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Morphology, Systematics, Evolution
DNA Barcoding Reveals Hidden Diversity of Sand Flies
(Diptera: Psychodidae) at Fine and Broad Spatial Scales in
Brazilian Endemic Regions for Leishmaniasis
Bruno Leite Rodrigues,
1,2,4Luís Fernando Carvalho-Costa,
2Israel de Souza Pinto,
3and
José Manuel Macário Rebêlo
11Laboratório de Entomologia e Vetores da Universidade Federal do Maranhão (LEV-UFMA), Avenida dos Portugueses, 1966, Bacanga, São Luís, Maranhão 65080–805, Brazil, 2Laboratório de Genética e Biologia Molecular da Universidade Federal do Maranhão (LabGeM-UFMA), Avenida dos Portugueses, 1966, Bacanga, São Luís, Maranhão 65080–805, Brazil, 3Unidade de Medicina Tropical, Universidade Federal do Espírito Santo, Marechal Campos Ave., Av. Fernando Ferrari, 514 - Goiabeiras, Vitória, Espirito Santo 29075–073, Brazil, and 4Corresponding author, e-mail: [email protected]
Subject Editor: Richard Wilkerson
Received 6 October 2017; Editorial decision 7 February 2018
Abstract
Sand fly (Diptera: Psychodidae) taxonomy is complex and time-consuming, which hampers epidemiological efforts directed toward controlling leishmaniasis in endemic regions such as northeastern Brazil. Here, we used a fragment of the mitochondrial cytochrome c oxidase I (COI) gene to identify sand fly species in Maranhão State (northeastern Brazil) and to assess cryptic diversity occurring at different spatial scales. For this, we obtained 148 COI sequences of 15 sand fly species (10 genera) from Maranhão (fine spatial scale), and joined them to COI sequences from other Brazilian localities (distant about 2,000 km from Maranhão, broad spatial scale) available in GenBank. We revealed cases of cryptic diversity in sand flies both at fine (Lutzomyia longipalpis (Lutz and Neiva) and Evandromyia termitophila (Martins, Falcão and Silva)) and broad spatial scales (Migonemyia migonei (França), Pressatia choti (Floch and Abonnenc), Psychodopygus davisi (Root), Sciopemyia sordellii (Shannon and Del Ponte), and Bichromomyia flaviscutellata (Mangabeira)). We argue that in the case of Bi. flaviscutellata, the cryptic diversity is associated with a putative new species. Cases in which DNA taxonomy was not as effective as morphological identification possibly involved recent speciation and/or introgressive hybridization, highlighting the need for integrative approaches to identify some sand fly species. Finally, we provide the first barcode sequences for four species (Brumptomyia avellari (Costa Lima), Evandromyia infraspinosa (Mangabeira), Evandromyia evandroi (Costa Lima and Antunes), and Psychodopygus complexus (Mangabeira)), which will be useful for further molecular identification of neotropical species.
Key words: COI, Phlebotominae, taxonomy, vectors
More than 500 species of sand flies (Diptera: Psychodidae: Phlebotominae) belonging to 23 genera (Shimabukuro et al. 2017) are currently recognized in the Americas. Some of these species are vectors of protozoan pathogens such as Leishmania, the etiologic agent of leishmaniasis (Maroli et al. 2013, Ready 2013, Brazil et al. 2015, Rêgo et al. 2015).
Brazil hosts the greatest diversity of sand flies in the Americas (Young and Duncan 1994, Shimabukuro et al. 2017), possibly due to its extensive area and variety of biomes. The Maranhão State, in northeastern Brazil, also presents a rich sand fly fauna (Rebêlo et al. 2010a) and multiple areas with high incidence of autoch-thonous cutaneous leishmaniasis (CL) and visceral leishmaniasis (VL) (Martins et al. 2004, Silva et al. 2008, Júnior et al. 2009). In 2016 alone, 833 cases of CL and 655 cases of VL were reported for
Maranhão (Ministry of Health 2015). This high incidence is mainly due to the presence of the Amazonian and Cerrado forest biomes and ecotone areas that, in addition to hosting a large number of sand fly species, hosts vertebrate reservoirs of a wide variety of Leishmania
species. The high density and species diversity of sand flies, together with autochthonous cases of the disease in rural areas close to inter-national tourism zones (Rebelo et al. 2010b, Júnior et al. 2009), like the Lençóis Maranhenses National Park, highlight the relevance of studies on these vectors.
Only some sand flies are pathogen vectors (Maroli et al. 2013); thus, entomological monitoring and species identification are needed to predict possible disease transmission foci and to adopt more effi-cient control measures (Bates et al. 2015). However, the available keys for morphological identification of phlebotomine species (e.g.,
doi: 10.1093/jme/tjy032 Advance Access Publication Date: 17 March 2018 Research Article
Young and Duncan 1994, Galati 2003) require mounting insects on slides for visualization of the diagnostic characters by microscopy, which is a time-consuming process that is dependent on the expertise of the taxonomist. Futhermore, because of very subtle morphological differences between cryptic species, separation may not be possible without the use of molecular analysis. Thus, these methods are being used more frequently for resolving systematic and taxonomic issues of sand flies, especially those based on sequencing of small DNA regions, like DNA barcoding (Araki et al. 2009, Depaquit 2014,
Grace-Lema et al. 2015).
DNA barcoding is among the most widely used tools for molecu-lar identification, where species delimitation is based on a fragment of the mitochondrial DNA gene cytochrome c oxidase subunit 1 (COI) (Hebert et al. 2003). This method depends on a reliable sequence database (BOLD Systems) and genetic distance-based algo-rithms for species delimitation (Ratnasingham and Hebert 2007,
2013). There are 229 sand fly species with barcode sequences (data from January 2017) from the Old and New World available in the database, which has increased the applicability of this tool for spe-cies identification (Krüger et al. 2011, Kumar et al. 2012, Scarpassa and Alencar 2013, Gutiérrez et al. 2014, Nzelu et al. 2015, Pinto et al. 2015, Polseela et al. 2015, Gajapathy et al. 2016, Romero-Ricardo et al. 2016, Sukantamala et al. 2016). However, sequences from additional sand fly species are needed to enhance the efficiency of molecular identification.
One challenge to this goal is that species delimitation by this method is not always efficient. For example, gene introgression events (Pinto et al. 2015) and low interspecific genetic divergence (Laurito et al. 2013) hamper species delimitation for some sand flies and mosquito species, respectively. However, in most cases, the suc-cess rate for identification reaches near 100% (Gutiérrez et al. 2014,
Romero-Ricardo et al. 2016, Gajapathy et al. 2016).
In addition to identifying specimens from known species, DNA barcoding also may foster the identification of new species, which is especially important for identifying species complexes among sand
flies (e.g., Pinto et al. 2015, Gajapathy et al. 2016). The identification of species complexes involving vectors is highly relevant from an epi-demiological viewpoint, since different species within the same com-plex may vary in vector competence (Maingon et al. 2008, Ready 2013). To this end, we used DNA barcoding to identify sand fly spe-cies from an endemic region of leishmaniasis in northeastern Brazil (Maranhão State), and to assess the cryptic diversity occurring on a fine (i.e., Maranhão) and broad spatial scales (i.e., Brazil).
Materials and Methods
Area of Study, Collection, and Morphological Identification of Specimens
Specimens were collected between 2013 and 2016 in six differ-ent municipalities located in differdiffer-ent biomes of Maranhão State (northeastern Brazil) with reported cases of leishmaniasis: São Luís (2°32′20′′ S; 44°16′58′′ W), São Domingos (5°34′30′′ S; 44°14′32′′
W), Barreirinhas (that harbours part of the Lençóis Maranhenses National Park) (2°45′32′′ S; 42°49′25′′ W), Alcântara (2°24′14′′
S; 44°24′55′′ W), Colinas (6°01′37′′ S; 44°14′48′′ W), and Itinga (4°08′58′′ S; 47°12′51′′ W) (Fig. 1). All geographic coordinates were obtained using Google Earth software (Google LLC) and represent the centroid of sampling sites distribution. The field sampling permit was provided by the System of Authorization and Information of Biodiversity - SISBIO (N. 46319-1), from Brazilian Ministry of the Environment.
Sand flies were collected from peri-domestic habitats, preferably near domestic animal shelters where the insects are found in greater abundance. CDC-type light traps were installed 1.5 m above ground from 18:00 to 6:00 o´clock of the following day. The captured insects were stored at −20°C until being processed. The heads and abdomens were removed and mounted on slides for morphological identification following Galati (2003). For the abbreviations of the genera, we followed the nomenclature of Marcondes (2007).
DNA Extraction, PCR, and Sequencing
Total DNA from each specimen was extracted from the remaining parts of sand flies (thorax, wings and legs) using the phenol-chlo-roform method (Sambrook and Russell 2001). Polymerase chain reaction (PCR) directed to the mitochondrial COI gene was car-ried out with a GoTaqFlexi DNA Polymerase kit (PROMEGA), fol-lowing the manufacturer’s instructions, and the primers LCO1490 (5′-GGTCAACAAATCATAAAGATATTGG-3′) and HCO2198 (5′-TAAACTTCAGGGTGACCAAAAAATCA-3′) (Folmer et al. 1994). The reactions were conducted in a thermal cycler under the following configurations: initial denaturation of 5 min (94°C); fol-lowed by 35 cycles at 94°C for 1 min, 47°C for 1 min, and 72°C for 1 min; and final extension of 72°C for 10 min. In each round of amplification, a negative control containing water instead of DNA was used. The amplification results were visualized on 1% agarose gel electrophoresis.
All positive samples presenting the expected amplicon size (700 base pairs [bp]) were purified with an ExoSap-IT kit (USB Corporation) according to the manufacturer’s instructions. The amplicons were sequenced on an ABI 3500 Genetic Analyzer (Applied Biosystems) using the Big Dye termination cycle sequenc-ing kit (Applied Biosystems) and the forward primer.
Data Analysis
The COI sequences were deposited in the BOLD Systems database (Ratnasingham and Hebert 2007) and are available in the “MABR Brazillian Northeast sandflies” project under process numbers MABR001-17 - MABR148-17.
The sequences were visualized and edited (trimming both 3′
and 5′ ends with poor base call quality) in the program BioEdit 5.0.9.0 (Hall 1999). Sequences alignment was done using ClustalW (Thompson et al. 1994) in the Mega 5 software (Tamura et al. 2011). We used DnaSP v5 (Librado and Rozas 2009) to obtain the number of haplotypes per species. Genetic distances were estimated using the Kimura-2-parameters model (K2P) (Kimura 1980), and were used to build a Neighbor-Joining (NJ) tree in Mega 5 (1,000 boot-straps). Following Hall (2001) and Schneider (2003), we considered as high bootstrap values to be those greater than 90% and moder-ate ones those between 70% and 89%. As outgroups, we used COI
sequences of Culicoides obsoletus (Meigen) (ASDIP607-15), Aedes albopictus (Skuse) (GBDCU001-12), and Culex quinquefasciatus
(Say) (CYTC706-12) from GenBank (NCBI, National Center for Biotechnology Information) (access numbers for outgoup sequences are in parentheses).
The existence of a barcode gap (gap between intra and inter-specific genetic distances) were checked by a histogram of genetic distance frequencies. The DNA barcoding method is more powerful for species delimitation when the intraspecific distances are smaller than the interspecific ones, i.e., with a barcode gap (Wiemers and Fiedler 2007).
The sequences of each specimen were identified at the Operational Taxonomic Unit (OTU) level, which, in the case of molecular data, are clusters of organisms sorted according to their similarities at a specific taxonomic marker gene (Blaxter et al. 2005). We used two algorithms to identify OTUs: the Refined Single Linkage (RESL) (Ratnasingham and Hebert 2013) and the Automatic Barcode Gap Discovery (ABGD) (Puillandre et al. 2012). The RESL algorithm (BOLD Systems) partitions the DNA barcode sequences into OTUs, linking the sequences into clusters and then optimizing them with a graphic analytical approach using a Markov Clustering (MCL) model (Ratnasingham and Hebert 2013). The ABGD algorithm (available at http://www.abi.snv.jussieu.fr/public/abgd/abgdweb.
html) organizes the sequences into hypothetical species according to the distribution of nucleotide distances between them (Puillandre et al. 2012). For the RESL, we used the default configuration for the parameters, while for ABGD, the values Pmin = 0.005, Pmax = 0.1 and X = 1.0 were used, which are the most efficient values for taxa delimitation by this algorithm (Ratnasingham and Hebert 2013). For the distinction of OTUs using ABGD, only partitions with prior intraspecific divergence (P) between 1.0% and 2.5% were used, as described in Pinto et al. (2015).
Polymorphism analysis using COI sequences from Maranhão State was considered to be representative of a fine spatial scale dis-tribution, due to the low dispersion capacity of phlebotomine spe-cies and the maximum distance among collection sites (580 km between Barreirinhas and Itinga municipalities). On the other hand, to uncover patterns of COI polymorphism at a broad spatial scale distribution, along with the 148 sequences from Maranhão, we added 643 sequences (available in GenBank) of sand fly species from other Brazilian regions, which are about 1,500 to 2,000 km away from Maranhão (access numbers KP112487 to KP113062 from
Pinto et al. 2015; and KF467531 to KF467597 from Scarpassa and Alencar 2013). For this combined dataset, a Neighbor-Joining tree was constructed, and submitted to ABGD analysis, since the RESL algorithm can only be used for sequences deposited in BOLD System and within the same project.
Both fine and broad spatial scale analyses may reveal hidden diversity, which may be associated with cryptic species or geographic variation within the same nominal species.
Results
The morphological identification of the 148 phlebotomines revealed 15 species from 10 genera: Bi. flaviscutellata, Br. avellari, Ev. evan-droi, Ev. infraspinosa, Evandromyia lenti (Mangabeira), Ev. termit-ophila, Lu. longipalpis, Mg. migonei, Micropygomyia trinidadensis
(Newstead), Nyssomyia antunesi (Coutinho), Nyssomyia whitmani
(Antunes and Coutinho), Pr. choti, Ps. davisi, Ps. complexus, and Sc. sordellii. Two females of the genus Psychodopygus (Chagasi Series) could not be identified to the species level using morphological traits, since many females of this genus are isomorphic (Galati 2003). Nevertheless, these samples were assigned to Psychodopygus com-plexus because they shared COI haplotypes with a male that was identified morphologically as belonging to this species.
Sequencing of the COI gene fragment from these 148 individuals resulted in an alignment containing 110 haplotypes (543 bp) with no visual indication (stop codons in the middle of sequences) of pseudo-genes and/or nuclear copies of mitochondrial origin (NUMT), which would indicate the presence of paralogous genes.
The intraspecific mean K2P distance was 0.7% (ranging from 0 to 1.87%) (Table 1), while the mean interspecific distance was 14.3% (0.8–17.7%) (Table 2). Evandromyia lenti and Ev. evandroi
showed the smallest interspecific distance (mean 0.8%), including shared haplotypes, which prevented the formation of a barcode gap (Fig. 2).
In the fine spatial scale analysis, ABGD identified 14 OTUs from the 15 morphologically identified species of Maranhão (with prior intraspecific divergence (P) values of 0.136 and 0.189). All the nom-inal species represented one OTU each, with the exception of Ev. lenti and Ev. evandroi, which were merged into the same OTU. On the other hand, RESL identified 16 OTUs, because Lu. longi-palpis and Ev. termitophila were split into two OTUs each. Similar to ABGD, Ev. evandroi and Ev. lenti also fell into the same OTU (Fig. 3). Nyssomyia antunesi and Ny. whitmani were assigned to
distinct OTU, and displayed well-supported clades each, despite hav-ing a genetic distance well below the interspecific average (Fig. 3).
The ABGD analysis using the combined dataset (broad spatial scale analysis) indicated 49 OTUs (Fig. 4). Although species from the genus Nyssomyia (Ny. intermedia, Ny. whitmani, Ny. yuilli yuilli, Ny. anduzei, Ny. antunesi, and Ny. umbratilis) presented well-supported clades, these species were merged into a single OTU. Also, only one OTU was estimated for Ev. lenti, Ev. carmelinoi, and Ev. evandroi. Two distinct clades with high to moderate bootstrap values were revealed for Mg. migonei (K2P = 1.3%), Pr. choti (K2P = 1.0%), Ps. davisi (K2P = 2.8%), and Sc. sordellii (K2P = 1.0%) when compar-ing samples from northeastern (Maranhão) and southeastern Brazil. Despite that, each of these four species formed a single OTU (Fig. 4).
Bichromomyia flaviscutellata was represented by two highly divergent (K2P = 10.7%) and unrelated groups: one belonging to Northeast (Maranhão) and the other from Brazilian Southeast (Fig. 4).
Discussion
We revealed cryptic diversity in seven species of phlebotomines, at both fine (Lu. longipalpis and Ev. termitophila) and broader (Mg. migonei,
Pr. choti, Ps. davisi, Sc. sordellii, and Bi. flaviscutellata) spatial scales, in areas endemic for leishmaniasis in Brazil. Most of the cryptic diversity is probably associated to microevolutionary processes (e.g., geographic variation due to isolation by distance), but there is strong evidence for a putative new species under Bi. flaviscutellata, with one them endemic to Maranhão. In addition, partial sequences of COI are now available for the first time for Br. avellari, Ev. infraspinosa, Ev. evandroi, and Ps. complexus, which will be useful for future molecular identification of these species in other locations in the neotropical region.
The ABGD algorithm identified 14 OTUs for the 15 species that were identified morphologically, while the RESL identified 16 OTUs for the same 15 species. The use of DNA taxonomy for phleboto-mines can reach 100% efficacy in most cases, even when species present high intraspecific values (e.g. Gutiérrez et al. 2014, Romero-Ricardo et al. 2016, Gajapathy et al. 2016). However, broader stud-ies, in terms of the geographic distribution of sampling and number of sampled species, can produce erroneous and/or ambiguous molecular species identification for sand flies and other groups of insects (Pinto et al. 2015, Lee et al. 2017).
One case of ambiguous molecular identification involved speci-mens morphologically identified as Ev. lenti and Ev. evandroi.
Table 2. Paired genetic distances (Kimura 2-parameters) among sand fly species from Maranhão, Brazil. The smallest genetic distances observed among the pairs Ev. evandroi/Ev. lenti and Ny. antunesi/Ny. whitmani are shown in bold. See Table 1 for the complete species names. Species (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (1) Bi. flaviscutellata (2) Br. avellari 0.140 (3) Ev. evandroi 0.125 0.138 (4) Ev. infraspinosa 0.142 0.162 0.107 (5) Ev. lenti 0.125 0.139 0.008 0.107 (6) Ev. termitophila 0.148 0.161 0.147 0.145 0.147 (7) Lu. longipalpis 0.134 0.143 0.143 0.125 0.145 0.154 (8) Mg. migonei 0.134 0.158 0.115 0.133 0.117 0.142 0.136 (9) Mi. trinidadensis 0.158 0.158 0.128 0.152 0.130 0.171 0.154 0.140 (10) Ny. antunesi 0.121 0.156 0.139 0.135 0.141 0.144 0.127 0.127 0.155 (11) Ny. whitmani 0.148 0.177 0.166 0.162 0.165 0.172 0.146 0.154 0.174 0.058 (12) Pr. choti 0.163 0.146 0.160 0.141 0.161 0.149 0.132 0.153 0.163 0.158 0.170 (13) Ps. davisi 0.148 0.152 0.131 0.148 0.134 0.170 0.138 0.145 0.159 0.125 0.131 0.166 (14) Ps. complexus 0.131 0.147 0.143 0.139 0.146 0.157 0.144 0.148 0.158 0.117 0.137 0.156 0.113 (15) Sc. sordellii 0.154 0.156 0.125 0.146 0.128 0.151 0.163 0.145 0.138 0.156 0.176 0.162 0.166 0.161
Table 1. List of morphologically identified sand fly species, the number of individuals per species (n), the number of haplotypes (H) by species, and the Kimura 2-parameters intraspecific distances (K2P) (minimum, maximum, and average) of sand flies from Maranhão, Brazil
Species n H Locality Min K2P distance (%) Mean K2P distance (%) Max K2P distance (%)
Bichromomyia flaviscutellata 8 7 1, 3 e 5 0 1.44 2.85 Brumptomyia avellari 17 15 1, 3 e 4 0 1.65 3.26 Evandromyia evandroi 13 9 3 0 0.75 1.89 Evandromyia infraspinosa 4 3 1 e 3 0 0.41 0.56 Evandromyia lenti 18 13 3 0 0.73 2.08 Evandromyia termitophila 4 4 3 e 6 0.37 1.87 3.23 Lutzomyia longipalpis 22 20 2, 3 e 5 0 1.16 4.42 Migonemyia migonei 3 3 5 0.37 0.63 0.74 Micropygomyia trinidadensis 13 8 1, 3 e 4 0 1.22 2.44 Nyssomyia antunesi 4 4 1 0.56 0.66 0.75 Nyssomyia whitmani 22 19 3, 5 e 6 0 0.93 2.84 Pressatia choti 8 3 6 0 0.09 0.37 Psychodopygus davisi 2 1 6 0 0 0 Psychodopygus complexus 3 2 6 0.0 0.12 0.18 Sciopemyia sordellii 7 3 1 e 3 0 0.11 0.37
These species displayed very small genetic differences, shared hap-lotypes, and were merged in the same OTU by the two algorithms. Apparently, this is common for this genus, as similar results were observed by Pinto et al. (2015) for the pair Ev. lenti and Ev. carmeli-noi, which are sister species with a marked morphological similarity. In addition, the combined dataset analysis categorized these three species (Ev. lenti, Ev. evandroi, and Ev. carmelinoi) as the same OTU (Fig. 4). There are three potential explanations for this outcome: introgression of mtDNA, incomplete lineage sorting due to recent speciation, or a combination of both.
The possibility of hybridization with introgression of the mtDNA between Ev. lenti and Ev. evandroi is the least likely of these sce-narios. Although these species have sympatric distribution along the sampling locations (Rebêlo et al. 2010a,b), and this type of event has already been recorded in several groups of sand flies (e.g., Testa et al. 2002, Pesson et al. 2004, Mazzoni et al. 2006, Mazzoni et al. 2008, Ready 2011, Pinto et al. 2015), the fact that they did not form separate clades (Fig. 3) supports the hypothesis of recent divergence. However, if this divergence resulted from a recent speciation event, they may still be able to hybridize if the reproductive barriers are incomplete.
Although Ev. evandroi and Ev. lenti have not been reported as vectors, infection of Ev. lenti by Leishmania spp. already has been detected in several areas endemic for the disease (Margonari et al. 2010, Paiva et al. 2010, Rêgo et al. 2015), indicating the possible participation of this species in the transmission of these pathogens. Thus, the possibility of introgression, although unlikely, should be reassessed using more molecular markers (e.g., microsatellites) and even genomics, since this phenomenon may affect vectorial capacity and resistance to insecticides (Marcondes et al. 1997).
We argue that this is a case of ambiguous molecular identi-fication due to the reasons given above and because Ev. evandroi
shows clear morphological distinction from Ev. lenti, especially in male genital structures such as the parameres and aedeagi (Galati 2003). Therefore, the observed pattern, of morphological differen-tiation disassociated with genetic differences, between these species may have resulted from recent speciation (either followed by intro-gression or not), meaning that insufficient time has passed for the emergence of genetic differences on COI despite the establishment of morphological changes.
After Ev. lenti and Ev. evandroi, the next smallest interspe-cific distance was between Ny. whitmani and Ny. antunesi (5.8%). Despite forming two distinct OTUs in Maranhão, with high boot-strap support values, the genetic distance between them was two-fold lower than the average interspecific distances between the other phlebotomine species. This pattern has been shown in another study with Nyssomyia genus. Nyssomyia whitmani and Ny. intermedia, which occur in the southeastern and midwestern regions of Brazil, and are grouped in the same OTU (Pinto et al. 2015), while Ny. umbratilis and Ny. anduzei (from the Brazilian Amazon) presented an interspecific distance of 4.4% (Scarpassa and Alencar 2013).
In the analysis using the combined dataset (GenBank + Maranhão
COI sequences), all species of Nyssomyia were merged in the same OTU (Fig. 4). In this case, although the molecular marker was able to separate each species into distinct clades with high bootstrap sup-port values, the ABGD algorithm was not capable to assign an OTU for each Nyssomyia species. These results demonstrate the possibil-ity of speciation events in Nyssomyia genus also may have occurred recently compared to the other groups of sand flies. This idea is rein-forced also by reports of gene introgression between sympatric spe-cies of this genus (Mazzoni et al. 2006, 2008).
The above case should be taken into account during species delimitation by molecular methods, especially when algorithms are used to estimate OTUs. Separate analyses for groups of recent spe-cies—as appears to be the case for Nyssomyia—are necessary when the pattern of genetic divergence differs from that of the other spe-cies of the dataset, and may bias OTU inferences. When we analyzed only the sequences of Maranhão, Ny. whitmani and Ny. antunesi
were grouped into two distinct OTUs by ABGD (Fig. 3). However, when ABGD was applied to the combined dataset of sand flies, only a single OTU was estimated, pointing to a taxon sampling sensi-tivity for ABGD results. The ABGD algorithm uses the distribution of nucleotide distances to partition hypothetical groups (Puillandre et al. 2012). When we analyzed only the 15 species from Maranhão, the interspecific distances were lower than those of the combined dataset, leading the algorithm to interpret the distances between
Nyssomyia species as part of an intraspecific variation within a single OTU.
In many cases, females of phlebotomine species are morphologic-ally indistinguishable, for example those from Brumptomyia and
Psychodopygus genera (Galati 2003). In these cases, DNA barcoding is a powerful tool for species identification. It was only possible to iden-tify morphologically all Brumptomyia specimens in this study because
they were males. That was not the case for Psychodopygus (Chagasi Series), in which two females could not be identified at the species level, although they were assigned to Ps. complexus due to its high similarity
Fig. 3. Neighbor-joining tree of CO1 sequences of sand flies from Maranhão, Brazil. Numbers near nodes indicate bootstrap values (only >70% are displayed). Gray bars represent the identification of OTUs by the ABGD and RESL algorithms. See Table 1 for the complete species names.
with sequences from morphologically identified males. Therefore, DNA barcode identification of males from Br. avellari and Ps. complexus
allows the identification of females from these species, as previously demonstrated for these, and other, sand fly genera (Pinto et al. 2015).
At the fine spatial scale, the RESL algorithm identified cryptic diversity for Lu. longipalpis and Ev. termitophila. from Maranhão.
Lutzomyia longipalpis was split into two OTUs (maximum intra-specific distance = 4.42%), however, at the broad spatial scale, Lu. longipalpis from Maranhão was grouped into two distinct clades with Lu. cruzi (Mangabeira) and Lu. alencari (Martins, Souza and Falcão), respectively (Fig. 4). These same clusters were observed in Pinto et al. (2015), and were related to the geographic distribu-tion of the species being grouped (Lu. longipalpis and Lu. cruzi in the Brazilian Midwest and Lu. longipalpis and Lu. alencari in the Southeast). Our data indicated that these clades can also occur sym-patrically, since they were found in the same location in Maranhão (São Domingos, in the Cerrado biome).
Several studies using different approaches, such as copulatory courtship sound production (Araki et al. 2009, Vigoder et al. 2010,
Vigoder 2015), pheromones (Araki et al. 2009), and genetic mark-ers (Araki et al. 2009, Vigoder et al. 2010, Araki et al. 2013), sug-gest that Lu. longipalpis represents a species complex throughout its distribution in the Brazilian territory (Souza et al. 2017). In this case, the use of mtDNA to identify this species is inefficient due to possible introgression events with closely related species such as Lu. cruzi and Lu. alencari (Pinto et al. 2015). These three species are highly morphologically similar and may have undergone recent spe-ciation processes, but they still may be placed within the Lu. longi-palpis complex (Vigoder et al. 2010, Lins et al. 2012). Therefore, we emphasize the need to review the taxonomic status of Lu. longipalpis
to address epidemiological interests, since it is the main vector of
Leishmania infantum, the etiologic agent of visceral leishmaniasis in Brazil (Rangel and Vilela 2008, Brazil 2013, Salomón et al. 2015).
Evandromyia termitophila, was also split into two OTUs by the RESL algorithm (maximum divergence = 3.23%) in Maranhão, indicat-ing cryptic diversity for the first time in this nominal species. However, the discovery of cryptic diversity at fine spatial scales should be analyzed with parsimony with RESL, because this algorithm may overestimate the diversity found (Stur and Borkent 2014). This reinforces that ABGD is more conservative than RESL for discovering OTUs at fine spatial scales (Maranhão), which has also been demonstrated in studies com-paring the accuracy of these algorithms in species delimitation in other insects (e.g., Song et al. 2016, Zhu et al. 2017). ABGD is, therefore, more suitable for analysis with samples at a larger geographic scale, since there is little chance of overestimating the species diversity. This may have occurred in the cases of Ev. termitophila and Lu. longipalpis, for which RESL assigned two OTUs for each taxon in Maranhão.
Migonemya migonei, Pr. choti, Ps. davisi, and Sc. sordellii formed distinct, and well supported, clades separated by a large geograph-ical distance (about 2,000 km) (Fig. 4): one clade with samples from northeastern Brazil (Maranhão) and the other from southeastern and midwestern Brazil (sequences from Pinto et al. 2015). All these species formed only one OTU each (Fig. 4) with genetic distances between clades varying from 1.0 to 2.8%, indicating microevolu-tionary processes driven by isolation by distance. Such intraspecific differences might be found commonly in studies using DNA barcod-ing analyses at large spatial scales (Bergsten et al. 2012).
In addition, Bi. flaviscutellata was the most remarkable case of cryptic diversity unraveled in the broad spatial scale analysis. This species displayed two OTUs with distant evolutionary relationships (K2P = 10.7%) (Fig. 4): one group with samples from Maranhão and another from southeastern Brazil (sequences from Pinto et al.
Fig. 4. Neighbor-joining tree of combined COI sequences of sand fly species from Maranhão and GenBank. Numbers nodes indicate bootstrap values (only >50% are displayed). The clades marked with a black triangle have sequences from Maranhão and GenBank. The clades marked with black circle only have sequences from Maranhão. The unmarked clades have GenBank sequences only. The gray bar represents the identification of OTUs by the ABGD algorithm.
2015). Given these evidence, we argue that these OTU repre-sent two distinct species for which one has not yet been formally described. Another explanation is erroneous morphological identi-fication, which is unlikely since the morphologically closest species,
Bichromomyia reducta (Feliciangeli, Ramírez-Pérez and Ramírez 1988), has not been reported in Maranhão (Rebêlo et al. 2010a). The possibility of one of these groups belonging to Bichromomyia inornata (Martins, Falcão and Silva 1965) can also be disregarded, because in the identification key of Galati (2003), the black scutel-lum of Bi. inornata is used as a diagnostic feature for identification. The checklist of Shimabukuro et al. (2017) considers the possibil-ity of error in the description of this character, since analyses of specimens deposited in collections indicate that this trait does not differ between Bi. flaviscutellata and Bi. inornata, suggesting that
Bi. inornata is synonymous with Bi. flaviscutellata. Our data, there-fore, reveal the need for a re-evaluation of the taxonomic status of
Bi. flaviscutellata, which has an important epidemiological role in the transmission of Leishmania amazonensis, a causative agent of cutaneous forms of leishmaniasis. If these two groups correspond to new taxa (one of them exclusively occurring in Maranhão), they may harbor variation in traits such as insecticide resistance (Hassan et al. 2012) or vector competence (Maingon et al. 2008, Ready 2013), which may affect the vector control measures.
In summary, DNA barcoding of phlebotomines revealed cryptic diversity both locally and regionally in endemic areas of leishmaniasis in Brazil that, in one case, is associated putatively with a new spe-cies. Further, COI sequences for four species (Br. avellari, Ev. infras-pinosa, Ev. evandroi, and Ps. complexus) are available for the first time, which will be useful for molecular identification of these species in future studies. The cases for which the DNA barcoding was not as effective as morphological identification are from species showing evidence of recent speciation (with or without mtDNA introgression), for which differences could not be detected at the COI polymorphism level. Future studies should be directed toward the cases of cryptic diversity, for example, to evaluate the implications of such geographic genetic variation and/or cryptic species on the epidemiology and con-trol of leishmaniasis in the Neotropical region.
Acknowledgments
We thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and the Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão (FAPEMA) for financial support.
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