ArticleScientific data2023
Interaction networks of Escherichia coli replication proteins under different bacterial growth conditions.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- The chromosomal origin of replication as the basis for the spatio-temporal biology of bacteria.Frontiers in microbiology · 2026Review
- A Multidrug-ResistantVeterinary sciences · 2025Article
- Hypothesis: bacteria live on the edge of phase transitions with a cell cycle regulated by a water-clock.Theory in biosciences = Theorie in den Biowissenschaften · 2024Article
- Ultraviolet technology application in urban water supply and wastewater treatment in China: Issues, challenges and future directions.Water research X · 2024Article
- Essential factors, advanced strategies, challenges, and approaches involved for efficient expression of recombinant proteins in Escherichia coli.Archives of microbiology · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
In this work we analyzed protein-protein interactions (PPIs) formed by E. coli replication proteins under three disparate bacterial growth conditions. The chosen conditions corresponded to fast exponential growth, slow exponential growth and growth cessation at the stationary phase. We performed affinity purification coupled with mass spectrometry (AP-MS) of chromosomally expressed proteins (DnaA, DnaB, Hda, SeqA, DiaA, DnaG, HolD, NrdB), tagged with sequential peptide affinity (SPA) tag. Composition of protein complexes was characterized using MaxQuant software. To filter out unspecific interactions, we employed double negative control system and we proposed qualitative and quantitative data analysis strategies that can facilitate hits identification in other AP-MS datasets. Our motivation to undertake this task was still insufficient understanding of molecular mechanisms coupling DNA replication to cellular growth. Previous works suggested that such control mechanisms could involve physical interactions of replication factors with metabolic or cell envelope proteins. However, the dynamic replication protein interaction network (PIN) obtained in this study can be used to characterize links between DNA replication and various cellular processes in other contexts.
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Registered trials
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