Comparative Genomics Determines Strain-Dependent Secondary Metabolite Production in Streptomyces venezuelae Strains

Deletions of conserved extracytoplasmic function sigma factors-encoding genes in Streptomyces have a major impact on secondary metabolism

BACKGROUND

Ethanol shock significantly affects expression of over 1200 genes in Streptomyces venezuelae NRRL B-65,442, including those involved in secondary metabolite biosynthesis and a cryptic gene pepX, which encodes a 19-amino acid peptide with an unknown function.

RESULTS

To establish a possible correlation between the PepX peptide and secondary metabolism in S. venezuelae, its gene was deleted, followed by analyses of the transcriptome and secondary metabolome of the mutant. Although the secondary metabolome of the pepX mutant was not strongly affected, pepX deletion, similar to ethanol shock, mostly resulted in downregulated expression of secondary metabolite biosynthesis gene clusters (BGCs). At the same time, there was a reverse correlation between the expression of certain extracytoplasmic function sigma factors (ECFs) and several BGCs. Individual deletions of three selected ECF-coding genes conserved in Streptomyces that were upregulated upon both pepX deletion and ethanol shock, had a profound positive effect on the expression of BGCs, which also correlated with the overproduction of specific secondary metabolites. Deletion of one such ECF-coding gene in a marine sponge-derived Streptomyces sp. also significantly altered the secondary metabolite profile, suggesting an important role of this ECF in the regulation of secondary metabolism.

CONCLUSIONS

These findings pave the way for the activation or upregulation of BGCs in Streptomyces bacteria harboring genes for ECFs homologous to those identified in this study, hereby assisting in the discovery of novel bioactive secondary metabolites.

Accessing the specialized metabolome of actinobacteria from the bulk soil of Paullinia cupana Mart. on the Brazilian Amazon: a promising source of bioactive compounds against soybean phytopathogens

The Amazon rainforest, an incredibly biodiverse ecosystem, has been increasingly vulnerable to deforestation. Despite its undeniable importance and potential, the Amazonian microbiome has historically received limited study, particularly in relation to its unique arsenal of specialized metabolites. Therefore, in this study our aim was to assess the metabolic diversity and the antifungal activity of actinobacterial strains isolated from the bulk soil of Paullinia cupana, a native crop, in the Brazilian Amazon Rainforest. Extracts from 24 strains were subjected to UPLC-MS/MS analysis using an integrative approach that relied on the Chemical Structural and Compositional Similarity (CSCS) metric, GNPS molecular networking, and in silico dereplication tools. This procedure allowed the comprehensive understanding of the chemical space encompassed by these actinobacteria, which consists of features belonging to known bioactive metabolite classes and several unannotated molecular families. Among the evaluated strains, five isolates exhibited bioactivity against a panel of soybean fungal phytopathogens (Rhizoctonia solani, Macrophomina phaseolina, and Sclerotinia sclerotiorum). A focused inspection led to the annotation of pepstatins, oligomycins, hydroxamate siderophores and dorrigocins as metabolites produced by these bioactive strains, with potentially unknown compounds also comprising their metabolomes. This study introduces a pragmatic protocol grounded in established and readily available tools for the annotation of metabolites and the prioritization of strains to optimize further isolation of specialized metabolites. Conclusively, we demonstrate the relevance of the Amazonian actinobacteria as sources for bioactive metabolites useful for agriculture. We also emphasize the importance of preserving this biome and conducting more in-depth studies on its microbiota.

Targeted Metabolomics and High-Throughput RNA Sequencing-Based Transcriptomics Reveal Massive Changes in the Streptomyces venezuelae NRRL B-65442 Metabolism Caused by Ethanol Shock

The species Streptomyces venezuelae is represented by several distinct strains with variable abilities to biosynthesize structurally diverse secondary metabolites. In this work, we examined the effect of ethanol shock on the transcriptome and metabolome of Streptomyces venezuelae NRRL B-65442 using high-throughput RNA sequencing (RNA-seq) and high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Ethanol shock caused massive changes in the gene expression profile, differentially affecting genes for secondary metabolite biosynthesis and central metabolic pathways. Most of the data from the transcriptome analysis correlated well with the metabolome changes, including the overproduction of jadomycin congeners and a downshift in the production of desferrioxamines, legonoxamine, foroxymithin, and a small cryptic ribosomally synthesized peptide. Some of the metabolome changes, such as the overproduction of chloramphenicol, could not be explained by overexpression of the cognate biosynthetic genes but correlated with the expression profiles of genes for precursor biosynthesis. Changes in the transcriptome were also observed for several genes known to play a role in stress response in other bacteria and included at least 10 extracytoplasmic function σ factors. This study provides important new insights into the stress response in antibiotic-producing bacteria and will help to understand the complex mechanisms behind the environmental factor-induced regulation of secondary metabolite biosynthesis. IMPORTANCE Streptomyces spp. are filamentous Gram-positive bacteria known as versatile producers of secondary metabolites, of which some have been developed into human medicines against infections and cancer. The genomes of these bacteria harbor dozens of gene clusters governing the biosynthesis of secondary metabolites (BGCs), of which most are not expressed under laboratory conditions. Detailed knowledge of the complex regulation of BGC expression is still lacking, although certain growth conditions are known to trigger the production of previously undetected secondary metabolites. In this work, we investigated the effect of ethanol shock on the production of secondary metabolites by Streptomyces venezuelae and correlated these findings with the expression of cognate BGCs and primary metabolic pathways involved in the generation of cofactors and precursors. The findings of this study set the stage for the rational manipulation of bacterial genomes aimed at enhanced production of industrially important bioactive natural products.

AdpA Positively Regulates Morphological Differentiation and Chloramphenicol Biosynthesis in Streptomyces venezuelae

In members of genus Streptomyces, AdpA is a master transcriptional regulator that controls the expression of hundreds of genes involved in morphological differentiation, secondary metabolite biosynthesis, chromosome replication, etc. However, the function of AdpASv, an AdpA ortholog of Streptomyces venezuelae, is unknown. This bacterial species is a natural producer of chloramphenicol and has recently become a model organism for studies on Streptomyces. Here, we demonstrate that AdpASv is essential for differentiation and antibiotic biosynthesis in S. venezuelae and provide evidence suggesting that AdpASv positively regulates its own gene expression. We speculate that the different modes of AdpA-dependent transcriptional autoregulation observed in S. venezuelae and other Streptomyces species reflect the arrangement of AdpA binding sites in relation to the transcription start site. Lastly, we present preliminary data suggesting that AdpA may undergo a proteolytic processing and we speculate that this may potentially constitute a novel regulatory mechanism controlling cellular abundance of AdpA in Streptomyces. IMPORTANCEStreptomyces are well-known producers of valuable secondary metabolites which include a large variety of antibiotics and important model organisms for developmental studies in multicellular bacteria. The conserved transcriptional regulator AdpA of Streptomyces exerts a pleiotropic effect on cellular processes, including the morphological differentiation and biosynthesis of secondary metabolites. Despite extensive studies, the function of AdpA in these processes remains elusive. This work provides insights into the role of a yet unstudied AdpA ortholog of Streptomyces venezuelae, now considered a novel model organism. We found that AdpA plays essential role in morphological differentiation and biosynthesis of chloramphenicol, a broad-spectrum antibiotic. We also propose that AdpA may undergo a proteolytic processing that presumably constitutes a novel mechanism regulating cellular abundance of this master regulator.

Re-classification of Streptomyces venezuelae strains and mining secondary metabolite biosynthetic gene clusters

Streptomyces species have attracted considerable interest as a reservoir of medically important secondary metabolites, which are even diverse and different between strains. Here, we reassess ten Streptomyces venezuelae strains by presenting the highly resolved classification, using 16S rRNA sequencing, MALDI-TOF MS protein profiling, and whole-genome sequencing. The results revealed that seven of the ten strains were misclassified as S. venezuelae species. Secondary metabolite biosynthetic gene cluster (smBGC) mining and targeted LC-MS/MS based metabolite screening of S. venezuelae and misclassified strains identified in total 59 secondary metabolites production. In addition, a comparison of pyrrolamide-type antibiotic BGCs of four misclassified strains, followed by functional genomics, revealed that athv28 is critical in the synthesis of the anthelvencin precursor, 5-amino-3,4-dihydro-2H-pyrrole-2-carboxylate (ADPC). Our findings illustrate the importance of the accurate classification and better utilization of misclassified Streptomyces strains to discover smBGCs and their secondary metabolite products.

A High-Yield Streptomyces Transcription-Translation Toolkit for Synthetic Biology and Natural Product Applications

Streptomyces spp. are a major source of clinical antibiotics and industrial chemicals. Streptomyces venezuelae ATCC 10712 is a fast-growing strain and a natural producer of chloramphenicol, jadomycin, and pikromycin, which makes it an attractive candidate as a next-generation synthetic biology chassis. Therefore, genetic tools that accelerate the development of S. venezuelae ATCC 10712, as well as other Streptomyces spp. models, are highly desirable for natural product engineering and discovery. To this end, a dedicated S. venezuelae ATCC 10712 cell-free system is provided in this protocol to enable high-yield heterologous expression of high G+C (%) genes. This protocol is suitable for small-scale (10-100 μL) batch reactions in either 96-well or 384-well plate format, while reactions are potentially scalable. The cell-free system is robust and can achieve high yields (~5-10 μM) for a range of recombinant proteins in a minimal setup. This work also incorporates a broad plasmid toolset for real-time measurement of mRNA and protein synthesis, as well as in-gel fluorescence staining of tagged proteins. This protocol can also be integrated with high-throughput gene expression characterization workflows or the study of enzyme pathways from high G+C (%) genes present in Actinomycetes genomes.

Streptomyces venezuelae NRRL B-65442: genome sequence of a model strain used to study morphological differentiation in filamentous actinobacteria

For over a decade, Streptomyces venezuelae has been used to study the molecular mechanisms that control morphological development in streptomycetes and it is now a well-established model strain. Its rapid growth and ability to sporulate in a near-synchronised manner in liquid culture, unusual among streptomycetes, greatly facilitates the application of modern molecular techniques such as ChIP-seq and RNA-seq, as well as fluorescence time-lapse imaging of the complete Streptomyces life cycle. Here we describe a high-quality genome sequence of our isolate of the strain (NRRL B-65442) consisting of an 8.2 Mb chromosome and a 158 kb plasmid, pSVJI1, which had not been reported previously. Surprisingly, while NRRL B-65442 yields green spores on MYM agar, the ATCC type strain 10712 (from which NRRL B-65442 was derived) produces grey spores. While comparison of the genome sequences of the two isolates revealed almost total identity, it did reveal a single nucleotide substitution in a gene, vnz_33525, likely to be involved in spore pigment biosynthesis. Replacement of the vnz_33525 allele of ATCC 10712 with that of NRRL B-65442 resulted in green spores, explaining the discrepancy in spore pigmentation. We also applied CRISPR-Cas9 to delete the essential parB of pSVJI1 to cure the plasmid from the strain without obvious phenotypic consequences.

Venn diagrams in bioinformatics

Venn diagrams are widely used tools for graphical depiction of the unions, intersections and distinctions among multiple datasets, and a large number of programs have been developed to generate Venn diagrams for applications in various research areas. However, a comprehensive review comparing these tools has not been previously performed. In this review, we collect Venn diagram generators (i.e. tools for visualizing the relationships of input lists within a Venn diagram) and Venn diagram application tools (i.e. tools for analyzing the relationships between biological data and visualizing them in a Venn diagram) to compare their functional capacity as follows: ability to generate high-quality diagrams; maximum datasets handled by each program; input data formats; output diagram styles and image output formats. We also evaluate the picture beautification parameters of the Venn diagram generators in terms of the graphical layout and briefly describe the functional characteristics of the most popular Venn diagram application tools. Finally, we discuss the challenges in improving Venn diagram application tools and provide a perspective on Venn diagram applications in bioinformatics. Our aim is to assist users in selecting suitable tools for analyzing and visualizing user-defined datasets.