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Article

Comparison of the Intestinal Microbiota Composition and Function of Red Claw Crayfish (Cherax quadricarinatus) Cultured in Ponds and Rice Fields

by
Libin Huang
1,†,
Tianhe Lu
1,†,
Xiaohua Lu
1,†,
Jingu Shi
2,
Yin Huang
1,
Xuesong Du
1,
Dapeng Wang
1,
Yi Liang
2,
Yanju Lei
3,
Lianggang Wang
1,
Rui Wang
1,* and
Huizan Yang
1,*
1
Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning 530021, China
2
Guangxi Fishery Technical Extension Station, Nanning 530022, China
3
Guangxi Aquatic and Animal Husbandry School, Nanning 530021, China
*
Authors to whom correspondence should be addressed.
†
These authors contribute equally to this work.
Fishes 2024, 9(9), 345; https://doi.org/10.3390/fishes9090345
Submission received: 25 June 2024 / Revised: 20 August 2024 / Accepted: 29 August 2024 / Published: 31 August 2024
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Abstract

The growth environment significantly influences the intestinal microbiota of aquatic organisms. We investigated the composition and functional differences in the intestinal microbiota of red claw crayfish (Cherax quadricarinatus) in rice fields (RB) and ponds (PB) by 16S rDNA high-throughput sequencing technology. The results indicate that the Shannon, Simpson, Sobs, Chao1, and ACE indices of PB are all higher than those of RB, demonstrating greater diversity and richness of intestinal microbiota. The dominant phyla in the intestinal microbiota of the Cherax quadricarinatus were Proteobacteria, Tenericutes, and Firmicutes. Tenericutes and Proteobacteria were significantly more abundant in the RB than in the PB, while Planctomycetes and Firmicutes were significantly more abundant in the PB than in the RB. The results of network correlation analysis indicate that Proteobacteria and Firmicutes exhibit strong connectivity with other microbial groups in the gut microbiota of Cherax quadricarinatus, showing significant centrality. They play an important role in the interactions within the gut microbiota community. The dominant bacterial genera in the Cherax quadricarinatus’s gut were Citrobacter, Candidatus_Bacilloplasma, and Clostridium_sensu_stricto_1. The abundance of the genus Clostridium was significantly higher in the PB than in the RB, whereas the abundance of Candidatus_Hepatoplasma and Vibrio was significantly lower in the PB than in the RB. The prediction function of KEGG enrichment showed that the abundance of Amino acid metabolism, Biosynthesis of Other Secondary Metabolites, Transport and Catabolism, Cancers, and Nervous System, Substance Dependence were significantly higher in the PB, while the infectious diseases pathway was enriched in the RB. In summary, our results revealed significant differences in the composition and diversity of intestinal microbiota in the Cherax quadricarinatus between rice paddy and pond farming environments. The intestinal microbiota of the Cherax quadricarinatus grown in pond environments exhibit higher diversity and stability, manifested by an increase in beneficial bacteria abundance and a decrease in opportunistic pathogens. These findings significantly improve understanding of the complex relationship among Cherax quadricarinatus, intestinal microbiota, and the environment.
Keywords:
Cherax quadricarinatus; gut microbiota; 16S rDNA; microbial interaction; aquaculture environment
Key Contribution: The study revealed the composition; dominant microbial communities; and differences in the gut microbiome of Cherax quadricarinatus under rice field and pond environments, the Proteobacteria and Firmicutes exhibit the highest intermediary centrality; Cherax quadriearinatus in the ponds have a higher gut microbial diversity and stability, and the interaction between the flora is stronger, promoting nutrient metabolism and energy conversion; ponds increased the abundance of beneficial bacteria in the intestinal flora of Cherax quadriearinatus, while decreased the abundance of opportunistic pathogenic bacteria.

1. Introduction

In recent years, Cherax quadricarinatus (Martens, 1868) farming has been developing vigorously in China, driving the rapid growth of the entire industry. In 2021, China’s Cherax quadricarinatus culture area was 1.733 million hectares, and the output was 2.6 million tons, and its output value was USD 11.76 billion. The total output value of the Cherax quadricarinatus industry has reached USD 60.31 billion, and it will continue to maintain a rapid growth momentum [1]. Cherax quadricarinatus farming mainly includes the rice field and pond cultivation model [1].
Cherax quadricarinatus, also known as red claw crayfish, is native to the rivers of Queensland in northern Australia [2]. Red claw crayfish is an omnivorous freshwater benthic animal, which usually moves and forages at night or in the evening, and lurks in a fixed habitat during the day. Due to its large size, easy survival, and high proportion of edible meat, it was introduced into China in 1992 and first cultured in Hubei and Guangdong Province. After about 30 years of promotion and breeding, it has become an important freshwater economic cultured shrimp in China [3]. However, in the process of breeding, the yield is often not satisfactory due to diseases, which affects the sustainable development of the industry. It is widely known that the diseases of aquatic animals are usually closely related to intestinal microorganisms [4].
Host–microbiota interactions play critical roles in host growth, immunity, and metabolism, and the intestinal microbiota exerts important and diverse effects on host physiology through maintaining immune balance and generating health-benefiting metabolites. The activity and metabolites of intestinal microorganisms can regulate the physiological stability of the host, thus affecting the disease and health of the host [5], and the genetic characteristics, living environment, and food composition of the host are the main reasons for the differences in the composition of intestinal microorganisms of aquatic animals [6]. The main pathogens of Cherax quadricarinatus are Vibrio parahaemolyticus, Aeromonas hydrophila, and Staphylococcus aureus [7]. Interestingly, they are not only widely present in aquatic environments but also in the intestines of Cherax quadricarinatus. Understanding the impact of the aquatic environment within aquaculture systems on the complex microbial communities within organisms is becoming increasingly important for comprehending how organisms interact with their surrounding environment, as well as their health, disease resistance, and overall well-being. This series of studies is crucial for innovating production management techniques, promoting sustainable aquaculture systems, and reducing or even eliminating the need for chemical treatments and antibiotics that contribute to antibiotic resistance.
The introduction of aquatic animals rearing to rice farming creates an integrated agro-ecological system. In recent years, farming aquatic animals in rice fields has been popular, forming comprehensive aquaculture models, including rice–shrimp [8], rice–fish [9], and rice–snail [10] systems. In this integrated breeding mode of rice and aquatic animals, the rice flowers, weeds, plankton, etc., in the system can be used as the food source of the breeding animals. The feces of farmed animals can be used as high-quality fertilizer for rice, forming a kind of recycling in the small system of rice aquatic animals. Compared with single-planting rice, the comprehensive planting and breeding mode will significantly increase the microbial abundance in the soil and affect the biochemical process in the system [11,12,13]. However, this model also to some extent limits the control of diseases in rice and aquaculture animals. The complex and ever-changing environment brings more challenges to the survival of aquaculture animals. In contrast, pond aquaculture provides a more stable environment, is easier to manage, and facilitates easier improvements in yield [14,15]. 16S rDNA sequencing technology is usually used to study the composition of intestinal microorganisms [4]. Therefore, this study used the 16S rDNA high-throughput sequencing technology to compare and analyze the intestinal microbial diversity of the Cherax quadricarinatus between ponds and rice fields. These findings broaden our understanding of the relationship between the host and intestinal microbiota, which will facilitate the modulation of intestinal microbiota for the production of healthy Cherax quadricarinatus and improvement in breeding mode.

2. Materials and Methods

2.1. Ethics Statement

All experimental procedures were strictly performed following the relevant national guidelines of China. Our study was approved by the Experimental Animal Management and Animal Welfare Ethics Committee, Guangxi Academy of Fisheries Science, with efforts made during the experiments to minimize the suffering of the sampled shrimp, in accordance with the ethical guidelines of the Chinese National Standard “Laboratory Animal—Guideline for Ethical Review of Animal Welfare”.

2.2. Experimental Animal and Sample Collection

In mid-April, Cherax quadricarinatus of the same age, reared under identical environmental conditions, healthy and undamaged, free from specific pathogens, weighing between 10.0 and 15.0 g, and measuring 4.0 to 5.0 cm in length, were introduced into three ponds of 1000 square meters each and three 1000-square-meter rice fields at the Red Crayfish Breeding Demonstration Base in Suxu Town (Nanning, China). These specimens were divided into three replicates for the pond group (PB) and rice field group (RB), respectively. Cherax quadricarinatus were stocked at a density of 12 individuals per square meter in the ponds, and at a density of 4 individuals per square meter in the rice fields. The Cherax quadricarinatus stocked in each rice field and pond are 4000 and 12,000 individuals, respectively. Each rice field is composed of 1/10 water pits (80 cm deep) and 9/10 rice cultivation area, interconnected with each other. The water pits reduce the impact of external environmental factors such as temperature, sunlight, and predators on Cherax quadricarinatus, while the rice cultivation area provides more space for activity for Cherax quadricarinatus. The experiment lasted for 80 days, during which the PB and RB were fed with shrimp compound feed produced by Guangxi Deyang Feed Technology Co., Ltd., Deyang, China. The ingredients and nutritional compositions are presented in Table 1. Feeding times were scheduled at 8:00 AM and 5:00 PM daily, with each feeding amounting to 2–3% of the body weight of Cherax quadricarinatus. Feeding quantities were adjusted promptly based on actual conditions to meet the growth requirements of Cherax quadricarinatus. No pesticides or toxic substances were used during the experiment. The pond and rice field use the same water source, and the water quality meets the fishery water quality standards (GB11607-89) [16]. During the experiment, water quality was monitored and adjusted daily, with the monitoring results shown in Table 2. The health and activity status of the Cherax quadricarinatus were observed and recorded daily. The water source for both the ponds and the rice fields was the same, with water temperatures ranging from 23.5 °C to 29.5 °C. Water quality was monitored daily, and observations and records of the health and activity of Cherax quadricarinatus were kept. At the end of the experiment, at the same time point, 10 healthy Cherax quadricarinatus were randomly sampled from each rice field and pond, ensuring they were undamaged and of uniform size, as detailed in Table 3. Subsequently, the Cherax quadricarinatus were disinfected with alcohol on a sterile bench. Intact intestinal samples were extracted using sterile scissors and forceps, rinsed with phosphate-buffered saline, and rapidly frozen in liquid nitrogen for intestinal microbiome sequencing.

2.3. DNA Library Preparation and Sequencing of Bacterial Genomes

Samples were removed from the −80 °C freezer and placed on wet ice for thawing. Microbial DNA was extracted according to HiPure Stool DNA Kits instructions (Magen, Guangzhou, China). The V3–V4 region of the bacteria 16S ribosomal RNA genes was amplified by PCR using primers 341F 5′-CCTACGGGNGGCWGCAG-3′ and 806R 5′-GGACTACHVGGGTATCTAAT-3′. The reaction system was 5 μL 10 × KOD Buffer, 5 μL 2 mM dNTPs, 1.5 μL 10 μM Forward Primer, 1.5 μL 10 μM Reverse Primer, 1 μL KOD Polymerase, 3 μL 25 mM MgSO4, and 100 ng Template DNA. The total PCR reaction volume was adjusted to 50 μL with aseptic ultrapure water. The reaction conditions were 94 °C for 2 min, 30 cycles of 98 °C for 35 s, 62 °C for 30 s, and 68 °C for 30 s, with a final extension step at 68 °C for 5 min. (The PCR procedure was as follows: initial denaturation at 94 °C for 2 min; 30 cycles of amplification with denaturation at 98 °C for 10 s, annealing at 62 °C for 30 s, and extension at 68 °C for 30 s; followed by final extension at 68 °C for 5 min.) The PCR products were resolved by electrophoresis in a 2% agarose gel and recycled using the AxyPrep DNA Gel Extraction Kit (Axygen, Biosciences, Torrance, CA, USA). Following PCR amplification and quality control by the ABI StepOnePlus Real-Time PCR System (Thermo Fischer Scientific, Waltham, MA, USA), the library products were sequenced using the Illumina NovaSeq PE250 platform (Illumina, San Diego, CA, USA) by Guangzhou Kidio Biotechnology Co., Ltd. (Guangzhou, China).

2.4. Analysis of the Intestinal Microbiota by High-Throughput Sequencing and Bioinformatics Analysis (Sequence Analysis)

The data from high-throughput sequencing were analyzed using Omicsmart, a dynamic real-time interactive online platform for data analysis (http://www.omicsmart.com, accessed on 10 January 2024). The raw sequencing data have been deposited in the National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/), BioProject number: PRJNA1135680. Analyses consisted of eight main steps. Quality control and preprocessing were performed on the original sequencing data. The UPARSE algorithm within USEARCH was used for cluster analysis of the operational taxonomic unit (OTU) according to a similarity cutoff value of 97%. With this, we assessed the relative abundance of each OTU in each sample by counting the number of tags from each OTU. OTUs were annotated with taxonomic information (Threshold: 0.8~1) based on the RDP classifier algorithm by using the GreenGene Database. Significant differences in Alpha and Beta diversity indices between groups were determined by t-test. Relative abundance (%) data of intestinal microbiome at the phyla and genus levels were analyzed. KEGG prediction and KO abundance statistics were finally implemented by Tax4Fun. SPSS 24.0 software (IBM Statistics, Armonk, NY, USA), Excel version 2019 (Microsoft, Redmond, WA, USA), and R-based stats package were used for statistical analysis.

3. Results

3.1. OTU Analysis

In total, 773,126 high-quality DNA sequences were obtained by gut microbial barcoding, with an average of 128,854 sequences per sample. After filtering, 118,202 valid sequences were produced, with an average length of 474 bp. The coverage of each sample was higher than 99%. Sequence clusters with a similarity of more than 97% were regarded as belonging to the same Operational Taxonomic Units (OTUs), and 1462 OTUs were obtained. To further compare the diversity and composition of gut microbiota, the shared and unique OTUs were detected using a Venn diagram (Figure 1). The specific OTUs of PB and RB were 847 and 251, respectively. And, 364 OTUs belonged to the shared bacterial OTUs, accounting for 24.90% of the total OTUs.

3.2. Alpha Diversities

Good’s coverage ranged from 99.74% to 99.75% in each sample (Figure 2F), indicating that the depth of sequencing was sufficient to reflect the composition of the intestinal microbiota of the samples and enough to cover all species in the samples. To investigate the difference in richness and diversity of intestinal flora, the alpha diversity index including Sobs, Chao1, and ACE (community richness indexes), Simpson, and Shannon (diversity indexes) was also calculated (Figure 2A–F). The α-diversity analysis showed that the Shannon and Simpson’s diversity indexes were higher in the PB (Figure 2D,E). The richness indexes Sobs, Chao1, and ACE showed that PB significantly increased gut microbial richness relative to the RB (Figure 2A–C).
Similarly, the dilution curve in the experimental results tended to be flat, which showed that the increase in sequencing depth did not affect the bacterial diversity, and the sequencing amount was sufficient (Figure 2G). The Rank (Figure 2H) abundance curve provides a visual representation of the taxonomic richness and evenness in a sample. Horizontally, the width of the curve reflects the abundance of different taxa, where a wider curve indicates a higher taxonomic richness. Vertically, the smoothness of the curve reflects the evenness of taxa in the sample, with a smoother curve indicating a more evenly distributed species composition. In the PB group, the curve spans a larger range on the x-axis compared to the RB group, indicating a significantly higher taxonomic abundance in the PB group. The curves of all groups were relatively smooth vertically, indicating a uniform distribution of bacterial species.

3.3. Beta Diversities

A Principal component analysis (PCoA) based on the relative abundance of bacterial OTUs and Bray–Curtis dissimilarities was shown in Figure 3, and the community structures of the intestinal microbiota were examined and compared. The results showed that there was an obvious difference in gut microbial community composition between the RB and PB, which was consistent with OTU analysis.

3.4. Microbial Communities Distribution and Correlation Analysis

As exhibited in Figure 4A, a total of 10 different bacterial phyla were identified. The most abundant of these phyla was considered to be the core intestinal flora: Proteobacteria (18.45–42.62%), Tenericutes (27.19–41.15%), and Firmicutes (6.79–42.87%) in the gut bacteria of Cherax quadricarinatus, which is similar to the indicator species result (Figure 4B). In general, these core microbiotas accounted for roughly 85% of the total in the group PB, but 95% in the RB groups. The abundance of core gut microbiota in RB from high to low was Proteobacteria, Tenericutes, and Firmicutes; in PB, it from high to low was Firmicutes, Tenerictes, and Proteobacteria. The results indicated that under different growth environments, even if the dominant bacterial structures at the phylum level in the intestines are similar, their proportions may vary.
At the genus level (Figure 4C), there were significant differences in core bacteria between PB and RB groups. The top five of the PB group were Clostridium_sensu_stricto_1, Candidatus_Bacilloplasma, Citrobacter, Acinetobacter, and Aeromonas; they were Candidatus_Bacilloplasma, Citrobacter, Candidatus_Hepatoplasma, Clostridium_sensu_stricto_1, and Vibrio in RB group, respectively. This was similar to the results for indicator species (Figure 4D). Among them, the relative abundance of Clostridium_sensu_stricto_1, Candidatus_Hepatoplasma, and Aeromonas was different between PB and RB groups. The relative abundance of the genera Clostridium_sensu_stricto_1 in the PB group was significantly higher than that in the RB group, while the relative abundance of Candidatus_Hepatoplasma, Vibrio, and Aeromonas in the PB group was significantly lower than that in RB group.
According to the Species correlation network diagram at the phyla level (Figure 4E), Euryarchaeota, Gemmatimonadetes, and Chloroflexi showed the greatest correlation, and they were all positively correlated with Acidobacteria. The Firmicutes were positively correlated with Planctomycetes. The Proteobacteria showed strongly negative correlations with the abundance of Firmicutes, Planctomycetes, Actinobacteria, and Verrucomicrobia. In addition, the Tenericutes were negatively correlated with Firmicutes and Planctomycetes, and had the strongest correlation. Among the aforementioned strongly correlated phyla, Tenericutes, Proteobacteria, and Firmicutes are all core intestinal microbiota, indicating that the core intestinal microbiota at the phylum level have a significant influence on other intestinal microbiota. At the genus level, Acinetobacter, Clostridium_sensu_stricto_12, Methanobacterium, Fonticella, Butyrivibrio_2, Singulisphaera, Ruminococcus_1, Rubellimicrobium, Shewanella, Christensenellaceae_R-7_group, Brevibacillus, and Saccharofermentans exhibit strong connectivity and are positively correlated (Figure 4F). Interestingly, none of them belong to the core intestinal microbiota at the genus level, yet Clostridium_sensu_stricto_12, Fonticella, Butyrivibrio_2, Ruminococcus_1, Christensenellaceae_R-7_group, Brevibacillus, and Saccharofermentans are all part of the core intestinal microbiota of the Firmicutes Phylum. The Acinetobacter and Rubellimicrobium belong to the core intestinal microbiota of the Proteobacteria Phylum. The results indicate that Proteobacteria and Firmicutes exhibit the highest intermediary centrality in the Cherax quadricarinatus gut microbiota, suggesting they may play crucial roles in the interactions within the gut microbial community.

3.5. Tax4Fun Functional Prediction of Microbial Communities

The functional characteristics of gut microbiota were predicted by Tax4Fun. All predicted functional genes were annotated with the Kyoto Encyclopedia of Gene and Genomes (KEGG), and a total of 6 primary pathways and 37 secondary pathways were discovered. Briefly, they were mainly associated with Metabolism pathway, Environmental information processing, Genetic information processing, Human diseases, Cellular processes, and Organismal system in KEGG level 1 and annotated to Carbohydrate metabolism, Membrane transport, Amino acid metabolism, Signal transduction, Metabolism of cofactors and vitamins, Energy metabolism, Nucleotide metabolism, Translation, Replication and repair, and Infection diseases in level 2 (Figure 5A). The highest abundance was found in the Metabolism pathway, including Carbohydrate metabolism, Amino acid metabolism, Metabolism of cofactors and vitamins, Energy metabolism, and Nucleotide metabolism. For the Environmental Information Processing group, the highest abundance was found in Membrane transport, as well as Signal transduction. In the PB group, the relative abundances of Amino acid metabolism, Biosynthesis of Other Secondary Metabolites, Transport and Catabolism, Cancers, Nervous System, and Substance Dependence were significantly higher than those in the RB group. Conversely, the RB group exhibited significantly higher enrichment in pathways related to infectious diseases and glycan biosynthesis and metabolism compared to the PB group (Figure 5B).

4. Discussion

The diversity of intestinal microorganisms is closely related to the functional stability and health of the host intestine [17]. The composition of intestinal microbiota can be affected, including host species [18], host growth stage [19], breeding mode [20], water quality [21], feed species [22], etc. Different aquaculture models have different effects on the growth of aquatic organisms and the intestinal environment. This study’s microbial composition sequencing results demonstrated that the dilution curve (Figure 2G) and Rank curve (Figure 2H) eventually reached a plateau, indicating a stable microbial diversity. Moreover, the sequencing saturation of each sample in all groups exceeded 99.72%, confirming high-quality and representative microbial sequencing data. In the alpha diversity analysis, the Shannon and Simpson’s diversity indexes were observed to be the highest for the PB (Figure 2D,E). The richness indexes Sobs, Chao1, and ACE showed that PB significantly improved gut microbial richness relative to the RB (Figure 2A–C). Our results suggest that Cherax quadricarinatus have higher gut microbiota diversity and richness in pond aquaculture environments. However, different from the results of this study, most of the research results on aquatic animals show that the intestinal microbial diversity of the rice field breeding mode is higher than that of the pond mode [23], and rice field breeding mode is more beneficial to biological growth, reproduction, and meat quality and flavor [24]. The microbial biomass in the soil in the paddy field culture model is higher than that in the pond culture model [11]. However, the gut microbiota composition of aquatic animals is more susceptible to factors such as breeding methods, water quality, and dietary composition [25,26,27]. Undoubtedly, pond aquaculture offers superior feeding management and growth environments, and provides optimal conditions for the growth and development of Cherax quadricarinatus.
Our results showed that the gut microbiota composition of Cherax quadricarinatus from both environments exhibited the same phylum-level dominant microbial groups, which were Proteobacteria, Tenericutes, and Firmicutes. These predominant bacteria were similar to the intestinal flora of other shrimps. The Proteobacteria have been found to be dominant gut bacterial phyla in Cherax quadricarinatus, Macrobrachium rosenbergii, and Litopenaeus vannamei [17,28,29]. Therefore, it can be seen that Proteobacteria is the most widely distributed phylum in shrimp, and it is also a resident bacterium in the intestinal tract of aquatic animals. The phylum Proteobacteria are commonly the most stable bacteria located in the shrimp gut regardless of diet and growth environment changes [30], which was consistent with this study. Therefore, the Proteobacteria are rich in species, and the change in their abundance can often lead to a change in intestinal microorganisms. Additionally, the beta diversity analysis showed that the microbiota composition of Cherax quadricarinatus cultured in ponds was significantly different from that cultured in paddy fields. There are significant differences in the abundance of phyla. The presence of Proteobacteria and Tenericutes in the gut microbiota of Cherax quadricarinatus from the pond group is significantly lower than that of the rice field group. Conversely, the abundance of Planctomycetes and Firmicutes in the gut microbiota of Cherax quadricarinatus from the pond group is significantly higher than that of the rice field group. Firmicutes are probiotics in aquatic animals, which are conducive to the decomposition of polysaccharides and fatty substances in food [31]. Some bacteria in Firmicutes contain PotN, a new member of the PII protein subfamily, which can significantly regulate cellular processes in response to the perceived cellular energy state of ATP/ADP ratio. The interaction with POTA may control the transport of polyamines into cells. It may also be involved in the metabolism of acetic acid produced by pyruvate conversion to maintain pH dynamic balance [32]. Most Planctomycetes are aerobic and resistant to most types of antibiotics. Most fungi in Planctomycetes can also convert different sugars and polysaccharides into carbon and energy. Peptide esters, yeast extract, urea, nitrate, and ammonium can also be used as nitrogen sources [33]. Previous research has shown that Tenericutes can be mutualistic symbionts in the gut of their host species [34]. Tenericutes play a role in the degradation of recalcitrant C sources in the stomach and pancreas of isopods [35]. However, their genomes are linked to an extreme reduction in metabolic capacity resulting from a lack of genes that are related to regulatory elements, biosynthesis of amino acids, and intermediate metabolic compounds, which must be imported from the host. Therefore, the Tenericutes might serve as an important indicator of host homeostasis and health [34].
The results of this study showed that the dominant bacteria in the intestinal microflora of red lobster were Candidatus_Bacilloplasma, Citrobacter, and Clostridium_sensu_stricto_1. Candidatus Bacilloplasma is the most prevalent bacterium present in the intestinal tract of Langurus, which is similar to the results of previous studies, and this bacterium is considered to be a member of the intestinal “native” flora [36]. Candidatus Bacilloplasma is a symbiotic microorganism found in the digestive system of crustaceans belonging to the class Malacostraca. It is considered a novel lineage within the order Rodentia [37,38]. Previous research has reported a close association between Candidatus Bacilloplasma and the digestive function of the Chinese mitten crab [39]. However, further investigation is needed to determine whether it can act as a probiotic that may confer health benefits to Cherax quadricarinatus. Clostridium is the main bacterial group that absorbs and utilizes cellulose, monosaccharides, and xylans in the gut [40]. Clostridium, isolated from human stool samples was able to accumulate Treg cells in the colon, thereby inhibiting intestinal inflammation. Clostridium plays an inflammatory inhibitory role in the gut of healthy Procambarus clarkii [41]. In addition, the ferritin contained in Clostridium is related to the regulation of ROS in the body, and is involved in the body’s antioxidant and immune systems [42]. In this study, there was a significant increase in the abundance of Clostridium in the intestinal tract of large individuals of Cherax quadricarinatus, greatly enhancing their metabolic and immune functions. Specifically, the abundance of Clostridium in the intestinal tract of the PB group was significantly higher than in that of the RB group, suggesting that the pond environment is more conducive to the growth of Clostridium in the intestinal tract. Citrobacter is a common opportunistic pathogen found in the gastrointestinal tract [43]. When the intestinal flora is unbalanced, Citrobacter can cause fleshy swelling or ulceration of the tail of Cherax quadricarinatus; peel off its cuticle, and the hepatopancreas can be observed to be pale yellow to brownish yellow, and severe cases can lead to death [44,45]. Many studies have shown that the pathogenicity of opportunistic pathogens correlates with their species’ abundance in the intestine. As their abundance decreases in the gut, their pathogenicity also decreases, thereby reducing the likelihood of providing ecological niches for other pathogenic microorganisms [45,46,47,48]. In this study, the abundance of Citrobacter in the intestinal tract of lobsters in the PB group was significantly lower than that in the RB group, indicating that the pond environment was conducive to reducing the abundance of Citrobacter in the intestinal tract and reducing its pathogenicity.
Similarly, most of the bacteria in Vibrio, Aeromonas, and Candida hepatitis are often considered opportunistic pathogens, and their increased abundance can increase host susceptibility to pathogens, and provide niches for colonization by other pathogens [49]. In this study, the abundance of Vibrio in the PB group was higher, and the abundance of Vibrio and other pathogenic bacteria has been shown to be positively correlated with the contents of nitrite and nitrate in water [50]. In the rice field culture mode, the content of nitrite and nitrate in the water was higher than that in the pond culture due to crop fertilization. However, the residual nitrite and sulfide after fertilization in rice fields will not only reduce the activity of antioxidant enzymes but also reduce the diversity and richness of intestinal microbiota [51]. This may also be the main reason why the microbial abundance of Cherax quadricarinatus in the rice field group is lower than that in the pond group in this study. The Aeromonas, a common pathogen of aquatic organisms, mostly exists in water bodies [52]. Some bacteria in Aeromonas are related to sepsis infection, and often cause Aeromonas sepsis (MAS) and chronic infection in aquatic animals [53]. The number of Aeromonas in the paddy field group was significantly higher than that in the pond group, and it was more prone to outbreaks of disease in the process of breeding. The above results indicate that the pond environment is beneficial for reducing the abundance of opportunistic pathogens in the gut microbiota of Cherax quadricarinatus, and this farming mode may help decrease the host’s sensitivity to pathogens and reduce available ecological niches for other pathogens to colonize. Additionally, the pond environment promoted an increase in beneficial bacteria abundance, enhancing the metabolic and immune functions of the host. The diversity and abundance of the gut microbiota are important factors that influence the digestion, absorption, and utilization of nutrients and energy. The gut microbiota forms a complex ecological network through cooperation, competition, predation, and other interactions. In this study, the Firmicutes and Proteobacteria phylum exhibit the highest correlation with other phyla. Specifically, within the Firmicutes phylum, taxa such as Clostridium_sensu_stricto_12, Fonticella, Butyrivibrio_2, Ruminococcus_1, Christensenellaceae_R_7_group, Brevibacillus, and Saccharofermentans, as well as within the Proteobacteria phylum, taxa such as Acinetobacter and Rubellimicrobium, demonstrate the strongest correlations and exert significant influence on other members of microbial community. The results indicate that Proteobacteria and Firmicutes exhibit the highest intermediary centrality in the Cherax quadricarinatus gut microbiota, suggesting that they may play crucial roles in the interactions within the gut microbial community. The stability of the gut microbiota community is positively correlated with the diversity and richness of the gut microbial population [42]. In this study, the results of functional prediction were consistent with the differences in intestinal microorganisms. In pond environments, the gut microbiota of Cherax quadricarinatus possess a richer array of metabolic pathways such as Amino acid metabolism, Biosynthesis of Other Secondary Metabolites, Transport and Catabolism, Cancers, Nervous System, and Substance Dependence, which to some extent promote their growth. In contrast, Cherax quadricarinatus in paddy field environments show an increased richness in infectious disease pathways within their gut microbiota, potentially increasing susceptibility to diseases.
In conclusion, the intestinal microbiota of Cherax quadricarinatus in pond environments exhibit higher stability and diversity, which to some extent promotes Cherax quadricarinatus growth and immune levels, reducing disease occurrence. On the other hand, the functionality of the Cherax quadricarinatus intestinal microbiota depends on certain specific bacterial groups. Exploring methods to cultivate these bacteria in the laboratory and scaling up the production of functional probiotics for distribution in ponds is crucial for the sustainable development of Cherax quadricarinatus aquaculture.

5. Conclusions

In summary, our study revealed that the composition and abundance of the intestinal flora of Cherax quadricarinatus were affected by the culture environment. The predominant bacterial phyla in the intestine of Cherax quadricarinatus were Proteobacteria, Tenericutes, and Firmicutes. The Proteobacteria and Firmicutes exhibit the highest intermediary centrality in the Cherax quadricarinatus gut microbiota. The dominant bacterial genera identified in this study include Candidatus_Bacilloplasma, Citrobacter, and Clostridium_sensu_stricto_1. Compared to rice paddy farming, Cherax quadricarinatus raised in pond farming exhibit higher richness and stability in their intestinal microbiota. There were differences in the abundance of opportunistic pathogens and beneficial bacteria between PB and RB groups. Additionally, the pond environment promotes interactions among the intestinal microbial community of Cherax quadricarinatus, facilitating the absorption of nutrients and utilization of energy conversion. The rice field environment reduced the stability of the gut microbiota in Cherax quadricarinatus, leading to an increase in the abundance of opportunistic pathogenic bacteria and an elevation in pathogenic pathways.

Author Contributions

Conceptualization, L.H.; Data curation, L.H. and T.L.; methodology, L.H., X.L. and Y.H.; software, D.W. and L.W.; validation, X.L., J.S., X.D. and Y.L. (Yanju Lei); formal analysis, L.H., T.L., Y.H., Y.L. (Yi Liang) and L.W.; investigation, J.S. and L.W.; resources, X.D. and L.W.; writing—original draft preparation, L.H.; writing—review and editing, R.W. and H.Y.; supervision, X.L. and H.Y.; project administration, Y.L. (Yanju Lei) and R.W.; funding acquisition, R.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by Guangxi Science and Technology Base and Talent Special Project (Guike AD23026270), Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture (2022-A-01-02, 2023-A-01-02), and Guangxi Shrimp and Shellfish Industry Innovation Team (nycytxgxcxtd-2023-14-01).

Institutional Review Board Statement

The study was conducted and approved by the Experimental Animal Management and Animal Welfare Ethics Committee, Guangxi Academy of Fisheries Science GX.No20230915SL1200904.

Informed Consent Statement

Not applicable.

Data Availability Statement

All datasets generated for this study are included in the article.

Acknowledgments

The authors thank the participants who gave their time to the trial.

Conflicts of Interest

The study does not involve conflicts of interest on any front.

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Figure 1. Venn diagram analysis: counting the number of shared and unique OTUs in each group.
Figure 1. Venn diagram analysis: counting the number of shared and unique OTUs in each group.
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Figure 2. Alpha diversity analysis of the gut microbiota of Cherax quadricarinatus in rice fields and ponds. The significance of differences in Alpha diversity indices was calculated using t-tests (and non-parametric tests): (A–F) represent Sob, ACE, Chao1, Shannon, Simpson indices, and Good’s coverage, respectively. The numerical values of P above the boxplots indicate intergroup differences. (G) Dilution curve analysis: the Sob index of the sample sequence at the OTU level. (H) Rank-Abundance curves analysis at the OTU classification level.
Figure 2. Alpha diversity analysis of the gut microbiota of Cherax quadricarinatus in rice fields and ponds. The significance of differences in Alpha diversity indices was calculated using t-tests (and non-parametric tests): (A–F) represent Sob, ACE, Chao1, Shannon, Simpson indices, and Good’s coverage, respectively. The numerical values of P above the boxplots indicate intergroup differences. (G) Dilution curve analysis: the Sob index of the sample sequence at the OTU level. (H) Rank-Abundance curves analysis at the OTU classification level.
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Figure 3. Principal coordinates (PCoA) analysis at the OTU level of the gut microbiota of Cherax quadricarinatus in rice fields and ponds.
Figure 3. Principal coordinates (PCoA) analysis at the OTU level of the gut microbiota of Cherax quadricarinatus in rice fields and ponds.
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Figure 4. Composition analysis of the gut microbiota of Cherax quadricarinatus in rice fields and ponds: (A,C) Stack map of species distribution of phyla and genus level; (B,D) Cladogram of the intestinal microbiota that are the topmost abundant as inferred by GraPhlAn at the phyla and genus level. Node size is proportional to the average abundance; color indicates the relative concentration of the clusters. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article. LDA > 3.) (E,F) Species correlation network diagram at the phyla and genus level.
Figure 4. Composition analysis of the gut microbiota of Cherax quadricarinatus in rice fields and ponds: (A,C) Stack map of species distribution of phyla and genus level; (B,D) Cladogram of the intestinal microbiota that are the topmost abundant as inferred by GraPhlAn at the phyla and genus level. Node size is proportional to the average abundance; color indicates the relative concentration of the clusters. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article. LDA > 3.) (E,F) Species correlation network diagram at the phyla and genus level.
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Figure 5. Tax4Fun was used to predict the functional characteristics of the gut microbiota of Cherax quadricarinatus in rice fields and ponds: (A) Stack diagram; (B) Welch’s t-test.
Figure 5. Tax4Fun was used to predict the functional characteristics of the gut microbiota of Cherax quadricarinatus in rice fields and ponds: (A) Stack diagram; (B) Welch’s t-test.
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Table 1. The ingredients and nutritional composition of the experimental diet.
Table 1. The ingredients and nutritional composition of the experimental diet.
Ingredients (g/kg Dry Weight)Nutritional Composition (%)
Fish meal240Crude protein430
Antarctic krill powder80Crude fiber120
Fish oil20Crude ash content160
Soybean meal160Crude fat50
Peanut bran120Total phosphorus30
Squid paste30Lysine24
Shrimp paste30Calcium30
Flour270
Plant extract30
Choline chloride5
Salt5
Vitamin premix 15
Mineral premix 25
Note: 1 Per gram vitamin premix: riboflavin 45.0 mg; thiamine 25.0 mg; vitamin K 10.0 mg; inositol 200.0 mg; pyridoxine hydrochloride 10.0 mg; vitamin B12 2 mg; calcium pantothenate 60.0 mg; biotin 1.3 mg; vitamin A 820.0 IU; vitamin D 500.0 IU; nicotinic acid 200.0 mg; folic acid 20.0 mg; vitamin E 1200.0 IU; vitamin C 1600.0 IU. 2 Per gram mineral premix: zinc sulfate 60.0 mg; sodium fluoride 50.0 mg; cobalt chloride 50.0 mg; potassium chloride 70.0 mg; 20.0 mg; calcium dihydrogen phosphate 80.0 mg; sulfate 80.0 mg; manganese sulfate 30.0 mg; ferrous sulfate 80.0 mg; calcium chloride 190.0 mg; copper sulfate 50.0 mg.
Table 2. Water quality management information table during the experiment.
Table 2. Water quality management information table during the experiment.
Water Quality IndexRadius
pH8.0 ± 0.8
Dissolved oxygen≥6.0 ppm
Ammonia nitrogen≤0.02 mg/L
Phosphates≤0.5 mg/L
Temperature23.5~29.5 °C
Nitrite≤0.2 mg/L
Table 3. Sampling information of Cherax quadricarinatus.
Table 3. Sampling information of Cherax quadricarinatus.
GroupsReplicatesInitial Body Weight/gInitial Body Length/cmWeight/gBody Length/cm
PB112.94 ± 1.554.23 ± 0.6979.58 ± 10.0410.14 ± 0.52
213.12 ± 1.434.50 ± 0.4381.18 ± 11.2810.38 ± 0.25
311.99 ± 1.624.14 ± 0.5270.38 ± 6.529.78 ± 0.31
RB112.23 ± 2.544.53 ± 0.6677.50 ± 8.1810.5 ± 0.35
213.65 ± 3.124.22 ± 0.5373.76 ± 14.1510.08 ± 0.66
312.65 ± 2.114.19 ± 0.4272.22 ± 6.559.96 ± 0.31
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Huang, L.; Lu, T.; Lu, X.; Shi, J.; Huang, Y.; Du, X.; Wang, D.; Liang, Y.; Lei, Y.; Wang, L.; et al. Comparison of the Intestinal Microbiota Composition and Function of Red Claw Crayfish (Cherax quadricarinatus) Cultured in Ponds and Rice Fields. Fishes 2024, 9, 345. https://doi.org/10.3390/fishes9090345

AMA Style

Huang L, Lu T, Lu X, Shi J, Huang Y, Du X, Wang D, Liang Y, Lei Y, Wang L, et al. Comparison of the Intestinal Microbiota Composition and Function of Red Claw Crayfish (Cherax quadricarinatus) Cultured in Ponds and Rice Fields. Fishes. 2024; 9(9):345. https://doi.org/10.3390/fishes9090345

Chicago/Turabian Style

Huang, Libin, Tianhe Lu, Xiaohua Lu, Jingu Shi, Yin Huang, Xuesong Du, Dapeng Wang, Yi Liang, Yanju Lei, Lianggang Wang, and et al. 2024. "Comparison of the Intestinal Microbiota Composition and Function of Red Claw Crayfish (Cherax quadricarinatus) Cultured in Ponds and Rice Fields" Fishes 9, no. 9: 345. https://doi.org/10.3390/fishes9090345

APA Style

Huang, L., Lu, T., Lu, X., Shi, J., Huang, Y., Du, X., Wang, D., Liang, Y., Lei, Y., Wang, L., Wang, R., & Yang, H. (2024). Comparison of the Intestinal Microbiota Composition and Function of Red Claw Crayfish (Cherax quadricarinatus) Cultured in Ponds and Rice Fields. Fishes, 9(9), 345. https://doi.org/10.3390/fishes9090345

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