Jian-Li Liu

Jun Yao
email: yaojun@cugb.edu.cn

Fei Wang

Ning Min

Ji-Hai Gu

Zi-Fu Li

Geoffrey Sunahara

Robert Duran

Tatjana Solevic-Knudsen

Karen A Hudson-Edwards

Tatjana Solevic Knudsen

Lena Alakangas

Bacterial diversity in typical abandoned multi-contaminated nonferrous metal(loid) tailings during natural attenuation

Keywords: bacterial community succession, metal(loid)s, natural attenuation, nonferrous metal(loid) tailings

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

Introduction

Mine tailings repositories are unwanted and uneconomic materials from the mineral processing deposited exposure in the air. Tailings often contain elevated concentrations of metal(loid)s, which are potentially toxic [START_REF] Lecumberri-Sanchez | Genetic relationship between silver-lead-zinc mineralization in the Wutong deposit, Guangxi province and Mesozoic granitic magmatism in the Nanling belt, southeast China[END_REF][START_REF] Hudson-Edwards | Tackling mine wastes[END_REF]. Abandoned nonferrous metal(loid) tailings (i.e., facilities having no operator or successor) have received considerable attention around the world because they represent a risk for the environment and human health [START_REF] Aleksandrovskii | Soils and cultural layers of ancient cities in the south of European Russia[END_REF]COM, 2016). Guangxi (China) is one of the predominant nonferrous mining areas in the world [START_REF] Rademaekers | Competitiveness of the EU non-ferrous metals industries FWC sector competitiveness studies[END_REF]. It is a karst landform with many ecologically sensitive areas and is located upstream of the Pearl River Basin (China's third longest river and second largest by volume) [START_REF] Wang | Analysis on Karst rocky desertification in upper reaches of Pearl River based on remote sensing[END_REF]. In Guangxi, different mining activities release waste that results in the formation of tailings with heterogeneous composition containing high concentrations of metal(loid)s and flotation reagents [START_REF] Liu | China's most typical nonferrous organic-metal facilities own specific microbial communities[END_REF]. Such level of multicomponent contamination is probably more serious than many other areas in the world [START_REF] Zhu | Combined effects of antimony and sodium diethyldithiocarbamate on soil microbial activity and speciation change of heavy metals. Implications for contaminated lands hazardous material pollution in nonferrous metal mining areas[END_REF].

Biotic and abiotic processes modify the speciation of metal(loid)s and physicalchemical characteristics in tailings (Ye et al., 2017a;Ye et al., 2017b), which facilitate metal(loid)s permeation into soil, surface runoff, and air transportation [START_REF] Deng | Research on soil multi-media environmental pollution around a Pb-Zn mining and smelting plant in the karst area of Guangxi Zhuang Autonomous Region, Southwest China[END_REF]COM, 2016;[START_REF] Jiang | On analysis and strategies for tailing ponds in Guangxi[END_REF][START_REF] Yi | Evaluation of biomonitoring methods using benthic biatoms in Longjiang River, China[END_REF][START_REF] Yuan | The leaching principles of heavy metals in Pb-Zn tailings in simulation acid rain[END_REF]. Natural attenuation occurs when natural processes (including pedogenesis) are managed to recover an ecosystem to a point where the original fauna and flora are replicated [START_REF] Clewell | Restoration of natural capital[END_REF]. Natural attenuation is more economical for re-purposing tailings compared to physical remediation, reclamation processes, or activated biochar addition on remediation [START_REF] Lima | The legacy of surface mining: remediation, restoration, reclamation and rehabilitation[END_REF][START_REF] Ye | The effects of activated biochar addition on remediation efficiency of co-composting with contaminated wetland soil[END_REF]. However, natural attenuation is a slow process that can take more than 100 years [START_REF] Bradshaw | Restoration of mined lands -using natural processes[END_REF][START_REF] Ciarkowska | Natural restoration of soils on mine heaps with similar technogenic parent material: A case study of long-term soil evolution in Silesian-Krakow Upland Poland[END_REF][START_REF] Lima | The legacy of surface mining: remediation, restoration, reclamation and rehabilitation[END_REF]. With time, microbial colonization follows the modification of physical-chemical parameters [START_REF] Giloteaux | Three-year survey of sulfatereducing bacteria community structure in Carnoulès acid mine drainage (France), highly contaminated by arsenic[END_REF] due to biogeochemical processes [START_REF] Haferburg | Microbes and metals: interactions in the environment[END_REF]. Knowledge of the colonization of microbial communities during natural attenuation in mine tailings is limited [START_REF] Bruneel | Archaeal diversity in a Fe-As rich acid mine drainage at Carnoulès (France)[END_REF][START_REF] Volant | Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and other drivers along an acid mine drainage[END_REF][START_REF] Zhan | Development of microbial properties and enzyme activities in copper mine wasteland during natural restoration[END_REF][START_REF] Chao | Structure, variation, and co-occurrence of soil microbial communities in abandoned sites of a rare earth elements mine[END_REF], particularly in the Guangxi area where only three tailings sites (Pb-Zn and Mn sites) have been investigated [START_REF] Jin | Canonical correspondence analysis of soil heavy metal pollution, microflora and enzyme activities in the Pb-Zn mine tailing dam collapse area of Sidi village, SW China[END_REF][START_REF] Liu | Soil characteristics and heavy metal accumulation by native plants in a Mn mining area of Guangxi, South China[END_REF][START_REF] Li | The effect of toxicity of heavy metals contained in tailing sands on the organic carbon metabolic activity of soil microorganisms from different land use types in the karst region[END_REF]. Recent results show that the distribution of bacterial communities in Guangxi nonferrous metal(loid)s tailings was best correlated with the combination of pH, Cu, Pb, and Mn, suggesting that these parameters influence the organization of bacterial communities [START_REF] Liu | China's most typical nonferrous organic-metal facilities own specific microbial communities[END_REF]. However, the modification of bacterial communities during natural attenuation in undisturbed nonferrous metal(loid) tailings is still uninvestigated.

To address this research gap, we examined nonferrous mine tailings sites with different periods of abandonment (from 3 to 31 years) in the Guangxi mining area (Fig. 1 and Table S1), which have different geochemical characteristics. We hypothesize that temporal changes in biogeochemical factors, and bacterial diversity and metabolic functions are part of the natural attenuation process occurring in these tailings. The present study offers the possibility to examine the ecological changes, such as primary succession of microbial communities during natural attenuation. The objectives of this study were to: (1) investigate the structure of the microbial community (by MiSeq sequencing of 16S rRNA genes) and predict the metabolic functions in mine tailings, and (2) analyze the combined effects of geochemical factors including pH, total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), and metal(loid)s content on the bacterial community structure. This study will provide a better understanding of microbial variations in nonferrous mine tailings, and useful information for the management of bacterial resources during natural attenuation of nonferrous metal(loid) tailings.

Materials and methods

Site description and sampling

Sampling was performed around Hechi City of Guangxi (China) (Fig. 1), which has a subtropical monsoon climate [START_REF] Bi | Climatic change characteristics of Hechi city in the last 56 years[END_REF]. Seven tailings sites with different composition and ages (ranging from three to 31 years old) were sampled to evaluate changes in bacterial communities during the natural attenuation (Fig. 1). The abandonment periods were determined using tailings pond records from the local Environmental Protection Agency. The types of tail sand at these seven tailings sites were mainly from Sb, Pb-Zn, and Sn mining and smelting industries (Table S1).

These tailings were not treated with amendments or any remediation technology.

There was no visible plant growth in all of the studied sites.

Surface samples (0-10 cm) with 3-10 subsamples for each site were collected in June 2016, using a wooden shovel according to EU international guideline [START_REF] Hansen | Uncertainty from sampling: workshop to launch a Nordtest handbook on sampling uncertainty estimation and control[END_REF]. All samples were directly placed into plastic pipes in cooler boxes (at 4°C) and transported to laboratory at the University of Science and Technology Beijing within 2 d of sampling. After thorough homogenization, the samples were split into two parts. Approximately 500 g for each sample was then stored at -20°C until DNA extraction. The remaining samples were used for geochemical analyses, and were stored at 4°C.

< insert Fig. 1 >

Analysis of geochemical factors

Samples were air-dried and analyzed according to the technical specifications for soil analysis for determination of pH, total organic carbon (TOC), total nitrogen (TN), and total phosphorus (TP) as defined by the China National Agricultural Technology Extension Center (2006). The operating conditions for the TOC solid sample module (SSM-5000A, Shimadzu) were: the oven temperature, 680°C, and the gas flow of high purity oxygen in TOC-V and SSM-5000A section, 150 and 500 mL/min, respectively. Samples were extracted with a solution of nitric, hydrochloric, and hydrofluoric acids (5:3:2, v/v/v) in a microwave unit to determine the total metal(loid)s content (T-M). The acid soluble fraction of metal(loid)s (H-M) were analyzed using the Chinese method HJ/T299-2007. This fraction of H-M represents the leachable compartment that could be released into the environment. The leaching solution was prepared by adding 0.09 mL of a solution of sulfuric and nitric acids (2:1, v/v) and taken up to 1 L with ultra-pure water (Milli-Q Academic Lab Water System, Millipore, USA). Certified reference materials of soil samples (GBW 07405 (GSS-5))

and polymetallic ore samples (GBW 07162 (GSO-1)) were used for quality control.

The limit of detection (LOD) for T-Ms was > 0.10×10 -3 mg/kg [START_REF] Liu | China's most typical nonferrous organic-metal facilities own specific microbial communities[END_REF] and for H-Ms was > 0.10 mg/kg [START_REF] Wang | Speciation changes of heavy metals in the process of tailings ecological restoration in northwest Guangxi[END_REF], according to the China Environmental Monitoring Technical guideline (HJ 168-2010). The recoveries were between 85% -110%. Samples were placed into 20 mL of leaching solution (pH 3.20 ± 0.05) and shaken for about 20 h. Induced coupled plasma optical emission spectrometry (ICP-OES) (iCAP 7000 SERIES, Thermo Scientific) was used to determine the metal(loid)s concentrations. The operating conditions were: auxiliary gas flow, 0.5 L/min; plasma gas stable time, 10 min; ICP RF power, 1150 W; and pump rate, 45 rpm. All the samples were sieved at 100-mesh size (0.149 mm, US standard) to determine the geochemical factors. The analyses were performed in duplicate to evaluate precision.

MiSeq sequencing and data processing

Genomic DNA was extracted using the SoilGen DNA Kit (CWBio, Bejing, China). DNA extraction kits allow to obtain high-quality DNA for PCR amplification and sequencing [START_REF] Bordenave | Structure and functional analyses of bacterial communities changes in microbial mats following petroleum exposure[END_REF][START_REF] Bordenave | Diversity of ringhydroxylating dioxygenases in pristine and oil contaminated microbial mats at genomic and transcriptomic levels[END_REF]. The potential damage during DNA extraction are prevented by diluting metal(loid)s and eliminating them in the first steps of the procedure allowing molecular analyses of highly contaminated samples such as acid mine drainage [START_REF] Giloteaux | Nested PCR and new primers for analysis of sulfate-reducing bacteria in low-cell-biomass environments[END_REF]. The universal primer set 338F/806R amplified the V3-V4 region of the bacterial 16S rRNA gene, and an 8 bp-tag was used for the sample identification [START_REF] Liu | Comparative studies of the composition of bacterial microbiota associated with the ruminal content, ruminal epithelium and in the faeces of lactating dairy cows[END_REF].

Polymerase chain reaction (PCR) amplification (20 μL) was conducted in triplicate and contained 10 ng DNA template, 4 μL of 5 × FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.2 μM of each primer, 0.4 μL FastPfu Polymerase, 0.2 μL bovine serum albumin, and double-distilled water. PCR was started with an initial denaturation (3 min at 95°C), followed by 28 cycles of denaturation (30 s at 95°C), annealing (30 s at 55°C), and extension (45 s at 72°C), and a final extension (10 min at 72°C).

Sequencing using a MiSeq platform was performed at a commercial facility (Shanghai Majorbio Bio-Pharm Technology Corporation, Shanghai, China).

All the 16S raw data were trimmed and filtered using Trimmomatic software (Manual v0.32), by trimming the average base quality region below 20 bp [START_REF] Trujillo | Genomic characterization of the LEED..PEEDs, a gene family unique to the Medicago lineage. G3-Genes Genom[END_REF]. The paired-end reads were merged using FLASH software. The sequences assigned to chloroplasts, mitochondria or eukaryotes were removed in the pretreatment of raw reads. Bacterial operational taxonomic units (OTUs) were clustered with 97% similarity using Usearch version 7.0 (http://drive5.com/uparse/) based on Silva Release128 (http://www.arb-silva.de). Taxonomy was assigned to OTUs using Qiime (http://qiime.org/scripts/assign_taxonomy.html) and ribosomal database project pipeline classification algorithm with a 70% confidence threshold [START_REF] Nakayama | Pyrosequence-based 16S rRNA profiling of gastrointestinal microbiota[END_REF]. Alpha diversity indices (ace, Shannon, Simpson evenness and Boneh) and hierarchical clustering were calculated with Qiime. Circos-0.67-7 was used to perform the bacterial composition of each sample, and the distribution ratio of dominant bacteria in different samples. Functional prediction of bacterial communities was determined using PICRUSt, a well-documented tool to assign sequencing information based on 16S input data to reveal the functions encoded in bacterial communities [START_REF] Langille | Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences[END_REF][START_REF] Mchardy | Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships[END_REF]. Kyoto Encyclopedia of Genes and Genomes (KEGG) databases (e-value cut-off 10 -5 ) were used for functional annotation and metabolism analyses [START_REF] Mchardy | Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships[END_REF][START_REF] Kanehisa | Data, information, knowledge and principle: back to metabolism in KEGG[END_REF][START_REF] Vrutika | Response and resilience of soil microbial communities inhabiting in edible oil stress/contamination from industrial estates[END_REF]. The weighted nearest sequenced taxon index (NSTI) was calculated to assess the accuracy of PICRUSt analysis [START_REF] Langille | Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences[END_REF].

Statistical analyses

One-way ANOVA was applied to test the differences of geochemical factors; a level of p < 0.05 was considered significant. The relationships between geochemical factors and alpha-diversity indexes were analyzed using Spearman correlation (SPSS v21). SIMPER analysis based on Bray-Curtis similarity measurement was used to test microbial differences in the tailings. Non-metric multidimensional scaling (NMDS) and distance-based redundancy analysis (db-RDA) analysis were conducted to test the correlation between bacterial communities and geochemical factors of tailings sites based on weighted normalized unifrac distance algorithm. The significance of geochemical factor was tested with Monte Carlo permutations (permu = 999).

Correlations of each bacterial community and each geochemical factor were calculated with p-values < 0.05 and plotted as a heatmap. Network analysis was used to reflect the relationship between tailings sites and genera. After detection for genera (Gephi software), each module was represented by network correlation shared values of abundance profile by using modularity analysis. BIOENV analysis was used to determine the combined effects of geochemical factors on the metabolic pathways of bacterial communities. All the analyses were done using R software (v 3.4.1) unless otherwise stated.

Results and discussion

Geochemical parameters of nonferrous mine tailings samples

The pH in the seven studied tailings (Table S1) decreased with the period of abandonment, notably around pH 7.3 at the youngest sites (from T_3Y to T_15Y), weakly acidic (pH 6.4) at site T_23Y, and extremely acidic (pH 2.6) at site T_31Y. This is consistent with other reports showing that the pH decreased in mine tailings undergoing more than 30 years of natural attenuation [START_REF] Huang | Spatial and temporal analysis of the microbial community in the tailings of a Pb-Zn mine generating acidic drainage[END_REF][START_REF] Zhan | Development of microbial properties and enzyme activities in copper mine wasteland during natural restoration[END_REF][START_REF] Ciarkowska | Natural restoration of soils on mine heaps with similar technogenic parent material: A case study of long-term soil evolution in Silesian-Krakow Upland Poland[END_REF]. The gradual acidification of tailings could be caused by microbial mediated oxidative dissolution of pyrite (FeS 2 ) and other sulfide minerals exposed to air and water during natural attenuation [START_REF] Huang | Microbial ecology and evolution in the acid mine drainage model system[END_REF]. The low nutrient concentrations of C/N/P could nevertheless support the observed growth of microorganisms (described below), at least during the early phases of natural attenuation [START_REF] Oudjehani | Natural attenuation potential of cyanide via microbial activity in mine tailings[END_REF].

As expected at nonferrous metal(loid) tailings sites, the total metal(loid)s contents (T-M) were higher compared with the reported tailing sites in other regions around the world [START_REF] Alakangas | Estimation of temporal changes in oxidation rates of sulphides in copper mine tailings at Laver, northern Sweden[END_REF][START_REF] Giloteaux | Three-year survey of sulfatereducing bacteria community structure in Carnoulès acid mine drainage (France), highly contaminated by arsenic[END_REF][START_REF] Bruneel | In-depth characterization of bacterial and archaeal communities present in the abandoned Kettara pyrrhotite mine tailings (Morocco)[END_REF].

The total arsenic content (T-As) was significantly correlated with total contents of Cd, Cr, and Zn (Spearman rho = from -0.82 to 0.86, p < 0.04; Table 1). Similar correlations between As, Zn, and Cd have been reported at mining-and aluminacontaminated soils [START_REF] Zacháry | Urban geochemical mapping for spatial risk assessment of multisource potentially toxic elements -a case study in the city of Ajka, Hungary[END_REF].

The acid soluble fraction of metal(loid)s (H-M), representing the leachable fraction, was generally higher in tailing sites with 31 years abandonment (Table S1).

Significant differences were also observed among the tailings sites, particularly for H-Cd, H-Cr, and H-Cu (ANOVA, p < 0.05, Table S1). Acid-soluble fraction in surface tailings represents the elements releasable that can migrate laterally or downwards via biotic and abiotic processes [START_REF] Alakangas | Estimation of temporal changes in oxidation rates of sulphides in copper mine tailings at Laver, northern Sweden[END_REF][START_REF] Volant | Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and other drivers along an acid mine drainage[END_REF]. The increased concentration of H-Ms and decreased pH with the age of abandonment suggested that a release of these metal(loid) was increasing over time, which was reported for other tailings [START_REF] Walder | Mineralogical and geochemical behavior of mill tailing material produced from lead-zinc skarn mineralization, Hanover, Grant County, New Mexico, USA[END_REF][START_REF] Shu | Acidification of lead/zinc mine tailings and its effect on heavy metal mobility[END_REF].

< Insert Table 1 >

Microbial community diversity and composition of nonferrous mine tailings

To determine the bacterial dynamics in abandoned tailings, a total of 1,481 bacterial OTUs were identified of all quality 16S rRNA bacterial sequences (265,487 in total) after removing singletons and chimeric sequences (Tables S2 andS3). These 1,481 OTUs represent a high coverage (99.8 ± 0.1 %, Table S2), indicating that the sequencing data could reflect the vast majority of microbial diversity in the real environment. Furthermore, the Shannon diversity indexes were between 2.88 -4.80, which were similar to an earlier report of a Pb-Zn mining site [START_REF] Chen | Shifts in microbial community composition and function in the acidification of a lead/zinc mine tailings[END_REF].

Bacterial diversity showed a decreasing relationship with the age of abandonment (Table S2 and Fig. S1). Nevertheless, the bacterial richness (Table S2) was up to eight times higher than that reported in an abandoned Pb-Zn mine tailing site [START_REF] Epelde | Adaptation of soil microbial community structure and function to chronic metal contamination at an abandoned Pb-Zn mine[END_REF], but no significant trend could be observed with abandonment age. This could be due to some more fundamental properties of tailings such as tailing matrix, mineral phases, and chemical composition since the tailings are from different types of mining and smelting industries (Fig. S1). In contrast, [START_REF] Chao | Structure, variation, and co-occurrence of soil microbial communities in abandoned sites of a rare earth elements mine[END_REF] reported clear differences, as well as a time-dependent increase, in bacterial richness among REE (Rare Earth Elements) tailings sites that were abandoned for 3, 6, and 10 years. The richness of bacterial communities had a significant correlation with PD (phylogenetic diversity, rho = 0.972, p = 0.0002; Table 1), which was statistically correlated with TP (rho = 0.79, p = 0.036; Table 1). Overall, our results indicated a high genetic diversity in the Guangxi nonferrous mine tailings sites.

Over 98% of the OTUs could be assigned to a taxonomic phylum with 70% confidence; while over 56% of sequences were generally identified as no-rank or unclassified genera (Table S3), which was lower than that in a Sb-rich tailings dump [START_REF] Xiao | Microbial diversity and community structure in an antimony-rich tailings dump[END_REF]. Coupled with the high coverage and sequencing depth (99.8 ± 0.1 %, Table S2), this low assigned rate suggested these tailings sites had vast unidentified populations and microbial resources. These results were consistent with an earlier report showing that 58% of the sequences in a vanadium-and 17% in a gold-mine water from a South African mine, could not be assigned to a particular phylum [START_REF] Keshri | Profile of bacterial communities in South African mine-water samples using Illumina next-generation sequencing platform[END_REF]. Specifically, the shared phyla of tailings sites were Proteobacteria, Firmicutes, and Actionobacteria, accounting for 76% of total microbial community (Fig. 2), which confirmed recent studies by [START_REF] Liu | China's most typical nonferrous organic-metal facilities own specific microbial communities[END_REF] at abandoned nonferrous metal tailings sites, and by [START_REF] Chao | Structure, variation, and co-occurrence of soil microbial communities in abandoned sites of a rare earth elements mine[END_REF] at an abandoned REE tailings facility. These studies reported the same or similar dominant bacterial communities (at the phylum level), despite differences in pH and geochemical factors of the tailings. < insert Fig. 2 > Among the total 507 genera identified from the seven tailings sites, 31 shared genera (relative abundance > 1% of total sequences at least in one tailing site) had different abundance among the seven tailings sites (Table S4). The differences observed were mainly due to different abundances of Sulfuriferula, Bacillus, Sulfurifustis, Gaiella, and Thiobacillus (Table 2). Sulfurifustis and Thiobacillus were the most abundant genera shared by tailings sites that were abandoned for < 15 years (Table S4), indicating that these two genera may have contributed to sulfur-and iron oxidation at these sites. To date only three studies have detected Sulfurifustis that could be involved in sulfur oxidation [START_REF] Kojima | Sulfurifustis variabilis gen. nov. sp. nov. a novel sulfur oxidizer isolated from a lake, and proposal of Acidiferrobacteraceae fam. nov. and Acidiferrobacterales ord. nov[END_REF][START_REF] Kojima | Sulfuricaulis limicola gen. nov. sp. nov. a sulfur oxidizer isolated from a lake[END_REF][START_REF] Umezawa | The complete genome sequences of sulfur-oxidizing Gammaproteobacteria Sulfurifustis variabilis, skN76 T, and Sulfuricaulis limicola, HA5 T[END_REF]. Thiobacillus is capable of iron/sulfur-oxidization and carbon/nitrogen fixation in the early stages of the acidification processes of tailings [START_REF] Yamanaka | Mechanisms of oxidation of inorganic electron donors in autotrophic bacteria[END_REF][START_REF] Huang | Microbial ecology and evolution in the acid mine drainage model system[END_REF]. Ralstonia, the most abundant genus in tailing sites abandoned for up to 23 years (29%; Table S4), is a ubiquitous inhabitant of soil, freshwater and even ultrapure water in industrial systems [START_REF] Gan | Genome sequence of Ralstonia sp. strain pba, a bacterium involved in the biodegradation of 4-aminobenzenesulfonate[END_REF]. This genus carries metal resistant genes, such as czc (resistance to cadmium, zinc, and cobalt) and ncc (cobalt and cadmium) [START_REF] Mergeay | Ralstonia metallidurans, a bacterium specifically adapted to toxic metals: towards a catalogue of metal-responsive genes[END_REF]. Acidithiobacillus was most abundant at the extremely acidic tailing site (pH = 2.0, Table S1) abandoned for 31 years (accounting for 29% of total communities, Table S4). This genus was found to be able of carbon/nitrogen fixation, iron/sulfur oxidation, and arsenic oxidation [START_REF] Huang | Microbial ecology and evolution in the acid mine drainage model system[END_REF]. Acidithiobacillus may play an important role in the iron and arsenic oxidation in late acidification of the present tailing sites as reported for other tailings sites [START_REF] Bruneel | Microbial diversity in a pyrite-rich tailings impoundment (Carnoulès, France)[END_REF][START_REF] Jorge | Acidithiobacillus ferrooxidansmetabolism: from genome sequence to industrial applications[END_REF][START_REF] Huang | Microbial ecology and evolution in the acid mine drainage model system[END_REF].

< insert Table 2 >

Structure of tailings microbial communities

Although the tailings sites shared bacterial populations, the whole bacterial structures were different (Fig. 3). Correlation analysis of geochemical factors and bacterial structure of tailings revealed four cluster groups: i) OTUs in T_4Y, T_8Y, and T_15Y correlated with TOC, ii) OTUs in T_6Y correlated with TN, T-As, and H-Pb, iii) OTUs in T_23Y correlated with pH and H-Sb, and iv) OTUs in T_31Y correlated with pH and TP (Fig. 3). These findings were consistent with earlier studies indicating that pH, total metal(loid)s, and acid leachable metal(loid)s were correlated with microbial communities in tailings sites [START_REF] Bruneel | In-depth characterization of bacterial and archaeal communities present in the abandoned Kettara pyrrhotite mine tailings (Morocco)[END_REF][START_REF] Gupta | Metagenomic exploration of microbial community in mine tailings of Malanjkhand copper project, India[END_REF][START_REF] Hao | Thin-layer heap bioleaching of copper flotation tailings containing high levels of fine grains and microbial community succession analysis[END_REF]. The acid leachable or bio-accessible fractions of metal(loid)s (such as H-Pb) can easily migrate with applications of acid rain or during natural acidification, and this process can be accelerated by the metabolic processes of adapted microbial communities [START_REF] Haferburg | Microbes and metals: interactions in the environment[END_REF]. For example, to survive in aquatic and soil environments with Pb 2+ contamination, some microbes have developed Pb 2+ resistance, involved extracellular binding, intracellular sequestration, active transport, and exclusion by forming a permeable barrier [START_REF] Pan | Microbial strategy for potential lead remediation: A review study[END_REF]. < insert Fig. 3 > Specific genera in each tailing site were also observed (Fig. 4A), suggesting that these tailings sites represent unique ecological niches during tailing colonization and natural attenuation. The distribution of these genera correlated with a combination of pH, TOC, H-Pb, and T-As (rM = 0.80, p = 0.01; Fig. 4B; Table 3), indicating that these four geochemical factors may play a key role in the distribution of microbial communities. In tailing sites with 3 years abandonment, Desulfurivibrio were specific (Fig. 4A), which always grow chemolithotrophically by sulfur/sulfide oxidation and dissimilate the reduction of nitrate/nitrite in slight alkali environments [START_REF] Sorokin | Dethiobacter alkaliphilus gen. nov. sp. nov., and Desulfurivibrio alkaliphilus gen. nov. sp. nov.: two novel representatives of reductive sulfur cycle from soda lakes[END_REF][START_REF] Thorup | Disguised as a sulfate reducer: growth of the Deltaproteobacterium Desulfurivibrio alkaliphilus by sulfide oxidation with nitrate[END_REF]. Although no plants were observed at the tailings sites, specific Rhizobium genus, beneficial for plant growth (Sujkowska-Rybkowska and Ważny, 2018), were observed in site T_23Y. This observation could be explained by aerial seeding by plants from the surrounding areas. The distribution of bacterial communities in T_23Y was correlated with pH and H-Sb content (Fig. 3B). In the extremely acidic T_31Y tailing site, most of the specific genera, such as Acidithiobacillus and Acidiferrobacter, were related to sulfur/iron oxidation (Fig. 4A).

These genera had significant and negative correlations with pH, and significant positive correlations with H-As, H-Cr, and H-Cu contents (p < 0.001, Fig. 5). This observation would be expected because Acidiferrobacter and Acidithiobacillus species participate in the metabolism of iron, sulfur, arsenic, and organic matter [START_REF] Fan | Microbial communities in riparian soils of a settling pond for mine drainage treatment[END_REF][START_REF] Bruneel | In-depth characterization of bacterial and archaeal communities present in the abandoned Kettara pyrrhotite mine tailings (Morocco)[END_REF]. In addition, acidophilic Acidithiobacillus-related sequences can generate AMD waters, and oxidize the ferrous sulfate to immobilize As 5+ in arsenic-contaminated soil [START_REF] Huang | Microbial ecology and evolution in the acid mine drainage model system[END_REF][START_REF] Yang | Combination of microbial oxidation and biogenic schwertmannite immobilization: a potential remediation for highly arsenic-contaminated soil[END_REF], suggesting that this species may have an important ecological role for increasing metal sulfide dissolution and controlling AMD production. The frequently encountered distribution and numerous dominance of iron/sulfur-oxidizing and metal-related genera in acidic environments during the long process of natural attenuation reflects their potential role in the natural attenuation of metal(loid)s and generating AMD at tailings sites [START_REF] Chen | Shifts in microbial community composition and function in the acidification of a lead/zinc mine tailings[END_REF][START_REF] Huang | Microbial ecology and evolution in the acid mine drainage model system[END_REF]. [START_REF] Chao | Structure, variation, and co-occurrence of soil microbial communities in abandoned sites of a rare earth elements mine[END_REF] showed that soil microbiota can vary significantly at different abandoned REE tailing sites, by the co-development of microbial and plant communities during natural attenuation. These studies showed that site-specific factors induced microbial changes within subgroups of abandoned sites, which is consistent with our findings. However, the tailing samples in the [START_REF] Chao | Structure, variation, and co-occurrence of soil microbial communities in abandoned sites of a rare earth elements mine[END_REF] contained vegetal material compared to the present study. Therefore, it is not known if the microbial changes described in the Chao et al. study are related to site factors or plant development, or both. [START_REF] Ridl | Plants rather than mineral fertilization shape microbial community structure and functional potential in legacy contaminated soil[END_REF] demonstrated that plants, and not the use of fertilizers, were the drivers of microbial community structure in contaminated soil, with the magnitude of effect depending on the type of plant species. Based on our study, in which plants were not observed, it is likely that microbial changes were caused by geochemical factors and the extremely unfavorable growing conditions (such as low C/N/P contents and high metal(loid)s concentrations).

< insert Fig. 4 > < insert Fig. 5 > < insert Table 3 >

Potential functional metabolism of bacterial communities

For successful survival and adaptation to a multi-contaminated environment, which constitutes an evolutionary challenge for organisms, sophisticated resistance strategies and mechanisms are required for microbial succession [START_REF] Guan | Microbial response to environmental stresses: From fundamental mechanisms to practical applications[END_REF].

PICRUSt analysis was used for exploring the possible metabolism pathways associated with the detoxification of metal(loid)s and transport of geochemical elements in tailings undergoing natural attenuation. The NSTI (nearest sequenced taxon index) values in the present study were less than 0.18 (except at site T_3Y) indicating that the PICRUSt prediction analysis was accurate (Table S2). The relationship between the KEGG pathways and bacterial community structures revealed that each tailing site had its specific functional pathways (Fig. 6). KEGG pathways related to DNA replication and repair, and recombination proteins were mainly clustered close to tailing sites with 31 years natural attenuation (Fig. 6). As well, the distribution of these predicted functional metabolic pathways was strongly correlated with pH, TOC, TP, T-As, T-Zn, and H-Cr (r = 0.98, Table S7). It is known that environmental stresses (such as pH, As, and Pb) can directly or indirectly damage the structure of DNA, which results in the mismatch of nucleic acids, and DNA degradation, thus affecting the diversity and structure of microorganisms [START_REF] Amaral-Zettler | Microbial community structure across the tree of life in the extreme Río Tinto[END_REF][START_REF] Bruneel | In-depth characterization of bacterial and archaeal communities present in the abandoned Kettara pyrrhotite mine tailings (Morocco)[END_REF][START_REF] Guan | Microbial response to environmental stresses: From fundamental mechanisms to practical applications[END_REF][START_REF] Hao | Thin-layer heap bioleaching of copper flotation tailings containing high levels of fine grains and microbial community succession analysis[END_REF]. These in turn could ultimately lead to microbial cell injury, protein degradation, and gene mutation [START_REF] Dai | The significant role of colloids in the transport and transformation of organic carbon and associated trace metals (Cd, Cu and Ni) in the Rhône delta (France)[END_REF][START_REF] Guan | Microbial response to environmental stresses: From fundamental mechanisms to practical applications[END_REF]. It is possible that the DNA repair system participated in the sensitive targets of microbial metal(loid)s toxicity observed in our study, resulting in the adaptation of bacterial communities to the extreme tailings environments. SIMPER analysis using the KEGG database indicated that the metabolic pathways directly related to ATP, methane, nitrogen, and energy generation (such as ABC transporters) also contributed to the differences of bacterial community structures in the seven tailings sites (Table S5 andS6). ABC transporters constitute large amounts of membrane proteins and could transport many diverse substrates, such as metal(loid)s and secondary metabolites [START_REF] Theodoulou | ABC transporter research: going strong 40 years on[END_REF]. As discussed above, metal(loid) oxidation-related genus of Acidithiobacillus could also encode the ABC transporter genes involved with zinc ion transport [START_REF] Hou | Identification and analysis of zinc transport genes in Acidithiobacillus ferrooxidans[END_REF].

Previous studies also confirmed that genetic expression of iron/sulfur-oxidizing and metal(loid) tolerance may propagate through horizontal gene transfer [START_REF] Sandoval | Transfer of RPS14 and RPL5 from the mitochondrion to the nucleus in grasses[END_REF][START_REF] Bouzat | Evolutionary analysis and lateral gene transfer of two-component regulatory systems associated with heavy-metal tolerance in bacteria[END_REF], which enables bacterial communities to acquire a gene (or genes) favoring the adaptation of bacterial communities to extreme environments during natural attenuation. To better understand the mechanisms of bacterial communities undergoing natural attenuation in nonferrous metal tailings, further analyses combining geochemical parameters (such as inorganic C, sulfides/sulfates/iron contents, and the neutralization capacity) with metatranscriptomic and metagenomic analyses will provide useful information.

Conclusions

Our study provides greater insight into the temporal dynamics of bacterial communities during natural attenuation. Each tailing site was identified as a unique ecological niche. Tailings abandoned for < 15 years were in a pre-acidification phase and undergoing acidification. Tailings ≥ 23 years abandonment had higher acid soluble As concentrations and the metal(loid)s that may represent a risk for human health and the environment (COM, 2016;[START_REF] Hudson-Edwards | Tackling mine wastes[END_REF]. A gradual succession of bacterial genera in the tailings sites was observed suggesting that the bacterial communities become more acidophilic and metal-resistant. Functional metabolic pathways of DNA repair and recombination may be the main potential mechanisms for the microbes to cope with oligotrophic and extreme tailings habitats.

The present study suggests that although natural attenuation may be a key strategy towards sustainability, careful monitoring of abandoned tailings sites should be considered as early as possible, to enable the timely management of any potential environmental risks present at these sites. Main genus contributed to the differences between different bacterial communities of tailings sites with different abandoned time. The relative abundances of genera ≥ 1 at least at one tailing site are shown. 2.00 Contrib, the contribution of each genus to the differences of bacterial communities of tailings sites; a, T_3Y; b, T_4Y; c, T_6Y; d, T_8Y and T_15Y; e, T_23Y and T_31Y; "-", the contribution data < 0.4.

Figure legends

Table 3

Correlation analysis of modules eigengenes in the bacterial community network (Fig. 4) and selected geochemical factors by BIOENV analysis and Monte-Carlo test.

Combination of geochemical factors

Module Mining activity, the types of these tail sand; TOC, total organic carbon; TN, total nitrogen; TP, total phosphorus; T-(metal), total content of metal(loid)s; H-(metal), the acid leachable metal(loid)s. The unit for TOC, TN, TP, and content of metal(loid)s is mg/kg. Different letters in the same row denote significant differences between tailings sites at p < 0.05 level. "-" = no data.

Table S2.

The average sequences data for 16S rRNA in each tailing site. S7.

BIOENV analysis for the relationships between geochemical variables and functional prediction of KEGG pathways.

Combination of geochemical factors

Fig. 1 .

 1 Fig. 1. Sample location map (top left) and aerial photograph (top right) of the seven

Fig. 2 .

 2 Fig. 2. Relative abundances of bacterial phyla in the seven abandoned tailings sites.

Fig. 3 .

 3 Fig. 3. (A) Non-metric multidimensional scaling (NMDS) analysis of bacterial

Fig. 4 .Fig. 5 .Fig. 6

 456 Fig. 4. (A) Network analysis for the detected bacterial communities (genus level) in

Fig. 1 .

 1 Fig. 1. Sample location map (top left) and aerial photograph (top right) of the seven tailings sites (T_3Y to T_31Y) close to Hechi city (• shown on map), Guangxi (China), where the surface samples ( on aerial photo) were collected for the present study. Field photographs of tailing sample sites are shown in the bottom panels (T_3Y to T_31Y). As an example, T_3Y corresponds to the tailing sample code. T_3Y means the tailing samples were taken from a three years old abandoned site (not-used).

Fig. 2 .

 2 Fig. 2. Relative abundance of bacterial communities at phylum level in the seven abandoned tailings sites. Relative abundance of Alpha-, Beta-, Gamma-, Delta-Proteobacteria-related and Actinobacteria classes are shown in the map inset.

Fig. 3 .

 3 Fig. 3. (A) Non-metric multidimensional scaling (NMDS) analysis of bacterial communities in seven tailings sites at genus level. (B) Distancebased redundancy analysis (db-RDA) of genus and selected geochemical factors in seven tailings sites. Both NMDS and db-RDA analysis were based on the weighted normalized unifrac distance algorithms. Direction and magnitude of arrows indicate the correlation of geochemical factors and genera.

Fig. 4 .Fig. 6

 46 Fig. 4. (A) Network analysis for the detected bacterial communities (genus level) in different tailings sites. Color was coded by tailings sites. Each node indicates one genus. Colors of node represent the different major phyla. The size the species-node denotes abundance of species. Black nodes represented the no_rank/un-classified genera which were shared by tailings sites. Light green nodes represented the no_rank/unclassified genera, which were specific in different tailings sites. The degree of node was assessed by the numbers of nodes connected directly to that node. The more lines on the node denotes the higher degree of correlation between the sites and other genera. (B) The sub-network analysis for modularity of genera. Colors of node represent the different module. Node size is proportional to the modularity class. The nodes without labels represented the no_rank/un-classified genera. B. P., Burkholderia-Paraburkholderia

  pH + TOC + TP + T-As + H-Cr 0.957 pH + TOC + TP + T-As + T-Zn + H-Cr 0.979 pH + TOC + TP + T-As + T-Zn + H-Cr + H-Cu 0.975 pH + TOC + TP + T-As + T-Zn + H-As + H-Cr + H-Cu 0.964 pH + TOC + TN + TP + T-Cd + T-Zn + H-Cr + H-Cu + H-Pb 0.946 pH + TOC + TN + TP + T-Cd + T-Zn + H-As + H-Cr + H-Cu + H-Pb 0.943 pH + TOC + TP + T-Cd + T-Cr + T-Cu + T-Zn + H-As + H-Cr + H-Cu + H-Pb 0.946 pH + TOC + TN + TP + T-As + T-Cd + T-Sb + T-Zn + H-As + H-Cr + H-Cu + H-Pb 0.921 pH + TOC + TN + TP + T-As + T-Cd + T-Cu + T-Zn + H-As + H-Cr + H-Cu + H-Pb + H-Zn 0.900 pH + TOC + TN + TP + T-As + T-Cd + T-Cr + T-Cu + T-Pb + T-Zn + H-As + H-Cr + H-Cu + H-Pb 0.875 pH + TOC + TN + TP + T-As + T-Cd + T-Cr + T-Cu + T-Sb + T-Zn + H-As + H-Cr + H-Cu + H-Pb + H-Sb 0.846 pH + TOC + TN + TP + T-As + T-Cd + T-Cr + T-Cu + T-Pb + T-Zn + H-As + H-Cr + H-Cu + H-Pb + H-Sb + H-Zn 0.800 pH + TOC + TN + TP + T-As + T-Cd + T-Cr + T-Cu + T-Pb + T-Sb + T-Zn + H-As + H-Cu + H-Cr + H-Pb + H-Sb + H-Zn 0.750 pH + TOC + TN + TP + T-As + T-Cd + T-Cr + T-Cu + T-Pb + T-Sb + T-Zn + H-As + H-Cd + H-Cr + H-Cu + H-Sb + H-Zn + H-Pb 0.646 Resulting values were weighted Spearman rank correlation coefficients (r).

Table 1

 1 Spearman correlation analysis for geochemical factor variables and a-diversity index (p < 0.05).

	Variables used	Correlated variables
	in analysis	|rho|>0.75	rho	p-value
	TOC	H-Cr	0.786 *	0.036
	T-As	T-Cd	0.786 *	0.036
		T-Cr	-0.821 *	0.023
		T-Zn	0.857 *	0.014
	T-Cd	T-Cu	0.786 *	0.036
		T-Zn	0.929 **	0.003
		H-Cr	-0.893 **	0.007
	T-Pb	H-Cd	0.821 *	0.023
		H-Pb	0.821 *	0.023
	T-Zn	H-Cr	-0.893 **	0.007
	H-Cd	H-Cu	0.929 **	0.003
		H-Zn	0.929 **	0.003
	H-Cu	H-Zn	0.929 **	0.003
	ace	PD	0.964**	0.0004
	PD	TP	-0.786*	0.036
	TOC, total organic carbon; TN, total nitrogen; TP, total phosphorus; T-(metal), total content of
	metal(loid)s; H-(metal), the acid extraction of metal(loid)s; ace, microbial richness; PD,
	phylogenetic diversity; rho, Spearman coefficient of product-moment correlation

Table 2

 2

Table S1 . Types of tail sand for mining and smelting industries and geochemical factors of the studied tailings sites.

 S1

			T_3Y		T_4Y	T_6Y		T_8Y	T_15Y	T_23Y	T_31Y
	Mining activity	Sb		Pb-Zn	Sn		Pb-Zn	Sb	Pb-Zn	Sn
	pH		7.40 ± 0.05a		7.55 ± 0.30a	7.39 ± 0.05a	7.45 ± 0.35ab	7.44 ± 0.09a	6.44 ± 2.69ab	2.59 ± 0.07b
	TOC		973 ± 108ab		358 ± 139ab	1 Module 2 Module 3 449 ± 233ab 487 ± 378ab	864 ± 29.3ab	511 ± 209ab	629 ± 104ab
	TN TP T-As T-Cd T-Cr	T-As TOC + H-Pb 57.1 ± 15.8ab 169 ± 5.08c 17300 ± 1060ab 26.0 ± 1.67ab pH + TOC + H-Pb 12.7 ± 0.58ab		rM p 18.1 ± 6.46b rM 180 ± 61.6c p 11500 ± 6950ab rM 36.2 ± 23.0ab p 30.6 ± 11.2ab	0.51 0.07 74.1 ± 22.6a 0.32 1470 ± 677a 0.20 22700 ± 4010ab 0.84 46.8 ± 0.53ab 0.01 7.82 ± 0.81ab	0.29 0.28 37.6 ± 13.3ab 0.54 0.10 0.58 205 ± 10.7c 0.59 0.03 20700 ± 4010ab 0.07 0.33 0.26 32.0 ± 17.3ab 0.11 0.19 19.4 ± 12.0ab	64.6 ± 23.4ab 343 ± 111bc 14600 ± 2820ab 19.9 ± 2.41ab 15.1 ± 1.60ab	48.5 ± 6.46ab 145 ± 80.1c 55700 ± 39400ab 53.7 ± 21.0ab 8.12 ± 3.91ab	62.2 ± 23.5ab 1119 ± 333ab 8313 ± 864ab 11.9 ± 7.78ab 24.8 ± 16.8ab
	T-Cu	TOC + H-Pb + T-As 134 ± 35.2ab		rM 290 ± 272ab	0.37 203 ± 25.2ab	0.53	0.62 225 ± 46.3ab	76.0 ± 6.92ab	343 ± 191ab	155 ± 110ab
	T-Pb		407 ± 71.3ab		p 384 ± 254ab	0.16 4270 ± 358ab	0.06 7100 ± 4600ab 0.08	266 ± 23.2ab	5940 ± 920ab	435 ± 225ab
	T-Sb	pH + TOC + H-Pb + T-As 378 ± 33.1ab		rM 1830 ± 625ab	0.80 3550 ± 192ab	0.37 6980 ± 450ab 0.48	775 ± 142ab	4920 ± 758ab	412 ± 248ab
	T-Zn		2280 ± 60.2ab		p 3770 ± 2270ab	0.01 5370 ± 149ab	0.10 3890 ± 1860ab 0.13	1840 ± 215ab	5180 ± 2691ab	630 ± 62.8ab
	H-As H-Cd	TOC + H-Pb + T-As + H-Sb 0.115 ± 0.08ab 0.009 ± 0.007b	rM p 0.40 ± 0.21ab 0.011 ± 0.01b	0.27 0.23 0.303 ± 0.05ab 0.041 ± 0.004b	0.69 0.08 0.963 ± 0.70ab 0.51 0.13 0.141 ± 0.06a	0.540 ± 0.01ab 0.007 ± 0.005b	7.31 ± 1.21ab 0.021 ± 0.02ab	29.3 ± 3.25ab 0.092 ± 0.08ab
	H-Cr		0.004 ± 0.003ab		0.002 ± 0.001b	0.002 ± 0.0004b	0.004 ± 0.003ab	0.009 ± 0.006ab	0.003 ± 0.002ab	0.05 ± 0.04a
	H-Cu		0.008 ± 0.006b		0.011 ± 0.01b	0.08 ± 0.008b		0.28 ± 0.20b	0.010 ± 0.009b	0.053 ± 0.009b	1.00 ± 0.516a
	H-Pb		0.006 ± 0.0003ab	0.0004 ± 0.002ab	0.023 ± 0.002ab	0.084 ± 0.08ab	0.01 ± 0.009ab	0.893 ± 0.154ab	0.035 ± 0.014ab
	H-Sb		0.41 ± 0.35ab		1.85 ± 1.19ab	0.23 ± 0.10ab	0.407 ± 0.32ab	0.70 ± 0.18ab	0.613 ± 0.41ab	0.084 ± 0.05ab
	H-Zn		0.71 ± 0.58ab		2.32 ± 1.68ab	2.78 ± 0.66ab	7.63 ± 5.61ab	0.45 ± 0.21ab	1.31 ± 0.16ab	7.70 ± 0.84ab

Table S3 . Average OTU distribution for 16S rDNA sequences in each tailing site

 S3 . T_3Y, T_4Y, T_6Y, T_8Y, T_15Y, T_23Y and T_31Y represent different tailing sites with different ages of abandonment. The table has been listed as a separate worksheet file.

	Sample ID	Seq_num	Mean_lengt	Shannon	ace	coverage	PD	NSTI
	T_3Y	36309	h 440	2.88	601	0.998	45.5	0.34
	T_4Y	41493	444	3.67	621	0.999	51.2	0.12
	T_6Y	44161	438	4.67	678	0.999	58.6	0.18
	T_8Y	37562	439	4.43	571	0.997	43.7	0.17
	T_15Y	37001	438	4.80	598	0.999	47.7	0.17
	T_23Y	33465	445	3.12	255	0.997	25.9	0.07
	T_31Y	35496	445	3.37	794	0.998	60.8	0.18
	Seq_num, the sequences number for each tailing site; Mean_length, the average length of
	sequences; NSTI, nearest sequenced taxon index. Four α-diversity indices (Shannon, ace,
	PD, and coverage) are shown to estimate bacterial community diversity, richness,
	phylogenetic diversity, and community coverage. The analysis for bacterial communities in
	seven tailings sites at OTU level were based on 97% similarity. Data points for T_3Y,
	T_4Y, T_6Y, T_8Y, T_15Y, T_23Y, and T_31Y represent tailings sites having 3, 4, 6, 8,
	15, 23, and 31 years of abandonment, respectively.

Table S5 . Relative abundance (%) of predicted KEGG pathways at studied tailing sites, based on 16S rRNA sequencing.

 S5 The top fifty metabolic pathways of KEGG subsytems (at level 3) are shown.

		Oxidative phosphorylation	0.01	0.02	0.02	0.02	0.02	0.01	0.02
		Peptidases	0.01	0.02	0.01	0.01	0.02	0.02	0.02
		Pyrimidine metabolism	0.01	0.02	0.01	0.01	0.01	0.01	0.01
		Amino acid related enzymes	0.01	0.01	0.01	0.01	0.01	0.01	0.01
	Metabolism pathway on level 1 Metabolism pathway on level 3 Arginine and proline metabolism Bacterial motility proteins Pyruvate metabolism Cellular Processes Flagellar assembly Methane metabolism Butanoate metabolism	0.01 T_3Y T_4Y T_6Y T_8Y T_15Y T_23Y T_31Y 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
	Environmental Information	Transporters Carbon fixation pathways in prokaryotes	0.03 0.01	0.06 0.01	0.05 0.01	0.05 0.01	0.04 0.01	0.05 0.01	0.04 0.01
	Processing	ABC transporters Glycolysis / Gluconeogenesis	0.02 0.01	0.03 0.01	0.03 0.01	0.03 0.01	0.03 0.01	0.03 0.01	0.02 0.01
		Two-component system Propanoate metabolism	0.01 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.02 0.01
		Secretion system Amino sugar and nucleotide sugar metabolism Other ion-coupled transporters Porphyrin and chlorophyll metabolism Alanine, aspartate and glutamate metabolism	0.01 0.01 0.01 0.01 0.01	0.02 0.01 0.01 0.01 0.01	0.02 0.01 0.01 0.01 0.01	0.02 0.01 0.01 0.01 0.01	0.02 0.01 0.01 0.01 0.01	0.02 0.01 0.01 0.01 0.01	0.01 0.02 0.01 0.01 0.01
		Bacterial secretion system Valine, leucine and isoleucine degradation	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.00
	Genetic Information Processing	DNA repair and recombination proteins Citrate cycle (TCA cycle)	0.02 0.01	0.03 0.01	0.03 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.03 0.01
		Ribosome Lipid biosynthesis proteins	0.01 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.02 0.01	0.02 0.01
		Chromosome Glycine, serine and threonine metabolism Transcription factors Energy metabolism Fatty acid metabolism	0.01 0.01 0.01 0.01 0.01	0.02 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.02 0.01 0.01	0.01 0.02 0.01 0.01 0.00
		Ribosome Biogenesis Glyoxylate and dicarboxylate metabolism	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01
		Aminoacyl-tRNA biosynthesis Cysteine and methionine metabolism	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01
		Chaperones and folding catalysts Valine, leucine and isoleucine biosynthesis	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01	0.01 0.01
		Transcription machinery Nitrogen metabolism DNA replication proteins Phenylalanine, tyrosine and tryptophan biosynthesis Peptidoglycan biosynthesis	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01	0.01 0.01 0.01 0.01 0.01
	Poorly characterized	Protein folding and associated processing General function prediction only	0.01 0.02	0.01 0.04	0.01 0.04	0.01 0.04	0.01 0.03	0.01 0.03	0.01 0.03
		Translation proteins Function unknown	0.01 0.01	0.01 0.02	0.01 0.02	0.01 0.02	0.01 0.02	0.01 0.02	0.01 0.02
	Others	Homologous recombination	0.01 0.56	0.01 0.35	0.01 0.36	0.01 0.36	0.01 0.37	0.01 0.37	0.01 0.36
		Replication, recombination and repair proteins	0.01	0.01	0.01	0.01	0.01	0.01	0.01
	metabolism	Purine metabolism	0.01	0.02	0.02	0.02	0.02	0.02	0.02

60

Table

Acknowledgments

This work was funded by the International Key Project from National Natural Science Foundation of China (41720104007), and Projects of Natural Science Foundation of China (41573080, U1402234, 41711530030, 41711530150, 41711530224), Public welfare project of Chinese Ministry of Environmental Protection (201509049), International key project of Ministry of Science and Technology of China (S2016G2135), and Fundamental Research Funds for the Central Universities (FRF-OT-16-025). We also acknowledge the support of the Centre National de la Recherche Scientifique (CNRS PRC1416, France), a Royal Society Newton Mobility Grant (IE161198), and National Natural Science Foundation International Joint collaboration China-Sweden (41430106).

Appendix A. Supporting information

Supplementary data related to this article can be found at the website of Environmental Pollution.

Supporting Information

Bacterial diversity in typical abandoned multi-contaminated nonferrous metal(loid) tailings during natural attenuation

Genetic Information Processing

Replication, recombination and repair proteins - Contrib, the contribution of each genus to the differences of bacterial communities of tailings sites. "-", there was no contribution to the the differences between different 66 metabolic pathways of tailings sites.


Jérôme Long

Aleksei O Tolpygin

Anton V Cherkasov

Konstantin A Lyssenko

Yannick Guari

Joulia Larionova

Alexander A Trifonov

Investigation of the Slow Relaxation of the Magnetization Dynamics in Homoleptic Ene-Diamido Organodysprosium(III) Complexes with K + /Arene Interactions

We report the synthesis, structure and magnetic investigations of two new Dy 3+ homoleptic ate-complexes based on different ene-diamido ligands [K(THF)2][Dy(DAD 2R )2] (R = H (1), Me (2) DAD 2R = [2,6-iPr2C6H3N-CR=CR-NC6H3iPr2-2,6 showing K + /Arene interactions. Magnetic investigations reval that both compounds exhibit a zero-field Single-Molecule Magnetic relaxation mainly governed by a Raman process.

Introduction

The ability of some mononuclear lanthanide complexes to exhibit slow relaxation of their magnetization possibly associated with magnetic bistability at the molecular scale opens exciting avenues for the information storage or spinbased computing. [1][2][3][4] In these so-called Single-Molecule Magnets (SMMs), the optimum balance between the specific 4f electronic density of defined lanthanide ions with the coordinated ligands engenders a crystal-field splitting which could lead to the appearance of an anisotropic barrier, , separating opposite orientations (± m J ) of the magnetic moments. [5][6][START_REF] Tang | Lanthanide Single Molecule Magnets[END_REF][START_REF] Layfield | Lanthanides and Actinides in Molecular Magnetism[END_REF] It is generally recognized that in efficient genuine SMMs, the energy barrier should be as large as possible and the retention of the magnetization (with hysteresis effect) should be achieved in zero magnetic field below a blocking temperature, which should be the highest possible. [START_REF] Giansiracusa | [END_REF] The theoretical modelling predicted, some years ago, that the most efficient strategy to fulfill such objectives consists in stabilizing the oblate electronic density of Dy 3+ ion by an axial crystal-field generated by the presence of two negatively charged ligands along an axis with short bond lengths and no coordinated species in the equatorial plane. 5, 10 This targeted environment permits to maximize the crystal-field splitting when a suitable symmetry is achieved. Such approach has been nicely demonstrated in both, coordination complexes [11][12][13][14][15][16][17][18] and organometallic metallocene complexes [19][20] with magnetic hysteresis observed up to 80 K. 21 Yet, these studies point out that additional processes, such as the Quantum Tunnelling of the Magnetization (QTM), as well as Raman and direct relaxations, may greatly complicate the overall relaxation mechanism by creating underbarrier pathways, reducing the SMMs hallmarks. [22][23] For instance, the exceptional magnetic performances of dysprosium metallocence family could be ascribed, not only to the tailored coordination environment, but also to the reduced molecular vibrations (vibrational modes) imposed by the rigid cyclopentadienyl ligands. 20-21, 23-25 It appears therefore critical, with the aim to ultimately optimize the SMMs, to gain deeper insights on the parameters affecting such spin-phonon coupling. Following this idea, we have recently investigated the use of diazabutadiene ligands for the design of lanthanide SMMs. [26][27] These doubly negatively charged ligands could act both, as n and -electron donors, while benefiting from a great tunability with respect to their steric and electronic features. -2,6], Cp* = C 5 Me 5 ) were also designed by associating DAD-type ligands providing short Dy-N distances with a rigid Cp* moiety. 28 However, in the previous examples, an additional ligand (Cl or THF) was coordinated in the equatorial plane that in turn decreases the axiality.

Encouraged by these results, we continued to explore the potential of the DAD ligands. We report here, the synthesis, structure and magnetic investigations of two cationic homoleptic complexes of Dy 3+ based on distinct dianionic DAD ligands with unusual K + /arene interactions and exhibiting a zero-field SMM behaviour. Remarkably, although the nature of the substituent on the DAD ligand and counter-ion directly affects the Dy 3+ coordination sphere, the magnetization is found to relax mainlt via a Raman process.

Experimental

Materials and Methods

General Procedures

All operations were carried out under an atmosphere of argon

X-Ray crystallography

The X-ray data for 1 and 2 were collected with Bruker Smart Apex II (1) and Rigaku OD Xcalibur (2) diffractometers (Mo Kαradiation, ω-scans technique, λ = 0.71073 Å) using APEX3 [START_REF] Bruker | APEX 3 and SAINT[END_REF] and CrysAlis Pro [START_REF] Crysalis | Agilent Technologies[END_REF] software packages. The structures were solved by direct methods and were refined by full-matrix least squares on F 2 for all data using SHELX. [START_REF] Sheldrick | [END_REF] SADABS 35 and SCALE3

ABSPACK scaling algorithm implemented in CrysAlis Pro were used to perform absorption corrections. All non-hydrogen atoms in 1 and 2 and hydrogen atoms of NCCN fragments in 1 were found from Fourier syntheses of electron density (all non-hydrogen atoms were refined anisotropically). All other hydrogen atoms were placed in calculated positions and were refined in the "riding" model with U(H) iso = 1.2U eq of their parent atoms (U(H) iso = 1.5U eq for methyl groups). Disordered fragments in both structures were restrained using AFIX, DFIX, SADI and FLAT instructions. Displacement parameters of nonhydrogen atoms of disordered fragments in 1 and all nonhydrogen atoms in 2 were restrained using RIGU instruction. The crystallographic data and structures refinement details are given in Table S1. CCDC-1994537 (1) and 1994538 (2) contains the supplementary crystallographic data for this paper. These data are provided free of charge by The Cambridge Crystallographic Data Centre: ccdc.cam.ac.uk/structures. The corresponding CIF files are also available in the Supporting Information.

Magnetic Measurements

Magnetic susceptibility data were collected with a Quantum Design MPMS-XL SQUID magnetometer working in the range 1.8-300 K with the magnetic field up to 7 Tesla. The samples were prepared in a glove box. The data were corrected for the sample holder and the diamagnetic contributions calculated from the Pascal's constants. The AC magnetic susceptibility measurements were carried out in the presence of a 3 Oe oscillating field in zero or applied external DC field.

Results and Discussions

Synthesis and crystal structures

The synthetic strategy to design the targeted homoleptic atecomplexes relies on the salt metathesis reactions of anhydrous After recrystallization from a THF/hexane mixture, complexes 1 and 2 were isolated as orange crystals in 62 and 68% yields, respectively. The X-ray diffraction study revealed that the homoleptic complexes crystallize in the triclinic (1) and monoclinic P2 1 /n (2) space groups, respectively, with one molecule of atecomplex in the asymmetric unit (Fig. 1, Table S1). The Dy 1). The nature of the substituents by the imino carbons in the NCCN fragment affects the angle defined by the Dy 3+ ion and the NCCN centroids of each DAD ligands ranging from 164.5 (complex 1) to 177.5° (complex 2) (Table 1). The shortest intermolecular Dy-Dy distances found by the analysis of the crystal packing (Fig. S1) are equal to 10.196 (7) and 10.947(7) Å for 1 and 2, respectively, indicating that the complexes are relatively well isolated.

Magnetic Properties

The magnetic properties were investigated in both, static and dynamic modes by using a SQUID MPMS-XL. The room temperature T values of 13.12, and 13.42 cm 3 .K.mol 1 for 1 and 2, respectively, are slightly lower than the value of 14.17 cm 3 .K.mol 1 , expected for a unique Dy 3+ ion using the free-ion approximation (Fig. 2). These lower experimental T values may be rationalized by a significant crystal-field splitting. Upon cooling, both samples exhibit a similar decrease of T due to the thermal depopulation of the Stark sub-levels, while the field dependence of the magnetization at 1.8 K reveals the typical unsaturated curves with the values of 5.81 and 4.90 N under 70 kOe for 1 and 2, respectively (Fig. 2). A clear opening in the hysteresis loops could be observed at low temperature for both compounds (Fig. S2), suggesting the occurrence of a slow relaxation of the magnetization. This was further confirmed by using alternate currents (ac) measurements to study the relaxation dynamics. Both samples exhibit a clear frequency dependence of the in-phase (') and out-of-phase (") components of the magnetic susceptibility (Fig. 3, Fig. S3-S4) indicating a SMM behavior. While for 1, a single frequency dependent peak could be observed, 2 exhibits a broad peak at low temperature with the appearance of a plateau at high frequency upon increasing temperatures.

Noticeably, such broad signals of " have also been observed in heteroleptic dysprosium DAD 2Me /Cp* complexes with the same DAD 2Me ligand. 28 The corresponding Cole-Cole plots for 1 and 2 (Fig. 4) could be fitted with a generalized Debye model (Tables S2-S3), but this treatment gives large values for the  parameter, especially for 2 (about 0.4) indicating a large distribution of the relaxation times. 38 This could result in large uncertainties in the determination of the relaxation time, .

Consequently, the program CC-FIT2, recently developed by Reta and Chilton, 39 was utilized to extract the values and the corresponding uncertainties from the underlying distribution function. QTM (Eq. 1), 40 for which the first term accounts for a thermally activated process, while the second and third ones stand for two-phonon Raman and QTM, respectively. This however leads to small  barriers and/or large uncertainties (Table S4), suggesting that, as previously observed for 3, the thermally activated Orbach process is not dominant or even not involved in the relaxation. 27 Consequently, the temperature dependence of the relaxation time was fitted with only a combination of Raman and QTM:

 1 = CT n +  1
QTM (Eq. 2). The best fit parameters could be found in Table 2. Despite the nice apparent fittings for all compounds (Fig. 5), the large uncertainties on the fit parameters obtained from the CC-FIT2 software suggest that such analysis could only be considered as qualitative. For comparison, the fitting parameters by considering solely the extracted  values (without taking into account the distribution of relaxation times) could be found in Table S5. For all compounds, the relaxation time becomes temperature independent at low temperature pointing out a significant QTM that could be shortcut by applying a dc magnetic field. Thus, the field dependence of the ac susceptibilities was monitored (Fig. S6, for 3 please refer to ref. 27 ). For 2, a second relaxation process could be discerned at high frequency upon applying dc fields but without a maximum.

Compound

n C (s 1 .K m ) QTM (s) 1 (0 Oe) 5(2) 10 3(3) 10 2.8(3)
1 (1000 Oe) 4.8(3) 10 3.0(4) -2 (0 Oe) 4(7) 10 1(9) 10 3.1 (5) 3 (0 Oe) 4(2) 10 1(2) 10 2.9 (2) 3 (3500 Oe) 4.8(7) 10 2.9(8) -Fig. 5. Temperature dependence of the relaxation time, , for 1-3. The uncertainties were determined from the CC-FIT2 software 39 while the solid magenta lines correspond to the fit with Eq. 2.

The corresponding field dependences of the relaxation time can be modelled with the equation,  1 = DH 4 T + B 1 /(1+B 2 H²) + K (Eq. 3), for which the first term accounts for the direct process (for Kramers-ion), the second one for the QTM, while the K constant accounts for Raman and thermally activated processes (Fig. S7, Table S6). The optimum field for which the relaxation time is the greatest is estimated at 1000 Oe and 2000 Oe for 1 and 2, respectively. The ac susceptibilities measured under these fields (Fig. S8) corroborates the decrease of the QTM contribution, while the corresponding Cole-Cole plots (Fig. S9, Tables S7-S8) unambiguously confirm the occurrence of a second relaxation process for 2. These Cole-Cole plots were therefore fitted with a generalized Debye model and with a sum of two modified Debye functions 38 for 1 and 2, respectively. Noticeably, a strong decrease in the  parameter values for 1 (< 0.05) is observed, indicating that the magnetic field causes a dramatic effect on the distribution of the relaxation times. Thus, a pertinent fitting of the temperature dependence of the relaxation time could be achieved for 1 and 3 using CC-FIT2 and by considering solely a Raman process,  1 = CT n (Table 2, Fig. 6 andS10), taken into account that the direct process should be inoperative for such weak values of the magnetic field. Remarkably, the obtained parameters are comparable with those obtained in zero dc fields (Table 2), but the associated small uncertainties indicate that, this in-field analysis for 1 and 3 could be considered as quantitative. Nevertheless, it was not possible to obtain a relevant fit with realistic parameters for 2, which could be ascribed to the presence of two relaxations. Hence, the comparison between 1 and 3 for the in-field data clearly shows almost identical (within the standard deviation) n and C parameters. These parameters are however found slightly altered without considering the distribution of relaxation times (Table S5). Nevertheless the superposition on the  vs. T plot for all compounds shows that they obviously follow the same trend (Fig. S10).

Magneto-structural correlations

At the exception of the large distribution of relaxation times for 2, the magnetic analysis indicates therefore a comparable behaviour of the slow relaxation of the magnetization in 1-3 despite the slightly different structures. To get further insights, the orientation of the anisotropic axes of the ground Kramers doublets was evaluated by using the MAGELLAN software. 41 A negative charge on each nitrogen atom of the DAD ligand was considered. For 1, the anisotropic axis does not pass through the center of the two DAD 2H ligands but is almost collinear (deviation of 16 and 18°) to the N2-Dy-N4 string (Fig. S11). The distance Dy-N2 is the second shortest one and is equal to 2.248(2) Å, while the Dy-N4 is longer 2.268(2) Å. However, the N2-Dy-N4 angle of 152.85° is closer to the linearity than any other N-Dy-N angles ranging from 109-119°. This may explain the deviation of the anisotropic axis with respect to the barycenter of the DAD 2H ligand. Moreover, the electrostatic influence of the K + ion most likely impacts the orientation of the anisotropic axis. In comparison, the anisotropic axis in complex 3 obtained with the same ligand, but with an uncoordinated Li + ion, passes through the middle of each DAD ligand (Fig. S11). This could be rationalized by the fact that the complex 3 is rather symmetrical regarding the two DAD 2H ligands and the N-Dy-N angles strongly deviate from linearity (ranging from 120 and 139°). 27 Consequently, it appears that the K + /arene interaction results in the alteration of the DAD ligands repartition in the coordination sphere of the Dy 3+ ion.

Similarly than for 3, the N1-Dy-N4 and N2-Dy-N3 angles in 2 are comparable and equal to 126 and 129°. In that case, the anisotropic axis is found to pass roughly through the barycentre of each DAD 2Me ligands (Fig. S11) which could be explained by a lesser electrostatic influence of the K + ion caused by a greater Dy 3+ -K+ distance.

It appears that in these homoleptic complexes, the magnetic relaxation is dominated by the Raman process, which clearly shortcut the Orbach relaxation, despite a noticeable crystal-field splitting. 27 Determining the influence of the Raman relaxation is relatively complex since this process is known to depend on numerous parameters, such as the crystal density, the speed of sound in the solid and the strength of spin-phonon interactions. 42 Recently, the decisive role of vibrational modes on the Raman parameters has been evidenced. 9, 20, 22-23, 25, 43 1 and 2 differ only by the nature of the substituent on the DAD ligand (H vs. Me). In contrast, 1 and 3 are based on the same ligand, but diverge by the nature of the counter-ion and its coordination mode. Hence, the comparable behaviours observed in our series suggest that: i) the K + /arene interactions appear to unsuccessfully rigidify the structure and therefore does not shortcut the Raman relaxation; ii) introduction of methyl substituents on the DAD ligands does not alter specifically also the Raman relaxation. Consequently, this implies that, in this series based on the DAD ligands, the Raman process seems to be mainly controlled by vibrational modes in the close vicinity of the Dy 3+ ion and most likely involves metal-ligand modes.

Analyzing the exact effect of the K + -arene interactions over the slow relaxation is however far to be unequivocal due to very subtle structural effects and the predominance of the Raman relaxation. Yet, the possibility to alter the coordination sphere of the Dy 3+ ion and in turn the orientation of the anisotropic axis through the electrostatic influence of the K + ion may provide new synthetic strategies to design high energy barriers SMMs involving a thermally activated relaxation.

Conclusions

In summary, we have reported here two new homoleptic Dy 3+ complexes based on DAD ligands bearing different substitution groups and involving K + /arene interactions. Both compounds exhibit a zero-field slow relaxation of the magnetization arising from a SMM behaviour. Although they differ by the nature of the substituent (H vs. Me) on the DAD ligands, both compounds exhibit comparable slow relaxation of the magnetization dynamics despite the observed changes in the Dy-N distances and the N-Dy-N sequence. In addition to the role of the substituent, the presence of K + /arene interactions provides also a route to tune the coordination environment of the Dy 3+ ion. Detailed magnetic analysis indicates that, in this series, the magnetic relaxation is governed by a Raman process, which only depends on molecular vibrations in the close vicinity of the Dy 3+ ion. This confirms that the in-depth understanding of the parameters affecting the Raman relaxation would be the key to improve the SMM features and achieve a high-temperature magnetic bistability.

Scheme 1 .

 1 Scheme 1. Synthesis of complexes 1 and 2.

- 1 :

 1 1914 (w), 1882 (w), 1835 (w), 1786 (w), 1645 (s), 1583 (s), 1560 (m), 1425 (s), 1362 (s), 1337 (s), 1254 (s), 1204 (s), 1156 (c), 1138 (s), 1111 (s), 1049 (s), 936 (s), 887 (s), 863 (s), 818 (s), 799 (m), 789 (m), 775 (s), 758 (s), 744 (s).

Fig. 1 .

 1 Fig. 1. Molecular structure of 1 and 2 and 3. 27 Color code: orange, Dy; red, O; grey, C; purple, K. Hydrogen atoms and Li + ion (for 3) have been omitted for clarity.

  DyCl 3 with two-fold amounts of [K(THF) n ][DAD 2R ] (R = H, Me), in situ prepared from DAD 2R and potassium shavings and giving [K(THF) 2 ][Dy(DAD 2R ) 2 ] (X = H (1), Me (2)) (Scheme 1). The reactions were carried out at 25 °C in THF solution within 24 h.

2 - 2 - 4 -

 224 3+ cation presents a comparable lanthanide coordination environment, reminiscent to the recently described [Li(DME) 3 ][Dy(DAD 2H ) 2 ] (3) complex. 27 It simply consists of two 2σ:η coordinated dianionic DAD ligands, the overall negative charge being compensated by a coordinated potassium ion in proximity with the Dy 3+ , the shortest Dy 3+ -K + distances being equal to 3.6548(8) and 4.6851(7) Å for 1 and 2, respectively. The K + cation interacts with one phenyl ring of each DAD ligand and completes its coordination sphere with two THF molecules. It is worthy of note that the two K•••Ar centre (Ar for aryl substituent of DAD) distances in 1 are equal to 3.5071(9) and 4.0800(9) Å) and are much longer compared to those found in 2 (2.978(8) and 3.26(2) Å). Accordingly, different types of coordination of aryl substituents to potassium ion are observed in these complexes. Thus in 1, the K + is η coordinated by one aryl fragment resulting in short K•••C distances of 3.071(2), 3.135(2) Å, while only one K•••C short contact (3.249(2) Å) is observed for the second phenyl ring (K•••C distances > 3.5 Å are declared as not bonding). 36-37 In 2, the potassium ion is η coordinated by one aryl fragment (3.175(2)-3.445(2) Å), whereas the interaction with the second one can be classified rather as η 6 (K•••C: 3.175(2)-3.450(2) Å). The Dy-N distances are in the ranges 2.239(2)-2.268(2) Å in 1 and 2.231(2)-2.259(2) Å in 2 (Table 1

6 Fig. 2 : 1 and 2 .

 6212 Fig. 2: Temperature dependence of T under an applied magnetic field of 1000 Oe for 1 and 2. Inset: field dependence of the magnetization at 1.8 K for 1 and 2.

Fig. 3 . 1 and 2

 312 Fig. 3. Frequency dependence of the out-of-phase susceptibility component, ", for 1 and 2 under a zero dc-field.

Fig. 4 .

 4 Fig. 4. Cole-Cole (Argand) plots obtained using the ac susceptibility data for 1 and 2 (0 Oe). The solid lines correspond to the best fit obtained with a Debye model.

Fig. 6 .

 6 Fig. 6. Temperature dependence of the relaxation time for 1-3 using the ac susceptibility data in the presence of a dc field. The solid lines represent the fit with a Raman process.

Synthesis of [K(THF) 2 ][Dy(2,6-iPr 2 C 6 H 3 NCHCHNC 6 H 3 iPr 2 -2,6) 2 ] (1).

	using Schlenk techniques or in a nitrogen filled glovebox. THF
	and	toluene	were	purified	by	distillation	from
	sodium/benzophenone ketyl and degassed thoroughly. Hexane
	was dried by distillation from sodium/triglyme and
	29 and DAD benzophenone ketyl prior to use. DyCl 3 , iPrC 6 H 3 -NC(R)C(R)NC 6 H 3 iPr-2,6) 30 (R = H, Me) were prepared 2R (2,6-
	according to literature procedures. Lanthanide metal analysis
	was carried out by complexometric titration.	31 IR spectra were
	recorded as Nujol mulls on a Bruker-Vertex 70
	spectrophotometer. Elemental analysis was performed in the
	microanalytical laboratory of IOMC.
	A solution of K 2 (THF) n [2,6-iPr 2 C 6 H 3 NCHCHNC 6 H 3 iPr 2 -2,6] in situ
	prepared from 2,6-iPr 2 C 6 H 3 NCHCHNC 6 H 3 iPr 2 -2,6 (0.75 g, 1.99
	mmol) and K shavings (0.16 g, 3.98 mmol) in 30 mL of THF was
	slowly added to a suspension of DyCl 3 (0.27 g, 0.99 mmol) in 5
	mL of THF. The reaction mixture was stirred for 12 h at
	ambient temperature. The volatiles were removed in vacuum
	and the solid residue was extracted with toluene (40 mL). The
	toluene extract was filtered, toluene was removed in vacuum.
	Recrystallization of the resulting solid from THF/hexane
	mixture at 20 °C afforded orange crystals of 1 (0.68 g, 0.62
	mmol, 62% yield). Elemental analysis calcd. (%) for
	C 60 H 88 DyKN 4 O 2 (1098.96g•mol	-1 ): C, 65.57; H, 8.07; Dy, 14.79;
	N, 5.10; found (%): C, 65.78; H, 7.93; Dy, 14.90; N, 5.21. IR
	(Nujol, KBr) ν/cm	-1 : 1919 (w), 1855 (w), 1836 (w), 1794 (w),
	1628 (s), 1581 (s), 1563 (m), 1530 (s), 1429 (s), 1368 (s), 1334
	(s), 1309 (s), 1265 (s), 1224 (s), 1208 (s), 1178 (s), 1151 (m),
	1141 (m), 1107 (s), 1074 (s), 1050 (s), 1005 (s), 922 (s), 890 (s),
	871 (s), 819 (s), 796 (s), 770 (s), 760 (s), 744 (s).

Synthesis of [K(THF) 2 ][Dy(2,6-iPr 2 C 6 H3NCMeCMeNC 6 H 3 iPr2- 2,6) 2 ] (2).

  The reaction mixture was stirred for 12 h at ambient temperature. The volatiles were evaporated and the solid residue was extracted with toluene (40 mL). The toluene extract was filtered, toluene was removed in vacuum. Recrystallization of the resulting solid from THF/hexane mixture at 20 °C afforded orange crystals of 2 (0.78 g, 0.67 mmol, 68% yield). Elemental analysis calcd. (%) for C 64 H 96 DyKN 4 O 2 (1155.07g•mol -1 ): C, 66.55; H, 8.38; Dy, 14.07; N, 4.85; found (%): C, 66.81; H, 8.11; Dy, 14.00; N, 4.69. IR (Nujol, KBr) ν/cm

	A solution of K 2 (THF) n [2,6-iPr 2 C 6 H 3 NCMeCMeNC 6 H 3 iPr 2 -2,6] in
	situ prepared from 2,6-iPr 2 C 6 H 3 NCMeCMeNC 6 H 3 iPr 2 -2,6 (0.80
	g, 1.98 mmol) and K shavings (0.15 g, 3.95 mmol) in 30 mL of
	THF was slowly added to a suspension of DyCl 3 (0.27 g, 0.99
	mmol) in THF (5 mL) at room temperature.

Table 1 :

 1 Some structural parameters for compounds 1-3.

	Compound	Dy-N distances / Å	DAD-DyDAD Angle centroids / ° NCCN	Trans N-angles Dy-N	Ref.
		2.239(2)
	1	2.248(2) 2.266(2)	164.5	109.34(5) 152.85(5)	This work
		2.268(2)
		2.231(2)
	2	2.238(2) 2.248(2)	177.5	126.39(6) 128.78(6)	This work
		2.259(2)
		2.221(3)
	3	2.226(4) 2.246(3)	172.2	125.01(7) 138.27(7)	27
		2.256(3)

Table 2 :

 2 Fit parameters of the temperature dependence of the relaxation time for 1 and 2.

Acknowledgements

The financial support of the Russian Science Foundation is highly acknowledged (Project № 17-73-30036). The X-ray study of 2 has been carried out in the framework of the Russian state assignment using the equipment of The Analytical Center of IOMC RAS. The French authors thank the University of Montpellier, CNRS and PAC of ICGM.

Conflicts of Interest

There are no conflicts to declare.