Application of microbial network analysis to discriminate environmental heterogeneity in Fildes Peninsula, Antarctica

https://doi.org/10.1016/j.marpolbul.2020.111244Get rights and content

Highlights

  • Characterize the composition of microbes in coastal seawaters of Antarctica

  • Exhibit spatial patterns of microbial communities and environmental conditions

  • Describe the linkages between microbes and the environmental parameters

  • Using co-occurrence networks to indicate the water quality

Abstract

In order to determine the practicability of developing a protocol for bioassessing polar marine environment based on network analysis, microplankton communities and co-occurrence patterns at Ardley Cove and Great Wall Cove (King George Island, Antarctica) were studied in January 2016 through high-through sequencing. The spatial patterns and significant differences between community structures in two coves clearly reflect those in environmental heterogeneity. Moreover, both coves had their discriminated network structure and keystones. Then multivariate analyses to quantify the relationship between environmental variation and planktonic microbes response, give further evidence that nitrate and temperature, alone or in combination with other several parameters, structuring the communities respectively indeed. This study presents the first detailed description on co-occurrence networks between microbes and local environmental parameters in Antarctic coastal water. These findings suggest that co-occurrence networks based on planktonic microbes have the robust potential to assess environmental heterogeneity in polar marine ecosystem.

Introduction

As the most remote region on Earth, Antarctica plays an essential role in the climate system. The scientific significance of Antarctica has been recognized in the fields of biology and chemistry (Padeiro et al., 2016). The Western Antarctic Peninsula (WAP) is undoubtedly the most extreme and dynamic area in Antarctica, and has experienced significant warming over the past 50 years (Alcamán-Arias et al., 2018). In recent decades, WAP and its offshore islands have been subjected to increasing human activities, resulting in substantial environmental impacts (Bargagli, 2008; Lu et al., 2012). As a pivotal component of Antarctic marine food webs, the response of microbial communities to these intense environmental variations in polar oceans is important (Padeiro et al., 2016).

Microbes are extremely diverse in different ecosystems, and play a crucial role in global biogeochemical cycles (Freimann et al., 2013; Wu et al., 2017; Mo et al., 2018). It has been shown that microbial community structure is sensitive to environmental variability, and its diversity is commonly used as a bioindicator of ecological functioning (Jiang et al., 2014a, Jiang et al., 2014b; Liu et al., 2019; Yang et al., 2019). For example, recent studies have demonstrated that physical, chemical, and biological properties of water remarkably affect the structure of microbial communities (Karimi et al., 2017). However, basic and detailed information about microbial communities in many parts of the polar oceans remains scarce (Luria et al., 2014). Previous studies have shown that planktonic eukaryotes and bacteria can be used to interpret integrated physicochemical variations in changing environments (Jiang et al., 2011, Jiang et al., 2014a, Jiang et al., 2014b, Jiang et al., 2016; Xu et al., 2017; Yang et al., 2019). Although most studies on the spatial variability of polar marine microbial communities have focused on either the bacterial or eukaryotic component (Diíez et al., 2004; Ghiglione and Murray, 2012; Winter et al., 2013; Lee et al., 2014; Wang et al., 2019), there are limited studies on both bacteria and eukaryotes (Luria et al., 2014). The entire microbial community (bacteria and eukaryotes) and its relationships with the native environment should be considered simultaneously in order to develop an integrated vision of the changing water quality.

Microbial community structure is affected by local and regional physicochemical conditions (Buchan et al., 2014; Mikhailov et al., 2019). Co-occurrence network analysis can reveal interspecific interactions within and between microbial communities. Analyses of the various microbial food webs in different habitats can reveal the relationship between microbial communities and the local environment (Karimi et al., 2017). Furthermore, next generation sequencing data can reveal correlation and co-occurrence patterns, which can provide an insight into the positive and negative interactions between species and environmental variables in the aquatic environment (Mo et al., 2018). However, co-occurrence patterns and linkages between microbes and environmental parameters in coastal seawaters of Antarctica have not yet been studied.

The main objectives of the present study were to: 1) exhibit spatial pattern of microbial community structure in response to environmental heterogeneity in coastal seawaters of two coves in the Fildes Peninsula, Antarctica; 2) reveal the co-occurrence patterns between microbes and abiotic variables in distinct environmental conditions; and 3) determine the feasibility of bioassessing polar environmental heterogeneity using network analysis based on marine microbial data.

Section snippets

Study site and sampling

Samples (2 L) were collected at 10 stations, from different depths (0, 5, 10, 20, 30 m), from the coastal seawaters of the Ardley Cove and Great Wall Cove, Antarctica, in January 2016 (Fig. 1). Around Ardley Cove, there are several scientific stations, civilian settlements, and nearby marine bird settlements (i.e., the Ardley Island which is connected with peninsula to separate the two coves and has full of penguins in the northern side of island) (Fig. 1). However, there is only one scientific

Environmental conditions

Supplementary Table S1 presents the environmental variables recorded in the Ardley Cove and Great Wall Cove in January 2016. Comparing the two coves, the seawater temperature was slightly higher at the Ardley Cove than at the Great Wall Cove, whereas the salinity, Chl a, DO and NH4-N concentration were higher at the Great Wall Cove than at the Ardley Cove. The measurements of SiO3-Si, NO2-N, NO3-N, and PO4-P were notably higher at the Ardley Cove (Fig. S1).

Principal components analyses (PCAs)

Discussion

Previous studies have shown that microbial eukaryotes and bacteria play key roles in the Antarctic marine ecosystem, acting as the main food source and the primary contributors to energy fluxes into the microbial food loop (Smetacek and Nicol, 2005; Browning et al., 2014; Moreno-Pino et al., 2016; Zeng et al., 2014; Mo et al., 2018). Among the components of the ecosystem (i.e., physical, chemical, and biological), the biological component is particularly sensitive to perturbations (Jiang et

Conclusions

The present study demonstrates that planktonic microbial communities, which are significantly different between two Coves in Antarctica, could successfully reflect the polar coastal environmental heterogeneity. Multivariate correlation analysis showed that NO3-N and temperature were the most important environmental variables at the Ardley Cove and Great Wall Cove, respectively. Moreover, comprehensive co-occurrence networks based on the micro-organisms and environmental variables precisely

Data accessibility

Sequence data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) database (accession numbers, PRJNA574228; PRJNA574242).

CRediT authorship contribution statement

Qian Liu:Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing - original draft, Writing - review & editing.Yong Jiang:Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing - original draft, Writing - review & editing.

Declaration of competing 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.

Acknowledgements

This study was supported by the National Natural Science Foundation of China (NFSC) (No. 41676178); Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) (Nos. 2018SDKJ0406-6, 2018SDKJ0104-4); the response and feedback of the Southern Ocean to climate change (RFSOCC2020-2025). We would like to thank Editage (www.editage.cn) for English language editing. And we greatly appreciate the editor and anonymous reviewers for their constructive

References (51)

  • Y. Wang et al.

    Seasonal dynamics of bacterial communities in the surface seawater around subtropical Xiamen Island, China, as determined by 16S rRNA gene profiling

    Mar. Pollut. Bull.

    (2019)
  • Y. Yang et al.

    Adaptive shifts of bacterioplankton communities in response to nitrogen enrichment in a highly polluted river

    Environ. Pollut.

    (2019)
  • M.E. Alcamán-Arias et al.

    Microbial activity during a coastal phytoplankton bloom on the Western Antarctic Peninsula in late summer

    FEMS Microbiol. Lett.

    (2018)
  • D. Anderson et al.

    Violence and exodus in Kenya's Rift Valley, 2008: predictable and preventable?

    J. East. Afr. Stud.

    (2008)
  • M.P. Ávila et al.

    Seasonality of freshwater bacterioplankton diversity in two tropical shallow lakes from the Brazilian Atlantic Forest

    FEMS Microbiol. Ecol.

    (2017)
  • A. Barberán et al.

    Using network analysis to explore co-occurrence patterns in soil microbial communities

    ISME J

    (2012)
  • T. Bouchez et al.

    Molecular microbiology methods for environmental diagnosis

    Environ. Chem. Lett.

    (2016)
  • J. Bråte et al.

    Freshwater Perkinsea and marine-freshwater colonizations revealed by pyrosequencing and phylogeny of environmental rDNA

    ISME J

    (2010)
  • T.J. Browning et al.

    Satellite-detected fluorescence: decoupling nonphotochemical quenching from iron stress signals in the South Atlantic and Southern Ocean

    Global. Biogeochem. Cy.

    (2014)
  • A. Buchan et al.

    Master recyclers: features and functions of bacteria associated with phytoplankton blooms

    Nat. Rev. Microbiol.

    (2014)
  • J.G. Caporaso et al.

    QIIME allows analysis of high-throughput community sequencing data

    Nat. Methods

    (2010)
  • Á.M. Ciotti et al.

    Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient

    Limnol. Oceanogr.

    (2002)
  • K.R. Clarke et al.

    PRIMER 7: User Manual/Tutorial

    (2015)
  • A.G.G. de Sousa et al.

    Diversity and composition of pelagic prokaryotic and protist communities in a thin Arctic sea-ice regime

    Microb. Ecol.

    (2019)
  • B. Diíez et al.

    Distribution of eukaryotic picoplankton assemblages across hydrographic fronts in the Southern Ocean, studied by denaturing gradient gel electrophoresis

    Limnol. Oceanogr.

    (2004)
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