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Original Research ARTICLE

Front. Microbiol., 02 October 2015 |

Turbulence-driven shifts in holobionts and planktonic microbial assemblages in St. Peter and St. Paul Archipelago, Mid-Atlantic Ridge, Brazil

Ana Paula B. Moreira1, Pedro M. Meirelles1, Eidy de O. Santos2, Gilberto M. Amado-Filho3, Ronaldo B. Francini-Filho4, Cristiane C. Thompson1 and Fabiano L. Thompson1*
  • 1Laboratory of Microbiology, Institute of Biology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
  • 2Fundação Centro Universitário Estadual da Zona Oeste (Uezo), Rio de Janeiro, Brazil
  • 3Diretoria de Pesquisa Científica, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro, Brazil
  • 4Department of Environment and Engineering, Federal University of Paraíba, Rio Tinto, Brazil

The aim of this study was to investigate the planktonic and the holobiont Madracis decactis (Scleractinia) microbial diversity along a turbulence-driven upwelling event, in the world's most isolated tropical island, St Peter and St Paul Archipelago (SPSPA, Brazil). Twenty one metagenomes were obtained for seawater (N = 12), healthy and bleached holobionts (N = 9) before, during and after the episode of high seawater turbulence and upwelling. Microbial assemblages differed between low turbulence-low nutrient (LLR) and high-turbulence-high nutrient (HHR) regimes in seawater. During LLR there was a balance between autotrophy and heterotrophy in the bacterioplankton and the ratio cyanobacteria:heterotrophs ~1 (C:H). Prochlorales, unclassified Alphaproteobacteria and Euryarchaeota were the dominant bacteria and archaea, respectively. Basic metabolisms and cyanobacterial phages characterized the LLR. During HHR C:H < < 0.05 and Gammaproteobacteria approximated 50% of the most abundant organisms in seawater. Alteromonadales, Oceanospirillales, and Thaumarchaeota were the dominant bacteria and archaea. Prevailing metabolisms were related to membrane transport, virulence, disease, and defense. Phages targeting heterotrophs and virulence factor genes characterized HHR. Shifts were also observed in coral microbiomes, according to both annotation–indepent and -dependent methods. HHR bleached corals metagenomes were the most dissimilar and could be distinguished by their di- and tetranucleotides frequencies, Iron Acquision metabolism and virulence genes, such as V. cholerae-related virulence factors. The healthy coral holobiont was shown to be less sensitive to transient seawater-related perturbations than the diseased animals. A conceptual model for the turbulence-induced shifts is put forward.

Marine microbial communities are recognized as engines of globally important processes, such as the marine carbon, nitrogen and sulfur cycles (Falkowski et al., 2008; Fuhrman, 2009). Only recently with the introduction of molecular techniques have satisfactory descriptions of natural microbial assemblages been generated (Fierer and Jackson, 2006; Rusch et al., 2007; Costello et al., 2009). Nevertheless, most marine ecosystems are understudied. As a result, there is limited information on the diversity of microbial assemblages in changing environments and on the environmental drivers of microbial diversity shifts (Karl, 2002).

Nutrient dynamics in the sea is inextricably linked to variations in physical processes. Either enhanced nutrient delivery from turbulent mixing or upwelling, or enhanced stratification can lead to shifts in microbial assemblages, with significant consequences for nutrient cycling (Cullen et al., 2002). Episodic mixing events must occur in order to balance supply and demand (Hayward, 1987, 1991). Because open-ocean microbial assemblages are metabolically active with a potential for relatively high specific growth, they are poised to respond quickly and effectively to environmental perturbations (Karl, 2002). A model of turbulence-nutrients regimes decoupled characteristics and adaptations of phytoplankton assemblages and how they relate to food web structure: (i) high turbulence—low nutrients: low biomass, slow turnover, adaptations for efficient use of light and nutrients (e.g., iron-limited, high latitude waters); (ii) LLR: smaller cells, high turnover, competition for nutrients, retention by recycling (microbial loop); (iii) low turbulence—high nutrients: larger cells, higher biomass, slower turnover, selective pressure to sequester nutrients and minimize losses (e.g., noxious toxic blooms); and (iv) HHR: larger cells, higher biomass, transient, and self-limiting selection for rapid growth (e.g., diatoms). According to this model, the microbial loop is present in all regimes but it dominates the biomass in the low turbulence—high nutrients regime (Cullen et al., 2002).

Some physical mechanisms that vertically supply nutrients from below to the oligotrophic oceanic surface layers are: (i) internal waves and tides, (ii) cyclonic mesoscale eddies, (iii) wind-driven Ekman pumping, and (iv) atmospheric storms (Karl, 1999). Internal waves are ubiquitous in deep-ocean environments (Garrett and Munk, 1972), and it appears that the high vertical shear of low-frequency internal waves contributes to occasional pulses of vertical mixing (Gregg et al., 1986; Sherman and Pinkel, 1991). Stochastic events, that may be short-lived, are of major ecological significance. They are undoubtedly undersampled by ship-based observation programs (Platt et al., 1989). Even a monthly sampling schedule, as adopted in the Hawaii Ocean Time-series (HOT) program, is considered too infrequent to register important but intermittent nutrient injections (Karl, 1999). Furthermore, most studies are restricted to the Pacific, Caribbean, and North Atlantic.

St. Peter and St. Paul Archipelago (SPSPA) are the smallest and most isolated tropical islands in the world. It comprises the most seaward Brazilian oceanic islands (~1000 km from mainland) and the unique on the northern hemisphere, lying 100 km off the equator (00°55′N; 29°22′W). Data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) evinces the chlorophyll pattern characteristic of mesotrophic waters (0.1–0.3 mg.m−3 Chla) (Supplementary Figures 1A,B), according to the classification of Shushkina et al. (1997). SPSPA is located in the biogeochemical Western Tropical Atlantic Province (WTRA) (Longhurst et al., 1995), under the influence of the Intertropical Convergence Zone. Its formed by minute summits of the Mid-Atlantic Ridge (MAR) within the St Paul Fault Zone (FZ), between the South American and the African Plates (Supplementary Figures 2A,B), where seismicity is frequent (Campos et al., 2010). The islets are devoid of shore and consist entirely of steep scarpments extending to 60–100 m depth, with the most limited area of shallow habitat among oceanic islands (~200 m) (Robertson, 2001). Within 2 km diameter bathyal depths are reached and within 5 km depths fall within the abyssal range (−3.600 to 5.000; Supplementary Figure 2B). The South Equatorial Current (SEC) flows E-W superficially and the Atlantic Equatorial Undercurrent (EUC) flows W-E at 60–100 m depth (Edwards and Lubbock, 1983). The latter is one of the fastest, varying and least predictable among the Atlantic currents, which reaches 120 cm.seg−1 above the thermocline (Philander, 1986). A permanent thermocline may prevent deep water masses to emerge (Macedo et al., 2009) nevertheless the eventual presence of deep water Pleurommama spp. and Heterorhabdus spp at the shallow layer during the diurnal period is contradictory to the former assumption (Macedo-Soares et al., 2009). There are no reports on local hydrodynamics but, seemingly, intermittent vertical flow of deep water masses should result from the violent interaction with the geomorphology—MAR—a perpendicular barrier to the currents. In principle, the friction between the SEC and EUC masses, which flow in opposing directions, should promote and intensify episodic extensions of the thermohaline to the photic zone.

Moreira et al. (2014) reported a significant enrichment process along an 8 days period during which an ever-growing turbulence with surge pulses was observed in SPSPA. The process occurred along the lunar phase from crescent to full moon. The work performed the first (and unique to date) characterization of the culturable heterotrophic bacterial community of SPSPA. Bacterial counts (colony forming units, CFU) correlated positively with nutrients in seawater, which in turn correlated positively with turbulence—energy and frequency of the surges. In the present work we analyzed the metagenomic composition and diversity of both the planktonic microbial assemblages and in the scleractinian coral M. decactis along the same period in the same locale. The aim was to characterize the microbial diversity during an upwelling-driven nutrient enrichment. We did not expect to find bleached corals in SPSPA. The coral holobionts were targeted in this survey to investigate whether there was a correlation between the metagenomic features and seawater parameters (vibrio counts, nutrients, bacterioplankton composition). Sampling was performed before, during and after a turbulence surge. It was a short-lived event, which is locally recurrent. We analyzed 21 metagenomic samples of seawater (n = 12), healthy and bleached corals (n = 9). The findings are summarized in a model of the physico-chemical-biological dynamics in SPSPA, where a cyclic recurrent pattern with extreme regimes of low turbulence-low nutrients (LLR) and high turbulence-high nutrients (HHR) is hypothesized to contribute to structure the marine ecosystem in that barren archipelago.

Materials and Methods

Field Sampling (Performed By Moreira et al., 2014)

In brief, sampling was performed by SCUBA diving at the Sub-caulerpa zone (mesophotic), according to the zonation of (Edwards and Lubbock, 1983; Moreira et al., 2014). The survey took place along the NW side of the archipelago from the inlet (ca 4500 m2) to Belmonte islet's contiguous vertical wall. The satellite view and topograghy of the inlet are shown in Supplementary Figures 1C, 2B, respectively. The turbulence surge occurred along the lunar phase from crescent (14/Sep/2010) to full moon (22/Sep/2010). The peak of the surge overlapped with cloudiness, wind and rain. Rain and swash flushed guano, a possible additional source of nutrients (Gagnon et al., 2013), from the cays into the bay. Samples were obtained from the onset (LLR, t1 = 14/Sep/2010), while enhancing (t2 = 15; t3 = 18/Sep/2010, HHR) and almost to recovery of LLR condition, or recovery for short (t4 = 22/set/2010). During climax (20–21/Sep/2010) the strong vortex precluded diving (Supplementary Video 1). Henceforth samples will be referred as 14, 15, 18, and 22. In total, 12 colony fragments (10 × 10 cm) of M. decactis (healthy: n = 8; bleached: n = 4) were collected with hammer and chisel. On days 14 and 15 bleached corals were not found. Coral samples processed for metagenomics were: (i) healthy corals (Mad): 14 (n = 1), 15 (n = 2), 18 (n = 1), and 22 (n = 1); and (ii) bleached corals (MadBle): 18 (n = 2) and 22 (n = 2). Seawater was sampled from the water column immediately above the corals (< 1 m) (4 samples: 14, 15, 18, and 22; 20 L/sample; 3 sterivex/sample). All samples were taken immediately to the Scientific Staion (SS) Laboratory, 20 m from the pier (Supplementary Figure 1D; view of the pier and the SS from the water at LLR). Seawater was filtered. Filters and coral samples were preserved in liquid nitrogen until DNA extraction (no longer than 3 months after).

Madracis Decactis (Lyman, 1859) (Scleractinia: Pocilloporideae)

Is a colonial zooxanthellate scleractinian coral. It has a variable bathymetric distribution, from 3 to 30 and up to 100 m (Neves and Johnsson, 2009). It is widespread in Brazil (N to SE), in Caribe, Gulf of Mexico and locally found in the Southeastern Atlantic (West Africa) (World Register of marine Species—WORMS: Free-living colonies of M. decactis display an unique formation off southern Brazil, at Galé Island. Spheroid shape, a.k.a. circumrotatory colonies, form the first corallith site discovered in the subtropical South Atlantic Ocean (SAO), at 6–15 m depth over 3400 m2 (coralreeefs-2012). In São Paulo (SE Brazil) it's a major contributor of reef structures, where bleaching has been seriously affecting its populations (Migotto, 1997), adding interest to the study of this coral species. In SPSPA, its one of the two scleractinian species locally found, mostly at the mesophotic zone. Healthy, bleached and with scars left by fish predation (Stegastes sanctipauli, Pomacentridae; Halichoeres radiatus, Labridae) in SPSPA are shown in Supplementary Figure 3.

Seawater: Temperature, Nutrients, and Microbial Abundance

Environmental parameters were analyzed by standard oceanographic methods with at least three replicates for each parameter and determined by Moreira et al. (2014). Temperature was recorded in situ with a HOBO UA-002-64/date Logger and UEMIS dive computer from 5, 15, 33, 45, and 65 m depth (n = 5 for each depth), during September/2010 and June/2011 (published in Crespo et al., 2014). Environmental data from (Moreira et al., 2014) and temperature from (Crespo et al., 2014) are summarized in Supplementary Figure 4, for aid in data interpretation.

Metagenomic DNA Extraction

Corals' DNA extraction was performed as in Trindade-Silva et al. (2012). Seawater was sequentially pre-filtered (100 and 20 μm) by gravity and then filtered on the Sterivex (0.22 μm) by positive pressure using Niskin system (2 L/Sterivex). The microbes collected at Sterivex filters were preserved with SET buffer (20% sucrose, 50 mM EDTA and 0.5 mM Tris–HCl). Metagenomic DNA extraction was performed using lysozyme (1 mg/mL) for 1 h at 37°C. Then, proteinase K (0.2 mg/mL) and sodium dodecyl sulfate (SDS) (1% v/v) were added and incubated (55°C; 60 min) under agitation. The lysate was rinsed into SET buffer (1 mL). Organic extraction was performed with one volume of phenol:chloroform:isoamyl alcohol (25:24:1). DNA precipitation was performed with ethanol (2,5 volumes) and amnonium acetate (0.7 M) at −20°C overnight. After centrifugation the pellet was washed twice with ethanol (70%) and air-dried. Elution was done in TE buffer (1X). Three libraries were prepared for each Sterivex and coral sample and pyrosequenced subsequently.

Metagenomic Library Construction

Metagenomes were obtained by pyrosequencing technology using a 454 GS Junior instrument (Roche) (Margulies et al., 2005). Shotgun libraries were generated with 500 ng of whole metagenome samples, sheared into fragments by nebulization. End-repair and adaptor ligation were performed using GS FLX Titanium kit (Roche). Quality control and quantification were performed with Agilent 2100 Bioanalyzer (Agilent Technologies) and TBS 380 Fluorometer (Turner Biosystems), respectively. After the libraries construction, approximately 106 molecules/metagenome were denatured and amplified by emulsion PCR.

Metagenomic Data Analysis

Raw sequences were submitted to quality control using PRINSEQ Standalone Lite (version 0.20.4; available at We analyzed 21 metagenomic samples of seawater (n = 12) and corals (n = 9) from 4 days (t1 = 14, t2 = 15, t3 = 18, t4 = 22, of set/2010) along the enrichment process (t4t1 = 8 days). Annotation was performed by Meta-Genome Rapid Annotation using Subsystems Technology (MG-RAST) server (Meyer et al., 2008) version 3.0, using (SEED) Subsystems Technology and the GenBank database for functional and organismal classifications, respectively. For this purpose, all BLAST queries were conducted with a maximum cutoff E-value 0.00001, a minimum identity of 60%, and a minimum alignment length of 20 measured in aa for protein and bp for RNA databases.

Metagenomes Comparison Trough Annotation-independent Analysis

Dinucleotide odds ratio and Karlin distances (δ) between the metagenomes, based on the dinucleotide relative abundances differences (according to Karlin et al., 1997), were calculated using Perl scripts as in Willner et al. (2009). The values in the Karlin matrix were multiplied by a 1000 for easier comparison. Tetranucleotide frequencies were calculated using a Perl script as in Albertsen et al. (2013). The divergence between the observed and expected tetranucleotide frequencies was transferred into z-scores and pairwise comparison of the metagenomic sequences was performed by computing the Pearson's correlation coefficients of the z-scores, both through Python scripts, according to (Teeling et al., 2004). Seawater metagenomes (Sw-14, -15, -18, and -22) were compared among each other, as well as coral metagenomes (Mad14, Mad15, Mad18, MadBle18, Mad22, MadBle22).

Phage Detection

The 21 metagenomic libraries were searched for phages using the PHAge Search Tool (PHAST), available at (Zhou et al., 2011). Briefly, pyfasta 0.5.2 (available at was used to split metagenomes into smaller subsets without splitting individual fasta entries, after which PHAST was used to phage search. The tool provides an ensemble of ORF prediction and translation (via GLIMMER; Salzberg et al., 1998), protein identification (via BLASTP; Altschul et al., 1997), phage sequence identification (via BLAST matching to a specific database), tRNA identification (using tRNAscan-SE; Lowe and Eddy, 1997), attachment site recognition (with ARAGORN; Laslett and Canback, 2004) and gene clustering density measurements using density-based spatial clustering of applications with noise (DBSCAN; Ester et al., 1996), and sequence annotation text mining. PHAST's database encloses protein sequences from two sources: the NCBI phage database and the prophage database (Srividhya et al., 2006). Specific keywords (e.g., “protease,” “integrase,” and “tail fiber”) are used for screening. Matched phage or phage-like sequences with E < 0.0001 are saved as hits and their positions tracked for subsequent evaluation for local phage density by DBSCAN. Phage schemes shown in Supplementary Figures 11–18 were generated with PHAST.

Sequence Comparison to the Virulence Factor Database

The 21 metagenomic libraries were compared to the virulence factor database (VFDB) (Chen et al., 2005) ( using BLASTX (E < 0.0001).

Statistical analysis was conducted using R Version 3.1.3 (Team, 2012) with a suite of packages. The comparison of the correlation coefficients of the z-scores obtained for the tetranucleotide frequencies was visualized through heatmaps using rpy2 and gplots (Gautier, 2008). An exploratory analysis aiming to correlate samples with nutrients' concentrations and metabolisms, according to the level 1 SEED classification, was performed by means of a principal component analysis (PCA) using the rda function of Vegan package (Oksanen et al., 2013). Abundance plots were drawn using the ggplot2 and reshape packages (Wickham, 2007; Wickham and Chang, 2009). The cluster analysis was performed with the APE package (Paradis et al., 2004) using Pearson correlation and ward distance.

Sequence Data

The metagenomic data that we generated are available in the MG-RAST v3 server ( under the unique identifiers: 4461594.3, 4463932.3, 4463930.3, 4463939.3, 4463927.3, 4461593.3, 4463933.3, 4463931.3, 4463928.3, 4463926.3, 4463925.3, 4468639.3, 4486661.3, 4486665.3, 4486669.3, 4486662.3, 4486667.3, 4486668.3, 4486664.3, 4486663.3, and 4486666.3; and in the Brazilian Marine Biodiversity database (BaMBa) (pmeirelles.18.1).

Sampling Permit

Ministério do Meio Ambiente (MMA), Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) Number 10112-2.

In this study 21 metagenomic libraries were obtained from seawater (n = 12) and corals (n = 9) with a total of 446,129 sequences (2.13 × 108 bp) (Table 1). Through annotation-independent analysis, samples Sw14, -15, and -22 were distinguished from -18 (Table 1). Average Karlin distances for pairs of seawater samples Sw14, -15, -18 and -22 defined three categories based on δ ranges. (i) δ < 11 grouped pairs 14-14 and 22-22, indicating high degree of genetic similarity; (ii) 11 < δ < 30 grouped pairs 15–15, 18–18, 14–15, 14–22, and 15–22, indicating intermediate genetic similarity, and (iii) δ> 30 grouped pairs 14–18, 15–18, and 18–22, indicating low genetic similarity. The most dissimilar samples (δ = 50.6) were Sw14 (LLR) and Sw18 (HHR) (Supplementary Figure 5). Similarly, average Karlin distances for coral samples Mad14, -15, -18, and -22 defined three categories. (i) δ < 11 grouped pairs 14–22, 14–15, 15–22, and 22–22; (ii) 11 < δ < 20 grouped pairs 15–15; and (iii) δ> 20 grouped pairs 14–18, 15–18, 18–22, and 18–18. Samples Mad18 were the most dissimilar in comparison with -14, -15, -22 and also among each other (Supplementary Figure 6). The same pattern was revealed by the analysis that resulted from the tetranucleotide frequencies estimated for seawater and coral metgenomes. Samples Sw18 (HHR) were the most dissimilar amongst seawater metagenomes (Supplementary Figure 7A) and metagenomes from HHR bleached corals (MadBle18) were the most dissimilar amongst the holobionts' metagenomes (Supplementary Figure 7B).

Table 1. General features of the metagenomes.

To analyze the overall relationships among the most abundant taxa we performed a clustering analysis (Figure 1). The hierarchical clustering of the 21 metagenomes corroborated the binning based in sequence composition (di- and tetranucleotides frequencies). Two major branches split seawater and coral metagenomes. Two seawater branches were defined, with samples 14 (and Sw15-1) representing the LLR. Samples 15 (Sw15-2 and 4), 18 and 22 reflected the turbulence surge (Figure 1). Coral metagenomes were split into healthy and bleached (with only two exceptions: MadBle18-1 grouped into the healthy corals branch and Mad22 into the bleached corals branch). Healthy corals also showed a trend to group according to the enrichment gradient. The healthy corals branch split Mad14 and Mad15-1 from the remainders Mad15-2, Mad18, and Mad22.

Figure 1. Hierarchical clustering of the metagenomes using Order level of the taxonomical identification by MG-Rast. The Pearson correlation and ward distance were used to create the dendrogram. The metagenomes from seawater, healthy and bleached M. decactis are indicated by the colors blue, brown, and red, respectively; and by the sampling day (of September/2010). Exceptions to the clustering of corals according to health status are detached (MadBle18-1 from bleached coral clustered within the healthy branch and Mad22 from healthy coral clustered within the bleached branch). The relative abundance of the 10 most abundant orders is presented at right.

Taxonomic Assignment of Seawater Metagenomes

Bacteria was the most abundant domain in all samples with overall average relative abundance of 97.0 ± 1.8% (Mean ± SD), followed by 1.11 ± 0.69% Eukarya (Supplementary Figure 8). Archaeal sequences accounted for ~0.4% of the overall sequences. The main groups were Euryarchaota (~58%) and Thaumarchaeota (21%). Viruses represented ~0.4% of sequences. The most abundant order was Caudovirales (~52%). The overall relative abundance of the most prevalent bacterial phyla were ~61% Proteobacteria, 32% Cyanobacteria followed by 2.4% Bacteroidetes (100% Flavobacteriales), 1.6% Firmicutes, and 1.3% Actinobacteria (Figure 1).

Shifts in Planktonic Assemblages

The taxonomic classification of seawater samples revealed a clear difference between LLR and the remainder groups (Sw15, -18, -22). In all samples the dominant groups were Cyanobacteria (C) and Proteobacteria (P). At LLR (Sw14), these groups were equally abundant in seawater (C:P ~1). Along the turbulence gradient, Proteobacteria members increased and Cyanobacteria decreased to a vanishingly small proportion (Sw18, HHR; C:P < < 0.05), with a subsequent recovery (Sw22; C:P > 0.5). The highest proportion of Proteobacteria occurred at HHR (92%) (Figure 2A). At LLR Alphaproteobacteria presented the highest relative abundance (Alpha 28.3% and Gamma 25.1%; ANOVA, P < 0.05), whereas Gammaproteobacteria was dominant in all the following samples (Sw15, -18, and -22: Gamma 29.4% and Alpha 24.8%; P < 0.05) (Supplementary Figure 9). Proteobacterial groups whose relative abundances enhanced during enrichment were Alteromonas, Vibrio and Pseudomonas (Gamma); Ruegeria, Roseobacter, and Candidatus Pelagibacter (Alpha) (Figure 2B). Cyanobacteria and unclassified Alphaproteobacteria (mostly SAR11) decreased correspondingly (Figure 1). Oceanospirillales was absent in the top ten rank at LLR, but appeared in Sw15-4 (2.5%), in HHR (5.6–7.3%), and Sw22 (2.5–2.7%). Archaeal groups also shifted dominance. The most abundant phyla in Sw14-15 was Euryarchaeeota, whereas in Sw18-22 it was Thaumarchaeota (Figure 2C).

Figure 2. Relative abundances of Cyanobacteria, Proteobacteria, and Archaea. (A) Cyanobacteria and Proteobacteria relative abundances in samples Sw14, -15, -18, and -22. The ratio C:P is shown above bars. (B) Relative abundances of GammaProteobacteria (Alteromonas, Vibrio, Pseudomonas) and AlphaProteobacteria (Candidatus pelagibacter, Ruegeria, and Roseobacter) in samples Sw14, -15, -18, and -22. (C) Relative abundances of Euryarchaeota, Thaumarchaeota and Crenarchaeota in pooled samples seawater Sw14–15, Sw18–22; and M. decactis healthy indicated as Healthy coral (14–15) and (18–22); and diseased indicated as Diseased Coral (18–22).

Functional Assignment of Seawater Metagenomes

The overall most abundant subsystems were Protein Metabolism (9.8 ± 1.0%), Amino Acids and Derivatives (9.4 ± 0.7%), Carbohydrates (9.4 ± 0.7%), Cofactors, Vitamins, Prosthetic Groups, Pigments (7.2 ± 0.7%), and RNA Metabolism (5.2 ± 0.7%) (Supplementary Figure 10). The most abundant gene per metagenome was the TonB-dependent receptor, of the subsystem Iron Acquisition and Metabolism, in samples Sw18 (HHR) (Supplementary Table 1). A phage protein encoding gene was the most abundant gene in five samples: Sw22-1,2 (recovery) and Sw14-1,2,3 (LLR). Phage detection through specific databases (using PHAST) revealed that the most probable hosts were cyanobacteria for Sw14 and -22 (LLR and recovery, respectively), and Proteobacteria for the remainders (Sw15 and HHR), with only two exceptions (Table 2; Supplementary Figures 11–18). The range of unknown proteins was 17.9–42.4% (Sw18-2 and Sw14-1, respectively).

Table 2. Abundance and characteristics of prophages found in the bacterioplankton in SPSPA.

Shifts in Metabolisms in Seawater Metagenomes

To investigate the metabolic profile of planktonic dwelling microbes and to correlate differences with the enrichment gradient, we performed a PCA analysis (Figures 3A,B). Clustering of samples Sw14 (LLR) was not explained by nutrients concentrations, contrarily to the remainder samples (Figure 3A). Basic cell functions such as Carbohydrates and Respiration explained the clustering of samples Sw14 (LLR), whether enrichment samples Sw15 and Sw18 (HHR) clustered in response to Virulence, Disease, and Defence; Membrane Transport and Nitrogen Metabolism subsystems (Figure 3B). Samples Sw15 were grouped by the concentration of the nutrients organic phosphorous, ammonia, orthophosphate, and nitrite. The former three showed the highest concentration at Sw15 (Figure 3A, Supplementary Figure 4). HHR samples (Sw18) were coupled by the heterotrophic-characteristic metabolisms, Membrane Transport and Virulence, Disease and Defense. Accordingly, their most abundant gene was the TonB-dependent receptor (Virulence, Disease and Defense). Recovery samples (Sw22) were coupled by the concentration of nitrate (the highest, Figure 3A, Supplementary Figure 4) and Nitrogen Metabolism (Sw22-1; Figure 3B), correspondingly.

Figure 3. Principal component analysis (PCA) diagrams. (A) Diagram generated for the bacterioplankton samples and nutrients in seawater. (B) Diagram generated for the bacterioplankton samples and metabolisms in seawater.

Taxonomic Assignment in Madracis Decactis Metagenomes

Bacteria was the most abundant identified Domain in all samples with overall relative abundance of 57.15%, followed by Eukarya (39.63%). Archaeal sequences represented 1.92% and viruses 0.1%. Within the domain Eukarya, 33.59% of the sequences were Cnidaria (Supplementary Figure 19A). Main overall archaeal phyla were Euryarchaeota (45.61%), Thaumarchaeota (42.11%), and Crenarchaeota (10.96%). (Figure 2C). There were marked differences in comparison with seawater metagenomes (Figure 1). The most abundant bacterial phyla were Proteobacteria (~48% of the counts), Firmicutes (17%), Actinobacteria (10%), Bacteroidetes (6%), and Cyanobacteria (4%). The most abundant proteobacterial orders were Rhizobiales (16.29%), Rhodobacterales (12.44%); Burkholderiales (10.77%), Pseudomonadales (4.85%), Pasteurellales (4.82%), Alteromonadales (4.68%), Desulfuromonadales (4.38%), Enterobacteriales (4.12%), Myxococcales (4.01%), and Chromatiales (3.46%). Cyanobacteria was mostly represented by Chroococcales (50.23%), Oscillatoriales (24.35%), Nostocales (20.03%), and Prochlorales (5.24%). Interestingly, Rhodobacterales, Rhizobiales, Actinomycetales, Burkholderiales, and Clostridiales were abundant in healthy and diseased M. decactis.

Shifts in Microbial Assemblages in Madracis Decactis Metagenomes

At HHR bleached corals (MadBle18) showed more sequences affiliated to Proteobacteria than the healthy corals (Mad18) (Supplementary Figure 19B). The presence of Pasteurellales among the ten most abundant orders in five out of nine metagenomes (in Mad15, -18, and, -22 with 11–14% of counts) appeared to be a diagnostic feature (Figure 1). Pasteurellales was found in low relative abundance (< 1%) in the remainder corals and in seawater metagenomes. Thaumarchaeota affiliates in all M. decatis samples (Mad14, -15, -18, and -22) approximated Sw18-22 abundance levels (Figure 2C). Cnidaria and Nematoda metagenomic sequences were more abundant in healthy and bleached corals, respectively (Supplementary Figure 8).

Functional Assignment in Madracis Decactis Metagenomes

The overall most abundant subsystems were Carbohydrates (16.6 ± 2.8%), Amino Acids and Derivatives (14.3 ± 1.2%), Protein Metabolism (9.66 ± 1.6%), Cofactors, Vitamins, Prosthetic groups, Pigments (8.9 ± 1.6%), and DNA Metabolism (6.6 ± 2.4%) (Supplementary Figure 20).

Shifts in Metabolisms is Madracis Decactis Metagenomes

To investigate major differences in metabolisms the corals' metagenomes were pooled (according to Figure 1 and Supplementary Figure 7B) in samples (i) healthy 14–15 (Mad14 and Mad15-1,2), (ii) healthy 18–22 (Mad18 and Mad22), and (iii) diseased 18–22 (MadBle18-1,2 and MadBle22-1,2). Seawater samples were included as reference (Sw14–15, Sw18–22). Prevalence of motility and chemotaxis in seawater compared to corals was the main difference observed between type samples. DNA metabolism prevailed in corals Mad18–22 (healthy and bleached) relative to the remainder samples (Supplementary Figure 20). DNA metabolism was the fourth most represented in corals. The overall most abundant gene (EC in corals was affiliated to this subsystem, which was the most abundant gene in three metagenomes of the Mad18–22 group, and in none of the Mad14–15 group (Supplementary Table 1). The Iron Acquisition subsystem was investigated further by pooling coral samples according to health status in (i) healthy and (ii) diseased. The relative abundance range was lower in healthy corals (5.56–9.09%) than in diseased corals (5.15–16.36%) (P < 0.05). Iron Acquisition in Vibrio was the most abundant function in overall samples, with a relative abundance range of 18.2–83.3% (MadBle22-1 and Mad22, respectively). Healthy corals presented higher relative abundances (60–83%) than diseased corals (18.2–34.4%) for this function. Six functions were represented only in diseased corals: Campylobacter Iron Metabolism (6.3–40.0%); Heme, Hemin Uptake and Utilization Systems in GramPositives (0–20.0%); Siderophore Pyoverdine (0–18.2%), Transport of Iron (0–14.9%); Iron Acquisition in Streptococcus (0–10.3%) and Iron(III) Dicitrate Transport System (0–3.1%). Heme, Hemin Uptake and Utilization Systems in Gram-Negatives was overrepresented in diseased (16.2%) compared to healthy corals (7.3%) (P < 0.05).

Shifts in the Profiles of Seawater- and Madracis Decactis- Dwelling Communities

The shift from autotroph:heterotroph-balance to offset was further investigated using virulence factors (VFs) as indicators of heterotrophy and risk or threat for corals. In total there were 21,230 significant similarities against the VFDB (Table 3). When normalized to library size, virulence genes were overrepresented in samples Sw 15, -18 (16.0–24.3) and, to a lesser extent in Sw22 (16.6–16.8) (recovery), compared to LLR (Sw14; 12.7–14.2); and in bleached (MadBle; 0.8–8.5) when compared to healthy corals (Mad; 0.6–3.1). We further investigated the iron uptake system, which is a nonspecific virulence system related to competition skills, and thus suitable to reflect the overall heterotrophic community. Iron related virulence genes comprised ~9% (n = 1817) of the total hits to the VFDB. Sw18 samples (HHR) presented the lower percentage of iron related genes relative to the total virulence hits per metagenome (P < 0.05), suggesting that other than iron uptake genes were most representative of the surplus heterotrophs. The VFDB lacks genes related to iron from vibrios (which was overly represented in healthy corals), but encompasses genes related to iron from Haemophilus (Pasteurellales). Among all virulence genes related to iron, ~33% (n = 606) fell into this category. V. cholerae related virulence genes, which confer infective skills, comprised ~6% (n = 1298) of the total virulence hits. The percentage range of these genes relative to total VFs per metagenome in seawater samples Sw14, -15, and -22 was 4.4–6.5% and in Sw18 (HHR) was 6.6–7.7%. Similarly, in healthy corals this range was 0.1–6.9%, and higher in diseased corals: 4.7–8.1% (Table 3). Heterotrophic populations that overgrew in response to turbulence-nutrient pulses were better represented by pathogenic (e.g., V. cholerae-related) than by non-specific (e.g., iron acquisition) VFs.

Table 3. Abundances of virulence factor genes from microbes in the bacterioplankton and M. decactis in SPSPA.

Microbial assemblages during LLR (Sw14) were comparable to those previously described for the surface layers in the western SAO (South Atlantic Gyral - SATL) (Alves Junior et al., 2015) and within the WTRA (Heywood et al., 2006; Schattenhofer et al., 2009), where the dominant groups (= 50%) detected were also Prochlorales and unclassified Alphaproteobacteria or SAR11 and related. Following LLR the microbial assemblages observed increasingly differed from previous studies focusing the surface layers of those most neighboring locations (Heywood et al., 2006; Schattenhofer et al., 2009; Swan et al., 2011). Alteromonadales appeared as the second most abundant group after Prochlorales, prevailing over unclassified Alphaproteobacteria, and Vibrionales emerged as a new group with >5% relative abundance (Sw15). Comparable Alteromonadales relative abundances, combined with lower abundances of unclassified Alphaproteobacteria (SAR11) were previously reported for the sub-superficial chlorophyll maximum (SCM) layer at higher depths (48–82 m) in the SAO, where, instead of Vibrionales, Pseudomonadales, and Mamiellales emerged as differing groups compared to the surface layers (Alves Junior et al., 2015). At HHR (Sw18), other Gammaproteobacteria appeared with > 5% relative abundance, i.e., Pseudomonadales and Oceanospirillales, whereas Thaumarchaota reached Euryarchaeota relative abundance levels. Pseudomonadales, Oceanospirillales, and Thaumarchaeota characterized deep waters (236–1200 m) in the SAO, and in which water masses Prochlorales was not amongst the 10 most abundant orders (AlvesJr-14). (Schattenhofer et al., 2009) reported a Gammaproteobacteria bloom in the North Atlantic Drift Province (NADR), with a maximum relative abundance of >50% of all picoplankton in surface waters, compared to the average values of 2–5% for all the other Atlantic provinces. Only a minor fraction was identified (Alteromonas/Colwellia and Pseudoalteromonas: 2–5%; Vibrio: 1%, and Oceanospirillum: 4%). The Gammaproteobacteria bloom was attributed to the end of the spring phytoplankton bloom, indicated by declining chlorophyll values. Massive growth of Bacteroidetes was concomitant and deep water Archaea presence at surface was not observed. Gammaproteobacteria have the potential to respond to sudden nutrient pulses released from phytoplankton (Cottrell and Kirchman, 2000). Members of Alteromonas, Pseudoalteromonas, and Vibrio are well known to rapidly respond to excess nutrient supply (Bano and Hollibaugh, 2002; Beardsley et al., 2003; Allers et al., 2007, 2008). Thaumarchaeota are typically more abundant at depths of ≥100 m, as oposed to Euryarchaeota, which is known for decreasing abundance below 100 m (Delong, 1992; Zhang et al., 2009; Santoro et al., 2010; Tseng et al., 2015). In SPSPA, concomitant with Thaumarchaeota increase, ammonia levels decreased, possibly due to its ammonia-oxidizing ability (Francis et al., 2005); and Flavobacteriales (Bacteroidetes) relative abundance decreased. Next (Sw22), the five most abundant groups at LLR recovered relative abundances almost to LLR (Sw14) levels (Prochlorococcus, unclassified Alphaproteobacteria—SAR11, Rhodobacterales, Rhizobiales, and Chroococcales), but Alteromonadales, Pseudomonadales, Vibrionales, and Oceanospirillales remained amongst the 10 most abundant groups, as well as Thaumarchaeota remained abundant, which is a distinctive assemblage for those geographical coordinates (Schattenhofer et al., 2009; Swan et al., 2011; Alves Junior et al., 2015). Shifts in planktonic assemblages at the mesophotic zone in SPSPA were possibly driven by the turbulence surge, meaning that microbes from progressively deeper layers could hitchhike with the vertical flux along the surge. The upwelling is also supported by the enrichment and by the wide variation of water temperatures registered for the sampling depth (Supplementary Figure 4).

A Model of Physical-Chemical-Biological Dynamics in SPSPA

Although sequence similarities to genes do not represent levels of gene expression, metagenomes have been shown to be strong predictors of the biogeochemical conditions driving the microbial community (Dinsdale et al., 2008). According to the lines of evidence garnered the microbiome of the mesophotic waters in SPSPA undergoes cyclic transient shifts in relation to turbulence-nutrients regimes. A microbial succession resulting from the interplay between physical and chemical factors is a plausible scenario. Two extreme turbulence-nutrient regimes can be clearly distinguished and alternate with intermediate conditions determining microbial assemblages: (i) When turbulence is low (LLR) at least 50% of the microbiome is composed of Prochlorococcus, followed by unclassified Alphaproteobacteria (SAR11 and related), which are small sized cells, highly adapted to oligotrophic conditions and starvation. Rhodobacterlaes, Rhizobiales, and Chroococcales are typical. In this environment phage genes are the most abundant in seawater, mostly from Prochlorococcus and Synechococcus, following the hosts' abundances. The viral shunt is probably less active toward relatively scarce cells. The proportion of unknown genes is the highest; (ii) Episodic surges promote vertical mixing from the immediate lower water mass to the mixed layer. Waves also wash guano from the cays flushing phosphates and ammonium into the inlet. Heterotrophs (Alteromonadales, Vibrionales) respond quickly and surpass autotrophs, motility, and chemotaxis related genes stand out; (iii) Ongoing eddies and intensified high-energy waves promote entrainment of deep water organisms such as Thaumarchaeota and nutrients (nitrite, nitrate) (HHR). Eventual cloudiness, winds and rain cope with turbulence, irradiance is intermittent and turbidity is enhanced. Heterotrophy predominates with dominance of Alteromonadales, Pseudomonadales, and Oceanospirillales. Gammaproteobacterial groups approximate 50% of the microbial assemblage, resembling the end of the spring phytoplankton bloom in higher latitudes (e.g., NADR). The gene pool in surface waters reflects the shift with membrane transport and virulence-related genes (e.g., TonB-dependent receptor, V. cholerae virulence genes) surpassing cyanobacterial phages and basic metabolisms genes. Phages targeting heterotrophs are active. The proportion of unknown genes is the lowest; (iv) Turbulence alleviates (e.g., after moon changes toward new). Larger cell sized heterotrophs begin to decline as viral lysis and predation by grazers overrides growth, which is constrained by the paucity of limiting nutrients (e.g., phosphorus). The microbial loop is most prominent at this stage. Autotrophs respond to irradiance and retake growth (if rain, wind, and cloudiness mitigate this response is accelerated). Nitrogen metabolism is intensive. A reversal to autotrophy:heterotrophy equilibrium is triggered (Figure 4). The short-lived but recurrent turbulence-nutrient pulses might be responsible for structuring the marine ecosystem in a bottom-up manner in SPSPA. These pulses might be indispensable to warrant the energy and carbon flow to the higher trophic levels concurring to the observed pelagic fishes biomass around the barren islets (Luiz and Edwards, 2011). On a stable LLR the growth of phytoplankton is largely supported by regenerated nutrients, so only a small proportion of primary production is available to higher trophic levels or for export to the deep sea (Cullen et al., 2002; Karl, 2014). Turbulence is physically forcing the co-ocurrence of nutrients and light in SPSPA, on the other hand, the fact that nutrient resupply is short-lived might concur to retain the local mesotrophic condition. Bacterioplankton shifts were shown to be transient, following the cyclic nutrient-turbulence pulses and other physical parameters (rain, cloudiness, winds, turbidity).

Figure 4. Cartoon model of the main processes in SPSPA Cyclic turbulence-nutrient pulses determine transient shifts in the bacterioplankton. Circular central blue arrow indicates the cyclic nature of the events. Left panel: during LLR calm tides, weak winds, absence of clouds, and clear waters correlate with lower levels (downwards red arrows) of nitrogen (N) and phosphorous (P), and equivalence between autotrophy and heterotropy, represented by the ratio cyanobacteria:heterotrophs (C:H) equalizing 1. Cyanobacterial phages (green poligons) reflect the abundance of the hosts. Right panel: during HHR harsh conditions are determined by violent turbulence resulting in upwelling and enrichment, represented by high levels (upwards red arrows) of N and P, and a shift to heterotrophy dominance, represented by a low ratio cyanobacteria:heterotrophs (C:H < < 1). Intense winds, cloudiness and rain, that washes the rocks covered with guano, contribute to enrichment and the shift to heterotrophy. Proteobacterial phages (red poligons) reflect the abundance of the hosts as well as Iron acquisition (red circle) and virulence factor (red crosses) genes. Vibrios abundance (blue elipses) reflect seawater parameters. Episodic surges frequently correlate with full moon. When turbulence pulses mitigate and weather assuages a recovery takes place in seawater, both in terms of nutrients concentrations and microbial assemblages (e.g., after moon changes toward new).

The Holobiont Madracis Decactis

Some bacterial taxa prevalent in bleached corals (Rhodobacterales, Rhizobiales, and Clostridiales) have been previously associated with opportunistic diseases (Frias-Lopez et al., 2002; Rosenberg et al., 2007; Sekar et al., 2008; Sunagawa et al., 2009; Mouchka et al., 2010). On the other hand, a study of the corals microbiome, aiming at distinguishing the core, the symbiotic and the whole community microbiome, suggested that Rhodobacterales pertains to the latter. Conversely, Rhizobiales members were suggested to belong to the symbiotic coral microbiome. Actinomycetales and Burkholderiales (both also prevalent in all coral samples) were characterized as part of the coral core microbiome (D Ainsworth et al., 2015). Pasteurellales was one of the most abundant bacteria in the coral metagenomes, contrasting to its dwindling relative abundance in seawater. Pasteurellales members can cause disease in a wide range of domestic and wild animals (Wilson and Ho, 2013). They are commonly found in fish tissues (Birkbeck et al., 2002). Reef fishes (Chaetodontidae) have been characterized as major vectors of coral diseases (Raymundo et al., 2009) and damselfish (Stegastes spp.) was shown to increase the prevalence of the coral Black Band Disease (BBD) (Casey et al., 2014). It is plausible that Pasteurellales are frequently transmitted to corals through fishes, possibly by fish bites, since M. decactis is frequently predated by S. sanctipauli, H. radiatus and other fishes in SPSPA (Supplementary Figure 3). This hypothesis explains the uneven distribution of Pasteurellales between healthy and diseased corals, as well as the disconnection to seawater parameters. Bleached corals were distinguished by enhanced Iron Acquisition metabolism. Six functions within this subsystem were represented only in bleached corals. HHR bleached corals samples (MadBle18) were the most dissimilar in terms of sequence composition (di- and tetranucletides frequencies), higher counts of Proteobacteria (including Vibrionales), and higher relative abundance of hits to the VFDB, including V. cholerae-related VFs. This dissimilarity, including the HHR healthy coral (Mad18), indicates that the healthy coral holobiont might be less sensitive to transient seawater-related perturbations than the diseased animals. The distinguishing characteristics of HHR bleached corals agree with the bacterioplankton and seawater features during HHR, reported both in the present and former study (Supplementary Figure 4; Moreira et al., 2014): sequence composition, higher relative abundance of motility and chemotaxis, and of membrane transport and virulence genes (e.g., Ton-B dependent receptor of the Iron Acquisition metabolism, V. cholerae-related VFs), higher vibrio counts and nutrients in seawater. Taken together, the datasets suggest coupling between the benthic and pelagic compartments, as previously reported (Chimetto Tonon et al., 2015).

Owing to the remote nature of this site, we do not have complete data sets. Resampling will be needed to strengthen the link between turbulence-upwelling and the shifts in microbial assemblages.

This work analyzed shifts in microbial composition related to physical forcings (turbulence-upwelling and storms) in SPSPA. LLR is characterized by the equilibrium between autotrophy-heterotrophy and microbial assemblages that resemble those of surface tropical waters previously characterized in the SAO. At HHR microbial communities shift to heterotrophic and deep-sea characteristic organisms (Thaumarchaota). HHR diseased corals are distinguished by sequence composition and enhanced VFs hits, suggesting some level of coupling between planktonic and coral microbial communities.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

This work was supported by CNPq, CAPES and FAPERJ. Comissão Interministerial para os Recursos do Mar partially supported the expedition. The authors are grateful to the Brazilian Navy for maintenance of the Scientific Station and training; to Ericka Coni for joining the expedition and participating in sampling; to the Transmar III crew, Douglas Abrantes and Camilo Ferreira for general logistical support, and to Prof. Rob Edwards (San Diego State University) for the valuable ideas and helpful discussion.

Supplementary Material

The Supplementary Material for this article can be found online at:

EUC, Atlantic Equatorial Undercurrent; BLAST, Basic Local Alignment Search Tool; chla, chlorophyll a; CFU, colony forming unit; DMSP, dimethylsulfoniopropionate; HOT, Hawaii Ocean Time-series; HHR, high turbulence-high nutrients regime; LLR, low turbulence-low nutrients regime; MAR, Mid-Atlantic Ridge; NCBI, National Center for Biotechnology Information; NADR, North Atlantic Drift Province; PHAST, PHAge Search Tool; SeaWiFS, Sea-viewing Wide Field-of-view Sensor; SATL, South Atlantic Gyral; SAO, South Atlantic Ocean; SPSPA, St Peter and St Paul Archipelago; FZ, St Paul Fault Zone; SEC, South Equatorial Current; SCM, sub-superficial chlorophyll maximum; VFs, virulence factors; VFDB, Virulence Factor Data Base; WTRA, Western Tropical Atlantic Province; WORMS, World Register of marine Species.

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Keywords: metagenomics, Atlantic Ocean, oceanic islands, Scleractinia, Madracis decactis

Citation: Moreira APB, Meirelles PM, Santos EO, Amado-Filho GM, Francini-Filho RB, Thompson CC and Thompson FL (2015) Turbulence-driven shifts in holobionts and planktonic microbial assemblages in St. Peter and St. Paul Archipelago, Mid-Atlantic Ridge, Brazil. Front. Microbiol. 6:1038. doi: 10.3389/fmicb.2015.01038

Received: 01 June 2015; Accepted: 11 September 2015;
Published: 02 October 2015.

Edited by:

Maurizio Labbate, University of Technology Sydney, Australia

Reviewed by:

Matthew Schrenk, Michigan State University, USA
Zhenfeng Liu, University of Southern California, USA
Katherine Dafforn, University of New South Wales, Australia

Copyright © 2015 Moreira, Meirelles, Santos, Amado-Filho, Francini-Filho, Thompson and Thompson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Fabiano L. Thompson, CCS, BIOMAR, Laboratório de Microbiologia, Institute of Biology, Cidade Universitária, Av. Carlos Chagas F°. S/N, Bloco A (Anexo) A3, sl 102, Rio de Janeiro, RJ, CEP 21941-599, Brazil,


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FUJITSU Software BS2000 TIAM

The access method for interactive mode in BS2000

Current version: V13.2

TIAM is the access method for interactive mode. It accepts connection requests from the terminal and initiates a separate task for each terminal. At the request of the terminal user, TIAM terminates the connection and releases the resources.

The dialog between the user of the terminal and the computer consists of a spontaneous sequence of commands, without prestructure, taken from the command language of the operating system. These commands, which are input directly at the terminal in interactive mode, enable functions such as program development and testing as well as the preparation of files.

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Nearly a third of UK home owners are looking to carry out work on their home in the next three years, with up to £6b – based on the premise of 17.5 million owner-occupied households – in projected works planned annually over the next three years, according to a new study from the Federation of Master Builders (FMB).

Driven by the Generation Stay trend, over a million home owners (1,050,000) are looking to build extra space to accommodate grown-up children who cannot afford to leave home. According to the study, families up and down the country are seeking to be more creative with the space in their property, with one in five homeowners (22%) investing because of a property plateau which sees them unable to afford to move in to a bigger property, despite having a growing family.

Almost 40% of home improvements are set to be major refurbishments, including new kitchens, new bathrooms and home extensions, while smaller works such as loft conversions and conservatories account for 38%.

Homeowners are putting families first, as wider motivations to invest in their property include planning for having a family and parents wishing to boost their children’s future inheritance.

Brian Berry, chief executive of the FMB, which commissioned the study, says: “We have seen a rising trend of multi-generational households, with grown-up children opting to stay with their parents while they save money for their own homes.”


text:
Wesley-Barrell is opening its newest showroom on 26th of October, situated within a new luxury homewares destination at the famous Mailbox building in the centre of Birmingham. Backing onto the Gas Street canal basin, this unique, award-winning development promises to be a place to shop, eat and relax in style.

Wesley-Barrell has been making fine English upholstery in Oxfordshire since 1895 and with this brand new location, it now offer 14 showrooms across the UK. A new generation of management has embraced Wesley Barrell's traditional ethos in furniture design and will introduce some future classics to the business' existing upholstery collection.

Today, Wesley Barrell offers handmade sofas, covered in the latest trending fabrics from some of the best fabric houses in the world, as well as its own collection of quality in-house fabrics. The company also has a large choice of cabinet furniture, fabric, paint and wallpaper which enables it to offer a more tailored and bespoke interior design experience.

With on-site 24-hour parking to help visitors explore this shopping experience, Wesley Barrell looks forward to welcoming visitors to its new showroom.


text:
Skip to 0 minutes and 4 secondsSo, not only is it important what we eat, but how much we eat is equally paramount. Especially with the rise of overweight and obesity across the world. I'm going to demonstrate some different serving sizes that can often be misleading. Meaning, that people eat or drink more than what they plan to. I'm going to start with alcohol because that's an area that can be quite confusing for people. A standard drink of wine is actually 100 ml. And, depending on the drink, the volume of a standard drink can vary. This bottle of wine says that it contains 6.8 standard drinks, and it's 11% alcohol volume. So, I'm going to pour 100 ml.

Skip to 0 minutes and 51 secondsSo that's just a tiny bit more than 100 ml. And in this glass, that's what it looks like. So that's a standard drink. Then what it looks like in a bigger glass, is only that much. And then in the restaurant size glass, you can see that it's even maybe only about a quarter. So, I wonder what a glass of that would be in ml.

Skip to 1 minute and 38 secondsIt is actually about 300 ml. So, we're looking at nearly half a bottle for a glass of wine. So, please be careful when you're drinking wine out of big glasses. And just remember, this goes for other drinks as well. Soft drinks, juices, we can always be misled according to the size of the glass or bottle that were being served. So, another way that people can overeat without meaning to, is what size chocolate bar we buy. So first, this was a chocolate bar that came as a twin pack. But it was all together. And I think most people, once they start opening the packet, they're going to finish the whole bar. Then there was a medium sized one.

Skip to 2 minutes and 26 secondsAnd then there is a fun-size one. So, you can still have chocolate. If you look at these fun-size one, it's actually about a quarter of the big one. And that's going to make a difference if you're only having this once a week as opposed to one of these ones every day. It's going to make a big difference to your saturated fat intake, your sugar intake, and your overall calorie intake. So, one serve of breads and cereals is half a cup of pasta. So, I'm going to show you what that looks like. Squash it down. OK, so this is one serve or half a cup. You can see what that looks like in the bowl.

Skip to 3 minutes and 6 secondsNow, putting it in a large bowl, it really looks like hardly anything. So, do the same thing as what I did with the wine with the amount of pasta. So, that's one serve-- half a cup-- two serves, three serves.

Skip to 3 minutes and 39 secondsAnd still the bowl's not quite full. So keep that in mind when you're having a big bowl of pasta. All though foods from the grains and cereals group we've encouraged you to eat, the amount is also important. Serve sizes also apply to prepackaged things such as bread. You can see that all of these breads are different sizes, different thicknesses. So looking at these two slices of bread, which are both soy and linseed, you can see that there are different sizes, and they're different thicknesses. Also, when you're looking at them, this one seems to have more soy and linseed. So it's likely that, because of the size, this one has fewer calories.

Skip to 4 minutes and 21 secondsAnd probably has more goodness because of all the extra grains and seeds that are in it. This smaller one is actually the size that fits in a serve of grains and cereals. So I would encourage people to buy smaller loaves of bread if they're trying to control their weight. Here's a really great way to increase your portion size of something without really increasing the calorie content, and adding a lot of vitamins and fibre to it. So here we have 125 gram of meat and 125 gram of meat. The difference is this patty has two serves of vegetables-- grated zucchini and onion. So this larger portion size is going to be a lot more satisfying once it reaches your stomach.

Skip to 5 minutes and 5 secondsBut also, it's a lot more satisfying to know that you're eating something substantial. When we look at something it's going to make us feel fuller if we think that it's bigger. Today, it's really difficult for us to control our portion sizes. A lot of us eat out, get takeaway, and portion sizes seem to be growing. One thing that we need to do is being aware of what a serving size is. And how different things like packet size, plate or bowl or glass size, can affect how much we're actually consuming.

Portion sizes

Watch Simone talk about portion size, and how different serving sizes can often be misleading and can lead to overeating.

Talking point

In the Comments, considering sharing with other learners your thoughts on the following question:

  • Do you think portion sizes encourage over consumption of food?

Don’t forget to contribute to the discussion by reviewing comments made by other learners, making sure you provide constructive feedback and commentary. You can also ‘Like’ comments or follow other learners throughout the course.

RACGP members, please engage deeply in the course

In order to meet the RACGP QI&CPD Program requirements to receive 40 Category 1 points, RACGP members must complete all parts of this course, being sure to make careful and considered responses to all of the talking points listed in this step, and throughout the course.

Because reflective and exploratory discussions are critical to learning, once you’ve shared your own thoughts, respond to at least one comment from another learner for each discussion point.

Doing so will allow you to build on your own ideas on how you can apply new approaches to your professional practice.

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Food as Medicine: Talking about Weight

Monash University

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Palm Peyto PFD / Buoyancy Aid From £97.99

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Smooth looks and subtle curves conceal a highly capable touring buoyancy aid. Comfort fit foam‚ a supple face fabric and accessible strap adjustment mean the Peyto fits comfortably‚ next to you skin or over a jacket. Hidden handwarmers‚ front pockets to swallow up a radio and other essentials‚ and a rear pocket to accommodate a drinks reservoir make this a premium quality all season PFD.

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Weight: 826 g (M/L)
Certification: EN ISO 12402-5 / 12402-6

Other Features: Clip-in point, Hydration Bladder compatible.

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Galaxy S6 Manual User Guide and Instructions

Galaxy S6 Manual User Guide has specially to guide you the functions and features of your Samsung Galaxy S6. You can download or read here. In this document are contains instructions and explanations on everything from setting up the device for the first time for users who still didn’t understand about basic function of the phone.

Samsung Galaxy S6 is an Android based smartphone manufactured and marketed by Samsung Electronics. The phone was officially unveiled in a press conference at Mobile World Congress on 1 March 2015. The device is a successor to the Galaxy S5, which was released in 2014.

galaxy s6 manual

Samsung Galaxy S6 line retains similarities in design to previous models, but now uses a unibody metal frame with a glass backing, a curved bezel with chamfered sides to improve grip, and the speaker grille was moved to the bottom. The devices will be available in “White Pearl”, “Black Sapphire”, and “Gold Platinum” color finishes; additional “Cobalt Blue” and “Emerald Green” finishes are exclusive to the S6 and S6 Edge respectively.

Samsung Galaxy S6 Key Specs

  • 64-bit Exynos 7420 chipset with 14nm architecture; octa-core CPU (quad 2.1GHz & quad 1.5GHz)
  • 3GB of LPDDR4 RAM; 32/64/128GB of UFS 2.0 flash memory; 115GB of Microsoft OneDrive storage for 2 years
  • 5.1″ QHD (2560 x 1440 pixels) Super AMOLED display with 577ppi for both models (dual edge design for Samsung Galaxy S6 edge); 600cd/mm brightness
  • 16MP f/1.9 camera with OIS; Auto HDR; 4K video capture; IR white balance detection
  • 5MP f/1.9 front-facing camera
  • Cat. 6 LTE; WiFi: 802.11 a/b/g/n/ac (2.4/5GHz); Bluetooth 4.1; NFC; IR Remote; USB 2.0
  • NFC and MST mobile payment support
  • 2,550mAh battery for Galaxy S6; 2,600mAh for the Galaxy S6
  • Qi (WPC) and PMA wireless charging support
  • Android 5.0.2 Lollipop with TouchWiz UX
  • Metal chassis; Corning Gorilla Glass 4 front and back

The Galaxy S6 run Android 5.0.2 “Lollipop” with Samsung’s TouchWiz software suite. TouchWiz has been streamlined on the S6 with a refreshed design and fewer bundled applications. Samsung Galaxy S6 is scheduled to be released on 10 April 2015 in 20 countries.

 Samsung Galaxy S6 Manual Guide

Galaxy S6 Manual Download (PDF, 7.93MB)

 Samsung Galaxy S6 Manual Guide for Other Country and Region

Netherlands SM-G920F, SM-G920FQ, SM-G920I Dutch  dbut1
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Spain -T-Mobile SM-G920T Spanish  dbut1
Spain – AT&T SM-G920A Spanish  dbut1
Thailand SM-G920F Thai Language  dbut1
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Vietnam SM-G920F Vietnamese  dbut1

NOTE: For open or reading this Galaxy S6 manual, your computer need Adobe Reader. You can get the Adobe Reader by going here

Samsung has just released the new Galaxy S9 and S9+ this month. For customers who need Samsung Galaxy S9 and S9+ user manual, please go to our partner site here, in this site also include tips and tricks for the new Galaxy S9 and S9+.


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Boost server

Ryzer RPG / DM []

Last refresh 0 ago

  • Bosnia and Herzegovina |
  • San Andreas Multiplayer

FreeBoost is available only to KGB Hosting clients.

You can activate FreeBoost in game panel, and its not possible to boost any servers outside of your panel.

To get access to FreeBoost, buy Premium server with 20+ slots, or Lite server with 30+ slots.

Claim ownership instructions:

1. Change your server's name to GameTracker (ex: type in console amx_cvar hostname "GameTracker")

2. Check if your server is online and showing new name "GameTracker"

3. Click on a button below

  • General info
    Game: San Andreas Multiplayer
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    Name: Ryzer RPG / DM []
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    Added by: Pexara
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    Boost status not available, read explanation on home page.
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    Players: 0/500
    Average number of players (last 12h): 0
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    The best rank: 346
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Greeting Card with Happenin' Holiday

This product is eco-friendly

Greeting Card with Happenin' Holiday with gold foil lined envelope and 3 logos.Card is printed on environmentally friendly SFI certified stock. Select the text that you like best or write your own at no additional cost.

Greeting Card with Happenin' Holiday

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Item Size:

5 x 7

Price includes your full color imprint in 3 standard locations - front of card, back of card and inside of card under stock verse selection. A set-up charge is additional at $25.00. Select the text that you like best or write your own at no additional cost.

Imprint Option 1:

Location: Front, Back, and/or Inside
Imprint Method: 4 Color Process
Imprint Area:
Set-up Charge: $25.00

Note: 1) Every order is unique and additional charges that are not listed may apply. For example, additional charges may be required for imprint color changes, copy changes, product assortments, packaging, etc. Price subject to change without notice. 2) Due to difference among color monitors, the colors that appear may not be exact.

What is the minimum order quantity?

Minimum Orders for this promotional item are listed as the first price column. You must order at least the minimum for customized or blank merchandise.

What is production time?

Production time is the time it takes to print and package merchandise. It does not include the time it takes for order processing and proof approval. Depending on the product, rush production may be available.

Standard Production: Standard production time varies. It is dependent on product, manufacturer, and printing method.

Rush Production: Rush production is available on a selection of products in our catalog. Rush production is sometimes called Rush Service or Rush Imprinting Service. Rush service can vary from 24hrs to 72hrs. Most rush items are limited to a one color/one location imprint. When ordering a rush product please be sure to review the rush service terms.

NOTE: Standard/Rush Production time does not include transit time for shipping and delivery.

What is an Imprint Area and Imprint Location?

Imprint Area: The imprint area is the allowable portion of a promotional product reserved for the printed advertising message. All artwork is different and your artwork may require adjustments in order to print it at its best without sacrificing quality. The size and placement of the artwork may vary from the proof when actually printed on the product. Proofs are for artwork verification & layout.

Imprint Location: The area that your logo/message is imprinted. Each product displays the available imprint locations.

What are Set-up, Run Charges, and Additional Charges?

Set-up: Set-up charges are different for every item and can be different for each imprint method. Set-ups are required by the factory to set-up the machinery and materials needed to personalize products with your logo, artwork and/or message. For example the set-up charge is used to create silk screens, tapes, dies and molds. Each product and/or imprinting method requires a different set-up process. The set-up charge is not based on the quantity ordered. A setup is the same whether the order is 20 pieces or 20000 pieces. The fee is applied per imprint color and imprint location. Some products may require you to order a specific amount for a particular imprint method.

Run Charge: Run charges are also different for every item and can be different for each imprint method. They are additional charges necessary to complete the imprinting of your items. Run charges, for example are added for secondary locations and/or colors. They can also be packaging charges or other options that are not included in the base price of the product.

Additional Charges: Additional Charges are things such as packaging fees, additional product accessories and options.

What are Pantone and Stock Imprint Colors?

Pantone: The PANTONE MATCHING SYSTEM (sometimes referred to as "PMS") identifies over 500 colors and the formulas for creating ink in those colors. Four-color process printing can only approximate many of these colors. You can select PANTONE Colors in various illustration and desktop publishing software programs.

Stock Colors: These are the standard colors that are kept in stock for each product line.

What are Blank Goods?

When you select to order Blank Goods, you are ordering the product with no artwork personalization.

Glossary e-Proofs Help with Artwork

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