The ISME Journal (2017) 11, 1483–1499 OPEN © 2017 International Society for Microbial Ecology All rights reserved 1751-7362/17 www.nature.com/ismej ORIGINAL ARTICLE Phylogenomics of Rhodobacteraceae reveals evolutionary adaptation to marine and non-marine habitats Meinhard Simon1, Carmen Scheuner2, Jan P Meier-Kolthoff2, Thorsten Brinkhoff1, Irene Wagner-Döbler3, Marcus Ulbrich4, Hans-Peter Klenk5, Dietmar Schomburg4, Jörn Petersen2 and Markus Göker2 1Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Oldenburg, Germany; 2Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany; 3Helmholtz Centre for Infection Research, Research Group Microbial Communication, Braunschweig, Germany; 4Institute of Biochemical Engineering, Technical University Braunschweig, Braunschweig, Germany and 5School of Biology, Newcastle University, Newcastle upon Tyne, UK Marine Rhodobacteraceae (Alphaproteobacteria) are key players of biogeochemical cycling, comprise up to 30% of bacterial communities in pelagic environments and are often mutualists of eukaryotes. As ‘Roseobacter clade’, these ‘roseobacters’ are assumed to be monophyletic, but non- marine Rhodobacteraceae have not yet been included in phylogenomic analyses. Therefore, we analysed 106 genome sequences, particularly emphasizing gene sampling and its effect on phylogenetic stability, and investigated relationships between marine versus non-marine habitat, evolutionary origin and genomic adaptations. Our analyses, providing no unequivocal evidence for the monophyly of roseobacters, indicate several shifts between marine and non-marine habitats that occurred independently and were accompanied by characteristic changes in genomic content of orthologs, enzymes and metabolic pathways. Non-marine Rhodobacteraceae gained high-affinity transporters to cope with much lower sulphate concentrations and lost genes related to the reduced sodium chloride and organohalogen concentrations in their habitats. Marine Rhodobacteraceae gained genes required for fucoidan desulphonation and synthesis of the plant hormone indole 3-acetic acid and the compatible solutes ectoin and carnitin. However, neither plasmid composition, even though typical for the family, nor the degree of oligotrophy shows a systematic difference between marine and non-marine Rhodobacteraceae. We suggest the operational term ‘Roseobacter group’ for the marine Rhodobacteraceae strains. The ISME Journal (2017) 11, 1483–1499; doi:10.1038/ismej.2016.198; published online 20 January 2017 Introduction Rhodobacteraceae include only few strains of mar- ine origin (Pujalte et al., 2014). Roseobacters show a Rhodobacteraceae (Garrity et al., 2005), one of the very versatile physiology to dwell in greatly varying major subdivisions of Alphaproteobacteria, include 4 4 marine habitats (Buchan et al., 2005; Wagner-Döbler 100 genera and 300 species with very diverse and Biebl, 2006; Brinkhoff et al., 2008; Newton et al., physiologies (Pujalte et al., 2014). Giovannoni and 2010; Sass et al., 2010; Laass et al., 2014; Luo and Rappé (2000) assigned most Rhodobacteraceae Moran, 2014; Collins et al., 2015) and account for to the Roseobacter group (‘roseobacters’), which 4 4 large proportions of bacterioplankton communities now includes 70 validly named genera, 170 (Selje et al., 2004; West et al., 2008; Alonso-Gutiérrez validly named species (Pujalte et al., 2014) and et al., 2009; Giebel et al., 2011; Buchan et al., 2014; numerous additional isolates and 16S rRNA phylo- Gifford et al., 2014; Wemheuer et al., 2015). types (http://www.arb-silva.de). Most roseobacters Genome plasticity might explain adaptability and originate from marine habitats but some from (hyper-) diversity of roseobacters (Luo and Moran, 2014). saline lakes or soil (Pujalte et al., 2014). Other Pelagic roseobacters show streamlined genomes (Voget et al., 2015) and possibly other adaptations to Correspondence: M Göker, Leibniz-Institut DSMZ – Deutsche an oligotrophic lifestyle. Extrachromosomal replicons Sammlung von Mikroorganismen und Zellkulturen GmbH, (ECRs) comprise chromids and genuine plasmids Inhoffenstraße 7 B, Braunschweig D-38124, Germany. (Harrison et al., 2010; Petersen et al., 2013). Four E-mail: [email protected] Received 2 August 2016; revised 29 October 2016; accepted replication systems (RepA, RepB, RepABC, DnaA-like) 19 November 2016; published online 20 January 2017 with about 20 phylogenetically distinguishable Rhodobacteraceae phylogenomics M Simon et al 1484 compatibility groups were identified in roseobacters group taxonomically assigned to Rhodobacteraceae (Petersen et al., 2013), but a comprehensive analysis of but rather placed within Rhizobiales in 16S rRNA Rhodobacteraceae genome architecture is lacking. gene analyses (Pujalte et al., 2014) were used as Whereas extensive studies of physiological, genetic outgroup. An extended data set including 132 and genomic features of roseobacters were performed, genomes was phylogenetically analysed using only scarce and unsystematic information is available Genome BLAST Distance Phylogeny (Auch et al., on how these traits are distributed among marine and 2006; Meier-Kolthoff et al., 2014). Digital DNA:DNA non-marine Rhodobacteraceae. hybridization was used to check all species affilia- The Roseobacter groupispresumedtobemono- tions (Auch et al., 2010; Meier-Kolthoff et al., 2013a). phyletic and thus frequently called ‘Roseobacter clade’ Pairwise 16S rRNA gene similarities (Meier-Kolthoff (Buchan et al., 2005; Newton et al., 2010; Luo et al., et al., 2013b) were determined after extraction with 2013; Pujalte et al., 2014). Strains within this group RNAmmer version 1.2 (Lagesen and Hallin, 2007). share 489% identity of the 16S rRNA gene (Brinkhoff The proteome sequences were phylogenetically et al., 2008; Luo and Moran, 2014) but a reliable investigated using the DSMZ phylogenomics pipe- delineation of this group from other Rhodobacteraceae line (Anderson et al., 2011; Breider et al., 2014; cannot be carried out with this gene (Breider et al., Frank et al., 2014; Stackebrandt et al., 2014; Verbarg 2014), as branch support and other rationales for et al., 2014). Alignments were concatenated to three suggested 16S rRNA gene-derived Rhodobacteraceae main supermatrices: (i) ‘core genes’, alignments lineages (Pujalte et al., 2014) are lacking. containing sequences from all proteomes; (ii) ‘full’, Even though more comprehensive phylogenetic alignments containing sequences from at least four analyses of the Roseobacter group have been conducted proteomes; and (iii) ‘MARE’, the full matrix filtered (Newton et al., 2010; Tang et al., 2010; Luo et al., 2012, with that software (Meusemann et al., 2010). The 2013; Luo and Moran, 2014; Voget et al., 2015), an core genes were further reduced to their 50, 100, 150 analysis of the phylogenetic affiliation of this group as a and 200 most conserved genes (up to 250 without component of the entire Rhodobacteraceae has not yet outgroup). Long-branch extraction (Siddall and been carried out. In the majority of phylogenomic Whiting, 1999) to assess long-branch attraction analyses of roseobacters (Luo et al., 2012, 2014; Luo and artefacts (Bergsten, 2005) was conducted by remov- Moran, 2014; Voget et al., 2015), non-roseobacter ing the outgroup strains, generating the superma- Rhodobacteraceae were missing, and a single set of trices anew and rooting the resulting trees with LSD selected genes was concatenated and analysed with a version 0.2 (To et al., 2015). single inference method such as Maximum Likelihood ML and maximum parsimony (MP) phylogenetic (ML) assuming a single amino-acid substitution model trees were inferred as described (Andersson et al., for all genes. However, selections of genes, strains and 2011; Breider et al., 2014; Frank et al., 2014; other factors influence the resulting phylogenies (Jeffroy Stackebrandt et al., 2014; Verbarg et al., 2014) but et al., 2006; Philippe et al., 2011; Salichos and Rokas, MP tree search was conducted with TNT version 1.1 2013; Breider et al., 2014). Even though evolutionary (Goloboff et al., 2008). Additionally, best substitution aspects of gene gains and losses of the Roseobacter models for each gene and ML phylogenies were group were analysed previously (Luo et al., 2013; calculated with ExaML version 3.0.7 (Stamatakis and Luo and Moran, 2014), these analyses did not consider Aberer, 2013). Ordinary and partition bootstrapping the content of specific genomic features as adaptations (Siddall, 2010) was conducted with 100 replicates to the environmental settings. except for full/ML for reasons of running time. To We carried out phylogenomic analyses of 106 assess conflict between the genomic data and sequenced Rhodobacteraceae genomes using distinct roseobacter monophyly, site-wise ML and MP scores inference algorithms and distinct gene selections were calculated from unconstrained and accordingly ranging from the analysis of the core genes to the ‘full’ constrained best trees, optionally summed up per supermatrix, to address the following questions: gene, and compared with Wilcoxon and T-tests (i) How is the Roseobacter group related to other (R Core Team, 2015) and, for ML, with the Rhodobacteraceae? (ii) Is this relationship robust approximately unbiased test (Shimodaira and against variations in gene selection and phylogenetic Hasegawa, 2001). Potential conflict with the 16S inference? (iii) Do stable subgroups exist within this rRNA gene was measured