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Pinseel E, Nakov T, Van den Berge K, Downey KM, Judy KJ, Kourtchenko O, Kremp A, Ruck EC, Sjöqvist C, Töpel M, Godhe A, Alverson AJ. Strain-specific transcriptional responses overshadow salinity effects in a marine diatom sampled along the Baltic Sea salinity cline. THE ISME JOURNAL 2022; 16:1776-1787. [PMID: 35383290 PMCID: PMC9213524 DOI: 10.1038/s41396-022-01230-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 03/16/2022] [Accepted: 03/21/2022] [Indexed: 05/01/2023]
Abstract
The salinity gradient separating marine and freshwater environments represents a major ecological divide for microbiota, yet the mechanisms by which marine microbes have adapted to and ultimately diversified in freshwater environments are poorly understood. Here, we take advantage of a natural evolutionary experiment: the colonization of the brackish Baltic Sea by the ancestrally marine diatom Skeletonema marinoi. To understand how diatoms respond to low salinity, we characterized transcriptomic responses of acclimated S. marinoi grown in a common garden. Our experiment included eight strains from source populations spanning the Baltic Sea salinity cline. Gene expression analysis revealed that low salinities induced changes in the cellular metabolism of S. marinoi, including upregulation of photosynthesis and storage compound biosynthesis, increased nutrient demand, and a complex response to oxidative stress. However, the strain effect overshadowed the salinity effect, as strains differed significantly in their response, both regarding the strength and the strategy (direction of gene expression) of their response. The high degree of intraspecific variation in gene expression observed here highlights an important but often overlooked source of biological variation associated with how diatoms respond to environmental change.
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Affiliation(s)
- Eveline Pinseel
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA.
| | - Teofil Nakov
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA
| | - Koen Van den Berge
- Department of Statistics, University of California, Berkeley, CA, USA
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Kala M Downey
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA
| | - Kathryn J Judy
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA
| | - Olga Kourtchenko
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Anke Kremp
- Leibniz-Institute for Baltic Sea Research Warnemünde, Rostock, Germany
| | - Elizabeth C Ruck
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA
| | - Conny Sjöqvist
- Environmental and Marine Biology, Åbo Akademi University, Åbo, Finland
| | - Mats Töpel
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Anna Godhe
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Andrew J Alverson
- Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA.
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