Proteomics reveals that the antifungal activity of fenbendazole against Cryptococcus neoformans requires protein kinases

Cryptococcus neoformans is responsible for over 100 000 deaths annually, and the treatment of this fungal disease is expensive and not consistently effective. Unveiling new therapeutic avenues is crucial. Previous studies have suggested that the anthelmintic drug fenbendazole is an affordable and nontoxic candidate to combat cryptococcosis. However, its mechanism of anticryptococcal activity has been only superficially investigated. In this study, we examined the global cellular response of C. neoformans to fenbendazole using a proteomic approach (data are available via ProteomeXchange with identifier PXD047041). Fenbendazole treatment mostly impacted the abundance of proteins related to metabolic pathways, RNA processing, and intracellular traffic. Protein kinases, in particular, were significantly affected by fenbendazole treatment. Experimental validation of the proteomics data using a collection of C. neoformans mutants led to the identification of critical roles of five protein kinases in fenbendazole's antifungal activity. In fact, mutants lacking the expression of genes encoding Chk1, Tco2, Tco3, Bub1, and Sch9 kinases demonstrated greater resistance to fenbendazole compared to wild-type cells. In combination with the standard antifungal drug amphotericin B, fenbendazole reduced the cryptococcal burden in mice. These findings not only contribute to the elucidation of fenbendazole's mode of action but also support its use in combination therapy with amphotericin B. In conclusion, our data suggest that fenbendazole holds promise for further development as an anticryptococcal agent.

Corrected and republished from: "Extracellular Vesicle Formation in Cryptococcus deuterogattii Impacts Fungal Virulence"

Small molecules are components of fungal extracellular vesicles (EVs), but their biological roles are only superficially known. NOP16 is a eukaryotic gene that is required for the activity of benzimidazoles against Cryptococcus deuterogattii. In this study, during the phenotypic characterization of C. deuterogattii mutants expected to lack NOP16 expression, we observed a reduced EV production. Whole-genome sequencing, RNA-Seq, and cellular proteomics revealed that, contrary to our initial findings, these mutants expressed Nop16 but exhibited altered expression of 14 genes potentially involved in sugar transport. Based on this observation, we designated these mutant strains as Past1 and Past2, representing potentially altered sugar transport. Analysis of the small molecule composition of EVs produced by wild-type cells and the Past1 and Past2 mutant strains revealed not only a reduced number of EVs but also an altered small molecule composition. In a Galleria mellonella model of infection, the Past1 and Past2 mutant strains were hypovirulent. The hypovirulent phenotype was reverted when EVs produced by wild-type cells, but not mutant EVs, were co-injected with the mutant cells in G. mellonella. These results connect EV biogenesis, cargo, and cryptococcal virulence.

Proteomic Analysis of a Rat Streptozotocin Model Shows Dysregulated Biological Pathways Implicated in Alzheimer's Disease

Alzheimer's Disease (AD) is an age-related neurodegenerative disorder characterized by progressive memory loss and cognitive impairment, affecting 35 million individuals worldwide. Intracerebroventricular (ICV) injection of low to moderate doses of streptozotocin (STZ) in adult male Wistar rats can reproduce classical physiopathological hallmarks of AD. This biological model is known as ICV-STZ. Most studies are focused on the description of behavioral and morphological aspects of the ICV-STZ model. However, knowledge regarding the molecular aspects of the ICV-STZ model is still incipient. Therefore, this work is a first attempt to provide a wide proteome description of the ICV-STZ model based on mass spectrometry (MS). To achieve that, samples from the pre-frontal cortex (PFC) and hippocampus (HPC) of the ICV-STZ model and control (wild-type) were used. Differential protein abundance, pathway, and network analysis were performed based on the protein identification and quantification of the samples. Our analysis revealed dysregulated biological pathways implicated in the early stages of late-onset Alzheimer's disease (LOAD), based on differentially abundant proteins (DAPs). Some of these DAPs had their mRNA expression further investigated through qRT-PCR. Our results shed light on the AD onset and demonstrate the ICV-STZ as a valid model for LOAD proteome description.

Proteomics reveals differentially regulated pathways when comparing grade 2 and 4 astrocytomas

Astrocytic tumors are known for their high progression capacity and high mortality rates; in this regard, proteins correlated to prognosis can aid medical conduct. Although several genetic changes related to progression from grade 2 to grade 4 astrocytoma are already known, mRNA copies do not necessarily correlate with protein abundance and therefore could shadow further comprehension about this tumor's biology. This motivates us to seek for complementary strategies to study tumor progression at the protein level. Here we compare the proteomic profile of biopsies from patients with grade 2 (diffuse, n = 6) versus grade 4 astrocytomas (glioblastomas, n = 10) using shotgun proteomics. Data analysis performed with PatternLab for proteomics identified 5,206 and 6,004 proteins in the 2- and 4-grade groups, respectively. Our results revealed seventy-four differentially abundant proteins (p < 0.01); we then shortlist those related to greater malignancy. We also describe molecular pathways distinctly activated in the two groups, such as differences in the organization of the extracellular matrix, decisive both in tumor invasiveness and in signaling for cell division, which, together with marked contrasts in energy metabolism, are determining factors in the speed of growth and dissemination of these neoplasms. The degradation pathways of GABA, enriched in the grade 2 group, is consistent with a favorable prognosis. Other functions such as platelet degranulation, apoptosis, and activation of the MAPK pathway were correlated to grade 4 tumors and, consequently, unfavorable prognoses. Our results provide an important survey of molecular pathways involved in glioma pathogenesis for these histopathological groups.

PatternLab V Handles Multiplex Spectra in Shotgun Proteomic Searches and Increases Identification

Complex protein mixtures typically generate many tandem mass spectra produced by different peptides coisolated in the gas phase. Widely adopted proteomic data analysis environments usually fail to identify most of these spectra, succeeding at best in identifying only one of the multiple cofragmenting peptides. We present PatternLab V (PLV), an updated version of PatternLab that integrates the YADA 3 deconvolution algorithm to handle such cases efficiently. In general, we expect an increase of 10% in spectral identifications when dealing with complex proteomic samples. PLV is freely available at http://patternlabforproteomics.org.

Increasing confidence in proteomic spectral deconvolution through mass defect

MOTIVATION

Confident deconvolution of proteomic spectra is critical for several applications such as de novo sequencing, cross-linking mass spectrometry and handling chimeric mass spectra.

RESULTS

In general, all deconvolution algorithms may eventually report mass peaks that are not compatible with the chemical formula of any peptide. We show how to remove these artifacts by considering their mass defects. We introduce Y.A.D.A. 3.0, a fast deconvolution algorithm that can remove peaks with unacceptable mass defects. Our approach is effective for polypeptides with less than 10 kDa, and its essence can be easily incorporated into any deconvolution algorithm.

AVAILABILITY AND IMPLEMENTATION

Y.A.D.A. 3.0 is freely available for academic use at http://patternlabforproteomics.org/yada3.

SUPPLEMENTARY INFORMATION

Supplementary information is available at Bioinformatics online.

Molecular Architecture of the Antiophidic Protein DM64 and its Binding Specificity to Myotoxin II From Bothrops asper Venom

DM64 is a toxin-neutralizing serum glycoprotein isolated from Didelphis aurita, an ophiophagous marsupial naturally resistant to snake envenomation. This 64 kDa antitoxin targets myotoxic phospholipases A₂, which account for most local tissue damage of viperid snakebites. We investigated the noncovalent complex formed between native DM64 and myotoxin II, a myotoxic phospholipase-like protein from Bothrops asper venom. Analytical ultracentrifugation (AUC) and size exclusion chromatography indicated that DM64 is monomeric in solution and binds equimolar amounts of the toxin. Attempts to crystallize native DM64 for X-ray diffraction were unsuccessful. Obtaining recombinant protein to pursue structural studies was also challenging. Classical molecular modeling techniques were impaired by the lack of templates with more than 25% sequence identity with DM64. An integrative structural biology approach was then applied to generate a three-dimensional model of the inhibitor bound to myotoxin II. I-TASSER individually modeled the five immunoglobulin-like domains of DM64. Distance constraints generated by cross-linking mass spectrometry of the complex guided the docking of DM64 domains to the crystal structure of myotoxin II, using Rosetta. AUC, small-angle X-ray scattering (SAXS), molecular modeling, and molecular dynamics simulations indicated that the DM64-myotoxin II complex is structured, shows flexibility, and has an anisotropic shape. Inter-protein cross-links and limited hydrolysis analyses shed light on the inhibitor’s regions involved with toxin interaction, revealing the critical participation of the first, third, and fifth domains of DM64. Our data showed that the fifth domain of DM64 binds to myotoxin II amino-terminal and beta-wing regions. The third domain of the inhibitor acts in a complementary way to the fifth domain. Their binding to these toxin regions presumably precludes dimerization, thus interfering with toxicity, which is related to the quaternary structure of the toxin. The first domain of DM64 interacts with the functional site of the toxin putatively associated with membrane anchorage. We propose that both mechanisms concur to inhibit myotoxin II toxicity by DM64 binding. The present topological characterization of this toxin-antitoxin complex constitutes an essential step toward the rational design of novel peptide-based antivenom therapies targeting snake venom myotoxins.

Characterizing protein conformers by cross-linking mass spectrometry and pattern recognition

MOTIVATION

Chemical cross-linking coupled to mass spectrometry (XLMS) emerged as a powerful technique for studying protein structures and large-scale protein-protein interactions. Nonetheless, XLMS lacks software tailored toward dealing with multiple conformers; this scenario can lead to high-quality identifications that are mutually exclusive. This limitation hampers the applicability of XLMS in structural experiments of dynamic protein systems, where less abundant conformers of the target protein are expected in the sample.

RESULTS

We present QUIN-XL, a software that uses unsupervised clustering to group cross-link identifications by their quantitative profile across multiple samples. QUIN-XL highlights regions of the protein or system presenting changes in its conformation when comparing different biological conditions. We demonstrate our software's usefulness by revisiting the HSP90 protein, comparing three of its different conformers. QUIN-XL's clusters correlate directly to known protein 3D structures of the conformers and therefore validates our software.

AVAILABILITYAND IMPLEMENTATION

QUIN-XL and a user tutorial are freely available at http://patternlabforproteomics.org/quinxl for academic users.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Leveraging the partition selection bias to achieve a high-quality clustering of mass spectra

In proteomics, the identification of peptides from mass spectral data can be mathematically described as the partitioning of mass spectra into clusters (i.e., groups of spectra derived from the same peptide). The way partitions are validated is just as important, having evolved side by side with the clustering algorithms themselves and given rise to many partition assessment measures. An assessment measure is said to have a selection bias if, and only if, the probability that a randomly chosen partition scoring a high value depends on the number of clusters in the partition. In the context of clustering mass spectra, this might mislead the validation process to favor clustering algorithms that generate too many (or few) spectral clusters, regardless of the underlying peptide sequence. A selection bias toward the number of peptides is desirable for proteomics as it estimates the number of peptides in a complex protein mixture. Here, we introduce an assessment measure that is purposely biased toward the number of peptide ion species. We also introduce a partition assessment framework for proteomics, called the Partition Assessment Tool, and demonstrate its importance by evaluating the performance of eight clustering algorithms on seven proteomics datasets while discussing the trade-offs involved. SIGNIFICANCE: Clustering algorithms are widely adopted in proteomics for undertaking several tasks such as speeding up search engines, generating consensus mass spectra, and to aid in the classification of proteomic profiles. Choosing which algorithm is most fit for the task at hand is not simple as each algorithm has advantages and disadvantages; furthermore, specifying clustering parameters is also a necessary and fundamental step. For example, deciding on whether to generate "pure clusters" or fewer clusters but accepting noise. With this as motivation, we verify the performance of several widely adopted algorithms on proteomic datasets and introduce a theoretical framework for drawing conclusions on which approach is suitable for the task at hand.

Quantitative analysis of proteins secreted by Leishmania (Viannia) braziliensis strains associated to distinct clinical manifestations of American Tegumentary Leishmaniasis

The role of Leishmania braziliensis in the development of different clinical forms of American Tegumentary Leishmaniasis (ATL) is unclear, but it has been suggested that molecules secreted/released by parasites could modulate the clinical outcome. Here, we analyzed the infection rate and cytokine profile of macrophages pretreated with the secretome of two L. braziliensis strains associated with polar clinical forms of ATL: one associated with localized self-healing cutaneous leishmaniasis (LCL) and other associated with the disseminated form (DL). Besides, we use an iTRAQ-based quantitative proteomics approach to compare the abundance of proteins secreted by those strains. In vitro infection demonstrated that pretreatment with secretome resulted in higher number of infected macrophages, as well as higher number of amastigotes per cell. Additionally, macrophages pretreated with LCL secretome exhibited a proinflammatory profile, whereas those pretreated with the DL one did not. These findings suggest that secretomes made macrophages more susceptible to infection and that molecules secreted by each strain modulate, differentially, the macrophages' cytokine profile. Indeed, proteomics analysis showed that the DL secretome is rich in molecules involved in macrophage deactivation, while is poor in proteins that activate proinflammatory pathways. Together, our results reveal new molecules that may contribute to the infection, persistence and dissemination of the parasite. SIGNIFICANCE: Leishmania braziliensis is associated to localized self-healing cutaneous lesions (LCL), disseminated leishmaniasis (DL), and mucocutaneous lesions (MCL). To understand the role of the parasite in those distinct clinical manifestations we evaluated infection rates and cytokine profiles of macrophages pre-treated with secretomes of two L. braziliensis strains associated with DL and LCL, and quantitatively compared these secretomes. The infection index of macrophages pretreated with the DL secretome was significantly higher than that exhibited by non-treated cells. Interestingly, whereas the LCL secretome stimulated a proinflammatory setting, favoring an effector cell response that would explain the proper resolution of the disease caused by this strain, the DL strain was not able to elicit such response or has mechanisms to prevent this activation. Indeed, DL secretome is rich in peptidases that may deactivate cell pathways crucial for parasite elimination, while is poor in proteins that could activate proinflammatory pathways, favoring parasite infection and persistence.

The impact of blood-processing time on the proteome of human peripheral blood mononuclear cells

Human peripheral blood mononuclear cells (PBMC) are key to several diagnostics assays and basic science research. Blood pre-analytical variations that occur before obtaining the PBMC fraction can significantly impact the assays results, including viability, composition, integrity, and gene expression changes of immune cells. With this as motivation, we performed a quantitative shotgun proteomics analysis using Isobaric Tag for Relative and Absolute Quantitation (iTRAQ 8plex) labeling to compare PBMC obtained from 24 h-stored blood at room temperature versus freshly isolated. We identified a total of 3195 proteins, of which 245 were differentially abundant (101 upregulated and 144 downregulated). Our results revealed enriched pathways of downregulated proteins related to exocytosis, localization, vesicle-mediated transport, cell activation, and secretion. In contrast, pathways related to exocytosis, neutrophil degranulation and activation, granulocyte activation, leukocyte degranulation, and myeloid leukocyte activation involved in immune response were enriched in upregulated proteins, which may indicate probable granulocyte contamination and activation due to blood storage time and temperature. Examples of upregulated proteins in the 24 h-PBMC samples are CAMP, S100A8, LTA4H, RASAL3, and S100A6, which are involved in an adaptive immune system and antimicrobial activity, proinflammatory mediation, aminopeptidase activities, and naïve T cells survival. Moreover, examples of downregulated proteins are NDUFA5, TAGLN2, H3C1, TUBA8, and CCT2 that are related to the cytoskeleton, cell junction, mitochondrial respiratory chain. In conclusion, the delay in blood-processing time directly impacts the proteomic profile of human PBMC, possibly through granulocyte contamination and activation.

Serum Proteomics Reveals Alterations in Protease Activity, Axon Guidance, and Visual Phototransduction Pathways in Infants With In Utero Exposure to Zika Virus Without Congenital Zika Syndrome

In 2015, ZIKV infection attracted international attention during an epidemic in the Americas, when neurological disorders were reported in infants who had their mothers exposed to ZIKV during pregnancy. World Health Organization (WHO) epidemiological data show that 5 to 15% of neonates exposed to ZIKV in the uterus have complications included in abnormalities related to Congenital Zika Syndrome (CZS). The risk of complications after birth is not well documented, however, clinical evidence shows that 6% of infants exposed to ZIKV during pregnancy have complications present at birth, and this rate rises to 14% when medical monitoring is performed in all exposed infants, regardless of birth condition. Thus, the evaluation and monitoring of all exposed infants are of foremost importance as the development of late complications has been increasingly supported by clinical evidence. The identification of changes in protein profile of infants exposed to ZIKV without CZS could provide valuable findings to better understand molecular changes in this cohort. Here, we use a shotgun-proteomics approach to investigate alterations in the serum of infants without CZS symptoms but exposed to intrauterine ZIKV (ZIKV) compared to unexposed controls (CTRL). A complex pattern of differentially expressed proteins was identified, highlighting the dysregulation of proteins involved in axon orientation, visual phototransduction, and global protease activity in children exposed to ZIKV without CZS. These data support the importance of monitoring children exposed to ZIKV during gestation and without early CZS symptoms. Our study is the first to assess molecular evidence of possible late disorders in children victims of the ZIKV outbreak in the Americas. We emphasize the importance of medical monitoring of symptomatic and asymptomatic children, as apparently unexplained late neurological and eye disorders may be due to intrauterine ZIKV exposure.

RawVegetable - A data assessment tool for proteomics and cross-linking mass spectrometry experiments

We present RawVegetable, a software for mass spectrometry data assessment and quality control tailored toward shotgun proteomics and cross-linking experiments. RawVegetable provides four main modules with distinct features: (A) The charge state chromatogram that independently displays the ion current for each charge state; useful for optimizing the chromatography for highly charged ions and with lower XIC values such as those typically found in cross-linking experiments. (B) The XL-Artefact determination, which flags possible noncovalently associated peptides. (C) The TopN density estimation, for detecting retention time intervals of under or over-sampling, and (D) The chromatography reproducibility module, which provides pairwise comparisons between multiple experiments. RawVegetable, a tutorial, and the example data are freely available for academic use at: http://patternlabforproteomics.org/rawvegetable. SIGNIFICANCE: Chromatography optimization is a critical step for any shotgun proteomic or cross-linking mass spectrometry experiment. Here, we present a nifty solution with several key features, such as displaying individual charge state chromatograms, highlighting chromatographic regions of under- or over-sampling and checking for reproducibility.

Proteomics pinpoints alterations in grade I meningiomas of male versus female patients

Meningiomas are among the most common primary tumors of the central nervous system (CNS) and originate from the arachnoid or meningothelial cells of the meninges. Surgery is the first option of treatment, but depending on the location and invasion patterns, complete removal of the tumor is not always feasible. Reports indicate many differences in meningiomas from male versus female patients; for example, incidence is higher in females, whereas males usually develop the malignant and more aggressive type. With this as motivation, we used shotgun proteomics to compare the proteomic profile of grade I meningioma biopsies of male and female patients. Our results listed several differentially abundant proteins between the two groups; some examples are S100-A4 and proteins involved in RNA splicing events. For males, we identified enriched pathways for cell-matrix organization and for females, pathways related to RNA transporting and processing. We believe our findings contribute to the understanding of the molecular differences between grade I meningiomas of female and male patients.

Thymic Microenvironment Is Modified by Malnutrition and Leishmania infantum Infection

Detrimental effects of malnutrition on immune responses to pathogens have long been recognized and it is considered a main risk factor for various infectious diseases, including visceral leishmaniasis (VL). Thymus is a target of both malnutrition and infection, but its role in the immune response to Leishmania infantum in malnourished individuals is barely studied. Because we previously observed thymic atrophy and significant reduction in cellularity and chemokine levels in malnourished mice infected with L. infantum, we postulated that the thymic microenvironment is severely compromised in those animals. To test this, we analyzed the microarchitecture of the organ and measured the protein abundance in its interstitial space in malnourished BALB/c mice infected or not with L. infantum. Malnourished-infected animals exhibited a significant reduction of the thymic cortex:medulla ratio and altered abundance of proteins secreted in the thymic interstitial fluid. Eighty-one percent of identified proteins are secreted by exosomes and malnourished-infected mice showed significant decrease in exosomal proteins, suggesting that exosomal carrier system, and therefore intrathymic communication, is dysregulated in those animals. Malnourished-infected mice also exhibited a significant increase in the abundance of proteins involved in lipid metabolism and tricarboxylic acid cycle, suggestive of a non-proliferative microenvironment. Accordingly, flow cytometry analysis revealed decreased proliferation of single positive and double positive T cells in those animals. Together, the reduced cortical area, decreased proliferation, and altered protein abundance suggest a dysfunctional thymic microenvironment where T cell migration, proliferation, and maturation are compromised, contributing for the thymic atrophy observed in malnourished animals. All these alterations could affect the control of the local and systemic infection, resulting in an impaired response to L. infantum infection.

A quantitation module for isotope-labeled peptides integrated into PatternLab for proteomics

We present a new module integrated into the widely adopted PatternLab for proteomics to enable analysis of isotope-labeled peptides produced using dimethyl or SILAC. The accurate quantitation of proteins lies within the heart of proteomics; dimethylation has shown to be reliable, inexpensive, and applicable to any sample type. We validate our algorithm using an M. tuberculosis dataset obtained from two biological conditions; we used three dimethyl labels, one serving as an internal control for labeling a mixture of samples from both biological conditions. This internal control certified the proper functioning of our software. Availability: http://patternlabforproteomics.org, freely available for academic use.

Top-Down Garbage Collector: a tool for selecting high-quality top-down proteomics mass spectra

Motivation

We present the first tool for unbiased quality control of top-down proteomics datasets. Our tool can select high-quality top-down proteomics spectra, serve as a gateway for building top-down spectral libraries and, ultimately, improve identification rates.

Results

We demonstrate that a twofold rate increase for two E. coli top-down proteomics datasets may be achievable.

Availability and implementation

http://patternlabforproteomics.org/tdgc, freely available for academic use.

Supplementary information

Supplementary data are available at Bioinformatics online.

TopoLink: evaluation of structural models using chemical crosslinking distance constraints

Summary

A software was developed to evaluate structural models using chemical crosslinking experiments. The user provides the types of linkers used and their reactivity, and the observed crosslinks and dead-ends. The software computes the minimum length of a physically inspired linker that connects the reactive atoms of interest, and reports the consistency of each distance with the experimental observation. Statistics on model consistency with the links are provided. Tools to evaluate the correlation of crosslinks in ensembles of models were developed. TopoLink was used to evaluate the potential crosslinks of all structures of the CATH database. The number of crosslinks expected as a function of protein size and linker length can be used as guide for experimental design.

Availability and implementation

TopoLink is available as free software at http://m3g.iqm.unicamp.br/topolink, and distributed as source code with a user-friendly graphical interface for Windows. A web server is also provided.

Supplementary information

Supplementary data are available at Bioinformatics online.

Data on antigen recognition hindrance by antibodies covalently immobilized to Protein G magnetic beads by dimethyl pimelimidate (DMP) cross-linking

The data presented herein is related to the article entitled "Trypanosoma cruzi immunoproteome: calpain-like CAP5.5 differentially detected throughout distinct stages of human Chagas disease cardiomyopathy" [1]. Electrophoretic analyses under denaturing and reducing conditions indicate that covalent immobilization of human IgG to Protein G magnetic beads by cross-linking with 50 mM dimethyl pimelimidate hinders the recognition of T. cruzi antigens in immunoprecipitation assays.

The EAL-domain protein FcsR regulates flagella, chemotaxis and type III secretion system in Pseudomonas aeruginosa by a phosphodiesterase independent mechanism

The second messenger c-di-GMP regulates the switch between motile and sessile bacterial lifestyles. A general feature of c-di-GMP metabolism is the presence of a surprisingly large number of genes coding for diguanylate cyclases and phosphodiesterases, the enzymes responsible for its synthesis and degradation respectively. However, the physiological relevance of this apparent redundancy is not clear, emphasizing the need for investigating the functions of each of these enzymes. Here we focused on the phosphodiesterase PA2133 from Pseudomonas aeruginosa, an important opportunistic pathogen. We phenotypically characterized P. aeruginosa strain K overexpressing PA2133 or its inactive mutant. We showed that biofilm formation and motility are severely impaired by overexpression of PA2133. Our quantitative proteomic approach applied to the membrane and exoprotein fractions revealed that proteins involved in three processes were mostly affected: flagellar motility, type III secretion system and chemotaxis. While inhibition of biofilm formation can be ascribed to the phosphodiesterase activity of PA2133, down-regulation of flagellar, chemotaxis, and type III secretion system proteins is independent of this enzymatic activity. Based on these unexpected effects of PA2133, we propose to rename this gene product FcsR, for Flagellar, chemotaxis and type III secretion system Regulator.

A multi-protease, multi-dissociation, bottom-up-to-top-down proteomic view of the Loxosceles intermedia venom

Venoms are a rich source for the discovery of molecules with biotechnological applications, but their analysis is challenging even for state-of-the-art proteomics. Here we report on a large-scale proteomic assessment of the venom of Loxosceles intermedia, the so-called brown spider. Venom was extracted from 200 spiders and fractioned into two aliquots relative to a 10 kDa cutoff mass. Each of these was further fractioned and digested with trypsin (4 h), trypsin (18 h), pepsin (18 h), and chymotrypsin (18 h), then analyzed by MudPIT on an LTQ-Orbitrap XL ETD mass spectrometer fragmenting precursors by CID, HCD, and ETD. Aliquots of undigested samples were also analyzed. Our experimental design allowed us to apply spectral networks, thus enabling us to obtain meta-contig assemblies, and consequently de novo sequencing of practically complete proteins, culminating in a deep proteome assessment of the venom. Data are available via ProteomeXchange, with identifier PXD005523.

Comparative proteomics of hydatid fluids from two Echinococcus multilocularis isolates

The hydatid fluid (HF) that fills Echinococcus multilocularis metacestode vesicles is a complex mixture of proteins from both parasite and host origin. Here, a LC-MS/MS approach was used to compare the HF composition of E. multilocularis H95 and G8065 isolates (EmH95 and EmG8065, respectively), which present differences in terms of growth and fertility. Overall, 446 unique proteins were identified, 392 of which (88%) were from parasite origin and 54 from culture medium. At least 256 of parasite proteins were sample exclusive, and 82 of the 136 shared proteins presented differential abundance between E. multilocularis isolates. The parasite's protein repertoires in EmH95 and EmG8065 HF samples presented qualitative and quantitative differences involving antigens, signaling proteins, proteolytic enzymes, protease inhibitors and chaperones, highlighting intraspecific singularities that could be correlated to biological features of each isolate. The repertoire of medium proteins found in the HF was also differential between isolates, and the relevance of the HF exogenous protein content for the parasite's biology is discussed. The repertoires of identified proteins also provided potential molecular markers for important biological features, such as parasite growth rate and fertility, as well potential protein targets for the development of novel diagnostic and treatment strategies for alveolar echinococcosis.

BIOLOGICAL SIGNIFICANCE

E. multilocularis metacestode infection of mammal hosts involve complex interactions mediated by excretory/secretory (ES) products. The hydatid fluid (HF) that fills the E. multilocularis metacestode vesicles contains complex repertoires of parasite ES products and host proteins that mediate important molecular interactions determinant for parasite survival and development, and, consequently, to the infection outcome. HF has been also extensively reported as the main source of proteins for the immunodiagnosis of echinococcosis. The performed proteomic analysis provided a comprehensive profiling of the HF protein composition of two E. multilocularis isolates. This allowed us to identify proteins of both parasite and exogenous (medium) origin, many of which present significant differential abundances between parasite isolates and may correlate to their differential biological features, including fertility and growth rate.

Dataset of proteins mapped on HepG2 cells and those differentially abundant after expression of the dengue non-structural 1 protein

The data supplied in this article are related to the research article entitled “The effect of the dengue non-structural 1 protein expression over the HepG2 cell proteins in a proteomic approach” (K. Rabelo, M.R. Trugillo, S.M. Costa, B.A. Pereira, O.C. Moreira, A.T. Ferreira et al., 2016) [1]. The present article provides the inventory of peptides and proteins mapped in a hepatocyte cell line (HepG2) by mass spectrometry in the presence of the non-structural protein 1 (NS1) of Dengue 2 virus (DENV2). Cells were transfected with pcENS1 plasmid, which encodes the DENV2 NS1 protein, or the controls pcDNA3 (negative control) or pMAXGFP, encoding the green fluorescent protein (GFP), a protein unrelated to dengue. Differentially abundant protein lists were obtained by comparing cells transfected with pcENS1 and controls.

Time-course proteome analysis of developing extrafloral nectaries of Ricinus communis

Floral and extrafloral nectaries are unique organs that secrete energy rich chemical components, but their contribution for nectar production is largely unknown. Here, we present the first comparative proteome dataset of four developmental stages of the extrafloral nectaries from castor plant (Ricinus communis), an important biofuel crop. Respectively, from stage I-IV, we identified 626, 613, 449 and 356 proteins, respectively, summing up 882 nonredundant proteins. Surprisingly, we identified two isoforms of the potent toxin ricin, indicating that ricin expression is not limited to seeds, but it may serve a general defense purpose for the castor plant. To date, this is the most complete dataset of proteins either from floral or extrafloral nectaries, thus contributing to lay the foundations for investigations on their ecological and evolutionary importance.

The effect of the dengue non-structural 1 protein expression over the HepG2 cell proteins in a proteomic approach

Dengue is an important mosquito borne viral disease in the world. Dengue virus (DENV) encodes a polyprotein, which is cleaved in ten proteins, including the non-structural protein 1 (NS1). In this work, we analyzed the effect of NS1 expression in one hepatic cell line, HepG2, through a shotgun proteomic approach. Cells were transfected with pcENS1 plasmid, which encodes the DENV2 NS1 protein, or the controls pcDNA3 (negative control) and pMAXGFP (GFP, a protein unrelated to dengue). Expression of NS1 was detected by immunofluorescence, western blot and flow cytometry. We identified 14,138 peptides that mapped to 4,756 proteins in all analyzed conditions. We found 41 and 81 differentially abundant proteins when compared to cells transfected with plasmids pcDNA3 and pMAXGFP, respectively. Besides, 107 proteins were detected only in the presence of NS1. We identified clusters of proteins involved mainly in mRNA process and viral RNA replication. Down regulation expression of one protein (MARCKS), identified by the proteomic analysis, was also confirmed by real time PCR in HepG2 cells infected with DENV2. Identification of proteins modulated by the presence of NS1 may improve our understanding of its role in virus infection and pathogenesis, contributing to development of new therapies and vaccines.

BIOLOGICAL SIGNIFICANCE

Dengue is an important viral disease, with epidemics in tropical and subtropical regions of the world. The disease is complex, with different manifestations, in which the liver is normally affected. The NS1 is found in infected cells associated with plasma membrane and secreted into the circulation as a soluble multimer. This protein is essential for virus viability, although its function is not elucidated. Some reports indicate that the NS1 can be used as a protective antigen for the development of a dengue vaccine, while others suggest its involvement in viral pathogenesis. In this work, we report an in-depth comprehensive proteomic profiling resulting from the presence of NS1 in HepG2 cells. These results can contribute to a better understanding of the NS1 role during infection.

Campomanesia adamantium extract induces DNA damage, apoptosis, and affects cyclophosphamide metabolism

Campomanesia adamantium (Cambess.) O. Berg. is originally from Brazil. Its leaves and fruits have medicinal properties such as anti-inflammatory, antidiarrheal and antiseptic properties. However, the mutagenic potential of this species has been reported in few studies. This study describes the mutagenic/antimutagenic, splenic phagocytic, and apoptotic activities of C. adamantium hydroethanolic extract with or without cyclophosphamide in Swiss mice. The animals orally received the hydroethanolic extract at doses of 30, 100, or 300 mg/kg with or without 100 mg/kg cyclophosphamide. Mutagenesis was evaluated by performing the micronucleus assay after treatment for 24, 48, and 72 h, while splenic phagocytic and apoptotic effects were investigated after 72 h. Short-term exposure of 30 and 100 mg/kg extract induced mild clastogenic/aneugenic effects and increased splenic phagocytosis and apoptosis in the liver, spleen, and kidneys. When the extract was administered in combination with cyclophosphamide, micronucleus frequency and apoptosis reduced. Extract components might affect cyclophosphamide metabolism, which possibly leads to increased clearance of this chemotherapeutic agent. C. adamantium showed mutagenic activity and it may decrease the effectiveness of drugs with metabolic pathways similar to those associated with cyclophosphamide. Thus, caution should be exercised while consuming these extracts, especially when received in combination with other drugs.

An Evaluation of the Crystal Structure of C-terminal Truncated Apolipoprotein A-I in Solution Reveals Structural Dynamics Related to Lipid Binding

Apolipoprotein (apo) A-I mediates many of the anti-atherogenic functions attributed to high density lipoprotein. Unfortunately, efforts toward a high resolution structure of full-length apoA-I have not been fruitful, although there have been successes with deletion mutants. Recently, a C-terminal truncation (apoA-I(Δ185-243)) was crystallized as a dimer. The structure showed two helical bundles connected by a long, curved pair of swapped helical domains. To compare this structure to that existing under solution conditions, we applied small angle x-ray scattering and isotope-assisted chemical cross-linking to apoA-I(Δ185-243) in its dimeric and monomeric forms. For the dimer, we found evidence for the shared domains and aspects of the N-terminal bundles, but not the molecular curvature seen in the crystal. We also found that the N-terminal bundles equilibrate between open and closed states. Interestingly, this movement is one of the transitions proposed during lipid binding. The monomer was consistent with a model in which the long shared helix doubles back onto the helical bundle. Combined with the crystal structure, these data offer an important starting point to understand the molecular details of high density lipoprotein biogenesis.

Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for the analysis of shotgun proteomic data. The contained modules allow for formatting of sequence databases, peptide spectrum matching, statistical filtering and data organization, extracting quantitative information from label-free and chemically labeled data, and analyzing statistics for differential proteomics. PatternLab also has modules to perform similarity-driven studies with de novo sequencing data, to evaluate time-course experiments and to highlight the biological significance of data with regard to the Gene Ontology database. The PatternLab for proteomics 4.0 package brings together all of these modules in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats. All updates to PatternLab, including new features, have been previously tested on millions of mass spectra. PatternLab is easy to install, and it is freely available from http://patternlabforproteomics.org.

Proteomic Analysis of the Endosperm Ontogeny of Jatropha curcas L. Seeds

Seeds of Jatropha curcas L. represent a potential source of raw material for the production of biodiesel. However, this use is hampered by the lack of basic information on the biosynthetic pathways associated with synthesis of toxic diterpenes, fatty acids, and triacylglycerols, as well as the pattern of deposition of storage proteins during seed development. In this study, we performed an in-depth proteome analysis of the endosperm isolated from five developmental stages which resulted in the identification of 1517, 1256, 1033, 752, and 307 proteins, respectively, summing up 1760 different proteins. Proteins with similar label free quantitation expression pattern were grouped into five clusters. The biological significance of these identifications is discussed with special focus on the analysis of seed storage proteins, proteins involved in the metabolism of fatty acids, carbohydrates, toxic components and proteolytic processing. Although several enzymes belonging to the biosynthesis of diterpenoid precursors were identified, we were unable to find any terpene synthase/cyclase, indicating that the synthesis of phorbol esters, the main toxic diterpenes, does not occur in seeds. The strategy used enabled us to provide a first in depth proteome analysis of the developing endosperm of this biodiesel plant, providing an important glimpse into the enzymatic machinery devoted to the production of C and N sources to sustain seed development.

SIM-XL: A powerful and user-friendly tool for peptide cross-linking analysis

Chemical cross-linking has emerged as a powerful approach for the structural characterization of proteins and protein complexes. However, the correct identification of covalently linked (cross-linked or XL) peptides analyzed by tandem mass spectrometry is still an open challenge. Here we present SIM-XL, a software tool that can analyze data generated through commonly used cross-linkers (e.g., BS3/DSS). Our software introduces a new paradigm for search-space reduction, which ultimately accounts for its increase in speed and sensitivity. Moreover, our search engine is the first to capitalize on reporter ions for selecting tandem mass spectra derived from cross-linked peptides. It also makes available a 2D interaction map and a spectrum-annotation tool unmatched by any of its kind. We show SIM-XL to be more sensitive and faster than a competing tool when analyzing a data set obtained from the human HSP90. The software is freely available for academic use at http://patternlabforproteomics.org/sim-xl. A video demonstrating the tool is available at http://patternlabforproteomics.org/sim-xl/video. SIM-XL is the first tool to support XL data in the mzIdentML format; all data are thus available from the ProteomeXchange consortium (identifier PXD001677). This article is part of a Special Issue entitled: Computational Proteomics.

A scoring model for phosphopeptide site localization and its impact on the question of whether to use MSA

The production of structurally significant product ions during the dissociation of phosphopeptides is a key to the successful determination of phosphorylation sites. These diagnostic ions can be generated using the widely adopted MS/MS approach, MS3 (Data Dependent Neutral Loss - DDNL), or by multistage activation (MSA). The main purpose of this work is to introduce a false-localization rate (FLR) probabilistic model to enable unbiased phosphoproteomics studies. Briefly, our algorithm infers a probabilistic function from the distribution of the identified phosphopeptides' XCorr Delta scores (XD-Scores) in the current experiment. Our module infers p-values by relying on Gaussian mixture models and a logistic function. We demonstrate the usefulness of our probabilistic model by revisiting the "to MSA, or not to MSA" dilemma. For this, we use human leukemia-derived cells (K562) as a study model and enriched for phosphopeptides using the hydroxyapatite (HAP) chromatography. The aliquots were analyzed with and without MSA on an Orbitrap-XL. Our XD-Scoring analysis revealed that the MS/MS approach provides more identifications because of its faster scan rate, but that for the same given scan rate higher-confidence spectra can be achieved with MSA. Our software is integrated into the PatternLab for proteomics freely available for academic community at http://www.patternlabforproteomics.org. Biological significance Assigning statistical confidence to phosphorylation sites is necessary for proper phosphoproteomic assessment. Here we present a rigorous statistical model, based on Gaussian mixture models and a logistic function, which overcomes shortcomings of previous tools. The algorithm described herein is made readily available to the scientific community by integrating it into the widely adopted PatternLab for proteomics. This article is part of a Special Issue entitled: Computational Proteomics.

Proteome analysis of formalin-fixed paraffin-embedded tissues from a primary gastric melanoma and its meningeal metastasis: a case report

Melanoma is the third most common brain metastasis cause in the United States as it has a relatively high susceptibility to metastasize to the central nervous system. Among the different origins for brain metastasis, those originating from primary gastric melanomas are extremely rare. Here, we compare protein profiles obtained from formalin-fixed paraffin- embedded (FFPE) tissues of a primary gastric melanoma with its meningeal metastasis. For this, the contents of a microscope slide were scraped and ultimately analyzed by nano-chromatography coupled online with tandem mass spectrometry using an Orbitrap XL. Our results disclose 184 proteins uniquely identified in the primary gastric melanoma, 304 in the meningeal metastasis, and 177 in common. Notably, we identified several enzymes related to changes in the metabolism that are linked to producing energy by elevated rates of glycolysis in a process called the Warburg effect. Moreover, we show that our FFPE proteomic approach allowed identification of key biological markers such as the S100 protein that we further validated by immunohistochemistry for both, the primary and metastatic tumor samples. That said, we demonstrated a powerful strategy to retrospectively mine data for aiding in the understanding of metastasis, biomarker discovery, and ultimately, diseases. To our knowledge, these results disclose for the first time a comparison of the proteomic profiles of gastric melanoma and its corresponding meningeal metastasis.

PepExplorer: a similarity-driven tool for analyzing de novo sequencing results

Peptide spectrum matching is the current gold standard for protein identification via mass-spectrometry-based proteomics. Peptide spectrum matching compares experimental mass spectra against theoretical spectra generated from a protein sequence database to perform identification, but protein sequences not present in a database cannot be identified unless their sequences are in part conserved. The alternative approach, de novo sequencing, can make it possible to infer a peptide sequence directly from a mass spectrum, but interpreting long lists of peptide sequences resulting from large-scale experiments is not trivial. With this as motivation, PepExplorer was developed to use rigorous pattern recognition to assemble a list of homologue proteins using de novo sequencing data coupled to sequence alignment to allow biological interpretation of the data. PepExplorer can read the output of various widely adopted de novo sequencing tools and converge to a list of proteins with a global false-discovery rate. To this end, it employs a radial basis function neural network that considers precursor charge states, de novo sequencing scores, peptide lengths, and alignment scores to select similar protein candidates, from a target-decoy database, usually obtained from phylogenetically related species. Alignments are performed using a modified Smith-Waterman algorithm tailored for the task at hand. We verified the effectiveness of our approach using a reference set of identifications generated by ProLuCID when searching for Pyrococcus furiosus mass spectra on the corresponding NCBI RefSeq database. We then modified the sequence database by swapping amino acids until ProLuCID was no longer capable of identifying any proteins. By searching the mass spectra using PepExplorer on the modified database, we were able to recover most of the identifications at a 1% false-discovery rate. Finally, we employed PepExplorer to disclose a comprehensive proteomic assessment of the Bothrops jararaca plasma, a known biological source of natural inhibitors of snake toxins. PepExplorer is integrated into the PatternLab for Proteomics environment, which makes available various tools for downstream data analysis, including resources for quantitative and differential proteomics.

Deciphering the human brain proteome: characterization of the anterior temporal lobe and corpus callosum as part of the Chromosome 15-centric Human Proteome Project

Defining the proteomes encoded by each chromosome and characterizing proteins related to human illnesses are among the goals of the Chromosome-centric Human Proteome Project (C-HPP) and the Biology and Disease-driven HPP. Following these objectives, we investigated the proteomes of the human anterior temporal lobe (ATL) and corpus callosum (CC) collected post-mortem from eight subjects. Using a label-free GeLC-MS/MS approach, we identified 2454 proteins in the ATL and 1887 in the CC through roughly 7500 and 5500 peptides, respectively. Considering that the ATL is a gray-matter region while the CC is a white-matter region, they presented proteomes specific to their functions. Besides, 38 proteins were found to be differentially expressed between the two regions. Furthermore, the proteome data sets were classified according to their chromosomal origin, and five proteins were evidenced at the MS level for the first time. We identified 70 proteins of the chromosome 15 - one of them for the first time by MS - which were submitted to an in silico pathway analysis. These revealed branch point proteins associated with Prader-Willi and Angelman syndromes and dyskeratosis congenita, which are chromosome-15-associated diseases. Data presented here can be a useful for brain disorder studies as well as for contributing to the C-HPP initiative. Our data are publicly available as resource data to C-HPP participant groups at http://yoda.iq.ufrj.br/Daniel/chpp2013. Additionally, the mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000547 for the corpus callosum and PXD000548 for the anterior temporal lobe.

Exploring the proteomic landscape of a gastric cancer biopsy with the shotgun imaging analyzer

Accessing localized proteomic profiles has emerged as a fundamental strategy to understand the biology of diseases, as recently demonstrated, for example, in the context of determining cancer resection margins with improved precision. Here, we analyze a gastric cancer biopsy sectioned into 10 parts, each one subjected to MudPIT analysis. We introduce a software tool, named Shotgun Imaging Analyzer and inspired in MALDI imaging, to enable the overlaying of a protein's expression heat map on a tissue picture. The software is tightly integrated with the NeXtProt database, so it enables the browsing of identified proteins according to chromosomes, quickly listing human proteins never identified by mass spectrometry (i.e., the so-called missing proteins), and the automatic search for proteins that are more expressed over a specific region of interest on the biopsy, all of which constitute goals that are clearly well-aligned with those of the C-HPP. Our software has been able to highlight an intense expression of proteins previously known to be correlated with cancers (e.g., glutathione S-transferase Mu 3), and in particular, we draw attention to Gastrokine-2, a "missing protein" identified in this work of which we were able to clearly delineate the tumoral region from the "healthy" with our approach. Data are available via ProteomeXchange with identifier PXD000584.

Comparative proteomic analysis of the aging soleus and extensor digitorum longus rat muscles using TMT labeling and mass spectrometry

Sarcopenia describes an age-related decline in skeletal muscle mass, strength, and function that ultimately impairs metabolism and leads to poor balance, frequent falling, limited mobility, and a reduction in quality of life. Here we investigate the pathogenesis of sarcopenia through a proteomic shotgun approach. In brief, we employed tandem mass tags to quantitate and compare the protein profiles obtained from young versus old rat slow-twitch type of muscle (soleus) and a fast-twitch type of muscle (extensor digitorum longus, EDL). Our results disclose 3452 and 1848 proteins identified from soleus and EDL muscles samples, of which 78 and 174 were found to be differentially expressed, respectively. In general, most of the proteins were structural related and involved in energy metabolism, oxidative stress, detoxification, or transport. Aging affected soleus and EDL muscles differently, and several proteins were regulated in opposite ways. For example, pyruvate kinase had its expression and activity different in both soleus and EDL muscles. We were able to verify with existing literature many of our differentially expressed proteins as candidate aging biomarkers and, most importantly, disclose several new candidate biomarkers such as the glioblastoma amplified sequence, zero β-globin, and prolargin.

Proteome analysis of plastids from developing seeds of Jatropha curcas L

In this study, we performed a proteomic analysis of plastids isolated from the endosperm of developing Jatropha curcas seeds that were in the initial stage of deposition of protein and lipid reserves. Proteins extracted from the plastids were digested with trypsin, and the peptides were applied to an EASY-nano LC system coupled inline to an ESI-LTQ-Orbitrap Velos mass spectrometer, and this led to the identification of 1103 proteins representing 804 protein groups, of which 923 proteins were considered as true identifications, and this considerably expands the repertoire of J. curcas proteins identified so far. Of the identified proteins, only five are encoded in the plastid genome, and none of them are involved in photosynthesis, evidentiating the nonphotosynthetic nature of the isolated plastids. Homologues for 824 out of 923 identified proteins were present in PPDB, SUBA, or PlProt databases while homologues for 13 proteins were not found in any of the three plastid proteins databases but were marked as plastidial by at least one of the three prediction programs used. Functional classification showed that proteins belonging to amino acids metabolism comprise the main functional class, followed by carbohydrate, energy, and lipid metabolisms. The small and large subunits of Rubisco were identified, and their presence in the plastids is considered to be an adaptive feature counterbalancing for the loss of one-third of the carbon as CO2 as a result of the conversion of carbohydrate to oil through glycolysis. While several enzymes involved in the biosynthesis of several precursors of diterpenoids were identified, we were unable to identify any terpene synthase/cyclase, which suggests that the plastids isolated from the endosperm of developing seeds do not synthesize phorbol esters. In conclusion, our study provides insights into the major biosynthetic pathways and certain unique features of the plastids from the endosperm of developing seeds at the whole proteome level.

Pinpointing differentially expressed domains in complex protein mixtures with the cloud service of PatternLab for Proteomics

Mass-spectrometry-based shotgun proteomics has become a widespread technology for analyzing complex protein mixtures. Here we describe a new module integrated into PatternLab for Proteomics that allows the pinpointing of differentially expressed domains. This is accomplished by inferring functional domains through our cloud service, using HMMER3 and Pfam remotely, and then mapping the quantitation values into domains for downstream analysis. In all, spotting which functional domains are changing when comparing biological states serves as a complementary approach to facilitate the understanding of a system's biology. We exemplify the new module's use by reanalyzing a previously published MudPIT dataset of Cryptococcus gattii cultivated under iron-depleted and replete conditions. We show how the differential analysis of functional domains can facilitate the interpretation of proteomic data by providing further valuable insight.

Epstein-Barr virus DNA associated with gastric adenocarcinoma and adjacent non-cancerous mucosa in patients from Manaus, Brazil

Gastric cancer is one of most frequent causes of death in Brazil. The city of Manaus has one of the highest incidences of this disease in Brazil. The Epstein-Barr virus (EBV) is a ubiquitous herpesvirus that is classified as a group 1 carcinogen by the International Agency for Research on Cancer. We obtained biopsies from 6 control subjects and 10 patients with gastric carcinomas living in Manaus. In the patients, the samples were taken from tumors and from adjacent non-cancerous mucosa. These samples were screened for EBV DNA by PCR to amplify the 288-bp fragments from the Bam M region. The EBV DNA was detected in 8 of the 10 tumor cases and in none of the 6 control subjects. In the positively identified samples, EBV DNA was detected in five corresponding resection margins. Previous research indicated only a weak association between EBV and gastric cancer. We suggest that EBV should be considered as a risk factor for gastric adenocarcinomas in Manaus.