Open Access

Cytochrome c oxidase subunit 1 gene as a DNA barcode for discriminating Trypanosoma cruzi DTUs and closely related species

  • Marina Silva Rodrigues1Email author,
  • Karina Alessandra Morelli2 and
  • Ana Maria Jansen1
Parasites & Vectors201710:488

https://doi.org/10.1186/s13071-017-2457-1

Received: 8 July 2017

Accepted: 5 October 2017

Published: 16 October 2017

Abstract

Background

The DNA barcoding system using the cytochrome c oxidase subunit 1 mitochondrial gene (cox1 or COI) is highly efficient for discriminating vertebrate and invertebrate species. In the present study, we examined the suitability of cox1 as a marker for Trypanosoma cruzi identification from other closely related species. Additionally, we combined the sequences of cox1 and the nuclear gene glucose-6-phosphate isomerase (GPI) to evaluate the occurrence of mitochondrial introgression and the presence of hybrid genotypes.

Methods

Sixty-two isolates of Trypanosoma spp. obtained from five of the six Brazilian biomes (Amazon Forest, Atlantic Forest, Caatinga, Cerrado and Pantanal) were sequenced for cox1 and GPI gene fragments. Phylogenetic trees were reconstructed using neighbor-joining, maximum likelihood, parsimony and Bayesian inference methods. Molecular species delimitation was evaluated through pairwise intraspecific and interspecific distances, Automatic Barcode Gap Discovery, single-rate Poisson Tree Processes and multi-rate Poisson Tree Processes.

Results

Both cox1 and GPI genes recognized and differentiated T. cruzi, Trypanosoma cruzi marinkellei, Trypanosoma dionisii and Trypanosoma rangeli. Cox1 discriminated Tcbat, TcI, TcII, TcIII and TcIV. Additionally, TcV and TcVI were identified as a single group. Cox1 also demonstrated diversity in the discrete typing units (DTUs) TcI, TcII and TcIII and in T. c. marinkellei and T. rangeli. Cox1 and GPI demonstrated TcI and TcII as the most genetically distant branches, and the position of the other T. cruzi DTUs differed according to the molecular marker. The tree reconstructed with concatenated cox1 and GPI sequences confirmed the separation of the subgenus Trypanosoma (Schizotrypanum) sp. and the T. cruzi DTUs TcI, TcII, TcIII and TcIV. The evaluation of single nucleotide polymorphisms (SNPs) was informative for DTU differentiation using both genes. In the cox1 analysis, one SNP differentiated heterozygous hybrids from TcIV sequences. In the GPI analysis one SNP discriminated Tcbat from TcI, while another SNP distinguished TcI from TcIII.

Conclusions

DNA barcoding using the cox1 gene is a reliable tool to distinguish T. cruzi from T. c. marinkellei, T. dionisii and T. rangeli and identify the main T. cruzi genotypes.

Keywords

Cytochrome c oxidase subunit 1 Trypanosoma cruzi Discrete typing unitsGlucose-6-phosphate isomeraseBarcodingSubgenus Trypanosoma (Schizotrypanum)

Background

How many species are there on Earth? Estimations suggest that approximately 90% of species remain undescribed [1]. The identification and classification of biodiversity is a practice that has always fascinated humankind. The Greek philosopher Aristotle (4th century BC) developed the first classification system, which was used for nearly 2000 years [2]. In the 1700s, Carl Linnaeus [3] developed the concept of binomial nomenclature using Latin, which was the language of educated men at his time. Binomial nomenclature is a standard method for scientists that speak different languages to classify living things to clearly communicate their discoveries. Recently, DNA sequences have been applied in the classification of life forms. However, different methods and DNA regions have been used to compare the same taxonomic groups, frequently leading to conflicting results.

In the search for a simple method to identify and compare species, Hebert et al. [4] proposed DNA barcoding, a new system of species identification using the cytochrome c oxidase subunit 1 mitochondrial gene (cox1 or COI) as a standardized single molecular marker for the classification of animal species. One of the requirements of the DNA barcoding approach is that species identification is associated with a voucher belonging to a curated biological collection, enabling follow up and a strategy for corroborating species identification [5]. Until recently, national barcode networks have been established in 11 countries, including Brazil, which uses the Brazilian Barcode of Life (BrBOL) [6].

In addition to the identification of known and new species, barcoding with the cox1 gene is suggested as a standard for cryptic taxa discovery, association of different life stages of the same species and wildlife conservation genetics [5]. Cox1 appears to have a better phylogenetic signal than the other mitochondrial genes [7]. Some authors argue that the evolution of the cox1 gene is sufficiently rapid to discriminate between closely related species and investigate intraspecific diversity [4, 8]. The cox1 region is highly efficient for discriminating vertebrate and invertebrate species [5, 9, 10], but is not suited for plants and some fungal species [4, 11, 12]. The use of cox1 for identifying protozoa and other unicellular organisms is still in its initial stage but has been demonstrated as a promising barcode marker for dinoflagellates, Paramecium sp., Nemertea [1315]. Moreover, joint analyses of nuclear and mitochondrial markers may be necessary to distinguish species [1].

Therefore, the small subunit ribosomal DNA (SSU rDNA) has been proposed as a first step for a protist barcode, followed by the use of a second marker specific for each group [6]. To confirm a gene as a barcode marker, it is essential to calculate the “barcoding gap”, that is, the gap between the maximum intraspecific and minimum interspecific genetic distances that establish the limits between species [16]. Several molecular targets for trypanosomatid identification have previously been used: internal transcribed spacer (ITS) [17], mini-exon [18], glucose-6-phosphate isomerase (GPI) [1921], cytochrome b (cytb) [22, 23], multilocus sequencing typing (MLST) [24], the variable regions V7 V8 of SSU rDNA, and glyceraldehyde-3-phosphate dehydrogenase (gGAPDH) genes [22, 25, 26]. However, there is no consistency concerning which DNA region to use as a trypanosomatid barcode, and none of these markers were evaluated as a universal marker for biodiversity analysis.

With the emergence of molecular techniques with higher analytical power, an increasing number of new species of Trypanosoma have been reported [26, 27] and it is becoming increasingly clear that there is a high diversity of Trypanosoma spp. within the subgenus Schizotrypanum of Trypanosoma. The extreme morphological similarity and phylogenetic proximity of these species, and the use of tools with lower analytical power, resulted in the isolation of numerous species of T. (Schizotrypanum) from the wild transmission cycle remaining only at the generic level or wrongly diagnosed as Trypanosoma cruzi, highlighting the importance of a universal method to characterize T. cruzi, its subpopulations and representatives of the subgenus Schizotrypanum.

Trypanosoma cruzi (Trypanosomatida: Trypanosomatidae) is a successful parasite that is capable of establishing an extracellular cycle in dozens of triatomine species (Hemiptera: Reduvidae) and infecting almost every cellular type from more than 100 mammal species distributed from the south of the USA to the south of Latin America [28, 29]. Although described as one taxon, T. cruzi has a remarkable genetic heterogeneity that was already recognized by the very first authors who researched it [3032]. The T. cruzi population structure has been classified as clonal or, at least, primarily clonal [32, 33] and hybridization events have also been observed, suggesting that genetic recombination occurs in this group [33, 34]. Moreover, the extent to which these hybridization events are responsible for the enormous heterogeneity of this parasite remains a controversial issue [19, 3537]. Several techniques, (biological, biochemical and molecular) applied to define T. cruzi subpopulations have led to different designations (Fig. 1) [25, 30, 35, 3851]. Presently, T. cruzi subpopulations are assembled in six discrete typing units (DTUs) - named TcI, TcII, TcIII, TcIV, TcV, TcVI [29] - and a genotype called Tcbat, initially described as being associated with Chiroptera [25], although it was previously isolated from a child [52] and from mummified human tissue [53]. However, Barnabé et al. [51] recently proposed the subdivision of T. cruzi into three mitochondrial clades (mtTcI, mtTcII and mtTcIII) based on the analysis of the nucleotide sequences available in the GenBank database, showing that the classification of T. cruzi subpopulations remains a debatable issue.
Fig. 1

Designations of T. cruzi subpopulations through time and according to the method employed. The numbers represent dates of publication. The red star indicates current consensus of T. cruzi nomenclature and subdivisions

In the present study, we tested cox1 as a DNA barcode to identify T. cruzi from other closely related species belonging to the subgenus Schizotrypanum and to examine the genetic diversity within T. cruzi and its DTUs to further understand the ecology of the species of T. (Schizotrypanum). Additionally, we evaluated cox1 as a target to also identify Trypanosoma (Tejeraia) rangeli, as this trypanosome shares the geographical distribution, vectors and mammal hosts of T. cruzi and is also included in the T. cruzi clade [54]. To evaluate the occurrence of mitochondrial introgression events and the presence of hybrid genotypes we tested a combination of cox1 (uniparental inheritance) and the nuclear gene glucose-6-phosphate isomerase (GPI) (biparental inheritance). GPI is one of the genes sequenced for an extensive number of T. cruzi isolates distributed over several geographic regions [51], enabling a comparison of the sequences generated in the present study. Thus, the precise identification of these Trypanosoma species is of the utmost importance. In addition, the present study will enhance the amount of nucleotide sequences available for comparison, since the GenBank database still lacks a broader deposit on trypanosomatid sequences for the cox1 gene.

Methods

Samples

The present study included 62 isolates of Trypanosoma spp. obtained from 16 different genera of free-ranging wild mammals and from triatomines of the genera Rhodnius and Triatoma, distributed in five of the six Brazilian biomes (Amazon Forest, Atlantic Forest, Caatinga, Cerrado and Pantanal) (Table 1 Fig. 2b). Isolates were cryopreserved and deposited in the Coleção de Trypanosoma de Mamíferos Silvestres, Domésticos e Vetores, Fiocruz - COLTRYP (Oswaldo Cruz Foundation, Rio de Janeiro - RJ/Brazil) in previous studies. Details on animal capture and parasite culture methods are described elsewhere [5557]. After thawing, the cells were sown in axenic culture media (NNN and LIT). When the cultures reached the exponential growth phase, DNA was extracted using the phenol-chloroform method, as described elsewhere [58]. The T. dionisii samples used in the present study were molecularly identified using 18S (SSU) and gGAPDH sequences and subsequently deposited in COLTRYP.
Table 1

Molecular identification, geographical and host origin of the COLTRYP isolates and reference stocks under study

Strain code

Host or Vector

State/Biome

Lineage

Hap (cox1)a

GenBank accession number

cox1

GPI

T. cruzi

 TCC 1994

Myotis levis

SP/Brazil

Tcbat

hap9

KT327226b

KT327312b

 COLTRYP 038

Rattus rattus

CE/Caatinga

TcI

hap3

KU145414

KT390200

 COLTRYP 039

Rattus rattus

CE/Caatinga

TcI

hap3

KU145415

KT390201

 COLTRYP 048

Didelphis albiventris

CE/Caatinga

TcI

hap3

KU256221

KU256227

 COLTRYP 087

Didelphis albiventris

CE/Caatinga

TcI

hap3

KU145426

KT390212

 COLTRYP 128

Didelphis albiventris

CE/Caatinga

TcI

hap3

KU145433

KT390219

 COLTRYP 018

Thylamys macrurus

MS/Pantanal

TcI

hap1

KU256219

KU256225

 COLTRYP 084

Oecomys sp.

MS/Pantanal

TcI

hap1

KU145425

KT390211

 COLTRYP 103

Monodelphis domestica

MS/Pantanal

TcI

hap3

KU145428

KT390214

 COLTRYP 115

Thylamys macrurus

MS/Pantanal

TcI

hap1

KU145430

KT390216

 COLTRYP 368

Nasua nasua

MS/Pantanal

TcI

hap3

KU145441

KT390227

 COLTRYP 468

Oecomys mamorae

MS/Pantanal

TcI

hap1

KU145443

KT390229

 COLTRYP 053

Rhodnius pictipes

PA/Amazon

TcI

hap2

KU145418

KT390204

 COLTRYP 055

Didelphis marsupialis

PA/Amazon

TcI

hap2

KU145419

KT390205

 COLTRYP 126

Didelphis marsupialis

PA/Amazon

TcI

hap2

KU145432

KT390218

 COLTRYP 220

Didelphis marsupialis

PA/Amazon

TcI

hap5

KU145435

KT390221

 COLTRYP 339

Rhodnius pictipes

PA/Amazon

TcI

hap2

KU145438

KT390224

 Epinet 88,115

Rhodnius robustus

PA/Amazon

TcI

hap3

KU145452

KT390238

 COLTRYP 356

Akodon cursor

RJ/Atlantic Forest

TcI

hap3

KU145439

KT390225

 Epinet 88,127

Rhodnius sp.

RJ/Atlantic Forest

TcI

hap4

KU145454

KT390240

 Epinet 88,132

Philander frenatus

RJ/Atlantic Forest

TcI

hap4

KU145456

KT390242

 Epinet 88,135

Philander frenatus

RJ/Atlantic Forest

TcI

hap4

KU145457

KT390243

 COLTRYP 003

Didelphis aurita

SC/Atlantic Forest

TcI

hap1

KU145410

KT390196

 COLTRYP 036

Didelphis albiventris

GO/Cerrado

TcI

hap8

KU145413

KT390199

 COLTRYP 042

Desmodus rotundus

TO/Cerrado

TcI

hap4

KU145416

KT390202

 COLTRYP 136

Phyllostomus albicola

TO/Cerrado

TcI

hap4

KU145434

KT390220

 COLTRYP 224

Carollia perspicillata

TO/Cerrado

TcI

hap4

KU145436

KT390222

 COLTRYP 305

Philander opossum

TO/Cerrado

TcI

hap6

KU145437

KT390223

 COLTRYP 362

Gracilinanus sp.

TO/Cerrado

TcI

hap6

KU145440

KT390226

 Colombiana

Homo sapiens

Colombia

TcI

hap7

KU168553

KU168558

 Dm28c

Didelphis marsupialis

Venezuela

TcI

hap4

KU168554

KU168559

 Silvio

Homo sapiens

PA/Amazon

TcI

hap2

FJ203996b

 

 OPS21cl11

Homo sapiens

Venezuela

TcI

  

AY484472b

 COLTRYP 061

Leontopithecus chrysomelas

BA/Atlantic Forest

TcII

hap11

KU145420

KT390206

 COLTRYP 062

Leontopithecus chrysomelas

BA/Atlantic Forest

TcII

hap11

KU145421

KT390207

 COLTRYP 063

Leontopithecus chrysomelas

BA/Atlantic Forest

TcII

hap11

KU145422

KT390208

 COLTRYP 072

Leontopithecus chrysomelas

BA/Atlantic Forest

TcII

hap11

KU145423

KT390209

 COLTRYP 081

Leontopithecus chrysomelas

BA/Atlantic Forest

TcII

hap11

KU145424

KT390210

 COLTRYP 099

Leontopithecus chrysomelas

BA/Atlantic Forest

TcII

hap11

KU145427

KT390213

 COLTRYP 006

Thrichomys apereoides

PI/Caatinga

TcII

hap10

KU256218

KU256224

 COLTRYP 021

Leontopithecus rosalia

RJ/Atlantic Forest

TcII

hap12

KU145411

KT390197

 COLTRYP 121

Leontopithecus rosalia

RJ/Atlantic Forest

TcII

hap10

KU145431

KT390217

 Epinet 88,130

Philander frenatus

RJ/Atlantic Forest

TcII

hap11

KU145455

KT390241

 COLTRYP 043

Triatoma tibiamaculata

SC/Atlantic Forest

TcII

hap10

KU145417

KT390203

 Epinet 88,121

Triatoma tibiamaculata

SC/Atlantic Forest

TcII

hap10

KU145453

KT390239

 Y

Homo sapiens

SP/Brazil

TcII

hap11

KU168555

KU168560

 Esmeraldo

Homo sapiens

BA/Brazil

TcII

hap11

DQ343646b

 

 Tu18cl2

Triatoma infestans

Bolivia

TcII

  

AY484477b

 COLTRYP 113

Monodelphis domestica

GO/Cerrado

TcIII

hap14

KU145429

KT390215

 COLTRYP 370

Rhodnius pictipes

PA/Amazon

TcIII

hap15

KU145442

KT390228

 COLTRYP 029

Galictis vittata

RJ/Atlantic Forest

TcIII

hap13

KU145412

KT390198

 3663

Panstrongylus geniculatus

AM/Brazil

TcIII

hap13

KU168556

KU168561

 M6241 cl6

Homo sapiens

PA/Brazil

TcIII

  

AY484478b

 COLTRYP 041

Thrichomys pachyurus

MS/Pantanal

TcIV

hap16

KU256220

KU256226

 COLTRYP 471

Oecomys mamorae

MS/Pantanal

TcIV

hap16

KU145444

KT390230

 COLTRYP 524

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145445

KT390231

 COLTRYP 526

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145446

KT390232

 COLTRYP 527

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145447

KT390233

 COLTRYP 528

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145448

KT390234

 COLTRYP 529

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145449

KT390235

 COLTRYP 531

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145450

KT390236

 COLTRYP 532

Triatoma sp.

MS/Pantanal

TcIV

hap16

KU145451

KT390237

 4167

Rhodnius brethesi

AM/Brazil

TcIV

hap16

KU168557

KU168562

 CANIIIcl1

Homo sapiens

PA/Brazil

TcIV

  

AY484474b

 Sc43cl1

Triatoma infestans

Bolivia

TcV

hap17

KU686477

KU686481

 Bug2148

Triatoma infestans

RS/Brazil

TcV

hap17

KU686478

KU686482

 CLBrener

Triatoma infestans

SP/Brazil

TcVI

hap17

KU686479

KU686483

 Tulacl2

Homo sapiens

Chile

TcVI

hap17

KU686480

KU686484

 CLBrener

Triatoma infestans

SP/Brazil

TcVI

hap17

DQ343645b

 

 Bug2148_1

Triatoma infestans

RS/Brazil

TcV

  

HQ452737b

 Bug2148_2

Triatoma infestans

RS/Brazil

TcV

  

HQ452738b

 CLBrener_1

Triatoma infestans

SP/Brazil

TcVI

  

HQ452739b

 CLBrener_2

Triatoma infestans

SP/Brazil

TcVI

  

HQ452740b

T. c. marinkellei

 COLTRYP 107

Phyllostomus discolor

GO/Cerrado

 

hap18

KU145458

KT390244

 COLTRYP 117

Phyllostomus discolor

GO/Cerrado

 

hap18

KU256222

KU256228

 COLTRYP 143

Phyllostomus discolor

GO/Cerrado

 

hap18

KU256223

KU256229

 COLTRYP 576

Phyllostomus hastatus

AC/Amazon

 

hap19

KX620471

KX620476

 COLTRYP 577

Phyllostomus hastatus

AC/Amazon

 

hap19

KX620472

KX620477

 B7

Phyllostomus discolor

BA/Brazil

 

hap18

KC427240b

AY484485b

 TCC 344

Carollia perspicillata

RO/Brazil

 

hap19

KT327227b

KT327313b

T. dionisii

 COLTRYP 596

Anoura geoffroyi

ES/Atlantic Forest

 

hap21

KX274234

KX274236

 COLTRYP 598

Carollia sp.

ES/Atlantic Forest

 

hap21

KX274235

KX274237

 COLTRYP 621

Anoura geoffroyi

ES/Atlantic Forest

 

hap21

KX620468

KX620473

 COLTRYP 622

Carollia sp.

ES/Atlantic Forest

 

hap21

KX620469

KX620474

 COLTRYP 623

Carollia sp.

ES/Atlantic Forest

 

hap21

KX620470

KX620475

T. rangeli

 R1625

Homo sapiens

El Salvador

 

hap23

KU176138

KU176137

 RGB

Canis familiaris

Colombia

   

AY484486b

 SC58

Echimys dasythrix

SC/Brazil

 

hap24

KJ803830b

 

aHap (cox1): haplotype inferred for cox1 in DnaSP v5.10.01

bSequences retrieved from GenBank

Abbreviations: Brazilian states: AC Acre, AM Amazonas, BA Bahia, CE Ceará, ES Espírito Santo, GO Goiás, MS Mato Grosso do Sul, PA Pará, PI Piauí, RJ Rio de Janeiro, RO Rondônia, RS Rio Grande do Sul, SC Santa Catarina, SP São Paulo, TO Tocantins

Fig. 2

Phylogenetic tree based on cox1 and the geographical origin of the isolates under study. a The cox1 gene differentiates T. cruzi DTUs TcI, TcII, TcIII and TcIV, Tcbat, T. c. marinkellei, T. dionisii and T. rangeli. The heterozygous hybrids TcV and TcVI cannot be differentiated and were placed into the same cluster as TcIV. The numbers at the nodes correspond to NJ, ML, MP and BI support values, respectively (only values >60 are shown). The scale-bar shows the number of nucleotide substitutions per site. The different haplotypes correspond to the diversity observed in cox1 sequences and are represented by colors in the tree. b The map represents the distribution of the characterized isolates among Brazilian biomes. Each colored circle indicates a different haplotype. Circle size represents the number of haplotypes. Abbreviations: Brazilian states: AC, Acre; BA, Bahia; CE, Ceara; ES, Espírito Santo; GO, Goiás; MS, Mato Grosso do Sul; PA, Pará; PI, Piauí; RJ, Rio de Janeiro; SC, Santa Catarina; TO, Tocantins

Nine T. cruzi references were also genotyped and used as DTU standards. Colombiana (COLPROT 004), Dm28c (COLPROT 010), Y (COLPROT 106), 3663 (COLPROT 608), 4167 (COLPROT 607) DNA samples obtained from the Protozoa Collection - COLPROT (FIOCRUZ, Rio de Janeiro, Brazil); Sc43cl1, Bug2148cl1, CLBrener and Tulacl2 DNA samples were a kind gift from Dr. Michael Miles from the London School of Hygiene & Tropical Medicine (London, UK). The T. rangeli lineage R1625 DNA sample (COLPROT 002) was obtained from COLPROT (Table 1). In addition, cox1 and GPI sequences were retrieved from the GenBank database and used as references (Table 1).

PCR and sequencing

A fragment of the mitochondrial gene cox1 was amplified using a set of forward (5′-CCA WAC AAC AAA CAT ATG ATG CTG C-3′) and reverse (5′-TCC HGA TAT GGT WTT KCC YCG-3′) primers. Polymerase chain reaction (PCR) was conducted in a 50 μl final reaction volume containing 2.5 mM MgCl2 (Invitrogen, Carlsbad, California, USA), 0.25 mM of each nucleotide (Thermo Scientific, Waltham, Massachusetts, USA), 0.25 mM of each primer (IDT, Coralville, Iowa, USA), 1.0 U of Platinum Taq DNA polymerase (Invitrogen), and 50 ng of DNA template. The amplification was performed using a Veriti 96-Well Thermal Cycler (Applied Biosystems, Foster City, California, USA) with the following cycle conditions: denaturation at 95 °C for 3 min; followed by 35 cycles at 95 °C for 1 min, 54 °C for 1 min, and 72 °C for 1 min; and a final elongation step at 72 °C for 10 min. Nucleotide sequences were also determined using a fragment of the nuclear gene GPI. The primers and cycling conditions are described elsewhere [20]. The PCR products were separated on 1.5% agarose gels and stained with GelRed (Biotium Inc., Fremont, California, USA). The fragments were purified using the Wizard Genomic DNA Purification Kit, according to manufacturer’s instructions (Promega, Madison, Wisconsin, USA), and direct sequencing of both strands of DNA was performed with BigDye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems) using an ABI 3730 DNA sequencer available at the RPT01A/FIOCRUZ sequencing facilities.

Data analysis

The sequences were manually edited using Geneious software version 8.1.6. (Biomatters, Auckland, New Zealand) and aligned using the CLUSTAL X version 2.1 multiple alignment program [59]. All sequences were translated to confirm the absence of premature stop codons. All sequences generated were deposited in the GenBank database (Table 1).

The heterozygous hybrid lineages (TcV and TcVI) amplified for GPI were subjected to haplotype reconstruction using the PHASE algorithm implemented in DnaSP v5.10.01 [60].

The neighbor-joining (NJ) method and Kimura 2-parameters (K2P) model were applied for both cox1 and GPI genes according to the barcode approach [4]. NJ analyses were performed with MEGA version 6 [61]. For each node, bootstrap percentages (BP) were computed after 1000 resamplings.

The maximum likelihood (ML) method was also applied to each topology. The model of nucleotide substitution that best fitted the cox1 data was the Hasegawa-Kishino-Yano’s model (HKY), with a gamma-distributed rate (Γ). For GPI, the best-fit model was the Tamura-Nei model, with a gamma-distributed rate. These models were selected using the Akaike Information Criterion corrected for small samples (AICc) approach implemented in the program jModelTest [62]. ML analyses were performed using PhyML 3.0 [63]. For each node, BP were computed after 1000 resamplings.

Maximum Parsimony (MP) analyses were performed using PAUP* 4.0b10 [64]. For the tree search and bootstrap we used a heuristic search with 100 random sequence addition replicates through tree bisection and reconnection (TBR) branch-swapping algorithm. Bayesian inference (BI) was run in MrBayes v3.2.6 [65] with a general time reversible model with gamma-distributed rate variation across sites and a proportion of invariable sites (GTR + Γ + I). The runs converged after 1,000,000 generations, by sampling every 100th generation and discarding the first 25% of the trees as ‘burn-in’. Cox1 and GPI sequences were concatenated in SequenceMatrix 1.8 [66] and submitted to NJ, ML, MP and BI analysis as described above.

The number of haplotypes, nucleotide diversity (π) and haplotype diversity (Hd) were calculated for both genes, except for Tcbat, which had a single sequence available in GenBank. The analyses were run in DnaSP v5.10.01 [60].

Molecular species delimitation was evaluated using distance-based methods and coalescent-based models. Distance-based analyses included the pairwise intraspecific and interspecific distances calculated using MEGA version 6 [61] and the Automatic Barcode Gap Discovery (ABGD) method, which detects a gap in the distribution of pairwise distances and uses this information to partition the sequences into groups of hypothetical species [67]. ABGD analysis was conducted in the web version: Jukes Cantor, K2P and p distances were calculated, and the remaining parameters were used as default [67]. Coalescent-based analysis included the single-rate Poisson Tree Processes (PTP) model [68], which considers that every species evolved at the same rate, and the multi-rate Poisson Tree Processes (mPTP) [69], which assumes a different evolution rate for each species. PTP and mPTP analyses were conducted using the web version of this software [69].

Results

Cox1 and GPI gene fragments were successfully amplified for a panel of 62 Trypanosoma spp. isolates and ten reference strains (Table 1). All sequences were translated to amino acids and compared to cox1 and GPI proteins. No indels (insertions/deletions) or stop codons were detected. No pseudo genes or contaminants were observed.

Phylogenetic tree reconstruction using cox1 as barcode

The clusters observed in the cox1 trees were the same for all methods tested, indicating that these groups are robust and do not depend on the evolutionary methods selected (Fig. 2a). Cox1 discriminated species belonging to the subgenus Schizotrypanum and T. cruzi DTUs. TcI and Tcbat were closely related but clearly constitute two different DTUs with a statistical support of 99, 70, 92 and 100 in NJ, ML, MP and BI analysis, respectively (Fig. 2a). TcIII and TcIV sequences were separated into two different clusters with bootstrap values of 99, 87, 93 and 100 in NJ, ML, MP and BI analysis, respectively. For the heterozygous hybrid lineages, TcV and TcVI formed an indistinguishable group in the same cluster as TcIV.

Phylogenetic tree reconstruction using GPI

Both GPI and cox1 helped recognize Schizotrypanum species, but not T. cruzi DTUs. Depending on the method used for the phylogenetic tree reconstruction there was a slightly different topology. Tcbat and TcI clustered together and could not be differentiated in the tree (Fig. 3). In NJ analysis TcIII constituted a separate DTU close to TcI (Fig. 3a). However, with ML, MP and BI methods TcI, Tcbat and TcIII clustered together (bootstrap of 80, 77 and 82, respectively) (Fig. 3b). GPI sequences generated for TcV and TcVI presented electropherograms with double peaks (i.e. with two bases at the same position) and were submitted to haplotype reconstruction prior to use in the final alignments and tree reconstructions. This analysis resulted in two sequences for each hybrid sample corresponding to alleles. One allele was closer to TcII, and the other allele was closer to TcIII (Fig. 3).
Fig. 3

Phylogenetic tree based on nuclear gene GPI. a Tree inferred with neighbor-joining method and Kimura-2-parameter model. GPI recognizes and differentiates T. cruzi DTUs TcI, TcII, TcIII and TcIV, T. c. marinkellei, T. dionisii and T. rangeli. One allele of TcV and TcVI sequences cluster with TcII, and the other allele clusters with TcIII. Tcbat was placed in the same cluster as TcI. b The tree inferred from maximum likelihood, parsimony and Bayesian inference. T. cruzi, T. c. marinkellei, T. dionisii and T. rangeli are clearly separated from each other. DTUs TcI and TcII are the most genetically divergent. Tcbat, TcI and TcIII fall in the same cluster. One allele of TcV and TcVI clustered with TcII, and the other allele clustered with the group comprising TcI, TcIII and Tcbat. The numbers at the nodes correspond to ML, MP and BI support values, respectively (only values >60 are shown). The scale-bar shows the number of nucleotide substitutions per site

The geographical distribution of the trypanosomatid isolates under study is represented in Fig. 2b. Both cox1 and GPI sequences demonstrated the differences between T. cruzi, T. c. marinkellei, T. dionisii and T. rangeli and also, to some degree, T. cruzi lineages. Cox1 and GPI phylogenies equally demonstrated that TcI and TcII are the most genetically distant branches, but showed differences concerning the positions of the DTUs TcIII, TcIV, TcV, TcVI and Tcbat in the phylogenetic trees. The mitochondrial gene cox1 may be a better discriminator of T. cruzi lineages, identifying five DTUs and TcV/TcVI as a single group (Fig. 2a). Additionally, these differences between mitochondrial and nuclear tree topologies, no incongruence was observed in DTU assignment (Table 1), and mitochondrial introgression events were absent in the present sample set.

Identification of T. cruzi DTUs through single nucleotide polymorphisms (SNPs)

Some T. cruzi sequences were not clearly assigned to a DTU based solely on information from the trees. In the cox1 tree, TcIV and TcV/TcVI sequences were arranged in the same cluster (Fig. 2a), whereas in GPI analyses, TcI, TcIII and Tcbat separation was blurred (Fig. 3). Therefore, the multiple sequence alignment of cox1 and GPI data was considered for the evaluation of single nucleotide polymorphisms (SNPs) using T. cruzi sequences only. These polymorphisms were informative to DTU differentiation for both genes.

In the cox1 gene fragment analysis, we identified 84 polymorphic sites. We observed a single nucleotide polymorphism (SNP) that differentiates the heterozygous hybrids from TcIV sequences. A T (thymine) was present at position 1264 of the cox1 gene in all ten TcIV sequences analyzed, whereas TcV and TcVI sequences display a C (cytosine) at the same site. No polymorphism differentiating TcV from TcVI was observed (Additional file 1: Figure S1).

In the GPI analysis we identified 20 polymorphic sites concerning all T. cruzi sequences. A thymine at position 315 separates Tcbat from TcI (cytosine) and one guanine to adenine change separates TcI from TcIII at position 396 of the gene (Additional file 2: Figure S2). No polymorphism discriminating TcV from TcVI sequences was observed.

Phylogenetic tree reconstruction using concatenated data

The concatenation of cox1 and GPI gene fragments confirmed, with robust statistical support values, the separation of species belonging to the subgenus Schizotrypanum and the T. cruzi DTUs.

TcI, TcII, TcIII and TcIV sequences constituted clearly separated clades. In addition, concatenated data supported Tcbat as a sister clade to TcI. The heterozygous hybrids TcV and TcVI could not be differentiated and formed a cluster separate from TcIV. The topologies observed in the trees were the same for the four methods tested (NJ, ML, MP and BI) and were supported by values above 80 in the main branches (Fig. 4).
Fig. 4

Phylogenetic tree based on the concatenation of cox1 and GPI sequences. The concatenated data show a clear separation between T. cruzi DTUs TcI, TcII, TcIII and TcIV, Tcbat, T. c. marinkellei, T. dionisii and T. rangeli. The heterozygous hybrids TcV and TcVI were not differentiated from each other. The numbers at the nodes correspond to NJ, ML, MP and BI support values, respectively (only values >60 are shown). The scale-bar shows the number of nucleotide substitutions per site

Genetic diversity evaluated with cox1 and GPI genes

Although the cox1 gene did not distinguish TcV from TcVI, this gene demonstrated diversity in T. cruzi DTUs TcI, TcII and TcIII and T. c. marinkellei and T. rangeli (Additional file 3: Table S1, Fig. 2b). GPI sequences also displayed distinct haplotypes in T. c. marinkellei and T. rangeli, but lower intra-DTU diversity. The correlation between haplotype and geographical area or host species was not evident.

In the cox1 analysis, TcI was demonstrated as the most diverse DTU with the highest nucleotide diversity and haplotype diversity of all DTUs, followed by TcIII and TcII. The TcI isolates and reference strains in the present study were distributed in eight haplotypes throughout five Brazilian biomes (Fig. 2b) and six different host orders (Carnivora, Chiroptera, Didelphimorphia, Hemiptera, Primates and Rodentia) (Table 1). In the Amazon, we observed the highest number of different TcI haplotypes in the Para state (hap 2, 3 and 5). Haplotypes 2 and 5 were observed only in the Para State, while haplotype 3 was widely distributed and detected in four different biomes (Amazon, Atlantic Forest, Caatinga and Pantanal). Additionally, in Para, we observed two different haplotypes in three TcI isolates derived from Didelphis marsupialis (Table 1). Thus, establishing a correlation between the TcI haplotype and location or host species would be premature. Substantial genetic diversity was also observed in TcIII sequences. In four TcIII isolates derived from Monodelphis domestica (Cerrado biome), Galictis vittata (Atlantic Forest), Rhodnius pictipes (Amazon biome) and a reference strain from Panstrongylus geniculatus (Amazon biome), we identified three different haplotypes (Table 1, Fig. 2b). These TcII isolates were divided into three haplotypes and originated from primates, a marsupial and triatomines captured in the Atlantic Forest and from a rodent captured in the Caatinga biome. The reference strains were isolated from humans in the Atlantic Forest. The three TcII haplotypes were distributed in the state of Rio de Janeiro, isolated from a Philander frenatus and two Leontopithecus rosalia (Table 1). Genetic diversity was not detected among the TcIV, TcV and TcVI isolates. Diversity could not be evaluated for Tcbat, reflecting the unique sequence available for this DTU.

The seven T. c. marinkellei isolates displayed three haplotypes (Additional file 3: Table S1, Fig. 2b). One haplotype was formed by isolates originated from P. discolor from the Goiás State (Cerrado) and the Bahia state (Atlantic Forest); another haplotype comprised isolates originated from P. hastatus from the Acre State (Amazon biome); and a third group was formed by the reference strain TCC 344, isolated from C. perspicillata (Amazon) (Table 1, Fig. 2a). Despite the low number of isolates, an apparent correlation between haplotype and host species was observed.

We compared two T. rangeli isolates previously identified as lineages C and D [54, 70, 71]. Sequences generated with cox1 exhibited two different haplotypes (Table 1, Additional file 3: Table S1). Trypanosoma dionisii sequences showed no diversity. Isolates derived from two different species of phyllostomid bats from the same geographical area and collected during the same field expedition (Table 1, Additional file 3: Table S1).

In the GPI analysis, intra-DTU diversity was lower than observed with cox1. TcI, TcII, TcIII and TcIV sequences displayed two different haplotypes each. In TcIV, one haplotype was formed by the nine isolates identified herein and the reference strain 4167, while the other haplotype only comprised the reference strain CANIII, which was not available for cox1 analysis. No diversity within TcV/TcVI sequences was detected.

The highest diversity in GPI sequences was observed in T. c. marinkellei with five haplotypes. One haplotype comprised three isolates from the Goiás state (Cerrado) and the other haplotypes corresponded to the other four isolates (Additional file 3: Table S1, Fig. 3). The two T. rangeli sequences generated with GPI were identified elsewhere as lineage C [71]. However, these sequences displayed distinct haplotypes (Additional file 3: Table S1, Fig. 3). No diversity within T. dionisii sequences was observed. No correlation between haplotype, host or geographical location could be established.

Barcoding gap and species delimitation with cox1 and GPI sequences

Based on the analysis of the barcode gaps we assessed and compared the efficiency of cox1 and GPI for the identification of trypanosomatids. In cox1 the mean genetic distance between T. cruzi sequences and T. c. marinkellei was 13%. The mean intraspecific divergence for T. cruzi was 7.6%, a value lower than the mean interspecific value. However, comparing the minimum and maximum values, we observed an overlap of the genetic distances between T. cruzi and T. c. marinkellei (10.1–15.3%) and the intraspecific divergence for T. cruzi (0–12.7%), indicating the absence of a limit that separates these two subspecies (i.e. absence of a barcoding gap). The divergence between T. cruzi and T. dionisii limits was 13.0–16.0%, while the divergence between T. cruzi and T. rangeli was 14.7–21.3%, indicating that the genetic distance separating T. cruzi, T. dionisii and T. rangeli as different species is 0.3 and 2.0%, respectively (Additional file 4: Table S2).

GPI was not as discriminative as cox1. The mean interspecific divergence between T. cruzi sequences and T. c. marinkellei, T. dionisii and T. rangeli was 3.6, 7.8 and 13.7%, respectively.

We observed differences between T. c. marinkellei sequences in the trees (Fig. 3) confirmed by an intraspecific distance ranging from 0 to 1.0% (Additional file 5: Table S3). Distance within T. rangeli sequences was 0.7% and there was no genetic difference between T. dionisii sequences. For T. cruzi, the intraspecific genetic distance ranged from 0 to 3.0%, i.e. lower than the mean interspecies values (Table 2). Similar to cox1, we observed an overlap of the genetic distances between T. cruzi and T. c. marinkellei with GPI, indicating the absence of a “barcoding gap”.
Table 2

cox1 and GPI sequences division in groups based on ABGD analysis

Substitution model

Xa

Partition

Prior intraspecific divergence (P)

0.059948

0.035938

0.021544

0.012915

0.007743

0.004642

0.002783

0.001668

0.001000

cox1

 Jukes Cantor

1.5

Initial

6

6

6

10

10

10

10

10

10

Recursive

  

8

11

14

14

14

21

21

 K2Pb

1.5

Initial

6

6

6

11

11

11

11

11

11

Recursive

  

8

 

14

14

14

19

19

 p-distance

1.5

Initial

 

6

6

6

6

6

6

6

6

Recursive

 

0

8

9

9

9

11

11

11

GPI

 Jukes Cantor

1.5

Initial

2

2

3

3

5

7

3

14

14

Recursive

      

7

  

 K2Pb

1.5

Initial

2

2

3

3

5

7

3

14

14

Recursive

      

7

  

 p-distance

1.5

Initial

2

2

3

3

5

5

5

7

7

Recursive

         

aX, relative gap width

b K2P Kimura 2-parameter

Trypanosoma cruzi and T. c. marinkellei were separated into distinct groups according to ABGD, PTP and mPTP analysis using cox1 and GPI data. Here, we report the results for the three substitution models and both initial and recursive partitions in the output of ABGD. The results varied from 6 to 21 for cox1 depending on the substitution model used, confirming diversity in T. cruzi sequences and the separation of T. cruzi, T. c. marinkellei, T. rangeli and T. dionisii (Table 2). Trypanosoma cruzi sequences were divided into a minimum of three groups in the three models tested. One group corresponded to Tcbat and TcI; another group corresponded only to TcII sequences only; and a third group comprised TcIII, TcIV, TcV and TcVI sequences. A maximum of 13 different groups were observed, with TcI sequences divided into eight different groups, showing the higher intra-DTU diversity of TcI compared to the other DTUs (Additional file 6: Table S4). In all models and partitions, T. dionisii sequences were arranged in one group.

The number of ABGD groups for GPI data varied from 2 to 14 depending on the model applied (Table 2). Trypanosoma cruzi sequences were separated into different groups. TcI sequences were grouped together, showing less variability with GPI. TcII sequences were divided into two groups: one group with only TcII sequences and another group with TcII, TcV (allele 1) and TcVI (allele 1). TcIII sequences were grouped together with sequences representing the other TcV and TcVI alleles. TcIV sequences were combined in one group, except for the reference strain CANIII, which was placed in a separated group. Trypanosoma cruzi marinkellei and T. rangeli sequences were divided into groups, reaffirming their diversity (Additional file 7: Table S5), while T. dionisii sequences formed one group in all tests (Table 2, Additional file 7: Table S5).

The number of groups recovered by ABGD was higher than the number of species studied. However, this finding confirms the genetic diversity within T. cruzi DTUs, T. c. marinkellei and T. rangeli observed in the phylogenetic trees (Figs. 2a and 3).

The PTP and mPTP models identified, respectively, a total of 10 and 7 putative species in the cox1 dataset (Table 3). Four of these putative species were subdivisions of T. cruzi, indicating the heterogeneity of this taxon. The PTP model also recognized diversity within T. c. marinkellei and T. rangeli sequences.
Table 3

Number of species according to PTP and mPTP delimitation methods

Gene and taxon

PTP

mPTP

Number of putative species

cox1

T. cruzi

4

4

T. c. marinkellei

3

1

T. dionisii

1

1

T. rangeli

2

1

 Total

10

7

GPI

T. cruzi

3

3

T. c.marinkellei

1

1

T. dionisii

1

1

T. rangeli

2

1

 Total

7

6

PTP and mPTP provided a similar number of putative species for GPI sequences (Table 3). Trypanosoma cruzi was divided into three groups, and T. c. marinkellei sequences were allocated into one group. The difference between models was observed in the T. rangeli sequences, separated into two groups or placed into one group.

In cox1 and GPI analysis using both models, T. cruzi, T. c. marinkellei, T. rangeli and T. dionisii were recognized as different species. The diversity of T. cruzi was confirmed, and no diversity was observed in T. dionisii sequences.

Discussion

In the present study, the DNA barcoding approach using the cox1 gene has been demonstrated to be efficient at recognizing Trypanosoma species and their major subpopulations. With cox1, we distinguished T. cruzi from T. c. marinkellei, T. donisii and T. (Tejeraia) rangeli, fulfilling the main DNA barcode demands of a short gene fragment that can be sequenced in diverse sample sets and generating comparable sequences that enable the distinction of species from each other [4]. We also generated a library of trypanosome sequences for cox1 and GPI genes. Each specimen analyzed is linked to an identification number, collection date, country, region and host of origin, geographical coordinates and other information that enable the tracking of the origin of the specimen and ensure the reproducibility of subsequent experiments.

Trypanosoma cruzi is currently divided into seven DTUs [29]. Using cox1, we identified five T. cruzi groups (TcI, TcII, TcIII, TcIV and Tcbat). The DTUs TcI and TcII are consistently shown as the most genetically distant groups, well separated by cox1 in all four methods tested (Fig. 2a). This structure has been observed by other authors in trees with high bootstrap support values, sustaining TcI and TcII as the two discernible DTUs, independently of gene or method used [25, 51, 72, 73]. Furthermore, this system showed the potential for separating genetically closer DTUs. We observed Tcbat as a separated cluster within T. cruzi and its proximity to TcI, consistent with Marcili et al. [25]. According to other studies using cytb, V7 V8 rRNA and gGAPDH genes this relationship is unanimous [26, 51, 74, 75]. However, the data on Tcbat are still limited, as only one sequence was generated with cox1 available in GenBank. Our cox1 sequences also showed the homozygous hybrids TcIII and TcIV forming distinct groups in all methods tested (Fig. 2a). These DTUs are proposed to have been originated from the genetic exchange between TcI and TcII and evolved separately giving origin to TcIII and TcIV [76, 77]. The genetic proximity between TcIII and TcIV is undeniable, and their separation and position in the phylogenetic trees is altered by the gene and method of inference selected. Based on cytb (inferred by MP), V7 V8, gGAPDH, GPI genes and MLST approaches, TcIII and TcIV were identified as two separate DTUs [2426, 28, 51]. However, in other studies using the cytb gene (inferred by neighbor-joining and maximum likelihood), TcIII and TcIV were identified as a single group [34, 51, 77]. TcV and TcVI sequences were indistinguishable and clustered with TcIV (Fig. 2a), consistent with previous cytb mitochondrial gene results [25]. In some studies, independently of the molecular marker and phylogenetic method applied, TcV and TcVI were also indistinguishable from each other. However, these hybrids clustered together with TcII or TcIII when analyzed using nuclear markers [25, 26, 34, 78]. In contrast, in studies using 4 to 10 gene fragments and neighbor-joining trees, TcV and TcVI appeared as two distinct DTUs [24, 79]. In the cox1 analysis, we observed one SNP that differentiates TcIV sequences from TcV/TcVI (Additional file 1: Figure S1). This nucleotide polymorphism, combined with the phylogenetic tree, was demonstrated as relevant to DTU assignment. However, TcV and TcVI are the less conspicuous lineages, and their separation remains an issue.

Cox1 was also suitable to determine diversity within DTUs TcI, TcII and TcIII (Additional file 3: Table S1). The number of sequences classified as TcI and the number of different haplotypes in these DTU sequences were the highest, compared to the other DTUs. The diversity within TcI is consistent with previous studies and may be explained by TcI being a multi-host lineage widely distributed throughout Brazilian biomes, representing the DTU with the largest set of samples analyzed, and consequently, the DTU with the most published studies compared to the other DTUs [20, 51, 52, 80, 81]. The nucleotide and haplotype diversity of the TcII sequences generated using cox1 were lower. However, this effect may not reflect the reality, but rather may show subsampling. In the Rio de Janeiro State, we observed one TcII haplotype circulating in a specimen of L. rosalia and a different haplotype in another specimen of L. rosalia. This observed diversity may reflect primates captured in different years and the changes in TcII haplotype circulation in that area. Nevertheless, the same host can harbor different haplotypes from the same parasite, and one haplotype can prevail over another in different moments of isolation. Diversity within TcII has previously been demonstrated through the sequencing of the glycoprotein 72 gene (gp72) and showed that this DTU has a higher distribution range than previously considered [56]. The high haplotype diversity observed in TcIII could result from overestimation, since we identified three different haplotypes in the four sequences analyzed, belonging to isolates from different Brazilian regions. However, this scenario shows TcIII distributed in a wide geographical range, infecting marsupials, carnivores and triatomines (Table 1). This finding clearly indicates that the richness within TcIII, and its dispersion is yet to be explored. Diversity in TcIII has previously been observed based on V7 V8, cytb, GPI, MLST approaches, but no correlation with geographical area or host species was evident [24, 25, 28]. In the present study, TcIV samples were isolated from triatomines and rodents from the same geographical area (Table 1). This aspect might explain the observation of only one haplotype in TcIV sequences. However, isolates from rodents were collected 11 years before the parasites isolated from the intestinal content of triatomines. Thus, we propose that TcIV haplotype circulation in the Pantanal area was at least equally predominant throughout more than a decade. However, the TcIV reference was isolated from a triatomine in the Amazon region (Table 1) and had the same haplotype as the Pantanal isolates. This finding could reflect the conservation of the cox1 region in TcIV. A correlation between TcIV diversity and the geographical region has been suggested by other studies based on mitochondrial genes cytb and cytochrome c oxidase subunit 2-NADH dehydrogenase subunit 1 (cox2-nad1) [28, 34, 77].

The cox1 tree topologies, independently of the method applied, showed T. c. marinkellei as a sister clade to the monophyletic clade formed by all T. cruzi DTUs (Fig. 2a); we also observed genetic diversity within T. c. marinkellei (Additional file 3: Table S1). Even with the characterization of a low number of isolates, the samples were separated into two groups, and a sequence retrieved from GenBank was positioned in a third group (Fig. 2a). Heterogeneity within T. c. marinkellei has previously been reported [75, 82, 83]. Subdivision into two major groups (T.c.m.I and II) and a potential third group (lineage Z) was proposed using multilocus enzyme electrophoresis (MLEE) and random amplified polymorphic DNA (RAPD). No association with a host or geographical distribution was confirmed [82]. This lack of evidence for an association and the different markers used prevented the comparison of these data.

We also observed genetic differences between T. rangeli reference sequences R1625 and SC58 classified, respectively, as lineage C and lineage D [54, 70]. Previous studies have proposed the subdivision of T. rangeli in five lineages (A-E), based on spliced leader and SSU rDNA [54, 70, 71]. Even with only two sequences, we suggest that cox1 can distinguish different T. rangeli lineages and is a promising tool for use in species identification.

In the present study, we showed the first T. dionisii sequences for the cox1 gene. The nucleotide sequences were deposited in GenBank, contributing to the enhancement of the barcode public library for Trypanosoma species. We did not observe diversity among these sequences (Fig. 2a, Additional file 3: Table S1), likely because the samples were collected from bats of the same area. No subdivisions in groups or subpopulations have been proposed for T. dionisii until recently. Although potential diversity within this species can be observed in cytb and 18S (SSU) phylogenetic trees, these data were not reported [84].

The concomitant analysis of the mitochondrial gene cox1 and the nuclear gene GPI enable the confirmation of the absence of mitochondrial introgression events in the sample set. The frequency of this genetic phenomenon is unknown and has primarily been observed in heterozygous hybrid DTUs TcV and TcVI, where uniparental inheritance of maxicircle kDNA is the rule [28, 36, 56, 85]. Cox1 has limitations and does not work as a single barcode in all situations [1], and since T. cruzi possesses heterozygous hybrid lineages and mitochondrial introgression events have previously been reported, we proposed this cox1-GPI barcoding system. Additionally, the concatenated analysis of cox1 and GPI confirmed T. cruzi DTU separation (Fig. 4).

Consistent with the cox1 results, GPI distinguished T. cruzi from T. c. marinkellei, T. donisii and T. (Tejeraia) rangeli. Additionally, with GPI, TcI and TcII were separated into two conspicuous groups. This nuclear gene recognizes a lower number of T. cruzi groups (Fig. 3) and considerably lower intra-DTU diversity compared to cox1 (Additional files 4 and 5: Tables S2 and S3). In contrast to the cox1 results, Tcbat and TcI were clustered together. The lower power of resolution to discriminate DTUs and intra-DTU diversity might reflect the fact that GPI is a housekeeping nuclear gene, which shows a lower evolution rate than mitochondrial genes [28, 85]. Furthermore, we compared the GPI sequences with the single Tcbat sequence available in GenBank and the results may change depending on the number of sequences available. It is likely that a larger set of Tcbat sequences would resolve the incongruence between the mitochondrial and nuclear gene trees. In addition, we also observed differences in DTU placement in the trees according to the method of inference in the GPI analyses. TcIII sequences formed a cluster separate from TcI when we applied the neighbor-joining method and clustered together with TcI when maximum likelihood, parsimony and Bayesian inference were used. This effect may reflect the fact that the neighbor-joining method was based on the genetic distance matrix, where a pairwise distance matrix is produced, and the tree is inferred from this matrix; maximum likelihood, parsimony and Bayesian inference were character-based methods of inference where each position of the alignment is analyzed [86]. However, in the GPI analysis, we detected SNPs that enable the differentiation of TcI, TcIII and Tcbat (Additional file 2: Figure S2). We observed diversity within T. c. marinkellei and generated the first five T. dionisii sequences for GPI. We could not compare T. rangeli sequences generated with GPI, as both sequences analyzed belonged to lineage C [54, 70].

Barcoding gap in trypanosomatids is still an unresolved issue. Therefore, there are no parameters or cut-off values available to compare with these results. As expected, we did not observe a barcoding gap between T. cruzi and T. c. marinkellei because T. c. marinkellei is considered a subspecies of T. cruzi [87] (Additional files 4 and 5: Tables S2 and S3).

The debate concerning the definition of species will always exist since species are not discrete units, but rather continuous entities.

Conclusions

The use of partial sequences of cox1 and GPI genes can clearly identify and separate T. cruzi samples from T. c. marinkellei, T. dionisii and T. rangeli. The two-locus barcoding system using cox1 and the nuclear gene GPI revealed that mitochondrial introgression was absent from the sample set. Additionally, the resolution of cox1 at the intraspecific level shows great potential for DTU characterization, separating five DTUs and recognizing the heterozygous hybrids TcV and TcVI as one group different from all the other DTUs; the resolution of cox1 at the intraspecific level also demonstrates intra-DTU genetic diversity. Moreover, with cox1, we evaluated the diversity within T. c. marinkellei sequences and identified two T. rangeli lineages. Therefore, the cox1 gene is a promising DNA barcode for studying the genus Trypanosoma and represents a simple, fast and reliable marker.

Abbreviations

ABGD: 

Automatic Barcode Gap Discovery

BI: 

Bayesian inference

BrBOL: 

Brazilian Barcode of Life

COLPROT: 

Protozoa Collection

COLTRYP: 

Trypanosomatid collection from wild and domestic mammals and vectors

cox1: 

cytochrome c oxidase subunit 1 gene

cox2-nad1: 

cytochrome c oxidase subunit 2-NADH dehydrogenase subunit 1 gene region

cytb

cytochrome b

DTU: 

Discrete typing unit

gGAPDH: 

glyceraldehyde-3-phosphate dehydrogenase

GPI

Glucose-6-phosphate isomerase

ITS: 

Internal transcribed spacer

K2P: 

Kimura 2-parameter

LIT: 

Liver infusion tryptose

ML: 

Maximum likelihood

MLST: 

Multilocus sequencing typing

MP: 

Maximum parsimony

mPTP: 

multi-rate Poisson Tree Processes

NJ: 

Neighbor-joining

NNN: 

Novy-McNeal-Nicole medium

PTP: 

single-rate Poisson Tree Processes

SSU rDNA: 

Small subunit ribosomal DNA

V7 V8: 

Variable regions 7 and 8

Declarations

Acknowledgments

The authors would like to thank Dr. Vera Bongertz for English corrections and Carlos Ardé and Marcos Antônio dos Santos Lima for technical support. The authors would also like to thank Dr. Michael Miles from the London School of Hygiene & Tropical Medicine (London, UK) and the Protozoa Collection - COLPROT from FIOCRUZ, Brazil for providing DNA samples for the present study and the RPT01A/FIOCRUZ sequencing facilities for sequencing the samples.

Funding

The present study was funded through a grant from the Oswaldo Cruz Institute - FIOCRUZ; PAPES VI; CNPq and FAPERJ. A doctoral grant was provided by the Oswaldo Cruz Institute to MSR. AMJ is a “Cientista do Nosso Estado”, provided by FAPERJ and is financially supported through CNPq (“Bolsista de Produtividade, nível 1”, CNPq). The funders played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Availability of data and materials

All sequences analyzed are available in GenBank under the accession numbers within the article.

Authors’ contributions

MSR, KAM and AMJ conceived and designed the experiments. MSR performed and analyzed the molecular characterization. KAM provided additional suggestions on content. MSR and AMJ drafted the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable. No special permission was required for the present study. We used DNA extracted from the cultures obtained from animals collected during previous field expeditions conducted by our group. The field expeditions were endorsed by the Ethics Committee of FIOCRUZ (Oswaldo Cruz Foundation, Brazil) (CEUA L-015/04; CEUA P-292-06).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Laboratory of Trypanosomatid Biology, Oswaldo Cruz Institute, Fiocruz
(2)
Department of Ecology, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro

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