MOLECULAR TOOLS FOR MONITORING HARMFUL ALGAL BLOOMS GPR-Analyzer: a simple tool for quantitative analysis of hierarchical multispecies microarrays

Abstract Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization-and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in "GPRAnalyzer", a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/ edvardse/gpranalyzer

Chlorophyll-binding proteins revisited - a multigenic family of light-harvesting and stress proteins from a brown algal perspective

<p>Abstract</p> <p>Background</p> <p>Chlorophyll-binding proteins (CBPs) constitute a large family of proteins with diverse functions in both light-harvesting and photoprotection. The evolution of CBPs has been debated, especially with respect to the origin of the LI818 subfamily, members of which function in non-photochemical quenching and have been found in chlorophyll a/c-containing algae and several organisms of the green lineage, but not in red algae so far. The recent publication of the <it>Ectocarpus siliculosus </it>genome represents an opportunity to expand on previous work carried out on the origin and function of CBPs.</p> <p>Results</p> <p>The <it>Ectocarpus </it>genome codes for 53 CBPs falling into all major families except the exclusively green family of chlorophyll a/b binding proteins. Most stress-induced CBPs belong to the LI818 family. However, we highlight a few stress-induced CBPs from <it>Phaeodactylum tricornutum </it>and <it>Chondrus crispus </it>that belong to different sub-families and are promising targets for future functional studies. Three-dimensional modeling of two LI818 proteins revealed features common to all LI818 proteins that are likely to interfere with their capacity to bind chlorophyll b and lutein, but may enable binding of chlorophyll c and fucoxanthin. In the light of this finding, we examined the possibility that LI818 proteins may have originated in a chlorophyll c/fucoxanthin containing organism and compared this scenario to three alternatives: an independent evolution of LI818 proteins in different lineages, an ancient origin together with the first CBPs, before the separation of the red and the green lineage, or an origin in the green lineage and a transfer to an ancestor of haptophytes and heterokonts during a cryptic endosymbiosis event.</p> <p>Conclusions</p> <p>Our findings reinforce the idea that the LI818 family of CBPs has a role in stress response. In addition, statistical analyses of phylogenetic trees show an independent origin in different eukaryotic lineages or a green algal origin of LI818 proteins to be highly unlikely. Instead, our data favor an origin in an ancestral chlorophyll a/c-containing organism and a subsequent lateral transfer to some green algae, although an origin of LI818 proteins in a common ancestor of red and green algae cannot be ruled out.</p

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

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

The Saccharina latissima microbiome: Effects of region, season, and physiology

IntroductionSaccharina latissima is a canopy-forming species of brown algae and, as such, is considered an ecosystem engineer. Several populations of this alga are exploited worldwide, and a decrease in the abundance of S. latissima at its southern distributional range limits has been observed. Despite its economic and ecological interest, only a few data are available on the composition of microbiota associated with S. latissima and its role in algal physiologyn.MethodsWe studied the whole bacterial community composition associated with S. latissima samples from three locations (Brittany, Helgoland, and Skagerrak) by 16S metabarcoding analyses at different scales: algal blade part, regions, season (at one site), and algal physiologic state.Results and DiscussionWe have shown that the difference in bacterial composition is driven by factors of decreasing importance: (i) the algal tissues (apex/meristem), (ii) the geographical area, (iii) the seasons (at the Roscoff site), and (iv) the algal host’s condition (healthy vs. symptoms). Overall, Alphaproteobacteria, Gammaproteobacteria, and Bacteroidia dominated the general bacterial communities. Almost all individuals hosted bacteria of the genus Granulosicoccus, accounting for 12% of the total sequences, and eight additional core genera were identified. Our results also highlight a microbial signature characteristic for algae in poor health independent of the disease symptoms. Thus, our study provides a comprehensive overview of the S. latissima microbiome, forming a basis for understanding holobiont functioning

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

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

The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea

Seagrasses colonized the sea(1) on at least three independent occasions to form the basis of one of the most productive and widespread coastal ecosystems on the planet(2). Here we report the genome of Zostera marina (L.), the first, to our knowledge, marine angiosperm to be fully sequenced. This reveals unique insights into the genomic losses and gains involved in achieving the structural and physiological adaptations required for its marine lifestyle, arguably the most severe habitat shift ever accomplished by flowering plants. Key angiosperm innovations that were lost include the entire repertoire of stomatal genes(3), genes involved in the synthesis of terpenoids and ethylene signalling, and genes for ultraviolet protection and phytochromes for far-red sensing. Seagrasses have also regained functions enabling them to adjust to full salinity. Their cell walls contain all of the polysaccharides typical of land plants, but also contain polyanionic, low-methylated pectins and sulfated galactans, a feature shared with the cell walls of all macroalgae(4) and that is important for ion homoeostasis, nutrient uptake and O-2/CO2 exchange through leaf epidermal cells. The Z. marina genome resource will markedly advance a wide range of functional ecological studies from adaptation of marine ecosystems under climate warming(5,6), to unravelling the mechanisms of osmoregulation under high salinities that may further inform our understanding of the evolution of salt tolerance in crop plants(7)

Metabolic interactions between algae and bacteria in changing conditions

Brown algae form key marine ecosystems and live in tight relationships with microbes essential to their growth and development. Environmental changes can cause imbalances in these biological systems, leading to shifts in bacterial communities and sometimes giving rise to pathogenic interactions. Hence, considering both the algae and their microbiome (i.e. the holobiont) is essential to better understand their reactions to environmental challenges. In this memoir, I will outline the research I have conducted over the past nine years to explore this topic and highlight some of my ideas and challenges for the future. I will first touch on my work establishing the small filamentous brown alga Ectocarpus and in particular, a freshwater strain of the species Ectocarpus subulatus that we have shown to depend on a specific microbiome for freshwater tolerance, as a model system for algal-bacterial interactions. This includes the coordination of the sequencing and annotation of the E. subulatus genome, the characterization of its microbiome both in the field and in laboratory samples, and the establishment of a collection of cultivated bacteria representative of its microbiome now comprising ca. 400 strains from nearly 100 different species or genera, many of which have been genome-sequenced. Using multi-omics analyses we have furthermore put forward new hypotheses on the role of bacteria during the algal stress response, notably, the continued provision of bacterial services, most importantly vitamin K production, and the induction of quorum sensing pathways (potentially indicative of a change in the bacterial lifestyle towards dysbiosis). To identify key services provided to the algae by bacteria without strong a priori assumptions, we have, in collaboration with Anne Siegel’s team from the IRISA Rennes, turned to metabolic complementarity as a predictor for potential mutualistic exchanges. The underlying idea is that beneficial metabolic exchanges between symbionts most likely occur where metabolic functions have been lost by one of the symbiotic partners, or vice versa functions may be lost once they have been replaced by external sources. Such points of intersection can be identified in silico using genome-scale metabolic networks. We have recently been able to prove the utility of this concept to predict beneficial metabolic interactions as well as the metabolic capacities of simplified holobiont systems in vitro, i.e. the algal host in co-culture with selected bacterial strains. Parallel to this work on Ectocarpus, we are starting to expand our research to the economically and ecologically more relevant kelp species Saccharina latissima. In this context, we have recently characterized the microbiome associated with both healthy and diseased S. latissima from different seasons and regions and generated a large collection of cultivated Saccharina-derived bacterial strains. These form a solid basis for both more targeted work with this model, such as more detailed studies on the role of Quorum Sensing (QS) in governing algal-bacterial interactions. Most recently we also commenced work on the S. latissima virome. The most important challenges in my future research will be, on one hand, to improve the reproducibility of experiments and thus to better control model systems, and the possible use of reverse genetics to gain precise functional insights into specific interactions. In parallel, I intend to expand our view of brown algal holobionts beyond bacteria and lately viruses to include fungi. Lastly, I hope to link work carried out in the laboratory to its potential applications, e.g. by assessing the impact of the microbiome on the defense-stimulating effect of Ascophyllum nodosum extracts in terrestrial plants