Skip to main content
SpringerLink
Log in

Regime transition Shapes the Composition, Assembly Processes, and Co-occurrence Pattern of Bacterioplankton Community in a Large Eutrophic Freshwater Lake

  • Microbiology of Aquatic Systems
  • Published:
Microbial Ecology Aims and scope Submit manuscript

Abstract

At certain nutrient concentrations, shallow freshwater lakes are generally characterized by two contrasting ecological regimes with disparate patterns of biodiversity and biogeochemical cycles: a macrophyte-dominated regime (MDR) and a phytoplankton-dominated regime (PDR). To reveal ecological mechanisms that affect bacterioplankton along the regime shift, Illumina MiSeq sequencing of the 16S rRNA gene combined with a novel network clustering tool (Manta) were used to identify patterns of bacterioplankton community composition across the regime shift in Taihu Lake, China. Marked divergence in the composition and ecological assembly processes of bacterioplankton community was observed under the regime shift. The alpha diversity of the bacterioplankton community consistently and continuously decreased with the regime shift from MDR to PDR, while the beta diversity presents differently. Moreover, as the regime shifted from MDR to PDR, the contribution of deterministic processes (such as environmental selection) to the assembly of bacterioplankton community initially decreased and then increased again as regime shift from MDR to PDR, most likely as a consequence of differences in nutrient concentration. The topological properties, including modularity, transitivity and network diameter, of the bacterioplankton co-occurrence networks changed along the regime shift, and the co-occurrences among species changed in structure and were significantly shaped by the environmental variables along the regime transition from MDR to PDR. The divergent environmental state of the regimes with diverse nutritional status may be the most important factor that contributes to the dissimilarity of bacterioplankton community composition along the regime shift.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data Availability

The raw reads were deposited into the NCBI Sequence Read Archive (SRA) database (BioProject: PRJNA511603).

Code Availability

Not applicable.

References

  1. Scheffer M, van Nes EH (2007) Shallow lakes theory revisited: various alternative regimes driven by climate, nutrients, depth and lake size. Hydrobiologia 584:455–466. https://doi.org/10.1007/s10750-007-0616-7

    Article  CAS  Google Scholar 

  2. Scheffer M, Hosper SH, Meijer ML, Moss B, Jeppesen E (1993) Alternative equilibria in shallow lakes. Trends Ecol Evol 8:275–279. https://doi.org/10.1016/0169-5347(93)90254-M

    Article  CAS  PubMed  Google Scholar 

  3. Wang Y, Cao X et al (2020) Distinct shifts in bacterioplankton community composition and functional gene structure between macrophyte-and phytoplankton-dominated regimes in a large shallow lake. Limnol Oceanogr 65:S208–S219. https://doi.org/10.1002/lno.11373

    Article  Google Scholar 

  4. Van der Gucht K, Sabbe K et al (2010) Contrasting bacterioplankton community composition and seasonal dynamics in two neighbouring hypertrophic freshwater lakes. Environ Microbiol 3:680–690. https://doi.org/10.1046/j.1462-2920.2001.00242.x

    Article  Google Scholar 

  5. Haukka K, Kolmonen E et al (2006) Effect of nutrient loading on bacterioplankton community composition in lake mesocosms. Microb Ecol 51:137–146. https://doi.org/10.1007/s00248-005-0049-7

    Article  PubMed  Google Scholar 

  6. Dakos V, Matthews B et al (2019) Ecosystem tipping points in an evolving world. Nat Ecol Evol 3:355–362. https://doi.org/10.1038/s41559-019-0797-2

    Article  PubMed  Google Scholar 

  7. Wang H, Wang H, Liang X, Wu S (2014) Total phosphorus thresholds for regime shifts are nearly equal in subtropical and temperate shallow lakes with moderate depths and areas. Freshw Biol 59:1659–1671. https://doi.org/10.1111/fwb.12372

    Article  CAS  Google Scholar 

  8. Wetzel RG, Søndergaard M (1998) Role of submerged macrophytes for the microbial community and dynamics of dissolved organic carbon in aquatic ecosystems. In: Jeppesen E, Søndergaard M, Søndergaard M, Christoffersen K (eds) The structuring role of submerged macrophytes in Lakes. Springer, New York, pp 133–148

    Chapter  Google Scholar 

  9. González Sagrario MA, Jeppesen E et al (2005) Does high nitrogen loading prevent clear-water conditions in shallow lakes at moderately high phosphorus concentrations? Freshw Biol 50:27–41. https://doi.org/10.1111/j.1365-2427.2004.01290.x

    Article  CAS  Google Scholar 

  10. Zimmer KD, Hanson MA, Herwig BR, Konsti ML (2009) Thresholds and stability of alternative regimes in shallow Prairie-Parkland Lakes of Central North America. Ecosystems 12:843–852. https://doi.org/10.1007/s10021-009-9262-4

    Article  Google Scholar 

  11. Hanashiro FTT, Mukherjee S et al (2019) Freshwater bacterioplankton metacommunity structure along urbanization gradients in Belgium. Front Microbiol 10:743. https://doi.org/10.3389/fmicb.2019.00743

    Article  PubMed  PubMed Central  Google Scholar 

  12. Khazaei T, Williams RL et al (2020) Metabolic multistability and hysteresis in a model aerobe-anaerobe microbiome community. Sci Adv 6:eaba353. https://doi.org/10.1126/sciadv.aba0353

    Article  CAS  Google Scholar 

  13. Hillebrand H, Langenheder S et al (2018) Decomposing multiple dimensions of stability in global change experiments. Ecol Lett 21:21–30. https://doi.org/10.1111/ele.12867

    Article  PubMed  Google Scholar 

  14. Gonze D, Lahti L, Raes J, Faust K (2017) Multi-stability and the origin of microbial community types. ISME J 11:2159–2166. https://doi.org/10.1038/ismej.2017.60

    Article  PubMed  PubMed Central  Google Scholar 

  15. Jeppesen E, Jensen JP et al (1997) Top-down control in freshwater lakes: the role of nutrient state, submerged macrophytes and water depth. Hydrobiologia 342:151–164. https://doi.org/10.1023/a:1017046130329

    Article  Google Scholar 

  16. Han X, Schubert CJ, Fiskal A, Dubois N, Lever MA (2020) Eutrophication as a driver of microbial community structure in lake. Environ Microbiol 22:3446–3462. https://doi.org/10.1111/1462-2920.15115

    Article  CAS  PubMed  Google Scholar 

  17. Corno G, Caravati E, Callieri C, Bertoni R (2008) Effects of predation pressure on bacterial abundance, diversity, and size-structure distribution in an oligotrophic system. J Limnol 67:107–119. https://doi.org/10.4081/jlimnol.2008.107

    Article  Google Scholar 

  18. Berga M, Östman Ö, Lindström ES, Langenheder S (2014) Combined effects of zooplankton grazing and dispersal on the diversity and assembly mechanisms of bacterial metacommunities. Environ Microbiol 17:2275–2287. https://doi.org/10.1111/1462-2920.12688

    Article  Google Scholar 

  19. Chang W, Sun J et al (2020) Effects of different habitats on the bacterial community composition in the water and sediments of Lake Taihu, China. Environ Sci Pollut Res 27:44983–44994. https://doi.org/10.1007/s11356-020-10376-0

    Article  CAS  Google Scholar 

  20. Wu QL, Zwart G et al (2010) Submersed macrophytes play a key role in structuring bacterioplankton community composition in the large, shallow, subtropical Taihu Lake, China. Environ Microbiol 9:2765–2774. https://doi.org/10.1111/j.1462-2920.2007.01388.x

    Article  CAS  Google Scholar 

  21. Pang X, Shen H et al (2014) Dissolved organic carbon and relationship with bacterioplankton community composition in 3 lake regions of Lake Taihu, China. Can J Microbiol 60:669–680. https://doi.org/10.1139/cjm-2013-0847

    Article  CAS  PubMed  Google Scholar 

  22. Zhou L, Zhou Y, Tang X, Zhang Y, Jeppesen E (2021) Biodegradable dissolved organic carbon shapes bacterial community structures and co-occurrence patterns in large eutrophic Lake Taihu. J Environ Sci 107:205–217. https://doi.org/10.1016/j.jes.2021.02.011

    Article  CAS  Google Scholar 

  23. Langenheder S, Székely AJ (2011) Species sorting and neutral processes are both important during the initial assembly of bacterial communities. ISME J 5:1086–1094. https://doi.org/10.1038/ismej.2010.207

    Article  PubMed  PubMed Central  Google Scholar 

  24. Stegen JC, Lin X, Fredrickson JK, Konopka AE (2015) Estimating and mapping ecological processes influencing microbial community assembly. Front Microbiol 6:370. https://doi.org/10.3389/fmicb.2015.00370

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zhou J, Ning D (2017) Stochastic community assembly: does it matter in microbial ecology? Microbiol Mol Biol Rev. https://doi.org/10.1128/mmbr.00002-17

    Article  PubMed  PubMed Central  Google Scholar 

  26. Stegen JC, Lin X et al (2013) Quantifying community assembly processes and identifying features that impose them. ISME J 7:2069–2079. https://doi.org/10.1038/ismej.2013.93

    Article  PubMed  PubMed Central  Google Scholar 

  27. Wang J, Shen J et al (2013) Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes. ISME J 7:1310–1321. https://doi.org/10.1038/ismej.2013.30

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Röttjers L, Faust K (2020) manta: a clustering algorithm for weighted ecological networks. Msystems. https://doi.org/10.1128/mSystems.00903-19

    Article  PubMed  PubMed Central  Google Scholar 

  29. Röttjers L, Faust K (2018) From hairballs to hypotheses–biological insights from microbial networks. FEMS Microbiol Rev 42:761–780. https://doi.org/10.1093/femsre/fuy030

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ma B, Wang Y et al (2020) Earth microbial co-occurrence network reveals interconnection pattern across microbiomes. Microbiome 8:1–12. https://doi.org/10.1186/s40168-020-00857-2

    Article  CAS  Google Scholar 

  31. Lima-Mendez G, Faust K et al (2015) Determinants of community structure in the global plankton interactome. Science 348:1262073. https://doi.org/10.1126/science.1262073

    Article  CAS  PubMed  Google Scholar 

  32. Berry D, Widder S (2014) Deciphering microbial interactions and detecting keystone species with co-occurrence networks. Front Microbiol 5:219. https://doi.org/10.3389/fmicb.2014.00219

    Article  PubMed  PubMed Central  Google Scholar 

  33. Qin B, Liu Z, Havens K (2007) Eutrophication of Shallow Lakes with Special Reference to Lake Taihu, China. Springer, Netherlands

  34. Janssen AB, de Jager VC et al (2017) Spatial identification of critical nutrient loads of large shallow lakes: implications for Lake Taihu (China). Water Res 119:276–287. https://doi.org/10.1016/j.watres.2017.04.045

    Article  CAS  PubMed  Google Scholar 

  35. Qin B, Xu P, Wu Q, Luo L, Zhang Y (2007) Environmental issues of Lake Taihu, China. Hydrobiologia 581:3–14. https://doi.org/10.1007/s10750-006-0521-5

    Article  CAS  Google Scholar 

  36. Caporaso JG, Lauber CL et al (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. Isme J Multidiscip J Microbial Ecol 6:1621–1624. https://doi.org/10.1038/ismej.2012.8

    Article  CAS  Google Scholar 

  37. Edgar RC (2013) UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996–998. https://doi.org/10.1038/nmeth.2604

    Article  CAS  PubMed  Google Scholar 

  38. Faith DP (1992) Conservation evaluation and phylogenetic diversity. Biol Conserv 61:1–10. https://doi.org/10.1016/0006-3207(92)91201-3

    Article  Google Scholar 

  39. Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71:8228–8235. https://doi.org/10.1128/AEM.71.12.8228-8235.2005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Oksanen J, Blanchet FG et al (2013) vegan: Community Ecology Package. R package version 2: http://CRAN.R-project.org/package=vegan

  41. Zapala MA, Schork NJ (2006) Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables. Proc Natl Acad Sci 103:19430–19435. https://doi.org/10.1073/pnas.0609333103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Chafee M, Fernàndez-Guerra A et al (2017) Recurrent patterns of microdiversity in a temperate coastal marine environment. ISME J 12:237–252. https://doi.org/10.1038/ismej.2017.165

    Article  PubMed  PubMed Central  Google Scholar 

  43. Legendre P, Legendre LF (2012) Numerical ecology, vol 24, 3rd edn. Elsevier Science, Oxford

    Google Scholar 

  44. Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5:e9490. https://doi.org/10.1371/journal.pone.0009490

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Dini-Andreote F, Stegen JC, Van Elsas JD, Salles JF (2015) Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession. Proc Natl Acad Sci 112:E1326–E1332. https://doi.org/10.1073/pnas.1414261112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Webb CO, Ackerly DD, McPeek MA, Donoghue MJ (2002) Phylogenies and community ecology. Annu Rev Ecol Syst 33:475–505. https://doi.org/10.1146/annurev.ecolsys.33.010802.150448

    Article  Google Scholar 

  47. Kembel SW, Cowan PD et al (2010) Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–1464. https://doi.org/10.1093/bioinformatics/btq166

    Article  CAS  PubMed  Google Scholar 

  48. Stegen JC, Lin X, Konopka AE, Fredrickson JK (2012) Stochastic and deterministic assembly processes in subsurface microbial communities. ISME J 6:1653–1664. https://doi.org/10.1038/ismej.2012.22

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Weiss S, Treuren WV et al (2016) Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J 10:1669–1681. https://doi.org/10.1038/ismej.2015.235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Faust K, Raes J (2012) Microbial interactions: from networks to models. Nat Rev Microbiol 10:538–550. https://doi.org/10.1038/nrmicro2832

    Article  CAS  PubMed  Google Scholar 

  51. Ognyanova K (2016) Network Analysis and Visualization with R and igraph

  52. Shannon P, Markiel A et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504. https://doi.org/10.1101/gr.1239303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Csardi G (2006) The igraph software package for complex network research 1695

  54. Guimerà R, Amaral LAN (2005) Functional cartography of complex metabolic networks. Nature 433:895–900. https://doi.org/10.1038/nature03288

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Guimerà R, Sales-Pardo M, Amaral LAN (2007) Classes of complex networks defined by role-to-role connectivity profiles. Nat Phys 3:63–69. https://doi.org/10.1038/nphys489

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Deng Y, Jiang Y et al (2012) Molecular ecological network analyses. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-13-113

    Article  PubMed  PubMed Central  Google Scholar 

  57. Zhao D, Cao X et al (2017) The heterogeneity of composition and assembly processes of the microbial community between different nutrient loading lake zones in Taihu Lake. Appl Microbiol Biotechnol 101:1–11. https://doi.org/10.1007/s00253-017-8327-0

    Article  CAS  Google Scholar 

  58. Ren L, Song X et al (2017) Contrasting patterns of freshwater microbial metabolic potentials and functional gene interactions between an acidic mining lake and a weakly alkaline lake. Limnol Oceanogr 63:S354–S366. https://doi.org/10.1002/lno.10744

    Article  CAS  Google Scholar 

  59. Brothers SM, Hilt S et al (2013) A regime shift from macrophyte to phytoplankton dominance enhances carbon burial in a shallow, eutrophic lake. Ecosphere 4:1–17. https://doi.org/10.1890/ES13-00247.1

    Article  Google Scholar 

  60. Xu H, Zhao D et al (2020) Distinct successional patterns and processes of free-living and particle-attached bacterial communities throughout a phytoplankton bloom. Freshw Biol 65:1363–1375. https://doi.org/10.1111/fwb.13505

    Article  Google Scholar 

  61. Zeng J, Jiao CC et al (2019) Patterns and assembly processes of planktonic and sedimentary bacterial community differ along a trophic gradient in freshwater lakes. Ecol Ind. https://doi.org/10.1016/j.ecolind.2019.105491

    Article  Google Scholar 

  62. Carpenter SR, Lathrop RC (2008) Probabilistic estimate of a threshold for eutrophication. Ecosystems 11:601–613. https://doi.org/10.1007/S10021-008-9145-0

    Article  CAS  Google Scholar 

  63. Qin B, Chen W, Hu W (2004) Succession of ecological environment and its mechanism in Lake Taihu (in Chinese). China Science Press, Beijing

    Google Scholar 

  64. Molinos-Senante M, Hernández-Sancho F, Sala-Garrido R, Garrido-Baserba M (2011) Economic feasibility study for phosphorus recovery processes. Ambio 40:408–416. https://doi.org/10.1007/s13280-010-0101-9

    Article  PubMed  Google Scholar 

  65. Huang L, Fang H, He G, Jiang H, Wang C (2016) Effects of internal loading on phosphorus distribution in the Taihu Lake driven by wind waves and lake currents. Environ Pollut 219:760–773. https://doi.org/10.1016/j.envpol.2016.07.049

    Article  CAS  PubMed  Google Scholar 

  66. Elser JJ, Marzolf ER, Goldman CR (1990) Phosphorus and nitrogen limitation of phytoplankton growth in the freshwaters of North America: a review and critique of experimental enrichments. Can J Fish Aquat Sci 47:1468–1477. https://doi.org/10.1139/f90-165

    Article  CAS  Google Scholar 

  67. Wu L, Ge G, Gong S, Li S, Wan J (2012) Diversity and composition of the bacterial community of Poyang Lake (China) as determined by 16S rRNA gene sequence analysis. World J Microbiol Biotechnol 28:233–244. https://doi.org/10.1007/s11274-011-0812-5

    Article  CAS  PubMed  Google Scholar 

  68. Zeng J, Bian YQ, Xing P, Wu QL (2012) Macrophyte species drive the variation of bacterioplankton community composition in a shallow freshwater lake. Appl Environ Microbiol 78:177–184. https://doi.org/10.1128/AEM.05117-11

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Su X, Steinman AD et al (2017) Response of bacterial communities to cyanobacterial harmful algal blooms in Lake Taihu, China. Harmful Algae 68:168–177. https://doi.org/10.1016/j.hal.2017.08.007

    Article  PubMed  Google Scholar 

  70. Kim B-R, Shin J et al (2017) Deciphering diversity indices for a better understanding of microbial communities. J Microbiol Biotechnol 27:2089–2093. https://doi.org/10.4014/jmb.1709.09027

    Article  PubMed  Google Scholar 

  71. Xing P, Guo L, Tian W, Wu QL (2010) Novel Clostridium populations involved in the anaerobic degradation of Microcystis blooms. ISME J 5:792–800. https://doi.org/10.1038/ismej.2010.176

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Li J, Wang G et al (2017) Dynamic changes of bacterial community structure in the occurrence process of cyanobacterial bloom. J China Agric Univ 22:134–142. https://doi.org/10.11841/j.issn.1007-4333.2017.07.16

    Article  Google Scholar 

  73. Zhou J, Deng Y et al (2014) Stochasticity, succession, and environmental perturbations in a fluidic ecosystem. Proc Natl Acad Sci 111:836–845. https://doi.org/10.1073/pnas.1324044111

    Article  CAS  Google Scholar 

  74. Zhou J, Liu W et al (2013) Stochastic assembly leads to alternative communities with distinct functions in a bioreactor microbial community. MBio 4:49–52. https://doi.org/10.1128/mBio.00584-12

    Article  Google Scholar 

  75. Van der Plas F, Anderson TM, Olff H (2012) Trait similarity patterns within grass and grasshopper communities: multitrophic community assembly at work. Ecology 93:836–846. https://doi.org/10.1890/11-0975.1

    Article  PubMed  Google Scholar 

  76. Gerisch M, Dziock F (2012) More species, but all do the same: contrasting effects of flood disturbance on ground beetle functional and species diversity. Oikos 121:508–515. https://doi.org/10.1111/j.1600-0706.2011.19749.x

    Article  Google Scholar 

  77. Chase JM (2010) Stochastic community assembly causes higher biodiversity in more productive environments. Science 328:1388–1391. https://doi.org/10.1126/science.1187820

    Article  CAS  PubMed  Google Scholar 

  78. Liu L, Yang J, Lv H, Yu Z (2014) Synchronous dynamics and correlations between bacteria and phytoplankton in a subtropical drinking water reservoir. FEMS Microbiol Ecol 90:126–138. https://doi.org/10.1111/1574-6941.12378

    Article  CAS  PubMed  Google Scholar 

  79. Berry MA, Davis TW et al (2017) Cyanobacterial harmful algal blooms are a biological disturbance to Western Lake Erie bacterial communities. Environ Microbiol 19:1149–1162. https://doi.org/10.1111/1462-2920.13640

    Article  CAS  PubMed  Google Scholar 

  80. Jiao C, Zhao D, Huang R, He F, Yu Z (2021) Habitats and seasons differentiate the assembly of bacterial communities along a trophic gradient of freshwater lakes. Freshw Biol 66:1515–1529. https://doi.org/10.1111/fwb.13735

    Article  CAS  Google Scholar 

  81. Jiao C, Zhao D, Zeng J, Guo L, Yu Z (2020) Disentangling the seasonal co-occurrence patterns and ecological stochasticity of planktonic and benthic bacterial communities within multiple lakes. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2020.140010

    Article  PubMed  PubMed Central  Google Scholar 

  82. Chaffron S, Rehrauer H, Pernthaler J, Mering CV (2010) A global network of coexisting microbes from environmental and whole-genome sequence data. Genome Res 20:947–959. https://doi.org/10.1007/s002890050103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Tilman D (2007) Interespecific competition and multispecies coexistence. In: May RM, McLean A (eds) Theoretical ecology principles and applications. University Press, Oxford, pp 84–97

    Google Scholar 

  84. Li H, Xing P, Wu QL (2017) Genus-specific relationships between the phytoplankton and bacterioplankton communities in Lake Taihu, China. Hydrobiologia 795:281–294. https://doi.org/10.1007/s10750-017-3141-3

    Article  Google Scholar 

  85. Cao X, Zhao D et al (2018) Heterogeneity of interactions of microbial communities in regions of Taihu Lake with different nutrient loadings: a network analysis. Sci Rep 8:1–11. https://doi.org/10.1038/s41598-018-27172-z

    Article  CAS  Google Scholar 

  86. Newman MEJ (2006) Modularity and community structure in networks. Proc Natl Acad Sci 103:8577–8582. https://doi.org/10.1073/pnas.0601602103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are especially grateful to Qinglong Wu for his experimental design of this study, Yujing Wang for her assistance in the sample collection and the measurement of physicochemical parameters. This work was supported by the National Natural Science Foundation of China (41871096, 32171563); the Natural Science Foundation of Jiangsu Province, China (BK20181311); the Fundamental Research Funds for the Central Universities (B210202009, B200203051); and the China Scholarship Council (No. 201906710009).

Funding

This work was supported by the National Natural Science Foundation of China (41871096, 32171563); the Natural Science Foundation of Jiangsu Province, China (BK20181311); the Fundamental Research Funds for the Central Universities (B210202009, B200203051); and the China Scholarship Council (No. 201906710009).

Author information

Authors and Affiliations

  1. Joint International Research Laboratory of Global Change and Water Cycle, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China

    Xinyi Cao, Dayong Zhao & Hongjie Zhang

  2. Laboratory of Molecular Bacteriology (Rega Institute), Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium

    Xinyi Cao, Lisa Röttjers & Karoline Faust

  3. Department of Civil, Environmental and Geomatic Engineering, University College London, London, UK

    Chaoran Li

Authors
  1. Xinyi Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dayong Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chaoran Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lisa Röttjers
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Karoline Faust
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hongjie Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: DZ, XC; Methodology: LR, KF, XC; Formal analysis and investigation: XC, LR, KF; Writing—original draft preparation: XC, HZ; Writing—review and editing: XC, LR, KF, DZ, C:L; Funding acquisition: DZ; Supervision: DZ.

Corresponding author

Correspondence to Dayong Zhao.

Ethics declarations

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Consent to Participate

Not applicable.

Consent for Publication

The publisher has the authors' permission to publish the content presented herein.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 9699 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cao, X., Zhao, D., Li, C. et al. Regime transition Shapes the Composition, Assembly Processes, and Co-occurrence Pattern of Bacterioplankton Community in a Large Eutrophic Freshwater Lake. Microb Ecol 84, 336–350 (2022). https://doi.org/10.1007/s00248-021-01878-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00248-021-01878-6

Keywords

Search

Navigation