Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.05.17.594525

Kinetic properties of optogenetic DNA editing by LiCre-loxP

Abstract

Advances in optogenetics now allow to specifically modify the DNA of live cells with light. However, using these technologies successfully requires to know their properties in terms of sensitivity, efficiency, kinetics and mechanism. We previously developed an optogenetic tool made of a single chimeric protein called LiCre that enables the induction of specific changes in the genome with blue light via DNA recombination between loxP sites [1]. Here, we used in vitro and in vivo experiments combined with kinetic modeling to provide a deeper characterization of the photo-activated LiCre-loxP recombination reaction. We find that LiCre binds DNA with high affinity in absence of light stimulus and that this binding is cooperative although not as much as for the Cre recombinase from which LiCre was derived. In yeast, addition of riboflavin to the culture medium had no effect on LiCres efficiency, even when cells over-expressed riboflavin kinase, suggesting that abundance of the flavin mono-nucleotide co-factor is not limiting for the reaction. However, LiCres efficiency in yeast gradually increased when raising temperature from 20{degrees}C to 37{degrees}C. The recombination kinetics observed in live cells are best explained by a model where photo-activation of two or more DNA-bound LiCre units (happening in seconds) can produce (in several minutes) a functional recombination synapse. This model was able to capture the effect of a point mutation altering LiCres light cycle. This deeper understanding of the LiCre-loxP system provides additional knowledge for designing experiments where specific genetic changes are induced in live cells with light. AUTHOR SUMMARYUsing a technology called optogenetics, scientists are now able to change the DNA sequence of live cells by illuminating them with light. In theory, they can trigger in genetically-engineered organisms a mutation of interest in specific cells at a specific time. This practice, however, is not common because optogenetics relies on light-controlled enzymes that are recent and not well characterized. We previously developed one of these enzymes, called LiCre, which recognizes a specific piece of DNA. Following illumination with blue light, LiCre can switch on or off whatever gene is close by. Here, we combined experiments and computational modeling to better understand how, and how fast, LiCre works. We find that, although it is inactive in the dark, LiCre does not need photo-activation to bind to its DNA partner. We estimated the speed at which LiCre gets deactivated in the dark and the speed at which active LiCre molecules modify DNA. We also showed the effect of temperature and illumination dynamics on LiCres efficiency. These results will help design strategies where LiCre can be used to conduct genetic studies at high spatio-temporal resolution, or implement it in industrial and biomedical applications.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dufour, A., Duplus-Bottin, H., Boukeke-Lesplulier, T., Casassa, E., Triqueneaux, G., Darthenay-Kiennemann, C., Dumont, A., Moali, C., Vittoz, F., Jost, D., Yvert, G.. 2024-05-18. Kinetic properties of optogenetic DNA editing by LiCre-loxP. https://doi.org/10.1101/2024.05.17.594525

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Synergy-informed bilevel optimization reveals joint-specific benefits for realistic exoskeleton torque prediction

Simulation-driven optimization can guide exoskeleton control design, but its utility is limited by the accuracy with which muscle coordination is predicted. Strict effort-minimization formulations predict non-physiological muscle shutdown under high exoskeleton assistance, leading to peak assistive torques that exceed values reported in human-in-the-loop experiments. We evaluated the accuracy of synergy-informed simulations at predicting assistance across four single-joint exoskeleton configurations: ankle plantarflexion, knee extension, hip flexion, and hip abduction. We implemented a bilevel optimization to predict a parameterized assistive torque that minimizes metabolic cost, with assisted muscle dynamics estimated via either effort-minimization simulations (minimizing muscle effort only) or synergy-informed simulations (minimizing muscle effort constrained to a synergy structure). We used experimental data from five unimpaired adults walking at their preferred speed and compared results descriptively between the two formulations within each subject. Assistance based on effort-minimization simulations shut down agonist muscle activations and overestimated peak assistive torque compared with experimental values. In contrast, constraining muscle controls to a synergy structure prevented non-physiological muscle shutdown and yielded assistive torques closer to those measured in human-in-the-loop experiments. This benefit was not observed equally across all assisted degrees of freedom or subjects, emerging only where no single synergy could be suppressed to unload the assisted muscles. Synergy weights can therefore be interpreted as joint-specific predictors of when simulations can reliably inform wearable robot design.

bioengineering↗

Engineered microvessel networks -- Longitudinal transcriptomic profiling validates chip-grown tissues as a robust model for studying vasculature

Vascularised Organ-on-Chip (OoC) models are promising New Approach Methodologies (NAMs), but their translation requires validation for defined Contexts of Use (CoU). Here, we combine microfluidic microvessel networks (MVNs) with longitudinal bulk and single-cell RNA sequencing to determine how cell provenance influences engineered vascular phenotype. Stromal cell identity produced distinct network architectures and transcriptional trajectories, demonstrating that support cells, commonly treated as interchangeable, represent an important CoU variable. Primary human pancreatic microvascular endothelial cells failed to form stable perfusable networks, but supplementation with 10% Human Umbilical Vein Endothelial Cells (HUVECs) or Blood Outgrowth Endothelial Cells (BOECs) rescued self-assembly. Single-cell transcriptomics identified specialised endothelial populations associated with vascular morphogenesis, including tip, stalk, phalanx, endothelial to mesenchymal transition (EndMT) and pericyte-like endothelial cells. Failed networks lacked coherent endothelial specialisation, whereas rescued networks restored stabilising cell states and revealed FLRT2--UNC5B signalling within pericyte-like HUVECs, recapitulating a pathway implicated in angiogenic development in vivo. These findings establish cell provenance as a critical determinant of microvascular NAM performance and demonstrate how transcriptomic validation can define and strengthen the biological relevance of microvessel-on-chip models for specific CoUs.

bioengineering↗

Benchmarking foundation models for resting-state functional magnetic resonance imaging time series in cognitive aging research

Foundation models trained on large neuroimaging datasets could help smaller studies investigate cognition from brain recordings. However, whether the foundation model-derived representations improve assessment of current cognition, prediction of follow-up cognition, or characterization of cognitive change remains unclear. We evaluated nine configurations from five model families that process regional resting-state functional magnetic resonance imaging time series, using 3,103 scans from 1,653 participants across two observational and five intervention aging cohorts. Primary frozen representations showed no consistent superiority over conventional functional connectivity for concurrent cognitive associations or diagnostic classification. Changing the readout improved selected concurrent cognitive associations without updating model weights, indicating that performance depended partly on how representations were extracted. Additional post-training and embedding alignment yielded gains in selected settings but did not consistently improve performance across outcomes. In the primary longitudinal analyses, imaging representations did not establish added value beyond baseline clinical measures. These findings show that readout choice influences concurrent cognitive associations, while the added value of these representations for longitudinal outcomes remains unestablished.

bioengineering↗