The download 5-Hydroxyflavone web section of the Ectocarpus genome portal as sctg_1 (http:bioinformatics.psb.ugent.beorcaeoverview Ectsi). Sctg_1 was identified as bacterial contaminant depending on the lack of introns and its circularity, and removed in the published dataset. To determine achievable plasmids belonging to the same genome TBLASTN searches making use of identified plasmid replication initiators had been carried out against the comprehensive E. siliculosus genome database, but yielded no outcomes. Scgt_1 was oriented in line with the DnaA protein, in addition to a 1st round of automatic annotations was generated working with the RAST server (Aziz et al., 2008). These annotations had been made use of for functional comparisons involving various bacteria with SEED viewer (Overbeek et al., 2005). The generated GenBank file together with the automatic annotations was then utilized in Pathway Tools version 17.5 (Karp et al., 2010) for metabolic network reconstruction including gap-filling and transporter prediction. Manual annotation was Promestriene supplier performed for selected metabolic pathways and gene households. Candidate genes have been identified utilizing bi-directional BLASTP searches with characterized protein sequences retrieved from the UniProt database. Furthermore, we made use of the transporter classification database (TCDB) as reference for transporters, as well as the carbohydrate active enzyme (CAZYme) database CAZY (Lombard et al., 2014) as reference for CAZYmes. Finally, candidate sequences had been compared to theIn order to identify possible complementarities amongst the “Ca. P. ectocarpi” metabolic network as well as the metabolic network of the alga it was sequenced with, the following analyses have been carried out. For E. siliculosus, an SBML file of its metabolic network was downloaded in the EctoGEM web-site (http:ectogem.irisa.fr; Prigent et al. pers. com.). In the context of this study, we chose EctoGEM-combined, a version of EctoGEM devoid of functional gap-filling, which we’ll refer to because the “non-gap filled algal network.” This was crucial for our evaluation as we aimed to determine probable gaps in EctoGEM that may perhaps be filled by reactions carried out by the bacterium. An SBML version of the “Ca. P. ectocarpi” metabolic network was then extracted from Pathway Tools and merged together with the non-gap filled algal network making use of MeMerge (http:mobyle.biotempo.univ-nantes.frcgi-bin portal.py#forms::memerge). Inside the context of this study, we refer to this merged network as the “holobiont network.” Following the procedure outlined on the EctoGEM web-site, we utilized Meneco 1.4.1 (https:pypi.python.orgpypimeneco) to test the capacity of your holobiont network to produce 50 target metabolites that have previously been observed in xenic E. siliculosus cultures (Gravot et al., 2010; Dittami et al., 2011) from the nutrients found inside the Provasoli culture medium as supply metabolites. The exact list of target and source metabolites is readily available from the EctoGEM internet site. Benefits obtained for the holobiont network have been also when compared with EctoGEM 1.0, the gap-filled and manually curated version from the E. siliculosus network, which we refer to as the “manually curated algal network” in this study.TAXONOMIC POSITION AND DISTRIBUTION OF “CA. P. ECTOCARPI”Phylogenetic analyses together with the predicted “Ca. P. ectocarpi” 16S rDNA sequence were carried out with selected representative sequences of recognized orders of Alphaproteobacteria. Sequences were aligned employing MAFFT (Katoh et al., 2002), and conserved positions manually chosen in Jalview two.eight (Waterhouse et al., 2009). The final.