2022Activity reportProject-TeamBIOCORE

7.1.1 In@lgae

• Name:
  Numerical simulator of microalgae based processes
• Keywords:
  Simulation, Microalgae system, Productivity
• Functional Description:
  In@lgae simulates the productivity of a microalgae production system, taking into account both the process type and its location and time of the year. The process is mainly defined by its thermal dynamics and by its associated hydrodynamics. For a given microalgal strain, a set of biological parameters describe the response to nitrogen limitation, temperature and light. As a result, the biomass production, CO2 and nitrogen fluxes, lipid and sugar accumulation are predicted.
• Release Contributions:
  The In@lgae platform has been optimised to make it faster. Some of the key models have been rewritten in C++ to allow a faster computation. Models have been improved to include, in the growth rate computation, the composition of the light spectrum. The graphical user interface has been enhanced and several sets of parameters describing different microalgal species have been stored.
• Contact:
  Olivier Bernard
• Participants:
  Étienne Delclaux, Francis Mairet, Olivier Bernard, Quentin Béchet

7.1.2 Odin

• Name:
  Platform for advanced monitoring, control and optimisation of bioprocesses
• Keywords:
  Bioinformatics, Biotechnology, Monitoring, Automatic control
• Scientific Description:

  ODIN is a distributed application, whose graphical interfaces can be launched remotely through the Internet. The application, developed in Erlang, is architected around an MQTT broker. It is robust and tolerant to hardware failures in order to avoid that a wrong manipulation can have harmful consequences on the biotechnological process.

  Thus, the implementation of a new algorithm is done by a plugin written in Python language. Modifying one of these algorithms does not require recompiling the code.

• Functional Description:
  This application proposes a framework for on-line supervision of bioreactors. It gathers the data sampled from different on-line and off-line sensors. ODIN is a distributed platform, enabling remote monitoring as well as remote data acquisition.More originally, it enables researchers and industrials to easily develop and deploy advanced control algorithms, optimisation strategies, together with estimates of state variables or process state. It also contains a process simulator which can be harnessed for experimentation and training purposes. It is modular in order to adapt to any plant and to run most of the algorithms, and it can handle the high level of uncertainties that characterises the biological processes. The architecture is based on Erlang, and communication between modules through a MQTT Broker with Python for running the algorithms. ODIN is developed in collaboration with the INRIA Ibis research team.
• URL:
  https://­team.­inria.­fr/­biocore/­software/­odin/
• Contact:
  Olivier Bernard
• Participants:
  Olivier Bernard, Nicolas Niclausse, Eugenio Cinquemani, Tamas Muszbek, Thibaud Kloczko, Nicolas Chleq, Jean-Luc Szpyrka, Pierre Fernique, Julia Elizabeth Luna, Come Le Breton, Jonathan Levy, Amine Lahouel, Tristan Cabel, François Caddet, Erwan Demairy, Riham Nehmeh, Marc Vesin, Carlos Zubiaga Pena

8.1.1 Mathematical study of ecological models

Participants: Frédéric Grognard, Ludovic Mailleret, Suzanne Touzeau, Clotilde Djuikem, Yves Fotso Fotso, Marine Courtois.

Semi-discrete models. Semi-discrete models have shown their relevance in the modeling of biological phenomena whose nature presents abrupt changes over the course of their evolution 86. We used such models and analyzed their properties in several practical situations, some of them requiring such a modeling to describe external perturbations of natural systems such as harvest, and others to take seasonality into account. We developed these models in the context of augmentative introduction of species for biological control 1 or the Sterile Insect Technique 62, seasonality in the dynamics of coffee leaf rust 79, 78, of banana and plantain burrowing nematodes 97, and of coffee berry borers 50, 55

Models in plant epidemiology. We developed and analysed dynamical models describing plant-parasite interactions, in order to better understand, predict and control the evolution of damages in crops. We considered several pathosystems, further described in Section 8.7, describing and controlling the impact on plants of fungi 76, 77 nematodes 97, and pests 33, 50.

8.1.2 Estimation and control

Participants: Frédéric Grognard, Ludovic Mailleret, Suzanne Touzeau, Yves Fotso Fotso, Clotilde Djuikem.

Optimal control and optimisation. We developed several approaches to control the evolution of crop pests. We solved optimal control problems to limit the damages due to coffee berry borers 45 and Coffee Leaf Rust 79 using the BOCOP software, which is developed by Inria team COMMANDS.

8.2.1 Cell metabolism

Genetic variability in fruit sugar metabolism. Genetic diversity in sugar metabolism has been studied in peach fruit, taking advantage of the simplified model developed by Kanso et al.  83. Thanks to the reduced parameter space and its lower complexity, the model has been calibrated over a population of 106 peach genotypes, using different calibration strategies. Results have been used to identify QTLs, providing information on the genetic control of sugar metabolism in peach fruit. Two articles are currently under preparation on this topic.

8.2.2 Resource allocation.

Modeling energy constraints in microbial growth. In the framework of the Maximic project (collab. H. de Jong, MICROCOSME team, and T. Gedeon, Montana State University) and as a follow up of our previous work 80, we developed a coarse-grained model of coupled energy and mass fluxes in microorganisms, based on minimal assumptions, and calibration of the model with data for E. coli56. We used the model to explore the variability of rate-yield phenotypes obtained by change in proteome allocation strategy. We found that the predicted rates and yields in different growth conditions correspond very well with the variability of rate-yield phenotypes observed across different E. coli wild type and mutant strains. Moreover, as reported in experimental data, the model predicts the occurrence of a growth rate-yield trade-off, as a generic property of the dependence of growth rate and growth yield on the distribution of resources over the production of ribosomes, enzymes in central metabolism and nutrient uptake, and enzymes in energy metabolism.

Optimal allocation of resources in bacteria. We studied by techniques of optimal control the optimal allocation between metabolism and gene expression during growth of bacteria, in collaboration with Inria MICROCOSME and MCTAO project-teams. We developed different versions of the problem, and considered problems where the aim is to optimize the production of a product in a batch or fedbatch bioreactor 47, 43, 59, 60, (ANR project Maximic, PhD thesis of Agustin Yabo).

Turnpike phenomena in biological optimal control problems: We addressed the problem of maximization of metabolite production in bacterial cells, formulated as an optimal control problem (in collaboration with McTAO). We proved the existence of a turnpike feature that characterizes the optimal solutions (22) and we extended the earlier theoretical results on turnpike properties derived in the context of the selection of microbial species (75, 74).

8.2.3 Bacterial communities

A synthetic community of bacteria. In the framework of ANR project Ctrl-AB, we consider a synthetic algal-bacterial consortium. The co-culture of E. coli with Chlorella could lead to higher biomass and lipid productivity. We develop a model, then study its dynamical behavior and eventually it is used to optimize some productivity criteria 44.

In the framework of IPL Cosy (E. Cinquemani), we study the coexistence of two strains of bacteria E. Coli in a bioreactor. The strains have been modified synthetically. The aim is to obtain a better productivity in the consortium than in a single strain, by control methods  90. We obtain optimisation results for the optimal production or yield 58.

In collaboration with L. Sacchelli (MCTAO), we studied during the internship of T. Rolin a problem of observability and estimation in a batch bioreactor.

8.2.4 Synchronization and control using hybrid models

Participants: Nicolas Augier, Madalena Chaves, Jean-Luc Gouzé, Agustín Yabo.

Qualitative control for synchronization of piecewise linear systems. We investigated the emergent dynamics in a network of $N$ coupled cells, each expressing a similar bistable switch  12. The bistable switch is modeled as a piecewise affine system and the cells are diffusively coupled. We show that both the coupling topology and the strength of the diffusion parameter may introduce new steady state patterns in the network. We study the synchronization properties of the coupled network and, using a control set of only three possible values ($u_{min}$, $u_{max}$, or 1), we propose different control strategies which stabilize the system into a chosen synchronization pattern, both in the weak and strong coupling regimes.

Weak synchronization and convergence in coupled genetic regulatory networks. We consider a general model of genetic networks and examine two forms of interconnection, either homogeneous or heterogeneous coupling, corresponding to coupling functions that are either equal or different from those governing the individual dynamics. In the case of individual subsystems having unique but different steady states, we prove that the homogeneous coupled system has a unique globally asymptotically stable steady state. Moreover, in the case of large coupling strength, we show that under suitable assumptions the network achieves weak synchronization in the sense that the individual steady states become arbitrarily close 13. In the heterogeneous case, we prove a similar weak synchronization result in the case of large coupling strength. We apply the results to the synchronization of damped oscillators and to the control of multistable systems.

Time-optimal control of piecewise affine bistable systems. In 14 we give a geometric characterization of the time-optimal trajectories for a piecewise affine bistable switch, based on an adaptation of the Hybrid Pontryagin’s Maximum Principle. Such hybrid models play a major role in systems biology, as they can expressively account for the behaviors of simple gene-regulatory networks

8.3.1 Analysis and coupling of circadian oscillators.

Cycle dynamics and synchronization in a coupled network mammalian circadian clocks. The intercellular interactions between peripheral circadian clocks, located in tissues and organs other than the suprachiasmatic nuclei of the hypothalamus, are still very poorly understood. To investigate this question, we performed a theoretical and computational study of the coupling between two or more clocks, using a reduced model of the mammalian circadian clock previously developed in 66. Based on a piecewise linearization of the dynamics of the mutual CLOCK:BMAL1 / PER:CRY inactivation term, we proposed a segmentation of the circadian cycle into six stages, to help analyse different types of synchronization between two clocks, including single stage duration, total period, and maximal amplitudes. Our model reproduces some recent experimental results on the effects of different regimes of fasting/feeding alternance in liver circadian clocks of mice 20. This method helps to further characterize the synchronization steps between two clocks of distinct (but close) periods 61. This work is in collaboration with F. Delaunay (ANR InSync), and is part of Odile Burckard PhD thesis.

8.3.2 Modeling the apoptotic signaling pathway

TRAIL-induced apoptosis signaling models and kinetic determinants of cell fate decision. To analyze the considerable amount of data from fate-seq 19,  91, a new workflow that analyses single-cell signaling, and uses them for an early prediction of cell fate in new experiments, we proposed an ODE model of the molecular pathways involved in cell death triggered by TRAIL calibrated on single-cell time-trajectories of a FRET reporter measuring apoptosis signaling dynamics in clonal HeLa cells  95. With this model, we constructed a timeline for the different steps in the regulation of apoptosis and located an initial cell fate decision just after TRAIL binding 46. Furthermore, we identified three specific parameter combinations that can distinguish between drug resistant or sensitive phenotypes 65. These parameters could be used to control or predict cell drug-response in the future. This work is part of the PhD thesis of Marielle Péré, in collaboration with J. Roux and his lab.

Integrating Machine Learning methods in single-cell experimental workflow. To more efficiently analyse single-cell data in response to anti-cancer drugs, we developed a pipeline called Fate-seq to profile drug-tolerant persisters, based on predictions of their drug response. To automatize and increase the prediction throughput, we combined a mathematical framework, composed of machine-learning classification models augmented by an ODE model. The first step is to calibrate an ODE model of the extrinsic apoptosis on time trajectories of hundreds of treated clonal HeLa cells, which leads to mechanistic features with predictive values for cell decision. The second step is to combine these with machine-learning classification models to determine the drug response of each cell before it commits to an irreversible decision. Our mechanistic-informed approach, combining our ODE system with machine learning classifiers, outperformed classic machine learning approaches and enabled the accurate cell response prediction of otherwise unpredictable cells 52. This work is part of the PhD thesis of Marielle Péré, in collaboration with Diego Oyarzun (University of Edinburgh). M. Péré presented this work as at several meetings 51 and as a poster both at the Signalife meeting 63 (November 2022) and the Sophia IA Summit 64 (November 2022). She was awarded a poster prize at both conferences.

Fields of application

8.4.1 Modeling microalgae production

Participants: Olivier Bernard, Antoine Sciandra, Walid Djema, Francesca Casagli, Bruno Assis Pessi, Ignacio Fierro, Ali Gharib, Liudi Lu, Jean-Philippe Steyer, Laetitia Giraldi [CALISTO].

Experimental developments

Running experiments in controlled dynamical environments. The experimental Phytopulse platform made of continuous photobioreactors driven by a set of automaton controlled by the ODIN+ software is a powerful and unique tool which gave rise to a quantity of very original experiments. This platform improved knowledge of several biological processes such as lipid accumulation or pigment dynamics under light fluctuation, nitrogen or temperature stress... 15, 34.

This experimental platform was used to control the long term stress applied to a population of microalgae using optimal control strategies 28. This Darwinian selection procedure generated several new strains more transparent after several months in the so called selectiostats 34 leading to an enhanced productivity at high density.

Experimental work was also carried out in collaboration with the Inalve startup with microalgal biofilm to determine the impact of light and dark sequences on cell growth and photoacclimation. The architecture of the biofilms was also observed for different species with confocal microscopic techniques 40, 30.

These works have been carried out in collaboration with A. Talec and E. Pruvost (CNRS/Sorbonne Université -Oceanographic Laboratory of Villefranche-sur-Mer LOV).

Metabolism of carbon storage and lipid production. A metabolic model has been set up and validated for the microalgae Chlorella vulgaris, on the basis of the DRUM framework , in order to simulate autotophic, heterotropic and mixotrophic growth, and to determine how to reduce substrate inhibition. The model was extended to other substrates such as glucose or glycerol. After a calibration phase, the model was successfully challenged with data from 122 experiments collected from scientific literature in autotrophic, heterotrophic and mixotrophic conditions 38.

As part of B.A. Pessi PhD thesis, this metabolic modeling framework is extended to describe a co-culture of bacteria and microalgae. First, by modeling a thiamine auxotroph E. coli to maximize the production of lactate. Then, we extend the previous developed metabolic model to describe a co-culture of Chlorella with bacteria E. coli overproducing the vitamin biotin. We represent the influence of biotin concentration in the accumulation of lipids. The model results show that a biotin overproducer E. coli could support the needs of vitamin by Chlorella and favor lipid accumulation.

The mechanisms to regulate the photosynthesis in conditions of nitrogen limitation were represented in a metabolic model, using the DRUM framework 15. Different mechanisms were hypothesized. On the basis of this model, an alternative interpretation of the Droop model was proposed, which can be understood as an accumulation of carbon during nitrogen stress, rather than the common belief of a nitrogen pool driving growth.

Modeling the coupling between photosynthesis and hydrodynamics. We consider a coupled physical-biological model describing growth of microalgae in a raceway pond cultivation process, accounting for hydrodynamics. Our approach combines a biological model (based on the Han model) and shallow water dynamics equations that model the fluid into the raceway pond. We developed an optimization procedure dealing with the topography to maximize the biomass production over one lap or multiple laps with a paddle wheel. The results show that a flat topography is optimal in a periodic regime. We then studied the influence of mixing, assuming that a mixing device can redistribute the algae so that they can have access to light 17. A strategy to optimally mix the algae was derived. It was finally combined with the a non flat topography 67.

Modeling photosynthetic biofilms. Several models have been developed to represent the growth of microalgae within a biofilm. A first structured physiological model 40 uses mixture theory to represent the microalgae growth, based on the consideration of intracellular reserves triggering the processes of growth, respiration and excretion. We consider separately the intracellular storage carbon (lipids and carbohydrates) and the functional part of microalgae. The model corroborated observations realised at the LGPM (CentraleSupelec) 30. Another approach accounts for the dynamics of the light harvesting systems when cells are submitted to rapid successions of light and dark phases. A simpler model was developed and used to identify the optimal working mode of a process based on photosynthetic biofilm growing on a conveyor belt. The model was used to identify the worldwide potential of microalgal biofilms under different climates. This study was extended considering the impact if the culture has to be heat in winter.

We studied the Han model for different alternation of high and low light intensities, with various durations. We showed that there are specific light levels than can enhance the biofilm growth 31. The experimental validation of this model, together with the extrapolation of productivities at larger scale is the topic of the PhD thesis of Yan GAO at CentraleSupelec (directed by F. Lopes and O. Bernard).

Modeling microalgae production processes. A model representing the dynamics of microalgae when growing in suboptimal conditions of light, nitrogen and phosphorus was developed. It consists in an extension of the Droop model accounting for the two quota of nitrogen and phosphorus. The model also represents the pigment acclimation to various light intensities. We have studied in 87 the response of a Droop model forced by periodic light or temperature signals. We transformed the model into a planar periodic system generating a monotone dynamical system. Combined with results on periodic Kolmogorov equations, the global dynamics of the system can be described.

Modeling thermal adaptation in microalgae. We studied a broad range of species and their response to temperature. It turns out that the optimal temperature, the minimal and the optimal temperature for growth are strongly correlated. A relationship between these cardinal temperatures and key parameters from the environment (sea surface temperature, solar flux, ...) was identified.

Experiments have been carried out in collaboration with A.-C. Baudoux (Biological Station of Roscoff) in order to study growth of various species of the microalgae genus Micromonas at different temperatures. After calibration of our models, we have shown that the pattern of temperature response is strongly related to the site where cells were isolated. We derived a relationship to extrapolate the growth response from isolation location. With this approach, we proved that the oceanwide diversity of Micromonas species is very similar to the oceanwide diversity of the phytoplankton 71. We have used Adaptive Dynamics theory to understand how temperature drives evolution in microalgae. We could then predict the evolution of this biodiversity in a warming ocean and show that phytoplankton must be able to adapt within 1000 generations to avoid a drastic reduction in biodiversity 71.

Modeling viral infection in microalgae. In collaboration with A.-C. Baudoux (Biological Station of Roscoff) a model was developed to account for the infection of a Micromonas population, with population of susceptible, infected and also free viruses. The model turned out to accurately reproduce the infection experiments at various temperatures, and the reduction of virus production above a certain temperature  72. The model was then extrapolated to the whole ocean to better understand how the warming will impact the mortality due to viruses.

8.4.2 Control and Optimization of microalgae production

Optimization of the microalgae production through optical depth. Dynamic light regimes strongly impact microalgal photosynthesis efficiency. Finding the optimal way to supply light is then a tricky problem, especially when the growth rate is inhibited by overexposition to light and, at the same time, there is a lack of light in the deepest part of the culture. We used the Han model to study the theoretical microalgal growth rate by applying periodically two different light intensities 31. For a large light period, we demonstrate that the average photosynthetic rate can be improved.

Productivity optimization turns out to be highly dependent on how light is distributed along the reactor, and is therefore related to the extinction rate and the background turbidity. In 16, we propose a theoretical analysis of this problem, by introducing the concept of optical depth productivity for systems where background turbidity must be accounted for. A global optimum maximizing productivity is proposed, extending the concept of the compensation condition, consisting in compensating the algal growth rate at the bottom of the reactor by the respiration. This condition can drive the optimization of the surface biomass productivity depending on the minimum reachable depth. We develop a nonlinear controller and prove the global asymptotic stability of the biomass concentration towards the desired optimal value. This is the subject of the PhD thesis of Ignacio Fierro in the framework of the ITN Digitalgaesation.

Optimization of the microalgae production through temperature control. Temperature plays a key role in the microalgae dynamics. We proposed a heat transfer model coupled with biological model to simulate the temperature evolution, depending on the meteorology, and its impact on the algal productivity. We propose a general framework to simulate these multiphysics systems, keeping a balanced degree of complexity between the biological and the physical models 26. This coupled model was validated on long term series in various reactor configurations 25, 24. We also considered the influence of a greenhouse on the medium temperature and subsequently on algal productivity 39 simulating different climatic conditions and the species for which the use of a greenhouse is beneficial.

A model predictive control algorithm was run based on simple microalgae models coupled with physical models where culture depth influences thermal inertia. Optimal operation in continuous mode for outdoor cultivation was determined when allowing variable culture depth. Assuming known weather forecasts considerably improved the control efficiency. This is the subject of the PhD thesis of Ali Gharib in the framework of the ITN Digitalgaesation.

Interactions between species. We have proposed an optimal control strategy to select in minimal time the microalgal strain with the lowest pigment content 73. The control takes benefit from photoinhibition to compute light stresses penalizing the strains with a higher pigment content and finally selecting microalgae with lower chlorophyll content. Another optimal control problem was considered for selecting a strain of interest within two species competing for the same substrate, when dynamics is represented by a Droop model. In both cases, the optimal control derived from the Pontryagin maximum principle also exhibits a turnpike behavior 75. This is a collaboration with team MCTAO. Strategies to improve algae productivity were derived. Strategies to optimally separate algae species were derived: design of an optimization procedure to select the most productive algae strains (28).

We assessed the effect of predation by zooplancton and studied the role of the dilution rate in the control of zooplankton populations and in the optimization of biomass productivity. We showed that in the long-term operation the optimal constant dilution rate must ensure the eradication of the zooplankton population. In the case of time-varying dilution rate, we numerically solve an optimal control problem over a finite interval of time. We find that the optimal solution approaches the solution for the static problem most of the time, except when zooplankton actively avoid the pond outflow 35, 88.

8.4.3 Modeling mitochondrial inheritance patterns

Most eukaryotes inherit their mitochondria from only one of their parents. When there are different sexes, it is almost always the maternal mitochondria that are transmitted. Indeed, maternal uniparental inheritance has been reported for the brown alga Ectocarpus but we show in this study 92 that different strains of Ectocarpus can exhibit different patterns of inheritance: Ectocarpus siliculosus strains showed maternal uniparental inheritance, as expected, but crosses using different Ectocarpus species (7 strains) exhibited either paternal uniparental inheritance or an unusual pattern of transmission where progeny inherited either maternal or paternal mitochondria, but not both. A possible correlation between the pattern of mitochondrial inheritance and male gamete parthenogenesis was investigated. Moreover, in contrast to observations in the green lineage, we did not detect any change in the pattern of mitochondrial inheritance in mutant strains affected in life cycle progression. Finally, an analysis of field-isolated strains provided evidence of mitochondrial genome recombination in both Ectocarpus species.

8.5.1 Control and optimization of bioprocesses for depollution

Participants: Olivier Bernard, Carlos Martinez von Dossow, Jean-Luc Gouzé, Francesca Casagli.

We consider artificial ecosystems including microalgae, cyanobacteria and bacteria in interaction. The objective is to more efficiently remove inorganic nitrogen and phosphorus from wastewater, while producing a microalgal biomass which can be used for biofuel or bioplastic production. Models have been developed including predators grazing the microalgae.

Algae-bacteria processes for treating wastewater are becoming a very attractive technology 36. We designed and calibrated a model, that was validated with more than one year of data 69. The model analysis revealed that despite pH regulation, a strong limitation for inorganic carbon was found to hinder the process efficiency and to generate conditions that are favorable for N${}_2$O emission. A control strategy regulating alkalinity turns out to be necessary to enhance the performance and avoid dammageable emissions 68. We developed a general framework for simulating biotechnological processes affected by meteorology, integrating, on top of the core biological model, a heat transfer model and a chemical sub-model for computing the speciation of all the dissociated chemical molecules. 26.The developed framework is a powerful tool for advanced control and optimization of environmental processes, which can guide the scaling-up and management of the most innovative bioprocesses. We explored and quantified, through a modeling study, the advantage of adding a solid/liquid separation system to uncouple Hydraulic Retention Time (HRT) and Solid Retention Time (SRT), in order to maximize the algal productivity and the nitrogen recycling 23. The temperature response for two different process configurations was also explored and compared 25, 24.

A work was started to simplify these models and enhance their calibration by considering artificial neural networks, which are integrated in a way that the full model respects some key constrains (positivity, boundness, ...) 96.

8.5.2 Coupling microalgae to anaerobic digestion

Participants: Olivier Bernard, Antoine Sciandra, Jean-Philippe Steyer, Carlos Martinez von Dossow, Francesca Casagli.

The coupling between a microalgal-bacteria high rate pond and an anaerobic digester is a promising alternative for sustainable energy production and wastewater treatment by transforming carbon dioxide into methane using light energy 36. The challenge when dealing with anaerobic digestion effluent for feeding the algae-bacteria process is the potential low alkalinity which can induce a competition between nitriying bacteria and algae 23. We showed that this competition for inorganic carbon can create conditions favorable for N${}_2$O emission. We studied the metabolism of Chlorella vulgaris growing on fermentation products and developed a metabolic model 38 that was validated with a large number of experiments covering various working modes (autotrophic, heterotrophic, mixotrophic).

8.7.1 Controlling plant arthropod pests

Participants: Frédéric Grognard, Ludovic Mailleret, Suzanne Touzeau, Yves Fotso Fotso, Clotilde Djuikem, Marine Courtois.

The question of how many and how frequently natural enemies should be introduced into crops to most efficiently fight a pest species is an important issue of integrated pest management. The topic of optimization of natural enemies introductions has been investigated for several years 85, and extends more generally to pulse perturbations in population dynamics. Importantly, we published a book chapter reviewing augmentative biological control methods 53. Our research in this context has expanded to the modeling and optimization of introduction strategies in the context of the Sterile Insect Technique (SIT). In the framework of the Ecophyto project 'CeraTIS Corse' we have developed a model for the dynamics of the mediterranean fruit fly Ceratitis capitata, with continuous introductions of sterile males. We have shown that residual fertility among the 'sterile' males could destabilize the pest-free, and gave a condition to be satisfied to ensure that the pest-free equilibrium is the only equilibrium, and that it is stable. However practical efficacy of SIT can be ensured even beyond that threshold 62. Initial developments for ANR project Suzukiis:me were obtained in the internship of Crésus Kounoudji, with the development of a first model of the dynamics of the fruit fly Drosophila suzukii with impulsive introductions.

Spatial population dynamics of biological control agents. We have been involved for several years in a mixed modeling-experimental approach to explore the spatio-temporal dynamics of populations, with special interest to micro-wasp parasitoids 93, 82. In particular, we studied the influence of Allee effects and density dependence in dispersal on range expansion, extending the concept of range pinning in Ecology and pointing out its interaction with demographic stochasticity 94. These works have been performed in collaboration with Elodie Vercken (ISA) and partly with Vincent Calcagno (ISA), and principally published through the Peer Community In (PCI) recommandation process.

Concurrently, we are exploring the correlation between biological control agents movement characteristics at different scales, from laboratory experimental characterization to field dispersal. This research is performed on various species of parasitoids belonging to the genus Trichogramma, and is the main topic of Melina Cointe PhD thesis that started in autumn 2020 (director Vincent Calcagno, ISA). In this context, interesting results have been published on the photo- an geo-tactic preferences of egg-parasitoids in the genus Trichogramma21. This research has been performed in collaboration with Vincent Calcagno (ISA).

Modeling and control of coffee berry borers. We developed a model describing the coffee berry borer dynamics based on the insect life-cycle and the berry availability during a single cropping season. A control was introduced, based on a biopesticide (entomopathogenic fungus such as Beauveria bassiana) that is sprayed and persist on the berries. An optimal control problem was solved previously 55 (see Section 8.1.2). A PDE model taking the age of the berries and the preference of coffee berry borers for more mature berries was developed, and we derives an explicit formula of the basic reproduction number, R0, using the next generation approach and the biological interpretation of this threshold in a specific case 33. Optimal control was also used on that model for the deployment of biological control agents. A semi-discrete multi-seasonal model was also developed, integrating the difference between the dynamics during the rainy and dry seasons, as well as harvesting and plantation cleansing as discrete events; a condition was obtained for the stability of the pest-free periodic solution, requiring sufficient cleansing to ensure that not too many borers survive from one season to the next 50. This research pertains to Yves Fotso Fotso's PhD thesis through the EPITAG associate team 55.

8.7.2 Controlling plant pathogens

Participants: Frédéric Grognard, Ludovic Mailleret, Suzanne Touzeau, Clotilde Djuikem, Pierre Bernhard.

Sustainable management of plant resistance. We studied other plant protection methods dedicated to fight plant pathogens. One such method is the introduction of plant cultivars that are resistant to one pathogen. This often leads to the appearance of virulent pathogen strains that are capable of infecting the resistant plants.

We built a generic spatio-temporal epidemiological model representing fungal diseases on annual field crops in a multi-pathogen context. This work benefits from data collected in INRAE projects COCODIV and DYNAMO. We plan to include the modeling developments in the SiDRes tool.

An epidemiological model of gene-for-gene interaction has been designed, considering increased defense to pathogen infections following previous exposure to a pathogen or an elicitor, namely priming. Priming provides a sort of immunity to virulent pathogens for resistant plants having undergone an infection attempt by an avirulent pathogen. After an initial result considering mixtures between susceptible and resistant hosts, mixtures of different resistant strains and the possible presence of supervirulent pathogens were studied; we have shown that, at equilibrium, pathogens that are present all have the same virulence complexity (number of resistant-breaking alleles) 70, 48. This was done in collaboration with Frédéric Hamelin (Agrocampus Ouest) in the framework of Pauline Clin's thesis that she defended in December 2022.

We also participated in an opinion paper advocating that the theoretical framework of population genetics could bridge the gap existing between evolution/epidemiology approaches and molecular approaches to the durability of resistance problem. This paper is the basis of an ANR project proposition that is under review 42.

Other methods for the control of plant pathogens Coffee leaf rust (CLR) is a disease caused by a basidiomycete fungus, Hemileia vastatrix, that has a major impact on coffee production around the world. We produced a stage structured model of the disease development representing young and mature leaves, with different health status (susceptible, latent, infectious, dry), berries and spores. We deduced from its analysis that very different forms of bifurcation could occur, with the possibility of having endemic equilibrium despite a reproduction number R0 smaller than one and even destruction of the plantation for large R0 49. We also studied a multi-seasonal impulsive version of a simplified form of this model, with multiple biocontrol agent releases per year.

8.7.3 Plant-nematode interactions

Participants: Valentina Baldazzi, Frédéric Grognard, Ludovic Mailleret, Suzanne Touzeau, Joseph Penlap.

Based on our previous work, an ecophysiological model of plant growth, including both the vegetative and the reproductive phases, has been developed and coupled to a model of nematode population dynamics. Briefly, the plant is divided into shoots, source of carbon for the plant, and roots, source of water, that exchange and employ resources for growth. During the reproductive phase, fruit set marks the addition of a new carbon sink for the plant. Nematodes are explicitly considered as feeding on plant resources, so that any change in the plant physiological status or plant composition will in turn affect pest growth and multiplication, and vice versa. The apparition of fruits, in particular, can substantially modify the allocation pattern of the plant among its compartments, with important consequences on plant susceptibility to pest attack. The model will be used to explore the dynamical behavior of the system and to gain insight into the relative role of plant development and phenotypic traits (including physiological and architectural features), pest development and environmental factors in the progression of the infection. The model is currently under calibration for two plant species, using experimental data collected in the framework of a previous project (INRAE ArchiNem project, 2020-2021). This work is part of the PhD thesis of Joseph Penlap Tamagoua (Inria-INRAE funding 2022-2025). A publication is currently in preparation focusing on the experimental results.

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an Inria International Program

10.2.1 Visits of international scientists

10.2.2 Visits to international teams

10.3.1 H2020 projects

10.4.1 National programmes

• ANR PhotoBioFilm Explorer: The first objective of the PhotoBioFilm project (2021-2024) is to explore the activity of the molecules produced within a microalgae biofilm, and explaining its resistance to contamination. The second objective is to identify, characterize and produce novel biocompounds with benefits for human or animal health. The target is antibiotics, but other activities will be tested, especially antiviral activities. Biocore will be in charge of the biofilm modeling and the optimization of the production of the molecules of interests. Project coordinated by O. Bernard.
• ANR Ctrl-AB: The objectives of the Ctrl-AB project (2021-2024) are (i) to develop new control methods for the optimization of the productivity of a microbial community, and (ii) to demonstrate the effectiveness of these methods on a synthetic algal-bacterial consortium. Interestingly, co-culturing of E. coli with Chlorella leads to higher biomass and lipid productivity. Improved growth of Chlorella occurs despite competition of E. coli for the same substrates. On top of its ability to produce molecules like vitamins, which are necessary for algal growth, the bacteria also produce carbon dioxide (CO${}_2$), which is the substrate of the photosynthesis of the algae. The algae can produce oxygen (O${}_2$) fueling bacterial growth, thus giving rise to a mutualistic pattern of interactions giving rise to several challenges for modeling and controlling this artificial ecosystem. Project coordinated by J.-L. Gouzé.
• ANR Maximic: The goal of the project (2017-2022) is to design and implement control strategies in a bacterium for producing at maximal rate a high value product. It is coordinated by H. de Jong (IBIS Grenoble), and involves members of Biocore and McTao.
• ANR InSync: This project (2022-2027) aims to decipher intercellular synchronization mechanisms responsible for robust rhythms in peripheral clocks. Focusing on hepatocytes, and using both 2D cultures and 3D spheroids, we will study cell communication patterns and cell clock synchronization. Project coordinated by M. Chaves, in collaboration with F. Delaunay (Institut Biologie de Valrose, UCA) and L.Tournier (MaIAGE, INRAE Jouy-en-Josas).
• ANR SuzuKIISS:ME "Gérer Drosophila SuzuKII grâce aux Insectes Super Stériles : Maturation et Efficacité" (2022-2025). This project covers the ground from the development of the operational capacity and release strategies to deploy Sterile Insect Techniques (SIT), to the socio-economic impact of SIT on the control of the fruit fly Drosophila Suzukii.
• Plan Cancer, Imodrez: The objective of this project (2018-2022) is to understand cancer drug response heterogeneity using tumor single-cell dynamics and developing mathematical models and computational approaches. A project coordinated by J. Roux (IRCAN).
• ITMO Cancer Aviesan, Cellema: The objective of this project (2022-2025) is to determine the molecular factors that regulate tumor cell response dynamics to immune cell cytotoxicity and contribute to the development of diagnosis tools for the rational design of cancer combination therapies. We will use single-cell response data to develop mathematical models and combine them with machine learning algorithms to enhance prediction of same-cell responses. Project coordinated by M. Chaves, in collaboration with J. Roux (IPMC, CNRS) and D. Oyarzun (Univ. Edinburgh).
• SIGNALIFE: Biocore is part of this Labex (scientific cluster of excellence, 2nd period 2020-2024) whose objective is to build a network for innovation on Signal Transduction Pathways in Life Sciences, and is hosted by the University Côte d'Azur.
• UMT FIORIMED: FioriMed is a Mixed Technology Unit created in January 2015 to strengthen the production and dissemination of innovation to the benefit of ornamental horticulture. Horticultural greenhouses are seen as a "laboratory" for the actual implementation of agroecology concepts with the possibility of generic outcomes being transfered to other production systems. The main partners of UMT FioriMed are ASTREDHOR (National Institute of Horticulture) and the ISA Joint Research Unit of INRAE-CNRS-UCA.
• EcoPhyto - CeraTIS Corse: “Territorial management of the Mediterranean fruit fly in Corsica by the Sterile Insect Technique” (2020-2022). This project is based on a pilot field experiment of sterile male releases and it integrates population dynamics and socio-economic approaches.
• EcoPhyto - INTERLUDE: “Territorial innovations to reduce phytoparmaceutical products for the sustainable production of vegetable crops” (2020-2022). BIOCORE members participate in a case study that focuses on the agroecological management of soil pests and pathogens in Provence.

10.4.2 Inria funding

• AMDT, SiDRes: (2020-) The Action Mutualisée de Développement Technologique “Simulateur pour le Déploiement de Résistances” aims at developing a user-friendly, upgradeable and efficient simulation tool to assess the durability of resistant cultivar deployment strategies. It focuses on the evolution of the interactions between fungal pathogens and annual field crop cultivars in an agricultural landscape. It involves the BIOCORE project-team and engineers from the SED, as well as INRAE colleagues.
• Inria Startup Studio, DareWin: (2022-2023). The DareWin project is consolidating the bases of a startup which will develop Darwinian selection approaches in highly controlled bioreactors to naturally select and improve microalgal strains of industrial interest.

10.4.3 INRAE funding

• COCODIV: “Crop disease co-occurrence in cereal systems: determinants, role and management of cultivated and wild diversity from plot scale to landscape level integration”, INRAE SuMCrop Metaprogramme (2022–2023), in which Biocore is a partner with INRAE Sophia Antipolis.
• DYNAMO: “Drivers of the epidemic dynamics of wheat rusts at the landscape scale of the Zone Atelier Plaine & Val de Sèvre”, INRAE SPE Division (2022-2024), in which Biocore is a partner with INRAE Sophia Antipolis.

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

Organization of the scientific BIOCORE Seminar

• Walid Djema organizes a monthly scientific seminar in which external guests and collaborators are regularly invited (see the Table below).

11.1.3 Journal

11.1.4 Invited talks

• W. Djema was an invited speaker at the 15th Viennese Conference on Optimal Control and Dynamic Games (July 12–15, 2022).
• W. Djema was invited to give a talk at LMBA Seminar (LMBA: Laboratoire de Mathématiques de Bretagne Atlantique) on 'Optimal Control of Microalgae'.
• M. Chaves was invited to give a talk at the Workshop on Hybrid Models and Methods in Systems Medicine (July, Institut Curie, Paris). She also gave an invited talk at the online GT BIOSS (Biologie des Systèmes) monthly seminars.
• F. Casagli was invited to give a talk within the IWA webinar " Modelling and Integrated Assessment Specialist Group (MIA)" the 21st of December, on the challenges for modelling algae-bacteria systems.
• O. Bernard was invited to give a conference at Sapienza, University in Roma, Department of Chemistry "Algae-bacteria systems for nitrogen recovery: promises and challenges through a modelling approach" the 16th of December 2022.

11.1.5 Scientific expertise

• M. Chaves is a member of the scientific committee of Labex Signalife (since 2020).
• M. Chaves participated in the selection committee for a post of Maître de Conférences at Polytech, Laboratoire I3S (Univ. Côte d’Azur).
• O. Bernard is a member of the scientific committee of the Inalve company.
• O. Bernard represents Inria at the ANCRE (Alliance Nationale de Coordination de la Recherche pour l'Energie).
• O. Bernard represents is a member of the scientific committee of IRD (Institute of Research for the Development) in the CSS5 section (models and data). He participated to the recruitment juries for researchers and research directors at IRD.
• O. Bernard is in the Scientific and Pedagogic committee of the UCA- EUR LIFE and in the steering committee of Federal Recherche Institut (IFR) Marine Ressources (MARRES).
• S. Touzeau participated in selection panels for INRAE junior research scientists.
• J.-L. Gouzé is in the scientific committee of Académie 4 of UCA-Jedi. He is a member of the board of the SFBT (French Speaking Society for Theoretical Biology).

11.1.6 Research administration

• M. Chaves, F. Grognard, and L. Mailleret are members of the INRAE Commission Scientifique Spécialisée (CSS) for Mathématique, Informatique, Sciences et Technologies du numérique, Intelli- gence artificielle et Robotique (MISTI).
• M. Chaves is a member of the local Inria committee for doctoral studies (CSD) and the committee NICE for welcoming external researchers (post-docs, “delegations”). She is also a representative of Inria at the Canceropole PACA. She is the coordinator of the UE Biologie Systémique 1 of the new Master option on Bioinformatics and Computational Biology of the EUR Sciences du Vivant et de la Santé.
• O. Bernard is a member of the ADT (Technological Development Actions) commission at Inria and of the local commission for sustainable development.
• M. Péré was one of the organizers of the Inria PhD Student Seminars, taking place every two weeks.
• F. Grognard is a member of the steering committee of Academy 3, Space, Environment, Risk and Resilience of UCA-JEDI. He is co-head of the development of the MSc Risk of UCA-JEDI and is a member of the Scientific Committee of the Agroecosystems department of INRAE.
• L. Mailleret is the head of the M2P2 team (Models and Methods for Plant Protection) of ISA. He’s in the Unit and scientific council of Institut Sophia Agrobiotech.
• L. Mailleret is an elected member (since 2020) of the Scientific and Pedagogic Council (CoSP) of the EUR LIFE (Graduate school in Life and Health Sciences ) of Université Côte d'Azur.
• S. Touzeau is a member of the steering committee of the INRAE Metaprogramme SuMCrop “Sustainable Management of Crop Health”, a follow-up of the SMaCH metaprogramme (since 2016).
• V. Baldazzi ans S. Touzeau are elected members of the Institut Sophia Agrobiotech council.
• J.-L. Gouzé is in the Inria committee supervising the doctoral theses, a member of the steering committee of Labex SIGNALIFE of Université Côte d’Azur, and of the scientific committee of Académie 4 (Life Sciences) of UCA.

11.2.1 Teaching

• Licence: F. Grognard (42h ETD) and L. Mailleret (24h ETD), “Equations différentielles ordinaires et systèmes dynamiques”, L3, 1st year Engineering in Modeling and Applied Mathematics, Polytech Nice Sophia, Université Côte d'Azur, France.
• Licence: W. Djema (20h ETD); "Mathématiques pour Biologistes: Analyse et Modélisation", L1 Université Côte d'Azur, France.
• Master: O. Bernard (4.5h ETD), “Bioenergy from microalgae”, M2, Master International Energy Management : alternatives pour l'énergie du futur, Ecole Nationale Supérieure des Mines de Paris, France.
• Master: O. Bernard (18h ETD), “Modeling biotechnological processes”, M2, Ecole CentraleSupelec, Saclay, France.
• Master: O. Bernard (18h ETD), “Automatic Control applied to biotechnological processes”, M2, Ecole CentraleSupelec, Saclay, France.
• Master: O. Bernard (6h ETD), “Cultivation and use of Microalgae”, Master Mares, Université Côte d'Azur, France.
• Licence: O. Bernard (35h ETD), “Use and optimization of photobioreactors”, Université de Pau et des pays de l'Adour, France.
• Master: O. Bernard (27h ETD) and W. Djema (27h ETD), “Enseignement d’Intégration EI – ST5 Méthanisation”, Ecole CentraleSupélec, Paris-Saclay, France.
• Licence: O. Bernard (3$\times$ 3h ETD); "Introduction to Life Cycle Assesment", L3 Université Côte d'Azur, France.
• Master : W. Djema (20h ETD); "Traitement du Signal", M1 IM, Université Côte d'Azur, France.
• Master: W. Djema (17h ETD) and M. Chaves (10h ETD); “Modélisation des réseaux biologiques”, M1 Sciences du Vivant, Université Côte d'Azur, France.
• Master : J.-L. Gouzé (20h ETD), M. Chaves (13.5h ETD), “Modeling biological networks by ordinary differential equations”, M1, 2nd year Engineering in Génie biologique, Polytech Nice Sophia, Université Côte d'Azur, France.
• Master: F. Grognard (21h ETD) and L. Mailleret (21h ETD), “Bio-Mathématiques”, M1, 2nd year Engineering in Modeling and Applied Mathematics, Polytech Nice Sophia, Université Côte d'Azur, France.
• Master: F. Grognard (30h ETD) and W. Djema (15h ETD), "Elements of mathematical modelling", M1, MSc in Environmental Hazards and Risks Management, Université Côte d'Azur, France.
• Licence: C. Djuikem (18h ETD), "Introduction à la modélisation mathématique et numérique", L3, 1st year in Water Engineering, Polytech Nice Sophia, Université Côte d'Azur, France.
• Licence: W. Djema (16h ETD); "Math0: Enjeux", L1 Université Côte d'Azur, France.
• Licence: C. Djuikem (40h ETD), "Analyse et modélisation", L1 Sciences de la vie, Université Côte d'Azur, France.
• Licence: C. Djuikem – ATER contract (24h ETD), "Processus Stochastiques", L3, 1st year Engineering in Modeling and Applied Mathematics, Polytech Nice Sophia, Université Côte d'Azur, France.
• Licence: C. Djuikem – ATER contract (60h ETD), "Statistiques", L1 Sciences de la vie, Université Côte d'Azur, France.
• Research School: J.-L. Gouzé gave extended conferences and S. Touzeau taught a course at the CIMPA School "Vert numérique", Tunisia.
• W. Djema gave lectures on 'Observers' and 'Dynamic Optimization' during the 'Summer School on Automatic Bioprocess Control' at Inria Sophia Antipolis, organized by O. Bernard on behalf of the ITN Digitalgaesation Project.

11.2.2 Supervision

• PhD: Y. Fotso Fotso. “Modeling, analysis and control of coffee berry borer”, University of Dschang, Cameroon, defended January 17. Supervisors: B. Tsanou (Univ. Dschang), S. Bowong (Univ. Douala), F. Grognard, S. Touzeau.
• PhD: P. Clin, "Understanding biodiversity to sustainably prevent plant diseases", defended December 16th, Université de Rennes 1. Supervisors: F. Hamelin, L. Mailleret, D. Andrivon.
• PhD in progress: M. Péré. “’Modeling cancer drug response heterogeneity using experimental tu- mor single-cell dynamics and transcriptomics’, since October 2019, Univ. Côte d’Azur. Supervisors: M. Chaves and J. Roux (IRCAN, Nice).
• PhD in progress: C. Djuikem. “Modelling and control of perennial plant phytopathogens”, Université Côte d'Azur, since October 2019 (defense January 5th 2023). Supervisors: F. Grognard, S. Touzeau, S. Bowong (Univ. Douala).
• PhD in progress: O. Burckard. "Coupling, synchronization, and control of cellular oscillators through mathematical modeling and analysis", Université Côte d’Azur, since 2021. Supervisor: M. Chaves.
• PhD in progress: M. Cointe. “Mieux prédire la propagation spatiale de groupes de trichogrammes pour améliorer le biocontrôle : de l’écologie du mouvement à la dispersion dans les cultures”, Université Côte d'Azur, since 2020. Supervisors V. Calcagno, L. Mailleret.
• PhD in progress: M. Courtois. "Modélisation de la technique de l’insecte stérile dans un contexte agricole : comment intégrer les réalités biologiques et techniques pour optimiser son déploiement ? ", Université Côte d'Azur, since 2022. Supervisors L. Mailleret, S. Touzeau, L. van Oudenhove.
• PhD in progress: I. Fierro Ulloa. “Development and analysis of a digital twin for monitoring, control and optimization applications in microalgae: the Microalgae Model”, since September 2021, UCA. Supervisor: O. Bernard.
• PhD in progress: A. Gharib. “Robust control of microalgae processes accounting for future meteorology”, since September 2021. (UCA, ITN Digitalgaesation). Supervisors: O. Bernard (director) and W. Djema (co-director).
• PhD in progress: B. Assis Pessi. “Modelling and Control of outdoor microalgal processes”, since November 2019, Université Côte d'Azur. Since 2019. Supervisors: O. Bernard and L. Giraldi (team McTao).
• PhD in progress: D. Penaranda Sandoval. “Environmental impact assesment of technologically immature processes”, Université Côte d'Azur. Since 2020. Supervisors: O. Bernard
• PhD in progress: Yan GAO. "Response of photosynthetic biofilms to fluctuating light", Université de Saclay, since 2018. Supervisor: F. Lopes and O. Bernard.
• PhD in progress: R. Ranini. "Deep leanring approaches for enhancing models in oceanography", UCA, since 2022. Supervisor: L. Guidi and O. Bernard.
• PhD in progress: R. Asswad. “Développement de stratégies de contrôle pour les consortiums microbiens synthétiques”, since October 2022, Université Grenoble-Alpes Supervisors J.-L. Gouzé and E. Cinquemani (Microcosme, Inria Grenoble).

11.2.3 Master theses and internships

• M2: K. Burger `Growing Algae without Water? A Computer-Model Machine-Learning Approach `” UCA, F. Casagli and O. Bernard.
• M1: Crésus Kounoudji. "Modéliser la dynamique des populations de Drosophila suzukii afin d’optimiser le déploiement de la Technique de l’Insecte Stérile", Aix Marseille Université, Supervisors: L. van Oudenhove, L. Mailleret, S. Touzeau, F. Grognard.
• M1: Emma Ceci. "Development and calibration of an integrated model of the plant-nematode system. Effect of phenotypic variations on plant growth.", INSA Lyon. Supervisor: V. Baldazzi and S. Touzeau.
• M1: T. Rolin, “Observability and observers for mathematical models of bacterial growth”. Polytech Nice MAM4, supervised by L. Sacchelli (MCTAO) and J.-L. Gouzé.

11.2.4 Juries

• M. Chaves was a reviewer for the PhD thesis of Samuel Buchet (École Central de Nantes) and a reviewer for the HDR of Céline Casenave (Université de Montpellier).
• S. Touzeau was in the jury and F. Grognard invited in the jury of Y. Fotso Fotso (Université de Dschang, Cameroon).
• L. Mailleret was in the jury and F. Grognard invited in the jury of P. Clin (Université de Rennes 1).
• O. Bernard was referee of the PhD of Dirk de Kobe, October 17th (Univ. Leuven).
• O. Bernard was referee of the PhD of F. Baudeau , December 15th (Univ. Toulouse).
• J.-L. Gouzé was a member of the jury for the PhD thesis of C. Djuikem (UCA), for the HDR of A. Goelzer (Univ. Paris Saclay), and was a rapporteur for the PhD thesis of Manel Dali Youcef (Univ. Montpellier).
• M. Chaves is in the PhD committee (CSI) of Sandra Kovachka and Romain Michelucci (Université Côte d'Azur), and also Pauline Delpierre (Université de Lille).
• F. Grognard and S. Touzeau are in the PhD committee of Pauline Clin (Université de Rennes 1).
• F. Grognard is in the PhD committee of Méline Saubin (Université de Lorraine) and of Christos Bountzoukis (Université Côte d'Azur)
• L. Mailleret is in the PhD committee of Clotilde Djuikem (Université Côte d'Azur).
• J.-L. Gouzé is in the PhD committee of P. Jacquet (Univ. Grenoble), A. Pavlou (Univ. Grenoble) and Odile Burckard (UCA).

11.3.1 Articles and contents

• Diego Penaranda published a popularisation paper published in Actu-Environment magazine. "Quantifying our impact on the environment: life cycle analysis"
• Francesca Casagli was interviewed from Nice Matin magazine for the award she received from the L'Oréal-UNESCO program For Women in Science. "Avec sa science, elle lutte contre les eaux polluées".
• Francesca Casagli was interviewed from 20 minutes magazine for the award she received from the L'Oréal-UNESCO program For Women in Science. "Alpes-Maritimes : Des microalgues pour décontaminer les eaux usées, les travaux d’une chercheuse récompensés".
• Francesca Casagli was interviewed from Nice Matin magazine for the Excellence Awards winners evening. Nice Matin published an 8-page supplement on the eve of the event dedicated to research at the University of Côte d'Azur . "Purifier les eaux polluées grâce à des microalgues".
• Walid Djema participated to the supervision of Baptiste Pellegrinetti (Stagiaire Amodiation Scientifique) during his Master internship @TerraNumerica and Inria. A poster on 'Microalgae Selection' has been prepared and presented during the official opening of the new Terra Numerica building in Sophia Antipolis.

11.3.2 Interventions

• W. Djema, member of the CLDD (Commission Locale de DD à Inria), organized a conference entitled "La mobilité active et durable : quand la psychologie et la géographie se combinent pour mieux la comprendre et la promouvoir" (June 7th, 2022) at Inria Sophia Antipolis. The conference was animated by Claudia Teran-Escobar (Institut des Géosciences de l'Environnement à Grenoble), with the help of Martine Olivi (FACTAS).
• P. Bernhard gave all-public presentations at the Nice médiathèque Raoul Mille, lycée Carnot (Cannes, 2 conferences), La Trinité, Menton, La Tour sur Tinée (2 conferences, with one at small Roussillon village), Beaulieu, Contes, Bonson, and Sospel.
• O. Bernard gave all-public presentations in Biot, Contes, Colomars and Venanson.
• M. Chaves gave an all-public presentation on research in mathematics at the occasion of the ceremony of prize distribution for the regional Mathematics Olympiads, at Inria (June 2022).
• In the context of the program "1 scientist – 1 class: Chiche!", C. Djuikem presented her work and interacted with students at the Thierry Maulnier high school in Nice (January 2022) and the Jules Ferry high school in Cannes (March 2022).
• C. Djuikem participated in the MathC2+ program (June 2022), which welcomes high school students with a scientific profile, who discover more about mathematics and Inria research.

International journals

• 11 articleN.Nicolas Augier, U.Ugo Boscain and M.Mario Sigalotti. Effective adiabatic control of a decoupled Hamiltonian obtained by rotating wave approximation.Automatica1362022, 110034HALDOI
• 12 articleN.Nicolas Augier, M.Madalena Chaves and J.-L.Jean-Luc Gouzé. Qualitative control strategies for synchronization of bistable gene regulatory networks.IEEE Transactions on Automatic Control2022HALback to text
• 13 articleN.Nicolas Augier, M.Madalena Chaves and J.-L.Jean-Luc Gouzé. Weak synchronization and convergence in coupled genetic regulatory networks: Applications to damped oscillators and multistable circuits.International Journal of Robust and Nonlinear Control2022HALback to text
• 14 articleN.Nicolas Augier and A. G.Agustín Gabriel Yabo. Time-optimal control of piecewise affine bistable gene-regulatory networks.International Journal of Robust and Nonlinear ControlJanuary 2022HALDOIback to text
• 15 articleC.Caroline Baroukh, F.Francis Mairet and O.Olivier Bernard. The paradoxes hidden behind the Droop model highlighted by a metabolic approach.Frontiers in Plant Science13August 2022, 16 p.HALDOIback to textback to text
• 16 articleO.Olivier Bernard and L.-D.Liu-Di Lu. Optimal optical conditions for Microalgal production in photobioreactors.Journal of Process Control1122022, 69-77HALDOIback to text
• 17 articleO.Olivier Bernard, L.-D.Liu-Di Lu and J.Julien Salomon. Optimal periodic resource allocation in reactive dynamical systems: Application to microalgal production.International Journal of Robust and Nonlinear ControlMay 2022HALDOIback to text
• 18 articleP.Pierre Bernhard, M.Marc Deschamps and G.Georges Zaccour. Large satellite constellations and space debris: exploratory analysis of strategic management of the space commons ⋆.European Journal of Operational ResearchFebruary 2023HAL
• 19 articleB.Benjamin Bian, A.Agnès Paquet, M.-J.Marie-Jeanne Arguel, M.Mickael Meyer, L.Ludovic Peyre, A.Asma Chalabi, M.Marielle Péré, K.Kevin Lebrigand, R.Rainer Waldmann, P.Pascal Barbry, P.Paul Hofman and J.Jérémie Roux. Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells.STAR Protocols33September 2022, 101600HALDOIback to text
• 20 articleO.Odile Burckard, M.Michèle Teboul, F.Franck Delaunay and M.Madalena Chaves. Cycle dynamics and synchronization in a coupled network of peripheral circadian clocks.Interface Focus123June 2022, 20210087HALDOIback to textback to text
• 21 articleV.Victor Burte, G.Guy Perez, F.Faten Ayed, G.Géraldine Groussier, L.Ludovic Mailleret, L.Louise van Oudenhove and V.Vincent Calcagno. Up and to the light: intra- and interspecific variability of photo- and geo-tactic oviposition preferences in genus Trichogramma.Peer Community Journal22022, e3HALDOIback to text
• 22 articleJ.-B.Jean-Baptiste Caillau, W.Walid Djema, J.-L.Jean-Luc Gouzé, S.Sofya Maslovskaya and J.-B.Jean-Baptiste Pomet. Turnpike property in optimal microbial metabolite production.Journal of Optimization Theory and ApplicationsApril 2022HALDOIback to text
• 23 articleF.Francesca Casagli, F.Fabrice Béline, E.Elena Ficara and O.Olivier Bernard. Optimizing resource recovery from wastewater with algae-bacteria membrane reactors.Chemical Engineering Journal451January 2023, 138488HALDOIback to textback to textback to text
• 24 articleF.Francesca Casagli and O.Olivier Bernard. Coupling heat transfer modelling to ALBA model for full predictions from meteorology.IFAC-PapersOnLine5520July 2022, 558-563HALDOIback to textback to text
• 25 articleF.Francesca Casagli and O.Olivier Bernard. How Heat Transfer Indirectly Affects Performance of Algae-Bacteria Raceways.Microorganisms108August 2022, 1515HALDOIback to textback to text
• 26 articleF.Francesca Casagli and O.Olivier Bernard. Simulating biotechnological processes affected by meteorology: Application to algae–bacteria systems.Journal of Cleaner Production377December 2022, 134190HALDOIback to textback to text
• 27 articleP.Pauline Clin, F.Frédéric Grognard, D.Didier Andrivon, L.Ludovic Mailleret and F. M.Frédéric Marie Hamelin. Host mixtures for plant disease control: Benefits from pathogen selection and immune priming.Evolutionary ApplicationsMay 2022HALDOIback to text
• 28 articleW.Walid Djema, T.Térence Bayen and O.Olivier Bernard. Optimal Darwinian Selection of Microorganisms with Internal Storage.Processes103March 2022, 461HALDOIback to textback to text
• 29 articleC.Clotilde Djuikem, F.Frédéric Grognard and S.Suzanne Touzeau. Impulsive modelling of rust dynamics and predator releases for biocontrol.Mathematical BiosciencesJanuary 2023, 108968HALDOI
• 30 articleA.Andrea Fanesi, T.Thierry Martin, C.Cyril Breton, O.Olivier Bernard, R.Romain Briandet and F.Filipa Lopes. The architecture and metabolic traits of monospecific photosynthetic biofilms studied in a custom flow‐through system.Biotechnology and Bioengineering119June 2022, pp. 2459-2470HALDOIback to textback to text
• 31 articleI.Ignacio Fierro, L.-D.Liu-Di Lu and O.Olivier Bernard. Theoretical growth rate of microalgae under high/low-flashing light.Journal of Mathematical Biology2023HALback to textback to text
• 32 articleY.Yves Fotso Fotso, S.Suzanne Touzeau, F.Frédéric Grognard, B.Berge Tsanou and S.Samuel Bowong. Optimal Control of Coffee Berry Borers: Synergy Between Bio-insecticide and Traps.Journal of Optimization Theory and Applications2023HALDOI
• 33 articleY.Yves Fotso Fotso, S.Suzanne Touzeau, B.Berge Tsanou, F.Frédéric Grognard and S.Samuel Bowong. Mathematical modelling of a pest in an age-structured crop model: The coffee berry borer case.Applied Mathematical Modelling1102022, 193-206HALDOIback to textback to text
• 34 articleY.Y. Lie, T.T. Lacour, B.B. Saint-Jean, G.G. Carrier, E.E. Pruvost, A.A. Talec, A.Antoine Sciandra, H.Hubert Bonnefond and O.Olivier Bernard. Dynamical Darwinian selection of a more productive strain of Tisochrysis lutea.Algal Research - Biomass, Biofuels and Bioproducts65June 2022, 102743HALDOIback to textback to text
• 35 articleC.Carlos Martínez, B. A.Bruno Assis Pessi and O.Olivier Bernard. Optimal production of microalgae in the presence of grazers.Journal of Process Control118October 2022, 153-164HALDOIback to text
• 36 articleJ. A.Jineth Arango Oviedo, R.Raúl Muñoz, A.Andrés Donoso-Bravo, O.Olivier Bernard, F.Francesca Casagli and D.David Jeison. A half-century of research on microalgae-bacteria for wastewater treatment.Algal Research - Biomass, Biofuels and Bioproducts67September 2022, 102828HALDOIback to textback to text
• 37 articleD.Diego Penaranda, H.Hubert Bonnefond, F.Freddy Guihéneuf, M.Marjorie Morales and O.Olivier Bernard. Life cycle assessment of an innovative rotating biofilm technology for microalgae production: An eco-design approach.Journal of Cleaner Production384January 2023, 135600HALDOIback to text
• 38 articleB. A.Bruno Assis Pessi, C.Caroline Baroukh, A.Anais Bacquet and O.Olivier Bernard. A universal dynamical metabolic model representing mixotrophic growth of Chlorella sp. on wastes.Water Research2292023, 119388HALDOIback to textback to text
• 39 articleB. A.Bruno Assis Pessi, E.Eric Pruvost, A.Amélie Talec, A.Antoine Sciandra and O.Olivier Bernard. Does temperature shift justify microalgae production under greenhouse?Algal Research - Biomass, Biofuels and Bioproducts61January 2022, 102579HALDOIback to text
• 40 articleB.Bastien Polizzi, A.Andrea Fanesi, F.Filipa Lopes, M.Magali Ribot and O.Olivier Bernard. Understanding photosynthetic biofilm productivity and structure through 2D simulation.PLoS Computational Biology184April 2022, e1009904HALDOIback to textback to text
• 41 articleR.Rémi Robin, N.Nicolas Augier, U.Ugo Boscain and M.Mario Sigalotti. Ensemble qubit controllability with a single control via adiabatic and rotating wave approximations.Journal of Differential Equations318May 2022HALDOI
• 42 articleM.Méline Saubin, C.Clémentine Louet, L.Lydia Bousset, F.Frédéric Fabre, I.Isabelle Fudal, F.Frédéric Grognard, F. M.Frédéric M. Hamelin, L.Ludovic Mailleret, S.Solenn Stoeckel, S.Suzanne Touzeau, B.Benjamin Petre and F.Fabien Halkett. Improving sustainable crop protection using population genetics concepts.Molecular Ecology2022HALDOIback to text
• 43 articleA. G.Agustín Gabriel Yabo, J.-B.Jean-Baptiste Caillau, J.-L.Jean-Luc Gouzé, H.Hidde de Jong and F.Francis Mairet. Dynamical analysis and optimization of a generalized resource allocation model of microbial growth.SIAM Journal on Applied Dynamical Systems2112022, 137-165HALDOIback to text

International peer-reviewed conferences

• 44 inproceedingsJ. C.Juan Carlos Arceo, O.Olivier Bernard and J.-L.Jean-Luc Gouzé. Model of Bacteria Mutualism in a Chemostat: Analysis and Optimization with Interval Detector.CDC 2022 - Conference on Decision and ControlCancun, Mexico2022HALback to text
• 45 inproceedingsY.Yves Fotso Fotso, B.Berge Tsanou, S.Samuel Bowong, S.Suzanne Touzeau and F.Frédéric Grognard. Optimal impulsive control of coffee berry borers in a berry age-structured epidemiological model.CARI'2022 - Colloque Africain sur la Recherche en Informatique et en Mathématiques AppliquéesTunis, TunisiaSeptember 2022HALback to text
• 46 inproceedingsM.Marielle Péré, D. A.Diego A. Oyarzun, J.Jérémie Roux and M.Madalena Chaves. Modeling isogenic cancer cell response upon varying TRAIL stimulations to decipher the kinetic determinants of cell fate decision.Foundations of Systems Biology in Engineering (FOSBE)Cambridge, Massachusetts, United StatesAugust 2022HALback to text
• 47 inproceedingsA. G.Agustin Gabriel Yabo, J.-B.Jean-Baptiste Caillau and J.-L.Jean-Luc Gouzé. Optimal allocation of bacterial resources in fed-batch reactors.2022 European Control Conference (ECC)London, United KingdomIEEEJuly 2022, 1466-1471HALDOIback to text

Conferences without proceedings

• 48 inproceedingsP.Pauline Clin, F.Frédéric Grognard, L.Ludovic Mailleret, D.Didier Andrivon and F. M.Frédéric M. Hamelin. Host mixtures for plant disease control: benefits from pathogen selection and immune priming.12th European Conference on Mathematical and Theoretical Biology (ECMTB)Heidelberg, GermanySeptember 2022HALback to text
• 49 inproceedingsC.Clotilde Djuikem, F.Frédéric Grognard and S.Suzanne Touzeau. Bifurcation analysis in a coffee leaf rust epidemiological model.12th European Conference on Mathematical and Theoretical Biology (ECMTB)Heidelberg, GermanySeptember 2022HALback to text
• 50 inproceedingsF.Frédéric Grognard, S.Samuel Bowong, Y.Yves Fotso Fotso, S.Suzanne Touzeau and B.Berge Tsanou. A multi-seasonal model of plant-pest interactions: the coffee berry borer.MPDEE 2022 - Conference on Mathematical Population Dynamics, Ecology and EvolutionTorino, ItalyJune 2022HALback to textback to textback to text
• 51 inproceedingsM.Marielle Péré, A.Asma Chalabi and J.Jérémie Roux. Modeling isogenic cancer cell response upon TRAIL treatment in multi-omics studies.Multiple facets of RNA in development and disease conferenceNice, FranceMarch 2022HALback to text
• 52 inproceedingsM.Marielle Péré, D.Diego Oyarzun, M.Madalena Chaves and J.Jérémie Roux. Analyzing single-cell trajectories with augmented machine learning methods predicts cancer drugs response in live-cell microscopy assays.ICSB 2022 - 21th international conference on systems biologyBerlin, GermanyOctober 2022HALback to text

Scientific book chapters

• 53 inbookA.Alexandre Bout, N.Nicolas Ris, C.Cécilia Multeau and L.Ludovic Mailleret. Augmentative biological control using entomophagous arthropods.Extended BiocontrolSpringer DordrechtJune 2022, 43-53HALDOIback to text
• 54 inbookH.Hélène Gautier, V.Valentina Baldazzi, N.Nadia Bertin, G.G. Vercambre, M.Michel Génard, B.Bénédicte Quilot-Turion, Z.Zhanwu Dai, L.Laurent Julhia and O.Olivier Pailly. Anticiper les impacts du changement climatique sur la qualité des fruits et le rendement, l’apport de la modélisation.Les productions fruitières à l’heure du changement climatique : risques et opportunités en régions tempéréeschapitre 9QuaeFebruary 2022HAL

Doctoral dissertations and habilitation theses

• 55 thesisY.Yves Fotso Fotso. Modelling, analysis and control of coffee berry borer.Université de Dschang (Cameroun)January 2022HALback to textback to textback to text

Reports & preprints

• 56 miscV.Valentina Baldazzi, D.Delphine Ropers, T.Tomas Gedeon, H.Hidde de Jong and J.-L.Jean-Luc Gouzé. Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains.June 2022HALDOIback to text
• 57 miscM.Maxime Dahirel, A.Aline Bertin, V.Vincent Calcagno, C.Camille Duraj, S.Simon Fellous, G.Géraldine Groussier, E.Eric Lombaert, L.Ludovic Mailleret, A.Anaël Marchand and E.Elodie Vercken. Landscape connectivity alters the evolution of density-dependent dispersal during pushed range expansions.March 2021HALDOI
• 58 miscC.Carlos Martinez, E.Eugenio Cinquemani, H.Hidde de Jong and J.-L.Jean-Luc Gouzé. Optimal protein production by a synthetic microbial consortium: Coexistence, distribution of labor, and syntrophy.January 2022HALDOIback to text
• 59 miscA. G.Agustín Gabriel Yabo, J.-B.Jean-Baptiste Caillau and J.-L.Jean-Luc Gouzé. Optimal bacterial resource allocation strategies in batch processing.June 2022HALDOIback to text
• 60 miscA. G.Agustín Gabriel Yabo, M.Mohab Safey El Din, J.-B.Jean-Baptiste Caillau and J.-L.Jean-Luc Gouzé. Stability analysis of a bacterial growth model through computer algebra.January 2023HALback to text

Other scientific publications

• 61 inproceedingsO.Odile Burckard, M.Michèle Teboul, F.Franck Delaunay and M.Madalena Chaves. Coupling and synchronization of peripheral circadian clocks.2022 Labex Signalife MeetingNice, FranceNovember 2022HALback to text
• 62 inproceedingsM.Marine Courtois, K.Kévan Rastello, F.Frédéric Grognard, L.Ludovic Mailleret, S.Suzanne Touzeau and L.Louise van Oudenhove. Sterile insect technique against the medfly: modelling, calibration and effect of residual fertility.ECMTB 2022 - 12th European Conference on Mathematical and Theoretical BiologyHeidelberg, GermanySeptember 2022HALback to textback to text
• 63 inproceedingsM.Marielle Péré, A.Asma Chalabi, D.Diego Oyarzun, M.Madalena Chaves and J.Jérémie Roux. Integrating machine learning methods to single cell signaling analyses increases throughput and accuracy for target identification in immuno-oncology.5th Signalife Labex MeetingNice, FranceNovember 2022HALback to textback to text
• 64 inproceedingsM.Marielle Péré, A.Asma Chalabi, D.Diego Oyarzun, M.Madalena Chaves and J.Jérémie Roux. Integrating machine learning methods to single-cell experimental workflow increases throughput and accuracy for target identification in immuno-oncology.Sophia Summit AISophia Antipolis, FranceNovember 2022HALback to textback to text
• 65 inproceedingsM.Marielle Péré, M.Madalena Chaves and J.Jérémie Roux. Modelling cell response to cancer drug treatment identifies dynamic features of efficient cell death initiation, enabling prediction and control of therapeutic response heterogeneity.inSiDE seminars (Signaling Dynamics and Encoding,)Connecting scientists interested in single-cell signaling dynamicsOnline, FranceJune 2022HALback to text