Modulation of xanthophyll cycle impacts biomass productivity in the marine microalga Nannochloropsis

Giorgio Perin, Alessandra Bellan, Tim Michelberger, Dagmar Lyska, Setsuko Wakao, Krishna K Niyogi, Tomas Morosinotto. Plant Biology. 2023 Jun 20;120(25):e2214119120. doi:


Life on earth depends on photosynthetic primary producers that exploit sunlight to fix CO2 into biomass. Approximately half of global primary production is associated with microalgae living in aquatic environments. Microalgae also represent a promising source of biomass to complement crop cultivation, and they could contribute to the development of a more sustainable bioeconomy. Photosynthetic organisms evolved multiple mechanisms involved in the regulation of photosynthesis to respond to highly variable environmental conditions. While essential to avoid photodamage, regulation of photosynthesis results in dissipation of absorbed light energy, generating a complex trade-off between protection from stress and light-use efficiency. This work investigates the impact of the xanthophyll cycle, the light-induced reversible conversion of violaxanthin into zeaxanthin, on the protection from excess light and on biomass productivity in the marine microalgae of the genus Nannochloropsis. Zeaxanthin is shown to have an essential role in protection from excess light, contributing to the induction of nonphotochemical quenching and scavenging of reactive oxygen species. On the contrary, the overexpression of zeaxanthin epoxidase enables a faster reconversion of zeaxanthin to violaxanthin that is shown to be advantageous for biomass productivity in dense cultures in photobioreactors. These results demonstrate that zeaxanthin accumulation is critical to respond to strong illumination, but it may lead to unnecessary energy losses in light-limiting conditions and accelerating its reconversion to violaxanthin provides an advantage for biomass productivity in microalgae.

Photorespiration is the solution, not the problem

Broncano LS, Pukacz KR, Reichel-Deland V, Schlüter U, Triesch S, Weber AP. Journal of Plant Physiology. 2023 Mar 1;282:153928. doi:


The entry of carbon dioxide from the atmosphere into the biosphere is mediated by the enzyme Rubisco, which catalyzes the carboxylation of ribulose 1,5-bisphosphate (RuBP) as the entry reaction of the Calvin Benson Bassham cycle (CBBC), leading to the formation of 2 molecules of 3-phosphoglyceric acid (3PGA) per CO2 fixed. 3PGA is reduced to triose phosphates at the expense of NADPH+ H⁺ and ATP that are provided by the photosynthetic light reactions. Triose phosphates are the principal products of the CBBC and the precursors for almost any compound in the biosphere.

PlantACT! : How to Tackle the Climate Crisis

Hirt, H., Al-Babili, S., Almeida-Trapp, M., Antoine, M., Aranda, M., Bartels, D., … Young, I. M. TRENDS IN PLANT SCIENCE, vol. 28, no. 5, 2023, pp. 537–43, doi: 10.1016/j.tplants.2023.01.005


Greenhouse gas (GHG) emissions have created a global climate crisis which requires immediate interventions to mitigate the negative effects on all aspects of life on this planet. As current agriculture and land use contributes up to 25% of total GHG emissions, plant scientists take center stage in finding possible solutions for a transition to sustainable agriculture and land use. In this article, the PlantACT! (Plants for climate ACTion!) initiative of plant scientists lays out a road map of how and in which areas plant scientists can contribute to finding immediate, mid-term, and long-term solutions, and what changes are necessary to implement these solutions at the personal, institutional, and funding levels.

COBREXA. jl: constraint-based reconstruction and exascale analysis

Kratochvíl M, Heirendt L, Wilken SE, Pusa T, Arreckx S, Noronha A, van Aalst M, Satagopam VP, Ebenhöh O, Schneider R, Trefois C.

Bioinformatics, Feb 2022, 15;38(4):1171-2, doi: 10.1093/bioinformatics/btab782


COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity. We report the architecture of the package, and demonstrate how the design promotes analysis scalability on several use-cases with multi-organism community models.

Computational Analysis of Alternative Photosynthetic
Electron Flows Linked With Oxidative Stress

Saadat N.P., Nies T, van Aalst M, Hank B, Demirtas  B, Ebenhöh O, Matuszyńska A. Frontiers in Plant Science. 2021, 12, p.750580. doi: 10.3389/fpls.2021.750580


During photosynthesis, organisms respond to their energy demand and ensure the supply of energy and redox equivalents that sustain metabolism. Hence, the photosynthetic apparatus can, and in fact should, be treated as an integrated supply-demand system. Any imbalance in the energy produced and consumed can lead to adverse reactions, such as the production of reactive oxygen species (ROS). Reaction centres of both photosystems are known sites of ROS production. Here, we investigate in particular the central role of Photosystem I (PSI) in this tightly regulated system. Using a computational approach we have expanded a previously published mechanistic model of C3 photosynthesis by including ROS producing and scavenging reactions around PSI. These include two water to water reactions mediated by Plastid terminal oxidase (PTOX) and Mehler and the ascorbate-glutathione (ASC-GSH) cycle, as a main non-enzymatic antioxidant. We have used this model to predict flux distributions through alternative electron pathways under various environmental stress conditions by systematically varying light intensity and enzymatic activity of key reactions. In particular, we studied the link between ROS formation and activation of pathways around PSI as potential scavenging mechanisms. This work shines light on the role of alternative electron pathways in photosynthetic acclimation and investigates the effect of environmental perturbations on PSI activity in the context of metabolic productivity.

Implementation of the β-hydroxyaspartate cycle increases growth performance of Pseudomonas putida on the PET monomer ethylene glycol

von Borzyskowski, L.S., Schulz-Mirbach, H., Castellanos, M.T., Severi, F., Gómez-Coronado, P.A., Paczia, N., Glatter, T., Bar-Even, A., Lindner, S.N. and Erb, T.J., Metabolic Engineering, 76, pp.97-109. doi: 10.1016/j.ymben.2023.01.011


Ethylene glycol (EG) is a promising next generation feedstock for bioprocesses. It is a key component of the ubiquitous plastic polyethylene terephthalate (PET) and other polyester fibers and plastics, used in antifreeze formulations, and can also be generated by electrochemical conversion of syngas, which makes EG a key compound in a circular bioeconomy. The majority of biotechnologically relevant bacteria assimilate EG via the glycerate pathway, a wasteful metabolic route that releases CO2 and requires reducing equivalents as well as ATP. In contrast, the recently characterized β-hydroxyaspartate cycle (BHAC) provides a more efficient, carbon-conserving route for C2 assimilation. Here we aimed at overcoming the natural limitations of EG metabolism in the industrially relevant strain Pseudomonas putida KT2440 by replacing the native glycerate pathway with the BHAC. We first prototyped the core reaction sequence of the BHAC in Escherichia coli before establishing the complete four-enzyme BHAC in Pseudomonas putida. Directed evolution on EG resulted in an improved strain that exhibits 35% faster growth and 20% increased biomass yield compared to a recently reported P. putida strain that was evolved to grow on EG via the glycerate pathway. Genome sequencing and proteomics highlight plastic adaptations of the genetic and metabolic networks in response to the introduction of the BHAC into P. putida and identify key mutations for its further integration during evolution. Taken together, our study shows that the BHAC can be utilized as ‘plug-and-play’ module for the metabolic engineering of two important microbial platform organisms, paving the way for multiple applications for a more efficient and carbon-conserving upcycling of EG in the future.

Network Reconstruction and Modelling Made Reproducible with moped

Saadat NP, van Aalst M, Ebenhöh O. Metabolites. 2022; 12(4):275. doi: 10.3390/metabo12040275


Mathematical modeling of metabolic networks is a powerful approach to investigate the underlying principles of metabolism and growth. Such approaches include, among others, differential-equation-based modeling of metabolic systems, constraint-based modeling and metabolic network expansion of metabolic networks. Most of these methods are well established and are implemented in numerous software packages, but these are scattered between different programming languages, packages and syntaxes. This complicates establishing straight forward pipelines integrating model construction and simulation. We present a Python package moped that serves as an integrative hub for reproducible construction, modification, curation and analysis of metabolic models. moped supports draft reconstruction of models directly from genome/proteome sequences and pathway/genome databases utilizing GPR annotations, providing a completely reproducible model construction and curation process within executable Python scripts. Alternatively, existing models published in SBML format can be easily imported. Models are represented as Python objects, for which a wide spectrum of easy-to-use modification and analysis methods exist. The model structure can be manually altered by adding, removing or modifying reactions, and gap-filling reactions can be found and inspected. This greatly supports the development of draft models, as well as the curation and testing of models. Moreover, moped provides several analysis methods, in particular including the calculation of biosynthetic capacities using metabolic network expansion. The integration with other Python-based tools is facilitated through various model export options. For example, a model can be directly converted into a CobraPy object for constraint-based analyses. moped is a fully documented and expandable Python package. We demonstrate the capability to serve as a hub for integrating reproducible model construction and curation, database import, metabolic network expansion and export for constraint-based analyses.

Knowledge of Regulation of Photosynthesis in Outdoor Microalgae Cultures Is Essential for the Optimization of Biomass Productivity

Perin G, Gambaro F, Morosinotto T. Frontiers in Plant Science. 2022 Apr 4;13:751. doi: 10.3389/fpls.2022.846496


Microalgae represent a sustainable source of biomass that can be exploited for pharmaceutical, nutraceutical, cosmetic applications, as well as for food, feed, chemicals, and energy. To make microalgae applications economically competitive and maximize their positive environmental impact, it is however necessary to optimize productivity when cultivated at a large scale. Independently from the final product, this objective requires the optimization of biomass productivity and thus of microalgae ability to exploit light for CO2 fixation. Light is a highly variable environmental parameter, continuously changing depending on seasons, time of the day, and weather conditions. In microalgae large scale cultures, cell self-shading causes inhomogeneity in light distribution and, because of mixing, cells move between different parts of the culture, experiencing abrupt changes in light exposure. Microalgae evolved multiple regulatory mechanisms to deal with dynamic light conditions that, however, are not adapted to respond to the complex mixture of natural and artificial fluctuations found in large-scale cultures, which can thus drive to oversaturation of the photosynthetic machinery, leading to consequent oxidative stress. In this work, the present knowledge on the regulation of photosynthesis and its implications for the maximization of microalgae biomass productivity are discussed. Fast mechanisms of regulations, such as Non-Photochemical-Quenching and cyclic electron flow, are seminal to respond to sudden fluctuations of light intensity. However, they are less effective especially in the 1–100 s time range, where light fluctuations were shown to have the strongest negative impact on biomass productivity. On the longer term, microalgae modulate the composition and activity of the photosynthetic apparatus to environmental conditions, an acclimation response activated also in cultures outdoors. While regulation of photosynthesis has been investigated mainly in controlled lab-scale conditions so far, these mechanisms are highly impactful also in cultures outdoors, suggesting that the integration of detailed knowledge from microalgae large-scale cultivation is essential to drive more effective efforts to optimize biomass productivity.

Europe’s farm to fork strategy and its commitment to biotechnology and organic farming: conflicting or complementary goals?

Purnhagen KP, Clemens S, Eriksson D, Fresco LO, Tosun J, Qaim M, Visser RG, Weber AP, Wesseler JH, Zilberman D. Trends in plant science. 2021 Jun 1;26(6):600-6. doi: 10.1016/j.tplants.2021.03.012


The European Commission’s Farm to Fork (F2F) strategy, under the European Green Deal, acknowledges that innovative techniques, including biotechnology, may play a role in increasing sustainability. At the same time, organic farming will be promoted, and at least 25% of the EU’s agricultural land shall be under organic farming by 2030. How can both biotechnology and organic farming be developed and promoted simultaneously to contribute to achieving the Sustainable Development Goals (SDGs)? We illustrate that achieving the SDGs benefits from the inclusion of recent innovations in biotechnology in organic farming. This requires a change in the law. Otherwise, the planned increase of organic production in the F2F strategy may result in less sustainable, not more sustainable, food systems.

Constructing and analysing dynamic models with modelbase v1. 2.3: a software update

van Aalst M, Ebenhöh O, Matuszyńska A. BMC bioinformatics. 2021 Dec;22(1):1-5. doi: 10.1186/s12859-021-04122-7



Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies, and disease evolution and transmission. Unfortunately, despite community efforts leading to the development of SBML and the BioModels database, many published models have not been fully exploited, largely due to a lack of proper documentation or the dependence on proprietary software. To facilitate the reuse and further development of systems biology and systems medicine models, an open-source toolbox that makes the overall process of model construction more consistent, understandable, transparent, and reproducible is desired.

Results and discussion

We provide an update on the development of modelbase, a free, expandable Python package for constructing and analysing ordinary differential equation-based mathematical models of dynamic systems. It provides intuitive and unified methods to construct and solve these systems. Significantly expanded visualisation methods allow for convenient analysis of the structural and dynamic properties of models. After specifying reaction stoichiometries and rate equations modelbase can automatically assemble the associated system of differential equations. A newly provided library of common kinetic rate laws reduces the repetitiveness of the computer programming code. modelbase is also fully compatible with SBML. Previous versions provided functions for the automatic construction of networks for isotope labelling studies. Now, using user-provided label maps, modelbase v1.2.3 streamlines the expansion of classic models to their isotope-specific versions. Finally, the library of previously published models implemented in modelbase is growing continuously. Ranging from photosynthesis to tumour cell growth to viral infection evolution, all these models are now available in a transparent, reusable and unified format through modelbase.


With this new Python software package, which is written in currently one of the most popular programming languages, the user can develop new models and actively profit from the work of others. modelbase enables reproducing and replicating models in a consistent, tractable and expandable manner. Moreover, the expansion of models to their isotopic label-specific versions enables simulating label propagation, thus providing quantitative information regarding network topology and metabolic fluxes.

A synthetic C4 shuttle via the β-hydroxyaspartate cycle in C3 plants

Roell MS, Schada von Borzykowski L, Westhoff P, Plett A, Paczia N, Claus P, Urte S, Erb TJ, Weber APM.  Proc Natl Acad Sci U S A. 2021 May 25;118(21):e2022307118. doi: 10.1073/pnas.2022307118.


Plants depend on the enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) for CO2 fixation. However, especially in C3 plants, photosynthetic yield is reduced by formation of 2-phosphoglycolate, a toxic oxygenation product of Rubisco, which needs to be recycled in a high-flux-demanding metabolic process called photorespiration. Canonical photorespiration dissipates energy and causes carbon and nitrogen losses. Reducing photorespiration through carbon-concentrating mechanisms, such as C4 photosynthesis, or bypassing photorespiration through metabolic engineering is expected to improve plant growth and yield. The β-hydroxyaspartate cycle (BHAC) is a recently described microbial pathway that converts glyoxylate, a metabolite of plant photorespiration, into oxaloacetate in a highly efficient carbon-, nitrogen-, and energy-conserving manner. Here, we engineered a functional BHAC in plant peroxisomes to create a photorespiratory bypass that is independent of 3-phosphoglycerate regeneration or decarboxylation of photorespiratory precursors. While efficient oxaloacetate conversion in Arabidopsis thaliana still masks the full potential of the BHAC, nitrogen conservation and accumulation of signature C4 metabolites demonstrate the proof of principle, opening the door to engineering a photorespiration-dependent synthetic carbon-concentrating mechanism in C3 plants.