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The Underlying Ecological Processes of Gut Microbiota Among Cohabitating Retarded, Overgrown and Normal Shrimp

  • Host Microbe Interactions
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Abstract

Increasing evidence of tight links among the gut microbiota, obesity, and host health has emerged, but knowledge of the ecological processes that shape the variation in microbial assemblages across growth rates remains elusive. Moreover, inadequately control for differences in factors that profoundly affect the gut microbial community, hampers evaluation of the gut microbiota roles in regulating growth rates. To address this gap, we evaluated the composition and ecological processes of the gut bacterial community in cohabitating retarded, overgrown, and normal shrimps from identically managed ponds. Gut bacterial community structures were distinct (P = 0.0006) among the shrimp categories. Using a structural equation modeling (SEM), we found that changes in the gut bacterial community were positively related to digestive activities, which subsequently affected shrimp growth rate. This association was further supported by intensified interspecies interaction and enriched lineages with high nutrient intake efficiencies in overgrown shrimps. However, the less phylogenetic clustering of gut microbiota in overgrown and retarded subjects may offer empty niches for pathogens invasion, as evidenced by higher abundances of predicted functional pathways involved in disease infection. Given no differences in biotic and abiotic factors among the cohabitating shrimps, we speculated that the distinct gut community assembly could be attributed to random colonization in larval shrimp (e.g., priority effects) and that an altered microbiota could be a causative factor in overgrowth or retardation in shrimp. To our knowledge, this is the first study to provide an integrated overview of the direct roles of gut microbiota in shaping shrimp growth rate and the underlying ecological mechanisms.

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References

  1. Sommer F, Bäckhed F (2013) The gut microbiota—masters of host development and physiology. Nat Rev Microbiol 11:227–238

    Article  CAS  PubMed  Google Scholar 

  2. Tap J, Furet JP, Bensaada M, Philippe C, Roth H, Rabot S, Lakhdari O, Lombard V, Henrissat B, Corthier G (2015) Gut microbiota richness promotes its stability upon increased dietary fibre intake in healthy adults. Environ. Microbiol. 17:4954–4964

    Article  CAS  PubMed  Google Scholar 

  3. Xiong J, Wang K, Wu J, Qiuqian L, Yang K, Qian Y, Zhang D (2015) Changes in intestinal bacterial communities are closely associated with shrimp disease severity. Appl. Microbiol. Biotechnol. 99:6911–6919

    Article  CAS  PubMed  Google Scholar 

  4. Mosca A, Leclerc M, Hugot JP (2016) Gut microbiota diversity and human diseases: should we reintroduce key predators in our ecosystem? Front. Microbiol. 7:455

    Article  PubMed  PubMed Central  Google Scholar 

  5. Yan Q, Li J, Yu Y, Wang J, He Z, Van Nostrand JD, Kempher ML, Wu L, Wang Y, Liao L, Li X, Wu S, Ni J, Wang C, Zhou J (2016) Environmental filtering decreases with fish development for the assembly of gut microbiota. Environ. Microbiol. doi:10.1111/1462-2920.13365

    Google Scholar 

  6. Ng'ambi J, Li R, Mu C, Song W, Liu L, Wang C (2016) Dietary administration of saponin stimulates growth of the swimming crab Portunus Trituberculatus and enhances its resistance against vibrio alginolyticus infection. Fish Shellfish Immunol 59:1050–4648

    Article  Google Scholar 

  7. Xiong J, Zhu J, Zhang D (2014) The application of bacterial indicator phylotypes to predict shrimp health status. Appl. Microbiol. Biotechnol. 98:8291–8299

    Article  CAS  PubMed  Google Scholar 

  8. Sabes-Figuera R, Knapp M, Bendeck M, Mompart-Penina A, Salvador-Carulla L (2015) The composition of the gut microbiota throughout life, with an emphasis on early life. Microb. Ecol. Health Dis. 26:24–29

    Google Scholar 

  9. Burns AR, Stephens WZ, Stagaman K, Wong S, Rawls JF, Guillemin K, Bohannan BJM (2016) Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development. ISME J 10:655–664

    Article  CAS  PubMed  Google Scholar 

  10. Ramayo-Caldas Y, Mach N, Lepage P, Levenez F, Denis C, Lemonnier G, Leplat JJ, Billon Y, Berri M, Doré J, Rogel-Gaillard C, Estellé J (2016) Phylogenetic network analysis applied to pig gut microbiota identifies an ecosystem structure linked with growth traits. ISME J 10:2973–2977

  11. Miyanaga A, Shimizu K, Noro R, Seike M, Kitamura K, Kosaihira S, Minegishi Y, Shukuya T, Yoshimura A, Kawamoto M (2011) Enterotypes of the human gut microbiome. Nature 473:174–180

    Article  Google Scholar 

  12. Sha Y, Liu M, Wang B, Jiang K, Sun G, Wang L (2016) Gut bacterial diversity of farmed sea cucumbers Apostichopus japonicus with different growth rates. Microbiology 85:109–115

    Article  CAS  Google Scholar 

  13. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444:1027–1031

    Article  PubMed  Google Scholar 

  14. Riva A, Borgo F, Lassandro C, Verduci E, Morace G, Borghi E, Berry D (2016) Pediatric obesity is associated with an altered gut microbiota and discordant shifts in Firmicutes populations. Environ. Microbiol. doi:10.1111/1462-2920.13463

    PubMed  Google Scholar 

  15. Holmes E, Li JV, Marchesi JR, Nicholson JK (2012) Gut microbiota composition and activity in relation to host metabolic phenotype and disease risk. Cell Metab. 16:559–564

    Article  CAS  PubMed  Google Scholar 

  16. Ferrer M, Ruiz A, Lanza F, Haange SB, Oberbach A, Till H, Bargiela R, Campoy C, Segura MT, Richter M (2013) Microbiota from the distal guts of lean and obese adolescents exhibit partial functional redundancy besides clear differences in community structure. Environ. Microbiol. 15:211–226

    Article  CAS  PubMed  Google Scholar 

  17. Sullam KE, Essinger SD, Lozupone CA, O’Connor MP, Rosen GL, Knight R, Kilham SS, Russell JA (2012) Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis. Mol. Ecol. 21:3363–3378

    Article  PubMed  Google Scholar 

  18. Wiens JJ, Ackerly DD, Allen AP, Anacker BL, Buckley LB, Cornell HV, Damschen EI, Davies TJ, Grytnes JA, Harrison SP (2010) Niche conservatism as an emerging principle in ecology and conservation biology. Ecol. Lett. 13:1310–1324

    Article  PubMed  Google Scholar 

  19. Zhu J, Dai W, Qiu Q, Dong C, Zhang J, Xiong J (2016) Contrasting ecological processes and functional compositions between intestinal bacterial community in healthy and diseased shrimp. Microb. Ecol. 72:975–985

    Article  PubMed  Google Scholar 

  20. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, Gordon JI (2009) A core gut microbiome in obese and lean twins. Nature 457:480–484

    Article  CAS  PubMed  Google Scholar 

  21. Duran-Pinedo AE, Paster B, Teles R, Friaslopez J (2011) Correlation network analysis applied to complex biofilm communities. PLoS One 6:e28438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Hallam SJ, McCutcheon JP (2015) Microbes don’t play solitaire: how cooperation trumps isolation in the microbial world. Environ. Microbiol. Rep. 7:26–28

    Article  PubMed  Google Scholar 

  23. Egan S, Gardiner M (2016) Microbial dysbiosis: rethinking disease in marine ecosystems. Front. Microbiol. 7:991

    PubMed  PubMed Central  Google Scholar 

  24. Faust K, Raes J (2012) Microbial interactions: from networks to models. Nat Rev Microbiol 10:538–550

    Article  CAS  PubMed  Google Scholar 

  25. Xiong J, Chen H, Hu C, Ye X, Kong D, Zhang D (2015) Evidence of bacterioplankton community adaptation in response to long-term mariculture disturbance. Sci Rep 5:15274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF (2011) Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J 5:1571–1579

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Magoč T, Salzberg SL (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963

    Article  PubMed  PubMed Central  Google Scholar 

  28. Caporaso JG, Kuczynski J, Stombaugh J (2010) QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7:335–336

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461

    Article  CAS  PubMed  Google Scholar 

  31. De Santis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied Environ Microbiol 72:5069–5072

    Article  CAS  Google Scholar 

  32. De Santis TZ, Hugenholtz P, Keller K, Brodie EL, Larsen N, Piceno YM, Phan R, Andersen GL (2006) NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes. Nucleic Acids Res. 34:394–399

    Article  Google Scholar 

  33. Price MN, Dehal PS, Arkin AP (2009) FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26:1641–1650

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Clarke KR (1993) Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 18:117–143

    Article  Google Scholar 

  35. R Development Core Team (2013) R: A language and environment for statistical computing

  36. Dufrêne M, Legendre P (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr. 67:345–366

    Google Scholar 

  37. Roberts DW (2007) labdsv: Ordination and multivariate analysis for ecology. R package version

  38. Chase JM, Kraft NJ, Smith KG, Vellend M, Inouye BD (2011) Using null models to disentangle variation in community dissimilarity from variation in α-diversity. Ecosphere 2:art24

    Article  Google Scholar 

  39. Stegen JC, Lin X, Fredrickson JK, Chen X, Kennedy DW, Murray CJ, Rockhold ML, Konopka A (2013) Quantifying community assembly processes and identifying features that impose them. ISME J 7:2069–2079

    Article  PubMed  PubMed Central  Google Scholar 

  40. Kembel SW, Cowan PD, Helmus MR, Cornwell WK, Morlon H, Ackerly DD, Blomberg SP, Webb CO (2010) Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–1464

    Article  CAS  PubMed  Google Scholar 

  41. Webb CO, Ackerly DD, McPeek MA, Donoghue MJ (2002) Phylogenies and community ecology. Ann Rev Ecol Syst 33:475–505

    Article  Google Scholar 

  42. Deng Y, Jiang Y, Yang Y, He Z, Luo F, Zhou J (2012) Molecular ecological network analyses. BMC Bioinformatics 13:113

    Article  PubMed  PubMed Central  Google Scholar 

  43. Newman MEJ (2003) The structure and function of complex networks. SIAM Rev. 45:167–256

    Article  Google Scholar 

  44. Shannon P, Markiel A, Ozier O, Baliga NS, Wang J, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13:2498–2504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Langille MG, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Thurber RLV, Knight R (2013) Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotech 31:814–821

    Article  CAS  Google Scholar 

  46. Wu J, Xiong J, Hu C, Shi Y, Wang K, Zhang D (2015) Temperature sensitivity of soil bacterial community along contrasting warming gradient. Appl. Soil Ecol. 94:40–48

    Article  Google Scholar 

  47. Newman ME (2006) Modularity and community structure in networks. Proc Nat Acad Sci USA 103:8577–8582

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Guimera R, Sales-Pardo M, Amaral LA (2007) Classes of complex networks defined by role-to-role connectivity profiles. Nat Physcis 3:63–69

    Article  CAS  Google Scholar 

  49. Bäckhed F, Fraser C, Ringel Y, Sanders ME, Sartor RB, Sherman P, Versalovic J, Young V, Finlay BB (2012) Defining a healthy human gut microbiome: current concepts, future directions, and clinical applications. Cell Host Microbe 12:611–622

    Article  PubMed  Google Scholar 

  50. Gilbert JA, Quinn RA, Debelius J, Xu ZZ, Morton J, Garg N, Jansson JK, Dorrestein PC, Knight R (2016) Microbiome-wide association studies link dynamic microbial consortia to disease. Nature 535:94–103

    Article  CAS  PubMed  Google Scholar 

  51. Xiong J, Dai W, Li C (2016) Advances, challenges, and directions in shrimp disease control: the guidelines from an ecological perspective. Appl Microbiol Biotech 100:6947–6954

    Article  CAS  Google Scholar 

  52. Fukami T (2015) Historical contingency in community assembly: integrating niches, species pools, and priority fffects. Ann Rev Ecol Evol Syst 46:1–23

    Article  Google Scholar 

  53. Fjellheim AJ, Playfoot KJ, Skjermo J, Vadstein O (2012) Inter-individual variation in the dominant intestinal microbiota of reared Atlantic cod (Gadus morhua L.) larvae. Aquac. Res. 43:1499–1508

    Article  Google Scholar 

  54. Harakeh SM, Khan I, Kumosani T, Barbour E, Almasaudi SB, Bahijri SM, Alfadul SM, Ajabnoor GMA, Azhar EI (2016) Gut microbiota: a contributing factor to obesity. Front Cell Infet Microbiol 6:95

    Google Scholar 

  55. Mcilroy SJ, Nielsen PH (2014) The family Saprospiraceae. pp 863–889

  56. Galitskaya P, Akhmetzyanova L, Selivanovskaya S (2016) Biochar carrying hydrocarbon decomposers promotes degradation during the early stage of bioremediation. Biogeosci Discuss 13:5739–5752

    Article  Google Scholar 

  57. Lebba V, Santangelo F, Totino V, Nicoletti M, Gagliardi A, De Biase RV, Cucchiara S, Nencioni L, Conte MP, Schippa S (2013) Higher prevalence and abundance of Bdellovibrio bacteriovorus in the human gut of healthy subjects. PLoS One 8:e61608

    Article  Google Scholar 

  58. Lozupone CA, Stombaugh JI, Gordon JI, Jansson JK, Knight R (2012) Diversity, stability and resilience of the human gut microbiota. Nature 489:220–230

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Stecher B, Chaffron S, Käppeli R, Hapfelmeier S, Freedrich S, Weber TC, Kirundi J, Suar M, Mccoy KD, Von MC (2010) Like will to like: abundances of closely related species can predict susceptibility to intestinal colonization by pathogenic and commensal bacteria. PLoS Path 6:e1000711

    Article  Google Scholar 

  60. Wagner A (2011) Genotype networks shed light on evolutionary constraints. Trends Ecol. Evol. 26:577–584

    Article  PubMed  Google Scholar 

  61. Adler PB, Hillerislambers J, Levine JM (2007) A niche for neutrality. Ecol. Lett. 10:95–104

    Article  PubMed  Google Scholar 

  62. Mayfield MM, Levine JM (2010) Opposing effects of competitive exclusion on the phylogenetic structure of communities. Ecol. Lett. 13:1085–1093

    Article  PubMed  Google Scholar 

  63. Inglis RF, Gardner A, Cornelis P, Buckling A (2009) Spite and virulence in the bacterium Pseudomonas Aeruginosa. Proc Nat Acad Sci USA 106:5703–5707

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Jousset A, Schulz W, Scheu S, Eisenhauer N (2011) Intraspecific genotypic richness and relatedness predict the invasibility of microbial communities. ISME J 5:1108–1114

    Article  PubMed  PubMed Central  Google Scholar 

  65. Yiu JHC, Dorweiler B, Woo CW (2016) Interaction between gut microbiota and toll-like receptor: from immunity to metabolism. J Mol Med. doi:10.1007/s00109-016-1474-4

  66. Mallon CA, Elsas JDV, Salles JF (2015) Microbial invasions: the process, patterns, and mechanisms. Trends Microbiol. 23:719–729

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the Zhejiang Province Public Welfare Technology Application Research Project (2016C32063), and the Open Fund of Key Laboratory of Marine Biogenetic Resources, Third Institute of Oceanography (HY201601); the Project of Science and Technology Department of Ningbo (2015C10062); and the KC Wong Magna Fund in Ningbo University.

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Authors and Affiliations

  1. School of Marine Sciences, Ningbo University, Ningbo, 315211, China

    Jinbo Xiong, Wenfang Dai, Jinyong Zhu & Qiongfen Qiu

  2. Collaborative Innovation Center for Zhejiang Marine High-Efficiency and Healthy Aquaculture, Ningbo, 315211, China

    Jinbo Xiong & Wenfang Dai

  3. Key Laboratory of Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100085, China

    Keshao Liu

  4. Key Laboratory of Marine Biogenetic Resources, Third Institute of Oceanography, State of Oceanic Administration, Xiamen, 361006, China

    Chunming Dong

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  1. Jinbo Xiong
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  4. Keshao Liu
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Correspondence to Jinbo Xiong.

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Xiong, J., Dai, W., Zhu, J. et al. The Underlying Ecological Processes of Gut Microbiota Among Cohabitating Retarded, Overgrown and Normal Shrimp. Microb Ecol 73, 988–999 (2017). https://doi.org/10.1007/s00248-016-0910-x

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