Comparative genomics of Cryptosporidium parvum reveals the emergence of an outbreak-associated population in Europe and its spread to the United States
Jazyk angličtina Země Spojené státy americké Médium electronic
Typ dokumentu časopisecké články
PubMed
38977307
PubMed Central
PMC11293552
DOI
10.1101/gr.278830.123
PII: gr.278830.123
Knihovny.cz E-zdroje
- MeSH
- Cryptosporidium parvum * genetika MeSH
- epidemický výskyt choroby * MeSH
- fylogeneze MeSH
- genom protozoální MeSH
- genomika metody MeSH
- jednonukleotidový polymorfismus MeSH
- kryptosporidióza * parazitologie epidemiologie MeSH
- lidé MeSH
- sekvenování celého genomu metody MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Čína epidemiologie MeSH
- Egypt epidemiologie MeSH
- Evropa epidemiologie MeSH
- Spojené státy americké epidemiologie MeSH
The zoonotic parasite Cryptosporidium parvum is a global cause of gastrointestinal disease in humans and ruminants. Sequence analysis of the highly polymorphic gp60 gene enabled the classification of C. parvum isolates into multiple groups (e.g., IIa, IIc, Id) and a large number of subtypes. In Europe, subtype IIaA15G2R1 is largely predominant and has been associated with many water- and food-borne outbreaks. In this study, we generated new whole-genome sequence (WGS) data from 123 human- and ruminant-derived isolates collected in 13 European countries and included other available WGS data from Europe, Egypt, China, and the United States (n = 72) in the largest comparative genomics study to date. We applied rigorous filters to exclude mixed infections and analyzed a data set from 141 isolates from the zoonotic groups IIa (n = 119) and IId (n = 22). Based on 28,047 high-quality, biallelic genomic SNPs, we identified three distinct and strongly supported populations: Isolates from China (IId) and Egypt (IIa and IId) formed population 1; a minority of European isolates (IIa and IId) formed population 2; and the majority of European (IIa, including all IIaA15G2R1 isolates) and all isolates from the United States (IIa) clustered in population 3. Based on analyses of the population structure, population genetics, and recombination, we show that population 3 has recently emerged and expanded throughout Europe to then, possibly from the United Kingdom, reach the United States, where it also expanded. The reason(s) for the successful spread of population 3 remain elusive, although genes under selective pressure uniquely in this population were identified.
Animal Health Diagnostic Unit Finnish Food Authority FI 70210 Kuopio Finland
Cryptosporidium Reference Unit Public Health Wales Swansea SA2 8QA United Kingdom
Department of Biology and Biotechnology University of Pavia 27100 Pavia Italy
Department of Biology and Biotechnology University of Pavia 27100 Pavia Italy;
Department of Biosciences University of Milan 20133 Milan Italy
Department of Infectious Diseases Istituto Superiore di Sanità 00161 Rome Italy
Department of Infectious Diseases Istituto Superiore di Sanità 00161 Rome Italy;
Department of Infectious Diseases Robert Koch Institute 13353 Berlin Germany
Department of Microbiology Public Health Agency of Sweden SE 171 82 Solna Sweden
Finnish Institute for Health and Welfare FI 00271 Helsinki Finland
IRCCS Fondazione Policlinico San Matteo 27100 Pavia Italy
Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche 06126 Perugia Italy
National Institute for Agricultural and Veterinary Research 1300 Lisbon Portugal
National Institute for Public Education Budapest 1007 Hungary
Norwegian Veterinary Institute N 1431 Ås Norway
Statens Serum Institut 2300 Copenhagen Denmark
Swansea Medical School Swansea University Swansea SA2 8PP United Kingdom
Swedish Veterinary Agency SE 751 89 Uppsala Sweden
Veterinary Research Institute Department of Food and Feed Safety 621 00 Brno Czech Republic
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Alves M, Xiao L, Sulaiman I, Lal AA, Matos O, Antunes F. 2003. Subgenotype analysis of Cryptosporidium isolates from humans, cattle, and zoo ruminants in Portugal. J Clin Microbiol 41: 2744–2747. 10.1128/JCM.41.6.2744-2747.2003 PubMed DOI PMC
Baptista RP, Li Y, Sateriale A, Sanders MJ, Brooks KL, Tracey A, Ansell BRE, Jex AR, Cooper GW, Smith ED, et al. 2022. Long-read assembly and comparative evidence-based reanalysis of Cryptosporidium genome sequences reveal expanded transporter repertoire and duplication of entire chromosome ends including subtelomeric regions. Genome Res 32: 203–213. 10.1101/gr.275325.121 PubMed DOI PMC
Beghini F, McIver LJ, Blanco-Míguez A, Dubois L, Asnicar F, Maharjan S, Mailyan A, Manghi P, Scholz M, Thomas AM, et al. 2021. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. eLife 10: e65088. 10.7554/eLife.65088 PubMed DOI PMC
Beja-Pereira A, Caramelli D, Lalueza-Fox C, Vernesi C, Ferrand N, Casoli A, Goyache F, Royo LJ, Conti S, Lari M, et al. 2006. The origin of European cattle: evidence from modern and ancient DNA. Proc Natl Acad Sci 103: 8113–8118. 10.1073/pnas.0509210103 PubMed DOI PMC
Bhalchandra S, Cardenas D, Ward HD. 2018. Recent breakthroughs and ongoing limitations in Cryptosporidium research. F1000Res 7: F1000 Faculty Rev-1380. 10.12688/f1000research.15333.1 PubMed DOI PMC
Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114–2120. 10.1093/bioinformatics/btu170 PubMed DOI PMC
Bowling GA. 1942. The introduction of cattle into colonial North America. J Dairy Sci 25: 129–154. 10.3168/jds.S0022-0302(42)95275-5 DOI
Braima K, Zahedi A, Oskam C, Reid S, Pingault N, Xiao L, Ryan U. 2019. Retrospective analysis of Cryptosporidium species in Western Australian human populations (2015-2018), and emergence of the C. hominis IfA12G1R5 subtype. Infect Genet Evol 73: 306–313. 10.1016/j.meegid.2019.05.018 PubMed DOI
Cacciò SM, Chalmers RM. 2016. Human cryptosporidiosis in Europe. Clin Microbiol Infect 22: 471–480. 10.1016/j.cmi.2016.04.021 PubMed DOI
Chavez MA, White C Jr. 2018. Novel treatment strategies and drugs in development for cryptosporidiosis. Expert Rev Anti Infect Ther 16: 655–661. 10.1080/14787210.2018.1500457 PubMed DOI
Chessa B, Pereira F, Arnaud F, Amorim A, Goyache F, Mainland I, Kao RR, Pemberton JM, Beraldi D, Stear MJ, et al. 2009. Revealing the history of sheep domestication using retrovirus integrations. Science 324: 532–536. 10.1126/science.1170587 PubMed DOI PMC
Corsi GI, Tichkule S, Sannella AR, Vatta P, Asnicar F, Segata N, Jex AR, van Oosterhout C, Cacciò SM. 2023. Recent genetic exchanges and admixture shape the genome and population structure of the zoonotic pathogen Cryptosporidium parvum. Mol Ecol 32: 2633–2645. 10.1111/mec.16556 PubMed DOI
Csardi G, Nepusz T. 2006. The igraph software package for complex network research. InterJournal, Complex Systems: 1695. https://igraph.org.
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, et al. 2011. The variant call format and VCFtools. Bioinformatics 27: 2156–2158. 10.1093/bioinformatics/btr330 PubMed DOI PMC
Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, Whitwham A, Keane T, McCarthy SA, Davies RM, et al. 2021. Twelve years of SAMtools and BCFtools. GigaScience 10: giab008. 10.1093/gigascience/giab008 PubMed DOI PMC
Darriba D, Posada D, Kozlov AM, Stamatakis A, Morel B, Flouri T. 2020. ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models. Mol Biol Evol 37: 291–294. 10.1093/molbev/msz189 PubMed DOI PMC
Delsol N, Stucky BJ, Oswald JA, Cobb CR, Emery KF, Guralnick R. 2023. Ancient DNA confirms diverse origins of early post-Columbian cattle in the Americas. Sci Rep 13: 12444. 10.1038/s41598-023-39518-3 PubMed DOI PMC
DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, et al. 2011. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43: 491–498. 10.1038/ng.806 PubMed DOI PMC
Dumaine JE, Sateriale D, Gibson AR, Reddy AG, Gullicksrud JA, Hunter EN, Clark JT, Striepen B. 2021. The enteric pathogen Cryptosporidium parvum exports proteins into the cytosol of the infected host cell. eLife 10: e70451. 10.7554/eLife.70451 PubMed DOI PMC
Edgar RC. 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797. 10.1093/nar/gkh340 PubMed DOI PMC
Emms DM, Kelly S. 2019. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 20: 238. 10.1186/s13059-019-1832-y PubMed DOI PMC
Feng Y, Li N, Roellig DM, Kelley A, Liu G, Amer S, Tang K, Zhang L, Xiao L. 2017. Comparative genomic analysis of the IId subtype family of Cryptosporidium parvum. Int J Parasitol 47: 281–290. 10.1016/j.ijpara.2016.12.002 PubMed DOI PMC
Feng Y, Ryan UM, Xiao L. 2018. Genetic diversity and population structure of Cryptosporidium. Trends Parasitol 34: 997–1011. 10.1016/j.pt.2018.07.009 PubMed DOI
Ficek RE. 2019. Cattle, capital, colonization. tracking creatures of the Anthropocene in and out of human projects. Current Anthropol 60: S260–S271. 10.1086/702788 DOI
Garcia-R JC, Hayman DTS. 2016. Origin of a major infectious disease in vertebrates: the timing of Cryptosporidium evolution and its hosts. Parasitology 143: 1683–1690. 10.1017/S0031182016001323 PubMed DOI
Gruber-Vodicka HR, Seah BKB, Pruesse E. 2020. phyloFlash: rapid small-subunit rRNA profiling and targeted assembly from metagenomes. mSystems 5: e00920-20. 10.1128/mSystems.00920-20 PubMed DOI PMC
Guo Y, Ryan U, Feng Y, Xiao L. 2022. Association of common zoonotic pathogens with concentrated animal feeding operations. Front Microbiol 12: 810142. 10.3389/fmicb.2021.810142 PubMed DOI PMC
Hadfield SJ, Pachebat JA, Swain MT, Robinson G, Cameron S, Alexander J, Hegarty MJ, Elwin K, Chalmers RM. 2015. Generation of whole genome sequences of new Cryptosporidium hominis and Cryptosporidium parvum isolates directly from stool samples. BMC Genomics 16: 650. 10.1186/s12864-015-1805-9 PubMed DOI PMC
Hemstrom W, Jones M. 2023. snpR: user friendly population genomics for SNP data sets with categorical metadata. Mol Ecol Res 23: 962–973. 10.1111/1755-0998.13721 PubMed DOI
Hijjawi N, Zahedi A, Al-Falah M, Ryan U. 2022. A review of the molecular epidemiology of Cryptosporidium spp. and Giardia duodenalis in the Middle East and North Africa (MENA) region. Infect Genet Evol 98: 105212. 10.1016/j.meegid.2022.105212 PubMed DOI
Huang W, Guo Y, Lysen C, Wang Y, Tang K, Seabolt MH, Yang F, Cebelinski E, Gonzalez-Moreno O, Hou T, et al. 2023. Multiple introductions and recombination events underlie the emergence of a hyper-transmissible Cryptosporidium hominis subtype in the USA. Cell Host Microbe 31: 112–123.e4. 10.1016/j.chom.2022.11.013 PubMed DOI PMC
Huson DH, Bryant D. 2006. Application of phylogenetic networks in evolutionary studies. Mol Biol Evol 23: 254–267. 10.1093/molbev/msj030 PubMed DOI
Innes EA, Chalmers RM, Wells B, Pawlowic MC. 2020. A one health approach to tackle cryptosporidiosis. Trends Parasitol 36: 290–303. 10.1016/j.pt.2019.12.016 PubMed DOI PMC
Jann HW, Cabral-Castro MG, Barreto Costa JV, de Barros Alencar ACM, Peralta JM, Saramago Peralta RE. 2022. Prevalence of human cryptosporidiosis in the Americas: systematic review and meta-analysis. Rev Inst Med Trop Sao Paulo 64: e70. 10.1590/S1678-9946202264070 PubMed DOI PMC
Khalil IA, Troeger C, Rao PC, Blacker BF, Brown A, Brewer TG, Colombara DV, De Hostos EL, Engmann C, Guerrant RL, et al. 2018. Morbidity, mortality, and long-term consequences associated with diarrhoea from Cryptosporidium infection in children younger than 5 years: a meta-analyses study. Lancet Glob Health 6: e758–e768. 10.1016/S2214-109X(18)30283-3 PubMed DOI PMC
Khan SM, Witola WH. 2023. Past, current, and potential treatments for cryptosporidiosis in humans and farm animals: a comprehensive review. Front Cell Infect Microbiol 13: 1115522. 10.3389/fcimb.2023.1115522 PubMed DOI PMC
Kotloff KL, Nataro JP, Blackwelder WC, Nasrin D, Farag TH, Panchalingam S, Wu Y, Sow SO, Sur D, Breiman RF, et al. 2013. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the global enteric multicenter study, GEMS): a prospective, case-control study. Lancet 382: 209–222. 10.1016/S0140-6736(13)60844-2 PubMed DOI
Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods 9: 357–359. 10.1038/nmeth.1923 PubMed DOI PMC
Long S, Anthony B, Drewry LL, Sibley LD. 2017. A conserved Ankyrin repeat-containing protein regulates conoid stability, motility and cell invasion in Toxoplasma gondii. Nat Commun 8: 2236. 10.1038/s41467-017-02341-2 PubMed DOI PMC
Manske M, Miotto O, Campino S, Auburn S, Almagro-Garcia J, Maslen G, O'Brien J, Djimde A, Doumbo O, Zongo I, et al. 2012. Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing. Nature 487: 375–379. 10.1038/nature11174 PubMed DOI PMC
Martin DP, Murrell B, Golden M, Khoosal A, Muhire B. 2015. RDP4: detection and analysis of recombination patterns in virus genomes. Virus Evol 1: vev003. 10.1093/ve/vev003 PubMed DOI PMC
Mathur V, Wakeman KC, Keeling PJ. 2021. Parallel functional reduction in the mitochondria of apicomplexan parasites. Curr Biol 31: 2920–2928. 10.1016/j.cub.2021.04.028 PubMed DOI
McKerr C, O'Brien SJ, Chalmers RM, Vivancos R, Christley RM. 2018. Exposures associated with infection with Cryptosporidium in industrialised countries: a systematic review protocol. Syst Rev 7: 70. 10.1186/s13643-018-0731-8 PubMed DOI PMC
McTavish EJ, Decker JE, Schnabel RD, Taylor JF, Hillis DH. 2013. New World cattle show ancestry from multiple independent domestication events. Proc Natl Acad Sci 110: E1398–E1406. 10.1073/pnas.1303367110 PubMed DOI PMC
Murrell B, Weaver S, Smith MD, Wertheim JO, Murrell S, Aylward A, Eren K, Pollner T, Martin DP, Smith DM, et al. 2015. Gene-wide identification of episodic selection. Mol Biol Evol 32: 1365–1371. 10.1093/molbev/msv035 PubMed DOI PMC
Nader JL, Mathers TC, Ward BJ, Pachebat JA, Swain MT, Robinson G, Chalmers RM, Hunter PR, van Oosterhout C, Tyler KM. 2019. Evolutionary genomics of anthroponosis in Cryptosporidium. Nat Microbiol 4: 826–836. 10.1038/s41564-019-0377-x PubMed DOI
Nash JHE, Robertson J, Elwin K, Chalmers RA, Kropinski AM, Guy RA. 2018. Draft genome assembly of a potentially zoonotic Cryptosporidium parvum isolate, UKP1. Microbiol Resour Announc 7: e01291-18. 10.1128/MRA.01291-18 PubMed DOI PMC
Peake L, Inns T, Jarvis C, King G, Rabie H, Henderson J, Wensley A, Jarratt R, Roberts C, Williams C, et al. 2023. Preliminary investigation of a significant national Cryptosporidium exceedance in the United Kingdom, August 2023 and ongoing. Euro Surveill 28: 2300538. 10.2807/1560-7917.ES.2023.28.43.2300538 PubMed DOI PMC
Pritchard JK, Stephens M, Donnelly P. 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945–959. 10.1093/genetics/155.2.945 PubMed DOI PMC
Puiu D, Enomoto S, Buck GA, Abrahamsen MS, Kissinger JC. 2004. CryptoDB: the Cryptosporidium genome resource. Nucleic Acids Res 32: D329–D331. 10.1093/nar/gkh050 PubMed DOI PMC
Rahman SU, Mi R, Zhou S, Gong H, Ullah M, Huang Y, Han X, Chen Z. 2022. Advances in therapeutic and vaccine targets for Cryptosporidium: challenges and possible mitigation strategies. Acta Trop 226: 106273. 10.1016/j.actatropica.2021.106273 PubMed DOI
R Core Team. 2021. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/.
Ryan U, Xiao L, Read C, Zhou L, Lal AA, Pavlasek I. 2003. Identification of novel Cryptosporidium genotypes from the Czech Republic. Appl Environ Microbiol 69: 4302–4307. 10.1128/AEM.69.7.4302-4307.2003 PubMed DOI PMC
Ryan UM, Feng Y, Fayer R, Xiao L. 2021a. Taxonomy and molecular epidemiology of Cryptosporidium and Giardia – a 50 year perspective (1971–2021). Int J Parasitol 51: 1099–1119. 10.1016/j.ijpara.2021.08.007 PubMed DOI
Ryan U, Zahed A, Feng Y, Xiao L. 2021b. An update on zoonotic Cryptosporidium species and genotypes in humans. Animals (Basel) 11: 3307. 10.3390/ani11113307 PubMed DOI PMC
Schaffner SF, Taylor AR, Wong W, Wirth DF, Neafsey DE. 2018. hmmIBD: software to infer pairwise identity by descent between haploid genotypes. Malaria J 17: 196. 10.1186/s12936-018-2349-7 PubMed DOI PMC
Stamatakis A. 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30: 1312–1313. 10.1093/bioinformatics/btu033 PubMed DOI PMC
Stanke M, Keller O, Gunduz I, Hayes A, Waack S, Morgenstern B. 2006. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res 34: W435–W439. 10.1093/nar/gkl200 PubMed DOI PMC
Straschil U, Talman AM, Ferguson DJP, Bunting KA, Xu Z, Bailes E, Sinden RE, Holder AA, Smith EF, Coates JC, et al. 2010. The Armadillo repeat protein pf16 is essential for flagellar structure and function in Plasmodium male gametes. PLoS One 5: e12901. 10.1371/journal.pone.0012901 PubMed DOI PMC
Troell K, Hallström B, Divne A, Alsmark C, Arrighi R, Huss M, Beser J, Bertilsson S. 2016. Cryptosporidium as a testbed for single cell genome characterization of unicellular eukaryotes. BMC Genomics 17: 471. 10.1186/s12864-016-2815-y PubMed DOI PMC
Tůmová L, Ježková J, Prediger J, Holubová N, Sak B, Konečný R, Květoňová D, Hlásková L, Rost M, McEvoy J, et al. 2023. Cryptosporidium mortiferum n. sp. (Apicomplexa: Cryptosporidiidae), the species causing lethal cryptosporidiosis in Eurasian red squirrels (Sciurus nulgaris). Parasites Vect 16: 235. 10.1186/s13071-023-05844-8 PubMed DOI PMC
Van der Auwera GA, Connor O, DB. 2020. Genomics in the cloud: using docker, GATK, and WDL in terra. O'Reilly Media, Sebastopol, CA.
Wang R, Zhang L, Axén C, Bjorkman C, Jian F, Amer S, Liu A, Feng Y, Li G, Lv C, et al. 2014. Cryptosporidium parvum IId family: clonal population and dispersal from Western Asia to other geographical regions. Sci Rep 4: 4208. 10.1038/srep04208 PubMed DOI PMC
Wang T, Guo Y, Roellig DM, Li N, Santín M, Lombard J, Kváč M, Naguib D, Zhang Z, Feng Y, et al. 2022. Sympatric recombination in zoonotic Cryptosporidium leads to emergence of populations with modified host preference. Mol Biol Evol 39: msac150. 10.1093/molbev/msac150 PubMed DOI PMC
Wick R, Judd LM, Gorrie CL, Holt KE. 2017. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 13: e1005595. 10.1371/journal.pcbi.1005595 PubMed DOI PMC
Wickham H. 2016. ggplot2: elegant graphics for data analysis. Springer, Cham, Switzerland.
Xu Z, Guo Y, Roellig DM, Feng Y, Xiao L. 2019. Comparative analysis reveals conservation in genome organization among intestinal Cryptosporidium species and sequence divergence in potential secreted pathogenesis determinants among major human-infecting species. BMC Genomics 20: 406. 10.1186/s12864-019-5788-9 PubMed DOI PMC
Zahedi A, Ryan U. 2020. Cryptosporidium: an update with an emphasis on foodborne and waterborne transmission. Res Vet Sci 132: 500–512. 10.1016/j.rvsc.2020.08.002 PubMed DOI
Zhang C, Dong S, Xu J, He W, Yang T. 2019. PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics 35: 1786–1788. 10.1093/bioinformatics/bty875 PubMed DOI