Pollution Gradients Altered the Bacterial Community Composition and Stochastic Process of Rural Polluted Ponds

Higher diversity of sulfur-oxidizing bacteria based on soxB gene sequencing in surface water than in spring in Wudalianchi volcanic group, NE China

INTRODUCTION

Sulfur-oxidizing bacteria (SOB) play a key role in the biogeochemical cycling of sulfur.

OBJECTIVES

To explore SOB diversity, distribution, and physicochemical drivers in five volcanic lakes and two springs in the Wudalianchi volcanic field, China.

METHODS

This study analyzed microbial communities in samples via high-throughput sequencing of the soxB gene. Physical-chemical parameters were measured, and QIIME 2 (v2019.4), R, Vsearch, MEGA7, and Mothur processed the data. Alpha diversity indices and UPGMA clustering assessed community differences, while heat maps visualized intra-sample variations. Canoco 5.0 analyzed community-environment correlations, and NMDS, Adonis, and PcoA explored sample dissimilarities and environmental factor correlations. SPSS v.18.0 tested for statistical significance.

RESULTS

The diversity of SOB in surface water was higher than in springs (more than 7.27 times). We detected SOB affiliated to β-proteobacteria (72.3 %), α-proteobacteria (22.8 %), and γ-proteobacteria (4.2 %) distributed widely in these lakes and springs. Rhodoferax and Cupriavidus were most frequent in all water samples, while Rhodoferax and Bradyrhizobium are dominant in surface waters but rare in springs. SOB genera in both habitats were positively correlated. Co-occurrence analysis identified Bradyrhizobium, Blastochloris, Methylibium, and Metyhlobacterium as potential keystone taxa. Redundancy analysis (RDA) revealed positive correlations between SOB diversity and total carbon (TC), Fe2+, and total nitrogen (TN) in all water samples.

CONCLUSION

The diversity and community structure of SOB in volcanic lakes and springs in the Wudalianchi volcanic group were clarified. Moreover, the diversity and abundance of SOB decreased with the variation of water openness, from open lakes to semi-enclosed lakes and enclosed lakes.

A comparative genomics study of the microbiome and freshwater resistome in Southern Pantanal

This study explores the resistome and bacterial diversity of two small lakes in the Southern Pantanal, one in Aquidauana sub-region, close to a farm, and one in Abobral sub-region, an environmentally preserved area. Shotgun metagenomic sequencing data from water column samples collected near and far from the floating macrophyte Eichhornia crassipes were used. The Abobral small lake exhibited the highest diversity and abundance of antibiotic resistance genes (ARGs), antibiotic resistance classes (ARGCs), phylum, and genus. RPOB2 and its resistance class, multidrug resistance, were the most abundant ARG and ARGC, respectively. Pseudomonadota was the dominant phylum across all sites, and Streptomyces was the most abundant genus considering all sites.

Evaluating groundwater ecosystem dynamics in response to post in-situ remediation of mixed chlorinated volatile organic compounds (CVOCs): An insight into microbial community resilience, adaptability, and metabolic functionality for sustainable remediation and ecosystem restoration

The in-situ remediation of groundwater contaminated with mixed chlorinated volatile organic compounds (CVOCs) has become a significant global research interest. However, limited attention has been given in understanding the effects of these remediation efforts on the groundwater microbial communities, which are vital for maintaining ecosystem health through their involvement in biogeochemical cycles. Hence, this study aimed to provide valuable insights into the impacts of in-situ remediation methods on groundwater microbial communities and ecosystem functionality, employing high-throughput sequencing coupled with functional and physiological assays. The results showed that both bioremediation and chemical remediation methods adversely affected microbial diversity and abundance compared to non-polluted sites. Certain taxa such as Pseudomonas, Acinetobacter, and Vogesella were sensitive to these remediation methods, while Aquabacterium exhibited greater adaptability. Functional annotation unveiled the beneficial impact of bioremediation on the sulfur cycle and specific taxa such as Cellvibrio, Massilia, Algoriphagus, and Flavobacterium which showed a significant positive relationship with dark oxidation of sulfur compounds. In contrast, chemical remediation showed adverse impacts on the nitrogen cycle with a reduced abundance of nitrogen and nitrate respiration along with a reduced utilization of amines (nitrogen rich substrate). The findings of this study offer valuable insights into the potential impacts of in-situ remediation methods on groundwater microbial communities and ecosystem functionality, emphasizing the need for meticulous consideration to ensure the implementation of effective and sustainable remediation strategies that safeguard ecosystem health and function.

Linking ecological niches to bacterial community structure and assembly in polluted urban aquatic ecosystems

Introduction

Bacterial communities play crucial roles in the functioning and resilience of aquatic ecosystems, and their responses to water pollution may be assessed from ecological niches. However, our understanding of such response patterns and the underlying ecological mechanisms remains limited.

Methods

In this study, we comprehensively investigated the effects of water pollution on the bacterial structure and assembly within different ecological niches, including water, sediment, submerged plant leaf surfaces, and leaf surfaces, using a 16S high-throughput sequencing approach.

Results

Ecological niches had a greater impact on bacterial community diversity than pollution, with a distinct enrichment of unique dominant phyla in different niches. This disparity in diversity extends to the bacterial responses to water pollution, with a general reduction in α-diversity observed in the niches, excluding leaf surfaces. Additionally, the distinct changes in bacterial composition in response to pollution should be correlated with their predicted functions, given the enrichment of functions related to biogeochemical cycling in plant surface niches. Moreover, our study revealed diverse interaction patterns among bacterial communities in different niches, characterized by relatively simply associations in sediments and intricate or interconnected networks in water and plant surfaces. Furthermore, stochastic processes dominated bacterial community assembly in the water column, whereas selective screening of roots and pollution events increased the impact of deterministic processes.

Discussion

Overall, our study emphasizes the importance of ecological niches in shaping bacterial responses to water pollution. These findings improve our understanding of the complicated microbial response patterns to water pollution and have ecological implications for aquatic ecosystem health.

Underpinning the ecological response of mixed chlorinated volatile organic compounds (CVOCs) associated with contaminated and bioremediated groundwaters: A potential nexus of microbial community structure and function for strategizing efficient bioremediation

Understanding the structure, dynamics, and functionality of microbial communities is essential for developing sustainable and effective bioremediation strategies, particularly for sites contaminated with mixed chlorinated volatile organic compounds (CVOCs), which can make the biodegradation process more complex and challenging. In this study, 16S rRNA amplicon sequencing revealed a significant change in microbial distribution in response to CVOCs contamination. The loss of sensitive taxa such as Proteobacteria and Acidobacteriota was observed, while CVOCs-resistant taxa such as Campilobacterota were found significantly enriched in contaminated sites. Additionally, varying abundances of crucial enzymes involved in the sequential biodegradation of CVOCs were expressed depending on the contamination level. Association analysis revealed that specific genera such as Sulfurospirillum, Azospira, Trichlorobacter, Acidiphilium, and Magnetospririllum could relatively survive under higher levels of CVOC contamination, whereas pH, ORP and temperature had a negative influence in their abundance and distribution. However, Dechloromonas, Thiobacillus, Pseudarcicella, Hydrogenophaga, and Sulfuritalea showed a negative relationship with CVOC contamination, highlighting their sensitivity towards CVOC contamination. These findings provide valuable insights into the relationship among ecological responses, the groundwater bacterial community, and their functionality in response to mixed CVOC contamination, offering a fundamental basis for developing effective and sustainable bioremediation strategies for CVOC-contaminated groundwater systems.

Adaptation of rhizosphere bacterial communities of drought-resistant sugarcane varieties under different degrees of drought stress

Sugarcane is highly sensitive to changes in moisture, and increased drought severely restricts its growth and productivity. Recent studies have shown that plant growth-promoting microorganisms are essential to reduce the adverse effects of environmental stresses, especially drought. However, our knowledge about the dynamics of rhizosphere microbial community structure in sugarcane under varying degrees of drought stress is limited. We analyzed the effects of different degrees of drought stress on the rhizosphere microbial communities of Zhongzhe 1(ZZ1) and Zhongzhe 6(ZZ6) with differences in drought resistance, by combining soil enzyme activity, nutrient content, and physiological and morphological characteristics of sugarcane roots. The results showed that rhizosphere bacterial community began to change at a field capacity of 50%, enriching the sugarcane rhizosphere with drought-resistant bacteria. The core strains of ZZ1 and ZZ6 rhizosphere enrichment were mainly Streptomycetales, Sphingomonadales, and Rhizobiales. However, compared to ZZ1, the changes in rhizosphere bacterial abundance in ZZ6 were primarily associated with the abundance of Streptomycetales as drought levels increased. Rhizobiales and Streptomycetales, enriched in the rhizosphere of ZZ6 under drought, were positively correlated with root tip number and total root length (TRL), increasing the distribution area of roots and, thus, improving water and nutrient uptake by the roots thereby enhancing the resistance of sugarcane to drought stress. This research enhances our understanding of the composition of the rhizosphere microbial community in sugarcane under different levels of drought stress and its interaction with the roots, thereby providing valuable insights for enhancing drought resistance in sugarcane. IMPORTANCE Drought stress is expected to further increase in intensity, frequency, and duration, causing substantial losses in sugarcane yields. Here, we exposed sugarcane to varying degrees of drought treatment during growth and quantified the eventual composition of the resulting sugarcane rhizosphere bacterial community groups. We found that sugarcane rhizosphere under mild drought began to recruit specific bacterial communities to resist drought stress and used the interactions of root tip number, total root length, and drought-resistant strains to improve sugarcane survival under drought. This research provides a theoretical basis for the rhizosphere microbiome to help sugarcane improve its resistance under different levels of drought stress.

Distribution and potential ecological risks of microplastics in Zhushan Bay, China

The interaction between microplastics (MPs) and microorganisms may alter the distribution of antibiotic resistance genes (ARGs) in water and increase the ecological risk of drinking water sources. To investigate the characteristics of MPs geographical distribution and its potential ecological risk in typical urban water, this study was conducted in Zhushan Bay, and we carried out a combination of tests to analyze the distribution of MPs and the migration changes of their surface microbial community composition and ARGs in different media by 16S rRNA gene high-throughput sequencing, non-targeted metabolomics and qPCR genomics in the near-shore (I), middle area (Ⅱ) and near-lake (Ⅲ) of Zhushan Bay. The results showed that MPs in fibrous form were dominant in the aquatic environment of Zhushan Bay; Polyurethane (PU) and Silicone were the main MPs types in Zhushan Bay. The abundance of MPs in the water of Zhushan Bay was winter > summer > autumn > spring; and in the sediment was winter > summer > autumn > spring, respectively. The distribution results of MPs in geographical location are as follows: In the water I > Ⅱ > Ⅲ, sediment exhibited Ⅱ > Ⅲ > I. The results indicate that physicochemical factors will affect the geographical distribution of MPs and their surface microbial community composition in the aquatic environment of Zhushan Bay. More cooperative behaviors and increased metabolically important pathways occurred in the microbial network on water-MPs compared to sediment-MPs. However, the microbial community in the sediment-MPs was more stable and had higher abundance of mobile genetic elements (MGEs). A total of 362 differential metabolites were detected, of which 193 were up-regulated and 19 down-regulated differential metabolites. blaTEM, Sul, and inti1 were prevalent in both the water and sediments of Zhushan Bay. Sul1 was most contaminated in ARGs. This study provides the latest field data and insights into MPs pollution in key aquatic environments.

Shifts in the bacterial community caused by combined pollutant loads in the North Canal River, China

A typical anthropogenically disturbed urban river polluted by a combination of conventional pollutants (nitrogen and phosphorus pollution) and heavy metals was investigated along a 238 km stretch. Changes in the bacterial community were evaluated using high-throughput sequencing, and the relationships between bacteria, heavy metals, and conventional pollutants were investigated. There was large spatial heterogeneity in the bacterial community along the river, and bacterial diversity in the upstream and midstream sections was much higher than in the downstream section. Heavy metals and conventional pollutants both exhibited close correlations with bacterial diversity and composition. For instance, potential fecal indicator bacteria, sewage indicator bacteria and pathogenic bacteria, such as Ruminococcus and Pseudomonas, were closely associated with Cu, Zn, and NH₄⁺-N. Rather than conventional pollutants, heavy metals were the main driving factors of the microbial community characteristics. These results confirm that bacterial communities play a crucial role in biogeochemical cycles. Therefore, heavy metals could be used as biomarkers of complex pollution to indicate the pollution status of riverine ecosystems and contribute to the restoration of habitats in anthropogenically disturbed urban rivers.

Intestinal bacteria diversity of suckermouth catfish (Pterygoplichthys pardalis) in the Cd, Hg, and Pb contaminated Ciliwung River, Indonesia

The contamination of aquatic environments with heavy metals poses a serious threat to fish, potentially leading to diseases or even death. Therefore, there is an urgent need for studies to investigate the adaptability of fish in heavy metal-contaminated environments. Several studies have explored the adaptability of suckermouth catfish (P. pardalis) to survive in the contaminated Ciliwung River. The findings obtained showed that the presence of intestinal bacteria helped these fish overcome the heavy metals in their intestines, thereby enabling the fish to survive. Analysis using the Next Generation Sequencing (NGS) technology has succeeded in identifying diversity of these bacteria in P. pardalis living in the Ciliwung River, which contaminated with Cd (0.3-1.6 ppm in the water & 0.9-1.6 ppm in the sediment), Hg (0.6-2 ppm in the water & 0.6-1.8 ppm in the sediment), and Pb (59.9-73.8 ppm in the water & 26.1-58.6 ppm in the sediment). Diversity index of intestinal bacteria in P. pardalis was relatively high, but it had a negative correlation with the presence of these contaminants. Actinobacteria, Firmicutes, and Proteobacteria were abundant in the intestines of P. pardalis from the upstream to downstream of the river, with an overall abundance range of 15-48%. Furthermore, Mycobacterium along with 6 other genera were identified as core intestinal bacteria. The presence of these bacterial communities in all the samples affected their survival in heavy metals-contaminated rivers. The fish's adaptability to live in this harsh environment indicated that it has the potential to be utilized as a bioremediator of heavy metals in river sediments.

Construction of the comprehensive evaluation system of waterbody pollution degree and the response of sedimentary microbial community

This study proposed and established a comprehensive evaluation system for the pollution degree of the waterbody by taking overlying water and sediment as a whole. By dividing different sampling points into three gradients according to the pollution degree, the changes in sedimentary microbes under various pollution gradients were compared. The results showed that microbial diversity, abundance and specific OTUs decreased significantly with the increase in pollution degree. Meanwhile, Firmicutes, Bacteroidota and Caldiseriota increased in the severely polluted group, while Chloroflexi and Acidobacteriota decreased. Spearman correlation analysis and co-occurrence network revealed that COD, pH in overlying water, and Mn, Fe in sediments were the most significant pollution degree evaluation indicators affecting sedimentary microorganisms, which drove the sedimentary microbial communities dominated by Proteobacteria and Firmicutes. FAPROTAX functional prediction indicated that increased pollution levels led to the weakening of functional genes related to nitrogen metabolism and sulfur metabolism and the increase of functional genes related to carbon metabolism in sediment microorganisms. This study not only provided new insights into waterbody pollution evaluation but also verified the feasibility of this evaluation method by the response of sedimentary microbial communities to different pollution degrees.

A poisoned apple: First insights into community assembly and networks of the fungal pathobiome of healthy-looking senescing leaves of temperate trees in mixed forest ecosystem

Despite the abundance of observations of foliar pathogens, our knowledge is severely lacking regarding how the potential fungal pathobiome is structured and which processes determine community assembly. In this study, we addressed these questions by analysing the potential fungal pathobiome associated with the senescing leaves and needles of 12 temperate tree species. We compared fungal plant pathogen load in the senescing leaves/needles and demonstrated that healthy-looking leaves/needles are inhabited by diverse and distinct fungal plant pathogens. We detected 400 fungal plant pathogenic ASVs belonging to 130 genera. The fungal plant pathogenic generalist, Mycosphaerella, was found to be the potential most significant contributor to foliar disease in seedlings. The analyses of assembly process and co-occurrence network showed that the fungal plant pathogenic communities in different tree types are mainly determined by stochastic processes. However, the homogenising dispersal highly contributes in broadleaf trees, whereas ecological drift plays an important role in coniferious trees. The deterministic assembly processes (dominated by variable selection) contributed more in broadleaf trees as compared to coniferous trees. We found that pH and P level significantly corresponded with fungal plant pathogenic community compositions in both tree types. Our study provides the first insight and mechanistic understanding into the community assembly, networks, and complete taxonomy of the foliar fungal pathobiome in senescing leaves and needles.

Anthropogenic pollution gradient along a mountain river affects bacterial community composition and genera with potential pathogenic species

Mountain regions in Poland are among the most frequently visited tourist destinations, causing a significant anthropogenic pressure put on the local rivers. In this study, based on numbers of 9 microorganisms, content of 17 antibiotics and 17 physicochemical parameters, we determined a pollution gradient in six sites along Białka, a typical mountain river in southern Poland. The E.coli/Staphylococcus ratio varied evidently between polluted and non-polluted sites, indicating that the possible utility of this parameter in assessing the anthropogenic impact on river ecosystems is worth further investigation. Then, using next generation sequencing, we assessed the changes in bacterial community structure and diversity as a response to the pollution gradient. Proteobacteria and Bacteroidetes were the most abundant phyla in the majority of samples. Actinobacteria were the most abundant in the most pristine (groundwater) sample, while Firmicutes and Verrucomicrobia were more prevalent in polluted sites. Bacterial diversity at various levels increased with water pollution. Eleven bacterial genera potentially containing pathogenic species were detected in the examined samples, among which Acinetobacter, Rhodococcus, and Mycobacterium were the most frequent. At the species level, Acinetobacter johnsonii was most prevalent potential pathogen, detected in all surface water samples, including the pristine ones. Two bacterial taxa-genus Flectobacillus and order Clostridiales showed very distinct variation in the relative abundance between the polluted and non-polluted sites, indicating their possible potential as biomarkers of anthropogenic impact on mountain river waters.

Hyperspectral Image Classification with Imbalanced Data Based on Semi-Supervised Learning

Hyperspectral remote sensing image classification has been widely employed for numerous applications, such as environmental monitoring, agriculture, and mineralogy. During such classification, the number of training samples in each class often varies significantly. This imbalance in the dataset is often not identified because most classifiers are designed under a balanced dataset assumption, which can distort the minority classes or even treat them as noise. This may lead to biased and inaccurate classification results. This issue can be alleviated by applying preprocessing techniques that enable a uniform distribution of the imbalanced data for further classification. However, it is difficult to add new natural features to a training model by artificial combination of samples by using existing preprocessing techniques. For minority classes with sparse samples, the addition of sufficient natural features can effectively alleviate bias and improve the generalization. For such an imbalanced problem, semi-supervised learning is a creative solution that utilizes the rich natural features of unlabeled data, which can be collected at a low cost in the remote sensing classification. In this paper, we propose a novel semi-supervised learning-based preprocessing solution called NearPseudo. In NearPseudo, pseudo-labels are created by the initialization classifier and added to minority classes with the corresponding unlabeled samples. Simultaneously, to increase reliability and reduce the misclassification cost of pseudo-labels, we created a feedback mechanism based on a consistency check to effectively select the unlabeled data and its pseudo-labels. Experiments were conducted on a state-of-the-art representative hyperspectral dataset to verify the proposed method. The experimental results demonstrate that NearPseudo can achieve better classification accuracy than other common processing methods. Furthermore, it can be flexibly applied to most typical classifiers to improve their classification accuracy. With the intervention of NearPseudo, the accuracy of random forest, k-nearest neighbors, logistic regression, and classification and regression tree increased by 1.8%, 4.0%, 6.4%, and 3.7%, respectively. This study addresses research a gap to solve the imbalanced data-based limitations in hyperspectral image classification.

A first calibration of culturable bacterial diversity and their dual resistance to heavy metals and antibiotics along altitudinal zonation of the Teesta River

Culturable bacterial diversity and co-occurrence of heavy metal and antibiotic resistance were investigated from the water and sediments along the course of the Teesta River, in the Eastern Himalayas. Water and sediment samples collected from six sampling points during the monsoon and winter seasons were subjected to analysis of physico-chemical parameters, heavy metal contamination and antibiotic tolerance. The culturable bacterial diversity established by application of bacterial culture and 16S rRNA gene sequencing, ascertained the majority belonged to Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes and Deinococcus-Thermus. Among the 5 phyla, Proteobacteria and Actinobacteria were the dominant phyla present in both water and sediment samples, whereas Bacteroidetes, Firmicutes and Deinococcus-Thermus were unique to particular sites. The Shannon index indicated that the bacterial richness was more in the water column as compared to sediment. From the total of 245 isolates, 69 genera were identified. Heavy metal tolerance and antibiotic resistance profiles showed some isolates to be tolerant to high levels of heavy metals and multiple antibiotics indicating a major concern in terms of river ecosystem serving as a pool for dissemination of such resistant genes. The antibiotic resistance and heavy metal contamination diversified along the human-impacted downstream sites, endorsing the contribution of anthropogenic factors. The present report on bacterial diversity and the associated metal and antibiotics tolerance among bacteria is the first of its kind on Teesta River, the only major river system flowing through the state of Sikkim and parts of North Bengal.

Pollution gradients shape the co-occurrence networks and interactions of sedimentary bacterial communities in Taihu Lake, a shallow eutrophic lake

The co-occurrence networks and interactions of bacterial communities in sediments are highly variable with environmental factors, which are vital to the nutrient biogeochemical cycle, pollutants biodegradation, and microbial community stability in lake ecosystems. Although pollution gradients reflect environmental variation comprehensively, few studies have characterized the changes in co-occurrence networks and interactions of bacterial communities along sediment pollution gradients. In order to investigate the impact of pollution gradients on compositions, co-occurrence networks, and interactions of sedimentary microbial communities, we studied the bacterial communities in the sediments of a typical shallow eutrophic lake, Taihu Lake, along pollution gradients using 16S rRNA gene high-throughput sequencing technology. All the sediment sampling sites were classified into mild, moderate, and severe pollution groups according to the sediments' physicochemical properties. Our results showed that the taxon richness was lowest in the severe pollution group, and the diversity of species decreased with the level of pollution. The complexity of the co-occurrence network decreased as the level of pollution increased, and the severe pollution group was characterized by a small-world network. The relative abundance of Proteobacteria, Bacteroidetes, and Chlorobi increased significantly as the level of pollution increased (P < 0.05). Strong inter-phyla co-occurrence or co-exclusion patterns demonstrated that the strength of interactions was enhanced in the severe pollution group, indicating stronger cooperative or competitive relationships. Chloroflexales and Chlorobiales were unique keystone taxa in the severe pollution group. The results of this study indicate that severe pollution reduces microbial diversity and network complexity, which may lead to community instability. The competition for nutrients of some copiotrophic bacteria may be enhanced as the level of pollution increased. The unique keystone taxa may contribute to photosynthesis and pollutant degradation in the severe pollution group. These findings expand our understanding of variation in bacterial co-occurrence networks and interactions along sediment pollution gradients.

Genetically Modified Sugarcane Intercropping Soybean Impact on Rhizosphere Bacterial Communities and Co-occurrence Patterns

Strategies involving genes in the dehydration-responsive element binding (DREB) family, which participates in drought stress regulation, and intercropping with legumes are becoming prominent options in promoting sustainable sugarcane cultivation. An increasing number of studies focusing on root interactions in intercropping systems, particularly involving transgenic crops, are being conducted to better understand and thus, harness beneficial soil microbes to enhance plant growth. We designed experiments to investigate the characteristics of two intercropping patterns, soybean with wild-type (WT) sugarcane and soybean with genetically modified (GM) Ea-DREB2B-overexpressing sugarcane, to assess the response of the rhizosphere microbiota to the different cropping patterns. Bacterial diversity in the rhizosphere microbial community differed between the two intercropping pattens. In addition, the biomass of GM sugarcane that intercropped with soybean was significantly improved compared with WT sugarcane, and the aboveground biomass and root biomass of GM soybean intercropping sugarcane increased by 49.15 and 46.03% compared with monoculture. Furthermore, a beneficial rhizosphere environment for the growth of Actinobacteria was established in the systems intercropped with GM sugarcane. Improving the production mode of crops by genetic modification is a key strategy to improving crop yields and provides new opportunities to further investigate the effects of intercropping on plant roots and soil microbiota. Thus, this study provides a basis for selecting suitable sugarcane-soybean intercropping patterns and a theoretical foundation for a sustainable sugarcane production.