Analysis of Resistance to Antimicrobials and Presence of Virulence/Stress Response Genes in Campylobacter Isolates from Patients with Severe Diarrhoea

Campylobacter infections are a major cause of diarrhoea world-wide and two of the antimicrobials used for their control (erythromycin and ciprofloxacin) have been losing efficacy in recent years. In a sample of 174 genotyped isolates from the stools of patients with severe diarrhoea in Qatar, collected between 2005 and 2012, 63.2% showed resistance to ciprofloxacin, 8.6% to erythromycin, 0.57% to chloramphenicol and all were sensitive to gentamycin. While 33.9% of isolates were sensitive to all four antimicrobials, 59.8% were resistant to at least one, 6.3% were resistant to two and none showed resistance to three antimicrobials. There was no host sex- or age-dependence among isolates resistant to ciprofloxacin and erythromycin and no significant variation was found with the region of origin of the patients. All isolates were screened for the presence of 3 virulence factors (ciaB, cadF and cdtB) and two stress-response factors (htrB and clpP), all of which were present in more than 50% of the isolates. Host sex-, age- and region of origin-dependent variations in prevalence were found for some of these factors. Data analysis for the combination of virulence factors and their effect on antimicrobial resistance indicated that the prevalence of resistance to both erythromycin and ciprofloxacin was higher in isolates harbouring ciaB but not clpP. Prevalence of resistance to ciprofloxacin was similar in clpP positive and negative isolates also possessing htrB, while for htrB-negative isolates prevalence was higher in the absence of clpP. These results are discussed and their implications are highlighted.     

Prediction of B cell and T cell epitopes of DBLalpha domain in Plasmodium falciparum malaria vaccine candidate var gene

P. falciparum encodes PfEMP-1 which is important in pathogenicity and virulence. We have analyzed the structure of the Duffy binding like (DBLalpha) domain of var genes and predicted the antigenic sites and T and B cell epitopes which present a highly variable picture with major implications in immune interactions and vaccine design.     

Oxypred： Prediction and Classification of Oxygen-Binding Proteins

This study describes a method for predicting and classifying oxygen-binding pro- teins. Firstly, support vector machine (SVM) modules were developed using amino acid composition and dipeptide composition for predicting oxygen-binding pro- teins, and achieved maximum accuracy of 85.5% and 87.8%, respectively. Sec- ondly, an SVM module was developed based on amino acid composition, classify- ing the predicted oxygen-binding proteins into six classes with accuracy of 95.8%, 97.5%, 97.5%, 96.9%, 99.4%, and 96.0% for erythrocruorin, hemerythrin, hemo- cyanin, hemoglobin, leghemoglobin, and myoglobin proteins, respectively. Finally, an SVM module was developed using dipeptide composition for classifying the oxygen-binding proteins, and achieved maximum accuracy of 96.1%, 98.7%, 98.7%, 85.6%, 99.6%, and 93.3% for the above six classes, respectively. All modules were trained and tested by five-fold cross validation. Based on the above approach, a web server Oxypred was developed for predicting and classifying oxygen-binding proteins(available from http://www.imtech.res.in/raghava/oxypred/).     

Carboxymethyl cellulase production optimization from Glutamicibacter arilaitensis strain ALA4 and its application in lignocellulosic waste biomass saccharification

Abstract

In this context, carboxymethyl cellulase (CMCase) production from Glutamicibacter arilaitensis strain ALA4 was initially optimized by one factor at a time (OFAT) method using goat dung as proficient feedstock. Two-level full factorial design (2⁵ factorial matrix) using first-order polynomial model revealed the significant (p?<?0.05) influence of pH, moisture, and peptone on CMCase activity. Central composite design at N?=?20 was further taken into account using a second-order polynomial equation, and thereby liberated maximum CMCase activity of 4925.56?±?31.61?U/g in the goat dung medium of pH 8.0 and 100% moisture containing 1% (w/w) peptone, which was approximately two fold increment with respect to OFAT method. Furthermore, the partially purified CMCase exhibited stability not only at high pH and temperature but also in the presence of varied metal ions, organic solvents, surfactants, and inhibitors with pronounced residual activities. The enzymatic hydrolysis using partially purified CMCase depicted the maximum liberation of fermentable sugars from alkali pretreated lignocellulosic wastes biomass in the order of paddy straw (13.8?±?0.15?mg/g)?>?pomegranate peel (9.1?±?0.18?mg/g)?>?sweet lime peel (8.37?±?0.16?mg/g), with saccharification efficiency of 62.1?±?0.8, 40.95?±?0.4, and 37.66?±?0.4%, respectively after 72?hr of treatment.     

‘Clustering’ SIRPα into the Plasma Membrane Lipid Microdomains Is Required for Activated Monocytes and Macrophages to Mediate Effective Cell Surface Interactions with CD47

SIRPα, an ITIMs-containing signaling receptor, negatively regulates leukocyte responses through extracellular interactions with CD47. However, the dynamics of SIRPα-CD47 interactions on the cell surface and the governing mechanisms remain unclear. Here we report that while the purified SIRPα binds to CD47 and that SIRPα is expressed on monocytes and monocytic THP-1 or U937, these SIRPα are ineffective to mediate cell binding to immobilized CD47. However, cell binding to CD47 is significantly enhanced when monocytes transmigrating across endothelia, or being differentiated into macrophages. Cell surface labeling reveals SIRPα to be diffused on naïve monocytes but highly clustered on transmigrated monocytes and macrophages. Protein crosslink and equilibrium centrifugation confirm that SIRPα in the latter cells forms oligomerized complexes resulting in increased avidity for CD47 binding. Furthermore, formation of SIRPα complexes/clusters requires the plasma membrane ‘lipid rafts’ and the activity of Src family kinase during macrophage differentiation. These results together suggest that ‘clustering’ SIRPα into plasma membrane microdomains is essential for activated monocytes and macrophages to effectively interact with CD47 and initiate intracellular signaling.     

A facile and rapid method for green synthesis of Achyranthes aspera stem extract-mediated silver nano-composites with cidal potential against Aedes aegypti L.

Aedes aegypti L. is the primary vector associated with transmission of globally concerned diseases; Zika, yellow fever, dengue and Chikungunya. Present study investigates an efficient, alternative and comparative approach for mosquito control which is safe to environment and non-target organisms. The silver nano-composites (AgNCs) were synthesized from the aqueous stem extract of Achyranthes aspera (AASE) using different concentration of aqueous silver nitrate (AgNO₃). The synthesis was tracked by UV-vis spectrophotometer and particle size analyser (DLS). The evaluation of their larvicidal potential against early fourth instars of Ae. aegypti showed significant potency, the toxicity increasing with the concentration of silver nitrate. The 24, 48 and 72 h bioassays resulted in respective LC₅₀ values of 26.693, 1.113 and 0.610 μg/mL (3 mM AASE-AgNO₃) 9.119, 0.420 and 0.407 μg/mL (4 mM AASE-AgNO₃) and that of 4.283, 0.3 and 0.248 μg/mL (5 mM AASE-AgNO₃). Keeping in view the significantly high larvicidal efficiency at lower concentration of silver nitrate, the 4 mM nano-composites were selected over 5 mM composites for further biophysical characterization carried out by X-ray Diffraction (XRD), Fourier transform infrared spectrometer (FTIR), Scanning electron microscopy (SEM), Energy dispersive X-ray (EDX) spectroscopy and Transmission electron microscopy (TEM). SEM and TEM confirmed the synthesis of spherical poly-dispersed AgNCs with average size ranging from 1–30 nm. Characterization through XRD showed the crystalline face-centered-cubic (fcc) structure of AgNCs with the highest intense peak obtained at 2θ value of 31.82°. FT-IR data suggests complex nature of AgNCs showing clearly defined peaks in different ranges. The present investigations recommend AgNCs of A. aspera stems as a low-cost and eco-friendly alternative to chemical insecticides for mosquito control.     

Analysis of the grasspea proteome and identification of stress-responsive proteins upon exposure to high salinity, low temperature, and abscisic acid treatment

Abiotic stress causes diverse biochemical and physiological changes in plants and limits crop productivity. Plants respond and adapt to such stress by altering their cellular metabolism and activating various defense machineries. To understand the molecular basis of stress tolerance in plants, we have developed differential proteomes in a hardy legume, grasspea (Lathyrus sativus L.). Five-week-old grasspea seedlings were subjected independently to high salinity, low temperature and abscisic acid treatment for duration of 36 h. The physiological changes of stressed seedlings were monitored, and correlated with the temporal changes of proteome using two-dimensional gel electrophoresis. Approximately, 400 protein spots were detected in each of the stress proteome with one-fourth showing more than 2-fold differences in expression values. Eighty such proteins were subjected to LC-tandem MS/MS analyses that led to the identification of 48 stress-responsive proteins (SRPs) presumably involved in a variety of functions, including metabolism, signal transduction, protein biogenesis and degradation, and cell defense and rescue. While 33 proteins were responsive to all three treatments, 15 proteins were expressed in stress-specific manner. Further, we explored the possible role of ROS in triggering the stress-induced degradation of large subunit (LSU) of ribulose-1,5-bisphosphate carboxylase (Rubisco). These results might help in understanding the spectrum of stress-regulated proteins and the biological processes they control as well as having implications for strategies to improve stress adaptation in plants.     

Profiling the humoral immune response of acute and chronic Q fever by protein microarray

Antigen profiling using comprehensive protein microarrays is a powerful tool for characterizing the humoral immune response to infectious pathogens. Coxiella burnetii is a CDC category B bioterrorist infectious agent with worldwide distribution. In order to assess the antibody repertoire of acute and chronic Q fever patients we have constructed a protein microarray containing 93% of the proteome of Coxiella burnetii, the causative agent of Q fever. Here we report the profile of the IgG and IgM seroreactivity in 25 acute Q fever patients in longitudinal samples. We found that both early and late time points of infection have a very consistent repertoire of IgM and IgG response, with a limited number of proteins undergoing increasing or decreasing seroreactivity. We also probed a large collection of acute and chronic Q fever patient samples and identified serological markers that can differentiate between the two disease states. In this comparative analysis we confirmed the identity of numerous IgG biomarkers of acute infection, identified novel IgG biomarkers for acute and chronic infections, and profiled for the first time the IgM antibody repertoire for both acute and chronic Q fever. Using these results we were able to devise a test that can distinguish acute from chronic Q fever. These results also provide a unique perspective on isotype switch and demonstrate the utility of protein microarrays for simultaneously examining the dynamic humoral immune response against thousands of proteins from a large number of patients. The results presented here identify novel seroreactive antigens for the development of recombinant protein-based diagnostics and subunit vaccines, and provide insight into the development of the antibody response.     

Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6–40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.