First-in-Class Inhibitors of Sulfur Metabolism with Bactericidal Activity against Non-Replicating M-tuberculosis

Development of effective therapies to eradicate persistent, slowly replicating M. tuberculosis (Mtb) represents a significant challenge to controlling the global TB epidemic. To develop such therapies, it is imperative to translate information from metabolome and proteome adaptations of persistent Mtb into the drug discovery screening platforms. To this end, reductive sulfur metabolism is genetically and pharmacologically implicated in survival, pathogenesis, and redox homeostasis of persistent Mtb. Therefore, inhibitors of this pathway are expected to serve as powerful tools in its preclinical and clinical validation as a therapeutic target for eradicating persisters. Here, we establish a first functional HTS platform for identification of APS reductase (APSR) inhibitors, a critical enzyme in the assimilation of sulfate for the biosynthesis of cysteine and other essential sulfur-containing molecules. Our HTS campaign involving 38?350 compounds led to the discovery of three distinct structural classes of APSR inhibitors. A class of bioactive compounds with known pharmacology displayed potent bactericidal activity in wild-type Mtb as well as MDR and XDR clinical isolates. Top compounds showed markedly diminished potency in a conditional Delta APSR mutant, which could be restored by complementation with Mtb APSR. Furthermore, ITC studies on representative compounds provided evidence for direct engagement of the APSR target. Finally, potent APSR inhibitors significantly decreased the cellular levels of key reduced sulfur-containing metabolites and also induced an oxidative shift in mycothiol redox potential of live Mtb, thus providing functional validation of our screening data. In summary, we have identified first-in-class inhibitors of APSR that can serve as molecular probes in unraveling the links between Mtb persistence, antibiotic tolerance, and sulfate assimilation, in addition to their potential therapeutic value.

Validation of polyvinylidene fluoride nasal sensor to assess nasal obstruction in comparison with subjective technique

Objective: The aim of this study is to validate the applicability of the PolyVinyliDene Fluoride (PVDF) nasal sensor to assess the nasal airflow, in healthy subjects and patients with nasal obstruction and to correlate the results with the score of Visual Analogue Scale (VAS). Methods: PVDF nasal sensor and VAS measurements were carried out in 50 subjects (25-healthy subjects and 25 patients). The VAS score of nasal obstruction and peak-to-peak amplitude (Vp-p) of nasal cycle measured by PVDF nasal sensors were analyzed for right nostril (RN) and left nostril (LN) in both the groups. Spearman's rho correlation was calculated. The relationship between PVDF nasal sensor measurements and severity of nasal obstruction (VAS score) were assessed by ANOVA. Results: In healthy group, the measurement of nasal airflow by PVDF nasal sensor for RN and LN were found to be 51.14 +/- 5.87% and 48.85 +/- 5.87%, respectively. In patient group, PVDF nasal sensor indicated lesser nasal airflow in the blocked nostrils (RN: 23.33 +/- 10.54% and LN: 32.24 +/- 11.54%). Moderate correlation was observed in healthy group (r = 0.710, p < 0.001 for RN and r = 0.651, p < 0.001 for LN), and moderate to strong correlation in patient group (r = 0.751, p < 0.01 for RN and r = 0.885, p < 0.0001 for LN). Conclusion: PVDF nasal sensor method is a newly developed technique for measuring the nasal airflow. Moderate to strong correlation was observed between PVDF nasal sensor data and VAS scores for nasal obstruction. In our present study, PVDF nasal sensor technique successfully differentiated between healthy subjects and patients with nasal obstruction. Additionally, it can also assess severity of nasal obstruction in comparison with VAS. Thus, we propose that the PVDF nasal sensor technique could be used as a new diagnostic method to evaluate nasal obstruction in routine clinical practice. (C) 2015 Elsevier Inc. All rights reserved.

Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity

Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Prediction and validation of gold nanoparticles (GNPs) on plant growth promoting rhizobacteria (PGPR): a step toward development of nano-biofertilizers

Several soil microbes are present in the rhizosphere zone, especially plant growth promoting rhizobacteria (PGPR), which are best known for their plant growth promoting activities. The present study reflects the effect of gold nanoparticles (GNPs) at various concentrations on the growth of PGPR. GNPs were synthesized chemically, by reduction of HAuCl 4, and further characterized by UV-Vis spectroscopy, X-ray diffraction technique (XRD), and transmission electron microscopy (TEM), etc. The impact of GNPs on PGPR was investigated by Clinical Laboratory Standards Institute (CLSI) recommended Broth-Microdilution technique against four selected PGPR viz., Pseudomonas fluorescens, Bacillus subtilis, Paenibacillus elgii, and Pseudomonas putida. Neither accelerating nor reducing impact was observed in P. putida due to GNPs. On the contrary, significant increase was observed in the case of P. fluorescens, P. elgii, and B. subtilis, and hence, GNPs can be exploited as nano-biofertilizers.

Validation of processing maps for 304L stainless steel using hot forging, rolling and extrusion

The development of a microstructure in 304L stainless steel during industrial hot-forming operations, including press forging (mean strain rate of 0.15 s(-1)), rolling/extrusion (2-5 s(-1)), and hammer forging (100 s(-1)) at different temperatures in the range 600-1200 degrees C, was studied with a view to validating the predictions of the processing map. The results have shown that excellent correlation exists between the regimes exhibited by the map and the product microstructures. 304L stainless steel exhibits instability bands when hammer forged at temperatures below 1100 degrees C, rolled/extruded below 1000 degrees C, or press forged below 800 degrees C. All of these conditions must be avoided in mechanical processing of the material. On the other hand, ideally, the material may be rolled, extruded, or press forged at 1200 degrees C to obtain a defect-free microstructure.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Standardization and validation of an induced ovulation model system in buffalo cows: Characterization of gene expression changes in the periovulatory follicle

In bovines characterization of biochemical and molecular determinants of the dominant follicle before and during different time intervals after gonadotrophin surge requires precise identification of the dominant follicle from a follicular wave. The objectives of the present study were to standardize an experimental model in buffalo cows for accurately identifying the dominant follicle of the first wave of follicular growth and characterize changes in follicular fluid hormone concentrations as well as expression patterns of various genes associated with the process of ovulation. From the day of estrus (day 0), animals were subjected to blood sampling and ultrasonography for monitoring circulating progesterone levels and follicular growth. On day 7 of the cycle, animals were administered a PGF2α analogue (Tiaprost Trometamol, 750 μg i.m.) followed by an injection of hCG (2000 IU i.m.) 36 h later. Circulating progesterone levels progressively increased from day 1 of the cycle to 2.26 ± 0.17 ng/ml on day 7 of the cycle, but declined significantly after PGF2α injection. A progressive increase in the size of the dominant follicle was observed by ultrasonography. The follicular fluid estradiol and progesterone concentrations in the dominant follicle were 600 ± 16.7 and 38 ± 7.6 ng/ml, respectively, before hCG injection and the concentration of estradiol decreased to 125.8 ± 25.26 ng/ml, but concentration of progesterone increased to 195 ± 24.6 ng/ml, 24 h post-hCG injection. Inh-α and Cyp19A1 expressions in granulosa cells were maximal in the dominant follicle and declined in response to hCG treatment. Progesterone receptor, oxytocin and cycloxygenase-2 expressions in granulosa cells, regarded as markers of ovulation, were maximal at 24 h post-hCG. The expressions of genes belonging to the super family of proteases were also examined; Cathepsin L expression decreased, while ADAMTS 3 and 5 expressions increased 24 h post-hCG treatment. The results of the current study indicate that sequential treatments of PGF2α and hCG during early estrous cycle in the buffalo cow leads to follicular growth that culminates in ovulation. The model system reported in the present study would be valuable for examining temporo-spatial changes in the periovulatory follicle immediately before and after the onset of gonadotrophin surge.

Validation-Based Sparse Gaussian Process Classifier Design

Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.

Influence of validation schemes in a laser Doppler anemometer period timing device for frequency measurement

The short duration of the Doppler signal and noise content in it necessitate a validation scheme to be incorporated in the electronic processor used for frequency measurement, There are several different validation schemes that can be employed in period timing devices. A detailed study of the influence of these validation schemes on the measured frequency has been reported here. These studies were carried out by using a combination of a fast A/D converter and computer. Doppler bursts obtained from an air flow were digitised and stored on magnetic discs. Suitable computer programs were then used to simulate the performance of period timing devices with different validation schemes and the frequency of the stored bursts were evaluated. It is found that best results are obtained when the validation scheme enables frequency measurement to be made over a large number of cycles within the burst.

Clinical and immunological studies on persons exposed toParthenium hysterophorus L

Studies on 300 persons subjected by occupational hazard to the allergenic weed, Parthenium hysterophorus L. for periods ranging from 3 to 12 months revealed that 4% of them developed contact dermatitis of the exposed parts of the body, while 56% of them got sensitized to the weed without apparently exhibiting any dermatitis. None of them suffered from allergic manifestations like rhinitis or bronchial asthma during the period of study which extended for 2 years.

A glimpse into the clinical proteome of human malaria parasites Plasmodium falciparum and Plasmodium vivax

Malaria causes a worldwide annual mortality of about a million people.Rapidly evolving drug-resistant species of the parasite have created a pressing need for the identification of new drug targets and vaccine candidates. By developing fractionation protocols to enrich parasites from low-parasitemia patient samples, we have carried out the first ever proteomics analysis of clinical isolates of early stages of Plasmodium falciparum (Pf) and P. vivax. Patient-derived malarial parasites were directly processed and analyzed using shotgun proteomics approach using high-sensitivity MS for protein identification. Our study revealed about 100 parasite-coded gene products that included many known drug targets such as Pf hypoxanthine guanine phosphoribosyl transferase, Pf L-lactate dehydrogenase, and Plasmepsins. In addition,our study reports the expression of several parasite proteins in clinical ring stages that have never been reported in the ring stages of the laboratory-cultivated parasite strain. This proof-of-principle study represents a noteworthy step forward in our understanding of pathways elaborated by the parasite within the malaria patient and will pave the way towards identification of new drug and vaccine targets that can aid malaria therapy.

Prevalence of multidrug-resistant Staphylococcus aureus in diabetics clinical samples

Antibiotic resistance in 40 Staphylococcus aureus clinical isolates from 110 diabetic patients (36%) was evaluated. Of these, 32 (80%) of the isolates showed multidrug-resistance to more than eight antibiotics and 35% isolates were found to be methicillin resistant S. aureus (MRSA). All 40 S. aureus strains (100%) screened from diabetic clinical specimens were resistant to penicillin, 63% to ampicillin, 55% to streptomycin, 50% to tetracycline and 50% to gentamicin. Where as low resistance rate was observed to ciprofloxacin (20%) and rifampicin (8%). In contrast, all (100%) S. aureus strains recorded susceptibility to teicoplanin, which was followed by vancomycin (95%). Genotypical examination revealed that 80% of the aminoglycoside resistant S. aureus (ARSA) have aminoglycoside modifying enzyme (AME) coding genes; however, 20% of ARSA which showed non-AME mediated (adaptive) aminoglycoside resistance lacked these genes in their genome. In contrast all MRSA isolates possessed mecA, femA genetic determinants in their genome.

Aminoglycoside-Resistance Mechanisms in Multidrug-Resistant Staphylococcus aureus Clinical Isolates

Aminoglycoside resistance in six clinically isolated Staphylococcus aureus was evaluated. Genotypical examination revealed that three isolates (HLGR-10, HLGR-12, and MSSA-21) have aminoglycoside-modifying enzyme (AME) coding genes and another three (GRSA-2, GRSA-4, and GRSA-6) lacked these genes in their genome. Whereas isolates HLGR-10 and HLGR-14 possessed bifunctional AME coding gene aac(6′)-aph(2′′), and aph(3′)-III and showed high-level resistance to gentamycin and streptomycin, MSSA-21 possessed aph(3′)-III and exhibited low resistance to gentamycin, streptomycin, and kanamycin. The remaining three isolates (GRSA-2, GRSA-4, and GRSA-6) exhibited low resistance to all the aminoglycosides because they lack aminoglycoside-modifying enzyme coding genes in their genome. The transmission electron microscopy of the three isolates revealed changes in cell size, shape, and septa formation, supporting the view that the phenomenon of adaptive resistance is operative in these isolates.