mibPOPdb: An online database for microbial biodegradation of persistent organic pollutants

oriTDB: a database of the origin-of-transfer regions of bacterial mobile genetic elements

Conjugation and mobilization are two important pathways of horizontal transfer of bacterial mobile genetic elements (MGEs). The origin-of-transfer (oriT) region is crucial for this process, serving as a recognition site for relaxase and containing the DNA nicking site (nic site), which initiates the conjugation or mobilization. Here, we present a database of the origin-of-transfer regions of bacterial MGEs, oriTDB (https://bioinfo-mml.sjtu.edu.cn/oriTDB2/). Incorporating data from text mining and genome analysis, oriTDB comprises 122 experimentally validated and 22 927 predicted oriTs within bacterial plasmids, Integrative and Conjugative Elements, and Integrative and Mobilizable Elements. Additionally, oriTDB includes details about associated relaxases, auxiliary proteins, type IV coupling proteins, and a gene cluster encoding the type IV secretion system. The database also provides predicted secondary structures of oriT sequences, dissects oriT regions into pairs of inverted repeats, nic sites, and their flanking conserved sequences, and offers an interactive visual representation. Furthermore, oriTDB includes an enhanced oriT prediction pipeline, oriTfinder2, which integrates a functional annotation module for cargo genes in bacterial MGEs. This resource is intended to support research on bacterial conjugative or mobilizable elements and promote an understanding of their cargo gene functions.

Unveiling the overlooked small-sized microbiome in river ecosystems

Enriching microorganisms using a 0.22-μm pore size is a general pretreatment procedure in river microbiome research. However, it remains unclear the extent to which this method loses microbiome information. Here, we conducted a comparative metagenomics-based study on microbiomes with sizes over 0.22 μm (large-sized) and between 0.22 μm and 0.1 μm (small-sized) in a subtropical river. Although the absolute concentration of small-sized microbiome was about two orders of magnitude lower than that of large-sized microbiome, sequencing only large-sized microbiome resulted in a significant loss of microbiome diversity. Specifically, the microbial community was different between two sizes, and 347 genera were only detected in small-sized microbiome. Small-sized microbiome had much more diverse viral community than large-sized fraction. The viruses had abundant ecological functions and were hosted by 825 species of 169 families, including pathogen-related families. Small-sized microbiome had distinct antimicrobial resistance risks from large-sized microbiome, showing an enrichment of eight antibiotic resistance gene (ARG) types as well as the detection of 140 unique ARG subtypes and five enriched risk rank I ARGs. Draft genomes of five major resistant pathogens having diverse ecological and pollutant-degrading functions were only assembled in small-sized microbiome. These findings provide novel insights into river ecosystems, and highlight the overlooked small-sized microbiome in the environment.

Meta-omics assisted microbial gene and strain resources mining in contaminant environment

Human activities have led to the release of various environmental pollutants, triggering ecological challenges. In situ, microbial communities in these contaminated environments are usually assumed to possess the potential capacity of pollutant degradation. However, the majority of genes and microorganisms in these environments remain uncharacterized and uncultured. The advent of meta-omics provided culture-independent solutions for exploring the functional genes and microorganisms within complex microbial communities. In this review, we highlight the applications and methodologies of meta-omics in uncovering of genes and microbes from contaminated environments. These findings may assist in future bioremediation research.

Utility of metagenomics for bioremediation: a comprehensive review on bioremediation mechanisms and microbial dynamics of river ecosystem

Global industrialization has contributed substantial amounts of chemical pollutants in rivers, resulting in an uninhabitable state and impacting different life forms. Moreover, water macrophytes, such as water hyacinths, are abundantly present in polluted rivers, significantly affecting the overall water biogeochemistry. Bioremediation involves utilizing microbial metabolic machinery and is one of the most viable approaches for removing toxic pollutants. Conventional techniques generate limited information on the indigenous microbial population and their xenobiotic metabolism, failing the bioremediation process. Metagenomics can overcome these limitations by providing in-depth details of microbial taxa and functionality-related information required for successful biostimulation and augmentation. An in-depth summary of the findings related to pollutant metabolizing genes and enzymes in rivers still needs to be collated. The present study details bioremediation genes and enzymes functionally mined from polluted river ecosystems worldwide using a metagenomic approach. Several studies reported a wide variety of pollutant-degrading enzymes involved in the metabolism of dyes, plastics, persistent organic pollutants, and aromatic hydrocarbons. Additionally, few studies also noted a shift in the microbiome of the rivers upon exposure to contaminants, crucially affecting the ecological determinant processes. Furthermore, minimal studies have focused on the role of water-hyacinth-associated microbes in the bioremediation potentials, suggesting the need for the bioprospecting of these lesser-studied microbes. Overall, our study summarizes the prospects and utilities of the metagenomic approach and proposes the need to employ it for efficient bioremediation.

Ecology and risks of the global plastisphere as a newly expanding microbial habitat

Plastic offers a new niche for microorganisms, the plastisphere. The ever-increasing emission of plastic waste makes it critical to understand the microbial ecology of the plastisphere and associated effects. Here, we present a global fingerprint of the plastisphere, analyzing samples collected from freshwater, seawater, and terrestrial ecosystems. The plastisphere assembles a distinct microbial community that has a clearly higher heterogeneity and a more deterministically dominated assembly compared to natural habitats. New coexistence patterns-loose and fragile networks with mostly specialist linkages among microorganisms that are rarely found in natural habitats-are seen in the plastisphere. Plastisphere microbiomes generally have a great potential to metabolize organic compounds, which could accelerate carbon turnover. Microorganisms involved in the nitrogen cycle are also altered in the plastisphere, especially in freshwater plastispheres, where a high abundance of denitrifiers may increase the release of nitrite (aquatic toxicant) and nitrous oxide (greenhouse gas). Enrichment of animal, plant, and human pathogens means that the plastisphere could become an increasingly mobile reservoir of harmful microorganisms. Our findings highlight that if the trajectory of plastic emissions is not reversed, the expanding plastisphere could pose critical planetary health challenges.

ICEberg 3.0: functional categorization and analysis of the integrative and conjugative elements in bacteria

ICEberg 3.0 (https://tool2-mml.sjtu.edu.cn/ICEberg3/) is an upgraded database that provides comprehensive insights into bacterial integrative and conjugative elements (ICEs). In comparison to the previous version, three key enhancements were introduced: First, through text mining and manual curation, it now encompasses details of 2065 ICEs, 607 IMEs and 275 CIMEs, including 430 with experimental support. Secondly, ICEberg 3.0 systematically categorizes cargo gene functions of ICEs into six groups based on literature curation and predictive analysis, providing a profound understanding of ICEs'diverse biological traits. The cargo gene prediction pipeline is integrated into the online tool ICEfinder 2.0. Finally, ICEberg 3.0 aids the analysis and exploration of ICEs from the human microbiome. Extracted and manually curated from 2405 distinct human microbiome samples, the database comprises 1386 putative ICEs, offering insights into the complex dynamics of Bacteria-ICE-Cargo networks within the human microbiome. With the recent updates, ICEberg 3.0 enhances its capability to unravel the intricacies of ICE biology, particularly in the characterization and understanding of cargo gene functions and ICE interactions within the microbiome. This enhancement may facilitate the investigation of the dynamic landscape of ICE biology and its implications for microbial communities.

APDB: a database on air pollutant characterization and similarity prediction

The World Health Organization estimates that 9 out of 10 people worldwide breathe air containing high levels of pollutants. Long-term and chronic exposure to high concentrations of air pollutants is associated with deleterious effects on vital organs, including increased inflammation in the lungs, oxidative stress in the heart and disruption of the blood-brain barrier. For this reason, in an effort to find an association between exposure to pollutants and the toxicological effects observable on human health, an online resource collecting and characterizing in detail pollutant molecules could be helpful to investigate their properties and mechanisms of action. We developed a database, APDB, collecting air-pollutant-related data from different online resources, in particular, molecules from the US Environmental Protection Agency, their associated targets and bioassays found in the PubChem chemical repository and their computed molecular descriptors and quantum mechanics properties. A web interface allows (i) to browse data by category, (ii) to navigate the database by querying molecules and targets and (iii) to visualize and download molecule and target structures as well as computed descriptors and similarities. The desired data can be freely exported in textual/tabular format and the whole database in SQL format. Database URL http://apdb.di.univr.it.