INTRODUCTION

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Has adaptation to novel environments by the extension of tolerance limits historically been an important mechanism by which the ecological requirements of microorganisms have diverged? While the breadth of physiological diversity exhibited by microorganisms suggests that this may be the case, the relevance of this mechanism is yet to be firmly established. Similarly, little is known about the consequences of this mode of adaptation for fitness in ancestral environments. For example, are there trade-offs or costs of adaptation such that there is a correlated loss in performance under ancestral conditions? Providing answers to the above questions may help microbiologists to better make sense of extant microbial diversity and its distribution on the planet.

The cyanobacteria provide an excellent system for testing hypotheses concerning the evolution of tolerance. During its evolutionary history, this ancient lineage of oxygen-evolving, photoautotrophic bacteria has established itself in diverse aquatic and terrestrial habitats exhibiting wide ranges in temperature, salinity, water potential, pH, and irradiance (36). An example of ecological diversification in the cyanobacteria is the invasion of alkaline hot spring habitats across western North America, Asia, Africa, and possibly Europe by members of the genus Synechococcus (8). Hot spring outflows typically exhibit marked temperature gradients, and microbial communities containing Synechococcus generally develop in these systems at temperatures between ~45 and 73°C, the thermal maximum for photosynthetic life (3, 4). Peary and Castenholz (26) demonstrated with laboratory isolates that at least four temperature strains of Synechococcus inhabited a single channel at Hunter's Hot Springs in Oregon. It was later hypothesized that more thermotolerant Synechococcus strains evolved from less thermotolerant ancestors growing at lower temperatures (5). It was not possible to test this hypothesis, however, because the data required to establish the branching order of the temperature strains in a phylogeny (i.e., their order of evolutionary divergence) were not available.

Conversely, substantial cyanobacterial molecular diversity has been identified among environmental 16S rRNA and rRNA gene fragment sequences recovered from microbial mat communities in Octopus Spring in Yellowstone National Park (32). Among these, phylogenetically similar sequences which clearly belong to Synechococcus have distribution patterns consistent with the hypothesis that genotypically distinct lines have diverged in temperature range (11, 13). However, while it is possible to gain an understanding of genealogical patterns from these molecular data, the lack of phenotypic data for the organisms limits the testing of evolutionary ecological hypotheses.

The ability to infer the patterns and processes of past ecological diversification therefore depends upon both the availability of comparative phenotypic data for the study organisms and an understanding of their phylogenetic relatedness. We have combined comparative physiology of laboratory isolates with phylogenetic approaches in order to investigate the evolution of thermotolerance in Synechococcus from Hunter's Hot Springs in Oregon. We first reconstructed molecular phylogenies to infer the evolutionary relationships of Synechococcus temperature strains isolated in laboratory culture from Hunter's Hot Springs. We next collected comparative growth rate data for these isolates at a series of temperatures in order to distinguish four groups of strains based on both identity of 16S rRNA gene sequence data and thermotolerance characteristics. From the phylogeny we then determined the order of evolutionary divergence of groups of strains with different thermotolerances to test the hypothesis that more thermotolerant strains of Synechococcus evolved from less thermotolerant ancestors. Finally, we incorporated phylogenetic information into a statistical analysis of the comparative physiological data in order to reveal possible phenotypic trade-offs during the evolution of increased thermotolerance.

	MATERIALS AND METHODS

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Sample collection, enrichment, and clone isolation. Hunter's Hot Springs comprises a cluster of several alkaline thermal sources located ~3 km north of Lakeview, Oreg. Between 1994 and 1998, several collections of microbial mat were taken at four temperatures (45, 55, 65, and 70°C) along one of the outflow channels (Jack's Spring). For each collection, the upper, Synechococcus-containing component of the mat was harvested with a sterile 10-ml syringe, transferred to a sterile 20-ml scintillation vial, and stored at ambient temperature in the dark until it was taken to the University of Oregon.

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DNA isolation, amplification, and sequencing. Genomic DNA of clones were isolated as described by Pitcher et al. (27). Fragments (ca. 950 bp) of the 16S rRNA gene were amplified from these DNA preparations. This gene was chosen because the database for it is the most extensive database among those for cyanobacterial loci, which facilitated adequate taxon sampling and placement of the Synechococcus strains within the context of the cyanobacterial phylogeny. The 50-µl amplification reaction mixtures contained 10 mM Tris-HCl (pH 8.3), 50 mM KCl, each deoxynucleoside triphosphate at a concentration of 200 µM, 1.12 mM MgCl₂, 1.25 U of Taq polymerase (Perkin-Elmer), ~10 ng of genomic DNA, 0.2 µM primer CYA359F (25), and 0.2 µM primer PLG2.3 (5'CTTCA[C/T]G[C/T]AGGCGAGTTGCAGC3'), a modification of PLG2.1 (31). The reaction conditions used were 40 cycles of 94°C for 1 min, 58°C for 1 min, and 72°C for 2 min. Amplification products were purified with a QIAquick-spin PCR purification kit (Qiagen), and cleaned amplification products were directly sequenced with an ABI Prism 377 sequencer at the DNA Sequencing Facility, University of Oregon.

Sequence alignment. 16S rRNA gene sequences were preliminarily aligned with Clustal W1.6 (29). Since the stem-loop structure of the mature 16S rRNA molecule contains information with respect to nucleotide positional homology, secondary structure was then syntactically imposed on each sequence for the fragment spanning Escherichia coli nucleotide positions 360 to 1326 as described by Titus and Frost (30). Previously published secondary-structure models aided identification of stem-encoding nucleotides of cyanobacterial and outgroup sequences (14, 37). A final pairwise alignment was made by using Malign 2.7 (35) with a gap cost to substitution cost of 3. Missing data were treated as unknown nucleotides.

Phylogeny reconstruction. Phylogenetic trees were constructed by using three optimality criteria. A neighbor-joining tree was built with MEGA 1.01 (20). For calculation of a distance matrix, Kimura's two-parameter model was assumed (19), and nucleotide positions containing gaps or missing data were deleted in a pairwise fashion. The tree was inferred with pairwise deletion of gaps and with 1,000 bootstrap pseudoreplicates. A maximum-parsimony phylogeny was constructed by using PAUP 3.1.1 (28). A heuristic search was performed by using the tree bisection-reconnection branch-swapping algorithm. Starting trees were obtained by stepwise addition of sequences and 10 replications of random sequence addition. The analysis was bootstrap pseudoreplicated 100 times. A maximum-likelihood tree was created with the "dnaml" program in PHYLIP 3.5c (10) by using a transition-to-transversion ratio of 2, sequential addition of sequences, and 100 bootstrap pseudoreplicates. All trees were rooted with Aquifex pyrophilus.

Determination of clone growth temperature ranges. Exponential growth rates were estimated at intervals along a clone's thermal range for growth by using the following method. Beginning at the clone's maintenance temperature, the growth rate was determined as described below. The experimental temperature was then shifted up, usually by 5°C, and cells were transferred to fresh medium as described below. Near the predicted upper thermal limit for the clone, based on data for temperature strains of Synechococcus from a previous study (26), the magnitude of the shift was decreased in order to resolve differences among clones with respect to thermal maxima. Growth rates were again estimated, and this procedure was repeated until the clone's lethal temperature was reached, as indicated by a lack of growth and cell bleaching. To evaluate clone performance at temperatures below that used for routine maintenance, an analogous procedure was employed with thermal down-shifts accompanying clone transfer.

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Statistical analyses. Growth rate data were analyzed with analysis of variance (ANOVA) models, and pairwise comparisons of means were made by using Bonferroni tests with a significance level of  = 0.05. All analyses were done with SPSS Base 8.0 (SPSS Inc.).

Nucleotide sequence accession numbers. The 16S rRNA gene sequence data obtained for the Synechococcus strains used in this study have been deposited in the GenBank database under accession numbers AF285244 to AF285253 (group I), AF285240 to AF285243 (group II), AF285259 (group III), AF285254 to AF285258 (Group IV), and AF285260 (Synechococcus sp. strain SH-94-5).

	RESULTS

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Synechococcus clones isolated from Hunter's Hot Springs. Twenty Synechococcus clones were isolated in two kinds of mineral salts media from samples collected at four temperatures at Hunter's Hot Springs (Table 1). Isolates were obtained from both diluted and undiluted enrichments (Table 1). Sixteen of these clones were obtained from along the temperature gradient of a single outflow channel (Jack's Stream). Clones OH12, OH16, and OH19 were derived from an adjacent site at Hunter's Hot Springs sampled in October 1994. At this time central Oregon was experiencing drought conditions, and Jack's Stream was dry at temperatures above ~45°C. By the following collection date in May 1995, the source of Jack's Stream was flowing again, and a microbial mat had become reestablished at higher temperatures.

16S rRNA gene sequence groups of Hunter's Hot Springs Synechococcus clones. All of the clones isolated in this study fall into four groups based on 100% sequence identity of an ~950-bp fragment of the 16S rRNA gene. All Synechococcus clones isolated from 45°C collections, as well as some clones obtained from 55°C collections, have identical sequences (group I) (Table 1). Clones representing two additional sequence groups, groups II and III, were isolated from 55°C collections, while all isolates from samples collected at 65°C or above have identical sequences (group IV) (Table 1).

Phylogenetic reconstructions. Cyanobacterial 16S rRNA gene sequence phylogenies were inferred by using maximum-parsimony, neighbor-joining, and maximum-likelihood methods (Fig. 1). While there are topological differences among the three phylogenies, they are similar in several important respects. First, Synechococcus clones belonging to sequence groups II, III, and IV, which were all derived from collections obtained at 55°C or above, form a clade in all three trees. The topology of this clade is consistent for all methods and is strongly supported by bootstrap analysis data in all cases (Fig. 1). The maximum-likelihood analysis, which provides error estimates for the estimated evolutionary distances between taxa, further supports the inferred structure of this clade. The estimated evolutionary distance between group II and IV Synechococcus clones is 0.051 substitution per site, with a 95% confidence interval of (0.024,0.079). The estimated evolutionary distance between group II and III Synechococcus clones is 0.038 substitution per site, with a 95% confidence interval of (0.017,0.061), while the distance between group III and IV Synechococcus clones was estimated to be 0.018 substitution per site, with a 95% confidence interval of (0.007,0.031). The fact that none of the confidence intervals overlaps zero provides strong evidence that a statistically significant evolutionary distance separates each pair of taxa and, therefore, that the 16S rRNA gene fragment used in this study contains sufficient genetic variation to resolve the phylogeny of the Hunter's Hot Springs sequence groups.

View larger version (100K): [in this window] [in a new window]   FIG. 1.   Cyanobacterial phylogenies inferred from ~950 bp of 16S rRNA gene sequence data by using neighbor-joining (A), maximum-parsimony (B), and maximum-likelihood (C) methods. Synechococcus clones from Hunter's Hot Springs are indicated by capital letters. A value at a node indicates the percentage of the time that the taxa to the right of the node formed a clade for 100 (A and C) or 1,000 (B) bootstrap pseudoreplicates. Only bootstrap values greater than 50% are indicated.

Temperature range of group I Synechococcus clones. Growth rate data were collected at temperatures between 30 and 60°C for five group I clones isolated from 45°C collections (Table 2). No differences were found among the clones in terms of growth temperature range; the highest temperature for growth was estimated to be 57°C, and the lower limit was less than 30°C (Table 2). However, there was variation in the mean growth rate among temperatures (Table 3). One-way ANOVAs were performed for each temperature treatment to partition this variation into among-clone and within-clone components. No clone effect was found at temperatures between 40 and 55°C (Table 3). The estimated mean growth rates at these temperatures (Table 3) could therefore be directly compared by using Bonferroni tests. The growth rate estimates increased in the order 55°C < 40°C (=50°C) < 45°C, which indicates that the optimal growth temperature of these group I clones was 45°C. The relative amount of variation in the growth rate (i.e., the coefficient of variation) increased at the temperature range extremes, and differences among clones explained much of this variation, as indicated by the high R² values (Table 3). The existence of genetic variation in the growth rate among clones at the extremes of the temperature range may indicate that the organisms do not typically experience these temperatures in situ; i.e., this genetic variation is not expressed phenotypically and can therefore accumulate without being subject to natural selection. Otherwise, it would be expected that this genetic diversity would be reduced by natural selection, as appears to be the case at intermediate temperatures, including the optimal temperature (Table 3). An alternative explanation for this pattern is that the variation was generated by mutation during laboratory cultivation. Distinguishing between these two hypotheses will require further experimentation.

Temperature range diversification in the group II-group III-group IV clade. The two group II Synechococcus clones which were examined (OH4 and OH20) grew at temperatures between 40 and 61°C (Table 4). ANOVA with clone and temperature as factors indicated that there was no difference between the clones in the exponential growth rate (F_[1,16] = 0.02; P = 0.89) and no clone-by-temperature interaction (F_[7,16] = 0.77; P = 0.62); i.e., the two clones had the same temperature response profile. Growth data for these clones were therefore pooled, and estimated growth rates at different temperatures were compared with Bonferroni tests. The mean growth rate increased in the order 40°C < 61°C (= 45°C = 50°C = 55°C) < 57°C, which indicates that the optimum temperature for growth of these clones is 57°C.

Evolution of enhanced thermotolerance in Synechococcus. The phylogenetic branching order of lineages which have different phenotypes for a particular trait provides information on the direction of phenotypic change during cladogenesis (21). For the clade comprising group II, III, and IV Synechococcus clones and their inferred sister taxa (Fig. 1), the least thermotolerant lineages are basal, while isolates with greater thermotolerance branch later along the phylogeny (Fig. 2). This pattern of diversification supports the hypothesis that Synechococcus strains capable of growing at increasingly higher temperatures evolved from less thermotolerant ancestors. This is the pattern of diversification expected if there has been an adaptive radiation of Synechococcus temperature strains up the thermal gradient in response to past directional selection along a hot spring outflow channel. The common ancestor of these three groups, however, was not group I-like in terms of its phylogenetic status, and a comparable radiation has not occurred in the group I Synechococcus lineage (Fig. 1; Table 2).

View larger version (19K): [in this window] [in a new window]   FIG. 2.   Phylogenetic pattern of thermotolerance diversification in the group II-group III-group IV Synechococcus clade.

Evidence for trade-offs. The observation that more thermophilic lineages of Synechococcus have lost the ability to grow at lower temperatures (Fig. 2) is evidence that there have been evolutionary costs of adapting to high temperatures. We wished to determine whether there may have been additional trade-offs during the evolution of thermotolerance in this clade. This can be assessed by testing whether different aspects of thermal performance are negatively correlated across taxa (18). However, because the study organisms are related to each other to different degrees due to common ancestry, phenotypic data collected from them may be nonindependent and consequently must first be transformed to meet the assumption of correlational analysis that data points are independent. We used Felsenstein's (9) method of independent contrasts (see Materials and Methods) to transform the data prior to estimating correlations.

	DISCUSSION

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A hot spring outflow produces a thermal gradient which directly selects for enhanced performance at higher temperatures. Phylogenetic analyses of ~950 nucleotides of the 16S rRNA gene were able to resolve a clade of increasingly more thermotolerant lineages of the cyanobacterium Synechococcus which have radiated in response to this directional selection to exploit previously inhospitable thermal niches (Fig. 2). While extension of the maximum temperature was integral to the evolution of thermotolerance in Synechococcus, there was not necessarily a corresponding increase in the optimal temperature, as evidenced by the lack of a detectable difference in this trait between group II clones and group III clone OH2 (Tables 4 and 5). The minimum temperature, however, has clearly shifted to higher values along with the maximum temperature (Fig. 2). Although we cannot infer the underlying mechanism(s) for this apparent trade-off, this is the expected pattern in the case of antagonistic pleiotropy in which there has been evolution of a gene or genes influencing performance at both ends of the thermal tolerance range (17). These genes could include many enzyme-encoding loci whose products are subject to thermodynamic constraints on performance (1). Because performance at lower temperatures decreased faster than performance at higher temperatures increased, the net evolutionary result has been a reduction in the breadth of the temperature range (Table 5), which further indicates that adaptation of Synechococcus to higher temperatures has come at the cost of increased thermal specialization.

The increase in thermal specialization may be related to the biogeographical structure suggested by the lack of identity between the 16S rRNA gene sequences of group II, III, and IV Synechococcus clones and clones from Octopus Spring in Yellowstone National Park. Hot spring Synechococcus isolates have low tolerance for freezing and desiccation, factors likely to be important in dispersal (6, 8). The more rapid loss of tolerance to lower temperatures during adaptation to higher temperatures may have limited the ability of cells to survive dispersal between habitats. Increased ecological specialization may therefore be an agent of geographical isolation.

It is worthwhile to compare the evolutionary trends revealed by this study with results obtained with E. coli lines selected for enhanced thermotolerance. A clone was more likely to extend its thermal limit if it was exposed to a lethal temperature (44°C) than if it was exposed to a high but nonlethal temperature (42°C) (2, 24). However, clones previously propagated at 42°C tended to be more predisposed to evolving an extended thermal limit upon lethal selection than were clones formerly maintained at the ancestral temperature, 37°C (24). An analogous predisposition for more thermotolerant lines to be derived from lines with a previous history of exposure to elevated temperatures has been recorded in the topology of the Synechococcus clade (Fig. 2). On the other hand, in contrast to the pattern suggested by our comparative data (Table 5), Mongold et al. (24) found that extension of the thermal limit in E. coli was not necessarily accompanied by a trade-off with performance at the lower thermal limit.

Directional selection still acts on Synechococcus at the thermal limit in nature, yet there is no evidence of positive population growth at temperatures above 73°C (3, 4). Since many nonphotosynthetic prokaryotes can grow at temperatures higher than 73°C, it has been suggested that the lack of a response to selection may be due to intrinsic limits in the stability of the photosynthetic apparatus (3). However, studies on a Synechococcus isolate from Hunter's Hot Springs with a group IV-like phenotype indicated that carbon reduction was more thermolabile than photosynthetic oxygen evolution (23). Clearly, more information is needed to determine the factor(s) underlying the upper temperature limit for photosynthesis. Having established a phylogenetic framework in which to study thermotolerance in Synechococcus, we are now in a position to trace the mechanistic history of biochemical adaptation in this clade and to investigate the possible evolutionary constraints which have prevented a further response to natural selection.