Metagenomic analysis reveal the phytoremediation effects of monocropping and intercropping of halophytes 
Soil is an important resource for human survival, but soil salinization is a growing problem globally, leading to soil degradation and seriously affecting agricultural production . The total area of saline soil globally is about 1 billion hectares, of which China has about 100 million hectares, accounting for more than one-tenth of the world’s total area, making it the third largest country in the world in terms of saline land distribution . In Northwestern China, salinity and drought usually occur together, and have become one of the main factors restricting agricultural development in the arid regions of Northwestern China . Due to its special soil conditions, the utilization and improvement of saline soils has been an important topic in agricultural science research . Earlier studies have shown that reducing soil salinity by planting halophytes to improve saline soil is one of the most effective ways to solve the problem of soil salinization and significantly improve quality of saline soils . In recent years, saline soil improvement methods centered on phytoremediation have gradually gained attention and have progressed . The impact of halophytes on soil microorganisms, however, is not clear. Macrogenomics is a technique to study microbial diversity and community structure and function, which reveals the microbial ecological characteristics of an environment by sequencing and analyzing all microbial genes in that environment . A deep understanding of the soil physicochemical properties and microbial diversity after planting halophytes, as well as the isolation and screening of salt-alkali-tolerant microbial communities, is of significance for improving saline soil. As the most active part of soil, microorganisms exhibit high response characteristics to soil material components, physicochemical properties, and the microenvironment . In the process of vegetation succession and restoration, soil microorganisms may play a series of roles in the plant rhizosphere . Rhizosphere microorganisms, as regulators of nutrient transformation and transport between soil and roots, are the soil microbial community most affected by plants . Their role in plant adaptation has been recognized, and many microorganisms beneficial for plants to cope with salt stress have been isolated and reapplied to saline soil to improve crop yield . Therefore, clarifying the dominant species and functions of bacterial diversity in the inter-root soil of saline plants can be used to improve the quality of saline soil microenvironments by utilizing salt-tolerant microorganisms in the inter-root soil of saline plants . In Northwestern China, Halogeton glomeratus and Suaeda glauca are the dominant plants used for salt removal. Halogeton glomeratus is a dicotyledonous herbaceous plant in the Chenopodiaceae family and has strong drought and salt tolerance. Its most significant feature is that the plant stems and leaves are highly fleshy, gradually changing salinized “waste fields” into tillable “treasure fields,” and is a characteristic plant resource in the arid region of Northwestern China. Suaeda glauca , a member of the Amaranthaceae family, is a pioneer species of dicotyledonous halophyte used for ecological phytoremediation of saline and alkaline soils . Planting halophytes to improve saline soil is a proven practical and feasible approach. Studies have shown that cotton–halophyte intercropping can reduce soil salinity and improve crop production . The content of salt and sodium ions (Na + ) was decreased by intercropping with S. salsa and Zea mays L . In moderately saline soils, intercropping of Arthrocaulon macrostachyum L. and tomatoes or planting tomatoes after harvest of a previous crop of A. macrostachyum L. reduced soil salinity and increased the yield of tomatoes . Both H. glomeratus and S. glauca have been widely used to improve saline soil as they are highly tolerant to both salt and alkali. It is generally believed that intercropping of H. glomeratus and S. glauca can improve the coverage of saline soil and improve the soil, but whether this method can improve saline soil more effectively has not been reported. In this experiment, we took H. glomeratus and S. glauca planted on saline and alkaline land in Northwestern China as research objects; analyzed the mechanism of saline soil improvement using macrogenomic methods; compared the differences in plant growth ability, soil physicochemical properties, and the effect of saline soil improvement of the two plants under different cultivation modes (monocropping and intercropping); and verified the results using potting experiments. The study aimed to (1) investigate the impact of three remediation methods on the physicochemical properties and microbial communities of the rhizosphere in saline soil; (2) compare monocropping and intercropping of H. glomeratus and S. glauca in saline soil improvement; and (3) analyze the relationship between the metagenome and environmental factors. The aim of this research is to enhance the development and utilization of saline plant resources by comparing the different effects of monocropping and intercropping on saline soil improvement, and to provide a scientific basis for saline soil improvement.   Experimental design and sampling collection The field trial was performed on saline soils in Northwestern China (39°13′N, 100°17′E; Fig. A) . This region has a temperate continental desert climate with low precipitation, receiving an average annual rainfall of 117.2 mm. In November 2021, seeds of H. glomeratus and S. glauca were collected from the saline flat of Hetan Town, Huining County, Baiyin City, Gansu Province (36°12′N, 104°97′E), and cleaned to remove impurities and stored in a low temperature seed cupboard at 4℃. The H. glomeratus and S. glauca seeds were sown in May 2022 in saline soils. In November 2022, the saline soils were sampled. A total of 10 rows of monocropping of H. glomeratus (Hg), monocropping of S. glauca (Sg), and H. glomeratus and S. glauca intercropping (Hg||Sg) were planted in plots of 5 m × 10 m (Fig. B). Seeds were planted at 10-cm intervals in each plot. Plots without plants were used as controls (CK) . Clinical trial number: not applicable. After harvesting the Hg and Sg, four treatment areas were selected to collect topsoil samples from saline soils. In each plot, sampling was repeated three times. Each composite sample consisted of 5-cm-diameter soil cores taken to a depth of 40 cm, giving a total of 12 soil samples and three replicates for each of the four treatments. After debris removal, soil samples were filtered through a 2-mm sieve, then each soil sample was divided into two parts, and soil samples from the same sampling area were crushed and mixed evenly into sterile aseptic sealed bags, which were stored in a foam cryopreservation box . The first sample was air-dried to determine the physical and chemical properties of the soil and the second sample was stored in liquid nitrogen at − 80 °C for the extraction of DNA from soil microbes. After planting on saline-alkali soil for one season, 3 samples of 5 m×5 m were randomly selected from each repeat of halophyte plants. After cutting, 3 samples were cleaned, separated according to different tissues and organs, placed in the oven at 105℃ for 30 min, and then dried to constant weight at 80℃ and crushed. Weigh an appropriate amount of the above-ground sample, decompose it, cool it to constant weight, dissolve it with distilled water, and transfer it to a 100 m| volumetric bottle at constant volume to prepare the liquid to be measured. Na + , K + , were determined by flame spectrophotometry. Ca 2+ and Mg 2+ were determined by EDTA titration. Each indicator is repeated 3 times to take the average value. In the pot experiment, we used glass bottles of diameter of 6.5 cm and Hoagland nutrient solution to prepare medium with pH 5.8. The NaCl environment was simulated using five different salt concentrations of 0, 50, 100, 150, and 200 mmol·L − 1 . The seeds of Hg and Sg were evenly planted on the medium, with 16 seeds for each medium. The glass bottles were placed flat in the incubator and the biomass of seedlings in each bottle was determined after 30 days of culture. Determination of dry biomass, soil pH, and nutrient contents The harvested materials were dried at 60 °C for 3 days and referred to as dry biomass. After planting on saline-alkali soil for one season, 3 samples of 5 m×5 m were randomly selected from each repeat of halophyte plants. After cutting, 3 samples were cleaned, separated according to different tissues and organs, placed in the oven at 105℃ for 30 min, and then dried to constant weight at 80℃ and crushed. Determination of Na, Ca, Mg, P , total water-soluble salt (TDS), soil organic matter (OM) , pH, total nitrogen (TN), alkaline dissolved nitrogen (AN), total phosphorus (TP), available phosphorus (AP), total potassium (TK), available potassium (AK) . Determination of soil microbial community Genomic DNA was extracted using HiPure Bacterial DNA Kits (Magen, Guangzhou, China) in accordance with the manufacturer’s instructions. Genome sequencing was performed on an Illumina Novaseq 6000 sequencer. Pair-end technology (PE 150) was used . Genes were predicted using MetaGeneMark (version 3.38) on the basis of the final assembly contigs (> 500 bp). Bowtie (version 2.2.5) was used to count the number of reads, and the reads were re-aligned to the predicted gene. Non-redundant genes with gene read counts > 2 were included in the final gene catalog . The R package ggplot2 was used to plot the box plot showing the number of genes in each group . Chao1, ACE, Shannon, and Simpson indices were calculated using the Python scikit-bio package (version 0.5.6). Comparison of α-index between groups was calculated using Kruskal–Wallis H-test in the vegan package of R. Bray–Curtis distance matrix based on gene/taxon/function abundance was generated using the vegan package. Multivariate statistical techniques including RDA (redundancy analysis) and NMDS (non-metric multidimensional scaling) of Bray–Curtis distances were calculated using the vegan package and plotted using ggplot2. Permanova and Anosim tests were calculated using the vegan package. Heatmap graphs were plotted using the R package pheatmap. Venn analysis between groups was performed using the R project Venn Diagram package and upset plot using the UpSetR package to identify unique and common species or functions. Comparison of species/functions between groups was calculated using Welch’s t-test in the vegan package. Comparison of species/functions between groups was calculated using analysis of variance in the vegan package. We used several complementary approaches to annotate the assembled sequences. The unigenes were annotated using DIAMOND (version 0.9.24) by alignment with those deposited in various protein databases, including the National Center for Biotechnology Information (NCBI) non-redundant protein (Nr) database and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Circular layout representations of functional gene abundance were plotted using Circos (version 0.69-3). Species comparisons between groups were calculated using Metastats (version 20090414). Differentially enriched KEGG pathways were identified according to their reporter score from the z-scores of individual Kos (KEGG orthologs). An absolute value of the reporter score = 1.96 or higher (95% confidence according to a normal distribution) was used as a detection threshold for pathways that differed significantly in abundance. Biomarker features of species and functions in each group were screened using LEfSe software (version 1.0). Statistical analysis Statistical analyses were performed using Microsoft Excel 2016 and SPSS25.0 (IBM, Armonk, New York, USA) with a two-way ANOVA. Evenness and Shannon diversity indices were assessed for each sample, and these indices were compared for four treatment soil samples using a Kruskal–Wallis test . The relationship between soil pH and α-diversity of the soil bacterial community was analyzed using Pearson’s correlation coefficients (r). Statistical analyses were performed using IBM SPSS Statistics (version 25.0; IBM Corp., Armonk, NY, USA). The significance level was set at P ≤ 0.05 . Values represent the mean ± standard error (SE) for the three repeated treatments.   The field trial was performed on saline soils in Northwestern China (39°13′N, 100°17′E; Fig. A) . This region has a temperate continental desert climate with low precipitation, receiving an average annual rainfall of 117.2 mm. In November 2021, seeds of H. glomeratus and S. glauca were collected from the saline flat of Hetan Town, Huining County, Baiyin City, Gansu Province (36°12′N, 104°97′E), and cleaned to remove impurities and stored in a low temperature seed cupboard at 4℃. The H. glomeratus and S. glauca seeds were sown in May 2022 in saline soils. In November 2022, the saline soils were sampled. A total of 10 rows of monocropping of H. glomeratus (Hg), monocropping of S. glauca (Sg), and H. glomeratus and S. glauca intercropping (Hg||Sg) were planted in plots of 5 m × 10 m (Fig. B). Seeds were planted at 10-cm intervals in each plot. Plots without plants were used as controls (CK) . Clinical trial number: not applicable. After harvesting the Hg and Sg, four treatment areas were selected to collect topsoil samples from saline soils. In each plot, sampling was repeated three times. Each composite sample consisted of 5-cm-diameter soil cores taken to a depth of 40 cm, giving a total of 12 soil samples and three replicates for each of the four treatments. After debris removal, soil samples were filtered through a 2-mm sieve, then each soil sample was divided into two parts, and soil samples from the same sampling area were crushed and mixed evenly into sterile aseptic sealed bags, which were stored in a foam cryopreservation box . The first sample was air-dried to determine the physical and chemical properties of the soil and the second sample was stored in liquid nitrogen at − 80 °C for the extraction of DNA from soil microbes. After planting on saline-alkali soil for one season, 3 samples of 5 m×5 m were randomly selected from each repeat of halophyte plants. After cutting, 3 samples were cleaned, separated according to different tissues and organs, placed in the oven at 105℃ for 30 min, and then dried to constant weight at 80℃ and crushed. Weigh an appropriate amount of the above-ground sample, decompose it, cool it to constant weight, dissolve it with distilled water, and transfer it to a 100 m| volumetric bottle at constant volume to prepare the liquid to be measured. Na + , K + , were determined by flame spectrophotometry. Ca 2+ and Mg 2+ were determined by EDTA titration. Each indicator is repeated 3 times to take the average value. In the pot experiment, we used glass bottles of diameter of 6.5 cm and Hoagland nutrient solution to prepare medium with pH 5.8. The NaCl environment was simulated using five different salt concentrations of 0, 50, 100, 150, and 200 mmol·L − 1 . The seeds of Hg and Sg were evenly planted on the medium, with 16 seeds for each medium. The glass bottles were placed flat in the incubator and the biomass of seedlings in each bottle was determined after 30 days of culture.   The harvested materials were dried at 60 °C for 3 days and referred to as dry biomass. After planting on saline-alkali soil for one season, 3 samples of 5 m×5 m were randomly selected from each repeat of halophyte plants. After cutting, 3 samples were cleaned, separated according to different tissues and organs, placed in the oven at 105℃ for 30 min, and then dried to constant weight at 80℃ and crushed. Determination of Na, Ca, Mg, P , total water-soluble salt (TDS), soil organic matter (OM) , pH, total nitrogen (TN), alkaline dissolved nitrogen (AN), total phosphorus (TP), available phosphorus (AP), total potassium (TK), available potassium (AK) .   Genomic DNA was extracted using HiPure Bacterial DNA Kits (Magen, Guangzhou, China) in accordance with the manufacturer’s instructions. Genome sequencing was performed on an Illumina Novaseq 6000 sequencer. Pair-end technology (PE 150) was used . Genes were predicted using MetaGeneMark (version 3.38) on the basis of the final assembly contigs (> 500 bp). Bowtie (version 2.2.5) was used to count the number of reads, and the reads were re-aligned to the predicted gene. Non-redundant genes with gene read counts > 2 were included in the final gene catalog . The R package ggplot2 was used to plot the box plot showing the number of genes in each group . Chao1, ACE, Shannon, and Simpson indices were calculated using the Python scikit-bio package (version 0.5.6). Comparison of α-index between groups was calculated using Kruskal–Wallis H-test in the vegan package of R. Bray–Curtis distance matrix based on gene/taxon/function abundance was generated using the vegan package. Multivariate statistical techniques including RDA (redundancy analysis) and NMDS (non-metric multidimensional scaling) of Bray–Curtis distances were calculated using the vegan package and plotted using ggplot2. Permanova and Anosim tests were calculated using the vegan package. Heatmap graphs were plotted using the R package pheatmap. Venn analysis between groups was performed using the R project Venn Diagram package and upset plot using the UpSetR package to identify unique and common species or functions. Comparison of species/functions between groups was calculated using Welch’s t-test in the vegan package. Comparison of species/functions between groups was calculated using analysis of variance in the vegan package. We used several complementary approaches to annotate the assembled sequences. The unigenes were annotated using DIAMOND (version 0.9.24) by alignment with those deposited in various protein databases, including the National Center for Biotechnology Information (NCBI) non-redundant protein (Nr) database and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Circular layout representations of functional gene abundance were plotted using Circos (version 0.69-3). Species comparisons between groups were calculated using Metastats (version 20090414). Differentially enriched KEGG pathways were identified according to their reporter score from the z-scores of individual Kos (KEGG orthologs). An absolute value of the reporter score = 1.96 or higher (95% confidence according to a normal distribution) was used as a detection threshold for pathways that differed significantly in abundance. Biomarker features of species and functions in each group were screened using LEfSe software (version 1.0).   Statistical analyses were performed using Microsoft Excel 2016 and SPSS25.0 (IBM, Armonk, New York, USA) with a two-way ANOVA. Evenness and Shannon diversity indices were assessed for each sample, and these indices were compared for four treatment soil samples using a Kruskal–Wallis test . The relationship between soil pH and α-diversity of the soil bacterial community was analyzed using Pearson’s correlation coefficients (r). Statistical analyses were performed using IBM SPSS Statistics (version 25.0; IBM Corp., Armonk, NY, USA). The significance level was set at P ≤ 0.05 . Values represent the mean ± standard error (SE) for the three repeated treatments.   Changes of aboveground biomass of halophytes after planting In the pot experiment, the Hg biomass under 0, 50, 100, 150, and 200 mmol·L − 1 NaCl treatment was the largest, consistent with the field experiment. The growth of Hg was stronger than that of Sg and Hg||Sg (Fig. C). The aboveground biomass of H. glomeratus and S. glauca under three improved modes was measured (Table ). The biomass of Hg was 12.35% and 5.68% higher than for Hg||Sg and Sg, respectively. Aboveground biomass of the different treatments differed significantly: Hg > Hg||Sg > Sg. Soil properties affected by planting different saline-tolerant plants After planting halophytes, Na content in soil decreased significantly, including 0.732 mg/kg under Hg treatment, 0.289 mg/kg under Sg treatment, and 0.530 mg/kg under Hg||Sg treatment. Ca content in soil decreased significantly, including 10.279 mg/kg under Hg treatment, 5.097 mg/kg under Sg treatment, and 8.781 mg/kg under Hg||Sg treatment. Soil Mg content decreased significantly, including 2.125 mg/kg under Hg treatment, 1.310 mg/kg under Sg treatment, and 1.282 mg/kg under Hg||Sg treatment. However, P content in soil increased significantly, with an increase of 0.905 mg/kg under Hg treatment, 0.464 mg/kg under Sg treatment, and 0.662 mg/kg under Hg||Sg treatment. It is worth noting that there was a significant correlation between halophytes before and after seeding except for bare soil ( P < 0.05). The impact of halophytes on soil pH was related to cropping type ( P < 0.05, Table ). There were significant differences in pH between the Hg and Hg||Sg sampled areas during seedling and after harvesting (Table ). Before and after planting halophytes, the soil pH of sample areas of Hg, Sg, and Hg||Sg decreased to 0.52, 0.19, and 0.34, respectively. For Hg, Sg, and Hg||Sg treatments, the TDS content in the soil decreased by 1.138, 0.744, and 0.923 g/kg, respectively, with the greatest decrease for Hg. Plant type significantly affected soil OM content. For Hg, Sg, and Hg||Sg treatments, the OM content in the soil of each treatment increased by 4.124, 1.113, and 2.563 g/kg, respectively. The order of OM content in the soil after different halophyte treatments follows: Hg > Hg||Sg > Sg. The impact of halophytes on soil TN content is shown in Table , the highest increase in soil TN content was Hg (0.231 g/kg). Under different coverage of halophytes, the highest increase AN content in the rhizosphere soil of vegetation was for Hg (27.399 mg/kg). The order of TN and AN contents in rhizosphere soil for the halophyte treatments follows: Hg > Hg||Sg > Sg. Soil TP content is mainly influenced by soil-forming parent material and climate type, but there is also a relationship with vegetation activities. TP content only increase after Hg treatment (0.091 g/kg), because there are no statistical different among any other samples. The AP content also increased, with the greatest increase for Hg (5.297 mg/kg). After treatment with different halophytes, the TP and AP contents in the rhizosphere soil were as follows: Hg > Hg||Sg > Sg. Apart from CK, the highest reduction in soil TK content was for Hg (3.712 g/kg), while the lowest reduction was for Sg (1.196 g/kg). Compared to seedling stage, soil AK levels differed markedly at harvest stage ( P < 0.05). Overall, after treatment with different halophytes, the order of TK and AK content in rhizosphere soil was Hg > Hg||Sg > Sg. As can be seen from Table , the aboveground content of Na + in halophytes was the highest under Hg, while the aboveground content in halophytes under Sg was the lowest. The aboveground part content of K + in halophytes was the highest under Sg, and the lowest under Hg||Sg. The content of Ca 2+ in the aboveground part of halophytes was the highest under Hg, and the lowest under Sg. The content of Mg 2+ in the aboveground part of halophytes was the highest under Hg and the least under Sg. Changes in soil microbiota after planting different saline-tolerant plants Metagenomic sequencing was used to analyze the characteristics and communities of soil microorganisms . Metagenome sequencing produced 121,882.49 Mbp of raw data. After removing low-quality reads, 121,405.36 Mbp of clean data were obtained. After sequencing, we obtained a total of 3.2 × 10 5 to 4.7 × 10 5 contigs and 2.0 × 10 5 to 5.1 × 10 5 open reading frames (ORFs) (Tables S1 and S2). A total of six kingdom, 161 phylum, 254 class, 426 order, 754 family, 2257 genus, and 9100 species level classifications were obtained by metagenomic sequencing. According to the species annotation, the microbial composition of soil samples was mainly bacteria (over 84.11%) (Fig. A). Analysis of species differences at the phylum level in a Wayne diagram showed seven species unique to CK, two species unique to Hg, one species unique to Sg, and a total of 114 species in CK, Hg, Sg, and Hg||Sg, which had 160, 48, 54, and 54 unique genera, respectively; with 930 genera shared by the four treatments (Fig. B and C). In this experiment, the effects of bare ground and Hg, Sg, and Hg||Sg treatments on the Chao, ACE, Shannon, and Simpson indices of microbial communities in remediated saline soils were investigated. The α-diversity index of soil microorganism communities showed significantly decreased species α-diversity (Chao 1 and ACE), and significantly increased species α-diversity (Shannon and Simpson) (Fig. D–G). The microbial community in the bare land (CK) significantly differed from those for the three halophyte cover treatments according to NMDS (Fig. H) . The NMDS analysis showed that with a stress rate of 0.007, among the three phytoremediation treatments, there was a clear difference in theβ-diversity estimates of soil microorganisms proportions based on NMDS. It is noteworthy that the symbols were distributed in four quadrants each, representing the soil microbiota of CK, Hg, Sg, and Hg||Sg. The distribution variation between the CK, Hg, Sg, and Hg||Sg treatments showed a significant effect of the cover plants on soil microorganism communities. Fig. 4The LEfSe method identifies the significantly different abundant taxa of soil bacterial communities (A). The taxa with significantly different abundances between treatments are represented by colored dots, and from the center outwards they represent the kingdom, phylum, class, order, family, genus, and species levels. Colored shadows represent trends of significantly different taxa. Only taxa with an LDA significance threshold > 3.5 are shown in this figure. Each colored point has an effect size LDA score as shown in Fig. S1. The RDA of bacterial community and environmental factors (B). Heatmap of the correlations between phyla and soil factors (C), note ** P < 0.01; * P < 0.05. The abbreviations indicate the same as in Fig. . The sequencing results were annotated by species, and the UPGMA (unweighted pair-group method using arithmetic averages) of each soil sample was constructed with weighted UniFrac distance matrix at gate-level means, non-weighted group average method clustering tree (Fig. I). The bacterial groups with the highest relative abundance in the rhizosphere soil were Proteobacteria and Actinobacteria. Bacteroidetes, Gemmatimonadetes, and Chloroflexi were all in low abundance in the soil. The cluster diagram showed that the community structure composition of the four soil microorganisms at the phylum level was similar for Hg and Sg treatment. Although the dominant phyla in the soils of the four treatments were essentially the same, the relative abundance of individual dominant phyla differed significantly at different stages. For example, the abundances of Proteobacteria in CK, Hg, Sg, and Hg||Sg treatments were 29.63%, 25.71%, 22.21%, and 23.18%, respectively (Fig. I). Chloroflexi had a significant positive correlation with salt tolerance, whereas Proteobacteria had a significant negative correlation. Among the top 20 genera, the dominant phylum in CK, Hg, Sg, and Hg||Sg was Proteobacteria, with 32.86%, 22.78%, 22.76%, and 21.6%, respectively (Fig. A). Furthermore, the Hg, Sg, and Hg||Sg treatments had significantly higher relative abundances of Chloroflexi, Candidatus_Tectomicrobia, and Acidobacteria compared with CK. The KEGG database was used to predict the gene function of non-redundant gene sets from saline soils covered by different halophytes. A total of 1,046,716 reads could correspond with the functional annotation results. There were 72,189 items in category Cellular Processes, 29,423 in category Human Diseases, and 40,508 in category Organismal Systems. There were 743,954 in Metabolism, 70,364 in Genetic Information Processing, and 90,278 in Environmental Information Processing. Among the four treatments, the most microbial functional genes belonged to Metabolism, while the least belonged to Human Diseases and Organismal Systems (Fig. B). The LEfSe analyses (LDA values shown in Fig. ) were used to check for significant differences in the abundance of soil bacterial taxa and to confirm the biological relevance of soil microbial species under different treatments (Fig. A). In particular, Gammaproteobacteria, Xanthomonadales, Proteobacteria, and Deltaproteobacteria were the most altered soil microorganism taxa for the CK; Betaproteobacteria, Acidobacteria, Burkholderiales, and Rhodospirillales were the most altered for Hg treatment; Sphingomonas and Gemmatimonadetes were the most altered for Sg treatment; and Actinobacteria, Chloroflexi, and Propionibacteriales were the most altered for Hg||Sg treatment. The KEGG heat map shows that for CK, the Two component system and Fatty acid metabolism are high, but decrease after planting Hg and Sg. After planting Sg, Valine, leucine, and isoleucine degradation, Propanoate metabolism, Citrate cycle (TCA cycle), Glyoxylate and dicarboxylate metabolism, Aminoacyl-tRNA biosynthesis, Purine metabolism, Carbon fixation pathways in prokaryrotes, ABC transporters, Butanoate metabolism, Alanine, aspartate, and glutamate metabolism, and Amino sugar and nucleoside sugar metabolism significantly increased. After planting Hg, there were no significant changes. After planting of Hg||Sg, Amino sugar and nucleotide sugar metabolism increased, while Fatty acid metabolism decreased. After Hg||Sg processing, Cysteine and methionine metabolism, Metabolic pathways, Oxidative physiology, Methane metabolism, Microbial metabolism in diverse environments, Quorum sensing, Carbon metabolisms, Pyruvate metabolism, Biosynthesis of amino acids, Glycolysis/gluconeogenesis, Biosynthesis of secondary metabolites, and Glycine, serine, and threonine metabolism significantly increased (Fig. ). Interactions between environmental factors and microbial communities The RDA was used out to understand the effect of changes in key soil physical and chemical properties on the composition of soil microbial communities under four saline alkaline soil treatments. Two RDA axes explained 96.94% of the differences in soil microbial community structure (Fig. B), indicating that environmental factors significantly influenced bacterial community structure. The RDA plots used Mg, pH, TK, OM, TP, Na, AN, P, TN, TDS, and Ca as soil environmental variables (represented by blue arrows). Only Mg was present in the third quadrant, with other environmental factors concentrated in the first and fourth quadrants (Fig. B). A greater effect on the microbial community composition was indicated by the longer exposure to TN. A lesser effect on microbial community composition was indicated by the shorter exposure to Ca. The dominant phyla, including Proteobacteria, Acidobacteria, and Actinobacteria, were the main contributors to microbial community changes. The RDA revealed that soil microbial groups were distributed in different quadrants according to functional analysis of CK, Hg, Sg, and Hg||Sg patches. Soil OM, TP, Na, AN, P, TN, and AK were significantly correlated with Sg soil microbial functions. Soil TK and pH were significantly correlated with soil microbial functions in the Hg treatment. The microorganisms whose components were in the top 20 with obvious differences among samples were selected, and their correlations with environmental factors analyzed. The TDS, Ca, Mg, pH, TN, AN, and AK were closely related to the abundance of dominant bacteria. The TDS content was positively correlated with Candidatus_Aenigmarchaeota ( r = 0.719, P < 0.01). The Ca content was positively correlated with Candidatus_Diaphorotes ( r = 0.587, P < 0.05), and negatively correlated with Candidatus_Lokiaarchaeota ( r = − 0.835, P < 0.01) and with Candidatus_levy bacteria ( r = − 0.596, P < 0.05). The Mg content was positively correlated with Crenarchaeota ( r = 0.723, P < 0.01) and Euryarchaeota ( r = 0.589, P < 0.05). Soil pH was positively correlated with Candidatus_korarchaeota ( r = 0.583, P < 0.05). The TN was positively correlated with Candidatus_Heimdallarchaeota ( r = − 0.741, P < 0.01), Bacteroidetes ( r = − 0.821, P < 0.01), and Proteobacteria ( r = − 0.889, P < 0.01). The TN was negatively correlated with Candidatus_levy bacteria ( r = 0.699, P < 0.05). The AK was positively correlated with Candidatus_Aenigmarchaeota ( r = 0.663, P < 0.05). The TN had the greatest influence on the change of microbial composition and quantity among the 13 indicators of soil. In the correlation heatmap, the main factors that significantly influenced the functions and relative abundances of the soil microbiome were soil Mg, pH, TK, OM, TP, Na, AN, P, TN, TDS, and Ca (Fig. C). The four soil samples were grouped by screening the top 200 most abundant species at the genus level, after removing species without names; Pearson’s correlations were calculated to screen for relationships with Pearson’s correlation |r| > 0.8, P < 0.05. A co-occurrence network analysis was performed and a microbial co-occurrence network constructed for each treatment group of the four soil samples. In addition, the modular structure of each network was revealed by visualizing nine main modules within these networks (Fig. ). Chloroflexi was the phylum with the highest number of nodes in the network in the four soil samples. In addition, Bacteroidetes and Deinococcus-Thermus had the highest number of nodes for the CK; Proteobacteria and Bacteroidetes had the highest number of nodes for the Hg treatment; Planctomycetes and Bacteroidetes nodes were the most numerous for the Sg treatment; and Bacteroidetes and Deinococcus-Thermus nodes were the most numerous for Hg||Sg treatment.   In the pot experiment, the Hg biomass under 0, 50, 100, 150, and 200 mmol·L − 1 NaCl treatment was the largest, consistent with the field experiment. The growth of Hg was stronger than that of Sg and Hg||Sg (Fig. C). The aboveground biomass of H. glomeratus and S. glauca under three improved modes was measured (Table ). The biomass of Hg was 12.35% and 5.68% higher than for Hg||Sg and Sg, respectively. Aboveground biomass of the different treatments differed significantly: Hg > Hg||Sg > Sg.   After planting halophytes, Na content in soil decreased significantly, including 0.732 mg/kg under Hg treatment, 0.289 mg/kg under Sg treatment, and 0.530 mg/kg under Hg||Sg treatment. Ca content in soil decreased significantly, including 10.279 mg/kg under Hg treatment, 5.097 mg/kg under Sg treatment, and 8.781 mg/kg under Hg||Sg treatment. Soil Mg content decreased significantly, including 2.125 mg/kg under Hg treatment, 1.310 mg/kg under Sg treatment, and 1.282 mg/kg under Hg||Sg treatment. However, P content in soil increased significantly, with an increase of 0.905 mg/kg under Hg treatment, 0.464 mg/kg under Sg treatment, and 0.662 mg/kg under Hg||Sg treatment. It is worth noting that there was a significant correlation between halophytes before and after seeding except for bare soil ( P < 0.05). The impact of halophytes on soil pH was related to cropping type ( P < 0.05, Table ). There were significant differences in pH between the Hg and Hg||Sg sampled areas during seedling and after harvesting (Table ). Before and after planting halophytes, the soil pH of sample areas of Hg, Sg, and Hg||Sg decreased to 0.52, 0.19, and 0.34, respectively. For Hg, Sg, and Hg||Sg treatments, the TDS content in the soil decreased by 1.138, 0.744, and 0.923 g/kg, respectively, with the greatest decrease for Hg. Plant type significantly affected soil OM content. For Hg, Sg, and Hg||Sg treatments, the OM content in the soil of each treatment increased by 4.124, 1.113, and 2.563 g/kg, respectively. The order of OM content in the soil after different halophyte treatments follows: Hg > Hg||Sg > Sg. The impact of halophytes on soil TN content is shown in Table , the highest increase in soil TN content was Hg (0.231 g/kg). Under different coverage of halophytes, the highest increase AN content in the rhizosphere soil of vegetation was for Hg (27.399 mg/kg). The order of TN and AN contents in rhizosphere soil for the halophyte treatments follows: Hg > Hg||Sg > Sg. Soil TP content is mainly influenced by soil-forming parent material and climate type, but there is also a relationship with vegetation activities. TP content only increase after Hg treatment (0.091 g/kg), because there are no statistical different among any other samples. The AP content also increased, with the greatest increase for Hg (5.297 mg/kg). After treatment with different halophytes, the TP and AP contents in the rhizosphere soil were as follows: Hg > Hg||Sg > Sg. Apart from CK, the highest reduction in soil TK content was for Hg (3.712 g/kg), while the lowest reduction was for Sg (1.196 g/kg). Compared to seedling stage, soil AK levels differed markedly at harvest stage ( P < 0.05). Overall, after treatment with different halophytes, the order of TK and AK content in rhizosphere soil was Hg > Hg||Sg > Sg. As can be seen from Table , the aboveground content of Na + in halophytes was the highest under Hg, while the aboveground content in halophytes under Sg was the lowest. The aboveground part content of K + in halophytes was the highest under Sg, and the lowest under Hg||Sg. The content of Ca 2+ in the aboveground part of halophytes was the highest under Hg, and the lowest under Sg. The content of Mg 2+ in the aboveground part of halophytes was the highest under Hg and the least under Sg.   Metagenomic sequencing was used to analyze the characteristics and communities of soil microorganisms . Metagenome sequencing produced 121,882.49 Mbp of raw data. After removing low-quality reads, 121,405.36 Mbp of clean data were obtained. After sequencing, we obtained a total of 3.2 × 10 5 to 4.7 × 10 5 contigs and 2.0 × 10 5 to 5.1 × 10 5 open reading frames (ORFs) (Tables S1 and S2). A total of six kingdom, 161 phylum, 254 class, 426 order, 754 family, 2257 genus, and 9100 species level classifications were obtained by metagenomic sequencing. According to the species annotation, the microbial composition of soil samples was mainly bacteria (over 84.11%) (Fig. A). Analysis of species differences at the phylum level in a Wayne diagram showed seven species unique to CK, two species unique to Hg, one species unique to Sg, and a total of 114 species in CK, Hg, Sg, and Hg||Sg, which had 160, 48, 54, and 54 unique genera, respectively; with 930 genera shared by the four treatments (Fig. B and C). In this experiment, the effects of bare ground and Hg, Sg, and Hg||Sg treatments on the Chao, ACE, Shannon, and Simpson indices of microbial communities in remediated saline soils were investigated. The α-diversity index of soil microorganism communities showed significantly decreased species α-diversity (Chao 1 and ACE), and significantly increased species α-diversity (Shannon and Simpson) (Fig. D–G). The microbial community in the bare land (CK) significantly differed from those for the three halophyte cover treatments according to NMDS (Fig. H) . The NMDS analysis showed that with a stress rate of 0.007, among the three phytoremediation treatments, there was a clear difference in theβ-diversity estimates of soil microorganisms proportions based on NMDS. It is noteworthy that the symbols were distributed in four quadrants each, representing the soil microbiota of CK, Hg, Sg, and Hg||Sg. The distribution variation between the CK, Hg, Sg, and Hg||Sg treatments showed a significant effect of the cover plants on soil microorganism communities. Fig. 4The LEfSe method identifies the significantly different abundant taxa of soil bacterial communities (A). The taxa with significantly different abundances between treatments are represented by colored dots, and from the center outwards they represent the kingdom, phylum, class, order, family, genus, and species levels. Colored shadows represent trends of significantly different taxa. Only taxa with an LDA significance threshold > 3.5 are shown in this figure. Each colored point has an effect size LDA score as shown in Fig. S1. The RDA of bacterial community and environmental factors (B). Heatmap of the correlations between phyla and soil factors (C), note ** P < 0.01; * P < 0.05. The abbreviations indicate the same as in Fig. . The sequencing results were annotated by species, and the UPGMA (unweighted pair-group method using arithmetic averages) of each soil sample was constructed with weighted UniFrac distance matrix at gate-level means, non-weighted group average method clustering tree (Fig. I). The bacterial groups with the highest relative abundance in the rhizosphere soil were Proteobacteria and Actinobacteria. Bacteroidetes, Gemmatimonadetes, and Chloroflexi were all in low abundance in the soil. The cluster diagram showed that the community structure composition of the four soil microorganisms at the phylum level was similar for Hg and Sg treatment. Although the dominant phyla in the soils of the four treatments were essentially the same, the relative abundance of individual dominant phyla differed significantly at different stages. For example, the abundances of Proteobacteria in CK, Hg, Sg, and Hg||Sg treatments were 29.63%, 25.71%, 22.21%, and 23.18%, respectively (Fig. I). Chloroflexi had a significant positive correlation with salt tolerance, whereas Proteobacteria had a significant negative correlation. Among the top 20 genera, the dominant phylum in CK, Hg, Sg, and Hg||Sg was Proteobacteria, with 32.86%, 22.78%, 22.76%, and 21.6%, respectively (Fig. A). Furthermore, the Hg, Sg, and Hg||Sg treatments had significantly higher relative abundances of Chloroflexi, Candidatus_Tectomicrobia, and Acidobacteria compared with CK. The KEGG database was used to predict the gene function of non-redundant gene sets from saline soils covered by different halophytes. A total of 1,046,716 reads could correspond with the functional annotation results. There were 72,189 items in category Cellular Processes, 29,423 in category Human Diseases, and 40,508 in category Organismal Systems. There were 743,954 in Metabolism, 70,364 in Genetic Information Processing, and 90,278 in Environmental Information Processing. Among the four treatments, the most microbial functional genes belonged to Metabolism, while the least belonged to Human Diseases and Organismal Systems (Fig. B). The LEfSe analyses (LDA values shown in Fig. ) were used to check for significant differences in the abundance of soil bacterial taxa and to confirm the biological relevance of soil microbial species under different treatments (Fig. A). In particular, Gammaproteobacteria, Xanthomonadales, Proteobacteria, and Deltaproteobacteria were the most altered soil microorganism taxa for the CK; Betaproteobacteria, Acidobacteria, Burkholderiales, and Rhodospirillales were the most altered for Hg treatment; Sphingomonas and Gemmatimonadetes were the most altered for Sg treatment; and Actinobacteria, Chloroflexi, and Propionibacteriales were the most altered for Hg||Sg treatment. The KEGG heat map shows that for CK, the Two component system and Fatty acid metabolism are high, but decrease after planting Hg and Sg. After planting Sg, Valine, leucine, and isoleucine degradation, Propanoate metabolism, Citrate cycle (TCA cycle), Glyoxylate and dicarboxylate metabolism, Aminoacyl-tRNA biosynthesis, Purine metabolism, Carbon fixation pathways in prokaryrotes, ABC transporters, Butanoate metabolism, Alanine, aspartate, and glutamate metabolism, and Amino sugar and nucleoside sugar metabolism significantly increased. After planting Hg, there were no significant changes. After planting of Hg||Sg, Amino sugar and nucleotide sugar metabolism increased, while Fatty acid metabolism decreased. After Hg||Sg processing, Cysteine and methionine metabolism, Metabolic pathways, Oxidative physiology, Methane metabolism, Microbial metabolism in diverse environments, Quorum sensing, Carbon metabolisms, Pyruvate metabolism, Biosynthesis of amino acids, Glycolysis/gluconeogenesis, Biosynthesis of secondary metabolites, and Glycine, serine, and threonine metabolism significantly increased (Fig. ).   The RDA was used out to understand the effect of changes in key soil physical and chemical properties on the composition of soil microbial communities under four saline alkaline soil treatments. Two RDA axes explained 96.94% of the differences in soil microbial community structure (Fig. B), indicating that environmental factors significantly influenced bacterial community structure. The RDA plots used Mg, pH, TK, OM, TP, Na, AN, P, TN, TDS, and Ca as soil environmental variables (represented by blue arrows). Only Mg was present in the third quadrant, with other environmental factors concentrated in the first and fourth quadrants (Fig. B). A greater effect on the microbial community composition was indicated by the longer exposure to TN. A lesser effect on microbial community composition was indicated by the shorter exposure to Ca. The dominant phyla, including Proteobacteria, Acidobacteria, and Actinobacteria, were the main contributors to microbial community changes. The RDA revealed that soil microbial groups were distributed in different quadrants according to functional analysis of CK, Hg, Sg, and Hg||Sg patches. Soil OM, TP, Na, AN, P, TN, and AK were significantly correlated with Sg soil microbial functions. Soil TK and pH were significantly correlated with soil microbial functions in the Hg treatment. The microorganisms whose components were in the top 20 with obvious differences among samples were selected, and their correlations with environmental factors analyzed. The TDS, Ca, Mg, pH, TN, AN, and AK were closely related to the abundance of dominant bacteria. The TDS content was positively correlated with Candidatus_Aenigmarchaeota ( r = 0.719, P < 0.01). The Ca content was positively correlated with Candidatus_Diaphorotes ( r = 0.587, P < 0.05), and negatively correlated with Candidatus_Lokiaarchaeota ( r = − 0.835, P < 0.01) and with Candidatus_levy bacteria ( r = − 0.596, P < 0.05). The Mg content was positively correlated with Crenarchaeota ( r = 0.723, P < 0.01) and Euryarchaeota ( r = 0.589, P < 0.05). Soil pH was positively correlated with Candidatus_korarchaeota ( r = 0.583, P < 0.05). The TN was positively correlated with Candidatus_Heimdallarchaeota ( r = − 0.741, P < 0.01), Bacteroidetes ( r = − 0.821, P < 0.01), and Proteobacteria ( r = − 0.889, P < 0.01). The TN was negatively correlated with Candidatus_levy bacteria ( r = 0.699, P < 0.05). The AK was positively correlated with Candidatus_Aenigmarchaeota ( r = 0.663, P < 0.05). The TN had the greatest influence on the change of microbial composition and quantity among the 13 indicators of soil. In the correlation heatmap, the main factors that significantly influenced the functions and relative abundances of the soil microbiome were soil Mg, pH, TK, OM, TP, Na, AN, P, TN, TDS, and Ca (Fig. C). The four soil samples were grouped by screening the top 200 most abundant species at the genus level, after removing species without names; Pearson’s correlations were calculated to screen for relationships with Pearson’s correlation |r| > 0.8, P < 0.05. A co-occurrence network analysis was performed and a microbial co-occurrence network constructed for each treatment group of the four soil samples. In addition, the modular structure of each network was revealed by visualizing nine main modules within these networks (Fig. ). Chloroflexi was the phylum with the highest number of nodes in the network in the four soil samples. In addition, Bacteroidetes and Deinococcus-Thermus had the highest number of nodes for the CK; Proteobacteria and Bacteroidetes had the highest number of nodes for the Hg treatment; Planctomycetes and Bacteroidetes nodes were the most numerous for the Sg treatment; and Bacteroidetes and Deinococcus-Thermus nodes were the most numerous for Hg||Sg treatment.   Effects of halophyte mulch on soil physicochemical properties The changing of soil properties is an essential element in changing microbial communities. In general, plants suitable for desalting in salinized soils should have high salt tolerance and produce more biomass . After planting cotton and alfalfa, the aboveground biomass of cotton and Suaeda salsa intercropping was higher than that of cotton and alfalfa intercropping during 2014–2016, by 20.5%, 26.3%, and 28.7%, respectively .In our study, Hg produced the most biomass, 9.6 t ha − 1 , in salinized soils with pH 8.36 (Table ). The field experiment and pot experiment results showed that the strength of the effect of different saline plants in improving saline soils was Hg > Hg||Sg > Sg (Table ). Our findings are similar to those of other studies using halophytes for soil desalination. Changes in plant growth conditions, soil pH, and nutrient levels are likely to be the main causes of changes in structure of the soil microbial community . As shown in Table , the content of AN, AP, and AK in soil decreased when no halophytes were planted to repair saline-alkali soil (CK), because the release and conversion ability of microorganisms to these nutrients was generally reduced in saline soil . On the contrary, the content of AN, AP and AK in soil increased after one season of halophyte harvest, and the effect was most obvious after halophyte treatment. This is because after phytoremediation, these nutrients are increased in the saline soil . The release and conversion ability of microorganisms to these nutrients was generally reduced in saline soil. After Elaeagnus angustifolia was planted in the salt-alkali land of the Songnen Plain, soil pH and electrical conductivity decreased, while contents of TP, TN, TK, DOC, DOM, and AK increased . After planting halophytes, soil pH in the Hg, Sg, and Hg||Sg sample areas decreased, and the TDS content in the halophyte rhizosphere decreased, with the greatest decrease for Hg. In particular, H. glomeratus monocropping significantly reduced soil pH and salinity compared with bare soil and the seedling stage (Table ). Results showed that soil pH, electrical conductivity, OM, and TK were the main physical and chemical properties affecting microbial communities. Therefore, halophytes desalinate soil by absorbing salt from soil and accumulating dry matter in aboveground parts, with Hg working best. Effects of planting halophytes on soil microbial communities To further explore the impact of H. glomeratus and S. glauca monocropping with that of H. glomeratus and S. glauca intercropping on improving saline soil in Northwestern China, the soil microbial communities and their functions were studied using metagenomic sequencing technology. Many studies have shown that soil salinity significantly inhibits the number, composition, and diversity of most soil microorganisms . Results confirmed that phytoremediation treatment significantly increased the diversity and abundance of soil bacteria . The α-diversity analysis revealed a decreasing trend in the ACE of the three improved Chao1 treatments, indicating that planting halophytes led to a reduction in bacterial abundance in saline-alkali soil. However, the Shannon and Simpson indices of the three improved treatments showed increasing trends, suggesting that halophyte planting increased saline microbial community diversity (Fig. ). Feng et al.  showed that planting S. salsa can reduce salt stress in soil, prevent degradation of saline soils, and increase the diversity of soil bacterial communities, thus benefiting saline soils in coastal areas. Microorganisms have different adaptability to different soil conditions . Earlier studies found that Chloroflexi has desiccation tolerance and drought resistance, and the relative abundance of Chloroflexi was also high in this study – the bacteria in this phylum can produce energy through photosynthesis, reflecting their photoautotrophic properties . In addition, Chloroflexi and Acidobacteria can promote nutrient uptake by the root system and maintain the balance between it and the microenvironment . Du et al.  found that Acidobacteria and Proteobacteria were the dominant bacterial groups in the inter-root soils of nine plants in saline and alkaline soils in Daqing, when they studied the microbial community structure in inter-root soils. In this study, dominant microorganisms such as Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi were present in the soils of the four treatments (Fig. A), and previous studies have shown that Actinobacteria and Acidobacteria as the dominant bacterial phyla are all salinophilic bacteria, and their occupancy in salinized soils is high. The soil in this experimental area is alkaline, which provides a good environment for the growth of Actinomycetes (Actinomycetes like a slightly alkaline environment) and makes them widely distributed in saline soil of Northwestern China . The relative abundances of Chloroflexi and Actinobacteria increased significantly with phytoremediation treatment in this study. After the modified treatment, pH in the saline soil tended to decrease, which was favorable for survival of Acidobacteria . The dominant bacterial phyla in this study area were consistent with previous studies . There are more microbial species in bare soil at the phylum and genus levels 9 (Fig. B-C). This can be attributed to the presence of various special environmental conditions in these soils, resulting in the selection of microorganisms with extreme tolerance. After plant restoration, the soil environment is improved, which helps the growth of some new microorganisms, but may lead to the reduction of the original saline-tolerant microorganisms . Therefore, although there are fewer microbial species in the repaired soil, there is usually a significant improvement in function and soil quality . In addition, the LEFSe analysis showed that the three types of phytoremediation treatments caused significant changes in several groups of microorganisms (Fig. A) : Gammaproteobacteria of the Proteobacteria was the most changed soil microorganism taxa under the CK; Betaproteobacteria was the most altered soil microorganism taxa under the Hg treatment – Betaproteobacteria is a class in the Proteobacteria and is most closely related to γ-Proteobacteria; under Sg treatment, Sphingomonas was the most altered soil microorganism taxa, and has high metabolic regulation mechanism and gene regulation ability, giving it great application potential in environmental remediation and plant growth promotion; and Actinobacteria was the most altered soil microorganism taxa under Hg||Sg treatment, is one of the most widespread bacteria in soil, and has attracted widespread attention for its excellent ability to degrade plant residues. The metagenomic analysis, which comprehensively reflects the variation in the functional constitution of soil microbes, showed that metabolism is the main function of soil microorganisms in saline soils to alleviate the adverse effects of salinized soils by comparing with the KEGG level A database (Fig. B). Relationship between microorganisms and soil physicochemical properties Soil microorganisms bridge the gap between soil and plant, and microorganisms can convert nutrients provided by soil into forms that can be absorbed and used by plants. At the same time, microorganisms can respond to the soil through altering community structure to maintain a dynamic balance of the soil microenvironment . This study measured and analyzed the physicochemical properties of saline soils under four treatments and found that soil salinity decreased after saline plant phytoremediation treatment, with the decrease reaching 93.89% after Hg phytoremediation treatment, and soil OM content increased. The RDA and Pearson correlation analysis (Fig. B and C) showed that specific bacterial groups were associated with specific soil factors, and soil nutrient content was an important environmental factor influencing soil microbial community diversity and richness , while OM and pH also played significant roles in microbiota composition. For example, the dominant bacterial phylum Acidobacteria was positively correlated with soil pH and TK. Many studies have also found that soil properties can directly affect microbial community structure . In this study, TN, OM, and Mg contents and pH were the main environmental factors causing differences in soil microbial community structure in saline soil of Northwestern China. There was clear separation of CK, Hg, Sg, and Hg||Sg treatments (Fig. H). Combined with the changes of network topological characteristics, the average clustering coefficients of Hg and Sg treatments significantly increased with the improvement, while the average clustering coefficients of Hg||Sg were basically unchanged, indicating that the aggregation and interaction of the microbial community co-occurrence network increased after Hg and Sg treatment. Thus, the Hg and Sg treatments not only improved the symbiotic relationship between microorganisms, but also made a closer connection between microbial communities.   The changing of soil properties is an essential element in changing microbial communities. In general, plants suitable for desalting in salinized soils should have high salt tolerance and produce more biomass . After planting cotton and alfalfa, the aboveground biomass of cotton and Suaeda salsa intercropping was higher than that of cotton and alfalfa intercropping during 2014–2016, by 20.5%, 26.3%, and 28.7%, respectively .In our study, Hg produced the most biomass, 9.6 t ha − 1 , in salinized soils with pH 8.36 (Table ). The field experiment and pot experiment results showed that the strength of the effect of different saline plants in improving saline soils was Hg > Hg||Sg > Sg (Table ). Our findings are similar to those of other studies using halophytes for soil desalination. Changes in plant growth conditions, soil pH, and nutrient levels are likely to be the main causes of changes in structure of the soil microbial community . As shown in Table , the content of AN, AP, and AK in soil decreased when no halophytes were planted to repair saline-alkali soil (CK), because the release and conversion ability of microorganisms to these nutrients was generally reduced in saline soil . On the contrary, the content of AN, AP and AK in soil increased after one season of halophyte harvest, and the effect was most obvious after halophyte treatment. This is because after phytoremediation, these nutrients are increased in the saline soil . The release and conversion ability of microorganisms to these nutrients was generally reduced in saline soil. After Elaeagnus angustifolia was planted in the salt-alkali land of the Songnen Plain, soil pH and electrical conductivity decreased, while contents of TP, TN, TK, DOC, DOM, and AK increased . After planting halophytes, soil pH in the Hg, Sg, and Hg||Sg sample areas decreased, and the TDS content in the halophyte rhizosphere decreased, with the greatest decrease for Hg. In particular, H. glomeratus monocropping significantly reduced soil pH and salinity compared with bare soil and the seedling stage (Table ). Results showed that soil pH, electrical conductivity, OM, and TK were the main physical and chemical properties affecting microbial communities. Therefore, halophytes desalinate soil by absorbing salt from soil and accumulating dry matter in aboveground parts, with Hg working best.   To further explore the impact of H. glomeratus and S. glauca monocropping with that of H. glomeratus and S. glauca intercropping on improving saline soil in Northwestern China, the soil microbial communities and their functions were studied using metagenomic sequencing technology. Many studies have shown that soil salinity significantly inhibits the number, composition, and diversity of most soil microorganisms . Results confirmed that phytoremediation treatment significantly increased the diversity and abundance of soil bacteria . The α-diversity analysis revealed a decreasing trend in the ACE of the three improved Chao1 treatments, indicating that planting halophytes led to a reduction in bacterial abundance in saline-alkali soil. However, the Shannon and Simpson indices of the three improved treatments showed increasing trends, suggesting that halophyte planting increased saline microbial community diversity (Fig. ). Feng et al.  showed that planting S. salsa can reduce salt stress in soil, prevent degradation of saline soils, and increase the diversity of soil bacterial communities, thus benefiting saline soils in coastal areas. Microorganisms have different adaptability to different soil conditions . Earlier studies found that Chloroflexi has desiccation tolerance and drought resistance, and the relative abundance of Chloroflexi was also high in this study – the bacteria in this phylum can produce energy through photosynthesis, reflecting their photoautotrophic properties . In addition, Chloroflexi and Acidobacteria can promote nutrient uptake by the root system and maintain the balance between it and the microenvironment . Du et al.  found that Acidobacteria and Proteobacteria were the dominant bacterial groups in the inter-root soils of nine plants in saline and alkaline soils in Daqing, when they studied the microbial community structure in inter-root soils. In this study, dominant microorganisms such as Proteobacteria, Actinobacteria, Acidobacteria, and Chloroflexi were present in the soils of the four treatments (Fig. A), and previous studies have shown that Actinobacteria and Acidobacteria as the dominant bacterial phyla are all salinophilic bacteria, and their occupancy in salinized soils is high. The soil in this experimental area is alkaline, which provides a good environment for the growth of Actinomycetes (Actinomycetes like a slightly alkaline environment) and makes them widely distributed in saline soil of Northwestern China . The relative abundances of Chloroflexi and Actinobacteria increased significantly with phytoremediation treatment in this study. After the modified treatment, pH in the saline soil tended to decrease, which was favorable for survival of Acidobacteria . The dominant bacterial phyla in this study area were consistent with previous studies . There are more microbial species in bare soil at the phylum and genus levels 9 (Fig. B-C). This can be attributed to the presence of various special environmental conditions in these soils, resulting in the selection of microorganisms with extreme tolerance. After plant restoration, the soil environment is improved, which helps the growth of some new microorganisms, but may lead to the reduction of the original saline-tolerant microorganisms . Therefore, although there are fewer microbial species in the repaired soil, there is usually a significant improvement in function and soil quality . In addition, the LEFSe analysis showed that the three types of phytoremediation treatments caused significant changes in several groups of microorganisms (Fig. A) : Gammaproteobacteria of the Proteobacteria was the most changed soil microorganism taxa under the CK; Betaproteobacteria was the most altered soil microorganism taxa under the Hg treatment – Betaproteobacteria is a class in the Proteobacteria and is most closely related to γ-Proteobacteria; under Sg treatment, Sphingomonas was the most altered soil microorganism taxa, and has high metabolic regulation mechanism and gene regulation ability, giving it great application potential in environmental remediation and plant growth promotion; and Actinobacteria was the most altered soil microorganism taxa under Hg||Sg treatment, is one of the most widespread bacteria in soil, and has attracted widespread attention for its excellent ability to degrade plant residues. The metagenomic analysis, which comprehensively reflects the variation in the functional constitution of soil microbes, showed that metabolism is the main function of soil microorganisms in saline soils to alleviate the adverse effects of salinized soils by comparing with the KEGG level A database (Fig. B).   Soil microorganisms bridge the gap between soil and plant, and microorganisms can convert nutrients provided by soil into forms that can be absorbed and used by plants. At the same time, microorganisms can respond to the soil through altering community structure to maintain a dynamic balance of the soil microenvironment . This study measured and analyzed the physicochemical properties of saline soils under four treatments and found that soil salinity decreased after saline plant phytoremediation treatment, with the decrease reaching 93.89% after Hg phytoremediation treatment, and soil OM content increased. The RDA and Pearson correlation analysis (Fig. B and C) showed that specific bacterial groups were associated with specific soil factors, and soil nutrient content was an important environmental factor influencing soil microbial community diversity and richness , while OM and pH also played significant roles in microbiota composition. For example, the dominant bacterial phylum Acidobacteria was positively correlated with soil pH and TK. Many studies have also found that soil properties can directly affect microbial community structure . In this study, TN, OM, and Mg contents and pH were the main environmental factors causing differences in soil microbial community structure in saline soil of Northwestern China. There was clear separation of CK, Hg, Sg, and Hg||Sg treatments (Fig. H). Combined with the changes of network topological characteristics, the average clustering coefficients of Hg and Sg treatments significantly increased with the improvement, while the average clustering coefficients of Hg||Sg were basically unchanged, indicating that the aggregation and interaction of the microbial community co-occurrence network increased after Hg and Sg treatment. Thus, the Hg and Sg treatments not only improved the symbiotic relationship between microorganisms, but also made a closer connection between microbial communities.   This study comprehensively studied the structure composition and function of rhizosphere soil microbial communities of halophytes H. glomeratus and S. glauca in saline soil in Northwestern China by analyzing the biomass of halophytes, soil physicochemical properties, and metagenomic analysis (Graphical Abstract). The soil microbial community composition changed under different phytoremediation, and the ameliorative effect of various halophytes on saline soil showed that Hg, Sg, and Hg||Sg increased the diversity and function of the soil microbial community. Proteobacteria, Acidobacteria, Actinobacteria, and Chloroflexi were the main microorganisms utilized by the halophytes. In addition, microbial community changes were mainly caused by plant, TN, OM, Mg, and pH changes. The results showed that monocropping and intercropping could improve saline soil effectively, but interestingly, monocropping of H. glomeratus had the best effect on saline soil, as proven in the pot experiment. The results are important for guiding saline soil phytoremediationin the semi-arid area of Northwestern China using halophyte H.glomertaus .   Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2   