Structure and diversity of intestinal methanogens in grass carp and black carp

doi:10.21203/rs.3.rs-1755081/v1

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Structure and diversity of intestinal methanogens in grass carp and black carp

https://doi.org/10.21203/rs.3.rs-1755081/v1

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The current study aimed to explore the community characteristics of methanogens in the intestinal tract of grass carp and black carp, and their correlation with methanogens in cultured water. Samples of grass carp, black carp and cultured water in a pond were collected in Spring 2021. Based on LIIumina HiSeq 2500 high-throughput sequencing platform, the metagenomic mcrA gene sequences of grass carp, black carp and cultured water samples were determined and analyzed. The results showed that the richness and diversity of methanogens in the intestinal tract of grass carp and black carp were highly correlated with the cultured water. A total of 5 bacteria genera were detected in the three groups of samples, Methanosarcina, Methanocorpusculum, Methanospirillum, Methanobacterium and Methanofollis, in which Methanosarcina and Methanocorpusculum were the dominant genera. In addition, Methanosarcina had the highest abundance in CY and Methanocorpusculum had the highest abundance in QY. In conclusion, Methanosarcina and Methanocorpusculum were the main methanogens in the intestinal tract of grass carp and black carp and culture water, and hydrolytic fermentative bacteria were its main metabolic substrate, hydrotrophic was its main metabolic pathway. The results will provide reference for the relationship between intestinal methanogens and aquaculture and greenhouse effect.

grass carp

black carp

high-throughput sequencing

methanogens

microbiota characteristics

Methanogens, also known as Methanogenic archaea, are a class of archaea microorganisms that can produce methane gas in an obligate anaerobic environment using hydrogen, carbon dioxide, acetic acid, formic acid, methanol and methylamine, etc., which are widespread in nature (Gibson et al. 1988, Ferry 1999, Shima et al. 2002, Karakashev et al. 2006). Methanogens are abundant and diverse. Methanogens have developed into 4 classes (Methanobacteria, Methanococci, Methanomicrobia, Methanopyri) and 5 orders (Methanococcales, Methanosarcinales, Methanopyrales, Methanomicrobiales and Methanobacteriales) by 2016 according to the Handbook of Berger Bacteria Identification (ninth edition) (Cui 2007). Methanogens mainly generate methane through H₂/CO₂ reduction pathway and acetic acid fermentation pathway, while methyl trophication pathway mainly occurs in specific environments such as river and pond sediments (Le Mer & Roger 2001, Ben et al. 2018).

Methane (CH₄) is a greenhouse gas produced by methanogens decomposing organic matter under anaerobic conditions, and its contribution to global climate warming is second only to that of carbon dioxide CO₂ (Xing et al. 2005, Pangala et al. 2010). Many CH₄ accumulated on the earth come from the action of microorganisms. Because methanogens play an important role in the natural carbon cycle, and methane is the second largest greenhouse gas contributing to global warming, methanogens and the mechanism of methane production have attracted much attention from researchers. Especially in recent years, researchers have conducted in-depth discussions on the living habits and metabolic mechanism of methanogens (Liu et al. 2012, Chaudhary et al. 2018, Lyautery et al. 2021). The results showed that the methanogens from sediments and animals were distinct, and the methanogens from fresh water and sea water were also different. Methanogens from the same sediments or animals have a high similarity, reflecting the close correlation between the ecological environment and the distribution of methanogens (Yan et al. 2017).

CH₄ emission from lakes and ponds is an important source of atmospheric methane (Schmid et al. 2007, Bastviken et al. 2011, Bussmann et al. 2012). Methanogens, as the main role of methane generation, are usually characterized by the diversity or abundance (Pester et al. 2004, Earl et al. 2005, Schwarz et al. 2008). Some scholars have studied the seasonal dynamics of the abundance, structure and diversity of methanogens and methanotrophic bacteria in lake sediments, and determined that the diversity of methanotrophic bacteria was dominated by methylobacter in the deep part and methylococcus in the shallow part, and organic matter was the main environmental parameter controlling methanogenes (Lyautey et al. 2021). In this study, we collected the samples of grass carp, black carp and cultured water from the same pond, and analyzed their methanogens community structure and diversity based on two different kinds of predatory fish intestine and their cultured water. The results will help to deepen the understanding of methanogens in the ecological functions of matter and energy circulation and transformation in the rural aquaculture pond ecosystem, and provide reference information for the ecological diversity of rural aquaculture ponds and the possible impact of aquaculture on the greenhouse effect.

Sample collection and preservation

Samples of black carp (QY), grass carp (CY) and cultured water (SY) were collected from the same pond of Loudi Fishery Science Research Institute (N27°43'47", E112°0'6"), Hunan Provence, China. The pond has a depth of 2.0 m and an area of 1.5 hm². The sampling time is 08:00 a.m. on January 19, 2021, with water temperature 17.8 ℃, PH 8.10–8.56 and dissolved oxygen > 4.35 mg/L. Five grass carps (1431.34 ± 33.25 g) and five black carps 2627.3 ± 42.69 g) of the same size without disease symptoms were randomly selected from the fish caught in the net and brought back to the laboratory together with water samples, and the others were put back into the pond.

In order to reduce pollution, the fish surface was washed with sterile water and 70% ethanol successively before dissection. The content samples of grass carp (no. CY1-CY5) and black carp (No. QY1-QY5), and water samples (No. SY1-SY5) were collected in the sterile operating trays, and then placed in a sterile centrifuge tube and refrigerate at -20 ℃ for later use.

Abundance detection of methanogens

The Tguide S96 kit was used to extract DNA from 15 samples, and the universal primers MLf and MLr were used to amplify methanogenic mcrA gene. After qualified PCR products were detected by electrophoresis, the target fragment was recovered, and the library was sequenced by Illumina HiSeq 2500. The primer, reaction system and amplification conditions are as follows. Primer synthesis and sequencing were completed by Beijing Biomarker Technologies Co., Ltd (Beijing, China).

Amplification primer: MLf (5'-GGTGGTGTMGGATTCACACARTAYGCWA CAGC-3'), MLr (5'-TTCATTGCRTAGTTWGGRTAGTT-3'). The amplification reaction was performed as follows: 5 µL KOD FX Neo Buffer, 0.3 µL (10 µM) of each forward primer and reverse primer, 2 µL (2 mM) of dNTPs, 0.2 µL KOD FX Neo, and 5–50 ng of DNA Template, ddH2O supplement to 10 µL.Reaction conditions: Initial denaturation at 95 ℃ for 5 min, followed by 25 cycles consisting of denaturation at 95 ℃ for 30 s, annealing at 50 ℃ for 30 s, and extension at 72℃ for 40 s, with a final extension of 7 min at 72℃.

Diversity analysis of methanogens

The original data obtained by sequencing were filtered by quality control (Trimmomatic, V0.33) (Bolger et al. 2014), and the identification and removal of primer sequences (Cutadapt, V1.9.1) (Martin 2011). Double-terminated sequence splicing (Usearch, V10) (Magoč & Salzberg 2011) and removal of chimeras (UCHIME, V4.2) (Edgar et al. 2011) obtained high-quality sequences for subsequent analysis. Usearch software can cluster reads with 97% similarity to obtain OUT (Edgar 2013). QIIME2 software (https://qiime2.org/) was used to calculate alpha and beta diversity in the samples to comprehensively assess the overall diversity and reveal differences between samples. Alpha diversity reflected the richness and diversity of species in individual samples, including Chao1, Ace, Shannon and Simpson. Chao1 and Ace indices measure species abundance, which is how many species there are. Shannon and Simpson indices measure species diversity and are affected by species abundance and community evenness in sample communities. Beta diversity analysis is used to judge the similarity in composition of different samples, including Principal Component Analysis (PCA), Principal Coordinat Analysis (PcoA), Nonmetric Multidimensional Scaling (NMDS) and Unweighted Pair-group Method with Arithmetic Mean (UPGMA), and calculate the distance between samples based on four different algorithms to obtain the beta value between samples.

Line Discriminant Analysis Effect Size (LEfSe) (Segata et al. 2011) uses linear discriminant analysis (LDA) to estimate the impact of each species’ abundance on the different effect size, and searched for species with significant differences among groups.

Statistical Analysis

SPSS 24.0 statistical software (IBM Corp., Armonk, NY, USA) was used for data statistics, the measurement data were represented by means ± standard deviations, and independent sample T test was used for pair comparison. P < 0.05 indicated statistically significant difference. The mcrA gene sequences obtained in this study were uploaded to the NCBI sequence read archive (accession number is PRJNA 838802 https://www.ncbi.nlm.nih.gov/).

Sequencing characteristics and OTU distribution of samples

The community characteristics of methanogens in grass carp, black carp and cultured water samples were analyzed using Illumina high-throughput sequencing technology. A total of 1512019 high-quality sequences were obtained from 15 samples of the three groups, and the average effective sequence of each sample was 90.99%, with the average sequence length concentrated in 421–435 bp. Through quality control, filtering and chimerism removal, a total of 25 OTUs were obtained based on 97% sequence similarity clustering. There were 21 OTU in CY samples. There were 21 OTU in QY samples. There were 22 OTU in SY samples. There were 16 identical OTU numbers in the three groups of samples. The results showed that there was no difference in the richness and diversity of methanogens among black carp, black carp and water samples (Fig. 1).

Comparison of alpha diversity of methanogens in grass carp, black carp and water samples

To illustrate the diversity and richness of methanogens in the intestinal tract of grass carp, black carp and cultured water, we used Mothur software to evaluate the alpha diversity index of samples. From the perspective of richness index, Chao1 index and Ace index in cultured water samples were the highest, and Chao1 index and Ace index in intestinal samples of grass carp and black carp were similar. From the perspective of diversity index, Simpson index and Shannon index of species in aquaculture water samples were the highest, which were similar to those in the intestinal samples of black carp, while Simpson index and Shannon index were the lowest in the intestinal samples of grass carp. The richness index in the intestinal samples of black carp and grass carp was significantly different from that in the cultured water samples (P < 0.05 or P < 0.01). The diversity index in the intestinal samples of black carp and water samples was similar, and the diversity index in the intestinal samples of grass carp was the lowest (Table 1, Fig. 2). These results indicated that the richness and diversity of methanogens in cultured water were the highest. The richness of methanogens in the intestinal tract of grass carp and black carp was similar to that of water samples, which was significantly different from that of water samples. The diversity of the intestinal tract samples of black carp was similar to that of water samples, but there was no significant difference.

Table 1

Difference analysis of alpha diversity index.
group	Chao1	Ace	Simpson	Shannon
CY	11.30 ± 2.9069*	12.8623 ± 2.3313*	0.3187 ± 0.3345*	0.9594 ± 1.0360
QY	11.44 ± 5.6007*	11.9343 ± 5.5446**	0.6105 ± 0.1340	1.6332 ± 0.7127
SY	18.15 ± 1.1673	19.1511 ± 1.2232	0.6339 ± 0.1111	1.7513 ± 0.4562
Note: CY stands for grass carp, QY stands for black carp; SY stands for water sample; Compared with water sample stands for p < 0.05,*stands for p < 0.01

Characterization of methanogens in grass carp, black carp and water samples

There were 3 classes, 4 orders, 5 families and 5 genera of methanogens were identified from 15 samples collected from CY, QY and SY groups. The genera detected were Methanosarcina, Methanocorpusculum, Methanospirillum, Methanobacterium and Methanofollis. Methanosarcina and Methanocorpusculum were the dominant genera, accounting for 91.15%, 89.36% and 69.17% of CY, QY and SY, respectively (Fig. 3, Table 2). Compared with SY samples, Methanosarcina and Methanospirillum increased in CY and QY samples to varying degrees. Methanobacterium and Methanofollis have decreased in CY and QY samples to varying degrees. Methanocorpusculum increased in QY samples, but decreased in CY samples. There were no significant differences among all genera.

Table 2

Relative abundance of methanogens at genus level
genus	CY	QY	SY
Methanosarcina	0.6014 ± 0.4409	0.4555 ± 0.1186	0.3020 ± 0.1841
Methanocorpusculum	0.3101 ± 0.4052	0.4380 ± 0.1498	0.3898 ± 0.1904
Methanospirillum	0.0628 ± 0.1391	0.0493 ± 0.1101	0.0002 ± 0.0001
Methanobacterium	0.0117 ± 0.0180	0.0571 ± 0.1271	0.2584 ± 0.2888
Methanofollis	0.0095 ± 0.0212	0.0001 ± 0.0000	0.0497 ± 0.0951
Note: CY stands for grass carp, QY stands for black carp; SY stands for water sample; Compared with water sample stands for p < 0.05,*stands for p < 0.01

Wighted Unifrac distance matrix was used to construct a cluster analysis of fifteen samples known as methanobacteria using the unweighted pair-group method with UPGMA. The results showed that the similarity of species composition among each group was relatively high (Fig. 4A). According to LefSe analysis results, Methanobacterium_sp and Methanofollis_ethanolicus are markers with statistical differences in SY samples (Fig. 4B).

Understanding changes in the abundance and diversity of microbial communities is a necessary condition for evaluating the role of microorganisms in the environment (Lyautey et al. 2021). Methanogens, as common microorganisms, are widely distributed in various environments, including soil (Kim et al. 2017, Heděnec et al. 2018), water sediments (McKay et al. 2017, Wang 2019) and animal digestive tracts (Moraes et al. 2014, van Lingen et al. 2017). Ponds and lakes are important natural emission sources of methane, and methane generation is closely related to methanogens community. At present, three main metabolic pathways have been described for methane production, namely hydrogenotrophic (convert H₂ plus CO₂ to CH₄), aceticlastic (convert acetate to CH₄ and CO₂) and methylotrophic (generate CH₄ by methanol, methylamine, dimethylamine and other mechanisms), which involve the diversity of methanogens (Conrad 2007, Özbayram 2012, Evans et al. 2019). In freshwater sediments, methane production is regulated by different environmental factors, such as hypoxia (Lehours et al. 2005), quality and quantity of organic matter (Bastviken et al. 2008, Schwarz et al. 2008), temperature (Duc et al. 2010), etc. Temperature variation is likely to be one of the factors affecting CH₄ production capacity in the shallowest areas of deep lakes or shallow lakes (Fuchs et al. 2016). In a certain range, the increase of temperature has an obvious promotion effect on the metabolic capacity of microorganisms, which is beneficial to improve the rate of gas production. In addition, the production capacity of CH₄ is closely related to the community abundance of fermentation microorganisms (Yang 2017). Therefore, it is helpful to clarify the relationship between aquaculture and greenhouse effect to study the community characteristics of methanogens in aquaculture water and intestinal tract of aquatic animals.

In this study, we applied high-throughput sequencing technology to methanogens in aquaculture water and aquatic animal intestines. Our results showed that a total of 5 genera were identified from methanogens, among which Methanosarcina, Methanocorpusculum and Methanobacterium were the three genera with the highest relative abundance. Methanosarcina is hydrogen and acetic acid mixotrophic methanogens, Methanocorpusculum and Methanobacterium are hydrogenotrophic methanogens (Yang 2017). The results showed that CH₄ was produced by H₂ reduction of CO₂ and acetic acid degradation, and mainly by hydrogen reduction of CO₂. In SY sample, Methanocorpusculum, Methanosarcina and Methanobacterium were the dominant bacteria, which is consistent with the characteristics of methanogenic bacteria community in wetland (Parkes et al. 2012, Zhang et al. 2020). In QY and CY samples, Methanosarcina and Methanocorpusculum were the dominant bacteria genera. In addition, Methanosarcina has the highest abundance in CY and Methanocorpusculum has the highest abundance in QY, which may be related to the feeding habits of grass carp and black carp.

Grass carp is an herbivorous freshwater fish, which feeds on the stems and leaves of aquatic plants, and its food riched in cellulose and polysaccharide. Black carp is a carnivorous freshwater fish, which feeds on snails, clams and other mollusks, and its food riched in protein and fat. The intestinal bacteria of grass carp and black carp are mainly Firmicutes (69% vs 37.5%), Proteobacteria (6.9% vs 37.5%) and Actinobacteria (6.9% vs 16.7%), which are highly similar to the bacterial community in cultured water (Wu et al. 2012, Zhang et al. 2013, Ding et al. 2021). Firmicutes, Proteobacteria and Actinomycetes belong to hydrolytic fermentation bacteria (Zhang et al. 2014). Among them, Clostridium in Firmicutes is a typical cellulose-decomposing bacteria with the function of fermenting monosaccharides to produce organic acids, while Streptococcus in Firmicutes is a typical protein-decomposing bacteria (Lawson 2016, Whitman 2015). Vibrio in Proteobacteria is the dominant lipopolysis bacteria (Zhang et al. 2004). In addition, the intestinal tract of grass carp is rich in amylase and cellulase (Wu et al. 2020), and the intestinal tract of black carp is rich in protease and lipase (Zhou et al. 2021). These facts indicate that metabolic matrix of methanogens in ponds and lakes mainly comes from hydrolytic fermentative bacteria, and methanogens can effectively use the H₂ and CO₂ generated by these hydrolytic fermentative bacteria to produce CH₄, which also fully demonstrates that ponds and lakes are important natural emission sources of methane, and are dominated by hydrogenotrophic methanogens.

In conclusion, we revealed the community structure and richness characteristics of methanogens in the intestinal tract of black carp and grass carp and aquaculture water for the first time, and clarified the relationship between intestinal methanogens and aquaculture and greenhouse effect. These results will provide reference for the relationship between intestinal methanogens and aquaculture and greenhouse effect.

Authors’ Contributions: Zhou-jin Tan designed the study; Jie-qi Wu collected the data; Jialin Liu analyzed the data; Cheng-xing Long wrote the manuscript and Zhoujin Tan and Wenge Li reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding: This research was funded by the Scientific Research Fund of Hunan Provincial Education Department, grant number 19A256 and the Ministry of Education, Humanities and Social Sciences Research Projects, grant number 19YJC7900766.

Data Availability Statement: The data in this study have been uploaded to the NCBI sequence read archive (accession number is PRJNA 838802)

Acknowledgments: We thank the editors and the reviewers of this paper for their constructive

Conflicts of Interest: The authors declare that there are no conflicts of interest regarding the publicationof this article.

Compliance with Ethical Standards：All animal work was carried out in accordance within the guidelines of the Institutional Animal Care and Use Committee of Hunan University of Chinese Medicine (NO.20171202). All authors knew and approved of this animal experiment.

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Structure and diversity of intestinal methanogens in grass carp and black carp

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Abstract

Figures

Introduction

Materials And Methods

Sample collection and preservation

Abundance detection of methanogens

Diversity analysis of methanogens

Statistical Analysis

Experimental Results

Sequencing characteristics and OTU distribution of samples

Comparison of alpha diversity of methanogens in grass carp, black carp and water samples

Characterization of methanogens in grass carp, black carp and water samples

Discussion

Declarations

References

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