Mathematical modeling suggests heterogeneous replication of Mycobacterium tuberculosis in rabbits.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2024-11-25 DOI:10.1371/journal.pcbi.1012563
Vitaly V Ganusov, Afsal Kolloli, Selvakumar Subbian
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Abstract

Tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb), remains a major health problem with 10.6 million cases of the disease and 1.6 million deaths in 2021. It is well understood that pulmonary TB is due to Mtb growth in the lung but quantitative estimates of rates of Mtb replication and death in lungs of patients or animals such as monkeys or rabbits remain largely unknown. We performed experiments with rabbits infected with a novel, virulent clinical Mtb isolate of the Beijing lineage, HN878, carrying an unstable plasmid pBP10. In our in vitro experiments we found that pBP10 is more stable in HN878 strain than in a more commonly used laboratory-adapted Mtb strain H37Rv (the segregation coefficient being s = 0.10 in HN878 vs. s = 0.18 in H37Rv). Interestingly, the kinetics of plasmid-bearing bacteria in lungs of Mtb-infected rabbits did not follow an expected monotonic decline; the percent of plasmid-bearing cells increased between 28 and 56 days post-infection and remained stable between 84 and 112 days post-infection despite a large increase in bacterial numbers in the lung at late time points. Mathematical modeling suggested that such a non-monotonic change in the percent of plasmid-bearing cells can be explained if the lung Mtb population consists of several (at least 2) sub-populations with different replication/death kinetics: one major population expanding early and being controlled/eliminated, while another, a smaller population expanding at later times causing a counterintuitive increase in the percent of plasmid-bearing cells. Importantly, a model with one kinetically homogeneous Mtb population could not explain the data including when the model was run stochastically. Given that in rabbits HN878 strain forms well circumscribed granulomas, our results suggest independent bacterial dynamics in subsets of such granulomas. Our model predictions can be tested in future experiments in which HN878-pBP10 dynamics in individual granulomas is followed over time. Taken together, our new data and mathematical modeling-based analyses illustrate differences in Mtb dynamics in mice and rabbits confirming a perhaps somewhat obvious observation that "rabbits are not mice".

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数学模型表明兔子体内结核分枝杆菌的异质复制。
结核病(TB)是由结核分枝杆菌(Mtb)引起的疾病,它仍然是一个重大的健康问题,2021 年将有 1060 万病例,160 万人死亡。众所周知,肺结核是由于Mtb在肺部生长造成的,但对Mtb在患者或猴子或兔子等动物肺部的复制率和死亡率的定量估算在很大程度上仍是未知数。我们用兔子感染了携带不稳定质粒 pBP10 的北京系新型强毒临床 Mtb 分离物 HN878 进行了实验。在体外实验中,我们发现 pBP10 在 HN878 菌株中比在更常用的实验室改良 Mtb 菌株 H37Rv 中更稳定(分离系数在 HN878 中为 s = 0.10,而在 H37Rv 中为 s = 0.18)。有趣的是,受 Mtb 感染的兔子肺中携带质粒的细菌的动力学并不遵循预期的单调下降规律;在感染后 28 天至 56 天期间,携带质粒的细胞百分比有所增加,在感染后 84 天至 112 天期间保持稳定,尽管在晚期时间点肺中的细菌数量大幅增加。数学模型表明,如果肺部 Mtb 群体由几个(至少两个)具有不同复制/死亡动力学的亚群体组成,那么就可以解释带质粒细胞百分比的这种非单调变化:一个主要群体在早期扩大并被控制/消灭,而另一个较小的群体在后期扩大,导致带质粒细胞百分比出现反直觉的增加。重要的是,只有一个动力学均匀的 Mtb 群体的模型无法解释数据,包括随机运行模型时也是如此。鉴于 HN878 菌株在兔子体内会形成周界清晰的肉芽肿,我们的研究结果表明这种肉芽肿的子集中存在独立的细菌动态。我们的模型预测可以在未来的实验中得到验证,在这些实验中,HN878-pBP10 在单个肉芽肿中的动态会随着时间的推移而变化。总之,我们的新数据和基于数学模型的分析表明了小鼠和兔子体内 Mtb 动态的差异,证实了 "兔子不是小鼠 "这一可能有些显而易见的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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