An Autoregulated Fine-Tuning Strategy for Titer Improvement of

Subscriber access provided by READING UNIV

Article

An autoregulated fine-tuning strategy for titer improvement of secondary metabolites using native promoters in Streptomyces Shanshan Li, Junyang Wang, Wensheng Xiang, Keqian Yang, Zilong Li, and Weishan Wang ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.7b00318 • Publication Date (Web): 31 Oct 2017 Downloaded from http://pubs.acs.org on November 1, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Synthetic Biology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Synthetic Biology

An autoregulated fine-tuning strategy for titer improvement of secondary metabolites using native promoters in Streptomyces Shanshan Li#,†,§, Junyang Wang#,†,‡, Wensheng Xiang§, Keqian Yang†, Zilong Li†,* and Weishan Wang†,* †

State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, No.1 West Beichen Road, Chaoyang District, Beijing 100101, China

§

State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China

‡

University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing 100049, China

#

S. L. and J. W. contributed equally to this work.

* Correspondence: Weishan Wang, E-mail: [email protected]; and Zilong Li, E-mail: [email protected].

1

ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract Streptomycetes are well-known producers of biologically active secondary metabolites. Various efforts have endeavored to increase productions of these metabolites, while few approaches could well coordinate the biosynthesis of secondary metabolites and other physiological events of their hosts. Here we develop a universal autoregulated strategy for fine-tuning the expression of secondary metabolites biosynthetic gene clusters (BGCs) in Streptomyces species. First, inducible promoters were used to control the expression of secondary metabolites BGCs. Then, the optimal induction condition was determined by response surface model in both dimensions of time and strength. Finally, native promoters with similar transcription profile to the inducible promoter under the optimal condition were identified based on time-course transcriptome analyses, and used to replace the inducible promoter following an elaborate replacement approach. The expression of actinorhodin (Act) and heterogeneous oxytetracycline (OTC) BGCs were optimized in Streptomyces coelicolor using this strategy. Compared to modulating the expression via constitutive promoters, our strategy could dramatically improve the titers of Act and OTC by 1.3- and 9.1-fold, respectively. The autoregulated fine-tuning strategy developed here opens a novel route for titer improvement of desired secondary metabolites in Streptomyces. Keywords Streptomyces; Fine-tuning; Autoregulation; Biosynthetic gene cluster; Native

2


Page 2 of 35

Page 3 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


promoter; Inducible promoter Introduction Streptomycetes are the richest known source of antibiotics and other valuable secondary metabolites, which have been applied in human medicine, animal health, as well as plant and crop protection.1, 2 Therefore, titer improvement of desired secondary metabolites in Streptomyces has caught decades of interest in both academia and industry.3-6 A notable nature of secondary metabolites is that they are usually produced in large amounts at stationary phase.7 During the lifetime of a fermentation culture, Streptomyces undergoes a major metabolic switch from exponential growth to secondary metabolites production,8 which is tightly regulated by the finely orchestrated regulation system.9 However, such a natural regulation system serves the purpose of physiological needs of the host,9, 10 rather than the yield improvement goal of metabolic engineering.11 Hence, establishing a general strategy to coordinate the biosynthesis of secondary metabolites and other physiological events within the hosts is a major challenge to optimize the production capability of Streptomyces.7, 12 To increase the production of secondary metabolites, various engineering strategies, such as increase of precursor supply and manipulation of regulatory genes, are often achieved through overexpression or knockout of target genes or pathways in streptomycetes.7, 13, 14 With the emergence of synthetic biology, tuning the expression of biosynthetic gene clusters (BGCs) by means of constitutive promoter libraries or

3



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

different ribosome binding sites has been employed to optimize the production capability of Streptomyces producers.15, 16 These strategies are effective for titer improvement, whereas they give constant modulation of gene expression in the strength level, which cannot temporally coordinate the trade-off between product biosynthesis and other physiological events, and concomitantly bring metabolic burdens to hosts.17-20 To address this issue, we therefore endeavored to develop a universal strategy to fine-tune the expression of secondary metabolites BGCs in Streptomyces. In this work, the expression of secondary metabolites BGCs were fine-tuned by well-characterized constitutive promoters and inducible promoters in different Streptomyces species. We found that inducible promoters were much better for titer improvement, which should be ascribed to their ability of fine-tuning the expression in both time and strength dimensions. Considering the cost and inconvenience caused by adding inducers in scaled-up fermentations, a novel autoregulated strategy independent from inducers was further developed. First, an inducible promoter was employed to control the expression of the target BGCs, and the optimal induction time and strength (dosage of inducer) were determined by means of the response surface model. Then, the native temporal promoters with similar behavior to that of the inducible promoter under the optimal condition were selected through time-course transcriptome analyses. Finally, the selected native temporal promoters were employed to replace the inducible promoter, thus achieving the optimal expression of BGCs without the need of any inducers. Applying this strategy, the expression of 4


Page 4 of 35

Page 5 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


actinorhodin (Act) and heterogeneous oxytetracycline (OTC) BGCs were fine-tuned in Streptomyces coelicolor M145 and M1146, respectively. Titers of Act and OTC were increased by 1.3- and 9.1-fold compared with those of the corresponding strains optimized by constitutive promoters, demonstrating the high efficiency and great potential of this autoregulated strategy for titer improvement in Streptomyces. Results and Discussion Fine-tuning the expression of secondary metabolites BGCs in Streptomyces To explore an appropriate fine-tuning strategy, the well-characterized Act BGC in S. coelicolor M145 was selected as a research target. First, nine constitutive promoters with different strengths15 were employed to control the expression of actII-orf4 gene (Figure S1a), which encodes the pathway-specific activator of Act BGC.21 We observed that the titers of Act did not always keep increasing with the strength of the nine promoters, and promoter SP26 with a moderate strength rather than the strongest gave the highest titer (Figure S2a). To further confirm this phenomenon, the expression of jadomycin B (JdB) BGC in S. venezuelae ATCC 10712 was tuned with these nine constitutive promoters via controlling the expression of jadJ gene, which is the first gene of the co-transcribed JdB BGC.22 The effect of promoter strength on the production of JdB in S. venezuelae was quite similar with that observed in S. coelicolor, the moderate promoter SP18 showed the highest titer (Figure S2b). Both cases indicate that tuning the expression strength of BGCs is quite crucial for titers improvement of desired secondary metabolites in Streptomyces.

5



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

It is known that the biosynthesis of secondary metabolites temporally occurs at the stationary phase in Streptomyces.8 Thus, we hypothesized that, the ″just-in-time″ tuning of the expression of BGCs might be as important as strength tuning. To verify this point, the expression of Act and JdB BGCs were further tuned at both levels by using cumate-inducible promoter23 and oxytetracycline-inducible promoter24 in S. coelicolor (M145-OA) and S. venezuelae (Sv-Potr), respectively. The inducer with gradient dosages were added at different timepoints, which enabled the modulation of BGCs expression in two dimensions of time and strength. As expected, changes of induction conditions remarkably affected the titers of both Act and JdB. The best induction timepoint and dosage were 35 h and 2.5 µM of cumate for Act (Figure 1a), and 7 h and 0.8 µM of OTC for JdB (Figure 1b), respectively. Under these conditions, the titers of Act and JdB increased to 1.6- and 1.5-fold of those controlled by the best tested constitutive promoters, and 3.0- and 2.3-fold of the corresponding parent strains, respectively (Figures 1c, d). These results indicate that optimizing the expression of target BGC in both dimensions of time and strength is a promising strategy to improve the titers of desired secondary metabolites in Streptomyces species. A novel autoregulated strategy for fine-tuning the expression of BGCs While fine-tuning the expression of BGCs by inducible promoters is effective, adding inducers increases the costs in industrial production. To settle this problem, an autoregulated strategy of utilizing qualified native temporal promoters instead of inducible promoters was developed as illustrated in Figure 2. First, the optimal induction condition for production of desired secondary metabolite was determined by 6


Page 6 of 35

Page 7 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


means of an inducible promoter (Figure 2a). Then, under the optimal induction condition, the time-course transcription profiles of global genes were analyzed and the qualified native temporal promoters showing the similar profile to the inducible promoter were identified (Figure 2b). Finally, the qualified native temporal promoters were used to replace the inducible promoter to control the expression of BGCs (Figure 2c). By this way, we could ensure the optimal expression of BGCs in both time and strength dimensions without the need of any inducers. Determination of the optimal induction condition As a proof-of-concept, this autoregulated strategy was used to optimize the expression of Act BGC in S. coelicolor. To get the optimal induction condition of the engineered strain M145-OA, a response surface model-based design was applied. First, single-factor tests were implemented to find out appropriate ranges of induction time and dosage. It was observed that triggering the expression of Act BGC between 20 and 45 h could significantly influence Act production (Figure S3a); meanwhile, Act titer was positively correlated to the induction strength when the concentration of cumate inducer ranged from 0.5 to 2.5 µM (Figure S3b). Thus, these ranges were appropriate for further two-factor two-level central composite design (CCD) design to probe the optimal induction condition. A total of 13 experiments generated from the CCD (Table S1). Quantitative relationship between the 13 induction conditions and Act titers was plotted as a 3D surface with contour plots projected on the x-y plane (Figure 3a), and described by a quadratic response surface model (Table S2). The model predicted that, when M145-OA was induced by 1.8 µM of cumate inducer at 35 7



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

h, titer of Act could reach the peak of 262 mg/L (Figure 3a). Subsequently, this predicted optimal condition was experimentally verified, resulting in the maximal Act titer of 257 mg/L, which was 32% higher than the maximal obtained in orthogonal experiments (Figure 3b). Selection of qualified native temporal promoters To distinguish the transcription profile of actII-orf4 controlled by the inducible promoter from that driven by its natural promoter, the integrated pathway-specific activator gene actII-orf4 driven by cumate-inducible promoter was designed to ″co-transcribe″ with the reporter gene sfgfp in the engineered strain M145-OA (Figure S1a). Theoretically, behavior of the cumate-inducible promoter could be characterized according to the transcription profile of the downstream sfgfp gene. To identify native promoters whose behavior is in consistence with that of the inducible promoter under the optimal induction condition, time-series transcriptome of M145-OA (GEO accession number: GSE100343) was performed at seven timepoints (T1 to T7), covering the exponential, transitional and stationary phase (Figure S4). Through hierarchical clustering, 50 genes with quite similar transcription profile with that of sfgfp gene were selected (Figure 4a). It is well-known that many of the genes in bacterial genomes are organized into operons and co-transcribed under the control of the same promoters.25 Thus, to obtain the promoters of the 50 qualified genes, operons were predicted by ProOpDB.26 Among them, 42 qualified genes were involved in 16 predicted operons, while the remaining eight genes were transcribed

8


Page 8 of 35

Page 9 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


individually. Hence, a total of 24 putative promoters were selected for promoter replacement (Table S3). An elaborate design for promoter replacement To get the intact native promoters, the DNA fragments including about 500 bp upstream and 100 bp downstream sequences of putative translation start site (TSS) of the selected genes were cloned (Figure 4b), as functional regions of a native promoter is usually less than 600 bp sequence.27 Hence, the cloned sequence could assure the consistency of promoter behaviors when applied in different locus. However, the native ribosome binding site (RBS) and the downstream sequence (~100 bp) of putative TSS will influence the translation of the following target genes. To avoid this problem, a triple stop codon was attached to the 3′-end of the amplified promoter sequence, which could terminate any possible translations of the sequence (Figure 4b). Such a design guaranteed the original activity and temporal profile of the selected native promoters at transcriptional level and avoided the influence of native RBS on translation level. Performance of the selected native temporal promoters Using the aforementioned approach of promoter replacement, the cumate-inducible promoter was replaced by the 24 selected native temporal promoters to control the expression of actII-orf4 and sfgfp genes. Compared with the cumate-inducible promoter under the optimal condition, 15 selected promoters (62.5%, pink columns) generated better (labelled with asterisk) or similar Act titers (Figure 5a and Table S4).

9



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

The result indicates that appropriate native temporal promoters are capable of substituting for inducible promoters. Hence, the autoregulated strategy of using native temporal promoters is practical to improve the titers of desired secondary metabolites in Streptomyces. Interestingly, we observed that almost all the selected native temporal promoters resulted in higher Act titers compared to the best tested constitutive promoter SP26 (Figure 5a and Table S4), further showing the advantage of fine-tuning in both time and strength dimensions. Despite of these satisfactions, the reasons why some native temporal promoters exhibited poor performances were also studied. The profile of sfgfp controlled by native temporal promoter was compared with that controlled by the cumate-inducible promoter under the optimal induction condition at transcriptional level. Correlation analysis showed that, among 24 tested native promoters, 20 of them exhibited quite similar transcription profiles with that of the cumate-inducible promoter (R2 > 0.9) (Figure 5b and Table S5), indicating the temporal consistency of most native promoter behaviors when applied in different locus following this strategy. However, nine promoters displayed quite different strengths from that of the cumate-inducible promoter (slope > 2 or slope < 0.5) (Figure 5b, Figure S5 and Table S5). This result explains the poor performances of these native temporal promoters. A primary reason should be that absolute strength of a promoter is unable to be determined from transcriptome microarray data. Theoretically, next-generation RNA-sequencing could make up for this, whereas we found that RNA-sequencing data could not well match the real-time qRT-PCR data, 10


Page 10 of 35

Page 11 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


which may arise from the high G-C content of Streptomyces genomes.28 As a result, transcriptome microarray, as a mature technology, was preferred in this work. For another reason, although we have developed an elaborate design for promoter replacement, behavior of the promoter might still be influenced by chromosomal position effect.29 Nevertheless, many satisfied strains were obtained in this work (Figures 5a), demonstrating our strategy is feasible to enable the optimal autoregulation of the expression of desired secondary metabolite BGCs in Streptomyces. Fine-tune the expression of OTC BGC in a heterologous host The ever-growing genome databases of Streptomyces present a large number of untapped secondary metabolite BGCs.30 Heterologous expression of BGCs in the chassis Streptomyces has been used extensively as a means to access new secondary metabolite.31 However, these strategies often end up with low or undetectable production of the target compounds.32-34 One of the main reasons might ascribe to the incoordination between the expression of heterologous BGCs and the physiological state of hosts.32, 33 The autoregulated fine-tuning strategy developed here might alleviate this problem. To prove this point, the expression of OTC BGC from Streptomyces rimosus was fine-tuned in heterologous host S. coelicolor M1146. We observed no detectable OTC despite the whole BGC was successfully integrated into the genome of M1146 (Figure 6a). Overexpressing the pathway-specific activator gene otcR using the strong constitutive promoter kasOp* enabled the detection of OTC (Figure 6a). Then the expression of OTC BGC was fine-tuned in both time and 11



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

strength dimensions by the cumate-inducible promoter. Under the optimal condition (Figure 6b), the maximal titer of OTC dramatically increased by 9.1 times of that using kasOp* (Figure 6a). Further, 15 qualified native temporal promoters with similar transcription profile to that of the inducible promoter under optimal condition were selected based on transcriptome analysis (Figure 6c). Here, six promoters showed nearly the same titers as the cumate-inducible promoter under the optimal induction condition (Figure 6d and Table S6). These results further demonstrate the great advantages of the ″just-in-time″ autoregulated strategy in heterologous expression of BGCs. In conclusion, although various efforts have endeavored to increase the production capability of Streptomyces producer, there still lacks general strategies to optimally coordinate product biosynthesis and other physiological events. Herein, we found that manipulating the trade-off between product biosynthesis and other physiological events by an inducible promoter is effective for titer improvement in Streptomyces. However, adding inducers are unwanted sometimes. Hence, a novel autoregulated strategy employing native promoters was developed. This strategy has two innovations: (I) it presents a universal approach of how to identify qualified native promoters to fulfill the requirements of fine-tuning in both time and strength dimensions: qualified native promoters with similar transcription profile to the inducible promoter could be identified by time-course transcriptome under the optimal induction condition, and the optimal condition could be determined by response surface model; (II) an elaborate replacement approach was designed to 12


Page 12 of 35

Page 13 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ensure the consistency of native promoter behaviors when applied in different locus (Figure 4b). As a proof-of-concept, the engineered Streptomyces with optimal production capabilities of Act and heterologous OTC was obtained under our culture conditions, indicating the high efficiency and great potential of this strategy for strain improvement. Streptomyces contain massive of native temporal promoters with various behaviors owing to their complex life cycle and metabolic switches,9, 27 thus the plentiful native temporal promoters are believed to be a valuable untapped toolkit for metabolic engineering and synthetic biology. Overall, our strategy will provide a universal route towards titer improvement of desired secondary metabolites. Methods Bacterial strains and culture conditions Strains used in the present study are listed in Table S7. Plasmids were propagated in Escherichia coli JM109 (Novagen) cultured in Luria-Bertani (LB) broth with 25 µg/mL apramycin at 37°C. E. coli ET12567/pUZ8002 for conjugation was grown in LB at 37°C supplemented with antibiotics (chloramphenicol, 25 µg/mL; kanamycin, 25 µg/mL). For spore preparation, S. coelicolor M145 and its derivatives were maintained on mannitol-soya flour (MS) agar plates,35 while Streptomyces venezuelae ATCC 10712 and its derivatives were grown on maltose-yeast extract-malt extract (MYM) agar plates.35 The conjugations of Streptomyces strains were implemented on MS agar plates with nalidixic acid (25 µg/mL) and apramycin (25 µg/mL). For fermentations, all S. coelicolor and S. venezuelae strains were shaken at 250 rpm in

13



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

the liquid supplemented minimal medium (SMM)35 and glucose-MOPS medium,36 respectively. All cultivations were carried out at 28°C. Construction of plasmids and engineered strains All plasmids used in this work are listed in Table S7. All primers and oligonucleotides are listed in Table S8. For the construction of pActII-sfgfp, actII-orf4 gene was amplified from genomic DNA of S. coelicolor M145 using the primer pair actII4-F/actII4-R, then assembled with the plasmid backbone amplified from pIJ8660::BsaI-sfgfp15 using primer pair P1-F/P1-R to generate pActII-sfgfp.37 To tune the expression of actII-orf4 by constitutive promoters, nine constitutive promoters ermE*, SP8, Sp18, SP24, SP26, SP31, kasO*, Sp42 and SP4415 were synthesized and treated with BglII and EcoRV, then inserted into the linear plasmid pActII-sfgfp digested with the same enzymes to generate corresponding plasmids pPc-actII-sfgfp (c indicates the name of the constitutive promoters, Figure S1). The nine plasmids were integrated into the genome of S. coelicolor M145. To tune the expression of JdB BGC, the nine synthetic constitutive promoters digested by BglII and an EcoRV were ligated with the plasmid backbone amplified from pIW01-jad24 using primer pair IW01-F/IW01-R, respectively. The nine plasmids were recombined with the native jadJ in the genome of S. venezuelae ATCC 10712 by single cross-over. To tune the expression of actII-orf4 by cumate-inducible promoter, the sequence of cumate-inducible promoter was amplified from pGCymRP2123 using primer pair cumate-F/cumate-R, then treated with BglII and EcoRV and inserted into the corresponding site of pActII-sfgfp to generate pCumate-actII-sfgfp (Figure S1 and 14


Page 14 of 35

Page 15 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table S2). Plasmids pCumate-actII-sfgfp and pIW01-jad were integrated into the genome of S. coelicolor M145 and S. venezuelae ATCC 10712, respectively. To replace the inducible promoter by native promoters, the selected native promoters were amplified from the genome of S. coelicolor M145 using the corresponding primer pairs (designated Pn-F/Pn-R, n indicates the name of genes, Table S2). Then the native promoters treated with BglII (or its isocaudamer BamHI) and EcoRV were inserted into the promoter-less backbone of pActII-sfgfp digested with BglII and EcoRV to generate a series of plasmids named pPn-actII-sfgfp (n indicates the name of genes, Figure S1 and Table S2). To generate pOtcR-sfgfp, otcR was amplified with a pair of primers otcR-F/otcR-R from genome of Streptomyces rimosus, and then assembled with the plasmid backbone amplified from pIJ8660::BsaI-sfgfp15 using primer pairs P1-F/P1-R. To control the expression of otcR by strong constitutive promoter kasO*, the BglII-EcoRV digested fragment was inserted into the promoter-less backbone of pOtcR-sfgfp treated with the same enzymes. Similar to the construction of pCumate-actII-sfgfp, plasmid pCumate-otcR-sfgfp was generated by inserting cumate-inducible promoter into the BglII-EcoRV site of pOtcR-sfgfp. To replace the cumate-inducible promoter, the selected native promoters were amplified from the genome of S. coelicolor M145 using the corresponding primer pairs (designated Pn-F/Pn-R, n indicates the name of genes, Table S2), treated by BglII (or its isocaudamer BamHI) and EcoRV, and then ligated with the BglII-EcoRV digested pOtcR-sfgfp (Figure S1). These plasmids, combining by pOxy1 containing whole 15



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 35

OTC BGCs,38 were integrated into the genome S. coelicolor M1146. Total RNA isolation Cells of S. coelicolor strains cultivated in liquid SMM were quickly harvested by fast filtration, flash frozen in liquid nitrogen, and ground into powder for total RNA extraction using TRNzol (Tiangen, China).35 The integrity and quantity of the isolated RNA were checked by denaturing agarose gel electrophoresis and NanoDrop 2000 spectrophotometer (NanoDrop Technologies, USA), respectively. Microarray experiments Cells of S. coelicolor M145-OA cultivated under the optimal induction condition were sampled at 18, 24, 30, 36, 42, 48, and 60 h for experiments. Details for microarray experiments were described in our previous work.39 The microarray data obtained in this work are available at NCBI Gene Expression Omnibus database with the accession numbers of GSE100343. Selection of the candidate native temporal promoters To find qualified native temporal promoters, genes with temporal transcription profiles were first selected based on transcriptome data. A temporally expressed gene contains one or more timepoints (Tn) where its transcriptional level was significantly signal of Tn signal of T1

different from that of the first timepoint (T1) (log 2

> 1). Then, hierarchical

clustering was implemented according to time-series transcriptional data of these genes.40 Finally, candidate native temporal promoters were selected via operon

16


Page 17 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


analysis by ProOpDB.26 Real-Time qRT-PCR Behaviors of the cumate-inducible promoter and all selected native temporal promoters were determined according to the transcription profiles of sfgfp in the corresponding strains. Cells of S. coelicolor strains sampled at 18, 24, 30, 36, 42, 48, and 60 h were used for experiments. For real-time qRT-PCR experiments, the first-strand synthesis of cDNA was carried out using 1 µg total RNA with a PrimeScript™ RT Reagent kit with gDNA Eraser (TaKaRa, Japan) following the manufacturer’s instructions. Primers used for real-time qRT-PCR are listed in Table S2. Details of the PCR procedures were described in our previous work.36 The sco3183 gene was used as an internal control.39 Detection of Act, JdB and OTC Titer of Act was assayed as previously described.35 Titer of JdB and OTC were assayed by HPLC, and detailed analytical conditions were described by Chen et al.41 and Yin et al.,18 respectively. Statistical analysis CCD and response surface model were implemented by Design-Expert (v8.0.6.1). All data in this work were obtained from three biological triplicates. Results were shown as the average or with the standard deviation (s. d.). Significance analysis was implemented by unpaired two-tailed Student’s t-test or one-way analysis of variance (ANOVA), with *** p < 0.001, ** p < 0.01, * p < 0.05. 17



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Supporting Information Figure S1. Map of plasmids designed for fine-tuning the expression of Act and OTC BGCs; Figure S2. Optimization of the expression of Act and JdB BGCs using constitutive promoters with different strengths; Figure S3. Determination of appropriate range of induction time and dosage by single factor test in M145-OA; Figure S4. Sampling timepoints for transcriptome experiments; Figure S5. Comparison of transcription profile of sfgfp controlled by native temporal promoter and the inducible promoter under optimal induction condition; Table S1. Results of the central composite design of M145-OA; Table S2. Description of the quadratic response surface model obtained from central composite design; Table S3. Information of the selected native temporal promoters; Table S4. Performance of native temporal promoters on Act production in S. coelicolor; Table S5. Investigation of the relationships between behaviors of native temporal promoter and the cumate-inducible promoter by correlation analysis; Table S6. Performance of native temporal promoters on OTC production in S. coelicolor; Table S7. Strains and plasmids used in this work; Table S8. Primers and oligonucleotides used in this work. Abbreviations BGC, biosynthetic gene cluster; Act, actinorhodin; OTC, oxytetracycline; JdB, jadomycin B; CCD, central composite design; RBS, ribosome binding site. Author information Corresponding Author Weishan Wang, Email: [email protected]; Address: State Key Laboratory of 18


Page 18 of 35

Page 19 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, People’s Republic of China. Correspondence may also be addressed to Zilong Li with the same address, E-mail: [email protected]. Author Contributions W.W. and K.Y. conceived and supervised the project. S.L. and J.W. designed and performed the main experiments and data analyses. F.Q. and W.X. prepared and analyzed the transcriptome data. S.L., W.W. and Z.L. wrote the manuscript. Notes: The authors declare no competing interest. Acknowledgement This work was supported by grants from National Natural Science Foundation of China (31772242, 31570031, 31400034); Ministry of Science and Technology of China (2013CB734001); Youth Innovation Promotion Association (2016087); The International Partnership Program of Chinses Academy of Science (153211KYSB20170014). We are grateful to Prof. Lixin Zhang (East China University of Science and Technology), Prof. Sang Yup Lee (Korea Advanced Institute of Science and Technology), and Prof. Linquan Bai (Shanghai Jiao Tong University) for their valuable suggestions on this work. We also thank Prof. Jing Han (Institute of Microbiology, Chinese Academy of Sciences) and Prof. Hang Wu (Anhui University) for critical reading of the manuscript. References 1.

Newman, D. J., and Cragg, G. M. (2012) Natural products as sources of new 19



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

drugs over the 30 years from 1981 to 2010, J. Nat. Prod. 75, 311-335. 2.

Watve, M. G., Tickoo, R., Jog, M. M., and Bhole, B. D. (2001) How many antibiotics are produced by the genus Streptomyces?, Arch. Microbiol.176, 386-390.

3.

Li, L., Zheng, G., Chen, J., Ge, M., Jiang, W., and Lu, Y. (2017) Multiplexed site-specific genome engineering for overproducing bioactive secondary metabolites in actinomycetes, Metab. Eng. 40, 80-92.

4.

Pickens, L. B., Tang, Y., and Chooi, Y. H. (2011) Metabolic engineering for the production of natural products, Annu. Rev. Chem. Biomol. Eng. 2, 211-236.

5.

Zhang, M. M., Wang, Y., Ang, E. L., and Zhao, H. (2016) Engineering microbial hosts for production of bacterial natural products, Nat. Prod. Rep. 33, 963-987.

6.

Tan, G.-Y., and Liu, T. (2017) Rational synthetic pathway refactoring of natural products biosynthesis in actinobacteria, Metab. Eng. 39, 228-236.

7.

Hwang, K.-S., Kim, H. U., Charusanti, P., Palsson, B. Ø., and Lee, S. Y. (2014) Systems biology and biotechnology of Streptomyces species for the production of secondary metabolites, Biotechnol. Adv. 32, 255-268.

8.

Nieselt, K., Battke, F., Herbig, A., Bruheim, P., Wentzel, A., Jakobsen, O., Sletta, H., Alam, M., Merlo, M., Moore, J., Omara, W., Morrissey, E., Juarez-Hermosillo, M., Rodriguez-Garcia, A., Nentwich, M., Thomas, L., Iqbal, M., Legaie, R., Gaze, W., Challis, G., Jansen, R., Dijkhuizen, L., Rand, D., Wild, D., Bonin, M., Reuther, J., Wohlleben, W., Smith, M., Burroughs, N., and Martin, J. (2010) The dynamic architecture of the metabolic switch in Streptomyces coelicolor, BMC

20


Page 20 of 35

Page 21 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Genomics 11, 10. 9.

Liu, G., Chater, K. F., Chandra, G., Niu, G., and Tan, H. (2013) Molecular regulation of antibiotic biosynthesis in Streptomyces, Microbiol. Mol. Biol. Rev. 77, 112-143.

10. Bibb, M. J. (2005) Regulation of secondary metabolism in streptomycetes, Curr. Opin. Microbiol. 8, 208-215. 11. Woolston, B. M., Edgar, S., and Stephanopoulos, G. (2013) Metabolic engineering: past and future, Annu. Rev. Chem. Biomol. Eng. 4, 259-288. 12. Medema, M. H., Breitling, R., Bovenberg, R., and Takano, E. (2011) Exploiting plug-and-play synthetic biology for drug discovery and production in microorganisms, Nat. Rev. Microiol. 9, 131-137. 13. Lu, C., Zhang, X., Jiang, M., and Bai, L. (2016) Enhanced salinomycin production by adjusting the supply of polyketide extender units in Streptomyces albus, Metab. Eng. 35, 129-137. 14. Liu, J., Chen, Y., Wang, W., Ren, M., Wu, P., Wang, Y., Li, C., Zhang, L., Wu, H., Weaver, D. T., and Zhang, B. (2017) Engineering of an Lrp family regulator SACE_Lrp improves erythromycin production in Saccharopolyspora erythraea, Metab. Eng. 39, 29-37. 15. Bai, C., Zhang, Y., Zhao, X., Hu, Y., Xiang, S., Miao, J., Lou, C., and Zhang, L. (2015) Exploiting a precise design of universal synthetic modular regulatory elements to unlock the microbial natural products in Streptomyces, Proc. Natl. Acad. Sci. USA 112, 12181-12186.

21



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

16. Luo, Y., Enghiad, B., and Zhao, H. (2016) New tools for reconstruction and heterologous expression of natural product biosynthetic gene clusters, Nat. Prod. Rep. 33, 174-182. 17. Özcengiz, G., Okay, S., Ünsaldı, E., Taşkın, B., Liras, P., and Piret, J. (2010) Homologous expression of aspartokinase (ask) gene in Streptomyces clavuligerus and its hom-deleted mutant: effects on cephamycin C production, Bioeng. Bugs 1, 191-197. 18. Yin, S., Wang, W., Wang, X., Zhu, Y., Jia, X., Li, S., Yuan, F., Zhang, Y., and Yang, K. (2015) Identification of a cluster-situated activator of oxytetracycline biosynthesis and manipulation of its expression for improved oxytetracycline production in Streptomyces rimosus, Microb. Cell Fact. 14, 46. 19. Zaslaver, A., Mayo, A. E., Rosenberg, R., Bashkin, P., Sberro, H., Tsalyuk, M., Surette, M. G., and Alon, U. (2004) Just-in-time transcription program in metabolic pathways, Nat. Genet. 36, 486-491. 20. Gupta, A., Reizman, I. M. B., Reisch, C. R., and Prather, K. L. J. (2017) Dynamic regulation of metabolic flux in engineered bacteria using a pathway-independent quorum-sensing circuit, Nat. Biotechnol. 35, 273-279. 21. Arias, P., Fernández-Moreno, M. A., and Malpartida, F. (1999) Characterization of the pathway-specific positive transcriptional regulator for actinorhodin biosynthesis in Streptomyces coelicolor A3(2) as a DNA-binding protein, J. Bacteriol. 181, 6958-6968. 22. Zhang, Y., Pan, G., Zou, Z., Fan, K., Yang, K., and Tan, H. (2013)

22


Page 22 of 35

Page 23 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


JadR*-mediated feed-forward regulation of cofactor supply in jadomycin biosynthesis, Mol. Microbiol. 90, 884-897. 23. Horbal, L., Fedorenko, V., and Luzhetskyy, A. (2014) Novel and tightly regulated resorcinol and cumate-inducible expression systems for Streptomyces and other actinobacteria, Appl. Microbiol. Biotechnol. 98, 8641-8655. 24. Wang, W., Yang, T., Li, Y., Li, S., Yin, S., Styles, K., Corre, C., and Yang, K. (2016) Development of a synthetic oxytetracycline-inducible expression system for streptomycetes using de novo characterized genetic parts, ACS Syn. Biol. 5, 765-773. 25. Ermolaeva, M. D., White, O., and Salzberg, S. L. (2001) Prediction of operons in microbial genomes, Nucleic Acids Res. 29, 1216-1221. 26. Taboada, B., Ciria, R., Martinez-Guerrero, C. E., and Merino, E. (2012) ProOpDB: Prokaryotic Operon DataBase, Nucleic Acids Res. 40, D627-D631. 27. Jeong, Y., Kim, J. N., Kim, M. W., Bucca, G., Cho, S., Yoon, Y. J., Kim, B. G., Roe, J. H., Kim, S. C., Smith, C. P., and Cho, B. K. (2016) The dynamic transcriptional and translational landscape of the model antibiotic producer Streptomyces coelicolor A3(2), Nat. Commun. 7, 11605. 28. Benjamini, Y., and Speed, T. P. (2012) Summarizing and correcting the GC content bias in high-throughput sequencing, Nucleic Acids Res. 40, e72. 29. Bilyk, B., Horbal, L., and Luzhetskyy, A. (2017) Chromosomal position effect influences the heterologous expression of genes and biosynthetic gene clusters in Streptomyces albus J1074, Microb. Cell Fact. 16, 5.

23



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

30. Ziemert, N., Alanjary, M., and Weber, T. (2016) The evolution of genome mining in microbes - a review, Nat. Prod. Rep. 33, 988-1005. 31. Ongley, S. E., Bian, X., Neilan, B. A., and Muller, R. (2013) Recent advances in the heterologous expression of microbial natural product biosynthetic pathways, Nat. Prod. Rep. 30, 1121-1138. 32. Tan, G. Y., Deng, K., Liu, X., Tao, H., Chang, Y., Chen, J., Chen, K., Sheng, Z., Deng, Z., and Liu, T. (2017) Heterologous biosynthesis of spinosad: an omics-guided large polyketide synthase gene cluster reconstitution in Streptomyces, ACS Synth. Biol. 6, 995-1005. 33. Komatsu, M., Komatsu, K., Koiwai, H., Yamada, Y., Kozone, I., and Izumikawa, M. (2013) Engineered Streptomyces avermitilis host for heterologous expression of biosynthetic gene cluster for secondary metabolites, ACS Synth. Biol. 2, 384-396. 34. Bekiesch, P., Basitta, P., and Apel, A. K. (2016) Challenges in the Heterologous Production of Antibiotics in Streptomyces, Archiv. Pharm. 349, 594-601. 35. Kieser, T., Bibb, M. J., Buttner, M. J., Chater, K. F., and Hopwood, D. A. (2000) Practical Streptomyces Genetics, The John Innes Foundation, Norwich, UK. 36. Li, S., Wang, J., Li, X., Yin, S., Wang, W., and Yang, K. (2015) Genome-wide identification and evaluation of constitutive promoters in streptomycetes, Microb. Cell Fact. 14, 172. 37. Gibson, D. G., Young, L., Chuang, R.-Y., Venter, J. C., Hutchison, C. A., and Smith, H. O. (2009) Enzymatic assembly of DNA molecules up to several

24


Page 24 of 35

Page 25 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


hundred kilobases, Nat. Methods 6, 343-345. 38. Yin, S., Li, Z., Wang, X., Wang, H., Jia, X., Ai, G., Bai, Z., Shi, M., Yuan, F., Liu, T., Wang, W., and Yang, K. (2016) Heterologous expression of oxytetracycline biosynthetic gene cluster in Streptomyces venezuelae WVR2006 to improve production level and to alter fermentation process, Appl. Microbiol. Biotechnol. 100, 10563-10572. 39. Li, S., Wang, W., Li, X., Fan, K., and Yang, K. (2015) Genome-wide identification and characterization of reference genes with different transcript abundances for Streptomyces coelicolor, Sci. Rep. 5, 15840. 40. Dahl, R. H., Zhang, F., Alonso-Gutierrez, J., Baidoo, E., Batth, T. S., Redding-Johanson, A. M., Petzold, C. J., Mukhopadhyay, A., Lee, T. S., Adams, P. D., and Keasling, J. D. (2013) Engineering dynamic pathway regulation using stress-response promoters, Nat. Biotechnol. 31, 1039-1046. 41. Chen, Y.-H., Wang, C.-C., Greenwell, L., Rix, U., Hoffmeister, D., Vining, L. C., Rohr, J., and Yang, K.-Q. (2005) Functional analyses of oxygenases in jadomycin biosynthesis and identification of JadH as a bifunctional oxygenase/dehydrase, J. Biol. Chem. 280, 22508-22514.

Figure legends and tables Figure 1 Effects of different fine-tuning approaches on the titers of secondary metabolites. (a) Titers of Act with the variation of induction condition in S. coelicolor M145-OA. (b) Titers of JdB with the variation of induction conditions in S. 25



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

venezuelae Sv-Potr. (c) Titers of Act obtained by different fine-tuning approaches. M145-PSP26 is the strain tuned by the optimal promoter SP26 (Figure S2a). (d) Titers of Act obtained by different fine-tuning approaches. Sv-PSP18 is the strain tuned by the optimal promoter SP18 (Figure S2b). Data was obtained from three biological replicates. Significance was analyzed by unpaired two-tailed Student’s t-test. *** p < 0.001, ** p < 0.01, * p < 0.05. Figure 2 Illustration of the autoregulated fine-tuning strategy. Figure 3 Determination of the optimal induction condition for Act production. (a) Determination of the optimal induction condition of M145-OA by response surface model. Regression coefficient of the model was R2 = 0.86. (b) Validation of Act titers under the predicted optimal condition. Adding 2.5 µM of cumate at 32 h is the best induction condition of orthogonal experiment (Figure 1a), while adding 1.8 µM of cumate at 35 h is the optimal induction condition determined by response surface model. Data was obtained from three biological replicates. Significance was analyzed by unpaired two-tailed Student’s t-test. *** p < 0.001, ** p < 0.01, * p < 0.05, ′ns′ indicates no significance. Figure 4 Replacement of inducible promoter using qualified native promoter. (a) Selection of appropriate native temporal promoters by hierarchical clustering. (b) Illustration of the elaborate design for promoter replacement. Asterisk indicates the putative translation start site of genes. Pcumate, the cumate-inducible promoter; actII-orf4, the coding gene of pathway specific activator of Act BGC; sfgfp,

26


Page 26 of 35

Page 27 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


super-folded gfp gene; aac, apramycin resistance gene; tfd, major transcription terminator of phage fd; to, transcription terminator from phage λ; int-phiC31 and attP, the integrase gene and attachment site of the temperate phage phiC31, respectively; ori-pUC18, origin of replication of pUC18; oriT, origin of transfer from plasmid RK2. Figure 5 Performance of the autoregulated strategy. (a) Comparison of Act titers controlled by different promoters. Significance analysis was conducted by one-way ANOVA. Columns in pink indicate similar (no significance, p > 0.05) or better (labelled with asterisk, *** p < 0.001, ** p < 0.01, * p < 0.05) performances of the corresponding native temporal promoters compared to the cumate-inducible promoter under the optimal induction condition (Table S4). (b) Correlation analysis of transcription profiles of sfgfp driven by the native temporal promoter and the cumate-inducible promoter at the optimal induction condition. Data was the average of three biological replicates. Figure 6 Fine-tuning the expression of OTC BGC in a heterogeneous host. (a) OTC titers obtained with different fine-tuning approaches. M1146-OTC is the strain integrated the whole OTC BGC into the genome of S. coelicolor M1146. M1146-OTCK is the strain with overexpressed otcR using kasOp* in M1146-OTC. M1146-OTCC is the strain with otcR tuned by the cumate-inducible promoter in M1146-OTC. The optimal induction condition was determined in (b), adding 2.2 µM of cumate at 30 h. ′ND′ means not detected. Data were obtained from three biological replicates. Significance was analyzed by unpaired two-tailed Student’s t-test. *** p < 0.001, ** p < 0.01, * p < 0.05. (b) Determination of the optimal induction condition 27



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

of M1146-OTCC by response surface model. Regression coefficient of the model was R2=0.94. (c) Selection of appropriate native temporal promoters with identical behavior to the cumate-inducible promoter under the optimal induction condition. (d) Performance of promoter replacement on OTC titers in engineered strains. Significance analysis was conducted by one-way ANOVA. Columns in pink indicate that performances of the corresponding native temporal promoters were similar (no significance, p > 0.05; Table S6) compared to the cumate-inducible promoter under the optimal induction condition. Data were obtained from three biological replicates.

28


Page 28 of 35

Page 29 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table of content 39x22mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 1 Effects of different fine-tuning approaches on the titers of secondary metabolites. (a) Titers of Act with the variation of induction condition in S. coelicolor M145-OA. (b) Titers of JdB with the variation of induction conditions in S. venezuelae Sv-Potr. (c) Titers of Act obtained by different fine-tuning approaches. M145-PSP26 is the strain tuned by the optimal promoter SP26 (Figure S2a). (d) Titers of Act obtained by different fine-tuning approaches. Sv-PSP18 is the strain tuned by the optimal promoter SP18 (Figure S2b). Data was obtained from three biological replicates. Significance was analyzed by unpaired two-tailed Student’s t-test. *** p < 0.001, ** p < 0.01, * p < 0.05. 137x112mm (300 x 300 DPI)


Page 30 of 35

Page 31 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2 Illustration of the autoregulated fine-tuning strategy. 71x33mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 3 Determination of the optimal induction condition for Act production. (a) Determination of the optimal induction condition of M145-OA by response surface model. Regression coefficient of the model was R2 = 0.86. (b) Validation of Act titers under the predicted optimal condition. Adding 2.5 µM of cumate at 32 h is the best induction condition of orthogonal experiment (Figure 1a), while adding 1.8 µM of cumate at 35 h is the optimal induction condition determined by response surface model. Data was obtained from three biological replicates. Significance was analyzed by unpaired two-tailed Student’s t-test. *** p < 0.001, ** p < 0.01, * p < 0.05, 'ns' indicates no significance. 90x52mm (300 x 300 DPI)


Page 32 of 35

Page 33 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4 Replacement of inducible promoter using qualified native promoter. (a) Selection of appropriate native temporal promoters by hierarchical clustering. (b) Illustration of the elaborate design for promoter replacement. Asterisk indicates the putative translation start site of genes. Pcumate, the cumate-inducible promoter; actII-orf4, the coding gene of pathway specific activator of Act BGC; sfgfp, super-folded gfp gene; aac, apramycin resistance gene; tfd, major transcription terminator of phage fd; to, transcription terminator from phage λ; int-phiC31 and attP, the integrase gene and attachment site of the temperate phage phiC31, respectively; ori-pUC18, origin of replication of pUC18; oriT, origin of transfer from plasmid RK2. 138x128mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 5 Performance of the autoregulated strategy. (a) Comparison of Act titers controlled by different promoters. Significance analysis was conducted by one-way ANOVA. Columns in pink indicate similar (no significance, p > 0.05) or better (labelled with asterisk, *** p < 0.001, ** p < 0.01, * p < 0.05) performances of the corresponding native temporal promoters compared to the cumate-inducible promoter under the optimal induction condition (Table S4). (b) Correlation analysis of transcription profiles of sfgfp driven by the native temporal promoter and the cumate-inducible promoter at the optimal induction condition. Data was the average of three biological replicates. 148x130mm (300 x 300 DPI)


Page 34 of 35

Page 35 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 6 Fine-tuning the expression of OTC BGC in a heterogeneous host. (a) OTC titers obtained with different fine-tuning approaches. M1146-OTC is the strain integrated the whole OTC BGC into the genome of S. coelicolor M1146. M1146-OTCK is the strain with overexpressed otcR using kasOp* in M1146-OTC. M1146-OTCC is the strain with otcR tuned by the cumate-inducible promoter in M1146-OTC. The optimal induction condition was determined in (b), adding 2.2 µM of cumate at 30 h. ′ND′ means not detected. Data were obtained from three biological replicates. Significance was analyzed by unpaired two-tailed Student’s ttest. *** p < 0.001, ** p < 0.01, * p < 0.05. (b) Determination of the optimal induction condition of M1146-OTCC by response surface model. Regression coefficient of the model was R2=0.94. (c) Selection of appropriate native temporal promoters with identical behavior to the cumate-inducible promoter under the optimal induction condition. (d) Performance of promoter replacement on OTC titers in engineered strains. Significance analysis was conducted by one-way ANOVA. Columns in pink indicate that performances of the corresponding native temporal promoters were similar (no significance, p > 0.05; Table S6) compared to the cumate-inducible promoter under the optimal induction condition. Data were obtained from three biological replicates. 134x121mm (300 x 300 DPI)


An Autoregulated Fine-Tuning Strategy for Titer Improvement of

Recommend Documents