Compatibility of intracellular binding: Evolutionary design principles for metal sensors

In the common cellular space, hundreds of binding reactions occur reliably and simultaneously without disruptive mutual interference. The design principles that enable this remarkable compatibility have not yet been adequately elucidated. In order to delineate these principles, we consider the intracellular sensing of transition metals in bacteria-an integral part of cellular metal homeostasis. Protein cytosolic sensors typically interact with metals through three types of lateral chain residues, containing oxygen, nitrogen, or sulfur. The very existence of complete sets of mutually compatible sensors is a nontrivial problem solved by evolution, since each metal sensor has to bind to its cognate metal without being "mismetallated" by noncognate competitors. Here, based solely on theoretical considerations and limited information about binding constants for metal-amino acid interactions, we are able to predict possible "sensor compositions," i.e., the residues forming the binding sites. We find that complete transition-metal sensor sets are severely limited in their number by compatibility requirements, leaving only a handful of possible sensor compositions for each transition metal. Our theoretical results turn out to be broadly consistent with experimental data on known bacterial sensors. If applicable to other cytosolic binding interactions, the results generated by our approach imply that compatibility requirements may play a crucial role in the organization and functioning of intracellular processes.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-04-30
DOI
https://doi.org/10.1073/pnas.2427151122
Citations
4
Primary Topic
Bacterial Genetics and Biotechnology
Type
article
Field-Weighted Citation Impact
7.27

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article

Compatibility of intracellular binding: Evolutionary design principles for metal sensors

Logan Chariker, Nicolas Lenner, Stanislas Leibler
4 citations
Proceedings of the National Academy of Sciences
Bacterial Genetics and Biotechnology
7.27
article

Compatibility of intracellular binding: Evolutionary design principles for metal sensors

Logan Chariker, Nicolas Lenner, Stanislas Leibler
article en
4 citations

Abstract

In the common cellular space, hundreds of binding reactions occur reliably and simultaneously without disruptive mutual interference. The design principles that enable this remarkable compatibility have not yet been adequately elucidated. In order to delineate these principles, we consider the intracellular sensing of transition metals in bacteria-an integral part of cellular metal homeostasis. Protein cytosolic sensors typically interact with metals through three types of lateral chain residues, containing oxygen, nitrogen, or sulfur. The very existence of complete sets of mutually compatible sensors is a nontrivial problem solved by evolution, since each metal sensor has to bind to its cognate metal without being "mismetallated" by noncognate competitors. Here, based solely on theoretical considerations and limited information about binding constants for metal-amino acid interactions, we are able to predict possible "sensor compositions," i.e., the residues forming the binding sites. We find that complete transition-metal sensor sets are severely limited in their number by compatibility requirements, leaving only a handful of possible sensor compositions for each transition metal. Our theoretical results turn out to be broadly consistent with experimental data on known bacterial sensors. If applicable to other cytosolic binding interactions, the results generated by our approach imply that compatibility requirements may play a crucial role in the organization and functioning of intracellular processes.

Proceedings of the National Academy of SciencesVol. 122(18)
Duke University (US), Laboratory of Molecular Genetics (PL), Center for Systems Biology (US), Toronto Metropolitan University (CA), Rockefeller University (US)
Simons Foundation
Openalex Percentile: Top 3%
Bacterial Genetics and Biotechnology
7.27
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