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.

pH-Dependence Cytotoxicity Evaluation of Artepillin C against Tumor Cells.

Brazilian green propolis is a well-known product that is consumed globally. Its major component, Artepillin C, showed potential as an antitumor product. This study explored the impact of Artepillin C on fibroblast and glioblastoma cell lines, used as healthy and very aggressive tumor cell lines, respectively. The focus of the study was to evaluate the pH-dependence of Artepillin C cytotoxicity, since tumor cells are known to have a more acidic extracellular microenvironment compared to healthy cells, and Artepillin C was shown to become more lipophilic at lower pH values. Investigations into the pH-dependency of Artepillin C (6.0-7.4), through viability assays and live cell imaging, revealed compelling insights. At pH 6.0, MTT assays showed the pronounced cytotoxic effects of Artepillin C, yielding a notable reduction in cell viability to less than 12% among glioblastoma cells following a 24 h exposure to 100 µM of Artepillin C. Concurrently, LDH assays indicated significant membrane damage, affecting approximately 50% of the total cells under the same conditions. Our Laurdan GP analysis suggests that Artepillin C induces autophagy, and notably, provokes a lipid membrane packing effect, contributing to cell death. These combined results affirm the selective cytotoxicity of Artepillin C within the acidic tumor microenvironment, emphasizing its potential as an effective antitumor agent. Furthermore, our findings suggest that Artepillin C holds promise for potential applications in the realm of anticancer therapies given its pH-dependence cytotoxicity.

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.

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.

Yeast Ribonucleotide Reductase Is a Direct Target of the Proteasome and Provides Hyper Resistance to the Carcinogen 4-NQO.

Various external and internal factors damaging DNA constantly disrupt the stability of the genome. Cells use numerous dedicated DNA repair systems to detect damage and restore genomic integrity in a timely manner. Ribonucleotide reductase (RNR) is a key enzyme providing dNTPs for DNA repair. Molecular mechanisms of indirect regulation of yeast RNR activity are well understood, whereas little is known about its direct regulation. The study was aimed at elucidation of the proteasome-dependent mechanism of direct regulation of RNR subunits in Saccharomyces cerevisiae. Proteome analysis followed by Western blot, RT-PCR, and yeast plating analysis showed that upregulation of RNR by proteasome deregulation is associated with yeast hyper resistance to 4-nitroquinoline-1-oxide (4-NQO), a UV-mimetic DNA-damaging drug used in animal models to study oncogenesis. Inhibition of RNR or deletion of RNR regulatory proteins reverses the phenotype of yeast hyper resistance to 4-NQO. We have shown for the first time that the yeast Rnr1 subunit is a substrate of the proteasome, which suggests a common mechanism of RNR regulation in yeast and mammals.

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.

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.

GIP Affects Hepatic Fat and Brown Adipose Tissue Thermogenesis but Not White Adipose Tissue Transcriptome in Type 1 Diabetes.

CONTEXT: Glucose-dependent insulinotropic polypeptide (GIP) has been proposed to exert insulin-independent effects on lipid and bone metabolism. OBJECTIVE: We investigated the effects of a 6-day subcutaneous GIP infusion on circulating lipids, white adipose tissue (WAT), brown adipose tissue (BAT), hepatic fat content, inflammatory markers, respiratory exchange ratio (RER), and bone homeostasis in patients with type 1 diabetes. METHODS: In a randomized, placebo-controlled, double-blind, crossover study, 20 men with type 1 diabetes underwent a 6-day continuous subcutaneous infusion with GIP (6 pmol/kg/min) and placebo (saline), with an interposed 7-day washout period. RESULTS: During GIP infusion, participants (26 ± 8 years [mean ± SD]; BMI 23.8 ± 1.8 kg/m2; glycated hemoglobin A1c 51 ± 10 mmol/mol [6.8 ± 3.1%]) experienced transiently increased circulating concentrations of nonesterified fatty acid (NEFA) (P = 0.0005), decreased RER (P = 0.009), indication of increased fatty acid ß-oxidation, and decreased levels of the bone resorption marker C-terminal telopeptide (P = 0.000072) compared with placebo. After 6 days of GIP infusion, hepatic fat content was increased by 12.6% (P = 0.007) and supraclavicular skin temperature, a surrogate indicator of BAT activity, was increased by 0.29 °C (P < 0.000001) compared with placebo infusion. WAT transcriptomic profile as well as circulating lipid species, proteome, markers of inflammation, and bone homeostasis were unaffected. CONCLUSION: Six days of subcutaneous GIP infusion in men with type 1 diabetes transiently decreased bone resorption and increased NEFA and ß-oxidation. Further, hepatic fat content, and supraclavicular skin temperature were increased without affecting WAT transcriptomics, the circulating proteome, lipids, or inflammatory markers.

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.

Use of quasi-SMILES to build models based on quantitative results from experiments with nanomaterials.

Quasi-SMILES deviate from traditional SMILES (simplified molecular input-line entry system) by the extension of additional symbols that encode for conditions of an experiment. Descriptors calculated with SMILES are useful for the development of quantitative structure-property/activity relationships (QSPRs/QSARs), while descriptors calculated with quasi-SMILES can be useful for the development of quantitative models of experimental results obtained under different conditions. Here, this approach has been applied for the development of generalized models using aquatic nanotoxicity data (i.e., related to fish and daphnia). The statistical quality of the above models (pLC50) is quite good with a determination coefficient for the external validation set ranging from 0.62 to 0.71 and RMSE ranging from 0.58 to 0.60. The principle of the approach includes splitting the experimental data into three random distributions defining training, calibration, and validation sets.

Proteome-wide analysis reveals molecular pathways affected by AgNP in a ROS-dependent manner.

The use of mass spectrometry-based proteomics has been increasingly applied in nanomaterials risk assessments as it provides a proteome-wide overview of the molecular disturbances induced by its exposure. Here, we used this technique to gain detailed molecular insights into the role of ROS as an effector of AgNP toxicity, by incubating Bend3 cells with AgNP in the absence or presence of an antioxidant N-acetyl L-cystein (NAC). ROS generation is a key player in AgNP-induced toxicity, as cellular homeostasis was kept in the presence of NAC. By integrating MS/MS data with bioinformatics tools, in the absence of NAC, we were able to pinpoint precisely which biological pathways were affected by AgNP. Cells respond to AgNP-induced ROS generation by increasing their antioxidant pool, via NRF2 pathway activation. Additionally, cell proliferation-related pathways were strongly inhibited in a ROS-dependent manner. These findings reveal important aspects of the AgNP mechanism of action at the protein level.

Multi-Omics Analysis of Glioblastoma Cells' Sensitivity to Oncolytic Viruses.

Oncolytic viruses have gained momentum in the last decades as a promising tool for cancer treatment. Despite the progress, only a fraction of patients show a positive response to viral therapy. One of the key variable factors contributing to therapy outcomes is interferon-dependent antiviral mechanisms in tumor cells. Here, we evaluated this factor using patient-derived glioblastoma multiforme (GBM) cultures. Cell response to the type I interferons' (IFNs) stimulation was characterized at mRNA and protein levels. Omics analysis revealed that GBM cells overexpress interferon-stimulated genes (ISGs) and upregulate their proteins, similar to the normal cells. A conserved molecular pattern unambiguously differentiates between the preserved and defective responses. Comparing ISGs' portraits with titration-based measurements of cell sensitivity to a panel of viruses, the "strength" of IFN-induced resistance acquired by GBM cells was ranked. The study demonstrates that suppressing a single ISG and encoding an essential antiviral protein, does not necessarily increase sensitivity to viruses. Conversely, silencing IFIT3 and PLSCR1 genes in tumor cells can negatively affect the internalization of vesicular stomatitis and Newcastle disease viruses. We present evidence of a complex relationship between the interferon response genes and other factors affecting the sensitivity of tumor cells to viruses.

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.

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.

Biological and Molecular Effects of Trypanosoma cruzi Residence in a LAMP-Deficient Intracellular Environment.

Trypanosoma cruzi invades non-professional phagocytic cells by subverting their membrane repair process, which is dependent on membrane injury and cell signaling, intracellular calcium increase, and lysosome recruitment. Cells lacking lysosome-associated membrane proteins 1 and 2 (LAMP1 and LAMP2) are less permissive to parasite invasion but more prone to parasite intracellular multiplication. Several passages through a different intracellular environment can significantly change T. cruzi's gene expression profile. Here, we evaluated whether one single passage through LAMP-deficient (KO) or wild-type (WT) fibroblasts, thus different intracellular environments, could influence T. cruzi Y strain trypomastigotes' ability to invade L6 myoblasts and WT fibroblasts host cells. Parasites released from LAMP2 KO cells (TcY-L2-/-) showed higher invasion, calcium signaling, and membrane injury rates, for the assays in L6 myoblasts, when compared to those released from WT (TcY-WT) or LAMP1/2 KO cells (TcY-L1/2-/-). On the other hand, TcY-L1/2-/- showed higher invasion, calcium signaling, and cell membrane injury rates, for the assays in WT fibroblasts, compared to TcY-WT and TcY-L1/2-/-. Albeit TcY-WT presented an intermediary invasion and calcium signaling rates, compared to the others, in WT fibroblasts, they induced lower levels of injury, which reinforces that signals mediated by surface membrane protein interactions also have a significant contribution to trigger host cell calcium signals. These results clearly show that parasites released from WT or LAMP KO cells are distinct from each other. Additionally, these parasites' ability to invade the cell may be distinct depending on which cell type they interact with. Since these alterations most likely would reflect differences among parasite surface molecules, we also evaluated their proteome. We identified few protein complexes, membrane, and secreted proteins regulated in our dataset. Among those are some members of MASP, mucins, trans-sialidases, and gp63 proteins family, which are known to play an important role during parasite infection and could correlate to TcY-WT, TcY-L1/2-/-, and TcY-L2-/- biological behavior.

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.

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.

PhosphoShield: Improving Trypsin Digestion of Phosphoproteins by Shielding the Negatively Charged Phosphate Moiety.

Protein phosphorylation is a post-translational modification that is essential to cellular signaling, cellular function, and associated disease progression. Bottom-up proteomics based on enzymatic digestion is the most widely used approach for identifying and quantifying phosphoproteins in complex biological samples. Researchers have largely optimized the experimental conditions for trypsin digestion, and it is now a routine procedure. However, trypsin digestion is impaired by the presence of phosphorylated residues in the protein sequence. This impairment arises from the fact that there are commonly salt bridges between a negatively charged phosphate group and the side chain of protonated arginine or lysine. On average, 55% of all phosphopeptides have their phosphosites located less than three amino acid residues from a cleavage site. Salt bridges reduce the cleavage accessibility for trypsin by masking the basic site chain groups of arginine and lysine. Thus, there are frequent missed cleavages in the vicinity of phosphorylation sites, thereby lessening both the depth of proteome coverage and the quantification accuracy of phosphoproteomics. In this work, we propose a method termed PhosphoShield to mitigate salt bridge formation by adding a digallium complex that exhibits a high binding affinity to the phosphate group. We tested our method using quantitative mass spectrometry analysis of the phosphoproteome of human liver cancer cells (HepG2). PhosphoShield enhances the cleavage frequency of at least 17% of tryptic phosphopeptides having cleavage sites close to the phosphate group.