Predicting taxonomic and functional structure of microbial communities in acid mine drainage

Nitrogen-cycling processes under long-term compound heavy metal(loids) pressure around a gold mine: Stimulation of nitrite reduction

Mining and tailings deposition can cause serious heavy metal(loids) pollution to the surrounding soil environment. Soil microorganisms adapt their metabolism to such conditions, driving alterations in soil function. This study aims to elucidate the response patterns of nitrogen-cycling microorganisms under long-term heavy metal(loids) exposure. The results showed that the diversity and abundance of nitrogen-cycling microorganisms showed negative feedback to heavy metal(loids) concentrations. Denitrifying microorganisms were shown to be the dominant microorganisms with over 60% of relative abundance and a complex community structure including 27 phyla. Further, the key bacterial species in the denitrification process were calculated using a random forest model, where the top three key species (Pseudomonas stutzei, Sphingobium japonicum and Leifsonia rubra) were found to play a prominent role in nitrite reduction. Functional gene analysis and qPCR revealed that nirK, which is involved in nitrite reduction, significantly accumulated in the most metal-rich soil with the increase of absolute abundance of 63.86%. The experimental results confirmed that the activity of nitrite reductase (Nir) encoded by nirK in the soil was increased at high concentrations of heavy metal(loids). Partial least squares-path model identified three potential modes of nitrite reduction processes being stimulated by heavy metal(loids), the most prominent of which contributed to enhanced nirK abundance and soil Nir activity through positive stimulation of key species. The results provide new insights and preliminary evidence on the stimulation of nitrite reduction processes by heavy metal(loids).

Deciphering microbial metabolic interactions and their implications for community dynamics in acid mine drainage sediments

The microbially-mediated reduction processes have potential for the bioremediation of acid mine drainage (AMD), which represents a worldwide environment problem. However, we know little about the microbial interactions in anaerobic AMD sediments. Here we utilized genome-resolved metagenomics to uncover the nature of cooperative and competitive metabolic interactions in 90 AMD sediments across Southern China. Our analyses recovered well-represented prokaryotic communities through the reconstruction of 2625 population genomes. Functional analyses of these genomes revealed extensive metabolic handoffs which occurred more frequently in nitrogen metabolism than in sulfur metabolism, as well as stable functional redundancy across sediments resulting from populations with low genomic relatedness. Genome-scale metabolic modeling showed that metabolic competition promoted microbial co-occurrence relationships, suggesting that community assembly was dominated by habitat filtering in sediments. Notably, communities colonizing more extreme conditions tended to be highly competitive, which was typically accompanied with increased network complexity but decreased stability of the microbiome. Finally, our results demonstrated that heterotrophic Thermoplasmatota associated with ferric iron and sulfate reduction contributed most to the elevated levels of competition. Our study shed light on the cooperative and competitive metabolisms of microbiome in the hazardous AMD sediments, which may provide preliminary clues for the AMD bioremediation in the future.

pH and thiosulfate dependent microbial sulfur oxidation strategies across diverse environments

Sulfur oxidizing bacteria (SOB) play a key role in sulfur cycling in mine tailings impoundment (TI) waters, where sulfur concentrations are typically high. However, our understanding of SOB sulfur cycling via potential S oxidation pathways (sox, rdsr, and S4I) in these globally ubiquitous contexts, remains limited. Here, we identified TI water column SOB community composition, metagenomics derived metabolic repertoires, physicochemistry, and aqueous sulfur concentration and speciation in four Canadian base metal mine, circumneutral-alkaline TIs over four years (2016 - 2019). Identification and examination of genomes from nine SOB genera occurring in these TI waters revealed two pH partitioned, metabolically distinct groups, which differentially influenced acid generation and sulfur speciation. Complete sox (csox) dominant SOB (e.g., Halothiobacillus spp., Thiomonas spp.) drove acidity generation and S2O3 2- consumption via the csox pathway at lower pH (pH ~5 to ~6.5). At circumneutral pH conditions (pH ~6.5 to ~8.5), the presence of non-csox dominant SOB (hosting the incomplete sox, rdsr, and/or other S oxidation reactions; e.g. Thiobacillus spp., Sulfuriferula spp.) were associated with higher [S2O3 2-] and limited acidity generation. The S4I pathway part 1 (tsdA; S2O3 2- to S4O6 2-), was not constrained by pH, while S4I pathway part 2 (S4O6 2- disproportionation via tetH) was limited to Thiobacillus spp. and thus circumneutral pH values. Comparative analysis of low, natural (e.g., hydrothermal vents and sulfur hot springs) and high (e.g., Zn, Cu, Pb/Zn, and Ni tailings) sulfur systems literature data with these TI results, reveals a distinct TI SOB mining microbiome, characterized by elevated abundances of csox dominant SOB, likely sustained by continuous replenishment of sulfur species through tailings or mining impacted water additions. Our results indicate that under the primarily oxic conditions in these systems, S2O3 2- availability plays a key role in determining the dominant sulfur oxidation pathways and associated geochemical and physicochemical outcomes, highlighting the potential for biological management of mining impacted waters via pH and [S2O3 2-] manipulation.

Synergistic impact of bioavailable PHEs and alkalinity on microbial diversity and traits in agricultural soil adjacent to chromium-asbestos mines

Soil microbial communities undergo constant fluctuations, particularly in response to environmental factors. Although the deposition of toxic mine waste is recognized for introducing potentially hazardous elements (PHEs) into the soil, its specific impacts on microbial communities remain unclear. This study aims to explore the combined effects of soil alkalinity and bioavailable PHEs on microbial diversity and traits in agricultural soil adjacent to a chromium-asbestos mining area. By employing a comprehensive analysis, this study indicated that microbiological attributes were reduced in contaminated areas (zone 1), whereas both the levels of bioavailable PHEs (CrWs: 31.08 mg/kg, NiWs: 13.90 mg/kg) and alkalinity indices (CROSS, MCAR, MH) were significantly higher. The spatial distribution of soil alkalinity and bioavailable PHEs, primarily originating from chromium-asbestos mines, has been determined. This study also elucidates the negative relationship between soil stressors (Alkalinity and PHEs) and microbial activities (soil enzymatic activity, microbial respiration, and biomass carbon). The vector's length exhibited a notable difference between zone 1 (0.51) and zone 2 (0.32), indicating a substantial limitation on carbon (C). Also, the investigation of soil bacterial diversity unveiled notable disparities in the prevalence of microbial populations inside zone 1. Proteobacteria constituted 57.18% of the total population indicating a noteworthy prevalence in the contaminated soils. Finally, the random forest (RF) algorithm from machine learning was selected and proven to be a robust choice in Taylor diagrams for predicting the causative stressors responsible for the deterioration of soil microbial health. Therefore, this research offers insights into the health and resilience of soil microbial communities under synergistic stress conditions, which will aid environmentalists in planning future interventions and improving sustainable farming techniques.

Effects of sulfur nanoparticles on rhizosphere microbial community changes in oilseed rape plantation soil under mercury stress

In the present study, experiments were conducted to assess the influence of nanoscale sulfur in the microbial community structure of metallophytes in Hg-contaminated rhizosphere soil for planting rapeseed. The results showed that the richness and diversity of the rhizobacteria community decreased significantly under Hg stress, but increased slightly after SNPs addition, with a reduction in the loss of Hg-sensitive microorganisms. Moreover, all changes in the relative abundances of the top ten phyla influenced by Hg treatment were reverted when subjected to Hg + SNPs treatment, except for Myxococcota and Bacteroidota. Similarly, the top five genera, whose relative abundance decreased the most under Hg alone compared to CK, increased by 19.05%-54.66% under Hg + SNPs treatment compared with Hg alone. Furthermore, the relative abundance of Sphingomonas, as one of the dominant genera for both CK and Hg + SNPs treatment, was actively correlated with plant growth. Rhizobacteria, like Pedobacter and Massilia, were significantly decreased under Hg + SNPs and were positively linked to Hg accumulation in plants. This study suggested that SNPs could create a healthier soil microecological environment by reversing the effect of Hg on the relative abundance of microorganisms, thereby assisting microorganisms to remediate heavy metal-contaminated soil and reduce the stress of heavy metals on plants.

Bioindicator responses to extreme conditions: Insights into pH and bioavailable metals under acidic metal environments

Acid mine drainage (AMD) caused environmental risks from heavy metal pollution, requiring treatment methods such as chemical precipitation and biological treatment. Monitoring and adapting treatment processes was crucial for success, but cost-effective pollution monitoring methods were lacking. Using bioindicators measured through 16S rRNA was a promising method to assess environmental pollution. This study evaluated the effects of AMD on ecological health using the ecological risk index (RI) and the Risk Assessment Code (RAC) indices. Additionally, we also examined how acidic metal stress affected the diversity of bacteria and fungi, as well as their networks. Bioindicators were identified using linear discriminant analysis effect size (LEfSe), Partial least squares regression (PLS-R), and Spearman analyses. The study found that Cd, Cu, Pb, and As pose potential ecological risks in that order. Fungal diversity decreased by 44.88% in AMD-affected areas, more than the 33.61% decrease in bacterial diversity. Microbial diversity was positively correlated with pH (r = 0.88, p = 0.04) and negatively correlated with bioavailable metal concentrations (r = -0.59, p = 0.05). Similarly, microbial diversity was negatively correlated with bioavailable metal concentrations (bio_Cu, bio_Pb, bio_Cd) (r = 0.79, p = 0.03). Acidiferrobacter and Thermoplasmataceae were prevalent in acidic metal environments, while Puia and Chitinophagaceae were identified as biomarker species in the control area (LDA>4). Acidiferrobacter and Thermoplasmataceae were found to be pH-tolerant bioindicators with high reliability (r = 1, P < 0.05, BW > 0.1) through PLS-R and Spearman analysis. Conversely, Puia and Chitinophagaceae were pH-sensitive bioindicators, while Teratosphaeriaceae was a potential bioindicator for Cu-Zn-Cd metal pollution. This study identified bioindicator species for acid and metal pollution in AMD habitats. This study outlined the focus of biological monitoring in AMD acidic stress environments, including extreme pH, heavy metal pollutants, and indicator species. It also provided essential information for heavy metal bioremediation, such as the role of omics and the effects of organic matter on metal bioavailability.

Environmental stress mediates groundwater microbial community assembly

Community assembly describes how different ecological processes shape microbial community composition and structure. How environmental factors impact community assembly remains elusive. Here we sampled microbial communities and >200 biogeochemical variables in groundwater at the Oak Ridge Field Research Center, a former nuclear waste disposal site, and developed a theoretical framework to conceptualize the relationships between community assembly processes and environmental stresses. We found that stochastic assembly processes were critical (>60% on average) in shaping community structure, but their relative importance decreased as stress increased. Dispersal limitation and 'drift' related to random birth and death had negative correlations with stresses, whereas the selection processes leading to dissimilar communities increased with stresses, primarily related to pH, cobalt and molybdenum. Assembly mechanisms also varied greatly among different phylogenetic groups. Our findings highlight the importance of microbial dispersal limitation and environmental heterogeneity in ecosystem restoration and management.

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and "transduce" signals to adjust internal processes. We hypothesized that an ecosystem's unique stimuli leave a sensor "fingerprint," able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection's nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient's disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model's feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

Compost, plants and endophytes versus metal contamination: choice of a restoration strategy steers the microbiome in polymetallic mine waste

Finding solutions for the remediation and restoration of abandoned mining areas is of great environmental importance as they pose a risk to ecosystem health. In this study, our aim was to determine how remediation strategies with (i) compost amendment, (ii) planting a metal-tolerant grass Bouteloua curtipendula, and (iii) its inoculation with beneficial endophytes influenced the microbiome of metal-contaminated tailings originating from the abandoned Blue Nose Mine, SE Arizona, near Patagonia (USA). We conducted an indoor microcosm experiment followed by a metataxonomic analysis of the mine tailings, compost, and root samples. Our results showed that each remediation strategy promoted a distinct pattern of microbial community structure in the mine tailings, which correlated with changes in their chemical properties. The combination of compost amendment and endophyte inoculation led to the highest prokaryotic diversity and total nitrogen and organic carbon, but also induced shifts in microbial community structure that significantly correlated with an enhanced potential for mobilization of Cu and Sb. Our findings show that soil health metrics (total nitrogen, organic carbon and pH) improved, and microbial community changed, due to organic matter input and endophyte inoculation, which enhanced metal leaching from the mine waste and potentially increased environmental risks posed by Cu and Sb. We further emphasize that because the initial choice of remediation strategy can significantly impact trace element mobility via modulation of both soil chemistry and microbial communities, site specific, bench-scale preliminary tests, as reported here, can help determine the potential risk of a chosen strategy.

Responses of the structure and function of microbes in Yellow River Estuary sediments to different levels of mercury

The health and stability of the estuary of the Yellow River ecosystem have come under increasing pressure from land-based inputs of heavy metals. While it is known that heavy metals affect the function and health of the microbial community, there remains little knowledge on the responses of the microbial community to heavy metals, particularly highly toxic mercury. The research aimed to characterize the responses of the sediment microbial community of the estuary of the Yellow River to different levels of mercury stress. Estuary sediment samples were collected for microbial community analysis, measurement of mercury [including total mercury (THg) and methylmercury (MeHg)], and measurement of other physicochemical factors, including pH, total organic carbon (TOC), sulfide, iron ratio (Fe3+/Fe2+), ammonium salt (NH4+), and biochemical oxygen demand (BOD). The application of 16S rRNA sequencing identified 60 phyla of bacteria, dominated by Proteobacteria, Firmicutes, and Bacteroidetes. Stations with higher THg or MeHg and lower microbial abundance and diversity were generally distributed further outside of the estuary. Besides mercury, the measured physicochemical factors had impacts on microbial diversities and distribution. Metagenomics assessment of three stations, representative of low, moderate, and high mercury concentrations and measured physicochemical factors, revealed the abundances and functions of predicted genes. The most abundant genes regulating the metabolic pathways were categorized as metabolic, environmental information processing, and genetic information processing, genes. At stations with high levels of mercury, the dominant genes were related to energy metabolism, signal transport, and membrane transport. Functional genes with a mercury-resistance function were generally in the mer system (merA, merC, merT, merR), alkylmercury lyase, and metal-transporting ATPase. These results offer insight into the microbial community structure of the sediments in the Yellow River Estuary and the microbial function of mercury resistance under mercury stress.

Predicting microbial community compositions in wastewater treatment plants using artificial neural networks

BACKGROUND

Activated sludge (AS) of wastewater treatment plants (WWTPs) is one of the world's largest artificial microbial ecosystems and the microbial community of the AS system is closely related to WWTPs' performance. However, how to predict its community structure is still unclear.

RESULTS

Here, we used artificial neural networks (ANN) to predict the microbial compositions of AS systems collected from WWTPs located worldwide. The predictive accuracy R²_1:1 of the Shannon-Wiener index reached 60.42%, and the average R²_1:1 of amplicon sequence variants (ASVs) appearing in at least 10% of samples and core taxa were 35.09% and 42.99%, respectively. We also found that the predictability of ASVs was significantly positively correlated with their relative abundance and occurrence frequency, but significantly negatively correlated with potential migration rate. The typical functional groups such as nitrifiers, denitrifiers, polyphosphate-accumulating organisms (PAOs), glycogen-accumulating organisms (GAOs), and filamentous organisms in AS systems could also be well recovered using ANN models, with R²_1:1 ranging from 32.62% to 56.81%. Furthermore, we found that whether industry wastewater source contained in inflow (IndConInf) had good predictive abilities, although its correlation with ASVs in the Mantel test analysis was weak, which suggested important factors that cannot be identified using traditional methods may be highlighted by the ANN model.

CONCLUSIONS

We demonstrated that the microbial compositions and major functional groups of AS systems are predictable using our approach, and IndConInf has a significant impact on the prediction. Our results provide a better understanding of the factors affecting AS communities through the prediction of the microbial community of AS systems, which could lead to insights for improved operating parameters and control of community structure. Video Abstract.

Eukaryotic Community Structure and Interspecific Interactions in a Stratified Acidic Pit Lake Water in Anhui Province

The stratified acidic pit lake formed by the confluence of acid mine drainage has a unique ecological niche and is a model system for extreme microbial studies. Eukaryotes are a component of the AMD community, with the main members including microalgae, fungi, and a small number of protozoa. In this study, we analyzed the structural traits and interactions of eukaryotes (primarily fungi and microalgae) in acidic pit lakes subjected to environmental gradients. Based on the findings, microalgae and fungi were found to dominate different water layers. Specifically, Chlorophyta showed dominance in the well-lit aerobic surface layer, whereas Basidiomycota was more abundant in the dark anoxic lower layer. Co-occurrence network analysis showed that reciprocal relationships between fungi and microalgae were prevalent in extremely acidic environments. Highly connected taxa within this network were Chlamydomonadaceae, Sporidiobolaceae, Filobasidiaceae, and unclassified Eukaryotes. Redundancy analysis (RDA) and random forest models revealed that Chlorophyta and Basidiomycota responded strongly to environmental gradients. Further analysis indicated that eukaryotic community structure was mainly determined by nutrient and metal concentrations. This study investigates the potential symbiosis between fungi and microalgae in the acidic pit lake, providing valuable insights for future eukaryotic biodiversity studies on AMD remediation.

Genome-resolved metagenomics reveals depth-related patterns of microbial community structure and functions in a highly stratified, AMD overlaying mine tailings

Acid mine drainage (AMD) is a worldwide environmental problem, yet bioremediation is hampered by a limited knowledge of the reductive microbial processes in the AMD ecosystem. Here, we generate extensive metagenome and geochemical datasets to investigate how microbial populations and metabolic capacities driving major element cycles are structured in a highly stratified, AMD overlaying tailings environment. The results demonstrated an explicit depth-dependent differentiation of microbial community composition and function profiles between the surface and deeper tailings layers, paralleling the dramatic shifts in major physical and geochemical properties. Specifically, key genes involved in sulfur and iron oxidation were significantly enriched in the surface tailings, whereas those associated with reductive nitrogen, sulfur, and iron processes were enriched in the deeper layers. Genome-resolved metagenomics retrieved 406 intermediate or high-quality genomes spanning 26 phyla, including major new groups (e.g., Patescibacteria and DPANN). Metabolic models involving nitrogen, sulfur, iron, and carbon cycles were proposed based on the functional potentials of the abundant microbial genomes, emphasizing syntrophy and the importance of lesser-known taxa in the degradation of complex carbon compounds. These results have implications for in situ AMD bioremediation.

Habitats modulate influencing factors shaping the spatial distribution of bacterial communities along a Tibetan Plateau riverine wetland

The Tibetan Plateau riverine wetland is very sensitive to global climate change. Understanding the mechanisms that maintain the spatial patterns of bacterial communities provides insight into the dominant biogeochemical processes within the plateau riverine wetlands. Nonetheless, the spatial distribution of bacterial communities along these wetlands has rarely been explored. We investigated the spatial patterns of bacterial community within rhizosphere soil, bulk soil, and sediment samples collected along the Yarlung Tsangpo riverine wetland (YTRW), the longest plateau riverine wetland in China. Our results indicated that the diversity of bacterial communities in all three habitats increased significantly along the YTRW. The slope of the linear relationship between distance and bacterial community diversity in sediment was steeper than those for bulk and rhizosphere soils. Furthermore, bacterial communities in all three habitats showed significant distance-decay relationships. A combination of historical factors (geographical distance and climatic factors) and contemporary environmental heterogeneity (edaphic properties) controlled spatial distributions of bacterial communities in all three habitats, although climatic factors were predominant. Climatic factors affected rhizosphere bacterial communities more than those in bulk soil and sediment. Co-occurrence network analysis revealed that the potential interactions between bacterial taxa may decrease along the YTRW. This field investigation highlighted that the climatic factors strongly influenced the spatial distribution of bacterial communities along the YTRW; however, habitat differences among rhizosphere soil, bulk soil, and sediment samples affected the relative importance of climatic factors on spatial distributions of the associated bacterial communities. These findings would improve the understanding of biogeochemical processes in these typical habitats and potential alterations provoked by climate change.

Impact of Petroleum Contamination on the Structure of Saline Soil Bacterial Communities

Petroleum contamination may lead to variations in soil microbial community structure and activities. The bioremediation of petroleum-contaminated soil typically depends on the characteristics and activities of oil-degrading microorganisms, which can be introduced or be part of the native soil microbiota. Thus, analyzing the structure of the microbial community and internal relationships in the bioremediation process is critical. Our study characterized the physical and chemical properties, microbial community structure, and microbial diversity of surface soil collected near an oilfield. The total carbon (TC), total organic carbon (TOC), and microbial diversity in oil-contaminated soil was found higher than in uncontaminated samples. Proteobacteria abundance was inhibited with oil pollution, while Actinomycetes abundance was enhanced. Some indigenous hydrocarbon-degrading bactera were enriched by oil pollution, such as Bacillus, Actinomarinales norank, Balneolaceae uncultured, Marinobacter, and Pseudomonas. Furthermore, Rokubacteria, Nitrospirae, and Entotheonellaeota were significant differences in the contaminated group. There were 16 genera with significant differences in the polluted group, such as Woeseia, Pelagibius, Pontibacillus, IS_44, Aliifodinibius, while Halothiobacillus, Algoriphagus, Novosphingobium, etc. had significant differences in the uncontaminated group. Redundancy analysis demonstrated that the responses of the microorganisms to the evaluated environmental factors were different, and TC was the most important driver of microbial community variation. Moreover, TOC was the largest contributor to operational taxonomic unit (OTU) and Chao index variations. Our results provide a theoretical basis for the enhancement of microbial activity in oil-contaminated soil, which might improve bioremediation efficacy.

Mercury drives microbial community assembly and ecosystem multifunctionality across a Hg contamination gradient in rice paddies

Soil microbial communities are critical for maintaining terrestrial ecosystems and fundamental ecological processes. Mercury (Hg) is a heavy metal that is toxic to microorganisms, but its effects on microbial community assembly and ecosystem multifunctionality in rice paddy ecosystems remain largely unknown. In the current study, we analyzed the microbial community structure and ecosystem multifunctionality of paddy soils across a Hg contamination gradient. The results demonstrated that Hg contamination significantly altered the microbial community structure. The microbial communities were predominantly driven by deterministic selection rather than stochastic processes. The random forest model and variation partition analysis demonstrated that the Hg level was the most important predictor of microbial profiles. Ecosystem multifunctionality decreased across the Hg concentration gradient, and multifunctionality was significantly correlated with soil biodiversity, suggesting that Hg-induced reductions in soil biodiversity led to reduced ecosystem services. A structural equation model showed that Hg contamination directly and indirectly affected ecosystem multifunctionality. The present work broadens our knowledge of the assembly of the microbiome in rice paddies across a Hg contamination gradient and highlights the significance of soil biodiversity in regulating ecosystem functions, especially in Hg-polluted rice paddies.

Unraveling diverse survival strategies of microorganisms to vanadium stress in aquatic environments

Worldwide vanadium contamination is posing serious risks to ecosystems. Although abilities of microbial communities to cope with vanadium stress using specific survival strategies have been reported, little is known regarding their relative importance and the underlying detoxification/tolerance mechanisms. Herein, we investigated the potential survival strategies of microbial communities and associated pathways in aquatic environments based on geochemistry and molecular biology. High vanadium content was observed for both water (12.6 ± 1.15 mg/L) and sediment (1.18 × 10³ ± 10.4 mg/kg) in the investigated polluted stream. Co-occurrence network investigation implied that microbial communities showed cooperative interactions to adapt to the vanadium-polluted condition. Vanadium was also characterized as one of the vital factors shaping the community structure via redundancy analysis and structural equation models. Based on the metagenomic technology, three survival strategies including denitrification pathway, electron transfer, and metal resistance in innate microbes under the vanadium stress were revealed, with comprehensively summarized vanadium detoxification/tolerance genes. Remarkable role of electron transfer genes and the prevalent existence of resistance genes during detoxifying vanadium were highlighted. Overall, these findings provide novel insights into survival strategies under the vanadium contamination in aquatic environments, which can be of great significance for the identification, isolation, and application of vanadium reducing bacteria in vanadium bioremediation.

The exacerbation of soil acidification correlates with structural and functional succession of the soil microbiome upon agricultural intensification

Agricultural intensification driven by land-use changes has caused continuous and cumulative soil acidification (SA) throughout the global agroecosystem. Microorganisms mediate acid-generating reactions; however, the microbial mechanisms responsible for exacerbating SA feedback remain largely unknown. To determine the microbial community composition and putative function associated with SA, we conducted a metagenomic analysis of soils across a chronosequence that has elapsed since the conversion of rice-wheat (RW) to rice-vegetable (RV) rotations. Compared to RW rotations, soil pH decreased by 0.50 and 1.56 units (p < 0.05) in response to 10-year and 20-year RV rotations, respectively. Additionally, acid saturation ratios were increased by 7.3% and 36.2% (p < 0.05), respectively. The loss of microbial beta-diversity was a key element that contributed to the exacerbation of SA in the RV. Notably, the 20-year RV-enriched microbial taxa were more hydrogen (H⁺)-, aluminium (Al³⁺)-, and nitrate nitrogen (NO₃^--N) -dependent and contained more genera exhibiting dehydrogenation functions than did RW-enriched taxa. "M00115, M00151, M00417, and M00004" and "M00531 and M00135" that are the "proton-pumping" and "proton-consuming" gene modules, respectively, were linked to the massive recruitment of acid-dependent biomarkers in 20-year RV soils, particularly Rhodanobacter, Gemmatirosa, Sphingomonas, and Streptomyces. Collectively, soils in long-term RV rotations were highly acidified and acid-sensitive, as the enrichment of microbial dehydrogenation genes allowing for soil buffering capacity is more vulnerable to H⁺ loading and consequently promotes the colonization of more acid-tolerant and acidogenic microbes, and ultimately provide new clues for researchers to elucidate the interaction between SA and the soil microbiome.

Remediation of cadmium contaminated soil by composite spent mushroom substrate organic amendment under high nitrogen level

Cadmium (Cd) contamination in soil poses a serious threat to ecological environment and crop quality, especially under high nitrogen level. Here, the efficiency of composite organic amendment (spent mushroom substrate and its biochar) on remediation of Cd contaminated soil under high nitrogen level has been studied through a 42 days' soil incubation experiment. The results showed: (i) the application of composite organic amendment minimized the repercussions of high nitrogen and significantly reduced the exchangeable Cd proportion by 28.3%-29.5%, especially for Ca(NO₃)₂ treatment; (ii) the application of composite organic amendment improved the physicochemical properties of soil, such as pH, CEC and organic matter content increased by 0.63-0.99 unit, 39.69%-45.00% and 7.77%-11.47%, and EC decreased by 16.21%-44.47% compared with non-amendment Cd-contaminated soil, respectively; (iii) the application of composite organic amendment significantly increased the soil enzyme activities and microbial biomass, among which urease activity was increased most by 12.06-16.42 mg·g^-1·d^-1, and the copy number of AOA was decreased by 30.6%- 92.0%, and the copy number of AOB was increased most by about 45 times. In brief, the composite organic amendment can alleviate the adverse effects of Cd and nitrogen on the soil, but its long-term efficacy needs to be verified in further field study.

Patterns and ecological drivers of viral communities in acid mine drainage sediments across Southern China

Recent advances in environmental genomics have provided unprecedented opportunities for the investigation of viruses in natural settings. Yet, our knowledge of viral biogeographic patterns and the corresponding drivers is still limited. Here, we perform metagenomic deep sequencing on 90 acid mine drainage (AMD) sediments sampled across Southern China and examine the biogeography of viruses in this extreme environment. The results demonstrate that prokaryotic communities dictate viral taxonomic and functional diversity, abundance and structure, whereas other factors especially latitude and mean annual temperature also impact viral populations and functions. In silico predictions highlight lineage-specific virus-host abundance ratios and richness-dependent virus-host interaction structure. Further functional analyses reveal important roles of environmental conditions and horizontal gene transfers in shaping viral auxiliary metabolic genes potentially involved in phosphorus assimilation. Our findings underscore the importance of both abiotic and biotic factors in predicting the taxonomic and functional biogeographic dynamics of viruses in the AMD sediments.

The biogeography of viral communities in extreme environments remains understudied. Here, the authors use metagenomic sequencing on 90 acid mine drainage sediments sampled across Southern China, showing the predominant effects of prokaryotic communities and the influence of environmental variables on viral taxonomy and function.

Microbial diversity in extreme environments

A wide array of microorganisms, including many novel, phylogenetically deeply rooted taxa, survive and thrive in extreme environments. These unique and reduced-complexity ecosystems offer a tremendous opportunity for studying the structure, function and evolution of natural microbial communities. Marker gene surveys have resolved patterns and ecological drivers of these extremophile assemblages, revealing a vast uncultured microbial diversity and the often predominance of archaea in the most extreme conditions. New omics studies have uncovered linkages between community function and environmental variables, and have enabled discovery and genomic characterization of major new lineages that substantially expand microbial diversity and change the structure of the tree of life. These efforts have significantly advanced our understanding of the diversity, ecology and evolution of microorganisms populating Earth's extreme environments, and have facilitated the exploration of microbiota and processes in more complex ecosystems.

Microbial biogeography of acid mine drainage sediments at a regional scale across Southern China

Investigations of microbial biogeography in extreme environments provide unique opportunities to disentangle the roles of environment and space in microbial community assembly. Here, we reported a comprehensive microbial biogeographic survey of 90 acid mine drainage (AMD) sediment samples from 18 mining sites of various mineral types across southern China. We found that environmental selection was strong in determining the AMD habitat species pool. However, microbial alpha diversity was primarily explained by mining sites rather than environmental factors, and microbial beta diversity correlated more strongly with geographic than environmental distance at both large and small spatial scales. Particularly, the presence/absence of widespread AMD habitat generalists was only correlated with geographic distance and independent of environmental variation. These distance-decay patterns suggested that spatial processes played a more important role in determining microbial compositional variation across space; which could be explained by the reinforced impacts of dispersal limitation in less fluid, spatially structured sediment habitat with diverse pre-existing communities. In summary, our findings suggested that the deterministic assembling and spatial constraints interact to shape microbial biogeography in AMD sediments; and provided implications that spatial processes should be considered when predicting microbial dynamics in response to severe environmental change across large spatial scales.

Anemochore Seeds Harbor Distinct Fungal and Bacterial Abundance, Composition, and Functional Profiles

Many plants adapted to harsh environments have evolved low seed mass ('light seeds') with specific dispersal strategies, primarily either by wind (anemochory) or water (hydrochory). However, the role of their seed microbiota in their survival, and their seed microbial abundance and structure, remain insufficiently studied. Herein, we studied the light seed microbiome of eight anemochores and two hydrochores (as controls) collected from four provinces in China, using qPCR and metagenomic sequencing targeting both bacteria and fungi. Substantial variations were found for seed endophytic fungi (9.9 × 1010~7.3 × 102 gene copy numbers per seed) and bacteria (1.7 × 1010~8.0 × 106). Seed microbial diversity and structure were mainly driven by the plant genotype (species), with weak influences from their host plant classification level or dispersal mode. Seed microbial composition differences were clear at the microbial phylum level, with dominant proportions (~75%) for Proteobacteria and Ascomycota. The light seeds studied harbored unique microbial signatures, sharing only two Halomonas amplicon sequence variants (ASVs) and two fungal ASVs affiliated to Alternaria and Cladosporium. A genome-level functional profile analysis revealed that seed bacterial microbiota were enriched in amino acid, nucleoside, and nucleotide biosynthesis, while in fungal communities the generation of precursor metabolites and respiration were more highly represented. Together, these novel insights provide a deeper understanding of highly diversified plant-specific light seed microbiota and ecological strategies for plants in harsh environments.

Effects of environmental factors on soil bacterial community structure and diversity in different contaminated districts of Southwest China mine tailings

A mass of tailings left by mineral exploitation have caused serious environmental pollution. Although many studies have shown that soil microorganisms have the potential to remediate environmental pollution, the interaction mechanism between microorganisms and the surrounding environment of tailings is still unclear. In this study, 15 samples around pyrite mine tailing were collected to explore the ecological effects of environmental factors on bacterial community. The results showed that most of the samples were acidic and contaminated by multiple metals. Cadmium (Cd), copper (Cu), nickel (Ni) migrated and accumulated to into downstream farmlands while chromium (Cr) was the opposite. Proteobacteria, Chloroflex and Actinobacteria were the dominant phyla. Soil pH, total phosphorus (TP), total nitrogen (TN), available potassium (AK), available phosphorus (AP), the bacteria abundance and diversity all gradually increased with the increase of the distance from the tailing. Invertase, acid phosphatase, total organic carbon (TOC), pH, TP and Cr were the main influencing factors to cause the variation of bacterial community. This work could help us to further understand the changes in soil microbial communities around pollution sources.

Composition and Functional Characteristics and Influencing Factors of Bacterioplankton Community in the Huangshui River, China

Bacterial community plays a key role in environmental and ecological processes of river ecosystems. Given the special climatic and geographical conditions, studying the compositional characteristics of microorganisms in highland rivers and the relationship between such microorganisms and water physicochemical factors is important for an in-depth understanding of microbial ecological mechanisms. In the present study, high-throughput sequencing was used to investigate and study the bacterioplankton community of the Huangshui River in the ecotone zone of the Qinghai Plateau and Loess Plateau. The results showed that the Huangshui River had significantly lower alpha diversity than the plain rivers. Despite the similarity in their environmental conditions, the main taxonomic compositions of the bacterial communities were distinct between the Huangshui River and polar regions (the Arctic and Antarctica). Proteobacteria accounted for the largest proportion (30.79–99.98%) of all the sequences, followed by Firmicutes (0–49.38%). Acidiphilium was the most numerous genera, which accounted for 0.03–86.16% of the assigned 16S reads, followed by Acidocella (0–95.9%), both belonging to Alphaproteobacteria. The diverse taxa of potential pathogens, such as Acinetobacter, Pseudomonas, and Aeromonas, were also identified. A principal coordinates analysis, coupled with a canonical correspondence analysis, showed spatial variations in the bacterial community composition. The water physical properties (e.g., Cr⁶⁺, total phosphorus, and COD_Mn); altitude; and land use (e.g., urban land cover and aquaculture) determined the distribution of the bacterioplankton composition. PICRUSt2 revealed that the overall functional profiles of the bacterial communities in different samples were similar, and our results suggested the potential health risks of water sources in this area. This work provided valuable insight into the composition of the plankton bacterial community and its relationship with the environmental factors in the Huangshui River in the ecotone zone of the Qinghai Plateau and Loess Plateau and a theoretical foundation for ecological health management.

Microbial Community Diversity Dynamics in Acid Mine Drainage and Acid Mine Drainage-Polluted Soils: Implication on Mining Water Irrigation Agricultural Sustainability

Environmental degradation related to mining-generated acid mine drainage (AMD) is a major global concern, contaminating surface and groundwater sources, including agricultural land. In the last two decades, many developing countries are expanding agricultural productivity in mine-impacted soils to meet food demand for their rapidly growing population. Further, the practice of AMD water (treated or untreated) irrigated agriculture is on the increase, particularly in water-stressed nations around the world. For sustainable agricultural production systems, optimal microbial diversity, and functioning is critical for soil health and plant productivity. Thus, this review presents up-to-date knowledge on the microbial structure and functional dynamics of AMD habitats and AMD-impacted agricultural soils. The long-term effects of AMD water such as soil acidification, heavy metals (HM), iron and sulfate pollution, greatly reduces microbial biomass, richness, and diversity, impairing soil health plant growth and productivity, and impacts food safety negatively. Despite these drawbacks, AMD-impacted habitats are unique ecological niches for novel acidophilic, HM, and sulfate-adapted microbial phylotypes that might be beneficial to optimal plant growth and productivity and bioremediation of polluted agricultural soils. This review has also highlighted the impact active and passive treatment technologies on AMD microbial diversity, further extending the discussion on the interrelated microbial diversity, and beneficial functions such as metal bioremediation, acidity neutralization, symbiotic rhizomicrobiome assembly, and plant growth promotion, sulfates/iron reduction, and biogeochemical N and C recycling under AMD-impacted environment. The significance of sulfur-reducing bacteria (SRB), iron-oxidizing bacteria (FeOB), and plant growth promoting rhizobacteria (PGPRs) as key players in many passive and active systems dedicated to bioremediation and microbe-assisted phytoremediation is also elucidated and discussed. Finally, new perspectives on the need for future studies, integrating meta-omics and process engineering on AMD-impacted microbiomes, key to designing and optimizing of robust active and passive bioremediation of AMD-water before application to agricultural production is proposed.

Linking population dynamics to microbial kinetics for hybrid modeling of bioelectrochemical systems

Mechanistic and data-driven models have been developed to provide predictive insights into the design and optimization of engineered bioprocesses. These two modeling strategies can be combined to form hybrid models to address the issues of parameter identifiability and prediction interpretability. Herein, we developed a novel and robust hybrid modeling strategy by incorporating microbial population dynamics into model construction. The hybrid model was constructed using bioelectrochemical systems (BES) as a platform system. We collected 77 samples from 13 publications, in which the BES were operated under diverse conditions, and performed holistic processing of the 16S rRNA amplicon sequencing data. Community analysis revealed core populations composed of putative electroactive taxa Geobacter, Desulfovibrio, Pseudomonas, and Acinetobacter. Primary Bayesian networks were trained with the core populations and environmental parameters, and directed Bayesian networks were trained by defining the operating parameters to improve the prediction interpretability. Both networks were validated with Bray-Curtis similarly, relative root-mean-square error (RMSE), and a null model. A hybrid model was developed by first building a three-population mechanistic component and subsequently feeding the estimated microbial kinetic parameters into network training. The hybrid model generated a simulated community that shared a Bray-Curtis similarity of 72% with the actual microbial community at the genus level and an average relative RMSE of 7% for individual taxa. When examined with additional samples that were not included in network training, the hybrid model achieved accurate prediction of current production with a relative error-based RMSE of 0.8 and outperformed the data-driven models. The genomics-enabled hybrid modeling strategy represents a significant step toward robust simulation of a variety of engineered bioprocesses.

Tree diversity and soil chemical properties drive the linkages between soil microbial community and ecosystem functioning

Microbial respiration is critical for soil carbon balance and ecosystem functioning. Previous studies suggest that plant diversity influences soil microbial communities and their respiration. Yet, the linkages between tree diversity, microbial biomass, microbial diversity, and microbial functioning have rarely been explored. In this study, we measured two microbial functions (microbial physiological potential, and microbial respiration), together with microbial biomass, microbial taxonomic and functional profiles, and soil chemical properties in a tree diversity experiment in South China, to disentangle how tree diversity affects microbial respiration through the modifications of the microbial community. Our analyses show a significant positive effect of tree diversity on microbial biomass (+25% from monocultures to 24-species plots), bacterial diversity (+12%), and physiological potential (+12%). In addition, microbial biomass and physiological potential, but not microbial diversity, were identified as the key drivers of microbial respiration. Although soil chemical properties strongly modulated soil microbial community, tree diversity increased soil microbial respiration by increasing microbial biomass rather than changing microbial taxonomic or functional diversity. Overall, our findings suggest a prevalence of microbial biomass over diversity in controlling soil carbon dynamics.

High arsenic levels increase activity rather than diversity or abundance of arsenic metabolism genes in paddy soils

Arsenic (As) metabolism genes are generally present in soils but their diversity, relative abundance, and transcriptional activity in response to different As concentrations remain unclear, limiting our understanding of the microbial activities that control the fate of an important environmental pollutant. To address this issue, we applied metagenomics and metatranscriptomics to paddy soils showing a gradient of As concentrations to investigate As resistance genes (ars) including arsR, acr3, arsB, arsC, arsM, arsI, arsP, and arsH as well as energy-generating As respiratory oxidation (aioA) and reduction (arrA) genes. Somewhat unexpectedly, the relative DNA abundances and diversity of ars, aioA, and arrA genes were not significantly different between low and high (∼10 vs ∼100 mg kg^-1) As soils. By comparison to available metagenomes from other soils, geographic distance rather than As levels drove the different compositions of microbial communities. Arsenic significantly increased ars genes abundance only when its concentration was higher than 410 mg kg^-1. In contrast, between low and high As soils, metatranscriptomics revealed a significant increase in transcription of ars and aioA genes, which are induced by arsenite, the dominant As species in paddy soils, but not arrA genes, which are induced by arsenate. These patterns appeared to be community-wide as opposed to taxon-specific. Collectively, our findings advance understanding of how microbes respond to high As levels and the diversity of As metabolism genes in paddy soils and indicated that future studies of As metabolism in soil, or other environments, should include the function (transcriptome) level. IMPORTANCE Arsenic (As) is a toxic metalloid pervasively present in the environment. Microorganisms have evolved the capacity to metabolize As, and As metabolism genes are ubiquitously present in the environment even in the absence of high concentrations of As. However, these previous studies were carried out at the DNA level and thus, the activity of the As metabolism genes detected remains essentially speculative. Here, we show that the high As levels in paddy soils increased the transcriptional activity rather than the relative DNA abundance and diversity of As metabolism genes. These findings advance our understanding of how microbes respond to and cope with high As levels and have implications for better monitoring and managing an important toxic metalloid in agricultural soils and possibly other ecosystems.

Effect of different types of anthropogenic pollution on the bacterial community of urban rivers

The health of urban rivers is threatened by multiple anthropogenic stressors. Bacterial communities in rivers can quickly respond to different types of polluted environments, making them useful for water quality assessments and predictive insights. However, research on river bacterial communities has largely ignored interactions between these communities. Here, 16S rRNA amplicon sequencing analysis is used to comprehensively analyze the bacterial communities in the water and sediments in different types of anthropogenically impacted urban river. The results show that distinct differences occur in the bacterial communities in the river sediment and water with different pollution types. The changes in the bacterial communities in sediments were more pronounced than those in the water. A modular analysis further showed that the microbial co-occurrence network under different types of pollution had a nonrandom modular structure, and this structure was mainly driven by classification correlation and bacterial function. Genes identified for nitrogen cycling in all the river water and sediment samples included major functional genes for nitrogen fixation, assimilatory nitrogen reduction, nitrification, denitrification, and ammonification. Carbon degradation genes were mainly observed in the carbon cycle. Taken together, the above findings provide further insights into microbial communities in urban river ecosystems under anthropogenic contamination. PRACTITIONER POINTS: The physical and chemical indicators of the four types of pollution drive bacterial community structure. Bacterial community has C, N, P metabolic genes indicating its ecological effect. River bacteria were connected more frequently in the same or similar type of pollution in the co-occurrence network. Microbe-environment correlations and microbe-microbe interactions were combined to determine crucial indicators.

Disentangling the syntrophic electron transfer mechanisms of Candidatus geobacter eutrophica through electrochemical stimulation and machine learning

Interspecies hydrogen transfer (IHT) and direct interspecies electron transfer (DIET) are two syntrophy models for methanogenesis. Their relative importance in methanogenic environments is still unclear. Our recent discovery of a novel species Candidatus Geobacter eutrophica with the genetic potential of IHT and DIET may serve as a model species to address this knowledge gap. To experimentally demonstrate its DIET ability, we performed electrochemical enrichment of Ca. G. eutrophica-dominating communities under 0 and 0.4 V vs. Ag/AgCl based on the presumption that DIET and extracellular electron transfer (EET) share similar metabolic pathways. After three batches of enrichment, Geobacter OTU650, which was phylogenetically close to Ca. G. eutrophica, was outcompeted in the control but remained abundant and active under electrochemical stimulation, indicating Ca. G. eutrophica's EET ability. The high-quality draft genome further showed high phylogenomic similarity with Ca. G. eutrophica, and the genes encoding outer membrane cytochromes and enzymes for hydrogen metabolism were actively expressed. A Bayesian network was trained with the genes encoding enzymes for alcohol metabolism, hydrogen metabolism, EET, and methanogenesis from dominant fermentative bacteria, Geobacter, and Methanobacterium. Methane production could not be accurately predicted when the genes for IHT were in silico knocked out, inferring its more important role in methanogenesis. The genomics-enabled machine learning modeling approach can provide predictive insights into the importance of IHT and DIET.

Remediation Techniques for Cadmium-Contaminated Dredged River Sediments after Land Disposal

This paper examines the remediation techniques of cadmium (Cd)-contaminated dredged river sediments after land disposal in a city in East China. Three remediation techniques, including stabilization, soil leaching, and phytoremediation, are compared by analyzing the performance of the techniques for Cd-contaminated soil remediation. The experimental results showed that the stabilization technique reduced the leaching rate of soil Cd from 33.3% to 14.3%, thus effectively reducing the biological toxicity of environmental Cd, but the total amount of Cd in soil did not decrease. Leaching soil with citric acid and oxalic acid achieved Cd removal rates of 90.1% and 92.4%, respectively. Compared with these two remediation techniques, phytoremediation was more efficient and easier to implement and had less secondary pollution, but it took more time, usually several years. In this study, these three remediation techniques were analyzed and discussed from technical, economic, and environmental safety perspectives by comprehensively considering the current status and future plans of the study site. Soil leaching was found to be the best technique for timely treatment of Cd contamination in dredged river sediments after land disposal.

High-throughput molecular analyses of microbiomes as a tool to monitor the wellbeing of aquatic environments

Aquatic environments are the recipients of many sources of environmental stress that trigger both local and global changes. To evaluate the associated risks to organisms and ecosystems more sensitive and accurate strategies are required. The analysis of the microbiome is one of the most promising candidates for environmental diagnosis of aquatic systems. Culture-independent interconnected meta-omic approaches are being increasing used to fill the gaps that classical microbial approaches cannot resolve. Here, we provide a prospective view of the increasing application of these high-throughput molecular technologies to evaluate the structure and functional activity of microbial communities in response to changes and disturbances in the environment, mostly of anthropogenic origin. Some relevant topics are reviewed, such as: (i) the use of microorganisms for water quality assessment, highlighting the incidence of antimicrobial resistance as an increasingly serious threat to global public health; (ii) the crucial role of microorganisms and their complex relationships with the ongoing climate change, and other stress threats; (iii) the responses of the environmental microbiome to extreme pollution conditions, such as acid mine drainage or oil spills. Moreover, protists and viruses, due to their huge impacts on the structure of microbial communities, are emerging candidates for the assessment of aquatic environmental health.

Spatio-temporal resolution of taxonomic and functional microbiome of Lonar soda lake of India reveals metabolic potential for bioremediation

Lonar Lake, India; a hypersaline and hyperalkaline extremophilic ecosystem having a unique microbial population has been rarely explored for bioremediation aspects. MinION-based shotgun sequencing was used to comprehensively compare the microbial diversity and functional potential of xenobiotic degradation pathways with seasonal changes. Proteobacteria and Firmicutes were prevalent bacterial phyla in the pre-monsoon and post-monsoon samples. Functional analysis from SEED-subsystem and KEGG database revealed 28 subsystems and 18 metabolic pathways for the metabolism of aromatic compounds and xenobiotic biodegradation respectively. Occurrence of N-phenyl alkanoic, benzoate, biphenyl, chloroaromatic, naphthalene, and phenol degradation genes depicted varied abundance in the pre-monsoon and post-monsoon samples. Further, KEGG analysis indicated nitrotoluene degradation pathway (ko00633) abundant in post-monsoon samples, and the benzoate degradation pathway (ko00362) predominant in 19LN4S (pre-monsoon) than 18LN7S (post-monsoon) samples. The abundant genes for benzoate degradation were pcaI: 3-oxoadipate CoA-transferase, alpha subunit, pcaH: protocatechuate 3,4-dioxygenase, beta subunit, and pcaB: 3-carboxy-cis, cis-muconate cycloisomerase, and 4-oxalocrotonate tautomerase. This metagenomic study provides a unique blueprint of hitherto unexplored xenobiotic biodegradation genes/pathways in terms of seasonal variations in the Lonar Lake, and warrants active exploitation of microbes for bioremediation purposes.

Metagenomic Approaches to Analyze Antimicrobial Resistance: An Overview

Antimicrobial resistance is a major global public health problem, which develops when pathogens acquire antimicrobial resistance genes (ARGs), primarily through genetic recombination between commensal and pathogenic microbes. The resistome is a collection of all ARGs. In microorganisms, the primary method of ARG acquisition is horizontal gene transfer (HGT). Thus, understanding and identifying HGTs, can provide insight into the mechanisms of antimicrobial resistance transmission and dissemination. The use of high-throughput sequencing technologies has made the analysis of ARG sequences feasible and accessible. In particular, the metagenomic approach has facilitated the identification of community-based antimicrobial resistance. This approach is useful, as it allows access to the genomic data in an environmental sample without the need to isolate and culture microorganisms prior to analysis. Here, we aimed to reflect on the challenges of analyzing metagenomic data in the three main approaches for studying antimicrobial resistance: (i) analysis of microbial diversity, (ii) functional gene analysis, and (iii) searching the most complete and pertinent resistome databases.

Enhanced Metabolic Potentials and Functional Gene Interactions of Microbial Stress Responses to a 4,100-m Elevational Increase in Freshwater Lakes

Elevation has a strong influence on microbial community composition, but its influence on microbial functional genes remains unclear in the aquatic ecosystem. In this study, the functional gene structure of microbes in two lakes at low elevation (ca. 530 m) and two lakes at high elevation (ca. 4,600 m) was examined using a comprehensive functional gene array GeoChip 5.0. Microbial functional composition, but not functional gene richness, was significantly different between the low- and high-elevation lakes. The greatest difference was that microbial communities from high-elevation lakes were enriched in functional genes of stress responses, including cold shock, oxygen limitation, osmotic stress, nitrogen limitation, phosphate limitation, glucose limitation, radiation stress, heat shock, protein stress, and sigma factor genes compared with microbial communities from the low-elevation lakes. Higher metabolic potentials were also observed in the degradation of aromatic compounds, chitin, cellulose, and hemicellulose at higher elevations. Only one phytate degradation gene and one nitrate reduction gene were enriched in the high-elevation lakes. Furthermore, the enhanced interactions and complexity among the co-occurring functional genes in microbial communities of lakes at high elevations were revealed in terms of network size, links, connectivity, and clustering coefficients, and there were more functional genes of stress responses mediating the module hub of this network. The findings of this study highlight the well-developed functional strategies utilized by aquatic microbial communities to withstand the harsh conditions at high elevations.

Revegetation approach and plant identity unequally affect structure, ecological network and function of soil microbial community in a highly acidified mine tailings pond

Owing to its sustainability and low cost, direct revegetation (DR) has been considered a promising alternative to capped revegetation (CR) for dealing with the serious environmental problem derived from various types of mine wastelands that are widespread in the world. However, a direct comparison of the performance of these two revegetation approaches for reclamation of extremely acidic mine wastelands and the underlying mechanisms is still lacking. To bridge this critical knowledge gap, we established 5000 m² of vegetation on a highly acidified (pH < 3) Pb/Zn mine tailings pond employing both CR and DR schemes (2500 m² for each scheme). We then profiled the structure, ecological network and function of soil microbial communities associated with two dominant plant species of the vegetations via high-throughput sequencing. Our results showed that CR and DR achieved a vegetation coverage of 59.7% and 90.5% within two years, respectively. This pattern was accompanied by higher concentrations of plant nutrients and lower acidification potentials in topsoils of the rhizospheres of the vegetation established by DR compared to those of CR. Revegetation approach, rather than plant identity, mostly affected the structure, ecological network and function of soil microbial community in the mine tailings pond. Rhizosphere soils of the vegetation established by DR generally had higher microbial diversity, higher relative abundances of dominant microbial phyla (e.g. Nitrospirae) that can aid plant uptake of nutrients, more complicated microbial interactive networks and more microbial genes responsible for nutrient cycling than those by CR. As the first report on a direct comparison of CR and DR schemes for reclamation of an extremely acidic mine wasteland, our study has important implications for not only the understanding of microbial ecology in revegetated mine wastelands but also the further development of sustainable revegetation schemes.

Insights into the Metabolism and Evolution of the Genus Acidiphilium, a Typical Acidophile in Acid Mine Drainage

Here, we report three new Acidiphilium genomes, reclassified existing Acidiphilium species, and performed the first comparative genomic analysis on Acidiphilium in an attempt to address the metabolic potential, ecological functions, and evolutionary history of the genus Acidiphilium In the genomes of Acidiphilium, we found an abundant repertoire of horizontally transferred genes (HTGs) contributing to environmental adaption and metabolic expansion, including genes conferring photosynthesis (puf, puh), CO2 assimilation (rbc), capacity for methane metabolism (mmo, mdh, frm), nitrogen source utilization (nar, cyn, hmp), sulfur compound utilization (sox, psr, sqr), and multiple metal and osmotic stress resistance capacities (czc, cop, ect). Additionally, the predicted donors of horizontal gene transfer were present in a cooccurrence network of Acidiphilium Genome-scale positive selection analysis revealed that 15 genes contained adaptive mutations, most of which were multifunctional and played critical roles in the survival of extreme conditions. We proposed that Acidiphilium originated in mild conditions and adapted to extreme environments such as acidic mineral sites after the acquisition of many essential functions.IMPORTANCE Extremophiles, organisms that thrive in extreme environments, are key models for research on biological adaption. They can provide hints for the origin and evolution of life, as well as improve the understanding of biogeochemical cycling of elements. Extremely acidophilic bacteria such as Acidiphilium are widespread in acid mine drainage (AMD) systems, but the metabolic potential, ecological functions, and evolutionary history of this genus are still ambiguous. Here, we sequenced the genomes of three new Acidiphilium strains and performed comparative genomic analysis on this extremely acidophilic bacterial genus. We found in the genomes of Acidiphilium an abundant repertoire of horizontally transferred genes (HTGs) contributing to environmental adaption and metabolic ability expansion, as indicated by phylogenetic reconstruction and gene context comparison. This study has advanced our understanding of microbial evolution and biogeochemical cycling in extreme niches.

Sediment Bacterial Community Structure Under the Influence of Different Domestic Sewage Types

Sediment bacterial communities are critical to the biogeochemical cycle in river ecosystems, but our understanding of the relationship between sediment bacterial communities and their specific input streams in rivers remains insufficient. In this study, we analyzed the sediment bacterial community structure in a local river receiving discharge of urban domestic sewage by applying Illumina MiSeq high-throughput sequencing. The results showed that the bacterial communities of sediments samples of different pollution types had similar dominant phyla, mainly Proteobacteria, Actinobacteria, Chloroflexi and Firmicutes, but their relative abundances were different. Moreover, there were great differences at the genus level. For example, the genus Bacillus showed statistically significant differences in the hotel site. The clustering of bacterial communities at various sites and the dominant families (i.e., Nocardioidaceae, and Sphingomonadaceae) observed in the residential quarter differed from other sites. This result suggested that environmentally induced species sorting greatly influenced the sediment bacterial community composition. The bacterial cooccurrence patterns showed that the river bacteria had a nonrandom modular structure. Microbial taxonomy from the same module had strong ecological links (such as the nitrogenium cycle and degradation of organic pollutants). Additionally, PICRUSt metabolic inference analysis showed the most important function of river bacterial communities under the influence of different types of domestic sewage was metabolism (e.g., genes related to xenobiotic degradation predominated in residential quarter samples). In general, our results emphasize that the adaptive changes and interactions in the bacterial community structure of river sediment represent responses to different exogenous pollution sources.

Impact of long-term industrial contamination on the bacterial communities in urban river sediments

BACKGROUND

The contamination of the aquatic environment of urban rivers with industrial wastewater has affected the abiotic conditions and biological activities of the trophic levels of the ecosystem, particularly sediments. However, most current research about microorganism in urban aquatic environments has focused on indicator bacteria related to feces and organic pollution. Meanwhile, they ignored the interactions among microorganisms. To deeply understand the impact of industrial contamination on microbial community, we study the bacterial community structure and diversity in river sediments under the influence of different types of industrial pollution by Illumina MiSeq high-throughput sequencing technology and conduct a more detailed analysis of microbial community structure through co-occurrence networks.

RESULTS

The overall community composition and abundance of individual bacterial groups differed between samples. In addition, redundancy analysis indicated that the structure of the bacterial community in river sediments was influenced by a variety of environmental factors. TN, TP, TOC and metals (Cu, Zn and Cd) were the most important driving factors that determined the bacterial community in urban river sediments (P < 0.01). According to PICRUSt analysis, the bacterial communities in different locations had similar overall functional profiles. It is worth noting that the 15 functional genes related to xenobiotics biodegradation and metabolism were the most abundant in the same location. The non-random assembly patterns of bacterial composition in different types of industrially polluted sediments were determined by a co-occurrence network. Environmental conditions resulting from different industrial pollutants may play an important role in determining their co-occurrence patterns of these bacterial taxa. Among them, the bacterial taxa involved in carbon and nitrogen cycles in module I were relatively abundant, and the bacterial taxa in module II were involved in the repair of metal pollution.

CONCLUSIONS

Our data indicate that long-term potential interactions between different types of industrial pollution and taxa collectively affect the structure of the bacterial community in urban river sediments.

Characterization of an acid rock drainage microbiome and transcriptome at the Ely Copper Mine Superfund site

The microbial oxidation of metal sulfides plays a major role in the formation of acid rock drainage (ARD). We aimed to broadly characterize the ARD at Ely Brook, which drains the Ely Copper Mine Superfund site in Vermont, USA, using metagenomics and metatranscriptomics to assess the metabolic potential and seasonal ecological roles of microorganisms in water and sediment. Using Centrifuge against the NCBI "nt" database, ~25% of reads in sediment and water samples were classified as acid-tolerant Proteobacteria (61 ± 4%) belonging to the genera Pseudomonas (2.6-3.3%), Bradyrhizobium (1.7-4.1%), and Streptomyces (2.9-5.0%). Numerous genes (12%) were differentially expressed between seasons and played significant roles in iron, sulfur, carbon, and nitrogen cycling. The most abundant RNA transcript encoded the multidrug resistance protein Stp, and most expressed KEGG-annotated transcripts were involved in amino acid metabolism. Biosynthetic gene clusters involved in secondary metabolism (BGCs, 449) as well as metal- (133) and antibiotic-resistance (8501) genes were identified across the entire dataset. Several antibiotic and metal resistance genes were colocalized and coexpressed with putative BGCs, providing insight into the protective roles of the molecules BGCs produce. Our study shows that ecological stimuli, such as metal concentrations and seasonal variations, can drive ARD taxa to produce novel bioactive metabolites.

Bacterial community responses to tourism development in the Xixi National Wetland Park, China

A large number of urban wetland parks have been established, but knowledge about the effects of tourism development on the microbial diversity and ecosystem functioning remains limited. This study aimed to clarify the responses of bacterial communities to tourism development targeted the Xixi National Wetland Park, China. By analyzing the diversity, composition, assembly pattern, and environmental drivers of bacterial communities, we found that tourism development considerably affected the water quality, which further decreased the α-diversity but increased the β-diversity in open areas for landscaping and recreation. Specifically, there was higher Simpson dissimilarity across functional wetland areas, indicating that species replacement mainly explained β-diversity patterns of bacterial communities. RDA analysis and ecological processes quantification further suggested that TOC and TC were the major factors in the open areas driving bacterial communities in water and sediment, respectively. Also, typical anti-disturbance taxa (Gammaproteobacteria) and potential pathogens (Bacillus) were enriched in the wetlands under more anthropogenic disturbances. Findings of the present study highlighted the effects of tourism development on bacterial communities resulted in obvious spatial variation in the Xixi National Wetland Park. This study gives us useful information for ecological assessments of urban wetlands, and further can provide references in making appropriate strategies to manage wetland ecosystems.

Bacterial community composition and potential pathogens along the Pinheiros River in the southeast of Brazil

The Pinheiros River in São Paulo, Brazil, crosses through the capital city and has its confluence with the River Tiete, which comprises several reservoirs along its course. Although Pinheiros River is considered one of the heaviest polluted rivers in Brazil, little is known about its bacterial composition, their metabolic functions or how these communities are affected by the physicochemical parameters of the river. In this study, we used the 16S rRNA gene Illumina MiSeq sequencing to profile the bacterial community from the water surface at 11 points along the course of the River. Taxonomical composition revealed an abundance of Proteobacteria phyla, followed by Firmicutes and Bacteroidetes, with a total of 233 classified bacterial families and 558 known bacterial genera. Among the 35 potentially pathogenic bacteria identified, Arcobacter was the most predominant genus. The disrupted physicochemical parameters detected in this study may possibly contribute to the composition and distribution of the bacterial community in the Pinheiros River. Predictive functional analysis suggests the River is abundant in motility genes, including bacterial chemotaxis and flagellar assembly. These results provide novel and detailed insights into the bacterial communities and putative function of the surface water in the Pinheiros River.

Uncovering microbial responses to sharp geochemical gradients in a terrace contaminated by acid mine drainage

Acid mine drainage (AMD) is harmful to the environment and human health. Microorganisms-mineral interactions are responsible for AMD generation but can also remediate AMD contamination. Understanding the microbial response to AMD irrigation will reveal microbial survival strategies and provide approaches for AMD remediation. A terrace with sharp geochemical gradients caused by AMD flooding were selected to study the microbial response to changes in environmental parameters related to AMD contamination. AMD intrusion reduced soil microbial community diversity and further changed phylogenetic clustering patterns along the terrace gradient. We observed several genera seldom reported in AMD-related environments (i.e., Corynebacterium, Ochrobactrum, Natronomonas), suggesting flexible survival strategies such as nitrogen fixation, despite the poor nutritional environment. A co-occurrence network of heavily-contaminated fields was densely connected. The phyla Proteobacteria, Acidobacteria, Chloroflexi, and Euryarchaeota were all highly interconnected members, which may affect the formation of AMD. Detailed microbial response to different soil characterizations were highlighted by random forest model. Results revealed the top three parameters influencing the microbial diversity and interactions were pH, Fe(III), and sulfate. Various acidophilic Fe- and S-metabolizing bacteria were enriched in the lower fields, which were heavily contaminated by AMD, and more neutrophiles prevailed in the less-contaminated upper fields. Many indicator species in the lower fields were identified, including Desulfosporosinus, Thermogymnomonas, Corynebacterium, Shewanella, Acidiphilium, Ochrobactrum, Leptospirillum, and Allobaculum, representing acid-tolerant bacteria community in relevant environment. The detection of one known sulfate-reducing bacteria (i.e., Desulfosporosinus) suggested that biotic sulfate reduction may occur in acidic samples, which offers multiple advantages to AMD contamination treatment. Collectively, results suggested that the geochemical gradients substantially altered the soil microbiota and enriched the relevant microorganisms adapted to the different conditions. These findings provide mechanistic insights into the effects of contamination on the soil microbiota and establish a basis for in situ AMD bioremediation strategies.

Ferric Uptake Regulator Provides a New Strategy for Acidophile Adaptation to Acidic Ecosystems

Acidophiles play a dominant role in driving elemental cycling in natural acid mine drainage (AMD) habitats and exhibit important application value in bioleaching and bioremediation. Acidity is an inevitable environmental stress and a key factor that affects the survival of acidophiles in their acidified natural habitats; however, the regulatory strategies applied by acidophilic bacteria to withstand low pH are unclear. We identified the significance of the ferric uptake regulator (Fur) in acidophiles adapting to acidic environments and discovered that Fur is ubiquitous as well as highly conserved in acidophilic bacteria. Mutagenesis of the fur gene of Acidithiobacillus caldus, a prototypical acidophilic sulfur-oxidizing bacterium found in AMD, revealed that Fur is required for the acid resistance of this acidophilic bacterium. Phenotypic characterization, transcriptome sequencing (RNA-seq), mutagenesis, and biochemical assays indicated that the Acidithiobacillus caldus ferric uptake regulator (AcFur) is involved in extreme acid resistance by regulating the expression of several key genes of certain cellular activities, such as iron transport, biofilm formation, sulfur metabolism, chemotaxis, and flagellar biosynthesis. Finally, a Fur-dependent acid resistance regulatory strategy in A. caldus was proposed to illustrate the ecological behavior of acidophilic bacteria under low pH. This study provides new insights into the adaptation strategies of acidophiles to AMD ecosystems and will promote the design and development of engineered biological systems for the environmental adaptation of acidophiles.IMPORTANCE This study advances our understanding of the acid tolerance mechanism of A. caldus, identifies the key fur gene responsible for acid resistance, and elucidates the correlation between fur and acid resistance, thus contributing to an understanding of the ecological behavior of acidophilic bacteria. These findings provide new insights into the acid resistance process in Acidithiobacillus species, thereby promoting the study of the environmental adaptation of acidophilic bacteria and the design of engineered biological systems.

Potential and limitations of a pilot-scale drinking water distribution system for bacterial community predictive modelling

Waterborne disease outbreaks are a persistent and serious threat to public health according to reported incidents across the globe. Online drinking water quality monitoring technologies have evolved substantially and have become more accurate and accessible. However, using online measurements alone is unsuitable for detecting microbial regrowth, potentially including harmful species, ahead of time in the distribution systems. Alternatively, observational data could be collected periodically, e.g. once per week or once per month and it could include a representative set of variables: physicochemical water characteristics, disinfectant concentrations, and bacterial abundances, which would be a valuable source of knowledge for predictive modelling that aims to reveal pathogen-related threats. In this study, we utilised data collected from a pilot-scale drinking water distribution system. A data-driven random forest model was used for predictive modelling and was trained for nowcasting and forecasting abundances of bacterial groups. In all the experiments, we followed the realistic crossline scenario, which means that when training and testing the models the data is collected from different pipelines. In spite of the more accurate results of the nowcasting, the 1-week forecasting still provided accurate predictions of the most abundant bacteria, their rapid increase and decrease. In the future predictive modelling might be used as a tool in designing control measures for opportunistic pathogens which are able to multiply in the favourable conditions in drinking water distribution systems (DWDS). Eventually, the forecasting information will be able to produce practically helpful data for controlling the DWDS regrowth.

Nitrogen combined with biochar changed the feedback mechanism between soil nitrification and Cd availability in an acidic soil

Inorganic nitrogen (N) inputs increase soil nitrification, acidification and trace metal toxicity e.g. cadmium (Cd). Biochar (B) has been widely used for metal immobilization. However, little is known about how the combination of N fertilizers with biochar (N-B) changes soil Cd availability through altering nitrification process. Here, (NH₄)₂SO₄ or CO(NH₂)₂ was applied in combination with biochar to an acidic, artificially enriched Cd contaminated soil. Not as we expected, available Cd did not increase following (NH₄)₂SO₄ or CO(NH₂)₂ addition. Nitrification and acidification of Cd contaminated soils were greatly inhibited, accompanied by elimination of ammonia-oxidizing bacteria (AOB). Exchangeable H⁺ of Cd contaminated soils was significantly lower than that of uncontaminated soils, thus inhibiting Cd itself from mobilization. N-B addition nearly halved soil available Cd and significantly increased nitrification by promoting AOB recovery. However, the restored nitrification did not cause soil acidification, due to the high buffering and slow liming effects of biochar. Available Cd continuously decreased with decreasing soil acidity and exchangeable Al. This study firstly demonstrated a feedback between soil nitrification and Cd after N application, and how biochar modified the feedback. Biochar, therefore, provides a feasible strategy for eliminating potential Cd toxicity on both soil biological and chemical processes.

Acid mine drainage in an Indian high-sulfur coal mining area: Cytotoxicity assay and remediation study

Opencast mining causes significant environmental concern due to acid mine drainage (AMD) caused by the oxidation of pyrites and other sulfur-bearing minerals. The present study intends to determine the seasonal variability of AMD in the affected area of the Ledo opencast mining, the cytotoxicity of the AMD, and the AMD remediation process. The physicochemical properties of the collected samples were analyzed by using laboratory-based methods and sophisticated instrumental tools. The cytotoxicity study of AMD water was performed by using different cell lines such as normal rat muscle and human carcinoma cells. The study demonstrates that the mine water samples have high conductivity (1.30-2.49 ms cm^-1) with high total dissolved solids (1068-1339 ppm) which can change the ionic composition of water. The concentration level of trace elements are also found to be higher than the permissible limit during monsoon season. A simple laboratory-based remediation process of AMD has been carried out in the current study by using size segregated pulverized limestone and the process reveals the decrease in elemental concentrations of AMD water. This study will be useful to develop a remediation technique to minimize the concentration levels of hazardous elements and ions in the AMD water.

Integrating high-throughput sequencing and metagenome analysis to reveal the characteristic and resistance mechanism of microbial community in metal contaminated sediments

Some metallic tailings from closed mines were scattered in upstream of the Miyun Reservoir, Beijing, threatening the ecological environment of rivers due to trace metals. The Liuli River, one of the main rivers affected, was investigated as a typical model in this work. In this study, we selected eight sites to assess interactions among the various geochemical factors especially between trace metals and sediment microbiota. Random forest predicted that low concentrations of Cu, Cd, Cr and Ni (lower than 61.8 mg/kg, 3.2 mg/kg, 173.2 mg/kg and 34.1 mg/kg, respectively) were able to enhance community diversity but generally, trace metals contamination impaired microbial diversity. Environmental factor correlation analysis showed that As, pH and available P were the major factors that shifted the distribution of the microbial communities. Metagenome sequencing revealed that Proteobacteria harbored the vast majority of heavy metal resistance genes followed by Actinobacteria and Bacteroidetes. Metal tolerance of Proteobacteria were achieved by exportation of metals by the corresponding transporters, by pumps and ion channels, or by their reduction via redox reactions. In addition, Proteobacteria harbored a greater ability to repair DNA damage via DNA recombination.

Metal and organic pollutants bioremediation by extremophile microorganisms

Extremophiles comprise microorganisms that are able to grow and thrive in extreme environments, including in an acidic or alkaline pH, high or low temperatures, high concentrations of pollutants, and salts, among others. These organisms are promising for environmental biotechnology due to their unique physiological and enzymatic characteristics, which allow them to survive in harsh environments. Due to the stability and persistence of these microorganisms under adverse environmental conditions, they can be used for the bioremediation of environments contaminated with extremely recalcitrant pollutants. Here, we provide an overview of extremophiles and the role of "omics" in the field of bioremediation of environmental pollutants, including hydrocarbons, textile dyes and metals.