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Response of marine bacterioplankton pH homeostasis gene expression to elevated CO2

Nature Climate Change volume 6, pages 483–487 (2016)Cite this article

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Abstract

Human-induced ocean acidification impacts marine life. Marine bacteria are major drivers of biogeochemical nutrient cycles and energy fluxes1; hence, understanding their performance under projected climate change scenarios is crucial for assessing ecosystem functioning. Whereas genetic and physiological responses of phytoplankton to ocean acidification are being disentangled2,3,4, corresponding functional responses of bacterioplankton to pH reduction from elevated CO2 are essentially unknown. Here we show, from metatranscriptome analyses of a phytoplankton bloom mesocosm experiment, that marine bacteria responded to lowered pH by enhancing the expression of genes encoding proton pumps, such as respiration complexes, proteorhodopsin and membrane transporters. Moreover, taxonomic transcript analysis showed that distinct bacterial groups expressed different pH homeostasis genes in response to elevated CO2. These responses were substantial for numerous pH homeostasis genes under low-chlorophyll conditions (chlorophyll a <2.5 μg l−1); however, the changes in gene expression under high-chlorophyll conditions (chlorophyll a >20 μg l−1) were low. Given that proton expulsion through pH homeostasis mechanisms is energetically costly, these findings suggest that bacterioplankton adaptation to ocean acidification could have long-term effects on the economy of ocean ecosystems.

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Figure 1: Changes in pH and microbiological parameters during the mesocosm experiments.
Figure 2: Bacterioplankton gene expression response under elevated CO2.
Figure 3: Model of bacterial strategies for pH homeostasis on acid stress.

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References

  1. Azam, F. Microbial control of oceanic carbon flux: the plot thickens. Science 280, 694–696 (1998).

    Article  CAS  Google Scholar 

  2. Hennon, G. M. M. et al. Diatom acclimation to elevated CO2 via cAMP signalling and coordinated gene expression. Nature Clim. Change 5, 761–765 (2015).

    Article  CAS  Google Scholar 

  3. Lohbeck, K. T., Riebesell, U. & Reusch, T. B. Adaptive evolution of a key phytoplankton species to ocean acidification. Nature Geosci. 5, 346–351 (2012).

    Article  CAS  Google Scholar 

  4. Tagliabue, A., Bopp, L. & Gehlen, M. The response of marine carbon and nutrient cycles to ocean acidification: large uncertainties related to phytoplankton physiological assumptions. Glob. Biogeochem. Cycles 25, GB3017 (2011).

    Article  Google Scholar 

  5. Pelejero, C., Calvo, E. & Hoegh-Guldberg, O. Paleo-perspectives on ocean acidification. Trends Ecol. Evol. 25, 332–344 (2010).

    Article  Google Scholar 

  6. Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences 10, 6225–6245 (2013).

    Article  Google Scholar 

  7. Häder, D. P. & Gao, K. Interactions of anthropogenic stress factors on marine phytoplankton. Front. Environ. Sci. 3, 14 (2015)10.3389/fenvs.2015.00014.

    Article  Google Scholar 

  8. Krause, E. et al. Small changes in pH have direct effects on marine bacterial community composition: a microcosm approach. PLoS ONE 7, e47035 (2012).

    Article  CAS  Google Scholar 

  9. Grossart, H. P., Allgaier, M., Passow, U. & Riebesell, U. Testing the effect of CO2 concentration on the dynamics of marine heterotrophic bacterioplankton. Limnol. Oceanogr. 51, 1–11 (2006).

    Article  CAS  Google Scholar 

  10. Arnosti, C. et al. Dynamics of extracellular enzyme activities in seawater under changed atmospheric p CO 2 : a mesocosm investigation. Aquat. Microb. Ecol. 64, 285–298 (2011).

    Google Scholar 

  11. Allgaier, M. et al. Coupling of heterotrophic bacteria to phytoplankton bloom development at different p CO 2 levels: a mesocosm study. Biogeosciences 5, 1007–1022 (2008).

    Google Scholar 

  12. Lindh, M. V. et al. Consequences of increased temperature and acidification on bacterioplankton community composition during a mesocosm spring bloom in the Baltic Sea. Environ. Microbiol. Rep. 5, 252–262 (2013).

    Article  CAS  Google Scholar 

  13. Piontek, J. et al. Acidification increases microbial polysaccharide degradation in the ocean. Biogeosciences 7, 1615–1624 (2010).

    Article  CAS  Google Scholar 

  14. Robinson, C. & Williams, P. J. B. in Respiration in Aquatic Ecosystems (eds del Giorgio, P. A. & Williams, P. J. B.) 147–181 (Oxford Univ. Press, 2005).

    Book  Google Scholar 

  15. Field, C. B. et al. (eds) in Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects (IPCC, Cambridge Univ. Press, 2014).

  16. Sala, M. M. et al. Contrasting effects of ocean acidification on the microbial food web under different trophic conditions. ICES J. Mar. Sci. (2015)10.1093/icesjms/fsv130.

  17. Baltar, F. et al. Response of rare, common and abundant bacterioplankton to anthropogenic pertubations in a Mediterranean coastal site. FEMS Microbiol. Ecol. 91, fiv058 (2015).

    Article  Google Scholar 

  18. Shibata, C. et al. Gene structure of Enterococcus hirae (Streptococcus faecalis) F1FO-ATPase, which functions as a regulator of cytoplasmic pH. J. Bacteriol. 174, 6117–6124 (1992).

    Article  CAS  Google Scholar 

  19. Spero, M. A., Aylward, F. O., Currie, C. R. & Donohue, T. J. Phylogenomic analysis and predicted physiological role of the proton-translocating NADH: quinone oxidoreductase (complex I) across bacteria. mBio 6, e00389–e00415 (2015).

    Article  Google Scholar 

  20. Maurer, L. M. et al. pH regulates genes for flagellar motility, catabolism, and oxidative stress in Escherichia coli K-12. J. Bacteriol. 187, 304–319 (2005).

    Article  CAS  Google Scholar 

  21. Mangold, S., Jonna Rao, V. & Dopson, M. Response of Acidithiobacillus caldus toward suboptimal pH conditions. Extremophiles 17, 689–696 (2013).

    Article  CAS  Google Scholar 

  22. Gómez-Consarnau, L. et al. Light stimulates growth of proteorhodopsin-containing marine Flavobacteria. Nature 445, 210–213 (2007).

    Article  Google Scholar 

  23. Akram, N. et al. Regulation of proteorhodopsin gene expression by nutrient limitation in the marine bacterium Vibrio sp. AND4. Environ. Microbiol. 15, 1400–1415 (2013).

    Article  CAS  Google Scholar 

  24. Fuhrman, J. A., Schwalbach, M. S. & Stingl, U. Proteorhodopsins: an array of physiological roles? Nature Rev. Microbiol. 6, 488–494 (2008).

    Article  CAS  Google Scholar 

  25. Duarte, C. M. et al. Is ocean acidification an open-ocean syndrome? Understanding anthropogenic impacts on seawater pH. Estuar. Coast. 36, 221–236 (2013).

    Article  CAS  Google Scholar 

  26. Spilling, K. Dense sub-ice bloom of dinoflagellates in the Baltic Sea, potentially limited by high pH. J. Plankton Res. 29, 895–901 (2007).

    Article  CAS  Google Scholar 

  27. Buchan, A., LeCleir, G., Gulvik, C. & González, J. Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nature Rev. Microbiol. 12, 686–698 (2014).

    Article  CAS  Google Scholar 

  28. Teeling, H. et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science 336, 608–611 (2012).

    Article  CAS  Google Scholar 

  29. Del Giorgio, P. A. et al. Coherent patterns in bacterial growth, growth efficiency, and leucine metabolism along a northeastern Pacific inshore-offshore transect. Limnol. Oceanogr. 56, 1–16 (2011).

    Article  Google Scholar 

  30. Riebesell, U. & Gattuso, J. P. Lessons learned from ocean acidification research. Nature Clim. Change 5, 12–14 (2015).

    Article  CAS  Google Scholar 

  31. Clayton, T. D. & Byrne, R. H. Spectrophotometric seawater pH measurements: total hydrogen ion concentration scale calibration of m-cresol purple and at-sea results. Deep-Sea Res. I 40, 2115–2129 (1993).

    Article  CAS  Google Scholar 

  32. Dickson, A. G., Sabine, C. L. & Christian, J. R. Guide to Best Practices for Ocean CO2 Measurements Vol. 3 (PICES Special Publication, 2007).

    Google Scholar 

  33. Kirchman, D., K’nees, E. & Hodson, R. Leucine incorporation and its potential as a measure of protein synthesis by bacteria in natural aquatic systems. Appl. Environ. Microbiol. 49, 599–607 (1985).

    CAS  Google Scholar 

  34. Smith, D. C. & Azam, F. A simple, economical method for measuring bacterial protein synthesis rates in seawater using 3H-leucine. Mar. Microb. Food Webs 6, 107–114 (1992).

    Google Scholar 

  35. Yentsch, C. S. & Menzel, D. W. A method for the determination of phytoplankton chlorophyll and phaeophytin by fluorescence. Deep-Sea Res. I 10, 221–231 (1963).

    CAS  Google Scholar 

  36. Allers, E. et al. Response of Alteromonadaceae and Rhodobacteriaceae to glucose and phosphorus manipulation in marine mesocosms. Environ. Microbiol. 9, 2417–2429 (2007).

    Article  CAS  Google Scholar 

  37. Pinhassi, J. et al. Changes in bacterioplankton composition under different phytoplankton regimes. Appl. Environ. Microbiol. 70, 6753–6766 (2004).

    Article  CAS  Google Scholar 

  38. Poretsky, R. S. et al. Comparative day/night metatranscriptomic analysis of microbial communities in the North Pacific subtropical gyre. Environ. Microbiol. 11, 1358–1375 (2009).

    Article  CAS  Google Scholar 

  39. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).

    Article  Google Scholar 

  40. Del Fabbro, C., Scalabrin, S., Morgante, M. & Giorgi, F. M. An extensive evaluation of read trimming effects on illumina NGS data analysis. PLoS ONE 8, e85024 (2013).

    Article  Google Scholar 

  41. Boisvert, S. et al. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol. 13, R122 (2012).

    Article  Google Scholar 

  42. Zerbino, D. R. & Birney, E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 18, 821–829 (2008).

    Article  CAS  Google Scholar 

  43. Rho, M., Tang, H. & Ye, Y. FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Res. 38, e191 (2010).

    Article  Google Scholar 

  44. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).

    Article  CAS  Google Scholar 

  45. Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).

    Article  CAS  Google Scholar 

  46. Overbeek, R. et al. The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res. 33, 5691–5702 (2005).

    Article  CAS  Google Scholar 

  47. Huson, D. H., Auch, A. F., Qi, J. & Schuster, S. C. MEGAN analysis of metagenomic data. Genome Res. 17, 377–386 (2007).

    Article  CAS  Google Scholar 

  48. Tripp, J. H. et al. Misannotations of rRNA can now generate 90% false positive protein matches in metatranscriptomic studies. Nucleic Acids Res. 39, 8792–8802 (2011).

    Article  CAS  Google Scholar 

  49. Rivers, A. R. et al. Transcriptional response of bathypelagic marine bacterioplankton to the Deepwater Horizon oil spill. ISME J. 7, 2315–2329 (2013).

    Article  CAS  Google Scholar 

  50. Satinsky, B. M. et al. The Amazon continuum dataset: quantitative metagenomic and metatranscriptomic inventories of the Amazon River plume, June 2010. Microbiome 2, 17 (2014).

    Article  Google Scholar 

  51. Beier, S., Rivers, A. R., Moran, M. A. & Obernosterer, I. Phenotypic plasticity in heterotrophic marine microbial communities in continuous cultures. ISME J. 9, 1141–1151 (2015).

    Article  Google Scholar 

  52. Marchetti, A. et al. Comparative metatranscriptomics identifies molecular bases for the physiological responses of phytoplankton to varying iron availability. Proc. Natl Acad. Sci. USA 109, E317–E325 (2011).

    Article  Google Scholar 

  53. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357–359 (2012).

    Article  CAS  Google Scholar 

  54. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The skilful technical assistance of S. Arnautovic, V. Balague, C. Cardelús, L. Cros, E. Vázquez-Domínguez, J. Movilla and À. López-Sanz made this experiment possible. We thank Anselm and the CEAB boat crew for assistance with sampling and M. A. Moran for insightful comments on our work. This research was financially supported by grants from the Göran Gustafsson Foundation for Research in Natural Sciences and Medicine, the Swedish Research Council VR, the Swedish Research Council FORMAS strong research programme EcoChange, and the BONUS BLUEPRINT project, which has received funding from BONUS, the joint Baltic Sea research and development programme (Art 185), funded jointly from the European Union’s Seventh Programme for research, technological development and demonstration and from the Swedish Research Council FORMAS to J.Pinhassi. The research was also financially supported by the Spanish Ministry of Science and Innovation project DOREMI (CTM2012-34294) to C.M. and J.M.Gasol, and by project CTM2013-48292-C3-3-R to J.M.Gasol. 

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Author notes

  1. Neelam Akram, Maria Vila-Costa & Joakim Palovaara

    Present address: Present addresses: Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-24, 08034 Barcelona, Catalunya, Spain (M.V.-C.); Department of Agrotechnology and Food Sciences, Wageningen University, 6703HA Wageningen, The Netherlands (J.P.); Department of Biosciences, COMSATS Institute of Information Technology, 44000 Islamabad, Pakistan (N.A.).,

Authors and Affiliations

  1. Centre for Ecology and Evolution in Microbial Model Systems, EEMiS, Linnaeus University, Barlastgatan 11, 391 82 Kalmar, Sweden

    Carina Bunse, Daniel Lundin, Christofer M. G. Karlsson, Neelam Akram, Joakim Palovaara, Lovisa Svensson, Karin Holmfeldt, Mark Dopson & Jarone Pinhassi

  2. Department of Continental Ecology, Group of Limnology, Centre d’Estudis Avançats de Blanes-CSIC, Accés Cala Sant Francesc 14, 17300 Blanes, Catalonia, Spain

    Maria Vila-Costa

  3. Department of Microbiology, University of La Laguna, 38200 La Laguna, Spain

    José M. González

  4. Departament de Biologia Marina i Oceanografia, Institut de Ciències del Mar—CSIC, Pg. Marítim de la Barceloneta 37-49, 08003 Barcelona, Catalonia, Spain

    Eva Calvo, Carles Pelejero, Cèlia Marrasé & Josep M. Gasol

  5. Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Catalonia, Spain

    Carles Pelejero

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Contributions

M.D., C.P., J.M.Gasol and J.Pinhassi conceived the study. C.P., C.M., J.M.Gasol and J.Pinhassi designed research. N.A., M.V.-C., J.M.González, E.C., C.P., C.M., J.M.Gasol and J.Pinhassi carried out the mesocosm experiment and collected samples for microbial and chemical analyses. E.C. and C.M. measured and adjusted pH. N.A., M.V.-C. and J.Palovaara carried out RNA extraction. C.B., D.L., C.M.G.K., L.S., K.H., J.M.González, M.D. and J.Pinhassi analysed data. C.B., D.L. and J.Pinhassi wrote the paper with help from C.M.G.K., L.S. and M.D. All authors discussed the results and commented on the manuscript.

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Correspondence to Jarone Pinhassi.

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Bunse, C., Lundin, D., Karlsson, C. et al. Response of marine bacterioplankton pH homeostasis gene expression to elevated CO2. Nature Clim Change 6, 483–487 (2016). https://doi.org/10.1038/nclimate2914

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