Abstract
Human activities such as agriculture and mining are leading causes of water pollution worldwide. Individual contaminants are known to negatively affect microbial communities. However, the effect of multifaceted pollution on these communities is less well understood. We investigated, using next-generation sequencing of the 16S rRNA genes, the effects of multisource (i.e., fertilizer industry and mining) chronic pollution on bacterial and archaeal communities in water and sediments from the Olifants River catchment, South Africa. Water samples showed less microbial species diversity than sediments and both habitats displayed different microbial communities. Within each of these habitats, pollution had no effect on alpha diversity but shaped the microbial composition and taxonomy-based predicted functions. Certain prokaryotic taxa and functional groups were indicative of different degrees of pollution. Heterotrophic taxa (e.g., Flavobacterium sp.) and sulphur-oxidizing bacteria (i.e., Thiobacillus sp.) were indicators of pollution in water and sediments, respectively. Ultimately, this information could be used to develop microbial indicators of water quality degradation.
Similar content being viewed by others
References
Baker BJ, Banfield JF (2003) Microbial communities in acid mine drainage. FEMS Microbiol Ecol 44:139–152. https://doi.org/10.1016/S0168-6496(03)00028-X
Bier RL, Voss KA, Bernhardt ES (2015) Bacterial community responses to a gradient of alkaline mountaintop mine drainage in Central Appalachian streams. ISME J 9:1378–1390. https://doi.org/10.1038/ismej.2014.222
Boscaro V, Felletti M, Vannini C, Ackerman MS et al (2013) Polynucleobacter necessarius, a model for genome reduction in both free-living and symbiotic bacteria. Proc Natl Acad Sci USA 110:18590–18595
Bryant JA, Stewart FJ, Eppley JM et al (2012) Microbial community phylogenetic and trait diversity declines with depth in a marine oxygen minimum zone. Ecology 93:1659–1673. https://doi.org/10.1890/11-1204.1
Calmano W, Hong J, Forstner U (1993) Binding and mobilization of heavy metals in contaminated sediments affected by pH and redox potential. Wat Sci Tech 28:223–235. https://doi.org/10.15480/882.450
Caporaso JG, Bittinger K, Bushman FD et al (2010a) PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26:266–267. https://doi.org/10.1093/bioinformatics/btp636
Caporaso JG, Kuczynski J, Stombaugh J et al (2010b) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. https://doi.org/10.1038/nmeth.f.303
Cole JR, Wang Q, Cardenas E et al (2009) The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 37:D141–D145. https://doi.org/10.1093/nar/gkn879
Cotner JB, Biddanda BA (2002) Small players, large role: microbial influence on biogeochemical processes in pelagic aquatic ecosystems. Ecosystems 5:105–121. https://doi.org/10.1007/s10021-001-0059-3
Crump BC, Amaral-Zettler LA, Kling GW (2012) Microbial diversity in arctic freshwaters is structured by inoculation of microbes from soils. ISME J 6:1629–1639. https://doi.org/10.1038/ismej.2012.9
Dodds WK (2006) Eutrophication and trophic state in rivers and streams. Limnol Oceanogr 51:671–680
Dufrene M, Legendre P (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol Monograph 67:345–366. https://doi.org/10.2307/2963459
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461. https://doi.org/10.1093/bioinformatics/btq461
Eiler A, Zaremba-Niedzwiedzka K, Martínez-García M et al (2014) Productivity and salinity structuring of the microplankton revealed by comparative freshwater metagenomics. Environ Microbiol 16:2682–2698. https://doi.org/10.1111/1462-2920.12301
Feris KP, Ramsey PW, Gibbons SM et al (2009) Hyporheic microbial community development is a sensitive indicator of metal contamination. Environ Sci Technol 43:6158–6163
García-Moyano A, González-Toril E, Aguilera A et al (2012) Comparative microbial ecology study of the sediments and the water column of the Río Tinto, an extreme acidic environment. FEMS Microbiol Ecol 81:303–314. https://doi.org/10.1111/j.1574-6941.2012.01346.x
Gibbons SM, Gilbert JA (2015) Microbial diversity-exploration of natural ecosystems and microbiomes. Curr Opin Gen Dev 35:66–72. https://doi.org/10.1016/j.gde.2015.10.003
Gomez-Arias, A, Castillo, J, van Heerden, E et al. (2016) Use of alkaline mine waste as treatment for acid drainage. In: Proceedings IMWA. Freiberg/Germany
Heath R, Coleman T, Engelbrecht J (2010) Water quality overview and literature review of the ecology of the Olifants River. Water Research Commission, Pretoria
Hsu LC, Huang CY, Chuang YH et al (2016) Accumulation of heavy metals and trace elements in fluvial sediments received effluents from traditional and semiconductor industries. Sci Rep 6:34250. https://doi.org/10.1038/srep34250
Jackson TA, Vlaar S, Nguyen N et al (2015) Effects of bioavailable heavy metal species, arsenic, and acid drainage from mine tailings on a microbial community sampled along a pollution gradient in a freshwater. Ecosyst Geomicrobiol J 32:724–750. https://doi.org/10.1080/01490451.2014.969412
Kembel SW, Cowan PD, Helmus MR, Cornwell WK et al (2010) Picante: R tools for integrating phylogenies and ecology. Bioinformatics 11:1463–1464. https://doi.org/10.1093/bioinformatics/btq166
Kuang JL, Huang LN, Chen LX et al (2013) Contemporary environmental variation determines microbial diversity patterns in acid mine drainage. ISME J 7:1038–1050. https://doi.org/10.1038/ismej.2012.139
Langenheder S, Berga M, Östman O et al (2012) Temporal variation of β-diversity and assembly mechanisms in a bacterial metacommunity. ISME J 6:1107–1114
Legendre P, Legendre L (1998) Numerical ecology, 2nd edn. Amsterdam, Elsevier Science BV
Lima-Mendez G, Faust K, Henry N et al (2015) Determinants of community structure in the global plankton interactome. Science 348:1262073. https://doi.org/10.1126/science.1262073
Lindstrom ES, Langenheder S (2012) Local and regional factors influencing bacterial community assembly. Environ Microbiol Rep 4:1–9. https://doi.org/10.1111/j.1758-2229.2011.00257.x
Louca S, Parfrey LW, Doebeli M (2016) Decoupling function and taxonomy in the global ocean microbiome. Science 353:1272–1277. https://doi.org/10.1126/science.aaf4507
Lozupone CA, Knight R (2007) Global patterns in bacterial diversity. Proc Natl Acad Sci USA 104:11436–11440. https://doi.org/10.1073/pnas.0611525104
Marr SM, Mohlala TD, Swemmer A (2017) The ecological integrity of the lower Olifants River, Limpopo province, South Africa: 2009–2015-Part B: tributaries of the Olifants River. Afr J Aquat Sci 42:171–179
McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8:e61217. https://doi.org/10.1371/journal.pone.0061217
Ofiteru ID, Lunn M, Curtis TP et al (2010) Combined niche and neutral effects in a microbial wastewater treatment community. Proc Natl Acad Sci USA 107:15345–15350. https://doi.org/10.1073/pnas.1000604107
Oksanen, J, Blanchet, FG, Kindt, R et al. (2013) Vegan: Community Ecology Package
Pei Y, Yu Z, Ji J et al (2018) Microbial community structure and function indicate the severity of chromium contamination of the Yellow River. Front Microbiol 9:38. https://doi.org/10.3389/fmicb.2018.00038
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
Pruesse E, Quast C, Knittel K et al (2007) SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35:7188–7196. https://doi.org/10.1093/nar/gkm864
Reynolds CS (2009) Phytoplankton population dynamics in natural environments. In: Likens GE (ed) Encyclo-pedia of inland waters. Elsevier, Amsterdam, pp 197–203
Salcher MM, Schaefle D, Kaspar M et al (2019) Evolution in action: habitat transition from sediment to the pelagial leads to genome streamlining in Methylophilaceae. ISME J 13:2764–2777
Salomons W, Stigliani W (1995) Biogeodynamics of pollutants in soils and sediments. Springer, Berlin
Samanovic MI, Ding C, Thiele DJ et al (2012) Copper in microbial pathogenesis: meddling with the metal. Cell Host Microbe 11:106–115. https://doi.org/10.1016/j.chom.2012.01.009
Team RDC (2011) R: a language and environment for statistical computing, R Foundation for Statistical Computing; https://www.R-project.org/
Tuan NN, Chang YC, Yu CP et al (2014) Multiple approaches to characterize the microbial community in a thermophilic anaerobic digester running on swine manure: a case study. Microbiol Res 169:717–724. https://doi.org/10.1016/j.micres.2014.02.003
Vörösmarty CJ, McIntyre PB, Gessner MO et al (2010) Global threats to human water security and river biodiversity. Nature 467:555–561. https://doi.org/10.1038/nature09440
Yergeau E, Lawrence JR, Sanschagrin S et al (2012) Next-generation sequencing of microbial communities in the Athabasca River and its tributaries in relation to oil sands mining activities. Appl Environ Microbiol 78:7626–7637. https://doi.org/10.1128/AEM.02036-12
Acknowledgements
Funding for this research was provided by the National Research Foundation and SANPARKS, South Africa. We are grateful to the soil chemistry laboratory at the University of Pretoria for performing the chemical analysis, and SANPARKS for facilitating the collection of the samples.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Erko stackebrandt.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Valverde, A., Cason, E.D., Gómez-Arias, A. et al. Pollution shapes the microbial communities in river water and sediments from the Olifants River catchment, South Africa. Arch Microbiol 203, 295–303 (2021). https://doi.org/10.1007/s00203-020-02035-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00203-020-02035-2