Multiple introductions and recombination events underlie the emergence of a hyper-transmissible Cryptosporidium hominis subtype in the USA

Huang, Wanyi; Guo, Yaqiong; Lysen, Colleen; Wang, Yuanfei; Tang, Kevin; Seabolt, Matthew H.; Yang, Fengkun; Cebelinski, Elizabeth; González-Moreno, Olga; Hou, Tianyi; Chen, Chengyi; Chen, Ming; Wan, Muchun; Li, Na; Hlavsa, Michele C.; Roellig, Dawn M.; Feng, Yaoyu; Xiao, Lihua

doi:10.1016/j.chom.2022.11.013

Cited by 21 publications

(31 citation statements)

References 54 publications

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“…Finally, using P. falciparum data from a highly-inbred parasite population in Guyana, we illustrate how our results based on theory and simulation translate empirically and the practical utility of various diagnostics. Beyond malaria genomic epidemiology, our results generalise to systems of largely haploid recombining eukaryotes [34, 35, 36, 37, 38] or highly-inbred diploid populations for which the haploid model of Leutenegger et al [39] is applicable.…”

Section: Introductionmentioning

confidence: 80%

“…Our results are motivated by but not limited to analyses of malaria parasites. They extend to any system concerned with pairwise relatedness of predominately haploid recombining eukaryotes (e.g., Cryptosporidium hominis [37] and Cryptosporidium parvum [36], leading causes of human and zoonotic cryptosporidiosis respectively; Coccidioides species which give rise to human coccidioidomycosis [34]; Cryphonectria parasitica, the pathogenic agent responsible for Chestnut blight [35] and Marchantia polymorpha, a model species of liverwort [38]) or highly-inbred populations of diploid organisms for which pairwise relatedness can be interrogated using a haploid model [39].…”

Section: Wgs Data)mentioning

confidence: 99%

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Systematic bias in malaria parasite relatedness estimation

Mehra,

Neafsey,

White

et al. 2024

Preprint

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Genetic studies of malaria parasites increasingly feature estimates of relatedness. However, various aspects of malaria parasite relatedness estimation are not fully understood. For example, estimates of relatedness based on whole-genome-sequence (WGS) data often exceed those based on more sparse data types. We explore systematic bias in relatedness estimation using theoretical, numerical and empirical approaches. Specifically, we use a non-ancestral model of pairwise relatedness to derive theoretical results; a simulation model of ancestry to independently verify and expand our theoretical results; and data on parasites sampled from Guyana to explore how theoretical and numerical results translate empirically. We show that allele frequencies encode, locus-by-locus, relatedness averaged over the set of sampled parasites used to compute them. These sample allele frequencies are typically plugged into the models used to estimate pairwise relatedness. Consequently, models of pairwise relatedness are misspecified and pairwise relatedness values are systematically underestimated. However, systematic underestimation can be viewed as population-relatedness calibration, i.e., a way of generating measures of relative relatedness. Systematic underestimation is unavoidable when relatedness is estimated assuming independence between genetic markers. It is mitigated when estimated using WGS data under a hidden Markov model (HMM), which exploits linkage between proximal markers. Estimates of absolute relatedness generated under a HMM using relatively sparse data should be treated with caution because the extent to which underestimation is mitigated is unknowable. That said, analyses dependent on absolute values and high relatedness thresholds are relatively robust. In summary, practitioners have two options: resolve to use relative relatedness estimated under independence or try to estimate absolute relatedness under a HMM. We propose various practical tools to help practitioners evaluate their situation on a case-by-case basis.

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Section: Introductionmentioning

confidence: 80%

Section: Wgs Data)mentioning

confidence: 99%

Systematic bias in malaria parasite relatedness estimation

Mehra,

Neafsey,

White

et al. 2024

Preprint

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“…Different strains of T. gondii show dramatic differences in their ability to antagonize IFN-γ-mediated GBP recruitment to the parasitophorous vacuole (49). Recent studies on the population structure of Cryptosporidium revealed adaptation to humans as a host and it seems likely that this was dependent on the development of species-specific immune evasion strategies (49)(50)(51). As such, the ability to compare Cryptosporidium species and strains that differ in virulence may provide new insights into host-specific interference with IFN-γ signalling while the ability to conduct genetic crosses between strains (52) offers the opportunity to uncover parasite genes and proteins that underlie these differences.…”

Section: Numerous Reports Have Described Histological Changes In the ...mentioning

confidence: 99%

Analysis of intestinal epithelial cell responses toCryptosporidiumhighlights the temporal effects of IFN-γ on parasite restriction

Pardy,

Walzer,

Wallbank

et al. 2023

Preprint

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The production of IFN-γ is crucial for control of multiple enteric infections, but its impact on intestinal epithelial cells (IEC) is not well understood.Cryptosporidiumparasites exclusively infect epithelial cells and the ability of interferons to activate the transcription factor STAT1 in IEC is required for parasite clearance. The use of single cell RNA sequencing to profile IEC during infection revealed induction of IFN-γ-dependent gene signatures that was comparable between uninfected and infected cells, and IEC expression of the IFN-γ receptor was required for parasite control. Unexpectedly, treatment ofIfng−/−mice with IFN-γ demonstrated the IEC response to this cytokine correlates with a delayed reduction in parasite burden but did not affect parasite development. These data sets provide insight into the impact of IFN-γ on IEC and suggest a model in which IFN-γ-mediated bystander activation of uninfected enterocytes is important for control ofCryptosporidium.AUTHOR SUMMARYThe cytokine interferon-gamma (IFN-γ) plays an important role in the control of intracellular infections by a wide variety of bacteria, viruses and parasites. While the impact of IFN-γ on immune cells has been a major research focus, how it impacts intestinal epithelial cells remains poorly understood.Cryptosporidiumparasites are an important cause of morbidity in a variety of epidemiological settings and exclusively infect intestinal epithelial cells (IEC). Recent advances in the ability to genetically modify and studyCryptosporidiumin wild-type hosts provides a useful model to investigate IEC-intrinsic mechanisms of pathogen control. In this study, single cell RNA-sequencing was used to analyze the IEC response to infection and IFN-γ signalling. We demonstrate broad changes in the epithelial compartment during infection that include the induction of an IEC population with robust induction of IFN-γ-stimulated genes. In addition, we show that infected IEC remain responsive to IFN-γ signalling, and that this cytokine causes a delayed reduction in parasite burden that correlates with the kinetics of IEC responsiveness to IFN-γ stimulation. Together, our work uncovers howCryptosporidiuminfection impacts the IEC compartment and helps define the relationship between the kinetics of IFN-γ responsiveness and pathogen control in IEC.

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“…Mixed infection in Cryptosporidium has been shown to promote genetic exchange, both intra-and inter-specific in the evolution of new subtypes that possess different biological potentials or host preferences (28). Specifically, admixture of these highly genetically diverse strains has led to the spread of drug-resistant parasites and the emergence of new strains with altered host preferences, or the creation of hypervirulent strains (29)(30)(31)(32)(33). High-resolution WGS data has proved to be highly sensitive and discriminatory and can detect population heterogeneity among circulating pathogens (i.e.…”

Section: Introductionmentioning

confidence: 99%

Phylogenomic reconstruction ofCryptosporidiumspp. captured directly from clinical samples reveals extensive genetic diversity

Khan,

Alves-Ferreira,

Vogel

et al. 2024

Preprint

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Cryptosporidium is a leading cause of severe diarrhea and mortality in young children and infants in Africa and southern Asia. More than twenty Cryptosporidium species infect humans, of which C. parvum and C. hominis are the major agents causing moderate to severe diarrhea. Relatively few genetic markers are typically applied to genotype and/or diagnose Cryptosporidium. Most infections produce limited oocysts making it difficult to perform whole genome sequencing (WGS) directly from stool samples. Hence, there is an immediate need to apply WGS strategies to 1) develop high-resolution genetic markers to genotype these parasites more precisely, 2) to investigate endemic regions and detect the prevalence of different genotypes, and the role of mixed infections in generating genetic diversity, and 3) to investigate zoonotic transmission and evolution. To understand Cryptosporidium global population genetic structure, we applied Capture Enrichment Sequencing (CES-Seq) using 74,973 RNA-based 120 nucleotide baits that cover ~92% of the genome of C. parvum. CES-Seq is sensitive and successfully sequenced Cryptosporidium genomic DNA diluted up to 0.005% in human stool DNA. It also resolved mixed strain infections and captured new species of Cryptosporidium directly from clinical/field samples to promote genome-wide phylogenomic analyses and prospective GWAS studies.

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Multiple introductions and recombination events underlie the emergence of a hyper-transmissible Cryptosporidium hominis subtype in the USA

Cited by 21 publications

References 54 publications

Systematic bias in malaria parasite relatedness estimation

Systematic bias in malaria parasite relatedness estimation

Analysis of intestinal epithelial cell responses toCryptosporidiumhighlights the temporal effects of IFN-γ on parasite restriction

Phylogenomic reconstruction ofCryptosporidiumspp. captured directly from clinical samples reveals extensive genetic diversity

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