Florian Barbi

Laurent Vallon

Carmen Guerrero-Galán

Sabine D Zimmermann

Delphine Melayah

Danis Abrouk

Jeanne Dore

Lemaire Marc

Laurence Fraissinet-Tachet

Patricia Luis

Jeanne Doré

Marc Lemaire

Laurence Fraissinet- 4 Tachet

Roland Marmeisse
email: roland.marmeisse@mnhn.fr

Datamining and functional environmental genomics reassess the phylogenetics and functional diversity of fungal monosaccharide transporters

Keywords: Fungi, sugar transporters, environmental genomics, metatranscriptomics 22 23

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

Introduction 49

In osmotrophic microorganisms such as Fungi, sugar transporters inserted in the cell 50 membrane are at the frontline for the provision of external soluble sugars to fuel primary 51 carbon metabolism [START_REF] Gonçalves | Stepwise functional 646 evolution in a fungal sugar transporter family[END_REF]. These transporters are confronted to, and may transport features in terms of substrate range, affinity or transport inhibition by non-99 transported competitive substrates (e.g. Reznicek et al. 2015;Li et al. 2016;Trichez et al. 100 2019). Despite this apparent wealth of knowledge regarding fungal sugar transporters, their 101 true phylogenetic and functional diversity within the kingdom Fungi remains underexplored. as "baits" to select sugar transporters, we concentrated our efforts on D-mannose. In the 118 literature, this monosaccharide had never been specifically used to select transporters 119 although it is widespread and abundant in natura as a component of plant biomass (mannans) 120 or as a component of glycoproteins as for example in the fungal cell wall mannoproteins 121 (including yeasts; see Lipke and Ovalle, 1998). Noticeably, gymnosperm cell walls are 122 specifically enriched in mannans that represent on average 31% of the needle's hemicellulose 123 specifically thrive in gymnosperm (e.g. P. abies) forest may express mannose-specific 125 transporters. Furthermore, in a context of biotechnology, the characterization of transporters 126 that efficiently transport mannose but no other monosaccharides could be used to engineer 127 yeast strains for an efficient use of this plant-derived sugar in a context where other sugars are 128 present.

129 Our objectives were thus (i) to update our current knowledge on fungal sugar 130 transporter functional diversification through the establishment of an exhaustive database of 131 characterized members of this fungal protein family and subsequent phylogenetic analysis of 132 the corresponding proteins, and (ii) to search for novel members possibly defining novel 133 substrate preferences (such as mannose) through an environmental genomics approach.

Materials and methods

135

Soil sampling, RNA extraction and cDNA library construction 136 Two organic matter-rich composite soil samples were collected in July 2007 in a beech (F. 137 sylvatica) and in a spruce (P. abies) forest (Damon et al. 2010;[START_REF] Young | Functional survey for heterologous 787 sugar transport proteins, using Saccharomyces cerevisiae as a host[END_REF]2012) (Wieczorke et al. 1999). For xylose, we used the EBY.X1-2 S. cerevisiae 159 strain which is the EBY.VW4000 strain in which had been introduced plasmids p414-TEF.X1 160 and p25G.X2 containing the XYL1 and XYL2 genes from Scheffersomyces stipitis, respectively 161 [START_REF] Young | Functional survey for heterologous 787 sugar transport proteins, using Saccharomyces cerevisiae as a host[END_REF]). These two genes code for a xylose reductase (XYL1) and a xylitol 162 dehydrogenase (XYL2), which are the two enzymes activities, absent from S. cerevisiae, 163 needed for the use of xylose as a carbon source. The EBY.VW4000 strain was grown at 30°C 164 in liquid or on solid yeast nitrogen base medium (YNB, 6.7 g.l -1 without amino acids, pH 5.9) 165 supplemented with (in g.l -1 ) adenine, 0.01; arginine, histidine and methionine, 0.02; lysine, 1). This is also the case for (i) four transporters, from four filamentous Ascomycota

353

When all environmental sequences were incorporated in the phylogenetic tree that 354 encompassed nearly all characterized fungal SPs, we observed that all of them (except the 355 divergent spB4 sequence used to root the tree) fell in clades of monosaccharide "M" 356 transporters (Fig. 1). Furthermore, more than half (11) of the environmental sequences fell in

376

While several transporters could be categorized as relatively generalists (e.g. spB2, 377 spS4, spS8, spS9 or spS11), leading to comparable growth rates on all four C6 sugars tested, 378 others had a more restricted substrate range. Noticeably, five environmental transporters 379 (spB3, spB4, spS1, spS2 and spS7) did not allow growth of the recombinant yeasts on all 380 three tested concentrations of glucose (particularly well visible in drop tests on solid media, 381 Online Resource 5). This proportion of "glucose negative" environmental transporters among 382 "mannose positive" ones (26%) is significantly higher (Chi2 test, P<0.01) than the proportion 383 observed among published transporters (two in 47; 4%). Among these five SPs, the 384 phylogenetically related spS2 and spS7 ones (Fig. 2) were seemingly mannose specific in 385 both liquid and solid cultures. However, both spS2 and spS7 were among the transporters for 386 which the final biomass yield was always low irrespective of the monosaccharide added to the 387 culture medium. Altogether, clustering of environmental transporters according to their 388 substrate range, deduced from the growth of the recombinant EBYVW4000 strain on different 389 concentrations of the four C6 monosaccharides (Fig. 3) demonstrated an absence of 390 correspondence between substrate preferences and phylogenetic proximity of the primary 391 sequences (Fig. 1 and2). no growth on glucose and spS2 supporting poor growth on all tested C6 sugars (Fig. 3).

410

Transport of mannose was confirmed for both selected transporters as expected from the yeast 411 complementation assay (spS1, n=24, N=7; spS2 n=16, N=7; where n is the number of studied 412 oocytes from N different batches) in test solutions complemented with 10 mM mannose at pH 413 5.5 (Fig. 4). When applying hyperpolarizing voltage pulses, negative currents of up to several 414 100 nA were induced dependent on the applied potential, thus indicating that both spS1 and 415 spS2 indeed functioned as sugar/ion co-transporters (Fig. 4A,B). Current induction by 416 mannose was not observed in water-injected control oocytes (n=4, N=3) and was reversible in 417 transporter-expressing oocytes, as perfusion with control solution reduced the substrate 418 specific currents (reversibility was tested for all recorded currents). These sugar-specific 419 negative currents would correspond to cation influx (or anion efflux). The observed currents 420 could be shown to be dependent on external pH (i.e. H + concentration) as no currents were 421 induced with mannose at pH 7.5 (n=3, N=2; Fig. 4C) indicating influx of protons and thus H + -422 mannose symport. Several sugar transporters have been described to function as H + -sugar symporters [START_REF] Bush | Electrogenicity, pH-dependence, and stoichiometry of the proton-sucrose 607 symport[END_REF][START_REF] Bush | Proton-coupled sugar and amino acid transporters in plants[END_REF][START_REF] Wolf | The Chlorella H + /hexose co-transporter gene[END_REF][START_REF] Boorer | Transport mechanism of the cloned 605 potato H + /sucrose transporter StSUT1[END_REF]Lemoine et al. 1996;Zhou 424 et al. 1997;Rottmann et al. 2016). Amplitudes of current induction varied between oocytes 425 probably because of different expression levels in oocytes and oocyte batches. Interestingly, 426 both transporters differed clearly with respect to transport of glucose (Fig. 4C). In agreement 427 with growth measurements, the transporter spS1 did not transport glucose (n=10, N=4; 428 Fig. 4C) whereas spS2 mediated undoubtedly glucose transport (n=6, N=5; Fig. 4B,C). In Glucose inhibition of transport of other monosaccharides by SPs that do not transport 451 glucose, as suggested here in the oocyte experiment for spS1, has been repeatedly reported in 452 the literature (Subtil and Boles 2012;[START_REF] Farwick | Engineering of yeast hexose 640 transporters to transport d-xylose without inhibition by d-glucose[END_REF]. We evaluated this phenomenon, as 453 well as potential inhibition by fructose, for five environmental transporters (spS1, spS2, spS7, 454 spB3 and spB6) that did not support significant growth on any concentration of both glucose 455 and fructose. For all five cases, we observed that in the presence of 10 g.l -1 of either glucose 456 or fructose in the culture medium, the EBYVW4000 strain expressing the corresponding 457 transporters failed to grow on either low (1 g.l -1 ), medium (5 g.l -1 ) or high (10 g.l -1 ) 458 concentrations of mannose (Online Resource 7). 1999) that would not normally support cell multiplication. These experimental artifacts can be 494 partly solved using the more labor-intensive expression of transporters in X. laevis oocytes for 495 electrophysiological measurements that also allows the evaluation of molecules that are not 496 normally assimilated by S. cerevisiae (e.g. C5 or L-sugars) as potential substrates. Using this 497 approach with two environmental SPs originally selected on mannose, we confirmed yeast 498 growth assay observations by showing that both spS1 and spS2 transport mannose, xylose and 499 galactose, and that they differ in their specificity towards fructose and glucose. Corresponding 500 to the yeast assays, we also observed that one of them accepted fructose, the other one glucose 501 as a substrate. Furthermore, we demonstrated that both transporters did not accept L-502 monosaccharides and di-saccharides as substrates.

503

Although not being specific towards one or two potential substrates, many transporters 504 are neither truly generalists and clearly do not transport several "common" monosaccharides.

505

Overrepresentation of glucose-transporting monosaccharide transporters may reflect the 506 widespread occurrence of this sugar in nature (albeit often as monomer of polysaccharides) 507 and its centrality in carbon metabolism [START_REF] Gunina | Sugars in soil and sweets for microorganisms: Review of 654 origin, content, composition and fate[END_REF]. Alternatively, it could 508 also be hypothesized that overrepresentation of glucose-transporting transporters in databases may reflect a scientific bias as numerous fungal transporters were precisely selected for their 510 capacity to transport glucose. For the specific case of mannose, the high prevalence of 511 glucose-transporting porters that can also transport mannose could be explained by the 512 observation that, at least in yeast, genes encoding enzymes necessary for its use as a carbon 513 source (hexokinases and mannose-6-phosphate isomerases) are expressed in both glucose and 514 mannose-containing media. This suggests that these two sugars can be assimilated 515 simultaneously, with however a preference for glucose over mannose.

516

By selecting transporters from metatranscriptomes based on their capacity to transport 517 mannose, we tested the hypothesis that "mannose specific" transporters, or at least 518 transporters that preferentially transport mannose over glucose may be present in soil Furthermore, as an excess of glucose seemingly inhibits these transporters, this observation 560 further suggests that indeed they may only be operational in environments depleted of this 561 sugar.

562

"Other than glucose" (e.g. xylose) monosaccharide transporters have been searched for 563 the independent, simultaneous and non-competitive entry of glucose and other sugars in 564 fungal (e.g. yeast) cells for their simultaneous co-fermentation. Alternatively, these 565 transporters can also be used for the specific utilization of the "other than glucose" 566 monosaccharide as carbon source in a context where glucose is also present. One limitation to 567 this strategy is that transporters that do not transport glucose are often inhibited by this sugar 568 [START_REF] Farwick | Engineering of yeast hexose 640 transporters to transport d-xylose without inhibition by d-glucose[END_REF]Li et al. 2016) which, possibly, clogs the entry pore of the protein. We 569 showed that this phenomenon may also affect mannose transport by mannose porters that do 570 not support glucose transport. Furthermore, we also show that this phenomenon is not 571 glucose-specific but can also be generated by other non-transported sugars such as fructose.

572

Several of the selected environmental transporters could thus be used for the co-fermentation 573 of mannose and other sugars or the specific use of mannose in the presence of other sugars, 574 providing that their inhibition by competing substrates could be relieved [START_REF] Farwick | Engineering of yeast hexose 640 transporters to transport d-xylose without inhibition by d-glucose[END_REF].

575

In the case of xylose transporters, mutagenesis and directed evolution, which resulted in a 576 limited number of changes in the primary sequence, have been successfully employed to 577 render glucose-insensitive the corresponding transporters [START_REF] Farwick | Engineering of yeast hexose 640 transporters to transport d-xylose without inhibition by d-glucose[END_REF]Li et al. 2016).

102

  Indeed, functional data available for fungal sugar transporters suffer from several potential 103 biases. On the one hand, (i) these data have been acquired from a limited number of fungal 104 species not necessarily representative of the phylogenetic and functional diversity of this 105 taxonomic group. On the other hand, (ii) a large number of the characterized transporters had 106 been selected either based on their phylogenetic proximity to already characterized 107 transporters or based on their capacity to transport a restricted number of sugars (often 108 glucose, xylose or fructose in the case of monosaccharide transporters). 109 To overcome the taxonomic bias, in the present study, we selected transporters by the 110 functional complementation of a S. cerevisiae yeast mutant defective in monosaccharide 111 transport using metatranscriptomic libraries made from polyadenylated mRNA extracted from 112 a broadleaf (Fagus sylvatica) and an evergreen (Picea abies) forest soils. Fungal communities 113 present in these soils encompass several hundreds of taxa distributed among several main 114 orders belonging to Basidiomycota, Ascomycota and Mucoromycota (Damon et al. 2010). 115 These taxa encompass nutritional strategies featuring either soil or litter saprotrophs, white or 116 brown rots, plant or animal pathogens and mycorrhizal mutualists. Regarding the sugars used

  117

  located in central 138 France (Breuil-Chenue site, 47°18'10''N, 4°4'44''E). More details about forests, soil 139 characteristics and sampling strategy are given in Damon et al. (2010). Total RNA was 140 extracted from 104 g of each frozen soil samples as previously described (Damon et al. 2010) 141 and eukaryotic cDNAs were synthesized from 3 μg of total soil RNA using the Mint-2 cDNA 142 synthesis kit (Evrogen, Moscow, Russia). After size-fractionation by 2-dimensional agarose 143 gel electrophoresis (Yadav et al. 2014), the recovered 1-3 kb cDNA fractions were PCR-144 amplified (26 cycles using the Mint-2 cDNA synthesis kit) and cloned downstream of the S. 145 cerevisiae PMA1 promoter in the pDR196 yeast-Escherichia coli shuttle vector (Rentsch et 146 al. 1995) into which a kanamycin resistance gene and SfiIA and SfiIB cloning sites had been 147 introduced. For each soil cDNA library, recombinant plasmids were introduced into electro-148 competent E. coli cells (MegaX DH10B™ T1R Electrocomp™ cells, Invitrogen, Thermo 149 Fisher Scientific, Illkirch, France) and at least 2 10 6 kanamycin resistant bacterial colonies 150 growing on agar medium were collected and pooled to constitute two soil cDNA plasmid 151 libraries after alkaline lysis extraction (Sambrook and Russell 2001). 152 Yeast strains, media, and culture methods 153 Environmental cDNAs encoding sugar transporters were selected for their capacity to restore 154 growth on mannose or xylose of yeast mutant strains deleted of their monosaccharide 155 transporters. For mannose, we used the EBY.VW4000 S. cerevisiae mutant strain (MATa 156 leu2-3, 112 ura3-52 trp1-289 his3-Δ1 MAL2-8c SUC2 Δhxt1-17 Δgal2 stlΔ::loxP agt1Δ::loxP 157 mph2Δ::loxP mph3Δ::loxP) unable to use mannose, but also glucose, fructose and galactose 158 as carbon sources

166

  tryptophan and uracil, 0.04; threonine and tyrosine, 0.05; isoleucine, leucine and 167 phenylalanine, 0.06; valine, 0.15 and maltose, 20. Selection of EBY.VW4000 transformants 168 expressing monosaccharide transporters was performed on solid YNB medium lacking uracil 169 and supplemented with amino acids and mannose as sole carbon source. Concerning the 170 EBY.X1-2 strain, it was grown at 30°C in liquid or on solid YNB medium lacking leucine and tryptophan and supplemented with 20 g.l -1 maltose. Selection of EBY.X1-2 transformants 172 expressing xylose transporters was performed on solid YNB medium lacking uracil, leucine and tryptophan and supplemented with xylose as sole carbon source. The wild-type S. 174 cerevisiae CEN.PK2-1C and its mutant derivatives (EBY.VW4000 and EBY.X1-2) were 175 complemented with the empty pDR196-SfiIA/B plasmid to use them as positive and negative 176 controls during growth rate measurements on different monosaccharides, respectively. 177 Selection of fungal sugar transporters by functional yeast complementation 178 Both soil cDNA plasmid libraries (from spruce and beech forest soils) were used to transform 179 S. cerevisiae using a standard lithium acetate protocol (Rose and Broach 1990). Concerning 180 the functional screening on mannose, EBY.VW4000 transformed yeast cells were selected 181 directly on a solid yeast nitrogen base (YNB) minimal medium supplemented with mannose 182 (0.2 or 0.5%) and amino acids but lacking uracil. In the case of xylose-transporter screening, 183 EBY.X1-2 transformed yeast cells were first plated on a solid YNB minimal medium supplemented with 2% maltose and amino acids but lacking uracil, leucine and tryptophan. 185 Then, after 3 days of growth, uracil prototrophic yeast colonies were collected, washed by 186 centrifugation and resuspended in sterile water before being plated on solid YNB minimal 187 medium supplemented with 2% xylose and amino acids but lacking uracil, leucine and 188 tryptophan. Plasmids from the yeast transformants were extracted using the Zymoprep Yeast 189 Plasmid Miniprep I (Zymo Research, Irvine, CA, U.S.A.) and used to transform One Shot 190 TOP10 chemically competent E. coli (Invitrogen) to kanamycin resistance. After plasmid 191 extraction (NucleoSpin Plasmid kit; Macherey Nagel, Hoerdt, France), inserts were Sanger 192 sequenced using primer PMA (5'-CTCTCTTTTATACACACATTC-3') and additional 193 internal primers. The different fungal sugar transporters retrieved from spruce and beech soil 194 cDNA libraries were annotated spS1 to spS12 and spB1 to spB7, respectively. Both yeast 195 mutant strains (EBY.VW4000 and EBY.X1-2) were further transformed with all of these 196 different environmental fungal sugar porters to study their capacity to transport different C6 197 and C5 monosaccharides. Sequences of environmental transporters that support the findings 198 of this study have been submitted to the EMBL database with accession codes LR862110-199 LR862128. 200 Phenotypic characterization of yeast transformants and growth rate measurements 201 The monosaccharide utilization profile of EBY.VW4000 transformants was performed using 202 drop-test assays on solid YNB minimal medium (Rose and Broach 1990) and 203 electrophysiology assays (Damon et al. 2011). Only mannose, fructose and glucose could be 204 tested using drop-test assays as other sugar sources are either not assimilated or naturally 205 transported by the EBY.VW4000 mutant strain. Due to the complexity of the methodological 206 approach, electrophysiological analyses were only performed with potential mannose specific 207 transporters (spS1 and spS2), found by screening of EBY.VW4000 cells, to test the transport 208 of sugar constitutive of cellulose and hemicelluloses (cellobiose, glucuronic acid, glucose, 209 fucose, galactose, rhamnose, arabinose, mannose, fructose and xylose). Additionally, maltose 210 and two disaccharides abundantly found in plant tissues (mannobiose and sucrose) were also 211 tested using these electrophysiological assays. Procedures used to characterize by voltage-212 clamp recordings the sugar transporters spS1 and spS2 expressed in Xenopus laevis oocytes 213 are detailed in Online Resource 1.214Growth rates of the transformed EBY.VW4000 yeast strains were measured in triplicate using 215 a Bioscreen C system (Growth Curves USA, Piscataway, NJ) equipped with a wide-band 216 filter (420 to 580 nm) recommended for optical density (OD) measurements(Young et al.

  2172011). A 1 l inoculum of fully-grown cultures diluted to 5.10 6 cells.ml -1 , was added to each 218 well filled with 250 l of YNB minimal medium supplemented with amino acids but lacking 219 uracil and with 0.1%, 0.5% or 1% (w/v) of carbon source (either maltose, D-glucose, D-220 fructose, D-mannose or D-galactose). The experiment was run 4 days at 30°C using a medium 221 amplitude and normal intermittent shaking (10s) and OD measurement every 10 min. 222 Inhibition of mannose transport by other non-assimilated carbon sources (either glucose or 223 fructose) was assessed in media containing 0, 0.1, 0.5 or 1% mannose and supplemented with 224 either 0 or 1% of either glucose or fructose. Growth rates of EBY.X1-2 transformants in 225 presence of xylose as carbon source were tested in liquid YNB minimal medium 226 supplemented with 1% xylose as described by Colabardini et al. (2014). Yeast transformants 227 were first grown on plates containing solid YNB minimal medium supplemented with 2% 228 xylose. After 21 days of incubation at 30°C, colonies were transferred in 3 ml of YNB 229 minimal medium supplemented with 1% maltose. After 24 h of culture at 180 rpm and 30°C, 230 1.5 10 6 yeast cells were washed with water and transferred in 3 ml of YNB minimal medium 231 supplemented with 1% xylose. Yeast-cell growth was estimated once every 2-3 days during a 232 period of 21 days by measuring the absorption at 600 nm. Exponential growth rates were analyzed using R (version 3.5.3) and the package 234 Growthcurver (Sprouffske et al. 2016). Growth data were fitted to a standard logistic equation 235 and the Area Under the Curve (AUC) parameter was estimated with a 95% confidence 236 interval to be able to detect any significant change between each condition (P value < 0.05). 237 Phylogenetic analyses 238 Environmental transporter sequences were compared to closest reference sequences retrieved 239 from public databases as well as to all sequences of fungal sugar transporters that have been 240 functionally characterized. Sequences highly similar to the selected environmental sugar 241 transporters were identified by BLASTp searches in the GenBank database. For the 242 taxonomic assignation of environmental sequences, the ten best BLAST hits were selected. 243 Amino acid sequences were aligned using MUSCLE (Edgar 2004). Maximum-likelihood 244 (ML) phylogenetic trees were generated with PhyML v.3.0 (Guindon et al. 2010) using the 245 LG substitution model (Le and Gascuel 2008) as implemented in SeaView v.4 (Gouy et al. 246 2010). Robustness of tree topologies was assessed by bootstrap analysis (1000 replicates). 247 Tree was drawn using FigTree v.1.4 (http://tree.bio.ed.ac.uk/software/figtree/). 248 Results 249 Phylogenetic and functional diversity of characterized fungal sugar porters (SPs) 250 From more than 70 literature references, we identified 123 fungal sugar transporters, 251 belonging to the SP family (TC 2.A.1.1) that had been functionally characterized (Online 252 Resource 2). A majority (109) of these genes originated from 30 Ascomycota species with an 253 overrepresentation of Saccharomycotina yeasts (15 species), among which S. cerevisiae is 254 represented by 22 genes. The database included nevertheless two transporters from the 255 Glomeromycotina (2 species) and 12 from the Basidiomycota (7 species). 256 In a majority of cases functional characterization consisted in the expression of the 257 corresponding fungal genes in a S. cerevisiae mutant deleted of its endogenous transporter 258 genes followed by growth tests of the corresponding recombinant strain on one or several 259 sugars that could no longer be assimilated by the yeast mutant (Young et al. 2011; Online 260 Resource 2). Based on this often-fragmentary functional information in terms of number and 261 diversity of tested substrates, we classified the transporters as monosaccharide (M) or 262 oligosaccharide (O) transporters. Monosaccharide transporters encompassed those capable of 263 transporting C5 or C6 monosaccharides but also structurally related molecules such as polyols 264 (e.g. glycerol, mannitol, myo-inositol or sorbitol), gluconic, galacturonic or quinic acids. 265 Oligosaccharides tested as potential substrates were mostly disaccharides (e.g. sucrose, 266 cellobiose, xylobiose, maltose or lactose) and more rarely tri-(e.g. cello-or maltotriose) or 267 tetraoses (cellotetraose). In five cases, transporters had been shown to transport both mono-268 and oligosaccharides (MO transporters). This is the case of the Kluyveromyces lactis LAC12 269 that transports both lactose and galactose Riley et al. 1987; Baruffini et al. 2006), but also of 270 the AGT1, MPH2 and MPH3 "maltose transporters" of S. cerevisiae whose deletions were 271 needed to suppress monosaccharide transport in the EBY.VW4000 mutant strain (Wieczorke 272 et al. 1999). Besides their substrate (sugars) specificities, fungal SPs have also been shown to function as either facilitators (e.g. Jordan et al. 2016) or H + symporters (e.g. Dos Reis et al. 274 2013) co-transporting a proton along with a sugar molecule. Since the transport mode was 275 very rarely assessed for published transporters, this information was not analyzed further. 276 Despite the fact that almost all "M" transporters had not been tested on 277 oligosaccharides and inversely regarding "O" transporters on monosaccharides (Online 278 Resource 2), this simple classification was well supported in a global phylogenetic analysis of 279 the characterized transporter sequences that grouped almost all "O" and "M" transporters in 280 distinct and well-supported clades (bootstrap values >80%; Fig. 1). The very few exceptions 281 to this rule may require additional functional data to further refine their true substrate 282 specificity prior to speculate about occasional reversal of "O" transporters to transport 283 monosaccharides. At least in the case of monosaccharide "M" transporters, sequences 284 originating from a single species, belonging to Ascomycota (e.g. the Saccharomycotina yeast 285 Yarrowia lipolytica or the Pezizomycotina A. nidulans) or to Basidiomycota (e.g. the 286 Agaricomycotina Laccaria bicolor) were often distributed in different clades suggesting that 287 divergences between these sequences occurred at least prior to the divergence between 288 Ascomycota and Basidiomycota. Besides specialization towards mono or oligosaccharides, 289 functional data available for most transporters (Online Resource 2) are however insufficient to 290 attribute a more specific specialization in terms of transported substrates to most clades 291 identified in the global phylogenetic tree. Nevertheless, we observed that six of the seven 292 myo-inositol transporters included in the tree, originating from three Ascomycota and one 293 Basidiomycota species respectively, grouped together to form a homogeneous clade (clade 294 VII, Fig.

  Fig.2). BLASTp searches for spB4 homologs in fully sequenced fungal genomes showed that

  357a single clade (clade III, Fig.1) that encompassed exclusively characterized proteins from 358 Ascomycota species although five of the environmental sequences attributed to this clade were 359 predicted to be from Basidiomycota (spS1, S2, S7, B2and B7; Fig.2). 360 Monosaccharide utilization profiles of sugar transporters isolated from soil cDNA libraries 361 Substrate range and preferences for D-monosaccharides was assessed by measuring the 362 growth of the recombinant EBYVW4000 yeast strain constitutively expressing each of the 363 environmental transporters on different concentrations of either fructose, galactose, glucose 364 and mannose as the sole C sources in both liquid (Fig. 3) and solid (Online Resource 5) 365 media. Additionally, growth of the recombinant EBY.X1-2 yeast strain expressing each of the 366 environmental transporters in combination with the S. stipitis xylose assimilation pathway 367 was assessed on a medium containing 10 g.l -1 of xylose as sole carbon source (Online 368 Resource 6). Regarding the use of C6 sugars a great variability was observed among these proteins in yeast (as already reported for sugar transporters by e.g. Dreyer et al. 1999; 374 Wieczorke et al. 2003) or may suggest that in vivo, in their respective fungal species, these 375 transporters may preferentially transport other sugars.

392

  As already reported in the literature, growth on xylose of recombinant yeast strains 393 expressing a heterologous xylose catabolic pathway is intrinsically low (Tran Nguyen Hoang 394 et al. 2018). We could nevertheless show that 18 out of the 19 environmental transporters 395 supported growth of this strain on xylose (Online Resource 6). Furthermore, all of these 396 proteins harbored the amino-acid motif "G-G/F-XXX-G" (where X represents a variable, but 397 usually non-polar, amino acid residue) in the first predicted transmembrane domain (Online 398 transport in SPs. Only the transporter spB4 belonging to FHS family did not support xylose 400 assimilation at all and did not present this xylose specific amino-acid motif (Online Resource 401 3). 402 To further analyze substrate range and specificity of the environmental transporters, 403 we hypothesized that they could function as symporters and two of them (spS1 and spS2 404 featuring different substrate specificities in growth tests) were expressed in X. laevis oocytes 405 to measure electrophysiological responses in presence of mono-or disaccharides including 406 several sources (e.g. L-C5 or L-C6 monosaccharides, cellobiose or mannobiose) that are not 407 assimilated by the wild-type S. cerevisiae. The selected transporters were spS1, which 408 supported good growth on mannose, moderate growth on fructose, galactose and xylose and 409

  429contrast, fructose was never transported by spS2 (n=6, N=5; Fig.4C) but partly by spS1 (n=5, 430 N=3; Fig.4A,C). However, first experiments suggested that spS1 did not transport fructose 431 (n=4, N=3) most probably by an inhibitory effect of the non-transported glucose due to the 432 sequential arrangement of the tests. This result suggests that glucose might bind to the spS1 433 transporter without inducing currents, thus hindering transport of other substrates. The 434 observed differences for the transport of glucose and fructose for the two tested mannose 435 transporters spS1 and spS2 underline the specificity of such transport systems. Interestingly, 436 both mannose transporters mediated currents in oocytes only for D-mannose but not for L-437 mannose (Fig. 4C; spS1 n=3, spS2 n=4) pointing to highly specific structural requirements 438 needed for binding or transport. Further tests of substrates with either D-or L-configuration 439 were pooled and confirmed the structural substrate specificity. The "L-pool" with L-440 arabinose, L-rhamnose, and L-fucose did not induce any current (spS1 n=5, spS2 n=1). The 441 "D-pool" with D-galactose, D-xylose, and D-glucuronic acid provoked unfortunately 442 endogenous currents also in control oocytes, so that these three substrates had to be tested 443 separately. In fact, D-glucuronic acid destabilized oocytes, even control ones, and could not 444 be tested. However, in agreement with growth measurements, D-galactose and D-xylose 445 induced currents for both transporters (n=3, each; Fig. 4C). In agreement with the 446 phylogenetic placement of the spS1 and S1 transporters among monosaccharide (M) 447 transporters (Fig. 1), four tested disaccharides (maltose (n=5, each), sucrose (spS1 n=3, spS2 448 n=4), mannobiose (n=4 each), and cellobiose (n=4 each)) did not activate any currents in 449 oocytes expressing the two transporters.450

  possibly all fungal SPs characterized thus far and their inclusion in a 461 phylogenetic context support earlier observations, made on more fragmentary datasets, of a 462 clear separation between mono-and oligosaccharide SPs in the Fungi (e.g. Peng et al. 2018) 463 However, the present analysis did not address the issue of potentially multiple origins of 464 either mono-or oligosaccharide clades of SPs in the Fungi. The presence, in several of the 465 clades, of transporters from both the Basidiomycota and Ascomycota and even from the 466 Glomeromycotina suggests that the corresponding clades originated early during the 467 diversification of the Fungi. Alternatively, this distribution of transporters across the 468 phylogenetic tree could also be the results of horizontal gene transfers between species 469 belonging to different clades as demonstrated for other transporter genes (Slot et al. 2007; 470 Coelho et al. 2013). 471 Confrontation of the functional database to the SP phylogenetic tree suggested that 472 few clades of "monosaccharide transporters" may feature functional specialization on specific 473 substrates structurally related to monosaccharides, such as myo-inositol, acidic sugar 474 derivatives or glycerol. This phylogenetic information could thus be used for the functional 475 annotation of similar transporters from sequenced fungal genomes. As for the other clades of 476 monosaccharide transporters, they encompass sequences that transport bona fide 477 monosaccharides (either C5 or C6 sugars), but also sugar alcohols without any clear 478 correspondence between clade identity and the exact nature of the transported molecules. 479 While for several yeast species (e.g. S. cerevisiae or Schizosaccharomyces pombe), most of 480 their monosaccharide SP genes seemed to originate from recent duplication events and belong 481 to the same clade, other species (e.g. A. nidulans, N. crassa, or Y. lipolytica) seem to rely on 482 different highly divergent SPs, belonging to different clades for their supply of 483 monosaccharides. 484 indicates that a large majority of the studied transporters accepts several sugars as substrates 486 and that specificity towards one or two molecules seems to be an exception (Online Resource 487 1). In this respect, occasional claims of a substrate-specific transporter often reflect the fact 488 that a very limited number of potential substrates have been studied (e.g. Wang et al. 2016). It 489 could however be argued that overexpression of a sugar transporter in the yeast S. cerevisiae, 490 the most widely used approach to characterize such transporters from fungi (Young et al. 491 2011), may overestimate the substrate range of the corresponding transporter. Overexpression 492 may indeed allow significant influx of otherwise poorly transported substrates (Dreyer et al.

  493

  519 organisms occasionally confronted to carbon sources with particularly high mannose content 520 (e.g. gymnosperm plant biomass or fungal necromass) (Lipke and Ovalle 1998; Schädel et al. 521 2010)). As previously observed in the case of oligopeptides (Damon et al. 2011), the 522 screening of environmental cDNA libraries for sugar transporters yielded genes from only 523 Fungi, although genes from other eukaryotic organisms were present among the studied 524 metatranscriptomes (Damon et al. 2012). Furthermore, all but one of the selected genes 525 encoded proteins that belonged to the SP family, suggesting that other sugar transporters 526 reported in fungal genomes may play a minor role in sugar assimilation by fungi. From a 527 taxonomic perspective, eight of the environmental transporters likely originated from 528 Basidiomycota, thus doubling the number of characterized sugar transporters from this fungal 529 phylum published thus far (Online Resource 1). From a phylogenetic perspective, 530 environmental SPs were distributed in several of the distinct clades that form this protein 531 family. However, more than half of them (11), from both Basidiomycota and Ascomycota, fell 532 in a single clade (clade III in Fig. 1) that, thus far, encompassed only published Ascomycota 533 sequences. This uneven distribution of environmental SPs across the global phylogenetic tree 534 of this fungal protein family could originate from a preferential functional expression of these 535 structurally related proteins in yeast. It could also suggest that Fungi preferentially use SPs 536 from a limited number of clades for their supply in monosaccharides. This latter hypothesis 537 could be addressed in model organisms by measuring the relative expression levels and 538 contribution to monosaccharide utilization of endogenous sugar porter encoding genes 539 belonging to different evolutionary lineages. Finally, screening of soil metatranscriptomes 540 also yielded a highly divergent fungal sugar transporter sequence (spB4) that belonged to the 541 poorly studied "Fucose: H + Symporter" (FHS) family (TC 2.A.1.7). In Fungi, only one 542 member of this FHS family able to transport monosaccharides was reported so far. In A. 543 niger, the related RhtA transports L-rhamnose and marginally D-fructose (Sloothaak et al. 544 2016). Since both rhamnose and fucose are deoxy sugars that occur in nature in the unusual 545 levorotary (L-) conformation, it could be hypothesized that fungal FHS family members are 546 specialized on these substrates and marginally accept other sugars as in the case of spB4 that 547 confers poor growth of recombinant S. cerevisiae on mannose and all other tested sugars. This 548 hypothesis could be tested by expression of this protein, as well as other homologous ones 549 found in fungal genomes, in X. laevis oocytes as performed for the spS1 and spS2 SPs. 550 Overall, our observations that result from the analysis of "environmental" sequences further 551 illustrate the power of functional genomics for quickly accessing the true diversity of specific 552 eukaryotic protein families (Damon et al. 2011; Marmeisse et al. 2017). 553 From a functional perspective, the analysis of environmental fungal sequences 554 reevaluates the known functional diversity of fungal SPs. It revealed the existence of 555 phylogenetically distinct transporters that allow mannose, but not glucose transport. This 556 lends support to the hypothesis that the presence of sugars other than glucose in the 557 environment may have led to the independent evolution of sugar transporters that 558 preferentially use mannose (and eventually other monosaccharides) over glucose.

578

  Paulsen PA, Custódio TF, Pedersen BP (2019) Crystal structure of the plant symporter STP10 711 illuminates sugar uptake mechanism in monosaccharide transporter superfamily. Nat 712 Commun. 10:407. doi: 10.1038/s41467-018-08176-9. 713 Peng M, Aguilar-Pontes MV, de Vries RP, Mäkelä MR (2018) In silico analysis of putative 714 sugar transporter genes in Aspergillus niger using phylogeny and comparative 715 transcriptomics. Front Microbiol 9:1045. 716 Popper ZA, Tuohy MG (2010) Beyond the green: understanding the evolutionary puzzle of 717 plant and algal cell walls. Plant Physiol 153:373-83. doi:10.1104/pp.110.158055. catabolism in recombinant Saccharomyces cerevisiae. Biotechnol Biofuels 5:14. 759 doi:10.1186/1754-6834-5-14 760 Takanaga H, Frommer WB (2010) Facilitative plasma membrane transporters function during 761 ER transit. FASEB J 24:2849-2858. 762 Tran Nguyen Hoang P, Ko JK, Gong G, Um Y, Lee SM (2018) Genomic and phenotypic 763 characterization of a refactored xylose-utilizing Saccharomyces cerevisiae strain for 764 lignocellulosic biofuel production. Biotechnol Biofuels 11:268. doi:10.1186/s13068-018-765 1269-7 766 Trichez D, Knychala MM, Figueiredo CM, Alves SL Jr, da Silva MA, Miletti LC, de Araujo 767 PS, Stambuk BU (2019) Key amino acid residues of the AGT1 permease required for 768 maltotriose consumption and fermentation by Saccharomyces cerevisiae. J Appl Microbiol 769 126:580-594. doi: 10.1111/jam.14161 770 Wang M, Yu C, Zhao H (2016) Directed evolution of xylose specific transporters to facilitate 771 glucose-xylose co-utilization. Biotechnol Bioeng 113:484-491. doi:10.1002/bit.25724 772 Wieczorke R, Krampe S, Weierstall T, Freidel K, Hollenberg CP, Boles E (1999) Concurrent 773 knock-out of at least 20 transporter genes is required to block uptake of hexoses in 774 Saccharomyces cerevisiae. FEBS Lett 464:123-128. doi:10.1016/s0014-5793(99)01698-1 775 Wieczorke R, Dlugai S, Krampe S, Boles E (2003) Characterisation of mammalian GLUT glucose 776 transporters in a heterologous yeast expression system. Cell Physiol Biochem. 13:123-134. doi: 777 10.1159/000071863 778 Wisedchaisri G, Park MS, Iadanza MG, Zheng H, Gonen T (2014) Proton-coupled sugar 779 transport in the prototypical major facilitator superfamily protein XylE. Nat Commun 5:4521.

  780 doi: 10.1038/ncomms5521.

Fig. 1

 1 Fig. 1 Phylogenetic diversity of 104 functionally characterized fungal sugar transporters

  816

Fig. 2

 2 Fig. 2 Putative taxonomic origins of the 19 environmental sugar transporter proteins retrieved

  822

Fig. 3

 3 Fig. 3 Growth of recombinant S. cerevisiae EBYVW4000 strain expressing each of the 19

Figure

  Figure

Fig. 3 Fig. 4

 34 Fig. 3

Acknowledgements.

718

Protzko RJ, Latimer LN, Martinho Z, de Reus E, Seibert T, Benz JP, Dueber JE (2018).

environmental transporters. While for each transporter, mannose was always the best sugar, or 370 among the best, in terms of final biomass yield at the end of the culture period (4 days), this 371 yield was particularly low for several transporters (namely spB4, spS2 and spS7) on all of the 372 tested concentrations of the different sugars. This may be the result of improper expression of Resource 3). According to [START_REF] Young | Rewiring yeast sugar transporter 790 preference through modifying a conserved protein motif[END_REF], this motif represents a signature for xylose The EBY.VW4000 S. cerevisiae mutant strain used to select environmental transporters was


Ai Kamitani

Satoshi Morishita

Hiroshi Kotaki

S Arscott

Miniaturized microDMFC using silicon microsystems techniques: performances at low fuel flow rates

published or not. The documents may come


Zouhour Hsine
email: zouhourhsine1@gmail.com

Saber Blili

Rym Milka

Hélène Dorizon

Ayoub Haj Said

Hafsa Korri- Youssoufi

Sensor based on

Keywords: Poly(para-phenylene), ferrocene, electrochemical detection, dopamine, ascorbic acid, uric acid

teaching and research institutions in France or abroad, or from public or private research centers.

Sensor based on redox conjugated poly(para-phenylene)

for the simultaneous detection of dopamine, ascorbic acid, and uric acid in human serum sample

Zouhour Hsine, Saber Blili, Rym Milka, Hélène Dorizon, Ayoub Haj Said,

Hafsa Korri-Youssoufi

To cite this version:

Zouhour Hsine, Saber Blili, Rym Milka, Hélène Dorizon, Ayoub Haj Said, et al.. Sensor based on redox conjugated poly(para-phenylene) for the simultaneous detection of dopamine, ascorbic acid, and uric acid in human serum sample. Analytical and Bioanalytical Chemistry, 2020, 412 [START_REF] Du | Novel graphene flowers modified carbon fibers for simultaneous determination of ascorbic acid, dopamine and uric acid[END_REF], pp.4433-4446. [START_REF] Wang | Neurotransmitter and psychostimulant recognition by the dopamine transporter[END_REF].1007/s00216-020-02686-6. hal-03066386

Introduction

Biomolecules such as dopamine [START_REF] Zhang | Highly Sensitive and Selective Detection of Dopamine Using One-Pot Synthesized Highly Photoluminescent Silicon Nanoparticles[END_REF][START_REF] Shang | Catalyst-Free Efficient Growth, Orientation and Biosensing Properties of Multilayer Graphene Nanoflake Films with Sharp Edge Planes[END_REF]-dihydroxyphenyl ethylamine, DA), ascorbic acid (vitamin C, AA) and uric acid (7,9-dihydro-1H-purine-2,6,8(3H)-trione, UA) coexist in the central nervous system and blood, and play a crucial role in human metabolic processes [START_REF] Zhang | Electrochemical sensing platform based on the biomass-derived microporous carbons for simultaneous determination of ascorbic acid, dopamine, and uric acid[END_REF][START_REF] Li | Association of Uric Acid with Metabolic Syndrome in Men, Premenopausal Women and Postmenopausal Women[END_REF].

Each biomolecule has its own role in the metabolic system. DA is an influential neurotransmitter present in the central nervous system (CNS) of the human body [START_REF] Zhang | Highly Sensitive and Selective Detection of Dopamine Using One-Pot Synthesized Highly Photoluminescent Silicon Nanoparticles[END_REF]. Lack of DA leads to neurological disorders, like Parkinson's disease, schizophrenia and Alzheimer [START_REF] Shang | Catalyst-Free Efficient Growth, Orientation and Biosensing Properties of Multilayer Graphene Nanoflake Films with Sharp Edge Planes[END_REF][START_REF] Wu | Sensitive electrochemiluminescence sensor based on ordered mesoporous carbon composite film for dopamine[END_REF]. AA has antioxidant properties [START_REF] Huang | Simultaneous electrochemical determination of dopamine, uric acid and ascorbic acid using palladium nanoparticle-loaded carbon nanofibers modified electrode[END_REF] and deficiency causes a disease called scurvy, which leads to a disturbance in the collagen metabolism [START_REF] Jothi | Simultaneous determination of ascorbic acid, dopamine and uric acid by a novel electrochemical sensor based on N2/Ar RF plasma assisted graphene nanosheets/graphene nanoribbons[END_REF], and a tendency to bleed and reduce women's fertility [START_REF] Shakkthivel | Simultaneous determination of ascorbic acid and dopamine in the presence of uric acid on ruthenium oxide modified electrode[END_REF]. UA is the end product of purine catabolism in humans [START_REF] Carvalho | Uric acid disrupts hypochlorous acid production and the bactericidal activity of HL-60 cells[END_REF] and it's abnormal concentration levels indicates some diseases, such as gout disease, hyperuricemia and Lesch-Nyhan syndrome [START_REF] Wang | Neurotransmitter and psychostimulant recognition by the dopamine transporter[END_REF]. Therefore, it is essential for the diagnosis of these diseases to detect DA, AA and UA levels in human physiological fluids. The three main methods to detect the level of these compounds in body fluids are liquid chromatography [START_REF] Wang | Electrochemical sensing and biosensing platform based on biomass-derived macroporous carbon materials[END_REF], capillary electrophoresis [START_REF] Herrasti | Electrochemical detection of dopamine using streptavidin-coated magnetic particles and carbon nanotube wiring[END_REF] and fluorescence spectroscopy [START_REF] Ebru Seçkin | Flow injection fluorescence determination of dopamine using a photo induced electron transfer (PET) boronic acid derivative[END_REF]. However, these techniques are associated with sample pretreatment, which requires a long time. Electrochemical sensors have numerous advantages thanks to the direct measurement without sample treatment, high sensitivity, fast response, low cost and could achieve the simultaneous detection of many compounds [START_REF] Qi | Determination of ascorbic acid, dopamine, and uric acid by a novel electrochemical sensor based on pristine graphene[END_REF][START_REF] Kimmel | Electrochemical Sensors and Biosensors[END_REF]. Thus DA, AA and UA are highly electroactive molecules able to give electrochemical responses directly associated with their amount in complex samples [START_REF] Peik-See | Simultaneous Electrochemical Detection of Dopamine and Ascorbic Acid Using an Iron Oxide/Reduced Graphene Oxide Modified Glassy Carbon Electrode[END_REF][START_REF] Florescu | Tyrosinase-Based Biosensors for Selective Dopamine Detection[END_REF] .

However, the main problem of electrochemical detection of these compounds is their redox potential of oxidation, which takes place in a similar range on classical unmodified electrode preventing their simultaneous detection [START_REF] Du | Novel graphene flowers modified carbon fibers for simultaneous determination of ascorbic acid, dopamine and uric acid[END_REF]. In addition, many other redox-active molecules present in the fluids sample could interfere and reduce the selectivity of the sensors [START_REF] Zhang | Electrochemical sensing platform based on the biomass-derived microporous carbons for simultaneous determination of ascorbic acid, dopamine, and uric acid[END_REF].

Another problem for the detection of these analytes is the variation of their concentrations in biological fluids, which depends on the nature of the biomolecules and the diseases. Thus, a very low concentration of DA in the nanomolar range exists in the extracellular fluid for patients suffering from Parkinson's disease and it varies from 0.01 to 1 µM for a healthy individual [START_REF] Venton | Realtime decoding of dopamine concentration changes in the caudate-putamen during tonic and phasic firing[END_REF]. However, the other molecules such as AA and UA in extracellular fluids are present with high concentrations level in healthy individuals in about µM to mM range.

Therefore, the simultaneous determination of these biomolecules with a good peak-to-peak separation, a good selectivity and a large liner range remained a challenge. The design of sensors for selective determination depends heavily on the nature of electrode surface used for the detection process. In this respect, a large number of materials have been applied for selective detection as shown in the review [START_REF] Si | Recent Advances in the Detection of Neurotransmitters[END_REF]. However, they suffer from major drawbacks such as the complicated electrode fabrication process, instability and selectivity for simultaneous detection of the various biomolecules in complex media. In this context, the use of conducting organic polymer as a sensing material is another common practice in the field of sensors. This is related to their properties such as, electrochemical activity, the ease of synthesis, large specific surface area and high stability [START_REF] Gracia | Polymers with redox properties: materials for batteries, biosensors and more[END_REF][START_REF] Moon | Conducting polymer-based electrochemical biosensors for neurotransmitters: A review[END_REF]. Various conducting polymers have been used for DA detection such as Poly(o-anisidine) [START_REF] Sangamithirai | Fabrication of neurotransmitter dopamine electrochemical sensor based on poly(o-anisidine)/CNTs nanocomposite[END_REF], polypyrrole [START_REF] Harley | The selective detection of dopamine at a polypyrrole film doped with sulfonated β-cyclodextrins[END_REF], polyaniline [START_REF] Feng | Polyaniline/Au Composite Hollow Spheres: Synthesis, Characterization, and Application to the Detection of Dopamine[END_REF]. The conductivity of these materials enhances signal transduction of biomolecule but some challenge stills in selectivity. To improve selectivity other functionalities could be added by the modification of polymers or by their association with other materials. It' has been demonstrated that materials bearing negative charges and having an anionic form improve the selectivity of the sensors, prevent non-specific interaction [START_REF] Chandra | Investigation on the downregulation of dopamine by acetaminophen administration based on their simultaneous determination in urine[END_REF] and enlarge the separation peaks between AA, DA and UA through electrostatic interaction [START_REF] He | CVD graphene incorporating polymerized Lcysteine as an electrochemical sensing platform for simultaneous determination of dopamine and ascorbic acid[END_REF][START_REF] Mathew | Direct electrochemical reduction of hematite decorated graphene oxide (α-Fe2O3@erGO) nanocomposite for selective detection of Parkinson's disease biomarker[END_REF]. Also redox molecules such as ferrocene modified nanomaterials give excellent electrocatalytic activity toward the oxidation of DA [START_REF] Kamyabi | Electrocatalytic oxidation and determination of nitrite on carbon paste electrode modified with oxovanadium(IV)-4-methyl salophen[END_REF]. Consequently, combining various properties in one material with easy production can be a challenge for the simultaneous detection of the three biocompounds in a complex sample.

Here we describe a redox conducting polymer based on poly(para-phenylene) (PPP)

bearing ferrocene (Fc) and carboxylic acid (Ac) as functional groups in side chains (Fc-ac-PPP) (Figure 1) which could provide a good surface for the simultaneous and selective detection of DA, AA and UA. This polymer presents a conjugated surface arising from aromatic ring, high conductivity and catalytic properties arising from ferrocene redox molecules and carboxylic acid groups attached in lateral position that provide electroactive and anionic surface. The design of electrochemical sensor for the individual and the simultaneous detection of DA, AA and UA based on Fc-ac-PPP modified Au electrode has been achieved. The sensor design is made by drop-casting of organic soluble polymer and the detection followed through electrochemical measurements with Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV), and chronoamperometry (CA) in both PBS and biological fluid such as urine and human serum samples.

Insert Fig. 1 2. Experimental

Reagents and materials

Reagents

The poly(p-phenylene) (PPP) modified with ferrocene groups (Fc), as side chains (Fc-PPP) has been synthesized and characterized by NMR and FTIR as described previously [START_REF] Bizid | Investigations of poly(p-phenylene) modified with ferrocene and their application in electrochemical DNA sensing[END_REF],

the poly(p-phenylene) (PPP) modified with ferrocene groups (Fc) and carboxylic acids (Ac) as functional groups in side chains (Fc-ac-PPP) has been prepared by the alkaline hydrolysis of the Fc-PPP and confirmed by FTIR spectra as described previously [START_REF] Bizid | Direct Electrochemical DNA Sensor based on a new redox oligomer modified with ferrocene and carboxylic acid: Application to the detection of Mycobacterium tuberculosis mutant strain[END_REF]. ) were made fresh before use each 2 days and storing at 4 °C for the second use. All solutions were prepared using deionized water produced by milli-Q water system. All other chemicals were of analytical grade and used without further purification.

Chloroform

Instrumentation

Electrochemical measurements were performed using an AUTOLAB PGSTAT 100 electrochemical analysis system controlled by NOVA software (Methrom). A three-electrode system was used with the bare Au (surface 2.01×10 -2 cm 2 ) or modified Au with Fc-PPP or Fcac-PPP polymers were used as the working electrode; an Ag/AgCl (3 M KCl) was used as reference electrode and platinum wire as counter electrode. The three-electrode cell was purchased from Sigma-Aldrich (France). The analyses were performed by cyclic voltammetry (CV), differential pulse voltammetry (DPV) and chronoamperometry (CA). The modified Au electrode is normally placed in a 0.1 M phosphate buffer solution (PBS (0.1 M), pH=7)

containing target species such as DA, AA and UA and then simply followed by fixing or scanning the potential. All experiments were conducted at ambient temperature (25 ± 0.1 °C).

The Au electrode was polished before each experiment.

Cyclic voltammetry (CV) analysis were realized in PBS (0.1 M, pH=7) with scan rate 50 mVs -1 .

Differential pulse voltammetry (DPV) measurements were carried out, with pulse height = 2.5 mV, pulse width = 100 ms, step height = 5 mV, step time = 500 ms, and scan rate = 10 mV s -1 .

Chronoamperometry (CA) detection of AA, DA and UA were performed in stirring PBS, with the potential set at -0.26 V, 0.17 V and 0.52 V respectively.

Surface preparation and modification

Before the analysis, in order to improve the adhesion of the Fc-PPP and Fc-ac-PPP polymers on the electrode surface, the gold substrates were cleaned with acetone in an ultrasonic bath for 10 min and dried under nitrogen flow. Then the electrode was activated by electrochemical oxidation and reduction in 0.5 M H 2 SO 4 aqueous solution by applying a potential range from -0.2 V to 1.9 V at a scan rate of 100 mVs -1 . After a thorough rinsing with distilled water, the gold surfaces were dried under nitrogen flow before electrochemical measurements. The Fc-ac-PPP and Fc-PPP solutions have been prepared by dispersing 5 mg of each polymer in 1.5 mL CHCl 3 , and ultra-sonicated for 30 min. The gold surface, after polishing steps, was dropped with an optimum amount of 5 µl Fc-ac-PPP or Fc-PPP solution as optimized previously [START_REF] Bizid | Direct Electrochemical DNA Sensor based on a new redox oligomer modified with ferrocene and carboxylic acid: Application to the detection of Mycobacterium tuberculosis mutant strain[END_REF] followed by a drying step under ambient temperature during 30 min. After the evaporation of the volatile solvent, the modified gold surface was then rinsed with distilled water to remove non-attached molecules.

Results and Discussion

The electrochemical properties of Fc-PPP and Fc-ac-PPP have been characterized by CV (see SI.1.1, Figure S1). An increase of the redox peak of Fc-ac-PPP compared to Fc-PPP has been observed. These results have demonstrated that adding carboxylic acid functionalities on the backbone of Fc-PPP enhanced it's conductivity and charge transfer coming from both redox center and π-conjugated aromatic backbone.

Electrochemical activity of DA, AA and UA on various modified surfaces

DPV of the various compounds at a concentration of normal level in healthy body (10 - 5 M DA, 10 -3 M AA, 10 -3 M UA) have been analyzed individually and in mixture at bare Au, Au/Fc-PPP and Au/Fc-ac-PPP (Figure 2). As can be seen in Figure 2A, the Ipa of DA at Au/Fc-PPP (Curve b) and Au/Fc-ac-PPP (Curve c) were 1.5 and 3 times higher than that bare Au (Curve a) which indicates that both polymers are very suitable for DA sensing. In Figures 2B and2C , we have observed that Ipa of AA and UA at Fc-PPP (curves b) is higher than that Au and Fc-ac-PPP (curves a and c) which indicates that Fc-PPP is more active for AA and UA sensing than the other electrodes. It is obvious that DA, AA and UA biomolecules with different structures have different interaction modes on the Au/Fc-PPP and Au/Fc-ac-PPP surfaces, which make it possible to realize the goal for simultaneous determination of AA, DA and UA. In order to clearly show the ability of the electrodes for the simultaneous determination of AA, DA and UA, the DPV results obtained in the co-existence system of AA, DA and UA are shown in Figure 2D. At bare Au (curve a), the oxidation peaks of DA and UA show a broad overlapped peak at 370 mV so that the simultaneous detection of AA, DA and UA at Au electrode is impossible [START_REF] Xiao | Hollow nitrogen-doped carbon microspheres pyrolyzed from self-polymerized dopamine and its application in simultaneous electrochemical determination of uric acid, ascorbic acid and dopamine[END_REF]. At Au/Fc-PPP (curve b), we observed an increase of the peaks intensities of AA, DA and UA compared to Au electrode, however Au/Fc-PPP still incapable to discriminate between DA and UA peaks. Consequently, Fc-PPP polymer can not be used as a platform for the simultaneous detection of the three biomolecules. In contrast, Au/Fc-ac-PPP (curve c) depicts a very well-defined redox signals with intense peaks currents for each analyte compared with bare Au and Au/Fc-PPP. The peaks potentials at about -262 mV, 177 mV, and 526 mV are for AA, DA and UA respectively and peaks separations for AA-DA and DA-UA are 439 mV and 349 mV, respectively, which are superior to that of the previously reported works (Table 1). These results affirm that Au/Fc-ac-PPP not only enhances the peaks currents of AA, DA and UA, but also favorably enlarges the peak separation when they are in mixture. Therefore, the catalytic current as well as the simultaneous detection of AA, DA and UA in mixture are enhanced by the presence of both carboxylic acid and ferrocene on the poly(para-phenylene).

Insert Fig. 2

Effect of pH and scan rate in the response of both polymers

The composition of the supporting electrolytes and pH plays an important role in proton transfer at electrode-solution interface, which in turn can alter the adsorption phenomenon and the kinetics of the charge transfer process at the electrode surface.

Therefore, the effect of various PBS buffers with pH ranges from 4 to 9 have been investigated for the redox process of DA, AA and UA on Au/Fc-PPP and Au/Fc-ac-PPP electrodes (Figure S2). Using figure S2, we have plotted the Ipa variations of AA, DA and UA oxidation versus the different pH ranges using Au/Fc-PPP and Au/Fc-ac-PPP electrodes (Figures 3A, 3C and3E). Concerning the DA, it can be seen in Figure 3A that Au/Fc-ac-PPP (curve b) leads to a higher peak current intensity of DA than the surface modified with Au/Fc-PPP (curve a) in all over pH range. This result could suggest that the acid groups in Au/Fcac-PPP are investigated during redox process of DA favoring its diffusion on the surface due probably to electrostatic interaction with the surface. On the contrary, for AA and UA, Figures 3C and3E, show that Au/Fc-PPP (curves a) depicts a higher peak current intensity for their oxidation than Au/Fc-ac-PPP (curves b) electrode in all over pH range. Thus, the anionic charge provided by acid group disfavors the electrochemical behavior of the two compounds compared to the non-anionic surface.

These results can be a good explanation for the ability of Fc-ac-PPP to separate DA, AA and UA peaks oxidation when they are in ternary mixture, because it demonstrates the importance of COOH groups in the Fc-ac-PPP polymer which not only enhances the conductivity of the polymer but also it realizes the electrostatic interaction with the three biomolecules.

Therefore, Fc-ac-PPP will be used in the following work with the aim to detect simultaneously DA, AA and UA.

Using Au/Fc-ac-PPP electrode (curves b), we have observed in Figure 3A that the best pH for DA peak oxidation is equal to 7, however for AA and UA (Figures 3C and3E) the best pH for their oxidation peaks can be observed to be between 7 and 8. Consequently, considering that the physiological pH is around 7, pH=7 will be optimized and fixed for all the rest of our work.

In order to highlight the number of electrons and protons involved during the oxidation of AA, DA and UA. We have plotted E pa variations of AA, DA and UA peaks oxidation versus the different pH ranges using Au/Fc-PPP and Au/Fc-ac-PPP electrodes (Figures 3B, 3D and3F). For DA, it can be seen in Figure 3B that the E pa varies linearly with the pH over the range 4-9. The corresponding linear regression equation for Au/Fc-PPP and Au/Fc-ac-PPP are expressed respectively as E pa (pH)= -0.0392 pH + 0.4821, E pa (pH)= -0.0473 pH + 0.5455 with a coefficient regression of R 2 value of 0.9883 and 0.9806 respectively. The slope of the regression equation corresponding to the Au/Fc-ac-PPP electrode is close to the expected Nernstian theoretical value of 59.1 mV/pH which indicates equal number of electrons and protons transfer process, therefore two protons and two electrons were involved in oxidation process [START_REF] Lian | Simultaneous determination of ascorbic acid, dopamine and uric acid based on tryptophan functionalized graphene[END_REF]. However for AA (Figure 3D), its oxidation potential does not change all over pH range using Au/Fc-ac-PPP (curve b). The same behavior was observed for UA (Figure 3F) over the range 6-9, but its oxidation potential varies linearly only with the pH over the range 4-6 with a linear regression equation of E pa (pH)= -0.0265 pH + 0.6585 (R 2 =0.8398) (curve b). The unchangeable oxidation potential of AA and UA using Fc-ac-PPP could be related to the low proton transfer at this pH range due to the low pKa of these compounds. For Fc-PPP polymer, the oxidation potentials of AA and UA varies linearly with the pH only over the range 6-9 (Figures 3D and3F). Their linear regression equations stated respectively as E pa (pH)= 0.0158 pH -0.4332 (R 2 =0.9964), E pa (pH)= -0.0447 pH + 0.7794 (R 2 =0.9338) respectively (curves a).

Insert Fig. 3 The effect of scan rate on CV and DPV responses of DA, AA and UA at Au/Fc-ac-PPP has been investigated to demonstrate the kinetics of the electrochemical reaction process (Figure 4A, 4B and4C). The linear relationships of the peak current versus scan rate (Figures 4a1, 4b1 and4c1) and versus square root of the scan rate (Figures 4a2, 4b2 and4c2) from 10 mVs -1 to 100 mV s -1 has been built. For each analyte, we have observed that the regression coefficient (R 2 ) value for the dependence of oxidative peak current on the scan rate [I pa (µA)=f (V(mVs -1 ))] is higher compared to the square root of scan rate [I pa (µA)=f (√V(mVs -1 ) 1/2 )].

Consequently, the electrochemical behavior of AA, DA and UA at Au/Fc-ac-PPP is electron transfer controlled process rather than diffusion. The same behavior has been demonstrated previously with carbon paste electrode (CPE) surface modified with the layer double hydroxide (LDH) and carbon quantum dots (CQD) (LDH / CQD/CPE) for metronidazole determination in which a better correlation coefficient was obtained for the dependence of reductive peak current on the scan rate (R 2 = 0.9927) compared to the square root of scan rate (R 2 = 0.95) [START_REF]A novel electrochemical sensor based on LDH / CQD @ Carbon paste electrode for voltammetric determination of metronidazole in real Samples[END_REF].

Insert Fig. 4

Simultaneous determination of DA, AA and UA at Au/Fc-ac-PPP

The electrochemical activity of Au/Fc-ac-PPP electrode provides a substantial basis for simultaneous determination of AA, DA and UA. In the following measurements, the concentration of the target biomolecule was only changed, while concentrations of the other two biomolecules were kept constant (Figures 5A, 5C and5E). We have observed that the electrochemical response of the target biomolecule increased linearly with the increase of its added concentration, while those of the other two biocompounds remain unchanged indicating selectivity of the modified electrode. The linear relationships between peak currents and concentrations of the three biomolecules are exhibited in Figures 5B, 5D and 5F. From these curves, a linear regression equations have been obtained with high coefficient regression. The detection limits (LOD) have been calculated based to signal to noise ratio S/N=3 and taking into account the standard deviation obtained for blank test with 3 repetitive measurements.

LODs are found to be 3×10 -10 M, 1.68×10 -8 M and 1.03×10 -8 M for the DA, AA and UA, respectively. These results strongly demonstrate that DA, AA and UA can be determined selectively and sensitively at the proposed sensor in their ternary mixture. In addition, it should be noted that the above analytical characteristics for the determination of the DA in the mixture of AA and UA at the Au/Fc-ac-PPP are nearly the same with that obtained in a solution only containing DA (see SI.1.3, Figure S3), confirming that AA and UA didn't affect the detection measurement.

Insert Fig. 5 3.4. Analytical performance

Measurement by chronoamperometry (i-t) (CA)

Chronoamperometric measurement is a powerful method to evaluate the response time as well as the sensitivity of the sensor. This method has been used for the individual detection of DA, AA and UA by selecting working potentials of each biomolecule on Au/Fc-ac-PPP.

All measurements have been made in stirred PBS and different concentrations for each target biomolecule have been added at steady intervals of 60 s. The amperometric current-time plots of DA, AA, and UA at the Au/Fc-ac-PPP are displayed in Figure 6. We have observed that the current signal rose rapidly with each addition of the target analyte, then reaching a steadystate current within 4 s (Figures 6A, 6C and6E). These results indicate a fast oxidation response behavior and a high sensitivity of the sensor to small changes in the concentration of the target biomolecule. A good linear relationship between the peak current and logarithm scale of the added concentration have been obtained for the three biomolecules (Figures 6B, 6D and 6F). Thus, detection limit of DA, AA and UA calculated from their calibration curves have been found to be 1.17×10 -10 M, 1.11×10 -8 M and 1.01×10 -8 M respectively. These LODs values are almost the same as previously in the case of the DPV.

Comparing the sensing performances of the Au/Fc-ac-PPP to other reported electrochemical sensor systems (Table 1), Au/Fc-ac-PPP sensor presents the lowest LOD for DA, the larger linear range for its detection and the higher peak to peak separation between AA-DA and DA-UA. Other advantages of the proposed sensor were that, in our work, DPV as well as chronoamperometry could be used to follow the presence of these biocompounds. Moreover, our fabrication method is based only on drop-casting and drying which is more facile and less time consuming than other methods. Insert Fig. 6

Selectivity, reproducibility, reusability and stability

Interference study of the proposed sensor towards the DA is an essential parameter in electrocatalysis. As discussed above, we have demonstrated that AA and UA do not influence the detection of DA. Therefore, it is necessary to test the interference of other different kinds of ions and biological molecules that coexist in the biological sample along with the DA and could cause interference during the detection. The impact of 10 -3 M of KCl, NaCl, NH 4 Cl, glucose, glycine and citric acid on the detection of different concentrations of DA has been investigated using Chronoamperometry (Figure 7A). It was clearly seen a well-marked amperometric signal for each addition of DA concentration, whereas no response was observed for any interfering molecule. This result proves that Au/Fc-ac-PPP displays outstanding anti-interfering behavior.

To test the reproducibility of the sensor, thirty Au/Fc-ac-PPP electrodes have been prepared independently and their peak currents for AA, DA and UA mixture have been investigated (Figure 7B). No significant change in the oxidation peak current of the three bioanalytes was observed as evident by the low relative standard deviation (RSD) for AA, DA and UA, which are 0.81%, 0.90% and 1.02% respectively. This result suggests the appreciable reproducibility of the proposed Au/Fc-ac-PPP.

The regeneration of the Au/Fc-ac-PPP sensor has been also investigated. CV of Au/Fc-ac-PPP in PBS before (curve a) and after regeneration (curve b) has been studied. The regeneration has been realized by removing the adsorbed DA at the modified surface by sonication in PBS for 6 min (30 Watts, Ultrasonic bath). The Au/Fc-ac-PPP in the presence of 10 -5 M of DA before (curve c) and after regeneration (curve d) has been also studied (Figure 7C). Results show that after regeneration, the sensor retained almost 100 % of its signal towards DA oxidation (curve d), which proves the excellent reusability of the sensor.

For a practical application, the stability of the sensor is of great importance. Therefore, the storage stability and shelf life of Au/Fc-ac-PPP electrodes were investigated by storing sensor at room temperature and monitoring the peak current change of AA, DA and UA every 7 days for one month (Figure 7D). After each measurement, the sensor was regenerated by sonication in PBS for 6 min to remove the adsorbed bioanalytes on the surface of the Fc-ac-PPP polymer. Then the sensor was kept at room temperature (~28 0 C) until the next use.

Results show that AA, DA and UA retained 88.30%, 94.35% and 99.70 % respectively of their initial current response after 28 days. This result proves that Au/Fc-ac-PPP has a very good stability and shelf life. Insert Fig. 7

Determination of DA in Biological fluids

The accuracy of the present methodology have been also investigated by applying it for the detection of DA in biological fluids firstly in urine samples and then in human serum samples.

Real sample assay in spiked urine sample

Urine bought from sigma Aldrich is devoid of DA. The urine sample was diluted 100 times with 0.1 M PBS (pH 7.0) before the measurement to avoid the interferences of the real samples matrix [START_REF] Liu | A double signal amplification platform for ultrasensitive and simultaneous detection of ascorbic acid, dopamine, uric acid and acetaminophen based on a nanocomposite of ferrocene thiolate stabilized Fe3O4@Au nanoparticles with graphene sheet[END_REF]. No other pretreatment process has been performed. Then a certain amount of DA (10 -4 µM, 10 -3 µM, 0.01µM, 0.1 µM and 1 µM) have been added into the diluted sample and then detected. The electrochemical measurement was performed using chronoamperometric method by applying a fixed potential corresponding to the oxidation of DA on Au/Fc-ac-PPP (Figure 8A). The analytical results have been resumed in Table 2 and the recovery is found in the range of 97 % to 104% with RSD < 7 % indicating the respectable reliability and applicability of the Au/Fc-ac-PPP for the determination of DA in urine sample. Further, to investigate the feasibility of our sensor and to rule out the interference effect, the same series of known concentrations of DA have been spiked into the diluted urine sample enriched with 10 -3 M of AA and UA (Figure 8B). The same recovery values have been achieved for both urine samples with or without the interference compounds (Table 2). These results also prove that high content of AA and UA in urine samples didn't affect DA detection. Insert Fig. 8

Determination of DA in human serum sample

The serum samples taken by healthy individuals have been centrifuged and then diluted to 4 times by PBS 0.1 M (pH 7.0) to reduce the matrix effect [START_REF] Rafati | Simultaneous determination of ascorbic acid, dopamine, and uric acid using a carbon paste electrode modified with multiwalled carbon nanotubes, ionic liquid, and palladium nanoparticles[END_REF][START_REF] Wang | Highly selective and sensitive determination of dopamine using a Nafion/carbon nanotubes coated poly(3methylthiophene) modified electrode[END_REF][START_REF] Sajid | Chemically modified electrodes for electrochemical detection of dopamine in the presence of uric acid and ascorbic acid: A review[END_REF]. No other pretreatment process was performed. To ascertain the correctness of the result, the standard addition method has been applied and different concentrations of DA have been added in the diluted serum sample, then the redox signal has been measured (Figure 9A). Before adding any concentrations of DA, the DPV voltammogram shows that the diluted serum present several anodic peaks, which are identified by the method of standard additions. The potential peaks recorded at -0.24 V, 0.16 V, and 0.48 V correspond respectively to AA, DA and UA oxidation. As can be seen, the different additions of DA cause an increase in the peak current of the introduced analyte and a small decrease in the current of the other peaks. Then calibration curve for DA oxidation has been built and it shows linear variation where the properties allow the determination of the DA value present in plasma sample (Figure 9B). The Standard addition method allows the determination of the initial concentration in the diluted serum [START_REF] Florescu | Tyrosinase-Based Biosensors for Selective Dopamine Detection[END_REF][START_REF] Yi | Background removal in soil analysis using laser-induced breakdown spectroscopy combined with standard addition method[END_REF]. This concentration has been found to be 3.1 μmol/L. These results were in accordance with those obtained by the HPLC method [START_REF] Loh | Phaeochromocytoma: a ten-year survey[END_REF] and it consistent with normal physiological concentrations for healthy people [START_REF] Yan | Synergetic catalysis based on the proline tailed metalloporphyrin with graphene sheet as efficient mimetic enzyme for ultrasensitive electrochemical detection of dopamine[END_REF][START_REF] Wang | Non-covalent iron(III)-porphyrin functionalized multi-walled carbon nanotubes for the simultaneous determination of ascorbic acid, dopamine, uric acid and nitrite[END_REF]. In addition, It can be seen from Table 3 that the recovery is found in the range of 93 % to 100% with RSD < 6 % indicating the respectable reliability and applicability of the Au/Fc-ac-PPP for the determination of DA in serum sample even with the presence of AA and UA. Insert Fig. 9

Conclusion

In this work, we have successfully designed an electrochemical sensor based on poly(para-phenylene) bearing in side chain position ferrocene and carboxylic acid and demonstrating that such polymer presents the most important properties for catalytic detection of biomolecules such DA, AA, UA. The electrochemical characterization of the polymer with and without carboxylic acid highlighted the importance of the existence of carboxylic acid, which largely enhances the conductivity and the electroactive properties and then the electrocatalytic properties towards AA, DA and UA oxidation. The sensor has better figures of merit for the simultaneous determination of AA, DA and UA with a low detection limit of 0.31×10 -9 M, 1.68×10 -8 M and 1.03×10 -8 M for DA, AA and UA respectively. The Au/Fc-ac-PPP sensor exhibits high selectivity for DA, long-term stability (1 month) and excellent reusability. In addition, the proposed sensor has demonstrated it's applicability for the determination DA in real samples (urine samples and human serum samples) with satisfactory results even with the presence of AA and UA concentrations.

The use of human serum samples for research was approved by the Ethics Committee of clinical laboratory of Sahline hospital, Sahline, Tunisia.

Figure 1 .Figure 2 .

 12 Figure 1. Chemical structure of (A) poly(para-phenylene) modified by ferrocene group (Fc-PPP), (B) poly(para-phenylene) modified by ferrocene and carboxylic acid groups (Fc-ac-PPP).

Figure 3 .

 3 Figure 3. Effect of pH solution on (A, C and E) the peak current and (B, D and F) the peak potential respectively at (a) Au/Fc-PPP and (b) Au/Fc-ac-PPP modified electrodes analyzed in presence of (A, B) 10 -5 M DA, (C, D) 10 -3 M AA, (E, F) 10 -3 M UA.

Figure 4 .

 4 Figure 4. CV and DPV curves of Au/Fc-ac-PPP in 0.1 M PBS containing (A) 10 -5 M DA, (B) 10 -3 M AA and (C) 10 -3 M UA at various scan rates from 10 to 100 mV/s, and the corresponding plots of (a1, b1 and c1) peak current versus scan rate and (a2, b2 and c2) peak current versus square root of scan rate

Figure 5 .Figure 6 .

 56 Figure 5. DPVs of Au/Fc-ac-PPP electrode in 0.1 M PBS pH 7.0 containing (A) 10 -3 M AA, 10 -3 M UA and DA in different concentrations (0 M, 10 -9 M, 10 -8 , 10 -7 , 10 -6 ,10 -5 M); (C) 10 -5M DA, 10 -3 M UA and AA in different concentrations (0 M, 10 -7 ,10 -6 ,10 -5 ,10 -4 , 10 -3 M); (E) 10 -3 M AA, 10 -5 M DA and UA in different concentrations (0 M,10 -7 ,10 -6 ,10 -5 ,10 -4 , 10 -3 M).Calibration curves of (B) DA, (D) AA and (F) UA

Figure 7 .

 7 Figure 7. (A) Amperometric (i-t) curve obtained for Au/Fc-ac-PPP upon addition of interference sources, including 1mM KCl, 1mM NaCl, 1mM NH 4 Cl, 1mM glucose, 1mM citric acid, 1mM glycine, at applied potential of 0.17 V. (B) DPV curves of 10 -3 M AA, 10 - 5 M DA and 10 -3 M UA in 0.1 M PBS (pH 7.0) obtained with various measurements. (C) CV at Au/Fc-ac-PPP in (a, b) PBS and in (c, d) PBS containing 10 -5 M DA (a, c) before and (b, d)

Figure 9 .

 9 Figure 9. (A) DPV response of Au/Fc-ac-PPP obtained in diluted serum before and after addition of successive concentrations of DA (0M, 10µM, 20µM, 30µM, 40µM and 50 µM). (B) The standard addition plot measured for the DA concentration in diluted serum sample with normalized current changes (∆I = I -I 0 ⁄I 0 , where I 0 is the initial current and I is the instantaneous current), the intersection of the curve with the abscissa axis allows calculating the initial value of DA present in sample.

Table 1 .

 1 Comparison of the sensing characteristics of the proposed sensor with some others developed with various modified electrodes for determination of dopamine in mixture of DA.

	Sensor	Linear range (μM)	LOD (μM)	DA in real samples	AA-DA (V)	DA-UA (V)	References
	Au/PEI/rGO	0.05-1	0.05	meat	-	-	[42]
	C-SPE
	(4mm)/SWCNT	0.1-5	0.002	urine	0.07	-	[12]
	wiring of MP (1m)
	Au/Gr-AuAg	0.3-300	0.205	PBS	0.19	0.12	[43]
	CILE/SnO2-GR	0.5-500.0	0.13	urine	-	0.17	[44]
	CILE/GR/DNA	0.1-10 3	0.027	human urine	0.14	-	[11]
	GCE/Au@Pd-RGO 0.01-100	0.002	human urine	0.17	0.16	[45]
	CPE/CD-β-S	0.5-500	0.133	-	0.16	0.10	[46]
	PCF	0.1-9.8	0.04	human urine	0.12	0.15	[47]
	GO/TmPO 4 /GCE	2-20	0.785	human urine	0.18	0.13	[48]
	AuNPs@GO/PPy/C FP	0.2-60	0.115	human urine	0.18	0.12	[49]
	MnO 2 NFs/NG	0.1-10	0.039	human serum	-	0.154	[50]
	Au/Fc-ac-PPP	0.001-1	0.0003	urine and human serum	0.43	0.34	This work

Table 2 :

 2 Evaluation of DA in urine samples using the Au/Fc-ac-PPP modified electrodes (number of sample 3). The first serial is urine and second is urine enriched with AA 10 -3 M and UA 10 -3 M.

Table 3 :

 3 Evaluation of DA in human serum sample using the Au/Fc-ac-PPP modified

	electrodes (number of sample 3)

Sample Determined concentration of DA in diluted serum (µM) Added (µM) Found (µM) Recovery (%) RSD (%)

	Sample		Added (µM)	Found (µM)	Recovery (%)	RSD (%)
			10 -3	10 -3	100.00	5.25
	Urine sample	10 -2 10 -1	1.03 10 -2 1.02 10 -1	103.00 102.00	1.10 1.00
			1	1.02	102.00	0.35
			10 -3	1.1 10 -3	104.00	6.58
	Urine enriched with 10 -3 M AA and 10 -3 M AU	10 -2 10 -1	9.7 10 -3 9.79 10 -2	97.00 97.90	2.00 5.52
			1	1.02	102.00	1.14
				10.00	12.17	90.70	5.15
				20.00	22.12	95.10	2.43
	Diluted Serum sample	3,1		30.00 40.00	31.12 43.11	93.40 100.02	1.44 1.00
				50.00	53.22	100.20	1.56

, 10 -3 M) in 0.1 M PBS (pH 7.4) under stirring. Working potentials were 0.17 V, -0.26V ,

Acknowledgments

We would like to thank the Minister of Higher Education for Scientific Research of Tunisia for the scholarship.

Compliance with ethical standards

Human serum samples were collected from a healthy volunteer with informed consent.