Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Supplemental Files
• Related Publications
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

Metabarcode samples collected from surface and chlorophyll maximum depths from R/V Pt. Sur PS 18-09 Legs 01 and 03, Hurricane Harvey RAPID Response cruise (western Gulf of Mexico) September-October 2017.

On each of 2 cruise legs 01 and 03, samples were collected at 7 stations (S01, S06, S11, S16, S21, SS and GI) from 2 depths [surface and chlorophyll maximum depth when possible; see HRR-bottle data] ) and triplicate 500-1000 ml samples were filtered and immediately fixed in RNALater. Triplicate samples from each station/depth were extracted with AllPrep DNA/RNA MiniKit (Qiagen, USA) following the manufacturer’s instructions. DNA concentration and quality were evaluated using a Nanodrop spectrophotometer (Thermo Fisher Scientific Inc, USA). All the samples extracted for DNA were normalized to 5ng/µl concentration for the amplicon library construction.

The V4 regions of the 18S rRNA genes were amplified using customized V4 primers (Bradley et al. 2016; Kozich et al. 2013). Library construction and amplicon sequencing was performed at Texas A&M University Agrilife’s Genomics and Bioinformatics Services (https://www.txgen.tamu.edu) using custom designed primers (Bradley et al. 2016; Kozich et al. 2013). Output of MiSeq results as fasta files were deposited in GenBank under the project number PRJNA592369.

Leg 01 Station 01 sample was not collected.

Sampling locations:

Fastq files for all 13 station samples were quality checked using FastQC. Illumina paired end reads (2x300 bp) were processed in mothur v1.39.0 (Schloss et al. 2009). Contigs were assembled and pre-cleaned processed for homopolymers and ambiguities. These sequences were then screened for chimera using UCHIME in denovo mode (Edgar et al. 2011). Sequences were de-noised by pre-clustering at 1 bp per 100 bp and generate unique sequence for taxonomic annotation and characterization. Sequences less than three were eluted out in our study and rest OTUs were characterized using BLAST search using PR2 database v4.12.0. The BLAST analysis used a assignment approach with similarity was ≥ 90% and query coverage was ≥ 70% against the reference sequence. Any OTU that did not compile with this criterion was not used in this study. The following thresholds for identity with BLAST results were used for taxonomic assignment clustering: species (97%), genus (94%), family (93%), class (92%) and order (90%).

HTS-metabarcoding procedures were followed as mentioned in Gaonkar et al., (2020). Only HTS metabarcodes haplotypes (OTUs) with reads more than 3 allocated to Chaetocerotaceae (Chaetoceros and Bacteriastrum) were used with a selection criterion of ≥ 90% similarity and ≥ 70% similarity after BLAST analysis using the protistan PR2 dataset. A total of 206 (n=82881) OTUs annotated as Chaetocerotacean haplotypes were obtained from the HRR dataset. See figures 1 and 2 in the Supplemental Files section.

BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions

NSF Award Abstract:
Hurricane Harvey is the strongest hurricane to hit the Texas coast in decades and the resulting tidal surges, flooding and terrestrial runoff have had a severe impact on the coastal ocean. The effects on the phytoplankton, the first link in the food chain, may be unprecedented. To determine how the phytoplankton community will respond to such drastic changes in salinity, nutrient inputs, and potential toxins, immediate and continuous sampling is the only way to fully capture the effects and to identify when conditions return to "normal". An automated, continuous phytoplankton imaging instrument that is deployed on the Texas coast records images of the phytoplankton and permits calculation of the abundance of different species. Together with molecular information on the genes that have been "turned on", or expressed, outcomes of this project will help determine the responses of individual types of phytoplankton. Extreme storms are expected to increase in frequency with future climate change, so the responses identified now will be valuable in predicting how such events will affect these primary producers, which in turn support most of the food webs in marine ecosystems, in the future.

High temporal resolution observations from the Imaging FlowCytobot (IFCB) have revealed that hurricanes in the Gulf of Mexico cause drastic changes in the phytoplankton community structure. The objectives of this RAPID project are: 1) to characterize the dynamics of the phytoplankton species in relation to the environmental variables along the Texas coast; 2) to assess the short and long-term changes in the phytoplankton community; and 3) to identify the strategies of the phytoplankton community for resource acquisition. To accomplish these objectives, this project will utilize IFCB time series to follow phytoplankton community structure during the recovery period from Hurricane Harvey. In addition, two RAPID response cruises (in late September and early October) to sample at 5 sites along a transect from Galveston to Port Aransas, TX. At each station, CTD profiles and water samples from surface and the chlorophyll maximum will be collected for nutrients, carbonate chemistry, and RNA sequencing for metatranscriptomic analysis. Metatranscriptomics can provide an indication of the metabolic strategies employed and functional relationships within the plankton community in response to changes in the environment. The advantage of a metatranscriptomic approach is that the entire molecular response to the environment is captured. So, while the response of phytoplankton to increased nutrient inputs from floodwater runoff is targeted, the responses to other environmental stresses (toxics, hypoxia, acidification) are also captured. Analyses of this time series using multivariate statistical techniques, such as principal component analysis (PCA), and network analysis, a powerful technique for identifying potential interactions among taxa, will provide insights on the environmental factors and metabolic responses structuring the community during the aftermath of the hurricane.

Related data from the The Texas Observatory for Algal Succession Time-Series (TOAST) can be found at the following: https://toast.tamu.edu/timeline?dataset=HRR_Cruise