Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Related Publications
• Parameters
• Instruments
• Project Information
• Funding

Incurrent/excurrent water samples were taken from three sponge species from the Florida Keys (USA) over two or three days using a modified version of the vacuSIP (Morganti et al. 2016). Briefly, acid-cleaned and combusted bottles were negatively pressurized and sealed. PEEK tubing lines were connected to the pressurized bottles via a needle, and this pulled seawater from the opening of the sponge ("excurrent") or nearby seawater ("incurrent") at a slow and steady rate to fill the bottles. Nutrient data from the seawater samples were compiled and organized by sponge species and water type (incurrent or excurrent) in an Excel file. Seawater samples from two sponge species (Niphates digitalis and Verongula rigida) were filtered through 0.2-micrometer (µm) polyethersulfone filters, while seawater from the sponge Xestspongia muta was filtered through 0.2 µm Teflon Omnipore filters. Filtrate was then saved for inorganic nutrients and those from X. muta were processed for dissolved organic matter composition using targeted metabolomics analysis. Flow cytometry of phytoplankton and bacteria data was collected from pre-filtered seawater and preserved in 0.5% paraformaldehyde final concentration. Seawater for total organic carbon (TOC) and total nitrogen (TN) was also collected prior to filtration and was acidified to ~pH 2 using concentrated HCl. Metabolomics and TOC analysis were performed at Woods Hole Oceanographic Institution at the Mass Spectrometry Facility.

Dissolved Organic Matter Extraction:
Filtered seawater was processed using PPL solid phase extraction following the protocol by Dittmar et al. (2008). Extracts were dried to nearly completeness, leaving a small viscous drop in the vial. These extracts were then shipped to WHOI for metabolomics analysis.

Targeted Metabolite Analysis by UPLC-MS:
DOM extracts were reconstituted in 200 microliters (μl) MilliQ water with 50 nanograms per milliliter (ng/ml) isotopically-labeled injection standards d2 biotin, d6 succinic acid, d4 cholic acid, and d7 indole 3 acetic acid. We used ultra-performance liquid chromatography (Accela Open Autosampler and Accela 1250 Pump, Thermo Scientific) coupled to a heated electrospray ionization source (H-ESI) and a triple quadrupole mass spectrometer (TSQ Vantage, Thermo Scientific) operated under selected reaction monitoring (SRM) mode. We performed chromatographic separation with a Waters Acquity HSS T3 column (2.1 × 100 millimeters (mm), 1.8 μm) equipped with a Vanguard pre-column and maintained at 40 degrees Celsius (°C). We eluted the metabolites from the column with (A) 0.1% formic acid in water and (B) 0.1% formic acid in acetonitrile at a flow rate of 0.5 milliliters per minute (mL min-1), according to the gradient: 0 min, 1% B; 1 min, 1%B; 3 min, 15%B; 6 min, 50%B; 9 min, 95%B; 10 min, 95%B; 10.2 min, 1%B; 12 min, 1%B (total run time = 12 min). Settings for source gases were 55 (sheath), 20 (auxiliary) and 0 (sweep), and these settings are presented in arbitrary units. The heated capillary temperature was 375 °C and the vaporizer temperature was 400 °C. For positive and negative modes, we performed separate autosampler injections of 5 μL each.

Flow Cytometry:
Samples were preserved and stored at -80°C until later batch analysis at the University of Hawaii SOEST Flow Cytometry Facility (www.soest.hawaii.edu/sfcf). Microbial cells were enumerated using flow cytometry (Selph, 2021). In brief, samples (0.1 mL) were thawed in batches, stained with the DNA dye Hoechst 34580 (1 microgram per milliliter (µg/mL) final), then run at 30 microliters per minute (µL min-1) on a Beckman-Coulter CytoFlex S flow cytometer, using lasers emitting at 375 nanometers (nm) (to detect Hoechst), 488 nm (for scatter and chlorophyll parameters), and 561 nm (for phycoerythrin). Resulting listmode files (FCS 3.0) were analyzed using FlowJo software (Becton Dickinson, v. 10.8.2) to distinguish microbial populations based on their fluorescence signals (chlorophyll, phycoerythrin, DNA), as well as forward and right-angle light scatter. Heterotrophic bacteria were distinguished from phytoplankton by their DNA signature and absence of pigment. Prochlorococcus and Synechococcus were separated from larger eukaryotic phytoplankton by their light scatter signatures, as well as their characteristic pigment and DNA signatures. Other phytoplankton (eukaryotes, mostly 2-20 µm pico- and nano-sized cells given the small volume analyzed) had higher light scatter and more chlorophyll fluorescence per cell.

Inorganic nutrients:
Inorganic nutrients included phosphate, nitrate+nitrite, nitrite, ammonia, and silicic acid. The phosphate method is a modification of the molybdenum blue procedure of Bernhardt and Wilhelms (1967), in which phosphate is determined as reduced phosphomolybdic acid employing hydrazine as the reductant. The nitrate + nitrite analysis uses the basic method of Armstrong et al. (1967), with modifications to improve the precision and ease of operation. Sulfanilamide and N-(1-Napthyl)ethylenediamine dihydrochloride react with nitrite to form a colored diazo compound. For the nitrate + nitrite analysis, nitrate is first reduced to nitrite using an OTCR and imidazole buffer as described by Patton (1983). Nitrite analysis is performed on a separate channel, omitting the cadmium reductor and the buffer. The method is based on that of Armstrong et al. (1967) as adapted by Atlas et al. (1971). The addition of an acidic molybdate reagent forms silicomolybdic acid, which is then reduced by stannous chloride. This indophenol blue method is modified from ALPKEM RFA methodology which references Methods for Chemical Analysis of Water and Wastes, March 1984, EPA-600/4-79-020, "Nitrogen Ammonia", Method 350.1 (Colorimetric, Automated Phenate) A detailed description of the continuous segmented flow procedures used can be found in Gordon et. al. (1994).

Targeted Metabolomics:
Samples were analyzed in random order and injected pooled samples at regular intervals (every 8 samples). We monitored two SRM transitions per compound for quantification and confirmation; these transitions were optimized previously using authentic standards. We generated 8-point external calibration curves based on peak area for each compound. We converted raw data files from proprietary Thermo (.RAW) format to mzML using the msConvert tool (Chambers et al., 2012) prior to processing with El-MAVEN (Agrawal et al., 2019). Metabolite concentrations were provided from WHOI as raw data in nanograms per milliliter (ng/ml) in the 200 microliters (μl) extract. We then converted the ng/ml values into total nanograms by multiplying by 0.2 then divided by the sample volume in liters to produce nanograms per liter (ng/L) concentrations. These concentrations were converted to micromolar concentrations using the formula weight for each metabolite.

Statistical Analysis:
Concentrations of dissolved nutrients (micromolar (μM)) and cells (cells per milliliter) were compared by analysis of variance (ANOVA) or Kruskal-Wallis, depending on if the dataset met assumption of ANOVA, followed by pairwise comparisons (either Tukey HSD or Dunn test). Permutational analysis of variance (PERMANOVA) was also used to assess an effect of sample, sponge species, or day on a matrix of all nutrients following conversion of the data to z-score.

- Imported original file "VacuSIP_3day_Jan22_For_BCO-DMO.xlsx" into the BCO-DMO system.
- Flagged "NA" as a missing data value (missing data are empty/blank in the final CSV file).
- Converted Date field to YYYY-MM-DD format.
- Renamed fields to comply with BCO-DMO naming conventions.
- Saved the final file as "965557_v1_sponge_3day_vacusip_jan2022.csv".

NSF Award Abstract:
The seawater around coral reefs is typically low in nutrients, yet coral reefs are teeming with life and are often compared to oases in a desert. Life exists in these 'marine deserts' in large part, due to symbiotic associations between single-celled microbes and invertebrates such as corals and sponges. The concentration and type of dissolved organic matter (DOM), a complex pool of organic nutrients such as amino acids, vitamins, and other diverse compounds, also affects the health of coral reefs. The composition of DOM on coral reefs is linked to both the composition of free-living microbes in the seawater and to the nutrition of filter-feeding organisms, such as corals and sponges. However, the factors that influence the composition of DOM on coral reefs and the consequences of how it changes are not well understood. Recent work suggests that sponges could have a significant impact on the composition of reef dissolved organic nutrients, depending on sponge species due to differences in filtration capacity and in their symbiotic microbial communities. This project characterizes how diverse sponge species process DOM on coral reefs and determines the impacts of this processing on the free-living microbial community. Seawater is collected from sponges (pre- and post- sponge filtration) on coral reefs in the relatively pristine region of Curacao, and incubation experiments measure the impact of sponge filtration on the growth of the free-living microbial community. The organic nutrients of seawater samples are analyzed using cutting-edge techniques to distinguish the types of nutrients that are processed by sponges. The incubation experiments, using free-living microbes collected from the coral reef, quantify the impact of sponge filtration on the growth and composition of this community. This project provides fundamental understanding of how sponges contribute to the base of the coral reef food web. As the human-driven impacts continue to alter the composition of organisms on reefs, this understanding is necessary to predict changes to reef microbial food webs and is thus essential for scientists, reef managers, and policy decision makers. This project trains undergraduate students and a postdoctoral scholar and contributes to undergraduate and K-12 education through development of sponge-centric lessons that focus on local U.S. east coast aquatic environments as well as coral reef ecosystems.

Sponges vary in their capacity to filter seawater and in their associated microbial communities, leading to diverse metabolic strategies that often coexist in one habitat. While it is well-established that sponges are important in processing dissolved organic matter (DOM), an important reservoir of reduced carbon compounds, and transferring this energy to benthic food webs, there has been limited work to understand the consequences of sponge processing on the composition of coral reef DOM and on pelagic food webs. Specifically, while studies have shown that exudates of corals and algae select for specific groups of picoplankton (autotrophic and heterotrophic, respectively), similar data for sponges are required to understand the multiple factors that shape the composition of DOM and of the picoplankton community on coral reefs. Thus, this project is aimed at addressing a major knowledge gap of the role of sponge-derived DOM (sponge exometabolome) in coral reef biogeochemistry. An in situ sampling design targeting prominent Caribbean sponges and picoplankton incubation experiments is coupled to address both the composition of sponge exometabolomes and delineate shifts in the picoplankton community derived from sponge exometabolomes. Molecular-level changes to seawater DOM by sponge processing and the impact of these changes on the overall coral reef DOM profile is assessed with two DOM analysis techniques: a commonly used fluorometry technique (fDOM analysis) and with high-resolution mass spectrometry (LC-MS/MS). Additionally, microbiome and functional gene profiling, growth metrics, and nutrient analyses are employed to assess changes in the picoplankton community in response to sponge exometabolomes. Advanced data analysis techniques then synthesize data generated by each approach to provide novel insight on a poorly uncharacterized biogeochemical pathway on coral reefs. The work outlined here represents entirely novel information on the impact of sponge metabolism on the composition of DOM, sheds light on biologically important molecules involved in benthic-pelagic coupling, and importantly, generates data using standardized methods, thus facilitating comparison to previous and future DOM datasets.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.