Surface chemical characterisation of Paenibacillus polymyxa before and after adaptation to sulfide minerals

A heterotroph Paenibacillus polymyxa bacteria is adapted to pyrite, chalcopyrite, galena and sphalerite minerals by repeated subculturing the bacteria in the presence of the mineral until their growth characteristics became similar to the growth in the absence of mineral. The unadapted and adapted bacterial surface have been chemically characterised by zeta-potential, contact angle, adherence to hydrocarbons and FT-IR spectroscopic studies. The surface free energies of bacteria have been calculated by following the equation of state and surface tension component approaches. The aim of the present paper is to understand the changes in surface chemical properties of bacteria during adaptation to sulfide minerals and the projected consequences in bioflotation and bioflocculation processes. The mineral-adapted cells became more hydrophilic as compared to unadapted cells. There are no significant changes in the surface charge of bacteria before and after adaptation, and all the bacteria exhibit an iso-electric point below pH 2.5. The contact angles are observed to be more reliable for hydrophobicity assessment than the adherence to hydrocarbons. The Lifschitz–van der Waals/acid–base approach to calculate surface free energy is found to be relevant for mineral–bacteria interactions. The diffuse reflectance FT-IR absorbance bands for all the bacteria are the same illustrating similar surface chemical composition. However, the intensity of the bands for unadapted and adapted cells is significantly varied and this is due to different amounts of bacterial secretions underlying different growth conditions.

Identification of carbohydrate structures as receptors for localised adherent enteropathogenic Escherichia coli

Enteropathogenic Escherichia coli strains of diffused adherent (DA) and localised adherent (LA) phenotypes were tested for their ability to bind to glycolipids. DA strains did not bind to the glycolipids tested, while LA strains bound to asialo GM1, asialo GM2, globoside and lacto-N-neotetraose in decreasing order of avidity. The minimum common sequence among the four glycolipids could be delineated as GalNac β 1–4 Gal as the binding epitope with GalNac β 1–3 Gal and GlcNac β 1–3 Gal serving as relatively weaker binders. The binding was not inhibited by a variety of free oligosaccharides or by the neoglycoproteins tested. Adhesion-negative mutants of an enteropathogenic LA strain showed a markedly reduced binding to asialo GM1 indicating that the recognition of GalNac β 1–4 Gal was correlated with the ability to adhere to HeLa cells. Thus recognition and binding to glycolipids could play an important role in colonisation through adherence to intestinal surfaces.

Factors associated with 2009 pandemic influenza A (H1N1) vaccination acceptance among university students from India during the post-pandemic phase

Background: There was a low adherence to influenza A (H1N1) vaccination program among university students and health care workers during the pandemic influenza in many parts of the world. Vaccination of high risk individuals is one of the recommendations of World Health Organization during the post-pandemic period. It is not documented about the student's knowledge, attitude and willingness to accept H1N1 vaccination during the post-pandemic period. We aimed to analyze the student's knowledge, attitude and willingness to accept H1N1 vaccination during the post-pandemic period in India. Methods: Vaccine against H1N1 was made available to the students of Vellore Institute of Technology, India from September 2010. The data are based on a cross-sectional study conducted during October 2010 to January 2011 using a self-administered questionnaire with a representative sample of the student population (N = 802). Results: Of the 802 respondents, only 102/802 (12.7%) had been vaccinated and 105/802 (13%) planned to do so in the future, while 595/802 (74%) would probably or definitely not get vaccinated in the future. The highest coverage was among the female (65/102, 63.7%) and non-compliance was higher among men in the group (384/595; 64.5%) (p < 0.0001). The representation of students from school of Bio-sciences and Bio-technology among vaccinees is significantly higher than that of other schools. Majority of the study population from the three groups perceived vaccine against H1N1 as the effective preventive measure when compared to other preventive measures. 250/595 (42%) of the responders argued of not being in the risk group. The risk perception was significantly higher among female (p < 0.0001). With in the study group, 453/802 (56.4%) said that they got the information, mostly from media. Conclusions: Our study shows that the vaccination coverage among university students remains very low in the post-pandemic period and doubts about the safety and effectiveness of the vaccine are key elements in their rejection. Our results indicate a need to provide accessible information about the vaccine safety by scientific authorities and fill gaps and confusions in this regard.

New Insights into Optimal Discrete Rate Adaptation for Average Power Constrained Single and Multi-Node Systems

The throughput-optimal discrete-rate adaptation policy, when nodes are subject to constraints on the average power and bit error rate, is governed by a power control parameter, for which a closed-form characterization has remained an open problem. The parameter is essential in determining the rate adaptation thresholds and the transmit rate and power at any time, and ensuring adherence to the power constraint. We derive novel insightful bounds and approximations that characterize the power control parameter and the throughput in closed-form. The results are comprehensive as they apply to the general class of Nakagami-m (m >= 1) fading channels, which includes Rayleigh fading, uncoded and coded modulation, and single and multi-node systems with selection. The results are appealing as they are provably tight in the asymptotic large average power regime, and are designed and verified to be accurate even for smaller average powers.

Rationalization and prediction of drug resistant mutations in targets for clinical anti-tubercular drugs

Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.