Construction, Model-Based Analysis, and Characterization of a

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Construction, model-based analysis and characterization of a promoter library for fine-tuned gene expression in Bacillus subtilis Dingyu Liu, Zhitao Mao, Jiaxin Guo, Leyi Wei, Hongwu Ma, Ya-Jie Tang, Tao Chen, Zhiwen Wang, and Xueming Zhao ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.8b00115 • Publication Date (Web): 26 Jun 2018 Downloaded from http://pubs.acs.org on June 27, 2018

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ACS Synthetic Biology

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Construction, model-based analysis and characterization of a

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promoter library for fine-tuned gene expression in Bacillus subtilis

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Dingyu Liua, Zhitao Maob,c, Jiaxin Guoa, Leyi Weid, Hongwu Mab,c, Yajie Tange, Tao

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Chena, Zhiwen Wanga* and Xueming Zhaoa

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a

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Research Platform, Collaborative Innovation Center of Chemical Science and

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Engineering (Tianjin), School of Chemical Engineering and Technology, Tianjin

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University, Tianjin 300072, People’s Republic of China.

Key Laboratory of Systems Bioengineering (Ministry of Education); Synbio

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b

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Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China

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c

University of Chinese Academy of Sciences, Beijing 100049, China

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d

School of Computer Science and Technology, Tianjin University, Tianjin 300072,

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People’s Republic of China

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e

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Laboratory of Industrial Microbiology, Hubei Provincial Cooperative Innovation

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Center of Industrial Fermentation, Hubei University of Technology, Wuhan 430068,

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China;

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* Corresponding author: Zhiwen Wang.

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Tel: +86-22-85356617; Fax: +86-22-85356617.

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Address: Department of Biochemical Engineering, School of Chemical Engineering

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and Technology, Tianjin University, Tianjin 300072, People’s Republic of China.

Key Laboratory of System Microbial Biotechnology, Tianjin Institute of Industrial

Key Laboratory of Fermentation Engineering (Ministry of Education), Hubei Key

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ACS Paragon Plus Environment

ACS Synthetic Biology 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

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E-mail addresses:

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Dingyu Liu: [email protected]

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Zhitao Mao: [email protected]

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Jiaxin Guo: [email protected]

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Leyi Wei: [email protected]

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Hongwu Ma: [email protected]

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Yajie Tang: [email protected]

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Tao Chen: [email protected]

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Zhiwen Wang: [email protected]

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Xueming Zhao: [email protected]

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Abstract

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Promoters are among the most important and basic tools for the control of metabolic

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pathways. However, previous researches mainly focused on screening and

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characterization of some native promoters in Bacillus subtilis. To develop a broadly

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applicable promoter system for this important platform organism, we created a de

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novo synthetic promoter library (SPL) based on consensus sequences by analyzing

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microarray transcriptome data of Bacillus subtilis 168. A total of 214 potential

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promoters spanning a gradient of strengths were isolated and characterized by a GFP

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fluorescence assay. Among these, a detailed intensity analysis was conducted on 9

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promoters with different strengths by RT-PCR and SDS-PAGE. Furthermore,

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reconstructed promoters and promoter cassettes (tandem promoter cluster) were

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designed via statistical model-based analysis and tandem dual-promoter, which

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increased by 1.2-fold and 2.77-fold in term of strength compared with promoter P43

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respectively. Finally, the SPL was employed in the production of inosine and acetoin

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by repressing and overexpressing the relevant metabolic pathways, yielding a 700%

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and 44% increase relative to the respective control strains. This is the first report of a

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de novo synthetic promoter library for B. subtilis, which is independent of any native

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promoter. The strategy of improving and fine-tuning promoter strengths will

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contribute to future metabolic engineering and synthetic biology projects in B.

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subtilis.

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KEYWORDS: synthetic promoter library; fine-tuning; model-based analysis; tandem

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promoter clusters; metabolic engineering; synthetic biology. 3



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Metabolic engineering and synthetic biology approaches to the design and

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construction of biological systems have an enormous potential for applications in

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industrial biotechnology.1 The implementation of the synthetic biology concept of

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engineered biological systems depends on the availability of standardized biological

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regulatory elements such as synthetic promoters, RBS (ribosome binding site) and

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terminators, etc..2 Moreover, rationally designed, analyzed and well-characterized

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genetic elements are invaluable tools for various metabolic engineering approaches in

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which the fine-tuning of gene expression is necessary.3, 4 Promoters serve a critical

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role in establishing a baseline transcriptional capacity for natural and synthetic circuits

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or metabolic pathways.5,

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biology parts and play an essential role in controlling biosynthetic pathways.7

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Therefore, a quantitatively characterized library of promoters is required to express

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target genes in a controlled fashion in order to optimize metabolic network.

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Thus, promoter elements are indispensable synthetic

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Native promoters, both constitutive and inducible, have long been used in gene

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expression and metabolic regulation.8-10 Although some native promoters are

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commonly used, they do not provide a wide and continuous range of transcriptional

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levels. Furthermore, naturally occurring promoters are influenced by host regulatory

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networks, complicating the prediction of precise transcriptional activities. Thus, it is

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desirable to develop synthetic promoters with the widest possible range of strengths,

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which are entirely synthetic in nature and orthogonal to intrinsic control networks to

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reduce endogenous cellular interactions. Synthetic promoter libraries (SPL) have been 4


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successfully constructed for Escherichia coli,11 Saccharomyces cerevisiae,12 Pichia

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pastoris,13 Corynebacterium glutamicum,14 Actinomycetesand15 and Lactobacillus

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plantarum.16

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Bacillus subtilis, a non-pathogenic, Gram-positive bacterium that is free of

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exotoxins and endotoxins, has long been used as an important cell factory for

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industrial applications.17-19 The overproduction of target metabolites usually occurs

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during the exponential or stationary phase and is influenced by a variety of

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physiological and environmental factors. For the successful engineering and

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regulation of metabolic networks, it is therefore indispensable to consider the

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appropriate balance of the expression of the involved genes. Hence, transcriptional

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fine-tuning and regulation are essential for optimal gene expression. Recently,

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although there are already some works about native promoters of Bacillus subtilis 20, 21,

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just a few high quality native promoters are wildly used in B. subtilis for gene

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expression and regulation, such as the constitutive promoters P4322 and Pveg,23 as

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well as the inducible promoters Pspa24 and PxylA.25 There are recent reports from

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large-scale “omic”-studies of Bacillus spp. that detected a number of high-quality

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native promoters and performed a strength analysis.26,

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synthetic promoters have been constructed and modified by optimization of their key

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elements to make them more suitable for practical applications.28 However, these

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promoters have not been comprehensively and quantitatively characterized in a same

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host. Moreover, the relevant promoter structures have not been analyzed to uncover

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the correlation between promoter sequences and their strengths in B. subtilis. Instead, 5


27

Simultaneously, several


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promoters were only generally described as weak or strong. To the best of our

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knowledge, there are no published reports of a fully artificial synthetic promoter

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library for B. subtilis.

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The aim of this study was to construct and characterize a de novo synthetic

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promoter library, and to reconstruct promoter based on tandem assembly and

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model-based analysis, in order to deliver a set of wide-ranging promoter strengths for

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metabolic engineering and synthetic biology in B. subtilis. We demonstrate that a

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previously published easy and fast PCR-based method for constructing promoter

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library in B. subtilis. Randomization of nucleotides was employed to construct a

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synthetic promoter library based on transcriptome analysis of the wild-type strain B.

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subtilis 168. Statistical model-based analysis of promoter sequences was further

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employed to rationally improve the strength of promoter. Fine-tuned expression of

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genes was verified by regulating purA in the purine pathway using different synthetic

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promoters. Finally, a tandem promoter cluster was developed to enhance the

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overexpression of xynA gene for the production of acetoin from xylan, demonstrating

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the potential of the promoter library in bio-based product manufacturing.

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RESULTS

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Analysis of microarray transcriptome data of B. subtilis

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Constitutive promoters offer relatively constant gene expression profiles, and the

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number of transcripts are strongly correlated with the promoter strengths. In our

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previous work, transcriptome profiles of wild-type B. subtilis 168 were performed on 6


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DNA microarray using early stationary phase cell samples grown in LB medium.29

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The microarray transcriptome data were reanalyzed to guide our design of the

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promoter library. The microarray data covered a total of 5039 B. subtilis genes. Global

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analysis of the gene expression profiles revealed the presence of 4167 gene transcripts,

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with 872 gene transcripts being marginal or absent.

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In B. subtilis, there are 17 sigma factors that associate with the RNA polymerase

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core enzyme for promoter recognition. The binding regions of these sigma factors are

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conserved in their respective recognized promoter sequences, and can be easily

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discerned in B. subtilis. Therefore, the SPL was designed based on these consensus

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regions for stable functioning. The 4167 genes were divided into different groups

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based on their different sigma factor-dependency. Most of the detected gene

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expression signals had signal strengths below 1000. To analyze the sequence features

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of high strength promoters, the genes with high transcript levels (signal strength above

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1000) were displayed (Figure 1). It was found that sigma A-dependent genes

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constituted the majority in the set of genes with high transcript levels, which were

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significantly higher than those dependent on other sigma factors. This result revealed

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that the binding regions of the sigma A factor are crucial to maintain an appropriate

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promoter strength. Therefore, the -35 and -10 elements of sigma A-dependent genes

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were integrated into our SPL design to maintain a satisfying strength. The promoter

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sequences of sigma factor-dependent genes and the results of motif alignment were

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obtained from DBTBS (http://dbtbs.hgc.jp/). The conserved -35, -10 boxes were

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consistent with classical “TTGACA” and “TATAAT” in promoter sequences of sigma 7



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A-dependent genes according to the alignment results. In addition, the upstream

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regions of sigma A-recognized -35 elements also exhibited weakly conserved An tracts

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and AT region according to the alignment results and previous reports30. Therefore,

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the UP (upstream of the -35 region) elements (An tracts and AT region) were reserved

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in our SPL to increase basal promoter transcription. Consequently, conserved -35, -10

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boxes and weakly conserved UP elements were designed in our SPL, yielding the

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classical “TTGACA”, “TATAAT” sequences, and An tracts, AT region and extended

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-35 region, respectively.

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Figure 1. Transcript levels of genes with stable expression profiles. A total of 4167

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gene transcripts were present. The genes with signal values above 1000 are shown.

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The Pearson correlation coefficient between the biological duplicates was about 0.95,

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implying that the microarray experiment was reproducible and reliable.

168 8


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Design and screening of a synthetic promoter library for B. subtilis

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Generally, a consensus promoter structure for bacteria includes -35, -10 motifs and

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a UP element. In addition, a TG dinucleotide motif, positioned 1 base upstream of the

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-10 region (-16 element), is reported to be conserved in B. subtilis.30 As the -16 region

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is not necessary for many promoters, its utility is context dependent.30 Thus, since the

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-16 element is required to assure the universality and specificity of a promoter, the

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-35,-10,-16 and UP elements were conserved in our synthetic promoter library (Figure

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S1). For evaluation of the promoters, a same ribosome binding site sequence

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“AAGAAGGAGATATACAT” was added between promoters and the gfp open

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reading frame. Finally, we created a de novo synthetic promoter library based on the

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consensus sequences obtained in the transcriptome analysis and additional references

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(Figure 2). The digested PCR fragment containing the varied synthetic promoters, was

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ligated into the reporter vector, and then the ligated plasmids were transformed into E.

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coli to obtain a high number of transformants. The purified library plasmids were used

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to directly transform B. subtilis 168 to screen and sequence the promoter region. The

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B. subtilis 168 synthetic promoter mutants were subsequently grown to stationary

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phase and subjected to a GFP assay for indirect assessment of promoter strengths. The

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GFP fluorescence was standardized to cell density. About 5000 colonies were

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randomly picked from rounds of transformation and the corresponding GFP

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expression levels were investigated. The P43 and Pveg promoters were used as

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positive controls. None of the clones showed a higher signal intensity than the

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promoter P43, and a part of them had a higher strength than Pveg. Taking into account 9



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the intensity gradient and sample size, 214 potential promoters with various strengths

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were isolated for subsequent characterization and analysis (Table S2). As shown in

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Figure 3, the resulting library of 214 synthetic promoters had strengths ranging from 2%

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to 94% of P43. Among these promoters, 49 promoters showed higher strengths than

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Pveg, and the highest strength promoter SP214 was almost equal to P43.

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Figure 2. Schematic overview of the experimental procedure for construction,

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analysis and characterization of SPL. An artificial promoter library was constructed

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rapidly. In step II, the red color in the reverse primer represents a randomized

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sequence. GFP, gfp reporter gene. rep60, origin of replication in B. subtilis. ColE1,

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origin of replication in E. coli. Cm, chloramphenicol resistance gene.

10


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Figure 3. Promoter strengths of SPL and control. Pveg (blue) and P43 (red) are

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positive controls. pAD123-gfp (white) is negative control without a promoter

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sequence in front of gfp gene.The relative activity is the strength of each promoter

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compared to the promoter P43. The error bars indicate the standard deviations of

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biological triplicates (three independent experiments with the same exconjugant).

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Characterization of the synthetic promoter library using RT-PCR and

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SDS-PAGE

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The GFP fluorescence assay only indirectly reflects the promoter strength since it

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is an indicator of the combined strength of transcription and translation of the

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resulting RNA into the functional reporter protein. To directly assess the promoter

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strength at transcriptional level, RT-PCR analysis was performed to facilitate the

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semi-quantitative analysis of the mRNA transcript of gfp from the selected promoters.

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Out of the 214 tested promoters, 9 promoters were selected for RT-PCR analysis and

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classified according to their respective levels of fluorescence intensity: high-strength

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group (H-group), intermediate-strength group (I-group) and low-strength group 11



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(L-group). The results showed that a high correlation between the number of mRNA

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transcripts of the gfp gene and the GFP fluorescence assayed in each strain (Figure 4),

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which suggested that the GFP fluorescence assay closely reflected the transcriptional

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level of the gfp gene, which was in agreement with previous studies.31

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Subsequently, the GFP expression levels of the nine strains were also confirmed

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by SDS-PAGE (Figure 5). All promoters in the H-group showed higher GFP protein

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expression levels than those in the I-group, which in turn were higher than those in the

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L-group. These results revealed that there were no discrepancies caused by

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translational influences in GFP expression, implying that the strength of the SPL

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should not be impacted at translational level in the case of easily-folded highly soluble

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proteins such as GFP.

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231 232

Figure 4. Results of GFP activity and relative transcription levels. Evaluation of

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promoter strength by fluorescence intensity and RT-PCR. H-group contains SP212,

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SP213 and SP214. I-group contains SP130, SP133 and SP136. L-group contains SP46, 12


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SP48 and SP50. All error bars represent the value of standard deviation which were

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caculated from three repeated experiments.

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Figure 5. Determination of the GFP expression of representative promoters from the

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SPL by SDS-PAGE. The gels were stained with Coomassine brilliant blue G-250.

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Lane 1, Protein Marker; Lanes 2-10, SP214, SP213, SP212, SP136, SP133, SP130,

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SP50, SP48, SP46. Lane 11, Negative control, plasmid of pAD123-P43 without gfp.

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Red arrow indicates GFP (~27 KDa).

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Model-based statistical analysis of promoter sequences

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It would be extremely valuable for metabolic engineering and synthetic biology to

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be able to rationally design promoters with precisely the desired strengths. In previous

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research, a method based on an analysis of the probability distribution of

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position/nucleotide combinations was developed to find nucleotide positions that have

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an influence on the strength of a promoter.32, 33 In this work, we present a similar

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comprehensive analysis of the sequence structures in the SPL. A statistical model was

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established to relate features of sequences and strengths of the corresponding

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promoters.

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The model-based analysis was implemented in the classes of strong and weak 13



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promoters, and a set of probabilities of position/nucleotide pairs was determined using

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equation (1). Position/nucleotide pairs that have a high p-value are shown on the

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x-axis (Figure 6a, Figure 6b and Figure S2). Using this technique, a number of

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high-frequency and low-frequency position/nucleotide pairs could be clearly

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identified as having a high influence on promoter strength. Here, the variable is a

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key parameter for the model, which is strongly related to the probability value and

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reliability of statistical data. The value was too high to obtain enough

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high-frequency position/nucleotide pairs. Otherwise, the statistical results are

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unreliability. When was 10, a number of high-frequency position/nucleotide

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combinations were determined in the class of strong promoters (Figure. 6a). The

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redesign

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position/nucleotide pairs. To design higher strength promoter directly, the

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position/nucleotide

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high-frequency pairs shown in Figure. 6a. The sequences of the promoter Pm1 and

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Pm2 were obtained, and their strength were measured in plasmid pAD123-Pm-gfp via

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GFP fluorescence. Compared to promoter P43, a 1.2-fold increase in terms of GFP

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fluorescence was achieved (Figure S3). This result demonstrated that model-based

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analysis of the SPL was able to effectively improve the promoter strength. However,

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the high-frequency position/nucleotide combinations could not be obtained with

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higher values, and only two high-frequency pairs were obtained, at =15 (Fig. 6b).

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The statistical results were not used to design strong promoter sequences directly

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because the high-frequency pairs were inadequate. However, a series of

of

promoter

pairs

was

of

implemented

SP214

were

based

replaced

14


on

by

the

the

high-frequency

corresponding

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low-frequency position/nucleotide pairs were obtained, which means that these

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position/nucleotide pairs rarely appear in strong promoters. We were able to predict

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the intensity range of certain promoters indirectly via the low-frequency pairs.

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In the class of weak promoters, similar results of low-frequency pairs were obtained

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when was 50 (Figure S2). It means that these low-frequency pairs could be used as

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reference when designing strong promoters. Consequently, improved promoters could

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be designed by analyzing high-frequency position/nucleotide pairs with appropriate

283

values. When the high-frequency pairs were inadequate, the low-frequency pairs were

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used for indirect analysis.

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286 287

Figure 6. Probability that a certain nucleotide at a certain position in promoter occurs

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more than x times in the promoters classified as strong, assuming it follows a 15



289

binomial distribution. Only position/nucleotide combinations with more than 10 (a) or

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15 (b) and with a p-value of more than 0.5 were retained.

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The method of statistical analysis is a quantitative prediction model and focused on

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the influence of single-base/position combinations. The model was used directly to

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design promoter based on replacing original position/nucleotide by the high-frequency

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pairs.

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Nonetheless, the accuracy and rationality of the model-based analysis were

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disturbed by the classification of the promoters. The Partial Least Squares (PLS)

297

regression does not have the above mentioned limitations,34 and was consequently

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used to link the promoter sequences to their strengths via matrices of lower

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dimensionality based on latent variables. This generalization of multiple linear

300

regression can be used to analyze data with strongly collinear and numerous

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independent variables as is the case for the SPL under study.

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The data-set was randomly divided into two parts: the training set, containing 180

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of the 214 promoters, and the test set, containing the remaining 3432, 35. The PLS

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model was built using the training set. The latent variables were determined using a

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previously described method.35 In this procedure, 16 latent variables were retained in

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the PLS model (when we kept 5 decimal places after the decimal point of PLS

307

R-squared).

16


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Figure. 7. The predicted promoter strength (predicted) versus the observed promoter

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strength (original) of the training set and the test set. The R criterion was given as the

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relative error sum of squares.

312 313

Subsequently, the predictive ability of the model was assessed. The strengths of the

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promoters from the test set were predicted by the fully trained PLS model. The

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predicted strengths versus the observed strength are shown in Figure 7. The strengths

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of almost all of the 34 test samples were predicted reasonably well. The R criterion

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was given as relative error sum of squares. In this work, the R2 was 0.72. This result

318

thus indicated a satisfactory correlation of promoter strength to its sequence. However,

319

in modeling PLS, the procedure is easy to occur over-fitting due to retaining different

320

latent variables. The PLS regression is more suitable for verify qualitatively

321

correlation of sequences with strengths. Hence, the statistical model-based analysis of

322

promoter sequences presented here was deemed more reasonable to design

323

quantitatively promoter. 17



324 325

Construction of tandem promoter clusters using the SPL

326

Although, stronger promoters were successfully obtained by redesigning promoter

327

based on the model-based analysis of SPL, a more dramatically improved promoter

328

was required for recombinant protein production. In terms of the structure of promoter

329

sequence in our SPL, only one promoter sequence was designed and involved. We

330

didn’t obtain a synthetic promoter that was stronger than promoter P43, which

331

contains two promoter sequences and is recognized by two sigma factors (sigma A

332

and sigma B).21 To obtain a higher strength of the synthetic promoter, we developed a

333

strategy to improve the transcriptional strength by constructing tandem promoter

334

clusters consisting of multiple recognition regions of sigma factors that associate with

335

RNA polymerase in B. subtilis (Figure 8a). For the construction and characterization

336

of tandem promoter clusters, we also chose the pAD123 as the cloning vector and gfp

337

gene as the indicator. As shown in Figure 8a, the promoter cluster TP1, which

338

consisted of two SP214 promoters aligned in tandem, was first synthesized artificially.

339

However, TP1 did not achieve the desired effect, and was only 1.2-fold stronger than

340

the SP214 promoter (Figure 8b). By contrast, TP2, which consisted of SP213 and

341

SP214 arranged in tandem, resulted in a remarkable improvement of promoter activity,

342

and was 2.95-fold stronger than the SP214. Moreover, the strength of TP2 exceeded

343

that of P43, corresponding to a 177% increase. In order to further improve the

344

strength of the promoter clusters, TP3 and TP4 were constructed by tandem

345

arrangements of corresponding promoters (Figure 8a). However, there was little 18


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improvement in the promoter strength of TP3 and TP4. It was difficult to prepare

347

excessive tandem repeats due to their self-recombination effort36. In light of

348

convenience and stability, the promoter cluster TP2 has the most potential for

349

practical applications, since it is more amenable to genetic manipulation owing to a

350

lack of superabundant repetitive sequences.

351

352 353 354

Figure 8. Construction and charaterization of promoter clusters. a Architecture of

355

different promoter clusters cassesstes. Multiple recognition regions of sigma A were

356

designed in promoter clusters cassesstes (-35 box, “TTGACA” and -10 box

357

“TATAAT”). b The fluorescence intensity of cells with GFP expression constructs

358

driven by different promoter clusters. Promoters SP214 and P43 were used as

359

controls.

360 19



361

Modification of purine pathway for inosine production by fine-tuning expression

362

of purA using synthetic weak promoters

363

Adenylosuccinate synthetase, encoded by purA, catalyzes the first step of the

364

conversion of IMP to AMP. Studies on inosine-overproducing B. subtilis showed a

365

significant increase of productivity in complex medium when purA gene was

366

inactivated.37, 38 However, the gene purA is an essential gene, which cannot be deleted

367

for cell growth in minimal medium. To repress the expression of purA, we previously

368

engineered strain I15 based on site saturation mutagenesis (SSM), which brought a

369

significant increase in inosine production while keeping the ability to grow in minimal

370

medium.37 This results were obtained by complex structural modeling and

371

time-consuming screening. In this work, the expression of purA was fine-tuned

372

dynamically using our SPL. Three weaker promoters, SP39, SP112 and SP144, with

373

15%, 35% and 65% of the PpurA, respectively (Figure 9b), were selected to substitute

374

the native promoter of purA in chromosome of the inosine-producing strain I12 using

375

a two-step mark-free modulation method39, resulting in strains BSP39, BSP112 and

376

BSP144 (Figure 9a).

377

These strains were further analyzed in shake flask fermentations to verify their

378

ability of inosine accumulation and cell growth. The strain BSP112 showed slower

379

growth and glucose consumption rates than BSP144 and I12 in M9 medium with 18

380

g/L original glucose. By contrast, BSP39 lost the ability to grow in M9 medium

381

because of insufficient supply of adenine due to the low expression level of purA.

382

(Figure 9c). At the same time, modulating purA resulted in an obvious improvement 20


Page 20 of 52

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383

of inosine production. The control strain I12 consumed 18 g/L glucose in 48 h and

384

accumulated 61.67 mg/L of inosine. Compared to I12, the inosine production of

385

BSP112, BSP144 and the SSM-strain I15 was increased 7.01-fold, 4.75-fold and

386

6.69-fold, respectively. The best strain BSP112, accumulated 428.67 mg/L of inosine

387

with a yield of 23.78 mg/g glucose (Figure 9d).

388

To further verify the downregulation of adenylosuccinate synthetase activity by

389

the SPL-derived weak promoters, crude enzyme extracts were prepared from different

390

engineered strains and their adenylosuccinate synthetase activities were analyzed

391

(Table 2). The SPL-modified strains and the SSM-strain showed a significantly

392

reduction of enzyme activity, which was most apparent in BSP112 (from 113.6 to 48.2

393

102 ΔA280 min-1 mg-1 protein). The introduction of the weak promoters therefore

394

clearly led to a decrease of enzyme activity and corresponding flux of IMP to AMP

395

conversion in BSP112 and BSP144. In conclusion, we successfully fine-tuned the

396

expression of a key gene in an important metabolic pathway using our promoter

397

library.

398 399 400 401

Table 2 Adenylosuccinate synthetase activity in different mutant strains Adenylosuccinate synthetase activity Strains Modifying type (102 △A280 min-1 mg-1 protein) I12

control

113.6±13.8

I15

SSM-strain

68.8±10.2

BSP112

SP112-modifying strain

48.2±9.5

BSP144

SP144-modifying strain

73.5±8.7

21



Page 22 of 52

402

a

403

synthetase activity, their corresponding inosine was increased. Data were averages of

404

values from three experiments.

SPL-modifying strain and SSM-strain showed a decreased adenylosuccinate

405

406 407

Figure 9. Modification of purine pathway for inosine production. a Metabolic

408

network of purine synthesis in B. subtilis and metabolic engineering strategies for

409

inosine production. Modified genes for improving inosine production are highlighted

410

in Bold. × indicates metabolic reactions that have been blocked by gene deletions.

411

Dotted arrow indicate step that are repressed by metabolic engineering strategies.

412

Abbreviations:

413

5-phospho-α-D-ribosyl-1-pyrophosphate; IMP, inosine 5’-mono-phosphate ； GMP,

414

guanosine

Ru-5-P,

5’-momo-phosphate;

Ribose-5-phosphate;

GTP,

guanosine

22


5’-tri-phosphate;

PRPP,

sAMP,

Page 23 of 52 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


415

succinyladenosine mono-phosphate; AMP, adenosine 5’-momo-phosphate ； ATP,

416

adenosine 5’-tri-phosphate. b Promoters weaker than the native purA promoter

417

(PpurA). The strength of PpurA was measured in plasmid pAD123-PpurA-gfp via

418

GFP fluorescence. The relative activity is the strength of each promoter compared to

419

the promoter P43. The error bars indicate the standard deviations of biological

420

triplicates (three independent experiments with the same exconjugant). c Cell growth

421

curves and residual glucose during shake-flask fermentation. d Comparison of inosine

422

production and yield between engineered strains developed using different metabolic

423

engineering strategies. BSP112, SP112-purA; BSP144, SP144-purA; I15, purAP242N.

424

All error bars represent the value of standard deviation which were caculated from

425

three repeated experiments.

426 427

Production of acetoin by expression of xylanase XynA driven by synthetic

428

promoter clusters

429

The applicability of SPL was extended by constructing tandem promoter clusters.

430

To demonstrate an application of the promoter clusters, the strongest promoter cluster

431

TP2 was used to overexpress the xylanase XynA in B. subtilis. XynA xylanase,

432

encoded by xynA in B. subtilis, is a key enzyme in the endoxylanase system for

433

utilization of xylan.40 Overexpression of xynA in B. subtilis, which promoted the

434

depolymerization of xylan, significantly improved the utilization of xylan.

435

In our previous study, we developed a B. subtilis strain 168ARSRCP∆acoA∆bdhA

436

which harbors three point mutations that enable it to efficiently utilize xylose to 23



437

produce acetoin under microaerobic conditions.41 In this work, xynA overexpression

438

was conducted based on the plasmid pHP13 using the promoter cluster TP2 to

439

improve the xylan-utilization capacity of strain 168ARSRCP∆acoA∆bdhA, with P43

440

promoter as control. The resulting strain BSDY harboring pHP13-TP2-xynA exhibited

441

higher growth rate under aerobiotic conditions in minimal medium containing xylan

442

than BS201, which contained pHP13-P43-xynA (Figure 10a). Moreover, the

443

maximum OD600 of BSDY (OD600=7.98) was higher than that of BS201 (OD600=6.84)

444

after 66 h. In addition, xylose was accumulated to a concentration of 2.33 g/L, which

445

was higher than that of strain BS201 (Figure 10a). This results can be attributed to the

446

fact that more xylan was converted into xylose due to a higher expression level of

447

xynA in the strain that uses the promoter TP2. In order to further validate the promoter

448

cluster’s activities and potential in metabolic engineering, the performance of acetoin

449

production from xylan of the strain BSDY was explored under microaerobic

450

conditions. As shown in Figure 10b, the strain BSDY had distinct advantages over

451

BS201 in the growth rate and utilization of xylan. At the same time, the strain BSDY

452

produced 2.81g/l acetoin from xylan in 60h, representing a 44% increase over BS201,

453

as expected. The higher acetoin titer of BSDY resulted from increased substrate

454

consumption due to higher xylanase activity.

455

To further validate the promoter activities, the endoxylanase activities of BSDY

456

and BS201 were analyzed. The strain BSDY exhibited a higher endoxylanase activity

457

of 684.7±3.5 U/L protein than that of strain BS201, which only had 344.2±3.3 U/L.

458

These results confirmed that the expression of XynA under the different promoters 24


Page 24 of 52

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459

was well correlated with the promoter strengths.

460 461

Figure 10. Fermentations of strain BS201 and BSDY under aerobic and microerobic

462

conditions. a The cell growth and xylose consumption of engineered strains in M9

463

xylan minimal medium under aerobic conditions. b Production of acetoin by strains

464

BS201 and BSDY in M9 xylan minimal medium under microaerobic conditions. The

465

error bars represent the standard deviations calculated from duplicates.

466 467

Discussion

468

As a commonly used gene expression host, B. subtilis has been successfully used to

469

produce many useful chemicals.42 In recent studies, promoter engineering of B.

470

subtilis based on endogenous promoters was widely employed in the production of

471

industrial enzymes.23,

472

promoter libraries were screened and characterized under different conditions.20, 21, 46

473

However, the isolation and characterization of native promoter can be tedious and

474

dependent on the specific genetic-context. Synthetic promoter libraries offer a rapid,

475

easy and efficient strategy to obtain suitable promoters for a specific application, and

476

as such have been widely employed in various industrial strains. To the best of our

43-45

Furthermore, endogenous and endogenous-dependent

25



477

knowledge, this is the first report of a fully non-native synthetic promoter library for B.

478

subtilis, which is independent of any endogenous promoter. The similar strategies of

479

SPL construction have been also established in other bacteria14, 31, 47, 48 and yeast49, 50,

480

but the majority of which were dependent on certain endogenous promoter or

481

completely random sequences. The library used in this study was reliably designed

482

based on specific microarray transcriptome data, enabling it to overcome the

483

limitations of endogenous promoter and random screening. The SPL spanned a wide

484

range of promoter strengths and was flexibly applied to gene downregulation and

485

overexpression in different genetic-contexts. As suspected, the relative promoter

486

strengths revealed by the GFP reporter, RT-PCR, and SDS-PAGE were consistent in

487

the same host strain. Furthermore, the synthetic promoters were short enough (52 bp)

488

to easily be incorporated into PCR primers and directly inserted in front of a gene or

489

operon. These results show that the SPL constructed in this study may be useful as a

490

plug-and-play synthetic biology toolbox for complex metabolic engineering goals in B.

491

subtilis.

492

During optimizing and analysis of metabolic networks, generating a dynamic range

493

of transcriptional levels is necessary to achieve diverse metabolic engineering goals.51

494

However, one challenge is that the limited number of synthetic biology tools restricts

495

the implementation of complex metabolic strategies. In our SPL, strong promoters as

496

well as tandem promoter clusters were generated for the overexpression of a key gene.

497

At the same time, the regulation of essential genes that require only low expression

498

levels for maintaining growth would benefit from weak promoters. As a toolkit, the 26


Page 26 of 52

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499

library can satisfy the needs of metabolic pathway regulation and can be helpful for

500

achieving of complex synthetic biology designs.

501

Although the synthetic promoter libraries have already been important regulatory

502

elements for developing different hosts as microbial cell factories, most of SPL were

503

constructed for up-regulation. In this study, our SPL could work for both

504

down-regulation and up-regulation in B. subtilis.

505

The ability to dynamically perturbing gene expression plays important roles in the

506

regulation of metabolic networks in bacteria, especially for essential genes, which

507

cannot be statically down-regulated by gene knockout approaches. In this work, the

508

SPL was employed to regulate the essential gene purA using weak promoters to

509

improve inosine production in strain I12. The engineered strain BSP112 produced

510

428.67 mg/L of inosine, a 7.01-fold increase compared to I12. Importantly, this strain

511

kept the ability to grow in inexpensive minimal medium. The performance of the

512

strain BSP112 regarding cell growth and inosine production was similar to that of

513

SSM-strain I15, which harbors the leaky mutation purAp242N. These results indicated

514

that both promoter engineering and site saturation mutagenesis are effective strategies

515

for metabolic engineering. Once a universal SPL with a wide-range of strengths is

516

obtained, promoter engineering becomes more rapid and efficient than other strategies

517

that employ complex design and high-throughput screening. Consequently, the

518

synthetic promoters in our library with tiny increments in strength can be used as tool

519

cassettes to achieve precise metabolic regulation goals in fine-tuned metabolic

520

networks for the production of target products. 27



Page 28 of 52

521

Typical experiments in genetic engineering also include the overexpression of a

522

gene of interest. We showed that our SPL can be successfully used for acetoin

523

production from xylan through the overexpression of xynA. XynA converts xylan to

524

xylose, which leads to an increase of biomass in xylose-utilizing strains. When the

525

promoter TP2, which is a tandem derivative of the SPL promoters, was used to

526

express xynA, the production of acetoin in the 168ARSRCP∆acoA∆bdhA host was

527

increased by 44% compared with the P43 promoter. In particular, the utilization of

528

xylan was successfully improved by SPL in biochemical production process of B.

529

subtilis, which will be beneficial in metabolic potential of B. subtilis for direct

530

conversion of hemicellulose to chemical feedstocks. Hence, SPL has great potential in

531

microbial biotechnology and production.

532

Synthetic biology requires accurate biological regulatory elements to design genetic

533

circuits in which the expression levels of the genetic components are tuned to an

534

appropriate input level for the next section of the circuit.52 Some examples of such

535

“tunability” have been achieved by rationally designing promoter sequences to adjust

536

their strengths using model-based prediction algorithms.48, 53 Furthermore, promoter

537

engineering is becoming an enabling technology to achieve the aims of rational design

538

and prediction of promoter elements.54 Some models have been established by

539

characterizing and analyzing core motifs of native promoters to estimate promoter

540

strengths based on thermodynamic and energetic principles.54,

541

conserved regions and core motifs were determined in advance, and the strength

542

gradient of SPL was created by introducing non-conserved sequences. Thus, these 28


55

In this study,

Page 29 of 52 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


543

models were not suitable for our SPL. In this study, model-based statistical analysis

544

and PLS regression were established, and these two models were useful tools to

545

rationally design a suitable promoter. Finally, we present a comprehensive statistical

546

analysis of non-conserved sequences in the SPL. This method focused on the

547

influence of single-base/position combinations. We developed a modular procedure

548

that was moderately predictive of promoter strength and showed that finding

549

high-frequency position/nucleotide combinations continued to improve the strength of

550

strongest promoter in SPL. Finally, the strengths of the redesigning promoter Pm1 and

551

Pm2 were increased by 20% compared to P43. These results have significant

552

implications for understanding the structure and rational design of promoters. Our

553

results also point to the significant challenges remaining before we are able to

554

understand more complex sequence structures and acquire stronger promoters by

555

model-based analysis of SPL. Furthermore, the method based on probability

556

distribution of position/nucleotide combinations could be used as a supplemental

557

strategy for models based on core motifs. We speculated that future promoter design

558

will likely focus on model-predicted conserved regions and statistical model-analysis

559

of non-conserved regions.

560

Another technology for improving strength of promoters is based on tandem

561

promoter clusters. A regulatory mechanism for improving gene expression has been

562

engineered in E. coli by using promoter clusters consisting of the same tac promoter56

563

or Pvgb promoter arranged in tandem repeats57. However, in this work, a tandem

564

repeat of the SP214 promoter did not achieve desired result in B. subtilis. Another 29



565

strategy widely used for developing stronger promoters is based on a dual-promoter

566

system, comprising two different promoters in tandem43. In a similar way, a TP2

567

dual-promoter exhibited the best performance, almost 3-fold stronger than that of P43.

568

This phenomenon was in accordance with previous reports in which the

569

transcriptional level was improved by using a dual-promoter system in B. subtilis43.

570

However, further attempts (TP3 and TP4) did not result in significant increases in

571

strength of promoter clusters (increased by 2.6% and 3.8%), which might be due to

572

more complex effects in the promoter region. Apparently, for promoter clusters,

573

excessive repeats and tandem arrangements were ineffective in terms of strength.

574

Nevertheless, in our work, stronger promoters were successfully obtained on the basis

575

of the original promoter library by constructing dual-promoter clusters consisting of

576

two different promoters in tandem. Therefore, it is possible to construct a derivative

577

library for enriching the range of strengths by using various original promoters in

578

tandem.

579 580

Conclusions

581

In summary, to develop more biology tools to facilitate the flexible fine-tuning of

582

genetic pathways, a synthetic promoter library with a gradient of strengths has been

583

constructed, characterized and put through a model-based analysis in B. subtilis.

584

Subsequently, model-based promoter redesign and construction of tandem promoter

585

cassettes were conducted based on the SPL. Finally, the practical applicability of

586

promoters was demonstrated by using them in two typical projects of metabolic 30


Page 30 of 52

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587

engineering in B. subtilis. We anticipate that our SPL will be of high value for the

588

design of metabolic pathways and development of synthetic biology tools. To the best

589

of our knowledge, this is the first report of a de novo synthetic promoter library for

590

Bacillus subtilis, which is independent of any native promoter. The SPL will

591

contribute to the extensive fine-tuning of genetic pathways and engineering of

592

synthetic biology parts in B. subtilis in the future.

593 594

Materials and methods

595

Strains, media and growth conditions.

596

All bacterial strains and plasmids used in this work are listed in Table 1. E. coli.

597

DH5α was used as the host strain for cloning and plasmid construction. B. subtilis 168

598

was used as the host for promoter library construction. All other B. subtilis strains

599

were derived from the wild-type B. subtilis168. Luria-Bertani (LB) medium was used

600

for plasmid construction in E. coli. SOC medium was used for transformed cell

601

recovery. M9 medium supplemented with glucose was used for inosine production

602

and test of physiological characterizations. M9 medium plus xylan was used for

603

acetoin production. 5FU medium was used for the selection of marker-free engineered

604

colonies of B. subtilis.39 During strain construction, the cultures were grown

605

aerobically at 37 °C in LB medium. When required, antibiotics were added to the

606

media at the following concentrations: 100 µg/ml ampicillin and 10 µg/ml

607

chloramphenicol for E. coli selection; 5 µg/ml chloramphenicol for B. subtilis

608

selection. 31



609

Strains were stored at -80 °C and revived by streaking on LB agar plates. Single

610

colonies were transferred into 5 mL of the indicated medium containing

611

corresponding antibiotics when required. All cultivations were performed at 37 °C.

612

To test the inosine biosynthetic activity of the strains, a single colony was transferred

613

into 5 ml of LB medium containing corresponding antibiotics and incubated at 220

614

rpm for 12 h to prepare the inocula. Then inocula were then added to flasks (500 mL)

615

containing 50 mL of M9 medium with 18 g/L glucose (initial OD600=0.05). For

616

fermentation from xylan, the seed culture was prepared in a 250-mL shake flask

617

containing 50 mL of M9 medium with 20 g/L xylan (1% v/v inoculum, 220 rpm, 12 h),

618

then cells were inoculated into 100 mL corresponding culture in a 250-mL flask with

619

silica gel plug kept agitated at a speed of 100 rpm with an initial OD600 of 0.05 for the

620

microaerobic fermentation. The aerobic fermentation from xylan was implemented

621

under the same medium and conditions as microaerobic fermentation, except 50 mL

622

culture with 220 rpm. Tryptophan (50 mg/L) was added to the M9 medium for all B.

623

subtilis strains. Cell growth was determined by measuring the optical density at 600

624

nm (OD600) using a UV-Vis spectrophotometer.

625 626

Plasmids construction

627

All primers used in this study are listed in Table S1. The fragments containing

628

synthetic promoters were individually fused to a truncated gapA fragment for easy

629

cloning, which was amplified from the B. subtilis 168 genome using SPL-F and the

630

corresponding reverse primers with embedded synthetic promoter sequences. The 32


Page 32 of 52

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631

PCR products were digested with KpnI-BamHI, and cloned into the same restriction

632

sites of pAD123-gfp to create a series of pAD123-gfp derivatives. The tandem

633

promoter clusters TP1, TP2 and TP3 were synthesized artificially and ligated with

634

KpnI-BamHI

635

pAD123-TP1-gfp, pAD123-TP2-gfp and pAD123-TP3-gfp. The TP1 was digested

636

with BglII-BamHI, and ligated with BamHI sites of plasmid pAD123-TP1-gfp,

637

yielding pAD123-TP4-gfp.

sites

of

plasmid

of

pAD123-gfp,

resulting

the

plasmids

638

For markerless replacement of the native promoter of purA, the purA upstream

639

fragment purA-F was first amplified from the B. subtilis genome using the primers

640

purA-F-U/L. Then, the downstream fragment SP39-purA-B was amplified from the B.

641

subtilis genome using the primers purA-B-SP39-U and purA-B-L, whereby promoter

642

SP39 was placed upstream of the purA gene. The two fragments were fused and

643

amplified by overlap-extension PCR with primers purA-FsnU/L. The fused fragment

644

was then digested with SalI-BamHI, and was ligated into the same digested sites of

645

pSS

646

pSS-SP144-purAFB were created with corresponding primers for the downstream

647

fragments.

to

create

pSS-SP39-purAFB.

Analogously,

pSS-SP112-purAFB

and

648

For the overexpression of xynA, the xynA gene and promoter P43 were amplified

649

from the B. subtilis 168 genome using the primers xynA-201U/L and P43-U/L.

650

Subsequently fragments xynA and P43 were cloned into plasmid pHP13 to yield

651

pHP13-P43-xynA. Plasmid pHP13-TP2-xynA was created with corresponding primers

652

for fragments xynA and TP2. Promoter TP2 was amplified from plasmid 33



Page 34 of 52

653

pAD123-TP2-gfp. The method used for these constructs was based on Gibson

654

assembly.58

655

Strains construction

656

The construction of BSP39 was based on a mutation delivery system as

657

described previously by Shi et al39. The plasmid pSS-SP39-purAFB was integrated

658

into strain I12 chromosome by first single-crossover chromosomal transformation and

659

the transformant was selected by chloramphenicol. Next, the resulting transformant

660

was cultured in LB liquid medium for 12 h, and then the cells were spread on a 5FU

661

medium plate. The grown colonies on 5FU plate were verified by PCR and Sanger

662

sequencing to confirm that the upp-cassette was popped out. After the upp-cassette

663

recycling event, the promoter SP39 was introduced upstream of purA locus, which

664

was denoted as BSP39. Analogously, BSP112 and BSP144 were constructed with

665

plasmids pSS-SP112-purAFB and pSS-SP144-purAFB. Plasmids of pHP13-TP2-xynA

666

and pHP13-P43-xynA were transformed into 168ARSRCP∆acoA∆bdhA to yield

667

BSDY and BS201.

668 669 670

Table 1 Strains and plasmids used in this study Name

Relevant genotype

Source/reference

B. subtilis 168

Wild-type strain, trpC2

BGSCa

E. coli. DH5α

Cloning host

Invitrogen

I12

Inosine-producing strain

37

I15

I12, purAP242N

37

BSP39

I12, SP39-purA

This study

Strains

34


Page 35 of 52 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


BSP112

I12, SP112-purA

This study

BSP144

I12, SP144-purA

This study

168ARSRCP

B. subtilis 168araR*

41

∆acoA∆bdhA

sinR*comP*∆acoA∆bdhA

BS201

168ARSRCP∆acoA∆bdhA

This study

harboring pHP13-P43-xynA BSDY

168ARSRCP∆acoA∆bdhA

This study

harboring pHP13-TP2-xynA Plasmids pAD123-gfp

Cmr, B. subtilis/E. coli shuttle vector, Lab stock for the expression of gfp

pAD123-SPL-gfp

pAD123-gfp derivative with

This study

synthetic promoter in front of gfp pAD123-SP212-gfp


This study

SP212 in front of gfp pAD123-SP213-gfp


This study



This study



This study



This study



This study



This study


pAD123-gfp derivative with SP48 in front of gfp 35


This study


pAD123-SP50-gfp


Page 36 of 52

This study

SP50 in front of gfp pAD123-PpurA-gfp


This study

PpurA in fromt of gfp pAD123-Pm1-gfp


This study

Pm1 in front of gfp pAD123-Pm2-gfp


This study

Pm1 in front of gfp pAD123-TP1-gfp


This study

TP1 in front of gfp pAD123-TP2-gfp


This study



This study



This study

TP4 in front of gfp pSS

Ampr, Cmr, pUC18 containing

39

the cat-upp cassette pSS-SP80-purAFB

pSS containing purA

This study

flanks under SP80 pSS-SP30-purAFB

pSS containing purA

This study

flanks under SP30 pSS-SP13-purAFB

pSS containing purA

This study

flanks under SP13 pHP13

Cmr, Emr,B. subtilis/E.coli

Lab stock

shuttle vector pHP13-TP2-xynA

derived from pHP13, for overexpression of xynA under TP2 promoter 36


This study

Page 37 of 52 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


pHP13-P43-xynA

derived from pHP13,

This study

for overexpression of xynA under P43 promoter 671

a

Bacillus Genetic Stock Center

672 673

Generation of the synthetic promoter library

674

The synthetic promoter library was constructed using the degenerate primer

675

SPL-L, containing 26 bp of the degenerate oligonucleotide N (with a 25% possibility

676

of each of the A, G, C, and T bases). The fragment containing the synthetic promoter

677

fused to a truncated gapA fragment was amplified from the B. subtilis168 genome

678

using the primers SPL-F and SPL-L. The synthetic promoter library was generated in

679

pAD123-gfp-SPL. Plasmid pAD123-gfp-SPL was then introduced into E. coli DH5α,

680

and transformed cells were cultured in SOC medium for recovery. The plasmids with

681

synthetic promoters were purified and stored. After cell cultivation and plasmid

682

preparation, the purified plasmid library was finally transferred into B. subtilis 168.

683

The transformation of B. subtilis was performed using a standard protocol for natural

684

competence.59 Transformed cells were cultivated on LB agar plates at 37 °C for 24 h.

685

All colonies were collected and stored at -80 °C as a 15% glycerol stock.

686 687

Library screening using a GFP reporter gene assay

688

Cells harboring the promoters were grown in LB medium at 220 rpm and 37 °C.

689

The expression of GFP was monitored by measuring whole-cell fluorescence on a

690

multimode microplate reader at stationary phase (OD600 of 4.0-6.0). The OD600 of 37



691

cells were firstly measured, then cells were centrifuged at 10 000 × g for 2 minutes,

692

the supernatant was discarded, and the cells resuspended in an equal volume of double

693

distilled water. A 200-µl sample was transferred to a black 96-well plate, and the GFP

694

fluorescence was measured at 533 nm after excitation at 485 nm using a plate reader

695

(Tecan). The activity of GFP was characterized by using GFP fluorescence/OD600. B.

696

subtilis 168 carrying the plasmid pAD123-gfp without a promoter sequence in front of

697

the gfp gene was used as the negative control and double distilled water was used as a

698

blank. Standard deviations are based on a minimum of three statistically independent

699

experiments.

700 701

Model-based analysis of promoter sequences

702

Promoter sequences were analyzed by a published statistical method32 for

703

identifying correlations between nucleotide positions and strengths of promoters. The

704

promoters were firstly divided into two classes based on the strength of promoter

705

Pveg: strong and weak, containing 49 and 165 promoters, respectively. The

706

probability of finding the nucleotide under consideration follows a binomial

707

distribution with chance p and population size q. The actual probability that a

708

nucleotide at given position occurs more than times in a given class was calculated

709

using equation (1).

− ≥ = 1 − 1 −

710

The position/nucleotide pairs with high p-values were obtained using statistical

711

calculation. The p-value was defined as ≥ , when ≥ > 0.5. 38


Page 38 of 52

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712

Otherwise, the p-value was defined as 1- ≥ . when ≥ ≤ 0.5. Finally,

713

position/nucleotide pairs with high p-values were displayed.

714

The value was used to evaluate the reliability of probabilities. In this work, the

715

value was determined by 20% or 30% of the population size in a certain class

716

(x=10 or 15 in the strong class and x=50 in the weak class) for obtaining appropriate

717

statistical model.

718 719

Analysis of fermentation products and metabolites

720

The concentrations of acetoin and xylose were determined by using HPLC

721

(HP1100, Agilent Technologies, Palo Alto, USA) equipped with a ion exclusion

722

Aminex HPX 87-H column (Bio-Rad, Richmond, USA) with 5 mM H2SO4

723

(0.4ml/min) as the mobile phase at 65 °C.Inosine concentrations in the culture broth

724

were measured by RP-HPLC (HP 1100, Agilent Technologies, USA) equipped with a

725

C18 column

726

mobile phase at room temperature. Glucose concentrations in the culture broth were

727

determined enzymatically by a bioanalyzer (SBA-40E, Shandong, China).

(Luna 150 ×4.6 mm) with 4% (v/v) acetonitrile (0.8 ml/min) as the

728 729

Real-time quantitative PCR (RT-PCR)

730

B. subtilis168 and its derivatives were harvested when grown to the exponential

731

phase under aerobic conditions. Total RNA was extracted using the RNA prep pure

732

Kit (TransGen Beijing, China). 500 ng of total RNA was transcribed into cDNA using

733

the Quant Reverse Transcriptase with random primers (TransGen Beijing, China). 39



734

Samples were then analyzed using a Light Cycler 480 II (Roche, Basel, Switerland)

735

with Real Master Mix (SYBR Green). The 16S rRNA gene was selected as a

736

reference for normalization and three biological replicates were performed. The

737

obtained data were analyzed by using the 2−∆∆Ct method as described previously.60

738

SDS-PAGE analysis of reporter proteins

739

After 16 h of cultivation, cells were harvested and lysed completely in isotonic PBS.

740

An aliquot comprising 20 µl of the supernatant containing GFP was subjected to

741

SDS-PAGE. SDS-PAGE was performed using a 4% acrylamide stacking gel and 12%

742

acrylamide resolving gel. Protein bands were detected using staining with Coomassie

743

brilliant blue G-250, and the areas below the GFP peaks were used to determine the

744

relative GFP amounts.

745 746

Enzyme activity assays

747

For adenylosuccinate synthase activity analysis, crude cell extracts were prepared

748

as described previously 29, and the enzyme activity in cell-free extracts was measured

749

according to a previously described method.61 The specific activity was defined as the

750

100 fold of the absorbance increase at 280 nm caused by 1 mg of enzyme extract in 1

751

min (100 × ∆A280 min-1 mg-1 protein). Total protein concentrations were determined

752

according to the Bradford method.62

753

Endoxylanase activity was determined using beech-wood xylan as substrate in

754

cell-free media by a modified method.63 The reducing monosaccharides released from

755

beech-wood xylan were measured by HPLC as described in section 2.7, with 40


Page 40 of 52

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756

D-xylose as the standard substrate for standard curves plot. One unit of enzyme

757

activity was defined as the amount of enzyme that releases 1 μmol of xylose

758

equivalents in 1 min under the described assay conditions.

759 760

ASSOCIATED CONTENT

761

Supporting Information

762

Figure S1. Oligonucleotide sequence (SPL) with consensus sequence and randomized

763

spacer sequences

764

Figure S2. Probability that a certain nucleotide at a certain position in promoter occurs

765

more than x times in the promoters classified as weak

766

Figure S3. Strengths of reconstructed promoter

767

Table S1. Primers used in this study

768

Table S2. Sequences of promoters used in this study

769

This material is available free of charge via the Internet at http://pubs,acs,org.

770 771

AUTHOR INFORMATION

772

Corresponding Author

773

Email: [email protected]

774

Author Contributions

775

D.L. and Z.W. designed the experiments; D.L., Z.M., J.G., H.M., Y.T. and L.W.

776

performed the experiments and analyzed the results; D.L., T.C. and Z.W wrote the

777

manuscript; Z.W. and X.Z. supervised the work. 41



778

Notes

779

The authors declare no competing financial interest.

780

Acknowledgement

781

This work was supported by National Natural Science Foundation of China

782

(NSFC-21576200, NSFC-21776209 and NSFC-21621004).

783 784

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51



Caption : For Table of Contents Use Only Manuscript title：Construction, model-based analysis and characterization of a promoter library for finetuned gene expression in Bacillus subtilis Authors：Dingyu Liu, Zhitao Mao, Jiaxin Guo, Leyi Wei, Hongwu Ma, Yajie Tang, Tao Chen, Zhiwen Wang* and Xueming Zhao 80x39mm (300 x 300 DPI)


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Construction, Model-Based Analysis, and Characterization of a

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