Introduction
A quarter of a century ago the importance of viruses as the
most abundant biological entity in the oceans (Bergh et al., 1989) and their
role in the material and energy cycles were recognized (Proctor and
Fuhrman, 1990; Suttle et al., 1990). Shortly afterwards, Smith et al. (1992)
conducted the first study on viral distribution and their relationship to
bacteria in the Southern Ocean. Since then, studies on viral abundance and
production or infectivity in the cold, high-latitude marine environments
remained limited or have only recently been accumulating (Bird et al., 1993;
Brussaard et al., 2008b; Evans and Brussaard, 2012; Evans et al., 2009;
Guixa-Boixereu et al., 2002; Higgins et al., 2009; Manganelli et al., 2009;
Marchant et al., 2000; Payet and Suttle, 2008, 2013; Smith et al., 1992;
Steward et al., 1996; Strzepek et al., 2005; Weinbauer et al., 2009). These
observations demonstrate that viruses are ecologically as important in these
cold environments as in the world's other oceans.
Viral lysis of cells converts particulate organic matter into dissolved and
colloidal organic matter, reduces the carbon flow to higher trophic levels
and increases the residence time of carbon and mineral nutrients in the
euphotic zone (Fuhrman, 1999). By this process, called the “viral shunt”
(Wilhelm and Suttle, 1999), heterotrophic bacteria are supplied with
substrate, which finally increases respiration (Bonilla-Findji et al., 2008;
Middelboe and Lyck, 2002). This could reduce the efficiency of the biological
carbon pump, i.e. the process which transforms inorganic to organic carbon,
part of which is then transferred to the deep ocean (Suttle, 2007). The
relative significance of viral lysis and protistan grazing can strongly vary
on temporal and spatial scales (Boras et al., 2009; Fuhrman and Noble, 1995).
This has also been shown for cold marine environments (Boras et al., 2010;
Guixa-Boixereu et al., 2002; Steward et al., 1996; Wells and Deming, 2006).
In about one-third of the World Ocean – including the subarctic northeast
Pacific, the equatorial Pacific and the Southern Ocean, phytoplankton growth
is limited by available iron, resulting in excess dissolved inorganic
phosphorus and nitrogen (Martin and Fitzwater, 1988). In these
high-nutrient–low-chlorophyll (HNLC) regions, bacterioplankton are thought to be
the key player of the “microbial ferrous wheel” (Kirchman, 1996),
i.e. the uptake and remineralization of iron. Bacterioplankton contains more
than twice the iron per carbon unit than eukaryotic phytoplankton, and they can
thereby store up to 50 % of the biogenic iron in the HNLC ocean (Tortell et al., 1996).
Viral activity has a potential impact on nutrient regeneration. Typically,
nutrients released as a result of viral lysis are thought to be organically
complexed, which may facilitate their use by marine plankton (Poorvin et
al., 2004; Rue and Bruland, 1997). Iron released by viral lysis can account
for more than 10 % of ambient Fe concentrations (Gobler et al., 1997) and
thus potentially relieve its limitation in depleted environments.
Furthermore, marine viruses may serve as nuclei for iron adsorption and
precipitation, and they thus represent a significant reservoir of iron in seawater
(Daughney et al., 2004). Despite their key role, viruses are hardly included
in iron enrichment studies. These experiments were originally stimulated by
the “iron hypothesis” (Martin, 1990), which assigns iron a paramount role in
controlling ocean productivity and consequently atmospheric carbon dioxide
concentrations. Only 2 out of 13 iron fertilization experiments so far
performed (Secretariat of the Convention on Biological Diversity, 2009)
report on viral abundance and activity (Higgins et al., 2009; Weinbauer et
al., 2009). Both studies – from the subarctic and Southern Ocean,
respectively – found that viral production was significantly enhanced after iron
fertilization.
Real-time satellite images of chlorophyll during the KEOPS cruise
dating from the first sampling of station A3 (19 Febuary 2005) (MODIS results
provided by CSIRO marine research) and overlaid transects and sampled
stations.
Above the Kerguelen Plateau in the Southern Ocean, the largest HNLC ocean, a
large phytoplankton bloom occurs annually during austral summer. The
continuous supply of Fe and major nutrients from below has been shown to
sustain this massive bloom (Blain et al., 2007). The region off Kerguelen
provides the opportunity to study natural iron fertilization in the Southern
Ocean and to compare it to blooms induced by mesoscale Fe additions. Within
the KEOPS1 project (KErguelen Ocean and Plateau compared Study1, 2005–2007),
we sampled the phytoplankton bloom above the Kerguelen Plateau during its
late successional stage (∼3rd month) along with the surrounding HNLC
waters. The aim of the present study was to assess the role of viruses within
the microbial food web affected by natural Fe fertilization and to elucidate
the possible implications for the final destiny of organic carbon. For this
purpose, we measured viral production, the fraction of infected cells (FIC),
lysogeny and estimated bacterial mortality through viral lysis in the bloom
and surrounding HNLC waters.
Material and methods
Description of the study site
Date, location, mixed layer depth (Zm) and physicochemical
characteristics of all sampled stations.
Date
Station
Latitude
Longitude
Water
Zm (m)
Sampling
T ∘C
Salinity
Chl a
type
depth (m)
µg L-1*
1/19/05
A3-1
50∘38′ S
72∘05′ E
+Fe
52
10
3.5
33.9
0.94
1/19/05
A3-1
50∘38′ S
72∘05′ E
+Fe
52
50
3.3
33.9
1.72
1/19/05
A3-1
50∘38′ S
72∘05′ E
+Fe
52
100
3
33.9
1.38
1/20/05
A11
49∘09′ S
74∘00′ E
+Fe
44
10
3.8
33.9
0.41
1/20/05
A11
49∘09′ S
74∘00′ E
+Fe
44
75
3.3
33.9
0.52
1/20/05
A11
49∘09′ S
74∘00′ E
+Fe
44
200
1.6
34.1
0.21
1/26/05
C11-1
51∘39′ S
78∘00′ E
-Fe
73
10
1.9
33.8
0.19
1/26/05
C11-1
51∘39′ S
78∘00′ E
-Fe
73
80
1.6
33.8
0.29
1/26/05
C11-1
51∘39′ S
78∘00′ E
-Fe
73
200
1.3
34.2
0.01
1/29/05
B11
50∘30′ S
77∘00′ E
-Fe
59
10
2.2
33.8
0.11
1/29/05
B11
50∘30′ S
77∘00′ E
-Fe
59
120
0.5
33.8
0.24
1/29/05
B11
50∘30′ S
77∘00′ E
-Fe
59
200
0.2
34.1
0.03
2/1/05
B5
51∘06′ S
74∘36′ E
+Fe
84
60
2.8
33.9
1.54
2/1/05
B5
51∘06′ S
74∘36′ E
+Fe
84
100
2.6
33.9
1.39
2/2/05
B1
51∘30′ S
73∘00′ E
+Fe
59
60
3.3
33.9
1.29
2/2/05
B1
51∘30′ S
73∘00′ E
+Fe
59
100
2.7
33.9
1.04
2/4/05
A3-4
50∘39′ S
72∘05′ E
+Fe
80
50
3.6
33.9
1.48
2/4/05
A3-4
50∘39′ S
72∘05′ E
+Fe
80
150
1.7
33.9
1.54
2/6/05
C11-2
51∘39′ S
78∘00′ E
-Fe
20
60
1.6
33.8
0.26
2/6/05
C11-2
51∘39′ S
78∘00′ E
-Fe
20
100
0.6
33.9
0.20
2/9/05
C3
52∘43′ S
74∘49′ E
-Fe
42
60
2.5
33.9
0.19
2/9/05
C3
52∘43′ S
74∘49′ E
-Fe
42
100
1.9
33.9
0.17
T: temperature in ∘Celsius; Chl a: total chlorophyll a,
+Fe:
iron-fertilized, -Fe: HNLC waters; * Data are from Uitz et al. (2009)
Sampling was performed in the Indian sector of the Southern Ocean above the
Kerguelen Plateau (49–53∘ S, 72–78∘ E) in austral summer
(18 January–13 February 2005) onboard the R/V Marion Dufresne in
the framework of the project KEOPS (Blain et al., 2008). We sampled a large
phytoplankton bloom dominated by diatoms from its peak to its decline
(Mosseri et al., 2008) (Fig. 1). Satellite images dated the onset of this
bloom more than 2 months before its first visit (Blain et al., 2007).
Hydrographic conditions are described in detail in Park et al. (2008).
Dissolved Fe concentrations in the surface mixed layer were low and similar
on and off the plateau (0.09±0.03 nM) but increased with depth
above the plateau, reaching a mean maximum of 0.35 nM at
500 m. This strong vertical gradient in combination with physical
features such as internal waves and tidal activity sustained the
phytoplankton bloom above the plateau (Blain et al., 2007).
Sampling strategy
Water was collected using General Oceanics 12 L Niskin bottles mounted on a
rosette with a Sea Bird SBE19 plus CTD sensor for salinity, temperature and
oxygen from two to three depths (within and below the surface mixed layer) at the
following stations to cover the centre and borders of each of three transects
(A, B, C): A3, A11, B1, B5, B11, C3 and C11 (Fig. 1, Table 1). The
stations A3 and C11 were considered as the most contrasting stations and
sampled repeatedly. The first sampling of station A3 (A3-1) was done during
the peak of the bloom, and about 2 weeks later station A3 was re-sampled
at a fourth visit (A3-4) during the decline of the bloom. Station B5 was
situated within a new phytoplankton bloom above the Kerguelen Plateau
(Obernosterer et al., 2008). Station A11 was located in iron-fertilized
waters. The annually occurring spring bloom developed prior to our visit,
explaining the low concentrations of Chl a at this site
(Table 1). Station C11 was in HNLC waters off the Kerguelen Plateau and was
sampled twice (Table 1). Stations B11 and C3 were in different environments
with relatively low Chl a contents and will also be considered as
representative of HNLC conditions in this study.
Total chlorophyll a (Chl a and divinyl-Chl a) was measured by
high-performance liquid chromatography (HPLC, Van Heukelem and Thomas, 2001; Uitz
et al., 2009).
Enumeration of viruses and prokaryotes
Subsamples (2 mL) were fixed with glutaraldehyde (0.5 % final
concentration), incubated for 15–30 min at 4 ∘C,
subsequently frozen in liquid nitrogen and stored at -80 ∘C. Within
a few days samples were thawed and viral particles and bacteria were stained
with SYBR Green I (molecular probes) and quantified using a FACScalibur
(Becton and Dickinson) flow cytometer after dilution with TE buffer (10 mM
Tris, 1 mM EDTA, ph =8). For viruses an optimized protocol by Brussaard
(2004) was followed. Viruses and prokaryotes were determined in plots of
90∘ light scatter (SSC) and green DNA fluorescence. Differences in the
green fluorescence and side scatter signature in the cytometric plot allowed
to separate prokaryotes with low nucleic acid content (LNA) from prokaryotes
with high nucleic acid content (HNA) as previously described by Gasol et
al. (1999). Similarly, different size classes of viruses were distinguished
on the basis of green fluorescence. Abundances were calculated by using the
flow rate measurements. Flow-cytometric assessment of viral abundance may
encompass particles other than viruses such as bacterial vesicles (Biller et
al., 2014). However, since bacterial and viral parameters were related
significantly (Table 4), a potential overestimation of viral abundances
probably did not bias the conclusions of the study.
To convert bacterial abundance (BA) to biomass, we used a conversion factor of
12.4 fgCcell-1 for oceanic prokaryotes (Fukuda et al., 1998).
Bacterial production
The incorporation of 3H leucine into protein (Smith and Azam, 1992) was
used to estimate the production of heterotrophic bacteria (BP). At each
depth, 1.5 mL duplicate samples and a trichloroacetic acid (TCA)-killed
control were incubated with a mixture of L-[4, 5–3H] leucine (Amersham,
160 Cimmol-1) and nonradioactive leucine added at final
concentrations of 7 and 13 nM for the upper 100 m, and 13 and
7 nM for the 100–200 m depth layer. Samples were incubated in the
dark at the ambient temperature of the depth where samples were collected.
The incubation time (2–3 h) was tested to satisfy linear
incorporation with time. We checked by concentration kinetics (2.5, 5, 10, 20
and 40 nM) at three stations inside and outside the bloom at 5 and
175 m depths that there was no isotopic dilution. The theoretical conversion
factor of 1.55 kg of Cmol-1 was used to convert leucine
incorporation rates to prokaryotic carbon production (Kirchman, 1993).
Viral production, the fraction of infected cells and the fraction of lysogenic cells
Lytic viral production (VP1), the FIC,
induced viral production (VPi) and the fraction of lysogenic
cells (FLC) were estimated using the virus reduction approach (VRA; Weinbauer
et al., 2010; Wilhelm et al., 2002). The rationale behind VRA is to reduce
viral abundance in order to stop new viral infection. Thus, the viruses
produced originate from already-infected cells. Briefly, bacteria from 200 mL
raw seawater were concentrated using a tangential flow system with a
peristaltic pump (Watson-Marlow 323) equipped with a 0.2 µm
cartridge (VIVAFLOW 50). To obtain virus-free seawater, the
0.2 µm pore-size ultrafiltrate was passed through a 100kDalton
cartridge (VIVAFLOW 50). The bacterial concentrates were brought up to the
original volume with virus-free seawater and incubated in duplicate 50 mL
Falcon tubes in the dark at ±2 ∘C in situ temperature for
24 h. Lysogeny was estimated by adding mitomycin C (SigmaChemical Co.,
Cat. No. M0503, final concentration 1 µgmL-1) to duplicate 50 mL
Falcon tubes in order to induce the lytic cycle in lysogens; untreated
duplicate samples served as controls (Paul and Weinbauer, 2010). Subsamples
(2 mL) for viral and bacterial abundance from each incubation were
taken immediately (t0 samples) and every 3–4 h, fixed with
glutaraldehyde (0.5 % final concentration), incubated for 15–30 minutes
at 4 ∘C, subsequently frozen in liquid nitrogen and stored at
-80 ∘C until enumeration using a flow cytometer as described
above. VPl was calculated as
VPl=(V2-V1)/(t2-t1),
where V1 and V2 are viral abundances and t1 and
t2 the elapsed time. Dividing the number of produced phages by an
estimated burst size (BS, i.e. the number of phages released during the
lysis of a single host) yields the number of lysed cells and thus gives an
estimation of FIC (Weinbauer et al., 2002). FIC was calculated as
FIC=100⋅[V2-V1]/BS/BA,
where BA is the bacterial abundance at t0. The difference in phage
production between the lysogeny treatment and the control is VPi,
calculated as
VPi=(VMC-VC)/(t2-t1),
where VMC and VC are the maximum difference in viral abundance at
corresponding time points in control and mitomycin C treatments,
respectively. Dividing the number of induced phages by BS and the bacterial
abundance at t0 (BA) gives an estimate of the FLC:
FLC=100⋅([VMC-VC]/BS/BA).
Calculations were performed for each replicate separately.
Contact rates
The rates of contact (R, number mL-1 d-1) between viruses and
bacteria were calculated by using the following equations (Murray
and Jackson, 1992).
R=Sh⋅2πd⋅Dv⋅VA⋅BA,
where Sh is the Sherwood number (1.06 for a bacterial community with 10 %
motile cells; Wilhelm et al., 1998), d is the diameter of the
target; VA and BA are the abundances of viruses and bacteria, respectively; and
Dv is the diffusivity of viruses.
Dv=k⋅T/(3⋅π⋅μ⋅dv)=5⋅10-8cm2s-1,
where k is the Boltzmann constant (1.38 × 10-23 J K-1), T is the in situ
temperature (∼ 275 K), μ is the viscosity of water (Pascal
s-1) and dv is the diameter of the viral capsid (∼ 60 nm). The contact rates were divided by in situ bacterial abundance to estimate the
number of contacts per cell on a daily basis.
Average ± SD values of viral and bacterial parameters from
the iron-fertilized and HNLC stations in the upper 200 m water layer and
results from one-way ANOVA for normally distributed data and Kruskal–Wallis
test for nonparametric data. Ranges are given in parentheses. The average
ratio between the two environments is shown, and significant differences are
indicated.
Parameters
Fe-fertilized stations
HNLC stations
Ratio
BA mL-1
3.9 ± 0.9 (1.9-5.3) × 105
2.4 ± 0.7 (1.3-3.8) × 105
1.7***
BP µgC L-1 d-1
1.1 ± 0.7 (0.1-2.5)
0.3 ± 0.2 (0.1-0.7)
4.1***
VA mL-1
9.9 ± 3.6 (3.4-14.2) × 106
4.7 ± 1.4 (3.1-7.4) × 106
2.1 *
VPl mL-1 d-1
59.0 ± 47.1 (9.9-117.9) × 106
14.5 ± 7.4 (6.0-25.6) × 106
4.1*
VPi mL-1 d-1a
50.9 ± 46.4 (2.8–125.5) × 106
13.9 × 106
3.7
FIC %
22 ± 17 (4–47)
12 ± 7 (3–23)
1.8
FLC %b
10 ± 14 (1–31)
3 ± 2 (1–4)
4.0
Prophage replication rate
18.1 ± 29.2 (0.6–61.5) × 103
1.0 ± 1.2 (0.2–2.4) × 103
18.5
rate mL-1 d-1b
R cell-1 d-1
29.4 ± 11.1 (10.3-43.0)
14.2 ± 4.4 (9.3-22.4)
2.1*
lysed bacteria mL-1 d-1
5.4 ± 4.1 (0.8-10.3) × 105
1.1 ± 0.6 (0.4-2.1) × 105
4.9*
VMM %
72 ± 72 (8–202)
27 ± 19 (6–58)
2.6
VA: viral abundance; VPl: lytic viral production; VPi: induced
viral production; FIC: fraction of infected cells; FLC: fraction of
lysogenic cells; BA: bacterial abundance; BP: bacterial production; R: viral
contacts per cell and day; VMM: virus-mediated bacterial mortality.* P < 0.05, ** P < 0.001, ***
P < 0.0001.a Detected in 6 out of 15 essays, only 1 in HNLC waters.
b Detected in 7 out of 15 essays.
Depth profiles of bacterial (a) and viral abundance (b) in the
Kerguelen study area. Full symbols indicate Fe-fertilized sites; open
symbols indicate HNLC waters.
Bacterial mortality
To obtain the rate of cell lysis, viral production corrected for in situ bacterial
abundance was divided by an estimated BS following the approach of
Wells and Deming (2006), i.e. dividing the number of viruses
produced during the first hours of incubation by the concomitant decline of
bacterial abundance. The number of lysed bacteria was converted into carbon
by the factor of 12.4 fg C cell-1 (Fukuda et al., 1998).
The fraction of bacterial mortality through viral lysis (VMM) was calculated
following the model by Binder (1999).
VMM=FIC/LN(2)⋅(1-0.186-FIC)
Statistics
Normal distribution of data was checked using the Shapiro–Wilk W test.
Differences between different trophic situations were analysed by the
Kruskal–Wallis test for nonparametric data and by one-way ANOVA (analysis of variance) for
normally distributed data. Spearman rank correlation for non-normally
distributed data was applied. Significance was considered for P < 0.05.
Results
Bacterial and viral abundances
From surface water down to 200 m, BA was on average 1.7 fold higher within
the Fe-fertilized (3.9 × 105 mL-1) than in HNLC waters (2.4 × 105 mL-1,
Kruskal–Wallis test, P < 0.0001, Table 2; Fig. 2). Similarly, viral abundance (VA) averaged 9.9 × 106 mL-1 at the
Fe-fertilized stations and was twice as high as in the HNLC environments
(4.7 × 106 particles mL-1, Kruskal–Wallis test, P < 0.05,
Table 2). VA ranged from 3.1 to 14.2 × 106 mL-1, with the highest
values found at the main bloom station A3 and the lowest value detected in
the deep layer of the HNLC station B11. Viruses were homogeneously
distributed with depth at the HNLC stations. The virus-to-bacteria ratio
(VBR) ranged from 11 to 34 and averaged 21 without significant differences
between stations or trophic situations.
In situ BP and viral parameters from all virus reduction experiments.
Station
Water type
Depth (m)
BP
VPl
FIC %
FLC %
VMM %
µgC L-1 d-1
106mL-1d-1
A3-1
+Fe
10
2.5
16.7
12
31
25
A3-1
+Fe
50
1.9
15.6
6
6
12
A3-1
+Fe
100
2.4
56.4
10
ND
19
A3-4
+Fe
50
1.2
105.6
34
ND
106
A3-4
+Fe
150
0.3
82.4
36
ND
115
B1
+Fe
60
1.7
117.9
41
ND
147
B1
+Fe
100
0.2
115.6
47
3
202
B5
+Fe
100
1.1
11.2
4
1
8
A11
+Fe
200
0.3
9.9
7
ND
14
B11
-Fe
10
0.2
16.3
14
ND
29
B11
-Fe
120
0.3
25.6
23
1
58
B11
-Fe
200
0.1
6.0
11
3
24
C3
-Fe
60
0.2
20.1
6
no exp
11
C3
-Fe
100
0.4
16.7
22
no exp
55
C11-1
-Fe
10
0.4
11.2
8
ND
17
C11-1
-Fe
80
0.7
9.6
9
4
17
C11-1
-Fe
200
0.1
7.5
6
ND
12
C11-2
-Fe
60
0.3
25.1
20
no exp
47
C11-2
-Fe
100
0.2
6.4
3
no exp
6
VPl: lytic viral production; FIC: fraction of infected cells; FLC: fraction
of lysogenic cells; VMM: virus-mediated bacterial mortality; ND: not
detectable; no exp: no lysogen induction essay.
Lytic viral production from the Fe-fertilized (a) and HNLC
(b) stations. Values are the averages of duplicates, and error bars indicate the
minimum and maximum values. When not visible, error bars are within the
width of the line.
Contact rates
Contact rates were significantly higher at the Fe-fertilized stations than
in HNLC waters (Kruskal–Wallis test, P < 0.05, Table 2). At the
Fe-fertilized stations, on average 29.4 ± 11.1 viruses contacted a
bacterial cell per day, while in the HNLC waters contact rates were 14.2 ± 4.4 viruses cell-1 d-1, with the highest values at the
bloom station A3 and the lowest at the HNLC station B11 in accordance to the
highest and lowest viral abundances, respectively (see Fig. 2).
Bacterial production, viral production, fraction of infected
cells and lysogeny
Bacterial production ranged from 0.1 to 0.7 µgC L-1 d-1 at
the HNLC stations and from 0.1 to 2.5 µgC L-1 d-1 at the
Fe-fertilized stations (Table 2). The highest values were found throughout
the depth profile of the main bloom station A3-1 and the lowest values were
measured between 150 and 200 m at the HNLC stations. Despite the wide range
of values, BP was on average 4 times higher at the Fe-fertilized stations
than at the HNLC stations (Kruskal–Wallis test, P < 0.0001, Table 2).
Initial virus abundance in the VRA was 45 ± 25 % (11–88 %) of
in situ abundance. The recovery efficiency for bacteria in the VRA was on average
26 ± 18 % (5–83 %).
Nonparametric Spearman rank correlation matrix for chlorophyll a, bacterial
and viral parameters from the fertilized (n= 8–9, except for BP–BA–Chl a:
36–41) and HNLC stations (n= 10, except for BP–BA–Chl a: 23–31). Bold
numbers are significant r values (* P < 0.05, ** P < 0.001,
*** P < 0.0001).
Chl a
BA
BP
VA
VPl
Fe-fertilized
BA
0.209
BP
0.243
0.633***
VA
0.357
0.548
0.762*
VPl
0.083
0.476
-0.050
0.310
FIC
-0.183
0.333
-0.267
0.095
0.900**
HNLC
BA
0.688*
BP
0.380*
0.635*
VA
0.164
0.576
0.515
VP
0.426
0.746*
0.406
0.273
FIC
0.168
0.304
0.310
-0.249
0.608
BA: bacterial abundance; BP: bacterial production; VA: viral abundance;
VPl: lytic viral production; FIC: fraction of infected cells.
Lytic viral production corrected for in situ bacterial abundance
averaged 59.0 × 106 mL-1d-1 in the naturally Fe-fertilized
patch, compared to 14.5 × 106 mL-1 d-1 in the HNCL
environments. This 4.1-fold difference was significant (Kruskal–Wallis test,
P < 0.05, Table 2). Induced viral production (VPi) was detected
in four out of nine stations (three fertilized stations and one HNLC station, Table 3) and
averaged 44.8 ± 44.2 × 106 mL-1 d-1 (Table 2). VPl
at the main bloom station A3 at 50 m increased from the first visit (15.6 × 106 mL-1 d-1)
to the fourth visit (105.6 × 106 mL-1 d-1) by a factor of 6.8, when the decline of the bloom was sampled. BS
estimates ranged from 36 to 261 viruses per bacterial cell, with mean values
of 115 ± 74 viruses per bacterial cell in the bloom and 139 ± 77 viruses
per bacterial cell in the HNLC waters.
Although FIC values at the Fe-fertilized stations almost doubled those in
HNLC waters, this difference between environments was not significant
(Kruskal–Wallis test, Table 2). Average values for duplicate assays ranged
from 4 to 47 % (average: 22 %) in fertilized waters and from 3
to 23 % (average: 12 %) in HNLC waters. Lysogenic infection of
bacterioplankton could be detected only in 7 out of 15 lysogenic phage
induction essays and ranged from 1 to 31 % in fertilized waters and from
1 to 4 % in the HNLC environment.
At the fertilized stations, on average 5.4 ± 4.1 × 105 bacteria mL-1 d-1
were lysed, 5 times more than at the HNLC stations (1.1 ± 0.6 105 bacteria mL-1 d-1, P < 0.05,
Kruskal–Wallis test, Table 2). The resulting virus-mediated loss of
bacterial standing stock was on average 44 ± 24 % per day in the
HNLC waters and more than twice as high at the fertilized stations, although
this was not significant (104 ± 76 % d-1, Kruskal–Wallis test,
Table 2). The fraction of bacterial mortality through viral lysis (VMM)
following the model by Binder (1999) averaged 72 ± 72 % in the
bloom and 27 ± 19 % at the HNLC sites (Kruskal–Wallis, ns, Table 2).
Relation between the different parameters
Spearman rank correlation coefficients ρ for chlorophyll a, viral and
bacterial parameters from HNLC and bloom stations are shown in Table 4. BA
and BP correlated positively throughout trophic situations, but only in HNLC
waters did BA and BP increase with Chl a. In the fertilized waters VA correlated
positively with BP, while in HNLC waters VP increased with BA. Only in these
waters did VPl correlate significantly and positively with the fraction of
infected cells (Table 4).
Discussion
Viruses were the dominant mortality factor of bacteria during the late stage
of a phytoplankton bloom induced by natural iron fertilization in the
Southern Ocean (second visit to A3) but accounted for a small part of
bacterial mortality within a new bloom (station B5, Table 3). Additionally,
observations from the early bloom phase showed that heterotrophic
nanoflagellates (HNFs) dominated the loss of BP, and viruses accounted for
only 10 % of bacterial mortality (Christaki et al.,
2014). These seasonal dynamics point to a switch from an efficient
functioning of the microbial food web during the onset of the phytoplankton
bloom to a microbial food web where organic carbon is mainly processed by
the viral shunt. The increase in virus-mediated release of dissolved organic
carbon over time has important consequences for the fate of part of the
photosynthetically fixed carbon and reduces its transfer to higher trophic
levels and export.
Comparison of viral data within high-latitude marine
environments
Viral production rates in the present study match well the data obtained
from the Australian sector of the Southern Ocean (Evans et
al., 2009) and are within the range of VP rates from an iron-induced bloom
in the subarctic Pacific (Higgins et al., 2009). However, our
VP rates are high when compared to data from an artificial
iron-fertilization experiment in the Southern Ocean
(Weinbauer et al., 2009) or those from other high-latitude marine environments, i.e. the Arctic Sea (Steward et
al., 1996; Boras et al., 2010) (Table 5). Differences between studies could
be due to spatiotemporal variations of VP; however, it is also conceivable
that differences between methods (Helton et al., 2005; Weinbauer et al.,
2009; Winget et al., 2005) have contributed to the variability of reported
VP data.
Comparison of viral abundance (VA) and production (VP),
virus-mediated bacterial mortality (VMM) and % loss of bacterial
production (% BP) and standing stock per day (% SS d-1) with
literature data from other polar/subpolar environments.
Location
Depth (m)
Method
VA (109L-1)
VP (109L-1d-1)
VMM (108L-1d-1)
% BP
% SS d-1
Source
SO : Fe-fertilized
0–150
VRA
3.4–14.2 (9.9 ± 3.6)
9.9–117.9 (59.0 ± 47.1)
0.8–10.3 (5.4 ± 4.1)
8–202 (72)
104
Present study
SO : HNLC
0–200
VRA
3.1–7.4 (4.7 ± 1.4)
6.0–25.6 (14.5 ± 7.4)
0.4–2.1 (1.1 ± 0.6)
6–58 (27)
44
Present study
Antarctic
0–100
VDR
1–74 (13 ± 10.4)
> 100
Guixa-Boixereu et al. (2002)
SO-subantarctic
10
VRA
6.1–26
17.5–216.3
3.6–43.3
43–63
40–130
Evans et al. (2009)
SO
5–200
VRA
0.5–7.6
0.4–16
0–8.7
0–72
Evans and Brussaard (2012)
SO : Fe patch
10–150
VRA
2.3–7(4.3 ± 5.5)
0.9–3.6(1.9 ± 0.5)
41–172 (104)*
Weinbauer et al. (2009)
SO : HNLC
10–150
VRA
1.4–2.5(2.1 ± 2)
0.3–0.8(0.6 ± 0.1)
14–70 (39)*
Weinbauer et al. (2009)
Arctic
0–10
TEM
2.5–36
0.2–4.6 (2)
2–36 (13)
Steward et al. (1996)
North waters
0–200
TEM
1.36–5.55(3.3 ± 1.6)
0.1–1.3
6–28
Middelboe et al. (2002)
Arctic
0–230
VDA
1.4–4.5(2.8 ± 1.3)
0.1–1.9
0.28–0.72
Wells and Deming (2006)
Subarctic Fe patch
0–10
TEM/VRA
40.5
30–200
90 ± 25
7.4
Higgins et al. (2009)
Subarctic outside
0–10
TEM/VRA
35.7
30–200
25.8 ± 6.1
7.2
Higgins et al. (2009)
Arctic
0–100
VRA
0.32–7.28
0.1–4.2
2–24 (9)
2–30
Boras et al. (2010)
Canadian Arctic Shelf
2–56
VRA
2.7–27
0.03–7.7
0.02–4.3
31–156
1.4–29
Payet and Suttle (2013)
SO: Southern Ocean; VDR: viral decay rates; TEM: frequency of visibly
infected cells by transmission electron microscopy; VDA: Virus dilution
approach; VRA: virus reduction approach. * Using BP in the VRA.
In the present study, the burst size averaged 128 viruses per bacterial cell
throughout the experiments. This value is high compared to two studies from
the Southern Ocean where measured BS was about 40 viruses per bacterial cell
(Strzepek et al., 2005; Weinbauer et al., 2009) and to a study in early
spring above and off the Kerguelen Plateau where BS evaluated with TEM
observations varied from 6 to 88 viruses per bacterial cell (mean ± SD,
22 ± 15; Christaki et al., 2014). These different
BS could be inherent to the study regions or due to the used method, i.e.
estimating BS by an increase in VA and a decrease of BA in the VRA
(Wells and Deming, 2006), which can result in increases of BP and thus
potentially increase VP (Helton et al., 2005; Weinbauer et al.,
2009; Winget et al., 2005). However, Steward et al. (1996) found BS as high
as 270 for areas of high productivity in the Chukchi Sea, and studies from
the North Sea have reported 100 phages produced per lysed bacterium
(Bratbak et al., 1992).
Viruses in HNLC waters versus a phytoplankton bloom induced by
natural iron fertilization
Viral distribution during the late stage of the phytoplankton bloom above
the Kerguelen Plateau as well as its relation to the bacterial hosts (e.g. VBR) and
phytoplankton biomass is extensively reported, discussed and compared to
existing data from similar regions in Brussard et al. (2008b). During the
late bloom stage, average viral abundance at the bloom stations was twice as
high as in HNLC waters (Brussaard et al., 2008b), while during the early
bloom viral abundance remained unaffected (Christaki et
al., 2014). Data from mesoscale Fe fertilization experiments showed that
viral abundance inside the fertilized patch was higher
(Weinbauer et al., 2009) or not substantially different
from outside (Higgins et al., 2009). The authors of the latter
study explained the lack of differences between inside and outside the
fertilized patch with the time-lag of the microbial response to the induced
bloom, since viral abundance and production were only increasing at the end
of their observations (day 12 after iron fertilization). This observation is
in line with the increase in viral abundance and activity on a seasonal
scale in the Kerguelen bloom (Christaki et al., 2014).
The present study observed a mature bloom and could thus track a period with
a more pronounced microbial response. The 4-times-higher viral production at
the naturally Fe-fertilized study sites compares well to the 3-fold increase
in phage production after an induced bloom through iron addition
(Weinbauer et al., 2009). Interestingly,
Christaki et al. (2014) reported higher VP rates already
at the early bloom stages. Thus, there is a trend of higher viral production
in the iron-fertilized bloom compared to the surrounding HNLC waters
consistent with existing data on iron fertilization
(Weinbauer et al., 2009). Complementary, within the
bloom, HNFs did not seem to control enhanced bacterial production rates, while
in HNLC waters HNFs consumed 95 % of bacterial production
(Christaki et al., 2008). These studies suggest that
there is a switch towards viral lysis dominating in the bloom situations.
More generally, this is in accordance with previous studies across
environments which showed viral influence to be more important in more
eutrophic waters (Weinbauer et al., 1993; Steward et al.,
1996), particulary in the cold environments such as the Arctic
(Steward et al., 1996) or the Southern Ocean, where Guixa-Boixereu
et al. (2002) found that viruses were responsible for the entire bacterial
mortality. The high virally induced mortality in the bloom could also be a
reason for low biomass accumulation, despite the high BP. We calculated
carbon release rates through viral lysis in two ways: first, based on VP,
and, second, based on VMM related to FIC by a model of Binder (1999)
(Table 6). Independent of the absolute values, which were 1 order of
magnitude higher in the former than in the latter way (Table 6), C release
through viral lysis was 5–8 times higher in the Fe-fertilized than in the
surrounding HNLC waters.
C and Fe release rates (L-1 d-1) through viral lysis
calculated from VP (12.4 fg C cell-1, Fukuda et al., 1998)
and from FIC following the model by Binder (1999) using bacterial iron quota
of 7.5 µMol Fe mol C-1 (Tortell et al., 1996). Averages
are given in parenthesis.
Release based on VP
Release based on FIC
pmol Fe L-1 d-1
µmol C L-1 d-1
pmol Fe L-1 d-1
µ mol C L-1 d-1
Fertilized stations
0.60–7.97 (4.18 ± 3.15)
0.08–1.06 (0.56 ± 0.42)
0.03–1.58 (0.42 ± 0.49)
0.003–0.21 (0.06 ± 0.07)
HNLC stations
0.28–1.60 (0.86 ± 0.43)
0.04–0.21 (0.11 ± 0.06)
0.004–0.12 (0.05 ± 0.05)
0.001–0.02 (0.01 ± 0.01)
Ratio
4.9*
4.9*
7.9*
7.9*
* Values are significantly higher in the Fe-fertilized than in the HNLC
stations (Kruskal–Wallis, P < 0.05).
The percentages of lysogens (i.e. bacteria containing temperate viruses)
were more variable in the fertilized (0–31 %) than in the HNLC waters
(0–4 %) but not significantly different between environments. Consistent
with our study, Weinbauer et al. (2009) did not find
differences inside and outside the iron-enriched patch during a
fertilization experiment in the Southern Ocean. The proportion of the
lysogenized bacterial population can vary extensively, for example, from 1.5
to 11.4 % in the Gulf of Mexico (Weinbauer and Suttle, 1996), from 4 to
38 % in the Canadian Arctic Shelf (Payet and Suttle, 2013) and
from 0 to 100 % in Tampa Bay, Florida (Williamson et al.,
2002). According to conceptual models, lysogeny should occur preferentially
in environments where the contact rate between infective phages and hosts
is too low to sustain the lytic lifestyle (Paul et
al., 2002). Empirically, this has been proven by Weinbauer et al. (2003),
who studied the frequency of lysogenic cells in contrasting marineenvironments and found the highest incidence of lysogens in deep waters
where the host abundance is typically low, and by Payet and Suttle (2013)
during a seasonal cycle study in the Arctic where lysogenic infection
prevailed in periods of low system productivity. Apparently, this was not
the case in the present study as the fraction of lysogenic cells was not
different between trophic situations although bacterial and virus abundances
and contact rates were significantly lower at the HNLC than at bloom
stations (Table 2). It was suggested that enhanced growth causes temperate
viruses to enter the lytic cycle (Wilson and Mann, 1997). Both filtration
and incubation could have stimulated bacterial production in the virus
reduction approach (Weinbauer et al., 2009) and
consequently induced prophages in the mitomycin C treatment controls.
Additionally, it has to be stressed that mitomycin C used as an inducing
agent of lysogens in the natural bacterial communities may not induce all
prophages and be toxic to some bacteria (Paul, 2008; Paul and Weinbauer,
2010). Thus, the apparent low incidence of lysogenic infection, particularly
in HNLC waters, might be an artefact. However, it could also be that the
study period was not long enough to induce potential changes of lysogenic
infection. In addition, our study provides no evidence that lysogens were
induced by relieving iron addition.
Simple sketch of the carbon and nutrient flow through the
microbial food web in the Fe-fertilized (left) and HNLC waters (right).
Arrow thickness represents the relative importance of factors controlling
the size of each pool of the microbial food web.
Role of viruses for sustaining phytoplankton productivity by
Fe supply
Bacteria store about 50 % of the biogenic iron in HNLC areas
(Tortell et al., 1996) and the mode of bacterial mortality will
affect the way of Fe regeneration and bioavailability (Kirchman,
1996; Mioni et al., 2005; Strzepek et al., 2005). While viral lysis liberates
organically complexed iron, which may be assimilated rapidly, grazing mainly
sets free inorganic Fe (Gobler et al., 1997; Poorvin et
al., 2004). Assimilation studies with a model heterotrophic bacterium
demonstrated that Fe in the virus-mediated cell lysates was more
bioavailable than the siderophores produced by the same cells, supporting the
importance of virus-mediated Fe regeneration in marine surface waters
(Poorvin et al., 2011). We calculated Fe release rates in
two ways: first, based on VP, and, second, based on VMM related to FIC by a
model of Binder (1999). The former resulted in average iron
regeneration rates due to viral lysis of bacteria of 4.18 and 0.86 pMol Fe d-1
in fertilized and HNLC waters, respectively, while the latter
resulted in more realistic values ranging from 0.03 to 1.58 pM d-1
(average: 0.42 ± 0.49 pM d-1) in iron-fertilized waters and
from 0.004 to 0.12 pM d-1 (average: 0.05 ± 0.05 pM d-1) in HNLC waters (Table 6). These values are similar to those found
in the Southern Ocean (Evans and Brussaard, 2012) and an iron-induced bloom
(ibid., Weinbauer et al., 2009) but low compared to other
studies. Poorvin et al. (2004) reported Fe regeneration rates of
19.2–75.5 pM d-1 in HNLC waters off Peru, and Strzepek et al. (2005) found a high range over 2 orders of magnitude of
0.4–28 pM d-1 in HNLC waters southeast of New Zealand. Fe regeneration rates
are calculated from virally induced bacterial loss, which is inversely related
to burst size. When taking into account that the calculated burst size in
the present study was 5 times higher than the assumed BS in the study of
Poorvin et al. (2004), the values in the present study compare
well to data on Fe regeneration through viral activity from artificial
fertilization experiments and other environments.
Significantly more iron was released by viral lysis within the naturally
Fe-fertilized bloom than at the HNLC stations (P < 0.05,
Kruskal–Wallis, Table 6). The concentration of dissolved iron in the surface
mixed layer on and off the Kerguelen Plateau were typical for the open
Southern Ocean and averaged 90 ± 34 pM (Blain et al., 2007), and the
estimated biogenic iron pool at the main bloom station equaled 80 ± 9 pM
(Sarthou et al., 2008). Taking into account the total Fe demand
of the producers within the bloom of 6.04 ± 0.62 pM d-1
(Sarthou et al., 2008), the remobilization of iron through viral
lysis above the Kerguelen Plateau following the model by Binder (1999)
accounts for up to 26 % of the demand of the producers, and this appears to
be a non-negligible iron source for sustaining plankton productivity.
Implications for carbon cycling and sequestration
Bacterial biomass and production were increased respectively from 287 to 797 mg C m-2 and from 23.5
to 304 mg C m-2 d-1 between the HNLC (C11) and the iron-fertilized (A3) areas
(Christaki et al., 2008). Bacterial abundance and
production are often correlated with viral abundance and production. Thus,
elevated bacterial activity in the (natural or induced) bloom could explain
the enhanced viral abundance and production found in previous in situ Fe enrichment
studies (Arrieta et al., 2000; Higgins et al., 2009; Weinbauer et al.,
2009).
The finding of higher viral lysis rates of bacteria in the sites of natural
Fe fertilization, where HNF grazing could only explain a small fraction of
bacterial mortality (Christaki et al., 2008), has
important implications for the carbon cycling. Due to enhanced viral lysis,
less carbon will be transferred to larger members of the food web but
becomes again part of the DOM pool (Middelboe et al., 1996).
This viral shunt should result in elevated bacterial production and
respiration; thus more CO2 would be produced and less carbon
sequestrated. Experimental studies indicate that most of the lysis products
belong to the labile fraction of DOM and are consequently rapidly degraded
(Weinbauer et al., 2011). By the transformation of bacterial biomass
into DOM, viruses have the effect of retaining carbon and nutrients in the
photic zone (Suttle, 2007). Thus, viral lysis of bacteria could
short-circuit the biological pump
(Brussaard et al., 2008a).
However, there are other possible scenarios. For example, microbial activity
converts part of the organic matter into recalcitrant DOM (RDOM) that is
resistant to microbial utilization and can persist in the interior of oceans
for up to thousands of years. The detailed role of viral lysis in this new
concept of the microbial carbon pump (MCP) (Jiao et al.,
2010) is still poorly known. However, a compilation of data suggests that
viral lysis increases the DOM pool and the ratio of recalcitrant vs. labile
organic matter (Weinbauer et al., 2011). Thus, enhanced viral lysis
of bacteria due to Fe fertilization could result in an enhanced carbon
sequestration not related to the biological pump.
Rates of bacterial production ([3H] leucine incorporation) and
respiration (< 0.8 µm size-fraction) were 5–6 times higher in
the bloom at station A3 than those in surrounding HNLC waters, indicating
that heterotrophic bacteria within the bloom processed a significant portion
of primary production, with most of it being rapidly respired
(Obernosterer et al., 2008), fuelling the CO2 pool. This
scenario is coherent with the finding of small particulate organic carbon
export fluxes to depth necessary for long-term sequestration (de Baar et
al., 2005; Street and Paytan, 2005), despite the role of iron in regulating
primary productivity. However, most in situ mesoscale iron enrichment experiments
so far performed in the HNLC regions did not last long enough to follow the
termination of the bloom (Buesseler and Boyd, 2003; Smetacek et al.,
2012). In the present study, we sampled a bloom in its late successional
stage and could thereby track the fate of fixed carbon by an iron-fertilized
phytoplankton bloom. Figure 4 shows a simple sketch to highlight the
importance of each compartment of the microbial food web in the transfer of
organic material in an Fe-fertilized bloom compared to HNLC waters.
Sequestration of material in viruses, bacteria and dissolved matter may lead
to stronger retention of nutrients in the euphotic zone in systems with high
viral lysis rates of bacteria, because more material remains in these small,
non-sinking forms. This could be of major importance for large-scale iron
fertilization of ocean regions as a means of enhancing the ability of the
ocean to store anthropogenic CO2 and mitigate 21st-century climate
change.