Monomorphic : towards reconciling phylogeny and pathologies Open Access

Abstract

and are animal infective trypanosomes conventionally classified by their clinical disease presentation, mode of transmission, host range, kinetoplast DNA (kDNA) composition and geographical distribution. Unlike other members of the subgenus , they are non-tsetse transmitted and predominantly morphologically uniform (monomorphic) in their mammalian host. Their classification as independent species or subspecies has been long debated and genomic studies have found that isolates within and have polyphyletic origins. Since current taxonomy does not fully acknowledge these polyphyletic relationships, we re-analysed publicly available genomic data to carefully define each clade of monomorphic trypanosome. This allowed us to identify, and account for, lineage-specific variation. We included a recently published isolate, IVM-t1, which was originally isolated from the genital mucosa of a horse with dourine and typed as . Our analyses corroborate previous studies in identifying at least four distinct monomorphic clades. We also found clear lineage-specific variation in the selection efficacy and heterozygosity of the monomorphic lineages, supporting their distinct evolutionary histories. The inferred evolutionary position of IVM-t1 suggests its reassignment to the type B clade, challenging the relationship between the species, the infected host, mode of transmission and the associated pathological phenotype. The analysis of IVM-t1 also provides, to our knowledge, the first evidence of the expansion of type B, or a fifth monomorphic lineage represented by IVM-t1, outside of Africa, with important possible implications for disease diagnosis.

Funding
This study was supported by the:
  • Wellcome Trust (Award 108905/B/15/Z)
    • Principle Award Recipient: GuyOldrieve
  • Wellcome Trust (Award 103740/Z/14/Z)
    • Principle Award Recipient: KeithRoland Matthews FRS FMedSci FRSE
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000632
2021-08-16
2024-03-28
Loading full text...

Full text loading...

/deliver/fulltext/mgen/7/8/mgen000632.html?itemId=/content/journal/mgen/10.1099/mgen.0.000632&mimeType=html&fmt=ahah

References

  1. Vassella E, Reuner B, Yutzy B, Boshart M. Differentiation of African trypanosomes is controlled by a density sensing mechanism which signals cell cycle arrest via the cAMP pathway. J Cell Sci 1997; 110:2661–2671 [View Article] [PubMed]
    [Google Scholar]
  2. Mony BM, MacGregor P, Ivens A, Rojas F, Cowton A et al. Genome-wide dissection of the quorum sensing signalling pathway in Trypanosoma brucei. Nature 2014; 505:681–685 [View Article] [PubMed]
    [Google Scholar]
  3. McDonald L, Cayla M, Ivens A, Mony BM, MacGregor P et al. Non-linear hierarchy of the quorum sensing signalling pathway in bloodstream form African trypanosomes. PLoS Pathog 2018; 14:e1007145 [View Article] [PubMed]
    [Google Scholar]
  4. Rojas F, Silvester E, Young J, Milne R, Tettey M et al. Oligopeptide signaling through TbGPR89 drives Trypanosome quorum sensing. Cell 2019; 176:306–317 [View Article] [PubMed]
    [Google Scholar]
  5. Hoare CA. The Trypanosomes of Mammals: a Zoological Monograph Oxford: Blackwells; 1972
    [Google Scholar]
  6. Büscher P, Gonzatti MI, Hébert L, Inoue N, Pascucci I et al. Equine trypanosomosis: enigmas and diagnostic challenges. Parasit Vectors 2019; 12:234 [View Article] [PubMed]
    [Google Scholar]
  7. Lai DH, Hashimi H, Lun ZR, Ayala FJ, Lukes J. Adaptations of Trypanosoma brucei to gradual loss of kinetoplast DNA: Trypanosoma equiperdum and Trypanosoma evansi are petite mutants of T. brucei. Proc Natl Acad Sci U S A 2008; 105:1999–2004 [View Article] [PubMed]
    [Google Scholar]
  8. Carnes J, Anupama A, Balmer O, Jackson A, Lewis M et al. Genome and phylogenetic analyses of Trypanosoma evansi reveal extensive similarity to T. brucei and multiple independent origins for dyskinetoplasty. PLoS Negl Trop Dis 2015; 9:e3404 [View Article] [PubMed]
    [Google Scholar]
  9. Cuypers B, Van den Broeck F, Van Reet N, Meehan CJ, Cauchard J et al. Genome-wide SNP analysis reveals distinct origins of Trypanosoma evansi and Trypanosoma equiperdum. Genome Biol Evol 2017; 9:1990–1997 [View Article] [PubMed]
    [Google Scholar]
  10. Kay C, Williams TA, Gibson W. Mitochondrial DNAs provide insight into trypanosome phylogeny and molecular evolution. BMC Evol Biol 2020; 20:161 [View Article] [PubMed]
    [Google Scholar]
  11. Schnaufer A, Domingo GJ, Stuart K. Natural and induced dyskinetoplastic trypanosomatids: how to live without mitochondrial DNA. Int J Parasitol 2002; 32:1071–1084 [View Article] [PubMed]
    [Google Scholar]
  12. Dewar CE, MacGregor P, Cooper S, Gould MK, Matthews KR et al. Mitochondrial DNA is critical for longevity and metabolism of transmission stage Trypanosoma brucei. PLoS Pathog 2018; 14:e1007195 [View Article] [PubMed]
    [Google Scholar]
  13. Peacock L, Ferris V, Sharma R, Sunter J, Bailey M et al. Identification of the meiotic life cycle stage of Trypanosoma brucei in the tsetse fly. Proc Natl Acad Sci USA 2011; 108:3671–3676 [View Article] [PubMed]
    [Google Scholar]
  14. Wheeler RJ, Scheumann N, Wickstead B, Gull K, Vaughan S. Cytokinesis in Trypanosoma brucei differs between bloodstream and tsetse trypomastigote forms: implications for microtubule-based morphogenesis and mutant analysis. Mol Microbiol 2013; 90:1339–1355 [View Article] [PubMed]
    [Google Scholar]
  15. Radwanska M, Vereecke N, Deleeuw V, Pinto J, Magez S. Salivarian trypanosomosis: a review of parasites involved, their global distribution and their interaction with the innate and adaptive mammalian host immune system. Front Immunol 2018; 9:2253 [View Article] [PubMed]
    [Google Scholar]
  16. Suganuma K, Narantsatsral S, Battur B, Yamasaki S, Otgonsuren D et al. Isolation, cultivation and molecular characterization of a new Trypanosoma equiperdum strain in Mongolia. Parasit Vectors 2016; 9:481 [View Article] [PubMed]
    [Google Scholar]
  17. Davaasuren B, Yamagishi J, Mizushima D, Narantsatsral S, Otgonsuren D et al. Draft genome sequence of Trypanosoma equiperdum strain IVM-t1. Microbiol Resour Announc 2019; 8:e01119–18 [View Article] [PubMed]
    [Google Scholar]
  18. Brun R, Hecker H, Lun ZR. Trypanosoma evansi and T. equiperdum: distribution, biology, treatment and phylogenetic relationship (a review. Vet Parasitol 1998; 79:95–107 [View Article] [PubMed]
    [Google Scholar]
  19. Leinonen R, Sugawara H, Shumway M. International Nucleotide Sequence Database Collaboration The Sequence Read Archive. Nucleic Acids Res 2011; 39:D19–D21 [View Article]
    [Google Scholar]
  20. Engstler M, Boshart M. Cold shock and regulation of surface protein trafficking convey sensitization to inducers of stage differentiation in Trypanosoma brucei. Genes Dev 2004; 18:2798–2811 [View Article] [PubMed]
    [Google Scholar]
  21. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  22. Berriman M, Ghedin E, Hertz-Fowler C, Blandin G, Renauld H et al. The genome of the African trypanosome Trypanosoma brucei. Science 2005; 309:416–422 [View Article] [PubMed]
    [Google Scholar]
  23. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv 2013
    [Google Scholar]
  24. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 2011; 43:491–498 [View Article] [PubMed]
    [Google Scholar]
  25. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, Del Angel G et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics 2013; 11:11 [View Article] [PubMed]
    [Google Scholar]
  26. Poplin R, Ruano-Rubio V, DePristo MA, Fennell TJ, Carneiro MO et al. Scaling accurate genetic variant discovery to tens of thousands of samples. BioRxiv 2017 [View Article]
    [Google Scholar]
  27. Danecek P, Auton A, Abecasis G, Albers CA, Banks E et al. The variant call format and VCFtools. Bioinformatics 2011; 27:2156–2158 [View Article] [PubMed]
    [Google Scholar]
  28. Cook DE, Andersen EC. VCF-kit: assorted utilities for the variant call format. Bioinformatics 2017; 33:1581–1582 [View Article] [PubMed]
    [Google Scholar]
  29. Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2015; 32:268–274 [View Article] [PubMed]
    [Google Scholar]
  30. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods 2017; 14:587–589 [View Article] [PubMed]
    [Google Scholar]
  31. Hoang DT, Chernomor O, von Haeseler A, Minh BQ, Vinh LS. Ufboot2: improving the ultrafast bootstrap approximation. Mol Biol Evol 2018; 35:518–522 [View Article] [PubMed]
    [Google Scholar]
  32. Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics 2007; 23:127–128 [View Article] [PubMed]
    [Google Scholar]
  33. Marçais G, Kingsford C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 2011; 27:764–770 [View Article] [PubMed]
    [Google Scholar]
  34. Vurture GW, Sedlazeck FJ, Nattestad M, Underwood CJ, Fang H et al. GenomeScope: fast reference-free genome profiling from short reads. Bioinformatics 2017; 33:2202–2204 [View Article] [PubMed]
    [Google Scholar]
  35. Narasimhan V, Danecek P, Scally A, Xue Y, Tyler-Smith C et al. BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data. Bioinformatics 2016; 32:1749–1751 [View Article] [PubMed]
    [Google Scholar]
  36. Nelson CW, Moncla LH, Hughes AL. SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data. Bioinformatics 2015; 31:3709–3711 [View Article] [PubMed]
    [Google Scholar]
  37. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25:2078–2079 [View Article] [PubMed]
    [Google Scholar]
  38. Kolde R. Pheatmap: Pretty Heatmaps. R package; 2019
  39. Wickham H. ggplot2: Elegant Graphics for Data Analysis; 2016
  40. Slowikowski K. ggrepel: Automatically Position Non-Overlapping Text Labels with 'ggplot2', version 08. R Package; 2018
  41. R Core Team R: A language and environment for statistical computing; 2019
  42. Jaron KS, Bast J, Nowell RW, Ranallo-Benavidez TR, Robinson-Rechavi M et al. Genomic features of parthenogenetic animals. J Hered 2020; 112:19–33 [View Article] [PubMed]
    [Google Scholar]
  43. Otto SP. Selective interference and the evolution of sex. J Hered 2021; 112:9–18 [View Article]
    [Google Scholar]
  44. Zweygarth E, Kaminsky R, Webster P. Trypanosoma brucei evansi: dyskinetoplasia and loss of infectivity after long-term in vitro cultivation. Acta Trop 1990; 48:95–99 [View Article] [PubMed]
    [Google Scholar]
  45. Kaminsky R, Schmid C, Lun ZR. Susceptibility of dyskinetoplastic Trypanosoma evansi and T. equiperdum to isometamidium chloride. Parasitol Res 1997; 83:816–818 [View Article] [PubMed]
    [Google Scholar]
  46. Claes F, Radwanska M, Urakawa T, Majiwa PA, Goddeeris B et al. Variable surface glycoprotein RoTat 1.2 PCR as a specific diagnostic tool for the detection of Trypanosoma evansi infections. Kinetoplastid Biol Dis 2004; 3:3 [View Article] [PubMed]
    [Google Scholar]
  47. Ngaira JM, Olembo NK, Njagi ENM, Ngeranwa JJN. The detection of non-RoTat 1.2 Trypanosoma evansi. Exp Parasitol 2005; 110:30–38 [View Article] [PubMed]
    [Google Scholar]
  48. Birhanu H, Gebrehiwot T, Goddeeris BM, Büscher P, Van Reet N. New Trypanosoma evansi type B isolates from Ethiopian dromedary camels. PLoS Negl Trop Dis 2016; 10:e0004556 [View Article] [PubMed]
    [Google Scholar]
  49. Dean S, Gould MK, Dewar CE, Schnaufer AC. Single point mutations in ATP synthase compensate for mitochondrial genome loss in trypanosomes. Proc Natl Acad Sci USA 2013; 110:14741–14746 [View Article]
    [Google Scholar]
  50. Weir W, Capewell P, Foth B, Clucas C, Pountain A et al. Population genomics reveals the origin and asexual evolution of human infective trypanosomes. Elife 2016; 5:e11473 [View Article] [PubMed]
    [Google Scholar]
  51. Marais GAB, Campos PRA, Gordo I. Can intra-Y gene conversion oppose the degeneration of the human Y chromosome? A simulation study. Genome Biol Evol 2010; 2:347–357 [View Article] [PubMed]
    [Google Scholar]
  52. Charlesworth B. Fundamental concepts in genetics: effective population size and patterns of molecular evolution and variation. Nat Rev Genet 2009; 10:195–205 [View Article] [PubMed]
    [Google Scholar]
  53. Jensen RE, Simpson L, Englund PT. What happens when Trypanosoma brucei leaves Africa. Trends Parasitol 2008; 24:428–431 [View Article] [PubMed]
    [Google Scholar]
  54. Schnaufer A. Evolution of dyskinetoplastic trypanosomes: how, and how often?. Trends Parasitol 2010; 26:557–558 [View Article] [PubMed]
    [Google Scholar]
  55. Lord JS, Hargrove JW, Torr SJ, Vale GA. Climate change and African trypanosomiasis vector populations in Zimbabwe’s Zambezi Valley: a mathematical modelling study. PLoS Med 2018; 15:e1002675 [View Article] [PubMed]
    [Google Scholar]
  56. Aregawi WG, Agga GE, Abdi RD, Büscher P. Systematic review and meta-analysis on the global distribution, host range, and prevalence of Trypanosoma evansi. Parasit Vectors 2019; 12:67 [View Article] [PubMed]
    [Google Scholar]
  57. Payne A, Holmes N, Clarke T, Munro R, Debebe B et al. Nanopore adaptive sequencing for mixed samples, whole exome capture and targeted panels. BioRxiv 2020; Feb 3: [View Article]
    [Google Scholar]
  58. Claes F, Büscher P, Touratier L, Goddeeris BM. Trypanosoma equiperdum: master of disguise or historical mistake?. Trends Parasitol 2005; 21:316–321 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000632
Loading
/content/journal/mgen/10.1099/mgen.0.000632
Loading

Data & Media loading...

Supplements

Supplementary material 1

EXCEL

Supplementary material 2

PDF

Most cited Most Cited RSS feed