Genome-enabled transcriptomics reveals archaeal populations that drive nitrification in a deep-sea hydrothermal plume

Abstract

Ammonia-oxidizing Archaea (AOA) are among the most abundant microorganisms in the oceans and have crucial roles in biogeochemical cycling of nitrogen and carbon. To better understand AOA inhabiting the deep sea, we obtained community genomic and transcriptomic data from ammonium-rich hydrothermal plumes in the Guaymas Basin (GB) and from surrounding deep waters of the Gulf of California. Among the most abundant and active lineages in the sequence data were marine group I (MGI) Archaea related to the cultured autotrophic ammonia-oxidizer, Nitrosopumilus maritimus. Assembly of MGI genomic fragments yielded 2.9 Mb of sequence containing seven 16S rRNA genes (95.4-98.4% similar to N. maritimus), including two near-complete genomes and several lower-abundance variants. Equal copy numbers of MGI 16S rRNA genes and ammonia monooxygenase genes and transcription of ammonia oxidation genes indicates that all of these genotypes actively oxidize ammonia. De novo genomic assembly revealed the functional potential of MGI populations and enhanced interpretation of metatranscriptomic data. Physiological distinction from N. maritimus is evident in the transcription of novel genes, including genes for urea utilization, suggesting an alternative source of ammonia. We were also able to determine which genotypes are most active in the plume. Transcripts involved in nitrification were more prominent in the plume and were among the most abundant transcripts in the community. These unique data sets reveal populations of deep-sea AOA thriving in the ammonium-rich GB that are related to surface types, but with key genomic and physiological differences.

Figure 1

Mapping of GB metagenomic fragments to the Nitrsospumilus maritimus genome. The outer-most ring is the complete genome of N. maritimus with open-reading frames (ORFs) colored based on clusters of orthologous genes (COG) categories. The black tiles inside are assembled genomic fragments from the Guaymas assembly that map by BLASTn to regions of the N. maritimus genome. The outer gray-shaded circle is a histogram showing percent sequence identity of top GB proteins that match N. maritimus proteins (scaled from 50% inside to 100% outside). The inner-most gray circle is the raw number of transcripts that map to those homologous proteins; only the range of 0–30 is shown ito highlight regions with little or no transcript recruitment. Genomic islands (>1 kb) missing in archaeal metagenomic data from Gulf of Maine surface waters (Tully et al., 2012) are highlighted with light red wedges. Note that nearly all the gaps in the GB genomic data occur in these genomic islands.

Figure 2

Abundance of raw (not normalized) transcripts mapped to genes in the GB MGI metagenomic bin (5744 total genes). Predicted hypothetical proteins that have matches to N. maritimus genes are labeled ‘Nmar'.

Figure 3

Stacked bar graph showing the number of transcripts recruited to MGI Archaea genes in the plume and background samples, and sorted by difference between the plume and background recruited, with the greatest being at the top. Numbers are normalized to length of the genes as well as the total number of transcripts per sample (raw number transcripts of recruited divided by gene length and library size, then multiplied by a million to it comparable to the raw number of reads). (a) shows transcripts that are most abundant in the plume. (b) shows transcripts of genes not present in Nitrosompumilus maritimus that are most up-regulated in the plume.

Figure 4

Transcript levels of sequence variants of ammonia monooxygenase genes in plume and background samples. Transcript numbers are normalized to gene length and library size. DNA fragments (contigs) with more than one gene are designated with gray bars on the x axis. Individual genes are labeled on top. Thin gray horizontal lines indicate contig coverage in the genomic libraries (see scale on the right).

Figure 5

Phylogenetic tree of ammonia monooxygenase (amoA) genes and abundance of their transcripts in plume and background datasets. Recruitment numbers were normalized to gene lengths and the library sizes. Notice the Gulf of California sequences recovered from the surface waters (Beman et al., 2008) are not related to the types found in this study.