Sensitive fluorescence in situ hybridization signal detection in maize using directly labeled probes produced by high concentration DNA polymerase nick translation

The signal produced by fluorescence in situ hybridization (FISH) often is inconsistent among cells and sensitivity is low. Small DNA targets on the chromatin are difficult to detect. We report here an improved nick translation procedure for Texas red and Alexa Fluor 488 direct labeling of FISH probes. Brighter probes can be obtained by adding excess DNA polymerase I. Using such probes, a 30?kb yeast transgene, and the rp1, rp3 and zein multigene clusters were clearly detected.     

Biodeterioration of Mayan buildings at uxmal and tulum,Mexico

Uxmal and Tulum are two important Mayan sites in the Yucatan peninsula. The buildings are mainly composed of limestone and grey/black discoloration is seen on exposed walls and copious greenish biofilms on inner walls. The principal microorganisms detected on interior walls at both Uxmal and Tulum were cyanobacteria; heterotrophic bacteria and filamentous fungi were also present. A dark‐pigmented mitosporic fungus and Bacillus cereus, both isolated from Uxmal, were shown to be acidogenic in laboratory cultures. Cyanobacteria belonging to rock‐degrading genera Synechocystis and Gloeocapsa were identified at both sites. Surface analysis previously showed that calcium ions were present in the biofilms on buildings at Uxmal and Tulum, suggesting the deposition of biosolubilized stone. Apart from their potential to degrade the substrate, the coccoid cyanobacteria supply organic nutrients for bacteria and fungi, which can produce organic acids, further increasing stone degradation.     

Rational antibiotic design: in silico structural comparison of the functional cavities of penicillin-binding proteins and ß-lactamases

The class of ß-lactam antibiotics has proven highly efficient in targeting bacterial penicillin-binding proteins (PBP) leading to the blocking of the bacterial cell wall synthesis. However, the benefit of these drugs is limited because of bacterial resistance mechanisms; the most widespread resistance involves ß-lactamase enzymes (ßLACT) that inactivate ß-lactam-based molecules. We focused on PBPs and ßLACTs from enterobacteria, and performed a detailed in silico study of PBPs whose inactivation is lethal for the bacteria and of ßLACTs that have a PBP-type catalytic mechanism. The comparison of the sequences and structures of PBPs and ßLACTs shows an almost perfect conservation of the catalytic site, and a high spatial resemblance of the whole functional cavity despite a very low overall sequence identity. Some notable differences in the functional cavity were observed in the vicinity of the catalytic site: four tyrosines are well conserved in the PBPs, whereas the residues occurring at equivalent positions in the ßLACT families present other physicochemical properties. These tyrosines are thus good candidates to be targeted in designing new antibiotic molecules with increased affinity and specificity for PBPs, with the goal of overcoming drug resistance. Our analysis also identified residues that have similar characteristics in most ßLACT families and different properties in PBPs; these are interesting targets for new ligands that specifically inhibit ßLACT proteins. The in silico approach presented here can be extended to other protein systems in view of guiding and improving rational drug design.     

Does the neuropeptide somatostatin have therapeutic potential against schistosomiasis?

The neuropeptide hormone somatostatin is used to treat bleeding oesophageal varices and to reduce portal pressure, and can prevent progression to severe fibrosis in chronic liver disease. We believe that somatostatin can also have therapeutic potential against schistosomiasis, based on recent observations that severe morbidity symptoms are associated with low levels of host somatostatin in patients infected with Schistosoma mansoni. The administration of exogenous doses of this neuropeptide could therefore alleviate the pathology caused by schistosomiasis.     

Identification of conformational B-cell Epitopes in an antigen from its primary sequence

Background

One of the major challenges in the field of vaccine design is to predict conformational B-cell epitopes in an antigen. In the past, several methods have been developed for predicting conformational B-cell epitopes in an antigen from its tertiary structure. This is the first attempt in this area to predict conformational B-cell epitope in an antigen from its amino acid sequence.

Results

All Support vector machine (SVM) models were trained and tested on 187 non-redundant protein chains consisting of 2261 antibody interacting residues of B-cell epitopes. Models have been developed using binary profile of pattern (BPP) and physiochemical profile of patterns (PPP) and achieved a maximum MCC of 0.22 and 0.17 respectively. In this study, for the first time SVM model has been developed using composition profile of patterns (CPP) and achieved a maximum MCC of 0.73 with accuracy 86.59%. We compare our CPP based model with existing structure based methods and observed that our sequence based model is as good as structure based methods.

Conclusion

This study demonstrates that prediction of conformational B-cell epitope in an antigen is possible from is primary sequence. This study will be very useful in predicting conformational B-cell epitopes in antigens whose tertiary structures are not available. A web server CBTOPE has been developed for predicting B-cell epitope http://www.imtech.res.in/raghava/cbtope/.     

Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs

Background

Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences.

Results

We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%.

Conclusion

While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.     

Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein

Background  

A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed genes, clustering of genes and regulatory network. On other hand there are only few studies on relation between expression level and composition of nucleotide/protein sequence, using expression data. There is a need to understand why particular genes/proteins express more in particular conditions. In this study, we analyze 3468 genes of Saccharomyces cerevisiae obtained from Holstege et al., (1998) to understand the relationship between expression level and amino acid composition.     

Sensitive fluorescence in situ hybridization signal detection in maize using directly labeled probes produced by high concentration DNA polymerase nick translation

The signal produced by fluorescence in situ hybridization (FISH) often is inconsistent among cells and sensitivity is low. Small DNA targets on the chromatin are difficult to detect. We report here an improved nick translation procedure for Texas red and Alexa Fluor 488 direct labeling of FISH probes. Brighter probes can be obtained by adding excess DNA polymerase I. Using such probes, a 30 kb yeast transgene, and the rp1, rp3 and zein multigene clusters were clearly detected.     

A reference microsatellite kit to assess for genetic diversity of Sorghum bicolor (Poaceae)

? Premise of the study: Discrepancies in terms of genotyping data are frequently observed when comparing simple sequence repeat (SSR) data sets across genotyping technologies and laboratories. This technical concern introduces biases that hamper any synthetic studies or comparison of genetic diversity between collections. To prevent this for Sorghum bicolor, we developed a control kit of 48 SSR markers. ? Methods and Results: One hundred seventeen markers were selected along the genome to provide coverage across the length of all 10 sorghum linkage groups. They were tested for polymorphism and reproducibility across two laboratories (Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement [CIRAD], France, and International Crops Research Institute for the Semi-Arid Tropics [ICRISAT], India) using two commonly used genotyping technologies (polyacrylamide gel-based technology with LI-COR sequencing machines and capillary systems with ABI sequencing apparatus) with DNA samples from a diverse set of 48 S. bicolor accessions. ? Conclusions: A kit for diversity analysis (http://sat.cirad.fr/sat/sorghum_SSR_kit/) was developed. It contains information on 48 technically robust sorghum microsatellite markers and 10 DNA controls. It can further be used to calibrate sorghum SSR genotyping data acquired with different technologies and compare those to genetic diversity references.