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. 2023 Mar 23;9(1):12.
doi: 10.1038/s41522-023-00379-3.

The potential to produce tropodithietic acid by Phaeobacter inhibens affects the assembly of microbial biofilm communities in natural seawater

Pernille Kjersgaard Bech  1 , Sheng-Da Zhang  1 , Nathalie Nina Suhr Eiris Henriksen  1 , Mikkel Bentzon-Tilia  1 , Mikael Lenz Strube  1 , Lone Gram  2
Affiliations

The potential to produce tropodithietic acid by Phaeobacter inhibens affects the assembly of microbial biofilm communities in natural seawater

Pernille Kjersgaard Bech et al. NPJ Biofilms Microbiomes. .

Abstract

Microbial secondary metabolites play important roles in biotic interactions in microbial communities and yet, we do not understand how these compounds impact the assembly and development of microbial communities. To address the implications of microbial secondary metabolite production on biotic interactions in the assembly of natural seawater microbiomes, we constructed a model system where the assembly of a natural seawater biofilm community was influenced by the addition of the marine biofilm forming Phaeobacter inhibens that can produce the antibiotic secondary metabolite tropodithietic acid (TDA), or a mutant incapable of TDA production. Because of the broad antibiotic activity of TDA, we hypothesized that the potential of P. inhibens to produce TDA would strongly affect both biofilm and planktonic community assembly patterns. We show that 1.9 % of the microbial composition variance across both environments could be attributed to the presence of WT P. inhibens, and especially genera of the Bacteriodetes were increased by the presence of the TDA producer. Moreover, network analysis with inferred putative microbial interactions revealed that P. inhibens mainly displayed strong positive associations with genera of the Flavobacteriaceae and Alteromonadaceae, and that P. inhibens acts as a keystone OTU in the biofilm exclusively due to its potential to produce TDA. Our results demonstrate the potential impact of microbial secondary metabolites on microbial interactions and assembly dynamics of complex microbial communities.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Total cell counts.
The absolute abundance of the total microbial population and Phaeobacter spp. across all samples was estimated by qPCR and standardized to log10 transformed CFUs/cm or mL found in the microbial biofilm or in the planktonic suspension, respectively. Shown in black are means (dots) and standard deviation (error bars) and significance letters (LMM & EMM; p-value < 0.05) between the treatments per day. Source data are provided as a Source Data file.
Fig. 2
Fig. 2. Microbial community composition.
NMDS ordination plot of V3-V4 16S gene amplicon data from marine biofilm and planktonic communities treated with or without the WT and the dTDA P. inhibens using Bray-curtis distances (k = 3, stress = 0.087, non-metric fit, R2 = 0.993). Samples are stratified by A Time, B Treatment and C Environment. Source data are provided as a Source Data file.
Fig. 3
Fig. 3. Identification of taxa that were differentially abundant between the WT and the dTDA systems.
Taxa were identified by the ANCOM-BC model using a 95 % confidence interval (two-sided; Holm adjusted) and adjusted p-values. A Bubbles representing the size equivalent to the accumulated sum of unique genera that are enriched in the respective treatment relative to the other. B ASVs are aggregated to order level and represented by effect size (Log10 fold change). Bars are coloured according to the mean relative abundance of the order enriched by the treatment relative to the other. Source data are provided as a Source Data file.
Fig. 4
Fig. 4. Network analysis of key taxa.
A Co-occurrence comparison networks between 135 genera (nodes) found in the WT and dTDA treated systems at day 4 in the biofilm samples. Edges represent positive (green) and negative (red) correlations > |0.6| calculated by the SparCC method. Nodes represent ASVs aggregated to genus level together with the P. inhibens OTU. Eigenvector centrality of each node was used to define hubs (bold). B Genera directly associated to the P. inhibens OTU in each treatment plotted as a function of the increase in relative abundance in the WT relative to the dTDA treated systems identified by the ANCOM-BC analysis and the correlation strength found by the SparCC method. Node colors represent the taxonomic class of the genera and sizes were scaled according to their eigenvector centrality score. Source data are provided as a Source Data file.
Fig. 5
Fig. 5. Hypothetical model illustrating the effects of P. inhibens and TDA in modulating microbial community assembly.
Proposed functions of TDA as reviewed in Henriksen & Lindqvist et al. (2021) and suggestions for the direct or indirect increase of the relative abundance of different classes such as the Flavobacteria observed in the WT system compared to the dTDA system. A The mode of action of TDA has been proposed to disrupt the proton motive force in fast-growing heterotropic bacteria leading to the inhibition of these members of the community that otherwise would outcompete other slow growing bacteria and/or B Since TDA has the potential to bind to the AHL regulator that induces changes in motility and biofilm formation, mutations in the TDA gene cluster might affect the extracellular polymeric substance (EPS) composition of the dTDA strain. Consequently, Flavobacteria and other members of the Bacteroidetes might be able to exploit specific compositional elements of the WT EPS matrix as carbon source that are not present in the dTDA EPS matrix. The illustration was created in Biorender.com.
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