Ecogenomics reveals community interactions in a long-term methanogenic bioreactor and a rapid switch to sulfate-reducing conditions

Andrew R. St. James* and Ruth E. Richardson

*Author/Owner of KBase Narratives

This Narrative is part of a collection used in a single publication. The paper took a metagnomic and metatranscriptomic approach to examine a bioreactor's response to the presence of sulfate, which reduces the production of methane, a valuable product, while producing hydrogen sulfide, a corrosive contaminant.

This Narrative collection has been created to highlight the types of analyses done for this publication. They are as follows (in order):

• SJ1 Metagenomes: a metagenomic analysis of sample SJ1, the initial bioreactor. View-only Narrative / Interactive Narrative Narrative.
• SJ1 Metatranscriptomes: QC-filtered raw RNA reads were aligned to individual MAGs and assembled into transcripts. View-only Narrative / Interactive Narrative.
• Metagenome-discovered food webs in a long-term methanogenic bioreactor and rapid switch to sulfate reducing conditions (current Narrative): the public Narrative referenced in the paper, which contains several key MAGs. Interactive Narrative.

Please cite: Andrew R St. James, Ruth E Richardson. Ecogenomics reveals community interactions in a long-term methanogenic bioreactor and a rapid switch to sulfate-reducing conditions, FEMS Microbiology Ecology, Volume 96, Issue 5, May 2020, https://doi.org/10.1093/femsec/fiaa050.

Published MAGs

Introduction to this Narrative

This Narrative contains the final MAGs that were published in the paper.

This publication involved a numerous layers of analyses and, as a result, elements are spread across many Narratives, some of which also contain exploratory analysis that was not continued further. Below, the bioinformatic methods used in the paper are described in detail, with links to two example Narratives, one containing a metagenomic analysis of the SJ1 samples and another containing metatranscriptomic analysis of the same sample.

Narrative Table of Contents

1. Introduction and Background
2. Methods
3. Results and Discussion
4. References
5. Supplementary Information

KBase Object Table

The KBase objects included in this Narrative correspond with the core MAGs referenced in Table 2 of the Publication, reproduced here. Also included is MAG001, a Sulfuricurvum-like MAG. MAG001 showed low expression of sulfur oxidation (Sox) genes, suggesting it is not catalyzing high levels of sulfur oxidation in the culture.

Table 2. Genome characteristics of core MAGs. RRA: relative read abundance. MTs: metatranscriptomes.

MAG	Organism name	Size (Mbp)	GC content	Contigs	Completeness (contamination)	RRA SJ1	RRA SJ1S	Range of RRA control MTs	Range of RRA sulfate MTs
MAG006	Desolfovibrionaceae sp. SJ1006	3.9	0.651	32	100.00% (0.00%)	0.0214	0.2599	1.52–8.24%	3.05–10.74%
MAG002	Syntrophomonas sp. UBA5314	4.3	0.493	68	97.96% (3.95%)	0.0742	0.0295	33.73–38.90%	31.62–39.68%
MAG015	Syntrophomonas sp. SJ1015	3.2	0.493	85	90.03% (2.93%)	0.0135	0.0201	9.53–12.80%	11.16–14.03%
MAG004	Methanosaeta concilli	2.7	0.519	94	100.00% (0.65%)	0.0311	0.036	7.03–23.91%	11.82–24.44%
MAG010	Methanospirillum hungatei	3.4	0.454	50	99.02% (0.98%)	0.013	0.0	4.63–12.64%	4.84–9.91%

Introduction and Background

Methane (CH₄) is a gas produced in organic waste streams that is important to harvest, both ecologically and environmentally.^1,2 The presence of sulfate and sulfate-reducing bacteria can limit the viability production of methane both by competing for carbon sources as well as producing hydrogen sulfide (H₂S), which is both corrosive and destructive to bioreactors and odorous and unpalatable to the general public.³ Many sulfate-reducing bacteria are metabolically flexible and only reduce activate sulfate-reducing machinery in the presence of high sulfate concentrations.⁴

This work investigates a model butyrate-to-methane bioreactor over 48 hours of pulse feeding with butyrate and sulfate, and analyzing the metabolic flexibilty of the sulfate-reducing bacteria and their relationship to methanogenic bacteria.

Methods

Bioreactor setup and culturing

The methanogenic bioreactor was maintained in an environment with 70% N₂ and 30% CO₂. SJ1, the sample shown in the linked Narratives, was started from an culture, DonnaII, that has been well-studied at Cornell University.^5-7 The culture was pulse fed tieh butyrate and fermented yeast extract. After 14 months of enrichment a stable, methanogentic, non-dechlorinating culture was observed, and a sulfate-enrichment culture (SJ1S) was taken from the SJ1 culture. The SJ1S culture was fed with the same enrichment as the SJ1 with sulfate added as well. Six microcosms were taken to analyze temporal transcriptomic differences, and methane concentration measurements were taken from each of those cultures. A graphical depiction of the cultures is shown below in Figure 1.

Figure 1: Overview of Sampling Scheme
Red: control culture and microcosms receiving not receiving sulfate
Green: samples receiving sulfate

Nucleic Acid Extraction and Non-KBase Computational Methods

Nucleic acids were extracted from the SJ1 and SJ1S samples, the 6 microcosms, and a 'starvation' sample taken from the SJ1 effluent at 0 hours. The DNA and RNA were sequenced using the Illumina HiSeq-2000 platform at the Department of Energy's (DOE) Joint Genome Institute (JGI). Quality control and read filtering were performed using BBTools (sourceforge.net/projects/bbmap) and annotated using the Integrated Microbial Genomes (IMG) system.⁸

KBase Analysis

Metagenomic analysis can be found in this Narrative.
Using KBase, contigs from SJ1 and SJ1S were binned using MaxBin2 (view in Narrative) and assessed for completeness and contamination with CheckM (view in Narrative). MAGs were extracted as assemblies from the binned contigs (view in Narrative). The MAGs were then annotated using RAST (view in Narrative).

Metatranscriptome analysis can be found in this Narrative.
QC-filtered reads were aligned using Bowtie2 (view in Narrative), and then relative abundance calculated using Cufflinks (view in Narrative).

Note: both Narrative contain exploratory analysis, and not all sections of the Narrative were included in the paper.

Results and Discussion

Proteobacteria are dominated by populations implicated in internal sulfur cycling including Sulfuricurvum as well as Desulfovirionales and Syntrophobacterales. Neither Firmicutes nor Bacteroidetes are dominated by single genera in the metagenomes. Euryarchaeota are dominated by reads mapping to the aceticlastic genus Methanosaeta and hydrogenotrophic genus Methanospirillum. In SJ1S, Proteobacteria, especially Desulfovibrionales increase while Methanospirillum and Sulfuricurvum effecively reach extinction. Binning from SJ1 resulted in 61 high-quality MAGs (>90% complete and <10% contaminated). Six of those MAGs of interest are stored in the KBase narrative cited in the paper. The MAG identified as Desulfovibrionacea sp. SJ1006 was found to show change in expression due to presence of sulfate, indicating the MAG shifts its physiological strategy in response to sulfate. The MAG identified as Syntrophomonas sp. SJ1015 was found in increase central carbon metabolism in response to sulfate.

For full results and discussion, please see the paper.

References

1. Stillwell AS, Hoppock DC, Webber ME. Energy recover from wastewater treatment plants in the United States: a case study of the energy–water nexus. Sustainability 2010;2:945–62.
2. Lin L, Xu F, Ge X et al. Improving the sustainability of organic waste management practices in the food–energy–water nexus: a comparative reviewof anaerobic digestion and composting. Renew Sustain Energy Rev 2018;89:151–67.
3. Muyzer G, Stams AJM The ecology and biotechnology of sulphate-reducing bacteria. Nat Rev Microbiol 2008;6:441–54.
4. Plugge CM, Scholten JCM, Culley DE et al. Global transcriptomics analysis of the Desulfovibrio vulgaris change from syntrophic growth with Methanosarcina barkeri to sulfidogenic metabolism. Microbiology 2010;156:2746–56.
5. Fennell DE, Gossett JM, Zinder SH. Comparison of butyric acid, ethanol, lactic acid, and propionic acid as hydrogen donors for the reductive dechlorination of tetrachloroethene. Environ Sci Technol 1997;31:918–26.
6. Rowe AR, Lazar BJ, Morris RM et al. Characterization of the community structure of a dechlorinating mixed culture and comparisons of gene expression in planktonic and bioflocassociated “Dehalococcoides” and Methanospirillum species. Appl Environ Microbiol 2008;74:6709–19.
7. Heavner GLW, Rowe AR,Mansfeldt CB et al. Molecular biomarkerbased biokinetic modeling of a PCE-dechlorinating and methanogenic mixed culture. Environ Sci Technol 2013;47: 3724–33.

Supplementary Information

The objects contained in this Narrative as well as the key objects used for all analyses in the publication can be viewed and copied for further analysis in the SJ1 Intermediate Files Narrative.