Microbial Ecology

, Volume 75, Issue 4, pp 917–929 | Cite as

Ecological Patterns Among Bacteria and Microbial Eukaryotes Derived from Network Analyses in a Low-Salinity Lake

  • Adriane Clark Jones
  • K. David Hambright
  • David A. Caron
Environmental Microbiology


Microbial communities are comprised of complex assemblages of highly interactive taxa. We employed network analyses to identify and describe microbial interactions and co-occurrence patterns between microbial eukaryotes and bacteria at two locations within a low salinity (0.5–3.5 ppt) lake over an annual cycle. We previously documented that the microbial diversity and community composition within Lake Texoma, southwest USA, were significantly affected by both seasonal forces and a site-specific bloom of the harmful alga, Prymnesium parvum. We used network analyses to answer ecological questions involving both the bacterial and microbial eukaryotic datasets and to infer ecological relationships within the microbial communities. Patterns of connectivity at both locations reflected the seasonality of the lake including a large rain disturbance in May, while a comparison of the communities between locations revealed a localized response to the algal bloom. A network built from shared nodes (microbial operational taxonomic units and environmental variables) and correlations identified conserved associations at both locations within the lake. Using network analyses, we were able to detect disturbance events, characterize the ecological extent of a harmful algal bloom, and infer ecological relationships not apparent from diversity statistics alone.


Freshwater ecology Network analyses Bacterial community Microbial eukaryotic community Protists Microbial interactions 



The authors would like to thank James D. Easton, Anne C. Easton, and Richard Zamor for field measurements, sample collection and microscopical counts, and Bruce Roe and Fares Z. Najar for DNA sequencing. All sequences are located in the NCBI short read archive under project BioProject PRJNA195945.

Funding Information

Funding was provided by a grant from the Oklahoma Department of Wildlife Conservation through the Sport Fish Restoration Program (grant F-61-R) to KDH. Oklahoma Mesonet data are provided courtesy of the Oklahoma Mesonet, which is jointly operated by Oklahoma State University and the University of Oklahoma. Continued funding for maintenance of the observing network is provided by the taxpayers of Oklahoma.

Supplementary material

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Fig. S1

Graphs depicting the annual trajectories of P. parvum cell counts (a), and Prymnesium-affiliated OTUs (b and c) in Lebanon Pool (A and B) and Wilson Creek (a and c). Panel a shows the abundances of P. parvum cell counts in Lebanon Pool (black symbols and lines; left Y axis) and Wilson Creek (grey symbols and lines; right Y axis). Note different scales. Panels b and c show the relative abundances of 18S OTU1 (solid symbols), plus 16S OTU1 and 16S OTU12 (open symbols) in Lebanon Pool (b) and Wilson Creek (c). Note the different scales in (b) and (c). (JPEG 33 kb)

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Fig. S2

Histograms of all the permuted p-values associated with all Spearman correlations from a) Lebanon Pool and b) Wilson Creek. (JPEG 23 kb)

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Fig. S3

The frequency, on a log scale, of a microbial OTUs relative abundance plotted against its number of significant Spearman correlations with other OTUs or environmental variables for the data from Lebanon Pool (a) and Wilson Creek (b). Lines indicate the 95% confidence intervals for the number of correlations per OTU, and its relative abundances. The boxes highlight OTUs of interest: 1) the open boxes outlined in gray, in the upper right contain OTUs with large (outside the 95% CI) relative abundances and numbers of significant correlations; 2) the shaded boxes on the upper left contain OTUs with large (outside the 95% CI) relative abundances and small (outside the 95% CI) numbers of significant correlations; and 3) the shaded box on the lower right contains OTUs with small (outside the 95% CI) relative abundances and large (outside the 95% CI) numbers of significant correlations. The average number of correlations per OTU in Lebanon Pool was 43 (Std. Dev = 31) and the average in Wilson Creek was 31 (Std. Dev = 24). There were OTUs with high average relative abundances and a large number of correlations (A and B, open gray boxes) for example: in Lebanon Pool a Prymnesium plastid (16S_1 = 6.7% average abundance and 10 occurrences), a diatom plastid (18S_10 = 3% average abundance and 12 occurrences), and a SAR11 (OTU_4 = 1.8% average abundance and 12 occurrences), each had over 87 correlations. In addition, we observed nodes that fell outside the 95% confidence intervals for number of correlations and average relative abundances (upper left shaded boxes). Two fungal OTUs (18S_5 and 18S_168), one in Lebanon Pool and both in Wilson Creek were highly abundant yet had fewer than 8 correlations each (upper left shaded boxes). In contrast, in Wilson Creek (lower right shaded box), a chlorophyte (18S_190), a ciliate (18S_223), and a fungal (18S_288) OTU each had low relative abundances but a high (> 70) number of significant correlations. (JPEG 34 kb)

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Fig. S4

Log distributions representing the number of significant spearman correlations per microbial OTU or environmental variable within the networks from: a) Lebanon Pool, b) Wilson Creek, and c) shared at both locations. Closed symbols represent the distribution from the experimental microbial association networks, and open symbols represent distributions constructed from Erdös-Réyni model networks of the same size as the experimental networks. The upper inset graphs in each panel show Poisson distributions fit to the Erdös-Réyni model data with r2s of: a) Lebanon Pool = 0.80, b) Wilson Creek = 0.87, and c) shared = 0.87. The distribution for the shared microbial association network (c, lower inset) had a moderate fit r2 of 0.6 to a power curve. (JPEG 29 kb)

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Fig. S5

Spearman correlations between the nodes within the network diagrams revealed seasonal abundance patterns among the microbial taxa shared at both locations. The networks were visualized with the unweighted force-directed layout (nodes in the network were positioned based on the number of Spearman correlations). OTUs with 75% or more of their relative abundances contained in the six month period of November-April (c) or May-October (d) are highlighted in yellow. Connections drawn from positive Spearman correlations are black solid lines, and those from negative correlations are gray dotted lines. All correlations (510 [>0.7 or <-0.7 and p-values ≤0.01]) are displayed in panels a, c and d. Only positive correlations (353) are displayed in panel b. Bacteria are red circles, eukaryotes are blue or purple (metazoa) diamonds, environmental parameters are orange squares, and chloroplasts are green circles. (JPEG 49 kb)

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Fig. S6

Network representations of selected individual positive Spearman correlations between a plastid’s OTUs and its likely photosynthetic eukaryotic host (i.e. 18S OTU or P. parvum cell count) are shown for the data from Lebanon Pool (a) and Wilson Creek (b). Connections represent positive Spearman correlations (>0.7 and p-values ≤0.01) and the exact values are written on the lines. Single-celled eukaryotes are blue diamonds, environmental parameters are orange squares, and chloroplasts are green circles. The size of the symbol reflects the average relative sequence abundance. The number on the symbols refers to the OTU identifier numbers. The following identification codes were used for the OTUs with good taxonomic resolution: Hap (haptophyte), Chr (chrysophyte), Chl (chlorophyte), Cry (cryptophyte), Dia (diatom), and Eug (euglenid), Dict (dictyophyte), UC (unclassified), Ppar (P. parvum cell counts). Refer to Tables S1 and S2 for a complete list of the OTUs and their identifications. (JPEG 89 kb)

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Adriane Clark Jones
    • 1
    • 2
  • K. David Hambright
    • 3
  • David A. Caron
    • 1
  1. 1.Department of Biological SciencesUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Department of Biological SciencesMount Saint Mary’s UniversityLos AngelesUSA
  3. 3.Program in Ecology and Evolutionary Biology, Department of BiologyUniversity of OklahomaNormanUSA

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