Experimental insights into the importance of aquatic bacterial community composition to the degradation of dissolved organic matter

Abstract

Bacteria play a central role in the cycling of carbon, yet our understanding of the relationship between the taxonomic composition and the degradation of dissolved organic matter (DOM) is still poor. In this experimental study, we were able to demonstrate a direct link between community composition and ecosystem functioning in that differently structured aquatic bacterial communities differed in their degradation of terrestrially derived DOM. Although the same amount of carbon was processed, both the temporal pattern of degradation and the compounds degraded differed among communities. We, moreover, uncovered that low-molecular-weight carbon was available to all communities for utilisation, whereas the ability to degrade carbon of greater molecular weight was a trait less widely distributed. Finally, whereas the degradation of either low- or high-molecular-weight carbon was not restricted to a single phylogenetic clade, our results illustrate that bacterial taxa of similar phylogenetic classification differed substantially in their association with the degradation of DOM compounds. Applying techniques that capture the diversity and complexity of both bacterial communities and DOM, our study provides new insight into how the structure of bacterial communities may affect processes of biogeochemical significance.

Figure 1

NMDS representation of bacterial communities from the four experimental treatments. NMDS ordination was derived from pairwise Bray–Curtis distances. Numbers depict replicates one, two and three. Hulls were drawn to group replicates within an experimental treatment. Abbreviations: Ba, Baltic; GW, groundwater; HL, headwater lake; VA, Vindelälven.

Figure 2

Trends of bacterial abundances (a) and DOC concentrations (b). Bacterial abundances and DOC concentrations were measured over the course of the experiment for the four treatments and the control (mean±s.e., n=3 replicates; except for time point 0, where n=1). Letters A and B in a denote significant differences between treatments with regard to bacterial abundances at the end of the experiment (A) or not (B), respectively, assessed by means of Tukey's post-hoc test on an ANOVA. Abbreviations: Ba, Baltic; C, control; GW, groundwater; HL, headwater lake; VA, Vindelälven.

Figure 3

Net changes in DOM fluorescence (a) and fluorescent intensities of components identified by PARAFAC analysis (b). (a) Excitation–emission matrices (EEMs) at the start of the experiment (n=1) together with the mean change and s.d. in fluorescence from the beginning to the end of the experiment across the three replicates for each treatment (n=3). Excitation (λEx) and emission (λEm) wavelengths are given on the x and y axis, respectively. (b) Pictures changes of fluorescent intensities of PARAFAC components: C₁, C₂, C₃ and C₄ (mean±s.e., n=3; except for time point 0 and time point 2 for VA only, where n=1). All components were normalised to zero for time point zero, except the ones in VA, which were normalised to zero for the second time point, as the measurement at time point zero had to be discarded owing to an erroneous reading. Insets visualise the respective spectral properties of the four fluorescent components identified by PARAFAC analysis. Abbreviations: Ba, Baltic; C, control; GW, groundwater; HL, headwater lake; VA, Vindelälven.

Figure 4

Results from principal component analysis of mass to charge ratios (m/z) that derived from ESI-MS. The first and second principal component explained 30.9% and 17.1% of the variability, respectively. Samples from both the beginning (not numbered) and end (numbered) of the experiment are visualised. Numbers depict replicates one, two and three. Hulls were drawn to group not only the replicates within a treatment but also the samples at the beginning of the experiment. Abbreviations: Ba, Baltic; C, control; GW, groundwater; HL, headwater lake; VA, Vindelälven.

Figure 5

Results from ESI-MS analyses. (a) An example for the mass spectra of DOM obtained from an experimental sample (that is, GW) at the beginning of the experiment. Mass to charge ratios (m/z) that were significantly reduced in intensity throughout the experiment are visualised in b. Numbers in brackets specify the total number of m/z significantly reduced in intensity per sample by the end of the experiment. (c) m/z that were significantly reduced in intensity by none of the four experimental treatments and their respective replicates (Times Reduced 0), all three replicates of just one treatment (Times Reduced 1), all three replicates of only two treatments (Times Reduced 2), all three replicates of three and all four experimental treatments (Times Reduced 3 and 4, respectively) by the end of the experiment. The dashed line visualises the distinction between LMWC (<600 m/z) and high-molecular-weight carbon masses (>600 m/z). Abbreviations: Ba, Baltic; C, control; GW, groundwater; HL, headwater lake; VA, Vindelälven.

Figure 6

Heatmap visualising the Spearman's rank correlation coefficients (Spearman's ρ) from the correlation analyses between the relative abundance of the 35 most abundant (that is, >100 reads per) OTUs at the end (rows) and the change in mass to charge ratios (m/z) from the beginning to the end of the experiment (columns). A high correlation coefficient (red) stands for a strong positive correlation between an OTU's relative abundance and the decrease in m/z from the beginning to the end of the experiment. The dendrogram clusters OTUs according to Spearman's ρ, whereas the colour columns depict affiliation of OTUs in accordance with taxonomic classification (from left to right: phylum, class and genus; colours match the legend to the right of the heatmap). The size of each bubble is proportional to the OTU's relative abundance.