Overexpression of human alpha-Synuclein leads to dysregulated microbiome/metabolites with ageing in a rat model of Parkinson disease
Bibliographic record
Abstract
Abstract Since Braak’s hypothesis stating that sporadic Parkinson’s disease follows a specific progression of the pathology from the peripheral to the central nervous system and can be monitored by detecting accumulation of the alpha-Synuclein protein. There is growing interest in understanding how the gut (commensal) microbiome can regulate alpha-Synuclein accumulation which can lead to PD. We studied a transgenic rat model overexpressing the human alpha-Synuclein and found that the protein overexpression resulted in gut alpha-Synuclein expression and aggregation in the gut neurons with advancing age. A progressive gut microbial composition alteration characterized by the reduction of Firmicutes to Bacteroidetes ratio could be detected in the young transgenic rat model and interestingly this ratio was then increased with aging. This observation was accompanied in older animals by intestinal inflammation, increase gut permeability and a robust alteration in metabolites production characterized by the increase of succinate level in the feces and serum. Manipulation of the gut bacteria by short-term antibiotics treatment revealed a complete loss of short-chain fatty acids (SCFAs) and reduction in succinate levels. Although antibiotics treatment did not change alpha-synuclein expression in the enteric nervous system of the colon, it can reduce alpha-synuclein expression in the olfactory bulb of the transgenic rats. In summary, synchronous with ageing, our data emphasize that the gut microbiome dysbiosis leads to a specific alteration of gut metabolites which are reflected in the serum and can be modulated by the 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".