Denter, M. | Search bioRxiv

bioRxiv2026

Systematic evaluation of Cyanidioschyzon merolae across photobioreactor systems: Linking reactor design to biomass production and biochemical composition

Extremophilic red microalgae are promising platforms for sustainable biotechnology, combining robust growth under selective thermoacidophilic conditions with production of thermostable phycobiliproteins and carbon-rich biomass. However, reactor-dependent effects on growth, product formation and biomass composition remain insufficiently resolved. Here, we systematically evaluated the extremophilic red microalga Cyanidioschyzon merolae across cultivation scales and reactor formats and benchmarked its performance against the well-established Galdieria javensis and Limnospira platensis. In small-scale multi-cultivator photobioreactors and microfluidic growth chambers, C. merolae showed superior growth, reaching a maximum growth rate of 0.034 {+/-} 0.001 h-1 and 8.3 {+/-} 0.3 g l-1 cell dry weight. Microfluidic cultivation enabled growth analysis at single-cell resolution and matched growth rates obtained in photobioreactors. To identify scalable production strategies, C. merolae was further cultivated in a flat-panel photobioreactor and a custom-designed internally illuminated photobioreactor. The custom-designed photobioreactor delivered the highest biomass concentration and productivity, yielding 11.5 {+/-} 0.6 g l-1 cell dry weight and 1.07 {+/-} 0.06 g l-1 d-1, and comparable yields with regard to R-phycocyanin and R-allophycocyanin. Biomass analysis revealed substantial carbon and nitrogen contents, starch accumulation up to > 20 % of cell dry weight, and fatty acids dominated by palmitic, linoleic and oleic acids. Despite its reduced cell wall fraction, C. merolae contained structurally diverse, cultivation-dependent polysaccharides. These results establish C. merolae as a versatile chassis for thermostable pigment production and renewable feedstock generation, highlighting photobioreactor design as a key determinant of productivity and biomass quality.

microbiology↗

bioRxiv2024

deadtrees.earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, not standardized and not spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map tree mortality over time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Drones provide a cost-effective source of training data by capturing high-resolution orthophotos of tree mortality events at sub-centimeter resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than a thousand centimeter-resolution orthophotos, covering already more than 300,000 ha, of which more than 58,000 ha are fully annotated. This community-sourced and rigorously curated dataset shall serve as a foundation for a global initiative to gather comprehensive reference data. In concert with Earth observation data and machine learning it will serve to uncover tree mortality patterns from local to global scales. This will provide the foundation to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. Thus, the open and interactive nature of deadtrees.earth together with the collective effort of the community is meant to continuously increase our capacity to uncover and understand tree mortality patterns.

ecology↗