The gut microbiome of healthy and moribund orange-spotted groupers reveals specialised metabolite profiles and potential beneficial species: A case study in Malaysian fish farm

doi:10.21203/rs.3.rs-3423006/v1

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The gut microbiome of healthy and moribund orange-spotted groupers reveals specialised metabolite profiles and potential beneficial species: A case study in Malaysian fish farm

https://doi.org/10.21203/rs.3.rs-3423006/v1

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The gut microbiome of carnivorous fish evolves in tandem with the host to adaptively increase the host fitness in a dynamically-changing environment. In order to identify the beneficial strains in supporting the survival of orange-spotted grouper, Epinephelus coioides in a culture environment, the foregut, midgut and hindgut were analysed in three healthy and two moribund individuals. This study was conducted in the Merbok River, northwest Peninsular Malaysia which is exposed to some degree of pollution. The 16S amplicon sequencing targeting the V3-V4 highly variable region revealed similar community richness among samples but compositional and functional differences between the healthy and moribund fishes in the three gut regions. The findings showed a higher abundance of beneficial microflora, including Halomonas, Curvibacter and Bacillus residing in healthy foreguts, coupled with elevated activities of aromatic compound degradation. In the midguts, more than 70% of microbiota comprised of Photobacterium and Vibrio in most specimens. The higher abundance of Vibrio and Photobacterim in moribund fish hindguts may be correlated with increased chitinolytic activity and altered metabolic pathways. The outcomes of the study provide a fundamental understanding of the gut microbiota structure and suggest the potential use of Halomonas, Curvibacter and Bacillus in the orange-spotted grouper survival in a polluted environment.

aquaculture

fish

probiotic

next generation sequencing (NGS)

intestinal

The orange-spotted grouper, Epinephelus coioides, is an important cultured marine fish in China and Southeast Asian countries for its fast growth performance and huge commercial value due to its high nutritional value and delicate taste (Huang et al., 2011; Yu et al., 2018). Regarded as one of the most favourite seafoods, the aquaculture industry of this teleost species has become widely expanded to meet the high market demand. However, the rapid development of intensive aquaculture activities exposes the groupers to various stressors, such as crowding and handling, potentially increasing susceptibility to diseases, threatening the grouper aquaculture industry (Harikrishnan et al., 2011).

Recent research has shown that the balance of gut microbiota composition generates related metabolites that have a diverse impact on many facets of host health and welfare, including digestion and nutrient uptake, metabolism, immune growth and defence systems against pathogens (Nie et al., 2017; Yukgehnaish et al., 2020). An impaired composition of gut microbiota could increase the host susceptibility against bacterial diseases (Hasan & Yang, 2019). In contrast to human and warm-blooded animals, the functions of gut microbiota in fish are poorly known. The fish gut is a complex ecosystem, colonized by particular microbiota including aerobes, facultative anaerobes and obligate anaerobe bacteria (Wang et al., 2018). This microbial composition may be modulated by multiple factors such as age, species, genetic background, nutritional status, diet and environmental conditions (Butt & Volkoff, 2019). Therefore, knowledge of intestinal microbiota is of great importance for disease prevention and for the production of healthy growth in cultured fish.

Merbok River has been known to host various aquaculture activities, including the farming of orange-spotted groupers (Ng et al. 2023) and oysters (Lim et al. 1995). The river was classified as heavily-polluted since decades ago (Lim et al. 1995), and the condition has not improved (likely worsened), a consequence of anthropogenic activities at the upper catchment and weathering (Ismail and Ibrahim 2015; Msahir Atshan et al. 2020; Zulkifli 2022). In this present study, we investigated the potential role of the gut microbial community in the survival of adult orange-spotted groupers reared in a commercial estuarine facility in the Merbok River. Two moribund and three healthy individuals were assessed for differences (if any) in the microbiome of their foregut, midgut and hindgut. The findings provide insights into identifying the potential beneficial strains that improve host resistance in surviving polluted environments.

Fish intestine sample collection

Five adult specimens from a local fish farm in Merbok, northwest Peninsula Malaysia (5.684035, 100.469320), were sampled in December 2019 (Fig. 1a). All fish were assessed physically and two specimens (M1, M2; n = 2) were characterised as moribund based on commercial grading by local fish farmers, i.e. sluggish with white skin patches and lesions (Fig. 1b-c). Healthy fish (H1, H2, H3; n = 3) showed normal activities without any skin condition. Each individual was euthanised by standard procedures with 100mg/L of MS-222 (Sigma, USA) and dissection was performed after 10 min of inactivity. The foregut (f), midgut (m) and hindgut (h) tissues were collected and preserved in RNAlater® (Thermo Fisher, USA). The specimens were kept in -80℃ until further use.

Genomic extraction

The total DNA was extracted following conventional phenol-chloroform extraction protocol. Each gut tissue specimen (1 cm³) was cut into small pieces and separately homogenized in 300 µL of TE buffer (pH 8.0). The tissue-containing buffer was boiled for 5 min and 300 µL of phenol was added after the buffer cooled to room temperature. The solution was mixed vigorously and centrifuged at 12,000 × g for 5 min. The supernatant was mixed with an equal volume of chloroform and centrifuged at 12,000 × g for 1 min. The upper aqueous layer was collected and mixed with 2× volume of absolute ethanol. The mixture was spun at 12,000 × g for 15 min and supernatant was discarded. The DNA pellet was washed with 70% ethanol. The DNA pellet was then air-dried and rehydrated in 50 µL of TE buffer (pH 8.0), and stored in ˗20 ℃ until further use.

16S rRNA gene amplicon sequencing

The V3-V4 variable region of 16S rRNA gene was amplified using degenerate primer pair, 341F (5’-CCTAYGGGRBGCASCAG-3’) and 806R (5’-GGACTACNNGGGTATCTAAT-3’) containing 8 bp sequence unique barcodes. The PCR reaction mixture consists of 1× TransStart® FastPfu buffer, 5 mM dNTPs, 4 µM of each forward and reverse primer, 1 U of TransStart® FastPfu DNA Polymerase (TransGen, China) and 10 ng or DNA template. The PCR was performed as follows: initial denaturation at 95 ℃ for 2 min, followed by 25 cycles of 95°C for 30s, 55°C for 30 s and 72°C for 30 s, and a final extension at 72°C for 5 min. The PCR amplicons were purified by AxyPrep DNA Extraction kit (Axygen Biosciences, USA) and quantified using QuantiFluor™ ST (Promega, USA). The purified amplicons were then paired-end sequenced on Illumina MiSeq platform to generate 250bp reads.

Bioinformatic data analysis

The raw paired-end reads were imported and processed in QIIME pipeline (v1.9.1). The raw reads were merged into raw tags using FLASH (Magoč and Salzberg 2011) and quality-filtered by Trimmomatic (Bolger et al. 2014). Chimeric sequences were identified and removed by UCHIME (Edgar et al. 2011) to obtain effective tags. Effective tags with ≥ 97% similarity were clustered into the same operational taxonomic unit (OTU) with UPARSE (v7.1)(Edgar 2013). The taxonomic assignment was conducted by RDP Classifier (http://rdp.cme.msu.edu/) against the public databases, including SILVA (SSU123) (Quast et al. 2012), RDP (Cole et al. 2009) and Greengenes (DeSantis et al. 2006) with confidence threshold set at 0.7. The alpha diversity indices (Chao, Ace, Shannon and Simpson), sequencing depth index (the Good’s coverage) and the rarefaction curve were generated by MOTHUR (Schloss et al. 2009). The microbial composition was analysed at phylum and genus levels. Unweighted and weighted UniFrac Principal Coordinate Analysis (PCoA) was used to compare the microbial community composition of the healthy and moribund groups in different gut sections. The functional profiling of the microbial community was predicted by PICRUSt2 (Douglas et al. 2020). Significant difference was flagged by the Tukey-Kramer post hoc test at p value < 0.05 with STAMP (Parks et al. 2014).

Fish gut microbiome complexity

A total of 15 datasets containing bacterial V3-V4 region of the 16S rRNA gene were obtained from three gut sections (foregut, midgut, and hindgut) of five fishes (three healthy and two moribund). The number of reads from each of the 15 samples ranged between 50,794 to 74,515, comprising a total of 591 identified OTUs that were classified into 23 bacterial phyla. The community richness and diversity indices (Table 1) in both experimental groups were not significantly different, implying that the gut microbial complexity in the three gut sections were similar. The Good’s coverage of all samples was above 0.99 and the rarefaction curve of all specimens were saturated (Supplementary Fig. S1), indicating sufficient sequencing depth for all libraries (Table 1).

Table 1

An overview and alpha-diversity indices in foregut, midgut and hindgut samples of healthy and moribund experimental groups.
Section	Group	Replicate	Read	Good’s coverage	Community Richness		Community Diversity
Section	Group	Replicate	Read	Good’s coverage	OTU	Chao1	Shannon	Simpson
Foregut	Moribund	M1-f	72228	0.9998	184	199	1.88	0.349
	Moribund	M2-f	53333	0.9996	144	160	2.57	0.1428
	Healthy	H1-f	69568	0.9998	168	183	2.01	0.3708
		H2-f	50169	0.9998	246	250	3.55	0.0577
		H3-f	73904	0.9999	155	161	2.55	0.1373
Midgut	Moribund	M1-m	73803	0.9994	127	177	1.26	0.4914
	Moribund	M2-m	63624	0.9994	132	165	1.87	0.298
	Healthy	H1-m	68759	0.9998	196	215	2.8	0.1559
		H2-m	55153	0.9996	150	159	1.55	0.4217
		H3-m	56944	0.9992	143	202	1.91	0.3148
Hindgut	Moribund	M1-h	70798	0.9995	141	159	2.45	0.1443
	Moribund	M2-h	66356	0.9998	126	141	2.56	0.1712
	Healthy	H1-h	56819	0.9999	95	97	2.49	0.1235
		H2-h	72577	0.9998	122	140	1.48	0.4713
		H3-h	57764	0.9998	206	210	1.99	0.3372

Microbial community in fish gut

The qualitative (unweighted) PCoA plot demonstrated that the H and M specimens did not form distinct clusters, except for H1-foregut and M2-midgut (Fig. 2a), which suggests most OTU were shared between the two groups. However, quantitative (weighted) comparison of microbial community composition in 15 gut specimens showed that most specimens did not cluster together with their own biological replicates (Fig. 2b). Thus, the findings cued, that while the residing microbial species were common between groups, their abundance was unique in each group.

A total of 23 bacterial phyla were identified from the 15 gut specimens combined, with Proteobacteria, Actinobacteria, Tenericutes, Cyanobacteria, Acidobacteria, Firmicutes, Fusobacteria, Bacteroidetes, Deinococcus-Thermus and Dependentiae being the ten most abundant phyla (Fig. 3). In the foregut, Proteobacteria is the most dominant phylum in both groups (Fig. 3a). Actinobacteria and Cyanobacteria were richer in healthy fishes than in moribund fishes. Proteobacteria remains the most abundant phylum in the midgut of all fishes (Fig. 3b). Except for specimen H1-hindgut, Firmicutes was the most dominant phylum in the hindgut of healthy group, followed by Proteobacteria. On the other hand, Proteobacteria was the most dominant phylum, followed by Actinobacteria and Bacteroidetes in N1-H. In the hindgut of moribund fishes, the abundance order was Proteobacteria > Firmicutes > Fusobacteria, but Fusobacteria was barely detected in healthy samples (Fig. 3c)..

A total of 365 genera were identified in the 15 gut specimens, where the less abundant genera (ranked above 30) were categorized as “Others” (Fig. 4, Supplementary file 1) with genera Nesterenkonia, Halomonas, Shewanella and Curvibacter more abundant in healthy foreguts than in moribund (Fig. 4a). Vibrio was quantitively higher in moribund foreguts than in healthy foreguts. The minor genera Chelativorans, Yangia, Oceanobacterium, Vibrioimonas, Rhodococcus and Brevundimonas were found only in healthy foreguts but not in moribund foreguts. In the midgut, > 70% of the microbial community were attributed to genera Photobacterium and Vibrio, except for H1-midgut (Fig. 4b). It is worth noting that three minor genera, Neorickettsia, Escherichia-shigella and Oceanirhabdus were only found in moribund midguts, and NS9 marine group only inhabit healthy midguts. In healthy hindgut (Fig. 4c), Bacillus accounted for more than 50% of the microbial community except in H1-hingut, where Halomonas was the most dominant genus, coupled with the distinct occurrences of minor genera such as Sphingomonas and Vermiphilaceae_norank. Meanwhile, Photobacterium remained as the most abundant genus in moribund midguts with unique presences of several minor genera, including Epulopiscium, Oceanirbiabdus, Gammaproteobacteria and the Clade Ia.

Predictive -functional profiles of gut microbial community

Comparison of fish gut microbiome functional profiles between healthy and moribund fishes revealed 15, six and 28 significantly distinct functions in the foregut, midgut and hindgut, respectively (p < 0.05) (Fig. 5). Multiple degradation pathways of aromatic compounds were more active in healthy foreguts, including catechol degradation, 4-methylcatechol degradation (ortho cleavage), aromatic compounds degradation via β-ketoadipate, phenylacetate degradation I (aerobic), superpathway of phenylethylamine degradation, superpathway of salicylate degradation and toluene degradation III (aerobic) (via p-cresol) (Fig. 5a). The tRNA charging activity seems to be slightly more active in moribund midguts. It is worth noting that three pathways, L-rhamnose degradation II, superpathway of L-threonine metabolism and superpathway of L-tryptophan biosynthesis were not detected in healthy midguts (Fig. 5b). Meanwhile, microbial communities that carry out energy-related metabolisms, such as TCA cycle VII and VIII, aerobic respiration I and various amino acid biosynthesis pathways were way more abundant in healthy hindguts, whereas in moribund hindguts, carbohydrate degradation and lipid biosynthesis were more active (Fig. 5c).

Gut microbial communities are known to influence the physiology of the host fish, including the general health, immune responses, feeding, digestive system and metabolism (Liu et al. 2016; Butt and Volkoff 2019; Yukgehnaish et al. 2020). Their association with the fitness of host fish has been previously reported in various fish species, including damselfish and cardinalfish (Parris et al. 2016). Besides that, fish are free-living aquatic organisms, where the microbial composition is believed to shift and evolve along with the host in order to adapt to the dynamically changing water conditions (Sullam et al. 2012).

In the present study, we explored the microbial diversity in different gut sections, as each section plays specialised functional roles, which contention made upon the unique cell structures (Salleh et al. 2019) and gene expression profiles (Martin et al. 2016) in these gut sections. Foregut and midgut are where enteric digestions occur while the hindgut, with its larger lumen is important for enteric immune functions (Buddington et al. 1997; Egerton et al. 2018; Salleh et al. 2019). Thus, the microbial compositional differences among these gut locations revealed in the present study were presumably due to gut functional division, as described in the rainbow trout (Betiku et al. 2023). However, irrespective of the health state, the most abundant phyla in all gut sections were Proteobacteria, Actinobacteria, Firmicutes, Fusobacteria and Tenericutes, known to be the persistent groups in fish gut (Wang et al. 2018).

This study found that Halomonas colonization was higher in healthy foreguts than in moribund groupers. Protease-producing strains, such as Halomonas, are particularly important in supporting high trypsin activity in carnivorous fish (Liu et al. 2016). Higher abundance of Halomonas residing in healthy foreguts, implies better protein-digesting processes in healthy orange-spotted groupers. The findings also revealed multiple aromatic compound degradation pathways and higher abundance of Curvibacter in healthy foreguts. Curvibacter genus is composed of anaerobic bacteria that are involved in the degradation of aromatic compounds and was widely studied for its application in bioremediation (Muratçobanoğlu et al. 2020). In this case, Curvibacter is potentially beneficial in enhancing host tolerance by removing the aromatic pollutants. This finding may push the boundaries of possibility to the use of Curvibacter in supporting the aquaculture activities, especially in waters of developing countries that are heavily polluted by aromatic compounds, such as Yellow River (Li et al. 2006), Tianjin rivers (Shi et al. 2005), Jiulong River Estuary and Western Xiamen Sea in China (Maskaoui et al. 2002), as well as Soltan Abad River, Iran (Kafilzadeh 2015) and Meliane river, Tunisia (Khabouchi et al. 2020).

Hindgut is considered a vital structure in fish immunity (Salleh et al. 2019). Healthy hindguts with a significantly higher abundance of Bacillus strains, may indicate its involvement in regulating host gut health, as in the Nile tilapia (Kuebutornye et al. 2020). Bacillus was previously found to only inhabit in the gut of fast-growing groupers (Sun et al. 2009) and its various enzyme and antimicrobial activities successfully ameliorated intestinal damage in trout (Yamamoto et al. 2010; Abriouel et al. 2011). Furthermore, inclusion of host-associated Bacillus spp. in the diet greatly enhanced mucosal immunity and tolerance of Nile Tilapia towards pathogen infection (Kuebutornye et al. 2020).

There was higher abundance of Fusobacteria residing in moribund hindguts. This gut microbiota is deemed invasive and is often associated with a number of diseases in other animal models (Swidsinski et al. 2011; Chun et al. 2020). As Fusobacteria appeared as a common persistent microbiota in fish guts of both groups, as well as in other fish species (Yukgehnaish et al. 2020), it is unlikely linked to the poor health state of moribund groupers in this study. Meanwhile, the higher abundance of Vibrio and Photobacterium in moribunds could be correlated with significantly increased degradation of chitin derivatives in moribund hindguts. Both are pathogenic chitinolytic bacteria (Hunt et al. 2008) in aquaculture and past evidences showed that increased Vibrio and Photobacterium may disrupt gut ecological balance, reduced the dominance of beneficial microflora and alter gut-microbiota-mediated functions in groupers (Sun et al. 2009; Deng et al. 2020; Liu et al. 2020). This is reflected in our study, as the moribund hindguts were found with enhanced lipid metabolisms, coupled with reduced metabolisms of energy, carbohydrate and protein (Fig. 5c).

In conclusion, our study reveals that corresponding with other investigations in other grouper species (Sun et al. 2009; Deng et al. 2020; Liu et al. 2020), gut microbiota changed dynamically and reflected the health state of farmed orange-spotted grouper, E. coioides. A number of microbial genera, including Halomonas, Curvibacter and Bacillus are potentially beneficial gut microbiome that could be developed into a probiotic in the aquaculture industry to enhance the general health and pollution tolerance of host fish, in particular, the future prospects in using Curvibacter to support the aquaculture water bodies with aromatic pollutants. The abundance of Vibrio and Photobacterium may impact the gut ecological balance and hence the metabolic stability. However, the functions of unique although minor microbiota in these gut regions could not be elucidated due to limited available data, but we believe they may play critical roles in maintaining gut health. Despite the low number of moribund fishes sampled in this study, the findings parallel previous studies and could serve as a good metric of data validity. Even so, we strongly recommend the inclusion of higher number of biological replicates in future studies.

Acknowledgements

We thank Universiti Malaysia Terengganu for providing funding support for this project (UMT/SRG/2018/53280) and Manjung Prawn Hatchery for sharing commercial data collection.

Data availability statement

Raw data not available due to commercial restrictions. The processed data that support the findings of this study are available on reasonable request from the corresponding author, MDD.

Disclosure statement

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

Contributions

Conceptual design: MDD, SAMN. Financial acquisition: SAMN, MPT. Specimen collection: MEMN and SKN. Data analysis: CCL, MDD. Manuscript writing: CCL, NAA. Manuscript revision: SAMN, MPT, NAA, LLW, MBM. Supervision: MDD, SAMN and YYS.

Ethics declarations

The handling of animals complied with the ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) and was approved by the Institutional Animal Care and Use Committee (IACUC) of Universiti Malaysia Terengganu.

ORCID

Cher Chien Lau: http://orcid.org/0000-0001-6551-2603

Siti Azizah Mohd Nor: https://orcid.org/0000-0002-9890-9612

Nor Afiqah-Aleng: https://orcid.org/0000-0003-0919-5126

Min Pau Tan: http://orcid.org/0000-0003-0149-5247

Yeong Yik Sung: https://orcid.org/0000-0001-5897-9037

Li Lian Wong: https://orcid.org/0000-0001-9045-4556

Mohammad Bodrul Munir: https://orcid.org/0000-0003-1162-1702

Muhd Danish-Daniel: http://orcid.org/0000-0001-9438-0128

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No competing interests reported.

SupplementaryFig.S1.pdf
Fig. S1 : The rarefaction curve of all specimens.
SupplementaryFile1.xlsx
File 1 : The abundance of gut microbiota analysed at genus level.

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The gut microbiome of healthy and moribund orange-spotted groupers reveals specialised metabolite profiles and potential beneficial species: A case study in Malaysian fish farm

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Abstract

Figures

Introduction

Materials and method

Fish intestine sample collection

Genomic extraction

16S rRNA gene amplicon sequencing

Bioinformatic data analysis

Results

Fish gut microbiome complexity

Microbial community in fish gut

Predictive -functional profiles of gut microbial community

Discussion

Declarations

References

Additional Declarations

Supplementary Files

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Version 1