Developing Magnetic Resonance Reporter Gene Imaging: Essential Magnetosome Proteins Interact in Mammalian Cells
Bibliographic record
Abstract
To detect cellular activities deep within the body using magnetic resonance (MR) platforms, magnetosomes are the ideal model of genetically-encoded nanoparticles. These organelle-like structures produced by magnetotactic bacteria (MTB) store iron biominerals in membrane-bound vesicles and are highly regulated by approximately 30 genes. To translate this technology into a gene-based iron contrast agent in mammalian cells [1], [2], we are introducing essential membrane-associated magnetosome (mam) genes mamI, mamL, mamB, and mamE into the human melanoma cell line MDA-MB-435 using fluorescent fusion protein vectors. While the expression of enhanced green fluorescent protein (EGFP)-MamI alone resulted in a net-like fluorescence pattern, individual expression of red fluorescent Tomato-MamL, Tomato-MamB, or Tomato-MamE all resulted in a mobile, punctate fluorescence pattern. Coexpression of MamL+I resulted in co-localization of both proteins in a mobile, punctate pattern. Here we report the transient expression of three magnetosome proteins (MamL+I+B or MamL+I+E) in mammalian cells, which results in the co-localization and interaction of all three proteins in a mobile, punctate pattern. These results further support interactions between essential magnetosome proteins in the mammalian intracellular compartment and the co-localization required to form a rudimentary magnetosome-like particle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".