Redefining bacterial origins of replication as centralized information processors
Bibliographic record
Abstract
In this review we stress the differences between eukaryotes and bacteria with respect to their different cell cycles, replication mechanisms and genome organizations. One of the most basic and underappreciated differences is that a bacterial chromosome uses only one ori while eukaryotic chromosome uses multiple oris. Consequently, eukaryotic oris work redundantly in a cell cycle divided into separate phases: First inactive replication proteins assemble on eukaryotic oris, and then they await conditions (in the separate "S-phase") that activate only the ori-bound and pre-assembled replication proteins. S-phase activation (without re-assembly) ensures that a eukaryotic ori "fires" (starts replication) only once and that each chromosome consistently duplicates only once per cell cycle. This precise chromosome duplication does not require precise multiple ori firing in S-phase. A eukaryotic ori can fire early, late or not at all. The single bacterial ori has no such margin for error and a comparable imprecision is lethal. Single ori usage is not more primitive; it is a totally different strategy that distinguishes bacteria. We further argue that strong evolutionary pressures created more sophisticated single ori systems because bacteria experience extreme and rapidly changing conditions. A bacterial ori must rapidly receive and process much information in "real-time" and not just in "cell cycle time." This redefinition of bacterial oris as centralized information processors makes at least two important predictions: First that bacterial oris use many and yet to be discovered control mechanisms and second that evolutionarily distinct bacteria will use many very distinct control mechanisms. We review recent literature that supports both predictions. We will highlight three key examples and describe how negative-feedback, phospho-relay, and chromosome-partitioning systems act to regulate chromosome replication. We also suggest future studies and discuss using replication proteins as novel antibiotic targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".