Zinc limitation in Klebsiella pneumoniae profiled by quantitative proteomics influences transcriptional regulation and cation transporter-associated capsule production
Bibliographic record
Abstract
BACKGROUND: Microbial organisms encounter a variety of environmental conditions, including changes to metal ion availability. Metal ions play an important role in many biological processes for growth and survival. As such, microbes alter their cellular protein levels and secretion patterns in adaptation to a changing environment. This study focuses on Klebsiella pneumoniae, an opportunistic bacterium responsible for nosocomial infections. By using K. pneumoniae, we aim to determine how a nutrient-limited environment (e.g., zinc depletion) modulates the cellular proteome and secretome of the bacterium. By testing virulence in vitro, we provide novel insight into bacterial responses to limited environments in the presence of the host. RESULTS: Analysis of intra- and extracellular changes identified 2380 proteins from the total cellular proteome (cell pellet) and 246 secreted proteins (supernatant). Specifically, HutC, a repressor of the histidine utilization operon, showed significantly increased abundance under zinc-replete conditions, which coincided with an expected reduction in expression of genes within the hut operon from our validating qRT-PCR analysis. Additionally, we characterized a putative cation transport regulator, ChaB that showed significantly higher abundance under zinc-replete vs. -limited conditions, suggesting a role in metal ion homeostasis. Phenotypic analysis of a chaB deletion strain demonstrated a reduction in capsule production, zinc-dependent growth and ion utilization, and reduced virulence when compared to the wild-type strain. CONCLUSIONS: This is first study to comprehensively profile the impact of zinc availability on the proteome and secretome of K. pneumoniae and uncover a novel connection between zinc transport and capsule production in the bacterial system.
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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) | 0.001 | 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".