Cofactory Ltd (2026)
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Findings below are derived from computational modelling and are not experimentally confirmed. They are provided for exploratory purposes only and require further validation before any commercial application.
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Sugar kelp is one of the most important seaweed crops. This project mapped out sugar kelp secondary metabolism to assess whether or not biorefineries are missing out on high-value chemicals (HVC). This briefing document summarises our findings.
Here, HVCs mean small molecule chemicals with higher-value applications than thickeners, fillers, etc. Even at low volumes, HVCs with useful activity can be very valuable as medicines, agrochemicals, synthetic intermediates, dyes, flavours and fragrances, etc.
This short project’s goal was to build a map of sugar kelp secondary metabolism to help the community assess whether or not we might be overlooking potentially high-value seaweed chemical products.
This project was funded by InnovateUK
[By Baralloco - Own work, CC BY-SA 3.0](https://commons.wikimedia.org/w/index.php?curid=15835952](https://commons.wikimedia.org/w/index.php?curid=15835952)
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Cofactory Ltd provides Technology Development support across Bioinformatics, AI and Process Modelling to help our partners solve difficult technical problems and define new product concepts.
Our Product Development supports cover customer profiling, marketing strategy, building sales channels and funnels, soft launches and pricing, and Sales team building.
We also provide Business Development support to spinouts and startups on pitching, grants, fundraises, and exits.
Read more about our published work across Biology, Chemistry, Computer Science and Process Engineering.
See our wider project portfolio.
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Sugar kelp evidently has abundant mid-value polymers, lipids and lipid derivatives, but our goal here was to focus on higher-value chemicals amongst secondary metabolites.
Figure 1. Industrial classes (purple), chemicals (yellow) and reactions (green) in the SBML.
The dominant chemical class of industrial interest was the terpenoids.
Amongst these, our industrial class definition maps monoterpenoids, diterpenoids, triterpenoids, sesquiterpenoids, and carotenoids.
Those in bold are most abundant in our network reconstruction (Figure 1).
Sugar kelp has the genetic potential to synthesise valuable terpenoids, although it is not possible to infer abundance from our analysis.
Prostaglandins are clinically important lipid mediators used in inflammation control, cardiovascular regulation, and reproductive medicine. They are known in several seaweed species where they mediate stress and defence responses upon tissue damage.
We identified regulators of prostaglandin-like biosynthetic genes (Table 1) that likely trigger in response to mechanical stress.
| Gene | EC | Evidence (BLAST/HMMER) | Call |
|---|---|---|---|
| FUN_001410 | 1.1.1.2 | Annotated AKR1A1, PFAM:PF00248 | Strong AKR‑family, PGF‑capable generalist |
| FUN_011149 | 1.11.1.20 | BLAST 89.4 (2.6e‑22), HMMER 104.0 (1.3e‑29) | Strong COX/peroxidase‑like |
| FUN_022274 | 1.14.99.1 | BLAST 57.8 (1.4e‑08) | Medium COX/P450‑like |
| FUN_019796 | 1.14.99.1 | HMMER 43.1 (3.4e‑11) | Medium COX/P450‑like |
| FUN_015735 | 5.3.99.2 | BLAST 109.0 (5.7e‑30) | Strong PGD‑synthase‑like |
| FUN_002507 | 5.3.99.3 | BLAST 116.0 (8.7e‑31) | Strong PGES‑like |
Table 1: Probable prostaglandin biosynthetic genes, mapped to Enzyme Classification (EC) numbers describing the chemical reactions they catalyse, with evidence based upon sequence comparisons.
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In two months, we used a plethora of computational tools to analyse sugar kelp DNA, reconstruct the metabolic network, and build a rich knowledge graph that integrates genes, their predicted functions and open public metabolic data.
Note that the network describes genetic potential, rather than proven chemical abundance. Without gene expression and/or metabolic concentration levels, we cannot easily assess chemical abundance, which is critical for biorefining. These results are best considered as opening up lines of future inquiry.
Future improvements might consider integration of licensed metabolic pathway data, plus more extensive use of Graph Data Science to plug gaps and impute missing or trim erroneous relationships deriving from prediction and source database errors.
Below, we make key project data files available as a community edition under a CC BY-SA 4.0 Attribution-ShareAlike license. For bespoke commercial analyses, such as queries about chemical classes of specific interest, we offer Enterprise services. Get in touch here.
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