Unraveling Plasmid Contributions to Phosphorus Acquisition in Soil Microbiomes

Unraveling Plasmid Contributions to Phosphorus Acquisition in Soil Microbiomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unraveling Plasmid Contributions to Phosphorus Acquisition in Soil Microbiomes Pablo Bruna, Patricio Javier Barra, Matías García, Ivan Liachko, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7644682/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Apr, 2026 Read the published version in Environmental Microbiome → Version 1 posted 12 You are reading this latest preprint version Abstract Background Phosphorus (P) is a fundamental macronutrient for plant and microbial growth, but its availability in soils is often constrained by strong interactions with minerals and organic matter. While the role of bacteriophages in P cycling has gained attention, plasmids remain comparatively underexplored despite their central role in horizontal gene transfer. This study aimed to investigate the occurrence, diversity, and ecological relevance of plasmid-borne genes involved in P acquisition across soils with contrasting P availability. Results Using curated plasmid databases and soil metagenomes from diverse biomes, we identified a broad repertoire of plasmid-encoded P-acquisition genes. These genes encompassed regulatory pathways, transport systems, organic P mineralization, and inorganic P solubilization. Regulatory and transporter genes were the most abundant categories, with phoB , phoP , and ugpC among the most frequently detected. Significant differences in gene abundance were observed between high- and low-P environments. High-P tundra environments favored plasmids with more regulatory and transport genes compared to low-P tundra, while P-deficient soils generally showed higher abundances of P transport and organic P mineralization genes. Taxonomic assignment revealed that Pseudomonadota were the predominant plasmid hosts, followed by Bacillota and Actinobacteriota , suggesting broad host diversity. Conclusions This study underscores the ecological significance of plasmid-borne P-acquisition genes in P cycling and their potential in microbial adaptation to P-deficient soils. The dominance of Pseudomonadota and Bacillota as plasmid hosts highlights their central contribution to these processes. Overall, our findings expand the current understanding of plasmid involvement in soil fertility and point to their potential application in bioaugmentation strategies to enhance P use efficiency and promote sustainable agriculture. Phosphorus acquisition genes Mobile genetic elements Metagenome Auxiliary metabolic genes Mobilome Phosphorus cycling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights Plasmids harbor key genes involved in phosphorus acquisition in soil environments Regulatory and transporter genes represent the most abundant functional categories Pseudomonadota and Bacillota are the dominant plasmid hosts for P-acquisition 1. Background Phosphorus (P) is an essential macronutrient necessary for a variety of biological functions in microorganisms [ 1 ]. In natural environments, P availability often limits the growth of microbes and plants. This is mainly because of its strong interactions with soil minerals and organic matter, which result in low solubility and bioavailability [ 2 ]. P limitation has become more pressing with climate change, because extreme weather events are projected to exacerbate P losses from agricultural soils through intensified erosion and runoff, further undermining soil fertility and contributing to environmental degradation [ 3 ]. In agriculture, P deficiency is addressed by applying inorganic phosphate fertilizers sourced from phosphate rock, which is composed primarily of apatite minerals such as fluorapatite (Ca 10 (PO 4 ) 6 F 2 ) and its variants. The global supply of high-quality phosphate rock is limited, with estimates suggesting that it could be exhausted within decades [ 4 , 5 ]. Moreover, P fertilization is inefficient, as much of the applied P rapidly becomes immobilized through precipitation or adsorption with iron and aluminum oxides in acidic soils or with calcium in alkaline soils, as well as through incorporation into organic matter [ 6 ]. These processes lead to the accumulation of recalcitrant, poorly bioavailable P forms, referred as legacy P in soils [ 7 , 8 ]. These limitations have driven growing interest in sustainable alternatives to enhance P acquisition in soils, such as the use of phosphate-solubilizing or mineralizing bacteria [ 9 ]. These bacteria enhance P availability in soils by solubilizing inorganic phosphate, primarily through the secretion of organic acids, which lower the pH and make inorganic phosphate soluble [ 10 ]. They also mineralize organic P compounds by secreting a variety of extracellular enzymes, including phosphatases, phytases, phosphonatases, and C–P lyases [ 11 ]. These bacteria can also efficiently manage P uptake pathways, as evidenced by the upregulation of phosphate-binding and transport proteins under P-deficient conditions [ 12 ], thereby enhancing plant P uptake and improving soil fertility [ 13 ]. While these microbial processes are well recognized, a deeper understanding of their genetic basis is critical to fully harness their potential. In particular, the mobility of P-acquisition genes within and between microbial populations is increasingly seen as a central factor shaping bacterial adaptation to environmental conditions, like P-deficient soils. The mobilome encompasses all mobile genetic elements (MGEs) within a given microbiome. These segments of genetic material can move within a genome or between genomes of different organisms [ 14 ]. Among MGEs, bacteriophages and plasmids play a key role in horizontal gene transfer (HGT) due to their mobility. In particular, the presence and dissemination of auxiliary metabolic genes (AMGs) in bacteriophages have attracted growing interest for their potential role in microbial P cycling [ 15 , 16 ]. Meanwhile, plasmids are critical for bacterial adaptation and survival in challenging environments, as they facilitate the HGT involved in nutrient acquisition [ 17 ]. Plasmids can be classified into three categories according to their mobility potential: (i) non-mobilizable plasmids, which lack recognizable transfer genes but may still move between cells through mechanisms other than direct conjugation; (ii) mobilizable plasmids, which encode a relaxase gene but depend on the mating pair formation (MPF) system of a co-resident conjugative element; and (iii) conjugative plasmids, which possess both a relaxase and a complete MPF/type IV secretion system (T4SS), enabling autonomous transfer [ 18 ]. In metagenomic datasets, however, plasmid contigs are frequently fragmented, complicating the detection of complete conjugative systems and favoring the identification of mobilizable elements. Despite their recognized ecological importance, a comprehensive understanding of P-acquisition genes in plasmids remains limited, particularly regarding their distribution, functionality, and mobility across diverse soil environments. Advances in high-throughput sequencing and bioinformatic analysis have facilitated the identification of P-related genes in microbial genomes and metagenomes [ 19 – 21 ]. However, the genetic strategies and ecological role of plasmid-mediated P acquisition remain underexplored, mainly due to the difficulties in distinguishing plasmids from chromosomal DNA in metagenomic datasets [ 22 ]. The increasing availability of curated plasmid databases, such as PLSDB [ 23 ], and specialized metabolic gene repositories, such as the P cycling database (PCycDB) [ 24 ], provides new opportunities to investigate the role of plasmids in microbial P metabolism. By integrating these resources with metagenomic approaches, it is possible to identify and characterize P-acquisition genes in plasmids retrieved from public databases and environmental metagenomes. This study aims to elucidate the distribution and functional classification of P-acquisition genes within plasmids in soil environments. Specifically, we sought to (i) identify P-acquisition genes in publicly available plasmid sequences retrieved from PLSDB, (ii) analyze the prevalence, diversity, and environmental distribution of P-acquisition genes in plasmids identified from publicly available metagenomes representing diverse soil types, and (iii) evaluate the mobility potential and taxonomic distribution of plasmid-borne P-acquisition genes across different environmental contexts. To achieve these objectives, we employed an in silico approach that integrated plasmid sequence retrieval, dereplication, functional gene annotation, and classification of plasmid mobility and host prediction. By addressing these knowledge gaps, this study provides a clearer understanding of how plasmids contribute to P cycling in microbiomes, emphasizing their involvement in P acquisition. Our findings provide a broader understanding of the diversity and ecological significance of plasmid-borne P-acquisition genes. 2. Material and methods 2.1. Identification of phosphorus acquisition genes in plasmids using public databases To determine the presence of bacterial genes involved in the P cycle within plasmids, an in silico review and search was conducted. For this purpose, the plasmid database PLSDB (v.2023_11_03_v2) [ 23 ] was used, as it provides curated plasmid sequences along with their associated metadata. For this analysis, all sequences indicating "soil" as the source of isolation were retrieved. For these sequences the protein-coding genes were predicted using prodigal v2.6.3 [ 25 ] and then aligned against the P cycling database (PCycDB v1.1) [ 24 ], a specialized database covering P metabolic processes that includes 139 gene families across 10 metabolic categories. The alignment was performed using DIAMOND BLASTP v0.9.14 [ 26 ] with an e-value threshold of 0.0001. To ensure accurate identification and minimize false positives, additional filters were applied: a minimum identity threshold of 70% and a minimum hit length of 25 amino acids, as recommended by the PCycDB guidelines, based on benchmarking results showing that this cutoff maintains accuracy in gene detection. Subsequently, plasmids containing genes related to the P cycle were grouped into four functional categories based on primary P acquisition processes in microorganisms: i) inorganic P solubilization ( ppk, ppa, gcd ), ii) organic P mineralization ( phoA, phoD, phoX, phoN, aphA, phoC, olpA, opd, phy, appA, pafA, ugpQ, glpQ, phnGHIJKLMNOPWXYZ ), iii) P transport ( pgtP, pstSCAB, pit, htxB, ptxABC, phnD_phosphite, phnDEC, ugpBAEC, phnSVUT, glpT, aepXVWPS ), and iv) P regulation ( phoU, phoR, phoB, phoP, SenX3, RegX3, pgtC, pgtB, pgtA, phnF ). Hereafter, these categories are referred to as the P-acquisition functional categories. To prevent overrepresentation of genes in the analysis, sequences were dereplicated using MMseqs2 v15.6f452 [ 27 ] with a sequence identity threshold > 0.6 and coverage > 0.5, in bidirectional mode (—cov-mode 0). This parameter minimized redundancy to prevent clustering of plasmids with highly similar backbone genes but distinct accessory regions. To further assess genomic relatedness among dereplicated sequences, pairwise average nucleotide identity was calculated using ANIclustermap v2.0.1 ( https://github.com/moshi4/ANIclustermap ) , which performs hierarchical clustering based on sequence similarity. The resulting dendrogram was visualized using iTOL v7 [ 28 ]. Finally, plasmids were classified based on their mobilization capacity using MOBFinder v1.0 [ 29 ]. This tool employs vector-based language models to characterize plasmids according to their transferability into mobility groups, based on ten validated MOB relaxase protein families (MOBB, MOBC, MOBF, MOBH, MOBL, MOBM, MOBP, MOBQ, MOBT, MOBV), which are categorized as mobilizable, while NON-MOB plasmids are classified as non-mobilizable. 2.2. Retrieval of metagenomic reads To retrieve metagenomic reads from soil for plasmid identification and the analysis of P-acquisition genes, a bibliographic search was conducted using the keywords "soil," "metagenome," and "illumina." This search was filtered based on the following criteria: (i) studies that employed whole-metagenome sequencing, (ii) studies that described physicochemical parameters of the soil, particularly P levels, and (iii) datasets with publicly available reads. As a result, 96 soil metagenomic datasets were retrieved from five publications [ 16 , 30 – 33 ] representing diverse biomes, including desert (n = 12), farmland (n = 15), grassland (n = 27), mine (n = 17), tundra (n = 16), and volcanic (n = 9) (Table S1 ). The classification of P availability across environments was based on two criteria: (i) if the study explicitly described the soil as P-deficient or P-enriched; otherwise, (ii) the classification was inferred from the reported concentration of bioavailable P, as measured using either the Olsen or Bray extraction methods. Soils with P concentrations ≥ 30 mg/kg were classified as having high P availability, whereas those with lower concentrations were categorized as having low P availability (Table S1 ). Although the specific P requirements of individual plant species and different types of soils may vary considerably, the 30 mg/kg threshold was adopted as a standardized operational criterion to distinguish between P-enriched and potentially P-deficient soils. This value is consistent with thresholds reported in agronomic and ecological literature, where Olsen P concentrations around 30 mg/kg are often used to distinguish between P availability [ 34 ]. 2.3. Metagenomic assembly and construction of the plasmid catalog The metagenomic sequencing reads were retrieved from the NCBI Sequence Read Archive and processed as paired-end reads using fasterq-dump from the sratoolkit (v3.1.1) with the --split-files parameter. Adapter sequences were removed and low-quality reads (Q-value < 20) were trimmed with Trimmomatic (v0.39) [ 35 ] using the SLIDINGWINDOW:4:20 parameter, which applies a 4-base sliding window and cuts the read when the average quality within the window drops below 20. Reads shorter than 50 base pairs after trimming were discarded using the MINLEN:50 parameter. The filtered reads were assembled using MEGAHIT (v1.2.9) [ 36 ] with the meta-large parameter, and contigs longer than ≥ 1000 base pairs were retained for downstream analysis. Plasmids were identified using geNomad (v1.8.0) [ 37 ] with default parameters and PLASMe (v1.1) [ 38 ] in balanced mode. The number of plasmids identified by each tool for each sample is shown in Table S1 . Following identification, the methodology described in section 2.1 was applied, including alignment against PCycDB, functional categorization of P cycle-related genes, dereplication of plasmids containing P-acquisition genes, and mobility classification, resulting in a non-redundant dataset used for downstream analyses. To estimate plasmid abundance, high-quality reads were mapped to the non-redundant dataset using CoverM v0.7.0 [ 39 ] under the contig model with the following parameters: -p minimap2-sr --min-read-percent-identity 0.95 --min-read-aligned-percent 0.75 -m tpm. An abundance table was generated by calculating transcripts per million (TPM), as described by Li et al. [ 40 ], facilitating robust comparisons of varying abundances across samples with different sequencing depths and technologies. Additionally, functional annotation of plasmid genes was performed using Bakta v1.9.3 [ 41 ] with the full database configuration, and the plasmid host range was estimated using HRPredict [ 42 ], which applies a protein language model and a one-class support vector machine algorithm to predict potential bacterial hosts based on plasmid-encoded proteins. 2.4. Statistical analysis Statistical analyses were conducted in R v4.3.1 using dplyr [ 43 ], ggplot2 [ 44 ], and stats packages. The normality of plasmid length and GC content was assessed using the Shapiro-Wilk test across P availability categories ("high" and "low") and mobility groups ("mobilizable" and "non-mobilizable"). For variables that did not meet the normality assumption (p < 0.05), differences between groups were evaluated using the non-parametric Mann-Whitney U tests (Wilcoxon rank-sum test). Pearson and Spearman correlation analyses were applied to examine the relationship between the number of P-acquisition genes and plasmid length. To visualize the functional gene distributions, a log2 transformation was applied to the input count and abundance matrices to reduce skewness and enhance interpretability. Heatmaps were generated using the ComplexHeatmap package [ 45 ]. To assess the differences in functional gene abundance between P conditions, TPM values were aggregated by P-acquisition functional categories, and comparisons between high- and low-P environments were performed using the Mann–Whitney U test. Additionally, cumulative TPM values across all P-acquisition functional categories per sample were calculated and compared between P conditions to evaluate the overall abundance trends. 3. Results 3.1. Phosphorus acquisition genes in plasmids retrieved from the PLSDB database To evaluate the presence of P-acquisition genes in soil-derived plasmids, a comprehensive analysis of the PLSDB database was conducted. This database comprises a total of 59,895 plasmids, representing a curated collection of publicly available plasmid sequences from diverse environments. After filtering for plasmids isolated from soil based on available metadata, 2,108 plasmids were identified. Notably, 473 (22.4%) of these plasmids carried P-acquisition genes, demonstrating that a substantial fraction of soil plasmids contributes to microbial P cycling. Following dereplication, 449 unique plasmids containing at least one P-acquisition gene were retained, representing 21.30% of the soil-derived plasmids in the database (Fig. S1 and S2; Table S2 ). In terms of genomic characteristics, these plasmids had a median length of 347,238 bp, with a vast range from 5,846 to 3,525,317 bp. The GC content showed a median of 59.02%, with a range from 24.19% to 72.65%. Additionally, a statistically significant difference was observed between the GC contents of the plasmids based on their mobility (Fig. 1 ). Notably, within the mobilizable plasmid group, the GC content varied markedly among the host phyla. Plasmids from Pseudomonadota exhibited higher GC content than those from Bacillota . In contrast, among non-mobilizable plasmids, Actinomycetota and Deinococcota displayed consistently high GC contents (Fig. 1 b). These differences suggest that the host genomic composition plays a role in shaping the plasmid GC content (Fig. S3 and S4). In comparison, no significant differences were found in plasmid length when mobility was considered (Fig. 1 a). To further explore the genomic features of plasmids encoding P-acquisition genes, the relationship between plasmid length and the number of encoded P-related genes was assessed. Both Pearson (r = 0.77, p < 0.001) and Spearman (r = 0.63, p < 0.001) correlation analyses revealed strong positive associations, indicating that longer plasmids tend to harbor more P-acquisition genes (Fig. S5). Altogether, these results reveal that the genomic architecture of plasmids harboring P-acquisition genes is shaped by both plasmid mobility and host taxa, with larger plasmids tending to carry more functional genes, reflecting potential adaptations to enhance P-acquisition in diverse environmental contexts. A total of 1,774 gene sequences related to the P-acquisition functional categories were identified across the analyzed plasmids. Among these, regulatory genes such as phoB , phoP , and RegX3 , as well as transporter genes like ugpC , phnE , and phnC , were the most prevalent, representing 42.73% and 40.02% of the P-acquisition genes detected in the analyzed plasmids, respectively. Notably, 1,314 of these sequences (74.07%) were found in plasmids classified as mobilizable, suggesting that these genes may be subject to horizontal transfer through plasmid mobilization (Fig. S6). The bacterial hosts of plasmids containing P-acquisition genes were analyzed across different taxonomic ranks: phylum, family, and genus. At the phylum level, the majority of soil-derived plasmids belonged to Pseudomonadota (n = 237), Bacillota (n = 144), and Actinomycetota (n = 49), with lower representation from Deinococcota (n = 10), Bacteroidota (n = 5), and Cyanobacteriota (n = 4). At the family level, Bacillaceae , Rhizobiaceae , Burkholderiaceae were the most prevalent. Genus rank analysis revealed Bacillus , Rhodococcus and Rhizobium as the dominant groups. Notably, a substantial fraction of plasmids were grouped under the ‘Others’ category, underscoring the broad taxonomic diversity of bacterial hosts harboring plasmids with P-acquisition genes (Fig. 2 a). These results highlight a strong representation of Pseudomonadota , suggesting contributions from a broad diversity of taxa, and indicate that both this phylum and Bacillota , predominantly represented by Bacillus , emerge as key contributors to P solubilization and mineralization. The heatmap further illustrates the count and distribution of P-acquisition genes across bacterial host families, showing that regulatory ( phoB , phoP and RegX3 ) and transporter genes ( ugpC , phnE , phnC ) were the most prevalent. Inorganic P solubilization and organic P mineralization genes were widely distributed, particularly among Comamonadaceae , Moraxellaceae , and Micrococcaceae , highlighting their potential role in P mobilization. The analysis reveals distinct patterns of functional specialization across bacterial lineages, with host families clustering according to similarities in the P-acquisition gene profiles of their associated plasmids, providing insights into the ecological roles of these mobile elements in P cycling. (Fig. 2 b). Despite the low representation of soil-isolated plasmids in the PLSDB database, the presence of P-acquisition genes was evident. This prompted further investigation into whether this gene abundance pattern is also observed in plasmids identified from soil metagenomes and how bioavailable P concentrations in soil influence these genetic elements. 3.2. Phosphorus acquisition genes in plasmids identified from soil metagenomes To further investigate the presence and distribution of P-acquisition genes in plasmids beyond those cataloged in PLSDB, we performed de novo assembly of metagenomic datasets derived from 96 soil samples, retrieved from public repositories and spanning six distinct biomes, in order to identify plasmids directly from soil microbial communities. A total of 248,750 contigs were identified as plasmid sequences using geNomad and PLASMe. Among these, 9,191 plasmids contained at least one gene related to the P cycle, encompassing all metabolic categories represented in the PCycDB database, such as two-component systems, oxidative phosphorylation, phosphonate metabolism, and other P cycling processes. From this broader set, 5,602 plasmids specifically harbored genes associated with the P-acquisition functional categories (Table S1 ). To minimize redundancy and overrepresentation, dereplication was performed, resulting in 1,966 representative plasmids retained for subsequent analyses (Table S3; Fig. S7). These plasmid sequences have a median length of 3,304 bp, with a minimum observed length of 1,001 bp and a maximum of 312,583 bp. Significant statistical differences were found in desert and grassland biomes when plasmids were grouped by mobility, as larger plasmids were identified in these environments (Fig. S8). GC content was significantly higher in non-mobilizable plasmids compared to mobilizable ones (Fig. 3 ), similar to the pattern observed in plasmids retrieved from PLSDB (Fig. 1 b). This finding confirms the correlation between genetic mobility and GC content in an independent dataset. Furthermore, the relationship between plasmid length and the number of encoded P-acquisition genes was evaluated. Results showed a weak positive correlation (Pearson: r = 0.19, p < 0.001; Spearman: r = 0.08, p < 0.001), suggesting that longer plasmids tend to harbor more P-acquisition genes (Fig. S9). However, the correlation was weak, as indicated by the low correlation coefficients, which highlight that plasmid length alone does not strongly determine the number of P-acquisition genes. This outcome is likely due to the fact that many of the identified sequences correspond to plasmid fragments rather than complete plasmids, which may not fully represent the genomic architecture of intact plasmids. A total of 2,503 genes were identified across the P-acquisition functional categories. Similar to the results obtained from the PLSDB plasmids, transporter and regulatory genes were the most abundant, accounting for 47.78% and 34.84% of the total, respectively. Among transporter genes, ugpC , pstB , and pstS were the most prevalent, while phoB , phoP , and RegX3 were the most frequent among the regulatory genes. Additionally, when analyzing the distribution of genes based on their mobilization capacity, 45.98% were found in plasmids classified as mobilizable (Fig. S10). To better understand the ecological relevance of these genes, we examined their distribution and abundance across contrasting soil environments. Our analysis revealed that plasmids and plasmid-derived fragments consistently encoded functional categories of P-acquisition genes in all analyzed biomes (Fig. S11). These include regulatory genes ( phoB , phoP , phoR , phoU , RegX3 , SenX3 ), transport systems ( pstSCAB , ugpBAEC , pit ), organic P mineralization genes ( phnGHIJKLMNW of the phn operon, glpQ , opd , phoD , phoX ), and inorganic P solubilization genes ( gcd , ppa , ppk ). To assess functional variation under different P availabilities, Z-score heatmap analysis (Fig. 4 ) indicated that high-P tundra environments exhibited a greater abundance of regulatory genes ( phoB , phoP , phoR , phoU , RegX3 ) than low-P tundra, and the ugpBAEC transport system was also more prevalent under high-P conditions. In mine soils, the glpT gene involved in P transport was notably enriched relative to other soil types. Despite the heterogeneity in soil physicochemical properties, these data demonstrate that plasmids consistently harbor a diverse repertoire of P-acquisition genes. In addition, when comparing the abundance of P-acquisition functional categories between high- and low-P environments (Fig. 5 ), P transport and organic P mineralization genes were significantly more abundant in P-deficient soils, whereas P regulation and inorganic P solubilization genes showed no significant variation. Furthermore, when the overall abundance of P-acquisition genes was compared between high- and low-P environments, plasmids from P-deficient soils were found to harbor a significantly higher number of these genes (Fig. S12). These results underscore the dynamic role of P availability in modulating the gene composition of plasmids related to P acquisition, with the transport and organic mineralization processes being particularly responsive to low P levels. Regarding the bacterial hosts, only those with a unique phylum-level taxonomic assignment were considered, since host prediction indicated that some plasmids could potentially be associated with up to five different bacterial phyla (Table S3). A total of 429 plasmids or plasmid fragments with a single predicted host phylum were analyzed. Consistent with the results from the PLSDB database, Pseudomonadota was the most abundant phylum, however, in this case, Actinomycetota ranked second, followed by Bacillota (Fig. S13). In terms of gene composition, phoR , pstCA , ugpC and phoD were present across all three host phyla. Additionally, Pseudomonadota and Actinomycetota hosts taxa exhibited a broad diversity of P-acquisition genes (Fig. S14). These findings provide a comprehensive overview of the diversity and hosts of P-acquisition genes in soil-associated plasmids, thereby setting the foundation for the exploration of their ecological implications. Our analysis revealed that P-acquisition genes are widely distributed across plasmids from diverse soil environments, highlighting their potential role as key vectors of microbial adaptation to P-deficient conditions. This finding underscores the importance of plasmids in shaping nutrient acquisition strategies in soil microbiomes and suggests that HGT may be a critical mechanism facilitating microbial P cycling. 4. Discussion HGT plays a key role in nutrient cycles, with growing evidence of genes involved in P, N, S, and C cycling in phages [ 15 , 16 , 46 , 47 ]. In contrast, the role of these functions in plasmids remains poorly understood. While some plasmid-associated genes linked to S [ 48 , 49 ] and N cycling [ 50 – 52 ] have been identified, their contribution to P acquisition is largely unknown. Here, we addressed this gap by analyzing P-acquisition genes in soil plasmids from PLSDB and metagenomes spanning six biomes. 4.1. Structural characteristics and mobility of soil plasmids: the role of GC content Plasmid analyses from PLSDB and soil metagenomes revealed that mobilizable plasmids, defined by validated MOB relaxase protein families, consistently exhibited lower GC content than non-mobilizable ones (Fig. 1 b and 3 ). This compositional pattern aligns with reports associating low GC content with reduced metabolic for the host and facilitate transfer across diverse bacterial lineages [ 53 , 54 ]. Conversely, non-mobilizable plasmids with higher GC content may reflect long-term coevolution and adaptation with their hosts (Fig. S4c), favoring structural stability and integration into the cellular environment [ 53 , 55 ]. Furthermore, we observed substantial variation in GC content across host phyla, particularly among mobilizable plasmids (Fig. 1 b). For instance, plasmids associated with Pseudomonadota exhibited higher GC content than those from Bacillota , while among non-mobilizable plasmids, those affiliated with Actinomycetota and Deinococcota retained consistently high GC values. These differences reflect the nucleotide composition of the host chromosome (Fig. S3). Plasmid GC content is often < 10% lower than that of their bacterial hosts due to selective pressures for genomic maintenance [ 55 , 56 ]. Because plasmids primarily carry operational genes, such as those involved in P-acquisition, they may be under selective pressure to optimize their GC composition for efficient transfer [ 57 ]. 4.2. Functional characterization of plasmid-borne P-acquisition genes P-acquisition genes were grouped into four main functional categories: regulation, transport, inorganic solubilization, and organic mineralization. These categories represent the key processes for microbial survival in P-deficient environments, facilitating P metabolism, recycling, and storage. Among the evaluated categories, transporter and regulatory genes stood out because of their abundance in the analyzed plasmids, underscoring their functional and adaptive relevance in the mobilization of P-acquisition genes. Among the transporter genes, ugpC was the most abundant, followed by the phosphate-specific transport system genes pstA , pstB , and pstS . UgpC encodes a protein that is part of the ATP-binding cassette transport system specific for sn-glycerol-3-phosphate (G3P) in bacteria and serves as an alternative P source under phosphate-limiting conditions [ 58 ]. The primary function of ugpC is to provide the energy required for G3P transport across the cell membrane via ATP hydrolysis [ 59 ]. The pstSCAB complex plays a crucial role in the active uptake of phosphate from the environment, and under conditions of Pi depletion, it propagates a signal that relieves the inhibition of phoR , allowing its autophosphorylation. Subsequently, phoR acts as a phosphodonor, transferring the phosphoryl group to the response regulator phoB , which activates the transcription of genes within the Pho regulon [ 60 ]. Notably, regulatory genes such as phoP , phoB , and phoR were among the most frequently identified genes in the plasmid-borne genetic content. While phoB is the canonical response regulator that directly activates the transcription of Pho regulon genes in organisms such as Escherichia coli , phoP has an equivalent regulatory role in Actinomycetota , particularly Streptomyces spp . In this context, the phoR / phoP two-component system functions as a phosphate-sensing mechanism, where phoR serves as a membrane-bound sensor kinase and phoP acts as a transcriptional regulator that governs gene expression in response to phosphate limitation [ 61 ]. In addition to phosphate homeostasis, this system also modulates secondary metabolism and developmental processes, underscoring its evolutionary and physiological significance [ 62 ]. These findings highlight the central role of plasmid-borne transporters and regulatory systems in enhancing microbial adaptation, and suggest that HGT via plasmids may significantly contribute to the dissemination of P-acquisition strategies across diverse soil microbiomes. Three genes related to the inorganic solubilization were identified: ppa , ppk , and gcd . Ppa encodes inorganic pyrophosphatase, an enzyme that hydrolyzes pyrophosphate to inorganic phosphate, thereby contributing to both energy regulation and P availability [ 63 ]. Ppk encodes polyphosphate kinase, which synthesizes and mobilizes polyphosphates and provides an efficient form of P storage under nutrient stress conditions [ 64 ]. Finally, gcd encodes glucose dehydrogenase, an enzyme involved in gluconic acid production that acidifies the environment and facilitates the solubilization of insoluble mineral phosphates, thereby increasing their availability for microorganisms. The gcd gene is predominant across soil samples and is considered a major determinant of bioavailable P [ 21 , 32 ]. In our results, gcd occurred on plasmids across multiple host families within the phyla Pseudomonadota and Bacillota (Fig. 2 ), consistent with prior reports [ 32 ], and compatible with horizontal dissemination may enhance the adaptive potential of microbial communities under P-limiting conditions. Finally, in the organic mineralization category, phosphatases, such as phoA , phoX , and phoD , along with phn operon genes, such as phnM and phnI , were the most abundant. These phosphatases hydrolyze organic phosphate esters, releasing inorganic phosphate. PhoA encodes an alkaline phosphatase active under basic pH conditions, while phoX differs structurally and functionally, being active in marine and alkaline environments [ 65 , 66 ]. PhoD exhibits a high affinity for organic phosphomonoesters and plays a prominent role in P mineralization in agricultural soils [ 67 ]. Collectively, these enzymes facilitate the conversion of organic P into bioavailable forms for microbial and plant uptake. Moreover, the phn operon encodes the carbon–phosphorus (C-P) lyase pathway, a multi-enzyme system responsible for cleavage of the chemically stable C–P bond present in organophosphonates [ 68 ]. The ability to catabolize phosphonates expands the ecological flexibility of microorganisms, enabling them to exploit alternative sources of P. 4.3. Ecological distribution and functional adaptation of P-acquisition genes The distribution and abundance of P-acquisition genes across various soil environments revealed that plasmids and plasmid fragments consistently encoded a broad spectrum of functional gene categories across all analyzed biomes. These included regulatory genes ( phoB , phoP , phoR , phoU , RegX3 , SenX3 ), transport systems ( pstSCAB , ugpBAEC , pit ), organic P mineralization genes ( phnGHIJKLMNW , glpQ , opd , phoD , phoX ), and inorganic P solubilization genes ( gcd , ppa , ppk ). This pattern persisted regardless of variations in P availability, climatic conditions, geographic locations, and soil types. Previous studies about soil bacteriophages also reported a wide diversity of P-acquisition genes [ 15 , 16 , 69 ]. The widespread presence of these genes in the mobilome suggests they form a prevalent functional repertoire, enabling microbes not only to maintain P homeostasis but also to swiftly adjust to nutrient fluctuations, a capacity that may confer broader ecological advantages and resilience in dynamic environments [ 70 ]. Although plasmids harbor a diverse range of P-acquisition genes, their abundances vary across environments. A closer examination of functional variation between different P availabilities (Fig. 4 ), shows that high-P tundra environments exhibited a higher abundance of regulatory genes ( phoB , phoP , phoR , phoU , RegX3 ) compared to low-P tundra, with the ugpBAEC transport system also showing increased abundance under high-P conditions. This suggests that high-P environments may favor plasmids that harbor genes capable of more efficient P uptake and regulation. Moreover, mine soils displayed a distinctive trend, with the glpT gene, part of the gpl regulon involved in the transport of organic P sources, such as glycerol, G3P, and glycerophosphodiesters [ 11 ], being notably enriched relative to other soil types. These findings suggest that local adaptations occur in response to varying P sources and availability in different soil types. Despite differences in soil physicochemical properties, we found that plasmids consistently harbor a diverse array of genes involved in P acquisition, highlighting the ecological adaptability of microbial P cycling across environments. This aligns with previous findings that plasmids not only serve as vehicles for accessory traits but also as dynamic contributors to microbial adaptation in diverse ecological contexts [ 71 ]. These findings highlight crucial implications for sustainable agriculture. In practice, harnessing plasmid-encoded P-solubilizing functions, for example through microbial inoculants or by managing indigenous P-solubilizing bacteria, can improve P use efficiency and reduce dependence on synthetic P fertilizers by unlocking native soil P pools [ 72 , 73 ]. Field studies have demonstrated that introducing P-solubilizing bacteria leads to greater P uptake and higher crop yields in P-deficient soils while allowing lower fertilizer application rates [ 74 ]. By leveraging plasmid-borne P acquisition genes in soil microbiomes, farmers can enhance crop productivity and soil fertility in a sustainable manner, improving yields on P-deficient lands and preserving nonrenewable phosphate resources for the future. Furthermore, the abundances of P transport and organic P mineralization genes were significantly more abundant in P-deficient soils than in high-P environments (Fig. 5 ). This suggests that P-deficient conditions trigger the activation and may induce mobilization of P-acquisition systems, which are critical for microbial survival under nutrient-limiting conditions [ 12 ]. In contrast, P regulation and inorganic P solubilization genes did not exhibit significant variation, suggesting that these processes may be less responsive to fluctuations in P availability at the plasmid level. Additionally, the cumulative analysis of P-acquisition gene abundance across all functional categories (Fig. S12) revealed that plasmids from P-deficient soils harbored a higher number of these genes compared to those from high-P environments. These findings emphasize the dynamic role of P availability in modulating the genetic composition of plasmids related to P acquisition, with the transport and organic mineralization processes being particularly responsive to low P levels. The taxonomic distribution of plasmids containing P-acquisition genes revealed consistent patterns in both PLSDB-derived and metagenomic analyses, with Pseudomonadota identified as the predominant phylum, suggesting a central role in the mobilization of P-related functions within soil ecosystems. Despite methodological differences, the convergence of taxonomic profiles supports the ecological relevance of this phylum and its associated lineages as key plasmid hosts. These findings are consistent with reports on P-solubilizing bacteria isolated from diverse soil environments [ 72 , 75 – 78 ]. The presence of these genes in well-characterized genera (e.g., Bacillus and Rhizobium ) and in less-studied lineages suggests that the taxonomic range of plasmid hosts remains underexplored, potentially revealing novel microbial hosts involved in P-acquisition. These findings highlight the ecological relevance of plasmids in the mobilization of P-acquisition genes, emphasizing their role in microbial resilience under high- and low-P conditions. The maintenance of biogeochemical P cycling and the functional stability of microbial communities could be supported by plasmids' capacity to mobilize P-acquisition genes. Furthermore, the identification of P-acquisition genes in plasmids supports their potential use in plasmid-mediated bioaugmentation strategies, providing a promising approach for improving soil fertility in P-deficient or contaminated environments [ 79 ]. Moreover, HGT of symbiotic genes to native soil bacteria was demonstrated by recent genomic studies on rhizobial inoculants [ 80 ]. This emphasizes the significance of tracking and controlling gene spread in order to preserve inoculant efficiency. These insights further support the relevance of mobile genetic elements, such as plasmids, in shaping microbial functionality in soil systems. While interpreting these results, it is important to acknowledge that many of the sequences identified from metagenomic assemblies likely represent fragmented plasmid contigs rather than complete elements. While the consistent trends observed across datasets lend robustness to the main patterns described, the incomplete nature of plasmid sequences limits the ability to make precise predictions regarding plasmid mobility and genomic features. To overcome these limitations and enhance resolution, future studies should integrate long-read sequencing technologies, such as those offered by Oxford Nanopore Technologies or Pacific Biosciences, which significantly improve the quality of metagenomic assemblies, particularly in complex environments such as soils [ 81 – 83 ]. Moreover, when the primary objective is to characterize HGT, proximity ligation methods such as Hi-C sequencing are recommended, as they allow for the high-throughput linkage of MGEs with their bacterial hosts, even within complex environmental samples [ 84 – 87 ]. As reviewed by Brito [ 71 ], a growing suite of molecular and computational tools, including Hi-C, OIL-PCR, and barcoded reporter constructs, now offers unprecedented resolution in assessing the ecology, frequency, and directionality of HGT within natural microbial communities. Incorporating such methods will be critical to fully understand the role of plasmid-borne AMGs in microbial adaptation, and advance the ecological interpretation of mobilome data in soil microbiomes. 5. Conclusion This study demonstrates that plasmids act as diverse genetic reservoirs for P acquisition functions, harboring key genes involved in regulation, transport, inorganic solubilization, and organic mineralization. These findings underscore their significant role in microbial P cycling. Notably, mobilizable plasmids exhibit lower GC content compared to non-mobilizable ones, suggesting their adaptation to a variety of bacterial hosts, particularly in competitive environments such as soils. Additionally, plasmids from P-deficient soils showed higher abundances of transport and organic mineralization genes, suggesting an adaptive response to low P availability. Taxonomic analysis shows that Pseudomonadota and Bacillota dominate as plasmid hosts, with key P-acquisition genes present across these phyla. These results highlight the importance of plasmid-borne genes in biotechnological applications as well as microbial ecology. Understanding the diversity and mobility of P-acquisition genes will drive the development of more effective microbial inoculants and targeted bioaugmentation techniques, improving soil fertility and promoting sustainable agriculture. Future research should focus on experimentally verifying the regulation, expression, and ecological impact of these genes within microbial communities. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This study was financed by the Agencia Nacional de Investigación y Desarrollo (ANID) of Chilean government through ANID Grant Doctorado Nacional 2023-21230832 (P.B.); FONDECYT Regular Projects 1251164 (M.A.); 1241293 (P.J.B.) and 1230084 (M.L.M.). This study was also funded by Concurso Anillos de Investigación en Áreas Temáticas, ANID ATE220038 (P.J.B.) and by Universidad de La Frontera (DiUFRO), Proyectos de Investigación Vinculados a la Red Nexer No. DNX22-0009 (P.J.B.). B.E.D. was supported by the European Research Council (ERC) Consolidator grant 865694: DiversiPHI, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2051 – Project-ID 390713860, and the Alexander von Humboldt Foundation in the context of an Alexander von Humboldt-Professorship founded by German Federal Ministry of Education and Research. Author Contribution PB, PJB, and MA conceived and designed the study. PB conducted investigation, data analyses, and prepared the original draft with support from PJB and MA. MG, IL, MLM, and BED improved the manuscript through suggestions and critical comments. MA, PJB, and MLM also contributed to project administration and funding acquisition. All authors read and approved the final manuscript. Acknowledgement The authors acknowledge the Scientific and Technological Bioresource Nucleus of Universidad de La Frontera (BIOREN–UFRO) and Service Management Analytical Research and Training Center (SmartC-BIOREN). The authors also acknowledge the supercomputing infrastructure of Soroban (SATREPS MACH—JPM/JSA1705), Centro de Modelación y Computación Científica, Universidad de La Frontera, Temuco. Data Availability Data is provided within the manuscript or supplementary information files References White PJ, Hammond JP. Phosphorus nutrition of terrestrial plants. In: White PJ, Hammond JP, editors. The ecophysiology of plant-phosphorus interactions. Springer; 2008. pp. 51–81. https://doi.org/10.1007/978-1-4020-8435-5_4 . Richardson AE, Simpson RJ. Soil microorganisms mediating phosphorus availability update on microbial phosphorus. Plant Physiol. 2011;156(3):989–96. https://doi.org/10.1104/pp.111.175448 . Walsh M, Schenk G, Schmidt S. 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Microorganisms. 2025;13(4):911. https://doi.org/10.3390/microorganisms13040911 . Garbisu C, Garaiyurrebaso O, Epelde L, Grohmann E, Alkorta I. Plasmid-Mediated Bioaugmentation for the Bioremediation of Contaminated Soils. Front Microbiol. 2017;8. https://doi.org/10.3389/fmicb.2017.01966 . Kohlmeier MG, O’Hara GW, Ramsay JP, Terpolilli JJ. Closed genomes of commercial inoculant rhizobia provide a blueprint for management of legume inoculation. Appl Environ Microbiol. 2025;91(2):0221324. https://doi.org/10.1128/aem.02213-24 . Tedersoo L, Albertsen M, Anslan S, Callahan B. Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology. Appl Environ Microbiol. 2021;87(17):0062621. https://doi.org/10.1128/AEM.00626-21 . Xu G, Zhang L, Liu X, Guan F, Xu Y, Yue H, et al. Combined assembly of long and short sequencing reads improve the efficiency of exploring the soil metagenome. BMC Genomics. 2022;23(1):37. https://doi.org/10.1186/s12864-021-08260-3 . Liu L, Chen Y, Shen J, Pan Y, Lin W. Metabolic versatility of soil microbial communities below the rocks of the hyperarid Dalangtan Playa. Appl Environ Microbiol. 2023;89(11):0107223. https://doi.org/10.1128/aem.01072-23 . Bickhart DM, Watson M, Koren S, Panke-Buisse K, Cersosimo LM, Press MO, et al. Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation. Genome Biol. 2019;20(1):153. https://doi.org/10.1186/s13059-019-1760-x . Stalder T, Press MO, Sullivan S, Liachko I, Top EM. Linking the resistome and plasmidome to the microbiome. ISME J. 2019;13(10):2437–46. https://doi.org/10.1038/s41396-019-0446-4 . Bickhart DM, Kolmogorov M, Tseng E, Portik DM, Korobeynikov A, Tolstoganov I, et al. Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities. Nat Biotechnol. 2022;40(5):711–9. https://doi.org/10.1038/s41587-021-01130-z . Regmi R, Anderson J, Burgess L, Mangelson H, Liachko I, Vadakattu G. Shotgun and Hi-C sequencing datasets for binning wheat rhizosphere microbiome. Sci Data. 2025;12(1):367. https://doi.org/10.1038/s41597-025-04651-3 . Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.xlsx Supplementaryinformation.pdf Cite Share Download PDF Status: Published Journal Publication published 06 Apr, 2026 Read the published version in Environmental Microbiome → Version 1 posted Editorial decision: Revision requested 26 Nov, 2025 Reviews received at journal 24 Nov, 2025 Reviews received at journal 07 Nov, 2025 Reviews received at journal 02 Nov, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers agreed at journal 26 Oct, 2025 Reviewers agreed at journal 24 Oct, 2025 Reviewers agreed at journal 24 Oct, 2025 Reviewers invited by journal 24 Oct, 2025 Editor assigned by journal 30 Sep, 2025 Submission checks completed at journal 19 Sep, 2025 First submitted to journal 17 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Dutilh","email":"","orcid":"","institution":"Friedrich Schiller University Jena","correspondingAuthor":false,"prefix":"","firstName":"Bas","middleName":"E.","lastName":"Dutilh","suffix":""},{"id":538902667,"identity":"0f684da4-2a38-447c-8952-4a45cc3ef699","order_by":6,"name":"Michel Abanto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYDAC5gNsYJofRCQUEKOFLQGkxYBBsgGkxYAULQYHGMA0YaDbxvzswc8df+SMz69O/PDAgEGeX+wAfi1mx9jMDXvPGBib3Xi7WQLoMMOZsxMIaLnfYCbB22aQuO3G2Q0gLQkGtwlpOcb+TfIvUMvmGWc3/yBSC4+ZNMiWDfy924i1hafcWLbN2FjiBu82iwQDCSL8cox928O3bXJy/P1nN9/8UWEjzy9NQAsCSIBVShCrHAT4D5CiehSMglEwCkYSAAAkfEOG6uI5qAAAAABJRU5ErkJggg==","orcid":"","institution":"University of La Frontera","correspondingAuthor":true,"prefix":"","firstName":"Michel","middleName":"","lastName":"Abanto","suffix":""}],"badges":[],"createdAt":"2025-09-18 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07:59:14","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":30682,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/6298800ae844288c67cda3b4.png"},{"id":95226483,"identity":"bf375336-7268-49f3-8523-592228a391b7","added_by":"auto","created_at":"2025-11-05 16:31:13","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":201624,"visible":true,"origin":"","legend":"","description":"","filename":"733687a518c4497d82a2bf6d7a5320681structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/da4a6c1979c46fed97bc288c.xml"},{"id":95178576,"identity":"4570df3b-f2ee-4149-8a06-174501dcee8d","added_by":"auto","created_at":"2025-11-05 07:59:14","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":220081,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/a4c624d18c2f0b93f0912ea4.html"},{"id":95178558,"identity":"8a192384-b9cb-4550-8319-a285b293beb9","added_by":"auto","created_at":"2025-11-05 07:59:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":166602,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the length and GC content of plasmids isolated from soil and retrieved from the PLSDB database containing P-acquisition genes. (A) Relationship between plasmid mobility and length. (B) Relationship between plasmid mobility and GC content. Asterisks indicate statistical significance: ns = not significant, **** = p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/3b5e9910cc25c4f38873c3a9.png"},{"id":95227073,"identity":"9ae3d14d-2739-4d7f-8fbe-abdeb89a0a85","added_by":"auto","created_at":"2025-11-05 16:32:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":190222,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic distribution of bacterial hosts and functional diversity of plasmids carrying P-acquisition genes retrieved from the PLSDB-soil database. (A) Relative abundance of bacterial host taxa, classified at the phylum, family, and genus levels. (B) Heatmap visualization showing the count and distribution of P-acquisition genes in plasmids across bacterial families, categorized into the P-acquisition functional categories.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/de9fbb93202692b30f0bf194.png"},{"id":95227144,"identity":"78c3cae2-6e74-4cf7-9b61-3bc9547adc63","added_by":"auto","created_at":"2025-11-05 16:32:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":121235,"visible":true,"origin":"","legend":"\u003cp\u003eGC content of plasmids containing P-acquisition genes identified in soil metagenomes. Plasmids are grouped by mobility class, and their distribution is shown across different soil environments. Asterisks indicate statistical significance: *** = p \u0026lt; 0.001, **** = p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/3e4f7c3773fd13ff73692e7e.png"},{"id":95226505,"identity":"7b3b2b2d-2580-43cd-b0f2-8b7d0bc4ac70","added_by":"auto","created_at":"2025-11-05 16:31:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":34505,"visible":true,"origin":"","legend":"\u003cp\u003eZ-score heatmap of P-acquisition gene profiles in plasmids across soil environments with varying P availability. Relative abundances of P-acquisition genes across six distinct soil types (desert, farmland, grassland, mine, tundra, and volcanic) were transformed using the Z-score to enable direct comparison. Environments were classified as low- or high-P based on available metadata.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/1ca8055e619dc9990bcfd9bc.png"},{"id":95178560,"identity":"7b19698e-05cf-4979-bef9-0acf1d11aafe","added_by":"auto","created_at":"2025-11-05 07:59:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":102521,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of differential abundance of P-acquisition genes in plasmids across biomes with contrasting P availability. A-D Boxplots shows the log2- transformed TPM values of genes involved in P regulation, P transport, organic P mineralization and inorganic P solubilization, respectively, grouped by P availability (High vs Low). Dots represent individual samples colored by biome. Asterisks indicate statistical significance: ns = not significant, ** = p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/5a59ba6d67fa7e01ee53e304.png"},{"id":106810745,"identity":"46aa646c-58e5-44fe-8ff1-b74cf4ab8b2c","added_by":"auto","created_at":"2026-04-13 16:16:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1467966,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/f9c560d7-8d27-4c35-98f2-9f2050f2208f.pdf"},{"id":95178564,"identity":"1fafea7b-b3e7-414e-993d-57c3a83e25ed","added_by":"auto","created_at":"2025-11-05 07:59:14","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":585656,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/cc29cb2d8bbbf6e34c0ed6b3.xlsx"},{"id":95227177,"identity":"cc92f1df-25c9-413a-b171-8dafa9b92ad6","added_by":"auto","created_at":"2025-11-05 16:32:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1112550,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7644682/v1/5a61aae86d560e2f3d39ee2b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unraveling Plasmid Contributions to Phosphorus Acquisition in Soil Microbiomes","fulltext":[{"header":"Highlights","content":"\u003cp\u003ePlasmids harbor key genes involved in phosphorus acquisition in soil environments\u003c/p\u003e\n\u003cp\u003eRegulatory and transporter genes represent the most abundant functional categories\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePseudomonadota\u003c/em\u003e and \u003cem\u003eBacillota\u003c/em\u003e are the dominant plasmid hosts for P-acquisition\u003c/p\u003e"},{"header":"1. Background","content":"\u003cp\u003ePhosphorus (P) is an essential macronutrient necessary for a variety of biological functions in microorganisms [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In natural environments, P availability often limits the growth of microbes and plants. This is mainly because of its strong interactions with soil minerals and organic matter, which result in low solubility and bioavailability [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. P limitation has become more pressing with climate change, because extreme weather events are projected to exacerbate P losses from agricultural soils through intensified erosion and runoff, further undermining soil fertility and contributing to environmental degradation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In agriculture, P deficiency is addressed by applying inorganic phosphate fertilizers sourced from phosphate rock, which is composed primarily of apatite minerals such as fluorapatite (Ca\u003csub\u003e10\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e6\u003c/sub\u003eF\u003csub\u003e2\u003c/sub\u003e) and its variants. The global supply of high-quality phosphate rock is limited, with estimates suggesting that it could be exhausted within decades [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, P fertilization is inefficient, as much of the applied P rapidly becomes immobilized through precipitation or adsorption with iron and aluminum oxides in acidic soils or with calcium in alkaline soils, as well as through incorporation into organic matter [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These processes lead to the accumulation of recalcitrant, poorly bioavailable P forms, referred as legacy P in soils [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These limitations have driven growing interest in sustainable alternatives to enhance P acquisition in soils, such as the use of phosphate-solubilizing or mineralizing bacteria [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These bacteria enhance P availability in soils by solubilizing inorganic phosphate, primarily through the secretion of organic acids, which lower the pH and make inorganic phosphate soluble [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. They also mineralize organic P compounds by secreting a variety of extracellular enzymes, including phosphatases, phytases, phosphonatases, and C\u0026ndash;P lyases [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These bacteria can also efficiently manage P uptake pathways, as evidenced by the upregulation of phosphate-binding and transport proteins under P-deficient conditions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], thereby enhancing plant P uptake and improving soil fertility [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. While these microbial processes are well recognized, a deeper understanding of their genetic basis is critical to fully harness their potential. In particular, the mobility of P-acquisition genes within and between microbial populations is increasingly seen as a central factor shaping bacterial adaptation to environmental conditions, like P-deficient soils.\u003c/p\u003e\u003cp\u003eThe mobilome encompasses all mobile genetic elements (MGEs) within a given microbiome. These segments of genetic material can move within a genome or between genomes of different organisms [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Among MGEs, bacteriophages and plasmids play a key role in horizontal gene transfer (HGT) due to their mobility. In particular, the presence and dissemination of auxiliary metabolic genes (AMGs) in bacteriophages have attracted growing interest for their potential role in microbial P cycling [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Meanwhile, plasmids are critical for bacterial adaptation and survival in challenging environments, as they facilitate the HGT involved in nutrient acquisition [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Plasmids can be classified into three categories according to their mobility potential: (i) non-mobilizable plasmids, which lack recognizable transfer genes but may still move between cells through mechanisms other than direct conjugation; (ii) mobilizable plasmids, which encode a relaxase gene but depend on the mating pair formation (MPF) system of a co-resident conjugative element; and (iii) conjugative plasmids, which possess both a relaxase and a complete MPF/type IV secretion system (T4SS), enabling autonomous transfer [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In metagenomic datasets, however, plasmid contigs are frequently fragmented, complicating the detection of complete conjugative systems and favoring the identification of mobilizable elements. Despite their recognized ecological importance, a comprehensive understanding of P-acquisition genes in plasmids remains limited, particularly regarding their distribution, functionality, and mobility across diverse soil environments.\u003c/p\u003e\u003cp\u003eAdvances in high-throughput sequencing and bioinformatic analysis have facilitated the identification of P-related genes in microbial genomes and metagenomes [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, the genetic strategies and ecological role of plasmid-mediated P acquisition remain underexplored, mainly due to the difficulties in distinguishing plasmids from chromosomal DNA in metagenomic datasets [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The increasing availability of curated plasmid databases, such as PLSDB [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and specialized metabolic gene repositories, such as the P cycling database (PCycDB) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], provides new opportunities to investigate the role of plasmids in microbial P metabolism. By integrating these resources with metagenomic approaches, it is possible to identify and characterize P-acquisition genes in plasmids retrieved from public databases and environmental metagenomes.\u003c/p\u003e\u003cp\u003eThis study aims to elucidate the distribution and functional classification of P-acquisition genes within plasmids in soil environments. Specifically, we sought to (i) identify P-acquisition genes in publicly available plasmid sequences retrieved from PLSDB, (ii) analyze the prevalence, diversity, and environmental distribution of P-acquisition genes in plasmids identified from publicly available metagenomes representing diverse soil types, and (iii) evaluate the mobility potential and taxonomic distribution of plasmid-borne P-acquisition genes across different environmental contexts. To achieve these objectives, we employed an \u003cem\u003ein silico\u003c/em\u003e approach that integrated plasmid sequence retrieval, dereplication, functional gene annotation, and classification of plasmid mobility and host prediction. By addressing these knowledge gaps, this study provides a clearer understanding of how plasmids contribute to P cycling in microbiomes, emphasizing their involvement in P acquisition. Our findings provide a broader understanding of the diversity and ecological significance of plasmid-borne P-acquisition genes.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Identification of phosphorus acquisition genes in plasmids using public databases\u003c/h2\u003e\u003cp\u003eTo determine the presence of bacterial genes involved in the P cycle within plasmids, an \u003cem\u003ein silico\u003c/em\u003e review and search was conducted. For this purpose, the plasmid database PLSDB (v.2023_11_03_v2) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] was used, as it provides curated plasmid sequences along with their associated metadata. For this analysis, all sequences indicating \"soil\" as the source of isolation were retrieved. For these sequences the protein-coding genes were predicted using prodigal v2.6.3 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and then aligned against the P cycling database (PCycDB v1.1) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], a specialized database covering P metabolic processes that includes 139 gene families across 10 metabolic categories. The alignment was performed using DIAMOND BLASTP v0.9.14 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] with an e-value threshold of 0.0001. To ensure accurate identification and minimize false positives, additional filters were applied: a minimum identity threshold of 70% and a minimum hit length of 25 amino acids, as recommended by the PCycDB guidelines, based on benchmarking results showing that this cutoff maintains accuracy in gene detection.\u003c/p\u003e\u003cp\u003eSubsequently, plasmids containing genes related to the P cycle were grouped into four functional categories based on primary P acquisition processes in microorganisms: i) inorganic P solubilization (\u003cem\u003eppk, ppa, gcd\u003c/em\u003e), ii) organic P mineralization (\u003cem\u003ephoA, phoD, phoX, phoN, aphA, phoC, olpA, opd, phy, appA, pafA, ugpQ, glpQ, phnGHIJKLMNOPWXYZ\u003c/em\u003e), iii) P transport (\u003cem\u003epgtP, pstSCAB, pit, htxB, ptxABC, phnD_phosphite, phnDEC, ugpBAEC, phnSVUT, glpT, aepXVWPS\u003c/em\u003e), and iv) P regulation (\u003cem\u003ephoU, phoR, phoB, phoP, SenX3, RegX3, pgtC, pgtB, pgtA, phnF\u003c/em\u003e). Hereafter, these categories are referred to as the P-acquisition functional categories. To prevent overrepresentation of genes in the analysis, sequences were dereplicated using MMseqs2 v15.6f452 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] with a sequence identity threshold\u0026thinsp;\u0026gt;\u0026thinsp;0.6 and coverage\u0026thinsp;\u0026gt;\u0026thinsp;0.5, in bidirectional mode (\u0026mdash;cov-mode 0). This parameter minimized redundancy to prevent clustering of plasmids with highly similar backbone genes but distinct accessory regions. To further assess genomic relatedness among dereplicated sequences, pairwise average nucleotide identity was calculated using ANIclustermap v2.0.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/moshi4/ANIclustermap\u003c/span\u003e\u003cspan address=\"https://github.com/moshi4/ANIclustermap\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, which performs hierarchical clustering based on sequence similarity. The resulting dendrogram was visualized using iTOL v7 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFinally, plasmids were classified based on their mobilization capacity using MOBFinder v1.0 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This tool employs vector-based language models to characterize plasmids according to their transferability into mobility groups, based on ten validated MOB relaxase protein families (MOBB, MOBC, MOBF, MOBH, MOBL, MOBM, MOBP, MOBQ, MOBT, MOBV), which are categorized as mobilizable, while NON-MOB plasmids are classified as non-mobilizable.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Retrieval of metagenomic reads\u003c/h2\u003e\u003cp\u003eTo retrieve metagenomic reads from soil for plasmid identification and the analysis of P-acquisition genes, a bibliographic search was conducted using the keywords \"soil,\" \"metagenome,\" and \"illumina.\" This search was filtered based on the following criteria: (i) studies that employed whole-metagenome sequencing, (ii) studies that described physicochemical parameters of the soil, particularly P levels, and (iii) datasets with publicly available reads. As a result, 96 soil metagenomic datasets were retrieved from five publications [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] representing diverse biomes, including desert (n\u0026thinsp;=\u0026thinsp;12), farmland (n\u0026thinsp;=\u0026thinsp;15), grassland (n\u0026thinsp;=\u0026thinsp;27), mine (n\u0026thinsp;=\u0026thinsp;17), tundra (n\u0026thinsp;=\u0026thinsp;16), and volcanic (n\u0026thinsp;=\u0026thinsp;9) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe classification of P availability across environments was based on two criteria: (i) if the study explicitly described the soil as P-deficient or P-enriched; otherwise, (ii) the classification was inferred from the reported concentration of bioavailable P, as measured using either the Olsen or Bray extraction methods. Soils with P concentrations\u0026thinsp;\u0026ge;\u0026thinsp;30 mg/kg were classified as having high P availability, whereas those with lower concentrations were categorized as having low P availability (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Although the specific P requirements of individual plant species and different types of soils may vary considerably, the 30 mg/kg threshold was adopted as a standardized operational criterion to distinguish between P-enriched and potentially P-deficient soils. This value is consistent with thresholds reported in agronomic and ecological literature, where Olsen P concentrations around 30 mg/kg are often used to distinguish between P availability [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Metagenomic assembly and construction of the plasmid catalog\u003c/h2\u003e\u003cp\u003eThe metagenomic sequencing reads were retrieved from the NCBI Sequence Read Archive and processed as paired-end reads using fasterq-dump from the sratoolkit (v3.1.1) with the --split-files parameter. Adapter sequences were removed and low-quality reads (Q-value\u0026thinsp;\u0026lt;\u0026thinsp;20) were trimmed with Trimmomatic (v0.39) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] using the SLIDINGWINDOW:4:20 parameter, which applies a 4-base sliding window and cuts the read when the average quality within the window drops below 20. Reads shorter than 50 base pairs after trimming were discarded using the MINLEN:50 parameter. The filtered reads were assembled using MEGAHIT (v1.2.9) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] with the meta-large parameter, and contigs longer than \u0026ge;\u0026thinsp;1000 base pairs were retained for downstream analysis.\u003c/p\u003e\u003cp\u003ePlasmids were identified using geNomad (v1.8.0) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] with default parameters and PLASMe (v1.1) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] in balanced mode. The number of plasmids identified by each tool for each sample is shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Following identification, the methodology described in section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e was applied, including alignment against PCycDB, functional categorization of P cycle-related genes, dereplication of plasmids containing P-acquisition genes, and mobility classification, resulting in a non-redundant dataset used for downstream analyses. To estimate plasmid abundance, high-quality reads were mapped to the non-redundant dataset using CoverM v0.7.0 [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] under the contig model with the following parameters: -p minimap2-sr --min-read-percent-identity 0.95 --min-read-aligned-percent 0.75 -m tpm. An abundance table was generated by calculating transcripts per million (TPM), as described by Li et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], facilitating robust comparisons of varying abundances across samples with different sequencing depths and technologies. Additionally, functional annotation of plasmid genes was performed using Bakta v1.9.3 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] with the full database configuration, and the plasmid host range was estimated using HRPredict [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], which applies a protein language model and a one-class support vector machine algorithm to predict potential bacterial hosts based on plasmid-encoded proteins.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were conducted in R v4.3.1 using dplyr [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], ggplot2 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and stats packages. The normality of plasmid length and GC content was assessed using the Shapiro-Wilk test across P availability categories (\"high\" and \"low\") and mobility groups (\"mobilizable\" and \"non-mobilizable\"). For variables that did not meet the normality assumption (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), differences between groups were evaluated using the non-parametric Mann-Whitney U tests (Wilcoxon rank-sum test). Pearson and Spearman correlation analyses were applied to examine the relationship between the number of P-acquisition genes and plasmid length.\u003c/p\u003e\u003cp\u003eTo visualize the functional gene distributions, a log2 transformation was applied to the input count and abundance matrices to reduce skewness and enhance interpretability. Heatmaps were generated using the ComplexHeatmap package [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. To assess the differences in functional gene abundance between P conditions, TPM values were aggregated by P-acquisition functional categories, and comparisons between high- and low-P environments were performed using the Mann\u0026ndash;Whitney U test. Additionally, cumulative TPM values across all P-acquisition functional categories per sample were calculated and compared between P conditions to evaluate the overall abundance trends.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Phosphorus acquisition genes in plasmids retrieved from the PLSDB database\u003c/h2\u003e\u003cp\u003eTo evaluate the presence of P-acquisition genes in soil-derived plasmids, a comprehensive analysis of the PLSDB database was conducted. This database comprises a total of 59,895 plasmids, representing a curated collection of publicly available plasmid sequences from diverse environments. After filtering for plasmids isolated from soil based on available metadata, 2,108 plasmids were identified. Notably, 473 (22.4%) of these plasmids carried P-acquisition genes, demonstrating that a substantial fraction of soil plasmids contributes to microbial P cycling. Following dereplication, 449 unique plasmids containing at least one P-acquisition gene were retained, representing 21.30% of the soil-derived plasmids in the database (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2; Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn terms of genomic characteristics, these plasmids had a median length of 347,238 bp, with a vast range from 5,846 to 3,525,317 bp. The GC content showed a median of 59.02%, with a range from 24.19% to 72.65%. Additionally, a statistically significant difference was observed between the GC contents of the plasmids based on their mobility (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Notably, within the mobilizable plasmid group, the GC content varied markedly among the host phyla. Plasmids from \u003cem\u003ePseudomonadota\u003c/em\u003e exhibited higher GC content than those from \u003cem\u003eBacillota\u003c/em\u003e. In contrast, among non-mobilizable plasmids, \u003cem\u003eActinomycetota\u003c/em\u003e and \u003cem\u003eDeinococcota\u003c/em\u003e displayed consistently high GC contents (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). These differences suggest that the host genomic composition plays a role in shaping the plasmid GC content (Fig. S3 and S4). In comparison, no significant differences were found in plasmid length when mobility was considered (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e\u003cp\u003eTo further explore the genomic features of plasmids encoding P-acquisition genes, the relationship between plasmid length and the number of encoded P-related genes was assessed. Both Pearson (r\u0026thinsp;=\u0026thinsp;0.77, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Spearman (r\u0026thinsp;=\u0026thinsp;0.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) correlation analyses revealed strong positive associations, indicating that longer plasmids tend to harbor more P-acquisition genes (Fig. S5). Altogether, these results reveal that the genomic architecture of plasmids harboring P-acquisition genes is shaped by both plasmid mobility and host taxa, with larger plasmids tending to carry more functional genes, reflecting potential adaptations to enhance P-acquisition in diverse environmental contexts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA total of 1,774 gene sequences related to the P-acquisition functional categories were identified across the analyzed plasmids. Among these, regulatory genes such as \u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, and \u003cem\u003eRegX3\u003c/em\u003e, as well as transporter genes like \u003cem\u003eugpC\u003c/em\u003e, \u003cem\u003ephnE\u003c/em\u003e, and \u003cem\u003ephnC\u003c/em\u003e, were the most prevalent, representing 42.73% and 40.02% of the P-acquisition genes detected in the analyzed plasmids, respectively. Notably, 1,314 of these sequences (74.07%) were found in plasmids classified as mobilizable, suggesting that these genes may be subject to horizontal transfer through plasmid mobilization (Fig. S6).\u003c/p\u003e\u003cp\u003eThe bacterial hosts of plasmids containing P-acquisition genes were analyzed across different taxonomic ranks: phylum, family, and genus. At the phylum level, the majority of soil-derived plasmids belonged to \u003cem\u003ePseudomonadota\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;237), \u003cem\u003eBacillota\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;144), and \u003cem\u003eActinomycetota\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;49), with lower representation from \u003cem\u003eDeinococcota\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;10), \u003cem\u003eBacteroidota\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;5), and \u003cem\u003eCyanobacteriota\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;4). At the family level, \u003cem\u003eBacillaceae\u003c/em\u003e, \u003cem\u003eRhizobiaceae\u003c/em\u003e, \u003cem\u003eBurkholderiaceae\u003c/em\u003e were the most prevalent. Genus rank analysis revealed \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eRhodococcus\u003c/em\u003e and \u003cem\u003eRhizobium\u003c/em\u003e as the dominant groups. Notably, a substantial fraction of plasmids were grouped under the \u0026lsquo;Others\u0026rsquo; category, underscoring the broad taxonomic diversity of bacterial hosts harboring plasmids with P-acquisition genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). These results highlight a strong representation of \u003cem\u003ePseudomonadota\u003c/em\u003e, suggesting contributions from a broad diversity of taxa, and indicate that both this phylum and \u003cem\u003eBacillota\u003c/em\u003e, predominantly represented by \u003cem\u003eBacillus\u003c/em\u003e, emerge as key contributors to P solubilization and mineralization.\u003c/p\u003e\u003cp\u003eThe heatmap further illustrates the count and distribution of P-acquisition genes across bacterial host families, showing that regulatory (\u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e and \u003cem\u003eRegX3\u003c/em\u003e) and transporter genes (\u003cem\u003eugpC\u003c/em\u003e, \u003cem\u003ephnE\u003c/em\u003e, \u003cem\u003ephnC\u003c/em\u003e) were the most prevalent. Inorganic P solubilization and organic P mineralization genes were widely distributed, particularly among \u003cem\u003eComamonadaceae\u003c/em\u003e, \u003cem\u003eMoraxellaceae\u003c/em\u003e, and \u003cem\u003eMicrococcaceae\u003c/em\u003e, highlighting their potential role in P mobilization. The analysis reveals distinct patterns of functional specialization across bacterial lineages, with host families clustering according to similarities in the P-acquisition gene profiles of their associated plasmids, providing insights into the ecological roles of these mobile elements in P cycling. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eDespite the low representation of soil-isolated plasmids in the PLSDB database, the presence of P-acquisition genes was evident. This prompted further investigation into whether this gene abundance pattern is also observed in plasmids identified from soil metagenomes and how bioavailable P concentrations in soil influence these genetic elements.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Phosphorus acquisition genes in plasmids identified from soil metagenomes\u003c/h2\u003e\u003cp\u003eTo further investigate the presence and distribution of P-acquisition genes in plasmids beyond those cataloged in PLSDB, we performed \u003cem\u003ede novo\u003c/em\u003e assembly of metagenomic datasets derived from 96 soil samples, retrieved from public repositories and spanning six distinct biomes, in order to identify plasmids directly from soil microbial communities. A total of 248,750 contigs were identified as plasmid sequences using geNomad and PLASMe. Among these, 9,191 plasmids contained at least one gene related to the P cycle, encompassing all metabolic categories represented in the PCycDB database, such as two-component systems, oxidative phosphorylation, phosphonate metabolism, and other P cycling processes. From this broader set, 5,602 plasmids specifically harbored genes associated with the P-acquisition functional categories (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). To minimize redundancy and overrepresentation, dereplication was performed, resulting in 1,966 representative plasmids retained for subsequent analyses (Table S3; Fig. S7).\u003c/p\u003e\u003cp\u003eThese plasmid sequences have a median length of 3,304 bp, with a minimum observed length of 1,001 bp and a maximum of 312,583 bp. Significant statistical differences were found in desert and grassland biomes when plasmids were grouped by mobility, as larger plasmids were identified in these environments (Fig. S8). GC content was significantly higher in non-mobilizable plasmids compared to mobilizable ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), similar to the pattern observed in plasmids retrieved from PLSDB (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). This finding confirms the correlation between genetic mobility and GC content in an independent dataset.\u003c/p\u003e\u003cp\u003eFurthermore, the relationship between plasmid length and the number of encoded P-acquisition genes was evaluated. Results showed a weak positive correlation (Pearson: r\u0026thinsp;=\u0026thinsp;0.19, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Spearman: r\u0026thinsp;=\u0026thinsp;0.08, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting that longer plasmids tend to harbor more P-acquisition genes (Fig. S9). However, the correlation was weak, as indicated by the low correlation coefficients, which highlight that plasmid length alone does not strongly determine the number of P-acquisition genes. This outcome is likely due to the fact that many of the identified sequences correspond to plasmid fragments rather than complete plasmids, which may not fully represent the genomic architecture of intact plasmids.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA total of 2,503 genes were identified across the P-acquisition functional categories. Similar to the results obtained from the PLSDB plasmids, transporter and regulatory genes were the most abundant, accounting for 47.78% and 34.84% of the total, respectively. Among transporter genes, \u003cem\u003eugpC\u003c/em\u003e, \u003cem\u003epstB\u003c/em\u003e, and \u003cem\u003epstS\u003c/em\u003e were the most prevalent, while \u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, and \u003cem\u003eRegX3\u003c/em\u003e were the most frequent among the regulatory genes. Additionally, when analyzing the distribution of genes based on their mobilization capacity, 45.98% were found in plasmids classified as mobilizable (Fig. S10).\u003c/p\u003e\u003cp\u003eTo better understand the ecological relevance of these genes, we examined their distribution and abundance across contrasting soil environments. Our analysis revealed that plasmids and plasmid-derived fragments consistently encoded functional categories of P-acquisition genes in all analyzed biomes (Fig. S11). These include regulatory genes (\u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, \u003cem\u003ephoR\u003c/em\u003e, \u003cem\u003ephoU\u003c/em\u003e, \u003cem\u003eRegX3\u003c/em\u003e, \u003cem\u003eSenX3\u003c/em\u003e), transport systems (\u003cem\u003epstSCAB\u003c/em\u003e, \u003cem\u003eugpBAEC\u003c/em\u003e, \u003cem\u003epit\u003c/em\u003e), organic P mineralization genes (\u003cem\u003ephnGHIJKLMNW\u003c/em\u003e of the \u003cem\u003ephn\u003c/em\u003e operon, \u003cem\u003eglpQ\u003c/em\u003e, \u003cem\u003eopd\u003c/em\u003e, \u003cem\u003ephoD\u003c/em\u003e, \u003cem\u003ephoX\u003c/em\u003e), and inorganic P solubilization genes (\u003cem\u003egcd\u003c/em\u003e, \u003cem\u003eppa\u003c/em\u003e, \u003cem\u003eppk\u003c/em\u003e). To assess functional variation under different P availabilities, Z-score heatmap analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) indicated that high-P tundra environments exhibited a greater abundance of regulatory genes (\u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, \u003cem\u003ephoR\u003c/em\u003e, \u003cem\u003ephoU\u003c/em\u003e, \u003cem\u003eRegX3\u003c/em\u003e) than low-P tundra, and the \u003cem\u003eugpBAEC\u003c/em\u003e transport system was also more prevalent under high-P conditions. In mine soils, the \u003cem\u003eglpT\u003c/em\u003e gene involved in P transport was notably enriched relative to other soil types. Despite the heterogeneity in soil physicochemical properties, these data demonstrate that plasmids consistently harbor a diverse repertoire of P-acquisition genes.\u003c/p\u003e\u003cp\u003eIn addition, when comparing the abundance of P-acquisition functional categories between high- and low-P environments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), P transport and organic P mineralization genes were significantly more abundant in P-deficient soils, whereas P regulation and inorganic P solubilization genes showed no significant variation. Furthermore, when the overall abundance of P-acquisition genes was compared between high- and low-P environments, plasmids from P-deficient soils were found to harbor a significantly higher number of these genes (Fig. S12). These results underscore the dynamic role of P availability in modulating the gene composition of plasmids related to P acquisition, with the transport and organic mineralization processes being particularly responsive to low P levels.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding the bacterial hosts, only those with a unique phylum-level taxonomic assignment were considered, since host prediction indicated that some plasmids could potentially be associated with up to five different bacterial phyla (Table S3). A total of 429 plasmids or plasmid fragments with a single predicted host phylum were analyzed. Consistent with the results from the PLSDB database, \u003cem\u003ePseudomonadota\u003c/em\u003e was the most abundant phylum, however, in this case, \u003cem\u003eActinomycetota\u003c/em\u003e ranked second, followed by \u003cem\u003eBacillota\u003c/em\u003e (Fig. S13). In terms of gene composition, \u003cem\u003ephoR\u003c/em\u003e, \u003cem\u003epstCA\u003c/em\u003e, \u003cem\u003eugpC\u003c/em\u003e and \u003cem\u003ephoD\u003c/em\u003e were present across all three host phyla. Additionally, \u003cem\u003ePseudomonadota\u003c/em\u003e and \u003cem\u003eActinomycetota\u003c/em\u003e hosts taxa exhibited a broad diversity of P-acquisition genes (Fig. S14). These findings provide a comprehensive overview of the diversity and hosts of P-acquisition genes in soil-associated plasmids, thereby setting the foundation for the exploration of their ecological implications.\u003c/p\u003e\u003cp\u003eOur analysis revealed that P-acquisition genes are widely distributed across plasmids from diverse soil environments, highlighting their potential role as key vectors of microbial adaptation to P-deficient conditions. This finding underscores the importance of plasmids in shaping nutrient acquisition strategies in soil microbiomes and suggests that HGT may be a critical mechanism facilitating microbial P cycling.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eHGT plays a key role in nutrient cycles, with growing evidence of genes involved in P, N, S, and C cycling in phages [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In contrast, the role of these functions in plasmids remains poorly understood. While some plasmid-associated genes linked to S [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and N cycling [\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] have been identified, their contribution to P acquisition is largely unknown. Here, we addressed this gap by analyzing P-acquisition genes in soil plasmids from PLSDB and metagenomes spanning six biomes.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Structural characteristics and mobility of soil plasmids: the role of GC content\u003c/h2\u003e\u003cp\u003ePlasmid analyses from PLSDB and soil metagenomes revealed that mobilizable plasmids, defined by validated MOB relaxase protein families, consistently exhibited lower GC content than non-mobilizable ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This compositional pattern aligns with reports associating low GC content with reduced metabolic for the host and facilitate transfer across diverse bacterial lineages [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Conversely, non-mobilizable plasmids with higher GC content may reflect long-term coevolution and adaptation with their hosts (Fig. S4c), favoring structural stability and integration into the cellular environment [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Furthermore, we observed substantial variation in GC content across host phyla, particularly among mobilizable plasmids (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). For instance, plasmids associated with \u003cem\u003ePseudomonadota\u003c/em\u003e exhibited higher GC content than those from \u003cem\u003eBacillota\u003c/em\u003e, while among non-mobilizable plasmids, those affiliated with \u003cem\u003eActinomycetota\u003c/em\u003e and \u003cem\u003eDeinococcota\u003c/em\u003e retained consistently high GC values. These differences reflect the nucleotide composition of the host chromosome (Fig. S3). Plasmid GC content is often\u0026thinsp;\u0026lt;\u0026thinsp;10% lower than that of their bacterial hosts due to selective pressures for genomic maintenance [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Because plasmids primarily carry operational genes, such as those involved in P-acquisition, they may be under selective pressure to optimize their GC composition for efficient transfer [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Functional characterization of plasmid-borne P-acquisition genes\u003c/h2\u003e\u003cp\u003eP-acquisition genes were grouped into four main functional categories: regulation, transport, inorganic solubilization, and organic mineralization. These categories represent the key processes for microbial survival in P-deficient environments, facilitating P metabolism, recycling, and storage. Among the evaluated categories, transporter and regulatory genes stood out because of their abundance in the analyzed plasmids, underscoring their functional and adaptive relevance in the mobilization of P-acquisition genes. Among the transporter genes, \u003cem\u003eugpC\u003c/em\u003e was the most abundant, followed by the phosphate-specific transport system genes \u003cem\u003epstA\u003c/em\u003e, \u003cem\u003epstB\u003c/em\u003e, and \u003cem\u003epstS\u003c/em\u003e. \u003cem\u003eUgpC\u003c/em\u003e encodes a protein that is part of the ATP-binding cassette transport system specific for sn-glycerol-3-phosphate (G3P) in bacteria and serves as an alternative P source under phosphate-limiting conditions [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The primary function of \u003cem\u003eugpC\u003c/em\u003e is to provide the energy required for G3P transport across the cell membrane via ATP hydrolysis [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The \u003cem\u003epstSCAB\u003c/em\u003e complex plays a crucial role in the active uptake of phosphate from the environment, and under conditions of Pi depletion, it propagates a signal that relieves the inhibition of \u003cem\u003ephoR\u003c/em\u003e, allowing its autophosphorylation. Subsequently, \u003cem\u003ephoR\u003c/em\u003e acts as a phosphodonor, transferring the phosphoryl group to the response regulator \u003cem\u003ephoB\u003c/em\u003e, which activates the transcription of genes within the \u003cem\u003ePho\u003c/em\u003e regulon [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Notably, regulatory genes such as \u003cem\u003ephoP\u003c/em\u003e, \u003cem\u003ephoB\u003c/em\u003e, and \u003cem\u003ephoR\u003c/em\u003e were among the most frequently identified genes in the plasmid-borne genetic content. While \u003cem\u003ephoB\u003c/em\u003e is the canonical response regulator that directly activates the transcription of \u003cem\u003ePho\u003c/em\u003e regulon genes in organisms such as \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e has an equivalent regulatory role in \u003cem\u003eActinomycetota\u003c/em\u003e, particularly \u003cem\u003eStreptomyces spp\u003c/em\u003e. In this context, the \u003cem\u003ephoR\u003c/em\u003e/\u003cem\u003ephoP\u003c/em\u003e two-component system functions as a phosphate-sensing mechanism, where \u003cem\u003ephoR\u003c/em\u003e serves as a membrane-bound sensor kinase and \u003cem\u003ephoP\u003c/em\u003e acts as a transcriptional regulator that governs gene expression in response to phosphate limitation [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In addition to phosphate homeostasis, this system also modulates secondary metabolism and developmental processes, underscoring its evolutionary and physiological significance [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. These findings highlight the central role of plasmid-borne transporters and regulatory systems in enhancing microbial adaptation, and suggest that HGT via plasmids may significantly contribute to the dissemination of P-acquisition strategies across diverse soil microbiomes.\u003c/p\u003e\u003cp\u003eThree genes related to the inorganic solubilization were identified: \u003cem\u003eppa\u003c/em\u003e, \u003cem\u003eppk\u003c/em\u003e, and \u003cem\u003egcd\u003c/em\u003e. \u003cem\u003ePpa\u003c/em\u003e encodes inorganic pyrophosphatase, an enzyme that hydrolyzes pyrophosphate to inorganic phosphate, thereby contributing to both energy regulation and P availability [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. \u003cem\u003ePpk\u003c/em\u003e encodes polyphosphate kinase, which synthesizes and mobilizes polyphosphates and provides an efficient form of P storage under nutrient stress conditions [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Finally, \u003cem\u003egcd\u003c/em\u003e encodes glucose dehydrogenase, an enzyme involved in gluconic acid production that acidifies the environment and facilitates the solubilization of insoluble mineral phosphates, thereby increasing their availability for microorganisms. The \u003cem\u003egcd\u003c/em\u003e gene is predominant across soil samples and is considered a major determinant of bioavailable P [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In our results, \u003cem\u003egcd\u003c/em\u003e occurred on plasmids across multiple host families within the phyla \u003cem\u003ePseudomonadota\u003c/em\u003e and \u003cem\u003eBacillota\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), consistent with prior reports [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and compatible with horizontal dissemination may enhance the adaptive potential of microbial communities under P-limiting conditions.\u003c/p\u003e\u003cp\u003eFinally, in the organic mineralization category, phosphatases, such as \u003cem\u003ephoA\u003c/em\u003e, \u003cem\u003ephoX\u003c/em\u003e, and \u003cem\u003ephoD\u003c/em\u003e, along with \u003cem\u003ephn\u003c/em\u003e operon genes, such as \u003cem\u003ephnM\u003c/em\u003e and \u003cem\u003ephnI\u003c/em\u003e, were the most abundant. These phosphatases hydrolyze organic phosphate esters, releasing inorganic phosphate. \u003cem\u003ePhoA\u003c/em\u003e encodes an alkaline phosphatase active under basic pH conditions, while \u003cem\u003ephoX\u003c/em\u003e differs structurally and functionally, being active in marine and alkaline environments [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. \u003cem\u003ePhoD\u003c/em\u003e exhibits a high affinity for organic phosphomonoesters and plays a prominent role in P mineralization in agricultural soils [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Collectively, these enzymes facilitate the conversion of organic P into bioavailable forms for microbial and plant uptake. Moreover, the \u003cem\u003ephn\u003c/em\u003e operon encodes the carbon\u0026ndash;phosphorus (C-P) lyase pathway, a multi-enzyme system responsible for cleavage of the chemically stable C\u0026ndash;P bond present in organophosphonates [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. The ability to catabolize phosphonates expands the ecological flexibility of microorganisms, enabling them to exploit alternative sources of P.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Ecological distribution and functional adaptation of P-acquisition genes\u003c/h2\u003e\u003cp\u003eThe distribution and abundance of P-acquisition genes across various soil environments revealed that plasmids and plasmid fragments consistently encoded a broad spectrum of functional gene categories across all analyzed biomes. These included regulatory genes (\u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, \u003cem\u003ephoR\u003c/em\u003e, \u003cem\u003ephoU\u003c/em\u003e, \u003cem\u003eRegX3\u003c/em\u003e, \u003cem\u003eSenX3\u003c/em\u003e), transport systems (\u003cem\u003epstSCAB\u003c/em\u003e, \u003cem\u003eugpBAEC\u003c/em\u003e, \u003cem\u003epit\u003c/em\u003e), organic P mineralization genes (\u003cem\u003ephnGHIJKLMNW\u003c/em\u003e, \u003cem\u003eglpQ\u003c/em\u003e, \u003cem\u003eopd\u003c/em\u003e, \u003cem\u003ephoD\u003c/em\u003e, \u003cem\u003ephoX\u003c/em\u003e), and inorganic P solubilization genes (\u003cem\u003egcd\u003c/em\u003e, \u003cem\u003eppa\u003c/em\u003e, \u003cem\u003eppk\u003c/em\u003e). This pattern persisted regardless of variations in P availability, climatic conditions, geographic locations, and soil types. Previous studies about soil bacteriophages also reported a wide diversity of P-acquisition genes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. The widespread presence of these genes in the mobilome suggests they form a prevalent functional repertoire, enabling microbes not only to maintain P homeostasis but also to swiftly adjust to nutrient fluctuations, a capacity that may confer broader ecological advantages and resilience in dynamic environments [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough plasmids harbor a diverse range of P-acquisition genes, their abundances vary across environments. A closer examination of functional variation between different P availabilities (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), shows that high-P tundra environments exhibited a higher abundance of regulatory genes (\u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, \u003cem\u003ephoR\u003c/em\u003e, \u003cem\u003ephoU\u003c/em\u003e, \u003cem\u003eRegX3\u003c/em\u003e) compared to low-P tundra, with the \u003cem\u003eugpBAEC\u003c/em\u003e transport system also showing increased abundance under high-P conditions. This suggests that high-P environments may favor plasmids that harbor genes capable of more efficient P uptake and regulation. Moreover, mine soils displayed a distinctive trend, with the \u003cem\u003eglpT\u003c/em\u003e gene, part of the \u003cem\u003egpl\u003c/em\u003e regulon involved in the transport of organic P sources, such as glycerol, G3P, and glycerophosphodiesters [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], being notably enriched relative to other soil types. These findings suggest that local adaptations occur in response to varying P sources and availability in different soil types. Despite differences in soil physicochemical properties, we found that plasmids consistently harbor a diverse array of genes involved in P acquisition, highlighting the ecological adaptability of microbial P cycling across environments. This aligns with previous findings that plasmids not only serve as vehicles for accessory traits but also as dynamic contributors to microbial adaptation in diverse ecological contexts [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. These findings highlight crucial implications for sustainable agriculture. In practice, harnessing plasmid-encoded P-solubilizing functions, for example through microbial inoculants or by managing indigenous P-solubilizing bacteria, can improve P use efficiency and reduce dependence on synthetic P fertilizers by unlocking native soil P pools [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Field studies have demonstrated that introducing P-solubilizing bacteria leads to greater P uptake and higher crop yields in P-deficient soils while allowing lower fertilizer application rates [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. By leveraging plasmid-borne P acquisition genes in soil microbiomes, farmers can enhance crop productivity and soil fertility in a sustainable manner, improving yields on P-deficient lands and preserving nonrenewable phosphate resources for the future.\u003c/p\u003e\u003cp\u003eFurthermore, the abundances of P transport and organic P mineralization genes were significantly more abundant in P-deficient soils than in high-P environments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This suggests that P-deficient conditions trigger the activation and may induce mobilization of P-acquisition systems, which are critical for microbial survival under nutrient-limiting conditions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In contrast, P regulation and inorganic P solubilization genes did not exhibit significant variation, suggesting that these processes may be less responsive to fluctuations in P availability at the plasmid level. Additionally, the cumulative analysis of P-acquisition gene abundance across all functional categories (Fig. S12) revealed that plasmids from P-deficient soils harbored a higher number of these genes compared to those from high-P environments. These findings emphasize the dynamic role of P availability in modulating the genetic composition of plasmids related to P acquisition, with the transport and organic mineralization processes being particularly responsive to low P levels.\u003c/p\u003e\u003cp\u003eThe taxonomic distribution of plasmids containing P-acquisition genes revealed consistent patterns in both PLSDB-derived and metagenomic analyses, with \u003cem\u003ePseudomonadota\u003c/em\u003e identified as the predominant phylum, suggesting a central role in the mobilization of P-related functions within soil ecosystems. Despite methodological differences, the convergence of taxonomic profiles supports the ecological relevance of this phylum and its associated lineages as key plasmid hosts. These findings are consistent with reports on P-solubilizing bacteria isolated from diverse soil environments [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan additionalcitationids=\"CR76 CR77\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. The presence of these genes in well-characterized genera (e.g., \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003eRhizobium\u003c/em\u003e) and in less-studied lineages suggests that the taxonomic range of plasmid hosts remains underexplored, potentially revealing novel microbial hosts involved in P-acquisition.\u003c/p\u003e\u003cp\u003eThese findings highlight the ecological relevance of plasmids in the mobilization of P-acquisition genes, emphasizing their role in microbial resilience under high- and low-P conditions. The maintenance of biogeochemical P cycling and the functional stability of microbial communities could be supported by plasmids' capacity to mobilize P-acquisition genes. Furthermore, the identification of P-acquisition genes in plasmids supports their potential use in plasmid-mediated bioaugmentation strategies, providing a promising approach for improving soil fertility in P-deficient or contaminated environments [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Moreover, HGT of symbiotic genes to native soil bacteria was demonstrated by recent genomic studies on rhizobial inoculants [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. This emphasizes the significance of tracking and controlling gene spread in order to preserve inoculant efficiency. These insights further support the relevance of mobile genetic elements, such as plasmids, in shaping microbial functionality in soil systems.\u003c/p\u003e\u003cp\u003eWhile interpreting these results, it is important to acknowledge that many of the sequences identified from metagenomic assemblies likely represent fragmented plasmid contigs rather than complete elements. While the consistent trends observed across datasets lend robustness to the main patterns described, the incomplete nature of plasmid sequences limits the ability to make precise predictions regarding plasmid mobility and genomic features. To overcome these limitations and enhance resolution, future studies should integrate long-read sequencing technologies, such as those offered by Oxford Nanopore Technologies or Pacific Biosciences, which significantly improve the quality of metagenomic assemblies, particularly in complex environments such as soils [\u003cspan additionalcitationids=\"CR82\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Moreover, when the primary objective is to characterize HGT, proximity ligation methods such as Hi-C sequencing are recommended, as they allow for the high-throughput linkage of MGEs with their bacterial hosts, even within complex environmental samples [\u003cspan additionalcitationids=\"CR85 CR86\" citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. As reviewed by Brito [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], a growing suite of molecular and computational tools, including Hi-C, OIL-PCR, and barcoded reporter constructs, now offers unprecedented resolution in assessing the ecology, frequency, and directionality of HGT within natural microbial communities. Incorporating such methods will be critical to fully understand the role of plasmid-borne AMGs in microbial adaptation, and advance the ecological interpretation of mobilome data in soil microbiomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates that plasmids act as diverse genetic reservoirs for P acquisition functions, harboring key genes involved in regulation, transport, inorganic solubilization, and organic mineralization. These findings underscore their significant role in microbial P cycling. Notably, mobilizable plasmids exhibit lower GC content compared to non-mobilizable ones, suggesting their adaptation to a variety of bacterial hosts, particularly in competitive environments such as soils. Additionally, plasmids from P-deficient soils showed higher abundances of transport and organic mineralization genes, suggesting an adaptive response to low P availability. Taxonomic analysis shows that \u003cem\u003ePseudomonadota\u003c/em\u003e and \u003cem\u003eBacillota\u003c/em\u003e dominate as plasmid hosts, with key P-acquisition genes present across these phyla. These results highlight the importance of plasmid-borne genes in biotechnological applications as well as microbial ecology. Understanding the diversity and mobility of P-acquisition genes will drive the development of more effective microbial inoculants and targeted bioaugmentation techniques, improving soil fertility and promoting sustainable agriculture. Future research should focus on experimentally verifying the regulation, expression, and ecological impact of these genes within microbial communities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study was financed by the Agencia Nacional de Investigaci\u0026oacute;n y Desarrollo (ANID) of Chilean government through ANID Grant Doctorado Nacional 2023-21230832 (P.B.); FONDECYT Regular Projects 1251164 (M.A.); 1241293 (P.J.B.) and 1230084 (M.L.M.). This study was also funded by Concurso Anillos de Investigaci\u0026oacute;n en \u0026Aacute;reas Tem\u0026aacute;ticas, ANID ATE220038 (P.J.B.) and by Universidad de La Frontera (DiUFRO), Proyectos de Investigaci\u0026oacute;n Vinculados a la Red Nexer No. DNX22-0009 (P.J.B.). B.E.D. was supported by the European Research Council (ERC) Consolidator grant 865694: DiversiPHI, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany\u0026rsquo;s Excellence Strategy \u0026ndash; EXC 2051 \u0026ndash; Project-ID 390713860, and the Alexander von Humboldt Foundation in the context of an Alexander von Humboldt-Professorship founded by German Federal Ministry of Education and Research.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePB, PJB, and MA conceived and designed the study. PB conducted investigation, data analyses, and prepared the original draft with support from PJB and MA. MG, IL, MLM, and BED improved the manuscript through suggestions and critical comments. MA, PJB, and MLM also contributed to project administration and funding acquisition. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors acknowledge the Scientific and Technological Bioresource Nucleus of Universidad de La Frontera (BIOREN\u0026ndash;UFRO) and Service Management Analytical Research and Training Center (SmartC-BIOREN). The authors also acknowledge the supercomputing infrastructure of Soroban (SATREPS MACH\u0026mdash;JPM/JSA1705), Centro de Modelaci\u0026oacute;n y Computaci\u0026oacute;n Cient\u0026iacute;fica, Universidad de La Frontera, Temuco.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWhite PJ, Hammond JP. Phosphorus nutrition of terrestrial plants. In: White PJ, Hammond JP, editors. The ecophysiology of plant-phosphorus interactions. 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Sci Data. 2025;12(1):367. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41597-025-04651-3\u003c/span\u003e\u003cspan address=\"10.1038/s41597-025-04651-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sigs","sideBox":"Learn more about [Environmental Microbiome](https://environmentalmicrobiome.biomedcentral.com)","snPcode":"40793","submissionUrl":"https://submission.nature.com/new-submission/40793/3","title":"Environmental Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Phosphorus acquisition genes, Mobile genetic elements, Metagenome, Auxiliary metabolic genes, Mobilome, Phosphorus cycling","lastPublishedDoi":"10.21203/rs.3.rs-7644682/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7644682/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePhosphorus (P) is a fundamental macronutrient for plant and microbial growth, but its availability in soils is often constrained by strong interactions with minerals and organic matter. While the role of bacteriophages in P cycling has gained attention, plasmids remain comparatively underexplored despite their central role in horizontal gene transfer. This study aimed to investigate the occurrence, diversity, and ecological relevance of plasmid-borne genes involved in P acquisition across soils with contrasting P availability.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eUsing curated plasmid databases and soil metagenomes from diverse biomes, we identified a broad repertoire of plasmid-encoded P-acquisition genes. These genes encompassed regulatory pathways, transport systems, organic P mineralization, and inorganic P solubilization. Regulatory and transporter genes were the most abundant categories, with \u003cem\u003ephoB\u003c/em\u003e, \u003cem\u003ephoP\u003c/em\u003e, and \u003cem\u003eugpC\u003c/em\u003e among the most frequently detected. Significant differences in gene abundance were observed between high- and low-P environments. High-P tundra environments favored plasmids with more regulatory and transport genes compared to low-P tundra, while P-deficient soils generally showed higher abundances of P transport and organic P mineralization genes. Taxonomic assignment revealed that \u003cem\u003ePseudomonadota\u003c/em\u003e were the predominant plasmid hosts, followed by \u003cem\u003eBacillota\u003c/em\u003e and \u003cem\u003eActinobacteriota\u003c/em\u003e, suggesting broad host diversity.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study underscores the ecological significance of plasmid-borne P-acquisition genes in P cycling and their potential in microbial adaptation to P-deficient soils. The dominance of \u003cem\u003ePseudomonadota\u003c/em\u003e and \u003cem\u003eBacillota\u003c/em\u003e as plasmid hosts highlights their central contribution to these processes. Overall, our findings expand the current understanding of plasmid involvement in soil fertility and point to their potential application in bioaugmentation strategies to enhance P use efficiency and promote sustainable agriculture.\u003c/p\u003e","manuscriptTitle":"Unraveling Plasmid Contributions to Phosphorus Acquisition in Soil Microbiomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-05 07:59:09","doi":"10.21203/rs.3.rs-7644682/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-26T07:20:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-25T02:24:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-08T00:47:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-02T23:04:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273528770227190115219719948374984104497","date":"2025-10-28T03:14:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233057094208621965690421052707962116392","date":"2025-10-26T14:11:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256124345327365200497884790358248660549","date":"2025-10-24T05:46:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110925418187168607962423578951992044361","date":"2025-10-24T05:39:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-24T04:39:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-30T11:10:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-19T09:11:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Microbiome","date":"2025-09-18T03:11:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sigs","sideBox":"Learn more about [Environmental Microbiome](https://environmentalmicrobiome.biomedcentral.com)","snPcode":"40793","submissionUrl":"https://submission.nature.com/new-submission/40793/3","title":"Environmental Microbiome","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"30356359-7607-4c3b-ab0a-871914bf8a37","owner":[],"postedDate":"November 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:14:51+00:00","versionOfRecord":{"articleIdentity":"rs-7644682","link":"https://doi.org/10.1186/s40793-026-00887-7","journal":{"identity":"environmental-microbiome","isVorOnly":false,"title":"Environmental Microbiome"},"publishedOn":"2026-04-06 15:57:32","publishedOnDateReadable":"April 6th, 2026"},"versionCreatedAt":"2025-11-05 07:59:09","video":"","vorDoi":"10.1186/s40793-026-00887-7","vorDoiUrl":"https://doi.org/10.1186/s40793-026-00887-7","workflowStages":[]},"version":"v1","identity":"rs-7644682","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7644682","identity":"rs-7644682","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}