Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns.
Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns.
复制标题
通过密码子使用模式估算培养物，宏基因组和单个细胞的最大微生物生长速率。
DOI：
10.1073/pnas.2016810118
复制
发表时间：
2021-03-23
影响因子：
11.1
通讯作者：
Fuhrman JA
中科院分区：
文献类型：
--
作者：
Weissman JL;Hou S;Fuhrman JA
尽管人们普遍认为微生物具有快速的生长速度，但许多环境，如海水和土壤，往往是由只能生长得非常缓慢的微生物主导的。我们关于生长的知识必然偏向于容易培养的生物，这些生物往往是那些生长迅速的生物，因为微生物的生长速率传统上是通过实验室生长实验来测量的。然而，潜在增长率在自然界中是如何分布的？利用基因组数据，我们预测了超过20万种生物的生长速度，其中包括许多尚未被种植的物种。这些数据揭示了当前的培养物收藏是如何强烈地偏向于快速生长的生物体的。最后，我们注意到最大生长速率的双峰分布，这表明微生物生长策略自然分为两类。最大生长速率是微生物生活方式的基本参数，其变化在几个数量级上，倍增时间从几分钟到几天不等。生长速率通常使用实验室培养实验来测量。然而，我们对大多数微生物的生理学缺乏足够的了解，无法为它们设计合适的培养条件，这严重限制了我们评估微生物生长速率全球多样性的能力。最大生长速率的基因组估计提供了一个实用的解决方案，调查微生物生长潜力的分布，无论培养状态。我们开发了一种改进的最大增长率估计器，并预测了超过20万个基因组、宏基因组组装基因组和单细胞扩增基因组的最大增长率，以调查原核生物多样性范围内的增长潜力;扩展允许仅从16 S rRNA序列估计以及从宏基因组加权社区估计。我们比较了培养的和未培养的生物体的生长速率，以说明培养物收集如何强烈地偏向于能够快速生长的生物体。最后，我们发现生物体自然地分为两个生长类，并观察到生长极慢的生物体的生长预测存在偏差。这些观察结果最终使我们提出了基于生物体占据的选择机制的寡养和共养的进化定义。我们发现，这些生长类与不同的选择制度和基因组功能潜力。
Despite the wide perception that microbes have rapid growth rates, many environments like seawater and soil are often dominated by microorganisms that can only grow very slowly. Our knowledge about growth is necessarily biased toward easily culturable organisms, which tend to be those that grow fast, because microbial growth rates have traditionally been measured using laboratory growth experiments. However, how are potential growth rates distributed in nature? Using genomic data, we predicted the growth rates of over 200,000 organisms, including many as yet uncultivated species. These data reveal how current culture collections are strongly biased toward fast-growing organisms. Finally, we noticed a bimodal distribution of maximal growth rates, suggesting a natural division of microbial growth strategies into two classes. Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.
登录
查看更多内容
影响因子：
3.4
作者：
Bobay LM;Ochman H
通讯作者：
Ochman H
影响因子：
14.9
作者：
Buchan JR;Aucott LS;Stansfield I
通讯作者：
Stansfield I
影响因子：
16.6
作者：
Emiola A;Oh J
通讯作者：
Oh J
影响因子：
9.5
作者：
Galperin, Michael Y.;Kristensen, David M.;Koonin, Eugene V.
通讯作者：
Koonin, Eugene V.
影响因子：
5.5
作者：
Anantharaman V;Makarova KS;Burroughs AM;Koonin EV;Aravind L
通讯作者：
Aravind L