Skip to main content

Advertisement

Log in

Dynamics in Bacterial Community Affected by Mesoscale Eddies in the Northern Slope of the South China Sea

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

Abstract

Mesoscale eddies are common oceanographic processes that can enhance primary productivity by transporting nutrients to the euphotic zone. In the northern South China Sea (SCS), eddies were frequently found to promote the exchange between the nutrient-rich shelf water and the oligotrophic water at the slope area. However, the response of bacterial community to eddy perturbations remains unclear. In the present study, we examined the variation of bacterial community under the impact of eddies in early spring and summer. The results showed that both the summer cyclonic eddy and spring anticyclonic eddy enhanced the bacterial abundance in surface water. The bacterial community composition and their functional potentials of surface samples were also influenced by the summer cyclonic eddy, while no significant change was observed in the case of spring anticyclonic eddy. Salinity and nutrients, which varied between the inside and outside of the eddies, were the significant factors explaining the differentiation of the community composition and related functions. Taken together, the results of our present study reveal the effects of mesoscale eddies on the bacterial community and associated metagenomes, providing a better understanding of the dynamics of bacteria in the slope ecosystem of the SCS.

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

Access this article

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data Availability

The amplicons and metagenomics sequences were deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive with the accession number PRJNA521300.

References

  1. DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard N-U, Martinez A, Sullivan MB, Edwards R, Brito BR, Chisholm SW, Karl DM (2006) Community genomics among stratified microbial assemblages in the ocean’s interior. Science 311:496–503. https://doi.org/10.1126/science.1120250

    Article  CAS  PubMed  Google Scholar 

  2. Falkowski PG, Fenchel T, Delong EF (2008) The microbial engines that drive earth’s biogeochemical cycles. Science 320:1034–1039. https://doi.org/10.1126/science.1153213

    Article  CAS  PubMed  Google Scholar 

  3. Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, Djahanschiri B, Zeller G, Mende DR, Alberti A, Cornejo-Castillo FM, Costea PI, Cruaud C, d’Ovidio F, Engelen S, Ferrera I, Gasol JM, Guidi L, Hildebrand F, Kokoszka F, Lepoivre C, Lima-Mendez G, Poulain J, Poulos BT, Royo-Llonch M, Sarmento H, Vieira-Silva S, Dimier C, Picheral M, Searson S, Kandels-Lewis S, Bowler C, de Vargas C, Gorsky G, Grimsley N, Hingamp P, Iudicone D, Jaillon O, Not F, Ogata H, Pesant S, Speich S, Stemmann L, Sullivan MB, Weissenbach J, Wincker P, Karsenti E, Raes J, Acinas SG, Bork P (2015) Structure and function of the global ocean microbiome. Science 348:1261359. https://doi.org/10.1126/science.1261359

    Article  CAS  PubMed  Google Scholar 

  4. Fuhrman JA, Cram JA, Needham DM (2015) Marine microbial community dynamics and their ecological interpretation. Nat Rev Microbiol 13:133–146. https://doi.org/10.1038/nrmicro3417

    Article  CAS  PubMed  Google Scholar 

  5. Moran MA (2015) The global ocean microbiome. Science 350:aac8455. https://doi.org/10.1126/science.aac8455

  6. Bunse C, Pinhassi J (2017) Marine bacterioplankton seasonal succession dynamics. Trends Microbiol 25:494–505. https://doi.org/10.1016/j.tim.2016.12.013

    Article  CAS  PubMed  Google Scholar 

  7. Baltar F, Arístegui J, Gasol JM, Lekunberri I, Herndl GJ (2010) Mesoscale eddies: hotspots of prokaryotic activity and differential community structure in the ocean. ISME J 4:975–988. https://doi.org/10.1038/ismej.2010.33

    Article  PubMed  Google Scholar 

  8. Giovannoni SJ, Vergin KL (2012) Seasonality in ocean microbial communities. Science 335:671–676. https://doi.org/10.1126/science.1198078

    Article  CAS  PubMed  Google Scholar 

  9. Grossart H-P, Massana R, McMahon KD, Walsh DA (2020) Linking metagenomics to aquatic microbial ecology and biogeochemical cycles. Limnol Oceanogr 65:S2–S20. https://doi.org/10.1002/lno.11382

    Article  CAS  Google Scholar 

  10. Barberán A, Fernández-Guerra A, Bohannan BJM, Casamayor EO (2012) Exploration of community traits as ecological markers in microbial metagenomes. Mol Ecol 21:1909–1917. https://doi.org/10.1111/j.1365-294X.2011.05383.x

    Article  CAS  PubMed  Google Scholar 

  11. Thompson LR, Williams GJ, Haroon MF, Shibl A, Larsen P, Shorenstein J, Knight R, Stingl U (2017) Metagenomic covariation along densely sampled environmental gradients in the Red Sea. ISME J 11:138–151. https://doi.org/10.1038/ismej.2016.99

    Article  CAS  PubMed  Google Scholar 

  12. Galand PE, Pereira O, Hochart C, Auguet JC, Debroas D (2018) A strong link between marine microbial community composition and function challenges the idea of functional redundancy. ISME J 12:2470–2478. https://doi.org/10.1038/s41396-018-0158-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hu J, Kawamura H, Hong H, Qi Y (2000) A review on the currents in the South China Sea: seasonal circulation, South China Sea warm current and Kuroshio intrusion. J Oceanogr 56:607–624. https://doi.org/10.1023/A:1011117531252

    Article  Google Scholar 

  14. Su J (2004) Overview of the South China Sea circulation and its influence on the coastal physical oceanography outside the Pearl River Estuary. Cont Shelf Res 24:1745–1760. https://doi.org/10.1016/j.csr.2004.06.005

    Article  Google Scholar 

  15. Wu C-R, Wang Y-L, Lin Y-F, Chao S-Y (2017) Intrusion of the Kuroshio into the south and East China Seas. Sci Rep 7:7895. https://doi.org/10.1038/s41598-017-08206-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Liu J, Yu S, Zhao M, He B, Zhang X-H (2014) Shifts in archaeaplankton community structure along ecological gradients of Pearl Estuary. FEMS Microbiol Ecol 90:424–435. https://doi.org/10.1111/1574-6941.12404

    Article  CAS  PubMed  Google Scholar 

  17. Zhang Y, Sintes E, Chen J, Zhang Y, Dai M, Jiao N, Herndl GJ (2009) Role of mesoscale cyclonic eddies in the distribution and activity of Archaea and Bacteria in the South China Sea. Aquat Microb Ecol 56:65–79. https://doi.org/10.3354/ame01324

    Article  Google Scholar 

  18. Xia X, Guo W, Liu H (2015) Dynamics of the bacterial and archaeal communities in the Northern South China Sea revealed by 454 pyrosequencing of the 16S rRNA gene. Deep Sea Res Part II 117:97–107. https://doi.org/10.1016/j.dsr2.2015.05.016

    Article  CAS  Google Scholar 

  19. Li D, Zhou M, Zhang Z, Zhong Y, Zhu Y, Yang C, Xu M, Xu D, Hu Z (2018) Intrusions of kuroshio and shelf waters on northern slope of South China Sea in summer 2015. J Ocean Univ China 17:477–486. https://doi.org/10.1007/s11802-018-3384-2

    Article  Google Scholar 

  20. McGillicuddy DJ Jr (2016) Mechanisms of physical-biological-biogeochemical interaction at the oceanic mesoscale. Ann Rev Mar Sci 8:125–159. https://doi.org/10.1146/annurev-marine-010814-015606

    Article  PubMed  Google Scholar 

  21. Benitez-Nelson CR, McGillicuddy DJ (2008) Mesoscale physical–biological–biogeochemical linkages in the open ocean: an introduction to the results of the E-Flux and EDDIES programs. Deep Sea Res Part II 55:1133–1138. https://doi.org/10.1016/j.dsr2.2008.03.001

    Article  Google Scholar 

  22. Cheng Z, Zhou M, Zhong Y, Zhang Z, Liu H, Zhou L (2020) Statistical characteristics of mesoscale eddies on the continental slope in the northern South China Sea. Acta Oceanol Sin 39:36–44. https://doi.org/10.1007/s13131-019-1530-3

    Article  Google Scholar 

  23. Xiu P, Chai F, Shi L, Xue H, Chao Y (2010) A census of eddy activities in the South China Sea during 1993–2007. J Geophys Res 115:C03012. https://doi.org/10.1029/2009JC005657

  24. Nelson CE, Carlson CA, Ewart CS, Halewood ER (2014) Community differentiation and population enrichment of Sargasso Sea bacterioplankton in the euphotic zone of a mesoscale mode-water eddy. Environ Microbiol 16:871–887. https://doi.org/10.1111/1462-2920.12241

    Article  PubMed  Google Scholar 

  25. Bao H, Wu Y, Zhang J (2015) Spatial and temporal variation of dissolved organic matter in the Changjiang: fluvial transport and flux estimation. J Geophys Res Biogeosci 120:1870–1886. https://doi.org/10.1002/2015jg002948

    Article  CAS  Google Scholar 

  26. Zhang M, Wu Y, Qi L, Xu M, Yang C, Wang X (2019) Impact of the migration behavior of mesopelagic fishes on the compositions of dissolved and particulate organic carbon on the northern slope of the South China Sea. Deep Sea Res Part II 167:46–54. https://doi.org/10.1016/j.dsr2.2019.06.012

    Article  CAS  Google Scholar 

  27. Zhang R, Zhu X, Yang C, Ye L, Zhang G, Ren J, Wu Y, Liu S, Zhang J, Zhou M (2019) Distribution of dissolved iron in the Pearl River (Zhujiang) Estuary and the northern continental slope of the South China Sea. Deep Sea Res Part II 167:14–24. https://doi.org/10.1016/j.dsr2.2018.12.006

    Article  CAS  Google Scholar 

  28. Zhang Y, Lu Y, Wang J, Xie L, Xu L, He Y, Xiao X, Xu J (2019) Diurnal variations of the microbial community in mesopelagic fish habitats of the northern slope of the south China sea. Deep Sea Res Part II 167:55–61. https://doi.org/10.1016/j.dsr2.2019.06.018

    Article  Google Scholar 

  29. Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, Glöckner FO (2012) Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 41:e1–e1. https://doi.org/10.1093/nar/gks808

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Salzberg SL, Magoč T (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963. https://doi.org/10.1093/bioinformatics/btr507

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335. https://doi.org/10.1038/nmeth.f.303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200. https://doi.org/10.1093/bioinformatics/btr381

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Quast C, Pruesse E, Gerken J, Peplies J, Yarza P, Yilmaz P, Schweer T, Glöckner FO (2012) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596. https://doi.org/10.1093/nar/gks1219

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Louca S, Parfrey LW, Doebeli M (2016) Decoupling function and taxonomy in the global ocean microbiome. Science 353:1272. https://doi.org/10.1126/science.aaf4507

    Article  CAS  PubMed  Google Scholar 

  35. Joshi N, Fass J. Sickle: a sliding-window, adaptive, quality-based trimming tool for FastQ files. 2011 (Version 1.33)[Software]. https://github.com/najoshi/sickle

  36. Li D, Luo R, Liu C-M, Leung C-M, Ting H-F, Sadakane K, Yamashita H, Lam T-W (2016) MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 102:3–11. https://doi.org/10.1016/j.ymeth.2016.02.020

    Article  CAS  PubMed  Google Scholar 

  37. Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359. https://doi.org/10.1038/nmeth.1923

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Hyatt D, Chen G-L, LoCascio PF, Land ML, Larimer FW, Hauser LJ (2010) Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11:119. https://doi.org/10.1186/1471-2105-11-119

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kanehisa M, Sato Y, Morishima K (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol 428:726–731. https://doi.org/10.1016/j.jmb.2015.11.006

    Article  CAS  PubMed  Google Scholar 

  40. Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, Bork P (2017) Fast genome-wide functional annotation through orthology assignment by eggNOG-Mapper. Mol Biol Evol 34:2115–2122. https://doi.org/10.1093/molbev/msx148

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Knight R, Vrbanac A, Taylor BC, Aksenov A, Callewaert C, Debelius J, Gonzalez A, Kosciolek T, McCall L-I, McDonald D, Melnik AV, Morton JT, Navas J, Quinn RA, Sanders JG, Swafford AD, Thompson LR, Tripathi A, Xu ZZ, Zaneveld JR, Zhu Q, Caporaso JG, Dorrestein PC (2018) Best practices for analysing microbiomes. Nat Rev Microbiol 16:410–422. https://doi.org/10.1038/s41579-018-0029-9

    Article  CAS  PubMed  Google Scholar 

  42. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara R, Simpson GL, Solymos P (2019) Vegan: community ecology package. R package version 2.5–6. https://CRAN.R-project.org/package=vegan

  43. Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer

    Book  Google Scholar 

  44. Anderson MJ, Walsh DCI (2013) PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecol Monogr 83:557–574. https://doi.org/10.1890/12-2010.1

    Article  Google Scholar 

  45. Braak CJFt, Smilauer P (2012) Canoco reference manual and user’s guide: software for ordination, version 50. Microcomputer Power, Ithaca

    Google Scholar 

  46. McArdle BH, Anderson MJ (2001) Fitting multivariate models to community data: a comment on distance-based redundancy analysis. Ecology 82:290–297. https://doi.org/10.1890/0012-9658(2001)082[0290:FMMTCD]2.0.CO;2

    Article  Google Scholar 

  47. Liu H, Zhu M, Guo S, Zhao X, Sun X (2020) Effects of an anticyclonic eddy on the distribution and community structure of zooplankton in the South China Sea northern slope. J Mar Syst 205:103311. https://doi.org/10.1016/j.jmarsys.2020.103311

    Article  Google Scholar 

  48. Dai S, Zhao Y, Liu H, Hu Z, Zheng S, Zhu M, Guo S, Sun X (2020) The effects of a warm-core eddy on chlorophyll a distribution and phytoplankton community structure in the northern South China Sea in spring 2017. J Mar Syst 210:103396. https://doi.org/10.1016/j.jmarsys.2020.103396

    Article  Google Scholar 

  49. He X, Xu D, Bai Y, Pan D, Chen C-TA, Chen X, Gong F (2016) Eddy-entrained Pearl River plume into the oligotrophic basin of the South China Sea. Cont Shelf Res 124:117–124. https://doi.org/10.1016/j.csr.2016.06.003

    Article  Google Scholar 

  50. Zhang W, Sun X, Zheng S, Zhu M, Liang J, Du J, Yang C (2019) Plankton abundance, biovolume, and normalized biovolume size spectra in the northern slope of the South China Sea in autumn 2014 and summer 2015. Deep Sea Res Part II 167:79–92. https://doi.org/10.1016/j.dsr2.2019.07.006

    Article  Google Scholar 

  51. Wang C, Li H, Zhao L, Zhao Y, Dong Y, Zhang W, Xiao T (2019) Vertical distribution of planktonic ciliates in the oceanic and slope areas of the western Pacific Ocean. Deep Sea Res Part II 167:70–78. https://doi.org/10.1016/j.dsr2.2018.08.002

    Article  CAS  Google Scholar 

  52. Wang L, Huang B, Laws EA, Zhou K, Liu X, Xie Y, Dai M (2018) Anticyclonic eddy edge effects on phytoplankton communities and particle export in the northern South China Sea. J Geophys Res: Oceans 123:7632–7650. https://doi.org/10.1029/2017JC013623

    Article  Google Scholar 

  53. Li J, Jiang X, Li G, Jing Z, Zhou L, Ke Z, Tan Y (2017) Distribution of picoplankton in the northeastern South China Sea with special reference to the effects of the Kuroshio intrusion and the associated mesoscale eddies. Sci Total Environ 589:1–10. https://doi.org/10.1016/j.scitotenv.2017.02.208

    Article  CAS  PubMed  Google Scholar 

  54. McGillicuddy DJ, Anderson LA, Bates NR, Bibby T, Buesseler KO, Carlson CA, Davis CS, Ewart C, Falkowski PG, Goldthwait SA, Hansell DA, Jenkins WJ, Johnson R, Kosnyrev VK, Ledwell JR, Li QP, Siegel DA, Steinberg DK (2007) Eddy/wind interactions stimulate extraordinary mid-ocean plankton blooms. Science 316:1021–1026. https://doi.org/10.1126/science.1136256

    Article  CAS  PubMed  Google Scholar 

  55. Zhang Y, Li J, Cheng X, Luo Y, Mai Z, Zhang S (2018) Community differentiation of bacterioplankton in the epipelagic layer in the South China Sea. Ecol Evol 8:4932–4948. https://doi.org/10.1002/ece3.4064

    Article  PubMed  PubMed Central  Google Scholar 

  56. Buchan A, LeCleir GR, Gulvik CA, González JM (2014) Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nat Rev Microbiol 12:686–698. https://doi.org/10.1038/nrmicro3326

    Article  CAS  PubMed  Google Scholar 

  57. West NJ, Lepère C, Manes C-LdO, Catala P, Scanlan DJ, Lebaron P (2016) Distinct spatial patterns of SAR11, SAR86, and Actinobacteria diversity along a transect in the ultra-oligotrophic South Pacific Ocean. Front Microbiol 7:234. https://doi.org/10.3389/fmicb.2016.00234

  58. Ye W, Zhang G, Zheng W, Zhang H, Wu Y (2019) Methane distributions and sea-to-air fluxes in the Pearl River Estuary and the northern South China sea. Deep Sea Res Part II 167:34–45. https://doi.org/10.1016/j.dsr2.2019.06.016

    Article  CAS  Google Scholar 

  59. Zhang Y, Zhao Z, Dai M, Jiao N, Herndl GJ (2014) Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea. Mol Ecol 23:2260–2274. https://doi.org/10.1111/mec.12739

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the scientists and crew of the cruises in 2014, 2015, and 2017 conducted by the R/V Nanfeng and the MCP cruise in 2016 conducted by R/V Kexue #3, for providing professional support and kind help in sampling and data collection. We thank Prof. Xiaoxia Sun and Dr. Shan Zheng from the Institute of Oceanology, Chinese Academy of Sciences, for providing the data of planktonic abundance and primary production in the sampling area.

Funding

This study was supported by the National Basic Research Program of China (Grant Number: 2014CB441503).

Author information

Authors and Affiliations

Contributions

J.X. and Y.L. designed the experiment. Y.L. and Y.Z. collected the samples. Y.L. performed the experiment and analysis. Y.W. and M.Z. provided the chemical data. Y.L. and J.W. performed the metagenomics processing. Y.L., Y.Z., X.X., and J.X. wrote the manuscript, in consultation with all authors.

Corresponding author

Correspondence to Jun Xu.

Ethics declarations

Ethics Approval

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

Conflict of Interest

The authors declare no competing interests.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 970 KB)

Supplementary file2 (XLSX 91 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, Y., Zhang, Y., Wang, J. et al. Dynamics in Bacterial Community Affected by Mesoscale Eddies in the Northern Slope of the South China Sea. Microb Ecol 83, 823–836 (2022). https://doi.org/10.1007/s00248-021-01816-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00248-021-01816-6

Keywords

Profiles

  1. Jun Xu