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A Plasmid System with Tunable Copy Number bioRxiv preprint doi: https://doi.org/10.1101/2021.07.13.451660; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 A Plasmid System with Tunable Copy Number 2 Miles V. Rouches and Yasu Xu 3 Field of Biophysics, Cornell University, Ithaca, NY 14853, USA ∗ 4 Louis Cortes and Guillaume Lambert 5 School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14853, USA 6 (Dated: July 13, 2021) Plasmids are one of the most commonly used and time-tested molecular biology platforms for genetic engineering and recombinant gene expression in bacteria. Despite their ubiquity, little consideration is given to metabolic effects and fitness costs of plasmid copy numbers on engineered genetic systems. Here, we introduce two systems that allow for the finely-tuned control of plasmid copy number: a plasmid with an anhydrotetracycline-controlled copy number, and a massively parallel assay that is used to generate a continuous spectrum of ColE1-based copy number variants. Using these systems, we investigate the effects of plasmid copy number on cellular growth rates, gene expression, biosynthesis, and genetic circuit performance. We perform single-cell timelapse measurements to characterize plasmid loss, runaway plasmid replication, and quantify the impact of plasmid copy number on the variability of gene expression. Using our massively parallel assay, we find that each plasmid imposes a 0.063% linear metabolic burden on their hosts, hinting at a simple relationship between metabolic burdens and plasmid DNA synthesis. Our plasmid system with tunable copy number should allow for a precise control of gene expression and highlight the importance of tuning plasmid copy number as tool for the optimization of synthetic biological systems. 7 INTRODUCTION 37 based plasmids to study the impact of copy number on 38 cellular growth and metabolism. Specifically, we first in- 39 8 Plasmids are an invaluable tool in biotechnology and troduce a strategy for finely tuning plasmid copy number 40 9 genetic engineering due to their small size and the ease in a way that is dependent on the concentration of an ex- 41 10 with which they can be engineered for biotechnological ogenous inducer molecule. Then, we develop a method 42 11 applications. Recent studies have highlighted the poten- which uses a massively parallelized assay for rapid screen- 43 12 tial benefits of fine-tuning plasmid copy number to the ing of the dependence of a system on plasmid copy num- 44 13 task at hand. For example, runaway replication has been ber. 14 used as a method for increasing cellular protein produc- 15 tion [1, 2]. Recent works have also leveraged plasmid 16 copy numbers to amplify a signal through a large increase 17 in copy number [3, 4] and to increase the cooperativity 18 and robustness of synthetic gene circuits [5]. Single cell 19 measurements have also been used to accurately quantify 20 the prevalence of plasmid loss within a population [6]. 21 While recent studies have probed the effect of plas- 22 mid copy number on host cell growth [7, 8] and the role 45 We further characterize our systems at both the macro- 23 of plasmids on central metabolic processes [9], we still 46 scopic and single cell level to uncover a relationship be- 24 lack a quantitative description of the relationship be- 47 tween gene copy number, protein production, and cellular 25 tween plasmid copy number and host metabolic burden. 48 growth rates. Our approach also leads to insights into the 26 Indeed, recombinant gene expression results in signifi- 49 variation in plasmid copy numbers and the phenomena 27 cant metabolic burden on bacterial cells [10{12] which 50 of plasmid loss and runaway replication at the single- 28 may interfere with normal cellular processes and even 51 cell level. We finally demonstrate that manipulations of 29 lead to cessation of growth. The control of plasmid copy 52 plasmid copy numbers can be used to tune the behav- 30 number can also drastically alter the behavior of simple 53 ior of synthetic gene circuits such as a simple CRISPRi 31 repression systems [13, 14] which may significantly im- 54 genetic inverter, and control the expression of complex 32 pact engineered gene circuits and should be important 55 biosynthetic pathways to optimize the production of the 33 considerations for plasmid-based biotechnology and bio- 56 pigment Violacein. Our work thus provides a straightfor- 34 engineering applications 57 ward method for generating copy number variants from 35 In this work, we use two novel approaches to actively 58 a specific plasmid backbone, which we anticipate will ex- 36 control the copy number of pUC19 and other ColE1- 59 pand the synthetic biology toolkit and constitute the ba- 60 sis for more nuanced attention to plasmid copy number 61 in synthetic gene circuits, protein biosynthesis, and other ∗ Corresponding author 62 biotechnological applications. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.13.451660; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 2 A pUC19 Plasmid map D E 0.03 Inhibition window 100 Pbla Pp,kp (n steps) Plac RNA-p 0.02 +1 +111 +360 +555 MCS pUC-pTet 1 10 Ptet 0.01 ampR ORI LacZa OD 600 P ,k 0 RNA-i i i 0 300 600 Time (mins) Growth rate (1/min) Plasmid Copy Number 1 B RNA-p C 0 0.01 0.1 1 10 100 1 10 100 aTc Concentration (ng/ml) Copy number RNA-i 100 1000 RNA-i/p 10 transcription PCN 1 F pUC-pLac G 100 0 60 120 Division time 0.020 ρ 300 pUC19 copy number Plac 10 0.015 RNA-i/p RNA-p hyperbolic (n=1) binding priming 200 Runaway replication 1 stableexponential plasmid copy (n=∞) number 0.010 Plasmid Copy Number 1 100 OD 600 0 0.005 0 300 600 Plasmid loss Time (mins) Growth Rate (1/min) Plasmid Copy Number 30 RNA-p 0.00 0.25 0.50 0.75 1.00 1.25 -4 -2 0 0.000 release 0 10 10 10 30 100 200 300 No Plasmid RNA production ratio IPTG Concentration (mM) Copy Number replication replication ( ) Fig. 1. Replication of ColE1 Origin Plasmids. A) Map of the pUC19 plasmid. The origin of replication consists of a 555 bp region containing the priming RNA (RNA-p), the inhibitory RNA (RNA-i), the inhibition window, and the site of replication initiation (ORI). B) Diagram of the steps leading to ColE1 replication. In the ColE1 Origin, reversible binding of the inhibitory RNA-i to RNA-p exercises control over the copy number by inhibiting replication (left branch). Production of RNA-p transcript may result hybridization with the ORI, which leads to plasmid replication (right branch). C) Predicted plasmid copy number for hyperbolic (upper) and exponential (lower) initiation models [15] plotted as a function of RNA-p transcription initiation rate. Inset shows the predicted dependence of plasmid copy number on host cell division time. Model parameters: = 0:545 = min, ρ = 0:65, r = 0:01 = min, ki = 0:95 = min. D) Plasmid copy number measurements made by digital droplet PCR of the aTc- inducible pUC-pTet plasmid at increasing aTc concentrations. E) Growth rates of cells hosting the pUC-pTet plasmid at increasing plasmid copy numbers. We see a marginal effect of plasmid copy number on cellular growth rates, inset shows individual growth curves colored by aTc concentration. F) Plasmid copy number measurements of a plasmid which contains an additional copy of the inhibitory RNA under the control of an IPTG-inducible promoter. G) Growth rate vs plasmid copy number of the IPTG-inducible plasmid shows a strong metabolic burden at high levels of RNA-i expression. 63 RESULTS 84 division. 85 Specifically, as the ratio of RNA-p transcription rate 86 kp to RNA-i transcription rate ki is increased, plasmid 64 Model of ColE1 Plasmid Replication and Copy 87 copy number N will also increase according to 65 Number p " 1 #n 66 The molecular mechanisms that regulate plasmid copy + r ρk n N = p − 1 (1) 67 number control have been well characterized [16]. In p ki − kp r 68 the ColE1 origin of replication, used extensively in this 69 work, two RNAs control replication (Fig. 1A): the prim- 88 where is the RNA degradation rate, ρ is the RNA-p 70 ing RNA (RNA-p), which acts in cis as a primer near 89 priming probability, r is the cellular growth rate, and 71 the origin of replication, and the inhibitory RNA (RNA- 90 n is the number of rate-limiting steps in the inhibition 72 i) which is transcribed antisense to RNA-p and acts in 91 window [15]. The n ! 1 and n ! 1 limits represent 73 trans to inhibit replication through binding to the prim- 92 hyperbolic and exponential inhibition, respectively (Fig. 74 ing RNA prior to hybridization near the origin (Fig. 1B) 93 1C). 75 [17]. 94 As the priming:inhibitory RNA production ratio kp=ki 76 A simple macroscopic-scale model developed by Pauls- 95 approaches 1, the number of inhibitory RNA will not 77 son et al. recapitulates these observations and predicts 96 be present in high enough number to sequester priming 78 the functional dependence of plasmid copy number on the 97 RNA transcripts, thereby failing to limit plasmids from 79 molecular details of this process [15] (Fig.
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