Functional Characterization of Polyketide Synthase Clusters in Streptomyces anandii J6

Article information

Plant Pathol J. 2025;41(4):539-544

Publication date (electronic) : 2025 August 1

doi : https://doi.org/10.5423/PPJ.NT.04.2025.0059

Da-Ran Kim¹, Youn-Sig Kwak^2,

¹National Institute of Horticultural and Herbal Science, Rural Development Administration, Wanju 55365, Korea

²Division of Applied Life Science (BK21) and Research Institute of Life Science, Gyeongsang National University, Jinju 52828, Korea

^*Corresponding author. Phone) +82-55-772-1922, FAX) +82-55-772-1929, E-mail) kwak@gnu.ac.kr

Handling Editor: Ki-Tae Kim

Received 2025 April 28; Revised 2025 July 11; Accepted 2025 July 15.

Streptomyces are well known for their antifungal properties and the production of numerous secondary metabolites, such as non-ribosomal peptides and polyketides (Lee et al., 2020; Yagüe et al., 2012). Therefore, extensive research on Streptomyces gene functions has been conducted, involving knockout and random mutagenesis strains to elucidate these functions (Cho et al., 2017; Bachmann et al., 2014; Hong et al., 2019; Kieser et al., 2000). Techniques for genetic manipulation have evolved from homologous recombination-based knockouts and cosmid protocols to the CRISPR-Cas9 system (Cobb et al., 2015; Sun et al., 2012). The CRISPR-Cas9 system has enabled the generation of mutant strains with high site-specificity and efficiency, respectively (Cobb et al., 2015). This has been integrated into the Streptomyces genetic tool wherein the Streptococcus pyogenes Cas9 protein was cloned into the pCRISPomyces-2 plasmid (Cobb et al., 2015; Mali et al., 2013). Previous studies using the pCRISPomyces-2 plasmid for targeted gene mutagenesis have successfully identified the functions of secondary metabolites in Streptomyces species, such as valinomycin and lasso peptides (Kim and Kwak, 2021; Kim et al., 2023).

Valinomycine biosynthetic genes vlm1 and vlm2 were deleted in the genome of S. bacillaris S8, and the loss-of-function mutants clearly demonstrated that valinomycin has antifungal activity against the turfgrass large patch pathogen (Jeon et al., 2019, 2021; Kim et al., 2022). Subsequent research findings have led to isolating biocontrol agents from rhizosphere soil for turfgrass diseases. Exceptional biocontrol agent, Streptomyces sp. J6 was obtained from turfgrass monoculture sites with different cultivation histories, such as 2, 13, and 25 years of continuous turfgrass cultivation (Jeon et al., 2021). These findings demonstrated that Streptomyces sp. J6 plays a crucial role in protection during the early stages of turfgrass growth. However, whole genome sequencing did not identify the strain at the genus level.

In this study, we reclassified Streptomyces sp. J6 as Streptomyces anandii J6 based on the whole genome sequencing information and characterized its antifungal polyketide gene clusters at the whole genome level. The whole genome sequencing was conducted based on our previous findings by Jeon et al. (2021). Re-classification of the J6 strain was performed compared to 25 Streptomyces and 4 Actinobacteria reference strains, with average nucleotide identity (ANI) analysis using MUMmer version 3.0 as the aligner (ANIm) (https://mummer.sourceforge.net). The J6 genome consisted of one chromosome and a plasmid (Fig. 1). The results showed that strain J6 showed a 97.6% ANI similarity at the chromosomal level with the S. anandii JCM4720 strain (Fig. 2). The J6 strain exhibited a GC content of 72.1%, 7,159 coding sequences (CDS), 81 tRNA genes, and 18 rRNA on the chromosome, and 69.9% GC content and 190 CDS on the plasmid (Table 1). Following genome identification, secondary metabolite gene clusters were analyzed using the antiSMASH 5.0 (https://docs.antismash.secondarymetabolites.org) (Medema et al., 2011). The J6 strain had eleven putative gene clusters that displayed moderate homology, and more than 30% of the proteins showed sequence similarity (Supplementary Table 1).

Fig. 1

Streptomyces anandii J6 genome reassigned with genome maps. (A) S. anandii J6 chromosome. (B) Plasmid of S. anandii J6. The genome map was drawn from the annotation result in Prokka v1.14.6. Marked characteristics are shown from outside to the center: coding sequence (CDS) on the forward strand (+), CDS on the reverse strand (−), GC content, and GC skew. The genome map was drawn using the ggplot2 package of R (v4.0.3).

Fig. 2

Average nucleotide identity (ANI) identification and alignment of 24 Streptomyces and 4 Actinobacteria reference strains. The lower left heatmap presents ANI identity. The trees show similarity by ANI identity scores.

Table 1

Streptomyces anandii J6 genome reassigned

Among these clusters, we focused on type II and type III polyketides, which are clusters 9, 10, and 12. To clearly elucidate the function of polyketide synthase (PKS) genes with antifungal activity among the various PKS clusters produced by Streptomyces, we conducted experiments on the PKS clusters of the J6 strain in this study. These three different clusters were nominated for antifungal functional gene clusters and were further analyzed using the CRISPR-Cas9 mutagenesis system to study their functions. The bacterial strain was prepared as a spore stock, which was collected from full-sporulated MS medium (20 g of mannitol, 20 g of soya flour per L) and adjusted to an optical density of 1.0 at 600nm (OD₆₀₀), corresponding to more than 10⁹ CFU/mL. At the time, the destination vector to conjugation was added to the homologous region (~1.2 kb), guide RNA (gRNA) region, and backbone plasmid as pCRISPomyces-2 (Cobb et al., 2015). The first step was amplified to the homologous region at the strain J6 genome using linked PCR; the PCR has three steps. Second, the product was purified with Expin GelSV kit (GeneAll Biotechnology, Seoul, Korea) and cloning the pGEM-T Easy Vector (Promega, Madison, WI, USA). The ligation mixture was then introduced into competent DH5α cells using a heat shock protocol (300–500 ng of DNA and 100 μL of DH5α cells, incubated on ice for 30 min, heat-shocked at 42°C for 1 min 30 s, then returned to ice for 2 min. Subsequently, added 900 μL of LB broth (30 g of Luria broth per L) was added. The mixture was spread on LB agar (30 g of Luria broth, 20 g of agar per L; 100 μg/mL of ampicillin, and 40 μg/mL of X-gal) for blue/white selection. After 16 h, a single white colony was inoculated into LB broth (30 g/L Luria broth) and cultured at 37°C for 16 h. Plasmid DNA was then extracted using the DokDo-Prep Plasmid Mini-Prep kit (ELPIS-Biotech, Daejeon, Korea) and was quantified using a NanoDrop 2000C spectrometer (Thermo Scientific, Waltham, MA, USA). Third, gRNA was cloned into the pBHA (2,002 bp) vector, which was synthesized by Bioneer (Daejeon, Korea). Fourth, the restriction and ligation step using BbsI for the homologous region and all PCR primers and plasmids in Supplementary Tables 2 and 3. The resulting fragments were ligated using T4 ligase, connecting the two fragments and subsequently linking them with the gRNA. The resultant plasmids were then transformed into E. coli ET12567 containing pUZ802 (Bierman et al., 1992). The transformed strains were revived on the LB agar. The agar medium was supplemented with kanamycin (30 μg/mL), chloramphenicol (25 μg/mL), and apramycin (50 μg/mL) according to the method described by Kieser et al. (2000).

Before mutagenesis of J6, the expression levels of genes in clusters 9, 10, and 12 were confirmed using RNA extracted by the TRIzol method (Van Dessel et al., 2004). A total of 800 ng of RNA was reverse transcribed using the ReverTra Ace-α kit (TOYOBO, Japan), and the resulting cDNA was used for quantitative real-time PCR (qRT-PCR) on a CFX96 Real-Time System (Bio-Rad, Hercules, CA, USA). Relative expression levels were calculated using the DCt method and analyzed in R version 3.3.1. qRT-PCR analysis showed that genes related to antibiotic biosynthesis were reliably expressed. (Fig. 3).

Fig. 3

qRT-PCR analysis of pks-related gene expression in Streptomyces anandii J6 and antifungal activity of loss-of-function mutants. Relative gene expression level was normalized and calculated using the housekeeping genes, hrdB and recA. The letters above the bars indicate statistically significant differences. (A) Cluster-9: cure. (B) Cluster-10: srsA. (C) Cluster-12: xanF. Antifungal activity of knockout mutants against Rhizoctonia solani AG2-2 (KACC no. 40132). The mutants were created by the CRSPR/cas9 system. The mutants (10 μL on a 0.8-cm filter disk) were incubated in PDK. After 5 days, an agar block of R. solani AG2-2 (0.4-cm diam.) was inoculated at the center of the plate and incubated at 28°C for 7 days (n = 5). The J6 strain treatment and the numbers on the disc indicated each mutant based on the cluster number.

In the confront assay against fungal pathogen, bacteria of S. anandii J6 and the generated mutant strains were grown on MS media (20 g of mannitol, 20 g of soya flour per L) and cultured at 28°C for 5 days. The spores were collected using a sterilized cotton ball and a 15-mL syringe for filtration, which was adjusted to OD_600nm = 0.7. Then, the spore stock was inoculated on a filter disk (8 mm diameter) in PDK agar media (10 g of potato dextrose broth, 10 g of peptone, 20 g of agar per L), and it was incubated at 28°C for 3 days for sporulation and added fungal pathogen at the center of the plate. Turfgrass large patch pathogen, Rhizoctonia solani AG 2-2 (KACC no. 40132), was cultured on PDA (24 g of potato dextrose broth, 20 g of agar per L) at 28°C for 5 days. Antagonism assay was performed for 7 days at 28°C. Three target gene mutants showed different antagonistic effects on the large patch pathogen (Fig. 3). Although DsrsA had dramatically decreased antifungal activity (Fig. 3B), DcurE and DxanF had no effect on inhibiting the fungal pathogen growth (Fig. 3A and C).

Based on the mutagenesis system, loss of antifungal activity was observed in the DsrsA mutant strain (Cluster 10). The srsA gene is known to synthesize alkylresorcinols from acyl-CoAs and various initial substrates with different chain lengths (Funbashi et al., 2008). Several Streptomyces species have been shown to synthesize resorcinols, which are known to exhibit antibiotic effects, and these alkylresorcinols are produced from one methylmalonyl-CoA and two malonyl-CoAs as extenders in SrsA (Ananthakrishnan et al., 1990). The SrsA protein, expressed in S. lividans, was a type III PKS (polyketide synthases) for the synthesis of phenolic lipids, including alkylresorcinols and alkylpyrones (Funabashi et al., 2008).

In these results, it was demonstrated that the phenolic lipids produced by the J6 strain have antifungal effects against the large patch pathogen. However, the DxanF deletion in the J6 strain did not affect antifungal activity. The xanF gene encodes a ketosynthase involved in the biosynthesis of xantholipin, known for its antitumor and antibiotic properties (Zhang et al., 2012).

Lantipeptides are well-known ribosomal synthesized peptides that serve as key antifungal agents produced by Streptomyces. Grisin, a class II lantipeptide produced by Streptomyces, has demonstrated strong antifungal activity against Fusarium oxysporum (Kim et al., 2019). Conprimycin, another class II lantipeptide, was identified as a novel antibiotic compound (Kim and Kwak, 2021). However, the ΔcurE mutant exhibited antifungal activity against R. solani, the causal agent of large patch disease.

Taken together, these findings suggest that the antibiotic effect does not necessarily correlate with antifungal activity, highlighting the need for further genetic analysis to explain the specific functions of these genes. Additionally, the results indicate that Streptomyces possess a wide variety of secondary metabolites encoded in their genome, although only some of these are associated with key antifungal activities. Biocontrol agents effective against fungal pathogens have been discovered under diverse environmental conditions, which exert varying selective pressures on these agents. Consequently, we focused on identifying and isolating strains from previously unexplored sources. Additionally, it is recommended to use the most recent versions of genomes databases, as the databases are continuously updated and subject to changes in classification and categorization.