Abstract
Soil microbial communities in landfills play a crucial in waste degradation and pollution mitigation, yet their diversity and functionality in many regions remain underexplored. This study used shotgun metagenomic sequencing to characterise microbial communities in soil samples from the Buffelsdraai landfill waste site (samples: XM-AA, XM-BB, XM-CC, XM-DD). We identified dominant taxa, namely, Actinobacteria, Acidobacteria, and Bacteroidetes, and evaluated their taxonomic diversity and metabolic potential. Diversity indices revealed high richness in XM-AA (Shannon: 4.188), suggesting the potential of a strong waste-processing capacity, while XM-BB showed reduced diversity (Shannon: 1.453), likely due to contaminant stress (eg, nickel, cobalt). XM-CC and XM-DD exhibited moderate diversity (Shannon: 2.671-2.942) with Actinobacteria dominance (99%), suggesting adaptation to landfill conditions. Functional profiling via Kyoto Encyclopaedia of Genes and Genomes pathways highlighted carbohydrate and lipid metabolism, alongside xenobiotic biodegradation, pointing to potential for organic waste and pollutant breakdown. Physicochemical analyses detected elevated sodium (22 640 mg/kg in cell 1) and trace metals (eg, Ni: 0.1469 mg/kg), influencing microbial composition. These results emphasise microbial diversity’s role in landfill soil functionality and position Actinobacteria as a bioremediation target for degrading leachate organics and immobilising metals. This study provides a baseline profile of microbial taxonomic and functional responses to landfill-associated environmental stressors in South Africa. The findings highlight the ecological roles of landfill microbial communities and their potential relevance for future bioremediation research.
Introduction
Investigating novel microorganisms and characterising their functions are key objectives in the fields of microbiology and biotechnology.1,2 Soil has presented a highly intricate and demanding environment for microbiologists and biochemists for decades. Traditional microbiology techniques have been limited in capturing the diversity of unculturable microbes; however, metagenomic approaches have substantially advanced the exploration and characterization of these communities.3-5 Metagenomics studies the collective genetic material recovered directly from environmental samples, enabling the analysis of entire microbial communities without the need for cultivation. This approach has transformed microbial ecology by allowing the discovery of novel genes, the classification of previously uncharacterised microorganisms, and the identification of species and functional traits present in a given environment.3,6,7 Existing classification approaches use factors such as oligonucleotide frequency to classify these sequences. Efficiently processing and analysing the large quantity of data produced by bio-sequencing technology is essential for uncovering the properties of microbial communities. 8 Classification techniques can be divided into 2 primary categories: those that rely on marker genes like 16S rRNA and those that use whole-genome sequencing. This is important for a range of applications, including analysing the microbiome in soil, diagnosing diseases, and monitoring outbreaks. 9 Soil microbial communities vary depending on the environmental conditions found in the sampling area. 3 Microorganisms thrive when their surroundings are undisturbed and free from contamination; thus, municipal landfills exemplify human-made environments that support a diverse range of microbial communities. 10 Therefore, the ongoing practice of waste disposal has not fully resolved the issue of introducing a mixture of various chemicals into the soil through leachate.11,12 In addition, studies have shown that the leachate contains significant levels of harmful substances such as heavy metals and organic matter. These contaminants pose a threat to the environment and have negative implications for public health. Moreover, this contamination has a slow degradation process and can leave behind harmful residue that persists for extended periods of time. 13 Microorganisms found in these environments play a crucial role in biogeochemical cycles, facilitating the breakdown of various carbon sources, including pollutants.10,13 Understanding and effectively managing these processes can have numerous applications, such as in landfills and leachate treatment. 14 In recent studies, researchers have discovered valuable information about the functional interactions within the microbial community at landfill sites. These findings shed light on the remarkable ability of microbes to break down and utilise both organic and inorganic chemicals, enabling them to thrive in challenging environments.5,15,16 These potential applications of these microbes and genes include bioremediation, biodegradation and the isolation of potential enzymes for industrial use. Thus, we hypothesise that local physicochemical stressors, such as elevated salinity and trace metal contamination, exert strong selective pressures on landfill soil microbiomes, shaping both their community structure and functional potential.
Materials and Methods
Site description
The Buffelsdraai Landfill Site, approximately 8 km west of Verulam, Durban, has operated under the eThekwini Municipality’s jurisdiction as a sanctioned waste disposal site for over 15 years. It represents the largest regional landfill managed by the eThekwini Municipality’s Durban Solid Waste Department, with an active waste disposal area covering 116.2 hectares. The surrounding buffer zone, encompassing 787 hectares, includes 580 hectares that have been afforested with indigenous tree species. The remaining areas consist of grasslands, woodlands, wetlands, and riparian zones that are subject to ongoing restoration and conservation efforts. To mitigate operational impacts such as odour, noise, and visual disturbance, additional trees have been strategically planted around the landfill perimeter, creating a protective barrier that also functions as a firebreak. A dense planting of thorny trees forms a ‘living fence’ along the buffer boundary, effectively preventing unauthorised entry by vehicles, individuals, and livestock. Despite its extensive operational history, the microbial diversity within Buffelsdraai has been minimally explored, presenting a novel opportunity to investigate microbial communities with potential industrial applications.
Sampling
Soil samples were collected from Buffelsdraai landfill (29.628686°S, 30.992008°E), Durban, South Africa, the region’s primary municipal waste disposal site. To capture variability between operational zones, 2 active landfill cells were selected for sampling. From each cell, 2 sampling points were chosen, yielding 4 composite samples: XM-AA and XM-BB from cell 1, and XM-CC and XM-DD from cell 2. At each sampling point, 3 subsamples were collected within a 5 m radius at a depth of 20 cm and pooled into a composite sample. This pooling approach was used to reduce small-scale variability and generate a representative profile of microbial communities at the cell level. While pooling may reduce the ability to detect fine-scale heterogeneity, it provides a robust overview of dominant microbial taxa and functions across landfill zones.17,18 Four samples (XM-AA and XM-BB from cell 1; XM-CC and XM-DD from cell 2) were obtained at 20 cm depth, with 3 subsamples per site pooled into 20 L sterile buckets. Samples were transported to the University of KwaZulu-Natal (Westville Campus). Upon arrival, they were stored at −20°C to preserve their integrity. To maintain sample quality, the collected soil was thoroughly mixed with a storage medium prior to analysis.
Physicochemical analysis
Organic matter content in soil samples
The content of organic matter was determined by the loss on ignition method. 19 Soil samples were air-dried and sieved through a 2 mm stainless sieve to remove gravel-sized particles. The samples were weighed, oven dried at 105°C overnight, cooled in a desiccator, and weighed before combustion at 550°C for 4 hours in a muffle furnace (AAF-1100, Carbolite-Gero, USA). After combustion, the samples were cooled in a desiccator and weighed to determine the weight loss difference. An estimation of soil organic matter was calculated using the following equation:
Grain size analysis
The grain size was obtained using a method of sequential sediment-sieving. 20 The soil samples were oven-dried at 105°C overnight. Hydrogen peroxide (30%) was added to each sample to completely remove the organic matter, following the addition of Calgon (1%) as a dispersing agent to segregate grain sizes. Each dried sample was then homogenised individually and sieved in an analytical sieve shaker (AS 200, Retsch GmbH, Germany) through 2, 1, 0.5, 0.25, 0.125, and 0.053 mm to assess the grain size fractions.
Heavy metals analysis in soil
Heavy metals were quantified by acid digestion. 21 Soil (0.5 g, <63 µm) was digested with HNO3:HF: H2O3 (3:1:1) at 180°C for 3 hours, filtered (0.45 µm), and diluted to 100 mL with 2% HNO3. Concentrations (mg/kg dry soil) were analysed using ICP-MS (NexION 300, PerkinElmer, USA), calibrated with multi-element standards (R2 > 0.999).
DNA extraction
Soil samples were subjected to filtration using Whatman Filter Paper No. 1 with a pore size of 0.45 µM. Subsequently, 200 µL of phosphate-buffered saline (PBS) and 750 µL of lysis solution were added to the residue and mixed thoroughly. Metagenomic DNA was extracted from the samples using ZR fungal/bacterial DNA Kit (Zymo Research, California, USA), as per the instruction manual. The DNA was eluted in 30 µL of ultrapure Milli-Q water (Millipore, Bedford, MA, USA). The integrity of the extracted genomic DNA was assessed by gel electrophoresis on a 0.8% agarose gel. The DNA concentration, quality, and purity were measured using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), where a 260/280 nm absorbance ratio of approximately 1.8 was considered indicative of pure DNA.
Sequencing of genomic DNA
Sequencing performed at Inqaba Biotechnical Industries, South Africa, a commercial NGS service provider. Libraries were prepared by fragmenting DNA to ~300 bp, followed by end-repair and adapter ligation using NEBNext Ultra II (llumina, San Diego, CA, USA). Sequencing was performed on Illumina MiSeq, v3, 600-cycle kit, (llumina, San Diego, CA, USA), generating 2 × 300 bp reads (~20 Mb/sample, ~33,000 reads). Reads were quality-filtered (Q > 20, Trimmomatic v0.39), 22 assembled into contigs (MEGAHIT v1.2.9), 23 and annotated against NCBI-nr (DIAMOND v2.0.15, e-value 1e−5). 24 Taxonomy and functions were assigned using MEGAN v6.21.7 25 with Kyoto Encyclopaedia of Genes and Genomes (KEGG), eggNOG, and SEED databases. Diversity indices (Shannon, Simpson) were computed from rarefied data (30 000 reads/sample). Raw reads were quality-filtered using Trimmomatic v0.39 with a Phred score cut-off of Q > 20. 22 Filtered reads were assembled into contigs using MEGAHIT v1.2.9 with default k-mer settings. 23 Taxonomic and functional annotation was performed using DIAMOND v2.0.15 in blastx mode, 24 against the NCBI-nr protein database, with an e-value cut-off of 1e-5, a minimum alignment length of 30 amino acids, and a sequence identity threshold of 70%. These thresholds were selected to balance sensitivity and specificity in functional assignment, in line with established metagenomic workflows.25,26 Resulting alignments were imported into MEGAN v6.21.7, 25 for taxonomic and functional binning using the Lowest Common Ancestor (LCA) algorithm with default parameters.
For functional profiling, we used both the KEGG and SEED databases. KEGG was selected for its well-curated metabolic and xenobiotic degradation pathways, relevant to landfill microbial ecology, 27 while SEED was included for its broader coverage of environmental and ecological functions. 28 This dual-database approach allowed comprehensive annotation of microbial community functional potential.
Diversity indices (Shannon, Simpson) were computed from rarefied datasets (30 000 reads/sample) to ensure comparability across samples with different sequencing depths. All analyses were conducted using consistent software versions and parameters across samples. Metagenomic DNA was extracted from 0.5 g soil using the ZR Fungal/Bacterial DNA Kit (Zymo Research) following manufacturer protocols. Soil was filtered (0.45 µm Whatman No. 1), mixed with 200 µL PBS and 750 µL lysis solution, and eluted in 30 µL ultrapure water. DNA purity (A260/A280 ≈ 1.8) was confirmed with a NanoDrop ND-1000.
Characterization of microbial community composition
Metagenomic workflow
The abundant and rare phyla were subjected to phylogenetic analysis using Diamond (http://www.diamondsearch.org/) and Megan (http://megan.husonlab.org/). The relative abundances of all samples were shown as bar charts, representing the number of reads per genus for each sample. Functional profiling of each sample was performed using InterPro2GO, eggnog, SEED, and KEGG databases. For microbiome sequence analysis, sequences were first aligned against a reference database of annotated protein sequences (NCBI-nr) using DIAMOND. Taxonomic and functional binning of the sequences were then performed based on the resulting alignments. Both short and long reads, including assembled contigs, were aligned using DIAMOND. Subsequently, taxonomic and functional binning, along with interactive exploration and analysis, were executed using MEGAN. 25
Data availability
The metagenome sequence is available under NCBI-SRA (Sequence Read Archive) with the accession number: PRJNA1270993. The SRA records will be accessible with the following link after the indicated release date: https://www.ncbi.nlm.nih.gov/sra/PRJNA1270993.
Results
Physiochemical analysis of the sampling site
Table 1 describes soil samples collected from the landfill, processed through acid digestion using a mixture of nitric acid, hydrofluoric acid, and hydrogen peroxide in a 3:1:1 ratio. Digestion was conducted on a hot plate at 180°C for 3 hours. Following digestion, samples were filtered with a 0.45-micron filter and diluted with 2% nitric acid to a final volume of 100 mL in volumetric flasks, thereby preserving all target metals. The resulting solutions underwent analysis using a NexION 300 ICP-MS. Calibration was conducted across a range of concentrations: Trace elements were calibrated at 0.001, 0.02, and 0.05 ppm, while major elements were calibrated at 0.1, 1, and 10 ppm.
Notably, sodium concentrations in cell 1 (22 640 mg/kg) and cell 2 (8571 mg/kg) were substantially high, suggesting potential salinisation. Potassium levels were also elevated, with cell 1 at 28 190 mg/kg and cell 2 at 22 260 mg/kg, indicating a possible nutrient imbalance. Elevated calcium levels in cell 1 (11 405 mg/kg) compared with cell 2 (2294 mg/kg) may influence soil pH and nutrient availability. Magnesium concentrations, high in cell 1 (2101 mg/kg) but lower in cell 2 (159 mg/kg), further contribute to salinity risks. For trace elements, lead levels were detected below permissible limits, with 0.0185 mg/kg in cell 1 and a higher concentration of 3.8820 mg/kg in cell 2, remaining within acceptable thresholds.
Arsenic levels were low and consistent (0.0280 mg/kg in cell 1 and 0.0290 mg/kg in cell 2), reflecting minimal contamination. Barium concentrations were low across both cells (0.0550 mg/kg in cell 1 and 0.0560 mg/kg in cell 2), suggesting no significant environmental impact. Cadmium was detected well below permissible limits (0.0004 mg/kg in cell 1 and 0.0003 mg/kg in cell 2), which is favourable given cadmium’s toxicity. However, cobalt concentrations exceeded permissible limits in both cells (0.0102 mg/kg in cell 1 and 0.0101 mg/kg in cell 2), indicating potential contamination concerns. Chromium levels approached permissible limits (0.1010 mg/kg in cell 1 and 0.1020 mg/kg in cell 2), suggesting the need for continued monitoring. Copper levels remained within acceptable limits (0.0237 mg/kg in cell 1 and 0.0242 mg/kg in cell 2). Iron and manganese concentrations were typical, indicating no significant environmental impact, while molybdenum levels were low, supporting potential benefits for plant growth. Nickel concentrations exceeded permissible limits (0.1469 mg/kg in cell 1 and 0.1337 mg/kg in cell 2), raising toxicity concerns. The substantial concentrations of sodium, potassium, calcium, magnesium, cobalt, and nickel in these samples underscore significant environmental and public health concerns. The application of ICP-MS proved effective for quantifying these elements, underscoring the importance of ongoing monitoring and potential remediation to address soil contamination and mitigate its environmental impacts.
Taxonomic composition, alpha diversity, and functional potential of landfill microbial communities
The microbial community analysis of Buffelsdraai landfill soil samples reveals essential insights into the ecological structure and functionality of the soil, informing both environmental health assessment and potential bioremediation strategies. High-throughput sequencing identified Actinobacteria as the predominant phylum, followed by Acidobacteria and Bacteroidetes, reflecting critical components of microbial activity in landfill-impacted soils. The extreme dominance of Actinobacteria observed in samples XM-CC and XM-DD (up to 99%) is striking and likely reflects genuine ecological selection rather than a solely methodological artefact. The Buffelsdraai landfill soils contained elevated concentrations of sodium, cobalt, and nickel (Table 1), conditions under which Actinobacteria are well documented to thrive due to their resilience to osmotic and metal stress, as well as their ability to degrade complex organic substrates. Similar dominance patterns have been reported in other contaminated and anthropogenically affected soils, where Actinobacteria function as key decomposers and pollutant-tolerant taxa.10,30 Nonetheless, potential methodological influences cannot be excluded. DNA extraction protocols, such as the ZR Fungal/Bacterial Kit used here, may favour Gram-positive taxa because of their robust cell walls, possibly introducing bias in relative abundance estimates. Furthermore, short-read Illumina sequencing and contig-based binning can limit the resolution of closely related taxa, potentially collapsing intra-phylum diversity and inflating apparent dominance. Taken together, the high relative abundance of Actinobacteria most likely reflects strong ecological adaptation to landfill conditions, although extraction and sequencing limitations may contribute. Acidobacteria, also prominent, are frequently associated with low-pH soils and play pivotal roles in organic matter degradation and biogeochemical cycling. Their significant representation implies that the soil may be mildly acidic or contain conditions favouring Acidobacteria proliferation. Through their contributions to mineral weathering and nutrient recycling, this phylum supports microbial diversity and bolsters the soil’s capacity for resilience in nutrient-deficient or contaminated conditions. Notably, Bacteroidetes were the most abundant phylum in sample XM-AA, indicating their adaptive capacity in specific microenvironments, as seen in Figure 1. Known as Gram-negative anaerobes, Bacteroidetes thrive in nutrient-rich environments where they play a vital role in polysaccharide degradation and complex carbohydrate metabolism. Their ability to degrade structural carbohydrates can enhance soil structure and fertility, marking them as key contributors in transforming organic residues into bioavailable nutrients within this sample. The application of high-throughput sequencing provides a detailed view of microbial diversity at the phylum level, emphasising the ecological roles of these dominant groups. The predominance of Actinobacteria highlights their role as primary decomposers and pivotal agents in pollutant degradation and soil structural stabilisation, which is especially critical in landfill settings where organic waste accumulation is prevalent. Characterising microbial communities in this context illuminates not only the dominant phyla but also their potential contributions to landfill soil functionality.
Distribution of the phylum across the different samples.
This comprehensive profiling of microbial populations in landfill soils underscores the importance of microbial diversity in contaminated environments, laying a foundation for bioremediation initiatives. Targeting Actinobacteria and other functional groups could be a promising strategy to enhance soil quality and mitigate pollution impacts. Understanding microbial abundance and functional capacities provides a scientific basis for developing remediation strategies that harness specific microbial taxa, ultimately contributing to restoring and maintaining soil health in contaminated sites. 30
Table 2 offers a snapshot of the bacterial diversity across 4 soil samples from the Buffelsdraai landfill, highlighting variations in dominant phyla between samples (XM-AA, XM-BB, XM-CC, and XM-DD). Each sample’s microbial composition varies significantly, indicating a dynamic microbial ecosystem influenced potentially by factors like soil composition, landfill age, and external environmental stressors. Actinobacteria: The dominance of Actinobacteria in samples XM-CC and XM-DD possibly suggests they play a critical role in these specific landfill soil environments, likely in decomposing complex organic materials and contributing to nutrient cycling, which is essential in waste breakdown processes.
Relative abundances of dominant phyla in landfill soil samples (XM-AA, XM-BB, XM-CC, XM-DD).
Each sample represents a composite of 3 pooled subsamples (n = 3) collected within a 5 m radius at 20 cm depth. Sequencing generated ~33,000 reads per sample, and all samples were rarefied to 30,000 reads (N = 30,000) for diversity and taxonomic analyses. Values are expressed as the percentage of reads assigned to each phylum.
Acidobacteria have a significant presence in sample XM-BB (85%) but are nearly absent in other samples, which may indicate a sensitivity to specific soil conditions, such as pH, moisture or nutrient availability, that are more favourable in XM-BB. Bacteroidetes and Proteobacteria: These phyla show moderate to high representation in samples XM-AA and XM-BB but are nearly absent in XM-CC and XM-DD. Their presence in XM-AA and XM-BB suggests a role in initial organic matter degradation and carbon cycling, as these phyla are often associated with these functions in soil environments. The relatively high abundance of Firmicutes in XM-AA (10%) and minimal presence in other samples may suggest a role in early-stage organic matter decomposition, possibly due to the sporulation ability of many Firmicutes, allowing them to survive and adapt to harsher landfill environments. Representing a mix of low-abundance bacterial groups, these ‘other’ taxa (eg, 33% in XM-AA) could encompass rare or unique microbial taxa that contribute to biodiversity and functional versatility within the landfill ecosystem. The variability in microbial composition across samples demonstrates that landfill soils at Buffelsdraai do not host a uniform bacterial community but instead harbour distinct communities, possibly driven by microenvironmental factors. This metagenomic profiling aids in understanding the microbial ecology of landfill sites, which is crucial for identifying which microbial taxa are involved in waste breakdown, and their adaptive mechanisms can support strategies for enhancing landfill remediation processes. Actinobacteria’s prominence, for instance, underscores its role in nutrient recycling, essential for soil fertility and ecosystem health in landfill-affected areas. Understanding microbial diversity in landfills helps assess the environmental impact of landfills and can potentially inform future waste management practices by targeting specific microbes to manage contamination or pollution.
Alpha diversity of microbial communities
The diversity indices for soil samples from the Buffelsdraai landfill provide a quantitative assessment of microbial community richness and evenness across different sampling sites (XM-AA, XM-BB, XM-CC, and XM-DD), offering insight into the ecological dynamics and health of these landfill-associated soils. The Shannon index, a metric that accounts for both richness and evenness, ranges from higher values (indicating more diverse communities with balanced species distribution) to lower values (indicating lower diversity or dominance by a few taxa). 31
Sample XM-AA has the highest Shannon index (4.188), indicating the richest and most balanced microbial community among the 4 samples. XM-BB has a notably lower Shannon index (1.453), suggesting a community with reduced richness or evenness, likely dominated by a limited number of microbial taxa. Samples analysed from XM-CC and XM-DD displayed similar Shannon values (2.671 and 2.942, respectively), representing intermediate diversity levels with more balanced community structures than XM-BB but less diverse than XM-AA. The variation in Shannon diversity suggests that XM-AA may be the least disturbed or most ecologically complex site, potentially due to specific soil characteristics or microenvironmental factors that support a broader range of microbial taxa. The reduced diversity observed in XM-BB may reflect environmental stressors such as elevated sodium, cobalt, and nickel concentrations, which can favour a smaller but more resilient group of microbes capable of tolerating these conditions. The Simpson index emphasises the probability of any 2 randomly selected individuals belonging to the same species, with higher values signifying higher diversity and lower values indicating dominance by fewer species. XM-AA again showed the highest Simpson index (3.304), reinforcing its status as the most diverse sample. Sample XM-BB has the lowest Simpson index (0.706), reflecting a community with limited diversity where specific taxa may dominate. XM-CC and XM-DD have moderate Simpson values (1.663 and 1.712, respectively), consistent with their intermediate Shannon index scores, which suggest a degree of species dominance but with moderate diversity maintained. The low Simpson index in XM-BB highlights a microbial community that may be constrained by environmental pressures, reducing its overall diversity and potentially affecting ecosystem stability and functionality.
Figure 2 shows a KEGG profile heatmap representing the functional distribution of microbial metabolic pathways in 4 landfill soil samples (XM-AA, XM-BB, XM-CC, and XM-DD). Each row corresponds to a distinct KEGG pathway, encompassing processes such as genetic information processing, environmental adaptation, and various metabolic activities. The colour scale (ranging from purple to green) represents z-scores, with higher values (green) indicating pathways that are more prominent in the microbial community and lower values (purple) indicating less prominent pathways. The clustering and colour gradients highlight patterns in the functional capabilities of the microbial communities within each sample. XM-AA and XM-BB display significant functional variability compared with XM-CC and XM-DD. This is evident from the distinct clustering patterns, suggesting that XM-AA and XM-BB harbour microbial communities with unique functional profiles relative to XM-CC and XM-DD. Pathways with higher z-scores, shown in green, indicate dominant functional pathways within the respective samples. For instance, pathways related to protein families, amino acid metabolism, and energy metabolism appear consistently active across most samples, implying their foundational role in landfill microbial communities. Pathways with low z-scores, shown in purple, such as genetic information processing and drug resistance (antimicrobial), are less represented, possibly reflecting lower microbial specialisation in these areas within the landfill environment.
Heatmap displaying the relative abundance of KEGG orthologs (KOs) across the 4 landfill soil samples (columns: XM-AA, XM-BB, XM-CC, and XM-DD).
Functional potential of microbial communities
The KEGG hierarchical tree, as seen in Figure 3, shows the primary category of biological pathways, including metabolism, genetic information processing, environmental information processing, cellular processes, organismal systems, human diseases, Brite hierarchies, and unclassified functions. Within each primary category, further subdivisions capture specific pathways and biological processes. The circular pie charts beside each category and subcategory show the relative proportions of detected functions, with varying colours indicating different pathway intensities or z-scores. The largest category, labelled with the highest number of pathway identifications, encompasses diverse sub-pathways such as carbohydrate metabolism, energy metabolism, amino acid metabolism, lipid metabolism, and xenobiotics biodegradation and metabolism. Carbohydrate and energy metabolism are highly represented, as indicated by larger proportions in the pie chart. This finding suggests that microbial communities in landfill soils are heavily involved in basic energy production and nutrient cycling, reflecting their role in decomposing organic material and sustaining microbial energy requirements. Amino acid and lipid metabolism pathways further emphasise the community’s capacity for complex organic matter decomposition, an essential function in landfill environments where diverse organic waste types accumulate. The presence of xenobiotic biodegradation and metabolism indicates that these microbes can metabolise foreign compounds, potentially aiding in the breakdown of pollutants or hazardous substances, thus playing a role in mitigating contamination.
KEGG (Kyoto Encyclopaedia of Genes and Genomes) hierarchical tree, summarising the functional categorisation of microbial pathways identified in the soil samples from the Buffelsdraai landfill.
This category includes processes like transcription, translation, replication and repair, and folding, sorting, and degradation. These pathways suggest an active microbial community engaging in cellular maintenance, repair, and protein synthesis, all of which are critical for survival in a dynamic and possibly stressful landfill environment. The prominence of replication and repair indicates that microbial populations are under selective pressure to maintain genomic integrity, potentially due to exposure to environmental toxins or high mutation rates associated with landfill pollutants. This category, with pathways such as membrane transport and signal transduction, signifies the microbes’ ability to interact with and adapt to the surrounding environment. Membrane transport is crucial for nutrient uptake and waste excretion, indicating that microbial communities are actively engaged in exchanges with their surroundings, likely to accommodate fluctuating nutrient availability and environmental stressors. Signal transduction pathways point to the ability of microbes to sense and respond to environmental signals, which is vital for adapting to the chemical and physical conditions of landfill soils. Pathways under this category, including cell growth and death and cellular community – prokaryotes, highlight essential cellular functions that facilitate population dynamics, biofilm formation, and microbial interactions. The presence of cellular community pathways suggests that the microbial population may form structured communities or biofilms, a common strategy in landfill ecosystems to resist environmental stress and enhance survival through cooperative interactions.
Although less represented, organismal systems such as endocrine and digestive systems pathways could relate to functional analogues within the microbial community or contamination from human waste in landfill inputs. These might not directly correlate with microbial physiology but could represent incidental pathways due to the environmental DNA present in the landfill samples. This category contains pathways associated with infectious diseases and drug resistance mechanisms. The detection of antimicrobial resistance pathways may indicate the presence of resistance genes, possibly due to selective pressure from contaminants in the landfill. The pathways related to infectious diseases suggest that some microbial members might carry genes commonly associated with pathogenicity, raising concerns about the potential for harmful microbes or horizontal gene transfer in the landfill environment, which could pose a risk to public health if these microbes spread outside the landfill. This section includes protein families and other functional classifications, emphasising the diversity of microbial proteins that support various metabolic and structural roles in the microbial community. Protein families involved in genetic information processing and signalling underscore the complexity of microbial interactions and regulatory mechanisms required to maintain cellular function under landfill conditions. A significant portion of pathways remains unclassified or poorly characterised, which suggests that a substantial fraction of microbial functions in landfill soils are yet to be fully understood. This highlights the potential for discovering novel biochemical processes or microbial species adapted to landfill environments.
Figure 4 presents a heatmap of taxonomic profiles based on microbial community composition across 4 soil samples (XM-AA, XM-BB, XM-CC, and XM-DD) from the Buffelsdraai landfill. The rows indicate different bacterial taxa identified in the samples, and the colour gradient represents the z-score values for the relative abundance of each taxon within the samples. High-positive z-scores are shown in shades of orange, indicating taxa with higher relative abundance, while shades of purple represent lower abundances.
Taxonomic profiles based on microbial community composition across 4 soil samples (XM-AA, XM-BB, XM-CC, and XM-DD) from the Buffelsdraai landfill.
The heatmap reveals that specific taxa are more abundant in certain samples. For example, the presence of orange blocks in XM-CC and XM-DD indicates a notable enrichment of specific microbial groups in these samples compared with XM-AA and XM-BB. The high z-scores for certain taxa in samples XM-CC and XM-DD suggest unique community structures or adaptations within these samples, possibly reflecting specific environmental conditions or nutrient availability that support the growth of these microbial groups. Most rows exhibit consistent green or purple shades across all samples, suggesting a stable, core microbiome across the landfill soil. This core community likely includes taxa that are well adapted to the general conditions within the landfill, such as low pH, high organic matter or pollutant presence, indicating these microbes’ roles in maintaining ecosystem functions within the landfill environment. Among the stable microbial taxa, groups such as Actinobacteria and Firmicutes are prominent. These phyla are commonly found in soil environments and are known for their roles in organic matter decomposition, nutrient cycling, and resilience in polluted environments. Samples XM-CC and XM-DD show taxonomic profiles with higher variability in z-scores, particularly for taxa that are sparsely represented or absent in samples XM-AA and XM-BB. This finding suggests that XM-CC and XM-DD may have distinct environmental factors influencing microbial growth, such as specific contaminants, nutrient sources or physicochemical properties. The enrichment of particular microbial groups in XM-CC and XM-DD may reflect adaptation to specialised functions, such as xenobiotic degradation or resistance to heavy metals, which are often found in landfill environments. The presence of such specialised microbes is critical for understanding the biodegradative potential of landfill microbial communities. The diversity of taxa shown in the heatmap indicates a high level of phylogenetic diversity within the landfill microbial communities. This diversity is significant, as a broad range of microbial taxa contributes to various ecological processes such as organic matter degradation, nutrient recycling, and pollutant detoxification. The presence of diverse bacterial groups highlights the resilience of landfill ecosystems, with various microbial members likely contributing to overlapping or complementary functions essential for ecosystem stability and bioremediation potential.
Based on the heatmap, XM-CC and XM-DD show unique microbial community profiles, with higher z-scores for certain taxa not as prevalent in XM-AA and XM-BB. This difference suggests that XM-CC and XM-DD would cluster closely together in the PCoA plot, reflecting a shared microbial community structure or similar environmental influences.
This clustering may represent unique functional adaptations in XM-CC and XM-DD to specific conditions, such as higher levels of contaminants or other environmental factors that support specific microbial taxa. XM-AA and XM-BB have relatively consistent and lower z-scores across most taxa, indicating a more stable and possibly less diverse microbial community. In the PCoA, these 2 samples would likely group together, representing a shared core microbiome or similar environmental conditions that influence a common microbial structure. Their clustering, distinct from XM-CC and XM-DD, may reflect less exposure to localised pollutants or different physicochemical conditions that support a more uniform community. The PCoA would likely show separation along the principal components, with 1 axis distinguishing the samples with enriched taxa (XM-CC and XM-DD) from those with more consistent profiles (XM-AA and XM-BB). This separation would indicate that the primary driver of variation is the presence of specific microbial groups in XM-CC and XM-DD. Another axis might capture minor differences within each pair of samples, possibly related to subtle environmental differences or sampling variability.
The diversity indices indicated variations in microbial community complexity among the different sites, suggesting distinct ecological niches influenced by localised environmental factors. In addition, functional annotation through KEGG pathways revealed the presence of genes associated with essential metabolic and environmental adaptation processes, underscoring the functional resilience and adaptive potential of these microbial communities in the face of landfill-induced stresses.
Discussion
This study used metagenomic profiling to investigate the taxonomic and functional diversity of microbial communities in soils from the Buffelsdraai landfill, South Africa. Landfills are complex environments where microbes play essential roles in organic matter decomposition, nutrient cycling, and pollutant degradation. However, the microbial diversity and functional capacities of such systems remain poorly characterised. 32 High-throughput sequencing revealed that landfill soils host distinct microbial communities shaped by local physicochemical conditions. Actinobacteria, Acidobacteria, Bacteroidetes, Proteobacteria, and Firmicutes dominated across samples, with Actinobacteria particularly enriched in heavily contaminated soils. Microorganisms including bacteria and archaea that have potential for extensive bioremediation activities are frequently found in landfills. 33 A recent study from Teng and Chen 34 also showed the dominance of the phylum Actinobacteria and Proteobacteria and genes involved in biomolecule metabolism, aromatic compound degradation, stress tolerance, and xenobiotic biodegradation in municipal landfill soils. According to Selvarajan et al, 35 Bacteroidetes have been receiving attention for use in bioconversion industries along with Actinobacteria, Firmicutes, and Proteobacteria because, reportedly, they grow quickly on laboratory media and have the ability to biodegrade biomass efficiently. The dominance of Actinobacteria in landfills is not uncommon as a recent study from Sekhohola-Dlamini et al 33 and Gupta et al 36 found more similar results to ours in terms microbial diversity. Close to Actinobacteria was Acidobacteria and Proteobacteria; this is not surprising as both phyla have been suggested to play an important role in the degradation of both organic and inorganic substances and these also include heavy metal contaminants in landfill soils.35,37 Overall, together these phyla sustain critical ecological processes in landfill systems, supporting organic waste decomposition, pollutant transformation and soil ecosystem resilience under contamination stress.35,38
Alpha diversity indices showed high microbial diversity in XM-AA, suggesting a functionally stable and resilient community, consistent with findings from other landfill and contaminated soil studies where elevated diversity was associated with broader metabolic potential and ecological robustness. 30 On the contrary, the low diversity observed in XM-BB likely reflects environmental stress from salinity and heavy metal accumulation, as similarly reported in metagenomic analyses of polluted soils where contaminants reduced microbial richness and functional redundancy. 39 Samples XM-CC and XM-DD showed moderate diversity, indicating partially resilient but environmentally impacted communities.39,40
Functional profiling highlighted enrichment of pathways involved in carbohydrate and lipid metabolism, xenobiotic degradation, and stress adaptation, consistent with the ecological roles of landfill microbes in decomposition and pollutant mitigation. 41 The presence of antimicrobial resistance and metal-tolerance pathways further reflected adaptation to chemical stressors such as high sodium, cobalt, and nickel levels. 42 In addition, municipal landfills have been reported as one of the major sources of antibiotics and antibiotic resistance. Therefore, the detection of antimicrobial resistance genes (ARGs) in landfill soils is of particular concern, as it suggests that these environments may serve as reservoirs for resistance determinants. 43 Similar observations have been reported in municipal and industrial landfill sites where ARGs, often associated with mobile genetic elements, were abundant and linked to heavy metal co-selection and antibiotic residues.44,45 For instance, Wan et al 46 investigated 2 landfills where they found 4 ARGs; they also found that the landfill was dominated by Actinobacteria, Proteobacteria, and Bacteroidetes. These findings suggest that landfills can facilitate horizontal gene transfer among environmental microbes and potential pathogens, increasing the risk of resistance propagation beyond the landfill ecosystem. 47 Therefore, continuous antimicrobial resistance surveillance in such environments is therefore crucial for early detection of emerging resistance determinants and for assessing potential risks to surrounding municipal waste landfills and water systems.48,49 Consequently, distinct clustering of samples (XM-AA/XM-BB vs XM-CC/XM-DD) suggests site-specific ecological pressures driving microbial specialisation. 50
Together, these findings establish a baseline for understanding landfill microbial ecology in South Africa. They demonstrate that landfill soils harbour both core microbial functions (nutrient cycling, organic matter breakdown) and variable, stress-adapted taxa with potential relevance for bioremediation. To add to that, our current inferences regarding bioremediation potential are primarily based on genomic predictions; future studies will aim to confirm the genetic potential observed in our data through actual microbial activity, for example, microcosm assays. Hence, our study preliminary highlights the ecological significance of microbial diversity in landfill systems and lays the groundwork for future studies that link contaminant profiles to microbial adaptation and functional resilience. Finally, the Buffelsdraai landfill soils is subject to several other methodological limitations and these include composite sampling, biases from DNA extraction and the absence of uncontaminated control soils further constraining ecological interpretation.
Conclusion
This study’s findings highlight microbial communities’ critical role in maintaining soil health and functionality within a contaminated landfill ecosystem. These microbial populations contribute to organic matter decomposition and nutrient cycling and exhibit functional capacities that could be harnessed for bioremediation and soil rehabilitation. This research provides a valuable baseline for future studies on microbial ecology in landfill environments. It underscores the importance of continuous monitoring and potential remediation efforts to mitigate the environmental impact of landfills. The insights gained here provide a baseline understanding of landfill microbial communities and their functional responses to environmental stressors, highlighting taxa and pathways with potential relevance for future bioremediation.
Footnotes
Ethical Considerations
This article does not contain any studies with human or animal participants.
Consent for Publication
All authors have agreed to submit the manuscript in the Journal of Bioinformatics and Biology Insights.
Author Contributions
Funding
We would like to acknowledge the financial support from the Department of Science and Innovation – Technology Innovation Agency SIIP (Strategic Industrial Bio-Innovation Programme) and the National Research Foundation (grant number: 112980 and 145396) of South Africa. The study also acknowledges the Research Office, of the University of KwaZulu-Natal.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.