scholarly journals High-throughput Analysis of Arabidopsis Stem Vibrations to Identify Mutants with Altered Mechanical Properties

2018 ◽  
Author(s):  
Miyuki T. Nakata ◽  
Masahiro Takahara ◽  
Shingo Sakamoto ◽  
Kouki Yoshida ◽  
Nobutaka Mitsuda

AbstractMechanical properties are rarely used as quantitative indices for the large-scale mutant screening of plants, even in the model plant Arabidopsis thaliana. The mechanical properties of plant stems generally influence their vibrational characteristics. Here, we developed Python-based software, named AraVib, for the high-throughput analysis of free vibrations of plant stems, focusing specifically on Arabidopsis stem vibrations, and its extended version, named AraVibS, to identify mutants with altered mechanical properties. These programs can be used without knowledge of Python and require only an inexpensive handmade setting stand and an iPhone/iPad with a high-speed shooting function for data acquisition. Using our system, we identified an nst1 nst3 double-mutant lacking secondary cell walls in fiber cells and a wrky12 mutant displaying ectopic formation of secondary cell wall compared with wild type by employing only two growth traits (stem height and fresh weight) in addition to videos of stem vibrations. Furthermore, we calculated the logarithmic decrement, the damping ratio, the natural frequency and the stiffness based on the spring-mass-damper model from the video data using AraVib. The stiffness was estimated to be drastically decreased in nst1 nst3, which agreed with previous tensile test results. However, in wrky12, the stiffness was significantly increased. These results demonstrate the effectiveness of our new system. Because our method can be applied in a high-throughput manner, it can be used to screen for mutants with altered mechanical properties.

2018 ◽  
Vol 9 ◽  
Author(s):  
Miyuki T. Nakata ◽  
Masahiro Takahara ◽  
Shingo Sakamoto ◽  
Kouki Yoshida ◽  
Nobutaka Mitsuda

2005 ◽  
Vol 152 (4) ◽  
pp. 129 ◽  
Author(s):  
D. Holmes ◽  
M.E. Sandison ◽  
N.G. Green ◽  
H. Morgan

2015 ◽  
Vol 11 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Luciano Cardoso ◽  
Suellen Cordeiro ◽  
Marcio Fronza ◽  
Denise Endringer ◽  
Tadeu de Andrade ◽  
...  

Author(s):  
Ruoxing Lei ◽  
Erin A. Akins ◽  
Kelly C. Y. Wong ◽  
Nicole A. Repina ◽  
Kayla J. Wolf ◽  
...  

The Analyst ◽  
2021 ◽  
Author(s):  
Jiawei Qi ◽  
Pinhua Rao ◽  
Lele Wang ◽  
Li Xu ◽  
Yanli Wen ◽  
...  

Pattern recognition, also called “array sensing” is a recognition strategy with a wide and expandable analysis range, based on the high-throughput analysis data. In this work, we constructed a sensor...


Author(s):  
Xiaojia Jiang ◽  
Mingsong Zang ◽  
Fei Li ◽  
Chunxi Hou ◽  
Quan Luo ◽  
...  

Biological nanopore-based techniques have attracted more and more attention recently in the field of single-molecule detection, because they allow the real-time, sensitive, high-throughput analysis. Herein, we report an engineered biological...


2002 ◽  
Vol 161 (5) ◽  
pp. 1557-1565 ◽  
Author(s):  
Chih Long Liu ◽  
Wijan Prapong ◽  
Yasodha Natkunam ◽  
Ash Alizadeh ◽  
Kelli Montgomery ◽  
...  

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