Biology subjects

Matuszynska, A.

Publications and source records attributed to Matuszynska, A..

8 recordsLinked to original sources

bioRxiv2026

Experimental and computational analyses of KEA3-dependent photosynthetic responses uncover species-specific molecular variation

- NPQ relaxation is thought to limit crop biomass and yield under natural, fluctuating light. The thylakoid K/H exchanger KEA3 accelerates NPQ relaxation by lowering the lumen proton concentration and thus should affect biomass and yield under frequent light fluctuations. - To investigate the impact of KEA3-dependent NPQ relaxation on Solanum lycopersicum (tomato), we generated knock-out and over-expression lines and measured NPQ, gas exchange, biomass and yield. We constructed a mathematical model to compare species-specific NPQ relaxation dynamics in tomato and the model plant Arabidopsis thaliana. - In polytunnel and controlled fluctuating-light conditions, KEA3-mediated NPQ relaxation did not translate into consistent differences in tomato biomass or yield. Although KEA3 levels strongly affected NPQ relaxation, more so than in A.thaliana, the resulting effects on CO2 assimilation were minor. Modeling results indicated that, besides minor changes in KEA3 regulation, the activity of PsbS, the primary NPQ trigger, largely determines the species-specific differences in NPQ relaxation. Structural models from both species predict sequence variation with impact on PsbS activation. - Manipulating KEA3 levels in tomato did not link NPQ relaxation with productivity. However, the results support robust cross-species mathematical model that accurately predicts the molecular interactions governing NPQ dynamics.

plant biology↗

bioRxiv2026

From Field Photosynthesis to Genetic Architecture: Insights from the First Dedicated Photosynthesis Hackathon

Photosynthesis is among the most consequential yet genetically complex traits in crop plants, and translating its natural variation into actionable genomic targets remains a central challenge for breeding climate-resilient varieties. To start addressing this, researchers are generating increasingly large, multi-environment field photosynthesis datasets. Yet, these data have been structurally under-analysed since their inception. Here we report the outcomes of the first dedicated hackathon focused on computational mining of such field data held in Accra, Ghana, in March 2026. Bringing together data scientists, plant physiologists, geneticists, and breeders from Europe and Africa, these interdisciplinary teams used photosynthetic data collected with hand-held fluorometers to genome-wide marker data across four crop species: cowpea (Vigna unguiculata), barley (Hordeum vulgare), common bean (Phaseolus vulgaris), and potato (Solanum tuberosum). Despite using different species and methods, independent teams identified the same three key findings. First, mechanism-informed feature engineering and dynamic modelling recover genetic signals that are not detected or discarded in standard analysis pipelines, resulting in traits with improved heritability and meaningful associations with yield. Secondly, machine learning methods proved effective at uncovering genetic associations, with temporally resolved features substantially outperforming single time-point measurements. Third, raw chlorophyll fluorescence and absorbance traces consistently contained more information and predictive power than the extracted parameters currently used. A defining feature of this event was having experimentalists and data scientists working together, enabling AI approaches to be grounded in domain knowledge and biological mechanisms rather than relying on data alone.

plant biology↗

bioRxiv2026

GreenSloth: a curated database and executable platform for mechanistic photosynthesis models

Mechanistic models of photosynthesis have expanded substantially over the past decades, covering processes from light reactions to carbon fixation. However, these models remain fragmented across the literature, inconsistently implemented, and difficult to reproduce or reuse, limiting their adoption beyond the research group that developed them. Here, we present GreenSloth, a freely accessible web-based database of 22 published mechanistic photosynthesis models, reimplemented as standardized, executable Python objects within MxlPy, an open-source framework for mechanistic biological modeling. Although the database is primarily designed for dynamic mechanistic models formulated as ordinary differential equations, the current implementation also includes the fields most widely cited steady-state mechanistic model and its variants. GreenSloth provides a structured environment for model discovery, comparison, and reuse, addressing reproducibility challenges in the field and enabling integration into emerging hybrid modeling approaches. It is also interactive: each model runs directly in the browser, with no installation, environment setup, or programming required. The resource is openly accessible and designed for long-term community maintenance, hoping to position itself as foundational infrastructure for the photosynthesis modeling community. Database URLhttps://greensloth.rwth-aachen.de/

systems biology↗

bioRxiv2026

Cooperation, privatization and cheating in microbial exoenzyme synthesis: theoretical analysis in view of biotechnological applications

This study presents a mathematical framework for investigating the dynamics of coexistence and competition among heterotrophic microbes across different time scales. Focusing on metabolic interactions, we examine how three strategies: public metabolizing, private metabolizing, and cheating, shape population behaviour. The framework integrates generalized Lotka-Volterra dynamics with evolutionary game theory to capture the effects of resource exchange, particularly glucose made available by public metabolizers and sucrose as a shared substrate driving population growth. Game-theoretic payoffs encode ecological costs and benefits, enabling analysis of frequency-dependent interactions among strategies. To capture evolutionary realism, we implement laboratory-inspired simulations in which strategies can switch between generations, mimicking mutation or phenotypic plasticity in microbial populations. These eco-evolutionary dynamics reveal conditions under which all three strategies coexist at interior equilibria and show how variation in growth advantages and, illustratively, phenotype-switching perturbations produce evolutionary shifts. Numerical analysis identifies ecological thresholds and fitness asymmetries that determine system robustness, long-term coexistence, and the persistence of a synthetic, cross-kingdom system linked by nutrient exchange. Together, these insights provide general principles for microbial coexistence and offer design guidelines for ecosystem engineering, biotechnological applications, and the construction of stable synthetic communities under ecological and evolutionary constraints.

ecology↗

bioRxiv2021

Impaired photoprotection in Phaeodactylum tricornutum KEA3 mutants reveals the proton regulatory circuit of diatoms light acclimation.

Diatoms are amongst the most successful clades of oceanic phytoplankton, significantly contributing to photosynthesis on Earth. Their ecological success likely stems from their ability to acclimate to changing environmental conditions, including e.g. variable light intensity. Diatoms are outstanding at dissipating light energy exceeding the maximum photosynthetic electron transfer (PET) capacity of via Non Photochemical Quenching (NPQ). While the molecular effectors of this process, as well as the role of the Proton Motive Force (PMF) in its regulation are known, the putative regulators of the PET/PMF relationship in diatoms remain unidentified. Here, we demonstrate that the H+/K+ antiporter KEA3 is the main regulator of the coupling between PMF and PET in the model diatom Phaeodactylum tricornutum. By controlling the PMF, it modulates NPQ responses at the onset of illumination, during transients and in steady state conditions. Under intermittent light KEA3 absence results in reduced fitness. Using a parsimonious model including only two components, KEA3 and the diadinoxanthin de-epoxidase, we can describe most of the feedback loops observed between PET and NPQ. This two-components regulatory system allows for efficient responses to fast (minutes) or slow (e.g. diel) changes in light environment, thanks to the presence of a regulatory Ca2+-binding domain in KEA3 that controls its activity. This circuit is likely finely tuned by the NPQ effector proteins LHCX, providing diatoms with the required flexibility to thrive in different ocean provinces. One sentence summaryThe author(s) responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plcell/pages/General-Instructions) is Giovanni Finazzi.

plant biology↗

bioRxiv2021

Chlorophyll fluorescence: How the quality of information about PAM instrument parameters may affect our research

Chlorophyll a fluorescence is a powerful indicator of photosynthetic energy conversion in plants and photosynthetic microorganisms. One of the most widely used measurement techniques is Pulse Amplitude Modulation (PAM) fluorometry. Unfortunately, parameter settings of PAM instruments are often not completely described in scientific articles although their variations, however small these may seem, can influence measurements. We show the effects of parameter settings on PAM measurements. We first simulated fluorescence signals using a previously published computational model of photosynthesis. Then, we validated our findings experimentally. Our analysis demonstrates how the kinetics of non-photochemical quenching (NPQ) induction and relaxation are affected by different settings of PAM instrument parameters. Neglecting these parameters may mislead data interpretation and derived hypotheses, hamper independent validation of the results, and cause problems for mathematical formulation of underlying processes. Given the uncertainties inflicted by this neglect, we urge PAM users to provide detailed documentation of measurement protocols. Moreover, to ensure accessibility to the required information, we advocate minimum information standards that can serve both experimental and computational biologists in our efforts to advance system-wide understanding of biological processes. Such specification will enable launching a standardized database for plant and data science communities. HighlightPAM fluorometry measurement is sensitive to instrument settings and protocols. Yet, protocols are published incompletely. We urge to reach an agreement on minimal protocol information of PAM experiments to be shared publicly.

plant biology↗

bioRxiv2018

Balancing energy supply during photosynthesis - a theoretical perspective

The photosynthetic electron transport chain (PETC) provides energy and redox equivalents for carbon fixation by the Calvin-Benson-Bassham (CBB) cycle. Both of these processes have been thoroughly investigated and the underlying molecular mechanisms are well known. However, it is far from understood by which mechanisms it is ensured that energy and redox supply by photosynthesis matches the demand of the downstream processes. Here, we deliver a theoretical analysis to quantitatively study the supply-demand regulation in photosynthesis. For this, we connect two previously developed models, one describing the PETC, originally developed to study non-photochemical quenching, and one providing a dynamic description of the photosynthetic carbon fixation in C3 plants, the CBB Cycle. The merged model explains how a tight regulation of supply and demand reactions leads to efficient carbon fixation. The model further illustrates that a stand-by mode is necessary in the dark to ensure that the carbon fixation cycle can be restarted after dark-light transitions, and it supports hypotheses, which reactions are responsible to generate such mode in vivo.

systems biology↗

bioRxiv2018

Building mathematical models of biological systems with modelbase, a Python package for semi-automatic ODE assembly and construction of isotope-specific models

The modelbase package is a free expandable Python package for building and analysing dynamic mathematical models of biological systems. Originally it was designed for the simulation of metabolic systems, but it can be used for virtually any deterministic chemical processes. modelbase provides easy construction methods to define reactions and their rates. Based on the rates and stoichiometries, the system of differential equations is assembled automatically. modelbase minimises the constraints imposed on the user, allowing for easy and dynamic access to all variables, including derived ones, in a convenient manner. A simple incorporation of algebraic equations is, for example, convenient to study systems with rapid equilibrium or quasi steady-state approximations. Moreover, modelbase provides construction methods that automatically build all isotope-specific versions of a particular reaction, making it a convenient tool to analyse non-steady state isotope-labelling experiments.

systems biology↗