Table of Contents

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

All the raw spectra, NMRPipe scripts for spectrum processing, and MATLAB scripts for data analysis are deposited in Metabolomics Workbench under Project ID PR001837 (see related datasets).

Temperature experiment: Axenic cultures of the diatom Thalassiosira pseudonana CCMP1335 (National Center for Marine Algae) were acclimated to three temperature conditions (below optimal: 14°C, optimal: 20°C, and above optimal: 28°C) for three months with weekly transfers (approximately 120 generations) in L1 medium with 35 ppt artificial seawater under 120 µmol photons m-2 s-1 (ULM-500 Light Meter, Walz) and a 16:8 h light:dark cycle. Diatom cultures were stepwise limited by B12 through three transfers. Ruegeria pomeroyi DSS-3  was grown overnight in ½ YTSS medium, harvested in exponential growth phase, washed five times in sterile artificial seawater at 6,000 RCF, and  inoculated into diatom flasks with 4 replicates per acclimation temperature. Flasks were harvested at late exponential growth phase on days 3 (28°C), 4 (20°C), and 6 (14°C), with sampling occurring 7 h into the light cycle.

From axenic and inoculated flasks, cultures were sequentially filtered through 2.0 µm-pore-size Isopore filters (Millipore, Burlington, MA) and 0.2 µm-pore-size Supor filters (PALL, Port Washington, NY) to collect 600 ml for diatom endometabolits analysis,  bacterial cells for RNA extraction. RNA filters were immediately flash-frozen in liquid nitrogen and stored at -80°C until processing.  RNA was subsequently extracted from filters using the ZymoBIOMICS RNA Miniprep Kit (Zymo Research, Irvine, CA, USA) according to the manufacturer’s protocol.

Stranded RNASeq libraries were prepared by the Joint Genome Institute (JGI) and sequenced on an Illumina NovaSeq.

Metabolites were analyzed by NMR spectroscopy using a 600 MHz AVANCE III HD instrument (Bruker) equipped with a 5 mm TCI cryoprobe and pulse programs of 1H-13C heteronuclear single quantum correlation (HSQC, hsqcetgpprsisp2.2 by Bruker nomenclature) and 1H-13C HSQC-total correlation spectroscopy (HSQC-TOCSY, hsqcdietgpsisp.2). TopSpin (Bruker) version 3.5 was used for NMR operation. Data were processed by NMRPipe.

Peak intensity was extracted by rNMR version 1.11 and data were analyzed by MATLAB (MathWorks) version R2023b. Peak intensity was normalized by biovolume and auto-scaled. Metabolites were annotated based on chemical shift (HSQC) and correlation information (HSQC-TOCSY). Chemical shift values for candidate peaks were obtained from the Biological Magnetic Resonance Data Bank and the Human Metabolome Database, and raw reference spectra from BMRB were used for validation.

Draw down experiment: Thalassiosira pseudonana CCMP1335 cells harvested from axenic flasks were rinsed from thawed filters into 10 ml sterile L1 medium, sonicated to lyse cells, and passed through a pre-combusted GF/F filter. Ruegeria pomeroyi DSS-3 was inoculated into a 2.7 ml aliquot of concentrated endometabolomes and grown for 10 h in 96-well plates with shaking at 30°C in dark conditions. Subsamples of 1 ml were collected at inoculation and at the end of the experiment for metabolite quantification. From these subsamples, 540 µl were mixed with 60 µL of the phosphate buffer and transferred to NMR tubes. Metabolites were analyzed by NMR spectroscopy using a 600 MHz AVANCE III HD instrument (Bruker) equipped with a 5 mm TCI cryoprobe and pulse programs of 1H-13C heteronuclear single quantum correlation (HSQC, hsqcetgpprsisp2.2 by Bruker nomenclature) and 1H-13C HSQC-total correlation spectroscopy (HSQC-TOCSY, hsqcdietgpsisp.2). TopSpin (Bruker) version 3.6.4 was used for NMR operation.

Data were processed by NMRPipe. Peak intensity was extracted by rNMR version 1.11 and data were analyzed by MATLAB (MathWorks) version R2023b. Peak intensity was normalized by biovolume and auto-scaled. Metabolites were annotated based on chemical shift (HSQC) and correlation information (HSQC-TOCSY). Chemical shift values for candidate peaks were obtained from the Biological Magnetic Resonance Data Bank and the Human Metabolome Database, and raw reference spectra from BMRB were used for validation.

Reads were filtered and trimmed using the JGI QC pipeline, followed by evaluation of artifact sequences by kmer matching (kmer=25) using BBDuk, allowing one mismatch; detected artifacts were trimmed from the 3´end of the reads. Quality trimming was performed using the phred trimming method set at Q6 and reads under the minimum length of 25 bases or 1/3 of the original read length were removed. Filtered reads from each library were aligned to the reference genome using HISAT2 version 2.2.0 and strand-specific coverage bigwig files were generated using deepTools v3.1. FeatureCounts was used to generate the raw gene counts, and DESeq2 (version 1.28.1) was used to determine relative expression differences between pairs of conditions. T. pseudonana gene annotations and biosynthesis pathways were based on Biocyc and PhyloDB. R. pomeroyi annotations were based on Roseobase (http://roseobase.org)

NSF Award Abstract:
Phytoplankton in the surface ocean are responsible for roughly half of all photosynthesis on the planet. Much of the organic material created by these photosynthetic organisms is ultimately consumed by diverse marine bacteria with differing preferences for specific types of chemical compounds. This project investigates how climate change (temperature and CO2) might alter the types and amounts of organic compounds produced by different species of marine phytoplankton and the types and amounts of compounds transferred from phytoplankton to marine bacteria. Shifts in organic compounds transferred to bacteria could alter the distribution of bacterial species in the ocean, their growth rates and efficiencies, and flows of energy through the global ocean. This project helps scientists better understand the effects of climate change on marine ecosystems. Two graduate students and a postdoctoral researcher are supported by the project, receiving interdisciplinary training in biology, chemistry, and ocean sciences. Summer research internships in the PIs' laboratories are offered to AP Biology students enrolled at Cedar Shoals High School in Athens, GA, a school that serves a diverse social and economic community.

Much of the bacterial secondary production in the surface ocean is supported by rapid uptake of labile metabolites released from phytoplankton, either directly through excretion and diffusion or indirectly through lysis and predation. This project investigates the effects of two climate change variables (temperature and CO2) on the metabolite pools produced and released by three model phytoplankton species (a diatom, a coccolithophore, and a cyanobacterium) and assesses changes in the composition and fate of metabolites transferred to bacteria. Phytoplankton species are being grown axenically at two different temperatures and CO2 concentrations in a factorial design and endo- and exometabolite composition is determined using NMR. A suite of phytoplankton physiological characteristics is measured and evaluated in the context of metabolite composition. Experiments with heterotrophic bacteria (either model bacteria or natural bacterial communities) are being conducted to assess the effects of climate change variables on metabolite transfer from phytoplankton to marine bacteria. In the first experiment type, bacteria are co-cultured with the phytoplankton at different temperatures and CO2 concentrations, and changes in bacterial gene expression and metabolite concentrations are used to assess shifts in the composition of metabolites transferred. In the second type, bacteria are grown on phytoplankton metabolite pools produced at different temperatures and CO2 concentrations in high-throughput bioassays, and changes in bacterial traits (growth rate, carrying capacity, growth efficiency) resulting from the different climate scenarios are used to indicate changes in metabolite quality. Knowledge of how the heterotrophic processing of phytoplankton metabolites might shift in response to climate change allows better prediction of Earth's future carbon cycle.

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.