Stress responses and survival strategies in the opportunistic pathogen Acinetobacter baumannii
Bibliographic record
Abstract
Acinetobacter baumannii, a Gram-negative opportunistic pathogen, is a leading cause of multi-drug resistant hospital-acquired infections. Understanding how this bacterium responds and survives stressful conditions is thus critical to inform development of treatments and clinical practices. Here, we elucidate key mechanisms of how A. baumannii responds to DNA damage and how this contributes to mutagenesis and antibiotic resistance acquisition. Furthermore, we shed light on the role of stress-induced physiological changes, namely biofilm formation, in this pathogen. Since it increases genomic mutagenesis, DNA damage from both exogenous and endogenous sources can lead to acquired antibiotic resistance through activation of the DNA damage response (DDR). The genetic network of the DDR in A. baumannii deviates from the bacterial DDR paradigm due to the lack of a highly-conserved global transcriptional regulator. Additionally, A. baumannii cells express classical DNA damage response genes with a bimodal pattern: within a genetically identical population, one fraction of cells has low expression while the other has high expression in response to DNA damage. We hypothesize that this bimodal response may produce phenotypic plasticity within clonal cells. The research presented in this dissertation has largely focused on determining the regulatory network underlying this phenomenon. Specifically, we identify a novel 5'Untranslated region (UTR) regulatory element in the transcript for the key DNA damage response gene, recA, that underlies phenotypic heterogeneity of its own expression. Maintenance of the 5'UTR structure is critical for maintaining transcript stability and mediating RecA-dependent processes, such as UV survival and acquired antibiotic resistance acquisition. In addition to a high frequency of antibiotic resistance acquisition, A. baumannii also robustly survives on surfaces. Thus, we chose to study multicellular, often surface-attached, communities known as biofilms in A. baumannii. We found that RecA negatively influences biofilm formation, and that ΔrecA mutant surface-attached cells are more difficult to eradicate with antibiotic treatment. We further expand the basic biology of A. baumannii and identified and characterized a role for the bacterial Lon protease in the physiology of A. baumannii. We find that Lon has a positive influence on biofilm, motility and a negative role in capsule formation. Overall, this work helped us to further understand the heterogeneity and complexity of stress responses and survival strategies in a highly-resistant bacterium.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".