Proteomic analysis of cerebrospinal fluid of amyotrophic lateral sclerosis patients in the presence of autologous bone marrow derived mesenchymal stem cells.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly progressive motoneuron degenerative disorder. There are still no drugs capable of slowing disease evolution or improving life quality of ALS patients. Thus, autologous stem cell therapy has emerged as an alternative treatment regime to be investigated in clinical ALS. METHOD: Using Proteomics and Protein-Protein Interaction Network analyses combined with bioinformatics, the possible cellular mechanisms and molecular targets related to mesenchymal stem cells (MSCs, 1 × 106 cells/kg, intrathecally in the lumbar region of the spine) were investigated in cerebrospinal fluid (CSF) of ALS patients who received intrathecal infusions of autologous bone marrow-derived MSCs thirty days after cell therapy. Data are available via ProteomeXchange with identifier PXD053129. RESULTS: Proteomics revealed 220 deregulated proteins in CSF of ALS subjects treated with MSCs compared to CSF collected from the same patients prior to MSCs infusion. Bioinformatics enriched analyses highlighted events of Extracellular matrix and Cell adhesion molecules as well as related key targets APOA1, APOE, APP, C4A, C5, FGA, FGB, FGG and PLG in the CSF of cell treated ALS subjects. CONCLUSIONS: Extracellular matrix and cell adhesion molecules as well as their related highlighted components have emerged as key targets of autologous MSCs in CSF of ALS patients. TRIAL REGISTRATION: Clinicaltrial.gov identifier NCT0291768. Registered 28 September 2016.

Knowledge-slanted random forest method for high-dimensional data and small sample size with a feature selection application for gene expression data.

The use of prior knowledge in the machine learning framework has been considered a potential tool to handle the curse of dimensionality in genetic and genomics data. Although random forest (RF) represents a flexible non-parametric approach with several advantages, it can provide poor accuracy in high-dimensional settings, mainly in scenarios with small sample sizes. We propose a knowledge-slanted RF that integrates biological networks as prior knowledge into the model to improve its performance and explainability, exemplifying its use for selecting and identifying relevant genes. knowledge-slanted RF is a combination of two stages. First, prior knowledge represented by graphs is translated by running a random walk with restart algorithm to determine the relevance of each gene based on its connection and localization on a protein-protein interaction network. Then, each relevance is used to modify the selection probability to draw a gene as a candidate split-feature in the conventional RF. Experiments in simulated datasets with very small sample sizes ( n ≤ 30 ) comparing knowledge-slanted RF against conventional RF and logistic lasso regression, suggest an improved precision in outcome prediction compared to the other methods. The knowledge-slanted RF was completed with the introduction of a modified version of the Boruta feature selection algorithm. Finally, knowledge-slanted RF identified more relevant biological genes, offering a higher level of explainability for users than conventional RF. These findings were corroborated in one real case to identify relevant genes to calcific aortic valve stenosis.

Insight from atomistic molecular dynamics simulations into the supramolecular assembly of the aldo-keto reductase from Trypanosoma cruzi.

CONTEXT: Currently, Chagas disease represents an important public health problem affecting more than 8 million people worldwide. The vector of this disease is the Trypanosoma cruzi (Tc) parasite. Our research specifically focuses on the structure and aggregation states of the enzyme aldo-keto reductase of Tc (TcAKR) reported in this parasite. TcAKR belongs to the aldo-keto reductase (AKR) superfamily, enzymes that catalyze redox reactions involved in crucial biological processes. While most AKRs are found in monomeric forms, some have been reported to form dimeric and tetrameric structures. This is the case for some TcAKR. To better understand how TcAKR multimers form and remain stable, we conducted a comprehensive computational analysis using molecular dynamics (MD) simulations. Our approach to elucidating the aggregation states of TcAKR involved two strategies. Initially, we explored the dynamic behaviour of pre-assembled TcAKR dimers. Subsequently, we examined the self-aggregation of eight monomers. This investigation led to the identification of crucial residues that contribute to the stabilization of protein-protein interactions. It was also found that TcAKRs can form stable supramolecular assemblies, with each monomer typically surrounded by three first neighbours. These findings align with experimental reports of tetrameric or more complex supramolecular structures. Our computational studies could guide further experimental investigations aiming at drug development and assist in designing strategies to modulate aggregation. METHOD: Atomistic molecular dynamics simulations were carried out. The TcAKR 3D model structure was obtained by homology modelling using the Swiss Model for the TcAKR sequence (GenBank accession no. EU558869). Further, we checked the model with Alphafold2 and found a high degree of similarity between models. Several tools were used to build the dimers including CLUSPRO, GRAMM-Docking, Hdock, and Py-dock. Protein superstructures were built using the PACKMOL package. CHARMM-GUI was used to set up the simulation systems. GROMACS version 2020.5 was used to perform the simulations with the CHARMM36 force field for the protein and ions and the TIP3P model for water. Further analyses were performed using VMD, GROMACS, AMBER tools, MDLovoFit, bio3d, and in-house programs.

The odyssey of the TR(i)P journey to the cellular membrane.

Ion channels are integral membrane proteins mediating ion flow in response to changes in their environment. Among the different types of ion channels reported to date, the super-family of TRP channels stands out since its members have been linked to many pathophysiological processes. The family comprises 6 subfamilies and 28 members in mammals, which are widely distributed throughout most tissues and organs and have an important role in several aspects of cellular physiology. It has been evidenced that abnormal expression, post-translational modifications, and channel trafficking are associated with several pathologies, such as cancer, cardiovascular disease, diabetes, and brain disorders, among others. In this review, we present an updated summary of the mechanisms involved in the subcellular trafficking of TRP channels, with a special emphasis on whether different post-translational modifications and naturally occurring mutagenesis affect both expression and trafficking. Additionally, we describe how such changes have been associated with the development and progress of diverse pathologies associated with the gain or loss of functional phenotypes. The study of these processes will not only contribute to a better understanding the role of TRP channels in the different tissues but will also present novel possible therapeutic targets in diseases where their activity is dysregulated.

Changes in the proteome of Apis mellifera acutely exposed to sublethal dosage of glyphosate and imidacloprid.

Uncontrolled use of pesticides has caused a dramatic reduction in the number of pollinators, including bees. Studies on the effects of pesticides on bees have reported effects on both metabolic and neurological levels under chronic exposure. In this study, variations in the differential expression of head and thorax-abdomen proteins in Africanized A. mellifera bees treated acutely with sublethal doses of glyphosate and imidacloprid were studied using a proteomic approach. A total of 92 proteins were detected, 49 of which were differentially expressed compared to those in the control group (47 downregulated and 2 upregulated). Protein interaction networks with differential protein expression ratios suggested that acute exposure of A. mellifera to sublethal doses of glyphosate could cause head damage, which is mainly associated with behavior and metabolism. Simultaneously, imidacloprid can cause damage associated with metabolism as well as, neuronal damage, cellular stress, and impairment of the detoxification system. Regarding the thorax-abdomen fractions, glyphosate could lead to cytoskeleton reorganization and a reduction in defense mechanisms, whereas imidacloprid could affect the coordination and impairment of the oxidative stress response.

Characterization of the interaction between the Sec61 translocon complex and ppαF using optical tweezers.

The Sec61 translocon allows the translocation of secretory preproteins from the cytosol to the endoplasmic reticulum lumen during polypeptide biosynthesis. These proteins possess an N-terminal signal peptide (SP) which docks at the translocon. SP mutations can abolish translocation and cause diseases, suggesting an essential role for this SP/Sec61 interaction. However, a detailed biophysical characterization of this binding is still missing. Here, optical tweezers force spectroscopy was used to characterize the kinetic parameters of the dissociation process between Sec61 and the SP of prepro-alpha-factor. The unbinding parameters including off-rate constant and distance to the transition state were obtained by fitting rupture force data to Dudko-Hummer-Szabo models. Interestingly, the translocation inhibitor mycolactone increases the off-rate and accelerates the SP/Sec61 dissociation, while also weakening the interaction. Whereas the translocation deficient mutant containing a single point mutation in the SP abolished the specificity of the SP/Sec61 binding, resulting in an unstable interaction. In conclusion, we characterize quantitatively the dissociation process between the signal peptide and the translocon, and how the unbinding parameters are modified by a translocation inhibitor.

In Silico Analysis of Protein-Protein Interactions of Putative Endoplasmic Reticulum Metallopeptidase 1 in Schizosaccharomyces pombe.

Ermp1 is a putative metalloprotease from Schizosaccharomyces pombe and a member of the Fxna peptidases. Although their function is unknown, orthologous proteins from rats and humans have been associated with the maturation of ovarian follicles and increased ER stress. This study focuses on proposing the first prediction of PPI by comparison of the interologues between humans and yeasts, as well as the molecular docking and dynamics of the M28 domain of Ermp1 with possible target proteins. As results, 45 proteins are proposed that could interact with the metalloprotease. Most of these proteins are related to the transport of Ca2+ and the metabolism of amino acids and proteins. Docking and molecular dynamics suggest that the M28 domain of Ermp1 could hydrolyze leucine and methionine residues of Amk2, Ypt5 and Pex12. These results could support future experimental investigations of other Fxna peptidases, such as human ERMP1.

Ligand- and Structure-Based Virtual Screening Identifies New Inhibitors of the Interaction of the SARS-CoV-2 Spike Protein with the ACE2 Host Receptor.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a fast-spreading viral pathogen and poses a serious threat to human health. New SARS-CoV-2 variants have been arising worldwide; therefore, is necessary to explore more therapeutic options. The interaction of the viral spike (S) protein with the angiotensin-converting enzyme 2 (ACE2) host receptor is an attractive drug target to prevent the infection via the inhibition of virus cell entry. In this study, Ligand- and Structure-Based Virtual Screening (LBVS and SBVS) was performed to propose potential inhibitors capable of blocking the S receptor-binding domain (RBD) and ACE2 interaction. The best five lead compounds were confirmed as inhibitors through ELISA-based enzyme assays. The docking studies and molecular dynamic (MD) simulations of the selected compounds maintained the molecular interaction and stability (RMSD fluctuations less than 5 Å) with key residues of the S protein. The compounds DRI-1, DRI-2, DRI-3, DRI-4, and DRI-5 efficiently block the interaction between the SARS-CoV-2 spike protein and receptor ACE2 (from 69.90 to 99.65% of inhibition) at 50 µM. The most potent inhibitors were DRI-2 (IC50 = 8.8 µM) and DRI-3 (IC50 = 2.1 µM) and have an acceptable profile of cytotoxicity (CC50 > 90 µM). Therefore, these compounds could be good candidates for further SARS-CoV-2 preclinical experiments.

Human protein-protein interaction networks: A topological comparison review.

Protein-Protein Interaction Networks aim to model the interactome, providing a powerful tool for understanding the complex relationships governing cellular processes. These networks have numerous applications, including functional enrichment, discovering cancer driver genes, identifying drug targets, and more. Various databases make protein-protein networks available for many species, including Homo sapiens. This work topologically compares four Homo sapiens networks using a coarse-to-fine approach, comparing global characteristics, sub-network topology, specific nodes centrality, and interaction significance. Results show that the four human protein networks share many common protein-encoding genes and some global measures, but significantly differ in the interactions and neighbourhood. Small sub-networks from cancer pathways performed better than the whole networks, indicating an improved topological consistency in functional pathways. The centrality analysis shows that the same genes play different roles in different networks. We discuss how studies and analyses that rely on protein-protein networks for humans should consider their similarities and distinctions.

Unveiling protein-protein interaction potential through Monte Carlo simulation combined with small-angle X-ray scattering.

Protein interactions are investigated under different conditions of lysozyme concentration, temperature and ionic strength by means of in-solution small angle X-Ray scattering (SAXS) experiments and Monte Carlo (MC) simulations. Initially, experimental data were analysed through a Hard-Sphere Double Yukawa (HSDY) model combined with Random Phase Approximation (RPA), a closure relationship commonly used in the literature for monodisperse systems. We realized by means of MC that the HSDY/RPA modelling fails to describe the protein-protein pair potential for moderated and dense systems at low ionic strength, mainly due to inherent distortions of the RPA approximation. Our SAXS/MC results thus show that lysozyme concentrations between 2 (diluted) and 20 mg/mL (not crowded) present similar protein-protein pair potential preserving the values of surface net charge around 7 e, protein diameter of 28 Å, decay range of attractive well potential of 3 Å and a depth of the well potential varying from 1 to 5 kBT depending on temperature and salt addition. Noteworthy, we here propose a novel method to analyse the SAXS data from interacting proteins through MC simulations, which overcomes the deficiencies presented by the use of a closure relationship. Furthermore, this new methodology of combining SAXS with MC simulations gives a step forward to investigate more complex systems as those composed of a mixture of proteins of distinct species presenting different molecular weights (and hence sizes) and surface net charges at low, moderate and very dense systems.

Cell annotation using scRNA-seq data: A protein-protein interaction network approach.

Pathway analysis is an important step in the interpretation of single cell transcriptomic data, as it provides powerful information to detect which cellular processes are active in each individual cell. We have recently developed a protein-protein interaction network-based framework to quantify pluripotency associated pathways from scRNA-seq data. On this occasion, we extend this approach to quantify the activity of a pathway associated with any biological process, or even any list of genes. A systems-level characterization of pathway activities across multiple cell types provides a broadly applicable tool for the analysis of pathways in both healthy and disease conditions. Dysregulated cellular functions are a hallmark of a wide spectrum of human disorders, including cancer and autoimmune diseases. Here, we illustrate our method by analyzing various biological processes in healthy and cancer breast samples. Using this approach we found that tumor breast cells, even when they form a single group in the UMAP space, keep diverse biological programs active in a differentiated manner within the cluster.•We implement a protein-protein interaction network-based approach to quantify the activity of different biological processes.•The methodology can be used for cell annotation in scRNA-seq studies and is freely available as R package.

Crosstalking interactions between P2X4 and 5-HT3A receptors.

Ionotropic receptors are ligand-gated ion channels triggering fast neurotransmitter responses. Among them, P2X and 5-HT3 receptors have been shown to physically interact each other and functionally inducing cross inhibitory responses. Nevertheless, despite the importance of P2X4 and 5-HT3A receptors that mediate for example neuropathic pain and psychosis respectively, complementary evidence has recently started to move forward in the understanding of this interaction. In this review, we discuss current evidence supporting the mechanism of crosstalking between both receptors, from the structural to the transduction pathway level. We expect this work may guide the design of further experiments to obtain a comprehensive view for the neuropharmacological role of these interacting receptors. This article is part of the Special Issue on "The receptor-receptor interaction as a new target for therapy".

A complex tissue-specific interplay between the Arabidopsis transcription factors AtMYB68, AtHB23, and AtPHL1 modulates primary and lateral root development and adaptation to salinity.

Adaptation to different soil conditions is a well-regulated process vital for plant life. AtHB23 is a homeodomain-leucine zipper I transcription factor (TF) that was previously revealed as crucial for plant survival under salinity conditions. We wondered whether this TF has partners to perform this essential function. Therefore, TF cDNA library screening, yeast two-hybrid, bimolecular fluorescence complementation, and coimmunoprecipitation assays were complemented with expression analyses and phenotypic characterization of silenced, mutant, overexpression, and crossed plants in normal and salinity conditions. We revealed that AtHB23, AtPHL1, and AtMYB68 interact with each other, modulating root development and the salinity response. The encoding genes are coexpressed in specific root tissues and at specific developmental stages. In normal conditions, amiR68 silenced plants have fewer initiated roots, the opposite phenotype to that shown by amiR23 plants. AtMYB68 and AtPHL1 play opposite roles in lateral root elongation. Under salinity conditions, AtHB23 plays a crucial positive role in cooperating with AtMYB68, whereas AtPHL1 acts oppositely by obstructing the function of the former, impacting the plant's survival ability. Such interplay supports the complex interaction between these TF in primary and lateral roots. The root adaptation capability is associated with the amyloplast state. We identified new molecular players that through a complex relationship determine Arabidopsis root architecture and survival in salinity conditions.

In Silico and In Vivo Studies of a Tumor-Penetrating and Interfering Peptide with Antitumoral Effect on Xenograft Models of Breast Cancer.

The combination of a tumor-penetrating peptide (TPP) with a peptide able to interfere with a given protein-protein interaction (IP) is a promising strategy with potential clinical application. Little is known about the impact of fusing a TPP with an IP, both in terms of internalization and functional effect. Here, we analyze these aspects in the context of breast cancer, targeting PP2A/SET interaction, using both in silico and in vivo approaches. Our results support the fact that state-of-the-art deep learning approaches developed for protein-peptide interaction modeling can reliably identify good candidate poses for the IP-TPP in interaction with the Neuropilin-1 receptor. The association of the IP with the TPP does not seem to affect the ability of the TPP to bind to Neuropilin-1. Molecular simulation results suggest that peptide IP-GG-LinTT1 in a cleaved form interacts with Neuropilin-1 in a more stable manner and has a more helical secondary structure than the cleaved IP-GG-iRGD. Surprisingly, in silico investigations also suggest that the non-cleaved TPPs can bind the Neuropilin-1 in a stable manner. The in vivo results using xenografts models show that both bifunctional peptides resulting from the combination of the IP and either LinTT1 or iRGD are effective against tumoral growth. The peptide iRGD-IP shows the highest stability to serum proteases degradation while having the same antitumoral effect as Lin TT1-IP, which is more sensitive to proteases degradation. Our results support the development of the TPP-IP strategy as therapeutic peptides against cancer.

Shared Molecular Signatures Across Zika Virus Infection and Multiple Sclerosis Highlight AP-1 Transcription Factor as a Potential Player in Post-ZIKV MS-Like Phenotypes.

Zika virus (ZIKV) is an arbovirus of the Flaviviridae genus that has rapidly disseminated from across the Pacific to the Americas. Robust evidence has indicated a crucial role of ZIKV in congenital virus syndrome, including neonatal microcephaly. Moreover, emerging evidence suggests an association between ZIKV infection and the development of an extensive spectrum of central nervous system inflammatory demyelinating diseases (CNS IDD), such as multiple sclerosis-like clinical phenotypes. However, the underlying mechanisms of host-pathogen neuro-immune interactions remain to be elucidated. This study aimed to identify common transcriptional signatures between multiple sclerosis (MS) and ZIKV infection to generate molecular interaction networks, thereby leading to the identification of deregulated processes and pathways, which could give an insight of these underlying molecular mechanisms. Our investigation included publicly available transcriptomic data from MS patients in either relapse or remission (RR-MS) and datasets of subjects acutely infected by ZIKV for both immune peripheral cells and central nervous system cells. The protein-protein interaction (PPI) analysis showed upregulated AP-1 transcription factors (JUN and FOS) among the top hub and bottleneck genes in RR-MS and ZIKV data. Gene enrichment analysis retrieved a remarkable presence of ontologies and pathways linked to oxidative stress responses, immune cell function, inflammation, interleukin signaling, cell division, and transcriptional regulation commonly enriched in both scenarios. Considering the recent findings concerning AP-1 function in immunological tolerance breakdown, regulation of inflammation, and its function as an oxidative stress sensor, we postulate that the ZIKV trigger may contribute as a boost for the activation of such AP-1-regulated mechanisms that could favor the development of MS-like phenotypes following ZIKV infection in a genetically susceptible individual.

Analysis of the Interactome of the Toxoplasma gondii Tgj1 HSP40 Chaperone.

Toxoplasma gondii is an obligate intracellular apicomplexan that causes toxoplasmosis in humans and animals. Central to its dissemination and pathogenicity is the ability to rapidly divide in the tachyzoite stage and infect any type of nucleated cell. Adaptation to different cell contexts requires high plasticity in which heat shock proteins (Hsps) could play a fundamental role. Tgj1 is a type I Hsp40 of T. gondii, an ortholog of the DNAJA1 group, which is essential during the tachyzoite lytic cycle. Tgj1 consists of a J-domain, ZFD, and DNAJ_C domains with a CRQQ C-terminal motif, which is usually prone to lipidation. Tgj1 presented a mostly cytosolic subcellular localization overlapping partially with endoplasmic reticulum. Protein-protein Interaction (PPI) analysis showed that Tgj1 could be implicated in various biological pathways, mainly translation, protein folding, energy metabolism, membrane transport and protein translocation, invasion/pathogenesis, cell signaling, chromatin and transcription regulation, and cell redox homeostasis among others. The combination of Tgj1 and Hsp90 PPIs retrieved only 70 interactors linked to the Tgj1-Hsp90 axis, suggesting that Tgj1 would present specific functions in addition to those of the Hsp70/Hsp90 cycle, standing out invasion/pathogenesis, cell shape motility, and energy pathway. Within the Hsp70/Hsp90 cycle, translation-associated pathways, cell redox homeostasis, and protein folding were highly enriched in the Tgj1-Hsp90 axis. In conclusion, Tgj1 would interact with a wide range of proteins from different biological pathways, which could suggest a relevant role in them.

Redox sensitive human mitochondrial aconitase and its interaction with frataxin: In vitro and in silico studies confirm that it takes two to tango.

Mitochondrial aconitase (ACO2) has been postulated as a redox sensor in the tricarboxylic acid cycle. Its high sensitivity towards reactive oxygen and nitrogen species is due to its particularly labile [4Fe-4S]2+ prosthetic group which yields an inactive [3Fe-4S]+ cluster upon oxidation. Moreover, ACO2 was found as a main oxidant target during aging and in pathologies where mitochondrial dysfunction is implied. Herein, we report the expression and characterization of recombinant human ACO2 and its interaction with frataxin (FXN), a protein that participates in the de novo biosynthesis of Fe-S clusters. A high yield of pure ACO2 (≥99%, 22 ± 2 U/mg) was obtained and kinetic parameters for citrate, isocitrate, and cis-aconitate were determined. Superoxide, carbonate radical, peroxynitrite, and hydrogen peroxide reacted with ACO2 with second-order rate constants of 108, 108, 105, and 102 M-1 s-1, respectively. Temperature-induced unfolding assessed by tryptophan fluorescence of ACO2 resulted in apparent melting temperatures of 51.1 ± 0.5 and 43.6 ± 0.2 °C for [4Fe-4S]2+ and [3Fe-4S]+ states of ACO2, sustaining lower thermal stability upon cluster oxidation. Differences in protein dynamics produced by the Fe-S cluster redox state were addressed by molecular dynamics simulations. Reactivation of [3Fe-4S]+-ACO2 by FXN was verified by activation assays and direct iron-dependent interaction was confirmed by protein-protein interaction ELISA and fluorescence spectroscopic assays. Multimer modeling and protein-protein docking predicted an ACO2-FXN complex where the metal ion binding region of FXN approaches the [3Fe-4S]+ cluster, supporting that FXN is a partner for reactivation of ACO2 upon oxidative cluster inactivation.

Molecular Interactions of the Copper Chaperone Atx1 of Paracoccidioides brasiliensis with Fungal Proteins Suggest a Crosstalk between Iron and Copper Homeostasis.

Paracoccidioides spp. are endemic fungi from Latin America that cause Paracoccidioidomycosis, a systemic disease. These fungi present systems for high-affinity metal uptake, storage, and mobilization, which counteract host nutritional immunity and mitigate the toxic effects of metals. Regarding Cu mobilization, the metallochaperone Atx1 is regulated according to Cu bioavailability in Paracoccidioides spp., contributing to metal homeostasis. However, additional information in the literature on PbAtx1 is scarce. Therefore, in the present work, we aimed to study the PbAtx1 protein-protein interaction networks. Heterologous expressed PbAtx1 was used in a pull-down assay with Paracoccidioides brasiliensis cytoplasmic extract. Nineteen proteins that interacted with PbAtx1 were identified by HPLC-MSE. Among them, a relevant finding was a Cytochrome b5 (PbCyb5), regulated by Fe bioavailability in Aspergillus fumigatus and highly secreted by P. brasiliensis in Fe deprivation. We validated the interaction between PbAtx1-PbCyb5 through molecular modeling and far-Western analyses. It is known that there is a relationship between Fe homeostasis and Cu homeostasis in organisms. In this sense, would PbAtx1-PbCyb5 interaction be a new metal-sensor system? Would it be supported by the presence/absence of metals? We intend to answer those questions in future works to contribute to the understanding of the strategies employed by Paracoccidioides spp. to overcome host defenses.

A Capsid Protein Fragment of a Fusagra-like Virus Found in Carica papaya Latex Interacts with the 50S Ribosomal Protein L17.

Papaya sticky disease is caused by the association of a fusagra-like and an umbra-like virus, named papaya meleira virus (PMeV) and papaya meleira virus 2 (PMeV2), respectively. Both viral genomes are encapsidated in particles formed by the PMeV ORF1 product, which has the potential to encode a protein with 1563 amino acids (aa). However, the structural components of the viral capsid are unknown. To characterize the structural proteins of PMeV and PMeV2, virions were purified from Carica papaya latex. SDS-PAGE analysis of purified virus revealed two major proteins of ~40 kDa and ~55 kDa. Amino-terminal sequencing of the ~55 kDa protein and LC-MS/MS of purified virions indicated that this protein starts at aa 263 of the deduced ORF1 product as a result of either degradation or proteolytic processing. A yeast two-hybrid assay was used to identify Arabidopsis proteins interacting with two PMeV ORF1 product fragments (aa 321-670 and 961-1200). The 50S ribosomal protein L17 (AtRPL17) was identified as potentially associated with modulated translation-related proteins. In plant cells, AtRPL17 co-localized and interacted with the PMeV ORF1 fragments. These findings support the hypothesis that the interaction between PMeV/PMeV2 structural proteins and RPL17 is important for virus-host interactions.

Conservation and divergence of the G-interfaces of Drosophila melanogaster septins.

Septins possess a conserved guanine nucleotide-binding (G) domain that participates in the stabilization of organized hetero-oligomeric complexes which assemble into filaments, rings and network-like structures. The fruit fly, Drosophila melanogaster, has five such septin genes encoding Sep1, Sep2, Sep4, Sep5 and Pnut. Here, we report the crystal structure of the heterodimer formed between the G-domains of Sep1 and Sep2, the first from an insect to be described to date. A G-interface stabilizes the dimer (in agreement with the expected arrangement for the Drosophila hexameric particle) and this bears significant resemblance to its human counterparts, even down to the level of individual amino acid interactions. On the other hand, a model for the G-interface formed between the two copies of Pnut which occupy the centre of the hexamer, shows important structural differences, including the loss of a highly favourable bifurcated salt-bridge network. Whereas wild-type Pnut purifies as a monomer, the reintroduction of the salt-bridge network results in stabilizing the dimeric interface in solution as shown by size exclusion chromatography and thermal stability measurements. Adaptive steered molecular dynamics reveals an unzipping mechanism for dimer dissociation which initiates at a point of electrostatic repulsion within the switch II region. Overall, the data contribute to a better understanding of the molecular interactions involved in septin assembly/disassembly.