Metagenome analysis from the sediment of river Ganga and Yamuna: In search of beneficial microbiome

Metagenomic insights into microbial community, functional annotation, and antibiotic resistance genes in Himalayan Brahmaputra River sediment, India

Introduction

The Brahmaputra, a major transboundary river of the Himalayas flowing predominantly through Northeast India, particularly Assam, is increasingly endangered by contamination due to rapid urbanization and anthropogenic pressures. These environmental changes pose significant risks at the microbial level, affecting nutrient cycling and productivity, and thereby impacting river ecosystem health. The next-generation sequencing technology using a metagenomics approach has revolutionized our understanding of the microbiome and its critical role in various aquatic environments.

Methods

The present study aimed to investigate the structure of the bacterial community and its functional potentials within the sediments of the Brahmaputra River, India, using high-throughput shotgun metagenomics. Additionally, this study sought to explore the presence of antimicrobial resistance genes in the river's sediment.

Results and discussion

Shotgun metagenomics revealed a diverse bacterial community comprising 31 phyla, 52 classes, 291 families, 1,016 genera, and 3,630 species. Dominant phyla included Pseudomonadota (62.47-83.48%), Actinobacteria (11.10-24.89%), Bacteroidetes (0.97-3.82%), Firmicutes (0.54-3.94%), Cyanobacteria (0.14-1.70%), and Planctomycetes (0.30-0.78%). Functional profiling highlighted significant involvement in energy metabolism, amino acid and central carbon metabolism, stress response, and degradation pathways, emphasizing the microbial community's role in ecosystem functioning and resilience. Notably, 50 types of antibiotic resistance genes (ARGs) were detected, with resistance profiles spanning multidrug, aminoglycoside, β-lactam, fluoroquinolone, rifampicin, sulfonamide, and tetracycline classes. Network analysis underscored the intricate relationships among ARG subtypes, suggesting potential mechanisms of resistance propagation. Furthermore, plasmid-related genes and 185 virulence factor genes (VFGs) were identified, indicating additional layers of microbial adaptation and potential pathogenicity within the river sediments. This comprehensive microbial and functional profiling of the Brahmaputra's sediment metagenome provides crucial insights into microbial diversity, resistance potential, and ecological functions, offering a foundation for informed management and mitigation strategies to preserve river health and mitigate pollution impacts.

Comparative metagenomic analysis from Sundarbans ecosystems advances our understanding of microbial communities and their functional roles

The Sundarbans mangrove, located at the mouth of the Ganges and Brahmaputra Rivers, is the world's largest tidal mangrove forest. These mangroves are also one of the most striking sources of microbial diversity, essential in productivity, conservation, nutrient cycling, and rehabilitation. Hence, the main objective of this study was to use metagenome analysis and provide detailed insight into microbial communities and their functional roles in the Sundarbans mangrove ecosystem. A comparative analysis was also done with a non-mangrove region of the Sundarbans ecosystem to assess the capability of the environmental parameters to explain the variation in microbial community composition. The study found several dominant bacteria, viz., Alphaproteobacteria, Actinomycetota, Bacilli, Clostridia, Desulfobacterota, Gammaproteobacteria, and Nitrospira, from the mangrove region. The mangrove sampling site reports several salt-tolerant bacteria like Alkalibacillus haloalkaliphilus, Halomonas anticariensis, and Salinivibrio socompensis. We found some probiotic species, viz., Bacillus clausii, Lactobacillus curvatus, Vibrio mediterranei and Vibrio fluvialis, from the Sundarbans mangrove. Nitrifying bacteria in Sundarbans soils were Nitrococcus mobilis, Nitrosococcus oceani, Nitrosomonas halophila, Nitrospirade fluvii, and others. Methanogenic archaea, viz., Methanoculleus marisnigri, Methanobrevibacter gottschalkii, and Methanolacinia petrolearia, were highly abundant in the mangroves as compared to the non-mangrove soils. The identified methanotrophic bacterial species, viz., Methylobacter tundripaludum, Methylococcus capsulatus, Methylophaga thiooxydans, and Methylosarcina lacus are expected to play a significant role in the degradation of methane in mangrove soil. Among the bioremediation bacterial species identified, Pseudomonas alcaligenes, Pseudomonas mendocina, Paracoccus denitrificans, and Shewanella putrefaciens play a significant role in the remediation of environmental pollution. Overall, our study shows for the first time that the Sundarbans, the largest mangrove ecosystem in the world, has a wide range of methanogenic archaea, methanotrophs, pathogenic, salt-tolerant, probiotic, nitrifying, and bioremediation bacteria.

Comparison of Yamuna (India) and Mississippi River (United States of America) bacterial communities reveals greater diversity below the Yamunotri Glacier

The Yamuna River in India and the Mississippi River in the United States hold significant commercial, cultural, and ecological importance. This preliminary survey compares the bacterial communities sampled in surface waters at 11 sites (Yamuna headwaters, Mississippi headwaters, Yamuna River Yamunotri Town, Mississippi River at Winona, Tons River, Yamuna River at Paonta Sahib, Yamuna River Delhi-1, Yamuna River Delhi-2, Yamuna River before Sangam, Sangam, Ganga River before Sangam). Bacterial 16S rDNA analyses demonstrate dominance of Proteobacteria and Bacteroidetes phyla. Actinobacteria were also dominant at sites near Sangam in India and sites in Minnesota. A dominance of Epsilonbacteraeota were found in Delhi, India. Principal component analysis (PCA) using unique operational taxonomic units (OTUs) resulted in the identification of 3 groups that included the Yamuna River locations in Delhi (Delhi locations), Yamuna headwaters and Yamuna River at Yamunotri (Yamuna River locations below the Glacier) and Mississippi, Ganga, Tons, and other Yamuna River locations. Diversity indices were significantly higher at the Yamuna River locations below the Glacier (Simpson D = 0.986 and Shannon H = 5.06) as compared (p value <0.001) to the Delhi locations (D = 0.951 and H = 4.23) and as compared (p value < 0.001) to Mississippi, Ganga, Tons, and other Yamuna River locations (D = 0.943 and H = 3.96). To our knowledge, this is the first survey to compare Mississippi and Yamuna River bacterial communities. We demonstrate higher diversity in the bacterial communities below the Yamunotri glacier in India.

Metagenomic landscape of sediments of river Ganga reveals microbial diversity, potential plastic and xenobiotic degradation enzymes

The Ganga is the largest river in India, serves as a lifeline for agriculture, drinking water, and religious rites. However, it became highly polluted due to the influx of industrial wastes and untreated sewages, leading to the decline of aquatic biodiversity. This study investigated the microbial diversity and plastic-xenobiotic degrading enzymes of six sediment metagenomes of river Ganga at Prayagraj (RDG, TSG, SDG) and Devprayag (KRG, BNG, BRG). The water quality parameters, higher values of BOD (1.8-3.7 ppm), COD (23-29.2 ppm) and organic carbon (0.18-0.51%) were recorded at Prayagraj. Comparative analysis of microbial community structure between Prayagraj and Devprayag revealed significant differences between Bacteroidetes and Firmicutes, which emerging as the predominant bacterial phyla across six sediment samples. Notably, their prevalence was highest in the BRG samples. Furthermore, 25 OTUs at genus level were consistent across all six samples. Alpha diversity exhibited minimal variation among samples, while beta diversity indicated an inverse relationship between species richness and diversity. Co-occurrence network analysis established that genera from the same and different groups of phyla show positive co-relations with each other. Thirteen plastic degrading enzymes, including Laccase, Alkane-1 monooxygenase and Alkane monooxygenase, were identified from six sediment metagenomes of river Ganga, which can degrade non-biodegradable plastic viz. Polyethylene, Polystyrene and Low-density Polyethelene. Further, 18 xenobiotic degradation enzymes were identified for the degradation of Bisphenol, Xylene, Toluene, Polycyclic aromatic hydrocarbon, Styrene, Atrazene and Dioxin etc. This is the first report on the identification of non-biodegradable plastic degrading enzymes from sediment metagenomes of river Ganga, India. The findings of this study would help in pollution abatement and sustainable management of riverine ecosystem.

Unveiling the Microbiome Landscape: A Metagenomic Study of Bacterial Diversity, Antibiotic Resistance, and Virulence Factors in the Sediments of the River Ganga, India

The global rise in antibiotic resistance, fueled by indiscriminate antibiotic usage in medicine, aquaculture, agriculture, and the food industry, presents a significant public health challenge. Urban wastewater and sewage treatment plants have become key sources of antibiotic resistance proliferation. The present study focuses on the river Ganges in India, which is heavily impacted by human activities and serves as a potential hotspot for the spread of antibiotic resistance. We conducted a metagenomic analysis of sediment samples from six distinct locations along the river to assess the prevalence and diversity of antibiotic resistance genes (ARGs) within the microbial ecosystem. The metagenomic analysis revealed the predominance of Proteobacteria across regions of the river Ganges. The antimicrobial resistance (AMR) genes and virulence factors were determined by various databases. In addition to this, KEGG and COG analysis revealed important pathways related to AMR. The outcomes highlight noticeable regional differences in the prevalence of AMR genes. The findings suggest that enhancing health and sanitation infrastructure could play a crucial role in mitigating the global impact of AMR. This research contributes vital insights into the environmental aspects of antibiotic resistance, highlighting the importance of targeted public health interventions in the fight against AMR.

Urbanization led to the abundance of Gram-negative, chemo-organo-heterotrophs, and antibiotic resistance genes in the downstream regions of the Ganga River water of India

The present investigation assesses the bacterial microbiome and antibiotic resistance genes (ARGs) of the river Ganga from Uttarakhand (upstream region; US group) and Uttar Pradesh (downstream region; DS group) regions using a 16S rRNA amplicon-based metagenomic approach. Gram-negative, aerobic, and chemo-organotrophic bacteria made up the majority of the bacterial genera during the overall analysis. Physicochemical analysis revealed a higher concentration of nitrate and phosphate in the downstream sites of the Ganga River. The prevalence of Gemmatimonas, Flavobacterium, Arenimonas, and Verrucomicrobia in the water of the DS region indicates a high organic load. Pseudomonas and Flavobacterium emerged as the most prevalent genera among the 35 significantly different shared genera (p-value < 0.05) in the US and DS regions, respectively. Overall antibiotic resistance analysis of the samples showed the dominance of β-lactam resistance (33.92%) followed by CAMP (cationic antimicrobial peptide) resistance (27.75%), and multidrug resistance (19.17%), vancomycin resistance (17.84%), and tetracycline resistance (0.77%). While comparing, the DS group exhibited a higher abundance of ARGs over the US group, where the CAMP resistance and β-lactam ARGs were dominant in the respective regions. The correlation (p-value < 0.05) analysis showed that most bacteria exhibit a significant correlation with tetracycline resistance followed by the phenicol antibiotic. The present findings draw attention to the need for regulated disposal of multiform human-derived wastes into the Ganga River to reduce the irrepressible ARGs dissemination.

Sulfur metabolism in subtropical marine mangrove sediments fundamentally differs from other habitats as revealed by SMDB

Shotgun metagenome sequencing provides the opportunity to recover underexplored rare populations and identify difficult-to-elucidate biochemical pathways. However, information on sulfur genes, including their sequences, is scattered in public databases. Here, we introduce SMDB ( https://smdb.gxu.edu.cn/ )-a manually curated database of sulfur genes based on an in-depth review of the scientific literature and orthology database. The SMDB contained a total of 175 genes and covered 11 sulfur metabolism processes with 395,737 representative sequences affiliated with 110 phyla and 2340 genera of bacteria/archaea. The SMDB was applied to characterize the sulfur cycle from five habitats and compared the microbial diversity of mangrove sediments with that of other habitats. The structure and composition of microorganism communities and sulfur genes were significantly different among the five habitats. Our results show that microorganism alpha diversity in mangrove sediments was significantly higher than in other habitats. Genes involved in dissimilatory sulfate reduction were abundant in subtropical marine mangroves and deep-sea sediments. The neutral community model results showed that microbial dispersal was higher in the marine mangrove ecosystem than in others habitats. The Flavilitoribacter of sulfur-metabolizing microorganism becomes a reliable biomarker in the five habitats. SMDB will assist researchers to analyze genes of sulfur cycle from the metagenomic efficiently.

An Improved Machine Learning-Based Approach to Assess the Microbial Diversity in Major North Indian River Ecosystems

The rapidly evolving high-throughput sequencing (HTS) technologies generate voluminous genomic and metagenomic sequences, which can help classify the microbial communities with high accuracy in many ecosystems. Conventionally, the rule-based binning techniques are used to classify the contigs or scaffolds based on either sequence composition or sequence similarity. However, the accurate classification of the microbial communities remains a major challenge due to massive data volumes at hand as well as a requirement of efficient binning methods and classification algorithms. Therefore, we attempted here to implement iterative K-Means clustering for the initial binning of metagenomics sequences and applied various machine learning algorithms (MLAs) to classify the newly identified unknown microbes. The cluster annotation was achieved through the BLAST program of NCBI, which resulted in the grouping of assembled scaffolds into five classes, i.e., bacteria, archaea, eukaryota, viruses and others. The annotated cluster sequences were used to train machine learning algorithms (MLAs) to develop prediction models to classify unknown metagenomic sequences. In this study, we used metagenomic datasets of samples collected from the Ganga (Kanpur and Farakka) and the Yamuna (Delhi) rivers in India for clustering and training the MLA models. Further, the performance of MLAs was evaluated by 10-fold cross validation. The results revealed that the developed model based on the Random Forest had a superior performance compared to the other considered learning algorithms. The proposed method can be used for annotating the metagenomic scaffolds/contigs being complementary to existing methods of metagenomic data analysis. An offline predictor source code with the best prediction model is available at (https://github.com/Nalinikanta7/metagenomics).

Spatio-temporal variation of the microbiome and resistome repertoire along an anthropogenically dynamic segment of the Ganges River, India

Aquatic ecosystems are regarded as a hub of antibiotic and metal resistance genes. River Ganges is a unique riverine system in India with socio-cultural and economic significance. However, it remains underexplored for its microbiome and associated resistomes along its anthropogenically impacted course. The present study utilized a nanopore sequencing approach to depict the microbial community structure in the sediments of the river Ganges harboring antibiotic and metal resistance genes (A/MRGs) in lower stretches known for anthropogenic impact. Comprehensive microbiome analyses revealed resistance genes against 23 different types of metals and 28 classes of antibiotics. The most dominant ARG category was multidrug resistance, while the most prevalent MRGs conferred resistance against copper and zinc. Seasonal differences dismally affected the microbiota of the Ganges. However, resistance genes for fosmidomycin and tetracycline varied with season ANOVA, p < 0.05. Interestingly, 333 and 334 ARG subtypes were observed at all the locations in pre-monsoon and post-monsoon, respectively. The taxa associated with the dominant ARGs and MRGs were Pseudomonas and Burkholderia, which are important nosocomial pathogens. A substantial phage diversity for pathogenic and putrefying bacteria at all locations attracts attention for its use to tackle the dissemination of antibiotic and metal-resistant bacteria. This study suggests the accumulation of antibiotics and metals as the driving force for the emergence of resistance genes and the affiliated bacteria trafficking them. The present metagenomic assessment highlights the need for comprehensive, long-term biological and physicochemical monitoring and mitigation strategies toward the contaminants associated with ARGs and MRGs in this nationally important river.

Bacteriophages diversity in India's major river Ganga: a repository to regulate pathogenic bacteria in the aquatic environment

Bacteriophages are key viruses that can kill thousands of harmful microbes generally present at polluted sites. Such bacteriophages are abundantly present in the river Ganga, where millions of people in India and abroad drink its water and take baths every day for spiritual reasons. Besides bacteriophages, several pathogenic and zoonotic microbes are present in the river Ganga. It is interesting to study the diversity and abundance of bacteria and their respective phages present in polluted or non-polluted sites. Thus, the metagenomics study was carried out at the most polluted sites of river Ganga near Kanpur and non-polluted sites at Farakka, which harbors several harmful bacteria and their phages. The results revealed a significantly higher percentage of Microviridae phage family, ssDNA viruses, and Mimiviridae virus family near Kanpur than Farakka. In addition, compared to Kanpur, Farakka has a more significant percentage of Myoviridae, an unidentified phage family, and Retroviridae viral families. Despite heavy drainage of untreated and contaminated effluents from the leather industry, pesticide industry, paper mills, metropolitan cities, and other sources, the vast number of said phages kills several harmful pathogenic microbes in polluted sites to maintain the Ganga water's healing power or natural sterility. In a polluted aquatic environment, the varieties of bacteriophages were identified in the Ganga and their interaction with the microbial host. The taxonomic diversity of several bacteriophages found in pathogenic host systems was investigated to get exceptional knowledge of these small viruses in the aquatic environment.

Bacterial diversity in the aquatic system in India based on metagenome analysis-a critical review

Microbial analysis has become one of the most critical areas in aquatic ecology and a crucial component for assessing the contribution of microbes in food web dynamics and biogeochemical processes. Initial research was focused on estimating the abundance and distribution of the microbes using microscopy and culture-based analysis, which are undoubtedly complex tasks. Over the past few decades, microbiologists have endeavored to apply and extend molecular techniques to address pertinent questions related to the function and metabolism of microbes in aquatic ecology. Metagenomics analysis has revolutionized aquatic ecology studies involving the investigation of the genome of a mixed community of organisms in an ecosystem to identify microorganisms, their functionality, and the discovery of novel proteins. This review discusses the metagenomics analysis of bacterial diversity in and around different aquatic systems in India.

Differences in bacterial community composition, structure and function between sediments in waterways and non-navigable channels in a plain river network area

Bacterial communities greatly help maintain the balance of river ecosystems and are highly sensitive to changes in environmental conditions. Plain river network areas (PRNs) are characterized by dense river networks, low-lying terrain, and slow water flow, where the bottom sediment is frequently disturbed by ship navigation due to the limited water depth and width of waterways, providing a unique ecological niche for bacterial growth. Hence, understanding how bacterial communities in PRNs respond to changes in hydrodynamic conditions, physicochemical parameters, and pollutants under ship navigation is essential to maintaining the stability of inland waterway ecosystems. The Taihu Lake Basin, a typical PRN, was selected to explore the differences in bacterial community composition, structure and function between sediments in waterways (WS) and non-navigable channels (NS). The results indicate that the sediment from NS possessed more diverse and complex bacterial communities than WS. NMDS and ANOSIM analyses further verified the significant differences in bacterial community structure between WS and NS. Combined with LEfSe, we observed the highly differential taxonomy between WS and NS from phylum to order. Moreover, a comparison of beta diversity dissimilarity indices revealed that although species replacement dominated both the WS and NS beta-diversity patterns, species loss caused the differences in the overall beta diversity between them. Variance partitioning analysis revealed that physicochemical parameters (clay content, pH, ORP, and others) and ship traffic volume (STV) were the main driving factors for bacterial community distribution between WS and NS, while pollutants (heavy metals, perfluoroalkyl acids, and others) had a relatively minor influence. PICRUSt2 analysis revealed that the changes in pH, ORP, and STV under ship navigation might inhibit the bacterial ability to metabolize carbohydrates. The results reveal the comprehensive effects of ship navigation disturbance on sediment bacterial communities in the PRN and contribute to further understanding of inland waterway ecosystems.

Ganga River sediments of India predominate with aerobic and chemo-heterotrophic bacteria majorly engaged in the degradation of xenobiotic compounds

Sediment provides a stagnant habitat to microbes that accumulate organic matter and other industrial pollutants from the upper layer of the water. The sediment of the Ganga River of India is overlooked for exploring the bacterial diversity despite their taxon richness over the water counterpart. To enrich the limited information on the bacterial diversity of the Ganga River sediment, the present study was planned that relies on amplicon-based bacterial diversity of the Ganga River sediment by using bacterial-specific 16S hypervariable region (V₃-V₄). The Illumina MiSeq2500 platform generated 1,769,226 raw reads from the metagenomes of various samples obtained from ten sites in five major cities of Uttar Pradesh and Uttarakhand regions traversing the Ganga River. Taxonomy level analysis assigned 58 phyla, 366 order, and 715 genera of bacterial type. The high values of various diversity indices (Chao1, Shannon, and Simpson) in Kanpur sediment indicate the high bacterial richness compared to the Rishikesh sediment. However, several other ecological parameters (Shannon index, Simpson index, enspie _vector, and Faith_pd) were comparatively higher in Rishikesh sediment which is a comparatively less disturbed region by human activities over the other sediments samples studied here. Ganga River sediment dominates with Gram-negative, chemo-heterotrophic, and aerobic bacteria that chiefly belong to Proteobacteria, Acidobacteria, Chloroflexi, and Bacteroidota. The abundance of Nitrospira, Hydrogenophaga, Thauera, Vicinamibacteraceae, and Latescibacterota in the Ganga River sediment could be considered as the ecological indicators that find a significant role in the degradation of xenobiotic compounds. The PICRUSt-based analysis showed that ~ 35% of genes were involved in benzoate and aminobenzoate degradation where a significant portion of genes belong to nitrotoluene degradation (14%). Thus, the study uncovers a new perspective in the lineage of bacterial communities and their functional characterization of the Ganga River sediment.

Taxonomic profiling and functional gene annotation of microbial communities in sediment of river Ganga at Kanpur, India: insights from whole-genome metagenomics study

The perennial river Ganga is recognized as one of India's largest rivers of India, but due to continuous anthropogenic activities, the river's ecosystem is under threat. Next-generation sequencing technology has transformed metagenomics in the exploration of microbiome and their imperative function in diverse aquatic ecosystems. In this study, we have uncovered the structure of community microbiome and their functions in sediments of river Ganga at Kanpur, India, at three polluted stretches through a high-resolution metagenomics approach using Illumina HiSeq 2500. Among the microbes, bacteria dominate more than 82% in the three polluted sediment samples of river Ganga. Pseudomonadota (alpha, beta, and gamma) is the major phylum of bacteria that dominates in three sediment samples. Genes involved in degradation of xenobiotic compounds involving nitrotoluene, benzoate, aminobenzoate, chlorocyclohexane, and chlorobenzene were significantly enriched in the microbiome of polluted stretches. Pathway analysis using KEGG database revealed a higher abundance of genes involved in energy metabolism such as oxidative phosphorylation, nitrogen, methane, sulfur, and carbon fixation pathways in the sediment metagenome data from the river Ganga. A higher abundance of pollutant degrading enzymes like 4-hydroxybenzoate 3-monooxygenase, catalase-peroxidase, and altronate hydrolase in the polluted microbiome indicates their role in degradation of plastics and dyes. Overall, our study has provided bacterial diversity and their dynamics in community structure and function from polluted river microbiome, which is expected to open up better avenues for exploration of novel functional genes/enzymes with potential application in health and bioremediation.

Community structure and function of microbiomes in polluted stretches of river Yamuna in New Delhi, India, using shotgun metagenomics

The large population residing in the northern region of India surrounding Delhi mostly depends on water of River Yamuna, a tributary of mighty Ganga for agriculture, drinking and various religious activities. However, continuous anthropogenic activities mostly due to pollution mediated by rapid urbanization and industrialization have profoundly affected river microflora and their function thus its health. In this study, potential of whole-genome metagenomics was exploited to unravel the novel consortia of microbiome and their functional potential in the polluted sediments of the river at Delhi. Analysis of high-quality metagenome data from Illumina NextSeq500 revealed substantial differences in composition of microbiota at different sites dominated by Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria and Chloroflexi phyla. The presence of highly dominant anaerobic bacteria like Dechloromonas aromatica (benzene reducing and denitrifying), Rhodopseudomonas palustris (organic matter reducing), Syntrophus aciditrophicus (fatty acid reducing) and Syntrophobacter fumaroxidans (sulphate reducing) in the polluted river Yamuna signifies the impact of unchecked pollution in declining health of the river ecosystem. A decline in abundance of phages was also noticed along the downstream river Yamuna. Mining of mycobiome reads uncovered plethora of fungal communities (i.e. Nakaseomyces, Aspergillus, Schizosaccharomyces and Lodderomyces) in the polluted stretches due to the availability of higher organic carbon and total nitrogen (%) could be decoded as promising bioindicators of river trophic status. Pathway analysis through KEGG revealed higher abundance of genes involved in energy metabolism (nitrogen and sulphur), methane metabolism, degradation of xenobiotics (Nitrotoluene, Benzoate and Atrazine), two-component system (atoB, cusA and silA) and membrane transport (ABC transporters). Catalase-peroxidase and 4-hydroxybenzoate 3-monooxygenase were the most enriched pollution degrading enzymes in the polluted study sites of river Yamuna. Overall, our results provide crucial insights into microbial dynamics and their function in response to high pollution and could be insightful to the ongoing remediation strategies to clean river Yamuna.

Plastisphere community assemblage of aquatic environment: plastic-microbe interaction, role in degradation and characterization technologies

It is undeniable that plastics are ubiquitous and a threat to global ecosystems. Plastic waste is transformed into microplastics (MPs) through physical and chemical disruption processes within the aquatic environment. MPs are detected in almost every environment due to their worldwide transportability through ocean currents or wind, which allows them to reach even the most remote regions of our planet. MPs colonized by biofilm-forming microbial communities are known as the ''plastisphere". The revelation that this unique substrate can aid microbial dispersal has piqued interest in the ground of microbial ecology. MPs have synergetic effects on the development, transportation, persistence, and ecology of microorganisms. This review summarizes the studies of plastisphere in recent years and the microbial community assemblage (viz. autotrophs, heterotrophs, predators, and pathogens). We also discussed plastic-microbe interactions and the potential sources of plastic degrading microorganisms. Finally, it also focuses on current technologies used to characterize those microbial inhabitants and recommendations for further research.

Using AnnoTree to Get More Assignments, Faster, in DIAMOND+MEGAN Microbiome Analysis

In microbiome analysis, one main approach is to align metagenomic sequencing reads against a protein reference database, such as NCBI-nr, and then to perform taxonomic and functional binning based on the alignments. This approach is embodied, for example, in the standard DIAMOND+MEGAN analysis pipeline, which first aligns reads against NCBI-nr using DIAMOND and then performs taxonomic and functional binning using MEGAN. Here, we propose the use of the AnnoTree protein database, rather than NCBI-nr, in such alignment-based analyses to determine the prokaryotic content of metagenomic samples. We demonstrate a 2-fold speedup over the usage of the prokaryotic part of NCBI-nr and increased assignment rates, in particular assigning twice as many reads to KEGG. In addition to binning to the NCBI taxonomy, MEGAN now also bins to the GTDB taxonomy.

IMPORTANCE The NCBI-nr database is not explicitly designed for the purpose of microbiome analysis, and its increasing size makes its unwieldy and computationally expensive for this purpose. The AnnoTree protein database is only one-quarter the size of the full NCBI-nr database and is explicitly designed for metagenomic analysis, so it should be supported by alignment-based pipelines.

Biofloc Microbiome With Bioremediation and Health Benefits

The biofloc system has recently attracted great attention as a cost-effective, sustainable, and environmentally friendly technology and expected to contribute toward human food security (Zero Hunger SDG 2). It is also expected that this endeavor can be adopted widely because of its characteristics of zero water exchange and reduced artificial feeding features. In the biofloc system, the flocs which are generally formed by aggregation of heterotrophic microorganisms, serve as natural bioremediation candidates. These microbes effectively maintain water quality by utilizing the nutrient wastes, mostly originated from digested, unconsumed, and metabolic processes of feed. Additionally, the flocs are important sources of nutrients, mainly a protein source, and when these are consumed by aquaculture animals they improve the growth performance, immunity, and disease tolerance of host against pathogenic microbial infection. Here in this review, we focus on recent advances that could provide a mechanistic insight on how the microbial community developed in the biofloc system helps in the bioremediation process and enhances the overall health of the host. We have also tried to address the possible role of these microbial communities against growth and virulence of pathogenic microbes.

Structural, functional, resistome and pathogenicity profiling of the Cooum river

The microbial community's structure and functions determine the health, quality, and anthropogenic conditions of the river ecosystems. The presence of Bacteria such as Arcobacter spp, Escherichia spp, and Campylobacters spp, have been shown to reflect the poor water quality of rivers. Apprehension of the microbial community in polluted water bodies is significant because it affects human health and the environment. Culture-independent metagenomic and metatranscriptomic approaches employed in the current study of the Cooum river unraveled the taxonomic classification of diverse microbes, including archaea, bacteria, viruses, and phages. The presence of abundant Macellibacteroides fermentans, Arcobacter bivolvorium, Arcobacter butzleri, Methanothrix soenhngeii, and Bacteroides graminisolvens were noted. Viruses and phages like Caudovirales, Human mastadenovirus C, Siphoviridae, Escherichia phage, Erwinia phage, Synechoccus phage, and Vibrio phage were relatively predominant. Various metabolic pathways like methane, sulfur, and nitrogen metabolism adopted by the microbiome confer dangerous gases. Mechanisms such as secretory systems, signal transduction, Chemotaxis, quorum sensing, transportation of chemicals and ions were significantly enriched. The microbes expressed antimicrobial resistance mechanisms as identified from the genes encoding beta-lactamase enzymes and aminoglycoside phosphotransferase enzymes. Metal resistance mechanisms against copper, tellurium, chromium, and cadmium were plentiful. Presence of human pathogens interactions with Yersinia pestis, Campylobacter jejuni, Escherichia coli, Helicobacter pylori, and Francisella tularensis subsp. tularensis suggested the possibilities of transmission of pathogenesis to humans. The current study is the first to apprehend the detailed microbiome composition of one of the highly polluted rivers in South India. The study elaborated the microbiome's structure, functions, and metabolic potential at a specific site of the polluted river.