PAcMEN · Project

Computational Tools to Engineer Microbes That Turn Waste Into Fuels and Chemicals

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Imagine you could reprogram yeast — the same stuff that makes bread rise — so instead of producing alcohol, it churns out jet fuel or industrial chemicals from agricultural waste. That's metabolic engineering, and the biggest headache is that redesigning a living cell is mostly trial and error today. PAcMEN trained 16 PhD researchers across Europe to build computer models that predict how engineered yeast will behave before you even touch a lab bench. The result: faster, cheaper design cycles for the biological factories that could eventually replace oil refineries.

By the numbers

PhD researchers trained in metabolic engineering

PhD positions funded by EU contribution

consortium partners across the network

countries represented in the consortium

European universities in the core network

industry partners in the consortium

54%

industry partner ratio in the consortium

genome-scale and kinetic models delivered for S. cerevisiae

The business problem

What needed solving

The world runs on fossil oil, gas, and coal for both energy and chemicals — but these resources are finite and environmentally destructive. Companies need to switch to bio-based production, but engineering microbes to convert biomass into target chemicals is painfully slow and unpredictable, with each design-build-test cycle taking months.

The solution

What was built

PAcMEN delivered kinetic models of native metabolism and production pathways in S. cerevisiae, plus a next-generation genome-scale model of S. cerevisiae that includes protein synthesis. These computational tools allow researchers to predict how engineered yeast strains will perform before committing to costly laboratory experiments.

Audience

Who needs this

Biorefinery operators designing new microbial production strainsSpecialty chemical companies transitioning from petrochemical to bio-based feedstocksIndustrial biotech SMEs developing yeast-based production platformsEnzyme manufacturers optimizing microbial cell factoriesBiofuel startups seeking to accelerate strain engineering timelines

Business applications

Who can put this to work

Biofuels & Renewable Energy

mid-size

Target: Biorefinery operators or biofuel producers looking to replace petroleum-based processes

If you are a biorefinery operator struggling with unpredictable fermentation yields — this project developed kinetic models and next-generation genome-scale models of S. cerevisiae that can predict cell behavior before lab testing. With 7 industry partners validating the approach across 8 countries, these models could cut your strain development cycle significantly.

Industrial Biotechnology & Chemicals

any

Target: Specialty chemical manufacturers switching from petrochemical to bio-based feedstocks

If you are a chemical manufacturer dealing with rising fossil feedstock costs and pressure to go green — PAcMEN built genome-scale models including protein synthesis for yeast, enabling more accurate prediction of how engineered strains produce target chemicals. The consortium included 3 SMEs working on real industrial problems, grounding the models in practical applications.

Enzyme & Biosensor Development

SME

Target: Biosensor companies or enzyme producers needing optimized microbial production platforms

If you are a biosensor or enzyme company facing long development timelines for new production strains — this project combined metabolic engineering with computational prediction tools across 13 partners. The kinetic models of native metabolism and production pathways in S. cerevisiae can help you screen strain designs computationally instead of running thousands of lab experiments.

Frequently asked

Quick answers

What would it cost to use these computational models in our R&D?

The project did not publish pricing or licensing terms for its models. Since PAcMEN was a publicly funded training network (MSCA-ITN-ETN), the underlying research is likely published in open-access journals. However, adapting these genome-scale models to your specific organism or product would require specialist expertise — potentially from the trained researchers themselves.

Can these models work at industrial production scale?

The models were developed for S. cerevisiae (baker's yeast), which is already used at industrial scale in bioethanol and brewing. However, the deliverables describe kinetic models and genome-scale models — these are predictive design tools, not production-ready strains. Scaling would require additional strain engineering and process development beyond what PAcMEN delivered.

Who owns the intellectual property from this project?

IP from MSCA training networks typically stays with the host institutions (5 universities and 2 SMEs in this case). The coordinator is Danmarks Tekniske Universitet in Denmark. Companies interested in licensing specific models should contact DTU or the relevant partner institution directly.

How mature is the technology — is it ready to use?

Based on available project data, the deliverables are computational models (kinetic models and genome-scale models of yeast metabolism). These are research-grade tools at roughly TRL 2-3. They demonstrate proof of concept but would need further validation and integration before commercial deployment.

What specific organisms and products were modeled?

The deliverables specifically mention S. cerevisiae (baker's yeast) and Yarrowia lipolytica, with models covering lipid production, native metabolism, and protein synthesis pathways. These are two of the most industrially relevant yeast species for bio-based chemical production.

Could this help us reduce our R&D costs for strain development?

That is exactly the problem PAcMEN addressed. Traditional metabolic engineering has low predictability and long turnover times for cell factory construction and screening. The predictive models developed here aim to let you test designs computationally first, reducing the number of expensive and slow lab iterations needed.

Is there ongoing support or follow-up from the consortium?

PAcMEN ended in September 2020 and the consortium included 13 partners across 8 countries. The 16 trained PhD researchers are now in the workforce — many likely in industry or academic positions in metabolic engineering. The project website (pacmen-itn.eu) may have alumni contacts, though ongoing consortium-level support has concluded.

Consortium

Who built it

PAcMEN assembled a strong mix of 13 partners — 7 from industry and 6 from universities — across 8 countries (Denmark, Germany, Netherlands, Sweden, Norway, Portugal, Switzerland, and the US). The 54% industry ratio is notably high for a training network, suggesting the research was grounded in real commercial needs rather than purely academic curiosity. The consortium includes 3 SMEs, indicating involvement of agile biotech companies alongside larger industrial players. The coordinator, Danmarks Tekniske Universitet (DTU), is one of Europe's leading technical universities with deep expertise in metabolic engineering and industrial biotechnology.

DANMARKS TEKNISKE UNIVERSITETCoordinator · DK
DONG ENERGY THERMAL POWER ASpartner · DK
BORREGAARD ASpartner · NO
DSM FOOD SPECIALTIES BVpartner · NL
RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHENparticipant · DE
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNEparticipant · CH
EVOLVA AGpartner · CH
SILICOLIFE LDAparticipant · PT
THE REGENTS OF THE UNIVERSITY OF CALIFORNIApartner · US
SESAM-BIOTECH GMBHparticipant · DE
TECHNISCHE UNIVERSITEIT DELFTparticipant · NL
CHALMERS TEKNISKA HOGSKOLA ABparticipant · SE

How to reach the team

Danmarks Tekniske Universitet (DTU), Denmark — metabolic engineering department. SciTransfer can help identify the right contact person.

Order a report on this consortium See DANMARKS TEKNISKE UNIVERSITET profile →

Next steps

Talk to the team behind this work.

Want to connect with PAcMEN researchers for your bio-based production challenge? SciTransfer can identify the right expert from the 16 trained specialists and arrange an introduction.

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