Direct effects of organic pollutants on the growth and gene expression of the Baltic Sea model bacterium Rheinheimera sp. BAL341

Organic pollutants (OPs) are critically toxic, bioaccumulative and globally widespread. Moreover, several OPs negatively influence aquatic wildlife. Although bacteria are major drivers of the ocean carbon cycle and the turnover of vital elements, there is limited knowledge of OP effects on heterotrophic bacterioplankton. We therefore investigated growth and gene expression responses of the Baltic Sea model bacterium Rheinheimera sp. BAL341 to environmentally relevant concentrations of distinct classes of OPs in 2-h incubation experiments. During exponential growth, exposure to a mix of polycyclic aromatic hydrocarbons, alkanes and organophosphate esters (denoted MIX) resulted in a significant decrease (between 9% and 18%) in bacterial abundance and production compared with controls. In contrast, combined exposure to perfluorooctanesulfonic acids and perfluorooctanoic acids (denoted PFAS) had no significant effect on growth. Nevertheless, MIX and PFAS exposures both induced significant shifts in gene expression profiles compared with controls in exponential growth. This involved several functional metabolism categories (e.g. stress response and fatty acids metabolism), some of which were pollutant-specific (e.g. phosphate acquisition and alkane-1 monooxygenase genes). In stationary phase, only two genes in the MIX treatment were significantly differentially expressed. The substantial direct influence of OPs on metabolism during bacterial growth suggests that widespread OPs could severely alter biogeochemical processes governed by bacterioplankton. © 2019 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.Funding text #1 Received 8 April, 2019; revised 15 May, 2019; accepted 15 May, 2019. *For correspondence. E-mail [email protected]; Tel. +46725949448 Microbial Biotechnology (2019) 12(5), 892–906 doi:10.1111/1751-7915.13441 Funding Information. This research was supported by the BONUS BLUEPRINT project, which has received funding from BONUS, the joint Baltic Sea research and development programme (Art 185), and the Swedish research council FORMAS. Funding was also provided through the Swedish governmental strong research programme EcoChange (FORMAS). Work by ECG and MVC was supported by a Fundación BBVA award to MVC (14_CMA_020) and by the Spanish MEIC through the project ISOMICS (CTM2015-65691-R). Funding text #2 We thank Josef Lautin for excellent technical assistance in the laboratory and Prof. Jordi Dachs for advice on organic pollutants. The authors would like to acknowledge the support from Science for Life Laboratory, the National Genomics Infrastructure, NGI, and Uppmax for providing assistance in massive parallel sequencing and computational infrastructure. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Funding text #3 Science (UPPMAX) under project b2011200. The research was supported by the BONUS BLUEPRINT project, which has received funding from BONUS, the joint Baltic Sea research and development programme (Art 185), and the Swedish research council FORMAS. Funding was also provided through the Swedish governmental strong research programme EcoChange (FORMAS). Work by ECG and MVC was supported by a Fundación BBVA award to MVC (14_CMA_020) and by the Spanish MEIC through the project ISOMICS (CTM2015-65691-R).Peer reviewe