Diversity of lactic acid bacteria of the bioethanol process

Background  

Bacteria may compete with yeast for nutrients during bioethanol production process, potentially causing economic losses. This is the first study aiming at the quantification and identification of Lactic Acid Bacteria (LAB) present in the bioethanol industrial processes in different distilleries of Brazil.     

Molecular epidemiology and phylogeny reveal complex spatial dynamics in areas where canine parvovirus is endemic

Canine parvovirus type 2 (CPV-2) is a severe enteric pathogen of dogs, causing high mortality in unvaccinated dogs. After emerging, CPV-2 spread rapidly worldwide. However, there is now some evidence to suggest that international transmission appears to be more restricted. In order to investigate the transmission and evolution of CPV-2 both nationally and in relation to the global situation, we have used a long-range PCR to amplify and sequence the full VP2 gene of 150 canine parvoviruses obtained from a large cross-sectional sample of dogs presenting with severe diarrhea to veterinarians in the United Kingdom, over a 2-year period. Among these 150 strains, 50 different DNA sequence types (S) were identified, and apart from one case, all appeared unique to the United Kingdom. Phylogenetic analysis provided clear evidence for spatial clustering at the international level and for the first time also at the national level, with the geographical range of some sequence types appearing to be highly restricted within the United Kingdom. Evolution of the VP2 gene in this data set was associated with a lack of positive selection. In addition, the majority of predicted amino acid sequences were identical to those found elsewhere in the world, suggesting that CPV VP2 has evolved a highly fit conformation. Based on typing systems using key amino acid mutations, 43% of viruses were CPV-2a, and 57% CPV-2b, with no type 2 or 2c found. However, phylogenetic analysis suggested complex antigenic evolution of this virus, with both type 2a and 2b viruses appearing polyphyletic. As such, typing based on specific amino acid mutations may not reflect the true epidemiology of this virus. The geographical restriction that we observed both within the United Kingdom and between the United Kingdom and other countries, together with the lack of CPV-2c in this population, strongly suggests the spread of CPV within its population may be heterogeneously subject to limiting factors. This cross-sectional study of national and global CPV phylogeographic segregation reveals a substantially more complex epidemic structure than previously described.     

DNA adducts formed from 4-hydroxytamoxifen are more mutagenic than those formed by alpha-acetoxytamoxifen in a shuttle vector target gene replicated in human Ad293 cells

The drug tamoxifen, used to treat breast cancer, causes liver cancer in rats and endometrial cancer in women. Tamoxifen forms liver DNA adducts in both short- and long-term dosing of rodents, and DNA adducts have also been reported in tissues of women undergoing tamoxifen therapy. It is not known if the induction of endometrial cancer in women is through these DNA adducts or through the estrogenic nature of the drug. In this study, we have investigated the mutagenicity of two model reactive intermediates of tamoxifen, alpha-acetoxytamoxifen and 4-hydroxytamoxifen quinone methide (4-OHtamQM). These form the same DNA adducts as those found in tamoxifen-treated rats. The two compounds were used to treat the pSP189 plasmid containing the supF gene, which was replicated in Ad293 cells before being screened in indicator bacteria. Plasmid reacted with 4-OHtamQM was more likely to be mutated (2-7-fold increase) than that reacted with alpha-acetoxytamoxifen, despite having a lower level of DNA damage (12-20-fold less), as assayed by (32)P-postlabeling. The two compounds induced statistically different mutation spectra in the supF gene. The majority of mutations in alpha-acetoxytamoxifen-treated plasmid were GC -->TA transversions while GC-->AT transitions were formed in 4-OHtamQM-treated plasmid. 4-OHTamQM-treated DNA induced a larger proportion of multiple mutations and large deletions compared to alpha-acetoxytamoxifen. Sites of mutational hotspots were observed for both compounds. In conclusion, the quantitatively minor DNA adduct of tamoxifen (dG-N(2)-4-hydroxytamoxifen) is more mutagenic than the major tamoxifen DNA adduct (dG-N(2)-tamoxifen).     

The Capsid Gene of Feline Calicivirus Contains Linear B-Cell Epitopes in both Variable and Conserved Regions

In order to map linear B-cell (LBC) epitopes in the major capsid protein of feline calicivirus (FCV), an expression library containing random, short (100- to 200-bp) fragments of the FCV F9 capsid gene was constructed. Analysis of this library showed it to be representative of the region of the capsid gene that encodes the mature capsid protein. The library was screened by using polyclonal antisera from a cat that had been challenged experimentally with F9 to identify immunoreactive clones containing LBC epitopes. Twenty-six clones that reacted positively to feline antisera in immunoblots were identified. FCV-derived sequence from these clones mapped to a region of the capsid that spanned 126 amino acids and included variable regions C and E. An overlapping set of biotinylated peptides corresponding to this region was used to further map LBC epitopes by using F9 antisera. Four principal regions of reactivity were identified. Two fell within the hypervariable region at the 5' end of region E (amino acids [aa] 445 to 451 [antigenic site (ags) 2] and aa 451 to 457 [ags 3]). However, the other two were in conserved regions (aa 415 to 421 [ags 1; region D] and aa 475 to 479 [ags 4; central region E]). The reactivity of the peptide set with antisera from 11 other cats infected with a range of FCV isolates was also determined. Ten of 11 antisera reacted to conserved ags 4, suggesting that this region may be useful for future recombinant vaccine design.     

Systematic integration of experimental data and models in systems biology

Background

The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals.

Results

With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives.

Conclusion

We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.     

CONSeQuence: prediction of reference peptides for absolute quantitative proteomics using consensus machine learning approaches

Mass spectrometric based methods for absolute quantification of proteins, such as QconCAT, rely on internal standards of stable-isotope labeled reference peptides, or "Q-peptides," to act as surrogates. Key to the success of this and related methods for absolute protein quantification (such as AQUA) is selection of the Q-peptide. Here we describe a novel method, CONSeQuence (consensus predictor for Q-peptide sequence), based on four different machine learning approaches for Q-peptide selection. CONSeQuence demonstrates improved performance over existing methods for optimal Q-peptide selection in the absence of prior experimental information, as validated using two independent test sets derived from yeast. Furthermore, we examine the physicochemical parameters associated with good peptide surrogates, and demonstrate that in addition to charge and hydrophobicity, peptide secondary structure plays a significant role in determining peptide "detectability" in liquid chromatography-electrospray ionization experiments. We relate peptide properties to protein tertiary structure, demonstrating a counterintuitive preference for buried status for frequently detected peptides. Finally, we demonstrate the improved efficacy of the general approach by applying a predictor trained on yeast data to sets of proteotypic peptides from two additional species taken from an existing peptide identification repository.     

Absolute quantification of the glycolytic pathway in yeast: deployment of a complete QconCAT approach

The availability of label-free data derived from yeast cells (based on the summed intensity of the three strongest, isoform-specific peptides) permitted a preliminary assessment of protein abundances for glycolytic proteins. Following this analysis, we demonstrate successful application of the QconCAT technology, which uses recombinant DNA techniques to generate artificial concatamers of large numbers of internal standard peptides, to the quantification of enzymes of the glycolysis pathway in the yeast Saccharomyces cerevisiae. A QconCAT of 88 kDa (59 tryptic peptides) corresponding to 27 isoenzymes was designed and built to encode two or three analyte peptides per protein, and after stable isotope labeling of the standard in vivo, protein levels were determined by LC-MS, using ultra high performance liquid chromatography-coupled mass spectrometry. We were able to determine absolute protein concentrations between 14,000 and 10 million molecules/cell. Issues such as efficiency of extraction and completeness of proteolysis are addressed, as well as generic factors such as optimal quantotypic peptide selection and expression. In addition, the same proteins were quantified by intensity-based label-free analysis, and both sets of data were compared with other quantification methods.