Beta-glucan activates microglia without inducing cytokine production in Dectin-1-dependent manner

Microglia are the resident mononuclear phagocytic cells that are critical for innate and adaptive responses within the CNS. Like other immune cells, microglia recognize and are activated by various pathogen-associated molecular patterns. beta-glucans are pathogen-associated molecular patterns present within fungal cell walls that are known to trigger protective responses in a number of immune cells. In an effort to better understand microglial responses to beta-glucans and the underlying response pathways, we sought to determine whether Dectin-1, a major beta-glucan receptor recently identified in leukocytes, plays a similar role in beta-glucan-induced activation in microglia. In this study, we report that Dectin-1 is indeed expressed on the surface of murine primary microglia, and engagement of the receptor with particulate beta-glucan resulted in an increase in tyrosine phosphorylation of spleen tyrosine kinase, a hallmark feature of the Dectin-1 signaling pathway. Moreover, phagocytosis of beta-glucan particles and subsequent intracellular production of reactive oxygen species were also mediated by Dectin-1. However, unlike in macrophages and dendritic cells, beta-glucan-mediated microglial activation did not result in significant production of cytokines or chemokines; thus, the interaction of microglial Dectin-1 with glucan elicits a unique response. Our results suggest that the Dectin-1 pathway may play an important role in antifungal immunity in the CNS.     

BiPPred: Combined sequence‐ and structure‐based prediction of peptide binding to the Hsp70 chaperone BiP

Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi‐scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence‐based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence‐based prediction models were fitted using this and other peptide binding data. A structure‐based position‐specific scoring matrix (SB‐PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB‐PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA‐based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi‐scale pipeline can readily be applied to other protein‐peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence‐based prediction models is not available. Proteins 2016; 84:1390–1407. © 2016 Wiley Periodicals, Inc.     

Database and tools for metabolic network analysis

Metabolic network analysis has attracted much attention in the area of systems biology. It has a profound role in understanding the key features of organism metabolic networks and has been successfully applied in several fields of systems biology, including in silico gene knockouts, production yield improvement using engineered microbial strains, drug target identification, and phenotype prediction. A variety of metabolic network databases and tools have been developed in order to assist research in these fields. Databases that comprise biochemical data are normally integrated with the use of metabolic network analysis tools in order to give a more comprehensive result. This paper reviews and compares eight databases as well as twenty one recent tools. The aim of this review is to study the different types of tools in terms of the features and usability, as well as the databases in terms of the scope and data provided. These tools can be categorised into three main types: standalone tools; toolbox-based tools; and web-based tools. Furthermore, comparisons of the databases as well as the tools are also provided to help software developers and users gain a clearer insight and a better understanding of metabolic network analysis. Additionally, this review also helps to provide useful information that can be used as guidance in choosing tools and databases for a particular research interest.     

Parkin Overexpression Ameliorates PrP106–126-Induced Neurotoxicity via Enhanced Autophagy in N2a Cells

Transmissible spongiform encephalopathies (TSEs) are caused by the accumulation of the abnormal prion protein scrapie (PrP^Sc). Prion protein aggregation, misfolding, and cytotoxicity in the brain are the major causes of neuronal dysfunction and ultimate neurodegeneration in all TSEs. Parkin, an E3 ubiquitin ligase, has been studied extensively in all major protein misfolding aggregating diseases, especially Parkinson’s disease and Alzheimer’s disease, but the role of parkin in TSEs remains unknown. Here we investigated the role of parkin in a prion disease cell model in which neuroblastoma2a (N2a) cells were treated with prion peptide PrP106–126. We observed a gradual decrease in the soluble parkin level upon treatment with PrP106–126 in a time-dependent manner. Furthermore, endogenous parkin colocalized with FITC-tagged prion fragment106–126. Overexpression of parkin in N2a cells via transfection repressed apoptosis by enhancing autophagy. Parkin-overexpressing cells also showed reductions in apoptotic BAX translocation to the mitochondria and cytochrome c release to the cytosol, which ultimately inhibited activation of proapoptotic caspases. Taken together, our findings reveal a parkin-mediated cytoprotective mechanism against PrP106–126 toxicity, which is a novel potential therapeutic target for treating prion diseases.     

Growth enhancement of black pepper (<Emphasis Type="Italic">Piper nigrum</Emphasis>) by a newly isolated <Emphasis Type="Italic">Bacillus tequilensis</Emphasis> NII-0943

A Gram positive, rod-shaped potential strain was selected from the pool of bacterial isolates obtained from the Western Ghats forest (India) on the basis of zone of P-solubilization activity. Identification based on 16S rRNA gene sequence revealed that the strain is of Bacillus species, sharing highest sequence similarity to Bacillus tequilensis NRRL B-41771^T (99.5%). Strain NII-0943 was able to produce good amount of indole acetic acid (IAA) and was positive for siderophore production. In addition to IAA and siderophore attributes, strain NII-0943 also possessed the characteristics like Ca₃(PO₄)₂ solubilization and growth in nitrogen-free medium. Seed inoculation with the strain NII-0943 resulted in significantly higher root initiation in black pepper cuttings grown under pots. The contents of nitrogen and phosphorus in both soil and plant were also enhanced significantly in treatments inoculated with these bacterial inocula. Hence, based on this evidence it is proposed that strain NII-0943 could be deployed as a plant growth-promoting inoculant to attain the desired results of bacterization.     

Genetic improvement of peanut (Arachis hypogea L.) genotypes by developing short duration hybrids

Peanut, the only cash crop of rainfed areas of Pakistan, is facing immense challenges due to global warming. Climatic factors particularly the temperature fluctuations and rain pattern shift significantly impact the production and yield of peanut and unavailability of resilient varieties exacerbate this impact. To deal with the cropping pattern change and yield losses, due to climate vagaries, a study was conducted to develop early maturing hybrids using line into tester mating design. The F₁ hybrids from the parental lines were produced in the year 2018 using Line × Tester mating design and then grown in the field in the year 2019 for further evaluation. The hybrids were evaluated based on the early maturity and yield-related attributes in comparison with the parental lines. Based on the general combining ability estimate, line V-3 (Golden), was found as best parent with highly significant values for plant height, days to peg formation, days to maturity, number of pegs per plant, number of pods per plants, number of seeds per plant, 100 pod weight 100 seed weight. Similarly, tester V-7 (PI 635006 01 SD) showed highly significant results of GCA for days to germination, day to 50% flowering, plant height, days to peg formation, days to maturity, number of pegs per plant, number of pods per plants, number of seeds per plant, 100 kernel weight, shelling percentage. All the combinations were evaluated for specific combining ability and significant results were observed for V-3 × V-4 (Golden × PI 619175 01 SD) and V-1 × V-6 (BARI-2000 × PI 564846 01 SD) by developing or maturity and yield-related attributes. The hybrid combinations V-3 × V-5 (Golden × PI 635006 01 SD) followed by V-3 × V-6 showed highly significant results for mid parent heterosis and better parent heterosis for days to 50% flowering, plant height, days to peg formation, number of pegs, days to maturity, number of mature seeds per plant, shelling ratio, 100 pod weight and 100 kernel weight. These parents and hybrid combinations with early maturity genes and high yield attributes can further be used for the development of short duration variety.