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Cupriavidus in the intestinal microbiota of Tibet endemic fish Glyptosternum maculatum can help it adapt to habitat of the Qinghai Tibet Plateau
BMC Veterinary Research volume 17, Article number: 377 (2021)
Gut microbes play an important role in the growth and development of fish. The Tibetan Plateau fish Glyptosternum maculatum is a unique species of sisorid catfish living in the river up to 4200 m altitude.
To understand the mechanisms underlying the ability of G. maculatum to adapt to the high-altitude habitat, the intestinal microbiota of G. maculatum was studied. We used high-throughput sequencing of the 16S ribosomal RNA gene of intestinal microorganisms of wild and cultured G. maculatum to explore the characteristics of intestinal microorganisms and compared the gut microbial community of wild and cultured G. maculatum. The results showed that the α-diversity and richness of the intestinal microbiome were higher in wild G. maculatum than in cultured fish. The most abundant phylum in both G. maculatum were Fusobacteria, Proteobacteria, Firmicutes, and Bacteroidetes; Cetobacterium and Cupriavidus are the most dominant genus. The membership and structure of intestinal bacterial communities in wild G. maculatum are similar to the cultured fish, suggesting that a core microbiota is present in both G. maculatum intestinal bacterial communities. Metastats analysis showed that six genera were differentially represented between the wild and cultured G. maculatum.
The most interesting characteristic of the intestinal microbial communities of G. maculatum is that there were large numbers of Cupriavidus, which may play an important role in the adaptation of G. maculatum to the water of the Yarlung Zangbo River with a high Cu content. This result, in turn, can guide us on breeding G. maculatum.
The Tibetan Plateau fish Glyptosternum maculatum  is a sisorid catfish of Siluriformes belonging to Glyptosternoids and is distributed in the Yarlung Zangbo River and its tributaries . Glyptosternum maculatum is an omnivorous fish with fish and benthos as the main food source. Glyptosternum maculatum is the sole species of sisorid catfish living in the river up to 4200 m altitude  and has become an important species in the study of evolution and phylogeny of Sisoridae. However, the development and evolution of G. maculatum were affected by interval uplift of the Tibetan Plateau  to adapt to the environment. Therefore, the fish provide an excellent resource with which to infer the geological and environmental history of the region .
G. maculatum is an important commercial fish species in Tibet, and the high demand has caused overexploitation of the natural populations. Consequently, the number of wild G. maculatum has decreased sharply, which may eventually lead to the extinction of G. maculatum. The protection of fish resources is facing severe challenges. Cultivating G. maculatum artificially is an alternative way of meeting the demand for G. maculatum without affecting the population of wild fish. Thus, G. maculatum has become the major aquaculture fish in Tibet. With the development of aquaculture in Tibet, as well as the important economic value of G. maculatum, the potential for controlled rearing of G. maculatum is becoming more and more optimistic. However, there are still some problems to be solved in the artificial culture of G. maculatum. For example, compared with the wild fish, the cultured G. maculatum is more likely to be infected and die.
The gut microbiota occupying the gastrointestinal tract of vertebrates is well known to live in symbiotic association with the vertebrate host, presents a broad range of metabolic activities, and may contribute to various metabolic processes of the host . Thus, microbiota may secrete extracellular enzymes, help the host to complement digestive processes, provide vitamins and enhance nutrition. The microbiota also prevents pathogens from colonizing and competing for nutrients. In addition, they may produce antimicrobial substances and may also modulate the immune system of the host [7,8,9,10].
Current information on the intestinal microbiota of fish has largely been derived from culture-based approaches, which often reveal only a limited range of microbial diversity . Comparing the intestinal microflora of cultured G. maculatum with the intestinal microflora of wild fish, we can fully understand the intestinal microbiota structure of fish, and how ecological and environmental factors impact fish gut microbiota composition, as well as the role of some important gut microbiota compositions in the growth and development of G. maculatum, which is conducive to guiding cultivation of healthy fish to increase the output of fish, and meet the demand of market for G. maculatum. The purpose of this study is to compare the intestinal microbiological differences between wild and cultured G. maculatum to guide the rearing of G. maculatum.
Materials and methods
Experimental fish and sampling procedures
The study was carried out in compliance with the ARRIVE guidelines. Five wild G. maculatum collected randomly from Xie Tongmen River (group A1–5) and Five cultured G. maculatum collected randomly from the Tibet Academy of Agricultural and Animal Husbandry Sciences, Institute of Fishery Sciences (group B1–5) (Table 1). Due to the restriction of growth conditions, the weight of the wild fish of the same age is about two times less than the weight of the cultured fish. The fish showed no visual signs of disease and remained healthy throughout the study. The fish were aseptically captured and immediately kept cold at 4 °C with ice bags during transport to the laboratory. The body weight and body length of the fish were measured, and then the belly of the fish was washed with 75% ethanol. Finally, the intestinal contents of the fish were collected under sterile conditions and then stored at − 80 °C until further processing.
For the welfare of the animals, all experiments and animal procedures were conducted strictly according to the protocols recommended by the Institutional Animal Care and Use Committee (IACUC) of Tibet Academy of Agricultural and Animal Husbandry Sciences (permit number: 21–0354) and the protocols supported by the regulation of experimental animal of Ministry of Science and Technology in China,2014. All experiments and methods were performed to minimize animal suffering.
Intestinal DNA extraction and 16S rRNA gene sequencing
The PowerFecal® DNA Isolation Kit (MoBio Laboratories, Carlsbad, CA, United States) was then used to isolate DNA of intestinal samples following the manufacturer’s recommendations. The quantities and qualities of DNA extracted were checked using a NanoDrop 2000 (ThermoFisher, Wilmington, DE, United States) and gel electrophoresis. Then submitted DNA samples to the Shanghai Personal Biotechnology Co., Ltd., for 16S rRNA gene sequencing. PCR amplification of the bacterial 16S rRNA gene V3-V4 region was performed using the forward primer (5′-ACTCCTACGGGAGGCAGCA-3′) and the reverse primer (5′-GGACTACHVGGGTWTCTAAT-3′). High throughput sequencing procedures refer to Wang et al. .
Sequencing reads of the 16S rRNA gene were spliced with the barcode and primer sequence and merged using FLASH software . The quality of the reads was assessed using QIIME software  to obtain the high-quality clean tags. The tags were compared with the reference database using the UCHIME algorithm  to detect and remove chimera sequences. The reads were then clustered into operational taxonomic units (OTUs) based on an identity threshold of 97% using UPARSE . Taxonomy assignment of the OTUs was performed by comparing sequences with the GreenGene Database based on Ribosomal Database Project (RDP) classifier algorithm to annotate taxonomic information . Multiple sequence alignment of OTUs was performed by MUSCLE software to analyze the phylogenetic relationship of different OTUs and the differences of dominant species in different samples . Rarefaction curves, alpha diversity and beta diversity were calculated by QIIME software. The unweighted UniFrac phylogenetic distance metric was analyzed by using a Principal Coordinate Analysis (PCoA) and Unweighted Pair Group Method with Arithmetic mean (UPGMA) Clustering. PCoA analysis was displayed by WGCNA package, stat packages and ggplot2 package in R softwar.
Function prediction of G. maculatum internal microbiota
The analysis process of picrust2 is as follows, 1) Firstly, align the 16S rRNA gene sequences of known microbial genomes, construct an evolutionary tree, and infer the gene function spectrum of their common ancestors. 2) The 16S rRNA characteristic sequence was aligned with the reference sequence to construct a new evolutionary tree. 3) Using castor hidden state prediction algorithm, according to the copy number of gene family corresponding to the reference sequence in the evolutionary tree, infer the nearest sequence species of the characteristic sequence, and then obtain the copy number of gene family. 4) Combined with the abundance of characteristic sequences of each sample, the copy number of gene family of each sample was calculated. 5) Finally, the gene family is “mapped” to various databases, and minpath is used by default to infer the existence of metabolic pathways, so as to obtain the abundance data of metabolic pathways in each sample. According to the metabolic pathway database and certain calculation methods, the abundance value of metabolic pathway can be obtained. KEGG database is used in this study. The core of KEGG database is KEGG pathway database, http://www.genome.jp/kegg/pathway.html). Among them, metabolic pathways are divided into six categories, including metabolism, genetic information processing, environmental information processing, cellular processes, organic systems and human diseases. Each category of metabolic pathways is further divided into multiple levels.
A completely randomized test design was used in this study. The significance of the difference between means of the groups was determined by Students t-test. P-values < 0.05 were considered significant. Statistical calculations used in this study were performed using IBM SPSS (24.0).
The operational taxonomic units (OTUs) between wild and cultured G. maculatum
A total of 587,199 high-quality sequences were obtained from 16S rRNA gene sequencing, ranging from 131 to 458 bp, acquired from the 10 samples. Group A (Wild G. maculatum) has the largest number of OTUs, 2072, while group B (Cultured G. maculatum) has a smaller number of OTUs, 1814. 1406 OTUs are shared by two G. maculatum groups, and the number of unique OTUs in group A is the highest, 666, while the number of unique OTUs in group B is 408 (Fig. 1). The OTUs comprised 28 bacterial phyla, 75 classes, 128 orders, 229 families, 380 genera, and 439 species (Table 2).
Alpha diversity of G. maculatum intestinal microbiota
The results of rarefaction curve showed that the curve of each sample tended to flatten with higher sequence numbers, indicating that the sample size was reasonable (Fig. 2). The results of alpha diversity index (Table 3) showed that the indexes of Chao1, ACE and Shannon in group A were significantly higher than those in group B. Although the Simpson and goods coverage indexes in group A were not significantly different from those in group B, they were higher than those in group B. The index showed that intestinal microbiota diversity and relative abundance were higher in wild G. maculatum samples (group A) than in cultured G. maculatum samples (group B).
Differences of G. maculatum intestinal microbiota at phylum level
The most abundant taxa of bacteria at the phylum level are shown in Fig. 3a. The most abundant phylum was Fusobacteria in all samples, accounting for 30.1 to 42.3% of the total bacterial sequences, indicating that the highest quantity of gut bacterial species are from this taxon. Proteobacteria was the second most common phylum, accounting for 22.1 to 44.9%. Other common taxa were Firmicutes, Bacteroidetes, Actinobacteria, and Chloroflexi, ranging between 0.5 and 14.5% in all the experimental samples.
Differences of G. maculatum intestinal microbiota at genus level
Composition of microbiota at the genus level is represented by two genera, Cetobacterium and Cupriavidus. Other major genera (> 1%) include some genera of unclassified Aeromonadaceae, Acinetobacter, Anoxybacillus, Clostridium, Ochrobactrum, unclassified Cyclobacteriaceae, Lactococcus, Faecalibacterium, unclassified Chitinophagaceae, Bacteroides, unclassified C111, unclassified Comamonadaceae, and Geobacillus. The relative abundance of Cetobacterium ranged from 30 to 42% and Cupriavidus ranged from 11.7 to 24% (Fig. 3b). Alpha diversity includes ACE, Chao1, Shannon and Simpson indexes, etc., which are often used to evaluate biodiversity. The results of this study show that the intestinal microbial diversity and abundance of wild fish are higher than those of cultured fish, but the difference is not significant (P-value > 0.05) (Table 3).
Specific taxa that were differentially distributed between wild and cultured G. maculatum were identified using Metastats. The results are shown in Fig. 4, which depicts each genus showing a significant difference between the wild G. maculatum (group A) and cultured G. maculatum (group B) intestinal microbiota. At the genus level, a total of six genera were differentially represented between the two conditions. Arthrobacter, Klebsiella, Phyllobacterium, Sphingobacterium and Tessaracoccus were much higher in the wild G. maculatum than in the cultured G. maculatum, while Hydrogenophaga was higher in the cultured G. maculatum. The results of PCoA showed that the degree of dispersion within each sample group in group A and group B was small, while the degree of dispersion between groups was large (Fig. 5).
Function prediction of G. maculatum intestinal microbiota
Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis showed that metabolism, genetic information processing, and the environmental information processing are the crucial KEGG pathways in the microbiome community (Fig. 5). The results also show that the main functions of genes included genes from biodegradation and metabolism of xenobiotics, metabolism of cofactors and vitamin pathway, energy metabolism pathway, translation of genetic information processing pathway, carbohydrate metabolism pathway, amino acid metabolism and pathway of metabolism, replication and repair and genetic information processing pathway and membrane transport of environmental information processing.
Accumulating evidence shows that vertebrate intestinal microbiota can stimulate the development of host immune system, assist the host to obtain nutrients and resistance to opportunistic pathogens. Therefore, the intestinal microbiota plays an indispensable role in host health . G. maculatum is an aquaculture species with important economic and ecological value that inhabits the Tibetan Plateau (4200 m above sea level). The unraveling of the structure of its intestinal microbiota and identification of its core microbiome as well as the intricate host-microbe symbioses and functions are essential to the ability to use the benefits of a healthy microbiome to the advantage in G. maculatum culture, and furthermore, to gain a deeper understanding of the roles of bacteria in vertebrate health to develop effective strategies for regulating intestinal microbiota to improve the health of G. maculatum. Recent technological advances in sequencing have led to a much more comprehensive assessment of the intestinal microbiota. 16S rRNA gene sequencing has been used widely in the study of the composition of the intestinal microbiota of multiple organisms, including freshwater fish and marine fish [20,21,22,23]. From the results of this studies, 16S rRNA gene sequencing has been found to be a very effective method for deep study of the intestinal microbiota composition and structure of G. maculatum.
The results revealed that the cultured and wild G. maculatum have high similarity at phylum and genus levels, which suggested that wild G. maculatum in their natural environment and G. maculatum that have been maintained in an artificial environment obtain a common intestinal microbiota. The results of 16S rRNA gene sequencing emphasized that a core microbiota are present in both G. maculatum intestinal microbiota. The concept of a core intestinal microbiota has been explored in the context of mammalian hosts [24, 25], rat , and bony fishes [23, 27]. In this study, the Chao1 value, Shannon and Simpson indexes of the wild G. maculatum intestinal microbiota were higher than those of cultured fish, indicating higher bacterial diversity in the wild G. maculatum gut microbiota compared to the cultured G. maculatum gut microbiota . As an “extra organ”, the gut microbiota are involved in the metabolic, nutritional, physiological, and immunological processes of the host, to help its host to reshape their growth, health and development . In the wild G. maculatum gut microbiota, higher bacterial diversity means that there are more microorganisms to help the wild G. maculatum cope with the sophisticated living conditions and increase nutrient absorption. For example, Metastats analysis showed that Arthrobacter was much higher in the wild G. maculatum than in the cultured G. maculatum. It is reported that Arthrobacter is a kind of probiotics commonly used in aquaculture. The metabolites of this kind of bacteria, such as amino acids, vitamins and enzymes, have high nutritional value and resist opportunistic pathogens [30,31,32].
The genus of Cetobacterium is common in intestinal tracts of various fish such as carp, channel catfish, Asian seabass, goldfish, zebrafish, rainbow trout, etc. [9, 33,34,35,36,37,38]. Cetobacterium was the most abundant genus without any significant differences in both wild and cultured samples of G. maculatum, suggesting that Cetobacterium spp. is a core species in the G. maculatum gut and plays an important role in the growth and development of G. maculatum. Cetobacterium play a vital role in the intestines of many herbivorous fishes because it is related to the breakdown of carbohydrates, thereby assisting the host in the absorption and utilization of nutrients . As we all know, Cetobacterium produces a large amount of vitamin B12, which can inhibit the growth of potential pathogens  and promote protein biosynthesis. It acts as a growth factor in many fishes, and a lack of Cetobacterium usually affects the growth and development of the host .
In the gut of both wild and cultured samples of G. maculatum, there were large numbers of Cupriavidus, which is the biggest unique feature of G. maculatum microbiota. To date, there had been no such reports in other fish intestinal microbiota, so this aspect is the most interesting feature of G. maculatum intestinal microbiota. The genus Cupriavidus was described by Makkar and Casida in 1987 to accommodate species that are characterized as Gram-stain-negative, motile by 2 to 10 peritrichous flagella, oxidase positive, catalase positive, chemoheterotrophic, can use several amino acids but not L-lysine or L-methionine as the sole source of carbon and nitrogen. The most interesting character of this genus is that they are resistant to copper at concentrations up to at least 800 μM, and growth initiation is stimulated by copper . Copper is an indispensable trace element for fish. Lack of dietary copper causes growth retardation and poor feed efficiency in carp, grouper, and yellow catfish . Supplementing channel catfish diets with copper sulfate, which can also be used as a therapeutic in the water, significantly increased fish resistance to pathogens such as Flavobacterium columnare, which can cause the most commercially detrimental bacterial diseases of channel catfish . However, at elevated concentrations (i.e., > 1–2 mM), copper becomes toxic for most cells . The upper reaches of the Yarlung Zangbo River Basin have been proved to contain a large number of copper resources and other related resources , which led to the high content of Cu in the upper and middle reaches of the Yarlung Zangbo River . High pH, high Cu content, and low temperature are adverse conditions unfavorable to the growth of fish. G. maculatum can survive under these conditions, so they must have the physiological characteristics to solve these adverse conditions. According to the results, there are large numbers of Cupriavidus in the gut microbiota of G. maculatum, which may play a vital role in the adaptation of G. maculatum to the water of the Yarlung Zangbo River with high Cu content. On the one hand, because Cupriavidus possesses a good ability for the absorption and removal of copper from the water, Cupriavidus can make G. maculatum able to live in the water with a relatively high concentration of copper ions. On the other hand, because there are many Cupriavidus in the gut microbiota of G. maculatum, this observation suggests that when we feed G. maculatum artificially, we can increase the content of copper ions in its feed diet, which can fulfill the demand of G. maculatum for copper ion and can also inhibit the growth of pathogenic bacteria, so that G. maculatum can grow healthily under the conditions of artificial culture. However, we need to verify through experiments what concentration of copper ion in the diet is appropriate. Therefore, future research could be focused on the relationship between G. maculatum and Cupriavidus. How does Cupriavidus affect the survival of G. maculatum in its high altitude, low temperature, high Cu-content habitat? How high a concentration of copper ion in the diet is appropriate?
The results of this study demonstrated that the intestinal microbiota of wild and cultured G. maculatum are similar in phylum and genus level structure. In addition, cetobacterium is the main component of G. maculatum’s intestinal core microbiota, indicating that cetobacterium plays a vital role in G. maculatum’s adaptation to the water environment of the Yarlung Zangbo River with high copper content.
Availability of data and materials
The datasets used and analysed during the current study are available from the Genebank of NCBI, Sequence Read Archive (SRA) under access number: PRJNA769970.
- G. maculatum :
- 16S rRNA:
16S ribosomal RNA
Operational Taxonomic Units
Ribosomal Database Project
Abundance-based Coverage Estimation
Principal Component Analysis
Principal Coordinate Analysis
Unweighted Pair Group Method with Arithmetic mean
Phylogenetic Investigation of Communities by Reconstruction of Unobserved States
Kyoto Encyclopedia of Genes and Genomes
Regan CT. Descriptions of five new cyprinid fishes from Lhasa, Tibet, collected by captain HJ Waller. Ann Mag Nat Hist. 1905;1:185–8.
Zhang HJ, Xie CX, Li DP, Liu HP, Yang XF. Blood cells of a sisorid catfish Glyptosternum maculatum (Siluriformes: Sisoridae), in Tibetan Plateau. Fish Physiol Biochem. 2011;37(1):169–76.
He S, Cao W, Chen Y. The uplift of Qinghai-Xizang (Tibet) plateau and the vicariance speciation of glyptosternoid fishes (Siluriformes: Sisoridae). Sci China C Life Sci. 2001;44(6):644–51.
He SPCY, Zhang YP. Preliminary study on mitochondrial cytochrome b DNA sequences and phylogeny of formalin fixed sisorid fishes (Teleostei: Siluriformes). Zool Res. 1999;20:81–7.
Ma X, Kang J, Chen W, Zhou C, He S. Biogeographic history and high-elevation adaptations inferred from the mitochondrial genome of Glyptosternoid fishes (Sisoridae, Siluriformes) from the southeastern Tibetan plateau. BMC Evol Biol. 2015;15:233.
Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, et al. Host-gut microbiota metabolic interactions. Science. 2012;336:1262–7.
Tarnecki AM, Burgos FA, Ray CL, Arias CR. Fish intestinal microbiome: diversity and symbiosis unravelled by metagenomics. J Appl Microbiol. 2017;123(1):2–17.
Xia JH, Lin G, Fu GH, Wan ZY, Lee M, Wang L, et al. The intestinal microbiome of fish under starvation. BMC Genomics. 2014;15:266.
Bledsoe JW, Waldbieser GC, Swanson KS, Peterson BC, Small BC. Comparison of channel catfish and blue catfish gut microbiota assemblages shows minimal effects of host genetics on microbial structure and inferred function. Front Microbiol. 2018;9:1073.
Ramirez C, Coronado J, Silva A, Romero J. Cetobacterium is a major component of the microbiome of Giant Amazonian fish (Arapaima gigas) in Ecuador. Animals (Basel). 2018;8(11):189.
Wong S, Rawls JF. Intestinal microbiota composition in fishes is influenced by host ecology and environment. Mol Ecol. 2012;21(13):3100–2.
Wang Y, Xu L, Sun X, Wan X, Sun G, Jiang R, et al. Characteristics of the fecal microbiota of high- and low-yield hens and effects of fecal microbiota transplantation on egg production performance. Res Vet Sci. 2020;129:164–73.
Magoc T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27(21):2957–63.
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6.
Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics. 2011;27(16):2194–200.
Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods. 2013;10(10):996–8.
Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;73(16):5261–7.
Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7.
Park H, Yeo S, Arellano K, Kim HR, Holzapfel W. Role of the gut microbiota in health and disease. In: Di Gioia D, Biavati B, editors. Probiotics and prebiotics in animal health and food safety. Cham: Springer International Publishing; 2018. p. 35–62.
Kashinskaya EN, Belkova NL, Izvekova GI, Simonov EP, Andree KB, Glupov VV, et al. A comparative study on microbiota from the intestine of Prussian carp (Carassius gibelio) and their aquatic environmental compartments, using different molecular methods. J Appl Microbiol. 2015;119(4):948–61.
Liu H, Guo X, Gooneratne R, Lai R, Zeng C, Zhan F, et al. The gut microbiome and degradation enzyme activity of wild freshwater fishes influenced by their trophic levels. Sci Rep. 2016;6(1):24340.
Hennersdorf P, Kleinertz S, Theisen S, Abdul-Aziz MA, Mrotzek G, Palm HW, et al. Microbial diversity and parasitic load in tropical fish of different environmental conditions. PLoS One. 2016;11(3):e0151594.
Dehler CE, Secombes CJ, Martin SAM. Environmental and physiological factors shape the gut microbiota of Atlantic salmon parr (Salmo salar L.). Aquaculture. 2017;467:149–57.
Sekelja M, Berget I, Naes T, Rudi K. Unveiling an abundant core microbiota in the human adult colon by a phylogroup-independent searching approach. ISME J. 2011;5(3):519–31.
Jalanka-Tuovinen J, Salonen A, Nikkila J, Immonen O, Kekkonen R, Lahti L, et al. Intestinal microbiota in healthy adults: temporal analysis reveals individual and common core and relation to intestinal symptoms. PLoS One. 2011;6(7):e23035.
Li D, Chen H, Mao B, Yang Q, Zhao J, Gu Z, et al. Microbial biogeography and Core microbiota of the rat digestive tract. Sci Rep. 2017;8:45840.
Roeselers G, Mittge EK, Stephens WZ, Parichy DM, Cavanaugh CM, Guillemin K, et al. Evidence for a core gut microbiota in the zebrafish. ISME J. 2011;5(10):1595–608.
Hughes JB, Hellmann JJ, Ricketts TH, Bohannan BJM. Counting the uncountable: statistical approaches to estimating microbial diversity. Appl Environ Microbiol. 2001;67(10):4399–406.
Dhanasiri AKS, Brunvold L, Brinchmann MF, Korsnes K, Bergh Ø, Kiron V. Changes in the intestinal microbiota of wild Atlantic cod Gadus morhua L. Upon Captive Rearing. Microbial Ecol. 2011;61(1):20–30.
Hentschel U, Schmid M, Wagner M, Fieseler L, Gernert C, Hacker J. Isolation and phylogenetic analysis of bacteria with antimicrobial activities from the Mediterranean sponges Aplysina aerophoba and Aplysina cavernicola. FEMS Microbiol Ecol. 2001;35(3):305–12.
Abrashev IR, Genova VE, Sotirova AV, Ilieva KZ. Purification and partial characterization of neuraminidase from the non-pathogenic Arthrobacter nicotianae. Enzym Microb Technol. 1998;22(3):142–6.
Xia Z, Zhu M, Zhang Y. Effects of the probiotic Arthrobacter sp. CW9 on the survival and immune status of white shrimp (Penaeus vannamei). Lett Appl Microbiol. 2014;58(1):60–4.
Larsen AM, Mohammed HH, Arias CR. Characterization of the gut microbiota of three commercially valuable warmwater fish species. J Appl Microbiol. 2014;116(6):1396–404.
Sugita H, Kitao S, Narisawa S, Minamishima R, Itoi S. Diversity of culturable bacterial communities in the intestinal tracts of goldfish (Carassius auratus) and their ability to produce N-acyl homoserine lactone. Folia Microbiol (Praha). 2017;62(3):263–7.
Ye T, Zhou T, Li Q, Xu X, Fan X, Zhang L, et al. HN-2, a novel quorum quenching bacterial isolate, is a potent biocontrol agent against Xanthomonas campestris pv. Campestris. Microorganisms. 2019;8(1):45.
Bai Z, Ren T, Han Y, Rahman MM, Hu Y, Li Z, et al. Influences of dietary selenomethionine exposure on tissue accumulation, blood biochemical profiles, gene expression and intestinal microbiota of Carassius auratus. Comp Biochem Physiol C Toxicol Pharmacol. 2019;218:21–9.
Zheng M, Lu J, Lin G, Su H, Sun J, Luan T. Dysbiosis of gut microbiota by dietary exposure of three graphene-family materials in zebrafish (Danio rerio). Environ Pollut. 2019;254(Pt A):112969.
Parshukov AN, Kashinskaya EN, Simonov EP, Hlunov OV, Izvekova GI, Andree KB, et al. Variations of the intestinal gut microbiota of farmed rainbow trout, Oncorhynchus mykiss (Walbaum), depending on the infection status of the fish. J Appl Microbiol. 2019;127(2):379–95.
Tsuchiya C, Sakata T, Sugita H. Novel ecological niche of Cetobacterium somerae, an anaerobic bacterium in the intestinal tracts of freshwater fish. Lett Appl Microbiol. 2008;46(1):43–8.
Garrigues L, Maignien L, Lombard E, Singh J, Guillouet SE. Isopropanol production from carbon dioxide in Cupriavidus necator in a pressurized bioreactor. New Biotechnol. 2019;56:16–20.
Zenon S, Andrzej S. Cobamide dependent enzymes. In: Schneider Zenon SA, editor. Comprehensive B12. Berlin: de Gruyter; 1987. p. 225–66.
Makkar NS, Casida LE Jr. Cupriavidus necator gen. Nov., sp. nov.: a nonobligate bacterial predator of Bacteria in soil. Int J Syst Bacteriol. 1987;37(4):323–6.
Tang QQ, Feng L, Jiang WD, Liu Y, Jiang J, Li SH, et al. Effects of dietary copper on growth, digestive, and brush border enzyme activities and antioxidant defense of Hepatopancreas and intestine for young grass carp (Ctenopharyngodon idella). Biol Trace Elem Res. 2013;155(3):370–80.
Farmer BD, Beck BH, Mitchell AJ, Rawles SD, Straus DL. Dietary copper effects survival of channel catfish challenged with Flavobacterium columnare. Aquac Res. 2017;48(4):1751–8.
Gillan DC, Van Camp C, Mergeay M, Provoost A, Thomas N, Vermard L, et al. Paleomicrobiology to investigate copper resistance in bacteria: isolation and description of Cupriavidus necator B9 in the soil of a medieval foundry. Environ Microbiol. 2017;19(2):770–87.
Zhiying H, Guangming L. Basic characteristic of porphyry copper deposits and its Perspecting in Yaluzangbujiang Metallogenic Province, Tibet. Geol Prospecting. 2004;40(1):1–6.
Hongjing L, Na Z, Xiaotao L. Spatio-temporal characteristics of Yarlung Zangbo River in Tibet. J Henan Normal Univ (Natural Science). 2010;38(2):126–30.
This research was supported by Key R & D and transformation program in Tibet Autonomous Region (Large scale breeding of Glyptosternum maculatum and conservation of reserved parent fish germplasm) Special Finance of the Ministry of Agriculture and Rural Areas (Investigation on Fishery Resources and Environment in Key Waters of Tibet). The funding body had no role in the study design, data collection and interpretation or the decision to submit the work for publication.
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All animal experiments were performed according to protocols and guidelines approved by the Institutional Animal Care and Use Committee of Tibet Academy of Agricultural and Animal Husbandry Sciences, China.
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Pan, Y., Li, Z., Zhou, J. et al. Cupriavidus in the intestinal microbiota of Tibet endemic fish Glyptosternum maculatum can help it adapt to habitat of the Qinghai Tibet Plateau. BMC Vet Res 17, 377 (2021). https://doi.org/10.1186/s12917-021-03092-5
- Glyptosternum maculatum
- Intestinal microbiota