ALBERT

Description: Background: Symbiosis genes (nod and nif) involved in nodulation and nitrogen fixation in legumes are plasmid-borne in Rhizobium. Rhizobial symbiotic variants (symbiovars) with distinct host specificity would depend on the type of symbiosis plasmid. In Rhizobium etli or in Rhizobium phaseoli, symbiovar phaseoli strains have the capacity to form nodules in Phaseolus vulgaris while symbiovar mimosae confers a broad host range including different mimosa trees. Results: We report on the genome of R. etli symbiovar mimosae strain Mim1 and its comparison to that from R. etli symbiovar phaseoli strain CFN42. Differences were found in plasmids especially in the symbiosis plasmid, not only in nod gene sequences but in nod gene content. Differences in Nod factors deduced from the presence of nod genes, in secretion systems or ACC-deaminase could help explain the distinct host specificity. Genes involved in P. vulgaris exudate uptake were not found in symbiovar mimosae but hup genes (involved in hydrogen uptake) were found. Plasmid pRetCFN42a was partially contained in Mim1 and a plasmid (pRetMim1c) was found only in Mim1. Chromids were well conserved. Conclusions: The genomic differences between the two symbiovars, mimosae and phaseoli may explain different host specificity. With the genomic analysis presented, the term symbiovar is validated. Furthermore, our data support that the generalist symbiovar mimosae may be older than the specialist symbiovar phaseoli.

Description: The cytochromes P450 (P450s) are a large superfamily of heme-containing monooxygenases involved in the oxidative metabolism of an enormous diversity of substrates. These enzymes require electrons for their act...

Description: Background High-throughput RNA sequencing (RNA-seq) offers unprecedented power to capture the real dynamics of gene expression. Experimental designs with extensive biological replication present a unique opportunity to exploit this feature and distinguish expression profiles with higher resolution. RNA-seq data analysis methods so far have been mostly applied to data sets with few replicates and their default settings try to provide the best performance under this constraint. These methods are based on two well-known count data distributions: the Poisson and the negative binomial. The way to properly calibrate them with large RNA-seq data sets is not trivial for the non-expert bioinformatics user. Results Here we show that expression profiles produced by extensively-replicated RNA-seq experiments lead to a rich diversity of count data distributions beyond the Poisson and the negative binomial, such as Poisson-Inverse Gaussian or Pólya-Aeppli, which can be captured by a more general family of count data distributions called the Poisson-Tweedie. The flexibility of the Poisson-Tweedie family enables a direct fitting of emerging features of large expression profiles, such as heavy-tails or zero-inflation, without the need to alter a single configuration parameter. We provide a software package for R called implementing a new test for differential expression based on the Poisson-Tweedie family. Using simulations on synthetic and real RNA-seq data we show that yields P-values that are equally or more accurate than competing methods under different configuration parameters. By surveying the tiny fraction of sex-specific gene expression changes in human lymphoblastoid cell lines, we also show that accurately detects differentially expressed genes in a real large RNA-seq data set with improved performance and reproducibility over the previously compared methodologies. Finally, we compared the results with those obtained from microarrays in order to check for reproducibility. Conclusions RNA-seq data with many replicates leads to a handful of count data distributions which can be accurately estimated with the statistical model illustrated in this paper. This method provides a better fit to the underlying biological variability; this may be critical when comparing groups of RNA-seq samples with markedly different count data distributions. The package forms part of the Bioconductor project and it is available for download at http://www.bioconductor.org.

Description: Background The marine cyanobacterium Lyngbya majuscula is a prolific producer of bioactive secondary metabolites. Although biosynthetic gene clusters encoding several of these compounds have been identified, little is known about how these clusters of genes are transcribed or regulated, and techniques targeting genetic manipulation in Lyngbya strains have not yet been developed. We conducted transcriptional analyses of the jamaicamide gene cluster from a Jamaican strain of Lyngbya majuscula, and isolated proteins that could be involved in jamaicamide regulation. Results An unusually long untranslated leader region of approximately 840 bp is located between the jamaicamide transcription start site (TSS) and gene cluster start codon. All of the intergenic regions between the pathway ORFs were transcribed into RNA in RT-PCR experiments; however, a promoter prediction program indicated the possible presence of promoters in multiple intergenic regions. Because the functionality of these promoters could not be verified in vivo, we used a reporter gene assay in E. coli to show that several of these intergenic regions, as well as the primary promoter preceding the TSS, are capable of driving β-galactosidase production. A protein pulldown assay was also used to isolate proteins that may regulate the jamaicamide pathway. Pulldown experiments using the intergenic region upstream of jamA as a DNA probe isolated two proteins that were identified by LC-MS/MS. By BLAST analysis, one of these had close sequence identity to a regulatory protein in another cyanobacterial species. Protein comparisons suggest a possible correlation between secondary metabolism regulation and light dependent complementary chromatic adaptation. Electromobility shift assays were used to evaluate binding of the recombinant proteins to the jamaicamide promoter region. Conclusion Insights into natural product regulation in cyanobacteria are of significant value to drug discovery and biotechnology. To our knowledge, this is the first attempt to characterize the transcription and regulation of secondary metabolism in a marine cyanobacterium. If jamaicamide is light regulated, this mechanism would be similar to other cyanobacterial natural product gene clusters such as microcystin LR. These findings could aid in understanding and potentially assisting the management of toxin production by Lyngbya in the environment.