The bacterial strains and plasmids used in this study are listed in Supplementary Table S1. For routine cloning strategies Escherichia coli Novablue (Novagen) was used. S. lividans T7 (Fischer, 1996) and SHP22-7 (Handayani et al., 2018) were applied for antibiotic production analysis, generation of overexpression strains, and transcriptional analysis. Cloning procedures and strain cultivation were carried out as described before (Mast et al., 2015). For cultivation and isolation of RNA, Streptomyces strains were grown in 100 ml of R5 medium in 500-ml Erlenmeyer flasks (with steel springs) on an orbital shaker (180 rpm) at 28°C (Kieser et al., 2000). For isolation of genomic DNA and protoplast transformation experiments, strains were grown in 100 ml of S-medium (Kieser et al., 2000). Kanamycin (50 μg/ml), apramycin (50 μg/ml), or thiostrepton (20 μg/ml) were used for selection when appropriate. For antibiotic production experiments with S. lividans, strains were grown in YEME medium as reported before (Mast et al., 2015). For antibiotic production experiments with SHP22-7, strains (SHP22-7papR2-OE; references: SHP22-7pRM4 and SHP22-7 WT) were grown in 50 ml NL410 medium consisting of glucose (10 g l^–1), glycerol (10 g l^–1), oat meal (5 g l^–1), soy flour (10 g l^–1), yeast extract (5 g l^–1), Bacto casamino acids (5 g l^–1), CaCO₃ (1 g l^–1), and distilled water (pH was adjusted to 7.0 with NaOH) as a preculture. After 3 days, 10 ml of preculture was transferred to 100 ml of sterile main culture medium NL19, consisting of mannitol (20 g l^–1), soy flour (20 g l^–1), and distilled water (pH adjusted to pH 7.5 with NaOH). Cells were grown for 168 h at 28°C.

Basic procedures for DNA manipulation were performed as described previously (Sambrook et al., 1989; Kieser et al., 2000). Primers used for PCR were obtained from MWG Biotech AG (MWG, Ebersberg, Germany) and are listed in Supplementary Table S1.

For papR2 overexpression experiments with SHP22-7, the papR2 gene was isolated as a NdeI/HindIII-fragment from plasmid pGM190/papR2 (Mast et al., 2015) and was cloned into the NdeI/HindIII restriction site of the integrative expression vector pRM4. In the resulting overexpression construct pRM4/papR2, the papR2 gene is under control of the constitutive promoter of the erythromycin resistance gene ermEp^∗. pRM4/papR2 was transferred to SHP22-7 by protoplast transformation. Transformants were selected with apramycin (50 μg/ml), which resulted in the overexpression strain SHP22-7papR2-OE. Strain SHP22-7pRM4, harboring the empty pRM4 vector, was generated by protoplast transformation accordingly and served as a reference.

For papR2 overexpression experiments SLpapR2-OE precultures were grown in 100 ml of YEME liquid medium for 2 days at 28°C. Five milliliters of preculture was used as inoculum for 100 ml YEME liquid medium as main culture with thiostrepton (12.5 μg/ml) as inductor for gene expression (Mast et al., 2015). The main culture was cultivated for 3 days at 28°C. PapR2 protein purification was carried out as reported before (Mast et al., 2015).

For Red detection, culture supernatant from SLpapR2-OE and SLpGM190 (reference) was treated as reported in Onaka et al. (2011) and absorption was measured with a Hitachi U-2000 spectrophotometer.

For SHP22-7 compound detection and bioassay tests, 5 ml culture samples of SHP22-7papR2-OE (references: SHP22-7pRM4 and SHP22-7 WT) was extracted with 5 ml ethyl acetate for 30 min at RT. Ethyl acetate samples were concentrated in vacuo completely and then redissolved in 0.75 ml of methanol. Methanolic extracts were used for bioassays and high-performance liquid chromatography/mass spectrometry (HPLC–MS) analysis.

Antibiotic activity was analyzed in disc diffusion assays using Bacillus subtilis ATCC6051 as test organism. Thirty microliters of methanolic extract from three independent biological samples of SHP22-7 WT, SHP22-7pRM4, and SHP22-7papR2-OE, respectively, was pipetted on a filter disc, which was placed on a B. subtilis test plate. Five microliters of kanamycin (50 μg/ml) was applied as a positive control and 30 μl of methanol as negative control to test the functionality of the B. subtilis bioassay plates. The plates were incubated overnight at 37°C. Antibiotic activity was quantified by measuring the diameter of the inhibition zone around the filter discs. The bioassay was carried out as 10 independent biological replicates.

High-performance liquid chromatography analyses were performed with a HP1090M system with ChemStation 3D software rev. A.08.03 (Agilent Technologies, Waldbronn, Germany) on a Nucleosil C18 column (5 μm, 125 mm × 3 mm) fitted with a precolumn (20 × 3 mm) and with a flow rate of 850 μl min^–1. Chromatography was done by linear gradient elution from 95.5 solvent A (water with 0.1% phosphoric acid) to 100% solvent B [acetonitrile (ACN)] over 15 min. The injection volume was 5 μl. Multiple wavelength monitoring was performed at 210, 230, 260, 280, 310, 435, and 500 nm. UV-Vis spectra were measured from 200 to 600 nm. The evaluation of the chromatograms (210 nm only) was done by means of an in-house HPLC–UV–Vis database.

High-performance liquid chromatography–mass spectrometry analysis of amicetin/plicacetin was performed with an Agilent 1200 series chromatography system (binary pump, high performance autosampler, DAD-detector) coupled with an LC/MSD Ultra Trap System XCT 6330 (Agilent Technologies, Waldbronn, Germany). The sample (5 μl) was injected on a Nucleosil 100 C18 column (3 μm, 100 × 2 mm) fitted with a precolumn (3 μm, 10 × 2 mm) at a flow rate of 400 μl/min and a linear gradient from 100% solvent A (0.1% HCOOH in water) to 100% solvent B (0.06% HCOOH in ACN) over 15 min at 40°C. UV–Vis-detection was done at 220, 260, 280, 360, and 435 nm. Electrospray ionization was performed in positive and negative ultra-scan mode (alternating) with a capillary voltage of 3.5 kV and a drying gas temperature of 350°C. Detection of m/z values was conducted with Agilent DataAnalysis for 6300 Series IonTrap LC/MS Version 3.4 (Bruker Daltonik). Upon HPLC–MS analyses amicetin, plicacetin, and plicacetin isomer were identified by comparisons of their UV/visible spectra, retention times, and molecular masses with authentic standards, as m/z 617.1 [M−H]^– and m/z 516.1 [M−H]^–, respectively.

With the webtool antiSMASH whole genomes can be scanned for the occurrence of BGCs. Gene cluster similarity is given in % and indicates the number of similar genes to a known cluster. Genes are similar if a BLAST-alignment results in an e-value <10^–5 and the sequence identity is >30%. Additionally, the shortest alignment must enclose >25% of the sequence. If all genes of a known cluster can be found in the query cluster, the similarity of the sequences is 100%. The similarity lowers if less genes of the known cluster can be found in the query cluster (Medema et al., 2011).

PatScan analysis (Blin et al., 2018) was performed with the S. lividans T7 genome (GenBank Accession Number ACEY00000000) and the PapR2 consensus sequence 5′-GTCAGSS-3′ using the software at https://patscan.secondarymetabolites.org/.

For EMSAs with Red-specific promoter regions, 182 bp DNA fragments of the upstream regions of redP and redQ were amplified by PCR from genomic DNA of S. lividans T7 with primer pairs PredPfw/rv and PredQfw/rv, respectively (Supplementary Table S1). For EMSAs with the pliA promoter region, a 230 bp DNA fragment of the upstream region of pliA was amplified by PCR from genomic DNA of strain SHP22-7 as template and primer pair PpliAfw/rv (Supplementary Table S1). Promoter DNA amplificates included a 16 bp Cy5 adapter sequence, each at the 3′- and 5′-end, which was added via the respective primer sequences. The generated amplificates were used as templates in a second PCR approach together with a Cy5 primer (Supplementary Table S1) in order to conduct Cy5 labeling of the promoter regions. Promoter labeling and PapR2 EMSAs were carried out with variable concentrations of PapR2 protein sample as reported before (Mast et al., 2015). To verify the specificity of the PapR2-DNA binding, an excess of unlabeled, specific, and non-specific DNA, respectively, was added to the EMSA mixture as described previously (Mast et al., 2015). DNA bands were visualized by fluorescence imaging using a Typhoon Trio^TM Variable Mode Imager (GE Healthcare).

SLpGM190 and SLpapR2-OE, as well as SHP22-7, SHP22-7pRM4, and SHP22-7papR2-OE were each grown under papR2-overexpression conditions as described above. Thirty milliliters of each cell culture was harvested after 48 h. Cell disruption was carried out with glass beads (150–212 μm; Sigma) at 6,500 rpm, 1 × 20-30 s, using a Precellys Homogenizer (Peqlab). Total RNA was isolated as described previously (Sambrook et al., 1989) and served as the basis for RT-PCR experiments. DNA was removed by digestion with DNase (Thermo Fisher Scientific) and absence of DNA was verified via PCR analysis. RNA concentrations and quality were checked using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific). cDNA from 3 μg RNA was generated with random primers, reverse transcriptase, and cofactors (Fermentas). For RT-PCRs, primers were used that amplify cDNA of 200–250 bp from internal gene sequences. PCR conditions were 98°C for 5 min, followed by 30 cycles of 95°C for 30 s, 60°C for 30 s, and 72°C for 45 s, and a final cycling step at 72°C for 5 min. As a positive control, cDNA was amplified from the 16S rRNA transcript, which is transcribed constitutively. To exclude DNA contamination, negative controls were carried out by using total RNA as a template for each RT-PCR reaction. At least three independent biological replicates have been tested.

Real-time qPCR analysis was applied for quantitative cDNA determination. PCR reactions were run with SYBR^® Green Supermix (BioRad) on an iQ5 Multicolor Real-Time-PCR Detection System (BioRad). The SYBR^® Green Dye shows increased fluorescence when bound to double-stranded DNA. The fluorescence is measured at 494 and 521 nm and gives the proportional amount of generated dsDNA. cDNA was generated from cultures of SLpGM190 and SLpapR2-OE as described above. The primer pairs redPintfw/rv and redQintfw/rv, respectively (Supplementary Table S1), which amplify fragments of about 180 bp from internal gene sequences, were used together with cDNA as template in qPCR reactions. hrdB was used as housekeeping gene in each experiment in order to standardize the results by eliminating variation in RNA and cDNA quantity and quality. Each reaction mixture of 10 μL volume contained 5 μL SYBR^® Green Supermix (BioRad), 3.85 μL nuclease-free water, 0.2 μL of each primer, and 0.75 μL template. PCR conditions were 98°C for 5 min, followed by 35 cycles of 95°C for 20 s, and 57°C for 30 s. To determine amplification specificity, melting curve analyses were performed after the last cycle, showing in all cases one single peak. Results were analyzed using the ΔΔCT-method (Livak and Schmittgen, 2001). Changes in gene expression are represented in relation to the data from samples of SLpGM190. Data are presented as the results from six independent biological replicates.

FASTA sequences of SARP proteins were extracted from the antiSMASH database version 2 (Blin et al., 2019) by querying for all genes that hit the antiSMASH smCoG (secondary metabolite clusters of orthologous groups) profile SMCOG1041 (transcriptional regulator, SARP family). These hits were checked for the presence of at least one out of four SARP-related profiles from the PFAM database: PF00486.27 (Trans_reg_C, the HTH-style DNA binding domain), PF93704.16 (BTAD, the transcriptional activator), PF00931.22 (NB-ARC, a domain of unknown function found, e.g., in Saccharopolyspora erythraea SARPs), and PF13424.6 (TPR_12, a TPR found in many larger SARPs). Sequences that did not hit at least one of these domains were discarded. Sequences were then annotated by which of the four profiles were hit and grouped by taxonomic order and BCG type.

Streptomyces lividans is a widely used heterologous host strain, which under specific laboratory conditions does not exhibit production of the two pigmented secondary metabolites actinorhodin and undecylprodigiosin (Hu et al., 2002; Martinez et al., 2005; Rodríguez et al., 2013). In frame of analyzing the regulatory role of PapR2 in S. pristinaespiralis, the papR2 gene was heterologously expressed in S. lividans T7 for protein purification purposes (Mast et al., 2015). For overexpression experiments the S. lividans strain SLpapR2-OE was used, which harbors the papR2 gene under control of the thiostrepton-inducible promoter P_tipA on the replicative medium-copy plasmid pGM190 (Mast et al., 2015). S. lividans strain SLpGM190 was used as a reference, containing the pGM190 empty vector. After 2–3 days of growth in YEME liquid medium with thiostrepton as inductor for gene expression, the whole SLpapR2-OE culture, as well as the culture supernatant showed an intensive red pigment formation, which was not observed for samples of SLpGM190 (Figure 1A). This phenomenon was also observed on R5 agar with thiostrepton, where SLpapR2-OE mycelium was intensively red colored after 3–4 days of cultivation, whereas SLpGM190 mycelium was not (Supplementary Figure S1). S. lividans is known to harbor a Red BCG, which remains silent under normal growth conditions (Horinouchi et al., 1986). Red biosynthesis has mainly been studied in S. coelicolor; however, since S. coelicolor and S. lividans are very closely related species, knowledge on Red biosynthesis and regulation can be transferred to S. lividans (van Wezel et al., 2000; Lewis et al., 2010). To investigate, whether the red color of the SLpapR2-OE cultures originates from the formation of the Red metabolite, we performed spectrophotometrical analysis. A pH shift was carried out with the culture supernatant of SLpapR2-OE and the absorption maxima of the sample was determined by using a Hitachi U-2000 spectrophotometer. Spectrophotometrical analysis led to the detection of the Red-specific spectral absorption maxima (Onaka et al., 2002) at 533 and 468 nm under acidic and basic conditions, respectively (Figure 1B), which proved that the SLpapR2-OE samples contained Red (Figure 1C). These data suggested that the overexpression of papR2 in S. lividans induced Red biosynthesis.

In S. lividans Red biosynthesis is under control of the SARP-type regulator RedD, which directly activates the Red biosynthetic genes (Takano et al., 1992; White and Bibb, 1997). An amino acid sequence comparison using BLASTP revealed that PapR2 and RedD are highly similar to each other (44% identity, 55% similarity) (Mast et al., 2015). This amino acid sequence similarity was even higher for the HTH motif of the protein (66% identity, 75% similarity). Thus, we suspected that PapR2 may substitute for the function of RedD and activates Red biosynthesis in S. lividans. In order to identify potential SARP-type binding motifs within the S. lividans Red BGC, the genome was analyzed with the bioinformatic tool PatScan, which allows for the identification of specific sequence patterns in a given genome sequence (Blin et al., 2018). PatScan analysis was performed with the previously described PapR2 consensus motif (5’-GTCAGSS-3’) (Mast et al., 2015) as sequence pattern on the S. lividans genome sequence. Thereby, two highly conserved PapR2-like motifs were identified within the intergenic region of the Red-specific biosynthetic genes redP (SCO5888) and redQ (SCO5887) with each 100 and 96.5% identity, respectively (Figure 2A). redP encodes a 3-ketoacyl-acyl carrier protein synthase, whereas redQ codes for an acyl carrier protein, both of which have been shown to be involved in Red biosynthesis (Mo et al., 2008). To analyze the functionality of the identified SARP motifs, EMSAs were performed with the PapR2 protein and the upstream regions of redP (PredP, 182 bp) and redQ (PredQ, 182 bp), respectively, harboring the PapR2 consensus sequence. EMSAs showed that PapR2 specifically binds to the PredP and PredQ fragment, respectively (Figure 2B), revealing the functionality of the identified SARP-type motifs.

To confirm the regulatory effect of PapR2 on the transcription of the Red BGC, we performed RT-PCR and quantitative qPCR experiments. For these studies SLpapR2-OE, as well as the reference strain SLpGM190 were grown in R5 medium. After 72 h of cultivation samples were harvested for RNA isolation. For each strain six biological replicates were performed. Isolated RNA was used as a template in RT-PCR experiments as a negative control (Figure 3A), whereas cDNA was used together with 16S primers as a positive control (Figure 3B). For red gene-specific transcriptional analysis, isolated RNA was used as template for RT-PCR experiments with the primer pairs redPintfw/rv and redQintfw/rv, which annealed to internal parts of redP and redQ, respectively. The transcriptional analysis revealed that there are stronger signals for the redP and redQ cDNA amplificates in SLpapR2-OE samples compared to SLpGM190 samples (Figures 3C,D, respectively). In order to quantify the amount of redP and redQ RT-qPCR was performed. Based on the threshold cycle it was calculated that redP and redQ transcripts were increased to 57- and 492-fold, respectively, in samples of SLpapR2-OE compared to samples of SLpGM190 (Supplementary Figure S2). Thus, transcriptional analyses demonstrated that PapR2 activates the transcription of the Red biosynthetic genes redP and redQ. Due to the intensive Red production of strain SLpapR2-OE together with the data obtained from PapR2 EMSA studies and transcriptional analysis, we propose that overexpressed PapR2 in S. lividans takes over the regulatory function of RedD and activates the transcription of the Red biosynthetic genes, which leads to the formation of the red colored secondary metabolite Red.

In order to study the general application of SARP-type regulators for activation of antibiotic biosynthesis, we exemplary tested strain SHP22-7 as a host for papR2 expression. SHP22-7 is a novel strain isolate from a soil sample of the unique desert island Enggano, Indonesia (Handayani et al., 2018). SHP22-7 shows broad-spectrum antibacterial activity against Gram-positive and Gram-negative bacteria, including E. coli, Staphylococcus carnosus, Micrococcus luteus, and B. subtilis. The SHP22-7 genome has been sequenced recently and antiSMASH analysis led to the identification of 25 potential secondary metabolite gene clusters (Handayani et al., 2018; Table 1). Four of the gene clusters (clusters 3, 6, 10, and 15) contain SARP genes, which makes SHP22-7 a good candidate strain for a SARP-guided activation. For papR2 expression studies in SHP22-7, the papR2 gene was cloned into the integrative plasmid pRM4 under control of the constitutive ermE^∗ promoter, resulting in construct pRM4/papR2. The pRM4 vector was used as expression plasmid in these analyses to avoid addition of thiostrepton as inductor (see above), which would influence subsequent antibacterial bioassays. The plasmid was transferred to SHP22-7 by protoplast transformation. The resulting expression strain SHP22-7papR2-OE, as well as the two reference strains SHP22-7pRM4, which harbors the empty pRM4 vector, and the SHP22-7 wild-type (WT) were used for antibacterial bioassay studies. SHP22-7papR2-OE, SHP22-7pRM4, and SHP22-7 WT were each cultivated in NL19 medium and samples were taken at 168 h. Methanolic culture extracts were applied for antibacterial bioassays using B. subtilis as test organism. Filter discs with kanamycin and methanol served as positive and negative control, respectively. Bioassays were carried out as 10 independent biological replicates. Thereby, significantly larger inhibition zones against B. subtilis were observed on average with extracts from SHP22-7papR2-OE compared to extracts from SHP22-7pRM4 or SHP22-7 WT (Figure 4A). The extract of SHP22-7papR2-OE caused a zone of inhibition of 11.7 ± 2.1 mm, whereas the extracts of SHP22-7pRM4 and SHP22-7 WT yielded smaller inhibitions zones of 8.3 ± 2.6 and 7.3 ± 2.7 mm, respectively (Figure 4B). These data showed that papR2 expression in SHP22-7 leads to a significantly improved antibiotic activity.

To identify the substance that is responsible for the antibiotic activity of SHP22-7 but avoid elaborative chemical analytics in the first place, we screened the SHP22-7 genome sequence for the occurrence of PapR2-like consensus sequences by using the PatScan tool. Here, we only considered motifs that were located within intergenic regions of genes from suggested SHP22-7 BGCs. The motif search led to the identification of PapR2-like consensus sequences within 5 of the 25 predicted BGCs from SHP22-7. These included clusters 6 and 10 (NRPS-like gene cluster), cluster 15 (type 2 PKS-butyrolactone-like gene cluster), as well as clusters 3 and 9 (“other” type of gene cluster) (Table 1). In order to find out which of the five gene clusters is activated by PapR2, comparative RT-PCR analysis was carried out with SHP22-7papR2-OE, SHP22-7pRM4, and SHP22-7 WT in four independent biological replicates. Cells were grown under antibiotic production conditions and samples were harvested at 168 h of cultivation. Two samples were collected for each strain and growth time point, whereby one sample was used for RT-PCR analysis and the second one for HPLC–MS analysis (see the section “SARP-Type Regulatory Genes Are Widespread in BGCs From Diverse Actinobacteria”). RT-PCR was carried out with RNA isolated from cell pellets of SHP22-7papR2-OE, SHP22-7pRM4, and SHP22-7 WT, respectively. Isolated RNA was used as a template in RT-PCR experiments as a negative control (Figure 5A), whereas cDNA was used together with 16S primers as a positive control (Figure 5B). For cluster specific transcriptional analysis, cDNA was generated with primer pairs cl3fw/rv, cl6fw/rv, cl9fw/rv, cl10fw/rv, and cl15fw/rv (Supplementary Table S1), each aligning to a predicted biosynthesis gene of clusters 3, 6, 9, 10, and 15, respectively. The transcriptional analysis revealed that there is a stronger signal for the cluster 9 amplificate in the SHP22-7papR2-OE samples compared to the samples of SHP22-7pRM4 and SHP22-7 WT, where there is nearly no signal at all (Figure 5C). This difference in signal intensity could not be observed for clusters 3, 6, 10, and 15 (Figure 5C). Thus, these data suggested that PapR2 activates the transcription of cluster 9 in SHP22-7papR2-OE.

In order to deduce for what type of metabolite cluster 9 encodes for, we analyzed the cluster sequence region in detail. The antiSMASH output predicted a 75% similarity of cluster 9 to the plicacetin/amicetin gene cluster from Streptomyces vinaceusdrappus NRRL 2363 (Table 1). The cluster similarity describes the number of genes with a similarity above the ClusterBlast threshold of 30% sequence similarity at over 25% coverage. Manually cluster analysis by sequence alignments yielded a 100% sequence similarity since the sequence region from amiA–amiD was not recognized by antiSMASH to be part of the amicetin BGC (Figures 6A vs. B). Plicacetin (Figure 6C) and amicetin (Figure 6D) are disaccharide pyrimidine nucleoside antibiotics with a broad-spectrum antibacterial (especially against Mycobacterium tuberculosis) and antiviral activity. They act as peptidyl transferase inhibitors and thus inhibit protein synthesis. Amicetin consists of the two deoxysugar moieties, D-amosamine and D-amicetose, as well as cytosine, p-aminobenzoic acid (PABA), and a terminal methylserine moiety, whereby the latter moiety is missing in plicacetin (Zhang G.G. et al., 2012; Korzybski et al., 2013). The gene cluster analysis of SHP22-7 revealed that the PapR2-like motif is located directly in front of the orf pliA (Figure 6B) and shows a rather weak sequence identity of 65.5% to the PapR2 consensus motif (Figure 2A). The same motif is present upstream of amiA in S. vinaceusdrappus. The pliA gene presents 99.75% gene nucleotide sequence identity to amiA of S. vinaceusdrappus, which translates to a 100% amino acid sequence identity among the predicted gene products. In S. vinaceusdrappus amiA is the first gene of the amicetin BCG and encodes a putative 4-amino-4-deoxychorismate lyase, which is suggested to catalyze the conversion from 4-amino-4-deoxychorismate to PABA (Zhang G.G. et al., 2012). Remarkably, all genes in the amicetin gene cluster of S. vinaceusdrappus and the amicetin-like gene cluster of SHP22-7 are organized in one direction, suggesting a unidirectional transcription. In this context, it would make sense that regulatory activation targets the promoter of the first gene of the unidirectional BGC. In order to find out if PapR2 can bind to the pliA promoter region, EMSAs were performed with the PapR2 protein and the pliA upstream region containing the PapR2 consensus sequence. However, no shifted band was detected in these assays (data not shown). Thus, it might be that the motif is not functional at all and does not constitute a SARP binding motif. It could also be that due to the less conserved PapR2 consensus sequence, the motif is not functional in such an in vitro assay. The presence of a SARP consensus sequence would hint for a pathway-specific regulatory gene located within the amicetin(-like) BGC. However, a SARP-type regulatory gene has not been identified in any of the amicetin(-like) clusters from SHP22-7 nor S. vinaceusdrappus (Table 1; Zhang X. et al., 2012). Overall, six SARP genes have been identified in total within the SHP22-7 genome (Supplementary Table S2). All of them are part of BGCs (clusters 3, 6, 10, and 15). Cluster 15 harbors three SARP genes, whereas the other BGCs each contain one SARP gene (Table 1). Furthermore, putative SARP binding motifs have been found within the promoter regions of the BGCs (Table 1 and Supplementary Table S2). It might be possible that one of these SARP-type regulators plays a role in trans-activating amicetin cluster transcription. So far, regulation of amicetin biosynthesis is not understood. In S. vinaceusdrappus three genes [orf(-3), orf(-2), amiP] have been identified, which encode for putative transcriptional regulators, whereby orf(-3) and orf(-2) seem not to be part of the amicetin BGC and amiP codes for TetR-like transcriptional regulator, which usually function as repressors of antibiotic biosynthesis (Zhang G.G. et al., 2012). Thus far, it cannot be excluded that also trans-acting regulator(s) are involved in the regulation of amicetin biosynthesis.

To investigate if an amicetin(-like) antibiotic is produced by SHP22-7, we analyzed methanolic extracts of cell culture samples from SHP22-7papR2-OE by HPLC/MS. To analyze if production is influenced by papR2 expression, extracts from samples of SHP22-7pRM4 and SHP22-7 WT served as references. For these analyses we used the second culture samples obtained from SHP22-7papR2-OE, SHP22-7pRM4, and SHP22-7 WT, respectively (see above). Based on comparisons with an in-house substance database, HPLC analysis revealed the presence of amicetin [retention time (RT) 4.0 min], plicacetin (RT 4.8 min), and a plicacetin isomer (RT 5.6 min) in all three samples (Figure 7A). The identity of the compounds was verified by MS/MS analysis (amicetin m/z 617.1 [M−H]; plicacetin m/z 516.1 [M−H]; plicacetin isomer m/z 516.1 [M−H]) (Figure 7B; for HRMS data see Supplementary Figures S3, S4). Comparisons between the HPLC spectra from samples of SHP22-7papR2-OE, SHP22-7pRM4, and SHP22-7 WT displayed that peak intensities were especially increased for plicacetin (mAU 605) and the plicacetin isomer (mAU 259) in samples of SHP22-7papR2-OE compared to samples of SHP22-7pRM4 [plicacetin (mAU 120), plicacetin isomer (mAU 97)] and SHP22-7 WT [plicacetin (mAU 66), plicacetin isomer (mAU 57)] (Figure 7C). Thus, it could be shown that papR2 expression in SHP22-7 activates explicitly plicacetin biosynthesis, whereas amicetin biosynthesis seems not to be affected. Overall, with this result it could be confirmed that PapR2 induced cluster 9 transcription, which resulted in an increased plicacetin production. Thus, it can be concluded that the increased bioactivity of SHP22-7papR2-OE samples against B. subtilis arises from the increased production of the nucleoside antibiotic plicacetin. However, since no direct interaction of the PapR2 regulator with the amicetin promoter region could be shown by EMSA analysis, it cannot be deduced if the activation effect is a direct or an indirect one. The SARP consensus motif harbors the central TCA triad, which is also present in the Pho box (GTTCACC), resembling the target site of the phosphate control two-component system PhoP/PhoR (Martin and Liras, 2020). This sequence region is also known to be bound by the large size SARP regulator AfsR (Martin and Liras, 2020). Additionally, the central TCA triad can be present in binding motifs recognized by the nitrogen regulator GlnR or the DmdR1 (Flores and Martín, 2004; Martin and Liras, 2020). Cross-talk between different transcriptional regulators via the interaction of the same binding sites have been shown before (Martín et al., 2011; Martin and Liras, 2020). Thus, it is also possible that transcriptional activation of the amicetin BGC is an effect from multiple regulatory interactions.

Of the top 10 genera containing SARP-type regulators in the antiSMASH database 2 (Blin et al., 2019), 9 belong to the phylum Actinobacteria. Broken up by genus, 98% of Streptomyces (611/625), 81% of Nocardia (78/96), 100% of Salinispora (72/72), 100% of Micromonospora (62/62), and 97% of Amycolatopsis (38/39) genomes harbor SARP-type regulatory genes, showing their prevalence in filamentous Actinobacteria. On the other hand, only 42% of Mycobacterium (115/276) species have SARP-type regulators. Outside of Actinobacteria, mainly Proteobacteria have hits for the SMCOG1041 profile, but mostly lack hits for the HTH motif domain or the BTAD (transcriptional activator domain) [e.g., 6% (79/1236) of Pseudomonas hit the smCoG profile, but none of them contain a BTAD match]. Thus, SMCOG1041 profiles from Proteobacteria may not represent typical SARP-type regulators.

Of the total of 6525 proteins containing a hit against any of the four SARP-related PFAM domains, 3289 (50%) are from the order Streptomycetales (Figure 8). These again break down into 47% “small” SARPs (only containing the HTH and BTAD domains) and 36% “large” SARPs (also containing the NB-ARC and/or TPR domains). The remaining proteins miss the HTH and/or BTAD domains, likely an artifact of bad sequencing data in published draft genomes. The overrepresentation of SARP-type regulators in Streptomycetales may also be explained by the higher abundance of available genomes in the database. Pseudonocardiales cover 17% of the SARP-type proteins (1080/6525). 31% (330/1080) are “small” SARPs and 39% (421/1080) “large” SARPs. In Micromonosporales, accounting for 13% (822/6526) of the dataset, 30% (244/822) are “small” SARPs, and 40% (330/822) are “large” SARPs (Figure 8). Interestingly, Micromonosporales is the only order to contain a significant amount (22%, 184/882) of SARP-type proteins only containing a hit against BTAD without hitting the HTH domain, suggesting a different subfamily of transcriptional activator. Furthermore, SARP genes were found to be present in various different types of BGCs with a prominent abundance in NRPS and PKS gene clusters (Figure 9), which however might also be associated with the higher frequency of these cluster types in the database.