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微米尺度游泳生物库(BOSO-Micro)。

The bank of swimming organisms at the micron scale (BOSO-Micro).

机构信息

Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom.

Faculty of Physics, University of Warsaw, Warsaw, Poland.

出版信息

PLoS One. 2021 Jun 10;16(6):e0252291. doi: 10.1371/journal.pone.0252291. eCollection 2021.

Abstract

Unicellular microscopic organisms living in aqueous environments outnumber all other creatures on Earth. A large proportion of them are able to self-propel in fluids with a vast diversity of swimming gaits and motility patterns. In this paper we present a biophysical survey of the available experimental data produced to date on the characteristics of motile behaviour in unicellular microswimmers. We assemble from the available literature empirical data on the motility of four broad categories of organisms: bacteria (and archaea), flagellated eukaryotes, spermatozoa and ciliates. Whenever possible, we gather the following biological, morphological, kinematic and dynamical parameters: species, geometry and size of the organisms, swimming speeds, actuation frequencies, actuation amplitudes, number of flagella and properties of the surrounding fluid. We then organise the data using the established fluid mechanics principles for propulsion at low Reynolds number. Specifically, we use theoretical biophysical models for the locomotion of cells within the same taxonomic groups of organisms as a means of rationalising the raw material we have assembled, while demonstrating the variability for organisms of different species within the same group. The material gathered in our work is an attempt to summarise the available experimental data in the field, providing a convenient and practical reference point for future studies.

摘要

生活在水相环境中的单细胞微生物在地球上的数量超过了所有其他生物。它们中的很大一部分能够在具有各种游动步态和运动模式的液体中自主推进。在本文中,我们对迄今为止关于单细胞微游泳生物运动特性的可用实验数据进行了生物物理调查。我们从现有文献中收集了四类生物体的运动的经验数据:细菌(和古细菌)、鞭毛真核生物、精子和纤毛。只要有可能,我们就会收集以下生物学、形态学、运动学和动力学参数:物种、生物体的形状和大小、游动速度、驱动频率、驱动幅度、鞭毛数量以及周围流体的特性。然后,我们使用已建立的低雷诺数推进流体力学原理对数据进行组织。具体来说,我们使用相同分类群的生物的理论生物物理模型来合理化我们所收集的原始材料,同时展示同一组内不同物种的生物体的可变性。我们收集的材料旨在总结该领域的现有实验数据,为未来的研究提供方便实用的参考点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3950/8191957/2a43048dda37/pone.0252291.g001.jpg

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