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Effects of heavy metal ions on white clover (Trifolium repens L.) growth in Cd, Pb and Zn contaminated soils using zeolite

  • # These authors contributed equally: Vasilios Sotiriou, Georgios Michas

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  • According to the Greek Ministry of Environment, there are 2,000 contaminated sites in Greece. The agricultural production in these sites should be evaluated to provide an assessment and recommendations on the necessary actions required for crop sustainability. This study investigated the effects of heavy metals on White clover (Trifolium repens L.) growth in an above-referenced multi-metal contaminated site in the absence/presence of zeolite as an agent empowering the rehabilitation of pollution and immobilization of heavy metals. The addition of 1% zeolite to the polluted soils significantly contributed to plant growth by limiting the availability of Cd, Pb and Zn. However, the dry biomass of plants grown in the presence of zeolite was evaluated to be unsuitable as a raw material (feed) in livestock production, due to the high Cd toxicity. In the context of sustainable production, this study aims to holistically approach and evaluate mechanisms of phytoremediation, bioaccumulation and the disposal of the bioaccumulator as a high value-added product (feed).
  • Medium chain fatty acids (MCFAs) represent molecules with one carboxylic acid bound to a medium alkyl chain (C6-C10), constituting important food constituents and essential feedstocks of biofuels or oleo-chemical industries. Compared to their long-chain counterparts with a long alkyl chain (C12 or more), the shorter chain lengths confer MCFAs with significant characters such as higher carbon conversion yield and lower freezing/cloudy point, suggesting their potential as substitutes for fossil fuels[1,2]. Furthermore, MCFAs exhibit other unique physicochemical properties, for instance, little tendency to deposit as body fat, weight control benefits, antimicrobial effects, immune-modulating effects, and improving clinical symptoms, constituting their unique advantages as food constituents or even chemotherapeutic agents[3,4].

    Currently, natural source extraction or petrol-based synthesis are the main processes by which to obtain MCFAs. In nature, MCFAs present only in coconut and palm kernel with low concentrations, ranging from 7.9% to 15% of total fatty acids. Due to the seasonal/regional limitations, long breeding cycles and low concentrations, plant extraction is not amendable for industrialization[2,5,6]. Besides, the growing scarcity of fossil fuels and environmental anxiety of rising petrol-based manufacturing costs, and owing to food safety considerations, this manner is unfavorable in the food and pharmaceutical industries[1]. Accordingly, efficient, scalable and sustainable procedures to obtain MCFAs from cheap and renewable resources are required as an impetus towards MCFAs more widespread adoption.

    Numerous advantages inherent to microbial conversion procedures, for instances, rapid replication speeds, the capability of utilizing renewable feedstocks or acting during mile pressures and temperatures, and easy realization of large-scale fermentation[2,5,79], means it is an attractive alternative for fatty acid production. Previous pioneering studies have firstly demonstrated efficient MCFA production at 1.1−1.3 g/L via utilizing reversal of β-oxidation cycle (r-BOX) associate with leveraging thioesterases[1012]. A series of our studies achieved the highest titer (3.8−15.6 g/L) reported to date through identifying pathway bottlenecks[13], satisfying redox cofactor requirement[14], or constructing artificial micro-aerobic metabolism[15]. All of these results have illustrated that E. coli-based bioconversion so far presents a good chassis to produce MCFAs.

    Despite the apparent capability for microbial production of MCFAs, product toxicity is a common issue in strain engineering, which would result in physiological perturbations including reducing cell viability and membrane integrity, inducing membrane stress responses and losing proton motive force[1618]. One promising strategy to abate this problem is improving the transport speed of MCFAs from cells, and our previous study has demonstrated that expressing transporter from E. coli responsible for accelerating MCFA export could improve the production of MCFAs[19]. However, current secreting system is constructed based on the endogenous transporters derived from E. coli, which is inefficient and requires inducible promoters for conducting the transport function. This is still incompatible with large-scale production.

    The rapid buildup of genomic information has revealed that metabolic abilities of virtually all organisms are vastly underappreciated[20,21], and sequenced microbial genomes may contain numerous efflux pumps and offer a vastly unexplored resource for mining novel pumps. Here, in order to efficiently mine genomes during large genomic datasets, a multi-layer genome mining and phylogenomic analysis was developed to screen a library of uncharacterized heterologous pumps among over 2000 microbial genomes. This led to the identification of efficient efflux pump combination acrE and acrF from Citrobacter tructae. When combining with the quorum-sensing (QS) circuit from Enterococcus faecalis, MCFA efflux presented as an autonomous behavior without inducer supplementation or human supervision, and this achieved a 4.9-fold boost in MCFA production.

    E. coli JM109 and BL21 (DE3) were used for all molecular experiments and bio-catalysis, respectively. The plasmids of pACYCDuet-1, pCDFDuet-1, and pETDuet-1 (Novagen, Darmstadt, Germany) used in this study required the supplementation of 20 μg/mL of chloramphenicol, 40 μg/mL of streptomycin, 100 μg/mL of ampicillin, respectively, to maintain in the same cell. T4 DNA ligase, FastDigest restriction enzymes, and Phusion DHA polymerase (Novagen, Darmstadt, Germany) were employed to perform standard molecular manipulations. UV/vis spectrophotometer (UVmini-1240, Shimadzu, kyoto, Japan) was utilized to measure cell growth (OD600).

    Genomes for general phylogenomic analysis of MCFA transporter families such as AcrE, MdtE, and MdtC, were selected from 397 representative species of prokaryotic microorganisms. These genome assemblies, which were obtained from NCBI FTP site based on the screening parameters such as completeness (≥ 80%), contig numbers (cut-off ≤ 400), N50 (≥ 20,000 bases)[22], were annotated through Rapid Annotation using Subsystem Technology[23]. The blast database was created based on these annotated genome assemblies via the makeblastdb program in Linux, and the executing parameters were set as dbtype prot, and parse_seqids, respectively. The amino acid sequences of AcrE, MdtE, and MdtC from E. coli were utilized as queries for bioinformatics screening to predict target regions responsible for MCFA efflux within the constructed blast database associated with the parameters such as E-value cutoff of 1E-12 and bit score cutoff of 200. MUSCLE v3.8.31 was then used to align, trim and concatenate the obtained homologs[24], and IQ-TREE was utilized for phylogenomic reconstruction based on the resulting matrix[25]. During phylogenomic reconstruction, ModelFinder was used to identify the suitable model of substitution, and ultrafast bootstrap was set as 10,000 replicates.

    In order to comprehensively analyze transporter-centric phylogenies which contained the genomic context surrounding the target gene acrE, genomes deposited as Citrobacteria or Escherichia were retrieved from the NCBI FTP site with the appropriate filter parameters such as contig number (cut-off ≤ 400), N50 (≥ 20,000 bases), and completeness (≥ 80%), resulting in 797 genomes of Citrobacteria and 1,084 genomes of Escherichia. Based on this, the evolutionary relationships focusing on the genomic context encompassing acrE gene among different organisms were analyzed through CORASON[21,26] via retrieving gene neighborhood of acrE up to 20 genes upstream and downstream from genomes.

    Primers and plasmids utilized here are shown in Supplemental Tables S1 and S2, respectively. In order to clearly annotate each primer or gene, all the names of these genetic parts contained both abbreviated species and gene names. The plasmid of pCDFD-T7-bktB-T7-fadB-T7-ter-T7-ydiI-T7-acs, which was used for MCFA production, was derived from our previous study[19]. All the predicted efflux pumps were amplified from the genomic DNA prepared by Ezup Column Bacteria Genomic DNA Purification Kit (Sangon Biotech, Shanghai, China), or synthesized by GenScript (Nanjing, China). Primers Pf_PA-others(NdeI) and Pr_PA-others(XhoI), Pf_PA-mdtC(NdeI) and Pr_PA-mdtC(XhoI), Pf_SC-mdtC(NdeI) and Pr_SC-mdtC(XhoI), Pf_SE-mdtC(NdeI) and Pr_SE-mdtC(XhoI), Pf_SE-acrE(NdeI) and Pr_SE-acrE(XhoI), Pf_SE-acrA(NdeI) and Pr_SE-acrA(XhoI) were used to amplify other efflux RND transporter periplasmic adaptor subunit families of Pseudomonas aeruginosa, mdtC of Pseudomonas aeruginosa, mdtC of Streptomyces coelicolor, and mdtC of Salmonella enterica, acrE of Salmonella enterica, acrA of Salmonella enterica from corresponding genomic DNA into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-PA-others, pETD-PA-mdtC, pETD-SC-mdtC, pETD-SE-mdtC, pETD-SE-acrE, pETD-SE-acrA, respectively.

    Primers Pf_CTR-acrE(NdeI) and Pr_CTR-acrE(XhoI), Pf_CTR-acrA(NdeI) and Pr_CTR-acrA(XhoI), Pf_CTR-mdtE(NdeI) and Pr_CTR-mdtE(XhoI), Pf_CTE-acrE(NdeI) and Pr_CTE-acrE(XhoI), Pf_CTE-acrA(NdeI) and Pr_CTE-acrA(XhoI), Pf_ES-acrE(NdeI) and Pr_ES-acrE(XhoI), Pf_ES-acrA(NdeI) and Pr_ES-acrA(XhoI), Pf_BA-acrE(NdeI) and Pr_BA-acrE(XhoI), Pf_BA-acrA(NdeI) and Pr_BA-acrA(XhoI), Pf_CU-acrE(NdeI) and Pr_CU-acrE(XhoI), Pf_CU-acrA(NdeI) and Pr_CU-acrA(XhoI), Pf_KV-acrE(NdeI) and Pr_KV-acrE(XhoI), Pf_KV-acrA(NdeI) and Pr_KV-acrA(XhoI), Pf_KV-others(NdeI) and Pr_KV-others(XhoI), Pf_RT-acrA(NdeI) and Pr_RT-acrA(XhoI), Pf_RT-others(NdeI) and Pr_RT-others(XhoI), Pf_AG-others(NdeI) and Pr_AG-others(XhoI), Pf_SF-others(NdeI) and Pr_SF-others(XhoI), Pf_CR-others(NdeI) and Pr_CR-others(XhoI), Pf_MP-others(NdeI) and Pr_MP-others(XhoI), Pf_ZA-acrA(NdeI) and Pr_ZA-acrA(XhoI) were used to amplify acrE of Citrobacter tructae, acrA of Citrobacter tructae, mdtE of Citrobacter tructae, acrE of Citrobacter telavivum, acrA of Citrobacter telavivum, acrE of Enterobacter soli, acrA of Enterobacter soli, acrE of Buttiauxella agrestis, acrA of Buttiauxella agrestis, acrE of Cronobacter universalis, acrA of Cronobacter universalis, acrE of Klebsiella variicola, acrA of Klebsiella variicola, other efflux RND transporter periplasmic adaptor subunit families of Klebsiella variicola, acrA of Raoultera terrigena, other efflux RND transporter periplasmic adaptor subunit families of Raoultera terrigena, other efflux RND transporter periplasmic adaptor subunit families of Acetobacter ghanensis, other efflux RND transporter periplasmic adaptor subunit families of Solimonas flava, other efflux RND transporter periplasmic adaptor subunit families of Caulobacter rhizosphaerae, other efflux RND transporter periplasmic adaptor subunit families of Methylibium petroleiphilum, acrA of Zavarzinia aquatilis from corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs, Ipswich, UK), resulting in plasmids of pETD-CTR-acrE, pETD-CTR-acrA, pETD-CTR-mdtE, pETD-CTE-acrE, pETD-CTE-acrA, pETD-ES-acrE, pETD-ES-acrA, pETD-BA-acrE, pETD-BA-acrA, pETD-CU-acrE, pETD-CU-acrA, pETD-KV-acrE, pETD-KV-acrA, pETD-KV-others, pETD-RT-acrA, pETD-RT-others, pETD-AG-others, pETD-SF-others, pETD-CR-others, pETD-MP-others, pETD-ZA-acrA, respectively.

    To fuse each predicted efflux pump to GFP individually, the stop codon of each predicted efflux pump was removed and two rounds of PCR was used to introduce a Gly-Ser-Gly linker between these two genes[27]. During the first round, two sets of primers such as Pf_PA-others-GSG-GFP(EcoNI) and Pr_PA-others-GSG-GFP, Pf_PA-others-GSG-GFP and Pr_PA-others-GSG-GFP(XhoI) were used. Secondly, primers Pf_PA-others-GSG-GFP(EcoNI)/Pr_fused-GFP(XhoI) were used to connect two above PCR products via overlapping extension PCR, resulted in pACYC-PA-others-GSG-GFP harboring fused gene construct encoding PA_others, three amino acid linker, and GFP. Similarly, Pf_PA-mdtC-GSG-GFP(EcoNI)/Pr_PA-mdtC-GSG-GFP and Pf_PA-mdtC-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SC-mdtC-GSG-GFP(EcoNI)/Pr_SC-mdtC-GSG-GFP and Pf_SC-mdtC-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SE-mdtC-GSG-GFP(EcoNI)/Pr_SE-mdtC-GSG-GFP and Pf_SE-mdtC-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SE-acrE-GSG-GFP(EcoNI)/Pr_SE-acrE-GSG-GFP and Pf_SE-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SE-acrA-GSG-GFP(EcoNI)/Pr_SE-acrA-GSG-GFP and Pf_SE-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTR-acrE-GSG-GFP(EcoNI)/Pr_CTR-acrE-GSG-GFP and Pf_CTR-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTR-acrA-GSG-GFP(EcoNI)/Pr_CTR-acrA-GSG-GFP and Pf_CTR-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTR-mdtE-GSG-GFP(EcoNI)/Pr_CTR-mdtE-GSG-GFP and Pf_CTR-mdtE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTE-acrE-GSG-GFP(EcoNI)/Pr_CTE-acrE-GSG-GFP and Pf_CTE-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_ES-acrE-GSG-GFP(EcoNI)/Pr_ES-acrE-GSG-GFP and Pf_ES-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_ES-acrA-GSG-GFP(EcoNI)/Pr_ES-acrA-GSG-GFP and Pf_ES-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_BA-acrE-GSG-GFP(EcoNI)/Pr_BA-acrE-GSG-GFP and Pf_BA-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_BA-acrA-GSG-GFP(EcoNI)/Pr_BA-acrA-GSG-GFP and Pf_BA-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CU-acrE-GSG-GFP(EcoNI)/Pr_CU-acrE-GSG-GFP and Pf_CU-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CU-acrA-GSG-GFP(EcoNI)/Pr_CU-acrA-GSG-GFP and Pf_CU-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_KV-acrE-GSG-GFP(EcoNI)/Pr_KV-acrE-GSG-GFP and Pf_KV-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_KV-acrA-GSG-GFP(EcoNI)/Pr_KV-acrA-GSG-GFP and Pf_KV-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_KV-others-GSG-GFP(EcoNI)/Pr_KV-others-GSG-GFP and Pf_KV-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_RT-acrA-GSG-GFP(EcoNI)/Pr_RT-acrA-GSG-GFP and Pf_RT-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_RT-others-GSG-GFP(EcoNI)/Pr_RT-others-GSG-GFP and Pf_RT-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_AG-others-GSG-GFP(EcoNI)/Pr_AG-others-GSG-GFP and Pf_AG-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SF-others-GSG-GFP(EcoNI)/Pr_SF-others-GSG-GFP and Pf_SF-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CR-others-GSG-GFP(EcoNI)/Pr_CR-others-GSG-GFP and Pf_CR-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_MP-others-GSG-GFP(EcoNI)/Pr_MP-others-GSG-GFP and Pf_MP-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_ZA-acrA-GSG-GFP(EcoNI)/Pr_ZA-acrA-GSG-GFP and Pf_ZA-acrA-GSG-GFP/Pr_fused-GFP(XhoI) were used to fuse other predicted efflux pumps to GFP, this resulted in pACYC-PA-mdtC-GSG-GFP, pACYC-SC-mdtC-GSG-GFP, pACYC-SE-mdtC-GSG-GFP, pACYC-SE-acrE-GSG-GFP, pACYC-SE-acrA-GSG-GFP, pACYC-CTR-acrE-GSG-GFP, pACYC-CTR-acrA-GSG-GFP, pACYC-CTR-mdtE-GSG-GFP, pACYC-CTR-acrE-GSG-GFP, pACYC-ES-acrE-GSG-GFP, pACYC-ES-acrA-GSG-GFP, pACYC-BA-acrE-GSG-GFP, pACYC-BA-acrA-GSG-GFP, pACYC-CU-acrE-GSG-GFP, pACYC-CU-acrA-GSG-GFP, pACYC-KV-acrE-GSG-GFP, pACYC-KV-acrA-GSG-GFP, pACYC-KV-others-GSG-GFP, pACYC-RT-acrA-GSG-GFP, pACYC-RT-others-GSG-GFP, pACYC-AG-others-GSG-GFP, pACYC-SF-others-GSG-GFP, pACYC-CR-others-GSG-GFP, pACYC-MP-others-GSG-GFP, pACYC-ZA-acrA-GSG-GFP, respectively.

    Primers Pf_CTR-envR(NdeI) and Pr_CTR-envR(XhoI) were used to amplify envR of Citrobacter tructae from corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-CTR-envR. Primers Pf_EC-envR(NdeI) and Pr_EC-envR(XhoI) were used to amplify envR of E. coli from genomic DNA into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-EC-envR. The lambda-red recombination-based method[28] was used to construct the EC_envR knockout mutant. Briefly, primers Pf_KanFRT-EC-envR and Pr_ KanFRT-EC-envR were used to amplify the FRT-flanked kanamycin resistance gene (KanFRT) from the plasmid pKD13[28], which included 40 bp of homology with the ends of EC-envR in both sides. This design would facilitate integration of this cassette into the corresponding sites. After transforming these cassettes, proper colonies were verified via colony PCR and following sequencing. The FRT-flanked Kan would be excised by FLP recombinase via pCP20 plasmid[28]. Primers Pf_CTR-acrF(G)/Pr_CTR-acrF(G), and Pf_pETD-CTR-acrE(G)/ Pr_pETD-CTR-acrE(G) were used to amplify CTR-acrF of Citrobacter tructae from corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into pETD-CTR-acrE through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-CTR-acrE-CTR-acrF.

    Primers and plasmids utilized here were shown in Supplemental Tables S1 and S2, respectively. Primer sets of Pf_Ptrc-PrgX(PETD)/Pr_Ptrc-PrgX(Pi), Pf_Pi-ccfA(G)/Pr_ccfA(G), Pf_prgZ(G)/Pr_prgZ(G), Pf_PprgQ-CTR-acrE(G)/Pr_PprgQ-CTR-acrE(G), and Pf_PprgQ-CTR-acrF(G)/Pr_PprgQ-CTR-acrF(PETD) were used to amplify prgX under Ptrc promoter, ccfA under Pi promoter, prgZ under P1 promoter, CTR_acrE under PprgQ promoter, and CTR_acrF under PprgQ promoter from pACYC-Ptrc-prgX, pETD-Ptrc-ccfA-Ptrc-prgZ, and corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into EcoNI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs) (i = 1−6). This would result in the plasmid of pETD-Ptrc-prgX-Pi-ccfA-PprgQ-CTR-acrE-PprgQ-CTR-acrF (i = 1−6).

    During the shake flask culture, LB medium associate with corresponding antibiotics was firstly utilized to culture engineered strains overnight (37 °C, 220 rpm orbital shaking). MOPS minimal medium supplemented with 10 g/L D-glucose was then used for re-culture with OD600 of 0.1, and the culture condition was then altered to 30 °C when OD600 reached 0.6[29]. At this time, 1 mM IPTG was added to induce the expression. Cell fluorescence and cell density were measured after 30 h of culture using Cytation 3 imaging reader system (BioTek, Winooski, USA).

    Each experiment was conducted in triplicate and the deviation was represented by the error bar. The extracellular and intracellular MCFA measurement was conducted based on our previous study[19]. Briefly, the supernatant of 1 mL cell culture was obtained (10,000 g, 5 min) for extracellular MCFA measurement, whereas the cell pellet of 1 mL cell culture was recovered (10,000 g, 5 min) with 1 mL deionized water for intracellular MCFA measurement. Based on our previous studies[13,14], gas chromatograph mass spectrometer (GC-MS) QP2010 Plus (Shimadzu) equipped with GC-MS column (Rtx-5 MS capillary with length of 30 m, film thickness of 0.25 μm, diameter of 0.25 mm) was utilized for the following free fatty acid extraction and quantification.

    MOPS minimal medium supplemented with 15 g/L D-glucose was used to perform the fermentations as demonstrated in our previous studies[13,14]. The overnight incubation in LB medium was firstly conducted to prepare the pre-inocula, which were then diluted into 50 mL MOPS minimal medium with an initial OD600 of 0.1 in 500-mL flasks. The parameters of 37 °C and 220 rpm orbital shaking were used to conduct the fermentation. The culture temperature was then altered to 30 °C with the supplementation of 1 mM IPTG when the OD600 reached 0.5−0.6. The concentration of MCFAs, including both extracellular and intracellular levels, was measured after a fermentation time of 48 h.

    Seed culture, which was performed on rotary shakers overnight (37 °C, 220 rpm), was then diluted into 3-L BioFlo 115 fermentor (New Brunswick Scientific Co, Edison, NJ, USA) as an OD600 of 0.1. This fermentor included 1.5 L MOPS minimal medium associate with corresponding antibiotics and 10 g/L D-glucose. During the fermentation, concentrated D-glucose (800 g/L) was used to maintain D-glucose concentration at 5 g/L. The cultivation temperature was changed to 30 °C when OD600 reached 0.5−0.6 associoate with the supplementation of 1 mM IPTG. 12.5% NH4OH solution or phosphoric acid solution was used to keep the pH at 6.5, and the agitation cascade (200−500 rpm) was utilized to keep the dissolved oxygen concentration at 30% saturation. Each MCFA fermentation was conducted in triplicate, and the deviation was represented via the error bar.

    Our previous secreting system screened numerous endogenous transporters including famous AcrAB-TolC system and other triphosphate (ATP)-binding cassette superfamily or annotated multidrug efflux superfamily, and found that the overexpression of resistance nodulation cell division family transporter acrE, mdtE and mdtC together with the deletion of multidrug efflux pump cmr from E. coli achieved the best performance[19]. However, owing to the rapid accumulation of genomic information, other sequenced microbial genomes may contain numerous efflux pumps and present a greatly unexplored resource for mining novel pumps. In order to screen the most favorable candidates during large genomic datasets, a multi-layer genome mining and phylogenomic analysis was developed. Firstly, the general evolutionary recapitulation of MCFA transporter families was investigated by comprehensive and systematic phylogenomics, and the input of the customized blast database for this analysis was constructed with 397 genomes belonging to different representative prokaryotic species.

    Our previous study identified that acrE, mdtE and mdtC from E. coli were responsible for accelerating MCFA export[19]. Hence, the amino acid sequences of AcrE, MdtE, and MdtC from E. coli were utilized as queries for the bioinformatics screen to predict target regions responsible for MCFA efflux within the constructed blast database. This screen was performed under E-value cutoff of 1E-12 and bit score cutoff of 200. The homology hits for AcrE, MdtE, and MdtC were 287, 284, 1446, respectively, among the constructed blast database, and the evolutionary relationships of AcrE, MdtE, and MdtC homology hits are presented in Figs 1, 2 & 3, respectively.

    Figure 1.  The evolutionary relationships of AcrE homology hits. When using AcrE as a query, the evolutionary relationships of 287 homology hits were analyzed and each homolog information was confirmed with BLASTp. It was found that the homology hits of AcrE mainly included AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits. The violet and red indicated the selected predicted efflux pumps for further analysis.
    Figure 2.  The evolutionary relationships of MdtE homology hits. When using MdtE as a query, the evolutionary relationships of 284 homology hits were analyzed and each homolog information was confirmed with BLASTp. It was found that the homology hits of MdtE also mainly comprised AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits. The colored areas indicate the relationships between Citrobacteria and E. coli species.
    Figure 3.  The evolutionary relationships of MdtC homology hits. (a) When using MdtC as a query, the evolutionary relationships of 1,446 homology hits were analyzed and each homolog information was confirmed with BLASTp. These homology hits could be divided into seven different enzyme families such as MdtC, MdtB, AcrD, AcrF, MdtF, AcrB, and CusA families. (b) The evolutionary history of MdtC families was further recapitulated. The colored areas indicate the selected predicted efflux pumps for further analysis.

    As seen in Fig. 1, the homologues of AcrE were distributed in 134 genomes, and most genomes contained more than one homology hit, indicating the deep genomic mining for the target gene. The information of these homologues was then confirmed via BLASTp. It was found that the homology hits of AcrE mainly included AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits such as MexX, MexA. Whereas the homologues of MdtE were also distributed in 134 genomes, and most genomes also contained multiple homology hits (Fig. 2). Similarly, the homology hits of MdtE also mainly comprised AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits, indicating the analogous evolutionary relationships between AcrE and MdtE. MdtC presented totally different evolutionary history compared with AcrE and MdtE, and the 1446 homology hits were distributed in 236 genomes (Fig. 3a). These homology hits could be divided into seven different enzyme families such as MdtC, MdtB, AcrD, AcrF, MdtF, AcrB, and CusA families, and the evolutionary history of MdtC was further recapitulated (Fig. 3b).

    When utilizing AcrE (Fig. 1) or MdtE (Fig. 2) as a query to mining genomes, homologues from Citrobacteria, Salmonella, and Enterobacteria species presented the closest evolutionary relationships with Escherichia species among both AcrE and AcrA families; Among the MdtE families, only the homologue from Citrobacteria tructae and Escherichia species existed; Whereas among efflux RND transporter periplasmic adaptor subunit families, merely homologues from partial Escherichia species were existing along with other species such as Pseudomonas, Acetobacteria species.

    When using MdtC as a query to mining genomes, homologues from Citrobacteria, Enterobacteria, and Salmonella species presented the closest evolutionary relationships with Escherichia species, and Enterobacteria species exhibited closer evolutionary relationships than Salmonella species among MdtC families (Fig. 3b), whereas these two species bestowed different evolutionary behaviors when using AcrE or MdtE as queries. Furthermore, the taxonomic relationship of each species was defined via constructing a species tree with the amino acid sequences of their RNA polymerase beta subunits (RpoB) (Fig. 4). It was found that Salmonella species exhibited closer evolutionary relationship with Escherichia species than Citrobacteria species, which was different when using AcrE, MdtE, or MdtC as queries, suggesting the interesting engineering targets of homologues from Citrobacteria species.

    Figure 4.  The taxonomic relationship of each species used for general evolutionary recapitulation. The taxonomic relationship of each species was defined via constructing a species tree with the amino acid sequences of their RNA polymerase beta subunits (RpoB). It was found that Salmonella species exhibited closer evolutionary relationship with Escherichia species than Citrobacteria species, which was different when using AcrE, MdtE, or MdtC as queries.

    The above bioinformatic metric rendered the ability to rank the entire set of pumps and pick a portion that manifested a uniform distribution of candidates. To construct the library, the predicted efflux pumps were amplified from the genomic DNA or synthesized by GenScript (Nanjing, China), and this library harbored 29 predicted efflux pumps, all of which had not been previously characterized for MCFA transport. This library mainly focused on AcrE or MdtE homologues, as in our previous study[19] demonstrated that these two transporters derived from E. coli exhibited better performance than MdtC. Besides, due to the large size of MdtC (> 3,000 bp), it is costly and not convenient to amplify or synthesize numerous MdtC homologues.

    AcrE or mdtE homologues from Citrobacter tructae and Citrobacter telavivum among AcrE families, AcrA families, and MdtE families were selected, as we observed that these species presented different evolutionary trajectories. For instance, under the same search parameters, when using AcrE as a query, suitable hits were obtained and occurred in similar evolutionary positions among the AcrE families (Fig. 1); Whereas only suitable hits from Citrobacter tructae were observed when using MdtE as a query among the MdtE family; When using MdtC as a query, suitable hits were obtained in both species, yet they occurred in different evolutionary positions among the MdtC families (Fig. 3). Other AcrE/MdtE homologues were selected from Salmonella enterica, Enterobacter soli, Buttiauxella agrestis and Cronobacter universalis among AcrE or AcrA families, Klebsiella variicola among AcrE families, AcrA families, or other efflux RND transporter periplasmic adaptor subunit families, Raoultera terrigena among AcrA families or other efflux RND transporter periplasmic adaptor subunit families, Pseudomonas aeruginosa, Acetobacter ghanensis, Solimonas flava, Caulobacter rhizosphaerae, and Methylibium petroleiphilum among other efflux RND transporter periplasmic adaptor subunit families, Zavarzinia aquatilis among AcrA families. Several MdtC homologues from Citrobacter tructae, Citrobacter telavivum, Pseudomonas aeruginosa, Streptomyces coelicolor, and Salmonella enterica were also selected for further investigation.

    To efficiently identify suitable transporters with the capability to export MCFAs from cells, a simple test system constructed in our previous study[19], was utilized. This test system consisted of two individual plasmids (Fig. 5b), which could stably maintain in one cell owing to their distinct replication origins and antibiotic resistance markers. The first plasmid pCDFD-T7-bktB-T7-fadB-T7-ter-T7-ydiI-t7-acs carrying thiolase (BktB) of Ralstonia eutropha, 3-hydroxyacyl-CoA dehydrogenase/enoyl-CoA hydratase (FadB) of E. coli, transenoyl-CoA reductase (Ter) of Euglena gracilis, thioesterase (YdiI) of E. coli, and acetyl-CoA synthetase (Acs) of E. coli, was responsible for MCFA production (Fig. 5a), whereas the other pETDuet-1 derived plasmid was utilized for the expression of various bacterial transporters.

    Figure 5.  Construction of MCFA efflux pump library. (a) Microbial production of MCFAs from D-glucose via the reversal of β-oxidation cycle and transporter engineering. (b) Illustration of the test system. This test system consisted of two individual plasmids. The first plasmid pCDFD-T7-bktB-T7-fadB-T7-ter-T7-ydiI-t7-acs was responsible for MCFA production, whereas the other pETDuet-1 derived plasmid was utilized for the expression of various bacterial transporters. (c) Effect of predicted efflux pump engineering on extracellular, intracellular and total MCFA production. Each experiment in this study was conducted in triplicate and error bars signify standard deviation (SD) with 95% confidence interval (CI).

    A set of 29 predicted efflux pumps were then overexpressed individually, and three different measurements including the extracellular MCFA concentration, the intracellular MCFA concentration, and the total MCFA concentration, were used to screen each target pump. Firstly, as these candidates have not been characterized previously, to assure their reliable gene expression, GFP was tagged to each candidate to measure translational output and normalized fluorescence measurements were conducted for each one by dividing measured fluorescence values to the OD600 of that well (Supplemental Fig. S1). As seen from Fig. 5c, it was found that homologues among AcrE/MdtE families exhibited better performance than among MdtC families and AcrA families, and the top-performing candidate pumps existed in Citrobacteria species.

    Although the top-performing efflux pumps exist in Citrobacteria species, AcrE homologues from different Citrobacteria species exhibited dissimilar behaviors. Besides, MCFA transporter homologues from Citrobacteria species occurred in divergent evolutionary positions, suggesting the necessity for future engineering efforts. Hence, genomes deposited as Citrobacteria were retrieved from the NCBI FTP site with the appropriate filter parameters such as contig number (cut-off ≤ 400), N50 (≥ 20,000 bases), and completeness (≥ 80%) to remove low-quality genomes and eliminate redundancy at the strain level. This resulted in a subset of 797 genomes used hereafter, to comprehensively analyze transporter-centric phylogenies which contained the genomic context surrounding target genes.

    Analysis of this AcrE-centric phylogenetic tree exhibited in Fig. 6a revealed that EnvR homologues, a predicted AcrEF/EnvCD operon regulator, were present in most Citrobacteria species. Hence, we then asked whether this transcriptional regulator could further affect MCFA production. It was found that overexpression of EnvR from Citrobacter tructae decreased extracellular MCFA production by 32% (Fig. 6b), suggesting that EnvR might act as a repressor. The AcrE-centric phylogenetic tree based on genomes of Escherichia species were then constructed, and 1084 genomes deposited as Escherichia were retrieved from the NCBI FTP site. This phylogenetic tree also manifested that EnvR homologues were existing in most Escherichia species (Fig. 7a), and it was observed that overexpression of EnvR from E. coli decreased extracellular MCFA production by 39%, whereas the deletion of endogenous EnvR further increased extracellular MCFA production by 168% associated with the overexpression of EnvR from Citrobacter tructae (Fig. 7b).

    Figure 6.  Detailed evolutionary divergence of MCFA transporter families in Citrobacter species. (a) Analysis of this AcrE-centric phylogenetic tree based on genomes from Citrobacter species. This revealed that EnvR homologues, a predicted AcrEF/EnvCD operon regulator, were present in most Citrobacteria species. (b) Effect of transcriptional regulator EnvR engineering on MCFA production. CT_EnvR indicated envR of Citrobacter tructae. Experiments in this study were conducted in triplicate and error bars signify SD with 95% CI.
    Figure 7.  Detailed evolutionary divergence of MCFA transporter families in Escherichia species. (a) Analysis of the AcrE-centric phylogenetic tree based on genomes of Escherichia species. This phylogenetic tree also manifested that EnvR homologues were existing in most Escherichia species. (b) Effect of transcriptional regulator EnvR engineering on MCFA production. EC_EnvR indicated envR of E. coli; CT_EnvR indicated envR of Citrobacter tructae; CT_AcrE indicated acrE of Citrobacter tructae; CT_AcrF indicated acrF of Citrobacter tructae. Experiments in this study were conducted in triplicate and error bars signify SD with 95% CI.

    Although the deletion of endogenous EnvR rendered the increase of extracellular MCFA production, we also observed the decrease of the cell growth (Supplemental Fig. S2). This would exert a negative influence on the total MCFA production and indicated that EnvR was not only involved in MCFA export, but also possessed unknown essential functions. In order to prevent the deactivation of the entire regulon by deleting EnvR, we sought to investigate whether there was a new protein potentially involved in MCFA export. As EnvR was a predicted AcrEF operon regulator, AcrF from Citrobacter tructae was then overexpressed associated with AcrE. It was found that overexpression of both AcrE and AcrF exhibited the best performance (2.5-fold) among all the candidates (Fig. 7b), demonstrating that AcrE and AcrF were responsible for MCFA export.

    In order to convert MCFA efflux to an autonomous behavior without inducer supplementation and human supervision, we turned to combining quorum-sensing (QS) circuitry with the efflux pumps. Our previous studies described two robust and autonomous QS-based circuits deriving from peptide pheromone responsive QS system of Enterococcus faecalis (QEX), and optimized acyl-homoserine lactone responsive QS system of Vibrio fisheri (QVX) by introducing T7 RNA polymerase as a genetic amplifier[26,30]. As the optimized QVX circuity needs the expression of T7 RNA polymerase, this would affect the utilization of T7 promoter for driving other pathway genes. Hence, in this study, T7 promoter driving the expression of efflux pumps was replaced by QEX circuity.

    During the QEX circuity, the operator sequence of the response promoter PprgQ was repressed by the master protein regulator PrgX, and the activation of this response promoter only occurred when heptapeptide cCF10 synthesized by heptapeptide CcfA bound to protein regulator PrgX (Fig. 8a)[30]. Our previous studies demonstrated that the components of functional QEX circuity must contain protein regulator PrgX and surface cCF10-binding protein PrgZ driven by constitutive Ptrc and P1 promoters, respectively, to assure both the low leakiness and robust response behavior of QEX circuity[30], whereas signal synthase CcfA was driven by constitutive promoters with different strength ranging from high strength P1 to low strength P6, to trigger QEX circuity at various times.

    Figure 8.  Construction of autonomous MCFA secreting systems. (a) Schematic of QEX circuity. (b) The effect of replacing T7 promoter with QEX circuity on MCFA production. The signal synthase CcfA was driven by constitutive promoters with different strength ranging from high strength P1 to low strength P6, to trigger QEX circuity at various times. (c) The evaluation of the performance of this autonomous MCFA secreting system in scaled-up bioreactors. Experiments in this study were conducted in triplicate and error bars signify SD with 95% CI.

    As seen in Fig. 8b, it was observed that different triggering times of QEX circuity driving the efflux pumps exerted different impact on extracellular MCFA concentrations and total MCFA concentrations. We found that an early or delayed triggering of efflux pumps led to the decrease of extracellular or total MCFA concentrations compared to the suitable triggering time (i = 2), further demonstrating the importance of examining the impact of different triggering times on efflux efficiency. It was presumed that during the early fermentation time, product toxicity did not present as an issue in strain engineering, and the early expression of efflux pumps would exert an extra metabolic burden on host strains; whereas the delay triggering of efflux pumps would not efficiently alleviate the product toxicity.

    We also evaluated the performance of this autonomous MCFA secreting system in scaled-up bioreactors (Fig. 8c), which presented as more industrially relevant procedures. The autonomous secreting system was then evaluated in a 5-L fermenter with the conduction of dissolved oxygen (30%), glucose (5 g/L) and pH control (6.5). It was observed that engineered strains in bioreactors exhibited better performance than in shake flasks, and a nearly 4.9-fold increase in MCFA titers (6.9 g/L) was observed. It was presumed that engineered strains in bioreactors produced higher concentration of MCFAs than shake flasks, and this would render more product toxicity to host strains, thus limiting their performance in bioreactors, whereas our autonomous secreting system would unleash their potential in target product synthesis.

    Most bio-chemicals present toxic effects and stresses towards host strains during high concentrations, which are essential for developing an economically viable and scalable bio-process[1,16,31]. Furthermore, extracting MCFAs through harvesting engineered organisms also exhibits energy- and cost-intensive characteristics. Numerous studies found that microbial efflux pumps could provide host strains the ability of resistance to high target product concentrations in fermentation broth via improving the secretion of endogenous compounds. More importantly, expediting product secretion could decrease product inhibition and improve target flux through reversible reactions due to the maintainence of low intracellular target product levels[16,17]. However, the information of efflux pumps specially responsible for MCFA transport is limited. Here, a multi-layer genome mining analysis combining with quorum-sensing circuit was developed to screen a library of uncharacterized heterologous pumps among over 2000 microbial genomes, and these efforts rewired the MCFA efflux to a robust and autonomous behavior without inducer supplementation or human supervision, paving the way to develop economically feasible bioprocesses.

    The current MCFA secreting system is built on the basis of endogenous transporters, which require both over-expression of acrE, mdtE, mdtC and deletion of cmr from E. coli[19]. However, fueled by rapid developments in high-throughput sequencing, numerous other sequenced microbial genomes contain abundant efflux pumps and present a largely unexplored resource for mining novel pumps[20,21]. In order to efficiently mine genomes during large genomic datasets, a multi-layer genome mining and phylogenomic analysis was developed. In the first layer, the general evolutionary recapitulation of target gene families was performed by comprehensive and systematic phylogenomics based on 397 genomes belonging to different representative prokaryotic species. In the second layer, special species which exhibited great potential after experimental verification were selected for future engineering efforts, and target gene-centric phylogenies, which contained the genomic context surrounding target genes based on all the genomes derived from these species, was conducted. This allowed us to perform detailed analyses of how gene cluster architectures evolved from their constituent independent enzymes or sub-clusters. This multi-layer analysis would enable us to identify hidden regulons related to target genes. Hence, this multi-layer bioinformatic framework could help us to effectively screen uncharacterized heterologous target genes or pathways across large strain collections during genome mining.

    MCFA efflux in organisms by nature could sense environmental changes in real time, and self-regulate cellular pathway fluxes, which would maximize product yields and minimize human supervision over the fermentation process control. Whereas current MCFA efflux systems required inducible promoters to conduct the transport function[19], and this was still incompatible with large-scale production[30,32,33]. In order to transform current MCFA efflux systems to an autonomous behavior eliminating inducer supplementation and human supervision, peptide pheromone responsive QS system of Enterococcus faecalis was combined with the efflux pumps. It was found that suitable triggering times of QEX circuity driving the efflux pumps yielded the best effect, and an early or delayed triggering of efflux pumps led to the decrease of extracellular or total MCFA concentrations, demonstrating the importance of examining the impact of different triggering times on efflux efficiency (Fig. 8b). This is, to our knowledge, the first report of autonomous and robust MCFA efflux system, and our autonomous secreting system would unleash microbial potential in target product synthesis, providing a valuable tool for advancing the field of high-value oleochemical research.

    Detailed information regarding the construction of MCFA efflux pump library and autonomous MCFA secreting systems, experimental details on the quantitation of MCFAs, culture conditions and batch culture are shown. The results regarding the confirmation of expressing each predicted efflux pump, cell growth of engineered strains, DNA sequences of modified genes (Supplemental Table S3) are also presented.

    Thanks to Pablo Cruz-Morales (Senior researcher, DTU Biosustain) to help us with the phylogenomics analysis for mining the efflux pumps. This work was financially supported by Natural Science Foundation of Jiangsu Province (BK20202002), Excellent Youth Foundation of Jiangsu Scientific Committee (BK20211526), Jiangsu Agricultural Science and Technology Innovation Fund (SCX(20)3332), National Natural Science Foundation of China (No. 31972060), Fellowship of China Postdoctoral Science Foundation (2020T130305), Fundamental Research Funds for the Central Universities (KYGD202003), China Postdoctoral Science Foundation (2018M640491), Postdoctoral Research Funding of Jiangsu Province (2018K030B), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

  • The authors declare that they have no conflict of interest.

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  • Cite this article

    Sotiriou V, Michas G, Xiong L, Drosos M, Vlachostergios D, et al. 2023. Effects of heavy metal ions on white clover (Trifolium repens L.) growth in Cd, Pb and Zn contaminated soils using zeolite. Soil Science and Environment 2:4 doi: 10.48130/SSE-2023-0004
    Sotiriou V, Michas G, Xiong L, Drosos M, Vlachostergios D, et al. 2023. Effects of heavy metal ions on white clover (Trifolium repens L.) growth in Cd, Pb and Zn contaminated soils using zeolite. Soil Science and Environment 2:4 doi: 10.48130/SSE-2023-0004

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Effects of heavy metal ions on white clover (Trifolium repens L.) growth in Cd, Pb and Zn contaminated soils using zeolite

Soil Science and Environment  2 Article number: 4  (2023)  |  Cite this article

Abstract: According to the Greek Ministry of Environment, there are 2,000 contaminated sites in Greece. The agricultural production in these sites should be evaluated to provide an assessment and recommendations on the necessary actions required for crop sustainability. This study investigated the effects of heavy metals on White clover (Trifolium repens L.) growth in an above-referenced multi-metal contaminated site in the absence/presence of zeolite as an agent empowering the rehabilitation of pollution and immobilization of heavy metals. The addition of 1% zeolite to the polluted soils significantly contributed to plant growth by limiting the availability of Cd, Pb and Zn. However, the dry biomass of plants grown in the presence of zeolite was evaluated to be unsuitable as a raw material (feed) in livestock production, due to the high Cd toxicity. In the context of sustainable production, this study aims to holistically approach and evaluate mechanisms of phytoremediation, bioaccumulation and the disposal of the bioaccumulator as a high value-added product (feed).

    • Industrial areas near arable land and coastal locations may engender a wide variety of environmental problems with impacts that extend considerably beyond the plant sites (Malizia et al., 2012; Muthusaravanan et al., 2018). These impacts range from relatively minor disturbances (such as temporary) to major disruptions e.g., water and soil pollution caused by toxic chemicals such as heavy metals (Tóth et al., 2016). The most commonly found heavy metals in industrial waste include arsenic, cadmium, chromium, copper, lead, nickel and zinc (Papamanolis et al., 2018) and are the most frequent form of environmental pollution around industrial areas (Malizia et al., 2012). Previously studies indicated that the interaction between Pb (II) ions, organic matter (humic acids) (Giannakopoulos et al., 2005) and clays (Giannakopoulos et al., 2006) results in the formation and stabilization of new radicals with a striking feature being their unusually low g-values, i.e., below the free electron g-value allowing for the formation of stable chelating Pb (II) complexes of Pb (II) with humic substances of soil. This metal-accumulation in soils at concentrations above the upper limit may cause soil malfunctions and toxicity in plants, animals and humans (Tóth et al., 2016; MEF, 2007). In the case of plants, the heavy metal uptake is evaluated by the bioaccumulation factor (BF) (Zhuang et al., 2007). As reported by Netty et al. (2013), if BF > 1, the plants are defined as 'metal super' accumulators; when the BF ranges between 0.1 and 1 the plants belong to the 'moderate' accumulators; and when the BF is between 0.01 and 0.1 the plants are classified as 'weak' accumulators.

      According to the principles of sustainable development in order to preserve natural resources and minimise the environmental impact of pollution upon plants, animals and humans, every agricultural production in multi-metal contaminated soils must be evaluated and provide an assessment and recommendations on the necessary actions required for crop sustainability (Tripathi et al., 2017). Nowadays, natural zeolites have been increasingly used in various application areas such as industry (Mench et al., 2002), agriculture (Tsadilas et al., 1997), environmental protection, and even medicine (Eroglu et al., 2017). More than 40 naturally occurring zeolites were reported by different research groups, and clinoptilolite, erionite, chabazite, heulandite, mordenite, stilbit and philipsite are the most well-known (Eroglu et al., 2017; Polat et al., 2004). Natural zeolites were discovered more than 200 years ago, and are studied due to their peculiar characteristics such as high degree of hydration, high degree of crystallinity, low density and the large volume of free spaces (dehydrated); shape selectivity, ion exchange characteristics, catalytic characteristics, sorption of molecules and ions and electric conductivity (Morante-Carballo et al., 2021). They can be described as 'crystalline aluminosilicates with a three-dimensional structure based on repeating units of silicon-oxygen (SiO4) and aluminium-oxygen (AlO4) tetrahedra', and are also attributed as 'molecular sieves' due to their ability to accept and reject molecules based on their size (Morante-Carballo et al., 2021). The studies mainly focus on water treatment, wastewater management, soil decontamination, and nuclear waste. Zeolite applications in environmental remediation are mainly due to its ion exchange properties, where, depending on the type of zeolite, its pore size, the shape of its internal channels, and the type of exchange cation—it can interact with cations from the environment, with which it can have high selectivity such as heavy metals (Morante-Carballo et al., 2021).

      The most common for agricultural applications is clinoptilolite since it has high absorption, cation exchange, catalysis and dehydration capacities (Polat et al., 2004). Its ability to absorb toxic and radioactive ions from liquids and soils is of great importance to ecology and human health (Misaelides et al., 2011). Kim et al. (2012), indicated that the zeolite demonstrate high heavy metal immobilization efficiency, reduces the availability of plants, and simultaneously mitigates the threat of food chain contamination with heavy metal ions. In particular, the addition of zeolite (at concentration < 1%) in the metal-contaminated soils contributes significantly to plant growth by limiting the availability of heavy metals (Muthusaravanan et al., 2018). As reported by Ahmed et al. (2010), and Prasad et al. (2014), the presence of zeolite in a metal contaminated soil increases the soil surface due to its porous structure and results in better aeration of the plants. Since zeolite absorbs heavy metals and nutrients enables the increase of plant growth and crop yield.

      A survey report issued by the Greek Ministry of Environment on the rehabilitation of sites contaminated by industrial and hazardous waste showed that there are 2,000 contaminated sites in Greece, out of which 300 need immediate rehabilitation according to the principles of sustainable development in order to preserve natural resources and minimise the environmental impact of pollution on future generations (GME, 2016).

      The purpose of this investigation was to examine the alternative use of white clover as a metal accumulator plant and as a raw material (feed) after its cultivation in heavy-metal contaminated soils. The selection of white clover is due to its properties as a versatile plant species that is widely used in sustainable agriculture to improve soil fertility (Abbasi & Khan, 2004) and has great agronomic value as it is used as forage, cover crop and a basic feed (Bailey & Laidlaw, 1998). In addition, the possibility of using zeolite as a strengthening agent for the restoration of pollution and the immobilization of heavy metals was assessed. The aforementioned characteristics are in accordance with the new EU Common Agricultural Policy (Green Deal) (EC, 2020). Nowadays, the EU Farm to Fork strategy has increased the urgency to focus research on the use of white clover for reduction of chemical N fertiliser use and the restoration of pollution and the immobilization of heavy metals (EC, 2020a). In this framework, the evaluation of the effects of heavy metals on crop growth in multi-metal contaminated soils is necessary for reducing the associated risks, making the land resources available for agricultural production, enhancing food security and scaling down land tenure problems arising from changes in the land use pattern (EC, 2020a; Tripathi et al., 2017).

    • Soil sampling was applied according to the protocol developed by Ahmad et al. (2018), and carried out on two field sites in the Thessaly Region of Greece. The first experimental site (coded as polluted soil, 'P') was located on soil polluted with heavy metals (Pb, Cd and Zn) in Volos, Greece (GME, 2016). In particular, the 'P' site is agricultural land affected by heavy metals soil contamination resulting from a decommissioned industrial activity. This soil has contents of Cd, Pb and Zn that exceed the limits set by Greek law for arable lands (GME, 2015) and on the basis of the GME's survey (GME, 2016) needs immediate rehabilitation according to the principles of sustainable development (Tripathi et al., 2017). The second experimental site (coded as unpolluted soil, 'C') was located on unpolluted land (control) surrounding the Institute of Industrial and Forage crops of the Hellenic Agricultural Organization-Demeter (HAO-DEMETER) at Larissa, Greece.

    • Soil samples were collected, according to the protocol developed by Ahmad et al. (2018), from the outer surface, i.e., 5 to 30 cm depth, after removing surface contamination that may consist of leaves or other transportable materials using a soil sampler or a simple shovel, up to the depth of 30 cm. The samples were collected in self-locking polythene bags and were sealed in double bags. The samples were then mixed and dried at 30 °C for 48 h, then ground with a porcelain mortar and pestle and sieved through a 2 mm sieve to remove large debris, stones and pebbles. The < 2 mm fraction of the soil was used for all soil analyses.

    • Soil physicochemical analysis was performed according to the protocol developed by Allison (1965), and Allison & Moodie (1965), whilst the essential nutrients such as Nitrogen, Phosphorus, and Potassium were determined as described by Hutchinson & Meema (1987). Particle-size analysis was performed by the hydrometer method (Bouyoucos et al., 1962), pH and electrical conductivity (EC) were measured in 1:1 suspension with water, and organic carbon was determined by the wet oxidation method (Walkley & Black, 1934). The method used for carbonate content was the Bernard method, by measuring the evolved CO2 after the addition of HCl (Nelson, 1982). Soil-available P was extracted by employing the method suggested by Olsen & Sommers (1982) and determined using spectrophotometry. Exchangeable cations were determined after extraction with 1M CH3COONH4 at pH 7 (Knudsen et al., 1982), with a Jenway PFP7 flame photometer used for measuring K (Jones & Case, 1990).

      Moreover, the total metal (Cd, Pb, and Zn) concentrations were determined by an atomic absorption spectrophotometer (Thermo Scientific, iCE 3000 Series) according to Hutchinson and Meema's protocol (Hutchinson & Meema, 1987) as described in the EPA 3050 method (determination of pseudo-total heavy metals in soil samples by aqua regia digestion at 140 oC for 5 h with 3:1 concentrated HCl : HNO3) (ISO/DIS 11466, 1994). Pseudo-total metals in particular, are acid-leachable metals that are not part of the silicate matrix (Relic et al., 2011). All the results are summarised in Table 1. X-ray diffraction (XRD) was performed on the soil samples 'C' and 'P' to assess the altered degree of mineralogical composition in the soils after amendments were added (1% Zeolite), in order to decipher the soil-texture of the modified soils as described earlier (Michas et al., 2020). Powder X-ray diffraction (XRD) of the soils was performed on a Bruker D8 Advance diffractometer, using a nickel-filtered CuKα (1.5418 Å) radiation source. The data collection was carried out in the range of 5° ≤ 2θ ≤ 80° with a step of 0.02° and an acquisition time of 0.5 s and diffraction data were analyzed by the Bruker DIFFRAC.EVA software, using the fully Crystallography Open Database, as described earlier (Flogeac et al., 2005).

      Table 1.  Nutrients, physical and chemical characteristics of the tested soils.

      SoilNutrients and physicochemical propertiesMetal concentration (mg/kg dry soil)
      N
      (g/100g)
      P
      (mg/kg)
      K
      (cmol+/kg)
      pH
      (+0.01)
      Organic
      matter
      %
      CaCO3 %CEC
      (meq/100 g
      dry soil)
      Sand
      %
      Clay
      %
      Silt
      %
      Soil
      type
      CdPbZn
      'P'0.10110.748.243.211.1034.9264.012.124.2Sandy loam4.30a291.10a1,458.12a
      'C'0.11101.517.320.672.2136.3131.044.225.0Claynd**17.32c76.21c
      Maximum allowable values*1.0060.0200.0
      * Ministry of the Environment–Finland (MEF, 2007). nd**: Not Detectable. P: polluted soil, C: unpolluted soil (control). Different letters in each column indicate statistically significant differences (F-test, p < 0.05).
    • Clinoptilolite rich tuff Zeolite (commercial sample: BZM 0.15, supplied by Imerys Minerals AD, Bulgaria) was used in this work is from the Beli Plast deposit (Bulgaria) and contains nearly 85 wt. % clinoptilolite, opal-CT ~15 wt. % and cation exchange capacity (CEC) > 150 cmol+/kg. The chemical composition (wt. %) – 69.62 SiO2, 13.62 Al2O3, 2.94 K2O, 0.55 Na2O, 0.75 Fe2O3, 0.11 TiO2, 3.28 CaO and 0.9 MnO of this clinoptilolite results from the following crystal chemical formula: Na0.3K1.8Ca2.0Mg0.3Al6.3Si28.7O72.21H2O (Lihareva et al., 2015).

    • In order to investigate the soil remediation potential of zeolite we applied 1% zeolite in a heavy-metal polluted Greek soil cultivated with white clover and in a non-polluted control soil. The addition of amendments into the soil could make heavy metals less bioavailable and thus could be suitable for heavy metal uptake mitigation by plants (Ahmed et al., 2010; Prasad et al., 2014). However, information about the effect of inorganic amendments on agricultural soils mainly with Cd (metal with high toxicity degree) is scarce. Keller et al. (2005) reported that the addition of zeolite in heavy metal-polluted soil at a dose of 1%, instead of 5%, was the most efficient way for reducing the average Cd concentration in tobacco plants. Under these considerations, pot experiments were performed in a HAO-DEMETER greenhouse to investigate the bio-accumulation capacity of White clover in a Cd, Pb, and Zn polluted soil remediation program in conjunction with incorporating 1% zeolite into the soil, as described earlier (Michas et al., 2020).

      Briefly, an equal number of pots were filled with 3 kg of contaminated, soil 'P' (12 pots) and non-contaminated, soil 'C' (12 pots). For each soil type half of the pots (6 pots in each soil) were treated with 1% zeolite per kg as descripted by Keller et al. (2005). Twenty seeds of white clover per pot were sown for each soil treatment while non-sown pots per treatment were left as a control. Three replicates were applied that correspond to 24 pots in total. Across all the treatments, 1.1 g P was applied to pots sown with white clover (Pederson, 1995) after taking into account the soil content of the above nutrients based on Table 1. The protocol proposed by Li et al. (2018), was followed during the growth period whereby all the pots remained free from weeds. The moisture content of each pot was adjusted to 60% of soil water capacity (Li et al., 2018) by weighing the pots twice a week and supplementing the corresponding water quantity. For the water capacity calculation, the weight of dry soil in each pot was calculated and subsequently water was added until saturation. The pot was weighed again and the difference corresponded to the water capacity value. Total plant samples were collected 90 d after sowing. Samples were washed with tap water to eliminate soil particles, rinsed with 0.1 M HCl and 0.1% soap substitute and deionized water, dried at 75 °C for 24 h and the dry matter was finally measured.

    • The BF in white clover plants with Cd, Pb, and Zn was calculated with the following equation (1) (Zhuang et al., 2007):

      BF=CptCs (1)

      where: Cpt is the metal concentration in plant tissue, and Cs is the metal concentration in soil.

      Specifically, Cpt corresponds to Cd, Pb, and Zn concentration in roots and shoots, whereas Ctot corresponds to the total heavy metal concentration in the soil types used for the experiment. The total Cd, Pb and Zn concentrations in plant tissues were determined by Dry Ashing Procedures (Jones & Case, 1990), whilst the available concentrations of Pb, Cd and Zn in the soil were determined with the extraction method (Giannakopoulos et al., 2017). For the statistical analysis a JPM8 statistical program (SAS Institute, ver. 2nd, 2009) was used to analyze the variance and compare the means. All differences among all soil samples were determined with One-way Anova (F-test, p < 0.05).

    • The composition of the 'C' soil samples that were collected from around the HAO-DEMETER institute was found to be clayey (USDA, 2009) (Table 1); the samples were described as neutral, pH = 7.32, with very low organic matter, 0.67%, and a high ion exchange capacity 36.31 meq/100gr. On the other hand, the 'P' soil samples near the industrial area were moderately alkaline and rich in organic matter (3.21%) (Table 1).

      The CEC was high, 34.92 meq/100gr, resulting in greater sorption and immobilization of the metals (Lasat, 2000). The soil was sandy loamy belonging to the coarse soils (USDA, 2009) with high pH (Table 1). The XRD diffractograms of the soil 'P' and soil 'C' in Fig. 1 show major peaks of SiO2 (Flogeac et al., 2005).

      Figure 1. 

      X-ray powder diffraction pattern of the (I) soil-'C' and (II) soil-'P'. The dotted lines show similar peaks. (C1: unpolluted soil, C2: unpolluted soil with the addition of 1% zeolite, P1: polluted soil and P2: polluted soil with the addition of 1% zeolite).

      Table 1 summarizes the concentrations of heavy metals Cd, Pb, and Zn in the soils used as plant substrates (not detectable, 17.32 and 76.21 mg/kg of dry soil C and 4.3, 291.1 and 1,458.12 mg/kg of dry soil P, in Cd, Pb, and Zn, respectively). According to our findings, the concentrations of Cd, Pb, and Zn in the contaminated soil 'P' were higher than the maximum allowable values of MEF (2007) (1, 60 and 200 mg/kg of dry soil, in Cd, Pb, and Zn, respectively).

    • White clover plants grown in contaminated soil 'P' and unpolluted 'C' soil, yielded higher dry matter of 2.83 g (= 8.33 − 5.50) and of 1.6 g (= 6.83 − 5.17) respectively, when the soil was amended with zeolite (Fig. 2). It is noteworthy that the largest quantity of biomass for White clover plants has been observed in contaminated 'P2' soil in the presence of zeolite. In particular, the addition of zeolite in 'P' and 'C' soils increased the dry biomass of plants by 51.4% and 32.1%, respectively.

      Figure 2. 

      Dry weight of white clover plants grown on the different tested soils. (P1: polluted soil without the addition of 1% zeolite, P2: polluted soil with the addition of 1% zeolite, C1: unpolluted soil without the addition of 1% zeolite, C2: unpolluted soil with the addition of 1% zeolite). * Different letters in each column indicate statistically significant differences (F-test, p < 0.05). Values ± SD.

    • The heavy metal bioaccumulation order in the total plant tissues of white clover plant followed the sequence: Zn > Pb > Cd. The concentrations of Cd, Pb, and Zn were also found to be significantly higher in the total plant tissue of white clover grown in contaminated soil, with 1.93, 11.74 and 199.31 mg/kg respectively, compared to that measured in the total plant tissue in unpolluted soil (nd**), 5.58 and 60.92 mg/kg, respectively (Table 2).

      Table 2.  Concentration of Cd, Pb and Zn in the total plant tissue of white clover plants.

      SoilWhite clover (mg/kg dry weight of plant)
      CdPbZn
      P11.93a*11.74a199.31a
      P21.43b7.98b141.95b
      C1nd**5.58c60.92c
      C2nd**3.66d54.16c
      Normal consumption
      limits as dry biomass:
      0.5030.00300.00
      P1: polluted soil without the addition of 1% zeolite, P2: polluted soil with the addition of 1% zeolite, C1: unpolluted soil without the addition of 1% zeolite, C2: unpolluted soil with the addition of 1% zeolite. *Different letters in each column indicate statistically significant differences (F-test, p < 0.05) nd**: not detectable.

      The statistical significant differences were also detected in the concentration of Cd, Pb and Zn in the total plant tissues of white clover plants grown in contaminated soil with or without zeolite (Table 2). The treatments of white clover grown in soil P with zeolite showed a significant 28.8 % reduction in Zn uptake, 25.9 % reduction in Cd uptake and 32 % reduction in Pb uptake. The reduction of Pb uptake of white clover in soil C after the zeolite amendment was significant, reaching 34.4%.

      On the basis of Table 2, it is noteworthy that the concentration of Cd in the white clover plant tissue developed in contaminated soil with or without zeolite in soil was higher, namely 1.43, 1.93 mg/kg dry weight of plant respectively, than normal consumption limits as dry biomass, namely 0.50 mg/kg dry weight of plant.

    • White clover was found to act as a 'moderate' accumulator of Cd and Zn, whilst the ability of white clover to accumulate Pb seems to be 'weak' (Fig. 3). The addition of zeolite to the soil contributed to the reduction in the BF of heavy metals (Fig. 3).

      Figure 3. 

      Bioaccumulation factor (BF) of white clover for Cd, Pb, and Zn. (P1: polluted soil without the addition of 1% zeolite, and P2: polluted soil with the addition of 1% zeolite,). Different letters in each column indicate statistically significant differences (F-test, p < 0.05). Values ± SD.

    • A decrease in the total concentration of Cd (45.81%), Pb (25.91%), and Zn (31.64%) was observed in the polluted soil 'P1' without the addition of 1% zeolite (Tables 1 & 3) after the cultivation of white clover. This decrease, in case of the polluted soil 'P2' with the addition of 1% zeolite was lower, namely: 39.01 % for Cd, 24.31% for Pb, and 28.45% for Zn (Table 3). Also, there is a statistically significant difference between the total and available heavy metals' soil concentration in polluted and unpolluted soil, studied after the plants harvest (Table 3). The potentially available metal fraction in soils may be a strong indication of recent metal depositions. Thus, using both total and potential available data sets for metal forms and examining their interrelations may assist with comprehending the possible effects by metals levels in soils on biological systems and the sources of current pollution events (Massas et al., 2013; Michas et al., 2020). However, after the white clover plants harvest, the total and available metal concentrations in the soil followed the descending order: Cd > Zn > Pb, independently of the treatment used with or without zeolite (Table 3).

      Table 3.  Total and available metal concentration in the soils after harvesting white clover plants.

      SoilMetal concentration (mg/kg dry soil)
      TotalAvailable
      CdPbZnCdPbZn
      P12.33a215.67a*996.67a0.39a31.00a84.67a
      P22.74b220.33b1043.33b0.40a32.33a93.67b
      C1nd**12.00c73.33cnd**2.07b5.97c
      C2nd**13.33c70.00cnd**2.1b6.87c
      P1: polluted soil without the addition of 1% zeolite. P2: polluted soil with the addition of 1% zeolite. C1: unpolluted soil without the addition of 1% zeolite. C2: unpolluted soil with the addition of 1% zeolite. * Different letters in each column indicate statistically significant differences (F-test, p < 0.05).
    • The low percentage addition of zeolite in soil (Michas et al., 2020) did not alter the soil matrix as was found by the XRD diffractograms (Fig. 1). On the other hand the polluted soils where rich in organic matter (Table 1), as compared to the average content of organic matter in Greek soils, which ranges between 1-2.5% (Zdruli et al., 2004).

      To assess the level of heavy metals concentration in the soil, we consulted the maximum allowable limits of heavy metals in the soil that was adopted by the Finnish legislation (MEF, 2007) and after investigation between the many different options of European countries (EC) (Tóth et al., 2016). As mentioned by Carlon et al. (2007), the above metal concentration limits of MEF (2007), taken into account herein, represent the average values in the national laws of different European Union countries, and are internationally implemented for evaluating and utilizing polluted soils in agricultural production (UNEP, 2013).

      Hence the studied soil was heavily polluted with heavy metals (Table 1), indicating that the industrial zone significantly contributes to the contamination of the adjacent areas with Cd, Pb and Zn (MEF, 2007). In addition, as reported by Iqbal & Saeed (2007) and by Vijayaraghavan & Yun (2008), in alkaline soils with pH > 8, the available concentration decreases due to precipitation and hydrolysis of the metal complexes, while some heavy metals were combined with carbonated ions by replacing calcium in the crystalline matrix of the carbonated minerals, thus limiting their availability (Hooda, 2010).

      The application of zeolite in both control and polluted soils resulted in the increase of white clover dry biomass (Fig. 2). These results are in accordance with Lin & Zhou (2009), whereby the incorporation of zeolite into soil contaminated with Pb, Cd and Cu has a positive effect on plant growth by preventing the uptake of heavy metals. As reported by Bidar et al. (2007), this could be attributed to the physiological resistance mechanisms with less oxidative damage in white clover in comparison to other plants. Plants exposed to environmental stress (i.e. temperature changes, UV light, ozone exposure, water deficiency, metallic ion excess, presence of redox active heavy metals) generally showed some alterations in the electron transport processes such as photosynthesis (chloroplast) and mitochondrial respiration. Thereafter, the disruption in the electron transport contributes to Reactive Oxygen Species (ROS) production, as well as the impairment in sophisticated enzymatic and/or non-enzymatic ROS scavenging systems. To counteract the adverse effects of ROS, plants developed antioxidant defense systems comprising enzymes as catalases, peroxidases superoxide dismutases and non-enzymatic constituents (a-tocopherol, ascorbate, reduced glutathione, etc.), which remove, neutralize, and/or scavenge oxidative species (Bidar et al., 2007).

      As expected, the total plant tissue of white clover in the polluted soil was found to possess significant higher values of heavy metals (> 110%) than in the control soil (Table 2), which are in accordance with Rebah et al. (2002), and Khan et al. (2011). Moreover, the application of zeolite resulted in the significant reduction of the heavy metals uptake of white clover in the polluted soil (Table 2), that is in line with Chlopecka & Andriano (1997), which found that zeolite and apatite can reduce the Cd, Pb and Zn accumulation in maize leaves. In fact, zeolite with its negative charge provides an ideal trap for positive cations such as Na+, Ca2+, Mg2+ and K+, and for positively charged groups such as water and NH4+ (Taffarel & Rubio, 2009). Therefore carbonate and nitrate ions can be bound within zeolites. Inasmuch, metallic cations are attracted in the same way and water can be absorbed by zeolites (Rhoades, 1982). Absorbed cations due to their weak attraction are relatively mobile and can be replaced by using ion-exchange techniques. In addition, as reported by Kim et al. (2012), zeolites have a wide range of surface areas containing multi-functional groups where heavy metals can be adsorbed and complexed.

      Nevertheless, since for the case of Cd the application of zeolite did not result in the reduction of its content in soil in lower levels than 0.5 mg/kg (Table 2), this signifies that the consumption of its dry mass from animals such as cattle, sheep, pigs and chickens could cause serious toxic effects and even lead to death. Potentially, if the concentration of heavy metals in roots and shoots had been measured separately, the results could be more encouraging with regard to its consumption by animals. This is confirmed by studies of Bidar et al. (2007), and Farrag et al. (2016), according to which the roots of white clover plants store higher concentrations of Cd, Pb and Zn than those measured in the shoots (stem) and leaves of the plant. As reported by Farrag et al. (2016), this limitation can be overcome by the removal of the roots of white clover plants from biomass (animal feed), resulting in low risk to animals (NRC, 1980).

      In this point it is important to state that even if the ability of white clover to accumulate Pb seems to be 'weak', the application of zeolite resulted in 32%–34.4% reduction in both polluted and control soil (Table 2). Therefore, the synchronous application of zeolite and white clover could result as a good practice for soil rehabilitation.

      Our findings are in accordance with Pricop et al. (2010), regarding the bioaccumulation capacity of white clover in heavy metal contaminated soils. Additionally, Peuke & Rennenberg (2005) found that constructive and cost-effective phytoremediation requires the use of plants with a bioaccumulation coefficient over 10 and biomass production capacity of at least 20 tn/ha, or alternatively the plants must at least have a bioaccumulation coefficient of 20 and biomass production greater than 10 tn/ha. On the other hand, the investigation of Ali et al. (2012), showed that the use of white clover alexandrinum for phytoremediation (by considering uprooting the plants in which case the accumulated heavy metals in the roots are removed from the soil) has many advantages. For example, it produces considerable biomass, has a relatively short life cycle, is resistant to prevailing environmental and climatic conditions and above all offers multiple harvests in a single growth period. Thus, this candidate species can be used for phytoremediation of toxic heavy metals (Michas et al., 2020).

      According to Massas et al. (2013), using both total and potential available data sets for metal forms and examining their interrelations may assist with comprehending the possible effects by metals levels in soils on biological systems and the sources of current pollution events (Table 3). In this context we found that the addition of zeolite soil controls the heavy-metal pollution in the soil matrix (Table 3), not allowing the white clover plants to bio-accumulate them into their biomass (Table 2). According to Ahmed et al. (2010), the presence of zeolite in the soil increases the retention of heavy metals as an absorber, thus, increasing crop yield. In fact, Ali et al. (2012), indicated that the white clover species such as Trifolium alexandrinum can be used for phytoremediation of toxic heavy metals and metalloids, including Cd, Pb, and Zn (Gatliff et al., 2016). Nevertheless, the total concentration of metals in the soil after the cultivation of white clover plants is lower but still above the permitted limits (Table 3) for Cd, Pb, and Zn (MEF, 2007), so perhaps the systematic monoculture of white clover with or without the zeolite amendment in the future may define whether the time and energy cost are enough to justify the practice.

    • This study demonstrated that the white clover plant is a 'moderate' accumulator of Cd and Zn, while its ability to accumulate Pb is 'weak'; the addition of zeolite in the heavy metal contaminated soils can minimise metal pollution in the environment and positively contribute to the growth of white clover plants. Moreover, the study showed that the concentration of Cd in the white clover plant tissue developed in contaminated soil with or without zeolite in soil was higher in its dry biomass than the normal consumption limits. Therefore, the white clover dry biomass consumption from animals such as cattle, sheep, pigs and chickens could cause serious bioaccumulation toxic effects and even lead to death. Consequently, the white clover alone seems to be inappropriate for soil remediation from Cd contamination in the context of sustainable development. On the other hand, the concentrations of Pb and Zn in the total plant tissue of white clover plants are below the maximum allowable limits for animal feed, resulting in low risk to animals. In order to achieve this goal contaminated fields with high concentrations of heavy metals should not be left unexploited during any growing season in order to decontaminate or reduce their pollution (exploitation of contaminated fields). Furthermore, previously polluted fields can be decontaminated or reduce their pollution with white clover which can be promoted for other uses such as dry fodder or for energy production contributing to the financial support of farmers. Moreover, the reduction of the soil heavy metals concentration leads to a reduction of the toxic elements amount that enter the underground aquifer with direct positive effects on the agro-ecosystem and the environment in general. Finally, the application of zeolite contributes to the increase of agricultural production as well as to the production of safe agricultural products. These results are expected to increase the productive actors' awareness on environmental issues and particularly on those related to the preservation of soil quality. In fact since soil is a natural resource closely related to agricultural productivity it is our outmost duty to protect it in order to provide sustainability for the future generations.

      • Preliminary results of the project were presented at the 11th European Conference on Pesticides and Related Organic Micropollutants & 17th Symposium on Chemistry and Fate of Modern Pesticides in Ioannina, Greece 23 to 26 June 2022. A part of the research project was funded by the University of Patras, in the frame work of the program 'MEDIKOS, 81938'. Also, we would like to thank Institute of Industrial and Forage crops HAO-DEMETER in Larissa, Greece for the logistic infrastructure that was provided in the experiments.

      • Marios Drosos is the Editorial Board member of Journal Soil Science and Envrionment. He was blinded from reviewing or making decisions on the manuscript. The article was subject to the journal's standard procedures, with peer-review handled independently of this Editorial Board members and his research groups.

      • # These authors contributed equally: Vasilios Sotiriou, Georgios Michas

      • Copyright: © 2023 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (3)  Table (3) References (66)
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    Sotiriou V, Michas G, Xiong L, Drosos M, Vlachostergios D, et al. 2023. Effects of heavy metal ions on white clover (Trifolium repens L.) growth in Cd, Pb and Zn contaminated soils using zeolite. Soil Science and Environment 2:4 doi: 10.48130/SSE-2023-0004
    Sotiriou V, Michas G, Xiong L, Drosos M, Vlachostergios D, et al. 2023. Effects of heavy metal ions on white clover (Trifolium repens L.) growth in Cd, Pb and Zn contaminated soils using zeolite. Soil Science and Environment 2:4 doi: 10.48130/SSE-2023-0004

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