4.6 Article

DNA-based quantification and counting of transmission stages provides different but complementary parasite load estimates: an example from rodent coccidia (Eimeria)

Journal

PARASITES & VECTORS
Volume 15, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s13071-021-05119-0

Keywords

Eimeria; Oocysts; qPCR; Parasite load; Resistance

Funding

  1. Projekt DEAL
  2. Humboldt University Berlin
  3. German Foundation of Scientific Research (DFG) [285969495/HE 7320/2-1, 440909536]
  4. German Academic Exchange Service (DAAD)
  5. Research Training Group 2046 Parasite Infections: From Experimental Models to Natural Systems(VHJD associated PhD student/EH Senior Researcher)

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This study suggests that DNA-based quantification is a better predictor of host health outcomes than counting transmissive stages. DNA quantification should be considered as a complementary source of information with potential specific biological relevance for each host-parasite system.
Background: Counting parasite transmission stages in faeces is the classical measurement to quantifyparasite load. DNA-based quantifications of parasite intensities from faecal samples are relatively novel and often validated against such counts. When microscopic and molecular quantifications do not correlate, it is unclear whether oocyst counts or DNA-based intensity better reflects biologically meaningful concepts. Here, we investigate this issue using the example of Eimeria ferrisi (Coccidia), an intracellular parasite of house mice (Mus musculus). Methods: We performed an infection experiment of house mice with E. ferrisi, in which the intensity of infection correlates with increased health impact on the host, measured as temporary weight loss during infection. We recorded the number of parasite transmissive stages (oocysts) per gram of faeces (OPG) and, as a DNA-based measurement, the number of Eimeria genome copies per gram of faeces for 10 days post-infection (dpi). We assessed weight loss relative to the day of experimental infection as a proxy of host health and evaluated whether DNA or oocyst counts are better predictors of host health. Results: Absolute quantification of Eimeria DNA and oocyst counts showed similar but slightly diverging temporal patterns during 10 dpi. We detected Eimeria DNA earlier than the first appearance of oocysts in faeces. Additionally, Eimeria OPGs within each dpi did not explain parasite DNA intensity. Early dpi were characterized by high DNA intensity with low oocyst counts, while late infections showed the opposite pattern. The intensity of Eimeria DNA was consistently a stronger predictor of either maximal weight loss (1 value per animal during the infection course) or weight loss on each day during the experiment when controlling for between-dpi and between-individual variance. Conclusions: Eimeria ferrisi oocyst counts correlate weakly with parasite intensity assessed through DNA quantification. DNA is likely partially derived from life-cycle stages other than transmissive oocysts. DNA-based intensities predict health outcomes of infection for the host more robustly than counts of transmissive stages. We conclude that DNA-based quantifications should not necessarily require validation against counts of transmissive stages. Instead, DNA-based load estimates should be evaluated as complementary sources of information with potential specific biological relevance for each host-parasite system.

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