Exploiting spatial dimensions to enable parallelized continuous directed evolution

Article21 September 2022Open Access Source Data Exploiting spatial dimensions to enable parallelized continuous directed evolution Ting Wei Ting Wei [email protected] orcid.org/0000-0003-2926-5849 CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Contribution: Data curation, ​Investigation, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Wangsheng Lai Wangsheng Lai CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Contribution: Data curation, ​Investigation, Methodology, Writing - original draft Search for more papers by this author Qian Chen Qian Chen CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Data curation, ​Investigation, Methodology, Writing - original draft Search for more papers by this author Yi Zhang Yi Zhang CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Contribution: Software, Methodology, Writing - original draft Search for more papers by this author Chenjian Sun Chenjian Sun CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Data curation, ​Investigation, Writing - original draft Search for more papers by this author Xionglei He Xionglei He State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China Contribution: Writing - review & editing Search for more papers by this author Guoping Zhao Guoping Zhao CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China CAS Key Laboratory for Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China Contribution: Writing - review & editing Search for more papers by this author Xiongfei Fu Corresponding Author Xiongfei Fu [email protected] orcid.org/0000-0003-3657-8296 CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Software, Supervision, Methodology, Writing - review & editing Search for more papers by this author Chenli Liu Corresponding Author Chenli Liu [email protected] orcid.org/0000-0003-3029-7207 CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Conceptualization, Supervision, Methodology, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Ting Wei Ting Wei [email protected] orcid.org/0000-0003-2926-5849 CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Contribution: Data curation, ​Investigation, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Wangsheng Lai Wangsheng Lai CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Contribution: Data curation, ​Investigation, Methodology, Writing - original draft Search for more papers by this author Qian Chen Qian Chen CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Data curation, ​Investigation, Methodology, Writing - original draft Search for more papers by this author Yi Zhang Yi Zhang CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Contribution: Software, Methodology, Writing - original draft Search for more papers by this author Chenjian Sun Chenjian Sun CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Data curation, ​Investigation, Writing - original draft Search for more papers by this author Xionglei He Xionglei He State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China Contribution: Writing - review & editing Search for more papers by this author Guoping Zhao Guoping Zhao CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China CAS Key Laboratory for Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China Contribution: Writing - review & editing Search for more papers by this author Xiongfei Fu Corresponding Author Xiongfei Fu [email protected] orcid.org/0000-0003-3657-8296 CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Software, Supervision, Methodology, Writing - review & editing Search for more papers by this author Chenli Liu Corresponding Author Chenli Liu [email protected] orcid.org/0000-0003-3029-7207 CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China University of Chinese Academy of Sciences, Beijing, China Contribution: Conceptualization, Supervision, Methodology, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Author Information Ting Wei1,†, Wangsheng Lai1,†, Qian Chen1,2,†, Yi Zhang1,†, Chenjian Sun1,2, Xionglei He3, Guoping Zhao1,4, Xiongfei Fu *,1,2 and Chenli Liu *,1,2 1CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China 2University of Chinese Academy of Sciences, Beijing, China 3State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China 4CAS Key Laboratory for Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China † These authors contributed equally to this work *Corresponding author. Tel: +86 755 86585243; E-mail: [email protected] *Corresponding author. Tel: +86 755 86585245; E-mail: [email protected] Molecular Systems Biology (2022)18:e10934https://doi.org/10.15252/msb.202210934 PDFDownload PDF of article text and main figures.PDF PLUSDownload PDF of article text, main figures, expanded view figures and appendix. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid-controlling system or robotic platforms, which limits their popularization and application in general laboratories. Inspired by our previous study on bacterial range expansion, in this study, we report a system termed SPACE for rapid and extensively parallelizable evolution of biomolecules by introducing spatial dimensions into the landmark phage-assisted continuous evolution system. Specifically, M13 phages and chemotactic Escherichia coli cells were closely inoculated onto a semisolid agar. The phages came into contact with the expanding front of the bacterial range, and then comigrated with the bacteria. This system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. In a prototypical problem, SPACE remarkably simplified the process and evolved the promoter recognition of T7 RNA polymerase (RNAP) to a library of 96 random sequences in parallel. These results establish SPACE as a simple, easy to implement, and massively parallelizable platform for continuous directed evolution in general laboratories. Synopsis The spatial competition among phages that infect range-expanding host bacteria is exploited to develop a spatial continuous directed evolution system that is simple, easy to implement, and massively parallelizable. SPACE is a system for rapid and parallelizable evolution of biomolecules, which introduces spatial dimensions into the phage-assisted continuous evolution system. The system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. SPACE is applied to evolve the promoter recognition of T7 RNA polymerase to a library of 96 random sequences in parallel. Introduction Directed evolution mimics natural evolution and typically proceeds with iterative rounds of genotype diversification and selection for desired phenotype activity (Bloom & Arnold, 2009). The steps required in the library construction and selection/screening cycles of conventional directed evolution methods are generally labor-intensive and time-consuming. In order to improve the efficiency and reduce manual labor, researchers are exploring to bring in sophisticated mechanical instruments such as microfluidic/millifluidic systems (Agresti et al, 2010; Fallah-Araghi et al, 2012; Wong et al, 2018) and automated robotic platforms (Pham et al, 2017; Piatkevich et al, 2018; Chory et al, 2021). Continuous directed evolution methods, on the other hand, employ delicate biological designs to enable autonomous cycles of mutant library construction and selection by coupling gene functions of interest to the fitness of replicating organisms (Esvelt et al, 2011; Crook et al, 2016; Ravikumar et al, 2018; English et al, 2019), leading to rapid optimization of biomolecules with little human intervention required. One representative of these methods, phage-assisted continuous evolution (PACE) has been applied to evolve a wide range of protein functions such as the specificity of RNA polymerase, TALEN, and Cas9, target specificity and drug resistance of proteases, activity and target compatibility of base editors, and improved soluble expression of proteins (Esvelt et al, 2011; Carlson et al, 2014; Dickinson et al, 2014; Hubbard et al, 2015; Badran et al, 2016; Bryson et al, 2017; Packer et al, 2017; Hu et al, 2018; Wang et al, 2018; Thuronyi et al, 2019; Richter et al, 2020; Blum et al, 2021). It links the desired property of biomolecules to phage propagation to enable rapid rounds of evolution, and utilizes a chemostat-like apparatus (upper panel, Fig 1A) to constantly supply both uninfected host bacterial cells and a continuously diluted environment for selection. Although the PACE system has been brilliantly designed, the complexity of continuous culturing apparatus and requisite process control make it challenging to perform continuous directed evolution in a highly parallelized form (d'Oelsnitz & Ellington, 2018) unless it is facilitated with robotic platforms (DeBenedictis et al, 2022). This limits its use for important application tasks such as evolution toward multiple targets and in different conditions, or high experimental replication to map evolutionary trajectories (Harms & Thornton, 2013) in general laboratories not equipped with sophisticated microfluidic or robotic instruments. The once-humble agar plate is increasingly seen as a useful platform that can address questions not amenable to study by standard "well-mixed" liquid culture (Baym et al, 2016; Bosshard et al, 2017; Fraebel et al, 2017; Ni et al, 2017; Shih et al, 2018; Liu et al, 2019). For instance, it has recently been utilized to study the evolution of antibiotic resistance (Baym et al, 2016) and the colonization strategies of bacterial range expansion (Liu et al, 2019). In such studies, bacterial cells are typically inoculated at the center or edge of the semisolid agar plate. The subsequent range expansion of bacteria is led by a propagating front of growing cells (blue circle in lower panel of Fig 1A) moving outward toward the uncolonized territory, while cells with lower motility are left behind to grow until the nutrients are exhausted (Cremer et al, 2019). The steadily advancing front and associated growing wake thus provide a "moving chemostat" that harbors exponentially growing fresh cells (Koster et al, 2012; Cremer et al, 2019), with spontaneous separation from old cells whose growth and motility slow dramatically as nutrients are depleted (lower panel, Fig 1A). In this study, we sought to develop a new method that combines the advantages of spatial range expansion and PACE. Compared with conventional methods where evolution plays out only on the temporal dimension, bringing in spatial dimensions enables visualization, separation of different evolutionary events, and straightforward operation without requirements for special culturing or monitoring equipment. Results We began by inoculating M13 phages, which conduct chronic infections without lysing or severely damaging their host cells, (purple dot in Fig 1B) in front of a motile bacterial inoculum. A substantial fraction of the expanding cells in the front encountered phages and got infected, resulting in a slowdown of their subsequent growth (Appendix Fig S1). Progeny phages were then produced and carried forward along the expansion route by infecting neighboring fresh cells. This combination of cell migration and repeated phage infection cycles was expected to result in the formation of a visible fan-shaped infection zone with lower cell density than the uninfected regions (Li et al, 2020) (Fig 1B). Experiments showed that a suspension of exponentially growing Escherichia coli FM15 cells (Appendix Table S1), when inoculated at the center of an 8.5-cm Petri dish containing 10 ml of LB medium and 0.25% agar, formed a uniform bacterial lawn after overnight incubation (first row in Fig 1C). In contrast, inoculating bacteria at the center and 103 PFU of M13 phages 1 cm away from the center of an identical semisolid agar plate led to formation of a dark (low cell density) fan-shaped pattern in the midst of a white (high cell density) bacterial lawn after overnight incubation (second row in Fig 1C). The fan-shaped pattern of low cell density area was stable for days until the agar dried up. To gain a quantitative understanding of the patterning process, we developed a mathematical model, RESIR (Range Expansion with Susceptible Infected Recovered kinetics) model derived from previous models (Kermack & McKendrick, 1927; Cremer et al, 2019), based on the characterized properties of the bacteria–phage interaction (Fig EV1A, Appendix Fig S2, Materials and Methods). In our model, numerical simulations with realistic parameter values (Appendix Table S2) recaptured the fan-shaped pattern as the experiments (bottom two rows in Fig 1C). The saturated cell density in this fan-shaped region is lower than that of uninfected region because the nutrient is partially consumed by phage production and is hence less available for supporting bacterial growth (Appendix Fig S3), thereby yielding a visible low cell density region. The development of the fan-shaped pattern was mainly driven by the expansion in the radial direction, supplemented by the extension in the lateral direction (Fig EV1B). Figure 1. Formation of the fan-shaped pattern by phage infection during bacterial range expansion A. Illustration of the analogy between bacterial range expansion in a semisolid agar plate and a chemostat-like continuous culturing device. B. Phage propagation during bacterial range expansion leads to the formation of a visible fan-shaped region of lower cell density. C. Time-lapse photographs of typical patterns obtained for bacteria alone and bacteria with phage, with corresponding model simulations. Scale bar represents 1 cm. D. The plot of the simulated phage-titer profile along bacterial expanding front at the time point of 24 h. The position of expanding front is shown by the red arc line in the schematic. E. Design of a reporter phage M13-GFP for fluorescence imaging of phage-infected region. F. Visualization of infected region. Escherichia coli FM15 was inoculated at the center of a semisolid agar plate and the reporter phage M13-GFP was inoculated 1-cm away from the center. Fluorescence images (Materials and Methods) were captured after overnight incubation using FITC channel and an exposure time of 200 ms. Scale bar represents 1 cm. G. Relative fluorescence intensity at the center and edge positions of the infection zone as shown in (F). The relative intensity was obtained by dividing the detected values with the maximum value of green fluorescence intensity on the plate. Data represent mean values ± s.d. for three values of the center and six values of the edge from three biological replicates. Two-tailed t-test was used to compare two groups. ***P = 0.0005. Source data are available online for this figure. Source Data for Figure 1 [msb202210934-sup-0003-SDataFig1.zip] Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Kinetic model of the interaction between bacteria and phage A. The bacterial populations are classified into three categories: susceptible, infected, and recovered bacteria. Infected bacteria are converted from susceptible bacteria by phage infection, and eventually become recovered bacteria. These three bacterial populations all proliferate by consuming the nutrition in the semisolid culture media. In our experimental system, motile bacteria expand their range into unoccupied territories by diffusion and chemotaxis. In the meantime, the nonmotile phages are transmitted by their host bacteria, and their titer depends on the level of infectious progeny phage production by infected and recovered bacteria. The details of this model are described in Materials and Methods and Appendix Table S2. B. The spatiotemporal dynamics of phage infection in the radial direction (①) and the lateral direction (②) of the fan-shaped infection region are distinct from each other. In the radial direction, the expansion of infection range is driven by a "hitchhiking effect" (Ping et al, 2020), that is, phages are transported by the bacteria at the moving front. The bacterial population at the front experiences an active infection process involving the emergence of infected and recovered cells, the annihilation of susceptible cells, and eventually all cells become recovered cells, maintaining a balance between cell growth at the front and back diffusion (Cremer et al, 2019) (③). Differently, along the sideward edge, the expansion of infection range is driven by a "relay effect" of infected bacteria in the lateral direction, that is, infected bacteria from the infected region invade into the uninfected region, in which they produce phages continuously encountering and infecting susceptible bacterial cells. This cycle repeats and shows a relay-like effect, effectively generating a moving boundary between the infected and uninfected regions, which is eventually presented as the sideward edge (②). C. Model prediction showing that the size of the fan-shaped pattern is positively correlated with the phage production rate. Source data are available online for this figure. Download figure Download PowerPoint One prediction of the model was that, at the boundaries of the fan, uninfected cells migrating side by side with infected cells continuously served as fresh hosts for progeny phages during the range expansion, resulting in a moderately higher phage titer at the sideward edge than in the central region of the fan-shaped infection zone (Fig 1C and D). To verify this, we visualized the phage-infected bacteria by introducing a fluorescence gene accompanied with phage infection. Specifically, we constructed a reporter phage M13-GFP harboring a "superfolder" variant of green fluorescent protein (gfp) gene located downstream of gene IV in the wild-type M13 phage genome. The infection of M13-GFP phage introduces the gfp gene into the host bacteria. Thus, the bacteria infected by M13-GFP phage could be visualized by the fluorescent signal which reflects the expression level of phage genes locally (Fig 1E). As shown in Fig 1F and G, the brightest fluorescent signals in the semisolid agar plate, which suggested the highest cumulative expression of genes in the phage genome including gfp, overlapped with the sideward edge of the infection zone, consistent with the model simulation (Fig 1D). The model simulation also predicted that the size of the fan-shaped pattern increased with the phage production rate (Fig EV1C). To test the proportionality predicted by the model, we borrowed one key design in PACE, an activity-dependent phage propagation module located in an accessory plasmid (Esvelt et al, 2011), which constructs a linkage between the function of the biomolecule to be evolved and phage propagation via the activation of gIII expression. It is known that the production of M13 phage scales with increasing levels of its minor coat protein pIII (encoded by gIII) over concentrations spanning two orders of magnitude (Rakonjac & Model, 1998). We used this design to vary the phage production rate by altering the expression level of gIII. Specifically, a selection phage (Esvelt et al, 2011) was constructed by replacing the intrinsic gIII of the M13 genome with the wild-type T7 RNA polymerase (RNAP) gene, while a copy of gIII was inserted into an accessory plasmid (Esvelt et al, 2011) in the host E. coli cell (Fig EV2A). The expression of gIII was put under the control of a library of 17 T7 promoter variants (Appendix Table S3), on which wild-type T7 RNAP exhibits different levels of activities ranging from 0.005 to 85% of the activity of wild-type T7 RNAP on the T7 promoter (Fig EV2B). When a high-copy-number accessory plasmid was used (Materials and Methods, Appendix Table S4), the area sizes of the fan-shaped pattern steadily increased with increasing expression levels of gIII, saturating at an activity level approximately 1.7% of the wild-type T7 RNAP activity on the T7 promoter (Fig EV2C). To distinguish more finely between high expression levels, a low-copy-number accessory plasmid was employed (Materials and Methods, Appendix Table S4). The combined utilization of the high- and low-copy-number accessory plasmids provided a measurement range of expression activity spanning 4 orders of magnitude (Fig EV2D). These results suggested that the area of the fan-shaped pattern could be used as a straightforward assessment of the activity of interest. We first used the high-copy-number accessory plasmid unless noted otherwise. Click here to expand this figure. Figure EV2. Relationship between the area of the fan-shaped pattern and the gIII expression level A. An activity-dependent phage propagation cassette on accessory plasmid. Expression level of gIII is under the control of a library of synthetic promoter variants. Selection phage carries a wild-type T7 RNA polymerase (RNAP) gene in place of its gIII. The T7 RNAP exhibits different transcriptional activities on different promoter variants. B. Relative expression levels of 17 synthetic promoter variants (sequences shown in Appendix Table S3) were determined by in vivo transcriptional activity assay (Materials and Methods). Error bars represent s.d. of three biologically independent assays. C. Photographs of a quarter of the semisolid agar plates with typical patterns obtained for bacteria carrying accessory plasmids containing representative promoters with different expression activities in (B). Scale bar represents 1 cm. D. Relationship between the area of the fan-shaped pattern and the gIII expression level. Data represent mean ± s.d. for at least three biological replicates. Fitting lines are generated with functions and for high- and low-copy accessory plasmids, respectively. Source data are available online for this figure. Download figure Download PowerPoint To develop our system of spatial directed evolution, we next sought to modulate the second key design in PACE, the mutagenesis plasmid (Badran & Liu, 2015; Bryson et al, 2017), to match the needs of the applications in semisolid media. The mutagenesis plasmid (MP4) typically used in PACE includes three mutators: DnaQ926, a dominant negative mutant of the delta domain of E. coli DNA polymerase, Dam, DNA adenine methyltransferase, and SeqA, a negative regulator of replication initiation (Badran & Liu, 2015). The expression of these mutator genes is driven by a small molecule inducer arabinose. Differently, for our spatial evolution system, we employed phage shock protein promoter (Ppsp) (Brissette et al, 1990, 1991) to drive the expression of the mutators upon M13 phage infection via a pIV-dependent signaling cascade (Brissette et al, 1991), generating the mutagenesis plasmid MP-s for this study (Appendix Table S4). The stringency of the Ppsp was confirmed by using E. coli FM15 cells carrying a plasmid with gfp under the control of Ppsp (Fig 2A). The cells exhibited green fluorescence only in the presence of phage infection (Fig 2B), confirming the stringency of this promoter could prevent undesired induction of mutagenesis in bacteria cells before they came into contact with phages. The mutation rate conferred by MP-s was measured to be comparable to that of MP4, which is 4.4 × 10−7 and approximately 5.9 × 10−4 substitutions per bp per generation for E. coli and M13 phage, respectively (Badran & Liu, 2015; Materials and Methods). Figure 2. Establishment of a prototypic SPACE system A. Reporter system to verify phage infection-inducible expression of proteins conferred by the phage shock protein (psp) promoter via a pIV-dependent signaling cascade (Brissette et al, 1991). In the mutagenesis plasmid MP-s developed in this study, gfp was replaced with mutator genes (Badran & Liu, 2015). B. Microscopic images of E. coli FM15 cells carrying a plasmid with gfp gene downstream of the psp promoter with or without wild-type M13 phage infection. Scale bar: 1 μm. C. Schematic design of SPACE coupling T7 RNAP activity with the expression of gIII. The host bacteria carry a mutagenesis module and an activity-dependent phage propagation module, which are harbored by the mutagenesis plasmid MP-s and the accessory plasmid, respectively. D. Photographs of a quarter of the semisolid agar plate of a SPACE experiment using high-copy accessory plasmid to improve within-cell activity of T7 RNAP on a synthetic promoter 1D8. An E. coli FM15 strain carrying no MP was used as control. Scale bar: 1 cm. E. Activity in cells of T7 RNAP and its mutants from the SPACE experiment in (D). Two clones of the ancestor and five clones of the mutants obtained from the evolution towards 1D8 recognition were measured by in vivo transcriptional assay (Materials and Methods). Two-tailed t-test was used to compare the two groups. ***P = 0.0001. Data represent mean values ± s.d. Source data are available online for this figure. Source Data for Figure 2 [msb202210934-sup-0004-SDataFig2.xlsx] Download figure Download PowerPoint By introduction of the accessory plasmid carrying the activity-dependent phage propagation module and MP-s carrying the in vivo mutagenesis module into our motile host strain, E. coli FM15, we established a prototypic system named as SPACE, standing for Spatial PACE. In SPACE, ancestor selection phages (Esvelt et al, 2011) carrying a wild-type T7 RNAP gene infect bacterial cells, and the expression of mutator genes induced by the infection leads to mutations in the RNAP gene during the replication of phage genome, and then expression of different RNAP variants. Desired RNAP variants with improved activity on the target synthetic promoter activate the expression of gIII on an accessory plasmid to produce infectious progeny phages, which in turn infect neighboring susceptible bacterial cells and repeat the process (Fig 2C). In contrast, RNAP variants