Bathyarchaeia (formerly Bathyarchaeota) is a group of highly abundant archaeal communities that play important roles in global biogeochemical cycling. The presence of Bathyarchaeia in arable soils is relatively limited. In this study, we aimed to investigate the spatial distributions and diversity of Bathyarchaeia in paddy soils across eastern China, which is a major rice production region. The relative abundance of Bathyarchaeia among total archaea ranged from 3% to 68%, and Bathy-6 was the dominant subgroup. Bathyarchaeia showed higher migration ability and wider niche. Soil pH and C/N ratio were identified as key factors influencing the Bathyarchaeia composition, whereas C/N ratio and mean annual temperature influenced the relative abundance of Bathyarchaeia. Network analysis showed that specific Bathyarchaeia taxa occupied keystone positions in the archaeal community and co-occurred with some methanogenic and ammonia-oxidizing archaea. This study provides important insights into the biogeography and niche differentiation of Bathyarchaeia in agroecosystems.

Increasing evidence suggests that fungal communities are key components of biogeochemical cycles in coastal ecosystems. While several studies highlighted strong spatial patterns in fungal abundance and diversity, there are very few studies using a more integrative approach to study the spatio-temporal distribution of fungi, taking also the active part of the community into account. To better understand the consequences of anthropogenic activities, e.g. marine aquaculture, for fungal community composition and activities, we simultaneously evaluated the temporal (four different seasons) and spatial dynamics in total (DNA) and active (RNA) fungal communities in relation to several major physicochemical properties. Fungal communities were highly diverse, but showed the ubiquitous dominance of Dikarya and the occasional predominance of Glomeromycota, Mucoromycota, Mortierellomycota, Chytridiomycota, Mortierellomycota, Olpidiomycota, and Rozellomycota. Thereby, fungal diversity indices showed a much higher seasonal variation than with the degree of aquaculture activity, for both total and active communities. This notion is supported by co-occurrence networks exhibiting a clear seasonal pattern. Furthermore, fungal community structure in coastal waters showed distinct relationships with environmental factors varying both with season and in space. For both, total and active fungal communities, a combination of environmental variables such as temperature, DO and NO2- exhibited the greatest impact on community structure. Our study demonstrates a distinct spatio-temporal dynamics of both, total and active fungi and provides a foundation to better understand the ecological roles of marine fungi in coastal ecosystems in relation to mariculture activities.

Metagenomics and metatranscriptomics are powerful tools to uncover key microbes and processes driving biogeochemical cycling in natural ecosystems. Currently available databases depicting metabolic functions from metagenomic/metatranscriptomic data are not dedicated to biogeochemical cycles. There are no databases encompass genes involved in the cycling of dimethylsulfoniopropionate (DMSP), an abundant organosulfur compound. Additionally, a recognized normalization mode to estimate and compare the relative abundance and environmental importance of pathways from metagenomic and metatranscriptomic data has not been available. These limitations impact the ability to accurately relate key microbial driven biogeochemical processes to differences in environmental conditions. Thus, an easy to use specialized tool that infers and visually compares the potential for biogeochemical processes, including DMSP cycling, is urgently required. To solve these issues, we developed DiTing, a tool wrapper to infer and compare biogeochemical pathways among a set of given metagenomic or metatranscriptomic reads in one step, based on the KEGG (Kyoto Encyclopedia of Genes and Genomes) and a manually created DMSP cycling gene database. Accurate and specific formulas for over 100 pathways were developed to calculate their relative abundance. Output reports detail the relative abundance of biogeochemically-relevant pathways in both text and graphical format. We applied DiTing to metagenomes from simulated data, hydrothermal vents and the Tara Ocean project. The DiTing outputs were consistent with genetic feature of genomes used in simulated benchmark data, and also demonstrated that the predicted functional profiles correlated strongly with changes in environmental conditions. DiTing can now be confidently applied to wider metagenomic and metatranscriptomic datasets.