scholarly journals Using measures of single‐cell physiology and physiological state to understand organismic aging

Aging Cell ◽  
2015 ◽  
Vol 15 (1) ◽  
pp. 4-13 ◽  
Author(s):  
Alexander Mendenhall ◽  
Monica Driscoll ◽  
Roger Brent
Keyword(s):  
Single Cell ◽  
Physiological State ◽  
Cell Physiology ◽  
Single Cell Physiology

Single Cell Physiology

2009 ◽  
pp. 305-316 ◽  
Author(s):  
Pierre Neveu ◽  
Deepak Kumar Sinha ◽  
Petronella Kettunen ◽  
Sophie Vriz ◽  
Ludovic Jullien ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Physiology ◽  
Single Cell Physiology

scholarly journals SINC-seq: correlation of transient gene expressions between nucleus and cytoplasm reflects single-cell physiology

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Mahmoud N. Abdelmoez ◽  
Kei Iida ◽  
Yusuke Oguchi ◽  
Hidekazu Nishikii ◽  
Ryuji Yokokawa ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Physiology ◽  
Gene Expressions ◽  
Single Cell Physiology

scholarly journals Single-Cell Physiology

2015 ◽  
Vol 44 (1) ◽  
pp. 123-142 ◽  
Author(s):  
Sattar Taheri-Araghi ◽  
Steven D. Brown ◽  
John T. Sauls ◽  
Dustin B. McIntosh ◽  
Suckjoon Jun
Keyword(s):  
Single Cell ◽  
Cell Physiology ◽  
Single Cell Physiology

scholarly journals Technical bias of microcultivation environments on single-cell physiology

Lab on a Chip ◽  
2015 ◽  
Vol 15 (8) ◽  
pp. 1822-1834 ◽  
Author(s):  
Christian Dusny ◽  
Alexander Grünberger ◽  
Christopher Probst ◽  
Wolfgang Wiechert ◽  
Dietrich Kohlheyer ◽  
...  
Keyword(s):  
Growth Rate ◽  
Single Cell ◽  
Specific Growth ◽  
Cell Physiology ◽  
Cell Cultivation ◽  
Division Rate ◽  
Platform Comparison ◽  
Cross Platform ◽  
Technical Bias ◽  
Single Cell Physiology

The cross-platform comparison of three different single-cell cultivation methods demonstrates technical influences on biological key parameters like specific growth rate, division rate and cellular morphology.

scholarly journals Correlation of gene expressions between nucleus and cytoplasm reflects single-cell physiology

2017 ◽  
Author(s):  
Mahmoud N. Abdelmoez ◽  
Kei Iida ◽  
Yusuke Oguchi ◽  
Hidekazu Nishikii ◽  
Ryuji Yokokawa ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Splicing ◽  
Single Cells ◽  
Physiological State ◽  
Microfluidic System ◽  
Leukemic Cells ◽  
Cell Physiology ◽  
Rna Seq ◽  
Gene Expressions ◽  
Sequencing Technologies

BackgroundEukaryotes transcribe RNAs in nuclei and transport them to the cytoplasm through multiple steps of post-transcriptional regulation. Existing single-cell sequencing technologies, however, are unable to analyse nuclear (nuc) and cytoplasmic (cyt) RNAs separately and simultaneously. Hence, there remain challenges to discern correlation, localisation, and translocation between them.ResultsHere we report a microfluidic system that physically separates nucRNA and cytRNA from a single cell and enables single-cell integrated nucRNA and cytRNA-sequencing (SINC-seq). SINC-seq constructs two individual RNA-seq libraries, nucRNA and cytRNA per cell, quantifies gene expression in the subcellular compartments and combines them to create a novel single-cell RNA-seq data enabled by our system, which we here term in-silico single cell.ConclusionsLeveraging SINC-seq, we discovered three distinct natures of correlation among cytRNA and nucRNA that reflected the physiological state of single cells: The cell-cycle-related genes displayed highly correlated expression pattern with minor differences; RNA splicing genes showed lower nucRNA-to-cytRNA correlation, suggesting a retained intron may be implicated in inhibited mRNA transport; A chemical perturbation, sodium butyrate treatment, transiently distorted the correlation along differentiating human leukemic cells to erythroid cells. These data uniquely provide insights into the regulatory network of mRNA from nucleus toward cytoplasm at the single cell level.

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