Introduction

Microbial studies in extreme environments seek to understand how extraordinary physicochemical stresses shape adaptive responses in both individual organisms and entire communities. Achieving this goal requires coordinated, detailed, accurate measurements of both physical and biological factors, but obtaining this information over temporal and spatial scales relevant to natural microbial communities is challenging. Extreme hypersaline aqueous environments harboring limited phylogenetic diversity provide tractable model ecosystems to confront these challenges (Demergasso et al., 2008; Bodaker et al., 2009; Pagaling et al., 2009; Oh et al., 2010; Boujelben et al., 2012; Makhdoumi-Kakhki et al., 2012; Oren, 2013). Although overall salt concentrations in these habitats are, by definition, at or exceeding the limits of ionic solubility, geochemical variation in water sources as well as minerals dissolved from surrounding rocks and sediments contribute to variable ratios of different ionic species over space and time (Javor, 1989; Oren, 2013). Evaporative concentration and mineral precipitation, accelerated at higher temperatures, selectively deplete some ionic species while enriching others (Javor, 1989). Intermittent rainfall, agricultural runoff and intrusion from groundwater aquifers provide additional sources of geochemical variability (Macumber, 1992; Ionescu et al., 2012).

The biological effects of dissolved ionic species are mediated not only by absolute concentrations but also by ionic ratios (Park, 2012), which affect the efficiency of cellular ion pumps and antiporters used for balancing intracellular osmolarity and establishing electrochemical gradients for energy production and nutrient transport (Oren, 2013). Ionic concentrations also affect the aqueous solubility of oxygen, which is vanishingly low in extreme hypersaline waters (Sherwood et al., 1991). Paradoxically, the dominant microorganisms in these habitats are aerobic, heterotrophic Archaea, along with bacteria from the genus Salinibacter. Although most cultivated microbial strains isolated from extreme hypersaline environments are capable of facultative anaerobic fermentation, they grow optimally in the laboratory under aerobic conditions (Dyall-Smith, 2009; Andrei et al., 2012). The surprising abundance of oxygen-loving organisms in environments with such low oxygen solubility may be explained by the occurrence of non-equilibrium conditions at the air-water interface, providing locally higher oxygen availability. The extent to which temporal differences in mixing efficiency from wind or other factors might affect oxygen distribution through the water column in natural hypersaline environments is largely unknown, but may vary greatly, especially over small distances relevant to microbial localization.

One the most successful microbes in extreme hypersaline waters, the square archaeaon Haloquadratum walsbyi, has a specialized cell morphology utilizing large intracellular gas vesicles to facilitate energy-efficient flotation of tightly packed, nearly two-dimensional flat colonies (Walsby, 1980; Bolhuis et al., 2004). This unique morphology may be an adaptation enabling these organisms to take advantage of higher oxygen concentrations at the surface, especially in shallow ponds where currents and wave action are minimized. The importance of near-surface positioning for this species is supported by the observation that laboratory cultures of Haloquadratum grow best in unmixed media (Mike Dyall-Smith, personal communication). In addition to greater oxygen availability, surface water localization offers higher levels of incident light, enhancing opportunities for energy production through the action of specialized, proton-pumping rhodopsins (Béjà et al., 2001; Sharma et al., 2006). However, these advantages may be partially offset by higher risks of UV-induced DNA damage, particularly when exposure levels peak during summer seasons (Ruiz-González et al., 2011).

Microorganisms able to survive the most extreme hypersaline environments employ a ‘salt-in’ strategy to achieve osmotic stability, balancing high extracellular sodium with high intracellular potassium (Oren et al., 2002). Direct measurements in both the archaeaon Halorubrum sodomense and the bacterium Salinibacter ruber confirm this pattern, demonstrating intracellular potassium levels exceeding 3.0 M (Oren, 1998; Oren et al., 2002). Extreme halophiles also contain much higher intracellular magnesium levels than non-halophiles. Cultured Halobacterium salinarum cells, for example, were found to have total intracellular magnesium concentrations exceeding 100 mM, more than three-fold higher than Escherichia coli cells (30 mM) measured using the same technique (de Médicis et al., 1986). However, work in this area is not sufficiently complete to determine whether intracellular concentrations of some ions might be better controlled than others under naturally occurring conditions, or whether particular combinations or ratios of ion concentrations might have synergistic effects that are not apparent when varying ionic species one at a time (Park, 2012).

Extensive changes to protein amino acid composition have been observed in microorganisms using a salt-in strategy, presumably to counter potential adverse effects of high salt concentrations on protein structure (Fukuchi et al., 2003; Bolhuis et al., 2008). Specifically, proteins of salt-in halophiles are enriched in amino acids with negatively charged side chains, enhancing solubility and depleted in residues with bulky hydrophobic groups, increasing structural flexibility. Little is known about whether nucleic acid sequences undergoing replication, transcription and/or translation might also need special adaptations to function in organisms using a salt-in strategy for osmotic balance. Nucleic acid structure and stability are known to be exquisitely sensitive to ionic concentrations in vitro, especially magnesium, which is orders of magnitude more active than sodium or potassium in increasing double-stranded DNA melting temperature (Hartwig, 2001; Owczarzy et al., 2008) and stabilizing RNA hairpin structures (Bizarro et al., 2012).

Cultured isolates of Haloquadratum walsbyi, which thrive in external magnesium concentrations as high as 2 M, have genomic nucleotide compositions with a much lower percent G+C than other halophilic Archaea. It has been proposed that the lower DNA melting temperature associated with this composition is useful in mitigating the effects of high internal magnesium concentrations, which might otherwise prevent strand separation for replication (Bolhuis et al., 2006). Conversely, it has been suggested that high G+C genomes found in extreme hyperthermophiles might help prevent hydrogen bond de-stabilization at higher temperatures (Saunders et al., 2003). Low G+C nucleotide compositions are also characteristic of prokaryotes found in oligotrophic, nitrogen-poor marine habitats (Giovannoni et al., 2005), but the shallow saltern crystallizer ponds where Haloquadratum walsbyi is commonly found generally contain abundant nitrogen and organic nutrients (Javor, 1989).

The microbial community of Lake Tyrrell, an extreme hypersaline habitat in Victoria, Australia, has previously been characterized using a variety of molecular biology techniques, including 16S and 18S rRNA gene amplification, metagenomic sequencing and de novo assembly of habitat-specific reference genomes for Archaea, bacteria, and viruses (Emerson et al., 2012; Narasingarao et al., 2012; Emerson et al., 2013; Heidelberg et al., 2013; Podell et al., 2013). The current study of Lake Tyrrell combines detailed ionic composition measurements with long-read metagenomic sequencing from the same geographic location during summer and winter seasons over a two-year period. These studies provide evidence suggesting that seasonal changes in concentrations of specific ionic species drive strain selection both within individual taxa and across the entire microbial community, and that this selection is intimately associated with shifts in genomic nucleotide composition.

Materials and methods

Sample collection, metagenome sequencing and assembly

Surface water samples were collected from at 0.3 m depth from Lake Tyrrell, Victoria, Australia (GPS coordinates −35.32, 142.80). Samples for metagenomic sequencing were passed through filters of decreasing porosity (20 μm>3 μm>0.8 μm>0.1 μm), as previously described (Narasingarao et al., 2012). DNA from 0.8 μm and 0.1 μm filters was sequenced using both paired-end Sanger sequencing and Roche 454 Titanium pyrosequencing at the J Craig Venter Institute, as described in (Goldberg et al., 2006). Sample collection dates and associated sequencing libraries are described in Supplementary Table S1. Each individual lake water sample used for DNA isolation and sequence library construction was also subjected to water chemistry analysis, as described below.

Individual metagenomic reads containing 16S rRNA gene fragments were identified from both Sanger and 454 data sets by low stringency BLASTN searches (e-value of 1e-4 or better) against the GreenGenes database (DeSantis et al., 2006). Reads containing 16S rRNA gene fragments were assembled using Celera Assembler version 5.4 using merSize=18, utgGenomeSize =2000 and utgErrorRate =0.02.

Habitat-specific consensus population genomes were reconstructed using iterative de novo assembly techniques, as described previously (Podell et al., 2013). All 232 354 Sanger reads from August 2007 (libraries DAM, EAM and EBM) were combined in a preliminary composite assembly using Celera Assembler version 5.4. with merSize=15, utgGenomeSize =500 000 and utgErrorRate=0.10. Scaffolds from this assembly were binned into provisional groups based on depth of coverage, percent G+C, predicted protein similarity to previously sequenced genomes and number of reads derived from 0.1 micron and 0.8 micron filters, as described in (Podell et al., 2013). August 2008 and January 2009 samples, consisting solely of unpaired 454 Titanium reads, were not assembled.

Preliminary scaffold groups were used to guide selection of August 2007 Sanger and 454 Titanium read subsets for inclusion in iterative, targeted assemblies using more stringent assembly parameters (utgErrorRate =0.06). Draft population consensus genomes assembled from metagenomic reads were annotated using the IMG-ER pipeline (Markowitz et al., 2009). Genome completeness was estimated based on the recovery of 53 transcription, translation and replication genes universally conserved in Archaea (Ciccarelli et al., 2006; Wu and Eisen, 2008; Puigbò et al., 2009; Narasingarao et al., 2012). 16S rRNA genes have been deposited into NCBI GenBank under accession numbers KF673165-KF673190 and assembled population genomes under AYLL00000000 (A07HR60), AYLK00000000 (A07HN63), AYLI00000000 (A07HR67) and AYLJ00000000 (A07HB70).

Phylogenetic diversity and abundance

Assembled 16S rRNA genes from January and August 2007 metagenomic data containing 1160 or more nucleotides (>75% complete) were trimmed and aligned using MUSCLE v 3.6 (Edgar, 2004). Maximum likelihood trees were constructed with FastTree version 2.1.1 (Price et al., 2010) using default parameter settings. Relative abundances of microbial taxa represented in unassembled metagenomic reads were estimated using PhymmBL version 3.2 (Brady and Salzberg, 2011). Taxonomic distributions of predicted proteins in metagenomic assemblies were assessed using DarkHorse version 1.4 (Podell and Gaasterland, 2007; Podell et al., 2008). Taxonomic classifications obtained from both PhymmBL and DarkHorse were based on custom reference libraries consisting of bacterial, archaeal, and phage genomes obtained from NCBI GenBank, supplemented with 12 Lake Tyrrell-specific consensus draft genomes from January 2007 (Podell et al., 2013) and 4 from the current study.

Water chemistry

Samples used for water chemistry were filtered through 0.2 μm filters, then diluted from 100- to 100 000-fold with either MilliQ water (for anions) or 1% trace metal grade HNO3 (for cations). Anion concentrations (F−, Cl− and SO42−) were determined using a Dionex DX4500i ion chromatograph. Cation concentrations were determined via inductively coupled plasma atomic emission spectroscopy on a Varian Vista Pro axial ICP-AES.

Results

Ionic composition measurements

Seasonal measurements of Lake Tyrrell water chemistry are shown in Table 1. As expected, both temperatures and total ionic strength were higher in samples collected during the Austral summer (January), than those obtained in winter (August). However, concentrations and ratios of individual ionic species varied considerably between samples taken in different years, even for the same season. The extent to which ionic concentrations might have been influenced by diurnal temperature fluctuations and short-term dilutions by small-scale rainfall events was not determined. However, daily air temperature and rainfall records for the 30 days prior to each sampling date from the nearest Australian Government Bureau of Meteorology station provide a contextual background for water measurement snapshots taken at the time of sample collection (Supplementary Table S2).

Table 1 Physical properties of Lake Tyrrell sample collection site
Full size table

Sodium, chloride and calcium concentrations were 30–60% lower in summer (January) samples collected in 2007 versus 2009. At the same time, magnesium, potassium and sulfate concentrations increased by 77–168%. Concentrations of individual ions were as much as 40% lower (calcium) or 70% higher (magnesium) in winter (August) samples from 2008 versus 2007. Ionic concentration measurements for water samples taken at two-day intervals varied by less than 5% (Supplementary Table S3), with the exception of magnesium, potassium and sulfate, which were 13–17% lower on the first of two January 2007 sampling dates, consistent with the occurrence of rain two days earlier.

Overall concentration patterns for potassium, magnesium and sulfate correlated strongly with each other across multiple samples, and inversely to sodium, chloride and calcium (Supplementary Figure S1). Although seasonal water temperatures, pH and overall ionic strength were relatively consistent from year to year, variability in concentrations of individual ionic species provided an opportunity to examine the effects of intra- as well as inter-seasonal variation on microbial community composition.

Microbial community diversity

To supplement Lake Tyrrell-specific genomes previously obtained in summer (January) 2007 (Podell et al., 2013), new consensus genomes were assembled for the most dominant microbial species present in winter (August) of the same year (Table 2, Supplementary Table S4). Two of the new genomes from winter 2007 (A07HN63 and A07HR60) included 16S rRNA gene sequences with 97% or greater identity to organisms from the previous summer, suggesting they might belong to the same species. The third genome (A07HR67) contained three 16S rRNA gene copies that were 95% identical to an 820 nt gene fragment from a small, low-coverage, Halorubrum-related scaffold from January 2007, suggesting possible membership in the same genus. The fourth new August 2007 genome (A07HB70) contained a 16S rRNA gene that was only 90% identical to previously observed sequences, indicating a more distant relationship.

Table 2 Lake Tyrrell-specific consensus genomes assembled from August 2007 metagenomic reads
Full size table

The four new assembled genomes accounted for approximately 8.4% of the August 2007 metagenomic reads, at coverage depths ranging from 9–14-fold. Assembly of the remaining August 2007 reads under less stringent conditions yielded thousands of additional scaffolds at 3–5-fold coverage depths, with closest BLAST matches in archaeal genera Haloquadratum, Halorhabdus, Haloarcula, phylum Nanohaloarchaea and bacterial genus Salinibacter. Most of the lower abundance scaffolds were too short for taxonomic binning methods to distinguish between closely related strains, precluding their assembly into discrete population genomes.

To obtain additional taxonomic diversity information, a stringent gene-specific assembly was performed using only August 2007 reads containing 16S rRNA fragments. This assembly yielded nine new 16S rRNA sequences of 1200 nt or longer, supplementing the 16S rRNA sequences obtained from selective population genome assemblies of A07HB70, A07HR67, A07HR60 and A07HN63. An additional 16S rRNA-specific assembly was performed on selected metagenomic reads from January 2007, yielding more complete versions of 16S rRNA genes than those previously published for halophilic archaeal species J07HX64 and J07HB67. Percent identities of 16S rRNA sequences to previously described environmental samples and cultured isolates are shown in Supplementary Table S5.

A phylogenetic tree of archaeal 16S rRNA genes recovered from both summer (January) and winter (August) 2007 samples is shown in Figure 1. Winter samples included nearly full-length 16S rRNA genes from all major taxonomic groups identified in the previous summer, except ‘Candidatus Nanosalinarum sp. J07AB56’ and Halonotius sp. J07HN4. Two new, previously undetected Halorhabdus-related 16S rRNA gene sequences (A07Hrhab_scf299 and A07Hrhab_scf310) and one new Halobaculum-related 16S rRNA gene sequence (A07HB70) were observed in winter, but not summer samples.

Figure 1
figure 1

Phylogenetic tree of Archaeal 16S rRNA genes. FastTree confidence values are indicated at nodes. Red sequences were obtained from January 2007 (summer) targeted assemblies and blue from August 2007 (winter) targeted assemblies. Black sequences indicate cultured isolates and environmental sequences from NCBI GenBank. Asterisks indicate sequences included in assembled population genomes (Supplementary Table S4). Additional information on 16S rRNA sequences is provided in Supplementary Table S5.

Full size image

Seasonal variation in genomic nucleotide composition

Average G+C percentages for individual genomes usually fall within a relatively narrow range, and closely related taxa generally have similar nucleotide compositions. These properties make G+C composition of metagenomic reads a useful metric for observing changes in overall community structure. Figure 2 shows that Lake Tyrrell metagenomic reads from January 2007 and January 2009 had similar, but not identical biphasic distributions, with a smaller peak at 60–65% G+C and a larger peak at approximately 48–50% G+C, respectively. Winter samples contained a greater percentage of sequences in the 60–65% G+C peak. Changes in relative peak heights were much more pronounced in winter 2007 than 2008. These distinctive peak distribution shapes were highly reproducible for samples collected two days apart, and for reads obtained using both Sanger and Roche 454 Titanium technologies (Supplementary Figure S2), confirming that observed seasonal differences were not due to sequencing technology bias.

Figure 2
figure 2

Seasonal variation in percent G+C distribution patterns. Unassembled, unbinned Titanium 454 metagenomic sequencing reads from January 2007 (summer) versus August 2007 (winter) are plotted as smoothed histograms. Panels a–d represent sequencing libraries ABT, DBT, HBT and GBT, as described in Supplementary Table S1. Histogram plots for additional libraries are shown in Supplementary Figure S2.

Full size image

Seasonal shifts in percent G+C distributions occurred not only in the overall set of metagenomic reads but also within read subsets from multiple pooled libraries that were classified into genus-level taxonomic groups (Figure 3). Sharp peaks in G+C plots coincide with increased relative abundance of individual population genomes reconstructed by de novo assembly, for example Haloquadratum strain J07HQW2 (47% GC), Halonotius-related strain J07HN4 (61% GC), Halobaculum-related strain J07HB67 (67% GC) and ‘Candidatus Nanosalina strain J07AB43’ (43% GC) in summer (January) 2007, as well as Halorubrum-related strain A07HR60 (59% GC) and Halobaculum-related strain A07HB70 (71% GC) in winter (August) 2007. Shifts to lower G+C distributions in summer (January) versus winter (August) 2007 samples were clearly apparent for every taxonomic group except Salinibacter, which remained relatively unchanged. Visually observable differences in G+C peak distribution patterns from summers two years apart (January 2007 versus January 2009) were smaller and more subtle than summer versus winter differences within a single year (Supplementary Figure S3). Percent G+C distributions for winter samples taken one year apart appeared to be less consistent than the summer samples, with lower values for Halonotius, Halorhabdus, Halorubrum, Halobaculum, Haloarcula and Nanosalina-related groups in 2008 versus 2007 (Supplementary Figure S4).

Figure 3
figure 3

Seasonal shifts in taxon-specific G+C nucleotide distribution patterns. Taxonomic groups are based on PhymmBL classified subsets of unassembled metagenomic reads from January 2007 (summer) and August 2007 (winter). G+C compositions of reads assigned to each taxonomic group have been plotted as smoothed histograms. Separate Y-axis scales have been used on samples from January 2007 (J07) and August 2007 (A07) to facilitate graphical comparisons.

Full size image

Evidence linking G+C composition to successional changes based on unassembled reads was corroborated by observations made using metagenomic sequence assembly. The phylogenetic tree of assembled 16S rRNA genes shown in Figure 1 indicated that most genus-level archaeal groups from January (summer) and August (winter) 2007 contained at least two closely related populations whose sequences could be assembled into nearly complete genomes (Supplementary Table S4). In most of these taxonomically related pairs, the population with lower G+C genomic nucleotide composition was more abundant in summer versus winter samples, whereas the converse was true in winter, when the higher genomic G+C composition populations were more abundant. Large summer to winter decreases in relative abundance were observed for Halonotius sp. J07HN4 (61% G+C), Halorhabus-related species J07HX5 (61% G+C), Halobaculum-related species J07HB67 (67% G+C) and ‘Candidatus Nanosalina J07AB43’ (43% G+C), which each represented the low end of genomic percent G+C within their taxonomic group. Relative abundances of both Haloquadratum sp J07HQW2 (47% G+C) and J07HQW1 (49% G+C) were decreased in winter samples, while Haloquadratum sp J07HQX50 (50% G+C) remained relatively constant. Conversely, Halobaculum-related species A07HB70 (70% G+C) and Halorubrum-related species A07HR67 (67% G+C), which each represented higher G+C composition populations within their taxonomic groups, were much more abundant in winter than summer samples.

Abundance levels of microbial taxa

Relative abundances of different microbial taxa were initially estimated by taxonomically classifying unassembled metagenomic read nucleotide sequences with PhymmBL (Figure 4). Nucleotide-based relative abundances obtained using PhymmBL were confirmed by comparison to amino acid sequence-based taxonomic analysis of predicted proteins from scaffolds obtained in composite assemblies of unbinned reads (Supplementary Figure S5). Both nucleic acid and amino acid-based analysis techniques showed that Haloquadratum and Nanohaloarchaea-related sequences were more abundant in summer (January) than winter (August) samples, while Halorubrum and Haloarcula-related sequences followed the opposite seasonal pattern. The decrease in Haloquadratum abundance was more pronounced in winter 2007 than 2008, consistent with the observed overall G+C peak distributions for unassembled reads (Figure 2). Winter 2007 samples included a larger increase in Salinibacter-related sequences than was observed in 2008, and a much more even distribution among different taxa than any of the other sampling dates. Halorhabdus-related sequences did not follow any apparent seasonal trend, but were more abundant in both summer and winter samples from 2008 and 2009 than 2007.

Figure 4
figure 4

Seasonal taxonomic abundance patterns. Percentage values indicate relative abundance based on PhymmBL classification of unassembled Titanium 454 metagenomic reads. Relative abundance values have not been corrected for different genome sizes.

Full size image

Haloquadratum abundance was positively correlated with elevated magnesium concentrations, while Halorubrum, Haloarcula, Halonotius, Halobaculum and Salinibacter-related sequences were negatively correlated (Figure 5). Microbial abundance relationships to potassium, sulfate and temperature were nearly identical to those observed for magnesium (Supplementary Figure S6), consistent with the co-variation of these parameters observed in physical water chemistry measurements. Unexpectedly, neither Nanohaloarchaea nor Halorhabdus-related sequences showed any correlation with ionic composition, and no correlations were observed for any microbial groups with environmental sodium, chloride or calcium concentrations.

Figure 5
figure 5

Microbial abundance relationships to environmental magnesium concentrations. Relative abundances of taxonomic groups based on number of nucleotides in PhymmBL classified taxonomic bins for unassembled Titanium 454 metagenomic reads. Abbreviations: Harc, Haloarcula; Hbac, Halobaculum; HN, Halonotius; HQ, Haloquadratum; Hrhab, Halorhabdus; Hrub, Halorubrum; Nsalin, Nanosalina; SB, Salinibacter.

Full size image

The abundances of Halorubrum, Haloarcula, Halobaculum and Salinibacter-related sequences were all inversely correlated to Haloquadratum levels, with R2 values exceeding 0.985 (Figure 6a). Salinibacter-related sequences declined most steeply as Haloquadratum increased, following a polynomial rather than a linear curve. Halonotius sequences were only moderately correlated with Haloquadratum abundance (R2=0.740), while Nanosalina-related (R2=0.181) and Halorhabdus-related (R2=0.003) sequences appeared to be completely independent (Figure 6b). In contrast, Nanosalina-related sequences correlated negatively with Halorhabdus-related sequences (R2=0.805), but were the only taxonomic group that showed any such correlation (Figures 6c and d). The disparate correlation levels observed between microbial groups may reflect shared sensitivities to environmental conditions and/or competitive versus non-competitive community relationships.

Figure 6
figure 6

Relative sequence abundance correlations between taxonomic groups. Panels a and b show abundances of taxonomic groups relative to Haloquadratum-like sequences, based on number of nucleotides in PhymmBL classified bins for unassembled Titanium 454 metagenomic reads. Panels c and d show relative abundances of taxonomic groups compared to Halorhabdus-like sequences.

Full size image

Discussion

This study has revealed strong correlations between concentrations of specific ions, genomic nucleotide compositions, and the relative abundance of different microbial community members over time in a single geographic location. Taxonomic classification of raw metagenomic reads, 16S rRNA gene sequences and predicted proteins from assembled scaffolds demonstrated that similar archaeal populations from class Haloarchaea, phylum Nanohaloarchaeota and the bacterial genus Salinibacter were present in both summer (January) and winter (August) samples, but at different relative abundance levels. Although the total number of environmental samples included in this study does not allow rigorous statistical testing of quantitative values, the patterns observed are supported by consistency of water chemistry measurements, nucleotide composition profiles, phylogenetic binning and de novo metagenomic assembly of multiple samples obtained at two-day intervals, repeated over two summer and two winter seasons. Further experiments will be required to determine whether the same relationships will be observed over a more extensive collection of samples, including a wider range of ionic concentrations, time intervals and geographical locations.

Several physical variables that appeared to influence taxonomic distribution in the Lake Tyrrell microbial community were linked to each other, complicating interpretation of the results. Relative abundance differences were initially observed to track both temperature and total ionic strength. However, significant differences in community abundance were discovered in August 2007 versus August 2008, when temperatures were similar but ionic conditions were different. Although these results do not explicitly rule out a role for temperature, they suggest that ionic composition plays a particularly important role in shaping microbial community structure.

On closer inspection, ionic strength effects on microbial composition were found to correlate with co-varying concentrations of potassium, magnesium and sulfate, but not calcium, sodium or chloride. Although no independent evidence is available suggesting that potassium or sulfate concentrations might influence microbial selection within the ranges observed, cultured isolates of Haloquadratum walsbyi have previously been shown to be much more tolerant of high magnesium than other halophilic Archaea (Bolhuis et al., 2004; Burns et al., 2004). These results support the hypothesis that observed changes in microbial community composition with ionic strength may be driven primarily by elevated magnesium concentrations, rather than other ionic species.

To the best of our knowledge, the current study provides the first reported evidence of selection for microbial strains with lower genomic G+C nucleotide compositions linked to extreme ionic stress in a natural environment. Seasonally linked G+C bias was detected at three different levels of granularity, including total raw reads, taxonomically binned archaeal read subgroups and relative abundance of assembled population genomes. The extent to which the extremely high intracellular magnesium concentrations observed in cultured halophilic Archaea might or might not be controlled by homeostatic mechanisms is unknown. If increased external magnesium concentrations elicit even higher internal magnesium levels, over-stabilization of nucleic acid hydrogen bonds might provide a significant selective disadvantage to microbial strains with higher G+C compositions. The observation that G+C nucleotide compositions were consistently lower in summer and higher in winter for multiple taxa suggests the possibility that seasonally linked selective pressures may contribute to population-level selection and successional changes in microbial community structure. This hypothesis should be amenable to future experimental testing under controlled laboratory conditions.

Results from the current study extend previous reports of an inverse seasonal relationship between the abundance of Haloquadratum and Halorubrum-related strains in Lake Tyrrell (Emerson et al., 2013) as well as other extreme hypersaline environments (Boujelben et al., 2012) by determining quantitative correlation values that also include the rest of the microbial community. This quantitative analysis led to the unexpected discovery that two relatively abundant Lake Tyrrell groups containing Nanohaloarchaea and Halorhabdus-related species varied independently of Haloquadratum, while the rest of the microbial community showed an inverse correlation with Haloquadratum abundance.

In retrospect, marked ecological phenotype differences between Nanohaloarchaea and other halophilic Archaea should not be surprising, considering their disparate evolutionary histories and cellular morphologies. Nanohaloarchaea are characterized by exceptionally small cells (∼0.6 μm in diameter) lacking gas vesicles, flagella and typical archaeal light-driven proton-pumping rhodopsin family genes (Ugalde et al., 2011; Narasingarao et al., 2012). These attributes are consistent with a reduced dependence on highly aerobic processes and light-driven energy production activities requiring close proximity to the air-water interface. Nearly complete population genomes for ‘Candidatus Nanosalina J07AB43’ and ‘Candidatus Nanosalinarum J07AB56’ (Supplementary Table S4) include genes suggesting availability of Embden–Meyerhoff glycolysis, oxidative pentose phosphate and glycogen catabolism pathways. However, the highly atypical amino acid compositions of predicted proteins from these genomes (Narasingarao et al., 2012) and their taxonomic distance from previously characterized database sequences (Rinke et al., 2013) have impeded confident determination of metabolic capabilities through bioinformatic inference alone. Since no cultured isolates have yet been obtained for any species in phylum Nanohaloarchaeota and no gene expression data is available, conditions required for optimal growth remain unknown.

Halorhabdus-related strains are more closely related to other Lake Tyrrell halophilic Archaea, and share many common core metabolic pathways. The genome of Halorhabdus-related strain J07HX64, estimated to be approximately 92% complete (Podell et al., 2013), encodes gas vesicle and flagellar synthesis genes and a chloride-pumping halorhodopsin, but no bacteriorhodopsin-type light-driven proton pumps like those found in Haloquadratum, Halonotius, Halorubrum, Haloarcula and Halobaculum-related genomes. However, failure to detect specific genes in unfinished genomes cannot be conclusive, and inferred metabolic functions based on genomic annotation must be verified using experimental methods.

It has not been determined whether the atypical abundance patterns of Nanohaloarchaea and Halorhabdus-related strains might be associated with additional environmental parameters not included in this study, for example, concentrations of nitrogen, phosphorus and dissolved organic material, or biological predation stresses imposed by viruses and/or picoeukaryotes. Uncharacterized halocin-like antimicrobial activities recently observed in a broad collection of cultured hypersaline Archaea and bacteria (Atanasova et al., 2013) may further influence community structure in natural environments.

It is tempting to speculate that the lack of apparent correlation between relative abundances of Nanosalina and Halorhabdus versus Haloquadratum-related populations might be due to greater reliance on fermentation rather than oxygen-requiring metabolic processes, removing the need to compete for near-surface positioning. Adaptive phenotype differences might also include dissimilar levels of daytime versus nighttime activity. Halorhabdus-related 16S rRNA sequences have been recovered at high abundance from the deep anoxic Discovery Basin in the Eastern Mediterranean Sea (van der Wielen et al., 2005), and cultured isolates of Halorhabdus tiamatea are highly unusual among Halobacteriaceae in preferring anaerobic conditions for optimal growth (Antunes et al., 2008). Although the unavailability of cultured isolates for the Nanohaloarchaea and Halorhabdus-related species present in Lake Tyrell currently precludes direct testing of these hypotheses, the linkage of detailed geochemical measurements and abundance data with the habitat-specific consensus population genomic sequences obtained in this study should provide valuable assistance to future cultivation efforts aimed at determining metabolic phenotypes experimentally.

The success of the current study in discovering and quantifying competitive and environmentally mediated effects on specific microbial taxa lacking cultured representatives would not have been possible without the reconstruction of multiple habitat-specific genomes via de novo metagenomic assembly. These newly reconstructed genomes from natural populations included many unique sequences absent from previously characterized microbial isolates, helping to ensure that databases used for metagenomic read classification encompassed sufficient community breadth to enable sensitive, accurate phylogenetic binning.

Despite these advances, metagenomic sequence assembly, phylogenetic binning, taxonomic abundance measurements and inferred predictions of gene function cannot, by themselves, completely describe the complexity of natural microbial communities. However, the application of these techniques in the current study has laid the essential groundwork necessary for future experiments using metatranscriptomic and metaproteomic techniques to capture gene expression levels linked to specific community members. These results can then be combined with long-term ecological monitoring and high-resolution sampling to reveal the contributions of both major taxonomic groups and individual microbial strains to essential functional activities and environmental adaptations of the entire community.