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J Bacteriol. Aug 2009; 191(15): 4896–4904.
Published online May 22, 2009. doi:  10.1128/JB.00087-09
PMCID: PMC2715712

Identification and Gene Disruption of Small Noncoding RNAs in Streptomyces griseus[down-pointing small open triangle]

Abstract

Small noncoding RNAs (sRNAs) have been shown to control diverse cellular processes in prokaryotes. To identify and characterize novel bacterial sRNAs, a gram-positive, soil-inhabiting, filamentous bacterium, Streptomyces griseus, was examined, on the assumption that Streptomyces should express sRNAs as important regulators of morphological and physiological differentiation. By bioinformatics investigation, 54 sRNA candidates, which were encoded on intergenic regions of the S. griseus chromosome and were highly conserved in those of both Streptomyces coelicolor A3(2) and Streptomyces avermitilis, were selected. Of these 54 sRNA candidates, 17 transcripts were detected by Northern blot analysis of the total RNAs isolated from cells grown on solid medium. Then, the direction of transcription of each sRNA candidate gene was determined by S1 nuclease mapping, followed by exclusion of four sRNA candidates that were considered riboswitches of their downstream open reading frames (ORFs). Finally, a further sRNA candidate was excluded because it was cotranscribed with the upstream ORF determined by reverse transcription-PCR. Thus, 12 sRNAs ranging in size from 40 to 300 nucleotides were identified in S. griseus. Seven of them were apparently transcribed in a growth phase-dependent manner. Furthermore, of the 12 sRNAs, the expression profiles of 7 were significantly influenced by a mutation of adpA, which encodes the central transcriptional regulator of the A-factor regulatory cascade involved in both morphological differentiation and secondary metabolism in S. griseus. However, disruption of all 12 sRNA genes showed no detectable phenotypic changes; all the disruptants grew and formed aerial mycelium and spores with the same time course as the wild-type strain on various media and produced streptomycin similarly to the wild-type strain.

Over the past few decades, a great deal of effort has been made to study small noncoding RNAs (sRNAs) in prokaryotic organisms (30, 31, 32). It is evident that sRNAs control a wide variety of cellular processes, including stress responses (1, 18, 26) and virulence (10, 15, 25). Many bacterial sRNAs characterized to date act as posttranscriptional regulators of gene expression by forming duplexes with 5′ untranslated regions of target mRNAs. This duplex formation leads to modulation of mRNA stability and access to the translational machinery (24). The sRNA-mediated gene regulation is a widely conserved mechanism for many bacterial species. Although many studies have examined the functional analysis of bacterial sRNAs, the main focus appears to be limited to gammaproteobacteria and certain other microorganisms. This tendency led to the characterization of sRNAs involved mainly in stress responses and virulence, and therefore, the abundance and functional roles of sRNAs across bacteria has not yet been fully elucidated.

Members of the gram-positive, soil-dwelling, filamentous bacterial genus Streptomyces, belonging to the Actinobacteria, are characterized by their complex morphological differentiation, resembling that of filamentous fungi, and by their ability to produce a wide variety of secondary metabolites, including many antibiotics. Spores of Streptomyces germinate to form a branched, multinucleoid substrate mycelium, which grows by hyphal-tip extension and then produces an aerial mycelium. After septa have been formed at regular intervals along the aerial hyphae, long chains of uninucleoid spores are formed. Secondary-metabolite production is often genetically coupled with morphological development and is sometimes called physiological differentiation. Although many studies have examined regulatory networks of the morphological and physiological differentiation in Streptomyces, especially in Streptomyces coelicolor A3(2) and Streptomyces griseus, many of the components of these complex networks have yet to be identified. Their complex life cycle, including both morphological and physiological differentiation, and their large genome sizes (approximately 9 Mb) suggest the existence of numerous novel sRNAs with important regulatory functions in Streptomyces species. However, very little is known about the functions of sRNAs in Streptomyces. The complete genome sequences of several species of Actinobacteria, including two Streptomyces species, S. coelicolor A3(2) (3) and Streptomyces avermitilis (11), facilitated bioinformatics prediction of candidate regions for sRNAs in Streptomyces. Recently, two studies (23, 27) reported the identification of sRNAs in S. coelicolor A3(2). Panek et al. (23) predicted 32 potential sRNAs, and the expression of 20 of them was detected by reverse transcription (RT)-PCR and DNA microarray analyses. Swiercz et al. (27) identified nine sRNAs in S. coelicolor A3(2) through a combination of bioinformatics and experimental approaches. However, the biological functions of these sRNAs in S. coelicolor A3(2) remain to be characterized. We started our research project on sRNAs in S. griseus in 2007, when its whole genome sequence had been completed (20).

In S. griseus, both morphological development and secondary metabolism are controlled by a chemical signaling molecule or a microbial hormone, A-factor (2-isocapryloyl-3R- hydroxymethyl-γ-butyrolactone). In our laboratory, we have long studied the A-factor regulatory cascade (7, 8). A-factor binds the A-factor-specific receptor (ArpA) that is bound to the promoter of adpA and dissociates ArpA from the promoter, resulting in induction of adpA transcription (21, 22). The AraC/XylS family transcriptional regulator AdpA then activates the transcription of many genes that are required for morphological differentiation and secondary metabolism, forming an AdpA regulon (19). Thus, S. griseus uses A-factor as a hormonal regulator at an upper stage in the regulatory hierarchy of secondary metabolism and morphogenesis. We assume that some sRNAs may be involved in the A-factor regulatory cascade in S. griseus.

Here, we describe the identification of 12 sRNAs, which were encoded on intergenic regions (IGRs) of the S. griseus chromosome and were highly conserved in both S. coelicolor A3(2) and S. avermitilis. The 12 sRNAs were expressed in the S. griseus wild-type strain grown on solid medium under the usual conditions. Seven of them were apparently transcribed in a growth phase-dependent manner. Of the 12 sRNAs, the expression profiles of 7 were significantly influenced by a mutation of adpA. However, AdpA seemed to control these sRNAs indirectly. To investigate the in vivo functions of the sRNAs, we deleted each of the 12 sRNA genes on the S. griseus chromosome and compared the phenotypes of the sRNA disruptants with those of the wild-type strain under several standard conditions. To our knowledge, this work is the first functional analysis of sRNAs in Streptomyces, although no detectable phenotypic changes were observed in any of the 12 sRNA disruptants under normal laboratory conditions.

MATERIALS AND METHODS

Bacterial strains and media.

S. griseus IFO13350 (NBRC102592) was obtained from the Institute of Fermentation (Osaka, Japan). The S. griseus ΔadpA mutant was described previously (21). Streptomyces strains were grown in YMPD medium (0.2% yeast extract [Difco], 0.2% meat extract [Kyokuto], 0.4% Bacto peptone [Difco], 0.5% NaCl, 0.2% MgSO4·7H2O, and 1% glucose [pH 7.2]). YMPD agar contained 2.2% agar. R2YE medium (13) was used for the regeneration of protoplasts. Bennett agar without glucose and SMM agar containing 2.5 mM KH2PO4 (6) were also used. Neomycin (20 μg/ml) was added when necessary. Escherichia coli JM109 and the vector pUC19 for DNA manipulation were purchased from Takara Biochemicals. E. coli JM110 containing dam and dcm mutations was used for preparing nonmethylated Streptomyces DNA for gene disruption. Histidine-tagged AdpA was purified from E. coli BL21(DE3) harboring pET-adpA as described previously (35). The media and growth conditions for E. coli were described by Maniatis et al. (17). Ampicillin (50 μg/ml) and kanamycin (50 μg/ml) were used when necessary.

General recombinant DNA studies.

Restriction enzymes, T4 DNA ligase, and other DNA-modifying enzymes were purchased from Takara Biochemicals. [α-32P]dCTP (110 TBq/mmol) for DNA labeling with a BcaBest DNA-labeling system (Takara Biochemicals) and [γ-32P]ATP (220 TBq/mmol) for end labeling at the 5′ ends with T4 polynucleotide kinase were purchased from Perkin-Elmer. DNA was manipulated in Streptomyces (13) and in E. coli (2, 17) as described previously. Nucleotide sequences were determined by the dideoxy chain termination method with a Thermo Sequenase fluorescence-labeled primer cycle-sequencing kit (GE Healthcare).

RNA isolation.

Total RNA was isolated with Isogen (Nippon Gene) from cells grown at 28°C on cellophane on the surface of YMPD agar medium. Isogen is a reagent containing phenol and guanidine thiocyanate. S. griseus cells were disrupted with glass beads in the reagent. Then, chloroform was added to the cell extract, and the mixture was vigorously shaken. After centrifugation, a water phase, which contained total RNA, was collected. RNA was precipitated by isopropanol and treated with DNase I to eliminate contaminating DNA. UV spectroscopy and agarose gel electrophoresis were used to assess the quantity and quality of RNA samples prepared.

Northern blot analysis.

RNA samples (30 μg) were separated on a 7% denaturing polyacrylamide gel and transferred to a Biodyne nylon membrane (Pall Life Sciences) using a semidry transfer cell (Nihon Eido) at 20 V for 50 min. The RNA was cross-linked to the membrane by UV. Probes, which almost covered the entire conserved regions (Table (Table1),1), were amplified by PCR using an appropriate set of primers and labeled using the BcaBest DNA-labeling system with [α-32P]dCTP and random primers. All PCR primers used in this study are listed in Table S2 in the supplemental material. The probes were hybridized with the membrane at 42°C overnight. The membrane was washed twice with 2× SSC (1× SSC is 0.15 M NaCl plus 0.015 M sodium citrate) containing 0.1% sodium dodecyl sulfate for 10 min, followed by a single wash with 0.2× SSC containing 0.1% sodium dodecyl sulfate for 10 min. Signals were detected and quantified using the Bio-Rad PhosphorImager FX and QuantityOne software.

TABLE 1.
IGRs examined by Northern blot analysis

Gel mobility shift assay.

Purification of histidine-tagged AdpA from E. coli BL21(DE3) and the gel mobility shift assay were described previously (35). The DNA fragments used for 32P-labeled probes were amplified by PCR and 32P labeled with T4 polynucleotide kinase. Probes were designed for each putative sRNA coding sequence and its upstream region.

S1 nuclease mapping.

S1 nuclease mapping was performed by a method described by Bibb et al. (4) and Kelemen et al. (12). Hybridization probes were prepared by PCR with a pair of 32P-labeled and unlabeled primers. hrdB, encoding a principal sigma factor of RNA polymerase, was used to check the purity and amount of RNA used, as described previously (21).

5′ and 3′ RACE.

Mapping of 5′ and 3′ ends was carried out using a Full RACE Core set (Takara Biochemicals), according to the manufacturer's instructions. In the 3′ rapid amplification of cDNA ends (RACE), total RNA was treated with poly(A) polymerase for the RT, using a poly(T) primer. The PCR products were cloned into pUC19 and sequenced.

RT-PCR.

RT-PCR was performed with 3 μg of RNA, 2 pmol of random primers, SuperScript II reverse transcriptase, and RNase H (Invitrogen) according to the manufacturer's instructions. The PCR cycling conditions were 98°C for 10 s, 60°C for 30 s, and 72°C for 60 s. A total of 25 cycles (for sgs2672, sgs2746, sgs3323, sgs3618, sgs4453, sgs4581, sgs5362, sgs5676, sgs6100, and sgs6109) or 30 cycles (sgs3903 and sgs4827) were executed.

Gene disruption.

Except for sgs3323, the start and endpoints of which were determined by RACE experiments, sRNA coding sequences were estimated by Northern blot analysis and low-resolution S1 nuclease mapping. To generate an sRNA disruptant, all or most of the putative sRNA coding sequence was deleted from the chromosome of S. griseus. Approximately 2-kb sequences of each of the upstream and downstream regions of an sRNA coding region were assembled in pUC19, together with the neomycin resistance gene aphII. This plasmid was introduced by protoplast transformation into S. griseus, and neomycin-resistant transformants resulting from a single crossover of the plasmid into the chromosome were first isolated. Neomycin-sensitive colonies, derived after a second crossover in one of the transformants, were candidates for sRNA-disrupted strains. The correct replacement was checked by Southern hybridization using each sRNA and the aphII sequences as 32P-labeled probes.

Streptomycin assay.

The amount of streptomycin produced was measured by a bioassay using Bacillus subtilis ATCC 6633 as an indicator (9).

RESULTS AND DISCUSSION

Comparative genomics and computational prediction of sRNA genes in S. griseus.

The intergenic sequences of the S. griseus chromosome were extracted using annotation information (http://park.itc.u-tokyo.ac.jp/hakko/genome/) and were subjected to a BLAST search against the S. coelicolor A3(2) and S. avermitilis chromosome sequences. We employed the following criteria to extract the conserved sequences in the IGRs of S. griseus: homology to both the S. coelicolor A3(2) and S. avermitilis sequences with E values of less than 1 × 10−10 in the BLAST search. When these criteria were used, 321 IGRs were shown to have a conserved sequence(s). Then, we excluded the replication origin, putative pseudogenes, and sequences encoding tRNA, rRNA, tmRNA, 4.5S RNA, and RNase P RNA. We also excluded regions where conservation was directly adjacent to the flanking open reading frames (ORFs) within 10 bp because they could represent conserved promoters (and operators) and terminators. After these in silico analyses, 129 IGR sequences remained as putative sRNA gene candidates (see Table S1 in the supplemental material). Because the lengths of sRNAs in prokaryotes are generally 40 to 500 nucleotides (nt) (33) and promoter sequences of the conserved sRNA genes seem to also be conserved among the three Streptomyces species, the sequence similarity of a conserved sRNA gene was expected to extend over at least 80 nt. We therefore eliminated a further 75 of the candidate sequences in which the homology was less than 80 nt. The remaining 54 sequences probably did not encode any peptides because they usually contained no translational start and/or termination codons at appropriate positions. A flowchart of the in silico analyses, as well as the experimental analyses, for identification of S. griseus sRNAs in this study is shown in Fig. Fig.1A1A.

FIG. 1.
Outline of the procedures used in this study. (A) Flowchart of the procedures for identifying sRNA genes. Each step is shown on the left, and the number of sRNA candidates selected in each step is given on the right. (B) Schematic representation of the ...

Experimental identification of sRNAs in S. griseus.

Northern blot hybridization was employed for detecting the 54 putative sRNA candidates. Total RNAs were isolated from S. griseus cells grown on a nutrient-rich YMPD agar at 28°C for 24, 48, and 72 h. This time course fully covered S. griseus' morphological development; the wild-type strain grew as substrate mycelium at 24 h, as a mixture of substrate and aerial mycelium at 48 h, and as a mixture of substrate mycelium and aerial hyphae with spores at 72 h. A 32P-labeled DNA probe (Table (Table1)1) was prepared for both strands of a highly conserved region of each IGR in a total of 54 candidates (Fig. (Fig.1B).1B). As shown in Fig. Fig.2,2, we detected transcripts from 17 sRNA candidate genes by Northern blotting using these DNA probes. Note that the intensities of signals were different from probe to probe and that each panel shows an image analyzed under different conditions. We designated the putative sRNAs “sgs” for S. griseus sRNA, followed by the annotated gene number of the right adjacent ORF. In most cases, the size of the RNA molecule detected was roughly in agreement with the prediction according to the length of the conserved sequences. The hybridization bands with appropriate sizes are indicated in Fig. Fig.2.2. However, the sizes of several RNA molecules were larger or smaller than the predicted sizes. We describe the start and endpoints of the transcripts and discuss the sizes of the putative sRNAs below. The remaining 37 sRNA candidate genes were presumably transcribed at extremely low levels or not transcribed at all under the conditions used in this study.

FIG. 2.
Experimental verification of predicted sRNAs by Northern blot analysis. Shown are Northern blots hybridized with 32P-labeled DNA probes. RNA was prepared from cells grown at 28°C on cellophane on the surface of YMPD agar for the times indicated ...

In the Northern blot analysis using both strands as the 32P-labeled probe, we were not able to discriminate which strands were actually transcribed from the conserved sequences. Therefore, we next performed low-resolution S1 nuclease mapping to determine the directions of the 17 transcripts that were detected by the Northern blotting. We used two hybridization probes, one of which was 32P labeled at the 5′ end of the sense strand while the other was 32P labeled at the 5′ end of the antisense strand (Fig. (Fig.1B).1B). Either 32P-labeled probe could hybridize with the putative sRNA and be detected as a protected fragment from S1 nuclease digestion (see Fig. Fig.5),5), showing an approximate transcriptional start point and the direction of the transcript. By this analysis, we were able to determine the directions of the 17 transcripts shown in Table Table1.1. After this step, four sRNA candidates, sgs2045, sgs3965, sgs6089, and sgs6151, were excluded (Fig. (Fig.1A);1A); they were regarded as riboswitches (28) for the downstream ORFs in the same direction, SGR2045, SGR3965, SGR6089 and SGR6151, respectively, by their homology to the known riboswitches, glycine riboswitch (sgs2045 and sgs6151) and flavin mononucleotide (FMN) riboswitch (sgs6089), and by several lines of circumstantial evidence (sgs3965). Transcription of SGR2045 and SGR6151, both of which encode components of the glycine cleavage system (14), was activated by glycine via the glycine riboswitches (16) in front of both genes (our unpublished data). In the glycine riboswitch system, transcription of the target gene is prematurely terminated in the absence of glycine (16). SGR6089, encoding a putative riboflavin deaminase, essential for FMN biosynthesis, appears to be regulated by the FMN riboswitch (34). SGR3965, encoding a putative thiosulfate-sulfur transferase, essential for cysteine biosynthesis (5), also seemed to be regulated by a riboswitch (our unpublished data). Presumably, we detected the premature transcripts, which were prevented from elongation by the riboswitches, as suggested in the glycine riboswitch system (16), in our Northern blotting and S1 nuclease mapping.

FIG. 5.
Time course of sRNA transcription determined by low-resolution S1 nuclease mapping. RNA was prepared from the wild-type (wt) and the ΔadpA mutant strains grown at 28°C on cellophane on the surface of YMPD agar for the times indicated above ...

Of the remaining 13 sRNA candidate genes (Fig. (Fig.1A),1A), sgs3072 was oriented in the opposite direction from the two flanking ORFs, indicating that this putative sRNA gene should be transcribed independently of the flanking ORFs. Therefore, we examined whether the 12 remaining putative sRNA genes could be cotranscribed with upstream and/or downstream ORFs by RT-PCR (Fig. (Fig.33 and and1B).1B). As illustrated in Fig. Fig.3A,3A, five putative sRNA genes were oriented in the same direction as the upstream ORFs and in the opposite direction from the downstream ORFs. We attempted to amplify three regions using the cDNA library prepared by random primers in RT reactions as a template: an internal region of the upstream ORF, a region covering the 3′ portion of the ORF and the 5′ portion of the sRNA gene, and an internal region of the sRNA gene (Fig. (Fig.3A).3A). In contrast, two putative sRNA genes were oriented in the same direction as the downstream ORFs and in the opposite direction from the upstream ORFs (Fig. (Fig.3B),3B), and five putative sRNA genes were oriented in the same direction as both the upstream and downstream ORFs (Fig. (Fig.3C).3C). Similarly, we attempted to amplify several regions shown in Fig. 3B and C by RT-PCR. As a result, we confirmed that 11 putative sRNA genes, with the exception of sgs4827, were transcribed independently of the flanking ORFs; no amplification of the intervening region between the putative sRNA gene and the adjacent ORF was detected (Fig. (Fig.3).3). In contrast, a region covering the 3′ portion of SGR4826 and the 5′ portion of sgs4827 was amplified by the RT-PCR analysis, indicating that sgs4827 was cotranscribed from the upstream ORF (SGR4826) and that a processed product of the SGR4826 transcript with a long 3′ untranslated region was detected in the Northern blotting and S1 nuclease mapping. Although we did not rule out the possibilities that sgs4827 had its own promoter and that sgs4827 encoded an sRNA that was cotranscribed with SGR4826, we excluded sgs4827 from the sRNA species. Hence, we experimentally identified 12 sRNAs in S. griseus (Fig. (Fig.1A1A).

FIG. 3.
RT-PCR experiment to confirm the transcriptional unit of identified sRNAs. RNA prepared from wild-type cells grown at 28°C for 72 h on YMPD agar was used for the RT reaction, using random primers to synthesize a cDNA library. The gene organizations ...

Transcriptional start and endpoints of sRNA genes.

As described above, low-resolution S1 nuclease mapping revealed the approximate transcriptional start points (±5 nt) of the 12 sRNAs (Table (Table2).2). Furthermore, we estimated the approximate transcriptional endpoints of the 12 sRNAs (Table (Table2)2) from the putative transcriptional start points determined by S1 nuclease mapping and the lengths of the sRNAs as determined by Northern blotting. Because estimating the lengths of sRNAs by Northern blotting may have an error of ±10%, the estimated transcriptional endpoints are less accurate than the estimated transcriptional start points.

TABLE 2.
Experimentally detected sRNAs

In most cases, the estimated transcriptional start and endpoints were located around the 3′ and 5′ ends of the conserved IGR sequences (Table (Table2).2). However, in some cases, the estimated transcriptional start and/or endpoints were located inside or outside of the conserved IGR sequences, which caused the appearance of longer or shorter (indicated in Fig. Fig.2)2) sRNAs than predicted. For example, the estimated transcriptional start and endpoints of sgs6109 were located approximately 140 nt upstream from the 5′ end and 60 nt downstream from the 3′ end, respectively, of the conserved IGR sequence, indicating that sgs6109 contained large nonconserved 5′ and 3′ extensions. In some cases, larger and/or smaller RNA molecules, in addition to the predicted sRNAs, were detected, although the amount of the former was much smaller than that of the latter.

Two protected fragments were detected in sgs4453 by S1 nuclease mapping. Two RNA species were also detected in sgs4453 by Northern blotting. Both RNA species seemed to have the same transcriptional end, as judged from their lengths and the 5′-end positions determined by S1 nuclease mapping. These results suggest two possibilities: sgs4453 has two different promoters, or posttranscriptional processing yields the short fragment.

Using 5′ and 3′ RACE, we determined the precise start and endpoints of sgs3323, the most abundant sRNA detected in this study, showing that sgs3323 was 229 nt in length (Table (Table2).2). The precise start and endpoints of sgs3323 were in good agreement with those estimated by S1 nuclease mapping and Northern blotting, suggesting that our estimation of start and endpoints of the sRNAs was appropriate. We predicted a secondary structure of sgs3323 (Fig. (Fig.4)4) by using the MFOLD program (36). A stem-loop structure, probably acting as a putative transcriptional terminator, was predicted near the 3′-end region. Several stem-loop structures may facilitate the high stability of sgs3323.

FIG. 4.
Predicted secondary structure of sgs3323. The precise transcriptional start and endpoints of sgs3323 were determined by the RACE experiments, showing that the sRNA was 229 nt (Table (Table2).2). The sgs3323 structure was predicted with the MFOLD ...

Expression profiles of sRNAs in the wild-type and an adpA-disrupted strains.

The Northern blotting and S1 mapping were performed using RNAs extracted from the wild-type S. griseus strain grown for 24, 48, and 72 h on solid medium to investigate the temporal changes in sRNA expression. 5S rRNA and the hrdB gene, which were transcribed throughout growth, were used as internal controls to check the integrity and amount of RNA used in Northern blotting and S1 mapping, respectively (Fig. (Fig.22 and and5).5). The expression profiles of sRNAs analyzed by the two methods were generally identical. Transcription of sgs3323, sgs4581, sgs5676, and sgs6109 was detected at all the time points at a rather constant level. In contrast, transcription of sgs2672, sgs2746, sgs3072, sgs3618, sgs4453, and sgs6100 was apparently enhanced in the later growth stages, although the timing and degree of the enhancement varied. Transcription of sgs3903 diminished as the morphological development proceeded. The expression profile of sgs5362 was unique; it was transcribed throughout growth, but most actively at 48 h. The growth phase-dependent expression of these sRNAs suggested their possible involvement in the morphological and physiological differentiation of S. griseus.

We next examined the expression of sRNAs in an adpA-disrupted (ΔadpA) strain, which is deficient in morphological and physiological differentiation, by S1 nuclease mapping (Fig. (Fig.5).5). Total RNA was isolated from the ΔadpA mutant grown for 24, 48, and 72 h on solid medium. The ΔadpA mutant grew as substrate mycelium throughout the time course. The adpA deletion did not have a significant effect on the transcription of sgs2672, sgs3323, sgs4581, or sgs5676 but did affect the transcription of the remaining eight sRNAs to various degrees. In the ΔadpA mutant, transcription of sgs3072 and sgs3903 was completely lost; transcription of sgs2746, sgs3618, and sgs6109 was greatly reduced; and transcription of sgs6100 was reduced to some extent. In other cases, the effect of the adpA deletion appeared only at some specific time points; transcription of sgs4453 and sgs5362 in the ΔadpA mutant was rather similar to that of the wild-type strain until 48 h but was completely lost at 72 h. Thus, we showed that the expression profiles of at least seven sRNAs (sgs2746, sgs3072, sgs3618, sgs3903, sgs4453, sgs5362, and sgs6109) were markedly influenced by the adpA deletion. We examined AdpA binding to the upstream regions of five sRNA genes (sgs2746, sgs3072, sgs3618, sgs3903, and sgs6109), transcription of which was completely lost or greatly reduced in the ΔadpA mutant, via a gel mobility shift assay using a recombinant histidine-tagged AdpA protein purified from E. coli. None of the probes tested in this assay gave a retarded signal (data not shown), indicating that AdpA indirectly activated the transcription of these sRNAs. Although the molecular mechanism of the transcriptional activation of these sRNA genes in the wild-type strain is unknown, no or very weak transcription of them in the differentiation-deficient mutant further suggests their possible involvement in the morphological and physiological differentiation of S. griseus. Moreover, developmental mutations (bld and whi mutations) were reported to exert various effects on the expression of several sRNAs in S. coelicolor A3(2) (27), while their in vivo functions remain to be characterized.

Functional analysis of the identified sRNAs.

To investigate the in vivo functions of the identified sRNAs, each sRNA gene was disrupted. We deleted all or most of the sRNA sequence without inserting a marker gene to avoid possible polar effects on the expression of the flanking ORFs (Fig. (Fig.1B;1B; Table Table22 shows each deleted region). The correct disruption of each sRNA was checked by Southern hybridization with appropriate probes (data not shown).

First, mutants with sRNA deleted (Δsgs) were incubated at 28°C on various media. The media used here were YMPD, R2YE, SMM, and Bennett agars. No difference was observed in morphological differentiation between the wild type and the 12 Δsgs mutants. Second, we examined the ability to produce streptomycin, which is representative of secondary metabolites under the control of A-factor in S. griseus, on Bennett agar without glucose. This medium has been routinely used for streptomycin production assays with B. subtilis as an indicator in our laboratory. However, no difference was observed between the amounts of streptomycin produced by the wild type and the 12 Δsgs mutants. These analyses indicated that mutant Δsgs strains exerted no apparent effect on morphological differentiation or secondary-metabolite formation under the culture conditions tested here. We assume that the sRNAs detected in this study function as a minor tuner, and not as an all-or-none switch, in the regulation of gene expression. The lack of phenotypic changes, however, might be ascribed to functional redundancy of sRNAs in S. griseus. Swiercz et al. (27) noted that three sRNAs appear to be duplicated within the S. coelicolor A3(2) genome. Although we could find no striking similarity between the identified sRNAs, a possibility remains that some sRNAs have the same function because an extremely short portion of sRNA can form a duplex with 5′ untranslated regions of the target mRNA.

Comparison of sRNAs identified in S. griseus and S. coelicolor A3(2).

As mentioned in the introduction, two studies of sRNAs in S. coelicolor A3(2) were reported during our study of sRNA in S. griseus (23, 27). Panek et al. (23) validated the expression of 20 sRNAs by RT-PCR and DNA microarray analyses. Of the 20 sRNAs, only two (identification no. 341 and 472) overlapped with sRNAs detected in this study, sgs3618 and sgs4581, respectively. Although the conserved region for sgs3323 in S. griseus was the same as that for an sRNA (no. 389) in S. coelicolor A3(2), sgs3323 and no. 389 sRNAs were transcribed from the opposite strands, showing that they were different sRNAs. Swiercz et al. (27) identified nine sRNAs in S. coelicolor A3(2) by a combination of bioinformatics and direct-cloning approaches. Of the nine sRNAs, only one, scr3974, overlapped with an sRNA detected in our present study, sgs3618. Thus, only one sRNA (sgs3618, no. 341, or scr3974) was detected in common among the three studies (Fig. (Fig.6B6B).

FIG. 6.
Diagram showing the numbers of putative sRNA genes in the analysis of sRNA in S. griseus and S. coelicolor A3(2). (A) Diagram showing the numbers of putative sRNA genes examined experimentally. We examined the expression of 54 conserved IGR sequences ...

Why do most of the sRNAs detected in the three studies not overlap with one another? The main reason was derived from the difference in the methods of comparative genomic analysis employed in the studies. As shown in Fig. Fig.6A,6A, most of the sRNA candidates predicted by bioinformatics analysis by the three groups did not overlap with one another. Both our study and that of Panek et al. (23) shared only five sRNA candidates, and our study and that of Swiercz et al. (27) shared only four sRNA candidates. Thus, only eight sRNA candidates in S. griseus and S. coelicolor A3(2) were examined in common. Panek et al. (23) predicted sRNA genes based on sequence conservation in IGRs, colocalized transcription terminators, and genomic synteny in the S. coelicolor A3(2) and S. avermitilis genomes. Swiercz et al. (27) conducted a comparative genomics-based search using sequence conservation in other actinomycetes, especially large (>200-nt) IGRs within the conserved core region of the S. coelicolor A3(2) genome. In this study, we used a simple method in which intergenic sequences highly conserved among the three streptomycetes were regarded as sRNA candidates at the starting point. The differences in the criteria of bioinformatics searches resulted in the small number of sRNA candidates that overlapped with one another.

In the eight common candidates, two sRNAs were detected in both S. griseus and S. coelicolor A3(2) (Fig. (Fig.6B).6B). In the remaining six common candidates, one sRNA (sgs2672) was detected only in S. griseus and two sRNAs (scr3045 and no. 676) were detected only in S. coelicolor A3(2). Two different sRNAs (sgs3323 and no. 389) were detected in the two species from the same IGR, as described above. No transcripts were detected in both species from the remaining two sRNA candidate genes. Although the expression profiles of orthologous genes are not necessarily similar between S. griseus and S. coelicolor A3(2), we assumed that the difference in culture conditions resulted in the different expression of the three common sRNA candidate genes: Panek et al. (23) extracted RNA samples from S. coelicolor A3(2) cells grown in a minimal liquid medium (NMMP) and on a nutrient-rich agar (PPS), Swiercz et al. (27) used S. coelicolor A3(2) cells grown on either solid R2YE (rich medium) or minimal medium, and we used S. griseus cells grown on nutrient-rich agar (YMPD). Note that Swiercz et al. (27) showed that several sRNAs were expressed in a medium-dependent manner in S. coelicolor A3(2).

Conclusions.

The bioinformatics approach used in this study produced over 100 IGR sequences, which are highly conserved among S. griseus, S. coelicolor A3(2), and S. avermitilis, as possible sRNA candidate genes. The subsequent experimental screen in S. griseus led us to successfully identify 12 sRNAs (40 to 300 nt) that were transcribed under standard culture conditions. From this study and the two previous reports on sRNA in S. coelicolor A3(2) (23, 27), Streptomyces species express many kinds of sRNAs under normal growth conditions. However, we detected no phenotypic changes in the 12 sRNA disruptants of S. griseus under normal laboratory conditions. Therefore, the in vivo function of sRNA in Streptomyces remains to be elucidated. Overexpression of the sRNA genes identified in this study may give us some clue to reveal their functions. Although S. griseus, as well as S. coelicolor A3(2) (27), has no Hfq-like protein, which is an RNA chaperone important for regulation mediated by sRNA in many bacteria (29), we assume that S. griseus has a novel RNA chaperone equivalent to Hfq. The sRNAs identified in this study can be used as tools for identifying the putative RNA chaperone. In fact, our preliminary in vitro binding assay using the sgs3323 sRNA as a probe suggested the existence of a protein(s) that could bind to the sRNA in S. griseus. The identification and characterization of such an sRNA binding protein may contribute to revealing the function of sRNA in Streptomyces.

Supplementary Material

[Supplemental material]

Acknowledgments

T. Tezuka was supported by the Japan Society for the Promotion of Science. This study was supported by a Grant-in-Aid for Scientific Research on Priority Area “Applied Genomics” from the Ministry of Education, Culture, Sports, Science and Technology of Japan.

Footnotes

[down-pointing small open triangle]Published ahead of print on 22 May 2009.

Supplemental material for this article may be found at http://jb.asm.org/.

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