Fasciola Gigantica, F. Hepatica and Fasciola Intermediate Forms: Geometric Morphometrics and an Artificial Neural Network to Help Morphological Identification
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Fasciola gigantica, F. hepatica and Fasciola intermediate forms: geometric morphometrics and an artificial neural network to help morphological identification Suchada Sumruayphol1,*, Praphaiphat Siribat2,*, Jean-Pierre Dujardin3, Sébastien Dujardin3, Chalit Komalamisra4 and Urusa Thaenkham5 1 Department of Medical Entomology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand 2 Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand 3 IRD, UMR, INTERTRYP IRD, CIRAD, University of Montpellier, Montpellier, France 4 Mahidol-Bangkok School of Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand 5 Department of Helminthology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand * These authors contributed equally to this work. ABSTRACT Background. Fasciola hepatica and F. gigantica cause fascioliasis in both humans and livestock. Some adult specimens of Fasciola sp. referred to as ``intermediate forms'' based on their genetic traits, are also frequently reported. Simple morphological criteria are unreliable for their specific identification. In previous studies, promising phenotypic identification scores were obtained using morphometrics based on linear measurements (distances, angles, curves) between anatomical features. Such an approach is commonly termed ``traditional'' morphometrics, as opposed to ``modern'' morphometrics, which is based on the coordinates of anatomical points. Methods. Here, we explored the possible improvements that modern methods of morphometrics, including landmark-based and outline-based approaches, could Submitted 8 August 2019 bring to solving the problem of the non-molecular identification of these parasites. Accepted 18 January 2020 Published 18 February 2020 F. gigantica and Fasciola intermediate forms suitable for morphometric characterization were selected from Thai strains following their molecular identification. Specimens Corresponding author Urusa Thaenkham, of F. hepatica were obtained from the Liverpool School of Tropical Medicine (UK). [email protected] Using these three taxa, we tested the taxonomic signal embedded in traditional linear Academic editor measurements versus the coordinates of anatomical points (landmark- and outline- Laura Wilson based approaches). Various statistical techniques of validated reclassification were used, Additional Information and based on either the shortest Mahalanobis distance, the maximum likelihood, or the Declarations can be found on artificial neural network method. page 20 Results. Our results revealed that both traditional and modern morphometric ap- DOI 10.7717/peerj.8597 proaches can help in the morphological identification of Fasciola sp. We showed that the accuracy of the traditional approach could be improved by selecting a subset of Copyright 2020 Sumruayphol et al. characters among the most contributive ones. The influence of size on discrimination by shape was much more important in traditional than in modern analyses. In our Distributed under study, the modern approach provided different results according to the type of data: Creative Commons CC-BY 4.0 satisfactory when using pseudolandmarks (outlines), less satisfactory when using OPEN ACCESS How to cite this article Sumruayphol S, Siribat P, Dujardin J-P, Dujardin S, Komalamisra C, Thaenkham U. 2020. Fasciola gigantica, F. hepatica and Fasciola intermediate forms: geometric morphometrics and an artificial neural network to help morphological identification. PeerJ 8:e8597 http://doi.org/10.7717/peerj.8597 landmarks. The different reclassification methods provided approximately similar scores, with a special mention to the neural network, which allowed improvements in accuracy by combining data from both morphometric approaches. Conclusion. We conclude that morphometrics, whether traditional or modern, represent a valuable tool to assist in Fasciola species recognition. The general level of accuracy is comparable among the various methods, but their demands on skills and time differ. Based on the outline method, our study could provide the first description of the shape differences between species, highlighting the more globular contours of the intermediate forms. Subjects Mathematical Biology, Parasitology, Taxonomy, Zoology Keywords Fasciola, Molecular identification, ITS1&ITS2 markers, Morphometrics, Artificial neural networks INTRODUCTION Fasciola hepatica Linnaeus, 1758 and F. gigantica Cobbold, 1855 are well-known as parasites that cause fascioliasis (Mas-Coma, Bargues & Valero, 2005). The parasites belong to the family Fasciolidae Railliet, 1895, subfamily Fasciolinae Stiles & Hassall, 1898. The adult worm infects the liver of various species of mammals, particularly livestock that consume fresh plant material contaminated with infective-stage metacercaria (Mas-Coma, Bargues & Valero, 2018). Climatic changes seem to have exacerbated the problem by expanding the geographic distribution of such parasites (Mas-Coma, Valero & Bargues, 2008; Mas-Coma, Valero & Bargues, 2009a). Typically, F. hepatica is reported worldwide, while F. gigantica occurs in a narrower range across Asia and Africa. The geographic distribution of these two parasites can overlap, particularly in the equatorial zone. The hybrid forms that can result between F. hepatica and F. gigantica are often reported as Fasciola ``intermediate forms'' (Periago et al., 2008; Mas-Coma, Valero & Bargues, 2009a; Mas-Coma, Valero & Bargues, 2009b). Like other countries in the tropical and subtropical areas, Thailand has reported Fasciola infections in both humans and livestock (Mas-Coma, Valero & Bargues, 2009a; Buranasin & Harinasuta, 1970; Srihakim & Pholpark, 1991; Aroonroch et al., 2006; Kanoksil et al., 2006; Tippawangkosol et al., 2017; Wannasan et al., 2014). Up until now, traditional morphometrics, which is based on linear measurements between anatomical landmarks, has been used to help in the identification of Fasciola species (Valero, Panova & Mas-Coma, 2005). Many factors have been noted which can modify the accuracy of phenotypical classification done in this way, including: (1) lymnaeid-host specificity, (2) bias arising from different types of definitive hosts, the technical bias for worm fixing, (3) the computerized image analysis system used, (4) the standardized methodology used for measurements, and (5) the effect of allometric growth (Valero, Panova & Mas-Coma, 2005; Periago et al., 2006). Size and some other variables or ratios that have been erroneously considered as a proxy for ``shape'' (body roundness (BR D BP2/4 πBA; BP D body perimeter; and BA D body area) could discriminate between adult F. hepatica, F. gigantica, and Fasciola intermediate forms collected from different countries Sumruayphol et al. (2020), PeerJ, DOI 10.7717/peerj.8597 2/25 in Asia (Periago et al., 2006), as well as being used to examine intraspecific diversity (Periago et al., 2008). A molecular identification technique was developed to discriminate between fasciolid adult worms based on ribosomal internal transcribed spacers (ITS) 1 and 2 (Lin et al., 2007; Lotfy et al., 2008). According to Amer et al. (2011), the identification of fasciolids requires at least ITS2 and mitochondrial cox1 or nad1 sequences. Itagaki et al. (2011) suggested that ITS1 sequences, which do not show variation in Europe or Oceania, are nonetheless useful molecular markers for discriminating F. hepatica, F. gigantica, and their hybrids occurring in Asia (Amer et al., 2011). In Thailand, Fasciola intermediate forms were found in the livers of cattle in slaughterhouses and identified as hybrids because of the heterosequences of nuclear ribosomal ITS1 and ITS2 (Chaichanasak et al., 2012; Siribat et al., 2018). For molecular discrimination between F. gigantica, F. hepatica, and Fasciola intermediate forms, ITS1 has been noted as the most effective DNA marker (Chaichanasak et al., 2012). Fasciola intermediate forms present no qualitative morphological attributes that allow clear identification. Alongside molecular discrimination techniques, traditional morphometrics has been suggested as a relatively simple and effective approach for species identification (Periago et al., 2006; Valero, Marcos & Mas-Coma, 1996; Valero, Panova & Mas-Coma, 2005; Ashrafi et al., 2006; Afshan et al., 2014). However, the dimensions of Fasciola intermediate forms may overlap with those of both F. gigantica and F. hepatica (Periago et al., 2006; Srimuzipo et al., 2000). Even when using many characters and multivariate statistical tools, the risk of using a morphometrics method is that linear distance measurements mainly provide information relating to size and provide limited information about shape. Previous studies inaccurately labeled as ``shape'' some variables which are actually another estimation of size, such as body roundness (BR = BP2/4πBA), body perimeter (BP), and body area (BA) (Periago et al., 2006; Mas-Coma, Valero & Bargues, 2009b; Valero et al., 2018). These characters are secondary constructions from linear measurements and produce variables redundant with size (Burnaby, 1966). A more convenient approach has recently been applied which enables variations in shape to be estimated from linear measurements (Valero et al., 2018). However, there are various techniques available that can be used for this. A comprehensive review was recently published distinguishing two ``schools'' via which it is possible to approach the allometric concept: the Huxley–Jolicoeur and the Gould–Mosimann