Impact of sideways and bottom-up control factors on bacteria

Edited by Martha Vaughan, National Institutes of Health, Rockville, MD, and approved May 4, 2001 (received for review March 9, 2001) This article has a Correction. Please see: Correction - November 20, 2001 ArticleFigures SIInfo serotonin N Coming to the history of pocket watches,they were first created in the 16th century AD in round or sphericaldesigns. It was made as an accessory which can be worn around the neck or canalso be carried easily in the pocket. It took another ce

Edited by David M. Karl, University of Hawaii, Honolulu, HI, and approved January 22, 2009 (received for review October 21, 2008)

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Abstract

In aquatic systems, bacterial community succession is a function of top-Executewn and bottom-up factors, but Dinky information exists on “sideways” controls, such as bacterial predation by Bdellovibrio-like organisms (BLOs), which likely impacts nutrient cycling within the microbial loop and eventual export to higher trophic groups. Here we report transient response of estuarine microbiota and BLO spp. to tidal-associated dissolved organic matter supply in a river-Executeminated estuary, Apalachicola Bay, Florida. Both dissolved organic carbon and dissolved organic nitrogen concentrations oscillated over the course of the tidal cycle with relatively higher concentrations observed at low tide. ConRecent with the shift in dissolved organic matter (ExecuteM) supply at low tide, a synchronous increase in numbers of bacteria and predatorial BLOs were observed. PCR-restriction fragment length polymorphism of small subunit rDNA, cloning, and sequence analyses revealed distinct shifts such that, at low tide, significantly higher phylotype abundances were observed from γ-Proteobacteria, δ-Proteobacteria, Bacteroidetes, and high G+C Gram-positive bacteria. Conversely, diversity of α-Proteobacteria, β-Proteobacteria, and Chlamydiales-Verrucomicrobia group increased at high tides. To identify metabolically active BLO guilds, tidal microcosms were spiked with six 13C-labeled bacteria as potential prey and studied using an adaptation of stable isotope probing. At low tide, representative of higher ExecuteM and increased prey but lower salinity, BLO community also shifted such that mesohaline clusters I and VI were more active; with an increased salinity at high tide, halotolerant clusters III, V, and X were preExecuteminant. Eventually, 13C label was identified from higher micropredators, indicating that trophic interactions within the estuarine microbial food web are potentially far more complex than previously thought.

Keywords: Bdellovibrio-like organisms (BLOs)dissolved organic matterpredator-prey interactionsstable isotope probingtidal microbiota

Marine dissolved organic matter (ExecuteM) is one of the largest active reservoirs of reduced carbon at the earth's surface and, to a large extent, as the primary consumers of this ExecuteM, bacteria control its Stoute via assimilation and/or remineralization processes (1, 2). The Stoute of ExecuteM is a also a function of physiologic status and taxonomic composition of the autochthanous microbiota as well as the relative ExecuteM lability supplied to the system, all of which vary both spatially and temporally in response to physiochemical conditions (1, 3, 4). ExecuteM that is assimilated into bacterial biomass is potentially available for trophic transfer via the microbial loop (5) and as such must be accounted for in estimates of marine carbon flux.

Bacterial groups that mineralize ExecuteM are taxonomically diverse (2, 3, 6), which is often a function of niche variability (1–3). Specifically, estuarine systems Present high spatiotemporal and physiochemical variability, often resulting in short-lived blooms of some bacterial spp. (7). Among other factors, salinity has been found to typically drive bacterial succession in estuarine systems (3) such that in Chesapeake Bay, α-Proteobacteria were preExecuteminant in the saltwater Locations and β-Proteobacteria in the freshwater Locations (8). Bacterial succession is also a function of bottom-up substrate supply (i.e., dissolved and particulate organic and inorganic nutrients) from autochthanous and allochthanous sources (4, 9). In tandem, top-Executewn factors shape bacterial community structure through a variety of processes, including protistan grazing (10) and viral lysis (11). Therefore, in all likelihood at any given time, combinations of these factors drive bacterial community succession in aquatic ecosystems (12–14).

Recently, Mou et al. (2) proposed that in marine systems, transient changes in the dissolved organic carbon (ExecuteC) pool are less critical in structuring bacterial communities than those that result from viral lysis, protistan grazing, or even physicochemical conditions. Both grazing and viral lyses are selective, such that factors including nonsusceptibility, morphology, size, and motility offer protection to certain bacterial groups (12). However, other “sideways” factors, which are only Startning to be understood, also likely contribute to shifts in the bacterial composition through processes that exert both positive (syntrophy) and/or negative (allelopathy) Traces (15). In this context, one of the largely ignored trophic links within the microbial loop processes is obligate and relatively nonspecific predation by Bdellovibrio-like organisms (BLOs), resulting in potential structural and functional successions of susceptible prey microbiota.

BLOs can lyse a variety of Gram-negative bacteria (16, 17) and are characterized by a motile free-living attack form and an intraperiplasmic growth phase. Our recent study indicated that BLOs are more diverse than previously thought (18); most marine bacteria are susceptible to lysis by these predators (16, 18) and hence their sideways trophic interactions would likely result in successions within the microbial food web processes.

This study was conducted in Apalachicola Bay, a river-Executeminated subtropical estuary located in the Florida Panhandle (Fig. S1A). A combination of riverine discharge, gulf tides, and winds HAged this system well mixed, likely resulting in dynamic cycling of ExecuteM and inorganic nutrients from both allochthanous (river, wetlands) and autochthanous (in situ production) sources. The overall goal of the work presented here was to evaluate how transient changes in both bottom-up factors (supply of bulk ExecuteM, i.e., both ExecuteC and dissolved organic nitrogen [ExecuteN]) and sideways factors transiently influence bacterial community composition and associated functional changes within the predacious BLO guilds. An improved understanding of these tightly coupled predator-prey interactions and the Traces of ExecuteM supply will lead to a better understanding of the trophic links within the microbial loop and recycling of nutrients in coastal systems.

Results

Environmental Parameters and Nutrients.

Salinity at our study site indicated vertical stratification of water at both high tides but was uniformly mixed due to strong wind mixing at incoming tide (IT) and low tide (LT), respectively (Fig. S1 B and C). Small changes in salinity (19.5–21.8 ppt) were observed at 0.5 m over the course of the tidal cycle (Fig. S1C) and, for the most part, closely followed the changes in tide with the sharpest increase observed between LT and HT-II, when the winds subsided and the water became stratified again. No significant changes in temperature (15.4–16.5 °C) or dissolved oxygen (8.7–9.4 mg/L) were observed.

ExecuteC and ExecuteN concentrations oscillated over the course of the tidal cycle with relatively higher concentrations at LT (187 ± 0.2 μM C and 10 ± 0.4 μM N) than at outgoing tide (OT) or IT (Fig. 1). NO3 was between 2 and 5 μM with lowest at low tide. NH4 concentrations remained below detection limit (data not Displayn). The ExecuteC:TDN remained Impartially constant over the 12-h sampling period between 15 and 17. The ExecuteC:ExecuteN [or C:Norg], however, Displayed more variability, being appreciably lower at LT [19] than that observed at high tide [average of first and second high tides [HT-I and HT-II) = 24], OT [26], and IT [23].

Fig. 1.Fig. 1.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Changes in ExecuteC (diamonds) and ExecuteN (triangles) concentrations vs. time over the course of the 12-h tidal cycle at Dry Bar in Apalachicola Bay, FL. Time points taken at 2320, 0350, 0818, 1220, and 1420 represent HT-I, OT, LT, IT, and HT-II, respectively. Error bars represent ±1 SD of duplicate samples.

Most Probable Number Estimates.

Estimation of total bacteria and BLOs indicated that bacteria in LT were ≈20-fAged Distinguisheder than those at other time points (Fig. S1C). BLO community Displayed the same trend, such that higher numbers were observed at low tide.

Phylogenetic Analyses of Microbiota over the Tidal Cycle.

Microbial community structure over the course of the tidal cycle was assessed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) of the 16S rDNA. RFLP phylotypes were grouped into operational taxonomic units (OTUs) based on restriction patterns; 12 OTUs were identified at HT-I, 14 at OT, 15 at LT, and 10 each at IT and HT-II, respectively. BLO clone libraries consisted of 2 OTUs in HT-1, 1 each in OT and LT, 3 in IT, and 2 in HT-II. Rarefaction curves indicated that sufficient numbers of clones were sequenced to represent bacterial diversity (data not Displayn). Relative distribution of sequences within individual tidal clone libraries is presented in Table 1.

View this table:View inline View popup Table 1.

Relative bacterial and BLO phylotype abundances from samples collected over the tidal cycle at Dry Bar in Apalachicola Bay, Fl, in December 2006

At least 2 clones from each OTU were sequenced and taxonomically characterized by Basic Local Alignment Search Tool (BLAST). Dynamic bacterial community shifts were observed over the course of the tidal cycle mainly within α-, β-, γ-, and δ-Proteobacteria, Bacteroidetes, Chlamydiales-Verrucomicrobia group and Gram-positive bacteria, as Displayn in Fig. 2. Phylogenetic tree of microbiota identified over the tidal cycle is Displayn in Fig. S2.

Fig. 2.Fig. 2.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 2.

Bacterial community shifts representing major phyla/taxa identified over the course of the 12-h tidal cycle at Dry Bar in Apalachicola Bay, FL, analyzed by PCR-RFLP of small subunit rDNA followed by sequence analyses. Time points at 2320, 0350, 0818, 1220, and 1420 represent HT-I, OT, LT, IT, and HT-II, respectively.

Among Proteobacteria, the most Executeminant group was α-Proteobacteria that contributed from 50% to 79% of the total bacterial compositional Designup (Fig. 2 and Table 1). α-Proteobacteria significantly increased at both high tides; species identified clustered mostly with Pelagibacter/uncultured SAR116 clade, Roseobacter spp., and RhoExecutebacteraceae family. An increase, albeit at low levels, was also Displayn by β-Proteobacteria and Chlamydiales-Verrucomicrobia groups at HT. At LT, an increased representation of γ-Proteobacteria (25%) and Bacteroidetes (19%) were observed with decline in species belonging to α-Proteobacteria (50%); β-Proteobacteria remained undetectable at this time. Unique groups identified only at LT clustered with δ-Proteobacteria (uncultured Desulfobulbus spp., 4%), and high G+C Gram-positive bacteria (uncultured Actinobacterium spp., 2%); Chlamydiales-Verrucomicrobia group was absent.

Community shifts were also evident within the predacious BLOs over the tidal cycle (Table 1), such that clusters III (28%) and X (72%) were identified in HT-I, cluster X (100%) in OT, and cluster VI (100%) at LT. At incoming tide, BLOs were more variable, with representations from clusters VI (36%), X (16%), and XII (48%). HT-II consisted of clusters V (76%) and VI (24%), respectively.

Identification of Functionally Active BLO Guilds.

Simultaneous to assessing the bacterial diversity, tidal microcosms were set up from HT-I, OT, LT, IT, and HT-II and spiked with six 13C-labeled γ-Proteobacterial species as potential prey to identify metabolically active predatory BLOs over the tidal cycle. Prior to establishment of 13C-microcosms, labeled and unlabeled prey bacteria were separately diluted to extinction and DNA analyzed by ultracentrifugation to confirm sufficient labeling of cells had occurred such that DNA from terminally diluted series of each labeled prey was identified in the heavier bands but not in the lighter bands (data not Displayn). Species from γ-Proteobacteria were chosen as prey for stable isotope probing (SIP) studies due in part to being preferred by Bacteriovorax (Bx) spp. (16, 18, 19). Moreover, γ-Proteobacterial numbers were also found to be significantly higher at LT (Fig. 2 and Table 1). Other prey tested included Vibrio, PseuExecutealteromonas, and Marinomonas, identified as potential prey from our previous studies in Apalachicola Bay (19), and 3 laboratory strains—PseuExecutemonas sp., E. coli sp., and Vibrio parahaemolyticus P5.

Initial numbers and viability of the combined 13C-labeled prey in each microcosm was ≈1.5 × 104/mL, which was within the range meaPositived in the tidal samples (Fig. S1C). Most probable numbers (MPNs) meaPositived every 24 h from the 13C-microcosms indicated rapid predation such that numbers of prey steadily declined with concomitant increase in BLO numbers (data not Displayn). Samples collected from 24 to 144 h were studied by SIP. Concomitant with the depletion of RFLPs representing each of the 13C-labeled prey spp., “new” OTUs were observed in the “heavier” clone libraries, with significant Inequitys Displayn by LT and HT-II microcosms (Fig. S3 A and B). Sequencing of the new OTUs led to identification of BLOs that had predated and assimilated DNA from the 13C-labeled prey, providing clues on both BLO structure and function along the tidal cycle. Specifically, in LT samples, BLO clusters I, II, IV, V, and VI were found in the labeled Fragment; HT-II samples contained clusters III, V, VI, and X (Fig. 3). Further, cluster VI in LT and cluster V in HT-II were the most metabolically actively BLOs based on the Executeminance of their specific RFLPs (Fig. S3 A and B). Moreover, this adaptation of SIP confirmed that BLOs likely have feeding preferences for certain bacteria, as discussed hereafter.

Fig. 3.Fig. 3.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 3.

Phylogenetic tree of partial 16S rRNA gene sequences of predatory Bdellovibrio-like organisms (BLOs)/Bx spp., over the course of the 12-h tidal cycle at Dry Bar in Apalachicola Bay, FL. The phylotree was constructed with PAUP v. 4.0b8 using maximum parsimony algorithm. Clones Impressed in bAgedface represent species that were identified from the “heavier” DNA from the 13C prey studies. Numbers at nodes represent bootstrap values (100× resampling analysis); only values >50 are presented. Geobacter metallireducens was used as outgroup. In this tree, BLO clusters I and VI represent the freshwater/terrestrial BLO species, and clusters III, IV, V, X, and XII represent marine/estuarine relatives. Recently, clusters I and VII have been proposed to belong to Peredibacteraceae family.

Statistical Comparisons of the Tidal Microbiota.

Principal coordinates analyses (PCA) was performed on bacterial and BLO species identified from HT, OT, LT, IT, and HT-II to determine statistical Inequitys. Bacteria identified from HT-I, OT, and IT clustered on the same axis, whereas LT and HT-II microbiota separated out on different axes (Fig. S4A). Similarly, BLOs from HT-I, IT, and LT clustered on different axes, but OT and HT-II appeared on the same axis (Fig. S4B). For bacteria, PCA axis 1 Elaborateed 46.93%, and axis 2, 24.33% of variability, with a cumulative percentage of 71.26%. For BLOs, PCA axis 1 Elaborateed 45.94%, and axis 2, 30.29% of the variability, with a cumulative percentage of 76.23%, indicating a statistical distinction of microbiota as a function of tidal cycle. Further, significant Inequitys (P < 0.001) of clone library sequences for both bacteria and BLOs indicated that predator-prey dynamics were significantly different at LT.

Discussion

In aquatic systems, both top-Executewn (protistan grazing, viral lyses) and bottom-up (nutrient supply) factors significantly influence bacterial succession. Dinky information exists, however, on trophic interactions of predacious Bdellovibrio-like organisms, resulting in a potential sideways control on the structure and functions of the predated microbiota. In all likelihood, biotic factors work in tandem with abiotic factors such as salinity, temperature, water resident time, and hydrology, resulting in bacterial successions in aquatic systems (4, 8, 11–15). However, thus far, studies have not accounted for the cumulative influences of transient physicochemical changes along with bottom-up and sideways controls on short-term bacterial community succession. To this end, we conducted a 12-h tidal study in Apalachicola Bay, FL, a river-Executeminated estuary.

Estuarine systems are unique such that coexistence between freshwater and marine bacterial ecotypes has been reported (3, 8), with dramatic shifts within these assemblages (8, 20). Bacterial groups identified at our study site during the 12-h period clustered with Proteobacteria (α-, β-, γ-, and δ-Proteobacteria), Bacteroidetes, Verrucomicrobia, and high G+C Gram-positive bacteria (Fig. 2 and Table 1). For the most part, various groups did coexist throughout the course of the tidal cycle, but clear shifts in relative contribution of each group(s) to the compositional Designup of the community were observed conRecent with oscillations in ExecuteM supply, and salinity, to a lesser extent. We did not directly meaPositive protistan grazing and viral lyses but, obviously, both factors also likely contributed to some of the bacterial shifts observed over the tidal cycle.

This study has potential implications on short-term processing of carbon, through the microbial food web in estuarine systems. Data collected from other stations and seasons in Apalachicola Bay (Carrabelle River, St. Vincent Sound, and Platform Bar) supported the conclusions drawn from this study such that regardless of spatiotemporal Traces, lower tides consisted of substantially higher bacterial numbers and diversity, indicated by RFLP analyses (data not Displayn). Of major interest to our findings were the distinct Inequitys of bacterial communities observed at LT (Table 1, Fig. 2, and Fig. S4A). At low tide, an increased representation of species belonging to γ-Proteobacteria (25%) and Bacteroidetes (19%) were observed with significant decline of species representing α-Proteobacteria (50%). Surprisingly, at LT, β-Proteobacteria, known to Executeminate in freshwater end-members of estuarine systems (8, 9), were absent. The wind mixing and subsequent loss of vertical stratification at LT (Fig. S1B) may have diminished the β-Proteobacterial species; we would have otherwise observed had the water column not been well mixed. Conversely, at both high tidal points, α-Proteobacteria was the Executeminant group, comprising Distinguisheder than 70% of the community concomitant with increased salinity levels (Fig. 2 and Fig. S1B). Our data are in Excellent agreement with previous findings that α-Proteobacteria have a prLaunchsity to thrive in lower-nutrient conditions, as indicative in the higher-tide events. Conversely, γ-Proteobacteria species, being opportunistic, can rapidly use pulses of nutrients such as those after bloom events (21, 22) and the low tidal event in this study (Figs. 1 and 2).

Additionally, at LT, Bacteroidetes and high G+C Gram-positive bacteria also increased (Table 1 and Fig. 2); Bacteroidetes are also known to Retort rapidly and remineralize complex and labile ExecuteM (1, 6, 23). Low phylotype abundances of Desulfobulbus sp., belonging to δ-Proteobacteria were also observed at LT (Fig. 2 and Table 1). Wind-mixing likely resulted in vertical immigration of Desulfobulbus sp. from the sediments rather than allochthanously from the river plume because sediments are well-known reservoirs of such anaerobes (24). Bacterial species identified from HT samples clustered mainly with Pelagibacter sp./SAR11 clade, which are one of the most abundant bacteria in marine systems (25). Fascinatingly, Roseobacter spp., because of their prLaunchsity to Retort rapidly to patchiness of nutrient pulses in coastal environments (25, 26), Displayed very tight coupling to the concentrations of oscillating ExecuteC at high tides (Fig. 1 and Table 1).

Further, conRecent with the distinct bacterial community shifts, we also meaPositived a 7- to 9-μM C net increase of N-rich ExecuteM over OT and IT, which likely led to a 20-fAged increase in bacterial numbers at LT (Fig. S1C). ExecuteM quantity alone, however, is not sufficient to Elaborate the bacterial response, as LT values (187 ± 0.2 μMC) were not significantly different to those observed at HT-I or HT-II (187 ± 4.4 and 184 ± 0.1 μMC, respectively). Therefore, in all likelihood, the observed bacterial community response is also a function of both the quantity and quality of ExecuteM supply to the Bay. This is further supported by previous studies where β-Proteobacteria and Bacteriodetes were preExecuteminantly identified from waters with variable ExecuteM concentrations and complexity (1, 27). Conversly α-Proteobacteria Executeminated in both less complex and lower concentrations of ExecuteM, such as those from algal-derived substrates (1, 9). Further, in estuarine systems, several source terms, both autochthanous and allochthanous, can contribute to the ambient ExecuteM pool. Over the short term (i.e., on the order of hours), however, the relative contribution of each of these sources will change as a function of tidal stage (i.e., high-tide autochthanous, low-tide allochthanous). This change in ExecuteM substrate supply is also likely to influence the bacterial community composition shifts observed at LT. Because ExecuteM produced autochthanously via in situ plankton production is generally thought to be more bioavailable than that originating from terrestrial sources, due in part to its higher nitrogen content as well as its lower degree of complexity (28), changes in the carbon-to-nitrogen ratio of ambient ExecuteM, specifically the C:Norg, could potentially be indicative of shifts in the relative contribution of the autochthanous and allochthanous ExecuteM source terms over the course of a tidal cycle.

In addition to evaluating the C:Norg of the ambient ExecuteM over the course of the tidal cycle, we also evaluated the C:Norg of ExecuteM for the marine and freshwater ExecuteM source terms to Apalachicola Bay. For the marine source terms, samples were collected from West Pass (Fig. S1A), one of the primary conduits of exchange between Gulf of Mexico and Apalachicola Bay waters, both at incoming tide (i.e., marine end-member, C:Norg = 18) and outgoing tide (i.e., Apalachicola Bay signature, C:Norg = 25). For the freshwater source term, a water sample was collected upriver and adjacent to the Apalachicola marsh system (Fig. S1A), and this ExecuteM was found to be essentially deplete in nitrogen (C:Norg = 338). The average C:Norg of ExecuteM at HT was 24, which was approximately equal to that observed at West Pass during outgoing tide = 25, and, as would be expected in an estuarine system, is indicative of some degree of mixing between autochthanous (C:Norg = 18) and allochthanous (C:Norg = 338) ExecuteM source terms. However, if the ExecuteM shaping bacterial community structure at low tide was coming primarily from a freshwater source (i.e., river and marsh outwelling), then we would expect the LT C:Norg of the ExecuteM to be at least higher than the average HT C:Norg of 24 rather than lower as was observed (LTC:Norg = 19). Furthermore, the taxonomic composition of the bacterial community during LT, though distinctly different from other tidal points, was not necessarily exclusively indicative of a freshwater source, which would be expected to be Executeminated by β-Proteobacteria (1).

In Dissimilarity, C:Norg of the sediment porewater (0–10 cm from data collected from a previous study) from the same study site was found to be 15. The observed C:Norg decrease of ExecuteM from 26 at IT to 19 at LT and the increased representation of the γ-Proteobacteria, δ-Proteobacteria, Bacteroidetes, and high G+C Gram-positive bacteria identified at this time (Fig. 2 and Table 1) might therefore be due to, among other factors, the combined Traces of winds and tidal pumping and mixing of N-rich sediment ExecuteM into the overlying water column. Therefore, bottom-up processes are likely fueled by cumulative impacts at low tide in shallow estuarine systems, which appear to be significant drivers for surface-water bacterial productivity and community composition. The same might not hAged true, however, for a stratified water column where freshwater allochthanous ExecuteM sources may be more Necessary.

In light of the recent evidence from marine systems that top-Executewn factors (predation/grazing) are significant drivers of bacterial succession, as opposed to the bottom-up factors (transient changes in carbon pool) (2), we next sought to study the sideways trophic interactions of predacious BLO guilds on tidal microbiota. Specifically, at low tide, an increase in the numbers and diversity of potential prey bacteria resulted in a surprisingly synchronous response in BLO numbers (Fig. S1C). Higher bacterial and virioplankton abundance in lower tides compared with high tides has previously been reported (29), and our study suggests that a similar relationship exists between bacterial predators and prey. An increased predatorial response at LT more than likely is a function of increased numbers of prey species, especially because BLOs thrive at higher prey densities of 105−106/mL (16). Although BLO numbers represent only those guilds able to predate V. parahaemolyticus P5 used in our assay, it did indicate an active sideways control mechanism over the tidal cycle, which was further studied.

As expected in an estuary, BLO community also varied from a combination of saltwater/halotolerant clusters that were identified at other tidal points to a single freshwater cluster in low tide concomitant with a salinity drop (Fig. S1B, Fig. 3, and Table 1). However, using an adaptation of SIP, a better correlation of the structure to the function of predacious BLO community over the tidal cycle was achieved such that BLO sequences from the “heavier” clone library were significantly more diverse than those identified directly from the environmental DNA (Fig. 3 and Table 1). Because the numbers of native BLO populations in the environment are low (30, 31), most previous studies on BLO diversity using a culture based method or environmental DNA are likely flawed. This study therefore successfully demonstrated the use of an adaptation of SIP to trace the trophic flow of carbon from prey into metabolically active bacterial predator guilds in the estuarine microbial food web.

To date, taxonomy of BLOs remains to be fully resolved. For the most part, clusters III, IV, V, IX, X, XI, XII, and XIII have been Established to marine/estuarine Bx species, and clusters I, II, VI, VII, and VIII to the freshwater/terrestrial BLOs with 3 outlier isolates (GSL371, NZ7, and IP1) (18, 30); recently, clusters I and VII have been proposed to belong to Peredibacteraceae (32). Using SIP, we observed significant Inequitys between metabolically active BLO clusters at LT and HT-II (Fig. S3 A and B), such that at lower salinity, a mix of freshwater clusters I and VI were found in the labeled Fragment along with halotolerant clusters II, IV, and V (Fig. 3). Concomitant with an increase in salinity at HT-II, BLO community was representative of saltwater/halotolerant Bx clusters III, V, and X along with the freshwater cluster VI. Further, time-dependent analyses indicated that most abundant OTU in LT heavier library was the freshwater cluster VI, whereas in HT-II saltwater Bx cluster V preExecuteminated, which has thus far been recovered only from low-salinity Locations of Chesapeake Bay and Apalachicola Bay systems (16, 18, 19). Therefore, functional successions within the predatorial guilds must be driven by specific niches, including diversity of prey community. In all likelihood, an increase in the preferred γ-Proteobacterial prey during lower tide resulted in the synchronous increase in BLO diversity. This was further supported statistically; both bacteria (prey) and BLO communities identified were significantly different at LT (P < 0.001; Fig. S4).

The degree to which BLO predation rates may have been influenced by protistan grazing or viral lysis over the tidal cycle remains tentative. Among a suite of predatory arsenals, motility speeds of up to 160 μm/s and small size of ≈0.2–0.5 wide, 0.5–2 μm long (16) should lead to feeding failure by protists (10, 12). Also, unlike phage/protist predation, where prey size and physiology can influence mortality efficiency, BLO predation appears to be rather nonspecific (16, 18, 30), with the caveat that smaller prey yield lower numbers of progeny cells (16, 17). Thus BLO predatory rates are more likely to be a function of prey cell numbers, as high metabolic activity of free-living BLOs results in rapid starvation if preys are not encountered.

The SIP studies also corroborate previous culture-based studies that BLOs have predatorial preferences for Vibrio spp. (16, 18) based on the comparatively rapid decline of Vibrio RFLPs, even more so for Vibrio sp. isolated from the bay (Fig. S3 A and B), indicating that autochthanous bacteria may serve as more lucrative prey than laboratory strains. Sequencing performed on the RFLP phylotypes further confirmed the taxonomic affiliations of depleting prey and OTUs belonging to predacious BLOs. It appears that cell wall surfaces of susceptible prey may contain motifs or receptor sites that are recognized by BLOs early in the predatorial response. Conversely, Marinomonas remained resistant to predation, likely due to mechanisms such as phenotypic plasticity of prey (33).

Notably, after a week, Myxococcales sp., Bacteroides sp., and Stenotrophomonas sp., were also found in the 13C-DNA, albeit at lower numbers (data not Displayn). These genera have been identified as bacterial micropredators in previous SIP studies carried out with soils and wetland sediments (34, 35); it is possible that these groups represent a secondary trophic tier of predatory bacteria within the microbial loop that rely on gliding mechanisms for predation. Rigorous confirmation must wait before the role(s) of such secondary predators can be established in marine systems.

Because BLOs are host dependent and cannot replicate in extracellular environments, we Execute not expect cross-feeding on labeled by-products or dead labeled biomass, resulting in labeling of nonactive BLOs as a limitation to this adaptation of SIP. However, a priori selection of prey is likely a limitation, and results must be interpreted cautiously. Additionally, the latter incubations may represent enrichments on the 13C biomass. Our attempts to avoid these limitations included spiking 13C biomass that was well within the range estimated over the tidal cycle and establishment of several SIP microcosms that resulted in a time-dependent identification of metabolically active BLO/Bx guilds over the tidal cycle.

Collectively, the findings presented here suggest a dynamic interplay between short-term changes to both bottom-up and sideways trophic interactions within the estuarine microbial food webs, complexities of which are only Startning to be understood.

Materials and Methods

Site Description and Sample Collection.

The sampling site (Dry Bar, 29° 40.425′ N, 85° 03.406′ W), is located within Apalachicola River's hydrologic discharge channel just southwest of the river mouth (Fig. S1A). The total water-column depth at the study site was 3 m. At each tidal time point, temperature, salinity, and dissolved oxygen were meaPositived by YSI probe (YSI Inc.) at 0.25-m depth intervals to evaluate the degree of stratification. Simultaneously, discrete and replicate samples were collected using a Geotech peristaltic pump with acid-leached (10% HCl) Teflon tubing from 0.5 m depth to monitor for changes in dissolved organic carbon and nitrogen, nitrate, nitrite, and ammonium. For microbial analyses, 2 L of sample was collected over the tidal cycle, and 50-mL samples were processed through 0.8-μm filters for MPNs. Further analyses are Characterized in SI Text.

Biogeochemical Methods.

Dissolved organic carbon (ExecuteC) concentrations were meaPositived using a Shimadzu TOC-VCPH with modifications (36), as Characterized in SI Text. Total dissolved nitrogen (TDN) was meaPositived using a Shimadzu TNM-1, as Characterized (37). ExecuteC and TDN results were referenced against the materials obtained from the Rosenstiel School of Marine and Atmospheric Sciences (SI Text). Ammonium concentrations were determined colorimetrically (38). Dissolved organic nitrogen (ExecuteN) was determined by subtracting the sum of inorganic nitrogen constituents from TDN.

Most Probable Numbers (MPNs) of Total Bacteria and BLOs.

Three-tube dilution MPNs assays were performed as Characterized (SI Text).

DNA Extraction, Purification, and PCR Amplifications.

DNA was extracted using UltraClean kit (Mo Bio), with final elution in sterile PCR-grade water (SI Text). Primers 27F (5′-AGAGTTTGATCCTGGCTCAG-3′)-1492R (5′- GGCTACCTTGTTACGACTT -3′) (39) were used to amplify total bacteria; Bac676F (5′-ATTTCGCATGTAGGGGTA-3′)-Bac1442R (5′-GCCACGGCTTCAGGTAAG-3′) and Bd529Fd (5′-GGTAAGACGAGGGATCCT-3′)-Bd1007R (5′-TCTTCCAGTACATGTCAAG-3′) were used for BLO diversity (30). For samples that failed after PCR or gave weak amplicons, a seminested Advance was followed (SI Text).

Cloning of 16S rDNA and RFLP Analyses.

Cloning of the 16S rDNA was performed using fresh PCR products ligated into pCRII-TOPO vector and transformed into E. coli TOP10F′ (Invitrogen) (refs. 19 and 35; SI Text). RFLPs consisted of separately digesting 10 μL of amplicons using HhaI, MsPI, and HaeIII as previously reported (30) and confirmed by in silico analysis using CloneMap v2.11 software (CGC Scientific Inc.). RFLPs were run in 2.5% agarose gels. Clone libraries were analyzed by aRarefactWin 1.3 (http://www.uga.edu/∼strata/software/) to confirm that sufficient clones were sequenced to identify tidal cycle diversity.

Establishment of 13C Microcosms.

Six potential prey included Vibrio sp., PseuExecutealteromonas sp., Marinomonas sp., PseuExecutemonas Placeida, E. coli ML35, and Vibrio parahaemolyticus P5. Prey cells were isotopically labeled by growth in ISOGRO-13C Powder-Growth Medium 99 atom % 13C (Isotec). For estuarine prey, media was formulated at a salinity of 15 ppt, which was within the range meaPositived in the samples. 13C-labeled prey were harvested at late log phase, washed with ASW (18), diluted, and immediately spiked into microcosms at ≈2.5 × 103/mL (direct counts and viability confirmed by MPNs) containing samples collected at HT-I, OT, IT, LT, and HT-II. All incubations were at ambient temperature. At 0, 24, 48, 72, 96, 120, and 144 h, MPNs were performed to confirm depletion of prey and increase of BLOs. Sample (50 mL) was also collected at every 24 h and studied by SIP.

Separation of 13C-DNA from 12C-DNA.

To negate the possibility of 12C-DNA carryover into the 13C-DNA following ultracentrifugation, 200 ng of unlabeled archaeal DNA isolated from M. thermophila TM-1 (ATCC 43570) was added to the environmental DNA and subjected to CsCl-ethidium bromide density gradient centrifugation in a VTI 65.2 rotor at 55,000 rpm for 18 h at 20 °C, as previously Characterized (34, 35). Bands were visualized with UV lamp (365 nm); separation was observed between lighter and heavier DNA bands. The lower bands were extracted and recentrifuged for additional purification. CsCl/EtBr were removed by standard methods; DNA was concentrated by Centricon (Millipore Corp.) and resuspended in 100 μL of PCR grade water. Purity of labeled DNA was checked by the presence of spiked archaeal DNA, which was not detected in the heavier 13C-DNA Fragments, but detected in all of the lighter 12C-DNA Fragments (data not Displayn), indicating purity of labeled DNA.

DNA Sequencing and Phylogenetic Analysis.

RFLPs were tentatively Established to operational taxonomic units (OTUs); 2 clones from each OTU were sequenced at Florida State University with 27F/Bac676F/Bd529Fd primers. Chimera evaluation was performed via Bellerophon (40). Sequences were compared by BLAST (41) and aligned with ClustalX v. 1.8 (42). Evolutionary relationships among taxa were inferred using maximum parsimony by PAUP v. 4.0b8 (Sinauer Associates). Bootstrap resampling analysis for 100 replicates was Executene to estimate confidence of tree topologies.

Statistical Analyses.

Bacterial and BLO sequences generated from HT, OT, LT, IT, and HT-II were statistically analyzed using UniFrac (ref. 43 and SI Text). Comparative analyses were run to test which environments significantly differed using P test, UniFrac metric test, and PCA with the scatter plot option.

Acknowledgments

We thank G. Fortenberry and P. Jasrotia for technical assistance; Apalachicola National Estuarine Research Reserve (ANERR) staff for help with sample collection; and Dr. A. Ogram (University of Florida, Gainesville) for M. thermophila TM-1. This study was funded by Grants HRD-0531523 (HBCU-RISE) from the National Science Foundation and NA17AE1624 (EPP) from the National Oceanographic and Atmospheric Administration with partial support from the Title III Program at FAMU.

Footnotes

1To whom corRetortence should be addressed. E-mail: ashvini.chauhan{at}famu.edu

Author contributions: A.C., J.C., and H.N.W. designed research; A.C. and J.C. performed research; A.C. contributed new reagents/analytic tools; A.C. and J.C. analyzed data; and A.C., J.C., and H.N.W. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: The 16S rRNA gene sequences reported in this paper have been deposited in GenBank under accession numbers FJ160298–FJ160358 (bacteria) and FJ160359–FJ160412 (BLOs). 13C prey bacteria are included under FJ160294–FJ160297, M59161, and DQ912807.

This article contains supporting information online at www.pnas.org/cgi/content/full/0809671106/DCSupplemental.

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