Comparative and pangenomic analysis of the genus Streptomyces

Combined transcriptomic and pangenomic analyses guide metabolic amelioration to enhance tiancimycins production

Exploration of high-yield mechanism is important for further titer improvement of valuable antibiotics, but how to achieve this goal is challenging. Tiancimycins (TNMs) are anthraquinone-fused enediynes with promising drug development potentials, but their prospective applications are limited by low titers. This work aimed to explore the intrinsic high-yield mechanism in previously obtained TNMs high-producing strain Streptomyces sp. CB03234-S for the further titer amelioration of TNMs. First, the typical ribosomal RpsL(K43N) mutation in CB03234-S was validated to be merely responsible for the streptomycin resistance but not the titer improvement of TNMs. Subsequently, the combined transcriptomic, pan-genomic and KEGG analyses revealed that the significant changes in the carbon and amino acid metabolisms could reinforce the metabolic fluxes of key CoA precursors, and thus prompted the overproduction of TNMs in CB03234-S. Moreover, fatty acid metabolism was considered to exert adverse effects on the biosynthesis of TNMs by shunting and reducing the accumulation of CoA precursors. Therefore, different combinations of relevant genes were respectively overexpressed in CB03234-S to strengthen fatty acid degradation. The resulting mutants all showed the enhanced production of TNMs. Among them, the overexpression of fadD, a key gene responsible for the first step of fatty acid degradation, achieved the highest 21.7 ± 1.1 mg/L TNMs with a 63.2% titer improvement. Our studies suggested that comprehensive bioinformatic analyses are effective to explore metabolic changes and guide rational metabolic reconstitution for further titer improvement of target products. KEY POINTS: • Comprehensive bioinformatic analyses effectively reveal primary metabolic changes. • Primary metabolic changes cause precursor enrichment to enhance TNMs production. • Strengthening of fatty acid degradation further improves the titer of TNMs.

Characterization of the family-level Borreliaceae pan-genome and development of an episomal typing protocol

Background The Borreliaceae family includes many obligate parasitic bacterial species which are etiologically associated with a myriad of zoonotic borrelioses including Lyme disease and vector-borne relapsing fevers. Infections by the Borreliaceae are difficult to detect by both direct and indirect methods, often leading to delayed and missed diagnoses. Efforts to improve diagnoses center around the development of molecular diagnostics (MDx), but due to deep tissue sequestration of the causative spirochaetes and the lack of persistent bacteremias, even MDx assays suffer from a lack of sensitivity. Additionally, the highly extensive genomic heterogeneity among isolates, even within the same species, contributes to the lack of assay sensitivity as single target assays cannot provide universal coverage. This within-species heterogeneity is partly due to differences in replicon repertoires and genomic structures that have likely arisen to support the complex Borreliaceae lifecycle in which these parasites have to survive in multiple hosts each with unique immune responses. Results We constructed a Borreliaceae family-level pangenome and characterized the phylogenetic relationships among the constituent taxa which supports the recent taxonomy of splitting the family into at least two genera. Gene content profiles were created for the majority of the Borreliaceae replicons, providing for the first time their unambiguous molecular typing. Conclusion Our characterization of the Borreliaceae pan-genome supports the splitting of the former Borrelia genus into two genera and provides for the phylogenetic placement of several non-species designated isolates. Mining this family-level pangenome will enable precision diagnostics corresponding to gene content-driven clinical outcomes while also providing targets for interventions.

BGCFlow: systematic pangenome workflow for the analysis of biosynthetic gene clusters across large genomic datasets

Genome mining is revolutionizing natural products discovery efforts. The rapid increase in available genomes demands comprehensive computational platforms to effectively extract biosynthetic knowledge encoded across bacterial pangenomes. Here, we present BGCFlow, a novel systematic workflow integrating analytics for large-scale genome mining of bacterial pangenomes. BGCFlow incorporates several genome analytics and mining tools grouped into five common stages of analysis such as: (i) data selection, (ii) functional annotation, (iii) phylogenetic analysis, (iv) genome mining, and (v) comparative analysis. Furthermore, BGCFlow provides easy configuration of different projects, parallel distribution, scheduled job monitoring, an interactive database to visualize tables, exploratory Jupyter Notebooks, and customized reports. Here, we demonstrate the application of BGCFlow by investigating the phylogenetic distribution of various biosynthetic gene clusters detected across 42 genomes of the Saccharopolyspora genus, known to produce industrially important secondary/specialized metabolites. The BGCFlow-guided analysis predicted more accurate dereplication of BGCs and guided the targeted comparative analysis of selected RiPPs. The scalable, interoperable, adaptable, re-entrant, and reproducible nature of the BGCFlow will provide an effective novel way to extract the biosynthetic knowledge from the ever-growing genomic datasets of biotechnologically relevant bacterial species.

Regulation of virulence mechanisms in plant-pathogenic Streptomyces

Streptomyces have a uniquely complex developmental life cycle that involves the coordination of morphological differentiation with the production of numerous bioactive specialized metabolites. The majority of Streptomyces spp. are soil-dwelling saprophytes, while plant pathogenicity is a rare attribute among members of this genus. Phytopathogenic Streptomyces are responsible for economically important diseases such as common scab, which affects potato and other root crops. Following the acquisition of genes encoding virulence factors, Streptomyces pathogens are expected to have specifically adapted their regulatory pathways to enable transition from a primarily saprophytic to a pathogenic lifestyle. Investigations of the regulation of pathogenesis have primarily focused on Streptomyces scabiei and the principal pathogenicity determinant thaxtomin A. The coordination of growth and thaxtomin A production in this species is controlled in a hierarchical manner by cluster-situated regulators, pleiotropic regulators, signalling and plant-derived molecules, and nutrients. Although the majority of phytopathogenic Streptomyces produce thaxtomins, many also produce additional virulence factors, and there are scab-causing pathogens that do not produce thaxtomins. The development of effective control strategies for common scab and other Streptomyces plant diseases requires a more in-depth understanding of the genetic and environmental factors that modulate the plant pathogenic lifestyle of these organisms.

Identification and evaluation of CAZyme genes, along with functional characterization of a new GH46 chitosanase from Streptomyces sp. KCCM12257

The genomic analysis of Streptomyces sp. KCCM12257 presented 233 CAZyme genes with a predominant glycosyl hydrolase family. This contributes degradation of various polysaccharides including chitin and chitosan, and other promising candidates for the production of different oligosaccharides. We screened the strain providing different polysaccharides as a sole source of carbon and strain KCCM12257, showed higher activity towards colloidal chitosan. Further, we identified and characterized a new chitosanase (MDI5907146) of GH46 family. There was no activity towards chitin, carboxymethylcellulose, or even with chitosan powder. This enzyme acts on colloidal chitosan and hydrolyzes it down into monoacetyl chitobiose, which consists of two glucosamine units with an acetyl group attached to them. The maximum enzyme activity was observed at pH 6.5 and 40 °C using colloidal chitosan as a substrate. The Co2+ metal ions almost double the reaction as compared to other metal ions. The dissociation constant (Km) and of colloidal chitosan (≥90 % and ≥75%DD) were 3.03 mg/ml and 5.01 mg/ml respectively, while maximum velocity (Vmax) values were found to be 36 mg/ml, and 30 μM/μg/min, respectively. Similarly, catalytic efficiency (Kcat/Km) of colloidal chitosan with ≥90 %DD was 1.9 fold higher than colloidal chitosan with ≥75%DD.

Phylogenetic classification of natural product biosynthetic gene clusters based on regulatory mechanisms

The natural products (NPs) biosynthetic gene clusters (BGCs) represent the adapting biochemical toolkit for microorganisms to thrive different microenvironments. Despite their high diversity, particularly at the genomic level, detecting them in a shake-flask is challenging and remains the primary obstacle limiting our access to valuable chemicals. Studying the molecular mechanisms that regulate BGC expression is crucial to design of artificial conditions that derive on their expression. Here, we propose a phylogenetic analysis of regulatory elements linked to biosynthesis gene clusters, to classify BGCs to regulatory mechanisms based on protein domain information. We utilized Hidden Markov Models from the Pfam database to retrieve regulatory elements, such as histidine kinases and transcription factors, from BGCs in the MIBiG database, focusing on actinobacterial strains from three distinct environments: oligotrophic basins, rainforests, and marine environments. Despite the environmental variations, our isolated microorganisms share similar regulatory mechanisms, suggesting the potential to activate new BGCs using activators known to affect previously characterized BGCs.

Genomic analysis of lignocellulolytic enzyme producing novel Streptomyces sp.MS2A for the bioethanol applications

The conversion of lignocellulosic waste to energy offers a cost-effective biofuel. The current study discusses the utilization of cellulose in rice husks by lichen-associated Streptomyces sp. MS2A via carbohydrate metabolism. Out of 39 actinobacteria, one actinobacterial strain MS2A, showed CMCase, FPase, and cellobiohydrolase activity. The whole genome analysis of Streptomyces sp. MS2A showed maximum similarity with Streptomyces sp. CCM_MD2014. The genome analysis confirmed the presence of cellulose-degrading genes along with xylan-degrading genes that code for GH3, GH6, GH9, GH11, GH43, GH51, and 15 other GH families with glycosyl transferase, carbohydrate-binding modules, and energy metabolism groups. Protein family analysis corroborates the enzyme family. Among the 19,402 genes of Streptomyces sp. MS2A, approximately 70 GH family codes for lignocellulose degradation enzymes. The structure of cellulase was modeled and validated. Scanning electron microscopy and gas chromatography-mass spectrometry (GCMS) was performed to analyze the lignocellulosic degradation of rice husk and the end product bioethanol.