Enhanced bioproduction and processing of mandelic acid enantiomers: towards a sustainable platform for high-value pharmaceutical and polymer applications
Bibliographic record
Abstract
BACKGROUND: Mandelic acid (MA) is a high-value chiral platform molecule with broad applications in pharmaceutical synthesis, cosmetic formulations, and polymer production. Conventional chemical synthesis is limited by harsh reaction conditions, poor enantioselectivity, and environmental concerns. Microbial biosynthesis offers a sustainable and stereoselective alternative; however, its industrial application is constrained by low titres, suboptimal productivity, and inefficient downstream recovery. This study reports an engineered microbial chassis that enables enhanced biosynthesis of MA enantiomers with integrated downstream compatibility. RESULTS: The biosynthetic potential of Escherichia coli was harnessed through targeted metabolic engineering and pathway optimisation for the biosynthesis of (R)- and (S)-MA. Batch fermentations in rich medium produced 1.6 g/L (R)-MA and 1.8 g/L (S)-MA. Transitioning to fed-batch cultivation in defined minimal medium, under non-optimised conditions, increased titres to 2.9 g/L; ee = 99% for (R)-MA and 5.7 g/L; ee = 93% for (S)-MA, representing the highest reported in vivo titres of MA enantiomers achieved in E. coli to date. A two-step downstream process comprising solvent extraction and crystallisation enabled the recovery of MA at high purity (> 99.0%), with recovery efficiencies of 84% for (S)-MA and 77% for (R)-MA. To validate the functional utility of bio-based MA, SAMMA, a sulfuric acid condensation polymer with documented antiviral and contraceptive properties, was synthesised from both bio-based and commercial MA. Additionally, mandelide, a monomer precursor for the biodegradable polystyrene analogue polymandelide (PM), was synthesised to illustrate the platform's relevance to sustainable polymer applications. CONCLUSIONS: This study establishes a robust proof of concept for a microbial platform enabling enantioselective MA biosynthesis from renewable carbon sources. Through the integration of metabolic engineering, downstream process development and application-driven validation, this platform lays the foundation for a scalable and industrially relevant bioproduction strategy. Aligned with the principles of green chemistry and the circular bioeconomy, this approach offers a sustainable and environmentally responsible route to high-value chiral chemicals.
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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) | 0.000 | 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 | 0.001 |
| 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 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".