Transcriptional studies on a Streptomyces clavuligerus oppA2 deletion mutant: N-Acetylglycyl-Clavaminic acid is an intermediate of clavulanic acid biosynthesis

[EN] The oppA2 gene encodes an oligopeptide-binding protein similar to the periplasmic substrate-binding proteins of the ABC transport systems. However, oppA2 is an orphan gene, not included in an ABC operon. This gene is located in the clavulanic acid (CA) gene cluster of Streptomyces clavuligerus and is essential for CA production. A transcriptomic study of the oppA2-null mutant S. clavuligerus ΔoppA2::aac showed changes in the expression levels of 233 genes from those in the parental strain. These include genes for ABC transport systems, secreted proteins, peptidases, and proteases. Expression of the clavulanic acid, clavam, and cephamycin C biosynthesis gene clusters was not significantly affected in the oppA2 deletion mutant. The genes for holomycin biosynthesis were upregulated 2-fold on average, and the level of upregulation increased to 43-fold in a double mutant lacking oppA2 and the pSCL4 plasmid. Strains in which oppA2 was mutated secreted into the culture the compound N-acetylglycyl-clavaminic acid (AGCA), a putative intermediate of CA biosynthesis. A culture broth containing AGCA, or AGCA purified by liquid chromatography-mass spectrometry (LC-MS), was added to the cultures of various non-CA-producing mutants. Mutants blocked in the early steps of the pathway restored CA production, whereas mutants altered in late steps did not, establishing that AGCA is a late intermediate of the biosynthetic pathway, which is released from the cells when the oligopeptide-binding protein OppA2 is not availableSIThis work was supported by grant BIO2013-34723 from the Spanish Ministry of Economy and Competitiveness. R. Álvarez-Álvarez and Y. Martínez-Burgo received a PFU fellowship from the Spanish Ministry of Science and Innovatio

Activation of Secondary Metabolite Gene Clusters in Streptomyces clavuligerus by the PimM Regulator of Streptomyces natalensis

Expression of non-native transcriptional activators may be a powerful general method to activate secondary metabolites biosynthetic pathways. PAS-LuxR regulators, whose archetype is PimM, activate the biosynthesis of polyene macrolide antifungals and other antibiotics, and have been shown to be functionally preserved across multiple Streptomyces strains. In this work we show that constitutive expression of pimM in Streptomyces clavuligerus ATCC 27064 significantly affected its transcriptome and modifies secondary metabolism. Almost all genes in three secondary metabolite clusters were overexpressed, including the clusters responsible for the biosynthesis of the clinically important clavulanic acid and cephamycin C. In comparison to a control strain, this resulted in 10- and 7-fold higher production levels of these metabolites, respectively. Metabolomic and bioactivity studies of S. clavuligerus::pimM also revealed deep metabolic changes. Antifungal activity absent in the control strain was detected in S. clavuligerus::pimM, and determined to be the result of a fivefold increase in the production of the tunicamycin complex

Análisis transcriptómico de cepas derivadas de Streptomyces clavuligerus ATCC 27064: expresión heteróloga de genes y activación de compuestos bioactivos = Transcriptomic analysis of strains obtained from Streptomyces clavuligerus atcc 27064: Heterologous gene expression and activation of bioactive compounds

498 p.Streptomyces clavuligerus es un actinomiceto conocido por ser el productor industrial de ácido clavulánico, un potente inhibidor de β-lactamasas que se administra en combinación con antibióticos β-lactámicos para el tratamiento de diversas infecciones, y productor de cefamicina C, un antibiótico β-lactámico empleado como molécula base en la elaboración de cefamicinas semisintéticas. Estos dos compuestos comparten mecanismos comunes de regulación de su biosíntesis. Tras la secuenciación del genoma de S. clavuligerus se ha descubierto que esta bacteria posee un megaplásmido de 1,8 Mb, hecho poco frecuente entre los Streptomyces, prescindible para su viabilidad. La información contenida en la secuencia del megaplásmido, pSCL4, y del cromosoma revela que ambos constituyen un reservorio de genes para la biosíntesis de compuestos bioactivos aún desconocidos. Por ello, en este trabajo se profundiza en la regulación del metabolismo secundario con el fin de poner en valor el potencial de S. clavuligerus en la producción de metabolitos secundarios aún no caracterizados. Para ello se abordaron los siguientes objetivos: la expresión heteróloga de la agrupación génica de la cefamicina C de S. clavuligerus en otras especies de Streptomyces, el análisis transcriptómico diferencial mediante micromatrices entre la cepa silvestre de S. clavuligerus y un mutante delecionado en el gen claR, el análisis transcriptómico diferencial mediante micromatrices entre la cepa silvestre de S. clavuligerus y un mutante carente del megaplásmido pSCL4, y, por último, la activación de compuestos bioactivos en S. clavuligerus mediante la expresión heteróloga del regulador PimM de Streptomyces natalensis

Additional file 1: Figure S1. of Discovering the potential of S. clavuligerus for bioactive compound production: cross-talk between the chromosome and the pSCL4 megaplasmid

Intergenic region from SCLAV_5488 to SCLAV_5489. Possible hairpin loop formed (ΔG = −85.98 kcal/mol) in the 294 nt excision region. The hairpin loop were predicted according to the M. Zuker’s DNA Fold Server http://unafold. rna.albany.edu/). Figure S2. Antibiotics production. S. clavuligerus ATCC27064 (white circles) and S. clavuligerus pSCL4− (black circles) were grown in SA medium, and production of clavulanic acid (left panel), cephamycin C (central panel) and holomycin (right panel) was quantified. Figure S3. RT-qPCR validation of the microarray data. (A) Genes tested: comparison of the data obtained for each gene analyzed in microarrays experiment (Mc values) and by RT-qPCR [log2 -2E(ΔΔCt)]. (B) Representation of the correlation between the results showed in panel A. Figure S4. MS and UV absortion spectra of the compounds detected in S. clavuligerus and the pSCL4− mutant. Only holomycin and N-propionyl holothin, detected in the mutant, have been described previously. Figure S5. Transcriptomic data of Methionine and Cysteine Metabolism Genes. A) Change of expression level of genes related to methionine or cysteine metabolism in S. clavuligerus pSCL4-. Genes not present in S. clavuligerus pSCL4− since they are in the megaplasmid are indicated with double asterisk (**); those genes present among the 231 CDS absent at the right arm of the chromosome are indicated with single asterisk (*). B) Pathways of methionine and cysteine metabolism in Streptomyces. Open arrows indicated upregulated genes in the pSCL4- strain. Steps carried by enzymes encoded by genes not present are marked with a black circle. Table S1. Effect of lack of pSCL4− in genes involved in cell envelope formation and morphological differentiation. Table S2. Oligonucleotides used in this work. (PDF 2056 kb

MicroRNA signature and integrative omics analyses define prognostic clusters and key pathways driving prognosis in patients with neuroendocrine neoplasms

Neuroendocrine neoplasms (NENs) are mutationally quiet (low number of mutations/Mb), and epigenetic mechanisms drive their development and progression. We aimed at comprehensively characterising the microRNA (miRNA) profile of NENs, and exploring downstream targets and their epigenetic modulation. In total, 84 cancer‐related miRNAs were analysed in 85 NEN samples from lung and gastroenteropancreatic (GEP) origin, and their prognostic value was evaluated by univariate and multivariate models. Transcriptomics (N = 63) and methylomics (N = 30) were performed to predict miRNA target genes, signalling pathways and regulatory CpG sites. Findings were validated in The Cancer Genome Atlas cohorts and in NEN cell lines. We identified a signature of eight miRNAs that stratified patients in three prognostic groups (5‐year survival of 80%, 66% and 36%). Expression of the eight‐miRNA gene signature correlated with 71 target genes involved in PI3K–Akt and TNFα–NF‐kB signalling. Of these, 28 were associated with survival and validated in silico and in vitro. Finally, we identified five CpG sites involved in the epigenetic regulation of these eight miRNAs. In brief, we identified an 8‐miRNA signature able to predict survival of patients with GEP and lung NENs, and identified genes and regulatory mechanisms driving prognosis in NEN patients