Coherent dynamics and association networks among lake bacterioplankton taxa - PubMed (original) (raw)
Coherent dynamics and association networks among lake bacterioplankton taxa
Alexander Eiler et al. ISME J. 2012 Feb.
Abstract
Bacteria have important roles in freshwater food webs and in the cycling of elements in the ecosystem. Yet specific ecological features of individual phylogenetic groups and interactions among these are largely unknown. We used 454 pyrosequencing of 16S rRNA genes to study associations of different bacterioplankton groups to environmental characteristics and their co-occurrence patterns over an annual cycle in a dimictic lake. Clear seasonal succession of the bacterioplankton community was observed. After binning of sequences into previously described and highly resolved phylogenetic groups (tribes), their temporal dynamics revealed extensive synchrony and associations with seasonal events such as ice coverage, ice-off, mixing and phytoplankton blooms. Coupling between closely and distantly related tribes was resolved by time-dependent rank correlations, suggesting ecological coherence that was often dependent on taxonomic relatedness. Association networks with the abundant freshwater Actinobacteria and Proteobacteria in focus revealed complex interdependencies within bacterioplankton communities and contrasting linkages to environmental conditions. Accordingly, unique ecological features can be inferred for each tribe and reveal the natural history of abundant cultured and uncultured freshwater bacteria.
Figures
Figure 1
NMDS of a Bray–Curtis resemblance matrix among 33 pelagic samples obtained from Lake Erken throughout a year. This analysis was based on re-sampled abundances of 1267 bacterial OTUs. Samples are grouped by season (see legend) and connected over time by the solid line.
Figure 2
Standardized abundance profiles (_z_-score) for identified tribes. Tribes with similar abundance profiles are plotted together according to their seasonality determined by k-means clustering. Each panel (a–j) includes two plots where the upper (stack) plot represents the average standardized abundance of the tribes in each cluster, whereas the lower plot represents the individual abundance profiles of each tribe. Panels are sorted according to the seasonal progression (succession). The numbers in parentheses following the tribe name correspond to phylum or sub-phylum names: (1) Actinobacteria, (2) α-proteobacteria, (3) β-proteobacteria, (4) γ-proteobacteria, (5) Bacteriodetes, (6) Cyanobacteria, (7) Verrucomicrobia, (8) OP10 and (9) Fibrobacteres. Different seasonal events are indicated by shading: (SPD) Spring diatom bloom, (ZOO) zooplankton bloom, (CYA) cyanobacterial bloom, (SUD) summer diatom bloom and (NIT) nitrification.
Figure 3
Sub-network organized around tribes within the actinobacterial lineages acI (a) and acIV (b). Sub-networks were extracted from the entire association network (see Supplementary Figure 5), including only the edges (correlations) between the target groups (actinobacterial lineage acI in panel a and acIV in panel b) and their associated groups and environmental variables (edges between non-targeted variables are not shown). The red rectangles represent freshwater bacterial tribes, with abbreviation according to Newton et al. (2011), where the strong red colored rectangles represent the target groups. The blue hexagons represent environmental variables. The black lines indicate positive correlations; the red lines indicate negative correlations; the dashed lines indicate a time shift in the correlations (lag of 1–3) and the arrows indicate the direction of the time shift (the arrow points to the variable lagging behind). The abbreviations for the environmental variables are translated as follows: absunfiltr, absolute water color; Amm, ammonium; BA, bacterial abundance; Cond, conductivity; LOI, loss on ignition; Oxy, Oxygen; PN, particulate nitrogen; PP, particulate phosphorus; secchi, secchi depth; Si, silicate concentration; SRP, soluble reactive phosphorus; Temp, temperature; TN, total nitrogen; TP, total phosphorus; Turb, turbidity.
Figure 4
Sub-network organized around α-proteobacterial (a) and β-proteobacterial (b) tribes. Sub-networks were extracted from the entire association network (see Supplementary Figure 5), including only the edges (correlations) between the target groups (α-proteobacterial tribes in panel a and β-proteobacterial in panel b) and their associated groups and environmental variables (edges between non-targeted variables are not shown). The red rectangles represent freshwater bacterial tribes, with abbreviation according to Newton et al. (2011), where the strong red colored rectangles represent the target groups. The blue hexagons represent environmental variables. The black lines indicate positive correlations; the red lines indicate negative correlations; the dashed lines indicate a time shift in the correlations (a lag of 1–3) and the arrows indicate the direction of the time shift (the arrow points to the variable lagging behind). The abbreviations for the environmental variables are translated as follows: BA, bacterial abundance; chla chlorophyll-a; Cond, conductivity; LOI, loss on ignition; PN, particulate nitrogen; PP, particulate phosphorus; secchi, secchi depth; Si, silicate concentration; SM, suspended matter; SRP, soluble reactive phosphorus; Temp, temperature; TN, total nitrogen; TP, total phosphorus; Turb, turbidity; WC, water color.
References
- Andersson AF, Riemann L, Bertilsson S. Pyrosequencing reveals contrasting seasonal dynamics of taxa within Baltic Sea bacterioplankton communities. ISME J. 2010;4:171–181. - PubMed
- Bahr M, Hobbie JE, Sogin ML. Bacterial diversity in an arctic lake: a freshwater SAR11 cluster. Aquat Microb Ecol. 1996;11:271–277.
- Bell RT, Stensdotter U, Pettersson K, Istanovics V, Pierson DC. Microbial dynamics and phosphorus turnover in Lake Erken. Adv Limnol. 1998;51:1–20.
- Bertilsson S, Eiler A, Nordqvist A, Jorgensen NOG. Links between bacterial production, amino-acid utilization and community composition in productive lakes. ISME J. 2007;1:532–544. - PubMed
- Cotner JB, Biddanda BA. Small players, large role: microbial influence on biogeochemical processes in pelagic aquatic ecosystems. Ecosystems. 2002;5:105–121.