Heavy metal tolerance and detoxification mechanism mediated by heavy metal resistance genes in compost habitat

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This study aims to reveal the heavy metal tolerance and detoxification mechanism mediated by heavy metal resistance genes (HMRGs) in compost habitat through metagenomics combined with chemical speciation analysis of heavy metals. The results showed that there were 37 HMRGs corresponding to 7 common heavy metal(loid)s in composting, and they had the ability to transform heavy metals into stable or low-toxic speciation by regulating enzyme transport, redox and methylation, etc. This study summarized the heavy metal metabolism pathway mediated by HMRGs, providing a new perspective for understanding the transformation of heavy metals in the composting process. Composting Heavy metal Heavy metal resistance genes Microorganisms Metagenomics Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Heavy metal pollution is an important factor limiting the land use of livestock manure composting products, and how to reduce the toxicity of heavy metals is the focus of resource recycling and sustainable development (Chen et al., 2020 ; Li et al., 2023 ). The heavy metals in compost mainly come from livestock and poultry manure in intensive farming, and micronutrients (Zn and Cu) are widely added to animal feed (Rensing et al., 2018 ; Liu et al., 2020 ). Meanwhile, some heavy metals such As, Hg, Cd, Cr and As entered the feed along with trace element minerals (Wang et al., 2021 ). However, animals have extremely low utilization of trace elements and excrete most of them (Rensing et al., 2018 ). Since heavy metals are non-biodegradable, toxic, persistent and bioenriched, the risks to agriculture and ecology should not be ignored. Long-term application of compost products without scientific treatment will introduce a large number of heavy metals into the soil (Zhen et al., 2020 ). Heavy metal pollution has gradually become the bottleneck restricting the recycling of livestock and poultry manure through composting. In-depth understanding of heavy metal transformation and detoxification mechanisms during composting has become the key to promote the recycling of organic resources. To date, considerable efforts have been made to identify biochemical pathways of heavy metal conversion during composting. For example, Cui et al. ( 2022 ) explored the complexation of dissolved organic matter on heavy metals in the composting process; Xu et al. ( 2022 ) analyzed the influence of environmental factors on the passivation of heavy metals. However, these studies mainly focus on the macro level, and there are few studies on the transport and detoxification of heavy metals by microbial expression of HMRGs during composting. In fact, HMRGs are valuable evolutionary products, and have important ecological significance and application value for in-situ transformation of heavy metals (He et al., 2023 ; Das et al., 2016 ; Zhu et al., 2022 ). In recent years, with the rapid development of modern molecular biology and bioinformatics, the application of metagenomics has provided a large number of information resources for the study of heavy metal pollution at the genes level. With the publication of various HMRGs map information and the establishment of gene information database, more and more HMRGs are known. Since Pal et al. ( 2014 ) created the BacMet database based on a systematic review of HMRGs in the scientific literature, the BacMet database currently contains 470 HMRGs and more than 25,000 potential resistance genes obtained from the public sequence library, laying the foundation for understanding HMRGs-mediated heavy metal conversion during composting. Compost fermentation is a complex biological process, and investigating the diversity and function characteristics of HMRGs is of great significance in determining the transformation of heavy metals. This study is put forward under such thinking and background. The contents of this study include: (1) The contents and chemical speciation of Cd, Zn, Cu, Pb, Cr, As and Hg were analyzed; (2) metagenomics was used to investigate the changes of HMRGs diversity and host microorganisms in different composting phase; (3) Clarify the internal relationship between HMRGs and the transformation and detoxification of heavy metals, and construct the heavy metal transformation network. 2. Materials and methods 2.1 Composting raw materials and design In this study, sawdust from Nanning Lumber Factory was selected as carbon source, and dairy manure from Guangxi University Agricultural College was selected as nitrogen source. The physiochemical properties of raw materials are shown in Table S1 . According to the suitable moisture content of the initial fermentation is 60–70% and C/N is 25–30 (Onwosi et al., 2017 ), the sawdust and dairy manure are mixed evenly at 1:3 and the pile weight is 20kg. Compost fermentation was carried out in a 60 L compost reactor, and representative samples of the initial phase (day 0), thermophilic phase (day3 and 8), cooling phase (day 22) and maturity phase (day 50) were obtained by multi-point sampling method. The obtained samples were stored at 20°C for subsequent heavy metal and metagenomic analysis (Meng et al., 2021 ). The Change of physicochemical properties during composting are shown in Table S2. 2.2 Heavy metal analysis The concentrations of exchangeable (EXC) fraction, reducible (RED) fraction, oxidizable (OXI) fraction and residual (RES) fraction of heavy metals were extracted by an improved BCR sequential extraction procedure (Li et al., 2023 ; Niu et al., 2022 ). Briefly, EXC fraction was extracted by 0.1 mol/L acetic acid, followed by the supernatant was used for EXC fraction analysis, and the solid residue was used for RED fraction analysis. The RED fraction was extracted by 0.5 mol/L hydroxylamine hydrochloride, and then the supernatant was used for RED fraction analysis. The solid residue in the centrifuge tube was used for OXI fraction analysis. The OXI fraction was first digested by 5mL H 2 O 2 and then extracted with 1mol/L ammonium acetate after drying and cooling. The supernatant was then used for oxidizable state analysis, and the solid residue in the centrifuge tube was used for RES fraction analysis. The RES fraction is extracted with a mixture of hydrochloric acid, nitric acid, hydrofluoric acid and perchloric acid. The heavy metals extracted by the above steps were determined by ICP-AES (ICPS-7510, Shimadzu). 2.3 Metagenomics analysis 2.3.1 DNA extraction The total DNA of composting sample was extracted from (5 g) using the E.Z.N.A.® Soil DNA Kit (Omega Bio-tek, Norcross, GA, U.S.) according to the manufacturer's instructions. TBS-380 and NanoDrop 2000 are used to detect concentration and purity of extracted DNA, respectively. DNA extract quality was confirmed by electrophoresis in 1% agarose gel at a voltage of 5 V/cm for 20 min (Huang et al., 2023 ). Subsequently, all DNA samples were sent to Majorbio Bio-Pharm Technology Co., ltd. (Shanghai, China) for sequencing. 2.3.2 DNA sequencing and bioinformatic analysis Metagenome sequencing was performed on Illumina NovaSeq/Hiseq Xten (Illumina Inc., San Diego, CA, USA) using NovaSeq Reagent Kits/HiSeq X Reagent Kits. CovarisM220 was used to fragment DNA, and the fragments of about 400bp were screened. Adaptor sequences were removed, and low-quality reads (reads with N bases, minimum length of 50 bp, and minimum quality threshold of 20) were filtered using fastp (version 0.20.0). MetaGen was used to identify Open reading frames (ORFs) in contigs with a length of at least 100 bp, which were then translated into amino acid sequences using the NCBI translation table. The non-redundant gene catalog was annotated based on the NCBI NR database using blastp with an e-value cutoff of 1e − 5 . Taxonomic annotations were done using Diamond (version 0.8.35). BacMet ( https://BacMet.biomedicine.gu.se/ ) gene catalog database was searched to identify HMRGs. The raw metagenomic sequencing data from this study can be viewed in the Mendeley Data ( https://doi.org/10.17632/4jpzn5k6j4.1 ). 2.4 Statistical analysis All experiments in this study adopted three repeated experimental groups, and the experimental values were shown as average values. Excel 2019 is used for data statistics and Origin2021b is used for drawing graphics. Significance was analyzed by ANOVA in IBM SPSS Statistics 26.0, and P < 0.05 was considered to be statistically significant. Microbial and heavy metal resistance gene analyses were carried out on the Majorbio cloud platform ( https://www.Majorbio.com ). 3. Results and discussion 3.1 Variations of heavy metal contents and chemical speciation Studies on the total amount and fraction transformation of heavy metals can reveal the existence state, migration and transformation rule, bioavailability, toxicity and possible environmental effects of heavy metals, so as to predict the long-term changes and environmental risks of heavy metals. As shown in Fig. 1 , The main heavy metals in compost include Zn (126.0-141.8mg/kg), Cu (48.8-52.1mg/kg), Cr (24.4-27.1mg/kg), Hg (9.3-10.5mg/kg), Mn (131.1-145.6mg/kg), As (28.1-32.9mg/kg), Cd (2.3–3.1 mg/kg). In terms of total heavy metal content, heavy metals are concentrated due to mineralization and decomposition of organic matter during the composting process (Lu et al., 2014 ). The content of As and Hg exceeded the limit of 15 mg/kg and 2 mg/kg, respectively, compared with the Chinese organic fertilizer standard (NY525-2021). Although China does not set limits on Zn, Cu and Mn, the content of these heavy metals in the samples is very high and poses a great ecological risk. As heavy metals cannot be removed, the need to minimize the bioavailability of Zn, Cu, Mn, Hg and As in animal manure to ensure their safe recycling into agricultural soils is highlighted. From the toxicity, mobility and bioavailability of heavy metals, EXC, RED, OXI and RES fraction decreased successively (Niu et al., 2022 ; Kou et al., 2020 ). In general, aerobic compost promoted the transformation of heavy metals to more stable OXI and RES fraction. During the transformation process, the stability of heavy metals was improved while the bioavailability was decreased. In addition, Mn, As and Cr mainly exist in OXI and RES fraction, while Zn and Cu mainly exist in EXC and RED fraction. 3.2 Variation of HMRGs abundance As an important heavy metal reservoir, compost has evolved a variety of HMRGs. As shown in Fig. 2 , there are 37 HMRGs conferring resistance to 6 metals (Zn, Cu, Mn, Cd, Cr, Hg) and 1 metalloid (As) in the composting samples. It can be seen that the genes resistant to Cu, Hg and Zn are the most abundant in the composting process. copA and zntA that confer resistance to Cu and Zn, respectively, are the two HMRGS with the highest abundance in composting process. mntABCRH and merABCEPRT confer resistance to Mn and Hg (Hao et al., 2020 ), respectively, and have low abundance throughout the composting process. In addition, the abundance of some HMRG ( czcD , zitB , arsA ) increased significantly on day 3, and then gradually decreased between day 8. Therefore, these genes may be mainly regulated by the succession of bacterial communities. Overall, HMRGs are widely present in composting and plays a key role in metal(loid) metabolism. 3.3 HMRGs host microbial community succession Based on metagenomic functional gene annotation, the abundance and diversity of heavy metal resistant microorganisms in the composting process were determined, and those with relative abundance less than 1% were classified as others (Fig. 3 a). In terms of community structure, Proteobacteria (9.08%), Actinobacteria (15.25%), Firmicutes (54.25%) and Bacteroidetes (15.88%) were the predominant phylum in the early phase. With the progress of compost fermentation, the abundance of Proteobacteria increased rapidly and reached its peak at the thermophilic phase ( Proteobacteria : 62.26%). Actinobacteria were on the rise throughout the composting process, and became the main microorganism in the maturity phase. On the contrary, the abundance of Firmicutes decreased gradually throughout the composting process. In the maturity phase, Proteobacteria (38.67%) and Actinobacteria (31.04%) were the dominant phylum. Similarly, similar microbial compositions have been found in heavy metal-contaminated river sediments and soils (Jacquiod et al., 2017). In terms of the diversity of heavy metal resistant microorganisms, 54, 70, 90, 103 and 101 species of resistant bacteria were detected in the five phases (Fig. 3 b), respectively, indicating that a variety of microorganisms acquired heavy metal resistance during the composting process. Figure 3 c shows the succession of heavy metal-resistant microbial communities at the generic level, and those whose abundance was less than 1% were classified as others. At genus level, the dominant microorganisms were Corynebacterium (7.84%), Escherichia (4.93%), Clostridiumn (5.80%), Bifidobacterium (4.14%) in initial phase. Subsequently, thermophilic microorganisms gradually replaced the initial microorganisms, and the dominant genus was Pseudoxanthomonas (13.58%), Pseudomonas (5.71%), Bacillus (2.84%), Streptomyces (3.90%). In fact, there were significant differences in dominant microorganism between different compost phase. However, bacillus had advantages in thermophilic phase, cooling phase (2.83%) and maturity phase (1.95%). Although Pseudoxanthomonas was the most abundant genus in the thermophilic phase of compost, it gradually decreased in the cooling and maturity phase. Previous studies have shown that bacillus is widespread in soil and shows high resistance to heavy metals such As Zn, Cu, Cd, Co, Hg, Pb and Se, which may account for its continued dominance in composting (Long et al., 2021 ). At the genus level, a total of 1196, 2036, 2237, 2084 and 1958 species of resistant bacteria were detected in the samples from 5 different phases (Fig. 3 d), respectively, among which 681 bacteria genera were shared in different periods of composting, which once again proved the diversity of heavy metal resistant microorganisms in the composting process. 3.4 Heavy metal transformation mediated by HMRGs Combining the summaries of HMRGs by pal et al. ( 2014 ) and He et al. ( 2023 ), it was found that the mechanisms of HMRGs mediated metal tolerance and detoxification in the compost habitat include extracellular isolation, osmotic barrier, active efflux, enzymatic detoxification, intracellular isolation, and reduced metal sensitivity (Fig. 4 ). HMRGs with extracellular isolation, permeability barrier, and active efflux functions can improve microbial adaptability to heavy metal environments and chelate heavy metals via cellular secretions (biosurfactants or extracellular polymers). This kind of HMRGs mainly come from Zn ( znuABC , zitB , zntA ), Cu ( cusABCRS , copAB ), Mn ( mntABCH ). In addition, for some non-essential elements of microorganisms (As, Cr, Hg, Cd), HMRGs can achieve in-situ detoxification of heavy metals and reduce the sensitivity of heavy metals by expressing resistance proteins to drive redox, methylation and demethylation. The microbial pathway encoded by the mer operon, which includes 4 distinct genes ( merA , merB , merR , and merH ), enzymatically reduces intracellular Hg 2+ to Hg 0 . Efficient green strategies for reducing Hg 2+ based on mer systems have shown potential for remediation and management of Hg contaminated environments (He et al., 2023 ). chrR belongs to Cr reductase gene, which can encode Cr resistance protein and convert highly toxic Cr 5+ into less toxic Cr 3+ , and then precipitate in the form of chromium hydroxide. axoA can encode As oxidase, which oxidizes highly toxic As 3+ to less toxic As 5+ , and can be converted to less toxic methylated arsenic through arsH . cueO is a gene encoding periplasmic polycopper oxidase that can oxidize Cu + to Cu 2+ with low toxicity. Cd associated HMRGs are mainly derived from cad operons and czc operons, which precipitate Cd under the combined action of cadC and metallothionein. The above studies indicate that the presence of these HMRGs is an important driving force for the transformation and detoxification of heavy metals during composting. 4. Conclusion HMRGs play an important role in heavy metal tolerance and detoxification during composting. For Zn, Cu and Mn, HMRGs mediated metal tolerance and detoxification mechanisms are mainly through extracellular isolation, osmotic barrier and active efflux. For Hg, As, Cd and Cr, the main mechanisms of metal tolerance and detoxification mediated by HMRGs are enzymatic detoxification, methylation and redox. The heavy metal metabolic relationship obtained from compost is expected to provide ideas for in-situ remediation of heavy metal pollution in the future. Declarations Acknowledgements This work was funded by the National Natural Science Foundation of China (No. 21878057). The authors also thank other members of our laboratory for their constructive advice and scientific assistance. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. CRediT authorship contribution statement Xiaoya Qin: Data curation, Methodology, Investigation, Formal analysis, Writing-original draft. Qunliang Li: Conceptualization, Supervision, Funding acquisition, Writing-review & editing. Ethical approval and consent to participate: Not applicable. Consent for publication: Not applicable. References Chen, X., Zhao, Y., Zhang, C., Zhang, D., Yao, C., Meng, Q., Zhao, R., Wei, Z., 2020. Speciation, toxicity mechanism and remediation ways of heavy metals during composting: A novel theoretical microbial remediation method is proposed. J. Environ. Manage. 272, 111109. https://doi.org/10.1016/j.jenvman.2020.111109. Cui, H., Zhao, Y., Zhao, L., Wei, Z., 2022. 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Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 17 Jun, 2024 Read the published version in Environmental Science and Pollution Research → Version 1 posted Editorial decision: Major Revision 03 May, 2024 Reviewers agreed at journal 25 Mar, 2024 Reviewers invited by journal 10 Mar, 2024 Editor invited by journal 07 Mar, 2024 Editor assigned by journal 04 Mar, 2024 First submitted to journal 29 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3999849","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277998367,"identity":"9c605832-d7d0-411c-b827-b1f6648721c8","order_by":0,"name":"Xiaoya Qin","email":"","orcid":"","institution":"Guangxi University College of Chemistry and Chemical Engineering","correspondingAuthor":false,"prefix":"","firstName":"Xiaoya","middleName":"","lastName":"Qin","suffix":""},{"id":277998368,"identity":"ef3d278c-122b-42c3-9a0e-f831ae5a4422","order_by":1,"name":"Qunliang 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07:05:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":401734,"visible":true,"origin":"","legend":"\u003cp\u003eAbundance analysis of HMRGs during composting\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3999849/v1/260f3b80ae7a8bf03fe53a69.png"},{"id":52578047,"identity":"15c3df98-f6e4-4e3d-9aa7-8b71facb67c4","added_by":"auto","created_at":"2024-03-13 07:13:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":709848,"visible":true,"origin":"","legend":"\u003cp\u003eSuccession of heavy metal resistant microorganisms at (a, b) phylum and (c, d) genus levels.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3999849/v1/bd3f388f01c06bbe3afa9af2.png"},{"id":52577537,"identity":"9dd3ed0c-1038-4d22-ba8a-c151d665ca1c","added_by":"auto","created_at":"2024-03-13 07:05:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":234170,"visible":true,"origin":"","legend":"\u003cp\u003eHeavy metal tolerance and detoxification mechanism mediated by HMRGs in compost habitat.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3999849/v1/e089a03e81b00fcfe4cc3d1a.png"},{"id":58822433,"identity":"6990e18a-e0cd-4168-8b2a-1d89d9c8940d","added_by":"auto","created_at":"2024-06-21 16:43:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1963662,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3999849/v1/82a77559-d22b-4fa3-b47a-944d468056ed.pdf"},{"id":52577539,"identity":"74f0efd1-5d0d-474c-aa49-9e8d4bf77fe9","added_by":"auto","created_at":"2024-03-13 07:05:37","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":13196,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3999849/v1/967a795835015183aefec04d.docx"}],"financialInterests":"","formattedTitle":"Heavy metal tolerance and detoxification mechanism mediated by heavy metal resistance genes in compost habitat","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHeavy metal pollution is an important factor limiting the land use of livestock manure composting products, and how to reduce the toxicity of heavy metals is the focus of resource recycling and sustainable development (Chen et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The heavy metals in compost mainly come from livestock and poultry manure in intensive farming, and micronutrients (Zn and Cu) are widely added to animal feed (Rensing et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Meanwhile, some heavy metals such As, Hg, Cd, Cr and As entered the feed along with trace element minerals (Wang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, animals have extremely low utilization of trace elements and excrete most of them (Rensing et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Since heavy metals are non-biodegradable, toxic, persistent and bioenriched, the risks to agriculture and ecology should not be ignored. Long-term application of compost products without scientific treatment will introduce a large number of heavy metals into the soil (Zhen et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Heavy metal pollution has gradually become the bottleneck restricting the recycling of livestock and poultry manure through composting. In-depth understanding of heavy metal transformation and detoxification mechanisms during composting has become the key to promote the recycling of organic resources.\u003c/p\u003e \u003cp\u003eTo date, considerable efforts have been made to identify biochemical pathways of heavy metal conversion during composting. For example, Cui et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) explored the complexation of dissolved organic matter on heavy metals in the composting process; Xu et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) analyzed the influence of environmental factors on the passivation of heavy metals. However, these studies mainly focus on the macro level, and there are few studies on the transport and detoxification of heavy metals by microbial expression of HMRGs during composting. In fact, HMRGs are valuable evolutionary products, and have important ecological significance and application value for in-situ transformation of heavy metals (He et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Das et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In recent years, with the rapid development of modern molecular biology and bioinformatics, the application of metagenomics has provided a large number of information resources for the study of heavy metal pollution at the genes level. With the publication of various HMRGs map information and the establishment of gene information database, more and more HMRGs are known. Since Pal et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) created the BacMet database based on a systematic review of HMRGs in the scientific literature, the BacMet database currently contains 470 HMRGs and more than 25,000 potential resistance genes obtained from the public sequence library, laying the foundation for understanding HMRGs-mediated heavy metal conversion during composting.\u003c/p\u003e \u003cp\u003eCompost fermentation is a complex biological process, and investigating the diversity and function characteristics of HMRGs is of great significance in determining the transformation of heavy metals. This study is put forward under such thinking and background. The contents of this study include: (1) The contents and chemical speciation of Cd, Zn, Cu, Pb, Cr, As and Hg were analyzed; (2) metagenomics was used to investigate the changes of HMRGs diversity and host microorganisms in different composting phase; (3) Clarify the internal relationship between HMRGs and the transformation and detoxification of heavy metals, and construct the heavy metal transformation network.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Composting raw materials and design\u003c/h2\u003e \u003cp\u003eIn this study, sawdust from Nanning Lumber Factory was selected as carbon source, and dairy manure from Guangxi University Agricultural College was selected as nitrogen source. The physiochemical properties of raw materials are shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. According to the suitable moisture content of the initial fermentation is 60\u0026ndash;70% and C/N is 25\u0026ndash;30 (Onwosi et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the sawdust and dairy manure are mixed evenly at 1:3 and the pile weight is 20kg. Compost fermentation was carried out in a 60 L compost reactor, and representative samples of the initial phase (day 0), thermophilic phase (day3 and 8), cooling phase (day 22) and maturity phase (day 50) were obtained by multi-point sampling method. The obtained samples were stored at 20\u0026deg;C for subsequent heavy metal and metagenomic analysis (Meng et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Change of physicochemical properties during composting are shown in Table S2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Heavy metal analysis\u003c/h2\u003e \u003cp\u003eThe concentrations of exchangeable (EXC) fraction, reducible (RED) fraction, oxidizable (OXI) fraction and residual (RES) fraction of heavy metals were extracted by an improved BCR sequential extraction procedure (Li et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Niu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Briefly, EXC fraction was extracted by 0.1 mol/L acetic acid, followed by the supernatant was used for EXC fraction analysis, and the solid residue was used for RED fraction analysis. The RED fraction was extracted by 0.5 mol/L hydroxylamine hydrochloride, and then the supernatant was used for RED fraction analysis. The solid residue in the centrifuge tube was used for OXI fraction analysis. The OXI fraction was first digested by 5mL H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and then extracted with 1mol/L ammonium acetate after drying and cooling. The supernatant was then used for oxidizable state analysis, and the solid residue in the centrifuge tube was used for RES fraction analysis. The RES fraction is extracted with a mixture of hydrochloric acid, nitric acid, hydrofluoric acid and perchloric acid. The heavy metals extracted by the above steps were determined by ICP-AES (ICPS-7510, Shimadzu).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Metagenomics analysis\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 DNA extraction\u003c/h2\u003e \u003cp\u003eThe total DNA of composting sample was extracted from (5 g) using the E.Z.N.A.\u0026reg; Soil DNA Kit (Omega Bio-tek, Norcross, GA, U.S.) according to the manufacturer's instructions. TBS-380 and NanoDrop 2000 are used to detect concentration and purity of extracted DNA, respectively. DNA extract quality was confirmed by electrophoresis in 1% agarose gel at a voltage of 5 V/cm for 20 min (Huang et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Subsequently, all DNA samples were sent to Majorbio Bio-Pharm Technology Co., ltd. (Shanghai, China) for sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 DNA sequencing and bioinformatic analysis\u003c/h2\u003e \u003cp\u003eMetagenome sequencing was performed on Illumina NovaSeq/Hiseq Xten (Illumina Inc., San Diego, CA, USA) using NovaSeq Reagent Kits/HiSeq X Reagent Kits. CovarisM220 was used to fragment DNA, and the fragments of about 400bp were screened. Adaptor sequences were removed, and low-quality reads (reads with N bases, minimum length of 50 bp, and minimum quality threshold of 20) were filtered using fastp (version 0.20.0). MetaGen was used to identify Open reading frames (ORFs) in contigs with a length of at least 100 bp, which were then translated into amino acid sequences using the NCBI translation table. The non-redundant gene catalog was annotated based on the NCBI NR database using blastp with an e-value cutoff of 1e\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. Taxonomic annotations were done using Diamond (version 0.8.35). BacMet (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://BacMet.biomedicine.gu.se/\u003c/span\u003e\u003cspan address=\"https://BacMet.biomedicine.gu.se/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) gene catalog database was searched to identify HMRGs. The raw metagenomic sequencing data from this study can be viewed in the Mendeley Data (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17632/4jpzn5k6j4.1\u003c/span\u003e\u003cspan address=\"10.17632/4jpzn5k6j4.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eAll experiments in this study adopted three repeated experimental groups, and the experimental values were shown as average values. Excel 2019 is used for data statistics and Origin2021b is used for drawing graphics. Significance was analyzed by ANOVA in IBM SPSS Statistics 26.0, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to be statistically significant. Microbial and heavy metal resistance gene analyses were carried out on the Majorbio cloud platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.Majorbio.com\u003c/span\u003e\u003cspan address=\"https://www.Majorbio.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Variations of heavy metal contents and chemical speciation\u003c/h2\u003e \u003cp\u003eStudies on the total amount and fraction transformation of heavy metals can reveal the existence state, migration and transformation rule, bioavailability, toxicity and possible environmental effects of heavy metals, so as to predict the long-term changes and environmental risks of heavy metals. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, The main heavy metals in compost include Zn (126.0-141.8mg/kg), Cu (48.8-52.1mg/kg), Cr (24.4-27.1mg/kg), Hg (9.3-10.5mg/kg), Mn (131.1-145.6mg/kg), As (28.1-32.9mg/kg), Cd (2.3\u0026ndash;3.1 mg/kg). In terms of total heavy metal content, heavy metals are concentrated due to mineralization and decomposition of organic matter during the composting process (Lu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The content of As and Hg exceeded the limit of 15 mg/kg and 2 mg/kg, respectively, compared with the Chinese organic fertilizer standard (NY525-2021). Although China does not set limits on Zn, Cu and Mn, the content of these heavy metals in the samples is very high and poses a great ecological risk. As heavy metals cannot be removed, the need to minimize the bioavailability of Zn, Cu, Mn, Hg and As in animal manure to ensure their safe recycling into agricultural soils is highlighted. From the toxicity, mobility and bioavailability of heavy metals, EXC, RED, OXI and RES fraction decreased successively (Niu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In general, aerobic compost promoted the transformation of heavy metals to more stable OXI and RES fraction. During the transformation process, the stability of heavy metals was improved while the bioavailability was decreased. In addition, Mn, As and Cr mainly exist in OXI and RES fraction, while Zn and Cu mainly exist in EXC and RED fraction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Variation of HMRGs abundance\u003c/h2\u003e \u003cp\u003eAs an important heavy metal reservoir, compost has evolved a variety of HMRGs. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, there are 37 HMRGs conferring resistance to 6 metals (Zn, Cu, Mn, Cd, Cr, Hg) and 1 metalloid (As) in the composting samples. It can be seen that the genes resistant to Cu, Hg and Zn are the most abundant in the composting process. \u003cem\u003ecopA\u003c/em\u003e and \u003cem\u003ezntA\u003c/em\u003e that confer resistance to Cu and Zn, respectively, are the two HMRGS with the highest abundance in composting process. \u003cem\u003emntABCRH\u003c/em\u003e and \u003cem\u003emerABCEPRT\u003c/em\u003e confer resistance to Mn and Hg (Hao et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), respectively, and have low abundance throughout the composting process. In addition, the abundance of some HMRG (\u003cem\u003eczcD\u003c/em\u003e, \u003cem\u003ezitB\u003c/em\u003e, \u003cem\u003earsA\u003c/em\u003e) increased significantly on day 3, and then gradually decreased between day 8. Therefore, these genes may be mainly regulated by the succession of bacterial communities. Overall, HMRGs are widely present in composting and plays a key role in metal(loid) metabolism.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 HMRGs host microbial community succession\u003c/h2\u003e \u003cp\u003eBased on metagenomic functional gene annotation, the abundance and diversity of heavy metal resistant microorganisms in the composting process were determined, and those with relative abundance less than 1% were classified as others (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). In terms of community structure, \u003cem\u003eProteobacteria\u003c/em\u003e (9.08%), \u003cem\u003eActinobacteria\u003c/em\u003e (15.25%), \u003cem\u003eFirmicutes\u003c/em\u003e (54.25%) and \u003cem\u003eBacteroidetes\u003c/em\u003e (15.88%) were the predominant phylum in the early phase. With the progress of compost fermentation, the abundance of \u003cem\u003eProteobacteria\u003c/em\u003e increased rapidly and reached its peak at the thermophilic phase (\u003cem\u003eProteobacteria\u003c/em\u003e: 62.26%). \u003cem\u003eActinobacteria\u003c/em\u003e were on the rise throughout the composting process, and became the main microorganism in the maturity phase. On the contrary, the abundance of \u003cem\u003eFirmicutes\u003c/em\u003e decreased gradually throughout the composting process. In the maturity phase, \u003cem\u003eProteobacteria\u003c/em\u003e (38.67%) and \u003cem\u003eActinobacteria\u003c/em\u003e (31.04%) were the dominant phylum. Similarly, similar microbial compositions have been found in heavy metal-contaminated river sediments and soils (Jacquiod et al., 2017). In terms of the diversity of heavy metal resistant microorganisms, 54, 70, 90, 103 and 101 species of resistant bacteria were detected in the five phases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), respectively, indicating that a variety of microorganisms acquired heavy metal resistance during the composting process.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec shows the succession of heavy metal-resistant microbial communities at the generic level, and those whose abundance was less than 1% were classified as others. At genus level, the dominant microorganisms were \u003cem\u003eCorynebacterium\u003c/em\u003e (7.84%), \u003cem\u003eEscherichia\u003c/em\u003e (4.93%), \u003cem\u003eClostridiumn\u003c/em\u003e (5.80%), \u003cem\u003eBifidobacterium\u003c/em\u003e (4.14%) in initial phase. Subsequently, thermophilic microorganisms gradually replaced the initial microorganisms, and the dominant genus was \u003cem\u003ePseudoxanthomonas\u003c/em\u003e (13.58%), \u003cem\u003ePseudomonas\u003c/em\u003e (5.71%), \u003cem\u003eBacillus\u003c/em\u003e (2.84%), \u003cem\u003eStreptomyces\u003c/em\u003e (3.90%). In fact, there were significant differences in dominant microorganism between different compost phase. However, bacillus had advantages in thermophilic phase, cooling phase (2.83%) and maturity phase (1.95%). Although \u003cem\u003ePseudoxanthomonas\u003c/em\u003e was the most abundant genus in the thermophilic phase of compost, it gradually decreased in the cooling and maturity phase. Previous studies have shown that bacillus is widespread in soil and shows high resistance to heavy metals such As Zn, Cu, Cd, Co, Hg, Pb and Se, which may account for its continued dominance in composting (Long et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). At the genus level, a total of 1196, 2036, 2237, 2084 and 1958 species of resistant bacteria were detected in the samples from 5 different phases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), respectively, among which 681 bacteria genera were shared in different periods of composting, which once again proved the diversity of heavy metal resistant microorganisms in the composting process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Heavy metal transformation mediated by HMRGs\u003c/h2\u003e \u003cp\u003eCombining the summaries of HMRGs by pal et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and He et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), it was found that the mechanisms of HMRGs mediated metal tolerance and detoxification in the compost habitat include extracellular isolation, osmotic barrier, active efflux, enzymatic detoxification, intracellular isolation, and reduced metal sensitivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). HMRGs with extracellular isolation, permeability barrier, and active efflux functions can improve microbial adaptability to heavy metal environments and chelate heavy metals via cellular secretions (biosurfactants or extracellular polymers). This kind of HMRGs mainly come from Zn (\u003cem\u003eznuABC\u003c/em\u003e, \u003cem\u003ezitB\u003c/em\u003e, \u003cem\u003ezntA\u003c/em\u003e), Cu (\u003cem\u003ecusABCRS\u003c/em\u003e, \u003cem\u003ecopAB\u003c/em\u003e), Mn (\u003cem\u003emntABCH\u003c/em\u003e). In addition, for some non-essential elements of microorganisms (As, Cr, Hg, Cd), HMRGs can achieve in-situ detoxification of heavy metals and reduce the sensitivity of heavy metals by expressing resistance proteins to drive redox, methylation and demethylation. The microbial pathway encoded by the \u003cem\u003emer\u003c/em\u003e operon, which includes 4 distinct genes (\u003cem\u003emerA\u003c/em\u003e, \u003cem\u003emerB\u003c/em\u003e, \u003cem\u003emerR\u003c/em\u003e, and \u003cem\u003emerH\u003c/em\u003e), enzymatically reduces intracellular Hg\u003csup\u003e2+\u003c/sup\u003e to Hg\u003csup\u003e0\u003c/sup\u003e. Efficient green strategies for reducing Hg\u003csup\u003e2+\u003c/sup\u003e based on \u003cem\u003emer\u003c/em\u003e systems have shown potential for remediation and management of Hg contaminated environments (He et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003echrR\u003c/em\u003e belongs to Cr reductase gene, which can encode Cr resistance protein and convert highly toxic Cr\u003csup\u003e5+\u003c/sup\u003e into less toxic Cr\u003csup\u003e3+\u003c/sup\u003e, and then precipitate in the form of chromium hydroxide. \u003cem\u003eaxoA\u003c/em\u003e can encode As oxidase, which oxidizes highly toxic As\u003csup\u003e3+\u003c/sup\u003e to less toxic As\u003csup\u003e5+\u003c/sup\u003e, and can be converted to less toxic methylated arsenic through \u003cem\u003earsH\u003c/em\u003e. \u003cem\u003ecueO\u003c/em\u003e is a gene encoding periplasmic polycopper oxidase that can oxidize Cu\u003csup\u003e+\u003c/sup\u003e to Cu\u003csup\u003e2+\u003c/sup\u003e with low toxicity. Cd associated HMRGs are mainly derived from \u003cem\u003ecad\u003c/em\u003e operons and \u003cem\u003eczc\u003c/em\u003e operons, which precipitate Cd under the combined action of \u003cem\u003ecadC\u003c/em\u003e and metallothionein. The above studies indicate that the presence of these HMRGs is an important driving force for the transformation and detoxification of heavy metals during composting.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eHMRGs play an important role in heavy metal tolerance and detoxification during composting. For Zn, Cu and Mn, HMRGs mediated metal tolerance and detoxification mechanisms are mainly through extracellular isolation, osmotic barrier and active efflux. For Hg, As, Cd and Cr, the main mechanisms of metal tolerance and detoxification mediated by HMRGs are enzymatic detoxification, methylation and redox. The heavy metal metabolic relationship obtained from compost is expected to provide ideas for in-situ remediation of heavy metal pollution in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the National Natural Science Foundation of China (No. 21878057). The authors also thank other members of our laboratory for their constructive advice and scientific assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eXiaoya Qin:\u003c/strong\u003e Data curation, Methodology, Investigation, Formal analysis, Writing-original draft. \u003cstrong\u003eQunliang Li:\u003c/strong\u003e Conceptualization, Supervision, Funding acquisition, Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, X., Zhao, Y., Zhang, C., Zhang, D., Yao, C., Meng, Q., Zhao, R., Wei, Z., 2020. 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Technol. 56(15), 10656\u0026ndash;10667. https://doi.org/10.1021/acs.est.2c00488.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Composting, Heavy metal, Heavy metal resistance genes, Microorganisms, Metagenomics","lastPublishedDoi":"10.21203/rs.3.rs-3999849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3999849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeavy metal pollution from compost is one of the most concerned environmental problems, which poses a threat to the ecosystem and human health. This study aims to reveal the heavy metal tolerance and detoxification mechanism mediated by heavy metal resistance genes (HMRGs) in compost habitat through metagenomics combined with chemical speciation analysis of heavy metals. The results showed that there were 37 HMRGs corresponding to 7 common heavy metal(loid)s in composting, and they had the ability to transform heavy metals into stable or low-toxic speciation by regulating enzyme transport, redox and methylation, etc. This study summarized the heavy metal metabolism pathway mediated by HMRGs, providing a new perspective for understanding the transformation of heavy metals in the composting process.\u003c/p\u003e","manuscriptTitle":"Heavy metal tolerance and detoxification mechanism mediated by heavy metal resistance genes in compost habitat","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-13 07:05:32","doi":"10.21203/rs.3.rs-3999849/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2024-05-03T11:55:16+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-03-25T16:51:22+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-10T22:21:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Environmental Science and Pollution Research","date":"2024-03-07T17:34:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-05T04:37:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2024-02-29T05:01:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"91426145-63f7-4650-a1c8-bf8216804276","owner":[],"postedDate":"March 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-21T14:54:52+00:00","versionOfRecord":{"articleIdentity":"rs-3999849","link":"https://doi.org/10.1007/s11356-024-33925-3","journal":{"identity":"environmental-science-and-pollution-research","isVorOnly":false,"title":"Environmental Science and Pollution Research"},"publishedOn":"2024-06-17 14:54:52","publishedOnDateReadable":"June 17th, 2024"},"versionCreatedAt":"2024-03-13 07:05:32","video":"","vorDoi":"10.1007/s11356-024-33925-3","vorDoiUrl":"https://doi.org/10.1007/s11356-024-33925-3","workflowStages":[]},"version":"v1","identity":"rs-3999849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3999849","identity":"rs-3999849","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}