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Article

Glyphosate-Induced Shifts in Edaphic Microbiota: A Comparative Study of Bacterial and Fungal Responses in Historical Milpa Soils

by
María Alejandra Ocaña-Ek
1,†,
Anell del Carmen García-Romero
1,†,
Oscar Omar Álvarez-Rivera
1,
Magnolia del Carmen Tzec-Gamboa
2,*,
Héctor Estrada-Medina
1 and
Miriam M. Ferrer
1,*
1
Departamento de Manejo y Conservación de Recursos Naturales Tropicales, Universidad Autónoma de Yucatán, Km. 15.5 Carretera Mérida-Xmatkuil, Mérida 97315, Mexico
2
Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, Km. 15.5 Carretera Mérida-Xmatkuil, Mérida 97315, Mexico
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Diversity 2025, 17(11), 803; https://doi.org/10.3390/d17110803
Submission received: 20 October 2025 / Revised: 15 November 2025 / Accepted: 15 November 2025 / Published: 20 November 2025
(This article belongs to the Special Issue Microbial Diversity in Changing Ecosystems: From Environmental Adaptation Mechanisms to Applications)
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Abstract

Glyphosate is the most widely used herbicide worldwide and in Mexico; however, its effects on soil microbiota in traditional agroecosystems remain unclear. We evaluated bacterial, archaeal, and fungal responses to commercial glyphosate in three representative karst soils of the Yucatán Peninsula (black Leptosol, red Leptosol, and red Cambisol) historically associated with the Mayan milpa system. The high-throughput sequencing of the 16S rRNA V4 and ITS1 regions was used to assess diversity patterns and differential abundance. Glyphosate application did not significantly alter alpha or beta diversity; however, fifteen taxa classified at the genus level exhibited shifts in relative abundance. Most bacterial taxa were depauperated in treated soils, whereas others, such as Arthrobacter, were enriched after application, indicating the presence of tolerant or resistant bacteria that may play a role in glyphosate degradation. Cordyceps, an entomopathogenic fungus, was depleted, indicating potential for natural pest control. The similarity of the core microbiota between samples with and without glyphosate application indicates that these communities are resilient. Overall, under short-term exposure, glyphosate induced compositional shifts in specific taxa without major effects on community structure but with potential implications for soil functionality and resilience in the Mayan milpa.

1. Introduction

The soil microbiota is the largest and most biodiverse fungal and bacterial reservoir on the planet [1]. It has important functions in biogeochemical cycles [2,3], soil formation, and biotic interactions [3,4,5]. In particular, soil microbiota and plant interactions are crucial, as they promote plant growth, development, and health in terrestrial ecosystems and cropping and forestry systems [6,7]. Soil management for conventional forestry and agricultural production entails practices such as fertilization and the application of herbicides, which, alone or in combination with other anthropogenic pressures, affect the diversity of the soil microbiota, promoting the proliferation of microorganisms with pathogenic potential [8]. On the other hand, the management of traditional agroecosystems, where ancestral practices remain largely unaltered, can sustain high biological and functional diversity of the microbiota, thereby contributing to both agricultural and forestry productivity [9]. The Mayan milpa, as an agroecological system that has deep cultural roots, entails forestry management with cycles of 5 to 35 years of forest recovery alternated with two or three cycles of polyculture [9,10]. Similarly to other traditional agroecosystems, this system faces challenges to its sustainability due to the adoption of conventional practices such as the use of herbicides [11]. Among these herbicides, glyphosate is the most widely used in the world [12] and in Mexico, where it is employed for corn, bean, and squash production, the main crops of Milpa [13].
Glyphosate (N-phosphonomethylglycine) is a compound that inhibits the EPSPS enzyme (5-Enolpyruvylshikimate-3-Phosphate Synthase) of the shikimate pathway, which is essential to the biosynthesis of aromatic amino acids (phenylalanine, tyrosine, and tryptophan) [12,14]. The inhibition of the shikimate pathway causes metabolic disruption in plants, bacteria, archaea, and fungi that present this enzyme [14]. EPSPS has mutations that affect sensitivity/resistance, with most microorganisms being sensitive to glyphosate (82% of archaea, 57% of bacteria, and 92% of fungi) [15]. On the other hand, it is known that molecular mechanisms such as the overproduction of the EPSPS enzyme, the biochemical degradation of glyphosate, a decrease in absorption, or an increase in the cell export of glyphosate could be associated with herbicide tolerance/resistance [16]. For this reason, the effects of glyphosate on the abundance of the soil microbiota can be differential, and after the application of herbicide to the soil, sensitive microorganisms may be depauperated or become extinct, while resistant/tolerant microorganisms may be enriched, with these changes potentially having an impact on biodiversity.
Due to the enormous biodiversity of the soil microbiota, performing analysis and classification using massive sequencing and bioinformatic tools is an approach that has greatly helped in microbiota characterization and the evaluation of the factors that affect its variability. The studies that have been carried out using massive parallel sequencing on field samples to evaluate the effects of glyphosate in soil mostly found no changes in the richness, diversity, and composition of the soil microbiota in rhizosphere and non-rhizosphere soils [17,18]. However, some studies in which the differential abundance of taxa has been evaluated suggest that enrichment/depauperation occurs in some bacterial taxa after the application of glyphosate in rhizosphere soil associated with three transgenic soybean lines [19,20,21] and transgenic maize [22]; similar findings have been reported for some bacteria and fungi in rhizosphere soil associated with oats [23] and sunflower [23] and in bulk soil (non-rhizosphere) associated with Spartina alterniflora [24], despite the fact that the richness indices and composition of the communities are not affected.
In this study, we conducted an exploratory evaluation of the effects of glyphosate (Velphosate®), applied at the manufacturer’s recommended doses, on the diversity of soil microbiota in three soil types widely distributed across the karst region of the Yucatán Peninsula—black Leptosol, red Leptosol, and red Cambisol [25]. The objective of this work was to identify archaeal, bacterial, and fungal taxa that were enriched or depauperated in the soil microbiota and to analyze alpha and beta diversity using the high-throughput sequencing of environmental DNA. We hypothesize that certain archaeal, bacterial, and/or fungal taxa may be differentially enriched or depauperated as a short-term effect of glyphosate application, while alpha and beta diversity indices may remain unaffected. These shifts in the differential abundance of taxa could be ecologically important if they involve key species within the soil microbiota. This study aims to contribute to the understanding of potential negative impacts of glyphosate on soil historically associated with traditional Mayan milpa agroecosystems, as an example of global threats to soil in traditional agroecosystems.

2. Materials and Methods

2.1. Study Sites

Soils were collected from two locations, Xmatkuil in September 2023 and Tahdziú in July 2023, with the prior consent of the landowners. Xmatkuil is located in the Yucatán’s municipality of Mérida (20°14′23″ N, 88°57′28″ W), while Tahdziú is found in the Yucatán’s municipality of Tahdziú (20°51′34″ N, 89°38′35″ W). The climate that characterizes these localities corresponds to the Aw0 category of the Köppen climate classification modified by García, which is characterized by concentrated rainfall in the summer (97.54%) and a dry season with low precipitation (2.46%), with an accumulated rainfall of 1000 to 1200 mm and average annual temperatures ranging between 24 and 28 °C.
The collected soil types exhibit contrasting characteristics, mainly in terms of depth, with Leptosols being shallow soils containing calcareous rock outcrops and Cambisols being deeper soils with less stoniness and the defined formation of at least two horizons. These soil types also differ in color according to the Munsell color system: reddish black for black Leptosol, dark reddish brown for red Leptosol, and dark red for red Cambisol. The soils were characterized by a pH ranging from neutral to slightly alkaline, and the electrical conductivity (<1 dS/m) in all soils indicates low salinity (Table 1). Black Leptosol and red Cambisol samples had higher organic carbon, nitrogen, phosphorus, and calcium contents, indicative of greater fertility compared with the red Leptosol samples, which had the lowest values in these parameters (Table 1). In contrast, red Leptosol had higher potassium content and lower sodium content (Table 1). In terms of texture, black Leptosol was classified as sandy loam and red Leptosol and red Cambisol as sandy clay loam (Table 1).

2.2. Sampling Design

The experiment followed an unbalanced design, because it only included plots which landowners accepted to work on with us. In Xmatkuil, black Leptosol and red Leptosol samples were collected from two different plots covered by secondary vegetation of tropical deciduous forest, approximately 25–30 years after the last cropping cycle. Red Cambisol samples were collected in Tahdziú from one plot with secondary vegetation of tropical deciduous forest, approximately 20–25 years after the last cropping cycle, and from three plots where secondary vegetation had recently been removed (slashing had been carried out one month earlier). In the latter, the landowner had applied glyphosate without our involvement, while in Xmatkuil, we were able to work directly with the landowner. Therefore, we prioritized the application of glyphosate in 6 different subplots of black Leptosol and red Leptosol, unbalancing the design, and selected two subplots without glyphosate application to collect control soil samples.
Soil subplots with glyphosate application were sprayed with Velfosato® (Velsimex, Ciudad de México, México, glyphosate isopropylamine, containing 41% glyphosate as the active ingredient) at doses ranging from 1.97 to 5.90 kg glyphosate/ha, a range that is the used by various producers in Yucatán. The corresponding glyphosate concentrations (w/w), considering the apparent soil density, ranged from 2.14 to 6.41 mg glyphosate/kg soil in black Leptosol, from 2.01 to 6.02 mg/kg in red Leptosol, and from 1.730 to 5.170 mg/kg in red Cambisol. After spraying, samples from the control plots and the glyphosate application plots and subplots were collected once at 30–60 days, in areas without associated vegetation to minimize the presence of rhizosphere soil. To represent spatial variability, 12 topsoil samples (0–5 cm depth) were taken for each soil type and treatment (with and without glyphosate application) to prepare composite samples. Subsamples were collected at equidistant points systematically distributed within each plot or subplot of 20 m × 20 m—eight along the inner edges (three on each side of the square) and four at the vertices of a central square of 1 m × 1 m—with the aim of obtaining a homogeneous representation of the plot.
To verify the presence or absence of glyphosate in the soil, 500 g of sieved composite soil samples (0–10 cm depth) was analyzed for glyphosate residues by using liquid chromatography–mass spectrometry (LC–MS) at Fertilab (Celaya, México). The measurement of soil before treatments and of controls during the experiment were null for glyphosate. The residual glyphosate concentrations in the subplots in which glyphosate had been applied ranged from 0.917 to 5.225 (median = 2.952) mg glyphosate/kg soil in the black Leptosol samples and from 0.132 to 3.929 (median = 0.518) mg/kg in the red Leptosol samples. Samples from Tahdziú could not be analyzed because the minimum amount of material required for analysis was not obtained on the field at collection time, and by the time we returned, the producer had applied a second dose of glyphosate.

2.3. DNA Isolation and Sequencing

DNA was isolated in two subsamples from the untreated topsoil composite samples of the three soil types, two subsamples from the glyphosate-treated composite samples of red Cambisol, and four subsamples from the glyphosate-treated composite samples of red and black Leptosols. Each subsample consisted of 125 mg of soil and was used to isolate DNA with a ZymoBIOMICS™ DNA Miniprep Kit (Zymo Research, Irvine, CA, USA). The concentration and purity of the DNA samples were evaluated using a nanodrop spectrophotometer (Thermo Scientific™, Whaltham, MA, USA), while DNA integrity was verified with sodium boric buffer electrophoresis in 0.8% agarose gels stained with Syber-safe (Thermo Scientific™, Whaltham, MA, USA) and visualized with Safe Imager 2.0 Blue light (Invitrogen, Carlsbad, CA, USA). Amplification, library construction, and DNA sequencing were performed at Novogene (Novogene, Shanghai, China) on the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA, USA) with the universal bacterial primers 515F (5′-GTGYCAGCMGCCGCGGGTAA-3′) and 907R (5′-CCGTCAATTCMTTRAGTTT-3′) for the V4–V5 regions of 16S rRNA and the fungal primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2aR (5′-GCTGCGTTCTTCATCGATGC-3′) for the amplification of the ITS1 region.

2.4. Bioinformatic Analyses

The pipeline in QIIME2 amplicon version 2024-9 [27] followed that reported by May-Mutul et al. [28] for quality analyses with Fastqc version 0.12.0 [29], denoising with dada2 version 2024.9 [30], and taxonomic assignation with the q2-feature classifier version 2024.9 [31]. The bacterial assignation was performed using the average 138.2 SSU-NR99 weighted Silva database [32,33] and the fungal assignation with Unite version 10.0 [32]. The diversity analyses were performed with R version 4.3.2 [34], using phyloseq package version 1.50.0 [35], as outlined in the pipeline (Supplementary File S1). ASVs were filtered to exclude unassigned, unclassified sequences and those assigned to Eukaryota based on 16SrRNA and to Viridiplantae and Protista based on the ITS datasets. The means of the observed ASVs and the Chao 1 and Shannon indices of treated and untreated samples and of samples from each of the soil types were compared using the Wilcoxon rank test and the Kruskal–Wallis test, respectively, on rarefied samples from the same depth. NMDS analyses, ANOSIM, and PermANOVA were performed on the Bray–Curtis distances using both raw counts and rarefied data to test for differences in the composition and structure of endophytic communities.
Relative abundance by phylum and genus was plotted for the major taxa, defined as those representing more than 1% of the total observed sequences. Differential abundance analyses with DESeq2 version 1.50.2 [36] were performed on the relative abundance of ASVs grouped at the genus and species levels, using glyphosate application as the contrast factor across all samples, rather than within each soil type due to the limited sample size per soil category. Only significantly enriched or depauperated taxa (Padj < 0.05) were included in the annotated heatmap. The differential abundance pattern associated with glyphosate application was recorded only when depauperated taxa were observed in at least two of the untreated samples and enriched taxa were observed in at least three of the glyphosate-treated samples.
To heuristically determine the complexity of the core microbiota, SPIEC-EASI (Sparse and Compositionally Robust Inference of Microbial Ecological Networks) version 1.0.7 [37] networks were obtained from four separate datasets. These datasets were obtained by first dividing the samples into glyphosate-treated and untreated groups for each 16SrRNA V4 region and ITS1 dataset. Then, to represent only the core microbiota, a combined abundance and occurrence approach was used [38], retaining ASVs with relative abundance higher than 0.1% that were present in at least half of the samples. The best sparsity parameter was obtained using Stability Approach to Regularization Selection (StARS) variability, and the minimum threshold was set to 0.3 for the four networks. The networks were visualized after being converted into igraph objects [39], grouping the ASVs at the genus level as depicted in the pipeline (Supplementary File S1). Given the small sample size of the datasets, no comparisons to evaluate glyphosate effects on network complexity, including degree, betweenness, transitivity, and clustering estimates obtained with igraph version 2.2.1 [39], were performed [40].

3. Results

A total of 6,776,256 raw sequences of the 16S rRNA V4 region and 6,220,622 sequences of the ITS1 region were obtained. After quality and chimera filtering, these were integrated into 30,689 bacterial and archaeal ASVs and 6515 fungal ASVs, with sample sizes ranging from 76,136 to 140,191 sequences and from 25,884 to 170,662 sequences, respectively. The filtering of unassigned ASVs and those not classified at least at the phylum level resulted in 29,256 ASVs for the bacteria and archaea domains and 4264 ASVs for fungi, which were further reduced to 28,465 ASVs and 3266 ASVs, respectively, after normalization to equal sample size. The rarefaction curves reached the asymptote for the number of ASVs that were included for each dataset, which indicates an adequate sampling size representative of the richness and diversity of the analyzed microbiota (Supplementary File S2 Figure S1).
The alpha diversity analyses for the microbiota of bacteria and archaea showed that the soil type had a significant effect on richness (p = 0.008 and p = 0.010, observed ASVs and Chao1 index) and diversity (p = 0.007, Shannon index) but that glyphosate application had no significant effect on the three indices (p > 0.05; Figure 1A). The mean richness, measured as the observed ASVs and Chao1 index, was higher in black Leptosol than in red Cambisol and red Leptosol, while diversity (Shannon index) in black Leptosol was only higher than in red Leptosol (Figure 1C).
Similarly, in the fungal microbiota, we also found significant effects of soil type on richness (p = 0.001 and p = 0.007, observed ASVs and Chao1 index) and diversity (p = 0.004 Shannon index) but no significant effects of glyphosate application on the three indices (p > 0.05; Figure 1B). The mean richness, measured as observed ASVs and Chao1 index, was higher in black Leptosol than in red Cambisol and red Leptosol, while diversity (Shannon index) in black Leptosol was only higher than in red Leptosol (Figure 1D). The diversity indices were similar between samples with and without glyphosate application within each soil type; only in red Cambisol, fungal ASVs were slightly richer under the glyphosate treatment (Supplementary File S2 Table S1).
The major taxa comprised 12 phyla for the microbiota of bacteria and archaea, which had similar patterns among all samples. The phyla Actinobacteriota, Proteobacteria, Firmicutes, and Acidobacteria together accounted for 72–83% of the sequences in all samples (Supplementary File S3 Figure S1). The other major phyla were Chloroflexi, Crenarchaeota, Entotheonellaeota, Gemmatimonadota, Myxococcota, RCP2-54, and Verrucomicrobiota, with relative abundance ranging from 1% to 5% of the sequences in the various samples. The minor genera (those with relative abundance lower than 1%) were the most prevalent across all samples, representing from 33% to 49% of all sequences for each sample (Supplementary File S3 Figure S2). Among the major taxa, 28 were classified at the genus level, 6 at the family level, and 2 at the order level. Rubrobacter, Bacillus, 67-14, and an unclassified Micrococcaceae showed relative abundance between 5% and 20% in all samples, irrespectively of soil type or glyphosate application.
In the fungal microbiota, the major taxa (those with relative abundance higher than 1%) comprised only four phyla, with a predominance of Ascomycota and Basidiomycota. The former accounted for more than 79% of the sequences in the black Leptosol samples and three out of four red Cambisol samples, whereas Basidiomycota represented more than 43% of the sequences in the remaining red Cambisol sample and all red Leptosol samples (Supplementary File S3 Figure S3). The phyla Mortierellomycota and Mucoromycota represented between 1.5% and 11% of the sequences only in the red Cambisol samples. Among the major taxa, 23 were classified at the genus level, 5 at the family level, 3 at the order level, 2 at the class level, and 2 at the phylum level (Supplementary File S3 Figure S4). Fusarium, Russula, Sebacina, Hygrocybe, Penicillium, an unclassified Nectriaceae, and an unclassified Ascomycota showed relative abundance higher than 20% in different samples. Distinct abundance patterns were identified according to the soil type: black Leptosol predominantly presented Aspergillus, Fusarium, Penicillium, and an unclassified Ascomycota; red Leptosol, Fusarium, Russula, and Sebacina; and red Cambisol, Hygrocybe in one sample and Fusarium together with an unclassified Nectriaceae in another, each accounting for more than 50% of the sequences.
In the NMDS plots, three distinct groups associated with the soil type were clearly observed for both the bacterial and archaeal microbiota (Figure 2A) and the fungal microbiota (Figure 2B). The stress values, 0.029 and 0.041, indicate excellent fit for the ordinations of bacteria and archaea and of fungi, respectively. Furthermore, the ANOSIM and PermANOVA analyses showed that for the bacterial and archaeal microbiota, the soil type had a significant effect on the Bray–Curtis distances (p = 0.04). Pairwise comparisons revealed significant differences in the average Bray–Curtis distances between black Leptosol and red Cambisol (Padj = 0.001), black Leptosol and red Leptosol (Padj = 0.001), and red Cambisol and red Leptosol (Padj = 0.002). Similarly, for the fungal microbiota, the soil type had a significant effect on the Bray–Curtis distances (p = 0.001), with significant pairwise differences for the same soil groups (Padj = 0.002 for all comparisons). In contrast, no effect of glyphosate application on the Bray–Curtis distances between treated and untreated samples was detected (p = 0.40, Padj = 0.17 for bacteria and archaea; p = 0.79, Padj = 0.30 for fungi).
In the DESeq2 differential abundance heatmap of the bacterial and archaeal microbiota, we observed significant differences in 27 taxa when the ASVs were grouped by genus and in 44 taxa when the ASVs were grouped by species. In total, 10 of the 27 taxa grouped at the genus level were recorded as depauperated, as they were significantly more abundant in at least two of the untreated samples, with 5 taxa being assigned to the genera Megamonas, Ilumatobacter, Pontibacter, Fusobacterium, and Microcoleus and the other 5 being classified at the family level or higher (Figure 3, Supplementary File S4 Table S1). On the other hand, 9 of the 27 taxa were enriched in at least three of the glyphosate-treated samples compared with untreated soil (Figure 3), and among them, 5 were assigned to the genera Paraprevotella, Romboutsia, Erysipelatoclostridium, Allobaculum, and Faecalibaculum, while the remaining 4 were classified at the family level or higher (Figure 3, Supplementary File S4 Table S2). Of the 44 taxa grouped at the species level, 8 were recorded as depauperated, being significantly more abundant in at least two of the untreated samples, with 1 of them being classified as Megamonas funiformis and the remaining 7 being classified at the genus level or higher (Supplementary File S4 Figure S1 and Table S3). Conversely, 11 of the 44 taxa were enriched in at least three of the glyphosate-treated samples compared with untreated soil (Supplementary File S4 Figure S1 and Table S4), with 4 of them being classified as Arthrobacter luteolus, Helicobacter hepaticus, Faecalibaculum rodentium, and Romboutsia ilealis and the remaining 7 being classified at the genus level or higher (Supplementary File S4 Figure S1 and Table S4).
In the DESeq2 differential abundance heatmap of the fungal microbiota, none of the taxa showed significant differences when the ASVs were grouped by genus, while 27 differed significantly when the ASVs were grouped by species (Supplementary File S4 Figure S2). Two taxa were recorded as depauperated, as they were originally more abundant in two or more of the untreated samples, including an unclassified Cordyceps and an unclassified Arthopyreniaceae (Supplementary File S4 Figure S2 and Table S5). In contrast, taxa enriched in more than three glyphosate-treated samples included Gliomastix murorum, Peroneutypa scoparia, an unclassified Paramicrothyrium, and an unclassified Tricholomataceae (Supplementary File S4 Figure S2 and Table S6).
The co-occurrence networks for the microbiota seemed equally complex whether they were constructed based on glyphosate-treated or untreated samples for either the archaeal and bacterial microbiota or the fungal microbiota (Figure 4). The number of ASVs in the core microbiota were similar in the glyphosate treatment networks, totaling 116 ASVs for the bacterial and archaeal microbiota and 79 ASVs for the fungal microbiota, compared with the 110 ASVs and 81ASVs found in the no-treatment networks, respectively. These ASVs were also grouped into a similar number of genera in the glyphosate treatment networks—39 bacterial and archaeal and 41 fungal genera—to the no-treatment networks—40 and 36 genera, respectively (Figure 4, Supplementary File S5 Table S1). The estimates of degree, betweenness, transitivity, or clustering between the networks were similar for those constructed from glyphosate-treated or untreated samples for either the archaeal and bacterial microbiota or the fungal microbiota (Table 2).

4. Discussion

Our results indicate that glyphosate can induce changes in the composition of bacterial, archaeal, and fungal microbiota, even though it does not significantly affect their overall structure (alpha and beta diversity), a result consistent with the evidence published in reviews about glyphosate effects. This is largely because the core microbiota of bacteria and archaea at the genus level is shared among the three soil types, and both these and other minor genera remain present after glyphosate application. Although fungal taxa varied across the soil types, it is possible that their diversity is differentially affected by glyphosate within each soil type, as suggested by the slight decrease in the observed ASVs for red Cambisol. Because fungal microbiota may be more susceptible to glyphosate application [24] and the number of samples in this study precludes robust statistical testing, further research is needed to clarify the effects of glyphosate across different soil types in the Yucatán karst. Nevertheless, the presence of different groups of saprophytes and large diversity indicate that soils maintain a diverse and healthy fungal microbiota after short-term glyphosate exposure. In previous studies carried out in the Yucatán karst, it has been reported that the phyla with the highest relative abundance in forests, home gardens, and agroforestry systems are Acidobacteria, Actinobacteria, Proteobacteria, and Firmicutes among bacteria and Ascomycota and Basidiomycota among fungi, although their proportions vary according to the type of soil [28,41,42,43], as also observed in the present study (Supplementary File S3 Figures S1 and S2). These results indicate that the microbial composition at the phylum level is consistent in the soils of the region and represents evidence of the existence of core microbiota.
In this study, the core microbiota defined by the major genera (Supplementary File S3 Figures S3 and S4) and those that have common ASVs at least in two samples co-occur in similarly complex networks between the samples in which glyphosate was applied and those without application. Consequently, interactions within the core microbiota across the soil types of the Yucatán karst may remain stable in the short-term, even after glyphosate application, provided it is used within the manufacturer’s recommended dose range. However, due to the small sample size of the datasets, no comparisons of degree, betweenness, transitivity, or clustering between networks were conducted. Further research including a larger number of samples is required to verify whether the network complexity of the core microbiota is indeed maintained in the short-term following glyphosate application at commercial doses and to determine the variability in microbiota interaction within the different types of Yucatán karst soils.
Consistently with previous studies, the effect of glyphosate on ASV richness, diversity (alpha diversity index), and community turnover (ASV dissimilarity) in the soil microbiota was not significant. Several studies have suggested that glyphosate applied at commercial doses does not exert a strong toxic effect on soil microbiota, either under controlled conditions [12] or in environmental samples [44,45,46]. Nevertheless, we detected compositional changes in 27 and 44 bacterial taxa grouped at the genus and species levels, respectively, and in 27 fungal taxa classified at the species level. Most of the compositional changes were detected when a taxon was more abundant in only one sample, suggesting that macro-environmental differences (sensu [4]) occurred among the analyzed plots. For instance, endophyte bacteria or fungi may have been present in plots where the host plant was located close to the collection site, while fecal-associated bacteria could have appeared in composite samples if the plots had been occasionally used by people as sanitary sites. Only a small fraction of the taxa recorded as enriched or depauperated were classified at the genus and species levels, a common result in metagenomic studies, often reflecting the uncultured nature or origin from environmental samples of these organisms (Supplementary File S4 Tables S1–S6). Because of this pattern, the large fraction of unclassified species observed in this study indicates that most of the species in which glyphosate may be inducing compositional shifts remain unknown (Supplementary File S4 Tables S1–S6). In the following paragraphs, only those taxa that exhibited glyphosate-induced compositional shifts and were classified at least at the genus level will be discussed. For ASVs grouped at the species level, we assume that the classification by genus is sufficiently reliable, since the recovery and accuracy at the genus level using QIIME2 and the SILVA database reach approximately 78.5% for soil samples [47]. Furthermore, when differential abundance analysis was performed at the genus level for bacteria and archaea, it was observed that most patterns were consistent with those obtained in the species-level analysis. The taxonomic identities should be validated using complementary approaches, such as microbiological culturing and molecular identification based on full-length 16S rRNA sequences and additional molecular markers.
Depauperated taxa after glyphosate application included the bacterial genera Megamonas, Ilumatobacter, Pontibacter, Fusobacterium, and Microcoleus and a taxon classified as Megamonas funiformis, while among the fungal taxa, only Cordyceps sp. was depauperated. The genus Megalomonas is characteristic of human feces [48], whereas Fusobacterium comprises species commonly associated with animal hosts, some of which have pathogenic potential in humans, although members of this genus can also occur freely in marine environments [49]. To our knowledge, neither of these genera has been previously reported in soils. The genus Ilumatobacter has been detected in agricultural soils [50,51] and in soils contaminated with heavy metals, indicating potential adaptation to nickel presence and a relevant role in biogeochemical cycles [52]. Pontibacter includes species found in various environments, predominantly in soil [53], and members of this genus have been studied for their ability to inhabit desert soils characterized by high radiation and low fertility [54], as well as for their diazotrophic potential [55], although they are susceptible to the herbicide atrazine [56]. Microcoleus is a cosmopolitan genus of cyanobacteria widely recognized for its role in biocrust formation in arid and semiarid soils [57]. Cordyceps is a fungal genus known for its potential use in biological control on account of its entomopathogenic properties [58,59,60]. If the functions of the depauperated taxa in Yucatán karst soil are similar to those previously reported for the corresponding genera, glyphosate may exert detrimental effects on processes such as biogeochemical cycling, nitrogen fixation, and pest-suppressive capacity. Therefore, in the short-term, glyphosate application may negatively affect soil fertility and the pest-free cultivation of crops. On the other hand, some bacteria that may be potential pathogens could also become depauperated following glyphosate application.
The observed enrichment patterns indicate the presence of microbiota that may be involved in the degradation of glyphosate. The residual glyphosate concentrations in red Leptosol and black Leptosol decreased substantially over time, from 4.32 mg kg−1 soil to 0.518 mg kg−1 (approximately 8-fold) and to 2.91 mg kg−1 (approximately 1.5-fold), respectively, indicating the potential presence of microorganisms capable of degrading glyphosate within the 30–60-day period considered in this study. Among the genera that were enriched following glyphosate application, Arthrobacter is a taxon of major interest due to previous reports of glyphosate degradation by congeneric species [61] or bacterial consortia [62]. This taxon was more enriched in black Leptosol (Supplementary File S4 Figure S1), indicating that glyphosate and soil type may have a differential growth-promoting effect on Arthrobacter. However, most of the enriched genera were microaerophilic or anaerobic bacteria, including Helicobacter, a mouse enterohepatic pathogen [63]; Faecalibaculum, isolated from the mouse gastrointestinal tract [64]; and Romboutsia, found in the rat gastrointestinal tract [65]. Other species of the enriched genera have also been identified in gut microbiome and human feces: Paraprevotella [66], Romboutsia [67], Erysipelatoclostridium [68], Allobaculum [69], and Faecalibaculum [70]. None of these taxa have been previously reported in soils. A plausible explanation for their enrichment could be that rodents may be attracted by plots treated with glyphosate, where these animals may defecate, introducing their gut-associated microbiota. However, studies evaluating contaminant exposure in wildlife have found that rodents and other small mammals do not exhibit a preference for farms under conventional versus organic management [71]. Interestingly, the enrichment patterns of these species resemble those of the bacterial cluster that included Arthrobacter (Figure 3). This similarity in the enrichment pattern suggests that these taxa may be capable of using glyphosate as a carbon source and potentially degrading the compound under anaerobic conditions, as previously proposed for Pseudomonas and Clostridium [72]. On the other hand, only two fungal species were enriched in more than two glyphosate-treated samples: Gliomastix murorum and Peroneutypa scoparia (Supplementary File S4 Figure S2. The first is an endophyte species [73] producing gibberellin, promoting plant growth, as evidenced by in vitro testing [74], and producing other metabolites with potential antimicrobial properties [75]. Peroneutypa scoparia is a cosmopolitan endophytic species that can switch to a saprophytic lifestyle when plant debris falls to the ground [76] or become pathogenic and cause canker disease in some crops, such as fig and vines [77]. The enrichment patterns observed in bacterial and fungal species following glyphosate application indicate that a bacterial consortium may function as a glyphosate-degrading community, contributing to the resilience of the soil microbiota.
In addition, some species of the core fungal microbiota may also have a key role in glyphosate degradation. Previous reports have shown that species of the genera Aspergillus, Penicillium, and Trichoderma possess the metabolic capacity to degrade glyphosate by utilizing it as a source of carbon or phosphorus [78]. Furthermore, isolates of species of three genera from Amazonian soils were able to degrade glyphosate [79]. Therefore, assessing the potential of the core and enriched species in this study as glyphosate degraders in the karst soils of Yucatán, as well as the differences in their degradation kinetics across the three soil types (black Leptosol, red Leptosol, and red Cambisol), is essential for evaluating their potential application in bioremediation programs. Further comprehensive studies, such as those proposed by Singh et al. [80], are required to better understand the functional roles and degradation mechanisms of these organisms. In the soils analyzed, glyphosate-degrading species appear to be particularly relevant in red Cambisol and red Leptosol, as these soils contain higher clay proportions, which can enhance glyphosate retention through adsorption processes. A further characterization of microorganisms capable of glyphosate degradation in these three soil types is important for assessing their contribution to soil resilience under herbicide exposure and exploring their biotechnological potential. Comprehensive studies, such as those proposed by Singh et al. [80] are required to deepen our understanding of the functional roles of the soil microbiota and the mechanisms underlying glyphosate degradation in these karst ecosystems.

5. Conclusions

In this study, short-term glyphosate application did not affect the alpha or beta diversity of soil microbiota. Fifteen bacterial and fungal taxa were found to be either enriched or depauperated after glyphosate application. Some species of the depauperated genera play a crucial role in biogeochemical cycles, nitrogen fixation, and biological control. Therefore, in the short-term, glyphosate application may negatively affect soil fertility and the pest-free cultivation of crops. These findings underscore the relevance of using differential abundance to detect subtle compositional shifts that may not be reflected in diversity metrics. Some genera that were enriched or form part of the core microbiota may be tolerant or resistant microorganisms that play a role in glyphosate degradation. The core microbiota observed after glyphosate application exhibited network structures that appeared to be as complex as those observed in soils where glyphosate had not been applied. It is plausible that bacterial consortia capable of degrading glyphosate play a key role in the resilience of soil microbiota to agricultural practices outside the traditional Mayan milpa system. There is a need for more detailed and long-term studies to better understand the implications for soil functionality and the sustainability of traditional agroecosystems under glyphosate use.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d17110803/s1, File S1: Pipeline for bioinformatic diversity and network analyses. File S2: Figure S1: Rarefaction curves for the observed ASVs and Shannon index of the bacteria and archaea (A) and fungal (B) microbiota for samples from three soil types with and without glyphosate application. Table S1: Diversity indices of observed ASVs and Shannon index of the bacteria and archaea, and fungal microbiota; mean per sample from three soil types with and without glyphosate application. File S3: Figures S1–S4: Relative abundance of the major taxa (relative abundance > 1% of the total samples) classified at the phylum level for the microbiota of bacteria and archaea (Figure S1) and fungi (Figure S2) and those classified at the genus level for the microbiota of bacteria and archaea (Figure S3) and fungi (Figure S4) among samples from three soil types and between samples with and without glyphosate application. File S4: Figures S1 and S2: DESeq2 heatmap of 44 taxa of bacterial and archaeal microbiota (Figure S1) and of 27 taxa of fungal microbiota (Figure S2) grouped at species level showing significant differences according to glyphosate application. Tables S1–S6: Taxonomic classification of depauperated (Tables S1, S3, and S5) and enriched (Tables S2, S4, and S6) taxa grouped at genus (Tables S1 and S2) and species (Tables S3–S6) levels for bacterial and archaeal (Tables S1–S4) and fungal (Tables S5 and S6) microbiota, identified in differential abundance analysis contrasting glyphosate-treated and untreated samples. Table S7: Taxonomic classification of undefined pattern taxa grouped at species level for bacterial, archaeal, and fungal microbiota, identified in differential abundance analysis contrasting glyphosate-treated and untreated samples. File S5: Table S1: Taxonomic classification of ASVs for the core microbiota of bacteria and archaea, and fungi. The ASVs from glyphosate-treated or untreated samples are presented in different sections.

Author Contributions

Conceptualization, M.M.F., H.E.-M., and M.d.C.T.-G.; methodology, M.M.F., H.E.-M., and M.d.C.T.-G.; validation, M.M.F.; formal analysis, M.M.F., A.d.C.G.-R., and M.A.O.-E.; investigation, A.d.C.G.-R., M.A.O.-E., M.M.F., H.E.-M., O.O.Á.-R., and M.d.C.T.-G.; resources, H.E.-M. and M.d.C.T.-G.; data curation, O.O.Á.-R. and M.M.F.; writing—original draft preparation, M.M.F. and O.O.Á.-R.; writing—review and editing, A.d.C.G.-R., M.A.O.-E., M.M.F., H.E.-M., O.O.Á.-R., and M.d.C.T.-G.; visualization, M.M.F.; supervision, M.M.F., H.E.-M., and M.d.C.T.-G.; project administration, H.E.-M. and M.d.C.T.-G.; funding acquisition, H.E.-M., M.M.F., and M.d.C.T.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research study was funded by Consejo Nacional de Humanidades, Ciencias y Tecnologías, México (CONAHCyT, now SECIHTI—Secretaría de Ciencia, Humanidades, Tecnología e Innovación), under grants number 321133 and CBF2023-2024/2907.

Institutional Review Board Statement

Not applicable, as this study did not involve humans or animals.

Data Availability Statement

Sequences for the 16SrRNA V4 and ITS1 regions were stored under GenBank BioProject accession number PRJNA1347131.

Acknowledgments

The authors thank Mariana López-Díaz and Victoriano Valle for allowing soil sample collection on their plots, Sofía Salazar-Coral for her assistance in designing the graphical abstract and compiling information for the Supplementary Materials, and Grelty Pech-Puch for assistance with soil sample preparation for physicochemical and glyphosate analyses.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
NMDSNon-metric multidimensional scaling
ASVAmplicon Sequence Variant
ANOSIMANalysis Of SIMilarities
PermANOVAPermutational Multivariate Analysis of Variance

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Diversity 17 00803 g001
Figure 1. Alpha diversity indices (observed ASVs, Chao1 for ASV richness, and Shannon index for ASV diversity) estimated in bacterial and archaeal (A,C) and fungal (B,D) and between glyphosate-treated and untreated soil samples (A,B) and microbiota for comparisons among three soil types (B,C).
Figure 1. Alpha diversity indices (observed ASVs, Chao1 for ASV richness, and Shannon index for ASV diversity) estimated in bacterial and archaeal (A,C) and fungal (B,D) and between glyphosate-treated and untreated soil samples (A,B) and microbiota for comparisons among three soil types (B,C).
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Figure 2. NMDS analyses for Bray–Curtis dissimilarity estimated for the bacterial and archaeal (A) and fungal (B) microbiota among samples of three soil types and between glyphosate-treated and untreated samples.
Figure 2. NMDS analyses for Bray–Curtis dissimilarity estimated for the bacterial and archaeal (A) and fungal (B) microbiota among samples of three soil types and between glyphosate-treated and untreated samples.
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Figure 3. DESeq2 heatmap of microbiota of bacteria and archaea including 27 taxa grouped at genus level showing significant differences according to glyphosate application.
Figure 3. DESeq2 heatmap of microbiota of bacteria and archaea including 27 taxa grouped at genus level showing significant differences according to glyphosate application.
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Figure 4. Co-occurrence networks for bacterial and archaeal (A,B) and fungal (C,D) microbiota for samples with (A,C) and without (B,D) glyphosate application from three different soil types in the Yucatán karst.
Figure 4. Co-occurrence networks for bacterial and archaeal (A,B) and fungal (C,D) microbiota for samples with (A,C) and without (B,D) glyphosate application from three different soil types in the Yucatán karst.
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Table 1. Physicochemical properties of the three soil types (BL = black Leptosol, RL = red Leptosol, and RC = red Cambisol) from the Yucatán karst in Mexico. Protocols for estimation followed those depicted in Estrada et al.’s study [26].
Table 1. Physicochemical properties of the three soil types (BL = black Leptosol, RL = red Leptosol, and RC = red Cambisol) from the Yucatán karst in Mexico. Protocols for estimation followed those depicted in Estrada et al.’s study [26].
Soil TypepHECOCNPNaKCaADSandSiltClay
(dS/m)(%)(mg/kg)(cmol/kg)g/cm3(%)
BL7.510.502.790.1620.170.130.0940.680.9267.4816.0016.52
RL7.240.521.500.132.370.150.1119.230.9845.4824.0030.52
RC6.920.302.860.398.300.030.256.821.1437.8216.1046.09
EC = electric conductivity, OC = organic carbon, and AD = apparent density.
Table 2. Estimates of complexity of co-occurrence networks of archaeal and bacterial, and fungal microbiota for samples with and without glyphosate treatment form three different soil types in the Yucatán karst.
Table 2. Estimates of complexity of co-occurrence networks of archaeal and bacterial, and fungal microbiota for samples with and without glyphosate treatment form three different soil types in the Yucatán karst.
GroupSamplesDegreeBetweennessLocal TransitivityGlobal TransitivityModularity (Greedy)
ABAPP0.01018.1210.7520.7510.109
ABNAP0.00913.3550.7890.7890.087
FUAPP0.01315.4120.7540.7570.124
FUNAP0.0148.9330.7910.7880.122
AB = archaea and bacteria, FU = fungi, APP = glyphosate application, and NAP = no glyphosate application.
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Ocaña-Ek, M.A.; García-Romero, A.d.C.; Álvarez-Rivera, O.O.; Tzec-Gamboa, M.d.C.; Estrada-Medina, H.; Ferrer, M.M. Glyphosate-Induced Shifts in Edaphic Microbiota: A Comparative Study of Bacterial and Fungal Responses in Historical Milpa Soils. Diversity 2025, 17, 803. https://doi.org/10.3390/d17110803

AMA Style

Ocaña-Ek MA, García-Romero AdC, Álvarez-Rivera OO, Tzec-Gamboa MdC, Estrada-Medina H, Ferrer MM. Glyphosate-Induced Shifts in Edaphic Microbiota: A Comparative Study of Bacterial and Fungal Responses in Historical Milpa Soils. Diversity. 2025; 17(11):803. https://doi.org/10.3390/d17110803

Chicago/Turabian Style

Ocaña-Ek, María Alejandra, Anell del Carmen García-Romero, Oscar Omar Álvarez-Rivera, Magnolia del Carmen Tzec-Gamboa, Héctor Estrada-Medina, and Miriam M. Ferrer. 2025. "Glyphosate-Induced Shifts in Edaphic Microbiota: A Comparative Study of Bacterial and Fungal Responses in Historical Milpa Soils" Diversity 17, no. 11: 803. https://doi.org/10.3390/d17110803

APA Style

Ocaña-Ek, M. A., García-Romero, A. d. C., Álvarez-Rivera, O. O., Tzec-Gamboa, M. d. C., Estrada-Medina, H., & Ferrer, M. M. (2025). Glyphosate-Induced Shifts in Edaphic Microbiota: A Comparative Study of Bacterial and Fungal Responses in Historical Milpa Soils. Diversity, 17(11), 803. https://doi.org/10.3390/d17110803

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