DNA-barcoding of forensically important blow flies (Diptera: Calliphoridae) in the Caribbean Region

Introduction

Forensic entomology is the application of the study of insects in legal investigations. Although several groups of insects, mainly of the orders Diptera and Coleoptera, are associated with cadaveric decomposition, blow flies (Diptera: Calliphoridae) are among the most dominant and conspicuous insects in the decomposition process (Catts, 1992). They are useful to determine time of death and, in particular situations, cause of death (Goff, 2000) or relocation of a body (Matuszewski, Szafalowicz & Jarmusz, 2013). During the last five decades of intensive studies in forensic entomology (Byrd & Castner, 2010; Catts & Haskell, 1990; Goff, 2000; Smith, 1986; Tomberlin & Benbow, 2015), the acceptance of insects as evidence in legal investigations has increased gradually and they are now included as standard operating procedures in crime scene investigations in many countries (Tomberlin & Benbow, 2015). Determining the post mortem interval (PMI) is one of the most important tasks during an investigation, and the use of immature stages of Calliphoridae is essential whenever time of death is difficult to establish based on other means (Catts & Haskell, 1990). Although the accurate determination of PMI and period of insect activity (PIA) depend of several factors that are discussed in detail by Catts (1992), the first one, and most important to resolve, is the correct identification of the specimens found at the crime scene. As each species has a specific developmental rate and range of distribution, the accurate identification of insects, mainly the larval stages, is critical because the incorrect determination will invalidate the estimated post mortem interval and impact other interpretations of the evidence (Goff, 2000; Wells & LaMotte, 2001).

Morphology is most commonly used to identify adult insects involved in cadaveric decomposition and taxonomic keys are available for most of the Calliphoridae species. In general, these taxonomic keys include the detailed description of the male and female genitalia, which is examined when external characteristics are not sufficient to establish identity (Tantawi, Whitworth & Sinclair, 2017; Whitworth, 2010; Whitworth, 2014; Whitworth & Rognes, 2012). Identification of immature stages (eggs, larvae and pupae) is more challenging, but possible when detailed taxonomic descriptions exist (Greenberg & Szyska, 1984; Sukontason et al., 2005; Szpila et al., 2013a; Szpila et al., 2014; Szpila & Villet, 2011; Wells, Byrd & Tantawi, 1999). However, in places like the Caribbean, where forensic entomology has not yet been developed, this approach is limited due to the lack of detailed descriptions of immature stages. For instance, from the 18 forensically important calliphorid species currently recognized in the Caribbean, plus the most important livestock pest parasite in the Americas, C. hominivorax (Whitworth, 2010), only eight have been documented well enough to be identified based on larvae, mainly using morphology of the third instar (Florez & Wolff, 2009; Wells, Byrd & Tantawi, 1999). For the other species, the identification of immature specimens would need to be done by rearing them to adulthood (Goff, 2000), which is time consuming, may delay legal investigations, and relies on the survival of larvae in the laboratory. Given local endemism, the scarce studies on this group in the Caribbean, and the lack of knowledge of immature stages for at least 11 species, developing alternative tools for identification is important.

With the advances in molecular methods, DNA barcoding has become a widely used technique for species delimitation and identification. This approach allows the identification of specimens during any development stage, including incomplete or damaged specimens, does not require taxonomic expertise, and it is also useful to recognize cryptic species that morphological approaches may not detect (Hebert et al., 2003; Hebert et al., 2004a; Hebert et al., 2004b). Worldwide many authors have used this method to identify species of the family Calliphoridae and these studies showed the potential of the ‘standard barcoding gene’ cytochrome c oxidase subunit I (COI) to distinguish between forensically significant species (Aly & Wen, 2013; Chen et al., 2009; Harvey et al., 2003; Liu et al., 2011; Nelson, Wallman & Dowton, 2007; Wells & Williams, 2007). However, COI does not reliably distinguish among certain closely related calliphorid species, specifically Chrysomya saffranea and Ch. megacephala (Harvey et al., 2008; Nelson, Wallman & Dowton, 2007), Ch. semimetalica and Ch. latifrons (Nelson, Wallman & Dowton, 2007), Calliphora stygia and C. albifrontalis, C. dubia and C. augur (Harvey et al., 2008; Wallman & Donnellan, 2001), C. aldrichia and C. montana (Tantawi, Whitworth & Sinclair, 2017), Cochliomyia macellaria and Co. aldrichi (Yusseff-Vanegas & Agnarsson, 2016), Lucilia mexicana and L. coeruleiviridis (DeBry et al., 2013; Whitworth, 2014), L. bazini and L. hainanenesis (Chen et al., 2014), L. illustris and L. caesar (Reibe, Schmitz & Madea, 2009; Sonet et al., 2012), L. cuprina and L. sericata (Williams & Villet, 2013). Given the serious implications of misidentification of forensic insects, an improved protocol for accurate identification is necessary. We propose using the nuclear internal transcribed spacer ITS2 as a second barcoding locus for taxonomic species determinations in calliphorids as suggested by GilArriortua et al. (2014). Although evaluations of ITS2 as unique identification marker have limitations for some taxa (Agnarsson, 2010), several studies have shown the potential application of ITS2 for blowfly species identification (Jordaens et al., 2013a; Nelson, Wallman & Dowton, 2007; Nelson, Wallman & Dowton, 2008, Song, Wang & Liang, 2008; Yusseff-Vanegas & Agnarsson, 2016). We expect a combination of barcodes from the nuclear and mitochondrial genomes to offer a general, simple and reliable way of identifying forensically important insects, even problematic sister species, as successfully done in certain other arthropod groups (Anslan & Tedersoo, 2015; Cao et al., 2016).

The success of DNA barcoding directly links to the quality of the underlying database (Candek & Kuntner, 2015; Coddington et al., 2016; DeBry et al., 2013; Harvey et al., 2003) not only in terms of the quality of identifications but also in terms of taxon sampling (species, geographic localities, populations). Existing efforts in this respect are lacking for Calliphoridae in the Caribbean, limiting the reliability of this technique for delimitation of species. Hitherto, three studies have included molecular data of a few Calliphoridae from the Caribbean (McDonagh, Garcia & Stevens, 2009; Whitworth, 2014; Yusseff-Vanegas & Agnarsson, 2016); they lack the geographic variation necessary to estimate the ratio between intraspecific variation and interspecific divergence from which barcoding accuracy depends (Meyer & Paulay, 2005). Our study provides the first thorough molecular study of Caribbean Calliphoridae.

Our aims are: (1) to establish COI barcode libraries for all Caribbean species and to test if barcodes offer reliable means of their identification, (2) to assess the usefulness of ITS2 as a second barcoding locus in species delimitation and identification, and, (3) to improve online databases with sequences from the Caribbean, including specimens from multiple localities in each island covering the geographic range for each species. To achieve these goals, we sampled 468 specimens of Calliphoridae representing 19 species.

Methods

Specimens and DNA extraction

A total of 473 specimens were included in this study. Of these, 468 represented ingroup taxa and five represented outgroup taxa from the family Sarcophagidae (Sarcophaga Carnaria Linnaeus, 1758; Neobellieria bullata Parker, 1916; Ravinia stimulans Walker, 1849; Blaesoxipha masculina Aldrich, 1916 and Blaesoxipha alcedo Aldrich, 1916). We used a total of 600 DNA sequences and we obtained 521 (COI  = 398, ITS2  = 123) while 79 (COI  = 44, ITS2  = 35) were previously published (Table 1). The specimens were collected throughout the Caribbean (Fig. 1) from between 2011 and 2013 (see Table 1 for details). All specimens were collected under appropriate permits: USA, Florida, Everglades, United States Department of the Interior National Park Service EVER-2013-SCI-0028; Puerto Rico, DRNA: 2011-IC-035 (O-VS-PVS15-SJ-00474-08042011); Jamaica, NEPA, reference number #18/27; USA, USDI National Park Service, EVER-2013-SCI-0028; Costa Rica, SINAC, pasaporte científico no. 05933, resolución no. 019-2013-SINAC; Cuba, Departamento de Recursos Naturales, PE 2012/05, 2012003 and 2012001; Dominican Republic, Ministerio de Medio Ambiente y Recursos Naturales, no 0577; Colombia, Authoridad Nacional de Licencias Ambientales, 18.497.666 issued to Alexander Gómez Mejía; Saba, The Executive Council of the Public Entity Saba, no 112/2013; Martinique, Ministère de L’Écologie, du Développement Durable, et de L‘Énergie; Nevis, Nevis Historical & Conservation Society, no F001; Barbados, Ministry of Environment and Drainage, no 8434∕56∕1 Vol. II. Although L. vulgata, L. mexicana and L. coeruleiviridis are not present in the Caribbean islands, they are included as outgroups to the Calliphoridae from the West Indies. James (1970) reported L. coeruleiviridis from Cuba, however, this is likely an error as no specimens have been seen in collections from the region (Whitworth, 2010) and no specimens were collected during this study. All specimens, except the ones from Mexico, were collected using a novel trap designed for this study. We modified a standard butterfly trap by adding a conic form on the top with a vessel attached to the highest point like in the Malaise trap. Flies entered the trap attracted by the bait (chicken) and funneled into the collecting vessel containing 95% ethanol. Traps were hung 1m off the ground and were used to collect flies for 2–3 days at each locality. These traps proved efficient in collecting specimens for our molecular purposes, given that caught specimens were preserved in ethanol while the trap remained in the field. Collected specimens were transferred to Whirl-paks with 95% ethanol and stored at −20 °C. Adults were identified using the Whitworth (2010) taxonomic keys and the specimens with uncertain identity were sent to Dr. Whitworth at Washington State University for detailed examination and species confirmation. DNA was isolated from thoracic muscle or two legs of each individual with the QIAGEN DNeasy Tissue Kit (Qiagen, Inc., Valencia, CA). The remainder of the specimen was retained as a voucher currently held by the Agnarsson Lab; they will be placed in the Zadock Thompson Zoological Collections at the UVM Natural History Museum following completion of other studies currently being conducted using the material.

Species delimitation

We used MEGA6 to calculate genetic distances within and among species level clades suggested by the barcoding analysis of the COI data and by morphology. We used the species delimitation plugin in Geneious 8.1.5 (Kearse et al., 2012; Masters, Fan & Ross, 2011) to estimate species limits under Rosenberg’s reciprocal monophyly P(AB) (Rosenberg, 2007) and Rodrigo’s P(RD) method (Rodrigo et al., 2008). For this analysis we used a 317 taxa subset of our data, produced by reducing the most densely sampled species like Co. minima, Co. macellaria, Ch. rufifacies and L. retroversa to 38 exemplars since P(RD) probability cannot be computed when there are more than 40 exemplars per clade. We also estimated the probability of population identification of a hypothetical sample based on the groups being tested P ID (Strict) and P ID (Liberal). The genealogical sorting index (gsi) statistic (Cummings, Neel & Shaw, 2008) was calculated using the gsi webserver (http://genealogicalsorting.org) on the estimated tree. As genetic distances in MEGA6, gsi and species delimitation metrics from Geneious require a priory species designation, 26 putative species were assigned to the data based on combined analysis of phylogenetic topology from COI and morphological and geographic information. Finally, we used a single locus Bayesian implementation (bPTP) of the Poisson tree processes model (Zhang et al., 2013) to infer putative species boundaries on a given single locus phylogenetic input tree available on the webserver: http://species.h-its.org/ptp/. The analysis was run as a rooted tree from the MrBayes analysis, for 500,000 generations with 10% burnin removed. For gsi and bPTP analysis we reduced the data to 103 taxa representing the 26 putative species because of limitations of the server.

Results

We present by far the most extensive DNA barcoding dataset of Calliphoridae from the Caribbean. It includes a ∼1,200 bp fragment of the mitochondrial COI gene from 437 Calliphoridae specimens and ∼450 bp of the ITS2 gene from 158 specimens chosen to represent unique COI haplotypes of all putative species and all localities (20 different islands in the Caribbean plus Florida, Colombia and Mexico). Ninety nine of the sequences are from specimens collected in the mainland and the other 496 are from the Caribbean Islands. In total, we included 19 species of Calliphoridae identified morphologically (Whitworth, 2006; Whitworth, 2010), 16 of them reported from the Caribbean and three species, L. coeruleiviridis, L. mexicana and L. vulgata, from the mainland. The sequences from the Caribbean represent 16 of the 18 species of forensically important Calliphoridae that occur in the West Indies plus one of the most important livestock pest parasites in the Americas, C. hominivorax (Whitworth, 2010). The two species not included in this dataset are reported from Bahamas (Phormia regina) and Trinidad (Hemilucilia segmentaria), where we were not able to sample. For most species we included numerous exemplars, covering the geographic range of each species in the region.

Discussion

Accurate identification of insects is a crucial step to using them as reliable evidence in legal investigations. Although morphology has been successfully used to identify immature specimens involved in cadaveric decomposition (Cardoso et al., 2014; Florez & Wolff, 2009; Szpila et al., 2013a; Szpila et al., 2013b; Szpila et al., 2014; Szpila & Villet, 2011; Wells, Byrd & Tantawi, 1999), this approach depends on the availability of taxonomic keys of the species present in the region. In the Caribbean, the immature stages of 11 species are unknown and other approaches are needed in order to identify them. Besides this, morphology may overlook potentially cryptic species and cannot be used on incomplete or destroyed specimens found on a crime scene. Here, we show DNA barcoding to be useful in overcoming these problems and provide tools to accelerate the identification and discovery of species. This is particularly important in areas like the Caribbean, where studies of insects involved in cadaveric decomposition are scarce (Whitworth, 2010; Yusseff-Vanegas & Agnarsson, 2016; Yusseff-Vanegas, 2007; Yusseff-Vanegas, 2014). One of the first steps required for this approach is creating a reliable DNA barcode database that can be used with confidence in order to identify unknown specimens found in death scenes investigation (DeBry et al., 2013; Harvey et al., 2003).

The success of DNA barcoding relies on the quality of the underlying database used to compare DNA sequences of new samples. A good database should contain DNA barcodes of expertly identified individuals, and preferably taxon sampling covering the distribution range of each species. Our study complies with both requirements and is the first thorough molecular study of Calliphoridae from the Caribbean. It includes a representative collection from all but two forensically relevant Calliphoridae from the region, and covers the whole geographic range of most of the investigated species (Table 1). All specimens in this study were carefully identified using traditional morphological taxonomy (Whitworth, 2006; Whitworth, 2010; Whitworth, 2014) and each individual was successfully allocated to one of the currently recognized calliphorid species, except for specimen CO027 that could only be identified to the genus level. Although morphological identification of specimens collected in this study corresponded to 19 previously reported species (Whitworth, 2010), our results based on molecular data indicate higher diversity. In all, 26 putative species lineages were identified, and in particular our results indicate that Lucilia and Chloroprocta are more diverse than suggested by current taxonomy. COI recovered substantial geographic variation for C. idioidea, L. eximia, L. retroversa and L. rica such that molecular data indicate up to eleven putative species lineages that cannot be, or at least have not been, recognized by morphology.

Lucilia eximia is considered a widespread species found from the southern United States through Central America to southern South America (Whitworth, 2014). Nevertheless, our molecular results show four distinct genetic clusters with an average inter-cluster divergence from 2.5 to 7.4% (Table 3). The clusters are geographically structured and three of them are widely separated (Fig. 2, Fig. S1). The first one is the Greater Antilles cluster (GA) that includes specimens from Puerto Rico, Mona Island and Dominican Republic, the second is a small cluster that includes specimens from Florida (FL), the third one contains specimens from Colombia and Mexico (CO-MEX), and the fourth contains specimens from the Lesser Antilles islands of Dominica and Saint Lucia (LA). Similar results were reported by Solano, Wolff & Castrol (2013) and Whitworth (2014) where widely separate clades of L. eximia were found using DNA barcodes. All species delimitation methods supported the uniqueness and genetic isolation of the four clades, each showing low intra-clade divergence (<1%, Table 4), and thus likely representing four distinct species. Although we found some morphological variation between L. eximia from the mainland and islands and among islands as previously reported (James, 1967; Whitworth, 2010; Woodley & Hilburn, 1994), detailed revision of those specimens by Dr. Whitworth from Washington State University concluded that there is not enough evidence to separate them as different morphological species, suggesting they may be morphologically cryptic species. Further studies on these populations will be necessary to establish their taxonomic status.

Lucilia rica was collected throughout the Lesser Antilles and is very abundant in most of the islands (personal observation). Although James (1970) listed this species from Puerto Rico, we did not find any specimens after very extensive collections on the island. Thus, we believe that L. rica is restricted to the Lesser Antilles and has not dispersed beyond Anguilla. Whitworth (2010) reported this species from Antigua, Bermuda, Guadalupe and St. Lucia; however, we found it in eight more islands (Table 1) and our data showed two geographic clusters (Figs. 2, 4; Figs. S1, S3). The first cluster (L. rica-1) contains specimens from St Martin, Saba, St. Eustatius, St. Kitts, Nevis and Martinique and the second one (L. rica 2) from Barbuda, Antigua, Montserrat and Guadeloupe. Although the genetic distance between clades is low (1%), it is much greater than the intra-clade divergences (<0.3%). While all species delimitation methods support the possibility of two different species (Tables 5 and 6), we did not find morphological evidence to support it. Nevertheless, given that this is the most abundant Lucilia species of the Lesser Antilles, additional studies on these populations are important to determine if the genetic difference is due to intraspecific variation or if they are cryptic species.

For Lucilia retroversa we find two geographic clusters, one from Cuba and one from the Dominican Republic with an average mtDNA distance of 2.5% (Table 3) and with low intra-clade divergence (<0.2%, Table 4). Whitworth (2010) reported some morphological differences between specimens from Bahamas (which share morphology with Cuban specimens) and the Dominican Republic, but after examination of male and female genitalia he concluded that those differences were intraspecific variation. However, he noticed that our L. retroversa specimens have a brown basicosta instead of white or yellow basicosta which is an important character used to separate L. retroversa from other species (see taxonomic key in Whitworth, 2010). Given that all of our species delimitation results support two possible cryptic species, we recommend further detailed molecular and morphological studies of these populations to determine if they merit the description of a separate species.