The role of inflammation and matrix proteins in airway remodelling

Asthma is a chronic inflammatory disorder of the airways. Remodelling in asthma is defined as the structural changes seen in the airways of asthmatics in comparison to healthy controls. Progressive loss of lung function also seen in asthma might be caused by remodelling. The research aims of this thesis were to investigate inflammation and remodelling in the airways of different types of asthmatics and smokers. The association between inflammation and remodelling was also examined in a mouse model of allergic airway inflammation. Healthy smokers showed increased numbers of macrophages in the BAL with no changes in the inflammatory cells in biopsies. Macrophages seemed to be quite quiescent, since mRNA expression for a wide variety of inflammatory mediators, especially chemokines CCL3, CCL4, CCL5 and CCL20, secreted by macrophages was significantly lower than in healthy non-smokers. Attenuated macrophage activity in the airway lumen may render smokers more susceptible to airway infections and have an impact on the development of other airway pathology. Patients with diisocyanate-induced asthma (DIA) on inhaled corticosteroids (ICS) who still had non-specific bronchial hyperreactivity (NSBHR) at the end of the follow-up showed increased expression of TNF-α, IL-6 and IL-15 mRNA in BAL cells compared to those without NSBHR. In addition to being markers for poor prognosis and possible slight glucocorticoid resistance, these cytokines might aid in guiding the treatment of DIA. The increase in the thickness of tenascin-C layer in the bronchial basement membrane (BM) was much less than usually seen in other types of asthma, which might not make tenascin-C a good marker for DIA. OVA-induced tenascin-C expression in the lung was attenuated in STAT4-/- mice with impaired Th1-type immunity compared to WT mice. Interestingly, STAT6-/- mice with impaired Th2-type immunity showed tenascin-C expression levels similar to those of WT mice. The clearest difference between these two knockout strains in response to OVA was that STAT4-/- mice exhibited no upregulation of IFN-γ and TNF-α mRNA expression. Thus, tenascin-C expression was unexpectedly more related to Th1 type reactions. In vitro studies confirmed the results. Human fibroblasts stimulated by TNF-α and IFN-γ showed increased expression of tenascin-C. Patients with newly diagnosed asthma showed increased expression of laminin α2 in the bronchial BM in comparison to patients with asthma symptoms only and healthy controls. Both patients with asthma and those with only asthma symptoms showed increased expression of the laminin β2 chain in comparison to controls. Thus, laminin α2 expression differentiated patients with clinical asthma from patients with symptoms only. Furthermore, the expression of laminin α2 and β2 was associated with NSBHR, linking very specific remodelling events to clinical findings.

Temperature-Sensitive Src-Transformed Mdck Cells nn 3d Cultures as a Model of Malignant Transformation of Epithelial Cells

The equilibrium between cell proliferation, differentiation, and apoptosis is crucial for maintaining homeostasis in epithelial tissues. In order for the epithelium to function properly, individual cells must gain normal structural and functional polarity. The junctional proteins have an important role both in binding the cells together and in taking part in cell signaling. Cadherins form adherens junctions. Cadherins initiate the polarization process by first recognizing and binding the neighboring cells together, and then guiding the formation of tight junctions. Tight junctions form a barrier in dividing the plasma membranes to apical and basolateral membrane domains. In glandular tissues, single layered and polarized epithelium is folded into tubes or spheres, in which the basal side of the epithelial layer faces the outer basal membrane, and the apical side the lumen. In carcinogenesis, the differentiated architecture of an epithelial layer is disrupted. Filling of the luminal space is a hallmark of early epithelial tumors in tubular and glandular structures. In order for the transformed tumor cells to populate the lumen, enhanced proliferation as well as inhibition of apoptosis is required. Most advances in cancer biology have been achieved by using two-dimensional (2D) cell culture models, in which the cells are cultured on flat surfaces as monolayers. However, the 2D cultures are limited in their capacity to recapitulate the structural and functional features of tubular structures and to represent cell growth and differentiation in vivo. The development of three-dimensional (3D) cell culture methods enables the cells to grow and to be studied in a more natural environment. Despite the wide use of 2D cell culture models and the development of novel 3D culture methods, it is not clear how the change of the dimensionality of culture conditions alters the polarization and transformation process and the molecular mechanisms behind them. Src is a well-known oncogene. It is found in focal and adherens junctions of cultured cells. Active src disrupts cell-cell junctions and interferes with cell-matrix binding. It promotes cell motility and survival. Src transformation in 2D disrupts adherens junctions and the fibroblastic phenotype of the cells. In 3D, the adherens junctions are weakened, and in glandular structures, the lumen is filled with nonpolarized vital cells. Madin-Darby canine kidney (MDCK) cells are an epithelial cell type commonly used as a model for cell polarization. Its-src-transformed variants are useful model systems for analyzing the changes in cell morphology, and they play a role in src-induced malignant transformation. This study investigates src-transformed cells in 3D cell cultures as a model for malignant transformation. The following questions were posed. Firstly: What is the role of the composition and stiffness of the extracellular matrix (ECM) on the polarization and transformation of ts v-src MDCK cells in 3D cell cultures? Secondly: How do the culture conditions affect gene expression? What is the effect of v-src transformation in 2D and in 3D cell models? How does the shift from 2D to 3D affect cell polarity and gene expression? Thirdly: What is the role of survivin and its regulator phosphatase and tensin homolog protein (PTEN) in cell polarization and transformation, and in determining cell fate? How does their expression correlate with impaired mitochondrial function in transformed cells? In order to answer the above questions, novel methods of culturing and monitoring cells had to be created: novel 3D methods of culturing epithelial cells were engineered, enabling real time monitoring of a polarization and transformation process, and functional testing of 3D cell cultures. Novel 3D cell culture models and imaging techniques were created for the study. Attention was focused especially on confocal microscopy and live-cell imaging. Src-transformation disturbed the polarization of the epithelium by disrupting cell adhesion, and sensitized the cells to their environment. With active src, the morphology of the cell cluster depended on the composition and stiffness of the matrix. Gene expression studies revealed a broader impact of src transformation than mere continuous activity of src-kinase. In 2D cultures, src transformation altered the expression of immunological, actin cytoskeleton and extracellular matrix (ECM). In 3D, the genes regulating cell division, inhibition of apoptosis, cell metabolism, mitochondrial function, actin cytoskeleton and mechano-sensing proteins were altered. Surprisingly, changing the culture conditions from 2D to 3D affected also gene expression considerably. The microarray hit survivin, an inhibitor of apoptosis, played a crucial role in the survival and proliferation of src-transformed cells.

Generation of Flat and Curved Membranes by Inverse-BAR Domain Proteins

Biological membranes are tightly linked to the evolution of life, because they provide a way to concentrate molecules into partially closed compartments. The dynamic shaping of cellular membranes is essential for many physiological processes, including cell morphogenesis, motility, cytokinesis, endocytosis, and secretion. It is therefore essential to understand the structure of the membrane and recognize the players that directly sculpt the membrane and enable it to adopt different shapes. The actin cytoskeleton provides the force to push eukaryotic plasma membrane in order to form different protrusions or/and invaginations. It has now became evident that actin directly co-operates with many membrane sculptors, including BAR domain proteins, in these important events. However, the molecular mechanisms behind BAR domain function and the differences between the members of this large protein family remain largely unresolved. In this thesis, the structure and functions of the I-BAR domain family members IRSp53 and MIM were thoroughly analyzed. By using several methods such as electron microscopy and systematic mutagenesis, we showed that these I-BAR domain proteins bind to PI(4,5)P2-rich membranes, generate negative membrane curvature and are involved in the formation of plasma membrane protrusions in cells e.g. filopodia. Importantly, we characterized a novel member of the BAR-domain superfamily which we named Pinkbar. We revealed that Pinkbar is specifically expressed in kidney and epithelial cells, and it localizes to Rab13-positive vesicles in intestinal epithelial cells. Remarkably, we learned that the I-BAR domain of Pinkbar does not generate membrane curvature but instead stabilizes planar membranes. Based on structural, mutagenesis and biochemical work we present a model for the mechanism of the novel membrane deforming activity of Pinkbar. Collectively, this work describes the mechanism by which I-BAR domain proteins deform membranes and provides new information about the biological roles of these proteins. Intriguingly, this work also gives evidence that significant functional plasticity exists within the I-BAR domain family. I-BAR proteins can either generate negative membrane curvature or stabilize planar membrane sheets, depending on the specific structural properties of their I-BAR domains. The results presented in this thesis expand our knowledge on membrane sculpting mechanisms and shows for the first time how flat membranes can be generated in cells.

Prediction of separation factor in foam separation of proteins

A phenomenological model has been developed for predicting separation factors obtained in concentrating protein solutions using batch-foam columns. The model considers the adsorption of surface active proteins onto the air-water interface of bubbles, and drainage of liquid from the foam, which are the two predominant processes responsible for separation in foam columns. The model has been verified with data collected on casein and bovine serum albumin (BSA) solutions, for which adsorption isotherms are available in the literature. It has been found that an increase in liquid pool height above the gas distributor and the time allowed for drainage result in a better separation. Further, taller foam columns yield poorer separation at constant time of drainage. The model successfully predicts the observed results. (C) 1997 Elsevier Science Ltd.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Structural biology of Mycobacterium tuberculosis proteins: The Indian efforts

Among the many different objectives of large scale structural genomics projects are expanding the protein fold space, enhancing understanding of a model or disease-related organism, and providing foundations for structure-based drug discovery. Systematic analysis of protein structures of Mycobacterium tuberculosis has been ongoing towards meeting some of these objectives. Indian participation in these efforts has been enthusiastic and substantial. The proteins of M. tuberculosis chosen for structural analysis by the Indian groups span almost all the functional categories. The structures determined by the Indian groups have led to significant improvement in the biochemical knowledge on these proteins and consequently have started providing useful insights into the biology of M. tuberculosis. Moreover, these structures form starting points for inhibitor design studies, early results of which are encouraging. The progress made by Indian structural biologists in determining structures of M. tuberculosis proteins is highlighted in this review. (C) 2011 Elsevier Ltd. All rights reserved.

Utilizing Model Nanostructured Porous Inorganic Compounds Such as Silica to Beneficially Confine “Bio”-Relevant Molecules and Demonstrate their Potential in Therapeutics

Abstract | The importance of well-defined inorganic porous nanostructured materials in the context of biotechnological applications such as drug delivery and biomolecular sensing is reviewed here in detail. Under optimized conditions, the confinement of “bio”-relevant molecules such as pharmaceutical drugs, enzymes or proteins inside such inorganic nanostructures may be remarkably beneficial leading to enhanced molecular stability, activity and performance. From the point of view of basic research, molecular confinement inside nanostructures poses several formidable and intriguing problems of statistical mechanics at the mesoscopic scale. The theoretical comprehension of such non-trivial issues will not only aid in the interpretation of observed phenomena but also help in designing better inorganic nanostructured materials for biotechnological applications.

Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of similar to 1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (Rank Score), which correlated with the residue depth, and identify active-site residues. Using these correlations, similar to 98% of correct models of CcdB (RMSD <= 4 angstrom) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout.

Intrinsically disordered proteins and conformational noise Implications in cancer

Intrinsically disordered proteins, IDPs, are proteins that lack a rigid 3D structure under physiological conditions, at least in vitro. Despite the lack of structure, IDPs play important roles in biological processes and transition from disorder to order upon binding to their targets. With multiple conformational states and rapid conformational dynamics, they engage in myriad and often ``promiscuous'' interactions. These stochastic interactions between IDPs and their partners, defined here as conformational noise, is an inherent characteristic of IDP interactions. The collective effect of conformational noise is an ensemble of protein network configurations, from which the most suitable can be explored in response to perturbations, conferring protein networks with remarkable flexibility and resilience. Moreover, the ubiquitous presence of IDPs as transcriptional factors and, more generally, as hubs in protein networks, is indicative of their role in propagation of transcriptional (genetic) noise. As effectors of transcriptional and conformational noise, IDPs rewire protein networks and unmask latent interactions in response to perturbations. Thus, noise-driven activation of latent pathways could underlie state-switching events such as cellular transformation in cancer. To test this hypothesis, we created a model of a protein network with the topological characteristics of a cancer protein network and tested its response to a perturbation in presence of IDP hubs and conformational noise. Because numerous IDPs are found to be epigenetic modifiers and chromatin remodelers, we hypothesize that they could further channel noise into stable, heritable genotypic changes.

Biochemical Properties of MutT2 Proteins from Mycobacterium tuberculosis and M. smegmatis and Their Contrasting Antimutator Roles in Escherichia coli

Mycobacterium tuberculosis, the causative agent of tuberculosis, is at increased risk of accumulating damaged guanine nucleotides such as 8-oxo-dGTP and 8-oxo-GTP because of its residency in the oxidative environment of the host macrophages. By hydrolyzing the oxidized guanine nucleotides before their incorporation into nucleic acids, MutT proteins play a critical role in allowing organisms to avoid their deleterious effects. Mycobacteria possess several MutT proteins. Here, we purified recombinant M. tuberculosis MutT2 (MtuMutT2) and M. smegmatis MutT2 (MsmMutT2) proteins from M. tuberculosis (a slow grower) and M. smegmatis (fast growing model mycobacteria), respectively, for their biochemical characterization. Distinct from the Escherichia coli MutT, which hydrolyzes 8-oxo-dGTP and 8-oxo-GTP, the mycobacterial proteins hydrolyze not only 8-oxo-dGTP and 8-oxo-GTP but also dCTP and 5-methyl-dCTP. Determination of kinetic parameters (K-m and V-max) revealed that while MtuMutT2 hydrolyzes dCTP nearly four times better than it does 8-oxo-dGTP, MsmMutT2 hydrolyzes them nearly equally. Also, MsmMutT2 is about 14 times more efficient than MtuMutT2 in its catalytic activity of hydrolyzing 8-oxo-dGTP. Consistent with these observations, MsmMutT2 but not MtuMutT2 rescues E. coli for MutT deficiency by decreasing both the mutation frequency and A-to-C mutations (a hallmark of MutT deficiency). We discuss these findings in the context of the physiological significance of MutT proteins.

Interaction of Silver Nanoparticles with Serum Proteins Affects Their Antimicrobial Activity In Vivo

The emergence of multidrug-resistant bacteria is a global threat for human society. There exist recorded data that silver was used as an antimicrobial agent by the ancient Greeks and Romans during the 8th century. Silver nanoparticles (AgNPs) are of potential interest because of their effective antibacterial and antiviral activities, with minimal cytotoxic effects on the cells. However, very few reports have shown the usage of AgNPs for antibacterial therapy in vivo. In this study, we deciphered the importance of the chosen methods for synthesis and capping of AgNPs for their improved activity in vivo. The interaction of AgNPs with serum albumin has a significant effect on their antibacterial activity. It was observed that uncapped AgNPs exhibited no antibacterial activity in the presence of serum proteins, due to the interaction with bovine serum albumin (BSA), which was confirmed by UV-Vis spectroscopy. However, capped AgNPs with citrate or poly(vinylpyrrolidone)] exhibited antibacterial properties due to minimized interactions with serum proteins. The damage in the bacterial membrane was assessed by flow cytometry, which also showed that only capped AgNPs exhibited antibacterial properties, even in the presence of BSA. In order to understand the in vivo relevance of the antibacterial activities of different AgNPs, a murine salmonellosis model was used. It was conclusively proved that AgNPs capped with citrate or PVP exhibited significant antibacterial activities in vivo against Salmonella infection compared to uncapped AgNPs. These results clearly demonstrate the importance of capping agents and the synthesis method for AgNPs in their use as antimicrobial agents for therapeutic purposes.

Reaction dynamics under confinement: an exact path integral treatment of a two-stage model of stochastic gene expression

Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: Implications for three-dimensional modeling

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naive Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (approximate to 85%) and specific (approximate to 95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. Proteins 2014; 82:1219-1234. (c) 2013 Wiley Periodicals, Inc.

Re-analysis of cryoEM data on HCV IRES bound to 40S subunit of human ribosome integrated with recent structural information suggests new contact regions between ribosomal proteins and HCV RNA

In this study, we combine available high resolution structural information on eukaryotic ribosomes with low resolution cryo-EM data on the Hepatitis C Viral RNA (IRES) human ribosome complex. Aided further by the prediction of RNA-protein interactions and restrained docking studies, we gain insights on their interaction at the residue level. We identified the components involved at the major and minor contact regions, and propose that there are energetically favorable local interactions between 40S ribosomal proteins and IRES domains. Domain II of the IRES interacts with ribosomal proteins S5 and S25 while the pseudoknot and the downstream domain IV region bind to ribosomal proteins S26, S28 and S5. We also provide support using UV cross-linking studies to validate our proposition of interaction between the S5 and IRES domains II and IV. We found that domain IIIe makes contact with the ribosomal protein S3a (S1e). Our model also suggests that the ribosomal protein S27 interacts with domain IIIc while S7 has a weak contact with a single base RNA bulge between junction IIIabc and IIId. The interacting residues are highly conserved among mammalian homologs while IRES RNA bases involved in contact do not show strict conservation. IRES RNA binding sites for S25 and S3a show the best conservation among related viral IRESs. The new contacts identified between ribosomal proteins and RNA are consistent with previous independent studies on RNA-binding properties of ribosomal proteins reported in literature, though information at the residue level is not available in previous studies.

A Gaussian network model study suggests that structural fluctuations are higher for inactive states than active states of protein kinases

We performed Gaussian network model based normal mode analysis of 3-dimensional structures of multiple active and inactive forms of protein kinases. In 14 different kinases, a more number of residues (1095) show higher structural fluctuations in inactive states than those in active states (525), suggesting that, in general, mobility of inactive states is higher than active states. This statistically significant difference is consistent with higher crystallographic B-factors and conformational energies for inactive than active states, suggesting lower stability of inactive forms. Only a small number of inactive conformations with the DFG motif in the ``in'' state were found to have fluctuation magnitudes comparable to the active conformation. Therefore our study reports for the first time, intrinsic higher structural fluctuation for almost all inactive conformations compared to the active forms. Regions with higher fluctuations in the inactive states are often localized to the aC-helix, aG-helix and activation loop which are involved in the regulation and/or in structural transitions between active and inactive states. Further analysis of 476 kinase structures involved in interactions with another domain/protein showed that many of the regions with higher inactive-state fluctuation correspond to contact interfaces. We also performed extensive GNM analysis of (i) insulin receptor kinase bound to another protein and (ii) holo and apo forms of active and inactive conformations followed by multi-factor analysis of variance. We conclude that binding of small molecules or other domains/proteins reduce the extent of fluctuation irrespective of active or inactive forms. Finally, we show that the perceived fluctuations serve as a useful input to predict the functional state of a kinase.