José R. Valverde

RB1 gene mutation up-date, a meta-analysis based on 932 reported mutations available in a searchable database

BackgroundRetinoblastoma, a prototype of hereditary cancer, is the most common intraocular tumour in children and potential cause of blindness from therapeutic eye ablation, second tumours in germ line carriers survivors, and even death when left untreated. The molecular scanning of RB1 in search of germ line mutations lead to the publication of more than 900 mutations whose knowledge is important for genetic counselling and the characterization of phenotypic-genotypic relationships.ResultsA searchable database (RBGMdb) has been constructed with 932 published RB1 mutations. The spectrum of these mutations has been analyzed with the following results: 1) the retinoblastoma protein is frequently inactivated by deletions and nonsense mutations while missense mutations are the main inactivating event in most genetic diseases. 2) Near 40% of RB1 gene mutations are recurrent and gather in sixteen hot points, including twelve nonsense, two missense and three splicing mutations. The remainder mutations are scattered along RB1, being most frequent in exons 9, 10, 14, 17, 18, 20, and 23. 3) The analysis of RB1 mutations by country of origin of the patients identifies two groups in which the incidence of nonsense and splicing mutations show differences extremely significant, and suggest the involvement of predisposing ethnic backgrounds. 4) A significant association between late age at diagnosis and splicing mutations in bilateral retinoblastoma patients suggests the occurrence of a delayed-onset genotype. 5) Most of the reported mutations in low-penetrance families fall in three groups: a) Mutations in regulatory sequences at the promoter resulting in low expression of a normal Rb; b) Missense and in-frame deletions affecting non-essential sequence motifs which result in a partial inactivation of Rb functions; c) Splicing mutations leading to the reduction of normal mRNA splicing or to alternative splicing involving either true oncogenic or defective (weak) alleles.ConclusionThe analysis of RB1 gene mutations logged in the RBGMdb has shown relevant phenotype-genotype relationships and provided working hypothesis to ascertain mechanisms linking certain mutations to ethnicity, delayed onset of the disease and low-penetrance. Gene profiling of tumors will help to clarify the genetic background linked to ethnicity and variable expressivity or delayed onset phenotypes.

Estimation of bacterial diversity using next generation sequencing of 16S rDNA: a comparison of different workflows.

BackgroundNext generation sequencing (NGS) enables a more comprehensive analysis of bacterial diversity from complex environmental samples. NGS data can be analysed using a variety of workflows. We test several simple and complex workflows, including frequently used as well as recently published tools, and report on their respective accuracy and efficiency under various conditions covering different sequence lengths, number of sequences and real world experimental data from rhizobacterial populations of glyphosate-tolerant maize treated or untreated with two different herbicides representative of differential diversity studies.ResultsAlignment and distance calculations affect OTU estimations, and multiple sequence alignment exerts a major impact on the computational time needed. Generally speaking, most of the analyses produced consistent results that may be used to assess differential diversity changes, however, dataset characteristics dictate which workflow should be preferred in each case.ConclusionsWhen estimating bacterial diversity, ESPRIT as well as the web-based workflow, RDP pyrosequencing pipeline, produced good results in all circumstances, however, its computational requirements can make method-combination workflows more attractive, depending on sequence variability, number and length.

Effect of Cry1Ab Protein on Rhizobacterial Communities of Bt-Maize over a Four-Year Cultivation Period

Background Bt-maize is a transgenic variety of maize expressing the Cry toxin from Bacillus turingiensis. The potential accumulation of the relative effect of the transgenic modification and the cry toxin on the rhizobacterial communities of Bt-maize has been monitored over a period of four years. Methodology/Principal Findings The accumulative effects of the cultivation of this transgenic plant have been monitored by means of high throughput DNA pyrosequencing of the bacterial DNA coding for the 16S rRNA hypervariable V6 region from rhizobacterial communities. The obtained sequences were subjected to taxonomic, phylogenetic and taxonomic-independent diversity studies. The results obtained were consistent, indicating that variations detected in the rhizobacterial community structure were possibly due to climatic factors rather than to the presence of the Bt-gene. No variations were observed in the diversity estimates between non-Bt and Bt-maize. Conclusions/Significance The cultivation of Bt-maize during the four-year period did not change the maize rhizobacterial communities when compared to those of the non-Bt maize. This is the first study to be conducted with Bt-maize during such a long cultivation period and the first evaluation of rhizobacterial communities to be performed in this transgenic plant using Next Generation Sequencing.

Analysis of Metagenomic Data Containing High Biodiversity Levels

In this paper we have addressed the problem of analysing Next Generation Sequencing samples with an expected large biodiversity content. We analysed several well-known 16S rRNA datasets from experimental samples, including both large and short sequences, in numbers of tens of thousands, in addition to carefully crafted synthetic datasets containing more than 7000 OTUs. From this data analysis several patterns were identified and used to develop new guidelines for experimentation in conditions of high biodiversity. We analysed the suitability of different clustering packages for these type of situations, the problem of even sampling, the relative effectiveness of Chao1 and ACE estimators as well as their effect on sampling size for a variety of population distributions. As regards practical analysis procedures, we advocated an approach that retains as much high-quality experimental data as possible. By carefully applying selection rules combining the taxonomic assignment with clustering strategies, we derived a set of recommendations for ultra-sequencing data analysis at high biodiversity levels.

Exploring the Feasibility of the Sec Route to Secrete Proteins Using the Tat Route in Streptomyces lividans

Streptomyces lividans uses mainly two pathways to target secretory proteins to the cytoplasmic membrane. The major pathway (Sec pathway) transports pre-proteins using the signal recognition particle, and the minor Tat pathway is responsible for the secretion using a folded conformation of a relatively low number of proteins. The signal peptides of the Sec-dependent alpha-amylase and the Tat-dependent agarase were interchanged and fused in-frame to the corresponding mature part of the other enzyme. Alpha-amylase was unable to use the Tat route when fused to the agarase signal peptide, while agarase used the Sec route when it was targeted by the alpha-amylase signal peptide. In addition to the signal peptide some yet unidentified parts of the secreted proteins may play a role in selecting the secretory route. Structure predictions for the Tat- and Sec-dependent proteins suggest that less structured proteins are more likely to be candidates for the Tat route.

Modelling the metabolism of protein secretion through the Tat route in Streptomyces lividans

BackgroundStreptomyces lividans has demonstrated its value as an efficient host for protein production due to its ability to secrete functional proteins directly to the media. Secretory proteins that use the major Sec route need to be properly folded outside the cell, whereas secretory proteins using the Tat route appear outside the cell correctly folded. This feature makes the Tat system very attractive for the production of natural or engineered Tat secretory proteins. S. lividans cells are known to respond differently to overproduction and secretion of Tat versus Sec proteins. Increased understanding of the impact of protein secretion through the Tat route can be obtained by a deeper analysis of the metabolic impact associated with protein production, and its dependence on protein origin, composition, secretion mechanisms, growth phases and nutrients. Flux Balance Analysis of Genome-Scale Metabolic Network models provides a theoretical framework to investigate cell metabolism under different constraints.ResultsWe have built new models for various S. lividans strains to better understand the mechanisms associated with overproduction of proteins secreted through the Tat route. We compare models of an S. lividans Tat-dependent agarase overproducing strain with those of the S. lividans wild-type, an S. lividans strain carrying the multi-copy plasmid vector and an α-amylase Sec-dependent overproducing strain. Using updated genomic, transcriptomic and experimental data we could extend existing S. lividans models and produce a new model which produces improved results largely extending the coverage of S. lividans strains, the number of genes and reactions being considered, the predictive behaviour and the dependence on specification of exchange constraints. Comparison of the optimized solutions obtained highlights numerous changes between Tat- and Sec-dependent protein secreting strains affecting the metabolism of carbon, amino acids, nucleotides, lipids and cofactors, and variability analysis predicts a large potential for protein overproduction.ConclusionsThis work provides a detailed look to metabolic changes associated to Tat-dependent protein secretion reproducing experimental observations and identifying changes that are specific to each secretory route, presenting a novel, improved, more accurate and strain-independent model of S. lividans, thus opening the way for enhanced metabolic engineering of protein overproduction in S. lividans.

Looking for Rhizobacterial Ecological Indicators in Agricultural Soils Using 16S rRNA metagenomic Amplicon Data.

Introduction Biological communities present in soil are essential to sustainable and productive agricultural practices; however, an accurate determination of the ecological status of agricultural soils remains to date an elusive task. An ideal indicator should be pervasive, play a relevant role in the ecosystem, show a rapid and proportional answer to external perturbations and be easily and economically measurable. Rhizobacteria play a major role in determining soil properties, becoming an attractive candidate for the detection of ecological indicators. The application of massive sequencing technologies to metagenomic analysis is providing an increasingly more precise view of the structure and composition of soil communities. In this work, we analyse soil rhizobacterial composition under various stress levels to search for potential ecological indicators. General Biodiversity Indicators Our results suggest that the Shannon index requires observation of a relatively large number of individuals to be representative of the true population diversity, and that the Simpson index may underestimate rare taxa in rhizobacterial environments. Taxonomical Classification Methods Detection of indicator taxa requires comparison of taxonomical classification of sequences. We have compared RDP classifier, RTAX and similarity-based taxonomical classification and selected the latter for taxonomical assignment because it provides larger detail. Taxonomy-Based Ecological Indicators The study of significant variations in common, clearly identified, taxa, using paired datasets allows minimization of non-treatment effects and avoidance of false positives. We have identified taxa associated to specific perturbations as well as taxa generally affected in treated soils. Changes in these taxa, or combinations of them, may be used as ecological indicators of soil health. The overall number and magnitude of changes detected in taxonomic groups does also increase with stress. These changes constitute an alternative indicator to measuring specific taxa, although their determination requires large sample sizes, better obtained by massive sequencing. Summary The main ecological indicators available are the Shannon index, OTU counts and estimators, overall detection of the number and proportion of changes, and changes of specific indicator taxa. Massive sequencing remains the most accurate tool to measure rhizobacterial ecological indicators. When massive sequencing is not an option, various cultivable taxonomic groups, such as specific groups in the Actinobacteria tree, are attractive as potential indicators of large disruptions to the rhizobiome.