IL-4Rα-Dependent Alternative Activation of Macrophages Is Not Decisive for Mycobacterium tuberculosis Pathology and Bacterial Burden in Mice

Classical activation of macrophages (caMph or M1) is crucial for host protection against Mycobacterium tuberculosis (Mtb) infection. Evidence suggests that IL-4/IL-13 alternatively activated macrophages (aaMph or M2) are exploited by Mtb to divert microbicidal functions of caMph. To define the functions of M2 macrophages during tuberculosis (TB), we infected mice deficient for IL-4 receptor α on macrophages (LysM^creIL-4Rα^-/lox) with Mtb. We show that absence of IL-4Rα on macrophages does not play a major role during infection with Mtb H37Rv, or the clinical Beijing strain HN878. This was demonstrated by similar mortality, bacterial burden, histopathology and T cell proliferation between infected wild-type (WT) and LysM^creIL-4Rα^-/lox mice. Interestingly, we observed no differences in the lung expression of inducible nitric oxide synthase (iNOS) and Arginase 1 (Arg1), well-established markers for M1/M2 macrophages among the Mtb-infected groups. Kinetic expression studies of IL-4/IL-13 activated bone marrow-derived macrophages (BMDM) infected with HN878, followed by gene set enrichment analysis, revealed that the MyD88 and IL-6, IL-10, G-CSF pathways are significantly enriched, but not the IL-4Rα driven pathway. Together, these results suggest that IL-4Rα-macrophages do not play a central role in TB disease progression.     

Structural adaptation of tooth enamel protein amelogenin in the presence of SDS micelles

Amelogenin, the major extracellular matrix protein of developing tooth enamel is intrinsically disordered. Through its interaction with other proteins and mineral, amelogenin assists enamel biomineralization by controlling the formation of highly organized enamel crystal arrays. We used circular dichroism (CD), dynamic light scattering (DLS), fluorescence, and NMR spectroscopy to investigate the folding propensity of recombinant porcine amelogenin rP172 following its interaction with SDS, at levels above critical micelle concentration. The rP172‐SDS complex formation was confirmed by DLS, while an increase in the structure moiety of rP172 was noted through CD and fluorescence experiments. Fluorescence quenching analyses performed on several rP172 mutants where all but one Trp was replaced by Tyr at different sequence regions confirmed that the interaction of amelogenin with SDS micelles occurs via the N‐terminal region close to Trp25 where helical segments can be detected by NMR. NMR spectroscopy and structural refinement calculations using CS‐Rosetta modeling confirm that the highly conserved N‐terminal domain is prone to form helical structure when bound to SDS micelles. Our findings reported here reveal interactions leading to significant changes in the secondary structure of rP172 upon treatment with SDS. These interactions may reflect the physiological relevance of the flexible nature of amelogenin and its sequence specific helical propensity that might enable it to structurally adapt with charged and potential targets such as cell surface, mineral, and other proteins during enamel biomineralization. © 2013 Wiley Periodicals, Inc. Biopolymers 101: 525–535, 2014.     

Nanobead-based interventions for the treatment and prevention of tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is one of the most devastating bacterial diseases to affect humans. M. tuberculosis is a robust pathogen that has evolved the capacity to survive and grow inside macrophage phagosomes. A cocktail of antibiotics has long been successfully used against M. tuberculosis but is becoming less effective owing to the emergence of multidrug resistance. The only available preventive vaccine, using Mycobacterium bovis bacille Calmette-Guérin, is considered to be ineffective against adult pulmonary TB, the most prevalent form of the disease. Here, we review the potential use of biodegradable nanoparticle-based anti-TB drug delivery systems that have been shown to be more effective against M. tuberculosis in animal models than conventional antibiotic treatment regimens. This technology also has substantial potential for vaccination and other therapeutic strategies against TB and other infectious diseases.     

VSGdb: a database for trypanosome variant surface glycoproteins,a large and diverse family of coiled coil proteins

Background  

Trypanosomes are coated with a variant surface glycoprotein (VSG) that is so densely packed that it physically protects underlying proteins from effectors of the host immune system. Periodically cells expressing a distinct VSG arise in a population and thereby evade immunity. The main structural feature of VSGs are two long α-helices that form a coiled coil, and sets of relatively unstructured loops that are distal to the plasma membrane and contain most or all of the protective epitopes. The primary structure of different VSGs is highly variable, typically displaying only ~20% identity with each other. The genome has nearly 2000 VSG genes, which are located in subtelomeres. Only one VSG gene is expressed at a time, and switching between VSGs primarily involves gene conversion events. The archive of silent VSGs undergoes diversifying evolution rapidly, also involving gene conversion. The VSG family is a paradigm for α helical coiled coil structures, epitope variation and GPI-anchor signals. At the DNA level, the genes are a paradigm for diversifying evolutionary processes and for the role of subtelomeres and recombination mechanisms in generation of diversity in multigene families. To enable ready availability of VSG sequences for addressing these general questions, and trypanosome-specific questions, we have created VSGdb, a database of all known sequences.     

Isolation and characterization of Anthraquinone from Streptomyces sp. ERINLG-26 with anticancer activity Against adenocarcinoma cell line COLO320

Applied Biochemistry and Microbiology - Anticancer activity of 9,10-anthraquinone isolated from soil-derived (Doddabetta forest, Nilgiris, Tamil Nadu, India) filamentous bacterium Streptomyces sp....     

Using workflows to explore and optimise named entity recognition for chemistry

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR.