These data are bacterial 16S rRNA sequences and a taxonomic summary table for biofilm samples from the bio-reactors. The data may provide background/supporting information for other researchers who have a similar experimental plan with a microbial electrochemical cell reactor. This dataset is associated with the following publication: Santodomingo, J., H. Lee, B. Dhar, J. An, B. Rittmann, H. Ren, and J. Chae. The Roles of Biofilm Conductivity and Donor Substrate Kinetics in a Mixed-Culture Biofilm Anod. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(23): 12799-12807, (2016).

These data are bacterial 16S rRNA sequences and a taxonomic summary table for biofilm samples from the bio-reactors. The data may provide background/supporting information for other researchers who have a similar experimental plan with a microbial electrochemical cell reactor. This dataset is associated with the following publication: Santodomingo, J., H. Lee, B. Dhar, J. An, B. Rittmann, H. Ren, and J. Chae. The Roles of Biofilm Conductivity and Donor Substrate Kinetics in a Mixed-Culture Biofilm Anod. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(23): 12799-12807, (2016).

These data include raw sequencing data (bacterial 16S and eukaryote 18S rRNA genes) and a summary result table for bacteria classification in an Excel file. This dataset is associated with the following publication: Hwang, J., H. Ryu, K. Rodriguez, S. Fahad, J. SantoDomingo, A. Kushima, and W. Lee. A strategy for power generation from bilgewater using a photosynthetic microalgal fuel cell (MAFC). JOURNAL OF POWER SOURCES. Elsevier Science Ltd, New York, NY, USA, 484: 229222, (2021).

These data include raw sequencing data (bacterial 16S and eukaryote 18S rRNA genes) and a summary result table for bacteria classification in an Excel file. This dataset is associated with the following publication: Hwang, J., H. Ryu, K. Rodriguez, S. Fahad, J. SantoDomingo, A. Kushima, and W. Lee. A strategy for power generation from bilgewater using a photosynthetic microalgal fuel cell (MAFC). JOURNAL OF POWER SOURCES. Elsevier Science Ltd, New York, NY, USA, 484: 229222, (2021).

Transcriptomic analysis of sponges that have been exposed to different environmental conditions can improve our understanding of molecular stress response pathways and enhance our ability to effectively manage these ecologically important filter feeders. Two common and widely distributed Indo-Pacific sponge species—Carteriospongia foliascens and Cliona orientalis were collected in May 2015 from Fantome Island and Pelorus Island in the Great Barrier Reef. Since C. orientalis is a bio-eroding sponge, ten C. orientalis drill cores (* 5cmin diameter) were collected from a single individual growing on a dead colony of Porites sp. An individual of C.foliascens was cut into ten pieces (see Pineda et al. 2016). Sponges were healed and acclimated under natural light and flowthrough seawater for 4 weeks before experiments were performed. Sponges were subjected to five different treatments at the Australian Institute of Marine Science (AIMS) National Sea Simulator: (i) decreased salinity, (ii) elevated temperature, (iii) elevated suspended sediment concentrations(SSCs) and sediment deposition, (iv) light attenuation, and(v) no stress control. Further details on these experiments can be found in Pineda et al. (2016). Transcriptome sequences were assembled for C. foliascens and C. ori-entalis and from the C. orientalis holobiont, i.e., host and symbiont, a partial reference transcriptome for Gerakladium endoclionum was constructed. Further details are found in the linked paper below Strehlow et al. (2021).

Data used to generate Figures 2, 3, and 4 as we ll as Table 3. This dataset is associated with the following publication: Banerji, A., M. Bagley, J. Shoemaker, D. Tettenhorst, C. Nietch, J. Allen, and J. Santodomingo. Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data. Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 86: 84-95, (2019).

Data used to generate Figures 2, 3, and 4 as we ll as Table 3. This dataset is associated with the following publication: Banerji, A., M. Bagley, J. Shoemaker, D. Tettenhorst, C. Nietch, J. Allen, and J. Santodomingo. Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data. Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 86: 84-95, (2019).

Algae and cyanobacteria form symbioses with many marine sponges, converting energy from the sun to donate to their host, and promoting sponge survival, growth and reproduction. These little-studied symbioses are similar to those between algae and coral, and make a significant contribution to the health of reefs in both tropical and temperate regions. This project will investigate the importance of photosynthetic symbionts in sponges in temperate and tropical regions, their host specificity and diversity. It will map photosynthetic symbiont biogeography and environmental preferences, contributing to an understanding of processes affecting the ecology of coastal reefs.

Bacterial communities in eight 16S rDNA clone libraries from calcareous sediments were investigated to assess bacterial diversity in sediments of the Great Barrier Reef and to investigate differences due to decreased water quality. Samples were taken from 2 locations (fore and back reefs) on each of 4 coral reefs: nearshore (Fitzroy and High Islands, subject to enhanced runoff) on the outer shelf (Hastings and Flynn Reefs, pristine conditions).Out of 221 non-chimeric sequences, 189 (85.5%) were unique and only one sequence occurred in more than one library. Cluster analyses and comparison to published sequences indicated that sequences retrieved belonged to the alpha, gamma and delta subdivisions of the Proteobacteria; Cytophaga, Flavobacteria, Bacteroidetes (CFB) group; Cyanobacteria; Planctomycetaceae; Verrucomicrobiaceae; and Acidobacteriaceae.Carbon (organic carbon, total carbon) and nitrogen in the sediments were analysed from two additional samples from each location. Calcium carbonate (%), exposure (front=more exposed to wave action; backreef=less exposure) and mean grain size (mm) were also recorded.Neighbour-joining trees were constructed representing sequences from the 8 clone libraries.All data sequence data are deposited on Genbank (DQ256505 to DQ256725). To contribute to the knowledge on microbial communities of the Great Barrier Reef.To provide a first sequence-based description of bacterial communities on calcareous reef sediments of the GBR.To test if these communities harbour characteristic species or groups which could be used as indicators for land runoff or decreased reef health. Closest matches to the Great Barrier Reef samples, GenBank accession numbers in brackets: arctic sea ice bacterium (AF468407); bacterium (AY258094); Balneatrix alpaca (BAY17112); Beggiatoa sp. (AF110276); benzene mineralizing bacterium (AF029047); cf Cytophaga (AF530130, AF530158); Cryomorphaceae bacterium (AB125062); Cytophaga fermentans (AB125062); Cytophaga sp. (AB015543, AB015545, AB073572); Defluvicoccus vanus (AF179678); Desulfobacterium cetonicum (AJ237603); Desulfobacterium corrodens (AY274450); Desulfovibrio vulgaris (M34399); endosymbiont (AF104473); Flexibacter canadensis (AB078046); Flexibacter roseolus (AB078061); Flexibacter sp. (AB058906); Geothrix fermentans (GF41563); gill symbiont (AB189713); Haslea wawrikae (AF514855); Lewinella persicus (AF039295); Lyngbya sp. (AY049751); marine bacterium (AF076897, AF406617, AY007676); marine gamma-proteobacterium (AY386339); marine snow bacterium (AF030776, AF030779); Nitrosococcus oceani (NOC29872); Orientia tsutsugamushi (D38625); Oscillatoria rosea (AB003164); Pseudomonas sp. (AB013829); Pseudospirillum japonicum (AB006766); Reichenbachia agariperforans (AB058919); Rhodopseudomonas julia (AY428572); Robiginitalea biformata (AY424900); Roseobacter sp. (AF098494); Saprospira grandis (AB088636); sponge symbiont (AF186415); sulfur-oxidising endosymbiont (AF165908, AF328856); sulfur-oxidising gill symbiont (X84984); sulfur-reducing endosymbiont (AF328857); symbiont (U78037); Teredinibacter turnerae (AY028398); Thalasomonas ganghwensis (AY194066); Trichodesmium thiebautii (AF091321); uncultured Acidobacteriaceae (AY225643) ; uncultured actinobacterium (AB116464); uncultured alpha-bacterium (AB015523, AB015526, AF406524, AF445669, AY225603); uncultured bacterium (AF143824, AF317768, AF328183, AF382112, AF382114, AF382143, AY133451, AY171303, AY171323, AY171332, AY171337, AY171357, AY171365, AY172271, AY193132, AY212707, AY216454, AY327875, AY344367, AY373412, AY375053, AY375097, AY500093, UBA56759); uncultured Bacteroidetes (AB116465, AF507866, AY225659, AY274839, UCY44123); uncultured delta-proteobacterium (AB015243, AB116394, AF424201, AF424227, AF424261, AJ58135, AY217484, AY225608, AY499998); uncultured Ectothiorhodospiraceae (AJ567603); uncultured gamma-proteobacterium (AB015252, AB015583, AB116435, AB116469, AF223300, AF351226, AY145601, AY225630, AY225635, U70702);

The files included in this data release are the raw and processed deoxyribonucleic acid (DNA) sequence files referenced in the journal article by Lawler and others (2016) entitled “Coral-Associated Bacterial Diversity is Conserved Across Two Deep-Sea Anthothela Species”. They represent a 16S rRNA gene amplicon survey of cold-water corals (Anthothela spp.) microbiomes completed using Roche 454 pyrosequencing with titanium reagents. The samples used in this study were collected from cold-water corals between 2012-2013, at Baltimore and Norfolk Canyons in the Atlantic Ocean. The raw data files associated with this study were also submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA), under Bioproject number PRJNA296835.