S Lacerda
email: sara.lacerda@cnrs.fr

J-F Morfin

C F G C Geraldes

É Tóth

Metal complexes for multimodal imaging of misfolded proteinrelated diseases

Aggregation of misfolded proteins and progressive polymerization of otherwise soluble proteins is a common hallmark of a wide range of highly debilitating and increasingly prevalent diseases, including Amyotrophic Lateral Sclerosis, Cerebral Amyloid Angiopathy, Type II Diabetes and Parkinson's, Huntington's and Alzheimer's diseases. There is a growing interest in creating imaging agents to detect such aggregates in various imaging modalities, including PET, SPECT and MRI. We present here an overview of recent efforts in the perspective of early diagnosis of amyloid diseases, with a major focus on Aβ detection and on metal complexes bearing PiB units. 2 | J. Name., 2012, 00, 1-3

This journal is

Introduction

Protein folding and unfolding processes govern biological activity in multiple ways. Proteins, only when correctly folded, have long-term stability in complex biological environments and are capable of interacting selectively with their natural partners. 1 The way a newly synthesized chain of amino acids converts into a perfectly folded protein depends both on the intrinsic properties of the amino-acid sequence and on multiple factors of the cellular milieu. In vitro parameters inducing aggregation may include temperature, pH, co-solvent, metal ions, surfactants etc; while in vivo factors imply mutation in the polypeptide chain, translational error, ageing and inability of cellular machinery to clear the aggregates. Water has a dual role: it protects the disordered peptide-chain by hydration but also helps globular chain-folding, stimulating protein aggregation. Metal ions (namely Cu 2+ , Zn 2+ and Fe 3+ ) also play a crucial role in the aggregation process, being therefore intrinsically connected to the onset and development of some neurodegenerative disorders.

2-4

Amyloidogenesis is the process where folded, globular proteins unfold or misfold (thus avoid the protein quality control and degradation system) and then misassemble into soluble and insoluble toxic oligomer/polymer cross-β-sheet fibrillary aggregates, known as amyloids. 3 In addition to the toxic oligomeric species, reactive oxygen species are generated during aggregation contributing also to cytotoxicity. Since aggregation is not a synchronized process, monomers, oligomers and fibrils co-exist with different physiological clearance rates for different species.

The preexisting fibrils can be further fragmentized into small pieces which act as new oligomeric nuclei to amplify aggregation. This process is known as ''secondary nucleation'' and has been identified in the case of αsynuclein and Aβ.

5

Figure 1 shows a schematic representation of the protein aggregation pathway. Aggregation of misfolded proteins and progressive polymerization of otherwise soluble proteins is a common hallmark of a wide range of highly debilitating and increasingly prevalent diseases. Indeed, about 30 different diseases are known to date to be related to protein misfolding and amyloidogenesis, including Prion Disease, Amyotrophic Lateral Sclerosis, Cerebral Amyloid Angiopathy, Type II Diabetes and Parkinson's, Huntington's It is still unclear whether inhibiting the oligomerization of the implicated proteins will actually prevent the clinical syndromes. Moreover, it has recently been reported that the proteins Aβ, tau (whose hyperphosphorylation induces protein aggregation) and α-syn interact in vivo, promoting the accumulation of one another, leading to heteroaggregation and accelerating cognitive dysfunction.

The in vivo toxicity of the amyloid proteins seems to depend on their aggregation level. Amyloid toxicity has been related to various mechanisms, namely: generation of reactive oxygen species, overloading of the misfolded protein response pathway, interaction with cell receptors, interaction with metal ions and the capacity of amyloid proteins to interact and disrupt cell membranes. [7][8][9] The antiparallel -sheet structure of short oligomers and/or fibers interact with cell membranes and promote their disruption in a two-step mechanism: (i) binding to the membrane with formation of a ion permeable pores, and (ii) membrane fragmentation via a detergent-like mechanism (due to the A fibrillization). Recently, it has been shown that the reduced pathological lipid bilayer thickness, which occurs in vivo in case of AD by initial aggregation and strain or incorporation of peroxidized lipids, is capable of altering the aggregation pathway of A and to stabilize distinct membrane-associated intermediate aggregates.

Currently, pathological examination of the postmortem brain tissue is the sole definitive diagnostic method for most neurodegenerative misfolded protein-related diseases, with no pre-onset diagnosis available. The conspicuous similarities and the common neuropathological hallmarks of these diseases, namely extracellular amyloid plaque deposition in the brain, make their accurate and early diagnostic very difficult. 11, 12 To monitor brain neurodegeneration, structural magnetic resonance imaging (MRI) studies of hippocampal and adjacent cortical atrophy are widely used. The morphological changes in the brain are accompanied by reactive gliosis, diffuse synaptic and neuronal loss, and by the presence of the pathological hallmarks of the disease: intracellular neurofibrillary tangles (NFT) and extracellular amyloid plaques. 12,13 Other biomarkers include increased cerebrospinal fluid (CSF) total tau concentration and hypometabolism, the latter typically assessed by Molecular imaging could play a central role in the early detection of misfolded protein pathologies and contribute (i) to an accurate diagnosis, (ii) to reveal new mechanisms and pathways in cell biology, (iii) to improve our understanding of disease and disease progression, and (iv) to the development of novel therapeutic strategies. In terms of molecular imaging, nuclear imaging techniques, such as PET and single photon emission computed tomography (SPECT), are used for visualization of amyloid deposits, as well as metabolic deficiencies in the brain, with imaging probes already in clinical use. PET and SPECT are molecular imaging techniques that rely on the detection of radioactivity of positron-or gamma-emitting isotopes that are incorporated into a molecular tracer. In PET, the emitted positron annihilates releasing two gamma photons travelling in opposite directions, with an energy of 511 KeV. Detection of the emitted photons allows the generation of an image with a spatial resolution of 3-5 mm in a clinical scanner and with high sensitivity (probe concentrations in pico-nanomolar range). In SPECT, the isotopes used have in general longer half-lives and therefore offer a longer imaging window. In SPECT, it is possible to image two or more radio-labelled probes simultaneously using energy discrimination, but it has lower sensitivity than PET (more than an order of magnitude).

14 Molecular probes for near infrared fluorescence imaging have been also proposed. Optical imaging has the limitation of low depth penetration and clinical translation for in vivo imaging of amyloid diseases seems compromised. On the other hand, it is rapid and inexpensive, which makes it well adapted for pre-clinical studies. The use of probes emitting in the near infrared region (600-1000 nm) allows for improved photon penetration through tissue and minimizes the effects of light scattering and tissue autofluorescence.

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Please do not adjust margins MRI is a powerful clinical and biological imaging tool, based on magnetic resonance signals produced by body nuclear spins. MRI signal intensity depends on local spin density, mainly of water and fat protons, but can also be made dependent on proton longitudinal (T 1 ) and transverse (T 2 ) relaxation times as well as on T 2 * relaxation times, which also reflect the effect of local magnetic field anisotropies. MRI offers non-invasive anatomical and functional information with excellent spatial resolution (50-200 µm for research and clinical scanners). Such high resolution can be relevant for detection and quantification of small amyloid lesions. Other advantages of MRI relative to nuclear techniques are wider availability and absence of radiation burden. However, a major limitation of MRI is its low sensitivity. This can be circumvented by increasing the magnetic field, using longer acquisition times or more sensitive pulse sequences, injecting hyperpolarized tracers and most commonly, applying exogenous contrast agents (CAs). These agents act by decreasing the relaxation times of tissue water protons in the body regions where they distribute. Due to its high electron spin and slow electronic relaxation, Gd 3+ is the most efficient paramagnetic ion to increase the water proton relaxation rate (1/T 1 ), generating a positive contrast in T 1 weighted images. Clinical CAs are stable Gd 3+ complexes of linear or macrocyclic polyamino carboxylate ligands. Their MRI efficiency is measured by the longitudinal relaxivity, r 1 , defined as the paramagnetic enhancement of longitudinal water proton relaxation rate normalized to 1 mM concentration. It is determined by several microscopic parameters of the complex, the most important being the number and the exchange rate of the water molecules in the inner coordination sphere of the Gd 3+ (q and k ex ), the rotational correlation time (τ R ) of the complex and the relaxation times of the Gd 3+ electron spin (T 11, 12, 17-19 In this Perspective paper, we would like to highlight the versatile potential of metal complexes as multimodal imaging agents in a variety of pathologies related to protein misfolding, well beyond AD which has been so far mostly explored in this context. Indeed, the majority of experimental data are available for -amyloid detection. These will be surveyed here with a specific focus on PiB-derivative metal chelates.

Imaging of misfolded protein-based diseases

Protein aggregates have been explored as biomarkers for both diagnostic and therapeutic purposes over the past years. In addition to AD, these studies involved other pathologies implicating misfolded proteins, namely Parkinson's disease, Amyotrophic Lateral Sclerosis, Huntington's Disease, Cerebral Amyloid Angiopathy and Type 2 diabetes mellitus and aimed either at the design of dedicated novel probes or the use of contrast agents which were previously tested for AD. The majority of the imaging agents reported is based on I derivatives of blood brain barrier (BBB) permeable small organic molecules, whose structures are derived from thioflavin-T, benzoxazoles and stilbenes. Such derivatives have been shown to target the aggregated forms of A. 12 Currently in phase III clinical trials, the first tracer with high affinity and selectivity for fibrillar A was 11 C-PiB (a thioflavin-T derivative), which is becoming the gold standard for A imaging. Nevertheless, its carbon-11 labeling, with a halflife of 20.4 minutes and the need of an onsite cyclotron and extensive radiochemistry capabilities, restricts the use of this probe to sophisticated centers. The development of comparable fluorine-18 labeled tracers enables widespread A imaging. Among the numerous compounds developed for visualization of A aggregates, three probes have been approved by the European Medicines Agency and the Food and Drug Administration in the USA: [ We should also note that various small molecular compounds have been also used as chemical tools to interrogate metal-A interaction and the associated aggregation. 20 Some of these compounds can be also exploited to create imaging probes.

More recently, there has been an increasing interest in using metal complexes for nuclear ( 99m Tc,

In,

Zr) or MR imaging (Gd). Various ligands and targeting units have been explored for the optimization of the biodistribution, affinity, selectivity and in vivo half-life of the probes, in the objective of achieving wider applicability.

A major advantage of metal based imaging probes is their versatility. Indeed, the same chelating framework can be used to form stable complexes with a large variety of metal ions, including those with appropriate magnetic properties for MRI, radioactive isotopes adapted to nuclear imaging and even luminescent metal ions for optical detection. In nuclear imaging, metal isotopes offer a great choice of emission mode and half-life. On the other hand, a potential disadvantage of metal complexes in this field can be their molecular size, which is typically larger than that of 11 C-or 18 F-labelled small tracers and which can prevent efficient BBB permeability in case of brain imaging. Finally, the conjugation of a relatively bulky metal complex to a protein recognition unit can also lead to a decreased affinity to the protein. This journal is © The Royal Society of Chemistry 20xx

Please do not adjust margins Please do not adjust margins Parkinson's Disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. The underlying molecular features include abnormal α-syn accumulation in intra-and interneuronal inclusions (Lewy bodies and Lewy neurites, respectively) along with degeneration of substantia nigra dopaminergic neurons. α-syn is a small (140 amino acids), highly soluble presynaptic protein that normally exists in a natively unfolded state. In PD, its conformation changes to α-helical fibrils and oligomers that form β-sheet rich fibrils. This resultant protein aggregation sets the ''misfolded hypothesis'' of PD. These aggregates can also migrate from affected to unaffected neurons, causing further misfolding. 21, 22 PET tracers used in PD imaging include labelled organic molecules: [ (hexamethylpropyleneamine oxime) [23][24][25] to assess cerebral perfusion changes. The majority of these probes do not target misfolded protein aggregates. Developing an α-syn tracer poses a great challenge, but would help distinguishing PD from other disorders. Like tau, aggregated α-syn is far less abundant in the brain than Aβ, requiring very high selectivity for α-syn over Aβ and tau. Moreover, like tau, α-syn accumulates mainly intracellularly, with some α-syn found extracellularly, either as a consequence of neuronal death or due to secretion from neurons and spreading in a prion-like manner.

22,26

Recently, a series of PET tracers have been proposed to target α-syn, based on molecules with high affinity for αsyn, Aβ and tau fibrils. The 11 C and 125 I radiolabeling of the phenothiazine analogues SIL5 and SIL26, respectively, yielded a PET and SPECT tracer that cross the BBB in healthy adult male rats. [ 11 C]-SL5 showed also brain uptake in healthy cynomolgus monkey, representing a promising probe for further in vivo α-syn imaging studies.

22

Huntington's Disease (HD) is an autosomal dominant monogenic neurodegenerative disease characterized by a CAG trinucleotide repeat expansion in the huntingtin gene, which results in a lengthened polyglutamine chain on huntingtin protein, leading to its abnormal neuronal aggregation. 27 25 Recently, HD has been associated to tau aggregation, and therefore [ 18 F]-AV-1451 PET was performed in patients highlighting the implication of tau pathology in HD. 28 However, no metal-based probes have been reported so far.

Amyotrophic Lateral Sclerosis (ALS), the most common motor disease, is a devastating and fatal adult-onset neurodegenerative disorder characterized by progressive degeneration of both upper motor neurons in the motor cortex and lower motor neurons in the spinal cord and brainstem. 29 Hallmarks of ALS include protein aggregates mainly found in spinal motor neurons which can consist of cytostatin C, transferrin, neurofilament-rich hyaline aggregates, TDP-43 and mutant SOD-1. Mutant SOD-1 proteins aggregate to a greater extent than the normal wild-type SOD1 protein. 30 Some mutations arise from oxidative stress, which comes from an imbalance of the reactive oxygen and nitrogen species. The resulting free radicals have been previously shown to play a major role in ALS. 31 On the other hand, accumulation of TDP-43 in the cytoplasm directly contributes to the development of ALS due to their abnormal localization in the mitochondria, where TDP-43 binds to mitochondrial DNA. In fact, the mislocalization of TDP-43 to the cytoplasm also represents a key pathological feature of other major neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease and Huntington's disease, 32 showing once more the conspicuous similarities of these diseases. About 35-50% ALS patients show amyloid deposition, even without dementia. Cu]-diacetyl-bis(N4methylthiosemicarbazone)), a PET radioligand that will be retained in cells displaying redox imbalance due to copper reduction to Cu(I). 29 Towner et al have reported on another indirect method of assessing the effect of oxidative stress by MRI, using an anti-DMPO probe, which consists of an Please do not adjust margins Please do not adjust margins anti-DMPO antibody covalently bound to an albumin-GdDTPA-biotin (DTPA = diethylenetriaminepentaacetic acid) MRI contrast agent. Free radicals generated from oxidative stress can be tagged by 5,5-dimethyl-1-pyrroline N-oxide (DMPO), that form DMPO-radical adducts, targeted by the antibody used.

31

Cerebral Amyloid Angiopathy (CAA), a major factor in intracerebral hemorrhage and vascular cognitive impairment is characterized by the deposition of amyloid aggregates in the walls of cerebral vasculature. Imaging probes capable of selective binding to Aβ deposited in the walls of the cerebral vasculature and differentiating CAA from AD are highly desired. To detect CAA but not AD senile plaques, low brain uptake of the imaging probe is favorable.

Iikuni et al reported a series of [

99m Tc]hydroxamamide complexes with a multivalent amyloid ligand, and utilized stilbene and benzothiazole as ligands for amyloid aggregates. These compounds are believed to hardly cross the BBB in vivo, and their high binding affinity for Aβ aggregates is important for imaging CAA. 33 Jaruszewski et al have designed theragnostic nanovehicles capable of targeting cerebrovascular amyloid (CVA). The nanovehicles were loaded with GdDTPA for MRI or with 125 I for SPECT detection, respectively. In addition, they carried either antiinflammatory or anti-amyloidogenic molecules such as curcumin or immunosuppressants such as dexamethasone, which were previously shown to reduce cerebrovascular inflammation. Specific targeting to CVA deposits was achieved via the anti-amyloid antibody (IgG4.1) grafted on the surface of the nanovehicles. 34 Kung et al have developed a series of 68 Ga-labelled complexes for PET imaging based on a bivalent polypegylated styrylpyridine conjugated to a N,N′-Bis[2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine-N,N′-diacetic acid (HBED). These probes were originally designed to detect Aβ deposits in the brain, but failed to efficiently cross the BBB and were then proposed as CAA probes. Preliminary results to map Aβ aggregates in blood vessels of CAA patients were very promising. 32 Type 2 Diabetes. Diabetes mellitus is one of the most common metabolic disorders characterized by chronic hyperglycemia resulting from defects in insulin secretion, insulin action, or both. About 90% of diabetic patients suffer from type 2 diabetes (T2D). This pathology is characterized by amyloid deposition in pancreatic islets (islet amyloid), formed from islet amyloid polypeptide (IAPP), also known as amylin. Amylin is a 37 amino acid protein, co-secreted with insulin in response to food intake. Islet amyloid formation is closely associated with β-cell dysfunction and a reduction of β-cell mass in diabetic patients.

Yashimura et al reported a 125 I-labeled pyridyl-benzofuran (PBF) derivative Aβ SPECT probe, [ 125 I]-IPBF, for the visualization of amylin. This probe binds to amylin with a K i in the nM range and binds to islet amyloids in sections of human pancreas tissue. 35 3). This probe binds to A 1-42 aggregates with an affinity in the nM range, confirmed by in vitro staining of Aβ plaques from brain sections of Tg2576 mice. Biodistribution studies in wild type mice revealed though a low brain uptake of 68 GaDOTA-C3-BF with 0.45 %ID/g at 2 min and 0.16 %ID/g at 60 min post-injection. 40 Mishra et al. reported a DTPA conjugated to two chalcone units via an amide linker (DT(Ch) 2 , Figure 3). The 68 Gacomplex showed high affinity to Aβ 1-42 aggregates and had an increased brain uptake of 1.24% ID/g at 2 min and 0.20 %ID/g at 60 min post-injection in normal mice, likely due to its higher lipophilicity. 41 Complexes based on curcumin derivatives were also reported; all forming complexes with 1:2 metal-to-ligand ratio (Figure 3). Ga(bDHC) 2 showed high affinity to Aβ when incubated with synthetic β-amyloid fibrils; 42 and nat Ga(CUR) 2 binds to amyloid-β plaques in human brain tissue (fluorescent studies). 43 Nevertheless, none of these probes was evaluated in vivo. We have also investigated Based on these promising results, the same authors moved on towards an improvement of the brain uptake, and developed hybrid ligands by conjugating thiosemicarbazone structures to A plaque targeting groups: trans-stilbene (L1), benzothiazole (L2) and styrylpyridine (L3 and 4) (Figure 4). The radiocomplex 64 CuL1 had a rather high brain uptake in APP/PS1 mice, but was difficult to radiolabel. Compound 64 CuL2 does not bind to A and 64 CuL3-4 show low brain uptake. 18 Ono et al. reported on two 64 Cu-labelled benzofuran derivatives, cyclen-C3-BF and DOTA-C3-BF (Figures 3 and4). 40 As previously found for the 68 Ga analogues, the 64 Cu complexes have low brain uptake in normal mice at 2 min post-injection (0.33 % and 0.36 %ID/g Please do not adjust margins Please do not adjust margins respectively) and similar uptake at 30 min (0.18 % and 0.17 %ID/g respectively).

SPECT imaging probes for A aggregates

Metal-based radiocomplexes reported for Aβ SPECT imaging involve 99m Tc (t 1/2 = 6h) and 111

In (t 1/2 = 67.3h).

99m

Tc is the most used SPECT isotope, due to its ideal halflife (6h) and energy (140 KeV) and its availability. ID/g at 2 min post-injection in normal mice (0.62 %ID/g at 60 min). This complex was further studied in rhesus monkeys, consisting in the first SPECT imaging in nonhuman primate for A detection (Figure 5). The semiquantitative data obtained (brain uptake of about 1 %ID at 0-10 mins and ≈0.7 %ID at 30-40 mins) confirmed the promising results observed in the murine model.

NIRF imaging probes for A aggregates

A series of molecules have been described for in vivo imaging of A plaques in animal models, capable of realtime monitoring of the progress of AD in transgenic mice with intact cranium. NIR imaging is a versatile and sensitive method for studying the potential effectiveness of anti-AD drug candidates in small animals. The large majority of the NIRF probes relies on the increase of fluorescence or on the shift of emission maxima upon binding to aggregated A proteins. NIAD-4, which combines chemical features of Congo Red and Thioflavin-T, presents a remarkable red shift and a 400-fold fluorescence enhancement upon binding to A aggregates in vitro (with K D ≈ nM). This first NIRF probe reported (2005), 50

MRI in AD's disease

In the absence of any CA, MR contrast allowing the visualization of mature, large (50 µm diameter) individual amyloid plaques might be provided by sufficiently high iron accumulation, which leads to hypo-intense spots in T 2 , T 2 * or susceptibility-weighted images. [57][58][59][60][61][62] These experiments require high magnetic fields (7 T or more) and long acquisition times impracticable in clinical MRI. Moreover, not all plaques contain iron and this approach is limited to advanced stages of AD.

The detection of plaques weakly loaded with iron requires the use of exogenous CAs. Despite the enormous success of CAs for imaging the brain, liver, kidney or the vascular system, the development of imaging probes for the detection of A amyloid brain deposits has been limited and reached only the preclinical stage, mainly due to the low sensitivity of MRI relative to nuclear techniques. To be clinically helpful for A plaque detection in early AD patients, MRI CAs, besides the general properties described above, should readily cross the blood-brain-barrier (BBB), accumulate sufficiently in the brain and bind specifically and selectively to A deposits. These remain currently major obstacles to molecular MR imaging in AD detection.

Non-specific, commercial CAs, such as GdDOTA (DOTAREM®), do not permeate intact BBB, and are clinically used to evaluate BBB leakage in multiple sclerosis and glioma. 63 Amyloid deposits in the brain of AD transgenic mice have been detected by MRI after intracerebroventricular injection of GdDOTA, showing that if small and non-specific CAs reach the brain tissue, the amyloid deposits can be imaged. Upon administration, the hydrophilic GdDOTA complex diffuses rapidly throughout the brain parenchyma but does not interact with the highly hydrophobic A plaques, which are observed as hypointense spots in T 1 -weighted images. 64 Transient opening of the BBB with application of unfocussed ultrasound and microbubbles have also been proposed to allow brain entry of CAs. F MRI visualization of Aβ plaques has been achieved in transgenic mice. Despite the lack of background signal in 19 F MRI, the intrinsic low sensitivity led to low resolution images, even at high probe doses.

Aβ-targeted iron oxide nanoparticles

The high r 2 relaxivities, thus high sensitivity of superparamagnetic iron oxide nanoparticles (SPIONs) have encouraged their use for AD imaging. and SPION-curcumin conjugates stabilized by PEG-PLA block polymer. 76 The presence of PEG at the NPs surface was claimed to increase blood circulation time and facilitate BBB crossing via transcytosis. 77 Other targeting strategies include conjugation with Aβ specific peptides selected in a phage display, with binding affinity in the µM range. 78 Again, in vivo T 2 *-weighted MRI plaque detection in AD transgenic mice required mannitol coadjuvant injection.

Aβ-targeted Gd-chelates

Gd-complexes have been linked to targeting moieties including small molecules, peptides as well as antibodies.

The first Aβ targeted Gd 3+ -based MRI CA was reported by Poduslo et al. already fifteen years ago. A GdDTPA complex was conjugated to human Aβ 1-40 or Aβ 1-42 peptides modified with the polyamine putrescine in order to improve BBB crossing. 79 Imaging of AD plaques in transgenic mice was achieved; however, it required the use of mannitol to open the BBB as well as long MRI scan times and high magnetic field (7 T). Later, the molecular design was improved by using synthetic modified Aβ derivatives as targeting moiety. shown that the presence of putrescine increased BBB permeability of the antibody fragment, while the in vitro binding ability to Aβ peptides and amyloid plaques was retained. 81 Incubation of AD mouse brain slices with this CA resulted in selective enhancement of individual plaques on T 1 -weighted spin-echo MR images. 82 The same antibody fragment was linked to smart nanovesicles made of polymeric chitosan NPs which could also cross the BBB and bind selectively and efficiently to Aβ plaques. 83 Austen et al have reported a series of GdDOTA-small peptide conjugates which bind to β-amyloid, but only crossed the BBB when adding a cationic cell penetration sequence and using microparticle assisted ultrasound activation. s -1 for the aggregates. Although an overall negative charge of the complex, either in the Gd(DOTA) moiety or in the linker, improved the solubility (above 5 mM), it had a negative effect on the binding to Aβ plaques. Long linkers separating the complex and the Aβtargeting moiety improved the affinity for Aβ aggregates.

The complex with the highest affinity, Gd(DOTA-Lys 3 -BTA) (BTA = (2-(4-N-methylaminophenyl)benzothiazole)), had a positively charged linker with three lysine residues. None of the compounds could cross the BBB in an in vitro model.

Curcumin (CUR) has also been used as targeting moiety either in small molecule conjugates with GdDTPA 87 or in a poly(β-L-malic) acid (PMLA) system decorated with GdDOTA. This latter was used to stain Aβ plaques in ex vivo human and mouse brains with monitoring in fluorescence microscopy or MRI.

88

We have used PiB derivatives as biovector for Aβ targeting in a modular approach to create a set of low molecular weight Gd 3+ -based CAs. [89][90][91] These probes consist of an imaging moiety formed by stable Gd 3+ complexes of bifunctional derivatives of DO3A-monoamide (DO3A= 1,4,7,10-tetraazacyclo dodecane-1,4,7-triacetic acid) or DOTAGA (1,4,7,10-tetraazacyclododecane-1,4,7-triacetic acid-10-glutaric acid) (L i , i =6-9, Figure 6), bound through different neutral spacers to the amino group of PiB . The ligands L6, L7 and L8 form neutral complexes and differ in the nature and size of the spacer, affecting their overall lipophilicity, while L9 forms a negatively charged complex. The metal chelating unit can efficiently coordinate, besides Gd 3+ or any other Ln 3+ , a variety of metal ions that can act as imaging agents in different modalities, such as 111 In 3+ in SPECT or 68 Ga 3+ for PET.

A water proton relaxometric assessment of micelle formation in aqueous solution showed that the amphiphilic Gd(L i ) chelates undergo micellar aggregation in aqueous solution, with critical micellar concentrations, cmc, in the 1.5-0.7 mM range. These cmc values are as low as those of other amphiphilic Gd 3+ complexes comprising relatively long (C 14 ) lipophilic tails, 92 showing that the aromatic structures in GdL i efficiently promote micellar aggregation. These micelles are, in major part, expected to dissociate in vivo when injected, due to probe dilution and binding to plasma proteins like HSA. The relaxivities at 40 MHz and 25 °C of the non-associated form, r 1 na = 6.1 -7.9

, are typical of medium sized complexes with one inner-sphere water molecule, while in the micellar form they attain considerably higher values, r 1 a = 13.8 -22.30 mM -

.

90, 91

The molecular parameters controlling the relaxivity of the GdL i complexes were determined via a combined [START_REF] Salerno | [END_REF] O NMR and 1 H Nuclear Magnetic Relaxation Dispersion (NMRD) study (Table 2). [START_REF] Salerno | [END_REF] O NMR data are useful as they give independent access to the water exchange rate, k ex , and the rotational correlation time, τ R .

1 H NMRD plots were obtained for the monomer as well as for the aggregated forms (Figure 7). A detailed description of their rotational dynamics was achieved by using the Lipari-Szabo treatment to analyze proton relaxation rates. It provided rotational correlation times for global ( g ) and local internal ( l ) This journal is © The Royal Society of Chemistry 20xx

Please do not adjust margins Please do not adjust margins motions and the order parameter S 2 . Interestingly, as compared to the analogous neutral complexes, GdL i (i = 6-8), the negative charge in GdL9 induces the formation of smaller micelles with a significant rigidity, which is reflected by slower and more restricted local motion of the Gd 3+ centers, and also evidenced by higher relaxivities at 20-60 MHz.

Table 2. Parameters characterizing water exchange and rotational motion. The water exchange rate, Kex, was calculated from [START_REF] Salerno | [END_REF] O NMR data, while rotational correlation times were obtained from the analysis of NMRD data below and above the cmc for the monomer and micellar form, respectively. All the GdL i complexes interact with serum albumin, reflected by the remarkable increase of relaxivity at intermediate fields in the presence of HSA (Figure 7). On one hand, strong albumin binding has a positive effect of preventing quick elimination of the agent from the body, but on the other hand, it reduces the BBB permeability of the agent. The binding affinity of GdL i to HSA has been assessed by Proton Relaxation Enhancement (PRE) measurements. Assuming one binding site in HSA (n = 1), binding constants were calculated which increase from K a = 0.25 mM for GdL8 to 0.91 mM for GdL6 and 6.53 mM for GdL9. The one order of magnitude higher affinity of GdL9 to HSA can be accounted for its negative charge.

We have used a variety of experimental techniques to explore the interaction of the lanthanide complexes with the Aβ 1-40 amyloid peptides including surface plasmon resonance (SPR), saturation transfer difference NMR (STD-NMR), circular dichroism (CD), dynamic light scattering (DLS) and transmission electron microscopy (TEM). In the Surface Plasmon Resonance (SPR) study, we used an immobilization protocol for Aβ 1-40 which allows for probing the aggregated state of the peptide in solution. The fitting of the SPR plots to a simple 1:1 Langmuir binding isotherm gave K D values in the 67-170 µM range. Table 4 compares the K D values obtained by SPR and other techniques for the interaction of different PiB conjugated Ln 3+ complexes and small benzothiazole molecules with aggregated Aβ 1-40 . The K D for the binding of the negatively charged Gd(L 4 ) is close or slightly higher than those obtained for the neutral LaL6 and La(L7, indicating that the presence of a negative charge does not improve the affinity of the complexes to the aggregated peptide. The conjugation of a metal chelate markedly reduces the binding affinity of the PiB to Aβ 1-40 aggregates, which is then two orders of magnitude lower than that of the positively charged ThT, and five orders of magnitude lower than that of the neutral PiB. Dissociation constants were also determined by STD-NMR and were in excellent agreement with the values obtained by SPR (Table 3). The group epitope mapping, also performed by STD-NMR, evidenced that the benzothiazole moiety and the methoxy group are the major actors in the interaction with the aggregated Aβ 1-40 . The higher STD effect for Gd-L9 also confirms the important contribution of the linker to the affinity. The interaction of GdLi (i = 6,8,9) with the non-aggregated The time-dependent aggregation of Aβ 1-40 , relevant for understanding the molecular origins of AD, has been monitored in the presence of increasing amounts of the complexes: in far UV CD spectroscopy, the bands measured are very sensitive to changes in the secondary structure of proteins, while DLS and TEM give us information on the size and shape of the aggregates (Figure 8). Altogether these results are coherent and evidence that, despite their relative structural similarities; the complexes influence differently the aggregation process. While natural fibril formation is slightly promoted by GdL6 and GdL9, it is remarkably inhibited by GdL8. The ability of EuL6 to interact ex vivo with senile plaques in human brain slices of AD patients was evaluated by taking advantage of the fluorescent properties of the PiB unit. This complex shows comparable distribution pattern and binding intensity to the senile plaques as the ones obtained with PiB or thioflavin-S (also fluorescent). The specificity of EuL6 for the amyloid deposits was evidenced by a doublefluorescence staining with a specific antibody (Figure 9). In]L6, which revealed an uptake of 0.36 and 0.5 %ID/g in the cortex and cerebellum at 2 min post-injection; while at 30 min, it was 0.11 and 0.21 %ID/g, respectively. The labeling of the ligands L6-8 with 68

Ga

3+ has revealed to be more challenging and lower radiochemical yields were achieved (11-42%). Nevertheless, the successful purification of the labeling reaction crude allowed the study of all 3 radiocomplexes on adult C57/BL6 control mice and on 18month-old APP/PS1 mice. Analysis of the µ-PET imaging showed similar values of brain uptake for [ 68 Ga] L6 or [ 68 Ga]L7 at 2 min post-injection in both animal models (0.9-1.1 %ID/cc). This differed greatly for [ 68 Ga]L8, for which a 2.5-fold greater BBB permeability (≈1.3 %ID/cc at 2 min) was observed in the APP/PS1 model by comparison with control mice (≈0.5 %ID/cc at 2 min). Overall, these studies showed that despite their promising features, these structures have to be further improved, namely regarding their lipophilic properties, leading to better BBB permeability and therefore higher brain uptake values. Brain delivery of these Gd-complexes could be improved via conjugation to nanocarriers capable of translocating across the BBB -either per se or upon targeting to transporters expressed in the brain vasculature. Carbon nanotubes (CNTs) display unique physico-chemical properties suitable for use in nanomedicine applications, including large surface area allowing conjugation of therapeutic and imaging molecules. Previous in vitro and in vivo proof-ofconcept studies demonstrated that functionalized multiwalled carbon nanotubes (f-MWNTs) are capable of crossing an intact BBB. 97 Aiming at improving brain delivery of our PiB derivatives, some of the complexes were non-

GdL6

GdL8 This journal is © The Royal Society of Chemistry 20xx

Please do not adjust margins Please do not adjust margins covalently conjugated to f-MWNTs.

98

MWNT characterization was performed using thermogravimetric analysis (TGA), while conjugation was evaluated using inductively coupled plasma mass spectrometry (ICP-MS) and fluorimetry. Radiolabelling with 111 In allowed quantification of in vivo biodistribution and brain uptake by SPECT/CT and γ-scintigraphy. The whole-brain uptake values were ~1.16 % ID/g of tissue at 30 min post injection, corresponding to a ~tenfold increase as compared to those for the free chelates without f-MWNTs.

Gd

3+ containing multimodal AGuIX nanoparticles have been also conjugated with specific targeting units for the diagnosis of different pathologies involving amyloidose.

Concluding Remarks

There is increasing evidence that misfolded protein aggregation is implicated in many incapacitating diseases, including Amyotrophic Lateral Sclerosis, Cerebral Amyloid Angiopathy, Type II Diabetes, Parkinson's, Huntington's and Alzheimer's diseases, although the underlying mechanisms are not always fully elucidated. Molecular imaging probes detecting amyloidogenesis could greatly contribute to a better understanding of these pathologies, provide more accurate and early diagnosis, and could be also useful in monitoring novel treatment strategies. So far, imaging agents have been proposed for several misfolded proteinbased pathologies, Alzheimer's disease being the most widely investigated in this respect. In particular, recent years have witnessed the emergence of metal-based imaging probes for nuclear (PET and SPECT) and MR imaging modalities. Despite the first successful in vivo results in PET and SPECT imaging using amyloid-targeted metal complexes, further improvement in the molecular design of the probes is expected in order to meet the challenge of higher target affinity and specificity. As most of the amyloid-related pathologies concern the brain, one major challenge is to improve blood-brain barrier permeability. In general, all approaches typically applied to drugs destined for the central nervous system could be considered. These involve intracerebral and intracerebroventricular administration, intranasal delivery or blood-to-brain delivery, resulting from a transient disruption of the blood-brain-barrier induced by biological, chemical or physical stimuli (mannitol, magnetic heating, ultrasound). Vector-mediated blood-to-brain delivery has also great potential. In particular, nanomaterials are promising transporters across the intact BBB thanks to their capability to enter the brain capillary endothelial cells via endocytosis and transcytosis.

101, 102 While the brain delivery of metal-based probes in sufficient quantities is within easier reach for nuclear imaging, this issue is evidently more problematic in MRI. For Gd 3+ complexes, the combination of different strategies might be an option to attain detectable brain concentrations. In this context, Gd 3+based MRI probes seem to be more adapted to preclinical animal studies where intracerebral and intracerebroventricular administration or BBB opening might be also applicable, while the clinical translation of nuclear probes, requiring lower amounts of the probe to be delivered in the brain, is more realistic. Alternatively, amyloid-related pathologies not requiring brain delivery, such as Cerebral Amyloid Angiopathy or Type II Diabetes can more easily benefit from metal-based molecular imaging agents. Finally, metal-based probes can be also valuable for studies aiming at a basic understanding of misfolded proteins. The versatile magnetic, optical and nuclear properties of metal ions open the possibility to use a large variety of biophysical techniques for such investigations. This potential is still to be fully explored. This journal is © The Royal Society of Chemistry 20xx

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Figure 1 :

 1 Figure 1: Schematic illustration of protein aggregation in amyloid disorders. Green and red arrows correspond to normal and abnormal processes, respectively.

18 F 18 F

 1818 ]-FDG) positron emission tomography (PET).

18 F

 18

18 F 11 C 18 F 18 F

 18111818 ]-DOPA to visualize dopamine synthesis, [ 11 C]-b-CFT for dopamine transporter, [ 11 C]-DTBZ for vesicular monoamine transporter type 2, [ 11 C]-raclopride for D2 receptor, [ 11 C]-WAY100635 for serotonin receptor, [ ]-PBR28 for translocator protein, [ 11 C]-HG-10-102-01 for detection of enzyme LRRK2, [ ]-AV-1451) for tau protein and [ 11 C]-PIB for aggregated -amyloid plaques. SPECT tracers include [ 123 I]-FP-CIT for assessment of the integrity of nigrostriatal dopaminergic system and cerebral perfusion changes, and [ 123 I]-IBZM which helps differentiating PD from atypical Parkinsonism. The only metal-based tracers used for PD imaging include [ 99m Tc]ECD (ethyl cysteinate diethylester) and [ 99m Tc]HMPAO

  HD has been indirectly assessed based on biomarkers which include: brain metabolism (using [

[ 11 C]-PiB and [ 18 F 18 F

 111818 ]-florbetaten have been used in patients, but only a small number showed increased tracer uptake. 29 ALS has been diagnosed based on decreased [ ]-FDG uptake as well as by indirect cerebral blood flow brain dysfunction quantification, using [ IPT SPECT are used for striatal presynaptic dopaminergic functioning; and [ 11 C]-flumazenil is used as biomarker for neuronal loss. Several probes have been developed allowing the assessment of neuroinflammation, excitotoxicity and synaptic density. Mitochondrial dysfunction and oxidative stress can be evaluated by the use

7 11 C-PiB. Although 11 C 39 Figure 2 : 68 Ge/ 68 Ga

 11113926868 Figure 2: Structure of PET tracers for A aggregates.

68 Ga 44 Figure 3 :

 68443 Figure 3: Structure of 68 Ga complexes for A detection.

46 Figure 4 :

 464 Figure 4: Structure of 64 Cu complexes for A detection.

  studied for Aβ targeting and reviewed.18, 19 The large majority of the chelators are tetradentate N 2 S 2 , N 2 O 2 or N 3 O ligands conjugated to benzothiazoles, benzofurans, flavones, chalcone, curcumin, naphthalene, dibenzylideneacetone and stilbene units. Among these, a 2-arylbenzothiazole derivative conjugated to a bis(aminoethanethiol) and complexed with 99m Tc (Figure5, [ 99m Tc]L5), showed highest brain uptake 2.11%

47 Figure 5 :

 475 Figure 5: Structure of [ 99m Tc]L5 (a) and SPECT images of [ 99m Tc]L5 in rhesus monkeys (A: 4 years old, male; B: 27 years old, female); SPECT images are overlaid on individual co-registered CT images (b). Adapted with permission from ref. [47] Thanks to its long half-life, 111 In is also adapted to antibody targeting. Pardridge et al. have reported a DTPA-[N-biotin]-A 1-40 conjugate which was labeled with 111 In and further coupled to a BBB targeting system, comprised of a peptidomimetic MAb and an avidin or streptavidin moiety. The binding of [ 111 In]DTPA-[N-biotin]-A 1-40 to amyloid plaques of AD in autopsy tissue sections was demonstrated by film and emulsion autoradiography. 48 More recently, Weerd et al. have conjugated the bifunctional chelator p-SCN-Bz-DTPA to a VHH-Fc fusion protein, a llama single domain antibody fragment which targets amyloid plaques. Nevertheless, the 111 In-VHH-Fc-DTPA did not cross the BBB and no A binding was detected either in control or in double transgenic APPswe/PS1dE9 mice.49

84 85 A 5

 84855 Among small molecular vectors, Congo Red (CR) was used in the CR-BSA-(GdDTPA) n conjugate (BSA = bovine serum albumin). Targeting was demonstrated by immunohistochemistry in brain sections from APP/PS1 transgenic mice. The authors suggested that CR-BSA-(Gd-DTPA)n could be used as a potential fluorescence and MR multi-modal imaging probe to display individual senile plaques in AD. library of sixteen small Gd -based CAs were synthesized using a building block strategy to investigate structureactivity relationships regarding physicochemical properties such as relaxivity and binding affinity to the Aβ aggregates. Three blocks were used to modulate the CA structures: (i) the Gd(III) chelates GdDOTA or GdPCTA (PCTA = 3,6,9,15tetraaza bicyclo[9.3.1]-pentadeca-1(15),11,13-triene-3,6,9triacetic acid), (ii) the biovectors (2-arylbenzothiazole, 2arylbenzoxazole and stilbene derivatives) and (iii) the linkers (neutral, positive and negative with several lengths). 86 A large majority of the CAs were found to form micelles in water but not in serum, suggesting an important binding to plasma proteins such as HSA. At 1.5 T, relaxivities in water were r 1 na =

Figure 6 :

 6 Figure 6: Modular structure of PiB-derivative complexes: units responsible for imaging (red), targeting moiety (green) and spacer (blue).

93 Figure 7 : 1 H

 9371 Figure 7: 1 H NMRD profiles of GdL9 at: 0.2 mM (■), 5 mM (▼), 0.2 mM in the presence of 0.2 mM Aβ1-40 (○) 0.2 mM in the presence of 0.2mM HSA (∆) (0.05M HEPES; pH 7.4, T = 310 K). Reproduced with permission from ref. 89.

94

 94

Figure 8 :

 8 Figure 8: TEM images after 20 d of incubation of 40 mm Ab1-40 in the absence (first row) or in the presence of 40 mm GdL6 (second row) and 40 mm GdL8 (third row). The bars correspond to 200 nm (left column) or 100 nm (right column). Reproduced with permission from ref. 94.

Figure 9 :

 9 Figure 9: Micrographs illustrating the colocalization of PiB or EuL6 and 6F3Dantibody labelling of amyloid deposits of postmortem human brain tissue of an AD patient: the co-localization is confirmed by the magenta colour in the merge images; scale bar = 20 μm. Reproduced with permission from ref. 89.

Table 3 .

 3 Binding affinities of small molecules to Aβ1-40

	Molecule	K D (µM) det by SPR	K D (µM) det by STD-NMR	Ref.
	LaL6	170	160	94
	LaL8	67	80	94
	GdL9	194	n.d.

  These studies suggest a weak but nonnegligible interaction of the GdL9 complex with Aβ 1-40 in the monomer state, in contrast to the negligible binding observed for the neutral complexes.

								Please do not adjust margins
				Monomer		Micellar form
				k ex [10 6 s 298 -1 ]	 RH [ps] 298	 g [ns] 298	l 298 [ps]	S	2
	GdL6	a			130	12	105	0.12
	GdL7	a			150	n.d. n.d.	n.d.
	GdL8	a		2.8	141	8	102	0.09
	GdL9	b		9.7	145	3.1	640	0.22
	GdDOTA	c	4.1	77	-	-	-
								by	15 N-Aβ 1-40 peptide was monitored N Heteronuclear Single Quantum Coherence 15 1 H-
								Please do not adjust margins

(HSQC) NMR.

  AGuIX particles are made of a polysiloxane network surrounded by several GdDOTAGA chelates and have a diameter smaller than 5 nm. Additional free ligands are available at the surface of AGuIX and can be used to chelate radioisotopes (e.g., The particles were functionalized with LPFFD and KLVFF, two small peptides derived from the sequence of Aβ 1-42 and highly specific for Aβ amyloid fibrils. 99 The capacity of such nanoparticles grafted with peptide to discriminate among different amyloid proteins was tested with Aβ 1-42 fibrils and with mutated-(V30M) transthyretin (TTR) fibrils, implicated in familial amyloid polyneuropathy, another type of amyloidosis. Both functionalized nanoparticles interact with Aβ(1-42) fibrils with equilibrium dissociation constant values of 350-400 μM, whilst they did not interact with V30M-TTR fibrils. This is in contrast to PiB, which is a general amyloid fibril marker and thus equally well interacts with both types of fibrils. AGuIX nanoparticles were also conjugated with the Pittsburgh compound B and the nanobody B10AP. 100 Their ability to target amyloid fibrils made of β-amyloid peptide, amylin or Val30Met mutated transthyretin formed in vitro or from pathological tissues was investigated by spectroscopic and biophysics techniques including fluorescence microscopy. Both probes interact with these three different amyloid fibrils, with the Kd being 10 micromolar and 10 nanomolar, for PiB-and B10AP-derived nanoparticles respectively. The amyloid deposits could be detected on pathological tissues. These functionalized nanoparticles are promising imaging tools for multimodal detection of different amyloid diseases, including AD, Type 2 diabetes mellitus and the familial amyloidotic polyneuropathy.

			99,
	100 68 Ga	3+ or	111 In 3+ ).

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Acknowledgements

Financial support of the Agence Nationale de la Recherche, France is acknowledged (ANR-16-CE18-0022-01). C.F.G.C.G Please do not adjust margins thanks the financial support from the Fundação para a Ciência e Tecnologia (F.C.T., Portugal, project RECI/QEQ-QFI/0168/2012), and the European Regional Development Fund -FEDER (projects CENTRO-07-CT62-FEDER and GINOP-2.3.2-15-2016-00008).

Conflict of interest

There are no conflicts to declare.


Thibaut Powolny
email: thibaut.powolny@yahoo.fr

Renaud Scheifler

Francis Raoul

Clémentine Fritsch

Is blood a reliable indicator of trace metals concentrations in organs of small mammals?

Keywords: Non-invasive methods, biomonitoring, wildlife, inorganic pollutants, toxic elements Highlights

Non-destructive biomonitoring approach is required for scientific and ethical reasons.

• We tested whether blood metal levels can serve as indicator of organ concentrations.

• This hypothesis was confirmed for Pb, Se, and Tl, with accurate modelling.

• For the other 8 investigated metals above the limit of detection, relationships were weak or nonsignificant.

• More toxicokinetic research is needed to develop the use of blood in ecotoxicology.

Introduction

In human, blood tests are often used in health care to determine physiological and biochemical states, giving information about organ function or diseases. In wildlife ecotoxicology, blood has also widely been used to evaluate various parameters of individuals' health [START_REF] Gorriz | Effects of air pollution on hematological and plasma parameters in Apodemus sylvaticus and Mus musculus[END_REF][START_REF] Nunes | Morphological and haematological parameters in the Algerian mouse (Mus spretus) inhabiting an area contaminated with heavy metals[END_REF][START_REF] Topashka-Ancheva | A comparative analysis of the heavy metal loading of small mammals in different regions of Bulgaria II: chromosomal aberrations and blood pathology[END_REF][START_REF] Rogival | Metal blood levels and hematological characteristics in wood mice (Apodemus sylvaticus L.) along a metal pollution gradient[END_REF][START_REF] Sánchez-Chardi | Haematology, genotoxicity, enzymatic activity and histopathology as biomarkers of metal pollution in the shrew Crocidura russula[END_REF][START_REF] Adham | Impact of heavy metal pollution on the hemogram and serum biochemistry of the libyan jird, Meriones libycus[END_REF]. The rationale for using blood rather than other body fluids or tissues is that sampling blood is a minimally invasive technique that does not necessitate sacrificing individuals, which has obviously both ethical and scientific benefits. There is indeed an increasing will from the large public to perform scientific studies with minimal impacts on the species being studied. Many countries have therefore developed regulation (see e.g.

Directive 2010/63/UE) that frame the use of lab and free-ranging animals (mostly vertebrates) used for scientific purposes. Accordingly, current scientific guidelines such as the one from the American Society of Mammalogists fully acknowledge those ethical issues and propose appropriate procedures minimizing stress, pain, and, generally speaking, impact on animals (Sikes and the Animal Care and Use Committee of the American Society of Mammalogists, 2016). From a scientific point of view, minimizing impact on studied animal models, particularly avoiding sacrificing individuals, is also crucial to limit disturbance of scientific investigations on the dynamics of local populations. This is a key issue for long-term monitoring and surveys, whose importance is increasingly recognized in ecotoxicology (Kendall, 2016). Moreover, lethal, or at least invasive methods inducing a risk for either survival or reproduction of captured individuals, cannot be applied on many rare and/or endangered species for conservation issues. In addition to important physiological parameters informing about the health status of individuals, blood, as integuments like feathers or hairs that are also widely used in ecotoxicology, provides information about the level of exposure to contaminants.

Free-ranging terrestrial vertebrates are considered to be exposed to metals mainly through ingestion of food and water, and secondarily through inhalation of aerosols and, in some instances, vapors [START_REF] Shore | Ecotoxicology of Wild Mammals[END_REF][START_REF] Smith | Contaminant exposure in terrestrial vertebrates[END_REF]. Whatever the exposure route, metals, after uptake, are transported and distributed to different organs within the body through blood, the main transporting medium in the body (Fig. 1). Excretion or clearance of metals from an organ or from the body as a whole can occur through various routes, including or not a transport through blood (Fig. 1), and depends on a number of metalspecific processes and their role (e.g. essential or non-essential metals) in organisms (Elder et al., 2015).

Epidemiological studies on human and laboratory experiments on model organisms have allowed the development of toxicokinetic studies for several metals. Toxicokinetics refer to the processes of absorption, distribution, biotransformation (i.e. formation or breakdown of metal-carbon bonds, or change of oxidation state of a metal in the biological system) and excretion, quantitatively studied as a function of time (Elder et al., 2015). According to general concepts in toxicokinetics, a constant exposure, associated to constant absorption and elimination rates, would lead, over time, to a steady-state equilibrium, where metal concentrations in blood could be used as a reliable estimate of concentrations in the organs. In the wild, however, the exposure of small mammals in a contaminated site is likely to be far from constant. Exposure of free-ranging mammals to metals, indeed, has been shown to greatly vary over time and space, with e.g. heterogeneity of soil contamination, habitat use, diet and foraging behaviour of organisms, or variations of food resources in the field [START_REF] Smith | Contaminant exposure in terrestrial vertebrates[END_REF][START_REF] Van Den Brink | Cadmium Accumulation in Small Mammals: Species Traits, Soil Properties, and Spatial Habitat Use[END_REF]. Bioavailability (i.e. the fraction of the total concentration of a metal in a given compartment that can actually be transferred into an organism) of metals in soils can also dramatically vary with both characteristics of the considered metal and the properties of the contaminated medium [START_REF] Harmsen | Measuring Bioavailability: From a Scientific Approach to Standard Methods[END_REF]. This is likely to be the case for metals in plant and animal tissues small mammals feed on but that issue has been less studied for terrestrial organisms than in the aquatic environment (see e.g. [START_REF] Rainbow | Trophically available metal -A variable feast[END_REF] or for human foodstuffs (Elder et al., 2015).

The rate of clearance of metals from organs (into blood or through excretion, Fig. 1), usually measured by the biological half-time (i.e. the time it takes to the concentration to be reduced to half of its initial value), is another process that influences the metal concentration in blood, and may therefore influence the relationship of metal concentrations between blood and organs.

In the line of some previous developments of minimally invasive ecotoxicological methods on small mammals [START_REF] Tête | Can Body Condition and Somatic Indices be Used to Evaluate Metal-Induced Stress in Wild Small Mammals[END_REF]2014;[START_REF] Tête | Blood parameters as biomarkers of cadmium and lead exposure and effects in wild wood mice (Apodemus sylvaticus) living along a pollution gradient[END_REF], the present work aims at studying the relationships between the concentrations of 18 essential and non-essential trace elements in blood and their concentrations in the liver and the kidneys, two accumulation and target organs, in small mammals sampled along a pollution gradient in Northern France. We hypothesise that blood concentrations of elements with high internal turnover will show a strong relationship between blood and internal tissues, allowing to develop simple modelling to be further used in ecotoxicology of free-ranging small mammals. Weak or no relationships will probably be found for elements whose blood concentration is more linked to daily exposure and/or for other toxicokinetic reasons.

Materials and Methods

Study site

We conducted fieldwork in an area surrounding the former lead (Pb) and zinc (Zn) smelter named Metaleurop Nord (Hauts-de-France Region, northern France, 5025042N, 300055E). The smelter was established by the end of the 20 th century, until its closure in 2003. Major emissions leading up to the smelter's closure were cadmium (Cd), lead (Pb), zinc (Zn). Soil contamination levels on this area are well documented and reported high Cd, Pb and Zn levels of contamination, ranging from 0.1 to 2,402 mg/kg for Cd, from 16 to 41,960 mg/kg for Pb and from 44 to 38,760 mg/kg for Zn (per dry weight, [START_REF] Douay | Contamination of woody habitat soils around a former lead smelter in the North of France[END_REF]Fritsch et al., 2010a). Cadmium, Pb and Zn concentrations in soils from woody habitats are highly correlated, with coefficients of determination ranging from 0.6 to 0.8. Concentrations decrease with the distance to the smelter and are related to the prevailing SW-NE winds (Fritsch et al., 2010b) but anthropogenic activities disturb this global pattern [START_REF] Douay | Contamination of woody habitat soils around a former lead smelter in the North of France[END_REF]. A 40 km² (8×5 km) study area around the former smelter was divided into 160 squares (500×500 m). Four sampling squares across an environmental metal contamination gradient were studied (from control to highly contaminated squares) for the present study.

Based on the Cd, Pb and Zn concentrations, sampling squares were classified as: control ("C"), low ("L"), medium ("M") and high ("H") pollution level (Table 1).

Data collection

From the 30 th of September to the 10 th of October 2014, 10 lines of 10 non-lethal INRA traps spaced 3 m apart were placed on each site for 3 consecutive trap nights. A total of 120 wood mice (Apodemus sylvaticus) were trapped along the gradient of pollution, according to the following distribution: 27 individuals at site ''control'', 33 at site ''L'', 34 at site ''M'' and 26 at site ''H'' (Table 1). No difference in age using crystalline lens mass (ANOVA,F=1,83;Df=3;p=0,146) nor in sex-ratio (F=1,56;Df=1;p=0,196) were observed between sites. Before animal sacrifice by cervical dislocation (following the American Veterinary Medical Association ethical guidelines (Sikes and the Animal Care and Use Committee of the American Society of Mammalogists, 2016), blood was collected from the orbital sinus using a Pasteur pipette, immediately transferred into heparinised microtubes. Blood samples were then stored at 4-8°C before freezing at -20°C within the following next 10 hours. Individuals were weighed, measured and sexed during dissection at the laboratory. The crystalline lenses were sampled and kept in a 3% formalin solution. All procedures involving the handling of animals were conducted by certified persons. During dissections, livers and kidneys were collected (mean liver mass: 1.010g ± 0.261g; mean kidney mass: 0.222g ± 0.045g), dried (65°C, drying oven) and stored until analysis. Sampling authorization was given by the Direction Régionale de l'Environnement, de l'Aménagement et du Logement (DREAL) of the Hauts-de-France Region.

Metal analysis

The concentrations of 18 metals (aluminum (Al), antimony (Sb), arsenic (As), Cd, chromium (Cr), cobalt (Co), copper (Cu), iron (Fe), Pb, manganese (Mn), molybdenum (Mo), nickel (Ni), selenium (Se), strontium (Sr), tin (Sn), titanium (Ti), thallium (Tl), and Zn) were determined in blood samples and organs. Blood samples were acid digested in 700 µl of nitric acid (HNO3, 65%, analytical quality, Optima) for half a day in open tubes under fume hood, and then for 60 h in closed tubes at 60 • C in an oven. After digestion, samples were diluted to 30 ml by the addition of ultra-pure water (18.2 MV.cm-²). Liver and kidney dried samples were digested with nitric acid (HNO3 at 69%) and then diluted by adding ultra-pure water (Elga, 18.2 MV.cm-²) prior to analyses. Blood and organs metals were analysed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS, ThermoFischer Scientific XSeries 2). Over the 18 metals measured, only 11 (Cd; Cu; Fe; Mn; Mo; Pb; Se; Sn; Ti, Tl, Zn) had a satisfactory proportion of values above quantification limits (Table S1), allowing further statistical analyses. For the values under quantification limits for these elements, values were replaced by the quantification limit divided by square root of two for statistical analysis (Helsel, 2010). Repeatability (within-run precision) and reproducibility of the measurements were surveyed (checking of RSD values and use of internal standards), and quality control (control solutions and blanks to check for the absence of drift) was conducted during measurements. Analysis accuracy was checked using certified reference materials (National Research Council Canada TORT-2 Lobster hepatopancreas, eEuropean Reference Material ERM®-CE196 Bovine blood). Blanks (acid + ultra-pure water) and certified reference materials were prepared and analysed using the same methods as the blood samples. Average recoveries of the certified reference materials are given Table S1. The concentrations of metals in the blood are expressed as µg/L and as µg/g dry mass for the liver and kidneys.

Statistical analyses

General Linear Models were used to investigate the relationship between blood and organs (liver and kidney) metal concentrations. A backward selection procedure starting from a full model that included all factors and their two-way interactions was performed. Quasi likelihood estimations were used to estimate the scale parameter, and the significance of terms in the model was tested using F-tests. Starting by continuous covariates, non-significant terms at p≤0.05 were sequentially removed to achieve a minimal adequate model [START_REF] Crawley | GLIM for ecologists[END_REF]. Wherever an interaction term was left in a model, the two corresponding factors were also included as main effects. All tissue concentrations (from blood, liver and kidneys) were log-transformed (log 10(x+1)) and normality and homoscedasticity assumptions were checked graphically.

Full models tested were: [Organ] ~ [Blood] + Sex + Crystalline mass + Sex*[Blood] + Crystalline mass* [Blood]. To reduce the effect of outliers, we removed points with a Cook's distance [START_REF] Cook | Detection of Influential Observation in Linear Regression[END_REF] of ≥0.95, and reran the linear regression. Tissue concentrations of metals were compared along the environmental contamination gradient of Cd, Pb and Zn using ANOVA test. When significant differences were detected among study squares, multiple comparisons were performed using Tukey HSD test. Each analysis was performed with the software R v. 3.15.1 (R Development Core Team).

Results

Metal concentrations around the former smelter

Among the 18 elements measured, Cu, Fe, Pb, Se, and Zn were the only elements to exhibit concentrations above the quantification limits of the analytical instruments, whatever the fluid (blood) or tissue (kidney and liver). Cd, Mn, Mo, Ti, and Tl were not always detectable in blood, while Sn was hardly detectable in organs. Over the 18 metals measured, only 11 (Cd; Cu; Fe; Mn; Mo; Pb; Se; Sn; Ti, Tl, Zn) had a satisfactory proportion of values above quantification limits and were included in further statistical analyses. Complete trace metal concentrations measured in blood, liver and kidneys are presented in Table S1.

The concentrations of Cd, Pb and Zn in blood, in the liver and in kidneys (Fig. 2) of wood mice showed a high variability, depending on squares. Lead concentrations in kidneys were significantly higher only in mouse coming from the most contaminated site (F=38.2; Df=3; p<0.001, Fig. 2A). In the liver, Pb concentrations also varied along the gradient (F=12.0; Df=3; p<0.001; Fig. 2B), with concentrations from the lowly and the highly contaminated squares not differing among them, but being significantly higher than those in the control and the medium squares (p<0.001). Concentrations from the highest contaminated square were also higher than in the medium level, and concentrations from the lowest contaminated square were higher than in the intermediate level of environmental pollution. The pattern was quite similar for (F=16.34; Df=3; p<0.001, Fig. 2H). For Cd, contrary to blood for which no differences were observed along the pollution gradient (F=0.29; Df=3; p=0.83, data not shown), liver (F=14.45; Df=3; p<0.001, Fig. 2C) and kidneys (F=16.89; Df=3; p<0.001, Fig. 2D) concentrations increased along the pollution gradient, except in the highest contaminated square where concentrations were not statistically higher than in the medium level of pollution. Zinc concentrations in blood (Fig. 2G), kidneys (Fig. 2E) and the liver (Fig. 2F) did not show any significant increase along the contamination gradient, even if, for blood and the liver, concentrations at the low level of contamination square were sometimes higher than in some other squares. Comparisons of concentrations in blood and the organs for the others metals (Cu, Fe, Mn, Mo, Se, Sn, Ti and Tl) along the contaminated gradient are presented in supplementary materials (Table S1 and Fig. S1), and are not presented here and will not be discussed extensively because the concentrations in the soils for those metals are not available. Only the relationships between blood and organs will be discussed for Cu, Fe, Mn, Mo, Se, Sn, Ti and Tl.

Relationships between trace element concentrations in different tissues

The relationships between blood and tissue concentrations varied considerably between elements and tissues. Copper (Cu) and Ti concentrations in tissues could not be modelled by any of our study variables (Table 2, Fig. S2 andS3). When examining Pb concentrations in liver and kidneys (Fig. 3A and3B), increases in blood Pb predicted increases in organs (R²=0.64, p < 0.001 for liver and R²=0.56, p < 0.001 for kidneys, Table 2). Molybdenum (Mo) was the only other element for which blood concentration was the only variable retained in models to predict organ concentrations. Contrary to Pb, however, the coefficients of determination of the models for Mo were low (R²= 0.26 for the liver, R²= 0.13 for kidneys, Table 2). Selenium (Fig. 4) and Tl (Fig. S2 andS3) provided good models with coefficients of determination ranging from 0.69 to 0.89, but sex was a variable to consider in the modelling of liver concentrations for both elements.

Cadmium concentrations in kidneys (Fig. 3D) were mainly predicted by age as assessed by crystalline masses (R²=0.43; p = 0.01; Table 2) and by the age (partial R²= 0.04; p < 0.001) and blood concentration with a weak explanation power (partial R²= 0.30; p = 0.01) in liver (R²= 0.34; p < 0.001). Iron (Fe) concentrations in organs were poorly modelled (R²<0.11) by blood concentrations for kidneys and by blood concentrations and sex for the liver (Table 2, Fig. 4). The liver concentrations for Zn, as for Tl, were significantly related to blood concentrations (p = 0.01 for Zn and p = 0.0001 for Tl) and to the interaction term between blood concentration and crystalline mass or sex, respectively (blood concentration*sex: p = 0.01 for Zn and blood concentration* crystalline mass: p = 0.02 for Tl, Table 2). Models for Zn exhibited relatively low coefficients of determination (R²= 0.28 for the liver, R²= 0.14 for kidneys).

Discussion

Measuring pollutants using internal tissue samples from small mammals is the current reference method to estimate the degree of exposure to, and the subsequent accumulation of, cumulative compounds. However, in recent years, for both scientific and ethical reasons, there is a strong and ongoing tendency to use non-destructive samples in biomonitoring studies. The main objective of the present study was therefore to evaluate whether blood concentration values can be indicative of liver and kidney trace metals concentration in wood mice (Apodemus sylvaticus) under field conditions. Studies of metal accumulation in small mammals have included many taxa, such as wood, field and yellow-necked mice (Damek-Poprawa and Sawicka-Kapusta, 2003;[START_REF] Van Den Brink | Effects of soil properties on food web accumulation of heavy metals to the wood mouse (Apodemus sylvaticus)[END_REF][START_REF] Tête | Hair as a noninvasive tool for risk assessment: Do the concentrations of cadmium and lead in the hair of wood mice (Apodemus sylvaticus) reflect internal concentrations? Ecotoxicol[END_REF], voles [START_REF] Appleton | The heavy metal content of the teeth of the bank vole (Clethrionomys glareolus) as an exposure marker of environmental pollution in Poland[END_REF], moles [START_REF] Komarnicki | Tissue, sex and age specific accumulation of heavy metals (Zn, Cu, Pb, Cd) by populations of the mole (Talpa europaea L.) in a central urban area[END_REF], or shrews [START_REF] Hamers | Risk assessment of metals and organic pollutants for herbivorous and carnivorous small mammal food chains in a polluted floodplain (Biesbosch, The Netherlands)[END_REF][START_REF] Sánchez-Chardi | Bioaccumulation of metals and effects of landfill pollution in small mammals. Part I. The greater white-toothed shrew, Crocidura russula[END_REF][START_REF] Moriarty | Arsenic Speciation, Distribution, and Bioaccessibility in Shrews and Their Food[END_REF][START_REF] Drouhot | Responses of wild small mammals to arsenic pollution at a partially remediated mining site in Southern France[END_REF]. However, most of these studies focused on organs (mainly liver and kidney) using lethal methods. Contrary to bird species [START_REF] Dauwe | Heavy-Metal Concentrations in Female Laying Great Tits (Parus major)and Their Clutches[END_REF][START_REF] Scheifler | Lead concentrations in feathers and blood of common blackbirds (Turdus merula) and in earthworms inhabiting unpolluted and moderately polluted urban areas[END_REF][START_REF] Espín | Tracking pan-continental trends in environmental contamination using sentinel raptorswhat types of samples should we use?[END_REF], scarce information on blood metal concentrations are available in literature for small mammals in their natural environment [START_REF] Rogival | Metal blood levels and hematological characteristics in wood mice (Apodemus sylvaticus L.) along a metal pollution gradient[END_REF][START_REF] Vermeulen | Relevance of hair and spines of the European hedgehog (Erinaceus europaeus) as biomonitoring tissues for arsenic and metals in relation to blood[END_REF].

Here, the significant correlations observed between blood and tissue concentrations for Se, Pb, and Tl indicates that blood samples are suitable to estimate concentrations of these metals in liver and kidneys in the wood mice. For both Se and Tl, sex or its interaction with blood concentration is a variable retained in the final models but, according to the partial R² of the variables (Table 2), its weight is low, and sex can relatively easily determined on alive animals using anogenital distance. Furthermore, these correlations have been observed over large concentration ranges, and occurred despite the varying relative age (using the crystalline mass as a proxy) or sex. Blood sampling could therefore be an adequate non-lethal method for estimating these metal concentrations in internal tissues over a wide range of biological and environmental conditions. For some other metals, however, the low (Fe, Mo and Zn), or even absent (Cu, Ti) relationship between blood and organ concentrations indicates that blood samples could hardly or not be used to predict tissue contamination in wild wood mice, at least for the metal concentrations recorded on our study site. Cd concentrations in organs were shown to be much more dependent of the age (as estimated here by the crystalline lenses mass) than by the concentrations in the blood. Similar pattern was noted on the same study site using hair [START_REF] Tête | Hair as a noninvasive tool for risk assessment: Do the concentrations of cadmium and lead in the hair of wood mice (Apodemus sylvaticus) reflect internal concentrations? Ecotoxicol[END_REF] and the influence of age on Cd accumulation in various tissues is a well-known issue. In the present study, investigations for this compound were however limited by the relatively low number of samples above detection limits in blood. It is worth to note that, in the present study, the essentiality of metals is not a key factor in explaining high or weak relationships between blood and organs. Rather, a better knowledge of toxicokinetics of the different metals wild animals may be exposed to would allow gaining insight in the understanding of internal exchanges between blood and organs.

Toxicokinetics of Cd, one of the main metals found in mining and smelting-impacted sites (including our study site of Metaleurop Nord), have been relatively extensively studied, mainly in birds. Cd accumulation occurs primarily in kidneys and in the liver [START_REF] Scheuhammer | The chronic toxicity of aluminium, cadmium, mercury, and lead in birds: A review[END_REF] and the release from kidneys has been proved to be very slow (Mayack et al., 1981). Thus, under conditions of chronic dietary exposure, Cd concentrations in kidneys are thought to represent long-term accumulation [START_REF] Scheuhammer | The chronic toxicity of aluminium, cadmium, mercury, and lead in birds: A review[END_REF]. In contrast, Cd in the blood equilibrates with exposure over a much shorter period of time (Hammond and Beliles, 1980), suggesting that concentrations in blood represent short term exposure. In addition, relative Cd accumulation by kidneys and the liver is dependent on the magnitude of the exposure; with increasing exposure, a higher proportion is deposited in the liver (Hammond and Beliles, 1980;[START_REF] Scheuhammer | The chronic toxicity of aluminium, cadmium, mercury, and lead in birds: A review[END_REF].

Since blood concentrations of Cd under steady-state conditions are expected to equilibrate with concentrations in both the liver and kidneys [START_REF] García-Fernández | Environmental Exposure and Distribution of Lead in Four Species of Raptors in Southeastern Spain[END_REF], changes in liver-kidney ratios of Cd will likely also influence blood-kidney ratios. For example, changes in body and organ masses may alter blood-organ ratios of metals. Moreover, and contrary to the liver or kidneys, blood does not constitute a tissue of storage. In the present study, the lowest concentrations of most elements were indeed found in the blood. In wild birds, Garcia-Fernandez et al. (1997) showed that Cd levels in blood represent a very small part of only 0.5% of Cd body burden, while liver and kidneys together contain 92% of the total (of which 61% for kidneys only). Moreover, it is possible that concentrations of elements in blood did not change in the same manner as those in the liver or kidneys because metal sequestration features and speciation (differed between the tissues, see [START_REF] Vijver | Internal Metal Sequestration and Its Ecotoxicological Relevance: A Review[END_REF] for details). For instance, it has been shown in the rainbow trout (Oncorhynchus mykiss) that the patterns of subcellular partitioning of Cd varied according to target organs, with a different pattern of Cd accumulation in subcellular fractions in the gill and in the liver [START_REF] Kamunde | Early subcellular partitioning of cadmium in gill and liver of rainbow trout (Oncorhynchus mykiss) following low-to-near-lethal waterborne cadmium exposure[END_REF]. Thus, changes in body and organ masses associated to blood and organs differences in their proportions of free/bound metals may stress different levels of total metals between blood and organs.

The imprecise relationship between blood and hepatic concentrations of metals may also be attributed partially to their different elimination rates in tissues. The elimination rate is initially faster from liver than from blood [START_REF] Heinz | Selenium accumulation and elimination in mallards[END_REF]. Additionally, binding of metals to inorganic molecules in the liver (as well as in other organs) may result in the formation of inert complexes with a long biological half-life [START_REF] Scheuhammer | Elevated lead concentrations in edible portions of game birds harvested with lead shot[END_REF] and the proportion of the total metal pool that is bound may affect its distribution among different tissues [START_REF] Cuvin-Aralar | Damage to the liver, kidney, and testis with reference to burden of heavy metals in yellow-necked mice from areas around steelworks and zinc smelters in Poland[END_REF]. Taken together, those data indicate that internal exchanges and rates of turn-over among tissues are key parameters in explaining blood-organ relationships, an area that would need further research.

General increase in concentrations of essential (Fe, Mg, Mn, Cu, and Cr) and non-essential elements (Pb) with age have been reported in organs in the wood mice [START_REF] Lopes | Influence of age, sex, and sexual activity on trace element levels and antioxidant enzyme activities in field mice (Apodemus sylvaticus and Mus spretus)[END_REF][START_REF] Beernaert | Non-destructive pollution exposure assessment by means of wood mice hair[END_REF] and in other mammals [START_REF] Scheirs | Genotoxicity in wood mice (Apodemus sylvaticus) along a pollution gradient: Exposure-, age-, and gender-related effects[END_REF][START_REF] Outridge | Bioaccumulation and Toxicology of Chromium: Implications for Wildlife[END_REF][START_REF] Sánchez-Chardi | Bioaccumulation of metals and effects of landfill pollution in small mammals. Part I. The greater white-toothed shrew, Crocidura russula[END_REF].

In our study, except for Cd, we did not detect age-related effects in the relationship between blood and organs concentrations. Age-related increases in organs have been reported for Cd [START_REF] Sheffield | Rodentia and lagomorpha[END_REF] and translate a Cd accumulation in storage organs along small mammals life.

The present study provides original results on the relationships between blood and organs concentrations for several metals. Our study provides simple and relatively accurate models (with R² ranging from 0.56 to 0.91) for Se, Pb and Tl, suggesting that blood sampling may be a useful tool in order to study these metals in wild, free-ranging small mammals. Conversely, for other metals such as Cd, Cu, Fe, Mo, Ti, and Zn, and in our levels of metals concentrations, blood concentrations were not a good indicator of internal concentrations, suggesting that blood sampling as a non-lethal methodology to predict organ concentrations may not be relevant for those metals. Further studies are clearly needed on other sites, on several years or at different seasons, and on different (small) mammal species to test (and modify if needed) the models developed here. The method would particularly be applicable where destructive sampling cannot be allowed, in protected areas and/or on endangered species.

Tables

Supplementary Data

Table S1. Certified values and average recoveries of the Certified Reference Materials used in this study (the number of reference samples analyzed for each certified reference materials is 9). High 6,01 6,01 6,01 6,01 0,086 0,084 0,002 0,171 0,105 0,119 0,065 0,218 14 100 7 0

Control 10,7 10,7 10,7 10,7 0,005 0,015 0,005 0,110 0,006 0,043 0,006 0,236 16 100 81 81

Low 10,7 10,7 10,7 10,7 0,005 0,015 0,005 0,134 0,006 0,071 0,006 0,712 15 100 87 80

Medium 10,7 10,7 10,7 10,7 0,005 0,009 0,005 0,049 0,006 0,047 0,006 0,189 11 100 91 27

High 10,7 10,7 10,7 10,7 0,005 0,005 0,005 0,005 0,036 0,074 0,006 0,377 12 100 100 50

Control 10,7 19,1 10,7 112 0,005 0,018 0,005 0,088 0,006 0,006 0,006 0,006 11 100 82 100

Low 10,7 10,7 10,7 10,7 0,005 0,007 0,005 0,039 0,006 0,078 0,006 0,305 18 94 94 61

Medium 10,7 10,7 10,7 10,7 0,005 0,008 0,005 0,036 0,006 0,037 0,006 0,263 23 100 91 78

High 10,7 13,0 10,7 43,4 0,005 0,009 0,005 0,039 0,006 0,091 0,006 0,738 14 Control 0,198 0,201 0,198 0,240 0,002 0,002 0,001 0,005 0,024 0,026 0,000 0,060 16 94 0 6 Low 0,198 0,198 0,198 0,198 0,003 0,005 0,001 0,014 0,047 0,048 0,006 0,136 15 100 0 0 Medium 0,198 0,205 0,198 0,280 0,004 0,005 0,001 0,015 0,026 0,040 0,013 0,132 11 91 0 0 High 0,520 0,666 0,198 2,08 0,031 0,040 0,007 0,135 0,260 0,459 0,125 1,65 12 25 0 0 Control 0,198 0,198 0,198 0,198 0,003 0,003 0,001 0,009 0,036 0,037 0,010 0,078 11 100 0 0 Low 0,198 0,210 0,198 0,400 0,004 0,004 0,002 0,006 0,034 0,035 0,007 0,077 18 89 0 0 Medium 0,198 0,198 0,198 0,198 0,004 0,007 0,002 0,023 0,039 0,074 0,009 0,286 23 100 0 0 High 0,660 1,98 0,198 13,2 0,043 0,135 0,012 0,867 0,499 1,21 0,149 7,06 14 7 0 0

FiguresFig. 1 .

 1 Figures

Fig. 2 .

 2 Fig. 2. Lead concentrations in kidneys (A), liver (B) and blood (H), Cd concentrations in kidney (C) and liver

Fig. 3 .

 3 Fig. 3. Relationship between blood and organs concentrations in the wood mouse Apodemus sylvaticus. (A)

Fig. 4 .

 4 Fig. 4. Relationship between blood and organs concentrations (liver and kidney) in male (blue) and female

Fig. S2 .

 S2 Fig. S2. Relationship between blood (in μg/L) and kidneys (in μg/g) concentrations for 9 trace metals (Se, Cd, Fe, Tl, Mo, Pb, Zn, Ti and Cu).

Fig. S3 .

 S3 Fig.S3. Relationship between blood (μg/L) and liver (μg/g) concentrations for 9 trace metals (Se, Cd, Fe ,Tl, Mo, Pb, Zn, Ti and Cu).

Fig. S4 .

 S4 Fig. S4. Concentrations in blood, kidneys and liver along the pollution gradient based on soil concentrations for Cd, Pb and Zn, for 11 trace metals (Cd, Cu, Fe, Mn, Mo, Pb, Se, Sn, Ti, Tl and Zn).

Table 1 .

 1 Summary of study squares characteristics. Median [minimum -maximum] Cd, Pb and ZN concentrations (μg/g, dry weight) in soils collected in the vicinity of the former Metaleurop Nord smelter. Results are presented for each sampling unit (square) corresponding to each pollution level.

	Sampling squares

Table 2 .

 2 Results from general linear models linking metal blood concentrations to liver and kidneys concentrations in wood mice. A backward selection procedure was used, with least significant variables being removed sequentially, until a minimum adequate model (presented). Bold indicates significant p

	values.

Table S2 .

 S2 Trace metal (TM) concentrations (median, mean, minimum and maximum) in blood (expressed in μg/L) and organs (liver and kidney expressed in μg/g) for the 18 tested TM. Total number of samples and the percentage of data under the quantification limit are given.

	Element			Al		As	Cd	Co	Cr	Cu	Fe	Mn	Mo	Ni	Pb	Sb	Se	Sn	Sr	Ti	Tl	Zn
		Control		8,90	8,90	8,90	8,90	0,008 0,017 0,008 0,089 0,010 0,010 0,010 0,010 16	100	88	100
		Low Medium Certified 8,90 8,90	8,90 8,90	8,90 8,90	8,90 8,90	0,008 0,013 0,008 0,084 0,010 0,010 0,010 0,010 15 0,008 0,008 0,008 0,008 0,010 0,010 0,010 0,010 11	100 100	7 100	100 100
		High		8,90	8,90	8,90	8,90	0,008 0,008 0,008 0,008 0,010 0,010 0,010 0,010 12	100	100	100
		Control	values	8,90	NS a 8,90	8,90	21.6 8,90	26.7 0,008 0,013 0,008 0,063 0,010 0,010 0,010 0,010 11 0.51 0.77 106 105	13.6 100	0.95 91	2.5 100	0.35	NS	5.63	0.04 c	45.2	NS	NS	180
		Low		8,90	8,90	8,90	8,90	0,008 0,008 0,008 0,008 0,010 0,010 0,010 0,010 18	94		100	100
	TORT-2	Medium High	(µg/g)	8,90 8,90	8,90 9,30	8,90 8,90	8,90 14,6	0,008 0,014 0,008 0,144 0,010 0,017 0,010 0,173 23 0,008 0,027 0,008 0,104 0,010 0,010 0,010 0,010 14	100 7	4 79	96 100
		Control		3,46	3,46	3,46	3,46	0,731 1,13 0,261 3,79	3,40	5,27 0,741 29,2 16	100	0	0
		Low Medium Recovery 3,46 3,46 High 3,46 (%) Control 3,46	5,56 ND b 5,45 4,46 9,24	2,40 3,46 2,72 3,46	19,6 99 19,6 15,6 50,0	2,27 98 5,99 3,38 0,523 0,945 0,121 4,70 3,97 0,186 12,8 89 14,9 0,460 59,9 5,62 0,635 17,9	6,87 72 13,4 19,4 1,74	15,9 1,02 56,4 15 80 75 27,4 2,77 74,4 11 21,1 2,40 46,1 12 2,70 0,376 7,56 11	40 64 58 82	77	0 100 0 0 0	0 78 0 0 0	120	ND	109	171	101	ND	ND	107
		Low		3,46	3,49	2,40	4,68	1,36	1,72 0,740 3,59	5,23	6,31 2,23 12,2 18	67		0	0
		Medium Certified 3,46 High 3,46	3,82 3,99	3,40 2,40	7,80 7,28	3,51 3,96	5,37 0,713 17,1 5,14 1,13 11,0	9,61 18,5	17,7 2,26 81,5 23 19,8 4,48 37,3 14	70 50		0 0	0 0
		Control Low	values	6,01 6,01	NS 6,14 6,01	5,64 6,01	NS 7,64 6,01	12.33 0,085 0,076 0,002 0,189 0,149 0,182 0,055 0,870 16 NS NS NS NS 0,055 0,063 0,002 0,195 0,099 0,117 0,050 0,362 15	NS 81 100	NS 25 33	NS 0 0	772	NS	NS	NS	NS	NS	NS	NS
	ERM®-CE196	Medium High Control Low	(µg/L)	6,01 6,01 6,01 6,01	6,01 6,01 6,10 6,36	6,01 6,01 6,01 6,01	6,01 6,01 7,04 11,96 0,067 0,067 0,002 0,173 0,096 0,145 0,002 1,02 18 0,076 0,070 0,002 0,096 0,106 0,105 0,060 0,152 11 0,073 0,077 0,002 0,151 0,098 0,110 0,002 0,196 12 0,12 0,13 0,002 0,260 0,111 0,125 0,002 0,224 11	100 100 91 94	91 17 9 28	0 8 91 11
		Recovery Medium 6,01	6,01	6,01	6,01	0,087 0,074 0,002 0,130 0,097 0,103 0,045 0,196 23	100	13	0
					ND		ND	77	ND	ND	ND	ND	ND	ND	ND	79	ND	ND	ND	ND	ND	ND	ND
			(%)
	a Not specified
	b Not determined
	c Indicative (not certified) value

% < LQ in blood % < LQ in liver % < LQ in kidney Element Sex Soil contamination level Blood concentration (µg/L) Liver concentration (µg/g) Median Mean Min Max Median Mean Min Max Median Mean Min Max

	Control	101	191	56	1089 0,009 0,040 0,009 0,308 0,011 0,082 0,011 0,427 16	0	87	75
	Low	44	90	22	396	0,009 0,032 0,009 0,274 0,011 0,055 0,011 0,281 15	47	9	80
	Medium	117	157	22	365	0,009 0,294 0,009 3,15 0,011 0,134 0,011 1,21 11	82	83	18
	High	99	579	22	3116 0,009 0,024 0,009 0,117 0,011 0,079 0,011 0,390 12	50	64	67
	Control	71,0	771 21,9 8164 0,009 0,070 0,009 0,259 0,102 0,248 0,011 0,936 11	9	89	45
	Low	62,3	132 21,9 440	0,009 0,104 0,009 1,36 0,116 0,303 0,011 1,46 18	39	96	50
	Medium	72,4	163 21,9 890	0,009 0,012 0,009 0,072 0,011 0,095 0,011 0,480 23	83	86	70
	High	88,3	641 21,9 2124 0,009 0,061 0,009 0,633 0,011 0,027 0,011 0,161 14	36	0	86
	Control	53,1	62,5 24,0 129	0,237 0,270 0,072 0,481 1,65	2,09 0,427 4,42 16	0	0	0
	Low	141	285 72,6 1901 0,816 0,922 0,055 2,88	3,97	4,59 0,286 9,17 15	0	0	0
	Medium	75,0	98,0 33,7 314	0,272 0,433 0,126 1,27	2,34	3,02 1,00 7,15 11	0	0	0
	High	145	156 80,3 250	0,698 0,774 0,207 1,97	12,8	34,9 4,64 229 12	0	0	0
	Control	64,7	75,8 10,8 240	0,257 0,433 0,047 2,38	1,96	2,66 0,259 9,10 11	0	0	0
	Low	91,4	107 23,0 288	0,346 0,643 0,082 3,11	3,16	3,89 0,451 9,14 18	0	0	0
	Medium	73,2	85,7 17,9 168	0,345 0,378 0,055 0,926 2,95	3,06 0,54 7,74 23	0	0	0
	High	178	207 87,6 440	1,00	1,48 0,196 4,74	17,5	27,1 3,26 117 14	0	0	0
	Control	3,95	3,95 3,95 3,95 0,002 0,002 0,002 0,002 0,003 0,003 0,003 0,003 16	100	100	100
	Low	3,95	3,95 3,95 3,95 0,002 0,002 0,002 0,002 0,003 0,003 0,003 0,003 15	100	100	100
	Medium	3,95	3,95 3,95 3,95 0,002 0,002 0,002 0,002 0,003 0,003 0,003 0,003 11	100	92	100
	High	3,95	3,95 3,95 3,95 0,002 0,003 0,002 0,010 0,003 0,006 0,003 0,040 12	100	92	83
	Control	3,95	3,95 3,95 3,95 0,002 0,002 0,002 0,002 0,003 0,003 0,003 0,003 11	100	89	100
	Low	3,95	3,95 3,95 3,95 0,002 0,003 0,002 0,016 0,003 0,003 0,003 0,003 18	100	96	100
	Medium	3,95	3,95 3,95 3,95 0,002 0,003 0,002 0,008 0,003 0,003 0,003 0,003 23	100	93	100
	High	3,95	3,95 3,95 3,95 0,002 0,004 0,002 0,022 0,003 0,005 0,003 0,032 14	100	0	93
	Control	92,5	95,4 62,5 146	2,34	2,64 1,01 5,44	5,52	5,38 2,85 8,46 16	0	0	0
	Low	70,5	81,5 32,2 239	1,43	1,78 0,462 4,68	5,69	5,17 2,65 7,45 15	0	0	0
	Medium	267	277 218	345	6,63	6,98 5,76 9,45	9,21	9,89 7,16 15,1 11	0	0	0
	High	421	428 256	626	8,36	8,48 6,49 12,1	16,3	24,2 9,46 91,7 12	0	0	0
	Control	91,2	90,1 73,3 112	2,04	2,19 1,27 3,51	5,20	5,43 4,02 7,39 11	0	0	0
	Low	91,0	84,8 39,7 124	2,51	2,42 0,85 4,39	6,00	5,79 4,14 7,68 18	0	0	0
	Medium	242	239 145	369	6,73	6,85 4,75 11,0	9,18	9,43 7,09 12,5 23	0	0	0
	High	363	406 238 1137	8,50	9,01 5,61 20,3	17,3	21,2 9,19 67,5 14

Table S3 .

 S3 Tukey's HSD tests summary. Comparisons between squares of increasing level of soil Cd, Pb and Zn contamination are presented for blood, liver and kidneys.

	Kidney Liver
		Fe Control Low Medium High Fe Control Low Medium High		Cd Control Low Medium High Cd Control Low Medium High
	F=0.21 F=0.76	Control Control				F=17.02 Control F=14.62 Control
	p=0.89 p=0.52 Blood Df=3 Df=3	Low Low Medium Medium	0.92 0.99 0.99 0.91	0.90 0.98		p<0.001 p<0.001 Df=3 Medium p<0.001 Low 0.004 Low 0.04 Df=3 Medium p<0.001	0.08 0.006
		Fe Control Low Medium High High 0.99 0.95 0.99 High 0.87 0.69 0.46		Cd Control Low Medium High High p<0.001 0.006 0.69 High p<0.001 0.033 0.98
	F=4.99	Control				F=0.30	Control
	p=0.003 Df=3 F=0.56 F=1.49 p=0.64 p=0.22	Low Medium 0.001 0.27 Cu Control Low Medium High 0.17 Cu Control Low Medium High High 0.09 0.91 0.60 Control Control Low 0.76 Low 0.79	p=0.82 Df=3 F=3.621 Control Low Mn Control Low Medium High 0.84 Mn Control Low Medium High Medium 0.94 0.99 High 0.84 0.99 F=8.48 Control 0.99 p=0.02 Low 0.19 p<0.001 Low p<0.001
	Df=3 Df=3	Medium Medium	0.99 0.93	0.74 0.39		Df=3 Medium Df=3 Medium	0.44 0.18	0.95 0.11
		Cu Control Low Medium High High 0.86 0.99 0.84 High 0.61 0.98 0.25		Mn Control Low Medium High High 0.008 0.50 0.22 High p<0.001 0.97 0.06
	F=33.51	Control				F=0.47	Control
	p<0.001 Df=3 F=4.9 F=3.97 p=0.003 p=0.01	Low Medium p<0.001 p<0.001 Mo Control Low Medium High 0.02 Mo Control Low Medium High High p<0.001 0.85 0.19 Control Control Low 0.91 Low 0.20	p=0.70 Df=3 F=38.2 F=12 p<0.001 p<0.001	Low Pb Control Low Medium High 0.98 Pb Control Low Medium High Medium 0.99 0.91 High 0.85 0.65 Control Control 0.94 Low 0.07 Low 0.004
	Df=3 Df=3	Medium Medium	0.03 0.57	0.002 0.005		Df=3 Medium Df=3 Medium	0.67 0.87	0.47 0.03
		Mo Control Low Medium High High 0.96 0.67 0.11 High 0.96 0.50 0.29		Pb Control Low Medium High High p<0.001 p<0.001 p<0.001 High p<0.001 0.20 p<0.001
	F=0.66	Control				F=16.34 Control
	p=0.57 Df=3 F=92.1 F=123.9 Control Low Medium Se Control Low Medium High 0.92 0.10 0.82 Se Control Low Medium High High 0.73 0.97 0.59 Control p<0.001 Low 0.99 p<0.001 Low 0.28	p<0.001 Df=3 F=0.452 Control Low Sn Control Low Medium High p<0.001 Sn Control Low Medium High Medium 0.28 0.07 High p<0.001 0.04 F=1.01 Control p<0.001 p=0.71 Low 0.99 p=0.39 Low 0.79
	Df=3 Df=3	Medium p<0.001 p<0.001 Medium p<0.001 p<0.001		Df=3 Medium Df=3 Medium	0.83 0.41	0.92 0.92
		Se Control Low Medium High High p<0.001 p<0.001 p<0.001 High p<0.001 p<0.001 0.05		Sn Control Low Medium High High 0.76 0.86 0.99 High 0.46 0.93 0.99
	F=185.7	Control				F=2.88	Control
	p<0.001 Df=3 F=1.09 F=1.6 p=0.36 p=0.19	Low Medium p<0.001 p<0.001 0.11 Ti Control Low Ti Control Low High p<0.001 p<0.001 Control Control Low 0.69 Low 0.19	Medium High Medium High p<0.001	p=0.04 Df=3 F=19.08 Control Low Tl Tl Medium High F=10.28 Control p<0.001 Low p<0.001 Low	0.04 Control Control 0.13 0.11 0.99 0.99	Low Low 0.94 0.99	Medium High Medium High 0.99
	Df=3 Df=3	Medium Medium	0.95 0.90	0.32 0.5		Df=3 Medium Df=3 Medium	0.99 0.99	0.99 0.99
		Ti High High	Control 0.99 0.46	Low 0.54 0.97	Medium High 0.99 0.82		Tl High High	Control p<0.001 p<0.001	Low p<0.001 p<0.001	Medium High p<0.001 p<0.001
	F=15.43	Control				F=19.08 Control
	p<0.001 Df=3 F=1.127 F=4.49 p=0.34 p=0.01	Low Medium Zn Control Low Medium High p<0.001 0.07 p<0.001 Zn Control Low Medium High High 0.09 p<0.001 0.99 Control Control Low 0.30 Low 0.03	p<0.001 Df=3	Low Medium High	0.99 0.99 p<0.001	0.99 p<0.001	p<0.001
	Df=3 Df=3	Medium Medium	0.95 0.96	0.57 0.004
		Zn Control Low Medium High High 0.81 0.86 0.97 High 0.99 0.08 0.85
	F=5.61	Control
	p=0.001	Low	0.04
	Df=3	Medium	0.85	0.002
		High	0.24	0.90	0.03

Acknowledgements

The authors gratefully thank Nadia Crini and Caroline Amiot for their technical help in metal analyses, and Virgile Baudrot, Javier Fernandez de Simon, Julie Montaz, Aurore Niechajowicz, Shinji Ozaki, Nicolas Tête, and Núria Vallverdu Coll, for their help in the field. The ADEME (Agence De l'Environnement et de la Maîtrise de l'Energie, https://www.ademe.fr/) financially supported the present work (programmes BIOTROPH N°1172C0030 and DYSPAT N°1572C0309).