Analysis of factors affecting rhizospheric impacts on microelement cycling under drought stress

Microelements are vital for regulating organismal growth and maintaining ecosystem structures and functions. Microorganisms help cycle microelements in soil; however, their regulatory mechanisms in dry desert regions remain unclear. To address this research gap, we performed metagenomic sequencing to analyze the rhizospheric microbiological community structures and functional gene profiles of three typical halophyte bushes in the Ebinur Lake Basin under natural drought stress gradients to reveal the response mechanisms of the functional genes of soil microbial microelements on rhizospheric effects and drought stress. As drought stress decreased, sand significantly decreased, whereas silt and soil organic carbon (OM) significantly increased ( P < 0.05). In the key pathways of the microelement cycle, cbiN for Ni and Co transport, znuA for Zn transport, mntBC for Mn) transport, sitABCD for Fe and Mn transport, and nikC for Ni transport showed a significant positive correlation with drought intensity, suggesting enhanced microelement transport under drought conditions. BG and NAG significantly affected the functional genes of soil microelement transport processes in the rhizosphere under mild to moderate drought, whereas silt and clay significantly affected the functional genes of the soil microelement transport process in the rhizosphere under severe drought stress. Proteobacteria and Actinobacteria were the dominant microbial taxa that participated in soil microelement cycling. Overall, the microbial regulation of soil microelement cycling was jointly influenced by drought stress and rhizospheric effects. These findings enhance our understanding of the microelement cycling mechanisms in arid regions and provide new theoretical and scientific support for studying material cycling in desert ecosystems. Analysis of factors affecting rhizospheric impacts on microelement cycling under drought stress Meiyu Wang a,b, Wenjing Li a,b*, Hengfang Wang a, b, Guanghui Lv a, b a College of Ecology and Environment, Xinjiang University, Urumqi Xinjiang, 830017, China b Key Laboratory of Oasis Ecology of Education Ministry, Xinjiang University, Urumqi 830017, China *Corresponding author: Wenjing Li E-mail: [email protected] Address: College of Ecology and Environment, Xinjiang University, Urumqi 830017, China Running title: Factors affecting microelement cycling

Microelements are vital for regulating organismal growth and maintaining ecosystem structures and functions. Microorganisms help cycle microelements in soil; however, their regulatory mechanisms in dry desert regions remain unclear. To address this research gap, we performed metagenomic sequencing to analyze the rhizospheric microbiological community structures and functional gene profiles of three typical halophyte bushes in the Ebinur Lake Basin under natural drought stress gradients to reveal the response mechanisms of the functional genes of soil microbial microelements on rhizospheric effects and drought stress. As drought stress decreased, sand significantly decreased, whereas silt and soil organic carbon (OM) significantly increased ( P < 0.05). In the key pathways of the microelement cycle, cbiN for Ni and Co transport, znuA for Zn transport, mntBC for Mn) transport, sitABCD for Fe and Mn transport, and nikC for Ni transport showed a significant positive correlation with drought intensity, suggesting enhanced microelement transport under drought conditions. BG and NAG significantly affected the functional genes of soil microelement transport processes in the rhizosphere under mild to moderate drought, whereas silt and clay significantly affected the functional genes of the soil microelement transport process in the rhizosphere under severe drought stress. Proteobacteria and Actinobacteria were the dominant microbial taxa that participated in soil microelement cycling. Overall, the microbial regulation of soil microelement cycling was jointly influenced by drought stress and rhizospheric effects. These findings enhance our understanding of the microelement cycling mechanisms in arid regions and provide new theoretical and scientific support for studying material cycling in desert ecosystems.

Drought stress, Rhizosphere, Microelement cycle, Influencing factors，Desert ecosystem 1.Introduction Microelements play crucial regulatory roles in ecological activities and biogeochemical cycles (Moreno-Jiménez et al., 2023). Soil microelements are essential for all organisms, and strongly influence the structures and functions of ecosystems. In terrestrial ecosystems, microelement cycles include biological, chemical, and physical processes such as plant uptake, biotransformation, chemical fixation, and dissolution reactions. The physicochemical processes of microelements in the soil include adsorption-desorption, solution complexation, oxidation-reduction, and precipitation-dissolution processes (Caporale et al., 2016). Microelements are important for plants; for example, iron and manganese are essential for numerous physiological functions in plants, including respiration, chlorophyll synthesis, and photosynthesis. However, little is known about the factors that influence microelements (Ochoa-Hueso et al., 2023). Unlike in the soil microenvironment, plant root activity influences the rhizosphere. Functioning as an active boundary for nutrient and energy transfer between the soil and plants, root systems increase metal availability through alterations in dissolved organic carbon concentrations, subsequently regulating soil micronutrient availability (Nguyen et al., 2017). Rhizosphere exudates can form root microenvironments, and their secretion rate and chemical composition can affect changes in soil microelements introduced by plants (Antoniadis et al., 2017). Simultaneously, through the exudation of diverse chemical compounds into the rhizosphere, plant roots modify both soil physicochemical characteristics and microbial community composition and regulate their relationship with microorganisms, thereby improving the living environment of microorganisms (Huang et al., 2014; Nihorimbere et al., 2011; Zhao et al., 2020). Similarly, rhizosphere microorganisms secrete organic acids that enhance the plant root acquisition of microelements (Rajkumare et al., 2012). However, current research has not elucidated the microbial species that pivotally affect the biogeochemical cycling of microelements. Water scarcity is a key limiting factor of microbial functions and nutrient transformations in arid regions. Drought stress can adversely affect plant morphological, physiological, and biochemical processes, promoting increased root depth and density and thereby changing the distribution and composition of microorganisms (Gu et al., 2023). Drought may change the mobility and bioavailability of microelements directly or indirectly by affecting the leaching of minerals and activity of microorganisms (Mu et al., 2023), which diminishes the root uptake of microelements and alters their spatial allocation within plant tissues (Peuke and Rennenberg, 2011). Aridity affects environmental factors in desert soil environments, notably affecting the percentage composition of different soil particles (silt, clay, and sand); this, in turn, affects soil nutrients and soil structures, and thus indirectly affects soil microorganisms. However, the effects of soil characteristics on micronutrient dynamics in arid zone vegetation remain unclear. To address this research gap, in this study, metagenomics was used to analyze the responses of soil microorganisms to drought stress and rhizosphere effects, as this information can provide useful insights into analyzing the strategies of microorganisms to adapt to environmental changes. This study aimed to: 1) uncover shifts in the soil microbial community composition and microelement cycling genes with the degree of drought stress, 2) explore the effect of the rhizosphere on microelement cycle-related genes, and 3) explore the influencing factors of the microbial microelement cycle under drought stress. 2. Materials and Methods 2.1 Summary of the study region The Ebinur Lake Wetland National Nature Reserve (EWNR) spans between 44°30′ to 45°09′ N and 82°36′ to 83°50′ E. This expansive protected area covers approximately 2,670.85 km². EWNR exhibits a characteristically temperate continental arid climate, averaging 7.8°C annually. This region experiences sparse rainfall; however, the evaporation rates are high throughout the year. The annual mean precipitation is 90–160 mm, with 2722.6 h of sunshine, and the annual moisture evaporation reaches 1662 mm. EWNR soils have high salinity and alkalinity (Zhang et al., 2016). The long-term scarcity of precipitation and strong evaporation cause the local ecological community to undergo severe moisture stress, and the vegetation coverage areas are saline-alkali land and meadow soil. EWNR ecosystems are fragile. The vegetation distribution in the reserve is affected by the flora of Central Asia and Mongolia, and the transition is obvious. The EWNR has the largest number of eremophyte species in Xinjiang and is sensitive to water content and vegetation declines (Yang et al., 2017). Sparse arid-resistant shrubs characterize this region’s zonal vegetation, with Reaumuria soongorica, Alhagi sparsifolia and Nitraria tangutorum being the three predominant species. 2.2 Study plot setting and sample acquisition During June 2019, the boundary zone between the Aqiksu River and Muttar Desert within the Ebinur Lake Wetland Nature Reserve was selected for this study. Within a 5 km natural hydrological gradient, three 30 m 2 × 30 m 2 standard quadrats (designated A, B, and C) were laid according to a 1.7 km spacing. The spatial distribution showed a gradual increase in distance from the riverbank. There is a distinct moisture gradient in this area, and the groundwater depth decreases with increasing distance from the Aqikesu River (Yang et al., 2019). The measured data confirmed the soil water content gradient in this study. The water content of surface soil (0–30 cm) was measured as follows: A (15.51 ± 0.61%), B (8.87 ± 0.77%), and C (3.34 ± 0.26%), and the plots were divided into high, medium, and low soil water content (SWC) plots (Li et al., 2022). According to the soil moisture measurements and China’s agricultural soil drought grade standard (GB / T32136-2015), when the soil moisture content ranges between 12–15%, a mild drought state (MiD) is in effect. When the moisture content is reduced to approximately 8%, the moderate drought state (MoD) has been reached. If the water content is less than 5%, this is considered a severe drought condition (SD) (Zhou et al., 2022). Therefore, plants in the three studied plots were subjected to mild, moderate, and severe drought stress, respectively (Yang et al., 2022). Each plot contained representative shrub species from Alhagi sparsifolia, Nitraria tangutorum, and Reaumuria soongorica, which are found in desert ecosystems. Soil samples were collected on June 25, 2019, and three consecutive sunny days were selected. In each plot, nine individuals of different plant species were selected, and three repeated soil samples were set for uniform mixing. Among the 54 composite samples obtained, 11 did not satisfy the sequencing-level DNA standards because of the limited abundance of bulk soil microorganisms in desert ecosystems. To analyze the macrogenomic data, 16 bulk and 27 rhizosphere soil samples were evaluated. Rhizosphere soil samples were collected using a previously described methodology (Edwards et al., 2015; Bram et al., 2017; Li et al., 2018). A sterilized shovel was used to extract the plant roots. After cleaning the root surface with loose soil and placing the roots in sterile bags, the samples were stored in a car refrigerator. Following root collection, samples were rapidly transferred to the laboratory and placed in a prepared phosphate-buffered saline (PBS) solution. The external soil on the roots was washed with disinfected tongs. Rhizosphere samples were condensed by centrifugation (-4 °C, 10,000 g, for 1 min). Bulk soil samples (fresh weight of approximately 50 g) were collected at 30–40 cm away from the plant and 30 cm deep. After collection, the samples were preserved in sterile bags. Two samples were simultaneously collected, with one used for metagenomics (transported back to the laboratory with a car refrigerator and stored at -80 °C), and the other for measuring soil physicochemical properties (soil enzymes were stored at -4 °C). 2.3 Analysis of soil physicochemical properties and nutrient contents 2.3.1 Soil physicochemical properties After transportation to the laboratory, the soil samples were pretreated as previously described (Edwards et al., 2015). Soil water content (SWC) was measured using the drying method. At a water–soil ratio of 2.5:1, the soil pH and EC were determined using a PHS-3C pH meter (LABO-HUB, China) and a DDSJ-319L conductivity meter (INESA Scientific Instrument Co., Ltd.), respectively. The organic carbon content was quantitatively analyzed using the potassium dichromate oxidation method. 2.3.2 Soil texture determination The composition of soil particles was measured by Microtrac (USA) S3500 laser particle size analyzer. The content distribution of sand (0.05–2 mm), silt (0.002–0.05 mm) and clay (<0.002 mm) was analyzed. 2.3.3 Soil enzyme analysis To gauge the activity of enzymes vital to phosphorus (alkaline phosphatase, AP), nitrogen (N-acetyl-β-D-glucosidase, NAG, and leucine aminopeptidase, LAP), and carbon cycles (β-1,4-glucosidase, BG), which are all important components of the soil ecosystem, we used the extracellular enzyme detection kit manufactured by Suzhou Keming Biotechnology Co., Ltd. (China). Multifunctional enzyme labeling was used to detect the fluorescence signal, and the microplate fluorescence quantitative technique was used to perform the analysis. The absorbance detection wavelengths for AP, NAG, LAP, and BG were set at 660, 405, and 400 nm, respectively. 2.4 Detection of soil microorganisms 2.4.1 DNA extraction, library construction, and sequencing Rhizosphere soil was separated and enriched as previously described (Edwards et al., 2015). Samples (0.2 g) of soil (rhizosphere or bulk) were weighed and placed in 2 mL sterile test tubes. DNA was extracted using a soil DNA kit (OMEGA BioTek E.Z.N.A.). DNA integrity was evaluated by 1% agarose gel electrophoresis, and the concentration was determined by Qubit 2.0 Fluorometer (ThermoFisher Scientific, USA). DNA samples were placed in a Covaris (USA) S220 Ultrasonicator for fragmentation to construct a double-end sequencing library. Upon completion of 12 bridge-PCR cycles, the amplified DNA clusters were transferred to an Illumina (USA) cBot. After quantitative detection of the library using a Thermo (USA) Qubit 4.0, sequencing and analysis of the constructed libraries were performed. Paired-end sequencing was performed using an Illumina (USA) Genome Analyzer. 2.4.2 Bioinformatics analysis To obtain relatively accurate data, we first used FastQC to assess raw sequencing data quality and then used Trimmomatic 0.36 for data filtering (Bolger et al., 2014). To obtain relatively accurate data, sequences with lengths less than 35 nucleotides, Q values < 20, and end reads were removed. High-quality reads were assembled using the IDBA_UD software (Peng et al., 2012), and contigs were obtained by overlapping regions between the reads. Subsequently, the obtained contigs were systematically evaluated. Prodigal 2.60 was used to predict the ORF from the splicing results and translate it into an amino acid sequence (Liu et al., 2013). We used the CD-HIT software to remove redundancy for gene prediction for each sample (Li and Godzik, 2006). Clean reads and nonredundant gene sets for each sample were aligned using the Bowtie 2 alignment tool (Langmead and Salzberg, 2012). Finally, gene lengths were normalized to the gene length for each sample (Li et al., 2009). Deduplicated gene sequences were compared to NR databases using BLASTP (version 2.2.28+) (The BLAST expectation parameter was configured at 1e-5) (Altschul et al., 1997). The NR reference database and its integrated taxonomic system were employed for species annotation by calculating relative abundance through the summation of species-associated gene counts. BLASTP uses the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to compare sequences in non-redundant gene sets. The results were annotated using KOBAS 2.0 (KEGG Orthology-based Annotation System) (Xie et al., 2011). Using Module databases and Enzyme, Pathway, and KEGG Orthology (KO), the abundance of each functional level in KEGG was calculated per sample based on the total gene abundance. 2.4.3 Functional gene analysis of soil microbial communities in microelements This study primarily examined the genes associated with the Ni, Mg, Zn, Mn, Co, Se, and Mo cycles. The specific functional genes are listed in annex Table 1. 2.5 Data analysis This study utilized the Analysis of Similarities (ANOSIM) feature within the ’vegan’ package of the R software to assess the differences in microelement-related functional genes among the drought gradients, rhizosphere types, and plant types. A weighted UniFrac PCoA analysis was performed using the ”ggplot2” package in R. To quantify the effects of physicochemical factors on the function and structure of the microbial community, we conducted a multivariate permutation analysis of variance (PERMANOVA) using the Adonis function in the ’vegan’ package of the R software. Three drought stress environmental factors and the relative abundances of functional genes were evaluated via variance analysis. Paired t-tests ( P < 0.05) were used to assess significant differences between the rhizosphere and bulk soil samples. We calculated the mean values with the corresponding standard deviations across all drought gradient plots and their rhizospheric environmental parameters. Variance decomposition analysis (VPA) was used to determine the distinct influence of environmental factors on rhizosphere microbial abundance during droughts. The ’vegan’ package of R was again used to perform the VPA analysis ( P < 0.05). Spearman’s correlation analysis was performed to assess functional gene-environmental factor interactions, which generated a symmetric correlation matrix that was subsequently converted to an absolute-valued similarity matrix using stringent thresholds ( P 0.8).

Differences in soil physicochemical properties The soil of Ebinur Lake was alkaline, with pH values ranging from 7.20 to 8.54. Our results demonstrated that soil pH and EC levels increased substantially as drought stress became less severe ( P < 0.05). In the soil samples under severe and mild drought conditions, OM, soil water content (SWC), total phosphorus (TP), AP, LAP, NAG, BG, clay, silt and sand contents exhibited significant variations ( P < 0.05) (Fig. 1), and were generally higher in the soil under mild drought conditions than in the soil under severe drought conditions (Table S1). In contrast, the sand content was significantly higher under severe drought conditions than under mild drought conditions ( P < 0.05). In addition, rhizosphere soils exhibited significantly higher OM and TP concentrations than bulk soils. In this study, soil samples under mild drought conditions were close to those of the rivers; therefore, they showed higher EC, OM, and nutrient levels, and plant growth was more extensive. In contrast, soil samples under severe drought conditions were far away from rivers, so their SWC was lower and nutrient elements were deficient, resulting in sparse plant growth. Genetic differences of soil microorganisms in microelement cycling First, a PcoA analysis was performed on the entire sample, and significant correlations were found between drought stress, rhizosphere effects, and microbial genes involved in the cycling of microelements ( P 0.05). The drought stress environment and rhizospheric effects explained 14.3% ( P = 0.002) and 71.4% ( P = 0.001) of the changes in microbial gene composition, respectively. Therefore, the differential functional genes in drought stress plots and rhizosphere types were analyzed. In the rhizosphere environment, the relative abundance of cbiN regulating Ni and Co transport in MiD plot was significantly lower than that in SD plot. The znuA gene’s relative abundance for Zn transport was markedly lower in the MiD plot than in the SD plot. The mntB and mntC expressions for manganese transport were notably diminished in the MiD plot compared to those in the SD plot. The relative abundances of sitABCD and nikC, which regulate Fe/Mn and Ni transport, respectively, were significantly lower in the MiD plot than in the SD plot ( P < 0.05) (Fig. 3). In bulk soils, MiD plots exhibited significantly lower levels of the modB gene expression, which regulates molybdenum transport, relative to SD plots ( P < 0.05). By contrast, the relative abundances of mntB, sitABCD, troABCD (which regulates Zn and Mn transport), and nikA (which regulates Ni transport) were markedly lower in the MiD plots than in the SD plots ( P < 0.05). In other microelement cycling pathways, CobS prevalence was most prominent in the SD plots, whereas wtpB richness peaked in the MoD plots. In the bulk soil environment, wtpA, wtpB, cobN, cobM, cbiD, cbiGH-cobJ, cobI-cbiL, cbiE, cobH-cbiC, cobK-cbiJ, cbiG, cbiT, SLC39A4 and ppaC showed significantly higher relative abundances in severe drought stress plots. zmpB had the highest relative abundance in all moderately stressed plots (Fig. S1 and S2). Microbial sources of key functional genes in microelement transport The microbial community analysis of the microelement transport process revealed that Proteobacteria and Actinobacteria accounted for 42.1 and 30.8% of the entire microbial community, respectively, for a total of 72.9% (Fig. S6). To explore which species affect the transport process of microelements, the α diversity chao1 index was used for further analysis. Under severe drought stress, Nocardioides, Pseudonocardia, and Mycobacterium populations were noticeably larger in the bulk soil samples than in the area directly surrounding the roots ( P < 0.05). Conversely, Devosia, Rhizobium, and Azospirillum were more abundant in the rhizospheric soil ( P < 0.05). Furthermore, Nocardioides was more abundant in SD than in MiD ( P < 0.05) (Fig. 4). At the genus level, Amycolatopsis, Nocardioides, Mycobacterium and Micromonospara were significantly higher in the SD plots than in the MiD plots. Influencing factors of soil microbial genes in microelement transport process The correlation analysis of the 12 environmental factors showed that BG was significantly positively correlated with silt, clay, and SWC, but significantly negatively correlated with sand. NAG was significantly positively related to SWC and significantly negatively related to sand. The clay content was significantly positively correlated with TP and OM, and the silt content was significantly and positively correlated with OM. The sand content was significantly negatively correlated with OM and SWC (Fig. 5). The Mantel test was used to assess the relationship between microelement transport genes and environmental factors. The relationships between the Ni and Co transport genes and clay was significant, and those between the Mn transport genes and TP, OM and clay were also significant. The relationships between the Mn and Zn transport gene and BG, OM, pH, SWC, clay, silt, sand and TP were significant. The relationships between Mo transport genes and OM, pH, clay, silt, sand, and TP were significant. In the rhizosphere environment under mild drought stress, NAG and BG significantly affected the functional genes of the soil microelement transport process ( P < 0.05), accounting for 19.57 and 20.15% of total variation, respectively. As a secondary influencing factor, AP significantly affected the functional genes involved in the soil microelement transport process, accounting for 18.81% of the total variation. In the rhizosphere under moderate drought stress, TP, AP, NAG, BG and silt significantly affected the functional genes of the soil microelement cycling transport process ( P < 0.05), accounting for 13.26, 11.56, 14.19, 13.00, and 10.59% of the total variation, respectively. In the rhizosphere under severe drought stress, silt and clay significantly affected the functional genes of the soil microelement transport process ( P < 0.05), accounting for 16.18 and 15.12% of the total variation, respectively. In the severe drought stress plots, EC and SWC significantly affected the functional genes of the soil microelement transport process ( P < 0.05), accounting for 17.34 and 20.45% of the total variation, respectively (Fig. 6). 4. Discussion 4.1. Rhizospheric effects on microelement cycle under drought stress Microbial gene abundances related to microelement cycling varied significantly between the rhizosphere and bulk soils under different drought conditions. The difference in microbial genes between the rhizosphere and bulk soil occurred because plants and microorganisms work synergistically to resist harsh environments. In arid ecosystems, although there are strong water limitations, microorganisms and enzymes that decompose organic substrates strongly influence nutrient exchange between the soil and plant rhizosphere (Cui et al., 2018). Microorganisms can control absorbable resources in plants by altering the production of enzymes during nutrient cycles (C, N, and P) (Chen and Sinsabaugh, 2021). The levels for the phosphorus cycle (AP), nitrogen cycle (NAG), and carbon cycle (BG) were markedly higher in the rhizosphere than in the bulk soil. In desert environments, because of the harsh soil environment, plants must provide fresh nutrient sources to promote microbial decomposition and positively influence the rhizosphere through secretions (Han et al., 2023). As proposed by Sun et al. (2023), when a bulk soil nutrient supply is insufficient, plants allocate additional carbon sources to the rhizosphere through fine root exudates, which stimulates microbial decomposition and positively affects the rhizosphere, functioning as a ”push” mechanism. This leads to high nutrient retention, which is characterized by roots in nutrient-deficient arid desert environments. Drought stress and rhizosphere effects changed the microelement cycle processes involved in microorganisms in different ways, and the influence of the rhizosphere was greater than that of drought. This difference occurred because drought stress can indirectly reduce the availability of microelements by reducing soil organic carbon (Moreno-Jiménez et al., 2019). The production of effective microelements is a scarce resource for plants and microorganisms. In rhizospheric soil, the solubility of microelements is affected by pH; therefore, the organic acids secreted by plants can improve the effectiveness of microelements (Wang et al., 2024). Plants control the solubility of microelements through root exudates, obtaining unstable microelements from the roots. Simultaneously, plants use root exudates and plant growth to promote the interactions of root bacteria, support arbuscular mycorrhizal symbiosis, and significantly and positively affect the plant absorption of microelements (Alford et al., 2010). Therefore, the rhizosphere microenvironment actively promotes the microbial-mediated cycling of microelements in arid desert ecosystems. In terrestrial ecosystems, the microelement cycle refers to the transformation of mineral elements between plants, animals, microorganisms, and soil solids, including biological, chemical, and physical processes such as plant absorption, biotransformation, chemical fixation, and dissolution reactions. Studies have shown that plant roots greatly influence the supply capacity of available microelements and are the main biological factors (McCulley et al., 2004). Metagenomic sequencing revealed that the study area contained more microelement transport genes. After absorption by plant roots, microelements in the soil are transported to the plants and accumulate through the regulation of complex genetic networks (Singh et al., 2020). Microelements are indispensable in some metabolic pathways that require specialized transport systems to transport them into the cells. Members of the ABC transporter family mediate a subset of transport functions, including the NikRABCDE system, which is involved in Ni transport (Navarro et al., 1993). The znuABC is involved in the absorption of Mn and potentially Zn. Molybdenum uptake occurs via another ABC transporter ( modABC ). Rhizosphere soils exhibited significantly greater relative abundances of micronutrient transporter genes ( znuA, modA, modC ) than bulk soils, demonstrating the essential role of the rhizosphere in mediating microelement transport. This phenomenon likely stems from root-exuded organic acids chelating metal ions, thereby destabilizing metal-organic complexes in the soil and enhancing metal bioavailability (Clarholm et al., 2015). In the rhizospheric soil, sit genes had a higher relative abundance. The sit gene family primarily regulates Fe and Mn transport. In the rhizosphere, root-exuded organic acids can mobilize Mn oxides through Fe-Mn redox coupling, thereby enhancing Mn bioavailability (Jones et al., 2020). 4.2. Role of microorganisms in the cycling of microelements Microorganisms are indispensable in maintaining soil composition and the circulation of microelements. Microbial sources of microelements showed that Proteobacteria, Actinobacteria, and Chloroflexi accounted for 81.4% of the microbial communities related to the microelement cycle, of which 42.1 and 30.8% were annotated to Proteobacteria and Actinobacteria, respectively. Previous studies have shown that Proteobacteria and Actinomycetes contribute to soil nutrient cycling (Zhou et al., 2023). In an oligotrophic environment, Actinobacteria secrete diverse extracellular hydrolases to break down recalcitrant soil organic matter, thereby securing essential nutrients for growth (Zhang et al., 2019). Simultaneously, organic matter in the soil can form complexes with metal microelements, which increases the bioabsorbable metal microelements (Nguyen et al., 2017). Proteobacteria and Actinomycetes exhibit Mn-solubilizing activity (Ghosh et al., 2016), indicating that the microbial community can convert Mn into Mn needed for plant growth in barren deserts and is more conducive to growth in arid environments. Through acidification, Proteobacteria convert ZnO to Zn(0) and produce organic acid metabolites (acetic, formic, and lactic). These acids subsequently chelate Zn into bioavailable organic complexes and promote its absorption by plants (Mumtaz et al., 2025). Drought stress reduced the relative abundance of Proteobacteria (Sun et al., 2024). For example, the relative abundance of Proteobacteria was significantly lower under severe drought stress than under mild drought stress. The microbial assemblages in the examined soils were mainly involved in the transport of microelements. At the genus level in bulk soil, under severe drought stress, we observed markedly higher relative abundances of Amycolatopsis, Nocardioides, Mycobacterium, and Micromonospora relative to moderately stressed plots, indicating that the microbes transported the soil microelements for their own use in arid environments to maintain their own growth. Previous experiments have shown that the microelement contents of plants inoculated with Rhizobium are higher than non-inoculated plants. Simultaneously, the combination of Rhizobium and microelements can improve plant growth and soil fertility. Researchers have speculated that Rhizobium is conducive for the transport of microelements into plants, making them conducive for survival in arid environments (Flores-Félix et al., 2015; Quddus et al., 2024). Azospirillum may have a direct effect on the abundance of transporters and the activity level of metal ion transport, and promote plant growth at low manganese concentrations (Housh et al., 2022). 4.3. Potential factors influencing microelement transporters In mild and moderate drought stress environments, the VPA showed that NAG and BG significantly affected the transport process of microelements, and the average interpretation of NAG and BG reached 33.46%. BG influences the C cycle in the soil, whereas NAG influences the nitrogen cycle in the soil, and β-glucosidase accelerates cellulose breakdown mainly by increasing cellulase expression (Li et al., 2013). The degradation of cellulose increases the OM content in the soil. OM mineralization liberates diverse microelements into the soil matrix, and concurrently released organic acids and humic substances solubilize mineral-bound nutrients, thereby enhancing soil micronutrient concentrations; these conditions are conducive to the transport of microelements and increases the phytoavailable microelements (Ye et al., 2015; Frąc et al., 2023). Soil texture significantly affected the transport of microelements in the severe drought environment evaluated in this study. In the rhizosphere environment under severe drought stress, clay and silt significantly affected the functional gene processes of soil microelement transport, and the degree of explanation reached 31.30%. Soil texture demonstrably affects soil physicochemical characteristics, thereby affecting microelement transformations (Shukla et al., 2015). In addition, soil organic matter complexation/chelation processes and mineral-surface adsorption-desorption equilibria predominantly affect microelements biogeochemical cycling (Jobbágy and Jackson, 2004; Sharma et al., 2004). A decline in clay abundance led to OM loss and reduced phytoavailable microelements, whereas sand dominance led to an overall microelement diminishment (Lv et al., 2016; Tan et al., 2022). These outcomes occurred because decreased clay and silt diminished the mineral adsorption capacity for nutrients in soils (Wang et al., 2020; Karki et al., 2021), and reduced the amount of microelements in the soil. Weathering was lower in soils with higher levels of sand particles. In severe drought stress environments, rhizosphere soils exhibit significantly larger clay and silt fractions but a reduced sand content compared to bulk soils. Therefore, rhizospheric soil under severe drought stress is more conducive to microelement and OM complexation and chelation. The available microelements in the soil are positively correlated with their total concentrations (Sharma et al., 2023). Therefore, clay and silt can indirectly affect the transport process by affecting the microelement content. 5. Conclusion This study found that the rhizosphere type and drought stress affected the microbial genes of the microelement cycle. The microelement cycle in the Ebinur Lake desert region was mainly based on the transport of microelements and showed differences in the rhizosphere type. The rhizosphere exhibited significantly elevated expression levels of functional genes compared to those in bulk soil. In terms of microbial composition, the microelement cycle mainly involved Actinobacteria and Proteobacteria, which promoted the formation of microelement complexes by releasing hydrolases and metabolites and thereby promoted the absorption of microelements by organisms. Drought stress inhibited Proteobacteria, which was not conducive for microelement cycling. The BG exhibited the highest activity levels in terms of physical and chemical properties. In the rhizosphere environment, BG and NAG significantly affected the transport of microelements under slight and moderate drought conditions, whereas under severe drought conditions, the most prominent influences were clay and silt; in a severely dry bulk soil environment, sand was predominant. These results provide new insights into the soil microelement cycle and its influencing factors in desert ecosystems and provide a new theory for soil microorganisms in arid areas and their effects on the microelement cycle.

This research was funded by the Youth of Natural Science Foundation of Xinjiang Uygur Autonomous Region in 2024 (2024D01C219), the National Natural Science Foundation of China (42171026; 32101587; 32360282) and the Key Research Program in Xinjiang Uygur Autonomous Region (2024B03017).

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Soil pH(pH), electrical conductivity (EC), soil organic carbon (OM), total phosphorus (TP), soil moisture content (SWC), alkaline phosphatase (AP), leucine aminopeptidase (LAP), N-acetyl-β-D-glucosidase (NAG), β-1,4-glucosidase (BG), Sand, Silt, Clay. Fig. 2 PCoA analysis of microelements cycle process under drought stress, rhizosphere and bulk soil and plant type. MiD, MoD, and SD correspond to mild, moderate, and severe drought stress. Fig. 3 Difference analysis of microelements functional genes in rhizosphere types and drought stress environment. Fig. 4 The differences of microorganisms involved in the circulation of microelements in rhizosphere type and drought stress environment (Genus level). Fig. 5 The correlation between environmental factors and their effects on microelements cycle. Nickel cycle functional genes (Ni), Zinc cycle function genes (Zn), Manganese cycle functional genes (Mn), Cobalt cycle functional genes (Co), Selenium cycle function genes (Se), Molybdenum cycle function genes (Mo). Fig. 6 Contribution of environmental factors to changing relative abundance of microelements transporter genes in soil microorganisms. Soil pH(pH), electrical conductivity (EC), organic matter (OM), total phosphorus (TP), soil water content (SWC), alkaline phosphatase (AP), leucine aminopeptidase (LAP), N-acetyl-β-D-glucosidase (NAG), β-1,4-glucosidase (BG), Sand, Silt, Clay. Figure abc represents the rhizosphere environment plots under mild, moderate and severe drought stress respectively, and def represents the bulk soil environment plots under mild, moderate, and severe drought stress respectively. Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License.

Authors Metrics & Citations Metrics Article Usage 254views 190downloads Citations Download citation Meiyu Wang, Wenjing Li, Wang Hengfang, et al. Analysis of factors affecting rhizospheric impacts on microelement cycling under drought stress. Authorea. 06 June 2025. DOI: https://doi.org/10.22541/au.174919168.87539710/v1 DOI: https://doi.org/10.22541/au.174919168.87539710/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.