Poglut2/3 double knockout in mice results in neonatal lethality with reduced levels of fibrillin in lung tissues
Bibliographic record
Abstract
Fibrillin microfibrils play a critical role in the formation of elastic fibers, tissue/organ development, and cardiopulmonary function. These microfibrils not only provide structural support and flexibility to tissues, but they also regulate growth factor signaling through a plethora of microfibril-binding proteins in the extracellular space. Mutations in fibrillins are associated with human diseases affecting cardiovascular, pulmonary, skeletal, and ocular systems. Fibrillins consist of up to 47 epidermal growth factor-like repeats, of which more than half are modified by protein O-glucosyltransferase 2 (POGLUT2) and/or POGLUT3. Loss of these modifications reduces secretion of N-terminal fibrillin constructs overexpressed in vitro. Here, we investigated the role of POGLUT2 and POGLUT3 in vivo using a Poglut2/3 double knockout (DKO) mouse model. Blocking O-glucosylation caused neonatal death with skeletal, pulmonary, and eye defects reminiscent of fibrillin/elastin mutations. Proteomic analyses of DKO dermal fibroblast medium and extracellular matrix provided evidence that fibrillins were more sensitive to loss of O-glucose compared to other POGLUT2/3 substrates. This conclusion was supported by immunofluorescent analyses of late gestation DKO lungs where FBN levels were reduced and microfibrils appeared fragmented in the pulmonary arteries and veins, bronchioles, and developing saccules. Defects in fibrillin microfibrils likely contributed to impaired elastic fiber formation and histological changes observed in DKO lung blood vessels, bronchioles, and saccules. Collectively, these results highlight the importance of POGLUT2/3-mediated O-glucosylation in vivo and open the possibility that O-glucose modifications on fibrillin influence microfibril assembly and or protein interactions in the ECM environment.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".