The prevailing paradigm in aquatic science is that microbial methanogenesis happens primarily in anoxic environments. Here, we used multiple complementary approaches to show that microbial methane production could and did occur in the well-oxygenated water column of an oligotrophic lake (Lake Stechlin, Germany). Oversaturation of methane was repeatedly recorded in the well-oxygenated upper 10 m of the water column, and the methane maxima coincided with oxygen oversaturation at 6 m. Laboratory incubations of unamended epilimnetic lake water and inoculations of photoautotrophs with a lake-enrichment culture both led to methane production even in the presence of oxygen, and the production was not affected by the addition of inorganic phosphate or methylated compounds. Methane production was also detected by in-lake incubations of lake water, and the highest production rate was 1.8-2.4 nM·h −1 at 6 m, which could explain 33-44% of the observed ambient methane accumulation in the same month. Temporal and spatial uncoupling between methanogenesis and methanotrophy was supported by field and laboratory measurements, which also helped explain the oversaturation of methane in the upper water column. Potentially methanogenic Archaea were detected in situ in the oxygenated, methane-rich epilimnion, and their attachment to photoautotrophs might allow for anaerobic growth and direct transfer of substrates for methane production. Specific PCR on mRNA of the methyl coenzyme M reductase A gene revealed active methanogenesis. Microbial methane production in oxygenated water represents a hitherto overlooked source of methane and can be important for carbon cycling in the aquatic environments and water to air methane flux. epilimnic methane peak | methanogens A lthough methane makes up <2 parts per million by volume (ppmv) of the atmosphere, it accounts for 20% of the total radiative forcing among all long-lived greenhouse gases (1). In the aquatic environments, methane is also an important substrate for microbial production (2). The prevailing paradigm is that microbial methanogenesis occurs primarily in anoxic environments (3, 4). A commonly observed paradox is methane accumulation in well-oxygenated waters (2, 5), which is often assumed to be the result of physical transport from anoxic sediment and water (6-8) or in situ production within microanoxic zones (9-11). Two recent studies challenged this paradigm and suggested that microbes in oligotrophic ocean can metabolize methylated compounds and release methane even aerobically (12, 13). These claims are not without caveats, because the amounts of methylated compounds added [1-10 μM methylphosphonate (12) and 50 μM dimethyl sulfoniopropionate (13)] were far higher than their environmental concentrations, and therefore, the ecological relevance remains obscure. Moreover, dissolved oxygen (DO) was not monitored during the long incubation (5-6 d), and the possibility that the experimental setups had become anoxic before methane production could not be dismissed.* Despite the unce...

We report here, for the first time, that bacteria associated with marine snow produce communication signals involved in quorum sensing in gram-negative bacteria. Four of 43 marine microorganisms isolated from marine snow were found to produce acylated homoserine lactones (AHLs) in well diffusion and thin-layer chromatographic assays based on the Agrobacterium tumefaciens reporter system. Three of the AHL-producing strains were identified by 16S ribosomal DNA gene sequence analysis as Roseobacter spp., and this is the first report of AHL production by these ␣-Proteobacteria. It is likely that AHLs in Roseobacter species and other marine snow bacteria govern phenotypic traits (biofilm formation, exoenzyme production, and antibiotic production) which are required mainly when the population reaches high densities, e.g., in the marine snow community.

Quantifying the rate at which bacteria colonize aggregates is a key to understanding microbial turnover of aggregates. We used encounter models based on random walk and advection-diffusion considerations to predict colonization rates from the bacteria's motility patterns (swimming speed, tumbling frequency, and turn angles) and the hydrodynamic environment (stationary versus sinking aggregates). We then experimentally tested the models with 10 strains of bacteria isolated from marine particles: two strains were nonmotile; the rest were swimming at 20 to 60 m s ؊1 with different tumbling frequency (0 to 2 s ؊1 ). The rates at which these bacteria colonized artificial aggregates (stationary and sinking) largely agreed with model predictions. We report several findings. Bacteria colonize marine aggregates where they grow and are preyed upon. Bacteria typically occur on aggregates in concentrations that are orders of magnitude higher than in the ambient water (10,11,40). They cause aggregates to solubilize and remineralize, apparently at high rates (1, 36, 37). Even if microbial processes on aggregates account for only a small fraction of the total microbial activity in the water column (4, 40), seepage of dissolved organic matter from degrading aggregates can affect microbial processes even outside the aggregates. For example, the few available estimates of leakage rates from aggregates suggest that aggregates may be quantitatively significant dissolved organic matter sources for free bacteria and that the solute plumes trailing behind sinking aggregates may be important sites of bacterial growth (19,23,39). Thus, marine aggregates are not only sinking vehicles but also important components of the pelagic food webs. Bacterial activities on aggregates are key to understanding this role.In resolving the population dynamics of bacteria on aggregates one needs to consider the rate at which bacteria colonize the aggregates. Several studies have described the succession of microbes on aggregates (19,26,36,41,43), but few have examined the colonization process at a relevant-i.e., short (minutes)-time scale (15), and none have adequately considered the effect of the flow environment on colonization. A significant fraction of pelagic bacteria are motile (15,18,30), and simulation models have shown that motility and chemosensing capability are important for colonization, even of sinking aggregate (21, 23). Here we develop encounter models to predict colonization rates based on observed motility patterns of the bacteria and the hydrodynamic environments. We then compare model predictions with empirical measurements by using artificial aggregates. MATERIALS AND METHODS Models of colonization.The change in the number of bacteria on an aggregate due to colonization, dN/dt, equals the transport of bacteria toward the aggregate, F, which in turn depends on the ambient concentration of bacteria, C,where ␤ is the "encounter rate kernel," i.e., the imaginary volume of water from which the aggregate "collects" bacteria per unit time. ...

The phylogenetic diversity and seasonal dynamics of freshwater Actinobacteria populations in four limnologically different lakes of the Mecklenburg-Brandenburg Lake District (northeastern Germany) were investigated. Fluorescence in situ hybridization was used to determine the seasonal abundances and dynamics of total Actinobacteria (probe HGC69a) and the three actinobacterial subclusters acI, acI-A, and acI-B (probes AcI-852, AcI-840-1, and AcI-840-2). Seasonal means of total Actinobacteria abundances in the epilimnia of the lakes varied from 13 to 36%, with maximum values of 30 to 58%, of all DAPI (4,6-diamidino-2-phenylindole)-stained cells. Around 80% of total Actinobacteria belonged to the acI cluster. The two subclusters acI-A and acI-B accounted for 60 to 91% of the acI cluster and showed seasonal means of 49% (acI-B) and 23% (acI-A) in relation to the acI cluster. Total Actinobacteria and members of the clusters acI and acI-B showed distinct seasonal changes in their absolute abundances, with maxima in late spring and fall/winter. In eight clone libraries constructed from the lakes, a total of 76 actinobacterial 16S rRNA gene sequences were identified from a total of 177 clones. The majority of the Actinobacteria sequences belonged to the acI and acIV cluster. Several new clusters and subclusters were found (acSTL, scB1-4, and acIVA-D). The majority of all obtained 16S rRNA gene sequences are distinct from those of already-cultured freshwater Actinobacteria.