First insights into the Aurelia aurita transcriptome response upon manipulation of its microbiome

Frontiers in Microbiology 01 frontiersin.org First insights into the Aurelia aurita transcriptome response upon manipulation of its microbiome NancyWeiland-Bräuer 1‡, VasilikiKoutsouveli 2‡, DanielaLangfeldt 1† and RuthA.Schmitz 1 * 1 Institute of General Microbiology, Kiel University, Kiel, Germany, 2 GEOMAR Helmholtz Center for Ocean Research Kiel, Düsternbrooker Weg, Kiel, Germany Introduction: The associated diverse microbiome contributes to the overall fitness of Aurelia aurita, particularly to asexual reproduction. However, how A. aurita maintains this specific microbiome or reacts to manipulations is unknown. Methods: In this report, the response of A. aurita to manipulations of its native microbiome was studied by a transcriptomics approach. Microbiomemanipulated polyps were generated by antibiotic treatment and challenging polyps with a non-native, native, and potentially pathogenic bacterium. Total RNA extraction followed by RNAseq resulted in over 155 million reads used for a de novo assembly. Results: The transcriptome analysis showed that the antibiotic-induced change and resulting reduction of the microbiome significantly affected the host transcriptome, e.g., genes involved in processes related to immune response and defense mechanisms were highly upregulated. Similarly, manipulating the microbiome by challenging the polyp with a high load of bacteria (2 × 107 cells/ polyp) resulted in induced transcription of apoptosis-, defense-, and immune response genes. A second focus was on host-derived quorum sensing interference as a potential defense strategy. Quorum Quenching (QQ) activities and the respective encoding QQ-ORFs of A. aurita were identified by functional screening a cDNA-based expression library generated in Escherichia coli. Corresponding sequences were identified in the transcriptome assembly. Moreover, gene expression analysis revealed differential expression of QQ genes depending on the treatment, strongly suggesting QQ as an additional defense strategy. Discussion: Overall, this study allows first insights into A. aurita’s response to manipulating its microbiome, thus paving the way for an in-depth analysis of the basal immune system and additional fundamental defense strategies. KEYWORDS Aurelia aurita, microbiome, transcriptome, immune system, defense mechanisms, quorum quenching 1. Introduction Cnidarians, such as the moon jellyfish Aurelia aurita, are distributed worldwide and play essential roles in shaping marine ecosystems (Brekhman etal., 2015). Cnidaria are dated back to about 700 million years and are considered a sister group to the Bilateria (Putnam etal., 2007; Park etal., 2012). Thus, they are among the simplest animals at the tissue level organization possessing two germ layers (ectoderm and endoderm) separated by the mesoglea (Ball etal., 2004). In addition to their morphological simplicity, many Cnidaria, particularly Scyphozoa, have a high level of developmental plasticity, allowing for an enormous tolerance, regeneration OPEN ACCESS EDITED BY Alejandra Prieto-Davó, National Autonomous University of Mexico, Mexico REVIEWED BY Ming Guo, Ningbo University, China Ojas Natarajan, University of South Florida, UnitedStates *CORRESPONDENCE Ruth A. Schmitz [email protected] †PRESENT ADDRESS Daniela Langfeldt, Institute of Clinical Molecular Biology (IKMB), Kiel University, Kiel, Germany ‡These authors have contributed equally to this work and share first authorship RECEIVED 10 March 2023 ACCEPTED 18 July 2023 PUBLISHED 10 August 2023 CITATION Weiland-Bräuer N, Koutsouveli V, Langfeldt D and Schmitz RA (2023) First insights into the Aurelia aurita transcriptome response upon manipulation of its microbiome. Front. Microbiol. 14:1183627. doi: 10.3389/fmicb.2023.1183627 COPYRIGHT © 2023 Weiland-Bräuer, Koutsouveli, Langfeldt and Schmitz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Original Research PUBLISHED 10 August 2023 DOI 10.3389/fmicb.2023.1183627 Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 02 frontiersin.org potential, and asexual proliferation during their life cycle (Richardson etal., 2009). Cnidaria have evolved and are constantly exposed to diverse microorganisms (Liu etal., 2019). This close association with microorganisms has profound effects on various host functions. Recent studies have demonstrated that specific host-associated microbiota can contribute to various host functions. Examples are host metabolism (Ochsenkühn etal., 2017), development (Rook etal., 2017), organ morphogenesis (Sommer and Bäckhed, 2013), pathogen protection and immunity (Moran and Yun, 2015), behavior (Ezenwa etal., 2012), environmental sensing and adaptation (Bang etal., 2018; Ziegler etal., 2019), developmental transitions (Webster and Reusch, 2017; Woznica etal., 2017), and reproduction (Chilton etal., 2015; Jacob etal., 2015). Evidently, Cnidarians are constantly exposed to microbes in the environment; consequently, molecular analyses have revealed a variety of molecular pathways to respond to microbial exposure (Dierking and Pita, 2020). In the first step, extracellular surface receptors recognize microbe-associated molecular patterns (MAMPs) during microbial epithelium colonization (Chu and Mazmanian, 2013). MAMPs include lipopolysaccharides (LPSs), peptidoglycan (PGN), flagellin, and microbial nucleic acids (Rosenstiel etal., 2009). In the first line of defense, antimicrobial peptides (AMPs) regulate establishing and maintaining a specific microbiota (Bosch, 2013; Bosch and Zasloff, 2021). Toll-like receptors (TLRs) at the host cell surface further perceive the MAMP signal, initiating MAMP-triggered immunity (Augustin etal., 2010; Bosch, 2013). Downstream of those conserved signaling cascades are stress-responsive transcription factors, including eukaryotic transcription factors of the proteins’ NF-kappaB (NF-kB) family (Zheng et al., 2005). Recent studies revealed that eukaryotic hosts also use quorum quenching (QQ) as a strategy to respond to bacterial colonization (Grandclâment etal., 2016). The hosts interfere with the small molecule-dependent bacterial communication through enzymatic degradation of the autoinducer, blocking autoinducer production, or its reception to control population-dependent behaviors like colonization, biofilm formation, and pathogenesis (Kiran etal., 2017; Mukherjee and Bassler, 2019). In the Cnidarian Hydra, the autoinducer signaling molecule 3-oxo-homoserine lactone has been shown to beconverted into the inactive 3-hydroxy counterpart by a host-derived oxidoreductase allowing host colonization of the main colonizer Curvibacter sp. (Pietschke etal., 2017). The Cnidarian A. aurita harbors a highly diverse and dynamic microbiota specific to the animal, the different sub-populations, and life stages (Weiland-Bräuer etal., 2015a). In the absence of the specific microbial community, the fitness of A. aurita was significantly compromised, and notably, asexual reproduction was almost halted (Weiland-Bräuer etal., 2020a). This microbial impact is crucial at the polyp life stage before entering the process of asexual offspring production (strobilation) to ensure a normal progeny output (Jensen etal., 2023). Moreover, in A. aurita, three proteins interfering with bacterial QS were identified (Weiland-Bräuer etal., 2019). Incubation of native animals with potentially pathogenic bacteria induced the expression of the identified QQ-ORFs, strongly suggesting a host defense strategy. Despite the growing knowledge about the impact of microbes on the host and the fundamental strategies of the host to respond, research to understand how microbiomes influence host gene expression is still in its infancy (Nichols and Davenport, 2021). Many studies of model organisms and humans demonstrated an interlinkage between the microbiome and the host’s gene expression. However, the direction of causality mainly remained unanswered (Nichols and Davenport, 2021). Comparing conventional (microbiome-containing) to germ-free systems is one way to assess whether the microbiome plays a causative role in regulating gene expression (Bäckhed etal., 2012; Al-Asmakh and Zadjali, 2015; Fu etal., 2017; Pierre, 2022). Genome-wide transcriptomic analyses are now routinely used to quantify the changing levels of each transcript under different conditions (Conesa etal., 2016). In the present study, weaimed to determine the influence of the associated microbiota on A. aurita’s gene expression. After microbiome manipulation (by antibiotic treatment or bacterial challenge), RNA was extracted from polyps, followed by RNA-Seq and a de novo transcriptome assembly. Gene ontology categories and gene expression patterns were analyzed to elucidate how A. aurita recognizes and responds to the manipulation of its native microbiome and the presence of potential pathogens. A particular focus was on hostderived QQ activities as an additional potential defense strategy. 2. Materials and methods 2.1. Aurelia aurita polyp husbandry Husbandry is described in detail by Weiland-Bräuer etal. (2015a, 2020a). Briefly, polyps of the sub-population North Atlantic (Roscoff, France) were kept in the lab in 2-liter plastic tanks in 3% artificial seawater (ASW) (tropical sea salts; Tropic Marin). Polyps were fed twice a week with freshly hatched Artemia salina (HOBBY, GrafschaftGelsdorf, Germany). 2.2. Reduction of the native Aurelia aurita polyp microbiota by antibiotics Single native polyps were placed in 48 well multiwell plates in 1 mL ASW supplemented with an antibiotic mixture (Provasoli’s antibiotic mixture with final concentrations of 360,000 U/L penicillin G, 1.5 mg/L chloramphenicol, 1.8 mg/L neomycin, and 9,000 U/L polymyxin B; all components from Carl Roth, Karlsruhe, Germany). No food was provided during the antibiotic treatment. The reduction and consequent change of the microbiota were tested by plating a single homogenized polyp (10 replicates) on Marine Bouillon agar plates (Carl Roth, Karlsruhe, Germany). Plates were incubated for 5 days at 20°C. Colony forming units (cfu) were calculated, and an 87 ± 9% reduction per polyp was determined. 2.3. Bacterial growth conditions and microbial challenge of polyps Bacteria (Pseudoalteromonas espejiana GenBank accession No. MK967174, and Vibrio anguillarum GenBank accession No. MK967055) for the microbial challenge were isolated from A. aurita polyps (Weiland-Bräuer etal., 2020b). Strains were grown in Marine Bouillon (MB; Carl Roth, Karlsruhe, Germany) at 30°C and 120 rpm to optical turbidity at 600 nm of 0.8. Klebsiella oxytoca M5aI (DSM No. Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 03 frontiersin.org 7342) was similarly grown in Luria-Bertani (LB) medium. Bacterial cell numbers were determined using a Neubauer count chamber (Assistant, Sondheim vor der Röhn, Germany). Pools of 20 native A. aurita polyps were separated in 6-well multiwell plates (Greiner, Kremsmünster, Austria) in 4 mL 3% ASW after washing them twice with sterile ASW. A pool of 20 native A. aurita polyps was incubated with 108 cells/mL (in 4 mL) of the respective strain at 20°C for 30 min. Next, polyps were washed twice with sterile ASW to remove the bacteria and used to isolate total RNA. 2.4. Experimental design for transcriptome analysis The North Atlantic sub-population polyps were generated from a single mother polyp by clonal budding. Pools of 20 daughter polyps were separated into 6-well plates in 4 mL 3% ASW. Polyps were kept in five conditions without food supply: 1. native polyps without treatment, 2. antibiotic (AB)-treated polyps, 3. native polyps challenged with 108 cells/mL Klebsiella oxytoca M5aI, 4. native polyps challenged with 10 8 cells/mL Pseudoalteromonas espejiana, and 5. native polyps challenged with 10 8 cells/mL Vibrio anguillarum (Figure 1). Three replicates (3 × 20 polyps) were used for each condition. For the bacterial challenges, 20 polyps in 4 mL ASW were supplemented with 4×108 cells and incubated for 30 min (Figure1). The total RNA was extracted from each pool of polyps. 2.5. RNA isolation Total RNA of a pool of 20 A. aurita polyps was isolated with an adapted protocol of Gold etal. (2019). In more detail, polyps were washed three times with sterile ASW (to remove antibiotic residues) and homogenized with a motorized pestle. RiboLock RNase Inhibitor (40 U/μL, Thermo Fisher Scientific, Waltham/Massachusetts, United States), 200 μL lysis solution (100 mM Tris/HCl, pH 5.5, 10 mM disodium EDTA, 0.1 M NaCl, 1% SDS, 1% ß-mercaptoethanol), and 2 μL Proteinase K (25 mg/mL, Thermo Fisher Scientific, Waltham/Massachusetts, UnitedStates) were added to the homogenate and incubated for 10 min at 55°C. Chilled solutions were added with 5 μL of 3 M sodium acetate (pH 5.2) and 250 μL phenol-chloroform-isoamyl alcohol (25:24:1) and incubated for 15 min on ice prior to 15 min centrifugation at 12,000 x g at 4°C. The upper phase was mixed with 1 volume 2-propanol, and precipitation occurred at-80°C overnight. The precipitate was centrifuged for 15 min at 12,000 x g at 4°C. The pellet was washed twice with 70% ethanol before the air-dried pellet was dissolved in 25 μL RNase-free water. DNA contaminations were removed with Turbo DNA-free DNase (Thermo Fisher Scientific, Waltham/ Massachusetts, UnitedStates). The RNA quality and quantity were assessed by NanoDrop1000 (Thermo Fisher Scientific, Waltham/ Massachusetts, UnitedStates) and 1.5% agarose gel electrophoresis, and the cDNA library was prepared with DNA-free host RNA (500 ng) using the TruSeq Stranded mRNA Library Preparation kit. The library was sequenced with the NextSeq500 System (Illumina, San Diego/ California, UnitedStates). 2.6. Transcriptome analysis The raw reads were trimmed with Trimmomatic (Bolger etal., 2014) to remove bad-quality reads and the adapters. A de novo assembly with the trimmed sequences was conducted with the Trinity package v2.8.4 (Grabherr etal., 2011a,b). The quality of the de novo assembly was assessed with several parameters, such as the N50 value and the percentage of the assembly-mapped reads, which was calculated with Bowtie2. Finally, Benchmarking Universal SingleCopy Orthologs (BUSCO V2/3) against metazoan cassettes (Simão etal., 2015) was used to evaluate the completeness of the assembly regarding the core genes found in metazoans. FIGURE1 Experimental setup. RNA extraction with subsequent RNAseq and analysis was conducted on a pool of 20 polyps (3 biological replicates). Polyps were kept under native and microbiome-manipulated conditions. Created with BioRenders. Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 04 frontiersin.org A Blastx of the transcriptome assembly was executed against the Swiss-Prot database for metazoans. For the gene expression analysis, reads were mapped to the reference assembly with Bowtie2 (Langmead and Salzberg, 2012). Transcript quantification was performed with RSEM (Li and Dewey, 2011). The differential gene expression (DGE) analysis was done with edgeR (Robinson etal., 2010; McCarthy etal., 2012). Pairwise comparisons between all experimental conditions were performed using FDR ≤ 0.001 and 2-fold changes as statistical parameters. Furthermore, GO enrichment analysis was conducted using a Fisher’s Exact Test in Blast2GOPRO (Conesa etal., 2005) with a value of p threshold of ≤0.05. Here, the total annotation file of the reference transcriptome was used as the “reference dataset,” whereas the upregulated genes in each condition served as the “test dataset.” Based on sequence depth and quality, only two out of three biological replicates were used for the gene expression analysis for the conditions of native polyps and native polyps under the bacterial challenges. Transcriptome data is deposited under the BioProject ID PRJNA938117. Gene expression patterns in the transcriptome data set were verified with qRT-PCRs of the housekeeping gene elongation factor 1 (EF1) (Weiland-Bräuer etal., 2019; Jensen etal., 2023). EF1 showed similar trends in gene expression for all treatments when comparing transcriptome data and qRT-PCR (Table1). Moreover, the previously published QQ genes aaqq1, aaqq2, and aaqq3 of A. aurita (Weiland-Bräuer etal., 2019) were identified in the transcriptome data set. Their expression profiles have been studied using qRT-PCR in native, antibiotic-treated, and K. oxytoca-treated polyps [see study (Weiland-Bräuer etal., 2019)]. Gene expression profiles were similar in transcriptome data and qRT-PCR, which werated and considered as internal control for our newly obtained data set and its validity (Table1). 2.7. Quorum quenching assay Quorum quenching (QQ) assays using the reporter strains AI1-QQ.1 and AI2-QQ.1 were performed with cell-free supernatants and cell extracts of EST clones from the A. aurita EST library as described (Weiland-Bräuer etal., 2015b). Briefly, QQ screening plates were prepared with LB agar containing 0.8% agar at 50°C supplemented with final concentrations of 100 μM N-(β-ketocaproyl)-l-homoserine lactone (3-oxo-C6-HSL) (Sigma-Aldrich, Munich, Germany), 100 μg/mL ampicillin, 30 μg/ mL kanamycin, and 10% (vol/vol) exponentially growing culture of the reporter strain AI1-QQ.1. Similarly, AI-2 QQ screening plates were prepared with final concentrations of 50 mM 4-hydroxy-5methyl-3-furanone (Sigma-Aldrich, Munich, Germany), 100 μg/mL ampicillin, 30 μg/mL kanamycin, and 5% (vol/vol) exponentially growing culture of the reporter strain AI2-QQ.1. LB agar plates were coated with the agar mixture. After 10 min, 5 μL of the test substances were applied, followed by overnight incubation at 37°C. QQ activities were visualized by the growth of the respective reporter strain. Preparation of cell extracts and cell-free culture supernatants was conducted with 5 mL overnight cultures of EST clones grown at 37°C and 120 rpm. Cells were harvested by centrifugation at 7,000 × g, and the culture supernatant was subsequently filtered using 0.2-μm centrifugal filter units (Carl Roth, Karlsruhe, Germany). The cell extract was prepared from the cell pellet using the Geno/Grinder 2000 (BT&C/OPS Diagnostics, Bridgewater, NJ). Cell extracts were filtered through 0.2-μm filter units. Following the manufacturer’s protocol, the plasmids of identified QQ-active single EST clones were purified using the Presto Mini Plasmid kit (GeneAid, New Taipeh City, Taiwan). The respective inserts were Sanger sequenced at the Institute of Clinical Molecular Biology in Kiel with the primer set T7_Promoter (5′-TAATACGACTCACTATAGGG-3′) and T7_Reverse (5’-TAGTT ATTGCTCAGCGGTGG-3′). Sequences are deposited at NCBI GenBank under Accession Nos. OQ581004- OQ581041. 3. Results A transcriptomics approach was applied to gain insights into the response of A. aurita polyps to manipulation of its native, associated microbiota, with a particular focus on quorum sensing interference as a potential host defense strategy. In general, pools of 20 polyps were treated and processed together in the experiments, each with three biological replicates using the following treatments: native, antibiotic-treated polyps resulting in 87 ± 9% reduced microbial cells per polyp (cfu/polyp), and native polyps challenged with Klebsiella oxytoca M5aI, Pseudoalteromonas espejiana, or Vibrio anguillarum (2 × 10 7 cells/polyp, Figure1). The TABLE1 Comparison of transcriptome data scores and qRT-PCR Ct values for verification. data origin ORF native AB-treated K. oxytoca V. anguillarum P. espejiana transcriptome data EF1 5.6 5.3 2.6 1.9 1.1 aaqq1 1.1 0.7 0.1 nd nd aaqq2 4.1 1.6 2.9 nd nd aaqq3 3.9 2.5 0 nd nd qRT-PCR EF1 20.4 20.1 13.6 14.2 11.3 aaqq1 11.9 8.6 5.5 nd nd aaqq2 14.0 6.9 8.2 nd nd aaqq3 6.3 6.9 5.4 nd nd For the housekeeping gene elongation factor 1 (EF1), the mean raw Ct value of three biological and three technical replicates is shown. Values for QQ-ORFs represent the mean ΔCt value (three biological and three technical replicates), normalized with the housekeeping gene actin (Weiland-Bräuer etal., 2019). nd, not detected. Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 05 frontiersin.org respective pools were used for total RNA extraction followed by RNAseq and transcriptome analysis. 3.1. Statistics of the de novo transcriptome assembly The RNAseq approach overall resulted in 167,269,257 raw reads. After quality trimming, 145,746,530 reads (87.1% of the total reads) remained for further analysis and were used for the de novo transcriptome assembly (Supplementary Table S1A). The de novo assembly resulted in 213,897 transcripts and 160,700 genes (Supplementary Table S1A) with an N50 value of 1,170 (Supplementary Table S1B). 94.25% of reads were successfully aligned back to the assembly, while the completeness of genes was 96.42% according to the BUSCO score for metazoans (Supplementary Table S1B). 30% (597,796 transcripts) of the assembly revealed an annotation against the Swiss-Prot database for metazoans (Supplementary Table S2). 3.2. Manipulation of its microbiome affects A. aurita’s transcriptome Transcriptome analysis identified five separated clusters corresponding to the different conditions, while biological replicates of a condition cluster together (Figure2). It should benoted that three replicates were only analyzed for antibiotic (AB)-treated polyps, as all other conditions resulted in an unacceptable low sequence depth for one replicate. Notably, two clusters were identified within the hierarchical clustering of transcripts. Here, native and AB-treated conditions yielded a tremendous difference. AB-treated polyps showed a massive reduction of the microbial load (by 87 ± 9%), assuming a rigorous change in the abundance and diversity of microbial colonizers. Bacteria-challenged polyps showed a mixture of native and AB-treated expression patterns (Figure2). In more detail, the comparison of native and AB-treated polyps resulted in the highest number of differentially expressed genes (22,073 genes), with 10,451 upregulated and 11,622 down-regulated genes in AB-treated compared to native polyps (Supplementary Table S3A). According to FIGURE2 Holistic expression patterns of A. aurita polyps. Heatmap including the Differential Expressed (DE) genes in all the pairwise comparisons of the native, AB-treated, and bacteria-challenged polyps, including replicates. Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 06 frontiersin.org FIGURE3 GO enrichment analysis of differentially expressed genes of native and AB-treated A. aurita polyps. (A,C) Barplots with GO-enriched gene categories when comparing native and Ab-treated polyps. Barplots indicate the proportion (%) of DE gene sequences involved in (A) upregulated and (C) downregulated GO-enriched categories compared to the reference (de novo assembly). (B,D) Heatmap of upregulated and down-regulated genes with the comparison of native and AB-treated polyps related to (B) immune response and apoptosis (D) and common physiological processes. Relative expression level increase from blue to red. the GO enrichment analysis (Conesa et al., 2005), the 10,451 upregulated genes were overrepresented in processes related to inflammation and immune response (e.g., acute inflammatory response to antigenic stimuli, MAP-kinase activity, cytokine production, and neutrophil cell activation) (Figure 3A; Supplementary Table S4A). Genes involved in immune response and apoptosis included, e.g., Caspases, Apoptosis regulators, Interferones, and Toll-like receptors (Figure3B; Supplementary Tables S3A, S4A). On the contrary, down-regulated genes in AB-treated polyps were enriched for processes related to development, morphogenesis, reproduction, stimuli response, and signaling (Figures 3C,D; Supplementary Tables S3A, S4A). When comparing expression patterns between native and bacteria-challenged polyps, differences based on the bacterial species used in each challenge were revealed (Figure4). The comparison of native polyps compared to those challenged with V. anguillarum gave the highest number of differentially expressed (DE) genes (7,193 genes, Figure 4A; Supplementary Table S3B), followed by polyps challenged with K. oxytoca (6,974 DE genes, Figure 4A; Supplementary Table S3C), and P. espejiana (2,721 genes, Figures4A; Supplementary Table S3D). Weobserved 2,210 genes were commonly upregulated among the treatments compared to native polyps (Figure4A; Supplementary Table S3E). At the same time, 52 genes were jointly downregulated (Figure4B; Supplementary Table S3E). Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 07 frontiersin.org Genes related to biological processes, such as defense, immune and inflammatory responses, and the regulation of apoptotic processes, were upregulated in bacteria-challenged polyps (Figure 4B; Supplementary Table S3E). In contrast, genes related to organism development, cell cycle processes, and cytoskeleton organization were down-regulated in challenged polyps (Figure 4B; Supplementary Table S3E). Moreover, exclusively upregulated and down-regulated genes were identified for each bacterial challenge (Figure4). 1,319 genes were exclusively upregulated in V. anguillarumchallenged polyps (Figure4A left panel; Supplementary Table S3F), 1,020 genes were exclusively upregulated in polyps challenged with K. oxytoca (Figure4A left panel; Supplementary Table S3G), and 160 genes exclusively upregulated in P. espejiana-challenged polyps (Figure4A left panel; Supplementary Table S3H). Similarly, exclusively down-regulated genes were identified (Figure 4A, right panel). Analyzing the GO-enriched categories for each species (Supplementary Table S4B–D), wefound categories common among all treatments (Supplementary Table S4E) as well as categories present in two different treatments or only in one (Figure 4B; Supplementary Table S4B–D). Focusing on genes exclusively upregulated after each species-specific challenge, weindeed observed that the same GO categories, e.g., immune response, MAPK signal transduction, autophagy, and DNA repair, were enriched to different degrees, though represented by various genes (depicted in Figure5). 3.3. Bacterial challenge of polyps affects host quorum quenching Recent studies revealed that interfering with Qurom sensing, so-called quorum quenching (QQ), might be a fundamental, additional inter-phylum interaction to maintain metaorganismal homeostasis. Consequently, weaimed to identify host-derived QQ activities. An expressed sequence tag (EST) library from A. aurita FIGURE4 GO enrichment and differential expression analysis of genes divergently transcribed in native compared to bacteria-challenged polyps. (A) Venn diagram indicating the genes that are commonly and exclusively upregulated (left panel) or down-regulated (right panel) in the different bacteriachallenged conditions. (B) Heatmap of up-and downregulated genes in native compared to bacteria-challenged polyps. Relative expression level increases from blue to red. Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 08 frontiersin.org FIGURE5 Exclusively upregulated genes in native vs. bacteria-challenged polyps. Bubble plot showing the degree of enrichment per category of exclusively upregulated genes in each bacteria-challenged compared to native conditions. polyps-derived mRNA was constructed in E. coli SoluBL21 (Ladewig etal., 2023). The library consisted of 29,952 clones with an insertion efficiency of approx. 98% and an average insert size of 1.46 kbp, resulting in 43 Mbps cloned host transcriptome, corresponding to an estimated 11.4% coverage [calculated A. aurita genome size 376 Mbps (Gold et al., 2019)]. The A. aurita EST library was successively screened for QQ activities toward acyl-homoserine lactones (AHL) and autoinducer-2 (AI-2) in cell-free cell extracts and culture supernatants of the EST clones using established E. coli-based reporter systems (Weiland-Bräuer etal., 2015b). Overall, 37 out of 29,952 EST clones were identified as QQ active (Table2). Predominantly, QQ activities against the Gram-negative signaling molecule AHL were detected. Although those host-derived QQ activities were identified in a functional screen, their biological activities in vivo and their functions in A. aurita have to beexplored. In a first attempt, plasmid insertions of QQ-active single EST clones were sequenced, and sequence data subsequently checked for homologies in the A. aurita transcriptome assembly. All QQ-conferring sequences were identified in the transcriptome assembly with homologies ranging from 83 to 100% (Supplementary Table S5). Furthermore, public databases (NCBI, UniProt, PFAM) were used for homology predictions and annotation (Supplementary Table S5). Unexpectedly, several QQ-ORFs showed homologies to highly conserved ribosomal proteins, suggesting a moonlighting function of those proteins (Jeffery, 2003; Singh and Bhalla, 2020). Secondly, analyzing transcription levels of those identified QQ-ORFs in the generated RNAseq data set (see above) allowed first insights into their transcriptional regulation in response to the respective treatments, which might support predicting their biological role. Relative expression of the 37 QQ-conferring genes was calculated for microbiome-manipulated versus native polyps. Hierarchical clustering observed four clusters of expression profiles. The first cluster represents QQ genes similarly expressed in microbiome-manipulated polyps compared to native ones (Figure6, right column highlighted in grey). The second cluster of genes showed decreased expression in all treatments, except when challenged with P. espejiana (Figure6, right column light orange cluster). The third Weiland-Bräuer et al. 10.3389/fmicb.2023.1183627 Frontiers in Microbiology 09 frontiersin.org cluster summarizes those genes with increased expression regardless of the type of manipulation (Figure6, right column dark orange cluster). The fourth cluster includes those genes with an increased expression after adding potential pathogens but reduced expression when polyps were AB-treated (Figure6, right column green cluster). Notably, P. espejiana primarily showed increased expression of QQ-ORFs; thus, hierarchal clustering showed the highest dissimilarity compared to the other treatments. 4. Discussion In the present study, we obtained the first insights into the transcriptomic response of A. aurita to microbiome manipulation. The manipulations of the polyp microbiome included a massive reduction of viable bacterial cells (87% reduction) due to applying a broad-spectrum antibiotics mixture. The mixture contained Penicillin, Polymyxin B, Chloramphenicol, and Neomycin (Provasoli and Pintner, 1980; Liu etal., 2017a; KleinJan etal., 2022), and has been shown to only partially eliminate an entire bacterial community (Azma etal., 2010; Liu etal., 2017a). Weassume that by drastically reducing the colony-forming units by 87%, the diversity and abundance of community members on the polyp are crucially changed. Consequently, the polyp was confronted with the loss of certain community members and a drastic change in the relative abundance of remaining ones. This extreme change in microbiome composition resulted in the up-regulation of various immune response mechanisms. Pattern recognition receptors (PRRs) like Tolllike receptors and Ficolins were upregulated, inducing the first line of defense (Figure3). Further, Caspases were enriched in AB-treated polyps, potentially maintaining homeostasis through regulating cell death and inflammation (McIlwain et al., 2013). Contrarily, all processes involved in morphogenesis and development, thus not essential for survival, were down-regulated in AB-treated polyps (Figure3). Furthermore, the native microbiome was affected by challenging the polyps with three different bacteria in high cell numbers: (i) K. oxytoca has not been detected in any life stage of A. aurita and thus represents a non-native bacterium (Weiland-Bräuer et al., 2015a, 2019); (ii) V. anguillarum, an opportunistic pathogen of various invertebrates and vertebrates, has been isolated from an A. aurita polyp (Austin, 2010; Frans etal., 2011; Weiland-Bräuer etal., 2015a,b); and (iii) P. espejiana was initially isolated from seawater but was also found in high abundance associated with all life stages of A. aurita, thus representing a native bacterium (Isnansetyo and Kamei, 2009; Weiland-Bräuer et al., 2015a,b). Due to bacterial challenges, weobserved the up-regulation of defense, immune, and inflammatory responses, and apoptosis regardless of the bacterial species. Based on this finding, wehypothesize that the host recognized the non-native and native bacteria as a potential threat, at least when present in such high cell numbers. The immune system of A. aurita likely responded with the four primary innate immune system functions as demonstrated for other Cnidarians and already partly observed for AB-treated polyps (Miller et al., 2007; Parisi et al., 2020). First, immune recognition occurred by PRRs, like Fucolectins, Ficolins, and NACHT-containing domain proteins, binding to bacterial MAMPs/ PAMPs (Figures4, 5). Subsequently, various transcription factors from the NF-κB family were activated (Figures4, 5). Intracellular signaling cascades (MAPK, interleukin, cytokines) led to target gene transcription to eliminate the threat and mitigate self-harm (Figures4, 5). Lastly, autophagy, DNA repair, and programmed cell death were upregulated after bacterial challenge (Figures4, 5). Our observations TABLE2 Aurelia aurita-derived quorum quenching activities derived from an expressed sequence tag (EST) library. QQ-ORF Original clone designation QQ activity AHL AI-2 QQ_Aa_1 115/H7 x x QQ_Aa_2 118/E4 x – QQ_Aa_3 118/G4 x x QQ_Aa_4 127/C7 x x QQ_Aa_5 164/A6 x – QQ_Aa_6 164/E2 x x QQ_Aa_7 184/A11 x – QQ_Aa_8 184/B9 x – QQ_Aa_9 202/G6 x – QQ_Aa_10 208/E9 x – QQ_Aa_11 208/A3 x – QQ_Aa_12 213/E2 x – QQ_Aa_13 213/F2 x – QQ_Aa_14 217/H4 x – QQ_Aa_15 221/C11 x x QQ_Aa_16 284/H11 x – QQ_Aa_17 115/A1 x – QQ_Aa_18 115/A11 x x QQ_Aa_19 115/G1 x – QQ_Aa_20 118/F5 x x QQ_Aa_21 164/B2 x – QQ_Aa_22 164/C8 x – QQ_Aa_23 164/D1 x – QQ_Aa_24 164/D6 x – QQ_Aa_25 164/F2 x – QQ_Aa_26 164/G1 x – QQ_Aa_27 127/A8 x x QQ_Aa_28 127/A10 x – QQ_Aa_30 127/C12 x – QQ_Aa_31 127/F8 x – QQ_Aa_32 184/A6 x – QQ_Aa_33 213/B7 x – QQ_Aa_34 223/E7 x – QQ_Aa_35 270/C5 x x QQ_Aa_36 273/A1 x – QQ_Aa_37 273/F12 x x QQ_Aa_38 284/A10 x x Functionally identified QQ-ORFs are listed with their QQ activity in the cell-free cell extract (CE) and culture supernatant (SN) against acyl-homoserine lactones (AHL) and autoinducer-2 (AI-2) with their potential annotations; x, activity; −, no activity.