Figure 2. Many MLGs were identified at multiple time points
throughout the epidemics in A) Little Appleton and B) Crooked, but,
overall, distance between P. ramosa populations increased with
time. C) For Little Appleton, this pattern is driven mostly by the
difference between the genotypes at the beginning of the outbreak and
those from later in the outbreak, whereas for Crooked (D), genetic
distance between populations increased steadily with time between
sampling dates. Genetic distance (C,D) is calculated between populations
and is the average difference in allele frequencies between the
populations summed over all loci
(Prevosti et al.,
1975).
DISCUSSION
We tracked P. ramosa genotypes through epidemics in two lakes,
one with a large outbreak and one with a small outbreak. Parasite
genetic diversity remained relatively constant over time, but,
surprisingly, genetic diversity was much higher in the lake with the
smaller outbreak (Crooked). We found signatures of evolution in both
lakes: parasite genotypes structured by sample date in Little Appleton
and the genetic distance between parasite populations increased with
time between sampling dates in both outbreaks. In Little Appleton, there
was a large change in genetic distance between the first sampling date
and the second and relatively little change thereafter, whereas in
Crooked, the increase in genetic distance occurred more gradually over
time. Overall, our data show that parasite evolutionary trajectories may
differ across outbreaks and that ecological drivers and feedbacks
associated with epidemic size should be more extensively explored.
A priori , we would have expected greater diversity of P.
ramosa in the larger outbreak, since the much larger number of infected
hosts would presumably allow more opportunities for P. ramosa to
infect. Why, then, did we see lower diversity in the much larger Little
Appleton population? One possibility is that selection might have been
more efficient during this larger outbreak; in general, selection is
more efficient in larger populations
(Weber, 1990). The observed
structuring of parasite genotypes by sampling date in Little Appleton
might indicate that different parasite genotypes were selected over time
perhaps due to changes in the host genotypes present or other ecological
factors impacting parasite fitness. Selection on parasites by hosts or
abiotic conditions can lead to local adaptation
(Lively et al.,
2004; Koskella, 2014) and negative frequency dependent selection
(Ebert, 2008). Importantly,
both phenomena have been observed in the Daphnia -P. ramosasystem. P. ramosa assemblages are locally adapted to abiotic
conditions (namely: light penetration into lakes;
(Rogalski & Duffy, 2020))
and negative frequency dependent selection has been observed in theDaphnia-P. ramosa system over decadal time scales
(Decaestecker et al.,
2007) and has been implicated in other Daphnia -parasite systems
from observations of Daphnia genotype turnover within epidemics
(Wolinska & Spaak,
2009; Turko et al., 2018). Additional ecological factors such as
predation could also influence parasite evolution in this system. It is
noteworthy that (Gowleret al., 2022) documented the evolution of reduced spore
production during this same epidemic in Little Appleton, potentially due
to the selective pressure to shift from vegetative growth to the
production of transmission spores earlier (thus generating fewer spores)
in a likely high predation environment.
Notably, the study lakes differed in host species (i.e., cladoceran)
diversity with Crooked home to more Daphnia species than Little
Appleton (unpublished data). Species diversity is often correlated with
genotypic diversity within species
(Vellend & Geber, 2005).
This could be important because diverse host populations often
experience smaller epidemics
(King & Lively,
2012; Ekroth et al., 2019; Gibson, 2021). Even if the diversity
within our focal host did not differ between the two populations, the
higher host species diversity in Crooked may have helped to minimize the
parasite outbreak via a dilution effect
(Keesinget al., 2006; Hall et al., 2009; Strauss et al.,
2016). While different Daphnia species tend to become infected
by distinct genotypes of P. ramosa(Duneau et al.,2011; Shaw, 2019), it is possible that these species can consume and
kill parasite spores that infect D. dentifera . Future studies
that track parasite evolution across several populations that vary in
host diversity would help uncover the links between interspecific host
diversity and genotypic diversity within parasite populations.
Migration is another important determinant of parasite diversity and
evolution. In this system, most migration is likely through time as
parasites from epidemics in previous years get resuspended from
sediments
(Decaestecker et
al., 2004, 2007). The relative contribution to infections from spores
from the spore bank vs. those produced in the ongoing epidemic is
unknown, and this contribution likely changes through time and may
depend on lake basin structure
(Cácereset al., 2006; Hall et al., 2010; Penczykowski et
al., 2014). The pattern from Little Appleton suggests that
transmission from the sediments occurs at the beginning of an epidemic
and after that, successful genotypes from the ongoing epidemic are
amplified. The pattern from Crooked – where more different genotypes
were found throughout the epidemic – may indicate instead that
infection from the spore bank might continue throughout the season
either due to feeding in the sediments or due to sediment resuspension
into the water column. Future work that tracks the genotypes of
free-living spores in the water column, as well as the genotypes in
infected hosts would help determine the relative contributions of spores
produced during an ongoing epidemic vs. those resuspended from sediment;
ideally, this would be done in multiple populations that varied in the
likelihood of spore resuspension (e.g., lakes that are weakly stratified
vs. those with very strong stratification).
Our data also indicate that
parasite genotypes might migrate between lakes as three genotypes were
shared between Little Appleton and Crooked which are 9 miles (14.5 km)
apart. Such distances are commonly traversed by waterfowl, which can
move parasite spores and infected hosts
(Green & Figuerola, 2005).
It is also possible that hosts in these lakes could be related to each
other due to long distance dispersal of ephippia by birds
(Green & Figuerola, 2005)
and that related hosts could become infected by related parasites in
different lakes; future studies tracking the genetic diversity of both
hosts and parasites in multiple lakes would help uncover whether this is
the case. However, it is also possible that, if we had more loci
available, we would discover that these were, in fact, not the same
genotype. While the number of loci that we used in this study was
sufficient to detect substantial diversity within and between lakes,
using newly discovered hypervariable regions of the P. ramosagenome (Andras et
al., 2020) would likely uncover additional variation that was not
captured by our VNTR analysis.
We quantified the genetic structure of populations of the parasiteP. ramosa in infected D. dentifera hosts and found
evidence of evolution within outbreaks, potentially acting on parasite
diversity introduced from the spore bank. We hypothesize that intra- and
interspecific host diversity, host population densities, and epidemic
size all influence the evolution of P. ramosa within epidemics.
Future studies that include more epidemics and measure host genotypic
diversity as well as genotypes of spores in the water column could help
disentangle the mechanisms underlying this evolution.
REFERENCES
Andras, J.P. & Ebert, D.
2013. A novel approach to parasite population genetics: experimental
infection reveals geographic differentiation, recombination and
host-mediated population structure in Pasteuria ramosa, a bacterial
parasite of Daphnia. Mol. Ecol. 22: 972–986. Wiley.
Andras, J.P., Fields, P.D.,
Du Pasquier, L., Fredericksen, M. & Ebert, D. 2020. Genome-Wide
Association Analysis Identifies a Genetic Basis of Infectivity in a
Model Bacterial Pathogen. Mol. Biol. Evol. 37:
3439–3452.
Auld, S.K.J.R., Wilson, P.J.
& Little, T.J. 2014. Rapid change in parasite infection traits over the
course of an epidemic in a wild host-parasite population. Oikos123: 232–238. Wiley.
Bento, G., Routtu, J.,
Fields, P.D., Bourgeois, Y., Du Pasquier, L. & Ebert, D. 2017. The
genetic basis of resistance and matching-allele interactions of a
host-parasite system: The Daphnia magna-Pasteuria ramosa model.PLoS Genet. 13: e1006596. journals.plos.org.
Burdon, J.J. 1993. The
structure of pathogen populations in natural plant communities.Annu. Rev. Phytopathol. 31: 305–323. Annual Reviews.
Cáceres, C.E., Hall, S.R.,
Duffy, M.A., Tessier, A.J., Helmle, C. & MacIntyre, S. 2006. Physical
structure of lakes constrains epidemics in Daphnia populations.Ecology 87: 1438–1444. Wiley Online Library.
Decaestecker, E., Gaba, S.,
Raeymaekers, J.A.M., Stoks, R., Van Kerckhoven, L., Ebert, D., et
al. 2007. Host-parasite “Red Queen” dynamics archived in pond
sediment. Nature 450: 870–873. Springer Science and
Business Media LLC.
Decaestecker, E., Lefever,
C., De Meester, L. & Ebert, D. 2004. Haunted by the past: Evidence for
dormant stage banks of microparasites and epibionts of Daphnia.Limnol. Oceanogr. 49: 1355–1364. Wiley.
Duffy, M.A., Brassil, C.E.,
Hall, S.R., Tessier, A.J., Cáceres, C.E. & Conner, J.K. 2008.
Parasite-mediated disruptive selection in a natural Daphnia population.BMC Evol. Biol. 8: 80. bmcecolevol.biomedcentral.com.
Duneau, D., Luijckx, P.,
Ben-Ami, F., Laforsch, C. & Ebert, D. 2011. Resolving the infection
process reveals striking differences in the contribution of environment,
genetics and phylogeny to host-parasite interactions. BMC Biol.9: 11.
Ebert, D. 2008. Host-parasite
coevolution: Insights from the Daphnia-parasite model system.Curr. Opin. Microbiol. 11: 290–301.
Ebert, D., Rainey, P.,
Embley, T.M. & Scholz, D. 1996. Development, life cycle, ultrastructure
and phylogenetic position of Pasteuria ramosa Metchnikoff 1888:
rediscovery of an obligate endoparasite of Daphnia magna Straus.Philos. Trans. R. Soc. Lond. B Biol. Sci. 351:
1689–1701. The Royal Society.
Eck, J.L., Barrès, B.,
Soubeyrand, S., Sirén, J., Numminen, E. & Laine, A.-L. 2021. Strain
Diversity and Spatial Distribution Are Linked to Epidemic Dynamics in
Host Populations. Am. Nat. 000–000. The University of Chicago
Press.
Ekroth, A.K.E., Rafaluk-Mohr,
C. & King, K.C. 2019. Host genetic diversity limits parasite success
beyond agricultural systems: a meta-analysis. Proc. Biol. Sci.286: 20191811. The Royal Society.
Excoffier, L., Smouse, P.E.
& Quattro, J.M. 1992. Analysis of molecular variance inferred from
metric distances among DNA haplotypes: application to human
mitochondrial DNA restriction data. Genetics 131:
479–491.
Forster, P., Forster, L.,
Renfrew, C. & Forster, M. 2020. Phylogenetic network analysis of
SARS-CoV-2 genomes. Proc. Natl. Acad. Sci. U. S. A. 117:
9241–9243.
Gandon, S. 2004. Evolution of
multihost parasites. Evolution 58: 455–469.
Gibson, A.K. 2021. Genetic
diversity and disease: The past, present, and future of an old idea.Evolution, doi:
10.1111/evo.14395.
Gowler, C.D., Essington, H.,
O’Brien, B., Shaw, C.L., Bilich, R.W., Clay, P.A., et al. 2022.
Virulence evolution during a naturally occurring parasite outbreak.Evol. Ecol. 1–17. Springer.
Gowler, C.D., Rogalski, M.A.,
Shaw, C.L., Hunsberger, K.K. & Duffy, M.A. 2021. Density, parasitism,
and sexual reproduction are strongly correlated in lake Daphnia
populations. Ecol. Evol. 11: 10446–10456. Wiley Online
Library.
Green, A.J. & Figuerola, J.
2005. Recent advances in the study of long-distance dispersal of aquatic
invertebrates via birds. Divers. Distrib. 11: 149–156.
Wiley.
Hall, S.R., Becker, C.R.,
Simonis, J.L. & Duffy, M.A. 2009. Friendly competition: evidence for a
dilution effect among competitors in a planktonic host–parasite system.Ecology. Wiley Online Library.
Hall, S.R., Smyth, R.,
Becker, C.R., Duffy, M.A., Knight, C.J., MacIntyre, S., et al.2010. Why Are Daphnia in Some Lakes Sicker? Disease Ecology, Habitat
Structure, and the Plankton. Bioscience 60: 363–375.
Oxford Academic.
Hite, J.L., Penczykowski,
R.M., Shocket, M.S., Griebel, K.A., Strauss, A.T., Duffy, M.A., et
al. 2017. Allocation, not male resistance, increases male frequency
during epidemics: a case study in facultatively sexual hosts.Ecology 98: 2773–2783. Wiley Online Library.
Kamvar, Z.N., Tabima, J.F. &
Grünwald, N.J. 2014. Poppr: an R package for genetic analysis of
populations with clonal, partially clonal, and/or sexual reproduction.PeerJ 2: e281.
Keesing, F., Holt, R.D. &
Ostfeld, R.S. 2006. Effects of species diversity on disease risk.Ecol. Lett. 9: 485–498. Wiley Online Library.
King, K.C. & Lively, C.M.
2012. Does genetic diversity limit disease spread in natural host
populations? Heredity 109: 199–203. nature.com.
Koskella, B. 2014.
Bacteria-phage interactions across time and space: merging local
adaptation and time-shift experiments to understand phage evolution.Am. Nat. 184 Suppl 1: S9–21.
Lin, J.-W., Tang, C., Wei,
H.-C., Du, B., Chen, C., Wang, M., et al. 2021. Genomic
monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that
modulates type I interferon response. Cell Host Microbe29: 489–502.e8.
Lively, C.M., Dybdahl, M.F.,
Jokela, J., Osnas, E.E. & Delph, L.F. 2004. Host sex and local
adaptation by parasites in a snail-trematode interaction. Am.
Nat. 164 Suppl 5: S6–18. journals.uchicago.edu.
Luijckx, P., Duneau, D.,
Andras, J.P. & Ebert, D. 2014. Cross-species infection trials reveal
cryptic parasite varieties and a putative polymorphism shared among host
species. Evolution 68: 577–586. Wiley.
Marcon, E., Hérault, B.,
Baraloto, C. & Lang, G. 2012. The decomposition of Shannon’s entropy
and a confidence interval for beta diversity. Oikos 121:
516–522. Wiley.
McCrone, J.T., Woods, R.J.,
Martin, E.T., Malosh, R.E., Monto, A.S. & Lauring, A.S. 2018.
Stochastic processes constrain the within and between host evolution of
influenza virus. Elife 7.
Mouton, L. & Ebert, D. 2008.
Variable-number-of-tandem-repeats analysis of genetic diversity in
Pasteuria ramosa. Curr. Microbiol. 56: 447–452.
Springer.
Nei, M. 1973. Analysis of
gene diversity in subdivided populations. Proc. Natl. Acad. Sci.
U. S. A. 70: 3321–3323.
Papkou, A., Gokhale, C.S.,
Traulsen, A. & Schulenburg, H. 2016. Host-parasite coevolution: why
changing population size matters. Zoology 119:
330–338.
Paplauskas, S., Brand, J. &
Auld, S.K.J.R. 2021. Ecology directs host-parasite coevolutionary
trajectories across Daphnia-microparasite populations. Nat
Ecol Evol 5: 480–486.
Park, D.J., Dudas, G., Wohl,
S., Goba, A., Whitmer, S.L.M., Andersen, K.G., et al. 2015. Ebola
Virus Epidemiology, Transmission, and Evolution during Seven Months in
Sierra Leone. Cell 161: 1516–1526.
Penczykowski, R.M., Hall,
S.R., Civitello, D.J. & Duffy, M.A. 2014. Habitat structure and
ecological drivers of disease. Limnol. Oceanogr. 59:
340–348. Wiley.
Prevosti, A., Ocaña, J. &
Alonso, G. 1975. Distances between populations ofDrosophila subobscura,
based on chromosome arrangement frequencies. Theor. Appl. Genet.45: 231–241. Springer.
R Core Team. 2020. R: A
Language and Environment for Statistical Computing. R Foundation for
Statistical Computing, Vienna, Austria.
Refardt, D. & Ebert, D.
2007. Inference of parasite local adaptation using two different fitness
components. J. Evol. Biol. 20: 921–929.
Rogalski, M.A. & Duffy, M.A.
2020. Local adaptation of a parasite to solar radiation impacts disease
transmission potential, spore yield, and host fecundity.Evolution 74: 1856–1864.
Routtu, J. & Ebert, D. 2015.
Genetic architecture of resistance in Daphnia hosts against two species
of host-specific parasites. Heredity 114: 241–248.
nature.com.
Salvaudon, L., Héraudet, V.
& Shykoff, J.A. 2005. Parasite-host fitness trade-offs change with
parasite identity: genotype-specific interactions in a plant-pathogen
system. Evolution 59: 2518–2524.
Schuelke, M. 2000. An
economic method for the fluorescent labeling of PCR fragments.Nat. Biotechnol. 18: 233–234. nature.com.
Shaw, C.L. 2019. Drivers of
Epidemic Timing and Size in a Natural Aquatic System. University of
Michigan.
Smirnov, N.N. 2017.Physiology of the Cladocera. Academic Press.
Strauss, A.T., Shocket, M.S.,
Civitello, D.J., Hite, J.L., Penczykowski, R.M., Duffy, M.A., et
al. 2016. Habitat, predators, and hosts regulate disease in Daphnia
through direct and indirect pathways. Ecol. Monogr. 86:
393–411. Wiley.
Turko, P., Tellenbach, C.,
Keller, E., Tardent, N., Keller, B., Spaak, P., et al. 2018.
Parasites driving host diversity: Incidence of disease correlated with
Daphnia clonal turnover. Evolution 72: 619–629.
Vellend, M. & Geber, M.A.
2005. Connections between species diversity and genetic diversity.Ecol. Lett. Wiley Online Library.
Weber, K.E. 1990. Increased
selection response in larger populations. I. Selection for wing-tip
height in Drosophila melanogaster at three population sizes.Genetics 125: 579–584. ncbi.nlm.nih.gov.
Wickham. 2016. Package
“ggplot2”: elegant graphics for data analysis. Springer-Verlag
New York. doi.
Wolinska, J. & Spaak, P.
2009. The cost of being common: evidence from natural Daphnia
populations. Evolution 63: 1893–1901.
Wright, S. 1978.Evolution and the genetics of populations: a treatise in four
volumes: Vol. 4: variability within and among natural populations.
University of Chicago Press.
Zhan, J., Mundt, C.C.,
Hoffer, M.E. & McDonald, B.A. 2002. Local adaptation and effect of host
genotype on the rate of pathogen evolution: an experimental test in a
plant pathosystem. J. Evol. Biol. 15: 634–647. Wiley.