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一种用户友好、低成本的恒浊器,基于扩展卡尔曼滤波器具有通用的生长速率估计功能。

A user-friendly, low-cost turbidostat with versatile growth rate estimation based on an extended Kalman filter.

作者信息

Hoffmann Stefan A, Wohltat Christian, Müller Kristian M, Arndt Katja M

机构信息

Molecular Biotechnology, Institute for Biochemistry and Biology, University of Potsdam, Potsdam-Golm, Germany.

Cellular and Molecular Biotechnology, Faculty of Technology, Bielefeld University, Bielefeld, Germany.

出版信息

PLoS One. 2017 Jul 26;12(7):e0181923. doi: 10.1371/journal.pone.0181923. eCollection 2017.

DOI:10.1371/journal.pone.0181923
PMID:28746418
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5529016/
Abstract

For various experimental applications, microbial cultures at defined, constant densities are highly advantageous over simple batch cultures. Due to high costs, however, devices for continuous culture at freely defined densities still experience limited use. We have developed a small-scale turbidostat for research purposes, which is manufactured from inexpensive components and 3D printed parts. A high degree of spatial system integration and a graphical user interface provide user-friendly operability. The used optical density feedback control allows for constant continuous culture at a wide range of densities and offers to vary culture volume and dilution rates without additional parametrization. Further, a recursive algorithm for on-line growth rate estimation has been implemented. The employed Kalman filtering approach based on a very general state model retains the flexibility of the used control type and can be easily adapted to other bioreactor designs. Within several minutes it can converge to robust, accurate growth rate estimates. This is particularly useful for directed evolution experiments or studies on metabolic challenges, as it allows direct monitoring of the population fitness.

摘要

对于各种实验应用而言,处于特定、恒定密度的微生物培养物比简单的分批培养具有很大优势。然而,由于成本高昂,能够以自由定义的密度进行连续培养的设备仍使用有限。我们开发了一种用于研究目的的小型恒浊器,它由廉价部件和3D打印部件制成。高度的空间系统集成和图形用户界面提供了用户友好的可操作性。所采用的光密度反馈控制允许在广泛的密度范围内进行恒定的连续培养,并能够在无需额外参数设置的情况下改变培养体积和稀释率。此外,还实现了一种用于在线生长速率估计的递归算法。基于非常通用的状态模型所采用的卡尔曼滤波方法保留了所用控制类型的灵活性,并且可以轻松适应其他生物反应器设计。在几分钟内,它就能收敛到稳健、准确的生长速率估计值。这对于定向进化实验或代谢挑战研究特别有用,因为它允许直接监测群体适应性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/628a4b7576ea/pone.0181923.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/1c21b3357591/pone.0181923.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/73d0067ddd53/pone.0181923.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/b883772f6d32/pone.0181923.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/a97644239130/pone.0181923.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/628a4b7576ea/pone.0181923.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/1c21b3357591/pone.0181923.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/5ba2b0185c8e/pone.0181923.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/73d0067ddd53/pone.0181923.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/b883772f6d32/pone.0181923.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/a97644239130/pone.0181923.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1230/5529016/628a4b7576ea/pone.0181923.g006.jpg

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