Role for urea in nitrification by polar marine Archaea.
Alonso-Sáez L, Waller AS
, Mende DR
, Bakker K, Farnelid H, Yager PL, Lovejoy C, Tremblay JE, Potvin M, Heinrich F, Estrada M, Riemann L, Bork P
, Pedrós-Alió C, Bertilsson S
2012 Oct 30; 109(44): 17989-94. Epub 2012 Oct 1; PubMed: 23027926.
Abstract + PDF
Despite the high abundance of Archaea in the global ocean, their metabolism and biogeochemical roles remain largely unresolved. We investigated the population dynamics and metabolic activity of Thaumarchaeota in polar environments, where these microorganisms are particularly abundant and exhibit seasonal growth. Thaumarchaeota were more abundant in deep Arctic and Antarctic waters and grew throughout the winter at surface and deeper Arctic halocline waters. However, in situ single-cell activity measurements revealed a low activity of this group in the uptake of both leucine and bicarbonate (<5% Thaumarchaeota cells active), which is inconsistent with known heterotrophic and autotrophic thaumarchaeal lifestyles. These results suggested the existence of alternative sources of carbon and energy. Our analysis of an environmental metagenome from the Arctic winter revealed that Thaumarchaeota had pathways for ammonia oxidation and, unexpectedly, an abundance of genes involved in urea transport and degradation. Quantitative PCR analysis confirmed that most polar Thaumarchaeota had the potential to oxidize ammonia, and a large fraction of them had urease genes, enabling the use of urea to fuel nitrification. Thaumarchaeota from Arctic deep waters had a higher abundance of urease genes than those near the surface suggesting genetic differences between closely related archaeal populations. In situ measurements of urea uptake and concentration in Arctic waters showed that small-sized prokaryotes incorporated the carbon from urea, and the availability of urea was often higher than that of ammonium. Therefore, the degradation of urea may be a relevant pathway for Thaumarchaeota and other microorganisms exposed to the low-energy conditions of dark polar waters.
Assessment of metagenomic assembly using simulated next generation sequencing data.
Abstract + PDF
Due to the complexity of the protocols and a limited knowledge of the nature of microbial communities, simulating metagenomic sequences plays an important role in testing the performance of existing tools and data analysis methods with metagenomic data. We developed metagenomic read simulators with platform-specific (Sanger, pyrosequencing, Illumina) base-error models, and simulated metagenomes of differing community complexities. We first evaluated the effect of rigorous quality control on Illumina data. Although quality filtering removed a large proportion of the data, it greatly improved the accuracy and contig lengths of resulting assemblies. We then compared the quality-trimmed Illumina assemblies to those from Sanger and pyrosequencing. For the simple community (10 genomes) all sequencing technologies assembled a similar amount and accurately represented the expected functional composition. For the more complex community (100 genomes) Illumina produced the best assemblies and more correctly resembled the expected functional composition. For the most complex community (400 genomes) there was very little assembly of reads from any sequencing technology. However, due to the longer read length the Sanger reads still represented the overall functional composition reasonably well. We further examined the effect of scaffolding of contigs using paired-end Illumina reads. It dramatically increased contig lengths of the simple community and yielded minor improvements to the more complex communities. Although the increase in contig length was accompanied by increased chimericity, it resulted in more complete genes and a better characterization of the functional repertoire. The metagenomic simulators developed for this research are freely available.
Transcriptional analysis of a dehalococcoides-containing microbial consortium reveals prophage activation.
Waller AS, Hug LA, Mo K, Radford DR, Maxwell KL, Edwards EA
Chlorinated solvents are among the most prevalent groundwater contaminants in the industrialized world. Biodegradation with Dehalococcoides-containing mixed cultures is an effective remediation technology. To elucidate transcribed genes in a Dehalococcoides-containing mixed culture, a shotgun metagenome microarray was created and used to investigate gene transcription during vinyl chloride (VC) dechlorination and during starvation (no chlorinated compounds) by a microbial enrichment culture called KB-1. In both treatment conditions, methanol was amended as an electron donor. Subsequently, spots were sequenced that contained the genes most differentially transcribed between the VC-degrading and methanol-only conditions, as well as spots with the highest intensities. Sequencing revealed that during VC degradation Dehalococcoides genes involved in transcription, translation, metabolic energy generation, and amino acid and lipid metabolism and transport were overrepresented in the transcripts compared to the average Dehalococcoides genome. KB-1 rdhA14 (vcrA) was the only reductive dehalogenase homologous (RDH) gene with higher transcript levels during VC degradation, while multiple RDH genes had higher transcript levels in the absence of VC. Numerous hypothetical genes from Dehalococcoides also had higher transcript levels in methanol-only treatments, indicating that many uncharacterized proteins are involved in cell maintenance in the absence of chlorinated substrates. In addition, microarray results prompted biological experiments confirming that electron acceptor limiting conditions activated a Dehalococcoides prophage. Transcripts from Spirochaetes, Chloroflexi, Geobacter, and methanogens demonstrate the importance of non-Dehalococcoides organisms to the culture, and sequencing of identified shotgun clones of interest provided information for follow-on targeted studies.
Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours.
, Waller AS
, Raes J
, Zelezniak A, Perchat N, Perret A, Salanoubat M, Patil KR, Weissenbach J, Bork P
Abstract + PDF
Despite the current wealth of sequencing data, one-third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome-scale metabolic models with these new sequence-function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction.