Open Access

DNA barcoding does not separate South American Triatoma (Hemiptera: Reduviidae), Chagas Disease vectors

Parasites & Vectors20147:519

https://doi.org/10.1186/s13071-014-0519-1

Received: 13 September 2014

Accepted: 4 November 2014

Published: 21 November 2014

Abstract

Background

DNA barcoding assumes that a biological entity is completely separated from its closest relatives by a barcoding gap, which means that intraspecific genetic distance (from COI sequences) should never be greater than interspecific distances. We investigated the applicability of this strategy in identifying species of the genus Triatoma from South America.

Findings

We calculated intra and interspecific Kimura-2-parameter distances between species from the infestans, matogrossensis, sordida and rubrovaria subcomplexes. In every subcomplex examined we observed at least one intraspecific distance greater than interspecific distances.

Conclusions

Although DNA barcoding is a straightforward approach, it was not applicable for identifying Southern American Triatoma species, which may have diverged recently. Thus, caution should be taken in identifying vector species using this approach, especially in groups where accurate identification of taxa is fundamentally linked to public health issues.

Keywords

Triatominae Chagas disease DNA barcoding Molecular identification

Findings

DNA barcoding, as proposed by Hebert et al. [1] assumes that a biological entity is completely separated from its closest relatives by a barcoding gap[2], which means that intraspecific genetic distances (from COI sequences) are never greater than interspecific distances.

Triatoma Laporte (Hemiptera: Reduviidae) is the most diverse genus of Chagas Disease vectors, and accurate identification of species is imperative for the efficiency of vector control programs. The Triatoma genus is divided into species complexes and subcomplexes according to geographic distribution and morphological similarity [3].

Recently, Justi et al. [4] reported that the relationships between species assigned to South American Triatoma subcomplexes could not be untangled with the data in hand. We were then prompted to investigate whether DNA barcoding would be a useful tool for identifying the species within the infestans, matogrossensis, sordida and rubrovaria subcomplexes [3].

Kimura-2-parameter genetic distances [5] were calculated pairwise within each of the above mentionedsubcomplexes (Table 1) using the software MEGA v. 5 [6], and intra and interspecific distances were compared.
Table 1

K2p-distances between species of the Triatoma subcomplexes studied

Subcomplex

GenBank

Number

Geographic Origin

            

infestans

    

1

2

3

4

5

      

KC249330

1

Chaco Tita, Cochabamba, Bolivia

T. delpontei 53

           

KC249346

2

Chaco Tita, Cochabamba, Bolivia

T. infestans 44

0.021

          

KC249349

3

Cotapachi, Cochabamba, Bolivia

T. infestans 58

0.025

0.018

         

KC249352

4

Mataral, Cochabamba, Bolivia

T. infestans 60

0.025

0.018

0.005

        

KC249354

5

Ilicuni, Cochabamba, Bolivia

T. infestans 63

0.021

0.016

0.000

0.006

       

KC249355

6

Montevideo, Uruguai

T. infestans 69

0.072

0.061

0.064

0.069

0.103

      

matogrossensis

    

7

8

9

10

11

12

     

KC249327,KC249328

7

Posse, GO, Brazil

T. costalimai 35

           

KC249329

8

Chiquitania, Cochabamba, Bolivia

T. costalimai 42

0.154

          

KC249360

9

São Gabriel D'oeste, MS, Brazil

T. matogrossensis 192

0.134

0.138

         

KC249361

10

Bahia, Brazil

T. matogrossensis 31

0.151

0.152

0.047

        

KC249391

11

Pantanal, MT, Brazil

T. vandae 28

0.156

0.151

0.047

0.040

       

KC249392

12

Rio Verde do MatoGrosso, MT, Brazil

T. vandae 73

0.138

0.146

0.005

0.046

0.045

      

KC249393,KC249394

13

Rondonópolis, MT, Brazil

T. vandae 74

0.158

0.150

0.048

0.059

0.007

0.052

     

rubrovaria

    

14

15

16

17

18

19

20

21

22

23

24

KC249322

14

São Gerônimo, RS, Brazil

T. carcavalloi 78

           

KC249323

15

Caçapava do Sul, RS, Brazil

T. circummaculata 120

0.039

          

KC249324

16

Sítio Faxina, Piratini, RS, Brazil

T. circummaculata 121

0.029

0.025

         

KC249325

17

Sítio Faxina, Piratini, RS, Brazil

T. circummaculata 122

0.017

0.039

0.033

        

KC249356

18

Nova Petrópolis, RS, Brazil

T. klugi 75

0.018

0.037

0.031

0.017

       

KC249369

19

Sítio Faxina, Piratini, RS, Brazil

T.rubrovaria 123

0.055

0.023

0.029

0.055

0.057

      

KC249370

20

Sítio venda da Lagoa, Canguçu, RS, Brazil

T.rubrovaria 134

0.065

0.052

0.065

0.065

0.061

0.070

     

KC249372

21

SítioFaxina, Pinheiro Machado, RS, Brazil

T.rubrovaria 136

0.042

0.019

0.027

0.036

0.036

0.031

0.035

    

KC249373

22

Sítiovenda da Lagoa, Canguçu, RS, Brazil

T.rubrovaria 140

0.038

0.020

0.019

0.043

0.040

0.029

0.032

0.012

   

KC249374

23

Canguçu, RS, Brazil

T.rubrovaria 156

0.039

0.020

0.019

0.045

0.042

0.029

0.032

0.012

0.000

  

KC249375

24

Caçapava do Sul, RS, Brazil

T.rubrovaria 76

0.021

0.029

0.021

0.016

0.016

0.033

0.074

0.034

0.038

0.038

 

KC249376

25

Quevedos, RS, Brazil

T.rubrovaria 77

0.029

0.030

0.043

0.022

0.029

0.046

0.065

0.031

0.046

0.048

0.026

sordida

    

26

27

28

29

30

31

32

33

34

  

KC249338

26

Rivadaria, Argentina

T. garciabesi 89

           

KC249342

27

Santa Cruz, Bolívia

T. guasayana 55

0.077

          

KC249343

28

Santa Cruz, Bolívia

T. guasayana 82

0.065

0.056

         

KC249379,KC249380

29

Romerillo, Cochabamba, Bolivia

T. sordida 46

0.029

0.060

0.060

        

KC249381,KC249382

30

Romerillo, Cochabamba, Bolivia

T. sordida 47

0.030

0.061

0.061

0.000

       

KC249383

31

La Paz, Bolívia

T. sordida 83

0.081

0.013

0.063

0.066

0.066

      

KC249384

32

Pantanal, MS, Brazil

T. sordid a 85

0.069

0.012

0.062

0.065

0.065

0.025

     

KC249385

33

Santa Cruz, Bolívia

T. sordida 86

0.043

0.082

0.074

0.035

0.035

0.073

0.082

    

KC249387

34

San Miguel Corrientes, Argentina

T. sordida 88

0.061

0.058

0.063

0.070

0.071

0.058

0.055

0.052

   

KC249388

35

Poconé, MT, Brazil

T. sordida 90

0.069

0.017

0.058

0.075

0.075

0.031

0.011

0.078

0.051

  

Highlighted distances deviate from the DNA barcoding premis that intraspecific distances are smaller than interspecific distances.

In all subcomplexes we observed at least one intraspecific distance greater than interspecific distances (Table 1). To be considered appropriate to identify species within a group, intraspecific distances must always be greater than interspecific ones [2], and therefore DNA barcoding is not accurate for the species-level identification of South American Triatoma. Moreover, the method fails to account for hybridization events, which are naturally observed in Triatoma[7],[8], and introgression, which is frequent in nuclear DNA [9]. These considerations argue that Hebert et al.’s [1] proposal of cataloguing biodiversity based only on DNA barcoding may severely underestimate it.

Besides that, as highlighted by Dujardin et al.[10], the morphological changes observed in closely related “species”, or “lineages” as we prefer to call them, may have led taxonomists to rush into describing subspecies or species, even genera. Molecular phylogenetic studies are in their infancy in unravelling the evolution of Triatominae, and a comprehensive molecular phylogeny, including more than one specimen for most lineages, was published only in 2014 [4], although several analyses were conducted focusing on small species groups. Taken together, these statements make it clear that further investigations of Triatominae evolution are long overdue, preferably integrating morphological, molecular and ecological data.

Lineage evolution has not occurred, but it is happening now. Concerning lineages designated in the infestans complex (including the subcomplexes studied here), separation is much clearer in terms of morphology than in molecular systematics. In cases where lineages have not reached reciprocal monophyly, defining taxonomic entities is not a straightforward issue [11]. Therefore caution is necessary, especially in a group where accurate identification of taxa is fundamentally linked to public health issues.

Conclusions

Although DNA barcoding is a straightforward approach, it was not applicable for identifying Southern American Triatoma species, which may have diverged recently. Thus, caution should be taken in identifying vector species using this approach, especially in groups where accurate identification of taxa is fundamentally linked to public health issues.

Authors’ information

CD is PhD student funded by Instituto Oswaldo Cruz and SAJ is a Post Doctoral Fellow funded by CNPq.

Declarations

Acknowledgements

We thank Carlos G. Schrago for reviewing our manuscript and for the useful comments.

Authors’ Affiliations

(1)
Instituto de Biologia, Laboratório de Biologia Evolutiva Teórica e Aplicada, Universidade Federal do Rio de Janeiro
(2)
Laboratório Nacional e Internacional de Referência em Taxonomia de Triatomíneos, InstitutoOswaldo Cruz, FIOCRUZ

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Copyright

© Justi et al.; licensee BioMed Central. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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