Caterina Maria Lombardo

Vasantha Kumar

Céline Douat

Frédéric Rosu

Jean-Louis Mergny

Gilmar Salgado
email: gilmar.salgado@u-bordeaux.fr

Gilles Guichard
email: g.guichard@iecb.u-bordeaux.fr

Design and Structure Determination of a Composite Zinc Finger Containing a Non-peptide Foldamer Helical Domain

Keywords: Zinc finger, oligourea foldamer, NMR structure, protein prosthesis, helix mimicry

A number of foldamer backbones have been described as useful mimics of protein secondary structure elements, enabling for example the design of synthetic oligomers with the ability to engage specific protein surfaces. Synthetic folded backbones can also be used to create artificial proteins in which a folded peptide segment (e.g. α-helix, a loop) is replaced by its unnatural counterpart, with the expectation that the resulting molecule would maintain its ability to fold while manifesting new exploitable features. The similarities in screw sense, pitch and polarity between α-helices and oligourea 2.5-helices suggest that a tertiary structure could be retained when swapping the two backbones in a protein sequence. In the present work we move a step towards the creation of such composite proteins by replacing the 10-residue long original α-helical segment in the Cys2His2 zinc finger 3 of transcription factor Egr1 (also known as Zif268) by an oligourea sequence bearing two appropriately spaced imidazole side chains for zinc coordination. We show by spectroscopic techniques and mass spectrometry analysis under native conditions that the ability of the peptide/oligourea hybrid to coordinate zinc ion is not affected by the foldamer replacement. Moreover, detailed NMR analysis provides evidence that the engineered zinc finger motif adopts a folded structure in which the native beta-sheet arrangement of the peptide region and global arrangement of DNA binding side chains are preserved. Titration in the presence of Egr1 target DNA sequence supports binding to GC bases as reported for the wild type zinc finger.

INTRODUCTION

Recent progress in the creation of artificial proteins with accurate control over chemical composition, three-dimensional structure, and appending functionalities [1][2][3][4][5][6] open avenues for a range of downstream applications from therapeutics and delivery systems to catalysts and bionanomaterials. In this context, protein backbone engineering (protein prosthesis 7 ), 3 which benefits from current advances in the total chemical synthesis and semi-synthesis of proteins, [8][9][10][11][12] can be used to interrogate protein folding, address the role of individual folded segments, modulate protein function and fine tune a range of properties among which immunogenicity, solubility, resistance to proteolytic degradation and cell permeability. A number of reports have investigated the effect of substituting the amide bond by surrogates, or small subsets of α-residues in loop and turn segments by either constrained or more flexible mimics. 7,10,[13][14][15][16][17][18][19][20][21] Fewer studies, however, have reported composite proteins in which a larger folded segment (e.g. an α-helix) was replaced by an artificial one. The ability to create isolated and stable artificial secondary structure elements from a variety of non-biological synthetic oligomeric backbones (i.e. foldamers [22][23][24] ) either close or remote from natural biopolymers provides new opportunities to design and investigate such composite proteins. 25 A noteworthy example is a semisynthetic analogue of human interleukin 8 (IL-8) in which the C-terminal α-helix was replaced by a 14-residue β 3 -peptide sequence. 26 Although the artificial chemokine retained significant biological activity, it should be noted that the incorporated 3 14 -c β-peptide segment differs from the original α-helix in both handedness and dipole orientation. 26,27 In the absence of high-resolution structural information, it is not possible to draw firm conclusion about the level of mimicry that was actually achieved in this system in terms of tertiary structure. Concurrently, structural details about the effect of β-residue substitutions evenly distributed in α-helical segments of discrete tertiary structures (e.g., B1

domain of protein G from Streptococcus bacteria (GB1), 28 villin headpiece subdomain, 29 ) and within coiled coils (e.g., yeast transcriptional activator GCN4-derived peptides) [30][31][32] have been reported independently by Gellman and Horne. In particular, the Horne group has shown that the GB1 tertiary fold can accommodate up to 20% unnatural residues (i.e., a combination of D-amino acid, aminoisobutyric acid, N-Me-amino acid, and β 3 -amino acid replacements) strategically placed in different secondary structure elements (helix, loop, sheet, and turn) 28 highlighting the substantial plasticity of the protein backbone.

Swapping a whole secondary structure element such as α-helix with its foldamer counterpart in a protein context without causing major unfolding remains a challenge and ideally requires the two folded backbones to exhibit a high degree of similarity and complementarity in terms of shape and side chain distribution. We have previously reported that c '-linked oligoureas, a class of non-peptidic foldamers that can be decorated with proteinogenic side chains, adopt a helical conformation closely resembling the α-helix in terms of diameter, pitch, handedness, and polarity. 33 Their stability in water and their high tunability have already been exploited to program the formation of complex assembled architectures, such as discrete helical bundles and channels. [34][35][36] Furthermore, it has been shown in model chimeric molecule c f f αhelical peptides segments (so called block co-foldamers), that the two helical structures both coexist and communicate. [37][38][39] Although the canonical oligourea and peptide helices differ by the number of residues per helix turn (2.5 for oligoureas 33 6 f α-peptides), an overlay of the two helical backbone reveals a relatively close match between a three-residue-long oligourea and an α-helical tetrapeptide (Root-mean square deviations (RMSDs) calculated for four carbonyl C atoms and four NHs = 0.7867 Å, Fig. 1a). This observation suggested to us that a composite foldamer protein could be generated by substituting an α-helical segment for a designed oligourea sequence of appropriate length, although care must be taken to preserve the distribution and space orientation of key side chains.

To test our ability to design such a foldamer-based mimic of a folded protein, we selected the Cys2His2 zinc finger motif. Zinc fingers are recurrent protein motifs (found in 2% of human genes) involved in specific duplex DNA recognition, whose folding properties have been extensively studied using native and simplified synthetic systems. [40][41][42][43] Cys2His2 zinc fingers are (relatively) small and modular units of about 30 residues, w c c f w f β-sheet connec ck α-helix. This archetypal ββα f stabilized by a single zinc ion coordinated f c c β-sheet and a pair of histidine residues located at the C-f α-helix in a tetrahedral geometry (Fig. 1b) 42 Zinc coordination is playing a key role at directing folding of the motif and at correctly orienting α-helix residues in direct contact with DNA, and thus it is crucial that the histidine and cysteine side chains are properly displayed. To the best of our knowledge, only few studies have investigated the effect of side chain metal coordination for the stabilization of foldamer secondary [44][45][46][47][48][49] or tertiary structures. 50 Here, we selected Egr1 (Zif268), a transcription factor involved in cell proliferation and in the regulation of apoptosis as a target zinc finger protein. We describe the design and synthesis of a chimeric oligourea-zinc finger mimic whereby the native α-helically folded segment containing the two key histidines and the DNA -binding side chains has been replaced by an oligourea sequence (Fig. 1b). [51][52] We have studied in detail the metal binding properties of the resulting composite protein by UV-Vis spectroscopy, circular dichroism (CD), ESI-MS and NMR analyses and have determined its three-dimensional solution structure by NMR spectroscopy. Our results

show that we successfully conceived a composite zinc finger that mimic the native protein in different aspects such as folding, metal and DNA binding.

RESULTS AND DISCUSSION

Design and synthesis. We focused our efforts on one of the three zinc finger motifs of the zinc finger region (hereafter numbered from residue 1 to 90) of Egr1, namely finger 3 (Fig. 1b) encompassing residues 62-90. Examination of the X-ray crystal structure of a complex between a protein fragment encompassing the three fingers of Egr1 and a duplex DNA with a consensus binding site, [START_REF] Pavletich | Zinc finger-DNA recognition: crystal structure of a Zif268-DNA complex at 2.1 A[END_REF][START_REF] Elrod-Erickson | Zif268 protein-DNA complex refined at 1.6 A: a model system for understanding zinc finger-DNA interactions[END_REF] revealed that the α-helix domain of finger 3 spans 11 residues (three helical turns) from Ser75 to His85. An overlay of the zinc finger helix with the X-ray crystal structure of a canonical oligourea helix 34 suggested to us that the distribution and spacing of the two key imidazole side chains (His81 and His85) could be preserved by substituting a short oligourea segment of 8 residues (whose sequence is shown in Fig. 1c) for the residues Asp76-His85 of the α-helix. His-type side chains which are in a i/i+4 relationship in the natural peptide sequence, are in a i/i+3 relationship in the chimeric molecule. It is noteworthy that the side chains at the N-terminus of the α-helix known to contact nucleobases in the major groove of DNA, namely Asp76 at P2, Glu77 at P3 and Arg80 at P6 have been maintained in the sequence of the cognate oligourea foldamer segment. The artificial zinc finger urea Fn3 was assembled using a fragment condensation approach on solid support, taking advantage of the presence of a glycine residue in the sequence (Fig. 2a, supplementary methods).

The hybrid C-terminus which contains the oligourea segment was synthesized on MBHA resin by microwave assisted solid-phase synthesis (SPS) using a set of N-Boc-protected-1,3-diamino monomers carrying the side chains of Ile, Lys, Asp, Glu and His (BB1-BB6) activated as succinimidyl carbamates for urea formation [START_REF] Douat-Casassus | Microwave-Enhanced Solid-Phase Synthesis of N,N '-Linked Aliphatic Oligoureas and Related Hybrids[END_REF][START_REF] Nelli | An activated building block for the introduction of the histidine side chain in aliphatic oligourea foldamers[END_REF] along with standard N-c α-amino acids. The key monomer containing the (1H-imidazolyl-4yl)methyl side chain of histidine (BB6) was prepared from

Trt-His(τ-Trt)-OMe in seven steps with an overall yield of 35 % as described previously. [START_REF] Nelli | An activated building block for the introduction of the histidine side chain in aliphatic oligourea foldamers[END_REF] The fully protected N-terminal fragment (residues 62-68) was synthesized on 2-chlorotrityl resin using N-Fmoc α-amino acids (plus Boc-Pro-OH as last residue) and released by treatment with a 3:2 mixture of hexafluoroisopropanol (HFIP) and CH 2 Cl 2 57

. It was then reacted directly with the αamino function of the solid-supported C-terminal fragment in the presence of BOP and HOBt as coupling agents, to afford the desired urea Fn3 with a 68% crude yield after HF cleavage. For head to head comparison, we also synthesized the native finger 3 peptide ( native Fn3) using standard SPS methodology and Fmoc strategy (see Supporting Information for details). Both urea Fn3 and native Fn3

were purified by preparative reversed-phase HPLC (C 18 ) to a final purity of >95%, lyophilized and characterized by ESI-MS (Fig. 2b).

Metal binding properties of urea Fn3. The ability to coordinate Zn 2+ cannot be directly assessed by UV-Vis spectroscopy, because Zn 2+ has a full d 10 shell, and is therefore UV silent. We thus performed a first titration experiment using Co 2+ , which is known to form complexes with the same geometry as Zn 2+ and has a partially empty d-shell. A signal between 500 and 800 nm, characteristic of the d-d transition of a tetrahedral Co 2+ complex was observed upon titrating both urea Fn3 and native Fn3 with CoCl 2 (Fig. 3a and Supplementary Information).

A sharp end point was reached in both cases upon addition of 1 equivalent of metal, supporting a 1:1 stoichiometry for the complexes and strong binding. The zinc finger─Co 2+ complexes were subsequently retro-titrated with ZnCl 2 , and for both compounds, a decrease of the signal in the visible region was observed, indicating a displacement of Co 2+ by Zn 2+ in the complex (Fig. 3b and Supplementary Information). The stability of the two zinc finger─Zn 2+ complexes was estimated by fitting the titration data to a 1:1 competitive binding model and very similar K d values were obtained (K d = 2•10 -9 M for urea Fn3─Zn 2+ and 6•10 -9 M for native Fn3─Zn 2+ ). In contrast, the kinetics of Co 2+ displacement varied between the two zinc fingers from 4 minutes for urea Fn3, to 20 minutes for native Fn3 (see Supplementary Information). Since the end point of the direct titration with Co 2+ was too sharp, the K d f z c f ─Co 2+ complexes was determined in an independent UV titration experiment, by using CoCl 2 in the presence of NTA as competitor (K d NTA─Co 2+ = 8.1•10 -8 M, 58 see

Supplementary Information). 43

To gain additional insight into the effect of metal complexation on the overall tertiary structure, we also recorded CD spectra for the two Zn finger motifs at increasing concentrations of Zn 2+ . For native Fn3 a decrease in the negative molar ellipticity around 200 nm and an increase of the signal around 220 nm are observed upon ZnCl 2 addition. A similar behavior was described in previous

reports 59,60 c c c f ββα f z c f f T D signature
of urea Fn3 differs substantially from the native domain: the molar ellipticity is positive around 200 nm, which is attributable to oligourea 2.5-helical folding. Furthermore, a negative signal at 230 nm, which decreases upon ZnCl 2 addition, suggests a partial reorganization of the system upon metal binding (Fig. 3c and supplementary Fig S8). The titration end point was reached upon addition of 1 equivalent of the metal in agreement with UV-vis spectroscopy experiments and the formation of a 1:1 complex. The stoichiometry of the complex with Zn 2+ was further supported by native mass spectrometry experiments (Fig. 4). For both motifs, only the 1:1 complexes were observed in the presence ZnAc 2 (3+ and 4+ charge states being the most populated regardless of the amount of metal added).

To further examine the metal binding profile of urea Fn3 in comparison with native Fn3, we recorded ESI-MS spectra in the presence of equimolar amounts of Zn 2+ , Co 2+ , Cd 2+ and Hg 2+ and an excess of zinc finger in 100 mM NH 4 OAc, pH ~6.8 (Fig. 4b). By comparing the relative intensities of the species observed it was possible to estimate the relative stability of the complexes formed, and thus the metal binding preferences of each motif. However, since the affinity of Hg 2+ for NH 3 significantly differs from that of the other metal ions, Hg 2+ being the most sequestered by NH 3 (from NH 4 Ac), care must be taken when interpreting intensity ratios with zinc finger-Hg 2+ complexes. The 1:1 complex with Zn 2+ and the 1:1 complex with Co 2+ were the most abundant species detected with both native and urea-containing sequences. The two sequences were found to differ by their binding profile to heavy metals. Whereas only a weak signal corresponding to 1:1 complexes with Cd 2+ and Hg 2+ was observed for the native sequence, the chimeric motif was found to readily bind Cd 2+ and Hg 2+ as revealed by the intense peaks corresponding to the 1:1 complexes and also by the substantial amount of the 2:1 urea Fn3─Cd 2+ complex in the ESI-MS spectrum. NOE analysis and structure calculation. Sequence-specific assignment of the 1:1 urea Fn3─Z complex was achieved using multiple multidimensional homonuclear and heteronuclear NMR experiments including 2D DQF-COSY, 1 H-15 N HSQC, 1 H-13 C edited HSQC, 1 H-1 H TOCSY and 1 H-1 H NOESY. High resolution 2D 1 H-1 H NOESY spectra obtained at high field (950 MHz) were necessary to unambiguously assign and sequentially link each oligourea spin system. In the end, nearly 97% of the expected resonances for urea Fn3─Z w (F Table S1).

Qualitative inspection of inter-residue NOEs extracted from NOESY experiments at 950 MHz revealed several key features supporting folding of urea Fn3─Z into a defined tertiary structure.

Firstly, the presence of repeated and typical medium range NOE cross peaks of the type H(i)/HN(i+2) and H(i)/HN 2 (i+2) all along the oligourea segment is consistent with the formation of a canonical oligourea 2.5-helix as previously reported. His U 83 residues confirmed protonation at the Nδ  position and that the Nε position is free to coordinate zinc metal ion. The solution NMR structure of the 3.4 KDa urea Fn3─Z was calculated using 231 experimental NOE inter proton distances in combination with 22 torsional angles (f α-L amino acids) and 32 weak hydrogen bond restraints for both natural and urea-type residues (Table S1) as described in the supplementary information. Briefly, NOE inter proton distance restraints were extracted from the in-depth analysis of 2D NOESY spectra acquired at different mixing time 120 and 250 ms and used for structure calculation in a simulated annealing protocol with AMBER 12 molecular dynamics package. [START_REF] Case | AMBER 12[END_REF] The 200 best lower energy coordinates from vacuum simulation were selected for further minimization and 40 ps simulated annealing NMR refinement using generalized Bohr (GB) implicit solvent model. The 10 conformers with the lowest total energy were extracted from the MD trajectory and subjected to further refinement in an explicit water box with periodic boundary condition. The final structure ensemble is shown in Fig. 6a and structural statistics are given in Table S1.

Owing to the composite nature of urea Fn3, the final NMR ensemble of conformers could not simply be checked with online structure validation tools. Structures of urea Fn3 were validated in two steps by first analyzing dihedral angles in the C-terminal oligourea segment over 40 ps of restrained molecular dynamics in comparison with values extracted from X-ray crystal structures of oligourea helices. 33,34 In a second step, the α-peptide segment in the structure (i.e. residues 62-75) was submitted to PROCHECK [START_REF] Laskowski | PROCHECK: a program to check the stereochemical quality of protein structures[END_REF] for validation.

Solution structure of urea Fn3 and comparison with the native fold. The solution structure of urea Fn3─Z was obtained with a well-defined backbone core and a root-mean-square deviation (RMSD) of 0.35 Å. As shown in Fig. 6, urea Fn3 adopts a native-like tertiary structure consisting of a short antiparallel β sheet connected to the helically folded oligourea segment. The structure is held together by tetrahedral zinc coordination of the two Cys residues in the peptide region and the imidazole side chains of the two His U units in the 2.5-helix oligourea segment. A general feature of native ββα zinc fingers is the presence of a small hydrophobic core that brings additional stabilization to the structure and that generally involves a highly conserved aromatic residue (Phe72 in native Fn3) packed edge to face against the proximal histidine (His81 in native Fn3).

Compared to the ββα f of native Fn3 (PDB ID: 1AAY), [START_REF] Elrod-Erickson | Zif268 protein-DNA complex refined at 1.6 A: a model system for understanding zinc finger-DNA interactions[END_REF] the hydrophobic core in urea Fn3 is less compact because the loop connection between the β-strand and the helix region is more extended.

This distortion of the loop segment may be due in part to the larger diameter of the oligourea helix c α-helix. However, the packing of the Phe72 over His U 80 is maintained.

Conformational similarities and differences between native Fn3 and urea Fn3 are further highlighted by the structural alignment of the two N-terminal peptide segments (13 to 13 Cα atoms) which gives an average root-mean-square deviation of 1.166 Å (calculated for the 10 lowest-energy structures (Fig. 6d).

DNA binding properties of the chimeric urea Fn3 zinc finger

We next evaluated the ability of urea Fn3 to interact with a short double-strand DNA sequence using chemical-shift mapping experiments and the Egr1 GC rich binding motif. First, the DNA imino region peak dispersion was monitored by 1D 1 H NMR spectroscopy upon successive additions of 0.5-2.5 molar equivalents of urea Fn3 to DNA. As depicted in Fig. 7, a clear shift of several imino peaks was observed, notably G2, G4 and a third ambiguous G imino peak. 1 H-1 H NOESY experiments were used to tentatively assign imino peaks in the dense region between 12.7 and 12.9 ppm. The results seem to indicate that urea Fn3 binds to the ' f DNA

( '-1 AGCGTGGGCG 11 T-') ( '-' TCGCACCCGC ' A-'). No important chemical shift variations w ' region f ( '-1 AGCGTGGGCG 11 T-')
Apparent dissociation constants (K d ) were obtained by fitting the titration data to a single-site ligand-binding mode and were found to be in the range of 0.19-0.25 mM (see the Supplementary Information and supplementary Fig. S9 for more details). These values are consistent with previous reports showing that a single Cys2His2 zinc finger domains bind with low affinity to DNA. [START_REF] Nedved | Cooperative, non-specific binding of a Zinc finger peptide to DNA[END_REF] High affinity recognition of DNA requires cooperativity and is achieved with protein domains containing three or more zinc fingers.

CONCLUSIONS

We have shown here that the structural resemblance between urea-based helical foldamers αhelical peptides can be exploited by combining the two backbones in a single chain to create protein mimics with defined tertiary structures. The design of the chimeric Cys2His2-type zinc finger reported in this work was guided by the knowledge of the structures of oligourea 2.5-helices at atomic resolution and was facilitated by their predictability, the helix folding propensity of urea oligomers being largely unaffected by the nature of the side-chains used. 34 We observed that the metal binding ability of the composite zinc finger ( urea Fn3) was fully retained upon substituting the α-helix by the designed oligourea prosthesis, which indicates that the distribution of histidine-type side chains at the surface of the oligourea helix is fully compatible with the formation of a tetrahedral zinc complex. Furthermore, detailed NMR-derived 3D structure determination of the composite zinc finger in solution showed that the native beta-sheet arrangement of the peptide region was not compromised by helix swapping, and that a well-defined tertiary structure akin to the native fold was formed. Specific features of urea Fn3 such as an extended loop w βstrand and the helix region and a less compact hydrophobic core compared to native Fn3 may account for the differences in kinetics of metal exchange and binding selectivity observed between urea Fn3 and native Fn3. Despite these differences, detailed inspection of the structure also revealed that overall the relative orientation of side chains involved in DNA binding by Cys2His2 Zinc fingers (namely Arg74, Asp U 76, Glu U 77 and Arg U 79 corresponding to -6 f αhelix) is relatively similar to that in the native zinc finger. The finding that urea Fn3 binds DNA suggests that affinity could be increased significantly by incorporating it into a larger protein sequence containing multiple zinc finger motifs. It would then be tempting to evaluate how the foldamer replacement affects sequence specificity of DNA binding knowing that a given zinc finger motif is contacting three base pairs in a sequence dependent manner.

The approach reported in this work may prove to be more general and could be applied to other systems that fold without metals. The ability to combine synthetic oligourea foldamers and natural polypeptides to re-design proteins can be seen as a promising approach to create proteinomorphous objects with properties and possible applications beyond those known for natural proteins.

EXPERIMENTAL SECTION

Chemistry. The composite zinc finger urea Fn3 was synthesized using a fragment condensation approach by coupling the fully protected peptide encompassing residues 62-69 directly to the growing peptide/oligourea chain (residues 70-86) on the solid support. The 62-69 peptide segment was synthesized on a 2-chlorotrityl chloride resin using standard N-Fmoc chemistry (at the exception of the final Pro residue incorporated as N-Boc-Pro-OH), whereas the chimera was assembled by using N-Boc protected amino acid residues and N-Boc-protected succinimidyl carbamate building blocks for urea formation starting from a low-loading MBHA resin. The native zinc finger was synthesized on solid support by standard Solid-phase peptide synthesis using N-Fmoc-c α-amino acid derivatives on low-loading Rink-amide MBHA resin. Additional details about chemical synthesis and purification and characterization of urea Fn3 and intermediates can be found in the Supplementary Information.

UV-vis and CD spectroscopy:

All the samples were dissolved in phosphate buffer 20 mM pH 7.5 and the measurements were performed under a positive atmosphere of Ar. The titrations were carried out in the presence of an excess of TCEP (about 0.5 mM), to ensure the complete reduction of the Cys residues. All the solutions used were previously purified through Chelex resin column (Bio-Rad), to eliminate any undesired metal contaminations, and degassed prior to use.

For the elaboration of the data the dilution was taken into account and all the curves were corrected for the blank and the baseline adjusted to zero. The curves were fitted to the appropriate equilibrium using the software Origin 8.0. CD experiments were performed on a Jasco J-815 spectrometer. Data were recorded at 20 °C with a speed of 50 nm/min between wavelengths of 200 and 300 nm, at 1 nm intervals and with an integration time of 2 seconds. Each measurement was repeated twice and averaged. For the elaboration of the data the dilution was taken into account and all the curves were corrected for the blank and the baseline adjusted to zero.

Experimental details are provided in Supplementary Information.

NMR spectroscopy, sequence specific assignment and restraints: Initial NMR experiments were performed at 298 K, unless specified otherwise, using Bruker 700 MHz, 800 MHz NMR spectrometers equipped with 5mm TXI and cryoprobe respectively, with the ability to apply pulse field gradient along z-axis. To obtain the sequence-specific-assignment of urea Fn3, a set of standard homonuclear NMR experiments including 2D 1 H-1 H DQF-COSY, 2D 1a) frequencies that resonate over 1.3 ppm (between 5.6 ppm to 6.9 ppm) on F2

dimension. The number of oligourea amide protons together with side chain chemical shifts degeneracy (on F1 & F2 dimensions) significantly contributed to poor spectral resolution and hampered the quality of NOESY spectra acquired on 800 MHz spectrometer. To alleviate resonance crowding and to improve both resolution and quality of NMR spectra all the above listed experiments were repeated on the same sample (90% H 2 O, 10% D 2 O, NaOH + HCl buffer, pH 6.5, total 220 µL) on a 950 MHz spectrometer equipped with a 5 mm cryogenically cooled probe-head with the z-axis pulse filed gradient (CERM, Florence). In all the experiments recycle delay was set to 1.5 s and water suppression was achieved by excitation sculpting method. Initial acquisition of 1 H-15 N spectra with standard acquisition parameters (spectral width and offset) did not show all the expected peaks. Preliminary observation confirmed that oligourea amide proton 1 H N2 and its directly bonded nitrogen 15 N 2 resonate far from the regular 15 N/ 1 H N chemical shift range, hence in 2D 1 H-15 N NMR experiment F1 dimension( 15 N) spectral offset was set to 100 ppm with the total spectra width of 60ppm. For the rest of the listed NMR experiments, standard offset and spectral width were used. All NMR spectra were processed using topspin 3.2 (Bruker BioSpin) and SPARKY [START_REF] Goddard | SPARKY 3[END_REF] for spectra analysis and data interpretation.

Structure calculation and refinement in explicit solvent. NMR restrained based structure calculation of urea Fn3 was performed using sander module of AMBER 12 (AMBER tool 14) and ff99SB force field [START_REF] Hornak | Comparison of multiple Amber force fields and development of improved protein backbone parameters[END_REF] by distance geometry simulated annealing in GB model and restrained molecular dynamics refinement in explicit solvent as described in Supplementary Methods.

ACKNOWLEDGMENTS

ASSOCIATED CONTENT

The Supporting Information is available free of charge on the ACS Publications website at DOI: , that shows the formation of predominantly a 1:1 complex between metal and peptide. On the right: ESI-MS profile of 75µM of native peptide in the presence of 15 µM of ZnAc 2 , CoCl 2 , CdAc 2 and HgAc 2 , respectively. The peptide shows similar affinities for Co 2+ and Zn 2+ , with which it forms predominantly 1:1 complexes (as demonstrated by the zoom on the distribution of charge). The peptide shows lower affinity for Cd 2+ and the presence of complexes with mixed stoichiometry with Cd 2+ is observed. Extra care must be taken with the intensity ratio of zinc finger-Hg 2+ because the affinity og Hg 2+ for NH 3 (from the ammonium acetate) is significantly higher than the other metal. b, on the left: ESI-MS profile of the chimeric Zinc Finger urea Fn3 in the presence of 1 equivalent of ZnAc 2 , that shows the formation of predominantly a 1:1 complex between metal and oligomer. On the right: ESI-MS profile of 75 µM of chimeric Zinc Finger in the presence of 15µM of ZnAc 2 , CoCl 2 , CdAc 2 and HgAc 2 , respectively. The oligomer shows similar affinities for Cd 2+ and Zn 2+ , and forms 1:1 complexes with the latter, as demonstrated by the distribution of charge. The formation of both a 1:1 and 2:1 oligomer/metal complexes is observed with Cd 2+ .The chimeric Zinc Finger shows lower affinity for Co 2+ . ( '-TCGCACCCGCA-') by urea FN3. a, Part of the 800 MHz 1D 1 H NMR spectra of duplex DNA in the absence (i), and in presence of 0.5 equiv. (ii), 1 equiv. (iii),1.5 equiv. (iv), 2 equiv. (v) and 2.5 (vi) of urea FN3. The addition of increasing amount of urea FN3 caused large chemical shift changes of mainly three imino protons of DNA duplex, G2, G4 and an ambiguous imino marked with an asterisk. b, Zoomed region of the 1 H-1 H NOESY spectra showing chemical shift variation crosspeaks of H8 from C bases and imino protons of G bases upon addition of 2.5 molar equivalents of urea FN3.

1H-

  NMR analysis qualitatively supports folding of urea Fn3 upon Zinc coordination. Onedimensional 1 H NMR spectra of urea Fn3 were recorded in the absence and presence of one equivalent of Zn 2+ metal ions in 10 mM Sodium phosphate buffer (NaPi) buffer at pH 6.5. 1 H NMR spectral comparison, depicted in Fig.5ashow remarkable changes in the chemical shift dispersion upon zinc addition indicating structural fluctuation and conformational change. In the absence of zinc 1 H NMR spectra of urea Fn3 show broader resonance lines and limited chemical shifts dispersion of NH (both amide and urea) signals, suggesting the absence of well-defined structure. Conversely, in the presence of zinc, the 1 H NMR spectra of urea Fn3 feature increased chemical shift dispersion of NH signals and sharp resonance peaks supporting the formation of a folded conformation as a result of metal coordination.

  This work was funded in part by the CNRS and ANR (Project ANR-12-BS07-0019). A Marie kł w k -Curie postdoctoral fellowship (FP7-PEOPLE-2012-IEF-330825) to C.M.L. is gratefully acknowledged. The work on the 800 MHz NMR spectrometer (IECB) was possible thanks to support from TGIR-RMN-THC Fr3050 CNRS, CNRS UMS3033, Inserm US001, Univ. Bordeaux. The project also received support from the Integrated structural biology (Instruct) program which is part of the European Strategy Forum on Research Infrastructures (ESFRI). We thank the personnel from the Center for Magnetic Resonance (CERM) Florence, Italy for the support during stay in Florence. G.G. also thank Olivier Sénèque and Valérie Gabélica for helpful discussions.

(Figure 1 .

 1 Figure 1. Design guided by the structure of composite proteins containing artificial helical foldamer region. a, Comparison of α-peptide (green) and oligourea (orange) backbones and overlay of their c c (α-helical tetrapeptide vs 2.5-helical triurea) illustrating the structural resemblance (dimensions, handedness, polarity) between the two helical backbones. b, Application to the construction of a composite Cys2His2 zinc finger w ββα f c, Sequence of designed composite zinc finger urea FN3 and the native zinc finger native FN3 derived from Zif268.

Figure 2 .

 2 Figure 2. Synthesis of urea Fn3. a, General Scheme illustrating the fragment condensation approach on solid-support which was used to assemble the composite zinc finger. b, HPLC trace and mass spectrometry data of the purified oligomer. Note: for clarity reasons all the side-chain protecting groups have been omitted.

Figure 3 .

 3 Figure 3. Spectroscopic analysis of Zn 2+ binding to urea Fn3. a, UV-Vis titration of urea Fn with excess CoCl 2 . The Inset on the left present a zoom on the regions corresponding to the LMCT bands and d-d transitions indicative of a tetrahedral coordination of Co 2+ . The inset on the right shows the concentration dependent increase of the signal upon addition of Co 2+ b, Progressive disappearance of this signature at 650 nm upon competitive titration with Zn 2+ and curve fitting using a 1:1 binding model. c, CD signature of urea Fn3 and native Fn3 in the absence and upon addition of one equivalent of Zn 2+ .

Figure 4 .

 4 Figure 4. ESI-MS analysis. a, on the left: ESI-MS profile of the native peptide in the presence of 1 equivalent of ZnAc 2, that shows the formation of predominantly a 1:1 complex between metal and peptide. On the right: ESI-MS profile of 75µM of native peptide in the presence of 15 µM of ZnAc 2 , CoCl 2 , CdAc 2 and HgAc 2 , respectively. The peptide shows similar affinities for Co 2+ and Zn 2+ , with which it forms predominantly 1:1 complexes (as demonstrated by the zoom on the distribution of charge). The peptide shows lower affinity for Cd 2+ and the presence of complexes with mixed stoichiometry with Cd 2+ is observed. Extra care must be taken with the intensity ratio of zinc finger-Hg 2+ because the affinity og Hg 2+ for NH 3 (from the ammonium acetate) is significantly higher than the other metal. b, on the left: ESI-MS profile of the chimeric Zinc Finger urea Fn3 in the presence of 1 equivalent of ZnAc 2 , that shows the formation of predominantly a 1:1 complex between metal and oligomer. On the right: ESI-MS profile of 75 µM of chimeric Zinc Finger in the presence of 15µM of ZnAc 2 , CoCl 2 , CdAc 2 and HgAc 2 , respectively. The oligomer shows similar affinities for Cd2+ and Zn 2+ , and forms 1:1 complexes with the latter, as demonstrated by the distribution of charge. The formation of both a 1:1 and 2:1 oligomer/metal complexes is observed with Cd 2+ .The chimeric Zinc Finger shows lower affinity for Co 2+ .

Figure 5 . 1 H

 51 Figure 5. 1 H NMR analyses of urea FN3. a, Comparison of 1D 1 H NMR spectra of urea FN3 in the absence (top) and in the presence of zinc cation (bottom). b, HN HSQC spectra of urea FN3 (left) H N from the regular amide protons and (right) H N and H N2 from the oligourea amide protons. Oligourea residues (76-83) are colored in orange whereas regular α-amino acid residues are shown in blue. c, 2D 1 H-1 H TOCSY (green) and NOESY (black) NMR spectra with a mixing time of 120 and 250 ms respectively.

Figure 6 .

 6 Figure 6. NMR-derived model of urea FN3. a, ten superimposed lowest-energy structures from the restrained molecular dynamics rMD-GB in explicit solvent with boundary conditions. The backbone CA RMDS between inter model is 0.6-0.7 Å. Carbon atoms in the peptide segment are depicted in light blue whereas those in the oligourea segment are depicted in orange. b, view of a representative conformation of urea FN3 highlighting coordination to zinc metal ion. c, Comparison with the structure of native FN3 as found in the X-ray crystal structure of Egr1 complexed with a duplex DNA sequence (PDB ID: 1AAY 54 ). d, Structural alignment of the N-terminal peptide segments ( α) of urea FN3 (one representative low energy structure) and native FN3 (PDB ID: 1AAY).

Figure 7 .

 7 Figure 7. 1 H NMR titration of Egr1 duplex DNA d( '-AGCGTGGGCGT-') ( '-TCGCACCCGCA-') by urea FN3. a, Part of the 800 MHz 1D 1 H NMR spectra of duplex DNA in the absence (i), and in presence of 0.5 equiv. (ii), 1 equiv. (iii),1.5 equiv. (iv), 2 equiv. (v) and 2.5 (vi) of

  as those between Hβ, Hγ and Hδ of Ile67 and protons Hδ1 and Hε from His U 83, suggest that both parts are aligned side-by-side. Moreover, the following NOE cross peaks Cys65 Hβ / Cys68 Hβ , Cys65 Hβ / His U 80 Hβ, and Cys68 Hβ / His U 83 Hβ indicate that the side chains of these ligand residues are in close spatial arrangement to satisfy zinc metal ion binding. The presence of NOE intra-residue crosspeaks between imidazole Hε with Hδ protons in His U 80 and

	61,62 A number of characteristic inter-residue
	NOEs are also observed in the peptide region encompassing residues 62-75. In addition to NOE
	cross peaks between side chain protons : Phe72 H1 / Cys65 Hβ	6 Hβ /	6 Hα, long
	range NOEs between Phe72 HN and Ala64 Hα, Phe63 HN and Ala64 Hα,	66 Hα	Gly69

HN, and Ile67 HN and Gly69 HN support the presence of a sheet structure. The long range NOEs observed between side chains of the β-sheet region and the oligourea helix/C-terminal tripeptide, such

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AUTHOR INFORMATION

Corresponding Authors *gilmar.salgado@u-bordeaux.fr *g.guichard@iecb.u-bordeaux.fr ORCID Frédéric Rosu : 0000-0003-3674-7539 Jean-Louis Mergny: 0000-0003-3043-8401 Gilmar Salgado: 0000-0002-0296-5979 Gilles Guichard: 0000-0002-2584-7502

Both authors contributed equally to the work.

The authors declare no competing financial interest.

REFERENCES:

(1)


Azlan Awang
email: azlan.awang@telecom-bretagne.eu

Xavier Lagrange
email: xavier.lagrange@telecom-bretagne.eu

David Ros
email: david.ros@telecom-bretagne.eu

A Cross-Layer Medium Access Control and Routing Protocol for Wireless Sensor Networks

Keywords: Cross-Layer Protocol, Medium Access Control, Routing, Wireless Sensor Networks

Many contention-based routing protocols in Wireless Sensor Networks (WSN) proposed so far require that the sensor node knows the location or position of all neighbors in its transmission range in order to forward packets in the geographic direction of the destination. Location awareness, gained by localization techniques such as observing beacon messages each node sends out periodically or with the help of Global Positioning System (GPS), is not practical for reasons of cost (in volume, money and power consumption). Therefore, a novel cross-layer integrated medium access control/routing protocol called RSSI-based Forwarding (RBF), based on a Received Signal Strength Indicator (RSSI) as a routing parameter, is proposed for multi-hop WSN. Without using prior knowledge of nodes' geographical locations and without maintaining neighborhood routing tables, the next-hop node for data-forwarding task is determined at the same time as the contention process among the possible forwarding nodes is solved. For an arriving beacon signal transmitted by the sink, received power levels are computed for each sensor node in the network and these levels are then used as a decision parameter for the nodes to contend for the forwarding task of the data packets. Simulation results are presented to evaluate the sensor nodes' end-to-end delay in transmitting the data packets towards the sink.

I. INTRODUCTION

Wireless Sensor Networks (WSN) greatly extend our ability to monitor and control the physical world in many applications such as search and rescue, disaster relief, vehicle tracking and biological and environmental monitoring. The networked sensors collaborate and aggregate the huge amount of sensed data in an unpredictable environment and condition for extensive periods of time. The possibility of node failure, wireless link failures and node transition into and out of sleep states to conserve energy introduces additional complexity to routing protocols that depend on up-to-date routing or neighborhood tables and makes routing state upkeep difficult. This therefore demands a routing solution that can deliver endto-end traffic to the data sink without knowledge of potentially invalid or dynamic routing and neighborhood tables. In Mobile Ad Hoc Networks (MANET), the protocols that maintain routes to all nodes are categorized as proactive routing protocols and the ones that are based on demand for the data transmission are categorized as reactive routing protocols. In reactive methods, the routes between nodes are determined only when they are explicitly needed to forward packets. The hybrid methods combine proactive and reactive methods to find efficient routes. Reactive methods are similarly referred to as "state-free" routing protocols in [START_REF] Dazhi Chen | On the Forwarding Area of Contention-Based Geographic Forwarding for Ad Hoc and Sensor Networks[END_REF], [START_REF] Blum | IGF: A Robust State-Free Communication Protocol for Wireless Sensor Networks[END_REF] and [START_REF] Dazhi Chen | A State-Free Data Delivery Protocol for Multihop Wireless Sensor Networks[END_REF]. The "state-free" is defined in [START_REF] Blum | IGF: A Robust State-Free Communication Protocol for Wireless Sensor Networks[END_REF] as having no dependence on knowledge of the network topology or the presence/absence of any other node, including the state of that node, at a particular time. While many of these state-free routing protocols that do not require maintenance of the neighborhood tables have been proposed in the past such as in [START_REF] Füβler | Contention-based forwarding for mobile ad hoc networks[END_REF], [START_REF] Dazhi Chen | On the Forwarding Area of Contention-Based Geographic Forwarding for Ad Hoc and Sensor Networks[END_REF], [START_REF] Blum | IGF: A Robust State-Free Communication Protocol for Wireless Sensor Networks[END_REF], [START_REF] Dazhi Chen | A State-Free Data Delivery Protocol for Multihop Wireless Sensor Networks[END_REF] and [START_REF] Zorzi | Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Multihop Performance[END_REF], however, these protocols assume knowledge of nodes' geographical locations as an important parameter for routing the sensed data towards the intended destination.

Location awareness is inherently one of the most essential parameters in these protocols and it is gained by localization techniques such as the help of a Global Positioning System (GPS). In WSN, nodes are densely deployed in a region of interest leverage their collaborative efforts to perform sensing, communication and processing tasks in a large quantity with low-cost, low-size and low-power consumption [START_REF] Akyldiz | Wireless Sensor Networks: a survey[END_REF], therefore, equipping a GPS receiver on every sensor node is not practical for reasons of cost (in volume, money and power consumption). In fact, in the past several years, many location discovery protocols have been proposed to reduce or completely remove the dependence on GPS in wireless sensor networks [START_REF] Liu | Detecting Malicious Beacon Nodes for Secure Location Discovery in Wireless Sensor Networks[END_REF], [START_REF] Bulusu | GPS-less low cost outdoor localization for very small devices[END_REF], [START_REF] He | Range-free localization schemes in large scale sensor networks[END_REF], [START_REF] Nasipuri | A directionality based location discovery scheme for wireless sensor networks[END_REF] and [START_REF] Savvides | Dynamic fine-grained localization in ad-hoc networks of sensors[END_REF].

In [START_REF] Füβler | Contention-based forwarding for mobile ad hoc networks[END_REF], Contention-Based Forwarding (CBF) is proposed for MANET, where the next-hop node is selected through a distributed contention process based on the actual positions of the nodes at the time a packet is forwarded. The CBF scheme consists of two parts: i) the selection of the next-hop node by means of contention; ii) the suppression to reduce the chance of selecting more than one nodes by some suppression methods such as using timer-based contention (biased timers), area-based suppression and active selection by using a combination of Request to Forward (RTF)/Clear to Forward (CTF) control messages with the timer as in the basic suppression scheme. The CBF, however, requires nodes accurate positions information for forwarding the data towards the sink.

In [START_REF] Dazhi Chen | On the Forwarding Area of Contention-Based Geographic Forwarding for Ad Hoc and Sensor Networks[END_REF], a Contention-based Geographic Forwarding (CGF) is proposed with a study of the fundamental problem in defining the forwarding areas: i) Maximum Forwarding Area (MFA); ii) Maximum Communication Area (MCA) and iii) 60-Degree Radian Area (DRA). The performance of the CGF by using the average single-hop packet progress is evaluated with different forwarding areas but the scheme has a disadvantage in which it cannot be well exploited under low nodal density which causes more serious network partition and more packet losses.

Implicit Geographic Forwarding (IGF) [START_REF] Blum | IGF: A Robust State-Free Communication Protocol for Wireless Sensor Networks[END_REF] assumes high node density and location awareness characteristics. Some energy consideration is proposed in the election of next-hop node to ensure energy depletion among the nodes occurs in a uniform manner. Being a state-free protocol, IGF assumes nodes have knowledge of their location (and optionally their remaining energy) to make non-deterministic forwarding decisions when routing point-to-point traffic. The sender, destination and receiver locations, however, are assumed to be available either using GPS or some distributed localization protocol.

Geographic Random Forwarding (GeRaF) [START_REF] Zorzi | Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Multihop Performance[END_REF] is proposed in which it also assumes knowledge of the nodes' geographical locations and random selection of the relaying nodes via contention among receivers.

A state-free competition-based data delivery protocol called State-free Implicit Forwarding (SIF) [START_REF] Dazhi Chen | A State-Free Data Delivery Protocol for Multihop Wireless Sensor Networks[END_REF] utilizes the distanceto-sink awareness for multi-hop wireless sensor networks. Similar to GeRaF [START_REF] Zorzi | Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Multihop Performance[END_REF] and IGF [START_REF] Blum | IGF: A Robust State-Free Communication Protocol for Wireless Sensor Networks[END_REF], SIF is also based on geographical location of the nodes and selection of the forwarding node via competition among receivers.

A cross-layer module (XLM) is proposed in [START_REF] Akyildiz | A Cross-layer Protocol for Wireless Sensor Networks[END_REF] that incorporates initiative determination, received based contention, local congestion control, and distributed duty cycle operation. Decision is made whether a node should participate in a communication when the conditions of RTS threshold, local congestion control threshold and remaining energy threshold are satisfied but also uses location as a parameter that determines the routing level of each node that makes progress of forwarding the packets.

The basic Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) MAC, as proposed for the sensor networks, provides carrier sensing prior to message transmission. Issues arise such as hidden terminal problem with current transmissions are addressed by using the Distributed Coordination Function (DCF) in IEEE 802.11 four-way RTS-CTS-DATA-ACK handshake when transmitting a Unicast packet. Network Allocation Vector (NAV) timers are used to monitor the expected channel occupancy during transmission and exponential backoff window is used to handle contention.

In this work, we propose an integrated medium access control/routing protocol that does not require nodes to maintain neighborhood state information and location awareness. RBF has some similarities with the schemes proposed in XLM, IGF and SIF as follows: i) selection of forwarding node via competition among receivers; ii) uses a four-way RTS-CTS-DATA-ACK handshake; iii) a node broadcasts an RTS packet to all its neighbors when it has a data packet to send. However, comparing with XLM, RBF has some differences as follows: i) XLM implements an initiative determination based on thresholds of received RTS's signal to noise ratio (SNR), buffer size and energy remaining in which a node will participate in the contention process if the conditions are satisfied; ii) XLM assumes a node knows the locations; the RTS frame contains source and destination locations information; iii) XLM implements a backoff scheme that differentiate nodes into different prioritization groups. In contrast, RBF does not use initiative determination based on threshold values for the RTS, buffer and energy remaining and it does not assume nodes to have knowledge of their locations. Instead, we use a received power of a beacon signal from the sink to decide whether a node should participate in the contention process. A next-hop node is selected for the forwarding task after the potential next-hop nodes, having larger RSSI values compared to the transmitter node wins in the contention process. This competition-based approach among the potential receiver nodes eliminates the need to select the next-hop forwarding sensor at the sender or to find a path toward the sink before the actual data transmission. It is noted that the usage of RTS/CTS mechanism helps to protect the network from hidden terminal problem [START_REF] Hou | Transmission range control in multihop packet radio networks[END_REF]. It is also very effective in terms of system performance, especially when large packets are considered, as it reduces the length of the frames involved in the contention process [START_REF] Bianchi | Performance Analysis of the IEEE 802.11 Distributed Coordination Function[END_REF].

The remainder of this paper is structured as follows: In section 2, we give a detailed description of the protocol. Section 3 presents the simulations results and provides an analysis of the data collected. Finally, in section 4, we conclude this paper with a summary of our findings and future works.

II. PROTOCOL DESCRIPTION

A. Background and Assumptions

We consider a wireless data collection network model with a large number of sensors and one sink. Each of the sensor nodes in the network is assumed to have a limited transmission power, and consequently limited transmission range, and therefore the data packets will be relayed towards the sink using multi-hop communication. The sink regularly transmits a beacon frame and we assume the transmission power of the sink is high enough to reach all sensors in the network. For an arriving beacon frame, each node measures the received power level of the beacon signal. Each node maintains and stores the RSSI value. We consider in this work one data sink. Extension for multiple sinks will be considered in the future works.

A basic assumption of the protocol is that the path loss is an increasing function of the distance. Because of the shadowing effect, this is not strictly true. This cannot be assumed in indoor environment. In this preliminary study, no shadowing and no fading is considered. The best use of this protocol is then for an outdoor environment. To cope with radio strength instability, RSSI level for each node is measured based on mean power received when the sink transmits regularly the beacon signals. Node's mobility does not prevent the protocol from being functioning properly since new measurements of RSSI can always be refreshed based on the regularly received beacon signals.

B. RBF Protocol

RBF protocol uses the same mechanism of the four-way RTS-CTS-DATA-ACK handshake as proposed in some schemes like XLM, SIF and IGF. Some of the key features of RBF are highlighted in Table I. It differs from SIF which assumes distance-to-sink information is available by some methods like pre-configuration for stationary sensors and sinks, GPS and other localization algorithms. When a node has some data to transmit, it broadcasts an RTS frame to all its neighbors. The RTS frame includes the RSSI value stored by the node (i.e., the power level of the received beacon signal). Other nodes that receive the RTS frame read the RSSI value and compare it with their RSSI levels. If their RSSI values are higher than the RSSI value in the RTS frame, which infer they are closer to the sink, they then participate in the contention process by choosing a random time slots within a contention window size. A winning node that has the earliest timeout will respond with a CTS frame, establishing itself as the only nexthop node. Other nodes stop contending when they hear the CTS frame. Several nodes may decide to transmit a CTS frame at the same time. If there is a CTS collision, RTS transmission is repeated. Finally, a normal DATA and ACK exchange follows between the two specific nodes. The process is repeated over multi-hop communications until the data is delivered to the sink.

C. Frame Exchange Sequence

In Fig. 1, as an example, an event occurs in the environment and triggers a data transmission by node 1. If the medium is determined to be idle for a period of Distributed Interframe Spacing (DIFS) time and its NAV is equal to zero, node 1 broadcasts an RTS frame to all its neighbors. The structure of an RTS frame is given in Fig. 2. A CTS_Wait timer is set in node 1 to wait for a CTS frame response from potential nexthop nodes that will be competing in the contention process. The sensor nodes that receive the RTS frame such as nodes 2, 3, 4 and 41 in Fig. 1 then compare their RSSI levels with node 1's RSSI value. In this figure, nodes 2 and 3 are assumed to have slightly higher received power levels than node 1, and hence they participate in the contention process. Nodes 2, 3 and 4 independently sets a CTS_Response timer, defines as a corresponding amount of time that must elapse before replying a CTS frame to node 1 as shown in Fig. 3. The amount of time that must elapse for each of these next-hop nodes depends on the random timeslots chosen between 0 and a fixed maximum contention window size ( € CW max ), as illustrated in Fig. 4, i.e., € t 2 , € t 3 and € t 4 respectively. The sensor node with the earliest timeout (in this example, node 4) responds to node 1 with a CTS frame, establishing itself as the only next-hop node. Other nodes hearing the CTS frame stop contending and update their NAV values.

The amount of time set for the CTS_Wait timer corresponds to a maximum time allowed to send the CTS response, that is, the maximum time of the contention window ( € CW max ). If the CTS_Wait timer expires without getting any expected CTS frame response, node 1 then performs backoff and re-transmits an RTS frame. For each RTS frame re-transmission, a counter that counts the number of RTS frame re-transmission, i.e., short_retry_count is increased by one. RTS frame retransmission is allowed if the value of short_retry_count is less than or equal to a maximum threshold, short_retry_limit.

After receiving a CTS frame from node 4, node 1 then sends the DATA frame to node 4 and set the ACK_Wait timer to wait for the ACK frame response. The ACK_Wait here is set to be equal to short interframe spacing (SIFS) time, sifs_time. After successful DATA frame transmission, node 4 sends an ACK frame to node 1. If, on the other hand, ACK frame is not received within the ACK_Wait timeout, node 1 assumes that frame lost has occurred and DATA frame will be re-transmitted. For each DATA frame re-transmission, a counter that counts the number of DATA frame retransmission, i.e., long_retry_count is increased by one. DATA frame re-transmission is allowed when the value of this counter is less than or equal to a maximum threshold, long_retry_limit. The medium access control/routing process described above is repeated until the DATA frame is progressively delivered to the sink. When setting the CTS_Response timer, we must not allow the timer ( € CW max * slot_time) to be more than DIFS value to ensure that other nodes waiting to transmit will not interfere with RTS frames that will cancel current CTS timers. Since an RTS frame does not contain an absolute duration of transmission (i.e., the waiting time of a next-hop node that will respond a CTS frame is unknown at this time), NAVs are set at the minimum time required for communication [i.e., Transmission time of (CTS+DATA+ACK) frames + 3 * sifs_time + € CW max *slot_time]. When node 4 replies with a CTS frame, the CTS_Response time of node 4 is known and the subsequent frames (CTS, DATA, ACK) then allow the NAV value to be updated reflecting more accurate transmission duration. To avoid multiple CTS responses, every forwarding candidate monitors the channel for any transmission during their waiting time. Whenever a CTS frame is heard, other nodes are aware that another sensor with an earlier timeout has sent out its CTS reply. They will cancel their CTS response timers and update their NAVs. The nodes that hear the CTS frame stop contending and remains silent as long as the duration of the NAVs for this transmitter-receiver pair. If a node which participates in the contention process detects the transmission of DATA by node 1 before the end of the contention window, it cancels its CTS_Response timer and updates the NAV.

In the case of several nodes sending CTS frames without hearing each other, possible techniques can be employed to avoid or resolve the CTS collision. It is also possible in the RTS re-transmission to indicate a CTS collision has occurred and subsequently inform the potential forwarding nodes to increase their transmission power when they reply with the CTS frame. Other possible technique to reduce the CTS collision is by adjusting the contention window size to a larger value so that chances of node to choose same or close timeslots are reduced but this introduces a trade off with endto-end latency.

D. Handling Void

Void is defined as the event when no next-hop forwarding sensor is available. This problem is also termed as holes or local minimum phenomenon in the literature [START_REF] Fang | Locating and Bypassing Routing Holes in Sensor Networks[END_REF].

Voids can still occur but the probability is quite low in our model that has the distribution and node's density as in Fig. 5. Observing that voids could be the result of an absent or temporarily unavailable sensor, the transmitter node should retransmit a RTS up to a threshold value, short_retry_limit, which is a protocol parameter that needs to be tuned. After that, the transmitter node can declare the absence of forwarding candidates if no CTS response is received. Possible technique that can be employed to handle voids is by increasing the transmission power of the transmitter node until at least a forwarding sensor is found. To assess the performance of the RBF protocol, a simulation scenario was designed using OPNET® Modeler [17]. We assume that the WSN is deployed within a circular … area of a radius of 140 m. A total of 112 sensor nodes are distributed uniformly on the seven circular rings within the area as in Fig. 5. The sink is placed at the center of the area. We note that the topology is meant for this particular study, and the nodes distribution will be deployed in random fashion for our subsequent study as in real life implementation. We suppose a transmitted signal fades according to classical propagation law in 1/r γ , where r is the transmission distance and γ is the radio frequency (RF) attenuation exponent. Parameters are chosen in accordance with ITU-R P.1238-1 recommendation document [18] that proposes propagation law for wireless personal area networks. Table II shows the parameters used in the simulation. As an illustration, the received power levels of the transmitted beacon signals for each ring are plotted in Fig. 6.

III. SIMULATION RESULTS

A. System Parameter

B. Simulation Results

We present simulation results for a sensor topology as in Fig. 5 by evaluating the end-to-end latency between the sensor nodes and the sink. The end-to-end latency refers to the amount of time elapsed when a source node generates a data packet and until the data packet is delivered to the sink. In XLM [START_REF] Akyildiz | A Cross-layer Protocol for Wireless Sensor Networks[END_REF], with a sensor topology of 300 nodes, it considered the simulation based on event that occurs within an event radius of 20 m. In SIF [START_REF] Dazhi Chen | A State-Free Data Delivery Protocol for Multihop Wireless Sensor Networks[END_REF], with two sensing fields of 50 and 75 sensors, it considered in each simulation run, only 3 sensors sending packets at a fixed rate to the sink. We considered a large number of sensors sending packets to the sink, i.e., all nodes on each ring at one time. In each simulation scenario, we let all nodes on each ring (at one time) generate data packets and perform the RTS/CTS frame exchanges before transmitting the data packets towards the sink. For each scenario, the simulation was performed for five runs with five different random seeds. The average end-to-end latencies, standard deviation, variance, 95% confidence interval (CI) lower limit and upper limit are tabulated in Table III (for nodes on ring 7, 6, 5 and 4) and Table IV (for nodes on ring 3, 2 and 1). As an illustration, Fig. 7 gives the end-to-end latencies for one simulation run performed for all the seven scenarios.

We considered a transmit power of 8.45 dBm for the sensors to let more nodes participate in the contention process for replying a CTS frame. With this power and path loss as in [18], a sensor node can reach its neighbors within a radius of 42 m, i.e., in the vicinity of 2 hops away. Nodes on ring 1 can reach the sink directly and the end-to-end latency is shown to be constant and smallest as expected. When the sink replies to the sensors with CTS/ACK frames, its transmit power is adjusted to be 8.45 dBm in order to avoid other nodes in the network from overhearing the frames which may deplete some of its energy.

For the nodes located on the outer rings that are multi-hops away from the sink, traversing through the inner rings introduce more delays when the sensors perform the contention, retransmission or defer when the medium is not idle. As indicated in the table, nodes on ring 7 which are seven hops away from the sink have the average end-to-latency of 146 ms in order to deliver data towards the sink.

Comparing to some previous works for MAC/Routing protocol that propose a sleep mode to save energy [START_REF] Akyildiz | A Cross-layer Protocol for Wireless Sensor Networks[END_REF], the average end-to-end latency is in the order of 2 to 7 s. In this protocol, during a sleep mode, the sensor cannot sense or transmit information. With many nodes in sleep mode, the end-to-end latency increases due to retransmissions when the sender cannot find any neighbors. The protocols are more suitable for a monitoring application but not for an eventdriven WSN. Our research work is meant for an event-driven WSN, whereby only some sensors need to send data when event occurs in the environment. Data aggregation technique among the sensors that sense similar events leads to a less number of nodes to transmit if the information is correlated with the transmitting source nodes.

IV. CONCLUSION

In this paper, we have proposed the RBF protocol, which combines the tasks of MAC and routing via cross-layer design, to deliver sensing data from sensor nodes to the sink. Our solution uses RSSI as a parameter for the receiver-based contentions among the next-hop nodes without requirement of global or local state maintenance of the routing tables. In addition, knowledge of the geographical locations of the sensor nodes is not required, and thus eliminating the costly techniques to determine the sensor nodes' locations. Latency has been considered as an important indicator to analyze the effectiveness of the protocol in this event-driven WSN, and the protocol has been shown to have low latency and robust data delivery. As for the future works, we would like to test the protocol with random network topology and improve the protocol by considering enhancements such as refining the approach so that node closer to the sink should have a higher probability of being picked-up as a next-hop node to forward the data. Energy efficiency technique will be considered such that nodes' remaining energy levels are taken into account when they participate in the contention process so that the energy consumptions are evenly distributed. Other possible future research works include the study of radio propagation shadowing effects to the protocol and how to alleviate the congestion among the nodes close to the sink or fairly spread the loads among the nodes.

Fig. 3 .

 3 Fig.3. Frame Exchange Sequence.

Fig. 4 .

 4 Fig. 4. Nodes random CTS_Response time.

Fig. 5 .

 5 Fig. 5. Topology of 112 sensor nodes and 1 Sink.

Fig. 6 .

 6 Fig. 6. RSSI (dBm) for nodes on each ring.

Fig. 7 .

 7 Fig. 7. End-to-end Latency (s) for data delivery to the sink for sensor nodes on ring 1, ring 2, ring 3, ring 4, ring 5, ring 6 and ring 7. Packet generation rate of 10 packets/s and Exponential Inter-arrival time with mean of 10 s.

TABLE III AVERAGE

 III END-TO-END LATENCY (SECOND) FOR NODES ON RING 7, RING 6, RING 5 AND RING 4 FOR A LOAD OF 10 PACKETS/S

		Ring 7	Ring 6	Ring 5	Ring 4
	Mean	1.46 x 10 -1	1.26 x 10 -1	9.40 x 10 -2	6.89 x 10 -2
	Latency (s)
	for 5 runs
	Standard	7.34 x 10 -3	1.74 x 10 -2	8.70 x 10 -3	2.33 x 10 -3
	Deviation
	Variance	5.39 x 10 -5	3.01 x 10 -4	7.56 x 10 -5	5.43 x 10 -6
	95% CI	1.37 x 10 -1	1.04 x 10 -1	8.32 x 10 -2	6.61 x 10 -2
	Lower Limit
	95% CI	1.55 x 10 -1	1.47 x 10 -1	1.05 x 10 -1	7.18 x 10 -2
	Upper Limit

TABLE IV AVERAGE

 IV END-TO-END LATENCY (SECOND) FOR NODES ON RING 3, RING 2 AND RING 1 FOR A LOAD OF 10 PACKETS/S

		Ring 3	Ring 2	Ring 1
	Mean	4.02 x 10 -2	3.13 x 10 -3	2.41 x 10 -3
	Latency (s)
	for 5 runs
	Standard	1.58 x 10 -3	5.65 x 10 -4	2.91 x 10 -11
	Deviation