Biocatalytic <i>in Vitro</i> and <i>in Vivo</i> FMN Prenylation and (De)carboxylase Activation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reversible UbiD-like (de)carboxylases represent a large family of mostly uncharacterized enzymes, which require the recently discovered prenylated FMN (prFMN) cofactor for activity. Functional characterization of novel UbiDs is hampered by a lack of robust protocols for prFMN generation and UbiD activation. Here, we report two systems for in vitro and in vivo FMN prenylation and UbiD activation under aerobic conditions. The in vitro one-pot prFMN cascade includes five enzymes: FMN prenyltransferase (UbiX), prenol kinase, polyphosphate kinase, formate dehydrogenase, and FMN reductase, which use prenol, polyphosphate, formate, ATP, NAD+, and FMN as substrates and cofactors. Under aerobic conditions, this cascade produced prFMN from FMN with over 98% conversion and activated purified ferulic acid decarboxylase Fdc1 from Aspergillus niger and protocatechuic acid decarboxylase ENC0058 from Enterobacter cloaceae. The in vivo system for FMN prenylation and UbiD activation is based on the coexpression of Fdc1 and UbiX in Escherichia coli cells under aerobic conditions in the presence of prenol. The in vitro and in vivo FMN prenylation cascades will facilitate functional characterization of novel UbiDs and their applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it