Common Presence of Phototrophic Gemmatimonadota in Temperate Freshwater Lakes
ABSTRACT
Members of the bacterial phylum Gemmatimonadota are ubiquitous in most natural environments and represent one of the top 10 most abundant bacterial phyla in soil. Sequences affiliated with Gemmatimonadota were also reported from diverse aquatic habitats; however, it remains unknown whether they are native organisms or represent bacteria passively transported from sediment or soil. To address this question, we analyzed metagenomes constructed from five freshwater lakes in central Europe. Based on the 16S rRNA gene frequency, Gemmatimonadota represented from 0.02 to 0.6% of all bacteria in the epilimnion and between 0.1 and 1% in the hypolimnion. These proportions were independently confirmed using catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH). Some cells in the epilimnion were attached to diatoms (Fragilaria sp.) or cyanobacteria (Microcystis sp.), which suggests a close association with phytoplankton. In addition, we reconstructed 45 metagenome-assembled genomes (MAGs) related to Gemmatimonadota. They represent several novel lineages, which persist in the studied lakes during the seasons. Three lineages contained photosynthesis gene clusters. One of these lineages was related to Gemmatimonas phototrophica and represented the majority of Gemmatimonadota retrieved from the lakes’ epilimnion. The other two lineages came from hypolimnion and probably represented novel photoheterotrophic genera. None of these phototrophic MAGs contained genes for carbon fixation. Since most of the identified MAGs were present during the whole year and cells associated with phytoplankton were observed, we conclude that they represent truly limnic Gemmatimonadota distinct from the previously described species isolated from soils or sediments.
IMPORTANCE Photoheterotrophic bacterial phyla such as Gemmatimonadota are key components of many natural environments. Its first photoheterotrophic cultured member, Gemmatimonas phototrophica, was isolated in 2014 from a shallow lake in the Gobi Desert. It contains a unique type of photosynthetic complex encoded by a set of genes which were likely received via horizontal transfer from Proteobacteria. We were intrigued to discover how widespread this group is in the natural environment. In the presented study, we analyzed 45 metagenome-assembled genomes (MAGs) that were obtained from five freshwater lakes in Switzerland and Czechia. Interestingly, it was found that phototrophic Gemmatimonadota are relatively common in euphotic zones of the studied lakes, whereas heterotrophic Gemmatimonadota prevail in deeper waters. Moreover, our analysis of the MAGs documented that these freshwater species contain almost the same set of photosynthesis genes identified before in Gemmatimonas phototrophica originating from the Gobi Desert.
INTRODUCTION
Microorganisms conduct key biogeochemical processes involved in the main fluxes of matter and energy on Earth. Most microbial diversity remains uncultured, and only analyses of environmental DNA samples have made it possible to unravel existing microbial diversity and to identify the main species involved (1). Indeed, out of 112 known bacterial phyla in the Genome Taxonomy Database (GTDB) (2), more than one half are still recognized only from environmental sequences (3).
One of the phyla that was first identified using molecular phylogenetic methods was Gemmatimonadota (also called Gemmatimonadetes [4]), which was originally established as the so-called BD group based on five 16S rRNA gene sequences, which originated from deep-sea sediments, soils, and reactor sludge (5, 6). Independently, the group was also proposed as a candidate division KS-B based on three 16S rRNA gene sequences retrieved from coastal sediment samples from French Guiana (7).
The first cultured strain T27 belonging to the BD/KS-B group was isolated from a wastewater treatment plant in Japan. The isolate was named Gemmatimonas aurantiaca and established the new phylum Gemmatimonadota, along with its first class Gemmatimonadetes and genus Gemmatimonas (8). Subsequently, three more Gemmatimonadota genera (Gemmatirosa, Longimicrobium, and Roseisolibacter) with type strains were described from various soil environments (9–11). Apart from class Gemmatimonadetes, phylum Gemmatimonadota consists of four more class-level groups which include class Longimicrobia, two terrestrial groups (BD2-11 and S0134), and one marine benthic group (PAUC43f) (10, 12). The four cultured representatives from the phyla were all chemo-organoheterotrophs that require oxygen and grow under fully aerobic or semiaerobic conditions (8–11). An interesting metabolic potential and ecological role was reported for G. aurantiaca, as this species has the ability to reduce the greenhouse gas N2O (13). However, with the discovery of Gemmatimonas phototrophica, which contains photosynthetic reaction centers (14, 15), Gemmatimonadota were added to several bacterial phyla containing anoxygenic phototrophic species alongside Proteobacteria, Chlorobi (now included as a class-level lineage in Bacteroidota [2]), Chloroflexota, Firmicutes (Bacillota), Acidobacteriota, and the newly discovered phylum “Candidatus Eremiobacterota” (WPS-2) (14, 16, 17). Anoxygenic phototrophs, such as G. phototrophica, are able to support their metabolism by harvesting light using bacteriochlorophylls; however, they require a supply of organic substrate for growth (18). Another characteristic found in G. phototrophica is the organization of its photosynthesis genes into a cluster called the photosynthesis gene cluster (PGC). Interestingly, the gene arrangement in the PGC of G. phototrophica is very similar to the one found in Proteobacteria, so it has been suggested that phototrophy in Gemmatimonadota originates from an ancient horizontal gene transfer of the entire PGC from Proteobacteria (14). As yet, this is the only known case of horizontal transfer of an entire set of photosynthesis genes between distant bacterial phyla (14, 19).
Information about the prevalence of Gemmatimonadota in different habitats is continuously growing, although information about their ecology is scarce. Members of this phylum were found in many natural environments (12, 20–22) and represent the eighth most abundant phylum in soils, accounting for about 1 to 2% of bacteria in soils worldwide (23). Their highest contributions are typically found in fertile agricultural and forest soils (20) but are also present in more unique soil environments, such as arid Antarctic Dry Valley soils (24, 25). It has been suggested that Gemmatimonadota may be relatively more abundant in dry soils (26). On the other hand, from the available data, it is known that they are also present in aquatic environments, such as freshwater lakes (27), sediments (22, 28–30), and estuaries (31, 32). In addition, G. phototrophica was isolated from a freshwater lake in Inner Mongolia (18). However, this organism does not grow in liquid culture and requires microaerophilic conditions, which are more typical for sediment-dwelling species. Thus, the data showing that Gemmatimonadota prefer dry environments does not seem to be universal. There is probably a large ecological and functional diversity among the members of Gemmatimonadota. The question remains whether Gemmatimonadota-related sequences identified in lakes originate from strictly limnic species, or perhaps they are just a passive component that enters the lakes along with runoff waters from surrounding soil.
Current progress in sequencing technologies and bioinformatics has circumvented the necessity for cultivated representatives and allowed biological and ecological inferences to be drawn by using genomic data recovered directly from microbial communities. Over the past few years, the usage of metagenome-assembled genomes (MAGs) has allowed the description of many novel bacterial divisions and unearthed large radiations in the prokaryotic tree of life (33). This approach has already led to the discovery of new phototrophic organisms belonging to the yet uncultured candidate phylum “Ca. Eremiobacterota” (16, 34). Also, two MAGs belonging to Gemmatimonadota were recovered from Lake Baikal. One MAG was more similar to Gemmatirosa kalamazoonensis found in soils and seemed more abundant at a depth of 5 m. The other MAG-encoded rhodopsin gene and was closely related to the phototrophic species G. phototrophica and showed a higher abundance at 20 m (35).
Therefore, in order to address the question whether there are any truly limnic Gemmatimonadota and to investigate their diversity, we analyzed metagenome data from five freshwater lakes in Czechia and Switzerland. The lakes were chosen based on their trophic status and included a representative mesoeutrophic Římov Reservoir, a dystrophic Jiřická pond, oligomesotrophic Lake Zurich and Lake Constance, and an ultraoligotrophic Lake Thun (Table 1). The metagenome sequences were collected over several years and seasons. The reconstructed MAGs were analyzed with the aim to identify the most common freshwater and photoheterotrophic Gemmatimonadota and to analyze their spatiotemporal variability. Using catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH), cells of Gemmatimonadota were visualized for the first time in their natural environment, and their association with other organisms was observed.
TABLE 1
| Characteristic | Římov Reservoir | Jiřická pond | Lake Zurich | Lake Constance | Lake Thun |
|---|---|---|---|---|---|
| Countrya | CZ | CZ | CH | CH | CH |
| Latitude | 48.50°N | 48°36'N | 47°18'N | 47°32'N | 46°41′N |
| Longitude | 14.29°E | 14°40'E | 8°34’E | 9°31'E | 7°43′E |
| Altitude (m) | 470 | 892 | 406 | 395 | 558 |
| Area (km2) | 2.10 | 0.035 | 88.66 | 536 | 48.3 |
| Volume (m3) | 34.5 × 106 | 6.59 × 103 | 3.3 × 109 | 48 × 109 | 6.5 × 109 |
| Avg depth (m) | 16.5 | 1.8 | 49 | 90 | 136 |
| Maximum depth (m) | 43 | 4.5 | 136 | 251 | 217 |
| Mean hydraulic residence time | 77 days | 9 days | 1.4 yrs | 5 yrs | 1.8 yrs |
| Trophic status | Mesoeutrophic | Dystrophic | Oligomesotrophic | Oligomesotrophic | Ultraoligotrophic |
| Mixing type | Dimictic | Polymictic | Monomictic | Monomictic | Monomictic |
| Sampling | 2015−2017 | 2016−2017 | 2010−2019 | 2018 | 2018 |
| No. of samplesb | E = 10, H = 8 | E = 5 | E = 6, H = 4 | E = 2, H = 2 | E = 1, H = 1 |
a
CZ, Czechia; CH, Switzerland.
b
E refers to epilimnion, and H refers to hypolimnion. The exact depths for each of the lakes are provided in Materials and Methods.
RESULTS
Abundance of Gemmatimonadota.
The presence of Gemmatimonadota in freshwater lakes was first assessed by using relative 16S rRNA abundances extracted from our metagenomic data sets. In all studied lakes, Gemmatimonadota formed only a small part of the bacterial community with relative abundances typically below 1%. The highest relative abundance was found in Římov Reservoir, where Gemmatimonadota sequences were present over the entire sampling period (2015 to 2017). Interestingly, their relative abundance was higher in the hypolimnion (0.58% ± 0.23%; n = 8) than in the epilimnion (0.24% ± 0.21%; n = 10), with the highest numbers (1.03%) in August 2016. A similar pattern of higher contribution in the hypolimnion (0.44% ± 0.27%; n = 4) than in the epilimnion (0.28% ± 0.25%; n = 6) was also observed in Lake Zurich, with the highest relative abundance occurring in spring (13 May 2013, 0.77%). The general pattern of higher abundance in the hypolimnion was observed also in both Lake Constance and Lake Thun and was recorded in summer with 0.81% and 0.58% relative abundance, respectively. Finally, the lowest contribution of Gemmatimonadota was found in Jiřická pond, where they represented less than 0.1% of the prokaryotic community, with a maximum of 0.09% recorded in summer, in August 2017.
Statistical analysis using distance-based linear models (DistLM) showed that the only environmental factor driving the Gemmatimonadota community in Římov Reservoir was water temperature, which explained 47% of the variability in the data set (P = 0.0002, pseudo-F = 13.303). A separate analysis of epilimnion and hypolimnion samples showed that temperature was also important in epilimnion (P = 0.0079, pseudo-F = 5.7106, and 41.6% of the explained variability in data set) but not in hypolimnion.
Metagenome-assembled genomes of Gemmatimonadetes and their distribution.
To explore the diversity of aquatic Gemmatimonadota, we performed genome-resolved metagenomics analyses. The freshwater MAGs (n = 45) obtained in our study were analyzed together with those publicly available (n = 226) in March 2019 (see Table S1 in the supplemental material for a complete list). Most of the MAGs assembled by us were obtained from Římov Reservoir (n = 27), followed by Lake Zurich (n = 10), Lake Constance (n = 5), Lake Thun (n = 2), and Jiřická pond (n = 1). Publicly available MAGs originated from various environments: mostly from marine habitats (n = 36) and soils (n = 37), followed by sediments of soda lakes (n = 38), permafrost (n = 23), and other (n = 11). Only three MAGs from freshwater environments were available in the database at the time of the study.
Phylogenomically, based on Genome Taxonomy Database (GTDB) taxonomy (39), all MAGs recovered in this study clustered within class Gemmatimonadetes (Fig. 1). Although they were all recovered from a freshwater environment, six of them were more closely related to publicly available MAGs from environments like soils and sediments. MAGs CH-Jul18-bin44, ZH-3nov15-207, and TH-Jun18-bin75 clustered with MAGs from soils, and CH-Jul18-bin76, CH-Jul18-bin112, and ZH-3nov15-212 clustered with MAGs from sediments. Similarly, in 16S rRNA phylogeny (see Fig. S1 in the supplemental material), all freshwater MAGs with recovered 16S rRNA genes clustered within class Gemmatimonadetes, with the exception of two previously mentioned MAGs (CH-Jul18-bin112 and ZH-3nov15-212) that clustered within the BD2-11 terrestrial group based on SILVA SSU v138 database taxonomy (12).
FIG 1
16S rRNA gene diversity.
The 16S rRNA gene fragments from metagenomes were classified taxonomically. As most of the Gemmatimonadota phylum consists of environmental sequences that remain uncultured, many of the fragments could not be classified. Therefore, in order to increase taxonomic resolution of unclassified Gemmatimonadota, we have used 16S rRNA gene sequences from our MAGs (Fig. S1) to define six new clusters (five from class Gemmatimonadetes and one from BD2-11 terrestrial group). In Římov Reservoir, the Gemmatimonadota community was solely composed of the class Gemmatimonadetes (Fig. 2). The genus Gemmatimonas was present in all seasons and both depths, but it was more abundant in the epilimnion, especially in summer (15-Aug-16). Epilimnion was dominated by the genus Gemmatimonas and unclassified Gemmatimonadaceae, with the exception of three samples (two in November and one in April) where other clusters were also present. In contrast, hypolimnion samples contained several different clusters, including phototrophic cluster PG1 that was one of the dominant clusters in every season. Similarly, clusters GRI1 and GSR7 were predominantly present in the hypolimnion. The presence of these three clusters in the epilimnion occurred only in November and April, when the reservoir was mixed. In Jiřícká pond, the Gemmatimonadota community was composed of three clusters from the class Gemmatimonadetes, i.e., genus Gemmatimonas, cluster GSR7, and cluster PG1, the latter being mostly dominant in summer. Additionally, the BD2-11 terrestrial group was also present in low proportions in summer. The highest taxonomic diversity within Gemmatimonadota was observed in Swiss lakes, where three other class-level groups in addition to Gemmatimonadetes were recovered, i.e., representatives of classes Longimicrobia, BD2-11 and S0134, groups that were previously known only from terrestrial 16S rRNA gene sequences (12). Here, genus Gemmatimonas was also predominantly present in the epilimnion, whereas cluster GSR7 dominated the hypolimnion. In Lake Zurich, a large contribution of class Longimicrobia was recorded in a spring sample (13-May-13) in both the epilimnion and hypolimnion.
FIG 2
Photosynthesis genes in Gemmatimonadota.
Further analyses of the assembled genomes of Gemmatimonadota revealed that 19 out of 45 freshwater MAGs contained phototrophic genes. In the phylogenetic tree, we could differentiate them into three distinct phototrophic groups (Fig. 1). Phototrophic group 1 contained eight MAGs from the hypolimnion of Římov Reservoir and one from Jiřická pond. Phototrophic group 2 was formed of nine MAGs (three from the epilimnion of Lake Zurich, five from the epilimnion of Římov Reservoir, and one from the hypolimnion of Římov Reservoir). Phototrophic group 2 also included the only cultured photoheterotrophic strain of the phylum, G. phototrophica, as well as the only three MAGs from freshwater environments that were publicly available. Phototrophic group 3 contained two MAGs from the hypolimnion of Římov Reservoir. All these MAGs were recovered from different time points (several years and different seasons).
Using representatives from each of these groups, we reconstructed the photosynthetic gene cluster and compared its structure and organization with the PGC found in G. phototrophica (14). For phototrophic groups 1 and 2, we reconstructed the entire PGC. In the case of phototrophic group 3, the PGC was missing several genes due to the incompleteness of the genomes (MAGs had completeness of 71.07. and 83.16%). From our findings, it appears that limnic Gemmatimonadetes have the same or very similar organization of phototrophic genes as G. phototrophica AP64 (Fig. 3 and Table S4). A distinct trait of G. phototrophica is a fragmented PGC divided by a set of hypothetical genes. The same split PGC was observed in three out of nine MAGs from phototrophic group 2, but it was absent in phototrophic groups 1 and 3. Furthermore, we observed the presence of the gene frhB (coenzyme F420-reducing hydrogenase, beta subunit) in the operon bchP2G, in the PGC of all members of phototrophic group 1, at the position where all other phototrophic Gemmatimonadetes have bch2. A full list of phototrophic genes for each MAG, as well as their distribution on contigs, is provided as Table S4.
FIG 3
As the presence of ribulose 1,5-bisphosphate carboxylase enzyme (RuBisCO) genes was previously reported in some sediment Gemmatimonadota MAGs, we also searched for them in our freshwater MAGs. We identified type IV RubisCO-like genes in eight phototrophic freshwater MAGs from Římov Reservoir (Fig. S3). Seven of these MAGs belonged to phototrophic group 1 recovered from hypolimnion, and one to phototrophic group 2 recovered from the epilimnion of Římov Reservoir.
Average amino acid identities and 16S rRNA and photosynthetic gene similarities of photoheterotrophic Gemmatimonadetes.
We calculated average amino acid identities (AAI) between all the freshwater MAGs and the three genomes of cultured reference strains (Gemmatimonas phototrophica, Gemmatimonas aurantiaca, and Gemmatirosa kalamazoonesis) (Fig. S4). All MAGs of the phototrophic group 1 represent the same species, with AAI values of 99 and 100%, that was recovered in both Římov Reservoir and Jiřická pond, multiple times through different years and seasons. When phototrophic group 1 was compared with phototrophic groups 2 and 3, AAI values were below 65%, suggesting that these groups represent different genera. Similarly, phototrophic group 1 showed AAI values below 65% (specifically 55 and 56%) compared with cultured representatives. In phototrophic group 2, the three MAGs from Lake Zurich represent the same species (AAI, 95 to 100%) recovered in different years, whereas other MAGs from Římov Reservoir in this group seem to belong to the same genus but are all different species (AAI, 77 to 82%). Phototrophic group 3 consists of two MAGs that represent the same species (AAI, 96 and 100%). Both phototrophic groups 2 and 3 (AAI, 66 to 68%) belong to the same genus as the cultured representatives G. phototrophica and G. aurantiaca (AAI 66%) but are different from Gemmatirosa kalamazoonensis (AAI, 56%).
From the phototrophic MAGs (phototrophic group 1), one MAG from the hypolimnion of Římov Reservoir (RH-18aug17-102) contained a 16S rRNA gene, which showed 92.8% identity with G. phototrophica and 91.5% and 89.6% identity with G. aurantiaca and Gemmatirosa kalamazoonensis, respectively (Fig. S1), and one MAG from Jiřická pond (Jr-7aug17-35) showed 92.1% 16S rRNA gene sequence identity with G. phototrophica.
To further analyze the differences among the identified phototrophic groups, we compared the pufM and acsF gene sequence identities between them and type species G. phototrophica. Both of these genes are markers for anoxygenic photoheterotrophic bacteria (22, 40). For the pufM gene (encoding the M subunit of the bacterial photosynthetic reaction center), phototrophic group 2 showed only 80 to 85% identity with G. phototrophica. Much lower identities were found for hypolimnion groups 3 and 1 (77 to 80% and 72%, respectively). The acsF gene (aerobic oxidative cyclase gene) gave similar results with only 71% identity between phototrophic group 1 and G. phototrophica. MAGs from phototrophic groups 2 and 3 had 79 to 89% and 78% identity of the acsF gene of G. phototrophica, respectively.
Relative abundance of MAGs of phototrophic and nonphototrophic Gemmatimonadota.
In order to compare the relative abundance of phototrophic and nonphototrophic Gemmatimonadota, we used 28 metagenomes from Římov Reservoir from which 27 MAGs were recovered for fragment recruitment (Fig. 4). Nonphotosynthetic MAGs showed the highest contribution in the hypolimnion, especially in summer (15 August 2016); however, their abundance was not constant and changed over time. Similarly, photosynthetic group 1 was also present mostly in the hypolimnion, and its relative abundance varied during the season. The only occurrence of this group in the epilimnion was in late autumn (9 November 2016), at times of deep mixing of the reservoir (41). In contrast, photosynthetic groups 2 and 3 were present mostly in the epilimnion but remained at very low relative abundances in all seasons and at all depths.
FIG 4
CARD-FISH analyses.
In order to visualize members of the class Gemmatimonadetes and access more information on their distribution and potential associations within freshwater environments, we designed the CARD-FISH probe Gemma_801 and applied it to a set of samples obtained from Římov Reservoir, comprising eight longitudinal transects collected during summer 2015. The hybridized cells were also counted; however, since the probe in silico matches only 35% of all Gemmatimonadetes, the presented numbers, while corresponding with 16S rRNA gene abundance from metagenomes, reflect only the detected, and not total Gemmatimonadetes, implying that the observed numbers can underestimate the absolute abundance of Gemmatimonadetes in the environments studied. The lowest relative (mean = 0.09%, minimum [min] = 0.00, maximum [max] = 0.19%) and absolute (mean = 3.25 × 103 cells ml−1, min = 0.00, max = 7.9 × 103 cells ml−1) abundances were observed at the river station of the reservoir (Fig. S2). However, at stations 2 and 3 (stations following the “river station” in the longitudinal transect), the contribution of hybridized planktonic cells had already reached up to 1.0% (4.3 × 104 cells ml−1) during a bloom of Fragilaria sp. at the end of June. Besides free-living Gemmatimonadetes, we observed hybridized cells that seemed to be attached to diatoms (Fig. 5a). On some Fragilaria sp. colonies, hybridized Gemmatimonadetes contributed up to 22% of all bacterial cells detected on the diatom surface. In addition, Gemmatimonadetes seemed to be associated with cyanobacteria, as higher densities were detected with agglomerations of Microcystis sp. colonies (Fig. 5b and Fig. S5a). However, the highest numbers of hybridized cells were observed in the hypolimnion (≥10 m) of Římov Reservoir (up to 4.43% and 2.75 × 104 cells ml−1, respectively; Fig. 5c, Fig. 6, and Fig. S5b). These cells displayed different shapes and were smaller than those detected in the epilimnion.
FIG 5
FIG 6
DISCUSSION
In the presented work, we clearly demonstrated that Gemmatimonadota were permanently present in all of the studied lakes showing the ubiquitous nature of this phylum in contrasting freshwater lakes ranging from ultraoligotrophic to mesoeutrophic. The freshwater Gemmatimonadota community followed seasonal patterns with water temperature as the main driving variable, especially in the epilimnion. This observation further supports the idea that the studied Gemmatimonadota are truly limnic, since abundances of passively transferred microorganisms correlate with water mass movements rather than with temperature (42). The stratification of the lake also seemed to have a significant effect on the Gemmatimonadota community, as clusters inhabiting the epilimnion differed from those present in the hypolimnion, suggesting that they can be metabolically diverse and be specialized in different ecological roles. While Gemmatimonadota were relatively stable in the hypolimnion, their numbers in the epilimnion varied with higher numbers in late summer and autumn and lower numbers in spring and early summer. The stratification effect was previously studied in Grand Lake (OK, USA) where the Gemmatimonadota community was present in late summer in the free-living fraction within the thermocline and hypolimnion. The highest abundance in the hypolimnion at this time seemed to be associated with the sedimentation of organic matter, turbidity, and a lack of oxygen that developed in the thermocline and hypolimnion (43). The Gemmatimonadota community in Grand Lake was mostly composed of the genus Gemmatimonas, which is suggested to participate in the degradation of organic matter after an algal bloom lysis (44). In contrast, we observed that the genus Gemmatimonas was present in both the epilimnion and hypolimnion, but it appeared with higher abundances in the epilimnion, while the hypolimnion community was dominated by other clusters, including phototrophic group 1. However, we could also correlate the highest abundance of the genus Gemmatimonas in the epilimnion (15-Aug-16) with the highest abundance of the cyanobacterial community in the same metagenome sample (41). The prokaryotic community of metagenomes from Římov Reservoir was analyzed previously (41) showing Actinobacteria as persistently abundant in Římov Reservoir through all seasons and in both the epilimnion and hypolimnion. Other more abundant groups in the epilimnion and the hypolimnion were Alphaproteobacteria, Bacteroidetes, and Burkholderiales (previously Betaproteobacteriales). Instead, while Cyanobacteria were abundant in the epilimnion, they were recovered in smaller numbers, which the authors attribute to the method of sampling where most of the filamentous Cyanobacteria are removed.
The clear difference between samples from the epilimnion and hypolimnion was also observed using epifluorescence microscopy. The highest number of small-sized hybridized cells was detected in the hypolimnion of Římov Reservoir. In contrast, the samples from the epilimnion contained many Gemmatimonadota cells attached or associated with photosynthetic organisms: diatoms (Fragilaria sp.) or cyanobacteria (Microcystis sp.) (Fig. 5a and b and Fig. 6). Since both phototrophic and heterotrophic Gemmatimonadota require an organic source of carbon, they may benefit from the input of organic carbon from algae and cyanobacteria, providing in exchange inorganic nutrients acquired through mineralizing organic substances (45). Additionally, cells from the epilimnion, where light is available, seemed to have a larger size. Some previous studies showed that aerobic anoxygenic photoheterotrophic bacteria can often increase carbon assimilation in the presence of light, which allows them to have larger cells (46, 47). Subsequently, the distribution of Gemmatimonadota in the epilimnion could be dependent upon the distribution and occurrence of diatoms like Fragilaria sp. and cyanobacteria like Microcystis sp., as their blooms can influence and alter bacterioplankton communities (45, 48). Likewise, this dependence is a plausible explanation for the reason why photoheterotrophic members of this phylum are proving to be difficult to culture.
The presented 45 metagenome-assembled genomes of Gemmatimonadota in this study represent the largest collection of freshwater metagenome-assembled genomes (MAGs) of this phylum so far available. The obtained MAGs further confirmed the limnic nature of Gemmatimonadota. With recovery of several MAGs that represent the same species based on AAI (with 99 or 100% similarity), we show that Gemmatimonadota MAGs are reassembled from metagenomes and recovered periodically from different years as well as different seasons. This confirms the strong resilience of their microdiversity in freshwater and cannot be taken as a random occurrence. Furthermore, 39 of the obtained MAGs are different from soil species (Fig. 1; also see Fig. S1 and S4 in the supplemental material) and form distinct phylogenetic groups (with AAI between 45 and 65%) with both photoheterotrophic and heterotrophic representatives (38). Six MAGs, gained from the hypolimnion of deep lakes, three from Lake Constance (CH-Jul18-bin44, CH-Jul18-bin76, and CH-Jul18-bin112), two from Lake Zurich (ZH-3nov15-207 and ZH-3nov15-212), and one from Lake Thun (TH-Jun18-bin75), (Fig. 1 and Fig. S1) are more closely related to genomes from soil and sediments. In the 16S rRNA phylogeny (Fig. S1), two previously mentioned MAGs (CH-Jul18-bin112 and ZH-3nov15-212) clustered within the BD2-11 terrestrial group based on SILVA SSU v138 database taxonomy (12). This is consistent with 16S rRNA gene abundance in Swiss lakes where we could episodically observe the occurrence of 16S rRNA sequences related with terrestrial groups, such as Longimicrobia, BD2-11, and S0134 that has, as yet, been connected only with soil environments (10). Environmental 16S rRNA gene sequences from freshwater have until now been associated only with the class Gemmatimonadetes (10–12), and all other groups were formed with soil and sediment representatives. While the six MAGs could represent new freshwater members of the soil-connected groups, due to the close phylogenomic similarity with soil representatives and not with other freshwater MAGs, it is more probable that they represent genomes recovered due to soil runoff. Nevertheless, the MAGs present in these different phylogenetic groups were assembled from metagenomes gained from different sampling times which shows Gemmatimonadota were recovered repeatedly from freshwater environments. All this evidence shows that at least 39 of the identified MAGs represent truly limnic and planktonic species that do not come from soils. Furthermore, with the notable genomic diversity of limnic Gemmatimonadota, we demonstrate the ecological relevance of this group, as different members are clearly able to persist in the water column, occupying different ecological niches as they occur both in the hypolimnion and in the epilimnion. Moreover, the distribution of Gemmatimonadota in contrasting freshwater lakes showed they are adapted to different types of aquatic environments. The highest diversity in terms of different genus level groups or species of Gemmatimonadota, especially photoheterotrophic representatives, was observed in Římov Reservoir. Despite this, we cannot associate the higher diversity to mesoeutrophic lakes, as the data set obtained from Římov Reservoir was substantially larger, allowing for an increased chance of recovering higher diversity. A higher trophic status of any lake is connected with higher phytoplankton productivity; therefore, lakes and reservoirs often show variations of microbial communities connected with phytoplankton productivity (49, 50). Specifically, the connection of bacterial communities with changes in phytoplankton has already been recorded in Římov Reservoir (51). Furthermore, anoxygenic phototrophic bacteria are often found in close association with algae (45, 52, 53), and since they seem to follow seasonal phytoplankton blooms in freshwater lakes (45, 48), it is suggested that they represent an important functional group in freshwater environments (54).
Phototrophic gene, phylogenomic, and AAI analyses have shown that phototrophy in the Gemmatimonadota spans multiple genera. The identified phototrophic Gemmatimonadota represent three different groups but share the same set of phototrophic genes with G. phototrophica. All identified PGCs share a very similar gene inventory (see Table S4 in the supplemental material) and organization (Fig. 3). It seems that the convergent orientation (→ ←) of superoperons bchFNBHLM and crtFbchCXYZ-puf is conserved among all the phototrophic Gemmatimonadota, in contrast to phototrophic Proteobacteria, where orientation of these superoperons may be divergent, convergent, or colinear (55). Moreover, the split of the PGC with inserted genes in the type strain G. phototrophica AP64 (14) is also present in several MAGs from the epilimnion. Previously, the PGC of G. phototrophica was compared with two PGCs reconstructed from the Odense wastewater metagenome (OdenseWW) and the Aalborg wastewater metagenome 2 (AalborgWW-2) which did not contain the insert of several hypothetical genes between two operons. The explanation proposed for the difference in having a split PGC or not was that it could represent different evolutionary history of phototrophic Gemmatimonadota originating from different environments (21). Apart from the split PGC present in some of the MAGs, we observed that members of phototrophic group 1 have coenzyme F420-reducing hydrogenase (frhB gene) instead of bacteriochlorophyll synthase 4.5-kDa chain (bch2), as part of the bchP2G operon. Coenzyme F420-reducing hydrogenase enzyme seems to have an important role in energy conservation and methanogenesis from CO2 (56).
In support of the true photoheterotrophic nature of Gemmatimonadota, a previous study conducted in Římov Reservoir, found active expression of their pufM genes (a common molecular marker gene for aerobic anoxygenic phototrophs) (27). Expression of the photosynthetic apparatus of Gemmatimonadota showed that they are an active part of bacterial community and do not just passively contain the phototrophic genes (27).
Recently, several Gemmatimonadota MAGs that originate from sediments of a soda lake were reported to contain both phototrophic genes and genes related to the large subunit of ribulose 1,5-bisphosphate carboxylase/oxygenase enzyme (57), suggesting that these soda lake MAGs represent the first photoautotrophic Gemmatimonadota (58). In contrast, some of our freshwater Gemmatimonadota contain phototrophic genes as well as type IV RuBisCO (Fig. S3), which is considered only a homologue of RuBisCO, since it does not have any carboxylation activity (59, 60). Type IV RuBisCO genes are present in many microorganisms, including both phototrophic and heterotrophic bacteria and Archaea and are thought to participate in some other metabolic pathways different from the Calvin-Benson cycle (61, 62). Therefore, these freshwater Gemmatimonadota MAGs are not photoautotrophs, rather have a photoheterotrophic metabolism, typical for aerobic anoxygenic photoheterotrophic bacteria. These bacteria do not fix inorganic carbon and need to rely on organic carbon produced by other organisms, so the ability to harvest light is used to supply energy for their mostly organoheterotrophic metabolism (40, 63, 64).
In conclusion, with MAGs from these contrasting freshwater lakes, we not only reveal the existence of several new phototrophic species that differ phylogenetically from the already cultured and characterized G. phototrophica but also show the considerable diversity of both photoheterotrophic and heterotrophic Gemmatimonadota in freshwater.
MATERIALS AND METHODS
Sampling for metagenomics analysis.
Samples from five European freshwater lakes representing a large range of size, depth, and/or trophic status (Table 1) were used to obtain genomic information from Gemmatimonadota. Samples were taken from the surface mixed-sun exposed layer known as the epilimnion and the deeper, colder layer where typically there is reduced turbulence and a smaller amount of light is present. This deeper layer is called the hypolimnion. Římov Reservoir is a mesoeutrophic, canyon-shaped dimictic water body that was built during 1970s by damming a 13.5-km-long section of the River Malše (65). The sampling was performed between June 2015 and August 2017, above the deepest point of the reservoir by using a Friedinger sampler. A volume of 20 liters of water was collected from both the epilimnion (0.5 m; n = 10) and hypolimnion (30 m; n = 8) and subjected to sequential peristaltic filtration through a series of 20-, 5-, and 0.2-μm-pore-size polycarbonate membrane filters (142 mm diameter) (Sterlitech Corporation, USA). Characteristics of the water column, depth, temperature, oxygen (GRYF XBQ4; Havlíčkův Brod, Czechia) and chlorophyll a (FluoroProbe TS-16-12; bbe Moldaenke, Kiel, Germany) were also measured. The sample collection and filtration steps were identical for the rest of the lakes unless otherwise stated. Jiřická pond is a dystrophic humic water body from which five epilimnion (0.5-m depth) water samples were collected between May 2016 and August 2017. Lake Zurich is an oligomesotrophic, perialpine monomictic water body, from which nine water samples were collected in a period between 2010 and 2018 from the epilimnion (5-m depth; n = 5) and hypolimnion (80/120-m depth; n = 4) of the lake and processed as described above. Lake Thun is an ultraoligotrophic, alpine water body. Two water samples were collected in June 2018 from 5-m and 180-m depth. Lake Constance is a large oligomesotrophic, perialpine lake. Four samples, which were collected in July and October 2018 from the epilimnion (5 m) and hypolimnion (200 m) were used for this study.
DNA extraction, sequencing, and assembly.
DNA was extracted from the 0.22-μm filters (0.2- to 5-μm fraction) using the ZR Soil Microbe DNA MiniPrep kit (Zymo Research, Irvine, CA, USA) in accordance with the manufacturer’s instructions. The total quantity of DNA was estimated using the Qubit dsDNA BR assay kit (Life Technologies, Foster City, CA, USA) on a Qubit 2.0 fluorometer (Life Technologies). DNA integrity was assessed by agarose gel (2%) electrophoresis and SYBR green I staining. Shotgun sequencing was performed using the Novaseq 6000 sequencing platform (2 × 150 bp) (Novogene, Hong Kong, China). Raw Illumina metagenomic reads were quality filtered in order to remove low-quality bases/reads and adapter sequences using bbmap package (66, 67). Briefly, the paired-end (PE) reads were interleaved by reformat.sh and quality trimmed by bbduk.sh (qtri = rltrimq = 18) (68). Subsequently, bbduk.sh (68) was used for adapter trimming and identification/removal of possible PhiX and p-Fosil2 contamination (k = 21 ref = vector file ordered cardinality). Additional checks (i.e., de novo adapter identification with bbmerge.sh [67]) were performed in order to ensure that the data sets met the quality threshold necessary for assembly. The obtained quality-filtered data sets were then assembled independently with MEGAHIT (v1.1.5) (69) using the k-mer sizes: 39, 49, 69, 89, 109, 129, 149, and default parameters.
16S rRNA abundance-based taxonomic classification.
The obtained quality-filtered data sets were converted to FASTA format and randomly subsampled to 20 million reads by using reformat.sh (68). These subsets (containing 20 million sequences each) were queried against the SILVA SSU database, release 132 (70), in order to identify RNA-like sequences by using MMSeqs2 (71) and an E-value cutoff of 1e−3. The bona fide 16S rRNA gene sequences (as identified by SSU-ALIGN [72]) were further compared by blastn, in nucleotide space (using as cutoff the E value 1e−5), against the SILVA SSU database amended with 16S rRNA genes recovered from Gemmatimonadota MAGs (see below), and classified if the sequence identity was ≥80% and the alignment length was ≥90 bp (sequences failing these thresholds were not used for downstream analyses). The taxonomic affiliation of each identified 16S rRNA read was inferred based on its best blastn hit. The relative abundances of Gemmatimonadota taxonomic categories were calculated as a percentage of total 16S rRNA reads.
The statistical relationships between environmental data (oxygen, temperature, and chlorophyll a) (41) and Gemmatimonadota abundance in Římov Reservoir was analyzed by distance-based linear models and nonmetric multidimensional scaling (nMDS) in the PERMANOVA+ add-on package of the PRIMER7 software (Primer Ltd., Lutton, UK). Abundance data were square root transformed, and analysis was done using a stepwise selection procedure. The best model was selected based on statistical significance (9,999 permutations), and the value of the Akaike’s information criterion (AICc) (73, 74). The same analysis was also done separately for the epilimnion and the hypolimnion.
Recovery of bacterial genomes.
Quality-filtered metagenomics data sets were mapped using bbwrap.sh (75) (kfilter = 31 subfilter = 15 maxindel = 80) against the assembled contigs (longer than 3 kb) in a lake-dependent fashion. The resulting BAM files were used to generate contig abundance files with jgi_summarize_bam_contig_depths (--percentIdentity 97) (76). The contigs and their abundance files were used for binning with MetaBAT2 (default settings) (76). Bin completeness, contamination, and strain heterogeneity were estimated using CheckM (with default parameters) (77). Bins with estimated completeness above 40% and contamination below 5% were denominated as metagenome-assembled genomes (MAGs). MAGs were taxonomically classified with GTDB-Tk (2) using default settings.
Phylogenomics.
MAGs belonging to Gemmatimonadota (n = 45), together with reference genomes (n = 226) recovered from public repositories (see Table S1 in the supplemental material) were annotated using the TIGRFAMs database (78). A total of 121 conserved marker proteins (Table S2) were extracted from the annotated Gemmatimonadota genomes. MAGs that had more than 40% markers present, together with reference genomes were used for phylogenetic reconstruction. Briefly, homologous proteins were independently aligned with PRANK (default settings) (79), trimmed with BMGE (-t AA -g 0.5 -b 3 -m BLOSUM30) (80), and concatenated. A maximum-likelihood phylogeny was constructed using IQ-TREE (81) with the LG+F+R10 substitution model (chosen as the best-fitting model by ModelFinder [82]) and 1000 ultrafast bootstrap replicates. Genomes appertaining to Fibrobacterota were used as an outgroup to root the tree.
The average amino acid identity (AAI) within coherent phylogenomic groups was determined by performing whole-genome pairwise coding DNA sequence (CDS) comparison, using BLAST, as previously described (83). Taxonomic categories for the MAGs were defined using the suggested standards (38).
The photosynthetic gene clusters within obtained phylogenomic groups were analyzed in Geneious Prime 2019.2.3. For each group, MAGs with the most complete photosynthetic gene cluster were chosen as representatives. The alignment and identity matrix for nucleotide pufM and acsF gene sequences from photoheterotrophic MAGs and G. photorophica was done with ClustalW 2.0.10 (84).
Phylogenetics.
The 16S rRNA sequences present in the recovered MAGs were identified by SSU-ALIGN (72). The ones with a length longer than 200 nucleotides (nt) were merged with a data set comprising Gemmatimonadota sequences recovered from SILVA SSU v138 database (reference NR 99; length, 1200 bp) (70). The sequences were aligned with PASTA v1.8.3 (85) and used to construct a maximum-likelihood phylogeny with IQ-TREE v1.6.10 (-m GTR+F+R10; chosen as the best fitting model by ModelFinder) (81, 82). Several sequences appertaining to Cyanobacteria and Fibrobacterota were used as outgroup to root the tree.
Eighteen proteins belonging to the large subunit of the ribulose 1,5-bisphosphate carboxylase enzyme (RuBisCO) were identified in the assembled MAGs (n = 106). These proteins, together with a data set comprised of 146 RuBisCO (types I to III) and RuBisCO-like (type IV) proteins (86) were treated with PREQUAL v1.02 (87) prior to alignment with PASTA v1.8.3 (85). The obtained alignment (854 aligned positions) was used to construct a maximum-likelihood phylogeny with IQ-TREE v.1.6.10 and the LG+F+R6 substitution model (chosen as the best-fitting model by ModelFinder) (81, 82).
Fragment recruitment.
The obtained MAGs and the metagenomic data sets were used to compute genome coverage per gigabase using RazerS 3 (using cutoffs of >95% identity and alignment lengths of ≥50 bp) (88). All rRNA sequences (5S, 16S, and 23S) present in the MAGs were identified using rrna_hmm (89) and were masked prior to comparisons with quality-filtered metagenomic sequences. The quality-filtered data sets were used to compute abundance profiles for the Gemmatimonadota MAGs. Raw data showing coverage per gigabase is shown in Table S3, and a heatmap (Fig. 4) was created using http://heatmapper.ca.
Design of oligonucleotide probes.
We designed a new oligonucleotide probe that targets a part of the class Gemmatimonadetes (Fig. S1). Originally, the probe was designed as a Gemmatimonadetes-specific broad-range (degenerate) PCR primer. Gemmatimonadetes and non-Gemmatimonadetes 16S rRNA gene sequences were retrieved from SSURef SILVA database (release 132 [70]), and aligned with the MUSCLE60 algorithm in MEGA7 software (90). The primers were then designed manually to target conserved regions specific for Gemmatimonadetes. The specificity of the primers was first tested in silico with the SILVA database (70) and then with PCR using DNA from Gemmatimonas phototrophica which was used as a positive control. Optimized PCR conditions were as follows: initial denaturation at 98°C for 3 min; 26 cycles with 1 cycle consisting of 98°C for 10 s, 60°C for 20 s, and 72°C for 20 s; and final elongation for 3 min. Primers were additionally tested with several other bacterial strains, which served as negative controls and showed no amplification. Finally, the primers were used on an environmental sample where their specificity was confirmed with Illumina amplicon sequencing. Briefly, three different primer sets were applied to an environmental sample collected at station DAM of Římov Reservoir. After Illumina sequencing, read quality was evaluated using FastQC v0.11.7 (Babraham Bioinformatics, Cambridge, UK). Primer sequences were trimmed using cutadapt v1.16 (91) and subsequently analyzed in the R/Bioconductor environment using the dada2 v1.6 package (37). Taxonomic assignment was performed using the SILVA 132 database (70). On the basis of these results, we opted to use the reverse primer (5′ TCG CTC CCC CAR RSA CCT AGT 3′) as a CARD-FISH-probe Gemma_801. As the probe-binding site was located within a hairpin loop and the accessibility of the binding site was low (92), we designed two 18-bp-long helpers to open the loop and facilitate hybridization (93): Gemma_801 H1 (5′-GCG CCG GCA YYC GAG GGG-3′) and Gemma_801 H2 (5′-GGG GDA CTT AAT GCG TTA-3′). The specificity of the probe was tested in silico using the ARB Probe_Match function and the SILVA online ProbeCheck tool against the ENA database (EMBL-EBI). The probe matches only six untargeted sequences and six more if one weighted mismatch is allowed (<0.0021% of all bacterial sequences), and all of them originate from soil or the rhizosphere. The coverage of the probe for class Gemmatimonadetes is 35%, so the usage of this probe was primarily justified with the intent to visualize the Gemmatimonadetes cells in the natural environment, and not to use it for absolute quantification. Hybridization conditions were optimized at 35°C and 46°C by a stepwise increase of formamide concentrations in the hybridization buffer (20% to 70% by 5%) using pure cultures of G. phototrophica AP64 and photoheterotrophic strain TET16 (36) as positive controls, and Limnohabitans planktonicus (Gammaproteobacteria/Betaproteobacteriales) and Sphingomonas sp. strain AAP5 (Alphaproteobacteria) as negative controls. The final protocol is described below.
Sampling for catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) analysis.
We applied the newly designed probe on a sample set collected between 14 May and 24 August 2015 at Římov Reservoir. Six permanent stations (river, stations 2, 3, 4, and 7, and dam) along the longitudinal transect of the reservoir (94) (Fig. S2) were sampled with a Friedinger sampler at 3-week intervals. Samples were taken from 0.5-m depth at all stations and at additional depths at lacustrine stations: 5 m and 10 m at stations 4 and 7; and 5 m, 10 m, 20 m, 30 m, and 40 m at the dam site. Water samples were fixed on-site with formaldehyde (2% final concentration [vol/vol]) and transported to the laboratory within 2 h. For the enumeration of bacterial densities,1 to 2 ml was stained with 4′,6′-diamidino-2-phenylindole (DAPI) and filtered onto black 0.2-μm-pore-size polycarbonate membranes (25 mm diameter; SPI Supplies, USA), and bacterial abundance was determined via epifluorescence microscopy (95).
CARD-FISH analysis.
Fixed formaldehyde water samples containing 1 × 106 to 2 × 106 bacteria were filtered onto polycarbonate membranes with a 0.2-μm pore size (47-mm diameter; Millipore, USA), and filters were stored at −20°C. The catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH) analysis was conducted as in the previously described protocol (96) with slight modification in digestion procedure, optimized for samples from Římov Reservoir. In brief, the microorganisms were immobilized on the membranes with low-melting-point agarose and permeabilized with lysozyme (10 μg ml−1, 1 h) and achromopeptidase (60 U ml−1, 20 to 25 min). Digestion was followed by neutralization of endogenous peroxidases and hybridization with the horseradish peroxidase-labeled probe Gemma_801 (biomers.net GmbH) and helpers in a hybridization buffer with 35% formamide concentration (vol/vol) at 35°C for 3 h. After the subsequent washing steps, amplification of the hybridization signal was performed with fluorescein-labeled tyramides (Invitrogen, Carlsbad, CA, USA) at 37°C for 30 min. Washed and dried filters were counterstained with DAPI (1 μg ml−1) and analyzed with epifluorescence microscopy (Olympus BX-53F) using UNWU, U-WB, and U-WG optical filter sets. Proportions of CARD-FISH stained bacteria were determined by inspecting more than 1000 DAPI-stained cells per sample.
Data availability.
Sequence data for all metagenomes generated in this work are archived at EBI European Nucleotide Archive and can be accessed under the BioProject accession number PRJEB35770. All metagenome-assembled genomes are also available at figshare (https://doi.org/10.6084/m9.figshare.12662132.v2).
ACKNOWLEDGMENTS
This research was supported by the PhotoGemm+ project (grant 19-28778X) from the Czech Science Foundation. R.G. was supported by the research grant 20-12496X (Grant Agency of the Czech Republic). A.-Ş.A. was supported by the research grants 17-04828S (Grant Agency of the Czech Republic) and MSM200961801 (Academy of Sciences of the Czech Republic). T.S. was supported by the research grant 20-23718Y (Grant Agency of the Czech Republic). M.M.S. was supported by the research grant 19-23469S (Grant Agency of the Czech Republic).
We are thankful to Yonghui Zeng and Thanassis Zervas (Aarhus University) for help in initial stages of this study. Petr Znachor and Pavel Rychtecký are acknowledged for providing samples from Římov Reservoir, and Petr Porcal for providing samples from Jiřická pond. We are also thankful to Thomas Posch and Eugen Loher (University of Zurich) for help with sampling of Lake Zurich, Laboratory for Water and Soil Protection of the Canton of Bern (GBL), Switzerland, for help with sampling of Lake Thun and the crew of the research vessel “Kormoran” (LUBW-ISF Langenargen) for help with sampling of Lake Constance. We are thankful to Alastair T. Gardiner for language corrections.
Supplemental Material
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File (msystems.01241-20-st001.xlsx)
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File (msystems.01241-20-st004.xlsx)
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mSystems
Volume 6 • Number 2 • 27 April 2021
eLocator: e01241-20
Editor: Steven J. Hallam, University of British Columbia
PubMed: 33727400
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© 2021 Mujakić et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.
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Received: 8 January 2021
Accepted: 21 February 2021
Published online: 16 March 2021
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Steven J. Hallam
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University of British Columbia
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