The long-read amplicon provides a species-level solution for the community. With the improvement of nanopore flowcells, the accuracy of Oxford Nanopore Technologies (ONT) R10.4.1 has been substantially enhanced, with an average of approximately 99%. To evaluate its effectiveness on amplicons, three types of microbiomes were analyzed by 16S ribosomal RNA (hereinafter referred to as “16S”) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1) in the current study. We showed the error rate, recall, precision, and bias index in the mock sample. The error rate of ONT R10.4.1 was greatly reduced, with a better recall in the case of the synthetic community. Meanwhile, in different types of environmental samples, ONT R10.4.1 analysis resulted in a composition similar to Pacbio data. We found that classification tools and databases influence ONT data. Based on these results, we conclude that the ONT R10.4.1 16S amplicon can also be used for application in environmental samples. IMPORTANCE: The long-read amplicon supplies the community with a species-level solution. Due to the high error rate of nanopore sequencing early on, it has not been frequently used in 16S studies. Oxford Nanopore Technologies (ONT) introduced the R10.4.1 flowcell with Q20+ reagent to achieve more than 99% accuracy as sequencing technology advanced. However, there has been no published study on the performance of commercial PromethION sequencers with R10.4.1 flowcells on 16S sequencing or on the impact of accuracy improvement on taxonomy (R9.4.1 to R10.4.1) using 16S ONT data. In this study, three types of microbiomes were investigated by 16S ribosomal RNA (rRNA) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1). In the mock sample, we displayed the error rate, recall, precision, and bias index. We observed that the error rate in ONT R10.4.1 is significantly lower, especially when deletions are involved. First and foremost, R10.4.1 and Pacific Bioscience platforms reveal a similar microbiome in environmental samples. This study shows that the R10.4.1 full-length 16S rRNA sequences allow for species identification of environmental microbiota.

Revealing the response of the soil bacterial community to external environmental disturbances is an important but poorly understood topic in microbial ecology. In this study, we evaluated the effect of high salinity on the bacterial community composition and key biogeochemical processes in salinized agricultural soils (0.22 to 19.98 dS m ⁻¹ ).

The mineral-organo composites control the speciation, mobility and bioavailability of heavy metals in soils and sediments by surface adsorption and precipitation. The dynamic changes of soil mineral, organic matter and their associations under redox, aging and microbial activities further complicate the fate of heavy metals. Over the past decades, the wide application of advanced instrumental techniques and modelling has largely extended our understanding on heavy metal behavior within mineral-organo assemblages. In this review, we provide a comprehensive summary of recent progress on heavy metal immobilization by mineral-humic and mineral-microbial composites, with a special focus on the interfacial reaction mechanisms of heavy metal adsorption. The impacts of redox and aging conditions on heavy metal speciations and associations with mineral-organo complexes are discussed. The modelling of heavy metals adsorption and desorption onto synthetic mineral-organo composites and natural soils and sediments are also critically reviewed. Future challenges and prospects in the mineral-organo interface are outlined. More in-depth investigations are warranted, especially on the function and contribution of microorganisms in the immobilization of heavy metals at the complex mineral-organo interface. It has become imperative to use the state-of-the-art methodologies to characterize the interface and develop in situ analytical techniques in future studies.

Soil contamination is one of the main threats to ecosystem health and sustainability. Yet little is known about the extent to which soil contaminants differ between urban greenspaces and natural ecosystems. Here we show that urban greenspaces and adjacent natural areas (i.e., natural/semi-natural ecosystems) shared similar levels of multiple soil contaminants (metal(loid)s, pesticides, microplastics, and antibiotic resistance genes) across the globe. We reveal that human influence explained many forms of soil contamination worldwide. Socio-economic factors were integral to explaining the occurrence of soil contaminants worldwide. We further show that increased levels of multiple soil contaminants were linked with changes in microbial traits including genes associated with environmental stress resistance, nutrient cycling, and pathogenesis. Taken together, our work demonstrates that human-driven soil contamination in nearby natural areas mirrors that in urban greenspaces globally, and highlights that soil contaminants have the potential to cause dire consequences for ecosystem sustainability and human wellbeing.