Research on entomopathogenic nematodes (EPN) in Egypt started in the 1970s, and focused heavily on imported, non-indigenous species (Abd-Elgawad, 2017). Surveys to isolate and identify indigenous EPNs began two decades later (Shamseldean and Abd-Elgawad, 1994). Inconsistent efficacy by expensive EPN products hinders their use by the Egyptian farmers, suggesting a need for further exploration to identify species which are adapted to North African conditions and best suited to infect local insect pests (Campbell and Gaugler, 1993; Koppenhöfer et al., 1998; Simões and Rosa, 1996). To this end, a comprehensive survey that employed soil baiting with sentinel insects to recover EPN from 1,000 samples from the Nile Delta and Mediterranean Sea coast, Nile valley, Upper Egypt, and Sinai Peninsula revealed just three species,
Entomopathogenic nematodes and their symbiotic bacterial species previously detected in Egypt.
Nematode species/genus | Authority | References |
---|---|---|
|
Poinar, 1976 | Shamseldean and Abd-Elgawad, 1994; Salama and Abd-Elgawad, 2001; Abd-Elbary et al., 2012 |
|
Travassos, 1927 | |
|
Poinar, 1976 | Abd-Elgawad and Nguyen, 2007 |
|
Abd-Elgawad and Ameen, 2005 | Abd-Elgawad and Ameen, 2005 |
|
Poinar, Karunakar & David, 1992 | Abu-Shady et al., 2011; Abd-Elbary et al., 2012; Shehata et al., 2019 |
|
Shamseldean, Abou El-Sooud, Abd-Elgawad & Saleh, 1996 | Shamseldean et al., 1996 |
|
Phan Subbotin, Nguyen & Moens, 2003 | Abd El-Rahman, 2006 |
|
(Steiner, 1929) Wouts, Mracek, Gerdin and Bedding, 1982 | Abd-Elbary et al., 2012; Abd-Elgawad et al., 2013 |
|
Elawad, Ahmad and Reid, 1997 | Abu-Shady et al., 2011; Abd-Elbary et al., 2012 |
|
(Weiser, 1955) Wouts, Mracek, Gerdin and Bedding, 1982 | Abu-Shady et al., 2011; Abd-Elbary et al., 2012 |
|
Mamiya, 1988 | Shamseldean and Atwa, 2004 |
|
(Artyukhovsky, 1967) Wouts, Mracek, Gerdin and Bedding, 1982 | Abu-Shady et al., 2011; Abd-Elbary et al., 2012 |
Soil baiting can fail to detect EPN for any number of reasons including incompatible host status of the sentinel (Nguyen and Smart, 1991), competition between EPN and other organisms (Duncan et al., 2007; Wu et al., 2018), and phased infectivity exhibited by many EPN populations (Baiocchi et al., 2017; Shields, 2015). Direct observation through microscopy is more likely than baiting to detect EPN but is time consuming. Both methods require considerable expertise to identify species and suffer from a lack of definitive morphological features. By contrast, quantitative PCR is both sensitive and accurate and is used increasingly to detect and identify EPN (Campos-Herrera et al., 2012). The primary limitation of qPCR is that it detects only those species matching the primer/probes that are used. Thus, for surveys, metagenomic methods provide the most reliable tool, regardless even of whether a species is represented in databases such as Genbank (Dritsoulas et al., 2020).
Citriculture has an increasing socio-economic importance in Egypt, but is subjected to considerable yield loss caused by insect pests such as such as the Mediterranean fruit fly
Soil and root samples were collected from El-Beheira and Al-Qalyubia governorates in Egypt during 2018 and 2019 season. The GPS coordinates of six orchards sampled in El-Beheira were: 30°36‘49.8“N, 30°32‘21.3“E (four samples); 30°38‘14.7“N, 30°33‘47.1“E (eight samples); 30°38‘07.5“N, 30°33‘43.7“E (six samples); 30°39‘25.2“N, 30°35‘06.6“E (four samples); 30°38‘06.5“N, 30°37‘20.6“E (four samples), and 30°38‘06.4“N 30°37‘19.2“E (four samples). The coordinates of seven orchards sampled in Al-Qalyubia were: 30°25‘18.2“N, 31°12‘43.5“E (six samples), with four samples each from orchards at 30°26‘01.8“N, 31°14‘34.9“E; 30°24‘19.6“N, 31°13‘18.5“E; 30°24‘12.2“N, 31°13‘19.3“E; 30°23‘25.5“N, 31°13‘59.1“E; 30°23‘12.6“N; 31°14‘09.1“E, and 30°22‘55.2“N, 31°14‘34.3“E. Ten subsamples from 10 adjacent trees were randomly collected by a shovel (ca. 30-cm diam. to a depth of 25 cm) and mixed to form a composite sample of approx. 1,500 cm3 (Abd-Elgawad et al., 2016). A total of 60 composite samples were collected for nematode analysis. All samples were kept in polyethylene bags, labeled, and transferred to the laboratory for nematodes extraction.
Samples were gently sieved through a 4 mm aperture screen to remove gravel and to separate roots from soil. For each sample, 300 ml of the sieved soil were put in a stainless steel bowl, covered with tap water, and agitated before pouring the soil suspension through a 20-mesh (850 µm aperture) sieve held over a second bowl. Nematodes were extracted from each soil sample by sucrose (545 g sugar L−1) centrifugation after processing through 325- and then 500-mesh sieves (Jenkins, 1964). Nematode suspensions were concentrated and 100% alcohol was added to each sample. The nematodes could settle in test tubes overnight at 4°C. Thereafter, most of the water with alcohol was evaporated and samples were transferred to 1.5 mL Eppendorf tubes and stored at −20°C until sent to the laboratory in Florida for DNA extraction (Campos-Herrera et al., 2011).
Based on our experience that samples in ethanol yield low DNA, following centrifugation and aspiration of excess ethanol, the tubes were refilled with 1xPBS (phosphate buffer saline) and incubated overnight at 4°C. After a second centrifugation and aspiration of excess PBS, DNA was extracted with the DNeasy® PowerSoil Kit (Qiagen).
Prior to library preparation process, DNA concentrations from each sample were measured using the Qubit® dsDNA High Sensitivity Assay Kit (ThermoFisher Scientific, USA). Libraries were constructed for two groups, (i) 58 libraries targeting nematodes and (ii) 16 libraries targeting soil microarthropods. Microarthropod libraries were from eight randomly selected samples from each governorate.
For nematodes, the primers targeted 5.8 S rDNA amplifying the ITS 2 region from bulk DNA using a
According to Illumina protocols, library preparation comprises four parts: (i) amplicon PCR, (ii) amplicon PCR cleanup, (iii) index PCR, and (iv) index PCR cleanup. Samples were standardized at 5 ng/ml DNA concentration. For the EPN, samples were amplified with the following conditions: initial denaturation 95°C for 3 min, 25 cycles of denaturation at 98°C for 30 s, annealing at 56°C for 30 s, elongation at 72°C for 60 s, and terminal elongation at 72°C for 10 min. For microarthropods the conditions were initial denaturation 95°C for 3 min, 25 cycles of denaturation at 98°C for 30 s, annealing at 55°C for 30 s, elongation at 72°C for 60 s, and terminal elongation at 72°C for 10 min. For all libraries a single 25 μL PCR reaction containing 2.5 μL of template of 5 ng/μL (12.5 ng total), 12.5 μL of 2x KAPA HiFi HotStart ReadyMix (KAPA biosystems), 1 μL of each 10 μM overhang primer, 8 μL of 10 mM Tris pH 8.5. Validity and reliability of PCR reactions was tested with positive controls using DNA extracted from laboratory culture of the nematodes
Index PCR products purified with 1.1× magnetic beads, eluted in 25 μL, and quantified using a fluorometric quantification method that uses dsDNA binding dyes. Concentrated final libraries diluted using 10 mM Tris pH 8.5 to 4 nM. All the 5 μL aliquots of diluted DNA from each library was mixed in a single pooling library. The pooling library was sequenced using MiSeq platform 2 × 300 bp paired-end Illumina at the Interdisciplinary Center for Biotechnology Research (ICBR) of University of Florida.
ICBR delivered raw data in fastq format which were demultiplexed and separated into respective sample identification codes. FASTQC v0.11 (Andrews et al., 2015) was used for quality assessment of each read, and then all the quality information was combined into a single document using MULTIQC (Ewels et al., 2016). ITS 2 and LSU D3-D5 amplicons of ribosomal DNA was used for the nematode and microarthropods identification respectively. The R1 and R2 reads combined and de-replicated with the ASV-based approach, using DADA2 algorithms, through QIIME2 v2019.4 (Callahan et al., 2016). ended up to a length of 350-430 bp for nematodes and 500 bp for microarthropods. Count tables were generated by mapping ASVs and assigning taxonomy. All the non-redundant nucleotide sequences from NCBI GenBank were combined to generate a standalone database for taxonomy assignment (
Phylogenetic analysis was carried out in MEGA 10.0.5 software. Each of the identified EPN species was evaluated using a unique tree derived from the metabarcoding process. Prior to constructing trees, sequences were aligned using ClustalW alignment method on default settings. The evolutionary history was inferred by using the Maximum Likelihood method and Tamura-Nei model while the robustness of clades of the trees was assessed using 1000 bootstrap replications.
Regional differences in soil properties and differences in sites with or without EPN were evaluated by
The high-throughput sequencing produced two datasets, one based on ITS2 targeting nematodes and the other on the D3-D5 region of 28 S rDNA targeting microarthropods. The ITS2 revealed 8,208,384 reads of which 43% (3,522,968) passed the quality filters and were denoised, merged and characterized as non-chimeric. 44,483 unique amplicon sequence variants (ASVs) were recovered from forty-nine phyla, with 2.1% (946 ASVs) assigned to phylum Nematoda. By setting a threshold of 80% coverage, sixty seven percent (639) of the unique ASVs belong to 19 nematode families. Finally, 22 ASVs were identified as entomopathogenic nematode. The D3-D5 dataset yielded 9,637,729 reads that reduced to 3,627,990 (37%) after filtering, denoising, merging and chimera removal. The total number of unique ASVs was 2324 from 27 phyla, of which 483 belong to arthropods. Setting a threshold of 70% coverage, revealed 221 ASVs from 28 families in the class Arachnida.
Phylogenetic analysis characterized 22 ASVs derived from ITS2 sequences as
Entomopathogenic nematode isolates of
The soils in El-Beheira governorates were consistently coarser textured with less organic matter than those in Al-Qalyubia (Table 2). Soil properties did not differ significantly in sites that were either positive or negative for EPN. The abundance of
Soil characteristics in the two regions of the citrus orchards in Egypt.
Variable | Governorate | Mean ± SE | Min–Max | Regional differences |
|
||
---|---|---|---|---|---|---|---|
|
El Beheira | 63.28 ± 5.21 | 20.8–88.8 | < 0.0001*** | 0.0046** | ||
Al Qalyubia | 23.39 ± 0.92 | 12.8–36.8 | |||||
|
El Beheira | 16.67 ± 2.7 | 2–44 | 0.0001*** | 0.0028** | ||
Al Qalyubia | 35.07 ± 0.44 | 28–38 | |||||
|
El Beheira | 20.09 ± 2.58 | 9–45.2 | < 0.0001*** | 0.0044** | ||
Al Qalyubia | 41.61 ± 0.63 | 35.2–53.2 | |||||
|
El Beheira | 1.81 ± 0.23 | 0.11–3.94 | 0.0038** | n.s. | ||
Al Qalyubia | 2.904 ± 0.12 | 1.93–4.75 | |||||
|
El Beheira | 0.307 ± 0.04 | 0.12–1.3 | 0.0013** | 0.0326* | ||
Al Qalyubia | 0.3518 ± 0.02 | 0.2–0.6 | |||||
|
El Beheira | 7.44 ± 0.07 | 6.6–8 | 0.0068** | 0.0013** | ||
Al Qalyubia | 7.04 ± 0.23 | 1–7.6 |
Microarthropods comprising 28 families were identified from the eight sites in each governorate with 13 detected in Al-Qualubiya and 23 in El-Beheira. Family richness in Beheira (9.75) was more than twice (
Microarthropod families whose occurrence differ significantly in two regions ecoregions evaluated by non-parametric test Kruskal-Wallis.
Taxa | Kruskal–Wallis test |
---|---|
Ascidae | 0.0008*** |
Tydeidae | 0.0031** |
Rhodacaridae | 0.0031** |
Ologamasidae | 0.0082** |
Oehserchestidae | 0.0107* |
Ereynetidae | 0.0273* |
Eupodidae | 0.0273* |
Damaeidae | 0.0645. |
Oppiidae | 0.0645. |
Terpnacaridae | 0.0645. |
Laelapidae | 0.0738. |
The factors regulating EPN species occurrence and abundance remain poorly understood despite an ever-expanding catalogue of EPN biogeography (Campos-Herrera et al., 2013, 2019a; Garcia Del Pino and Palomo, 1996; Mráček et al., 1999; Tarasco et al., 2015; Valadas et al., 2014). While habitat biological and abiotic complexity obscures key processes affecting EPN, enhanced accessibility of metagenomic tools has vastly increased the resolution of soil food web characterization. The inventory created here of EPNs in the citrus orchards of two Egyptian ecoregions, demonstrates the enhanced capacity of metagenomic tools to detect, identify and, to some extent, quantify EPN across habits (Dritsoulas et al., 2020). The detection frequency in these samples (41%) far exceeds those of previous Egyptian surveys where EPNs were recovered from 9.5% of 661 soil samples (Shamseldean and Abd-Elgawad, 1994) and from 16% of 1,120 soil samples (Abd-Elbary et al., 2012). Critically, metabarcoding detected known and undescribed species whose relevant sequences are not registered in the GenBank databases. When blasting the sequencing output, each ASV is identified as an organism regardless of the proximity of the query to the reference sequence. The query sequences are not always identical to the reference sequences, but may differ by a few nucleotides, a phenomenon described by Porazinska et al. (2010) as generally conforming to a head (many identical) tail (few variants) pattern. While most sequences detected in our samples followed this pattern, we also detected ASVs identified with low affinity (< 79.5%) as
The constructed phylogenetic topology was critical also because it showed that multiple ASV characterized as EPN in Genbank databases actually belong to distant, unrelated nematode families (data not shown). Moreover, four ASVs of the sequencing output were identified as
Among the EPN detected here,
The limited occurrence and low abundance of EPN in this survey precluded detecting relationships between most EPN and the different habitat/foodweb properties of the ancient agricultural fields of the Nile Delta compared to those in land reclaimed from desert just since the early 1950s, some in this survey as recently as 30 years ago. Only
The occurrence of soil microarthropods also differed between the two ecoregions, with El-Beheira richer in microarthropods than Al-Qualubiya. Clay and elevation had the strongest relationship to microarthropod communities here and in some previous reports (Benckiser, 1997; Maraun et al., 2013; Marian et al., 2018). Although the relatively small changes in altitude in this survey suggest a relationship with a hidden variable such as water table depth (Campos-Herrera et al., 2013), soil microarthropods depend strongly on soil texture as they need pore space for all of their activities. Among the seven families found to be significantly more abundant in Beheira (Ascidae, Tydeidae, Rhodacaridae, Ologamasidae, Oehserchestidae, Ereynetidae, Eupodidae), most are nematophagous (Epsky et al., 1988; Karagoz et al., 2007; Santos and Whitford, 1981) including species of Rhodacaridae shown to be strongly inversely related to
This project has detected for the first time evidence of two new EPN species in Egypt, one described and represented in Genbank, the other not in Genbank and potentially undescribed. It more fully characterized the distribution and abundance of EPN in the citrus orchards of the Nile Delta and the reclaimed desert regions using the most sensitive methods currently available. As such the data are more comparable to those in other recent surveys employing molecular methods, rather than sentinel baiting, to survey EPN in citrus orchards in different parts of the world (Campos-Herrera et al., 2013, 2019a, b; Dritsoulas, 2020; Dritsoulas et al., 2020). Only by standardizing methodology will EPN biogeography and the mechanisms regulating occurrence and abundance be accurately revealed. Recent work has indicated that sucrose centrifugation combined with molecular identification and quantitation is highly efficient for characterizing food web components such as nematophagous fungi, parasitic bacteria, and microarthropod predators capable of modulating EPN populations (Dritsoulas and Duncan, 2020; Dritsoulas et al., 2020; Pathak et al., 2017). Improved understanding of how food webs function in different habitats is necessary to discover cultural practices that can enhance biological control by introduced or naturally occurring EPN.