Seafloor Incubation Experiment with Deep-Sea Hydrothermal Vent Fluid Reveals Effect of Pressure and Lag Time on Autotrophic Microbial Communities

Diverse microbial communities drive biogeochemical cycles in Earth’s ocean, yet studying these organisms and processes is often limited by technological capabilities, especially in the deep ocean. In this study, we used a novel marine microbial incubator instrument capable of in situ experimentation to investigate microbial primary producers at deep-sea hydrothermal vents.


SIP metatranscriptomic library preparation
Using results from RT-qPCR, four fractions from each of the 12 C and 13 C samples from the shipboard and incubator samples were sequenced, including fractions with the peak number of 16S rRNA genes and fractions on either side of the peak, for a total of 16 metatranscriptomic libraries. For each SIP metatranscriptomic library, double stranded cDNA was constructed using SuperScript III First-strand synthesis system and mRNA second strand synthesis module. Double stranded cDNA was sheared to a fragment size of 275bp using a Covaris S-series sonicator. SIP metatranscriptomic library construction was completed using the Ovation Ultralow Library DR multiplex system. following manufacturer's instructions. Sequencing was performed on an Illumina NextSeq 500 at the W.M. Keck sequencing facility at the Marine Biological Laboratory. All libraries were paired-end, with a 30 bp overlap, resulting in an average merged read length of 275 bp.

Metagenomic and metatranscriptomic library preparation
The 47mm flat filters were cut in half with a sterile razor, with half used for DNA and half used for RNA extraction. RNA was extracted using the mirVana miRNA isolation kit with added bead-beating step using RNA PowerSoil beads. A total volume of 100 µl was extracted and was then DNase treated using the Turbo-DNase kit (Ambion), purified, and concentrated using the RNAeasy MinElute kit. Ribosomal RNA removal, cDNA synthesis, and metatranscriptomic library preparation was carried out using the Ovation Complete Prokaryotic RNA-Seq DR multiplex system following manufacturer instructions. Prior to library construction, cDNA was sheared to a fragment size of 275 bp using a Covaris S-series sonicator. For DNA extraction, the DNA filter was first rinsed with sterile Phosphate Buffered Saline (PBS) to remove RNAlater and then was extracted using a phenol-chloroform method adapted from Crump et al. (2003) and Zhou et al. (1996). DNA was then sheared to a fragment size of 275 bp using a Covaris S-series sonicator. Metagenomic library construction was completed using the Ovation Ultralow Library DR multiplex system (Nugen) following manufacturer instructions. Metagenomic and metatranscriptomic sequencing was performed on an Illumina Nextseq 500 at the W.M. Keck sequencing facility at the Marine Biological Laboratory. All libraries were paired-end, with a 30 bp overlap, resulting in an average merged read length of 275 bp.

Analysis of Marker 33 metagenome, metatranscriptome, and RNA-SIP metatranscriptomes:
To identify ribosomal RNA reads, the Marker 33 metatranscriptome and RNA-SIP metatranscriptomes were mapped to SILVA SSU and LSU databases ( (2018). Metagenomic reads were mapped to each ORF using Bowtie2 (v2.0.0-beta5 Langmead and Salzberg 2012), with end to end alignment. For the Marker 33 metatranscriptome as well as all 16 RNA-SIP metatranscriptomes, non-rRNA transcripts were mapped to ORFs identified in the Marker 33 metagenome. After mapping, abundances for each ORF were normalized to gene or transcript length. Metagenomic read abundance was normalized to the number of Reads per Kilobase per Genome (RPKG). Number of genomes per metagenome was estimated using hits to the single-copy gene, DNA-directed RNA polymerase beta subunit gene (rpoB). The Marker 33 metatranscriptome and all RNA-SIP metatranscriptomes were normalized to the number of Transcripts Per Million reads (TPM). Normalized KO abundances were used for bubble plot construction, hierarchical clustering, and heatmap generation. Hierarchical clustering of samples (average-linkage method) was carried out using the statistical program R (v3.3.2, R-Development-Core-Team 2011) and the R package pvclust. Heatmaps were constructed in R using the package heatmap3.
To determine taxonomy of non-rRNA transcripts as shown in Figure 3, the RNA-SIP metatranscriptomes were assembled using CLC Genomics Workbench (v 7.0) using default settings and submitted to IMG/MER for ORF identification. The taxonomy for each ORF was determined using the Phylogenetic Distribution tool in IMG, part of the IMG/MER annotation pipeline. To determine taxonomic abundance, the non-rRNA reads were then mapped to each ORF using Bowtie2 (v2.0.0-beta5 Langmead and Salzberg 2012).

References:
Crump    Table S3: Results of temperature distribution testing. The experiment was conducted in an ice bath in the lab to determine the steady state temperature distribution throughout the incubation bag relative to the temperature measured at the controlling RTD sensor used in the field deployments. Sensors were placed throughout the bag to measure variation both longitudinally and radially. Longitudinal variation was measured by sensors placed at the controlling RTD sensor, middle and distal end of the bag, and held in place with a custom bracket fabricated to fit snugly within the incubation bag. Radial variation was measured using sensors placed in the longitudinal center, and at the top and bottom surface of the bag. Sensors generally all showed good agreement with each other and with the controlling RTD sensor used to monitor temperature during field deployment. We observed a small but constant offset between bag temperature and controlling RTD temperature, but these lab temperature distribution results are expected to be the worst case, with mixing driven solely by natural convection. In the field experiments there will be additional mixing from vehicle motion. Note, thermocouple numbers reference the RTD temperature probe readings and thermistor numbers represent readings from bag sensors.  Figure S1. Temperature record of the four incubator units during Jason Dive 825 at Marker 33 with all positions heated to 55°C. Blue line shows measured temperature inside the incubation chamber. The brief dip in measured incubation temperature before 18:00 UTC corresponds to intake of 40°C vent fluid into the incubator, marking the beginning of the incubation. Temperatures were very stable throughout the incubation. The black line is the temperature inside the electronics pressure case.      Figure S7: Concatenated marker gene tree of thermophilic Epsilonbacteraeota metagenome assembled genomes (MAGs). Amino acid alignments were constructed using the program Phylosift using a reference set of 37 marker genes. Tree was constructed using RAxML. MAG completeness, as determined via CheckM, is denoted at the end of each MAG name. Legend denotes the assigned taxonomy of MAGs as determined in Anvi'o.