- Email: [email protected]
The use of antibiotics to reduce bacterioplankton uptake of phytoplankton extracellular organic carbon (EOC) in the Potomac River estuary
Journal of Experimental Marine Biology and Ecology 342 (2007) 242 – 252 www.elsevier.com/locate/jembe
The use of antibiotics to reduce bacterioplankton uptake of phytoplankton extracellular organic carbon (EOC) in the Potomac River estuary Leila J. Hamdan ⁎, Robert B. Jonas Department of Environmental Science and Policy, George Mason University, MSN 5F2, 4400 University Drive, Fairfax, Virginia 22030, United States Received 25 August 2006; accepted 29 October 2006
Abstract Phytoplankton production and accumulation of extracellular organic carbon (EOC) was tracked during diel intervals in microcosms by inhibiting bacterioplankton assimilation of EOC with streptomycin and kanamycin. Bacterioplankton production (3H-thymidine incorporation) and metabolism (14C-glucose incorporation) were monitored in samples collected from the Potomac River estuary to determine the effect of the antibiotics. Particulate (i.e., raw water) primary production and EOC (i.e., water passing through 1.0 μm glass fiber filter) production rates were monitored to determine the impact of antibiotics on phytoplankton. In preliminary experiments, neither streptomycin nor kanamycin alone significantly inhibited bacterioplankton activity compared to controls, but when both were present secondary production and metabolism were reduced up to 90%, and remained as such for 45 h. During field evaluations using a streptomycin and kanamycin mixture (50 μM each) particulate primary production and EOC production were not statistically different in control and antibiotic treated samples indicating that the antibiotics did not negatively influence phytoplankton production rates. In the presence of antibiotics dissolved free amino acids (DFAA) and, to a lesser extent, monosaccharides were significantly elevated compared to controls. This study demonstrates that streptomycin and kanamycin are capable of inhibiting bacterioplankton metabolism and uptake of dissolved organic carbon (DOC) in the samples tested so that the contribution of EOC to the DOC pool and to bacterioplankton metabolism could be measured and assessed. © 2006 Elsevier B.V. All rights reserved. Keywords: Bacterioplankton; Extracellular organic carbon (EOC); Kanamycin; Phytoplankton production; Streptomycin
1. Introduction Dissolved organic carbon (DOC) accounts for a significant portion of total organic carbon in aquatic ⁎ Corresponding author. Present address: Marine Biogeochemistry Section, Code 6114, U.S. Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, District of Columbia 20375, United States. Tel.: +1 202 767 3364; fax: +1 202 404 8515. E-mail address: [email protected] (L.J. Hamdan). 0022-0981/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jembe.2006.10.054
ecosystems (Nagata, 2000). In some locations extracellular organic carbon (EOC) produced by phytoplankton is a significant source of autochonous DOC (Baines and Pace, 1991; Nagata, 2000). EOC is primarily composed of dissolved free amino acids (DFAA), carbohydrates and short chain organic acids (Chróst and Faust, 1983; Münster and Chróst, 1990; Leboulanger et al., 1997; Maurin et al., 1997; Søndergaard et al., 2000). Although reports of EOC production are numerous, few studies in eutrophied estuaries have examined this source of DOC.
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
Faust and Chróst (1981) reported on EOC released by phytoplankton in the Rhode River, a shallow subestuary of the Chesapeake Bay. In their study, EOC accounted for up to 50% of photo-assimilated carbon during a phytoplankton bloom, thus indicating the potential importance of EOC to carbon availability and cycling in that system. Recent reports indicate that DFAA and monosaccharides may double during a diel period in association with phytoplankton blooms in the Patuxent River Estuary, also a sub-estuary of the Chesapeake Bay (Sellner and Nealley, 1997). Some have reported on the tight coupling between phytoplankton EOC and bacterioplankton growth and metabolism (Chróst and Faust, 1983; Søndergaard et al., 1985; Münster and Chróst, 1990), which is likely attributable to the lability of EOC to bacterioplankton. Bacterioplankton may utilize up to 80% of phytoplankton EOC in some systems (Faust and Chróst, 1981; Larsson and Hagström, 1982; Lancelot and Billen, 1984). Studies that investigate the classes of molecules composing EOC and its rates of release by phytoplankton assist in resolving the principal sources of DOC in aquatic systems and lend insight to the importance of EOC to the microbial food web. However, because of the tight coupling between EOC release and bacterioplankton uptake it is difficult to observe accumulation of EOC or DOC in general in the presence of metabolically active bacterioplankton that may consume EOC at rates comparable to its production (Faust and Chróst, 1981; Larsson and Hagström, 1982; Lancelot and Billen, 1984). Hence, experiments that incorporate both bacterially active and bacterially inhibited samples may shed light on EOC production as well as consumption by bacterioplankton. Filtration and antibiotics have been used to track EOC transfer from phytoplankton to bacterioplankton with limited success (Cole et al., 1982; Jensen, 1983, 1984; Jensen and Søndergaard, 1985; Bjørnsen et al., 1988; Maurin et al., 1997). To render samples bacterioplankton-free by filtration requires sieving through membranes with a nominal pore size of 0.2 μm which may remove or physiologically stress phytoplankton and possibly alter EOC production rates (Jensen, 1983, 1984; Jensen and Søndergaard, 1985; McArthur and Tuckfield, 2000). Antibiotics have been used to suppress bacterioplankton in natural samples for varying time intervals (Cole et al., 1982; Jensen, 1983, 1984; Jensen and Søndergaard, 1985; Maurin et al., 1997). In one study polymixin reduced bacterioplankton uptake of DFAA by 75% compared to controls (Jensen, 1984). The study demonstrated significant inhibition on a short scale
243
(approximately 4 h) but did not evaluate if this inhibition was sustained during longer periods. In a study of EOC production in a oligomesotrophic lake, streptomycin suppressed bacterioplankton glucose metabolism for short periods (6 h) up to 62% of controls, but higher degrees of suppression for longer intervals were not investigated (Maurin et al., 1997). Another study analyzed vancomycin and mefoxithin inhibition on freshwater and estuarine bacterioplankton, and found that individually these only inhibited bacterioplankton DFAA metabolism up to 50% compared to controls (Jensen and Søndergaard, 1985). Few studies have specifically addressed the impact of prokaryotic antibiotics on phytoplankton EOC production and uptake by heterotrophic bacterioplankton. In one study, nearly 90% of bacterioplankton production (BP) was inhibited by streptomycin even when the experiment was carried out over a period of several days. Although these results were promising, the effect on bacterioplankton catabolism was not measured and significant inhibition of prokaryotic primary producers (up to 29%) was evident (Jensen, 1983). Because the effect of antibiotics on primary producers in many systems is unknown, and since secondary production and metabolism do not always co-vary, it is necessary to test amino glycoside antibiotics further before they can be used experimentally to decouple EOC production by phytoplankton and consumption by bacterioplankton. The purpose of this study was to determine if streptomycin and kanamycin used in tandem are capable of suppressing bacterioplankton production and metabolism under field conditions for up to 30 h. The main goal of this work was to demonstrate that the antibiotics could be effective at reducing bacterioplankton activity but have no significant impact on phytoplankton such that EOC production by phytoplankton and its accumulation during a diel cycle could be measured in the absence of bacterioplankton uptake. 2. Materials and methods 2.1. Sample collection and handling Water samples were collected at Station 3 (38.16 N, 76.59 W) in the main channel of the mesohaline Potomac River. A detailed description of this site is provided by Hamdan and Jonas (2006). On July 17, 2002 water samples were collected with a submersible impeller pump and hose system (Jonas and Tuttle, 1990) from a depth of 1 m and dispensed directly into four 7.5 L polyethylene cubitainers which were filled
244
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
simultaneously by alternating the hose between containers at 15-s intervals to homogenize the replicate samples. Two of the four samples were treated with a combination of streptomycin monosulfate and kanamycin monosulfate (Fisher Scientific) to yield a final concentration of 50 μM each. Preliminary laboratory experiments determined that this dose could yield reductions in BP and glucose turnover rate (GTR) by ≥ 90% of controls for up to 45 h (see Results). Antibiotic stock solutions were made in double distilled/deionized (DD/DI), sterile water within 15 min of sample inoculation. The concentrated stock was added separately to samples in appropriate volumes to yield the desired final concentration in a volumetric ratio of sample to antibiotic solution of approximately 1000:1. The samples were shaken gently to distribute the antibiotic solution. Two cubitainers were translucent and incubated in situ; the remaining were blacked out with aluminum foil and duct tape to reduce all light to sample and inhibit photosynthesis. One each of the light and dark samples was inoculated with antibiotics; the remaining two were left untreated as controls. The samples were identified as follows: dark control, light control, light antibiotictreatment (AT), dark AT. The samples were pre-incubated overnight under in situ conditions for 13 h to attain maximum inhibition of prokaryotes as determined by preliminary experiments (see Results). The experimental protocol conducted shipboard, began the following sunrise and concluded shortly after sunset. The cubitainers were sub-sampled at 3 h intervals, and between sampling were returned to a depth of 1 m (approximately one-half the depth of the euphotic zone). Samples were suspended on a boom to keep them out of the boat shadow and weights were attached to the bottom of the cubitainers to prevent them from rising to the surface. Samples were held in this manner for up to 30 h. Fig. 1 provides an overview of the sampling design. 2.2. Glucose metabolism The dual-label radioisotope method which simultaneously measures BP and GTR described by Jonas et al. (1988) was used. Ten-milliliter sub-samples were transferred to 20-mL all-polypropylene syringes. Prior to inoculation with radiolabeled substrates an abiotic control was heat killed (80 °C, 15 s) in a microwave. Sub-samples were inoculated with 50 μL of a mixture containing a final concentration of 1.2 μg L− 1 D[U-14C] glucose (ICN Radiochemicals). Measurements of monosaccharides (see Results) verified that glucose
additions increased the ambient monosaccharide pool by an average of 0.002% thus making this a true tracer assay. Samples were incubated for 30 min in situ in the dark, and killed by addition of 10 mL ice-cold 10% trichloracetic acid (TCA). Particle associated radioactivity was collected on 0.2 μm, cellulose ester membrane filters (Millipore Corp.) and rinsed with 5% TCA. Scintiverse II (Fisher Scientific) was added to filters and radioactivity was determined using a Beckman-Coulter model LS6500 liquid scintillation counter operating in dual DPM (3H/14C) mode. GTR was calculated by dividing the radioactivity on the filter by the total radioactivity added (measured from direct addition of the radioactive inoculum to scintillation cocktail). The monosaccharide metabolic rate was calculated by multiplying ambient monosaccharide concentration by the turnover rate. 2.3. Bacterioplankton production The dual-label radioisotope method (Jonas et al., 1988) described above was used to determine BP. Each sub-sample contained a final concentration of 5 nM 3Hmethyl-thymidine per liter in addition to D-[U-14C] glucose. Uptake was calculated as ñmole thymidine incorporated and converted to the rate of cells produced L− 1 h− 1 using a factor of 2 × 1018 cells produced per mole incorporated thymidine (16). The bacterioplankton cell production rate was converted to mg C L− 1 h− 1 according to Hoch and Kirchman (1993). 2.4. Bacterioplankton abundance Bacterioplankton abundance was determined according to Hobbie et al. (1977) with modifications described elsewhere (Hamdan and Jonas, 2006). Briefly, subsamples preserved with a final concentration of 2% 0.2 μm filtered formaldehyde were diluted 1:1 with 0.2 μm-filtered Potomac River water, stained with 0.1%, 0.2 μm-filtered acridine orange, collected on 0.2 μm black polycarbonate filters (Osmonics, Inc.) and observed at 1000× total magnification. An Optronics UTV1X single chip video camera and DEI-750 image integrator (Optronics Engineering) were used to capture high resolution images which were viewed and enumerated using Bioquant Nova Prime Image Analysis software. 2.5. Primary production Particulate primary production (PPP) was measured by tracking the uptake of NaH214CO3 as described by
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
245
Fig. 1. Design of field experiment. Samples were held in situ overnight for a 13 h pre-incubation period and for the duration of the experiment which began at T = 13 h. Samples for DOC measurements (monosaccharides, DFAA and glycolic acid) and EOC production rates were pre-filtered through Gelman type A/E glass fiber filters (nominal porosity 1.0 μm). All samples were collected in triplicate at 3 h intervals from T = 13 h to T = 25 h.
Parsons et al. (1984). Triplicate 10 mL samples were collected in 20-mL glass vials, inoculated with 80 μCi NaH2 14CO3 L− 1, and incubated for 1 h under in situ conditions. Incubations were terminated by placing samples in the dark and filtering through Gelman type A/E filters (nominal porosity 1.0 μm) (Pall Corp.) at approximately 125 mm Hg. Filters were placed in 20mL scintillation vials and acidified with 500 μL of 1 N hydrochloric acid to convert unincorporated 14CO3 to gaseous CO2 (Jensen and Søndergaard, 1985) and vented. Ten milliliters of Scintiverse II was added to the vials and radioactivity was determined using a Beckman-Coulter LS6500 scintillation counter. EOC production was measured using filtrate from samples filtered for PPP. Filtrate was transferred to 20mL scintillation vials acidified as for PPP, purged by bubbling air through the solution, and vented for an additional hour. The removal efficiency of 14CO2 by this
method was tested, although it has been used successfully by others (Jensen and Søndergaard, 1985; Riemann and Jensen, 1991; Maurin et al., 1997). For the test, replicate 10-mL control samples were inoculated with 80 μCi L− 1 Na2 14CO3, and incubated for 15 min to allow abiotic adsorption of the substrate. Samples were acidified and purged for 0 to 30 min and compared in triplicate to controls that only had the substrate addition. Compared to controls, 60% of 14CO3 remained in acidified samples after 0 min purging. After two minutes, approximately 35% remained and by 4 min, less than 0.22% remained. 2.6. Monosaccharides Monosaccharides were measured by the colorimetric method of Johnson and Sieburth (1977). Samples were filtered through Gelman type A/E glass-fiber filters,
246
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
collected in pre-combusted (450 °C for 4 h) glass 20-mL scintillation vials and frozen at − 20 °C until analysis. The assay reduces monosaccharides to sugar alcohols, oxidizes them to aldehyde groups and the final derivatization step with 3-methyl-2-benzothirazolione hydrazone hydrochloride (Sigma-Aldrich) produces a colored product. Absorbance was measured at 635 nm on a Perkin-Elmer Lambda 25 UV/VIS Spectrometer (Perkin-Elmer). 2.7. Dissolved free amino acids DFAA were determined according to Parsons et al. (1984). Samples were collected and preserved as for monosaccharide analysis. O-phthalaldehyde in a buffered reagent (0.4 M boric acid — pH 9.5) containing 2mercaptoethanol (all Sigma-Aldrich) was used to react primary amines to form fluorescent products and fluorescence was determined at an excitation wavelength of 342 nm and emission wavelength of 452 nm. Because both antibiotics used in this study contain hexose sugar and amino groups. They were detected during monosaccharides and DFAA analysis. To compensate for this the antibiotic mixture was prepared in DD/DI water at a final concentration of 50 μM each and measured by both methods so that the value could be subtracted from antibiotic treated samples. Thus, monosaccharide and DFAA data for antibiotic treated samples are the field observations minus an antibiotic correction factor. 2.8. Glycolic acid Glycolic acid was analyzed by liquid chromatography-mass spectrometry (LC-MS) using a Waters 2690 separations module and Micromass Z2000 single quadrupole MS with an electrospray ionization probe optimized to produce negative glycolate ions (Hamdan et al., in review). Separation occurred on a Polarity dC18 column. Glycolic acid was eluted isocraticly with 9 mM formate at 200 μL min− 1 after which, the mobile phase was run at gradient to 90% acetonitrile to purge the column. Samples were quantified using external glycolic acid standards. 2.9. Data analysis Data were analyzed to determine differences among treatments as a result of treatment effects using ANOVA F tests with Tukey–Kramer post-hoc test for variance at a significance level of P = 0.05. Statistical analyses were conducted on triplicate sub-samples collected every 3 h
to determine variance among treatments during the experiments. In addition, the experimental means (average of all measurements) of each treatment were compared. Analyses were conducted using SPSS version 12.0 (SPSS Inc.) and Minitab version 13.2 (Minitab, Inc.). 3. Results 3.1. Preliminary experiments to determine antibiotic dosage Three laboratory experiments using mesohaline Potomac River water were conducted to determine an effective dosage of antibiotics to suppress metabolic activity in natural bacterioplankton populations for extended times. Samples were collected as described above, transported to the laboratory and held at in situ temperature (in a re-circulating bath) for 11–45 h, and sampled every 3–6 h. The first experiment with streptomycin (6–50 μM) yielded reductions in GTR by approximately 40% compared to controls after 11 h of incubation. Streptomycin had no significant effect on BP. Because streptomycin is a protein synthesis inhibitor, preformed enzymes could continue to be active after the antibiotic addition; hence, a longer preincubation was required for this type of antibiotic. A second experiment tested streptomycin (50– 1000 μM), kanamycin (50–500 μM) and combined treatments of both (50 μM each). At concentrations up to 1000 μM streptomycin reduced GTR and BP by approximately 40% compared to controls. All concentrations of kanamycin significantly reduced BP and GTR (max 91 and 95%, respectively) compared to controls at T = 0 h by T = 45 h. The greatest suppression of metabolic activity resulted from streptomycin and kanamycin used together and yielded 80 and 78% reductions in BP and GTR (respectively) by T = 13 h compared to the control at T = 0 h and 87 and 81% (respectively) compared to the control at T = 13 h. At T = 45 h, the combined dose sustained reduction of BP and GTR up to 100 and 91% (respectively) of controls at T = 0 h. A final experiment only tested combined streptomycin and kanamycin treatments (25–200 μM). All treatments resulted in significantly lower BP and GTR compared to controls. The lowest antibiotic dose (25 μM each) had the least significant effect on bacterioplankton activity; however, there was no simple dose response effect as the highest dosage (200 μM each) was only slightly more effective. Both antibiotics present at 50 μM yielded reductions in BP and GTR
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
247
greater than 90% at T = 13 h, and remained as such for 24 h. 3.2. Field experiment 3.2.1. Bacterioplankton production and abundance Controls and the light AT were included for bacterioplankton analyses. At the onset of sampling (T = 13 h; 07:30 h) there was no significant difference in BP between light and dark controls (Fig. 2A). BP in the light AT was significantly lower than controls. At subsequent time points, BP in the dark control was generally equal to or less than the light control. However, at T = 25 h the difference between controls was significant due to a decline in BP in the dark control (Fig. 2A). BP in both controls was always significantly higher than the light AT. Overall, BP in the light AT was reduced by 91% of the light control and, 89% of the dark control. Bacterioplankton abundance was measured at T = 0 h to evaluate enclosure effects on abundance. At T = 0 h, abundance was 7.5 × 106 cells mL− 1 (not shown). Experimental means for the controls and light AT were 12.7 and 10.0 × 106 cells mL− 1, respectively. For the duration of the experiment, abundance did not differ significantly between controls (Fig. 2B), nor from T = 13 h to T = 25 h. At T = 16, 22 and 25 h abundance in one or both controls was statistically higher than the light AT (Fig. 2B).
Fig. 2. Bacterioplankton production (A) and abundance (B) in the dark-control (○), light-control (▵) and light antibiotic treatment (AT) (▿). Antibiotic treated samples were inoculated with streptomycin and kanamycin (50 μM each).
Fig. 3. Monosaccharide (A), dissolved free amino acids (B), and glycolic acid (C) concentrations in the dark-control (○), light-control (▵), light AT (▿) and dark AT (□). Samples handled as described in Fig. 2.
3.2.2. Monosaccharides, dissolved free amino acids and glycolic acid Monosaccharides ranged from 25 to 500 μg C L− 1 (all data) (Fig. 3A). The experimental mean for both controls and the light AT (80 μg C L− 1 ) was significantly lower than the experimental mean for the dark AT (146 μg C L− 1). At T = 16 h, monosaccharides in the dark AT were significantly elevated compared to all other treatments, and at T = 19 and 22 h was significantly elevated compared to both light treatments. DFAA ranged from 23 to 2650 μg C L− 1, and averaged 54 and 2010 μg C L− 1 in controls and ATs, respectively. The difference between controls and ATs was highly significant at all times (Fig. 3B). Experimental means for glycolic acid ranged between 90 and 500 μg C L− 1. The experimental mean for the dark control (172 μg C L− 1) was significantly lower than all other treatments (average 311 μg C L− 1) (Fig. 3C). The light control had the highest experimental mean (356 μg C L− 1). The light treatments tracked consistently with each other from T = 16 h through T = 25 h. At T = 16 and 22 h (10:30 and 16:30 h) glycolic
248
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
acid was significantly elevated in light treatments compared to dark treatments. 3.2.3. Glucose metabolism GTR in the light control averaged 15% h − 1 throughout the experiment (Fig. 4A). GTR in the dark control declined from T = 16 h to T = 25 h, and at T = 25 h did not differ significantly from the light AT. Otherwise, the difference between controls and the light AT was significant. Average GTR in the light AT (0.83% h− 1) was approximately 95% and 93% lower than experimental means for light and dark control respectively. Glucose metabolism in the light treatments tracked closely with GTR but deviated for the dark control (Fig. 4B). Instead of decreasing consistently
over the experiment, as did GTR in the dark control (Fig. 3A), the metabolic rate averaged 12 μg C L− 1 h− 1 for the majority of the experiment and declined only at T = 25 h. Despite the late decline in the dark control, experimental means for both controls were similar (10 μg C L− 1 h− 1), and significantly higher than the light AT (0.5 μg C L− 1 h− 1). 3.2.4. Primary production Experimental means for PPP were 11, 78 and 63 μg C L− 1 h− 1 in the dark control, light control and light AT, respectively. From T = 13 h to T = 19 h PPP in the dark control was significantly lower than both light samples (Fig. 4C). PPP in the light control and light AT was similar except at T = 19 h (13:30 h) as PPP in the light control was significantly higher (30%). EOC did not differ significantly among the treatments at any time during the experiment. Overall, EOC averaged 124, 149 and 154 μg C L− 1 h− 1 in the dark control, light control and light AT, respectively. EOC was highest in the light control at T = 16 h, and the light AT at T = 22 h (Fig. 4D). 4. Discussion 4.1. Bacterioplankton abundance and production
Fig. 4. Glucose turnover rate (A), particulate primary production (B) and EOC production in the dark-control (○), light-control (▵) and light AT (▿). Samples handled as described in Fig. 2.
With enclosure experiment there is an expected increase in bacterioplankton abundance due to what is commonly known as the “bottle effect” (Zobell and Anderson, 1936). Enclosure effects in experiments carried out in containers smaller than 1 m3 can cause increases in abundance of up to 500% (Ferguson et al., 1984). Although minor relative to what is typically expected, enclosure did cause an increase in planktonic abundance from T = 0 h. When the experimental means are compared to the control at T = 0 h, the overall increase is approximately 60%. The controls deviated from the T = 0 h value most significantly. Abundance did not differ significantly between T = 13 h and T = 25 h for any of the experimental groups and likewise, the difference in abundance between controls was not significant. Although there was an overall increase in abundance during this experiment, it appears that by the time sampling began at T = 13 h, population abundance had stabilized. During this study, only planktonic abundance was measured, and it should be noted that the enclosure possibly resulted in an increase in abundance on the cubitainers walls. Along with a significant increase in bacterioplankton abundance, an increase in BP would also be expected if the bottle effect were significant (Ferguson et al., 1984). A T = 0 h measurement of BP was not made and hence
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
deviations in BP from the onset of the experiment cannot be estimated. However, had the bottle effect been significant it would have been evident during the experimental period with a steady increase in BP in the controls. No significant increase was detected between time points in any of the treatments. To the contrary, in the dark control BP declined significantly at T = 25 h. The decline in BP in the dark control coincided with an increase in bacterioplankton abundance. Although on the surface this refutes the influence of enclosure on increasing abundance and production rates, a second explanation may be that while BP is an instantaneous measurement of the rate of DNA replication, the abundance measurement is a cumulative record of the events of the previous 3 h (Riemann and Søndergaard, 1984). It is possible that an increase in BP occurred prior to the sampling period at T = 25 h in the dark control but was not evident as the cells had already undergone a cycle of rapid growth. If it were merely the enclosure effect causing the increase in abundance and by proxy BP it would be expected in all treatments and since this was not the case, it is likely that the different trend in BP and abundance in the dark control were in response to treatment effects, and not experimental error. 4.2. Primary production, EOC accumulation and bacterioplankton metabolism A significant difference in the concentration of DFAA between the controls and the ATs was observed. This indicates that since bacterioplankton were metabolically suppressed by antibiotics, DFAA accumulated in the ATs under both light regimes due to a lack of bacterioplankton uptake. However, a clear indication of continual accumulation during the diel cycle was not evident since a linear increase in DFAA was not observed in any treatments. In general, the level of bacterioplankton suppression (production and metabolism) was approximately 90% of controls. It is possible that the remaining metabolically active population in the ATs could have accounted for enough removal of DFAA during the experiment such that their activity masked the further appearance of newly produced DFAA. Nevertheless, their activity was insignificant enough that the major accumulated fraction was evident. A similar significant difference in concentration between controls and ATs was expected for monosaccharides and glycolic acid; however, this was not the case. Only the dark AT had significantly elevated concentrations of monosaccharides compared to the
249
experimental means for the controls and the light AT. However, at T = 22 h the concentration of monosaccharides in the dark control was elevated compared to both light treatments. By contrast, the experimental mean for glycolic acid concentration in the dark control was significantly lower than all other treatments. The remaining metabolically active portion of the bacterioplankton population likely complicated these results and masked more subtle differences between control and AT groups; however, there appears to be a treatment effect evident in these samples related to light availability. 4.3. Light availability and EOC production Glycolic acid is a byproduct of photorespiration formed by the dephosphorylation of phosphoglycolate created from the oxidation of ribulose-1-5-bisphosphate (Leboulanger et al., 1994). Because of its specific origin, it may be a biomarker of EOC release and possibly its appearance enhanced in light samples. Because glycolic acid concentration was elevated and approximately equivalent in both the light control and light AT at approximately 10:30 and 16:30 h compared to both dark samples provides compelling evidence of the influence of light on glycolic acid production and by proxy, algal exudation of EOC. A similar trend in the data was observed for DFAA concentration in the light AT. Alternately, it can be argued that photo-oxidation of larger molecules under high irradiance was occurring and producing glycolic acid molecules. However if this were the case, the decrease in glycolic acid in both light treatments at T = 19 h would not be expected and instead appears to be an indicator of photo-inhibition due to the high sun angle at that time. Studies have demonstrated that low solar irradiance can cause an increase in EOC release, specifically in the form of carbohydrates by phytoplankton (de Brouwer and Stal, 2002; Dason et al., 2004). Light limitation appears to have influenced monosaccharide production during this study since accumulation was observed overall in the dark AT and towards the end of the experiment in the dark control. The experimental mean for the dark AT was significantly higher than all other treatments, and at T = 22 h, the dark control and dark AT were significantly higher than both light treatments. Data on bacterioplankton abundance, production and metabolism and phytoplankton production indicate that the monosaccharides may have continued to increase towards T = 25 h in the dark control, but due to bacterioplankton metabolism its appearance may have
250
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
been masked. Between T = 16 and 22 h, the decrease in GTR was coupled with an increase in monosaccharide concentration (at T = 22 h) and a steady rate of glucose metabolism. The decrease in GTR at T = 22 h is likely not the result of slower metabolic rates, but instead a larger substrate pool. An increase in the substrate pool 3 h prior could have been responsible for the increase in bacterioplankton abundance and concurrent decrease in GTR in the dark control at T = 25 h resulting from a reduction in carbon limitation due to the elevated supply of EOC (relative to PPP). The increased supply may have been in the form of monosaccharides, but accumulation was not observed in the dark control possibly because the bacterioplankton uptake rate matched the monosaccharide production rate. However, it is important to note that typically substrate limited bacterioplankton exhibit low or stable rates of BP (Wright and Coffin, 1983; Hamdan and Jonas, 2006) which implies that instead of declining, BP should have increased at T = 25 h. In the absence of data between T = 22 and 25 h we can only speculate that an increase in BP occurred prior to sampling and bacterioplankton abundance remains the only record of such an event. EOC in all treatments exceeded PPP for the majority of the experiment. Because of elevated PPP at T = 19 h, total primary production (TPP = PPP + EOC) in the light control was elevated compared to other treatments (not shown). Specifically, at T = 19 h, PPP in the light control was 30% higher than the light AT, indicating antibiotic suppression of phytoplankton at peak solar irradiance. Otherwise, there was no significant difference in TPP between the light control and light AT. The percent extracellular release (PER) in both light treatments did not differ significantly at any time (not shown). PER in the dark control exceeded both light treatments for the duration of the experiment. Mean PER in the dark control was 92%. PER for both light treatments averaged 71%, was highest at T = 25 h (sunset) (94%), and lowest at T = 19 h (mid-day) (46%) indicating light as a strong controlling factor for EOC production. 4.4. Bacterioplankton inhibition by antibiotics Earlier laboratory experiments indicated that neither streptomycin nor kanamycin alone was effective at sustaining reductions in bacterioplankton activity up to 90% of controls. As such, only a combination of both will be effective in controlling bacterioplankton metabolic activity (production and catabolism). Previ-
ous studies have demonstrated a lesser degree of kanamycin resistance compared to streptomycin and neomycin resistance (Leff et al., 1993; McArthur and Tuckfield, 2000) in freshwater bacterioplankton communities thus indicating that although similar, the mode of action between these two antibiotics is distinct. This may explain why the antimicrobial properties of one of these chemicals are enhanced by the presence of the other. Total inhibition of bacterioplankton activity was not generally achieved during this study, and others have argued that in order to predict accurately EOC production and utilization in enclosure experiments total inhibition must be achieved (Jensen and Søndergaard, 1985). It is evident that total inhibition would have been beneficial in determining subtle patterns in diel production and release of DFAA and monosaccharides since it seems likely that bacterioplankton assimilation of these components of EOC complicated the interpretation of results in ATs. Total bacterioplankton inhibition is vital in studies of oligotrophic systems where bacterioplankton abundance and production are lower and the difference between control and treated groups more subtle. However in the Potomac River, this was not the case since, in general, BP, abundance and GTR were significantly lower in the presence of antibiotics and DOC concentrations were at times significantly higher. Thus, > 90% bacterioplankton inhibition in eutrophied systems such as the Potomac River, would likely allow for informative predictions of phytoplankton EOC accumulation as well as bacterioplankton uptake of autochonous DOC. When using antibiotics to understand production, accumulation and bacterioplankton utilization of phytoplankton EOC it is important to be certain that the antibiotics are only affecting prokaryotic bacterioplankton and not significantly impacting phytoplankton assemblages. There was no significant difference between control and treated samples for EOC production and only one instance when PPP differed between control and AT groups. However, in some cases we did observe slightly elevated EOC production at times consistent with elevated glycolic acid and DFAA concentration in antibiotic treated samples. This might suggest that the antibiotic exerts a deleterious effect on phytoplankton and may enhance EOC production via autolysis. However the lack of a decline in PPP in general argues against this and instead suggests that in the absence of metabolically active bacterioplankton EOC may have accumulated even in the short time frame of the one hour
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
incubation. This finding supports the idea of using antibiotics in microcosms to study the production and release of EOC and to understand better the complex relationship between phytoplankton and bacterioplankton in eutrophied estuarine ecosystems. 5. Conclusions An antibiotic treatment capable of providing significant inhibition of bacterioplankton production and metabolism in natural bacterioplankton populations has been determined. BP and glucose metabolism were suppressed by an average of 90% compared to untreated controls when the antibiotics streptomycin and kanamycin were used in tandem. Except at maximum solar irradiance, antibiotics did not have a significant or lasting effect on total primary production rates and at no time had a significant impact on EOC production. Suppression of bacterioplankton appears to have allowed EOC, DFAA and to a lesser extent monosaccharides to accumulate in antibiotic treated samples. These data indicate that antibiotics are useful tools to be used in experiments aimed at refining estimates of EOC production and its contribution to the DOC pool. Acknowledgements This study was supported by the National Aeronautics and Space Administration, the Washington Area Explorers Club, George Mason University's Department of Environmental Science and Policy and the Stephen J. Wright Scholars Program. We thank D. Emerson for sharing his microscope and imaging system, T. Huff, T. Jordan and K. Lauer for analytical expertise, A. Sinha for field assistance and T. Boyd and R. Coffin for comments on the draft manuscript. [SS] References Baines, S.B., Pace, M.L., 1991. The production of dissolved organicmatter by phytoplankton and its importance to bacteria — patterns across marine and fresh-water systems. Limnol. Oceanogr. 36, 1078–1090. Bjørnsen, P.K., Riemann, B., Horsted, S.J., Nielsen, T.G., Pocksten, J., 1988. Trophic interactions between heterotrophic nanoflagellates and bacterioplankton in manipulated seawater enclosures. Limnol. Oceanogr. 33, 409–420. Chróst, R.H., Faust, M.A., 1983. Organic-carbon release by phytoplankton — its composition and utilization by bacterioplankton. J. Plankton Res. 5, 477–493. Cole, J.J., Likens, G.E., Strayer, D.L., 1982. Photosynthetically produced dissolved organic-carbon — an important carbon source for planktonic bacteria. Limnol. Oceanogr. 27, 1080–1090.
251
Dason, J.S., Emma Huertas, I., Colman, B., 2004. Source of inorganic carbon for photosynthesis in two marine dinoflagellates. J. Phycol. 40, 285–292. de Brouwer, J.F.C., Stal, L.J., 2002. Daily fluctuations of exopolymers in cultures of the benthic diatoms Cylindrotheca closterium and Nitzchia sp. (Bacillariophyceae). J. Phycol. 38, 464–472. Faust, M.A., Chróst, R.H., 1981. Photosynthesis, extracellular release and heterotrophy of dissolved organic matter in Rhode River estuarine plankton. In: Neilson, B.J., Cronin, L.E. (Eds.), Estuaries and Nutrients: Contemporary Issues in Science and Society. Humana Press, Clifton, N.J., pp. 465–479. Ferguson, R.L., Buckley, E.N., Palumbo, A.V., 1984. Response of marine bacterioplankton to differential filtration and confinement. Appl. Environ. Microbiol. 47, 49–55. Hamdan, L.J., Jonas, R.B., 2006. Seasonal and interannual dynamics of free-living bacterioplankton and microbially labile organic carbon along the salinity gradient of the Potomac River. Estuar. Coasts 29, 40–53. Hamdan, L.J., Huff, T.B., Jonas, R.B., in review. Determination of glycolic acid in un-concentrated estuarine water samples by liquid chromatography electrospray ionization mass spectrometry. Mar. Chem. Hobbie, J.E., Daley, R.J., Jasper, S., 1977. Use of nuclepore filters for counting bacteria by fluorescence microscopy. Appl. Environ. Microbiol. 33, 1225–1228. Hoch, M.P., Kirchman, D.L., 1993. Seasonal and inter-annual variability in bacterial production and biomass in a temperate estuary. Mar. Ecol., Prog. Ser. 98, 283–295. Jensen, L.M., 1983. Phytoplankton release of extracellular organic carbon, molecular weight composition, and bacterial assimilation. Mar. Ecol., Prog. Ser. 11, 39–48. Jensen, L.M., 1984. Antimicrobial action of antibiotics on bacterial and algal carbon metabolism: on the use of antibiotics to estimate bacterial uptake of algal extracellular products (EOC). Arch. Hydrobiol. 99, 423–432. Jensen, L.M., Søndergaard, M., 1985. Comparison of two methods to measure algal release of dissolved organic carbon (EOC) and the subsequent uptake by bacteria. J. Plankton Res. 7, 41–56. Johnson, K.M., Sieburth, J.M., 1977. Dissolved carbohydrates in seawater. I. A precise spectrophotometric analysis for monosaccharides. Mar. Chem. 5, 1–13. Jonas, R.B., Tuttle, J.H., 1990. Bacterioplankton and organic carbon dynamics in the lower mesohaline Chesapeake Bay. Appl. Environ. Microbiol. 56, 747. Jonas, R.B., Tuttle, J.H., Stoner, D.L., Ducklow, H.W., 1988. Duallabel radioisotope method for simultaneously measuring bacterial production and metabolism in natural-waters. Appl. Environ. Microbiol. 54, 791–798. Lancelot, C., Billen, G., 1984. Activity of heterotrophic bacteria and its coupling to primary production during the spring phytoplankton bloom in the southern bight of the North-Sea. Limnol. Oceanogr. 29, 721–730. Larsson, U., Hagström, A., 1982. Fractionated phytoplankton primary production, exudate release and bacterial production in a Baltic eutrophication gradient. Mar. Biol. 67, 57–70. Leboulanger, C., Descolas-Gros, C., Jupin, H., 1994. HPLC determination of glycolic acid in seawater. An estimation of phytoplankton photorespiration in the Gulf of Lions, western Mediterranean Sea. J. Plankton Res. 16, 897. Leboulanger, C., Oriol, L., Jupin, H., Descolas-Gros, C., 1997. Diel variability of glycolate in the eastern tropical Atlantic Ocean. Deep-Sea Res., Part 1, Oceanogr. Res. Pap. 44, 2131–2139.
252
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
Leff, L.G., Dana, J.R., McArthur, J.V., Shimkets, L.J., 1993. Detection of Tn5-like sequences in kanamycin-resistant stream bacteria and environmental DNA. Appl. Environ. Microbiol. 59, 417–421. Maurin, N., Amblard, C., Bourdier, G., 1997. Phytoplanktonic excretion and bacterial reassimilation in an oligomesotrophic lake: molecular weight fractionation. J. Plankton Res. 19, 1045–1068. McArthur, J.V., Tuckfield, R.C., 2000. Spatial patterns in antibiotic resistance among stream bacteria: effects of industrial pollution. Appl. Environ. Microbiol. 66, 3722–3726. Münster, U., Chróst, R.J., 1990. Origin, composition, and microbial utilization of dissolved organic matter. In: Overbeck, J., Chróst, R.H. (Eds.), Aquatic Microbial Ecology: Biochemical and Molecular Approaches. Springer-Verlag, New York, pp. 8–46. Nagata, T., 2000. Production mechanisms of dissolved organic matter. In: Kirchman, D.L. (Ed.), Microbial Ecology of the Oceans. WileyLiss, Inc., New York, NY, pp. 121–152. Parsons, T.R., Maita, Y., Lalli, C.M., 1984. A Manual of Chemical and Biological Methods for Seawater Analysis. Pergamon Press, Elmsford, NY. 73 pp. Riemann, B., Jensen, L.M., 1991. Measurements of phytoplankton primary production by means of the acidification and bubbling method. J. Plankton Res. 13, 853–862.
Riemann, B., Søndergaard, M., 1984. Measurements of diel rates of bacterial secondary production in aquatic environments. Appl. Environ. Microbiol. 47, 632–638. Sellner, K.G., Nealley, E.W., 1997. Diel fluctuations in dissolved free amino acids and monosaccharides in Chesapeake Bay dinoflagellate blooms. Mar. Chem. 56, 193–200. Søndergaard, M., Riemann, B., Jorgensen, N.O.G., 1985. Extracellular organic carbon (EOC) released by phytoplankton and bacterial production. Oikos 45, 323–332. Søndergaard, M., Worm, J., Williams, P.J.L.B., Cauwet, G., Riemann, B., Robinson, C., Woodward, E.M.S., Terzic, S., 2000. Net accumulation and flux of dissolved organic carbon and dissolved organic nitrogen in marine plankton communities. Limnol. Oceanogr. 45, 1097–1111. Wright, R.T., Coffin, R.B., 1983. Planktonic bacteria in estuaries and coastal waters of northern Massachusetts — spatial and temporal distribution. Mar. Ecol., Prog. Ser. 11, 205–216. Zobell, C.E., Anderson, D.Q., 1936. Observations on the multiplication of bacteria in different volumes of stored sea water and the influence of oxygen tension and solid surfaces. Biol. Bull. 71, 324–342.
The use of antibiotics to reduce bacterioplankton uptake of phytoplankton extracellular organic carbon (EOC) in the Potomac River estuary Leila J. Hamdan ⁎, Robert B. Jonas Department of Environmental Science and Policy, George Mason University, MSN 5F2, 4400 University Drive, Fairfax, Virginia 22030, United States Received 25 August 2006; accepted 29 October 2006
Abstract Phytoplankton production and accumulation of extracellular organic carbon (EOC) was tracked during diel intervals in microcosms by inhibiting bacterioplankton assimilation of EOC with streptomycin and kanamycin. Bacterioplankton production (3H-thymidine incorporation) and metabolism (14C-glucose incorporation) were monitored in samples collected from the Potomac River estuary to determine the effect of the antibiotics. Particulate (i.e., raw water) primary production and EOC (i.e., water passing through 1.0 μm glass fiber filter) production rates were monitored to determine the impact of antibiotics on phytoplankton. In preliminary experiments, neither streptomycin nor kanamycin alone significantly inhibited bacterioplankton activity compared to controls, but when both were present secondary production and metabolism were reduced up to 90%, and remained as such for 45 h. During field evaluations using a streptomycin and kanamycin mixture (50 μM each) particulate primary production and EOC production were not statistically different in control and antibiotic treated samples indicating that the antibiotics did not negatively influence phytoplankton production rates. In the presence of antibiotics dissolved free amino acids (DFAA) and, to a lesser extent, monosaccharides were significantly elevated compared to controls. This study demonstrates that streptomycin and kanamycin are capable of inhibiting bacterioplankton metabolism and uptake of dissolved organic carbon (DOC) in the samples tested so that the contribution of EOC to the DOC pool and to bacterioplankton metabolism could be measured and assessed. © 2006 Elsevier B.V. All rights reserved. Keywords: Bacterioplankton; Extracellular organic carbon (EOC); Kanamycin; Phytoplankton production; Streptomycin
1. Introduction Dissolved organic carbon (DOC) accounts for a significant portion of total organic carbon in aquatic ⁎ Corresponding author. Present address: Marine Biogeochemistry Section, Code 6114, U.S. Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, District of Columbia 20375, United States. Tel.: +1 202 767 3364; fax: +1 202 404 8515. E-mail address: [email protected] (L.J. Hamdan). 0022-0981/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jembe.2006.10.054
ecosystems (Nagata, 2000). In some locations extracellular organic carbon (EOC) produced by phytoplankton is a significant source of autochonous DOC (Baines and Pace, 1991; Nagata, 2000). EOC is primarily composed of dissolved free amino acids (DFAA), carbohydrates and short chain organic acids (Chróst and Faust, 1983; Münster and Chróst, 1990; Leboulanger et al., 1997; Maurin et al., 1997; Søndergaard et al., 2000). Although reports of EOC production are numerous, few studies in eutrophied estuaries have examined this source of DOC.
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
Faust and Chróst (1981) reported on EOC released by phytoplankton in the Rhode River, a shallow subestuary of the Chesapeake Bay. In their study, EOC accounted for up to 50% of photo-assimilated carbon during a phytoplankton bloom, thus indicating the potential importance of EOC to carbon availability and cycling in that system. Recent reports indicate that DFAA and monosaccharides may double during a diel period in association with phytoplankton blooms in the Patuxent River Estuary, also a sub-estuary of the Chesapeake Bay (Sellner and Nealley, 1997). Some have reported on the tight coupling between phytoplankton EOC and bacterioplankton growth and metabolism (Chróst and Faust, 1983; Søndergaard et al., 1985; Münster and Chróst, 1990), which is likely attributable to the lability of EOC to bacterioplankton. Bacterioplankton may utilize up to 80% of phytoplankton EOC in some systems (Faust and Chróst, 1981; Larsson and Hagström, 1982; Lancelot and Billen, 1984). Studies that investigate the classes of molecules composing EOC and its rates of release by phytoplankton assist in resolving the principal sources of DOC in aquatic systems and lend insight to the importance of EOC to the microbial food web. However, because of the tight coupling between EOC release and bacterioplankton uptake it is difficult to observe accumulation of EOC or DOC in general in the presence of metabolically active bacterioplankton that may consume EOC at rates comparable to its production (Faust and Chróst, 1981; Larsson and Hagström, 1982; Lancelot and Billen, 1984). Hence, experiments that incorporate both bacterially active and bacterially inhibited samples may shed light on EOC production as well as consumption by bacterioplankton. Filtration and antibiotics have been used to track EOC transfer from phytoplankton to bacterioplankton with limited success (Cole et al., 1982; Jensen, 1983, 1984; Jensen and Søndergaard, 1985; Bjørnsen et al., 1988; Maurin et al., 1997). To render samples bacterioplankton-free by filtration requires sieving through membranes with a nominal pore size of 0.2 μm which may remove or physiologically stress phytoplankton and possibly alter EOC production rates (Jensen, 1983, 1984; Jensen and Søndergaard, 1985; McArthur and Tuckfield, 2000). Antibiotics have been used to suppress bacterioplankton in natural samples for varying time intervals (Cole et al., 1982; Jensen, 1983, 1984; Jensen and Søndergaard, 1985; Maurin et al., 1997). In one study polymixin reduced bacterioplankton uptake of DFAA by 75% compared to controls (Jensen, 1984). The study demonstrated significant inhibition on a short scale
243
(approximately 4 h) but did not evaluate if this inhibition was sustained during longer periods. In a study of EOC production in a oligomesotrophic lake, streptomycin suppressed bacterioplankton glucose metabolism for short periods (6 h) up to 62% of controls, but higher degrees of suppression for longer intervals were not investigated (Maurin et al., 1997). Another study analyzed vancomycin and mefoxithin inhibition on freshwater and estuarine bacterioplankton, and found that individually these only inhibited bacterioplankton DFAA metabolism up to 50% compared to controls (Jensen and Søndergaard, 1985). Few studies have specifically addressed the impact of prokaryotic antibiotics on phytoplankton EOC production and uptake by heterotrophic bacterioplankton. In one study, nearly 90% of bacterioplankton production (BP) was inhibited by streptomycin even when the experiment was carried out over a period of several days. Although these results were promising, the effect on bacterioplankton catabolism was not measured and significant inhibition of prokaryotic primary producers (up to 29%) was evident (Jensen, 1983). Because the effect of antibiotics on primary producers in many systems is unknown, and since secondary production and metabolism do not always co-vary, it is necessary to test amino glycoside antibiotics further before they can be used experimentally to decouple EOC production by phytoplankton and consumption by bacterioplankton. The purpose of this study was to determine if streptomycin and kanamycin used in tandem are capable of suppressing bacterioplankton production and metabolism under field conditions for up to 30 h. The main goal of this work was to demonstrate that the antibiotics could be effective at reducing bacterioplankton activity but have no significant impact on phytoplankton such that EOC production by phytoplankton and its accumulation during a diel cycle could be measured in the absence of bacterioplankton uptake. 2. Materials and methods 2.1. Sample collection and handling Water samples were collected at Station 3 (38.16 N, 76.59 W) in the main channel of the mesohaline Potomac River. A detailed description of this site is provided by Hamdan and Jonas (2006). On July 17, 2002 water samples were collected with a submersible impeller pump and hose system (Jonas and Tuttle, 1990) from a depth of 1 m and dispensed directly into four 7.5 L polyethylene cubitainers which were filled
244
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
simultaneously by alternating the hose between containers at 15-s intervals to homogenize the replicate samples. Two of the four samples were treated with a combination of streptomycin monosulfate and kanamycin monosulfate (Fisher Scientific) to yield a final concentration of 50 μM each. Preliminary laboratory experiments determined that this dose could yield reductions in BP and glucose turnover rate (GTR) by ≥ 90% of controls for up to 45 h (see Results). Antibiotic stock solutions were made in double distilled/deionized (DD/DI), sterile water within 15 min of sample inoculation. The concentrated stock was added separately to samples in appropriate volumes to yield the desired final concentration in a volumetric ratio of sample to antibiotic solution of approximately 1000:1. The samples were shaken gently to distribute the antibiotic solution. Two cubitainers were translucent and incubated in situ; the remaining were blacked out with aluminum foil and duct tape to reduce all light to sample and inhibit photosynthesis. One each of the light and dark samples was inoculated with antibiotics; the remaining two were left untreated as controls. The samples were identified as follows: dark control, light control, light antibiotictreatment (AT), dark AT. The samples were pre-incubated overnight under in situ conditions for 13 h to attain maximum inhibition of prokaryotes as determined by preliminary experiments (see Results). The experimental protocol conducted shipboard, began the following sunrise and concluded shortly after sunset. The cubitainers were sub-sampled at 3 h intervals, and between sampling were returned to a depth of 1 m (approximately one-half the depth of the euphotic zone). Samples were suspended on a boom to keep them out of the boat shadow and weights were attached to the bottom of the cubitainers to prevent them from rising to the surface. Samples were held in this manner for up to 30 h. Fig. 1 provides an overview of the sampling design. 2.2. Glucose metabolism The dual-label radioisotope method which simultaneously measures BP and GTR described by Jonas et al. (1988) was used. Ten-milliliter sub-samples were transferred to 20-mL all-polypropylene syringes. Prior to inoculation with radiolabeled substrates an abiotic control was heat killed (80 °C, 15 s) in a microwave. Sub-samples were inoculated with 50 μL of a mixture containing a final concentration of 1.2 μg L− 1 D[U-14C] glucose (ICN Radiochemicals). Measurements of monosaccharides (see Results) verified that glucose
additions increased the ambient monosaccharide pool by an average of 0.002% thus making this a true tracer assay. Samples were incubated for 30 min in situ in the dark, and killed by addition of 10 mL ice-cold 10% trichloracetic acid (TCA). Particle associated radioactivity was collected on 0.2 μm, cellulose ester membrane filters (Millipore Corp.) and rinsed with 5% TCA. Scintiverse II (Fisher Scientific) was added to filters and radioactivity was determined using a Beckman-Coulter model LS6500 liquid scintillation counter operating in dual DPM (3H/14C) mode. GTR was calculated by dividing the radioactivity on the filter by the total radioactivity added (measured from direct addition of the radioactive inoculum to scintillation cocktail). The monosaccharide metabolic rate was calculated by multiplying ambient monosaccharide concentration by the turnover rate. 2.3. Bacterioplankton production The dual-label radioisotope method (Jonas et al., 1988) described above was used to determine BP. Each sub-sample contained a final concentration of 5 nM 3Hmethyl-thymidine per liter in addition to D-[U-14C] glucose. Uptake was calculated as ñmole thymidine incorporated and converted to the rate of cells produced L− 1 h− 1 using a factor of 2 × 1018 cells produced per mole incorporated thymidine (16). The bacterioplankton cell production rate was converted to mg C L− 1 h− 1 according to Hoch and Kirchman (1993). 2.4. Bacterioplankton abundance Bacterioplankton abundance was determined according to Hobbie et al. (1977) with modifications described elsewhere (Hamdan and Jonas, 2006). Briefly, subsamples preserved with a final concentration of 2% 0.2 μm filtered formaldehyde were diluted 1:1 with 0.2 μm-filtered Potomac River water, stained with 0.1%, 0.2 μm-filtered acridine orange, collected on 0.2 μm black polycarbonate filters (Osmonics, Inc.) and observed at 1000× total magnification. An Optronics UTV1X single chip video camera and DEI-750 image integrator (Optronics Engineering) were used to capture high resolution images which were viewed and enumerated using Bioquant Nova Prime Image Analysis software. 2.5. Primary production Particulate primary production (PPP) was measured by tracking the uptake of NaH214CO3 as described by
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
245
Fig. 1. Design of field experiment. Samples were held in situ overnight for a 13 h pre-incubation period and for the duration of the experiment which began at T = 13 h. Samples for DOC measurements (monosaccharides, DFAA and glycolic acid) and EOC production rates were pre-filtered through Gelman type A/E glass fiber filters (nominal porosity 1.0 μm). All samples were collected in triplicate at 3 h intervals from T = 13 h to T = 25 h.
Parsons et al. (1984). Triplicate 10 mL samples were collected in 20-mL glass vials, inoculated with 80 μCi NaH2 14CO3 L− 1, and incubated for 1 h under in situ conditions. Incubations were terminated by placing samples in the dark and filtering through Gelman type A/E filters (nominal porosity 1.0 μm) (Pall Corp.) at approximately 125 mm Hg. Filters were placed in 20mL scintillation vials and acidified with 500 μL of 1 N hydrochloric acid to convert unincorporated 14CO3 to gaseous CO2 (Jensen and Søndergaard, 1985) and vented. Ten milliliters of Scintiverse II was added to the vials and radioactivity was determined using a Beckman-Coulter LS6500 scintillation counter. EOC production was measured using filtrate from samples filtered for PPP. Filtrate was transferred to 20mL scintillation vials acidified as for PPP, purged by bubbling air through the solution, and vented for an additional hour. The removal efficiency of 14CO2 by this
method was tested, although it has been used successfully by others (Jensen and Søndergaard, 1985; Riemann and Jensen, 1991; Maurin et al., 1997). For the test, replicate 10-mL control samples were inoculated with 80 μCi L− 1 Na2 14CO3, and incubated for 15 min to allow abiotic adsorption of the substrate. Samples were acidified and purged for 0 to 30 min and compared in triplicate to controls that only had the substrate addition. Compared to controls, 60% of 14CO3 remained in acidified samples after 0 min purging. After two minutes, approximately 35% remained and by 4 min, less than 0.22% remained. 2.6. Monosaccharides Monosaccharides were measured by the colorimetric method of Johnson and Sieburth (1977). Samples were filtered through Gelman type A/E glass-fiber filters,
246
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
collected in pre-combusted (450 °C for 4 h) glass 20-mL scintillation vials and frozen at − 20 °C until analysis. The assay reduces monosaccharides to sugar alcohols, oxidizes them to aldehyde groups and the final derivatization step with 3-methyl-2-benzothirazolione hydrazone hydrochloride (Sigma-Aldrich) produces a colored product. Absorbance was measured at 635 nm on a Perkin-Elmer Lambda 25 UV/VIS Spectrometer (Perkin-Elmer). 2.7. Dissolved free amino acids DFAA were determined according to Parsons et al. (1984). Samples were collected and preserved as for monosaccharide analysis. O-phthalaldehyde in a buffered reagent (0.4 M boric acid — pH 9.5) containing 2mercaptoethanol (all Sigma-Aldrich) was used to react primary amines to form fluorescent products and fluorescence was determined at an excitation wavelength of 342 nm and emission wavelength of 452 nm. Because both antibiotics used in this study contain hexose sugar and amino groups. They were detected during monosaccharides and DFAA analysis. To compensate for this the antibiotic mixture was prepared in DD/DI water at a final concentration of 50 μM each and measured by both methods so that the value could be subtracted from antibiotic treated samples. Thus, monosaccharide and DFAA data for antibiotic treated samples are the field observations minus an antibiotic correction factor. 2.8. Glycolic acid Glycolic acid was analyzed by liquid chromatography-mass spectrometry (LC-MS) using a Waters 2690 separations module and Micromass Z2000 single quadrupole MS with an electrospray ionization probe optimized to produce negative glycolate ions (Hamdan et al., in review). Separation occurred on a Polarity dC18 column. Glycolic acid was eluted isocraticly with 9 mM formate at 200 μL min− 1 after which, the mobile phase was run at gradient to 90% acetonitrile to purge the column. Samples were quantified using external glycolic acid standards. 2.9. Data analysis Data were analyzed to determine differences among treatments as a result of treatment effects using ANOVA F tests with Tukey–Kramer post-hoc test for variance at a significance level of P = 0.05. Statistical analyses were conducted on triplicate sub-samples collected every 3 h
to determine variance among treatments during the experiments. In addition, the experimental means (average of all measurements) of each treatment were compared. Analyses were conducted using SPSS version 12.0 (SPSS Inc.) and Minitab version 13.2 (Minitab, Inc.). 3. Results 3.1. Preliminary experiments to determine antibiotic dosage Three laboratory experiments using mesohaline Potomac River water were conducted to determine an effective dosage of antibiotics to suppress metabolic activity in natural bacterioplankton populations for extended times. Samples were collected as described above, transported to the laboratory and held at in situ temperature (in a re-circulating bath) for 11–45 h, and sampled every 3–6 h. The first experiment with streptomycin (6–50 μM) yielded reductions in GTR by approximately 40% compared to controls after 11 h of incubation. Streptomycin had no significant effect on BP. Because streptomycin is a protein synthesis inhibitor, preformed enzymes could continue to be active after the antibiotic addition; hence, a longer preincubation was required for this type of antibiotic. A second experiment tested streptomycin (50– 1000 μM), kanamycin (50–500 μM) and combined treatments of both (50 μM each). At concentrations up to 1000 μM streptomycin reduced GTR and BP by approximately 40% compared to controls. All concentrations of kanamycin significantly reduced BP and GTR (max 91 and 95%, respectively) compared to controls at T = 0 h by T = 45 h. The greatest suppression of metabolic activity resulted from streptomycin and kanamycin used together and yielded 80 and 78% reductions in BP and GTR (respectively) by T = 13 h compared to the control at T = 0 h and 87 and 81% (respectively) compared to the control at T = 13 h. At T = 45 h, the combined dose sustained reduction of BP and GTR up to 100 and 91% (respectively) of controls at T = 0 h. A final experiment only tested combined streptomycin and kanamycin treatments (25–200 μM). All treatments resulted in significantly lower BP and GTR compared to controls. The lowest antibiotic dose (25 μM each) had the least significant effect on bacterioplankton activity; however, there was no simple dose response effect as the highest dosage (200 μM each) was only slightly more effective. Both antibiotics present at 50 μM yielded reductions in BP and GTR
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
247
greater than 90% at T = 13 h, and remained as such for 24 h. 3.2. Field experiment 3.2.1. Bacterioplankton production and abundance Controls and the light AT were included for bacterioplankton analyses. At the onset of sampling (T = 13 h; 07:30 h) there was no significant difference in BP between light and dark controls (Fig. 2A). BP in the light AT was significantly lower than controls. At subsequent time points, BP in the dark control was generally equal to or less than the light control. However, at T = 25 h the difference between controls was significant due to a decline in BP in the dark control (Fig. 2A). BP in both controls was always significantly higher than the light AT. Overall, BP in the light AT was reduced by 91% of the light control and, 89% of the dark control. Bacterioplankton abundance was measured at T = 0 h to evaluate enclosure effects on abundance. At T = 0 h, abundance was 7.5 × 106 cells mL− 1 (not shown). Experimental means for the controls and light AT were 12.7 and 10.0 × 106 cells mL− 1, respectively. For the duration of the experiment, abundance did not differ significantly between controls (Fig. 2B), nor from T = 13 h to T = 25 h. At T = 16, 22 and 25 h abundance in one or both controls was statistically higher than the light AT (Fig. 2B).
Fig. 2. Bacterioplankton production (A) and abundance (B) in the dark-control (○), light-control (▵) and light antibiotic treatment (AT) (▿). Antibiotic treated samples were inoculated with streptomycin and kanamycin (50 μM each).
Fig. 3. Monosaccharide (A), dissolved free amino acids (B), and glycolic acid (C) concentrations in the dark-control (○), light-control (▵), light AT (▿) and dark AT (□). Samples handled as described in Fig. 2.
3.2.2. Monosaccharides, dissolved free amino acids and glycolic acid Monosaccharides ranged from 25 to 500 μg C L− 1 (all data) (Fig. 3A). The experimental mean for both controls and the light AT (80 μg C L− 1 ) was significantly lower than the experimental mean for the dark AT (146 μg C L− 1). At T = 16 h, monosaccharides in the dark AT were significantly elevated compared to all other treatments, and at T = 19 and 22 h was significantly elevated compared to both light treatments. DFAA ranged from 23 to 2650 μg C L− 1, and averaged 54 and 2010 μg C L− 1 in controls and ATs, respectively. The difference between controls and ATs was highly significant at all times (Fig. 3B). Experimental means for glycolic acid ranged between 90 and 500 μg C L− 1. The experimental mean for the dark control (172 μg C L− 1) was significantly lower than all other treatments (average 311 μg C L− 1) (Fig. 3C). The light control had the highest experimental mean (356 μg C L− 1). The light treatments tracked consistently with each other from T = 16 h through T = 25 h. At T = 16 and 22 h (10:30 and 16:30 h) glycolic
248
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
acid was significantly elevated in light treatments compared to dark treatments. 3.2.3. Glucose metabolism GTR in the light control averaged 15% h − 1 throughout the experiment (Fig. 4A). GTR in the dark control declined from T = 16 h to T = 25 h, and at T = 25 h did not differ significantly from the light AT. Otherwise, the difference between controls and the light AT was significant. Average GTR in the light AT (0.83% h− 1) was approximately 95% and 93% lower than experimental means for light and dark control respectively. Glucose metabolism in the light treatments tracked closely with GTR but deviated for the dark control (Fig. 4B). Instead of decreasing consistently
over the experiment, as did GTR in the dark control (Fig. 3A), the metabolic rate averaged 12 μg C L− 1 h− 1 for the majority of the experiment and declined only at T = 25 h. Despite the late decline in the dark control, experimental means for both controls were similar (10 μg C L− 1 h− 1), and significantly higher than the light AT (0.5 μg C L− 1 h− 1). 3.2.4. Primary production Experimental means for PPP were 11, 78 and 63 μg C L− 1 h− 1 in the dark control, light control and light AT, respectively. From T = 13 h to T = 19 h PPP in the dark control was significantly lower than both light samples (Fig. 4C). PPP in the light control and light AT was similar except at T = 19 h (13:30 h) as PPP in the light control was significantly higher (30%). EOC did not differ significantly among the treatments at any time during the experiment. Overall, EOC averaged 124, 149 and 154 μg C L− 1 h− 1 in the dark control, light control and light AT, respectively. EOC was highest in the light control at T = 16 h, and the light AT at T = 22 h (Fig. 4D). 4. Discussion 4.1. Bacterioplankton abundance and production
Fig. 4. Glucose turnover rate (A), particulate primary production (B) and EOC production in the dark-control (○), light-control (▵) and light AT (▿). Samples handled as described in Fig. 2.
With enclosure experiment there is an expected increase in bacterioplankton abundance due to what is commonly known as the “bottle effect” (Zobell and Anderson, 1936). Enclosure effects in experiments carried out in containers smaller than 1 m3 can cause increases in abundance of up to 500% (Ferguson et al., 1984). Although minor relative to what is typically expected, enclosure did cause an increase in planktonic abundance from T = 0 h. When the experimental means are compared to the control at T = 0 h, the overall increase is approximately 60%. The controls deviated from the T = 0 h value most significantly. Abundance did not differ significantly between T = 13 h and T = 25 h for any of the experimental groups and likewise, the difference in abundance between controls was not significant. Although there was an overall increase in abundance during this experiment, it appears that by the time sampling began at T = 13 h, population abundance had stabilized. During this study, only planktonic abundance was measured, and it should be noted that the enclosure possibly resulted in an increase in abundance on the cubitainers walls. Along with a significant increase in bacterioplankton abundance, an increase in BP would also be expected if the bottle effect were significant (Ferguson et al., 1984). A T = 0 h measurement of BP was not made and hence
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
deviations in BP from the onset of the experiment cannot be estimated. However, had the bottle effect been significant it would have been evident during the experimental period with a steady increase in BP in the controls. No significant increase was detected between time points in any of the treatments. To the contrary, in the dark control BP declined significantly at T = 25 h. The decline in BP in the dark control coincided with an increase in bacterioplankton abundance. Although on the surface this refutes the influence of enclosure on increasing abundance and production rates, a second explanation may be that while BP is an instantaneous measurement of the rate of DNA replication, the abundance measurement is a cumulative record of the events of the previous 3 h (Riemann and Søndergaard, 1984). It is possible that an increase in BP occurred prior to the sampling period at T = 25 h in the dark control but was not evident as the cells had already undergone a cycle of rapid growth. If it were merely the enclosure effect causing the increase in abundance and by proxy BP it would be expected in all treatments and since this was not the case, it is likely that the different trend in BP and abundance in the dark control were in response to treatment effects, and not experimental error. 4.2. Primary production, EOC accumulation and bacterioplankton metabolism A significant difference in the concentration of DFAA between the controls and the ATs was observed. This indicates that since bacterioplankton were metabolically suppressed by antibiotics, DFAA accumulated in the ATs under both light regimes due to a lack of bacterioplankton uptake. However, a clear indication of continual accumulation during the diel cycle was not evident since a linear increase in DFAA was not observed in any treatments. In general, the level of bacterioplankton suppression (production and metabolism) was approximately 90% of controls. It is possible that the remaining metabolically active population in the ATs could have accounted for enough removal of DFAA during the experiment such that their activity masked the further appearance of newly produced DFAA. Nevertheless, their activity was insignificant enough that the major accumulated fraction was evident. A similar significant difference in concentration between controls and ATs was expected for monosaccharides and glycolic acid; however, this was not the case. Only the dark AT had significantly elevated concentrations of monosaccharides compared to the
249
experimental means for the controls and the light AT. However, at T = 22 h the concentration of monosaccharides in the dark control was elevated compared to both light treatments. By contrast, the experimental mean for glycolic acid concentration in the dark control was significantly lower than all other treatments. The remaining metabolically active portion of the bacterioplankton population likely complicated these results and masked more subtle differences between control and AT groups; however, there appears to be a treatment effect evident in these samples related to light availability. 4.3. Light availability and EOC production Glycolic acid is a byproduct of photorespiration formed by the dephosphorylation of phosphoglycolate created from the oxidation of ribulose-1-5-bisphosphate (Leboulanger et al., 1994). Because of its specific origin, it may be a biomarker of EOC release and possibly its appearance enhanced in light samples. Because glycolic acid concentration was elevated and approximately equivalent in both the light control and light AT at approximately 10:30 and 16:30 h compared to both dark samples provides compelling evidence of the influence of light on glycolic acid production and by proxy, algal exudation of EOC. A similar trend in the data was observed for DFAA concentration in the light AT. Alternately, it can be argued that photo-oxidation of larger molecules under high irradiance was occurring and producing glycolic acid molecules. However if this were the case, the decrease in glycolic acid in both light treatments at T = 19 h would not be expected and instead appears to be an indicator of photo-inhibition due to the high sun angle at that time. Studies have demonstrated that low solar irradiance can cause an increase in EOC release, specifically in the form of carbohydrates by phytoplankton (de Brouwer and Stal, 2002; Dason et al., 2004). Light limitation appears to have influenced monosaccharide production during this study since accumulation was observed overall in the dark AT and towards the end of the experiment in the dark control. The experimental mean for the dark AT was significantly higher than all other treatments, and at T = 22 h, the dark control and dark AT were significantly higher than both light treatments. Data on bacterioplankton abundance, production and metabolism and phytoplankton production indicate that the monosaccharides may have continued to increase towards T = 25 h in the dark control, but due to bacterioplankton metabolism its appearance may have
250
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
been masked. Between T = 16 and 22 h, the decrease in GTR was coupled with an increase in monosaccharide concentration (at T = 22 h) and a steady rate of glucose metabolism. The decrease in GTR at T = 22 h is likely not the result of slower metabolic rates, but instead a larger substrate pool. An increase in the substrate pool 3 h prior could have been responsible for the increase in bacterioplankton abundance and concurrent decrease in GTR in the dark control at T = 25 h resulting from a reduction in carbon limitation due to the elevated supply of EOC (relative to PPP). The increased supply may have been in the form of monosaccharides, but accumulation was not observed in the dark control possibly because the bacterioplankton uptake rate matched the monosaccharide production rate. However, it is important to note that typically substrate limited bacterioplankton exhibit low or stable rates of BP (Wright and Coffin, 1983; Hamdan and Jonas, 2006) which implies that instead of declining, BP should have increased at T = 25 h. In the absence of data between T = 22 and 25 h we can only speculate that an increase in BP occurred prior to sampling and bacterioplankton abundance remains the only record of such an event. EOC in all treatments exceeded PPP for the majority of the experiment. Because of elevated PPP at T = 19 h, total primary production (TPP = PPP + EOC) in the light control was elevated compared to other treatments (not shown). Specifically, at T = 19 h, PPP in the light control was 30% higher than the light AT, indicating antibiotic suppression of phytoplankton at peak solar irradiance. Otherwise, there was no significant difference in TPP between the light control and light AT. The percent extracellular release (PER) in both light treatments did not differ significantly at any time (not shown). PER in the dark control exceeded both light treatments for the duration of the experiment. Mean PER in the dark control was 92%. PER for both light treatments averaged 71%, was highest at T = 25 h (sunset) (94%), and lowest at T = 19 h (mid-day) (46%) indicating light as a strong controlling factor for EOC production. 4.4. Bacterioplankton inhibition by antibiotics Earlier laboratory experiments indicated that neither streptomycin nor kanamycin alone was effective at sustaining reductions in bacterioplankton activity up to 90% of controls. As such, only a combination of both will be effective in controlling bacterioplankton metabolic activity (production and catabolism). Previ-
ous studies have demonstrated a lesser degree of kanamycin resistance compared to streptomycin and neomycin resistance (Leff et al., 1993; McArthur and Tuckfield, 2000) in freshwater bacterioplankton communities thus indicating that although similar, the mode of action between these two antibiotics is distinct. This may explain why the antimicrobial properties of one of these chemicals are enhanced by the presence of the other. Total inhibition of bacterioplankton activity was not generally achieved during this study, and others have argued that in order to predict accurately EOC production and utilization in enclosure experiments total inhibition must be achieved (Jensen and Søndergaard, 1985). It is evident that total inhibition would have been beneficial in determining subtle patterns in diel production and release of DFAA and monosaccharides since it seems likely that bacterioplankton assimilation of these components of EOC complicated the interpretation of results in ATs. Total bacterioplankton inhibition is vital in studies of oligotrophic systems where bacterioplankton abundance and production are lower and the difference between control and treated groups more subtle. However in the Potomac River, this was not the case since, in general, BP, abundance and GTR were significantly lower in the presence of antibiotics and DOC concentrations were at times significantly higher. Thus, > 90% bacterioplankton inhibition in eutrophied systems such as the Potomac River, would likely allow for informative predictions of phytoplankton EOC accumulation as well as bacterioplankton uptake of autochonous DOC. When using antibiotics to understand production, accumulation and bacterioplankton utilization of phytoplankton EOC it is important to be certain that the antibiotics are only affecting prokaryotic bacterioplankton and not significantly impacting phytoplankton assemblages. There was no significant difference between control and treated samples for EOC production and only one instance when PPP differed between control and AT groups. However, in some cases we did observe slightly elevated EOC production at times consistent with elevated glycolic acid and DFAA concentration in antibiotic treated samples. This might suggest that the antibiotic exerts a deleterious effect on phytoplankton and may enhance EOC production via autolysis. However the lack of a decline in PPP in general argues against this and instead suggests that in the absence of metabolically active bacterioplankton EOC may have accumulated even in the short time frame of the one hour
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
incubation. This finding supports the idea of using antibiotics in microcosms to study the production and release of EOC and to understand better the complex relationship between phytoplankton and bacterioplankton in eutrophied estuarine ecosystems. 5. Conclusions An antibiotic treatment capable of providing significant inhibition of bacterioplankton production and metabolism in natural bacterioplankton populations has been determined. BP and glucose metabolism were suppressed by an average of 90% compared to untreated controls when the antibiotics streptomycin and kanamycin were used in tandem. Except at maximum solar irradiance, antibiotics did not have a significant or lasting effect on total primary production rates and at no time had a significant impact on EOC production. Suppression of bacterioplankton appears to have allowed EOC, DFAA and to a lesser extent monosaccharides to accumulate in antibiotic treated samples. These data indicate that antibiotics are useful tools to be used in experiments aimed at refining estimates of EOC production and its contribution to the DOC pool. Acknowledgements This study was supported by the National Aeronautics and Space Administration, the Washington Area Explorers Club, George Mason University's Department of Environmental Science and Policy and the Stephen J. Wright Scholars Program. We thank D. Emerson for sharing his microscope and imaging system, T. Huff, T. Jordan and K. Lauer for analytical expertise, A. Sinha for field assistance and T. Boyd and R. Coffin for comments on the draft manuscript. [SS] References Baines, S.B., Pace, M.L., 1991. The production of dissolved organicmatter by phytoplankton and its importance to bacteria — patterns across marine and fresh-water systems. Limnol. Oceanogr. 36, 1078–1090. Bjørnsen, P.K., Riemann, B., Horsted, S.J., Nielsen, T.G., Pocksten, J., 1988. Trophic interactions between heterotrophic nanoflagellates and bacterioplankton in manipulated seawater enclosures. Limnol. Oceanogr. 33, 409–420. Chróst, R.H., Faust, M.A., 1983. Organic-carbon release by phytoplankton — its composition and utilization by bacterioplankton. J. Plankton Res. 5, 477–493. Cole, J.J., Likens, G.E., Strayer, D.L., 1982. Photosynthetically produced dissolved organic-carbon — an important carbon source for planktonic bacteria. Limnol. Oceanogr. 27, 1080–1090.
251
Dason, J.S., Emma Huertas, I., Colman, B., 2004. Source of inorganic carbon for photosynthesis in two marine dinoflagellates. J. Phycol. 40, 285–292. de Brouwer, J.F.C., Stal, L.J., 2002. Daily fluctuations of exopolymers in cultures of the benthic diatoms Cylindrotheca closterium and Nitzchia sp. (Bacillariophyceae). J. Phycol. 38, 464–472. Faust, M.A., Chróst, R.H., 1981. Photosynthesis, extracellular release and heterotrophy of dissolved organic matter in Rhode River estuarine plankton. In: Neilson, B.J., Cronin, L.E. (Eds.), Estuaries and Nutrients: Contemporary Issues in Science and Society. Humana Press, Clifton, N.J., pp. 465–479. Ferguson, R.L., Buckley, E.N., Palumbo, A.V., 1984. Response of marine bacterioplankton to differential filtration and confinement. Appl. Environ. Microbiol. 47, 49–55. Hamdan, L.J., Jonas, R.B., 2006. Seasonal and interannual dynamics of free-living bacterioplankton and microbially labile organic carbon along the salinity gradient of the Potomac River. Estuar. Coasts 29, 40–53. Hamdan, L.J., Huff, T.B., Jonas, R.B., in review. Determination of glycolic acid in un-concentrated estuarine water samples by liquid chromatography electrospray ionization mass spectrometry. Mar. Chem. Hobbie, J.E., Daley, R.J., Jasper, S., 1977. Use of nuclepore filters for counting bacteria by fluorescence microscopy. Appl. Environ. Microbiol. 33, 1225–1228. Hoch, M.P., Kirchman, D.L., 1993. Seasonal and inter-annual variability in bacterial production and biomass in a temperate estuary. Mar. Ecol., Prog. Ser. 98, 283–295. Jensen, L.M., 1983. Phytoplankton release of extracellular organic carbon, molecular weight composition, and bacterial assimilation. Mar. Ecol., Prog. Ser. 11, 39–48. Jensen, L.M., 1984. Antimicrobial action of antibiotics on bacterial and algal carbon metabolism: on the use of antibiotics to estimate bacterial uptake of algal extracellular products (EOC). Arch. Hydrobiol. 99, 423–432. Jensen, L.M., Søndergaard, M., 1985. Comparison of two methods to measure algal release of dissolved organic carbon (EOC) and the subsequent uptake by bacteria. J. Plankton Res. 7, 41–56. Johnson, K.M., Sieburth, J.M., 1977. Dissolved carbohydrates in seawater. I. A precise spectrophotometric analysis for monosaccharides. Mar. Chem. 5, 1–13. Jonas, R.B., Tuttle, J.H., 1990. Bacterioplankton and organic carbon dynamics in the lower mesohaline Chesapeake Bay. Appl. Environ. Microbiol. 56, 747. Jonas, R.B., Tuttle, J.H., Stoner, D.L., Ducklow, H.W., 1988. Duallabel radioisotope method for simultaneously measuring bacterial production and metabolism in natural-waters. Appl. Environ. Microbiol. 54, 791–798. Lancelot, C., Billen, G., 1984. Activity of heterotrophic bacteria and its coupling to primary production during the spring phytoplankton bloom in the southern bight of the North-Sea. Limnol. Oceanogr. 29, 721–730. Larsson, U., Hagström, A., 1982. Fractionated phytoplankton primary production, exudate release and bacterial production in a Baltic eutrophication gradient. Mar. Biol. 67, 57–70. Leboulanger, C., Descolas-Gros, C., Jupin, H., 1994. HPLC determination of glycolic acid in seawater. An estimation of phytoplankton photorespiration in the Gulf of Lions, western Mediterranean Sea. J. Plankton Res. 16, 897. Leboulanger, C., Oriol, L., Jupin, H., Descolas-Gros, C., 1997. Diel variability of glycolate in the eastern tropical Atlantic Ocean. Deep-Sea Res., Part 1, Oceanogr. Res. Pap. 44, 2131–2139.
252
L.J. Hamdan, R.B. Jonas / Journal of Experimental Marine Biology and Ecology 342 (2007) 242–252
Leff, L.G., Dana, J.R., McArthur, J.V., Shimkets, L.J., 1993. Detection of Tn5-like sequences in kanamycin-resistant stream bacteria and environmental DNA. Appl. Environ. Microbiol. 59, 417–421. Maurin, N., Amblard, C., Bourdier, G., 1997. Phytoplanktonic excretion and bacterial reassimilation in an oligomesotrophic lake: molecular weight fractionation. J. Plankton Res. 19, 1045–1068. McArthur, J.V., Tuckfield, R.C., 2000. Spatial patterns in antibiotic resistance among stream bacteria: effects of industrial pollution. Appl. Environ. Microbiol. 66, 3722–3726. Münster, U., Chróst, R.J., 1990. Origin, composition, and microbial utilization of dissolved organic matter. In: Overbeck, J., Chróst, R.H. (Eds.), Aquatic Microbial Ecology: Biochemical and Molecular Approaches. Springer-Verlag, New York, pp. 8–46. Nagata, T., 2000. Production mechanisms of dissolved organic matter. In: Kirchman, D.L. (Ed.), Microbial Ecology of the Oceans. WileyLiss, Inc., New York, NY, pp. 121–152. Parsons, T.R., Maita, Y., Lalli, C.M., 1984. A Manual of Chemical and Biological Methods for Seawater Analysis. Pergamon Press, Elmsford, NY. 73 pp. Riemann, B., Jensen, L.M., 1991. Measurements of phytoplankton primary production by means of the acidification and bubbling method. J. Plankton Res. 13, 853–862.
Riemann, B., Søndergaard, M., 1984. Measurements of diel rates of bacterial secondary production in aquatic environments. Appl. Environ. Microbiol. 47, 632–638. Sellner, K.G., Nealley, E.W., 1997. Diel fluctuations in dissolved free amino acids and monosaccharides in Chesapeake Bay dinoflagellate blooms. Mar. Chem. 56, 193–200. Søndergaard, M., Riemann, B., Jorgensen, N.O.G., 1985. Extracellular organic carbon (EOC) released by phytoplankton and bacterial production. Oikos 45, 323–332. Søndergaard, M., Worm, J., Williams, P.J.L.B., Cauwet, G., Riemann, B., Robinson, C., Woodward, E.M.S., Terzic, S., 2000. Net accumulation and flux of dissolved organic carbon and dissolved organic nitrogen in marine plankton communities. Limnol. Oceanogr. 45, 1097–1111. Wright, R.T., Coffin, R.B., 1983. Planktonic bacteria in estuaries and coastal waters of northern Massachusetts — spatial and temporal distribution. Mar. Ecol., Prog. Ser. 11, 205–216. Zobell, C.E., Anderson, D.Q., 1936. Observations on the multiplication of bacteria in different volumes of stored sea water and the influence of oxygen tension and solid surfaces. Biol. Bull. 71, 324–342.