High level of genetic diversity among Steinernema monticolum in Korea revealed by single-enzyme amplified fragment length polymorphism

Journal of Invertebrate Pathology 113 (2013) 146–151

Contents lists available at SciVerse ScienceDirect

Journal of Invertebrate Pathology journal homepage: www.elsevier.com/locate/jip

High level of genetic diversity among Steinernema monticolum in Korea revealed by single-enzyme amplified fragment length polymorphism Huan Wang a,b,1, Young Hak Jung b,1, Daeyoung Son b, Ho Yul Choo b,⇑ a

College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang 110866, China Division of Applied Life Science (BK 21 Program), Department of Applied Biology, College and Institute of Agriculture and Life Sciences, Gyeongsang National University, Jinju 660-701, Gyeongnam, Republic of Korea

b

a r t i c l e

i n f o

Article history: Received 12 October 2012 Accepted 11 March 2013 Available online 22 March 2013 Keywords: Steinernema monticolum SE-AFLP Population Genetic diversity

a b s t r a c t Steinernema monticolum was first described from a mountainous forest at sites of Sancheong, Gyeongnam province in Korea. Since S. monticolum is one of the most commonly isolated entomopathogenic nematodes from Korea, it is desirable to investigate the diversity of this species. Single-enzyme amplified fragment length polymorphism (SE-AFLP) analyses were used to differentiate 32 S. monticolum populations. Our results revealed a high level of genetic diversity within S. monticolum at the population level. On the geographic scale, SE-AFLP analysis revealed that there was no correlation between the genetic similarity of populations of this species and their geographical proximity. Ó 2013 Elsevier Inc. All rights reserved.

1. Introduction Entomopathogenic nematodes (EPNs) are considered one of the most potent non-chemical alternatives to insect pest control due to their ability to active location for insect hosts as well as their high reproductive potential, capacity for mass production and safety to vertebrates and plants (Kaya and Gaugler, 1993; Burnell and Stock, 2000). Steinernema monticolum is one of the EPN species isolated from Korea (Stock et al., 1997). This species is an effective biological control agent because of its high virulence against some insect pests such as, Spodoptera depravata (Butler) (Kang et al., 2004), Pryeria sinica Moore (Lee, 2006), Arge captiva (Smith), Arge pagana pagana (Panzer), and Arge similis (Vollenhoven) (Yang et al., 2007). Since environmental conditions influence survival, virulence and reproductive potential of EPN strains, EPNs exhibit considerable variation by means of genetic and biological populations (Gaugler et al., 1989). Understanding the genetic diversity and evolutionary relationships between different EPN populations will increase the success of their use in biological control programs. Even though they seem to have uniform body plans, EPNs are more diverse at the molecular level than was previously recognized (Bird et al., 2005; Adams et al., 2006). Numerous molecular approaches have been applied to the evolutionary relationships of EPNs. Initial efforts including numerous techniques such as ⇑ Corresponding author. Address: Department of Applied Biology, Gyeongsang National University, Jinju 660-701, Gyeongnam, Republic of Korea. E-mail address: [email protected] (H.Y. Choo). 1 These authors contributed equally to this work. 0022-2011/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jip.2013.03.005

PCR-RFLP, ribosomal small subunit (SSU, or 18S gene), ribosomal large subunit (LSU), internal transcribed spacer (ITS) and mitochondrial NADH dehydrogenase subunit 4 (ND4), cytochrome oxidase gene (COI), and small mitochondrial ribosomal RNA gene (16S) have been developed to reconstruct the phylogenetic relationships among EPNs (Liu et al., 1997; Reid et al., 1997; Adams et al., 1998; Liu et al., 1999; Szalanski et al., 2000; Nguyen et al., 2001; Nguyen et al., 2004). Among the molecular tools that may be used, some effective approaches for EPN characterization include combinations of different methods (Jagdale et al., 2006). The amplified fragment length polymorphism (AFLP) is a reliable and powerful DNA fingerprint tool for genetic characterization analysis and exploring population structure in EPNs (Qin et al., 2000; Masumu et al., 2006). Single-enzyme amplified fragment length polymorphism (SE-AFLP) analysis is a PCR-based DNA fingerprinting method, which was derived from the AFLP technique by use of one instead of two adapters (Bootsma et al., 2000). This molecular approach has already been applied to analyze the genetic diversity of different isolates of the same bacterial species (Giammanco et al., 2007) and the genetic relationships of Mermithidae (Jiang et al., 2008). Compared with other molecular approaches, in terms of availability and cost of equipment, complexity of data, subsequent ease of analysis and highly reproducible, SE-AFLP is likely to prove more widely applicable (Hudson et al., 2001; Champion et al., 2002; Miraglia et al., 2012). In this study, we tested the SE-AFLP method to analyze the genetic diversity of different S. monticolum populations from Korea. The result will contribute to the body of knowledge about the characterization of S. monticolum populations in Korea and intraspecific diversity of EPNs for biological control programs.

147

H. Wang et al. / Journal of Invertebrate Pathology 113 (2013) 146–151

2. Materials and methods 2.1. Nematode populations A total of 1026 soil samples were collected in spring (from March 1990 to May 1991, from March 2002 to May 2004 and from March 2010 to May 2011) and in autumn (from September 1990 to November 1991, from September 2002 to November 2004 and from September 2011 to November 2012) from 84 locations in Korea. A total of 32 S. monticolum populations were isolated from 17 locations (Table 1). The soil texture of these 17 locations was sandy clay. All populations of S. monticolum were identified to species level using morphological and molecular methods (data not shown). All the populations isolated were identified and stored in the Nematode Laboratory of Gyeongsang National University. EPNs were recovered from the soil samples using the insect-baiting method of Bedding and Akhurst (1975). The morphological identification was performed as described by according to Poinar (1990), Kaya and Stock (1997), Stock et al. (1997), and Nguyen and Hunt (2007) and the molecular identification used sequences of ITS (Spiridonov et al., 2004). The names of the 32 S. monticolum populations isolated were abbreviated as Sm, from Sm1 to Sm32. EPNs were propagated in the last instar of Galleria mellonella and harvested using White traps (Chung et al., 2010; Kaya and Stock, 1997). They were stored in the sterilized distilled water at 10 °C for 5 – 21 days until use at the Nematode Laboratory, Gyeongsang National University.

2.2. SE-AFLP Genomic DNA (gDNA) was extracted as described by Yilmaz et al. (2009) and measured using a Biophotometer (GeneQuant Pro, Amersham Biosciences, Buckinghamshire, United Kingdom).

The SE-AFLP method was carried out as described by Jiang et al. (2008) and Srinivasan et al. (2001). We examined a number of enzyme combinations (such as HindIII, EcoRI, MseI, NsiI and RsaI) and found that EcoRI was the most reproducible and discriminatory for analysis of S. monticolum populations. 10 ll of gDNA was digested overnight at 37 °C with 10 U of EcoRI (Fermentas, Canada) in 2 ll 10  enzyme buffer and water in a volume of 20 ll. The adapter oligonucleotides used were complementary sequences to EcoRI fragments that were ligated to each end of the restriction fragment and were tagged to PCR amplification. Subsets of the ligated fragments were selectively amplified, since the primers used had one additional nucleotide as the final 30 base, which extended into the restriction fragment. Ligation was carried out at 16 °C overnight in a total reaction volume of 20 ll containing 2 ll of digested DNA, distilled water, 2 ll of 10  ligase buffer, 107 ng of adapters (H1, 50 -CTCGTAGACTGCGTACC- 30 and H2, 50 -AATTGGTAGGCAGTCTA C- 30 ) (Jiang et al., 2008) and 2 U of T4 DNA ligase (Promega, USA). Digested-ligated DNA was heated to 65 °C for 20 min to inactivate the ligase. PCR reaction consisted of 5 ll of digested-ligated DNA, 10 mM each deoxynucleoside triphosphate (dNTP), 150 ng of each primer and 1U Taq polymerase in 10  PCR buffer and water in a volume of 50 ll. The primers had the sequence 50 -GACTGCGTACCA ATTCXXX-, XXX was either ATG, ACA or AAC, respectively (Madani et al., 2007; Jiang et al., 2008). These primers were called EP-ATG, EP-ACA and EP-AAC. The suitable primer was selected according to the quality of amplified fragments. PCR amplification was performed in a DNA Engine PTC-1148 (Bio-RAD, USA) and consisted of 1 cycle at 94 °C for 2 min, followed by 35 cycles of 94 °C for 20 s, 46 °C for 40 s, and 72 °C for 2 min, and one final step of 10 min at 72 °C. PCR products were loaded onto a 1.0% agarose gel and electrophoresed for 2 h at 100 V. After electrophoresis, the gel was treated with ethidium bromide for 20 min and DNA fragments were visu-

Table 1 S. monticolum populations collected from Korea and habitat characteristics. Population S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S. S.

monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum monticolum

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Population abbreviation

Location

Habitat

Dominant vegetation

Sm1 Sm2 Sm3 Sm4 Sm5 Sm6 Sm7 Sm8 Sm9 Sm10 Sm11 Sm12 Sm13 Sm14 Sm15 Sm16 Sm17 Sm18 Sm19 Sm20 Sm21 Sm22 Sm23 Sm24 Sm25 Sm26 Sm27 Sm28 Sm29 Sm30 Sm31 Sm32

Bonghwa Bonghwa Bonghwa Bonghwa Bonghwa Gumi Hapcheon Hapcheon Hapcheon Inje Jangsu Jecheon Jeongseon Jeju Jeju Jeju Jeju Jeju Jeju Jeju Jeju Muju Mungyeong Mungyeong Pocheon Sanchung Sanchung Taebaec Ulleung Wonju Yeonhyang Yeongcheon

Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest Forest National arboretum Forest Forest Forest Forest Forest Riparian Forest

Larch Larch Larch Larch Larch Acorn Larch + red pine Larch Chestnut Larch Chestnut Acorn + red pine Larch Scrub Broad-leaved tree Scrub Scrub Scrub Scrub Scrub Scrub Larch + Sasa borealis (Hack.) Makino Larch Larch Red oak Larch Larch Larch Scrub Chestnut Weeds Scrub

148

H. Wang et al. / Journal of Invertebrate Pathology 113 (2013) 146–151

alized by UV illumination. The sizes of digested products were estimated by comparison with 1000 bp DNA ladder. 2.3. Computer analysis of SE-AFLP patterns The amplicons were analyzed and registered by an image capturing system Quantity One software (Bio-Rad, Richmond, CA). SE-RFLP banding patters were assessed visually and by NTSYS-pc 2.1 software (Mickett et al., 2003). Fragments were transferred from SE-AFLP-QuantarPro to a binary (1/0) data matrix. Pairwise genetic distance matrices were generated using Nei’s coefficient of similarity (Nei and Li, 1979). A dendrogram was generated from the above matrix using unweighted pair group method with arithmetical averages (UPGMAs) (Sokal and Michener, 1958). 3. Results A total of 32 S. monticolum populations were isolated from 17 locations in Korea (Table 1). Both molecular and morphologic/morphometric examinations were used for species identification. SEAFLP analysis evaluated DNA segments which were obtained from EcoRI digestion and distributed all over the EPN genome. In an initial screening, randomly selected S. monticolum cultures were used to assess the suitability of the three selective primers according to quality of amplified fragments. All the populations were analyzed using one single primer PCR-reaction and each primer tested produced reasonably well-defined banding patterns. SE-AFLP produced 4 – 10 distinct fragments ranging between approximately 400 and 3500 bp using primer EP-ACA. However, primer EP-ATG and EP-AAC produced few bands, making comparative analysis difficult. Thus, the primer EP-ACA was selected for further evaluations. Our study revealed a high level of genetic diversity of S. monticolum at the population level (Fig. 1). In the dendrogram generated by UPGMA based on the Nei’s genetic distance matrices for all 32

populations, three clusters were clearly formed separating the S. monticolum isolates from each other (Fig. 1). Cluster analysis of these SE-AFLP patterns indicated that four pairs of populations (Sm7 and Sm26, Sm9 and Sm24, Sm13 and Sm14, Sm18 and Sm32) were 100% homologous. Sm25 had a unique profile and Sm22 had a profile distinct from other populations. No correlation between location of EPNs and SE-AFLP data was detected, because S. monticolum populations in the same location were found in different branches of the dendrogram, as we observed elsewhere. The mean genetic distance among different S. monticolum populations was 0.316 (0 – 0.692) (Table 2). The genetic distance of some populations (Sm4 and Sm16, Sm4 and Sm20, Sm4 and Sm25, Sm11 and Sm25) was 0.692, while some populations (Sm7 and Sm26, Sm9 and Sm24, Sm13 and Sm14, Sm18 and Sm32) from apparently sporadic cases clustered with 100% homology.

4. Discussion The present study describes the application of SE-AFLP for genotyping S. monticolum populations isolated from different locations in Korea. A total of 1026 soil samples were collected from 84 locations in Korea for 7 years. The survey yielded 6 different EPN populations (including S. monticolum, S. carpocapsae, S. glaseri, S. longicaudum, Heterorhabditis megidis and Heterorhabditis bacteriophora); 75 – 80% EPNs belonged to S. monticolum (unpublished data). S. monticolum was first found and described in Korea (Stock et al., 1997). S. monticolum adapted to cool temperatures and can infect a wide range of insect species, but appears to be best adapted to lepidopteran larvae as hosts (Koppenhöfer et al., 2000). As S. monticolum is the most frequently isolated EPN from Korea and has potential to provide natural control of pests, it is essential to investigate the diversity of this species within the country. In the future, we will analyze more nematode samples

Fig. 1. Dendrogram showing the genetic distance S. monticolum populations on the basis of SE-AFLP patterns. The dendrogram was constructed by use of UPGMA (unweighted pair group method using arithmetic average) method.

Table 2 Genetic distance matrix among 32 populations of S. monticolum. 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

Sm1 Sm2 Sm3 Sm4 Sm5 Sm6 Sm7 Sm8 Sm9 Sm10 Sm11 Sm12 Sm13 Sm14 Sm15 Sm16 Sm17 Sm18 Sm19 Sm20 Sm21 Sm22 Sm23 Sm24 Sm25 Sm26 Sm27 Sm28 Sm29 Sm30 Sm31 Sm32

0.00 0.158 0.333 0.571 0.059 0.333 0.286 0.200 0.333 0.286 0.429 0.250 0.385 0.385 0.467 0.294 0.177 0.333 0.250 0.294 0.125 0.333 0.294 0.333 0.529 0.286 0.467 0.177 0.429 0.429 0.375 0.333

0.00 0.375 0.333 0.222 0.500 0.333 0.375 0.250 0.333 0.600 0.177 0.429 0.429 0.500 0.333 0.222 0.375 0.294 0.333 0.294 0.368 0.222 0.250 0.556 0.333 0.500 0.111 0.467 0.167 0.529 0.375

0.00 0.455 0.429 0.333 0.455 0.333 0.500 0.455 0.455 0.385 0.400 0.400 0.500 0.429 0.429 0.500 0.539 0.571 0.385 0.467 0.571 0.500 0.571 0.455 0.500 0.429 0.455 0.455 0.385 0.500

0.00 0.539 0.636 0.400 0.636 0.273 0.400 0.600 0.333 0.556 0.556 0.636 0.692 0.539 0.636 0.667 0.692 0.667 0.571 0.385 0.273 0.692 0.400 0.455 0.385 0.600 0.400 0.667 0.636

0.00 0.286 0.231 0.143 0.286 0.231 0.385 0.333 0.333 0.333 0.429 0.375 0.250 0.286 0.200 0.250 0.067 0.294 0.250 0.286 0.500 0.231 0.429 0.125 0.385 0.385 0.333 0.286

0.00 0.455 0.167 0.500 0.273 0.455 0.539 0.400 0.400 0.500 0.429 0.429 0.333 0.385 0.429 0.231 0.467 0.571 0.500 0.429 0.455 0.500 0.429 0.455 0.455 0.231 0.333

0.00 0.273 0.091 0.200 0.400 0.167 0.111 0.111 0.273 0.385 0.231 0.273 0.333 0.385 0.333 0.429 0.231 0.091 0.538 0.00 0.273 0.231 0.200 0.200 0.333 0.273

0.00 0.333 0.273 0.273 0.385 0.200 0.200 0.333 0.286 0.286 0.167 0.231 0.286 0.077 0.333 0.429 0.333 0.429 0.273 0.500 0.286 0.273 0.455 0.231 0.167

0.00 0.273 0.455 0.077 0.200 0.200 0.333 0.429 0.286 0.333 0.385 0.429 0.385 0.467 0.143 0.00 0.571 0.091 0.333 0.286 0.273 0.273 0.385 0.333

0.00 0.600 0.333 0.333 0.333 0.455 0.385 0.231 0.273 0.333 0.385 0.333 0.429 0.385 0.273 0.385 0.200 0.273 0.231 0.400 0.200 0.500 0.273

0.00 0.500 0.333 0.333 0.455 0.539 0.539 0.455 0.500 0.539 0.333 0.429 0.539 0.455 0.692 0.400 0.455 0.539 0.400 0.600 0.167 0.455

0.00 0.273 0.273 0.385 0.333 0.200 0.385 0.429 0.467 0.429 0.500 0.200 0.077 0.600 0.167 0.385 0.333 0.333 0.333 0.429 0.385

0.00 0.00 0.200 0.333 0.333 0.200 0.273 0.333 0.273 0.539 0.333 0.200 0.500 0.111 0.400 0.333 0.111 0.333 0.273 0.200

0.00 0.200 0.333 0.333 0.200 0.273 0.333 0.273 0.539 0.333 0.200 0.500 0.111 0.400 0.333 0.111 0.333 0.273 0.200

0.00 0.286 0.429 0.167 0.231 0.286 0.385 0.600 0.429 0.333 0.429 0.273 0.500 0.429 0.091 0.455 0.385 0.167

0.00 0.250 0.143 0.333 0.375 0.333 0.529 0.500 0.429 0.500 0.385 0.572 0.375 0.385 0.539 0.467 0.143

0.00 0.286 0.333 0.375 0.333 0.412 0.375 0.286 0.375 0.231 0.429 0.250 0.385 0.385 0.467 0.286

0.00 0.231 0.286 0.231 0.467 0.429 0.333 0.429 0.273 0.500 0.286 0.273 0.455 0.385 0.00

0.00 0.067 0.143 0.500 0.333 0.385 0.333 0.333 0.539 0.200 0.167 0.500 0.429 0.231

0.00 0.200 0.529 0.375 0.429 0.375 0.385 0.571 0.250 0.231 0.539 0.467 0.286

0.00 0.375 0.333 0.385 0.467 0.333 0.539 0.200 0.333 0.500 0.286 0.231

0.00 0.412 0.467 0.529 0.429 0.467 0.294 0.571 0.571 0.375 0.467

0.00 0.143 0.500 0.231 0.429 0.250 0.385 0.385 0.467 0.429

0.00 0.571 0.091 0.333 0.286 0.273 0.273 0.385 0.333

0.00 0.539 0.571 0.500 0.385 0.385 0.600 0.429

0.00 0.273 0.231 0.200 0.200 0.333 0.273

0.00 0.429 0.455 0.273 0.385 0.500

0.00 0.385 0.385 0.467 0.286

0.00 0.400 0.00 0.333 0.500 0.00 0.273 0.455 0.385 0.00

H. Wang et al. / Journal of Invertebrate Pathology 113 (2013) 146–151

Sm

149

150

H. Wang et al. / Journal of Invertebrate Pathology 113 (2013) 146–151

from different sources and test the population characterization of other species. The SE-AFLP technique was developed from AFLP. The AFLP technique relies on selective amplification of restriction fragments from a digest of gDNA (Vos et al., 1995). Two restriction enzymes are used to digest DNA, giving rise to fragments of a size suitable for resolution on polyacrylamide gels (Bootsma et al., 2000). Double-stranded adapters, specific for either restriction site, are ligated to the DNA fragments, which serve as target sites for primers used in PCR amplification. AFLP markers have been applied to nematodes and proved fruitful for investigating subspecific relationships and genetic variation among closely related species of Meloidogyne (Semblatt et al., 1998). Application of AFLP genotyping and fingerprinting to EPNs is an appropriate tool for exploring population structure (van der Voort et al., 2000). This technique has been applied to analyze the genetic diversity within Heterodera schachtii populations from Western Europe, Australia and Africa (Madani et al., 2007) and 11 populations in Ireland (Dillon et al., 2008). RAPD (randomly amplified polymorphic DNA), which is similar to the information content of AFLP, can also be a powerful molecular systematic tool and has been used to explore genetic diversity among species and strains of EPNs (Hashmi and Gaugler, 1998), determine phylogenetic relationships (Liu and Berry, 1996), and complement descriptions of new species (Stock et al., 1996). However, RAPD analysis has displayed non-reproducible patterns and inconsistent band intensity (Tavechio et al., 1996) and limited discriminatory power has also been reported in repetitive sequence polymerase chain reaction (Rep-PCR) analysis. For more detailed investigations, fluorescent AFLP (FAFLP) with two restriction enzymes and fluorescently labeled primers enables detection of many fragments that may be subsequently analyzed on automated DNA sequencers (Mortimer and Arnold, 2001). However, in terms of availability and cost of equipment, complexity of data and subsequent ease of analysis, SE-AFLP is likely to prove more widely applicable. Thus, we performed SE-AFLP to analyze the genetic diversity of S. monticolum populations in Korea. In SE-AFLP, a single adapter is used instead of two, which circularizes the DNA fragments because the adapter will ligate to the cohesive ends generated by both restriction enzymes (Bootsma et al., 2000). Compared with the original AFLP technique, SE-AFLP results in less variation in peak intensities and improved reproducibility. Furthermore, the SE-AFLP technique allows a greater choice of restriction enzymes, because enzymes generating blunt ends also can be used. However, prior to this study there has not been any report on diversity within the same EPN species using SE-AFLP method. In this study, EcoRI was found to be the most reproducible and discriminatory enzyme for analysis of S. monticolum populations. Subsequent amplification of the circularized restriction fragments was done with primers specific for the adapter and adjacent restriction site. To reduce the number of bands, selective nucleotides can be included at the 30 ends of the PCR primers, allowing amplification of more DNA fragments. After initial screening of several primer pairs with different selective nucleotides, we used a primer with ‘‘ACA’’ overhang on both primers. To determine the reproducibility of the SE-AFLP method, restriction digestion and subsequent PCR reactions were done in triplicate for 32 populations and separated on different gels. As expected, the SE-AFLP approach was able to distinguish each population analyzed. The application of large numbers of EPNs to control agricultural pests is likely to have an impact on the local EPN fauna, yet little is known about the intraspecific relationships among EPN populations (Rolston et al., 2009). Rolston et al. (2009) examined intraspecific phylogenies among 12 isolates of Steinernema feltiae (nine isolates from Bull Island, Dublin Bay, one isolate from County Carlow, Ireland, one isolate from County Kildare, and one commercial

isolate from the UK) using exon-primed, intron-crossing (EPIC) PCR and found that there was no correlation between geographical and genetic distances. However, Yoshida (2003) revealed different RFLP patterns between the Japanese isolates of S. feltiae and European isolates with DdeI and HinfI restriction digests. The Japanese isolate of Steinernema kraussei also showed RFLP variation from UK and Russian isolates. Phylogenetic analysis of isozyme patterns revealed that genetic divergence among populations of H. bacteriophora is relatively independent of geographic distance (Jagdale et al., 2006). All these data indicate that the relationship between genetic divergence among different EPN populations and the geographic distance is relatively independent regardless of the molecular approach used. Similarly, SE-AFLP analysis of S. monticolum populations revealed that within Korea, there was no correlation between the genetic similarity and geographical proximity. On the geographic scale, SE-AFLP data of S. monticolum populations from Korea revealed a high level of genetic diversity despite the lack of differentiation according to geographical origin. These observations are indicative of a high level of gene flow among S. monticolum populations in this region. The data of five populations from Bonghwa in Gyeongbug province and eight populations from Jeju in Jeju province revealed a very high level of genetic variability within populations. Some of S. monticolum populations were more closely related to populations from other locations than to populations collected from the same location. Population Sm2, Sm3 and Sm4 from the same location (Bonghwa) were more closely related to populations from other locations than to populations collected from the same location. However, populations Sm1 and Sm5 were also collected from Bonghwa and formed a distinctive cluster. Population Sm18 from Jeju showed 100% homology with Sm32 from Yeongcheon, and was not closely related to populations collected from the same location. Also, populations from the same location (Mungyeong, Gyeongbug province) did not form a distinctive cluster, but are intermingled with populations from Hapcheon in Gyeongnam province. S. monticolum populations isolated from the riparian and national arboretum had alternative SE-AFLP patterns, which were different from those found in forest populations. Among S. monticolum populations, Sm25 was the only population isolated from the soil of red oak at the national arboretum in Pocheon, Gyeonggi province. Additionally, Sm22 was the only population from the soil of forest in Muju in Jeonbug province. In conclusion, SE-AFLP analysis provided a simple approach for analyzing the genetic diversity of EPN. According to the SE-AFLP data, S. monticolum revealed a high level of genetic diversity at the population level. Based on the SE-AFLP analysis, there was no correlation between the genetic similarity of populations and their geographical proximity.

Acknowledgment This work was supported by grants from the Korea–China Young Scientist Exchange Program.

References Adams, B.J., Burnell, A.M., Powers, T.O., 1998. A phylogenetic analysis of Heterorhabditis (Nemata: Rhabditidae) based on internal transcribed spacer 1 DNA sequence data. J. Nematol. 30, 22–39. Adams, B.J., Fodor, A., Koppenhöfer, H.S., Stackebrandt, E., Stock, S.P., Klein, M.G., 2006. Biodiversity and systematics of nematode–bacterium entomopathogens. Biol. Control 37, 32–49. Bedding, R.A., Akhurst, R.J., 1975. A simple technique for the detection of insect parasitic rhabditid nematodes in soil. Nematologica 21, 109–110.

H. Wang et al. / Journal of Invertebrate Pathology 113 (2013) 146–151 Bird, D.M., Blaxter, M.L., McCarter, J.P., Mitreva, M., Sternberg, P.W., Thomas, W.K., 2005. A white paper on nematode comparative genomics. J. Nematol. 37, 408– 416. Bootsma, H.J., Van der Heide, H.G.J., Van de Pas, S., Schouls, L.M., Mooi, F.R., 2000. Analysis of Moraxella catarrhalis by DNA typing: evidence for a distinct subpopulation associated with virulence traits. J. Infect. Dis. 181, 1376–1387. Burnell, A.M., Stock, S.P., 2000. Heterorhabdits, Steinernema and their bacterial symbionts–lethal pathogens of insect. Nematology 2, 31–42. Champion, O.L., Best, E.L., Frost, J.A., 2002. Comparison of pulsed-field gel electrophoresis and amplified fragment length polymorphism techniques for investigating outbreaks of enteritis due to campylobacters. J. Clin. Microbiol. 40, 2263–2265. Chung, H.J., Lee, D.W., Yoon, H.S., Lee, S.M., Park, C.G., Choo, H.Y., 2010. Temperature and dose effects on the pathogenicity and reproduction of two Korean isolates of Heterorhabditis bacteriophora (Nematoda: Heterorhabditidae). J. Asia-Pacific Entomol. 13, 277–282. Dillon, A.B., Rolston, A.N., Meade, C.V., Downes, M.J., Griffin, C.T., 2008. Establishment, persistence, and introgression of entomopathogenic nematodes in a forest ecosystem. Ecol. Appl. 18, 735–747. Gaugler, R., Mcguire, T., Campbell, J., 1989. Genetic variability among strains of the entomopathogenic nematode Steinernema feltiae. J. Nematol. 21, 247–253. Giammanco, G.M., Mammina, C., Romani, C., Luzzi, I., Dionisi, A.M., Nastasi, A., 2007. Evaluation of a modified single-enzyme amplified fragment length polymorphism (SE-AFLP) technique for subtyping Salmonella enterica serotype Enteritidis. Res. Microbiol. 158, 10–17. Hashmi, G., Gaugler, R., 1998. Genetic diversity in insect-parasitic nematodes (Rhabditida: Heterorhabditidae). J. Invertebr. Pathol. 72, 185–189. Hudson, C.R., Garcia, M., Gast, R.K., Maurer, J.J., 2001. Determination of close genetic relatedness of the major Salmonella Enteritidis phage types by pulsed-field gel electrophoresis and DNA sequence analysis of several Salmonella virulence genes. Avian Dis. 45, 875–886. Jagdale, G.B., Saeb, A.T.M., Somasekhar, N., Grewal, P.S., 2006. Genetic variation and relationships between isolates and species of the entomopathogenic nematode genus Heterorhabditis deciphered through isozyme profiles. J. Parasitol. 92, 509– 516. Jiang, A.L., Rao, X.J., He, J.F., Wang, G.X., 2008. Phylogenetic relationships among common species of Mermithidae (Nematoda) in China based on SAFLP. Acta Entomol. Sinica 51 (9), 924–929. Kang, Y.J., Lee, D.W., Choo, H.Y., Lee, S.M., Kweon, T.W., Shin, H.K., 2004. Biological control of Spodoptera depravata (Butler) (Lepidoptera: Noctuidae) using entomopathogenic nematodes. Korean J. Appl. Entomol. 43, 61–70. Kaya, H., Gaugler, R., 1993. Entomopathogenic nematodes. Ann. Rev. Entomol. 38, 181–206. Kaya, H.K., Stock, S.P., 1997. Techniques in insect nematology. In: Lacey, L.A. (Ed.), Manual of Techniques in Insect Pathology. Academic Press, San Diego, pp. 281– 322. Koppenhöfer, A.M., Ganguly, S., Kaya, H.K., 2000. Ecological characterization of Steinernema monticolum, a cold-adapted entomopathogenic nematode from Korea. Nematology 2, 407–416. Lee, D.W., Yang, J.Y., Han, G.Y., Choo, H.Y., Lee, S.M., Kim, H.H., Park, C.G., Choo, Y.M., 2006. Entomopathogenic nematodes for biological control of Pryeria sinica Moore (Lepidoptera: Zygaenidae) and persistence on Euonymus japonica Thunberg foliage. J. Asia-Pacific Entomol. 9, 165–172. Liu, J., Berry, R.E., 1996. Heterorhabditis marelatus n. sp. (Rhabditida: Heterorhabditidae) from Oregon. J. Invertebr. Pathol. 67, 48–54. Liu, J., Berry, R.E., Moldenke, A.F., 1997. Phylogenic relationships of entomopathogenic nematodes (Heterorhabditidae and Steinernematidae) inferred from partial 18S rRNA gene sequences. J. Invertebr. Pathol. 69, 246– 252. Liu, J., Berry, R.E., Blouin, M.S., 1999. Molecular differentiation and phylogeny of entomopathogenic nematodes (Rhabditida: Heterorhabditidae) based on ND4 gene sequences of mitochondrial DNA. J. Parasitol. 85, 709–715. Madani, M., Kyndt, T., Colpaert, N., Subbotin, S.A., Gheysen, G., Moens, M., 2007. Polymorphism among sugar beet cyst nematode Heterodera schachtii populations as inferred from AFLP and ITS rDNA gene analyses. Russ. J. Nematol. 15, 117–128. Masumu, J., Geysen, D., Vansnick, E., Geerts, S., Van den Bossche, P., 2006. A modified AFLP for Trypanosoma congolense isolate characterization. J. Biotechnol. 125, 22–26. Mickett, K., Morton, C., Feng, J., Li, P., Simmons, M., Cao, D., Dunham, R.A., Liu, Z., 2003. Assessing genetic diversity of domestic populations of channel catfish (Ictalurus punctatus) in Alabama using AFLP markers. Aquaculture 228, 91– 105.

151

Miraglia, F., de Morais, Z.M., Dellagostin, O.A., Seixas, F.K., Freitas, J.C., Zacarias, F.G.S., Delbem, Á.C., Ferreira, T.S.P., Souza, G.O., Hartskeerl, R.A., Vasconcellos, S.A., Moreno, A.M., 2012. Molecular and serological characterization of Leptospira interrogans serovar Canicola isolated from dogs, swine, and bovine in Brazil. Trop. Anim. Health Prod. http://dx.doi.org/10.1007/s11250-012-01816. Mortimer, P., Arnold, C., 2001. FAFLP: last word in microbial genotyping. J. Med. Microbiol. 50, 393–395. Nei, M., Li, W.H., 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA 76, 5269–5273. Nguyen, K.B., Hunt, D.J., 2007. Entomopathogenic nematodes: systematics, phylogeny and bacterial symbionts. Brill Leiden, Boston. Nguyen, K.B., Maruniak, J., Adams, B.J., 2001. Diagnostic and phylogenetic utility of the rDNA internal transcribed spacer sequences of Steinernema. J. Nematol. 33, 73–82. Nguyen, K.B., Shapiro-Ilan, D.I., Stuart, R.J., McCoy, C.W., James, R.R., Adams, B.J., 2004. Heterorhabditis mexicana n. sp. (Rhabditida: Heterorhabditidae) from Tamaulipas, Mexico, and morphological studies of the bursa of Heterorhabditis spp. Nematology 6, 231–244. Poinar Jr., G.O., 1990. Taxonomy and biology of Steinernematidae and Heterorhabditidae. In: Gaugler, R., Kaya, H.K. (Eds.), Entomopathogenic Nematodes in Biological Control. CRC Press, Boca Raton, Fl, pp. 23–61. Qin, L., Overmars, B., Helder, J., Popeijus, H., van der Voort, J.R., Groenink, W., van Koert, P., Schots, A., Bakker, J., Smant, G., 2000. An efficient cDNA-AFLP-based strategy for the identification of putative pathogenicity factors from the potato cyst nematode Globodera rostochiensis. Mol. Plant Microbe. In. 13, 830–836. Reid, A.P., Hominick, W.M., Briscoe, B.R., 1997. Molecular taxonomy and phylogeny of entomopathogenic nematode species (Rhabditida: Steinernematidae) by RFLP analysis of the ITS region of the ribosomal DNA repeat unit. Syst. Parasitol. 37, 187–193. Rolston, A., Meade, C., Boyle, S., Kakouli-Duarte, T., Downes, M., 2009. Intraspecific variation among isolates of the entomopathogenic nematode Steinernema feltiae from Bull Island. Ireland Nematol. 11, 439–451. Semblatt, J.P., Wajnberg, E., Dalmasso, A., Abad, P., Castagnone-Sereno, P., 1998. High resolution DNA fingerprinting of parthenogenetic root-knot nematodes using AFLP analysis. Mol. Ecol. 7, 119–125. Sokal, R.R., Michener, C.D., 1958. A statistical method for evaluating systematic relationships, vol. 28. University of Kansas Scientific Bulletin, 1409–1438. Spiridonov, S.E., Krasomil-Osterfeld, K., Moens, M., 2004. Steinernema jollieti sp. n. (Rhabditida: Steinernematidae), a new entomopathogenic nematode from the American Midwest. Russ. J. Nematol. 12, 85–95. Srinivasan, J., Pires-daSilva, A., Gutierrez, A., Zheng, M., Jung-blut, B., Witte, H., Schlak, I., Sommer, R.J., 2001. Microevolutionary analysis of the nematode genus Pristionchus suggests a recent evolution of redundant developmental mechanisms during vulva formation. Evol. Dev. 3, 229–240. Stock, S., Strong, D., Gardner, S., 1996. Identification of Heterorhabditis (Nematoda: Heterorhabditidae) from California with a new species isolated from the larvae of the ghost moth Hepialis californicus (Lepidoptera: Hepialidae) from the Bodega Bay natural reserve. Fund. Appl. Nematol. 19, 585–592. Stock, S.P., Choo, H.Y., Kaya, H.K., 1997. An entomopathogenic nematode, Steinernema monticolum sp. n. (Rhabditida: Steinernematidae) from Korea with a key to other species. Nematologica 43, 15–29. Szalanski, A.L., Taylor, D.B., Mullin, P.G., 2000. Assessing nuclear and mitochondrial DNA sequence variation within Steinernema (Rhabditida: Steinernematidae). J. Nematol. 32, 229–233. Tavechio, A.T., Fernandes, S.A., Neves, B.C., Dias, A.M.G., Irino, K., 1996. Changing patterns of Salmonella serovars: increase of Salmonella Enteritidis in Sa˘o Paulo, Brazil. Revista do Instituto de Medicina Tropical de Sa˘o Paulo. 38, 315–322. Van der Voort, J.R., van der Vossen, E., Bakker, E., Overmars, H., van Zandroort, P., Hutten, R., Lankhorst, R.K., Bakker, J., 2000. Two additive QTLs conferring broadspectrum resistance in potato to Globodera pallida are localized on resistance gene clusters. Theor. Appl. Genet. 101, 1122–1130. Vos, P., Hogers, R., Bleeker, M., 1995. AFLP: a new technique for DNA fingerprinting. Nucleic. Acids. Res. 23, 4407–4414. Yang, J.Y., Kim, H.H., Lee, D.W., Lee, S.M., Shin, H.C., Choo, H.Y., 2007. Biological control of Arge Captiva, Arge pagana pagana, and Arge similis with entomopathogenic nematodes. J. Korean For. Soc. 96, 1–6. Yilmaz, H., Waeyenberge, L., Demir, M., Moens, M., Demirbag, Z., 2009. First record of the entomopathogenic nematode Heterorhabditis megidis (Nematoda: Heterorhabditidae), from Turkey. Turk. J. Agric. Forest 33, 385–391. Yoshida, M., 2003. Intraspecific variation in RFLP patterns and morphological studies on Steinernema feltiae and S. kraussei (Rhabditida: Steinernematidae) from Hokkaido. Jpn. Nematol. 5, 735–746.