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Cited by 361

The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.

Addiction Modules and Programmed Cell Death and Antideath in Bacterial Cultures

Engelberg-Kulka, Hanna, Glaser, Gad·1999·Annual Review of Microbiology

Abstract

▪ Abstract In bacteria, programmed cell death is mediated through “addiction modules” consisting of two genes. The product of the second gene is a stable toxin, whereas the product of the first is a labile antitoxin. Here we extensively review what is known about those modules that are borne by one of a number of Escherichia coli extrachromosomal elements and are responsible for the postsegregational killing effect. We focus on a recently discovered chromosomally borne regulatable addiction module in E. coli that responds to nutritional stress and also on an antideath gene of the E. coli bacteriophage λ. We consider the relation of these two to programmed cell death and antideath in bacterial cultures. Finally, we discuss the similarities between basic features of programmed cell death and antideath in both prokaryotes and eukaryotes and the possibility that they share a common evolutionary origin.

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Crossref · 10.1146/annurev.micro.53.1.43

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Metadata

Authors
Engelberg-Kulka, H., & Glaser, G.
Venue
Annual Review of Microbiology
Published
1999-10
Volume
53
Issue
1
Pages
43-70
ISSN
  • 0066-4227 (ISSN-L)
  • 1545-3251
OpenAlex
W2167420567
Cited by
361
References
72
FWCI
1.33
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Addiction Modules and Programmed Cell Death and Antideath in Bacterial Cultures. https://app.cochat.ai/papers/10.1146/annurev.micro.53.1.43
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Engelberg-Kulka, H., & Glaser, G. (1999). Addiction Modules and Programmed Cell Death and Antideath in Bacterial Cultures. Annual Review of Microbiology. https://doi.org/10.1146/annurev.micro.53.1.43

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.