Agustin Zavala

Pascal Retailleau

Eddy Elisée

Bogdan I Iorga
email: bogdan.iorga@cnrs.fr

Thierry Naas
email: thierry.naas@aphp.fr

Genetic, biochemical and structural characterization of CMY-136 b-lactamase, a peculiar CMY-2 variant

Keywords: beta-lactamase, crystal structure, docking, molecular dynamics, antibiotic resistance, CMY-2, cephalosporinase, ESAC, CAZ, TIC, Ω-loop

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With the widespread use and abuse of antibiotics for the past decades, antimicrobial resistance poses a serious threat to public health nowadays. β-Lactams are the most used antibiotics, and βlactamases the most widespread resistance mechanism. Class C β-lactamases, also known as cephalosporinases, usually do not hydrolyse the latest and most potent β-lactams, expanded spectrum cephalosporins and carbapenems. However, the recent emergence of extended-spectrum AmpC cephalosporinases, their resistance to inhibition by classic β-lactamase inhibitors, and the fact that they can contribute to carbapenem resistance when paired with impermeability mechanisms, means that these enzymes may still prove worrisome in the future. Here we report and characterize the CMY-136 β-lactamase, a Y221H point mutant derivative of CMY-2. CMY-136 confers an increased level of resistance to ticarcillin, cefuroxime, cefotaxime and ceftolozane/tazobactam. It is also capable of hydrolysing ticarcillin and cloxacillin, which act as inhibitors of CMY-2. X-ray crystallography and modelling experiments suggest that the hydrolytic profile alterations seem to be the result of an increased flexibility and altered conformation of the Ω-loop, caused by the Y221H mutation.

inhibition by clavulanic acid. Performing susceptibility testing on cloxacillin containing plates restored susceptibility to ticarcillin and expanded spectrum cephalosporins, suggesting a class C enzyme. PCR was positive for CMY-2, and sequencing revealed a novel CMY-2-like variant, which was assigned the name CMY-136, differing by a single amino acid substitution, Y221H, in a highly conserved position in class C β-lactamases [START_REF] Naas | Beta-Lactamase Database (BLDB) -Structure and Function[END_REF] . The sequence alignment between CMY-2 and CMY-136 is shown in Fig. S1.

Phenotypical characterization of CMY-136

The antimicrobial susceptibility profile conferred by CMY-136 was compared to that of CMY-2 by transforming E. coli TOP10 cells with a pTOPO plasmid harbouring either blaCMY-2 or blaCMY-136 genes and performing disk diffusion susceptibility tests and MICs assays. CMY-2 and CMY-136 show similar resistance profiles, they both confer resistance to penicillins and cephalosporins, and show susceptibility to cefepime and carbapenems (see Fig. S2 for the chemical structures of these β-lactams). Based on the disk diffusion test, when compared to CMY-2, CMY-136 confers increased resistance to ticarcillin and cefotaxime, low level resistance to cefoxitin, and shows increased susceptibility to inhibition by clavulanic acid. The MICs show that when compared to CMY-2, CMY-136 confers to E. coli decreased resistance to piperacillin and cefoxitin, and an increased level of resistance to ticarcillin, cefuroxime and cefotaxime (Table 1). According to the breakpoints of EUCAST, E. coli TOP10 expressing CMY-136 is also resistant to ceftolozane/tazobactam, whereas under the same conditions CMY-2 confers no resistance to it.

Genetic support of blaCMY-136 gene

Kieser [START_REF] Kieser | Factors Affecting the Isolation of CCC DNA from Streptomyces Lividans and Escherichia Coli[END_REF] extracted DNA from E. coli EC13 was electroporated into electrocompetent E. coli TOP10 cells and plated on ampicillin-containing plates (100 mg/L). Several colonies that grew on ampicillin were confirmed by PCR and sequencing to be blaCMY-136 positive. Kieser DNA of E. coli EC13 and of electrotransformed E. coli TOP10 cells run on a 0.7% agarose gel revealed a single plasmid, pCMY-136 of ca. 90 Kbp in both isolates. Whole genome sequencing using Illumina technology of E. coli TOP10 (pCMY-136) revealed a 90844 bp plasmid in size, that belonged to the IncI1 group, and carried a single antibiotic resistance gene, blaCMY-136. BLAST search showed the closest deposited plasmid sequence to be the blaCMY-2 carrying plasmid pCVM22462 (accession number CP009566.1) [START_REF] Cao | Complete Sequences of Six IncA/C Plasmids of Multidrug-Resistant Salmonella Enterica Subsp. Enterica Serotype Newport[END_REF] , isolated from a Salmonella enterica strain. It is 99.98% identical to pCMY-136, excluding a 3,888-bp fragment that is absent in pCMY-136. This deletion is located 1,965-bp upstream of blaCMY-136/blaCMY-2 genes. This 3,888-bp fragment contains 3 hypothetical protein ORFs and occurred contiguously downstream of an IS1294-like insertion sequence present on both plasmids.

Purification and biochemical characterization of CMY-136

CMY-136 and CMY-2 were overexpressed and purified by Immobilized Metal Affinity Chromatography (IMAC), and purity of both enzymes was confirmed by SDS-PAGE, where a single band of ca. 41 kDa was observed. Steady-state kinetic parameters were determined to compare the catalytic activity of CMY-136 to that of CMY-2 against several β-lactams (Table 2). CMY-136 showed around a 10-fold increase in Km for most β-lactams assayed, with however, a few exceptions: (i) cephalothin (CEF), which showed a slightly higher affinity for CMY-136 than CMY-2, although other authors have reported a lower Km for CMY-2 against CEF [START_REF] Kotsakis | Increased Hydrolysis of Oximino-β-Lactams by CMY-107, a Tyr199Cys Mutant Form of CMY-2 Produced by Escherichia Coli[END_REF][START_REF] Endimiani | Enhancing Resistance to Cephalosporins in Class C Beta-Lactamases: Impact of Gly214Glu in CMY-2[END_REF][START_REF] Bauvois | Kinetic Properties of Four Plasmid-Mediated AmpC Beta-Lactamases[END_REF] ; (ii) cefoxitin (FOX), which showed a practically identical Km for both enzymes; (iii) β-lactams with a very high affinity for CMY-2 and a bulky, non-linear, R1 substituent, namely cefuroxime (CXM), cefotaxime (CTX) and ceftazidime (CAZ), which show a 10 3 -10 4 -fold increase in Km for CMY-136; (iv) other β-lactams, namely ticarcillin (TIC) and cloxacillin (CLX), for which CMY-2 shows high affinity and no hydrolysis unlike CMY-136 that does hydrolyze them (see Fig. S2 for the meaning of the R1 and R2 substituents).

CMY-136 showed a decreased kcat for most of the preferred substrates of CMY-2, namely amino-penicillins and first generation cephalosporins, and also cefoxitin. However, it also shows an increased kcat for cefepime and ceftolozane, and a remarkably increased kcat (10 2 -10 3 -fold) for those β-lactams for which the most dramatic Km increase was also seen, CAZ, CTX, CXM. CMY-136 is also capable of hydrolysing cloxacillin and ticarcillin, which are not hydrolysed by CMY-2. In terms of their catalytic efficiency, all these translate into CMY-136 showing a lower efficiency than CMY-2 for most β-lactams tested, except for those not hydrolysed by CMY-2, TIC and CLX, and also ceftolozane.

CMY-136 crystallization and X-ray crystallography

CMY-136 crystallized in 0.1 M HEPES pH 7.5; 20% w/v PEG4000; 10% isopropanol. The structure was determined by molecular replacement using the deposited CMY-2 structure (PDB: 1ZC2) as a template, and the model was refined to 1.60 Å (Table 4). R/Rfree values seem to be relatively high for the resolution obtained, which may be a consequence of merging two datasets (see experimental procedures). The asymmetric unit contains two protein chains, A and B, showing no significant conformational differences between them. They have been modelled with 359 residues each, with clear electron density observed for all regions of the protein. Several ordered water molecules have been modelled in the structure as well as phosphate anions and isopropyl alcohol molecules, from the crystallization condition. Both chains present the typical class C fold with an α-helical region and a mixed α-helix/β-sheet region. 99% of all residues are inside the favoured regions of the Ramachandran plot, and 1% in the allowed regions. 1.04 Values in parenthesis correspond to the higher resolution bin. CMY-136 shows the same overall conformation as CMY-2, and 3D alignment reveals a Cα RMSD of 0.465-0.486 Å between them. Several structural differences can be found when comparing CMY-136 (Fig. 1) to CMY-2: (i) A phosphate molecule is positioned inside the active site of both CMY-136 chains, with one of its oxygens buried inside the oxyanion hole. CMY-2 was crystallized with a citrate molecule inside the active site; (ii) The conformation adopted by the TYR221 in CMY-2, which interacts with the backbone of the Ω-loop at SER212 O and GLN215 O via two bridging waters, is different from the conformation found in CMY-136 for HIS221, whose sidechain invades the active site cavity, hydrogen bonding the aforementioned phosphate oxygen atom. The TYR221 residue and its conformation are highly conserved in all class C enzymes reported to date (with the exception of PDC-85) and in all class C crystallographic structures deposited in the PDB that have a consensus length Ω-loop; (iii) In turn, the sidechain of ASP217 turns towards the interior of the Ωloop to partially occupy the space left by the conformational change of the Y221H mutation; (iv)

The conformation adopted by the backbone of the Ω-loop residues ARG204 to GLN215 in CMY-136 is different from the one found in CMY-2, that is also highly conserved in deposited class C structures with a consensus length loop, which translates into a backbone atoms RMSD between said residues in both crystal structures of 2.176 -2.219 Å, a 4.56 -4.68 Å displacement in the position of the Cα of VAL211, and the loss of the hydrogen bonds between GLU61 Oε and VAL211 N (Fig. 2) and between VAL209 O and GLY202 N (Fig. 2B). Two water molecules, w502 and w504,occupy the usual space of residues V209-V211 backbone, and partially replace those lost hydrogen bonds (Fig. 2B); (v)The configuration of HIS210 sidechain is shifted from being positioned between, and interacting via pi-pi stacking with, TYR199 and TRP201 in CMY-2another highly conserved feature of class C structures, that fill this space with either HIS210 or ARG210 sidechains -to not directly interacting with any other residue, and hydrogen bonding w502 (Fig. 2B). The space between TYR199 and TRP201 in the CMY-136 structure is filled by LYS290 from another CMY-136 chain in the neighbouring asymmetric unit in the crystal structure; (vi) The conformation of the active site cavity residues and the hydrogen bond network between them is 10 highly conserved, with the exception of TYR150, which is slightly shifted towards the phosphate anchored in the active site, with a 3.1 Å displacement of its hydroxyl oxygen atom compared to TYR150 of the CMY-2 structure (Fig. 1 and Fig. S3). A water molecule can be found occupying this position, and TYR150 is still hydrogen bonding LYS67, and now also hydrogen bonds with the phosphate molecule and possibly ASN152, but no longer interacts with LYS315.

Modelling of covalent complexes of CMY-2 and CMY-136 with β-lactams

As no crystal structure of CMY-2 co-crystallized with β-lactams is available, covalent complexes of CMY-2 and CMY-136 with ceftazidime, cefotaxime and cefuroxime were created by superposing the structures of CMY-2 and CMY-136 with the available structures of class C enzymes with ceftazidime (PDB code 1IEL) and cefotaxime (PDB code 4KG2), and in the case of cefuroxime, the covalently bound substrate was modelled on the conformation of the cefotaxime complex, given no covalent complex of class C enzymes with cefuroxime is available and both molecules show minor differences. Results show that in the case of CMY-2, acyl-enzyme complexes have minor clashes with L293 (Fig. 3A). In the case of CMY-136 numerous overlaps with residues H221 and Y150 exist (Fig. 3C), which may explain the approximately 1000-fold increase in Km values for expanded spectrum cephalosporins for CMY-136 compared to CMY-2. Covalent complexes were then subjected to energy minimization steps, and results showed the conformational changes needed to resolve overlaps in the case of CMY-2 were smaller than those for CMY-136 (Fig. 3B andD, respectively). Both H221 and the R1 substituent of cephalosporins are displaced in opposite directions in the CMY-136 complexes, pushing the substrate outwards from the active site cavity and H221 towards the Ω-loop. In the case of CMY-2, displacements were smaller in magnitude, and they tended to approach the R1 substituent towards Y221 (see Fig. S2 for the meaning of the R1 substituent).

Molecular dynamics simulations of CMY-2 and CMY-136

To investigate the role of the Y221 mutation on the dynamics of the protein structure, 10 ns molecular dynamics (MD) simulations were performed in triplicate with four different systems (Fig. S4): CMY-2, CMY-136, CMY-136 with the Ω-loop modelled on the CMY-2 structure, and CMY-2 with the Ω-loop modelled on the CMY-136 structure. For these MD simulations, citrate and phosphate ions were removed from the active sites of CMY-2 and CMY-136 structures, respectively. Root-mean-square deviation (RMSD) analysis of the trajectories reveals that the simulations reached stability within 2 ns and remained stable after that. Root-mean-square fluctuation (RMSF) analysis of Cα atoms in CMY-2 and CMY-136, expressed as B-factors, reveals some differences between them, regarding the flexibility of several parts of the structure (Fig. 4A).

CMY-136 displays increased flexibility in the Ω-loop and H7 helix, from R204 up to H221, except for a short segment in the middle. An increased flexibility can also be found for part of the Q120 loop, part of H10 and H11 helixes, and the C terminus of B3 strand, S318 and T319. Other loops around CMY-136 also have increased flexibility compared to CMY-2, to a lesser extent. There are also segments of decreased flexibility towards the exterior of the structure, contiguous to the previously described regions, the N-terminus of H10 helix and its preceding loop, C-terminus of H11 helix, H4 helix, G320, part of helixes H5 and H6, directly behind H4 helix in the tertiary structure, and also S343, next to the C-terminus of strand B3. It should be noted that R349, in the middle of H11, also shows decreased flexibility. Regions with increased flexibility can be found surrounding and forming the walls of the active site cavity, with regions of decreased flexibility further away (Fig. 4B). The MD simulations also demonstrate how the sidechain of Y221 in CMY-2 remains constantly in the same conformation, pointing outwards of S64, with its hydroxyl hydrogen bonding with the backbone of the Ω-loop directly or through bridging waters (Fig. 5A). In contrast, H221 in CMY-136 displays much more flexibility, adopting several conformations in the active site throughout the MD simulation (Fig. 5B and6). Other parts of the Ω-loop also show increased sidechain flexibility (Fig. 6), namely H210-S212 and Y199-W201, which normally interact closely with each other and with E61. This same H221 flexibility can be observed for the simulation of the CMY-136 model with the Ωloop, H7 and H221 sidechain starting with the same conformation as the CMY-2 crystal structure.

In contrast, for the CMY-2 model with the Ω-loop, H7 and Y221 sidechain starting with the same conformation as the CMY-136 crystal structure, the native conformation of Y221 is not reached.

Simulations for both enzymes starting either with the Ω-loop in the conformation observed in their own crystal structure, or in that of the other enzyme, seem to show that the conformation acquired by the Ω-loop during the simulations is independent of starting conformation. Snapshots of these four simulations were extracted every 1 ns and fitted on the CMY-2 or CMY-136 crystal structure as references. Ω-loop Cα RMSD between the snapshot and the reference was determined, to assess conformational differences (Fig. S5). The analysis shows that both CMY-136 simulations, starting with a Ω-loop, H7 and H221 conformation as that observed in either the CMY-136 crystal structure or the CMY-2 crystal structure, present a lower RMSD compared to CMY-136 than to CMY-2 crystal structures towards the end of the simulation. Similarly, for the CMY-2 simulation starting from the CMY-2 crystal structure conformation, some fluctuations can be observed during the simulation but finally the RMSD is also lower for its own native crystal structure than for that of the other enzyme, and in the same magnitudes as observed for CMY-136. In contrast, in the simulation of CMY-2 starting with the Ω-loop, H7 and Y221 conformation of the CMY-136 loop does not converge to the CMY-2 crystal structure conformation and remains closer to the CMY-136 crystal structure conformation. As mentioned earlier, for this simulation, Y221 does not acquire the native conformation observed in all class C structures.

DISCUSSION

We report here a novel β-lactamase belonging to the CMY-2 family, with an unusual mutation, Y221H, in a highly conserved position in class C β-lactamases. Analysis of the plasmid harbouring blaCMY-136 suggests it may have originated by mutation deriving from the blaCMY-2 harbouring plasmid pCVM22462. It is noteworthy that the 3888bp fragment absent from pCMY-136 but present in pCMY-2 occurs directly adjacent to IS1294, which may suggest its involvement in the deletion of this fragment [START_REF] Kusumoto | Insertion Sequence-Excision Enhancer Removes Transposable Elements from Bacterial Genomes and Induces Various Genomic Deletions[END_REF] .

The biochemical characterization of CMY-136 suggests it to be less efficient than CMY-2 in hydrolysing most β-lactams, the exception being ceftolozane, and also those not hydrolysed by the latter, cloxacillin and ticarcillin. The results for these three β-lactams corroborate what can be observed in the MIC assays. However, other significant differences in MICs for CMY-136 when compared to CMY-2 (increased MIC for cefotaxime and cefuroxime, and decreased MIC for cefoxitin) are not reflected in the catalytic efficiencies determined. In this regard, it has been previously suggested that for class C enzymes, kcat may better represent the degree of resistance towards β-lactams [START_REF] Lefurgy | Analysis of the Structure and Function of FOX-4 Cephamycinase[END_REF][START_REF] Thomas | Structural Bases for Stability-Function Tradeoffs in Antibiotic Resistance[END_REF] . Therefore, the comparison of kcat may explain better what is observed for the MICs. A 10-fold increase in kcat, or bigger, is observed for CMY-136 for cloxacillin, ticarcillin, cefuroxime, cefotaxime, ceftazidime, and ceftolozane, and a 10-fold decrease for cephalothin and cefoxitin. This corresponds well with observed MIC results, except for cloxacillin and cephalothin, for which MICs were not determined, and ceftazidime, which showed no difference in MIC between CMY-136 and CMY-2.

These results for CMY-136 are consistent with previously published results for similar cases. PDC-85, a variant of the chromosomally-encoded AmpC of Pseudomonas aeruginosa, is the only other class C enzyme presenting a Y221H mutation [START_REF] Berrazeg | Mutations in β-Lactamase AmpC Increase Resistance of Pseudomonas Aeruginosa Isolates to Antipseudomonal Cephalosporins[END_REF] . Similarly to CMY-136, the PDC-85 variant showed an increase in MIC for ticarcillin and ceftolozane/tazobactam, and a decreased susceptibility to inhibition by cloxacillin, probably related to CMY-136 being capable of hydrolysing cloxacillin. In a different study, it was observed that the E. coli AmpC Y221G laboratory mutant showed an increased Km and kcat for cefotaxime, while at the same time significantly losing activity on cephalothin [START_REF] Thomas | Structural Bases for Stability-Function Tradeoffs in Antibiotic Resistance[END_REF] . The authors evidenced that this mutation decreases the enzyme thermal stability, increase flexibility, and expand the active site cavity, and attribute the increase in cefotaxime hydrolysis to these effects, allowing for a better accommodation of the acylenzyme complex into a catalytically competent conformation for de-acylation. For cephalothin, they propose the now missing stabilizing interactions between the substrate and the Y221G mutation to be responsible for the loss of hydrolysis.

The crystal structure of CMY-136 shows the same conformation as that of CMY-2, except for those differences described in the Results section. Just as for the Y221G AmpC mutant study, in CMY-136 the space no longer occupied by Y221 is partially occupied by D217, which turns towards the active site cavity. Another possible common feature is the expansion of the active site cavity, as the CMY-136 Ω-loop conformation displaces the V211 Cα from its usual position in class C structures by about 4.6Å. It is unclear whether the changes observed in the CMY-136 conformation are the result of the crystal configuration and interactions between neighbouring chains in it, the crystallization with a phosphate molecule in the active site, the consequences of the Y221H mutation, or a combination of them.

In order to investigate the high differences in affinity for expanded spectrum cephalosporins between CMY-2 and CMY-136, covalent complexes were created by superimposing the structures with available complexes and subjected to energy minimization, to evidence the conformations adopted by the acyl-enzyme complexes. As shown in Fig. 3, minimization does not lead to important conformational changes in the case of CMY-2. Superposition of the CMY-136 crystal structure on the complexes structures shows that there would be significant overlapping between the R1 sidechain of β-lactams and the H221 sidechain. This serves to explain why CMY-136 may show an increased Km for most β-lactams: in order for the β-lactam and the enzyme to interact, either the R1 sidechain or the H221 sidechain, or both, must adopt a different conformation from the one seen in most structures of class C enzymes in complex with substrates or the CMY-136 structure, respectively. Such conformational change most likely implies an energetic cost, that in turn represents an increase in Km. Furthermore, this higher energetic cost -and increase in Km -for CMY-136 interacting with most β-lactams seems to correlate with how big, bulky, ramified or rigid is the R1 substituent. There are much larger increases in Km for cloxacillin, ceftazidime, cefuroxime and cefotaxime than for those with a simpler R1 sidechain like benzylpenicillin or cephalothin. One possible explanation as for why such Km increase is less intense or doesn't exist for CEF or FOX compared to CAZ or CXM, is that the R1 sidechain of the former is not as bulky, ramified, or rigid as for the others, and thus they may prove easier to accommodate inside the active site of CMY-136 with its Y221H mutation, implying less movement restrain for H221, or making more favourable contacts and hydrogen bonds, and thus with a lesser cost in terms of binding energy and Km.

The analysis of MD simulations suggests that the CMY-136 structure may show increased flexibility around the R1 and R2 pockets in the active site. The R2 pocket is usually described as surrounded by the R2 loop (residues 289-307) and the proximal residues of helixes H10 and H11 [START_REF] Jacoby | AmpC Beta-Lactamases[END_REF][START_REF] Powers | Structural and Functional Aspects of Extended-Spectrum AmpC Cephalosporinases[END_REF] , and the R1 pocket is defined ad surrounded by the Ω loop (residues 178-226) [START_REF] Jacoby | AmpC Beta-Lactamases[END_REF][START_REF] Powers | Structural and Functional Aspects of Extended-Spectrum AmpC Cephalosporinases[END_REF] (Fig. S6). The R1 substituent of ceftazidime, and other β-lactams, also interacts with other residues surrounding it, namely Q120, N152, residues 218-220 and S343 (Fig. S6). As previously proposed by other authors [START_REF] Kotsakis | Increased Hydrolysis of Oximino-β-Lactams by CMY-107, a Tyr199Cys Mutant Form of CMY-2 Produced by Escherichia Coli[END_REF][START_REF] Kotsakis | Effects of the Val211Gly Substitution on Molecular Dynamics of the CMY-2 Cephalosporinase: Implications on Hydrolysis of Expanded-Spectrum Cephalosporins[END_REF] , an increased kcat may be a consequence of an increased protein flexibility, that may allow the acyl-enzyme complexes to more often adopt a conformation competent for being attacked by the hydrolytic water and be released. In the case of CMY-136, a change in the Ω-loop conformation, widening the active site cavity by displacing V211, may also participate in the kcat increase observed for certain substrates. As observed by the superposition and RMSD analysis of the MD simulations, the CMY-136 Ω-loop tends to adopt a conformation more similar to the one observed in the CMY-136 structure than to that observed in the CMY-2 structure, regardless of the starting conformation. For CMY-2 starting with the Ω-loop in its native conformation, some fluctuation is observed but finally a conformation more similar to this native one than to the one in CMY-136 crystal structure is adopted. As mentioned earlier, this is not observed for the CMY-2 simulation starting with a CMY-136 Ω-loop conformation. In this simulation the loop remains more flexible and the Y221 sidechain adopts different conformations, as observed in the case of CMY-136. The stability of the native Y221 conformation (conserved in class C structures) in the CMY-2 MD simulation, and the fact that this conformation is not reached in a 10 ns simulation starting from a different conformation, suggests that the native conformation of the Ω-loop of class C enzymes may be quite stable, and a relatively high energetic barrier might have to be overcome to reach, or come out of it. In contrast, H221 in CMY-136 easily adopts several conformations throughout the simulations, starting from either crystal structure conformations (CMY-2 and CMY-136). This in turn may help to explain the experimental data observed, i.e. a flexible H221 would allow CMY-136 to hydrolyse β-lactams in spite of its conformation in the crystal structure. Were H221 to remain in this conformation, CMY-136 would most likely be incapable of interacting with its substrates, especially those with a more rigid, bulkier, ramified R1 sidechain. The fact that H221 can adopt different conformations during the MD simulation, one of them similar to the Y221 conformation in CMY-2, helps to imagine how it may still accommodate the substrates in its active site cavity. On the other hand, this flexibility may also explain the increase in Km observed for most β-lactams. Although H221 seems to be much more flexible than Y221 and may adopt several conformations, once CMY-136 is interacting with the substrate, H221 would probably lose much of its movement freedom. This would imply an energetic cost, and an increase in Km for the reaction.

Such increase in Km would clearly not be observed in the case of CMY-2 or other class C enzymes with Y221 in its native conformation, as it is probably static enough that no movement restrain is imposed on it upon binding of the substrate.

CONCLUSION

CMY-136 is a novel β-lactamase, which belongs to the CMY-2-like family. It possesses a single unusual mutation, Y221H, in a position highly conserved in all class C β-lactamases. We compared here its genetic environment to that of the closest plasmid harbouring CMY-2 and characterized CMY-136 both biochemically and structurally. Finally, in silico modelling techniques suggested a possible structural explanation for the differences observed compared to CMY-2. These results allowed us to better assess the potential of class C β-lactamases for their spectrum extension and for their potential threat to public health. Finally, the identification of the Y221H mutation in a natural variant of CMY-2 and which confers resistance to ceftolozane/tazobactam prior to the use of this latter antibiotic in clinics is worrisome, since it may indicate a more rapid appearance of resistance, as this type of enzyme may be selected.

EXPERIMENTAL PROCEDURES

Bacterial strains

blaCMY-136 was recovered from a urinary tract E. coli isolate EC13 [START_REF] Mammeri | Naturally Occurring Extended-Spectrum Cephalosporinases in Escherichia Coli[END_REF] . blaCMY-2 was recovered from the E. cloacae ec-204 strain (Bicêtre strain collection). E. coli TOP10 (Invitrogen, Saint-Aubin, France) and E. coli BL21 (DE3) (Novagen, VWR International, Fontenay-sous-Bois, France) were used for cloning experiments and protein overproduction, respectively.

Plasmid extraction and cloning

Plasmid DNA from E. coli EC13 was extracted using the Kieser method [START_REF] Kieser | Factors Affecting the Isolation of CCC DNA from Streptomyces Lividans and Escherichia Coli[END_REF] . The Kieser extracted DNA was used to transform E. coli TOP10 strain by electroporation. The electroporants were plated on TSA plate containing ampicillin (100 µg/ml). Transformants were analyzed by PCR using the primers CMY-2A and CMY-2B (5'-aaaaacatatgatgaaaaaatcgttatgctgc-3' and 5'aaaaggatccttattgcagcttttcaagaatgc-3', respectively). From the transformants harbouring blaCMY-2-like genes, plasmid DNA was extracted using Kieser's method and subsequently analysed on a 0.7% agarose gel stained with ethidium bromide. Plasmids of ca. 154, 66, 48, and 7 kb of E. coli NCTC 50192 were used as plasmid size markers [START_REF] Dortet | Genetic and Biochemical Characterization of OXA-405, an OXA-48-Type Extended-Spectrum β-Lactamase without Significant Carbapenemase Activity[END_REF] .

Plasmid sequencing (WGS)

Plasmid DNA was extracted from an E. coli TOP10 clone harbouring the wild type pCMY-136 plasmid using the QIAGEN Plasmid Maxi Kit following the manufacturer's instructions. The DNA concentration and purity were controlled by a Qubit ® 2.0 Fluorometer using the dsDNA HS and/or BR assay kit (Life technologies, Carlsbad, CA, US). The DNA library was prepared using the Nextera XT-v3 kit (Illumina, San Diego, CA, US) according to the manufacturer's instructions and then run on Miseq (Illumina) for generating paired-end 300-bp reads. De novo assembly was performed by CLC Genomics Workbench v9.5.3 (Qiagen, Hilden, Germany) after quality trimming (Qs ≥ 20) with word size 34.

The acquired antimicrobial resistance genes were identified by uploading the assembled plasmid to the Resfinder server v2.

β-Lactamase purification

Overnight cultures of E. coli BL21 (DE3) harbouring either pET41b-cmy-2 or pET41b-cmy-136 recombinant plasmids were used to inoculate 2 L of BHI broth containing 50 mg/L kanamycin.

Bacteria were cultured at 37ºC until reaching an OD of 0.6 at 600 nm, and protein expression was induced overnight at 25ºC with 0.2 mM IPTG. Cultures were then centrifuged at 6000 g for 15 min

and the pellets resuspended with 10 mL of Buffer A (20 mM PBS, 175 mM K2SO4, 40 mM imidazol, pH 7.40). Bacterial cells were disrupted by sonication and protein solution was clarified by centrifugation at 10,000 g for 1 h at 4ºC. The supernatant was then centrifuged at 48,000 g for 1 h at 4ºC. CMY-136 or CMY-2 was purified using a NTA-Nickel pseudo-affinity chromatography column (GE Healthcare, Freiburg, Germany). Elution was performed in a gradient of 0 to 100% Buffer B (20 mM PBS, 175 mM K2SO4, 500 mM imidazol, pH 7.40). Purity was assessed by SDS-PAGE, and pure fractions were pooled and dialyzed against 100 mM sodium phosphate buffer (pH 7.4) 50 mM potassium sulphate and concentrated up to 6.4 mg/ml using Vivaspin® columns (GE Healthcare, Freiburg, Germany). Protein concentration was determined using Bradford Protein assay (Bio-Rad) [START_REF] Bradford | A Rapid and Sensitive Method for the Quantitation of Microgram Quantities of Protein Utilizing the Principle of Protein-Dye Binding[END_REF] . Molecular dynamics simulations of CMY-2 and CMY-136 were performed with Gromacs v4.6 37 using the OPLS-AA force field. 38 The covalent ligands were parametrized using a modified version of our in house MOL2FF tool. Each system was energy-minimized until convergence using a steepest descents algorithm. Molecular dynamics with position restraints for 200 ps was then performed followed by the production run of 10 ns, which was repeated three times to ensure the reproducibility. During the position restraints and production runs, the Parinello-Rahman method was used for pressure coupling, and the temperature was coupled using the Nosé-Hoover method at 300 K. Electrostatics were calculated with the particle mesh Ewald method. The P-LINCS algorithm was used to constrain bond lengths, and a time step of 2 fs was used throughout.

Steady-state kinetic parameters

Nucleotide sequences accession numbers and PDB deposition.

The amino acid sequence of blaCMY-136 gene and the nucleotide sequence of its natural plasmid pCMY-136 have been submitted to the EMBL/Genbank nucleotide sequence database under the accession numbers AVR61040.1 and MG844436.1, respectively. The crystallographic structure of CMY-136 has been deposited to the PDB, accession code 6G9T. Authors will release the atomic coordinates and experimental data upon article publication.

Fig. 1 Fig. 2

 12 Fig. 1 Crystal structure of CMY-136. Active site cavity of CMY-136, with a phosphate molecule

Fig. 3 .

 3 Fig. 3. Modelling of covalent complexes of CMY-2 and CMY-136 with ceftazidime. Covalent

Fig. 4 .

 4 Fig. 4. Altered flexibility of CMY-136 Structure. a) CMY-2 and CMY-136 RMSF analysis,

Fig. 5 .

 5 Fig. 5. Flexibility of TYR 221 in CMY-2 and HIS 221 in CMY-136. A) Snapshot from the CMY-

Fig. 6 .

 6 Fig. 6. Flexibility of Ω-loop in CMY-136 vs CMY-2. Individual atom B-factors of CMY-136 and

  Structure analysis, covalent complexes and molecular dynamics simulationsCMY-136 structure comparison to the previously published CMY-2 structure (PDB code 1ZC2) and analysis of docking results were performed with UCSF Chimera package 37 .Covalent complexes of CMY-2 and CMY-136 with ceftazidime, cefotaxime and cefuroxime were created by superposing the structures of CMY-2 and CMY-136 with the available structures of class C enzymes with ceftazidime (PDB code 1IEL) and cefotaxime (PDB code 4KG2), and modelling cefuroxime on the conformation of cefotaxime. Ligand structures were generated with 3D Structure Generator CORINA Classic (Molecular Networks GmbH, Nuremberg, Germany).

Table 1

 1 MICs for E. coli TOP10 pTOPO-CMY-2 and E. coli TOP10 pTOPO-CMY-136.

	β-lactam	E. coli TOP10 pTOPO-CMY-2 MIC (g/L) CLSI EUCAST	E. coli TOP10 pTOPO-CMY-136 MIC (g/L) CLSI EUCAST
	Amoxicillin	>256	-*	R	>256	-*	R
	Amoxicillin + CLA a	32	R	R	24	I	R
	Ticarcillin	32	-*	R	>256	-*	R
	Temocillin	24	-*	R	24	-*	R
	Piperacillin	24	I	R	12	S	I
	Piperacillin + TAZ b	4	S	S	2	S	S

b TAZ: tazobactam c AVI: avibactam

Table 2

 2 Steady-state kinetic parameters of β-lactamases CMY-136 and CMY-2.

		Km (µM)	kcat (s -1 )		kcat/Km (mM -1 s -1 )
	Substrate	CMY-2 CMY-136 CMY-2 CMY-136 CMY-2	CMY-136
	Benzylpenicillin	0.6 b	10.1*	24 b	7.83	40000 b	775
	Cloxacillin	0.0002*	543	N.H.	0.47	N.H.	0.9
	Ampicillin	0.16 c	3.5*	0.55 c	0.43	3437 c	122

Table 3

 3

	IC50 values (µM) for inhibitors of CMY-136 and CMY-2.
	Inhibitor	CMY-2	CMY-136
	Tazobactam	3.2 a	5.5
	Clavulanic acid	N.D.	137
	Aztreonam	N.D.	0.11
	N.D.: not determined
	a taken from 13

Table 4

 4 Crystallography data collection and refinement statistics.

	Data collection
	Space group	P 1 21 1
	Cell dimensions
	a, b, c (Å)	60.58, 58.09, 100.08
	α, β, γ (°)	90.00, 89.97, 90.00
	Resolution (Å)	16.1-1.60 (1.62-1.60)
	Rmerge	0.092 (0.67)
	I/σ(I)	9.9 (3.9)
	Completeness (%)	95.0 (96.3)
	Redundancy	4.2 (4.4)
	CC (1/2)	0.991 (0.775)
	Refinement
	Resolution range (Å)	16.10-1.60
	No. unique reflections	87,503
	Rwork/Rfree	23.4%/26.4%
	No. non-hydrogen atoms
	Protein	5,642
	Water	396
	Ligand/Ions	67
	Total	6105
	Average B, all atoms (Å2)	19.8
	Protein	19.4
	Water	25.2
	Ligand/Ions	29.6
	Root mean squared deviations
	Bond lengths (Å)	0.01
	Bond angles (°)

  1 (http://cge.cbs.dtu.dk/services/ResFinder-2.1)[START_REF] Zankari | Identification of Acquired Antimicrobial Resistance Genes[END_REF] . Plasmid incompatibility group was obtained by uploading the plasmid sequence to PlasmidFinder server 1.3 (https://cge.cbs.dtu.dk/services/PlasmidFinder/)[START_REF] Carattoli | In Silico Detection and Typing of Plasmids Using PlasmidFinder and Plasmid Multilocus Sequence Typing[END_REF] . //blast.ncbi.nlm.nih.gov/Blast.cgi)[START_REF] Altschul | Basic Local Alignment Search Tool[END_REF] and compared to the best hit using Artemis Comparison Tool[START_REF] Carver | ACT: The Artemis Comparison Tool[END_REF] . Applied Biosystems, Les Ulis, France). The nucleotide sequences were analysed using software available at the National Center for Biotechnology Information website (http://www.ncbi.nlm.nih.gov).

	Plasmid	sequence	was	blasted
	(https:Cloning of blaCMY-136 and blaCMY-2 genes PCR amplification of blaCMY-136 and blaCMY-2 genes was performed using total DNA extraction of E. coli EC13 and Enterobacter cloacae ec-204, and primers CMY-2A (5'-aaaaacatatgatgaaaaaatcgttatgctgc-3') and CMY-2B (5'-aaaaggatccttattgcagcttttcaagaatgc-3'). -2A (5'-aaggagatatacatatgatgaaaaaatcgttatgct-3') and INFcmy-2B (5'-ggtggtggtgctcgaattgcagcttttcaagaatgc-3') and cloned into pET-41b(+) expression vector (Novagen, VWR International, Fontenay-sous-Bois, France) using the NEBuilder® HiFiDNA Assembly Cloning Kit (New England BioLabs®Inc, United Kingdom), following the manufacturer's instructions. Recombinant plasmids pET41b-cmy-136 and pET41b-cmy-2 were electroporated into electrocompetent E. coli BL21 (DE3) and selected using TSA-plates containing kanamycin (50 mg/L). Recombinant plasmids were extracted using the Qiagen miniprep kit and both strands of the inserts were sequenced using M13 F and M13 R primers, for the pCR®-Blunt II-TOPO® plasmid (Invitrogen, Illkirch, France), and T7 promoter and T7 terminator primers, for pET-41b(+) (Novagen, VWR International, Fontenay-sous-Bois, France), with an automated sequencer (ABI Antimicrobial susceptibilities were determined by disk diffusion technique on Mueller-Hinton agar (Bio-Rad, Marnes-La-Coquette, France) and interpreted according to the EUCAST breakpoints, updated in 2015 (http://www.eucast.org). Minimal inhibitory concentration (MIC) values were Prism 3100; Antimicrobial agents, susceptibility testing and microbiological techniques determined using the Etest technique (BioMérieux, Paris, France).

Amplicons were cloned into pCR®-Blunt II-TOPO® cloning plasmid (Invitrogen, Illkirch, France) under regulation by the pLac promoter. The recombinant pTOPO-cmy-136 and pTOPO-cmy-2 plasmids were electroporated into the E. coli TOP10 strain and then selected using TSA-plate containing kanamycin (50 mg/L). blaCMY-136 and blaCMY-2 were amplified using primers INFcmy

Kinetic parameters of purified CMY-136 and CMY-2 were determined at 100mM sodium phosphate buffer (pH 7.0), with extinction coefficients as detailed in Table S1. When available, published values from previous studies for CMY-2 were used for comparison with those determined for CMY-136 (Table 2). The kcat and Km values were determined by analysing hydrolysis of βlactams under initial-rate conditions with an ULTROSPEC 2000 model UV spectrophotometer (Amersham Pharmacia Biotech) using the Eadie-Hoffstee linearization of the Michaelis-Menten equation. The different β-lactams were purchased from Sigma-Aldrich (Saint-Quentin-Fallavier, France). Low Km values were determined as competitive inhibition constants, Ki, in the presence of a good reporter substrate (cephalothin) [START_REF] Bauvois | Kinetic Properties of Four Plasmid-Mediated AmpC Beta-Lactamases[END_REF] .

Protein crystallization and crystallography

Initial crystallization screenings of CMY-136 were set up using the Mosquito® HTS (TTP LabTech) in four crystallization screening suites: Classics, AmSO4, PEGs and PEGs II (Qiagen/NeXtal). Plates were incubated at 293K in the ROCK IMAGER 1000 (Formulatrix, Inc).

The crystal was transferred to a cryo-protectant solution consisting of the mother liquor supplemented with 25% glycerol and flash-frozen in liquid nitrogen.

Diffraction data was collected at 100 K in a nitrogen cryostream on the PROXIMA2 beamline at the SOLEIL synchrotron (Saint-Aubin, France). The data were indexed and integrated with XDS [START_REF] Kabsch | Integration, Scaling, Space-Group Assignment and Post-Refinement[END_REF] in the autoPROC toolbox [START_REF] Vonrhein | Data Processing and Analysis with the AutoPROC Toolbox[END_REF] . Two incomplete datasets were merged to try to make as complete a dataset as possible, using autoPROC. Data scaling was performed using AIMLESS [START_REF] Evans | How Good Are My Data and What Is the Resolution?[END_REF] from the CCP4 suite [START_REF] Winn | Overview of the CCP4 Suite and Current Developments[END_REF] . Data collection and refinement statistics are given in Table 4. The structure of CMY-136 was solved by the molecular replacement method with Phaser 31 using the structure of CMY-2 (PDB code 1ZC2) as a search model. The model was rebuilt manually in Coot [START_REF] Emsley | Features and Development of Coot[END_REF] and then refined using BUSTER-TNT [START_REF] Bricogne | AutoBUSTER, Version 1.6. 0[END_REF] with local noncrystallographic symmetry (NCS) restraints and a translationlibration-screw (TLS) description of B factors [START_REF] Murshudov | REFMAC 5 for the Refinement of Macromolecular Crystal Structures[END_REF] . The quality of the final refined model was assessed using MolProbity [START_REF] Chen | MolProbity : All-Atom Structure Validation for Macromolecular Crystallography[END_REF] . Crystal structure images were generated using PyMOL [START_REF] Schrödinger | The PyMOL Molecular Graphics System[END_REF] .

AKNOWLEDGEMENTS

We acknowledge SOLEIL for provision of synchrotron radiation facilities (proposal ID BAG20150780) in using PROXIMA beamlines. This work was supported by the Laboratory of Excellence in Research on Medication and Innovative Therapeutics (LERMIT) [grant number ANR-10-LABX-33], by the JPIAMR transnational project DesInMBL [grant number ANR-14-JAMR-0002] and by the Région Ile-de-France (DIM Malinf).

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interests with the content of this article. Supporting Information. Sequence alignment of CMY-2 and CMY-136 (Fig. S1), chemical structures of β-lactams and β-lactamase inhibitors used in this study (Fig. S2), different conformations of Y150 in the CMY-2 and CMY-136 structures (Fig. S3), RMSD of the MD simulations (Fig. S4), RMSD analysis of Ω-loop from MD trajectories (Fig. S5), R1 and R2 pockets in CMY-2 (Fig. S6) and extinction coefficients and wavelengths for β-lactams (Table S1).

For Table of Contents Use Only

Supplementary Information

Genetic, biochemical and structural characterization of CMY-136 b-lactamase, a peculiar CMY-2 variant Agustin Zavala S8


Armand Huet
email: armand.huet@ensam.eu

Romain Pinquié

Philippe Veron

Frederic Segonds

Victor Fau

Romain Pinquie

Design rules application in manufacturing industries: a state of the art survey and proposal of a context-aware approach

Keywords: Design rule, product design, knowledge graph, context awareness, cognitive assistant

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Designing a product is a knowledge-intensive activity. Thus, to prevent design errors, i.e., choices that make certain designs "not allowed" or inappropriate for their intended use, design departments prescribe design rules. A design rule is a prescriptive statement -often an unstructured blend of text and graphical objects (equation, sketch, etc.) -aiming at assisting deployed designers for the achievement of a proof design, in compliance with best practices, applicable regulations, and DfX constraints. Many factors like the increasing complexity of design products or the number of norms per industrial domain tend to increase the number of designer rules an industrial designer has to comply with. The ever increasing number of design rules leads to critical issues when industrial companies want to use and manage such "Big Data".

While a designer is working on a product, he or she often needs to check design rules if he or she wants to provide a design free of errors. An expert designer may have memorized all crucial rules of his domain. A non-expert designer does not have in mind all applicable design rules. He/she has no other alternative than to spend a large amount of time finding the subset of design rules that matches his design context by either searching in design manuals or asking expert-colleagues to guide him/her. This task is even more time consuming because design rules often come from different domains and are stored in documents or databases that may not be correctly organized. Unstructured documents are still common in the industry [START_REF] Kassner | Product Life Cycle Analytics -Next Generation Data Analytics on Structured and Unstructured Data[END_REF]. Many companies still store design rule knowledge in unstructured documents -mainly PDF format -which are over tens or hundreds of pages.

As we will see in the next sections, there already exists many industrial tools and researchers' proposals for managing design rules. For each approach, several researches have been performed on google scholar [START_REF]Google Scholar[END_REF] as well as ScienceDirect [3] between the 12/17/2019 and the 12/20/2019. From the obtained results, we selected two types of contributions: Conceptual work to present a definition of the concept or approach, and application work in the domain of industrial design to illustrate pros and cons of the approach.

We will firstly present a design rule definition and classification (Sec. 2). Then, we will review the existing tools supporting the application of design rules (Sec 3.). Finally, we will focus on technologies that provide context awareness capabilities and briefly discuss how our Context-Aware Design Assistant would contribute to the current state-of-the-art solutions.

Design rules

For this paper, design rule definition is based on the work of Fu et al. [START_REF] Fu | Design Principles: Literature Review, Analysis, and Future Directions[END_REF] who propose a formal definition of a Prescriptive Design Principle: It is stated in the grammatical imperative form. It includes a prescriptive action for a designer to take It increases the likelihood of reaching a desirable consequence It is situated within a particular context and point in time In this paper, we will reduce the scale of this definition and consider a more technical definition. Calkins et al. [START_REF] Calkins | Knowledge-Based Engineering (KBE) Design Methodology at the Undergraduate and Graduate Levels[END_REF] in the field of Knowledge Based Engineering (KBE) consider that design rules synthesize the knowledge of a company and indicate how it should be used during conception to create a proven design. In our case, we also want to put the emphasis on how this knowledge is stored in databases or in design books. After reviewing numerous design manuals, we assume that a design rule is a prescriptive statement in natural language, often associated with descriptive graphical objects (equation, table, chart, etc.) guiding the work of the designer in a specific design context to improve design quality.

Authors previously cited both emphasis on the heterogeneous aspect of design rules. Calkins et al. consider four different origins possible for design rules: Heuristic (rules from companies' best practices), Empirical (based on experimental data), Legislated constraints (established by official norms), Physic (based on analytical or numerical physical models). Design rules affect not only the design but also all the phase of a product lifecycle, such as product recyclability [START_REF] Bralla | Design for Manufacturability Handbook[END_REF] or maintainability [START_REF] Pahl | Engineering Design: A Systematic Approach[END_REF].

We conclude that design rules have various origins and objectives and that each one relates to a specific design context. They are essential for maintaining the quality level of industrial products and their number is significantly increasing.

State of the art of design rule application tools

Most industrial design rule checkers [8-10] adopt procedural approach. They have built a set of rules for each possible rule origin. For example, a tool may have a set of a few dozen rules to check on a part machined using a milling process. Each rule is an algorithm that detects geometrical features in the CAD data that do not respect the rule. Bo Huang et al. [START_REF] Huang | An automatic 3D CAD model errors detection method of aircraft structural part for NC machining[END_REF] give a good example of the work realized in this field. Such a rule application strategy results in expert systems that have a predefined number of rules focusing on a very specific problem. They are efficient in detecting CAD quality errors and rules directly associated with a design issue like a manufacturing process. However, this approach has some flaws:  Rule editing requires the work of experts in order to modify or create algorithms. As explained previously, a design rule is due to evolves with technology or even company habits. It is not trivial to maintain or personalize the design rule set with this technology.

 Design rule storage across multiple domain silos makes multi-domain rules application complicated. Design is a multi-domain process and many design rules do not fit in the pre-defined contexts fixed by those tools.

 Some rules represent unstructured knowledge that cannot be translated into algorithms. Traditional rule checking tools cannot process these rules but the designer still need to know and consider them for his design.

To improve design rule application, scientists explored declarative approach of design rule application. They use new technologies such as Semantic Networks (SN) to represent the knowledge associated with the product and the design rules. According to JF Sowa [START_REF] Sowa | Semantic Networks[END_REF]: "A semantic network or net is a graph structure for representing knowledge in patterns of interconnected nodes and arcs." They are primarily used to represent conceptual knowledge as natural language expressions in a structured and unbiased way. This process is not straightforward for design rules but many scientists work to improve design rules representation in SNs like S. Kang et al. [START_REF] Kang | Extraction of Manufacturing Rules From Unstructured Text Using a Semantic Framework[END_REF]. Using a SN could allow us to process all kind of design rules.

Various teams experimented SNs for design rule application in the manufacturing industry [START_REF] Garcia | An Ontology-based Feature Recognition and Design Rule Checker for Engineering[END_REF][START_REF] Moitra | Automated Capture and Execution of Manufacturability Rules Using Inductive Logic Programming[END_REF][START_REF] Fortineau | Expressing formal rules within ontology-based models using SWRL: an application to the nuclear industry[END_REF]. Their strategy is to build a data model to represent the type of product they focus on. Once this model is built, they implement a translation algorithm to automatically generate a semantic representation from the digital mock-up. Then, they can edit rules that will apply on the knowledge representation of the product. They are able to identify design errors as well as automatically correct some of them. In this method, design rules are not algorithms that will explore the geometry. They are description of what the semantic representation of the product should be. This makes design rules easier to implement. Some teams even develop their own high-level language to facilitate new design rules editing.

However, this approach is not flawless. Each type of industrial product needs his own semantic representation to perform well with this approach. These representations are hard to develop and maintain [START_REF] Fortineau | Expressing formal rules within ontology-based models using SWRL: an application to the nuclear industry[END_REF] and are domain specific. Therefore, only specialized industrial domains can benefit from this approach. An industrial part often go through multiples manufacturing processes, needs to comply with assembly rules and has mechanical constraints. Creating the semantic representation of this part and the set of associated rules would be extremely difficult with the previous approach.

Introducing a Context-Aware Cognitive Design Assistant

In [START_REF] Dey | Understanding and using context[END_REF], A. K. Dey describes the context of a software user as: "Any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves." In our case, any in-formation describing the conception process, the digital mock-up or the team members in charge of the conception, is part of the conception context.

A. K. Dey gives a definition of a Context-Aware System (CAS): "A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user's task." Therefore, a context-aware application for rule application would have to provide rule information and conception guidance when the user needs it to progress without mistakes in his conception task. As context knowledge is multi-domain, such a tool would have a greater ability to process multi-domain design rules.

CAS are by definition user centered. Each user will have a different context and different needs in different times. The CAS will provide a suitable service for each case. This is crucial in industrial context where team members need to coordinate their work on a complex task. For example, M. A. Dhuieb et al. propose a context-aware architecture to present manufacturing knowledge to workers in factories [START_REF] Dhuieb | Context-awareness: A Key Enabler for Ubiquitous Access to Manufacturing Knowledge[END_REF]. Conception context can be compared to this one as each designer has a specific task and level of expertise, but need to work with his/her team. Therefore, we propose to use context awareness in a rule application tool to improve multidomain rules recommendation as well as the designer's productivity, which are the main flaws of state-of-the-art rule application tools previously presented.

On a practical aspect, context knowledge is represented in state-of-the-art CAS by a Semantic Network. The context graph is complex and evolves dynamically. A structural data model is essential to run context aware applications. J. Aguilar et al. propose a general data model for context modeling [START_REF] Aguilar | CAMeOnto: Context awareness meta ontology modeling[END_REF]. In our domain of application, R. Pinquie et al. [START_REF] Pinquié | A Property Graph Data Model for a Context-Aware Design Assistant[END_REF] propose a data model to represent the user's design context in a context aware design assistant. This assistant would perform design rule recommendation on the fly to improve user's productivity. We propose to develop a proof of concept of such an assistant to demonstrate the efficiency of context aware technology for design rule application.

Conclusion and future work

The goal of this paper is to review the state-of-the-art of design rules and design rules application to demonstrate the need for a context-aware design assistant.

First, we discussed about the concept of design rules in the manufacturing industry. We demonstrated that the use of design rules is a crucial issue to improve design efficiency.

Then, we reviewed existing tools for managing rules. Tools based on a semantic network enable designers to better detect design flaws and ease the edition of rules. We raised the issue that all these product-centered tools failed to process efficiently multi-domain rules, which are very common in design activity. Moreover, semantic representations of industrial products are fastidious to produce and limited to a single domain.

Finally, we presented CAS and how they could be used to improve multidomain rule application as well as user specific rule recommendation. This is why we propose in a future work to develop a Proof of Concept of this approach with an industrial set of data.


Sâannibè Ciryle Some

Jean François Barthelemy

Ferhat Virginie Mouillet

C Somé

J-F Barthélémy

F Hammoum

Effect of ageing kinetics on the rheological properties of bituminous binders and mixes: experimental study

Keywords: bituminous mixture, ageing, stiffness modulus, multi-scale modeling

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Bituminous mixes are viscoelastic complex composite materials build up from a mixture of aggregates, bitumen, fillers and additives. As such, their end performances entirely depend on their components percentage and properties, their interaction with each other and the evolution of their properties other time. Many parameters have a significant influence, such as aggregate size and grading, filler size distribution, bitumen properties and the interaction between bitumen and aggregates. Understanding the influence of all these parameters is a challenging task and requires a multi-scale modeling to assess the effect of each component [START_REF] Ch | Generalized self-consistent scheme for upscaling of viscoelastic properties of highlyfilled matrix-inclusion composites Application in the context of multiscale modeling of bituminous mixtures[END_REF], [START_REF] Alam | Viscoelastic properties of asphalt concrete using micromechanical self-consistent model[END_REF]. Moreover, the ageing induced by the manufacturing conditions and the field climatic modifies the chemical composition of the binder that makes the mixes' performances to evolve. Indeed, the ageing of mixes occurs in two main stages: The short-term ageing is caused by the manufacturing in the mix plant, the transport and the paving during which the ageing process is mainly associated to a departure of the volatile compounds of bitumen and the long-term ageing during pavement life is influenced by climatic conditions, and road traffic and is related to steric hardening, oxidation and UV rays which affects only the 12 mm upper layer of the roads.

In order to simulate the ageing that has taken place over several years, accelerated ageing methods were developed in laboratory. Among these methods, one can distinguish the ageing processes on bitumen RTFOT (Rolling Thin Film Oven Test) followed by PAV (Pressure Aging Vessel) which is claimed to reproduce 7 to 10 years natural ageing of a asphalt pavement [START_REF] Xiao | Rheology evaluations of WMA binders using ultraviolet and PAV agingprocedures[END_REF]) and those carried out on loose mixes. The prediction of field ageing based on laboratory ageing protocols is still questionable and imprecise (from 1 RILEM International Symposium on Bituminous Materials, ISBM Lyon 2020, Lyon, France, 14 au 16 décembre 2020 5 to 10 years). In general, the predictions are more or less based on the analysis of one of the following indicators: carbonyl or sulfoxide indexes [START_REF] Kambham | Investigation of laboratory and field aging of bituminous concrete with and without anti-aging additives using FESEM and FTIR[END_REF], rheological properties, mechanical performance but never all indicators together. More than twenty ageing procedures on the mixes can be found in the literature but to our knowledge there is no equivalence between these latter and the RTFOT+PAV ageing methods that can be performed on bitumens. For WMA the ageing protocols are still under investigations.

This study has three main objectives: Firstly it aims to compare HMA and WMA in term of ageing by characterizing the rheological properties of the mixes and the extracted binders taking into account several ageing kinetics. Secondly, it aims to implement a multi-scale model capable to predict the rheological properties of both HMA and WMA based on theirs constituents (bitumens, aggregates, air voids) properties. Incidentally, it also allows to compare the RILEM ageing protocol on loose mixes (described CEN TS 12697-52) and the RTFOT+PAV method on bitumen (described in EN 12607-1 (RTFOT) and EN 14769 (PAV)) developed for HMA and proposes an adaptation of these ageing protocols to foamed WMA.

Materials and mix design 2.1 Materials properties

The mixes were produced with a paving grade bitumen, whose properties of needle penetration (EN 1426) and softening temperature (EN 1427)

Ageing of asphalt mixture

Ageing of hot mix asphalt (HMA): The hot mixes were manufactured respectively at 165 o C and then subjected to different ageing durations from 0 to 9 days. After the mixing, the loose HMA mixture was cool down to 135 o C and spread in thin layer (not more than 2.5 cm) into a tray and placed in a ventilated oven during 4 hours to simulate the short term ageing. Then, it was cool down to 85 o C and kept in the oven for 3, 6 or 9 days to reproduce the long term ageing. At the end of the ageing procedure the loose mixes were reheated at 135 o C during 2 hours then compacted. The reference hot mix was compacted without long-term ageing and designated H0 while those subjected to long-term ageing were labeled H3, H6, H9 corresponding to the 3, 6 or 9 days ageing.

Ageing of foamed warm mix asphalt (WMA): The foamed bitumen was produced with a mixture of hot bitumen, 1% of Cecabase additive and 5.5% of added water which allows to obtain maximum expansion. The WMA were manufactured at 135 o C then immediately spread in thin layer. The short and long term ageing and compaction procedures applied are similar to that of HMA. The mixes manufactured were labeled W0, W3, W6, W9 for reference, 3, 6 or 9 days ageing respectively.

Ageing of bitumen

Simulation of HMA field ageing by RTFOT and PAV protocols: The RTFOT and PAV ageing protocols were carried out on fresh bitumen to simulate respectively the short-term and long-term ageing that a binder undergoes during HMA production until paving and its natural ageing during the service life. The RTFOT was carried out at 163 o C during 75 min according to EN 12607-1. The long-term ageing of HMA was simulated using the pressure ageing vessel (PAV) test in accordance to the EN 14769.

Simulation of WMA field ageing by RTFOT and PAV protocols: The short term ageing of WMA was simulated by the RTFOT performed at a temperature of 140 o C other parameters remaining unchanged. This temperature has been selected in order to be the closest to the manufacturing temparture of WMA The RTFOT and RTFOT+PAV aged bitumens and those recovered from the mixes (H0 to H9, W0 to W9) were tested with dynamic shear rheometer (DSR).

3 Rheological tests

Mixes rheological tests

The complex modulus E * of the mixes was carried out on a prismatic cantilever beam in accordance to EN 12697-26 (Annex A: 2P-PR) varying the temperature from -10 o C to 50 o C and the frequency from 3 Hz to 40 Hz. The master curves of |E * | and the phase angle δ were built by shifting horizontally the isotherms as described in reference [START_REF] Chailleux | A mathematical-based master-curve construction method applied to complex modulus of bituminous materials[END_REF], [START_REF] Booij | Generalization of Kramers-Kronig transforms and some approximations of relations between viscoelastic quantities[END_REF]. Figs. 1 show that the stiffness modulus increases logically with the long term ageing duration for both HMA and WMA. This increase in the modulus induces a decrease in the phase angle as shown in Figs. [START_REF] Alam | Viscoelastic properties of asphalt concrete using micromechanical self-consistent model[END_REF]. Moreover, the experimental data of complex modulus have been curve-fitted with the modified Huet-Sayegh model model described in [START_REF] Olard | General 2S2P1D Model and Relation Between the Linear Viscoelastic Behaviours of Bituminous Binders and Mixes[END_REF], [START_REF] Ch | Analyse du comportement visqueux des bitumes[END_REF], [START_REF] Sayegh | Contribution a l'étude des propriétés viscoélastiques des bitumes purs et des beétons bitumineux[END_REF] [START_REF] Ch | Susceptibilité au vieillissement des bitumes -Expérimentation A08 Groupe national Bitume[END_REF]. However, the long term ageing simulated by the RTFOT at 163 o C + PAV is more severe than the RILEM long term ageing procedure at 9 days on loose mixes. Regarding the WMA, the RILEM ageing procedure on loose mixes is more severe than the RTFOT at 140 o C and RTFOT at 140 o C+PAV. The |G * | of the bitumen extracted from short term aged mixture W 0 is similar to that of the RTFOT at 140 o C+PAV which is supposed to simulate the long term ageing. In addition, it should be noted that the complex modulus of the bitumen recovered from W9 was not tested because this latter was so hard. In addition, these data were also curve-fitted with the modified Huet-Sayegh model and the obtained parameters are given in Table 2.

Multiscale modeling

The AC is a multiscale material that we propose to decompose into three scales (see Fig. 3): -the macroscale is made of coarse aggregates coated with bitumen, a mortar phase partially filling the intergranular space and air voids (voids content estimated to be 5.6% ± 0.8% for the tested mixes), -at the mesoscale, the mortar is composed of a mastic matrix embedding sand grains, -at the microscale, the mastic is composed of a bitumen matrix embedding fillers. The aggregates are assumed spherical coated with soft bitumen layer whose thickness e is proportional to the aggregate diameter d according to the relation inspired from Duriez' relation e = e 0 × (d/d 0 ) 0.8 , where d 0 = 1 mm, e 0 is a setting parameter which varies between 20 and 28 µm according to Duriez [START_REF] Duriez | Traité de matériaux de construction[END_REF]. At the mastic and mortar scales, the Mori-Tanaka (matrix / inclusions) scheme was used while the generalized self consistent scheme was applied at the mixture scale as in ref. [START_REF] Ch | Generalized self-consistent scheme for upscaling of viscoelastic properties of highlyfilled matrix-inclusion composites Application in the context of multiscale modeling of bituminous mixtures[END_REF]. At low frequency and high temperature, the bitumen behaves like a Newtonian fluid therefore, the model based on coated aggregate by thin bitumen layer fails to predict the complex modulus of the mix as previously mentioned [START_REF] Benedetto | Linear viscoelastic behaviour of bituminous materials: From binders to mixes[END_REF]. Moreover, stiffness is needed to account the contact between aggregates when the binder becomes liquid. Thus, according to an idea proposed in [START_REF] Benedetto | Linear viscoelastic behaviour of bituminous materials: From binders to mixes[END_REF], the contact is modeled by a juxtaposition of bitumen thin layer (of surface fraction χ) and actual grain contacts (of surface fraction (1 -χ)). The grain contact does not allow interpenetration of grains but only relative sliding so that it is characterized by a linear spring model relating the local shear stress to the tangential displacement jumps thanks to a shear stiffness k t . For χ = 1, the grains are entirely surrounded by a thin layer of bitumen, which implies a total loss of stiffness at high temperature or low frequency. On the contrary if χ < 1 such a model is consistent with the idea of connexity of the granular skeleton even at high temperature or low frequency. The aggregates linear isotropic elastic properties are E = 62 GPa, ν = 0.2. The bitumen bulk modulus K was assumed constant while the shear modulus µ * = 3KE * 9K-E * depends on ω. The parameters k t , χ and α have been determined by minimizing the objective function between the multiscale prediction and the data fitted with the modified H-S model whose parameters are given in Table 2. Figs. 4 a comparison between the multiscale and the modified H-S models. The results show a relatively good agreement for k t between 10 and 410 M P a.mm -1 from softest to stiffest mixes, χ 0.1 and 0.1 ≤ e 0 ≤ 0.4 µm. For readability purposes, only a few results have been represented.

0 -6 1 0 -5 1 0 -4 1 0 -3 1 0 -2 1 0 -1 1 0 0 1 0 1 1 0 2 1 0 3 1 0 4 1 0 5 1 0 6 1 0 7 1 0 8 1 0 9 1 0 2 1 0 3 1 0 4 | E * | ( M P a ) ω ( r a d / s ) H 0 _ H S H 0 _ h o m H 0 _ e x p H 9 _ H S H 9 _ h o m H 9 _ e x p W 0 _ H S W 0 _ h o m W 0 _ e x p W 3 _ H S W 3 _ h o m W 3 _ e x p W 6 _ H S W 6 _ h o m W 6 _ e x p 1 0 -6 1 0 -5 1 0 -4 1 0 -3 1 0 -2 1 0 -1 1 0 0 1 0 1 1 0 2 1 0 3 1 0 4 1 0 5 1 0 6 1 0 7 1 0 8 1 0

Conclusion

The effect of HMA and WMA ageing kinetic on the l.v.e. properties of binders and mixes has been investigated. The results show that the mixes stiffness increases highly with the ageing duration specially for WMA. Moreover, RTFOT and PAV ageing procedure have been also performed on fresh bitumen to simulate HMA short term ageing then their l.v.e. characterized. Furthermore, RTFOT and PAV ageing procedure were adapted to reproduce ageing of WMA. The results showed an increase of the binders' stiffness with the ageing duration, consistent with the mixes properties. In addition, a multiscale model has been implemented to predict the l.v.e. of the mixes based on those of the constituents. The model predict relatively well the l.v.e. properties of the mixes, by means of good calibration of the contact parameters k t , χ and α. These latter can be well calibrated by performing laboratory experiments in a wide range of temperatures. Finally, in this study the bitumen Poisson's ratio ν is assumed following the modified HS model and bounded at 0.4 and ≈ 0.5. As a perspective, an experimental measurement of ν can allow improving the multiscale model.

Figure 1 :

 1 Figure 1: Master curves of complex phase angle of mixes at T ref = 10 o C

Figure 2 :

 2 Figure 2: Master curves of binders at T ref = 10 o C

Figure 3 :

 3 Figure 3: Multiscale model for asphalt mix

1

 1

Figure 4 :

 4 Figure 4: Comparison between multi-scale model (hom), modified H-S model and experiments (exp)

Table 1 :

 1 are respectively 57 × 0.1 mm and 49.6 o C, and porphyry aggregates which Los Angeles (EN 1097-2) and Microdeval (EN 1097-1) properties are 17% and 8%. The mixture composition and the constituents densities are given in Table 1. Mix composition

	Constituent	Mass content (in %) Density (in kg.m -3 )
	Limestone filler	2.96	2700
	0/2	27.59
	2/6.3	25.05	2720
	6.3/10	44.4
	Bitumen	5.4	1040
	Cecabase for WMA	1% (bitumen mass)	900

  at a reference temperature of 10 o C. The parameters are given in Table2then used to validate the multiscale model presented in section 4.

	Mixes	E 0	E∞	δ	τ	k	h	β
		(MPa)	(MPa)
	W 0	88.7	2.21e+04 2.78	1.45	0.231 0.771 1000
	W 3	44.9	2.29e+04 2.69	5.27	0.173 0.573 1000
	W 6	2.10	2.72e+04 2.51	24.5	0.148 0.478 1000
	W 9	23.8	2.51e+04 2.45	704	0.159 0.515 1000
	H 0	1.53	4.85e+04 2.34 2.34e-02	0.1	0.446 7902
	H 3	484	5.00e+04 3.64 9.75e-02 0.107 0.480	404
	H 6	0.03	3.34e+04 2.30 4.65e-01 0.127 0.425	200
	H 9	35.5	4.24e+04 3.12 3.07e-01 0.108 0.457 1000
	Bitumen	G 0	G∞	δ	τ	k	h	β
	B 0	1.e-05	3.00e+03 10.9 5.94e-05 0.238 0.660	124
	B(RT F OT 163)	1.e-05	3.63e+02 2.50 4.67e-03 0.350 0.664	64.4
	B(RT F OT 163 + P AV )	1.e-05	4.32e+02 4.82 1.38e-02 0.331 0.646	160
	B(H 0 )	1.e-05	2.40e+03 10.3 2.42e-04 0.268 0.656	173
	B(H 3 )	1.e-05	5.47e+02 3.82 2.37e-03 0.296 0.643	114
	B(H 9 )	1.e-05	1.45e+03 9.92 1.06e-03 0.279 0.653	211
	B(RT F OT 140)	1.e-05	3.00e+03 10.3 6.37e-05 0.246 0.645	237
	B(RT F OT 140 + P AV )	1.e-05	1.02e+03 8.12 1.47e-03 0.263 0.626	346
	B(W 0 )	1.e-05	3.00e+03 17.4 4.08e-04 0.230 0.623	269
	B(W 3 )	1.e-05	4.50e+02 7.20 3.31e-02 0.278 0.627	193
	B(W 6 )	1.e-05	2.61e+03 23.7 2.61e-03 0.237 0.593 1680

Table 2 :

 2 Modified H-S model parameters for binders and mixes curve-fitted at T ref = 10 o C 3.2 Properties of bitumen Dynamic shear rheometer (DSR) test was performed to characterize the linear viscoelastic properties (l.v.e.) of the asphalt binders. It was performed over a temperature range from 10 o C to 80 o C and over the frequency sweep from 0.681 to 21.54 Hz. Applying the same approach as before for mixes, the master curves of the norm of the shear modulus |G * | and phase angle δ were built and represented in Figs. 2. Figs. 2 show that the shear modulus increases with the long term ageing duration for all binders recovered from HMA and WMA. This increase in the modulus induces a decrease in the phase angle as shown in Figs. 2. In addition, one can observe the temperature imposed in RTFOT test at 163 o C test simulates quite well the short term ageing of the HMA (H0) production as already shown by literature