Revealing the Ultrastructure and Intracellular Distributions of Secretory Granules in Malignant Human Mast Cells by Volume Electron Microscopy
Bibliographic record
Abstract
The human mast cell-1 (HMC-1) cell line was established from a patient with mast cell leukemia and is the first established continuously growing HMC line which has been widely employed for in vitro studies of human mast cell biology. HMC-1 has been further subcloned into two sublines: HMC-1.1 and HMC-1.2, having one point and two-point mutations in the protooncogene c-kit, respectively. It has been hypothesized that these specific mutations in c-kit are associated with changes in granule biogenesis except for the phenotype and cellular growth rate [1, 2]. In our previous study, transmission electron microscopy (TEM) micrography of ultra-thin sections showed that the secretory granules in the two sublines of resting HMC-1 cells have different ultrastructures. And the structural evolution of granules in HMC-1.2 is prominent upon drug treatment with sodium butyrate [2]. However, individual 2D images of cell thin sections couldn’t give a full picture of differences in terms of granular distribution, content density or ultrastructures. It is therefore necessary to develop approaches that can better distinguish changes in granule using more robust techniques. Herein, volume electron microscopy (vEM) was applied to explore 3D intracellular structures of secretory granules and their cytoplasmic distributions in HMC-1 cells, which may link their structures to physiological function differences [3]. In brief, HMC-1 cells were cultured in suspension using standard protocols [2]. After 1 month of culture with a complete media change every 2 days, cells were collected for volume EM sample preparation. The harvested cells were chemically fixed with 1.5% glutaraldehyde and 2% paraformaldehyde, and pre-stained with heavy metal salt solution containing osmium tetroxide and lead aspartate. Then cell pellets were sequentially dehydrated using 30%, 50%, 70%, 90%, 100% ethanol, followed by embedding with fresh LR white and polymerization at 55°C for overnight. Resin blocks of the cells were trimmed and sectioned using ultramicrotomy to expose the cell interfaces and evaluated for image contrast in SEM. Then the exposed block surfaces were coated with gold thin films for slicing and imaging in a plasma focused ion beam scanning electron microscope (FIB-SEM) dual beam system. Cells with cytoplasmic granules and in the position of half a cell (judged by the nuclear size) were selected for slicing and viewing. FIB slicing step size was set to 5 nm and images were taken every second slice. The total sliced volume was 25 µm x 22 µm x 7 µm. After tilt corrections for image pixel resolution and alignment, the 3D ultrastructure of half a cell or cell in a depth great than 3 µm was reconstructed. The secretory granules, mitochondria and nuclear organelles were identified from sliced images and the reconstructed 3D volume view of cells, as shown in Fig. 1 of a typical reconstructed 3D micrography of HMC-1.2 cell. The secretory granules of interest are elliptical in shape with more uniform contents in the compartments with a size of 300-600 nm and 200-480 nm in long and short axis, respectively. The granular membranes are bilayer membranes. Compared with those in HMC-1.2 cells, granules in HMC-1.1 cells have more vacuoles and densely packed contents. The size and compartment contents are more heterogeneous, which may result in heterogeneous morphology and size of HMC-1.1 cells [4]. Three – dimensional rendering of a typical reconstructed intracellular structure of HMC-1.2 cell: a) slice view; and b) volume view.
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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".