2.1 Study area and sampling:
Khartoum State (31.5-34 E, 15-16 N) is located in the heart of Sudan at the confluence of the White Nile and the Blue Nile, where the two rivers unite to form the River Nile. Most of the state lies in the climatic semi-desert region, while northern areas lie in desert zones. The climate of the state is ranging from hot to very hot. According to Köppen climate classification the climate of the state is warm desert climate (Bwh). The weather is rainy in summers, cold and dry in winters. Average rainfall reaches 100-200 mm in the north-eastern areas and 300-200 mm in the north-western areas. Temperature ranges in summer between 25-40 degrees in the months from April to June, and 20-35 in the months from July to October. In winter, however, temperatures continue to decline between November to March from 25--15 degrees.
Two sites in Khartoum State with different soil types (clay and sandy textures) were chosen to study the soil fungal community. The first site is located in Shambat area, Khartoum North and the second site is located in Omdurman locality particularly west Omdurman. Four land-use types were considered to collect the soil samples. These were onion (Allium cepa), Mango (Mangifera indica), forage sorghum (Sorghum bicolor (L.) Moench var. Abu Sabeen) and bare land that have not been cultivated for several years.
At each site and for each land-use, soil samples were collected from the top 20 cm of the surface soil of three locations (points); five replicates for each location were taken. Samples of the five replicates were mixed and pooled to make a composite sample for each collection point. GPS coordinates for each sampling point were recorded. A representative sample of each collection (about 1 Kg) was put in a plastic bag to be used for determination of soil properties. Also, 20 grams of the sample was taken in zip- lock plastic bags and kept cooled till being transferred to the laboratory for DNA extraction.
The sampling was conducted in two seasons, winter, and summer, following the same sampling technique.
2.2 Sample preparation:
In the laboratory, roots and rocks were removed from the samples before sieving. The 1 kg-sized samples were left to air-dry at room temperature, whereas samples taken for DNA extraction were kept at -20 C˚ until processed.
2.3 Soil analyses:
2.3.1 Determination of soil physicochemical properties:
Soil physicochemical properties were determined using the standard recommended methods. These were: particle size (clay%, sand% and silt%), saturation percent (SP%), pH, electrical conductivity (ECe in DS/m), calcium carbonate (CaCo3%), total nitrogen (N%), phosphorus (ppm), organic carbon (O.C%), organic matter (O.M%), Carbon/ Nitrogen ratio (C/N%) was calculated from the obtained N% and C%.
2.3.2 Metabarcoding and metagenomic analysis:
Each soil sample (250 mg) was used to extract the DNA using Qiagen Dneasy® PowrSoil® DNA extraction kit (Qiagen) according to the manufacturer’s instructions. The quality of the extracted DNA was checked using NanoDrop™ 2000c spectrophotometer (Thermo Fisher Scientific Inc, USA).
To study the soil fungal community, the ITS1 region was amplified using forward primer, ITS1FKYO2 (5′-TAGAGGAAGTAAAAGTCGTAA-3′) and the reverse primer ITS2KYO2 (5′ - TTYRCTRCGTTCTTCATC-3′, Toju et al. 2012). The forward primer was linked with Ion Torrent specific adapters and Ion-Xpress barcodes to ease samples demultiplexing.
PCR reaction mixtures (20 µl each) contained: 10 µl of Q5® Hot Start High-Fidelity 2X Master Mix (New England Biolabs, UK, Ltd), 0.5 µ l of each primer, 8.5 µ l of ultra-pure water (Prepared by Millipore Direct-Q® 3 UV Water Purification System) and 0.5 µ l of template DNA (1 to 10 µ g / µ l based on the checked concentrations). For each sample, PCR was performed in two replicates using BioRad T100™ Thermal Cycler (Bio-Rad Laboratories, Inc.).
The PCR program consisted of initial denaturation step at 98 ºC for 30 seconds;35 cycles of: 98 ºC for 10 seconds, 53 ºC for 30 seconds, 72 ºC for 1 minute; then final extension at 72 ºC for 2 minutes and incubation (infinite hold) at 12 ºC. The PCR products were verified using 1.2 % agarose gel in 1% TAE Buffer. An aliquot of 3 μl of each PCR product sample was loaded after mixing with 1 μl of SYBR green dye and 0.5 μl of 6x loading buffer. Then samples were allowed to separate for 20 minutes using 100 volts in MUPID-EXU horizontal electrophoresis system (Gel Company, Inc.).
A molecular weight marker (0.1-20 kbp Gene Ladder Wide 2, NIPPON GENE CO., LTD) was also loaded with the samples. The gel was visualized in FujiFilm Luminescent Image Analyzer Model LAS-4000 (FUJIFILM CORPORATION).
To purify the PCR amplicon from the excess primers, nucleotides, salts and enzymes, amplicons were subjected to high-throughput purification using AGENCOURT® AMPURE XP PCR Purification system (Beckman Coulter, Inc., Brea, CA). This system utilizes an optimized buffer to selectively bind PCR amplicons 100 bp and larger to paramagnetic beads.
The purified PCR products were quantified using Invitrogen QubitTM dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA, USA) as described by the manufacturer. Then the tubes were read in the Qubit® 2.0 fluorometer (Thermo Fisher Scientific).
According to the lowest concentration, the library was prepared by mixing different volumes of the purified PCR products in DNA LoBind tube (Eppendorf North America, Inc., USA). The size and the quantity of the library were checked using Agilent High Sensitivity DNA Kit (Agilent Technologies) in Agilent 2100 Bioanalyzer integrated with 2100 Expert software.
Emulsion PCR was conducted using Ion PGM Hi-Q View OT2 kit 400 on the Ion OneTouchTM 2 system (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Sequencing was then performed using Ion Personal Genome Machine (Thermo Fisher Scientific, Waltham, Massachusetts, USA) with Ion PGM sequencing 400 Kit and Ion 316TM chip v2 BC (Life Technology, Inc.).
2.3.3 Quantification of the fungal biomass using qPCR:
The quantitative PCR (Real Time PCR) was used to determine the quantity of the fungi in the soil samples using LightCycler® 2.0 Instrument and the LightCycler® FastStart DNA MasterPLUS SYBR Green I Kit (Roche Diagnostics GmbH, Mannheim, Germany). The primers set for fungal rRNA genes was nu-SSU-1196F (5′ -GGAAACTCACCAGGTCCAGA-3′) and nu-SSU-1536R (5′ - ATTGCAATGCYCTATCCCCA-3′, Borneman and Hartin 2000).
2.4 Metagenomic data processing
The ITS1 raw sequencing data were obtained from the Torrent Server-Torrent Suite™ as a demultiplexed FASTQ files. All analyses were done in QIIME2 version 2019.10.0 and 2020.6.0 (Bolyen et al. 2019), R software version 3.6.3 (R Core Team 2020) and RStudio version 1.2.5033 (RStudio Team 2019). Firstly, the primers were removed using QIIME2 Plugin 'cutadapt' version 2019.10.0 from package 'q2-cutadapt' version 2019.10.0 (Martin 2011; Bolyen et al. 2019). The data were then analyzed using DADA2 pipeline through the R package DADA2 version 1.16.0 (Callahan et al. 2016). The quality of the reads in the FASTQ data files was inspected, then the data were filtered and trimmed using DADA2 standard filtering parameters.
Chimeras were removed from each filtered read using removeBimeraDenovo function. Then the Amplicon Sequence Variants (ASVs) table was created. The table records the number of times each exact amplicon sequence variant was observed for each sample. The taxonomy was assigned to ASVs using assignTaxnomy function of dada2 package. The UNITE general FASTA release for Fungi Version 04.02.2020 (Abarenkov et al. 2020) was used as a reference database for the fungal ITS1 sequences.
Samples were checked for total number of reads to be more than 5,000 reads. To enable comparisons, the ASVs counts were standardized by transformation to relative abundance and then multiplication by the median sample read depth using phyloseq package (McMurdie and Holmes 2013). The standardized data were merged at the lowest available taxonomic level or annotation using modified tax_glom.kv function of the same package. The merged taxa were filtered by removing taxa that are only present at very low numbers in a small minority of samples, that are present at least 10 counts in at least 20% of samples or that have a total relative abundance of at least 1% of the total number of reads (Lennard). The filtered data were used for further analyses.
2.5 Soil fungal community composition and diversity:
To study the fungal diversity within each soil community, the observed taxa (Richness) and Shannon indices were used as alpha diversity (Within-samples) measures and they were measured on unmerged standardized data. The estimate_richness function of phyloseq package was used for this purpose.
Beta diversity (between-samples) was examined on the merged filtered taxonomies using Bray-Curtis dissimilarity measure and the non-metric multidimensional scaling (NMDS) as ordination method using phyloseq package. Heat maps for the top 50 most abundant taxa were created using unsupervised hierarchical clustering with Bray-Curtis distances for all samples.
2.6 Functional composition prediction:
The processed ASVs were used to predict functional communities of the samples. FUNGuild tool (v1.0 Beta) was used to taxonomically parse the fungal ASVs by ecological guild (Nguyen et al. 2016). The tool was used through the python script, provided by the tool developers, that has been run from the Ubuntu 16.04 command line.
2.7 Data analysis:
All analyses were performed in R software version 3.6.3 (R Core Team 2020).
The analysis of soil properties was conducted using one-way ANOVA to compare the properties for the different land-use in the same site and two-way ANOVA to compare the properties of land-use types in different sites.
Taxonomic bar plotst o show taxonomic composition (at different levels) in all samples phyloseq package and for each site with the different land-use type were created using phyloseq R package. On the other hand, Tukey's ‘Honest Significant Difference’ (TukeyHSD) test was carried out to determine the statistical differences between different sites and land-use types’ communities (alpha diversity measures). Then alpha diversity box plots were plotted using amplicon R package.
To examine how the composition of microbiome communities varies across different land-use types and the two sites, statistical test of significance on beta diversity was performed through permutational multivariate analysis of variance (PERMANOVA) using adonis function of vegan package version 2.5-6 (Oksanen et al. 2019).
The homogeneity of dispersion test was performed to estimate the homogeneity of each group regarding the taxonomic composition of their samples.
To determine the ASVs (taxa) that are significantly different between between the two sites, super.fitZig.kv function modified from metagenomeseq's fitzig and mrfulltable functions in R were used The following parameters were used to determine significance: the ASV should have 0.2% presence across samples, and that to keep only ASVs where at least one of the sites have 20% of the samples positive for that ASV, had a fold change (beta coefficient) of 1.25 and had adjusted p-value of 0.5.
2.8 Effect of study factors on soil fungal biomass
To study the effect of different land-use types, site and the two seasons on the fungal biomass (ITS gene copy number), two-way ANOVA was performed in R. Before that, Levene's Test for Homogeneity of Variance for different groups was performed using Levene's Test function in car package.