16S rDNA-based diversity analysis of bacterial communities associated with soft corals of the Red Sea, Al Rayyis, White Head, KSA

Abstract

Coral reef endogenous to the Red Sea ecosystem is one of the largest globally known living reefs that are remarkably distinctive to constant high temperature and salinity. Coral microbiota is one of the most important prespectives contributing to coral survival in such conditions. Four soft corals endogenous to the eastern Red Sea side at Al Rayyis White Head, KSA were collected and identified as Litophyton sp., Sinularia sp., Xenia sp. and Sarcophyton sp. Soft corals-associated microbiota were investigated using Illumina sequencing of bacterial 16S rRNA genes. Results revealed higher bacterial diversity. Assignment of bacterial reads at the phylum level revealed the predominance of Proteobacteria in all coral-associated microbiotas followed by Bacteroidetes and Firmicutes. At the family level, Litophyton sp. was dominated by Hahellaceae, Staphylococcaceae, Prevotellaceae, Moraxellaceae and Bacteroidaceae, while Xenia sp. was dominated by Hahellaceae and Anaplasmataceae. The microbiota of Sinularia sp. were dominated by Pseudomonadaceae and Enterobacteriaceae. Sarcophyton sp. microbiota mainly include members of Enterobacteriaceae only.

KEYWORDS:

• Diversity
• 16S rDNA
• microbiota
• soft corals
• Red sea

1. Introduction

Corals are dynamic associations of marine invertebrates which host a wide variety of microbes including bacteria, fungi, archaea and viruses. This assemblage of the host animal and many other species is known as coral holobiont [1]. Coral-associated microbes play important roles in keeping corals healthy and immune [2,3]. Microbes are likely to fix and cycle essential nutrients, e.g. nitrogen, sulphur and other nutrients, to their coral host [4,5]. Additionally, they could guard their hosts against infection and prediction via the production of bioactive secondary metabolites [6,7]. Moreover, the microbes stimulate the coral host adaptation against adverse environmental conditions [8]. In return, microbes benefit from the ecological niches and nutrients provided by the host coral [9]. In healthy and degraded coral reefs, microbes are critical parts of the coral holobiont [10,11]. Since 2001, culture-independent techniques have been employed to unravel the diversity of coral-related microbes [12,13]. The coral-associated microbes were reported as coral species-specific [14] and site-specific [15]. Furthermore, several reports indicated that these associated microbes may shift under the influence of environmental conditions [16].

The Red Sea is a distinctive (regarding its constant high temperature and salinity) and largely undiscovered marine ecosystem. Interestingly, about 200 coral species were recorded over an extensive area of the Red Sea shoreline [17,18]. Previous research showed that corals had diverse and plentiful microbial populations [12,18,19]. However, there was no thorough survey of the Red Sea corals’ microbial diversity. A few studies were performed in order to explore the coral diversity associated with microbes in the Red Sea [13]. In 2012, Lee and colleagues [13] indicated that Proteobacteria was the dominant group in the identified coral-associated microbiota. Proteobacteria was identified as the dominant phylum in coral-associated microbiota in another study performed by Ziegler and co-workers [20]. Ziegler’s group indicated the opportunistic bacterial families, e.g. Vibrionaceae and Rhodobacteraceae, were more abundant in corals at sites impacted by anthropogenic pollution.

Until now, little is known about the coral microbiota of the distinctive marine body of the Red Sea. This study aims to exploit Illumina sequencing of bacterial 16S rRNA genes to explore bacterial community composition associated with soft corals dominated on the eastern side of the Red Sea, and, therefore, intensify our understanding of the diversity of such unrevealed microbiotas.

2. Materials and methods

2.1. Sample collection and identification of soft corals

Four marine soft coral samples were collected from four sites (Table 1) along Al Rayyis White Head (Red Sea, KSA) by a self-contained underwater breathing apparatus (SCUBA) diving as well as snorkeling during the autumn of 2019 (Figure 1). Samples were photographed in situ and coral morphology and the surrounding environment and habitat of the collected soft corals were recorded on an underwater slate. The samples were collected by means of a scalpel or a pair of scissors. Four independent colonies were sampled underwater from each species, three of which were used for diversity analysis and the remaining one for identification. Samples were collected in 50 mL Falcon tubes filled with seawater and transported immediately to the laboratory. Soft coral samples collected for identification were fixed with 70% ethanol as a preservative. Once arrived at the laboratory, diversity analysis was performed after smooth washing with double-distilled water to remove loosely attached bacteria and kept at −20°C for DNA extraction purposes. For identification, corals were fixed in 4% formalin in seawater for 24 h before rinsing in fresh water and then kept in 70% ethanol as a final preservative. Sodium hypochlorite was used to dissolve tissues, and the remaining sclerites were carefully rinsed with double-distilled water. The collected soft coral species were identified at the Red Sea Research Center, King Abdullah University of Science and Technology, Harvey Mudd College, USA and Marine Science Department, Suez Canal University, Egypt via adaptive methodology from Lieske and Myers, Rohwer et al. and Pollock et al. [12,17,18,21]. Small squares of approximately 1 cm were cut from the colony with a scalpel and mounted on a glass slide with 2 drops of bleach. Once the bubbles have ceased, the sclerites were spread out by stirring, and the specimen was examined under a light microscope (Olympus CH20, 100× and 400× magnification).

Figure 1. A geographical map showing the sampling sites for the four soft corals along Al Rayyis White Head (Red Sea, KSA).

Table 1. Sampling sites for the dominant soft corals at Al Rayes White Head point.

Sample ID	Location	Coordinates	Identification	Temperature (°C)	Salinity (%0)
RWH1	L1	23°31'42.5"N 38°34'07.7"E	Litophyton sp.	26.1	37.4
RWH2	L2	23°31'55.7"N 38°33'35.1"E	Sinularia sp.	26.3	37.6
RWH3	L3	23°32'14.8"N 38°33'00.9"E	Xenia sp.	27	37.2
RWH4	L4	23°32'27.3"N 38°32'36.6"E	Sarcophyton sp.	26.6	37.1

2.2. Genomic DNA extraction

Frozen samples were thawed and tissues were broken down into small pieces and macerated at room temperature. DNA was isolated from three colonies of the same species and then pooled before diversity analysis. Total bacterial community DNA was extracted from macerated tissues using an Ultra Clean Soil DNA purification kit (Mo Bio Laboratories, Solana Beach, CA, USA). About 1.0 g of macerated tissues was transferred to bead-beating tubes and vortexed horizontally for 2 min at room temperature. DNA was extracted, precipitated and purified according to the manufacturer’s instructions. The purity and concentration of extracted DNA were checked using a NanoDrop Spectrophotometer (Thermo Fisher Scientific).

2.3. PCR amplification of bacterial 16S rRNA genes

The V3–V4 hypervariable regions of bacterial 16S rRNA genes were amplified using the universal primer pair 341F (CCTACGGGNGGCWGCAG) and 805R (GACTACHVGGGTATCTAATCC) [18,22–24]. The primers were synthesized with a specific Illumina overhang adapter. The PCR amplification was conducted at Macrogen (Seoul, Korea) and according to the Illumina 16S Metagenomic Sequencing Library protocols (www.illumina.com). The PCR amplification was conducted in a thermal cycler as follows: 1 cycle of 95°C for 3 min as initial denaturation; 25 cycles of 95°C for 30 s, 55°C for 30 s and 72°C for 30 s and a final extension of 72°C for 5 min. Amplicons were electrophoresed on 1% agarose gel and visualized using a UV transilluminator.

2.4. Illumina amplicon sequencing and data analysis

The amplified 16S rRNA genes were then sequenced on the MiSeq Illumina platform using 2 × 300 pair-end technology. The Fast Length Adjustment of Short Reads (FLASH; V1.2.11) pipeline [25] was used for merging pair-end reads. Raw sequence filtering and trimming followed by error-sequence picking were done by CD-HIT-OUT software [26]. Identification of Operational Taxonomic Units (OTUs) was also done using CD-HIT-OUT software at a 97% sequence similarity cutoff value. Taxonomic composition from phylum to genus level for sequences of each sample employed in this study was conducted by Quantitative Insights into Microbial Ecology QIIME UCLUST pipeline [27] using the Ribosomal Database Project (RDP) (https://rdp.cme.msu.edu/) as a reference database. OTUs were then annotated and clustered based on 97% sequence similarity. All sequences obtained in this study were deposited into the NCBI database and are available under BioProject accession number PRJNA892143.

2.5. Microbiota diversity analysis

For a given sample (microbiota), alpha-diversity indices (Chao1, Shannon, inverse Simpson and Good's coverage) were calculated using QIIME software [28]. The Chao1 index estimates the richness (number of OTUs) of a given community by considering rare OTUs (singletons and doublets). Shannon and Inverse Simpson indices estimate species richness (number of OTUs) and species evenness (relative abundance), respectively. The Good’s coverage reflects how well the obtained sequences represent the environment. Alfa refraction curves were generated using QIIME software [28] and were employed to determine whether the sequence number was sufficient for OTU identification. Beta-diversity, represented by a principal coordinate analysis (PCoA) plot, was employed to evaluate the variations across the samples (or microbiotas). PCoA plot was conducted using QIIME software [28] based on weighted UniFrac metrics.

3. Results

3.1. Soft corals of Al Rayyis White Head, Red Sea, KSA

Four dominant soft corals designated RWH1 to RWH4 were collected for Al Rayyis, White Head beach and identified according to established identification schemes. RWH1 was characterized as a smooth flowery soft coral with bushy colonies of about 6–12 cm long. The colony has numerous fat cylindrical stems with short widely-spaced branches and embedded sclerites in the tissues. Tiny polyps with eight beige or brown branched tentacles are clustered along the side branches. RWH1 was identified as Litophyton sp, a genus of the family Nephtheidae (Figure 2(a)).

Figure 2. Collected soft corals endogenous to the eastern Red Sea side at Al Rayyis White Head, KSA.

RWH2 was characterized as soft coral that forms large colonies of large branching stalks with a height up to 30 cm. The lectotype is about 12 cm high and 8 cm wide with primary lobes that give off short finger-like lobules up to 1 cm long from which the name finger leather coral was derived. RWH2 was identified as Sinularia sp., a species of soft coral belonging to the family Alcyoniidae (Figure 2(b)).

RWH3 was characterized by a thick club-shaped colony forming a mushroom-like structure with branches resembling arms emerging from the top and end in many sub-branches resembling fingered hands. Densely dotted with smaller star-shaped polyps are carried on stalks. Long tentacles with many short thin row-shaped pinnules were detected. RWH3 was identified as Xenia sp., a genus of soft marine corals belonging to the family Xeniidae (Figure 2(c)).

RWH4 was characterized by a soft-skinned colony usually referred to as toadstool leather corals covered with numerous polyps all over its skin. It has a single stalk with a broadening smooth and folded top. It has eight tentacles and eight mesenteries on its polyps. It does not have a calcified skeleton structure. RWH4 was identified as Sarcophyton sp., a genus of soft corals in the family Alcyoniidae (Figure 2(d)).

3.2. Soft corals associated with bacterial microbiotas

In this study, the bacterial microbiotas associated with four soft coral genera located at the central Red Sea were screened and identified using Illumine Miseq sequencing approach of 16S rRNA genes. The refraction curves of the four microbiotas using observed OTUs (Figure 3(a)) and Chao1 index (Figure 3(b)) reached a plateau and showed a good depth of sample coverage. This indicates that the number of reads employed in OTUs identification was sufficient. Illumine Miseq sequencing yielded after the elimination of low-quality sequences 210,063 reads for the four microbiotas ranging from 49,828 to –54,442 (Table 2). Moreover, the Good’s coverage values ranged from 0.99% to 1.00%, indicating that the sequencing was sufficient for undergoing reliable microbial composition analysis. A total of 274 OTUs, ranging from 10 to 109, were produced from clustering of all yielded reads in this study at a 97% sequence similarity threshold.

Figure 3. Refraction curves for the four soft coral-microbiomes identified in this study using observed OTUs (a) and Chao1 index (b).

Table 2. Numbers of sequences, OTUs, chao1 index and Good's Coverage of bacteria associated with the four soft corals in this study.

	Diversity analysis
Soft corals	Read count	GC (%)	OTUs	Chao1	Good's coverage
Litophyton sp.	52,307	53.22	59	59	1.0
Sinularia sp.	53,486	55	10	10	0.99
Xenia sp.	49,828	52.49	109	109	0.99
Sarcophyton sp.	54,442	53.75	96	96	0.99

The microbiota of Litophyton sp was first described in this study. Assignment of bacterial reads at the phylum level (Figure 4(a)) indicated the predominance of Proteobacteria (ranged 85-100% of total sequences) in all microbiotas obtained in this study. Next to Proteobacteria, other phyla represented significantly (more than or equal to 1% of total sequences) were Bacteroidetes (1%) in Xenia sp. microbiota and Bacteroidetes (6%) and Firmicutes (6%) in Litophyton sp. microbiota.

Figure 4. Bacterial community composition associated with the four soft corals at phylum (a), family (b) and genus (c) level.

At the family level (Figure 4(b)), the microbiotas were dominated by families Hahellaceae (60.77%) and Anaplasmataceae (32.46%) in Xenia sp. microbiota, Enterobacteriaceae (78.8%) and unassigned (2.53%) in Sarcophyton sp. microbiota, Hahellaceae (79.31%), Staphylococcaceae (5.58%), Prevotellaceae (3.59%), Moraxellaceae (3.12%), Bacteroidaceae (2%) and unassigned OTU (1.51%) in Litophyton sp. microbiota and Pseudomonadaceae (97.33%) and Enterobacteriaceae (2.63%) in S. polydactyla microbiota. At the genus level (Figure 4(c)), it was noted that few genera comprise the majority of identified sequences in all microbiotas. S. polydactyla microbiota was largely predominated by Pseudomonas spp. (97.33%) followed by a small abundance of Salmonella (2.40%). In Sarcophyton sp. microbiota, the most abundant bacterial genera were Erwinia (78.77%), unassigned OTU (8.52%) and another unassigned OTU (2.53%). Microbiotas of Litophyton sp. and Xenia sp. revealed the predominance of the genus Endozoicomonas at 79.31% and 94.22%, respectively. Next to genus Endozoicomonas, other abundant genera were Staphylococcus (5.58%), Prevotella (3.59%), Enhydrobacter (1.62%), Maricurvus (1.51%) and Acinetobacter (1.50%) in Litophyton sp. microbiota and Anaplasma (32.46%) and unassigned OTU (11.56%) in Xenia sp. microbiota.

3.3. Microbiota’s diversity analysis

PCoA analysis indicated significant separation in the bacterial structure between the four microbiotas addressed in this study (Figure 5). PCoA plot showed that microbiotas of Litophyton sp. RWH1 and Xenia sp. RHW3 have clustered closer to each other and away from those associated with both Sinularia sp. RWH2 and Sarcophyton sp. RHW4. This pattern is compatible with the fact that the genus Endozoicomonas is the predominant genus in both microbiomes at 49 and 79% abundance levels in Litophyton sp. RWH1 and Xenia sp. RHW3, respectively. Alpha-diversity estimates at the 97% OTU level revealed a higher number of OTUs in Litophyton sp. RWH1 and Xenia sp. RHW3 followed by Sarcophyton sp. RHW4 than those observed in Sinularia sp. RWH2 showed the least number of OTUs (Figure 6). Shannon and Inverse Simpson indexes showed higher diversity for Litophyton sp. RWH1 and Xenia sp. RHW3 microbiotas compared to the slightly diverse microbiota of Sarcophyton sp. RHW4. Sinularia sp. RWH2 microbiota showed the lowest diversity indices compared with other microbiotas in this study which indicated less richness and less diversity. The richness and relative abundances of bacteria associated with the four soft corals at the genus level (Figure 7) revealed a significant variation among the four investigated soft corals. This indicates that each soft coral is likely to harbour-specific microbiota that would play key roles in health and immunity of corals.

Figure 5. Principal coordinates analysis (PCoA) plot showing clustering of the four microbiomes obtained in this study between the four microbiomes. The plot was performed based on weighted UniFrac distances.

Figure 6. Shannon and Inverse Simpson indexes observed for the four soft coral-microbiomes identified in this study.

Figure 7. Heat map showing the relative abundances of the bacteria associated with the four soft corals at the genus level.

4. Discussion

The Red Sea is a distinctive and broadly undiscovered marine habitat [13,17,18] that harbours a wide variety of stony and soft corals. Upon investigating Red Sea corals, much attention has been obviously given to stony corals as compared to soft ones. In this study, the microbiotas of four soft coral genera collected from the central Red Sea were explored. The exploration was conducted using the NGS platform, Illumina Miseq, as it was proven to give better diversity data than traditional methods, e.g. DGGE. To the best of our knowledge, this is the first time to identify the microbiota associated with the soft coral Litophyton sp.

Phylum Proteobacteria was the most abundant in the microbiota of the four corals which is in line with the data obtained from the previous studies [13]. Microbiota associated with the coral genus Sarcophyton showed the highest number of phyla (11 phyla) while the coral genus Sinularia showed the lowest number of bacterial phyla (1 phylum). It was reported that the reduction in coral microbiota is of adverse impact on coral holobiont immunity. Reduction in coral microbiota was recorded before the development of white syndrome signs on coral holobiont [21]. This reduction could be attributed to anthropogenic disturbances and/or nutrient enrichment. Consequently, it was suggested that the existence of only a single Phylum (Proteobacteria) in the Sinularia microbiota might reflect a future negative impact on coral holobiont due to human activities at the site from which the corals were collected.

The opportunistic families Rhodobacteraceae and Vibrionaceae were detected as minor populations (<1%) in the microbiota of coral genera Xenia sp. and Sarchophyton. The detection of these potential pathogenic bacterial families was returned before [20] to the impacts of anthropogenic pollution. Wastewater from Yanbu industrial city, just a few kilometres from the coral samples collection sites in this study, is assumed to be discharged in the Red Sea. In addition, further classification for the family Vibrionaceae at the genus level revealed the presence of the genus Vibrio sp. in. The genus Vibrio sp. causes coral bleaching and is thus considered pathogenic.

On the other hand, beneficial bacterial taxa were also detected in microbiotas obtained in this study, as exemplified by the detection of the genus Endozoicomonas. The genus Endozoicomonas was reported as a major population in microbiotas associated with coral genera Xenia and Litophyton. The genus also was detected as a minor population (<1%) in microbiotas of the other two coral genera. The genus is commonly detected in coral halobiont and its presence is considered an indicator of healthy coral. Specifically, the genus serves the coral host by preventing mitochondrial dysfunction of the coral and sharing in the coral carbohydrate and protein cycling [29,30]. Planctomycetes and Verrucomicrobia represent other examples of beneficial bacteria detected in this study. Many members belonging to both phyla have great potential for many biotechnological and industrial applications including the production of bioactive substances and antibiotics, bioremediation and removal of unwanted ammonium during wastewater treatment [31]. In 2017 using culture-independent molecular techniques, it was reported that [32] all novel species of Planctomycetes and Verrucomicrobia have secondary metabolites genes. Moreover, Graca and co-workers [33] showed the presence of one or two classes of secondary metabolites genes in 95% of the screened Planctomycetes. The study also indicated that about half of the obtained Planctomycetes extracts showed antimicrobial activity [33]. The genus Erwinia, which was identified in this study as the predominant genus in the Sarcophyton microbiota, was previously identified among the cultivable protease-producing bacteria accompanying scleractinian corals [34]. Protease-producing bacteria play an essential role in marine habitats by degrading organic nitrogen into easily accessible amino acids and peptides [35]. The genus Pseudomonas detected as the major genus prevailing the microbiota of Sinularia sp. was isolated before from the soft coral Sinularia [36]. In the same study, the isolated Pseudomonas showed an antibacterial against Streptococcus equi. The genus Anaplamsa, the second major genus in Xenia microbiota, was identified before as a part of the reef coral Mussismilia microbiota [37]. The genus was reported among the obligate endosymbionts bacteria which are characterized by a reduced genome carrying only genes to serve the host [38,39].

5. Conclusion

In this study, bacterial communities associated with four Red Sea dominant soft corals, Litophyton sp., Sinularia sp., Xenia sp. and Sarcophyton sp at Al Rayyis White Head, KSA were investigated. Coral-associated microbiotas showed a higher bacterial diversity. Diversity analysis indicates higher species richness and diversity in Litophyton sp. and Xenia sp. compared to Sarcophyton sp. and Sinularia sp. Additionally, significant variation in bacterial community structure, among the four investigated soft corals, indicates that each soft coral is likely to harbour-specific microbiota that would play key roles in the health and immunity of corals.

Detection of Endozoicomonas in Xenia and Litophyton microbiotas indicates a healthy coral status as well as their roles in coral carbohydrate and protein cycling. Specifically, genus Anaplamsa, the second major genus in Xenia microbiota was reported among the obligate endosymbionts bacteria. This may indicate the importance of such a genus to nitrogen cycling. Furthermore, the detection of Rhodobacteraceae and Vibrionaceae reflects the anthropogenic pollution by wastewater from nearby industrial activities. Beneficial bacteria, which have great potential for many biotechnological and industrial applications belonging to Planctomycetes and Verrucomicrobia, were also detected. Members belonging to both phyla were reported as potential producers of bioactive substances and antibiotics. Moreover, they were found to have a role in bioremediation and removal of ammonium from wastewater. Particularly, these bacteria could be targeted in the future study.

Acknowledgement

The authors are thankful to Dr. Rafat Afif, director of the marine science department, at Suez Canal University, Ismailia, Egypt, Dr. Michael Berumen, marina science director, Red Sea research center, Dr. Francesca Benzoni at King Abdullah university of science and technology, Dr. Cathy McFadden, Department of Biology, Harvey Mudd College, Claremont, USA for their assistance in identifying the soft corals.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Taibah University.