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Synthetic biology

Solutions for your needs in bioinformatics, data handling and modelling

Synthetic biology research team at VTT can provide you with solutions for your needs in bioinformatics, data handling and modelling. In addition, we offer novel solutions for the genetic engineering of efficient cell factories for the production of useful chemicals/biofuels.

A central bottleneck and cost in novel microbial cell factory establishment is the long development time required. Our computing abilities combined with novel approaches to engineer microbes speeds up this process significantly. 

Contact us to learn how we can help you!

Core competencies

Our core competences are metabolic model reconstruction based on genome sequence data, metabolic flux analysis, genome wide data analysis, comparative genomics, protein family analysis, genome editing technologies and microbial gene expression systems. 

For the target product, we can select the most promising alternative pathways among several and predict through modelling the expected performance of the production pathway in a host organism. The best enzymes for the pathway can then be selected by protein family analysis and experimental genome-wide data used to optimise the production host.

Our recent scientific merits include e.g. the establishment of the Metabolic model reconstruction approach CoReCo,  and yeast S. cerevisiae genome editing method YOGE.

Our offering

Using the CoReCo metabolic model reconstruction method, based on the genome sequence, we can efficiently generate a metabolic model for your organism of interest so as to guide metabolic engineering approaches for the production of desired compounds. This approach has already been used successfully in our projects with the chemical and biofuel industries.

Our expertise is strengthened by our links with cutting edge synthetic biology research through our membership in the Industry programme of the Synthetic Biology Engineering Research Center (SynBERC), a network of top US universities within the synthetic biology field (MIT, Harvard, UC Berkeley, UC San Francisco and Stanford).

Our technologies enable the production of novel chemicals and biofuels in industrially relevant microorganisms.

You can learn more about CoReCo here.

​Partners: VTT Technical Research Centre of Finland, Aalto University, University of Turku

Coordinator: Research Professor Merja Penttilä, VTT

Tekes funding: € 3 955 000 (2014 - 2016)

The goal of Living Factories programme is to realise the full potential of Synthetic Biology in Finland. Synthetic Biology is considered one of the key breakthrough technologies that will have a major impact on our future. It is based on the design and engineering of new-to-nature biological systems. It has a great potential to generate novel industrial processes and products.

In Living Factories programme, we will create an academia-education-industry environment that builds on forward-looking know-how and exploits the unique functionalities that biology - combined with engineering sciences - can offer, and which will be highly competitive internationally. This will serve as an inspiration for novel and visionary solutions for a sustainable biobased society.

The key focus of the programme is to develop Synthetic Biology solutions that enable industrial processes that are energy and carbon efficient.


​Selected scientific publications



Synthetic Transcription Amplifier System for Orthogonal Control of Gene Expression in Saccharomyces cerevisiae. Rantasalo A, Czeizler E, Virtanen R, Rousu J, Lähdesmäki H, Penttilä M, Jäntti J, Mojzita D. PLoS One. 2016 Feb 22;11(2):e0148320. doi: 10.1371/journal.pone.0148320. eCollection 2016. PubMed PMID: 26901642.


Xylose-induced dynamic effects on metabolism and gene expression in engineered Saccharomyces cerevisiae in anaerobic glucose-xylose cultures. Alff-Tuomala S, Salusjärvi L, Barth D, Oja M, Penttilä M, Pitkänen JP, Ruohonen L, Jouhten P. Appl Microbiol Biotechnol. 2016 Jan;100(2):969-85. doi: 10.1007/s00253-015-7038-7. Epub 2015 Oct 10. PubMed PMID: 26454869.

Identification of novel isoprene synthases through genome mining and expression in Escherichia coli. Ilmén M, Oja M, Huuskonen A, Lee S, Ruohonen L, Jung S. Metab Eng. 2015 Sep;31:153-62. doi: 10.1016/j.ymben.2015.08.001. Epub 2015  Aug 12. PubMed PMID: 26275749.

A novel aldose-aldose oxidoreductase for co-production of D-xylonate and xylitol from D-xylose with Saccharomyces cerevisiae. Wiebe MG, Nygård Y, Oja M, Andberg M, Ruohonen L, Koivula A, Penttilä M, Toivari M. Appl Microbiol Biotechnol. 2015 Nov;99(22):9439-47. doi: 10.1007/s00253-015-6878-5. Epub 2015 Aug 12. PubMed PMID: 26264136; PubMed Central PMCID: PMC4628093.

Comparison of intracellular and secretion-based strategies for production of human α-galactosidase A in the filamentous fungus Trichoderma reesei. Smith W, Jäntti J, Oja M, Saloheimo M. BMC Biotechnol. 2014 Oct 27;14:91. doi: 10.1186/s12896-014-0091-y. PubMed PMID: 25344685; PubMed Central PMCID: PMC4219008.

Metabolic engineering of the fungal D-galacturonate pathway for L-ascorbic acid production. Kuivanen J, Penttilä M, Richard P. Microb Cell Fact. 2015 Jan 8;14:2. doi: 10.1186/s12934-014-0184-2. PubMed PMID: 25566698; PubMed Central PMCID: PMC4299797.

Bimolecular fluorescence complementation (BiFC) technique in yeast Saccharomyces cerevisiae and mammalian cells. Weber-Boyvat M, Li S, Skarp KP, Olkkonen VM, Yan D, Jäntti J. Methods Mol Biol. 2015;1270:277-88. doi:10.1007/978-1-4939-2309-0_20. PubMed PMID: 25702124.

Suppression of RNAi by dsRNA-degrading RNaseIII enzymes of viruses in animals and plants.  Weinheimer I, Jiu Y, Rajamäki ML, Matilainen O, Kallijärvi J, Cuellar WJ, Lu R, Saarma M, Holmberg CI, Jäntti J, Valkonen JP. PLoS Pathog. 2015 Mar 6;11(3):e1004711. doi: 10.1371/journal.ppat.1004711. eCollection 2015 Mar. PubMed PMID: 25747942; PubMed Central PMCID: PMC4352025.


Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species. Pitkänen E, Jouhten P, Hou J, Syed MF, Blomberg P, Kludas J, Oja M, Holm L, Penttilä M, Rousu J, Arvas M. PLoS Comput Biol. 2014 Feb 6;10(2):e1003465.


Single cell and in vivo analyses elucidate the effect of xylC lactonase during production of D-xylonate in Saccharomyces cerevisiae. Nygård Y, Maaheimo H, Mojzita D, Toivari M, Wiebe M, Resnekov O, Gustavo Pesce C, Ruohonen L, Penttilä M. Metab Eng. 2014 Sep;25:238-47.


Labelling analysis for ¹³C MFA using NMR spectroscopy.  Jouhten P, Maaheimo H. Methods Mol Biol. 2014;1191:143-64.


Electrochemical properties of honeycomb-like structured HFBI self-organized membranes on HOPG electrodes. Yamasaki R, Takatsuji Y, Lienemann M, Asakawa H, Fukuma T, Linder M, Haruyama T. Colloids Surf B Biointerfaces. 2014 Nov 1;123:803-8.


Taxonomically and functionally diverse microbial communities in deep crystalline rocks of the Fennoscandian shield. Nyyssönen M, Hultman J, Ahonen L, Kukkonen I, Paulin L, Laine P, Itävaara M, Auvinen P. ISME J. 2014 Jan;8(1):126-38.


Integration of transcription and flux data reveals molecular paths associated with differences in oxygen-dependent phenotypes of Saccharomyces cerevisiae. Lindfors E, Jouhten P, Oja M, Rintala E, Orešič M, Penttilä M. BMC Syst Biol. 2014. Feb 14;8:16.


Re-annotation of the CAZy genes of Trichoderma reesei and transcription in the presence of lignocellulosic substrates. Häkkinen M, Arvas M, Oja M, Aro N, Penttilä M, Saloheimo M, Pakula TM. Microb Cell Fact. 2012 Oct 4;11:134.



Yeast oligo-mediated genome engineering (YOGE). DiCarlo JE, Conley AJ, Penttilä M, Jäntti J, Wang HH, Church GM. ACS Synth Biol. 2013 Dec 20;2(12):741-9.


Single-cell measurements of enzyme levels as a predictive tool for cellular fates during organic acid production. Zdraljevic S, Wagner D, Cheng K, Ruohonen L, Jäntti J, Penttilä M, Resnekov O, Pesce CG. Appl Environ Microbiol. 2013 Dec;79(24):7569-82.


Noninvasive high-throughput single-cell analysis of the intracellular pH of Saccharomyces cerevisiae by ratiometric flow cytometry. Valkonen M, Mojzita D, Penttilä M, Bencina M. Appl Environ Microbiol. 2013 Dec;79(23):7179-87.


Unconventional microbial systems for the cost-efficient production of high-quality protein therapeutics. Corchero JL, Gasser B, Resina D, Smith W, Parrilli E, Vázquez F, Abasolo I, Giuliani M, Jäntti J, Ferrer P, Saloheimo M, Mattanovich D, Schwartz S Jr, Tutino ML, Villaverde A. Biotechnol Adv. 2013 Mar-Apr;31(2):140-53.



Metabolic modelling in the development of cell factories by synthetic biology. Jouhten P.  Comput Struct Biotechnol J. 2012 Nov 12;3:e201210009.


Dynamic flux balance analysis of the metabolism of Saccharomyces cerevisiae during the shift from fully respirative or respirofermentative metabolic states to anaerobiosis. Jouhten P, Wiebe M, Penttilä M. FEBS J. 2012 Sep;279(18):3338-54.


Metabolic flux profiling of recombinant protein secreting Pichia pastoris growing on glucose:methanol mixtures. Jordà J, Jouhten P, Cámara E, Maaheimo H, Albiol J, Ferrer P. Microb Cell Fact. 2012 May 8;11:57.


Engineering filamentous fungi for conversion of D-galacturonic acid to L-galactonic acid. Kuivanen J, Mojzita D, Wang Y, Hilditch S, Penttilä M, Richard P, Wiebe MG. Appl Environ Microbiol. 2012 Dec;78(24):8676-83.


L-xylo-3-hexulose reductase is the missing link in the oxidoreductive pathway for D-galactose catabolism in filamentous fungi. Mojzita D, Herold S, Metz B, Seiboth B, Richard P. J Biol Chem. 2012 Jul 27;287(31):26010-8.



Correlation of gene expression and protein production rate - a system wide study. Arvas M, Pakula T, Smit B, Rautio J, Koivistoinen H, Jouhten P, Lindfors E, Wiebe M, Penttilä M, Saloheimo M. BMC Genomics. 2011 Dec 20;12:616.



Detecting novel genes with sparse arrays. Arvas M, Haiminen N, Smit B, Rautio J, Vitikainen M, Wiebe M, Martinez D, Chee C, Kunkel J, Sanchez C, Nelson MA, Pakula T, Saloheimo M, Penttilä M, Kivioja T. Gene. 2010 Nov 1;467(1-2):41-51.


Identification of an L-arabinose reductase gene in Aspergillus niger and its role in L-arabinose catabolism. Mojzita D, Penttilä M, Richard P. J Biol Chem. 2010 Jul 30;285(31):23622-8.


Synthetic biology group

      VTT Synthetic biology group


Jussi Jäntti   Jussi Jäntti

My research activities have included studying the protein secretion process and intracellular membrane fusion in yeast and mammalian cells and in C. elegans nematodes. Currently, focus on efficient microbe strain engineering methods for rapid strain construction (e.g. Synthetic biology tools work package leader in the Living Factories project of the Finnish Funding Agency for Innovation, TEKES.)
Career at glance:
M.Sc. 1991, Department of Biochemistry, University of Helsinki
Ph.D. 1995, Department of Biochemistry, University of Helsinki
Docent (Adjunct professor) in Biochemistry, 2002, University of Helsinki
Academy Research Fellow, 2005-2009 Academy of Finland
Group leader, 2005 – 2013, University of Helsinki, Institute of Biotechnology
Research Team leader, 2014- Synthetic biology, VTT Technical Research Centre of Finland.


Merja Oja   Merja Oja


I'm an expert in bioinformatics and systems biology. I received my PhD in bioinformatics from Department of Computer Science and Engineering, Helsinki University of Technology (currently Aalto University) in 2007. After a post doc year at University of Washington in Seattle, I joined VTT in 2009. I have a machine learning background and have developed methods for exploratory data analysis and visualization of large genomic data sets. At VTT I have applied systems biology tools for the study of genome wide measurement data of yeast and fungal species in bioprocess conditions. I worked with fungal genomics, including genome sequencing and annotation projects, and supported enzyme discovery and protein engineering work by developing workflows for genome mining the abundant sequence data resources. I have expertise in metabolic modelling, including methods for metabolic model reconstruction. I have acted as the (deputy) team leader for the Computational Biology team of the CoE in White Biotechnology – Green chemistry (2008-2013) and am currently acting as a (deputy) team leader for the “In silico design of living factories” work package of the Living Factories Programme, a Tekes funded large strategic opening.


Mikko Arvas    Mikko Arvas

( , I am specialised on fungal genome analysis for the needs of industrial biotechnology. I received my PhD in genetics in 2007 from University of Helsinki. I have analysed transcriptomics, proteomics, and strain and species level comparative genomics data to select candidate genes to be produced in fungi or to improve capabilities of fungal production strains. During my career at VTT I have worked as a visiting scientist at Universities of Ghent, Manchester and Cambridge. In 2010 I received a 4 year Academy of Finland Postdoctoral fellow grant for development of metabolic model reconstruction (



Gholamreza Bidkhori    Gholamreza Bidkhori

I received my PhD in Bioinformatics from the University of Tehran, Iran, where my research focused on Lung Cancer Systems Biology. I then worked as lecturer and researcher in the field of cancer modeling in the University of Tehran. My current projects as a metabolic modeler at VTT are related to integration of expression data into metabolic networks and ODE modeling of bacterial metabolic pathways. I am specialized in network reconstruction, Kinetic modeling and parameter estimation, constraint-based modeling, omics data analysis and integration of the data into the signaling, gene regulatory and metabolic networks. ( , )


Michael Lienemann   Michael Lienemann

My current research focus is the production of organic commodities from electricity and simple carbon compounds using electromicrobiology techniques. Earlier during 1998 – 2005, I have conducted my diploma studies in “Technical Biology” at the University of Stuttgart and investigated the bioconversion of terpene compounds using genetically engineered monooxygenase enzymes during my thesis work. This was followed by my doctoral thesis studies which I have conducted at VTT Espoo until the year 2010. Here, interactions between neolectins and their ligands were studied using rational protein design. My areas of expertise include AFM, SPR, molecular engineering, protein purification and electrochemical measurement techniques.

Joosu Kuivanen    Joosu Kuivanen

I received my B.Sc. and M.Sc. degrees from University of Tampere in biochemistry and molecular biology and D.Sc. (Tech) degree from Aalto University in biotechnology (2015). In my doctoral thesis studies I engineered the catabolic D-galacturonate pathway for chemical production in filamentous fungi. I have expertise in metabolic engineering of yeasts and filamentous fungi for industrial biotechnology applications. In addition, I have experience in discovery and characterization of metabolic pathways in fungi.  The current research focus is on development and exploitation of synthetic biology tools and automation in strain engineering.


Sandra Castillo   Sandra Castillo

I studied my M.Sc. in the UAB (Universidad autónoma de Barcelona). My specialization was in genetics in the first and biochemistry in the second. I started working at VTT in 2007 in a metabolomic team. My task was to develop tools in java to store, process and analyze the data (LC-MS and GCxGC-Tof) (MZmine 2 ,Guineu). I moved to synthetic biology team in 2013 where my main task was to set up and run a pipeline for the creation of whole genome metabolic models (CoReCo). My main skills are programming (java, python, R, C#..), database technologies (mysql, neo4j), metabolic and transcriptomic data analysis and algorithm development for curation and visualization of metabolic models.

Dominik Mojzita   Dominik Mojzita

Strong background in molecular biology and genetic engineering of yeast and filamentous fungi. Last 15 years worked on the identification and characterization of novel genes and metabolic pathways, transcriptional and metabolic regulation, genome-wide and gene-specific expression analysis, the production of organic compounds, single-cell analysis, development of synthetic expression tools and the establishment of synthetic control circuits in S. cerevisiae and A. niger.