Damien Tedoldi
email: damien.tedoldi@insa-lyon.fr

Rayan Charafeddine

Philippe Branchu

Eric Thomas

Marie-Christine Gromaire

Intra-and inter-site variability of soil contamination in road shoulders -Implications for maintenance operations

Keywords: Metals, Polycyclic Aromatic Hydrocarbons (PAHs), Road runoff, Roadside soil, Stormwater management, Traffic

This study addresses soil contamination in vegetated road shoulders with diffuse inflow of runoff. It aims (i) to characterize the spatial distribution of three metals (copper, lead, zinc) and PAHs, and (ii) to identify influencing factors for the inter-site differences. An extensive sampling campaign was carried out on forty road segments in the Paris region, targeting various distances and soil depths. Copper and zinc contamination was found to be mainly restricted to the first 30 cm from the road, where their concentrations ranged respectively between 40-270 mg.kg -1 and 150-950 mg.kg -1 (with a few additional extreme values related to the presence of a galvanized steel guardrail). Lead contamination was moderate (< 100 mg.kg -1 in more than 75% of the sites) and relatively uniform across the width of the shoulders.

Conversely, highest PAH concentrations were found further from the road. These differences between contaminants were likely due to the varying importance of wet weather-related processes and atmospheric transport in their dispersion mechanisms. Copper and zinc concentrations correlated well with the traffic density, which alone explained ≥ 69% of the inter-site variability, whereas lead and PAHs did not exhibit such dependence. Soil organic matter was found to control the "ceiling" concentration of metals, thus limiting the maximum amounts that can be intercepted from road runoff. These results illustrate the feasibility of estimating contamination levels on road shoulders, and thus offer interesting perspectives for better consideration of the infrastructures' maintenance needs and improved routine operations.

INTRODUCTION

In road environments, especially medium-sized roads, stormwater management is generally achieved via a roadside ditch, connected to detention/infiltration basins or other structural Best Management Practices.

However, where the road shoulderi.e., the space between the roadway and the ditchis not covered with asphalt (Fig. 1), it is subject to the progressive formation of a humus and sediment layer, due to vegetation growth and suspended solid accumulation [START_REF] Tedoldi | Zirconium deficit as a tracer of urban sediment accumulation in Sustainable Urban Drainage Systems -Application to the calibration of a filtration model[END_REF]. This layer eventually constitutes an obstacle that compromises the diffuse evacuation of road runoff, and may cause safety hazards during wet weather (flooding of the road, water ponding at low points). Thus, a regular maintenance of the shouldermostly consisting of surface soil scrapingis required in order to preserve the infrastructure's hydraulic functions. These operations generate large amounts of scraped soil that need to be subsequently managed.

Fig. 1 -Typical French configuration of a vegetated road shoulder followed by a longitudinal ditch.

On the other hand, it has been widely documented that road traffic generates ubiquitous and persistent compounds such as trace metals or polycyclic aromatic hydrocarbons (PAHs), which accumulate durably in roadside soils as a result of runoff spreading and infiltration, and atmospheric deposition [START_REF] Dierkes | Pollution retention capabilities of roadside soils[END_REF]. This pervasive contamination brings about several questions regarding the specific requirements for the disposal, treatment or direct reuse of the scraped materials during maintenance operations. This requires addressing (i) the spatial extent of the contaminated area within each road shoulderproviding insight into the feasibility and benefit of implementing differentiated management for "contaminated" and "non-contaminated" soiland (ii) the predictability of the contamination levels from site-specific characteristics.

Despite a relatively abundant literature about roadside soil contamination [START_REF] Kaur | Heavy Metals and Polycyclic Aromatic Hydrocarbons in roadside soil samples: A review[END_REF][START_REF] Werkenthin | Metals in European roadside soils and soil solution -A review[END_REF], focusing on either metalsthe most widely studied ones being copper, lead and zincor PAHs, it is still difficult to identify pragmatic responses to these concerns. First, the intra-site variability of concentrations has rarely been characterized at resolutions fine enough to be of interest regarding the present objective. The number of sampled distances within two meters from the road is often limited to 1 or 2, while the investigated zone reaches up to 10-50 m [START_REF] Chen | Heavy metal concentrations in roadside soils and correlation with urban traffic in Beijing, China[END_REF][START_REF] Wang | Traffic-related trace elements in soils along six highway segments on the Tibetan Plateau: Influence factors and spatial variation[END_REF][START_REF] Yang | Polycyclic aromatic hydrocarbons in air, soil and vegetation in the vicinity of an urban roadway[END_REF]. When finer sampling grids were used, however, it was evidenced that metal concentrations sharply decrease with increasing distance from the inflow zone [START_REF] Legret | Heavy metal deposition and soil pollution along two major rural highways[END_REF]Tedoldi et al., 2017a), so that their accumulation mostly occurs within less than 3 meters from the road [START_REF] Steiner | Modelling heavy metal fluxes from traffic into the environment[END_REF]. Hence, the concentrations measured outside this 3-meter-wide strip are likely to show more uniform distributions [START_REF] Aljazzar | Monitoring of contaminant input into roadside soil from road runoff and airborne deposition[END_REF][START_REF] Jaradat | Contamination of roadside soil, plants, and air with heavy metals in Jordan, a comparative study[END_REF]) and weaker correlations with the site-specific sources of contamination [START_REF] Bernardino | Metal accumulation in roadside soils of Rio de Janeiro, Brazil: impact of traffic volume, road age, and urbanization level[END_REF].

Spatial patterns of PAHs, however, do not appear to be as systematic as for metals: while [START_REF] Yang | Polycyclic aromatic hydrocarbons in air, soil and vegetation in the vicinity of an urban roadway[END_REF] observed a consistently decreasing trend with increasing distance from the road, in other studies, the highest PAH concentrations were not always measured close to the road edge [START_REF] Dierkes | Pollution retention capabilities of roadside soils[END_REF][START_REF] Marusenko | Distribution of Polycyclic Aromatic Hydrocarbons in soils of an arid urban ecosystem[END_REF][START_REF] Piguet | The diffuse infiltration of road runoff: An environmental improvement[END_REF]. [START_REF] Kumar | Distribution behavior and carcinogenic level of some polycyclic aromatic hydrocarbons in roadside soil at major traffic intercepts within a developing city of India[END_REF], who analyzed soil samples collected at 1, 2, and 3 m from various roads, even found different patterns depending on the considered compound. For both metals and PAHs, it appears necessary to better characterize the spatial distribution of soil contamination in the first 2-3 meters from the road, so as to identify, where applicable, the area subject to the highest accumulation.

As regards the inter-site variability of roadside soil contamination, many governing factors have been proposed and investigated so far, but there is no consensus over their effects or relative importance. For metals, traffic density and composition were identified as key factors by [START_REF] Assirey | Impact of traffic density on roadside pollution by some heavy metal ions in Madinah City, Kingdom of Saudi Arabia[END_REF][START_REF] Horstmeyer | Evaluation of site-specific factors influencing heavy metal contents in the topsoil of vegetated infiltration swales[END_REF] and [START_REF] Yassoglou | Heavy metal contamination of roadside soils in the Greater Athens area[END_REF], so was the vehicular speed [START_REF] De Silva | Metal accumulation in roadside soil in Melbourne, Australia: Effect of road age, traffic density and vehicular speed[END_REF], whereas [START_REF] Carrero | Diagnosing the traffic impact on roadside soils through a multianalytical data analysis of the concentration profiles of traffic-related elements[END_REF] and [START_REF] Franco | Distribution of biogenic and non-biogenic trace metals in roadside soils. A study of Uppsala City[END_REF] found metal concentrations to be mostly dependent on the road age. [START_REF] Hiller | Concentrations of selected trace elements in surface soils near crossroads in the city of Bratislava (the Slovak Republic)[END_REF] proposed a double linear regression to predict copper, lead and zinc concentrations from 39 crossroads as a function of both annual average daily traffic and road age (R 2 = 0.17-0.32).

Traffic fluidity has also been proposed as an additional factor since some metals are released to the environment during braking mechanisms [START_REF] Davis | Loading estimates of lead, copper, cadmium, and zinc in urban runoff from specific sources[END_REF]. On one hand, [START_REF] Horstmeyer | Evaluation of site-specific factors influencing heavy metal contents in the topsoil of vegetated infiltration swales[END_REF] observed higher contamination on road crossings and transects that witness stop-and-go traffic, which was also noted by [START_REF] Pérez | Assessment of heavy metals remobilization by fractionation: Comparison of leaching tests applied to roadside sediments[END_REF]. On the other hand, factors such as the presence of road signs [START_REF] Hjortenkrans | New metal emission patterns in road traffic environments[END_REF] and the number of traffic lights [START_REF] Aslam | Heavy metals contamination in roadside soil near different traffic signals in Dubai, United Arab Emirates[END_REF] have also been deemed significant. Additionally, several authors suggested that the direction and intensity of the prevailing winds may contribute to this variability by affecting metal dispersion, since they noticed some differences in the soil contents on either side of the road [START_REF] Alsbou | Heavy metal concentrations in roadside soil and street dust from Petra region, Jordan[END_REF][START_REF] Jaradat | Contamination of roadside soil, plants, and air with heavy metals in Jordan, a comparative study[END_REF].

Inter-site comparisons are somewhat scarcer for PAHs, and their conclusions are non-concordant as well. [START_REF] Kim | Impact of traffic volumes on levels, patterns, and toxicity of polycyclic aromatic hydrocarbons in roadside soils[END_REF] evidenced a positive correlation between PAHs concentrations in roadside soil and traffic density, however the values fell within a narrow range (∑ 16 PAHs between 0.3-1.8 mg/kg) compared to other studiescf. the data synthesized by [START_REF] Marusenko | Distribution of Polycyclic Aromatic Hydrocarbons in soils of an arid urban ecosystem[END_REF]. The influence of traffic density was also supported by the results of [START_REF] Kumar | Distribution behavior and carcinogenic level of some polycyclic aromatic hydrocarbons in roadside soil at major traffic intercepts within a developing city of India[END_REF], and to a lesser extent [START_REF] Marusenko | Distribution of Polycyclic Aromatic Hydrocarbons in soils of an arid urban ecosystem[END_REF]; in the latter case, the most influent factor was found to be soil organic matter. Conversely, [START_REF] Agarwal | Concentration level, pattern and toxic potential of PAHs in traffic soil of Delhi, India[END_REF] noticed a lack of correlation between total PAH concentrations and the soil's organic carbon, and stated that the variations of concentrations could be explained in terms of vehicular composition (two-wheelers, cars, heavy-duty vehicles), as well as immediate surroundings of the road that modify atmospheric transport mechanisms. Similar assumptions were made by [START_REF] Garcia-Flores | Polycyclic Aromatic Hydrocarbons in road-deposited sediments and roadside soil in Tijuana, Mexico[END_REF] to explain their data. [START_REF] Dierkes | Pollution retention capabilities of roadside soils[END_REF] observed a relationship between PAHs and the age of the road shoulders; in their study, the effects of traffic density appeared to be less marked, but it should be mentioned that all samples were not taken at the same distance from the road.

The above-mentioned divergences could be due to different levels of representativeness of the samples collected from one study to another (e.g., different sampling depths or distances from the road, with single or composite samples). In any case, given the absence of recurring correlation in the available literature, soil contamination does not appear to be systematically predictable. This literature overview emphasizes the interest of combining a fine assessment of the site-specific distribution of metals and PAHs in road shoulders with a large panel of study sites. This may (i) confirm the recurring patterns of concentrations within each site, (ii) help identify accurate descriptors of soil contamination among site-specific characteristics, and (iii) provide insight into its consequences in terms of soil management. These are the objectives of the present work, for which the French department of Seine-et-Marne, in the Paris region, has been retained as a study area, targeting 40 shoulders receiving direct runoff from departmental roads with different characteristics.

MATERIAL AND METHODS

Study sites

Seine-et-Marne is a department of ~6,000 km 2 . It is highly urbanized in its western edge which intersects the Paris region, and more rural on the eastern part (Fig. 2). It contains around 4,500 kilometers of roadways managed by the county council. The 40 study sites were spread across all the department's area to encompass most of its soil types and environments: scattered dwellings, open countryside, forest. They were chosen to guarantee a uniform bivariate distribution of two road factors which were deemed relevant and were systematically available from the department's database: the annual average daily traffic (AADT) and the percentage of semi-trucks, which in our panel respectively varied from 900 to 25,000 veh/day and from 2 to 26%. The site characteristics are presented as Supplementary material, Table S1.

So as to specifically target the traffic-related sources of contamination, none of the study sites had a metallic guardrailexcept two of them which were retained for comparison purposesnor had them road signs or street lights along the sampled sections. The latter were chosen in straight and relatively flat areas, which are most likely to induce a diffuse inflow of runoff on the shoulder and limit the influence of the driving style; in particular, the absence of local depression on the road (which could have created a "concentration effect" for runoff) was systematically checked before undertaking soil samplings. The width of the road shoulder varied from 1.5 to 3 mgenerally the roads with low traffic had narrower shoulders. The road sub-base extended under the shoulder to a certain distance, which varied from a few tens of centimeters to > 1 m depending on the traffic characteristics. During road construction, this subbase was covered with topsoil from the site to create a flat shoulder; then the growth of spontaneous vegetation, combined with the accumulation of sediment brought by road runoff, induced a pedogenesis at the soil surface. All study sites were uniformly covered with grass (similar to the example shown in Fig. 1), thus vegetation is not expected to contribute to inter-site variability in soil contamination. The soil depth depended on the geometry of the sub-base: it was often ~2 cm close to the road, and increased with increasing distance. The date of the latest maintenance (i.e., soil scraping) was not always known with precision, but the operation time of each retained site was in any case higher than five years, and almost certainly lower that ten years (usual frequency of such operations).

In order to set some meteorological context, the average annual precipitation depth in the Paris region is ~640 mm/year, and the rainfall distribution is dominated by small events: during the period 1993-2008, 60% of the daily rainfall depths were ≤ 10 mm, and 80% were ≤ 17 mm. A 1-year frequency storm corresponds to 18 mm in 1 h, and 33 mm in 24 h; a 10-year frequency storm corresponds to 32 mm in 1 h, and 61 mm in 24 h (source: Météo France).

Sampling methodology

Field investigations were undertaken between August and December 2018. The sampling methodology was designed to capture the transversal trend of contaminant concentrations, i.e., their distribution with respect to the distance from the road. Soil samples were collected at four to five distances depending on the width of each shoulder (0, 0.3, 0.7, 1.2, and 1.8-3 m whenever possible) with stainless steel sample rings. The sampling depths corresponded to the upper 2 cm, and the underlying layer (2-5 cm) whenever the sub-base was deep enough.

Former assessments evidenced a potential variability of soil concentrations at a given distance from the road (Tedoldi et al., 2017a). In order to mitigate these effects, a mean sample was composited for each investigated distance from 6 different subsamples collected over a 25-m length (Fig. 3); it was then quartered on the field to achieve a 100-g representative sample. The sampling material was cleaned and rinsed twice with ultrapure water between two distances from the road. This procedure led to a maximum of 10 samples in each site (4-5 distances × 1-2 depths).

Fig. 3 -Schematic representation of the methodology for soil sampling and analysis (in the case of metals).

All 10 samples could not be analyzed for PAHs due to cost constraints: it was therefore chosen to retain (i) a composite sample formed by merging the subsamples collected at 0 and 0.3 m, and (ii) a sample collected on the opposite side of the shoulder.

Laboratory analyses

Metals

The soil samples intended for metal analysis were pre-treated according to the international standard ISO 11464 ( 2006), i.e. oven-dried at 40 °C for 7 days, ground with a pestle, then passed through a 2-mm nylon sieve. Elemental analysis was achieved via X-ray fluorescence (XRF) spectrometry (Thermo Scientific, portable Niton™ analyzer XL3t in a standard soil mode, 60 s per beam). Among the analytical range of the apparatus, copper, lead and zinc were retained as tracers of traffic-derived contamination, because of their well-documented relevance in urban and highway stormwater runoff [START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF]. 5 to 6 homogenized subsamples were analyzed independently, thus enabling the repeatability to be checked, then each sample was assigned its average metal concentrations. All soil concentrations (in mg.kg -1 ) presented in the subsequent developments are based on dry mass. The limits of quantification are sample-dependent, as they vary according to the signal received by the analyzer, but they were in any case < 30 mg.kg -1 whatever the metal.

Portable XRF being a non-conventional practice for the elemental analysis of solid samples, a comparison with a reference approach (ICP-based analyses following acid digestion) was carried out on soil samples from three different sites with contrasting characteristics and contamination levels. The results are presented as Supplementary material. For copper and zinc, the data points were distributed on the first bisector (Fig. S1a andc), whereas lead displayed a slight offset (Fig. S1b), indicating that XRF analysis consistently underestimates total Pb contents by ~15 mg.kg -1 . Overall, this comparison showed that combining an advanced pre-treatment method (sample drying, grinding and sieving at 2 mm) and an averaging process of ≥ 5 measurements enabled a satisfying reliability of the XRF-determined concentrations. This good accuracy was confirmed by a comparison with NIST soil standards (i.e., materials with well-characterized composition): relative errors ranged from -12 to 5% for Cu, -7 to 16%

for Zn, and -35 to -13% for Pb (negative values indicate an underestimation of the certified contents).

PAHs

The two samples from each site intended for PAH analysis were sent to an analytical laboratory. The analyzed compounds were the 16 PAHs classified as priority pollutants by the US-EPA: naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)anthracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, dibenzo(ah)anthracene, indeno(123-cd)pyrene, and benzo(ghi)perylene. After fine grinding of the soil samples, PAHs were extracted with a mixture of acetone and dichloromethane, followed by GC/MS analysis. The complete method is referenced in the European standard EN 15527 ( 2008). The limit of quantification was 10 µg.kg -1 for each individual compound except for naphthalene (30 µg.kg -1 ).

Additional details regarding the analytical uncertainties are provided as Supplementary material.

Soil organic matter

Given the importance of soil organic matter (SOM) in the physico-chemical retention of dissolved metals and hydrophobic compounds such as PAHs [START_REF] Turer | Heavy metal contamination in highway soils. Comparison of Corpus Christi, Texas and Cincinnati, Ohio shows organic matter is key to mobility[END_REF], the volatile matter (VM) content often taken as a proxy for SOMwas determined in two surface samples from each site: (i) the closest sample to the road (composed of a mixture of soil and sediment), and (ii) the sample collected at 1.2 m (most likely composed of soil only). 10-g subsamples, previously oven-dried, were calcined at 550 °C for 6 hours, then the volatile matter content was calculated from mass difference.

Estimation of the reference contents in soils

Characterizing the site-specific contamination requires evaluating the reference contents in the soils of the study area. The latter term is preferred to "background contents", as all soils in urban or semi-rural regions undergo diffuse contamination, e.g., due to long-range atmospheric transport. For metals, usual content ranges were estimated from a national database of trace metals in agricultural topsoils called "BDETM":

over the period 2000-2010, ~2300 soil samples were collected within the Seine-et-Marne district and analyzed for eight metals [START_REF] Baize | Content of eight trace metals[END_REF]. The 1 st and 9 th deciles of the measurements were respectively 8-20 mg.kg -1 for copper, 13-28 mg.kg -1 for lead, and 38-68 mg.kg -1 for zinc. For each metal, the 9 th decile was presently retained as a conservative estimate of the reference content, i.e., the exceeding accumulation could be reasonably attributed to site-specific sources of contamination.

As to PAHs, data are available at the national level via a measurement network called "RMQS -Réseau de Mesures de la Qualité des Sols", which conducts long-term monitoring of soil quality based on a regular sampling grid with 2200 points over the entire metropolitan territory [START_REF] Jolivet | Manuel du Réseau de Mesure de la Qualité des Sols (RMQS)[END_REF]. The 1 st and 9 th deciles of ∑ 16 PAHs were respectively 0.13-0.40 mg.kg -1 .

Data availability

The present dataset has been added to an online data repository [START_REF] Charafeddine | Data for "Intraand inter-site variability of soil contamination in road shoulders -Implications for maintenance operations[END_REF].

RESULTS AND DISCUSSION

3.1 Typical patterns of soil contamination in the road shoulders

Metals

Copper, lead and zinc were consistently above the analyzer's limits of quantification. Across all sites, Cu and Zn appeared to be strongly correlated, with Spearman's 𝜌 = 0.93 (𝑝 ≪ 0.01); on average, Zn concentrations were 3 times higher than Cu concentrations, as previously observed by Horstmeyer et al.

(2016) in various roadside swales. This usual Zn/Cu ratio enabled the detection of anomalous behaviors due to additional sources of metals: for instance, in the two sites equipped with a galvanized guardrail, a steep albeit localized increase in Zn concentrations (> 900 mg.kg -1 ) was visible under the guardrail: this resulted in a Zn/Cu ratio > 6 at this point, while the rest of the shoulders did not appear to be impacted. In one site that was adjacent to a cultivated field, Cu concentrations exceeded that of Zn, as a result of which agricultural contamination of copper was suspected (e.g., by copper sulfate).

Within each shoulder, Cu and Zn displayed significant accumulation close to the road, followed by an overall decrease in concentrations with increasing distance; the median ratio between the concentrations found at 0 and 1.2 m was 2:1 (Fig. 4a-b). At the highest distance from the road, their concentrations were approaching the usual content ranges in agricultural soils of Seine-et-Marne. Generally, no significant differences were observable between the surface sample (0-2 cm) and the underlying one (2-5 cm), whatever the distance from the road (Fig. S2). These patterns were however not systematically replicated by Pb, the distributions of which showed a relative uniformity across the entire width of the road shoulders, without the systematic buildup close to the road that characterized Cu and Zn behavior (Fig. 4c). These concentrations corresponded to a moderate contamination relative to usual agricultural contents.

The reason for the bounded accumulation of copper and zinc lies in their main transport processes, and notably (i) the deposition of particles at the soil surface, and (ii) the non-uniform nature of spreading and infiltration processes within road shoulders. The latter is especially true for the low-intensity, longduration rainfall events which prevail in the Paris region and induce a localized infiltration (Tedoldi et al., 2017a). The spatial variability of copper and zinc in the surface soil constitutes a demonstration that runoff water from the road rarely reaches the other end of the permeable shoulder, which was confirmed by other approaches such as hydrological modelling [START_REF] Flanagan | Evaluation of the relative roles of a vegetative filter strip and a biofiltration swale in a treatment train for road runoff[END_REF] or direct observations of the water pathways [START_REF] García-Serrana | Infiltration capacity of roadside filter strips with non-uniform overland flow[END_REF]. Metal patterns provide an overall, time-integrated signature of the cumulative infiltration fluxes and sedimentation processes at the soil surface, most of which occur within 1 to 1.5 m from the road edge.

Conversely, the even distribution of lead, as well as its moderate concentrations in most sites, is probably a consequence of the diminishing sources of this metal in road environments. The review carried out by [START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF] highlighted a clear historical trend in Pb concentrations in road runoff, with a net decrease during the 1990s and 2000s resulting from the elimination of leaded gasoline, and substitution of Pb in tires and brake linings, lubricating oil and grease. The studies on roadside soil contamination published prior to the 2000s did show the same distribution for lead as for other metals [START_REF] Dierkes | Pollution retention capabilities of roadside soils[END_REF][START_REF] Jaradat | Contamination of roadside soil, plants, and air with heavy metals in Jordan, a comparative study[END_REF][START_REF] Olajire | Contamination of roadside soil and grass with heavy metals[END_REF][START_REF] Yassoglou | Heavy metal contamination of roadside soils in the Greater Athens area[END_REF].

Contrariwise, for newer sites such as those in this study, lead probably accumulates in amounts insufficient to generate a significant spatial trend.

Within the soil matrix, particulate contaminants undergo mechanical filtration, while the reactive transport of dissolved metals induces (i) a gradual increase in surface concentrations due to sorption onto the upper horizon, and (ii) a downward migration of the "front" between contaminated and uncontaminated soil.

These two processes lead to a local equilibrium state in which the soil's sorption capacities are exhausted up to a certain depth. Dissolved metals are then transported downwards and retained onto the underlying horizon. This vision is consistent with the fact that differences in metal levels between the upper and lower samples were often negligible.

PAHs

PAH concentrations in road shoulders were significantly higher than reference values: across all sites, the minimum values of ∑ 16 PAHs measured close and far from the road were respectively 1.6 and 1.1 mg.kg -1 , whilst the 9 th decile of usual contents in agricultural topsoils amounted to only 0.4 mg.kg -1 , indicating a strong influence of traffic-based emissions. The distribution of PAHs among the 16 analyzed compounds appeared to be fairly homogeneous from one site to another, with limited differences between the two sampling locations (Fig. 5). Fluoranthene, pyrene and benzo(b)fluoranthene were the three predominant PAHs, together contributing > 35% of ∑ 16 PAHs. These profiles were somewhat dissimilar to what was previously found in the soil of various infiltration devices for urban runoff management (Tedoldi et al., 2017b), where phenanthrene and chrysene concentrations were proportionally higher than in the present roadside soils (resp. 10 and 12% of ∑ 16 PAHs), and benzo(b)fluoranthene and benzo(a)pyrene concentrations were lower (resp. 8 and 6%).

It has been widely documented that "diagnostic ratios" between certain PAH concentrations enable the identification of the main pollution emission sources [START_REF] Tobiszewski | PAH diagnostic ratios for the identification of pollution emission sources[END_REF] and K4 = BaP/BghiP (where ANT, PHE, IcdP, BghiP, and BaP respectively refer to anthracene, phenanthrene, indeno(123-cd)pyrene, benzo(ghi)perylene, and benzo(a)pyrene concentrations), led to the same conclusion based on the threshold values reported by [START_REF] Tobiszewski | PAH diagnostic ratios for the identification of pollution emission sources[END_REF]. However, for the most polluted sites (> 90 mg.kg -1 , cf. Fig. 4d), these ratios were approaching the threshold values between coal/wood and traffic-based emissions, as a reason of which "historical" contamination of the soil was also suspected.

In contrast to the spatial patterns of metals, PAH concentrations were often lower in the samples collected near the road than at the other end of the shoulder (Fig. 4d). This dissimilarity, which was also acknowledged in most reviewed studies (cf. Introduction), probably indicates that the major transport and dispersion processes are different. While most metal fluxes appear to be associated with wet weather (runoff and spray), with a short-range influence, as previously discussed, atmospheric transport plays a greater role for traffic-emitted PAHs [START_REF] Agarwal | Concentration level, pattern and toxic potential of PAHs in traffic soil of Delhi, India[END_REF]: air turbulence caused by passing vehicles likely results in less deposition in the immediate vicinity of the road.

3.2

Inter-site variability of the contamination levels

Influence of the traffic characteristics on metal concentrations

Beyond the recurring structure of metal distribution within each study site, Fig. 4 emphasizes the important inter-site dispersion which affects the values measured at a given distance. For example, close to the road edge, copper and zinc concentrations ranged respectively from 45 to 270 mg.kg -1 , and from 150 to 850 mg.kg -1 . So as to further explore the causes of such variability, inter-site comparisons were carried out. The data from each site were synthesized into three indicators to be conceivably explained by different influencing factors: (i) the mean concentrations of copper and zinc in the first 30 cm from the road, (ii) the mean concentrations in the middle of the shoulder (70-120 cm), and (iii) the values measured on the opposite side. They are hereinbelow plotted against AADT in the case of zinc, with color gradients representing the percentage of semi-trucks (Fig. 6). The same graph is provided as Supplementary material for copper (Fig. S3). The samples with "anomalous" Zn/Cu ratios, reflecting additional sources of contamination (cf. paragraph 3.1.1), were not accounted for in the present approach. Despite a vertical dispersion of the data points, concentrations from the most contaminated zone (indicator i) displayed a clear increasing trend over the entire range of traffic (Fig. 6a); interestingly, the influence of AADT on soil contamination was still visible in the center of the shoulder (indicator ii)albeit less markedly and with more deviating behaviors (Fig. 6b). These trends reflect the effect of increasing traffic-related emission sourceswhich in road environments have been shown to be essentially brake and tire wear for copper and zinc, respectively [START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF] on pollutant loads and build-up in roadside soil. AADT alone explained respectively 81% and 69% of the variability of Cu and Zn levels via the following linear models:

Cu 0-30 cm = (49 ± 16) + (7.7 ± 1.3) • AADT 1000 [mg.kg -1 ] (1a)
Zn 0-30 cm = (141 ± 61) + (22.6 ± 5.1)

• AADT 1000 [mg.kg -1 ] (1b)
The constant term of each model is close but still slightly higher than the estimated reference contents of the soils in Seine-et-Marne (cf. paragraph 2.4). The residuals were tested for normality (Shapiro-Wilk test)

and absence of autocorrelation (Durbin-Watson test); homoscedasticity was established in the case of copper, but not zinc (Breusch-Pagan test) at a 0.05 level.

Conversely, the contamination levels at 1.8-3 m from the road appeared to fluctuate independently from the traffic characteristics, in a relatively narrow range close to the usual agricultural contentsexcept for a few points (Fig. 6c). Such observation confirmed that this area of the shoulder was only marginally affected by runoff-derived contamination.

In order to evaluate the influence of truck traffic on the residual variability of metal concentrations, a multiple regression was carried out, including both AADT and %Trucks as predictors. The quality of the model was slightly improved for Zn (the adjusted R 2 increased to 0.73, and the residuals could be considered homoscedastic) but not for Cu. This was not deemed enough to justify the use of a twovariable model in the following developments. The variability unexplained by the traffic characteristics may therefore be interpreted in terms of (i) differences in traffic conditions from one site to another (e.g., frequency of traffic jams), (ii) differences in road environments (open countryside, forest, proximity of dwellings), (iii) differences in operation time, and/or (iv) differences in soil characteristicsresulting in variable retention properties of dissolved metalswhich are discussed in the following paragraph.

Influence of the soil organic matter

Among the different soil properties, SOM is frequently reported as the most important characteristic governing the sorption of dissolved metals, as it participates both in chemisorption and physisorption processes (i.e., chemical reactions with surface functional groups, and charge-driven mechanisms, respectively [START_REF] Tedoldi | Impact of runoff infiltration on contaminant accumulation and transport in the soil/filter media of Sustainable Urban Drainage Systems: A literature review[END_REF]). As presented in the Material and Methods section, the volatile matter (VM) content was presently retained as a proxy for SOM, which is a common approach in soil studies. In the samples collected close to the road, VM ranged from 4 to 14% depending on the site; the lowest value corresponded to a calcareous shoulder, while most values fell between 7 and 11%. Fig. 7 displays the Zn concentration versus the VM content of these samples, with colors representing the AADT on the adjacent road.

Organic matter appears to control the maximum concentration of metals that can be sorbed onto the soil, i.e., the upper envelope of the data points, below which Zn concentrations spread according to the traffic density, as previously discussed. This envelope forms approximately a straight line for VM contents ≤ 11%, the equation of which was obtained from a linear regression after isolating the upper points:

Zn max = (80 ± 12) • VM + (-90 ± 115) [mg.kg -1 ] (2)
The same behavior is observable for copper (see Supplementary material, Fig. S4).

Although the present result is of great interest from a scientific perspective, including the VM content in a predictive model of soil contamination is not operationally functional, as the latter, just like metal contents, is unknown a priori. While the design of Best Management Practices (and especially swales or bioretention systems) is subject to precise guidelines in several countries, which set an acceptable range for the organic matter content of the soil/filter media, this is usually not the case for road shoulders in

France. As a result, VM would have to be determined from in-situ sampling due to its potential variability.

Thus, in the subsequent part, where the practical implications are looked upon, only the above-mentioned traffic-based regression model will be focused on. with its 95% confidence interval).

Case of PAHs

PAH concentrations did not exhibit the same dependence on road traffic as copper and zinc. As a reminder, not all examined studies mentioned traffic density as a significant factor influencing PAH contamination either [START_REF] Kim | Impact of traffic volumes on levels, patterns, and toxicity of polycyclic aromatic hydrocarbons in roadside soils[END_REF][START_REF] Kumar | Distribution behavior and carcinogenic level of some polycyclic aromatic hydrocarbons in roadside soil at major traffic intercepts within a developing city of India[END_REF][START_REF] Marusenko | Distribution of Polycyclic Aromatic Hydrocarbons in soils of an arid urban ecosystem[END_REF]. Another remarkable difference with metals was that the contamination levels across all study sites displayed a noticeably lower variability at 0-0.3 m than at 2-3 m (Fig. 4d). So as to interpret this observation, it should be kept in mind that the samples collected close to the pavement were composed of a mixture of soil and sediment, the latter originating from road dust mobilization by runoff. Interestingly, a literature review conducted by [START_REF] Majumdar | Worldwide distribution of polyclyclic aromatic hydrocarbons in urban road dust[END_REF] showed that PAH concentrations in road dust from worldwide traffic areas were distributed within a very narrow range of values: ∑ 16 PAHs frequently fell between 1 and 35 mg.kg -1 , as reported on Fig. 4d. This relative stability of road dust composition is consistent with the low dispersion and the range of the measurements near the roadway.

At the other end of the shoulder, not only did the values span a wider range, but they were also relatively high compared to the available data about roadside soil contamination. For instance, the third quartile of the present measurements at 2-3 m (40 mg.kg -1 ) corresponds to the highest value reported by [START_REF] Marusenko | Distribution of Polycyclic Aromatic Hydrocarbons in soils of an arid urban ecosystem[END_REF] from a literature survey gathering 23 different studies. Nevertheless, such contamination levels were also measured by [START_REF] Mikkelsen | Experimental assessment of soil and groundwater contamination from two old infiltration systems for road runoff in Switzerland[END_REF] in two old infiltration systems for road runoff (∑ 16 PAHs between 31 and 220 mg.kg -1 ). A conceivable assumption for this behavior is that this zone may not have been scraped during all previous maintenance operations, depending on the length of the equipment used: if so, this would entail different accumulation times from one site to another at 2-3 m.

While this is not of major importance for metals, which have been proven to be mostly transported by short-range, wet weather-related processes (and therefore accumulate close to the roadway), it may lead to larger differences for PAHs if the prevalence of mid-to long-range atmospheric transport is ascertained.

Under such assumptions, PAH concentrations measured far from the road would result from a continuous integration of the deposits at the soil surface over a larger period of time. It may also reinforce the influence of the road environment on the inter-site variability of PAH concentrationsinasmuch as the presence of trees or other obstacles affects atmospheric dispersion, as discussed by [START_REF] Agarwal | Concentration level, pattern and toxic potential of PAHs in traffic soil of Delhi, India[END_REF] making the derivation of predictive relationships more complex.

Practical implications

Optimization of maintenance practices

The unequally polluted soil which is scraped during usual maintenance operations of road shoulders is ordinarily managed as a whole, inducing a "dilution" of the contamination. Due to the recurrent patterns of soil contaminants, it may be practically interesting to consider a differentiated management for the different parts of the vegetated strip. This concern may be rephrased as follows: is it possible to systematically isolate a certain proportion of the pollutants accumulated in each shoulder, by excavating it over a controlled width? For PAHs, the spatial resolution of the data was not deemed sufficient to carry out such appraisal; however, for metals, this proportion was calculated as a function of the distance 𝑑 from the road, according to Eq. 3.

𝐹(𝑑) = ∫ 𝜌 𝐶 acc (𝑥) 𝑑𝑥 𝑑 0

∫ 𝜌 𝐶 acc (𝑥) 𝑑𝑥 𝐷 0

(3)

where 𝐷 is the entire width of the road shoulder (1.5 to 3 m depending on the site), 𝜌 is the soil's bulk density (which is assumed to be uniform in the sampled layer, and thus no longer intervenes in this equation), and 𝐶 acc (𝑥) is the concentration of accumulated metal at a distance 𝑥 from the road (averaged over the soil depth). The latter term was conservatively estimated as:

𝐶 acc (𝑥) = max(𝐶(𝑥) -𝐶 ref , 0) (4)
where 𝐶 ref is the upper bound of usual agricultural contents in Seine-et-Marne (cf. paragraph 2.4), and 𝐶(𝑥) results from linear interpolation of the concentrations measured at 0, 0.3, 0.7, 1.2, and 1.8-3 m.

The results are displayed on Fig. 8 in the case of zinc. As can be seen of this graph, scraping 1.5 m of the shoulder starting from the road will likely remove between 75 and 100% of the accumulated metal. In nine cases out of ten, a 80% removal can be achieved by targeting ≤ 1.8 m. This evaluation is of particular interest near heavily trafficked roads, where metal contamination levels in the soil can be locally high, thus emphasizing the benefits of treating this pollution separately via a differentiated management of the scraped materials. 1 st and 3 rd quartiles (dark envelope), 1 st and 9 th deciles (light envelope).

Potential for reuse of the excavated soils

So as to evaluate the suitability of partially contaminated soils for certain uses (e.g., residential, agricultural or commercial), a conventional approach consists of comparing contaminant concentrations to threshold values. In case of exceedance, it is considered that such uses are to be prohibited and/or specific actions are needed: for this reason, these values are often referred to as "intervention thresholds" or "soil cleanup standards". Despite the apparent simplicity of this procedure, [START_REF] Provoost | Comparison of Soil Clean-up Standards for trace elements between countries: Why do they differ?[END_REF] underlined the fact that thresholds can differ significantly from one country to anotherwhere they exist: for instance, in France, the only regulatory guidelines about soil contamination are aimed to restrict the spreading of sewage sludge in agricultural fields deemed "too polluted". In previous research works addressing soil contamination in stormwater Best Management Practices, authors referred to the Dutch, Swiss, Austrian, Swedish, or Danish standards, in which intervention thresholds vary from 100 to 1000 mg.kg -1 for copper, and from 500 to 2500 mg.kg -1 for zinc [START_REF] Tedoldi | Impact of runoff infiltration on contaminant accumulation and transport in the soil/filter media of Sustainable Urban Drainage Systems: A literature review[END_REF]. For PAHs, it is common for these thresholds to be additionally compound-dependent, as several PAHs have been proven

to present carcinogenic hazards and are therefore subject to stricter regulations.

It is beyond the scope of this paper to discuss which thresholds should be preferably retained and which ones have a lesser relevance to quantify the impacts of soil pollution; instead, a different strategy may be proposed for metals. Considering the established relationships between soil concentrations and vehicular density (paragraph 3.2.1), each existing threshold can be associated a "compatible" range of traffic, such that all roads below the "cutoff" AADT would be expected to generate lower concentrations than the pollution threshold. A conservative approach can be adopted by considering the upper limit of the prediction interval for the data points at 0-30 cm (Fig. 6a): this corresponds to the highest possible concentrations on the road shoulder for a given AADT. As an illustration, let us consider the intervention thresholds adopted in the Netherlands (NMHSPE, 2000) and in Sweden (Swedish EPA, 1997), which are relatively close (respectively 190 and 200 mg.kg -1 for copper, and 720 and 700 mg.kg -1 for zinc).

Considering the aforementioned regression analysis (see Fig. S3 for copper), roads with daily traffic below 17,000 veh/day are not expected to generate metal contamination exceeding these thresholds.

Conversely, the state of the art as well as the present work reveal our lesser understanding of the characteristics of PAH contamination, and more generally organic micropollutants of emerging concern such as phthalates, alkylphenols and their derivatives. These substances have been shown to be ubiquitous in road runoff [START_REF] Flanagan | Field performance of two biofiltration systems treating micropollutants from road runoff[END_REF], but investigations on roadside soils are still scarce [START_REF] Hongjun | Distribution of phthalate esters in topsoil: a case study in the Yellow River Delta, China[END_REF][START_REF] Lü | Soil contamination and sources of phthalates and its health risk in China: A review[END_REF]. Further research is needed to address their emissions from road traffic, retention and persistence in soil, so as to move towards a more integrated approach to environmental hazards and possible remediation techniques.

Operational perspectives: road shoulders as treatment devices for contaminated runoff

Although road shoulders are not initially designed and maintained for this purpose, they offer interesting perspectives for the mitigation of runoff-generated contaminant fluxes to the environment, since the soil acts as a filter for both dissolved and particulate substances. Hence, it may be valuable to consider these infrastructures as multi-functional nature-based solutions, the characteristics of which may be enhanced towards an effective treatment of road runoff. The fact that soil organic matter controls the maximum amount of metals that can be retained from contaminated water (paragraph 3.2.2) emphasizes the interest of avoiding low-organic materials such as calcareous soils when implementing road shoulders, and bringing some organic-rich material to maximize contaminant retention in the presence of sensitive issues (e.g., groundwater used as a source of drinking water). Similarly, the depth of this filter material should be such that subsequent scraping operations would not expose deeper soil horizonswith potentially lower sorption capacities and poorer biological activityotherwise the post-maintenance retention efficiency would be significantly lessened.

CONCLUSIONS

In the present study, soil contamination in road shoulders was investigated through an extensive sampling campaign on 40 study sites, with a dual focus on intra-and inter-site variability of concentrations. The achieved results demonstrated:

i. a good reproducibility of the "typical" distribution of metal concentrations within each site: for copper and zinc, this consisted of a significant accumulation close to the road, and a continuous decrease with increasing distance, so that the first 1.5 m of the shoulder systematically contained ≥ 75% and up to 100% of the accumulated metals. Lead displayed more uniform distributions, closer to the usual content range for agricultural soils from the study area.

ii. contrasting patterns for PAHs, the concentrations of which fell within a relatively narrow range of values close to the road, whereas highest buildup occurred at the other end of the shoulders.

iii. a satisfying predictability of copper and zinc levels from the annual average daily traffic of the nearby road, which explained respectively 81% and 69% of the inter-site variability.

iv. the existence of a "ceiling" concentration of metals in soil, controlled by its organic matter content, which limits the amounts that can be intercepted from road runoff.

Unlike metals, which are mostly carried by short-range, wet weather-related processes, the dispersion mechanisms by which PAHs are transported from the road to the adjacent shoulders remain unclear. The higher concentrations found further away from the road could either indicate the prevalence of longerrange mechanisms, mainly governed by atmospheric transport, or be due to longer accumulation times.

Overall, these results demonstrate that road shoulders enable the mitigation of runoff-generated contaminant fluxes to the environment, and may therefore be considered as treatment devices and optimized as such. Additionally, the existence of explicit relationships between traffic density and metal concentrations makes it possible to route the scraped soil towards the most suitable valorization or treatment option according to the site characteristics. Further research could refine the understanding of PAH behavior and include other emerging organic micropollutants in these considerations, to achieve an integrated vision of the hazards posed by roadside soil contamination.

Interestingly, most studies which focused on road runoff hardly evidenced a correlation between traffic indicators and metal concentrations in water, owing to their significant inter-event variability. However, their long-term accumulation in soil acts like an averaging process which enables this trend to be reconstructed. Considering the soil's propensity to act as a "passive sampler" of contaminantsinsofar as the latter are not or only slightly subject to dissipation processesstudying soil contamination in stormwater Best Management Practices may offer promising perspectives for the further characterization and modelling of pollutant fluxes.

Fig. 2 -

 2 Fig. 2 -Location of the study sites in the Paris region. The colors and shapes indicate respectively the classes of traffic and trucks percentage on the adjacent road.

Fig. 4 -

 4 Fig. 4 -Concentrations of (a) copper, (b) zinc, (c) lead, and (d) ∑ 16 PAHs across all sites, as a function of the distance from the road. The bottom and top of each box correspond to the first and third quartiles, and the thick line represents the median value (𝑁 = 40).

  . Let us consider for instance the ratio K1 = BaA/[BaA + CHR], where BaA and CHR respectively refer to benzo(a)anthracene and chrysene concentrations in soil. K1 < 0.2 indicates petrogenic sources of PAHs, 0.2 < K1 < 0.35 uncovers pyrogenic sources dominated by coal or wood combustion, while K1 > 0.35 corresponds to vehicular emissions. Unsurprisingly, the soil samples from all study sites belonged to the latter category (K1 ≥ 0.4). Applying other ratios, i.e., K2 = ANT/[ANT + PHE], K3 = IcdP/[IcdP + BghiP],

Fig. 5 -

 5 Fig. 5 -Relative contribution of each individual PAH to their total concentration, across all sites.

Fig. 6 -

 6 Fig. 6 -Relationship between the traffic characteristics (AADT on the horizontal axis and %Trucks represented as a color gradient) and the mean Zn concentrations (a) in the first 30 cm, (b) between 70 and 120 cm from the road, and (c) on the opposite side of each shoulder. The red and grey envelopes correspond respectively to the 95% confidence and prediction intervals of the regression.

Fig. 7 -

 7 Fig. 7 -Relationship between volatile matter and zinc concentrations in the samples collected close to the road. The upper envelope of the data points (defined as the highest Zn concentration for each value of the volatile matter content) was modeled via a linear regression in the range 4% ≤ VM ≤ 12% (blue line, along

Fig. 8 -

 8 Fig. 8 -Fraction of zinc accumulated in the shoulder as a function of the distance from the road. The lines and envelopes represent statistics established from the 40 study sites: median accumulation (solid line),

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the Departmental Council of Seine-et-Marne for its financial support, as well as Vincent Laurent for his help in organizing the sampling campaigns.


Lama Ahmad

Laurent Salmon

Hafsa Korri-Youssoufi

Electrochemical detection of the human cancer biomarker 'autocrine motility factor-phosphoglucose isomerase' based on a biosensor formed with a monosaccharidic inhibitor

Keywords: cancer, biomarker, biosensor, diagnosis, label-free, dendrimer, phosphoglucose isomerase, autocrine motility factor

Human intracellular glycolytic enzyme phosphoglucose isomerase (hPGI) plays the role of autocrine motility factor (AMF) once secreted in the extracellular medium. AMF is a cytokine that stimulates tumor cell motility in vitro and metastases development in vivo. High blood levels of the protein have been reported to be closely related to metastases formation. Since it is secreted by a large variety of tumors, AMF is considered as a validated cancer biomarker. In this work, we report a specific and sensitive electrochemical biosensor designed for the detection and quantification of AMF which is a cancer biomarker present in urine and/or blood of cancer patients. Overexpression and purification of the human protein were performed as well as the synthesis of the inhibitor N-(5-phosphate-D-arabinoyl)-2-amino ethanamine that selectively interacts with the protein. Affinity of the inhibitor for the protein was first evaluated by molecular docking and then by measuring its binding affinity (IC50 = 0.95 µM). The biosensor was constructed by covalent attachment of the synthesized inhibitor bearing an amine function in terminal position to a transducer which is formed with polypyrrole bearing the redox dendrimer PAMAM G2. Protein interactions were quantified by amperometric measurement in a range of 1 pM to 1 µM in HEPES buffer. The biosensor demonstrated a detection limit of 43 fM in phosphate buffer (PBS) and high selectivity for AMF when compared with non-specific Dglucose-6-phosphate dehydrogenase (G6PDH) protein. Detection of AMF in spiked human plasma was performed to demonstrate the efficiency of such system in real sample.

Introduction

The early diagnosis of a pathology makes possible to limit its effects and to start the appropriate treatment as soon as possible. Screening is therefore the first step leading to treatment and eventually healing, especially in the case of serious diseases such as cancer.

Indeed, as soon as metastases appear, the patient's state of health can quickly deteriorated. Early detection of metastases associated with a poor prognosis is therefore a priority of oncology research. For example, prostate specific antigen (PSA) in prostate cancer or CA 15-3 antigen in breast cancer are used as tumor progression markers allowing detecting patients at high risk of relapse [START_REF] Duffy | Clinical uses of tumor markers: a critical review[END_REF]. Tumor markers are useful not only for cancer screening but also help to track a patient and assess response to cancer treatment [START_REF] Nagpal | Tumor markers: A diagnostic tool[END_REF].

Inside the cell, phosphoglucose isomerase (PGI) is a glycolytic enzyme which catalyzes the reversible interconversion of β-D-fructofuranose 6-phosphate (β-F6P) to α-D-glucopyranose 6phosphate (α-G6P) [START_REF] Willem | Dual anomeric specificity and dual anomerase activity of phosphoglucoisomerase quantified by two-dimensional phase-sensitive 13C EXSY NMR[END_REF]. Upon secretion by tumor cells to the extracellular medium, human PGI plays however the role of a metastatic cytokine called 'autocrine motility factor' AMF AMF and PGI are strictly identical proteins, both in terms of sequence and three-dimensional structure, which were discovered independently. They are localized in two different environments with two different activities, this is why they named differently.AMF acts by binding to the membrane receptor AMFR/gp78 of tumor cells [START_REF] Watanabe | Purification of human tumor cell autocrine motility factor and molecular cloning of its receptor[END_REF]. Activation of AMFR has been shown to alter tumor cell adhesion and stimulate their motility [START_REF] Watanabe | Purification of human tumor cell autocrine motility factor and molecular cloning of its receptor[END_REF][START_REF] Tsutsumi | Autocrine motility factor signaling enhances pancreatic cancer metastasis[END_REF].

Overexpression of AMF and/or its receptor AMFR/gp78 is closely associated to progression and malignancy of tumors in several types of cancers such as breast, kidney, gastrointestinal, colorectal, pancreatic, bladder, prostate, bone, hepatocellular, and lung cancers [START_REF] Chiu | Autocrine motility factor receptor: a clinical review[END_REF][START_REF] Huang | Aberrant expression of the autocrine motility factor receptor correlates with poor prognosis and promotes metastasis in gastric carcinoma, Asian Pac[END_REF][START_REF] Paschos | Enzymatic function of multiple origins regulates the progression of colorectal cancer and the development of metastases[END_REF][START_REF] Bayo | Increased Migration of Human Mesenchymal Stromal Cells by Autocrine Motility Factor (AMF) Resulted in Enhanced Recruitment towards Hepatocellular Carcinoma[END_REF]. Furthermore, AMF has been used as a biomarker of cancer progression since it has been detected in the serum and/or urine of patients in numerous types of tumors [START_REF] Guirguis | Detection of Autocrine Motility Factor in Urine as a Marker of Bladder Cancer[END_REF][START_REF] Baumann | The diagnostic validity of the serum tumor marker phosphohexose isomerase (PHI) in patients with gastrointestinal, kidney, and breast cancer[END_REF][START_REF] Filella | Serum phosphohexose isomerase activities in patients with colorectal cancer[END_REF]. Thus, design of an analytical tool for the detection of this AMF protein in human fluids would constitute a significant scientific breakthrough in oncology.

Methods described in the literature for the detection of AMF in biological fluids include enzymatic, colorimetric and immunological methods [START_REF] Bodansky | Serum phosphohexose isomerase in cancer. II. as an index of tumor growth in metastatic carcinoma of the breast[END_REF][START_REF] Gracy | Phosphoglucose isomerase of human erythrocytes and cardiac tissue[END_REF][START_REF] Dai | Elevated serum glucose-6-phosphate isomerase correlates with histological disease activity and clinical improvement after initiation of therapy in patients with rheumatoid arthritis[END_REF]. However, these conventional methods are usually complex and difficult to implement. In addition, sample preparation and results exploitation increase duration of the analysis. In this context, the development of fast and miniaturized sensors appears as a priority. Such tools would offer the possibility of real-time analysis prior to sample preparation. The great commercial success in this area is illustrated by the glucometer which allows better management and optimized monitoring of the health status of diabetic patients.

Electrochemical biosensors can detect trace amounts of cancer-related biomarkers in biological fluids. So far, a number of promising electrochemical strategies have been described for the detection of cancer biomarkers including enzyme, DNA and immuno-based biosensors [START_REF] Topkaya | Electrochemical Biosensors for Cancer Biomarkers Detection: Recent Advances and Challenges[END_REF]. Such devices are very promising tools for a sensitive, specific and non-invasive detection for early cancer diagnosis. Thus, combining electrochemical sensors with relevant biomarkers is a good alternative to design efficient biosensors towards point-of-care diagnostic tools.

The first electrochemical biosensor for AMF detection we reported was based on the use of the enzyme substrate fructose 6-phosphate (F6P) and rabbit muscle PGI as a model of the human enzyme AMF [START_REF] Devillers | Carbohydrate-based electrochemical biosensor for detection of a cancer biomarker in human plasma[END_REF]. The detection was performed through measuring the redox signal of an external redox marker to prove F6P/protein interaction. The F6P-biosensor demonstrated a detection limit of 6.6 fM in PBS and high selectivity when compared to other non-specific glycolytic proteins such as D-glucose-6-phosphate dehydrogenase. We report here the development of an electrochemical biosensor for real time detection of the human protein AMF .

Various parameters are studied in the design of such biosensor. Firstly, a label free detection, where the redox marker is directly attached to the surface, is developed through transducers formed with modified conducting polypyrrole with redox dendrimers. The association of conducting polypyrrole and redox dendrimers was proven to underline lower of detection limit in the case of affinity biosensors [START_REF] Miodek | Electrochemical functionalization of polypyrrole through amine oxidation of poly(amidoamine) dendrimers: Application to DNA biosensor[END_REF]. The recognition element is formed with N-(5-phosphate-Darabinoyl)-2-aminoethanamine (5PAED) which is a strong inhibitor and designed as a mimic of the linear form of the enzyme substrate F6P. Inhibitor accessibly to the binding site as well as binding affinity toward human enzyme are studied. Detection of the human AMF overexpressed cancer biomarker was performed in buffer solution as well as in spiked human plasma samples.

The general scheme of the proposed biosensor is reported below (Scheme 1). Biolayer formation was characterized through FT-IR spectroscopy, SEM, AFM and XPS, as well as electrochemistry. Molecular recognition between the immobilized monosaccharide and the protein in solution was detected through square wave voltammetry (SWV) by following the redox signal of attached ferrocenyl groups. We demonstrated that a sensitive and selective biosensor based on a monosaccharide inhibitor specifically designed for detection of the human cancer biomarker AMF was obtained and displayed fast and efficient detection properties both in buffer and spiked human plasma samples.

Materials and methods

Reagents

Pyrrole, polyamidoamine dendrimers of second generation (PAMAM G2), lithium perchlorate, acetonitrile (ACN), Saccharomyces cerevisiae glucose-6-phosphate dehydrogenase (ScG6PDH), Dowex 50WX4 ion-exchange column (Na + form), β-nicotinamide adenine dinucleotide phosphate (NADP, sodium salt), F6P and G6P (disodium salts) were purchased from Sigma-Aldrich company. Human blood plasma samples were purchased from Helena Biosciences Europe (UK).

Phosphate buffered saline (PBS, pH 7.4, 10 mM Na 2 HPO 4 , 1.8 mM KH 2 PO 4 , 2.7 mM KCl, 137 mM NaCl), and HEPES buffer (pH 7.1, 50 mM) were prepared with double distilled water, filtered on 0.22 μm membranes, and stored at 4 °C before use. Pyrrole was distilled before use and modified ferrocene was synthesized following the procedure described previously [START_REF] Miodek | Direct electrochemical detection of PB1-F2 protein of influenza A virus in infected cells[END_REF][START_REF] Korri-Youssoufi | Electrochemical biosensing of DNA hybridization by electroactive ferrocene functionalized polypyrrole[END_REF].

Instruments

Electrochemical experiments were performed using a Bio-Logic potentiostat controlled with Ec-lab software. All electrochemical experiments were performed using a three-electrode cell (Basi) which consists of a reference Ag/AgCl electrode, a platinum stem as the counter electrode and a gold electrode as the working electrode (surface = 2.01.10 -2 cm 2 ). A small volume cell of 0.2 mL (Basi) equipped with porous frit that allows connection with the large volume cell was used for electrodeposition of pyrrole and PAMAM. The working electrode was cleaned by polishing several times with different thickness of diamond paste (6, 3 and 1 µm) and then activated in 0.5 M sulfuric acid solution by sweeping the potential between 0 to 1.8 V at 100 mV.s -1 for 10 cycles.

Cyclic voltammetry (CV) analysis was conducted in 5 mM [Fe(CN) 6 ] 4-/[Fe(CN) 6 ] 3-or 10 mM PBS (pH 7.4) from -0.2 to 0.6 V using a scan rate of 50 mV.s -1 . Square wave voltammetry (SWV) was conducted in PBS from -0.2 (or -0.1) to 0.4 V using a conditioning time of 60 s, a frequency of 2 Hz, and modulation amplitude of 20 mV.

X-ray Photoelectron Spectroscopy (XPS) measurements were performed with a K Alpha spectrometer by Thermo-Fisher, using a monochromatic Al X-ray Source (Kα 1486.6 keV). For all measurements, a spot size of 400 µM was employed. The hemi-spherical analyser was operated in CAE (Constant Analyser Energy) mode, with a pass energy of 200 eV and a step of 1 eV for acquisition of survey spectra, a pass energy of 50 eV and a step of 0.1 eV for acquisition of high resolution spectra.

Fourier Transform infrared spectra (FT-IR) were performed using a Bruker IFS66 FT-IR spectrometer equipped with a Mercury-Cadmium-Telluride (MCT) detector and an attenuated total reflectance (ATR) germanium crystal.

UV absorbance measurements for IC50 evaluation were conducted with CARY 300 Bio spectrophotometer equipped with a thermostat regulation device, using 1 mL of Brand polystyrene disposable cuvettes of 1 cm optical path.

Atomic force microscopy (AFM) analyses were conducted with tapping mode topography and phase imaging and were accomplished using an Innova AFM Bruker with NanoDrive v8.02 software. Tapping mode images were acquired using silicon tips from Nanosensors (PPP NCSTR) with a resonance frequency ranging between 76 and 263 kHz. The obtained images were processed using WsXM software. Scanning electron microscopy (SEM) images were performed with MEB-FEG ZEISS Supra 55 VP.

Synthesis of monosaccharide inhibitor

N-(5-Phosphate-D-arabinoyl)-2-aminoethanamine (5PAED) was synthesized using the following procedure. In a round-bottom flask placed under argon containing D-arabinono-1,4lactone 5-phosphate (128 mg, 0.56 mmol) in anhydrous methanol (5 mL), 0.13 mL of ethylenediamine (2.0 mmol, 3.5 eq) was added. A white precipitate appeared immediately. The reaction mixture was stirred at rt for 1 h. Following concentration of the reaction mixture, the residue was eluted with water on a Dowex 50WX4 ion-exchange column (Na + form) and lyophilized to afford the desired product with quantitative yield.

Protein production

Human autocrine motility factor-or phosphoglucose isomerase AMF or hPGIwas produced according to the procedure described previously by Read et al [START_REF] Read | The crystal structure of human phosphoglucose isomerase at 1.6 A resolution: implications for catalytic mechanism, cytokine activity and haemolytic anaemia[END_REF] except that we used pRSET-C as plasmid. The pRSET-C plasmid carrying the gene coding for AMF was purshased from Thermofisher Invitrogen.

Evaluation of affinity constant

PGI activity was spectrophotometrically assayed at 25 °C (λ = 340 nm) in the direction from F6P to G6P by coupling to yeast D-glucose-6-phosphate dehydrogenase (G6PDH) following a procedure adapted from the literature [START_REF] Noltmann | Isolation of crystalline phosphoglucose isomerase from rabbit muscle[END_REF][START_REF] Dyson | The Effect of pH and Temperature on the Kinetic Parameters of Phosphoglucose Isomerase[END_REF]. G6P resulting from the isomerization of F6P was oxidized to 6-phosphogluconolactone by G6PDH. This latter reaction requires NADP + as cofactor and was accompanied by the formation of NADPH giving a spectrophotometric signal measurable at 340 nm (ε = 6220 M -1 .cm -1 ). Measurement of NADPH absorbance gave access to PGI-catalyzed reaction initial velocity. Activity measurements were made using the multicuvette mode with the temperature held at 25 °C. Specific activities were measured using a substrate concentration of at least 5 times the corresponding K M value. The assay mixture contained, in a volume of 1 mL, 50 mM HEPES buffer pH 7.1, previously sterilized and filtered (0.22 µM), 5 mM MgCl 2 (500 mM in HEPES buffer), 0.5 -2 mM F6P sodium salt (100 mM in HEPES buffer), 0.4 mM NADP + sodium salt (40 mM in HEPES buffer, used up to 2 weeks after preparation), 0.6 U of G6PDH. The 5PAED inhibitor was included at final concentrations of 0 -2 µM (10 mM in HEPES buffer appropriately diluted 10 or 100 times). To ensure valid assay conditions, several precautions were taken. G6PDH was added in excess (0.6 U) so that the ratelimiting reaction was the PGI-catalyzed isomerization of F6P to G6P. The reaction mixture was allowed to pre-incubate before adding PGI for 6-8 min until no further increase in absorbance due to G6P oxidation occurred. The reaction was then initiated by the addition of PGI (0.006 U).

Absorbance rate due to NADPH formation coupled to F6P isomerization was then measured in presence (Vo I ) and in absence (Vo) of inhibitor. Reporting the ratio Vo I /Vo as a function of inhibitor concentration gives the half maximal inhibitory concentration (IC50) value for Vo I /Vo = 50%.

Biosensor construction

The strategy used for the construction of the biosensor comprises 5 steps as shown in scheme 1. Before proceeding to the development of the biosensor, electrochemical cleaning of the gold electrodes was carried out. The cleaning step serves to remove any contaminants that may persist after the polishing step of electrodes and that could subsequently affect reproducibility of the results as well as subsequent grafting steps. Each electrode was thus activated in a degassed solution of sulfuric acid (0.5 M) by sweeping potential from 0 to 1.8 V for 10 cycles at 100 mV.s -1 .

Biosensor construction proceeded by electrodeposition of pyrrole on the gold surface. A solution of 20 mM pyrrole was used. Electrodeposition was conducted by scanning the potential from -0.4 to 0.9 V for 2 cycles at 50 mV.s -1 (see Supp.

Protein detection

Detection in HEPES buffer. Human autocrine motility factor-AMFwas detected and quantified in a wide range of concentrations from 1 pM to 1 μM. All protein solutions were prepared in 50 mM HEPES buffer (pH 7.1). This pH was chosen in a way to be as close as possible to physiological pH. A solution of G6PDH prepared at 100 pM in the same buffer was used to test the specificity of the biosensor.

Detection in human plasma. Human plasma provided as a freeze-dried powder form was dissolved in 1 mL of HEPES buffer (50 mM, pH 7.1). All desired concentrations of AMF (1 pM to 1 μM) were prepared by adding the target protein to the solution of human plasma. A volume of 100 μL of protein solution at the desired concentration was added on the biosensor surface and incubated for only 10 min at rt. After incubation, the working electrode was washed with double distilled water and dried under argon. Interaction between the protein and the biosensor was followed by square wave voltammetry (SWV) in PBS buffer (10 mM, pH 7.4) using a conditioning time of 60 s, a frequency of 2 Hz, and a modulation amplitude of 25 mV.

Results and discussion

3.1. Design of 5PAED-biosensor for AMF-PGI detection 5PAED was designed as a bioreceptor of choice because it is a strong inhibitor of human AMFPGI. 5PAED, derived from the linear form of the enzyme substrate F6P (Fig. 1A), gave us a half maximal inhibitory concentration (IC50) value of 0.95 µM (Fig. 1B) at a -F6P concentration equals to K M (50 µM), which leads to an estimated competitive inhibition constant (K i ) value of about 0.5 µM. PGI are known to have much more affinity for linear F6P than cyclic -F6P, which explains strong binding affinity of 5PAED at the active site of the enzyme. 5PAED differs from linear F6P only in its head part bearing an ethylene diamine group (Fig. 1A). Its terminal amino group allows the grafting to the transducers surface by simple coupling reaction.

Grafting of 5PAED via this terminal amine function could lead to the loss of some active site interactions with the enzyme. However, it was demonstrated from the literature that the case of PGI-substrate/inhibitor complexes, the essential part for carbohydrate is polyhydroxy backbone and the phosphate to maintain the affinity to the protein the [START_REF] Jeffery | Crystal Structure of Rabbit Phosphoglucose Isomerase Complexed with 5-Phospho-d-Arabinonate Identifies the Role of Glu357 in Catalysis[END_REF][START_REF] Arsenieva | The crystal structure of rabbit phosphoglucose isomerase complexed with 5-phospho-D-arabinonohydroxamic acid[END_REF][START_REF] Davies | The structure of human phosphoglucose isomerase complexed with a transition-state analogue[END_REF]. Therefore, grafting of the selected monosaccharide to the surface of the electrode via the terminal amine function should not prevent AMF detection. In addition, the amine function is spaced from the amide function by two carbons,, which makes the remainder of the backbone more accessible for interaction with the active site residues. To validate the feasibility of the biosensor design based on immobilized 5PAED, the active site structure of human AMF-PGI in complex with 5PAED was studied using PyMol software [START_REF]The PyMOl Molecular Graphics System[END_REF] through building and docking of 5PAED from the reported structure of human PGI in complex with 5-phospho-D-arabinonate (PDB ID code 1NUH) reported by Davies et al [START_REF] Davies | The structure of human phosphoglucose isomerase complexed with a transition-state analogue[END_REF]. Figure 1C shows that the amino group is potentially accessible for covalent grafting at the surface of the biosensor, while the remainder of the backbone and in particular the phosphate group is well buried into the protein active site. AMF-PGI in complex with 5PAED using PyMol software [START_REF]The PyMOl Molecular Graphics System[END_REF] and the 3D structure of human PGI in complex with 5-phosphate-D-arabinonate (PDB 1NUJ) [START_REF] Davies | The structure of human phosphoglucose isomerase complexed with a transition-state analogue[END_REF].

In order to carry out the construction of the biosensor, a gold electrode modified with a polypyrrole layer and then functionalized with PAMAM redox dendrimers was chosen as the transducer. In this way, the transducer can be formed in a simple manner and is very sensitive for monitoring the bioreceptor/target interaction without the need for an external redox marker [START_REF] Miodek | Electrochemical functionalization of polypyrrole through amine oxidation of poly(amidoamine) dendrimers: Application to DNA biosensor[END_REF].

These remarkable characteristics come from the properties of polypyrrole (Ppy) which is an electroactive polymer with high conductivity and stability. In addition, Ppy can be easily functionalized, chemically [START_REF] Markova | Selective synthesis and radical polymerization of N-vinyl-2-(1naphthyl)-and N-vinyl-2-(2-naphthyl)pyrroles[END_REF][START_REF] Zotti | Poly(N-hexylcyclopenta[c]pyrrole) -A Novel 1,3,4-Alkyl-substituted Polypyrrole Soluble in Organic Solvents and Redox Conducting[END_REF] and electrochemically through electrochemical deposition [START_REF] Ramanavičius | Electrochemical sensors based on conducting polymer-polypyrrole[END_REF][START_REF] Richard | The Electrochemistry of Antibody-Modified Conducting Polymer Electrodes[END_REF], which allows introduction of various functional groups for further modification. Thus, the biolayer was formed by electrodeposition of Ppy followed by electrodeposition of PAMAM G2.. The choice of PAMAM G2 instead of the larger PAMAM G4 was optimized before. We demonstrated here that the dense layer obtained with PAMAM G4 induces a lower sensitivity because of the steric hindrance provided by the large size of the AMF protein.

The ferrocene group (Fc) modified with two carboxylic functions activated with phthalimide was then chemically bound to amines of PAMAM G2 forming the PPy-PAMAM-Fc layer. The grafting of 5PAED on the second Fc ester function was carried out, followed by the reaction of the unmodified ester groups of ferrocene with ethanolamine. This last step also aims stabilizing the redox signal of Fc because its ester function can hydrolyze in aqueous solution and prevent non-specific interactions. Details of biolayer formation and characterization are reported in Supp.

Info. SI. 1.

Characterization of the biosensor construction

Molecular structure of the biosensor was characterized by photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FT-IR). Morphology of the biosensor was determined using scanning electron microscopy (SEM) and atomic force microscopy (AFM).

XPS provides important information about surface modifications and chemical composition.

XPS spectra confirm modification of the gold surface by Ppy and modification of the latter by PAMAM G2 as demonstrated previously (see Supp. Info. SI. 2). XPS data obtained after grafting of ferrocene and 5PAED showed the appearance of two peaks at 708.18 and 720.98 eV (Figure 2A) corresponding to Fc iron and a peak at 133.58 eV (Figure 2B) corresponding to the phosphate group of 5PAED. The latter is characteristic of a pentavalent phosphorus atom and refers to P-O bonds of phosphate. These results confirm the grafting of both Fc and 5PAED on the surface of the biosensor.

FT-IR data demonstrates efficient attachment of PAMAM G2 to polypyrrole layers (see Supp. Info. SI. 2). Few changes are observed following grafting of both ferrocene and 5PAED where a larger peak between 3000 and 3700 cm -1 was observed due to the hydroxyl groups of the sugar moiety (Figure 2C). AFM (Figure 3A) and SEMs images (Figure 3B) were recorded to analyze the modifications in surface morphologies after the different steps of biosensor formation. AFM images showed that polypyrrole deposition led to a layer with a nodular appearance typical of polypyrrole, which clearly demonstrated its deposit on the gold surface (Figure 3A, image b). Modification of the surface appearance was accompanied by an increase of the surface roughness (RMS roughness).

A less rough surface was however observed after grafting of PAMAM where the value of roughness decreases from 7 to 5.5 nm (Figure 3A,image c). Surface roughness further decreased after grafting of both ferrocene and 5PAED to reach 4 nm (Figure 3A,image d). Once the enzyme was attached to the surface of the biosensor and the formation of the complex occurred, the surface roughness reaches a value of 6 nm and the surface becomes homogeneous. Protein aggregates are observed (figure 3A, image e) in agreement with the homodimeric quaternary structure of AMF-PGI. The SEM analysis showed the same behavior of the surface topology after formation of the biosensor and interaction of the protein (Figure 3B). A cauliflower structure highlights grafting of PPy [START_REF] Paschen | Morphology of a conducting polymer and its relation to the electronic properties[END_REF] (Figure 3B, image a). Structured surface is obtained after biolayer formation and sugar attachment, where appearance of a smoother surface is observed (Figure 3B, image b).

However, a remarkable change in surface topography is obtained after protein interaction with small nanoparticles associated to protein attachment (Figure 3B,image c). This behavior confirms the results of AFM images and demonstrates the efficient formation of a biological layer that occurs by the formation of a complex between the immobilized monosaccharide and the AMF protein.

Electrochemical characterization was performed after ferrocene and bioreceptor grafting. A well reversible redox signal is observed which confirms ferrocene attachment (See Supp. Info. SI 1, Figure S3). Square wave voltammetry (SWV) analysis shows electrochemical behavior of the biolayer after bioreceptor and ethanolamine attachment (Figure 4). A small drop in current variation with a small potential shift to a lower value is obtained after covalent attachment of monosaccharide. This result related to the chemical structure of the carbohydrate moiety providing various hydroxyl functions and the negative charges of the phosphate group blocking the electron transfer capacity. Covalent attachment of ethanolamine leads to small increase of current. This could be related to the change in the chemical and electronic environment of ferrocene from hydroxyphtalimido to ethanol group which is more hydrophilic molecule improving the ionic diffusion and then the electroactivity.

-0,3 -0,2 -0,1 0,0 0,1 0,2 0,3

Analytical performances of the biosensor

The human AMF protein was detected in a concentration range varying from 1 pM to 1 µM in 50 mM HEPES buffer (pH 7.1) at rt during 10 min. The time of association was optimized and shows that the maximum association is reached after 10 min. This short time demonstrates an effective accessibility of the protein active site, since a longer time is generally required [START_REF] Liu | Amplified electrochemical detection of protein kinase activity based on gold nanoparticles/multi-walled carbon nanotubes nanohybrids[END_REF][START_REF] Sun | Gold nanoparticles-based electrochemical method for the detection of protein kinase with a peptide-like inhibitor as the bioreceptor[END_REF][START_REF] Shen | A single electrochemical biosensor for detecting the activity and inhibition of both protein kinase and alkaline phosphatase based on phosphate ions induced deposition of redox precipitates[END_REF][START_REF] Akter | Amplified Electrochemical Detection of a Cancer Biomarker by Enhanced Precipitation Using Horseradish Peroxidase Attached on Carbon Nanotubes[END_REF]. To monitor sugar-protein interaction, SWV analyses were performed in PBS buffer. Figure 5A shows a decrease in the peak current of the redox signal of attached ferrocene upon increasing enzyme concentration. This behavior is related to the decrease in charge transfer caused by protein binding and confirms the formation of the complex (5PAED/AMF).

In order to estimate the biosensor sensitivity, the average value of peak current variations for each detected concentration was calculated. The calibration curve depicted in Figure 5B represents the average variation of the current ΔI / I 0 as a function of the logarithmic value of protein concentration with standard deviation obtained for three measurements. The curve shows a good linear relation with a coefficient regression R 2 = 0.997 and the equation of ΔI / I 0 = 0.044488 log [AMF-hPGI] + 0.63807. A limit of detection of AMF in HEPES buffer of 43 fM was calculated according to a signal to noise ratio of 3 and considering the mean value of standard deviations of the measurements (SD = 0.0128) and the slope of the calibration curve.

Although 5PAED has much more affinity for the protein than its F6P cyclic substrate, the detection limit is slightly higher than that obtained with the F6P-biosensor described previously for the detection of RmPGI (6.6 fM) [START_REF] Devillers | Carbohydrate-based electrochemical biosensor for detection of a cancer biomarker in human plasma[END_REF]. This could be explained by the loss of some interactions at the terminal nitrogen level of 5PAED and/or by the size of AMF greater than that of RmPGI.

The biosensor selectivity was investigated using another glycolytic enzyme, namely glucose-6-phosphate dehydrogenase (G6PDH) from Saccharomyces cerevisiae which catalyzes the oxidation of G6P to 6-phospho-gluconolactone. The G6PDH solution was prepared in HEPES buffer (pH 7.1). After incubation for 10 min, the electrode was then analyzed by SWV.

Figure 5C shows that the ferrocene signal is not modified after incubation of the electrode with 100 pM G6PDH. On the contrary, a decrease in signal intensity is observed after interaction with 100 pM AMF-PGI. This result demonstrates high selectivity of the biosensor described to AMF compared to other glycolytic protein and underlines the role of the selected carbohydrates.

Biosensor reproducibility for the detection of AMF was studied through the evaluation of three independent biosensors and using various concentrations of AMF. Each sensing layer was freshly prepared. A value of the relative standard deviation (RSD) of 8% was calculated, which demonstrated a good reproducibility of the biosensors.

Detection in plasma sample

Detection of AMF-PGI in human plasma was also carried out. A solution of 100 pM of AMF was spiked in human plasma and incubated using the same conditions as reported in HEPES buffer. Figure 5D shows a SWV analysis of the biosensor response obtained in free human plasma and with spiked protein. A decrease in peak current is observed after incubation of the electrode in the plasma solution with the protein. An average value of the current variation of 13% was found compared to the value of 19% obtained for the same protein concentration detected in HEPES buffer. The recovery between measurement in HERPES and Plasma is about 68% which could be related to the effects of the plasma sample [START_REF] Hossain | Fabrication of sensitive enzymatic biosensor based on multi-layered reduced graphene oxide added PtAu nanoparticles-modified hybrid electrode[END_REF][START_REF] Gifford | Protein interactions with subcutaneously implanted biosensors[END_REF]. These results further support the ability of the biosensor to selectively detect human AMF-PGI not only in HEPES buffer but also in a complex media such as human plasma. Further improvement in recovery could be optimized by adding others blocking agent such as polyethylene glycol chains that has antifouling properties and should prevent the plasma effect. Our approach in the design of carbohydrate-based biosensors could be applied for various applications provided that the targeted protein is secreted in plasma or urine and avoids all the steps necessary for samples preparation. Depending on the targeted biomarker protein, the location of its binding site, and its tolerance to accept a bioreceptor, virtually any type of inhibitor could be considered as potential bioreceptor notably in the area of glycomics and glycoproteomics [START_REF] Kailemia | Glycans and glycoproteins as specific biomarkers for cancer[END_REF]. Using monosaccharides for the detection of sugar binding proteins in human fluids could be achieved through the designed electrochemical biosensor.

For example, serum and urine neuraminidase activity is higher in patients with diabetic nephropathy when compared to control groups [START_REF] Roozbeh | Significance of serum and urine neuraminidase activity and serum and urine level of sialic acid in diabetic nephropathy[END_REF]. Grafting sialic acid onto an electrode could lead to the development of a new biosensor for the electrochemical detection of this inflammatory biomarker in diabetes. Carbohydrate-based biosensors might also be useful for the effective detection of pathogenic bacteria [START_REF] Ahmed | Biosensors for Whole-Cell Bacterial Detection[END_REF]. In the area of cancer, glycans and glycoproteins are known as cancer biomarkers detectable in human fluids, some of them being clinically used.

Detection of glycosidases and glycosyltransferases in human fluids or at the surface of cancer cells might also be diagnosized by carbohydrate-based electrochemical biosensors. [START_REF] Zhang | Carbohydrate derivative-functionalized biosensing toward highly sensitive electrochemical detection of cell surface glycan expression as cancer biomarker[END_REF] Indeed, increased sialidase activity were demonstrated in serum of cancer patients [START_REF] Hata | Increased sialidase activity in serum of cancer patients: Identification of sialidase and inhibitor activities in human serum[END_REF], and sialic acid metabolism has been shown to be upregulated in incurable metastatic breast cancer [START_REF] Teoh | Sialic Acid Metabolism: A Key Player in Breast Cancer Metastasis Revealed by Metabolomics[END_REF]. To conclude, the simple, rapid and efficient diagnosis of many pathological processes, including cancer, microbial infections, inflammatory and cardiovascular diseases, is currently the subject of intense research with high added value throughout the world. This highly promising and sensitive work on sugar proteins of interest is currently underway in our laboratory.

Conclusion

We report in this study the construction, characterization and evaluation of a new electrochemical biosensor designed for the detection of the human autocrine motility factor/ phosphosglucose isomerase (AMF or PGI) protein, a known cancer metastatic biomarker, in human plasma. The biosensor was developed using a strong inhibitor of human PGI as the recognition element, N-(5-phosphate-D-arabinoyl)-2-aminoethanamine (5PAED). The internal redox probe ferrocene was attached to the sensitive layer formed with PPy-PAMAM G2.

Covalent immobilization of the bioreceptor 5PAED chemically grafted was achieved without significantly altering its interaction properties and led to efficient direct amperometric detection of the cancer biomarker in a complex sample. Biosensor performances were evaluated in HEPES buffer with a dynamic detection range extending from 1 pM to 1 μM and displays high sensitivity to AMF-PGI with a detection limit of 43 fM. It also has a high specificity to AMF-PGI compared to the other glycolytic protein, glucose-6-phosphate dehydrogenase (G6PDH).

The 5PAED-biosensor is also able to detect AMF-PGI in a complex medium such as human plasma and requires only a 10 min period of time to achieve protein detection. Such a device would most likely allow easy, rapid and efficient detection of the AMF cancer biomarker in human serum. It could further be a valuable analytical tool for cancer screening and cancer patient's follow-up. Such approach using an enzyme inhibitor for the design of a direct biosensor could likely be applied for the detection of other pathological biomarkers.

Scheme 1 .

 1 Scheme 1. The different steps of biosensor construction. (1) : electropolymerization of pyrrole on gold electrode. (2) : electrodeposition of PAMAM G2 leading to an aminated surface. (3): chemical grafting of the redox marker by simple coupling between ester functions of modified ferrocene and amino groups of PAMAM G2. (4): grafting of bioreceptor 5PAED by coupling to the second ester function of the redox marker. (5): replacement of N-hydroxyphthalimido groups of free ferrocene molecules by ethanolamine.

Figure 1 .

 1 Figure 1. (A) Structures of the linear form of AMF-PGI substrate (F6P) and inhibitor N-(5phosphate-D-arabinoyl)-2-aminoethanamine (5PAED). (B) Determination of half maximal inhibitory concentration (IC50) value for 5PAED on AMF-PGI (50 mM HEPES buffer, 25 °C, pH 7.1) depicting ratio of initial velocity in presence (Vo I ) and absence (Vo) of inhibitor as a function of inhibitor concentration. (C) Docking surface representation of the active site of

Figure 2 .

 2 Figure 2. XPS results showing the peaks corresponding to (A) ferrocene and (B) phosphorus atom of 5PAED. (C) Comparison of FT-IR spectra (top) before and (bottom) after grafting of 5PAED.

Figure 3 .

 3 Figure 3. (A) AFM images (a) naked gold plate (RMS = 4 nm), (b) Ppy (RMS = 7 nm), (c) Ppy-PAMAM (RMS = 5.5 nm), (d) Ppy-PANAM-Fc-5PAED (biosensor, RMS = 4 nm), and (e) after protein interaction (RMS = 6 nm). (B) SEM images of various surfaces: (a) gold modified Ppy, (b) gold modified with PPy/biolayer, (c) after protein interaction.

E

Figure 4 .

 4 Figure 4. Characterization by SWV of the modified surface before and after grafting of 5PAED and ethanolamine (EtOA) in 10 mM PBS buffer, pH 7.4, frequency = 2 Hz.

Figure 5 .

 5 Figure 5. (A) SWV measurements obtained with a modulation amplitude of 20 mV and a 2 Hz frequency with the biosensor alone and after incubation in HEPES buffer with AMF concentrations varying from 1 pM to 1 µM, respectively from top to bottom. (B) Calibration curve obtained from SWV data of the 5PAED-biosensor as a function of AMF concentration (logarithmic scale). Error bars represents the standard deviation (SD) across three independent measurements. (C) SWV measurements obtained for the biosensor alone and after incubation with 100 pM G6PDH and 100 pM AMF in HEPES buffer (respectively from top to bottom). (D) SWV measurements obtained for the biosensor alone (top) and after incubation with 100 pM AMF (bottom) in human plasma.