The genome sequence of the psychrophilic archaeon, <i>Methanococcoides burtonii</i>: the role of genome evolution in cold adaptation

Allen, Michelle A.; Lauro, Federico M.; Williams, Timothy J.; Burg, Dominic; Siddiqui, Khawar Sohail; Francisci, Davide De; Chong, Kevin Wai Yin; Pilak, Oliver; Chew, Hwee H; Maere, Matthew Z De; Ting, Lily; Katrib, Marilyn; Ng, Charmaine; Sowers, Kevin R.; Galperin, Michael Y.; Anderson, Iain; Ivanova, Natalia; Dalin, Eileen; Martinez, Michele; Lapidus, Alla; Hauser, Loren; Land, Miriam; Thomas, Torsten; Cavicchioli, Ricardo

doi:10.1038/ismej.2009.45

Cited by 148 publications

(171 citation statements)

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“…Low rates of diazotrophy are also likely to occur in the mixolimnion (for example, by cyanobacteria) and monimolimnion (Figure 4b). In the monimolimnion, methanogens that encode nif genes, such as M. burtonii (Allen et al, 2009), could benefit from nitrogen fixation. Symbiotic relationships between diazotrophic archaea and SRB that have been reported to occur in marine environments (Dekas et al, 2009) may also occur in Ace Lake.…”

Section: Resultsmentioning

confidence: 99%

“…Mineralization low abundance of Euryarchaeota (B2-5% of the total community), coupled to the very low potential for aerobic methane oxidation and the absence of 16S rRNA signatures for ANME Euryarchaeota. One of the two methanogenic archaea isolated from the lake, M. burtonii, possesses several genes most closely related to Epsilonproteobacteria and Deltaproteobacteria (Allen et al, 2009). The relative abundance of Epsilonproteobacteria and Deltaproteobacteria (Figure 2), and an overrepresentation of transposable elements (Figure 3 and Supplementary Figure S6) is consistent with gene exchange occurring within the microbial community in this zone, particularly between the Epsilonproteobacteria and Deltaproteobacteria and M. burtonii; the normalized number of transposases throughout the Ace Lake metagenome is two orders of magnitude higher than in marine metagenomes (for example, Global Ocean Survey).…”

Section: Resultsmentioning

confidence: 99%

“…The lake is a structured, relatively closed system with marine-derived biota making it ideal for studying the short-term evolution of species and ecosystem function. A range of studies have described archaea, bacteria, eucarya and viruses in the lake, including several unusual bacteria, and the psychrophilic methanogens Methanogenium frigidum and Methanococcoides burtonii (Gibson, 1999;Rankin et al, 1999;Bowman et al, 2000;Coolen et al, 2004Coolen et al, , 2006Cromer et al, 2005;Laybourn-Parry et al, 2005;Madan et al, 2005;Powell et al, 2005;Cavicchioli, 2006;Allen et al, 2009). The lake is sensitive to climatic influences and is a sentinel for monitoring climate change.…”

Section: Introductionmentioning

confidence: 99%

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An integrative study of a meromictic lake ecosystem in Antarctica

et al. 2010

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In nature, the complexity and structure of microbial communities varies widely, ranging from a few species to thousands of species, and from highly structured to highly unstructured communities. Here, we describe the identity and functional capacity of microbial populations within distinct layers of a pristine, marine-derived, meromictic (stratified) lake (Ace Lake) in Antarctica. Nine million open reading frames were analyzed, representing microbial samples taken from six depths of the lake size fractionated on sequential 3.0, 0.8 and 0.1 lm filters, and including metaproteome data from matching 0.1 lm filters. We determine how the interactions of members of this highly structured and moderately complex community define the biogeochemical fluxes throughout the entire lake. Our view is that the health of this delicate ecosystem is dictated by the effects of the polar light cycle on the dominant role of green sulfur bacteria in primary production and nutrient cycling, and the influence of viruses/phage and phage resistance on the cooperation between members of the microbial community right throughout the lake. To test our assertions, and develop a framework applicable to other microbially driven ecosystems, we developed a mathematical model that describes how cooperation within a microbial system is impacted by periodic fluctuations in environmental parameters on key populations of microorganisms. Our study reveals a mutualistic structure within the microbial community throughout the lake that has arisen as the result of mechanistic interactions between the physico-chemical parameters and the selection of individual members of the community. By exhaustively describing and modelling interactions in Ace Lake, we have developed an approach that may be applicable to learning how environmental perturbations affect the microbial dynamics in more complex aquatic systems.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An integrative study of a meromictic lake ecosystem in Antarctica

et al. 2010

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“…Power-law distributions can imply a scale-free network, whereby the number of links to nodes provides a measure of node fitness (43), and the abundance of transposons has been linked to cold adaptation (44)(45)(46). The fact that tADL has the highest abundance and is highly connected to ISs (Fig.…”

Section: Discussionmentioning

confidence: 99%

High level of intergenera gene exchange shapes the evolution of haloarchaea in an isolated Antarctic lake

DeMaere

Williams

Allen

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Deep Lake in Antarctica is a globally isolated, hypersaline system that remains liquid at temperatures down to −20°C. By analyzing metagenome data and genomes of four isolates we assessed genome variation and patterns of gene exchange to learn how the lake community evolved. The lake is completely and uniformly dominated by haloarchaea, comprising a hierarchically structured, low-complexity community that differs greatly to temperate and tropical hypersaline environments. The four Deep Lake isolates represent distinct genera (∼85% 16S rRNA gene similarity and ∼73% genome average nucleotide identity) with genomic characteristics indicative of niche adaptation, and collectively account for ∼72% of the cellular community. Network analysis revealed a remarkable level of intergenera gene exchange, including the sharing of long contiguous regions (up to 35 kb) of high identity (∼100%). Although the genomes of closely related Halobacterium, Haloquadratum, and Haloarcula (>90% average nucleotide identity) shared regions of high identity between species or strains, the four Deep Lake isolates were the only distantly related haloarchaea to share long high-identity regions. Moreover, the Deep Lake high-identity regions did not match to any other hypersaline environment metagenome data. The most abundant species, tADL, appears to play a central role in the exchange of insertion sequences, but not the exchange of high-identity regions. The genomic characteristics of the four haloarchaea are consistent with a lake ecosystem that sustains a high level of intergenera gene exchange while selecting for ecotypes that maintain sympatric speciation. The peculiarities of this polar system restrict which species can grow and provide a tempo and mode for accentuating gene exchange. mobile genetic elements | Antarctic haloarchaea | saltern | fragment recruitment | BJ1 virus

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“…This homeoviscosity is achieved by steric hindrances introduced into the lipid bilayer via incorporation of cis-unsaturated and branched-chain lipids, a decrease in average chain length, and an increase both in methyl branching and in the ratio of anteiso-to isobranching (Russell, 2007). More recently, several genomes from psychrophilic bacteria have been sequenced (Danchin, 2007;Casanueva et al, 2010) but only a few of them have been analyzed with respect to cold adaptation (Saunders et al, 2003;Rabus et al, 2004;Medigue et al, 2005;Methe et al, 2005;Riley et al, 2008;Allen et al, 2009;Ayala-del-Rio et al, 2010). However, the lack of common features shared by all these psychrophilic genomes has suggested that cold adaptation superimposes on pre-existing cellular organization and, accordingly, that the adaptive strategies may differ between the various microorganisms (Bowman, 2008;Piette et al, 2010).…”

Section: Introductionmentioning

confidence: 99%