Illumina MiSeq sequencing reveals high arbuscular mycorrhizal fungi diversity in the rhizosphere soil of Prunus africana trees in fragmented Afromontane forests

doi:10.21203/rs.3.rs-2374240/v1

Download PDF

Research Article

Illumina MiSeq sequencing reveals high arbuscular mycorrhizal fungi diversity in the rhizosphere soil of Prunus africana trees in fragmented Afromontane forests

https://doi.org/10.21203/rs.3.rs-2374240/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 25 May, 2023

Read the published version in Annals of Microbiology →

You are reading this latest preprint version

Purpose Arbuscular mycorrhizal fungi (AMF) play a key role in the phytochemical modulation of medicinal plant species, besides their ecological role in shaping plant communities. Knowledge about the diversity and structure of AMF species associated with the endangered Prunus africana is valuable in the conservation and domestication of the species for its medicinal products. Methods Thus, we investigated the diversity and structure of AMF species communities in the rhizosphere soils of P. africana trees occurring in four fragmented Afromontane forests found in Cameroon; (Mount Cameroon and Mount Manengouba) and Kenya (Chuka and Malava) using Illumina Miseq of 18S rRNA gene amplicons. Results The forward and the reverse reads were A total of 64 virtual taxa (VT) belonging to eight genera were detected, namely Glomus (43 VT), Claroideoglomus (6 VT), Paraglomus (5 VT), Acaulospora (4 VT), Diversispora (3 VT), and Archaeospora, Pacispora, and Scutellospora with 1 VT each. Scutellospora heterogama VTX00286 was the most abundant and common species in all four sites (49.62%). Glomeraceae and Gigasporaceae were the most abundant families found across the sites, while Acaulosporaceae, Pacisporaceae, and Archaeosporaceae were rare, represented by <1% of all the detected taxa. Conclusion Our data show a high diversity of AMF species associated with P. africana, and variable community structure partially shaped by local edaphic factors. This study provides preliminary information on the possibility of using indigenous AMF inoculum, for the cultivation and domestication of P. africana for the sustainable management of this important medicinal plant.

Arbuscular mycorrhizal fungi

Prunus africana

Afromontane Forest

Metagenomic diversity

community composition

Cameroon

Kenya

Prunus africana (Hook F.) Kalkman (Rosaceae) is among the few endemic species found across all the Afromontane forests (White 1978; Kadu et al. 2013; Vinceti et al. 2013). It is an endangered species whose distribution range spans more than 22 African countries (Kadu et al. 2013; Vinceti et al. 2013). It has a wide distribution across fragmented Afromontane forests caused by anthropogenic disturbance. The bark of the medicinal P. africana tree is the most harvested and internationally traded non-timber forest product in Africa (Cunningham et al. 2016). Consequently, the bark of the tree is a high source of income for local communities where the species is found and is used in traditional pharmacopoeia to treat diseases such as stomach aches, urinary, and bladder infections, among others (Betti 2008; Bii et al. 2010; Otieno and Analo 2012; Mwitari et al. 2013; Koros et al. 2016). The phytochemical compounds in the tree's bark are used to treat benign prostate hyperplasia and potentially treat prostate cancer (Komakech et al. 2017). The high demand for the bark has led to unsustainable exploitation of P. africana population for several decades, leading to a threat to the species in its natural habitat (Cunningham et al. 2016). One of the key strategies to conserve the threatened P. africana is to facilitate its domestication. Therefore, knowledge of the occurrence, diversity, and interactions with its soil symbionts such as mycorrhiza in natural habitats is crucial information for the cultivation of P. africana for ex-situ regeneration.

There are two major types of mycorrhizae: arbuscular mycorrhizal fungi (AMF) and ectomycorrhizal fungi. Arbuscular mycorrhizal fungi are soil microorganisms belonging to the subphylum Glomeromycotina (Spatafora et al. 2016) and are associated with c 71 % of terrestrial plans (Brundrett and Tedersoo 2018). They are present in almost all ecosystems, from desert to arable lands, and tropical to temperate forests (Brundrett 2009; Heijden et al. 2015). The main characteristic of AMF species is the formation of tree-like subcellular structures inside the roots' cells of the host, known as arbuscle which plays a key role in the nutrient exchange between the two symbionts (Armstrong and Peterson 2002; Choi et al. 2018). Indeed, c 70–80 % of the overall plant’s inorganic phosphate (Pi), is provided by the fungus (Hoeksema et al. 2010). AMF species supply N and microelements like Zn, Fe,Mn, and Cu to their host (Adesemoye and Kloepper 2009). Besides nutritional function, AMF species can stimulate the plant’s immune system (Cameron et al. 2013), and alleviate biotic stress like soil pathogens, and abiotic stress like drought and salinity of the host plant (Morte et al. 2001; Begum et al. 2019; Nanjundappa et al. 2019; Porter et al. 2019). In return, c 3 to 20 % of the carbon (C) assimilated by the plant is allocated to the fungus (Bravo et al. 2017; Treseder et al. 2018). AMF species play a key role in ecosystem maintenance by shaping the plant community structure (Lin et al. 2015; Bauer et al. 2020). AMF species can modulate the soil structure and texture through their extraradical mycelium networks and contrbute to soil stability (Rillig et al. 2010; Pellegrino et al. 2020). Despite the ecological importance of AMF species, very little is known about their community composition in African tropical forests, particularly in Afromontane forests. AMF species community composition and diversity vary from one ecosystem to another, mostly due to the variation of environmental factors and host species (Husband et al. 2002; Lovelock et al. 2003; Opik et al. 2010; Rodríguez-Echeverría et al. 2017). In an earlier study, Wubet et al. (Wubet et al. 2004) indicated the presence of Glomus-dominated AMF types from roots of P. africana and spores obtained from trap cultures of indigenous soils from two dry Afromontane forests of Ethiopia. Previous studies have reported AMF species' effect on medicinal plant species' secondary metabolites. For instance, Almeida et al (Almeida et al. 2018) recorded a variation of bioactive compounds in Mikania laevigata and Mikania glomerata (Asteraceae) when inoculated with Rhizosphagus irregularis. These authors observed an increase of diterpene kaurenoic acid in M. laevigata leaves whereas a decrease of tricaffeoylquinic was reported in M. glomerata with R. irregularis inoculum. More recently, Tchiechoua et al. (Tchiechoua et al. 2020) showed that indigenous AMF species from the rhizosphere soil of P. africana were able to improve the growth and modulate the phytochemical compounds of vegetatively propagated P. africana plants in glasshouse conditions. Therefore, for the first time, we investigated the composition and structure of AMF species in the rhizosphere soil of P. africana found in four eco-climatically different Afromontane forests in Cameroon and Kenya, using Illumina MiSeq sequencing of the 18S rRNA gene. We also explored which edaphic factors could potentially affect AMF communities within these forests.

Overall sequencing information and taxonomy composition

The rarefaction curves showed that the intensity of sampling for all soil samples was sufficient to identify the majority of AMF present in all four sites (Fig. 1). All data obtained from the Illumina sequencing were deposited in the Sequence Read Archive (SRA) at NCBI under accession number PRJNA657954.

A total of 16,736,209 trimmed reads obtained from 7 soil samples were clustered into 16,279 features (OTUs) and assigned to the subphylum Glomeromycotina by using the MaarjAM database (Opik et al., 2010). Sample CT2 was discarded due to its low number of reads (16 reads). These features were grouped into eight families, namely Gigasporaceae (49.62%)-the most abundant across the samples, followed by Glomeraceae (37.3%), Claroideoglomeraceae (4.40%), Diversisporaceae (2.4%), Paraglomeraceae (2.15%), Acaulosporaceae (0.6%), Pacisporaceae (0.4%), and Archaeosporaceae (0.02%), while the rest (3.11%) were unclassified families (Figs. 2 and 3). Diversisporaceae, Acaulosporaceae, Pacisporaceae, and Archaeosporaceae were unique to Cameroonian sites (MC and MM). (Fig. 3).

At the species level, 64 AMF species or virtual taxa (VT) were identified as belonging to the genus Glomus (43 VT; 67.1%), Claroideoglomus (6 VT; 9.4%), Paraglomus (5 VT; 7.8%), Acaulospora (4 VT; 6.2%), Diversispora (3 VT; 4.7%), Archaeospora (1 VT; 1.6%), Pacispora (1 VT; 1.6%), and Scutellospora (1 VT; 1.6%) (Fig. 3). These results are also congruent with the average count abundance per family shown in Fig. 2. Species belonging to the genera Glomus, Claroideoglomus, Paraglomus, and Scutellospora were detected in all four sites. Diversispora species were not detected in sample CT1 from the Chuka site. Archaeospora and Pacispora had one species each, detected in samples MC2, MM1, and MM2, all from Cameroon. Scutellospora heterogama (VTX00286) appeared to be the most common species across all sample sites with the highest magnitude (Fig. 4, Additional file 1).

The four sites shared 39 VT (52% of the total number of different taxa identified) (Fig. 5). Cameroonian sites had the highest number of unique VT (27 VT from seven genera, namely Glomus, Acaulospora, Archaeospora, Claroideoglomus, Diversispora, Pacispora and Paraglomus; Additional file 2). Mount Cameroon (MC) had the highest number of unique species (10 AMF species), representing 13.3% of all species identified, whereas Chuka Tharaka-Nithi (CT) had one unique AMF species (Fig. 5).

AMF community diversity

Estimation of alpha diversity within AMF species communities using Shannon’s (H), Chao1 and ACE indices weighted more toward richness, and Simpson index (D) weighted toward evenness was conducted and shown in Fig. 6. Considering samples from Cameroon, observed OTUs in sample MM1 was the highest with 8195, whereas sample MC1 was the lowest with 3919. The highest observed OTUs in samples from Kenya were scored in MK1 with 5369 and the lowest in CT with 4079. However, there was no significant difference between samples from Cameroon and Kenya (Kruskal-Wallis test P = 0.7237). Shannon index for richness species was higher in three of the four samples from Cameroon (H_MM2=7.52, H_MC2=7.55, and H_MM1=7.56) compared to the samples from Kenya (H_CT1=6.88, H_MK1=7.21, and H_MK2=7.23) (Fig. 8). Nevertheless, there was no significant difference between the Shannon indices of the two countries (Kruskal-Wallis test, P = 0.1573). Evenness estimated using the Simpson index was highest in MM2, but with no significant difference between the provenances (Fig. 6).

The non-metric multidimensional scaling (NMDS) using the Bray-Curtis dissimilarity distance matrix showed that AMF species communities from Malava and Kakamega had more similarity to each other, while samples from Cameroon had less similarity (Fig. 7). The stress value of 0.014, indicates a good representation of ordinate.

Physicochemical parameters of the P. africana rhizosphere soil from Cameroon and Kenya

The physicochemical parameters of P. africana rhizosphere soil, collected in Cameroon and Kenya sites are shown in Table 1. The P. africana rhizosphere soils were acidic. Soil acidity was significantly higher in CT and MM than in MK and MC sites. The % C, total P (ppm), Na (ppm), and EC (mS/cm) were significantly higher in MC and MM (Cameroonian sites) than in MK and CT (Kenyan sites). In contrast, % N and the Ca (ppm) were significantly higher in MK and CT than in MC and MM sites.

Table 1

Physicochemical parameters of *P. africana* rhizosphere soil samples.
Site code	pH (H₂O)	EC (mS/cm)	%C	%N	P (mg L^− 1)	K (mg L^− 1)	Na (mg L^− 1)	Ca (mg L^− 1)
MK	6.8a	0.14c	7.6c	0.78a	7.9c	564a	18c	5316a
CT	5.9b	0.12d	8.3c	0.83a	6.00d	555a	11d	4470b
MC	6.7a	0.26a	14.9a	0.57b	37.3a	255b	81a	4085d
MM	6.2b	0.22b	12.4b	0.66b	35.1b	565a	77b	4339c

Malava Kakamega (MK), Chuka Tharaka-Nithi (CT), Mount Cameroon (MC), and Mount Manengouba (MM) sites. Values followed by the same letter do not differ significantly according to the ANOVA test, P < 0.05, n = 4.

Relationship between soil physicochemical properties and AMF communities

The physicochemical analyses of P. africana rhizosphere soil indicated that the available P concentration in samples from Cameroon was almost 5-fold greater than in samples from Kenya, whereas the concentration of total N in samples from Kenya was significantly higher compared to samples from Cameroon (Table 1). However, there was a weak correlation between AMF species community composition and physicochemical parameters when the db-RDA analysis was performed on Bray-Curtis dissimilarity distance (Fig. 8). The eigenvalues of the first two axes of db-RDA were 0.09 and 0.02, and the first axis explained 79% whereas the second explained 19% of the variance in the AMF species–physicochemical parameters relationship. The abundance of AMF species in samples from MK was positively correlated with the available P in the soil and negatively correlated with the total N and K. In addition, total N and K were positively correlated to the abundance of AMF species in MC and CT (Fig. 8).

AMF composition and diversity have been poorly reported in relationship with medicinal plants in Afromontane regions, though they are of interest for plant growth and phytochemical improvement (Solaiman and Anawar 2015). A recent study showed a positive effect of indigenous AMF inoculum from rhizosphere soil on the growth and phytochemical compounds of P. africana seedlings when compared to the non-mycorrhizal plants (Tchiechoua et al. 2020). Thus, this study aimed to assess the community composition and diversity of AMF in the rhizosphere soil of P. africana found in four fragmented Afromontane forests of Cameroon and Kenya, using Next Generation Sequencing technology. We obtained a total of 16,736,209 sequences, clustered into 16,279 OTUs, representing eight Glomeromycotina families (Gigasporaceae, Glomeraceae, Claroideoglomeraceae, Diversisporaceae, Paraglomeraceae, Acaulosporaceae, Pacisporaceae, and Archaeosporaceae), with a total of 64 virtual taxa (VT). Our study shows a high species richness compared to an earlier study of AMF associated with P. africana in dry Afromontane forests of Ethiopia using low-throughput sequencing and internal transcribed spacer (ITS) as a marker gene method on roots and trap cultures. They identified taxa belonging only to three AMF families: Glomeraceae, Diversisporaceae, and Archaeosporaceae (Wubet et al. 2004). However, the difference in the detection of AMF associated with P. africana is also likely due to the methods used: high- vs low-throughput sequencing, and rhizosphere soil vs root and spores from trap cultures. In our study, we observed that the Gigasporaceae family had the highest number of OTUs, with the only VT identified to species level (Scutellospora heterogama VTX00286) found in all the four sites. Members of Gigasporaceae are known to be nearly as dominant as those of Glomeraceae in Afrotropical biomes and are reported to be overrepresented in the tropics biogeography database (Stürmer et al. 2018). At the species level, several studies using low-throughput (Moreira et al. 2006; Lakshmipathy et al. 2012; Wetzel et al. 2014; Pereira et al. 2020) to high-throughput (Schlaeppi et al. 2016; Egan et al. 2018; Marinho et al. 2019) have revealed the presence of Scutellospora species (Gigasporaceae) in samples from tropical environments. Contrary to findings from these studies, Opik et al. (Opik et al. 2010) found that the Gigasporaceae family was underrepresented in Africa. However, in our study, the only representative of the Gigasporaceae family represented only 6% of the total VT. In contrast, the Glomeraceae family had 43 VT, representing 67.1% of taxa identified. This is not surprising since numerous studies have shown that members of the Glomeraceae family are ubiquitous, and cosmopolitan found distributed throughout the world on all or nearly all continents and climatic zones (Opik et al. 2010; Stürmer et al. 2018; Lara-Pérez et al. 2020).

Although we did not observe a significant difference in AMF diversity when considering the alpha diversity indices, there were unique differences between or among sites. The diversity of AMF was generally higher in samples from Cameroon than Kenya. Similarly, the Venn diagrams (Fig. 6) showed that Cameroonian samples had more unique AMF species, representing 36% of the total VT, whereas Kenyan samples only had 12% of the total VT. On the other hand, the beta diversity showed a distinct community composition between the samples from different country provenances, suggesting a strong influence of local biotic and abiotic factors as reported for other studies in the tropics (Alguacil et al. 2015; Stevens et al. 2020).

Various biotic and abiotic factors can explain the differences in the diversity indices and community structure of AMF. Zhao et al. (Zhao et al. 2017) showed that soil clay content was negatively correlated with the AMF diversity in a semi-arid mountain in China, while Vieira et al. (Vieira et al. 2020) indicated that higher soil clay content was found with less AMF richness in soil samples in a tropical semi-arid region of Brazil. In this study, we found differences in a few physicochemical properties among sites, and are likely to have influenced local the diversity and structure of AMF species communities in these Afromontane sites. For instance, the application of db-RDA using Bray-Curtis distance dissimilarity showed that available P, the total N, and the K content were correlated with the AMF community structure. In contrast, soil pH did not appear to be one of the factors shaping the AMF composition at any of the sites investigated. A similar observation was made by Abdedaiem et al. (Abdedaiem et al. 2020); even though soil pH has previously been shown to be one of the main factors besides available P that influence the AMF community composition (Bainard et al. 2014; Trevizan Chiomento et al. 2019). Previous studies found a negative correlation between available P and AMF community composition diversity (Bainard et al. 2014; Abdedaiem et al. 2020). Besides, none of the soil parameters measured significantly impacted the AMF community composition in the rhizosphere soil of P. africana. Similar observations were made in a study by Manoharan et al. (Manoharan et al. 2017) that investigated AMF species diversity under the influence of agricultural management practices. Our results suggest that soil physicochemical parameters and a host of other factors, including climate, should be considered when studying the AMF community composition and diversity in rhizosphere soil. For instance, the geographical distance was also identified as one of the main factors influencing the AMF community composition and diversity when considering aspects like climate, soil type, land use type, and vegetation type (Xu et al. 2016; Hontoria et al. 2019; Huang et al. 2019). Therefore, the differences we observed in the community composition of AMF species might also be attributed to other local factors yet to be established, than only to the physicochemical composition of the rhizosphere soil of P. africana in these forests.

Using 18S Metagenomics in this study revealed a higher diversity and distinct composition of AMF communities associated with P. africana than in previous studies. Our data showed that the AMF community in Cameroon had higher VT than that in Kenya. Moreover, Scutellospora heterogama VTX00286 was identified as the most common and abundant VT at the species level. Also, 39 VT were common in the samples from Cameron and Kenya. In contrast, 27 VT were exclusively identified in Cameroonian samples, whereas only 9 VT were exclusively identified in Kenyan samples. Further investigation of AMF community composition in P. africana roots should bring more insights into the factors and mechanisms underpinning their symbiotic interactions and guide the production of improved AMF inoculum to support propagation and conservation work in these forests.

Study sites

The study was carried out in four Afromontane sites in Cameroon and Kenya (Fig. 9). In Cameroon, the two targeted sites were Mount Cameroon (MC) and Mount Manengouba (MM), 120 km from each other. The MC site is in the South-West Region of Cameroon at 04°08'34.3'' N; 09°07'21.0'' E, 2280 meters above sea level (masl). The annual rainfall in MC is one of the highest in the world ranging between1,800 mm and 12,000 mm with two seasons; the dry season from November to February and the rainy season from March to October. The mean temperature is 25°C and the relative humidity ranges between 75% and 80% throughout the year (Fonge et al. 2019). The vegetation in MC is mainly composed of a dense layer of graminaceous species and tall herbaceous species belonging to the Acanthaceae and Begoniaceae families. The main tree species include Agauria sp. (Ericaceae), Crassocephalum mannii (Asteraceae), Hypericum sp. (Hypericaceae), and a less dense population of P. africana (Nkeng et al. 2010). The MM site is located between the Littoral and South-West Regions at 05°01'50.8'' N; 09°49'31.7'' E, 1968 masl. The MM site is dominated by dense undergrowth, including Aframomum sp., Acanthaceae, Brillantaceae, Begoniaceae, and Gramineae family, while the main trees species are Harungana madagascariensis (Hypericaceae), Maesa lanceolata (Primulaceae), Polyscias fulva (Araliaceae‎), and P. africana (Nkeng et al. 2010). Both MC and MM sites have volcanic soil types (Andosol) that vary from loam to silt loam, and the top layer is rich in organic matter (Manga et al. 2014; Tegha and Yinda 2016). Both mountains are located on the Cameroon Volcanic Line magmatism (De Plaen et al. 2014). In Kenya, the two targeted sites were the Chuka forest (CT) and Malava forest (MK) separated by approximately 320 km. The CK site is located near Chuka Tharaka-Nithi in the Central Province of Kenya at 0°17'45.57'' N, 37°36'52.85'' E, 1620 masl. The annual rainfall is bimodal and ranges from 1500 to 2500 mm. The vegetation in the CT site is dominated by a range of species, including Podocarpus latifolia (Podocarpaceae), Artemisia afra (Asteraceae), Croton macrostachus (Euphorbiaceae), and P. africana among others. The soils are red with high clay content, and Nitisols, Cambisols, and Andosols are the main soil groups (Kaburi and Medley 2011; Mugo 2015). The MK Forest is located in Kakamega in the Western province at 0°27'57.57'' N, 34°52'8.55'' E, 1615 masl. The annual temperature in the region is about 25°C with a hot and wet climate, and annual rainfall ranging between 1500 mm and 2000 mm (Seswa et al. 2018). The dominant species include P. africana and several other species belonging to Euphorbiaceae, Moraceae, Rubiaceae, Acanthaceae, Fabaceae, and Bignoniaceae (Additional file 1) (Seswa et al. 2018).

Soil sampling and analysis

Soil sample collection

In each of the four sites (Mount Cameroon: MC; Mount Manengouba: MM; Chuka Tharaka-Nithi: CT; Malava Kakamega: MK) (Fig. 1), 20 mature P. africana trees (≥ 30 cm dbh) were randomly selected. Rhizosphere soil samples were collected from each tree at four cardinal points by following the roots from the trunk to the fine roots, and at about 20 cm from the trunk. Each sample consisted of approximately 50g of soil collected aseptically at a depth of 30 cm, after removing the surface soil litter. The samples from each tree were then pooled to form a composite sample of 200 g per tree. Subsequently, the composite sample per tree was further pooled to form a composite sample of 4 kg per site. A subsample of 500 g from each composite sample was air-dried at ambient temperature for soil chemical analyses. The remaining subsamples were taken to the laboratory and stored at 4°C for molecular analyses.

Soil chemical analyses

Soil samples were analyzed to determine the pH (H2O), electrical conductivity (EC), percentage of carbon (% C), total nitrogen (% N), available phosphorus (P), potassium (K), sodium (Na), and calcium (Ca), present in the soil samples at the Kenya Forestry Research Institute (KEFRI) soil analysis laboratory as described by Odee et al. (Odee et al. 2002).

Soil DNA extraction

For each composite soil sample, 100 g of sample was ground using a mortar and pestle. A duplicate subsample of 0,25 g of the ground soil was used to extract gDNA using the DNeasy PowerSoil kit following the supplier’s recommendation (Qiagen, Hilden, Germany). Quantification and quality control of extracted DNA was done using a NanoDrop™ 2000 spectrophotometer (Thermo Scientific, USA) and 0.8% agarose gel electrophoresis. The concentration of extracted DNA was normalized to 25 ng/µl in a total volume of 50 µl. Amplification of the small subunit of the rDNA (SSU rDNA) region was conducted using the primer pairs AML1/AML2 known to have better specificity and coverage for AMF diversity (Lee et al. 2008). However, previous studies have mentioned that non-target amplification PCR reaction was done using the Taq PCR Kit (New England, BioLabs® Inc, USA), in a reaction volume of 50 µl, containing 5 µl of 10X Standard Taq Reaction Buffer, 1 µl of 10 mM dNTPs, 1 µl of 10 µM AML1 (forward), 1 µl of 10 µM AML2 (reverse), 5 µl of 25 ng/µl DNA template and 0.5 µl of 0.5 U Taq DNA polymerase. Thermocycling conditions were as follows: initial denaturation at 94 ⁰C for 3 min, followed by 35 cycles at 94 ⁰C for 1 min, 58 ⁰C for 1 min, 72 ⁰C for 1 min, and a final extension step at 72 ⁰C for 10 min.

Library preparation and Illumina MiSeq sequencing

Before library preparation, PCR products were purified using the QIAquick® PCR purification kit (Qiagen, USA). Quantification was done using NanoDrop™ 2000 spectrophotometer (Thermo Scientific, USA) and the PCR purified products were normalized to 30 ng/µl. Amplicons were further diluted to 0.5 ng/µl using nuclease-free water and quantified by Qubit® fluorometry (Thermo Scientific, USA), and used for library preparation. The library construction was done using Nextera XT DNA Sample Preparation Kit (Illumina, San Diego, USA) following the manufacturer’s protocol. This protocol started with an enzymatic reaction called tagmentation where the enzyme transposase fragmented and tagged the amplicon samples with adapters in random positions. The sequencing indices were added to the fragmented amplicons through a PCR reaction of 12 cycles. This step was followed by amplicon purification and size selection using AMPure® XP beads (Beckman Coulter, USA) technology. The products were quantified using Qubit® fluorometry with the dsDNA HS (High Sensitivity) Assay kit (Thermo Scientific, USA) and the quality and size were checked using the Agilent TapeStation 2000 system (Agilent Technologies, USA). The quantified and sized amplicons were normalized, pooled at equimolar concentrations, and then submitted for sequencing to Illumina MiSeq 300PE reads.

Bioinformatics and statistical analyses

All bioinformatics analyses were performed using the Quantitative Insights Into Microbial Ecology (QIIME2) version 2019.10 (https://docs.qiime2.org/2019.10/) (Caporaso et al. 2010). The FASTQ files containing the forward and the reverse reads obtained were first checked for quality control using FastQC v0.11.7 (Andrews 2010). The sequences were demultiplexed to assign each read to a specific sample using q2-demux, and then, the sequences were denoised and trimmed to retain only bases with a quality score greater than 25. The sequences were then truncated from the 3’ end of the forward and the reverse sequences at 240 and 200 bp, respectively, using the qiime deblur plugging pipeline (Amir et al. 2017). Sample CT2 was discarded due to the low number of sequence reads (< 1000). Picking and clustering of the operational taxonomic units (OTUs) were done using the Silva 138 database (https://www.arb-silva.de/) and the taxonomy assignment was done using MaarjAM 5 database (Opik et al. 2010) (http://maarjam.botany.ut.ee/) as a classifier in QIIME2 q2-feature-classifier plugin (Bokulich et al. 2018) with 97 % similarity. The features table also known as the OTUs table and the taxonomy table genrated from QIIME2 were extracted and imported into R 4.0 (R Core Team 2020) as phyloseq objects for downstream analyses. All statistical analyses were performed using the R software version 4.0 (R Core Team 2020) unless otherwise specified. To estimate the AMF OTUs diversity among the samples from Cameroon and Kenya separately, the count reads were transformed and normalized into relative abundance (Lemos et al. 2011) using the “filter.taxa()” function of the phyloseq package (version 1.32.0) in R software (McMurdie and Holmes 2013). The significant difference between the alpha diversity metrics of AMF taxa from Cameroon and Kenya was calculated using the Kruskal-Wallis test. The Beta diversity was carried out to compare the AMF community between the different samples using the non-metric multidimensional scaling (NMDS), based on the Bray-Curtis dissimilarity distance matrix with the function “metaMDS()” of the vegan package (version 2.5-6). The dissimilarity matrices were then plotted on the principal coordinate. The relationship between the main soil physicochemical parameters and the AMF community composition was tested using the distance-based redundancy analysis (db-RDA) (Legendre and Andersson 1999), applying the function “capscale()” of the vegan package version 2.5-6 (Oksanen et al. 2019) in R (version 4.0). A Venn diagram analysis was conducted to identify unique and shared AMF communities among the samples and provenance in the online interactive tool Venny (https://bioinfogp.cnb.csic.es/tools/venny/).

AMF

Arbuscular mycorrhizal fungal

Virtual taxa

OTUs

Operational taxonomy units

db-RDA

Distance-based redundancy analysis

NMDS

Non-metric multidimensional scaling

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Competing interests

The authors declare that they have no competing interests

Funding

The sampling collection was supported by the Pan African University Institute of Basic Science, Technology and Innovation of the African Union Commission. The soil physicochemical analysis was supported by the Kenya Forestry Research Institute (KEFRI) and the LTS-ODA SUNRISE Programme (#NEC06476), UK Centre for Ecology and Hydrology (UKCEH). The metagenomics analyses were funded by the BecA-ILRI Hub through the Africa Biosciences Challenge Fund (ABCF) program. The ABCF program is funded by the Australian Department for Foreign Affairs and Trade (DFAT) through the BecA-CSIRO partnership; the Syngenta Foundation for Sustainable Agriculture (SFSA); the Bill & Melinda Gates Foundation (BMGF); the UK Department for International Development (DFID) and the Swedish International Development Cooperation Agency (SIDA).

Authors' contributions

YT, DWO, EN, ML, JK, VN, and RP conceptualized the study. YT, EM, and RP collected data. YT and BW performed the data analysis. YT, DWO, and RP interpreted the data. YT wrote the initial draft. All the authors contributed to the final manuscript and approved the submitted version.

Acknowledgements

The authors would like to thank Emmanuel Makatiani, Charles Oduor from Biotechnology Laboratory, Kenya Forestry Research Institute (KEFRI) and Enthua Yossa Armel from the University of Yaounde I for their assistance during the sampling collection; John Gicheru from Biotechnology Laboratory, Kenya Forestry Research Institute (KEFRI) for his support during the molecular analyses; Dr Jean-Baka Domelevo and John Juma from Biosciences Eastern and Central Africa - International Livestock Research Institute (BecA-ILRI) Hub for their assistance during the metagenomics analyses.

Abdedaiem R, Rejili M, Mahdhi M, et al (2020) Phylogeny and distribution of arbuscular mycorrhizal fungi associated with Vachellia tortilis ssp. raddiana in relation to soil properties under arid ecosystems of Tunisia. Mycol Prog 19:495–504. https://doi.org/10.1007/s11557-020-01572-w
Adesemoye AO, Kloepper JW (2009) Plant-microbes interactions in enhanced fertilizer-use efficiency. Appl Microbiol Biotechnol 85:1–12. https://doi.org/10.1007/s00253-009-2196-0
Alguacil MM, Torrecillas E, Lozano Z, Roldán A (2015) Arbuscular mycorrhizal fungi communities in a coral cay system (Morrocoy, Venezuela) and their relationships with environmental variables. Science of the Total Environment 505:805–813. https://doi.org/10.1016/j.scitotenv.2014.10.030
Almeida C de L, Sawaya ACHF, de Andrade SAL (2018) Mycorrhizal influence on the growth and bioactive compounds composition of two medicinal plants : Mikania glomerata Spreng . and Mikania laevigata Sch . Bip . ex Baker (Asteraceae). Brazilian Journal of Botany 41:233–240. https://doi.org/10.1007/s40415-017-0436-6
Amir A, Daniel M, Navas-Molina J, et al (2017) Deblur Rapidly Resolves Single-. American Society for Microbiology 2:1–7
Andrews S (2010) A Quality Control Tool for High Throughput Sequence Data [Online]
Armstrong L, Peterson RL (2002) The interface between the arbuscular mycorrhizal fungus Glomus intraradices and root cells of Panax quinquefolius: A Paris-type mycorrhizal association. Mycologia 94:587–595. https://doi.org/10.1080/15572536.2003.11833187
Bainard LD, Dai M, Gomez EF, et al (2014) Arbuscular mycorrhizal fungal communities are influenced by agricultural land use and not soil type among the Chernozem great groups of the Canadian Prairies. Plant Soil 387:351–362. https://doi.org/10.1007/s11104-014-2288-1
Bauer JT, Koziol L, Bever JD (2020) Local adaptation of mycorrhizae communities changes plant community composition and increases aboveground productivity. Oecologia 192:735–744. https://doi.org/10.1007/s00442-020-04598-9
Begum N, Qin C, Ahanger MA, et al (2019) Role of Arbuscular Mycorrhizal Fungi in Plant Growth Regulation: Implications in Abiotic Stress Tolerance. Front Plant Sci 10:1–15. https://doi.org/10.3389/fpls.2019.01068
Betti JL (2008) Non- detriment findings report on Prunus africana (Rosaceae) in Cameroon
Bii C, Korir KR, Rugutt J, Mutai C (2010) The potential use of Prunus africana for the control, treatment and management of common fungal and bacterial infections. Journal of Medicinal Plants Research 4:995–998. https://doi.org/10.5897/JMPR09.227
Bokulich NA, Kaehler BD, Rideout JR, et al (2018) Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6:1–17. https://doi.org/10.1186/s40168-018-0470-z
Bravo A, Brands M, Wewer V, et al (2017) Arbuscular mycorrhiza-specific enzymes FatM and RAM2 fine-tune lipid biosynthesis to promote development of arbuscular mycorrhiza. New Phytologist 214:1631–1645. https://doi.org/10.1111/nph.14533
Brundrett MC (2009) Mycorrhizal associations and other means of nutrition of vascular plants: Understanding the global diversity of host plants by resolving conflicting information and developing reliable means of diagnosis. Plant Soil 320:37–77. https://doi.org/10.1007/s11104-008-9877-9
Brundrett MC, Tedersoo L (2018) Evolutionary history of mycorrhizal symbioses and global host plant diversity. New Phytologist
Cameron DD, Neal AL, van Wees SCM, Ton J (2013) Mycorrhiza-induced resistance: More than the sum of its parts? Trends Plant Sci 18:539–545. https://doi.org/10.1016/j.tplants.2013.06.004
Caporaso JG, Kuczynski J, Stombaugh J, et al (2010) correspondEnce QIIME allows analysis of high-throughput community sequencing data Intensity normalization improves color calling in SOLiD sequencing. Nature Publishing Group 7:335–336. https://doi.org/10.1038/nmeth0510-335
Choi J, Summers W, Paszkowski U (2018) Mechanisms Underlying Establishment of Arbuscular Mycorrhizal Symbioses. Annu Rev Phytopathol 56:1–26. https://doi.org/doi.org/10.1146/annurev-phyto-080516- 035521
Cunningham A, Anoncho VF, Sunderland T (2016) Power, policy and the Prunus africana bark trade, 1972 – 2015. J Ethnopharmacol 178:323–333. https://doi.org/10.1016/j.jep.2015.11.042
De Plaen RSM, Bastow ID, Chambers EL, et al (2014) The development of magmatism along the Cameroon Volcanic Line: Evidence from seismicity and seismic anisotropy. J Geophys Res Solid Earth 119:4233–4252. https://doi.org/10.1002/2013JB010583
Egan CP, Rummel A, Kokkoris V, et al (2018) Using mock communities of arbuscular mycorrhizal fungi to evaluate fidelity associated with Illumina sequencing. Fungal Ecol 33:52–64. https://doi.org/10.1016/j.funeco.2018.01.004
Fonge BA, Essomo SE, Bechem TE, et al (2019) Market trends and ethnobotany of orchids of Mount Cameroon. J Ethnobiol Ethnomed 15:1–11. https://doi.org/10.1186/s13002-019-0308-1
Heijden MGA van der, Martin FM, Selosse M-A, Sanders IR (2015) Mycorrhizal ecology and evolution: the past, the present, and the future. New Phytologist 205:1406–1423. https://doi.org/10.1111/nph.13288
Hoeksema JD, Chaudhary VB, Gehring CA, et al (2010) A meta-analysis of context-dependency in plant response to inoculation with mycorrhizal fungi. Ecol Lett 13:394–407. https://doi.org/10.1111/j.1461-0248.2009.01430.x
Hontoria C, García-González I, Quemada M, et al (2019) The cover crop determines the AMF community composition in soil and in roots of maize after a ten-year continuous crop rotation. Science of the Total Environment 660:913–922. https://doi.org/10.1016/j.scitotenv.2019.01.095
Huang Z, Zhao F, Wang M, et al (2019) Soil chemical properties and geographical distance exerted effects on arbuscular mycorrhizal fungal community composition in pear orchards in Jiangsu Province, China. Applied Soil Ecology 142:18–24. https://doi.org/10.1016/j.apsoil.2019.05.017
Husband R, Herre EA, Turner SL, et al (2002) Molecular diversity of arbuscular mycorrhizal fungi and patterns of host association over time and space in a tropical forest. Mol Ecol 11:2669–2678. https://doi.org/10.1046/j.1365-294X.2002.01647.x
Kaburi SM, Medley KE (2011) Community Perspectives on Fuelwood Resources in East Africa. Mt Res Dev 31:315–324. https://doi.org/10.1659/mrd-journal-d-10-00121.1
Kadu CAC, Konrad H, Schueler S, et al (2013) Divergent pattern of nuclear genetic diversity across the range of the Afromontane Prunus africana mirrors variable climate of African highlands. Ann Bot 47–60. https://doi.org/10.1093/aob/mcs235
Komakech R, Kang Y, Lee JH, Omujal F (2017) A review of the potential of phytochemicals from Prunus africana (Hook f.) Kalkman stem bark for chemoprevention and chemotherapy of prostate cancer. Evidence-based Complementary and Alternative Medicine 1–11
Koros H, Malombe I, Mwendwa K, et al (2016) Indigenous Knowledge, Uses and Conservation of Prunus africana (Hook. F.) Kalkman in Nandi Forests. Journal of Natural Sciences Research 6:56–62
Lakshmipathy R, Balakrishna AN, Bagyaraj DJ (2012) Abundance and diversity of AM fungi across a gradient of land use intensity and their seasonal variations in Niligiri Biosphere of the Western Ghats, India. Journal of Agricultural Science and Technology 14:903–918
Lara-Pérez LA, Oros-Ortega I, Córdova-Lara I, et al (2020) Seasonal shifts of arbuscular mycorrhizal fungi in Cocos nucifera roots in Yucatan, Mexico. Mycorrhiza. https://doi.org/10.1007/s00572-020-00944-0
Lee J, Lee S, Young JPW (2008) Improved PCR primers for the detection and identification of arbuscular mycorrhizal fungi. Federation of European Microbiological Societies 65:339–349. https://doi.org/10.1111/j.1574-6941.2008.00531.x
Legendre P, Andersson MJ (1999) Distance-based redundancy analysis: Testing multispecies responses in multifactorial ecological experiments. Ecol Monogr 69:1–24. https://doi.org/10.1890/0012-9615(1999)069[0001:DBRATM]2.0.CO;2
Lemos LN, Fulthorpe RR, Triplett EW, Roesch LFW (2011) Rethinking microbial diversity analysis in the high throughput sequencing era. J Microbiol Methods 86:42–51. https://doi.org/10.1016/j.mimet.2011.03.014
Lin G, Mccormack ML, Guo D (2015) Arbuscular mycorrhizal fungal effects on plant competition and community structure. Journal of Ecology 103:1224–1232. https://doi.org/10.1111/1365-2745.12429
Lovelock CE, Andersen K, Morton JB (2003) Arbuscular mycorrhizal communities in tropical forests are affected by host tree species and environment. Oecologia 135:268–279. https://doi.org/10.1007/s00442-002-1166-3
Manga VE, Agyingi CM, Suh CE (2014) Trace Element Soil Quality Status of Mt. Cameroon Soils. Advances in Geology 2014:1–8. https://doi.org/10.1155/2014/894103
Manoharan L, Rosenstock NP, Williams A, Hedlund K (2017) Agricultural management practices influence AMF diversity and community composition with cascading effects on plant productivity. Applied Soil Ecology 115:53–59. https://doi.org/10.1016/j.apsoil.2017.03.012
Marinho F, Oehl F, da Silva IR, et al (2019) High diversity of arbuscular mycorrhizal fungi in natural and anthropized sites of a Brazilian tropical dry forest (Caatinga). Fungal Ecol 40:82–91. https://doi.org/10.1016/j.funeco.2018.11.014
McMurdie PJ, Holmes S (2013) Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS One 8:. https://doi.org/10.1371/journal.pone.0061217
Moreira M, Baretta D, Siu MT, Cardoso EJBN (2006) Spore density and root colonization by arbuscular mycorrhizal fungi in preserved or disturbed Araucaria angustifolia (Bert.) O. Ktze. ecosystems. Sci Agric 63:380–385. https://doi.org/10.1590/s0103-90162006000400009
Morte A, Diaz G, Rodriguez P, et al (2001) Growth and Water Relations in Mycorrhizal and Nonmycorrhizal Pinus halepensis Plants in Response to Drought. Biol Plant 44:263–267
Mugo EN (2015) Chuka Participatory Forest Management Plan
Mwitari PG, Ayeka PA, Ondicho J, et al (2013) Antimicrobial Activity and Probable Mechanisms of Action of Medicinal Plants of Kenya : Withania somnifera, Warbugia ugandensis, Prunus africana and Plectrunthus barbatus. PLoS One 8:4–12. https://doi.org/10.1371/journal.pone.0065619
Nanjundappa A, Bagyaraj DJ, Saxena AK, et al (2019) Interaction between arbuscular mycorrhizal fungi and Bacillus spp. In soil enhancing growth of crop plants. Fungal Biol Biotechnol 6:1–10. https://doi.org/10.1186/s40694-019-0086-5
Nkeng PF, Ingram V, Awono A (2010) Assessment methods of Prunus africana bark exploitation methods and sustainable exploitation in the South west, North-West and adamaoua regions of Cameroon
Odee DW, Indieka SA, Lesueur D (2002) Evaluation of inoculation procedures for Calliandra calothyrsus Meisn. grown in tree nurseries. Biol Fertil Soils 36:124–128. https://doi.org/10.1007/s00374-002-0519-8
Oksanen J, Blanchet FG, Friendly M, et al (2019) vegan: Community Ecology Package
Opik M, Vanatoa A, Vanatoa E, et al (2010) The online database Maarj AM reveals global and ecosystemic distribution patterns in arbuscular mycorrhizal fungi ( Glomeromycota ). New Phytologist 223–241. https://doi.org/doi: 10.1111/j.1469-8137.2010.03334.x
Otieno NE, Analo C (2012) Local indigenous knowledge about some medicinal plants in and around Kakamega forest in western Kenya [ version 2 ; referees : 2 approved ] Referee Status : F1000Res 1–40. https://doi.org/10.12688/f1000research.1-40.v1
Pellegrino E, Gamper HA, Ciccolini V, Ercoli L (2020) Forage Rotations Conserve Diversity of Arbuscular Mycorrhizal Fungi and Soil Fertility. Front Microbiol 10:1–17. https://doi.org/10.3389/fmicb.2019.02969
Pereira JM, Vasconcellos RLF, Pereira APA, et al (2020) Reforestation processes, seasonality and soil characteristics influence arbuscular mycorrhizal fungi dynamics in Araucaria angustifolia forest. For Ecol Manage 460:. https://doi.org/10.1016/j.foreco.2020.117899
Porter SS, Bantay R, Friel CA, et al (2019) Beneficial microbes ameliorate abiotic and biotic sources of stress on plants. Funct Ecol 1–12. https://doi.org/10.1111/1365-2435.13499
R Core Team (2020) R: A language and environment for statistical computing
Rillig MC, Mardatin NF, Leifheit EF, Antunes PM (2010) Mycelium of arbuscular mycorrhizal fungi increases soil water repellency and is sufficient to maintain water-stable soil aggregates. Soil Biol Biochem 42:1189–1191. https://doi.org/10.1016/j.soilbio.2010.03.027
Rodríguez-Echeverría S, Teixeira H, Correia M, et al (2017) Arbuscular mycorrhizal fungi communities from tropical Africa reveal strong ecological structure. New Phytologist 213:380–390. https://doi.org/10.1111/nph.14122
Schlaeppi K, Bender SF, Mascher F, et al (2016) High-resolution community profiling of arbuscular mycorrhizal fungi. New Phytologist 212:780–791
Seswa F, Manohar S, Kitur E (2018) Current Floristic Composition and Growth Forms of Equatorial Rainforest, Kakamega County Kenya. International Journal of Agriculture and Forestry 8:70–76. https://doi.org/10.5923/j.ijaf.20180802.04
Solaiman ZM, Anawar HM (2015) Rhizosphere Microbes Interactions in Medicinal Plants. In: Egamberdieva D, Shrivastava S, Varma A (eds) Soil Biology. Springer, New York
Spatafora JW, Chang Y, Benny GL, et al (2016) A phylum-level phylogenetic classification of zygomycete fungi based on genome-scale data. Mycologia 108:1028–1046. https://doi.org/10.3852/16-042
Stevens BM, Propster JR, Öpik M, et al (2020) Arbuscular mycorrhizal fungi in roots and soil respond differently to biotic and abiotic factors in the Serengeti. Mycorrhiza. https://doi.org/https://doi.org/10.1007/s00572-020-00931-5
Stürmer SL, Bever JD, Morton JB (2018) Biogeography of arbuscular mycorrhizal fungi (Glomeromycota): a phylogenetic perspective on species distribution patterns. Mycorrhiza 28:587–603. https://doi.org/10.1007/s00572-018-0864-6
Tchiechoua YH, Kinyua J, Ngumi VW, Odee DW (2020) Effect of Indigenous and Introduced Arbuscular Mycorrhizal Fungi on Growth and Phytochemical Content of Vegetatively Propagated Prunus africana (Hook. f.) Kalkman Provenances. Plants 9:37. https://doi.org/10.3390/plants9010037
Tegha KC, Yinda GS (2016) Soil organic carbon stocks in Mount Cameroon National Park under different land uses. Journal of Ecology and the Natural Environment 8:20–30. https://doi.org/10.5897/JENE2015.0553
Treseder KK, Allen EB, Egerton-Warburton LM, et al (2018) Arbuscular mycorrhizal fungi as mediators of ecosystem responses to nitrogen deposition: A trait-based predictive framework. Journal of Ecology 106:480–489. https://doi.org/10.1111/1365-2745.12919
Trevizan Chiomento JL, Stürmer SL, Carrenho R, et al (2019) Composition of arbuscular mycorrhizal fungi communities signals generalist species in soils cultivated with strawberry. Sci Hortic 253:286–294. https://doi.org/10.1016/j.scienta.2019.04.029
Vieira LC, da Silva DKA, Escobar IEC, et al (2020) Changes in an arbuscular mycorrhizal fungi community along an environmental gradient. Plants 9:1–16. https://doi.org/10.3390/plants9010052
Vinceti B, Loo J, Gaisberger H, et al (2013) Conservation Priorities for Prunus africana Defined with the Aid of Spatial Analysis of Genetic Data and Climatic Variables. PLoS One 8:. https://doi.org/10.1371/journal.pone.0059987
Wetzel K, Silva G, Matczinski U, et al (2014) Superior differentiation of arbuscular mycorrhizal fungal communities from till and no-till plots by morphological spore identification when compared to T-RFLP. Soil Biol Biochem 72:88–96. https://doi.org/10.1016/j.soilbio.2014.01.033
White F (1978) The Afromontane Region. 463–513. https://doi.org/10.1007/978-94-009-9951-0_11
Wubet T, Weiß M, Kottke I, et al (2004) Molecular diversity of arbuscular mycorrhizal fungi in Prunus africana, an endangered medicinal tree species in dry Afromontane forests of Ethiopia. New Phytologist 161:517–528. https://doi.org/10.1046/j.1469-8137.2003.00924.x
Xu T, Veresoglou SD, Chen Y, et al (2016) Plant community, geographic distance and abiotic factors play different roles in predicting AMF biogeography at the regional scale in northern China. Environ Microbiol Rep 8:1048–1057. https://doi.org/10.1111/1758-2229.12485
Zhao H, Li X, Zhang Z, et al (2017) Species diversity and drivers of AMF communities in a semi_arid mountain in China. PeerJ 5:18. https://doi.org/10.7717/peerj.4155

Additionalfile1.Readsabundancepersample.xlsx
Additional file 1. Reads abundance per sample.
Additionalfile2.UniqueandsharedAMFtaxa.xlsx
Additional file 2. Unique and shared top representative AMF taxa in the rhizosphere soil of Prunus africana.
Additionalfile3.Environmentalcharacteristics.xlsx
Additional file 3. Environmental characteristics of sampling sites.

Download PDF

Journal Publication

published 25 May, 2023

Read the published version in Annals of Microbiology →

Editorial decision: Revise before peer review
19 Dec, 2022
First submitted to journal
13 Dec, 2022

You are reading this latest preprint version

Illumina MiSeq sequencing reveals high arbuscular mycorrhizal fungi diversity in the rhizosphere soil of Prunus africana trees in fragmented Afromontane forests

Status:

Journal Publication

Version 1

Abstract

Figures

Background

Results

Discussion

Conclusion

Methods

Soil sample collection

Soil chemical analyses

Soil DNA extraction

Library preparation and Illumina MiSeq sequencing

Bioinformatics and statistical analyses

Abbreviations

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 1