Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Nov 5;12(11):e0144824.
doi: 10.1128/spectrum.01448-24. Epub 2024 Oct 14.

Dynamic microbiome diversity shaping the adaptation of sponge holobionts in coastal waters

Affiliations

Dynamic microbiome diversity shaping the adaptation of sponge holobionts in coastal waters

Bifu Gan et al. Microbiol Spectr. .

Abstract

The microbial communities associated with sponges contribute to the adaptation of hosts to environments, which are essential for the trophic transformation of benthic-marine coupling. However, little is known about the symbiotic microbial community interactions and adaptative strategies of high- and low-microbial abundance (HMA and LMA) sponges, which represent two typical ecological phenotypes. Here, we compared the 1-year dynamic patterns of microbiomes with the HMA sponge Spongia officinalis and two LMA sponge species Tedania sp. and Haliclona simulans widespread on the coast of China. Symbiotic bacterial communities with the characteristic HMA-LMA dichotomy presented higher diversity and stability in S. officinalis than in Tedania sp. and H. simulans, while archaeal communities showed consistent diversity across all sponges throughout the year. Dissolved oxygen, dissolved inorganic phosphorus, dissolved organic phosphorus, and especially temperature were the major factors affecting the seasonal changes in sponge microbial communities. S. officinalis-associated microbiome had higher diversity, stronger stability, and closer interaction, which adopted a relatively isolated strategy to cope with environmental changes, while Tedania sp. and H. simulans were more susceptible and shared more bacterial Amplicon Sequence Variants (ASVs) with surrounding waters, with an open way facing the uncertainty of the environment. Meta-analysis of the microbiome in composition, diversity, and ecological function from 13 marine sponges further supported that bacterial communities associated with HMA and LMA sponges have evolved two distinct environmental adaptation strategies. We propose that the different adaptive ways of sponges responding to the environment may be responsible for their successful evolution and their competence in global ocean change.

Importance: During long-term evolution, sponge holobionts, among the oldest symbiotic relationships between microbes and metazoans, developed two distinct phenotypes with high- and low-microbial abundance (HMA and LMA). Despite sporadic studies indicating that the characteristic microbial assemblages present in HMA and LMA sponges, the adaptation strategies of symbionts responding to environments are still unclear. This deficiency limits our understanding of the selection of symbionts and the ecological functions during the evolutionary history and the adaptative assessment of HMA and LMA sponges in variable environments. Here, we explored symbiotic communities with two distinct phenotypes in a 1-year dynamic environment and combined with the meta-analysis of 13 sponges. The different strategies of symbionts in adapting to the environment were basically drawn: microbes with LMA were more acclimated to environmental changes, forming relatively loose-connected communities, while HMA developed relatively tight-connected and more similar communities beyond the divergence of species and geographical location.

Keywords: coastal zones; environmental adaptative strategy; meta-analysis of microbiome; sponge holobiont; symbiotic microbial community; temporal variation.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig 1
Fig 1
Differences between HMA and LMA sponges. (a) Pictures of three sponge species (T, H, S) and transmission electron microscopy observation (T, H, S). (b) Alpha diversity of the microbial community. (c) Microbial community composition (phylum level). (d) Hierarchical clustering dendrogram of microorganisms in sponge and seawater. The dendrogram was constructed based on the Bray–Curtis distance method. T = Tedania sp., H = Haliclona simulans, S = Spongia officinalis, SW = seawater, with “B” signifying bacteria and “A” signifying archaea; bac = bacteria; sc = sponge cells.
Fig 2
Fig 2
Diversity and composition of microbial communities in sponges and seawater. (a and b) Alpha diversity (Shannon index) of the microbial community. (c) NMDS ordination of sponge and seawater microbial communities based on Bray-Curtis distances. (d and e) Microbial community composition (phylum level) under seasonal variation. The Arabic numerals in the x-axis represent different months in 1 year. Data = mean (n = 3). A significance of alpha diversity in different months is shown: *P < 0.05, **P < 0.01, ***P < 0.001. T = Tedania sp., H = Haliclona simulans, S = Spongia officinalis, SW = seawater, with “B” signifying bacteria and “A” signifying archaea.
Fig 3
Fig 3
Microbial community structure and its correlation with environmental factors. (a) Dynamics of seawater environmental parameters during the study period. CCA was used to analyze the relationships between microbial communities and environmental factors and between different taxa (b). T = Tedania sp., H = Haliclona simulans, S = Spongia officinalis, SW = seawater, with “B” signifying bacteria and “A” signifying archaea.
Fig 4
Fig 4
Properties of the correlation-based bacterial (a and b) and archaeal (c and d) networks. Network analysis shows the intra-associations within each subcommunity and inter-associations between different subcommunities. The size of each node is proportional to the number of connections (i.e., degree). The nodes are colored according to different types of taxa (a and c) and microbial community compositions at the phylum level (b and d). The numbers in brackets represent the percentage of nodes in different categories. N nodes, L links, AT abundant taxa, RT rare taxa, DT dominant taxa. T = Tedania sp., H = Haliclona simulans, S = Spongia officinalis, SW = seawater, with “B” signifying bacteria and “A” signifying archaea.
Fig 5
Fig 5
Ecological functions of sponges. (a) Venn diagram showing the numbers of unique and shared ASVs in the microbial community between sponges and seawater. (b) The niche width of the sponges and seawater microbial communities. Values = mean ± standard error, n = 3. T = Tedania sp., H = Haliclona simulans, S = Spongia officinalis, SW = seawater, with “B” signifying bacteria and “A” signifying archaea.
Fig 6
Fig 6
Microbiome diversity and ecological functions of diverse sponge species. (a) Map of sampling sites retrieved from the Sponge Microbiome Project. The map was drawn by Ocean Data View (ODV) version 5.2.0 (46). M northwest coast of the Mediterranean (42.05°N, 3.20°E, 2007), Hawaii, United States (21.43°N, 157.79°W, 2012). (b) NMDS ordination of microbial communities based on Bray-Curtis distances. (c and d) Hierarchical clustering dendrogram of sponge adults and seawater at the M (c) and U (d) stations retrieved from the Sponge Microbiome Project. The dendrogram was constructed based on the Bray–Curtis distance method. Sponge phenotype is indicated by shapes next to the species name. (e) Phylogenetic tree of the sponge 18S rRNA gene sequences constructed with the neighbor-joining method. The 18S rRNA gene sequence of H. simulans was not queried by the National Center for Biotechnology Information (NCBI) and was replaced by three sponges of the same genus. (f and g) Alpha diversity (Shannon index) of bacterial communities at the M (f) and U (g) stations. (h and i) The niche width of the sponges and seawater microbial communities at the M (h) and U (i) stations. Values = mean ± standard error, n ≥ 3. (j) topological characteristics of the MENs of diverse sponge-associated microorganisms, including links/nodes (L/N), average connectivity (agvK), Modularity (M) and Connectedness (Con). Aplysina cavernicola (Aca) (n = 6), Axinella damicornis (Ada) (n = 12), Cliona celata (Cce) (n = 3), Clathrina clathrus (Ccl) (n = 3), Cliona viridis (Cvi) (n = 6), Dysidea avara (Dav) (n = 11), Dysidea fragilis (Dfr) (n = 6), and Spongia agaricina (Sag) (n = 6) come from northwest coast of the Mediterranean. Axinella sp. (Axi), Agelas oroides (Aor), Crambe crambe (Ccr), Chondrosia reniformis (Cre), Petrosia ficiformis (Pfi) come from Hawaii, United States, and three replicate samples in all sponge species. A. oroides and S. agaricina were defined as HMA sponge, and A. damicornis, C. celata, C. viridis, C. clathrus, D. avara, D. fragilis, and Axinella sp. were defined as LMA sponge were according to Moitinho-Silva et al. (18). A. cavernicola, C. reniformis, and P. ficiformis were defined as HMA sponge and C. crambe was defined as LMA sponge were according to Gloeckner et al. (19).
Fig 7
Fig 7
HMA and LMA sponges have different adaptation strategies to cope with environmental changes. The symbiotic microbial communities of HMA sponges were highly abundant and diverse, had tight microbial association, maintained a stable microbial community composition, and had higher ecological resource utilization capacity. Therefore, it adopted a barrier-like adaptation strategy to cope with the variable environment. On the other hand, although the microbial diversity and abundance of LMA sponges were lower than those of HMA sponges, LMA sponges could adapt to environmental stress by more significant horizontal transmission, loose structure of the microbial community, and changing their microbial community composition, forming an open-like adaptation strategy. The drawing was done by Figdraw.

References

    1. Hacquard S, Garrido-Oter R, González A, Spaepen S, Ackermann G, Lebeis S, McHardy AC, Dangl JL, Knight R, Ley R, Schulze-Lefert P. 2015. Microbiota and host nutrition across plant and animal kingdoms. Cell Host Microbe 17:603–616. doi:10.1016/j.chom.2015.04.009 - DOI - PubMed
    1. Kümmerli R, Jiricny N, Clarke LS, West SA, Griffin AS. 2009. Phenotypic plasticity of a cooperative behaviour in bacteria. J Evol Biol 22:589–598. doi:10.1111/j.1420-9101.2008.01666.x - DOI - PubMed
    1. Bang C, Dagan T, Deines P, Dubilier N, Duschl WJ, Fraune S, Hentschel U, Hirt H, Hülter N, Lachnit T, Picazo D, Pita L, Pogoreutz C, Rädecker N, Saad MM, Schmitz RA, Schulenburg H, Voolstra CR, Weiland-Bräuer N, Ziegler M, Bosch TCG. 2018. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology (Jena) 127:1–19. doi:10.1016/j.zool.2018.02.004 - DOI - PubMed
    1. Drew GC, Stevens EJ, King KC. 2021. Microbial evolution and transitions along the parasite–mutualist continuum. Nat Rev Microbiol 19:623–638. doi:10.1038/s41579-021-00550-7 - DOI - PMC - PubMed
    1. Konopka A, Lindemann S, Fredrickson J. 2015. Dynamics in microbial communities: unraveling mechanisms to identify principles. ISME J 9:1488–1495. doi:10.1038/ismej.2014.251 - DOI - PMC - PubMed

LinkOut - more resources