Biology subjects

Arnspang, E. C.

Publications and source records attributed to Arnspang, E. C..

2 recordsLinked to original sources

bioRxiv2025

Iterative and modular expression of Botryococcus braunii genes enhances isoprenoid production in the diatom Phaeodactylum tricornutum

Isoprenoids are essential natural compounds with high structural and functional diversity. Among them, carotenoids and triterpenoids such as squalene have high biotechnological value but remain challenging to produce sustainably. The green microalga Botryococcus braunii synthesizes large amounts of triterpenoids through specialized methylerythritol phosphate (MEP) pathway configurations involving distinct 1-deoxy-D-xylulose-5-phosphate synthase (DXS) isoforms, a bifunctional squalene synthase (SQS) and squalene synthase-like (SSL) enzymes working together for the synthesis of the compound. However, its slow growth limits industrial application. In this work, we established the fast-growing diatom Phaeodactylum tricornutum as a heterologous chassis for terpenoid production using a synthetic biology Design-Build-Test-Learn (DBTL)-based approach. Episomal uLoop assembly enabled rapid expression and evaluation of B. braunii DXS and SQS variants, enhancing precursor flux and resulting in the co-accumulation of squalene and carotenoids. This work demonstrates the functional transfer of specialized algal terpenoid enzymes into a tractable diatom host and highlight P. tricornutums potential as a versatile platform for sustainable, high-value isoprenoid biosynthesis.

synthetic biology↗

bioRxiv2022

Detection of low numbers of bacterial cells in pharmaceutical drug product using Raman Spectroscopy and PLS-DA multivariate analysis.

Sterility testing is a laborious and slow process to detect contaminants present in drug products. Raman spectroscopy is a promising label-free tool to detect microorganisms and thus gaining relevance as future alternative culture-free method for sterility testing in pharmaceutical industry. However, reaching detection limits similar to standard procedures while keeping a high accuracy remains challenging, due to weak bacterial Raman signal. In this work, we show a new non-invasive approach focusing on detect different bacteria in concentrations below 100 CFU/ml within drug product containers using Raman spectroscopy and multivariate data analysis. Even though Raman spectra form drug product with and without bacteria are similar, a partial least squared discriminant analysis (PLS-DA) model shows great performance to distinguish samples with bacteria contaminants in limits below 10 CFU/ml. We use spiked samples with bacteria spores for independent validation achieving a detection accuracy of 99%. Our results indicate a great potential of this rapid, and cost-effective approach to be use in quality control of pharmaceutical industry.

bioengineering↗