Bacterial regulation of coral larval metamorphosis and settlement in Pocillopora damicornis

Xiangrui Guo; Ying Zhang; Xiaoyu Tang; Qingsong Yang; Hao Sun; Juan Ling; Junde Dong; Yanying Zhang

doi:10.1038/s42003-025-08720-6

. 2025 Aug 23;8:1271. doi: 10.1038/s42003-025-08720-6

Bacterial regulation of coral larval metamorphosis and settlement in Pocillopora damicornis

Xiangrui Guo ^1,^#, Ying Zhang ^2,^#, Xiaoyu Tang ², Qingsong Yang ², Hao Sun ¹, Juan Ling ², Junde Dong ^2,^✉, Yanying Zhang ^1,^✉

PMCID: PMC12375082 PMID: 40849345

Abstract

Bacteria play a significant role in triggering coral larval metamorphosis and settlement in many coral species. However, the underlying molecular mechanisms behind coral larval metamorphosis and settlement triggered by bacteria remain enigmatic. Thus, we perform a bacteria-induced metamorphosis and settlement experiment using larvae of Pocillopora damicornis along with high-throughput sequencing, proteomic, and metabolomic analyses. Our results demonstrate that the Metabacillus indicus strain cB07 significantly alters the composition of the microbial community in cultured seawater and coral larvae. Genera associated with promoting coral larval metamorphosis and settlement, including Leisingera and Thalassobius, along with the anti - fouling genus Winogradskyella, undergo notable changes in the coral larvae and culture water. Differentially expressed proteins (DEPs) and metabolites (DEMs) in the cB07 - induced coral larvae are significantly enriched in the immune system, signal transduction, and energy metabolism. According to a protein and metabolite change model, strain cB07 induces coral larval settlement and metamorphosis through retinoic aldehyde pathway, the tricarboxylic acid cycle, and GABA synthesis. Our findings together help to elucidate how associated bacteria interact with coral holobionts and how M. indicus cB07 triggers coral larval metamorphosis and settlement, providing insight into the role bacteria play in marine invertebrates.

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Subject terms: Water microbiology, Molecular ecology

Microbial high-throughput sequencing combined with proteomic and metabolomic analyses reveal that Metabacillus indicus cB07 alters microbial communities and induces settlement of Pocillopora damicornis larvae via key metabolic pathways.

Introduction

Coral cover has decreased worldwide due to natural and anthropogenic stressors^1–3. As natural coral reef recovery after stress is slow even under optimal conditions^4,5, active coral restoration of degraded reefs has been taken up to minimize coral loss and enhance coral recovery⁶. Lately, coral transplantation has been used widely in coral restoration⁶. The coral seedings obtained via asexual and sexual propagation in nurseries are planted onto degraded reefs⁷. Sexually propagated seeding-based coral restoration has significant benefits owing to genetic diversity and environmental adaptability⁸. However, larval metamorphosis and settlement and post-settlement survival are bottlenecks in coral sexual propagation⁹. Coral lifecycles are typically characterized by planktonic larval and benthic adult life stages¹⁰. Many gametes are released by coral parents; however, only a few larvae develop into adult polyps⁸. During metamorphosis and settlement, reef-building stony corals undergo drastic morphological and habitat changes. A free-swimming, non-calcified coral larva grows into a sessile, calcified, and sedentary polyp¹¹. A successful larval metamorphosis and settlement is critical for coral development. Environmental conditions markedly affect larval metamorphosis and settlement by influencing larval ability to successfully metamorphose, feed, and grow⁸. In addition, exogenous factors, such as substratum-associated physical, chemical, or biological parameters, particularly free amino acids from conspecific individuals, bacterial quorum sensors, and extracellular polymeric substances, such as polysaccharides, lipids, or proteins affect larval metamorphosis and settlement^8,12. In recent decades, coral recruitment success has declined due to environmental degradation, making coral cover less likely to settle or metamorphose⁸.

Settlement cues are critical for establishing and maintaining marine benthic communities; their absence leads to delayed or halted settling. However, these cues likely vary among marine invertebrates species^13,14. Previous studies have shown that chemical cues from specific bacteria are essential for habitat selection and larval establishment in many marine invertebrates, including sponges, corals, and mussels^12,13. Microorganisms secrete metabolic products via functional outer membrane vesicles (OMVs), metamorphosis-associated contractile structures (MACs), and biofilms, which can significantly induce the settlement and metamorphosis of marine invertebrates’ larvae^15,16. However, these cues likely vary among bacterial species. Specifically, OMVs shed from gram-negative bacterial cell surface contain components, such as lipopolysaccharides, peptidoglycan, and flagellin proteins. These constituents are known to trigger metamorphosis and development in mussel larvae¹⁵. Pseudoalteromonas luteoviolacea, for instance, produces MACs that are pivotal in inducing metamorphosis in Hydroides elegans larvae¹⁶. In contrast, exposure to MACs from a mac-deficient P. luteoviolacea strain results in the failure of complete metamorphosis in H. elegans larvae¹⁶. Further experimentation has unveiled that the polysaccharide O-antigen from inductive gram-negative bacteria, such as Cellulophaga lytica HI1, Pseudoalteromonas luteoviolacea H1, Thalassotalea euphylliae H1, and Tenacibaculum aiptasiae T48, serves as an inductive element for H. elegans larvae¹⁷. Furthermore, tetrabromopyrrole (TBP) from Pseudoalteromonas has been identified as an inducer of coral larvae metamorphosis with and without settlement in various coral species^18,19. The members of genera Pseudoalteromonas have a bmp cluster responsible for TBP production⁸. In a previous study, we showed that the gram-positive bacterium cB07 is capable of inducing settlement and metamorphosis in Pocillopora damicornis^20,21. The genomic sequence analysis of cB07, however, revealed the absence of bmp and mac clusters, which are typically associated with TBP and MACs production in bacteria²⁰. This revealed that gram-positive bacteria may trigger the settlement and metamorphosis of coral larvae by secreting specific, yet unidentified, extracellular metabolites.

Bacteria-stimulated coral larval metamorphosis and settlement have been widely reported, and they serve as the basis for the recruitment of new corals in coral reef ecosystems^19,21–24. However, little is known about the mechanisms governing this bacterial-coral interaction²⁵. Previous sequencing and transcriptome studies have revealed that various sensory and signal transduction genes are involved in coral larval metamorphosis and settlement, including ion channels, neuropeptide receptors, and G protein-coupled receptors^24,26–29. However, genetic data are insufficient to reveal the complete molecular mechanism. As protein expression is highly dynamic and is regulated by post-transcriptional and post-translational modifications as well as protein degradation³⁰, there is no direct correlation between gene expression levels and protein abundance³¹. Simultaneously, the settlement of coral larvae is accompanied by metabolite changes. During the induction of coral larval settlement and metamorphosis by specific bacterial strains, notable shifts occur in the larval total carbohydrate, protein, and lipid content²¹. These changes not only reflect the transformation of larval physiological state and function but are also intricately linked to environmental adaptation and morphogenesis. However, a link between exogenous cues and endogenous factors has yet to be established. Due to the decline in coral reef ecosystems, molecular mechanisms underlying metamorphosis and settlement of reef-building coral larvae are of particular interest^8,21.

Coral larvae are associated with diverse microorganisms^32–34. We hypothesized that bacteria induce coral larval metamorphosis and settlement through exogenous bacterial inducers and coral symbiotic microorganisms. During this process, the proteome and metabolome of coral larvae undergo changes. These alterations are intricately connected to specific metabolic pathways, which are pivotal in mediating bacteria-induced metamorphosis and settlement of coral larvae. We conducted this study to investigate bacterial community composition, proteomics, and metabolomics during coral larval metamorphosis and settlement induced by Metabacillus indicus cB07. The aim was to determine how the proteins and metabolites of coral larvae and coral-associated bacterial communities respond to bacteria-triggered metamorphosis and settlement of coral larvae. Moreover, we clarified the key metabolic pathways involved in bacteria-induced coral larvae metamorphosis and settlement. By understanding the molecular triggers of bacteria-initiated coral metamorphosis, we may manipulate bacteria more effectively to restore coral reef ecosystems.

Results

Bacterial community composition

In this study, the timing of metamorphosis and settlement in bacteria-inoculated group and control group was not synchronized. We collected samples based on the morphological changes of metamorphosed and settled larvae²¹. Metamorphosis larvae were flat, buoyant, and unattached, with obvious septal mesenteries radiating from the central oral region. Settled larvae attached to the surface of the substrate and formed primary mesentery filaments²¹. We conducted an analysis of bacterial microbiota in coral larvae and culture water samples, categorized by developmental stage and treatment group, using 16S rRNA gene amplicons. Fifteen coral larvae samples yielded a total of 1,331,646 high-quality sequences and 5689 amplicon sequence variants (ASVs), with a median of 88,776 reads per sample. These sequences were randomly resampled to match the minimum depth of 589,960 sequences per sample. Fifteen coral culture water samples generated 1,266,679 high-quality sequences and 5162 ASVs, with a median read count of 84,445 per sample. The sequence data were resampled to the minimum depth of 639,250 sequences per sample.

To evaluate α-diversity of coral larvae’s bacterial microbiota, we used four indices: Richness, Shannon, Pielou, and Simpson indices. The results revealed no significant differences in bacterial Shannon index in coral larvae across different developmental stages and treatments (Tukey’s post hoc test, p > 0.05; Fig. 1a). However, significant differences in bacterial Shannon index and richness in coral culture water were observed between bacteria-inoculated metamorphosed larvae (BM) and metamorphosed larvae of the control group (CM) (Tukey’s post hoc test, p < 0.05; Fig. 1b, d). There were significant differences in bacterial richness of coral larvae at different developmental stages, with the metamorphosis stage significantly higher than the settlement stage (Tukey’s post hoc test, p > 0.05; Fig. 1c). Among all the groups, the BM group exhibited the highest richness (1031 ± 334) and Shannon index (4.72 ± 0.51) values (Fig. 1 and Supplementary Table 1). Comparisons of bacterial evenness across the five groups, as measured by Simpson and Pielou indices, revealed significant differences specifically between the BM and the settled larvae of the control group (CP) (Tukey’s post hoc test, p < 0.05; Supplementary Fig. 1b, d). The BM group demonstrated the highest Simpson index (0.97 ± 0.01) and Pielou (0.68 ± 0.04) values (Supplementary Fig. 1 and Supplementary Table 1).

Fig. 1 — a–d Alpha diversity indices, e, f principal co-ordinates analysis, a, c, e coral larvae; b, d, f culture water; (Different letters above boxes indicate significant differences based on Tukey’s post hoc test (α = 0.05). CF newly released larvae, CM metamorphosed larvae in control group, BM metamorphosed larvae in bacteria-inoculated group, CP settled larvae in control group, BP settled larvae in bacteria-inoculated group).

β-diversity, assessed by PCoA, indicated significant clustering within the control group’s metamorphosed and settled larvae, distinct from newly released larvae. Contrastingly, in the bacteria-inoculated group, metamorphosed and newly released larvae shared similar bacterial community compositions, differing from settled larvae (Fig. 1e). The coral culture water mirrored coral larvae clustering patterns in the control group, whereas in the bacteria-inoculated group, each developmental stage formed a distinct cluster (Fig. 1f). Nonparametric multivariate statistical methods (multi response permutation procedure [MRPP], permutational multivariate analysis of variance [Adonis], and analysis of similarities [ANOSIM]) using the Bray-Curtis dissimilarity index confirmed that larval developmental stage significantly influenced the bacterial community structure in coral larvae and culture water samples (p < 0.05, Supplementary Table 2).

Microbiota composition at different coral life stages

In our comprehensive analysis of coral larvae and culture water, we identified 27 bacterial phyla and 2 archaeal phyla in coral larvae and 27 bacterial phyla and 1 archaeal phylum in culture water. Proteobacteria was the dominant phylum in both cases, followed by Firmicutes, Bacteroidetes, Planctomycetes, and Cyanobacteria in coral larvae, and Bacteroidetes, Verrucomicrobia, Planctomycetes, and Patescibacteria in culture water (Fig. 2a, c).

Fig. 2 — a Coral larvae bacterial community composition at phylum level, b coral larvae bacterial community composition at genus level, c culture water bacterial community composition at phylum level, d culture water bacterial community composition at genus level. Taxonomic classification followed abundance-based thresholds: genera with >1% relative abundance was listed individually (others grouped as “other”), while phyla required >0.1% abundance for separate display. CF newly released larvae, CM metamorphosed larvae in control group, BM metamorphosed larvae in bacteria-inoculated group, CP settled larvae in control group, BP settled larvae in bacteria-inoculated group.

Specifically, in newly released coral larvae (CF), Proteobacteria and Bacteroidetes were predominant, constituting 66.56% and 13.42% of the total bacterial community, respectively (Fig. 2a). In CM, Proteobacteria and Planctomycetes became especially abundant, representing 41.30% and 15.02% of the community. Similarly, in BM, Proteobacteria and Firmicutes were highly abundant, at 41.66% and 14.79%, respectively. This trend was mirrored in CP, with Proteobacteria and Firmicutes accounting for 29.99% and 19.13%, respectively, of the community. Contrastingly, bacteria-inoculated settled larvae (BP) showed a high abundance of Proteobacteria and Bacteroidetes, comprising 60.45% and 21.26%, respectively. At the genus level, Rubritalea was the most dominant, followed by Enterobacter, Thalassobius, Romboutsia, and Clostridium (Fig. 2b and Supplementary Data 1). Myroides and Stenotrophomonas were notably present in high proportions in the CF group, whereas Rubritalea was abundant in CM and CP groups, at 7.95% and 16.24%, respectively. The BM group showed high abundance of Enterobacter and Helicobacter, whereas the CP group was characterized by Rubritalea and Romboutsia, contributing 16.24% and 5.29%, respectively, to the microbiome. The BP group exhibited significant abundances of Thalassobius and Winogradskyella, at 8.70% and 6.67%, respectively (Supplementary Data 1).

In coral culture water, a high abundance of specific bacterial phyla was identified across different groups. The CF group was characterized by a significant presence of Proteobacteria (62.65%) and Bacteroidetes (23.72%) (Fig. 2c). The CM group displayed a similar trend with a significant presence of Proteobacteria (45.86%), though Verrucomicrobia (28.96%) emerged as a substantial component. Likewise, the BM group showed high abundances of Proteobacteria (63.18%) and Bacteroidetes (24.72%). The CP group revealed a shift with Planctomycetes becoming a major phylum along with Proteobacteria, constituting 40.39% and 28.01% of the community, respectively. The BP group mirrored the high abundances of Proteobacteria and Bacteroidetes, representing 60.01% and 14.51% of total bacteria, respectively (Fig. 2c). Rubritalea was the most abundant genus, followed by Marivita, Rhodopirellula, Thalassobius, and Winogradskyella (Fig. 2d and Supplementary Data 2). Thalassobius and Neptuniibacter were notably abundant in the CF group, at 14.04% and 8.42%, respectively (Fig. 2d). The CM group was marked by high abundances of Rubritalea and Marivita, at 45.83% and 14.76%, respectively. The BM group showed high abundances of Leisingera and Winogradskyella, at 7.62% and 7.07%, respectively. The CP group had Rhodopirellula and Rubritalea in high abundance, at 37.19% and 15.07%, respectively, whereas the BP group exhibited high abundances of Marivita and Rubritalea, at 24.86% and 9.29%, respectively (Fig. 2d and Supplementary Data 2).

The linear discriminant analysis effect size (LEfSe) identified the enrichment of multiple bacterial phyla in coral larvae of the BM group, with Acidobacteria, Actinobacteria, Chloroflexi, and Gemmatimonadetes being prominent (Fig. 3a). Actinobacteria enrichment was driven by the class Acidimicrobiia, the order Propionibacteriales, and the family Nocardioidaceae. The family Lachnospiraceae was enriched in the BM group, although no higher taxonomic level enrichment was observed (Fig. 3a). Gemmatimonadetes enrichment was driven by the class S0134 terrestrial group. Classes Deltaproteobacteria and Alphaproteobacteria were enriched in the BP group. The orders Myxococcales, Rhodobacterales and Caulobacterales were key to Deltaproteobacteria and Alphaproteobacteria enrichment. The orders Flavobacteriales and Nitrosococcales were found to be enriched in the BP group, with Flavobacteriaceae and Methylophagaceae were the enriched families in these orders (Fig. 3a). The order Phycisphaerales, potentially represented by the family Phycisphaeraceae within this order, showed marked enrichment. The family Marinobacteraceae was enriched in the BP group, although no higher taxonomic level enrichment was observed. Genera, such as Thalassobius, Winogradskyella, SM1A02, Nautella, Erythrobacter, Methylophaga, and Nonlabens, which had an average abundance greater than 0.5%, were identified as core members of the settlement-related bacterial community in coral larvae (Supplementary Data 1).

Fig. 3 — a Coral larvae, b culture seawater. Taxa with significantly higher abundances (Kruskal–Wallis test, p value < 0.05, logarithmic LDA score >3.5) are defined as enriched taxa and are presented in the figure. CF newly released larvae, CM metamorphosed larvae in control group, BM metamorphosed larvae in bacteria-inoculated group, CP settled larvae in control group, BP settled larvae in bacteria-inoculated group. Different colors represent different groups. Enriched taxa with the same color as that of a group indicate the taxa that are significantly enriched in that group.

For the enrichment analysis (using LEfSe) of the culture water samples, Firmicutes, Bacteroidetes, and Proteobacteria were enriched in the BM group. Firmicutes enrichment was mainly driven by the family Bacillaceae. The family Flavobacteriaceae was vital for Bacteroidetes abundance (Fig. 3b). Proteobacteria enrichment was attributed to a diverse group, including the class Deltaproteobacteria, the order Caulobacterales, and the families Hyphomonadaceae and Marinobacteraceae. In the BP group, the class Alphaproteobacteria and Phycisphaerae were enriched, with contributions from the orders Rickettsiales and Rhodobacterales and the calss Phycisphaerae. The unclassified family AB1, family Rhodobacteraceae and order Phycisphaerales were pivotal for Rickettsiales, Rhodobacterales and Phycisphaerales enrichment, respectively (Fig. 3b). The order Chitinophagales was enriched, with the family Saprospiraceae as the prominent taxon within this order. Genera, such as Marivita, Winogradskyella, Leisingera, Nautella, SM1A02, Nonlabens, Donghicola, and Metabacillus, with average abundance over 0.5%, were considered settlement-related bacteria in culture water (Supplementary Data 2).

Alterations of molecules on the proteomic level

In this study, we employed proteomics to delineate protein expression profiles within complex biological samples of coral larvae. We identified 5469 proteins from a dataset comprising 34,311 peptides. Subsequently, we screened differentially expressed proteins (DEPs) between BP and CP groups to identify key proteins and their related pathways. Compared to control coral larvae, cB07 addition significantly downregulated 228 DEPs and upregulated 378 DEPs (Fig. 4a). Most of the downregulated DEPs were associated with thermogenesis, ribosomes, focal adhesion, Th1 and Th2 cell differentiation, and T cell receptor signaling pathway (Fig. 4b). Contrastingly, upregulated DEPs were predominantly associated with carbon metabolism, phagosomes, lysosomes, amino acid biosynthesis, glycolysis/gluconeogenesis, and one carbon pool by folate (Fig. 4c).

Fig. 4 — a Upregulated and downregulated DEPs in BP vs. CP groups, identified by Student’s t test with p < 0.05 and |Log2 FC | > 0. b KEGG annotation of downregulated DEPs. c KEGG annotation of upregulated DEPs. d Enriched KEGG pathways of downregulated DEPs in BP vs. CP groups, determined by Student’s t test with p < 0.05. e Enriched KEGG pathways of upregulated DEPs in BP vs. CP groups, evaluated by Student’s t test with p < 0.05. f DEP differences in BP vs. CP groups, as analyzed by Student’s t test with p < 0.05. BP settled larvae in bacteria-inoculated group, CP settled larvae in control group.

To elucidate the functional implications of these DEPs, we conducted an in-depth enrichment analysis of Kyoto encyclopedia of genes and genomes (KEGG) pathways with a significance threshold of Student’s t test with p < 0.05. We detected that pathways showing significant downregulation were involved in citrate cycle (TCA cycle), Th1 and Th2 cell differentiation, and T cell receptor signaling pathway (Student’s t test, p < 0.05; Fig. 4d). Although pathways involving thermogenesis, ribosome, and endocytosis were characterized by a relatively high number of DEPs, they did not exhibit significant enrichment. Conversely, significantly enriched upregulated KEGG pathways were predominantly associated with one carbon pool by folate, carbon metabolism, and proteasome (Student’s t test, p < 0.05, Fig. 4e). Finally, 16 potential DEP candidates were identified. These proteins either exhibited a relatively high fold-change (FC) or had been previously reported to participate in larval settlement and metamorphosis (Fig. 4f). These identified proteins have the potential to function as regulatory elements during coral larvae settlement and metamorphosis, thereby suggesting their significance in these crucial developmental stages.

Metabolites in settled coral larvae and culture medium

Our analysis of the metabolite profiles of the settled coral larvae and surrounding seawater provided insights into the influence of cB07 on coral larvae settlement. A total of 4234 metabolites were identified, with 3883 metabolites annotated in the human metabolite database (HMDB), accounting for approximately 91.7% of the total metabolites. In all settled coral larval samples, 3956 metabolites were detected. These included 1225 lipids and lipid-like molecules, 756 organic acids and their derivatives, and 508 organoheterocyclic compounds. In seawater samples, 2184 metabolites were detected, comprising 729 lipids and lipid-like molecules, 380 organic acids and their derivatives, and 315 organoheterocyclic compounds (Supplementary Table 3).

To gain a deeper understanding of metabolite alterations in coral larvae, we conducted a comprehensive screening of all metabolites to identify key differentially expressed metabolites (DEMs) associated with cB07. A total of 444 DEMs were found to be downregulated and 630 were upregulated (Supplementary Fig. 2). The composition of these DEMs exhibited a comparable pattern. Specifically, a significantly higher proportion of amino acid, peptides, and their analogs were observed in the upregulated and downregulated DEMs (Fig. 5a, b). By annotating the DEMs against the KEGG database, we observed that the downregulated and upregulated DEMs had a similar pattern (Fig. 5c, d). They were predominantly associated with lipid metabolism, amino acid metabolism, digestive system, and signal transduction. Subsequently, an enrichment analysis was carried out. This analysis revealed that alanine, aspartate. and glutamate metabolism, protein digestion and absorption, and alpha-linolenic acid metabolism were significantly enriched in the BP group (Student’s t test, p < 0.05; Supplementary Fig. 3a). To further explore changes in differentially expressed metabolic pathways, we performed separate enrichment analyses on upregulated and downregulated metabolic pathways (Fig. 5e, f). The results indicated that numerous enriched upregulated DEMs were involved in alpha-linolenic acid metabolism and phospholipase D signaling pathway (Student’s t test, p < 0.05; Fig. 5f). Alpha-linolenic acid metabolism, retinol metabolism, and arginine and proline metabolism were only enriched in the BP group (Supplementary Fig. 3b).

Fig. 5 — a Annotation of downregulated DEMs in BP group against HMDB database. b Annotation of upregulated DEMs in BP group against HMDB database. c Annotation of downregulated DEMs in BP group against KEGG database. d Annotation of upregulated DEMs in BP group against KEGG database. e Top 20 enrichment analysis of DEMs in downregulated KEGG pathway. f Top 20 enrichment analysis of DEMs in upregulated KEGG pathways. BP settled larvae in bacteria-inoculated group, CP settled larvae in control group. Number refers to the count of DEMs.

Of all the DEMs, we selected 25 potential metabolites based on their high FC values or previous reporting to be involved in larval settlement and metamorphosis (Supplementary Fig. 4). Compared to that in the CP group, upregulation of dimethylsulfoniopropionate and diacylglycerol (DAG) levels were observed in the BP group, along with a concomitant downregulation in retinal, proline, and glutamate levels. PA (22:6(4Z,7Z,10Z,12E,16Z,19Z)-OH14/8:0), phenytoin dihydrodiol, benzyl 6-O-beta-D-apiofuranosyl-beta-D-glucoside, apronal, (S)-3-(methylthio)hexyl acetate, and N-benzyladriamycin-14-valerate have high FC values and may be serve as potential biomarkers in bacteria-induced coral larvae settlement and metamorphosis. The upregulation of dipeptides, such as Ile-Gln, Ile-Leu, Ser-Val, and Prolyl-Arginine, were observed in the BP group, while amino acid, such as proline, glutamate, and serine, were downregulated (Student’s t test, p < 0.05; Supplementary Fig. 5).

Impact of cB07 treatment on proteins and metabolites observed in KEGG pathway

We developed a comprehensive model to illustrate the potential induction mechanism of cB07 on protein and metabolite changes (Fig. 6). We detected an upregulation of DEMs involved in citrate and (S)-malate—key energy components in TCA cycle—in the BP group (Student’s t test, p < 0.05). However, a downregulation of DEPs involved in aconitase (ACO), isocitrate dehydrogenase 3 (IDH3), lipoyl synthase 1 (LCS1), lipoyl synthase 2 (LCS2), malate dehydrogenase 1 (MDH1), and ATP-citrate lyase (ACLY) were observed in the BP group. Furthermore, among all the DEMs, those associated with the downstream pathways of retinol metabolism, including all-trans-4-hydroxy-retinoic acid and all-trans-retinoyl β-glucuronide, were upregulated. Contrastingly, the upstream metabolite all-trans-retinal was downregulated, and the enzyme alcohol dehydrogenase (ADH) was upregulated. In addition, downregulation of all-trans-retinoyl β-glucuronide was detected in the extracellular environment. In tryptophan metabolism, upregulation of amine oxidase copper-containing 1 (AOC1) and indole-3-acetaldehyde were detected. Conversely, N-formyl-kynurenine—a by-product of tryptophan metabolism—underwent additional metabolic changes and was excreted. This led to the extracellular release of 2-aminomuconate semialdehyde, whereas 2-amino-muconate was reduced intracellularly. Intracellularly, an upregulation of biotin—a vitamin non-synthesizable by corals—was observed. Concurrently, a downregulation of dethiobiotin and an upregulation of its product, biotinyl-5’-AMP, were detected. Regarding γ-aminobutyric acid (GABA) synthesis, the related metabolite γ-glutamyl-γ-amino-butyrate and associated proteins ACO1 and MPAO were upregulated. Glutamate was downregulated intracellularly but upregulated extracellularly (Fig. 6).

Discussion

Sexual propagation of corals, particularly through the use of larvae, offers a promising avenue for reef restoration, as it enhances genetic diversity and environmental adaptability^35,36. However, the process of larval metamorphosis and settlement remains a significant challenge in coral sexual reproduction. The delayed settlement and metamorphosis of coral larvae in 0.22 µm filtered seawater, along with a low proportion of settlement and metamorphosis²¹, further confirmed the importance of bacterial cues in coral larvae settlement and metamorphosis^13,14. Our results unequivocally showed that cB07 addition triggered profound shifts in the composition of coral-associated microbial communities. Specifically, there was a marked increase in the bacterial taxa that play a pivotal role in promoting larval settlement and metamorphosis. Concurrently, these bacteria exerted a regulatory influence on the proteomic and metabolomic profiles of the larvae. This regulation ultimately led to successful completion of larval settlement and metamorphosis, providing insights into ecological processes and symbiotic relationships occurring within coral reef ecosystems.

Microbial community changes during coral larval metamorphosis and settlement induced by strain cB07

The health, nutrition, and disease dynamics of corals are significantly influenced by their symbiotic relationship with various bacteria³⁷, which form a dynamic community that evolves throughout the coral’s life cycle³². Our study has revealed that the inoculation of M. indicus cB07 led to a notable shift in the microbial composition of coral larvae and surrounding seawater. Several bacterial genera enriched in coral larvae were the same as those in culture water, such as genera Winogradskyella, SM1A02, Nonlabens, Nautella, Mesoflavibacter, Henriciella, and Erythrobacter. These bacterial genera were consistent with various bacterial taxa that coral larvae acquire from the environment during development³². The genera Thalassobius, Winogradskyella, and Nonlabens, are known for their ability to encode genes that scavenge reactive oxygen species (ROS) and reactive nitrogen species (RNS)³³. In accordance with the theory of oxidative stress-related coral bleaching, bacteria capable of scavenging ROS and RNS enhance coral thermal resilience^38,39. Additionally, Mesoflavibacter and Erythrobacter can produce carotenoids, such as zeaxanthin—an antioxidant^40,41. Zeaxanthin produced by Muricauda mitigated light and thermal stress by scavenging ROS and RNS in coral holobiont^42,43. The enrichment of these bacteria in cB07-induced coral larvae may significantly bolster coral’s ability to endure environmental stressors, thereby improving its thermal resilience.

Marine bacterial biofilms are recognized for their role in inducing metamorphosis and settlement of various marine invertebrates, including polychaete, sponges, and echinoderms^44,45. Among the bacteria identified in biofilms, Pseudovibrio, Acinetobacter, Pseudoalteromonas, and Microbulbifer have been shown to induce coral larvae undergo metamorphosis and settlement⁴⁶. In our study, we observed an enrichment of the genus Thalassobius in coral larvae and Leisingera in the culture water following inoculation with M. indicus cB07. Thalassobius, known for its high abundance in biofilms^47,48, has been linked to the promotion of H. elegans settlement⁴⁹. Leisingera’s capacity to encode the components of type VI secretion system and effector proteins suggests its role in biofilm formation and induction of Mytilus coruscus settlement⁴⁸. In this study, the genus Thalassobius was enriched in coral larvae, and the genus Leisingera was enriched in the coral larvae culture water inoculated with strain cB07. The enrichment of these genera in the context of coral larvae suggests a parallel function in promoting metamorphosis and settlement. Furthermore, our study observed a notable enrichment of the genus Metabacillus in the cB07-inoculated culture waters of coral larvae, emerging as the primary driver of this enrichment. This microbial restructuring post-cB07 inoculation may not only enhance coral larvae metamorphosis and settlement but also endow them with a microbiome that supports their health and resilience. These findings provide valuable insights into the mechanisms by which biofilms and specific bacterial taxa contribute to the early life stages of corals, offering potential applications in restoration efforts.

Protein and metabolite changes during coral larval metamorphosis and settlement induced by strain cB07

The coral larvae metamorphosis and settlement represent a complex, multi-faceted biological process¹¹. It integrates the reception of inducing signals, developmental progression, and establishment of symbiotic associations with environmental bacteria and the family Symbiodiniaceae¹¹. This intricate process has been shown to cause changes in proteins related to larval development and signal reception^{11,26,27,29,50,51}. The induction of metamorphosis and settlement by bacteria, as evidenced in our cB07 strain-induced samples, introduces additional layers of complexity. This includes identification of exogenous inducing factors and changes in symbiotic microorganisms, which are often linked to immune system modulation, inflammatory responses, and sedimentation processes^24,52. For instance, the metamorphosis of a tubeworm H. elegans by P. luteoviolacea is mediated by genes pivotal for tissue remodeling, immunity, and signaling pathways¹⁶. Coral, like all invertebrates, lacks advanced antibody-based adaptive immunity characteristic of vertebrates and only possesses innate immune system⁵³. Invertebrates respond to microorganisms through three main mechanisms: recognition by pattern recognition receptors, cellular immunity in the form of phagocytic response, and humoral components comprising acellular and biochemical factors^24,52. Symbiotic and pathogenic microbes share a common mechanism of directing recognizing interactions. However, in symbiosis, unlike in pathogenic elimination, the recognition event does not lead to the destruction of invading microbes but rather to the production of adhesion mediators or formation of special organs to accommodate these mutualistic partners. Lectins play a pivotal role in the recognition of coral symbionts⁵⁴. A previous study has reported that C-type lectins are capable of recognizing zooxanthellae⁵⁵. During bacteria-induced coral larvae settlement and metamorphosis, the C-type lectin receptor signaling pathway became significantly enriched suggesting that cB07 successfully established a symbiotic relationship with the host²¹. In this study, the downregulation of immune signals, such as Th1 and Th2 cell differentiation and T cell receptor signaling pathway, in coral larvae potentially facilitated cB07 colonization and promoted a harmonious coexistence with the host. Consequently, cB07 abundance in the coral larvae’s microbiome increased significantly following treatment, suggesting a more effective metabolism and a stable living environment for the bacterial strain, which in turn promote coral larvae metamorphosis and settlement.

Settlement cues from bacteria are thought to be received by planulae, presumably via sensory neurons, and converted into signals to undergo metamorphosis⁵⁶. Neurotransmitters, such as GABA, play an important role in settlement and metamorphosis of marine invertebrate larvae^57,58. GABA and GABA receptors influence the early substrate-seeking behavior of coral larvae; GABA function gradually disappears after metamorphosis^29,51. In this study, in settled M. indicus cB07-inoculated coral larvae, GABA precursor-synthesizing proteases AOC1 and MPAO, along with the precursor substance of GABA, γ-glutamyl-γ-aminobutyric acid, were significantly upregulated. These findings imply that cB07-induced coral larvae stimulate the GABA signaling pathway, accelerating the substrate-seeking process and enhancing the settlement capacity. Furthermore, amino acid monomers, as representative substances of metabolism, promote larval metamorphic processes at appropriate concentrations⁵⁹. During settlement and metamorphosis, we observed significant changes in dipeptides. Dipeptides can act as signaling molecules, metabolites, or intermediates and play important roles within and between cells. However, molecular mechanisms underlying the role of dipeptides in coral larvae settlement and metamorphosis are still unclear⁵⁹.

Calcium signals play a fundamental role in physiological functions occurring in marine invertebrate larvae, including larval metamorphosis and settlement^60,61. The intracellular calcium transients and calcium signal-related gene expression were found to be highly related to larval metamorphosis and settlement⁶². Calmodulin (CALM)—a Ca²⁺ binding protein—regulates various downstream effector molecules in cell signaling pathways⁶³. The expression of CALM and calcium homeostasis-related genes in the coral Montastraea faveolata were upregulated during the development of polyp from planula⁶⁴. In cB07 induction experiments, we observed CALM upregulation. Additionally, the upregulation of the protein PPIF and the metabolite DAG—both associated with calcium signaling pathway—was detected. These changes in proteins and metabolites suggest that cB07 may induce coral larvae settlement and metamorphosis through the activation of the calcium signaling pathway.

Retinoic acid (RA) signaling is known to regulate life cycle transitions in invertebrates^65–67. Exogenous all-trans RA can induce metamorphosis after settlement in starfish larvae, and it mediates metamorphosis in starfish on receiving specific environmental cues⁶⁶. Microorganisms can regulate the retinal synthesis pathway, affect the production of downstream signaling metabolites, and thus influence the life-cycle transition in jellyfish⁶⁸. In this study, we observed downregulation of all-trans-retinal synthase ADH during bacterial induction. Downregulation of all-trans-retinal was observed, whereas its downstream metabolites, such as all-trans-4-hydroxy-retinoic acid and all-trans-retinoyl β-glucuronide, were upregulated. It is known that all-trans-retinoate can produce all-trans-retinoyl β-glucuronide and all-trans-5,6-epoxy-5,6-dihydroretinoic acid. We detected extracellular downregulation of both of these metabolites. We speculated that all-trans-4-hydroxy-retinoic acid, all-trans-5,6-epoxy-5,6-dihydroretinoic acid, and all-trans-retinoyl β-glucuronide are potential biomarkers in the RA signaling pathway that positively influence coral larval settlement and metamorphosis.

Energy metabolism is essential for the growth and development of coral larvae. For coral, cell proliferation and differentiation during larval settlement and metamorphosis requires sufficient energy supply from metabolic pathways. Lipid metabolism, a critical process for energy storage and utilization during metamorphosis and settlement⁶⁹, is significantly enriched in cB07-induced samples²¹. TCA cycle connects various catabolic and anabolic process, such as carbohydrate, lipid, and amino acid metabolism⁷⁰. In the present study, metabolites, such as citrate and (S)-malate, were upregulated in the TCA cycle, but the proteins associated with these pathways, such as ACO, IDH3, LCS1, LCS2, MDH1, and ACLY, were downregulated. Linsmayer et al. revealed that coral energy metabolism was regulated through adjustments in metabolite fluxes and not through changes in enzyme abundance⁷¹. We hypothesized that upregulated citrate and malate were accumulated intracellularly and energized coral larvae during settlement and metamorphosis. Besides, the downregulation of proteases associated with the TCA cycle was the result of negative feedback regulation.

Methods

Coral larvae collection

Twenty healthy adult P. damicornis colonies were collected from Luhuitou fringing reefs, Sanya Bay (18°12'19''N, 109°28'27''E), on August 28, 2019 and were cultivated in water tanks at the laboratory of Tropical Marine Biological Research Station in Hainan, China. At the time of ovulation, each adult coral colony was put into a 15 L plastic bucket with flowing seawater. The seawater was pumped from the ocean in Sanya Bay, pre-filtered, stored, and filtered through 4 µm filters. The excreted larvae were trapped by a 180 μm sieve. The collected larvae were transferred to a large tank for aerated culturing. During the temporary cultivation period, the culture density was 1 larva per ml, light intensity was 250 µmol photons m⁻² s⁻¹, and the culture water body was changed with the help of a screen every day.

Preparation of pure bacterial cultures

The strain stored at −80 °C was taken out and was recovered in the 2216E agar medium (5 g tryptone, 1 g yeast extract, 0.1 g FePO₄·2H₂O, 25 g NaCl, 1 L ddH₂O, 18 g agar, pH 7.0–7.8). The strain was fermented in the MA medium (18 g Difco marine broth, 9 g NaCl, 1 L ddH₂O). In brief, the pure strain was inoculated into 500 mL MA medium and incubated in a shaker (28 °C, 180 rpm). The bacterial growth was estimated using a spectrophotometer. When the strain grew to the logarithmic growth stage, the cultures were centrifuged at 8000 rpm for 5 min to remove the supernatant. The cell pellets were resuspended in 0.22 µm filtered seawater (FSW). Cell numbers were estimated using a spectrophotometer, hemocytometer, and light microscope. The final bacterial concentration added was 3.2 × 10⁷ cells mL⁻¹. In the control group, the bacterial suspension was replaced with FSW.

Experimental design and sampling

The experimental system included 24 independent round glass petri dishes (φ = 20 cm, h = 3 cm). Twenty-four petri dishes were randomly divided into two groups: a control group lacking strain cB07 and a treatment group with 3.2 × 107 cB07 cells/mL, with 3 replicates per group including 12 petri dishes. Each dish contained 600 mL bacterial suspension (treatment group) or FSW (control group), and 900 newly released coral larvae. The dish received 250 μmol photons m⁻² s⁻¹, with a 12-h light/12-h dark photoperiod, and the seawater temperatures were maintained at 28 ± 1°C.

Coral larvae were observed under a dissecting microscope (Nikon SMZ800N, Tokyo, Japan). Sampling was conducted once the larvae underwent metamorphosis or settlement²¹. In the treatment group, planula underwent metamorphosis 48 h after bacterial inoculation and settled on the 5th day. Therefore, metamorphosed and settled larvae samples were sampled at 48 h and 5th day after bacterial inoculation. In the control group, planula underwent metamorphosis on the 7th day after the experiment began and settled on the 10th day. Thus, metamorphosed and settled larvae in the control group were collected at 7th and 10th day after the experiment began. The newly released coral larvae sample were collected using a Pasteur pipette. Metamorphosed larvae were collected immediately using a Pasteur pipette after the coral larvae metamorphosed. Settled larvae were taken using a sterile blade on the second day after settlement. For comprehensive molecular profiling, 120 larvae were sequentially collected from each replicate—60 for 16S rRNA analysis and another 60 for proteome analysis. After sampling, 100 mL culture medium was taken from each replicate and filtered through 0.22 μm sterile membrane. The membrane was used to analyze the microbial community. All samples were quickly frozen in liquid nitrogen immediately after collection and transferred to -80°C refrigerator the next day.

DNA extraction and amplicon sequencing

DNA was extracted from the coral larvae samples (60 coral larvae per sample) using the HiPure soil DNA kit (Megan, China) following the manufacturer’s protocol. DNA concentration and purity were determined using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA). The V3-V4 region of the 16S rRNA genes was targeted using specific primer pairs, 341 F (5′-CCTACGGGNGGCWGCAG-3′) and 805 R (5′-GACTACHVGGGTATCTAATCC-3′)⁷².

Genomic DNA was amplified by PCR following the methods elaborated in our previous study²¹. The reaction was carried out in 50-μL volumes containing 5 μL of 10× KOD buffer, 2 μL of 2 mM dNTPs, 3 μL of 25 mM MgSO₄, 1.5 μL of 10 μM each primer, 1 μL of KOD polymerase (TOYOBO Co., Osaka, Japan), and 100 ng of DNA template, with water added to complete the volume. Three PCR reactions were conducted for each sample. PCR cycling parameters included an initial denaturation at 94 °C for 2 min, followed by 30 cycles of 98 °C for 10 s, 62 °C for 30 s, and 68 °C for 30 s, concluding with a final extension at 68 °C for 5 min. The PCR products were purified with AMPure XP beads and quantified using a Qubit 3.0 fluorometer. A second round of PCR was conducted using similar reaction conditions but with 12 cycles and a different annealing temperature of 65 °C. The purified products were then quantified using an ABI StepOnePlus real-time PCR system (Life Technologies, USA). Equal molar concentrations of the purified PCR products were pooled, and a sequencing library was constructed. The library was sequenced using 2 × 250 bp paired-end sequencing on an Illumina HiSeq 2500 platform by Gene-Denovo (Guangzhou).

Bacterial community structure analyses

Raw data were filtered using QIIME2 (version 2022.2)⁷³ and trimmed with FASTP to remove low-quality reads (<100 bp)⁷⁴. Sequences were then merged using FLASH⁷⁵ with a minimum overlap of 10 bp and a maximum error rate of 5%. Then, the ASVs of 16S rRNA were clustered using QIIME2 with 100% similarity. Subsequently, the DADA2 plugin integrated within QIIME2 software⁷⁶ was utilized to rigorously remove barcodes, chimeras, primer sequences, and any remaining low-quality reads. To standardize the sequencing depth across samples, a random rarefaction approach was applied to achieve uniformity in the minimum number of sequences per sample. The taxonomic classification of the 16S rRNA gene sequence for all ASVs was analyzed against the Silva 138 16S rRNA database using a classify-sklearn classifier with a confidence threshold of 70%.

Proteome analysis

Coral larvae samples (60 coral larvae per sample) were transferred into the lysis buffer containing 1% SDS, 7 M urea, 0.1% PMSF, and 65 mM DTT. After homogenization, the mixture was centrifuged at 14,000 rpm for 30 min at 4 °C to isolate the supernatant. The supernatant’s protein concentration was quantified using the BCA protein assay kit (Beyotime, Shanghai, China). Then, 50 μg of protein was transferred into a fresh Eppendorf tube, and the final volume was adjusted to 50 μL with 1 M DTT (1 μL) and incubated at 55 °C for 1 h. Subsequently, 5 μL of 1 M iodoacetamide was added to the samples, which were then incubated for an additional hour at room temperature in the dark. Proteins were precipitated by adding five volumes of pre-chilled acetone at −20 °C overnight. The precipitated proteins were washed twice with 1 mL of pre-chilled 90% acetone and resuspended in 50 mM ammonium bicarbonate. Protein digestion was performed using sequence-grade modified trypsin (Promega, Madison, WI) at an enzyme-to-protein ratio of 1:50 (w/w) at 37 °C overnight.

Peptide mixtures were fractionated by high-pH reversed-phase separation and subsequently re-dissolved in solvent A (0.1% formic acid in water). The samples were then analyzed by online nanospray liquid chromatography-tandem mass spectrometer (LC-MS/MS) in an Orbitrap Fusion Lumos coupled to EASY-nLC 1200 system (Thermo Fisher Scientific, MA, USA). Furthermore, 3 μL peptide sample was loaded onto the analytical column (Acclaim PepMap C18, 75 mm × 25 cm) with a 120-min gradient, in 5 to 35% solvent B (B: 0.1% formic acid in acetonitrile). The column was operated at a flow rate of 200 nL/min and maintained at a temperature of 40 °C. The electrospray ionization was performed at a voltage of 2 kV relative to the mass spectrometer’s inlet. Mass spectrometry was conducted in data-independent acquisition (DIA) mode, allowing for automated transitions between mass spectrometric (MS) and tandem mass spectrometric (MS/MS) acquisition.

Metabolomic analysis

Fifty milligrams of newly released free-swimming coral larvae, settled coral larvae, and dried culture medium were used for the extraction and detection of metabolites. Samples were added into 2 mL centrifuge tubes, containing a 6 mm grinding bead and 400 μL extraction solution (methanol: water: 4:1 (v:v). The mixture was then subjected to multiple processing steps: it was first incubated at −20 °C and processed using a high-throughput tissue crusher Wonbio-96c (Shanghai Wonbio Biotechnology Co. Ltd) at 50 Hz for 6 min. Subsequently, the sample was vortexed for 30 s and ultrasonicated at 40 kHz for 30 min at 4 °C. Afterwards, the samples were further incubated at −20 °C for 30 min to aid in protein precipitation. Finally, the sample were centrifuged at 13,000 × g at 4 °C for 15 min, following which the supernatant was transferred to sample vials for UPLC-MS analysis. Standard samples for QC were prepared by pooling equal volumes of the samples and injecting every five settled coral larvae or nine culture medium samples.

The LC-MS/MS analysis of samples was conducted using a Thermo UHPLC-Q exactive HF-X system equipped with an ACQUITY HSS T3 column (100 mm × 2.1 mm i.d., 1.8 μm; Waters, Milford, Massachusetts, USA). The mobile phases contained 0.1% formic acid in water:acetonitrile (95:5, v/v; solvent A) and 0.1% formic acid in acetonitrile:isopropanol:water (47.5:47.5, v/v; solvent B). The column temperature was maintained at 40 °C. MS data were collected using a Thermo UHPLC-Q exactive HF-X mass spectrometer equipped with an electrospray ionization source operating in positive and negative modes. Data processing, including filtering, peak detection, alignment, correction, normalization, logarithmic transformation, and identification, were performed as described previously⁷⁷. Briefly, raw data were imported into the Progenesis QI software (v2.3, Nonlinear Dynamics, Waters, Milford, Massachusetts, USA) for peak detection and alignment to generate a data matrix comprising retention time, mass-to-charge ratio (m/z), and peak intensity. The metabolites detected in ≥ 80% of samples were retained, and then minimum metabolite values were set for the samples below the limit of quantitation. Metabolites were normalized by summation. The QC data were used as the internal standard, and metabolites with a relative standard deviation > 30% were discarded. The logarithmic transformation was performed to identify significant differences in metabolite levels between groups. The metabolites were identified by comparing observed accurate mass and MS/MS spectra to accurate mass data and spectra available on web-based databases, including Metlin database and HMDB^78,79.

Statistics and reproducibility

Bacterial alpha diversity indices, including richness, Shannon, Pielou, and Simpson indices, were calculated using QIIME2⁷³. The dissimilarity among microbial communities was assessed through PCoA. ANOSIM, Adonis, and MRPP analyses were performed to evaluate the difference in beta diversity among groups. LEfSe was applied to identify enriched taxa with a discriminative linear discriminant analysis score threshold of >3, which were considered as potential biomarkers⁸⁰. Unless specified otherwise, Kruskal-Wallis and Tukey’s post hoc tests were employed to evaluate differences in bacterial community composition and alpha diversity across various stages of coral larvae and coral culture water, respectively. All statistical analyses were conducted using SPSS version 24.0 (SPSS Inc., Chicago, IL, USA), with p values less than 0.05 and 0.01 denoting various levels of statistical significance.

The resulting DIA raw data were processed and analyzed using Spectronaut X software (Biognosys AG, Switzerland) with default settings. Only precursor ions that passed the established filters were considered for peptide quantification. The average top three filtered peptides that passed the 1% Q value cutoff were used to calculate the major group quantities. After subjecting to Student’s t test, DEPs were filtered if p < 0.05. To elucidate the functions of the identified proteins, we utilized KEGG databases. DEPs were screened for significant KEGG functions and pathways. Statistical significance was determined using Student’s t test, with p < 0.05 serving as a significance threshold.

Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed after Pareto scaling transformation to determine the differences in metabolites between CP and BP groups using R (v4.3.2) with the “ropls” package, and the variable importance in projection (VIP) was calculated. Metabolites showing significant difference between groups (Student’s t test, p < 0.05), VIP values > 1, and FC > 1 were considered for DEMs. These DEMs were mapped to their respective biochemical pathways through metabolic enrichment and pathway analysis based on the KEGG database as described previously⁷⁷. Correlations between metabolites in different groups were assessed using Spearman’s correlation test.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Supplementary information

Supplementary Information^{(1MB, pdf)}

42003_2025_8720_MOESM2_ESM.pdf^{(29KB, pdf)}

Description of Additional Supplementary Files

Supplementary Data 1^{(46.5KB, xlsx)}

Supplementary Data 2^{(36.7KB, xlsx)}

Reporting summary^{(3.5MB, pdf)}

Acknowledgements

This research was supported by the National Key Research and Development Program of China (2022YFC3103602; 2022YFC3102004; 2022YFC3102003), the National Natural Science Foundation of China (No. 41976147), and the NSFC-Shandong Joint Fund (No. U2106208). We are grateful to Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in sequencing analysis.

Author contributions

Y.Y.Z. and J.D. conceived and designed the study. X.G. and Y.Z. acquired and analyzed the data. X.G. and Y.Z. drew graphs. X.G. and Y.Y.Z. drafted the manuscript. X.T., Q.Y., H.S., and J.L. reviewed the manuscript and provided valuable edits. All authors have read and approved the submitted version of the manuscript.

Peer review

Peer review information

Communications Biology thanks Yin-Ru Chiang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Michele Repetto and Aylin Bircan.

Data availability

Raw reads of the 16S rRNA gene generated in this work were deposited in the NCBI sequence read archive under the BioProject accession number PRJNA1155960. The proteomic mass spectrometry data reported in this paper have been deposited in the OMIX, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (https://ngdc.cncb.ac.cn/omix: accession no. OMIX007271) under the BioProject PRJCA029801.

Competing interests

The authors declare no competing interests.

Ethical approval

Coral sampling and experiment were conducted in accordance with the relevant guidelines and regulations, and were approved by the Department of Agriculture and Rural Areas of Hainan Provinces.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Xiangrui Guo, Ying Zhang.

Contributor Information

Junde Dong, Email: dongjd@scsio.ac.cn.

Yanying Zhang, Email: zhyanying@ytu.edu.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s42003-025-08720-6.

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Associated Data

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Supplementary Materials

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Supplementary Data 2^{(36.7KB, xlsx)}

Reporting summary^{(3.5MB, pdf)}

Data Availability Statement

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[CR60] 60.Yang, Q. et al. Promoting larval settlement of coral Pocillopora damicornis by calcium. Coral Reefs41, 223–235 (2022). [Google Scholar]

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[CR66] 66.Yamakawa, S. et al. Mechanism underlying retinoic acid-dependent metamorphosis in the starfish. Dev. Biol.492, 119–125 (2022). [DOI] [PubMed] [Google Scholar]

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[CR69] 69.Leal, I. et al. Lipid allocation in late-stage barnacle larvae from subtropical and temperate waters. Mar. Ecol. Prog. Ser.661, 147–161 (2021). [Google Scholar]

[CR70] 70.Akram, M. Citric acid cycle and role of its intermediates in metabolism. Cell Biochem. Biophys.68, 475–478 (2014). [DOI] [PubMed] [Google Scholar]

[CR71] 71.Linsmayer, L. B., Deheyn, D. D., Tomanek, L. & Tresguerres, M. Dynamic regulation of coral energy metabolism throughout the diel cycle. Sci. Rep.10, 19881 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Bacterial regulation of coral larval metamorphosis and settlement in Pocillopora damicornis

Xiangrui Guo

Ying Zhang

Xiaoyu Tang

Qingsong Yang

Hao Sun

Juan Ling

Junde Dong

Yanying Zhang

Abstract

Introduction

Results

Bacterial community composition

Fig. 1. Alpha diversity indices and principal co-ordinates analysis (PCoA) of bacterial communities at amplicon sequence variant level in coral larvae and culture water based on Bray-Curtis metrics.

Microbiota composition at different coral life stages

Fig. 2. Bacterial community composition in coral larvae and culture water.

Fig. 3. LEfSe analysis of bacterial communities in coral larvae and culture seawater.

Alterations of molecules on the proteomic level

Fig. 4. DEPs in coral larvae of the BP and CP group.

Metabolites in settled coral larvae and culture medium

Fig. 5. DEMs in settled coral larvae of BP and CP groups.

Impact of cB07 treatment on proteins and metabolites observed in KEGG pathway

Fig. 6. Model of DEPs and DEMs observed in KEGG pathways.

Discussion

Microbial community changes during coral larval metamorphosis and settlement induced by strain cB07

Protein and metabolite changes during coral larval metamorphosis and settlement induced by strain cB07

Methods

Coral larvae collection

Preparation of pure bacterial cultures

Experimental design and sampling

DNA extraction and amplicon sequencing

Bacterial community structure analyses

Proteome analysis

Metabolomic analysis

Statistics and reproducibility

Reporting summary

Supplementary information

Acknowledgements

Author contributions

Peer review

Peer review information

Data availability

Competing interests

Ethical approval

Footnotes

Contributor Information

Supplementary information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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