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Greischar, M. A.

Publications and source records attributed to Greischar, M. A..

2 recordsLinked to original sources

How to quantify developmental synchrony in malaria parasites

Malaria infections represent an iconic example of developmental synchrony, where periodic fevers can result when the population of parasites develops synchronously within host red blood cells. The level of synchrony appears to vary across individual hosts and across parasite species and strains, variation that--once quantified--can illuminate the ecological and evolutionary drivers of synchrony. Yet current approaches for quantifying synchrony in parasites are either biased by population dynamics or unsuitable when population growth rates vary through time, features ubiquitous to parasite populations in vitro and in vivo. Here we develop an approach to estimate synchrony that accounts for population dynamics, including changing population growth rates, and validate it with simulated time series data encompassing a range of synchrony levels in two different host-parasite systems: malaria infections of mice and human malaria parasites in vitro. This new method accurately quantifies developmental synchrony from per capita growth rates using obtainable abundance data even with realistic sampling noise, without the need to sort parasites into developmental stages. Our approach enables variability in developmental schedules to be disentangled from even extreme variation in population dynamics, providing a comparative metric of developmental synchrony.

ecology↗

Developmental synchrony and extraordinary multiplication rates in pathogenic organisms

The multiplication rates of pathogenic organisms influence disease progression, efficacy of immunity and therapeutics, and potential for within-host evolution. Thus, accurate estimates of multiplication rates are essential for biological understanding. We recently showed that common methods for inferring multiplication rates from malaria infection data substantially overestimate true values (i.e., under simulated scenarios), providing context for extraordinarily large estimates in human malaria parasites. A key unknown is whether this bias arises specifically from malaria parasite biology or represents a broader concern. Here we identify the potential for biased multiplication rate estimates across pathogenic organisms with different developmental biology by generalizing a within-host malaria model. We find that diverse patterns of developmental sampling bias--the change in detectability over developmental age--reliably generate overestimates of the fold change in abundance, obscuring not just true growth rates but potentially even whether populations are expanding or declining. This pattern emerges whenever synchrony, the degree to which development is synchronized across the population of pathogenic organisms comprising an infection, decays with time. Only with simulated increases in synchrony do we find noticeable underestimates of multiplication rates. Obtaining robust estimates of multiplication rates may require accounting for diverse patterns of synchrony in pathogenic organisms. Subjectscomputational biology, theoretical biology, ecology, developmental biology

ecology↗