Synthetic biology can provide an
alternative method for the production of bio-based industrial chemicals. But
constructing the engineered microbial strains required for producing new chemicals
can be time consuming. In this paper, the authors try to quantify the time
requirements, on the basis of a state-of-the-art semi-automated strain
engineering platform, using a collection of monomers for biomaterial production
as their test case.
Psylocibin is a compound most
famously found in “magic mushrooms”. It has potent psychotropic properties,
which aside from its notorious recreational uses, is also thought to hold
potential for the treatment of a range of psychological and neurological ailments.
In their study, Milne et al demonstrate that psylocibin could be
produced using engineered yeast Saccharomyces cerevisiae. Furthermore,
the yeast could produce psilocybin derivatives that may have new useful
Aromatic amino acids are valuable
chemicals and are precursors for a range of industrial compounds. This
particular study looks at p-coumaric acid, which is a central precursor
for many aromatic secondary metabolites, and aims to improve its production in
yeast. Borja et al observed a significant effect that the carbon source
had on the production, where xylose was a better substrate for p-coumaric acid production than glucose.
The comprehensive study of metabolites
within cells, biofluids and tissues, referred to as metabolomics, often generates
huge amounts of complex data generated by mass spectrometry. Identifying
specific metabolites from such large amounts of data is a major challenge faced
by researchers running metabolomics experiments. In this paper, Del Carratore et
al. describe a new annotation method, explaining how the annotations are
being applied and how to evaluate the confidence of the resulting annotations.
The need for efficient DNA
construction methods is inherent to the field of Synthetic Biology. With this
comes the need to verify the accuracy and quality of the engineered DNA through
high-precision sequencing methods. In this paper, the researchers outline an
innovative methodology that will enable newly constructed DNA samples to be
sequenced and verified accurately and cheaply.
- Correia, J., et al., (2019). Artificial Intelligence in Biological Activity Prediction. In: Fdez-Riverola F., Rocha M., Mohamad M., Zaki N., Castellanos-Garzón J. (eds) Practical Applications of Computational Biology and Bioinformatics, 13th International Conference. PACBB 2019. Advances in Intelligent Systems and Computing, vol 1005. Springer, Cham.
Rosmarinic acid is a compound found in several plants. It is widely used as a food and cosmetic ingredient and has various pharmaceutical applications. However the production of this compound remains limited as natural availability is low and chemical synthesis is too complex. This study, for the first time, shows recombinant production of rosmarinic acid in engineered yeast.
Resveratrol is a plant secondary
metabolite with a range of medicinal properties. Its low availability from the plants
has led researchers to develop microbial production of the compound, however commercially
viable production levels are still proving difficult. In this study, the
authors demonstrated that Yarrowia lipolytica is a promising host for
the production of resveratrol along with several other valuable products.
Metabolic engineering involves the
engineering and optimization of processes from single-cell to fermentation in
order to increase production of valuable chemicals. Significant advances in
strain engineering are leading metabolic engineering to become a truly manufacturing
technology capable of producing goods on an industrial scale. This review
article demonstrates that the success of metabolic engineering heavily relies
on biodesign algorithms which identify promising production routes and
The increasing demand for bio-based
compounds is now allowing biofoundries to produce and deliver valuable goods on
an industrial scale. Nowadays, entire portfolios of producer strains are being
developed in record times thanks to the integration and automation of the
design, build, test and learn (DBTL) steps of the production cycle. As new in
silico design tools are being developed to improve the efficacy of DBTL pipelines, the
ever-increasing data gathered by biofoundries can now be added to these in-silico tools,
therefore rendering them even more powerful and reliable. This paper discusses
the future of biomanufacturing in an environment where the process will not
only be fully automated, but will also be able to learn and adapt quickly to
produce optimal designs.
Scientific results from the ShikiFactory100 project will also be made available via CORDIS (Community Research and Development Information Service, the European Commission's public repository for the dissemination of information from all EU-funded research projects.
Results are to be stored and shared between partners via the ICE and GitLab platforms.