| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
1 Environmental Biology Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
2 Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8572, Japan
Correspondence
Makoto M. Watanabe
makoto{at}biol.tsukuba.ac.jp
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
The GenBank/EMBL/DDBJ accession numbers for the ftsZ, glnA, gltX, gyrB, pgi, recA and tpi sequences of the Microcystis aeruginosa strains examined in this study are AB324850–AB325402.
A supplementary figure showing the individual phylogenetic trees for the seven MLST loci, and supplementary tables showing strain information and the degenerate primer sequences used for isolating five of the seven MLST genes, are available with the online version of this paper.
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
). Traditionally, five dominant morphospecies, M. aeruginosa, Microcystis novacekii, Microcystis ichthyoblabe, Microcystis viridis and Microcystis wesenbergii are recognized within the water-bloom-forming Microcystis, primarily on the basis of colony morphology, including the arrangement of cells and sheath characteristics (Watanabe, 1996). Given that the colony characteristics of these morphospecies are known to be highly variable and that the variation sometimes exceeds species criteria, the species definition of the genus Microcystis has been called into question (Otsuka et al., 2000). Indeed, molecular and chemotaxonomic data clearly demonstrate that each of the five morphospecies is non-monophyletic and that they are genetically and biochemically highly similar to each other, leading to the recent synthesis of the five morphospecies into one species, M. aeruginosa (Otsuka et al., 2001).
Hepatotoxic compounds produced by Microcystis, called microcystins, have become widely recognized as a serious public health concern. Accidental drinking of water contaminated with microcystins causes severe liver damage in both humans and animals as a consequence of the inhibition of protein phosphatases 1 and 2A (PP1 and PP2A) in hepatocytes. In addition, the involvement of microcystins in tumour promotion has been suggested (reviewed by Dittmann & Wiegand, 2006). Microcystins are a family of cyclic heptapeptides that are non-ribosomally synthesized by the microcystin synthetase (mcy) complex, which is encoded by 10 genes, mcyA–mcyJ (Tillett et al., 2000). Since both toxic and non-toxic colonies coexist in nature, researchers have been focusing on developing a rapid molecular typing method to discriminate toxic strains. To date, many attempts have been made to develop a method to distinguish toxic M. aeruginosa; these include RAPD fingerprinting (Neilan, 1995), 16S rDNA (Lyra et al., 2001; Neilan et al., 1997; Tillett et al., 2001), 16S–23S rDNA internal transcribed spacer (ITS; Janse et al., 2004; Otsuka et al., 1999), a part of the phycocyanin operon cpcBA intergenic spacer (IGS; Neilan et al., 1995; Tillett et al., 2001), and mcy genes (Kurmayer et al., 2002; Nishizawa et al., 1999; Tillett et al., 2001). However, these analyses consistently demonstrated that genetic similarity and toxicity are not always consistent, even when employing microcystin genes themselves as markers (i.e. a single mcy genotype encompasses both toxic and non-toxic strains). This inconsistency could be overcome by the use of a higher-resolution typing method.
For the past few decades, the impact of recombination on natural genetic diversity has become a central interest in the field of population genetics of bacteria. Accumulated evidence suggests that population structures of bacteria vary greatly depending on the species or subspecies, ranging from strictly clonal to panmictic (Smith et al., 1993). Since multilocus markers with which we can index the degree of clonality are, however, not currently available for Microcystis, none of the genotyping studies has addressed this issue. However, molecular evolutionary studies have suggested that recombination contributes substantially to the genetic diversity of mcy genes of M. aeruginosa (Mikalsen et al., 2003; Tanabe et al., 2004), highlighting the potential importance of genetic exchange to the population genetic structure of this species. At the same time, recombination is of particular concern when one attempts to reconstruct a phylogenetic history because recombination breaks up correlations between genetic distances and strain relatedness. Therefore, a molecular tool that is less affected by genetic mixing is a prerequisite for phylogenetic analysis of recombinogenic bacteria such as M. aeruginosa. Unfortunately, almost all previous efforts to differentiate genotypes of Microcystis have used either a single gene-based approach or fingerprinting, neither of which is free from problems invoked by recombination.
In this study, we developed a multilocus sequence typing (MLST) scheme for M. aeruginosa. MLST is a DNA sequence-based genotyping approach that indexes the genetic variation of seven or more housekeeping loci, each of which is free from vigorous selection pressure, and ideally the loci are scattered around the chromosome to reflect overall genome evolution (Maiden et al., 1998). MLST has been widely and successfully used in describing the population structure of many bacterial species, particularly pathogenic bacteria (Feil & Enright, 2004). Our MLST protocol employed seven housekeeping loci, with which we characterized the genetic variation of 164 isolates of M. aeruginosa. Based on the results of MLST, we performed linkage disequilibrium analyses to infer the population genetic structure of M. aeruginosa. We also performed phylogenetic analyses, and we discuss the potential utility of MLST for characterizing toxic genotypes. To our knowledge, this is the first report of an MLST scheme for cyanobacteria.
|
METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
) at 25 °C for 1–3 weeks under a 12 : 12 h light : dark cycle with a photon density of 15 µmol m–2 s–1. Genomic DNA was extracted and purified using a FastDNA kit (Qbiogene).
MLST and mcy gene detection.
Seven housekeeping loci, ftsZ, glnA, gltX, gyrB, pgi, recA and tpi, were selected for MLST. All of these loci have been employed in MLST of other bacteria. Each locus is present as a single copy, but their physical positions on the genome are currently difficult to determine (T. Kaneko & S. Tabata, personal communication). In order to develop the MLST primers for ftsZ, glnA, gltX, pgi and recA, degenerate primers targeting segments of each candidate gene were designed and used for PCRs using the genomic DNA of M. aeruginosa NIES102 as a reference strain (degenerate primer sequences are shown in Supplementary Table S2). Amplicons of the expected sizes were cloned and sequenced, followed by the identification of the corresponding MLST genes with the aid of BLAST searching. Based on the sequences we obtained, internal primers were designed. In the case of the remaining two loci, gyrB and tpi, primers were designed using published sequences from M. aeruginosa (DDBJ accession numbers AB014988–89 and AY238889–91, respectively) as a guide. As a result of the successful PCR amplification and following direct sequencing of several strains, we validated these primers as MLST primers (Table 1). Using ExTaq DNA polymerase (Takara), each locus was PCR-amplified (in 25 µl volumes) with initial denaturation at 94 °C for 3 min, followed by 40 cycles of 94 °C for 60 s, 60–68 °C (optimal annealing temperatures for each locus are listed in Table 1) for 60 s, and 72 °C for 30 s. To detect the potential toxicity of strains, a partial segment of mcyG (549 bp in length) was amplified using the previously described primer pair GF and GR (Tanabe et al., 2004) under the same PCR conditions as for MLST, except that the annealing temperature was 60 °C. PCR products were purified using ExoSAP-IT (USB) and were sequenced in both directions using a DTCS Quick Start kit and a CEQ8000 autosequencer (Beckman Coulter). Sequence data have been submitted to the DDBJ/EMBL/GenBank databases under accession numbers AB324850–AB325402. For each locus, each different allele was assigned a different arbitrary number, and a unique combination of seven allele numbers (‘allelic profile’) unambiguously defines the sequence type (ST) of a strain. Allelic profiles were used for subsequent linkage disequilibrium analysis.
|
(n is the number of samples and pi is the relative frequency of the ith allele), nucleotide diversity (
; Nei, 1987), and a test for neutrality based on Tajima's D (equal to zero at neutral equilibrium; Tajima, 1989) were performed using DnaSP version 4.00 (Rozas et al., 2003). Intragenic recombination was investigated using RDP2 software (Martin et al., 2005) with all the methods available at the default settings. Multilocus linkage disequilibrium was assessed using the index of association (IA, Smith et al., 1993) and rD (Agapow & Burt, 2001) with the program MULTILOCUS version 1.2.2 (Agapow & Burt, 2001). rD is virtually a standardized measure of IA ranging from 0 (panmixia) to 1 (absolute linkage disequilibrium). rD is free from dependence on the number of loci analysed, as encountered with IA, and makes comparison among studies possible. The statistical significance of non-zero values of these indices was also inferred, based on the comparison of those values estimated from 1000 randomized datasets under a null hypothesis of panmixia.
Phylogenetic analysis.
The most appropriate model of DNA sequence evolution of MLST loci was selected by the hierarchical likelihood ratio test using MODELTEST version 3.7 (Posada & Crandall, 1998). Using PAUP* version 4.0b10 (Swofford, 2002), neighbour-joining (NJ) phylogenetic trees were constructed based on the maximum-likelihood (ML) distance calculated with the inferred model and parameters. NJ bootstrap (NJBP) analyses were also performed to assess the statistical confidence for nodes based on the alignments generated by 1000 resamplings of the data with the same settings used for phylogenetic reconstruction. Bayesian ML phylogenetic reconstruction was performed using MrBayes version 3.1.2 (Ronquist & Huelsenbeck, 2003). Based on the DNA evolution model chosen by MODELTEST, and using the NJ tree as a starting tree, two independent runs were performed, each with four chains for 2 000 000 generations, in which trees were sampled every 100 generations. Statistical confidence for branch support was assessed using posterior probability (PP) estimated from the 50 % majority consensus tree after discarding the burn-in phase of 500 000 generations. Shimodaira–Hasegawa (SH) tests (Shimodaira & Hasegawa, 1999) were performed to statistically assess phylogenetic incongruence between loci based on the ML parameter estimates, as described above.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
. The mean overall nucleotide sequence divergence (x100) was 2.3 %, where the maximum was 4.3 % in pgi, and the minimum was 1.3 % in recA. From 164 isolates, 79 STs were found. The number of alleles ranged from 40 for ftsZ to 57 for gltX. This allows about 550 billion different allelic profiles to be discriminated within M. aeruginosa. The average gene diversity over seven loci was H=0.951. None of the Tajima's D values for each MLST locus deviated significantly from zero (P>0.10).
|
). Multilocus linkage disequilibrium was analysed using IA and rD based on the MLST allelic profile (Table 4). Analysis of all isolates indicated IA=3.608 and rD=0.608, both of which were significantly positive values (P<0.001). When analysing allelic profiles of the 79 unique STs only, smaller values were obtained (IA=1.755, rD=0.314), but were still significantly positive (P<0.001). Subsets of local populations were also analysed individually. All of the IA values of local populations were still significantly positive (P<0.001). Notably, all indices of local populations were larger than the values obtained by the entire dataset. Among them, those for Lake Okutama and Shirakaba indicated complete linkage disequilibrium (IA=6.000, rD=1.000).
|
|
) was used for diagnosis of potential toxicity of a given strain. The results of PCR detection experiments are shown in Supplementary Table S1. All toxic strains were positive for mcyG, whereas all but five non-toxic strains representing three STs (ST48, ST51 and ST55) were negative for mcyG. Sequencing experiments confirmed that all of these PCR products represent authentic mcyG. Non-toxicity of these three STs was further confirmed by liquid chromatography electrospray ionization MS (LC ESI-MS) (T. Sano, personal communication).
Phylogenetic analysis
Phylogenetic analyses of individual MLST genes failed to resolve almost all of the phylogenetic relationships with confidence (Supplementary Fig. S1). This poor resolution is likely due to a few phylogenetic signals within the individual gene sequences. We therefore concatenated the seven MLST sequences, obtaining a much longer alignment of 2992 bp. Also, this procedure has an advantage in that it can buffer the consequences of local recombination that could affect the recovery of true phylogenetic relationships when a phylogeny based on one or a small number of genes is employed (Hanage et al., 2005). A hierarchical likelihood-ratio test using the MODELTEST program indicated that the DNA evolution of the concatenated data was best explained by the GTR+I+G model (GTR, the general time reversible DNA substitution model; I, invariable sites; G, rate heterogeneity among sites under a gamma distribution with four categories), in which the rate matrix was estimated as R(a) [A–C]=0.8742, R(b) [A–G]=3.0433, R(c) [A–T]=0.5537, R(d) [C–G]=1.8297, R(e) [C–T]=6.5145, R(f) [G–T]=1.0000, the gamma shape parameter is 
=0.4669, and the proportion of invariable sites is 0.8192. An NJ midpoint-rooted tree based on the ML distance inferred from the selected model and parameters is shown in Fig. 1. As expected, relationships between strains were much more resolved, as illustrated by several highly supported monophyletic clades in the tree. (Bayesian ML analysis identified a phylogenetic tree with a different topology; however, the main differences lie in internal branches between and within major clades, and the robustness of each major clade was also supported by Bayesian PP.) In this tree, most toxic strains fell into two lineages, groups A and B, and only two toxic strains (ST23 and ST57) were not included in one of the two groups. All strains included in group A were toxic, except for one of the 10 representatives of ST55, whereas group B included both toxic and non-toxic strains. Support for group A was weak (<50 %, both in NJBP and PP), and it could be subdivided into at least three highly supported groups (>90 %, both in NJBP and PP). Support for group B was moderate to strong (52 % NJBP; 100 % PP). ST40 was, however, more or less divergent from other strains of group B, as illustrated by the long branch leading to ST40 (Fig. 1). In fact, the position of ST40 was variably placed depending on the phylogenetic method used, in some cases even located outside group B (data not shown). The two toxic STs ST23 and ST57 were located near the base of group A. However, this placement received little support, and was indeed variable depending on the phylogenetic method used. Three strongly supported (100 % NJBP; 100 % PP) monophyletic groups that exclusively contained non-toxic strains were identified (groups C, D and E). The other non-toxic strains were distributed across the tree, but in most cases with no support for their placement.
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
) and Bacillus subtilis (H=0.44; Istock et al., 1992). Direct comparison of these two values with our estimate for M. aeruginosa may be meaningless, since these two estimates are based on multilocus enzyme electrophoresis (MLEE), where only a genotype with a mutation that causes an electromobility shift is distinguished as a distinct allele. However, our estimate of H is still higher than the reported MLST estimates for Enterococcus faecium (H=0.60; Homan et al., 2002) and Streptococcus pneumoniae (H=0.82; Enright & Spratt, 1998), as well as that for a hyperthermophilic archaeon (Halorubrum) (H=0.69; Papke et al., 2004). These comparisons highlight the extremely high genetic diversity of M. aeruginosa. Theoretically, high genetic diversity is unexpected for clonal organisms such as bacteria. This is because clonal organisms are purged of genetic diversity at all loci by recurrent selective sweeps, so-called ‘periodic selection’ (Atwood et al., 1951). Then how do we explain such a high level of genetic diversity in M. aeruginosa? One possibility is that M. aeruginosa contains several ecologically distinct populations or ‘ecotypes’. Given that ecological divergence is expected to accompany genetic divergence, it follows that if more ecotypes exist within a single species, then higher genetic diversity is maintained within it. Cohan (2002) has suggested that each ecotype falls into its own sequence-based cluster through time. In fact, a number of distinct clusters are observed in the phylogenetic tree of M. aeruginosa (Fig. 1
), suggesting that each cluster might represent a bona fide cryptic ecotype. If so, it is likely that ecological divergence contributes greatly to the high genetic diversity of M. aeruginosa. It should be noted that STs belonging to different clusters are often isolated from a single locality, even in the same water sample. This observation implies the presence of distinct microhabitats at a very fine scale. Future investigation of ecological parameters that potentially characterize each clade is essential to test this possibility.
Recombination and clonal population structure
Our results strongly suggest that recombination is an important evolutionary force for the generation and maintenance of the genetic diversity of M. aeruginosa. Many phylogenetic conflicts are evident among the individual gene phylogenies (Supplementary Fig. S1). This is further supported by the results of SH tests, which indicate statistically significant discrepancies in almost all pair-wise comparisons between single-gene phylogenies (Table 3), which is most likely explained by recombination at different loci. Although recombination appears to be substantial in M. aeruginosa, alleles at different loci were not assorted randomly. In fact, both the total and local IA and rD values indicated a significant deviation from the null model of panmixia (Table 4), suggesting a ‘clonal’ population structure for M. aeruginosa. Theoretically, a clonal population structure under a high rate of recombination can be observed when several particular STs are over-represented due to non-random and limited sampling, as in this study. However, an analysis of only single representatives of 79 STs indicates slightly lower but still significant non-zero values, excluding the possibility of an ‘epidemic’ population structure (Smith et al., 1993). To our knowledge, this is the second report of clonal population structure of cyanobacteria, following the Baltic Sea population of Nodularia revealed by an allele-specific PCR study (Barker et al., 2000). The recovery of the same ST from distantly separated locations (e.g. ST26 was isolated from Japan and China) also provides circumstantial evidence for clonality. Interestingly, all local IA and rD values are higher than those for the total, as clearly exemplified by the theoretical maximum values (IA=6, rD=1) obtained from two lakes, Lake Okutama and Lake Shirakaba (Table 4). This result suggests that geographical isolation does not influence the strong linkage disequilibrium inferred from the entire dataset. Concurrently, this implies that a sympatric population might contain a number of genetically isolated clones, which further supports the clonal population structure.
The properties of vectors may be responsible for the clonal population structure of recombigenic bacteria. At present, vectors involved in natural genetic exchange among Microcystis have yet to be identified. Basically, only three are possible: plasmids, conjugating plasmids or phages. Plasmids (Takahashi et al., 1996, Wallace et al., 2002) and cyanophages (Tucker & Pollard, 2005; Yoshida et al., 2006) have been isolated from natural populations of Microcystis, and hence are good candidates for being responsible for recombination in nature. In vitro experiments have indicated that Microcystis is competent but sometimes difficult to transform due to the extracellular secretion of nucleases that may cause breakdown of foreign DNA (Dittmann et al., 1997; Takahashi et al., 1996). This observation is in line with the clonal population structure of M. aeruginosa, whereby recombination appears to be more or less restricted. Although the effects of conjugation and transduction on genetic exchange in Microcystis have never been investigated, these two mechanisms might also play a limited role(s) in the recombination of Microcystis, thus contributing to the clonal population structure of M. aeruginosa.
Phylogenetic relationships among toxic and non-toxic M. aeruginosa
Phylogenetic analyses identified a number of well- (and less-well-) defined clades within M. aeruginosa. Notably, most toxic strains are assigned to two clades, groups A and B. Group A is a weakly supported clade that includes three well-supported subclades. In group A, microcystin toxicity appears to be stably maintained. Group B is better supported, but, in contrast with group A, the toxicity appears to be unstable. This implies that the toxin genes in group B are frequently lost and/or gained. The two toxic STs ST23 and ST57 are exceptional, and are not located within either group A or group B. The origin of toxicity of these two STs is unknown, and awaits future mcy genealogical analysis.
There are five anomalous strains that are non-toxic but have at least a part of the toxin gene mcyG. The otherwise toxic ST55 in group A includes one non-toxic strain that is also positive for mcyG. Group B also includes four strains represented by ST48 and ST51, which are also non-toxic but positive for mcyG. The presence of these inconsistent genotypes is most likely explained by the loss of function of the mcy genes due to a recent mutation caused by transposition, or a large deletion within the toxin genes or the relevant regulatory regions, as reported for the mcy genes of Planktothrix spp. (Christiansen et al., 2006). In M. aeruginosa, transpositional inactivation has also been documented in the gas vesicle genes (gvp) for buoyancy (Mlouka et al., 2004). Indeed, sequence comparisons revealed that the mcyG of non-toxic ST55 is distinct from that of any other toxic ST55, in that it contains one base substitution relative to the sequences of toxic ST55 (Y. Tanabe, unpublished data). Although we have yet to discern whether this point mutation is directly involved in the loss of microcystins, it is likely that another large mutation (e.g. insertion of IS elements) that occurred within the essential region might be responsible. Obtaining the sequences of the entire microcystin gene regions from these non-toxic strains and their transcriptional analysis are critical to address this issue. Another possible reason for non-toxicity is that the amount of microcystin production in these STs is too low to be detected by canonical HPLC and LC ESI-MS techniques. However, we consider this unlikely, since production of trace levels of microcystins has never been documented. Interestingly, non-toxic strains that possess an mcy gene (ST48 and ST51) form a monophyletic group. The stable retention of mcy genes in this non-toxic clade through phylogenetic timescales suggests the possibility that the mcy genes of these strains might function differently from other microcystin-producing genotypes. It is possible that these two STs do not produce microcystins under laboratory culture conditions and require certain physiological factors for microcystin production. Since the toxicity of our strains was assayed from cells grown in only one standard culture medium (T. Sano, personal communication), microcystins could be produced when different media are used. In any event, these groups of non-toxic strains should be characterized by molecular genetic experiments to clarify the mechanism underlying their non-toxic nature.
In contrast to the clustering of toxic strains, non-toxic strains are widely scattered in the phylogenetic tree (Fig. 1). Rantala et al. (2004) proposed the ‘microcystin-early’ hypothesis, in which the ability to produce microcystins has been vertically inherited through the diversification of toxic cyanobacterial genera and thereafter repeatedly lost. Although relationships between toxic and non-toxic groups are not statistically supported, this pattern of distribution could be explained by later acquisition of toxin genes in the toxic clade during the evolution of M. aeruginosa. Genealogical analyses of mcy are needed to test whether the gain of microcystin genes is also an important factor in the evolution of toxic Microcystis.
Utility of MLST for research on population dynamics
Due to their ecological and environmental importance, a reliable genotyping scheme is fundamental to the monitoring and control of the occurrence of water blooms of M. aeruginosa. The MLST developed here is a convenient technique with which we can unambiguously characterize the genotype of a clone. Indeed, our MLST potentially distinguishes more than 550 billion multilocus genotypes, and thus has high resolution. Although most of the strains analysed in this study are isolates from Japan, we have successfully recovered MLST genes for isolates from other Asian regions (e.g. China, Nepal and Thailand) as well as regions of other continents (e.g. Britain and Canada) using the same sets of primers. We therefore expect that our MLST protocol will be applicable to isolates worldwide. In fact, our preliminary survey of another 100 strains of diverse origins successfully recovered all of the MLST genes without exception (data not shown). Since the results of MLST are portable and therefore easily comparable to those of other researchers, our MLST would serve as a very valuable tool to investigate the global population structure of M. aeruginosa.
Our MLST survey demonstrated that toxic and non-toxic strains are distinct in their MLST profiles. This means that our MLST is valuable in that it can be used diagnostically to discriminate toxic from non-toxic strains. As noted above, there is one exception in the toxic ST55, which contains one non-toxic strain. However, such cases appear to be scarce, and are not expected to seriously influence the diagnosis with regard to toxicity in general. If one wants to determine toxicity with confidence, it may be desirable to use chemical techniques, such as HPLC, in combination with MLST.
Conclusions
In this study, we developed an MLST scheme for M. aeruginosa, demonstrated high genetic diversity, clonal population structure and substantial recombination, and identified toxic and non-toxic clades based on a collection of diverse samples. One might think that our results are no more than a partial snapshot and far from a full description of the global genetic diversity and toxicity of M. aeruginosa. Nevertheless, our MLST of M. aeruginosa has high discriminatory power, assuring a significant contribution to future detailed studies. Investigation of other important population genetic forces, such as gene flow, natural selection, etc., with more extensive and/or focused sampling, would provide more insights into the spatial and temporal population dynamics of M. aeruginosa.
|
ACKNOWLEDGEMENTS |
|---|
Edited by: K. Forchhammer
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
|---|
Atwood, K. C., Schneider, L. K. & Ryan, F. J. (1951). Periodic selection in Escherichia coli. Proc Natl Acad Sci U S A 37, 146–155.
Barker, G. L., Handley, B. A., Vacharapiyasophon, P., Stevens, J. R. & Hayes, P. K. (2000). Allele-specific PCR shows that genetic exchange occurs among genetically diverse Nodularia (cyanobacteria) filaments in the Baltic Sea. Microbiology 146, 2865–2875.
Christiansen, G., Kurmayer, R., Liu, Q. & Borner, T. (2006). Transposons inactivate biosynthesis of the nonribosomal peptide microcystin in naturally occurring Planktothrix spp. Appl Environ Microbiol 72, 117–123.
Cohan, F. M. (2002). What are bacterial species?. Annu Rev Microbiol 56, 457–487.[CrossRef][Medline]
Dittmann, E. & Wiegand, C. (2006). Cyanobacterial toxins – occurrence, biosynthesis and impact on human affairs. Mol Nutr Food Res 50, 7–17.[CrossRef][Medline]
Dittmann, E., Neilan, B. A., Erhard, M., von Dohren, H. & Borner, T. (1997). Insertional mutagenesis of a peptide synthetase gene that is responsible for hepatotoxin production in the cyanobacterium Microcystis aeruginosa PCC 7806. Mol Microbiol 26, 779–787.[CrossRef][Medline]
Enright, M. C. & Spratt, B. G. (1998). A multilocus sequence typing scheme for Streptococcus pneumoniae: identification of clones associated with serious invasive disease. Microbiology 144, 3049–3060.[CrossRef][Medline]
Feil, E. J. & Enright, M. C. (2004). Analyses of clonality and the evolution of bacterial pathogens. Curr Opin Microbiol 7, 308–313.[CrossRef][Medline]
Hanage, W. P., Fraser, C. & Spratt, B. G. (2005). Fuzzy species among recombinogenic bacteria. BMC Biol 3, 6[CrossRef][Medline]
Holt, J. G., Krieg, N. R., Sneath, P. H. A., Staley, J. T. & Williams, S. T. (1994). Group 11. Oxygenic phototrophic bacteria. In Bergey's Manual of Determinative Bacteriology, 9th edn, pp. 377–425. Edited by J. G. Holt. Baltimore: Williams & Wilkins.
Homan, W. L., Tribe, D., Poznanski, S., Li, M., Hogg, G., Spalburg, E., Van Embden, J. D. & Willems, R. J. (2002). Multilocus sequence typing scheme for Enterococcus faecium. J Clin Microbiol 40, 1963–1971.
Istock, C. A., Duncan, K. E., Ferguson, N. & Zhou, X. (1992). Sexuality in a natural population of bacteria – Bacillus subtilis challenges the clonal paradigm. Mol Ecol 1, 95–103.[Medline]
Janse, I., Kardinaal, W. E., Meima, M., Fastner, J., Visser, P. M. & Zwart, G. (2004). Toxic and nontoxic Microcystis colonies in natural populations can be differentiated on the basis of rRNA gene internal transcribed spacer diversity. Appl Environ Microbiol 70, 3979–3987.
Kasai, F., Kawachi, M., Erata, M. & Watanabe, M. M. (2004). NIES-Collection, List of Strains, Microalgae and Protozoa, 7th edn. Tsukuba, Japan: National Institute for Environmental Studies.
Kurmayer, R., Dittmann, E., Fastner, J. & Chorus, I. (2002). Diversity of microcystin genes within a population of the toxic cyanobacterium Microcystis spp. in Lake Wannsee (Berlin, Germany). Microb Ecol 43, 107–118.[CrossRef][Medline]
Lyra, C., Suomalainen, S., Gugger, M., Vezie, C., Sundman, P., Paulin, L. & Sivonen, K. (2001). Molecular characterization of planktic cyanobacteria of Anabaena, Aphanizomenon, Microcystis and Planktothrix genera. Int J Syst Evol Microbiol 51, 513–526.[Abstract]
Maiden, M. C., Bygraves, J. A., Feil, E., Morelli, G., Russell, J. E., Urwin, R., Zhang, Q., Zhou, J., Zurth, K. & other authors (1998). Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad Sci U S A 95, 3140–3145.
Martin, D. P., Williamson, C. & Posada, D. (2005). RDP2: recombination detection and analysis from sequence alignments. Bioinformatics 21, 260–262.
Mikalsen, B., Boison, G., Skulberg, O. M., Fastner, J., Davies, W., Gabrielsen, T. M., Rudi, K. & Jakobsen, K. S. (2003). Natural variation in the microcystin synthetase operon mcyABC and impact on microcystin production in Microcystis strains. J Bacteriol 185, 2774–2785.
Mlouka, A., Comte, K., Castets, A. M., Bouchier, C. & Tandeau de Marsac, N. (2004). The gas vesicle gene cluster from Microcystis aeruginosa and DNA rearrangements that lead to loss of cell buoyancy. J Bacteriol 186, 2355–2365.
Nei, M. (1987). Molecular Evolutionary Genetics. New York: Columbia University Press.
Neilan, B. A. (1995). Identification and phylogenetic analysis of toxigenic Cyanobacteria by multiplex randomly amplified polymorphic DNA PCR. Appl Environ Microbiol 61, 2286–2291.[Abstract]
Neilan, B. A., Jacobs, D. & Goodman, A. E. (1995). Genetic diversity and phylogeny of toxic cyanobacteria determined by DNA polymorphisms within the phycocyanin locus. Appl Environ Microbiol 61, 3875–3883.[Abstract]
Neilan, B. A., Jacobs, D., Del Dot, T., Blackall, L. L., Hawkins, P. R., Cox, P. T. & Goodman, A. E. (1997). rRNA sequences and evolutionary relationships among toxic and nontoxic cyanobacteria of the genus Microcystis. Int J Syst Bacteriol 47, 693–697.
Nishizawa, T., Asayama, M., Fujii, K., Harada, K. & Shirai, M. (1999). Genetic analysis of the peptide synthetase genes for a cyclic heptapeptide microcystin in Microcystis spp. J Biochem (Tokyo) 126, 520–529.
Otsuka, S., Suda, S., Li, R., Watanabe, M., Oyaizu, H., Matsumoto, S. & Watanabe, M. M. (1999). Phylogenetic relationships between toxic and non-toxic strains of the genus Microcystis based on 16S to 23S internal transcribed spacer sequence. FEMS Microbiol Lett 172, 15–21.[CrossRef][Medline]
Otsuka, S., Suda, S., Li, R., Matsumoto, S. & Watanabe, M. M. (2000). Morphological variability of colonies of Microcystis morphospecies in culture. J Gen Appl Microbiol 46, 39–50.[CrossRef][Medline]
Otsuka, S., Suda, S., Shibata, S., Oyaizu, H., Matsumoto, S. & Watanabe, M. M. (2001). A proposal for the unification of five species of the cyanobacterial genus Microcystis Kutzing ex Lemmermann 1907 under the rules of the Bacteriological Code. Int J Syst Evol Microbiol 51, 873–879.[Abstract]
Papke, R. T., Koenig, J. E., Rodriguez-Valera, F. & Doolittle, W. F. (2004). Frequent recombination in a saltern population of Halorubrum. Science 306, 1928–1929.
Posada, D. & Crandall, K. A. (1998). MODELTEST: testing the model of DNA substitution. Bioinformatics 14, 817–818.
Rantala, A., Fewer, D. P., Hisbergues, M., Rouhiainen, L., Vaitomaa, J., Borner, T. & Sivonen, K. (2004). Phylogenetic evidence for the early evolution of microcystin synthesis. Proc Natl Acad Sci U S A 101, 568–573.
Ronquist, F. & Huelsenbeck, J. P. (2003). MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574.
Rozas, J., Sanchez-DelBarrio, J. C., Messeguer, X. & Rozas, R. (2003). DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19, 2496–2497.
Selander, R. K. & Levin, B. R. (1980). Genetic diversity and structure in Escherichia coli populations. Science 210, 545–547.
Shimodaira, H. & Hasegawa, M. (1999). Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol Biol Evol 16, 1114–1116.
Smith, J. M., Smith, N. H., O'Rourke, M. & Spratt, B. G. (1993). How clonal are bacteria?. Proc Natl Acad Sci U S A 90, 4384–4388.
Swofford, D. L. (2002). PAUP* – Phylogenetic analysis using parsimony (*and other methods), version 4. Sunderland, MA: Sinauer Associates.
Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595.
Takahashi, I., Hayano, D., Asayama, M., Masahiro, F., Watahiki, M. & Shirai, M. (1996). Restriction barrier composed of an extracellular nuclease and restriction endonuclease in the unicellular cyanobacterium Microcystis sp. FEMS Microbiol Lett 145, 107–111.[CrossRef][Medline]
Tanabe, Y., Kaya, K. & Watanabe, M. M. (2004). Evidence for recombination in the microcystin synthetase (mcy) genes of toxic cyanobacteria Microcystis spp. J Mol Evol 58, 633–641.[CrossRef][Medline]
Tillett, D., Dittmann, E., Erhard, M., von Dohren, H., Borner, T. & Neilan, B. A. (2000). Structural organization of microcystin biosynthesis in Microcystis aeruginosa PCC7806: an integrated peptide-polyketide synthetase system. Chem Biol 7, 753–764.[CrossRef][Medline]
Tillett, D., Parker, D. L. & Neilan, B. A. (2001). Detection of toxigenicity by a probe for the microcystin synthetase A gene (mcyA) of the cyanobacterial genus Microcystis: comparison of toxicities with 16S rRNA and phycocyanin operon (phycocyanin intergenic spacer) phylogenies. Appl Environ Microbiol 67, 2810–2818.
Tucker, S. & Pollard, P. (2005). Identification of cyanophage Ma-LBP and infection of the cyanobacterium Microcystis aeruginosa from an Australian subtropical lake by the virus. Appl Environ Microbiol 71, 629–635.
Wallace, M. M., Miller, D. W. & Raps, S. (2002). Characterization of pMa025, a plasmid from the cyanobacterium Microcystis aeruginosa UV025. Arch Microbiol 177, 332–338.[CrossRef][Medline]
Watanabe, M. (1996). Isolation, cultivation, and classification of bloom-forming Microcystis in Japan. In Toxic Microcystis, pp. 13–34. Edited by M. F. Watanabe, K. Harada, W. W. Carmichael & H. Fukui. Boca Raton, FL: CRC press.
Yoshida, T., Takashima, Y., Tomaru, Y., Shirai, Y., Takao, Y., Hiroishi, S. & Nagasaki, K. (2006). Isolation and characterization of a cyanophage infecting the toxic cyanobacterium Microcystis aeruginosa. Appl Environ Microbiol 72, 1239–1247.
Received 13 June 2007;
revised 15 July 2007;
accepted 17 July 2007.
This article has been cited by other articles:
|
|
 |
|
  G. Christiansen, C. Molitor, B. Philmus, and R. Kurmayer Nontoxic Strains of Cyanobacteria Are the Result of Major Gene Deletion Events Induced by a Transposable Element Mol. Biol. Evol., August 1, 2008; 25(8): 1695 - 1704. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. Kaneko, N. Nakajima, S. Okamoto, I. Suzuki, Y. Tanabe, M. Tamaoki, Y. Nakamura, F. Kasai, A. Watanabe, K. Kawashima, et al. Complete Genomic Structure of the Bloom-forming Toxic Cyanobacterium Microcystis aeruginosa NIES-843 DNA Res, January 11, 2008; (2008) dsm026v1. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| INT J SYST EVOL MICROBIOL | MICROBIOLOGY | J GEN VIROL |
| J MED MICROBIOL | ALL SGM JOURNALS | |
