Presentation Information
[P03-376]Growth phase–dependent dynamics of proteome allocation in Escherichia coli
○Atsushi Hatano1, Yuki Soma2, Masahito Hosokawa3, Masaki Matsumoto1 (1. Graduate School of Medical and Dental Sciences, Niigata University (Japan), 2. Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology (Japan), 3. Graduate School of Advanced Science and Engineering, Waseda University (Japan))
Keywords:
Proteomics,Proteome allocation
[Purpose]
Proteome allocation is a key determinant of bacterial growth and adaptation, yet its regulation across growth phases remains incompletely understood. To address this, we aimed to establish a high-throughput proteomics workflow and apply it to systematically characterize growth phase–dependent proteome dynamics in Escherichia coli.
[Method]
Proteome allocation is a key determinant of bacterial growth and adaptation, yet its regulation across growth phases remains incompletely understood. To address this, we aimed to establish a high-throughput proteomics workflow and apply it to systematically characterize growth phase–dependent proteome dynamics in Escherichia coli.
[Method]
We developed a new workflow by building upon our previously established iSDAC method, originally designed for mammalian cells, and optimizing it for bacterial proteome analysis. To address biases in protein recovery from bacterial cells, we incorporated a heat treatment step, establishing an improved method (hot-iSDAC). This workflow enables reproducible proteome profiling across a wide range of sample inputs, including low-input conditions, and was applied to time-resolved analysis across six growth phases.
[Results]
We quantified 2,567 proteins, of which ~29% exhibited significant growth-dependent changes. Growing-phase cells showed enrichment of iron acquisition and utilization pathways, whereas stationary-phase cells displayed increased abundance of proteins involved in fermentation and anaerobic respiration. Most dynamic proteins followed monotonic trends, with proteome remodeling largely plateauing in stationary phase. Comparative analysis of two E. coli strains, BW25113 and BL21, revealed that although relative protein abundances differed, temporal response patterns were highly conserved. Notably, 89% of proteins with significant temporal changes exhibited similar trajectories between strains. Furthermore, analysis of metabolic gene deletion mutants demonstrated that perturbations in central metabolism differentially reshape proteome allocation, with effects correlating with growth phenotypes.
[Consideration]
These results suggest that growth phase–dependent proteome remodeling follows a largely conserved regulatory program, while relative protein abundance reflects strain-specific and genetic differences. Additionally, metabolic perturbations can substantially alter proteome allocation, indicating a tight coupling between metabolic state and global protein distribution.
[Conclusion]
Our study provides a comprehensive view of growth phase–dependent proteome remodeling in E. coli. The hot-iSDAC workflow enables scalable and reproducible proteome analysis and reveals both conserved and condition-specific principles of bacterial resource allocation.
Proteome allocation is a key determinant of bacterial growth and adaptation, yet its regulation across growth phases remains incompletely understood. To address this, we aimed to establish a high-throughput proteomics workflow and apply it to systematically characterize growth phase–dependent proteome dynamics in Escherichia coli.
[Method]
Proteome allocation is a key determinant of bacterial growth and adaptation, yet its regulation across growth phases remains incompletely understood. To address this, we aimed to establish a high-throughput proteomics workflow and apply it to systematically characterize growth phase–dependent proteome dynamics in Escherichia coli.
[Method]
We developed a new workflow by building upon our previously established iSDAC method, originally designed for mammalian cells, and optimizing it for bacterial proteome analysis. To address biases in protein recovery from bacterial cells, we incorporated a heat treatment step, establishing an improved method (hot-iSDAC). This workflow enables reproducible proteome profiling across a wide range of sample inputs, including low-input conditions, and was applied to time-resolved analysis across six growth phases.
[Results]
We quantified 2,567 proteins, of which ~29% exhibited significant growth-dependent changes. Growing-phase cells showed enrichment of iron acquisition and utilization pathways, whereas stationary-phase cells displayed increased abundance of proteins involved in fermentation and anaerobic respiration. Most dynamic proteins followed monotonic trends, with proteome remodeling largely plateauing in stationary phase. Comparative analysis of two E. coli strains, BW25113 and BL21, revealed that although relative protein abundances differed, temporal response patterns were highly conserved. Notably, 89% of proteins with significant temporal changes exhibited similar trajectories between strains. Furthermore, analysis of metabolic gene deletion mutants demonstrated that perturbations in central metabolism differentially reshape proteome allocation, with effects correlating with growth phenotypes.
[Consideration]
These results suggest that growth phase–dependent proteome remodeling follows a largely conserved regulatory program, while relative protein abundance reflects strain-specific and genetic differences. Additionally, metabolic perturbations can substantially alter proteome allocation, indicating a tight coupling between metabolic state and global protein distribution.
[Conclusion]
Our study provides a comprehensive view of growth phase–dependent proteome remodeling in E. coli. The hot-iSDAC workflow enables scalable and reproducible proteome analysis and reveals both conserved and condition-specific principles of bacterial resource allocation.
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