Expanding the toolbox of broad host-range transcriptional terminators

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Letter

Expanding the toolbox of broad host-range transcriptional terminators for Proteobacteria through metagenomics Vanesa Amarelle, Ananda Sanches-Medeiros, Rafael Silva-Rocha, and María-Eugenia Guazzaroni ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.8b00507 • Publication Date (Web): 03 Apr 2019 Downloaded from http://pubs.acs.org on April 3, 2019

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ACS Synthetic Biology

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Expanding the toolbox of broad host-range transcriptional terminators for

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Proteobacteria through metagenomics

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by

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Vanesa Amarelle1,3#, Ananda Sanches-Medeiros2#, Rafael Silva-Rocha2 and María-Eugenia

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Guazzaroni3*

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1Department

of Microbial Biochemistry and Genomics, Biological Research Institute

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Clemente Estable, Montevideo, Uruguay

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2FMRP

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3FFCLRP

- University of São Paulo, Ribeirão Preto, SP, Brazil - University of São Paulo, Ribeirão Preto, SP, Brazil

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#Both

authors contributed equally for this work

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Running Title: Mining broad-host range transcriptional terminators

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Keywords: transcriptional terminators, functional metagenomics, synthetic biology,

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biological parts, Proteobacteria

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___________________________________________________________________________

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*Correspondence to: María-Eugenia Guazzaroni, [email protected]

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Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Av.

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Bandeirantes, 3.900. CEP: 14049-901, Ribeirão Preto, São Paulo, Brazil.

ACS Paragon Plus Environment

ACS Synthetic Biology 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Abstract

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As the field of synthetic biology moves towards the utilization of novel bacterial chassis,

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there is a growing need for biological parts with enhanced performance in a wide number of

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hosts. Is not unusual that biological parts (such as promoters and terminators), initially

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characterized in the model bacterium Escherichia coli, do not perform well when

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implemented in alternative hosts, such as Pseudomonas, therefore limiting the construction of

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synthetic circuits in industrially relevant bacteria, for instance Pseudomonas putida. In order

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to address this limitation, we present here the mining of transcriptional terminators through

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functional metagenomics to identify novel parts with broad host-range activity. Using a GFP-

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based terminator trap strategy and a broad host-range plasmid, we identified 20 clones with

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potential terminator activity in P. putida. Further characterization allowed the identification of

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4 unique sequences ranging from 58 bp to 181 bp long that efficiently terminates transcription

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in P. putida, E. coli, Burkholderia phymatum and two Pseudomonas strains isolated from

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Antarctica. Therefore, this work presents a new set of biological parts useful for the

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engineering of synthetic circuits in Proteobacteria.

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Introduction

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Bacteria play a central role in the biotechnology industry and the field of synthetic biology is

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rapidly growing towards the generation of novel tools and protocols for the engineering of

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these organisms 1,2. In order to take advantage of their full potential, it is essential to have an

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efficient set of tools that can be used in organisms with relevant features related to the

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application intended. For example, E. coli is a classical host in terms of protein production

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and metabolic engineering 3, while gram-positive bacteria such as Streptomyces hold the

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potential for the production of small bioactive molecules 4. By the same token, the natural

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features of Salmonella make them a suitable host for tumor targeting applications 5, while the


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metabolic robustness and versatility of Pseudomonas make these bacteria promising chassis

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for harsh industrial conditions 6. Yet, most genetic tools have been initially constructed for E.

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coli and it is not unusual that biological parts required for synthetic circuit assemble are not

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fully functional in alternative hosts 2. In these cases, the initial failure of synthetic circuits

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constructed in alternative hosts leads to the need of intense re-adaptation of these parts to the

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new hosts

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there is a growing demand for orthogonal systems that could efficiently operate in a broad

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number of hosts

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novel expression systems 11, transformation/DNA delivery strategies 12,13 and plasmid vectors

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14,

7,8.

Therefore, as synthetic biologists turn towards non-classical bacterial chassis,

9,10.

Attempts in this direction have been made towards the construction of

among others.

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Recently, several reports have described the construction of novel expression systems, based

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on inducible as well as constitutive promoters, both with narrow or wide host-range 7,10,15,16,2.

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Yet, while much is known about transcription initiation, considerably less information is

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available about transcriptional termination

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mainly through two mechanisms. In intrinsic termination – also termed Rho-independent

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termination –, strong secondary structures are formed at the 3’ end of nascent RNA transcript

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which lead to the detachment of the RNA Polymerase (RNAP), and this mechanism does not

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seem to require any additional trans acting element

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termination requires a helicase which navigates the mRNA and actively detaches paused

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RNAPs 19. Similar mechanisms are found in Archaea and Eukarya 20. For the construction of

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complex synthetic circuits, efficient transcription termination sequences are required to ensure

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insulation of each part of the system. Failure in this process could lead to unwanted regulatory

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interactions. Yet, while some recent works have systematically characterized intrinsic

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terminators in bacteria, this has been mainly performed in the model organism E. coli

17,18.

In Bacteria, transcription termination occurs

17.

On the other hand, Rho-dependent


21,22.


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Therefore, there are few well-characterized fully functional terminator sequences that can be

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used in different bacterial hosts. In this sense, functional metagenomics holds the potential to

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access a great diversity of biological parts that can be used in a number of applications 23,24. In

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this work, we search for novel transcriptional terminators in soil microbial communities by a

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functional metagenomic approach. Using a GFP-based terminator trap broad host-range

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vector, we identified several candidate sequences by the functional screening of a

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metagenomic library constructed in Pseudomonas putida. We demonstrated that these new

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terminator sequences are functional in several Proteobacteria, including E. coli, and this new

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set of tools could be useful for novel synthetic biology projects in non-classical chassis.

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Results and discussion

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Mining transcriptional terminators in metagenomic libraries

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As presented above, while many transcriptional terminators have been well-characterized in E.

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coli, only few functional terminators are available for non-classical bacteria. As an example,

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the widely used minimal lambda T1 terminator from E. coli is not fully functional in P. putida

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KT2440, as this element allows readthrough when placed in broad host-range vectors (Fig.

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S1). In this sense, we hypothesize that an optimal terminator screening strategy would require

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these elements to be first validated in the organism of interest and only then assayed in E. coli.

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The overall strategy used in this work is schematically represented in Fig. 1. In order to

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identify novel transcriptional terminator elements, we constructed a metagenomic library

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from environmental DNA (eDNA) extracted from soil samples. For this purpose, a strong

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constitutive promoter (BBa_J23100) controlling the expression of a GFPlva reporter was

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cloned into the broad-host range vector pSEVA231

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14.

GFPlva is a modified version of the

Green Fluorescent Protein with reduced half-life, which is more suitable for the study of


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temporal gene expression. The resulting reporter vector was used for terminator trapping by

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cloning the eDNA in the region between the promoter and the ribosome binding site of

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GFPlva (Fig. 1). The constructs were introduced in P. putida KT2440 and the metagenomic

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library was screened for the lack or reduction in GFP signal. Using this approach, a total of

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163 colonies were screened and 20 colonies with apparent GFP signal reduction/absence were

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selected for further validation. Plasmid DNA extraction, digestion and DNA sequencing

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revealed that all 20 clones presented a DNA fragment ranging from 58 to 424 bp, with an

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average insert length of 211 bp (Table 1). These clones were randomly named T1 to T20 and

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were used for further experimental validation as described below. Table S1 provides

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information about sequence similarity, both at nucleotide and amino-acid level, of the

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metagenomic inserts.

112 25)

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Diverse algorithms (Mfold and ARNold, FindTerm

were applied in order to identify

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potential intrinsic terminators present in all the eDNA sequences cloned. FindTerm retrieved

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T18 as the only putative Rho-independent terminator, while the analysis of RNA secondary

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structure with Mfold allowed identifying a putative typical Rho-independent terminator in T1

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sequence. As these algorithms are designed to search for typical Rho-independent

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transcriptional terminator motifs, a hairpin structure followed by a poly-U tract, the presence

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of Rho-dependent terminators or even unusual Rho-independent terminators in the

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metagenomic sequences cannot be discarded, considering the diverse phylogenetic origin of

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the DNA sequences screened 26,27.

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Metagenomic approaches has allowed the investigation of the huge biochemical and genetic

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diversity present in the genomes of unculturable bacteria from a plethora of environmental

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samples (Handelsman et al. 1998; Alves et al, 2018). In particular, functional metagenomics



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have permitted the retrieval of a significative number of enzymes and other structural genes

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through a broad repertoire of activity-driven assays 28–30. However, the identification of novel

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bacterial regulatory elements using function-driven metagenomic strategies has been poorly

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explored, presenting at the moment a few examples directed to the recovery of new

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constitutive

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report of using a function-driven metagenomic approach for trapping terminator sequences.

31,32

or inducible promoters

33,34.

To the best of our knowledge, this is the first

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The novel transcriptional terminators display broad host-range activity

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Once we identified candidate terminators in P. putida, we further characterize these sequences

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by quantifying terminator activity in vivo. We selected seven candidate terminators with

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different efficiencies in P. putida for their assessment in the alternative hosts; therefore the

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results are focused on those seven terminators. As shown in Fig. 2A, all seven P. putida

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clones presented reduced GFP expression when compared to the positive control harboring

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pSEVA231-Pj100GFP plasmid, where no sequence is inserted between the strong promoter

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and the reporter gene. While some sequences presented only partial terminator activity (T2,

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T3 and T5), others presented expression levels very close to the negative control harboring

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pSEVA231 plasmid (such as for T1, T7, T9 and T12). It is worth noting that these four

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sequences were very short (between 58 and 181 bp long) (Table 1), resulting thus into

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promising new sequences for transcriptional termination in P. putida. The terminator effect

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was maintained for all constructs over a period of 8 hours (Fig. 2B). As shown in Fig. 2C, the

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presence of pSEVA231-Pj100GFP plasmid (C+) slightly affects growing if compared to the

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presence of the empty cloning vector pSEVA231 (C-). This agrees with previous reports

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where plasmids expressing a protein, such as GFP, proved to be metabolically demanding to

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the cell 35,36. Also in agreement with this trait is the fact that those plasmids harboring strong

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terminators displayed a growing pattern similar to cells harboring pSEVA231 (Fig. 2C). Is


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7 151

also interesting that the presence of T2 sequence, despite of having a reduce GFP expression

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when compared to the positive control (Fig. 2A and 2B), has a more profound effect on

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growing. This might suggest that the eDNA of T2 sequence might be somehow toxic to the

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cell. The characterization of the remaining 13 candidate sequences evidenced a wide range of

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termination efficiencies (Fig. S2).

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Once we analyzed the terminators in P. putida, we investigated their functionality in four

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additional Proteobacteria host. For this purpose, we introduced the plasmids presented in Fig.

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2 into E. coli DH10B, Burkholderia phymatum STM815T and two psychrotolerant

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Pseudomonas strains isolated from Antarctica

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Pseudomonas spp. UYIF41. As shown in Fig. 3A-B, all tested E. coli clones presented GFP

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expression levels virtually undistinguishable from the negative control, indicating that all

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seven terminator sequences were fully functional in this host. This result strengthens the

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notion that functional terminators in E. coli are not always active in other hosts such as P.

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putida. It is worth mentioning that plasmids were extracted from E. coli and the presence of

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the terminator sequences originally identified in P. putida were confirmed by PCR. When

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these terminators were analyzed in B. phymatum and the two psychrotolerant Pseudomonas

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strains (Fig. 3C-H), the termination profile was very similar to that of P. putida, where T1

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was the most effective terminator in all strains and a host-dependent efficiency for T7, T9 and

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T12 was observed. Also, the introduction of these constructs in all four strains did not cause a

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significant defect in growth under the experimental conditions assayed (Fig. S3). Taken

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together, these results demonstrate that the novel terminators identified in this work are highly

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functional in a broad range of bacterial strains.

37,

named as Pseudomonas spp. UYIF39 and

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The novel terminators are functional at single cell level



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While most characterization of biological parts are usually performed at population levels, the

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role of cell individuality is widely recognized as crucial for network performance

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sense, bacterial expression systems are usually categorized as having graded or all-or-none

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behavior, and these have strong consequences for the final circuit dynamics

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we decided to investigate how the newly-identified terminators behave at the single-cell level.

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For this purpose, the three best terminators (T1, T7 and T9) were assayed by flow cytometry

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in the five hosts. As shown in Fig. 4, while terminator T1 displayed a low-expression

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dynamics with a single population of cells similar to the negative control in all strains,

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terminators T7 and T9 displayed a low-expression population with broader distribution than

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the negative control, being distribution strain-dependent. In this sense, strains P. putida, B.

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phymatum and Pseudomonas spp. UYIF39 were more heterogeneous, yet with a single

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population present. Taken together, these results demonstrated that three of the strongest

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terminators identified in this work are efficient in transcription termination at the single-cell

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level as none of them displayed both, active and inactive, populations.

39,40.

38.

In this

Therefore,

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Conclusions

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In this work, we present a strategy for the mining of novel functional terminator sequences in

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Proteobacteria other than E. coli. Using a functional metagenomic approach, twenty

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terminators with different efficiencies and host-dependency were identified, being the most

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promising ones less than 200 bp. This set of new, short, and wide host-range terminator

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sequences could be crucial for future synthetic biology projects requiring complex circuits,

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since re-use of parts could lead to DNA rearrangements due to homologous recombination

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events. Also, the fact that these new elements are functional in several bacteria allows the user

200

to construct and test the circuit in one host and then implement it in a different one without


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the loss of functionality. We anticipate that similar functional metagenomic approaches could

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be used in the future to mine other broad host-range elements, such as RBS and promoters,

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increasing the toolbox for the construction of truly orthogonal synthetic circuits.

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Methods

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Bacterial strains, plasmids and growth conditions

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Bacteria and plasmids used in this study are detailed in supplementary Table S2. E. coli and

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Pseudomonas strains were grown aerobically at 30 °C or 25 °C (in the case of the Antarctica

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strains) and 200 rpm in either LB or M9 minimal media

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casamino acids and 1% glycerol as carbon source (M9-gly). Burkhordelia was grown in either

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TY

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(M9-fruc). When required, 50 µg/ml kanamycin (Km) or 25 µg/ml chloramphenicol (Cm)

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were added to the media.

41

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supplemented with 0.1 mM

or M9 minimal media supplemented with 0.1 mM casamino acids and 0.2% fructose

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Construction of the metagenomic library

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In order to build the terminator trap vector, a 857 pb DNA fragment harboring the GFPlva

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protein under the control of a strong synthetic constitutive promoter (BBa_J23100) was

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obtained from pMR1-Pj100 plasmid

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Pj100GFP region was later cloned at the HindIII/EcoRI sites of pSEVA231

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plasmid pSEVA231-Pj100GFP that was used for terminator trapping in eDNA. For this

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purpose, previously isolated eDNAs

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with Sau3AI enzyme to produce fragments between 100 bp and 400 bp that were cloned at the

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BamHI site of pSEVA231-Pj100GFP, which is located between Pj100 promoter and the

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ribosome binding site (RBS) of GFPlva gene. The constructs were introduced in P. putida by

42,

43

after digestion with HindIII/EcoRI. The resulting 14,

generating

obtained from soil samples were partially digested



10 226

electroporation. The metagenomic library was plated in LB Km and colonies were screened

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for the lack or reduction in GFP signal in a blue-light transilluminator. Colonies harboring

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putative terminator sequences from eDNA origin were selected for further analysis.

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Analysis of transcriptional terminator activity

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In order to quantify the termination efficiency, P. putida harboring putative transcriptional

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terminators were used to assess GFP expression in vivo. Single colonies were grown

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overnight in M9-gly at 30 ºC and 200 rpm. The overnight culture was placed in a 96-well

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plate and diluted 1:20 in 200 µl of M9-gly. The analysis was made using a Victor X3 plate

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reader (PerkinElmer) over a period of eight hours at 30 °C, measuring every 30 minutes the

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optical density 600 nm (OD) and fluorescence (excitation 488 nm and emission 535 nm). P.

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putida harboring either pSEVA231 or pSEVA231-Pj100GFP were used as negative and

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positive controls, respectively. All assays were done in technical triplicates in the same plate

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and in biological triplicates in different experiments.

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To assess the effectiveness of the terminator sequences found in P. putida in other

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Proteobacteria hosts, seven constructs were selected based on the strength of the putative

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terminator effect. Four plasmids harboring efficient terminator sequences (T1, T7, T9, T12)

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and three plasmids harboring medium terminators (T2, T3, T5) were obtain from P. putida

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and used to transform E. coli, Pseudomonas spp. UYIF39, Pseudomonas spp. UYIF41 and B.

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phymatum by electroporation. As negative and positive controls, all strains were transformed

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with either pSEVA231 or pSEVA231-Pj100GFP, respectively. For quantification of the

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termination efficiency in these hosts, GFP expression was assessed in vivo as mentioned

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before for P. putida, performing it at 30 °C for E. coli and, B. phymatum, and 25 °C for


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Pseudomonas spp. UYIF39 and UYIF41. For B. phymatum, M9-fruc media was used. The

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results were processed in R program (https://www.r-project.org/) using ad hoc scripts.

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In order to evaluate the termination efficiency at the single cell level, flow cytometry analysis

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was made for terminators T1, T7 and T9 in all hosts. For this purpose, a single colony from P.

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putida, E. coli, Pseudomonas spp. UYIF39, Pseudomonas spp. UYIF41 and B. phymathum

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strains harboring each of these constructs, plasmid pSEVA231 and plasmid pSEVA231-

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Pj100GFP were grown overnight in M9 media as aforementioned. Cells were diluted 1:10 in

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fresh M9 appropriate media and grown for an additional 6 hours. Cultures were stored in ice

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and sequentially analyzed on the Millipore Guava EasyCyte Mini Flow Cytometer, to

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quantify GFP fluorescence. For each sample three independent experiments were made. The

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data generated was processed with R scripts (https://www.r-project.org/), using the flowCore

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and flowViz packages, available on Bioconductor (https://bioconductor.org/).

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Analysis of terminator sequences

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Putative terminators were sequenced using primer 3gfp102 (5’-TCC GTA TGT TGC ATC

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ACC -3’). Sequences were trimmed from primers and subject to comparison with NCBI

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database using the BLAST algorithm (Blastn and Blastp). Sequences were aligned using

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ClustalW 44. Putative secondary structure of the terminator sequences at the RNA level were

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predicted with Mfold

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terminators, programs ARNold (http://rna.igmors.u-psud.fr/toolbox/arnold/) and FindTerm

271

were used with default parameters.

45

using default parameters. For the prediction of transcriptional

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Funding


25


12 274

This work was supported by the Young Research Awards by the Sao Paulo State Foundation

275

(FAPESP, award numbers 2015/04309-1 and 2012/21922-8). VA and ASM are beneficiaries

276

of National Agency for Research and Innovation (ANII) and FAPESP fellowships (VA,

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MOV_CA_2017_1_138168; AS-M, FAPESP PhD fellowship number 2018/04810-0),

278

respectively.

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Supporting Information

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Figure S1. Efficiency of T1 terminator in P. putida KT2440. Figure S2. Characterization of

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additional putative terminators in P. putida KT2440. Figure S3. Growth profile of bacterial

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strains harboring the different constructs. Table S1. Description of the ORFs contained in the

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metagenomic inserts and their sequence similarities. Table S2. Strains and plasmids used in

285

this study. References.

286 287

Acknowledgments

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The authors are thankful to lab colleagues for insightful discussion about this manuscript.

289 290

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Figure Legends

450


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19 451

Figure 1. Schematic representation of the strategy used in this study. A) Metagenomic

452

DNA fragments carrying potential transcriptional terminators were cloned between the strong

453

promoter Pj100 and the RBS (ribosome-binding site) in the reporter trap-vector pSEVA231-

454

Pj100GFP. Functional elements of the plasmid backbone are shown: KmR, antibiotic

455

resistance marker; oriT, origin of transfer; ori pBBR1, broad host-range origin of replication;

456

ter1 and ter0, transcriptional terminators. B) Metagenomic library clones presenting lack or

457

reduction in GFP signal, in a blue-light transilluminator, are indicated by arrows.

458 459

Figure 2. Characterization of novel terminators in P. putida KT2440. In order to

460

characterize the transcriptional termination effect in selected metagenomic clones, P. putida

461

KT2440 clones harboring the different reporter plasmids were grown in liquid M9-gly media

462

during 8h and the optical density at 600 nm (OD600) and fluorescence (GFP) were measured

463

every 30 min. P. putida harboring either pSEVA231 or pSEVA231-Pj100GFP were used as

464

negative (C-) and positive (C+) controls, respectively. A) Terminator activity at 4h. B)

465

Terminator activity (in log10 scale) over time. C) Growth curve of the P. putida clones (a

466

2.5x factor should be applied due to the optical path length).

467

All graphs represent the average from three independent experiments. Standard deviation

468

from three experiments is represented as vertical bars in A and as shaded regions in B and C.

469 470

Figure 3. Characterization of novel terminators in alternative hosts. In order to

471

characterize the transcriptional termination effect in alternative hosts other than P. putida,

472

plasmids were transferred to E. coli, B. phymatum and the psychrotolerant Pseudomonas spp.

473

UYIF39 and UYIF41. All the strains were grown in liquid M9, with the appropriate carbon

474

source, during 8h and the optical density at 600 nm (OD600) and fluorescence (GFP) were

475

measured every 30 min. Strains harboring either pSEVA231 or pSEVA231-Pj100GFP were



Page 20 of 27

20 476

used as negative (C-) and positive (C+) controls, respectively. A) Terminator activity (in

477

log10 scale) of E. coli clones over time. B) Terminator activity of the E. coli clones at 4h. C)

478

Terminator activity (in log10 scale) of B. phymatum clones over time. D) Terminator activity

479

of B. phymatum clones at 4h. E) Terminator activity (in log10 scale) of the Pseudomonas spp.

480

UYIF39 clones over time. F) Terminator activity of the Pseudomonas spp. UYIF39 clones at

481

four 4h. G) Terminator activity (in log10 scale) of the Pseudomonas spp. UYIF41 clones over

482

time. H) Terminator activity of the Pseudomonas spp. UYIF41 clones at 4h. All graphs

483

represent the average from three independent experiments. Standard deviation from three

484

experiments is represented as shaded regions in A, C, E and G, and as vertical bars in B, D, F

485

and H.

486 487

Figure 4. Flow cytometry analysis of three broad-host range terminators in different

488

hosts. Strains were gown in M9 media supplemented with an appropriate carbon source for

489

4h and analyzed by flow cytometry. Data from 20,000 events were collected and processed

490

using flowCore and flowVIz packages in R. The results are representative of three

491

independent experiments. Strains harboring either pSEVA231 or pSEVA231-Pj100GFP were

492

used as negative (-) and positive (+) controls, respectively.

493 494

Tables

495

Table 1. Sequences of the putative transcriptional terminators from eDNA identified in

496

this study. Name T1

Size (bp) 158

%GC

Sequence

63.9

5´GAGCGCATGCTCGAGTACTTCGCCTGGACCATGCTCGCCGTCGTCTTCGGCTTCCTGCT CTTCGTCAACCTCGCCTACGTCCCCCTCGGCCACTGGGCCGAGACCTTCGCCGGCTTCTTC AAATTTTCAGGGCTGCCGCACCCCATCGACTGGGGGCT-3´

T2

118

74.6

5´TCCGGGCCCGGTCACGGTCAGCGCGACGTCGTAGCTGCCCGCGGCGGCGTAGACGTG GGACGGGCTCGCGGACGTGGAGGTGCCGCCGTCTCCGAACGTCCATGCCCAGGAGGCG ACC-3´

T3

355

68.2

5´TGCGCTTCGACGCGGTGCCCGAACGCGTCGACGTGCATATCATCAACCGTCCCGGCCA


Page 21 of 27 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


21 GCCCTTCCTCGGCAGCGGCGAAACCGGCCAGGGCCCTGCGGCCGCTTCGATCGTGGACG GTCGGCTCCCTCGGGCGCCGATCTGCGATACGTTGAACTTTCAGCTGCTCGAGGTCGAG CGCGGTCGCGCCGTATTTCAGGGCACGCCGAAGCCCGAGCACTACAACCCGCTCGGCTC GATCCATGGCGGTTGGCCCGCGACGCTGCTCGACTCCTGCATGGCGTGCGCCGTGCACA CCACGCTCGCCGCGGGCCAGGGCTATACGACGGTGGAGTTCAAGCTGAATCTGGTGCG GCC-3´

T4

172

58.1

5´TGGGTTGGACCCGTTGCTTCGTGCAAGGTCGCCACGCTGTCCAGACCTATGCTCCCCA ACCGCGTAGATGGAACGTTAAGACGCCGGATGCTGGTTGCGTCGGTCCGGAAGTCCTCA CTGGCACGAACGTGGACCTCATACTGCTCGCCGTTTTCGTTATAGGTCGAGACTT-3´

T5

311

68

5ĆCGTGGCGCAGCCTGCAAAACACAAAAAGCGCCCGGAGGAACGTCTCCTGAAACGCG TCTTCGGCCTGCTGCGGTCCGAGCCTCCGGCGGAGGAGCGCCAGCACGATGCCTCGATG CTCCTCGTAGAAGGTCTCGAACGGCGGTATCGCCATCGCCTCCATCATGCTCTGAAACG GCCGAGGCGGGCGCCGCGTGAGATCACCGCCCGCGCCGATCTCGATTCGCCGGTTCTTG GCGCGGCCCTCGGCGGTGTCATTCCCCAAGGGAGACCGGCTGTCGGCGAACGAGACCG CGGCCAGGCGCGTCTTGTC-3´

T6

424

67.9

5´GTGCTCGATGGTCGAGAAGAGCAGAGGACGCCCGTCGTCAACCACCGTGGCGTTGAA GACTACGCCGGGACGGTTGCCCGCCCTTGCGTCGCGCTTCCAGTCGCCGAGCATGGCTT TCAGATCCCGATGCCCGGCACCGTGCACGGCGCGTAGCCGCCGAACAGCGGCTGCGGA GTCTGGAGCTTGCTGTTGTCGGCGATGCACATCAGCAGCACCATCGGCGCCTGGTGGGC GACCCAGGGCTGCACCGTCCCCACCCCCCCACGGTGCTTGCCCGCGCCGCACGAGTCCG TCCAGTGCTGCGACAGCGGCACGAGGATCGTATGAAATTCGGCGACATCATCGCGCTCG CGTGGCGCAATCTCCGGCAGGCCAGGCTGAGAACCTCGTTGACGGTCATCGGCGTCGTC GTCGGCGTCGCGGC-3´

T7

58

63.8

5ĆGCTCGTGCTCGCCGCGACCTTCCTCTTCATGCACCTCTTCGGCATCGGGCTGCACAA3´

T8

229

65.5

5´TCCGACCACGTTGTCGTCTCGTACCGCTCGCCGTGGACGTTCCTGACGTCGGCGTAGC GCGCGTAGAGCTGCGCGAGTGCGACGAAGCGATCGCCTCGTCATTGCGTCCATGGCCCG CCCACGCTTCGGCCATGTTCACGTAGGCCGAGACGATCCGCGGCGCATATTTTGCGCGC ACCGCGGCGTCGCCGCTCTTGACCGCGTCGATCATCCAGGTCGAGTGCTTGAT-3´

T9

181

54.7

5´GGAATCTCCTTCTCGCCTCTTTCGCTGAACACGAAAGCGAATCCGTTCAGCACACACT TTACGATATGGCGCAAAAAGTCCTCGGCTGCGTGCCGGAAGTGAAAGACATCCACCTCA CCATGCCCAACAAGCATTGCCTGCTCGTGGACCTGTCCCGCTTCGGTCAGGACAATCCC AACGA-3´

T10

175

54.9

5ĆCGTTTGATATTTGCCCCCGCTTTCAAAAAGAATGAGCTCGGCCCCAAGTTCGCGAAT CAACATGCGCCGTTCCTCGCTGGCCGTAGCGGACATGAGTATTGTGACTGCATACCCTT TGGCGGCTCCCACCATTGAAAGCGCGATTCCGGTATTGCCGCTGGAGCATTCGAGGAT3´

T11

249

62.6

5´TCCGCCACCTGCAGCAGGGCATGGACCACCGGCATCAACAACGGCGGAAAGCCGTCC ACTCTTCCGCGAAGCCACACTTCCGGTTGCTCGGTCATAGCACCACAGTACCAGCGTCG GCCCGCCAAGCTCCAGATGTCTCTTACAATCGCGAGTGATGCCGCGAGACTACGTGCCG CAACTGGCGACGCTCGTCAAGACGCCACCGCAGGGCGACGGCTGGTGGCACGAAATCA AGTTCGACGGCTATCG-3´

T12

129

69

5ĆTCGCTCTATCTCCATCACCCGACCGCGACCGACCCAAAAATGGCGCCGCCGGGCCAT TCGACCTTCTACGCGCTCGCGCCGGTCCCCCATCTCGGCAAATTCCCCGTCGACTGGGC GCGCGTCGGGCC-3´

T13

150

59.3

5´TTCACCCGGCCAGGAGCGGTGTGCTAATTCCTCGTTGACCATCACCGCATCGGGCGCG TCGGCGCTGTCGCGTTCGGTAAACTCGCGCCCCTTTAGAAGCCGAATACCCATCGCACG AAAATAGCCAACGGTAATCGCGCGATAATCCGC-3´

T14

251

60.2

5´GTGGCAGCCGCCAAGGCCGCCTATGCCCACGATTTCATCATGTCCTTTCCGCGCGGCT ATGACACACCGGTTGGCGAGCACGGCATGCAGCTCTCGGGTGGACAGCGTCAAAGAGT GGCTATCGCCCGCGCTCTCATTAAAAACGCACCGATCATTCTGCTTGACGAAGCAACGG CGGCGCTCGATTCCGAATCCGAGTTGCAGGTGCGTGAAGCCGTGGAACATCTCTGTCAA GGCCGCACGACGCTCGT-3´

T15

372

56.9

5´GGTGATTTCCTGGCGTACCAGTACGTCACTGACGTCAACTACAGCCGGGTGACCAACT TCAGCGAGATGGAGTTCGTCGTCCCCGGCCCCGGCGCCGTGGACGGGATACGTAAATGC



Page 22 of 27

22 TTTGCCGACACCGGGGGGCTGAACCACTCGGAAGTCATCCGGTTCATGGCCGACCGCCA AGAGATCGGTCTTTTGAGTCCGACCGCAGCGACATTTGCAACAAACTCCTTGAAGGCCT TTCGATTGCGGTCGCGAGGATTGACCACATCAATCAGATGCAAGGGGATTATCTCGATA GCAGGCAAGTTGGGAGGATCGCTCATGTAGCCTCCGCCAGTGTCGACCTCTCAATTAGG CTAATCACCCCCTCCAAGC-3´

T16

208

57.2

5´GCGACGAGAACTGCGACGGCATGCGCACCTGCTTCGCCAACGCCGACGGCGACATGT ATCGGACGGCGATCAGGATGCTCGCCGCGCGAAATTCGGCAATTCCGCTTGCATGCAGG AGCCCAATTTGAAAAACGGCTGCGGCGGTCTGCGCGATTTTCAAAATCTGCTCTGGATG ACTTTCTTCAAATATCGCACCCGCTCCCTCAAT-3´

T17

152

50.7

5´TGTTACCCAGCTCTGTAATTCGTGTGCAACCGAAGACATCCCTGACACTTCAATCCGA GGACATTCCTGACAGCTTTTGAGAGAGCTCTTTCTCCACCAGATCAGCCATCCTGCCTTT AGTTGGTGTGAAGGGGAGTGTAGGCACTTGTCG-3´

T18

266

64.7

5ÁTCGCGCGCACCGCGGAAGAACTGCTGCTGCTCGTGCCGAACACGCTGCGCGAGGGA GCGTTGGCGCTGGGGGCCACGCGCGCGCGCGCGGTGTTCAGCGTGGTTCTTCCGGCAGC CGCACCAGGGATCGCTGCGTGCCGAGTGTACCGATGCACATCTGCGATGTCGTCTGCCG TACGAGGCTTGAAATCTGCCGCCGCTGGGTGGGAAGACACTACATCAATCAGCTAAAA AGGCCTCCGTTCGGGAAGAACGGAGGCCCAAGT-3´

T19

224

68.7

5ÁCGTGGCGCTTGCCGGACGCGCCTTGCCGGAAGCGGCTCACGACGCCGTGAACGCTG CGCGCCATACCCCCCAAGCTGAGCGTGAGGGTCGCCGAGCGGCCGACGATATCGCGCA GCGCCGACGACGTCTCCTCGGTCGCCAGGGTCACCTGGAACTGAAACAGCTCCGAGATT GCCTCGACGCCCTCCAAGCGAACCAAGCGCAGCGCTTGGGAGACGCCGGT-3´

T20

86

67.4

5´TACGACCAGTGCAACTCGCTGCACACGAACGCCTACGACGAGGCGATCACGACGCCG ACCGAGGAGTCGGTGCGCCGCGCGATGGC-3´

497 498


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Page 24 of 27

A Page 25 of 27 ACS Synthetic Biology

Optical OD600 Density (600nm)

Fluorescence activity (GFP/OD) GFP expression (RU, log10)

1 2 3 4 5 6 7 8 9 10 11 B 12 13 14 15 16 17 18 19 20 21 22 23 24 25 C 26 27 28 29 30 31 32 33 34 35 36 37

GFP expression (RU, x10 )

Fluorescence intensity(GFP/OD) 5

Pseudomonas putida

10 1e+06 8 8e+05 6 6e+05 4 4e+05 2 2e+05 0 0e+00 C−

C+

T1

T2

T3

T5

T7

T9

T12

Pseudomonas putida

Terminators

6.0 5.5 5.0 4.5

T1 T2 T3 T5 T7 T9 T12 C+ C−

4.0 3.5 3.0 0

2

4

6

8

Time (h) putida Pseudomonas

0.30 0.25 0.20 0.15

T1 T2 T3 T5 T7 T9 T12 C+ C−

0.10 0.05


0.00 0

2

4 Time (h)

6

8


4.5

T1 T2 T3 T5 T7 T9 T12 C+ C−

4.0 3.5

E. coli

3.0

2

4

6

GFP expression (RU, x105)

5.0

Fluorescence intensity(GFP/OD)

5.5

250000 2.5 200000 2.0 150000 1.5

1.0 100000 0.5 50000 0

0 C−

8

C+

T1

Burkholderia Time (h)

3

B. phymatum 0

2

4

6

T7

T9

T12

T9

T12

1.5 150000 100000 1.0

0.5 50000 0

0 C−

C+

T1

T2

T3

T5

Pseudomonas 39 Terminators

GFP expression (RU, x10 )

1000000 10

5.0 4.5

T1 T2 T3 T5 T7 T9 T12 C+ C−

4.0 3.5

Pseudomonas UYIF39 0

2

4

6

800000 8 600000 6 400000 4 200000 2

00 C−

C+

T1

Time (h)

Pseudomonas UYIF41

5.5 5.0 4.5

T1 T2 T3 T5 T7 T9 T12 C+ C−

4.0 3.5

0

2

4

6

T3

T5

T7

Terminators

Pseudomonas 41

H

3.0

T2

8

Pseudomonas 41 6.0

T12

1200000 12

5.5

3.0

T9

200000 2.0

F

6.0

T7

250000 2.5

8

Pseudomonas 39 Time (h)

T5

3.0 300000

Fluorescence intensity(GFP/OD) 5

2

GFP expression (RU, x105)

T1 T2 T3 T5 T7 T9 T12 C+ C−

Fluorescence intensity(GFP/OD)

4

T3

3.5 350000

Fluorescence intensity(GFP/OD) GFP expression (RU, x105)

GFP Fluorescence expressionactivity (RU,(GFP/OD) log10)

5

T2

Terminators Burkholderia

D

6

Page 26 of 27

Escherichia coli

B

6.0

0

GFP expression (RU, log10) Fluorescence activity (GFP/OD)

1 2 3 4 5 6 7 8 9 10 11 C 12 13 14 15 16 17 18 19 20 21 22 23 24 E 25 26 27 28 29 30 31 32 33 34 35 36 37 G 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56

Fluorescence activity (GFP/OD) GFP expression (RU, log10)

A

GFP expression (RU, log10) Fluorescence activity (GFP/OD)

Escherichia coli

350000

3.5

300000

3.0

250000

2.5

200000

2.0

150000

1.5

100000

1.0

50000

0.5

0

0 ACS Paragon Plus Environment C− 8

C+

T1

T2

T3

T5

Time (h)

Terminators

T7

T9

T12

E. coli

Page 27 ofP.27putida Pseudomonas putida

B. phymatum

Pseudomonas UYIF39


Escherichia coli

GFPlog

Pseudomonas UYIF41

Pseudomonas 39

Burkholderia

Pseudomonas 41

GFPlog

GFPlog

GFPlog

GFPlog

-

1 2+ 3 4 T1 5 6 T7 7 8 T9 9 10 0 11 12 5 C−.fcs

5 C−.fcs

5 C−.fcs

5 C−.fcs

5 C−.fcs

4 C+.fcs

4 C+.fcs

4 C+.fcs

4 C+.fcs

4 C+.fcs

3 T1.fcs

3 T1.fcs

3 T1.fcs

3 T1.fcs

3 T1.fcs

2 T7.fcs

2 T7.fcs

2 T7.fcs

2 T7.fcs

2 T7.fcs

1 T9.fcs

0

1

2

2

GFP intensity

3

3

4

4

1 T9.fcs

1 T9.fcs

1 T9.fcs

1

0

0

1

1

2

2

GFP intensity

3

3

ACS Paragon Plus Environment 4

4

0

1

0

1

2

3

4

2

3

4

GFP intensity

GFP (log10)

1 T9.fcs

0

0

1

1

2

2

GFP intensity

3

3

4

4

0

0

1

1

2

2

GFP intensity

3

4

3

4

Expanding the toolbox of broad host-range transcriptional terminators

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