Resistance and resilience of soil microbiomes under climate change

Soil microbiomes play key roles in plant productivity and nutrient cycling, and we need to understand whether and how they will withstand the effects of global climate change. We exposed in situ soil microbial communities to multiple rounds of heat, drought, or both treatments, and profiled microbial communities with 16S rRNA and ITS amplicon sequencing during and after these climatic changes, and then tested how domain and symbiotic lifestyle affected responses. Fungal community composition strongly shifted due to drought and its legacy. In contrast, bacterial community composition resisted change during the experiment, but still was affected by the legacy of drought. We identified fungal and bacterial taxa with differential abundance due to heat and drought and found that taxa affected during climate events are not necessarily the taxa affected in recovery periods, showing the complexity and importance of legacy effects. Additionally, we found evidence that symbiotic groups of microbes important to plant performance respond in diverse ways to climate treatments and their legacy, suggesting plants may be impacted by past climatic events like drought and warming even if they do not experience the event themselves.

Methods
We conducted this study at the Koffler Scientific Reserve (KSR, www.ksr.utoronto.ca) in Ontario, Canada (latitude 44°01'48”N, longitude 79°32'01”W) in an old field environment.

We collected soil from a temperature-free-air-controlled enhancement experiment that had plots which were droughted, heated, droughted and heated, or left control. There were two periods of active treatment: rainout structures were present July-November 2020, and June-October 2021, for a total of 8 months; heaters were active in heated plots August-December 2020, and August 2021-January 2022, for a total of 9 months. There were three replicate plots per climate treatment, and we took three subsamples of soil per plot, per timepoint. Soil was sampled in June 2021 (first recovery period), September 2021 (active treatment), and June 2022 (second recovery period).

We extracted microbial DNA from the soil, and performed 16S rRNA amplicon sequencing on the conserved hypervariable V4 region (primer pair 515F-806R) and ITS region (primer pair ITS1FP2-58A2RP3). Raw data can be found on NCBI's Short Read Archive under PRJNA1177093. Reads from sub-samples of plots were then merged such that each plot had one set of reads per timepoint.

In QIIME2, we removed ASVs that had fewer than 10 reads across all samples, and assigned taxonomy using the ‘sklearn’ feature classifier (Pedregosa et al. 2011); we used Greengenes 16S V4 region reference for bacteria (McDonald et al. 2012), and UNITE (Nilsson et al. 2019) version 9.0 with dynamic clustering of global and 97% singletons for fungi. We then filtered out reads assigned as cyanobacteria and mitochondria to remove plant and animal DNA. Finally, for each of the bacterial and fungal datasets we constructed a phylogeny using QIIME2’s MAFFT (Katoh & Standley 2013) and FastTree (Price et al. 2010) functions to obtain a rooted tree. 

The .qza files were used downstream in the included R code.