Melpomeni Dimopoulou
email: dimopoulou@i3s.unice.fr

Marc Antonini

Image storage in DNA using Vector Quantization

Rapid technological advances and the increasing use of social media has caused a tremendous increase in the generation of digital data, a fact that imposes nowadays a great challenge for the field of digital data storage due to the shortterm reliability of conventional storage devices. Hard disks, flash, tape or even optical storage have a durability of 5 to 20 years while running data centers also require huge amounts of energy. An alternative to hard drives is the use of DNA, which is life's information-storage material, as a means of digital data storage. Recent works have proven that storing digital data into DNA is not only feasible but also very promising as the DNA's biological properties allow the storage of a great amount of information into an extraordinary small volume for centuries or even longer with no loss of information. In this work we present an extended end-to-end storage workflow specifically designed for the efficient storage of images onto synthetic DNA. This workflow uses a new encoding algorithm which serves the needs of image compression while also being robust to the biological errors which may corrupt the encoding.

I. INTRODUCTION

Data explosion is one of the biggest challenges for the digital world as the development of efficient storage devices has reached a certain limit improving the storage density at a 20% every year while the equivalent data growth per year is estimated to increase by 60%. In short, we are about to have a serious data-storage problem that will only become more severe over time. Furthermore, a great percentage of the generated data is "cold" (very rarely accessed) but for legal and regulatory compliance reasons needs to be stored for a long duration (more than 50 years). Unfortunately conventional means of cold data storage such as hard disk drives or tapes have a very limited life-span from 5 to 20 years equivalently, requiring frequent maintenance and replacement of the storage devices. Some pioneer, yet very interesting works have studied the use of DNA, the genetic code of living organisms as an alternative approach for the storage of digital data. This can be achieved by encoding the digital information into a quaternary stream of A, T, C and G. One of the first attempts of encoding digital data into DNA is described in [START_REF] George M Church | Next-generation digital information storage in DNA[END_REF] by the works of Church et al. proposing a simple encoding of each binary bit to one nucleotide. To improve the encoding density as well as the robustness of the encoding to errors following works have adopted some more complex and efficient encoding algorithms. More precisely Goldman et al. in [START_REF] Goldman | Towards practical, high-capacity, low-maintenance information storage in synthesized DNA[END_REF] applies a ternary huffman algorithm to compress the binary sequence into a ternary stream of three symbols (trits). Then each of the This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 863320.

trits is encoded into a symbol from the dictionary {A, T, C, G} each time avoiding the symbol that has been previously used. Blawat et al [START_REF] Blawat | Forward error correction for DNA data storage[END_REF] propose the use of 5 nucleotides to encode 8 bits of information while also using forward error correction in the decoding to deal with the sequencing error. In the works of Grass et al [START_REF] Robert N Grass | Robust chemical preservation of digital information on DNA in silica with error-correcting codes[END_REF], the encoding is performed using Reed Solomon codes while Bornholt et al in [START_REF] Bornholt | A DNA-based archival storage system[END_REF] have applied the same encoding as in [START_REF] Goldman | Towards practical, high-capacity, low-maintenance information storage in synthesized DNA[END_REF] improving the encoding scheme and avoiding the fourfold redundancy which is suggested by the latter. Erlich et al [START_REF] Erlich | DNA fountain enables a robust and efficient storage architecture[END_REF] have implemented an encoding using Fountain codes to reach a high coding potential while in [START_REF] Sm Hossein | Portable and error-free dna-based data storage[END_REF] Yazdi et al. proposed a new encoding method to allow rewritable random access while also introducing error correction to handle sequencing errors.

All the prior works are doing basically transcoding, i.e., converting to a quaternary code a binary sequence coming from the output of an encoder, without considering the characteristics of the input signal being encoded, nor the transcoding cost. To reduce the high DNA synthesis cost we propose an extended end-to-end encoding workflow which optimally compresses an image before it is stored into DNA, allowing control of the encoding rate and thus reducing the synthesis cost which is unfortunately relatively high (around 0.02$ per nucleotide). Another strong advantage of our proposed workflow is the use of an encoding algorithm, which has been proposed and analyticaly described in [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF], which can be extended to the encoding of more than 8 bits of information and can be applied to any type of input data (binary or not).

II. OVERVIEW OF THE OVERALL STORAGE WORKFLOW

As shown in figure 1, our proposed workflow consists of 4 main parts. The first part is image compression where the data has to be compressed using some compression protocol. In this work we are using a discrete wavelet transform (DWT) and quantizing each subband of the wavelet decomposition independently using Vector Quantization (VQ). In order to optimize the compression we also use an optimal nucleotide allocation algorithm, which works similar to the bit allocation algorithms described in [START_REF] Shoham | Efficient bit allocation for an arbitrary set of quantizers (speech coding)[END_REF], designed to serve the needs of the DNA coding process as described in the section IV-C. This allocation serves to the choice of an optimal quantization codebook for each wavelet subband for storing the maximum possible bits in one nucleotide for a given encoding rate. Consequently, the number of DNA sequences (oligos) to be synthesized is minimized for a specified image quality. In the second part of the workflow the quantized subbands are independently encoded into a quaternary code of A, T, C and G using a novel encoding algorithm which is robust to the errorprone process of DNA sequencing (reading) by respecting some constraints which will be further described in section IV-B. The encoded sequences are then cut into chunks and formatted adding headers to produce the final oligos (small pieces of DNA strands). The encoded oligos are then processed biologically in vitro so that in the third part of the process they are being synthesized into DNA and stored safely into special capsules which keep the DNA safe from corruptions and data loss for hundreds of years. DNA synthesis is generally an error-free process as long as the oligos to be synthesized are not longer than 300 nucleotides (nts). This justifies the need for cutting our oligos into smaller DNA chunks with the process of formatting. The reading of the stored data is then performed using a process which is called sequencing. The main challenge of the DNA data storage lies in the fact that this is an error prone procedure which can introduce errors in the synthesized DNA strands while reading them by sequencing. This yields that the addition of extra redundancy is necessary to protect the reliability of the decoding. This redundancy is added thanks to a biological process called Polymerase Chain Reaction (PCR) amplification before sequencing by creating many copies of the synthesized oligos. After amplification the oligos are read using a sequencing device (as for example Illumina NextSeq or Oxford Nanopore MinIon). The description of the sequencing process is out of the scope of the paper so it will not be further described. Interested readers may refer to [START_REF] Illumina | An introduction to next-generation sequencing technology[END_REF]. The sequencing provides us a set of many copies of our synthesized oligos retrieved. Similarly to channel coding in which packets are sent in many copies selecting the most frequent ones as the most reliable, in the fourth step of the DNA coding workflow the oligos which are found in many copies are selected as the most representative ones. Finally, the last part of the scheme corresponds to the decoding and reconstruction of the initial image from the sequenced oligos. At this point it is important to denote that apart from the addition of the compression sub-part, this is a classical workflow for DNA data coding. Our novelty lies in the fact that, to our knowledge, this is the first work to include the compression process into the DNA storage schema so to allow control of the DNA synthesis cost by optimizing the compression parameters.

III. OUR CONTRIBUTION

Until this point it is clear that the encoding of data into DNA is not a simple process and is constrained by many biological factors. Previous works until today have been transcoding binary information from many types of data into DNA, without taking into consideration the data characteristics. Thus, when encoding an image into DNA, the state of the art works have been using the protocol of JPEG which optimally compresses an image given some arbitrary target rate of compression expressed in bits/pixel. Then, the output bitstream of JPEG is transcoded to a quaternary stream leading to an "open loop" coding solution. However, as the DNA synthesis process is an expensive process requiring several dollars per synthesized oligo, it is fundamental to control this cost by including the compression into the process of encoding. Therefore In our approach we don't use some fixed black box of compression. We rather designed a new codec (fully controllable) embedding a quaternary encoder leading to a "closed loop" coding solution so to be able to perform an optimal source allocation algorithm that can optimally compress the image given a target rate expressed in nucleotides/pixel (or bits/nucleotide) and not in bits/pixel. Indeed, our approach doesn't perform "transcoding" from binary to quaternary (as state of the art is doing) but rather we are directly encoding using a quaternary code the quantized coefficients allowing optimal rate/distortion control. Therefore, the encoding process in DNA is considered as a main factor for the optimal compression, something which is not possible when using the standard JPEG to compress.

In [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF] , we have made a first attempt to optimally compress an image into DNA by using a simple scalar quantizer. The proposed solution has been validated by a wet lab experiment, generating real synthetic oligonucleotides that were stored in a DNAShell capsule. Although very promising, our results could be improved by using some more sophisticated method of compression. Attempting to improve our previous results, we are making a first step in using Vector Quantization for DNA image coding using a nucleotide allocation algorithm for the optimization of the compression. The techniques used for the encoding are clearly described in the next sections.

IV. THE PROPOSED ENCODING PROCESS

A. Vector Quantization

The compression of the input image is performed using a Vector Quantization (VQ) on the coefficients of the subbands b ∈ {1, 2, . . . , B}, with B = 3i + 1 produced by an i-level DWT decomposition. The advantages of using VQ instead of scalar quantization is that it can provide good compression performance while associated to a fixed length code. In our case, the choice of using a fixed length code rather than a variable length one, was motivated by the fact it is an efficient Fig. 2. Coding/decoding workflow using Vector Quantization.

way to be more robust to the sequencing noise. The purpose of VQ is to map n-dimensional vectors in the vector space R n into a finite set of vectors Σ (the codebook) where Σ = { vj ∈ R n |j = 1, 2, . . . , K}. The vector set Σ contains the centroid vectors that have been computed after clustering a set of training vectors according to the generalized Lloyd algorithm presented in [START_REF] Linde | An algorithm for vector quantizer design[END_REF].

B. Construction of the code

The purpose of the proposed DNA coding workflow is the encoding of some input quantization vectors using a quaternary code composed by the alphabet {A, T, C, G} to be later synthesized into DNA. Let Σ = { v1 , v2 , . . . , vK }, with |Σ| = K, be a set of symbols to be encoded into a set C * = {c 1 , c 2 , . . . , c L } of L quaternary codewords of length l ∈ N \ {0, 1}. In [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF], we have analytically described an efficient encoding algorithm for the encoding of digital data into quaternary words, which is robust to the sequencing errors which can occur if the encoded sequences contain homopolymer runs (same nucleotide repeated more than 3 times) and a percentage of G,C nucleotides which is higher than the percentage of A and T nucleotides. The encoding proposed in [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF] proposes the creation of codewords from a set of duplets (pairs of symbols) which create an acceptable sequence when assembled in a longer strand. This means that this assembly creates no homopolymer runs and contains a percentage of G and C which is lower or equal to the percentage of A and T. More precisely, the codewords are constructed by selecting elements from the following dictionaries:

• C 1 = {AT, AC, AG, T A, T C, T G, CA, CT, GA, GT } • C 2 = {A, T, C, G}
Dictionary C 1 is composed only by pairs of symbols that when assembled in a longer strand will not create homopolymers, or a high G,C content. Consequently, the dictionary C 1 does not contain pairs of the same symbol and the pairs GC and CG are omitted. Codewords of an even length are constructed by only selecting pair symbols from C 1 while codewords of an odd length also require the addition of a symbol from C 2 in their ending. The code size L that can be constructed is then given by the following relation:

L = 10 l 2 , if l is even 10 l-1 2 * 4, if l is odd (1)
It is obvious that the code length increases at an order of O(n). More specifically, in the worst case where one needs to add an extra pair of symbols to the codeword length to cover the needed size K of symbols to be encoded into quaternary, the code size L will be multiplied by 10. This code extension can be relatively big compared to the encoding needs and can possibly leave a big part of codewords unused. However, this unused part can be exploited to deal with an extra biological restriction of pattern repetitions. According to [START_REF] Todd | Repetitive DNA and nextgeneration sequencing: computational challenges and solutions[END_REF], the existence of repetition of short DNA sequences that can create patterns can affect the performance of the sequencer. This is a restriction that had not been taken into consideration by previous works and can occur in the case where the same symbol is repeated many times in the initial sequence. The idea is that every symbol is represented at least twice in the DNA code so that in the case of repeated occurency of the same symbol, one can alternate the two different representations to avoid repetition of short patterns that can cause a problem in the encoding. To this aim, we propose to use the remaining unused codewords of the code for a double representation of the most frequent symbols of the source in such a way so to make use of the full code length. This is an important characteristic of our encoding as in the case of image compression, while strongly quantizing the coefficients of the subbands of some sparse transform, the quantized output can contain multiple repetitions of the same value which can cause patterns in the encoded strand. Pattern repetition problem: VQ is an efficient way for compressing images as blocks of information are being packed into quantization vectors which are then encoded to a codeword of C * . While this quantization is very efficient in terms of coding potential, the fact that more than one elements can be represented by the same codeword can easily cause the problem of pattern repetitions which is an ill-case for DNA 5' end of payload -ATGT ATAT ATAT ATAT ATGT ATGT GTGT GTAT ATAT ATAT GTGT ATGT ATGT ATAT ACAT ATGT GTAT ATGT -3' end of payload 5' end of payload -TGAAG TTGAA GCATA TGATG ACTCT GATCG AGCTC GTCGG TGCTT TGACT CTGAA TAAGC CTTCT TATAG -3' end of payload coding as it can produce errors in the sequencing process. Figure 3 depicts an example of the same information encoded in an oligo using VQ with (bottom oligo) and without (top oligo) treating the case of pattern repetitions. Therefore, by applying a double representation to the most frequent vectors, the pattern repetition can be avoided. This is due to the fact that in the case of repetition of the same vector one can alternate the two associated codewords increasing this way the robustness of the encoded sequence. More precisely, we propose two different cases of mapping to deal with patterns. In the first case which is depicted in figure 4a all the vectors in Σ are mapped once to the K first codewords of C * .Then the p most probable vectors from Σ are also mapped to a second codeword from the L -K remaining vectors of C * . In the second case we ensure that all vectors in Σ can be encoded by at least m different codevectors in C * (L = 2K).

In our experiments we used m=2. This second case of mapping is described in figure 4b. For further details in the encoding algorithm and the mapping process the reader can refer to [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF].

C. Nucleotide allocation

This paragraph describes the source allocation algorithm, which we call nucleotide allocation and can provide the optimal quantization parameters for a given rate R T . The purpose of the nucleotide allocation is the minimization of the total image distortion D T such that the total rate R T is lower than a given target rate R target . In other words the goal is to find an optimal number K b * as well as an optimal length n b * of quantization vectors so to achieve the best possible image quality for a given compression rate. This can be mathematically described by the following relation: To get the slopes λ of the R-D curves for each subband b we exhaustively compute the rate and the distortion produced by the vector quantizer for each set of parameters (K b , n b ). Then, from the set of produced points on the R-D curve, we select the points lying on the convex hull. As the convex hull may not be smooth enough to allow correct computation of the slopes λ we use an exponential decay approximation which can provide a fair estimation of the slope at each computed point. Figure 5 V. RESULTS This last curve depicts the results of comparison of our compression scheme proposed in [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF] (scalar case) and 4 different cases of VQ: -Using only 80% of the code C * for the encoding (K = 80 100 L) and using the 20% remaining codewords (K -L) to allow double representation of the most frequent quantized vectors.

-Mapping 100% of the code (L = 2K).

The results show significant improvement in comparison to the previously published work.

At this point it is important to denote the fact that the oligos produced using the method proposed in this paper avoid patterns and follow a structure and statistical content very similar to the oligos produced in our previous biological experiment which was carried out with success [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF]. Thus, even if there is no wet lab experiment provided in this work we are hopeful to believe that if one uses the same techniques for synthesis and sequencing as the ones used in [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF] there is a very strong probability that this new experiment will be successful too. Furthermore, since this work proposes a close-loop solution of source allocation to provide an optimal compression which is specific for DNA coding, a fair comparison with classical compression protocols such as JPEG which specialise in bit/rate optimization is not possible except if transcoding is performed. A comparison of our proposed quaternary code construction to state of the art methods using transcoding along with JPEG and JPEG2000 can be found in our study in [START_REF] Dimopoulou | Storing digital data into dna: A comparative study of quaternary code construction[END_REF].

VI. CONCLUSIONS

In an attempt to improve our previous results presented in [START_REF] Dimopoulou | A biologically constrained encoding solution for long-term storage of images onto synthetic DNA[END_REF], in this work we have proposed an efficient workflow to be used for storing images into DNA which uses vector quantization. Our results have been very encouraging since they have shown significant improvement allowing an even better control of the compression rate which can lead to the reduction of the synthesis cost. As this is only just a first attempt to use a more sophisticated model for the compression, further experiments will allow a more complete study of this promising workflow, hoping that it can bring interesting advantages to the field of DNA data storage.

Fig. 1 .

 1 Fig. 1. Proposed workflow for storing images into DNA.

Fig. 3 .

 3 Fig. 3. Pattern Repetitions: Example of an oligo encoded using one to one mapping (top oligo) and avoiding pattern repetition (bottom case).

  D b (K b , n b ), w.r.t.

Fig. 4 .

 4 Fig. 4. Mapping of symbols to DNA words.

  b (K b , n b ) ≤ R target where w b is the weight of each subband b taking into consideration the non orthogonality of the DWT in case of biorthogonal transform, a b the weight that takes into account the subband size, D b and R b the subband distortion and subband rate respectively, K b = α 100 L b with α ∈ [0, 100] the number of quantization vectors (codebook size) and n b the length of each vector (vector space dimension) for a subband b. For the minimization of the distortion in every subband we will employ the method described in [9]. This work proposes an unconstrained minimization of a function of the form J = D(B) + λR(B) where λ denotes the slope of the rate-distortion (R-D) curve and the minimization is over all subbands B. They noted that for any λ ≥ 0, the solution B * (λ) to the unconstrained problem of minimizing J over all B is also the solution of the problem of minimizing D(B) over all subbands B while satisfying the constraint that R(B) ≤ R(B * (λ)). Consequently, assuming that R b is a function of n b and K b (and consequently of the code size L b ), and D b is a function of R b , our optimization problem can be written into the following minimization criterion: b (R b ) + λ B b=1 a b R b .For a given λ, the solution is obtained when: ∂D b

  shows a typical example of the R-D curve for one subband of a 9-7 biorthogonal wavelet decomposition along with the convex hull and its exponential approximation. Finally, by selecting the points that correspond to the desired slope for every subband one can select the optimal tuning, i.e. the values of K * b and n * b for b ∈ {1, 2, . . . , B}, which provides the lowest distortion D b for a given subband rate R b . The global R-D curve for encoding an 512x512 image of Lena 1 is depicted in figure 6.

Fig. 5 .

 5 Fig. 5. Behaviour of the rate-distortion curve in one wavelet subband of Lena image. Each point corresponds to different value of K b and n b . The convex hull is plotted in black and its continuous exponential approximation in red.

Fig. 6 .

 6 Fig. 6. Comparison of the global rate-distortion curves for 5 different cases of quantization of Lena image. Blue: scalar quantizer, Orange curve: VQ, Lena inside the training set with pattern repetition (K b = L b for all b). Yellow: VQ, Lena outside the training set with pattern repetition. Purple: VQ, Lena outside the training set no patterns (NP) with L=2K. Green: VQ, Lena outside the training set using only 80% of the code (K b is 80% of L b for all b). • Without treating patterns: Lena inside or outside the training set. • Treating patterns (for Lena outside the training set):-Using only 80% of the code C * for the encoding (K = 80 100 L) and using the 20% remaining codewords (K -L) to allow double representation of the most frequent quantized vectors.-Mapping 100% of the code (L = 2K).

The performance has been tested in other images too but due to lack of space we only present results on one image.


Véronique Gasser
email: veronique.gasser@unistra.fr

Etienne Baco

Olivier Cunrath

Pamela Saint August

Quentin Perraud

Nicolas Zill

Christian Schleberger

Alexander Schmidt

Aurélie Paulen

Dirk Bumann

Gaëtan L A Mislin

Isabelle J Schalk
email: isabelle.schalk@unistra.fr

Catechol siderophores repress the pyochelin pathway and activate the enterobactin pathway in Pseudomonas aeruginosa: an opportunity for siderophore-antibiotic conjugates development

INTRODUCTION

The emergence of resistant and, in some cases pan-resistant (resistant to all the antibiotics currently available) bacteria has led to an urgent need to discover new bactericidal molecules with different targets and innovative strategies for preserving or increasing the efficacy of known antibiotics. In recent years, a number of reviews have highlighted the possible use of bacterial iron uptake pathways as a Trojan horse strategy for promoting the transport of drugs into bacteria, thereby increasing their efficacy (Ji et al., 2012b;[START_REF] Rebuffat | Microcins in action: amazing defence strategies of Enterobacteria[END_REF][START_REF] Page | Siderophore conjugates[END_REF][START_REF] Mislin | Siderophore-dependent iron uptake systems as gates for antibiotic Trojan horse strategies against Pseudomonas aeruginosa[END_REF]. Iron is a cofactor in many important biological processes, and it is therefore an essential nutrient for bacterial growth and infectious processes [START_REF] Ratledge | Iron metabolism in pathogenic bacteria[END_REF]. One of the most common strategies for obtaining iron used by bacteria involves siderophores, small organic iron chelators (MW between 200 and 2000 Da; [START_REF] Hider | Chemistry and biology of siderophores[END_REF]). These molecules are synthesized by bacteria and have a high affinity for iron. They are released into the environment, where they scavenge iron highly efficiently before being taken up again by the bacteria, resulting in the transport of the iron they carry to the bacterial cytoplasm [START_REF] Schalk | Structure, function and binding selectivity and stereoselectivity of siderophore-iron outer membrane transporters[END_REF][START_REF] Schalk | Fate of ferrisiderophores after import across bacterial outer membranes: different iron release strategies are observed in the cytoplasm or periplasm depending on the siderophore pathways[END_REF].

Antibiotics can be attached to siderophores in a Trojan horse strategy resulting in the delivery of the conjugates to the bacterial cytoplasm via siderophore-mediated iron uptake pathways.

In Gram-negative bacteria, the ferri-siderophore complexes formed in the environment surrounding the bacterium are transported back across the bacterial outer membrane by specific TonB-dependent transporters (TBDTs), the uptake activity of which is regulated by the inner membrane protein TonB [START_REF] Schalk | Structure, function and binding selectivity and stereoselectivity of siderophore-iron outer membrane transporters[END_REF]. They are further transported across the inner membrane by specific ABC transporters or protonmotive force-dependent permeases [START_REF] Schalk | Fate of ferrisiderophores after import across bacterial outer membranes: different iron release strategies are observed in the cytoplasm or periplasm depending on the siderophore pathways[END_REF]. The iron is generally then released from the siderophores in the bacterial cytoplasm, through a process involving both iron reduction and an enzymatic degradation or modification of the siderophores (for a review see [START_REF] Schalk | Fate of ferrisiderophores after import across bacterial outer membranes: different iron release strategies are observed in the cytoplasm or periplasm depending on the siderophore pathways[END_REF]).

Accepted Article

In some siderophore pathways, a different sequence of events occurs: for example, during iron uptake via pyoverdine (PVD) or citrate in P. aeruginosa, the iron is released from the siderophore in the periplasm, and only the iron is transported further into the cytoplasm, by an ABC transporter [START_REF] Greenwald | Real-time FRET visualization of ferric-pyoverdine uptake in Pseudomonas aeruginosa: a role for ferrous iron[END_REF][START_REF] Marshall | Citrate-mediated iron uptake in Pseudomonas aeruginosa: involvement of the citrate-inducible FecA receptor and the FeoB ferrous iron transporter[END_REF][START_REF] Brillet | An ABC transporter with two periplasmic binding proteins involved in iron acquisition in Pseudomonas aeruginosa[END_REF][START_REF] Schalk | Fate of ferrisiderophores after import across bacterial outer membranes: different iron release strategies are observed in the cytoplasm or periplasm depending on the siderophore pathways[END_REF].

Most bacteria acquire iron by producing their own siderophores, but they can also use siderophores from other microorganisms (siderophore piracy). P. aeruginosa, an opportunist pathogen, used as a model organism in this study, produces two major siderophores, pyoverdine (PVD) and pyochelin (PCH). However, it can also use many xenosiderophore (not produced by the bacterium itself) like pyoverdines from other pseudomonads, enterobactin [START_REF] Poole | Enterobactin-mediated iron transport in Pseudomonas aeruginosa[END_REF], cepabactin [START_REF] Mislin | Binding properties of pyochelin and structurally related molecules to FptA of Pseudomonas aeruginosa[END_REF], mycobactin and carboxymycobactin [START_REF] Llamas | Characterization of five novel Pseudomonas aeruginosa cell-surface signalling systems[END_REF], desferrichrysin, desferricrocin, coprogen [START_REF] Meyer | Exogenous siderophore-mediated iron uptake in Pseudomonas aeruginosa: possible involvement of porin OprF in iron translocation[END_REF]), vibriobactin, aerobactin, fungal siderophores (ferrichrome [START_REF] Llamas | The heterologous siderophores ferrioxamine B and ferrichrome activate signaling pathways in Pseudomonas aeruginosa[END_REF], deferrioxamines [START_REF] Vasil | The response of Pseudomonas aeruginosa to iron: genetics, biochemistry and virulence[END_REF][START_REF] Llamas | The heterologous siderophores ferrioxamine B and ferrichrome activate signaling pathways in Pseudomonas aeruginosa[END_REF], and natural chelators, such as citrate [START_REF] Cox | Iron uptake with ferripyochelin and ferriccitrate by Pseudomonas aeruginosa[END_REF][START_REF] Harding | Acquisition of iron from citrate by Pseudomonas aeruginosa[END_REF], (for reviews see [START_REF] Poole | Iron acquisition and its control in Pseudomonas aeruginosa: many roads lead to Rome[END_REF][START_REF] Cornelis | Pseudomonas aeruginosa adapts its iron uptake strategies in function of the type of infections[END_REF]).

Many studies have shown that siderophore iron uptake pathways can be used to transport antibiotics into bacteria (Mollmann et al., 2009;Ji et al., 2012b;[START_REF] Page | Siderophore conjugates[END_REF][START_REF] Mislin | Siderophore-dependent iron uptake systems as gates for antibiotic Trojan horse strategies against Pseudomonas aeruginosa[END_REF]. Microorganisms have themselves developed siderophore-antibiotic conjugates known as sideromycins [START_REF] Braun | Active transport of iron and siderophore antibiotics[END_REF][START_REF] Braun | Sideromycins: tools and antibiotics[END_REF][START_REF] Mislin | Siderophore-dependent iron uptake systems as gates for antibiotic Trojan horse strategies against Pseudomonas aeruginosa[END_REF], in which the antibiotic moiety is connected to the siderophore via a spacer arm.

The archetypal conjugates of this type are albomycins [START_REF] Benz | Konstitution der Desferriform der Albomycine δ1, δ2, ε[END_REF][START_REF] Braun | Active transport of iron and siderophore antibiotics[END_REF][START_REF] Mislin | Siderophore-dependent iron uptake systems as gates for antibiotic Trojan horse strategies against Pseudomonas aeruginosa[END_REF], ferrimycins [START_REF] Bickel | Constitution of ferrimycin A1[END_REF], danomycins [START_REF] Tsukiura | Danomycin, a New Antibiotic[END_REF], salmycins [START_REF] Tsukiura | Danomycin, a New Antibiotic[END_REF] and certain microcins [START_REF] De Lorenzo | Isolation and characterization of microcin E492 from Klebsiella pneumoniae[END_REF]de Lorenzo et al., 1984;[START_REF] Thomas | Siderophore peptide, a new type of post-translationally modified antibacterial peptide with potent activity[END_REF][START_REF] Destoumieux-Garzon | Parasitism of iron-siderophore receptors of Escherichia coli by the siderophore-peptide microcin E492m and its unmodified counterpart[END_REF][START_REF] Nolan | Investigations of the MceIJ-catalyzed posttranslational modification of the microcin E492 C-terminus: linkage of ribosomal and nonribosomal peptides to form "trojan horse" antibiotics[END_REF]

Accepted Article

Walsh, 2008). These natural siderophore-antibiotic conjugates can chelate iron(III) and are then transported into the target bacterium via the siderophore-dependent iron uptake pathways. This energy-coupled transport across the bacterial membranes greatly increases the antibiotic efficacy of sideromycins: their minimal inhibitory concentration is often at least two orders of magnitude lower than that of the antibiotic without the siderophore, which enters the cell by diffusion [START_REF] Braun | Sideromycins: tools and antibiotics[END_REF]. Trojan horse strategies based on the use of bacterial iron uptake pathways are, therefore, currently considered to be a promising approach for the treatment of infection. Several research teams have developed different synthetic siderophore-antibiotic conjugates (Rivault et al., 2007;[START_REF] Page | In vitro properties of BAL30072, a novel siderophore sulfactam with activity against multiresistant gram-negative bacilli[END_REF][START_REF] Noel | Synthesis and biological properties of conjugates between fluoroquinolones and a N3''functionalized pyochelin[END_REF]Ji et al., 2012b;Ji et al., 2012a;[START_REF] Milner | Staphyloferrin A as siderophore-component in fluoroquinolone-based Trojan horse antibiotics[END_REF][START_REF] Page | Siderophore conjugates[END_REF]Wencewicz et al., 2013;Wencewicz and Miller, 2013;[START_REF] Fardeau | Synthesis and antibacterial activity of catecholate-ciprofloxacin conjugates[END_REF][START_REF] Zheng | Enterobactin-mediated delivery of beta-lactam antibiotics enhances antibacterial activity against pathogenic Escherichia coli[END_REF][START_REF] Ji | Siderophore-fluoroquinolone conjugates containing potential reduction-triggered linkers for drug release: synthesis and antibacterial activity[END_REF], some of which have potentially useful antibiotic activities.

However, for such Trojan horse strategies to be effective, the target bacteria must prefer to use xenosiderophores present in their environment rather than producing their own siderophores to obtain iron. In this context, it is vital to have a precise understanding of the ability of bacteria to sense the presence of xenosiderophores (or sideromycins in a Trojan horse strategy) in their environment and to switch from one siderophore pathway to another for iron acquisition. Catecholate siderophores are the iron-chelating compounds most frequently tethered to various antibiotics (Ji et al., 2012a;Wencewicz and Miller, 2013;[START_REF] Fardeau | Synthesis and antibacterial activity of catecholate-ciprofloxacin conjugates[END_REF][START_REF] Zheng | Enterobactin-mediated delivery of beta-lactam antibiotics enhances antibacterial activity against pathogenic Escherichia coli[END_REF]Chairatana et al., 2015). In this study, we therefore evaluated the capacity of P. aeruginosa to use several catechol xenosiderophores in conditions of iron limitation: enterobactin (a well known siderophore produced by Escherichia coli, used here as a reference), protochelin and azotochelin (siderophores produced by Azotobacter vinelandii [START_REF] Knosp | Cell-surface signaling in Pseudomonas: stress responses, iron transport, and pathogenicity[END_REF][START_REF] Cornish | Role of molybdate and other transition metals in the accumulation of protochelin by Azotobacter vinelandii[END_REF]) and two synthetic chelators (the tris-catechol vector, TCV and the bis-catechol vector, BCV (Baco et

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al., 2014)), which could potentially be used for the vectorization of antibiotics for transport into P. aeruginosa cells (Figure 1). We show here that when P. aeruginosa cells are grown in the presence of catechol compounds, the expression of the TBDT PfeA (the enterobactin outer membrane transporter) is highly activated and the expression of the genes encoding for proteins involved in the endogenous PCH iron uptake pathway is repressed. Using 55 Fe uptake assays, we show that iron is transported by these catechol compounds via PfeA, into P. aeruginosa cells.

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RESULTS

Enterobactin, azotochelin, protochelin, BCV and TCV induce the expression of the outer

membrane transporter PfeA. P. aeruginosa is known to be able to sense xenosiderophores in its extracellular environment, and the detection of these molecules leads to an upregulation of the genes encoding the corresponding ferrisiderophore uptake proteins [START_REF] Dean | Expression of the ferric enterobactin receptor (PfeA) of Pseudomonas aeruginosa: involvement of a two-component regulatory system[END_REF][START_REF] Llamas | Characterization of five novel Pseudomonas aeruginosa cell-surface signalling systems[END_REF]Llamas et al., 2014). We used RT-qPCR and proteomic approaches to investigate whether the presence of catecholate chelators in the growth medium activated the transcription of one or more siderophore TBDTs in P. aeruginosa. For both approaches, experiments were carried out with PAO1 ATCC15692 and the corresponding PVD-and PCH-deficient ∆pvdF∆pchA strain (Table S1 in the Supporting Information) grown in LB or iron-deficient CAA medium, with or without supplementation with 10 µM of enterobactin (the reference compound), azotochelin, protochelin, BCV or TCV.

We studied 10 genes in RT-qPCR experiments: 7 genes corresponding to TBDTs (piuA,pirA,pfeA,cirA,fvbA,pfuA and PA0434) potentially involved in iron acquisition via catechol chelators according to the annotation of the P. aeruginosa PAO1 genome [START_REF] Winsor | Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes[END_REF], the fpvA and fptA genes to assess changes in the transcription of the genes encoding the PVD and PCH TBDTs, and the housekeeping gene uvrD, which was used for normalization. RT-qPCR demonstrated a large increase in transcript levels for pfeA (Figure 2) but not for any of the other TBDT genes tested (fold-changes of less than 7 for these other genes; Figure S1 in the Supporting Information) in the presence of enterobactin and the other four catecholate chelators tested. In the iron-deficient CAA medium, all five molecules tested strongly activated the transcription of pfeA, even in the wild-type strain PAO1, which produced and secreted large amounts of the endogenous siderophores, PVD and PCH (Cunrath et al., 2015a). TCV and protochelin were the most effective activators of pfeA transcription (3,000-and 4,500-fold changes in PAO1 and ∆pvdF∆pchA, respectively), followed by protochelin, enterobactin (1,400-fold change), and azotochelin, with BCV the Accepted Article least effective molecule (520-and 810-fold changes in PAO1 and ∆pvdF∆pchA, respectively).

In LB medium (containing about 4 µM iron (Cunrath et al., 2015a)), TCV, protochelin and enterobactin were able to promote pfeA transcription in both strains tested, with fold-changes of between 100 and 700 for TCV (Figure 2F). In LB medium, TCV was again the most effective compound for the activation of pfeA transcription. This activation of pfeA transcription in LB medium strongly suggested that P. aeruginosa made use of the enterobactin pathway to acquire iron even in iron-rich media, such as LB, if tris-catechol siderophores were present. The proteomic investigation was carried out on the wild-type PAO1 strain grown in CAA medium in the presence of enterobactin, BVC or TCV (Figure 3).

It clearly demonstrated an activation of expression for the PfeA gene but for no other TBDT gene (Figure 3A).

In conclusion, RT-qPCR and proteomic investigations showed strong induction of the transcription and expression of pfeA in the presence of catechol chelators in iron-deficient and iron-rich media.

Enterobactin, azotochelin, protochelin, BCV and TCV can transport iron into P.

aeruginosa cells via the TBDT PfeA. The activation of pfeA transcription and expression in the presence of the various catechol siderophores strongly suggests that these chelators transport iron into P. aeruginosa cells via this TBDT. We therefore assessed the ability of a mutant with a pfeA deletion to transport and accumulate 55 Fe in the presence of the various catechol siderophores.

In the first experiment (Figure 4A-4E), we prevented iron uptake by the endogenous siderophores by using the PCH-and PVD-negative P. aeruginosa mutant ∆pvdF∆pchA and its pfeA deletion mutant derivative ∆pvdF∆pchA∆pfeA, grown in the presence of 10 µM enterobactin to induce PfeA expression. We also repeated all the 55 Fe uptake experiments

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with cells subjected to pretreatment with the protonophore CCCP (Figure 4A-4E), which inhibits the protonmotive force of the bacteria, thereby preventing any TonB-dependent uptake [START_REF] Clément | The binding mechanism of pyoverdin with the outer membrane receptor FpvA in Pseudomonas aeruginosa is dependent on its iron-loaded status[END_REF]. 55 Fe uptake was observed in ∆pvdF∆pchA cells (shown in black in Figure 4A-4E) in the presence of the five molecules tested, but not in cells that had been treated with CCCP (shown in green in Figure 4A-4E). Thus, none of the five catechol-55 Fe complexes tested were able to diffuse across the outer membrane: the iron uptake observed was mediated exclusively by TBDTs. A complete inhibition of iron uptake was also observed for the pfeA mutant in the presence of enterobactin-55 Fe, protochelin-55 Fe and TCV-55 Fe (shown in red in Figure 4A, 4C and4E), as shown by comparison with the ∆pvdF∆pchA strain expressing PfeA, indicating that these three compounds transport iron into P. aeruginosa cells via PfeA only, with no other TBDT able to perform this function. In the presence of BCV and, to a lesser extent, azotochelin (Figure 4D and 4B), the inhibition of 55 Fe uptake in ∆pvdF∆pchA∆pfeA cells was incomplete, suggesting the involvement of another TBDT, in addition to PfeA, in iron acquisition by these two bis-catechol compounds.

Iron uptake was restored by the complementation of ∆pvdF∆pchA∆pfeA with pMMB190pfeA, a pMMB derivative carrying the pfeA gene for all five catecholate compounds tested (shown in blue in Figure 4A-4E).

As all the 55 Fe uptake assays with the different catechol siderophores were carried out with enterobactin as the inducer of pfeA expression, the expression levels of this protein are equivalent in all the uptake assays using PAO1 in Figures 4A-4E. Therefore, the 55 Fe transport efficiency of the different catecholate compounds can be compared: uptake rates of 2 x 10 3 Fe atoms/bacterium/min were recorded in the presence of enterobactin as siderophore, 1.3 x 10 3 Fe atoms/bacterium/min in the presence of azotochelin, 0.6 x 10 3 in the presence of protochelin or BCV and 0.3 10 3 Fe atoms/bacterium/min for TCV. In these experimental

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conditions, TCV appears about 7 times less efficient than enterobactin for 55 Fe uptake in P.

aeruginosa.

We then compared these uptake rates obtained with PVD-and PCH-deficient ∆pvdF∆pchA cells grown in conditions of iron limitation with those obtained when siderophore-producing PAO1 cells were grown in iron-rich media (Figure 5 and Table 1). The idea here was to compare 55 Fe uptake by catecholate compounds in more favorable (ironrestricted growth conditions with a strain unable to produce any endogenous siderophore) and less favorable conditions (iron-rich growth conditions with a strain able to produce two endogenous siderophores). In addition, we also investigated the effect of (i) a lack of induction of PfeA expression (black bares in Figure 5), (ii) induction with the siderophore enterobactin (gray bares in Figure 5) and (iii) induction with the catechol chelator used in the 55 Fe uptake assays (white bares in Figure 5), which lead to the induction of the transporter with different efficiencies according to Figure 2. A significant 55 Fe uptake via PfeA was observed only when the bacteria were grown in the presence of a catechol chelator inducing PfeA expression (Figure 5), confirming again that this TBDT must be expressed to observe any 55 Fe uptake in the presence of such compounds. However, this rule was not respected in the case PAO1 cells grown in LB with protochelin and TCV used as siderophores. The second interesting point is an efficient iron transport via enterobactin, azotochelin and BCV even in PVD-and PCH-producing P. aeruginosa cells grown in iron-rich medium. At last, iron uptake rates did not differ significantly between cells in which PfeA expression was induced with enterobactin and cells in which PfeA expression was induced with the siderophores used for 55 Fe uptake assays, despite the high capacity of compounds such as TCV to induce PfeA expression (Figure 2F).

This apparent absence of connection between the level of PfeA expression and iron uptake

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rates may be due to differences in siderophores recognition efficiencies with the different proteins of the enterobactin iron uptake pathway in P. aeruginosa.

Thus, all the five catechol compounds transported iron into P. aeruginosa cells via PfeA, with enterobactin being the more efficient. The uptake rates could reach with enterobactin 1306 ± 220 Fe atoms/bacterium/min in P. aeruginosa cells unable to produce siderophores grown in iron-deficient medium, and it remained as high as 827 ± 64 Fe atoms/bacterium/min, even in a PVD-and PCH-producing strain grown in iron-rich medium (Figure 5 and Table 1).

Enterobactin, azotochelin, protochelin, BCV and TCV repress the expression of the PCH pathway, but not that of the PVD pathway.

In parallel with the induction of PfeA expression, proteomic analyses on P. aeruginosa cells grown in iron-deficient medium in the presence of 10 µM enterobactin, BCV or TCV showed a repression of the expression of the genes involved in PCH biosynthesis (pchA, pchB, pchC, pchD, pchE, pchF and pchG), the genes encoding the outer and inner membrane importers of PCH-Fe (fptA and fptX, respectively) and the pchH and pchI genes of the PCH locus, the functions of which are unknown (Figure 3B). No effect on the expression of the genes of the PVD locus was observed. Since P. aeruginosa cells produce no PVD and PCH in LB (an iron-rich medium; (Cunrath et al., 2015a)), the repression of PCH pathway genes in the presence of catecholate compounds was observed only in conditions of iron limitation (CAA medium). RT-qPCR experiments confirmed that, in conditions of iron limitation, the presence of catechol compounds in the growth medium of P. aeruginosa clearly repressed the transcription of pchE (a non-ribosomal peptide synthetase involved in PCH biosynthesis), fptA and fptX (Figure 6A), with an 80 % decrease in the fold-changes recorded. Again, no repression of transcription was observed for the genes of the PVD pathway (fpvA, encoding the TBDT; fpvF, encoding a periplasmic Accepted Article binding protein involved in ferri-PVD import and pvdJ, encoding an enzyme involved in PVD biosynthesis; Figure 6B).

We investigated the timing of this repression using P. aeruginosa cells expressing mCherry-tagged PchE or FptX (pchEmcherry and fptXmcherry, Table S1 in Supplemental Information). The constructions of these strains have been described previously (Cunrath et al., 2015b;[START_REF] Gasser | Cellular organization of siderophore biosynthesis in Pseudomonas aeruginosa: Evidence for siderosomes[END_REF]. Chromosomal insertion of mcherry was chosen to obtain physiological protein expression levels. The insertion of mcherry, by allelic exchange, into wild-type PAO1 produced strains expressing mCherry fused to the C-terminus of either FptX (fptXmcherry strain) or PchE (pchEmcherry strain). We monitored the growth of these two strains in iron-depleted CAA medium after addition of 200 µM enterobactin, BCV or TCV, by measuring optical density at 600 nm upon time (Figure 7). These two strains carrying the fusion proteins grew as well as the parental strains PAO1 and the addition of the catechol compounds stimulated bacterial growth, a feature commonly observed with siderophores [START_REF] Youard | Pseudomonas fluorescens CHA0 produces enantio-pyochelin, the optical antipode of the Pseudomonas aeruginosa siderophore pyochelin[END_REF]. After 8 h culture, PchE-mCherry and FptX-mCherry were already expressed in P. aeruginosa cells, and a clear repression of PchE-mCherry and FptX-mCherry expression was observed, beginning about one hour after the addition of catechol chelators to the growth medium. This repression was most effective with TCV and least effective with BCV, and persisted over about 20 h of culture. This switching off of the PCH pathway was confirmed by carrying out PCH-55 Fe uptake assays (Figure 4F) on P. aeruginosa cells grown in the presence or absence of BCV or TCV. 55 Fe uptake via PCH was observed for bacteria grown in the presence of BCV or TCV, indicating that the repression of the PCH pathway documented by proteomic and RT-qPCR studies was not total, with the bacteria still able to acquire iron via PCH. However, 55 Fe uptake was clearly slower in cells grown in the presence of BCV or TCV (no plateau reached Accepted Article after more than 15 min, Figure 4F curve in blue and red) than in cells grown in the absence of these compounds (plateau reached in about 3 min, Figure 4F curve in black).

These data show that the presence of catechol chelators in the growth medium of P. aeruginosa cells strongly represses the proteins of the PCH pathway. This repression occurred after about one hour of growth in planktonic conditions in CAA medium and was maintained throughout the rest of the culture period (20 h). This repression was not total, with the bacterium still able to acquire iron via the PCH siderophore.

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DISCUSSION

In addition to its own siderophores, PVD and PCH, P. aeruginosa can use many siderophores produced by other microorganisms [START_REF] Poole | Iron acquisition and its control in Pseudomonas aeruginosa: many roads lead to Rome[END_REF][START_REF] Cornelis | Pseudomonas aeruginosa adapts its iron uptake strategies in function of the type of infections[END_REF], consistent with the presence in the genome of this pathogen of more than 30 genes encoding TBDTs [START_REF] Cornelis | A survey of TonB-dependent receptors in fluorescent pseudomonads[END_REF], which act as gates allowing the various ferrisiderophore complexes to enter bacteria. All these siderophore-dependent iron uptake pathways, indicating a high potential of this bacterium to adapt to different conditions of iron limitation, may be also considered as possible gates for the entry of siderophore-antibiotic conjugates in Trojan horse strategies.

We show here that the presence in the growth medium of catechol xenosiderophores (azotochelin and protochelin) or two synthetic chelators (BCV and TCV) that can be linked to antibiotics by click chemistry induced the expression of PfeA in P. aeruginosa, as previously reported for enterobactin [START_REF] Dean | Expression of the ferric enterobactin receptor (PfeA) of Pseudomonas aeruginosa: involvement of a two-component regulatory system[END_REF].

By contrast, no other TBDT was induced (Figure 2 and3A). The efficiency of PfeA induction was highest for TCV, followed by protochelin, enterobactin, azotochelin and, finally BCV. Dean and Poole have shown that two genes, pfeS and pfeR (located immediately upstream from pfeA), encode the sensor kinase and response regulator, respectively, of a two-component system involved in regulating pfeA expression in response to enterobactin [START_REF] Dean | Expression of the ferric enterobactin receptor (PfeA) of Pseudomonas aeruginosa: involvement of a two-component regulatory system[END_REF][START_REF] Rodrigue | Twocomponent systems in Pseudomonas aeruginosa: why so many?[END_REF]. It is tempting to hypothesize that this two-component system is also involved in the regulation of pfeA expression in response to other catechol compounds. The sequence of PfeS suggests that it is an inner membrane protein [START_REF] Dean | Expression of the ferric enterobactin receptor (PfeA) of Pseudomonas aeruginosa: involvement of a two-component regulatory system[END_REF], and further studies are required to gain insight into the mechanism of stimulus perception by this Accepted Article protein: do the catechol compounds interact with this protein only after their transport into the bacterial periplasm or is another mechanism involved?

Despite the current lack of information concerning the molecular mechanisms underlying this stimulation of PfeA expression, the findings presented here already have interesting implications for the development of siderophore conjugates for Trojan horse strategies. First, the induction of PfeA expression (or switching on of the enterobactin pathway) was even significant in a wild-type PAO1 strain, indicating that, in the presence of catechol compounds, P. aeruginosa makes use of these molecules to obtain iron, despite its ability to produce the highly efficient siderophores PVD and PCH. In addition, the enterobactin pathway was switched on even in iron-rich medium (LB), leading to efficient iron uptake via this siderophore: 827 ± 64 Fe atoms/bacterium/min (Figure 5 and Table 1). The total iron content of bacteria in this medium is in the range of 810,000 Fe atoms/bacterium (Cunrath et al., 2015a). This switching on of the enterobactin pathway was accompanied by a clear repression of the expression of the PCH pathway. However, the PCH pathway was not totally switched off (Figure 3F), the bacteria were still able to gain access to iron via PCH at any moment. This repression occurred as long as the bacteria were in contact with catechol chelators (Figure 7). No repression of the PVD pathway was observed.

Interestingly, this hierarchy of iron uptake pathway expression reflects the affinity of the siderophores for ferric iron (10 52 M -1 , 10 30.8 M -1 and 10 28.8 M -2 for enterobactin, PVD and PCH, respectively [START_REF] Carrano | Trageting Virulence: Salmochelin modification tunes the antibacterial activity spectrum of beta-lactams for pathogen-selective killing of Escherichia coli[END_REF][START_REF] Albrecht-Gary | Bacterial iron transport: coordination properties of pyoverdin PaA, a peptidic siderophore of Pseudomonas aeruginosa[END_REF][START_REF] Brandel | Pyochelin, a siderophore of Pseudomonas aeruginosa: Physicochemical characterization of the iron(III), copper(II) and zinc(II) complexes[END_REF]). Moreover iron chelation needs only one molecule of enterobactin or PVD per iron ion, but two molecules of PCH (2:1 -PCH:Festoichiometry) to get an octahedral coordination. This suggests that, when several siderophores are present in the bacterial environment, the siderophore most successful Accepted Article at chelating the available iron will scavenge it and deliver it to the microorganism.

Consequently, the bacterium will specifically up regulate the expression of all the proteins required to obtain iron via this specific siderophore. In the presence of tricatechol chelators, PCH, which has a lower affinity for iron and chelates this metal with a 2:1 (PCH:Fe) stoichiometry, is probably not competitive for the chelation of this metal. Consequently, fewer PCH-Fe complexes are formed and transported into P. aeruginosa cells for activation of the PCH pathway via the cytoplasmic regulator PchR. By contrast, the presence of catechol-Fe complexes in the bacterial environment leads to the enterobactin pathway being switched on. Accordingly, in the development of siderophore-antibiotic conjugates, it may be important to design a siderophore moiety with a high enough affinity for iron to compete with the natural siderophores produced by the pathogen. Consequently, it is not surprising that compounds like siderophore conjugate monocarbams are poorly efficient in a Trojan horse strategy in P. aeruginosa infections [START_REF] Tomaras | Adaptation-based resistance to siderophore-conjugated antibacterial agents by Pseudomonas aeruginosa[END_REF][START_REF] Kim | Pharmacodynamic profiling of a siderophore-conjugated monocarbam in Pseudomonas aeruginosa: assessing the risk for resistance and attenuated efficacy[END_REF]. Such compounds have certainly affinities for iron lower than that of PCH and will not be competitive with the endogenous siderophores to provide iron to P. aeruginosa cells. Moreover, the iron chelation stoichiometry of such compounds is not 1:1 (siderophore:Fe) as for many natural siderophores; therefore iron loaded monocarbam conjugates may have complex tridimensional structures, which may be poorly recognized by TBDT for uptake. 55 Fe uptake assays demonstrated that P. aeruginosa cells used the TBDT PfeA to assimilate iron complexed with catechol compounds (Figure 4). Deletion of the PfeA gene abolished completely iron uptake by these compounds, with the exception of BCV, for which another, as yet unidentified TBDT must be involved in BCV-Fe assimilation. Previous studies have suggested that TBDTs are highly specific for iron

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transport via one specific siderophore or structurally related siderophores, but never siderophores with very different chemical structures (for a review see [START_REF] Schalk | Structure, function and binding selectivity and stereoselectivity of siderophore-iron outer membrane transporters[END_REF]). In P. aeruginosa, PfeA recognizes the ferric forms of the tris-catechol compounds enterobactin, azotochelin and TCV, but also the bis-catechol compounds protochelin and BCV at the bacterial cell surface and transports them across the outer membrane. Consequently, PfeA should be able to take up BCV-antibiotic and TCVantibiotic conjugates.

In all conditions tested, enterobactin was the most efficient siderophore for iron uptake into P. aeruginosa, whereas protochelin with TCV were the least efficient (figures 4 and 5 and Table S4): 1306 ± 220 Fe atoms/bacterium/min for enterobactin and 273 ± 62 Fe atoms/bacterium/min for protochelin, for cells grown in iron-deficient conditions. Surprisingly, the uptake rates of the different catechol chelators did not reflect the ability of these compounds to induce PfeA expression. This apparent absence of connection between the level of PfeA expression and the rates of iron uptake mediated by catechol siderophores may be due to differences in the recognition and interaction efficiencies between these catecholate compounds and the different protein partners involved in iron acquisition via enterobactin in P. aeruginosa.

The iron uptake rates of enterobactin (1306 ± 220 Fe atoms/bacterium/min in iron-deficient medium and 827 ± 64 Fe atoms/bacterium/min in LB -Figure 5 and Table 1-) indicate that this siderophore should be able to transport large amounts of antibiotics in a Trojan horse strategy. The lower uptake rate of protochelin and TCV probably reflects difficulties interacting with one of the proteins involved in enterobactin uptake pathway: PfeA or another, unidentified partner. Iron uptake via enterobactin has been studied in detail in E. coli and involves transport across the outer membrane by the TBDT FepA, across the inner membrane by the ABC transporter

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FepBCD and the release of the metal from the siderophore in the cytoplasm, via a mechanism involving iron reduction and siderophore hydrolysis [START_REF] Raymond | Enterobactin: an archetype for microbial iron transport[END_REF][START_REF] Schalk | Fate of ferrisiderophores after import across bacterial outer membranes: different iron release strategies are observed in the cytoplasm or periplasm depending on the siderophore pathways[END_REF]. This scenario does not seem to apply to P. aeruginosa, particularly as the operon containing pfeA in this bacterium contains only the PA2689 gene (downstream from pfeA) encoding a putative esterase [START_REF] Winsor | Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes[END_REF] with a typical signaling sequence suggesting a periplasmic distribution. No gene coding for an inner membrane transporter is present on the genome in the vicinity of pfeA, strongly suggesting that, as for iron acquisition via PVD, iron may be released from enterobactin and other catechol chelators in the periplasm of P. aeruginosa, rather than in the cytoplasm as in E. coli. However, further studies are required to obtain insight into the enterobactin pathway in P. aeruginosa, to identify the various protein partners and molecular mechanisms involved and to improve our understanding to facilitate the design of optimal catechol-antibiotic conjugates transported into P. aeruginosa cells with the same efficiency as for the natural siderophore enterobactin.

In conclusion, the development of Trojan horse strategies involves considering different parameters to ensure the design of siderophore-antibiotic compounds with a high probability of ensuring effective drug delivery. It involves the synthesis of siderophore-antibiotic conjugates having a very high affinity for iron, able to compete for this nutrient with the endogenous siderophores produced by the target bacterium. Moreover, it is crucial that the siderophore-antibiotic conjugates once loaded with iron can still be recognized by TBDTs with good affinities. Consequently, vectors having structural homologies with natural siderophores will be vectors with the highest probability to transport efficiently antibiotics into bacteria. At last, the development of such Trojan horse strategies also requires an excellent knowledge of the molecular mechanisms involved in ferrisiderophore uptake.

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The data presented here indicate that enterobactin-antibiotic conjugates should 405 have a high potential for activating PfeA transcription, facilitating the transport of 406 large amounts of antibiotic into the bacteria (the transport of 800 to 2000 molecules of 407 antibiotic might be predicted). The high potential of TCV to activate the transcription 408

of PfeA is also of potential interest in such a study, to ensure that the catechol-409 antibiotic conjugates remain close to the bacterial cell surface, ready to be transported. 410

An ideal catechol vector for the transport of antibiotics into bacteria would be a 411 compound able to activate the transcription of PfeA, like TCV, but able to ensure 412 transport with the uptake rate of enterobactin. 413 414

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MATERIALS AND METHODS

Chemicals.

The pyochelin (PCH) used for 55 Fe uptake assays was synthesized and purified as previously described [START_REF] Zamri | An improved stereocontrolled synthesis of pyochelin, a siderophore of Pseudomonas aeruginosa and Burkholderia cepacia[END_REF][START_REF] Youard | Pseudomonas fluorescens CHA0 produces enantio-pyochelin, the optical antipode of the Pseudomonas aeruginosa siderophore pyochelin[END_REF]. Enterobactin was purchased from Sigma-Aldrich. Azotochelin (BCS), BCV and TCV were synthesized as previously described [START_REF] Baco | Diphenyl-benzo[1,3]dioxole-4carboxylic acid pentafluorophenyl ester: a convenient catechol precursor in the synthesis of siderophore vectors suitable for antibiotic Trojan horse strategies[END_REF]. The syntheses of protochelin (TCS) is described in the Supplementary Material.

Bacterial strains, plasmids and growth conditions. The P. aeruginosa and Escherichia coli strains and plasmids used in this study are listed in Table S1 in Supporting Information. E. coli strains were routinely grown in Luria-Bertani broth [(LB); Difco] at 37°C. P. aeruginosa strains were first grown overnight at 30°C in LB broth and were then washed, resuspended and cultured overnight at 30°C in iron-deficient CAA medium (casamino acid medium, composition: 5 g l -1 low-iron CAA (Difco), 1.46 g l -1 K 2 HPO 4 3H 2 O, 0.25 g l -1 MgSO 4 7H 2 O.

Carbenicillin was added at a concentration of 150 µg ml-1 when required.

Mutant construction.

All enzymes for DNA manipulation were purchased from Fermentas and were used in accordance with the manufacturer's instructions. E. coli strain TOP10 (Invitrogen) was used as the host strain for all plasmids. The DNA fragments from P. aeruginosa used for cloning were amplified from the genomic DNA of the PAO1 strain with Phusion High-Fidelity DNA polymerase (ThermoFisher Scientific). The primers used are listed in Table S2 of the Supporting Information. As previously described [START_REF] Guillon | High cellular organisation of pyoverdine biosynthesis in Pseudomonas aeruginosa: localization of PvdA at the old cell pole[END_REF], the general procedure involved the insertion of the 700 bp flanking sequences on either side of the gene to be deleted into the pME3088 suicide vector [START_REF] Voisard | Biocontrol of root diseases by Pseudomonas fluorescens CHAO: current concepts and Accepted Article experimental approaches[END_REF].

Mutations in the chromosomal genome of P. aeruginosa were generated by transferring the suicide vector from E. coli TOP10 strains into the PAO1 strain and allowing the plasmid to integrate into the chromosome, with selection for tetracycline resistance. A second crossingover event excising the vector was achieved by enrichment for tetracycline-sensitive cells, to Accepted Article generate the corresponding mutants [START_REF] Ye | Anaerobic activation of the entire denitrification pathway in Pseudomonas aeruginosa requires Anr, an analog of Fnr[END_REF]. All gene-deletion mutants were verified by PCR and sequencing.

For construction of the complementation plasmid encoding pfeA under the control of its own promoter, the gene was amplified from the chromosomal DNA of P. aeruginosa PAO1 by PCR with the pfeAatg-104F and pfeAstop+31R primers (Table S2 in Supporting Information). The PCR fragment was trimmed by digestion with EcoRI and HindIII and inserted between the sites for these enzymes in pMMB190 [START_REF] Morales | A series of wide-host-range lowcopy-number vectors that allow direct screening for recombinants[END_REF] and bacteria transformed with this vector.

Growth and quantification of fluorescence intensity. The cells were cultured overnight in

CAA medium, pelleted by centrifugation and resuspended in fresh CAA medium and the resulting suspension was diluted so as to obtain an optical density at 600 nm of 0.01 units. We dispensed 200 µl of the suspension per well into a 96-well plate (Greiner, U-bottomed microplate). The plate was incubated at 30°C, with shaking, in a Tecan microplate reader (Infinite M200, Tecan) for measurements of OD 600nm and mCherry (excitation/emission wavelengths: 570 nm/610 nm) fluorescence at 30-minute intervals, for 40 h. After 8 h of culture, we added 200 µM enterobactin, BCV or TCV and continued measurements of OD 600nm and mCherry fluorescence. We calculated the mean of three replicates for each measurement.

Quantitative real-time PCR. Specific gene expression was measured by reverse transcription-quantitative PCR (RT-qPCR), as previously described [START_REF] Gross | Genomics of secondary metabolite production by Pseudomonas spp[END_REF].

Briefly, overnight cultures of strains grown in LB or CAA medium were pelleted, resuspended and diluted in fresh medium to obtain an OD 600nm of 0.1 units. The cells were then incubated in the presence or absence of 10 µM enterobactin, azotochelin, protochelin, BCV and TCV, with vigorous shaking, at 30°C for 3 h (LB medium) or 8 h (CAA medium).

An aliquot of 2.5 x 10 8 cells from this culture was added to two volumes of RNAprotect

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Bacteria Reagent (Qiagen). Total RNA was extracted with an RNeasy Mini kit (Qiagen), treated with DNase (RNase-Free DNase Set, Qiagen) and purified with an RNeasy Mini Elute cleanup kit (Qiagen). We then reverse-transcribed 1 µg of total RNA with a High-Capacity RNA-to-cDNA Kit, in accordance with the manufacturer's instructions (Applied Biosystems).

The amounts of specific cDNAs were assessed in a StepOne Plus instrument (Applied Biosystems) with Power Sybr Green PCR Master Mix (Applied Biosystems) and the appropriate primers (Table S1), with the uvrD mRNA used as an internal control. The transcript levels for a given gene in a given strain were normalized with respect to those for uvrD and are expressed as a ratio (fold-change) relative to the reference conditions. Proteomics analysis. For the digestion and cleanup steps, 10 9 P. aeroginosa cells were lysed in 50 l lysis buffer (2% sodium deoxycholate, 0.1M ammoniumbicarbonate) and disrupted by two cycles of sonication for 20 seconds (Hielscher Ultrasonicator). Protein concentration was determined by BCA assay (Thermo Fisher Scientific) using a small sample aliquot.

Proteins were reduced with 5 mM TCEP (Tris (2-Carboxyethyl) phosphine Hydrochloride)

for 10 min at 95°C, alkylated with 10 mM iodoacetamide for 30 min in the dark at room temperature. Sample were diluted with 0.1M ammoniumbicarbonate solution to a final concentration of 1% sodium deoxycholate before digestion with trypsin (Promega) at 37°C over night (protein to trypsin ratio: 50:1). After digestion, the samples were supplemented with TFA to a final concentration of 0.5% and HCl to a final concentration of 50 mM. Precipitated sodium deoxycholate was removed by centrifugation (15 minutes at 4°C at 14,000 rpm). Then, peptides were desalted on C18 reversed phase spin columns according to the manufacturer's instructions (Macrospin, Harvard Apparatus), dried under vacuum and stored at -80°C until further processing.

For the shotgun proteomics assays, 1 ug of peptides of each sample were subjected to LC-MS (Liquid chromatography-mass spectrometry) analysis using a dual pressure LTQ-Orbitrap

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Elite mass spectrometer connected to an electrospray ion source (both Thermo Fisher Scientific) as described recently [START_REF] Glatter | Largescale quantitative assessment of different in-solution protein digestion protocols reveals superior cleavage efficiency of tandem Lys-C/trypsin proteolysis over trypsin digestion[END_REF] with a few modifications. In brief, peptide separation was carried out using an EASY nLC-1000 system (Thermo Fisher Scientific) equipped with a RP-HPLC column (75 μm × 45 cm) packed in-house with C18 resin (ReproSil-Pur C18-AQ, 1.9 μm resin; Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) using a linear gradient from 95% solvent A (0.15% formic acid, 2% acetonitrile) and 5% solvent B (98% acetonitrile, 0.15% formic acid) to 28% solvent B over 120 min at a flow rate of 0.2 μl/min. The data acquisition mode was set to obtain one high resolution MS scan in the FT part of the mass spectrometer at a resolution of 240,000 full width at halfmaximum (at m/z 400) followed by MS/MS scans in the linear ion trap of the 20 most intense ions using rapid scan speed. The charged state screening modus was enabled to exclude unassigned and singly charged ions and the dynamic exclusion duration was set to 30s. The ion accumulation time was set to 300 ms (MS) and 25 ms (MS/MS).

For label-free quantification, the generated raw files were imported into the Progenesis LC-MS software (Nonlinear Dynamics, Version 4.0) and analyzed using the default parameter settings. MS/MS-data were exported directly from Progenesis LC-MS in mgf format and searched against a decoy database the forward and reverse sequences of the predicted proteome from P. aeruginosa (SGD, download date: 04/03/2014, total of 23,971 entries) using MASCOT (version 2.4.0). The search criteria were set as follows: full tryptic specificity was required (cleavage after lysine or arginine residues); 3 missed cleavages were allowed; carbamidomethylation (C) was set as fixed modification; oxidation (M) as variable modification. The mass tolerance was set to 10 ppm for precursor ions and 0.6 Da for fragment ions. Results from the database search were imported into Progenesis and the final peptide feature list and the protein list containing the summed peak areas of all identified peptides for each protein, respectively, were exported from Progenesis LC-MS. Both lists

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were further statically analyzed using an in-house developed R script (SafeQuant) and the peptide and protein false discovery rate (FDR) was set to 1% using the number of reverse hits in the dataset [START_REF] Glatter | Largescale quantitative assessment of different in-solution protein digestion protocols reveals superior cleavage efficiency of tandem Lys-C/trypsin proteolysis over trypsin digestion[END_REF].

Iron uptake. The protonophore CCCP (carbonyl cyanide m-chlorophenylhydrazone) was purchased from Sigma. 55 FeCl 3 was obtained from Perkin Elmer Life and Analytical Sciences (Billerica, MA, USA), in solution, at a concentration of 71.1 mM, with a specific activity of 10.18 Ci/g. Siderophore-55 Fe complexes were prepared at 55 Fe concentrations of 20 µM, with a siderophore:iron (mol:mol) ratio of 20:1. Iron uptake assays were carried out as previously described for PVD-Fe transport [START_REF] Schalk | Ironfree pyoverdin binds to its outer membrane receptor FpvA in Pseudomonas aeruginosa: a new mechanism for membrane iron transport[END_REF][START_REF] Hoegy | Monitoring iron uptake by siderophores[END_REF], except that bacteria were grown in CAA medium in the presence or absence of 10 µM enterobactin or catechol chelator, to induce PfeA expression. The bacteria were then washed with 50 mM Tris-HCl pH 8.0, to eliminate the siderophores used to induce PfeA expression, and diluted to an OD 600nm of 1. Bacteria were then incubated in the presence of 200 nM chelator-55 Fe and the incorporation of radioactivity into the bacteria over time was monitored by filtration [START_REF] Schalk | Ironfree pyoverdin binds to its outer membrane receptor FpvA in Pseudomonas aeruginosa: a new mechanism for membrane iron transport[END_REF][START_REF] Hoegy | Monitoring iron uptake by siderophores[END_REF]. The experiments were repeated with cells pretreated with 200 µM CCCP. This compound inhibits the protonmotive force across the bacterial cell membrane, thereby inhibiting TonB-dependent iron uptake [START_REF] Clément | The binding mechanism of pyoverdin with the outer membrane receptor FpvA in Pseudomonas aeruginosa is dependent on its iron-loaded status[END_REF]. For the data presented in Table S3, the radioactivity incorporated into the bacteria was monitored after 15 minutes of incubation with the chelator-55 Fe complexes. 55 Fe uptake assays in the presence of PCH-55 Fe (200 nM) were carried out as for enterobactin except that the bacteria were harvest by centrifugation, as previously described [START_REF] Hoegy | Stereospecificity of the siderophore pyochelin outer membrane transporters in fluorescent Pseudomonads[END_REF][START_REF] Hoegy | Monitoring iron uptake by siderophores[END_REF], and not by filtration to avoid an adsorption of PCH-55 Fe on the GFB filters.

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Figure 1 :

 1 Figure 1: Structures of enterobactin (ENT), azotochelin (BCS), protochelin (TCS), bis-

Figure 2 :

 2 Figure 2: Analysis of changes in the transcription of the pfeA gene. RT-qPCR was

Figure 3 :

 3 Figure 3: Analysis of expression changes for TBDTs (panel A) and proteins of the PVD

Figure 4 :

 4 Figure 4: Panels A-E. Time-dependent 55 Fe assimilation in P. aeruginosa cells in the presence of 55 Fe-loaded enterobactin, azotochelin, protochelin, BCV and TCV. The

Figure 6 :

 6 Figure 6: A. Analysis of changes in transcription for the genes of the PCH pathway. fptA

Figure 7 :

 7 Figure 7: Monitoring of PchE-mCherry (panel A) and FptX-mCherry (panel B)

TABLE 55

 55

			Fe atoms/bacterium/min
		Enterobactin Azotochelin Protochelin	BCV	TCV
	PAO1 in LB	827 ± 64	299 ± 33	98 ± 4	661 ± 32 145 ± 14
	∆pvdF∆pchA in CAA 1306 ± 220	712 ± 126	273 ± 62 372 ± 68 363 ± 36

Table 1 : 55 Fe assimilation in P. aeruginosa PAO1 and ∆pvdF∆pchA cells in the presence of 55 Fe -loaded enterobactin, azotochelin, protochelin, BCV and TCV

 1 . PAO1 was grown in LB and the corresponding PVD-and PCH-deficient ∆pvdF∆pchA strain in CAA medium. Cells were grown with 10 µM of the catechol compound used for 55 Fe uptake to induce PfeA expression. The bacteria were then washed with 50 mM Tris-HCl (pH 8.0) and transport assays were initiated by adding the various catechol compounds loaded with 55 Fe to a concentration of 200 nM. Samples (100 µl) were taken from the suspensions at various time points and filtered; the radioactivity retained was measured. The results are expressed as atoms of 55 Fe transported per bacterium per min (n = 3).

ACKNOWLEDGMENTS 539

This work was partly funded by the Centre National de la Recherche Scientifique and 540 grants from the ANR (Agence Nationale de Recherche, IronPath ANR-12-BSV8-541 0007-01). In addition, these results were generated as part of the work of the 542

Translocation Consortium (www.translocation.com)