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Increasing the Scalability of Toxin–Intein Orthogonal Combinations

Authors: Rocío López-Igual; Pedro Dorado-Morales; Didier Mazel;

Increasing the Scalability of Toxin–Intein Orthogonal Combinations

Abstract

Inteins are proteins embedded into host proteins from which they are excised in an autocatalytic reaction. Specifically, split inteins are separated into two independent fragments that reconstitute the host protein during the catalytic process. We recently developed a novel strategy for the specific killing of pathogenic and antibiotic resistant bacteria based on toxin-intein combinations. Bacterial type II toxin-antitoxin systems are protein modules in which the toxin can provoke cell death whereas the antitoxin inhibits toxin activity. Although our previous system was based on a split intein (iDnaE) and the CcdB toxin, we demonstrated that iDnaE is able to reconstitute four different toxins. To expand the applicability of our system by widening the repertoire of toxin-intein combinations for complex set-ups, we introduced a second intein, iDnaX, which was artificially split. We demonstrate that iDnaX is able to reconstitute the four toxins, and we manage to reduce its scar size to facilitate their use. In addition, we prove the orthogonality of both inteins (iDnaE and iDnaX) through a toxin reconstitution assay, thus opening the possibility for complex set-ups based on these toxin-intein modules. This could be used to develop specific antimicrobial and other biotechnological applications.

Countries
France, France, France, Spain
Keywords

bacterial killing, inteins, Proteins, Bacterial killing, Toxin−antitoxin systems, Inteins, Protein splicing, microbial synthetic biology, protein splicing, Microbial synthetic biology, Protein Splicing, [SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology, toxin-antitoxin systems

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selected citations
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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!
views
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