Promoting chiral metalaxyl degradation by bioaugmentation with a host-guest soil microbial consortium

Bioaugmentation with isolated pollutant-degrading strains is often limited by their poor establishment in native soils. The present study tested the hypothesis that introducing an active “guest” soil with high rac-metalaxyl-degrading capacity into a poorly degrading “host” soil would promote the establishment of degrading microorganisms, reshape the bacterial community, and enhance enantioselective transformation. Host soil (S1) and guest soil (S2) were mixed at various ratios and preincubated for different durations. Microbial biomass carbon (MBC), soil enzyme activities, bacterial community characteristics, and rac-metalaxyl transformation kinetics were evaluated. Soil mixing increased MBC by 10%–15% compared with values predicted from proportional contributions of the individual soils, and bacterial richness in host–guest soils exceeded that of either native soil. Selected enzyme activities and the relative abundances of dominant bacterial phyla responded nonlinearly to the guest soil proportion. Bacterial community dissimilarity increased logarithmically with the proportion of guest soil, maintaining a distinct community structure even after 120 days of preincubation. In the 4:1 host–guest mixture, the initial transformation rate (r 0) reached 48% and 71% of that in guest soil S2 after 14 and 120 days of preincubation, respectively. Transformation enantioselectivity was more closely associated with bacterial community structure than with richness. Active soil can serve as a functionally stable whole-community inoculum, offering a practical bioaugmentation strategy when the establishment of single isolated strains is constrained.

Microorganisms are ubiquitous and highly abundant in soil, which may contain up to 10 9 bacterial cells per gram (Roesch et al., 2007). A recent global estimate suggests that microbially derived carbon contributes approximately 40% of the global soil carbon stock (Hu et al., 2024). Soil microorganisms regulate numerous biogeochemical and ecological processes, including carbon and nitrogen cycling (Mason-Jones et al., 2021; Sokol et al., 2022), the transformation of xenobiotic chemicals (Han et al., 2021), and the maintenance of multiple ecosystem functions (Delgado-Baquerizo et al., 2016). However, microbial abundance, diversity, and community composition vary substantially among soils (Labouyrie et al., 2023; Roesch et al., 2007; Sokol et al., 2022). Such variation, together with differences in soil physicochemical properties, may contribute to the contrasting transformation of organic pollutants among terrestrial ecosystems. Bioaugmentation has therefore been proposed as an environmentally compatible approach for enhancing the detoxification of contaminated soils (Cycoń, 2026; Li et al., 2024; Mrozik and Piotrowska-Seget, 2010). Conventional bioaugmentation often involves the introduction of a selected bacterial strain with a high capacity to transform the target pollutant (Zhao et al., 2025), whereas more recent studies have increasingly investigated microbial consortia because of their potentially greater metabolic versatility and environmental adaptability (Lü et al., 2024). Nevertheless, bioaugmentation performance remains variable, partly because introduced strains or consortia may exhibit poor survival, establishment, or activity under complex in situ conditions (Fida et al., 2017). Moreover, the ecological behavior of introduced microorganisms and their effects on resident soil microbial communities remain insufficiently understood (Moreno-Forero and van der Meer, 2015; Zhao et al., 2025).

Immobilization has been used to improve the persistence of introduced microorganisms and enhance pollutant transformation. Several studies have demonstrated that immobilized microbial inocula can survive more effectively and promote the removal of target pollutants (Liu et al., 2026; Li et al., 2022; Wang et al., 2010). For example, Wang et al. (2010) reported that inoculation with a 1,2,4-trichlorobenzene (1,2,4-TCB)-mineralizing microbial community immobilized on clay particles resulted in greater cumulative 1,2,4-TCB mineralization than inoculation with either a single degrading strain or a microbial consortium in liquid form. Similarly, biochar carrying selected pollutant-degrading bacteria achieved an 80.54% reduction in chemical oxygen demand in contaminated soil after 63 days of treatment (Liu et al., 2026). However, the large quantities of carrier material that may be required could restrict the field-scale application of immobilized inocula (Owsianiak et al., 2010). These constraints motivate the evaluation of less processed inocula that can transfer pollutant-transformation capacity while retaining the ecological interactions present in the source environment.

Because pollutant-degrading strains and consortia are frequently obtained from soils in which the target compound is rapidly eliminated, an active soil can itself be considered a whole-community inoculum. In the present study, such an active soil is referred to as “guest soil,” whereas the receiving soil with limited degradation capacity is referred to as “host soil.” Unlike the introduction of an isolated strain or a defined consortium, guest-soil inoculation transfers a taxonomically complex microbial community together with its native soil matrix and does not require strain isolation, consortium reconstruction, or the addition of a separate carrier. The use of active soil as a microbial inoculum has been reported previously but has received relatively limited research attention. Gentry et al. (2004) demonstrated that the addition of activated soil enhanced chlorobenzoate degradation in a non-active soil. Innemanová et al. (2018) further showed that inoculation with active soil pre-amended with exogenous degraders improved the degradation of polycyclic aromatic hydrocarbons in an aged industrial soil. These studies established that degradation capacity can be transferred through active-soil inoculation. However, they primarily evaluated whether pollutant removal could be enhanced. Systematic evidence remains limited regarding how the proportion of active soil influences bacterial community reassembly and soil enzyme activities and whether these ecological changes are associated with pollutant transformation. In particular, the effects of guest-soil proportion on the enantioselective transformation of chiral pesticides have rarely been investigated.

The transformation of chiral pesticides provides an informative system for investigating the relationship between soil microbial communities and pollutant biotransformation because the two enantiomers may be transformed at different rates. Enantioselective pesticide degradation is frequently associated with microbially or enzymatically mediated transformation processes (Arenas et al., 2022). Racemic metalaxyl (rac-metalaxyl) is a widely used fungicide for the control of plant diseases, and its enantioselective degradation in soil has been extensively investigated (Buerge et al., 2003; Celis et al., 2015; Celis et al., 2013; Gámiz et al., 2013; Gámiz et al., 2016; Huang et al., 2018; Liang et al., 2016; Zhou et al., 2020). In the present study, two agricultural soils with contrasting rac-metalaxyl degradation capacities were selected: rac-metalaxyl was rapidly transformed in soil S2 but showed little degradation in soil S1 over the same incubation period. Soil S1 was therefore used as the host soil, whereas soil S2 was used as the guest soil, and the two soils were combined at different host ratios.

The current study established a ratio-controlled host–guest soil system that integrates measurements of bacterial community composition and diversity, soil enzyme activities, and enantiomer-specific rac-metalaxyl transformation. The objectives were therefore to (i) determine how the host soil ratio affects bacterial community composition, bacterial diversity, and soil enzyme activities and (ii) examine whether these changes are associated with the degradation kinetics and enantioselectivity of rac-metalaxyl. By focusing on ratio-dependent community responses and enantiomer-specific transformation outcomes, this study addresses the knowledge gap between efficacy-oriented active-soil inoculation and the ecological responses accompanying whole-soil bioaugmentation.

Chemicals

Racemic-metalaxyl (rac-metalaxyl, 98%) was purchased from Aladdin (Shanghai, China). Ultrapure water was used throughout the experiments.

Soil samples

Native soil (host soil S1 and guest soil S2): Two agricultural soils with distinct properties were used in this study (Huang et al., 2018). These soils were selected based on previous experiments that demonstrated the varying enantioselective transformation of rac-metalaxyl in each soil (Huang et al., 2018). The soil with a low capacity for rac-metalaxyl degradation was designated as host soil S1, whereas the soil with a high degradation capacity was designated as guest soil S2. The essential parameters for host and guest soils were listed in Supplementary Table S1 in the Supplementary Material (SI).

Host−Guest soil: Air dried host soil S1 and guest soil S2 were directly mixed at different weight ratios ranging from 10:1 to 1:1 (host:guest; w: w). The resulting soils were then preincubated in the dark at 25 °C and a water content of 15% for 7, 14, 21 and 120 days.

Host−Guest reference soil: Air dried host soil S1 and guest soil S2 were preincubated separately under the same condition for 7, 14, 21 and 120 days. After preincubation, the corresponding host and guest soils were thoroughly mixed. The resulting mixtures were used as host−guest reference soils.

Incubation of rac -metalaxyl in soils

Different volumes of rac-metalaxyl stock solution (400 mg/L) were added to glass beaker containing 40 g of soil (native soil S1 or S2, host-guest soil, or host-guest reference soil) and thoroughly mixed. The resulting initial concentration of rac-metalaxyl in the soil were approximately 0.6, 1.1, 1.6, and 3.2 mg/kg. The soil samples were adjusted to a moisture content of 15%. Each beaker was sealed with a fine-meshed transparent film to minimize evaporation and incubated under light irradiation at 25 °C. The irradiation source is shown in Supplementary Figure S1 of the Supplementary Material (SI), and the irradiance at the soil surface was 1.2 mW/cm 2.

All treatments were established in three independently prepared and incubated beakers. Each beaker was regarded as an independent experimental unit and constituted one biological replicate (n = 3). At each sampling time, 2 g soil was collected separately from each beaker and retained as an independent sample throughout all subsequent analyses. Samples from different beakers were not pooled. The results were shown as the mean value of these samples (n = 3), and the error bars represented the standard deviation.

Bacterial community diversity and DNA content analysis

Native soil S1, S2, and host-guest soils preincubated for 14 days were collected for DNA extraction and bacterial community analysis. DNA was extracted with a FastDNA™ SPIN Kit (MP Biomedicals, Solon, USA) following the manufacturer’s instructions. The content of extracted DNA was determined with a NanoDrop ND-2000 spectrophotometer (Nano-Drop, Wilmington, DE, USA). The 16S rDNA fragment of the isolates was amplified using universal primer and polymerase chain reaction (PCR) products were sequenced in both directions. The forward and reverse primers were 338 F (5′-ACT​CCT​ACG​GGA​GGC​AGC​AG-3′) and 806 R (5′-GGACTACHVGGGTWTCTAAT-3′), respectively. The amplification reaction was performed with a program that consisted of an initial denaturation at 95 °C for 3 min, 27 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and an extension at 72 °C for 45 s, with the last cycle followed by a 10 min extension at 72 °C, before being stored at room temperature. The sequences were then determined by Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd (Shanghai, China). The 16S rDNA sequence was aligned with reference sequences in the Silva (http://www.arb-silva.de).

Raw reads were quality-filtered using fastp v0.23.4 and merged using FLASH v1.2.11. OTUs were clustered at 97% sequence similarity, and taxonomic assignment was performed against the SILVA release 138 database. The plateauing rarefaction curves and Good’s coverage values confirmed that the sequencing depth was sufficient.

Enzyme activity analysis method

Alkaline phosphatases activity (EC 3.1.3.1, pH 11) was measured using an S-AKP/ALP Test Kit (Baiaolaibo technology Co. Ltd, Beijing, China) according to the manufacturer’s instructions. Invertase activity (EC 3.2.1.26) was determined by quantifying the reducing sugars produced from sucrose hydrolysis using Fehling titrimetric method. Catalase activity (EC 1.11.1.6) was measured according to a previously reported method (Johnson and Temple, 1964).

Extraction and enantiomers analysis of metalaxyl

Soil samples containing residual metalaxyl were transferred into a glass tube, followed by the addition of 2 mL of acetonitrile and 2 mL of ultrapure water. The tubes were vortexed for 1 min to disperse the soil particles and then shaken in the dark on a reciprocating shaker at 250 rpm and 25 °C for 12 h. After centrifugation, the supernatants were filtered through 0.45 μm nylon membrane filter prior to analysis by chiral HPLC. Preliminary experiments showed that the recovery of metalaxyl using this extraction method exceed 90%. Enantioselective analysis was performed using chiral HPLC with a Biotech pump (System 522) (Pharmacia Biotech, Uppsala, Sweden) and an ultraviolet detector (Waters 2487, Milford, MA, USA). A CHIRALCEL OD-RH column (150 mm × 4.6 mm i. d., 5 μm) was used to separate the enantiomers with a water/acetonitrile (65/35, v / v) eluent mixture at a flow rate of 1 mL/min, 20 μL sample injection volume, and UV detection at 210 nm.

Data analysis

Enantiomer fraction (EF) was calculated by Equation 1: c S and c R are the concentrations of S-metalaxyl and R-metalaxyl, respectively.

The kinetics of S-metalaxyl and R-metalaxyl degradation (pseudo-first-order rate constant) were determined from the regression of the slope of a plot of S-metalaxyl or R-metalaxyl concentration versus time using Equation 2: c t and c 0 represent the concentration of metalaxyl at reaction time “ t ” and the initial concentration, respectively, and k obs (d −1) represent the observed transformation kinetic constants of rac-metalaxyl, which was expressed as k S and k R for S-metalaxyl and R-metalaxyl.

The initial transformation rate (r 0, mg kg −1 d −1) was recovered from the fit of the initial, linear portion of the concentration data of R-metalaxyl and S-metalaxyl with transformation time.

The soil samples used for enzyme activity and bacterial community analyses were pre-incubated for 14 days without metalaxyl amendment. Because all samples were collected at the same time point and differed only in the proportion of guest soil, guest-soil proportion was the sole explanatory factor in these analyses. Enzyme activities and univariate microbial community variables were therefore compared using one-way ANOVA. Tukey’s HSD test was used for pairwise comparisons. Exact p -values and 95% confidence intervals were reported where applicable. Statistical analyses were based on three independent biological replicates per treatment (n = 3). The significance symbols are retained only as visual aids and are defined as follows: * for 0.01 < p < 0.05, for 0.001 < p < 0.01, and * for p < 0.001. We have also added 95% confidence intervals for the reported group estimates.

Microbial abundance and enzyme activity in native and host-guest soils

The MBC of host soil S1 was 70.0 ± 1.1 mg C/kg, while that of guest soil S2 was 142.7 ± 6.3 mg C/kg. After the two soils were mixed, the MBC values of the host-guest soils were 84.6 ± 0.6, 94.9 ± 5.1, 109.1 ± 9.7, and 117.3 ± 4.6 mg C/kg at host:guest ratios of 10:1, 4:1, 2:1, and 1:1, respectively. These results indicate that microbial biomass in the host−guest soils increased with the addition of guest soil S2. Interestingly, the observed MBC values of the host−guest soils were higher than the corresponding proportional MBC values (MBC prop) calculated using Equation 3, under the assumption that host soil S1 and guest soil S2 did not affect each other’s microbial communities (Supplementary Figure S2). In Equation 3, f represents the weight fraction of guest soil S2, while MBC S1 and MBC S2 represent the MBC values of host soil S1 and guest soil S2, respectively.

The activities of alkaline phosphatase, invertase, and catalase are shown in Figure 1. Catalase activity (μg H 2 O 2 g −1 h −1) was lowest in host soil S1 (3,403 ± 72) and highest in guest soil S2 (3,975 ± 218). There was no significant difference in catalase activity between the host−guest soils and either native soil. Alkaline phosphatase activity (μg phenol g −1 d −1) in host soil S1 was 388 ± 52, which was approximately half that observed in guest soil S2. Alkaline phosphatase activity in the host−guest soils increased with an increasing proportion of guest soil S2 and reached a plateau at a host ratio of 2:1 (Figure 1b). Invertase activity (mg glucose g −1 d −1) in host soil S1 was 6.1 ± 0.3 (Figure 1c), which was significantly lower (p < 0.05) than that in guest soil S2 (8.9 ± 1.0). Although invertase activity in the host−guest soils was higher than that in host soil S1, the difference was significant only at a host ratio of 10:1.

Bacterial diversity in native and host-guest soil

Sequencing yielded an average of 57,127 high-quality sequences per sample (n = 18; range: 47,178–72,870) across the native and host−guest soils. These sequences were then clustered into operational taxonomic units (OTUs) at 97% sequence similarity, resulting in 2,689 OTUs in host soil S1; 3,500, 3,635, 3,676, and 3,676 OTUs in the host−guest soils at ratios of 10:1, 4:1, 2:1, and 1:1, respectively; and 3,190 OTUs in guest soil S2. As shown in Figure 2, Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Firmicutes, Bacteroidetes, Gemmatimonadetes, and Nitrospirae were the dominant phyla in both the native and host−guest soils, although their relative abundances differed among the soils. In host soil S1, the most abundant phyla were Actinobacteria (24.1%), Proteobacteria (23.7%), Chloroflexi (18.8%), and Acidobacteria (14.7%), whereas in guest soil S2, they were Proteobacteria (32.1%), Acidobacteria (19.3%), Actinobacteria (16.9%), and Chloroflexi (10.0%). The relative abundances of Actinobacteria and Gemmatimonadetes differed significantly between host soil S1 and guest soil S2 (p < 0.001), as did those of Chloroflexi, Bacteroidetes, and Nitrospirae (0.001 < p < 0.01) and Proteobacteria (0.01 < p < 0.05; Supplementary Figure S3). The differences in phylum-level relative abundance between the two native soils differed from those reported previously (Huang et al., 2018), possibly because the soils were sampled at different times. Principal coordinate analysis (PCoA) based on Bray−Curtis and UniFrac distance matrices derived from the OTU profiles was performed to assess beta-diversity patterns among the native and host−guest soils (Figures 2b,c). The microbial communities in the host−guest soils were distinct from those in either host soil S1 or guest soil S2. The proximity of the microbial communities in the host−guest soils to those in the two native soils depended strongly on the host ratio. At host ratios greater than 2:1, the microbial communities in the host−guest soils were more similar to those in host soil S1, whereas at ratios less than 2:1, they were more similar to those in guest soil S2.

The bacterial phyla displayed varying responses to changes in the host soil ratio (Figure 3). Specifically, the relative abundances of Acidobacteria, Bacteroidetes, and Nitrospirae increased linearly, whereas those of Actinobacteria and Gemmatimonadetes decreased linearly as the proportion of guest soil S2 increased. This trend may be explained by the lower relative abundances of Actinobacteria and Gemmatimonadetes in guest soil S2 than in host soil S1. The relative abundance of Proteobacteria initially increased with the proportion of guest soil S2 before reaching a plateau. In contrast, the relative abundance of Chloroflexi initially decreased and then stabilized at approximately 10%. Planctomycetes and Verrucomicrobia exhibited similar trends in relative abundance, decreasing initially and then increasing as the proportion of guest soil S2 increased.

Transformation of rac-metalaxyl in native and host-guest soils

The transformation of rac-metalaxyl in host soil S1 was significantly slower than that in guest soil S2 (Supplementary Figure S4), consistent with the findings of a previous study (Huang et al., 2018). Preliminary results showed little variation in the transformation of rac-metalaxyl in guest soil S2 after preincubation periods of 7, 14, and 21 days (Supplementary Figure S4). This finding suggests that the abundance of soil microorganisms, particularly rac-metalaxyl-degrading bacteria, stabilized after 7 days of preincubation. However, in the 1:1 host−guest soil, the rac-metalaxyl transformation rate increased with increasing preincubation time. The k obs values were 0.074 ± 0.002, 0.083 ± 0.005, and 0.096 ± 0.002 days −1 for R-metalaxyl and 0.013 ± 0.002, 0.013 ± 0.002, and 0.019 ± 0.002 d −1 for S-metalaxyl after 7, 14, and 21 days of preincubation, respectively (Figure 4a; Supplementary Figure S5a). Additionally, the transformation of both R-metalaxyl and S-metalaxyl in the 1:1 host−guest reference soil was slower than that in the corresponding host−guest soil (Figure 4b; Supplementary Figure S5b).

After 14 days of preincubation, the k obs values for R-metalaxyl transformation in the host−guest soils were 0.015 ± 0.002, 0.051 ± 0.005, 0.060 ± 0.005, and 0.083 ± 0.002 days −1 at host ratios of 10:1, 4:1, 2:1, and 1:1, respectively (Figure 5a). The transformation of S-metalaxyl was slower than that of R-metalaxyl in all host−guest soils (Supplementary Figure S6). This pattern was consistent with that observed in guest soil S2 but contrasted with that observed in host soil S1. The rate of change in EF also increased as the host ratio decreased from 10:1 to 1:1 (Figure 5b). Notably, in the 10:1 host−guest soil, the transformation rates of R-metalaxyl and S-metalaxyl were comparable, and EF increased to only 0.54 after 24 days of incubation. This suggests that microorganisms responsible for degrading R-metalaxyl and S-metalaxyl contributed similarly to rac-metalaxyl transformation.

Change of microbes in soils inoculated with strain or other soils

It has been reported that following inoculation, bacterial colony-forming unit (CFU) counts may decrease significantly because of rapid cell death or a transition to a viable but nonculturable (VBNC)-like state (Fliessbach et al., 2009; Moreno-Forero and van der Meer, 2015). The survival rate of Sphingomonas wittichii RW1, a bacterium capable of mineralizing dibenzodioxins and dibenzofurans in nonsterile sand, was approximately 70% when cells were inoculated during the exponential phase but only 30%–40% when they were inoculated during the stationary phase (Moreno-Forero and van der Meer, 2015). Fida et al. (2017) reported that approximately 99% of inoculated Novosphingobium sp. LH128 cells entered a VBNC-like state after 4 h of incubation; however, the culturable population subsequently increased to approximately 37% of the predicted initial cell density after 10 days of incubation. Notably, the VBNC-like cells retained their ability to degrade phenanthrene. Conversely, increases in the populations of inoculated bacteria have also been observed, particularly when the target pollutant is present (Dai et al., 2015; Li et al., 2017; Wang et al., 2010).

Three metalaxyl-degrading bacteria, including Enterobacter cloacae strain colR/S, a bacterial symbiont of Bactrocera correcta strain RL73, and bacterium CSR-60, were isolated from guest soil S2 (Liang et al., 2016). However, attempts to establish these metalaxyl-degrading bacteria in host soil S1 were unsuccessful, consistent with previous reports that an inoculated single strain is often outnumbered or outcompeted by indigenous microorganisms. Conversely, the observed MBC of the host-guest soil was 10%–15% larger than the sum of the proportional MBC from the two native soils (Supplementary Figure S2), indicating that interactions between the microbial communities of the two native soils synergistically promoted microbial growth.

The numbers of OTUs were significantly higher in the host−guest soils than in either host soil S1 or guest soil S2, indicating a higher bacterial richness in these mixed soils. This was further supported by the increased transformation rate observed with the inoculated guest soil S2 (see detailed discussion in Section 4.2). These results are consistent with previous findings illustrates that adapted soil microbial communities and their associated soil environment may contribute jointly to pesticide biodegradation (Gentry et al., 2004; Li et al., 2017; Mrozik and Piotrowska-Seget, 2010; Sethi et al., 2025; Wang et al., 2010; Wang et al., 2013; Wang et al., 2008).

Previous studies have documented varying responses of indigenous microbial communities to the introduction of specific bacterial strains or consortia. In some cases, the composition of the indigenous microbial community was not significantly affected by the introduction of atrazine-degrading microbial communities (Goux et al., 2003). Similarly, bioaugmentation with the 2,4-D degrading bacterium Novosphingobium strain DY4 (Dai et al., 2015) or the flurochloridone degrading bacterium Streptomyces sp. F-G-2 (Zhao et al., 2025) barely influenced soil bacterial community structure. However, bioaugmentation with Arthrobacter sp. Strain SD1, a simazine-degrading bacterium, induced shifts in the community structures of both ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in nonagricultural soil, with a more pronounced effect on the AOA community (Wan et al., 2014). Shifts in microbial community structure were also observed in soils inoculated with Pseudomonas sp. Strain WBC-3 or Pseudomonas sp. AKS2 (Tribedi and Sil, 2013; Wang et al., 2014).

In this study, the bacterial community in the host-guest soils was expected to change as the ratio of host soil S1 to guest soil S2, varied because the two native soils had distinctly different bacterial community structures (Supplementary Figure S3). Community dissimilarity, measured using Bray−Curtis and UniFrac distances, increased monotonically as the proportion of guest soil S2 increased (Supplementary Figure S7). Furthermore, even after a 120-day preincubation, the bacterial community in the 4:1 host-guest soil remained distinct from those in both native soils (Figure 6b), and the degree of dissimilarity was comparable to that observed after 14 days of preincubation (Figure 2b). Moreover, the bacterial community structure differed significantly between the 4:1 host-guest soil and its corresponding host−guest reference soil. These findings suggest that a distinct and stable bacterial community became established in the mixed-soil habitat and did not converge toward the community of either host soil S1 or guest soil S2.

Soil microbes are sensitive to numerous environmental factors, including climate, landscape topography, and terrestrial plants (Coleine et al., 2024; Frey et al., 2013; Taş et al., 2018; Waldrop and Firestone, 2006), as well as intrinsic soil properties such as moisture content, organic matter content, and pH (Delgado-Baquerizo et al., 2018; Karimi et al., 2018; Philippot et al., 2024; Rousk et al., 2010; Siles and Margesin, 2016; Tripathi et al., 2018). Among these factors, soil pH is considered a particularly important driver of microbial community structure at a global scale (Delgado-Baquerizo et al., 2018). Host soil S1 and guest soil S2 differ significantly in bacterial diversity, organic matter content, and pH (Huang et al., 2018); therefore, mixing these soils alters both the biotic and abiotic conditions of the resulting host−guest soils. For example, the pH of the 10:1 host-guest soil was 7.4, which is higher than that of host soil S1 (6.0) but lower than that of guest soil S2 (8.6). When the proportion of guest soil S2 exceeded 25%, the pH of the host-guest soil increased to above 8.0. Because of the contrasting properties of the two native soils, nutrient conditions in the host−guest soils differed from those in either native soil. Therefore, the edaphic environment of the host−guest soils was distinct from that of both native soils. Different bacterial groups responded differently to these changes in the soil environment (Figure 3), resulting in shifts of varying magnitudes in bacterial community structure. Overall, the response of MBC and bacterial community structure to the host:guest soil ratio demonstrate that the microbial communities in the host−guest soils were not merely physical mixtures of those in the two native soils.

Correlation between enantioselective degradation rac-metalaxyl and bacterial diversity

Over the same incubation period, rac-metalaxyl transformation in host soil S1 was negligible relative to that in guest soil S2. Therefore, it is reasonable to infer that R-metalaxyl transformation in the host−guest soils was primarily attributable to the activity of rac-metalaxyl-degrading bacteria introduced with guest soil S2. Accordingly, R-metalaxyl transformation, as reflected by the rate of change in EF, was expected to increase with an increasing proportion of guest soil S2. The transformation of rac-metalaxyl at different initial concentrations was well described by the Michaelis-Menten kinetic model (Supplementary Figure S8). The maximum transformation rate velocity (ν max) and Michaelis constant (K M) were 22 mg/(kg•d) and 1.8 mg/kg, respectively. Assuming that the rac-metalaxyl-degrading bacteria introduced with guest soil S2 did not proliferate in the host−guest soils, Vmax would be proportional to the proportion of guest soil S2, resulting in a linear relationship between the initial transformation rate (r 0) and the proportion of guest soil S2. However, the observed r 0 increased logarithmically as the proportion of added guest soil S2 increased (Figure 5c), suggesting that the rac-metalaxyl-degrading bacteria proliferated after their introduction into the host−guest soils. This result was consistent with the response of MBC to changes in the host soil ratio.

The survival and proliferation of rac-metalaxyl-degrading bacteria were further supported by the transformation of rac-metalaxyl in the host−guest soil after 120 days of preincubation (Figure 6c). Rac-metalaxyl transformation remained negligible in host soil S1 after 25 days of incubation. The r 0 value (determined after the lag phase) for R-metalaxyl decreased to 0.062 mg/(kg•d) in guest soil S2, possibly because bacterial abundance declined during the prolonged preincubation period without nutrient input. Conversely, the r 0 value for R-metalaxyl in the 4:1 host−guest soil decreased only slightly, from 0.054 to 0.044 mg/(kg•d), when the preincubation period was extended from 14 to 120 days.

The correlation coefficients among R-metalaxyl transformation, soil pH, MBC, and microbial community dissimilarity quantified using Bray−Curtis distance are listed in Supplementary Table S2. The results showed that r 0 was positively correlated with soil pH (p < 0.05), MBC (p < 0.001), and Bray-Curtis distance (p < 0.001). Further analysis showed that r 0 was significantly correlated with the relative abundances of Chloroflexi, Gemmatimonadetes, and Acidobacteria (p < 0.05), as well as those of Actinobacteria, Bacteroidetes and Nitrospirae (0.001 < p < 0.01).

The number of OTUs in the host−guest soils showed no clear relationship with the host ratio, whereas EF increased with an increasing proportion of guest soil S2. This finding suggests that bacterial richness was not a key factor governing the enantioselective transformation of rac-metalaxyl, particularly because bacterial richness was consistently high across all soil samples. After 120 days of preincubation, the numbers of OTUs were 1,466, 1,711, and 2,045 in host soil S1, guest soil S2, and the 4:1 host−guest soil, respectively. However, both r 0 and the rate of change in EF decreased in the following order: guest soil S2 > the 4:1 host−guest soil > host soil S1. This lack of correspondence indicates that the enantioselective transformation of rac-metalaxyl was not directly associated with bacterial richness. By contrast, bacterial community structure differed significantly between the host−guest soils and their corresponding reference soils, and marked differences in EF were also observed between these soils. Together, these findings suggest that bacterial community structure, rather than bacterial richness, was closely associated with the enantioselectivity of rac-metalaxyl transformation.

From a microbiome-engineering perspective, bioaugmentation should be evaluated not only in terms of pollutant-transformation efficiency but also in terms of the functional performance, persistence, and ecological safety of the introduced community (Cycoń, 2026). In the present study, bacterial community structure was associated with rac-metalaxyl transformation, but these correlations neither identify the active degraders nor demonstrate the functional pathways involved. Future studies integrating metagenomics, metatranscriptomics, and metabolomics could link community-level changes with catabolic genes and metabolic pathways, thereby providing a more mechanistic assessment of guest-soil bioaugmentation (Alidoosti et al., 2024). Moreover, because the present results were obtained under controlled laboratory conditions, their direct applicability to field environments remains uncertain. Rainfall, temperature fluctuations, plant-root activity, microbial competition, and nutrient dynamics may affect the establishment, persistence, and activity of guest-soil-associated microbial populations, thereby altering rac-metalaxyl transformation and enantioselectivity. Consequently, the effective guest-soil proportions identified in this study should not be considered directly transferable to field application. Field experiments across different soil types, cropping systems, and environmental conditions are required to evaluate microbial persistence, functional performance, transformation efficacy, and potential ecological effects before practical implementation.

This study investigated microbial biomass carbon (MBC), soil enzyme activities, bacterial community composition based on 16S rRNA gene amplicon sequencing, and the enantioselective transformation of rac-metalaxyl in host soil, guest soil, host–guest soil mixtures, and a reference soil. MBC and enzyme activities exhibited nonlinear responses to the host-soil ratio. Although the dominant bacterial phyla were generally shared among the soils, their relative abundances differed significantly among the soil mixtures. Following the 14-day pre-incubation, taxa associated with both the host and guest soils were detected in the host–guest mixtures. Bacterial richness was higher in some mixtures than in either the host or guest soil, and individual bacterial taxa responded differently to the proportion of guest soil.

Changes in bacterial abundance, diversity, and community structure were associated with differences in rac-metalaxyl transformation and enantioselectivity. However, these relationships were correlative and do not establish that the bacterial community changes directly caused the observed transformation patterns. Metabolites, microbial interactions, nutrient exchange, and functional genes were not directly examined, and 16S rRNA gene sequencing cannot identify the active degraders or the functional pathways involved. Therefore, the proposition that guest soil provides a suitable microenvironment for microbial establishment and rac-metalaxyl transformation remains a hypothesis requiring further investigation.