From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package

Abstract

Soil microbial communities play critical roles in various ecosystem processes, but studies at a large spatial and temporal scale have been challenging due to the difficulty in finding the relevant samples in available data sets as well as the lack of standardization in sample collection and processing. The National Ecological Observatory Network (NEON) has been collecting soil microbial community data multiple times per year for 47 terrestrial sites in 20 eco-climatic domains, producing one of the most extensive standardized sampling efforts for soil microbial biodiversity to date. Here, we introduce the neonMicrobe R package-a suite of downloading, preprocessing, data set assembly, and sensitivity analysis tools for NEON's newly published 16S and ITS amplicon sequencing data products which characterize soil bacterial and fungal communities, respectively. neonMicrobe is designed to make these data more accessible to ecologists without assuming prior experience with bioinformatic pipelines. We describe quality control steps used to remove quality-flagged samples, report on sensitivity analyses used to determine appropriate quality filtering parameters for the DADA2 workflow, and demonstrate the immediate usability of the output data by conducting standard analyses of soil microbial diversity. The sequence abundance tables produced by neonMicrobe can be linked to NEON's other data products (e.g., soil physical and chemical properties, plant community composition) and soil subsamples archived in the NEON Biorepository. We provide recommendations for incorporating neonMicrobe into reproducible scientific workflows, discuss technical considerations for large-scale amplicon sequence analysis, and outline future directions for NEON-enabled microbial ecology. In particular, we believe that NEON marker gene sequence data will allow researchers to answer outstanding questions about the spatial and temporal dynamics of soil microbial communities while explicitly accounting for scale dependence. We expect that the data produced by NEON and the neonMicrobe R package will act as a valuable ecological baseline to inform and contextualize future experimental and modeling endeavors.

Niche modelling predicts that soil fungi occupy a precarious climate in boreal forests

“…Soil samples were derived from two sampling networks: the Dimensions of Biodiversity of Ectomycorrhizal Fungi (DoB‐Fun) network, which includes 68 sites distributed across North American forests dominated by Pinaceae, and the National Ecological Observatory Network (NEON), which includes 47 terrestrial sites distributed across all major eco‐climatic zones in the United States. DoB‐Fun samples were collected in 2011 through 2013, and we compiled data from all NEON soil samples collected in 2016 through 2018 (National Ecological Observatory Network, 2021) using the ‘neonMicrobe’ R package (Qin et al, 2021) in R version 3.6.0 (R Core Team, 2019). Across DoB‐Fun sites, sampling and DNA extraction were conducted using methods previously described by Talbot et al (2014).…”

Standardized NEON organismal data for biodiversity research

“…Users interested in further explorations of these data products may find more information on the NEON data portal (https://data.neonscience.org/). Additionally, concurrent work on a suggested bioinformatics pipeline and how to run sensitivity analyses on user‐defined parameters for NEON soil microbial data, including code and vignettes, is described in Qin et al (2021).…”

The National Ecological Observatory Network’s soil metagenomes: assembly and basic analysis

“…Complementary data streams can also be leveraged to link soil microbial data to ecosystem-level biogeochemical fluxes, plant growth, soil quality ( Vestergaard et al , 2017 ) and more. We recommend Qin et al (2021) for a discussion of the high-level questions that may be tackled using NEON soil microbial data; below we highlight a few topics and recommended resources.…”

“…NEON microbial data is well-suited for elucidating basic patterns in soil microbial ecology, such as the variation between communities at different spatial and temporal scales ( Qin et al , 2021 ). The nested sampling, in which soil samples come from plots within each site, can be used to investigate spatial variability and autocorrelation among genes or taxa ( Averill et al , 2021 ).…”

“…NEON performs amplicon sequencing (NEON.DP1.10108.001) for soil fungi and bacteria, approximately 3 times per year at each site. These amplicon sequencing data can be accessed through the specialized neonMicrobe R package ( Qin et al , 2021 ). To link amplicon sequences with metagenome-assembled genomes (MAGs; Section 6), MAGs must include the gene regions used for amplicon sequencing.…”