Viruses and Protists Cause Similar Bacterial Mortality in Coastal Seawater

Viruses and Protists Cause Similar Bacterial Mortality in Coastal SeawaterAuthor(s): Jed A. Fuhrman and Rachel T. NobleSource: Limnology and Oceanography, Vol. 40, No. 7 (Nov., 1995), pp. 1236-1242Published by: American Society of Limnology and OceanographyStable URL: http://www.jstor.org/stable/2838680 .

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Limnol Oceanogr., 40(7), 1995, 1236-1242 ? 1995, by the American Society of Limnology and Oceanography, Inc.

Viruses and protists cause similar bacterial mortality in coastal seawater

Jed A. Fuhrman and Rachel T. Noble Department of Biological Sciences, University of Southern California, Los Angeles 90089-0371

Abstract Mesocosms filled with 80 liters of coastal seawater from Santa Monica, California, were used twice (June

and November) to budget bacterial production and loss, as well as to assess the relative significance of viral lysis and protist grazing in bacterial mortality. Bacterial abundance was - 6 x 109 cells liter-' in June and 2 x 109 in November, with viral abundances 2 x 1010 particles liter-' in June and 1.5 x 1010 in November. Incorporation of [3H]thymidine and leucine yielded essentially identical production estimates and allowed calculation of total bacterial mortality in these closed systems. Bacterial growth rates were 1-2 d-' in June and 1-3 d- I in November. Three independent lines of evidence indicated that bacterial mortality attributed to grazing by protists was about equal to that attributed to viruses: size fractionation of disappearance of labeled DNA, with a 50% reduction after protists were removed; comparison of protist grazing rates estimated with fluorescently labeled bacteria and virus production-based bacterial lysis rates, with 40-50% of the total ascribed to viruses; and model-based interpretation of the 3.3-4.6% of bacteria visibly infected with assembled intracellular viruses, suggesting that 24-66% of loss is due to infection. Redundant production and loss measurements as well as the independent loss process estimates agreed within 30%, yielding a reasonably balanced budget. We believe the loss of bacteria to viruses reflects a significant dissipation of energy in this ecosystem and that viruses and protists contribute similarly to bacterial mortality.

It is well established that a significant fraction of the total carbon flux in marine planktonic systems passes through free-living bacteria (Azam et al. 1983; Cole et al. 1988; Fuhrman 1992). It was earlier thought that virtually all of this production passes on to higher trophic levels via protists, primarily small flagellates, grazing on bacteria (see McManus and Fuhrman 1988; Pace 1988). However, in recent years it has been recognized that infection by viruses may contribute significantly to bacterial loss (Bergh et al. 1989; Proctor and Fuhrman 1990; see also Fuhrman and Suttle 1993). The action of bacterial viruses in planktonic systems can have several far-reach- ing impacts on the system as a whole. It has been theorized that viral infection of bacteria leads to a "futile cycle" or "short circuit" of C flow between the bacterial, viral, and dissolved organic C (DOC) compartments, with substan- tial respiratory losses as the cycle turns (Bratbak et al. 1990; Fuhrman 1992). As an example of the potential impact of bacterial vi-

ruses, a quantitative model of such a cycle embedded in a steady state food web suggested that inclusion of a bacterial loss term from viruses equivalent to the loss from protists leads to 27% increases in bacterial production and respiration but a 37% decrease in export of bacterial carbon to protistan grazers and a 7% decrease in mac- rozooplankton production (Fuhrman 1992). Thus, viral activity shifts more production and respiration into the bacteria and away from other heterotrophs. Viruses also

Acknowledgments Thanks to Robin M. Wilcox, Alison A. Davis, and Ximena

A. Hernandez for assistance with measurements and ideas for improvements on the mesocosms and to M. Weinbauer for suggestions regarding the manuscript.

This work was supported by NSF grant OCE 92-18234 and USC Sea Grant.

affect the species composition and diversity of the bacterial community because viruses are usually highly specific for certain hosts (Fuhrman and Suttle 1993), but a given protist can graze on a variety of bacterial species. Overall, the impact of the viruses on these food-web processes depends on how the bacterial losses from viruses compare to those from protists.

Recent studies have attempted to quantify the extent of bacterial mortality caused by viruses and the relative significance of viruses and protists to the loss of bacteria; the results have suggested losses from viral lysis are in the same range as those attributed to protist grazing (Proc- tor and Fuhrman 1990, 1992; Suttle et al. 1992). How- ever, these studies rely on models or other indirect measures, and individual studies have each used only a single method and have been unconfirmed by other means; as a result, these previous studies are not as convincing as they might have been. Also, Bratbak et al. (1992) tried to balance bacterial production against estimates of loss due to viruses, but their study yielded loss estimates that were inexplicably several times higher than production. Clearly, there is no consensus on this issue. Our purpose was to make as complete a budget as possible of bacterial growth and loss by independent, redundant measurements and to provide direct comparisons of losses at- tributable to viruses and protists. We found that such budgets balanced reasonably well and that viruses and protists were responsible for similar amounts of bacterial loss in the southern California coastal environment we examined.

Methods

Sample collection -Samples were collected by acid- rinsed bucket from Santa Monica Pier (34?05'N,

1236



Causes of bacterial mortality 1237

11 8?30'W), transported to our lab, and put (within 1 h) into a Nalgene polyethylene 80-liter carboy that had been rinsed with 5% HCl and then rinsed several times with seawater. A long-shaft plastic propeller (3-cm diam) was mounted through the cap and rotated at 200-300 rpm in the middle of the carboy. The carboy was placed outside in a seawater-temperature-controlled polyethylene bath in full sunlight. Mesocosm 1 was started on 15 June 1993 at 1745 hours and mesocosm 2 on 17 November 1993 at 1200 hours. Samples were removed through a medical- grade silicone siphon that was cleared of several tubing volumes before each use.

Bacterial growth rates-Thymidine and leucine incorporation methods were modified from Fuhrman and Azam (1982), Kirchman et al. (1985), and Simon and Azam (1989). At each time point, duplicate 42-ml samples and 1% Formalin-killed controls were subsampled into well- rinsed sterile 50-ml polypropylene tubes (VWR brand). Samples were inoculated with 5 nM [methy/-3H]thymidine or [3,4,5-3H]leucine (both from Dupont New England Nuclear). Subsamples were incubated in the lab at seawater temperature in a fluorescent-lighted (during day- time, dark at night) incubator. After 30-min incubations, duplicate 20-ml samples from each tube were passed through HAWP Millipore filters (mixed cellulose acetate and cellulose nitrate, 0.45-,um nominal pore-size) in cold stainless steel filtration funnels in a 10-place manifold (Hoefer Scientific). Filtration valves were then closed, and 2 ml of ice-cold 5% trichloroacetic acid (TCA) was added. After 2 min, the TCA was filtered through, and the filters and funnels were rinsed 3 times with 1 ml of cold 5% TCA; the funnels were then removed, and the edge of the filters was rinsed 3 times with 1 ml of 5% TCA. Filters were placed in a glass 20-ml vial, and 1 ml of 1 N HCl was added; the filters were heated to 90-1 00?C for 1 h (to hydrolyze the nucleic acids). After the vials cooled, 5 ml of Ecoscint (National Diagnostics) was added, and the samples were counted by liquid scintillation with quench correction (Packard). Conversion factors used to calculate production from the moles of thymidine or leucine incorporated were the averages reported by Fuhrman and Azam (1982) at 2 x 1018 cells produced per mole thymidine incorporated and those reported by Chin-Leo and Kirchman (1988) and Kirchman (1992) at 1.5 x 10'7 cells produced per mole leucine incorporated.

Virus counts-Viruses were counted by ultracentrifug- ing (120,000 x g, 3 h, 20?C) 4-ml seawater samples onto carbon-stabilized Formvar-coated 200-mesh copper grids (B0rsheim et al. 1990; Cochlan et al. 1993) and subse- quently staining the grids with 1% uranyl acetate for 30 s. Viruses were counted on a JEOL 100 CXII transmission electron microscope (TEM), and taper corrections were implemented into final calculations (Suttle et al. 1992). Viruses were typically counted at 27,000 x and the bacteria at 10,000 x at 80 keV. The percentage of bacteria infected with visible viruses was determined two ways. In the first method, thin sections were prepared from bacteria on filters that had been preserved and embedded,

then sectioned, as described by Hennes and Simon (1995). This method involves filtering 100 ml of preserved buf- fered (0.05 M sodium barbital, 0.025 M sodium acetate, pH 8.2, 1% glutaraldehyde) seawater onto a 13-mm-diameter Irgalan black-stained Sartorius cellulose-nitrate filter with the filtration area restricted to 20 mm2 to con- centrate the bacteria in one location. The filter is then enrobed in ultralow-melting agarose, sliced into 0.5-mm strips, postfixed with 2% OS04 for 2 h, dehydrated with a graded ethanol series, infiltrated and embedded in Spurrs low-viscosity embedding medium, cut into ultrathin sections, stained in 1% uranyl acetate and 1% lead citrate for 20 min each, and viewed by TEM at 80 keV. Cells with three or more visible viruslike particles inside were counted as infected (Proctor and Fuhrman 1990).

The second method used TEM to look through the bacteria at the relatively high acceleration voltage of 100 keV to enumerate the number of bacteria in the sample that contained virus-shaped particles, as described by Weinbauer et al. (1993). Only those bacteria with resolution great enough to enable visualization of the interior of the cells were counted. Bacteria containing five or more viruses were counted as infected.

Cell counts-Bacteria were directly counted from 2% Formalin-preserved samples by epifluorescence microscopy with acridine orange stain (Hobbie et al. 1977) and an Olympus Vanox microscope. Bacteria were also counted by TEM from the samples prepared for virus counts. Protists were counted from 1 % glutaraldehyde-preserved samples by epifluorescence with proflavine stain (Haas 1982); counts included estimates of size (to the nearest gim) and presence or absence of chlorophyll fluorescence.

Virus production-Virus production was estimated by thymidine incorporation into TCA-insoluble <0.2 ,um DNAse-resistant material by a method modified from Steward et al. (1992b). Duplicate 50-ml samples were collected into conical 50-ml tubes, and [3H]thymidine was added to 5 nM final concentration. Subsamples (7 ml) were collected at 0, 6, 15, and 24 h. From each subsample, 5 ml was filtered through a 0.2-,um Acrodisc (Gel- man), and the filtrate was split into duplicate 2-ml samples. Nucleases (10 ,l each from stocks containing 1 unit DNase I, 1 unit RNase, or 5 units Micrococcal nuclease per gul) were added to the 2-ml subsamples, which were then incubated at room temperature for 1 h. Then 40 ,ul of Formalin was added to each to stop the enzymes, and the samples were refrigerated. Within 1 d, each tube was subsampled into duplicate 900-,ul volumes in 2-ml mi- crofuge tubes on ice, and carrier solution (50 jg ml- I each DNA, RNA, and BSA) was added to each. To each subsample, 300 ,l of cold 20% TCA was added; one duplicate remained on ice, and the other was incubated at 100?C for 1 h. After the 1-h incubations, the hot sample was cooled on ice for 10 min. Tubes were shaken hard to resuspend precipitates and the suspensions passed through 25-mm HA Millipore filters. Tubes were rinsed with 1 ml of 5% TCA that was then poured through the filter. Filters were rinsed and counted as described above for



1238 Fuhrman and Noble

30x107 Mesocosm 1 A Viruses

A~~~~~ 2 O x 107

E

Q 1 Ox 10 Bacteria

0

0 10 20 30 40 50

2 O x 107 Mesocosm 2

12x107 A A

A A ~~~Viruses A

1 2 x 107 A

E

U 80x106

Cu

O I p

0 10 20 30 40 50

time (hours)

Fig. 1. Bacterial and viral abundances in mesocosm 1 and mesocosm 2.

thymidine incorporation. Control samples were killed with 1% Formalin. Conversion of DNA incorporation values (cold TCA-hot TCA) into virus production used the factor of 6.17 x 1020 viruses produced per mole thymidine incorporation previously determined for coastal southern California (Steward et al. 1992a).

Mortality rates-The total bacterial mortality rate (and its size fractionation) was estimated by the method of Servais et al. (1985), in which bacterial DNA is "pulse- labeled" and then the decline in labeled bacterial DNA is monitored over a 2-d period. The pulse labeling was done by adding a low level of [3H]thymidine (0.5 nM) to a 1-liter subsample in a polypropylene bottle which was incubated in the water bath next to the large carboy. At periodic intervals, duplicate 40-ml samples were taken and extracted with TCA (as for thymidine incorporation). Radioactivity was counted to determine when the incorporation peaked (an indication that labeled substrate was exhausted). Further changes in incorporation represent degradation of DNA due to mortality. When the incorporation peak was confirmed by successive measurements (after 10-20-h total incubation), the sample was divided, and half was gravity filtered through a 47-mm- diameter Nuclepore filter (1.0-Am pore-size in June, 0.6- Am in November) to remove protists. The two half-samples were incubated side-by-side, subsampled, and ex-

tracted with TCA periodically. Mortality was calculated from the decay rate of TCA-insoluble label determined by linear regression of the decline of the log of radioactivity with time.

Bacterial mortality from protist grazing was determined twice in each mesocosm by disappearance of fluorescently labeled bacteria (FLB; Sherr et al. 1987) as per Pace et al. (1990). FLB were produced from Santa Monica Bay seawater by concentration with an Amicon 30-kD spiral cartridge unit and heat treatment at 60?C to kill and stain the cells with 5-([4, 6-dichlorotriazin-2- YL]amino) fluorescein. FLB were added to a 1-liter subsample taken from the mesocosm, with initial FLB concentration of 0.9-1.3 x 105 cells ml-' as determined by unstained epifluorescence counts (blue excitation). Slides were prepared within 1 d of sampling. FLB concentrations were measured every 6-8 h. Controls were alternately killed with 1% Formalin and prefiltered through a Nu- clepore filter (1.0 Am in mesocosm 1 and 0.6 Am in mesocosm 2). The mortality rate was estimated from the best fit (linear or exponential) to the decline of the FLB abundance with time, corrected by subtracting the decline in controls. Because FLB are nonmotile (heat killed), their removal by grazers underestimates grazing rates when the actual prey are motile (Landry et al. 1991; Gonzalez et al. 1993). This underestimate ranges from a factor of 2.2 for slow-moving prey to 2.7 for fast-moving prey (with natural assemblages of grazers). Because we do not know the relative abundances of nonmotile, slow, and fast bacteria in natural assemblages, we have assumed an equal proportion of the three types and have applied a correction factor of 2 (i.e. the FLB disappearance rates were doubled to estimate protist grazing of natural bacteria). Live stained bacteria (Landry et al. 1991) were not used because they could divide or become infected with viruses over the 2-d experiments.

Results

Bacterial, viral, and nonpigmented nanoplankton abundance-In mesocosm 1, bacterial abundance stayed relatively constant at 5-7 x 109 cells liter-' (avg, 6.5 x 109). Viruses were more dynamic, ranging from 1.5 to 3 x 1010 particles liter-', and tended to be lowest in the middle of the experiment (Fig. 1). In mesocosm 2, the pattern was opposite; bacterial abundance ranged from 1 to 2.5 x 109 cells liter-' (avg, 1.88 x 109) and viruses were more constant, ranging from 1.2 to 1.8 x 1010 particles liter-' (Fig. 1). In both experiments, bacterial counts by epifluorescence were statistically indistinguishable from counts by TEM (t-test, P > 0.05). Potentially bacteri- vorous protist counts at the beginning of the experiments showed 5.9 x 106 nonpigmented nanoplankton liter-' with an average equivalent spherical diameter of 3.2 Am in mesocosm 1 and 6.1 x 106 nonpigmented nanoplankton liter-' with an average equivalent spherical diameter of 3.6 Am in mesocosm 2.

Bacterial production-In both mesocosms, bacterial production as measured by thymidine incorporation was very close to that measured by leucine incorporation (Fig.




2). Bacterial specific growth rates (production divided by bacterial abundance) were 1-2 d- I in mesocosm 1 and -0.5-3 d-I in mesocosm 2. Average production rates were 3.08?0.14x 108 cells liter-' h-l (mean ? SE of the mean) in mesocosm 1 and 1.48 ?0.09 x 108 cells liter-' h'-I in mesocosm 2. Calculated as average hourly specific rates to compare with loss estimates, these correspond to 4.7% h-l in mesocosm 1 and 7.9% h-' in mesocosm 2.

Bacterial loss-The loss of bacteria was calculated several ways. First, because the mesocosms were closed systems, we could calculate a loss rate from our knowledge of production and changes in cell abundance from the equation

Loss = production - (N, - NO). (1)

N, and No are bacterial abundance at the end and beginning of the time period over which the production and loss occur. These loss rates tended to follow the production rates because changes in bacterial abundance were generally smaller than the bacterial production rate. The average loss rates were 4.4?0.3% h-l in mesocosm 1 and 8.3 ?0.8% h- I in mesocosm 2 (Table 1). When compared to the average production estimates, these rates correspond to the observed small net increase in bacterial abundance in mesocosm 1 (i.e. production slightly ex- ceeded loss) and a small net decrease in mesocosm 2.

Second, we estimated total loss and size-fractionated rates for the experiments that measured the disappearance of labeled DNA. In mesocosm 1, the decline in the unfiltered sample was twice that seen in the 1-,um filtrate (Table 1, Fig. 3). Therefore, removal of protists elimi- nated half of the loss, suggesting roughly equal contri- butions of protists and viruses (or other nonprotist loss mechanisms). In mesocosm 2, it was more difficult to estimate the rates because the radioactivity was initially flat, then declined rapidly, followed by a slower decline (Fig. 3). This pattern does not follow the expected model, so its application is questionable. If one uses the sharp 2-point decline between 25 and 29 h only, it was 8.2% h- I in the unfiltered water and about the same in the 0.6- ,um filtrate. The similarity of the two rates in mesocosm 2 suggests that most loss is not due to protists, but we do not have much confidence in this result because the filtration removed 75% of the label, declines were short lived, and the estimates were based on only two data points for each calculation.

6 0 x 1 o8

Mesocosm 1

45x10 8 eocs

a)

4> 3 0Ox 108 > - \ t? ~~~~~Leucine 0

0

L_ 15x108 a.

0 0 10 20 30 40 50

2 5 x 108 * Mesocosm 2

2 0 x 108

Thymidine X 1 5 x 108 Leucine A

A, 15x108 A

0

CL 0 1 Ox 108

20

5 0 x 1 07

0

0 10 20 30 40 50

time (hours)

Fig. 2. Bacterial production in mesocosm 1 and mesocosm 2 as determined by incorporation of [3H]thymidine and [3H]leucine.

Third, we estimated loss due to protist grazing directly from the corrected decline in FLB, which was -2% h-' in mesocosm 1 and 3. 1% h- I in mesocosm 2 (Table 1, Fig. 4).

Fourth, once each day we estimated loss due to viruses directly from virus production. These production rates were 1.78 ? 0.12 and 1.61 0. 1 1 x 109 viruses liter- ' h- I in mesocosm 1 and 1.05 0.07 and 1.03 ?0.05 x 109 in mesocosm 2. These rates require an estimate of burst size to convert them to bacterial mortality estimates. We estimate from our TEM observations of infected bacteria that the burst size in these samples is about 20 virus

Table 1. Bacterial loss rates in % h-', expressed as mean ? SE (ND-not determined).

Process Method Mesocosm 1 Mesocosm 2 "Total" loss rate 1. Production (TdR and Leu) - A AODC 4.4?0.3 8.3?0.8 Minimum loss estimate 2A. Disappearance of labeled DNA 2.4?0.2 8.2* Minimum loss without protists 2B. Same < 1 ,um 1.2?0.2 ND Protist-caused loss 3. Disappearance of FLB 1.8?0.02 day 1 2.8 ?0.2 day 1

2.2?0.02 day 2 3.4?0.2 day 2 Virus-caused loss 4. Virus production/burst size 1.4?0.1 day 1 2.8 ?0.2 day 1

1.2?0.1 day2 2.7?0.1 day2 Protists + viruses Sum of 3 + 4 3.3(75% of total) 5.9(71% of total) * No SE calculated, estimate is from line generated by only two time points.




5 9

Mesocosm 1

5 7

E ~~~~~~~~~~~~~~~unfiltered a-

o 55

<1 0 gm size fraction

53 3 , , 0 10 20 30 40 50

60

Mesocosm 2

56 unfiltered

E

o 52 <0 6 gm

\ size fraction

A

48 0 10 20 30 40 50

time (hours)

Fig. 3. Decline in tritiated TCA-insoluble material (largely bacterial [3H]DNA) produced by bacterial incorporation from a tracer level of [3H]thymidine added at time zero and exhausted from the media before declines could be measured. Mesocosm 1-whole seawater and <1-,um size fraction. Mesocosm 2- whole seawater and <0.6-,um size fraction. In mesocosm 2, only the sharp decline between 25 and 29 h was used for calculation (see text).

particles, which implies that lysis of the bacterial popu- lation was 1.3% h-1 in mesocosm 1 and 2.8% h-' in mesocosm 2 (Table 1).

Fifth, we could also estimate the proportion of loss due to viruses from the fraction of bacteria containing mature assembled viruses. The embedded samples from mesocosm 1 were unusable due to a problem with the embedding medium. At the beginning of mesocosm 2, 3.3% of the bacteria appeared infected; about midway (25.8 h) through mesocosm 2, 4.6% of the bacteria appeared infected. The model of Proctor and Fuhrman (1990) and Proctor et al. (1993) suggests that the proportion of total mortality that can be ascribed to viruses is about equal to the percentage of visibly infected bacteria multiplied by a factor ranging from 7.4 to 14.3. Therefore, the initial proportion of infected bacteria in mesocosm 2 is estimated to be 24-47%, and in the middle of the experiment, 34-66%.

5 1 Mesocosm 1

1 0-pim- filtered

Formalin- control O 5 killed o

control

0)~~~

0 4 9

A

48 0 10 20 30 40 50

53

Formalin-

5 1 killed 0 6-pm- o control filtered Mesocontroc

4 9 E m _j ~~ ~~~~~~~~A A U- 4 7A

0

A

4 5

Mesocosm 2

43 l l l

0 10 20 30 40 50 60

time (hours)

Fig. 4. Disappearance of fluorescently labeled bacteria (FLB). Mesocosm 1-in the first experiment (0-22 h), Formalin-killed control (0) vs. untreated seawater (A). In the second experiment (22-46 h), 1.0-,um-filtered control (0) vs. untreated seawater (A). Mesocosm 2-in the first experiment (0-35 h), Formalin- killed control (0) vs. untreated seawater (A). In the second experiment (28-52 h), 0.6-,um filtered control (0) vs. untreated seawater (A).

Because of the difficulty with embedding medium in mesocosm 1, we tried the alternative method of looking through whole bacteria (Weinbauer et al. 1993). With these samples, we found that the visual resolution of this approach was much lower than when we used thin sections, and it was more difficult to identify cellular inclu- sions as viruses. Therefore, we used a different criterion to consider a cell "infected": five rather than three viruses per bacterium. The observed proportions of visibly infected bacteria were 1.8-2.9% in mesocosm 1 and 0.7- 1.5% in mesocosm 2 (counted at the same sample times as the thin sections). It is likely that some infected cells were missed in the whole-cell approach because of vari- ations in staining and cell thickness. Also, some infected cells may disrupt at the centrifugation speed used here (M. Weinbauer pers. comm.). Because of potential dif- ferences between analysis of thin sections and whole cells




as well as the different criteria in scoring cells, the model of Proctor and Fuhrman (1992) was not applied to whole- cell results.

Virus turnover-Although it was not one of our primary goals, our data permit estimation of virus turnover rates in these samples. The virus production rates imply virus turnover rates averaging 9% h-' in mesocosm 1 and 7% in mesocosm 2.

Discussion

Agreement from redundant independent measures lends considerable strength to a conclusion, and we have incorporated such redundancy into our study. The epifluorescence and TEM counts of bacteria were essentially identical, confirming the accuracy of the method by which we converted TEM observations into abundances; because such counts are straightforward, we assume they are accurate. The bacterial production estimates from thymidine and leucine were also essentially identical, and each used independently determined conversion factors; therefore, we believe these values are correct. However, because the accuracy of bacterial production measurements is not always obvious (see Ducklow and Carlson 1992), it is still possible that both measurements are in- correct by exactly the same amount. We will still assume, however, that the bacterial production measurements are accurate. The bacterial production values determined over time allow direct calculation of bacterial losses from the mesocosms (method 1 above) which we use as a baseline to compare the other methods (Table 1).

One other method yielded direct estimates of total bacterial mortality (disappearance of labeled DNA-method 2A and B), but this method is expected to produce an underestimate because the death of bacteria does not nec- essarily entail degradation of its DNA (Servais et al. 1989). Grazers and even viruses can retain the label in TCA- insoluble macromolecules in a way that masks the mortality from measurement by this method. Indeed, this approach yielded lower values than the baseline method 1 in both mesocosms; the mortality from mesocosm 1 was only 55% of the "total," and mortality from mesocosm 2 was a nearly identical 99% (but only from two data points).

Size fractionation of the DNA disappearance showed that in mesocosm 1, the rate of mortality in the l-,im- filtered sample was half the rate of the unfiltered sample. Filtration removes all but a tiny portion of the protists (and those that pass are extremely small and unlikely to be significant grazers). If we make the simplifying as- sumption that the mortality processes of the < l-,um and > l-,um bacteria are similar, this suggests that protists are responsible for about half the mortality and that agents passing a l-,um filter, presumably viruses, are responsible for the other half. In mesocosm 2, the decline did not follow the expected model (the rate declined drastically with time), and the slopes were similar in unfiltered and filtered samples over the short time frame. However, be-

cause only 25% of the label passed the 0.6-,um filter and only two data points were used, it does not seem reason- able to extrapolate this rate to the entire bacterial community. It does appear that viruses were important mortality agents in this experiment as well.

Servais et al. (1985, 1989) developed and used the disappearance of labeled DNA to estimate mortality; they used 2-,um filtrations to partition loss between protists and other causes. Typically, they found about half the mortality was removed by the filtrations in coastal Bel- gian and Mediterranean waters, similar to our results. However, because protists sometimes include individuals that can squeeze through 2-,um filters, especially in less productive waters, Servais et al. were not certain how to interpret their size-fractionation results. They also con- cluded from a lab experiment (with lysogenic Escherichia coli) that lysis by phage is not detectable by this method. However, we suggest that due to the great variety in phage nutrition and regulation of host nucleic acids (Ackermann and DuBow 1987), some phage-induced mortality is probably detectable immediately and some may require degradation of the phage before detection. With the rapid phage turnover we observed, the results probably still indicate much of the mortality. Therefore, this method probably underestimates the contribution of phages to bacterial mortality by an unknown amount.

The other mortality measurements were for specific mechanisms, and we can sum them together so as to budget the total and attribute specific fractions of the mortality to particular mechanisms (Table 1). The FLB disappearance should be attributed to protist grazing (the FLBs were heat killed to prevent infection), and the virus production measurements have been converted directly into bacterial mortality estimates. In mesocosm 1, these two estimates add up to 75% of the "total" mortality calculated from method 1. Of the subtotal, protist grazing is estimated to make up 61% and viral lysis 39%. In mesocosm 2, the FLB + viral production-based estimated add up to 71% of the "total," with the grazing making up 53% of the subtotal and viral lysis 47%. There- fore, we can specifically account for 70-75% of the total apparent mortality with these two mechanisms, and each mechanism appears to contribute a comparable amount. Given the uncertainties in such measurements, we believe the results are surprisingly consistent. The underestimate in accounting for the total could be due to errors in our determinations or to possible other mortality mechanisms, such as antibiosis, about which we have no data.

Three independent lines of evidence lead us to conclude that viruses and protists cause comparable rates of bacterial mortality in this system. First, the size fractionation of labeled DNA disappearance, indicating 50% ascribed to protists and 50% to viruses. Second, the partitioning of total mortality between grazers (measured by FLB) and viruses (measured by virus production), indicating 40- 50% due to viruses. Third, the model-based interpretation of the percentage of bacteria seen in thin sections with assembled viruses inside, indicating 24-66% due to viruses. It therefore seems clear that mortality from viral




activity must be considered in studies of bacterioplankton processes.

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Submitted: 14 March 1995 Accepted: 9 May 1995

Amended: 19 July 1995



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Viruses and Protists Cause Similar Bacterial Mortality in Coastal Seawater