Narrative for Bioproject PRJNA623111
Joy
Generated August 18, 2021

Novel taxa of Acidobacteriota implicated in seafloor sulfur cycling

Mathias Flieder, Joy Buongiorno*, Craig W. Herbold, Bela Hausmann, Thomas Rattei, Karen G. Lloyd, Alexander Loy, and Kenneth Wasmund

*Author/Owner of KBase Narratives

This Narrative is part of a collection used in publications focused on the microbial ecology of fjord sediment in the high Arctic, Svalbard. This paper took a genome-centric approach to uncover novel metabolic capabilities of the Acidobacteriota clade. Metagenomic data was coupled with amplicon sequencing of 16S rRNA and dissimilatory sulfite reductase (dsrB) genes, and transcripts (available under NCBI-Genbank Bioproject PRJNA623111), and gene expression analyses of tetrathionate-amended microcosms.

This Narrative contains the metagenomic assemblies that were constructed within KBase for reproducibility. These include:

These metagenome assemblies served as the launching point for an additional publication focused on a different clade of bacteria (Buongiorno et al., 2020). Link to that Narrative landing page here.

Please cite: Flieder, Mathias, Joy Buongiorno, Craig W. Herbold, Bela Hausmann, Thomas Rattei, Karen G. Lloyd, Alexander Loy, and Kenneth Wasmund. "Novel taxa of Acidobacteriota implicated in seafloor sulfur cycling." The ISME Journal (2021): 1-22.

Narrative Table of Contents

  1. Sample Information
  2. Introduction and Background
  3. Methods
  4. Results and Discussion
  5. References
  6. Acknowledgements

Sample Info Table

Metagenomic sample origin* General biogeochemical type Sample site coordinates Illumina read pairs Read coverage normalised# Lab
Smeerenburgfjorden; Station J, 0-4 cmbsf Ferruginous/sulfidic 79° 42.83N, 11° 05.10E   45,996,553 Vienna
Smeerenburgfjorden; Station J, 10-15 cmbsf Sulfidic 79° 42.83N, 11° 05.10E   73,362,243 Vienna
Smeerenburgfjorden; Station J, 17-20 cmbsf Sulfidic 79° 42.83N, 11° 05.10E   49,176,577 Vienna
Smeerenburgfjorden; Station J, 59 cmbsf Sulfidic 79° 42.83N, 11° 05.10E   56,792,638 Vienna
Smeerenburgfjorden; Station J, 5-10 cmbsf, microcosm with tetrathionate + molybdate Sulfidic 79° 42.83N, 11° 05.10E   99,662,741 Vienna
Smeerenburgfjorden; Station J, 5-10 cmbsf, microcosm with thiosulfate + molybdate Sulfidic 79° 42.83N, 11° 05.10E   53,175,346 Vienna
Smeerenburgfjorden; Station J, 5-10 cmbsf, microcosm with tetrathionate Sulfidic 79° 42.83N, 11° 05.10E 197828199 to 100x  Vienna
Van Kuelenfjorden; Station AC, 18 cmbsf Ferruginous/manganous 77°32.260’ N, 15°39.434’ E 167411750 to 100x  Vienna
Van Kuelenfjorden; Station AB, 0-5 cmbsf Ferruginous/manganous 77°35.249’ N, 15°05.121’E   98,211,882 to 100x Knoxville
Kongsfjorden; Station F, 0-5cmbsf Ferruginous/manganous 78°55.075’ N, 12°15.929’ E   75,827,490 to 100x  Knoxville


* All samples taken July 2016
#prior to assembly

Introduction and Background

Sulfate reduction is a major process in marine sediments, the activities, distributions, and diversity of SRMs have been relatively well studied1-3. Surveys of functional marker genes for sulfite/sulfate reducers in marine sediments, i.e., of dsrAB, have repeatedly shown that dsrAB from the phylum Desulfobacterota are typically the dominant dsrAB-harboring group in marine sediments, but importantly, that several other lineages of uncultivated dsrAB-harboring organisms are also abundant and prevalent4. In this study, we aimed to gain insights into the metabolic potential of uncultured Acidobacteriota lineages in marine sediments, as well as their diversity and distributions. We therefore recovered metagenome-assembled genomes (MAGs) from abundant Acidobacteriota populations present in marine fjord sediments of Svalbard, and predicted their metabolic features. Focus was placed on MAGs from the class Thermoanaerobaculia of the Acidobacteriota, which represent a newly described lineage of dsrAB-harboring organisms that may be important sulfur cycling bacteria in marine sediments. These analyses were complemented with comparative genomics, incubation experiments, transcript analyses, and analyses of Acidobacteriota distributions in Svalbard sediments and publicly available datasets, together revealing they may play various roles in sedimentary biogeochemical cycles, and that they are a prominent group of sulfur-dissimilating organisms.

Methods

Sample collection.

Marine sediments were collected from Smeerenburgfjorden, Kongsfjorden and Van Keulenfjorden, of Svalbard, Norway, in July 2016 and/or June 2017 with the vessel “MS Farm”. From Smeerenburgfjorden, individual core samples were taken from three stations: station GK (79°38.49N, 11°20.96E), station J (79°42.83N, 11°05.10E), and station GN (79°45.01N, 11°05.99E), with the station J cores being taken in both 2016 and 2017. Duplicate core samples from Van Keulenfjorden were taken from sites AC (77°32.260′N, 15°39.434′E) and AB (77°35.249′N, 15°05.121′E). A sample was also taken from Kongsfjorden station F (78°55.075′N, 12°15.929′E)5.

Microcosm incubations with tetrathionate additions.

A sediment slurry was prepared inside an anoxic glove box (nitrogen atmosphere containing 2% hydrogen and 10% CO2), from samples collected in 2017 from 5 to 10 cmbsf at Station J, Smeerenburgfjorden. Sediments had been stored at 4 °C for 6 months prior to the experiment. Anoxic artificial seawater containing 28 mM sulfate was well-mixed with a 2:1 ratio with sediment. Autoclaved serum bottles (250 ml) that were left in the anoxic glove box overnight prior to the experiment to remove traces of oxygen, were filled with 30 ml of sediment slurry. All microcosms received a small amount of organic material to boost heterotrophic activity, i.e., yeast extract (0.22 mg ml−1) (Oxoid). All experiments were set up in triplicates. The experimental treatments included additions of: (i) tetrathionate (500 µM final), or (ii) “no substrate” controls. All microcosms were sealed with autoclaved butyl rubber stoppers. The experiment was incubated at 4 °C for 8 days, and samples were taken at the start of the experiments, day 1 and day 8. Additional tetrathionate (to make 500 µM additional) was spiked into the microcosms on day 5. Subsampling was done inside the anoxic glove box with microcosms placed on ice-pads to reduce warming of the samples. Samples (250 µl) were taken for DNA/RNA-based analyses, kept on the ice-pads in the anoxic glove box and transferred immediately to dry-ice outside the glove box, and stored at −80 °C.

Nucleic acid extractions and reverse transcription.

For amplicon-based analyses, DNA and RNA was extracted from the sediment core samples (~500 µl) and microcosm samples (~250 µl) using the RNeasy PowerSoil Total RNA Kit (Qiagen) according to the manufacturer’s instructions. Additionally, a phenol/chloroform based extraction method6, was used to extract total nucleic acids from sediment samples from station J sampled in July 2016. Eluted nucleic acids were stored in molecular biology grade water at −80 °C. Aliquots for DNA-based analyses were used as eluted, while aliquots for RNA-based analyses were DNase-treated using the TURBO DNA-free kit (Thermo Fisher), followed by reverse transcription of the RNA to cDNA using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher) according to the manufacturer’s instructions. To test if any DNA remained in the RNA samples after the DNase digestion step, control samples were processed as above except the RevertAid M-MuLV Reverse Transcriptase was excluded. These controls were checked for DNA by PCR using 16S rRNA gene targeting primers (described in paper). Sediment samples from 2016 were used for metagenome sequencing. DNA was extracted by the Vienna group from 3 to 5 mL of sediment from varying depths or microcosms derived from station J, Smeerenburgfjorden, and 18 centimeters below seafloor (cmbsf) from station AC of Van Keulenfjorden using the DNeasy PowerSoil Kit (Qiagen) according to the manufacturer’s protocol. DNA was also extracted by the Knoxville group from 2 g of sample spanning 0–5 cmbsf from site AB of Van Keulenfjorden and site F of Kongsfjorden, using the RNeasy PowerSoil Kit (Qiagen) with DNA elution following the manufacturer’s protocol.

Metagenome sequencing and genome binning.

DNA libraries were prepared from individual samples and sequenced using 2 × 150 bp paired-end mode with Illumina HiSeq 3000. Metagenomic libraries were generated from the combined extracts from the first 5 cm (spanning 0–5 cm downcore) in sites AB and F in the Center for Environmental Biotechnology, Knoxville, using HiSeq (Illumina), 2 × 250 bp in paired-end mode5.

KBase narratives.

Reads from each sample were quality filtered, trimmed, and normalized. Reads were then assembled separately on a local server using IDBA-UD (version 1.1.1)7 (read libraries and assemblies in Narrative here. Reads from site F (Kongsfjorden) were assembled locally via metaSPAdes (version 3.11)8 with kmer sizes set to 21, 33, 55, 77, 99, and 127 to find the best assembly (reads and assemblies available in Narrative here). Sample AB reads (Van Keulenfjorden) were assembled using metaSPAdes and Megahit9 on the KBase server (Narrative here). Binning with Maxbin210 was performed on all samples in KBase (Narrative here).

Note

All narratives contain exploratory analysis, and not all sections of the Narratives were included in this publication

Results and Discussion

This study provides the first insights into the genomes and metabolic potential of abundant Thermoanaerobaculia from marine sediments, and new insights into the metabolisms of Ca. Polarisedimenticolia (Acidobacteriota subdivision 22 or GTDB class Mor1). Most notably, we revealed that MAGs from both of the major lineages of Acidobacteriota from marine sediments have capabilities to dissimilate various inorganic sulfur compounds. Genes for the full dissimilatory sulfate reduction pathway provided the first direct link between genomes of marine sediment Acidobacteriota and DsrAB sequences of the previously undescribed “Uncultured family-level lineage 9” clade (here named “Thermoanaerobaculia Dsr lineage”). In addition to being abundant and actively transcribed in Svalbard sediments as shown here, our analysis of dsrAB sequences from various sediment sites around the world further revealed Acidobacteriota are the next most abundant dsr-harboring lineage outside of Desulfobacterota in marine sediments in general. Together, this indicates Acidobacteriota are a widespread and prominent group of inorganic sulfur-dissimilating microorganisms in marine sediments, and therefore likely make significant contributions to the sulfur-cycle in global marine sediments. Full results, discussion, and supplemental information can be found within the original publication.

References

  1. Jørgensen BB, Findlay AJ, Pellerin A. The biogeochemical sulfur cycle of marine sediments. Front Microbiol. 2019;10:849.

  2. Revsbech NP, Barker Jorgensen B, Blackburn TH. Oxygen in the Sea Bottom Measured with a microelectrode. Science. 1980;207:1355.

  3. Wasmund K, Mußmann M, Loy A. The life sulfuric: microbial ecology of sulfur cycling in marine sediments. Environ Microbiol Rep. 2017;9:323–44.

  4. Müller AL, Kjeldsen KU, Rattei T, Pester M, Loy A. Phylogenetic and environmental diversity of DsrAB-type dissimilatory (bi)sulfite reductases. ISME J. 2015;9:1152–65.

  5. Buongiorno J, Sipes K, Wasmund K, Loy A, Lloyd KG. Woeseiales transcriptional response to shallow burial in Arctic fjord surface sediment. PLOS ONE. 2020;15:e0234839.

  6. Angel R, Claus P, Conrad R. Methanogenic archaea are globally ubiquitous in aerated soils and become active under wet anoxic conditions. ISME J. 2012;6:847–62.

  7. Peng Y, Leung HCM, Yiu SM, Chin FYL. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics. 2012;28:1420–8.

  8. Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 2017;27:824–34.

  9. Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674–6.

  10. Wu Y-W, Simmons BA, Singer SW. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 2016;32:605–7.

Acknowledgements

This research was supported by the Austrian Science Fund (FWF grants P29426 to KW and P25111-B22 to AL) and the MetaBac Research Platform of the University of Vienna. We thank Captain Stig Henningsen of MS Farm during Svalbard expeditions. We particularly thank Bo Barker Jørgensen, Alexander Michaud, and Susann Henkel for organizing the 2016 and 2017 Svalbard expeditions, and all members of Svalbard expeditions for help with sample collection, especially Claus Pelikan. We thank the Alfred Wegener Institute—Institute Paul Emile Victor (AWIPEV) station and staff for housing and excellent logistics support. We thank the Biomedical Sequencing Facility (BSF) Vienna for sequencing of metagenome samples, the Joint Microbiome Facility (JMF) of the Medical University of Vienna and the University of Vienna, and Microsynth for sequencing amplicons. We specifically thank Jasmin Schwarz, Gudrun Kohl, and Petra Pjevac from the JMF for assisting with amplicon sequencing. We thank Marc Mussman and Stefan Dyksma for providing the hydrogenase database. We are grateful to Bernhard Schink for help with Latin naming of taxa.