Metabolome based reaction graphs of M.tuberculosis and M.leprae: A comparative network analysis

Background. Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. Methodology/Principal Findings. Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. Conclusions. We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension.

Ring Resonators and Micro Fluidics: Novel Design for Drug/Disease Detection

MEMS systems are technologically developed from integrated circuit industry to create miniature sensors and actuators. Originally these semiconductor processes and materials were used to build electrical and mechanical systems, but expanded to include biological, optical fluidic magnetic and other systems 12]. Here a novel approach is suggested where in two different fields are integrated via moems, micro fluidics and ring resonators. It is well known at any preliminary stage of disease onset, many physiological changes occur in the body fluids like saliva, blood, urine etc. The drawback till now was that current calibrations are not sensitive enough to detect the minor physiological changes. This is overcome using optical detector techniques 1]. The basic concepts of ring resonators, with slight variations can be used for optical detection of these minute disease markers. A well known fact of ring resonators is that a change in refractive index will trigger a shift in the resonant wavelength 5]. The trigger for the wavelength shift in the case discussed will be the presence of disease agents. To trap the disease agents specific antibody has to be used (e. g. BSA).

Quantitation of spermatogenesis by DNA flow cytometry: Comparative study among six species of mammals

Suspensions of testicular germ cells from six species of mammals were prepared and stained for the DNA content with a fluorochrome (ethidium bromide) adopting a common technique and subjected to DNA flow cytometry. While uniform staining of the germ cells of the mouse, hamster, rat and monkey could be obtained by treating with 0.5% pepsin for 60 min followed by staining with ethidium bromide for 30 min, that of the guinea pig and rabbit required for optimal staining pepsinization for 90 min and treatment with ethidium bromide for 60 min. The procedure adopted here provided a uniform recovery of over 80% of germ cells with each one of the species tested and the cell population distributed itself according to the DNA content (expressed as C values) into 5 major classes-spermatogonia (2C), cells in S-phase, primary spermatocytes (4C), round spermatids (1C), and elongating/elongated spermatids (HC). Comparison of the DNA distribution pattern of the germ cell populations between species revealed little variation in the relative quantities of cells with 2C (8-11%), S-phase (6-9%), and 4C (6-9%) amount of DNA. Though the spermatid cell populations exhibited variations (1C:31-46%, HCI:7-20% and and HC2:11-25%) they represented the bulk of germ cells (70-80%). The overall conversion of 2C to 1C (1C:2C ratio) and meiotic transformation of 4C cells to IC (1C:4C ratio) kinetics were relatively constant between the species studied. The present study clearly demonstrates that DNA flow cytometry can be adopted with ease and assurance to quantify germ cell transformation and as such spermatogenesis by analysing a large number of samples with consistency both within and across the species barrier. Any variation from the norms in germ cell proportions observed following treatment, for e.g. hormonal stimulation or deprivation can then be ascribed due to a specific effect of the hormone/drug on single/multiple steps in germ cell transformation

A comparative analysis of regeneration in natural forests and joint forest management plantations in Uttara Kannada district, Western Ghats

Five villages undertaking joint forest management (JFM) were chosen in Uttara Kannada district, Karnataka for assessing regeneration in plantations and nearby natural forests of the village. Species number, stem density, diversity index, similarity in species composition in less disturbed and disturbed forests and plantations in the village were compared. Stem density was low in all the disturbed forests; however, the species number was low in disturbed forests of three villages and high in two villages. Plantations showed lower diversity values compared to the adjacent natural forests. Regeneration in all less disturbed forests was better compared to the disturbed counterparts. Villages were ranked based on number of landless families, per, capita forest available and number of cut stems. Assessment of village forests using ranks indicates that parameters such as per capita availability, cut stems in the forests may determine the success of JFM.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Use of Vertex Index in Structure-Activity Analysis and Design of Molecules

The last few decades have witnessed application of graph theory and topological indices derived from molecular graph in structure-activity analysis. Such applications are based on regression and various multivariate analyses. Most of the topological indices are computed for the whole molecule and used as descriptors for explaining properties/activities of chemical compounds. However, some substructural descriptors in the form of topological distance based vertex indices have been found to be useful in identifying activity related substructures and in predicting pharmacological and toxicological activities of bioactive compounds. Another important aspect of drug discovery e. g. designing novel pharmaceutical candidates could also be done from the distance distribution associated with such vertex indices. In this article, we will review the development and applications of this approach both in activity prediction as well as in designing novel compounds.

Conformational dynamics of HIV-1 protease: a comparative molecular dynamics simulation study with multiple amber force fields

Flap dynamics of HIV-1 protease (HIV-pr) controls the entry of inhibitors and substrates to the active site. Dynamical models from previous simulations are not all consistent with each other and not all are supported by the NMR results. In the present work, the er effect of force field on the dynamics of HIV-pr is investigated by MD simulations using three AMBER force fields ff99, ff99SB, and ff03. The generalized order parameters for amide backbone are calculated from the three force fields and compared with the NMR S2 values. We found that the ff99SB and ff03 force field calculated order parameters agree reasonably well with the NMR S2 values, whereas ff99 calculated values deviate most from the NMR order parameters. Stereochemical geometry of protein models from each force field also agrees well with the remarks from NMR S2 values. However, between ff99SB and ff03, there are several differences, most notably in the loop regions. It is found that these loops are, in general, more flexible in the ff03 force field. This results in a larger active site cavity in the simulation with the ff03 force field. The effect of this difference in computer-aided drug design against flexible receptors is discussed.

Comparative study on optical properties of Se-Zn-In and Se-Zn-Te-In chalcogenide glasses

In contemporary world optoelectronics materials are used in daily life owing to its verity of applications. Utility of these materials makes them attractive for investigations. Specifically study regarding optical properties of recent developed materials is worth for technical uses. Therefore, this work demonstrates a comparative study of extinction coefficient (K), real dielectric (epsilon') and imaginary dielectric (epsilon `') constants, refractive index (n) and optical energy band gap (E-g) with structural unit < r > for Se98-xZn2Inx (0 <= X-In <= 10) and Se93-yZn2Te5Iny (0 <= Y-In <= 10) chalcogenide glasses. Fixed amount of Te with increasing In concentration as cost of Se is largely influence the optical parameters of the materials. Values of optical parameters are obtained higher and lower respectively at thresholds structural units values. This comparative study demonstrates that enhanced values of optical parameters have been obtained for Te containing Se-Zn-In glasses.

A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India

[1] Evaporative fraction (EF) is a measure of the amount of available energy at the earth surface that is partitioned into latent heat flux. The currently operational thermal sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) on satellite platforms provide data only at 1000 m, which constraints the spatial resolution of EF estimates. A simple model (disaggregation of evaporative fraction (DEFrac)) based on the observed relationship between EF and the normalized difference vegetation index is proposed to spatially disaggregate EF. The DEFrac model was tested with EF estimated from the triangle method using 113 clear sky data sets from the MODIS sensor aboard Terra and Aqua satellites. Validation was done using the data at four micrometeorological tower sites across varied agro-climatic zones possessing different land cover conditions in India using Bowen ratio energy balance method. The root-mean-square error (RMSE) of EF estimated at 1000 m resolution using the triangle method was 0.09 for all the four sites put together. The RMSE of DEFrac disaggregated EF was 0.09 for 250 m resolution. Two models of input disaggregation were also tried with thermal data sharpened using two thermal sharpening models DisTrad and TsHARP. The RMSE of disaggregated EF was 0.14 for both the input disaggregation models for 250 m resolution. Moreover, spatial analysis of disaggregation was performed using Landsat-7 (Enhanced Thematic Mapper) ETM+ data over four grids in India for contrasted seasons. It was observed that the DEFrac model performed better than the input disaggregation models under cropped conditions while they were marginally similar under non-cropped conditions.

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

Comparative evaluation of inversion approaches of the radiative transfer model for estimation of crop biophysical parameters

The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

Recognizing drug targets using evolutionary information: implications for repurposing FDA-approved drugs against Mycobacterium tuberculosis H37Rv

Drug repurposing to explore target space has been gaining pace over the past decade with the upsurge in the use of systematic approaches for computational drug discovery. Such a cost and time-saving approach gains immense importance for pathogens of special interest, such as Mycobacterium tuberculosis H37Rv. We report a comprehensive approach to repurpose drugs, based on the exploration of evolutionary relationships inferred from the comparative sequence and structural analyses between targets of FDA-approved drugs and the proteins of M. tuberculosis. This approach has facilitated the identification of several polypharmacological drugs that could potentially target unexploited M. tuberculosis proteins. A total of 130 FDA-approved drugs, originally intended against other diseases, could be repurposed against 78 potential targets in M. tuberculosis. Additionally, we have also made an attempt to augment the chemical space by recognizing compounds structurally similar to FDA-approved drugs. For three of the attractive cases we have investigated the probable binding modes of the drugs in their corresponding M. tuberculosis targets by means of structural modelling. Such prospective targets and small molecules could be prioritized for experimental endeavours, and could significantly influence drug-discovery and drug-development programmes for tuberculosis.

Dual Drug Conjugate Loaded Nanoparticles for the Treatment of Cancer

Two antineoplastic agents, Imatinib (IM) and 5-Fluorouracil (FU) were conjugated by hydrolysable linkers through an amide bond and entrapped in polymeric Human Serum Albumin (HSA) nanoparticles. The presence of dual drugs in a common carrier has the advantage of reaching the site of action simultaneously and acting at different phases of the cell cycle to arrest the growth of cancer cells before they develop chemoresistance. The study has demonstrated an enhanced anticancer activity of the conjugate, and conjugate loaded stealth HSA nanoparticles (NPs) in comparison to the free drug in A-549 human lung carcinoma cell line and Zebra fish embryos (Danio rerio). Hydrolysability of the conjugate has also been demonstrated with complete hydrolysis being observed after 12 h. In vivo pharmacodynamics study in terms of tumor volume and pharmacokinetics in mice for conjugate (IM-SC-FU) and conjugate loaded nanoparticles showed significant anti-cancer activity. The other parameters evaluated were particle size (86nm), Poly Dispersive Index (PDI) (0.209), zeta potential (-49mV), drug entrapment efficiency (96.73%) and drug loading efficiency (89%). Being in stealth mode gives the potential for the NPs to evade Reticulo-Endothelial system (RES), achieve passive targeting by Enhanced Permeation Retention (EPR) effect with controlled release of the therapeutic agent. As the conjugate cleaves into individual drugs in the tumor environment, this promises better suppression of cancer chemoresistance by delivering dual drugs with different modes of action at the same site, thereby synergistically inhibiting the growth of cancerous tissue.

Disaggregation of LST over India: comparative analysis of different vegetation indices

The non-availability of high-spatial-resolution thermal data from satellites on a consistent basis led to the development of different models for sharpening coarse-spatial-resolution thermal data. Thermal sharpening models that are based on the relationship between land-surface temperature (LST) and a vegetation index (VI) such as the normalized difference vegetation index (NDVI) or fraction vegetation cover (FVC) have gained much attention due to their simplicity, physical basis, and operational capability. However, there are hardly any studies in the literature examining comprehensively various VIs apart from NDVI and FVC, which may be better suited for thermal sharpening over agricultural and natural landscapes. The aim of this study is to compare the relative performance of five different VIs, namely NDVI, FVC, the normalized difference water index (NDWI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI), for thermal sharpening using the DisTrad thermal sharpening model over agricultural and natural landscapes in India. Multi-temporal LST data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors obtained over two different agro-climatic grids in India were disaggregated from 960 m to 120 m spatial resolution. The sharpened LST was compared with the reference LST estimated from the Landsat data at 120 m spatial resolution. In addition to this, MODIS LST was disaggregated from 960 m to 480 m and compared with ground measurements at five sites in India. It was found that NDVI and FVC performed better only under wet conditions, whereas under drier conditions, the performance of NDWI was superior to other indices and produced accurate results. SAVI and MSAVI always produced poorer results compared with NDVI/FVC and NDWI for wet and dry cases, respectively.

Multi-drug resistance profiles and the genetic features of Acinetobacter baumannii isolates from Bolivia

Introduction: Acinetobacter baumannii is opportunistic in debilitated hospitalised patients. Because information from some South American countries was previously lacking, this study examined the emergence of multi-resistant A. baumannii in three hospitals in Cochabamba, Bolivia, from 2008 to 2009. Methodology: Multiplex PCR was used to identify the main resistance genes in 15 multi-resistant A. baumannii isolates. RT-PCR was used to measure gene expression. The genetic environment of these genes was also analysed by PCR amplification and sequencing. Minimum inhibitory concentrations were determined for key antibiotics and some were determined in the presence of an efflux pump inhibitor, 1-(1-napthylmethyl) piperazine. Results: Fourteen strains were found to be multi-resistant. Each strain was found to have the bla(OXA-58) gene with the ISAba3-like element upstream, responsible for over-expression of the latter and subsequent carbapenem resistance. Similarly, ISAba1, upstream of the bla(ADC) gene caused over-expression of the latter and cephalosporin resistance; mutations in the gyrA(Ser83 to Leu) and parC (Ser-80 to Phe) genes were commensurate with fluoroquinolone resistance. In addition, the adeA, adeB efflux genes were over-expressed. All 15 isolates were positive for at least two aminoglycoside resistance genes. Conclusion: This is one of the first reports analyzing the multi-drug resistance profile of A. baumannii strains isolated in Bolivia and shows that the over-expression of thebla(OXA-58), bla(ADC) and efflux genes together with aminoglycoside modifying enzymes and mutations in DNA topoisomerases are responsible for the multi-resistance of the bacteria and the subsequent difficulty in treating infections caused by them.