Microbial Diversity and Screening for Potential Pathogens and Beneficial Bacteria of Five Jellyfish Species-Associated Microorganisms Based on 16S rRNA Sequencing

The five jellyfish species varied in shape and size (Fig. 1A). The abundance percentages of commensal microorganisms on the tentacles of the five jellyfish species were analyzed at the taxonomic level of the family, revealing significant differences in microbial species composition among these jellyfish. Dominant microbial families varied across different jellyfish species: Mycoplasmataceae in A. coerulea, Sphingomonadaceae in C. andromeda, Alphaproteobacteria_unclassified (family level) in C. quinquecirrha, Parcubacteria_unclassified in P. camtschatica, and both Chlamydiaceae and Alphaproteobacteria_unclassified (family level) in R. esculentum (Fig. 1B). Furthermore, a shared and unique microbial community analysis at the family level indicated 23 families of microorganisms were common among the five jellyfish, while A. coerulea harbored 10 unique families, C. andromeda had 39 unique families, C. quinquecirrha had 46 unique families, P. camtschatica had 13, and R. esculentum had four unique families (Fig. 1C).

Fig. 1.

Analysis of commensal microbial community compositions in five jellyfish species.

A) From (a) to (e): Aurelia coerulea, Rhopilema esculentum, Phacellophora camtschatica, Cassiopea andromeda, and Chrysaora quinquecirrha; B) the microbial community compositions at the taxonomic level of the family for different jellyfish species. C) the shared and unique counts of microbial families among different jellyfish samples at the family level. D) the Circos relationship diagram depicting the top commensal microbial families corresponding to different jellyfish species based on their abundance. We selected the top 30 bacteria with the highest abundance and drew these figures.

From the 23 shared families of microorganisms, the top five families based on average abundance were selected for Circos plot analysis to illustrate the distribution proportions of predominant species across different sample groups: Mycoplasmataceae constituted approximately 99.21% of the microbial composition in A. coerulea, Sphingomonadaceae accounted for about 22.81% in C. andromeda, Alphaproteobacteria_unclassified (family level) represented roughly 64.09% in C. quinquecirrha, Parcubacteria_unclassified (family level) comprised approximately 93.11% in P. camtschatica, and Chlamydiaceae and Alphaproteobacteria_unclassified (family level) constituted about 35.05% and 38.73%, respectively, in R. esculentum (Fig. 1D).

Alpha diversity measures the number of microbial species within an individual sample (species richness) and the proportion of each microbial species (evenness). Higher species richness indicates a greater variety of microbial species within a sample, while higher evenness signifies a more balanced proportion of each microbial species. Results from the Chao1 index indicated that C. quinquecirrha exhibited the highest microbial species richness, followed by R. esculentum, while A. coerulea and P. camtschatica showed similar and comparatively lower levels of microbial richness (Fig. 2A). However, considering the Shannon and Simpson indices, significant differences in diversity among the jellyfish groups were observed. Overall, microbial diversity was highest in C. andromeda, while A. coerulea displayed the lowest diversity when considering microbial richness and evenness together (Fig. 2B and 2C).

Fig. 2.

Microbial community diversity analysis in five jellyfish species.

A) Alpha diversity based on the Chao1 index; B) alpha diversity based on the Shannon index. C) alpha diversity based on the Simpson index; D) within-group PCA analysis among different jellyfish species; E) PCoA analysis among different jellyfish species; F) NMDS analysis among different jellyfish species.

* – p < 0.05, ** – p < 0.01

Beta diversity assesses differences in microbial community composition among different samples. Principal Component Analysis (PCA) demonstrates minimal differences in microbial community composition within the samples of P. camtschatica and A. coerulea. In contrast, other samples exhibited good similarity (Fig. 2D). Principal Coordinates Analysis (PCoA) and Non-Metric Multi-Dimensional Scaling (NMDS) based on Weighted UniFrac analysis revealed minimal variation in microbial community composition within A. coerulea, whereas C. andromeda exhibited the most significant differences in microbial community composition within its groups (Fig. 2E and 2F). This discrepancy in C. andromeda microbial diversity might contribute to these observed differences.

Beta diversity analysis revealed differences in microbial community composition within and among groups. Constructing an evolutionary branching diagram from phylum to family for the selected five microbial families showed their significant roles across the five jellyfish species, primarily classifying these important species at the family level (Fig. 3A). Moreover, the top 14 microbial families based on average relative abundance exhibited significant differences among the five jellyfish species (Fig. 3B). Results from random forest analysis emphasized the importance of five dominant families: Mycoplasmataceae, Sphingomonadaceae, Alphaproteobacteria_unclassified, Parcubacteria_unclassified, and Chlamydiaceae. Among these, Mycoplasmataceae and Sphingomonadaceae appeared to play predominant roles based on their significance levels (Fig. 3C and 3D). Potential beneficial microbial families encompassed Sphingomonadaceae, Endozoicomonadaceae (Hochart et al. 2023), Bacteriovoracaceae, Rhodospirillaceae, Methylophagaceae, Burkholderiaceae, while potential pathogenic microbial families comprised Helicobacteraceae, Chlamydiaceae, Vibrionaceae, Enterobacteriaceae, Mycoplasmataceae, Cryomorphaceae.

Fig. 3.

Analysis of microbial community differences in the five jellyfish species.

A) Evolutionary branching of the most abundant commensal microbial species from the order to genera level across the five jellyfish species. B) comparative differences in relative abundance among the top 14 families of commensal microbes at the family level; C) random forest analysis based on the mean decrease accuracy index. D) random forest analysis based on the mean decrease Gini index. We selected the dominant bacteria and drew these figures.

Alphaproteobacteria_unclassified, Parcubacteria _unclassified, Chlamydiaceae_unclassified, Sphingomonas, and Mycoplasma, exhibited correlated microorganisms within their respective groups. These microorganisms also displayed inter-correlations, primarily negative, except for a nonsignificant positive correlation between Alphaproteobacteria_unclassified and Chlamydiaceae_unclassified. Among these, significant correlations existed between Mycoplasma and Alphaproteobacteria_unclassified, as well as between Sphingomonas and Mycoplasma, with the negative correlation between Mycoplasma and Alphaproteobacteria_unclassified being notably pronounced. Furthermore, among these correlated microbes, potential pathogens included Mycoplasma, Chlamydiaceae _ unclassified, Vibrio, Acinetobacter, and Simkaniaceae _ unclassified, while the potentially beneficial microorganisms, Sphingomonas, stood out. Notably, the difference was most significant between Mycoplasma and Acinetobacter, demonstrating a positive correlation. Sphingomonas, a potentially beneficial genus, exhibited a positive correlation with the potentially pathogenic Acinetobacter but demonstrated negative correlations with other potential pathogens, mostly non-significant (refer to Fig. 4).

Fig. 4.

The correlation network heatmap of commensal microbiota across the five species of jellyfish. (The red lines indicate positive correlations and blue lines for negative correlations). Solid lines represent significant differences, while dashed lines indicate non-significant differences. The thickness of the lines represents the relative abundance. We selected the top 20 bacteria and drew this figure.

This experiment’s environmental factor analysis encompassed five species of jellyfish, examining the correlation between the top 10 abundant microbes categories from phylum to species levels and each jellyfish species. Most microorganisms demonstrated a negative correlation with C. quinquecirrha. However, microorganisms positively correlated with C. quinquecirrha were significantly influenced by C. quinquecirrha, resulting in lower sample similarity levels compared to other jellyfish. A. coerulea exhibited the highest sample similarity, with most commensal microorganisms displaying a negative correlation and experiencing minimal influence from A. coerulea.

A strong positive correlation was shown between C. quinquecirrha and the potential pathogens Proteobacteria but exhibited a negative correlation with other potential pathogens. Other jellyfish species displayed a lower positive correlation with other potential pathogens (Fig. 5A). A strong positive correlation was demonstrated between C. quinquecirrha and the potential pathogens belonging to the classes Gammaproteobacteria and Alphaproteobacteria, while a negative correlation was shown with other potential pathogens. Other jellyfish species displayed a lower positive correlation with other potential pathogens (Fig. 5B). At the order level, a strong positive correlation was exhibited with potential pathogens Vibrionales and Rickettsiales, while other jellyfish species showed a lower positive correlation with other potential pathogens (Fig. 5C). At the family level, a strong positive correlation was displayed between C. quinquecirrha with potential pathogen Vibrionaceae, whereas other jellyfish species exhibited a lower positive correlation with other potential pathogens (Fig. 5D). At the genus level, a strong positive correlation was showed between C. quinquecirrha with the potential pathogen Vibrio, whereas other jellyfish species exhibited a lower positive correlation with other potential pathogens (Fig. 5E). At the species level, a strong positive correlation was displayed between C. quinquecirrha with the potential pathogen Vibrio sp. PH1. Conversely, the potential pathogen uncultured Vibrio sp. exhibited a high negative correlation with all five jellyfish species, while other potential pathogens showed a lower positive correlation with other jellyfish species (Fig. 5F).

Fig. 5.

Correlation analysis between the five jellyfish and their associated microbial communities.

A-F) Correlation analysis between the associated jellyfish and microbial communities at different levels of taxonomical categories. RDA analysis was conducted using the top 10 abundant associated microbial communities across all samples.

Five jellyfish species (A. coerulea, C. andromeda, C. quinquecirrha, P. camtschatica, and R. esculentum) were annotated with 466, 473, 1,082, 2,084, and 1,633 gene functions by 16S rRNA sequencing, respectively. Among these, there were 62 genes shared among the five jellyfish (Fig. 6A). The expression levels of selected genes in the microbiota associated with A. coerulea were significantly lower than those in the other four jellyfish, especially in C. andromeda and P. camtschatica, where these genes were highly expressed. K03088, K01990, K01992, K06147, and K02003 exhibited relatively higher expression levels across the five jellyfish (Fig. 6B). We predicted the possible functions that microbial genes may carry based on KEGG (Table I).

Fig. 6.

Analysis of predicted gene functions and pathogenic phenotype prediction in microbial communities associated with five jellyfish species.

A) Number of annotated genes unique and shared among different jellyfish samples; B) predicted pathogenic phenotype in microbial communities associated with different jellyfish species; C) differential analysis of predicted gene functions and metabolic pathways in microbial communities using STAMP analysis; D) composition of potential pathogenic bacterial communities across different jellyfish samples; E) composition of potential beneficial bacterial communities across different jellyfish samples.

We selected the dominant bacteria and the top 30 genes with total expression levels from shared expression genes to draw these figures.

According to the prediction of potential pathogenic bacterial phenotypes (Ward et al. 2017), A. coerulea, C. quinquecirrha, and P. camtschatica showed higher pathogenic bacterial abundance compared to the other two jellyfish, with R. esculentum exhibiting the lowest pathogenic bacterial abundance (Fig. 6C). At the phylum level, the top five abundant potential pathogenic bacteria were Proteobacteria, Tenericutes, Chlamydiae, and Epsilonbacteraeota. The highest abundance of potentially pathogenic bacteria in A. coerulea was Tenericutes, in P. camtschatica was Epsilonbacteraeota, and in R. esculentum was Chlamydiae. The other two jellyfish showed the highest abundance of potentially pathogenic bacteria as Proteobacteria (Fig. 6D). Conversely, potentially beneficial bacteria only encompassed three phyla: Cyanobacteria, Deinococcus-Thermus, and Nitrospirae, primarily associated with C. andromeda and C. quinquecirrha (Fig. 6E). Overall, the relative abundance of potentially beneficial bacteria was considerably lower than that of potentially pathogenic bacteria.

The microbial communities associated with different jellyfish species and various parts of the jellyfish themselves exhibited differences in composition, species richness, and diversity (Kos Kramar et al. 2019; Liu et al. 2019). Liu et al. (2019) found that among four jellyfish species, Phyllorhiza punctata, Cyanea capillata, Chrysaora melanaster, and Aurelia coerulea, the relatively abundant top five families of microorganisms were Staphylococcaceae, Mycoplasmataceae, Moraxellaceae, Pseudomonadaceae, and Brucellaceae. In our study, the five predominant microbial families were Mycoplasmataceae, Sphingomonadaceae, Alphaproteobacteria_unclassified, Chlamydiaceae, and Parcubacteria_unclassified within the five jellyfish species. A comparison of these two results reveals significant differences in the composition and abundance of associated microorganisms within jellyfish species, indicating that jellyfish species may be a critical factor determining the composition of commensal microorganisms, which is also identical with the results reported by Peng et al. (2023) On the other hand, alterations in the jellyfish community structure, particularly during jellyfish blooms, severely impact coastal facilities and marine ecosystems (Purcell et al. 2007; Fu et al. 2014). Consequently, the microbial communities associated with jellyfish undergo changes accordingly (Basso et al. 2019; Kos Kramar et al. 2019). Furthermore, variations in water quality conditions, such as fluctuations in temperature and salinity, also influence the abundance of marine microorganisms (Kim et al. 2023), subsequently affecting the composition and abundance of microorganisms associated with the jellyfish.

Over the past few decades, research on pathogenic bacteria within marine microorganisms has increased (Little et al. 2020), exerting significant impacts on the stability of marine ecosystems and the regulation of jellyfish populations. Commensal microorganisms can influence jellyfish life cycle and growth. The absence of microbial communities reduced the number of early-stage ephyra in A. coerulea metamorphosis, while resettlement of microbial communities could restore their numbers (Peng et al. 2023). Weiland-Bräuer et al. (2020) also found that the native microbiome was crucial for offspring generation and fitness of Aurelia aurita. Additionally, metabolites from commensal microorganisms assist jellyfish in waste degradation, immune system enhancement, and food digestion. For instance, during the later stages of organic matter breakdown in jellyfish, the dominance of Vibrionaceae and Alteromonadaceae may aid in the accumulation of organic nitrogen compounds and inorganic nutrients during jellyfish dissolution (Tinta et al. 2023). Notably, Vibrionaceae, especially in C. quinquecirrha, exhibit a high relevance, suggesting a potentially crucial role in the life processes of C. quinquecirrha. Despite numerous studies on marine microbial metabolites, our understanding of the synthesis pathways and functions of commensal microbial products in jellyfish remains limited. In corals, metabolites from beneficial microorganisms provide nutrition, promote growth, and inhibit some pathogens, contributing to the balance and restoration of marine ecosystems (Peixoto et al. 2021). Two bacterial genera, Polaribacter and Psychrobacter, which produce physiologically active diketopiperazines, polyhydroxybutyrate salts (PHBs), bile acids, and other beneficial metabolites (Oppong-Danquah et al. 2023), are also present within the studied five jellyfish species. The products of these beneficial bacterial communities can serve as antibiotic alternatives, combating pathogens and protecting hosts from harm (Banerjee et al. 2007; Badhul Haq et al. 2012; Grotkjær et al. 2016). Therefore, the antagonistic effects of beneficial commensal microbes with jellyfish offer a promising approach for eradicating pathogenic microbes in aquatic environments.

On the contrary, potential pathogenic commensal microorganisms with jellyfish may exert detrimental effects, leading to diseases. In this study, potentially pathogenic bacteria were screened, including Helicobacteraceae, Chlamydiaceae, Vibrionaceae, Enterobacteriaceae, Mycoplasmataceae, and Cryomorphaceae. Vibrio splendidus and Vibrio neptunius from Vibrionaceae can cause umbrella tissue lysis in reared A. aurita (Chi et al. 2018). The combination of other pollutants and pathogens in the ocean intensifies the threat to jellyfish. For instance, widespread microplastics in marine environments readily adhere to various microorganisms, including pathogens (Sun et al. 2023), and can easily attach to the jellyfish mucus containing a glycoprotein, potentially infecting the jellyfish (Ben-David et al. 2023). The presence of pathogenic microbes within jellyfish may affect their growth, survival rates, and the health of predators, consequently disrupting the marine food chain and ecological balance. When numerous environmental pathogens are present, they could doubly impact near-shore aquaculture during jellyfish blooms (Clinton et al. 2020). Accumulation of pathogenic microorganisms within jellyfish triggers specific defense mechanisms, which is significant for studying jellyfish immune mechanisms (Weiland-Bräuer et al. 2019).

In addition, the symbiotic microorganisms associated with jellyfish have certain potential for biotechnology utilization. Specifically, bioremediation: some microorganisms associated with jellyfish may have unique abilities to degrade pollutants or decompose organic matter. Biopharmaceuticals: microorganisms associated with jellyfish may produce bioactive compounds with potential medicinal applications. Biotechnology experts can separate and characterize these compounds for drug development. Enzyme production: some microorganisms associated with jellyfish may produce enzymes with special functions. Probiotics: although microorganisms associated with jellyfish may include pathogens, they may also contain beneficial microorganisms used to improve intestinal health or enhance immune function in humans or other animals (Dong and Shang 2021).

Jellyfish provide a suitable substrate for the growth and metabolism of bacteria; for example, jellyfish mucus is rich in proteins and lipids, providing high-quality energy for bacteria. Bacteria associated with jellyfish are involved in the carbon-nitrogen, sulfur, and phosphorus cycling (Lee et al. 2018), indicating a symbiotic relationship. Proteobacteria can participate in the synthesis and metabolism of a variety of biomolecules, such as Kiloniellaceae, which are producers of antibiotic compounds (Wiese et al. 2009). It has been shown that Tenericutes is a potential endosymbiotic bacterium in jellyfish (Weiland-Bräuer et al. 2015). Chlamydiae are intracellular bacteria with potential pathogenic ability that threatens human health because of the lack of effective vaccines (Elwell et al. 2016). As photosynthetic microorganisms, Cyanobacteria provide nutrients for both themselves and their hosts (Mulkidjanian et al. 2006).

Our data also includes related gene expressions. The gene expression of substrate transport systems can reveal how bacteria meet their growth and metabolic needs by acquiring nutrients provided by jellyfish. At the same time, they may reflect the nutrient acquisition strategies of bacteria within jellyfish, as well as their symbiotic or competitive ways (Onyeabor et al. 2020) with jellyfish. The expression of perceptive and adaptive genes, such as methyl receptive chemotactic proteins and CspA family proteins (Yamanaka et al. 1998), may demonstrate how bacteria perceive and adapt to chemical signals and temperature changes in jellyfish. The expression patterns of these genes may reflect bacterial responses to jellyfish immune systems, physiological conditions, and competition with other bacteria. Transcriptional regulation of gene expression, such as RNA polymerase sigma factor (Campbell et al. 2008) expression, can reveal how bacteria regulate gene transcription in jellyfish to adapt to different external signals and environmental conditions. The expression of antioxidant and detoxification genes, such as coacyl-CoA thioester hydrolase genes (Black et al. 2000), may reflect the ability of bacteria to cope with internal oxidative stress and toxin loading in jellyfish. The expression patterns of these genes can reveal how bacteria respond to host immune system attacks or other environmental pressures. In summary, the expression patterns of these genes can provide insights into the survival of bacteria in jellyfish and their interactions with them, thereby helping to understand the dynamics and complexity of the symbiotic relationship between jellyfish and microorganisms.

Jellyfish blooms are frequent and widespread in recent years, and jellyfish may act as vectors of bacterial pathogens in coastal areas, responsible for severe gill diseases of farmed fish (Ferguson et al. 2010; Stabili et al. 2020). Wound infection may occur in the victims stung by box jellyfish (Thaikruea and Siriariyaporn 2015; Thaikruea 2023). Marine Vibrionaceae, as a main potential pathogenic microbial family found in our study, was reported to cause severe necrotizing fasciitis of the extremities and diarrhea in patients (Jiang 1991; Joynt et al. 1999). Changes in the abundance or location of these potentially pathogenic bacteria may influence the health status of humans and also of marine organisms. Further studies are needed on this issue. In addition, due to the accumulation of certain pathogenic bacteria in the body of some edible jellyfish, there is a risk of infection when consumed by humans without proper cooking, which has potential negative impacts on human health (FAO 2022).

Due to the lack of commensal microbial community genome data, this study does not systematically explore how the imbalance of commensal microbial communities affects the host. To expand this research, subsequent studies could employ metagenomics and metatranscriptomics to determine the genomic composition and expression data of commensal microbial communities (Segata et al. 2011; Douglas et al. 2019), thereby accurately investigating the potential mechanisms by which commensal microbial communities affect hosts (Oppong-Danquah et al. 2023). Conducting metabolomic profiling and studying the metabolites and antibacterial activity of microorganisms will be crucial. Metabolites represent one of the primary means through which commensal microbial communities influence hosts. Associating commensal microbial community data with metabolomic data will facilitate a multidimensional explanation of the interaction between commensal microbial communities and hosts. Conducting causal validation experiments by transplanting commensal microbial communities into germ-free mice to verify phenotypic changes would directly demonstrate the causal relationship between commensal microbial communities and diseases.