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Investigating the Antibiotic Productivity of Streptomyces rimosus A. MACFADYEN 1 , Z. TANG 1,2 , R. KIRBY 3 , R. EDRADA-EBEL 1 , I. HUNTER 1 and P. HERRON 1

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Investigating the Antibiotic Productivity of Streptomyces rimosus

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  1. Investigating the Antibiotic Productivity of Streptomycesrimosus A. MACFADYEN1, Z. TANG1,2, R. KIRBY3, R. EDRADA-EBEL1, I. HUNTER1 and P. HERRON1 1Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK; 2State Key Laboratory of Bioreactor Engineering, East China University of Science and Engineering, Shanghai, China; 3Department of Life Sciences and Institute of Genome Science, National Yang-Ming University, Taipei, Taiwan Introduction Streptomyces rimosus, the industrial strain used in the production of the type-II polyketide antibiotic oxytetracycline (OTC), has undergone extensive strain improvement over the past 50 years. This has resulted in OTC levels increasing from less than 0.5g per litre in the original soil isolate to over 70g per litre for the current production strain. By analysing the genome sequences of four strains that lie within this lineage (Figure 1), each with a different level of OTC productivity, we have begun to investigate the genetic basis behind increased OTC yield. Objectives To determine the genetic and metabolomic reasons behind increased antibiotic production, by comparing the original soil isolate to the later strains in the lineage Methodology Figure 1: Geneology of Strains. Denotes the strains of which we have genome sequences for. Sequence Strains SNP Paired-end Reads Roche 454 Sequence M4018 Illumina 30 bp paired-end sequence – G7, 15883S and 23383 DELETION Comparative analysis Individual Analysis Strain Improvement SEED Viewer HMMER RAST Artemis Number of Single Nucleotide Polymorphisms Figure 2: Histogram of the Single Nucleotide Polymorphisms identified using MAQ SNP files generated during alignments. Move from in silico to in vivo Results CCG to UCG = Proline to Serine Cycloheximide 100 mg/mL -ve Control Strain (OTC g/L) • Conclusions • Loss of production of other secondary metabolites may lead to increased antibiotic production • Modification of regulatory proteins may influence antibiotic production • Alteration within metabolic pathways may alter the antibiotic productivity • Single nucleotide polymorphisms can have a major impact on the production levels of an antibiotic • Genomic comparisons can lend great insights into the varying contributions to differing antibiotic production levels and allow for targeted genetic engineering of industrial strains G7 M4018 15883S 23383 Figure 3: Rimocidin assay. Saccharomyces cerevisiae was used as the test organism. The negative control was ethanol. Figure 4: 23383 aligned with M4018 in Artemis. The SNP highlighted is within a homologue of SCO1937, a zwf gene, which are associated with antibiotic production. • A loss of 155 Kb is present in 15883S which is unrelated to the spontaneous OTC cluster deletion • There is a loss of genes required to encode the Polyketide Synthase of another secondary metabolite in strains M4018, 15883S and 23383 (Figure 3) • >600 SNPs identified in the latest strain • Most noteworthy are Non-Synonymous SNPs in a putative Glucose 6-phosphate 1-dehydrogenase (Figure 4) and other proteins associated with regulation. • Future Work • Recreate deletions in early strains and mutate the putative Glucose 6-Phosphate 1-Dehydrogenase • Analyse mutant and wild type strains using metabolomics