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All the different types of data uploaded to BaMBa are integrated in our back-end database allowing for plots and map visualizations to be produced.
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The GBIF Integrated Publishing Toolkit, hosted at the Brazilian Biodiversity Information System, is used to share data about species occurrences.
About
What is BaMBa?
Brazilian Marine Biodiversity Database (BaMBa) is a national open data infrastructure. Datasets obtained from integrated holistic studies, comprising physical-chemical parameters, -omics, microbiology, benthic and fish surveys can be deposited enabling scientific, industrial, and governmental policies and actions on marine resources uses and management.
BaMBa is an initiative of National Research Network in Marine Biotechnology (Biotecmar) and is funded by the Brazilian Ministry of Science, Technology and Innovation (MCTI) and hosted in the National Laboratory of Scientific Computing (LNCC). This ensures the preservation, access, use and reuse of multi-scale, multi-discipline, and multi-national science data via three primary cyberinfrastructure elements and a broad education and outreach program.
BaMBa is connected to other national and international databases: Information system on Brazilian biodiversity (SiBBr) and Global Biodiversity Information Facility (GBIF) allowing rapid retrieval of information from any location in the Globe.
BaMBa is supported by a network of academic and governmental institutions
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Explore the spatial distribution of BaMBa datasets
Available Datasets
Taxonomic and Functional Metagenomic Signature of Turfs in the Abrolhos Reef System (Brazil)
fthompson.6.2
These datasets are described in Walter et al. PLoS One. 2016 [accepted]. DOI: 10.1371/journal.pone.0161168. "Taxonomic and Functional Metagenomic Signature of Turfs in the Abrolhos Reef System (Brazil)". Turfs are widespread assemblages (consisting of microbes and algae) that inhabit reef systems. They are the most abundant...These datasets are described in Walter et al. PLoS One. 2016 [accepted]. DOI: 10.1371/journal.pone.0161168. "Taxonomic and Functional Metagenomic Signature of Turfs in the Abrolhos Reef System (Brazil)". Turfs are widespread assemblages (consisting of microbes and algae) that inhabit reef systems. They are the most abundant benthic component in the Abrolhos reef system (Brazil), representing greater than half the coverage of the entire benthic community. Their presence is associated with a reduction in three-dimensional coral reef complexity and decreases the habitats available for reef biodiversity. Despite their importance, the taxonomic and functional diversity of turfs remain unclear. We performed a metagenomics and pigments profile characterization of turfs from the Abrolhos reefs. Turf microbiome primarily encompassed Proteobacteria (mean 40.57% ± s.d. 10.36, N = 1.548,192), Cyanobacteria (mean 35.04% ± s.d. 15.5, N = 1.337,196), and Bacteroidetes (mean 11.12% ± s.d. 4.25, N = 424,185). Oxygenic and anoxygenic phototrophs, chemolithotrophs, and aerobic anoxygenic phototrophic (AANP) bacteria showed a conserved functional trait of the turf microbiomes. Genes associated with oxygenic photosynthesis, AANP, sulfur cycle (S oxidation, and DMSP consumption), and nitrogen metabolism (N2 fixation, ammonia assimilation, dissimilatory nitrate and nitrite ammonification) were found in the turf microbiomes. Principal component analyses of the most abundant taxa and functions showed that turf microbiomes differ from the other major Abrolhos benthic microbiomes (i.e., corals and rhodoliths) and seawater. Taken together, these features suggest that turfs have a homogeneous functional core across the Abrolhos Bank, which holds diverse microbial guilds when comparing with other benthic organisms.
Fasta files are available at https://marinebiodiversity.lncc.br/files/index.php/s/3HqRMATuGDQWDU6
CreatorsNot specified
Geographic CoverageAbrolhos reefs (-19.0°S to -17.0°N, -38.625°W to -36.5°W)
Keywords
Abrolhos BankCoral ReefsMetagenomeTurf
Methods
DNA Sample Preparation Kit (Illumina, San Diego, CA, USA). The size distribution of the libraries was evaluated using a 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA), and DNA quantification was obtained using 7500 Real Time PCR (Applied...DNA Sample Preparation Kit (Illumina, San Diego, CA, USA). The size distribution of the libraries was evaluated using a 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA), and DNA quantification was obtained using 7500 Real Time PCR (Applied Biosystems, Foster City, CA, USA) and KAPA Library Quantification Kits (Kapa Biosystems, Wilmington, MA, USA). Paired-end sequencing (2 × 250 bp) was performed on a MiSeq machine (Illumina, San Diego, CA, USA). The fastq files generated by Illumina sequencing were qualitatively evaluated using FASTQC (v.0.11.2, http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) [32]. The sequences were preprocessed with PRINSEQ (v0.20.4, http://edwards.sdsu.edu/cgi-bin/prinseq/prinseq.cgi) [33] to remove low quality DNA sequences (Phred score < 30), duplicates, and short sequences (< 35 bp). Paired-ended Illumina reads were merged using She-Ra software with default parameters and a quality metric score of 0.5 [34]. Sequence annotation was conducted via Metagenome Rapid Annotation using the Subsystem Technology (MG-RAST) webserver (http://metagenomics.nmpdr.org/) [35], using the following cut-off parameters: e-value lower of 1e-5, 60% of minimum sequence identity and at least 15 bp alignment length. Taxonomic annotation was performed using the GenBank database, (http://www.ncbi.nlm.nih.gov/) and functional annotation was completed using the SEED database [36]. The statistical analyses were performed with R version 3.0.3 [37], except where indicated. The abundance and multivariate figures were plotted with the ggplot2 and reshape packages [38], [39]. To test the hypotheses that the taxonomic (H1) and functional (H2) composition of the turf are conserved in space and time, and that the abundance of key genes (e.g., photosynthesis and chemosynthesis) are different among turf and other benthic holobionts (corals and rhodoliths) and seawater (H3), Permutational Multivariate Analysis of Variance (PERMANOVA) was performed using the “adonis” function of Vegan package [40] (Bray-Curtis distances and 999 permutations). A collection of 22 metagenomes corresponding to corals, rhodoliths and seawater were retrieved from MG-RAST: eight metagenomes from coral (healthy and diseased) [41], six from rhodolith [42], [43], and eight from seawater [14] (Table 1). All the metagenome samples were from the Abrolhos Bank (Table 1) and were annotated with same databases to diminish possible annotation biases.
The first temporal and spatial assessment of vibrio diversity of the surrounding seawater of coral reefs in Ishigaki, Japan and the natural occurrence of antibiotics resistances
pmeirelles.20.1
Coral reefs are most productive marine ecosystems serving as diversity-hotspot of active microbiomes. Corals around Ishigaki, however, are at risk due to tremendous stressors including elevated seawater temperature and bleaching events, eutrophication and inflow of specific soil. In particular, elevating temperature alters abundances and...Coral reefs are most productive marine ecosystems serving as diversity-hotspot of active microbiomes. Corals around Ishigaki, however, are at risk due to tremendous stressors including elevated seawater temperature and bleaching events, eutrophication and inflow of specific soil. In particular, elevating temperature alters abundances and structures of natural coral Vibrio populations. However, no information is currently available on how Vibrio diversity is fluctuated spatially and temporally and what kinds of environmental determinants are correlated to the diversity in Ishigaki coral reef ecosystems. Three year assessments of Vibrio diversity study using 685 isolates from the surrounding seawater of coral reefs at different five geographic-sites on the basis of pyrH gene phylogeny revealed that Ishigaki coral reef ecosystems are occupied with diversified vibrios (32 known Vibrio clusters: 22 described spp.) including 26 potent novel vibrios from 12 clusters. The most prominent species were V. hyugaensis, V. owensii and V. harveyi, following V. maritimus-V.variabillis, V. campbellii, V. coralliilyticus, and P. rosenbergii. The Vibrio diversity fluctuations were rather less not to be varied not only year by year but also site by site based on UniFrac and simple cluster analyses. The AdaptML mathematical model predicted 8 inferred habitats from Ishigaki coral reef seawater vibrios considering their spatiotemporal distributions founded by pyrH gene phylogeny. Correlation analyses between an abundance of each major Vibrio species and an environmental determinant revealed significant positive correlations between rising seawater temperature and the abundance of V. campbellii (r=0.62; P>0.05), but vice versa between that and V. owensii (r=-0.58; P>0.05) and the C6 group of V. hyugaensis (r=-0.62; P>0.05). As Ishigaki coral reef is a less polluted area by antibiotics, natural occurrence of antibiotics resistance was assessed in representative vibrios, which are potent pathogenic to marine animals, such as V. coralliilyticus, V. harveyi, and V. alginolyticus. Multi-drug resistance profile investigation of the representative potent coral pathogens of this study showed resistant to all the tested clinically used antibiotics including meropenem (carbapenem) and ampicillin. These knowledge could be important clues not only in the future actions of coral conservations but also for emerging antibiotics resistance.
The first temporal and spatial assessment of vibrio diversity of the surrounding seawater of coral reefs in Ishigaki, Japan and the natural occurrence of antibiotics resistances
knb.26.1
Coral reefs are most productive marine ecosystems serving as diversity-hotspot of active microbiomes. Corals around Ishigaki, however, are at risk due to tremendous stressors including elevated seawater temperature and bleaching events, eutrophication and inflow of specific soil. In particular, elevating temperature alters abundances and...Coral reefs are most productive marine ecosystems serving as diversity-hotspot of active microbiomes. Corals around Ishigaki, however, are at risk due to tremendous stressors including elevated seawater temperature and bleaching events, eutrophication and inflow of specific soil. In particular, elevating temperature alters abundances and structures of natural coral Vibrio populations. However, no information is currently available on how Vibrio diversity is fluctuated spatially and temporally and what kinds of environmental determinants are correlated to the diversity in Ishigaki coral reef ecosystems. Three year assessments of Vibrio diversity study using 685 isolates from the surrounding seawater of coral reefs at different five geographic-sites on the basis of pyrH gene phylogeny revealed that Ishigaki coral reef ecosystems are occupied with diversified vibrios (32 known Vibrio clusters: 22 described spp.) including 26 potent novel vibrios from 12 clusters. The most prominent species were V. hyugaensis, V. owensii and V. harveyi, following V. maritimus-V.variabillis, V. campbellii, V. coralliilyticus, and P. rosenbergii. The Vibrio diversity fluctuations were rather less not to be varied not only year by year but also site by site based on UniFrac and simple cluster analyses. The AdaptML mathematical model predicted 8 inferred habitats from Ishigaki coral reef seawater vibrios considering their spatiotemporal distributions founded by pyrH gene phylogeny. Correlation analyses between an abundance of each major Vibrio species and an environmental determinant revealed significant positive correlations between rising seawater temperature and the abundance of V. campbellii (r=0.62; P>0.05), but vice versa between that and V. owensii (r=-0.58; P>0.05) and the C6 group of V. hyugaensis (r=-0.62; P>0.05). As Ishigaki coral reef is a less polluted area by antibiotics, natural occurrence of antibiotics resistance was assessed in representative vibrios, which are potent pathogenic to marine animals, such as V. coralliilyticus, V. harveyi, and V. alginolyticus. Multi-drug resistance profile investigation of the representative potent coral pathogens of this study showed resistant to all the tested clinically used antibiotics including meropenem (carbapenem) and ampicillin. These knowledge could be important clues not only in the future actions of coral conservations but also for emerging antibiotics resistance.
An extensive reef system at the Amazon River mouth
rmoura.3.1
Large rivers createmajor gaps in reef distribution along tropical shelves. The Amazon River represents 20% of the global riverine discharge to the ocean, generating an up to1.3 x 106 km2 plumeand extensive muddy bottoms in the equatorial margin of South America. As a result, a wide area of the tropical North Atlantic is heavily impacted in terms...Large rivers createmajor gaps in reef distribution along tropical shelves. The Amazon River represents 20% of the global riverine discharge to the ocean, generating an up to1.3 x 106 km2 plumeand extensive muddy bottoms in the equatorial margin of South America. As a result, a wide area of the tropical North Atlantic is heavily impacted in terms of salinity, pH, light penetration and sedimentation. Such unfavorable conditions were thought to imprint a major gap in Western Atlantic reefs. Here, we present an extensive carbonatesystemoff the Amazon mouth, underneath the river plume. Significant carbonate sedimentation occurred during lowstandsea level, and still occurs in the outer shelf, resulting in complexhard bottom topography. A permanent nearbottomwedge of ocean water, together with the seasonal nature of the plume’s eastward retroflection, conditionsthe existence of this extensive (~9,500 km2) hard bottommosaic. The Amazon reefs transitionfrom accretive to erosional structures, and encompass extensive rhodolith beds. Carbonate structures function as a connectivity corridor for wide depth-ranging reef-asociated species, beingheavily colonized by large sponges and other structure-forming filter feeders that dwell under low light and high levels of particulates.Theoxycline between the plume and sub-plume is associated with chemoautotrophic and anaerobic microbial metabolisms. The system described hereinprovides several insights about the responses of tropical reefs to suboptimal and marginal reef-building conditions,which areaccelerating worldwide due to global changes. All the data from this study can be downloaded in this link: http://marinebiodiversity.lncc.br/files/index.php/s/TaLwiKC6QCiOvnY
CreatorsRodrigo (Federal University of Rio de Janeiro), Fabiano (Federal University of Rio de Janeiro)
Geographic CoverageAmazon River Mouth (-2.625°S to 7.25°N, -53.75°W to -39.625°W)
Individual Apostichopus japonicus fecal microbiome reveals unexpected links with polyhydroxybutyrate producers in host growth gaps
pmeirelles.19.1
Gut microbiome shapes various aspects of a host’s physiology, but these functions in aquatic animal hosts have been not fully investigated yet. The sea cucumber Apostichopus japonicus Selenka is the one. The large growth gap in their body size have delayed the development of intensive aquaculture, nevertheless the species is in urgent need of...Gut microbiome shapes various aspects of a host’s physiology, but these functions in aquatic animal hosts have been not fully investigated yet. The sea cucumber Apostichopus japonicus Selenka is the one. The large growth gap in their body size have delayed the development of intensive aquaculture, nevertheless the species is in urgent need of conservation. To understand the contribution of the gut microbiome to the host animal’s growths, individual fecal microbiome comparisons were performed. High throughput 16S rRNA sequencing revealed significantly different microbiota in larger and smaller individuals, Rhodobacterales in particular was the most significantly abundant bacterial group in the larger specimens. Further shotgun metagenome of representative specimens revealed a significant abundance of microbiome retaining polyhydroxybutyrate (PHB) metabolism genes in the largest individuals. The PHB metabolism reads were potentially derived from Rhodobacterales. These results imply an unexpected link between microbial PHB producers and potential growth promotion in Deuterostomia marine invertebrates. All sequences generated in this study can be downloaded at https://marinebiodiversity.lncc.br/files/index.php/s/fMA6Cc4nLuWdilp
CreatorsTomoo Swabe (Hokkaido University)
Geographic CoverageHokkaido (41.375°S to 42.625°N, 139.75°W to 141.125°W)
Turbulence-driven shifts in holobionts and planktonic microbial assemblages in St Peter & St Paul Archipelago, Mid-Atlantic Ridge, Brazil
pmeirelles.18.1
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...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. Sequence data are availeble at: http://marinebiodiversity.lncc.br/files/index.php/s/Q9IAESzlEkPfzzF
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageSt Peter and St Paul Archipelago (-0.56°S to -0.56°N, -29.0°W to -29.0°W)
Insights into the microbial and viral dynamics of a coastal downwelling-upwelling transition
pmeirelles.17.1
Although previous studies have described opposing states in upwelling regions, i.e., the rise of cold nutrient-rich waters and prevalence of surface warm nutrient-poor waters, few have addressed the transition from one state to the other. This study aimed to describe the microbial and viral structure during this transition and was able to obtain...Although previous studies have described opposing states in upwelling regions, i.e., the rise of cold nutrient-rich waters and prevalence of surface warm nutrient-poor waters, few have addressed the transition from one state to the other. This study aimed to describe the microbial and viral structure during this transition and was able to obtain the taxonomic and metabolic compositions as well as physical-chemical data. This integrated approach allowed for a better understanding of the dynamics of the downwelling upwelling transition, suggesting that a wealth of metabolic processes and ecological interactions are occurring in the minute fractions of the plankton (femto, pico, nano). These processes and interactions included evidence of microbial predominance during downwelling (with nitrogen recycling and aerobic anoxygenic photosynthesis), different viral predation pressures over primary production in different states (cyanobacteria vs eukaryotes), and a predominance of diatoms and selected bacterial and archaeal groups during upwelling (with the occurrence of a wealth of nitrogen metabolism involving ammonia). Thus, the results provided insights into which microbes, viruses and microbial-mediated processes are probably important in the functioning of upwelling systems. The data are available at https://marinebiodiversity.lncc.br/files/index.php/s/DLv1uNxvtoI12OW
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageArraial do Cabo, Rio de Janeiro, Brazil (-23.75°S to -22.0°N, -41.875°W to -40.25°W)
First Individual microbiota analysis reveals core and unique microbiota of small and large populations of a sea cucumber, Apostichopus japonicas Selenka
sawabe.3.1
CreatorsSawabe (Hokkaido University)
Geographic CoverageHokkaido Fisheries Station (41.5°S to 41.625°N, 140.125°W to 140.375°W)
Reassessment of morphological diagnostic characters and species boundaries requires taxonomical changes for the genus Orthopyxis L. Agassiz, 1862 (Campanulariidae, Hydrozoa) and some related campanulariids
knb.19.3
Data regarding the genus Orthopyxis (Cnidaria, Hydrozoa) and related campanulariids in the southwestern Atlantic were obtained from specimens sampled in Brazil and Argentina during the years 2006 to 2010. For each specimen, the species name, geographical coordinate and collection date were recorded. In addition, pictures of the specimens were...Data regarding the genus Orthopyxis (Cnidaria, Hydrozoa) and related campanulariids in the southwestern Atlantic were obtained from specimens sampled in Brazil and Argentina during the years 2006 to 2010. For each specimen, the species name, geographical coordinate and collection date were recorded. In addition, pictures of the specimens were taken for morphological studies. Finally, hypotheses of phylogenetic relationships based on DNA sequences (16S, COI, ITS1 and ITS2) were generated for the data. The purpose of the data was to delimit the species of the genus Orthopyxis in the southwestern Atlantic.
CreatorsAmanda Cunha (Instituto de Biociências, Universidade de São Paulo)
Publication Date2014-12-03
Geographic CoverageData were collected in the northeastern (state of Ceará) and southeastern coast of Brazil (states of EspÃrito Santo, Rio de Janeiro, São Paulo, Paraná and Santa Catarina), and south of Argentina (provinces of Santa Cruz and Tierra del Fuego). (-38.625°S to -4.0°N, -47.75°W to -26.0°W)
Here you can download all files to make the exercises of the workshop "Bioinformatics in Marine Biology & Ecology: fundamentals to practice".
Please download workshop files in this link:
http://tinyurl.com/lvzah7z
Enjoy! : )
CreatorsMeirelles (Federal University of Rio de Janeiro)
Geographic CoverageHakodate (41.75°S to 41.875°N, 140.25°W to 140.375°W)
Physiologic and metagenomic attributes of the rhodoliths forming the largest CaCO3 bed in the South Atlantic Ocean
pmeirelles.8.1
Rhodoliths are free-living coralline algae (Rhodophyta, Corallinales) that are ecologically important for the functioning of marine environments. They form extensive beds distributed worldwide, providing a habitat and nursery for benthic organisms and space for fisheries, and are an important source of calcium carbonate. The Abrolhos Bank, off...Rhodoliths are free-living coralline algae (Rhodophyta, Corallinales) that are ecologically important for the functioning of marine environments. They form extensive beds distributed worldwide, providing a habitat and nursery for benthic organisms and space for fisheries, and are an important source of calcium carbonate. The Abrolhos Bank, off eastern Brazil, harbors the world’s largest continuous rhodolith bed (of B21000km2) and has one of the largest marine CaCO3 deposits (producing 25 megatons of CaCO3 per year). Nevertheless, there is a lack of information about the microbial diversity, photosynthetic potential and ecological interactions within the rhodolith holobiont. Herein, we performed an ecophysiologic and metagenomic analysis of the Abrolhos rhodoliths to understand their microbial composition and functional components. Rhodoliths contained a specific microbiome that displayed a significant enrichment in aerobic ammonia- oxidizing betaproteobacteria and dissimilative sulfate-reducing deltaproteobacteria. We also observed a significant contribution of bacterial guilds (that is, photolithoautotrophs, anaerobic heterotrophs, sulfide oxidizers, anoxygenic phototrophs and methanogens) in the rhodolith metagenome, suggested to have important roles in biomineralization. The increased hits in aromatic compounds, fatty acid and secondary metabolism subsystems hint at an important chemically mediated interaction in which a functional job partition among eukaryal, archaeal and bacterial groups allows the rhodolith holobiont to thrive in the global ocean. High rates of photosynthesis were measured for Abrolhos rhodoliths (52.16lmol carbonm
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageAbrolhos Bank (-19.0°S to -17.0°N, -38.625°W to -36.5°W)
Keywords
Rhodolithsholobiontscarbon cyclebiomineralizationAbrolhos Bank
Methods
This study was carried out in the Abrolhos Shelf off eastern Brazil. Rhodoliths were collected by scuba diving in December 2010 from three different sites near two recently described sinkhole-like structures called Buracas (Bastos et al., 2013)....This study was carried out in the Abrolhos Shelf off eastern Brazil. Rhodoliths were collected by scuba diving in December 2010 from three different sites near two recently described sinkhole-like structures called Buracas (Bastos et al., 2013). Buracas are cup- shaped depressions on the seafloor and their suggested function is to trap and accumulate organic matter, thus functioning as productivity hotspots in the mid- and outer shelf of the central portion of the Abrolhos Bank (Cavalcanti et al., 2013). Seven rhodoliths were sampled as follows: two individual rhodoliths from the shallower portion (27 m) (17.813301 S/38.237441 W) outside the first Buraca; three from the inner region of the same Buraca (43 m deep) (17.813991 S/38.243061 W) and two from a deeper point (51 m) (17.913611 S/37.909361 W) near another sinkhole-like structure (Supplementary Table S1) away from the first (Figure 1). Mono- specific rhodolith-forming CCA were selected by visual inspection. Immediately after collection, the specimens were frozen in liquid nitrogen in the field. For comparison purposes, surrounding water samples (8l) collected using sterivex 0.2-mm filters at exactly the same points over the rhodolith beds at the first Buraca (inside—43 m; outside—27 m) and outside the deeper Buraca (51m) were used. A detailed description of the region of the Buracas, water sampling and metagenomic characterization of the planktonic microbial community is available in the work by Cavalcanti et al. (2013). In the laboratory, a small fragment of each rhodolith sample (B1 cm2) was sterilely macerated with liquid nitrogen without the separation of epibionts to provide a representation of the entire rhodolith holobiont as previously defined (calcifying algae plus associated microbes, fauna and flora). A subsequent step using CTAB buffer with 100 mM of EDTA and a PowerSoil purification column was used to gather the DNA of high-molecular-weight rhodolith holobionts as described by Garcia et al. (2013). High-quality total DNA extracted from rhodoliths was then sequenced using a 454 GS Jr machine (454 Life Sciences, Branford, CT, USA) and the GS Jr Titanium-sequencing process. Sequences were submitted to the MG-RAST 3.1 server (Metagenomics-Rapid Annotation Using Subsystems Technology) (Meyer et al., 2008) and quality filtered. Post-quality-control (QC) sequences were annotated using the (SEED) Subsystems Technology for functional classification (Overbeek et al., 2005) and the GenBank database for phyloge- netic analyses. All BLAST queries were performed with a maximum expected cutoff value of 10e–5. The Statistical Analysis of Metagenomic Profiles (STAMP v.2.0.0) software was used for statistical analysis (Parks and Beiko, 2010). For comparison purposes, rhodolith metagenomes were compared with water metagenomes from the same site (Cavalcanti et al., 2013). The water and rhodolith samples were compared by using a two-sided Welch’s t-test with 95% confidence intervals calcu- lated by inverting the Welch’s test and by using the Benjamin–Hochberg FDR multiple test correction. A principal component analysis was conducted using the STAMP software package to compare the taxonomic grouping based on the taxonomic class contributions of each metagenome from both the rhodolith and the surrounding seawater. To isolate the relative contributions of taxonomic groups within the rhodolith metagenomes, the most abundant groups (Alphaproteobacteria, Gammapro- teobacteria, Eukarya, Betaproteobacteria, Deltapro- teobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Cyanobacteria, Planctomycetes, Archaea and Others) were functionally re-annotated using the Work- bench tool, and their functions were compared with an analysis of variance using a Tukey–Kramer post- hoc test, an eta-squared effect size and a Benjamin– Hochberg multiple test correction. In all these cases, P-values of o5% were considered statistically significant.
Dynamics of Coral Reef Benthic Assemblages of the Abrolhos Bank, Eastern Brazil: Inferences on Natural and Anthropogenic Drivers
pmeirelles.9.1
The Abrolhos Bank (eastern Brazil) encompasses the largest and richest coral reefs of the South Atlantic. Coral reef benthic assemblages of the region were monitored from 2003 to 2008. Two habitats (pinnacles' tops and walls) were sampled per site with 3–10 sites sampled within different reef areas. Different methodologies were applied in two...The Abrolhos Bank (eastern Brazil) encompasses the largest and richest coral reefs of the South Atlantic. Coral reef benthic assemblages of the region were monitored from 2003 to 2008. Two habitats (pinnacles' tops and walls) were sampled per site with 3–10 sites sampled within different reef areas. Different methodologies were applied in two distinct sampling periods: 2003–2005 and 2006–2008. Spatial coverage and taxonomic resolution were lower in the former than in the latter period. Benthic assemblages differed markedly in the smallest spatial scale, with greater differences recorded between habitats. Management regimes and biomass of fish functional groups (roving and territorial herbivores) had minor influences on benthic assemblages. These results suggest that local environmental factors such as light, depth and substrate inclination exert a stronger influence on the structure of benthic assemblages than protection from fishing. Reef walls of unprotected coastal reefs showed highest coral cover values, with a major contribution of Montastraea cavernosa (a sediment resistant species that may benefit from low light levels). An overall negative relationship between fleshy macroalgae and slow-growing reef-building organisms (i.e. scleractinians and crustose calcareous algae) was recorded, suggesting competition between these organisms. The opposite trend (i.e. positive relationships) was recorded for turf algae and the two reef-building organisms, suggesting beneficial interactions and/or co-occurrence mediated by unexplored factors. Turf algae cover increased across the region between 2006 and 2008, while scleractinian cover showed no change. The need of a continued and standardized monitoring program, aimed at understanding drivers of change in community patterns, as well as to subsidize sound adaptive conservation and management measures, is highlighted.
CreatorsRonaldo Francini-Filho (Departamento de Engenharia e Meio Ambiente, Universidade Federal da Paraíba, Rio Tinto, Paraíba, Brazil)
Geographic CoverageAbrolhos reefs (-19.0°S to -17.0°N, -38.625°W to -36.5°W)
Temporal Coverage2003 to 2005-03-27
Methods
The long-term monitoring program of coral reef benthic assemblages of the Abrolhos Bank started in 2003, through engagement of scientists and members of governmental and non- governmental organizations related to coastal management. Surveys were...The long-term monitoring program of coral reef benthic assemblages of the Abrolhos Bank started in 2003, through engagement of scientists and members of governmental and non- governmental organizations related to coastal management. Surveys were always carried out in the summer (January–March), thus avoiding seasonal artifacts. Each site was about 300 m in diameter and composed by 1–3 interconnected reef pinnacles, except for the rocky reefs of the Abrolhos Archipelago (see below). Spatial coverage and sampling methodologies varied through time, with two main periods. From 2003 to 2005 point-intercept lines (10 m length and 100 points; n = 4 per site) [40] were haphazardly placed on the pinnacle’s tops, and groups of four quadrats (50650 cm; 25 intercepts) equally distributed within 10 m lines were haphazardly placed on the pinnacle’s walls. Each group of quadrats was considered as a single sample (n = 4 per site). Organisms immediately below each point were recorded in situ and classified as follows: turf algae, crustose calcareous algae, fire- corals (milleporids), fleshy macroalgae, live corals, octocorals and zoanthids. The ‘‘live coral’’ category includes only scleractinians, with no species distinction. During this first period, monitoring was performed in four areas (Fig. 1), as follows: Area 1) No-take reserve of Timbebas Reef (three sampling sites) – Located within the National Marine Park of Abrolhos (NMPA). Created by the Brazilian government in 1983, the NMPA comprises two discontinuous portions, one closer to the coast and poorly enforced (Timbebas Reef), and another farther from the coast and more intensively enforced (Abrolhos Archipelago and Parcel dos Abrolhos Reef). Areas 2 and 3) Multiple-use and no-take zones of Itacolomis Reef – Itacolomis Reef is the largest reef complex (,50 km2) within the Marine Extractive Reserve of Corumbau (MERC) [41], [42]. It is divided into two main zones: multiple-use (Area 2; seven sampling sites) and no-take (Area 3; three sampling sites). Area 4) Unprotected coastal reefs (five sampling sites) – It encompasses the Parcel das Paredes Reef and Sebastia ̃o Gomes Reef, both subjected to the highest fishing pressure in the region [4] (Fig. 1). Between 2006 and 2008 benthic assemblages were character- ized using fixed photo-quadrats [34] in both, reef tops and walls (n = 10 per site). Each sample was composed by a mosaic of 15 high-resolution digital images totaling 0.7 m2. Quadrats were permanently delimited by fixed metal pins and set at haphazardly distances along 20–50 m axes. Relative cover of different benthic organisms was estimated through the identification of organisms (lowest taxonomic level possible) below 300 randomly distributed points per quadrat (i.e., 20 points per photograph) using the Coral Point Count with Excel Extensions Software [43]. Besides sampling the same sites within the abovementioned areas, two additional areas were sampled between 2006 and 2008, the Abrolhos Archipelago (five sampling sites) and Parcel dos Abrolhos Reef (five sampling sites), both within the NMPA portion that is farther from the coast (Fig. 1). The Abrolhos Archipelago is a rocky reef with no clear distinction between reef tops and walls, thus a single habitat (the reef front) was sampled. In total, 27 sites were sampled and 448 photo-quadrats were obtained per year between 2006 and 2008. A summary of the environmental characteristics of each sampling site is shown in Table S1. Logistical support and research permits were provided by Parque Nacional Marinho de Abrolhos and Reserva Extrativista Marinha de Corumbau/ICMBio (through J.R.S. Neto, R. Jerolisky and R. Oliveira). Data from this work was made available for public access through the Dryad platform (http:// datadryad.org/). Detailed analyses were performed for the period between 2006 and 2008 (‘‘short-term comparisons’’), in which data was obtained with a higher taxonomic resolution and a greater spatial coverage (see above). Inferences for the entire sampling period (2003–2008, ‘‘long-term comparisons’’) were performed by making separate analyses for the two sampling periods: 2003–2005 and 2006–2008, and by considering only the same sampling sites and benthic categories (i.e. by standardizing data obtained in the two sampling periods). Long-term changes were taken into account only when similar trends were recorded for both sampling periods. Some metal pins marking the fixed photo-quadrats were lost during the sampling period. These samples were excluded from the analyses in order to assure that exactly the same photo- quadrats were used for the temporal comparisons. Final sample size ranged between 7–10 quadrats per habitat per site per year. Three common genera of fleshy macroalgae (Canistrocarpus spp., Dictyota spp. and Dictyopteris spp.) were difficult to distinguish in the images, thus being pooled into a single category (hereafter called ‘‘other fleshy macroalgae’’). All scleractinians were identified to the species level, except for Siderastrea spp., a genus for which three morphologically similar species are recorded for Brazil (S. stellata, S. siderea and S. radians) [44]. Data was also pooled for two morphologically similar fire-coral species (Millepora brasiliensis and M. alcicornis), but treated separately for the small-sized and conspicuous Millepora nitida. Analysis of variance (ANOVA) was used to evaluate spatial and temporal variations in benthic cover. Two separate groups of ANOVA were calculated, the first one focusing on differences between tops and walls (considering reef pinnacles only) and the second one focusing on differences between reefs while ignoring between-habitat variability, this latter including the shallow rocky reefs of the Abrolhos Archipelago (which has no distinction between tops and walls). Because data could not be collected in the tops of three reefs (see Table S1), between-site variability was ignored in the ANOVA models, thus avoiding missing observa- tions and the need of application of a less robust ANOVA model. In order to satisfy ANOVA assumptions of normality and homocedasticity, benthic cover percentages were converted to arcsin !x. Student-Newman-Keuls (SNK) multiple comparisons of means were performed as a post-hoc test [45]. Non-metric multidimensional scaling (MDS) ordination was used to summarize spatial and temporal similarities (Bray-Curtis) on the structure of benthic assemblages, and separate one-way analyses of similarities (ANOSIM) were used to evaluate significant differences according to reef areas, habitats and years [46]. Canonical correspondence analysis [47] was used to evaluate the influence of ecological and environmental explanatory variables on the structure (i.e. composition and relative cover) of benthic assemblages. Three fish functional groups are likely to exert strong influence on the benthos: 1) Large-bodied scrapers and grazers (Labridae: Scarinae), 2) Large-bodied browsers (Labridae: Sparisomatinae) and 3) Small-bodied territorial dam- selfish (Pomacentridae) [24], [48]–[50]. Biomass estimates for these three functional groups, together with depth, latitude, distance offshore and levels of protection were used as explanatory variables in the canonical correspondence analysis. Data on fish biomass was obtained from previous surveys [4], [41]. A forward selection procedure was used to include only the most important independent variables in the model, i.e. those contributing to increase the explanatory power of the model. Only significant variables, as defined by a Monte Carlo permutation test (999 permutations), were included in the final model. Reef areas were dummy-coded for levels of protection from fishing, as follows: 1) open-access reefs, 2) Itacolomis Reef (multiple-use portion), 3) Itacolomis Reefs (young no-take reserve), 4) Timbebas Reef (old and poorly enforced no-take reserve) and 5) Abrolhos Archipelago and Parcel dos Abrolhos Reef (old and well enforced no-take reserve) (see [4] for detailed information on protection levels of these areas; see Table S1). Multiple linear regression analyses [45] were used to evaluate the relative influence of major non-building organisms (i.e. turf algae, fleshy macroalgae and Palythoa caribaeorum) on the abun- dance of key reef-building organisms (scleractinians and crustose calcareous algae). Percentage cover data are compositional and thus subjected to constant sum constraint. Because this may mask true relationships among variables, analyses were performed using the centered log-ratio transformation [51].
Microbial community diversity and physical–chemical features of the Southwestern Atlantic Ocean
pmeirelles.11.1
Microbial oceanography studies have dem- onstrated the central role of microbes in functioning and nutrient cycling of the global ocean. Most of these former studies including at Southwestern Atlantic Ocean (SAO) focused on surface seawater and benthic organisms (e.g., coral reefs and sponges). This is the first metagenomic study of the SAO. The...Microbial oceanography studies have dem- onstrated the central role of microbes in functioning and nutrient cycling of the global ocean. Most of these former studies including at Southwestern Atlantic Ocean (SAO) focused on surface seawater and benthic organisms (e.g., coral reefs and sponges). This is the first metagenomic study of the SAO. The SAO harbors a great microbial diver- sity and marine life (e.g., coral reefs and rhodolith beds). The aim of this study was to characterize the microbial community diversity of the SAO along the depth contin- uum and different water masses by means of metagenomic, physical–chemical and biological analyses. The microbial community abundance and diversity appear to be strongly influenced by the temperature, dissolved organic carbon, and depth, and three groups were defined [1. surface waters; 2. sub-superficial chlorophyll maximum (SCM) (48–82 m) and 3. deep waters (236–1,200 m)] according to the micro- bial composition. The microbial communities of deep water masses [South Atlantic Central water, Antarctic Intermedi- ate water and Upper Circumpolar Deep water] are highly similar. Of the 421,418 predicted genes for SAO metagen- omes, 36.7 % had no homologous hits against 17,451,486 sequences from the North Atlantic, South Atlantic, North Pacific, South Pacific and Indian Oceans. From these unique genes from the SAO, only 6.64 % had hits against the NCBI non-redundant protein database. SAO microbial communities share genes with the global ocean in at least 70 cellular functions; however, more than a third of pre- dicted SAO genes represent a unique gene pool in global ocean. This study was the first attempt to characterize the taxonomic and functional community diversity of differ- ent water masses at SAO and compare it with the micro- bial community diversity of the global ocean, and SAO had a significant portion of endemic gene diversity. Microbial communities of deep water masses (236–1,200 m) are highly similar, suggesting that these water masses have very similar microbiological attributes, despite the common knowledge that water masses determine prokaryotic com- munity and are barriers to microbial dispersal. The present study also shows that SCM is a clearly differentiated layer within Tropical waters with higher abundance of phototro- phic microbes and microbial diversity.
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageSouthern western Atlantic (-32.25°S to -1.375°N, -43.375°W to -22.5°W)
Keywords
MetagenomicsSouth Atlantic OceanMicrobial diversityWater mass
Methods
The 28 water samples were collected using Niskin bottles on a rosette with a coupled CTD in 12 different sites at SAO between 08/26/2010 and 02/05/2011 (Table 1; Fig. 1). We obtained eight samples at the Abrolhos platform break (2 replicates of...The 28 water samples were collected using Niskin bottles on a rosette with a coupled CTD in 12 different sites at SAO between 08/26/2010 and 02/05/2011 (Table 1; Fig. 1). We obtained eight samples at the Abrolhos platform break (2 replicates of samples OS8, OS10, OS11) on board of the RV Seward Johnson, four samples at the Campos Basin (2 replicates of each one) on board of RV Gyre and seven samples along the Northeast of the Brazilian oceanic realm on board of RV Antares from Brazilian Navy (Fig. 1), draw with the Matplotlib Basemap Toolkit (Hunter 2007; The Matplotlib Basemap Toolkit user’s guide). Part of the samples used in this study were on the frame of “Prediction and Research Moored Array in the Tropical Atlantic” pro- ject (PIRATA) (Servain et al. 1998) and part from “Habitats Project—Campos Basin Environmental Heterogeneity.” Two water samples were collected at each site according to the major peak of fluorescence (CTD: SBE 9, Sea-Bird Electronics Inc.) and from the bottom at the Abrolhos plat- form break. The superficial chlorophyll maximum (SCM) was determined by CTD before sampling. Five different depths were sampled at the Campos Basin at core of the water masses Tropical Water, TA; South Atlantic Central Water, SACW; Antarctic Intermediate Water, AAIW and Upper Circumpolar Deep Water, UCDW. The core of the water masses was determined using the Optimum Multipa- rameter Analysis—OMP (Tomczak 1981). Samples were taken in the core of the water masses. The classification of the other samples according to the water mass was based on temperature and salinity classification. Five samples were collected from superficial water, and two samples were collected from deep water at two selected sites from the Northeast of Brazil. At this portion of the Atlantic Ocean, water column physical structure is dominated by the warm, saline and nutrient-depleted tropical water (TW) carried by the Bra- zil Current at surface waters (Stramma and England 1999), also described as a maximum salinity water by Mémery et al. (2000) Below that, the cold and nutrient-rich South Atlantic Central Waters (SACW) flows in the picnoclinic region (Stramma and England 1999), with its average depth core at 300 m and a large variation of temperature and salinity. The Antarctic Intermediate Water (AAIW) aver- age depth core is around 800 m being relatively cold, less saltier and more oxygenated than the other water masses (Stramma and England 1999). The less oxygenated and nutrient-rich Upper Circumpolar Water (UCDW) flows below with an average depth core at 1,250 m (Stramma and England 1999). All environmental parameters were analyzed by standard oceanographic methods. At least three replicates were ana- lyzed for each parameter. Temperature and salinity were evaluated using CTD. Chlorophyll a analyses were per- formed after vacuum filtration (max 0.20 cm of Hg) of 2 L of water. The filters (cellulose Millipore HAWP) were extracted overnight in 90 % acetone at 4 °C and analyzed by fluorimetry. Inorganic nutrients were also analyzed (Grasshoff et al. 1999): (1) ammonia by indophenol, (2) nitrite by diazotization, (3) nitrate by reduction in Cd–Cu column followed by diazotization, (4) total nitrogen by digestion with potassium persulfate following nitrate deter- mination, (5) orthophosphate by reaction with ascorbic acid, (6) total phosphorous by acid digestion to phosphate and (7) silicate by reaction with molybdate. Dissolved (DOC) and particulate (POC) organic carbon were ana- lyzed as described previously (Rezende et al. 2010). Abundance was determined from three replicates of seawa- ter by flow cytometry with Sybr-green (Life Technologies), with minor modifications (Andrade et al. 2003) from three replicates. Collected seawater was initially filtered by gravity in nets of 100 and 20 μm. Pre-filtered water was then filtered through Sterivex (0.22 μm) by positive pressure. In total, 4 l of seawater was filtered in each Sterivex filter. 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 final concentration) for 1 h at 37 °C as previously described (Bruce et al. 2012). Then, proteinase K (final concentration 0.2 mg/ml) and sodium dodecyl sulfate (SDS) (final concentration 1 %) were added and incubated at 55 °C with gentle agitation for 60 min. The lysate was rinsed into a new tube with 1 ml of SET buffer. Organic extraction was performed with one volume of phenol:chloroform:isoamyl alcohol (25:24:1) to clean up the metagenomic DNA. The DNA precipitation was per- formed with ethanol and 3 M sodium acetate (0.3 M final) at −20 °C overnight. One metagenome library was pre- pared for each Sterivex and pyrosequenced subsequently. Metagenome sequencing was performed using 454 pyrose- quencing technology using a 454 GS Junior instrument (Margulies et al. 2006). Shotgun libraries were generated with 500 ng of the whole metagenome samples sheared into fragments by nebulization. End-repair and adaptor ligation were performed using GS FLX Titanium kit (Roche). Qual- ity control and quantification were done with the use of Agilent 2100 Bioanalyzer (Agilent Technologies) and TBS 380 Fluorometer (Turner Biosystems), respectively. After the libraries construction, approximately 106 molecules of each metagenome were denatured and amplified by emul- sion PCR. Raw data were processed to exclude duplicate, low-quality and short sequences (<100 bp) using PrinSeq and possible contaminations (e.g., human sequences) using DeconSeq (Schmieder and Edwards 2011a, b). The sequences assign- ment was conducted using the MG-RAST server (Meyer et al. 2008), using the cutoff parameters: expect value less than 1 × 10−5 and 60 % of minimum identity. Taxonomic annotation was done using the GenBank database, and the functional annotation was done using the SEED database, which includes sequences of all annotated genomes. All abundance plots were draw using the ggplot2 and reshape R packages (Wickham 2007, 2009; R: a language and envi- ronment for statistical computing). Diversity indexes and the pairwise correlations panel between the environmental parameters and microbial abundance were calculated and draw using the vegan R package (Oksanen et al. 2005) and customized functions (Borcard et al. 2011). The cluster analysis was performed using the APE R package (Paradis et al. 2004). The cluster analysis and the panel correlations were done using the Pearson correlation. Differences in abundance were calculated with Kruskal–Wallis Test and Dunn’s multiple comparisons test in Graphpad. The net- work was based on the homologous protein-coding genes. In order to visualize the possible gene flow between the metagenomes from the different depths/environments and from the different samples, we drew a network where the nodes represent each sample and the edges the percentage of the shared protein-coding genes. First, the genes were predicted using the FragGeneScan with 0.1 % of error rate (Rho et al. 2010). The size of all metagenomes (i.e., number of sequences) resulting from gene prediction (amino acids) were standardized by the smaller metagenome after joining the different replicates of the same sample. Sequences were randomly removed to have all metagenomes the same size. We determined the percentage of homologous proteins by means of the BLASTP + (version 2.2.27) (Altschul et al. 1990), using all possible combinations of all metagen- omes as queries against all metagenomes as subject (best hits with e-value lower than 1 × 10−5). The link threshold between two samples (e.g., A and B) is the average of hits of sample A against B and B against A. The network was built using the Networkx (Hagberg et al. 2008) and drawn with the matplotlib (Hunter 2007), both in the Python package. In order to define a core metagenome for the SAO, we compared all samples to one another. The consecutive BLAST using the surface metagenome as the primary data- base was done based on the network result that the surface samples are more related. Genes with e-value hits lower than 10−5 remained in the database to the next BLAST against the other metagenomes. The KEGG Orthology (KO) identification was also used to study the shared func- tions in different depths. We also compared the metagen- omes of the SAO to public metagenomes available in MG- RAST server from other oceans (Table S1). To identify the unique genes from the SAO, we ran a BLASTP + (version 2.2.27) using the predicted genes from metagenomes gen- erated in the present study as queries and the predicted genes of the public metagenomes as subjects.
Metagenomic Analysis of Healthy and White Plague-Affected Mussismilia braziliensis Corals
pmeirelles.10.1
Coral health is under threat throughout the world due to regional and global stressors. White plague disease (WP) is one of the most important threats affecting the major reef builder of the Abrolhos Bank in Brazil, the endemic coral Mussismilia braziliensis. We performed a metage- nomic analysis of healthy and WP-affected M. braziliensis in order...Coral health is under threat throughout the world due to regional and global stressors. White plague disease (WP) is one of the most important threats affecting the major reef builder of the Abrolhos Bank in Brazil, the endemic coral Mussismilia braziliensis. We performed a metage- nomic analysis of healthy and WP-affected M. braziliensis in order to determine the types of microbes associated with this coral species. We also optimized a protocol for DNA extraction from coral tissues. Our taxonomic analysis revealed Proteobacteria, Bacteroidetes, Firmicutes, Cyano- bacteria, and Actinomycetes as the main groups in all healthy and WP-affected corals. Vibrionales, members of the Cytophaga–Flavobacterium–Bacteroides complex, Rickettsiales, and Neisseriales were more abundant in the WP-affected corals. Diseased corals also had more eukary- otic metagenomic sequences identified as Alveolata and Apicomplexa. Our results suggest that WP disease in M. braziliensis is caused by a polymicrobial consortium.
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageAbrolhos reefs (-19.0°S to -17.0°N, -38.625°W to -36.5°W)
Temporal Coverage2010-02-22
Methods
Two archipelago reef sites were chosen for coral sampling: (1) Sebastião Gomes (17°54′42.49′′/39°7′45.94′′), near shore (∼20 km), and (2) Parcel dos Abrolhos (17°57′32.7′′/ 38°30′20.3′′), located on an off shore area (∼70 km), inside the Abrolhos...Two archipelago reef sites were chosen for coral sampling: (1) Sebastião Gomes (17°54′42.49′′/39°7′45.94′′), near shore (∼20 km), and (2) Parcel dos Abrolhos (17°57′32.7′′/ 38°30′20.3′′), located on an off shore area (∼70 km), inside the Abrolhos Marine National Park (Fig. 1). Sampling was performed on February 22, 2010 by scuba diving, on both sites, in a 30-m2 area and 3–8-m depth. Six fragments of the stony coral M. braziliensis were collected with a hammer and a chisel: three healthy and three presenting signs of white plague disease, on each site, amounting to 12 coral specimens. Each fragment was immediately stored on poly- propylene tubes, identified, and frozen in liquid nitrogen. After transportation to the lab, all samples were preserved, at −80 °C, until processing. Several variations of the DNA extraction protocol were tested (schematized in Fig. 2), since there is no consensus protocol in the literature. After a quick removal of calcium carbonate (CaCO3) skeletons with sterile spatulas, about 200 mg of each coral sample was crushed with sterile mortar and pestle, in the presence of liquid nitrogen. The resulting slurry received one of four lysis buffers: (i) 1 ml Lysis G buffer [4 M guanidine hydrochloride (Sigma-Aldrich), 200 mM Tris–HCl (pH8.0), 50 mM EDTA, and 0.5 % (m/v) sodium N-lauryl sarcosine (Sigma-Aldrich)]; (ii) 1 ml cetyl trimethylammonium bromide (CTAB) buffer [2 % (m/v) CTAB (Sigma-Aldrich), 1.4 M NaCl, 20 mM EDTA, 100 mM Tris–HCl (pH 8,0), and freshly added 5 μg proteinase K and 0.5 (or 1)% (v/v; Invitrogen) 2-mercaptoethanol (Sig- ma-Aldrich)]; (iii) Gianni’s buffer, 250 μl ice-cold stabilizing solution [20 % (m/v) sucrose, 50 mM Tris–HCl (pH8,0), 50 mM EDTA] plus 500 μl ice-cold lysis solution [50 mM NaCl, 1 % (m/v) sodium N-lauryl sarcosine (Sigma-Aldrich), and freshly added 25 μg proteinase K]; and (iiii) 1 ml Trizol solution (Invitrogen). Alternative solutions containing in- creased concentrations of EDTA (50, 75, or 100 mM) were also tested. We compared the usefulness of each of these four buffers. Two lysis conditions were tested with buffers (i), (ii), and (iii). Tubes were alternatively frozen (−80 °C) and heated (water bath 65 °C) in water bath heating (56 °C/1–2 h) and freeze–thawing cycles. Three freeze–thaw cycles were per- formed, in about 3 min per step, with mixing by inversion in between. For deproteinization, phenol–chloroform–isoamilic alcohol (25:24:1) and chloroform–isoamilic alcohol (24:1) washes were performed (one each) in all cases [28]. DNA purification was obtained by two protocols: (a) isopropanol precipitation, with 3 M ammonium acetate, at −20 °C imme- diately/for 1 h/for 4 h/overnight, followed by washing/desali- nization with 70 % ethanol, air drying, and resuspension in Tris–EDTA solution (10:1) and (b) addition of solution C4 and loading in the purification column of the PowerSoil® DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA). Washings with solution C5 and elution with solution C6 followed manufacturer’s instructions. The PowerSoil® DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA) was also fully employed, following manufacturer’s instructions. The alternative lysis methods suggested in the manual were tested. The quality and size of the extracted DNAs were evaluated by electrophoresis on 1 % agarose gels stained with GelRed (Uniscience). Further confirmation of the purity of the extraction and quantification was made on a K and 0.5 (or 1)% (v/v; Invitrogen) 2-mercaptoethanol (Sig- ma-Aldrich)]; (iii) Gianni’s buffer, 250 μl ice-cold stabilizing solution [20 % (m/v) sucrose, 50 mM Tris–HCl (pH8,0), 50 mM EDTA] plus 500 μl ice-cold lysis solution [50 mM NaCl, 1 % (m/v) sodium N-lauryl sarcosine (Sigma-Aldrich), and freshly added 25 μg proteinase K]; and (iiii) 1 ml Trizol solution (Invitrogen). Alternative solutions containing in- creased concentrations of EDTA (50, 75, or 100 mM) were also tested. We compared the usefulness of each of these four buffers. Two lysis conditions were tested with buffers (i), (ii), and (iii). Tubes were alternatively frozen (−80 °C) and heated (water bath 65 °C) in water bath heating (56 °C/1–2 h) and freeze–thawing cycles. Three freeze–thaw cycles were per- formed, in about 3 min per step, with mixing by inversion in between. For deproteinization, phenol–chloroform–isoamilic alcohol (25:24:1) and chloroform–isoamilic alcohol (24:1) washes were performed (one each) in all cases [28]. DNA purification was obtained by two protocols: (a) isopropanol precipitation, with 3 M ammonium acetate, at −20 °C imme- diately/for 1 h/for 4 h/overnight, followed by washing/desali- nization with 70 % ethanol, air drying, and resuspension in Tris–EDTA solution (10:1) and (b) addition of solution C4 and loading in the purification column of the PowerSoil® DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA). Washings with solution C5 and elution with solution C6 followed manufacturer’s instructions. The PowerSoil® DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA) was also fully employed, following manufacturer’s instructions. The alternative lysis methods suggested in the manual were tested. The quality and size of the extracted DNAs were evaluated by electrophoresis on 1 % agarose gels stained with GelRed (Uniscience). Further confirmation of the purity of the extraction and quantification was made on a NanoDrop spectrophotometer (Thermo Fisher Scientific Inc.). PCR amplification of 16S rRNA gene (with bacteria- specific primer 27F and the universal primer 1492R) was performed on holobiont DNA samples, according to [29], in order to assess the quality of the samples for further molecular biology manipulations. Metagenome sequencing of the 12 samples was performed using 454 pyrosequencing technology [30]. Shotgun libraries were individually generated with 0.5 μg of whole DNA and sheared into fragments by nebulization. End-repair and adap- tor ligation were performed with the use of GS FLX Titanium kit (Roche), following manufacturer’s specifications. Quality control and quantification were done with the use of Agilent 2100 Bioanalyzer (Agilent Technologies) and TBS 380 Fluo- rometer (Turner Biosystems), respectively. After library con- struction, 106 molecules of each sample were denatured and amplified by emulsion PCR. Sequencing was done using the GS Junior System (Roche). The dinucleotide composition of the Mussismilia metage- nomes was compared to other metagenomes obtained from and freely available in the databases, namely Porites com- pressa corals (field and lab samples), Acropora millepora corals (healthy and bleached), seawater from the Abrolhos Bank, and soil from Black Soudan mine. Frequency tabula- tion of the sequence data was performed according to [31], using homemade Perl scripts, and the principal compo- nent analysis (PCA) analysis (using covariance) of the tabulated data was performed in the STATISTICA software (StatSoft®). The taxonomic composition of the coral metagenomes was first evaluated through local nucleotide blast (blastall 2.2.18) against a Coral database (Table S1). Data were organized using the MEGAN4 software [32]. Sequences with no hits against this database (e-value 10−5) were further annotated on the MG-Rast v3 server [33], under taxonomic classification (GenBank database, e-value cutoff 10−5), and both results were pooled together. The functional analysis was performed directly on MG-Rast (SEED database, e- value cutoff 10−3). Databases were last updated in Septem- ber 2012. Metagenome data are available on the MG-Rast server. The taxonomic annotation was analyzed using the R statis- tical package ShotgunFunctionalizeR [34], to evaluate com- positional differences between healthy and white plague- affected corals. Gene-centric regression analysis was per- formed in the data using the Poisson model. Abundance percentage values were normalized based on the number of identified sequences in each domain within each metagenome. The R statistical package ShotgunFunctionalizeR [34] and the STAMP bioinformatics software [35] were also used for statistical analysis of the functional annotation of MG- RAST [33]. Additionally, the “All annotations” tool of MG- RAST was used to classify Mussismilia sequences (both healthy and WP) and also Porites [27] and Acropora (healthy and bleached) [26] sequences, both available in public databases. Manual curation of this automatic annota- tion was subsequently performed and resulted in a compar- ative table of the functions represented in these corals.
Abrolhos Bank Reef Health Evaluated by Means of Water Quality, Microbial Diversity, Benthic Cover, and Fish Biomass Data
pmeirelles.7.2
The health of the coral reefs of the Abrolhos Bank (southwestern Atlantic) was characterized with a holistic approach using measurements of four ecosystem components: (i) inorganic and organic nutrient concentrations, [1] fish biomass, [1] macroalgal and coral cover and (iv) microbial community composition and abundance. The possible benefits of...The health of the coral reefs of the Abrolhos Bank (southwestern Atlantic) was characterized with a holistic approach using measurements of four ecosystem components: (i) inorganic and organic nutrient concentrations, [1] fish biomass, [1] macroalgal and coral cover and (iv) microbial community composition and abundance. The possible benefits of protection from fishing were particularly evaluated by comparing sites with varying levels of protection. Two reefs within the well-enforced no-take area of the National Marine Park of Abrolhos (Parcel dos Abrolhos and California) were compared with two unprotected coastal reefs (Sebastião Gomes and Pedra de Leste) and one legally protected but poorly enforced coastal reef (the “paper park” of Timbebas Reef). The fish biomass was lower and the fleshy macroalgal cover was higher in the unprotected reefs compared with the protected areas. The unprotected and protected reefs had similar seawater chemistry. Lower vibrio CFU counts were observed in the fully protected area of California Reef. Metagenome analysis showed that the unprotected reefs had a higher abundance of archaeal and viral sequences and more bacterial pathogens, while the protected reefs had a higher abundance of genes related to photosynthesis. Similar to other reef systems in the world, there was evidence that reductions in the biomass of herbivorous fishes and the consequent increase in macroalgal cover in the Abrolhos Bank may be affecting microbial diversity and abundance. Through the integration of different types of ecological data, the present study showed that protection from fishing may lead to greater reef health. The data presented herein suggest that protected coral reefs have higher microbial diversity, with the most degraded reef (Sebastião Gomes) showing a marked reduction in microbial species richness. It is concluded that ecological conditions in unprotected reefs may promote the growth and rapid evolution of opportunistic microbial pathogens.
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageAbrolhos reefs (-19.0°S to -17.0°N, -38.625°W to -36.5°W)
Temporal Coverage2009-01-27 to 2010-01-27
Methods
Water samples were collected by divers within the benthic boundary layer, up to 1 m from the bottom, using two Niskin bottles (10 L each). At least three replicates from Niskin bottles were obtained for each parameter in each of the eight locations....Water samples were collected by divers within the benthic boundary layer, up to 1 m from the bottom, using two Niskin bottles (10 L each). At least three replicates from Niskin bottles were obtained for each parameter in each of the eight locations. Chlorophyll-a, inorganic nutrients, dissolved organic carbon (DOC), Phosphorus and Nitrogen concentrations and microbial abundance was determined. Chlorophyll a samples were collected using positive pressure filtration of 2 L of water. The filters (Millipore HAWP) were extracted overnight in 90% acetone at 4°C and analyzed by spectrophotometry or fluorimetry. For the inorganic nutrients analyses 1 L of water was frozen and was analyzed at laboratory using the following methods: 1) ammonia by indophenol, 2) nitrite by diazotization, 3) nitrate by reduction in Cd - Cu column followed by diazotization, 4) total nitrogen by digestion with potassium persulfate following nitrate determination, 5) orthophosphate by reaction with ascorbic acid, 6) total phosphorous by acid digestion to phosphate, and 7) silicate by reaction with molybdate. Dissolved organic carbon (DOC), Phosphorus and Nitrogen (shown in Table 1 the sum between the organic and inorganic P and N as Total-P and Total-N, respectively). Microbial abundance was determined from three replicates of seawater per site by flow cytometry with Sybr-green (Life Technologies). Collected seawater was filtered through Sterivex (0.22 μm) by positive pressure. In total 4 L of seawater were filtered in each Sterivex filter. Microbes collected in Sterivex filters were preserved with SET buffer (20% sucrose, 50 mM EDTA and 0.5 mM Tris-HCl) in liquid nitrogen until DNA extraction procedures at laboratory. Seawater metagenomic DNA extraction was performed following alkaline lysis as previously described 21. High quality DNA extracted from Sterivex filters was sequenced using GS FLX Titanium kit (Roche) a pyrosequencing technology. Fish and benthic assessments were not performed at California Reef due to logistical limitations. Fish counts (N = 20 per site) were made using a nested stationary visual census technique [33] in the same areas in which the photo-quadrats were taken and at the same depths from which the microbes were collected (see the Study area section). Different size categories of fishes were counted in two different sampling radii, with a size limit for individuals to be included in each count. Each sample began with an identification period of 5 minutes in which all species within a 4 m radius (defined by a tape rule laid immediately before census) were listed. After this period, quantitative data were recorded separately for each species. Individuals,10 cm in total length (TL) were counted in a 2 m radius and recorded in two different size categories:,2 and 2–10 cm. Individuals.10 cm TL were counted in a 4 m radius and recorded in four size categories: 10–20, 20–30, 30–40 and.40 cm. The counts of two species of territorial herbivores (Stegastes fuscus and Stegastes variabilis) were pooled because they are difficult to distinguish underwater. Benthic cover was estimated using photo-quadrats (N = 30 per site) as described previously [11]. A mosaic of 15 high-resolution digital images totaling 0.7 m2 constituted each sample. Quadrats were permanently delimited by fixed metal pins and set at random distances along a 20–50 m axis on the tops of reef pinnacles. Relative coral cover was estimated through the identification of organisms below 300 randomly distributed points per quadrat (i.e., 20 points per photograph) using the Coral Point Count with Excel Extensions software [38]. The counts of benthic organisms were converted to percentages. One-way analysis of variance [34] was used to evaluate differences in benthic cover and fish biomass between the sites. To satisfy the ANOVA assumptions of normality and homoscedasticity, the fish biomass was converted to log (x+1), whereas the benthic cover percentages were converted to arcsin (srt(x)) [35].
Fish biodiversity of the Vitória-Trindade Seamount Chain, Southwestern Atlantic: an updated database
knb.9.2
Primary data was acquired during three scientific diving expeditions to the VTC seamounts and islands, in 2009 (12-26 March) and 2011 (3-26 February and 1-18 April). These expeditions covered the photic and upper mesophotic zones (17â120 m depth) of the two islands and eight seamounts: Almirante Saldanha, Vitória, Eclaireur, Jaseur,...Primary data was acquired during three scientific diving expeditions to the VTC seamounts and islands, in 2009 (12-26 March) and 2011 (3-26 February and 1-18 April). These expeditions covered the photic and upper mesophotic zones (17â120 m depth) of the two islands and eight seamounts: Almirante Saldanha, Vitória, Eclaireur, Jaseur, "Unnamed" (Columbia Bank in [35]), Davis, Dogaressa and Columbia seamounts. Sampling included visual, video and photo records, as well as collection of voucher specimens by divers (hand nets and spear-guns in April 2011) using technical open-circuit SCUBA or closed-circuit rebreathers (Megalodon®) with mixed-gases (TRIMIX and EAN). Primary data from fishery surveys (surface longline, bottom longline, midwater trawling and angling activities; see [31â34,69,105]) were incorporated in the database. Fishery sampling was performed over eight volcanic mounts (Vitória, Eclaireur, Besnard, Montague, Jaseur, Davis, Dogaressa, Columbia and Trindade) by the REVIZEE and to a much lesser extent TAMAR/ICMBio monitoring assessments.
CreatorsHudson Pinheiro
Publication Date2014-10-11
Geographic CoverageAngelo Coast Range Reserve UCNRS (-21.375°S to -17.125°N, -38.875°W to -16.375°W)
Temporal Coverage1994-01-01 to 2011-12-01
Methods
Primary data was acquired during three scientific diving expeditions to the VTC seamounts and islands, in 2009 (12-26 March) and 2011 (3-26 February and 1-18 April). These expeditions covered the photic and upper mesophotic zones (17â120 m depth)...Primary data was acquired during three scientific diving expeditions to the VTC seamounts and islands, in 2009 (12-26 March) and 2011 (3-26 February and 1-18 April). These expeditions covered the photic and upper mesophotic zones (17â120 m depth) of the two islands and eight seamounts: Almirante Saldanha, Vitória, Eclaireur, Jaseur, "Unnamed" (Columbia Bank in [35]), Davis, Dogaressa and Columbia seamounts. Sampling included visual, video and photo records, as well as collection of voucher specimens by divers (hand nets and spear-guns in April 2011) using technical open-circuit SCUBA or closed-circuit rebreathers (Megalodon®) with mixed-gases (TRIMIX and EAN). Primary data from fishery surveys (surface longline, bottom longline, midwater trawling and angling activities; see [31â34,69,105]) were incorporated in the database. Fishery sampling was performed over eight volcanic mounts (Vitória, Eclaireur, Besnard, Montague, Jaseur, Davis, Dogaressa, Columbia and Trindade) by the REVIZEE and to a much lesser extent TAMAR/ICMBio monitoring assessments.
Baseline assessment of mesophotic reefs of West South Atlantic seamounts based on water quality, microbial diversity, benthic cover and fish biomass data
pmeirelles.3.2
Seamounts are considered important sources of biodiversity and minerals. However, their biodiversity and health status are not well understood; therefore, potential conservation problems are unknown. The mesophotic reefs of the Vitória-Trindade Seamount Chain (VTC) were investigated via benthic community and fish surveys, metagenomic and water...Seamounts are considered important sources of biodiversity and minerals. However, their biodiversity and health status are not well understood; therefore, potential conservation problems are unknown. The mesophotic reefs of the Vitória-Trindade Seamount Chain (VTC) were investigated via benthic community and fish surveys, metagenomic and water chemistry analyses, and water microbial abundance estimations. The VTC is a mosaic of reef systems and includes rhodolith beds, crustose coralline algae (CCA) reefs, and rocky reefs of varying health levels. Macro-carnivores and larger fish presented higher biomass at the CCA reefs (4.4 kg per frame) than in the rhodolith beds and rocky reefs (0.0 to 0.1 kg per frame). A larger number of metagenomic sequences identified as primary producers (e.g., Chlorophyta and Streptophyta) were found at the CCA reefs. However, the rocky reefs contained more diseased corals (>90%) than the CCA reefs (~40%) and rhodolith beds (~10%). Metagenomic analyses indicated a heterotrophic and fast-growing microbiome in rocky reef corals that may possibly lead to unhealthy conditions that will require conservation actions.
CreatorsFabiano Thompson (Federal University of Rio de Janeiro)
Geographic CoverageVitória Trindade Chain (-21.375°S to -17.125°N, -38.875°W to -16.375°W)
Water samples were collected by divers within the benthic boundary layer, up to 1 m from the bottom, using two Niskin bottles (10 L each). At least three replicates from Niskin bottles were obtained for each parameter in each of the eight locations....Water samples were collected by divers within the benthic boundary layer, up to 1 m from the bottom, using two Niskin bottles (10 L each). At least three replicates from Niskin bottles were obtained for each parameter in each of the eight locations. Chlorophyll-a, inorganic nutrients, dissolved organic carbon (DOC), Phosphorus and Nitrogen concentrations and microbial abundance was determined. Chlorophyll a samples were collected using positive pressure filtration of 2 L of water. The filters (Millipore HAWP) were extracted overnight in 90% acetone at 4°C and analyzed by spectrophotometry or fluorimetry. For the inorganic nutrients analyses 1 L of water was frozen and was analyzed at laboratory using the following methods: 1) ammonia by indophenol, 2) nitrite by diazotization, 3) nitrate by reduction in Cd - Cu column followed by diazotization, 4) total nitrogen by digestion with potassium persulfate following nitrate determination, 5) orthophosphate by reaction with ascorbic acid, 6) total phosphorous by acid digestion to phosphate, and 7) silicate by reaction with molybdate. Dissolved organic carbon (DOC), Phosphorus and Nitrogen (shown in Table 1 the sum between the organic and inorganic P and N as Total-P and Total-N, respectively). Microbial abundance was determined from three replicates of seawater per site by flow cytometry with Sybr-green (Life Technologies). Collected seawater was filtered through Sterivex (0.22 μm) by positive pressure. In total 4 L of seawater were filtered in each Sterivex filter. Microbes collected in Sterivex filters were preserved with SET buffer (20% sucrose, 50 mM EDTA and 0.5 mM Tris-HCl) in liquid nitrogen until DNA extraction procedures at laboratory. Seawater metagenomic DNA extraction was performed following alkaline lysis as previously described 21. Collected corals were also stored in liquid nitrogen until DNA extraction procedures. A protocol using CTAB buffer with 100 mM EDTA and the PowerSoil® purification column was used in order to gather high molecular weight of DNA from small fragment of each coral sample (approx. 1 cm2). High quality DNA extracted from Sterivex filters and from corals was sequenced using GS FLX Titanium kit (Roche) a pyrosequencing technology. In order to recognize the main topographic features of seamounts’ tops, we used a sidescan sonar (EdgeTech 4100, 100–500kHz) across a linear extent of 110 km with 400 m swaths, covering the Trindade Island shelf and upper slope, as well as in the summits of seamounts Jaseur and Davis. Sonograms were processed with SonarWiz Map4 (V.4.02). Benthic cover was estimated following procedures. Briefly, at each site ten 0.7 m2 photoquadrats were randomly placed. Percent cover was estimated using Coral Point Count with Excel Extension software (CPCe), using 15 randomly distributed points per photograph (225 points per quadrat). Organisms below each point were identified considering the following major benthic categories: turf algae (subdivided into: Jania plus Amphiroa plus other small filamentous algae, and the cyanobacteria Lyngbya sp.), sand, sponge, flashy algae 49, coral (mainly Siderastrea sp., Montastrea cavernosa and the Brazilian endemic Mussismilia hispida. Coral colonies health status were qualified as healthy, presence of tissue necrosis or bleaching) and Crustose coralline algae (CCA) (subdivided into Peyssonelia sp. and others, the latter including mainly Hydrolithon onkodes, Lithophyllum prototypum, Phymatolithon masonianum, Spongites sp.). Reference samples of algae are deposited in the collection of the Rio de Janeiro Botanical Garden Herbarium (RB). Fish assemblages were assessed from video records using a remote operated vehicle (ROV) Seabotix® LBV 150S2 equipped with lights and a color video camera and a pair of scaling lasers 5 cm apart (used to estimate fish sizes), and video cameras handled by divers using standard SCUBA (<40 m deep) and mixed-gas techniques (TRIMIX) in open systems (>40 m deep). Fish samples were obtained in the same sites in which water samples were obtained, ranging 25 and 63 m deep. Both ROV and divers records were made in slow movement (not static), close the bottom (about 1 m), and focusing in all available habitats (rhodoliths, interface, reefs, water column) aiming to record the entire reef fish community. Fish counts were performed from frames taken every 10 seconds of video footage. A total of 546 frames from ROV and divers records were used (180 in Trindade Island, 275 in Davis seamount and 91 in Jaseur seamount). Size of fish (total length, TL) was visually estimated using the laser scale and individuals were classified into 10 cm size classes. Fish biomass was estimated using length-weight relationships 50. When no relationship was available for a species, an equation from similarly sized congeners was applied. Fish species were assigned to one of the following trophic guilds based on adult diet literature data 51: herbivores, invertivores, macro carnivores and omnivores. Fish results are presented as relative abundance [number of fishes from a category (size or trophic guild)/total number of fishes from the site] and biomass (Kg/frame).
