Evidence map›Paper›PMID 42080835›Full record

ArticleFEMS yeast research2026

Optimization and scale up of L-malic acid production from methanol by the methylotrophic yeast Ogataea polymorpha.

Alessandra Mauri, Miroslava Yovcheva, Philipp Demling, Eva Miriam Buhl, Hendrik Ballerstedt, Lars M Blank

Abstract read
In one paragraph

Article in FEMS yeast research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alessandra MauriInstitute of Applied Microbiology, RWTH Aachen University, Aachen 52074, Germany.ORCID 0009-0007-8669-0127
Miroslava YovchevaInstitute of Applied Microbiology, RWTH Aachen University, Aachen 52074, Germany.
Philipp DemlingInstitute of Applied Microbiology, RWTH Aachen University, Aachen 52074, Germany.ORCID 0000-0002-0351-1119
Eva Miriam BuhlElectron Microscopy Facility, Institute of Pathology, RWTH University Hospital, Aachen 52074, Germany.
Hendrik BallerstedtInstitute of Applied Microbiology, RWTH Aachen University, Aachen 52074, Germany.
Lars M BlankInstitute of Applied Microbiology, RWTH Aachen University, Aachen 52074, Germany.

Funding

Deutsche Forschungsgemeinschaft
6 · The paper itself

Abstract

Industrial production of malic acid remains dependent on fossil resources or, when performed microbiologically, on sugar-based feedstocks. Both routes come with caveats, generating emissions and competing with food supply. The use of CO₂-derived one-carbon substrates offers a promising alternative to circumvent these constraints. In this study, the malic acid production process from methanol in metabolically engineered Ogataea polymorpha NYCY495 LEU-ΔSTE12 Pyc Mdh MAE1 strain was optimized and scaled up. A two-phase cultivation strategy, using glycerol for biomass formation and methanol for product synthesis, was established in shake flasks and subsequently transferred to a 1 L bioreactor. Process optimization through automated feeding strategies was evaluated. DO-based feeding was the most effective approach, using a combination of methanol and glycerol, achieving a final molar yield of 0.1 molMA molMeOH ⁻¹ and a maximum productivity of 0.5 g l⁻¹ h⁻¹. This successful fermentation strategy was validated using green methanol, showcasing the feasibility of "closing the loop" as envisioned in the bioeconomy. Finally, a comparative study of the effect of glycerol, methanol, and their mixture on O. polymorpha NYCY495 LEU-ΔSTE12 Pyc Mdh MAE1 methanol metabolism, peroxisome biogenesis, and cellular redox balance is presented, supporting the positive cumulative effect of both on gene transcription.

Indexed as

MalatesMethanolSaccharomycetalesBiomassBioreactorsFermentationGlycerolMetabolic EngineeringGlycerolmalic acidMethanolbioprocess optimizationC1 metabolismcofeedinggreen methanolmethylotrophic yeasttranscriptomics

Identifiers

PMID42080835
PMCPMC13189001

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.