1 Technische Universität Berlin, Inst. Chemie, AG Biochemie und molekulare Biologie, Franklinstrasse 29, 10587 Berlin, Germany
2 Institut für Gewässerökologie und Binnenfischerei, Müggelseedamm 301, 12587 Berlin, Germany
3 Humboldt-Universität Berlin, Inst. Biologie, Luisenstrasse 53, 10117 Berlin, Germany
Correspondence
Martin Welker
martin.welker{at}chem.tu-berlin.de
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ABSTRACT |
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Present address: Institut Pasteur, Unité des Cyanobactéries, 28 rue du Dr Roux, 75724 Paris Cedex 15, France.
Present address: Landesamt für Natur und Umwelt, Hamburger Chaussee 25, 24220 Flintbek, Germany.
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INTRODUCTION |
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The genetic diversity of Microcystis (in field populations) seems to be much lower than the morphological diversity. In recent years sequence information has become available for a number of Microcystis strains, mainly from a part of the phycocyanin operon (intergenic spacer between cpcB and cpcA, IGS) and the 16S-23S-rRNA-DNA internal transcribed spacer (ITS). Both regions are considered highly variable in general, but for the genus Microcystis sequence homology was found to be very high (Otsuka et al., 1998, 1999
), and it was proposed to unify Microcystis in a single species (M. aeruginosa) and to consider the other morphospecies as subspecies by application of the bacteriological code of nomenclature (Stanier et al., 1978
; Otsuka et al., 2001
). There is, however, at present no theoretically founded general concept about what the term species' should mean in (cyano)bacteria comparable to the evolutionary species concept for higher eukaryotes (Cohan, 2002
). A third perspective to describe the diversity of Microcystis is related to the production of secondary metabolites. Microcystis and cyanobacteria in general can produce a broad variety of peptides of as yet unknown function for the producing organisms that are presumably synthesized by the non-ribosomal peptide synthetase (NRPS) pathway. The majority of peptides that have been isolated from Microcystis can be grouped into six classes according to structural characteristics, as summarized in Table 1
. However, the number of known peptides is probably far from reflecting the total diversity of peptide compounds occurring in Microcystis. The gene clusters encoding the respective NRPSs are probably all in a size range of 2560 kbp, dependent on the number of amino acid residues and modifying domains such as epimerization domains (von Döhren et al., 1997
). Although only few data are available on the distribution of other NRPS genes (Christiansen et al., 2001
) a correlation between peptide production (i.e. detectability) and presence of the respective genes can be assumed. Strains that are known to produce certain peptides do so for extended periods of time and independent of the culture conditions, giving the respective strains a distinct peptide fingerprint.
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For the present study an investigation was conducted to compare Microcystis chemotype diversity in a number of lakes in and around Berlin during the peak blooming season. A major objective was to include as many individual peptides in the analysis as possible, which was enabled by an increased amount of data in a fragment pattern database held at AnagnosTec GmbH, Luckenwalde, Germany, and to improve the data analysis by subjecting the data matrix to ordination statistics.
We were especially interested in the distribution of chemotypes in relation to the hydrological connectivity of the lakes and in the correlation between chemotypes and morphospecies.
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METHODS |
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In July and August 2000 a net sample (30 µm) was taken from each lake at near-shore sites by vertical hauls from about 1·5 m depth to the surface, and samples were stored in a cooling bag. In the laboratory individual colonies were immediately isolated from the samples under a dissecting microscope and washed in sterile water several times before being photographed with an analogue and a digital camera. Colonies were assigned to morphospecies according to Komárek & Anagnostidis (1999) during the isolation procedure and a second and third time independently from slides and digital images, respectively. The colonies were then placed on a stainless steel MALDI-TOF MS sample plate and allowed to dry at room temperature. During the isolation procedure the intention was to select representatively the different morphotypes present in the samples. As performance of the MS analysis depends also on the size of the colonies, smaller colonies (<50 µm diameter) were omitted to ensure good performance in MS analysis.
MS analysis.
Extraction of the cells was performed directly on the template with the matrix solution consisting of a saturated solution of -cyanohydroxycinnamic acid (HCA) in a mixture of water, ethanol and acetonitrile (1 : 1 : 1) acidified with 0·1 % (v/v) trifluoroacetic acid.
MALDI-TOF MS analyses were performed on a Voyager-DE PRO Biospectrometry workstation (Applied Biosystems) equipped with a reflecting ion mirror, post-source decay (PSD) and collision-induced dissociation (CID) options as described previously (Welker et al., 2003). Peaks matching known masses were further analysed by fragmentation (PSD spectra; Kaufmann et al., 1993
) and comparison of the resulting fragment spectra to theoretical fragment patterns (Erhard et al., 1999
). Mass signals of unknown compounds with sufficient intensities (>103 counts in accumulated spectra) were analysed and fragment patterns were compared to a database containing fragment patterns of known and partly characterized cyanobacterial peptides. For some colonies mass spectra were obtained also in negative-ion extraction mode.
Since the naming of cyanobacterial oligopeptides is not done according to a broadly accepted nomenclature many synonyms exist for peptides with similar structural characteristics. Therefore in this study we refer to the characteristics listed in Table 1 for classes of peptides.
Data processing and statistical analysis.
MALDI-TOF MS can be considered only as semi-quantitative, although attempts have been made to use it for the quantification of a diversity of compounds including microcystins (Ling et al., 1998; Fastner et al., 2002
). In our study, where unknown mixtures of a variety of compounds were analysed, effects influencing mass signal intensity like quenching or ionization efficiency could not be estimated. On the other hand, in the mass spectra patterns of relative signal intensities were evident. To allow a statistical analysis of the data by a multivariate technique the mass spectra were therefore processed without losing quantitative patterns (i.e. counts in mass spectra).
The detection of chlorophyll derivatives (pheophytin at m/z=871·6 Da and/or pheophorbide at m/z=593·3 Da) was set as minimum criterion for the inclusion of respective colonies in the further analysis. When no respective mass signals were obtained, the colonies were considered either as too small or already decaying at the time of preparation, or inefficiently extracted. All mass spectra were first processed with the de-isotoping option of the DataExplorer 4.0 software based on a generic peptide formula (Welker et al., 2002). Resulting mass spectra were checked for the presence of sodium and potassium adduct peaks, and in the cases where these could be identified, the respective monoisotopic counts were added to the protonated mass signal. In a next step all mass signals that could not be identified as a peptide metabolite were excluded, i.e. glycolipid signals, matrix-associated signals, or those that could not be identified as peptides with certainty.
Principal components analysis (PCA) is a form of indirect gradient analysis (Jongman et al., 1997) and was conducted to explore differences and gradients in the peptide occurrence in colonies. The compounds included in the PCA were selected when they met either of the following criteria: (1) present in at least one colony mass spectrum with a minimal relative intensity of 70 %, or (2) present in at least three colonies with a minimal relative intensity of 30 %. Prior to statistical analysis, the variability of the absolute intensities of the remaining peptide mass signals was reduced by normalizing peak heights to the interval [0;1]. The skewness of the data was reduced by a logarithmic transformation. The ordination was performed by using CANOCO 4.02 for Windows (ter Braak & Smilauer, 1998
).
The sum of counts per particular peptides processed in this way was than considered as the colony-specific metabolic fingerprint.
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RESULTS |
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From a total of more than 190 colonies that were analysed by MS, 165 yielded mass spectra with identifiable mass signals of chlorophyll a derivatives, glycolipids or peptides. Mass signals in the spectra were exclusively recorded from singly charged ions. In 146 out of 165 at least one mass signal was recorded that could be identified as a peptide. The remaining 19 colonies gave no peptide mass signal; 16 of these colonies were M. wesenbergii, two M. botrys and one M. flos-aquae. In most cases, mass signals of several compounds per colony generally were intense enough to perform PSD fragmentation. For many colonies the laser energy had to be reduced sharply to avoid a signal overflow.
In most of the mass spectra a number of peaks with high intensity was recorded (Fig. 1) and individual compounds could be identified clearly. Besides mass signals of known compounds, in many colonies a number of less intense mass signals were recorded that could not be assigned to any known (peptide) mass. Differences in mass spectra of individual colonies from a single sample were immediately evident (Fig. 1
). In some colonies, such as MU023 and MU037, the same peptides could be detected, e.g. Mcyst-LR, Mcyst-RR, cyanopeptolin W, and a chlorinated variant of cyanopeptolin W. In MU037, anabaenopeptin E/F and kasumigamide were additionally detected but were absent in MU023. The latter two peptides in turn were detected in a colony, MU035, which was found negative for microcystins and cyanopeptolins. Several mass signals occurred frequently but could not be characterized unambiguously and therefore were excluded from the further analysis, e.g. M+H=1174·6 Da or M+H=1270·6 Da.
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A new cyanopeptolin with a mass of M+H=973·5 Da (cyanopeptolin 972) was repeatedly detected and analysed by PSD from colonies originating from three sampled lakes. The proposed amino acid sequence of this peptide is [Arg-Ahp-Leu/Ile-MTyr-Val-O-Thr]-Asp-HA (HA, hexanonic acid).
Another new cyanopeptolin detected in colonies from lakes Parsteiner See, Wesensee and Wannsee had a mass of M+H=1007·4 Da (cyanopeptolin 1006) and the proposed amino acid sequence is [Arg-Ahp-Phe-MTyr-Val-O-Thr]-Asp-HA.
New aeruginosins were recognized by intense fragment peaks m/z=140 Da and m/z=122 Da, indicative of the Choi-immonium ion and its dehydrated derivative. For one aeruginosin (M+H=603·3 Da) an amino acid sequence can be proposed as [Hpla-Leu-Choi-Argininal] whereas for another aeruginosin (M+H=679·3 Da) a full structure elucidation was not possible.
Individual peptides or peptide classes were detected with pronounced differences in frequency (Table 3). The most common individual peptides were microcystin variants that occurred in 30 % (Mcyst-YR) to more than 60 % (Mcyst-LR) of all colonies. Differences among sampled lakes were considerable: in more than 90 % of the colonies from Schlachtensee Mcyst-LR was detected while in colonies of Herrensee the proportion was below 20 %. In Herrensee, however, the Microcystis community was dominated by M. wesenbergii, which did not produce any detectable peptides (10 out of 16) colonies. The frequency of other individual peptides in colonies from the sampled lakes differed more than observed for microcystins. For example, anabaenopeptins B and E/F were not detected in any colony of lakes Herrensee, Parsteiner See, Pehlitzsee and Schlachtensee, while some 40 % of the colonies from Müggelsee and Wannsee produced these peptides. A similar pattern was found for the chlorinated cyanopeptolin W, which occurred exclusively in lakes Müggelsee and Wannsee. Other peptides, such as aeruginosin 602 and cyanopeptolin 1020, were found in colonies from most of the lakes but with a lower frequency compared to microcystins.
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The number of individual peptides detected in single colonies varied considerably, from zero to ten, with a median of three. Likewise the number of peptide classes varied. The number of peptide classes (Table 1) that were detected in a single colony ranged from zero (11 % of the colonies) to five (1·2 % of the colonies). Besides these extremes, the distribution was the following: one class of peptides in 14 %, two classes in 40 %, three classes in 25 % and four classes in 7·2 % of the 165 colonies. Thus a majority of more than 60 % of the colonies produced peptides of two or three peptide classes.
Co-production of peptides from different classes showed some patterns of preference (Table 4). Microcystins, for example, were co-produced with cyanopeptolins in 57 % of the colonies. Microcystins and cyanopeptolins in turn were coproduced with microviridins in 20 % and 19 % of the colonies, respectively. Rare combinations were microcystins and microginins (1 %), aeruginosins and microviridins (4 %), and aeruginosins and anabaenopeptins (4 %).
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A distinct cluster of colonies without microcystins was found in group V, which is characterized by high contents of anabaenopeptins B and E/F and of microcystilide A. Nine of the colonies originated from Wannsee, four from Müggelsee, and two from Wesensee. Beside these main groups some 40 colonies scattered on the plot or formed small groups that were distinguishable only after enlargement of the respective area (in the F1xF2 scores). The colonies that are found in the enlarged area contained neither microcystins nor anabaenopeptins. One small group (VI) was formed by colonies containing kasumigamide (Fig. 2) and another one by colonies containing aeruginosin 602 and micropeptin B (VII). Other colonies that seemed not to be linked to any larger distinct group either contained rare peptides or contained peptides in a rare combination.
The colonies of all lakes scattered strongly along the PCA factors; no clear correlation of chemotypes to particular lakes was evident and differences in chemotype diversity between lakes thus were gradual. The majority of colonies from Schlachtensee, as one extreme, clustered tightly in groups I and IV (n=17 and n=10, respectively), while only two were placed in group III and two not associated to any group. On the other hand, out of 25 colonies from Müggelsee only nine were placed in groups I to V and the remaining 16 colonies scattered widely. Fig. 4(b) shows the same F1xF2 factorial plot with the colonies labelled with respect to their morphospecies. The few M. wesenbergii morphotypes with detectable peptides (n=5) were distributed irregularly, giving no indication of a related chemotype. M. flos-aquae colonies were placed in groups I, II and V, and with three in group VI. About half of M. ichthyoblabe colonies were placed in group V and only 20 % were found in groups IIV. For M. aeruginosa morphotypes the pattern was reversed, with 77 % of the colonies placed in groups IIV and none in group V, and the remaining 23 % distributed widely. A similar pattern was obtained for M. botrys, with 67 % of the colonies in groups IIV, and none in group V.
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DISCUSSION |
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When field samples are analysed for peptides it has to be addressed whether the detected peptides (and other metabolites) actually originate from a specific cyanobacterial taxon, in our case Microcystis, or potentially from other organisms that can not be separated mechanically in the sample preparation process. Microcystis colonies from natural waters are hardly ever pure: colonies are populated by heterotrophic prokaryotes (Brunberg, 1999), other cyanobacteria, diatoms, green algae, or protozoa like Vorticella. Nonetheless, for several reasons we are confident that the peptides that we detected by MALDI-TOF MS are indeed produced by Microcystis and that the peptide patterns are metabolic fingerprints' of Microcystis clones. Firstly, nearly all the peptides we detected are either known or are congeners of known peptides that have been isolated from axenic and unialgal Microcystis strains. Secondly, similar peptides have not been reported from eukarytic algae or protozoa so far and although heterotrophic bacteria in principle can be considered to produce oligopeptides, the peptides that were detected in Microcystis are structurally different from these.
The production of several non-ribosomal peptides by an individual clone has been shown repeatedly for axenic strains of Microcystis, with varying combinations of peptide classes (Martin et al., 1993; Fastner et al., 2001
). There is, of course, a residual uncertainty whether the colonies we isolated and analysed were indeed clonal or inseparable conglomerates of several clones. By applying several washing steps and visual control a potential respective bias was minimized.
Diversity of peptide structures and chemotypes
Considerable efforts have been undertaken in recent decades to isolate and identify cyanobacterial peptides, mainly for pharmacological purposes, and a wealth of structures has been published (Namikoshi & Rinehart, 1996; Burja et al., 2001
). Nonetheless, the number of individual peptides, many of them not described previously, that could be detected in a limited number of samples was surprising. For cyanopeptolins, for example, some 70 congeners are known. Still, that number seemingly reflects only a small part of the actual number of naturally occurring congeners of this peptide class: in 165 colonies 12 new structural variants of cyanopeptolins alone were detected. A similar situation was encountered for microviridins, where we found four putative new variants.
The highest number of individual peptide signals detected in a colony was ten, while the median was three. Accordingly, the number of peptide classes detected in individual colonies has to be regarded as a minimum number, although the production of two or three peptide classes seems to be common in Microcystis isolates.
The diversity of chemotypes and their distribution in and among sampled lakes showed considerable differences, although the PCA ordination results were determined by the occurrence of a few quantitatively important peptides in the colonies. Considering the biochemistry of non-ribosomal peptide synthesis (i.e. the presence of NRPS gene clusters) a more complex picture arises. For example a clone that produces two microcystin variants and a third (non-microcystin) peptide clearly differs from a clone producing the same microcystins but another additional peptide from a different class.
Distribution of chemotypes in samples and relation to morphospecies
Among the Microcystis samples were some with high chemotype diversity like Wannsee and Müggelsee and some with low chemotype diversity like Schlachtensee und Wesensee. The high diversity and similarity in Müggelsee and Wannsee was probably due to the hydrological connection of these two lakes by the rivers Spree and Havel. Schlachtensee, in contrast, is hydrologically isolated, being fed mainly by groundwater. However, the assumption that isolation of the ecosystem leads to a reduction in diversity following competitive exclusion should be examined carefully while so little is known about the interaction of Microcystis clones and the role of peptide metabolites. A striking correlation of a morphospecies to a single group in the PCA plot or chemotype was not obtained for any morphospecies. Only for M. ichthyoblabe was a vague correlation to group V evident. When all groups with microcystin-producing colonies were combined it became evident that, for example, M. aeruginosa was predominantly toxic, while M. ichthyoblabe was not, supporting previous findings (Fastner et al., 2001). But for all morphospecies microcystin-producing and -non-producing strains were found (except for M. viridis), and taking into account the total number of peptides no clear correlation of morphospecies to a single chemotype is obtained. Thus, peptide production is arguably, to a certain degree, independent of the genes determining the morphology. Nonetheless, if only the production of mirocystins is considered a prediction could be made for some morphospecies with fair accuracy.
What is the adaptive value of cyanobacterial oligopeptides?
The proximate explanation for the presence of diverse peptide structures that differ sometimes only in one amino acid residue (e.g. microcystins -LR and -RR) or even only in a single atom (e.g. chlorine) is related to the non-ribosomal peptide synthesis. The activation and incorporation of different amino acids is dependent on the amino acid residues that line the binding pocket of the adenylation domain of individual modules (Stachelhaus et al., 1999; Challis et al., 2000
). Further variation in peptide structures is achieved by N-methylation and chlorination, for example, which are not performed on all the synthesized molecules.
The production of a diversity of peptides by individual Microcystis clones and the physiological/ecological function of non-ribosomal peptides in cyanobacteria are not well understood yet. A number of hypotheses on their role as grazing protection, allelochemicals or infochemicals have been proposed. It has to be considered that the production of structurally diverse peptides seems to be more beneficial compared to a single or a few structural variant(s) since natural selection did not lead to the dominance of a few chemotypes, not even in a narrow geographical range as in our study. Individual peptides or peptide classes seem not to be essential for the fitness of Microcystis clones otherwise the communities should be dominated by a few chemotypes or by chemotypes producing certain peptides. But producing and non-producing strains obviously generally coexist in most environments without any clear superiority of one over the other.
For further studies on chemotype diversity, sequence information on the respective gene clusters is required to evaluate the correlation of genes and peptide diversity. A good correlation between the presence of microcystins and detection of the mcyB gene in Microcystis colonies has been established (Kurmayer et al., 2002).
Several studies have shown the presence of the mcy gene in strains that cluster more or less independently in phylogenetic trees (Neilan et al., 1995, 1997
; Otsuka et al., 1999
). This recently led to the hypothesis that the distribution of mcy genes among Microcystis strains is only partly the result of vertical gene transfer and to a certain degree due to horizontal gene transfer, lateral recombination and gene loss (Mikalsen et al., 2003
), processes that might also be important factors for the distribution of other non-ribosomal peptides among Microcystis clones. For other genes it has been hypothesized that horizontal gene transfer may occur within taxonomic units like genera (Rudi et al., 1998
; Barker et al., 2000
).
At present, there are no data available on clonal dynamics in field populations, and the methods required to follow the dynamics of clones in experiments and under field conditions, like real time-PCR (Kurmayer & Kutzenberger, 2003) or DGGE (Janse et al., 2003
), have emerged only recently. It can be concluded that a prediction or a modelling of peptide (namely Mcyst) occurrence and dynamics is currently only possible in combination with long-term data series (Welker et al., 2003
), owing to the lack of understanding of the interaction between Microcystis clones with differing peptide patterns.
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ACKNOWLEDGEMENTS |
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Received 28 November 2003;
revised 2 February 2004;
accepted 9 February 2004.
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