Fisheries and Aquatic Sciences
The Korean Society of Fisheries and Aquatic Science
SHORT COMMUNICATION

Comparison of gut microbiota composition of farmed olive flounder (Paralichthys olivaceus) according to growth stage

Su-Jeong Lee1https://orcid.org/0009-0006-3552-5992, Young-Sun Lee1https://orcid.org/0009-0001-4274-9330, Tae-Rim Kim1https://orcid.org/0009-0000-6460-4338, Eun-Woo Lee1,2https://orcid.org/0000-0003-4091-6606, Won Je Jang1,2,*https://orcid.org/0000-0002-2372-8366
1Department of Biopharmaceutical Engineering, Dong-eui University, Busan 47340, Korea
2Research Institute for Microbiology, Dong-eui University, Busan 47340, Korea
*Corresponding author: Won Je Jang, Department of Biopharmaceutical Engineering, Dong-eui University, Busan 47340, Korea, Tel: +82-51-890-1522, E-mail:wjjang@deu.ac.kr

Copyright © 2024 The Korean Society of Fisheries and Aquatic Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Feb 14, 2024; Revised: Mar 26, 2024; Accepted: Apr 12, 2024

Published Online: Aug 31, 2024

Abstract

The strategy of cultivating healthy fish by manipulating their gut microbiota composition using probiotics is crucial for establishing sustainable fish farms. Information on the gut microbiota composition of healthy fish is important for the efficient development of probiotics and the aquaculture strategies that would apply them. This study assessed the gut microbiota composition of farmed olive flounder according to the growth stage to provide useful information for the development of probiotics. The fish were classified according to their weight, and the intestines of five juveniles weighing less than 100 g and five subadults weighing between 400 and 800 g were used for analysis. The results of alpha diversity analysis confirmed higher richness and diversity in the subadult group than in the juvenile group. Beta diversity analysis revealed clear boundaries and distances between the groups; however, individuals within each group were similar. The two groups showed marked differences in their gut microbiota composition. Phylum-level analysis revealed that the most abundant phylum was Proteobacteria in the juvenile group and Firmicutes in the subadult group. Notably, genus-level analysis revealed that Vibrio accounted for more than 50% of the total composition in the juvenile group. Linear discriminant analysis effect size revealed that the genera Vibrio, Photobacterium, and Leuconostoc were representative of the juvenile group, whereas 19 genera, including Lactococcus and Vagococcus, were representative of the subadult group. Thus, information on the representative microorganisms abundantly present in the intestines of healthy olive flounder can be considered for the selection and development of a probiotic genus for olive flounder farming.

Keywords: Growth stage; Gut microbiota; Microbiome; Olive flounder; Probiotics

Introduction

Olive flounder (Paralichthys olivaceus) is one of the most farmed fish in South Korea. Its average production over the past five years (2018–2022) was 42,398 tons, accounting for 48.82% of the total production and making it a very important fish species at an industrial level (Statistics Korea, 2024). Although olive flounder aquaculture technology continues to develop, environmental destruction, the emergence of fish pathogens, and instability in fishmeal supply due to the depletion of marine fishery resources negatively impact olive flounder production (Hasan et al., 2018; Lee et al., 2024). In this situation, probiotics are attracting attention as microbial additives that can help build eco-friendly fish farms, improve fish immunity, and enhance the digestibility of low-fishmeal feed (Jang et al., 2023).

Probiotics are defined as live microorganisms that provide beneficial health effects to the host when supplied in adequate amounts (FAO/WHO, 2001). They are considered to aid digestion and absorption, stimulate immune cells, produce antibacterial substances to kill pathogens, and change the composition of the gut microbiota to a healthy one (Jang et al., 2021; Nawaz et al., 2018; Nayak, 2010). However, most probiotics applied to fish so far are lactic acid bacteria of terrestrial origin (Jang et al., 2023; Van Doan et al., 2020). The concept of host-associated probiotics has recently been reported, and attempts have been made to use microorganisms isolated from the intestines of fish as probiotics (Jang et al., 2021, 2022, 2023; Van Doan et al., 2020). However, lactic acid bacteria have also been mainly isolated and targeted for use as probiotics (Cathers et al., 2022; Kader et al., 2021). In fact, lactic acid bacteria, such as Lactobacillus and Lactococcus, are considered beneficial for humans and animals (Jang et al., 2024). However, whether lactic acid bacteria are the optimal probiotic candidates for fish, which have different gut microbiota compositions from humans, remains questionable (Jang et al., 2023; Van Doan et al., 2020). Moreover, the growth temperature of most lactic acid bacteria is similar to the human intestinal temperature. However, because the intestinal temperature of fish is relatively low, it may not be an optimal environment for lactic acid bacteria. Hence, to develop appropriate probiotics, it is important to know the gut microbiota composition of healthy fish.

This study therefore assessed the gut microbiota composition of farmed olive flounder. Gut microbiota analysis was performed by dividing the fish into growth stages according to their weight. Moreover, the microbial composition, relative microbial abundance, and representative microorganisms at each stage were investigated.

Materials and Methods

Sample collection and DNA extraction

Ten farmed olive flounders were provided by the Aquafeed Research Center of the National Institute of Fisheries Science (Pohang, Korea). The fish were weighed and divided into a juvenile group weighing less than 100 g and a subadult group weighing between 400 and 800 g (Niu et al., 2020). Then, the intestines of all the fish were aseptically separated. All contents present in the isolated intestines were collected, and the total bacterial DNA in the intestinal contents was isolated using the ZymoBIOMICS DNA Miniprep Kit (Zymo Research, Irvine, CA, USA), according to the manufacturer’s instructions.

Sequencing

The V3–V4 region of the 16S rRNA sequence was amplified from the total DNA of the isolated microorganisms using the forward primer 5′-TCGTC GGCAG CGTCA GATGT GTATA AGAGA CAGCC TACGG GNGGC WGCAG-3′ and the reverse primer 5′-GTCTC GTGGG CTCGG AGATG TGTAT AAGAG ACAGG ACTAC HVGGG TATCT AATCC-3′. PCR was performed with a Veriti 96-well thermal cycler (Applied Biosystems, Foster City, CA, USA) at the Core Facility Center for Tissue Regeneration, Dong-eui University (Busan, Korea). Moreover, 16S rRNA gene amplicon libraries for sequencing were prepared according to the method described in 16S Metagenomic Sequencing Library Preparation: Preparing 16S Ribosomal RNA Gene Amplicons for the Illumina MiSeq System (Illumina, San Diego, CA, USA) (Illumina, 2013).

Data analysis

Paired-end (2 × 300 bp) raw sequencing data were processed using Quantitative Insights Into Microbial Ecology 2 (QIIME2) v2023.5 (https://qiime2.org/) (Bolyen et al., 2019). The 5′ end of the primer was trimmed, and the 3′ end was truncated to the region where the average quality score per sequence location was greater than 25. Sequences were filtered, denoised, and merged and chimeras were removed using the Divisive Amplicon Denoising Algorithm 2 (DADA2) pipeline (GitHub; https://github.com/benjjneb/dada2/); reads were clustered into amplicon sequence variants (ASVs) (Callahan et al., 2016). The ASVs were taxonomically assigned by the sklearn classifier method using SILVA database v138 (arb-silva, Bremen, Germany; https://www.arb-silva.de/). Reads not assigned to a taxon were removed from the analysis by using the taxa filter-table function. The results of alpha diversity analysis, beta diversity analysis, microbial composition analysis, and linear discriminant analysis (LDA) effect size (LEfSe) (Segata et al., 2011) were visualized using QIIME2 View (https://view.qiime2.org/) and MicrobiomeAnalyst (Microbiomeanalyst, Montreal, QC, Canada; https://www.microbiomeanalyst.ca/) (Chong et al., 2020).

Results

On measuring the weight of the olive flounders, five fish were found to weigh less than 100 g; these fish were included in the juvenile group. The average weight of the fish in the juvenile group was 90.30 ± 4.47 g. The remaining five fish were included in the subadult group; their average weight was 505.80 ± 58.48 g.

Alpha diversity was compared between the groups based on three estimators: observed features, Shannon’s evenness index, and Pielou’s evenness index. The observed features metric was significantly higher (p = 0.028) in the subadult group (362 ± 82) than in the juvenile group (226 ± 75) (Fig. 1A). Shannon’s and Pielou’s evenness indices were also significantly higher (p = 0.009) in the subadult group (6.67 ± 0.64 and 0.79 ± 0.09, respectively) than in the juvenile group (3.78 ± 0.99 and 0.48 ± 0.10, respectively) (Fig. 1B and 1C).

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Fig. 1. Alpha diversity analysis of the gut microbiota of olive flounder. Alpha diversity was analyzed based on observed features (A), Shannon’s evenness index (B), and Pielou’s evenness index (C). For all estimates, each group is represented as a boxplot with the median.
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Beta diversity analysis of the olive flounder gut microbiota was performed based on the Jaccard distance (Fig. 2A and 2B) and Bray-Curtis distance (Fig. 2C and 2D) between the samples using the principal coordinate analysis (PCoA) plot. In all the results, the two groups showed clear boundaries, indicating that differences existed between the groups.

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Fig. 2. Beta diversity analysis of the gut microbiota of olive flounder. Principal coordinate analysis (PCoA) plots are displayed based on the Jaccard distance (A and B) and Bray-Curtis distance (C and D) between samples.
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Assessment of the relative microbial abundance at the phylum level based on the SILVA database revealed differences in microbial compositions between the two groups (Fig. 3). The most abundant phylum in the juvenile group was Proteobacteria (76.13 ± 12.98%), followed by Firmicutes (19.58 ± 11.05%) and Actinobacteriota (2.03 ± 0.95%). On the other hand, the most abundant phylum in the subadult group was Firmicutes (56.88 ± 24.06%), followed by Proteobacteria (26.68 ± 12.40%) and Actinobacteriota (5.90 ± 5.51%).

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Fig. 3. Composition and relative abundance of bacterial phyla at different growth stages of olive flounder. The phylum accounting for more than 1% of the total microbial composition in each sample (A) and the group average (B) are shown.
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Assessment of the relative abundance at the genus level revealed that the most abundant genus in the juvenile group was Vibrio (58.06 ± 10.09%), followed by Photobacterium (14.33 ± 9.67%) and Lactobacillus (6.93 ± 4.06%). The most abundant genus in the subadult group was Lactococcus (12.37 ± 6.50%), followed by Vagococcus (10.53 ± 5.88%) and Lactobacillus (7.07 ± 1.84%) (Fig. 4).

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Fig. 4. Composition and relative abundance of bacterial genera at different growth stages of olive flounder. The top 20 genera with high abundance in each sample (A) and the group average (B) are shown.
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LEfSe revealed a total of three phyla in the juvenile and subadult groups based on an LDA score of 4. The phylum Proteobacteria represented the juvenile group, while the phyla Firmicutes and Actinobacteriota represented the subadult group (Fig. 5A). A comparison of the observed phylum counts in the juvenile and subadult groups revealed that the Proteobacteria counts were 57,571 and 22,337, respectively; Firmicutes counts were 15,352 and 55,717, respectively; and Actinobacteriota counts were 1,580 and 5,516, respectively (Fig. 5B).

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Fig. 5. Linear discriminant analysis (LDA) effect size (LEfSe) of the differential abundance of taxa within the gut microbiota of olive flounder. (A) LDA score of the abundance of taxa at the phylum level. (B) Comparison of counts of corresponding taxa between groups.
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Based on an LDA score of 4, the genera Vibrio, Photobacterium, Leuconostoc, and Brevibacterium were considered to represent the juvenile group. On the other hand, 19 genera, including Lactococcus, Vagococcus, and Streptococcus, represented the subadult group (Fig. 6).

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Fig. 6. Linear discriminant analysis (LDA) effect size (LEfSe) of the differential abundance of taxa at the genus level.
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Discussion

A striking feature of vertebrate evolution is that vertebrates have developed adaptive immunity, expressing antigen-specific receptors that allow them to recognize and remember microorganisms (McFall-Ngai, 2007). Studies have suggested that this evolution of vertebrates has promoted the expansion of their resident microbiota (Maynard et al., 2012; McFall-Ngai, 2007). Therefore, while the gut microbiota of invertebrates consists of only a small number of species, that of vertebrates is more complex. Moreover, complex interactions exist between the host and the microbiota (Kostic et al., 2013; McFall-Ngai, 2007). In humans, infants are born with an essentially sterile intestine. Thereafter, dramatic changes can occur in microbial diversity during infancy. However, Bacteroidetes and Firmicutes gradually become prevalent in adults, a composition that is conserved across humans (Kostic et al., 2013). Similarly, in this study, differences were noted in the gut microbiota diversity and composition of olive flounder depending on the growth stage. Alpha diversity analysis revealed that the gut microbiota of the subadult group was more diverse than that of the juvenile group. In addition, the gut microbiota composition at the phylum and genus levels was more diverse and complex in the subadult group.

Phylum-level analysis of the gut microbiota according to the growth stages of olive flounder revealed a clear difference between the groups; the abundance of Proteobacteria decreased, while that of Firmicutes increased. Proteobacteria was the predominant phylum in all fish. Studies using zebrafish have revealed that Proteobacteria can cause intestinal inflammation in fish (Brugman et al., 2009). On the other hand, Firmicutes may have a direct effect on fatty acid storage (Ley et al., 2006, 2008; Turnbaugh et al., 2009). These results indicate that juvenile olive flounder may be prone to intestinal inflammation and that the gut microbiota composition may change to facilitate fat storage as the olive flounder progresses to subadult stages. Interestingly, in our previous study, the most abundant phylum in the gut microbiota of olive flounder, belonging to the juvenile group, was also Proteobacteria. Additionally, supplementation with appropriate probiotics decreased the proportion of Proteobacteria and increased Firmicutes. The group fed probiotics had increased digestive enzyme activity (Lee et al., 2024). However, this interpretation cannot be confirmed until the effects of specific microorganisms are investigated in actual germ-free olive flounder.

In this study, Vibrio and Photobacterium were representative genera in the gut microbiota of juvenile olive flounder. Differences in the gut microbiota composition may exist as a characteristic of the diversity in fish (Egerton et al., 2018). Nevertheless, studies conducted to date have shown that the genera Vibrio, Photobacterium, and Clostridium are key members of the fish gut microbiota (Egerton et al., 2018). Clostridium is associated with herbivorous diets, while Vibrio and Photobacterium are commonly found in carnivores (Egerton et al., 2018). This study confirmed that Vibrio and Photobacterium are abundant in olive flounder, a carnivorous fish species, during the juvenile stage. However, changes are induced as it progresses to subadult stages.

Many studies are attempting to use probiotics to manipulate the gut microbiota composition toward a healthy one (Jang et al., 2019, 2020). However, one of the biggest obstacles is the lack of data on the baseline gut microbiota composition of healthy fish (Monroig et al., 2013). Therefore, increasing the focus on collecting such data is essential to ensure that diet manipulation strategies achieve their full benefit (Monroig et al., 2013). In this study, Vibrio was abundant in the intestines of healthy juvenile flounder. Vibrio species are well known to cause vibriosis (Sanches-Fernandes et al., 2022). However, some of the reported Vibrio species are the main bacterial species producing polyunsaturated fatty acids (PUFAs) in the fish gut (Monroig et al., 2013). Therefore, studying the potential utilization of Vibrio species as PUFA-producing bacteria for probiotic purposes could be a novel and interesting research avenue for fish health and nutrition (Monroig et al., 2013). Similarly, based on the results of this study, the use of microorganisms presents in subadult olive flounder, such as Lactococcus and Vagococcus species, could also be considered.

Competing interests

No potential conflict of interest relevant to this article was reported.

Funding sources

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1I1A1A01049238).

Acknowledgements

Not applicable.

Availability of data and materials

Upon reasonable request, the datasets of this study can be available from the corresponding author.

Ethics approval and consent to participate

This study conformed to the guidance of animal ethical treatment for the care and use of experimental animals.

References

1.

Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019; 37:852-7

2.

Brugman S, Liu KY, Lindenbergh-Kortleve D, Samsom JN, Furuta GT, Renshaw SA, et al. Oxazolone-induced enterocolitis in zebrafish depends on the composition of the intestinal microbiota. Gastroenterology. 2009; 137:1757-67

3.

Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016; 13:581-3

4.

Cathers HS, Mane SP, Tawari NR, Balakuntla J, Plata G, Krishnamurthy M, et al. In silico, in vitro and in vivo characterization of host-associated Latilactobacillus curvatus strains for potential probiotic applications in farmed Atlantic salmon (Salmo salar). Sci Rep. 2022; 12:18417

5.

Chong J, Liu P, Zhou G, Xia J. Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat Protoc. 2020; 15:799-821

6.

Egerton S, Culloty S, Whooley J, Stanton C, Paul Ross R. The gut microbiota of marine fish. Front Microbiol. 2018; 9:873

7.

Food and Agriculture Organization of the United Nations [FAO] / World Health Organization [WHO]. Evaluation of health and nutritional properties of probiotics in food including powder milk with live acid bacteria. Córdoba: Joint FAO/WHO Expert Consultation. 2001.

8.

Hasan MT, Jang WJ, Kim H, Lee BJ, Kim KW, Hur SW, et al. Synergistic effects of dietary Bacillus sp. SJ-10 plus β-glucooligosaccharides as a synbiotic on growth performance, innate immunity and streptococcosis resistance in olive flounder (Paralichthys olivaceus). Fish Shellfish Immunol. 2018; 82:544-53

9.

Illumina I. 16S Metagenomic sequencing library preparation: preparing 16S ribosomal RNA gene amplicons for the illumina MiSeq system. San Diego, CA: Illumina. 2013.

10.

Jang WJ, Hasan MT, Lee BJ, Hur SW, Lee S, Kim KW, et al. Effect of dietary differences on changes of intestinal microbiota and immune-related gene expression in juvenile olive flounder (Paralichthys olivaceus). Aquaculture. 2020; 527:735442

11.

Jang WJ, Jeon MH, Lee SJ, Park SY, Lee YS, Noh DI, et al. Dietary supplementation of Bacillus sp. PM8313 with β-glucan modulates the intestinal microbiota of red sea bream (Pagrus major) to increase growth, immunity, and disease resistance. Front Immunol. 2022; 13:960554

12.

Jang WJ, Lee JM, Tawheed Hasan M, Lee BJ, Lim SG, Kong IS. Effects of probiotic supplementation of a plant-based protein diet on intestinal microbial diversity, digestive enzyme activity, intestinal structure, and immunity in olive flounder (Paralichthys olivaceus). Fish Shellfish Immunol. 2019; 92:719-27

13.

Jang WJ, Lee KB, Jeon MH, Lee SJ, Hur SW, Lee S, et al. Characteristics and biological control functions of Bacillus sp. PM8313 as a host-associated probiotic in red sea bream (Pagrus major) aquaculture. Anim Nutr. 2023; 12:20-31

14.

Jang WJ, Lee SJ, Jeon MH, Kim TY, Lee JM, Hasan MT, et al. Characterization of a Bacillus sp. KRF-7 isolated from the intestine of rockfish and effects of dietary supplementation with mannan oligosaccharide in rockfish aquaculture. Fish Shellfish Immunol. 2021; 119:182-92

15.

Jang WJ, Oh DN, Lee EJ, Lee JM. Encapsulation of probiotics with poly-γ-glutamic acid alters gut microbiota and short-chain fatty acid content by maintaining cell viability in the gastrointestinal tract. Food Hydrocoll. 2024; 147:109328

16.

Kader MA, Zahidah Azahar N, Iehata S, Bulbul M, Islam MM, Sarker J, et al. Dietary supplementation of host‐associated lactic acid bacteria modulates growth, metabolic activities, and immune‐related gene expression in giant freshwater prawn, Macrobrachium rosenbergii. J World Aquac Soc. 2021; 52:216-30

17.

Kostic AD, Howitt MR, Garrett WS. Exploring host-microbiota interactions in animal models and humans. Genes Dev. 2013; 27:701-18

18.

Lee SJ, Noh DI, Lee YS, Hasan MT, Hur SW, Lee S, et al. Effects of host-associated low-temperature probiotics in olive flounder (Paralichthys olivaceus) aquaculture. Sci Rep. 2024; 14:2134

19.

Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Stephen Bircher J, et al. Evolution of mammals and their gut microbes. Science. 2008; 320:1647-51

20.

Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006; 444:1022-3

21.

Maynard CL, Elson CO, Hatton RD, Weaver CT. Reciprocal interactions of the intestinal microbiota and immune system. Nature. 2012; 489:231-41

22.

McFall-Ngai M. Adaptive immunity: care for the community. Nature. 2007; 445:153

23.

Monroig Ó, Tocher DR, Navarro JC. Biosynthesis of polyunsaturated fatty acids in marine invertebrates: recent advances in molecular mechanisms. Mar Drugs. 2013; 11:3998-4018

24.

Nawaz A, Javaid AB, Irshad S, Hoseinifar SH, Xiong H. The functionality of prebiotics as immunostimulant: evidences from trials on terrestrial and aquatic animals. Fish Shellfish Immunol. 2018; 76:272-8

25.

Nayak SK. Probiotics and immunity: a fish perspective. Fish Shellfish Immunol. 2010; 29:2-14

26.

Niu KM, Lee BJ, Kothari D, Lee WD, Hur SW, Lim SG, et al. Dietary effect of low fish meal aquafeed on gut microbiota in olive flounder (Paralichthys olivaceus) at different growth stages. MicrobiologyOpen. 2020; 9e992

27.

Sanches-Fernandes GMM, Sá-Correia I, Costa R. Vibriosis outbreaks in aquaculture: addressing environmental and public health concerns and preventive therapies using gilthead seabream farming as a model system. Front Microbiol. 2022; 13:904815

28.

Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011; 12:R60

29.

Statistics Korea. The current fish culture by city & province, ward & county, by culture type by species [Internet]. 2024.[cited 2024 Feb 2]https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1EZ0008&vw_cd=MT_ZTITLE&list_id=K2_4&scrId=&seqNo=&lang_mode=ko&obj_var_id=&itm_id=&conn_path=MT_ZTITLE&path=%252FstatisticsList%252FstatisticsListIndex.do.

30.

Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature. 2009; 457:480-4

31.

Van Doan H, Hoseinifar SH, Ringø E, Ángeles Esteban M, Dadar M, Dawood MAO, et al. Host-associated probiotics: a key factor in sustainable aquaculture. Rev Fish Sci Aquac. 2020; 28:16-42