Diversity and phylogeny of Baltic Sea picocyanobacteria inferred from their ITS and phycobiliprotein operons.

Abstract

Picocyanobacteria of the genus Synechococcus span a range of different colours, from red strains rich in phycoerythrin (PE) to green strains rich in phycocyanin (PC). Here, we show that coexistence of red and green picocyanobacteria in the Baltic Sea is widespread. The diversity and phylogeny of red and green picocyanobacteria was analysed using three different genes: 16S rRNA-ITS, the cpeBA operon of the red PE pigment and the cpcBA operon of the green PC pigment. Sequencing of 209 clones showed that Baltic Sea picocyanobacteria exhibit high levels of microdiversity. The partial nucleotide sequences of the cpcBA and cpeBA operons from the clone libraries of the Baltic Sea revealed two distinct phylogenetic clades: one clade containing mainly sequences from cultured PC-rich picocyanobacteria, while the other contains only sequences from cultivated PE-rich strains. A third clade of phycourobilin (PUB) containing strains of PE-rich Synechococcus spp. did not contain sequences from the Baltic Sea clone libraries. These findings differ from previously published phylogenies based on 16S rRNA gene analysis. Our data suggest that, in terms of their pigmentation, Synechococcus spp. represent three different lineages occupying different ecological niches in the underwater light spectrum. Strains from different lineages can coexist in light environments that overlap with their light absorption spectra.

Full text

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Diversity and phylogeny of Baltic Sea
picocyanobacteria inferred from their ITS and
phycobiliprotein operons
Thomas Haverkamp,1Silvia G. Acinas,1†
Marije Doeleman,1Maayke Stomp,2Jef Huisman1,2
and Lucas J. Stal1,2*
1Department of Marine Microbiology, Netherlands
Institute of Ecology, NIOO-KNAW, P.O. Box 140,
4400 AC Yerseke, the Netherlands.
2Aquatic Microbiology, Institute for Biodiversity and
Ecosystem Dynamics, University of Amsterdam,
Nieuwe Achtergracht 127, 1018 WS Amsterdam,
the Netherlands.
Summary
Picocyanobacteria of the genus Synechococcus span
a range of different colours, from red strains rich in
phycoerythrin (PE) to green strains rich in phyco-
cyanin (PC). Here, we show that coexistence of red
and green picocyanobacteria in the Baltic Sea is
widespread. The diversity and phylogeny of red and
green picocyanobacteria was analysed using three
different genes: 16S rRNA-ITS, the cpeBA operon of
the red PE pigment and the cpcBA operon of the
green PC pigment. Sequencing of 209 clones showed
that Baltic Sea picocyanobacteria exhibit high levels
of microdiversity. The partial nucleotide sequences of
the cpcBA and cpeBA operons from the clone librar-
ies of the Baltic Sea revealed two distinct phyloge-
netic clades: one clade containing mainly sequences
from cultured PC-rich picocyanobacteria, while the
othercontainsonlysequences
PE-rich strains. A third clade of phycourobilin (PUB)
containing strains of PE-rich Synechococcus spp. did
not contain sequences from the Baltic Sea clone
libraries. These findings differ from previously pub-
lished phylogenies based on 16S rRNAgene analysis.
Our data suggest that, in terms of their pigmentation,
Synechococcus spp. represent three different lin-
eages occupying different ecological niches in the
underwater light spectrum. Strains from different
fromcultivated
lineages can coexist in light environments that
overlap with their light absorption spectra.
Introduction
Picocyanobacteria of the Synechococcus group span a
range of different colours, depending on their pigment
composition (Wood, 1985; Olson et al., 1990; Pick, 1991;
Vörös et al., 1998; Stomp et al., 2007). Picocyanobacteria
with high concentrations of the pigment phycoerythrin
(PE) absorb green light effectively, and have a red
appearance. Picocyanobacteria with high concentrations
of phycocyanin (PC) absorb red light effectively, and have
a blue-green colour. Recent competition models and labo-
ratory experiments showed that red picocyanobacteria
win the competition in green light, green picocyanobacte-
ria win in red light, while red and green picocyanobacteria
can coexist in white light by partitioning of the light spec-
trum (Stomp et al., 2004). This matches their distribution
patterns. Red picocyanobacteria are dominant compo-
nents of the Synechococcus group in open ocean waters
(Li et al., 1983; Platt et al., 1983; Campbell and Carpen-
ter, 1987; Campbell and Vaulot, 1993), where green and
particularly blue light penetrate deeply into the water
column. Moreover, red picocyanobacteria can have two
different bilin pigments known as phycoerythrobilin (PEB)
and phycourobilin (PUB), which both bind to the apopro-
tein phycoerythrin. The absorption peak of PUB is shifted
slightly further to the blue part of the spectrum, and pico-
cyanobacteria with a high PUB/PEB ratio are typically
dominant in oligotrophic regions of the oceans where
blue light prevails (Olson et al., 1990; Wood et al., 1998;
Toledo et al., 1999). In addition, some strains are able to
modify their pigmentation through the synthesis of PE with
two alternative chromophores, PEB and PUB (type IV CA;
Everroad et al., 2006). Green picocyanobacteria domi-
nate in turbid waters, where red light prevails (Stomp
et al., 2007). Coexistence of red and green picocyanobac-
teria can be found in waters of intermediate colouration,
including coastal seas and many freshwater lakes (Pick,
1991; Vörös et al., 1998; Murrell and Lores, 2004; Katano
et al., 2005; Mózes et al., 2006; Stomp et al., 2007).
The genus Synechococcus is polyphyletic. Several
clusters have been identified, based on photosynthetic
Received
correspondence. E-mail L.Stal@nioo.knaw.nl; Tel. (+31) 113 577300;
Fax (+31) 113 573616.†Present address: Institut de Ciencies del Mar,
CMIMA, 08003, Barcelona, Spain.
Publication 4153 Netherlands Institute of Ecology (N100-KNAW).
30May,2007;accepted 11 August,2007.*For
Environmental Microbiology (2008) 10(1), 174–188 doi:10.1111/j.1462-2920.2007.01442.x
© 2007 The Authors
Journal compilation © 2007 Society for Applied Microbiology and Blackwell Publishing Ltd

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pigmentation, nitrogen requirements, motility and salinity
(Herdman et al., 2001). In marine environments, Syn-
echococcus spp. are dominated by members of cluster 5.
Synechococcus cluster 5 is divided in two subclusters,
5.1 and 5.2. Both subclusters consist of isolates from the
ocean as well as from coastal origin. Members of cluster
5.1 typically have a red colour. They produce PE as their
main photosynthetic pigment, have a GC content between
55% and 62%, and require elevated salt levels for growth.
In contrast, members of cluster 5.2 have a green
appearance. They produce the pigment PC but lack PE,
have a GC content between 63% and 66% and are often
able to grow without elevated salt requirements (Herdman
et al., 2001).
Freshwater picocyanobacteria are often assigned to
Cyanobium, a genus closely related to Synechococcus.
Cyanobium is only known from freshwater and brackish
environments (Crosbie et al., 2003; Ernst et al., 2003). It
contains PC as its main photosynthetic pigment and pos-
sesses a high GC content (66–71%). Cyanobium is com-
posed of clusters that are distinguished by salt tolerance
and GC content (Herdman et al., 2001).
Thephylogenetictreeofpicocyanobacteriaisnotalways
consistent with their pigmentation type. Some strains iso-
lated from marine and freshwater environments produce
PE, but are related to the Cyanobium cluster according to
sequence information of their 16S rRNA gene, the riboso-
mal internally transcribed spacer (ITS) region and the
rpoC1 gene (Crosbie et al., 2003; Ernst et al., 2003; Ever-
road and Wood, 2006). Conversely, most members of
Synechococcus cluster 5.1 are rich in PE, but PC-rich
isolates were obtained from the Red Sea. Although the
genomic GC content of one of these isolates, strain
RS9917 (64%), is within the range of Cyanobium, it is
unknown whether this is also the case for the other strains
of that clade (VIII) of cluster 5.1 (Fuller et al., 2003).
Here, we studied natural communities of picocyanobac-
teria from the Baltic Sea by constructing clone libraries of
partial sequences of the 16S rRNA-ITS, cpeBA and
cpcBA operons. The latter two encode for the pigments
PE and PC respectively. Earlier studies suggested that
the phylogeny of cpcBA of freshwater picocyanobacteria
correlated with pigmentation (Neilan et al., 1995; Robert-
son et al., 2001; Crosbie et al., 2003). Our results dem-
onstrate that a phylogeny based on the operons encoding
for phycocyanin and phycoerythrin in picocyanobacteria
differs from earlier phylogenies based on the 16S rRNA-
ITS operon.
Results
Environmental conditions
Stratification. In July 2004, water was sampled at four
stations in the Gulf of Finland and Baltic Sea proper
(Fig. 1). Station S298 had a triple thermal stratification at
5, 10 and 20 m depth (Fig. 2). The density profile of this
station revealed that the upper 5 m was well mixed, while
density gradually increased with depth below this shallow
surface-mixed layer. Station S300 showed a clear
surface-mixed layer of ~15 m depth. Station S314 had a
slightly shallower surface-mixed layer, with a thermocline
and pycnocline at 10–12 m depth. Both stations S300 and
Fig. 1. The sampling stations S298, S300,
S314 and S320 along the East-West transect
from the Gulf of Finland to the Baltic Sea
during the CYANO cruise in 2004.
298
300
314
320
Sweden
Finland
Russia
Latvia
Estonia
Gulf of
Bothnia
Gulf of Finland
Baltic Sea
Phylogeny of red and green picocyanobacteria175
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S314 had a subtle secondary stratification at ~21 m depth.
Station S320 was not stratified, but showed nearly homo-
geneous vertical profiles of salinity, temperature and
density up to 30 m depth (Fig. 2).
Underwater light spectra. The underwater light spectrum
of natural waters largely depends on light attenuation by
water itself, by the ‘background turbidity’ caused by dis-
solved organic matter (known as gilvin in the optics litera-
ture) and inanimate suspended particles (tripton, like
sediment and detritus), and by phytoplankton species
present in the water column (Kirk, 1994). Water absorbs
strongly in the red part of the spectrum, whereas gilvin
and tripton are responsible for rapid attenuation of blue
wavelengths. In the Baltic Sea, light absorption in the blue
and the red end of the spectrum is of a similar magnitude.
At all four stations, this yielded an underwater light spec-
trum that narrowed to green wavelengths with increasing
depth (Fig. 3A). The light absorption spectra of a red
and a green strain of Baltic Sea picocyanobacteria are
depicted in Fig. 3B as an example to illustrate how
they are tuned to the underwater light spectrum.
Phycoerythrin-rich strains have an absorption peak at
~560 nm, and hence absorb green light effectively.
Phycocyanin-rich strains have an absorption peak at
~625 nm, and absorb orange-red light effectively. Chloro-
phyll peaks were also clearly visible in the absorption
spectra at 440 nm (Soret band) and 680 nm.
We found euphotic depths of 10.5 m at station S298,
15.3 m at station S300 and 20.3 m at stations S314 and
S320, where the euphotic depth is defined as the depth at
which the irradiance [PAR (photosynthetically active
radiation), 400–700 nm] equals 1% of the surface
irradiance. Hence, the background turbidity of the surface
water decreased from the Eastern towards the Western
part of the Gulf of Finland.
Nutrients. Dissolved inorganic nitrogen and phosphorus
were measured in water samples from the surface (0 m)
and from 30 m depth (Table 1). At all stations, nitrogen
and phosphorus concentrations were lower at the surface
than at depth. Nitrate and nitrite concentrations at the
surface were at or below the detection limit of 0.01 mM. At
station S320, the phosphorus concentration at the surface
was also below the detection limit. At all stations, the N:P
ratios were well below the Redfield ratio of 16 (Table 1),
S298
4
Depth (m)
0
10
20
30
40
S300
S314
S320
Salinity (psu)
0
Depth (m)
0
10
20
30
40
Temperature (oC)
2
Depth (m)
0
10
20
30
40
Density (kg m-3)
56745674567
45
6
7
5
10
15
200
5
10
15
200
5
10
15
200
5
10
15
20
3
4
56
2
3
4
56
2
3
4
56
2
3
4
56
Fig. 2. Vertical profiles of salinity, temperature and density at the stations S298, S300, S314 and S320.
176T. Haverkamp et al.
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Page 4

indicating that nitrogen was relatively more limiting for
phytoplankton growth than phosphorus.
Distribution of picocyanobacteria
Chlorophyll a was measured in two size fractions, a small-
size fraction (< 20 mm) and a large-size fraction (> 20 mm).
Microscopic examination indicated that the small-size
fraction in the Baltic Sea contained mainly picocyanobac-
teria (< 2 mm) and also small filaments of Pseudanabaena
spp., consistent with earlier studies (Albertano et al.,
1997; Stal and Walsby, 2000; Stal et al., 2003). The large-
size fraction was dominated by the filamentous, N2-fixing
cyanobacteria Nodularia spumigena, Anabaena spp. and
Aphanizomenon flos-aquae, which were mainly concen-
trated in the upper 10 m of the water column (Fig. 4).
Picocyanobacteria were mainly distributed over the upper
15–20 m at stations S300, S314 and S320, and even
down to 30 m at station S298. The small-size fraction
represented 70–80% of the total chlorophyll a in the upper
10 m, and even more than 90% of the total chlorophyll a
below 10 m (Fig. 4).
Red and green picocyanobacteria were counted by
flow cytometry, on the basis of their size and pigment
composition. The depth distributions revealed that red and
green picocyanobacteria coexisted throughout the upper
30 m (Fig. 4). The cell numbers of the green picocyano-
bacteria showed a gradual decline with depth, while the
red picocyanobacteria formed a subsurface maximum. At
stations S298, S300 and S314, the subsurface maximum
of the red picocyanobacteria was at the euphotic depth.At
station S320, which lacked a clear stratification pattern
(Fig. 2), the subsurface maximum at ~8 m was less pro-
nounced (Fig. 4).
The 16S rRNA and ITS region
The diversity of picocyanobacteria was assessed by
sequencing environmental clone libraries containing poly-
merase chain reaction (PCR) fragments with a part of the
16S rRNA gene and the internally transcribed spacer
between the 16S and 23S rRNA genes (ITS). At all four
stations, samples were taken at 3 and 12 m depth, where
both PC-rich and PE-rich picocyanobacteria were abun-
dant (Fig. 4). The samples were size fractionated, to
separate the small cyanobacteria (< 20 mm) from the
larger phytoplankton. This yielded a total of eight samples,
from which DNA was extracted and PCR amplified using
oligonucleotide primers specific for cyanobacteria. We
sequenced the last 400 bases of the 16S rRNA gene and
Irradiance
(μmol photons m-2 s-1 nm-1)
0
1
2
3
4
5
6
450400
Absorption
(Relative to maximum)
0.0
0.5
1.0
CCY0417
CCY0448
Surface
1m
2m
3m
5m
8m
12m
A
B
500600700
550
650
Fig. 3. Comparison of the underwater light spectrum and the light
absorption spectra of PE-rich and PC-rich picocyanobacteria.
A. Underwater light spectra measured at station S320 in the [Gulf
of Finland (Baltic Sea)]. The spectrum narrows to the green
waveband with increasing depth. Underwater light spectra at the
three other stations were similar.
B. Absorption spectra of the PC-rich strain CCY0417 and the
PE-rich strain CCY0448 isolated from the Gulf of Finland (Baltic
Sea). Absorption spectra are scaled to their maximum value.
Table 1. Concentrations of PO43–, NO3–, NO2–and NH4+(in mmol l-1) measured at the four sampling stations, both from the surface layer and at
30 m depth.
Stations
PO43–(mM)NO3–(mM)NO2–(mM)NH4+(mM)N:P
0 m 30 m0 m 30 m0 m30 m 0 m 30 m0 m 30 m
S298
S300
S314
S320
0.02
0.18
0.09
0
0.28a
0.85
0.32
0.19
0
0
0
0.03
0.01a
1.11
0.32
0.09
0
0
0
0
0.01a
0.29
0.08
0
0.18
0.21
0.11
0.07
0.17a
0.86
1.56
1.3
9
1.17
1.22
n.d.
0.68a
2.66
6.13
7.32
a. At station S298, deep samples were from 20 m instead of 30 m.
Phylogeny of red and green picocyanobacteria177
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Page 5

the complete ITS of 74 clones, and compared these
sequences against existing databases (NCBI, RDP-II)
(Table S1, Fig. S1). One clone appeared to be from the
filamentous heterocystous cyanobacterium Anabaena
flos-aquae (99% similarity to the 16S rRNA sequence;
AJ630422), and was therefore not further considered.
The vast majority of clones (65 of the 74) exhibited
high sequence similarity (96–99%) to several closely
related Synechococcus strains (LM94, BO8807 and
S. rubescens), which all belong to freshwater group B
(Crosbie et al., 2003; Ernst et al., 2003) (Table S1,
Fig. S1). This is consistent with earlier studies, which
have shown that strains of group B are more than 99%
similar at the 16S-rRNA level (Crosbie et al., 2003), and
more than 95% similar at the ITS sequence (Ernst et al.,
2003). The remaining clones displayed high sequence
similarity (96–98%) to other freshwater Synechococcus
strains (Table S1, Fig. S1). One of our clone sequences
(TH320-12-6) had a 99% similarity to the 16S rRNA gene
of Synechococcus strain MH305 (Crosbie et al., 2003).
The ITS sequence of this clone was completely disparate
from the other clones, except for the tRNA genes. The
position of the clone TH320-12-6 in our phylogenetic
analysis confirms this by placing the sequence close to
the root of the tree with low bootstrap support (Fig. S1).
We observed large variations in ITS length and GC
content in our clone libraries, consistent with earlier
studies (Laloui et al., 2002; Rocap et al., 2002; Ernst
et al., 2003; Chen et al., 2006).
Comparison of the clone libraries from 3 m and 12 m
depth, using the program Web-Libshuff (Singleton et al.,
2001), revealed that there was no significant difference
between the libraries obtained from the two sampling
depths (P > 0.05). We therefore assumed that the libraries
from 3 m and 12 m depth have the same composition,
and they were lumped in our diversity analysis. The diver-
sity in the clone libraries was analysed using the program
DOTUR that calculates several diversity estimators and can
be used to create rarefaction curves and similarity plots
(Schloss and Handelsman, 2005). Rarefaction was used
to determine the diversity structure within the 16S rRNA
gene-ITS clone library (Fig. 5A, Table 2). These results
indicate a high degree of microdiversity in our clone
library, suggesting that many of the sequences belong to
the same or closely related ‘species’. When the similarity
was further reduced, the number of operational taxonomic
units (OTUs) continued to decrease until all clones
merged into a single OTU at 73% similarity (Fig. 5B).
Because the ITS region is highly variable, we also
tested the diversity within our library by using only the
sequences encoding part of the 16S rRNA gene (487 bp).
This revealed that 68% of the partial 16S rRNA
sequences fall into the 99% clusters (Table 2).
Several diversity estimators were calculated, such as
the Shannon–Weaver and Simpson diversity indices,
Good’s Coverage, and the Chao and ACE richness esti-
mates (Good, 1953; Magurran, 1988; Chao and Lee,
1992). Assuming a 99% similarity criterion, the Chao and
ACE richness estimates indicated a species richness of
37 and 36 respectively (Table 2).
The phycocyanin operon
We included known cpcBA sequences in our alignment for
comparison with the 68 clones that we obtained from the
Baltic Sea. The lengths of the sequences available in
GenBank ranged from 320 bp to almost 500 bp (excluding
the intergenic spacer, IGS), complicating phylogenetic
analysis of the cpcBA genes. We decided to remove
sequences shorter than 380 bp (IGS excluded) from our
Fig. 4. Vertical profiles of chlorophyll a and
picocyanobacteria at stations S298, S300,
S314 and S320.
A. Concentration of chlorophyll a in the
large-size fraction (blue dots; >20 mm) and in
the small-size fraction (green triangles;
< 20 mm). Total concentration of chlorophyll a
is shown in black.
B. Concentration of PC-rich picocyanobacteria
(green dots) and PE-rich picocyanobacteria
(red triangles). In black is shown the total
number of picocyanobacterial cells.
S298
0
Depth (m)
0
10
20
30
40
S314S320
A
Chlorophyll a (μg l-1)
0
Depth (m)
0
10
20
30
40
B Picocyanobacterial cells (x 103 ml-1)
S300
246024602460246
10
20300
10
20300
10
20300
10
2030
178 T. Haverkamp et al.
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Page 6

alignment to avoid incorrect topologies (Nei et al., 1998;
Tamura et al., 2004). This approach gave a more robust
phylogenetic tree of the cpcBA gene.
Figure 6 shows the phylogenetic tree that we obtained
for the partial cpcBA gene sequences. Many of the pico-
cyanobacteria of the Baltic Sea are closely related to the
known groups A, B, H and I (Robertson et al., 2001;
Crosbie et al., 2003; Table S2), confirming the results
based on the 16S rRNA-ITS operon. The Baltic Sea
Group 3 is probably a novel taxon within the picocyano-
bacteria, as these sequences form a monophyletic group
that separates with a long branch and with good bootstrap
support from the other sequences. We cannot exclude
that the other Baltic Sea groups might also represent
unique groups although the branch lengths separating
these sequences from known sequences are small.
Hence, this might as well represent microdiversity
between the clusters.
A
B
Cluster similarity (%)
70
Number of OTUs
0
10
20
30
40
50
Number of clones sequenced
0
Number of OTUs
0
10
20
30
40
50
100%
99%
98%
97%
96%
204060 80
7580 859095100
Fig. 5. Diversity patterns of the Baltic Sea picocyanobacteria using
16S rRNA-ITS sequences.
A. Rarefaction curves of the number of observed OTUs at 100%,
99%, 98%, 97% and 96% similarity cut-offs.
B. Number of OTUs plotted against different cluster cut-off values
in 1.0% increments for sequences grouped into similarity clusters.
Table 2. Diversity estimators for the clone libraries of the 16S rRNA-ITS, 16S rRNA, cpcBA operon and cpeBA operon, with and without intergenic spacers.
Gene
Number of clones
OTUs (100%/99%/97%)
Good’s Coverage (%)
Chao-1
S-ACE
Shannon index
Simpson index (1/D)
16S-ITS complete
73
40/22/11
86.3
37 (26–86)
36 (26–66)
2.64
10.90
16S without ITS
73
19/6/1
95.9
9 (6–31)
14 (7–79)
0.89
1.85
cpcBA operon
68
24/11/8
92.65
21 (13–63)
16 (12–37)
1.52
2.76
cpcBA without IGS
68
20/10/8
94.12
16 (11–48)
13 (11–30)
1.49
2.75
cpeBA operon
68
24/11/5
91.8
26 (14–79)
28 (14–107)
1.85
5.52
cpeBA without IGS
68
24/12/6
91.8
27 (15–80)
23 (14–70)
2.01
6.66
The number of operational taxonomic units (OTUs) is shown at 100%, 99% and 97% similarity cut-off values. The coverage is expressed as defined by Good (1953). The Chao-1 richness, ACE
richness, Shannon diversity index and Simpson diversity index use 99% similarity cut-off values. Numbers within parentheses for the Chao-1 and ACE richness estimators are 95% confidence
intervals.
Phylogeny of red and green picocyanobacteria 179
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Page 7

BS group 1 (40), 31, 64
AY151222, MW99B6, 28, 64
DQ526401, LS0530, 29, 64
AY151223, MW97C4, 28, 65
AY151224, MW100C3, 28, 64
BS group 2 (6), 30, 63
EF513487, BO8805, 29, 66
group I
AAN01000009, WH5701, 28, 65
S320-12-7, 28, 66
BS group 3 (6), 33, 61
100
DQ526396, LS0534, 31, 63
group A (12), 25, 66
AANP01000000, RS9917, cpcBA1, 26, 63
AANP01000000, RS9917, cpcBA2, 26, 63
AF223443, PS681, 28, 65
EF513488, CCY9201(BS4), 29, 64
S314-3-9, 29, 64
S314-12-3, 29, 63
BS group 4
AF223436, PS724, 32, 63
AF223428, PS680, 31, 67
group D (5), 28, 64
AF223451, PS729, 34, 58
AF223447, PS727, 33, 58
group B (19), 41, 58
EF513489, CCY9202 (BS5), 39, 59
AF223449, PS716, 45, 56
AF223435, PS722, 38, 58
AF223445, PS719, 39, 59
group E
AAOK00000000, WH7805, 41, 59
PUB – Synechococcus (7), 39, 58
group H (12), 45, 54
Syn. cluster 1, 39, 56
Syn. cluster 3, 44, 51
Syn. cluster 2 (7), 37, 55
100
100
100
99
96
100
93
81
100
76
100
100
69
97
100
62
57
90
67
84
54
78
54
99
70
50
96
68
99
100
92
57
100
99
0.05
Out-
groups
Fig. 6. Neighbour-joining tree of the picocyanobacterial cpcBA genes. Clades were condensed for clarity, showing the group designations
following Crosbie and colleagues (2003) (Fig. S2). BS group designations are assigned to clades formed solely by clone sequences from the
Baltic Sea. For condensed groups, the number of cpcBA sequences is indicated within brackets. For single sequences, the GenBank
accession number and the strain designation are given. For each clade with known isolates, the pigment phenotype is indicated with the
colours red (PE-rich) and green (PC-rich). Numbers indicate the mean ENC number and the mean GC content respectively. The tree was
calculated with the software MEGA with the neighbour-joining method using the Kimura two-parameter model of nucleotide substitution with
1000 replicates (Kumar et al., 2004). Bootstrap values (> 50%) are shown at the nodes. As outgroups were used the cpcBA sequences of
Synechococcus cluster 1 (strains PCC6301, PCC7942 and PCC7943), Synechococcus cluster 2 (strains PCC6716, PCC6717, Synechococcus
elongates, JA-2-3b and JA-3-3b) and Synechococcus cluster 3 (PCC7002).
180 T. Haverkamp et al.
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There are also some striking differences between the
cpcBA phylogeny and the existing 16S rRNA phylogenies
(Crosbie et al., 2003; Fuller et al., 2003). First, the cpcBA
phylogeny separated most picocyanobacteria with a
green phenotype from picocyanobacteria with a red phe-
notype, although there were a few red strains within the
green clusters (Fig. 6, Fig. S2). Second, in contrast to the
16S rRNA phylogeny, in the cpcBA phylogeny green pico-
cyanobacteria isolated from marine environments (e.g.
strains RS9917 and WH5701) clustered with green fresh-
water picocyanobacteria. Third, the green Cyanobium
strain CCY9201 (previously known as BS4) and the red
Cyanobium strain CCY9202 (previously known as BS5),
which were nearly identical according to the 16S rRNA-
ITS phylogeny (Crosbie et al., 2003; Ernst et al., 2003),
were completely separated in the cpcBA phylogeny.
Fourth,thecpcBA phylogeny
producing picocyanobacteria form a distinct cluster within
the red picocyanobacteria.
The cpcBA phylogeny pointed at a close correlation
between pigment phenotype and GC content (Fig. 6).
Phycocyanin-rich isolates had GC contents higher than
60%, while most PE-rich isolates had GC contents less
than 60% although there were a few exceptions. The
difference in GC content between the cpcBA sequences
was mainly caused by higher GC content at the third
codon position, resulting in synonymous mutations in
most of the codons investigated. Likewise, the cpcBA
phylogeny pointed at a close correlation between
pigment phenotype and the effective number of codons
(ENC). The ENC number represents a measure for the
codon usage bias (Comeron and Aguade, 1998). An
ENC number of 20 means that only one codon is used
for each amino acid, while an ENC number of 61 indi-
cates that all codons are used equally often and in that
case there is no bias in codon usage (Wright, 1990).
Phycocyanin-rich isolates had a low ENC number in the
range of 23–32, while almost all PE-rich isolates had a
high ENC number ranging from 33 to 45 (Fig. 6). Inter-
estingly, PE-rich strains with a GC content exceeding
60% and an ENC number below 33 clustered with the
PC-rich strains.
revealedthat PUB-
The phycoerythrin operon
Polymerase chain reaction amplification of the cpeBA
operon encoding the pigment phycoerythrin resulted in 68
clones (for primers see Everroad and Wood, 2006). The
number of cpeBA sequences available in existing data-
bases such as GenBank was limited to 37 full-length
sequences of different cyanobacteria and red algae.
BLASTN searches using the nucleotide sequences of all
our cpeBA clones returned only one of two different top
hits, marine Synechococcus strains WH7803 (X72961)
and WH8102 (BX569694) (Table S3). Our sequences
showed only 81–90% similarity with these two sequences.
BLASTP searches using our cpeBA sequences as query
were performed using the CPE-A and the CPE-B protein-
coding sequences. Both fragments showed the highest
similarity with the CPE-A (range 86–93%) and CPE-B
(91–97%) proteins from the marine Synechococcus strain
WH7805 (Table S3).
We performed a phylogenetic analysis using our Baltic
Sea partial cpeBA nucleotide sequences and those recov-
ered from existing databases. Analysis of the phenotypes
revealed that all cultured strains within the cpeBA phylog-
eny were PE-rich strains with a GC content between 53%
and 63% and a ENC number ranging from 30 to 45
(Fig. S3). The cpeBA phylogeny yielded two major groups
(Fig. 7). Again these two groups matched the pigmenta-
tion of picocyanobacteria. The first group was formed by
cpeBA genes from freshwater and marine Synechococ-
cus strains producing PEB only, while the second group
consisted of marine strains producing both PUB and PEB.
This topology was consistent with the cpcBA phylogeny,
where the PUB-producing picocyanobacteria formed a
distinct cluster (Fig. 6). All cpeBA sequences that we
obtained from the Baltic Sea were constrained within the
PEB group (Fig. 7). These Baltic Sea sequences were
separated into two major clades, one clade comprising
the clusters 1 and 2, and the other clade formed by
clusters 3 and 4. Comparison of the overall similarity at
the amino acid level showed that the similarity within each
of these two clades is more than 98%, while the similarity
between the two clades is only 86.6%.
Calculation of diversity estimators showed that the
diversity in the cpcBA library and cpeBA library is low
compared with the 16S rRNA-ITS library (Table 2). This
might be attributed to inherent differences in variability
between these libraries, but also to differences in length
between the 16S rRNA-ITS sequences and the cpcBA
and cpeBA sequences. The number of OTUs was
rather similar for the cpcBA and cpeBA operons. Accord-
ing to the Chao-1 and ACE richness estimates and
the Shannon–Weaver and Simpson diversity indices,
however, the diversity at the cpeBA operon encoding for
phycoerythrin was slightly higher than the diversity at the
cpcBA operon encoding for phycocyanin (Table 2).
Discussion
Colourful coexistence of red and green
picocyanobacteria
Our results show that PC-rich and PE-rich picocyanobac-
teria coexist in the Baltic Sea, where they are approxi-
mately equally abundant players in the cyanobacterial
community (Fig. 4). This confirms earlier results of Stomp
Phylogeny of red and green picocyanobacteria181
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Page 9

and colleagues (2004; 2007). Phycocyanin-rich picocy-
anobacteria were slightly more abundant in the upper 5 m
of the water column, while PE-rich picocyanobacteria
were numerically more dominant at 5–15 m depth. This
vertical distribution matches the underwater light spec-
trum, as green light penetrates more deeply into the Baltic
Sea than red light (Fig. 3A). Remarkably, the PC-rich and
PE-rich picocyanobacteria maintained their vertical distri-
bution even in waters with a nearly homogeneous tem-
perature and density profile (Station S320, Figs 2 and 4).
As picocyanobacteria lack buoyancy regulation, this indi-
cates that the local growth rates of the PE-rich and
PC-rich populations at these depths exceeded the rate of
vertical mixing by hydrodynamic processes (Huisman
et al., 1999).
Sequencing of 209 clones revealed that picocyanobac-
teria of the Baltic Sea exhibit high levels of microdiversity.
Approximately 46–54% of the OTUs present in each clone
library were constrained at 99% similarity clusters (micro-
clusters; Fig. 5, Table 2). Such high levels of microdiver-
sity have also been detected by many previous studies of
marine microbial communities and other natural bacterial
populations (Acinas et al., 2004; Lopez-Lopez et al.,
2005; Pommier et al., 2007; Rusch et al., 2007). The high
microdiversity of Synechococcus spp. genes found in
our clone libraries may reflect local adaptive radiation of
picocyanobacteria which allows them to proliferate under
a wide range of different conditions in the Baltic Sea.
Phylogeny of red and green picocyanobacteria
Our results show that a phylogeny based on the cpcBA
gene (phycocyanin) and cpeBA gene (phycoerythrin)
differs from a phylogeny based on 16S rRNA gene
sequences. This is especially clear for the cpcBA data set,
where clustering of the different phylotypes largely
matched the pigment composition of the picocyanobacte-
ria (see also Robertson et al., 2001; Crosbie et al., 2003).
This is exemplified by the green CCY9201 (previously
known as BS4) and red CCY9202 (previously known as
BS5) strains used in the competition experiments of
Stomp and colleagues (2004). On the basis of their ITS
Baltic Sea cluster 1 (28)
Baltic Sea cluster 2 (17)
EF513490, Synechococcus CCY9202(BS5) cpeBA
DQ248026, G11cpeBA
DQ248022, G4.1cpeBA
AAOK00000000, Synechococcus WH7805
DQ248023, G5.1cpeBA
S298-3m-9
Baltic Sea cluster 3 (7)
Baltic Sea cluster 4 (15)
PEB
X72961, Synechococcus WH7803
NC_007516, Synechococcus sp.CC9605
NC 005070, Synechococcus WH8102
NC_007513, Synechococcus sp.CC9902
M95288, Synechococcus WH8020-I
PUB/PEB
99/100
87/100
100/100
100/100
94/100
100/100
92/100
99/100
57/100
89/100
-/100
99/100
83/100
-/100
100/100
73/96
0.02
Fig. 7. Unrooted neighbour-joining tree of the picocyanobacterial cpeBA genes. Sequences were obtained from the Baltic Sea and from
Synechococcus strains with sequenced genomes spanning the cpeBA-IGS region. Baltic Sea clusters indicate clades formed solely by clone
sequences from the Baltic Sea. The number of cpeBA clone sequences is indicated within brackets. Synechococcus sequences extracted
from existing genome sequences or GenBank are shown in bold. Additional Synechococcus sequences from strains used in this study are
shown in italics. The tree revealed that the cpeBA sequences separated into clades containing PEB only and PUB/PEB-producing clades. The
Baltic Sea sequences separated into four clusters and one single clone (S298-3m-9). Bootstrap values (> 50%) based on 1000 replicates are
shown at the nodes, using distance analysis (first number) and maximum parsimony analyses (second number). A hyphen ‘-’ indicates not
significant.
182T. Haverkamp et al.
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Page 10

sequences, these two strains are more than 99% similar
(Ernst et al., 2003), whereas their cpcBA gene sequences
are well separated (Fig. 6), where the green strain
CCY9201 clusters in the group of PC-rich picocyanobac-
teria while the red strain CCY9202 clusters in the group of
PE-rich picocyanobacteria (Fig. 6). The few sequences of
red strains that cluster with the cpcBA operons of green
isolates can be explained by horizontal gene transfer
(HGT).
Another example is the placement of the PC-rich
marine isolate RS9917. This strain forms a distinct cluster
with other PC-rich isolates within the marine picocyano-
bacteria based on the 16S rRNA gene sequences (Fuller
et al., 2003). According to our phylogenetic analysis,
the partial cpcBA sequences of strain RS9917 clusters
withthe cpcBA sequences
picocyanobacteria. This could have been caused by HGT
of the cpcBA operon of a freshwater picocyanobacterium.
Likewise, clustering of similar pigmentation types is also
evident from the placement of PUB/PEB-producing
marine Synechococcus in both the cpcBA and cpeBA
phylogeny. The marine strain WH7805 produces PEB, but
in contrast to other PE-rich marine Synechococcus strains
it is not capable of producing PUB (Fuller et al., 2003). In
the cpeBA and cpcBA phylogenetic trees, strain WH7805
is clustered separately from the PUB-producing marine
Synechococcus strains. Only strains that produce PUB
might possess the capacity of chromatic adaptation of
type IV. We have not retrieved any sequences in our Baltic
Sea clone libraries that are related to PUB-producing
picocyanobacteria.
Overall, our phylogenetic analyses extend earlier find-
ings of Robertson and colleagues (2001) and Crosbie and
colleagues (2003), who showed that the cpcBA operon
separates PE-rich and PC-rich picocyanobacterial iso-
lates from freshwater lakes. In our analysis, we included
picocyanobacteria from brackish waters and marine eco-
systems, and studied not only the cpcBA operon but also
the cpeBA operon. This revealed three distinct groups of
picocyanobacteria separated in line with their pigmenta-
tion, namely PUB/PEB-producing strains, PEB-producing
strains and PC-producing strains. All are members of the
monophyletic clade formed by Synechococcus and
Cyanobium.
of PC-rich freshwater
Correlations with GC content and ENC number
Differences in pigmentation in the cpcBA phylogeny cor-
related with the ENC number and the GC content of
the sequences. Phycocyanin-rich picocyanobacteria had
higher GC contents and lower ENC numbers than PE-rich
picocyanobacteria (Fig. 6). One possible explanation for
differences in GC content in PE-rich and PC-rich picocy-
anobacteria is that it may reflect differences in expression
levels of the cpcBA gene. In fact, highly expressed genes
in Prochlorococcus strain MED4 had a higher GC content
compared with low expressed genes (Banerjee and
Ghosh, 2006). A PE-rich cyanobacterial phycobilisome
has one disk of PC proteins while containing multiple
disks of PE proteins. A PC-rich phycobilisome usually has
several disks of PC. The higher demand for phycocyanin
might require a higher expression level and, hence a
higher GC content of the cpcBA operon in PC-rich
cyanobacteria. Alternatively, it could also be that the
genomes of PC-rich picocyanobacteria have a higher GC
content. We tested this hypothesis by analysing the GC
content of the protein-coding genes of the genome
sequences of Synechococcus spp. present in GenBank
(Table S4). This showed that the overall GC content of the
protein-coding genes of the PC-rich Synechococcus
strains WH5701 and RS9917 is higher compared with
those of the PE-rich picocyanobacteria (Table S4). This
would contradict the theory that higher expression levels
cause the higher GC content in the cpcBA operons of
PC-rich Synechococcus spp. It also confirms the place-
ment of RS9917 among the freshwater picocyanobacteria
in our phylogenetic analysis and that it is unlikely that this
is caused by HGT of phycobiliprotein genes.
Another explanation for the relationship between GC
content and pigmentation might come from the environ-
ment. Comparative studies suggest that the GC contents
of microbial genomes or environmental shotgun libraries
vary among habitats of different productivity (Goo et al.,
2004; Carbone et al., 2005; Foerstner et al., 2005). For
instance, Foerstner and colleagues (2005) observed that
the average GC content of open reading frames (ORFs)
from the oligotrophic Sargasso Sea is only 34%, whereas
the GC content of ORFs from productive Minnesota soil
samples is 61%. These large differences in GC content
were not merely an effect of differences in species compo-
sition between these two contrasting environments, but
remained when the same analysis was focused on phyla
present in both environments or on genes present in both
environments. Extrapolated to the cpcBA phylogeny, this
would mean that the high GC sequences of PC-rich pico-
cyanobacteria come from environments with higher levels
of nutrients than the sequences of PE-rich picocyanobac-
teria that have a lower GC content. This explanation is
consistentwiththeglobaldistributionpatternofpicocyano-
bacteria (e.g. Stomp et al., 2007), where PC-rich picocy-
anobacteria dominate in productive lakes and coastal
waters while PE-rich picocyanobacteria dominate in the
oligotrophic open ocean.
Conclusions
We have found high microdiversity among picocyanobac-
teria of the Baltic Sea, where coexistence of red and
Phylogeny of red and green picocyanobacteria183
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Page 11

green Synechococcus strains is widespread. Analysis of
the cpcBA and cpeBA operons revealed a phylogenetic
tree in which picocyanobacteria are divided into three
different pigment groups: PC-rich, only PEB-producing
and PUB/PEB-producing strains. The PC-rich strains had
consistently higher GC contents and lower ENC numbers
than the two other pigment groups. These findings differ
from the picocyanobacterial phylogeny based on 16S
rRNA, which separates marine and freshwater species
but not the pigmentation groups. This indicates that pico-
cyanobacterial phylogenies based on the phycocyanin
and phycoerythrin genes are not easily compared with the
16S rRNA phylogeny. The topologies can be dissimilar
because of different evolutionary histories of the different
genes within the same group of organisms.
Experimental procedures
Sample collection
Water samples from the Baltic Sea were collected from 12 to
19 July 2004 during a research cruise with the Finnish RV
Aranda. For the work reported here, we sampled four stations
(stations S298, S300, S314, S320; Fig. 1), positioned along
an East-West transect from the Gulf of Finland into the Baltic
Sea proper (from N 59.1–60.0°N and E 22.2–26.2°E to
59.1°N 22.2°E). Samples were taken at 3 m depth intervals
from the surface to 30 m depth using a rosette sampler. A
Seabird 911 CTD was connected to the rosette sampler, to
measure temperature and salinity along these depth profiles.
Nutrient concentrations in the water samples were analysed
according to standard methods (Grasshoff et al., 1983).
Underwater light spectra
Spectra of the incident light and underwater light spectra
were measured with a RAMSES-ACC-VIS spectroradiometer
(TriOS, Oldenburg, Germany). Light absorption spectra of
isolated strains were measured using a Cary 100 Bio
equipped with an integrating sphere DRA-CA-3300, with dis-
tilled water as a reference.
Chlorophyll analysis
For chlorophyll a analysis, the phytoplankton was divided into
two size classes. Total chlorophyll a was obtained by filtering
0.5 l on GF/F filters (Whatman, nominal pore size 0.7 mm).
Chlorophyll a of the large-size fraction of phytoplankton was
obtained by filtering 1 l on 20 mm nylon mesh (plankton net).
Chlorophyll a of the small-size fraction was calculated as the
difference between total chlorophyll a and chlorophyll a of
the large-size fraction. This procedure largely discriminates
between picoplankton and the larger filamentous cyanobac-
teria in the Baltic Sea (Stal and Walsby, 2000). Chlorophyll a
was extracted overnight in the dark at room temperature by
96% ethanol and absorption was measured spectrophoto-
metrically at 665 nm. Chlorophyll concentration was calcu-
lated using an absorption coefficient of 72.3 ml mg-1cm-1
(Stal et al., 1999).
Counting red and green picocyanobacteria
The concentrations of red and green picocyanobacteria in the
samples were counted by flow cytometry (Jonker et al., 1995;
Stomp et al., 2007), using a Coulter Epics Elite ESP flow
cytometer (Beckman Coulter Nederland BV, Mijdrecht, the
Netherlands) equipped with a green laser (525 nm) and a red
laser (670 nm). The flow cytometer distinguished between
picocyanobacteria and larger phytoplankton by their size
(using side scattering). Red and green picocyanobacteria
were distinguished based on their different fluorescence
signals. Cells rich in PE emitted orange light (550–620 nm)
when excited by the green laser, whereas cells rich in PC
emitted far red light (> 670 nm) when excited by the red laser.
Extraction of nucleic acids
From each station 1 l of seawater from each sampling depth
was pre-filtered through 20 mm nylon mesh and collected in
polycarbonate bottles that were rinsed by 0.5 M NaOH. The
pre-filtered seawater was immediately filtered through 0.2 mm
Sterivex filtration units (Millipore) using a peristaltic pump.
Subsequently, the Sterivex filters were filled with 2 ml of lysis
buffer [400 mM NaCl, 20 mM EDTA, 50 mM Tris-HCl (pH 9.
0), 0.75 M sucrose] (Massana et al., 1997; Moon-van der
Staay et al., 2001) and stored at -20°C.
Nucleic acids were extracted as described by Massana
and colleagues (1997) with modifications. In brief, lysozyme
(final concentration 1 mg ml-1) was added to the Sterivex
unit and incubated for 45 min at 37°C. Subsequently,
proteinase-K (final concentration 50 mg ml-1) and sodium
dodecyl sulfate (SDS) 1% w/v were added and incubation
was continued overnight at 55°C. The lysate was recovered
from the Sterivex unit by extracting it twice with an equal
amount of phenol–chloroform–isoamyl alcohol (25:24:1;
pH 8) and once with the same volume of chloroform–isoamyl
alcohol (24:1). The extracts were centrifuged (Sigma 4k15
with a swing-out rotor, No. 11156) for 15 min at 1300 r.p.m.
and 25°C. The aqueous phase was transferred to a 15 ml
Greiner tube and two volumes of 96% ethanol and 1/10
volume 3 M Na-acetate were added and subsequently incu-
bated for 2 h at -70°C to precipitate the DNA. Subsequently,
the DNA was centrifuged for 20 min at 14000 r.p.m. and 4°C.
The pellet was washed with cold 70% ethanol (-20°C) and
centrifuged for 5 min at 14000 r.p.m. and 4°C. The superna-
tant was removed by pipetting and the pellet was air dried.
The dry pellet was suspended in 100 ml 10 mM Tris-HCl
(pH 8.5). Because the DNA was not PCR grade after this
procedure, it was further purified using the Powersoil DNA
extraction kit (MoBio Laboratories) following the manufactur-
er’s recommendations.
Primer design
For amplification of part of the 16S rRNA gene and the
internal transcribed spacer between the 16S and 23S rRNA
genes, we designed oligonucleotide primers that bind to the
5′ region of the 23S rRNA sequences of cyanobacteria
(Table 3). Cyanobacterial 23S rRNA gene sequences were
obtained from GenBank and aligned using the CLUSTALW
184T. Haverkamp et al.
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Page 12

program in Bioedit (Thompson et al., 1994; Hall, 1999). The
alignment was imported to Primer Premier software (Premier
Biosoft International, version 5.0) and 23S rRNA gene oligo-
nucleotide primers were designed using B1055 as the
forward 16S rRNA primer (Singh et al., 1998; Zaballos et al.,
2006; Table 3). Primer sequences were checked for their
specificity by performing
BLASTN searches against the
GenBank database.
Polymerase chain reaction primers targeting the phycocya-
nin cpcBA operons in a wide range of cyanobacteria were
available from the literature (Neilan et al., 1995; Robertson
et al.,2001;Crosbie et al.,
sequences from a variety of picocyanobacteria became avail-
able providing the opportunity to design primers that target
specifically the cpcBA genes from Synechococcus-like
cyanobacteria. Using the Integrated Microbial Genomes
database (http://img.jgi.doe.gov/cgi-bin/pub/main.cgi), cpcBA
operons were obtained from the following (un-)finished
picocyanobacterialgenomes:
(AP008231), PCC7942 (CP000100), CC9311 (CP000435),
CC9605(CP000110), CC9902
(AANP01000000), WH5701
(AAOK01000000) and WH8102 (BX548020) (Markowitz
et al., 2006). The cpcBA operons M95288 and M95289 from
Synechococcus strain WH8020 were downloaded from
GenBank (Delorimier et al., 1993). The full-length cpcBA
operons were aligned in Bioedit using the
algorithm. The alignment was imported in Primer Premier 5.0
and used to design primers specifically targeting the cpcBA
genes from the marine cluster B (Synechococcus WH5701)
(Table 3).
2003).Recently, genome
Synechococcus PCC6301
(CP000097),
(AANO01000000),
RS9917
WH7805
CLUSTALW
Polymerase chain reaction and
clone library construction
DNAobtained from 3 and 12 m depth of stations S298, S300,
S314 and S320 were used to amplify the cyanobacterial 16S
rRNA-ITS region, the cpeBA operon and the cpcBA operons
using the primers listed in Table 3. The PCR reaction mixture
was composed of 1 ml of template DNA (1–20 ng ml-1), 2.5 ml
of 10¥ PCR buffer (Qiagen), 0.5 ml of 10 mM dNTP’s mixture
(Roche) and 0.62 units of HotStarTaq DNA polymerase
(Qiagen). We added 10 pmol of each forward and reverse
primer, except for the 16S rRNA-ITS PCR where 5 pmol was
used. Sterile MilliQ grade water was added to a final reaction
volume of 25 ml.
The PCR reactions were run on a GeneAmp System 2700
thermocycler. The programme for the 16S-ITS amplification
consisted of 15 min hot start at 94°C; 35 cycles of 1 min at
94°C; 1 min at 62°C; and 1 min at 72°C; which was followed
by a final elongation step at 72°C for 10 min. For amplification
of the cpeBA genes the following programme was applied:
15 min at 94°C, 40 cycles of 30 s at 94°C, 30 s at 55°C and
1.5 min at 72°C. The final elongation step was 10 min at
72°C. The same programme was used to amplify cpcBA
except that the elongation step was only 1 min.
Polymerase chain reactions were performed in triplicate to
decrease variations in amplification (Polz and Cavanaugh,
1998). The PCR products of the triplicate reactions were
pooled and cloned. Cloning was performed using the TOPO
TA cloning kit for sequencing (Invitrogen) following the
instructions of the manufacturer. For each sample and PCR
product 20 clones were picked using sterile toothpicks. The
cells were transferred to 200 ml of sterile LB broth and grown
overnight. Twenty-five microlitres of culture was mixed with
25 ml of Milli-Q water and heated at 94°C for 10 min. Five
microlitres of the mixture was used for PCR amplification of
the insert using the T3 and T7 primers of the vector. Subse-
quently, 10 positive PCR reactions were chosen per sample
and purified using the DNA Clean and Concentrator (Zymo
Research). The DNA concentration was measured using a
Nanodrop ND1000 (NanoDrop Technologies) spectrophoto-
meter. The PCR product was sequenced using the Big Dye
Terminator v1.1 Cycle sequencing kit (Applied Biosystems)
according to the manufacturer’s instructions. The clones con-
taining cpeBA and cpcBA fragments were sequenced using
the T3 and T7 primers, while the 16S rRNA-ITS clones were
sequenced with the primers B1055, Cya23S-58R2, PITS1
and PITS3 (Table 3). Sequencing was performed with a 3130
Genetic Analyser (Applied Biosystems). For each clone, the
forward and reverse sequences were manually aligned in
Bioedit and the sequences were checked against GenBank
using BLASTN and BLASTP (Altschul et al., 1990; McGinnis
and Madden, 2004). Furthermore, the 16S rRNA clone
sequences were compared with the RDP-II database (Cole
et al., 2005).
Diversity calculations and phylogenetic analysis
For the diversity calculations, the clone sequences of the
different sampling stations were grouped together. The
program DOTUR was used for calculating rarefaction, library
coverage, Shannon–Wiener diversity index (H′), Simpson
index (D), Chao-1 non-parametric richness estimator and the
ACE coverage-based richness estimator (Schloss and
Handelsman, 2005). Calculations were performed on a
Table 3. Oligonucleotide primers used in this study.
Primer nameTarget geneSequence 5′-3′
Temperature (°C)Reference
B1055
Cya23S-58r2
PITS 1
PITS 3
SyncpcB-Fw
SyncpcA-Rev
B3FW
SynA1R
16S rRNA
23S rRNA
ITS
ITS
cpcB
cpcA
cpeB
cpeA
ATG GCT GTC GTC AGC TCGT
CGT CCT TCA TCG CCT CTG
TCA GTT GGT AGA GCG CCT GC
GTTAGCGGACTCGAACCGC
ATGGCTGCTTGCCTGCG
ATCTGGGTGGTGTAGGG
TCA AGG AGA CCT ACA TCG
CAG TAG TTG ATC AGR CGC AGG T
66
58
56
65
61
50
58
64
Zaballos et al. (2006)
This study
Ernst et al. (2003)
Ernst et al. (2003)
This study
This study
Everroad and Wood (2006)
Everroad and Wood (2006)
Phylogeny of red and green picocyanobacteria 185
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Page 13

Jukes–Cantor corrected distance matrix created with the
DNADIST program from the PHYLIP package (Felsenstein,
1989).
Sequences previously identified to be closely related by
BLASTN comparison were imported from GenBank into Bioedit
and aligned against the clone sequences using CLUSTALW.
Alignments of the 16S rRNA-ITS sequences were performed
manually in Bioedit by reference of the ITS alignment of the
predicted secondary structure models proposed in several
papers describing the cyanobacterial ITS sequences (Iteman
et al., 2000; Laloui et al., 2002; Rocap et al., 2002; Taton
et al., 2003). Sequence comparison and phylogenetic analy-
ses were performed using the software MEGA3.1 (Kumar
et al., 2004). For the 16S rRNA-ITS region the sequences
were compared using the neighbour-joining algorithm with
Jukes–Cantor correction and 1000 bootstraps. The coding
regions of the cpeBA and cpcBA operon were both used in
phylogenetic analyses. Both data sets were separately analy-
sed using the following approach. Phylogenetic analyses
were performed with the neighbour-joining method as well as
with maximum parsimony. Neighbour-joining was performed
with the Kimura two-parameter model for nucleotide evolution
with 1000 bootstraps. Maximum parsimony was used with the
close-neighbour-interchange search algorithm with random
tree addition using 100 bootstraps.
Codon usage in the cpcBA and cpeBA coding regions was
analysed using DnaSP version 4.0 (Rozas et al., 2003).
Nucleotide sequence accession numbers
The sequence data reported in this article have been submit-
ted to the GenBank database under accession numbers:
16SrRNA-ITS clones(EF513279–EF513350);
clones (EF513351–EF513418); cpeBA clones (EF513418–
EF513486); BO8805cpcBA (EF513487); CCY9201cpcBA
(EF513488); CCY9202cpcBA (EF513489); CCY9202cpeBA
(EF513490); Anabaena-like 16S-ITS clone TH298-12-6
(EF530539).
cpcBA
Acknowledgements
We thank M. Laamanen for the opportunity to join cruise
CYANO-04, and the crew of the research vessel Aranda for
help during sampling. We also thankA. Wijnholds-Vreman for
carrying out the flow cytometry analyses. We thank C.
Everroad and A.M. Wood for sharing with us their cpeBA
primer sequences before publication. We gratefully acknowl-
edge the comments of two anonymous referees. M.S. and
J.H. were supported by the Earth and Life Sciences Founda-
tion (ALW), which is subsidized by the Netherlands Organi-
zation for Scientific Research (NWO). T.H and L.J.S.
acknowledge support from the European Commission
through the project MIRACLE (EVK3-CT-2002-00087).
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amorphologicalandmolecular
Supplementary material
The following supplementary material is available for this
article online:
Fig. S1. Full-length neighbour-joining tree of the picocyano-
bacterial ITS sequences.
Fig. S2. Neighbour-joining tree of the partial sequences of
picocyanobacterial cpcBA genes, showing the positions of all
cpcBA clones obtained from the Baltic Sea.
Fig. S3. Neighbour-joining tree of the partial sequences of
picocyanobacterial cpeBA genes, showing the positions of all
cpeBA clones obtained from the Baltic Sea.
Table S1. Comparisonof 16S
GenBank and RDPII databases.
Table S2. Comparison of cpcBA clones with GenBank
databases.
Table S3. Comparison of cpeBA clones with GenBank
databases.
Table S4. Comparison of GC content from cyanobacterial
genomes and the protein coding genes found in these
genomes.
rRNA-ITS cloneswith
This material is available as part of the online article from
http://www.blackwell-synergy.com
188 T. Haverkamp et al.
© 2007 The Authors
Journal compilation © 2007 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 10, 174–188