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Updated: Jun 18, 2025

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

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Published on: August 18, 2023

Experimental evolution of gene essentiality in bacteria.

Liang Bao¹, Zan Zhu¹, Ahmed Ismail¹

¹Department of Oral and Craniofacial Molecular Biology, Philips Institute for Oral Health Research, School of Dentistry, Virginia Commonwealth University, Virginia, USA.

Biorxiv : the Preprint Server for Biology

|July 29, 2024

Summary

Researchers created essential gene deletion mutants in Streptococcus sanguinis, revealing over 1000 suppressor mutations. This work advances understanding of gene essentiality and gene network interactions in bacteria.

Keywords:

Experimental evolution F1Fo-ATPase/V1Vo-ATPase/TrkA1-H1 gene pathway Gene essentiality Spontaneous mutations Streptococcus Whole-genome sequencing

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Area of Science:

Microbiology
Genetics
Systems Biology

Background:

Essential genes are crucial for cellular functions but challenging to study due to the lack of mutants.
Understanding essential gene interactions is vital for deciphering cellular networks.

Purpose of the Study:

To generate and characterize essential gene deletion mutants in *Streptococcus sanguinis*.
To identify spontaneous mutations and uncover gene and pathway relationships through experimental evolution.

Main Methods:

Deletion mutagenesis of 32 essential genes in *Streptococcus sanguinis*.
Experimental evolution of 243 mutant populations.
Whole-genome sequencing to identify spontaneous suppressor mutations.

Main Results:

Generated 23 viable essential gene deletion mutants exhibiting slow growth.
Identified over 1000 spontaneous suppressor mutations across evolved populations.
Discovered novel gene and pathway relationships, including F1Fo-ATPase/V1Vo-ATPase/TrkA1-H1, and observed distinct mutation patterns compared to wildtype.

Conclusions:

Essential gene deletion mutants provide a platform for studying gene essentiality and interactions.
Experimental evolution coupled with sequencing is effective for uncovering gene network components.
The identified mutations offer insights into bacterial evolution and adaptation mechanisms.