Microarray estimation of genomic inter-strain variability in the genus Ectocarpus (Phaeophyceae)

<p/> <p>Background</p> <p>Brown algae of the genus <it>Ectocarpus </it>exhibit high levels of genetic diversity and variability in morphological and physiological characteristics. With the establishment of <it>E. siliculosus </it>as a model and the availability of a complete genome sequence, it is now of interest to analyze variability among different species, ecotypes, and strains of the genus <it>Ectocarpus </it>both at the genome and the transcriptome level.</p> <p>Results</p> <p>We used an <it>E. siliculosus </it>gene expression microarray based on EST sequences from the genome-sequenced strain (reference strain) to carry out comparative genome hybridizations for five <it>Ectocarpus </it>strains: four <it>E. siliculosus </it>isolates (the male genome strain, a female strain used for outcrosses with the genome strain, a strain isolated from freshwater, and a highly copper-tolerant strain), as well as one strain of the sister species <it>E. fasciculatus</it>. Our results revealed significant genomic differences between ecotypes of the same species, and enable the selection of conserved probes for future microarray experiments with these strains. In the two closely related strains (a male and a female strain used for crosses), genomic differences were also detected, but concentrated in two smaller genomic regions, one of which corresponds to a viral insertion site.</p> <p>Conclusion</p> <p>The high variability between strains supports the concept of <it>E. siliculosus </it>as a complex of cryptic species. Moreover, our data suggest that several parts of the <it>Ectocarpus </it>genome may have evolved at different rates: high variability was detected particularly in transposable elements and fucoxanthin chlorophyll a/c binding proteins.</p

No downregulation of immune function during breeding in two year-round breeding bird species in an equatorial East African environment

Some equatorial environments exhibit substantial within-location variation in environmental conditions throughout the year and yet have year-round breeding birds. This implies that breeding in such systems are potentially unrelated to the variable environmental conditions. By breeding not being influenced by environmental conditions, we become sure that any differences in immune function between breeding and non-breeding birds do not result from environmental variation, therefore allowing for exclusion of the confounding effect of variation in environmental conditions. This create a unique opportunity to test if immune function is down-regulated during reproduction compared to non-breeding periods. We compared the immune function of sympatric male and female chick-feeding and non-breeding red-capped Calandrella cinerea and rufous-naped larks Mirafra africana in equatorial East Africa. These closely-related species occupy different niches and have different breeding strategies in the same grassland habitat. Red-capped larks prefer areas with short grass or almost bare ground, and breed during low rainfall periods. Rufous-naped larks prefer areas of tall grass and scattered shrubs and breed during high rainfall. We measured the following immune indices: nitric oxide, haptoglobin, agglutination and lysis, and measured total monthly rain, monthly average minimum (T-min) and maximum (T-max) temperatures. Contrary to our predictions, we found no down-regulation of immune function during breeding; breeding birds had higher nitric oxide than non-breeding ones in both species, while the other three immune indices did not differ between breeding phases. Red-capped larks had higher nitric oxide concentrations than Rufous-naped larks, which in turn had higher haptoglobin levels than red-capped larks. T-max was higher during breeding than during non-breeding for red-capped larks only, suggesting potential confounding effect of T-max on the comparison of immune function between breeding and non-breeding birds for this species. Overall, we conclude that in the two year-round breeding equatorial larks, immune function is not down-regulated during breeding

Normalisation genes for expression analyses in the brown alga model Ectocarpus siliculosus

<p>Abstract</p> <p>Background</p> <p>Brown algae are plant multi-cellular organisms occupying most of the world coasts and are essential actors in the constitution of ecological niches at the shoreline. <it>Ectocarpus siliculosus </it>is an emerging model for brown algal research. Its genome has been sequenced, and several tools are being developed to perform analyses at different levels of cell organization, including transcriptomic expression analyses. Several topics, including physiological responses to osmotic stress and to exposure to contaminants and solvents are being studied in order to better understand the adaptive capacity of brown algae to pollution and environmental changes. A series of genes that can be used to normalise expression analyses is required for these studies.</p> <p>Results</p> <p>We monitored the expression of 13 genes under 21 different culture conditions. These included genes encoding proteins and factors involved in protein translation (ribosomal protein 26S, EF1alpha, IF2A, IF4E) and protein degradation (ubiquitin, ubiquitin conjugating enzyme) or folding (cyclophilin), and proteins involved in both the structure of the cytoskeleton (tubulin alpha, actin, actin-related proteins) and its trafficking function (dynein), as well as a protein implicated in carbon metabolism (glucose 6-phosphate dehydrogenase). The stability of their expression level was assessed using the Ct range, and by applying both the geNorm and the Normfinder principles of calculation.</p> <p>Conclusion</p> <p>Comparisons of the data obtained with the three methods of calculation indicated that EF1alpha (EF1a) was the best reference gene for normalisation. The normalisation factor should be calculated with at least two genes, alpha tubulin, ubiquitin-conjugating enzyme or actin-related proteins being good partners of EF1a. Our results exclude actin as a good normalisation gene, and, in this, are in agreement with previous studies in other organisms.</p

Distribution, occurrence and biotoxin composition of the main

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Field testing for toxic algae with a microarray: initial results from the MIDTAL project

One of the key tasks in the project MIDTAL (MIcroarrays for the Detection of Toxic ALgae) is to demonstrate the applicability of microarrays to monitor harmful algae across a broad range of ecological niches and toxic species responsible for harmful algal events. Water samples are collected from a series of sites used in national phytoplankton and biotoxin monitoring programmes across Europe. The samples are filtered; the rRNA is extracted, labelled with a fluorescent dye and applied to a microarray chip. The signal intensity from >120 probes previously spotted on the chip is measured and analysed. Preliminary results comparing microarray signal intensities with actual field counts are presented

Monoclonal antibodies directed to fucoidan preparations from brown algae

Cell walls of the brown algae contain a diverse range of polysaccharides with useful bioactivities. The precise structures of the sulfated fucan/fucoidan group of polysaccharides and their roles in generating cell wall architectures and cell properties are not known in detail. Four rat monoclonal antibodies, BAM1 to BAM4, directed to sulfated fucan preparations, have been generated and used to dissect the heterogeneity of brown algal cell wall polysaccharides. BAM1 and BAM4, respectively, bind to a non-sulfated epitope and a sulfated epitope present in the sulfated fucan preparations. BAM2 and BAM3 identified additional distinct epitopes present in the fucoidan preparations. All four epitopes, not yet fully characterised, occur widely within the major brown algal taxonomic groups and show divergent distribution patterns in tissues. The analysis of cell wall extractions and fluorescence imaging reveal differences in the occurrence of the BAM1 to BAM4 epitopes in various tissues of Fucus vesiculosus. In Ectocarpus subulatus, a species closely related to the brown algal model Ectocarpus siliculosus, the BAM4 sulfated epitope was modulated in relation to salinity levels. This new set of monoclonal antibodies will be useful for the dissection of the highly complex and yet poorly resolved sulfated polysaccharides in the brown algae in relation to their ecological and economic significance

Global expression analysis of the brown alga Ectocarpus siliculosus (Phaeophyceae) reveals large-scale reprogramming of the transcriptome in response to abiotic stress

The brown alga Ectocarpus siliculosus, unlike terrestrial plants, undergoes extensive reprogramming of its transcriptome during the acclimation to mild abiotic stress

Field testing for toxic algae with a microarray: initial results from the MIDTAL project

One of the key tasks in MIDTAL (MIcroarrays for the Detection of Toxic ALgae) is to demonstrate the applicability of microarrays to monitor harmful algae across a broad range of ecological niches and toxic species responsible for harmful algal events. Water samples are collected from a series of sites used in national phytoplankton and biotoxin monitoring across Europe. The samples are filtered; rRNA is extracted, labelled with a fluorescent dye and applied to a microarray chip. The signal intensity from >120 probes previously spotted on the chip is measured and analysed. Preliminary results comparing microarray signal intensities with actual field counts are presented.Versión del edito

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system