Découvrez les derniers papiers de recherche publiés au sein de la Biofonderie de Paris
Restez informé des dernières avancées et des projets en cours au Biofoundry DNA et Microbe. Notre recherche est à la pointe de l’ingénierie microbienne et de la biologie synthétique, faisant progresser les innovations en matière d’assemblage d’ADN, de phénotypage microbien et d’ingénierie biologique durable. Des découvertes pionnières aux études collaboratives, nos mises à jour présentent le travail de pointe qui façonne l’avenir de la biotechnologie.
Découvrez ci-dessous les récentes réalisations et développements de nos chercheurs :
Maria Meloni, Edoardo Jun Mattioli, Silvia Fanti, Ginevra Marie Eloise Peppi, Tancredi Bin, Giuseppe Gabellini, Daniele Tedesco, Julien Henri, Paolo Trost, Stéphane Lemaire, Matteo Calvaresi, Simona Fermani, Mirko Zaffagnini.
Abstract
Protein S-nitrosylation is a reversible redox-based post-translational modification that plays an important role in cell signaling by modulating protein function and stability. At the molecular level, S-nitrosylation consists of the formation of a nitrosothiol (-SNO) and is primarily induced by the trans-nitrosylating agent nitrosoglutathione (GSNO). Triosephosphate isomerase (TPI), which catalyzes the interconversion of dihydroxyacetone phosphate and glyceraldehyde-3-phosphate, has been identified as a putative target of S-nitrosylation in both plant and non-plant systems. Here we investigate the molecular basis for GSNO-dependent regulation of chloroplast TPI from the model green alga Chlamydomonas reinhardtii (CrTPI). Molecular modelling identified Cys14 and Cys219 as potential sites for interaction with GSNO, though crystallography of GSNO-treated CrTPI revealed S-nitrosylation only at Cys14. To disclose GSNO target sites, we generated and characterized Cys-to-Ser variants for Cys14 and Cys219, identifying Cys219 as a key residue mediating the GSNO-dependent modulation of CrTPI activity. Molecular dynamics simulations further revealed the stabilizing interactions of S-nitrosylated cysteines with their local environments. Overall, our results indicate that CrTPI catalysis is modulated by GSNO through a redox-based mechanism involving Cys219, which highlights a conserved regulatory strategy shared with human TPI.
Engineering Photosynthetic Microorganisms in Biofoundries: Challenges and Opportunities
Damien Douchi, Mathieu Husser, Lucile Jomat, Christophe Marchand, Pierre Crozet, Stéphane Lemaire
Abstract
Photosynthetic microorganisms can convert sunlight and CO₂ directly into biomass and bioproducts. Yet, most biofoundries still optimize heterotrophic chassis reliant on agricultural sugars, limiting impact on global decarbonization. This review argues that sustainable manufacturing requires integrating microalgae and cyanobacteria into Design–Build–Test–Learn pipelines and shifting from biomass conversion to light- and CO₂-driven production. We highlight advances in genetic and cellular engineering in model photosynthetic microbes including modular cloning, genome editing, and organelle engineering that enable pathway design for lipids, isoprenoids, and proteins. We discuss phototroph-specific bottlenecks for automation and standardization, including slower growth, variable transgene expression, chlorophyll autofluorescence, and the need for controlled illumination and gas exchange with linked data pipelines. Finally, we examine cultivation and scale-up constraints, emphasizing co-optimization of strain traits, reactor design, and downstream processing to improve techno-economic and environmental performance. Photosynthetic biofoundries are therefore both necessary and increasingly feasible for a low-carbon bioeconomy.
Antoine Levrier, Paul Soudier, David Garenne, ZIane Izri, Steven Bowden, Ariel Lindner, Vincent Noireaux
Abstract
Viral infection of living cells, exemplified by bacteriophage interaction with bacteria, is fundamental to biology and universal across living systems. Here, we establish an all-cell-free viral cycle where T7 phages infect synthetic cells, equipped with lipopolysaccharides on the outer leaflet of the lipid membrane, while encapsulating a cell-free gene expression system. We track each cycle step to demonstrate T7 phage-specific adsorption onto the liposomes, genome entry, replication, expression, and assembly of new infectious virions within the synthetic cells. We quantify key characteristics of the cycle, including the multiplicity of infection, replication efficiency, liposome size constraints, and phage rebinding dynamics. This work establishes a versatile, fully defined in vitro platform for reconstructing and investigating viral infections from individual molecular components.
Stéphane Lemaire, David Turek, Dave Landsman, Marthe Colotte, Tom de Greef
Abstract
Deoxyribonucleic acid (DNA) computing and data storage are emerging fields that are unlocking new possibilities in information technology. Here, we discuss technologies and challenges regarding using DNA molecules as computing substrates and data storage media.
S giaveri, Z Abil, S Kohyama, M Fu, A Levrier, K Adamala, W Chinatuya, C Dekker, N Deng, J Fredens, K Hagino, K Jahnke, X Li, A Lindner, C Liu, S Majumder, V Noireaux, P Schwille, I Westensee
Abstract
Synthetic cells (SynCells) are artificial constructs designed to mimic cellular functions, offering insights into fundamental biology, as well as promising impact in the fields of medicine, biotechnology, and bioengineering. Achieving a functional SynCell from the bottom up, i.e. by assembling it from molecular components, requires a global collaboration to overcome the many challenges of engineering and assembling life-like modules while addressing biosafety, equity, and ethical concerns in order to guide responsible innovation. Here, we highlight major scientific hurdles, such as the integration of functional modules by ensuring compatibility across diverse synthetic subsystems, and we propose strategies to advance the field.
Antoine Van de Vloet, Lucas Prost-Boxoen, Quinten Bafort, Yunn Thet Paing, Griet Casteleyn, Lucile Jomat, Stéphane Lemaire, Olivier De Clerck, Yves Van de Peer
Abstract
Whole-genome duplications, widely observed in plant lineages, have significant evolutionary and ecological impacts. Yet, our current understanding of the direct implications of ploidy shifts on short- and long-term plant evolution remains fragmentary, necessitating further investigations across multiple ploidy levels. Chlamydomonas reinhardtii is a valuable model organism with profound potential to study the impact of ploidy increase on the longer term in a laboratory environment. This is partly due to the ability to increase the ploidy level. We developed a strategy to engineer ploidy in C. reinhardtii using noninterfering, antibiotic, selectable markers. This approach allows us to induce higher ploidy levels in C. reinhardtii and is applicable to field isolates, which expands beyond specific auxotroph laboratory strains and broadens the genetic diversity of parental haploid strains that can be crossed. We implement flow cytometry for precise measurement of the genome size of strains of different ploidy. We demonstrate the creation of diploids, triploids, and tetraploids by engineering North American field isolates, broadening the application of synthetic biology principles in C. reinhardtii. However, our newly formed triploids and tetraploids show signs of rapid aneuploidization. Our study greatly facilitates the application of C. reinhardtii to study polyploidy, in both fundamental and applied settings.
Adibvafa Fallahpour, Vicent Gureghian, Guillaume Filion, Ariel Lindner, Amir Pandi
Abstract
Degeneracy in the genetic code allows many possible DNA sequences to encode the same protein. Optimizing codon usage within a sequence to meet organism-specific preferences faces combinatorial explosion. Nevertheless, natural sequences optimized through evolution provide a rich source of data for machine learning algorithms to explore the underlying rules. Here, we introduce CodonTransformer, a multispecies deep learning model trained on over 1 million DNA-protein pairs from 164 organisms spanning all domains of life. The model demonstrates context-awareness thanks to its Transformers architecture and to our sequence representation strategy that combines organism, amino acid, and codon encodings. CodonTransformer generates host-specific DNA sequences with natural-like codon distribution profiles and with minimum negative cis-regulatory elements. This work introduces the strategy of Shared Token Representation and Encoding with Aligned Multi-masking (STREAM) and provides a codon optimization framework with a customizable open-access model and a user-friendly Google Colab interface.