DOI: 10.5061/dryad.m37pvmczk
title: Effects of Hedysarum leguminous plants on soil bacterial microbiome in the Mu Us desert, northwest China

description: By assessing the influence of rhizocompartment types (i.e. root,
 rhizosphere soil, root zone soil, and inter-shrub bulk soil) on the
 diversity of soil microbial communities under desert leguminous plant
 shrubs, and the influence of, and variations in, soil physicochemical
 factors in interactions among leguminous plants, soil, and microbes. Both
 16S rRNA high-throughput genome sequencing and conventional soil
 physicochemical index determination were used to characterise the
 bacterial diversity and soil physicochemical properties in the
 rhizocompartments of two Hedysarum spp. (Hedysarum mongolicum and
 Hedysarum scoparium) in the Mu Us Desert. We found that all the nutrient
 indices (except TP and AP), values in rhizosphere soil were uniformly
 higher than those in root zone soil and inter-shrub bulk soil (P &lt;
 0.05). The bacterial community diversity in the root, under-shrub
 (rhizosphere, root zone) and inter-shrub bulk soil also have significant
 differences (P &lt; 0.05). Desert leguminous plants had significant
 effects on hierarchical filtration and enrichment of specific soil
 bacterial microbiomes (P &lt; 0.05). Root endophyte and rhizosphere
 soil microbiomes were mainly influenced by soil nutrients, while the
 bacterial communities in root zones soil and inter-shrub bulk soil were
 mainly influenced by soil pH and NH4+-N. The rhizocompartment types of
 desert leguminous plants have a significant influence on the diversity of
 soil microbial communities. According to our findings, nitrogen-fixing
 rhizobia can co-exist with non-symbiotic endophytes in the roots of desert
 leguminous plants, and plants have a hierarchical filtering and enriching
 effect on beneficial microbes in soil via rhizocompartments. Soil
 physicochemical factors have a significant influence on the structure and
 composition of microbial communities in various rhizocompartments, and
 this influence is derived from the interactions among leguminous plants,
 soil, and microbes.
description: After excavating to the roots, we used tweezers to pick up the
 soil particles adhering to the roots as rhizosphere soil only for
 determine soil physicochemical properties. After that, the roots were dug
 out and slightly shaken to remove the attached large soil aggregates, and
 gloves were worn to collect the large soil aggregates as root zone soil,
 which were then put into an aseptic bag. Root samples were obtained from
 the secondary or tertiary branches of plant roots, and healthy and intact
 roots with an even thickness (5-8 cm) were removed and stored in sterile
 sample bags. Inter-shrub bulk soil was collected at the same sampling
 depth as root zone soil, 10-40 cm below inter-shrub bare soil. All the
 samples collected were stored in preservation boxes with dry ice, and
 brought back to the laboratory for subsequent treatment.
 DNA was extracted from fresh 0.5 g samples using the EZNA Soil
 DNA Kit (Omega Bio-Tek, Norcross, GA, USA) following the manufacturer’s
 instructions, and stored at -80℃ for later use. After thawing on ice,
 extracted DNA samples were centrifuged separately and fully mixed; sample
 quality was determined using NanoDrop, and 30 ng DNA was used for PCR
 amplification. PCR amplification was performed in 25-μL reaction volumes
 containing 10× PCR buffer, 0.5 μL dNTPs, 1 μL of each primer, 3 μL bovine
 serum albumin (2 ng/μL), 12.5 μL 2× Taq Plus Master Mix, ultrapure
 H<sub>2</sub>O, and 30 ng template DNA. The PCR amplification
 program included initial denaturation at 94°C for 5 min, followed by 28
 cycles of denaturing at 94°C for 30 s, annealing at 55°C for 30 s, and
 extension at 72°C for 60 s, followed by completion of the PCR
 amplification program at 4°C. The forward primer F799
 (5′-AACMGGATTAGATACCCKG-3′) and reverse primer R1193
 (5′-ACGTCATCCCCACCTTCC-3′) were used to target the V5–V7 regions of 16S
 rRNA.  An agarose gel DNA purification kit (Axygen Biosciences, Union
 City, CA, USA) was used for purifying and combining PCR amplicons. After
 purification, PCR amplicons were mixed at an equimolar concentration,
 followed by paired-end sequencing using the Illumina MiSeq sequencing
 system (Illumina, San Diego, CA, USA) according to a standardised
 process. After sequencing using the Illumina MiSeq
 system (Illumina), the results were stored in Fastq format. The
 quantitative insights into microbial ecology (QIIME) software (version
 1.8; http://qiime.org/) was
 used to analyse original Fastq files and conduct quality control according
 to the following criteria: (i) base sequences with a
 quality score &lt; 20 at read tails were removed, and the window was
 set at 50 bp; if the mean quality score in the window was &lt; 20, the
 posterior-end base sequences were discarded from the window, and reads
 shorter than 50 bp were removed after quality control;
 (ii) paired reads were assembled into one sequence according to
 the overlapping relationship between paired-end reads (minimum overlapping
 length: 10 bp); (iii) the maximum allowable mismatch
 ratio of the overlapping areas of assembled sequences was set at 0.1, and
 sequences failing to meet this criterion in pairs were removed;
 (iv) samples were distinguished according to barcodes and primers
 at the head and tail ends of sequences, and the sequence directions were
 adjusted based on the number of mismatches allowed by barcodes;
 (v) different reference databases were selected according to the
 type of sequencing data, using Usearch (version 8.1.1861;
 http://www.drive5.com/usearch/) to remove chimeras, and smaller-length
 tags were discarded using Mothur to acquire clean tags of high-quality
 sequences. The sequences were clustered into
 operational taxonomic units (OTUs) using UPARSE (version 7.1;
 http://drive5.com/uparse/) based on a 97% sequence identity cut-off
 (excluding single sequences), and representative sequences and an OTU
 table were obtained.
description: After sequencing using the Illumina MiSeq system (Illumina), the
 results were stored in Fastq format (fastq1 and fastq2).