Redox biology of Mycobacterium tuberculosis H37Rv: protein-protein interaction between GlgB and WhiB1 involves exchange of thiol-disulfide

<p>Abstract</p> <p>Background</p> <p><it>Mycobacterium tuberculosis</it>, an intracellular pathogen encounters redox stress throughout its life inside the host. In order to protect itself from the redox onslaughts of host immune system, <it>M. tuberculosis </it>appears to have developed accessory thioredoxin-like proteins which are represented by ORFs encoding WhiB-like proteins. We have earlier reported that WhiB1/Rv3219 is a thioredoxin like protein of <it>M. tuberculosis </it>and functions as a protein disulfide reductase. Generally thioredoxins have many substrate proteins. The current study aims to identify the substrate protein(s) of <it>M. tuberculosis </it>WhiB1.</p> <p>Results</p> <p>Using yeast two-hybrid screen, we identified alpha (1,4)-glucan branching enzyme (GlgB) of <it>M. tuberculosis </it>as a interaction partner of WhiB1. <it>In vitro </it>GST pull down assay confirmed the direct physical interaction between GlgB and WhiB1. Both mass spectrometry data of tryptic digests and <it>in vitro </it>labeling of cysteine residues with 4-acetamido-4' maleimidyl-stilbene-2, 2'-disulfonic acid showed that in GlgB, C⁹⁵and C⁶⁵⁸are free but C¹⁹³and C⁶¹⁷form an intra-molecular disulfide bond. WhiB1 has a C³⁷XXC⁴⁰motif thus a C⁴⁰S mutation renders C³⁷to exist as a free thiol to form a hetero-disulfide bond with the cysteine residue of substrate protein. A disulfide mediated binary complex formation between GlgB and WhiB1C⁴⁰S was shown by both in-solution protein-protein interaction and thioredoxin affinity chromatography. Finally, transfer of reducing equivalent from WhiB1 to GlgB disulfide was confirmed by 4-acetamido-4' maleimidyl-stilbene-2, 2'-disulfonic acid trapping by the reduced disulfide of GlgB. Two different thioredoxins, TrxB/Rv1471 and TrxC/Rv3914 of <it>M. tuberculosis </it>could not perform this reaction suggesting that the reduction of GlgB by WhiB1 is specific.</p> <p>Conclusion</p> <p>We conclude that <it>M. tuberculosis </it>GlgB has one intra-molecular disulfide bond which is formed between C¹⁹³and C⁶¹⁷. WhiB1, a thioredoxin like protein interacts with GlgB and transfers its electrons to the disulfide thus reduces the intra-molecular disulfide bond of GlgB. For the first time, we report that GlgB is one of the <it>in vivo </it>substrate of <it>M. tuberculosis </it>WhiB1.</p

Quantum dynamics in strong fluctuating fields

A large number of multifaceted quantum transport processes in molecular systems and physical nanosystems can be treated in terms of quantum relaxation processes which couple to one or several fluctuating environments. A thermal equilibrium environment can conveniently be modelled by a thermal bath of harmonic oscillators. An archetype situation provides a two-state dissipative quantum dynamics, commonly known under the label of a spin-boson dynamics. An interesting and nontrivial physical situation emerges, however, when the quantum dynamics evolves far away from thermal equilibrium. This occurs, for example, when a charge transferring medium possesses nonequilibrium degrees of freedom, or when a strong time-dependent control field is applied externally. Accordingly, certain parameters of underlying quantum subsystem acquire stochastic character. Herein, we review the general theoretical framework which is based on the method of projector operators, yielding the quantum master equations for systems that are exposed to strong external fields. This allows one to investigate on a common basis the influence of nonequilibrium fluctuations and periodic electrical fields on quantum transport processes. Most importantly, such strong fluctuating fields induce a whole variety of nonlinear and nonequilibrium phenomena. A characteristic feature of such dynamics is the absence of thermal (quantum) detailed balance.Comment: review article, Advances in Physics (2005), in pres

Analysis and prediction of cancerlectins using evolutionary and domain information

<p>Abstract</p> <p>Background</p> <p>Predicting the function of a protein is one of the major challenges in the post-genomic era where a large number of protein sequences of unknown function are accumulating rapidly. Lectins are the proteins that specifically recognize and bind to carbohydrate moieties present on either proteins or lipids. Cancerlectins are those lectins that play various important roles in tumor cell differentiation and metastasis. Although the two types of proteins are linked, still there is no computational method available that can distinguish cancerlectins from the large pool of non-cancerlectins. Hence, it is imperative to develop a method that can distinguish between cancer and non-cancerlectins.</p> <p>Results</p> <p>All the models developed in this study are based on a non-redundant dataset containing 178 cancerlectins and 226 non-cancerlectins in which no two sequences have more than 50% sequence similarity. We have applied the similarity search based technique, i.e. BLAST, and achieved a maximum accuracy of 43.25%. The amino acids compositional analysis have shown that certain residues (e.g. Leucine, Proline) were preferred in cancerlectins whereas some other (e.g. Asparatic acid, Asparagine) were preferred in non-cancerlectins. It has been found that the PROSITE domain "Crystalline beta gamma" was abundant in cancerlectins whereas domains like "SUEL-type lectin domain" were found mainly in non-cancerlectins. An SVM-based model has been developed to differentiate between the cancer and non-cancerlectins which achieved a maximum Matthew's correlation coefficient (MCC) value of 0.32 with an accuracy of 64.84%, using amino acid compositions. We have developed a model based on dipeptide compositions which achieved an MCC value of 0.30 with an accuracy of 64.84%. Thereafter, we have developed models based on split compositions (2 and 4 parts) and achieved an MCC value of 0.31, 0.32 with accuracies of 65.10% and 66.09%, respectively. An SVM model based on Position Specific Scoring Matrix (PSSM), generated by PSI-BLAST, was developed and achieved an MCC value of 0.36 with an accuracy of 68.34%. Finally, we have integrated the PROSITE domain information with PSSM and developed an SVM model that has achieved an MCC value of 0.38 with 69.09% accuracy.</p> <p>Conclusion</p> <p>BLAST has been found inefficient to distinguish between cancer and non-cancerlectins. We analyzed the protein sequences of cancer and non-cancerlectins and identified interesting patterns. We have been able to identify PROSITE domains that are preferred in cancer and non-cancerlectins and thus provided interesting insights into the two types of proteins. The method developed in this study will be useful for researchers studying cancerlectins, lectins and cancer biology. The web-server based on the above study, is available at <url>http://www.imtech.res.in/raghava/cancer_pred/</url></p

TNF-dependent regulation and activation of innate immune cells are essential for host protection against cerebral tuberculosis

BACKGROUND: Tuberculosis (TB) affects one third of the global population, and TB of the central nervous system (CNS-TB) is the most severe form of tuberculosis which often associates with high mortality. The pro-inflammatory cytokine tumour necrosis factor (TNF) plays a critical role in the initial and long-term host immune protection against Mycobacterium tuberculosis (M. tuberculosis) which involves the activation of innate immune cells and structure maintenance of granulomas. However, the contribution of TNF, in particular neuron-derived TNF, in the control of cerebral M. tuberculosis infection and its protective immune responses in the CNS were not clear. METHODS: We generated neuron-specific TNF-deficient (NsTNF / ) mice and compared outcomes of disease against TNF f/f control and global TNF / mice. Mycobacterial burden in brains, lungs and spleens were compared, and cerebral pathology and cellular contributions analysed by microscopy and flow cytometry after M. tuberculosis infection. Activation of innate immune cells was measured by flow cytometry and cell function assessed by cytokine and chemokine quantification using enzyme-linked immunosorbent assay (ELISA). RESULTS: Intracerebral M. tuberculosis infection of TNF / mice rendered animals highly susceptible, accompanied by uncontrolled bacilli replication and eventual mortality. In contrast, NsTNF / mice were resistant to infection and presented with a phenotype similar to that in TNF f/f control mice. Impaired immunity in TNF / mice was associated with altered cytokine and chemokine synthesis in the brain and characterised by a reduced number of activated innate immune cells. Brain pathology reflected enhanced inflammation dominated by neutrophil influx. CONCLUSION: Our data show that neuron-derived TNF has a limited role in immune responses, but overall TNF production is necessary for protective immunity against CNS-TB

Genome-Wide Functional Profiling Reveals Genes Required for Tolerance to Benzene Metabolites in Yeast

Benzene is a ubiquitous environmental contaminant and is widely used in industry. Exposure to benzene causes a number of serious health problems, including blood disorders and leukemia. Benzene undergoes complex metabolism in humans, making mechanistic determination of benzene toxicity difficult. We used a functional genomics approach to identify the genes that modulate the cellular toxicity of three of the phenolic metabolites of benzene, hydroquinone (HQ), catechol (CAT) and 1,2,4-benzenetriol (BT), in the model eukaryote Saccharomyces cerevisiae. Benzene metabolites generate oxidative and cytoskeletal stress, and tolerance requires correct regulation of iron homeostasis and the vacuolar ATPase. We have identified a conserved bZIP transcription factor, Yap3p, as important for a HQ-specific response pathway, as well as two genes that encode putative NAD(P)H:quinone oxidoreductases, PST2 and YCP4. Many of the yeast genes identified have human orthologs that may modulate human benzene toxicity in a similar manner and could play a role in benzene exposure-related disease

Mouse models of breast cancer metastasis

Metastatic spread of cancer cells is the main cause of death of breast cancer patients, and elucidation of the molecular mechanisms underlying this process is a major focus in cancer research. The identification of appropriate therapeutic targets and proof-of-concept experimentation involves an increasing number of experimental mouse models, including spontaneous and chemically induced carcinogenesis, tumor transplantation, and transgenic and/or knockout mice. Here we give a progress report on how mouse models have contributed to our understanding of the molecular processes underlying breast cancer metastasis and on how such experimentation can open new avenues to the development of innovative cancer therapy

New therapeutic targets in Alzheimer's disease: brain deregulation of calcium and zinc

The molecular determinants of Alzheimer's (AD) disease are still not completely known; however, in the past two decades, a large body of evidence has indicated that an important contributing factor for the disease is the development of an unbalanced homeostasis of two signaling cations: calcium (Ca2+) and zinc (Zn2+). Both ions serve a critical role in the physiological functioning of the central nervous system, but their brain deregulation promotes amyloid-β dysmetabolism as well as tau phosphorylation. AD is also characterized by an altered glutamatergic activation, and glutamate can promote both Ca2+ and Zn2+ dyshomeostasis. The two cations can operate synergistically to promote the generation of free radicals that further intracellular Ca2+ and Zn2+ rises and set the stage for a self-perpetuating harmful loop. These phenomena can be the initial steps in the pathogenic cascade leading to AD, therefore, therapeutic interventions aiming at preventing Ca2+ and Zn2+ dyshomeostasis may offer a great opportunity for disease-modifying strategies