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Cell
Article
License: Elsevier Non-Commercial
Data sources: UnpayWall
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Cell
Article . 2018 . Peer-reviewed
License: Elsevier Non-Commercial
Data sources: Crossref
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A Synthetic Bacterial Cell-Cell Adhesion Toolbox for Programming Multicellular Morphologies and Patterns

Authors: David S, Glass; Ingmar H, Riedel-Kruse;

A Synthetic Bacterial Cell-Cell Adhesion Toolbox for Programming Multicellular Morphologies and Patterns

Abstract

Synthetic multicellular systems hold promise as models for understanding natural development of biofilms and higher organisms and as tools for engineering complex multi-component metabolic pathways and materials. However, such efforts require tools to adhere cells into defined morphologies and patterns, and these tools are currently lacking. Here, we report a 100% genetically encoded synthetic platform for modular cell-cell adhesion in Escherichia coli, which provides control over multicellular self-assembly. Adhesive selectivity is provided by a library of outer membrane-displayed nanobodies and antigens with orthogonal intra-library specificities, while affinity is controlled by intrinsic adhesin affinity, competitive inhibition, and inducible expression. We demonstrate the resulting capabilities for quantitative rational design of well-defined morphologies and patterns through homophilic and heterophilic interactions, lattice-like self-assembly, phase separation, differential adhesion, and sequential layering. Compatible with synthetic biology standards, this adhesion toolbox will enable construction of high-level multicellular designs and shed light on the evolutionary transition to multicellularity.

Related Organizations
Keywords

Metabolic Engineering, Cell Adhesion, Escherichia coli, Cell Differentiation, Synthetic Biology, Single-Domain Antibodies, Bacterial Physiological Phenomena, Biological Evolution, Metabolic Networks and Pathways, Gene Library

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    174
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
174
Top 1%
Top 10%
Top 1%
hybrid