Drug resistance in Vibrio cholerae strains isolated from clinical specimens

Cholera is a serious epidemic and endemic disease caused by the Gram-negative bacterium Vibrio cholerae. SXT is an integrative conjugation element (ICE) that was isolated from a V. cholerae; it encodes resistance to the antibiotics chloramphenicol, streptomycin and sulfamethoxazole/trimethoprim. One hundred seven V. cholerae O1 strains were collected from cholera patients in Iran from 2005 to 2007 in order to study the presence of SXT constin and antibiotic resistance.The study examined 107 Vibrio cholerae strains isolated from cholera prevalent in some Iranian provinces. Bacterial isolation and identification were carried out according to standard bacteriological methods. Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) to four antibiotics (chloramphenicol, streptomycin, sulfamethoxazole, and trimethoprim) were determined by broth microdilution method. PCR was employed to evaluate the presence of established antibiotic resistance genes and SXT constin using specific primer sets.The resistance of the clinical isolates to sulfamethoxazole, trimethoprime, chloramphenicol, and streptomycin was 97%, 99%, 99%, and 90%, respectively. The data obtained by PCR assay showed that the genes sulII, dfrA1, floR, strB, and sxt element were present in 95.3%, 95.3%, 81.3%, 95.3%, and 95.3% of the V. cholerae isolates.The Vibrio strains showed the typical multidrug-resistance phenotype of an SXT constin. They were resistant to sulfamethoxazole, trimethoprime, chloramphenicol, and streptomycin. The detected antibiotic resistance genes included dfrA for trimethoprim and floR, strB, sulII and int, respectively, for chloramphenicol, streptomycin, sulfamethoxazole, as well as the SXT element.     

Exploring biological processes involved in embryonic stem cell differentiation by analyzing proteomic data

Since, proteins carry out many functional roles in a cell with different concentrations, proteomics is likely a more appropriate approach to explain biological processes and cellular events than mRNA studies. Although, gene ontology provides a systematic and organized vocabulary of biological terms for proteins, we need more details to decide about the correct duty and annotation of proteins in a specific condition. One can assume that a change of protein concentration is related to a biological process of that protein with negligible error. Therefore, we can obtain more information about the function of proteins by studying these profiles. In this study, we used time-course proteomic data of a twenty day differentiation study of embryonic stem cells (ESCs) differentiating to embryoid bodies (EBs). Hierarchical clustering was used to cluster time-series concentration profile of proteins. Our results demonstrate that there are eleven active processes with distinct concentration profiles in this initial differentiation. According to the concentration profiles of proteins, we suggest new change points (or equivalently, new stages) in the course of embryonic differentiation.     

Genome-scale metabolic model-based engineering of Escherichia coli enhances recombinant single-chain antibody fragment production

Biotechnology Letters - Escherichia coli is an attractive and cost-effective cell factory for producing recombinant proteins such as single-chain variable fragments (scFvs). AntiEpEX-scFv is a...     

Isolation and characterization of a first set of polymorphic microsatellite markers in saffron, Crocus sativus (Iridaceae)

? Premise of the study: Twelve novel polymorphic microsatellite loci were developed and characterized from a repeat-enriched genomic library of Crocus sativus to study population and conservation genetics of this economically and medically important species. ? Methods and Results: The microsatellite loci were isolated using a modified Fast Isolation by AFLP of Sequences COntaining repeats (FIASCO) method. The average number of alleles per locus was 2.6. The observed and expected heterozygosities varied from 0.07 to 0.92 and 0.1 to 0.58, respectively. Polymorphic information content value ranged from 0.09 to 0.55 with an average of 0.34. Four out of twelve loci showed significant departures from Hardy-Weinberg equilibrium. ? Conclusions: The microsatellite markers reported here will be useful for evaluating genetic diversity and will likely serve as an ideal resource for use in marker-assisted breeding programs, germplasm analysis, and varietal identification.     

Impact of RNA structure on the prediction of donor and acceptor splice sites

Background  

gene identification in genomic DNA sequences by computational methods has become an important task in bioinformatics and computational gene prediction tools are now essential components of every genome sequencing project. Prediction of splice sites is a key step of all gene structural prediction algorithms.     

Conformational study of human serum albumin in pre-denaturation temperatures by differential scanning calorimetry, circular dichroism and UV spectroscopy

Thermal conformational changes of human serum albumin (HSA) in phosphate buffer, 10 mM at pH = 7 are investigated using differential scanning calorimetric (DSC), circular dichroism (CD) and UV spectroscopic methods. The results indicate that temperature increment from 25 degrees C to 55 degrees C induces reversible conformational changes in the structure of HSA. Conformational change of HSA are shown to be a three-step process. Interestingly, melting temperature of the last domain is equal to the maximum value of fever in pathological conditions, i.e. 42 degrees C. These conformational alterations are accompanied by a mild alteration of secondary structures. Study of HSA-SDS (sodium dodecyl sulphate) interaction at 45 degrees C and 35 degrees C reveals that SDS affects the HSA structure at least in three steps: the first two steps result in more stabilization and compactness of HSA structure, while the last one induces the unfolding of HSA. Since HSA has a more affinity for SDS at 45 degrees C compared to 35 degrees C, It is suggested that the net negative charge of HSA is decreased in fever, which results in the decrease of HSA-associated cations and plasma osmolarity, and consequently, heat removal via the increase in urine volume.     

Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism

Elementary modes (EMs) are steady-state metabolic flux vectors with minimal set of active reactions. Each EM corresponds to a metabolic pathway. Therefore, studying EMs is helpful for analyzing the production of biotechnologically important metabolites. However, memory requirements for computing EMs may hamper their applicability as, in most genome-scale metabolic models, no EM can be computed due to running out of memory. In this study, we present a method for computing randomly sampled EMs. In this approach, a network reduction algorithm is used for EM computation, which is based on flux balance-based methods. We show that this approach can be used to recover the EMs in the medium- and genome-scale metabolic network models, while the EMs are sampled in an unbiased way. The applicability of such results is shown by computing “estimated” control-effective flux values in Escherichia coli metabolic network.     

Correlations between genomic GC levels and optimal growth temperatures are not 'robust'

Musto et al. [FEBS Lett. 573 (2004) 73] studied the correlations between GC levels and optimal growth temperatures in 20 prokaryotic families. They reported that positive correlations are generally observed, and many of these are significant. Here, we have shown that these correlations are not "robust," i.e., correlation coefficients and/or significance of correlations can be considerably influenced by exclusion of very few (even as small as one) species from each dataset. The sensitivity of correlations is assumed as a result of high levels of bias in the family datasets. We concluded that solely based on these data, one cannot establish that GC contents of prokaryotic genomes increase as a result of growth temperature increments.