Davide Lorito

Yves Schuurman

Claude Mirodatos

Controlling Aging Processes during Bio-Syngas Methanation: SSITKA experiments over Ni/Al 2 O 3 catalysts

    Controlling aging processes during bio-syngas methanation: SSITKA experiments over Ni/Al2O3 catalysts D. Lorito, Y. Schuurman, C.

Introduction

Ni-based catalysts are currently used for the conversion of syngas (CO+H2) into methane as synthetic natural gas (SNG) due to their relatively high activity and low cost. The basic requirements for performing methanation catalysts are both high activity at low temperatures and high stability at high temperatures. However, Ni-based catalysts suffer from various aging processes including sintering of the Ni particles as well as coke formation under harsh reaction conditions, as reviewed in [1,[START_REF] Miao | Catalysis mechanisms of CO2 and CO methanation[END_REF]. Recently, attention has been paid to new eco-friendly processes linked to biomass or solid waste gasification. These alternative resources lead to a syngas feed containing a variety of impurities among which NH3, HCl, H2S, tars and various alkali. Despite large efforts for syngas downstream cleaning, traces of these impurities remain detrimental for the catalytic conversion of syngas to substitute natural gas processes [3,[START_REF] Aravind | Evaluation of high temperature gas cleaning options for biomass gasification product gas for solid oxide fuel cells[END_REF]. In this context, the exact role and effect of these biomass-derived impurities on methanation catalysts remains an open debate, especially when aging factors like poisoning (or promoting) combine with structural processes such as metal sintering under operating conditions. More precisely the proper impact of these various combined aging factors on methanation mechanism and kinetics remains poorly explored. To that end, Steady-State Isotopic Transient Kinetic Analysis (or SSITKA), which was found well adapted to understand the mechanism of methanation in the absence of poisoning effects, [1,[START_REF] Miao | Catalysis mechanisms of CO2 and CO methanation[END_REF][START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst II. A Mechanistic Study by Transient Kinetics and Infrared Spectroscopy[END_REF][START_REF] Ledesma | Recent Approaches in Mechanistic and Kinetic Studies of Catalytic Reactions Using SSITKA Technique[END_REF], was used in the present work in the presence of those impurities. In the absence of any impurities, as reported in [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF][START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF], both Ni sintering and carbon deposition were shown to control the deactivation mechanism. After an initial period of carbon deposition, fast sintering and particle smoothing via nickel carbonyl transfer, the reacting surface was described as a layer of nickel carbide, largely covered by CO adspecies. The rate of hydrogenation was shown to be controlled by the probability for a dihydrogen molecule to collide with a carbonaceous adspecies (CHX) issued from the carbide layer, surrounded by Ni atoms free from adsorbed CO. The regeneration of the carbidic layer is ensured by CO dissociation after methane desorption. A rate equation was proposed with physically meaningful kinetic parameters [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF].

In the present study, the sensitivity of this type of kinetic analysis to the effect of poisons representative of syngas obtained from biomass gasification, is evaluated. Ammonia and acetonitrile were selected for representing N-containing compounds, trichloroethylene for Cl-containing compounds and toluene as tar representative. The effects of sulfur containing molecules can be found in [START_REF] Legras | Impact and Detailed Action of Sulfur in Syngas on Methane Synthesis on Ni/γ-Al2O3 Catalyst[END_REF]. Ni/Al2O3 catalysts were used, being recognized as more sintering resistant than Ni/SiO2 catalysts.

Experimental

Catalyst characterization

All kinetic experiments were performed over a well-dispersed 20%Ni/Al2O3 catalyst. The nickel loading was determined by inductively coupled plasma mass spectrometry (ICP-MS) technique. The BET surface area, pore volume and average pore diameter were determined by N2 sorption/desorption isotherms at 77K on a BELSORP-Mini (BelJapan) automated system. The samples were outgassed under vacuum (≈10 -4 mbar) at 473 K for 12h before starting the kinetic measurements. BET values around 100 m²/gcat were found for the catalysts. Transmission Electron Microscopy (TEM) images were used to determine the distribution of nickel particle size and the overall metal dispersion.

Catalytic test

The SSITKA device used in this work is described in [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF]. It contains two independent feed lines. The first line is dedicated to unlabeled compounds ( 12 CO, H2, Ar), the second one to the isotopic compounds and the tracer ( 13 CO, H2, Ar and Kr). The pressure transducers are used to adjust the same pressure drop for both lines. Isotopic switches were realized using a two-position four way Valco-valve and monitored with an online INFICON quadrupole mass spectrometer.

Steady-state and transient kinetic experiments

Reference steady-state and transient SSITKA experiments. In the absence of poisons, reference SSITKA experiments were performed in a fixed-bed reactor (Din=7mm, Lbed=1cm) filled with 0.2 g of catalysts diluted with SiC, to reduce dead volume in the reactor. The catalysts pellet size was in the range of 100÷200 µm. The Ni catalyst was reduced in situ at 500°C for 10h (temperature ramping at 1°C/min) under a 20%H2/80%Ar gas flow at 100 mL/min. The catalyst was then exposed to the 15%CO/60%H2/25%Ar reaction mixture, at a total flowrate of 100 mL/min. The pressure transducers allowed to adjust the same pressure drop for both lines. Isotopic switches were performed at 4 different TOS (2h, 50h, 72h, 164h) from 12 CO/H2/Ar to 13 CO/H2/Ar and Kr Inert Krypton has been added to analyze the gas hold up of reactor system 8 . All the SSITKA experiments were performed at 225 °C, atmospheric pressure and a H2/CO ratio equal to 4. Steady-state and transient kinetic experiments in the presence of poisons. The same reference SSITKA experiments were then performed under poisoned gas flows. To feed these molecules a flowrate of 5 mL/min of argon was sent to a temperature-controlled saturator that contained a certain catalyst "poison". Through a calibration curve, the amount of these components was controlled and kept constant during the whole kinetic experiment. When the steady-state conditions were reached a SSITKA switch was performed again. All reaction product containing lines and valves were heated at 393 K. The selected poisons were acetonitrile, trichloroethylene and toluene. Under operating methanation conditions it was checked that acetonitrile was totally decomposed into ammonia and methane, the latter being accounted for in the conversion calculation. For the case of trichloroethylene it was decomposed into chlorine and hydrocarbons by-products (essentially ethylene). It was chosen to work at low concentration of poisoning molecule, 0.23 and 0.13 vol.% for the acetonitrile and trichloroethylene, respectively, to mimic realistic conditions of bio-mass derived syngas composition (after up-stream cleaning), also keeping a negligible contribution of decomposition products to the methanation reaction products. For mimicking the effect of tar on the methanation rate, toluene was fed with the syngas feed at the concentration of 0.13 vol.% (see Table 1

Results and discussion

3.1 Catalyst sintering with time-on-stream in the absence of poisons Drastic changes in nickel dispersion have been observed with time on stream under non poisoned methanation feed conditions by TEM and DRX analyses, as reported in [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF][START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF] and completed by new TEM analyses. The Ni dispersion observed on the freshly reduced sample displays a rather narrow particle size distribution centered around 5 nm [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF][START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF]. As shown in Figure 1A, the observed Ni particles by TEM reveal rather spherical shape, but rough surfaces and the hkl plan indexes indicate dominant NiO structure as expected from the reoxidation occurring during the sample preparation for TEM analysis. Such a reoxidation of small particles was also reported in [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF] for close samples analyzed by XRD, while in situ magnetic measurements i.e., without any contact with air, indicated that the dominant phase was metallic nickel.

A/ B/ -In contrast, the catalyst aged for 164h under methanation conditions exhibits a particle size distribution now centered on 30 nm [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF][START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF], but displaying also very large particles, over 50 nm in diameter. For the latter most images revealed the formation of flat terraces separated by step structures. From XRD patterns [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF], the nickel phase of all these large particles was kept essentially as a metal, showing the resistance of the sintered nickel to reoxidation. In situ magnetic measurements confirmed that the sintered particles were formed of metallic nickel while a layer of carbide Ni3C was surrounding the particles [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF].

The change in the metal phase dispersion, D (%), was estimated from the formula:

𝐷𝐷 = 6 ( 𝑣𝑣 𝑚𝑚 𝑎𝑎 𝑚𝑚 ) 𝑑𝑑 𝑉𝑉𝑉𝑉 * 100%
where vm is the volume occupied by a Ni atom in the bulk, am the surface area occupied by an atom of Ni and dVA the average particle size estimated by TEM measurements. As a result, the Ni dispersion changed from 20% to less than 5% after long term methanation.

From the outlet gas analysis, the conversion profile revealed a fast initial decay within the first 2 h on stream as detailed in [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF], followed by a much slower and regular decay for longer time on stream as depicted in Figure 2. That series of long term experiments was combined with SSITKA experiments, as shown later on. .

Active surface characterization by SSITKA

Once the steady state was achieved (i.e. after at least 2 h on methanation stream), the SSITKA switch was performed as described in the experimental part. The delay observed between the reference Kr inert tracer transient and the 13 CO / 12 CO responses results from the time required for the labeled carbon monoxide to replace the surface reservoir of unlabeled one. This phenomenon is commonly referred to as a chromatographic effect [START_REF] Shannon | Characterization of Catalytic Surfaces by Isotopic-Transient Kinetics during steady-state reaction[END_REF]. From this time lag and knowing the flow rate of carbon monoxide, the amount of this reversibly adsorbed CO reservoir at steady-state can be directly deduced. The same reasoning holds for the labelled and unlabeled methane responses, which are controlled by the residence time of methane precursors on the working surface. The delay between the inert tracer curve and the labeled CO and CH4 molecules transient responses is representative of the mean surface lifetime, respectively indicated as τCO and τCHx (s), of the active intermediates accumulated on the surface under steady-state conditions. From the mean surface lifetime estimate, it is also possible to quantify the amounts of CO adsorbed in equilibrium with the gas phase and the amounts of reacting intermediates CHx adsorbed on the surface, referred to as NCO and NCHx, (µmol/gcat) respectively [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF].

Where Fi (mol/s) is the molar flow, Wcat (kg), the catalyst mass, X SS the steady-state CO conversion, Ei(t) (-), the normalized transient response and t (s), the time. From these surface concentrations of reversibly adsorbed CO and of CH4 precursors, the steady-state coverage of these ad-species can be derived, accounting for the effective metal dispersion and amount of catalyst involved in each SSITKA experiment. These values are reported in Table 2 Figure 4 shows the changes in 13 CO SSITKA responses as a function of TOS. As can be seen, the amount of reversibly adsorbed CO is decreasing with time on stream, in line with the Ni particles sintering/restructuring upon catalyst aging. As can be seen, on the still well dispersed sample after 2h of reaction (black dots), the decay of 12 C into methane product is essentially fast and linear, which reveals a single type of kinetic behavior. It might indicate a single or a dominant reaction mechanism for methanation. In contrast, after 50h on stream, the log transform (grey dots) clearly indicated two SSITKA decay regimes, one close to the previous one, and a second one with a much slower dynamic response, progressively merging with the labelled signal noise. As such, it is revealed that upon aging, the dynamics of the catalyst move from a single mode as observed on fresh samples to a double mode on aged ones, in line with the previously observed changes in catalyst structure [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF].

N 13CH 4 = τ 13CH 4 F 13CO X 𝐶𝐶𝐶𝐶 𝑠𝑠𝑠𝑠 W cat = F 13CO X 𝐶𝐶𝐶𝐶 𝑠𝑠𝑠𝑠 W cat � �E Kr (t) -E 13CH 4 (t)� 𝑡𝑡 0 dt N 13CO = τ 13CO F 13CO W cat = F 13CO W cat � [E Kr (t) -E 13CO (t)] 𝑡𝑡 0 dt

Effect of poisons on methanation kinetics

As said before, the methanation SSITKA experiments were carried out alternatively in the presence of acetonitrile, trichloroethylene and toluene in the SSITKA feeds. In line with the above analysis revealing changes in methane responses with TOS, we report here essentially the log transform of the methane response in order to identify potential changes in surface dynamics upon the various selected poisonings. In order to identify specifically poison effects on the SSITKA curves, these experiments were carried out after similar TOS for the three tested poisons, i.e., after ca. 24h on stream for each experiment. Thus, Figure 6 describes the log transform of the CH4 SSITKA response in the absence and in the presence of the three different added poisons. These data were regressed following a sequence of two linear models and Table 3 -In the presence of acetonitrile, i.e., a N-containing poison (Fig 6B ), a two-zone log transform is still observed, though a deactivation process affecting those two zones of log transform decay was revealed. As such, the slopes of the two-zone semi-log transform are slightly decreased, in line with that deactivation process. -In the presence of trichloroethylene, i.e., a Cl-containing poison (Fig 6C ), a major change is observed since only a single-zone log transform remains over the whole SSITKA relaxation zone. This would indicate that the part of the catalyst responsible for the second-zone semi-log transform has been completely deactivated. A similar decrease in the value of log transform slope as for acetonitrile is observed in Table 3. -In the presence of toluene (Fig 6D ), the SSITKA transforms are similar to the ones of the reference data, as also seen in Table 3.

Mechanistic rationale

As above pointed out, the poisons effects can be ranked by comparing the rate values and the SSITKA dynamics with i) a measurable poisoning effect after acetonitrile addition (i.e., ammonia effect) and ii) a still more intense poisoning effect after trichloroethylene addition (i.e., chlorine effect), iii) no measurable effect after toluene addition (i.e. no coke effect superimposed to the overall deactivation). As reported in [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF], a similar ranking was observed both for CO coverages observed by DRIFT carbonyl band intensity and θCO from SSITKA. The next step in the reasoning is now to determine if one can correlate the above reported SSITKA effects (changes in methane response dynamics via the semi-log transforms) to the morphology of the tested samples. From the TEM analyses (Fig1) completed by hydrogen adsorption measurements, one can consider that the Ni phase for all the samples tested in the present study consists in a mix of i) small and rather rough particles (indexed as NiO after reoxidation in the open air) and of ii) large flat and rafted ones, with poly-crystalline structures and many defects such as steps between low index terrace planes [START_REF] Paredes-Nunez | Origins of the poisoning effect of chlorine on the CO hydrogenation activity of alumina-supported cobalt monitored by operando FT-IR spectroscopy[END_REF].

In line with our previous study on Ni sintering under methanation conditions [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF], the large particles develop with TOS at the detriment of the small ones via Ni carbonyls transfer. Thus, the Ni phase corresponding to the mid-aging period tested for this SSITKA analysis is a complex combination of surface defects and flat zones distributed over a large domain of particle size. Based on these results, the question arises now as to relate these SSITKA analyses to the methanation mechanism(s). i) Methanation mechanisms in the absence of poisons. Refereeing to our previous papers on methanation [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst II. A Mechanistic Study by Transient Kinetics and Infrared Spectroscopy[END_REF][START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF], it was proposed that in the absence of any poison, the rate determining step is essentially controlled by the probability for gaseous hydrogen to dissociate around a CH x adsorbate on the nickel surface. As determined from the kinetic modeling of the transient SSITKA responses reported in [START_REF] Lorito | Understanding deactivation processes during bio-syngas 1 methanation: DRIFTS and SSITKA experiments and modeling over 2 Ni/Al2O3 catalysts[END_REF], the typical reacting site would correspond to an ensemble of few adjacent Ni atoms around a CHX adspecies issued from CO dissociation. Here the "active site" description is directly deduced from the SSITKA curves modeling, without any direct information on the precise structure of the Ni ensembles allowing the CO activation and its further hydrogenation into methane. Note in addition that a carbide-like pool of C stored within the Ni particles during the initial period on methanation stream might also participate to the methanation process. As a matter of fact, a carbide like layer (Ni3C) was shown to build around the Ni particles as soon as the methanation reacting mixture was admitted on a fresh catalyst, by using a special reactor designed for allowing in situ magnetic measurements [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF]. This result was obtained by relating i) the loss of ferromagnetism of a freshly reduced sample after contact with the methanation mixture (Ni carbide is no more ferromagnetic) and ii) the amount of C deposits measured by TPO. In order to discuss a step further the methanation mechanism in the absence of poison, let us quote an important statement about active site structure on group VIII metals as proposed by Ojeda et al [START_REF] Ojeda | CO activation pathways and the mechanism of Fischer-Tropsch synthesis[END_REF]. Here two types of CO activation modes are assumed to occur in the presence of hydrogen as depicted in Fig 7. A close H-assisted model was also recently proposed by Quindimil et al [START_REF] Quindimil | Intrinsic kinetics of CO2 methanation on low-loaded Ni/Al2O3 catalyst: Mechanism, model discrimination and parameter estimation[END_REF] for the CO2 methanation reaction over Ni/Al2O3, also involving rate determining steps such as the step 6 of the above model. On the basis of our own SSITKA analyses on Ni/Al203 and of the above proposal of two modes for CO activation (steps 3 and 6 in Fig. 7), we tentatively assume that, at least for the present case of Ni-based catalysts, the two processes are competing, depending on the active site structure for the initial surface carbonyl formation, either as bridged or linearly adsorbed species. In that respect, one could consider that on particle defects (steps, kinks, corners, etc) the bridged CO adsorption unassisted by hydrogen would be thermodynamically and kinetically more favored than on flat and defect-free surfaces. Inversely, linear carbonyl species adsorbed on flat terraces would require H-assistance for dissociation. Such a statement agrees with the DFT calculations and experimental data reported in the literature [START_REF] Andersson | Structure sensitivity of the methanation reaction: H2-induced CO dissociation on nickel surfaces[END_REF][START_REF] Ge | Adsorption and Activation of CO over Flat and Stepped Co Surfaces: A First Principles Analysis[END_REF][START_REF] Qi | Discrimination of the mechanism of CH4 formation in Fischer-Tropsch synthesis on Co catalysts: a combined approach of DFT, kinetic isotope effects and kinetic analysis[END_REF] The above reasoning might explain the present observation revealed by the SSITKA analysis showing two distinct types of dynamics during the methanation process: -on freshly reduced samples, i.e., on small and rough particles, the "direct dissociation process" would dominate for CO activation. In addition, multi carbonyl formation would occur on defects such as corner and edge Ni atoms leading to tetra-carbonyl gaseous species explaining the nickel transfer from small to large particles as described in [START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF], -on aged samples, where step defects develop between smooth terrace-like planes, the two modes for CO activation, H-assisted and direct dissociation processes, would co-exist. The H-assisted process would be favored on the flat planes and terraces, while the direct dissociation of CO would be favored on steps and surface defects. A schematic view of these two CO activation processes occurring during methanation on Ni-based catalysts in the presence of hydrogen but in the absence of poisons is presented in Fig 8. ii) Specificity of the tested poisons on surface dynamics. On the basis of the above reasoning, one can now schematize the observed impact of the various tested poisons on the SSITKA dynamics: -In the presence of a mild poison such as nitrogen containing molecules (ammonia or acetonitrile type) the probability for CO hydrogenation into CHx and further on into methane is slightly decreased by the presence of weakly adsorbed nitrogen around all types of active sites. This weak and non-selective adsorption would decrease only slightly the sites reactivity, as suggested by the rather unchanged SSITKA dynamics. As such, the N-based poisoning can be considered as structure insensitive. -In the presence of a strong but reversible poisoning by chlorine containing compounds (trichloroethylene type), Cl -ions would preferentially adsorb on or close to the step/defects sites. That specificity was also proposed by Paredes-Nunez et al in [START_REF] Paredes-Nunez | Origins of the poisoning effect of chlorine on the CO hydrogenation activity of alumina-supported cobalt monitored by operando FT-IR spectroscopy[END_REF] assuming that the strength of the C-O bond in carbonyl adspecies on metal particles (Co for that case) was increased in the presence of chlorine, due to a weaker electron back-donation from the metal d-orbitals into the CO anti-bonding π* molecular orbital. Thus, by increasing the C-O bond strength, the direct CO dissociation would logically be slowed down. As such, this specific chlorine effect would explain that the SSITKA semi-log transform typical of sintered samples more or less vanishes after Cl -poisoning. Fig. 9 illustrates that specific effect of chlorine ions on defects sites carbonylation, such as steps between flat planes, which makes that poisoning type as structure sensitive. Step sites and defects, typical of small particles, but also developing on sintered particles, favoring the unassisted CO activation  Plane sites, typical of large sintered particles favoring the H-assisted process -For the case of toluene and other aromatics, the absence of measurable poisoning effects either on conversion rates or intrinsic kinetic parameters can be assigned to the weak chemical interaction of these aromatics with the metallic or more precisely already carbided surface (essentially via π-bonding close to physical adsorption). As such, only a further polymerization and severe coking leading to external carbon deposits (filament type) favored at increasing temperature might generate a poisoning effect by hindering the diffusion to and from the surface of the active methanation components. In a word, the C-based poisoning can be considered as structure insensitive.

Conclusion

For understanding the role of metal sintering combined with poisoning during the methanation reaction on Ni based catalysts, a rationale of complex aging processes is proposed by using SSITKA dynamics analysis. In the absence of metal poisoning, the changes in the log transforms of the methane SSITKA response is shown to correspond to the continuous changes in the Ni particles morphology via sintering with the Ni transfer from small to large particles as gaseous nickel carbonyl. This morphological aging results in the formation of raft-like larger particles developing step defects, while the smaller and smaller ones are characterized by a higher concentration of surface defects. The sensitivity of the SSITKA dynamics to such deep morphological changes is revealed by a simple change in the semi-log transform slopes of the methane SSITKA responses under overall steady-state kinetic conditions. On that basis, such a statement was further used as a tool for characterizing surface poisoning issued from the biomass gasification before syngas methanation. Here, the various toxicities and poisoning modes of C-N-and Cl-containing molecules were revealed as well by the changes in the SSITKA dynamics. A common explanation is proposed, based on the assumption of two distinct nickel surface sites associated with two different modes of CO activation on a metal surface, as proposed in the literature: an H-assisted and a non-assisted CO activation. The direct CO activation, leading to CO dissociation into surface carbide and adsorbed oxygen, would be favored for bridged carbonyl species on step and edge sites, present both on small and sintered metal particles. The H-assisted CO activation leading to H-CO* intermediates, would happen essentially on sites favoring the density of adsorbed hydrogen around carbonyl adspecies. We assume these sites to develop on terrace sites, typical of sintered particles. From the above statement combined with the observed SSITKA dynamics for the typical poisons tested for methanation, it was deduced that N-containing poisons were only weakly toxic due to weak and unselective adsorption on Ni particles, small or large. In contrast, from quite distinct SSITKA dynamics, the poisoning by Cl containing molecules, such as trichloroethylene, was found much more toxic, especially on large particles, suggesting a preferential poisoning on defects zones for this kind of molecules, typical of a structure sensitive behavior. Finally, carbon deposition induced by toluene decomposition as typical of a third potential type of poisoning was shown to be ineffective for methanation rate, probably due to the fact that the carbonaceous deposits typical of aromatics decomposition (carbon veil and/or filaments) do not change the intrinsic geometry of the Ni sites responsible for CO activation. Therefore, both N-and C-based poisoning can be considered as structure insensitive. As such, this study revealed the efficiency and selective sensitivity of SSITKA dynamics, which then appears to be an efficient tool to detect and unravel complex and low-noise aging phenomena. Combined with a full kinetic modeling as already proposed, this methodology sounds quite well adapted to the new trends in chemistry, which deals with more and more poisons containing feedstocks such as bio-and waste ones.

Figure 1 :

 1 Figure 1 : TEM images and corresponding particle size distribution of A/ freshly reduced Ni/Al2O3 catalyst then reacted for 1h, and B/ reacted catalyst for 164h on methanation stream

Figure 2 :

 2 Figure 2 : CO conversion versus time on stream (TOS) with a 15%CO/60%H2/25%Ar reaction mixture, at a total flowrate of 100 mL/min and at 225 °C. SSITKA experiment were performed at 4 different TOS (2h, 50h, 72h, 164h) corresponding to the conversion data reported in the figure.

  Figure shows typical SSITKA responses at 225°C and 1.2 bar.

Figure 3 :

 3 Figure 3 : Normalized concentration of Kr,12 CO,13 CO, 12 CH4, 13 CH4 as a function of time during 12 CO+H2→13 CO+H2 SSITKA experiment at 225°C after 2h on methanation stream. Similar experimental conditions as in Figure2

Figure 4 :

 4 Figure 4 : Normalized concentration of 13 CO and Kr(dotted line) as a function of time during 12 CO+H2→ 13 CO+H2 SSITKA experiment at 225°C after 2h, 50h, 72h and 164h on methanation stream. Similar experimental data as in Figure 2

Figure 5 :

 5 Figure 5: Semi-log transforms of the 12 C content decay in CH4 response as a function of time during 12 CO+H2→ 13 CO+H2 SSITKA experiment at 225°C after 2h and 50h on methanation stream

  These results can be analyzed as follows: -The reference curve, registered for the pure feed in the absence of any poison (Fig 6A), displays two zones for the log transform, corresponding to a domain with two well differentiated zones as depicted in Fig 5 for used catalysts.

Figure 6 :

 6 Figure 6: Normalized log decay of 12 C content in to CH4 as a function of time during 12 CO+H2→ 13 CO+H2 SSITKA experiment at 225°C on fresh samples: (A) Pure feed, (B) with 0.13% acetonitrile, (C) with 0.23% trichloroethylene, (D) with 0.23% toluene. Similar experimental data as in Figure 2.

Fig 7 :

 7 Fig 7: Mechanistic scheme proposed by Ojeda et al [Error! Bookmark not defined.] for CO hydrogenation process over group VIII metal particles.A close H-assisted model was also recently proposed by Quindimil et al[START_REF] Quindimil | Intrinsic kinetics of CO2 methanation on low-loaded Ni/Al2O3 catalyst: Mechanism, model discrimination and parameter estimation[END_REF] for the CO2 methanation reaction over Ni/Al2O3, also involving rate determining steps such as the step 6 of the above model. On the basis of our own SSITKA analyses on Ni/Al203 and of the above proposal of two modes for CO activation (steps 3 and 6 in Fig.7), we tentatively assume that, at least for the present case of Ni-based catalysts, the two processes are competing, depending on the active site structure for the initial surface carbonyl formation, either as bridged or linearly adsorbed species. In that respect, one could consider that on particle defects (steps, kinks, corners, etc) the bridged CO adsorption unassisted by hydrogen would be thermodynamically and kinetically more favored than on flat and defect-free surfaces. Inversely, linear carbonyl species adsorbed on flat terraces would require H-assistance for dissociation. Such a statement agrees with the DFT calculations and experimental data reported in the literature[START_REF] Andersson | Structure sensitivity of the methanation reaction: H2-induced CO dissociation on nickel surfaces[END_REF][START_REF] Ge | Adsorption and Activation of CO over Flat and Stepped Co Surfaces: A First Principles Analysis[END_REF][START_REF] Qi | Discrimination of the mechanism of CH4 formation in Fischer-Tropsch synthesis on Co catalysts: a combined approach of DFT, kinetic isotope effects and kinetic analysis[END_REF] The above reasoning might explain the present observation revealed by the SSITKA analysis showing two distinct types of dynamics during the methanation process: -on freshly reduced samples, i.e., on small and rough particles, the "direct dissociation process" would dominate for CO activation. In addition, multi carbonyl formation would occur on defects such as corner and edge Ni atoms leading to tetra-carbonyl gaseous species explaining the nickel transfer from small to large particles as described in[START_REF] Agnelli | CO Hydrogenation on a Nickel Catalyst I. Kinetics and Modeling of a low temperature sintering process[END_REF], -on aged samples, where step defects develop between smooth terrace-like planes, the two modes for CO activation, H-assisted and direct dissociation processes, would co-exist. The H-assisted process would be favored on the flat planes and terraces, while the direct dissociation of CO would be favored on steps and surface defects. A schematic view of these two CO activation processes occurring during methanation on Ni-based catalysts in the presence of hydrogen but in the absence of poisons is presented inFig 8.

Figure 8 :

 8 Figure 8 : Scheme of the two main types of active sites on Ni particles for CO activation in the methanation process. Multi-carbonyl sites leading to Ni transport via Ni(CO)4 are not included.

Fig. 9 :

 9 Fig. 9: Scheme of active sites developing on step sites inhibited in the presence of chlorine, reinforcing the C=O bonding via electron transfer to the Cl ions (adapted from Fig 8 in [Error! Bookmark not defined.])

Table 1 :

 1 ). Concentration of poisoning species determined from operating conditions (flowrate and saturator temperature).

		Tsaturator[°C]	PPMV	%vol*
	Acetonitrile(C2H3N)	10	2340	0.23
	Trichloroethylene(C2HCl3) 0	1328	0.13
	Toluene(C7H8)	22	1345	0.13
	*Total Flowrate=100mL/min

Table 2 Amounts

 2

of reversibly adsorbed CO and of reacting intermediates CHx determined by SSITKA experiments at 225°C and H2/CO=4, in the absence of any poison. The surface coverage θCO and θCHx are calculated by dividing the surface concentration N (µmol/gcat) values by the number of surface Ni atoms NiS determined from TEM dispersion measurements, i.e. assuming a surface stoichiometry CO/NiS = CHx/Nis= 1 and the evolution of metal phase dispersion proportionally to the TOS.

Table 3 :

 3 reports the slope obtained from the semi-log transform regression. SSITKA conditions a Slope parameter (a) obtained from the linear regressions of semi-log transforms of methane responses in SSITKA experiments (y=ax +b). * symbol means that only one linear model was observed for that case.

	Without added poisons	-0.0141	-0.0022
	+ 0.13% acetonitrile	-0.0096	-0.0045
	+ 0.23% trichloroethylene	-0.0096	*
	+ 0.13% toluene	-0.0151	-0.0011

5 Acknowledgements: This work was partly supported by the French National Agency for Research, project "BioSyngOp", ANR-11-BS07-026. References


Joy Lachat

Gaëlle Lextrait

Romain Jouan

Amira Boukherissa

Aya Yokota

Seonghan Jang

Kota Ishigami

Ryo Futahashi

Raynald Cossard

Delphine Naquin

Vlad Costache

Luis Augusto

Pierre Tissière

Emanuele G Biondi

Benoît Alunni

Tatiana Timchenko

Tsubasa Ohbayashi

Yoshitomo Kikuchi
email: kikuchi@aist.go.jp

Peter Mergaert
email: peter.mergaert@i2bc.paris-saclay.fr

Hundreds of antimicrobial peptides create a selective barrier for insect gut symbionts

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.

Main text

The animal gut is colonized by large numbers of bacteria, which provide essential functions to the host [START_REF] Moran | Evolutionary and ecological consequences of gut microbial communities[END_REF][START_REF] Clemente | The impact of the gut microbiota on human health: an integrative view[END_REF]. Their presence constitutes an immunological challenge and the intestinal epithelium responds to them with the activation of a diversified repertoire of immune effectors [START_REF] Chu | Innate immune recognition of the microbiota promotes hostmicrobial symbiosis[END_REF][START_REF] Hooper | Interactions between the microbiota and the immune system[END_REF]. The members of the microbiota have a coevolved relationship with this active immune system, enabling them to colonize the gut stably [START_REF] Faith | The longterm stability of the human gut microbiota[END_REF][START_REF] Martens | Interactions of commensal and pathogenic microorganisms with the intestinal mucosal barrier[END_REF]. Among the prominent immune mechanisms is the production of AMPs, which are secreted in the gut lumen and come in contact with the microbiota [START_REF] Hu | Small proline-rich protein 2A is a gut bactericidal protein deployed during helminth infection[END_REF][START_REF] Sun | Angiogenin maintains gut microbe homeostasis by balancing α-Proteobacteria and Lachnospiraceae[END_REF][START_REF] Gallo | Epithelial antimicrobial defence of the skin and intestine[END_REF][START_REF] Mergaert | Role of antimicrobial peptides in controlling symbiotic bacterial populations[END_REF]. Thus, gut commensals are expected to be resilient to AMPs [START_REF] Cullen | Antimicrobial peptide resistance mediates resilience of prominent gut commensals during inflammation[END_REF] but how they adapt and how important this is for gut colonization remains largely unexplored.

The bean bug Riptortus pedestris has a particular gut organization, associated with a (nearly) mono-specific microbiota present in the specialized posterior midgut region M4 composed of two rows of crypts branched on a central tract [START_REF] Kikuchi | Insect-microbe mutualism without vertical transmission: a stinkbug acquires a beneficial gut symbiont from the environment every generation[END_REF]. This microbiota is acquired from the environment through feeding. The M4 bacteria are very specific, belonging to the Caballeronia genus and are mostly present as a single colonizer, established through a multifaceted selection process [START_REF] Itoh | Host-symbiont specificity determined by microbe-microbe competition in an insect gut[END_REF][START_REF] Ohbayashi | Insect's intestinal organ for symbiont sorting[END_REF][START_REF] Kikuchi | Burkholderia insecticola triggers midgut closure in the bean bug Riptortus pedestris to prevent secondary bacterial infections of midgut crypts[END_REF][START_REF] Jang | Symbiont coordinates stem cell proliferation, apoptosis, and morphogenesis of gut symbiotic organ in the stinkbug-Caballeronia symbiosis[END_REF]. Among the bean bug colonizers, Caballeronia insecticola has emerged as a model species [START_REF] Takeshita | Burkholderia insecticola sp. nov., a gut symbiotic bacterium of the bean bug Riptortus pedestris[END_REF]. We took advantage of this simplified gut-microbe interaction model to explore how gut bacteria are adapted to resist intestinal AMP challenge.

The Riptortus pedestris midgut produces hundreds of AMPs

A preliminary transcriptome analysis of the M4 midgut region has identified a novel class of secretory peptides, which we call the CCRs [START_REF] Futahashi | Gene expression in gut symbiotic organ of stinkbug affected by extracellular bacterial symbiont[END_REF][START_REF] Ohbayashi | Comparative cytology, physiology and transcriptomics of Burkholderia insecticola in symbiosis with the bean bug Riptortus pedestris and in culture[END_REF]. In order to define the expression pattern of CCR genes, the transcriptome was determined by RNA-seq in midgut regions of insects that were reared for different times in the presence or absence of the C. insecticola gut symbiont (Fig. 1A). Hidden Markov Models based on the previously identified CCR sequences were used to identify in the newly generated transcriptome the complete set of CCR sequences. This analysis revealed 310 CCR transcripts (data S1). The encoded CCR peptides do not show high similarity apart from a pattern of conserved cysteine residues (Fig. 1B). Despite their sequence divergence, AlphaFold2 predicted similar folds for tested CCR peptides, consisting of three pairs of -sheets that are probably connected by cystine bridges (Fig. 1C). Differential expression analysis revealed that the majority of the CCR genes are most strongly expressed in the midguts of symbiotic insects (Fig. 1D, data S1). Subsets of genes were specific for the M3, M4B and the majority for the M4 region carrying the C. insecticola bacteria, suggesting that the encoded peptides target the symbionts. Moreover, the CCRs are among the most strongly expressed transcripts in the overall transcriptome (fig. S1), suggesting a primordial role of the peptides in the midgut. The CCR genes did not exhibit similarity to known sequences of other organisms. However the taxonomically restricted nature of the genes as well as the structure of the CCRs, being small, secreted and characterized by conserved cysteine residues, remind strongly to AMP gene families [START_REF] Mergaert | Role of antimicrobial peptides in controlling symbiotic bacterial populations[END_REF] and AMP prediction tools confirmed this presumption (Fig. 1C, data S1). Whole mount in situ hybridization with the infected-M4-specific gene CCR0043

showed that the gene is expressed uniformly by the epithelial cells in all M4 crypts (Fig. 1E, fig. S2). This pattern contrasts with the mammalian small intestine where specialized cell types at the base of crypts express AMP genes [START_REF] Clevers | Paneth cells: maestros of the small intestinal crypts[END_REF].

Based on the expression pattern and the predicted AMP activity, we selected CCRs for chemical synthesis (Fig. 1C, table S1). These seven CCRs, together with thanatin and riptocin, two known innate immunity-related AMPs of R. pedestris [START_REF] Kim | Insect gut symbiont susceptibility to host antimicrobial peptides caused by alteration of the bacterial cell envelope[END_REF], LL37 and NCR335, from mammal and plant origin respectively [START_REF] Burton | The chemistry and biology of LL-37[END_REF][START_REF] Farkas | Comparative Analysis of the Bacterial Membrane Disruption Effect of Two Natural Plant Antimicrobial Peptides[END_REF] and bacterial polymyxin B (PMB), were tested for growth inhibiting activity against a panel of taxonomically diverse bacterial species Bacillus subtillis, Sinorhizobium meliloti, Paraburkholderia fungorum and C. insecticola. The first two species are unable to colonize the R. pedestris midgut while the latter two can efficiently proliferate in the crypts [START_REF] Itoh | Host-symbiont specificity determined by microbe-microbe competition in an insect gut[END_REF]. In agreement with the bioinformatics predictions, the CCRs had growth inhibiting activity against B. subtilis and S. meliloti although with variable strengths (Fig. 2A,B). On the other hand, the two species, P. fungorum and C. insecticola, that are able to colonize the gut crypts, are not or only weakly affected by the tested CCRs (Fig. 2A,B). This pattern of sensitivity/resistance to CCRs matches with the response of these species to PMB and in part to the other tested peptides. CFU counting showed the bacterial reduction from 10 7 CFU to no colonies after treatment of sensitive S. meliloti with the CCR1659 peptide for a few hours, indicating that the growth inhibition results from a bactericidal activity, similarly as for PMB (Fig. 2C). The bactericidal activity of CCR1659 was abolished by prior Proteinase K treatment of the peptide and inhibited by the presence of the divalent cations Ca 2+ and Mg 2+ , which interfere with the electrostatic interaction of AMPs with negatively charged membrane lipids and diminish the activity of membrane-targeting AMPs (24) (Fig. 2C; fig. S3). To acquire insight in the killing mode of CCR1659, we tested the hypothesis that the peptide disrupt bacterial membranes, like PMB and the other tested AMPs do [START_REF] Poirel | Polymyxins: Antibacterial activity, susceptibility testing, and resistance mechanisms encoded by plasmids or chromosomes[END_REF][START_REF] Moubareck | Polymyxins and bacterial membranes: A review of antibacterial activity and mechanisms of resistance[END_REF][START_REF] Lazzaro | Antimicrobial peptides: Application informed by evolution[END_REF]. Outer and inner membrane integrities in S. meliloti were consecutively damaged by both CCR1659 and PMB treatment, as measured respectively by 1-N-PhenylNaphthylamine (NPN) and Propidium Iodide (PI) uptake leading to enhanced fluorescence (Fig. 2D). In agreement with the membrane disruption, fluorescence microscopy showed that FITC-modified CCR1659 labelled the envelope of S. meliloti cells in a similar way as polylysine-FITC, which is a polycation known to interact with negatively charged membranes of bacteria (Fig. 2E) [START_REF] Spohn | Integrated evolutionary analysis reveals antimicrobial peptides with limited resistance[END_REF][START_REF] Rossetti | Interaction of poly(Llysine)-g-poly(ethylene glycol) with supported phospholipid bilayers[END_REF]. Binding of CCR1659 to the envelope suggests that its killing efficiency depends on the strength of envelope binding. To test this assumption, we measured with flow cytometry the binding level of CCR1659-FITC and polylysine-FITC to the above panel of species. Strikingly, CCR1659sensitive S. meliloti and B. subtilis were strongly labeled with these two molecules while resistant C. insecticola and P. fungorum only weakly (Fig. 2F). Thus, the level of binding to cells is correlated with the susceptibility/resistance pattern. Scanning electron microscopy (SEM) of CCR1659-treated S. meliloti cells further confirmed the membrane-perturbing activity of the peptide that provoked the leakage of fibrous materials from damaged cells similarly as PMB (Fig. 2G; fig. S4). Together, this data reveal that the M4 symbiotic region of the gut produces a remarkably large arsenal of CCR peptides with membrane-damaging AMP activity.

The Caballeronia insecticola genetic repertoire determining AMP resistance

Species that colonize the midgut display a high level of resistance to CCRs and other AMPs suggesting that resistance is a prerequisite for efficient gut colonization. To test this hypothesis, we aimed to identify the resistance determinants in C. insecticola and assess if they control gut colonization. A transposon mutant library [START_REF] Jouan | Transposon sequencing reveals the essential gene set and genes enabling gut symbiosis in the insect symbiont Caballeronia insecticola[END_REF] was used to perform a Tn-seq screen with PMB, since PMB has a similar membrane action as CCR peptides and is commercially accessible in sufficient quantities for Tn-seq experiments. The screen, performed with three sub-lethal PMB concentrations, resulted in 54 genes whose mutation provoked a fitness defect with the highest concentration. With the lower PMB concentrations, subsets of these genes were identified suggesting a multifactorial resistance with some mechanisms contributing more strongly than others (Fig. 3A,B; fig. S5,data S2). In agreement with the membrane-targeting mode of action of PMB, the majority of fitness genes are involved in the generation of bacterial envelope components, including LPS, peptidoglycan, phospholipids, hopanoids and membrane protein machineries. In order to validate the Tn-seq results, we constructed insertion and deletion mutants in 11 genes selected among the 54 PMB fitness genes. These genes are predicted to be involved in the biosynthesis of the LPS core (dedA, waaC and waaF) [START_REF] Kim | The lipopolysaccharide core oligosaccharide of Burkholderia plays a critical role in maintaining a proper gut symbiosis with the bean bug Riptortus pedestris[END_REF][START_REF] Panta | A DedA family membrane protein is required for Burkholderia thailandensis colistin resistance[END_REF][START_REF] Panta | A link between pH homeostasis and colistin resistance in bacteria[END_REF], LPS O-antigen (wbiF, wbiG, wbiI, wzm and rfbA) [START_REF] Kim | The symbiotic role of O-antigen of Burkholderia symbiont in association with host Riptortus pedestris[END_REF], peptidoglycan (dedA), membrane protein machineries (tolB and tolQ) [START_REF] Sit | Undecaprenyl phosphate translocases confer conditional microbial fitness[END_REF][START_REF] Szczepaniak | The multifarious roles of Tol-Pal in Gramnegative bacteria[END_REF], in addition to a gene (tpr) encoding a tetratricopeptide repeat protein of unknown function. Complementing strains were constructed for some of the mutants.

Sensitivity assays with PMB and colistin (COL), another polymyxin-family AMP, confirmed that each mutant had an 8-to 32-fold increased sensitivity compared to the WT (Fig. 3C) while the complemented mutants were restored to WT-levels (fig. S6). Thus, the Tn-seq analysis correctly identified genetic determinants for PMB resistance in C. insecticola.

In line with the sensitivity of the mutants to PMB and the membrane-attacking properties of CCRs, we found that all mutants were more sensitive than WT for at least one of the tested CCR peptides and the other available AMPs (Fig. 3C,D). The tolB and tolQ mutants were the least sensitive and displayed only a slight difference compared to WT for all tested peptides.

The dedA and tpr mutants were strongly affected by the CCR1659 peptide (Fig. 3D) and moderately by the other tested peptides. The mutants wzm, wbiF, wbiG, wbiI and rfbA were sensitive to several of the tested CCRs although in many cases, enhanced sensitivity was not resulting in a complete growth inhibition but in a retarded and lesser growth compared to untreated control and the WT grown with the same peptide concentration. The waaC and waaF mutants were the most strongly affected, being more sensitive than WT to all tested peptides and at higher peptide concentrations, their growth was completely blocked (Fig. 3D). Taken together, the C. insecticola genes that were revealed by the PMB Tn-seq screen, contribute also to resistance towards other membrane-attacking AMPs, including the CCRs.

Because the tested AMPs interfere with bacterial membrane function, we characterized the cell envelope of the mutants. Since some of the mutated genes are known or suspected to be involved in LPS biosynthesis, we analyzed the LPS structure of all mutants by PAGE profiling and by mass spectrometry analysis of their lipid A moiety, which is proposed to be a direct target of PMB (25,26) (Fig. 4A,B). The tpr, dedA and tolQ mutants had a PAGE LPS profile that was indistinguishable from the WT. The wzm, rfbA, wbiF, wbiG and wbiI mutants produced a similar LPS that lacked the O-antigen but had a lipid A/core oligosaccharide moiety that was indistinguishable from WT while the waaC and waaF mutants had an altered lipid A/core moiety, in agreement with the predicted heptosyl-transferase activity of the encoded enzymes that perform the first steps of the core oligosaccharide synthesis. Mass spectrometry analysis of the lipid A moieties suggested that none of the mutants had an altered lipid A structure and notably, that all mutants produced lipid A carrying the 4-amino-4-deoxy-L arabinose (Ara4N) modification that is known to confer PMB resistance in related species (Fig. 4B; fig. S7) [START_REF] Panta | A DedA family membrane protein is required for Burkholderia thailandensis colistin resistance[END_REF][START_REF] Panta | A link between pH homeostasis and colistin resistance in bacteria[END_REF][START_REF] Valvano | Remodelling of the Gram-negative bacterial Kdo2-lipid A and its functional implications[END_REF].

We assessed the steady-state outer membrane integrity of the mutants by NPN labeling and sensitivity to detergents (fig. S8). The waaC and waaF mutants had a higher NPN-derived fluorescence and slightly higher sensitivity to the non-ionic detergent Triton X100 and the cationic detergent CTAB than the WT, while the other mutants were similar to WT. The tolB and tolQ mutants on the other hand were more sensitive to the anionic detergent SDS than to other tested strains. Overall, this indicates that although the outer membrane in some mutants has a reduced robustness, the AMP sensitivity of the mutants is not a direct consequence of a generic membrane instability but of the deficiency of specific resistance mechanisms. The capacity of the bacterial envelope to bind membrane-disrupting AMPs is a parameter influencing AMP sensitivity. The waaC and wbiF LPS mutants showed indeed a strong labeling of their envelope with CCR1659-FITC, contrary to the WT that did not show any labelling (Fig. 4C). However, the tpr mutant was also not labeled. Therefore, we quantified the relative capacity of the envelope of all the mutants to bind membrane-disrupting AMPs by labeling the cells with the fluorescent polylysine-FITC peptide or CCR1659-FITC, followed by flow cytometry analysis (Fig. 4D). All the mutants with altered LPS (waaC, waaF, wzm, rfbA, wbiF, wbiG and wbiI) had a strongly enhanced labeling with both peptides indicating a more accessible cell surface for AMP binding. However, the dedA and tpr mutants displayed a peptide labeling that was identical to the WT while the tolB and tolQ mutants were even labelled less intensively. Thus, the LPS mutants might be more sensitive to the AMPs because of the higher accessibility of their membranes for interactions with AMPs but the sensitivity of the dedA, tpr and tolBQ mutants has to be explained by a different mechanism. Interestingly, cryptcolonizing C. insecticola bacteria have lost their O-antigen after establishing in the crypts [START_REF] Kim | Insect gut symbiont susceptibility to host antimicrobial peptides caused by alteration of the bacterial cell envelope[END_REF] and thus have an LPS that is similar to the LPS of the wzm, rfbA, wbiF, wbiG and wbiI mutants.

In agreement, bacteria isolated from the crypts are hypersensitive to PMB and the CCR1659 peptide (Fig. 3C,D) and they strongly bind polylysine-FITC and CCR1659-FITC (Fig. 4D).

To confirm that the set of mutants are affected in different pathways for AMP resistance, we created the waaC/tpr, waaC/dedA and waaC/wbiF double mutants. We reasoned that if genes are part of the same pathway, double mutants should not show an additive phenotype compared to the single mutants, while in case genes are in separate pathways, double mutants might display a more severe phenotype than single mutants. We found that the three double mutants were more sensitive than the corresponding single mutants to PMB and CCR1659 and bound more CCR1659-FITC (fig. S9), suggesting that indeed "waaC and tpr" or "waaC and dedA" or "waaC and wbiF" define different pathways to PMB resistance. The synthetic phenotype of the waaC/wbiF mutant further suggest that the LPS core and the O-antigen constitute two distinct barriers for AMPs to reach the membrane. SEM of untreated WT and tpr, dedA, tolB, waaC and wzm mutants showed that the mutants affect the bacterial envelope in various ways (fig. S10). SEM of CCR1659-treated cells reveals that the response to the peptide in the waaC and tpr mutant is markedly different. In the waaC mutant, very strong membrane distortions are visible and frequent cell lysis, indicated by the cellular material released from cells. The tpr mutant on the other hand shows only minor modifications on the cell surface, similar to WT, although infrequent release of large amounts of cellular material was also observed (Fig. 4E). Collectively, the properties of the single and double mutants suggest that in C. insecticola different mechanisms contribute to AMP resistance.

AMP resistance in Caballeronia insecticola is crucial for midgut colonization

Since the midgut crypts are the site of intensive AMP production, we next analyzed the capacity of the AMP sensitivity mutants to colonize the M4 midgut region of the R. pedestris midgut.

As a preliminary test and to exclude that gut colonization phenotypes can be attributed to trivial reasons, we confirmed that each mutant has similar growth patterns as WT (fig. S11A) and is motile (fig. S11B) since motility is crucial for colonization of the M4 crypts [START_REF] Ohbayashi | Insect's intestinal organ for symbiont sorting[END_REF]. Analysis at 5 days post infection (dpi) of second instar nymphs showed that the 11 mutants had the capacity to colonize the crypts although they were to various extends less efficient than the WT. The WT had a 100% efficiency (n=10) and the number of bacteria per gut was consistently high (>10 7 genome copies per gut). In contrast, the mutants displayed a large variability in colonization level between insect individuals, ranging from a wild-type colonization level for some individuals to a failure to establish in the crypts in other individuals (Fig. 5A). The waaC and tpr mutants were particularly affected in agreement with their strong AMP sensitivity. This intriguing probabilistic colonization of the gut by the mutants is reminiscent to stochastic colonization of the Drosophila gut by underperforming Lactobacillus plantarum strains while a strong colonizer strain had a 100% efficiency [START_REF] Obadia | Probabilistic invasion underlies natural gut microbiome stability[END_REF].

Next, the fitness of the mutants in M4 colonization was evaluated when they were in competition with WT. Insects were infected with fifty-fifty mixtures of RFP-marked WT and one of the mutants (or WT as a control) that were marked with GFP. The outcome of the competitions was analyzed at 5 dpi by fluorescence microscopy of dissected M4 midguts and flow cytometry quantification of their bacterial content (Fig. 5B). In the control competition, RFP-and GFP-marked WT were kept in balance. However, in competitions with the mutants, the WT nearly completely outcompeted each of them, confirming their reduced colonization capacity.

Finally, we also tested if the mutants have a reduced capacity to outcompete a less efficient crypt colonizing species. We previously showed that P. fungorum can colonize the M4 crypts but that it is outcompeted by C. insecticola [START_REF] Itoh | Host-symbiont specificity determined by microbe-microbe competition in an insect gut[END_REF]. Here, the outcompetition of P. fungorum by C. insecticola WT in co-infection experiments was confirmed while wzm, waaC, tolB, tpr and dedA mutants were significantly less efficient in outcompeting P. fungorum (Fig. 5C). Thus, high AMP resistance in C. insecticola is an important factor contributing to the efficiency of this strain in occupying the R. pedestris gut.

We conclude from these infection experiments that the reduced resilience to AMPs of mutants in different resistance mechanisms makes them less apt to colonize the midgut crypts.

Presumably, AMP resistance is critical during the initial infection stages, from the entering of a few hundred cells into the crypt region to the rapid multiplication in two to three days of this founder population to a crypt-space-filling population of about 10 7 -10 8 bacteria [START_REF] Kikuchi | Burkholderia insecticola triggers midgut closure in the bean bug Riptortus pedestris to prevent secondary bacterial infections of midgut crypts[END_REF]. Thus the surprisingly large diversity of CCR peptides, several of them already expressed in the M3 and M4 before the microbiota establishment, could be an adaptation to create a selective environment, restricting the bacteria that have a chance to establish in the M4 crypts. This mechanism could favor optimal beneficial Caballeronia strains among the variability of bacteria that the insect can ingest from the environment. Indeed, recent insights have changed the previous view on AMPs as generic, non-specific antimicrobials by the demonstration that they can display a degree of specificity and synergism. Accordingly, AMP repertoires in organisms dynamically evolve according to the diversity of microbes encountered in the natural environment [START_REF] Zasloff | Antimicrobial peptides of multicellular organisms[END_REF][START_REF] Lazzaro | Antimicrobial peptides: Application informed by evolution[END_REF][START_REF] Hanson | Ecology-relevant bacteria drive the evolution of host antimicrobial peptides in Drosophila[END_REF]. On the other hand, once established in the crypts, the bacteria lose their O-antigen by an unknown mechanism [START_REF] Kim | Insect gut symbiont susceptibility to host antimicrobial peptides caused by alteration of the bacterial cell envelope[END_REF], which renders them sensitive to the CCR peptides. This suggests a second function of the CCR peptide arsenal that could be related to the protection of the crypt epithelia and prevention of the bacteria breaching these epithelia. Indeed, in R. pedestris the crypt epithelium lack mucus or peritrophic protective layers and is therefore in direct contact with the microbiota [START_REF] Jang | Symbiont coordinates stem cell proliferation, apoptosis, and morphogenesis of gut symbiotic organ in the stinkbug-Caballeronia symbiosis[END_REF]. Additionally, the membrane fragilization of the cryptbacteria by the CCR peptides could facilitate the retrieval of nutrients from the bacteria [START_REF] Ohbayashi | Insect's intestinal organ for symbiont sorting[END_REF], suggesting that the insect tames the gut symbionts with the CCRs. Blue-black-yellow heat map of the relative expression profile of the identified CCR genes and white-grey heat map of AMP predictions. Sample identity in the expression heat map is indicated at the top and is according to panel A. AMP prediction tools are Random Forest (RF), Support Vector Machine (SVM), Artificial Neural Network (ANN), AMPpredictor (dbAMP); iAMPpred; Antimicrobial Peptide Scanner (AMPscanner); (AmPEP_v1 and AmPEP_v2). A consensus prediction (6 out of 7 positive predictions) is indicated in the last column. The peptides used for functional characterization are indicated at the right of the heat maps. E. Whole-mount in situ hybridization with a CCR0043 antisense probe on the dissected midgut of a 3 dpi symbiotic insect. Positive signal appears with a blue-brownish color. CCR0043 is specifically expressed in the M4 and uniformly in all crypts. Control in situ hybridizations on the gut of aposymbiotic insects and with a sense probe on symbiotic insects are shown in Supplemental Figure S2.

Fig. 1 .

 1 Fig. 1. CCRs are symbiosis-specific AMP-like peptides. A. Experimental setup for transcriptome analysis. First day second instars were divided in two groups. To one of them, C. insecticola symbionts were administered (green, Sym) and the other group remained free of symbionts (blue, Apo). Insects were dissected in the second (1, 2, and 3 days post inoculation [dpi]) or fifth instar (12 dpi) and the M3, M4B and M4 regions were harvested for transcriptome analysis. The pictures at the right show representative guts of a Sym insect at 3 dpi (top) and a same age Apo insect (bottom). B. Logo profile of the mature CCR peptides identified in the transcriptome, highlighting the sequence diversity of the peptides and the ten conserved cysteine residues. C. AlphaFold2 structural predictions of examples of CCR peptides showing antiparallel -sheets carrying the cysteine residues. D. Blue-black-yellow heat map of the relative expression profile of the identified CCR genes and white-grey heat map of AMP predictions. Sample identity in the expression heat map is indicated at the top and is according to panel A. AMP prediction tools are Random Forest (RF), Support Vector Machine (SVM), Artificial Neural Network (ANN), AMPpredictor (dbAMP); iAMPpred; Antimicrobial Peptide Scanner (AMPscanner); (AmPEP_v1 and AmPEP_v2). A consensus prediction (6 out of 7 positive predictions) is indicated in the last column. The peptides used for functional

Fig. 2 .

 2 Fig. 2. CCR peptides are membrane-targeting AMPs. A. Growth inhibition of the indicated bacterial species by different concentrations of CCR1659. Error bars are standard deviations (n=3). B. Minimal concentrations (in µM) of growth inhibition of the indicated strains by various peptides. C. Bactericidal activity of 25 µM CCR1659 and 25 µM PMB. PK: proteinase K; Ca 2+ : activity in the presence of 5 mM CaCl2; Mg 2+ activity in the presence of 5 mM MgCl2. Error bars are standard deviations (n=3). D. NPN and PI uptake by S. meliloti cells in response to treatment with 10 µM CCR1659 or 10 µM PMB in the presence or absence of 5 mM MgCl2. NPN is a lipophilic dye that fluoresces in hydrophobic environments such as bacterial phospholipids exposed by outer membrane damage; PI is a membrane impermeant DNAintercalating dye that fluoresces upon DNA binding in the cytoplasm, indicative of permeabilisation of both the outer and inner membrane. Error bars are standard deviations (n=3). E. Fluorescence microscopy (left) of S. meliloti cells treated with Polylysine-FITC or CCR1659-FITC at the indicated concentrations. Corresponding bright field images are shown at the right. F. Flow cytometry analysis of Polylysine-FITC (top) or CCR1659-FITC binding by the indicated strains. Light purple histograms are control measurements without fluorescent label (-label); the dark purple histograms are in the presence of the fluorescent label (+label). G. SEM micrographs of untreated S. meliloti cells (left) or treated with 1.5 µM CCR1659 (middle) or with 3.6 µM PMB (right). The arrows indicate cellular material released from cells. The double arrowheads indicate cells with lost turgor.

Fig. 3 .

 3 Fig. 3. Identification of AMP resistance genes by Tn-seq. A. Heat map showing the level of depletion of transposon insertions in the indicated genes in the C. insecticola population grown in the presence of PMB at the indicated concentrations. The color-code scale indicates the log2 fold change in the insertion abundance under the test conditions relative to the control conditions. B. IGV view of Tn-seq sequencing data for a selected genomic region of C. insecticola. The histograms indicate the abundance of mutants in the Tn-seq population for the indicated samples. Genes whose products contribute to PMB resistance have a lower frequency of Tn insertions in peptide treatment screens than in the control. C. Mutants in selected genes are hypersensitive to AMPs. Heat map and minimal concentrations of growth inhibition of the indicated wild-type and mutant strains by the listed peptides. Minimal concentrations are indicated in µM. The color key of the heat map is as indicated at the right. Grey cells indicate not tested. D. Growth inhibition of the indicated strains by different concentrations of CCR1659. Gut indicates crypt-colonizing C. insecticola bacteria, directly isolated from dissected M4. Error bars are standard deviations (n=3).

Fig. 4 .

 4 Fig. 4. Surface properties of the AMP-sensitive mutants. A. Polyacrylamide gel electrophoresis analysis of total LPS extracted from the indicated strains. The waaC/waaC strain is the complemented mutant. Despite the altered core in the waaC mutant, an O-antigen ladder is visible, that has a similar profile to the wild type, possibly corresponding to the O-

Fig. 5 .

 5 Fig. 5. AMP-sensitive mutants are impaired in gut colonization. A. Single-strain infections of R. pedestris second instar nymphs with C. insecticola WT or indicated mutants or no bacteria (apo). Colonization of the M4 crypt region was determined at 5 dpi by dissection and microscopy observation of the guts and symbiont titer determination by qPCR in M4 total DNA extracts. The % above the dot plots indicate the proportion of insects that showed colonization by microscopy observation (n=10). The qPCR measurements for each individual insect are indicated by green dots and the mean per mutant is indicated by a horizontal black line. B. Coinfections of R. pedestris with an equal mix of RFP-labelled C. insecticola WT and indicated GFP-labelled WT or mutant strains. Relative abundance of the two strains in the M4 midgut regions at 5 dpi was determined by flow cytometry on dissected intestines. The competition index expresses for all samples the ratio of WT to the indicated mutant, corrected by the ratio of the inoculum, which was in all cases close to 1. Each dot represents the competition index in an individual and the mean per mutant is indicated by a horizontal black line (n=10). C. Coinfections of R. pedestris with a 1:1 mix of GFP-labelled P. fungorum and indicated mScarlett-I-labelled WT or mutant C. insecticola. Relative abundance of the two strains in the M4 midgut regions at 5 dpi was determined by flow cytometry on dissected intestines. The competition index expresses for all samples the ratio of P. fungorum to the indicated mutant, corrected by the ratio of the inoculum, which was in all cases close to 1. Each dot represents the competition index in an individual and the mean per mutant is indicated by a horizontal black line (n=10). In all panels, different letters indicate statistically significant differences (P<0.05). Statistical significance was analyzed by Kruskal-Wallis test, Dunn post hoc test and Benjamini-Hochberg correction.

Acknowledgements

We are grateful to Olga Soutourina (University Paris-Saclay, France) and Yu Matsuura (University of the Ryukyus, Japan) for critical reading of the manuscript and constructive comments. This work benefited from financial support by Saclay Plant Sciences-SPS, by the ANR grant ANR-19-CE20-0007, and by a JSPS-CNRS Bilateral Open Partnership Joint Research Project (18KK0211) and a CNRS International Research Project to Y.K. and P.M. Y.K. was supported by the MEXT KAKENHI (21K18241, 22H05068). J.L., G.L. and R.J. were supported by Ph.D. fellowships from the French Ministry of Higher Education, Research, and Innovation and A.B. benefited from a PhD contract in the frame of the CNRS 80|PRIME -2021 program. This work was supported by JSPS Research Fellowships for Young Scientist to S.J. (21F21090), K.I. (22KJ0057) and T.O (14J03996, 20170267 and 19J01106). Tn-seq sequencing and data treatment were performed by the I2BC high-throughput sequencing facility, supported by France Génomique (funded by the French National Program Investissement d'Avenir ANR-10-INBS-09). This work has benefited from the facilities and expertise of MIMA2 (Université Paris-Saclay, INRAE, AgroParisTech, 78350, Jouy-en-Josas, France).

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