3.2Clones from the DNA (16S rRNA gene) and RNA (16S rRNA) library and their distribution in different bacterial phyla
Most DNA and RNA clones (72.5%) fell into the major phyla α- and γ-Proteobacteria. The remaining 55 clones (27.5%) were related to the Δ-Proteobacteria, green non-sulfur Bacteria, Cyanobacteria, plastids, Bacteroidetes, Actinobacteria-Firmicutes, Chlorobium-Fibrobacter and grouped together as shown in Table 1. DNA clones alone indicated that 52% were affiliated to α-Proteobacteria and 22.44% to the γ-Proteobacteria. The remaining DNA clones (25.51%) were distributed over distinct bacterial phyla, where only 1–7 clones were found per group (Table 2). For the RNA library, 28% of the clones were affiliated to α-Proteobacteria, but 44% to the γ-Proteobacteria. The remaining RNA clones (28%) were distributed over the remaining phyla with 1–5 clones per group, except for the clones affiliated to the Actinobacteria-Firmicutes contributing 11% to the RNA clones (Table 2). DNA clones in the α-Proteobacteria showed that 60% were >97% similar to the SAR11 clade, and 14% of these DNA clones clustered with SAR11 (SAR11 clustered, Fig. 1(a)). For the RNA clones, 36% fell into the SAR11 clade, and 14% clustered with SAR11. However, only 2 DNA clones and 1 RNA clone fell into the SAR116 clade, and the remaining clones grouped as shown in Table 1. Since 31% of our DNA clones clustered within the SAR11 clade, our results agree reasonably well with the ∼26% abundance of SAR11 clones in DNA libraries from seawater and therefore potentially relate to oligotrophic marine Bacteria[38,39]. Since our sample originated from a depth of 200 m, only 10% of the clones in the RNA library related to SAR11 and somehow agreed with decreased FISH counts towards depth for this clade. On the other hand, 39% of the RNA clones in the γ-Proteobacteria fell into the SAR86 clade (Fig. 1(b)). For the DNA clones, 23% were related to the SAR86 clade and the remaining RNA clones grouped as shown in Table 1. These results indicate a well mixed water column since SAR86 has been previously detected only in the surface water column, where divergent proteorhodopsins light-driven proton pumps have been recently detected in this group. Furthermore, clones affiliated to Actinobacteria-Firmicutes (ACT_6) and Chlorobium-Fibrobacter (CHL_2) might also contribute to a certain extent to the bacterial activity in the community, based on their occurrence only in the RNA library. A previous study confirmed the occurrence of clones affiliated to Chlorobium-Fibrobacter at mesopelagic depths but rather on the DNA level, while we detected these clones (e.g., Table 1 CHL_2) primarily on the RNA level.
Table 1. Phylogenetic affiliation of the clones in the DNA (16S rRNA gene) and RNA (16S rRNA) libraries
|Phylogenetic group||Representative clone||n DNA||n RNA||Closest GenBank relative||BLAST scores of group|
|α-Proteobacteria|| || || || |
|ALP_9||AEGEAN_208||0||1||Pelagibacter ubique (AF510192)||98|
|ALP_14||AEGEAN_207||0||2||Rhodobium orientis MB312 (D30792)||89|
|ALP_17||AEGEAN_238||0||3||Roseobacter sp. ISM (AF098495)||97|
|ALP_22||AEGEAN_205||0||6||env.Olavius loise endosymb. 2 (AF104473)||89|
|γ-Proteobacteria|| || || || |
|Δ-Proteobacteria|| || || || |
|Green non-sulfur bacteria|| || || || |
|GNS_1||AEGEAN_116||1||0||env.sponge sy PAWS52f (AF186417)||90|
|Cyanobacteria|| || || || |
|CYA_4||AEGEAN_172||1||0||Prochlorococcus sp. MIT9313 (AF053399)||99|
|Plastids|| || || || |
|PLA_1||AEGEAN_118||1||0||Mantoniella squamata (X90641)||95|
|PLA_4||AEGEAN_115||3||3||Mantoniella squamata (X90641)||96|
|Bacteroidetes|| || || || |
|Actinobacteria-Firmicutes|| || || || |
|Chlorobium-Fibrobacter|| || || || |
Table 2. Distribution of the clones (n= number of clones) from the DNA (16S rRNA gene) and RNA (16S rRNA) among the main phylogenetic groups found in this study
|Phylogenetic group|| ||Clones only in DNA or RNA library n||Clones in DNA and RNA libraries n||Unique clones n||Coverage values for clones in this group %|
|Removed clones|| || || || |
The combined analysis of DNA and RNA clones from the same bacterial community leads to a characterization of phylotypes otherwise uncharacterized when the DNA or RNA clones would be analyzed alone. Table 2 indicates that ∼25% of DNA clones are characteristic only for this library, and no close relatives (>97% similarity) in the RNA library were found. Comparable values were also observed for clones from the RNA library, as ∼21% of RNA clones did not indicate close relatives in the DNA library (Table 2). For example, clones related to ALP_19, GAM_10, GNS_1, CYA_1–4 and B_1–4 were only represented in the DNA library, while clones related to ALP_22, GAM_14, DEL_2, ACT_6 and CHL_2 only in the RNA library (Table 1).
Three aspects in the distribution pattern of clones in the DNA and RNA libraries can be considered in an ecological context. First, repetitive DNA clones (e.g., ALP_19, ALP_23, ALP_24, Table 1) might be representative for Bacteria high in cellular abundance and/or with multiple operons within their cells. However, the much lower number or absence of similar clones in the RNA library could indicate that these DNA clones are from Bacteria with less ribosomes and therefore, probably representative for cells with reduced metabolic activity. Secondly, a high number of repetitive clones in the RNA library (e.g., GAM_17, Table 1) could represent active members of the complex community with more ribosomes present in their cells. Thirdly, clones from Bacteria with low cellular abundance and/or low operon numbers, which were not detected in the DNA library, might indicate members in the complex community that are not detectable on their DNA level (beyond the detection threshold of our approach), but on their RNA level (e.g., ALP_22, GAM_13, ACT_6, CHL_2). This observed mismatch between the DNA and RNA libraries suggests that these clones originate from Bacteria low in cellular abundance but with potentially high metabolic activity as indicated by their clonal presence in RNA libraries.
In our study, stringent controls in sample preparation, (RT-) PCR and sequencing were performed, however, we did not detect (RT-) PCR biases leading to sequencing artifacts, which could explain the observed mismatch between our DNA and RNA libraries. In fact, we found >97% sequence similarity between clones from both libraries (∼50% of all clones analyzed), indicating that the often hypothesized increase in sequencing errors and preferential chimera formation for RT-PCR products did not determine the outcome of our RNA library. Only two sequences were chimeras and originated from the DNA library. Instead, we found well-aligned sequences for the DNA as well as the RNA library. We are aware that our study does not address the possibility that bacterial cells have to differ in numbers of rRNA molecules as a function of size, physiology and even time of the day. Furthermore large cells are likely to have more rRNA even if growing at lower doubling times than small (more) active cells. Besides these uncertainties, our study indicates that distinct microorganisms with low BLAST scores (e.g., RNA clones ALP_22, GAM_13 and CHL_2) might contribute to activity patterns of marine microorganisms, which remained undetected when 16S rRNA genes were analyzed.
Recent studies show that microheterogeneity accounts for a large portion of the diversity (by means of phylotype richness based on 16S rRNA genes) in complex bacterial communities [42,43]. Most of the diversity resulted from ∼50% of the sequences displaying <1% nucleotide difference to each other and it has been hypothesized that ‘microdiversity' is a feature of co-existing strains. Since sequences with a similarity >97% were considered the same phylotype and therefore grouped together in our study, rRNA (gene) sequences from different operons within the same cell would probably fall within the same phylotype. Higher similarity values were used for phylotype characterization in microdiversity studies, thereby increasing the microdiversity tremendously. We applied the ‘common rule of thumb’, which classifies organisms that are more than 3% different in 16S rRNA sequences as different phylotypes. This extrapolation has been used for the majority of 16S rRNA gene clone libraries from various environments, and seems therefore for the sake of comparison a valid phylotype detection threshold [45,46]. However, different ‘ecotypes' could share sequence similarities >97% and would therefore group together within the same phylotype. Although our study does not sample a bacterial community at such a high resolution than these recent studies [42,43], our smaller clone libraries indicate important differences between DNA and RNA libraries in (I) how clones from these 2 libraries are repetitively distributed in different phyla and (II) which phylotypes might be potentially important in terms of metabolic activity and which are not. Thus, our study contributes to the open question on the ecological significance of this observed microdiversity when RNA libraries are included in phylogenetic analysis. This could reveal whether DNA or RNA microdiversity represents populations (‘ecotypes') that share similar ecological niches and adaptations.
Still, because of the multiplicity and heterogeneity of 16S rRNA genes within bacterial strains [48,49], 16S rRNA gene analysis is rather a proxy for sequence ‘diversity' than for ‘diversity' of prokaryotic cells itself. Thus, multiple operons within the bacterial cell could lead to a 2–15 times over-representation of certain clones, if we assume unbiased PCR amplification. Recent analysis of bacterial genomes with multiple rRNA operons indicated that a vast majority of interoperonic sequence differences within 76 bacterial genomes showed a <1% divergence, although the genomes under analysis tend to have more operons since they were derived from microorganisms in culture. Taking these results into consideration, there might be a 2.5 × overestimation of bacterial diversity (by means of type richness) when using cloning and sequencing approaches of 16S rRNA genes. A recent study also indicates that a highly abundant marine strain (Candidatus Pelagibacter ubique gen. nov., sp. nov.) seems to have a single rRNA operon, which has been previously found for another oligotrophic marine bacterium. Whether this is a general feature of marine microorganisms in the oligotrophic ocean remains to be determined.
3.3Unique clones in the DNA and RNA libraries and coverage of these libraries
Unique clones (clones only once in the clone library) were determined to evaluate the size of our clone libraries. Since 72.5% of the clones in DNA and RNA libraries were related to α- and γ-Proteobacteria, high overall coverage values within these groups indicate that the data presented here are representative for the complex community, based on our combined DNA/RNA approach (Table 2). For all clones in the DNA library, the coverage was 68%, whereas for all clones in the RNA library the coverage reached 89% (Table 2). Combining the DNA and RNA libraries since they were derived from the nucleic acids of the same complex community, the coverage was 78.5%. The observed lower coverage values for the DNA library (68%) can be explained by the higher number of unique DNA clones (n= 16) affiliated to the ‘other groups' cluster (Table 2). Unique clones were found more often in the DNA library (32 clones) than in the RNA library (11 clones), thereby contributing considerably to the overall complexity (by lowering the coverage values), while the RNA library seems less affected by unique clones. Unique clones probably represent an insignificant part of the community since they could originate from Bacteria with low operon numbers and slow metabolism or Bacteria low in cellular abundance.
PCR (and cloning) biases might explain the high number of unique clones in our DNA library, because of an inefficient amplification of template DNA, an uncertainty every PCR based approach is confronted with. We do not know (and we are not aware of any study that addresses this question) how many phylotypes are actually excluded from molecular analysis because specific primers are used in 16S rRNA (gene) techniques. Novel sensitive approaches [52,53] with specific FISH probes for representative clones from the DNA and RNA library could address many of the questions raised above. Also, the use of additional PCR primers with other specificity might resolve some of PCR related concerns.
Although we only analyzed a single free-living bacterial community from the oligotrophic Aegean Sea, insights into the bacterial community structure based on DNA and RNA was obtained. The majority of our clones indicated GenBank entries related to bacterioplankton clones from major ocean provinces such as the Sargasso Sea (22 clones), Atlanic Ocean (47 clones), North Sea (53 clones), Arctic Ocean (10 clones), Pacific Ocean (20 clones) as closest relatives. The remaining clones were related to marine symbionts (11 clones), deep sea microorganisms (7 clones), lake bacterioplankton (1 clone), marine mesocosms (10 clones) and 17 clones could not be clearly affiliated where the clones originated from. Although BLAST scores for our sequences were sometimes low, the dominance of related sequences from various marine provinces as closest relatives indicates that the DNA and RNA clone libraries are representative for oceanic bacterioplankton. Interestingly, RNA clones also showed low BLAST scores to sequences from GenBank, indicating a potential characterization of distinct phylotypes from the marine environment (Table 1). These results also indicate the potential of this combined DNA/RNA approach for the characterization of the bacterial community and the identification of members of the community on the RNA level. Therefore, conservative estimates can be made as abundant Bacteria, Bacteria with multiple operons per cell and Bacteria with higher ribosome numbers per cell are likely to be repetitively more abundant in clone libraries.