DOI: 10.5061/dryad.kd51c5b7h
title: Reconstruction of a soil microbial network induced by stress temperature

description: By applying a nonlinear time-series analysis to the metagenomic data of
 the soil microbiota cultured under suitable (30℃) or stressful (37℃)
 conditions, we show how the microbial interaction network responds to
 temperature stress. While the genera that persisted only under the
 suitable condition gave fewer positive effects, the genera that appeared
 only under the stressful condition received more positive effects in
 agreement with SGH. However, temperature changes also induce
 reconstruction of a community network, leading to an increased proportion
 of negative interactions at the whole community level. The anti-SGH
 pattern can be explained by the stronger competition caused by increased
 metabolic rate and population densities. 
description: The soil was sampled at depths of 5-10 cm from the surface in May
 19, 2011, and large particles were removed with a 2-mm mesh sieve. First,
 the soil suspended in phosphate-buffered saline (PBS) was homogenized
 using a blender. Then, large soil particles were allowed to settle by weak
 centrifugation (420 × g, 10 min, 10°C), and cells in the supernatant were
 transferred to a flask. Afterward, the precipitated soil particles were
 subjected to two more sets of cell isolation, after which a pooled cell
 suspension in the flask obtained from 1 kg of the soil was filtered (pore
 size 7μm) to remove small soil particles, and centrifuged (8000 × g, 20
 min, 10°C) to obtain cell pellets.  The microbial
 community was inoculated into liquid medium in a Sakaguchi flask and
 incubated at 30 °C and 37 °C with shaking in triplicate, respectively. The
 composition of the liquid medium was as follows: 1/10-strength W medium
 (KH2PO4, 170 mg; Na2HPO4, 980 mg; (NH4)2SO4, 100 mg; MgSO4, 48.7 mg;
 FeSO4, 0.52 mg; MgO, 10.75 mg; CaCO3, 2.0 mg; ZnSO4, 0.81 mg; CuSO4, 0.16
 mg; CoSO4, 0.15 mg; and H3BO3, 0.06 mg per liter), containing 10% the soil
 extract as a carbon source. We extracted soil
 microbiota community DNA using DNeasy PowerSoil Kit (QIAGEN, Hilden,
 Germany).  We amplified the V3-V4 region using 29
 cycles of denaturing at 98 °C for 15 s, annealing at 55 °C for 30 s, and
 extension at 68 °C for 30 s. Subsequently, PCR products were purified
 using AmPure XP. Then, amplicon libraries were indexed with a Nextera XT
 index kit (Illumina), followed by sequencing with an Illumina Miseq
 platform, using a Miseq reagent kit v3 (300 cycles, paired-end).
 We determined the total abundance of microbial community using
 qPCR with CFX Connect real-time system (Bio-Rad). DNA extraction
 efficiency was determined by adding a known concentration of DNA encoding
 the egfp gene as an internal standard. We used a
 nonlinear causality test, UIC, to identify the interaction between various
 soil microbiota genera. UIC is based on the state-space reconstruction
 founded on the Takens Embedding Theorem, and it was developed based on CCM
 (Sugihara et al., 2012; Osada & Ushio 2021). To avoid indirect
 interactions due to long time lag as much as possible, we fixed the time
 lag to −1 (i.e., 0.5 days). Then, results were verified as significant
 using bootstrap and surrogate data (Thiel et al. 2006). Furthermore, a
 regularized S-map (Cenci et al. 2019) was used to determine the strength
 and sign of individual interactions. For this investigation, we used the
 mean of the S-map coefficients at each time point to represent the
 strength of the interactions between the two genera.
description: GitHub. https://github.com/yutakaos/rUIC/tree/v0.1.5