A Cell–Cell Communication-Based Screening System for Novel Microbes with Target Enzyme Activities

2016 ◽  
Vol 5 (11) ◽  
pp. 1231-1238 ◽  
Author(s):  
Haseong Kim ◽  
Eugene Rha ◽  
Wonjae Seong ◽  
Soo-Jin Yeom ◽  
Dae-Hee Lee ◽  
...  
Keyword(s):  
Enzyme Activities ◽  
Cell Communication ◽  
Screening System ◽  
A Cell ◽  
Target Enzyme ◽  
Cell Cell

scholarly journals Erratum: A cell-cell communication signal integrates quorum sensing and stress response

2013 ◽  
Vol 9 (6) ◽  
pp. 406-406
Author(s):  
Jasmine Lee ◽  
Jien Wu ◽  
Yinyue Deng ◽  
Jing Wang ◽  
Chao Wang ◽  
...  
Keyword(s):  
Stress Response ◽  
Quorum Sensing ◽  
Cell Communication ◽  
Communication Signal ◽  
A Cell ◽  
Cell Cell

scholarly journals A cell-cell communication system regulates protease production during sporulation in bacteria of the Bacillus cereus group

2011 ◽  
Vol 82 (3) ◽  
pp. 619-633 ◽  
Author(s):  
Stéphane Perchat ◽  
Thomas Dubois ◽  
Samira Zouhir ◽  
Myriam Gominet ◽  
Sandrine Poncet ◽  
...  
Keyword(s):  
Bacillus Cereus ◽  
Communication System ◽  
Cell Communication ◽  
Protease Production ◽  
Bacillus Cereus Group ◽  
A Cell ◽  
Cell Cell

scholarly journals A new improved and extended version of the multicell bacterial simulator gro

2016 ◽  
Author(s):  
Martín Gutiérrez ◽  
Paula Gregorio-Godoy ◽  
Guillermo Pérez del Pulgar ◽  
Luis Muñoz ◽  
Sandra Sáez ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Timed Automata ◽  
Cell Communication ◽  
Colony Growth ◽  
Communication Process ◽  
Intercellular Signaling ◽  
Dividing Cells ◽  
A Cell ◽  
Local Cell ◽  
Cell Cell

Abstractgro is a cell programming language developed in Klavins Lab for simulating colony growth and cell-cell communication. It is used as a synthetic biology prototyping tool for simulating multicellular biocircuits. In this work, we present several extensions made to gro that improve the performance of the simulator, make it easier to use and provide new functionalities. The new version of gro is between one and two orders of magnitude faster than the original version. It is able to grow microbial colonies with up to 105 cells in less than 20 minutes. A new library, CellEngine, accelerates the resolution of spatial physical interactions between growing and dividing cells by implementing a new shoving algorithm. A genetic library, CellPro, based on Probabilistic Timed Automata, simulates gene expression dynamics using simplified and easy to compute digital proteins. We also propose a more convenient language specification layer, ProSpec, based on the idea that proteins drive cell behavior. CellNutrient, another library, implements Monod-based growth and nutrient uptake functionalities. The intercellular signaling management was improved and extended in a library called CellSignals. Finally, bacterial conjugation, another local cell-cell communication process, was added to the simulator. To show the versatility and potential outreach of this version of gro, we provide studies and novel examples ranging from synthetic biology to evolutionary microbiology. We believe that the upgrades implemented for gro have made it into a powerful and fast prototyping tool capable of simulating a large variety of systems and synthetic biology designs.

scholarly journals A Cell-Cell Communication Marker for Identifying Targeted Tumor Therapies

2014 ◽  
Vol 9 (3) ◽  
pp. 255-262 ◽  
Author(s):  
Diane Matesic ◽  
Amna Ali ◽  
Tatyana Sidorova ◽  
Timothy Burns
Keyword(s):  
Cell Communication ◽  
A Cell ◽  
Cell Cell

scholarly journals FunRes: resolving tissue-specific functional cell states based on a cell–cell communication network model

2020 ◽  
Author(s):  
Sascha Jung ◽  
Kartikeya Singh ◽  
Antonio del Sol
Keyword(s):  
Communication Network ◽  
Communication Networks ◽  
Cell Communication ◽  
Cell Types ◽  
Computational Method ◽  
Tissue Specific ◽  
Great Utility ◽  
A Cell ◽  
Cell Cell

Abstract The functional specialization of cell types arises during development and is shaped by cell–cell communication networks determining a distribution of functional cell states that are collectively important for tissue functioning. However, the identification of these tissue-specific functional cell states remains challenging. Although a plethora of computational approaches have been successful in detecting cell types and subtypes, they fail in resolving tissue-specific functional cell states. To address this issue, we present FunRes, a computational method designed for the identification of functional cell states. FunRes relies on scRNA-seq data of a tissue to initially reconstruct the functional cell–cell communication network, which is leveraged for partitioning each cell type into functional cell states. We applied FunRes to 177 cell types in 10 different tissues and demonstrated that the detected states correspond to known functional cell states of various cell types, which cannot be recapitulated by existing computational tools. Finally, we characterize emerging and vanishing functional cell states in aging and disease, and demonstrate their involvement in key tissue functions. Thus, we believe that FunRes will be of great utility in the characterization of the functional landscape of cell types and the identification of dysfunctional cell states in aging and disease.

A cell-cell communication signal integrates quorum sensing and stress response

2013 ◽  
Vol 9 (5) ◽  
pp. 339-343 ◽  
Author(s):  
Jasmine Lee ◽  
Jien Wu ◽  
Yinyue Deng ◽  
Jing Wang ◽  
Chao Wang ◽  
...  
Keyword(s):  
Stress Response ◽  
Quorum Sensing ◽  
Cell Communication ◽  
Communication Signal ◽  
A Cell ◽  
Cell Cell
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