Exploiting Charge State Distribution To Probe Intramolecular Interactions in Gas-Phase Phosphopeptides and Enhance Proteomics Analyses.

Charging of analytes is a prerequisite for performing mass spectrometry analysis. In proteomics, electrospray ionization is the dominant technique for this process. Although the observation of differences in the peptide charge state distribution (CSD) is well-known among experimentalists, its analytical value remains underexplored. To investigate the utility of this dimension, we analyzed several public data sets, comprising over 250,000 peptide CSD profiles from the human proteome. We found that the dimensions of the CSD demonstrate high reproducibility across multiple laboratories, mass analyzers, and extensive time intervals. The general observation was that the CSD enabled effective partitioning of the peptide property space, resulting in enhanced discrimination between sequence and constitutional peptide isomers. Next, by evaluating the CSD values of phosphorylated peptides, we were able to differentiate between phosphopeptides that indicate the formation of intramolecular structures in the gas phase and those that do not. The reproducibility of the CSD values (mean cosine similarity above 0.97 for most of the experiments) qualified CSD data suitable to train a deep-learning model capable of accurately predicting CSD values (mean cosine similarity - 0.98). When we applied the CSD dimension to MS1- and MS2-based proteomics experiments, we consistently observed around a 5% increase in protein and peptide identification rate. Even though the CSD dimension is not as effective a discriminator as the widely used retention time dimension, it still holds the potential for application in direct infusion proteomics.

Potential of Negative-Ion-Mode Proteomics: An MS1-Only Approach.

Current proteomics approaches rely almost exclusively on using the positive ionization mode, resulting in inefficient ionization of many acidic peptides. This study investigates protein identification efficiency in the negative ionization mode using the DirectMS1 method. DirectMS1 is an ultrafast data acquisition method based on accurate peptide mass measurements and predicted retention times. Our method achieves the highest rate of protein identification in the negative ion mode to date, identifying over 1000 proteins in a human cell line at a 1% false discovery rate. This is accomplished using a single-shot 10 min separation gradient, comparable to lengthy MS/MS-based analyses. Optimizing separation and experimental conditions was achieved by utilizing mobile buffers containing 2.5 mM imidazole and 3% isopropanol. The study emphasized the complementary nature of data obtained in positive and negative ion modes. Combining the results from all replicates in both polarities increased the number of identified proteins to 1774. Additionally, we analyzed the method's efficiency using different proteases for protein digestion. Among the four studied proteases (LysC, GluC, AspN, and trypsin), trypsin and LysC demonstrated the highest protein identification yield. This suggests that digestion procedures utilized in positive-mode proteomics can be effectively applied in the negative ion mode. Data are deposited to ProteomeXchange: PXD040583.

Ultra-Fast Mass Spectrometry in Plant Biochemistry: Response of Winter Wheat Proteomics to Pre-Sowing Treatment with Iron Compounds.

In recent years, ultrafast liquid chromatography/mass spectrometry methods have been extensively developed for the use in proteome profiling in biochemical studies. These methods are intended for express monitoring of cell response to biotic stimuli and elucidation of correlation of molecular changes with biological processes and phenotypical changes. New technologies, including the use of nanomaterials, are actively introduced to increase agricultural production. However, this requires complex approbation of new fertilizers and investigation of mechanisms underlying the biotic effects on the germination, growth, and development of plants. The aim of this work was to adapt the method of ultrafast chromatography/mass spectrometry for rapid quantitative profiling of molecular changes in 7-day-old wheat seedlings in response to pre-sowing seed treatment with iron compounds. The used method allows to analyze up to 200 samples per day; its practical value lies in the possibility of express proteomic diagnostics of the biotic action of new treatments, including those intended for agricultural needs. Changes in the regulation of photosynthesis, biosynthesis of chlorophyll and porphyrin- and tetrapyrrole-containing compounds, glycolysis (in shoot tissues), and polysaccharide metabolism (in root tissues) were shown after seed treatment with suspensions containing film-forming polymers (PEG 400, Na-CMC, Na2-EDTA), iron (II, III) nanoparticles, or iron (II) sulfate. Observations at the protein levels were consistent with the results of morphometry, superoxide dismutase activity assay, and microelement analysis of 3-day-old germinated seeds and shoots and roots of 7-day-old seedlings. A characteristic molecular signature involving proteins participating in the regulation of photosynthesis and glycolytic process was suggested as a potential marker of the biotic effects of seed treatment with iron compounds, which will be confirmed in further studies.

Proteomic analysis reveals stage-specific reprogramed metabolism for the primary breast cancer cell lines MGSO-3 and MACL-1.

Breast cancer is the most prevalent cancer in women worldwide. Its molecular subtypes are based on the presence/absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). MACL-1 and MGSO-3 are cell lines derived from primary tumor sites of patients diagnosed with luminal A subtype carcinoma (ER+/PR+/HER2-) and ductal carcinoma in situ (ER-/PR-/HER2+), respectively. However, these cell lines lost the expression of these markers over cell culturing, and both have triple-negative phenotypes (ER-/PR-/HER2-), which has the poorest prognosis. Here, we sought to study the proteome signature of MGSO-3 and MACL-1, comparing them with the epithelial cell line MCF-10A and the well-established metastatic-derived breast cancer cell line MDA-MB-231. Our results showed that proteins associated with the tricarboxylic acid cycle (TCA) and oxidative phosphorylation (OXPHOS) were upregulated in MGSO-3 and MACL-1 cells. These cell lines also showed upregulation of pro-apoptotic proteins when compared with MDA-MB-231. The molecular differences highlighted in this study may clarify the molecular basis behind cancer cells functioning and may reveal novel signatures across the breast cancer cell models.

Phosphoproteomic studies of alamandine signaling in CHO-MrgD and human pancreatic carcinoma cells: An antiproliferative effect is unveiled.

Alamandine is a heptapeptide from the renin-angiotensin system (RAS) with similar structure/function to angiotensin-(1-7) [ang-(1-7)], but they act via different receptors. It remains elusive whether alamandine is an antiproliferative agent like ang-(1-7). The goal of this study was to evaluate the potential antiproliferative activity of alamandine and the underlying cellular signaling. We evaluated alamandine effect in the tumoral cell lines Mia PaCa-2 and A549, and in the nontumoral cell lines HaCaT, CHO and CHO transfected with the alamandine receptor MrgD (CHO-MrgD). Alamandine was able to reduce the proliferation of the tumoral cell lines in a MrgD-dependent fashion. We did not observe any effect in the nontumoral cell lines tested. We also performed proteomics and phosphoproteomics to study the alamandine signaling in Mia PaCa-2 and CHO-MrgD. Data suggest that alamandine induces a shift from anaerobic to aerobic metabolism in the tumoral cells, induces a negative regulation of PI3K/AKT/mTOR pathway and activates the transcriptional factor FoxO1; events that could explain, at least partially, the observed antiproliferative effect of alamandine. This study provides for the first time a comprehensive investigation of the alamandine signaling in tumoral (Mia PaCa-2) and nontumoral (CHO-MrgD) cells, highlighting the antiproliferative activity of alamandine/MrgD and its possible antitumoral effect.

DirectMS1Quant: Ultrafast Quantitative Proteomics with MS/MS-Free Mass Spectrometry.

Recently, we presented the DirectMS1 method of ultrafast proteome-wide analysis based on minute-long LC gradients and MS1-only mass spectra acquisition. Currently, the method provides the depth of human cell proteome coverage of 2500 proteins at a 1% false discovery rate (FDR) when using 5 min LC gradients and 7.3 min runtime in total. While the standard MS/MS approaches provide 4000-5000 protein identifications within a couple of hours of instrumentation time, we advocate here that the higher number of identified proteins does not always translate into better quantitation quality of the proteome analysis. To further elaborate on this issue, we performed a one-on-one comparison of quantitation results obtained using DirectMS1 with three popular MS/MS-based quantitation methods: label-free (LFQ) and tandem mass tag quantitation (TMT), both based on data-dependent acquisition (DDA) and data-independent acquisition (DIA). For comparison, we performed a series of proteome-wide analyses of well-characterized (ground truth) and biologically relevant samples, including a mix of UPS1 proteins spiked at different concentrations into an Echerichia coli digest used as a background and a set of glioblastoma cell lines. MS1-only data was analyzed using a novel quantitation workflow called DirectMS1Quant developed in this work. The results obtained in this study demonstrated comparable quantitation efficiency of 5 min DirectMS1 with both TMT and DIA methods, yet the latter two utilized a 10-20-fold longer instrumentation time.

Assessing the effects of Leishmania (Leishmania) infantum and L. (L.) amazonensis infections in macrophages using a quantitative proteome approach.

Leishmania (Leishmania) infantum is the causative agent of visceral leishmaniasis, while L. (L.) amazonensis is associated with localized cutaneous and diffuse leishmaniasis, which can affect different organ tissues leading to visceral manifestations in some hosts. The wide range of clinical manifestations of leishmaniasis depends on host factors such as the immune response and on the species of Leishmania involved in the infection. Macrophages are the main infected cells in the vertebrate host, and proteins play a pivotal role in Leishmania-macrophage interactions. Here, we performed difference gel electrophoresis (DIGE) and shotgun quantitative mass spectrometry-based proteomics by means of tandem mass tags (TMT) isobaric peptide labeling followed by LC-MS/MS to investigate differentially abundant proteins in BALB/c macrophages infected with these Leishmania species. Using DIGE for comparison, we found that 2.34% spots (29/1240) were differentially intense in infected murine macrophages. Leishmania (L.) infantum and L. (L.) amazonensis induced similar changes in the host cells; 11 spots were selected as differentially intense in each species and seven in the uninfected control group. Using TMT, 5939 Mus musculus proteins were identified, of which 410 and 433 were differentially abundant in L. (L.) infantum and L. (L.) amazonensis infections, respectively, while 170 proteins were commonly regulated by both the species. Gene ontology enrichment analysis indicated that Leishmania infection interfered with apoptotic mechanisms in macrophages and induced epigenetic changes that may affect gene transcription. Moreover, downregulation of proteins such as PYCARD and MyD88 seemed to influence the inflammatory process in L. (L.) amazonensis infection, whereas upregulation of TAP1 and ERAP1 was involved in the adaptive immune response in L. (L.) infantum infection. Differentially abundant proteins identified in this study may contribute to a better understanding of the factors that determine the course of infection. Our results suggest several possible targets for vaccines, drugs, and diagnosis of leishmaniasis.

Boosting MS1-only Proteomics with Machine Learning Allows 2000 Protein Identifications in Single-Shot Human Proteome Analysis Using 5 min HPLC Gradient.

Proteome-wide analyses rely on tandem mass spectrometry and the extensive separation of proteolytic mixtures. This imposes considerable instrumental time consumption, which is one of the main obstacles in the broader acceptance of proteomics in biomedical and clinical research. Recently, we presented a fast proteomic method termed DirectMS1 based on ultrashort LC gradients as well as MS1-only mass spectra acquisition and data processing. The method allows significant reduction of the proteome-wide analysis time to a few minutes at the depth of quantitative proteome coverage of 1000 proteins at 1% false discovery rate (FDR). In this work, to further increase the capabilities of the DirectMS1 method, we explored the opportunities presented by the recent progress in the machine-learning area and applied the LightGBM decision tree boosting algorithm to the scoring of peptide feature matches when processing MS1 spectra. Furthermore, we integrated the peptide feature identification algorithm of DirectMS1 with the recently introduced peptide retention time prediction utility, DeepLC. Additional approaches to improve the performance of the DirectMS1 method are discussed and demonstrated, such as using FAIMS for gas-phase ion separation. As a result of all improvements to DirectMS1, we succeeded in identifying more than 2000 proteins at 1% FDR from the HeLa cell line in a 5 min gradient LC-FAIMS/MS1 analysis. The data sets generated and analyzed during the current study have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD023977.

Biosaur: An open-source Python software for liquid chromatography-mass spectrometry peptide feature detection with ion mobility support.

RATIONALE: One of the important steps in initial data processing of peptide mass spectra is the detection of peptide features in full-range mass spectra. Ion mobility offers advantages over previous methods performing this detection by providing an additional structure-specific separation dimension. However, there is a lack of open-source software that utilizes these advantages and detects peptide features in mass spectra acquired along with ion mobility data using new instruments such as timsTOF and/or FAIMS-Orbitrap. METHODS: Recently, a utility called Dinosaur was presented, which provides an efficient way for feature detection in peptide ion mass spectra. In this work we extended its functionality by developing Biosaur software to fully employ the additional information provided by ion mobility data. Biosaur was developed using the Python 3.8 programming language. RESULTS: Biosaur supports the processing of data acquired using mass spectrometers with ion mobility capabilities, specifically timsTOF and FAIMS. In addition, it processes mass spectra obtained in negative ion mode and reports cosine correlation table for peptide features which is useful for differentiation between in-source fragments and semi-tryptic peptides. CONCLUSIONS: Biosaur is a utility for detecting peptide features in liquid chromatography-mass spectra with ion mobility and negative ion supports. The software is distributed with an open-source APACHE 2.0 license and is freely available on Github: https://github.com/abdrakhimov1/Biosaur.

SARS-CoV-2 infection in pregnancy in Denmark-characteristics and outcomes after confirmed infection in pregnancy: A nationwide, prospective, population-based cohort study.

INTRODUCTION: Assessing the risk factors for and consequences of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during pregnancy is essential to guide clinical care. Previous studies on SARS-CoV-2 infection in pregnancy have been among hospitalized patients, which may have exaggerated risk estimates of severe outcomes because all cases of SARS-CoV-2 infection in the pregnant population were not included. The objectives of this study were to identify risk factors for and outcomes after SARS-CoV-2 infection in pregnancy independent of severity of infection in a universally tested population, and to identify risk factors for and outcomes after severe infection requiring hospital admission. MATERIAL AND METHODS: This was a prospective population-based cohort study in Denmark using data from the Danish National Patient Register and Danish Microbiology Database and prospectively registered data from medical records. We included all pregnancies between March 1 and October 31, 2020 and compared women with a positive SARS-CoV-2 test during pregnancy to non-infected pregnant women. Cases of SARS-CoV-2 infection in pregnancy were both identified prospectively and through register linkage to ensure that all cases were identified and that cases were pregnant during infection. Main outcome measures were pregnancy, delivery, maternal, and neonatal outcomes. Severe infection was defined as hospital admission due to coronavirus disease 2019 (COVID-19) symptoms. RESULTS: Among 82 682 pregnancies, 418 women had SARS-CoV-2 infection during pregnancy, corresponding to an incidence of 5.1 per 1000 pregnancies, 23 (5.5%) of which required hospital admission due to COVID-19. Risk factors for infection were asthma (odds ratio [OR] 2.19, 95% CI 1.41-3.41) and being foreign born (OR 2.12, 95% CI 1.70-2.64). Risk factors for hospital admission due to COVID-19 included obesity (OR 2.74, 95% CI 1.00-7.51), smoking (OR 4.69, 95% CI 1.58-13.90), infection after gestational age (GA) 22 weeks (GA 22-27 weeks: OR 3.77, 95% CI 1.16-12.29; GA 28-36 weeks: OR 4.76, 95% CI 1.60-14.12), and having asthma (OR 4.53, 95% CI 1.39-14.79). We found no difference in any obstetrical or neonatal outcomes. CONCLUSIONS: Only 1 in 20 women with SARS-CoV-2 infection during pregnancy required admission to hospital due to COVID-19. Risk factors for admission comprised obesity, smoking, asthma, and infection after GA 22 weeks. Severe adverse outcomes of SARS-CoV-2 infection in pregnancy were rare.

HUMOS: How to Understand My Orbitrap Spectrum?-An Interactive Web-Based Tool to Teach the Basics of Mass-Spectrometry-Based Proteomics.

The Orbitrap mass analyzer can provide high mass accuracy and throughput, which has significantly improved proteome research and made this type of instrumentation one of the most frequently applied in proteomics. The efficient use of Orbitrap mass spectrometers requires training. Students in the field of proteomics can benefit from a deeper understanding of the Orbitrap technology to comprehend mass spectral interpretation, troubleshooting, and judgment of experimental settings. Unfortunately, the cost of high-end mass spectrometers limits the implementation of this type of equipment in educational laboratories. Guided by these concerns, we developed an eLearning web application called HUMOS aimed to help teach Orbitrap mass spectrometry. Although a typical proteomics experiment includes the use of several different technologies, such as liquid chromatography, mass spectrometry, and bioinformatics, the learning objectives of HUMOS are focused on mass spectrometry. HUMOS models a mass spectrum of a peptide mixture, allowing us to investigate the influence of mass spectral acquisition parameters. By changing the parameters and observing the differences, students can learn more about the mass spectral resolution, duty cycle, throughput of the analysis, ion accumulation, and spectral dynamic range and get familiar with advanced spectral acquisition methods, such as BoxCar. HUMOS is an open-source software published under the Apache license; the live installation is available at http://humos.bmb.sdu.dk.

Moving Pieces in a Cellular Puzzle: A Cryptic Peptide from the Scorpion Toxin Ts14 Activates AKT and ERK Signaling and Decreases Cardiac Myocyte Contractility via Dephosphorylation of Phospholamban.

Cryptic peptides (cryptides) are biologically active peptides formed after proteolysis of native precursors present in animal venoms, for example. Proteolysis is an overlooked post-translational modification that increases venom complexity. The tripeptide KPP (Lys-Pro-Pro) is a peptide encrypted in the C-terminus of Ts14-a 25-mer peptide from the venom of the Tityus serrulatus scorpion that has a positive impact on the cardiovascular system, inducing vasodilation and reducing arterial blood pressure of hypertensive rats among other beneficial effects. A previous study reported that KPP and its native peptide Ts14 act via activation of the bradykinin receptor B2 (B2R). However, the cellular events underlying the activation of B2R by KPP are unknown. To study the cell signaling triggered by the Ts14 cryptide KPP, we incubated cardiac myocytes isolated from C57BL/6 mice with KPP (10-7 mol·L-1) for 0, 5, or 30 min and explored the proteome and phosphoproteome. Our results showed that KPP regulated cardiomyocyte proteins associated with, but not limited to, apoptosis, muscle contraction, protein turnover, and the respiratory chain. We also reported that KPP led to AKT phosphorylation, activating AKT and its downstream target nitric oxide synthase. We also observed that KPP led to dephosphorylation of phospholamban (PLN) at its activation sites (S16 and T17), leading to reduced contractility of treated cardiomyocytes. Some cellular targets reported here for KPP (e.g., AKT, PLN, and ERK) have already been reported to protect the cardiac tissue from hypoxia-induced injury. Hence, this study suggests potential beneficial effects of this scorpion cryptide that needs to be further investigated, for example, as a drug lead for cardiac infarction.

DirectMS1: MS/MS-Free Identification of 1000 Proteins of Cellular Proteomes in 5 Minutes.

Proteome characterization relies heavily on tandem mass spectrometry (MS/MS) and is thus associated with instrumentation complexity, lengthy analysis time, and limited duty cycle. It was always tempting to implement approaches that do not require MS/MS, yet they were constantly failing to achieve a meaningful depth of quantitative proteome coverage within short experimental times, which is particularly important for clinical or biomarker-discovery applications. Here, we report on the first successful attempt to develop a truly MS/MS-free method, DirectMS1, for bottom-up proteomics. The method is compared with the standard MS/MS-based data-dependent acquisition approach for proteome-wide analysis using 5 min LC gradients. Specifically, we demonstrate identification of 1 000 protein groups for a standard HeLa cell line digest. The amount of loaded sample was varied in a range from 1 to 500 ng, and the method demonstrated 10-fold higher sensitivity. Combined with the recently introduced Diffacto approach for relative protein quantification, DirectMS1 outperforms most popular MS/MS-based label-free quantitation approaches because of significantly higher protein sequence coverage.

Rpn4 and proteasome-mediated yeast resistance to ethanol includes regulation of autophagy.

Distilled spirits production using Saccharomyces cerevisiae requires understanding of the mechanisms of yeast cell response to alcohol stress. Reportedly, specific mutations in genes of the ubiquitin-proteasome system, e.g., RPN4, may result in strains exhibiting hyper-resistance to different alcohols. To study the Rpn4-dependent yeast response to short-term ethanol exposure, we performed a comparative analysis of the wild-type (WT) strain, strain with RPN4 gene deletion (rpn4-Δ), and a mutant strain with decreased proteasome activity and consequent Rpn4 accumulation due to PRE1 deregulation (YPL). The stress resistance tests demonstrated an increased sensitivity of mutant strains to ethanol compared with WT. Comparative proteomics analysis revealed significant differences in molecular responses to ethanol between these strains. GO analysis of proteins upregulated in WT showed enrichments represented by oxidative and heat responses, protein folding/unfolding, and protein degradation. Enrichment of at least one of these responses was not observed in the mutant strains. Moreover, activity of autophagy was not increased in the RPN4 deletion strain upon ethanol stress which agrees with changes in mRNA levels of ATG7 and PRB1 genes of the autophagy system. Activity of the autophagic system was clearly induced and accompanied with PRB1 overexpression in the YPL strain upon ethanol stress. We demonstrated that Rpn4 stabilization contributes to the PRB1 upregulation. CRISPR-Cas9-mediated repression of PACE-core Rpn4 binding sites in the PRB1 promoter inhibits PRB1 induction in the YPL strain upon ethanol treatment and results in YPL hypersensitivity to ethanol. Our data suggest that Rpn4 affects the autophagic system activity upon ethanol stress through the PRB1 regulation. These findings can be a basis for creating genetically modified yeast strains resistant to high levels of alcohol, being further used for fermentation in ethanol production.

Elucidating the cellular response of silver nanoparticles as a potential combinatorial agent for cisplatin chemotherapy.

BACKGROUND: Combination chemotherapy uses drugs that target different cancer hallmarks, resulting in synergistic or additive toxicity. This strategy enhances therapeutic efficacy as well as minimizes drug resistance and side effects. In this study, we investigated whether silver nanoparticles act as a combinatorial partner to cisplatin. In so doing, we compared post-exposure biological endpoints, intracellular drug accumulation, and changes in the proteome profile of tumoral and normal cell lines. RESULTS: Combinatorial exposure corresponded to cytotoxicity and oxidative stress in both cell lines, yet was substantially more effective against tumoral cells. Proteome analysis revealed that proteins related to energy metabolism pathways were upregulated in both cell lines, suggesting that combinatorial exposure corresponded to energetic modulation. However, proteins and upstream regulators involved in the cell cycle were downregulated, indicating reduced cell proliferation. The response to oxidative stress was markedly different in both cell lines; downregulation of antioxidant proteins in tumoral cells, yet upregulation of the antioxidant defense system in normal cells. These outcomes may have avoided higher cell death rates in normal cells. CONCLUSIONS: Taken together, our results indicate that combining silver nanoparticles with cisplatin increases the biological activity of the latter, and the combination warrants further exploration for future therapies.

Assessment of protein extraction and digestion efficiency of well-established shotgun protocols for heart proteomics.

Ischemic heart disease is the leading cause of deaths worldwide. Thus, understanding the molecular mechanisms underlying disease progression is needed. Due to heart importance and lack of studies evaluating different sample preparation methods for heart proteomics, we compared three well-established protocols in shotgun proteomics using dimethyl label quantitation to allow relative quantitation. The tested methods for the analysis of left ventricle (LV) tissue were: i) in-solution digestion (ISD); ii) on-pellet digestion (OPD); and iii) on-filter digestion (OFD). Protein extraction was done using SDS-containing buffer for OPD and OFD while this step was under urea-containing buffer for ISD. We used an optimized one-step reaction for reduction of disulfide bonds and alkylation of thiol groups in ISD and OPD. Using the same amount of tissue, we observed that OFD and ISD extracted significantly higher amount of protein than OPD. ISD outperformed OFD and OPD in the number of proteins identified. We did not observe significant bias related to physicochemical features of the identified proteins when comparing the three protocols. ISD was more efficient to identify low abundant proteins and yielded more proteins per protocol duration. Thus, we concluded that the optimized ISD suited better for heart proteomics than OFD and OPD.

Uranyl Photocleavage of Phosphopeptides Yields Truncated C-Terminally Amidated Peptide Products.

The uranyl ion (UO22+ ) binds phosphopeptides with high affinity, and when irradiated with UV-light, it can cleave the peptide backbone. In this study, high-accuracy tandem mass spectrometry and enzymatic assays were used to characterise the photocleavage products resulting from the uranyl photocleavage reaction of a tetraphosphorylated ß-casein model peptide. We show that the primary photocleavage products of the uranyl-catalysed reaction are C-terminally amidated. This could be of great interest to the pharmaceutical industry, as efficient peptide amidation reactions are one of the top challenges in green pharmaceutical chemistry.

Peptide de novo sequencing of mixture tandem mass spectra.

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co-isolation and thus prone to false identifications. The deconvolution approach matched complementary b-, y-ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co-isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20-35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications.

High-performance hybrid Orbitrap mass spectrometers for quantitative proteome analysis: Observations and implications.

We present basic workups and quantitative comparisons for two current generation Orbitrap mass spectrometers, the Q Exactive Plus and Orbitrap Fusion Tribrid, which are widely considered two of the highest performing instruments on the market. We assessed the performance of two quantitative methods on both instruments, namely label-free quantitation and stable isotope labeling using isobaric tags, for studying the heat shock response in Escherichia coli. We investigated the recently reported MS3 method on the Fusion instrument and the potential of MS3-based reporter ion isolation Synchronous Precursor Selection (SPS) and its impact on quantitative accuracy. We confirm that the label-free approach offers a more linear response with a wider dynamic range than MS/MS-based isobaric tag quantitation and that the MS3/SPS approach alleviates but does not eliminate dynamic range compression. We observed, however, that the choice of quantitative approach had little impact on the ability to statistically evaluate the E. coli heat shock response. We conclude that in the experimental conditions tested, MS/MS-based reporter ion quantitation provides reliable biological insight despite the issue of compressed dynamic range, an observation that significantly impacts the choice of instrument.

Charge inversion of phospholipids by dimetal complexes for positive ion-mode electrospray ionization mass spectrometry analysis.

Phospholipids are vital constituents of living cells, as they are involved in signaling and membrane formation. Mass spectrometry analysis of many phospholipids is preferentially performed in the negative ion-mode because of their acidic nature. Here we have studied the potential of a digallium and dizinc complex to charge-invert a range of different types of phospholipids and measured their ion yield and fragmentation behavior in positive ion-mode tandem mass spectrometry. The dimetal complexes bind specifically the phosphate groups of phospholipids and add an excess of up to three positive charges per phosphate group. Three different phosphoinositide phosphates (mono-, di-, and triphosphorylated inositides), a phosphatidic acid, a phosphatidylcholine, a phosphatidylethanolamine, and a phosphatidylglycerol were investigated. The intensities obtained in positive ion-mode of phosphoinositide phosphates and phosphatidic acid bound to {LGa2}(5+) were between 2.5- and 116-fold higher than that of the unmodified lipids in the negative ion-mode. Native phosphoinositide ions yielded upon CID in the negative ion-mode predominantly product ions due to losses of H3PO4, PO3(-) and H2O. In comparison, CID spectra of {LGa2}(5+)-bound phosphoinositides generally resulted in fragment ions corresponding to loss of the full diglyceride chain as well as the remaining headgroup bound to {LGa2}(5+) as the most abundant peaks. A number of signature fragment ions of moderate abundance were observed that allowed for distinction between the three regioisomers of 1,2-di(9Z-octadecenoyl)-sn-glycero-3-[phosphoinositol-x,y-bisphosphate] (PI(3,4)P2, PI(3,5)P2, PI(4,5)P2).