Table of Contents

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

Sampling summary: Discrete samples were all obtained from ~0.2m using a diaphragm pump and weighted, marked hose. All containers were kept in dark coolers at ambient temperature during transport to the laboratory.  All filtration was done within a few hours of collection and when conditions permitted, on board the research vessel.

Diagnostic phytoplankton photopigments were identified, separated and quantified by high performance liquid chromatography (HLPC) coupled to an in-line photodiode array spectrophotometer (Jeffrey et al.  1997):  Known volumes of water sample (500-1000 milliliters, enough to obtain color on the filter) were vacuum filtered (less than 25 kiloPascals) through 25 or 47 millimeter Whatman glass microfibre filters (GF/F) under reduced light conditions.  The filters were blotted dry, folded in half, wrapped in foil and then immediately frozen at -20 degrees Celsius until analysis.  The filters were placed in 15 milliliter centrifuge tubes containing 1.5-3.0 milliliters of 100% acetone (HPLC Grade), sonicated for 30-60 seconds using a Fisher Sonic Dismembrator 300 with microtip and extracted at -20 degrees Celsius for 12-24 hours.  After extraction the samples were centrifuged at 4500 rpm and the supernatant (i.e.- the combined extracted pigments) collected & filtered into amber glass autosampler vials using Millipex Millipore 0.45 micometer PTFE.  Two hundred microliters of extractant from each vial was injected into the HPLC system using a Spectra Physics (now Thermo Separations Products) AS3000 autosampler and SP8800 pump, running a non-linear, 55 minute, 2-solvent gradient adapted from Van Heukelem et.al. 1994 or 1995?.  The nonlinear, variable flow, binary gradient consisted of solvent A [80% methanol : 20% ammonium acetate (0.5 M adjusted to pH 7.2)] and B (80% methanol : 20% acetone).  The extractant was separated into individual pigments using a series of C18 reverse-phase columns to optimize photopigment separations:  The column order was a Rainin Microsorb guard column (0.46 x 1.5 centimeters, 3 micrometer packing) followed by a single monomeric reverse-phase C18 column (Rainin Microsorb-MV, 0.46 x 10 cm, 3 µm packing) followed by two polymeric reverse-phase C18 columns (Vydac 201TP5, 0.46 x 25 cm, 5 µm packing).  The columns were kept at a constant 52 degrees Celsius in an Alltech 330 column heater.  The separated pigments were then passed through an in line Shimadzu SPD-M10AV photodiode array detector which measured the absorbance of the sample/extractant, scanning the range of 350-800 nanometers every 2 seconds.  The data was collected and analyzed using Shimadzu's EZChrom software (Agilent Technologies, Inc (n.d.)).  Individual pigments are identified using a combination of peak retention time and absorbance spectrum shape.  Retention times and absorbance spectra are identified for each pigment by analyzing known pigments (either as pure standards or pigments or isolated from algal cultures).  Pigments are quantified from their peak areas, calculated at 440nm. A calibration curve is generated by injecting various volumes of a mixed standard composed of known quantities of seven pure pigment standards (fucoxanthin, zeaxanthin, bacteriochlorophyll a, canthaxathin, chlorophyll b, chlorophyll a, echinenone and ß-carotene) and calculating the peak areas of those pigments   The peak areas are regressed against the known quantities of each pigment to calculate the slope (Response Factor) for that pigment.  Response factors for pigments we do not have reference standards for are calculated using the ratio of absorbance coefficients of each pigment to its closest structurally related reference pigment, multiplying the known pigment's response factor by that ratio. Pigments extracted from the samples are then quantified by multiplying the peak areas of a chromatogram at 440nm by the response factors. Pigment values listed as below detection were below the software threshold for peak detection or had spectra below a similarity of 0.9 compared to library spectra. Technician expert judgment was used in difficult cases.

See the "Related Datasets" section for in-situ hydrography methods and data collected as part of the same study at the same field sampling locations.

Formatting and organization of data was completed in Excel (Microsoft).

BCO-DMO Data Manager Processing Notes:
* Data from source file BLAMM_METADATA_HPLC_7_3_24_RWP.xlsx Sheet "HPLC ugL" were imported into the BCO-DMO data system with "-7777" (meaning no data) and "-9999" (meaning below detection limit) values in numeric columns imported as blank (null) values.
* Additional *_flag columns added to provide information about what type of missing data each blank value corresponds to. For example Cantha_flag. Indicates if the blank value in the Cantha column is due to below detection limit (BDL) or not analyzed/measured/recorded (NA).

** Missing data in the BCO-DMO system displays as a blank (null values) by default and will vary depending upon the file format downloaded (blank in csv files, NaN in .mat matlab files, etc).

* Parameters (column names) renamed to comply with BCO-DMO naming conventions. See https://www.bco-dmo.org/page/bco-dmo-data-processing-conventions

* Site name (geolocation), lat, lon were added to the data table from an additional sheet provided in related dataset excel file (hydrography) BLAMM_METADATA_7_3_24_RWP.xlsx

* Decimals rounded to 5 decimal places.

* DateTime (UTC) column added in ISO 8601 format yyyy-mm-ddTHH:MM:SSZ using local date and time provided (EST/EDT). Date and time format changed to ISO 8601 format.

NSF Award Abstract:
Planktonic marine bacteria significantly impact global elemental cycling, productivity, and water quality. Recent evidence shows that abundant and diverse marine bacterioplankton require external vitamin B1 or precursors (B1 herein) to survive, and addition of these nutrients stimulates bacterial production. This suggests that it is favorable for most marine bacteria to rely on supplied B1, making B1 dynamics an environmentally relevant test case to study nutrient exchanges within the planktonic microbiome. Notably though, links between extracellular B1 availability and the composition, function, and fitness of marine bacteria are poorly understood. This project sheds light on 1) which activities and interactions are modulated by B1 availability, and 2) the benefits of exogenous B1 use by ubiquitous marine bacterioplankton. Experiments are being conducted to address uncertainty regarding B1 limitation of natural bacterioplankton, help predict plankton responses to natural or anthropogenic increases in B1 and reveal more on the rules governing nutrient exchange between plankton. Greater knowledge of the advantages of bacterial B1 use will benefit fields beyond oceanography, such as synthetic biology which focuses on streamlined microbial product generation. B1-deficiency in animals is a current concern in marine ecosystems.  Greater knowledge of costs and quotas at the microbial level will best position the larger community to ask deficiency questions at other trophic levels.  The teaching and training components of this project include support for graduate students and a post-doctoral scholar. The major outreach component is a newly conceived Mobile Aquatic Microbial Laboratory (MAML) that seeks to improve public awareness of aquatic microbes and their ecosystem impact, as well as convey concepts of nutrient limitation and why cells need vitamins. Pre- and post-assessment and social distancing measures are integrated into MAML, as are incentives for participants to share via social media images and contribute to the program.

This project investigates the impact of vitamin B1 and B1 congeners on bacterioplankton in marine ecosystems where vitamins have garnered little recent consideration as influential nutrients.  The work is conducted in the Neuse River estuary, the second largest estuary in the lower USA, and in the offshore coastal ocean.  Nutrient amendment experiments are being conducted to test whether B1/congeners modulate bacterioplankton growth, composition, and gene transcription (reflecting putative function).  Complementary lab-based experiments with wildtype and genetically engineered bacterioplankton are being conducted to test whether use of exogenous B1/congener significantly improves cell fitness and to address why reliance upon exogenous B1/congener is so prevalent among wild bacterioplankton.  Additional lab experiments with isolates are being conducted to examine the protein-related cost of B1 de novo biosynthesis versus exogenous B1/congener use as well as cell quotas of B1 and precursors using mass spectrometry techniques.  The work reaches beyond recent genome-based extrapolations to address how exogenous B1/congener availability shapes bacterioplankton metabolism, community structure, microbial interactions, and fitness.