2 scans as compared with the MS1 precursor ion abundance.To partially alleviate some of these limitations in SWATH MS2 scan quantitation it is potentially advantageous to exploit MS1 ion intensity data, which is acquired independently as part of each SWATH scan cycle. Recently, our laboratories and others have developed label free quantitation tools for data dependent acquisitions (11, 12, 23) using MS1 ion intensity data. For example, the MS1 Filtering algorithm uses expanded features in the open source software application Skyline (11, 24). Skyline MS1 Filtering processes precursor ion intensity chromatograms of peptide analytes from full scan mass spectral data acquired during data dependent acquisitions by LC MS/MS. New graphical tools were developed within Skyline to enable visual inspection and manual interrogation and integration of extracted ion chromatograms across multiple acquisitions. MS1 Filtering was subsequently shown to have excellent linear response across several orders of magnitude with limits of detection in the low attomole range (11). We, and others, have demonstrated the utility of this method for carrying out large-scale quantitation of peptide analytes across a range of applications (25–28). However, quantifying peptides based on MS1 precursor ion intensities can be compromised by a low signal-to-noise ratio. This is particularly the case when quantifying low abundance peptides in a complex sample where the MS1 ion “background” signal is high, or when chromatograms contain interferences, or partial overlap of multiple target precursor ions.Currently MS1 scans are underutilized or even deemphasized by some vendors during DIA workflows. However, we believe an opportunity exists that would improve data-independent acquisitions (DIA) experiments by including MS1 ion intensity data in the final data processing of LC-MS/MS acquisitions. Therefore, to address this possibility, we have adapted Skyline to efficiently extract and process both precursor and product ion chromatograms for label free quantitation across multiple samples. The graphical tools and features originally developed for SRM and MS1 Filtering experiments have been expanded to process DIA data sets from multiple vendors including SCIEX, Thermo, Waters, Bruker, and Agilent. These expanded features provide a single platform for data mining of targeted proteomics using both the MS1 and MS2 scans that we call Integrated Dual Scan Analysis, or IDSA. As a test of this approach, a series of SWATH MS2 acquisitions of simple and complex mixtures was analyzed on an SCIEX TripleTOF 5600 mass spectrometer. We also investigated the use of MS2 scans for differentiating a case of phosphopeptide isomers that are indistinguishable at the MS1 level. In addition, we investigated whether smaller SWATH m/z windows would provide more reliable quantitative data in these cases by reducing the number of potential interferences. Lastly, we performed a statistical assessment of the accuracy and reproducibility of the estimated (log) fold change of mitochondrial lysates from mouse liver at different concentration levels to better assess the overall value of acquiring MS1 and MS2 data in combination and as independent measurements during DIA experiments.     

pepgrep: A Tool for Peptide MS/MS Pattern Matching

Typically, detection of protein sequences in collision-induced dissociation (CID) tandem MS (MS2) dataset is performed by mapping identified peptide ions back to protein sequence by using the protein database search (PDS) engine. Finding a particular peptide sequence of interest in CID MS2 records very often requires manual evaluation of the spectrum, regardless of whether the peptide-associated MS2 scan is identified by PDS algorithm or not. We have developed a compact cross-platform database-free command-line utility, pepgrep, which helps to find an MS2 fingerprint for a selected peptide sequence by pattern-matching of modelled MS2 data using Peptide-to-MS2 scoring algorithm. pepgrep can incorporate dozens of mass offsets corresponding to a variety of post-translational modifications (PTMs) into the algorithm. Decoy peptide sequences are used with the tested peptide sequence to reduce false-positive results. The engine is capable of screening an MS2 data file at a high rate when using a cluster computing environment. The matched MS2 spectrum can be displayed by using built-in graphical application programming interface (API) or optionally recorded to file. Using this algorithm, we were able to find extra peptide sequences in studied CID spectra that were missed by PDS identification. Also we found pepgrep especially useful for examining a CID of small fractions of peptides resulting from, for example, affinity purification techniques. The peptide sequences in such samples are less likely to be positively identified by using routine protein-centric algorithm implemented in PDS. The software is freely available at http://bsproteomics.essex.ac.uk:8080/data/download/pepgrep-1.4.tgz.     

Antioxidant and phenolic acid profiles of tissue cultured and acclimatized Merwilla plumbea plantlets in relation to the applied cytokinins

Merwilla plumbea (Lindl.) Speta is an important medicinal plant widely used in traditional medicine. We evaluated the effect of five cytokinins [benzyladenine (BA), 2-isopentenyladenine (2iP), meta-topolin (mT), meta-topolin riboside (mTR), and meta-methoxy-9-tetrahydropyran-2-yl-topolin (MemTTHP)] on the level of phenolic acids and antioxidant activity of M. plumbea during the tissue culture and acclimatization stages. Two cytokinins (mT and mTR) significantly improved the antioxidant activity of tissue culture plantlets while the control plantlets were better after acclimatization. Using UPLC–MS/MS, the levels of hydroxybenzoic and hydroxycinnamic acid derivatives (phenolic acids) varied significantly during tissue culture and acclimatization, depending on the cytokinin and plant part analyzed. Vanillic acid (24.9 μg g⁻¹) detected in underground parts of tissue culture plants supplemented with BA was the most abundant phenolic acid detected. The current findings indicate that the phytochemicals together with the bioactivity during in vitro propagation of M. plumbea is influenced by the cytokinin type used and the stage of plant material collection.     

Reproducibility of an HPLC-ESI-MS/MS method for the measurement of stable-isotope enrichment of in vivo-labeled muscle ATP synthase beta subunit

We sought to evaluate the reproducibility of a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based approach to measure the stable-isotope enrichment of in vivo-labeled muscle ATP synthase β subunit (β-F1-ATPase), a protein most directly involved in ATP production, and whose abundance is reduced under a variety of circumstances. Muscle was obtained from a rat infused with stable-isotope-labeled leucine. The muscle was homogenized, β-F1-ATPase immunoprecipitated, and the protein was resolved using 1D-SDS PAGE. Following trypsin digestion of the isolated protein, the resultant peptide mixtures were subjected to analysis by HPLC-ESI-MS/MS, which resulted in the detection of multiple β-F1-ATPase peptides. There were three β-F1-ATPase unique peptides with a leucine residue in the amino acid sequence, and which were detected with high intensity relative to other peptides and assigned with >95% probability to β-F1-ATPase. These peptides were specifically targeted for fragmentation to access their stable-isotope enrichment based on MS/MS peak areas calculated from extracted ion chromatographs for selected labeled and unlabeled fragment ions. Results showed best linearity (R² = 0.99) in the detection of MS/MS peak areas for both labeled and unlabeled fragment ions, over a wide range of amounts of injected protein, specifically for the β-F1-ATPase_134-143 peptide. Measured stable-isotope enrichment was highly reproducible for the β-F1-ATPase_134-143 peptide (CV = 2.9%). Further, using mixtures of synthetic labeled and unlabeled peptides we determined that there is an excellent linear relationship (R² = 0.99) between measured and predicted enrichment for percent enrichments ranging between 0.009% and 8.185% for the β-F1-ATPase_134-143 peptide. The described approach provides a reliable approach to measure the stable-isotope enrichment of in-vivo-labeled muscle β-F1-ATPase based on the determination of the enrichment of the β-F1-ATPase_134-143 peptide.     

Hylaranins: prototypes of a new class of amphibian antimicrobial peptide from the skin secretion of the oriental broad-folded frog,Hylarana latouchii

Amphibian skin secretions contain a broad spectrum of biologically active compounds, particularly antimicrobial peptides, which are considered to constitute a first line of defence against bacterial infection. Here we describe the identification of two prototype peptides representing a novel structural class of antimicrobial peptide from the skin secretion of the oriental broad-folded frog, Hylarana latouchii. Named hylaranin-L1 (GVLSAFKNALPGIMKIIVamide) and hylaranin-L2 (GVLSVIKNALPGIMRFIAamide), both peptides consist of 18 amino acid residues, are C-terminally amidated and are of unique primary structures. Their primary structures were initially deduced by MS/MS fragmentation sequencing from reverse-phase HPLC fractions of skin secretion that demonstrated antimicrobial activity. Subsequently, their precursor-encoding cDNAs were cloned from a skin secretion-derived cDNA library and their primary structures were confirmed unequivocally. Synthetic replicates of both peptides exhibited broad-spectrum antimicrobial activity with mean inhibitory concentrations (MICs) of 34 μM against Gram-negative Escherichia coli, 4.3 μM against Gram-positive Staphylococcus aureus and 4–9 μM against the yeast, Candida albicans. Both peptides exhibited little haemolytic activity (<6 %) at the MICs for S. aureus and C. albicans. Amphibian skin secretions thus continue to provide novel antimicrobial peptide structures that may prove to be lead compounds in the design of new classes of anti-infection therapeutics.     

Using chemical derivatization and mass spectrometric analysis to characterize the post-translationally modified Staphylococcus aureus surface protein G

The Staphylococcus aureus surface protein G (SasG) is an important mediator of biofilm formation in virulent S. aureus strains. A detailed analysis of its primary sequence has not been reported to date. SasG is highly abundant in the cell wall of the vancomycin-intermediate S. aureus strain HIP5827, and was purified and subjected to sequence analysis by MS. Data from MALDI-TOF and LC-MS/MS experiments confirmed the predicted N-terminal signal peptide cleavage site at residue A₅₁ and the C-terminal cell wall anchor site at residue T₁₀₈₆. The protein was also derivatized with N-succinimidyloxycarbonyl-methyl-tris(2,4,6-trimethoxyphenyl) phosphonium bromide (TMPP-Ac-OSu) to assess the presence of additional N-terminal sites of mature SasG. TMPP-derivatized SasG peptides featured m/z peaks with a 572 Da mass increase over the equivalent underivatized peptides. Multiple N-terminal peptides, all of which were observed in the 150 amino acid segment following the signal peptide cleavage at the residue A₅₁, were characterized from MS and MS/MS data, suggesting a series of successive N-terminal truncations of SasG. A strategy combining TMPP derivatization, multiple enzyme digestions to generate overlapping peptides and detailed MS analysis will be useful to determine and understand functional implications of PTMs in bacterial cell wall-anchored proteins, which are frequently involved in the modulation of virulence-associated bacterial surface properties.     

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.     

Non-ribosomal peptides produced by Planktothrix agardhii from Siemianówka Dam Reservoir SDR (northeast Poland)

Planktothtrix agardhii (Oscillatoriales) is a filamentous cyanobacterium, which frequently forms blooms in shallow, polymictic and eutrophicated waters. This species is also a rich source of unique linear and cyclic peptides. In the current study, the profile of the peptides in samples from the P. agardhii-dominated Siemianówka Dam Reservoir (SDR) (northeast Poland) was analyzed for four subsequent years (2009–2012). The LC–MS/MS analyses revealed the presence of 33 peptides. Twelve of the most abundant ones, including five microcystins, five anabaenopeptins, one aeruginosin and one planktocyclin, were present in all field samples collected during the study. The detection of different peptides in two P. agardhii isolates indicated that the SDR population was composed of several chemotypes, characterized by different peptide patterns. The total concentration of microcystins (MCs) positively correlated with the biomass of P. agardhii. Between subsequent years, the changes in the ratio of the total MCs concentration to the biomass of P. agardhii were noticed, but they were less than threefold. This is the first study on the production of different classes of non-ribosomal peptides by freshwater cyanobacteria in Poland.