WO2025129656A1 - 一种模块化正交真核转录因子模型构建方法 - Google Patents

一种模块化正交真核转录因子模型构建方法 Download PDF

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WO2025129656A1
WO2025129656A1 PCT/CN2023/141107 CN2023141107W WO2025129656A1 WO 2025129656 A1 WO2025129656 A1 WO 2025129656A1 CN 2023141107 W CN2023141107 W CN 2023141107W WO 2025129656 A1 WO2025129656 A1 WO 2025129656A1
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transcription factor
lbd
dbd
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陈业
黎欣睿
栗曾理
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Shenzhen Institute of Advanced Technology of CAS
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    • C12N15/63—Introduction of foreign genetic material using vectors; Vectors; Use of hosts therefor; Regulation of expression
    • C12N15/79—Vectors or expression systems specially adapted for eukaryotic hosts
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    • C12N15/81—Vectors or expression systems specially adapted for eukaryotic hosts for fungi for yeasts
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  • Transcription factors can be used as a signal converter, which can affect the probability of RNA polymerase binding to the promoter by recognizing and binding to specific sites on DNA, called operator sequences, thereby affecting gene transcription. After being stimulated by external chemical or physical signals, transcription factors undergo a series of structural changes to produce different operator sequence binding affinities, bind to the promoter or fall off the promoter, thereby affecting the transcription and expression of downstream genes. Transcription factors that bind to DNA must have three characteristics: 1 ability to bind to specific DNA sequences; 2 ability to respond to signals; 3 ability to control transcription (Schleif, RF, Modulation of DNA binding by gene-specific transcription factors. Biochemistry, 2013.
  • transcription factors are composed of DNA binding domains, ligand binding domains, and transcription activation domains.
  • Each domain can be described by several reaction equations when performing its function.
  • Each reaction equation can be abstracted into a parameter - the reaction equilibrium constant. Therefore, in our Saccharomyces cerevisiae host, a certain domain of a specific sequence can be abstracted into a specific parameter, and different domains with different parameters together constitute a complete transcription factor with a specific transcriptional regulatory behavior, and the behavior of the transcription factor in a specific transcription system is described by the reaction equation.
  • transcription factors commonly used for transcriptional regulation in eukaryotic cells can be divided into two categories according to their sources: prokaryotic natural host transcription factors and artificially synthesized transcription factors. LacI, TetR, and XylR from prokaryotes are induced by IPTG, aTc, and xylose, respectively, and applied to eukaryotic cells (Chen, Y., et al., Genetic circuit design automation for yeast. Nature Microbiology, 2020.5(11): p.1349-1360.).
  • modular DBD, LBD, and AD were assembled to form artificial transcription factors XEV and lexA-ER-VP16 commonly used in eukaryotic systems (Louvion, J.F., B.Havaux-Copf, and D.Picard, Fusion of GAL4-VP16 to a steroid-binding domain provides a tool for gratuitous induction of galactose-responsive genes in yeast. Gene, 1993.131(1): p.129-34.).
  • the optimization of the transcriptional regulation process can be divided into two aspects: the optimization of the performance parameters of the transcription factor itself and the optimization of the transcriptional regulation mode.
  • Khalil et al. proposed a series of mutually orthogonal zinc finger libraries with different regulatory activities corresponding to different transcription factor binding affinity parameters for DNA.
  • high-affinity zinc finger DNA binding modules By using high-affinity zinc finger DNA binding modules, the performance of the transcription factor itself can be optimized (Khalil, AS, et al., A synthetic biology framework for programming eukaryotic transcription functions. Cell, 2012. 150 (3): p. 647-58.).
  • the output promoter of 8 operators can achieve a regulation factor of ⁇ 60 times, which is ⁇ 10 times that of a single operator promoter (Khalil, AS, et al., A synthetic biology framework for programming eukaryotic transcription functions. Cell, 2012. 150 (3): p. 647-58.).
  • changes in the transcriptional regulation mode also provide an optimization idea.
  • transcription factors mostly act in a holistic form, with a poor regulatory range, high background leakage and low induction strength; there is a lack of orthogonality considerations required for multi-induction systems, and there are no multiple pairs of transcription factors with high induction ranges that exist simultaneously and do not interact with each other and the host; the existing model is based on a conformational regulatory system, which is unable to achieve modularization and effective replacement of structural domains, and has a narrow available range.
  • the present invention provides a modular orthogonal eukaryotic transcription factor model construction method, which solves the shortcomings of the prior art that eukaryotic transcription regulation is based on conformational regulation, cannot achieve modularization and effective replacement of domains, and has a narrow applicable range.
  • the present invention adopts the following technical solutions:
  • a method for constructing a modular orthogonal eukaryotic transcription factor model comprises the following steps:
  • DBD DNA binding domain
  • LBD ligand binding domain
  • AD transcription activation domain
  • DBD-LBD-AD DNA binding domain
  • LBD ligand binding domain
  • AD transcription activation domain
  • DBD-LBD-AD 1-87aa of the E. coli SOS regulatory protein lexA is used as DBD, 1-179aa of the Rhodopseudomonas palustris quorum sensing transcription factor RpaR is used as LBD, and VP16 is used as AD.
  • the screening cerevisiae strain for the DNA binding domain (DBD) in S2 is obtained by the following method: constructing a DBD screening transcription factor expression vector, constructing a corresponding reporter gene expression vector, enzymatically cutting the reporter gene expression vector to obtain a transcription factor expression fragment, integrating the transcription factor expression fragment into yeast, and obtaining a DBD screening cerevisiae strain.
  • the DBD screening transcription factor expression vector is obtained by using aTc-induced ptet as a promoter, tENO2 as a terminator, and replacing the DBD domain in the transcription factor basic structure DBD-LBD-AD with CCDB.
  • screening transcription factor expression vector sequence of the DBD is as shown in SEQ ID NO: 1.
  • a DBD corresponding reporter gene expression vector was constructed, and the corresponding reporter gene used a promoter containing two corresponding DBD-regulated operators to control the expression of yellow fluorescent protein YFP, with tENO2 as a terminator; CCDB was placed at the promoter position of the reporter gene plasmid.
  • the screening obtains effective DBD sequences such as SEQ ID NO: 7-18.
  • the screening cerevisiae strain of the ligand binding domain (LBD) in S2 is obtained by the following method: constructing a screening transcription factor expression vector of LBD, constructing a corresponding reporter gene expression vector, performing enzyme digestion on the reporter gene expression vector to obtain a transcription factor expression fragment, integrating the transcription factor expression fragment to yeast to obtain LBD screening Saccharomyces cerevisiae strains.
  • the LBD screening transcription factor expression vector is obtained by using aTc-induced ptet as a promoter, tENO2 as a terminator, and replacing the LBD domain in the transcription factor basic structure DBD-LBD-AD with CCDB.
  • LBD screening transcription factor expression vector sequence is as shown in SEQ ID NO: 2.
  • the reporter gene corresponding to the LBD corresponding reporter gene expression vector constructed in S2 uses a promoter containing two operators regulated by the corresponding DBD to control the expression of the yellow fluorescent protein YFP, with tENO2 as the terminator.
  • the screening obtains effective LBD sequences such as SEQ ID NO: 19-31.
  • the screening cerevisiae strain for the transcription activation domain (AD) in S2 is obtained by the following method: constructing an AD screening transcription factor expression vector, constructing a corresponding reporter gene expression vector, enzymatically cutting the reporter gene expression vector to obtain a transcription factor expression fragment, and integrating the transcription factor expression fragment into yeast to obtain an AD screening cerevisiae strain.
  • sequence of the AD screening transcription factor expression vector is as shown in SEQ ID NO: 3.
  • a quantitative test brewer's yeast strain for the DNA binding domain (DBD) in S3 is obtained by the following method: constructing a transcription factor expression vector for quantitative test of DBD parameters, then constructing a corresponding reporter gene vector, enzymatically cutting the reporter gene expression vector to obtain a transcription factor expression fragment, and integrating the transcription factor expression fragment into yeast to obtain a DBD quantitative test brewer's yeast strain.
  • the DBD parameter quantitative test transcription factor expression vector is obtained by using xylose-induced pxyluas as a promoter, tENO2 as a terminator, and replacing the DBD domain with CCDB.
  • the DBD parameter quantitatively tests the transcription factor expression vector sequence such as SEQ ID NO: 4.
  • the reporter gene corresponding to the reporter gene expression vector corresponding to DBD constructed in S3 uses a promoter containing an operator corresponding to DBD regulation to control the expression of yellow fluorescent protein YFP, with tENO2 as a terminator; CCDB is placed at the promoter position of the reporter gene plasmid to obtain.
  • the quantitative test brewer's yeast strain of the ligand binding domain (LBD) in S3 is obtained by the following method: constructing a transcription factor expression vector for quantitative test of LBD parameters, then constructing a corresponding reporter gene vector, enzymatically cutting the reporter gene expression vector to obtain a transcription factor expression fragment, and integrating the transcription factor expression fragment into yeast to obtain a LBD quantitative test brewer's yeast strain.
  • the parameter quantitative test of the LBD transcription factor expression vector is obtained by using xylose-induced pxyluas as a promoter, tENO2 as a terminator, and replacing the LBD domain with CCDB.
  • LBD parameter quantitative test transcription factor expression vector such as SEQ ID NO: 5.
  • the reporter gene corresponding to the LBD reporter gene expression vector constructed in S3 uses a promoter containing an operator corresponding to DBD regulation to control the expression of yellow fluorescent protein YFP, with tENO2 As a terminator.
  • the specific process of quantitative test culture is as follows: the constructed screening brewer's yeast strain is inoculated in the corresponding defective SD culture medium and cultured for a period of time, transferred to a new SD culture medium for the first time to perform an induction range test, set different xylose concentration gradients, obtain different transcription factor expression amounts, set two groups of ⁇ maximum working concentration inducers under different xylose concentrations, and obtain the regulation induction range under each transcription factor expression amount; select the transcription factor expression amount with a suitable induction range, test the induction curve under different inducer concentration gradients, continue to culture in the SD culture medium containing the corresponding xylose concentration for a period of time, set a control group and different experimental groups, transfer to the SD culture medium containing different inducer concentrations under the corresponding xylose concentration for the second time, take the bacterial solution, dilute it, detect the expression amount of fluorescent protein YFP in each group, and calculate the relative fluorescence expression amount and the regulation multiple of the transcription factor.
  • RPU (YFP test - YFP CYE72 )/(YFP CYE72/CY637 - YFP CYE72 ); wherein CYE72 was a negative control, and CYE72/CY637 was a ptet-induced control.
  • the quantitative transcriptional regulation model includes a non-nuclear receptor dimerization transcriptional activation model (without considering the nuclear entry process) and a nuclear receptor dimerization transcriptional activation model (considering the nuclear entry process);
  • the nuclear receptor dimerization transcription activation model equation is as follows:
  • the F1 factor is a parameter that describes the performance of transcription factors under a specific DBD-LBD combination
  • c is the concentration of LBD in different forms
  • I0 is the background leakage expression intensity of the specific sequence promoter
  • Imax is the theoretical maximum activation intensity of the specific sequence promoter
  • I is the inducer concentration
  • Ltot is the sum of the monomeric forms of the expression amounts of all forms of transcription factors
  • ⁇ DBD describes the behavior of DBD
  • K1, K2, and K3 describe the behavior of LBD
  • K* and K*' describe the nuclear entry process of transcription factors.
  • the method for constructing a modular orthogonal eukaryotic transcription factor model of the present invention determines the basic architecture of the modular transcription factor, ultimately establishes a quantitative model of transcriptional regulation, and parameterizes the modular domain of the transcription factor; the modular domain parameters of the transcription factor can be optimized through the quantitative model, and a transcription factor with optimized performance is obtained.
  • the present invention determines the optimization effect of introducing the synergistic dimerization process into the transcriptional regulation process on transcriptional regulation, establishes a domain library with different parameter ranges for each domain, and establishes a domain library with mutually orthogonal DBD ⁇ operator and LBD ⁇ inducer levels, providing tools for the realization of complex gene regulation circuits.
  • FIG1 is a schematic diagram of the basic structure of the modular domain transcription factor of the present invention.
  • FIG2 is a schematic diagram of a DBD domain screening test vector and system constructed by the present invention.
  • FIG3 is a schematic diagram of a LBD domain screening test vector and system constructed by the present invention.
  • FIG4 is a schematic diagram of an AD domain screening test vector and system constructed by the present invention.
  • FIG5 is a DBD domain quantitative test vector constructed by the present invention.
  • FIG6 is a quantitative test vector for LBD domain constructed by the present invention.
  • FIG7 is a transcription factor quantitative test vector constructed by the present invention.
  • FIG8 is a diagram showing the effective DBD test results and orthogonality of the present invention.
  • FIG10 is an effective AD test result of the present invention.
  • FIG12 is a quantitative test result of the present invention.
  • FIG13 is an orthogonal table of LBD ⁇ inducer of the present invention.
  • FIG15 is a partial parameter value of the preliminary fitting of the model of the present invention.
  • FIG. 16 is a diagram showing the optimization guided by the model of the present invention.
  • yeast screening test culture conditions in the following examples are as follows:
  • yeast transformants After obtaining the yeast transformants, they were inoculated into a 96-deep-well plate containing 500 ⁇ l of the corresponding defective SD medium, and then cultured at 30°C and 800 rpm for 24 hours, and then transferred to a new 96-deep-well plate with SD medium at a ratio of 1:200.
  • each experimental group was set up with non-induced--, adding inducer anhydrotetracycline aTc+- (working concentration: 100 ng/ml) or the corresponding inducer-+ at the maximum working concentration, or both adding ++ groups.
  • yeast quantitative test culture conditions in the following examples are as follows:
  • yeast transformants After obtaining the yeast transformants, they were inoculated into a 96-deep-well plate containing 500 ⁇ l of the corresponding defective SD medium and cultured at 30°C and 800 rpm for 24 h. Then, they were transferred to a new 96-deep-well plate with SD medium at a ratio of 1:200 for the first time to conduct an induction range test: different xylose concentration gradients (0, 0.2, 0.3, 0.4, 0.5, 0.6, 0.8, 0.9, 1, 1.5, 2, 5, 10, 20 mM) were set according to the input promoter induction curve to obtain different transcription factor expression levels; further, ⁇ maximum working temperature was set at different xylose concentrations. Two groups of concentration inducers were made. Under the conditions of this series of experimental groups, the 96-deep-well plate was placed at 30°C and 800 rpm for 16 hours, and then the first sampling test was performed. Thus, the regulatory induction range under the expression level of each transcription factor was obtained.
  • transcription factors with a suitable induction range (generally set 0.4, 0.6, 1, 2, 10mM xylose concentration gradients), and test the induction curves under different inducer concentration gradients: after the first transfer, culture at 30°C, 800rpm for 24h, select the corresponding concentration +xylose group as the mother solution, transfer to a new SD medium 96 deep well plate at a ratio of 1:200 for the second time, and set different inducer concentration gradients under these different xylose concentrations. After culturing at 30°C, 800rpm for 16h, take samples for the second test.
  • a suitable induction range generally set 0.4, 0.6, 1, 2, 10mM xylose concentration gradients
  • a blank control group CYE72 and a constitutive expression control group CYE72/CY671 were set up for each transfer; the input promoter inducible expression control bacteria CYE72/LXR347 was used for each test to calibrate the expression of the input promoter at the corresponding xylose concentration.
  • the appropriate amount of bacterial solution was diluted with 1xPBS solution, and the expression of the fluorescent protein YFP of 10,000 cells was detected using the flow analyzer BD FACSCelesta TM FITC-A channel. The obtained data was processed with FlowJo, and the median was taken as the fluorescence value of each sample well.
  • primers 66-F (5'-GGTTCTAAGGATATCTCTGCTGGAGACATGA-3') and 66-R (5'-CATTTTTTATTTATTTTTGTAGCTTGATATTCTCTATCAC-3') were used to amplify PCR fragment 1.
  • primers CY386 (containing the lethal gene ccdb) in the laboratory as a template, primers The CCDB lethal gene was obtained by amplifying PCR fragment No.
  • DBDs of a series of transcription factors derived from prokaryotes or viruses were intercepted according to their structural characteristics to obtain the amino acid and nucleotide sequences of their DBDs (see SEQ ID NO: 7-18).
  • Different DBD sequences were obtained by gene synthesis, genomic sequences or existing plasmid sequences. AATG and GGTT scars as well as BpiI recognition sites and protective bases were added to both ends by PCR, and transcription factor plasmids containing different DBDs were constructed by the BpiI Golden Gate method.
  • the existing plasmid pXJH1 in the laboratory was used as a vector, and a reporter gene plasmid containing the corresponding DBD regulatory operator was obtained by segmented long primer PCR and overlap PCR.
  • the restriction endonuclease BsaI was used for digestion to obtain the transformed enzyme fragment.
  • the zymo Frozen-EZ Yeast Transformation II Kit TM was used to prepare the competent cells of strain CYE72, and then the enzyme-cut fragments were transferred to the competent cells of CYE72 in two steps to obtain yeast transformants.
  • test bacterial solution was obtained by yeast screening test culture, and the BD FACSCelesta TM flow analysis was used for detection.
  • Each DBD was set up with two groups: non-induced, induced expression, and induced dimerization.
  • the test results of the 12 effective DBDs screened are shown in Figure 8. As shown in Figure 8, promoters containing different operators have different degrees of basic expression strength, and the activation strength also changes with different DBDs under the expression amount under the test conditions.
  • primers 77-F (5'-GGTAGCCCTAAGAAAAAGAGAAAAGTGG-3') and 77-R (5'-GATCATGAGCGGGCTTGGCCA-3') were used to amplify PCR fragment 1.
  • primers Homo-CCDB-77-F 5'-GGCCAAGCCCGCTCATGATCAGGTCTTCTTATATTCCCCAGAACATCAG-3'
  • Homo-CCDB-77-R 5'-CTCTTTTTCTTAGGGCTACCAGGTCTTCGGCTTACTAAAAGCCAGATAAC-3'
  • restriction endonuclease BsaI was used to digest the fragments to obtain the transformed fragments.
  • the CYE72/LXR152 competent strain was prepared using the zymo Frozen-EZ Yeast Transformation II Kit TM yeast transformation kit, and the fragments were transformed to obtain yeast transformants.
  • LBDs mainly come from three types of proteins: single-domain antibodies, prokaryotic quorum sensing transcription regulatory proteins, and mammalian nuclear receptors. Under the expression level of the test conditions, different LBDs will lead to different degrees of background activation strength brought by background dimerization of transcription factors. Different LBDs correspond to different inducer concentrations, and the maximum activation strengths that different LBDs can achieve at their maximum working concentrations of the inducers are also different.
  • primers 233-F (5'-TAAAAGCTTTTGATTAAGCCTTCTAGTCCAAAAAAC-3') and 233-R (5'-CACTTTTCTCTTTTTCTTAGGGCTACCATTAC-3') were used to amplify PCR fragment No. 1.
  • restriction endonuclease BsaI was used to digest the fragments to obtain the transformed fragments.
  • the CYE72/LXR152 competent strain was prepared using the zymo Frozen-EZ Yeast Transformation II Kit TM yeast transformation kit, and the fragments were transformed to obtain yeast transformants.
  • LBD represents the transcription factor monomer protein
  • LBD 2 represents the dimer formed by two transcription factor monomer proteins
  • I represents the inducer molecule
  • LBD: I represents the intermediate form of the binding of monomer protein and inducer molecule
  • LBD 2 I 2 represents the dimer formed by two protein monomers and two inducer molecules
  • P 0 represents the inactive state promoter
  • P 1 and P 2 represent the active state promoter formed by the dimer formed by different pathways
  • the possible states of the promoter include: 1 empty promoter; 2 only binds to RNAP; 3 binds to RNAP and transcription factor background dimer at the same time; 4 binds to RNAP and transcription factor induced dimer at the same time. 3 and 4 correspond to different activity states of the promoter, and according to the partition equation, the model equation can be described as follows:
  • LBD and LBD* represent the extranuclear and intranuclear states of transcription factor monomer proteins, respectively.
  • LBD 2 and LBD 2 * represent the extranuclear and intranuclear states of the dimer formed by two transcription factor monomer proteins, respectively.
  • I represents the inducer molecule.
  • LBD: I and LBD*: I represent the intermediate forms of the binding of monomer proteins and inducer molecules outside and inside the nucleus, respectively.
  • LBD 2 : I 2 and LBD 2 *: I 2 represent the extranuclear and intranuclear states of the dimer formed by two protein monomers and two inducer molecules.
  • the process can be represented by the following equation:
  • the restriction endonuclease BsaI was used to digest the fragments to obtain the transformed fragments.
  • the CYE72 competent strain was prepared using the zymo Frozen-EZ Yeast Transformation II Kit TM yeast transformation kit, and the fragments were transferred to the CYE72 competent strain in two steps to obtain yeast transformants.
  • the logarithm of the regulation multiples of all LBDs obtained in the test to all inducers was taken to make a 10 ⁇ 10 orthogonal table, as shown in Figure 13.
  • the color of each grid in the orthogonal table corresponds to the value of the logarithm of the regulation multiple. The larger the value, the darker the color. Only the dark diagonal line indicates a completely orthogonal situation with no interaction.
  • crosstalk exists in the LBDs and inducers selected by this method, including two types: optimizable crosstalk that is weaker than the natural response (such as CinRori 2-179 to 3OC12-HSL) and non-optimizable crosstalk that is stronger than the natural response (such as TraR 1-174 to 3OC12-HSL).
  • the corresponding induction curve of LBD to the inducer is obtained by the yeast quantitative test culture method, as shown in Figure 14.
  • the test results provide fitting data of the corresponding LBD response control parameters K2' and K3' to the inducer.
  • primers 370-F (5'-CAGTGAGAAGACCTGGTAGCCCTAAGAAAAAGAGAAAAGTGG-3') and 370-R (5'-CAGTACGAAGACTACATTTTTTATTTATTTTTGTAGCTTGATATTCTAGTTTGTTG-3') were used to amplify PCR fragment 1.
  • CCDB-370-F (5'-CAGTGAAATGAGGTCTTCTTATATTCCCCAGAACATCAG-3') and CCDB-370-R (5'-TAAGCCTACCAGGTCTTCGGCTTACTAAAAGCCAGATAAC-3') were used to amplify PCR fragment 2 CCDB lethal gene.
  • the yeast transcription activator ligand binding domain parameter quantitative test vector LXR370 was obtained by Golden Gate technology using BpiI restriction endonuclease, see SEQ ID NO: 6.
  • yeast liquid was obtained by the yeast quantitative test culture method, and the induction curve was tested at the expression level given by the model, and then compared with the theoretical output results of the model.
  • Some fitting results are shown in Figure 15.
  • the experimental data can basically meet the theoretical prediction, R2>0.84, and the prediction output accuracy of the model is good.
  • the model describes the transcriptional regulation performance of a specific transcription activator in Saccharomyces cerevisiae, as shown in Figure 16a. In general, it is specifically manifested as follows: 1 The sequence of the operator corresponding to a specific DBD, as part of the promoter sequence, determines the theoretical minimum leakage and maximum transcriptional activation strength determined by the promoter; 2 The background dimerization degree k1 of LBD determines the leakage degree caused by background dimerization under the expression level of a specific transcription factor, that is, the minimum value of the induction curve under this expression level; 3 The inducible dimerization ability k2 and k3 of LBD determines its sensitivity of transcriptional regulation and the transcriptional activation strength it can achieve, that is, the EC50 and maximum activation of the curve; in general, the parameters of LBD determine the shape of the curve; 4 The affinity k4 and k5 of DBD binding to the operator and the expression level of the transcription factor make the induction curve translate in the coordinate system.

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Abstract

本发明提供一种模块化正交真核转录因子模型构建方法，包括以下步骤：S1、确立转录因子基本架构DBD-LBD-AD；S2、构建结构域筛选载体和系统，筛选得到有效的DBD、LBD和AD；S3、筛选出DBD、LBD各结构域的对应参数；S4、根据DBD、LBD各结构域的对应参数来表征转录因子调控过程，建立转录调控定量模型；通过转录调控定量模型预测不同DBD和LBD组合情况下转录因子，获得性能优化的转录因子。本发明模块化正交真核转录因子模型构建方法，通过确定了模块化转录因子的基本架构，最终建立了转录调控定量模型，实现对转录因子进行模块化结构域参数优化，获得了性能优化的转录因子。

Description

一种模块化正交真核转录因子模型构建方法 技术领域
本发明属于生物技术领域，具体涉及一种模块化正交真核转录因子模型构建方法。
背景技术
细胞能够接受外界的化学或物理信号，将其转化为生物信号，从而对环境做出响应。转录因子可以作为一种信号转化器，通过识别并结合DNA上特定位点，称为操纵序列，影响RNA聚合酶结合启动子的概率，从而影响基因转录。在感受外界化学或物理信号刺激后，转录因子通过一系列结构改变产生不同的操纵序列结合亲和力，与启动子结合或从启动子上掉落，进而影响下游基因的转录和表达。结合DNA的转录因子必须有三个特性：①能够与特定的DNA序列结合；②能够响应信号；③能够控制转录(Schleif，R.F.，Modulation of DNA binding by gene-specific transcription factors.Biochemistry，2013.52(39)：p.6755-65.)。这些特性可以分别由结构和功能模块化的不同结构域来执行。根据其执行的功能，转录因子由DNA结合结构域、配体结合结构域、转录激活结构域组成。每一个结构域在行使功能时，可以分别用几个反应方程来描述。每一个反应方程式又可以抽象为一个参数——反应平衡常数。因此，在我们的酿酒酵母宿主中，特定序列的某一结构域可以抽象为一个特定参数，不同参数的不同结构域共同组成了特定转录调控行为的完整转录因子，而转录因子在特定转录系统中的行为又被反应方程所描述。
目前常用于真核细胞转录调控的转录因子根据来源可分为原核天然宿主转录因子和人工合成转录因子两大类。来自原核的LacI、TetR和XylR分别受到IPTG、aTc和xylose的诱导应用于真核细胞中(Chen，Y.，et al.，Genetic circuit design automation for yeast.Nature Microbiology，2020.5(11)：p.1349-1360.)。人工合成转录因子常利用锌指、TALE和CRISPR-dCas9作为自定义的DNA结合模块，连接配体结合结构域或转录激活结构域等功能性结构域进行构建[9]。如Khalil基于三个锌指结构结合9bp DNA建立的一系列DBD-operator系统(Khalil，A.S.，et al.，A synthetic biology framework for programming eukaryotic transcription functions.Cell，2012.150(3)：p.647-58.)。另外，分别将模块化的DBD、LBD、AD组装，形成真核系统中常用的人工转录因子XEV，lexA-ER-VP16(Louvion，J.F.，B.Havaux-Copf，and D.Picard，Fusion of GAL4-VP16 to a steroid-binding domain provides a tool for gratuitous induction of galactose-responsive genes in yeast.Gene，1993.131(1)：p.129-34.)。
复杂基因线路中多个不同诱导系统的使用要求获得诱导信号接受和DNA序列结合两方面均相互正交的多对转录因子。现有的真核转录因子难以满足这一要求。主要原因有：其一，特征良好的常用真核转录系统数量不足，强度不足，需要通过使用多个operator或增加协同性相互作用来进行优化；其二，大多数现有真核转录调控系统中转录因子以整体形式作用，存在本底泄露高表达、诱导强度不足，动态范围较差的现象；其三，真核转录系统之间，或与宿主已有系统之间存在串扰。因此，为了解决这一类问题，需要开发一组通用的可设计的正交真核转录体系。
对于转录调控过程的优化可以分为转录因子本身性能参数的优化和转录调控模式的优化两方面。Khalil等提出的一系列相互正交的不同调控活性的锌指库对应不同的转录因子结合DNA的亲和力参数，通过使用高亲和力的锌指DNA结合模块，可以对转录因子本身的性能进行优化(Khalil，A.S.，et al.，A synthetic biology framework for programming eukaryotic transcription functions.Cell，2012.150(3)：p.647-58.)。另外通过使用多个operator来增加潜在的希尔系数，通过使用8个operator的输出启动子达到～60倍的调控倍数，是单个operator启动子情况下的～10倍(Khalil，A.S.，et al.，A synthetic biology framework for programming eukaryotic transcription functions.Cell，2012.150(3)：p.647-58.)。除了对单个转录因子的转录调控过程的优化，转录调控模式的改变也提供了一个优化思路。2019年和2023年，Khalil等也通过增加表达一个结合多个锌指转录激活因子的“支架”来增加转录调控的协同性，从而在单个转录因子低亲和力的情况下对转录调控进行优化(Bashor，C.J.，et al.，Complex signal processing in synthetic gene circuits using cooperative regulatory assemblies.Science，2019.364(6440)：p.593-597.)(Bragdon，M.D.J.，et al.，Cooperative assembly confers regulatory specificity and long-term genetic circuit stability.Cell，2023.186(18)：p.3810-3825.e18.)。2018年Rob Phillips等使用Monod-Wyman-Changeux模型对转录因子变构调控过程针对转录因子浓度、诱导剂浓度和转录因子-operator结合能的变化进行了定量描述，但其变构系统只能通过突变对转录因子-operator结合能进行调整，无法实现结构域的模块化和有效替换优化(Razo-Mejia M，Barnes S L，Belliveau N M，et al.Tuning Transcriptional Regulation through  Signaling：A Predictive Theory of Allosteric Induction.2017[2023-11-10].DOI：10.1016/j.cels.2018.02.004)。
现有真核转录调控系数中转录因子多以整体形式作用，调控范围较差，具有高本底泄露和低诱导强度；缺少多诱导系统所需的正交性方面的考虑，没有多对同时存在的、相互及与宿主之间不存在交互作用的高诱导范围的转录因子；现有模型以变构型调控系统为基础，无法实现结构域的模块化和有效替换，可用范围较窄。
发明内容
本发明提供一种模块化正交真核转录因子模型构建方法，解决现有技术中真核转录调控以变构型调控为基础，无法实现结构域的模块化和有效替换，可用范围较窄的不足
为实现上述目的，本发明采用以下技术方案：
一种模块化正交真核转录因子模型构建方法，包括以下步骤：
S1、确立由DNA结合结构域(DBD)、配体结合结构域(LBD)、转录激活结构域(AD)三种结构域组成的转录因子基本架构DBD-LBD-AD；
S2、在转录因子基本架构DBD-LBD-AD基础上，分别构建DNA结合结构域(DBD)、配体结合结构域(LBD)、转录激活结构域(AD)三种结构域的筛选酿酒酵母菌株，然后对筛选酿酒酵母菌株进行筛选测试培养，筛选得到有效的DBD、LBD和AD；
S3、在转录因子基本架构DBD-LBD-AD基础上，以筛选出的DBD、LBD分别构建用于结构域参数定量测试的定量测试酿酒酵母菌株；对定量测试酿酒酵母菌株进行定量测试培养，获得转录因子表达量下的调控诱导范围和调控倍数；对获得调控诱导范围和调控倍数数据进行拟合，得到筛选出的DBD、LBD各结构域的对 应参数；
S4、根据DBD、LBD各结构域的对应参数来表征转录因子调控过程，建立转录调控定量模型；通过转录调控定量模型预测不同DBD和LBD组合情况下转录因子，获得性能优化的转录因子。
本发明中，所述基本架构DBD-LBD-AD中以E.coli SOS调控蛋白lexA的1-87aa作为DBD，以沼泽红假单胞菌群体感应转录因子RpaR的1-179aa作为LBD，以VP16作为AD。
本发明中，S2中DNA结合结构域(DBD)的筛选酿酒酵母菌株，通过以下方式得到：构建DBD的筛选转录因子表达载体，构建对应的报告基因表达载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到DBD筛选酿酒酵母菌株。
进一步地，所述DBD的筛选转录因子表达载体以aTc诱导的ptet作为启动子、tENO2作为终止子、用CCDB替换转录因子基本架构DBD-LBD-AD中的DBD结构域得到。
进一步地，所述DBD的筛选转录因子表达载体序列如SEQ ID NO：1。
进一步地，S2中构建DBD对应报告基因表达载体以对应的报告基因用含有两个对应DBD调控的operator的启动子，控制黄色荧光蛋白YFP的表达，以tENO2作为终止子；将CCDB放置在报告基因质粒的启动子位置得到。
本发明中，所述筛选得到有效的DBD序列如SEQ ID NO：7-18。
本发明中，S2中配体结合结构域(LBD)的筛选酿酒酵母菌株，通过以下方式得到：构建LBD的筛选转录因子表达载体，构建对应的报告基因表达载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合 到酵母中，得到LBD筛选酿酒酵母菌株。
进一步地，所述LBD的筛选转录因子表达载体以aTc诱导的ptet作为启动子、tENO2作为终止子、用CCDB替换转录因子基本架构DBD-LBD-AD中的LBD结构域得到。
进一步地，所述LBD的筛选转录因子表达载体序列如SEQ ID NO：2。
进一步地，S2中构建LBD对应报告基因表达载体对应的报告基因用含有两个对应DBD调控的operator的启动子，控制黄色荧光蛋白YFP的表达，以tENO2作为终止子得到。
本发明中，所述筛选得到有效的LBD序列如SEQ ID NO：19-31。
本发明中，S2中转录激活结构域(AD)的筛选酿酒酵母菌株，通过以下方式得到：构建AD的筛选转录因子表达载体，构建对应的报告基因表达载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到AD筛选酿酒酵母菌株。
进一步地，所述AD的筛选转录因子表达载体以aTc诱导的ptet作为启动子、tENO2作为终止子、用CCDB替换转录因子基本架构DBD-LBD-AD中的AD结构域得到。
进一步地，所述AD的筛选转录因子表达载体的序列如SEQ ID NO：3。
进一步地，S2中构建AD对应报告基因表达载体对应的报告基因用含有两个对应DBD调控的operator的启动子，控制黄色荧光蛋白YFP的表达，以tENO2作为终止子得到。
本发明中，所述筛选得到有效的AD序列如SEQ ID NO：32-40。
本发明中，筛选测试培养的具体过程如下：将构建的筛选酿酒酵母菌株接种 于对应缺陷型SD培养基中培养一段时间，转接至新的SD培养基，设置对照组和不同实验组，继续培养，取菌液，稀释后，检测每组荧光蛋白YFP表达量，计算相对荧光表达量。
本发明中，S3中DNA结合结构域(DBD)的定量测试酿酒酵母菌株，通过以下方式得到：构建DBD的参数定量测试转录因子表达载体，然后构建对应的报告基因载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到DBD定量测试酿酒酵母菌株。
进一步地，所述DBD的参数定量测试转录因子表达载体以xylose诱导的pxyluas作为启动子、tENO2作为终止子、用CCDB替换DBD结构域得到。
进一步地，所述DBD的参数定量测试转录因子表达载体序列如SEQ ID NO：4。
进一步地，S3中构建DBD对应报告基因表达载体对应的报告基因用含有一个对应DBD调控的operator的启动子，控制黄色荧光蛋白YFP的表达，以tENO2作为终止子；将CCDB放置在报告基因质粒的启动子位置得到。
本发明中，S3中配体结合结构域(LBD)的定量测试酿酒酵母菌株，通过以下方式得到：构建LBD的参数定量测试转录因子表达载体，然后构建对应的报告基因载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到LBD定量测试酿酒酵母菌株。
进一步地，所述LBD的参数定量测试转录因子表达载体以xylose诱导的pxyluas作为启动子、tENO2作为终止子、用CCDB替换LBD结构域得到。
进一步地，所述LBD的参数定量测试转录因子表达载体如SEQ ID NO：5。
进一步地，S3中构建LBD对应报告基因表达载体对应的报告基因用含有一个对应DBD调控的operator的启动子，控制黄色荧光蛋白YFP的表达，以tENO2 作为终止子得到。
本发明中，定量测试培养的具体过程如下：将构建的筛选酿酒酵母菌株接种于对应缺陷型SD培养基中培养一段时间，第一次转接至新的SD培养基进行诱导范围测试，设置不同xylose浓度梯度，获得不同转录因子表达量，在不同xylose浓度下分别设置±最大工作浓度诱导剂两组，获得每个转录因子表达量下的调控诱导范围；选取具有合适诱导范围的转录因子表达量，分别进行不同诱导剂浓度梯度下的诱导曲线的测试，含有对应xylose浓度的SD培养基中继续培养一段时间，设置对照组和不同实验组，第二次转接至含有对应xylose浓度下不同诱导剂浓度的SD培养基中培养，取菌液，稀释后，检测每组荧光蛋白YFP表达量，计算相对荧光表达量和转录因子的调控倍数。
进一步地，每个实验组的相对荧光表达量的计算方法为：RPU＝(YFP测试-YFPCYE72)/(YFPCYE72/CY637-YFPCYE72)；其中，CYE72是阴性对照，CYE72/CY637是ptet诱导对照。
转录因子的调控倍数的计算方法为：Fold Change＝RPU诱导后/RPU诱导前。
本发明中，所述转录调控定量模型包括非核受体二聚化转录激活模型(不考虑入核过程)和核受体类二聚化转录激活模型(考虑入核过程)；
非核受体二聚化转录激活模型方程如下：

核受体类二聚化转录激活模型方程如下：

其中，F1因子为描述特定DBD-LBD组合下转录因子性能的参数；c为LBD不同形态下的浓度，I0为特定序列启动子的本底泄露表达强度，Imax为特定序列启动子的理论最大激活强度，I为诱导剂浓度，Ltot为所有形式的转录因子的表达量的单体形式的总和，ΔεDBD描述DBD的行为，K1、K2、K3描述LBD的行为，K*和K*’描述转录因子的入核过程。
本发明具有以下有益效果：
(1)本发明模块化正交真核转录因子模型构建方法，通过确定了模块化转录因子的基本架构，最终建立了转录调控定量模型，对转录因子模块化结构域进行参数化；通过定量模型可实现对转录因子进行模块化结构域参数优化，获得了性能优化的转录因子。
(2)本发明确定了协同性二聚化过程引入转录调控过程对转录调控的优化效果，建立了各结构域不同参数范围的结构域库，建立了DBD×operator、LBD×inducer两个层面均相互正交的结构域库，为复杂基因调控线路的实现提供了工具。
附图说明
下面结合说明书附图和具体实施方式对本发明的技术方案做进一步说明。
图1是本发明模块化结构域转录因子的基本架构示意图；
图2是本发明构建的DBD结构域筛选测试载体和系统示意图；
图3是本发明构建的LBD结构域筛选测试载体和系统示意图；
图4是本发明构建的AD结构域筛选测试载体和系统示意图；
图5是本发明构建的DBD结构域定量测试载体；
图6是本发明构建的LBD结构域定量测试载体；
图7是本发明构建的转录因子定量测试载体；
图8是本发明有效DBD测试结果及正交性；
图9是本发明有效LBD测试结果；
图10是本发明有效AD测试结果；
图11是本发明非核受体类转录调控定量模型示意图；
图12是本发明定量测试结果；
图13是本发明LBD×inducer正交表；
图14是本发明crosstalk诱导曲线；
图15是本发明模型初步拟合的部分参数值；
图16是本发明模型指导优化情况。
具体实施方式
下述实施例中的实验方法，如无特殊说明，均为常规方法，按照本领域内的文献所描述的技术或条件或者按照产品说明书进行。下述实施例中所用的材料、试剂等，如无特殊说明，均可从商业途径得到。
下述实施例实例中所用的golden gate体系及条件如下：
下述实施例中酵母筛选测试培养条件如下：
得到酵母转化子后，将其接种于含500μl的对应缺陷型SD培养基的96深孔板中，并置于30℃、800rpm培养24h后，以1∶200的比例转接至新的SD培养基96深孔板中。与此同时每个实验组设置非诱导--、添加诱导剂脱水四环素aTc+-(工作浓度：100ng/ml)或最大工作浓度的对应诱导剂-+、或两者均添加++组。培养16h后，取适量菌液，并用1xPBS溶液稀释后，使用流式分析仪器BDFACSCelestaTM FITC-A通道检测10,000个细胞的荧光蛋白YFP表达量。用FlowJo对获得的数据进行处理，取中位数作为每个样品孔的荧光值。以CYE72/CY671为表达量对照，每个实验组的相对荧光表达量的计算方法为：RPU＝(YFP测试-YFPCYE72)/(YFPCYE72/CY637-YFPCYE72)。
下述实施例中酵母定量测试培养条件如下：
得到酵母转化子后，将其接种于含500μl的对应缺陷型SD培养基的96深孔板中，并置于30℃、800rpm培养24h后，以1∶200的比例第一次转接至新的SD培养基96深孔板中进行诱导范围测试：根据输入启动子诱导曲线设置不同xylose浓度梯度(0、0.2、0.3、0.4、0.5、0.6、0.8、0.9、1、1.5、2、5、10、20mM)，以获得不同的转录因子表达量；进一步，在不同xylose浓度下分别设置±最大工 作浓度诱导剂两组。在该一系列设置实验组条件下，将96深孔板置于30℃、800rpm培养16h后，第一次取样测试。从而获得每个转录因子表达量下的调控诱导范围。
选取具有合适诱导范围的转录因子表达量(一般情况下设置0.4、0.6、1、2、10mM xylose浓度梯度)，分别进行不同诱导剂浓度梯度下的诱导曲线的测试：第一次转接后，30℃、800rpm培养24h，分别选取对应浓度的+xylose组，作为母液，以1∶200的比例第二次转接至新的SD培养基96深孔板中，同时分别设置这些不同xylose浓度下的不同诱导剂浓度梯度。30℃、800rpm培养16h后，第二次取样测试。
对于两次转接，每次转接设置空白对照组CYE72、组成型表达对照组CYE72/CY671；每次测试用输入启动子诱导型表达对照菌CYE72/LXR347进行对应xylose浓度下的输入启动子的表达量标定。对于两次取样测试，取样时，将适量菌液用1xPBS溶液稀释后，使用流式分析仪器BD FACSCelestaTM FITC-A通道检测10,000个细胞的荧光蛋白YFP表达量。用FlowJo对获得的数据进行处理，取中位数作为每个样品孔的荧光值。以CYE72/CY671为表达量对照，每个实验组的相对荧光表达量的计算方法为：RPU＝(YFP测试-YFPCYE72)/(YFPCYE72/CY671-YFPCYE72)。从而获得每个转录因子表达量下的调控诱导范围。
实例一：有效DNA结合结构域筛选
1.DNA结合结构域筛选载体LXR66构建
以实验室已有质粒pXJH119(ptet-lexAec1-87-RpaR1-179-VP16-tENO2)为模板，用引物66-F(5’-GGTTCTAAGGATATCTCTGCTGGAGACATGA-3’)和66-R(5’-CATTTTTTATTTATTTTTGTAGCTTGATATTCTCTATCAC-3’)扩增得到1号PCR片段。以实验室已有的质粒CY386(含有致死基因ccdb)为模板，用引物 Homo-CCDB-66-F(5’-ACAAAAATAAATAAAAAATGAGGTCTTCTTATATTCCCCAGAACATCAGGTTAATGG-3’)和Homo-CCDB-66-R(5’-GCAGAGATATCCTTAGAACCAGGTCTTCGGCTTACTAAAAGCCAGATAACAGTATGC-3’)扩增得到2号PCR片段CCDB致死基因。使用诺维赞II One Step Cloning Kit C112试剂盒对2个PCR片段进行同源重组，获得酿酒酵母转录激活因子DBD筛选载体LXR66，见SEQ ID NO：1。
2.DNA结合结构域筛选系统构建
根据载体LXR66的序列，通过Golden Gate方法，用BpiI进行酶切，通过两个粘性末端的scar序列：AATG和GGTT，实现不同DBD的CCDB替换。对一系列来源于原核或病毒的转录因子根据其结构特征进行DBD的截取，获得其DBD的氨基酸和核苷酸序列(见SEQ ID NO：7-18)。不同DBD序列通过基因合成、基因组序列或已有质粒序列获得，通过PCR过程在两端分别加上AATG和GGTT scar以及BpiI识别位点和保护碱基，通过BpiI Golden Gate的方法，构建含有不同DBD的转录因子质粒。对应的，以实验室已有质粒pXJH1为载体，通过分段长引物PCR和overlap PCR获得含有对应DBD调控operator的报告基因质粒。获得所需要的构建之后，通过用限制性内切酶BsaI酶切，得到带转化的酶切片段。利用zymo Frozen-EZ Yeast Transformation II KitTM酵母转化试剂盒制备菌株CYE72感受态，再将酶切片段分两步转至CYE72感受态中，得到酵母转化子。
包含酵母筛选测试系统所需DBD和operator的质粒如表1：
表1酵母筛选测试系统所需DBD和operator的质粒

3.不同DNA结合结构域对转录调控的影响
获得酵母测试转化子后，通过酵母筛选测试培养得到测试菌液，用BD FACSCelestaTM流式分析检测，每个DBD设置非诱导、诱导表达且诱导二聚两个组。筛选到的12个有效的DBD测试结果如图8。如图8所示，含不同operator的启动子存在不同程度的基础表达强度，在测试条件的表达量下激活强度也随不同DBD改变。
实例二：有效配体结合结构域筛选
1.配体结合结构域筛选载体LXR77构建
以实验室已有质粒pXJH119(ptet-lexAec1-87-RpaR1-179-VP16-tENO2)为模板，用引物77-F(5’-GGTAGCCCTAAGAAAAAGAGAAAAGTGG-3’)和77-R(5’-GATCATGAGCGGGCTTGGCCA-3’)扩增得到1号PCR片段。以实验室已有的质粒CY386 为模板，用引物Homo-CCDB-77-F(5’-GGCCAAGCCCGCTCATGATCAGGTCTTCTTATATTCCCCAGAACATCAG-3’)和Homo-CCDB-77-R(5’-CTCTTTTTCTTAGGGCTACCAGGTCTTCGGCTTACTAAAAGCCAGATAAC-3’)扩增得到2号PCR片段CCDB致死基因。使用诺维赞II One Step Cloning Kit C112试剂盒对2个PCR片段进行同源重组，获得酿酒酵母转录激活因子配体结合结构域筛选载体LXR77，见SEQ ID NO：2。
2.配体结合结构域筛选系统构建
根据载体LXR77的序列，通过Golden Gate方法，用BpiI进行酶切，通过两个粘性末端的scar序列：GATC和GGTA，实现不同LBD的CCDB替换。根据文献调研，将一系列存在化学诱导二聚化的蛋白进行配体结合-二聚化结构域的截取，获得其氨基酸和核苷酸序列(有效LBD序列见SEQ ID NO：19-31)。不同LBD序列通过基因合成或已有质粒序列获得，通过PCR过程在两端分别加上GATC和GGTA scar以及BpiI识别位点和保护碱基，通过BpiI Golden Gate的方法，构建含有不同LBD的转录因子质粒。需说明的是，大部分LBD以LXR77为载体进行筛选构建，匹配lexAec1-87作为DBD。但转录因子的整体表现同时受所有结构域影响，故对于部分LBD也在其他DBD情况下验证得到有效性。筛选获得LBD有效性的构建如表2：
表2筛选获得LBD有效性的构建情况

获得所需要的构建之后，通过用限制性内切酶BsaI酶切，得到带转化的酶切片段。利用zymo Frozen-EZ Yeast Transformation II KitTM酵母转化试剂盒制备菌株CYE72/LXR152感受态，再将酶切片段进行转化，得到酵母转化子。
3.不同配体结合结构域对转录调控的影响
获得酵母测试转化子后，通过酵母筛选测试培养得到测试菌液，用BD FACSCelestaTM流式分析检测，每个LBD设置非诱导、诱导表达、诱导表达且诱导二聚三个组。筛选到的13个有效的LBD测试结果如图9。如图9所示，LBD主要来自三类蛋白：单结构域抗体、原核群体感应转录调控蛋白和哺乳动物核受体。在测试条件的表达量下，不同LBD会导致不同程度的转录因子本底二聚化带来的本底激活强度，不同LBD对应不同的诱导剂浓度，其分别在其诱导剂最大工作浓度下不同LBD能达到的最大激活强度也不同。
实例三：有效转录激活结构域筛选
1.转录激活结构域筛选载体LXR233构建
以实验室已有质粒pXJH119(ptet-lexAec1-87-RpaR1-179-VP16-tENO2)为模板，用引物233-F(5’-TAAAAGCTTTTGATTAAGCCTTCTAGTCCAAAAAAC-3’)和233-R(5’-CACTTTTCTCTTTTTCTTAGGGCTACCATTAC-3’)扩增得到1号PCR片段。以实验室已有的质粒CY386为模板，用引物Homo-GGS5-CCDB-233-F(5’-CTAAGAAAAAGAGAAAAGTGGGTGGCAGTGGCGGAAGCGGGGGATCAGGTGGTTCTGGAGGGTCCAGGTCTTCTTATATTCCCCAGAACATCAGGTTAATGG-3’)和Homo-CCDB-233-R(5’-GGCTTAATCAAAAGCTTTTAAGGTCTTCGGCTTACTAAAAGCCAGATAACAGTATGCA-3’)扩增得到2号PCR片段CCDB致死基因。使用诺维赞II One Step Cloning Kit C112试剂盒对2个PCR片段进行同源重组，获得酿酒酵母转录激活因子配体结合结构域筛选载体LXR233，见SEQ ID NO：3。
2.转录激活结构域筛选系统构建
通过文献调研，Ariel Erijman等2020年提出一个AD结构和功能预测模型，预测了一系列具有转录激活功能的氨基酸序列。我们从中挑选出7个预测功能良好的转录激活氨基酸序列，并且对一些常用的酵母转录激活结构域进行测试，以获取多个匹配多个转录因子的AD。不同AD序列通过基因合成或已有质粒序列获得，通过PCR过程在两端分别加上与载体LXR233匹配的GTCC和TAAA scar以及BpiI识别位点和保护碱基，通过BpiI Golden Gate的方法。
获得所需要的构建之后，通过用限制性内切酶BsaI酶切，得到带转化的酶切片段。利用zymo Frozen-EZ Yeast Transformation II KitTM酵母转化试剂盒制备菌株CYE72/LXR152感受态，再将酶切片段进行转化，得到酵母转化子。
3.不同转录激活结构域对转录调控的影响
获得酵母测试转化子后，通过酵母筛选测试培养得到测试菌液，用BD FACSCelestaTM流式分析检测，每个DBD设置非诱导、诱导表达且诱导二聚两个组。结果如图10，从图10中结果可以看出，不同AD对转录因子的最大激活强度具有不同程度的影响。从筛选的13个AD中，其中有9个有明显的转录激活效果(SEQ ID NO：32-40)，其中在VP16的情况下最大激活强度最强。
实例四：激活型转录调控模型构建
1.非核受体二聚化转录激活模型(不考虑入核过程)
本方法中的转录调控过程可描述如下(参数见图11)：①输入启动子以一定表达量表达转录因子单体；②转录因子单体可以自发或受到诱导剂作用两种形式不同程度地形成转录因子二聚体；③转录因子二聚体以一定地亲和力识别并结合启动子上的operator序列。用LBD表示转录因子单体蛋白，LBD2表示两个转录因子单体蛋白形成的二聚体，I表示诱导剂分子，LBD：I表示单体蛋白和诱导剂分子结合的中间形态，LBD2：I2表示两个蛋白单体和两个诱导剂分子形成的二聚体，P0表示非活性状态启动子，P1和P2分别表示结合不同途径形成的二聚体的活性状态启动子；该过程可用以下方程表示：




调控过程中，启动子可能状态包括：①空启动子；②只结合RNAP；③同时结合RNAP和转录因子本底二聚体；④同时结合RNAP和转录因子诱导二聚体。③和④分别对应启动子的不同活性状态，根据配分方程，可得到模型方程描述如下：

其中，F1因子为描述特定DBD-LBD组合下转录因子性能的参数；c为LBD不同形态下的浓度，I0为特定序列启动子的本底泄露表达强度，Imax为特定序列启动子的理论最大激活强度，I为诱导剂浓度，Ltot为所有形式的转录因子的表达量的单体形式的总和，ΔεDBD(K4、K5)描述DBD的行为，K1、K2、K3描述LBD的行为。
2.核受体类二聚化转录激活模型(考虑入核过程)
核受体类转录调控过程增加了各类转录因子蛋白的入核过程，用LBD、LBD*分别表示转录因子单体蛋白核外、核内状态，LBD2、LBD2*分别表示两个转录因子单体蛋白形成的二聚体核外、核内状态，I表示诱导剂分子，LBD：I、LBD*：I分别表示单体蛋白和诱导剂分子在核外、核内结合的中间形态，LBD2：I2、LBD2*：I2表示两个蛋白单体和两个诱导剂分子形成的二聚体核外、核内状态，该过程可用以下方程表示：
核外：


入核：



核内：




根据配分方程，可得到模型方程描述如下：

其中，F1因子为描述特定DBD-LBD组合下转录因子性能的参数；c为LBD不同形态下的浓度，I0为特定序列启动子的本底泄露表达强度，Imax为特定序列启动子的理论最大激活强度，I为诱导剂浓度，Ltot为所有形式的转录因子的表达量的单体形式的总和，ΔεDBD(K4、K5)描述DBD的行为，K1、K2、K3描述LBD的行为，K*和K*’描述转录因子的入核过程。
实例五：结构域参数定量测试
1.DNA结合结构域参数定量测试载体LXR322构建
以已构建质粒LXR319(pxyluas-lexAec1-87-CarHc-VP16-tENO2)为模板，用引物322-F(5’-CAGTGAGAAGACCTGTAGCCCTAAGAAAAAGAGAAAAGTGGG-3’)和322-R(5’-CAGTACGAAGACTACATTTTTTATTTATTTTTGTAGCTTGATATTCTAGTTTGTTG-3’)扩增得到1号PCR片段。以实验室已有质粒pXJH119为模板，用引物RpaR-322-F(5’-CAGTGAGAAGACCTGGTTCTAAGGATATCATTGTGGGTGAAGATCAGCTGTGG-3’)和RpaR-322-R(5’-TAAGCCGAAGACCTCTACCATTACGACGAATCGGTTTCG-3’)扩增得到2号PCR片段，RpaR1-179LBD结构域。以实验室已有的质粒CY386为模板，用引物CCDB-322-F(5’-CAGTGAAATGAGGTCTTCTTATATTCCCCAGAACATCAG-3’)和 CCDB-322-R(5’-TAAGCCAACCAGGTCTTCGGCTTACTAAAAGCCAGATAAC-3’)扩增得到3号PCR片段CCDB致死基因。通过BpiI限制性内切酶的Golden Gate技术，获得酿酒酵母转录激活因子DNA结合结构域参数定量测试载体LXR322，见SEQ ID NO：4。
2.DNA结合结构域参数定量测试系统构建
将筛选到的12个DBD通过PCR扩增在两端加上与载体LXR322匹配的AATG和GGTT scar以及BpiI识别位点和保护碱基，通过BpiI Golden Gate的方法，构建用于不同DBD参数定量测试的质粒。为了简单化参数测试，调控启动子均只包含一个operator，以lexAec1-87对应的lexO为例，启动子序列为： 加粗字体位置为启动子的polyA、TATA box、TSS和kozak序列，大写非加粗位置为lexO。通过在此位置替换不同operator，构建一系列调控启动子质粒。通过长引物PCR和overlap PCR获得两端带有酶切位点的启动子片段，以实验室已有质粒pXJH1为载体，通过BpiI Golden Gate的方法，获得不同DBD定量测试对应的报告基因质粒。用于DBD定量测试的质粒信息如表3：
表3用于DBD定量测试的质粒信息

获得所需要的构建之后，通过用限制性内切酶BsaI酶切，得到带转化的酶切片段。利用zymo Frozen-EZ Yeast Transformation II KitTM酵母转化试剂盒制备菌株CYE72感受态，再将酶切片段分两步转至CYE72感受态中，得到酵母转化子。
3.配体结合结构域参数定量测试载体LXR321构建
以已构建质粒LXR319(pxyluas-lexAec1-87-CarHc-VP16-tENO2)为模板，用引物321-F(5’-CAGTGAGAAGACCTGGTAGCCCTAAGAAAAAGAGAAAAGTGG-3’)和321-R(5’-CAGTACGAAGACTACATTTTTTATTTATTTTTGTAGCTTGATATTCTAGTTTGTTG-3’)扩增得到1号PCR片段。以已构建质粒LXR36为模板，用引物lexAbs1-94-321-F(5’-CAGTGAGAAGACCTAATGTCTACGAAGCTATCAAAAAGGCAAC-3’)和lexAbs1-94-321-R(5’-TAAGCCGAAGACCTGATATCCTTAGAACCAGGAGATCCCGCCGTGACTTTC-3’)扩增得到2号PCR片段，lexAbs1-94DBD结构域。以实验室已有的质粒CY386为模板，用引物CCDB-321-F(5’-CAGTGATATCAGGTCTTCTTATATTCCCCAGAACATCAG-3’)和CCDB-321-R(5’-TAAGCCTACCAGGTCTTCGGCTTACTAAAAGCCAGATAAC-3’)扩增得到3号PCR片段CCDB致死基因。通过BpiI限制性内切酶的Golden Gate技术，获得酿酒酵母转录激活因子配体结合结构域参数定量测试载体LXR321，见SEQ ID NO：5。
4.配体结合结构域参数定量测试系统构建
将筛选到的13个LBD通过PCR扩增在两端加上与载体LXR321匹配的TATC和GGTA scar以及BpiI识别位点和保护碱基，通过BpiI Golden Gate的方法，构建用于不同LBD参数定量测试的质粒。需说明的是，大部分LBD以LXR321为载体进行定量测试构建，匹配lexAbs1-94作为DBD。但考虑到不同DBD对于诱导曲线的影响，部分LBD也在其他DBD情况下进行定量测试。用于LBD定量测试的质粒信息如表4：
表4用于LBD定量测试的质粒信息
获得所需要的构建之后，通过用限制性内切酶BsaI酶切，得到带转化的酶切片段。利用zymo Frozen-EZ Yeast Transformation II KitTM酵母转化试剂盒制备菌株CYE72/LXR349感受态，并将酶切片段转化入感受态，得到酵母转化子。
5.结构域参数测量和拟合
本方法中主要对DBD和LBD两个结构域的对应参数ΔεDBD和K1 K2 K3进行定量测试。获得酵母测试转化子后，通过酵母定量测试培养方法得到测试菌液，用BD FACSCelestaTM流式分析检测，用FlowJo进行数据处理，测试数据结果如图12。将获得的测试数据使用模型进行拟合，初步获得不同DBD和LBD的对应参数。
实例六：配体结合结构域结合配体正交性测试
1.正交表测量
选择除了PR、GR、MR之外的其他LBD的有效转录因子构建，用酵母定量测试培养方法获取酵母菌液。设置RPU＝0.67和RPU＝1.24两个转录因子表达量，分别在两个表达量下对所有LBD和诱导剂进行全排列正交性测试。其中，在添加诱导剂时，对每个LBD设置所有诱导剂最大工作浓度的诱导组和非诱导表达组，从而获得特定表达量下每个LBD响应不同诱导剂的诱导范围和调控倍数。用于正交表测试的质粒信息和诱导剂信息如表5：
表5用于正交表测试的质粒信息和诱导剂信息

分别在两个表达量下，用测试所获得的所有LBD对所有诱导剂响应的调控倍数取对数，制作10×10的正交表，如图13。正交表每个格子的颜色对应调控倍数的对数的数值，数值越大，颜色越深。仅有对角线深色表示无交互作用的完全正交的情况。如图13所示，crosstalk存在于本方法所选的LBD和诱导剂之中，包括弱于天然响应的可优化crosstalk(如CinRori2-179对3OC12-HSL)和强于天然响应的不可优化crosstalk(如TraR1-174对3OC12-HSL)两种。
2.Crosstalk诱导曲线测试和参数拟合
对于正交表测试得到的crosstalk的可优化部分，通过酵母定量测试培养方法，获得对应的LBD对诱导剂的诱导曲线，如图14。该测试结果提供对应LBD对于诱导剂的响应调控参数K2’、K3’的拟合数据。
实例七：模型指导理性优化
1.结构域模块化转录因子表达载体LXR370构建
以已构建质粒LXR319(pxyluas-lexAec1-87-CarHc-VP16-tENO2)为模板，用引物370-F(5’-CAGTGAGAAGACCTGGTAGCCCTAAGAAAAAGAGAAAAGTGG-3’)和370-R(5’-CAGTACGAAGACTACATTTTTTATTTATTTTTGTAGCTTGATATTCTAGTTTGTTG-3’)扩增得到1号PCR片段。以实验室已有的质粒CY386为模板，用引物CCDB-370-F(5’-CAGTGAAATGAGGTCTTCTTATATTCCCCAGAACATCAG-3’)和CCDB-370-R(5’-TAAGCCTACCAGGTCTTCGGCTTACTAAAAGCCAGATAAC-3’)扩增得到2号PCR片段CCDB致死基因。通过BpiI限制性内切酶的Golden Gate技术，获得酵母转录激活因子配体结合结构域参数定量测试载体LXR370，见SEQ ID NO：6。
2.模型验证
挑选模型输出中14个不同转录因子及其对应表达量，进行模型输出的实验测试验证。以LXR370为载体，分别通过PCR获得两端带有相应scar和linker的DBD作为1号PCR片段、LBD作为2号PCR片段，通过BpiI Golden Gate的方法，获得以VP16作为AD、不同DBD和LBD组合情况下的酵母转录激活因子构建，用于组合测试和参数化模型验证。获得相关转录因子质粒后，通过用限制性内切酶BsaI酶切，得到带转化的酶切片段。利用zymo Frozen-EZ Yeast Transformation II KitTM酵母转化试剂盒制备含有对应DBD调控启动子的酵母感受态，并将酶切片段转化入感受态，得到酵母转化子。模型验证组合测试相关的质粒信息、转化感受态以及转录因子表达量如表6：
表6模型验证组合测试相关的质粒信息、转化感受态以及转录因子表达量
获得酵母转化子后，通过酵母定量测试培养方法获取酵母菌液，在模型给出的表达量下进行诱导曲线的测试，随后于模型理论输出结果进行对比，部分拟合结果如图15。如图15所示，实验数据基本能够符合理论预测，R2＞0.84，模型的预测输出准确性较好。
3.模型指导优化
模型描述了酿酒酵母中特定转录激活因子的转录调控性能，如图16a所示。一般来说，具体表现为：①特定DBD对应的operator的序列作为启动子序列的一部分，决定了启动子确定的理论上的最小泄露和最大转录激活强度；②LBD的本底二聚化程度k1决定了特定转录因子表达量下由本底二聚化造成的泄露程度，即该表达量下诱导曲线的最小值；③LBD的诱导二聚化能力k2和k3决定了其转录调控的敏感性和其能够实现的转录激活强度，即曲线的EC50和最大激活；总的来说LBD的参数确定了曲线形状；④DBD与operator结合的亲和力k4和k5和转录因子表达量则使得诱导曲线在坐标系中平移，亲和力越强、转录因子表达量越高，诱导曲线越倾向于朝左上移动。据此，对于响应特定诱导剂小分子的特定LBD，我们可以通过改变DBD-operator和转录因子表达量来实现对于本底泄露表达强度、激活表达强度、正交性等的优化。如图16b，在相同的转录因子表达量下，以LasR2-177为LBD，更换不同DBD，可以获得本底二聚泄露表达、诱导激活表达不同的转录因子，从而可以实现诱导范围的优化，在lexAxa1-101DBD下实现最优调控。另外，如图16c和d，ER282-595能够响应自身诱导剂β-estradiol，同时对DHBR282-595的诱导剂DHB存在交互作用。可以通过改变表达量来使得ER282-595对两种诱导剂的响应在一个相对正交的范围内(激活强度相差＞10倍)，在lexAbs1-94DBD情况下，可以通过将表达量控制在0.1～0.5RPU范围内，实现低本底、高激活、相对正交。进一步替换 DBD进行优化，在DeoR1-92DBD情况下，可以实现在一个比较合适的转录因子表达量下(1～7RPU)实现对自身诱导剂诱导范围良好、并且相互正交的情况。由此可以实现模型指导下，对于转录因子调控的泄露、本底表达、激活强度、动力学范围、对诱导剂敏感性以及多转录因子正交性等多指标的优化。
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以上所揭露的仅为本发明较佳实施例而已，当然不能以此来限定本发明之权利范围，因此依本发明权利要求所作的等同变化，仍属本发明所涵盖的范围。

Claims (11)

  1. 一种模块化正交真核转录因子模型构建方法，包括以下步骤：
    S1、确立由DNA结合结构域、配体结合结构域、转录激活结构域三种结构域组成的转录因子基本架构DBD-LBD-AD；
    S2、在转录因子基本架构DBD-LBD-AD基础上，分别构建DNA结合结构域、配体结合结构域、转录激活结构域三种结构域的筛选酿酒酵母菌株，然后对筛选酿酒酵母菌株进行筛选测试培养，筛选得到有效的DBD、LBD和AD；
    S3、在转录因子基本架构DBD-LBD-AD基础上，以筛选出的DBD、LBD分别构建用于结构域参数定量测试的定量测试酿酒酵母菌株；对定量测试酿酒酵母菌株进行定量测试培养，获得转录因子表达量下的调控诱导范围和调控倍数；对获得调控诱导范围和调控倍数数据进行拟合，得到筛选出的DBD、LBD各结构域的对应参数；
    S4、根据DBD、LBD各结构域的对应参数来表征转录因子调控过程，建立转录调控定量模型；通过转录调控定量模型预测不同DBD和LBD组合情况下转录因子，获得性能优化的转录因子。
  2. 根据权利要求1所述模块化正交真核转录因子模型构建方法，其特征在于，所述基本架构DBD-LBD-AD中以E.coli SOS调控蛋白lexA的1-87aa作为DBD，以沼泽红假单胞菌群体感应转录因子RpaR的1-179aa作为LBD，以VP16作为AD。
  3. 根据权利要求2所述模块化正交真核转录因子模型构建方法，其特征在于，S2中DNA结合结构域的筛选酿酒酵母菌株，通过以下方式得到：构建DBD的筛选转录因子表达载体，构建对应的报告基因表达载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到DBD筛选酿酒酵母菌株。
  4. 根据权利要求3所述模块化正交真核转录因子模型构建方法，其特征在于，所述DBD的筛选转录因子表达载体序列如SEQ ID NO：1；所述筛选得到有效的DBD序列如SEQ ID NO：7-18。
  5. 根据权利要求3或4所述模块化正交真核转录因子模型构建方法，其特征在于，S2中配体结合结构域的筛选酿酒酵母菌株，通过以下方式得到：构建LBD的筛选转录因子表达载体，构建对应的报告基因表达载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到LBD筛选酿酒酵母菌株。
  6. 根据权利要求5所述模块化正交真核转录因子模型构建方法，其特征在于，所述LBD的筛选转录因子表达载体序列如SEQ ID NO：2；所述筛选得到有效的LBD序列如SEQ ID NO：19-31。
  7. 根据权利要求1所述模块化正交真核转录因子模型构建方法，其特征在于，S3中DNA结合结构域的定量测试酿酒酵母菌株，通过以下方式得到：构建DBD的参数定量测试转录因子表达载体，然后构建对应的报告基因载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中，得到DBD定量测试酿酒酵母菌株。
  8. 根据权利要求7所述模块化正交真核转录因子模型构建方法，其特征在于，所述DBD的参数定量测试转录因子表达载体序列如SEQ ID NO：4。
  9. 根据权利要求7所述模块化正交真核转录因子模型构建方法，其特征在于，S3中配体结合结构域的定量测试酿酒酵母菌株，通过以下方式得到：构建LBD的参数定量测试转录因子表达载体，然后构建对应的报告基因载体，对报告基因表达载体进行酶切，得到转录因子表达片段，将转录因子表达片段整合到酵母中， 得到LBD定量测试酿酒酵母菌株。
  10. 根据权利要求9所述模块化正交真核转录因子模型构建方法，其特征在于，所述LBD的参数定量测试转录因子表达载体如SEQ ID NO：5。
  11. 根据权利要求1所述模块化正交真核转录因子模型构建方法，其特征在于，所述转录调控定量模型包括非核受体二聚化转录激活模型和核受体类二聚化转录激活模型；
    非核受体二聚化转录激活模型方程如下：

    核受体类二聚化转录激活模型方程如下：

    其中，F1因子为描述特定DBD-LBD组合下转录因子性能的参数；c为LBD不同形态下的浓度，I0为特定序列启动子的本底泄露表达强度，Imax为特定序列启动子的理论最大激活强度，I为诱导剂浓度，Ltot为所有形式的转录因子的表达量 的单体形式的总和，ΔεDBD描述DBD的行为，K1、K2、K3描述LBD的行为，K*和K*’描述转录因子的入核过程。
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