Molecular Characterization and Genetic Diversity Of

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Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Jorge Mario Londoño Caicedo

Universidad Nacional de Colombia Facultad de Ciencias Agropecuarias Sede Palmira Palmira Valle del Cauca, Colombia 2017 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Jorge Mario Londoño Caicedo

Tesis de grado presentada como requisito parcial para optar al título de:

Magister en Ciencias Biológicas

Director: PhD. Jaime Eduardo Muñoz Flórez

Línea de Investigación: Biotecnología vegetal

Grupo de Investigación: Diversidad Biológica

Universidad Nacional de Colombia Facultad de Ciencias Agropecuarias Sede Palmira Palmira Valle del Cauca, Colombia 2017

Acknowledgements

My sincere thanks to my parents for their daily support and to encourage me keep going forward in my career. Angélica Buitrago for her invaluable help in different fields; for some of the good friends from Diversidad Biológica research team for their company and support in our daily activities. Also special thanks to Fondo de Ciencia, Tecnología e investigación del Sistema General de Regalías FCTelSGR through the project “Desarrollo de Tecnologías Innovadoras para el Manejo Integrado de Plagas y Enfermedades Limitantes de Plátano y Banano en el Valle del Cauca” directed by Universidad Nacional de Colombia Sede Palmira. To professor Jaime Eduardo Muñoz for the opportunity to be part of the research group Diversidad Biológica.

3 Abstract and Resumen

Abstract

Banana and plantain are edible fruit crops widespread in tropical and subtropical regions, with high importance as a source of energy, nutrients and incomes for lots of families in developing countries. The Musa genus comprises twenty-eight species where M. acuminata and M. balbisiana are the most important species for commercial purposes. However several diseases and pests affect the productivity and fruit quality generating considerable losses every year. Banana weevil complex species are one of the main responsible of such losses worldwide; nevertheless several attempts have been carried out to control banana weevil populations. Cosmopolites sordidus is the most frequent species reported worldwide and with more interest for population control. In the present study four banana weevil species (C. sordidus, Metamasius hemipterus, M. hebetatus, Polytus mellerborgii) were found associated to banana and plantain stands. Genetic analysis on banana weevil species, from mtDNA and nr DNA Loci, indicated a widespread of few haplotypes across 12 municipalities of Valle del Cauca, also a low number of alleles were found indicating a possible bottleneck mediated by human activities. Additionally a survey for entomopathogenic nematodes (EPN) associated to plantain and banana stands was made, were Steinernematids and Heterorhabditids species were found, however molecular characterization indicates a low genetic diversity in EPN isolates. Two nuclear Loci (ITS and LSU) were sequenced and employed for species identification, indicating that from 14 isolates obtained, 10 of them belonged to Steinernema carpocapsae and four to Heterorhabditis spp. For the latter there was contrasting results when either ITS or LSU region was employed for species identification, nevertheless a concatenated analysis showed the presence of two species, Heterorhabditis bacteriophora and Heterorhabditis sp. These indigenous EPN isolates could be promising for biological control of weevil banana complex species, since this isolates were found associated to plantain and banana stands and, together with the low genetic diversity found in weevil species, it is expected to develop strategies for pests management using EPN isolates obtained in the present study. Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Keywords: Banana weevil, Haplotype, Genetic Diversity, Cytochrome Oxidase I, Ribosomal DNA.

Abstract and Resumen

Resumen

El plátano y el banano son frutos comestibles cultivados en las regiones tropicales y subtropicales, presentan importancia como fuente de energía, nutrientes e ingresos económicos para muchas familias de países en desarrollo. El género Musa comprende 28 especies siendo M. acuminata y M. balbisiana las especies mas importantes para propósitos comerciales. Sin embargo diversas enfermedades y pestes afectan la productividad y calidad del fruto generando pérdidas considerables cada año. El complejo de especies del picudo del banano son uno de los principales responsables de tales pérdidas a nivel mundial. No obstante varios intentos se han llevado a cabo para controlar las poblaciones del picudo del banano. Cosmopolites sordidus es la especie mas frecuente reportada a nivel mundial y en la cual mayor interés se ha llevado a cabo para su control. En el presente estudio cuatro especies de picudo del banano (C. sordidus, Metamasius hemipterus, M. hebetatus, Polytus mellerborgii) se encontraron asociadas a cultivos de plátano y banano. Análisis genéticos en especies de picudos, a partir de Loci mitocondrial y nuclear, indicaron un amplia distribución de pocos haplotipos en 12 municipios evaluados en el Valle del Cauca, también un bajo numero de alelos fue identificado indicando un posible efecto cuello de botella mediado por las actividades humanas. Adicionalmente se realizaron evaluaciones para obtención de nematodos entomopatógenos (NEP) asociados a plantaciones de plátano y banano, donde se encontraron especies de Steinernematidos y Heterorhabditidos, sin embargo la caracterización molecular mostró baja diversidad genética en los aislamientos. Dos Loci nucleares (ITS y LSU) fueron secuenciados y empleados para la identificación de especies, indicando que a partir de 14 aislamientos obtenidos 10 pertenecieron a Steinernema carpocapsae y cuatro a Heterorhabditis spp. Para este último hubo resultados contrastantes respecto a las regiones ITS o LSU y la asignación de especies, no obstante un análisis concatenado mostró la presencia de dos especies, Heterorhabditis bacteriophora y Heterorhabditis sp. Estos asilamientos nativos podrían ser promisorios para el control biológico de las especies del complejo de picudos, ya que fueron hallados en plantaciones de plátano y banano y, junto a la baja diversidad genética identificada en las especies del complejo de picudos, se espera desarrollar estrategias para el control de pestes usando los aislamientos de NEP obtenidos en este estudio.

Palabras clave: Picudo del Banano, Haplotipo, Diversidad Genética, Citocromo Oxidasa I, ADN Ribosomal.

Summary

Acknowledgements ...... 3 Summary ...... 8 List of figures ...... 10 List of tables ...... 11 Introduction ...... 12 1. Chapter 1 ...... 14 Genetic diversity and haplotype distribution of banana weevil species complex (Curculionidae; Dryophthorinae)...... 14 1.1 Introduction ...... 15 1.2 Methodology ...... 19 1.2.1 Sampling area ...... 19 1.2.2 Taxon sampling and DNA extraction ...... 19 1.2.3 PCR amplification for mtDNA and rDNA Loci ...... 21 1.2.4 DNA sequencing and Genetic analysis ...... 21 1.3 Results ...... 24 1.3.1 Genetic analysis in Weevil species through 28S Ribosomal RNA ...... 24 1.3.1.1 Haplotype diversity ...... 24 1.3.1.2 Haplotype Network ...... 26 1.3.1.3 Genetic dissimilarity in weevil species ...... 29 1.3.1.4 Principal Coordinate Analysis (PCoA) ...... 30 1.3.1.5 Maximum Likelihood analysis in Weevils ...... 35 1.3.2 Genetic analysis in Weevil species through COI mtDNA ...... 37 1.4 Discussion ...... 54 1.4.1 Haplotype distribution dispersal and movement ...... 55 1.4.2 Genetic diversity ...... 56 1.4.3 Amino acid composition in weevil species for COI mtDNA ...... 58 1.4.4 Phylogenetic analysis ...... 60 1.5 Conclusions ...... 62 1.6 References ...... 63 2. Chapter 2 ...... 76 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae) in Valle del Cauca as a source for biological control ...... 76 2.1. Abstract ...... 77 2.2. Resumen ...... 78 2.3. Introduction ...... 79

8 2.4. Methodology ...... 81 2.4.1. Sampling area ...... 81 2.4.2. Taxon sampling and DNA extraction ...... 81 2.4.3. DNA extraction and PCR amplifications for entomopathogenic nematodes ...... 82 2.4.4. DNA sequencing and Genetic analysis ...... 83 2.5. Results ...... 86 2.5.1. Analysis with Interspaced Transcribed Spacer (ITS) Ribosomal DNA region...... 86 2.5.2. Haplotype Network ...... 87 2.5.3. Dissimilarity Analysis ...... 90 2.5.4. Maximum Likelihood Analysis ...... 92 2.5.5. Analysis with Large Ribosomal Subunit (LSU) ...... 95 2.5.6. Maximum Likelihood Analysis ...... 100 2.6. Discussion ...... 106 2.6.1. Recovery and frequency of EPN ...... 106 2.6.2. Nucleotide composition and substitution rate in EPN ...... 107 2.6.3. Haplotype identification and genetic diversity in EPN ...... 109 2.6.4. Phylogenetic analysis in EPN ...... 109 2.7. Conclusions ...... 112 2.8. Annex ...... 113 2.9. References ...... 119

List of figures

Figure 1. Agarose gel 1% for genomic DNA extraction in weevil species ...... 20 Figure 2. PCR product for 28S and COI regions visualized in agarose gel 1.5% ...... 23 Figure 3. Haplotype network for weevil using 28S rDNA ...... 27 Figure 4. Weevil PCoA analysis for 28S rDNA ...... 31 Figure 5. Three-dimensional plot for genetic distance in weevil species using 28S rDNA ...... 32 Figure 6. Dissimilarity analysis in four weevil species for 28S rDNA ...... 34 Figure 7. Maximum likelihood analysis in four weevil species using 28S rDNA ...... 36 Figure 8. Haplotype network for weevil species using COI mtDNA ...... 39 Figure 9. PCoA for weevil species using COI mtDNA ...... 42 Figure 10. Three-dimensional plot fo weevil genetic distance for COI mtDNA ...... 43 Figure 11. Dissimilarity analysis in four weevil species using COI mtDNA ...... 44 Figure 12. Maximum likelihood analysis for four weevil species using COI mtDNA ...... 46 Figure 13. Amino acid sequences analyzed in four weevil species ...... 49 Figure 14. Maximum likelihood analysis in weevil species for amino acid composition ...... 51 Figure 15. Phylogenetic inference for weevil species using concatenated analysis including 28S and COI mtDNA gene ...... 52 Figure 16. Visualization of PCR product in EPN for LSU region ...... 83 Figure 17. Contig assemble for LSU rDNA from two independently sequenced fragments ...... 84 Figure 18. Network analysis for EPN haplotypes under ITS rDNA ...... 88 Figure 19. Simplified network for ITS rDNA in EPN ...... 89 Figure 20. Dissimilarity analysis in EPN for ITS rDNA ...... 91 Figure 21. Maximum likelihood tree for Heterorhabditis spp. under ITS rDNA region ...... 93 Figure 22. Maximum likelihood analysis for Steinernema spp. under ITS rDNA ...... 94 Figure 23. Network analysis for EPN haplotype under LSU rDNA region ...... 96 Figure 24. Network analysis for UN isolates EPN under ITS rDNA sequence ...... 98 Figure 25. Dissimilarity analysis in EPN for LSU rDNA ...... 99 Figure 26. Maximum likelihood analysis for Heterorhabditis spp...... 101 Figure 27. Maximum likelihood tree for Steinernema spp. under rDNA region ...... 103 Figure 28. Maximum likelihood analysis for Steinernema spp. under LSU rDNA ...... 104

List of tables

Table 1. Primer list used for weevil amplification ...... 22 Table 2. Haplotype diversity in weevil species ...... 25 Table 3. Nei genetic distance between weevil species ...... 29 Table 4. Nei genetic identity between weevil species ...... 29 Table 5. Nucleotide composition for weevil species respect to 28S rDNA ...... 37 Table 6. Haplotype diversity in weevil species for COI mtDNA gene ...... 38 Table 7. Nei genetic distance for weevil species using COI mtDNA ...... 40 Table 8. Nei genetic identity in weevil species for COI mtDNA ...... 41 Table 9. Nucleotide composition for COI mtDNA in weevil species ...... 47 Table 10. Amino acid composition for COI mtDNA in banana weevil species ...... 47 Table 11. Primer sequence for EPN molecular analysis ...... 82 Table 12. Haplotype diversity in EPN species for ITS rDNA ...... 87 Table 13. Haplotype diversity in EPN for LSU rDNA ...... 95 Table 14. Weevil Samples inclded in the analysis ...... 114 Table 15. UN isolates for Heterorhabditis nucleotide alignment ...... 116 Table 16. UN isolates for Steinernema nuclotide alignment ...... 117

Introduction

“Banana is an edible fruit crop that is widespread in tropical and subtropical regions around the world” (Biswas et al., 2015). Twenty-eight described species compose the Musa genus where Musa balbisiana and Musa acuminata are the most important species as a source of food and nutrients in tropical and subtropical regions (Introductionreview & Literature, n.d.). Edible Musa spp. originated in South-Eastern Asia and its distribution was from eastern part of India to Northern Australia. This distribution pattern is believed that Philippine spread Banana eastwards to the pacific islands, including Hawaii; and westward due to major trade routes reaching Africa around 500 AD. From there, in the 10th century, bananas arrived to Europe and then to Canary islands to finally reach South America during colonial times (Introductionreview & Literature, n.d.).

Worldwide production of Banana and Plantain is about 145.4 million tons, being China, Philippines, Ecuador and Indonesia the main producers (FAOSTAT, 2011). Economical incomes are about USD$98.7 billion dollars annually and approximately 311.942 families worldwide are benefited from this crop. The production area of Musaceae in America corresponds to 1.9 million hectares where Ecuador, Costa Rica, Colombia and Brazil are the main producers. In Colombia the annual production is about 3.9 million tones, where Antioquia and Magdalena are the most important departments for Banana production, and where 93.150 families obtain their incomes from it (FAOSTAT, 2011).

Introduction hebetatus, Metamasius submaculatus and Polytus mellerborgii (Rubio & Acuña, 2006) cause considerable damage in Banana crops decreasing dramatically yields and fruit quality, and at the same time increasing cost production, soil and water pollution due to high levels of pesticides to control weevil populations (Rubio & Acuña, 2006; Sánchez & Vallejo, 2010).

Several attempts have been made to control weevil populations using biological control agents such as entomopathogenic nematodes (EPN) due to their high ability to infect and kill their host, mainly at larval stage of development. Entomopathogenic nematodes (EPN) (Rhabditida) are cylindrical organisms, non-segmented that are free living or parasitic of arthropods, this condition makes the nematodes a source for biological control, especially the species from Steinernematidae and Heterorhabditidae families (Shapiroilan, Gaugler, & Brunswick, 2002). Symbiotic associations of these nematodes with specific bacteria (Xenorhabdus spp. associated with Steinernema, and Photorhabdus spp. associated with Heterorhabditis) facilitate the pathogenicity. Although some axenic nematodes species can cause host death occasionally, associations of nematodes and bacteria are necessary for a high level of pathogenicity; taking into account that bacteria cannot penetrate into the host by itself and requires the nematodes to get into the host, at the same time nematodes are benefited by bacteria because they create optimal conditions for nematodes reproduction into the host cadaver (Grewal, De Nardo, & Aguillera, 2001).

Considering the EPN applicability for weevil population control and all the phytosanitary issues involved in banana and plantain crops affecting negatively yield and fruit quality, the knowledge of genetic diversity, species identification and relatedness of EPN can lead to a positive and biological management for pest control and decreasing soil and water pollution due to abuse of agrochemicals. Currently the application of Next Generation Sequencing (NGS) for genome and transcriptome analyses had increased the comprehension of organisms at the genomic level. These new applications is a step forward to understand the natural history and biology of EPN with promising applicability in several fields such as biological control and alternative source of genetic products form associated bacteria for pest management. In the present study, genetic identifications and diversity surveys, on banana weevil species and EPN, were carried out to identify the status of pest species and parasitic species in Valle del Cauca to shed light about population diversity in both, pest and parasite species, and strategies for biological control in plantain and banana stands.

1. Chapter 1

Genetic diversity and haplotype distribution of banana weevil species complex (Curculionidae, Dryophthorinae)

Chapter 1

1.1 Introduction

Worldwide production of Banana and Plantain is about 145.4 million tons, being China, Philippines, Ecuador and Indonesia the main producers (FAOSTAT, 2011). Economical incomes are about USD$98.7 billion dollars annually and approximately 311.942 families worldwide are benefited from this crop. The production area of Musaceae in Latin America corresponds to 1.9 million hectares where Ecuador, Costa Rica, Colombia and Brazil are the main producers. In Colombia the annual production is about 3.9 million tones, where Antioquia and Magdalena are the most important departments for Banana production, and where 93.150 families obtain their incomes from it (FAOSTAT, 2011).

In Valle del Cauca Department this crop is cultivated in 27.000 hectares benefiting 12.500 producers. Varieties such as Dominico harton, Guayabo, Gros Michel and Guineo, are distributed in monoculture and intercalated with other crops, mainly coffee (ICA, 2014). However phytosanitary issues caused by Bacterial pathogens (Moko – Ralstonia solanacearum), Fungus (Sigatokas Mycosphaerella spp., Mal de Panamá Fusarium oxysporum), Phytoplasmas (probably the causal agent of Elefantiasis) (Álvarez et al., 2013); and pests such as weevil complex species that comprises Cosmopolites sordidus, Metamasius hemipterus, Metamasius hebetatus, Metamasius submaculatus and Polytus mellerborgii (Rubio & Acuña, 2006). These species cause considerable damage in Banana crops decreasing dramatically yields and fruit quality, and at the same time increasing cost production, soil and water pollution due to high levels of pesticides to control weevil populations (Rubio & Acuña, 2006; Sánchez & Vallejo,

2010). Weevils represent a stunning radiation of species, are classified in the superfamily Curculionidae that contains 60.000 species and 6.000 genera, being one of the richest groups in terms of evolution and diversity and remains one of the most challenging groups for taxonomy and stability of classification (Marvaldi, Sequeira, Brien, & Farrell, 2002; Oberprieler, 2007). These organisms use every plant part and infect almost every plant taxon. Weevils constitute various taxonomic groups that feed on roots, stem, leaves, flowers, fruits or seeds on conifers, cycads, dicots and monocots. Due to their herbivore behavior have shifted in plant taxa innumerable times, even in several studies some patterns have been identified, these patterns could be related to ecological and genetic bases of evolutionary processes among and within species (Marvaldi et al., 2002).

Weevils are beetles of rigid body with a high degree of chitin and strong rostrum used to drill the pseudostem, whether to obtain food or to lay eggs. The larval stage causes serious damage to plat tissue weakening the plant, and through the wounds, pathogens can colonize and consequently kill the plant, even could be related to facilitate the entering of the fungus that is the causal agent of Mal de Panamá disease (Fusarium oxysporum) and Ralstonia solanacearum bacteria, the causal agent of Moko disease (ICA, 2014).

The origin of banana weevils is believed to be Indo-Malaysian region, as well as the origin of banana species, however these insects have been disseminated throughout the world making difficult to determine its center of origin (Hasyim & Hilman, 1964).

Within banana weevil complex, the black weevil (Cosmopolites sordidus), is the most frequent species found worldwide in plantain and banana stands (Sirjusingh, Kermarrec, Mauleon, Lavis, & Etienne, 1992; Trejo, 1971). Several population studies consider the presence of this organism in tropical and subtropical regions (Carballo 1990; ICA 2014), indicating the probability that human activities are the main source of banana weevil dispersal due to the low dissemination behavior identified in this species (Carballo, 1990).

Several studies have been made in weevil species, especially in C. sordidus due to its high frequency and damage, these studies include identification of germplasm plant resistant (Kiggundu, Gold, Labuschagne, Vuylsteke, & Louw, 2003), plant antifeedants, cultural control practices and biological control (Aranzazu et al., 2000; Côte et al., 2009; Dahlquist, 2008; C. Gold, Okech, & Nokoe, 2002; C. S. Gold, Pena, & Karamura, 2003; Ittyeipe, 1986; Silva &

16 Introduction

Fancelli, 1998). However information about genetic diversity is still poor, additionally for species such as Metamasius hemipterus, M. hebetatus, M. submaculatus and Polytus mellerborgii, which there is no information available in databases indicating a possible lack of interest to know about genetic populations and haplotype distribution in different regions of the world, or perhaps their frequency is not significant to catch the attention.

Some genetic analyses have been carried out in C. sordidus. Graaf (2006) analyzed C. sordidus populations from different parts of the world using AFLP marker (Amplified Fragment Length Polymorphism) to identify genetic relatedness within and among geographically separated weevil populations; Marvaldi et al. (2002) performed a phylogenetic hypothesis for Curculionidae family through 18S rDNA and 115 morphological characters, where Dryophthorinae subfamily was identified as a monophyletic group; Lefèvre et al. (2004) studied symbiotic bacteria in 19 Dryophthorinae species identifying specialized cells product of a co- speciation of the host and the endosymbionts; Wild & Maddison (2008) proposed new Loci for protein-coding gene in beetles for molecular analysis applicable for weevil species; Dutrillaux et al. (2008) evaluated mitotic and meiotic differences between Curculionidae and Dryophthorinae families, indicating that karyotype is a character that could split Curculionidae family into two families; McKenna et al. (2009) identified divergence time and phylogeny of weevils based in 8 kilobases of DNA from different Loci; Jordal et al. (2011) studied the subsociality behavior of weevil species to identify the success of these species in several environments; Duque (2012) analyzed the population structure of banana weevils in three departments from Colombia, identifying low genetic variability between populations; Valencia et al. (2016) performed pyrosequencing in C. sordidus midgut identifying larval physiology and targeting novel genomic sites for management and approaches in this species.

The understanding of diversity and populations of weevil species, their biological cycle and the interaction with other organisms, can lead to strategies for biological control as an alternative method to decrease soil pollution and costs for Banana and Plantain production. Several studies have applied this method. (Castiñeiras, López, Calderón, Cabrera, & Luján, 1990) applied biological control using natural enemies, in that study the weevil populations where controlled by two ant species Pheidole megacephala and Tetramorium gunieense, where the former decreased weevil population up to 55% and the lasts 83%, also the proportion damage of Banana plantations decreased 65% and 67% respectively. Fungal species such as Bauveria

17 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control bassiana and Metarhizium anisopliae are promising organisms as a source for this purpose, (Carballo, 1990) using differential spores concentrations produced a mortality of insects between 81% and 95% in rice and bean. Additionally (Côte et al., 2009) used entomopathogenic nematodes to control C. sordidus populations, where Steinernema carpocapsae was the most infective species for weevil control. These studies have shown the applicability and importance of biological control as a method for pest population control and decrease the use of toxic pesticides and soil and water pollution.

The purpose of the present study is i) to evaluate the genetic diversity of weevil complex species associated to Banana and Plantain crops, as well as to identify, through molecular data, banana weevil species commonly found in the North, Center and Western of Valle del Cauca; ii) to identify haplotype distribution in Valle del Cauca department and possible patterns of banana weevil migration from molecular data and iii) verify the status of banana weevils respect to Dryophthorinae in Curculionidae clade as a monophyletic group.

Chapter 1

1.2 Methodology

1.2.1 Sampling area description

Sampling period was carried out form November 2015 to December 2016 in twelve municipalities from Valle del Cauca covering the north, center and western of the department. Thirty-three farms were included with areas that ranged from 0.64 hectares to 30 ha and from 7 m.a.s.l (Buenaventura) to 1.734 m.a.s.l. (El Cairo), in total 325.76 ha were covered for sampling. The average number of plants in all farms visited was 2.740, being Plátano Hartón and Banano común the most frequent varieties planted, with the lowest number found in Buenaventura municipality (40) and the highest in Yotoco municipality (30.000). Also the most frequent municipality visited was Argelia with 9 farms followed by Yotoco and Buenaventura with 8 farms sampled each; El Cairo 7, Sevilla 6, Palmira 4, Roldanillo 3, and Obando, Ginebra, Buga and Bugalagrande with two farms sampled each. Several plantain and banana stands were associated mainly with coffee and cassava, and in some cases were associated with fruit trees.

1.2.2 Taxon sampling and DNA extraction

Weevil sampling was carried out from banana and plantain stands using direct capture of individuals from different stages of development (larval, pupa, adult) and properly neutralized, sacrificed and stored in alcohol 70% for morphological and molecular analysis. In almost all cases the organisms were collected from fallen stems, and seldom from alive stems, because that meant cut them down. Approximately 300 weevils were obtained from species Cosmopolites sordidus, Metamasius hemipterus, Metamasius hebetatus and Polytus mellerborgii; this taxa classification was considering morphological characters a priori. All samples were transported to Universidad Nacional de Colombia sede Palmira and stored at 4ºC. The encephalic region from each individual at larval or pupa stage of development was used for DNA extraction, this body part was employed to avoid contamination from all digestive tract symbionts and possible errors from sequencing data, this procedure was carried out using Vivantis® tissue GF-1 DNA extraction kit following the instructions of the manufacturer. This body arthropods segment were ground directly in DNA extraction buffer until obtain small pieces, then were placed at 65ºC in presence

Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control of proteinase K overnight. Once the tissue was completely dissolved the DNA extraction procedure was followed according with the instructions of the manufacturer.

For adult individuals several methods for DNA extraction based on Phenol and Chloroform were evaluated (Acevedo, Navarro, Constantino, Gil, & Benavides, 2007; Aljanabi & Martínez, 1997; Sambrook, Fritsch, & Maniatis, 1989), and commercial kits Vivantis®, these methods were applied to obtain a good DNA quality, however due to the presence of chitin, this process was more difficult. Nevertheless dissection of individuals in adult stage of development were performed, for this process the thorax of the organism was dissected to get the muscles present in that region of the body, the muscles were ground in DNA buffer, provided by the manufacturer in the Vivantis® kit, and put in presence of proteinase K at 65ºC overnight, later the protocol for DNA extraction was performed according with the instructions of the manufacturer. Once the DNA was extracted an electrophoresis in agarose gel 1% was carried out to verify the quality of the nucleic acids, the DNA samples were stained with GelRed® and visualized under UV light (Fig. 1). Additionally all DNA stock samples were quantified in Spectrophotometer Colibri Titertek Berthold®, an average concentration of 200ng/µl was get; finally the DNA concentration was normalized for each sample preparing a working solution at 30ng/µl for PCR reactions. A total of 150 banana weevil individuals, for all species analyzed here, were extracted but 110 showed good DNA quality for PCR amplifications.

Figure 1. Agarose gel 1% for genomic DNA extraction in weevil species

Genomic DNA from weevil species visualized in agarose gel 1% were DNA from 10 samples are shown, The last fragment corresponds to DNA Lambda with a concentration of 200ng/µl. The smears correspond to the presence of RNA and partially degraded DNA.

Chapter 1

1.2.3 PCR amplification for mtDNA and rDNA Loci

Five Loci were evaluated in weevils genomic DNA, four from nuclear DNA, Internal Transcribed Spacer (ITS), Large Ribosomal Subunit (LSU 28S), Elongation Factor Alpha (EFα) and Topoisomerase I, and one from mitochondrial DNA Cytochrome Oxidase I (COI) (Table 1). All reactions were performed in a final volume of 50µl of PCR cocktail mixing 4µl of DNA 30ng/µl;

5µl of PCR Buffer 10X (NH4)2SO4; 4µl MgCl2 25mM; 2µl dNTP’s 20mM; 0.8µl Primer F 10mM; 0.8µl Primer R 10mM; 1µl BSA 5X; 2µl Trehalose 10%; 0,32µl Taq DNA polymerase 5U/µl; and 30µl of ultra pure water. These conditions were applied for the five Loci in he four weevil species collected.

The PCR profile for COI Loci was as follows: 95ºC x 5 min; 1 cycle of 95ºC x 1min; 42ºC x 45 sec; 72ºC x 1 min; followed for 32 cycles of 95ºC x 1 min; 40ºC x 45 sec; 72ºC x 1 min; final extension of 72ºC x 10 min. For Topoisomerase I the conditions were equally as described for COI but with a Tm of 59ºC, ITS rDNA 54ºC, 28S 55ºC, and EFα a touchdown PCR profile of 44- 58ºC. However for Loci ITS unspecific fragments were obtained even after several modifications of PCR cocktail and thermal profile; EFα showed two fragments amplified in all conditions evaluated and Topoisomerase I did not amplified at all under any of the possible changes applied. The visualization for all Loci amplified was carried out in agarose gel 1.5% and electrophoresed at 120 volts for 45 min in TBE buffer 0.5X; all amplified products were stained with GelRed® nucleic acid gel staining, gel visualization was performed in transiluminador under UV light (Fig. 2).

1.2.4 DNA sequencing and Genetic analysis

DNA sequencing was carried out in both directions (Forward and Reverse) using the primers employed for PCR amplification. For these process the PCR products were purified following the protocol proposed by Schmitz & Riesner (2006), afterwards the samples were visualized again in agarose gel 1.5% and stained with GelRed® to verify the quality and concentration of the product. For the Sequencing process forward and reverse directions were considered to obtain more accurate information about the nucleotide composition for every organism.

Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Raw sequence data were visualized and edited manually in Geneious R10 (Kearse et al., 2012), contigs where evaluated with primer forward and reverse sequences to remove them, in than way the sequences had a specific length to verify any INDEL event among and between species.

Table 1. Primer list used for weevil amplification

Primer name Primer sequence 5´- 3´ Direction Gene Region Author

LCO1490 GGTCAACAAATCATAAAGATATTGG Forward COI Mitochondrial Formel et al 1994

HCO2198 TAAACTTCAGGGTGACCAAAAAATCA Reverse COI Mitochondrial Formel et al 1994

28S Pic 3690 F GAGAGTTMAASAGTACGTGAAAC Forward 28S Nuclear Jordal et al 2011

28S Pic 4394 R TCGGAAGGAACCAGCTACTA Reverse 28S Nuclear Jordal et al 2011

EFS 149 Pic F ATCGAGAAGTTCGAGAAGGAGGCYCARGAAATGGG Forward Elongation factor Nuclear Jordal et al 2011

EFA 754 Pic R CCACCAATTTTGTAGACATC Reverse Elongation factor Nuclear Jordal et al 2011

TP643F GAC GAT TGG AAR TCN AAR GAR ATG Forward Topoisomerase Nuclear Wild & Maddison 2008

TP932R GGW CCD GCA TCD ATD GCC CA Reverse Topoisomerase Nuclear Wild & Maddison 2008

ITS_Pic_F GGG TCG ATG AAG AAC GCA GC Forward Intergenic spacer Nuclear Navajas et al. 1998

ITS_Pic_R ATA TGC TTA AAT TCA GCG GG Reverse Intergenic spacer Nuclear Navajas et al. 1998

Nucleotide bases different to A, T, C, G, correspond to ambiguous bases, degenerated points in the sequence.

Sequences were aligned using Bioedit® v. 7.1.11 (Hall, 1999) for further genetic analysis. For haplotype identification DNAsp v. 5 (Rozas & Rozas, 1995) software was employed to identify the number of haplotypes, mutational positions and nucleotide diversity contained in every sequence. For Network building the software Network 5.0.01 (Fluxus-engineering, 2015) was employed, this software identify the haplotypes present in the populations and build a network according to mutational steps found among the sequences, also through median vector statistics hypothetical intermediate ancestral sequences can be created to reduce the network complexity for an easy interpretation. Following this description the networks were built considering Transversions three times weighted than Transitions, due to that the former is less probable to occur creating a less complex and stepwise network, maximum parsimony.

Chapter 1

Figure 2. PCR product for 28S and COI regions visualized in agarose gel 1.5%

Weevil DNA amplified with 28S Pic 3690 F, 28S Pic 4394 R for 28S rDNA, and LCO1490, HCO2198 primers for mtDNA. Visualization of the PCR product was carried out in agarose gel 1.5%. Molecular ladder used to verify the size product amplified was 100bp plus Thermo Scientific®. The first three lines correspond to 28S rDNA region, the last two correspond to COI mtDNA gene region.

For dissimilarity analysis GenAlex v.6.5 (Peakall & Smouse, 2012) was employed to identify genetic distance between species and among individuals, this matrix was used for Principal Coordinate Analysis (PCoA) that represents a spatial distribution of populations (species) and individuals in a 2 dimensional Cartesian plane plot, however despite the difficulty to interpret a PCoA in two-dimensional plot an additional analysis with Xlstat (Addinsoft, 1993) was employed for a three-dimensional plot to ease the interpretation of genetic distance in terms of spatial distribution.

Dissimilarity Analysis and Representation for Windows DARWIN v. 6.0.014 (Perrier, Flori, & Bonnot, 2003) was performed in all sequence data under Neighbor-Joining algorithm to identify the closeness of samples in an unrooted tree computing the bootstrap method with 3000 replicates and obtaining the most parsimonious tree. Several tree topologies were obtained but the most explainable are shown. For phylogenetic inferences Mega 7.0 (Tamura, Dudley, Nei, & Kumar, 2007) was used, this phylogenetic analysis for Weevils was carried out through Maximum likelihood, using a Bootstrap of 1000 replicates based on Kimura two-parameter model with a heuristic search considering the Maximum Parsimony for the initial tree.

23 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

1.3 Results

From 12 municipalities visited, 33 villages and 33 farms that range in size from 0.64 hectares to 30 hectares, and from 7 m.a.s.l to 1.734 m.a.s.l. Approximately 300 weevil individuals from Cosmopolites sordidus, Metamasius hemipterus, M. hebetatus and Polytus mellerborgii species in different stages of development (Larvae, Adult and Pupa) were collected. However 150 were used for DNA extraction and 110 could be extracted for PCR amplification, nevertheless 94 samples were successfully amplified for 28S Ribosomal DNA with a fragment of approximately 800 base pairs, and 96 samples, including the 94 amplified for 28S region, were amplified for COI mtDNA region generating a fragment of approx. 600 base pairs. From there 35% of the samples were sequenced for M. hebetatus, 33% for M. hemipterus, 22% for C. sordidus and 10% for P. mellerborgii.

1.3.1 Genetic analysis in Weevil species through 28S Ribosomal DNA 1.3.1.1 Haplotype diversity

A total of 94 weevil samples that belongs to 4 species (Cosmopolites sordidus, Metamasius hemipterus, Metamasius sp. and Polytus mellerborgii) were sequenced for 28S ribosomal DNA. C. sordidus comprises 16 samples from 2 municipalities, M. hemipterus comprises 33 samples from 6 municipalities, Metamasius sp. comprises 35 samples from 7 municipalities and Polytus mellerborgii with 10 samples obtained in two municipalities (Table 2). From the 28S ribosomal region sequenced for the four species, 857 sites were considered in the analysis from which 568 were monomorphic sites, 142 were polymorphic sites and parsimony informative sites were 136. Also form the total 857 sites, 47 were gaps, 141 INDEL events, and a total of 162 mutations were identified (Table 2).

Curculionidae has been identified as a highly diverse family, even Coleoptera order is one of the most complex taxon in phylogeny and natural history (Jordal et al., 2011; Kajtoch, Lachowska- Cierlik, & Mazur, 2009; Andrea S Sequeira, Normark, & Farrell, 2000; Wild & Maddison, 2008).

In the present study the genetic variation identified trough 28S Ribosomal region in four banana weevil species could indicate low complexity of the species, but if its consider that only 857 nucleotides were surveyed, a low number of individuals were analyzed and the sampling area

Chapter 1 was basically the north side of Valle del Cauca, this low variation can be affected for those conditions.

Table 2. Haplotype diversity in weevil species

Haplotype Diversity in weevils identified using 28S rDNA region

No. Haplotype Nucleotide Number of Segregating Species Municipality Haplotypes Specimens Diversity Diversity sites

C. sordidus Argelia - Obando 16 2 0.125 0.00123 7

Yotoco - El cairo - Argelia - Metamasius sp. Roldanillo - Caicedonia - Obando 35 2 0.057 0.00008 1 - Buga El Cairo - Argelia - Sevilla - Cria M. hemipterus 33 3 0.424 0.00062 2 - B/ventura - Obando

Polytus Palmira - Caicedonia 10 1 0 0 0 mellerborgii

Total Data 94 8 0.7677 0.06562 142 Total number of data for 4 Weevil species using 28S rDNA region

Total Number of sites: 857 Sites excluding gaps: 710 Number of gaps: 47 Total number of mutations: 162 Total number of INDEL: 141 Monomorphic sites: 568 Polymorphic sites: 142 Parsimony Informative sites: 136

Due to in that area banana and plantain crops are commonly grown, the population sampling is limited in terms of population delimitation, also the distance between sampling was low. This was reflected in haplotype diversity identified in the four species, the high differentiation of nucleotide composition between them was (0.7677), despite that these species belongs to the same superfamily (Curculionidae) and family (Dryophthorinae) the genetic variation was high enough to discriminate between species.

Respect to haplotypes identified in this analysis (8) and considering 94 samples evaluated, this indicates low levels of variation between one sequence respect to the other; if we consider that one haplotype is exactly the same sequence shared by two or more individuals. In the case of Polytus mellerborgii only one haplotype was identified in 10 samples from two distant municipalities (Palmira and Caicedonia), being this species the lowest in frequency for the whole study. For C. sordidus two haplotypes were identified, however this species was sampled mainly in Argelia and Obando municipalities where the population density was very high; for Metamasius sp., that was collected in 7 municipalities, only two haplotypes were identified and for M. hemipterus 3 haplotypes were present in 6 municipalities. This pattern of homogeneous haplotypes across all municipalities and for all species analyzed here could be an indicative of

25 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

gene flow among distant populations, however banana weevil migration behavior for long distance has not been reported yet and this topic is going to be addressed in the discussion section.

In terms of diversity within species, C. sordidus represented 0.125 of haplotype diversity and 0.00123 of nucleotide diversity, Metamasius sp. 0.057 and 0.00008 respectively, M. hemipterus 0.424 and 0.00062, and P. mellerborgii with no variation at haplotype and nucleotide composition (Table 2). It is important to highlight that haplotype diversity do not correspond directly to nucleotide diversity, because the former is very sensitive to any change in nucleotide composition generating a different haplotype, whereas the latter consider the number of changes identified respect to the length of the sequence. If these slight changes can be identified in a population this diversity measurement would be high, however nucleotide diversity could be very low, as was identified in the present study, and that is because few nucleotide changes in a long DNA sequence is not representative for this measurement.

To represent this scenario, the number of segregating sites for every species analyzed was considerably low, taking into account that this genomic region is highly conserved within taxa. For C. sordidus 7 segregating sites were identified and the nucleotide diversity was the highest in the study (0.00123), for M. hemipterus were 3 the segregating sites and for Metamasius sp. were 2, finally for P. mellerborgii there was no any changes; despite this values, the total number of changes, considering the four species in a single analysis, 142 segregating sites were identified, that corresponds to the genetic distance between species (Table 2).

1.3.1.2 Haplotype Network

Network analysis included 94 samples as mentioned above and 857 nucleotide positions. This analysis considered gaps and nucleotide variants indicating which organisms share the same sequence (haplotype); also the network was built under the most parsimonious steps for point mutations. The analysis carried out for 28S Ribosomal region showed 12 nodes, where two corresponds to Metamasius sp., five for M. hemipterus, two for C. sordidus and 3 for P. mellerborgii. Additionally every node was divided according with the origin of the sample (Pie chart) and the respective connection with the closest haplotype (Fig. 3).

Chapter 1

The source of all samples include 12 municipalities and from breeding process for M. hemipterus. Argelia was the municipality that possessed the highest frequency of individuals for Metamasius sp. and C. sordidus, also Metamasius sp. was the most frequent species covering 7 of the 12 municipalities sampled, followed by M. hemipterus found in six municipalities and C. sordidus and P. mellerborgii found in two municipalities each (Fig. 3).

Figure 3. Haplotype network for weevil using 28S rDNA

Metamasius hemipterus

Metamasius sp.

Argelia Yotoco El Cairo Breeding B/ventura Polytus mellerborgii Obando Cosmopolites sordidus Sevilla Caicedonia Roldanillo Palmira Buga Ginebra Network analysis in four weevil species. Every circle represents a specific haplotype and every color represents the origin of the sample (municipality). Red lines indicate connection of haplotypes within the same species, blue lines connects nodes (circles) between species.

Respect to haplotype distribution Metamasius sp. was the species more spread, mainly in Yotoco and Argelia, however this species was found in all the municipalities that belongs to the

27 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control north of Valle del Cauca, C. sordidus was restricted to Argelia and Obando, M. hemipterus was in the north of Valle del Cauca, however two samples were collected in Buenaventura but the haplotype identified for these samples was the same found in the north of the department; this could indicate a recent distribution of the species in the western slope of the western range, possibly due to human carriage.

Polytus mellerborgii presented 3 nodes distributed in two municipalities (Caicedonia and Palmira); this low distribution is related with the low frequency of the species in all the places sampled, additionally the small size of the organisms makes them difficult to find in the field. Nevertheless, and despite the small number of individuals, P. mellerborgii showed genetic differentiation in haplotype distribution, where Palmira and Caicedonia has very differentiated haplotypes in two nodes, and one-third haplotype shared for these municipalities.

Haplotype network indicates that Metamasius sp. is close to M. hemipterus (less nucleotide changes among them) and this species (M. hemipterus) possess haplotypes with low mutational changes respect to C. sordidus and P. mellerborgii. According to this network Metamasius sp. possess the less mutated sequences and the high frequency restricted to one haplotype, indicated as the “ancestral” sequence and is used by the program as the initial state of the sequence and from which all the calculations are made. In this sense, the order and distribution of the haplotypes in the four species consider Metamasius sp. as the “initial state” of the characters, then M. hemipterus as the first derivative with the lowest variations accumulated, followed by C. sordidus and P. mellerborgii with the highest mutations or variations accumulated respect to the sequence of the “initial state”, however M. hemipterus is the only intermediate species that connect the network, but four of the haplotypes has certain similarity with the haplotypes from C. sordidus and P. mellerborgii and one of the M. hemipterus haplotype (green and blue light node) did not showed any relatedness to other species, this indicate a possible interesting haplotype to consider in further studies.

The comparison between the analysis carried out by DNAsp and Network indicate differences in number of haplotypes identified, this incongruence is explained by the fact that DNAsp do not consider gaps as point mutations and Network does, under this scope Network identified more haplotypes giving rise to the richness of the nodes for every species.

Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

1.3.1.3 Genetic dissimilarity in weevil species

Dissimilarity analysis was carried out to identify the genetic distance between species, that were treated as populations. A total 858 characters per sample were included in the analysis and 94 samples were evaluated, generating a data set of 80,652 characters; one sequence from Anthribidae family (accession number HQ883527) was included as an out-group, this species was also employed in the same way by (Jordal et al., 2011). Nei genetic distance showed that M. hemipterus and P. mellerborgii are more closely related to each other being the lowest genetic distance identified (0.01), this can be related with the number of branches shared in Network analysis where these two species interconnect four times and is the most complex network between species evaluated (Table 3).

On the other hand C. sordidus and P. mellerborgii were the most distant related species (0.180), this is consistent with Network analysis where no branches were shared between the two of them. On the next level Metamasius sp. and M. hemipterus have a genetic distance of 0.041 being the second lowest differentiation, and C. sordidus was the most differentiated species with values ranging from 0.152 (with M. hemipterus) up to 0.180 (with P. mellerborgii) (Table 3).

Table 3. Nei genetic distance between weevil species

Pairwise Population Matrix of Nei Genetic Distance C. sordidus Metamasius sp. M. hemipterus P. mellerborgii Anthribidae sp. 0.000 C. sordidus 0.167 0.000 Metamasius sp. 0.152 0.041 0.000 M. hemipterus 0.180 0.054 0.010 0.000 P. mellerborgii 0.231 0.159 0.153 0.171 0.000 Anthribidae sp.

Table 4. Nei genetic identity between weevil species

Pairwise Population Matrix of Nei Genetic Identity

C. sordidus Metamasius sp. M. hemipterus P. mellerborgii Antrhibidae sp. 1.000 C. sordidus 0.846 1.000 Metamasius sp. 0.859 0.960 1.000 M. hemipterus 0.836 0.947 0.991 1.000 P. mellerborgii 0.794 0.853 0.858 0.843 1.000 Anthribidae sp.

Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

The genetic identity showed values between 0.991 (M. hemipterus and P. mellerborgii) and 0.836 (C. sordidus and P. mellerborgii) with an average genetic distance of 0.880 (Table 4). These values correspond to those of genetic distance and corroborate the similarity between species analyzed. Respect to Anthribidae sp. (out-group) the highest differentiation was with C. sordidus (0.231) and the lowest with M. hemipterus (0.153). However this out-group was classified into the Anthribidae subfamily and Curculionidae family; but the species, from which the sequence was obtained, has not been classified and no information is available, nevertheless has been used as out-group for Coleoptera phylogenetic studies (Jordal et al., 2011).

1.3.1.4 Principal Coordinate Analysis (PCoA)

This analysis employed the matrix of Nei genetic distance between populations, where population 1 corresponds to C. sordidus, population 2 Metamasius sp. population 3 M. hemipterus, population 4 P. mellerborgii and population 5 Anthribidae as the out-group. The analysis explained in three coordinates the genetic variation between populations and considers which populations are closer and which are the most distant. In the first coordinate the total genetic variation explained was 44.42%, the second coordinate explains 42.71% of genetic variation, and with an accumulative of 87.13%, the third coordinate explains 11.42% of genetic variation with an accumulative of 98.55% of genetic variation explained. In three coordinates all the variability is explained to almost 100%, which indicates that the differentiation between populations is high enough to be explained in a few axis or coordinates.

Population 1, which corresponds to C. sordidus, is the most differentiated as well as Anthribidae (out-group) showing disperse plot in the axes 1 and 2. Respect to population 2 (Metamasius sp.), population 3 (M. hemipterus) and population 4 (P. mellerborgii), are the closest group showing low genetic differentiation. If its consider that M. hemipterus and Metamasius sp. belongs to the same genus, is consistent with the closeness identified in the PCoA analysis, however P. mellerborgii seems to be closer to Metamasius species despite the differences in morphology, but this genetic region, 28S Ribosomal RNA, could be more conserved between them and the changes in nucleotide composition are more discrete respect to C. sordidus and Anthribidae sp. (Fig. 4).

Chapter 1

Figure 4. Weevil PCoA analysis for 28S rDNA

C. sordidus

Metamasius sp.

M. hemipterus P. mellerborgii Anthribidae Out-group Principal Coordinate Analysis (PCoA) for weevil species shown into four populations represented in every color.

The Principal Coordinate Analysis used for the whole set of samples (94) considered every individual as a unique sample, in this method the genetic distance was employed without consider the population from which every sample comes from. This method make comparisons among the whole set of samples, as independent ones, and plot them according to the dissimilarity identified. The lower the differences between the samples the closer the plotting. Under this method all biases are eliminated giving a more reliable grouping of the samples in three-dimensional plot.

31 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 5. Three-dimensional plot for genetic distance in weevil species using 28S rDNA

Metamasius sp.

P. mellerborgii.

M. hemipterus.

C. sordidus

Anthribidae sp.

Genetic distance between weevil species represented in a three dimensional spatial plot for 28S rDNA. Every species is codified with a respective color.

The three-dimensional plotting is understood if the axes X, Y and Z can be identified in the plane. For the figure (Fig. 5) the three axes are colored; in yellow is highlight the axis X where 44.42% of genetic variation is explained and the most distant group to this axis is C. sordidus (dark green); for the Y axis, colored with light blue, 42.71% of genetic variation is explained, the most distant group respect to this axis is Anthribidae (dark blue), and for the axis Z, colored with light green, explained 11.42% of genetic variation, where P. mellerborgii (light green) and Anthribidae were the most distant species respect to this axis.

Once the axes are defined, it can be identified that all the groups are very distinctive and separated to one another, and the distance within every group is minimum indicating the low genetic variation into every group. C. sordidus and Anthribidae are genetically distant, while Metamasius sp. and M. hemipterus are close to axis X, P. mellerborgii seems to be close to Metamasius sp., but also is closer to M. hemipterus than C. sordidus indicating that P. mellerborgii is the closest group to Metamasius genus. This plotting obtained is similar to the

Chapter 1 plotting for populations (Fig. 4) where C. sordidus is genetically different in the analysis, M. hemipterus, Metamasius sp. and P mellerborgii are close to one another and the out-group is distant to weevil species.

The dissimilarity analysis carried out in Darwin, it can be identify 4 branches that correspond to every species. The longest branch belongs to Metamasius sp. indicating more mutational events in the sequences from that species. Every small sub-branch, coming from the main one, represents an individual sequence and the length of these correspond to mutations accumulated respect to a particular sequence, in this sense the longer the branch the higher the number of mutations identified. Once we have this in mind, the branch that corresponds to Metamasius sp. is longer, following for the branch of M. hemipterus, C. sordidus and P. mellerborgii. In the case of M. hemipterus three discrete branches can be identified corresponding to three haplotypes identified in this species; for Metamasius sp. it can be noticed the direction of the branches respect to the centroid (red point), there are two directions that corresponds to branch division indicating two haplotypes present in the sequence analyzed for this species. For C. sordidus there is a clear long branch indicating one haplotype, also is closer to P. mellerborgii, which had no differentiation in tree topology related to only one haplotype identified (Fig. 6).

The branches organization indicates to Metamasius sp. (in green) as the starting point of the analysis, M. hemipterus as the closest species after the first split of the main branch, then the cluster conformed by P. mellerborgii and C. sordidus, under de same branch, indicates sequences with more nucleotide substitution respect to Metamasius sp. It is important to highlight that this tree topology is unrooted and the placement of the samples is based on Neighbor-Joining algorithm, indicating that the samples are integrated to the closest neighbor from which the dissimilarity is the lowest identified. This analysis was performed with a Bootstrap of 3000 replicates making the comparisons more accurate, and tree topology was based on the most parsimonious tree (Fig. 6).

33 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 6. Dissimilarity analysis in four weevil species for 28S rDNA

Cosmopolites sordidus

Polytus mellerborgii

Metamasius hemipterus

Metamasius sp.

Unrooted tree for dissimilarity analysis in four weevil species based on 28S rDNA. Every species is represented in a single color. Each sample corresponds to every small branches connected to the main ones.

Chapter 1

1.3.1.5 Maximum Likelihood analysis in Weevils

The Ribosomal DNA 28S region sequenced for tis study comprises 857 sites, however 725 nucleotide positions were included in the analysis and 132 gaps were identified. This region separated all weevil species in specific clusters, being Metamasius sp. and M. hemipterus closely related to each other and C. sordidus and P. mellerborgii forming a separate group. The bootstrap tree had a support of 100% for all branches; even the two branches related to M. hemipterus were well supported in the analysis. This two branches scenario in M. hemipterus indicates two divergent sequences, however the genetic distance is not long enough to generate a separate group that could indicates a different species (Fig. 7). This Metamasius sp. group corresponds to samples that phenotypically were identified as Metamasius hebetatus, after DNA extraction from adult organisms and high quality PCR amplification and sequencing, this species could not be verified in the NCBI database, because there are no reports for this species in the Genbank. The closest species identified in the BLAST algorithm in NCBI was Rinchophorus cruentatus, but the sequence coverage was 85% indicating a very distant sequence. However after several evaluations of phenotypic traits, it was concluded that Metamasius sp. correspond to M. hebetatus.

The nucleotide composition for every species showed that Cytosine and Guanine are the most frequent nucleotides with an average of 25% and 30% respectively, whereas Adenine and Thymine had an average of 21% and 22% respectively (Table 5). Mutation rates respect to Transitions and Transversions showed that Transitions are more frequent than Transversions. In the first case, Transitions, the value obtained was 16.80% for A/G and C/T changes; while for Transversions the value obtained was 4.09% for A/T, A/C, T/G, C/G changes.

35 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 7. Maximum likelihood analysis in four weevil species using 28S rDNA

Maximum Likelihood analysis for weevil species using 28S rDNA region. Bootstrap tree represents every species with a particular color. Bootstrap values obtained for external nodes were 100%, bootstrap values for internal nodes were over 70% probability (data not shown).

Chapter 1

Table 5. Nucleotide composition for weevil species respect to 28S rDNA

Species T/U C A G Total Cosmopolites sordidus 21.7 25.7 22.2 30.4 816.0 Metamasius hemipterus 22.1 25.5 21.6 30.8 783.0 Polytus mellerborgii 24.2 24.5 22.6 28.7 827.0 Metamasius sp. 21.9 25.6 20.9 31.6 770.0 HQ883527 Anthribidae sp. 18.1 28.7 20.5 32.7 790.0 Values shown are in percentage; the column that corresponds to Total represents the length of every sequence.

1.3.2 Genetic analysis in banana weevil species through COI mtDNA

1.3.2.1 Haplotype diversity

Mitochondrial Cytochrome Oxidase I have been proposed as the best source of genetic information for species identification (Hebert, Cywinska, Ball, & deWaard, 2003; A S Sequeira, Sijapati, Lanteri, & Roque Albelo, 2008; Simon et al., 1994), for that reason is a good source of information for difficult species like weevils due to their phenotypic plasticity. Additionally this mitochondrial region is subject to a high rate of nucleotide substitution, being an important source of information for species distribution, gene flow among populations and identification of species dispersal through haplotype verification (Hebert et al., 2003).

In the present study 661 nucleotides from COI mtDNA region were included in the analysis for 96 samples, nevertheless 655 were used as sites for alignment excluding all gaps in the sequences. Four species were considered for the analysis, 22 samples for Cosmopolites sordidus, 36 for Metamasius sp., 31 for Metamasius hemipterus and 7 for Polytus mellerborgii. A total of 23 haplotypes were identified, being M. hemipterus the species with the highest number of haplotypes (12); followed by Metamasius sp. with 8 haplotypes; P. mellerborgii with 2 haplotypes and C. sordidus with 1 haplotype (Table 6). In terms of diversity, M. hemipterus possess a high haplotype diversity (0.7849), which corresponds to the number of haplotypes identified for this species, additionally the segregating sites were 18, that means the number of nucleotide possible changes in all M. hemipterus sequences evaluated, and nucleotide diversity of 0.0069, indicating a few point mutations respect the length of the sequence.

37 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

For Metamasius hebetatus the haplotype diversity was 0.5158 and a nucleotide diversity of 0.00141 with 7 segregating sites, being this species the second more diverse in the study through COI mtDNA region. However for P. mellerborgii the indices of diversity are interesting considering the number of samples (7), where two haplotypes were identified giving a haplotype diversity of 0.5714, moreover the number of segregating sites were 10 corresponding the second more diverse nucleotide segregation in the study, and nucleotide diversity of 0.00881 that was the highest for the whole analysis (Table 6).

The total estimates for COI region corresponds to 23 haplotypes, 233 segregating sites, a haplotype diversity of 0.8585 and a nucleotide diversity of 0.14821. The INDEL event sites estimated were 5, with 6 INDEL haplotypes and a diversity of 0.282. Additionally the total number of invariable sites (monomorphic) was 422, the number of variable sites (polymorphic) was 233, with 231 parsimony informative sites, and the total number of mutations was 286 (Table 6).

Table 6. Haplotype diversity in weevil species for COI mtDNA gene

Haplotype Diversity in weevils identified using COI mtDNA region Species Municipality No. Specimens Haplotypes Haplotype Diversity Nucleotide Diversity Number of Segregating sites

C. sordidus Argelia - Obando 22 1 0 0 0 Yotoco - El cairo - Argelia - Roldanillo Metamasius sp. 36 8 0.5157 0.00141 7 - Caicedonia - Obando - Buga El Cairo - Argelia - M. hemipterus Sevilla - Cria - 31 12 0.7849 0.00703 18 B/ventura - Obando Palmira - P. mellerborgii 7 2 0.5714 0.00881 10 Caicedonia Total Data 96 23 0.8585 0.1482 233

Total number of data for 4 Weevil species related to COI mtDNA region Total Number of sites: 661 Sites excluding gaps: 655 Number of gaps: 6 Total number of mutations: 286

Total number of INDEL: 5 Monomorphic sites: 422 Polymorphic sites: 233 Parsimony Informative sites: 231

1.3.2.2 Haplotype Network

The network obtained using COI as a source of genetic information showed that M. hebetatus and M. hemipterus are the most diverse groups with four nodes each, where one of the nodes corresponding to the highest frequency of the haplotypes. The size of the nodes is relative to

Chapter 1 the number of individuals contained in each of them, in that sense C. sordidus, and M. hebetatus possess the largest frequency of haplotypes.

Figure 8. Haplotype network for weevil species using COI mtDNA

Cosmopolites sordidus

Polytus mellerborgii

Metamasius hemipterus Argelia

Yotoco

El Cairo Breeding B/ventura

Obando Metamasius sp. Sevilla Caicedonia Roldanillo Palmira Buga Network analysis in four weevil species. Every circle represents a specific haplotype and every color represents the origin of the sample (municipality).

M. hemipterus individuals are more equally distributed in the four haplotypes while P. mellerborgii has a 1:1 ratio of haplotypes. Ten municipalities and Breeding were the source of all weevil samples in different stages of development. Argelia municipality was the most frequent locality for C. sordidus and M. hebetatus, on the contrary Buenaventura was the less frequent municipality. The information found in COI mtDNA gene demonstrate, as was identified for 28S Ribosomal RNA, that M. hemipterus is an intermediate species that “connect” M.

39 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

hebetatus and C. sordidus. The species M. hebetatus was the widespread covering seven of the municipalities, being only one haplotype present in those areas (Fig. 8).

1.3.2.3 Genetic dissimilarity in weevil species

Dissimilarity analysis carried out with COI mtDNA gene comprises 661 sites in 96 individuals, generating a square matrix of 63,456 characters; the out-group employed for the analysis was Scarabaeus viettei under accession number GU305943. Nei genetic distance showed that C. sordidus and P mellerborgii are more related with a genetic distance of 0.007, followed by the distance between C. sordidus and M. hemipterus (0.019), and C. sordidus respect to M. hebetatus was (0.042) (Table 7). Using COI gene it can be identified the high relatedness between C. sordidus and P. mellerborgii, also the genetic distance found between M. hebetatus and M. hemipterus (0.070) was the higher in all species comparisons. These results look confusing, even if it’s considered that the two Metamasius species belong to the same genus. It would be expected the lowest genetic distance between species under the same genus, however every species has an independent events for adaptation, also consider the reproductive barriers in the species avoiding any kind of gene flow among closely related ones. Although the genetic similarity found between C. sordidus and P. mellerborgii does not mean any gene flow in the species, this results only considered 661 nucleotides as the case of mtDNA, and the number of characters involved in the analysis only is a small representation of the genetic variability that could be present in the species.

Table 7. Nei genetic distance for weevil species using COI mtDNA

Pairwise Population Matrix of Nei Genetic Distance

Scarabaeus viettei C. sordidus Metamasius sp. M. hemipterus P. mellerborgii GU305943.1 0.000 C. sordidus 0.042 0.000 Metamasius sp.

0.019 0.070 0.000 M. hemipterus

0.007 0.067 0.043 0.000 P. mellerborgii Scarabaeus viettei 1.366 1.353 1.366 1.397 0.000 GU305943.1

Chapter 1

Table 8. Nei genetic identity in weevil species for COI mtDNA

Pairwise Population Matrix of Nei Genetic Identity

Scarabaeus viettei C. sordidus Metamasius sp. M. hemipterus P. mellerborgii GU305943.1 1.000 C. sordidus 0.959 1.000 Metamasius sp. 0.981 0.933 1.000 M. hemipterus 0.993 0.935 0.957 1.000 P. mellerborgii Scarabaeus viettei 0.255 0.259 0.255 0.247 1.000 GU305943.1

Nei Genetic identity showed that C. sordidus and P. mellerborgii are closer (0.993) and M. hebetatus is distant to M. hemipterus (Table 8), indicating the correlation found in genetic distance previously mentioned. M. hebetatus was the most distant species in the analysis, and based on the haplotype network, the high frequency of the samples for this species are grouped in only one haplotype that is distant to other species, which means, the connection of the main haplotype of M. hebetatus respect to haplotypes from other species is mediated through intermediate haplotypes, this scenario can give rise a hypothesis that the main M. hebetatus haplotype, in certain sense, is divergent in nucleotide composition respect the other weevil species.

1.3.2.4 Principal Coordinate Analysis (PCoA)

For this analysis the species were treated as populations where C. sordidus was the population 1, M. hebetatus population 2, M. hemipterus population 3, P. mellerborgii population 4, and S. viettei (out-group) population 5. The PCoA analysis indicates, in dimensional space based on Cartesian Plane, the genetic distance between populations, where the axis 1 explained 94.60% of the genetic variability found in all populations, indicating that in only 1 axis almost all diversity is explained separating the five populations according with the level of dissimilarity. The axis two explains 3.46% with an accumulative percentage of 98.06, and the axis 3 explains 1.94% with an accumulative of 100%. Once the genetic variability is explained in three axes, population two (M. hebetatus) and population five (out-group) are the most differentiated ones, on the other hand, populations one (C. sordidus), three (M. hemipterus) and four (P. mellerborgii) are close to one another, being population tree and four the highest related populations (Fig. 9).

41 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 9. PCoA for weevil species using COI mtDNA

C. sordidus

Metamasius sp.

M. hemipterus

P. mellerborgii

Anthribidae Out-group

Principal Coordinate Analysis (PCoA) for weevil species represented in four populations, the fifth population corresponds to Scarabaeus viettei (out-group).

Respect to the whole set of samples, when are treated without any population assignment, a genetic dissimilarity analysis was carried out to identify how the clusters are formed, and to verify the genetic identity from every sample respect to others in the same species, this strategy is to avoid any bias respect to the information contained in every sequence analyzed. The plotting observed in the (Fig. 10) indicate how distant is M. hebetatus, clustering apart from the X axis (colored in red), while P. mellerborgii seems to be closer to the out-group, and C. sordidus and M. hemipterus are apart from each other. In general, this graph shows the distance between species and how different they are, also the compactness of every group. As it can be seen, the distance of the spheres within every group corresponds to the nucleotide

Chapter 1 substitutions identified, however this separation only occurs following the X axis, in this sense C. sordidus (in blue) has a scattered-like shape spheres, P. mellerborgii (in light green) and M. hemipterus (in dark green) have a more compact fashion, and Metamasius sp. (in yellow), again, scattered-like shape distribution (Fig 10).

Figure 10. Three-dimensional plot fo weevil genetic distance for COI mtDNA

S. viettei

Metamasius sp.

P. mellerborgii

M. hemipterus

C. sordidus

Genetic distance between weevil species represented in a three dimensional spatial plot for mtDNA. Every species is codified with a respective color.

Dissimilarity analysis obtained in Darwin software indicates that M. hebetatus is the most distant species; also the species distribution and samples along the branches represent the nucleotide substitution. M. hemipterus possess three branches sequences indicating three different nucleotide composition, although not differently enough among them (Fig 11).

43 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 11. Dissimilarity analysis in four weevil species using COI mtDNA

Metamasius hemipterus

Polytus mellerborgii

Cosmopolites sordidus

Metamasius sp.

Unrooted tree for dissimilarity analysis in four weevil species based on COI mtDNA. Every species is represented in a single color. Each sample corresponds to every small branches connected to the main ones.

Under this analysis COI gene has been consistent in species identification and diversity within the groups, except for C. sordidus which only one haplotype was identified. Four branches were built in the analysis and every one corresponds to every species and, as found with 28S Ribosomal DNA region, M. hebetatus possess the longest branch, C. sordidus has a unique branch with short and small ones representing every individual, M. hemipterus with some

Chapter 1 divergent sequences and P. mellerborgii with one short branch where all sequences emerge. This results also corroborates how consistent is the group M. hebetatus, considering the lack of information available for this group in databases. All DNA extracted using individual adults and larvae obtained through a breeding process were highly consistent in sequence information, and considering the different sources of DNA (adult or larvae) the variability is not enough to generate a different group (Fig. 11). Using the information from COI mtDNA, 28S rDNA, this group was identified as Metamasius hebetatus.

1.3.2.5 Maximum Likelihood analysis in Weevils

The phylogenetic analysis used to build a Maximum Likelihood tree was considering a Bootstrap of 1000 replicates based on Kimura 2 parameter model under a heuristic search with Maximum Parsimony for the initial tree. Ninety-six sequence samples were included and Scarabaeus viettei (Accession number GU305943) was employed as out-group. The Cytochrome Oxidase I sequence comprised 661 sites, however 655 were nucleotide positions and 6 were gaps. All external nodes were supported with 100% of probability separating the main clusters that corresponds to every species, the internal nodes were supported with 65% of probability and basically this number is due to low substitution rate among the individuals (Fig. 12).

The phylogenetic tree shows five well-differentiated clusters that correspond to every species analyzed, including the out-group. In the first node the cluster is composed for two branches that corresponds to Metamasius hemipterus and Cosmopolites sordidus with approximately 12% of genetic differentiation (scale not shown); the second node is composed for one branch that corresponds to M. hebetatus (Metamasius sp. in the tree); the third node possess the P. mellerborgii branch and the fourth node correspond to the branch of the out-group (Fig. 12).

45 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 12. Maximum likelihood analysis for four weevil species using COI mtDNA

Maximum Likelihood analysis for weevil species using COI mtDNA gene. Bootstrap tree represents every species with a particular color. Bootstrap values obtained for external nodes were 100%, bootstrap values for internal nodes were over 70% probability (data not shown).

The nucleotide composition for C. sordidus was basically composed by Adenine (A) and Thymine (T) in 60.4% and a Guanine (G) – Cytosine (C) content of 30.6%; for M. hemipterus the A-T content was 65.4% and a G-C content of 36.6%; for Metamasius sp. the A-T content

Chapter 1 was 65.2% and a G-C content of 34.8%; P. mellerborgii had an A-T content of 63.6% and a G-C content of 36.4% (Table 9). For the case of Transitions - Transversions, Transitions were more common representing 12.8% of G/A or A/G of the mutational events in average for all species, for T/C or C/T the mutational events were 12.8%. Respect to Transversions whether A/T, A/C, T/A, T/G, C/A, C/G, or G/T, C/C had the same percentage of 6.07.

Table 9. Nucleotide composition for COI mtDNA in weevil species

Species T(U) C A G Total C. sordidus 32.1 24.2 27.7 16.1 658.0 Metamasius sp. 35.4 18.7 29.6 16.3 658.0 M. hemipterus 35.8 19.3 27.5 17.4 657.0 Polytus mellerborgii 34.7 20.5 29.0 15.8 658.0 Columns were nucleotide letters are headers contains values in percentage, the column that corresponds to Total header represent the length of every sequence.

1.3.2.6 Amino Acid composition for COI mtDNA

Due to COI mtDNA gene sequence corresponds to a coding Mitochondrial gene, an amino acid sequence was obtained for every species to identify if there were changes in amino acid residues composition respect to the rate of nucleotide substitution found in nucleotide sequences. Also to verify how conserved is the amino acid sequence for COI mtDNA in banana weevil species analyzed (Table 10).

Table 10. Amino acid composition for COI mtDNA in banana weevil species

Species Ala Cys Asp Glu Phe Gly His Ile Lys Leu Met Asn Pro Gln Arg Ser Thr Val Trp Tyr Total

Metamasius 9.59 0.00 3.65 0.91 6.39 9.59 1.83 10.05 0.46 15.53 5.94 5.02 5.94 0.91 2.28 7.31 5.94 4.57 2.28 1.83 219.00 sp.

C. sordidus 7.62 0.00 3.14 0.90 6.28 9.87 1.79 9.87 0.90 14.80 6.28 4.48 6.28 0.90 2.24 9.42 6.28 4.93 2.24 1.79 223.00

M. hemipterus 9.13 0.00 3.65 0.91 6.39 9.59 1.83 11.42 0.46 14.16 5.94 4.57 5.94 0.91 2.28 9.13 5.02 4.57 2.28 1.83 219.00 P. 8.26 0.00 3.67 0.92 5.96 9.63 1.83 9.63 0.46 15.60 6.42 4.59 5.96 0.92 2.29 9.63 5.96 4.13 2.29 1.83 218.00 mellerborgii AY131107 7.73 0.00 3.86 0.97 6.76 9.18 1.93 12.08 0.48 14.01 5.80 5.31 6.76 0.97 2.42 8.21 4.35 4.83 2.42 1.93 207.00

For this analysis one haplotype from every species was chosen to compare the codon composition and subsequent translation into amino acid, this process was made using a reference sequence reported by (Jordal et al., 2011) for Cosmopolites sordidus under accession

47 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

number AY131107. The parameters employed to identify amino acid composition from 661 nucleotide positions obtained for COI gene in the present study, were using Invertebrate Genetic Code and the reading frame was the third nucleotide position, which means that from the DNA sequence obtained, the first nucleotide do not necessarily corresponds to the first nucleotide of the first codon for the sequence, to corroborate this, a search in NCBI database was employed to identify the DNA COI gene sequence, messenger RNA (mRNA) and Coding DNA Sequence (CDS). To do this the reference sequence AY131107 was used as a source for this information, then a BLAST was carried out with the primers used to amplify the COI fragment of the present study, once the primers were attached to the reference sequence, this mRNA was exported and used as a template to identify the amino acid sequence translated for every one o the species of this study.

Two hundred and twenty three codons were identified from 671 nucleotides sequence for C. sordidus, 219 amino acid residues for M. hebetatus, 219 for M. hemipterus and 218 for P. mellerborgii. All amino acid residues, less Cysteine (Cys), were present in the sequences. The less frequent amino acids were Lysine (Lys), Glutamine (Glu) and Glycine (Gln) (< 1%), whereas Histidine (His), Tyrosine (Tyr), Arginine (Arg), Tryptophan (Trp), Aspartic acid (Asp), Valine (Val), Asparagine (Asn), Methionine (Met), Proline (Pro), Threonine (Thr), Phenylalanine (Phe), Serine (Ser), Alanine (Ala) and Glycine (Gly) were between 1% and 10% of frequency, and Isoleucine (Ile), and Leucine (Leu) had a frequency >10% (Table 11).

Despite the similar frequency of amino acid composition for every species analyzed, the organization of these amino acids along the sequence changes significantly. A multiple sequence alignment was carried out to identify the amino acid composition between species. Two hundred twenty four amino acids were aligned, where 174 (79.1%) sites do not change position in the sequence and 50 sites does (20.9%). Considering that COI is a coding sequence region and four different species were analyzed, this region is considerably conserved (Fig. 13).

Chapter 1

Figure 13. Amino acid sequences analyzed in four weevil species

Amino acid sequences obtained for four weevil species and one for reference sequence AY131107. Number 1 corresponds to Polytus mellerborgii, number 2 Metamasius hemipterus, number 3 Metamasius hebetatus, number 4 Cosmopolites sordidus and number 5 Cosmopolites sordidus reference sequence AY131107. Changes in amino acid residues to every sequence are highlighted in color. The thick green bar line represents consensus sequence and over it amino acid letter frequency according with its size.

The sequence number one corresponds to P. mellerborgii, sequence number two M. hemipterus, sequence three Metamasius sp., sequence four C. sordidus and sequence five reference AY131107. It can be identified, however, that P. mellerborgii has a codon insertion in the position number ten that codifies for Serine (S) and is the sequence with more number of changes among the species. On the other hand Metamasius sp. and M. hemipterus has the same amino acid sequence, even the same changes occur respect to other species. This indicates that basically all haplotypes identified within species corresponds to nucleotide substitution in third codon position, and almost all changes are synonymous where there are no amino acid changes in the sequence.

A maximum likelihood analysis was developed using amino acid sequences to identify the accuracy and resolution provided by this kind of characters in species discrimination. This analysis was to test the relatedness of the amino acid sequences from COI gene and possibly species mixture, however an accurate species separation was obtained, indicating that even COI amino acid sequence can discriminate between species and how conserved is this region among species and the accuracy as a source of genetic information for species identification,

49 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

despite the high rate of nucleotide substitution, the differences in haplotypes is not high enough to generate divergent sequences within species (Fig. 14).

This analysis generates four main nodes and five branches, similar to the clustering obtained using nucleotide information. In the first node the out-group Scarabaeus viettei is separated forming a cluster apart from banana weevils, the second node comprises all weevil species were P. mellerborgii is the more distant due to high difference in amino acid composition, the third node includes M. hemipterus, C. sordidus and M. hebetatus being the latter a separate group but with low genetic distance respect to C. sordidus and M. hemipterus cluster. This last cluster includes C. sordidus and M. hemipterus, being C. sordidus more divergent in the sequence due to this species has 4 more amino acid residues respect to the other sequences (Fig 14).

1.3.2.7 Phylogenetic analysis in weevil species

For phylogenetic analysis 28S Ribosomal RNA region and COI mtDNA gene were fused to generate a data matrix of approximately 1,500 characters for every sample, additionally sequences from Jordal et al. (2011) from 7 family taxa were included in the analysis (Accession numbers are indicated in the phylogenetic tree). This phylogenetic analysis was carried out using the closest species of Dryophthorinae subfamily, where weevils are classified, and also considering some of them with parental care behavior; this conditions were tanking into account to identify if could be possible such a behavior in weevil species studied, that is because these species are successful and very invasive in plantain and banana crops, for that reason this analysis was basically to verify how distant are those taxa with parental care behavior respect to weevil species analyzed in the present study (Fig. 15).

Phylogenetic analysis tree was built considering a Bootstrap of 1000 replicates based on Kimura 2 parameter model under a heuristic search considering Maximum Parsimony for the initial tree. This analysis corroborates that all species included in the present study plus the species reported by (Jordal et al., 2011) such as Cosmopolites sordidus, Dynamis borassi, Rhynchophorus palmarum, Sitophilus oryzae, Cactophagus spinolae and Sphenophorus

Chapter 1 venatus, clustered together in a remarkable cluster of Dryophthorinae subfamily, all of them with wood boring behavior, but with no parental care behavior. Figure 14. Maximum likelihood analysis in weevil species for amino acid composition

13.M. hemipterus AY131107 45.M. hemipterus 44.M. hemipterus 36.M. hemipterus 35.M. hemipterus 99 34.M. hemipterus Metamasius hemipterus 32.M. hemipterus 30.M. hemipterus 22.M. hemipterus 46 19.M. hemipterus 15.M. hemipterus 14.M. hemipterus 11.1 C. sordidus

72 3.1 C. sordidus Cosmopolites sordidus 99 AY131111 1.1 Metamasius sp. 18.Metamasius sp. 23.Metamasius sp. Metamasius sp. 96 25.Metamasius sp. 1.Metamasius sp. 28.1 Metamasius sp. 59.Polytus mellerborgii 58.Polytus mellerborgii 60.Polytus mellerborbii

62.Polytus mellerborgii Polytus mellerborgii 95 64.Polytus mellerborgii 50.Polytus mellerborgii 65.Polytus mellerborgii

Scarabaeus viettei Outgroup

0.010 Maximum Likelihood analysis for weevil species using COI mtDNA amino acid residues sequences. Bootstrap tree represents every species with a particular color. Bootstrap values obtained for species nodes ranged form 95% to 99%.

However the closest group to Dryophthorinae, composed by Cossoninae and Molytinae families, have contrasting behavior, for the first family, Cossoninae, the species Araucarius sp. possess parental care behavior whereas the species of Molytinae does not (Fig. 15).

51 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 15. Phylogenetic inference for weevil species using concatenated analysis including 28S and COI mtDNA gene

Maximum Likelihood analysis considering 28S rDNA and COI mtDNA gene. Highlighted in green, weevil samples analyzed in the present study.

Chapter 1

This phylogenetic analysis can give rise some questions about if there could be any parental care behavior in banana weevil species, scoped in the present study, that could explain the success of this species populations in plantain and banana crops. Unfortunately the breeding for banana weevil species is very difficult to verify such a behavior, and more studies regarded to biology and ecology of these species is necessary, considering the limitations for plantain and banana production in different areas of the world caused by banana weevils.

All the families and subfamilies analyzed in its phylogenetic history shows that Curculionidae order is a very difficult group, and this condition could be identified in the Maximum Likelihood tree, where there is no consensus organization of species in their respective families or subfamilies, however the number of characters analyzed here are not enough to solve the monophyly for each taxa, but in the paper published by (Jordal et al., 2011), a number of 128 morphological data and four genetic and genomic regions were analyzed, generating a phylogenetic hypotheses for boring weevils and parental care behavior, separating clearly all families and subfamilies indicating the importance of integrated data (morphological and molecular) for phylogenetic inferences.

53 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

1.4 Discussion

The understanding of genetic diversity and gene flow among banana weevil populations could derive in strategies for population dynamics control of these species in banana and plantain crops. In the current scenario the low genetic diversity found in species such as C. sordidus, P. mellerborgii and M. hemipterus across Valle del Cauca municipalities, is an advantage for biological control purposes due to the susceptibility faced by homogeneous populations, where a few alleles are available to overcome a parasitic event driving, probably, an easier way to control weevil populations at least in the surveyed ares. Also haplotype identification is a useful tool to determine how variable and limited are weevil’s dwelling in a particular area, possible weevil dispersal under a particular environmental conditions, and human impact respect to weevil transportation, through contaminated banana and plantain seeds. Additionally rain and drought fluctuations can affect weevil reproduction or synchrony of species giving them advantages in mating and egg lying under favorable conditions. This inference was made from certain behavior found in field observations between October and December 2015 in banana and plantain crops, where under drought conditions there were no presence of adult individuals, instead pupa stage of development was found, mainly for Metamasius hemipterus.

All farms visited during that period of time showed basically the same stage of development for banana weevil species, commonly found in banana and plantain fallen stems in decomposition process. According to IDEAM Colombia on that period of time there was precipitation deficit from 25% to 60%, causing a latency state of weevil species (C. S. Gold et al., 2003). After a rainy period, approximately 6 months later, where precipitations increased more than 50% (IDEAM, 2017), the presence of adult individuals rose up and weevils from all stages of development were found in the same areas. Gold et al. (2002) evaluating banana weevil fluctuations respect to rain and drought found a decrease in number of individuals in one year period from 13,400 individuals/ha to 11,400/ha, however in posterior studies carried out by Gold et al. (2003) the number of individuals were reduced by 42% and weevil populations changed in the first 6 months in which rainfall deceased from 635 mm to 245 mm. However the reported precipitations for sampled areas in Valle del Cauca ranged from 1000mm to 1500mm annually (IDEAM, 2017), higher than reported by Gold et al (2003), situation that could indicate the increase of weevil populations favored by humid conditions.

Chapter 1

1.4.1 Haplotype distribution, dispersal and movement

Haplotype distribution of weevils found in the present study can give raise a question and is if weevil dispersal is high or if there is another way for weevil dispersal. Species like Metamasius hebetatus had the same haplotype distributed over 7 municipalities in the north side of Valle del Cauca department, however for Metamasius hemipterus the distribution covers 6 municipalities, even distant ones with a biogeographic barrier, as the case of western range, that splits the north side of Valle del Cauca and Buenaventura in the Pacific coast. In the case of Cosmopolites sordidus the same haplotype was found in Argelia and Obando, both municipalities in the north side of Valle del Cauca, and for Polytus mellerborgii the distribution covered Palmira (center of Valle del Cauca) and Caicedonia (north of Valle del Cauca). Is important to highlight some bias in the results due to samples available for the analysis, specially for P. mellerborgii and C. sordidus, that means the number of individuals per species sequenced do not covered the whole areas surveyed. Nevertheless this intriguing distribution of weevil species (basically M. hemipterus and M. hebetatus), based on haplotypes for 28S rDNA and COI mtDNA gene, over distant municipalities increases even when weevil dispersal have been reported as very limited and slow (Carval, Perrin, Duyck, & Tixier, 2015; C. S. Gold et al., 2003). Also studies carried out with marked weevils showed that after 10 weeks of released 60% of the weevils moved >10 m, later after 6 months of released the recaptured weevils were found within 5m and 39% moved 6-15 m and only 3% moved more than 25m, indicating a sedentary behavior of these organisms, however soil moisture could stimulates activity and movement, additionally also was found that females had a tendency to be more active than males moving long distances and quicker during the moment of release (C. S. Gold et al., 2003). Despite of these findings, it does not solve the dispersal dilemma of haplotypes distribution in distant localities surveyed in the present study.

Other studies were focused in flight behavior where no or seldom fight has been identified (Cardenas & Arango, 1986; C. Gold et al., 2002; C. S. Gold et al., 2003; Nonveiller, 1965; Sponagel, FJ, & Cribas, 1995; Wardlaw, 1972) indicating that banana weevils are relatively sedentary and dispersal through crawling or flight is very limited, additionally the movements account basically in local or neighboring banana and plantain stands (C. S. Gold et al., 2003). Due to this limited movement and all the results obtained in previous studies, where weevil banana behavior respect to movement has demonstrated the sedentary of these species, is possible to consider that weevil banana dispersal found in the present study could be directly

55 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

related with human activities of seed dispersal already contaminated with banana weevil eggs or larvae. This proposal has been demonstrated in previous studies (Cardenas & Arango, 1986; Castrillon, 2000; Jones, 1986; Pinese & Piper, 1994), indicating infesting plant material containing adults in leaf sheaths and weevils in immature stages of development in the stem a corm. Additionally (Abera, 1999) reported 0.4-1.5 eggs per plat for peppers and suckers, suggesting the importance of use clean plant material to control weevil population and dispersal (C. S. Gold et al., 2003).

1.4.2 Genetic diversity

Two Loci were evaluated in the present study, one from nuclear origin, as the case of 28S Ribosomal RNA, that has demonstrated high levels of genetic variability (Bae, Robbins, & Szalanski, 2010; Gillespie et al., 2005; Gottschling & Plötner, 2004; Petrov et al., 2014), and was selected as a possible source of genetic variation within banana weevil species and to identify possible genetic differentiation among weevil populations respect the origin of the samples. The second Loci comprise a fragment of the Mitochondrial gene Cytochrome Oxidase I, that has been considered as a barcode sequence in several studies (Díaz de Astarloa & Mabragaña, n.d.; González, 2010; Hebert et al., 2003; Lanteri, 2007; Mardulyn & Whitfield, 1999; Romero & Ramirez, 2011; A S Sequeira et al., 2008; Sharma & Kobayashi, 2014; Simon et al., 1994), and also as a source of genetic variation. The employment of COI mtDNA gene was directed to verify species assignation from all specimens collected to proceed into a correct classification in the correspondent species.

A total of 857 nucleotide positions were evaluated for 94 weevil individuals belonging to 4 species. Using 28S Ribosomal DNA region, 16 sequences were for Cosmopolites sordidus, 33 for Metamasius hemipterus, 10 for Polytus mellerborgii, and 35 for Metamasius hebetatus. For COI mtDNA gene, 661 nucleotide positions and amino acid sequence for gene partial sequencing of COI mtDNA included 96 weevil individuals belonging to 4 species, being 22 individuals from C. sordidus, 36 M. hebetatus, 31 M. hemipterus, and 7 P. mellerborgii. The two Loci showed well-differentiated species with low genetic diversity among them, indicating a correlation found with haplotype diversity and network analysis. Respect to 28S rDNA C. sordidus showed higher haplotype diversity (0.125) compared to COI mtDNA (0.00), but the

Chapter 1 other species does not; instead for M. hemipterus, M. hebetatus, and P. mellerborgii for COI mtDNA the haplotype diversity was higher compared to 28S rDNA, obtaining values of 0.78, 0.51 and 0.57 respectively, being P. mellerborgii the species more diverse in terms of haplotype diversity.

These results also correlate with additional variables found in the analysis. For C. sordidus the number of segregating sites were 7 for 28S rDNA, however the nucleotide diversity (Nd) is very low, because only 7 from 661 positions are different among the samples evaluated, indicating that, despite the haplotype diversity (Hd) for C. sordidus is relatively high (0.125) there are few point mutations among the sequences. This condition was also found for M. hebetatus with a nucleotide diversity of (0.001) and a haplotype diversity of 0.51, M. hemipterus showed (Nd=0.006, Hd=0.78) and P. mellerborgii (Nd=0.008, Hd=0.57). In previous studies (Rodriguero, Lanteri, & Confalonieri, 2010) found low values of haplotype diversity in ITS region respect to COI gene, Graaf (2006) evaluated C. sordidus populations in South Africa using AFLP marker and identified high genetic differences comparing South Coastal, North Coast and Tzannen populations, indicating significant differences of 51.59% amongst populations and 48.41% within populations, however a low within-population diversity was found in this study, respect to small populations, indicating the possibility of a founder effect where the current population could be introduced with small number of individuals genetically related into a new area, also this author argued another hypothesis that comprises a selective pressure driven by human impact due to excessive use of chemical control that can contribute to decrease the genetic diversity in that populations. This condition could be infer from low genetic diverse populations and species found in the present study, moreover a possible low number of alleles in the populations could be related to those that, in a certain way, had acquire a kind of adaptation to the habitat that could drive in the increasing of such allele in plantains and banana stands.

Another perspective consider the movements carried out for weevils under specific conditions, Carval et al. (2015) suggest that individuals may perceive conspecific densities and patch quality indicating movement for fitness dependent, additionally Ruxton & Rohani (1998) showed that banana weevils movement in a meta-population depends not only of the local density, but also density of patches where dispersing of individuals could be settle, also (Carval et al., 2015) suggest that banana weevils movement could be affected by a homogeneous environment like those provided by banana crops, leading to the individuals remain in a certain place generating clustered populations. Considering the perspectives previously discussed, both of them drives

57 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

to explain why weevil populations are not diverse, however the case, in the present study the low genetic variability found in weevil species indicate the possibility that human activities are favoring the frequency of few alleles in the populations, moreover weevil dispersal carried out by contaminated seeds can spread even more such alleles, that in turn seems to have a possible adaptation to environmental conditions making them more difficult to control.

If behavioral reproduction is taking into account, is probable to have low genetic diversity. Regarded to oviposition under controlled conditions this behavior range from 1-4 eggs/week and 10-270 in the lifetime of the weevil, also seasonal effects can contribute to decrease the number of eggs lying, where the number of eggs could range from 7.8/female/month in rainy season to 0.4 eggs/female/month in dry season (C. S. Gold et al., 2003). These results also correspond to field observations in the present study, where the rate of weevils in dry seasons was very low compared to the sampling carried out in wet and humid seasons.

1.4.3 Amino acid composition in weevil species for COI mtDNA

The nucleotide composition for C. sordidus was composed basically by Adenine (A) and Thymine (T) in 60.4% and a Guanine (G) – Cytosine (C) content with 30.6%; for M. hemipterus the A-T content was 65.4% and a G-C content of 36.6%; for M. hebetatus A-T content was 65.2% and a G-C content of 34.8%; P. mellerborgii had an A-T content of 63.6% and a G-C content of 36.4%. Respect to Transversions – Transitions, Transitions were more common representing 12.8%, for G/A or A/G substitutions, of the mutational events in average for all species; for T/C or C/T the mutational events were 12.8%. For Transversions whether, A/T, A/C, T/A, T/G, C/A, C/G, or G/T, C/C had the same percentage of 6.07. This similar nucleotide composition was found by Duque (2012) (data not published) where species of banana weevil were collected in several departments from Colombia showing no variation in nucleotide composition and with a considerable A-T richness. Additionally DeSalle, Freedman, Prager, & Wilson, (1987); Simon et al., (1994); Wahlberg & Zimmermann, (2000) proposed that a typical mtDNA of insects is composed basically of A-T nucleotides located mainly in third codon position.

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The fragment amplified for COI mtDNA in all banana weevil species corresponded to a segment of coding region. For C. sordidus the sequence length obtained was 671 nucleotides corresponding to 223 codons and the same number of amino acid residues; M. hemipterus had 219 codons corresponding to 219 amino acid residues; M. hebetatus 219 amino acid residues, and P. mellerborgii with 218 amino acid residues. The difference in size basically is related to C. sordidus with four additional codons and, consequently, four amino acid residues longer. The amino acid composition for weevil species evaluated under COI mtDNA partial gene sequence comprises 19 of the 20 amino acids from the genetic code, where Cysteine (Cys) was not present in the coding region, Lysine (Lys) was the less frequent ranging from 0.46% in M. hebetatus to 0.90% in C. sordidus, and Leucine (Leu) was the most frequent amino acid residue that ranges from 15.60% in P. mellerborgii to 14.16% in M. hemipterus.

For COI mtDNA gene region sequenced, C. sordidus do not show any change in nucleotide composition among samples, conversely M. hebetatus showed 8 nucleotide changes among samples but all in third nucleotide position of the codon, being synonymous mutations; for M. hemipterus 12 nucleotide changes were identified, however two of the sequences were removed from amino acid analysis due to inconsistences of nucleotide composition, all mutations identified in this species occurred basically in the third nucleotide position respect to codons. But for the sample 35 (M. hemipterus), collected in Sevilla municipality in larvae stage of development, one point mutation identified was in the first codon position, however with no change of amino acid residue. This mutation was located in the nucleotide number 50 of the sequence amplified in the present study; the frequent codon composition found, in that particular place, for all M. hemipterus samples was CUA compared to the mutational event UUA, these two codons codify for the same amino acid (Leucine). Another important change was identified in the sample 34 for M. hemipterus, collected also in Sevilla in larval stage of development, this point mutation involves the second nucleotide of codon position that codifies for Arginine CGA, but this sample, instead, possess the codon CAA that codifies for Glycine, being so a transitional mutation event where G changes for A.

Despite the number of point mutations identified in this population Rodriguero et al., (2010) found considerable events of substitution for COI mtDNA gene in weevils, Wahlberg & Zimmermann (2000) found high variation in nucleotide composition for COI mtDNA region in Lepidoptera, reporting that this point mutations were found basically in third codon positions and arguing that is a typical event for protein coding regions. Farrell et al. (2001) reported a

59 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

tendency in decreasing evolution from 28S, COI, the enolases, EF-1 alpha and 18S for Curculionidae, in this respect COI is considered to have a high rate of evolution indicating considerable point mutations accumulated over time; Jordal et al. (2011) reported COI mtDNA gene as the most variable in a set of five genes evaluated in a phylogenetic analysis in Curculionidae. These authors also, after a comparison of proportions for gene divergence, found that COI displayed the highest ratio of first and second codon position substitution to third codon position substitution.

1.4.4 Phylogenetic analysis

Phylogenetic analysis were carried out with the sequences obtained in the present study for 4 weevil banana species and sequences reported by Jordal et al. (2011), in that study the authors estimated the time of origin for Curculionidae in various subfamily groups, where Dryophthorinae subfamily was included, also indicates the subsociality behavior of some groups in boring weevil species. This additional analysis, including DNA sequences from boring weevil species, was considered in the present study due to the possible relationship that could exist between banana weevil species and other species identified with parental care behavior; in this sense, it was considered important to evaluate the closeness of banana weevil species respect to those with subsocial behavior to understand why banana weevils are so successful despite the low diversity found in Mitochondrial and Nuclear genes.

The phylogenetic tree built for this analysis considered a bootstrap of 1000 replicates based on Kimura 2 parameter model under a heuristic model considering Maximum Parsimony. This analysis showed that C. sordidus, M. hemipterus, M. hebetatus and P. mellerborgii are located in Dryophthorinae cluster and close to Cossoninae family where species such as Araucarius sp. possess parental care behavior. However the species Dynamis borassi, Rhynchophorus palmarum, Sitophilus oryzae, Cactophagus spinolae and Sphenophorus venatus, which compose the Dryophthorinae cluster, does not show parental care (Jordal et al. 2011), also these authors reported to Dryophthorinae as a monophyletic family, that is consistent with the results obtained here, also in the present study only 28S and COI sequences were used for both, banana weevils sequenced in this study and the sequences reported by Jordal et al.

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(2011), showing the Dryophthorinae bfamily as the only monophyletic group compared to the other subfamilies.

Despite that Jordal et al. (2011) do not report parental care behavior in non of the Dryophthorinae species evaluated, Delattre (1980); Ittyeipe (1986); Treverrow & Bedding (1993); Aranzazu et al. (2000) reported certain behavior of banana weevil that comprises nocturnal activity, negative phototropism, strong hygrotrophism and gregariousness, this last behavior indicates that organisms live in groups under overlapping generations that could favor reproduction and could increase the probability of success for the offspring. One of the important characters found in parental care behavior of some weevils reported by Jordal et al. (2011), is that the adults excavates galleries for egg laying, and both parents take care for their offspring, similar behavior respect to excavating, has been reported by Silva & Fancelli, (1998); N Treverrow, Peasley, & Ireland, (1992), where adults of banana weevils are associated with banana mat, around the roots and occasionally in larval galleries. However laying eggs in corms, and other plants or plantain areas has been reported (C. S. Gold et al., 2003), additionally in the present study, excavation behavior has been identified for M. hemipterus under breeding conditions using sugar cane as a source of food and shelter (data not shown). This behavior is still unknown for banana weevils and the phylogenetic hypothesis provided by Jordal et al (2011) do not provide sufficient resolution to infer the direction of parental care in some groups, moreover the phylogenetic analysis carried out by these authors indicates multiple origins of subsocial breeding systems associated with wood boring habit.

61 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

1.5 Conclusions

• Genetic diversity in banana weevils indicates an apparent lose of diversity for the populations surveyed, however still is unclear if this low diversity found in big populations, mainly in C. sordidus, is a consequence of human impact that could be leading to genetic erosion, and if the low allele frequencies identified in different municipalities with high population densities reflects a possible resistance of these organisms to chemical control commonly used in banana and plantain stands.

• Haplotype distribution for banana weevil species in Valle del Cauca is probably due to human activities, basically in weevil dispersal across the department through contaminated seeds with weevil eggs or larvae, indicating that the same haplotype (M. hebetatus and M. hemipterus) was present in 70% and 60%, respectively, on the sampled areas, this scenario has favored the negative impact of these species in banana and plantain production, under this conditions more regulations for seed dissemination are required to control weevil populations and probably dispersal of possible resistant alleles that could be present in these species.

• The current scenario for banana weevil species is an indicator of a possible genetic drift for the populations surveyed in the present study, also the apparent genetic erosion found here could drive to infer that human selection on banana weevils is leading to these species into a faster process of evolution, where more adaptive organisms could appear over time. However the inclusion of conserved genomic and mitochondrial regions in the analysis, could lead to misinterpretation of the results, nevertheless human impacts in these populations seems generating a selective process in weevil species.

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2. Chapter 2

Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae) Associated to Plantain and Banana Crops in Valle del Cauca

Chapter 2

2.1. Abstract

Entomopathogenic nematodes are cylindrical and microscopic organisms that are obligate parasites of insects. These nematodes are classified into two families, Steinernematidae and Heterorhabditidae, where the former possess 96 species already described while for the second 16 species compose the family. Together with their symbiotic bacteria, Xenorhabdus for Steinernematidae and Photorhabdus for Heterorhabditidae, are lethal symbionts with a high potential for biological control of crop pests. However the phylogenetic understanding of these organisms is difficult due to high variation at morphological and molecular level. In the present study a survey was carried out across Valle del Cauca department, where 12 municipalities (the same surveyed for banana weevil species) were included and 495 soil samples were evaluated. The number of positive samples for entomopathogenic nematodes (EPN) was 14 (2.8%). Ten isolates for Steinernematids and four for Heterorhabditids were recovered and evaluated through molecular analysis. DNA sequencing for ITS rDNA (Internal Transcribed Spacer) and LSU rDNA (Large Ribosomal Subunit) showed low genetic variability. From 910 nucleotide site positions for ITS region, 374 nucleotides were polymorphic and three haplotypes were identified. Additionally three species could be identified through these sequences; for Steinernematidae family, Steinernema carpocapsae was the only species found and for Heterorhabditids, Heterorhabditis sp. and H. bacteriophora, were identified. On the other hand for LSU rDNA region 905 nucleotide positions were evaluated, from which 285 showed polymorphism and three haplotypes were identified for both Steinernematids and Heterorhabditids. Also three species, S. carpocapsae, H. bacteriophora and H. marelatus, were identified in all isolates. However contrasting results were identified among these two ribosomal sequence regions respect to isolate UNPS16, which through ITS rDNA was identified as H. bacteriophora and with LSU rDNA was identified as H. marelatus, reflecting the complexity for EPN taxonomy. Nevertheless after a phylogenetic analysis carried out with a concatenated analysis for ITS rDNA and LSU rDNA, UNPS16 was identified as H. bacteriophora. The molecular characterization of EPN in the present study indicates the genetic diversity and complexity of these organisms, also their potential as a source for biological control of insect pests, as banana weevil complex species.

Keywords: Entomopathogenic Nematodes, Ribosomal DNA, Biological Control, Haplotype, Genetic Diversity, Phylogeny.

77 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

2.2. Resumen

Los nematodos entomopatógenos son organismos microscópicos que presentan una estructura corporal cilíndrica en forma de gusano y son parásitos obligados de los insectos. Estos nematodos están clasificados en dos familias, Steinernematidae y Heterorhabditidae, donde los primeros poseen 96 especies ya descritas y para los segundos 16 especies componen la familia. Junto con sus bacterias simbióticas, Xenorhabdus para Steinernematidae y Photorhabdus para Heterorhabditidae, son simbiontes letales con potencial biológico para el control de pestes. Sin embargo el entendimiento de su naturaleza y la filogenia de estos organismos ha presentado dificultades debido a la considerable variación morfológica y molecular que presentan. En este estudio se llevó a cabo una evaluación en 12 municipios del departamento del Valle del Cauca, donde 495 muestras de suelo fueron analizadas para detección de NEP, sin embargo 14 de ellas (2.8%) fueron positivas para nematodos entomopatógenos. Diez aislamientos para Steinernematidae y cuatro para Heterorhabditidae fueron obtenidos y analizados por métodos moleculares. La secuenciación de ADN ribosomal para ITS rDNA (Internal Transcribed Spacer) y la región LSU (Large Ribosomal Subunit) mostraron baja variabilidad genética a nivel intraespecífico. A partir de 910 posiciones nucleotídicas para ITS, 374 fueron polimórficas y tres haplotipos fueron identificados. Adicionalmente tres especies se hallaron por medio de estas secuencias, para Steinernematidae Steinernema carpocapsae fue la única especie y para Heterorhabditidae Heterorhabditis sp. y H. Bacteriophora fueron identificados. Por otra parte para la región LSU 905 posiciones nucleotídicas fueron evaluadas, de las cuales 285 presentaron variación polimórfica y se hallaron tres haplotipos. Tres especies, S. carpocapsae, H. bacteriophora y H. marelatus fueron identificadas para esta región. Sin embargo resultados contrastantes entre estas dos regiones ribosomales se observaron respecto al asilamiento UNPS16, el cual fue identificado como H. bacteriophora para ITS y H. marelatus para LSU, esto refleja la complejidad en la taxonomía de NEP. No obstante después de un análisis filogenético concatenado fara ITS y LSU, el aislamiento UNPS16 fue identificado como H. bacteriophora. La caracterización molecular de NEP en el presente estudio indica la diversidad genética y la complejidad de estos organismos, también su potencial para ser empleados como controladores biológicos en insectos peste como el complejo de especies del picudo del banano. Palabras clave: Nematodos entomopatógenos, ADN Ribosomal, Control Biológico, Haplotipo, Diversidad Genética, Filogenia.

78 Chapter 2

2.3. Introduction

Entomopathogenic nematodes (EPN) (Rhabditida: Steinernematidae and Heterorhabditidae) are cylindrical non-segmented organisms, that are free living or parasitic of arthropods; this condition makes the nematodes a source for biological control, especially the species from Steinernematidae and Heterorhabditidae families (Shapiroilan et al., 2002). Symbiotic associations of these nematodes with specific bacteria (Xenorhabdus spp. associated with Steinernema, and Photorhabdus spp. associated with Heterorhabditis) facilitate the pathogenicity. Although some axenic nematodes species can cause host death occasionally, associations of nematodes and bacteria are necessary for a high level of pathogenicity, taking into account that bacteria cannot penetrate into the host by itself and requires the nematodes to get into the host, at the same time nematodes are benefited by bacteria because they create optimal conditions for nematodes reproduction into the host cadaver (Grewal et al., 2001).

This symbiotic association had been identified as a potential source for biological control using both Steinernema and/or Heterorhabditis species (Ansari, Tirry, & Moens, 2005; Bruck & Walton, 2007; Corley, Villacide, & Liebhold, 2014; Fenton, Norman, Fairbairn, & Hudson, 2001; Hazir, Kaya, Stock, & Keskin, 2004; Karagoz, Gulcu, Hazir, Kaya, & Hazir, 2009; Kiewnick, S., & Sikora, 2006; Protection, 2006; Shapiroilan et al., 2002), and this association had give rise to a new method, probably more efficient for biological control, using entomopathogenic toxins produced by symbiotic bacteria of EPN, indicating the possibility to employ genetic engineering for mass production of such a toxins from Photorhabdus spp. and Xenorhabdus spp. (Adams et al., 2006; N. . Boemare, 2002; Brown et al., 2006; Brown, Cao, Hines, Akhurst, & East, 2004; Han & Ehlers, 2001; Hu, Li, Li, Webster, & Chen, 2006; Jin, Zeng, Dong, & Zhang, 2014; Keun, Jun, Yeon, & Sun, 2000; Kumari, Mahapatro, Banerjee, & Sarin, 2015; Shrestha et al., 2011; Waterfield, Ciche, & Clarke, 2009). Despite of the applicability and use of EPN and its symbiotic bacteria, phylogenetic issues and organism’s classifications are still undergoing. However Steinernematids had been identified as the most specious family respect to Heterorhabditids and this feature could be related to hermaphroditic nature of Heterorhabditids in the first generation, this condition is perhaps an environmental adaptation to maximize the reproductive opportunities avoiding the requirement of at least two adults of opposite sex to be involved (Hunt, Nguyen, et al., 2016). Steinernema spp. seems to be exclusively amphimictic, however S. hermaphroditum is apparently occurring in hermaphroditism (S. Stock, Griffin, & Chaerani, 2004). Another important situation in this

79 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control group of organisms is the morphological complexity that they carry since the most traditional parameters are highly variable for both EPN families, this morphological characters are subject of many changes driving to interpretation problems basically in three-dimensional structures due to angle view and interpretational skills of the observer (Hunt et al., 2016).

The advent of molecular applications has increased the accuracy for classification and phylogenetic analysis in these groups, a tool that even has facilitated species identification and proposal of new species. However some more challenges have arose because of uncertainty such as sequence length and mistakes in sequence reading that could lead to misinterpretation of the characters (Hunt et al., 2016). Additionally intra individual variability is part of the uncertainty since several haplotypes can be identified in the same EPN isolates (Hunt et al., 2016; Půža, Chundelová, Nermuť, Žurovcová, & Mráček, 2015). Another issue is considered when the genomic regions being surveyed carry a considerable variation, making difficult species assignation for EPN isolates as the case of ITS region, this condition has been described by Půža et al. (2015) were a considerable intra-individual variability was identified in in Steinernema species, a condition that can impact upon taxa only for a few changes in sequences characters from one or more nominal species (Hunt et al., 2016; Půža et al., 2015).

Considering the EPN applicability for weevil population control and all the phytosanitary issues involved in banana and plantain crops affecting negatively yield and fruit quality, the knowledge of genetic diversity, species identification and relatedness of EPN can lead to a positive and biological management for pest control and decreasing soil and water pollution due to abuse of agrochemicals. Currently the application of Next Generation Sequencing (NGS) for genome and transcriptome analyses had increased the comprehension of organisms at the genomic level. Bai et al. (2009) through transcriptomic analysis carried out in Heterorhabditis bacteriophora found a total of 31.485 EST (Expressed Sequence Tag), form there 554 specific EST were considered involved in parasitic nature of this organism compare to free living nematodes. These findings is a step forward to understand the natural history and biology of EPN with promising applicability in several fields such as biological control and alternative source of genetic products form associated bacteria for pests management.

The objectives of the present study were i) to evaluate genetic diversity of EPN present in banana and plantain stands, and ii) evaluate the haplotype distribution of EPN in the sampled areas.

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2.4. Methodology

2.4.1. Sampling area

Sampling period was carried out from November 2015 to December 2016 in twelve municipalities of Valle del Cauca covering the north, center and western of the department. Thirty-three farms were included with areas that range from 0.64 hectares to 30 ha and from 7 m.a.s.l (Buenaventura) to 1.734 m.a.s.l (El Cairo). In total 325.76 ha were covered for sampling. The average number of plants per farm was 2.740, being Plátano Hartón and Banano común the most frequent varieties planted, with the lowest number of plants found in Buenaventura municipality (40 plants) and the highest in Yotoco municipality (30,000 plants). Also the most frequent municipality visited was Argelia with 9 farms followed by Yotoco and Buenaventura with 8 farms sampled each; El Cairo 7, Sevilla 6, Palmira 4, Roldanillo 3, and Obando, Ginebra, Buga and Bugalagrande with two farms sampled each. Several plantain and banana stands sampled were associated mainly with coffee and cassava, and in some cases were associated with fruit trees.

2.4.2. Taxon sampling and DNA extraction

Sampling for Entomopathogenic Nematodes (EPN) was carried out from banana and plantain stands. Ten plants were chosen per hectare and 3 soil samples were taken from each plant at 20 cm from the corm at two different depths (20 and 40 cm) and equally distributed. Every soil sample contained approx. 1 kg for nematodes evaluation. From every soil sample 3 separate replicates were made, approx. 300 gr each, for nematodes recovery. Ten individuals of Galleria mellonella species at larval stage of development were put in each of the three evaluations per soil sample under specific humidity and temperature conditions. Five days after larval contact with soil samples were checked for EPN infection, this evaluation was carried out according to some morphological changes in the larvae appearance. Traits such as turgidity and change of color (yellowish or reddish), were the symptoms to identify the possible infected larvae. The selected ones were dissected to obtain EPN females for morphological and molecular characterization; also the infective juveniles were recovered for pathogenicity evaluations.

81 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

2.4.3. DNA extraction and PCR amplifications for entomopathogenic nematodes

Entomopathogenic nematodes, isolated from Galleria mellonella larvae, were stored in alcohol 70%. From every isolate a single EPN female was selected for DNA extraction using Quiagen® DNeasy blood and tissue kit, all samples were digested in presence of proteinase K overnight until the whole EPN was completely dissolved, then the conditions for DNA extraction were carefully followed according with the manufacturer’s conditions. A final volume of 25µl of DNA solution was recovered with an average concentration of 20ng/µl. The DNA quantification was carried out in Spectrophotometer Colibri Titertek Berthold®, afterwards all DNA samples were used directly from stock solution for PCR amplifications. PCR reactions were made for three mitochondrial regions (COI, 12S, and ND4) and two for nuclear regions (ITS and LSU) (Table 12). Amplification for every region was made mixing 2µl of

DNA 20ng/µl or 30ng/µl; 2,5µl of PCR Buffer 10X (NH4)2SO4; 2µl MgCl2 25mM; 1µl dNTP’s 20mM; 0.4µl Primer F 10mM; 0.4µl Primer R 10mM; 0,5µl BSA 5X; 1µl Trehalose 10%; 0,16µl Taq DNA polymerase 5U/µl; and 15µl of ultra pure water in a final volume of 25µl.

Due to the length of the ITS and LSU rDNA sequences, approximately 900bp, internal primers were employed to split the region into two fragments of approx. 500bp each, this strategy was carried out to improve sequencing reaction of the fragments and guarantee quality of the sequences.

Table 11. Primer sequence for EPN molecular analysis

Primer Name Primer Sequence 5´- 3´ Primer Direction Gene Region Author (Steven A. Nadler et al., COX 1 F AGT TCT AAT CAT AA(A/G)* GAT AT(C/T)* GG Forward COI Mitochondrial 2006) (Steven A. Nadler et al., COX 1 R TAA ACT TCA GGG TGA CCA AAA AAT CA Reverse COI Mitochondrial 2006) (Steven A. Nadler et al., 12S F GTT CCA GAA TAA TCG GCT AGA C Forward mtrDNA Mitochondrial 2006) (Steven A. Nadler et al., 12S R TCT ACT TTA CTA CAA CTT ACT CCC C Reverse mtrDNA Mitochondrial 2006) nd4 F GGC TGG CTT ATT ATT AAA ATT AG Forward mtNDHgene Mitochondrial (Saeb & Grewal, 2014) nd4 R CAA AGA ATA ATA AAA AGA TAC CAA Reverse mtNDHgene Mitochondrial (Saeb & Grewal, 2014) (S P Stock, Campbell, LSU F 93-391 AGC GGA GGA AAA GAA ACT AA Forward rDNA 28S Nuclear & Nadler, 2001) LSU R 501 TCG GAA GGA ACC AGC TAC TA Reverse rDNA 28S Nuclear (S P Stock et al., 2001)

ITS_Interno_F 533 CAA GTC TTA TCG GTG GAT CAC Forward rDNA ITS Nuclear (S P Stock et al., 2001)

ITS_Interno_R 534 GCA ATT CAC GCC AAA TAA CGG Reverse rDNA ITS Nuclear (S P Stock et al., 2001) *Ambiguous of nucleotide bases, this corresponds to degenerated position for that specific nucleotide.

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The PCR profile was as follows: 95ºC x 5 min; 95ºC x 1min; 42ºC x 45 sec; 72ºC x 1 min; followed for 32 cycles of 95ºC x 1 min; 40ºC x 45 sec; 72ºC x 1 min; final extension of 72ºC x 10 min. The PCR products were observed in 1.5% agarose gel and electrophoresed at 120 volts for 45 min in TBE solution 0.5X. Fragment visualization was carried out in transiluminador under UV light (Fig. 16). These amplification profiles were applied to all genomic regions with changes in annealing temperature; for COI the annealing temperature was 40ºC, for 12S region 52ºC, for ND4 48ºC, for ITS region 50ºC, and for LSU 52ºC.

Figure 16. Visualization of PCR product in EPN for LSU region

Visualization of PCR product for primer combinations of LSU rDNA.

2.4.4. DNA sequencing and Genetic analysis

DNA sequencing was performed in both directions (Forward and Reverse) using the primers employed for PCR amplification. Two primer combinations were necessary to amplify ITS and LSU rDNA regions (Table 12). All PCR products were purified following the protocol proposed by Schmitz & Riesner (2006), afterwards the samples were visualized again in agarose gel 1.5% and stained with GelRed® to verify the quality and concentration of the product. For the Sequencing process forward and reverse directions were considered to obtain more accurate information about the nucleotide composition for every organism.

Raw sequence data were visualized and edited manually in Geneious R10 (Kearse et al., 2012), contigs where generated independently for each primer combination sequenced removing

83 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

primer forward and reverse from the sequence, in than way the sequences had a specific length to verify any INDEL event among and between species. After contigs generation, two fragments for each region, ITS or LSU rDNA, were assembled generating the complete 900bp of the sequences with high quality, the overlapping region among the contings was approx. 150bp (Fig. 17).

Figure 17. Contig assemble for LSU rDNA from two independently sequenced fragments

5´ sequence 3´ sequence Consensus sequence

Contig 5´ end Contig 3´ end

Overlapping region

Sequences were aligned using Bioedit® v. 7.1.11 (Hall, 1999) for further genetic analysis. For haplotype identification DNAsp v. 5 (Rozas & Rozas, 1995) software was employed to identify the number of haplotypes, mutational positions and nucleotide diversity contained in every sequence. For Network building the software Network 5.0.01 (Fluxus-engineering, 2015) was employed, this software identify the haplotypes present in the populations and build a network according to mutational steps found among the sequences, also through median vector statistics hypothetical intermediate ancestral sequences can be created to reduce the network complexity for an easy interpretation. Following this description the networks were built considering Transversions three times weighted than Transitions due to the former is less probable to occur creating a less complex and stepwise network.

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For dissimilarity analysis GenAlex v.6.5 (Peakall & Smouse, 2012) was employed to identify genetic distance between species and among individuals, this matrix was used for Principal Coordinate Analysis (PCoA) that represents a spatial distribution of populations (species) and individuals in a 2 dimensional Cartesian plane plot. However despite the difficulty to interpret a PCoA in two-dimensional plot, an additional analysis with Xlstat (Addinsoft, 1993) was employed for a three-dimensional plot to ease the interpretation of genetic distance in terms of spatial distribution.

Dissimilarity Analysis and Representation for Windows DARWIN v. 6.0.014 (Perrier et al., 2003) was performed in all sequence data under Neighbor-Joining algorithm to identify the closeness of samples in an unrooted tree computing the bootstrap method with 3000 replicates and obtaining the most parsimonious tree. Several tree topologies were obtained but the most explainable are shown. For phylogenetic inferences Mega 7.0 (Tamura et al., 2007) was used through Maximum likelihood, using a Bootstrap of 1000 replicates based on Kimura two- parameter model with a heuristic search considering the Maximum Parsimony for the initial tree.

85 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

2.5. Results

A total of fourteen entomopathogenic nematodes (EPN) were isolated from 495 soil samples obtained from 12 municipalities, 33 villages and 33 farms, corresponding to 2.8% of the samples positive to EPN, were samples from Buenaventura, Obando and Palmira contained EPN. After recovery of F1 progeny from Galleria mellonella infected larvae, from the first infection event, and an appropriate storage of the samples in Isopropanol, a unique F1 individual from every isolate (Steinernematid or Heterorhabditid) was used for DNA extraction and for PCR amplification.

Two genomic regions were amplified from every DNA extracted from every F1 individual; these regions, Interspaced Transcribed Spacer (ITS) and Large Ribosomal Subunit (LSU) of the nuclear Ribosomal DNA (rDNA) were sequenced for the 14 isolates. Two EPN families (Steinernematidae and Heterorhabditidae) were identified based on the infection characteristics and morphology on Galleria mellonella larvae. Based on this previous information PCR amplifications were carried out to obtain the highest quality for sequencing reactions. The ITS region was fragmented in two parts to guarantee sequencing quality. Every fragment generates approximately 500 base pairs in length; the same condition was applied for LSU region due to high coverage to be amplified and sequenced.

2.5.1. Analysis with Interspaced Transcribed Spacer (ITS) Ribosomal DNA region.

The ITS region sequenced and assembled generates a total of 797 nucleotide positions for Heterorhabditis sp. and 773 nucleotide positions for Steinernema sp. After a multiple alignment of Steinernema sp. and Heterorhabditis sp. sequences, 10 isolates and 4 isolates respectively, a total of 910 characters (nucleotides and gaps) were identified from which 240 were gaps and 670 were nucleotides; moreover 296 were monomorphic sites and 374 polymorphic sites from which 319 were considered as parsimony informative sites. Haplotype analysis showed three haplotypes in 14 isolates, two were identified for Heterorhabditis sp. and one for Steinernema sp. (Table 13).

According to these results Heterorhabditis sp. showed be more diverse than Steinernema sp., considering that for Heterorhabditis sp. with four isolates two haplotypes were identified, and

86 Chapter 2 this haplotype distribution corresponds to: three Heterorhabditis sp. isolates UNPS19, UNPS20, UNPS21 that share the same sequence and one isolate UNPS16 with a different haplotype where 173 mutated positions could be identified among them. This level of differentiation indicates that UNPS16 corresponds to a different species among the four samples analyzed. This particular group had 595 monomorphic sites and 173 polymorphic sites, and a G+C content of 0.44.

Table 12. Haplotype diversity in EPN species for ITS rDNA

Haplotype Diversity in EPN identified using ITS rDNA region Species No. Specimens Haplotypes Haplotype Diversity Nucleotide Diversity Number of Segregating sites Steinernema sp. 10 1 0 0 0 Heterorhabditis 4 2 0.5 0.1297 147

Total number of data for EPN species using to ITS rDNA region Total Number of sites: 910 Sites excluding gaps: 670 Number of gaps: 240 Total number of mutations: 421

Total number of INDEL: 206 Monomorphic sites: 296 Polymorphic sites: 374 Parsimony Informative sites: 319

2.5.2. Haplotype Network

This analysis included 56 nucleotide sequences for ITS region where 10 belongs to UN Steinernema sp. isolates and 12 Steinernema spp. accessions from Stock et al. (2001) and NCBI database, additionally 4 UN Heterorhabditis sp. isolates, 20 Heterorhabditis spp. accession sequences from Stock et al. (2001) and accessions from NCBI database were included. This strategy was carried out to identify the closest species for both, Steinernema sp. and Heterorhabditis spp. isolates and to know the mutational steps between isolates and species analyzed. This network also connects the nearby species giving a clue to classify the isolates obtained into species. After a BLAST in NCBI it could be identified that Steinernema isolates had an identity of 99% with Steinernema carpocapsae, however building a network it could verify the closeness of Steinernema isolates to S. carpocapsae.

For Heterorhabditis the scenario is different considering the presence of a divergent sequence, after a BLAST three of the sequences (UNPS19, UNPS20, UNPS21) had an identity of 99% with Heterorhabditis amazonensis and one (UNPS16) had a identity of 100% with Heterorhabditis bacteriophora. In that sense, the species potentially related to EPN isolates

87 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

were included in the network analysis (Fig. 18) along with other species that could show relatedness.

Figure 18. Network analysis for EPN haplotypes under ITS rDNA

H. taysearae S. sasonense S. minutum S. huense

S. backanense S. siamkayai H. sonorensis H. noenieputensis UN Isolates Heterorhabditis H. indica H. mexicana

H. noenieputensis

UN Isolates Steinernema sp. H. marelatus H. floridensis H. pakistanence UPNS16 H. baujardi

H. brevicaudis H. bacteriophora

H. safricana Heterorhabditis sp. S. carpocapsae H. argentinensis H. georgiana H. zelandica H. hepialius

UN Isolates Steinernema sp. H. megidis Steinernema sp. Genbank accessions Heterorhabditis sp. Genbank accessions UN Isolates Heterorhabditis sp. H. downesi

Network analysis for EPN haplotypes. Every circle represents a specific haplotype and every color represents the origin of the samples. Green circle UN isolates (Steinernematids); dark blue circles Steinernema carpocapsae accession from NCBI; fuchsia circles UN Heterorhabditids isolates; light blue circles Heterorhabditis accessions from NCBI.

Network results indicate a clear separation between Steinernema (dark blue circles) and Heterorhabditis species (light blue circles) and all the connections of every node represent mutational steps between haplotypes. Every circle represents a certain number of individuals that share the same haplotype, and the red dots, called “median vectors”, represents hypothetical intermediate sequences to shortened the length of the branches that interconnect the nodes. The UN isolates for Steinernematids (10 samples) are grouped in a single circle (green) that indicates only one haplotype, and S carpocapsae accessions are grouped below UN isolates. Several circles compose the S. carpocapsae cluster indicating genetic variability

88 Chapter 2 among accessions, also there are two median vectors between UN Steinernema isolates and S. carpocapsae cluster indicating a considerable nucleotide substitution in between.

Heterorhabditis spp. isolates showed a more complex network and three of the four UN isolates formed one haplotype (fuchsia circle) closer to Heterorhabditis sp. (NCBI accessions), through a diagonal branch and one median vector, that indicates not a significant divergence between the two, but under this analysis there is no species definition for those isolates. One isolate (UNPS16) showed complete identity with Heterorhabditis bacteriophora indicating the classification of it.

Figure 19. Simplified network for ITS rDNA in EPN

UN Isolates Steinernema sp.

Steinernema carpocapsae Genebank accessions

Heterorhabditis sp. Genebank accessions

UN Isolates Heterorhabditis sp.

Heterorhabditis bacteriophora

Network analysis for ITS rDNA haplotypes considering UN isolates from both Steinernematids (green circle) and Heterorhabditids (fuchsia circle) strands, and the closest species identified form NCBI accessions.

To decrease the complexity of the network an alternative strategy was carried out, this consists in reduce the number of species and only consider those closer to the UN isolates. From the initial network S. carpocapsae, Heterorhabditis sp. and H. bacteriophora species were selected to build an alternative, less complex network. Steinernema sp. isolates compose one node (green circle) indicating the presence of only one haplotype, close to this node is S.

89 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control carpocapsae samples (dark blue circles) which are connected without median vectors, indicating low mutational steps that interconnect them; following downwards there are the Heterorhabditis species organized in three circles, in light blue is Heterorhabditis sp., in fuchsia UN Heterorhabditids isolates and the combined fuchsia and purple corresponds to UNPS16 (fuchsia) and H. bacteriophora (purple). Notice that there are no median vectors among them, even between species, however the branch length indicates high number of mutations or substitutions between species (Fig. 19).

2.5.3. Dissimilarity Analysis

This method was employed to consider differences in nucleotide composition among the samples and to generate a clustering under Neighbor-Joining algorithm. Due to uncertainties for species assignment in some of the UN isolates obtained in the present study, this analysis showed very defined branches according with the lowest genetic difference among the samples (Fig. 20). For this analysis several Genbank accessions for Steinernema spp. and Heterorhabditis spp. were included. In the upper side of the tree Steinernema UN isolates and S. carpocapsae are close to each other, as expected according with the results obtained after a comparison in BLAST algorithm (NCBI), the other Steinernema species are grouped in the middle of the tree forming three discrete branches according to the species which they belong. In the lower side of the tree is the Heterorhabditis spp. cluster where the UN isolates UNPS19, UNPS20, UNPS21 are clustered together and UNPS16 is clustered apart, demonstrating that there are more differences between this isolates and there are two different species (Fig. 20).

Despite the considerable divergence in nucleotide composition between UN Heterorhabditis spp. isolates, they belong to Heterorhabditis genus, moreover it is also identified the genetic richness at the interior of every group. This results are consistent to those analyzed from alternative perspectives (e.g. infection traits, differences in size of F1 females and distinctive larvae phenotype that they infected), indicating a clear separation between the two genus, and consequently the two EPN families. This remarkable analysis indicates that despite to be parasitic organisms with similar behavior and mechanisms to infect arthropods, genetically are very distant and also very diverse within each group, not only into their respective family, but also at the species level, and that condition could be directed because of the reproductive mechanisms and the high rate of mating and short life cycle.

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Figure 20. Dissimilarity analysis in EPN for ITS rDNA

UN Isolates Steinernema sp.

Steinernema carpocapsae

Steinernema spp. Genbank Accessions

UN Isolates Heterorhabditis sp.

UN Isolate UNPS16 Heterorhabditis sp. Heterorhabditis sp. Genbank Accessions

Dissimilarity analysis in EPN for ITS rDNA region where every species is and/or source of the sequence is represented with specific color. The unrooted tree represents the distance among samples in terms of dissimilarity.

91 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

2.5.4. Maximum Likelihood Analysis

2.5.4.1. Heterorhabditis spp.

The phylogenetic analysis for EPN was carried out using ITS Ribosomal RNA region considering 797 nucleotide positions for Heterorhabditis spp. isolates and 773 nucleotide positions for Steinernema spp. isolates through Maximum likelihood, using a Bootstrap of 1000 replicates based on Kimura two-parameter model with a heuristic search considering the Maximum Parsimony for the initial tree. A total of 48 nucleotide sequences for ITS ribosomal region belonging to 22 Heterorhabditis species were included in the analysis (including Genbank accessions), using Steinernema monticolumn as the out-group. All sites were included (nucleotides and gaps) to identify the most accurate tree topology (Fig. 21).

This analysis showed that UPNS 19, UPNS 20 and UPNS 21 are clustered together with Heterorhabditis sp. under a bootstrap probability of 85%. On the other hand UNPS16 is clustered with H. bacteriophora under a bootstrap probability of 89%. This results are conclusive to verify what species were isolated in the present study, however UPNS 19, UPNS 20 and UPNS 21 isolates grouped with Heterorhabditis sp., however H. amazonensis is the closest group and can be a candidate for species assignment of UN isolates. From a wide spectrum of species included in the analysis, the clusters are very defined and isolates well supported in every branch, indicating a low error probability in species assignment for UN isolates (Fig. 21).

2.5.4.2. Steinernema spp.

Phylogenetic analysis for EPN was carried out using LSU Ribosomal RNA region considering 905 nucleotide positions for Heterorhabditis isolates and 875 nucleotide positions for Steinernema Isolates through Maximum likelihood, using a Bootstrap of 1000 replicates based on Kimura two-parameter model with a heuristic search considering the Maximum Parsimony for the initial tree. A total of 34 nucleotide sequences for LSU ribosomal region belonging to 9 Heterorhabditis species (including Genbank accessions) were included in the analysis, using Steinernema monticolumn as the out-group. All sites were included (nucleotides and gaps) to identify the most accurate tree topology (Fig. 22).

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Figure 21. Maximum likelihood tree for Heterorhabditis spp. under ITS rDNA region

Maximum likelihood tree for Heterorhabditis species where UN isolates are highlight in green. The green branch represents the cluster for 3 EPN isolates from UN with Heterorhabditis sp. accession EF217328 from NCBI database. The blue branch corresponds to the H. bacteriophora NCBI accessions in a cluster with UNPS16 isolate.

93 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Under this analysis UN isolates are clustered together in the same main node of Steinernema carpocapsae with a very low genetic variability among them. S. carpocapsae isolates were chosen from NCBI database and from Stock et al. (2001), considering the region or country of origin to identify a possible genetic differentiation within the species. However a compact and low genetic variable cluster for Steinernema was identified under a Maximum Likelihood Analysis, indicating low genetic variability of this genetic region (Fig. 22); this has advantages and disadvantages, for the first case, advantages, is a stable region that can help to identify species due to low rate of nucleotide substitution at species level, in that sense this genetic information is stable enough to avoid misinterpretation of genetic analysis, in the second case, disadvantages, is not variable enough to identify genetic variability within the species as could be identified in the present analysis.

Figure 22. Maximum likelihood analysis for Steinernema spp. under ITS rDNA

Maximum likelihood analysis for Steinernema spp. In green UN Steinernematids isolates, in red Steinernema carpocapsae NCBI accessions, in blue Steinernema species from NCBI.

An interesting location of one UN isolate is related to UNPS09 that shows a slight difference respect to other isolates, but it is important to take in mind that UN Steinernema isolates only had one haplotype, one unique sequence shared by all the isolates, perhaps this grouping could

94 Chapter 2 be due to a gap present in the sequence, and as mentioned before, this analysis considered all site positions to infer a parsimonious tree, also the genetic differentiation is very low in the cluster (Fig. 22).

2.5.5. Analysis with Large Ribosomal Subunit (LSU)

The Large Ribosomal Subunit (LSU) amplified generates 905 nucleotide positions for Heterorhabditis isolates (UNPS16, UNPS19, UNPS20 and UNPS21) and 875 nucleotide positions for Steinernema isolates (UNPS03, UNPS05, UNPS09, UNPS10, UNPS12, UNPS13, UNPS15, UNPS18, UNPR52 and UNPR73). After multiple sequence alignment 907 sites were generated, from which 51 corresponds to gaps, 856 nucleotide positions to compare, 571 monomorphic sites, 285 polymorphic sites, 273 parsimony informative sites and 50 INDEL events. All the nucleotide changes were spread along the sequences form position 6 to position number 870.

Table 13. Haplotype diversity in EPN for LSU rDNA

Haplotype Diversity in EPN identified using LSU rDNA region

Species No. Specimens Haplotypes Haplotype Diversity Nucleotide Diversity Number of Segregating sites

Steinernema sp. 10 1 0 0 0

Heterorhabditis 4 2 0.5 0.0197 33

Total number of data for EPN species analyzed with LSU rDNA region Total Number of sites: 907 Sites excluding gaps: 856 Number of gaps: 51 Total number of mutations: 295

Total number of INDEL: 50 Monomorphic sites: 571 Polymorphic sites: 285 Parsimony Informative sites: 273

The haplotype diversity obtained was similar to ITS region evaluation, were Steinernema isolates presented one haplotype in ten samples and Heterorhabditis isolates presented two haplotypes in four samples, showing again more diversity in Heterorhabditidae group (Table 14).

95 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Figure 23. Network analysis for EPN haplotype under LSU rDNA region

S. cubanum

Steinernema sp. S. longicaudum

S. karii S. glaseri UN Isolates Heterorhabditis

H. floridensis

S. arenarium Heterorhabditis sp. H. mexicana S. oregonense S. feltiae

S. kraussei H. amazonensis H. indica S. intermedium H. safricana H. megidis S. kushidai S. affine H. indica H. zelandica S. ceratophorum S. riobravis S. siamkayai

H. neonieputensis S. abbasi H. georgiana S. bicornutum S. scapterisci

S. puertoricense UN Isolates Steinernema sp. UNPS 16 Heterorhabditis sp.

H. marelatus H. bacteriophora

H. atacamensis S. rarum S. monticolum

S. carpocapsae

UN Isolates Steinernema sp.

Steinernema spp.

S. carpocapsae

Heterorhabditis spp.

UN Isolates Heterorhabditis sp.

Heterorhabditis sp. Accession KY055370

H. amazonensis Accession EU099036

Network analysis in EPN haplotypes. Every circle represents a specific haplotype and every color represents the origin of the samples. Green circle UN isolates Steinernematids; yellow circles Steinernema carpocapsae accessions from NCBI; dark blue circles Steinernema spp. accessions from NCBI; fuchsia circles UN Heterorhabditids isolates; orange circle Heterorhabditis sp.; purple H. amazonensis; light blue circles Heterorhabditis accessions from NCBI.

A clear separation from Steinernema species (left side of the figure) and Heterorhabditis species (right side of the figure) indicates low genetic similarity, and that is expected for two

96 Chapter 2 different families. In the case of S. carpocapsae (highlighted in yellow) grouped very close to UN isolates (highlighted in green), it can be notice that there is only one node between the four Steinernema accessions and UN isolates, also this species cluster is differentiated from other Steinernema species (highlighted in dark blue), showing several nodes (red points) that interconnect them representing more point mutations and consequently more genetic distance. UN isolates shows two green circles that represents two haplotypes, however as was previously reported Steinernema isolates only had one haplotype, but gaps were not consider under that analysis, in the case of this network all sites were included resulting two haplotypes related basically to gaps into the sequence (Fig. 23).

The complexity of this network represents the high number of nucleotide substitution between the two families, also within species some genetic variability could be identified, whether or not corresponds to gaps or nucleotide substitutions. In general terms all Steinernema species shows a high genetic variability and despite of that is a compact cluster well differentiated to Heterorhabditis species that, again, showed a clear differentiation (Fig. 23).

In the case of Heterorhabditids, UN isolates (fuchsia circle) are split into two separately circles, the first circle possess the isolates (UNPS19, UNPS20, UNPS21) and are very close to Heterorhabditis sp. (orange circle) under accession number KY055370, also Heterorhabditis amazonensis (purple circle) under accession number EU099036 is closer but with more mutations accumulated. Respect to results obtained under BLAST in NCBI where Heterorhabditis sp. and Heterorhabditis amazonensis had the same identity of 99%, this analysis shows that Heterorhabditis sp. is the most probable sequence close to UN isolates (Fig. 23).

For UNPS16, grouped apart form the other three isolates, the circle is shared with Heterorhabditis marelatus (circle light blue and fuchsia) indicating a perfect match in nucleotide sequence, also verifying that this isolates corresponds to that species. This also explains the high divergence of UNPS16 respect to other UN Heterorhabditis isolates. Moreover there are many mutational steps from H. marelatus and UNPS19, UNPS20, UNPS21, and according with this grouping and the obtained for Steinernema, an additional small and less complex network was built. (Fig. 24).

97 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

This less complex network was built considering S. carpocapsae, H. bacteriophora, Heterorhabditis sp. and UN isolates. Heterorhabditis isolates are connected to Heterorhabditis sp. (light blue circle) and UNPS16 (red circle), at the same time the red circle (UNPS16) is connected to H. bacteriophora verifying the compatibility of this isolate with that species (Fig. 24).

Figure 24. Network analysis for UN isolates EPN under ITS rDNA sequence

UN Isolates Heterorhabditis sp.

Heterorhabditis sp.

UN Isolate UNPS16

H. bacteriophora

UN Isolates Steinernema sp.

S. carpocapsae sp.

Network for EPN UN Heterorhabditis isolates. Blue circles UN Steinernematids, green S. carpocapsae, fuchsia Heterorhabditids UN isolates, light blue Heterorhabditis sp. yellow H. bacteriophora, red UNPS16.

Despite these results, the isolates that have a match with Heterorhabditis sp. are still unresolved to know what species could they be, although it is probable to cluster with H. amazonensis if its consider that there is an identity of 99% under a BLAST comparison. In the case of Steinernema UN isolates there is a complete similarity with S. carpocapsae, where two haplotypes are identified and the green circle that belongs to S. carpocapsae do not present any

98 Chapter 2 nodes in between, also it can be notice a clear separation between Heterorhabditis and Steinernema, at least 173 point mutations that separate them (Fig. 24).

2.5.5.1. Dissimilarity analysis using LSU ribosomal region

Dissimilarity analysis was employed in all UN isolates and Genbank accessions to identify the differences in sequence composition. Through this analysis only the differences are considered, so this can differentiate small changes in nucleotide composition and group the samples according with the Neighbor-Joining algorithm (Fig. 25).

Figure 25. Dissimilarity analysis in EPN for LSU rDNA

UN Isolates Steinernema sp.

Steinernema carpocapsae

Steinernema spp. Genbank Accessions

Steinernema spp. Genbank Accessions UN Isolates Heterorhabditis sp.

Heterorhabditis sp. Genbank Accessions

UN Isolate UNPS16 Dissimilarity analysis in EPN for LSU rDNA region where every species is and/or source of the sequence is represented with specific color. The unrooted tree represents the distance among samples in terms of dissimilarity.

99 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Dissimilarity tree deployed 8 define branches from which 2 corresponds to Steinernema isolates and S. carpocapsae, three Steinernema spp. accessions and three to Heterorhabditis spp. group. For Steinernema group in one branch UN isolates and S. carpocapsae accessions are grouped together, verifying that 10 UN Steinernema isolates corresponds to this species, the second branch of this group is composed also with S. carpocapsae accessions but with a higher dissimilarity. The other Steinernema species are clustered apart in the middle of the tree forming three well-differentiated groups. For Heterorhabditis UN isolates, these are split in two of the three branches that compose this group. In one of the branches UNPS19, UNPS20 and UNPS21 are clustered, close to Heterorhabditis sp. and UNPS16 is close to H. bacteriophora accession indicating the closeness of this isolate with that particular species (Fig. 25).

This results are consistent between ITS and LSU region, however despite of the fact that 3 Heterorhabditis isolates do not present a particular species assignation, and the closest similarity match with Heterorhabditis sp. more analysis are necessary, perhaps Cytochrome Oxidase I Mitochondrial gene could give a possible and specific species assignation, since this mitochondrial region has been proposed and evaluated as an additional tool to solve taxonomic issues in difficult species. Because of availability of information and universality of ITS and LSU ribosomal region in entomopathogenic nematodes (EPN), this genomic segments were employed in the present study giving important information for species identification, however additional Loci would necessary to identify intra species variability.

2.5.6. Maximum Likelihood Analysis

2.5.6.1. Heterorhabditis spp.

A total of 905 nucleotide positions were employed in the analysis, 21 DNA samples were analyzed (including 17 Genbank accessions and four UN isolates) and distributed in 15 species, where Panagrellus redivivus was used as out-group. LSU region showed more variability within species indicating more nucleotide substitution. UN isolates were split apart according with the similarity shared respect to the species included, being UNPS19, UNPS20 and UNPS21 isolates separate in a cluster close to Heterorhabditis sp., respect to UNPS16 share the same branch with H. marelatus, the same condition was found in Network analysis, however is contrasting with the results obtained for ITS region where this isolate is grouped with H.

100 Chapter 2 bacteriophora, this situation can be explain by the fact that LSU was more diverse in nucleotide substitution comparing UNPS16 and other Heterorhabditis isolates, moreover the closeness between H. bacteriophora and H. marelatus, as shown in ML tree, also could be a source of discrepancy observed in ITS and LSU. All Heterorhabditis species showed a well-defined cluster with bootstrap values higher than 70% (Fig. 26).

Figure 26. Maximum likelihood analysis for Heterorhabditis spp.

Maximum likelihood tree for Heterorhabditis species where UN isolates are highlight in green. The green branch represents the cluster for 3 EPN isolates from UN with Heterorhabditis sp. accession KY055370 from NCBI database. The isolate UNPS16 is clustered with H. marelatus NCBI accession DQ145665.

2.5.6.2. Steinernema spp.

All UN isolates clustered together with S. carpocapsae accessions from different origin; this cluster shows slight variations within the group that confirms the substitutions identified with LSU region. Steinernema spp. shows a well-supported bootstrap nodes with values over 80%

101 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

and longer branches that represents higher variability among the samples. These results, plus ITS results, demonstrate that UN isolates Steinernema definitely belongs to S. carpocapsae (Fig. 27).

Species organization in the tree shows that S. abbasi is the closest species to S. carpocapsae and consequently to UN Steinernema isolates, however there is a considerable genetic distance between the two. This main cluster also contains S. riobravis, S. bicornutum and S. ceratophorum supported with a bootstrap of 80%. The other clusters are well supported forming four clusters, and the out-group Panagrellus redivivus forming the final cluster (Fig. 27).

One contrasting result found in this analysis was the grouping of S. carpocapsae accession number AF331900 reported by Stock et al. (2001) and reported by Nadler et al. (2006), this sequences reported for 28S ribosomal region are clustered with S. siamkayai, S. scapterisci, and S monticolumn, however do not clustered with other S. carpocapsae accessions. In the tree this accessions are located in the last cluster, just in the opposite side of the S. carpocapsae and UN isolates cluster. A more detailed review is necessary to verify these sequences reported previously and those clustered with UN isolates.

Considering the discrepancies for species assignation of the isolate UNPS16 respect to ITS and LSU ribosomal region, an additional analysis was carried out to solve it. A data matrix was built fusing nucleotide sequences from ITS and LSU ribosomal regions generating a data matrix of 1735 sites in average. For UN Steinernema isolates, the nucleotide composition was T 32%, C 16%, A 24% and G 25% for a final sequence length of 1646 nucleotides. Respect to Heterorhabditis UN isolates the nucleotide composition was T 27%, C 19%, A 26% and G 27% with a sequence length of 1702 nucleotides. The shortest nucleotide sequence corresponded to S. monticolumn (AF331895) with 1598 sites and the longest corresponded to H. floridensis (DQ372922) with 1992 nucleotide sites. This matrix was analyzed in Mega 7 through Maximum likelihood method, using a Bootstrap of 1000 replicates based on Kimura two-parameter model with a heuristic search, considering the Maximum Parsimony for the initial tree.

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Figure 27. Maximum likelihood tree for Steinernema spp. under rDNA region

Maximum likelihood analysis for Steinernema spp. In green UN Steinernematids isolates, in red Steinernema spp. NCBI accessions.

A total of 33 DNA sequences that corresponds to EPN species (including Genbank accessions) were included, being 22 for Steinernema spp., 11 for Heterorhabditis spp. and one for out-group Caenorhabditis elegans (X03680). Species such as S. carpocapsae, with accession number AF331900 (S P Stock et al., 2001), Heterorhabditis sp. with accession number HQ896631 and H. bacteriophora, with accession number EU099033 and JQ178377, were incorporated in the analysis with the aim to identify how UN isolates are grouped and also to verify if the accession AF331900 is related to other S. carpocapsae accessions reported in NCBI database (Fig. 28).

103 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

The tree shows a clear separation between Steinernema and Heterorhabditis species. All main tree nodes were well supported with bootstrap values of 99% or 100% where UN Steinernema isolates generate a unique cluster with S. carpocapsae accessions from NCBI, being S. siamkayai the closest group. Respect to accession AF33190 reported by (S P Stock et al., 2001) is still controversial, this accession clustered away form S. carpocapsae group, closer to S. scapterisci and S. monticolumn. Despite to include approximately 1700 nucleotide sites, this accession does not grouped with the species that suppose to be (Fig. 28).

Figure 28. Maximum likelihood analysis for Steinernema spp. under LSU rDNA

Maximum likelihood analysis for Heterorhabditis spp. and Steinernema spp. In green all UN isolates obtained in the present study. Green branch corresponds to S. carpocapsae cluster. Red branch Steinernema species from NCBI. Purple UNPS16 with H. bacteriophora cluster. Fuchsia branch Heterorhabditis species from NCBI. Blue branch UN Heterorhabditis isolates.

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Heterorhabditis UN isolates were split into two branches, one grouped only UN isolates UNPS19, UNPS20 and UNPS21 with the closest group H. Mexicana and the isolate UNPS16 cluster perfectly with H. bacteriophora confirming this isolate belonging to that species.

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2.6. Discussion

2.6.1. Recovery and frequency of EPN

The number of individuals recovered from samples soil was very low representing 2.8% positive for EPN, from there 71.42% corresponded to Steinernematids (recovered from Obando and Palmira) and 28.57% to Heterorhabditids (recovered from Buenaventura). This low recovery of EPN could be related to soil conditions due to all samplings were from banana and plantain stands, with a considerable impact of agrochemicals because of the presence of weevils, the constant irrigations and changes in soil conditions could drive to worse conditions for EPN. Despite in the present study there were no soil analyzes several reports considered the impact on soil pollution in cultivated areas, for instance López-Núñez et al. (2007) obtained only 3% positive samples for EPN where 92.86% belonged to Steinernematids and 7.8% for Heterorhabditids, this sampling was carried out in different crops, agro-forest and forest groves where soil conditions basically possess high organic matter and acidic conditions. Mráček et al. (2006) in their research found several conditions that could affect EPN recovery from soil such as heavy rain and flooding areas, however more positive samples came from deciduous forest habitats and oak forests, this natural conditions can favor the occurrence of EPN, under this report it can be assumed that human impacts in soil can affect the survival and establishment of EPN in banana and plantain crops. Gruner et al. (2007) reported that soil parameters such as texture, bulk density, pH, organic content and soil water potential can affect infective juvenile (IJ) behavior, survival and host infectivity.

According with the conditions previously described it can be infer the high susceptibility of EPN to altered soils, but taking into account that UN isolates were recovered from plantain and banana stands under constant chemical irrigations, seems that EPN can tolerate certain environmental pollution, however the low number of isolates recovered, EPN seems to resist changes in soil conditions. Hazir et al. (2004) reported that effects of agrochemicals may or may not interact with EPN and is basically due to the characteristics of the chemicals applied, application system and physico-chemical characters of the system. Also identified that some EPN are compatible with some herbicides, fungicides and insecticides, although various pesticides have been documented for a negative effect in EPN.

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Another factor found in this study was the frequency of Steinernematids respect to Heterorhabditids, where for the former was 3 times higher than Heterorhabditids. However as reported by Hominick, (1996) this organisms are widespread all over the world except for Antarctica continent, but is reported that Steinernematids dominate cooler conditions and Heterorhabditids dominate tropical conditions, nevertheless there are two species that appear to have a global distribution, namely Steinernema feltiae and S. carpocapsae and are commonly found in habitats such as pastures, roadsides, garden forests and national parks where human impact is minimal. This report is related with the results obtained in the present study, where Steinernematids isolates, that account for 71.42% of all EPN recovery, were S. carpocapsae. In contrast (Liu & Berry, 1997) found EPN with a higher frequency in coastal areas of Oregon and Heterorhabditis spp. were the most commonly found species, while in most studies (Commission, 1998; Hashmi & Gaugler, 1998; Hazir et al., 2004; Hominick, 1996; López-Núñez et al., 2007; Puza & Mrácek, 2007; Shapiroilan et al., 2002; S. Patricia Stock, 2005; S. Patricia Stock & Gress, 2006a, 2006b) Steinernematids were more common than Heterorhabditids, and a possible explanation for this is because there are more Steinernema species than Heterorhabditis species, and they, therefore, can occupy more niches. Moreover the differences in life history “favors” to Steinernematids because Infective Juvenile (IJ) males and females are necessary for reproduction, therefore this species are more expected to be more abundant in the environment giving the possibility for recovery from soil, in contrast Heterorhabditids have a different mode of reproduction, hermaphroditism, indicating that with only one IJ is sufficient to multiply (Hunt et al., 2016; Mwaitulo, Haukeland, Sæthre, Laudisoit, & Maerere, 2011).

2.6.2. Nucleotide composition and substitution rate in EPN

In the present study a total of 14 entomopathogenic nematodes (EPN) were isolated from 495 soil samples representing 2.8% of the sampling. Ten isolates (UNPS03, UNPS05, UNPS09, UNPS10, UNPS12, UNPS13, UNPS15, UNPS18, UNPR52 and UNPR73) corresponded to Steinernema carpocapsae, three (UNPS19, UNPS20, UNPS21) corresponded to Heterorhabditis sp. and one (UNPS16) to Heterorhabditis bacteriophora. Several analyses were carried out to verify the species assignment for each of the isolates, additional analyses were considered to identify both, within and among species diversity. The nucleotide composition obtained for every species and for ITS region under a nucleotide sequence length of 773 site positions was 38.4% (T), 16% (C), 23.7% (A), and 21.9% (G) for S. carpocapsae UN Isolates;

107 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

respect to Heterorhabditis spp. UN isolates with a sequence length of 783 site positions, the nucleotide composition was 29.8% (T), 19.4% (C), 25.7% (A), and 25.2% (G); and for UN isolate identified as Heterorhabditis bacteriophora with a sequence length of 796 site positions, the nucleotide composition was 29.4% (T), 19.5 (C), 26% (A), and 25.1% of (G). This nucleotide composition indicates that Thymine (T) had the highest difference found between Steinernema and Heterorhabditis isolates, also nucleotide sequence length was slightly higher for Heterorhabditis isolates.

For LSU region the nucleotide composition was 27.9% (T), 17.4% (C), 25.3% (A), and 29.3% (G). The sequence length obtained for Steinernematids UN isolates was 873 nucleotide positions, whereas for Heterorhabditids 902 nucleotide positions were identified with nucleotide proportions slightly different 25.1% (T), 19.2 (C), 26.6% (A), and 29.1% (G), respect to Steinernematids. When comparisons included the genetic distance among Steinernematids and among Heterorhabditids, for the former showed 0.00 of genetic distance values, all of them belonging to the same species Steinernema carpocapsae, while for the second group the genetic distance among UNPS19, UNPS20 and UNPS21 was 0.00, but when compared Steinernematids UN isolates to Heterorhabditids UNPS19, UNPS20 and UNPS21 the genetic distance was 0.797, and between Steinernematids UN to UNPS16 was 0.838; additionally the comparison including UNPS19, UNPS20 and UNPS21 respect to UNPS16 the genetic distance was 0.263. This genetic distance indicates the presence of three well-differentiated species being Steinernematids the most distant group.

Considering the nucleotide composition for every species and the both nuclear regions analyzed for rDNA, it is also important identify Transition-Transversion events, where the former, Transitions, were the most common events for both ITS* and LSU** rDNA, being A/G with 16.9%* and 10.05%**, G/A 16.83%* and 11.07%**, T/C 21.16%* and 23.28%**, C/T 9.75%* and 15.77%**. On the other hand Transversions were less common A/T - A/C 4.6%* and 5.08%**, T/A – T/G 6.41%* and 5.27**%, C/A – C/G 2.96%* and 3.57%**, G/T – G/C 4.14%* and 5.8%**.

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2.6.3. Haplotype identification and genetic diversity in EPN

Despite this mutational events identified for ITS and LSU nuclear regions, these have been considered as a barcode sequences for species identification (Chaerani, Stock, & Griffin, 2004; Phan, Subbotin, Waeyenberge, & Moens, 2005; Půža et al., 2015; S. Patricia Stock & Gress, 2006a, 2006b; S P Stock et al., 2001; Uribe-Lorío, Mora, & Stock, 2007), phylogenetic analysis, evolutionary relationships, delimitation of taxa and for diagnostic purposes (Chaerani et al., 2004; S P Stock et al., 2001). Additional Loci as ITS rDNA has been included in this kind of analysis due to high resolution in species identification and variability found among species, also this region seems to be only useful for resolving relationships among closely related Steinernema species, however its variability is too high for phylogenetic analysis at genus level being considered no optimal for this analysis because can incur in misdiagnosis or homoplasy among taxa (Chaerani et al., 2004; S P Stock et al., 2001). Nevertheless is considered optimal when species are closely related or the samples are collected into the same population, in this sense fixed autapomorphies can be identified between species or genus (Chaerani et al., 2004).

In the present study some analysis were contrasting when LSU and ITS rDNA were compared. For the first case in network analysis the genetic distance among Steinernema carpocapsae species, evaluated under LSU rDNA, was very small with no nodes in between the haplotypes, however for ITS rDNA at least two median vectors were identified, indicating more genetic distance among the species, additionally for dissimilarity analysis Steinernematids UN isolates are grouped in the same branch respect to S. carpocapsae NCBI accessions analyzed with LSU rDNA, but with ITS rDNA more differences were identified even generating two separate closely related clusters.

2.6.4. Phylogenetic analysis in EPN

Some discrepancies were found in the phylogenetic trees and network analysis. For Heterorhabditis UNPS16 isolate, evaluated with ITS region, had 99% of similarity with H. bacteriophora, but this isolate evaluated with LSU showed 99% similarity with H. marelatus. This contrasting results could be related to high levels of nucleotide substitution found in both rDNA regions, in the first case ITS rDNA showed transitional events higher that LSU. This condition was identified by Půža et al. (2015) who reported high variability in ITS region

109 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

including nucleotide substitution and variation in sequence length. Additionally proposed something important, and is about when individual nematodes are sequenced not all individuals carry variability, suggesting the number of haplotypes per individual and strain could be underestimated.

Following the characteristics previously described and discrepancy respect to species assignation for UNPS16, the sequence from ITS and LSU region were fused to obtain approx. 1.500 nucleotide positions to compare in an additional analysis. This tree showed that UNPS16 is in the same cluster with H. bacteriophora with no genetic distance among them under a bootstrap probability of 100%, respect to isolates UNPS19, UNPS20 and UNPS21, the cluster is supported with 100% of bootstrap probability and with a very low distance to H. amazonensis. These analyses also were conclusive for S. carpocapsae where all UN isolates clustered together. However S. carpocapsae isolate from Stock et al. (2001) under accession number AF331900 for LSU and AF331913 for ITS clustered apart indicating a different sequence that do not belong to S. carpocapsae species, instead is closer to S. scapterisci and S. siamkayai species. This condition was confirmed through a BLAST comparison, where the accession AF331900 had a similarity of 99% with S. scapterisci and S. siamkayai and despite to have also a similarity of 99% with one S. carpocapsae isolate, published by Nadler et al. (2006), this sequence also do not show similarity with S. carpocapsae reported sequence species (data not shown). However for the same isolate AF331913 reported by S P Stock et al., (2001), the ITS region showed high similarity with S. carpocapsae isolates already reported in NCBI database, this results are more intriguing due to the fact that LSU have been reported as very conserved sequence (Adhikari et al., 2009; Hashmi & Gaugler, 1998; Liu & Berry, 1997; S A Nadler & Hudspeth, 1998; Steven A Nadler, Bolotin, & Stock, 2006; Půža et al., 2015; S P Stock et al., 2001), moreover the phylogenetic analysis reported by S P Stock et al., (2001), showed trees under maximum parsimony where in all cases S. carpocapsae AF331900, S. scapterisci and S. siamkayai where clustered, indicating the closeness of these species under LSU sequence.

This conflicting finding was also found by Mráček et al. (2014) where they reported that the sequences with accession number AF331900 in fact belongs to nematodes of the family Heterorhabditidae, and had generated conflicting results in some phylogenetic studies of the Steinernematidae family and proposed that this sequence must be removed from database or adequately renamed.

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Stock et al. (2001) reported that the results obtained may reflect a lack of robustness for the partial rDNA dataset, also showed a relative reliability of small number of clades, from which inferred hypothesis of the clades are based only on data from a single locus, and interpretations of evolutionary history and relatedness are based in that particular characters. It is important to consider that in these studies, were hypothesis of evolutionary history and character description only few data are considered as informative, complexity of natural organisms and the plasticity found in species makes difficult to assign exclusive characters as autapomorphies that could represent a plausible phylogenetic hypothesis.

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2.7. Conclusions

The presence of entomopathogenic nematodes in banana and plantain stands seem to be resistant to soil pollution, however the low frequency of EPN in soils could also be related to harsh conditions modified by human activities such as physico-chemical soil properties affected by agrochemical doses for fertilization and pest control. Additionally the loss of infectivity from EPN to larvae could be related to environmental conditions in the laboratory, as well as the target insect employed for EPN recovery making difficult the infection success.

The evaluation of ITS and LSU rDNA regions as a source of genetic information to identify genetic variability and species had been puzzled for several studies. LSU rDNA is reported as the most conserved region respect to ITS, however in the present study this variability was reduced in Steinernema and Heterorhabditis isolates, probably affected by soil conditions form where these isolates were recovered leading to a loss of genetic variability due to anthropic influence. Nevertheless some contrasting results were related to ITS region for Heterorhabditis UN isolates which indicates the complexity of these group of organisms; this situation was confirmed comparing NCBI accessions previously reported and after several analysis, this study and other reported in 2014, found deep discrepancies respect to accessions reported.

The complexity and lack of genetic information for EPN can be reflected in misinterpretation of morphological and genetic data, indicating that more Loci should be evaluated to increase the accuracy for species boundaries and definition, also for genetic diversity present in these organisms that currently are taking more interest as a potential source of biological control.

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2.8. Annex

113 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Table 14. Weevil Samples inclded in the analysis

Consecutive Species Municipality State of Development Consecutive Species Municipality State of Development

1 C. sordidus** Obando Adult 26 M. hemipterus** El Cairo Larvae

2 C. sordidus** Obando Pupa 27 M. hemipterus** El Cairo Larvae

3 C. sordidus* Argelia Adult 28 M. hemipterus** El Cairo Larvae

4 C. sordidus* Argelia Adult 29 M. hemipterus** El Cairo Larvae

5 C. sordidus* Argelia Adult 30 M. hemipterus** El Cairo Larvae

6 C. sordidus* Argelia Adult 31 M. hemipterus** El Cairo Larvae

7 C. sordidus** Argelia Adult 32 M. hemipterus** Argelia Larvae

8 C. sordidus* Argelia Adult 33 M. hemipterus** Argelia Larvae

9 C. sordidus* Argelia Adult 34 M. hemipterus** Argelia Larvae

10 C. sordidus** Argelia Adult 35 M. hemipterus** Sevilla Larvae

11 C. sordidus** Argelia Adult 36 M. hemipterus** Sevilla Larvae

12 C. sordidus** Argelia Adult 37 M. hemipterus** Sevilla Larvae

13 C. sordidus** Argelia Adult 38 M. hemipterus** Sevilla Larvae

14 C. sordidus** Argelia Adult 39 M. hemipterus** Sevilla Larvae

15 C. sordidus** Argelia Adult 40 M. hemipterus** Sevilla Larvae

16 C. sordidus** Argelia Adult 41 M. hemipterus** Sevilla Pupa

17 C. sordidus** Argelia Adult 42 M. hemipterus** Sevilla Pupa

18 C. sordidus** Argelia Adult 43 M. hemipterus** Sevilla Pupa

19 C. sordidus** Argelia Adult 44 M. hemipterus** Cria Larvae

20 C. sordidus** Argelia Adult 45 M. hemipterus** Cria Larvae

21 C. sordidus** Argelia Adult 46 M. hemipterus** Cria Larvae

22 C. sordidus** Argelia Adult 47 M. hemipterus** Cria Larvae

23 M. hemipterus** El Cairo Larvae 48 M. hemipterus** Buenaventura Adult

24 M. hemipterus** El Cairo Larvae 49 M. hemipterus** Buenaventura Adult

25 M. hemipterus** El Cairo Larvae 50 M. hemipterus** Obando Larvae *Samples sequenced for COI mtDNA **Samples sequenced for both COI mtDNA and 28S rDNA ***Samples sequenced for 28S rDNA

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Continuation of table 14 State of State of Consecutive Species Municipality Development Consecutive Species Municipality Development

51 M. hemipterus** Argelia Adult 76 Metamasius sp.** Caicedonia Adult

52 M. hemipterus** Argelia Adult 77 Metamasius sp.** Obando Pupa

53 M. hemipterus** Argelia Adult 78 Metamasius sp.** Buga Adult M. 54 hemipterus*** Argelia Adult 79 Metamasius sp.** Adult Adult M. 55 hemipterus*** Argelia Adult 80 Metamasius sp.** Adult Adult Metamasius 56 sp.** Yotoco Larvae 81 Metamasius sp.** Adult Adult Metamasius 57 sp.** Yotoco Larvae 82 Metamasius sp.** Adult Adult Metamasius 58 sp.** Yotoco Larvae 83 Metamasius sp.** Adult Adult Metamasius 59 sp.** Yotoco Larvae 84 Metamasius sp.** Adult Adult Metamasius 60 sp.** Yotoco Larvae 85 Metamasius sp.** Adult Adult Metamasius 61 sp.** Yotoco Larvae 86 Metamasius sp.** Adult Adult Metamasius 62 sp.** Yotoco Larvae 87 Metamasius sp.** Adult Adult Metamasius 63 sp.** Yotoco Larvae 88 Metamasius sp.** Adult Adult Metamasius 64 sp.** Yotoco Larvae 89 Metamasius sp.** Adult Adult Metamasius 65 sp.** Yotoco Larvae 90 Metamasius sp.** Adult Adult Metamasius 66 sp.** Yotoco Larvae 91 Metamasius sp.* Adult Adult Metamasius Polytus 67 sp.** Yotoco Larvae 92 mellerborgii** Palmira Adult Metamasius Polytus 68 sp.** El Cairo Larvae 93 mellerborgii** Palmira Adult Metamasius Polytus 69 sp.** Argelia Larvae 94 mellerborgii** Palmira Adult Metamasius Polytus 70 sp.** Argelia Larvae 95 mellerborgii** Palmira Adult Metamasius Polytus 71 sp.** Argelia Larvae 96 mellerborgii** Caicedonia Adult Metamasius Polytus 72 sp.** Argelia Larvae 97 mellerborgii** Caicedonia Adult Metamasius Polytus 73 sp.** Argelia Larvae 98 mellerborgii** Palmira Adult Metamasius 74 sp.** Argelia Larvae 99 Polytus mellerborgii* Caicedonia Adult Metamasius 75 sp.** Roldanillo Adult 100 Polytus mellerborgii* Caicedonia Adult

101 Polytus mellerborgii* Palmira Adulto

*Samples sequenced for COI mtDNA **Samples sequenced for both COI mtDNA and 28S rDNA ***Samples sequenced for 28S rDNA

115 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Table 15. UN isolates for Heterorhabditis nucleotide alignment

* No changes in nucleotide position. – Gaps.

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Table 16. UN isolates for Steinernema nuclotide alignment

* No changes in nucleotide position

117 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

Continuation of table 16

* No changes in nucleotide position

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2.9. References

119 Molecular Characterization and Genetic Diversity of Entomopathogenic Nematodes, Rhabditida: (Steinernematidae and Heterorhabditidae), in Valle del Cauca as a Source for Biological Control

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