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致病生物中的发育同步性和极高繁殖率。

Developmental synchrony and extraordinary multiplication rates in pathogenic organisms.

作者信息

Greischar Megan A, Childs Lauren M

机构信息

Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA.

Department of Mathematics, Virginia Tech, Blacksburg, VA 24061, USA.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2025 Jan 23;380(1918):20230337. doi: 10.1098/rstb.2023.0337.

Abstract

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.This article is part of the Theo Murphy meeting issue 'Circadian rhythms in infection and immunity'.

摘要

致病生物的增殖率会影响疾病进展、免疫和治疗效果以及宿主内进化的可能性。因此,准确估计增殖率对于生物学理解至关重要。我们最近表明,从疟疾感染数据推断增殖率的常用方法会大幅高估真实值(即在模拟场景下),这为人类疟原虫的极高估计值提供了背景。一个关键的未知因素是这种偏差是 specifically 源于疟原虫生物学特性还是代表了更广泛的问题。在这里,我们通过推广宿主内疟疾模型,确定了不同发育生物学的致病生物在增殖率估计上存在偏差的可能性。我们发现,发育采样偏差的多样模式——可检测性随发育年龄的变化——可靠地导致对丰度倍数变化的高估,不仅掩盖了真实增长率,甚至可能掩盖了种群是在增长还是在下降。只要同步性——在构成感染的致病生物群体中发育同步的程度——随时间衰减,就会出现这种模式。只有在模拟同步性增加的情况下,我们才发现增殖率有明显的低估。要获得增殖率的可靠估计,可能需要考虑致病生物中同步性的多样模式。本文是西奥·墨菲会议议题“感染与免疫中的昼夜节律”的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63f7/11753877/accc593aff39/rstb.2023.0337.f001.jpg

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