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A Plasmid System with Tunable Copy Number 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 16, 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 e↵ects 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 e↵ects 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 enables the precise control of gene expression and highlight the importance of tuning plasmid copy number as a tool for the optimization of synthetic biological systems. 7 INTRODUCTION 38 cellular growth and metabolism. Specifically, we first in- 39 troduce a strategy for finely tuning plasmid copy number 40 8 Plasmids are an invaluable tool in biotechnology and in a way that is dependent on the concentration of an ex- 41 9 genetic engineering due to their small size and the ease ogenous inducer molecule. Then, we develop a method 42 10 with which they can be engineered for biotechnological which uses a massively parallelized assay for rapid screen- 43 11 applications. Recent studies have highlighted the poten- ing of the dependence of a system on plasmid copy num- 44 12 tial benefits of fine-tuning plasmid copy number to the ber. 13 task at hand. For example, runaway replication has been 45 We further characterize our systems at both the macro- 14 used as a method for increasing cellular protein produc- 46 scopic and single cell level to uncover a relationship be- 15 tion [1, 2]. Recent works have also leveraged plasmid 47 tween gene copy number, protein production, and cellular 16 copy numbers to amplify a signal through a large increase 48 growth rates. Our approach also leads to insights into the 17 in copy number [3, 4] and to increase the cooperativity 49 variation in plasmid copy numbers and the phenomena 18 and robustness of synthetic gene circuits [5]. Single cell 50 of plasmid loss and runaway replication at the single- 19 measurements have also been used to accurately quantify 51 cell level. We finally demonstrate that manipulations of 20 the prevalence of plasmid loss within a population [6]. 52 plasmid copy numbers can be used to tune the behav- 21 While recent studies have probed the e↵ect of plas- 53 ior of synthetic gene circuits such as a simple CRISPRi 22 mid copy number on host cell growth [7, 8] and the role 54 genetic inverter, and control the expression of complex 23 of plasmids on central metabolic processes [9], we still 55 biosynthetic pathways to optimize the production of the 24 lack a quantitative description of the relationship be- 56 pigment Violacein. Our work thus provides a straightfor- 25 tween plasmid copy number and host metabolic burden. 57 ward method for generating copy number variants from 26 Indeed, recombinant gene expression results in signifi- 58 a specific plasmid backbone, which we anticipate will ex- 27 cant metabolic burden on bacterial cells [10–12] which 59 pand the synthetic biology toolkit and constitute the ba- 28 may interfere with normal cellular processes and even 60 sis for more nuanced attention to plasmid copy number 29 lead to cessation of growth. The control of plasmid copy 61 in synthetic gene circuits, protein biosynthesis, and other 30 number can also drastically alter the behavior of simple 62 biotechnological applications. 31 repression systems [13, 14] which may significantly im- 32 pact engineered gene circuits and should be important 33 considerations for plasmid-based biotechnology and bio- 63 RESULTS 34 engineering applications 35 In this work, we use two novel approaches to actively 64 Model of ColE1 Plasmid Replication and Copy 36 control the copy number of pUC19 and other ColE1- 65 Number 37 based plasmids to study the impact of copy number on 66 The molecular mechanisms that regulate plasmid copy 67 number control have been well characterized [16]. In Corresponding author ⇤ 68 the ColE1 origin of replication, used extensively in this 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 ampR ORI LacZa 0.01 P ,k OD 600 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 0.015 RNA-i/p 10 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) 30 Growth Rate (1/min) RNA-p Plasmid Copy Number 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 555bp 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 triggers plasmid replication through the hybridization of RNA-p with the ORI (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, ⇢ =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 e↵ect 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. 69 work, two RNAs control replication (Fig. 1A): the prim- 88 where ✏ is the RNA degradation rate, ⇢ 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 limits represent ! !1 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-to-inhibitory RNA production ratio 76 A simple macroscopic-scale model developed by Pauls- 95 kp/ki approaches 1, the number of inhibitory RNA will 77 son et al. recapitulates these observations and predicts 96 not be present in high enough number to sequester prim- 78 the functional dependence of plasmid copy number on the 97 ing RNA transcripts, thereby failing to limit plasmids 79 molecular details of this process [15] (Fig. 1C). This pro- 98 from duplicating in a process called runaway replication 80 cess is classified as inhibitor-dilution copy number control 99 (Fig. 1C). In addition, increasing the plasmid copy num- 81 [18], owing to the fact that the copy number is controlled 100 ber may increase the metabolic burden associated with 82 through a combination of replication inhibition and dilu- 101 plasmid expression and reduce the growth rate r,which 83 tion of plasmids and regulatory components due to cell 102 in turn increases the plasmid copy number further as 84 division. 103 r 0. ! 85 Specifically, as the ratio of RNA-p transcription rate 104 On the other hand, as the RNA production ratio kp/ki 86 kp to RNA-i transcription rate ki is increased, plasmid 105 decreases, the number of plasmids inside each cell will ap- 87 copy number Np will also increase according to 106 proach 1 and small variations in the number of plasmids 107 apportioned to each daughter cell during cell divisions 108 may lead to the catastrophic consequence of plasmid loss.
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