Draft genome of Serratia sp. R1 gives an insight into the antibiotic resistant genes against multiple antibiotics

Recent advances in environmental antibiotic resistance genes detection and research focus: From genes to ecosystems

Antibiotic resistance genes (ARGs) persistence and potential harm have become more widely recognized in the environment due to its fast-paced research. However, the bibliometric review on the detection, research hotspot, and development trend of environmental ARGs has not been widely conducted. It is essential to provide a comprehensive overview of the last 30 years of research on environmental ARGs to clarify the changes in the research landscape and ascertain future prospects. This study presents a visualized analysis of data from the Web of Science to enhance our understanding of ARGs. The findings indicate that solid-phase extraction provides a reliable method for extracting ARG. Technological advancements in commercial kits and microfluidics have facilitated the efficacy of ARGs extraction with significantly reducing processing times. PCR and its derivatives, DNA sequencing, and multi-omics technology are the prevalent methodologies for ARGs detection, enabling the expansion of ARG research from individual strains to more intricate microbial communities in the environment. Furthermore, due to the development of combination, hybridization and mass spectrometer technologies, considerable advancements have been achieved in terms of sensitivity and accuracy as well as lowering the cost of ARGs detection. Currently, high-frequency terms such as "Antibiotic Resistance, Antibiotics, and Metagenomics" are the center of attention for study in this area. Prominent topics include the investigation of anthropogenic impacts on environmental resistance, as well as the dynamics of migration, dissemination, and adaptation of environmental ARGs, etc. The research on environmental ARGs has made significant advancements in the fields of "Microbiology" and "Biotechnology Applied Microbiology". Over the past decade, there has been a notable increase in the fields of "Environmental Sciences Ecology" and "Engineering" with a similar growth trend observed in "Water Resources". These three domains are expected to continue driving extensive study within the realm of environmental ARGs.

Ecological risk assessment and identification of the distinct microbial groups in heavy metal-polluted river sediments

To assess the health of river ecosystems, it is essential to quantify the ecological risk of heavy metals in river sediments and the structure of microbial communities. As important tributaries of the Tuo River in the upper reaches of the Yangtze River, the Mianyuan River and the Shiting River, are closely related to the economic development and human daily life in the region. This study assessed the ecological risks of heavy-metal-polluted river sediments, the heavy-metal-driven bacterial communities were revealed, and the relationships between the ecological risks and the identical bacterial communities were discussed. The Cd content was significantly greater than the environmental background value, leading to a serious pollution and very high ecological risk at the confluence of the two rivers and the upper reaches of the Mianyuan River. Microbial community analysis showed that Rhodobacter, Nocardioides, Sphingomonas, and Pseudarthrobacter were the dominant bacterial genera in the sediments of the Shiting River. However, the dominant bacterial genera in the Mianyuan River were Kouleothrix, Dechloromonas, Gaiella, Pedomicrobium, and Hyphomicrobium. Mantel test results showed (r = 0.5977, P = 0.005) that the Cd, As, Zn, Pb, Cr, and Cu were important factors that influenced differences in the distribution of sediment bacterial communities Mianyuan and Shiting rivers. A correlation heatmap showed that heavy metals were negatively correlated for most bacterial communities, but some bacterial communities were tolerant and showed a positive correlation. Overall, the microbial structure of the river sediments showed a diverse spatial distribution due to the influence of heavy metals. The results will improve the understanding of rivers contaminated by heavy metals and provide theoretical support for conservation and in situ ecological restoration of river ecosystems.