Perezjunker4000

Gram-positive bacteria ubiquitously produce membrane vesicles (MVs), and although they contribute to biological functions, our knowledge regarding their composition and immunogenicity remains limited. Here we examine the morphology, contents and immunostimulatory functions of MVs produced by three Staphylococcus aureus strains; a methicillin resistant clinical isolate, a methicillin sensitive clinical isolate and a laboratory-adapted strain. We observed differences in the number and morphology of MVs produced by each strain and showed that they contain microbe-associated molecular patterns (MAMPs) including protein, nucleic acids and peptidoglycan. Analysis of MV-derived RNA indicated the presence of small RNA (sRNA). Furthermore, we detected variability in the amount and composition of protein, nucleic acid and peptidoglycan cargo carried by MVs from each S. aureus strain. S. aureus MVs activated Toll-like receptor (TLR) 2, 7, 8, 9 and nucleotide-binding oligomerization domain containing protein 2 (NOD2) signalling and promoted cytokine and chemokine release by epithelial cells, thus identifying that MV-associated MAMPs including DNA, RNA and peptidoglycan are detected by pattern recognition receptors (PRRs). Moreover, S. aureus MVs induced the formation of and colocalized with autophagosomes in epithelial cells, while inhibition of lysosomal acidification using bafilomycin A1 resulted in accumulation of autophagosomal puncta that colocalized with MVs, revealing the ability of the host to degrade MVs via autophagy. This study reveals the ability of DNA, RNA and peptidoglycan associated with MVs to activate PRRs in host epithelial cells, and their intracellular degradation via autophagy. These findings advance our understanding of the immunostimulatory roles of Gram-positive bacterial MVs in mediating pathogenesis, and their intracellular fate within the host.Extracellular vesicles (EVs) mediate the cross-talk between cancer cells and the cells of the surrounding Tumour Microenvironment (TME). Professional killer cells include Natural Killer (NK) cells and CD8+ Cytotoxic T-lymphocytes (CTLs), which represent some of the most effective immune defense mechanisms against cancer cells. Recent evidence supports the role of EVs released by NK cells and CTLs in killing cancer cells, paving the road to a possible therapeutic role for such EVs. This review article provides the state-of-the-art knowledge on the role of NK- and CTL-derived EVs as anticancer agents, focusing on the different functions of different sub-types of EVs. We also reviewed the current knowledge on the effects of cancer-derived EVs on NK cells and CTLs, identifying areas for future investigation in the emerging new field of EV-mediated immunotherapy of cancer.The global pandemic caused by the SARS-CoV-2 virus continues to spread. Infection with SARS- CoV-2 causes COVID-19, a disease of variable severity. Mutation has already altered the SARS-CoV-2 genome from its original reported sequence and continued mutation is highly probable. These mutations can (i) have no significant impact (they are silent), (ii) result in a complete loss or reduction of infectivity, or (iii) induce increase in infectivity. Physical generation, for research purposes, of viral mutations that could enhance infectivity are controversial and highly regulated. The primary purpose of this project was to evaluate the ability of the DeepNEU machine learning stem-cell simulation platform to enable rapid and efficient assessment of the potential impact of viral loss-of-function (LOF) and gain-of-function (GOF) mutations on SARS-CoV-2 infectivity. Our data suggest that SARS-CoV-2 infection can be simulated in human alveolar type lung cells. Simulation of infection in these lung cells can be used to model and assess the impact of LOF and GOF mutations in the SARS-CoV2 genome. We have also created a four- factor infectivity measure the DeepNEU Case Fatality Rate (dnCFR). dnCFR can be used to assess infectivity based on the presence or absence of the key viral proteins (NSP3, Spike-RDB, N protein, and M protein). dnCFR was used in this study, not to only assess the impact of different mutations on SARS-CoV2 infectivity, but also to categorize the effects of mutations as loss of infectivity or gain of infectivity events.SARS-CoV-2 and Influenza co-infection turned out to be a huge threat in recent times. The clinical presentation and disease severity is common in both the infection condition. The present paper deals with studying co-infection model system through systems biology approaches. Understanding signaling regulation in COVID-19 and co-infection model systems aid in the development of network-based models thereby suggesting intervention points for therapeutics. This paper highlights the aim of revealing such perturbations to decipher opportune mediating cross talks characterizing the deadly viral disease. The comparative analysis of both the models reveals major signaling protein NFκB and STAT1 playing a crucial role in establishing co-infection. By targeting these proteins at cellular level, it might help modulating the release of potent pro-inflammatory cytokines thereby taming the severity of the disease symptoms. Mathematical models developed here are precisely tailored and serves as a first step towards co-infection model offering flexibility and pitching towards therapeutic investigation.Glycoside hydrolases (GHs) are essential for plant biomass deconstruction. GH11 family consist of endo-β-1,4-xylanases which hydrolyze xylan, the second most abundant cell wall biopolymer after cellulose, into small bioavailable oligomers. Structural requirements for enzymatic mechanism of xylan hydrolysis is well described for GH11 members. However, over the last years, it has been discovered that some enzymes from GH11 family have a secondary binding sites (SBS), which modulate the enzymes activities, but mechanistic details of the molecular communication between the active site and SBS of the enzymes remain a conundrum. In the present work we structurally characterized GH11 xylanase from Paenibacillus xylanivorans A57 (PxXyn11B), a microorganism of agricultural importance, using protein crystallography and molecular dynamics simulations. The PxXyn11B structure was solved to 2.5 Å resolution and different substrates (xylo-oligosaccharides from X3 to X6), were modelled in its active and SBS sites. Molecular Dynamics (MD) simulations revealed an important role of SBS in the activity and conformational mobility of PxXyn11B, demonstrating that binding of the reaction products to the SBS of the enzyme stabilizes the N-terminal region and, consequently, the active site. Furthermore, MD simulations showed that the longer the ligand, the better is the stabilization within active site, and the positive subsites contribute less to the stabilization of the substrates than the negative ones. These findings provide rationale for the observed enzyme kinetics, shedding light on the conformational modulation of the GH11 enzymes via their SBS mediated by the positive molecular feedback loop which involve the products of the enzymatic reaction.Macroalgae is regarded as a promising third-generation marine biomass that can be utilized as a sustainable feedstock for bio-industry due to the high sugar level and absence of lignin. Alginate, composed of 1,4-linked D-mannuronate (M) and L-guluronate (G), is one of the major carbohydrates in brown macroalgae. It is difficult to be assimilated by most industrial microorganisms. Therefore, developing engineered microorganisms that can utilize alginate as a feedstock in order to produce natural products from marine biomass is critical. In this study, we isolated, characterized, and sequenced Vibrio sp. SP1 which rapidly grows using alginate as a sole carbon source. We further engineered this strain by introducing genes encoding enzymes under the control of synthetic expression cassettes to produce lycopene and β-carotene which are attractive phytochemicals owing to the antioxidant property. We confirmed that the engineered Vibrio sp. SP1 could successfully produce 2.13 ± 0.37 mg L-1 of lycopene, 2.98 ± 0.43 mg L-1 of β -carotene, respectively, from 10 g L-1 of alginate as a sole carbon source. Furthermore, our engineered strain could directly convert 60 g L-1 of brown macroalgae Sargassum fusiforme into 1.23 ± 0.21 mg L-1 of lycopene without any pretreatment which had been vitally required for the previous productions. As the first demonstrated strain to produce high-value product from Sargassum, Vibrio sp. SP1 is evaluated to be a desirable platform for the brown macroalgae-based biorefinery.Interactions between transmembrane (TM) proteins are fundamental for a wide spectrum of cellular functions, but precise molecular details of these interactions remain largely unknown due to the scarcity of experimentally determined three-dimensional complex structures. Computational techniques are therefore required for a large-scale annotation of interaction sites in TM proteins. Foxy-5 mouse Here, we present a novel deep-learning approach, DeepTMInter, for sequence-based prediction of interaction sites in α-helical TM proteins based on their topological, physiochemical, and evolutionary properties. Using a combination of ultra-deep residual neural networks with a stacked generalization ensemble technique DeepTMInter significantly outperforms existing methods, achieving the AUC/AUCPR values of 0.689/0.598. Across the main functional families of human transmembrane proteins, the percentage of amino acid sites predicted to be involved in interactions typically ranges between 10% and 25%, and up to 30% in ion channels. DeepTMInter is available as a standalone package at https//github.com/2003100127/deeptminter. The training and benchmarking datasets are available at https//data.mendeley.com/datasets/2t8kgwzp35.Since its introduction, nanopore sequencing has enhanced our ability to study complex microbial samples through the possibility to sequence long reads in real time using inexpensive and portable technologies. The use of long reads has allowed to address several previously unsolved issues in the field, such as the resolution of complex genomic structures, and facilitated the access to metagenome assembled genomes (MAGs). Furthermore, the low cost and portability of platforms together with the development of rapid protocols and analysis pipelines have featured nanopore technology as an attractive and ever-growing tool for real-time in-field sequencing for environmental microbial analysis. This review provides an up-to-date summary of the experimental protocols and bioinformatic tools for the study of microbial communities using nanopore sequencing, highlighting the most important and recent research in the field with a major focus on infectious diseases. An overview of the main approaches including targeted and shotgun approaches, metatranscriptomics, epigenomics, and epitranscriptomics is provided, together with an outlook to the major challenges and perspectives over the use of this technology for microbial studies.Modulation of the structure and function of biomaterials is essential for advancing bio-nanotechnology and biomedicine. Microtubules (MTs) are self-assembled protein polymers that are essential for fundamental cellular processes and key model compounds for the design of active bio-nanomaterials. In this in silico study, a 0.5 μs-long all-atom molecular dynamics simulation of a complete MT with approximately 1.2 million atoms in the system indicated that a nanosecond-scale intense electric field can induce the longitudinal opening of the cylindrical shell of the MT lattice, modifying the structure of the MT. This effect is field-strength- and temperature-dependent and occurs on the cathode side. A model was formulated to explain the opening on the cathode side, which resulted from an electric-field-induced imbalance between electric torque on tubulin dipoles and cohesive forces between tubulin heterodimers. Our results open new avenues for electromagnetic modulation of biological and artificial materials through action on noncovalent molecular interactions.