Unravelling the role of crustose coralline algae microbiomes on coral larval settlement in the Great Barrier Reef

Unravelling the role of crustose coralline algae microbiomes on coral larval settlement in the Great Barrier Reef | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unravelling the role of crustose coralline algae microbiomes on coral larval settlement in the Great Barrier Reef Abigail C. Turnlund, Paul O’Brien, Laura Rix, Sophie Ferguson, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7850943/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Crustose coralline algae (CCA) enhance coral recruitment, but the response of coral larval settlement to CCA varies between CCA species. Furthermore, it is unclear whether coral larvae respond to settlement cues from the algal host itself or its associated microorganisms. To determine whether CCA-derived settlement cues have a microbial origin, we interrogated the microbiome of 14 coralline algal species and a calcareous non-coralline alga eliciting varying levels of settlement across 14 coral species from a wide diversity of families found in the Great Barrier Reef. Linear regression, differential abundance, indicator species, and random forest analyses were used to identify microbial taxa associated with high or low coral settlement. We found that the relative abundance of specific microbial amplicon sequence variants (ASVs) correlated with settlement and that these responses were largely coral species-specific. A select few microbial taxa associated with high or low settlement were shared across the corals Dipsastrea favus , Echinophyllia aspera, Lobophyllia corymbosa, Mycedium elephantotus , and Platygrya sinensis , suggesting potential shared settlement or inhibition cues. While shared ASVs associated with high coral settlement were found across multiple CCA species, low settlement AVSs were confined to few low settlement CCA species. Candidatus Nitrosopumilus and Filomicrobium microbes were found as potential shared microbial inducers, and members of Pirellulaceae and Flavobacteriaceae were identified as potential settlement inhibitors. These findings contribute to our growing knowledge of potential coral larval settlement cues and provide deeper insights into the link between the CCA microbiomes and coral recruitment. coral recruitment coral larvae crustose coralline algae microbial communities settlement inducer/inhibitor 16S rRNA amplicon sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The growth of coral reefs worldwide crucially depends on successful reproduction and larval recruitment of single individuals. Ongoing severe climate-related events (e.g. elevated sea temperatures and subsequent coral bleaching) have negatively impacted corals’ ability to successfully reproduce and survive ( 1 , 2 ).The planktonic phase of coral larvae is especially sensitive to environmental disturbances, as larval development and swimming behaviour are markedly affected at higher sea water temperatures and lower pH levels ( 3 , 4 ). This further alters the ability of larvae to settle in response to environmental cues, metamorphose, and survive, thus creating a major bottleneck that limits new coral growth and genetic diversity on reefs ( 5 ). In addition, different settlement cues are likely simultaneously being altered in response to environmental changes. However, a comprehensive assessment of this is lacking as the specific cues that trigger coral larval settlement are largely uncharacterised. The planktonic larvae of most coral species actively select a suitable settlement substrate ( 6 , 7 ), with a variety of environmental cues including surface structures (8, 9), sound ( 10 ), colour ( 11 – 13 ), light ( 14 ), and biochemical cues ( 15 , 16 ) influencing this selection. Many coral species have been shown to settle in response to crustose coralline algae (CCA), calcifying red algae that are abundant on tropical reefs and that play a key role in maintaining coral reef structure and biodiversity ( 17 – 19 ). Corals typically have a preference for specific CCA species ( 7 , 20 – 25 ), and some studies suggest that corals may in fact settle in response to cues originating from CCA surface-associated microorganisms ( 24 , 26 ) rather than the CCA themselves. Prior research has shown that CCA surface microbiomes are distinct from the surrounding water column ( 27 , 28 ) and that microbial community composition varies between CCA species ( 19 , 24 )(Turnlund et al. in review). However, it has been challenging to untangle the effects of CCA microbial communities from the CCA host on coral larval settlement. To separate host and microbial effects, analysis of crude extracts and microbial strains isolated from the CCA surface has uncovered morphogens that induce high levels of coral larval settlement ( 29 , 30 ). For example, two different strains of Pseudoalteromonas sp. , isolated from the CCA species Neogoniolithon fosliei and Porolithon ( Hydrolithon ) onkodes ( 30 , 31 ) produce the morphogen tetrabromopyrrole (TBP) that can induce larval settlement and metamorphosis in Acropora corals. More recently, cycloprodigiosin, an alkaloidal pigment isolated from a Pseudoalteromonas rubra strain found on the CCA Hydrolithon reinboldii , was found to induce coral settlement once activated under high-light conditions ( 32 ). However, the morphogenic attributes of any given microbe grown in cultivation might differ when part of a mixed-species community in the natural environment ( 33 ). For example, Pseudoalteromonas were found to be less inductive when in mixed-species biofilms ( 34 ), while extracts of TBP are often unstable and its effect on settlement can be concentration and strain dependent ( 35 ). Other studies have administered antibiotics to CCA surfaces to remove CCA surface microbial communities and isolate the inductive capacity of the CCA host on larvae of different marine invertebrates, with mixed results ( 36 – 39 ). Johnson and Sutton ( 36 ) found that removing microorganisms from CCA surfaces negatively impacted Crown-of-Thorns starfish larval settlement, but settlement response improved after re-inoculating single strains to CCA surfaces. Other studies found that coral larval metamorphosis response to CCA was not affected by the antibiotic treatment but still identified single strains ( Pseudoalteromonas ) that promoted larval settlement ( 37 ). However, CCA surface microbiomes consist of mixed-species communities, and despite these advances, our understanding of the role that CCA-associated microbial communities play in promoting coral larval settlement for a wide diversity of coral species remains in its infancy. Abdul Wahab, Ferguson ( 7 ) explored larval settlement of 15 different Great Barrier Reef (GBR) coral species in response to 14 coralline algae species and the non-coralline alga Ramicrusta . They found that different CCA elicited varying coral larval settlement responses depending on the coral species ( 7 ). This experimental design provided the opportunity to investigate whether these settlement differences were driven primarily by the CCA host or the CCA associated microbiome. Hence, in this study we extend Abdul Wahab et al.’s findings to microbiome-related settlement cues by examining whether variations in microbiomes found on these CCA hosts were associated with differences in larval settlement responses. Further, we aimed to identify candidate settlement-inducing and inhibiting taxa and determine whether these taxa are coral species-specific or common across multiple species. Using a combination of statistical approaches, we identified individual microorganisms associated with high settlement for multiple coral species, and unique microbial taxa associated with low settlement inducing CCA species. Methods Full details of coral and algal collection and identification, spawning, maintenance of larval cultures, and settlement assays are described in Abdul Wahab, Ferguson ( 7 ) and are summarised briefly below. Coral collection, spawning & larval culture Colonies from fifteen different coral species, across 5 taxonomic families, from the Great Barrier Reef (GBR) were collected and used in settlement assays ( Acropora hyacinthus, A. tenuis , A. anthocersis, Caulastrea furcata , Coelastrea aspera , Dipsastrea favus , Echinophyllia aspera , Fungia fungites , Goniastrea favulus , Lobophyllia corymbosa, Montipora aequituberculata , Mycedium elephantotus , Platygyra daedalea , Platygrya sinensis , and Porites lobata ). Coral colonies were collected between the 9th to 20th October and 14th to 21st November 2021 from Magnetic Island (19˚07’45.78”S 146˚52’40.14”E), the Palm Island Group (18˚45’56.4”S 146˚32’2.58”E) and Davies Reef (18˚49’13.5”S 147˚38’40.32E) at 1 − 9 m depths under the GBRMPA Permit G21/45348.1. Corals were collected on SCUBA using a hammer and chisel and were transported into 70 L aquaria with consistent flow-through seawater for 4 − 6 h until their arrival at the National Sea Simulator (SeaSim) facility at the Australian Institute of Marine Science (AIMS) in Townsville, Australia. At SeaSim, corals were held in outdoor semi-recirculating aquaria with filtered seawater at ~ 27.2˚C and natural light. When the setting of gametes was observed, colonies that produce egg-sperm bundles were moved to separate aquaria and buoyant bundles collected within the first hour of their release and gametes were fertilised. Embryos were gently washed with filtered seawater (FSW) to remove extra sperm after one hour and transferred to either 500 L or 70 L flow-through culture tanks. For P. lobata, F. fungites, L. corymbosa and G. favulus (i.e. gonochoric species, or hermaphroditic species releasing eggs and sperm separately), water containing sperm was mixed in aquaria that contained colonies with eggs, and embryos transferred to culture tanks within 30 to 45 min after signs of cleavage were observed. All larval cultures were maintained in flow-through culture tanks until the settlement experiment. Algal collection and identification Thirteen non-geniculate CCA ( Adeylithon cf. bosencei , Hydrolithon cf. reinboldii , Lithophyllum cf. insipidium, L. cf. kotschyanum , L. cf. pygmaeum , Lithothamnion cf. proliferum , Melyvonnea cf. madagascariensis , Neogoniolithon cf. fosliei , Porolithon onkodes, Porolithon sp.1, Porolithon sp.2, Sporolithon sp., and Titanoderma cf. tessellatum ), one geniculate coralline alga Amphiroa cf. foliacea , and one calcareous non-coralline alga Ramicrusta sp. (Peyssonneliaceae) were collected at 1–10 m depth on SCUBA from habitats that had either low-, moderate- and high-light with a hammer and chisel from Davies Reef and Havannah Island between the 9th and 20th of October 2021 (Table S1 ). The 15 species are collectively hereafter referred to as CCA. Algal identification was first performed visually looking at anatomical and morphological traits and further identified with molecular analysis as previously detailed in Abdul Wahab, Ferguson ( 7 ). Collected CCA were moved to AIMS SeaSim and cut into 10 x 10 mm pieces with a wet diamond band saw (Gryphon) and glued on a poly-vinyl-chloride (PVC) rack. These racks were placed in indoor semi-recirculating aquaria with 1 µm filtered seawater (~ 3 turnovers per day) at ~ 27.2˚C and held for either 2 − 3 weeks (October spawning, Table S2) or 4 − 6 weeks (November spawning, Table S3). CCA were kept under light conditions resembling the habitats they were collected from with the maximum midday irradiance levels for low-, moderate- and high- light adapted CCA was 12.7 − 15 µmol quanta m − 2 s − 1 , 56 − 58 µmol quanta m − 2 s − 1 , and ~ 120 µmol quanta m − 2 s − 1 , respectively. Settlement assays and CCA sampling Settlement assays were conducted in 6-well plates (Costar) with 10 mL of 0.1 µm FSW per well. Ten active larvae and one 5 x 5 mm CCA chip (tissue-side up) were placed in each well. Twelve replicates of each CCA treatment were randomised across 36 plates for each coral species except for C. furcata , where only 6 treatment replicates were used due to low larval stock. Autoclaved aragonite chips and blank wells were used as controls. Settlement was recorded after 46 − 55 hours by counting permanently attached and metamorphosed larvae under a dissecting microscope. Settlement assays were repeated three times for C. aspera at different larval ages (5, 8 and 18 days) due to initial low competency at 5 days, with the 8-day larval settlement assay results analysed in this study. Further, samples from A. anthocersis were omitted from further analysis due to indiscriminate settlement of larvae (up to 40%) when CCA cues were not present (controls). After settlement was recorded, each CCA chip (n = 12 replicates) was placed in a sterile cryovial and frozen in liquid nitrogen. Five of the twelve replicates were selected for CCA microbiome analysis. These replicates were chosen to cover a range of larval settlement outcomes, which allowed us to test if the variation in microbiome composition within a CCA species correlated with settlement success. The chip with the highest and lowest settlement response and three chips within the 50th percentile of settlement scores were chosen for sequencing (Table S4). FSW used in the settlement assays was sampled through the intake lines with 5 L per sample filtered onto 0.2 µm Sterivex filters (Millipore/Merck). Three replicate larval samples were also collected for each coral species to differentiate any larvae-associated microbes from the CCA microbiome. CCA, coral larvae, and water samples were stored in -75˚C freezers at AIMS until DNA extraction at the Australian Centre of Ecogenomics (ACE), University of Queensland, Brisbane. DNA extraction, sequencing & bioinformatics DNA was extracted from CCA samples (n = 75 per coral species, except for C. furcata due to lower assay replication (n = 45) and C. aspera (n = 73) where two samples were removed due to poor extraction results) and blank extraction controls (a blank tube with no CCA chip present; n = 1 per coral species) following a lysozyme and proteinase K buffer extraction protocol described in Wilson, Li ( 40 ). Water samples were extracted from sterivex filters using a Phenol:Chloroform:IAA method described in Botté, Nielsen ( 41 ) and coral larvae DNA was extracted with the DNeasy® UltraClean® Microbial DNA extraction kit (Qiagen) following the manufacturer’s instructions. DNA quality was measured with a nanodrop (Thermo Scientific) for 260/280 and 260/230 absorbency ratios and quantified with a Qubit 1.0 Fluorometer and Qubit dsDNA HS assay kit (Invitrogen) before storage at -20˚C until sequencing. Sequencing was conducted at ACE using 16S rRNA gene amplicon sequencing targeting the V4 region on the Illumina MiSeq platform (2 x 250 bp) with primers 515F ‘GTGYCAGCMGCCGCGGTAA’ and 806R ‘GGACTACNVGGGTWTCTAAT’ ( 42 ). Demultiplexed sequences were processed in QIIME2 (version 2022.8) and denoised with the DADA2 plug-in ( 43 ), which merges pair-ends and clusters reads into amplicon sequence variants (ASVs). The forward sequences were truncated to 245 bp, while the first 7 bp of the reverse sequences were removed to eliminate reduced quality bases and additionally truncated at 183 bp. The QIIME2 feature-classifier function was used to classify ASVs with the SILVA database (version 138.1, 99_majority taxonomy). ASVs classified as Eukaryote, mitochondria, and chloroplast were removed from the ASV table and reads were filtered at 0.01% relative abundance, which removed sequences found in blank extraction controls and filtered seawater samples. Samples that had less than 10,000 reads were eliminated from further analyses, resulting in two C. aspera samples (n = 69), two P. daedalea samples (n = 73), one E. aspera sample (n = 74), one D. favus sample (n = 74) and one M. elephantotus sample (n = 74) being removed. Statistical analyses Microbial community composition To identify microbial communities and specific microbial taxa associated with different larval settlement levels we performed community structure and differential abundance analyses of the microbiome ( 44 ). Permutational multivariate analysis of variance (PERMANOVA) and pairwise PERMANOVAs were used to test whether microbial community diversity differed between groupings of biologically relevant features. In particular, they were conducted between sample type (CCA, water, and coral larvae species) and between CCA species to determine whether CCA microbiomes were distinct from those found in surrounding seawater, coral larvae, and between CCA species. For each coral species, pairwise PERMANOVAs were performed to compare CCA microbial communities associated with different settlement categories (low [0–30%], medium [30–60%] and high [60–100%], defined through histogram partitions as described in Turnlund, Vanwonterghem ( 45 )), and to ascertain if microbial community composition differed according to the associated settlement response (Figure S1 ). All PERMANOVAs were performed on distance matrices created from log(x + 1) transformed ASV counts. The function vegdist() was used to calculate Bray-Curtis dissimilarity matrices, adonis2() for PERMANOVAs, and pairwise.adonis() for pairwise PERMANOVAs from the vegan package ( 46 ). All statistical analyses were performed in RStudio ( 47 ). For each coral species, CCA microbial communities were compared between different CCA species and larval settlement scores using non-metric multidimensional scaling (nMDS) ordination plots with Bray-Curtis dissimilarity. ASV count matrices were log(x + 1) transformed before creating distance matrices with the metaMDS() function from the vegan R package ( 46 ). All plots were visualised with ggplot2 ( 48 ). Identifying ASVs associated with high and low settlement A combination of statistical analyses was used, including linear models (LM), differential abundance, indicator species, and machine learning analysis, to identify specific microbial taxa associated with settlement. Indicator species analysis evaluates the strength of an ASV association with metadata variables based on both presence and relative abundance, and was performed on the relative abundance of the filtered ASV table using the Multipatt() function of the Indicspecies package ( 49 ). Indicator analyses were computed at p < 0.05 significance, and alpha specificity and beta-fidelity values of 0.75 to identify indicator taxa for each settlement category per coral species. Indicator species values consider both site fidelity and specificity scores to assign a single indicator score between 1 (an ASV that is found in every sample within a specific settlement level and only that specific settlement level) and 0 (an ASV that is not exclusive or persistent amongst samples in a certain settlement level). Differential abundance was calculated using the ancombc2() function from the ANCOM-BC package ( 50 , 51 ), which models the microbiome data with a linear regression framework in log-scale and reports significant log fold changes (LFC) between sample groups. The p-value was adjusted with the false discovery rate method (FDR), taxon proportion filters were set to zero (prv_cut = 0) since data was pre-filtered, and the parameter “Pairwise” was set to TRUE to account for pairwise comparisons between all settlement levels. Significant log-fold changes at the ASV level between high and low settlement-inducing CCA species were visualised for each coral assay with a bar plot using the package ggplot2 ( 48 ). Correlations between ASV abundance and coral settlement values were also analysed using multivariate linear models (LM) with the R package Maaslin2 ( 52 ). Models were run for each coral separately and microbial data (post-filtering at 0.01% minimum abundance and 0.1% minimum prevalence) was log-transformed and normalised with total-sum scaling. CCA host was considered a random effect, and the continuous percent settlement score was used as a fixed effect. A Random Forest (RF) analysis that uses Breiman’s random forest algorithm was conducted for each coral to identify ASVs with the highest predictive ability for coral settlement with the randomForest package ( 53 , 54 ). ASVs with significant prediction model importance values (p < 0.05) were kept if the ASV also had significant results in LM, indicator species and/or differential abundance analyses. Data visualisation Coral larval settlement per CCA treatment were visualised with box plots in ggplot2 ( 48 ) for each coral and significant Maaslin2 LM results were shown in a heatmap using pheatmap ( 55 ). Corals with LM results that overlapped with other analyses (e.g. indicator species, differential abundance, RF) were further visualised and the relative abundance of these ASVs per CCA treatment were graphed with ggplot bar charts and bubble plots, respectively ( 48 ). For each coral species, ASVs were further investigated if they were identified as being significantly correlated with settlement (p < 0.05) in the LM analysis and were also differentially abundant (ANCOM-BC), an indicator for high/low settlement (Indicspecies) and/or significant RF model importance values. LM coefficient score, log fold change, indicator, and RF model importance values for each ASV of interest were visualised with bar plots and the relative abundances of the ASVs across CCA samples were presented using bubble plots in ggplot2 ( 48 ). CCA samples that did not contain any of the ASVs of interest were removed from the bubble plot. Results & Discussion To investigate the potential role of crustose coralline algae (CCA) microorganisms in coral larval settlement, this study interrogated the microbiomes of 15 CCA species that elicited varying settlement responses for 14 Great Barrier Reef (GBR) coral species. We found that although CCA microbiomes were distinct and species-specific, there was also minor microbial compositional variation within CCA species. Importantly, differences within CCA species microbiomes reflected differences in coral larval settlement responses, with individual microbial taxa identified as settlement inducing or inhibiting. Microbiomes are distinct across CCA species and coral larval settlement response CCA microbial communities were distinct from the surrounding seawater and coral larvae (PERMANOVA: F = 7.16, p < 0.001; Table S5), and they also differed between CCA species at the amplicon sequence variant (ASV) level. Previous research has shown that CCAs host species-specific microbial community communities ( 24 , 26 )(Turnlund et al. in review), and our results highlight that this pattern persists in aquaria after collection from the field (Fig. 1 ; see Table S6 for full PERMANOVA results). CCA species shared similar microbial orders, such as Rhodobacterales, Flavobacteriales, Pirellulales, Rhizobiales , and Altermonadales , consistent with previous reports of CCA microbiomes ( 24 , 26 , 56 ) (Fig. 2 ). Settlement responses of coral larvae varied both across and within CCA species (Fig. 3 ) ( 7 ). To investigate whether this variation was driven by the CCA microbiome, we analysed differences in the composition of CCA microbiomes across levels of larval settlement for each coral species. CCA microbial communities mostly grouped according to CCA species, with some CCA species and some samples within CCA species promoting higher settlement than others (Fig. 1 ; see Table S6 for full PERMANOVA results). For example, when comparing high and low settlement groups across CCA species, there was a significant difference between microbial communities associated with high versus low settlement for every coral tested, except for F. fungites, P. daedalea , and P. lobata (Table S7). It is still unclear whether coral larval settlement cues originate from the CCA host, their epiphytic microbial communities, or a combination of both. However, since CCAs associated with low settlement had significantly different microbial communities than CCAs associated with high settlement, there may be a microbial settlement cue for most of the corals tested here. Where no significant difference was observed between inductive and non-inductive CCA microbiomes, abiotic or host derived cues may explain the patterns found in coral settlement instead ( F. fungites, P. daedalea , and P. lobata ; Table S7). Gómez-Lemos, Doropoulos ( 57 ) found that Titanoderma tessellatum chemistry had a stronger effect on Acropora millepora settlement than T. tessellatum surface microbial communities and the microbial communities were only inductive in the presence of algal dissolved organic carbon (DOC). In our study, T. cf. tessellatum elicited differing settlement responses per coral species (Fig. 3 ). Interestingly, for some corals (i.e. C. aspera, E. aspera, L. corymbosa , and M. aequituberculata ; Fig. 1 ), there was a significant difference between microbial communities associated with high and low settlement, suggesting potential involvement of the microbiome. On the contrary, such differences in microbiome composition were not observed for A. millepora settlement, aligning with the findings of Gómez-Lemos, Doropoulos ( 57 ). Meanwhile, Giorgi, Monti ( 39 ) administered a range of antibiotics to CCA surfaces to differentiate host and microbial cue responses for Orbicella faveolata , and found that larval settlement increased with antibiotic treatment for some CCA species (likely a host originated cue paired with the decrease of a microbial inhibitor), but decreased settlement for other CCA species (likely a microbial cue). Therefore, the origin of these cues (host vs microbial vs a combination of both) are likely coral species specific and cannot be generalised ( 39 , 58 ). While our findings suggest involvement of the CCA microbiome for some coral species, additional experiments are required to fully untangle the contributions of microorganisms, CCA host, and chemicals produced. Specific ASVs associate with high or low coral larval settlement Multiple metrics were used to identify ASVs associated with high or low coral settlement, including (linear models (LM), differential abundance (DA) analysis, indicator species (IA), and random forest (RF) analysis). All analysis was done at the ASV level but are taxonomically classified to the most specific level available. ASVs were considered associated with a specific coral larval settlement level if they were identified by at least two of these metrics for higher confidence. This allowed us to narrow down potential microbial inducers or inhibitors and compare their presence and relative abundance across CCA species. Overall, out of the 66,408 ASVs present in the entire dataset, 96 ASVs correlated with high coral settlement and 254 ASVs correlated with low settlement, with specific ASVs associated with high or low settlement for most coral species (Fig. 4 ). Specifically, we identified a group of coral species that displayed similar groups of ASVs correlated with high or low coral settlement ( M. elephantotus, L. corymbosa, E. aspera, D. favus , and P. sinensis : herein referred to as ‘Group A corals’ as first defined by Abdul Wahab, Ferguson ( 7 )) (Figs. 4 & 5 ). These corals were previously identified to have similar selective CCA settlement preferences ( 7 ), while a second group identified by Abdul Wahab, Ferguson ( 7 ) ( A. tenuis , P. daedalea, C. furcata , and P. lobata : herein referred to as ‘Group B corals’) did not share similar ASVs correlated with high or low settlement (Fig. 4 ). For generalist coral larvae (i.e., larvae that do not show a strong preference for the CCA species they settle on), like Group B corals and to a lesser extent Acropora hyacinthus , there were less settlement-associated ASVs identified compared to corals with selective settlement preferences (i.e., larvae that only settle on a few specific CCA species), like Group A corals (Fig. 4 ). Specifically, we found that Group A corals shared common ASVs associated with high or low settlement, however three ASVs from genera Fodinicurvata , Pegibius and Lewinella elicited different responses across different species of corals (e.g. Fodinicurvata was associated with high E. aspera , but low P. sinensis settlement; Pegibius was associated with high P. sinensis , but low L. corymbose settlement; Lewinella was associated with high P. sinensis , but low E. aspera settlement; Fig. 5 ). This coral species specificity at the ASV level highlights the importance of identifying potential inductive microbial taxa at the lowest taxonomic level possible. Notably, these microbial associations were less clear when communities were considered at broader levels, whereby taxonomic families may comprise both inducing and inhibiting ASVs (Fig. 5 ). For the remaining coral species not included in Groups A or B, our analyses were able to identify only a few or no ASVs associated with high settlement (see Supplementary Information). This suggests that larvae of these corals are either selectively responding to CCA host derived cues, settlement cues originating from other symbionts and/or not settling in response to microbial and/or host inhibitory cues. Shared taxa correlated with high settlement Amongst group A corals, D. favus and P sinensis shared the highest number of ASVs associated with high larval settlement, while L. corymbosa had lowest overlap (Fig. 5 ). In contrast, a study testing the settlement responses of similar coral species ( D. favus , E. aspera , L. corymbosa , P. lobata , and P. sinensis ) to microbial biofilms found little overlap in ASVs correlating with high settlement between corals overall ( 59 ). This may reflect differences in microbial habitat niches available on CCA versus abiotic substrates (e.g., microbial biofilms), whereby inductive microorganisms may first need resources provided by the CCA host to successfully colonise, increase their settlement cue potency with the presence of algal DOC ( 57 ), and/or the corals are settling better in response to presence the CCA host themselves. Despite the numerous ASVs associated with high settlement shared amongst the group A corals, only one Filomicrobium ASV was associated with high settlement between all of them (Fig. 5 ). This Filomicrobium ASV was associated with high settlement from LM analysis and was additionally found to have higher differential abundance (DA) in high settlement compared to low settlement samples of D. favus (Log Fold Change (LFC): 2.10 ± 0.44), E. aspera (LFC: 2.03 ± 0.54), and P. sinensis (LCF: 2.10 ± 0.44). Filomicrobium has been previously identified in microbiomes of healthy Galaxea fascicularis and Porites pukoensis corals ( 60 ), brown algae Cystoseira compressa ( 61 ), and green seaweed Halimeda opuntia ( 62 ) and was found in multiple CCA species characterised in this study. Therefore, this microorganism may be linked to algae-host symbiosis and indicative of healthy algae (free of disease), which could be a better suited settlement substrate that produced more inductive compounds than diseased algae. The other ASVs associated with high settlement of Group A corals were shared across a combination of species (Fig. 5 ). For example, one Candidatus Nitrosopumilus ASV was shared amongst all corals except L. corymbosa for LM analysis and was also a high settlement indicator for D. favus (Indicator species value (ISV): 0.57) and P. sinensis settlement (ISV: 0.69) (Table S8). A second Ca. Nitrosopumilus ASV was shared amongst D. favus , M. elephantotus , and P. sinensis for LM analysis, and showed significantly higher relative abundance in high settlement D. favus (LFC: 1.43 ± 0.48) and P. sinensis (LFC: 1.43 ± 0.48) samples (Table S8). Nitrosopumilus is an ammonia-oxidizing bacteria commonly found in sponges ( 63 – 65 ). Certain members have been shown to produce nitric oxide ( 66 ), a key signalling molecule for marine invertebrate larval settlement ( 67 – 69 ). Future research should explore the role of nitric oxide by Nitrosopumilus sp. in regulating coral larval settlement. In addition, two Neptuniibacter ASVs also correlated with high Group A coral settlement for LM analysis. One Neptuniibacter ASV was more differentially abundant in high settlement G. favulus (LFC: 0.44 ± 0.12), M. elephantotus (LFC: 0.26 ± 0.08), and P. sinensis (LFC 0.10 ± 0.03) samples compared to low settlement samples, and the other was more differentially abundant in L. corymbosa (0.18 ± 0.07) and M. elephantotus (0.17 ± 0.07) (Table S8). Neptuniibacter also correlated with Acropora millepora settlement on mixed-species CCA microbial biofilms ( 26 ). This genus has also been previously associated with microbiomes of the CCA species P. onkodes ( 26 , 70 ), green algae ( 71 ), and Mussisimilia corals ( 72 ). Furthermore, Neptuniibacter was found enriched in macroalgae that induced settlement of the coral Pocillopora damicornis ( 73 ). The Neptuniibacter ASVs that correlated with high settlement were present in every CCA species tested, including Amphiroa foliacea samples at lower relative abundances, which elicited little to no settlement from any coral (Figures S3-S15). Therefore, if a settlement response is initiated by Neptuniibacter , it is likely concentration dependent, reliant on the presence of other microorganisms in a mixed-biofilm community and/or coupled to a host-derived cue. Overall, ASVs identified from high settlement samples with LM analysis that were shared amongst Group A corals were found across multiple CCA species. This suggests these corals are responding to a microbial signal present across the different CCA species, yet further testing is required to confirm this hypothesis. Shared taxa correlated with low settlement Similar to identifying ASVs associated with high settlement, LM results were also used to compare ASVs associated with low settlement (Fig. 4 ). Within Group A corals, D. favus and E. aspera shared the greatest number of ASVs associated with low settlement from LM analysis (Fig. 5 ), and these mostly belonged to Planctomycetes, like Pir4 and OM190 lineages, and Flavobacteriaceae (Table S8). Microbes belonging to either of these groups are commonly associated with different types of algae ( 74 – 77 ) and have been shown to degrade polysaccharides in algal cell walls ( 77 , 78 ). While there were no ASVs associated with low settlement that were shared across all Group A corals, a Flavobacteriaceae ASV belonging to the genus Winogradskeylla was correlated with low settlement for three coral species within Group A corals: D. favus (LFC: -0.98 ± 0.31), M. elephantotus (LFC: -1.40 ± 0.40), and P. sinensis (LFC: -1.0 + 0.31) (Fig. 5 ; Table S8). This genus was previously identified in diseased coral ( 79 ) and alga microbiomes ( 74 , 77 , 80 ). It also has reported biocidal activity by producing poly-ethers that inhibited barnacle Balanus amphitrite ( 81 , 82 ) and Hydroides elegans settlement ( 83 ). Furthermore, Winogradskeylla also correlated with low P. sinensis settlement from microbial biofilms, suggesting that even separated from the CCA host, this microorganism may inhibit P. sinensis settlement ( 59 ). Within the phylum Planctomycetes, ASVs belonging to the Pir4 and OM190 lineages and the genus Blastopirellula were correlated with low settlement from LM analysis. The specific ASVs varied depending on the combinations of group A corals that they were associated with (Fig. 5 ). For example, low settlement in M. elephantotus and P. sinensis was associated with a Pir4 lineage ASV, while three OM190 ASVs were correlated with low settlement in L. corymbosa and M. elephantotus (Fig. 5 ). Furthermore, the genus Blastopirellula was associated with low settlement across five corals; with three Blastopirellula ASVs each linked to low settlement in a different pair of coral species: L. corymbosa and M. elephantotus , D. favus and E. aspera , and E. aspera and P. sinensis (Fig. 5 ). In contrast, Pir4 lineage and Blastopirellula were associated with high P. sinensis and P. lobata settlement in response to microbial biofilms ( 59 ), suggesting that the settlement effect of these microorganisms may differ when paired with the CCA host. For example, the CCA host might be counteracting the settlement inducing ability of the microbes resulting in different coral larval settlement responses. These lineages are commonly found within algal microbiomes ( 75 – 77 , 84 , 85 ) and members of the phylum Planctomycetes have been associated with algal dysbiosis ( 78 ) and antibiotic resistance ( 78 , 86 – 89 ). Biocidals produced by some members of the phylum Planctomycetes could directly curb colonisation of settlement-inducing microbes and/or shape the microbial community to deter larval settlement. Furthermore, Planctomycetes ASVs were mostly found in CCA occupying mid-high light habitats, i.e., A. cf. foliacea , that elicited very low settlement responses overall. Abdul Wahab, Ferguson ( 7 ) suggested that corals adapted to certain light habitats were induced by CCA found within similar habitat light conditions, with Group A coral species preferring CCA more adapted to mid-low light habitats. This preference could be reflected in the microbiomes between the different CCAs, as settlement of Group A corals largely negatively correlated with ASVs unique to high-light habitat CCAs (Table S1 ; Figure S6; S7; S10; S12; S14). For example, low settlement ASVs were frequently found in low settlement samples of CCA found in high-light conditions (i.e., P. onkodes , L. cf. pygmaeum and A. cf. foliacea ) for each Group A coral species. A. cf. foliacea is a branched, nongeniculate coralline alga that induces weak settlement responses for a wide diversity of GBR coral species ( 7 ), despite the presence of microbial taxa that correlate with high settlement. While this could be attributed to the presence of microbial inhibitors that may have a stronger inhibitory effect than the inductive microbes, it may also be attributed to the host algae itself, and/or biochemicals released potentially have a strong inhibitory effect. Therefore, further work is required to confirm whether the Blastopirellula , OM190 , and Pir4 lineage ASVs or a habitat-specific abiotic or host cue is responsible for the inhibitory effect. Most corals in this study had more ASVs correlated with low than high larval settlement levels and this were shared across a variety of CCA species. This trend is largely consistent with previous coral larval settlement studies ( 45 , 59 , 73 , 90 ). For example, Lewinella (Saprospiraceae) was correlated with low M. aequituberculata and D. favus settlement (Table S8) in this study and was also found to negatively correlate with A. tenuis coral settlement by Padayhag, Nada ( 90 ). In addition, members of Planctomycetes and Rhizobiaceae were associated with low C. furcata, M. elephantotus, D. favus, C. aspera, L. corymbosa and P. sinensis settlement (Table S8) and were also found to correlate with low A. tenuis ( 90 ) and P. damicornis coral settlement ( 73 ), respectively. It has been postulated that Rhizobiaceae encourages macroalgae growth through enriched nitrogen fixation ( 73 , 91 ). Rhizobiaceae has also been found associated with coral disease ( 92 – 94 ) and bleaching ( 95 ), and has been assumed to be detrimental to larval settlement ( 73 ). Although several taxa from the phylum Planctomycetes, such as Pir4 lineage and Blastopirellula , and the family Flavobacteriaceae , like Winogradskeylla , correlated with low coral settlement, these ASVs were unique to CCA with overall low settlement ( A. cf. foliacea ). This shows that CCA species with low coral settlement response often host microbial taxa that are not found in settlement-inducing CCA. Further research remains warranted to establish whether the apparent inhibitory effect is due to a specific microbial cue or the CCA host. Microbial taxonomic families elicit differing coral larval responses depending on the coral species Within a single microbial family, some ASVs were identified as inducers while others were potential inhibitors, depending on the coral species, further highlighting the complexity of settlement responses. For example, one Tenacibaculum (Flavobacteriaceae) ASV was associated with high settlement of A. tenuis (ISV: 0.793) and was found in every single CCA species tested, with higher relative abundance in L. insipidium and Porolithon sp.2 samples (Figure S3). Tenacibaculum has previously been postulated to influence larval settlement of the coral P. damicornis ( 73 ) and the health of Tubastraea coccinea ( 96 ). However, in this study, this same ASV was also associated with low D. favus settlement (LMC: -0.61 0.22). Tenacibaculum and one unassigned Flavobacteriaceae were the only Flavobacteriaceae ASVs correlated with high settlement (for A. tenuis and C. aspera , respectively; Table S8), with the rest of the Flavobacteriaceae ASVs identified ( Aquimarina, Flagellimonas , and Maribacter ) correlating with low coral larval settlement (Table S8). Certain isolates of Flavobacteriaceae have also been associated with low settlement of mussels ( 97 ) and high settlement of the corals A. microphthalma ( 98 ), P. sinensis, E. aspera , and P. lobata ( 59 ). Similar results were found for a Granulosicoccus ASV, which correlated with high P. daedalea settlement (LM Coefficient: 0.35 0.11), but also low C. furcata (LMC: -0.58 0.10; LFC: -1.78 0.45; IVC: 0.755) and M. elephantotus (LFC: -1.64 0.4; IVC: 0.757) settlement. Granulosicoccus have previously been found in biofilms that elicited high larval settlement in coral A. tenuis ( 45 ), but a mixed settlement response between P. daedalea, C. furcata , and M. elephantotus (corals belonging to the Merulinidae family), suggesting that microbial cues vary within coral families, are species-specific, and that microbial taxonomy at the family and even genus level does not necessarily reveal the inductive capacity of a microbe. Rhodobacteraceae is another taxonomic family that has previously been associated with both high and low levels of coral larval settlement ( 45 , 59 , 90 ). In this study, ASVs belonging to Rhodobacteraceae were correlated with low settlement in C. furcata, M. aequituberculata, C. aspera, A. hyacinthus, D. favus and P. sinensis , but they differed amongst microbial genera and correlation strength across coral species (Table S8). In particular, the two unassigned Rhodobacteraceae ASVs associated with low C. aspera settlement were found in at least one sample for every CCA across a range of settlement, but were particularly abundant in low settlement samples, especially in L. proliferum (Figures S4). However, it is also possible that these unassigned Rhodobacteraceae ASVs are not necessarily a low settlement inhibitor, as they were also present in lower abundances in a few high settlement samples, but co-occur with other microbial inhibitors in a low settlement community that is in the middle of succession to resemble a microbial community that induces more settlement. Turnlund, Vanwonterghem ( 45 ) suggested that Rhodobacteraceae may be an important microorganism for biofilm community succession to change from a low to high settlement inducing biofilm; however, since our data represents one time point, we cannot determine if the presence of Rhodobacteraceae would alter the present microbial community overtime to create niches for microbial inducers. Conclusion and future directions Specific microorganisms associated with high or low larval settlement were identified for 14 different GBR coral species. These putative inducers and inhibitors belonged to a diverse range of microbial taxa and represent important targets for future research to distinguish the role of the algal-host versus microbiome. Further, these taxa can be tested in validation experiments using isolated mono- or mixed-species biofilms or through manipulation of CCA microbiomes by enriching potential inducers or lowering inhibitor abundance. Building on these findings, we also suggest that future research focus on the functional characterisation of the CCA microbiome to better interrogate whether common functions or biochemical pathways, rather than taxa, are the source of microbial settlement cues. While coral larvae are responding to different combinations of microbial taxa, these may represent complementary functional pathways that trigger larval settlement. The identification of microbial inducers and inhibitors for larval settlement is critically important for our understanding of coral settlement behaviour, which would in turn inform recruitment and coral populations dynamics as microbial communities shifts under anthropogenic stressors such as human-induced climate change ( 99 , 100 ). Furthermore, this study significantly adds to our knowledge and capability to guide the development of attractive substrates for coral larval settlement to optimise large-scale reef restoration. Declarations Ethics approval and consent to participate Not applicable Consent for publications Not applicable Data Availability The dataset supporting the conclusions of this article are available in the NCBI Sequence Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra) under the BioProject accession number PRJNA1100425. Competing interests The authors declare that they have no competing interests Funding This work was supported by the Australian Government Research Training Program, UQ Graduate school, and the Reef Restoration and Adaptation Program, which aims to develop effective interventions to help the Reef resist, adapt and recover from the impacts of climate change, and which is funded by the partnership between the Australian Governments Reef Trust and the Great Barrier Reef Foundation. Authors’ contributions ACT was responsible for conceptualization, writing the original draft, and formal analysis. PB, LR, NW, ML, and IV were responsible for conceptualization, and formal analysis. SF, GD-P, MAW was responsible for investigation. All authors edited and approved the final manuscript. Acknowledgements We would like to acknowledge and pay our respects to the Manbarra, Bindal, Wulgurukaba and Turrbal people, the Traditional Custodians of the land and sea country on which this research was performed on. We also thank Lesa Peplow and Sara Bell for their help in teaching the DNA extraction method and shipping the samples, and the RRAP CAD1 team for their work in collecting CCA. References Hughes TP, et al. Ecological memory modifies the cumulative impact of recurrent climate extremes. Nat Clim Change. 2019;9(1):40–3. Pratchett MS, et al. Recurrent mass-bleaching and the potential for ecosystem collapse on Australia’s Great Barrier Reef , in Ecosystem Collapse and Climate Change . Springer; 2021. pp. 265–89. Randall CJ, Szmant AM. Elevated temperature affects development, survivorship, and settlement of the elkhorn coral, Acropora palmata (Lamarck 1816). Biol Bull. 2009;217(3):269–82. Jorissen H, et al. High CO2 inhibits substratum exploration and settlement of coral larvae. Mar Ecol Prog Ser. 2022;689:47–56. Sarribouette L, et al. Post-settlement demographics of reef building corals suggest prolonged recruitment bottlenecks. Oecologia. 2022;199(2):387–96. Anthony KRN, Connolly SR. Environmental limits to growth: Physiological niche boundaries of corals along turbidity–light gradients. Oecologia. 2004;141:373–84. Abdul Wahab M, et al. Hierarchical settlement behaviours of coral larvae to common coralline algae. Sci Rep. 2023;13(1):5795. Nozawa Y. Micro-crevice structure enhances coral spat survivorship. J Exp Mar Biol Ecol. 2008;367(2):127–30. Doropoulos C, et al. Characterizing the ecological trade-offs throughout the early ontogeny of coral recruitment. Ecol Monogr. 2016;86(1):20–44. Vermeij MJA, et al. Coral larvae move toward reef sounds. PLoS ONE. 2010;5(5):e10660. Mason B, Beard M, Miller MW. Coral larvae settle at a higher frequency on red surfaces. Coral Reefs. 2011;30(3):667–76. Strader ME, Davies SW, Matz MV. Differential responses of coral larvae to the colour of ambient light guide them to suitable settlement microhabitat. R Soc Open Sci. 2015;2(10):150358. Foster T, Gilmour JP. Seeing red: Coral larvae are attracted to healthy–looking reefs. Mar Ecol Prog Ser. 2016;559:65–71. Petersen LE, et al. Photosensitivity of the bacterial pigment cycloprodigiosin enables settlement in coral larvae–light as an understudied environmental factor. Front Mar Sci. 2021;8:1599. Moeller M, Nietzer S, Schupp PJ. Neuroactive compounds induce larval settlement in the scleractinian coral Leptastrea purpurea. Sci Rep. 2019;9(1):1–9. Whitman TN, et al. Settlement of larvae from four families of corals in response to a crustose coralline alga and its biochemical morphogens. Sci Rep. 2020;10(1):16397. Silva PC, Johansen HW. A reappraisal of the order Corallinales (Rhodophyceae). Br Phycol J. 1986;21(3):245–54. Littler MM, Littler DS. The nature of crustose coralline algae and their interactions on reefs. Smithson Contrib Mar Sci. 2013;39:199–212. Sneed JM, Ritson-Williams R, Paul VJ. Crustose coralline algal species host distinct bacterial assemblages on their surfaces. ISME J. 2015;9(11):2527–36. Harrington L, et al. Recognition and selection of settlement substrata determine post-settlement survival in corals. Ecol. 2004;85(12):3428–37. Price N. Habitat selection, facilitation, and biotic settlement cues affect distribution and performance of coral recruits in French Polynesia. Oecologia. 2010;163(3):747–58. Ritson-Williams R, et al. Larval settlement preferences of Acropora palmata and Montastraea faveolata in response to diverse red algae. Coral Reefs. 2014;33:59–66. Ritson-Williams R, Arnold SN, Paul VJ. Patterns of larval settlement preferences and post–settlement survival for seven Caribbean corals. Mar Ecol Prog Ser. 2016;548:127–38. Jorissen H, et al. Coral larval settlement preferences linked to crustose coralline algae with distinct chemical and microbial signatures. Sci Rep. 2021;11(1):1–11. Erwin PM, Song B, Szmant AM. Settlement behavior of Acropora palmata planulae: Effects of biofilm age and crustose coralline algal cover . in Proceedings of the 11th International Coral Reef Symposium 2008. Ft. Lauderdale, Florida. Siboni N, et al. Crustose coralline algae that promote coral larval settlement harbor distinct surface bacterial communities. Coral Reefs. 2020;39(6):1703–13. Johnson CR, Muir DG, Reysenbach AL. Characteristic bacteria associated with surfaces of coralline algae: A hypothesis for bacterial induction of marine invertebrate larvae. Mar Ecol Prog Ser. 1991;74:281–94. Ritson-Williams R, et al. Larval settlement preferences and post-settlement survival of the threatened Caribbean corals Acropora palmata and A. cervicornis. Coral Reefs. 2010;29(1):71–81. Siboni N, et al. Using bacterial extract along with differential gene expression in Acropora millepora larvae to decouple the processes of attachment and metamorphosis. PLoS ONE. 2012;7(5):e37774. Sneed JM, et al. The chemical cue tetrabromopyrrole from a biofilm bacterium induces settlement of multiple Caribbean corals. Proc R Soc B-Biol Sci. 2014;281(1786):20133086. Tebben J, et al. Induction of larval metamorphosis of the coral Acropora millepora by tetrabromopyrrole isolated from a Pseudoalteromonas bacterium. PLoS ONE. 2011;6(4):e19082. Petersen LE, et al. Photodegradation of a bacterial pigment and resulting hydrogen peroxide release enable coral settlement. Sci Rep. 2023;13(1):3562. Nielsen SJ, Harder T, Steinberg PD. Sea urchin larvae decipher the epiphytic bacterial community composition when selecting sites for attachment and metamorphosis. FEMS Microbiol Ecol. 2015;91(1):1–9. Tran C, Hadfield MG. Larvae of Pocillopora damicornis (Anthozoa) settle and metamorphose in response to surface-biofilm bacteria. Mar Ecol Prog Ser. 2011;433:85–96. Sneed JM et al. Coral settlement induction by tetrabromopyrrole is widespread among Caribbean corals and compound specific. Front Mar Sci, 2024. 10. Johnson CR, Sutton DC. Bacteria on the surface of crustose coralline algae induce metamorphosis of the crown-of-thorns starfish Acanthaster planci. Mar Biol. 1994;120(2):305–10. Negri AP, et al. Metamorphosis of broadcast spawning corals in response to bacteria isolated from crustose algae. Mar Ecol Prog Ser. 2001;223:121–31. Nielsen S. Bacteria on coralline algae and their role as sea urchin settlement cues , in Centre for Marine Science and Innovation . 2014, UNSW Sydney. Giorgi A, et al. Larvae from three Caribbean corals settle differently in response to crustose coralline algae and their bacterial communities. Mar Ecol Prog Ser. 2024;751:53–69. Wilson K, et al. Genetic mapping of the black tiger shrimp Penaeus monodon with amplified fragment length polymorphism. Aquac. 2002;204(3–4):297–309. Botté ES, et al. Changes in the metabolic potential of the sponge microbiome under ocean acidification. Nat commun. 2019;10(1):4134. Caporaso JG, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108:4516–22. Callahan BJ, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13(7):581–3. Turnlund AC, et al. Understanding the role of micro-organisms in the settlement of coral larvae through community ecology. Mar Biol. 2025;172(3):1–15. Turnlund AC et al. Linking differences in microbial network structure with changes in coral larval settlement. ISME Commun, 2023. 3(1). Oksanen J et al. Vegan: Community ecology package . 2019. RStudio Team. RStudio: Integrated Development Environment for R. 2019; Available from: http://www.rstudio.com/ Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-; 2016. Cáceres MD, Legendre P. Associations between species and groups of sites: Indices and statistical inference. Ecol. 2009;90(12):3566–74. Lin H, Peddada SD. Analysis of compositions of microbiomes with bias correction. Nat commun. 2020;11(1):3514. Lin H, Eggesbø M, Peddada SD. Linear and nonlinear correlation estimators unveil undescribed taxa interactions in microbiome data. Nat commun. 2022;13(1):4946. Mallick H, et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol. 2021;17(11):e1009442. Breiman L. Random forests. Mach Learn. 2001;45:5–32. Breiman L. Manual on setting up, using, and understanding Random Foreswts V3.1 . 2002; Available from: https://www.stat.berkeley.edu/~breiman/Using_random_forests_V3.1.pdf Kolde R. pheatmap: pretty heatmaps . 2015. Meistertzheim AL, et al. Pathobiomes differ between two diseases affecting reef building coralline algae. Front Microbiol. 2017;8:1686. Gómez-Lemos LA, et al. Coralline algal metabolites induce settlement and mediate the inductive effect of epiphytic microbes on coral larvae. Sci Rep. 2018;8(1):1–11. Gómez-Lemos LA, et al. Coralline algal metabolites induce settlement and mediate the inductive effect of epiphytic microbes on coral larvae. Sci Rep. 2018;8(1):17557. O’Brien PA, et al. Light and dark biofilm adaptation impacts larval settlement in diverse coral species. Environ microbiome. 2025;20(1):11. Xu M, et al. Bacterial communities vary from different scleractinian coral species and between bleached and non-bleached corals. Microbiol Spectr. 2023;11(3):e04910–22. Mancuso FP, et al. Warming and nutrient enrichment can trigger seaweed loss by dysregulation of the microbiome structure and predicted function. Sci Total Environ. 2023;879:162919. Yang F, et al. Calcified macroalgae and their bacterial community in relation to larval settlement and metamorphosis of reef-building coral Pocillopora damicornis. FEMS Microbiol Ecol. 2021;97(1):fiaa215. Simister R, et al. Sponge-microbe associations survive high nutrients and temperatures. PLoS ONE. 2012;7(12):e52220. Zhang F, et al. Symbiotic archaea in marine sponges show stability and host specificity in community structure and ammonia oxidation functionality. FEMS Microbiol Ecol. 2014;90(3):699–707. Engelberts JP, et al. Characterization of a sponge microbiome using an integrative genome-centric approach. ISME J. 2020;14(5):1100–10. Martens-Habbena W, et al. The production of nitric oxide by marine ammonia‐oxidizing archaea and inhibition of archaeal ammonia oxidation by a nitric oxide scavenger. Environ Microbiol. 2015;17(7):2261–74. Song H, Hewitt OH, Degnan SM. Arginine biosynthesis by a bacterial symbiont enables nitric oxide production and facilitates larval settlement in the marine-sponge host. Curr Biol. 2021;31(2):433–7. Castellano I, Ercolesi E, Palumbo A. Nitric oxide affects ERK signaling through down-regulation of MAP kinase phosphatase levels during larval development of the ascidian Ciona intestinalis. PLoS ONE. 2014;9(7):e102907. Ueda N, Degnan SM. Nitric oxide is not a negative regulator of metamorphic induction in the abalone Haliotis asinina. Front Mar Sci. 2014;1:1–13. Webster NS, et al. Ocean acidification reduces induction of coral settlement by crustose coralline algae. Glob Chang Biol. 2013;19(1):303–15. Liang Z, et al. High-throughput sequencing revealed differences of microbial community structure and diversity between healthy and diseased Caulerpa lentillifera. BMC Microbiol. 2019;19(1):1–15. de Castro AP, et al. Bacterial communities associated with three Brazilian endemic reef corals (Mussismilia spp.) in a coastal reef of the Abrolhos shelf. Cont Shelf Res. 2013;70:135–9. Xiao Z, et al. Marine macroalgae and their associated bacterial communities affect larval settlement and survivorship of the coral Pocillopora damicornis. Mar Environ Res. 2024;199:106597. Kumar V, et al. Multiple opportunistic pathogens can cause a bleaching disease in the red seaweed Delisea pulchra. Environ Microbiol. 2016;18(11):3962–75. James AK, et al. Giant kelp microbiome altered in the presence of epiphytes. Limnol oceanogr lett. 2020;5(5):354–62. Ihua MW, et al. Diversity of bacteria populations associated with different thallus regions of the brown alga Laminaria digitata. PLoS ONE. 2020;15(11):e0242675. Kopprio GA, et al. Insights into the bacterial community composition of farmed Caulerpa lentillifera: A comparison between contrasting health states. MicrobiologyOpen. 2021;10(6):e1253. Bondoso J, et al. Epiphytic Planctomycetes communities associated with three main groups of macroalgae. FEMS Microbiol Ecol. 2017;93(3):fiw255. Krishnaswamy VG, et al. Prevalence of differential microbiome in healthy, diseased and nipped colonies of corals, Porites lutea in the Gulf of Kachchh, north-west coast of India. Environ Res. 2023;216:114622. Liu Q, et al. Changes in phycospheric and environmental microbes associated with an outbreak of yellow spot disease on Pyropia yezoensis. Aquac. 2020;529:735651. Dash S, et al. Antibacterial and antilarval-settlement potential and metabolite profiles of novel sponge-associated marine bacteria. J Ind Microbiol Biotechnol. 2009;36(8):1047–56. Dash S, et al. Poly-ethers from Winogradskyella poriferorum: Antifouling potential, time-course study of production and natural abundance. Bioresour Technol. 2011;102(16):7532–7. Almeida JR, Vasconcelos V. Natural antifouling compounds: Effectiveness in preventing invertebrate settlement and adhesion. Biotechnol Adv. 2015;33(3–4):343–57. Storesund JE, Øvreås L. Diversity of Planctomycetes in iron-hydroxide deposits from the Arctic Mid Ocean Ridge (AMOR) and description of Bythopirellula goksoyri gen. nov., sp. nov., a novel Planctomycete from deep sea iron-hydroxide deposits. Antonie Van Leeuwenhoek. 2013;104:569–84. Lage OM, Bondoso J. Planctomycetes and macroalgae, a striking association. Front Microbiol. 2014;5:267. Schlesner H. The development of media suitable for the microorganisms morphologically resembling Planctomyces spp., Pirellula spp., and other Planctomycetales from various aquatic habitats using dilute media. Syst Appl Microbiol. 1994;17(1):135–45. Cayrou C, Raoult D, Drancourt M. Broad-spectrum antibiotic resistance of Planctomycetes organisms determined by Etest. J Antimicrob Chemother. 2010;65(10):2119–22. Lage OM, Bondoso J. Planctomycetes diversity associated with macroalgae. FEMS Microbiol Ecol. 2011;78(2):366–75. Lage OM. Characterization of a Planctomycete associated with the marine dinoflagellate Prorocentrum micans Her. Antonie Van Leeuwenhoek. 2013;104(4):499–508. Padayhag BM, et al. Microbial community structure and settlement induction capacity of marine biofilms developed under varied reef conditions. Mar Pollut Bull. 2023;193:115138. Rincon-Rosales R, et al. Rhizobia with different symbiotic efficiencies nodulate Acaciella angustissima in Mexico, including Sinorhizobium chiapanecum sp. nov. which has common symbiotic genes with Sinorhizobium mexicanum. FEMS Microbiol Ecol. 2009;67(1):103–17. Becker CC, et al. Microbial bioindicators of Stony Coral Tissue Loss Disease identified in corals and overlying waters using a rapid field-based sequencing approach. Environ Microbiol. 2022;24(3):1166–82. Meyer JL, et al. Microbial community shifts associated with the ongoing stony coral tissue loss disease outbreak on the Florida Reef Tract. Front Microbiol. 2019;10:2244. Cárdenas A, et al. Shifts in bacterial communities of two caribbean reef-building coral species affected by white plague disease. ISME J. 2012;6(3):502–12. Haydon TD, et al. Rapid shifts in bacterial communities and homogeneity of Symbiodiniaceae in colonies of Pocillopora acuta transplanted between reef and mangrove environments. Front Microbiol. 2021;12:756091. Carlos C, Torres TT, Ottoboni LM. Bacterial communities and species-specific associations with the mucus of Brazilian coral species. Sci Rep. 2013;3(1):1624. Yang J-L, et al. Silver nanoparticles impact biofilm communities and mussel settlement. Sci Rep. 2016;6(1):37406. Webster NS, et al. Metamorphosis of a scleractinian coral in response to microbial biofilms. App Environ Microbiol. 2004;70(2):1213–21. Webster NS, et al. Elevated seawater temperature causes a microbial shift on crustose coralline algae with implications for the recruitment of coral larvae. ISME J. 2011;5(4):759–70. Webster N, et al. Host-associated coral reef microbes respond to the cumulative pressures of ocean warming and ocean acidification. Sci Rep. 2016;6(1):19324. Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Oct, 2025 Editor assigned by journal 21 Oct, 2025 Submission checks completed at journal 16 Oct, 2025 First submitted to journal 13 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7850943","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":530591222,"identity":"eb62c7eb-a4f0-413d-8e02-070bb49e20ea","order_by":0,"name":"Abigail C. Turnlund","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYPACCyBOPgAkJGSIUM0MIiSAOC0BxOAhRUuOAYhFWAt/+/lj0pU7JBK3s+d8fnWjxoKHgf3w0Q34tEicSWaTPHtGInFnz9tt1jnHgA7jSUu7gdeaG8xsko1tEokbbuRuM85hA2qR4DHDq0UeoSXnmXHOPyK0GCBpYX6c20aEFsMzycaWQC3GG848M2PO7ZPgYSPkF7njBx/ebGyzkd1wPPnx55xvdXL87IeP4fc+EmCTAJPEKgcB5g+kqB4Fo2AUjIKRAwAqv0Wky3i0ZQAAAABJRU5ErkJggg==","orcid":"","institution":"Australian Centre for Ecogenomics, The University of Queensland","correspondingAuthor":true,"prefix":"","firstName":"Abigail","middleName":"C.","lastName":"Turnlund","suffix":""},{"id":530591223,"identity":"9ad8bbb9-7ba3-4ce6-9dad-c69821fca3f2","order_by":1,"name":"Paul O’Brien","email":"","orcid":"","institution":"Australian Centre for Ecogenomics, The University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"O’Brien","suffix":""},{"id":530591226,"identity":"7d2bc4dd-0872-4909-ba61-232b535c9ff9","order_by":2,"name":"Laura Rix","email":"","orcid":"","institution":"Australian Centre for Ecogenomics, The University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Rix","suffix":""},{"id":530591228,"identity":"3e4aa3e5-5909-48e5-9288-6b7180eaef8b","order_by":3,"name":"Sophie Ferguson","email":"","orcid":"","institution":"Australian Institute of Marine Science","correspondingAuthor":false,"prefix":"","firstName":"Sophie","middleName":"","lastName":"Ferguson","suffix":""},{"id":530591229,"identity":"a2e44348-af8c-4ea8-8f6f-9dea0748b689","order_by":4,"name":"Nicole Webster","email":"","orcid":"","institution":"Institute of Marine and Antarctic Studies, University of Tasmania","correspondingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Webster","suffix":""},{"id":530591230,"identity":"6ef90303-6baf-4c2f-b78b-8eb3939cb78d","order_by":5,"name":"Guillermo Diaz-Pulido","email":"","orcid":"","institution":"Coastal and Marine Research Centre, School of Environment and Science, Nathan Campus, Griffith University","correspondingAuthor":false,"prefix":"","firstName":"Guillermo","middleName":"","lastName":"Diaz-Pulido","suffix":""},{"id":530591233,"identity":"4bc94090-53ec-4f31-a2a7-d4ccbac886bd","order_by":6,"name":"Muhammad Abdul Wahab","email":"","orcid":"","institution":"Australian Institute of Marine Science","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Abdul","lastName":"Wahab","suffix":""},{"id":530591235,"identity":"26ae12d5-a16c-49bc-8a0d-f301d24bd602","order_by":7,"name":"Miguel Lurgi","email":"","orcid":"","institution":"Department of Biosciences, Swansea University","correspondingAuthor":false,"prefix":"","firstName":"Miguel","middleName":"","lastName":"Lurgi","suffix":""},{"id":530591236,"identity":"2a2397fd-d146-47a2-8ce8-2e6080c7c9d5","order_by":8,"name":"Inka Vanwonterghem","email":"","orcid":"","institution":"Commonwealth Scientific and Industrial Research Organisation","correspondingAuthor":false,"prefix":"","firstName":"Inka","middleName":"","lastName":"Vanwonterghem","suffix":""}],"badges":[],"createdAt":"2025-10-13 16:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7850943/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7850943/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93987085,"identity":"7122ef35-94c7-404d-bee6-fb90b8152d3e","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":128642,"visible":true,"origin":"","legend":"","description":"","filename":"TurnlundManuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/8663408b4960b1fc1fa62d5c.docx"},{"id":93987086,"identity":"f0265a69-f0ce-46f9-b198-50984cefa852","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1959238,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/229c22ef5efd95b427ab807c.png"},{"id":93987089,"identity":"9162eff7-ea68-4095-a616-4b831dbf931d","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":660860,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/51e923e98d165f1d7f39dd1b.png"},{"id":93987091,"identity":"ae8eea30-8df7-4467-b1f8-3f0245625aa4","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1059242,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/02b688ba91a10a6f554ab72a.png"},{"id":93987093,"identity":"533f4b75-0504-4e0f-8282-5c7e021f74fb","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":324549,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/cf43312add0e5d7c68fbdd63.png"},{"id":93987095,"identity":"0b7c2b08-8f27-49e8-beb0-71bf88e096ac","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1180897,"visible":true,"origin":"","legend":"","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/24b73286a1df25d4d56144b8.png"},{"id":93987103,"identity":"9966ed69-446a-42e2-8456-6cc466c2b23a","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"json","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10360,"visible":true,"origin":"","legend":"","description":"","filename":"d41a55b439e34f65bb2e5d502f5177a6.json","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/da0f8ca764b531b7d9026e74.json"},{"id":93987112,"identity":"de6ac371-b31d-4328-a539-d8dea24771aa","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5888122,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/f4babf37cc27ffd88ecc31c4.docx"},{"id":93988039,"identity":"5a392b77-ee31-44e0-8310-5335914732bc","added_by":"auto","created_at":"2025-10-21 04:42:08","extension":"xml","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":176589,"visible":true,"origin":"","legend":"","description":"","filename":"d41a55b439e34f65bb2e5d502f5177a61enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/324f0144b2c9395fb9e07461.xml"},{"id":93987097,"identity":"ba6987f8-9a5a-47a8-ac0c-c6d3ff80de98","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1959238,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/fdf00aca26821a06de893c62.png"},{"id":93987101,"identity":"51dab33a-10a6-4b34-bb58-3bafe791f67f","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":660860,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/f32c07c548c3cfb9af4ecac9.png"},{"id":93988040,"identity":"9af43735-b9a1-4a11-b100-88a5cce2da01","added_by":"auto","created_at":"2025-10-21 04:42:08","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1059242,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/24b56b1c9d9a0b1e17c171bb.png"},{"id":93987098,"identity":"fd5382cf-96ba-4abb-9dac-ee36eb8cab9e","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":324549,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/7fc63ce8a6839b86ea1d61aa.png"},{"id":93987107,"identity":"1de22acc-508b-4f8c-81f6-fd7dda9a4a52","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1180897,"visible":true,"origin":"","legend":"","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/396afc6312f721dd089a0671.png"},{"id":93987332,"identity":"f2470241-008f-4020-ac7f-ba5b5b9518f7","added_by":"auto","created_at":"2025-10-21 04:34:08","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":678776,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/eb5c7865f8b04105b9e2be7e.png"},{"id":93987106,"identity":"8b25e350-afb7-42cd-9f0a-28584696af7c","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":451950,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/b3fd196507c82f27fd50a45d.png"},{"id":93987102,"identity":"5dec1688-2d44-4176-a620-224d864422fc","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":561239,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/200910422aa7ee922840fc7d.png"},{"id":93987104,"identity":"74ea43e9-f580-4a75-8773-7f1603c21e84","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161995,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/83394e3eecef1e7ae71cc8a0.png"},{"id":93987330,"identity":"6b75ac66-28c2-4e2e-9165-7b6ae10e6b0d","added_by":"auto","created_at":"2025-10-21 04:34:08","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":472042,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/8aa2024895ee966e367ea17e.png"},{"id":93987109,"identity":"23a6cbfd-ecec-4049-8ce0-6484472bf32b","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":174605,"visible":true,"origin":"","legend":"","description":"","filename":"d41a55b439e34f65bb2e5d502f5177a61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/9cc6f43fa05bee3e74c12aa6.xml"},{"id":93987111,"identity":"586f4b0b-06f1-4913-b52e-a39783dbc8fa","added_by":"auto","created_at":"2025-10-21 04:26:08","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":192462,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/eb1fbd32183d16820c39d6ff.html"},{"id":93987088,"identity":"49a0aa52-421a-445d-8f61-591209ddd300","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1959238,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial communities differentiate by crustose coralline algae (CCA) species and by coral larval settlement strength. Non-metric multidimensional scaling (nMDS) ordination plots based on Bray-Curtis dissimilarity comparing microbiome composition for CCA samples collected per coral species settlement assay. For each coral, two similar nMDS plots are shown, one coloured by CCA species (left) and one coloured by larval settlement score (right).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/10d000248b452cafcc76333f.png"},{"id":93987326,"identity":"739af0a9-17ad-4461-8a5e-57e87a7572fe","added_by":"auto","created_at":"2025-10-21 04:34:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":660860,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial community composition varies across crustose coralline algae (CCA) species. Each bar shows the mean relative abundance per CCA species sampled for each coral species’ larval settlement experiment. The top 20 taxonomic orders are shown, and the less abundant orders were combined in the ‘Other’ category.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/aff32b7f5d7fd741e369ae98.png"},{"id":93987090,"identity":"1fc11ac6-bc62-4bd7-9aa6-a12b96dbe45d","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1059242,"visible":true,"origin":"","legend":"\u003cp\u003eCoral larval settlement preferences differ by coral species and vary within crustose coralline algae (CCA) species. Each panel shows the results for a single coral species and box plots are coloured by CCA species. The results presented here are a subset of the samples from Abdul Wahab, Ferguson (7) and were selected across the range of settlement values for each CCA and coral combination (n=5 per CCA for each coral species, except for corals with dropped samples as specified in the methods). Each diamond represents the mean settlement for the samples sequenced for this study (see Abdul Wahab, Ferguson (7) for full CCA settlement response data)\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/45a1cdf68c152f4fa2fb5811.png"},{"id":93987327,"identity":"17ac7d62-9e0c-4d17-9ec4-d876bbfbff3e","added_by":"auto","created_at":"2025-10-21 04:34:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":324549,"visible":true,"origin":"","legend":"\u003cp\u003eAmplicon sequence variants (ASVs) associated with high or low settlement for each coral species. Each row represents an ASV with a significant linear model regression coefficient (LM) and is coloured by this coefficient (Red = high settlement; Blue = low settlement). The dendrogram is clustered by corals that share similar ASVs associated with positive and negative linear regression scores. ASVs were chosen if they were significant in the linear model regression and at least one other test, including random forests, differential abundance, or indicator species analysis. Overall, 96 ASVs were associated with high settlement and 254 ASVs were associated with low settlement. ASVs are represented by rows and coloured on the left axis by the Phylum or the highest classification the ASV belongs to (labeled unassigned (un.)). Columns represent coral species with two groups of corals (Group A and Group B) showing similar CCA settlement preferences as identified by Abdul Wahab, Ferguson (7). \u003cem\u003ePorites lobata\u003c/em\u003e (Group B coral) is omitted from this graph because no significant ASVs were identified to correlate with high or low settlement in the linear regression analysis.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/7c99d4db31052a79f1a26a60.png"},{"id":93987094,"identity":"29c62abd-66f6-46bb-b77b-145b0aa2b27f","added_by":"auto","created_at":"2025-10-21 04:26:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1180897,"visible":true,"origin":"","legend":"\u003cp\u003eAmplicon sequence variants (ASVs) associated with high or low settlement that are shared amongst Group A coral species (\u003cem\u003eDipsastrea favus, Echinophyllia aspera, Lobophyllia corymbosa, Mycedium elephantotus, and Platygrya sinensis\u003c/em\u003e). Bar lengths represent the linear model coefficient value for ASVs that were significant for more than two species within coral Group A. Individual rows are labeled by the ASV genus name and a unique ASV identifier used in this study. Bars are coloured by the taxonomic family they belong to (left legend) and are separated by their associations with high or low settlement. ASVs with stars are associated with high settlement for one coral but associated with low settlement for another coral.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/d8774f72ff7188e308c22c2b.png"},{"id":93988217,"identity":"a5d312aa-7b57-47d1-9b83-9924be9518b3","added_by":"auto","created_at":"2025-10-21 04:50:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6444739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/4cb95d76-2e97-486c-8571-f52a829d3956.pdf"},{"id":93987328,"identity":"466d740e-4ad7-4037-8cdb-b7e1c310411d","added_by":"auto","created_at":"2025-10-21 04:34:08","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":5888122,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-7850943/v1/81bee4d8b128dd68143a5646.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unravelling the role of crustose coralline algae microbiomes on coral larval settlement in the Great Barrier Reef","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe growth of coral reefs worldwide crucially depends on successful reproduction and larval recruitment of single individuals. Ongoing severe climate-related events (e.g. elevated sea temperatures and subsequent coral bleaching) have negatively impacted corals\u0026rsquo; ability to successfully reproduce and survive (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).The planktonic phase of coral larvae is especially sensitive to environmental disturbances, as larval development and swimming behaviour are markedly affected at higher sea water temperatures and lower pH levels (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This further alters the ability of larvae to settle in response to environmental cues, metamorphose, and survive, thus creating a major bottleneck that limits new coral growth and genetic diversity on reefs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In addition, different settlement cues are likely simultaneously being altered in response to environmental changes. However, a comprehensive assessment of this is lacking as the specific cues that trigger coral larval settlement are largely uncharacterised.\u003c/p\u003e\u003cp\u003eThe planktonic larvae of most coral species actively select a suitable settlement substrate (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), with a variety of environmental cues including surface structures (8, 9), sound (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), colour (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), light (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), and biochemical cues (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) influencing this selection. Many coral species have been shown to settle in response to crustose coralline algae (CCA), calcifying red algae that are abundant on tropical reefs and that play a key role in maintaining coral reef structure and biodiversity (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Corals typically have a preference for specific CCA species (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and some studies suggest that corals may in fact settle in response to cues originating from CCA surface-associated microorganisms (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) rather than the CCA themselves. Prior research has shown that CCA surface microbiomes are distinct from the surrounding water column (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) and that microbial community composition varies between CCA species (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)(Turnlund \u003cem\u003eet al.\u003c/em\u003e in review). However, it has been challenging to untangle the effects of CCA microbial communities from the CCA host on coral larval settlement.\u003c/p\u003e\u003cp\u003eTo separate host and microbial effects, analysis of crude extracts and microbial strains isolated from the CCA surface has uncovered morphogens that induce high levels of coral larval settlement (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). For example, two different strains of \u003cem\u003ePseudoalteromonas sp.\u003c/em\u003e, isolated from the CCA species \u003cem\u003eNeogoniolithon fosliei\u003c/em\u003e and \u003cem\u003ePorolithon\u003c/em\u003e (\u003cem\u003eHydrolithon\u003c/em\u003e) \u003cem\u003eonkodes\u003c/em\u003e (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) produce the morphogen tetrabromopyrrole (TBP) that can induce larval settlement and metamorphosis in \u003cem\u003eAcropora\u003c/em\u003e corals. More recently, cycloprodigiosin, an alkaloidal pigment isolated from a \u003cem\u003ePseudoalteromonas rubra\u003c/em\u003e strain found on the CCA \u003cem\u003eHydrolithon reinboldii\u003c/em\u003e, was found to induce coral settlement once activated under high-light conditions (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, the morphogenic attributes of any given microbe grown in cultivation might differ when part of a mixed-species community in the natural environment (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). For example, \u003cem\u003ePseudoalteromonas\u003c/em\u003e were found to be less inductive when in mixed-species biofilms (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), while extracts of TBP are often unstable and its effect on settlement can be concentration and strain dependent (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOther studies have administered antibiotics to CCA surfaces to remove CCA surface microbial communities and isolate the inductive capacity of the CCA host on larvae of different marine invertebrates, with mixed results (\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Johnson and Sutton (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) found that removing microorganisms from CCA surfaces negatively impacted Crown-of-Thorns starfish larval settlement, but settlement response improved after re-inoculating single strains to CCA surfaces. Other studies found that coral larval metamorphosis response to CCA was not affected by the antibiotic treatment but still identified single strains (\u003cem\u003ePseudoalteromonas\u003c/em\u003e) that promoted larval settlement (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). However, CCA surface microbiomes consist of mixed-species communities, and despite these advances, our understanding of the role that CCA-associated microbial communities play in promoting coral larval settlement for a wide diversity of coral species remains in its infancy.\u003c/p\u003e\u003cp\u003eAbdul Wahab, Ferguson (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) explored larval settlement of 15 different Great Barrier Reef (GBR) coral species in response to 14 coralline algae species and the non-coralline alga \u003cem\u003eRamicrusta\u003c/em\u003e. They found that different CCA elicited varying coral larval settlement responses depending on the coral species (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This experimental design provided the opportunity to investigate whether these settlement differences were driven primarily by the CCA host or the CCA associated microbiome. Hence, in this study we extend Abdul Wahab et al.\u0026rsquo;s findings to microbiome-related settlement cues by examining whether variations in microbiomes found on these CCA hosts were associated with differences in larval settlement responses. Further, we aimed to identify candidate settlement-inducing and inhibiting taxa and determine whether these taxa are coral species-specific or common across multiple species. Using a combination of statistical approaches, we identified individual microorganisms associated with high settlement for multiple coral species, and unique microbial taxa associated with low settlement inducing CCA species.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eFull details of coral and algal collection and identification, spawning, maintenance of larval cultures, and settlement assays are described in Abdul Wahab, Ferguson (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) and are summarised briefly below.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCoral collection, spawning \u0026amp; larval culture\u003c/h2\u003e\u003cp\u003eColonies from fifteen different coral species, across 5 taxonomic families, from the Great Barrier Reef (GBR) were collected and used in settlement assays (\u003cem\u003eAcropora hyacinthus, A. tenuis\u003c/em\u003e, \u003cem\u003eA. anthocersis, Caulastrea furcata\u003c/em\u003e, \u003cem\u003eCoelastrea aspera\u003c/em\u003e, \u003cem\u003eDipsastrea favus\u003c/em\u003e, \u003cem\u003eEchinophyllia aspera\u003c/em\u003e, \u003cem\u003eFungia fungites\u003c/em\u003e, \u003cem\u003eGoniastrea favulus\u003c/em\u003e, \u003cem\u003eLobophyllia corymbosa, Montipora aequituberculata\u003c/em\u003e, \u003cem\u003eMycedium elephantotus\u003c/em\u003e, \u003cem\u003ePlatygyra daedalea\u003c/em\u003e, \u003cem\u003ePlatygrya sinensis\u003c/em\u003e, and \u003cem\u003ePorites lobata\u003c/em\u003e). Coral colonies were collected between the 9th to 20th October and 14th to 21st November 2021 from Magnetic Island (19˚07’45.78”S 146˚52’40.14”E), the Palm Island Group (18˚45’56.4”S 146˚32’2.58”E) and Davies Reef (18˚49’13.5”S 147˚38’40.32E) at 1 − 9 m depths under the GBRMPA Permit G21/45348.1. Corals were collected on SCUBA using a hammer and chisel and were transported into 70 L aquaria with consistent flow-through seawater for 4 − 6 h until their arrival at the National Sea Simulator (SeaSim) facility at the Australian Institute of Marine Science (AIMS) in Townsville, Australia. At SeaSim, corals were held in outdoor semi-recirculating aquaria with filtered seawater at ~ 27.2˚C and natural light.\u003c/p\u003e\u003cp\u003eWhen the setting of gametes was observed, colonies that produce egg-sperm bundles were moved to separate aquaria and buoyant bundles collected within the first hour of their release and gametes were fertilised. Embryos were gently washed with filtered seawater (FSW) to remove extra sperm after one hour and transferred to either 500 L or 70 L flow-through culture tanks. For \u003cem\u003eP. lobata, F. fungites, L. corymbosa\u003c/em\u003e and \u003cem\u003eG. favulus\u003c/em\u003e (i.e. gonochoric species, or hermaphroditic species releasing eggs and sperm separately), water containing sperm was mixed in aquaria that contained colonies with eggs, and embryos transferred to culture tanks within 30 to 45 min after signs of cleavage were observed. All larval cultures were maintained in flow-through culture tanks until the settlement experiment.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAlgal collection and identification\u003c/h3\u003e\n\u003cp\u003eThirteen non-geniculate CCA (\u003cem\u003eAdeylithon\u003c/em\u003e cf. \u003cem\u003ebosencei\u003c/em\u003e, \u003cem\u003eHydrolithon\u003c/em\u003e cf. \u003cem\u003ereinboldii\u003c/em\u003e, \u003cem\u003eLithophyllum\u003c/em\u003e cf. \u003cem\u003einsipidium, L.\u003c/em\u003e cf. \u003cem\u003ekotschyanum\u003c/em\u003e, \u003cem\u003eL.\u003c/em\u003e cf. \u003cem\u003epygmaeum\u003c/em\u003e, \u003cem\u003eLithothamnion\u003c/em\u003e cf. \u003cem\u003eproliferum\u003c/em\u003e, \u003cem\u003eMelyvonnea\u003c/em\u003e cf. \u003cem\u003emadagascariensis\u003c/em\u003e, \u003cem\u003eNeogoniolithon\u003c/em\u003e cf. \u003cem\u003efosliei\u003c/em\u003e, \u003cem\u003ePorolithon onkodes, Porolithon\u003c/em\u003e sp.1, \u003cem\u003ePorolithon\u003c/em\u003e sp.2, \u003cem\u003eSporolithon\u003c/em\u003e sp., and \u003cem\u003eTitanoderma\u003c/em\u003e cf. \u003cem\u003etessellatum\u003c/em\u003e), one geniculate coralline alga \u003cem\u003eAmphiroa\u003c/em\u003e cf. \u003cem\u003efoliacea\u003c/em\u003e, and one calcareous non-coralline alga \u003cem\u003eRamicrusta\u003c/em\u003e sp. (Peyssonneliaceae) were collected at 1–10 m depth on SCUBA from habitats that had either low-, moderate- and high-light with a hammer and chisel from Davies Reef and Havannah Island between the 9th and 20th of October 2021 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The 15 species are collectively hereafter referred to as CCA. Algal identification was first performed visually looking at anatomical and morphological traits and further identified with molecular analysis as previously detailed in Abdul Wahab, Ferguson (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCollected CCA were moved to AIMS SeaSim and cut into 10 x 10 mm pieces with a wet diamond band saw (Gryphon) and glued on a poly-vinyl-chloride (PVC) rack. These racks were placed in indoor semi-recirculating aquaria with 1 µm filtered seawater (~ 3 turnovers per day) at ~ 27.2˚C and held for either 2 − 3 weeks (October spawning, Table S2) or 4 − 6 weeks (November spawning, Table S3). CCA were kept under light conditions resembling the habitats they were collected from with the maximum midday irradiance levels for low-, moderate- and high- light adapted CCA was 12.7 − 15 µmol quanta m\u003csup\u003e− 2\u003c/sup\u003e s\u003csup\u003e− 1\u003c/sup\u003e, 56 − 58 µmol quanta m\u003csup\u003e− 2\u003c/sup\u003e s\u003csup\u003e− 1\u003c/sup\u003e, and ~ 120 µmol quanta m\u003csup\u003e− 2\u003c/sup\u003e s\u003csup\u003e− 1\u003c/sup\u003e, respectively.\u003c/p\u003e\n\u003ch3\u003eSettlement assays and CCA sampling\u003c/h3\u003e\n\u003cp\u003eSettlement assays were conducted in 6-well plates (Costar) with 10 mL of 0.1 µm FSW per well. Ten active larvae and one 5 x 5 mm CCA chip (tissue-side up) were placed in each well. Twelve replicates of each CCA treatment were randomised across 36 plates for each coral species except for \u003cem\u003eC. furcata\u003c/em\u003e, where only 6 treatment replicates were used due to low larval stock. Autoclaved aragonite chips and blank wells were used as controls. Settlement was recorded after 46 − 55 hours by counting permanently attached and metamorphosed larvae under a dissecting microscope. Settlement assays were repeated three times for \u003cem\u003eC. aspera\u003c/em\u003e at different larval ages (5, 8 and 18 days) due to initial low competency at 5 days, with the 8-day larval settlement assay results analysed in this study. Further, samples from \u003cem\u003eA. anthocersis\u003c/em\u003e were omitted from further analysis due to indiscriminate settlement of larvae (up to 40%) when CCA cues were not present (controls).\u003c/p\u003e\u003cp\u003eAfter settlement was recorded, each CCA chip (n = 12 replicates) was placed in a sterile cryovial and frozen in liquid nitrogen. Five of the twelve replicates were selected for CCA microbiome analysis. These replicates were chosen to cover a range of larval settlement outcomes, which allowed us to test if the variation in microbiome composition within a CCA species correlated with settlement success. The chip with the highest and lowest settlement response and three chips within the 50th percentile of settlement scores were chosen for sequencing (Table S4). FSW used in the settlement assays was sampled through the intake lines with 5 L per sample filtered onto 0.2 µm Sterivex filters (Millipore/Merck). Three replicate larval samples were also collected for each coral species to differentiate any larvae-associated microbes from the CCA microbiome. CCA, coral larvae, and water samples were stored in -75˚C freezers at AIMS until DNA extraction at the Australian Centre of Ecogenomics (ACE), University of Queensland, Brisbane.\u003c/p\u003e\n\u003ch3\u003eDNA extraction, sequencing \u0026amp; bioinformatics\u003c/h3\u003e\n\u003cp\u003eDNA was extracted from CCA samples (n = 75 per coral species, except for \u003cem\u003eC. furcata\u003c/em\u003e due to lower assay replication (n = 45) and \u003cem\u003eC. aspera\u003c/em\u003e (n = 73) where two samples were removed due to poor extraction results) and blank extraction controls (a blank tube with no CCA chip present; n = 1 per coral species) following a lysozyme and proteinase K buffer extraction protocol described in Wilson, Li (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Water samples were extracted from sterivex filters using a Phenol:Chloroform:IAA method described in Botté, Nielsen (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) and coral larvae DNA was extracted with the DNeasy® UltraClean® Microbial DNA extraction kit (Qiagen) following the manufacturer’s instructions. DNA quality was measured with a nanodrop (Thermo Scientific) for 260/280 and 260/230 absorbency ratios and quantified with a Qubit 1.0 Fluorometer and Qubit dsDNA HS assay kit (Invitrogen) before storage at -20˚C until sequencing.\u003c/p\u003e\u003cp\u003eSequencing was conducted at ACE using 16S rRNA gene amplicon sequencing targeting the V4 region on the Illumina MiSeq platform (2 x 250 bp) with primers 515F ‘GTGYCAGCMGCCGCGGTAA’ and 806R ‘GGACTACNVGGGTWTCTAAT’ (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Demultiplexed sequences were processed in QIIME2 (version 2022.8) and denoised with the DADA2 plug-in (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e), which merges pair-ends and clusters reads into amplicon sequence variants (ASVs). The forward sequences were truncated to 245 bp, while the first 7 bp of the reverse sequences were removed to eliminate reduced quality bases and additionally truncated at 183 bp. The QIIME2 feature-classifier function was used to classify ASVs with the SILVA database (version 138.1, 99_majority taxonomy). ASVs classified as Eukaryote, mitochondria, and chloroplast were removed from the ASV table and reads were filtered at 0.01% relative abundance, which removed sequences found in blank extraction controls and filtered seawater samples. Samples that had less than 10,000 reads were eliminated from further analyses, resulting in two \u003cem\u003eC. aspera\u003c/em\u003e samples (n = 69), two \u003cem\u003eP. daedalea\u003c/em\u003e samples (n = 73), one \u003cem\u003eE. aspera\u003c/em\u003e sample (n = 74), one \u003cem\u003eD. favus\u003c/em\u003e sample (n = 74) and one \u003cem\u003eM. elephantotus\u003c/em\u003e sample (n = 74) being removed.\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMicrobial community composition\u003c/h2\u003e\u003cp\u003eTo identify microbial communities and specific microbial taxa associated with different larval settlement levels we performed community structure and differential abundance analyses of the microbiome (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePermutational multivariate analysis of variance (PERMANOVA) and pairwise PERMANOVAs were used to test whether microbial community diversity differed between groupings of biologically relevant features. In particular, they were conducted between sample type (CCA, water, and coral larvae species) and between CCA species to determine whether CCA microbiomes were distinct from those found in surrounding seawater, coral larvae, and between CCA species. For each coral species, pairwise PERMANOVAs were performed to compare CCA microbial communities associated with different settlement categories (low [0–30%], medium [30–60%] and high [60–100%], defined through histogram partitions as described in Turnlund, Vanwonterghem (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e)), and to ascertain if microbial community composition differed according to the associated settlement response (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All PERMANOVAs were performed on distance matrices created from log(x + 1) transformed ASV counts. The function vegdist() was used to calculate Bray-Curtis dissimilarity matrices, adonis2() for PERMANOVAs, and pairwise.adonis() for pairwise PERMANOVAs from the vegan package (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). All statistical analyses were performed in RStudio (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor each coral species, CCA microbial communities were compared between different CCA species and larval settlement scores using non-metric multidimensional scaling (nMDS) ordination plots with Bray-Curtis dissimilarity. ASV count matrices were log(x + 1) transformed before creating distance matrices with the metaMDS() function from the vegan R package (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). All plots were visualised with ggplot2 (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eIdentifying ASVs associated with high and low settlement\u003c/h3\u003e\n\u003cp\u003eA combination of statistical analyses was used, including linear models (LM), differential abundance, indicator species, and machine learning analysis, to identify specific microbial taxa associated with settlement. Indicator species analysis evaluates the strength of an ASV association with metadata variables based on both presence and relative abundance, and was performed on the relative abundance of the filtered ASV table using the Multipatt() function of the Indicspecies package (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Indicator analyses were computed at p \u0026lt; 0.05 significance, and alpha specificity and beta-fidelity values of 0.75 to identify indicator taxa for each settlement category per coral species. Indicator species values consider both site fidelity and specificity scores to assign a single indicator score between 1 (an ASV that is found in every sample within a specific settlement level and only that specific settlement level) and 0 (an ASV that is not exclusive or persistent amongst samples in a certain settlement level).\u003c/p\u003e\u003cp\u003eDifferential abundance was calculated using the ancombc2() function from the ANCOM-BC package (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), which models the microbiome data with a linear regression framework in log-scale and reports significant log fold changes (LFC) between sample groups. The p-value was adjusted with the false discovery rate method (FDR), taxon proportion filters were set to zero (prv_cut = 0) since data was pre-filtered, and the parameter “Pairwise” was set to TRUE to account for pairwise comparisons between all settlement levels. Significant log-fold changes at the ASV level between high and low settlement-inducing CCA species were visualised for each coral assay with a bar plot using the package ggplot2 (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCorrelations between ASV abundance and coral settlement values were also analysed using multivariate linear models (LM) with the R package Maaslin2 (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Models were run for each coral separately and microbial data (post-filtering at 0.01% minimum abundance and 0.1% minimum prevalence) was log-transformed and normalised with total-sum scaling. CCA host was considered a random effect, and the continuous percent settlement score was used as a fixed effect.\u003c/p\u003e\u003cp\u003eA Random Forest (RF) analysis that uses Breiman’s random forest algorithm was conducted for each coral to identify ASVs with the highest predictive ability for coral settlement with the randomForest package (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). ASVs with significant prediction model importance values (p \u0026lt; 0.05) were kept if the ASV also had significant results in LM, indicator species and/or differential abundance analyses.\u003c/p\u003e\n\u003ch3\u003eData visualisation\u003c/h3\u003e\n\u003cp\u003eCoral larval settlement per CCA treatment were visualised with box plots in ggplot2 (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e) for each coral and significant Maaslin2 LM results were shown in a heatmap using pheatmap (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Corals with LM results that overlapped with other analyses (e.g. indicator species, differential abundance, RF) were further visualised and the relative abundance of these ASVs per CCA treatment were graphed with ggplot bar charts and bubble plots, respectively (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). For each coral species, ASVs were further investigated if they were identified as being significantly correlated with settlement (p \u0026lt; 0.05) in the LM analysis and were also differentially abundant (ANCOM-BC), an indicator for high/low settlement (Indicspecies) and/or significant RF model importance values. LM coefficient score, log fold change, indicator, and RF model importance values for each ASV of interest were visualised with bar plots and the relative abundances of the ASVs across CCA samples were presented using bubble plots in ggplot2 (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). CCA samples that did not contain any of the ASVs of interest were removed from the bubble plot.\u003c/p\u003e"},{"header":"Results \u0026 Discussion","content":"\u003cp\u003eTo investigate the potential role of crustose coralline algae (CCA) microorganisms in coral larval settlement, this study interrogated the microbiomes of 15 CCA species that elicited varying settlement responses for 14 Great Barrier Reef (GBR) coral species. We found that although CCA microbiomes were distinct and species-specific, there was also minor microbial compositional variation within CCA species. Importantly, differences within CCA species microbiomes reflected differences in coral larval settlement responses, with individual microbial taxa identified as settlement inducing or inhibiting.\u003c/p\u003e\u003ch2\u003eMicrobiomes are distinct across CCA species and coral larval settlement response\u003c/h2\u003e\u003cp\u003eCCA microbial communities were distinct from the surrounding seawater and coral larvae (PERMANOVA: F = 7.16, p \u0026lt; 0.001; Table S5), and they also differed between CCA species at the amplicon sequence variant (ASV) level. Previous research has shown that CCAs host species-specific microbial community communities (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)(Turnlund \u003cem\u003eet al.\u003c/em\u003e in review), and our results highlight that this pattern persists in aquaria after collection from the field (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; see Table S6 for full PERMANOVA results). CCA species shared similar microbial orders, such as \u003cem\u003eRhodobacterales, Flavobacteriales, Pirellulales, Rhizobiales\u003c/em\u003e, and \u003cem\u003eAltermonadales\u003c/em\u003e, consistent with previous reports of CCA microbiomes (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSettlement responses of coral larvae varied both across and within CCA species (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). To investigate whether this variation was driven by the CCA microbiome, we analysed differences in the composition of CCA microbiomes across levels of larval settlement for each coral species. CCA microbial communities mostly grouped according to CCA species, with some CCA species and some samples within CCA species promoting higher settlement than others (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; see Table S6 for full PERMANOVA results). For example, when comparing high and low settlement groups across CCA species, there was a significant difference between microbial communities associated with high versus low settlement for every coral tested, except for \u003cem\u003eF. fungites, P. daedalea\u003c/em\u003e, and \u003cem\u003eP. lobata\u003c/em\u003e (Table S7). It is still unclear whether coral larval settlement cues originate from the CCA host, their epiphytic microbial communities, or a combination of both. However, since CCAs associated with low settlement had significantly different microbial communities than CCAs associated with high settlement, there may be a microbial settlement cue for most of the corals tested here. Where no significant difference was observed between inductive and non-inductive CCA microbiomes, abiotic or host derived cues may explain the patterns found in coral settlement instead (\u003cem\u003eF. fungites, P. daedalea\u003c/em\u003e, and \u003cem\u003eP. lobata\u003c/em\u003e; Table S7).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGómez-Lemos, Doropoulos (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e) found that \u003cem\u003eTitanoderma tessellatum\u003c/em\u003e chemistry had a stronger effect on \u003cem\u003eAcropora millepora\u003c/em\u003e settlement than \u003cem\u003eT. tessellatum\u003c/em\u003e surface microbial communities and the microbial communities were only inductive in the presence of algal dissolved organic carbon (DOC). In our study, \u003cem\u003eT.\u003c/em\u003e cf. \u003cem\u003etessellatum\u003c/em\u003e elicited differing settlement responses per coral species (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Interestingly, for some corals (i.e. \u003cem\u003eC. aspera, E. aspera, L. corymbosa\u003c/em\u003e, and \u003cem\u003eM. aequituberculata\u003c/em\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), there was a significant difference between microbial communities associated with high and low settlement, suggesting potential involvement of the microbiome. On the contrary, such differences in microbiome composition were not observed for \u003cem\u003eA. millepora\u003c/em\u003e settlement, aligning with the findings of Gómez-Lemos, Doropoulos (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Meanwhile, Giorgi, Monti (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) administered a range of antibiotics to CCA surfaces to differentiate host and microbial cue responses for \u003cem\u003eOrbicella faveolata\u003c/em\u003e, and found that larval settlement increased with antibiotic treatment for some CCA species (likely a host originated cue paired with the decrease of a microbial inhibitor), but decreased settlement for other CCA species (likely a microbial cue). Therefore, the origin of these cues (host vs microbial vs a combination of both) are likely coral species specific and cannot be generalised (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). While our findings suggest involvement of the CCA microbiome for some coral species, additional experiments are required to fully untangle the contributions of microorganisms, CCA host, and chemicals produced.\u003c/p\u003e\u003ch2\u003eSpecific ASVs associate with high or low coral larval settlement\u003c/h2\u003e\u003cp\u003eMultiple metrics were used to identify ASVs associated with high or low coral settlement, including (linear models (LM), differential abundance (DA) analysis, indicator species (IA), and random forest (RF) analysis). All analysis was done at the ASV level but are taxonomically classified to the most specific level available. ASVs were considered associated with a specific coral larval settlement level if they were identified by at least two of these metrics for higher confidence. This allowed us to narrow down potential microbial inducers or inhibitors and compare their presence and relative abundance across CCA species. Overall, out of the 66,408 ASVs present in the entire dataset, 96 ASVs correlated with high coral settlement and 254 ASVs correlated with low settlement, with specific ASVs associated with high or low settlement for most coral species (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Specifically, we identified a group of coral species that displayed similar groups of ASVs correlated with high or low coral settlement (\u003cem\u003eM. elephantotus, L. corymbosa, E. aspera, D. favus\u003c/em\u003e, and \u003cem\u003eP. sinensis\u003c/em\u003e: herein referred to as ‘Group A corals’ as first defined by Abdul Wahab, Ferguson (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)) (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These corals were previously identified to have similar selective CCA settlement preferences (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), while a second group identified by Abdul Wahab, Ferguson (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) (\u003cem\u003eA. tenuis\u003c/em\u003e, \u003cem\u003eP. daedalea, C. furcata\u003c/em\u003e, and \u003cem\u003eP. lobata\u003c/em\u003e: herein referred to as ‘Group B corals’) did not share similar ASVs correlated with high or low settlement (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor generalist coral larvae (i.e., larvae that do not show a strong preference for the CCA species they settle on), like Group B corals and to a lesser extent \u003cem\u003eAcropora hyacinthus\u003c/em\u003e, there were less settlement-associated ASVs identified compared to corals with selective settlement preferences (i.e., larvae that only settle on a few specific CCA species), like Group A corals (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Specifically, we found that Group A corals shared common ASVs associated with high or low settlement, however three ASVs from genera \u003cem\u003eFodinicurvata\u003c/em\u003e, \u003cem\u003ePegibius\u003c/em\u003e and \u003cem\u003eLewinella\u003c/em\u003e elicited different responses across different species of corals (e.g. \u003cem\u003eFodinicurvata\u003c/em\u003e was associated with high \u003cem\u003eE. aspera\u003c/em\u003e, but low \u003cem\u003eP. sinensis\u003c/em\u003e settlement; \u003cem\u003ePegibius\u003c/em\u003e was associated with high \u003cem\u003eP. sinensis\u003c/em\u003e, but low \u003cem\u003eL. corymbose\u003c/em\u003e settlement; \u003cem\u003eLewinella\u003c/em\u003e was associated with high \u003cem\u003eP. sinensis\u003c/em\u003e, but low \u003cem\u003eE. aspera\u003c/em\u003e settlement; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This coral species specificity at the ASV level highlights the importance of identifying potential inductive microbial taxa at the lowest taxonomic level possible. Notably, these microbial associations were less clear when communities were considered at broader levels, whereby taxonomic families may comprise both inducing and inhibiting ASVs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For the remaining coral species not included in Groups A or B, our analyses were able to identify only a few or no ASVs associated with high settlement (see Supplementary Information). This suggests that larvae of these corals are either selectively responding to CCA host derived cues, settlement cues originating from other symbionts and/or not settling in response to microbial and/or host inhibitory cues.\u003c/p\u003e\u003ch2\u003eShared taxa correlated with high settlement\u003c/h2\u003e\u003cp\u003eAmongst group A corals, \u003cem\u003eD. favus\u003c/em\u003e and \u003cem\u003eP sinensis\u003c/em\u003e shared the highest number of ASVs associated with high larval settlement, while \u003cem\u003eL. corymbosa\u003c/em\u003e had lowest overlap (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In contrast, a study testing the settlement responses of similar coral species (\u003cem\u003eD. favus\u003c/em\u003e, \u003cem\u003eE. aspera\u003c/em\u003e, \u003cem\u003eL. corymbosa\u003c/em\u003e, \u003cem\u003eP. lobata\u003c/em\u003e, and \u003cem\u003eP. sinensis\u003c/em\u003e) to microbial biofilms found little overlap in ASVs correlating with high settlement between corals overall (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). This may reflect differences in microbial habitat niches available on CCA versus abiotic substrates (e.g., microbial biofilms), whereby inductive microorganisms may first need resources provided by the CCA host to successfully colonise, increase their settlement cue potency with the presence of algal DOC (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e), and/or the corals are settling better in response to presence the CCA host themselves.\u003c/p\u003e\u003cp\u003eDespite the numerous ASVs associated with high settlement shared amongst the group A corals, only one \u003cem\u003eFilomicrobium\u003c/em\u003e ASV was associated with high settlement between all of them (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This \u003cem\u003eFilomicrobium\u003c/em\u003e ASV was associated with high settlement from LM analysis and was additionally found to have higher differential abundance (DA) in high settlement compared to low settlement samples of \u003cem\u003eD. favus\u003c/em\u003e (Log Fold Change (LFC): 2.10 ± 0.44), \u003cem\u003eE. aspera\u003c/em\u003e (LFC: 2.03 ± 0.54), and \u003cem\u003eP. sinensis\u003c/em\u003e (LCF: 2.10 ± 0.44). \u003cem\u003eFilomicrobium\u003c/em\u003e has been previously identified in microbiomes of healthy \u003cem\u003eGalaxea fascicularis\u003c/em\u003e and \u003cem\u003ePorites pukoensis\u003c/em\u003e corals (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), brown algae \u003cem\u003eCystoseira compressa\u003c/em\u003e (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e), and green seaweed \u003cem\u003eHalimeda opuntia\u003c/em\u003e (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e) and was found in multiple CCA species characterised in this study. Therefore, this microorganism may be linked to algae-host symbiosis and indicative of healthy algae (free of disease), which could be a better suited settlement substrate that produced more inductive compounds than diseased algae.\u003c/p\u003e\u003cp\u003eThe other ASVs associated with high settlement of Group A corals were shared across a combination of species (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For example, one \u003cem\u003eCandidatus Nitrosopumilus\u003c/em\u003e ASV was shared amongst all corals except \u003cem\u003eL. corymbosa\u003c/em\u003e for LM analysis and was also a high settlement indicator for \u003cem\u003eD. favus\u003c/em\u003e (Indicator species value (ISV): 0.57) and \u003cem\u003eP. sinensis\u003c/em\u003e settlement (ISV: 0.69) (Table S8). A second \u003cem\u003eCa. Nitrosopumilus\u003c/em\u003e ASV was shared amongst \u003cem\u003eD. favus\u003c/em\u003e, \u003cem\u003eM. elephantotus\u003c/em\u003e, and \u003cem\u003eP. sinensis\u003c/em\u003e for LM analysis, and showed significantly higher relative abundance in high settlement \u003cem\u003eD. favus\u003c/em\u003e (LFC: 1.43 ± 0.48) and \u003cem\u003eP. sinensis\u003c/em\u003e (LFC: 1.43 ± 0.48) samples (Table S8). \u003cem\u003eNitrosopumilus\u003c/em\u003e is an ammonia-oxidizing bacteria commonly found in sponges (\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e–\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Certain members have been shown to produce nitric oxide (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e), a key signalling molecule for marine invertebrate larval settlement (\u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e–\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Future research should explore the role of nitric oxide by \u003cem\u003eNitrosopumilus\u003c/em\u003e sp. in regulating coral larval settlement.\u003c/p\u003e\u003cp\u003eIn addition, two \u003cem\u003eNeptuniibacter\u003c/em\u003e ASVs also correlated with high Group A coral settlement for LM analysis. One \u003cem\u003eNeptuniibacter\u003c/em\u003e ASV was more differentially abundant in high settlement \u003cem\u003eG. favulus\u003c/em\u003e (LFC: 0.44 ± 0.12), \u003cem\u003eM. elephantotus\u003c/em\u003e (LFC: 0.26 ± 0.08), and \u003cem\u003eP. sinensis\u003c/em\u003e (LFC 0.10 ± 0.03) samples compared to low settlement samples, and the other was more differentially abundant in \u003cem\u003eL. corymbosa\u003c/em\u003e (0.18 ± 0.07) and \u003cem\u003eM. elephantotus\u003c/em\u003e (0.17 ± 0.07) (Table S8). \u003cem\u003eNeptuniibacter\u003c/em\u003e also correlated with \u003cem\u003eAcropora millepora\u003c/em\u003e settlement on mixed-species CCA microbial biofilms (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This genus has also been previously associated with microbiomes of the CCA species \u003cem\u003eP. onkodes\u003c/em\u003e (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e), green algae (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e), and \u003cem\u003eMussisimilia\u003c/em\u003e corals (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e). Furthermore, \u003cem\u003eNeptuniibacter\u003c/em\u003e was found enriched in macroalgae that induced settlement of the coral \u003cem\u003ePocillopora damicornis\u003c/em\u003e (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). The \u003cem\u003eNeptuniibacter\u003c/em\u003e ASVs that correlated with high settlement were present in every CCA species tested, including \u003cem\u003eAmphiroa foliacea\u003c/em\u003e samples at lower relative abundances, which elicited little to no settlement from any coral (Figures S3-S15). Therefore, if a settlement response is initiated by \u003cem\u003eNeptuniibacter\u003c/em\u003e, it is likely concentration dependent, reliant on the presence of other microorganisms in a mixed-biofilm community and/or coupled to a host-derived cue. Overall, ASVs identified from high settlement samples with LM analysis that were shared amongst Group A corals were found across multiple CCA species. This suggests these corals are responding to a microbial signal present across the different CCA species, yet further testing is required to confirm this hypothesis.\u003c/p\u003e\u003ch2\u003eShared taxa correlated with low settlement\u003c/h2\u003e\u003cp\u003eSimilar to identifying ASVs associated with high settlement, LM results were also used to compare ASVs associated with low settlement (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Within Group A corals, \u003cem\u003eD. favus\u003c/em\u003e and \u003cem\u003eE. aspera\u003c/em\u003e shared the greatest number of ASVs associated with low settlement from LM analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), and these mostly belonged to Planctomycetes, like \u003cem\u003ePir4\u003c/em\u003e and \u003cem\u003eOM190\u003c/em\u003e lineages, and \u003cem\u003eFlavobacteriaceae\u003c/em\u003e (Table S8). Microbes belonging to either of these groups are commonly associated with different types of algae (\u003cspan additionalcitationids=\"CR75 CR76\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e–\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e) and have been shown to degrade polysaccharides in algal cell walls (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). While there were no ASVs associated with low settlement that were shared across all Group A corals, a \u003cem\u003eFlavobacteriaceae\u003c/em\u003e ASV belonging to the genus \u003cem\u003eWinogradskeylla\u003c/em\u003e was correlated with low settlement for three coral species within Group A corals: \u003cem\u003eD. favus\u003c/em\u003e (LFC: -0.98 ± 0.31), \u003cem\u003eM. elephantotus\u003c/em\u003e (LFC: -1.40 ± 0.40), and \u003cem\u003eP. sinensis\u003c/em\u003e (LFC: -1.0 + 0.31) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; Table S8). This genus was previously identified in diseased coral (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e) and alga microbiomes (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). It also has reported biocidal activity by producing poly-ethers that inhibited barnacle \u003cem\u003eBalanus amphitrite\u003c/em\u003e (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e) and \u003cem\u003eHydroides elegans\u003c/em\u003e settlement (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). Furthermore, \u003cem\u003eWinogradskeylla\u003c/em\u003e also correlated with low \u003cem\u003eP. sinensis\u003c/em\u003e settlement from microbial biofilms, suggesting that even separated from the CCA host, this microorganism may inhibit \u003cem\u003eP. sinensis\u003c/em\u003e settlement (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWithin the phylum Planctomycetes, ASVs belonging to the \u003cem\u003ePir4\u003c/em\u003e and \u003cem\u003eOM190\u003c/em\u003e lineages and the genus \u003cem\u003eBlastopirellula\u003c/em\u003e were correlated with low settlement from LM analysis. The specific ASVs varied depending on the combinations of group A corals that they were associated with (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For example, low settlement in \u003cem\u003eM. elephantotus\u003c/em\u003e and \u003cem\u003eP. sinensis\u003c/em\u003e was associated with a \u003cem\u003ePir4\u003c/em\u003e lineage ASV, while three \u003cem\u003eOM190\u003c/em\u003e ASVs were correlated with low settlement in \u003cem\u003eL. corymbosa\u003c/em\u003e and \u003cem\u003eM. elephantotus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Furthermore, the genus \u003cem\u003eBlastopirellula\u003c/em\u003e was associated with low settlement across five corals; with three \u003cem\u003eBlastopirellula\u003c/em\u003e ASVs each linked to low settlement in a different pair of coral species: \u003cem\u003eL. corymbosa\u003c/em\u003e and \u003cem\u003eM. elephantotus\u003c/em\u003e, \u003cem\u003eD. favus\u003c/em\u003e and \u003cem\u003eE. aspera\u003c/em\u003e, and \u003cem\u003eE. aspera\u003c/em\u003e and \u003cem\u003eP. sinensis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In contrast, \u003cem\u003ePir4\u003c/em\u003e lineage and \u003cem\u003eBlastopirellula\u003c/em\u003e were associated with high \u003cem\u003eP. sinensis\u003c/em\u003e and \u003cem\u003eP. lobata\u003c/em\u003e settlement in response to microbial biofilms (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), suggesting that the settlement effect of these microorganisms may differ when paired with the CCA host. For example, the CCA host might be counteracting the settlement inducing ability of the microbes resulting in different coral larval settlement responses. These lineages are commonly found within algal microbiomes (\u003cspan additionalcitationids=\"CR76\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e–\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e) and members of the phylum Planctomycetes have been associated with algal dysbiosis (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e) and antibiotic resistance (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan additionalcitationids=\"CR87 CR88\" citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e–\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e). Biocidals produced by some members of the phylum Planctomycetes could directly curb colonisation of settlement-inducing microbes and/or shape the microbial community to deter larval settlement. Furthermore, Planctomycetes ASVs were mostly found in CCA occupying mid-high light habitats, i.e., \u003cem\u003eA.\u003c/em\u003e cf. \u003cem\u003efoliacea\u003c/em\u003e, that elicited very low settlement responses overall. Abdul Wahab, Ferguson (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) suggested that corals adapted to certain light habitats were induced by CCA found within similar habitat light conditions, with Group A coral species preferring CCA more adapted to mid-low light habitats. This preference could be reflected in the microbiomes between the different CCAs, as settlement of Group A corals largely negatively correlated with ASVs unique to high-light habitat CCAs (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e; Figure S6; S7; S10; S12; S14). For example, low settlement ASVs were frequently found in low settlement samples of CCA found in high-light conditions (i.e., \u003cem\u003eP. onkodes\u003c/em\u003e, \u003cem\u003eL.\u003c/em\u003e cf. \u003cem\u003epygmaeum\u003c/em\u003e and \u003cem\u003eA.\u003c/em\u003e cf. \u003cem\u003efoliacea\u003c/em\u003e) for each Group A coral species. \u003cem\u003eA. cf. foliacea\u003c/em\u003e is a branched, nongeniculate coralline alga that induces weak settlement responses for a wide diversity of GBR coral species (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), despite the presence of microbial taxa that correlate with high settlement. While this could be attributed to the presence of microbial inhibitors that may have a stronger inhibitory effect than the inductive microbes, it may also be attributed to the host algae itself, and/or biochemicals released potentially have a strong inhibitory effect. Therefore, further work is required to confirm whether the \u003cem\u003eBlastopirellula\u003c/em\u003e, \u003cem\u003eOM190\u003c/em\u003e, and \u003cem\u003ePir4\u003c/em\u003e lineage ASVs or a habitat-specific abiotic or host cue is responsible for the inhibitory effect.\u003c/p\u003e\u003cp\u003eMost corals in this study had more ASVs correlated with low than high larval settlement levels and this were shared across a variety of CCA species. This trend is largely consistent with previous coral larval settlement studies (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e). For example, \u003cem\u003eLewinella\u003c/em\u003e (Saprospiraceae) was correlated with low \u003cem\u003eM. aequituberculata\u003c/em\u003e and \u003cem\u003eD. favus\u003c/em\u003e settlement (Table S8) in this study and was also found to negatively correlate with \u003cem\u003eA. tenuis\u003c/em\u003e coral settlement by Padayhag, Nada (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e). In addition, members of \u003cem\u003ePlanctomycetes\u003c/em\u003e and Rhizobiaceae were associated with low \u003cem\u003eC. furcata, M. elephantotus, D. favus, C. aspera, L. corymbosa\u003c/em\u003e and \u003cem\u003eP. sinensis\u003c/em\u003e settlement (Table S8) and were also found to correlate with low \u003cem\u003eA. tenuis\u003c/em\u003e (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e) and \u003cem\u003eP. damicornis\u003c/em\u003e coral settlement (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e), respectively. It has been postulated that \u003cem\u003eRhizobiaceae\u003c/em\u003e encourages macroalgae growth through enriched nitrogen fixation (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e). \u003cem\u003eRhizobiaceae\u003c/em\u003e has also been found associated with coral disease (\u003cspan additionalcitationids=\"CR93\" citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e–\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e) and bleaching (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e), and has been assumed to be detrimental to larval settlement (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). Although several taxa from the phylum Planctomycetes, such as Pir4 lineage and \u003cem\u003eBlastopirellula\u003c/em\u003e, and the family \u003cem\u003eFlavobacteriaceae\u003c/em\u003e, like \u003cem\u003eWinogradskeylla\u003c/em\u003e, correlated with low coral settlement, these ASVs were unique to CCA with overall low settlement (\u003cem\u003eA.\u003c/em\u003e cf. \u003cem\u003efoliacea\u003c/em\u003e). This shows that CCA species with low coral settlement response often host microbial taxa that are not found in settlement-inducing CCA. Further research remains warranted to establish whether the apparent inhibitory effect is due to a specific microbial cue or the CCA host.\u003c/p\u003e\u003ch2\u003eMicrobial taxonomic families elicit differing coral larval responses depending on the coral species\u003c/h2\u003e\u003cp\u003eWithin a single microbial family, some ASVs were identified as inducers while others were potential inhibitors, depending on the coral species, further highlighting the complexity of settlement responses. For example, one \u003cem\u003eTenacibaculum\u003c/em\u003e (Flavobacteriaceae) ASV was associated with high settlement of \u003cem\u003eA. tenuis\u003c/em\u003e (ISV: 0.793) and was found in every single CCA species tested, with higher relative abundance in \u003cem\u003eL. insipidium\u003c/em\u003e and \u003cem\u003ePorolithon\u003c/em\u003e sp.2 samples (Figure S3). \u003cem\u003eTenacibaculum\u003c/em\u003e has previously been postulated to influence larval settlement of the coral \u003cem\u003eP. damicornis\u003c/em\u003e (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e) and the health of \u003cem\u003eTubastraea coccinea\u003c/em\u003e (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e). However, in this study, this same ASV was also associated with low \u003cem\u003eD. favus\u003c/em\u003e settlement (LMC: -0.61 0.22). \u003cem\u003eTenacibaculum\u003c/em\u003e and one unassigned Flavobacteriaceae were the only Flavobacteriaceae ASVs correlated with high settlement (for \u003cem\u003eA. tenuis\u003c/em\u003e and \u003cem\u003eC. aspera\u003c/em\u003e, respectively; Table S8), with the rest of the Flavobacteriaceae ASVs identified (\u003cem\u003eAquimarina, Flagellimonas\u003c/em\u003e, and \u003cem\u003eMaribacter\u003c/em\u003e) correlating with low coral larval settlement (Table S8). Certain isolates of Flavobacteriaceae have also been associated with low settlement of mussels (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e) and high settlement of the corals \u003cem\u003eA. microphthalma\u003c/em\u003e (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e), \u003cem\u003eP. sinensis, E. aspera\u003c/em\u003e, and \u003cem\u003eP. lobata\u003c/em\u003e (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Similar results were found for a \u003cem\u003eGranulosicoccus\u003c/em\u003e ASV, which correlated with high \u003cem\u003eP. daedalea\u003c/em\u003e settlement (LM Coefficient: 0.35 0.11), but also low \u003cem\u003eC. furcata\u003c/em\u003e (LMC: -0.58 0.10; LFC: -1.78 0.45; IVC: 0.755) and \u003cem\u003eM. elephantotus\u003c/em\u003e (LFC: -1.64 0.4; IVC: 0.757) settlement. \u003cem\u003eGranulosicoccus\u003c/em\u003e have previously been found in biofilms that elicited high larval settlement in coral \u003cem\u003eA. tenuis\u003c/em\u003e (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), but a mixed settlement response between \u003cem\u003eP. daedalea, C. furcata\u003c/em\u003e, and \u003cem\u003eM. elephantotus\u003c/em\u003e (corals belonging to the \u003cem\u003eMerulinidae\u003c/em\u003e family), suggesting that microbial cues vary within coral families, are species-specific, and that microbial taxonomy at the family and even genus level does not necessarily reveal the inductive capacity of a microbe.\u003c/p\u003e\u003cp\u003eRhodobacteraceae is another taxonomic family that has previously been associated with both high and low levels of coral larval settlement (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e). In this study, ASVs belonging to Rhodobacteraceae were correlated with low settlement in \u003cem\u003eC. furcata, M. aequituberculata, C. aspera, A. hyacinthus, D. favus\u003c/em\u003e and \u003cem\u003eP. sinensis\u003c/em\u003e, but they differed amongst microbial genera and correlation strength across coral species (Table S8). In particular, the two unassigned Rhodobacteraceae ASVs associated with low \u003cem\u003eC. aspera\u003c/em\u003e settlement were found in at least one sample for every CCA across a range of settlement, but were particularly abundant in low settlement samples, especially in \u003cem\u003eL. proliferum\u003c/em\u003e (Figures S4). However, it is also possible that these unassigned Rhodobacteraceae ASVs are not necessarily a low settlement inhibitor, as they were also present in lower abundances in a few high settlement samples, but co-occur with other microbial inhibitors in a low settlement community that is in the middle of succession to resemble a microbial community that induces more settlement. Turnlund, Vanwonterghem (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) suggested that Rhodobacteraceae may be an important microorganism for biofilm community succession to change from a low to high settlement inducing biofilm; however, since our data represents one time point, we cannot determine if the presence of \u003cem\u003eRhodobacteraceae\u003c/em\u003e would alter the present microbial community overtime to create niches for microbial inducers.\u003c/p\u003e"},{"header":"Conclusion and future directions","content":"\u003cp\u003eSpecific microorganisms associated with high or low larval settlement were identified for 14 different GBR coral species. These putative inducers and inhibitors belonged to a diverse range of microbial taxa and represent important targets for future research to distinguish the role of the algal-host versus microbiome. Further, these taxa can be tested in validation experiments using isolated mono- or mixed-species biofilms or through manipulation of CCA microbiomes by enriching potential inducers or lowering inhibitor abundance. Building on these findings, we also suggest that future research focus on the functional characterisation of the CCA microbiome to better interrogate whether common functions or biochemical pathways, rather than taxa, are the source of microbial settlement cues. While coral larvae are responding to different combinations of microbial taxa, these may represent complementary functional pathways that trigger larval settlement. The identification of microbial inducers and inhibitors for larval settlement is critically important for our understanding of coral settlement behaviour, which would in turn inform recruitment and coral populations dynamics as microbial communities shifts under anthropogenic stressors such as human-induced climate change (\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e). Furthermore, this study significantly adds to our knowledge and capability to guide the development of attractive substrates for coral larval settlement to optimise large-scale reef restoration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the conclusions of this article are available in the NCBI Sequence Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra) under the BioProject accession number PRJNA1100425.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Australian Government Research Training Program, UQ Graduate school, and the Reef Restoration and Adaptation Program, which aims to develop effective interventions to help the Reef resist, adapt and recover from the impacts of climate change, and which is funded by the partnership between the Australian Governments Reef Trust and the Great Barrier Reef Foundation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eACT was responsible for conceptualization, writing the original draft, and formal analysis. PB, LR, NW, ML, and IV were responsible for conceptualization, and formal analysis. SF, GD-P, MAW was responsible for investigation. All authors edited and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge and pay our respects to the Manbarra, Bindal, Wulgurukaba and Turrbal people, the Traditional Custodians of the land and sea country on which this research was performed on. We also thank Lesa Peplow and Sara Bell for their help in teaching the DNA extraction method and shipping the samples, and the RRAP CAD1 team for their work in collecting CCA.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHughes TP, et al. Ecological memory modifies the cumulative impact of recurrent climate extremes. Nat Clim Change. 2019;9(1):40\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePratchett MS, et al. \u003cem\u003eRecurrent mass-bleaching and the potential for ecosystem collapse on Australia\u0026rsquo;s Great Barrier Reef\u003c/em\u003e, in \u003cem\u003eEcosystem Collapse and Climate Change\u003c/em\u003e. Springer; 2021. pp. 265\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRandall CJ, Szmant AM. Elevated temperature affects development, survivorship, and settlement of the elkhorn coral, Acropora palmata (Lamarck 1816). Biol Bull. 2009;217(3):269\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJorissen H, et al. High CO2 inhibits substratum exploration and settlement of coral larvae. Mar Ecol Prog Ser. 2022;689:47\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSarribouette L, et al. Post-settlement demographics of reef building corals suggest prolonged recruitment bottlenecks. Oecologia. 2022;199(2):387\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnthony KRN, Connolly SR. Environmental limits to growth: Physiological niche boundaries of corals along turbidity\u0026ndash;light gradients. Oecologia. 2004;141:373\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbdul Wahab M, et al. Hierarchical settlement behaviours of coral larvae to common coralline algae. Sci Rep. 2023;13(1):5795.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNozawa Y. Micro-crevice structure enhances coral spat survivorship. J Exp Mar Biol Ecol. 2008;367(2):127\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDoropoulos C, et al. Characterizing the ecological trade-offs throughout the early ontogeny of coral recruitment. Ecol Monogr. 2016;86(1):20\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVermeij MJA, et al. Coral larvae move toward reef sounds. PLoS ONE. 2010;5(5):e10660.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMason B, Beard M, Miller MW. Coral larvae settle at a higher frequency on red surfaces. Coral Reefs. 2011;30(3):667\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStrader ME, Davies SW, Matz MV. Differential responses of coral larvae to the colour of ambient light guide them to suitable settlement microhabitat. R Soc Open Sci. 2015;2(10):150358.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoster T, Gilmour JP. Seeing red: Coral larvae are attracted to healthy\u0026ndash;looking reefs. Mar Ecol Prog Ser. 2016;559:65\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePetersen LE, et al. Photosensitivity of the bacterial pigment cycloprodigiosin enables settlement in coral larvae\u0026ndash;light as an understudied environmental factor. Front Mar Sci. 2021;8:1599.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoeller M, Nietzer S, Schupp PJ. Neuroactive compounds induce larval settlement in the scleractinian coral Leptastrea purpurea. Sci Rep. 2019;9(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWhitman TN, et al. Settlement of larvae from four families of corals in response to a crustose coralline alga and its biochemical morphogens. Sci Rep. 2020;10(1):16397.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilva PC, Johansen HW. A reappraisal of the order Corallinales (Rhodophyceae). Br Phycol J. 1986;21(3):245\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLittler MM, Littler DS. The nature of crustose coralline algae and their interactions on reefs. Smithson Contrib Mar Sci. 2013;39:199\u0026ndash;212.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSneed JM, Ritson-Williams R, Paul VJ. Crustose coralline algal species host distinct bacterial assemblages on their surfaces. ISME J. 2015;9(11):2527\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarrington L, et al. Recognition and selection of settlement substrata determine post-settlement survival in corals. Ecol. 2004;85(12):3428\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrice N. Habitat selection, facilitation, and biotic settlement cues affect distribution and performance of coral recruits in French Polynesia. Oecologia. 2010;163(3):747\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRitson-Williams R, et al. Larval settlement preferences of Acropora palmata and Montastraea faveolata in response to diverse red algae. Coral Reefs. 2014;33:59\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRitson-Williams R, Arnold SN, Paul VJ. Patterns of larval settlement preferences and post\u0026ndash;settlement survival for seven Caribbean corals. Mar Ecol Prog Ser. 2016;548:127\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJorissen H, et al. Coral larval settlement preferences linked to crustose coralline algae with distinct chemical and microbial signatures. Sci Rep. 2021;11(1):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eErwin PM, Song B, Szmant AM. \u003cem\u003eSettlement behavior of Acropora palmata planulae: Effects of biofilm age and crustose coralline algal cover\u003c/em\u003e. in \u003cem\u003eProceedings of the 11th International Coral Reef Symposium\u003c/em\u003e 2008. Ft. Lauderdale, Florida.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSiboni N, et al. Crustose coralline algae that promote coral larval settlement harbor distinct surface bacterial communities. Coral Reefs. 2020;39(6):1703\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJohnson CR, Muir DG, Reysenbach AL. Characteristic bacteria associated with surfaces of coralline algae: A hypothesis for bacterial induction of marine invertebrate larvae. Mar Ecol Prog Ser. 1991;74:281\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRitson-Williams R, et al. Larval settlement preferences and post-settlement survival of the threatened Caribbean corals Acropora palmata and A. cervicornis. Coral Reefs. 2010;29(1):71\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSiboni N, et al. Using bacterial extract along with differential gene expression in Acropora millepora larvae to decouple the processes of attachment and metamorphosis. PLoS ONE. 2012;7(5):e37774.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSneed JM, et al. The chemical cue tetrabromopyrrole from a biofilm bacterium induces settlement of multiple Caribbean corals. Proc R Soc B-Biol Sci. 2014;281(1786):20133086.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTebben J, et al. Induction of larval metamorphosis of the coral Acropora millepora by tetrabromopyrrole isolated from a Pseudoalteromonas bacterium. PLoS ONE. 2011;6(4):e19082.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePetersen LE, et al. Photodegradation of a bacterial pigment and resulting hydrogen peroxide release enable coral settlement. Sci Rep. 2023;13(1):3562.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNielsen SJ, Harder T, Steinberg PD. Sea urchin larvae decipher the epiphytic bacterial community composition when selecting sites for attachment and metamorphosis. FEMS Microbiol Ecol. 2015;91(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTran C, Hadfield MG. Larvae of Pocillopora damicornis (Anthozoa) settle and metamorphose in response to surface-biofilm bacteria. Mar Ecol Prog Ser. 2011;433:85\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSneed JM et al. Coral settlement induction by tetrabromopyrrole is widespread among Caribbean corals and compound specific. Front Mar Sci, 2024. 10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJohnson CR, Sutton DC. Bacteria on the surface of crustose coralline algae induce metamorphosis of the crown-of-thorns starfish Acanthaster planci. Mar Biol. 1994;120(2):305\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNegri AP, et al. Metamorphosis of broadcast spawning corals in response to bacteria isolated from crustose algae. Mar Ecol Prog Ser. 2001;223:121\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNielsen S. \u003cem\u003eBacteria on coralline algae and their role as sea urchin settlement cues\u003c/em\u003e, in \u003cem\u003eCentre for Marine Science and Innovation\u003c/em\u003e. 2014, UNSW Sydney.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiorgi A, et al. Larvae from three Caribbean corals settle differently in response to crustose coralline algae and their bacterial communities. Mar Ecol Prog Ser. 2024;751:53\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilson K, et al. Genetic mapping of the black tiger shrimp Penaeus monodon with amplified fragment length polymorphism. Aquac. 2002;204(3\u0026ndash;4):297\u0026ndash;309.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBott\u0026eacute; ES, et al. Changes in the metabolic potential of the sponge microbiome under ocean acidification. Nat commun. 2019;10(1):4134.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaporaso JG, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA. 2011;108:4516\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCallahan BJ, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13(7):581\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTurnlund AC, et al. Understanding the role of micro-organisms in the settlement of coral larvae through community ecology. Mar Biol. 2025;172(3):1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTurnlund AC et al. Linking differences in microbial network structure with changes in coral larval settlement. ISME Commun, 2023. 3(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOksanen J et al. \u003cem\u003eVegan: Community ecology package\u003c/em\u003e. 2019.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRStudio Team. RStudio: Integrated Development Environment for R. 2019; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rstudio.com/\u003c/span\u003e\u003cspan address=\"http://www.rstudio.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-; 2016.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eC\u0026aacute;ceres MD, Legendre P. Associations between species and groups of sites: Indices and statistical inference. Ecol. 2009;90(12):3566\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin H, Peddada SD. Analysis of compositions of microbiomes with bias correction. Nat commun. 2020;11(1):3514.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin H, Eggesb\u0026oslash; M, Peddada SD. Linear and nonlinear correlation estimators unveil undescribed taxa interactions in microbiome data. Nat commun. 2022;13(1):4946.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMallick H, et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol. 2021;17(11):e1009442.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBreiman L. Random forests. Mach Learn. 2001;45:5\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBreiman L. \u003cem\u003eManual on setting up, using, and understanding Random Foreswts V3.1\u003c/em\u003e. 2002; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.stat.berkeley.edu/~breiman/Using_random_forests_V3.1.pdf\u003c/span\u003e\u003cspan address=\"https://www.stat.berkeley.edu/~breiman/Using_random_forests_V3.1.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKolde R. \u003cem\u003epheatmap: pretty heatmaps\u003c/em\u003e. 2015.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeistertzheim AL, et al. Pathobiomes differ between two diseases affecting reef building coralline algae. Front Microbiol. 2017;8:1686.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eG\u0026oacute;mez-Lemos LA, et al. Coralline algal metabolites induce settlement and mediate the inductive effect of epiphytic microbes on coral larvae. Sci Rep. 2018;8(1):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eG\u0026oacute;mez-Lemos LA, et al. Coralline algal metabolites induce settlement and mediate the inductive effect of epiphytic microbes on coral larvae. Sci Rep. 2018;8(1):17557.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eO\u0026rsquo;Brien PA, et al. Light and dark biofilm adaptation impacts larval settlement in diverse coral species. Environ microbiome. 2025;20(1):11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu M, et al. Bacterial communities vary from different scleractinian coral species and between bleached and non-bleached corals. Microbiol Spectr. 2023;11(3):e04910\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMancuso FP, et al. Warming and nutrient enrichment can trigger seaweed loss by dysregulation of the microbiome structure and predicted function. Sci Total Environ. 2023;879:162919.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang F, et al. Calcified macroalgae and their bacterial community in relation to larval settlement and metamorphosis of reef-building coral Pocillopora damicornis. FEMS Microbiol Ecol. 2021;97(1):fiaa215.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSimister R, et al. Sponge-microbe associations survive high nutrients and temperatures. PLoS ONE. 2012;7(12):e52220.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang F, et al. Symbiotic archaea in marine sponges show stability and host specificity in community structure and ammonia oxidation functionality. FEMS Microbiol Ecol. 2014;90(3):699\u0026ndash;707.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEngelberts JP, et al. Characterization of a sponge microbiome using an integrative genome-centric approach. ISME J. 2020;14(5):1100\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartens-Habbena W, et al. The production of nitric oxide by marine ammonia‐oxidizing archaea and inhibition of archaeal ammonia oxidation by a nitric oxide scavenger. Environ Microbiol. 2015;17(7):2261\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSong H, Hewitt OH, Degnan SM. Arginine biosynthesis by a bacterial symbiont enables nitric oxide production and facilitates larval settlement in the marine-sponge host. Curr Biol. 2021;31(2):433\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCastellano I, Ercolesi E, Palumbo A. Nitric oxide affects ERK signaling through down-regulation of MAP kinase phosphatase levels during larval development of the ascidian Ciona intestinalis. PLoS ONE. 2014;9(7):e102907.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUeda N, Degnan SM. Nitric oxide is not a negative regulator of metamorphic induction in the abalone Haliotis asinina. Front Mar Sci. 2014;1:1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWebster NS, et al. Ocean acidification reduces induction of coral settlement by crustose coralline algae. Glob Chang Biol. 2013;19(1):303\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang Z, et al. High-throughput sequencing revealed differences of microbial community structure and diversity between healthy and diseased Caulerpa lentillifera. BMC Microbiol. 2019;19(1):1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Castro AP, et al. Bacterial communities associated with three Brazilian endemic reef corals (Mussismilia spp.) in a coastal reef of the Abrolhos shelf. Cont Shelf Res. 2013;70:135\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao Z, et al. Marine macroalgae and their associated bacterial communities affect larval settlement and survivorship of the coral Pocillopora damicornis. Mar Environ Res. 2024;199:106597.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumar V, et al. Multiple opportunistic pathogens can cause a bleaching disease in the red seaweed Delisea pulchra. Environ Microbiol. 2016;18(11):3962\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJames AK, et al. Giant kelp microbiome altered in the presence of epiphytes. Limnol oceanogr lett. 2020;5(5):354\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIhua MW, et al. Diversity of bacteria populations associated with different thallus regions of the brown alga Laminaria digitata. PLoS ONE. 2020;15(11):e0242675.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKopprio GA, et al. Insights into the bacterial community composition of farmed Caulerpa lentillifera: A comparison between contrasting health states. MicrobiologyOpen. 2021;10(6):e1253.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBondoso J, et al. Epiphytic Planctomycetes communities associated with three main groups of macroalgae. FEMS Microbiol Ecol. 2017;93(3):fiw255.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKrishnaswamy VG, et al. Prevalence of differential microbiome in healthy, diseased and nipped colonies of corals, Porites lutea in the Gulf of Kachchh, north-west coast of India. Environ Res. 2023;216:114622.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu Q, et al. Changes in phycospheric and environmental microbes associated with an outbreak of yellow spot disease on Pyropia yezoensis. Aquac. 2020;529:735651.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDash S, et al. Antibacterial and antilarval-settlement potential and metabolite profiles of novel sponge-associated marine bacteria. J Ind Microbiol Biotechnol. 2009;36(8):1047\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDash S, et al. Poly-ethers from Winogradskyella poriferorum: Antifouling potential, time-course study of production and natural abundance. Bioresour Technol. 2011;102(16):7532\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlmeida JR, Vasconcelos V. Natural antifouling compounds: Effectiveness in preventing invertebrate settlement and adhesion. Biotechnol Adv. 2015;33(3\u0026ndash;4):343\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStoresund JE, \u0026Oslash;vre\u0026aring;s L. Diversity of Planctomycetes in iron-hydroxide deposits from the Arctic Mid Ocean Ridge (AMOR) and description of Bythopirellula goksoyri gen. nov., sp. nov., a novel Planctomycete from deep sea iron-hydroxide deposits. Antonie Van Leeuwenhoek. 2013;104:569\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLage OM, Bondoso J. Planctomycetes and macroalgae, a striking association. Front Microbiol. 2014;5:267.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchlesner H. The development of media suitable for the microorganisms morphologically resembling Planctomyces spp., Pirellula spp., and other Planctomycetales from various aquatic habitats using dilute media. Syst Appl Microbiol. 1994;17(1):135\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCayrou C, Raoult D, Drancourt M. Broad-spectrum antibiotic resistance of Planctomycetes organisms determined by Etest. J Antimicrob Chemother. 2010;65(10):2119\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLage OM, Bondoso J. Planctomycetes diversity associated with macroalgae. FEMS Microbiol Ecol. 2011;78(2):366\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLage OM. Characterization of a Planctomycete associated with the marine dinoflagellate Prorocentrum micans Her. Antonie Van Leeuwenhoek. 2013;104(4):499\u0026ndash;508.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePadayhag BM, et al. Microbial community structure and settlement induction capacity of marine biofilms developed under varied reef conditions. Mar Pollut Bull. 2023;193:115138.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRincon-Rosales R, et al. Rhizobia with different symbiotic efficiencies nodulate Acaciella angustissima in Mexico, including Sinorhizobium chiapanecum sp. nov. which has common symbiotic genes with Sinorhizobium mexicanum. FEMS Microbiol Ecol. 2009;67(1):103\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBecker CC, et al. Microbial bioindicators of Stony Coral Tissue Loss Disease identified in corals and overlying waters using a rapid field-based sequencing approach. Environ Microbiol. 2022;24(3):1166\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeyer JL, et al. Microbial community shifts associated with the ongoing stony coral tissue loss disease outbreak on the Florida Reef Tract. Front Microbiol. 2019;10:2244.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eC\u0026aacute;rdenas A, et al. Shifts in bacterial communities of two caribbean reef-building coral species affected by white plague disease. ISME J. 2012;6(3):502\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaydon TD, et al. Rapid shifts in bacterial communities and homogeneity of Symbiodiniaceae in colonies of Pocillopora acuta transplanted between reef and mangrove environments. Front Microbiol. 2021;12:756091.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarlos C, Torres TT, Ottoboni LM. Bacterial communities and species-specific associations with the mucus of Brazilian coral species. Sci Rep. 2013;3(1):1624.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang J-L, et al. Silver nanoparticles impact biofilm communities and mussel settlement. Sci Rep. 2016;6(1):37406.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWebster NS, et al. Metamorphosis of a scleractinian coral in response to microbial biofilms. App Environ Microbiol. 2004;70(2):1213\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWebster NS, et al. Elevated seawater temperature causes a microbial shift on crustose coralline algae with implications for the recruitment of coral larvae. ISME J. 2011;5(4):759\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWebster N, et al. Host-associated coral reef microbes respond to the cumulative pressures of ocean warming and ocean acidification. Sci Rep. 2016;6(1):19324.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sigs","sideBox":"Learn more about [Environmental Microbiome](https://environmentalmicrobiome.biomedcentral.com)","snPcode":"40793","submissionUrl":"https://submission.nature.com/new-submission/40793/3","title":"Environmental Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"coral recruitment, coral larvae, crustose coralline algae, microbial communities, settlement inducer/inhibitor, 16S rRNA amplicon sequencing","lastPublishedDoi":"10.21203/rs.3.rs-7850943/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7850943/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCrustose coralline algae (CCA) enhance coral recruitment, but the response of coral larval settlement to CCA varies between CCA species. Furthermore, it is unclear whether coral larvae respond to settlement cues from the algal host itself or its associated microorganisms. To determine whether CCA-derived settlement cues have a microbial origin, we interrogated the microbiome of 14 coralline algal species and a calcareous non-coralline alga eliciting varying levels of settlement across 14 coral species from a wide diversity of families found in the Great Barrier Reef. Linear regression, differential abundance, indicator species, and random forest analyses were used to identify microbial taxa associated with high or low coral settlement. We found that the relative abundance of specific microbial amplicon sequence variants (ASVs) correlated with settlement and that these responses were largely coral species-specific. A select few microbial taxa associated with high or low settlement were shared across the corals \u003cem\u003eDipsastrea favus\u003c/em\u003e, \u003cem\u003eEchinophyllia aspera, Lobophyllia corymbosa, Mycedium elephantotus\u003c/em\u003e, and \u003cem\u003ePlatygrya sinensis\u003c/em\u003e, suggesting potential shared settlement or inhibition cues. While shared ASVs associated with high coral settlement were found across multiple CCA species, low settlement AVSs were confined to few low settlement CCA species. \u003cem\u003eCandidatus Nitrosopumilus\u003c/em\u003e and \u003cem\u003eFilomicrobium\u003c/em\u003e microbes were found as potential shared microbial inducers, and members of \u003cem\u003ePirellulaceae\u003c/em\u003e and \u003cem\u003eFlavobacteriaceae\u003c/em\u003e were identified as potential settlement inhibitors. These findings contribute to our growing knowledge of potential coral larval settlement cues and provide deeper insights into the link between the CCA microbiomes and coral recruitment.\u003c/p\u003e","manuscriptTitle":"Unravelling the role of crustose coralline algae microbiomes on coral larval settlement in the Great Barrier Reef","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 04:26:03","doi":"10.21203/rs.3.rs-7850943/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-21T13:17:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-21T13:17:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-16T11:05:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Microbiome","date":"2025-10-13T16:08:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sigs","sideBox":"Learn more about [Environmental Microbiome](https://environmentalmicrobiome.biomedcentral.com)","snPcode":"40793","submissionUrl":"https://submission.nature.com/new-submission/40793/3","title":"Environmental Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"93eb4255-5973-4b31-8bf9-6efcbddef624","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T08:38:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 04:26:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7850943","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7850943","identity":"rs-7850943","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}