Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain

International audienceRecent studies have established a reciprocal causal link between aging and the activation of transposable elements, characterized in particular by a de-repression of LINE-1 retrotransposons. These LINE-1 elements represent 21% of the human genome, but only a minority of these sequences retain the coding potential essential for their mobility. LINE-1 encoded proteins can induce cell toxicity implicated in aging and neurodegenerative diseases. However, our knowledge of the expression and localization of LINE-1-encoded proteins in the central nervous system is limited. Using a novel approach combining atlas-based brain mapping with deep-learning algorithms on large-scale pyramidal brain images, we unveil a heterogeneous, neuron-predominant and widespread ORF1p expression throughout the murine brain at steady-state. In aged mice, ORF1p expression increases significantly which is corroborated in human post-mortem dopaminergic neurons by an increase in young LINE-1 elements including those with open reading frames. Mass spectrometry analysis of endogenous mouse ORF1p revealed novel, neuron-specific protein interactors. These findings contribute to a comprehensive description of the dynamics of LINE-1 and ORF1p expression in the brain at steady-state and in aging and provide insights on ORF1p protein interactions in the brain

Droplet-on-demand using a positive pressure pulse

International audienceDroplet generation under steady conditions is a common microfluidic method for producing biphasic systems. However, this process works only over a limited range of imposed pressure: beyond a critical value, a stable liquid jet can instead form. Furthermore, for a given geometry the pressure conditions set both the generation rate of droplets and their volume. Here, we report on-demand droplet production using a positive pressure pulse to the dispersed-phase inlet of a flow-focusing geometry. This strategy enables confined droplet generation within and beyond the pressure range observed under steady conditions, and decouples volume and production rate. In particular, elongated plugs not possible under steady conditions may be formed when the maximal pressure during the pulse reaches the jet regime. The measured volume of droplets-on-demand, as well as the onset of droplet generation are both captured with a simple model that considers hydraulic resistances. This work provides a strategy and design rules for processes that require individual droplets or elongated plugs in a simple microfluidic chip design

Unsupervised detection and fitness estimation of emerging SARS-CoV-2 variants. Application to wastewater samples (ANRS0160)

Repeated waves of emerging variants during the SARS-CoV-2 pandemics have highlighted the urge of collecting longitudinal genomic data and developing statistical methods based on time series analyses for detecting new threatening lineages and estimating their fitness early in time. Most models study the evolution of the prevalence of particular lineages over time and require a prior classification of sequences into lineages. Such process is prone to induce delays and bias. More recently, few authors studied the evolution of the prevalence of mutations over time with alternative clustering approaches, avoiding specific lineage classification. Most of the aforementioned methods are however either non parametric or unsuited to pooled data characterizing, for instance, wastewater samples. In this context, we propose an alternative unsupervised method for clustering mutations according to their frequency trajectory over time and estimating group fitness from time series of pooled mutation prevalence data. Our model is a mixture of observed count data and latent group assignment and we use the expectation-maximization algorithm for model selection and parameter estimation. The application of our method to time series of SARS-CoV-2 sequencing data collected from wastewater treatment plants in France from October 2020 to April 2021 shows its ability to agnostically group mutations according to their probability of belonging to B.1.160, Alpha, Beta, B.1.177 variants with selection coefficient estimates per group in coherence with the viral dynamics in France reported by Nextstrain. Moreover, our method detected the Alpha variant as threatening as early as supervised methods (which track specific mutations over time) with the noticeable difference that, since unsupervised, it does not require any prior information on the set of mutations

Crystal structures of monomeric BsmI restriction endonuclease reveal coordinated sequential cleavage of two DNA strands

International audienceBsmI, a thermophilic Type IIS restriction endonuclease from Bacillus stearothermophilus, presents a unique structural composition, housing two distinct active sites within a single monomer. Recognition of the non-symmetrical 5'-GAATGC-3' sequence enables precise cleavage of the top and bottom DNA strands. Synthetic biology interventions have led to the transformation of BsmI into Nb.BsmI, a nicking endonuclease. Here we introduce Nt*.BsmI, tailored for top-strand cleavage, which is inactive on standard double-stranded DNA, but active on bottom-strand nicked DNA, suggesting a sequential cleavage mechanism. Crystallographic structures of pre- and post-reactive complexes with cognate DNA show one major conformational change, a retractable loop possibly governing sequential active site accessibility. The x-ray structures reveal the position of the divalent metal ions in the active sites and the DNA:protein interactions, while the models predicted by Alphafold3 are incorrect. This comprehensive structural and functional study lays a foundation for rational enzyme redesign and potential applications in biotechnology

Ethyl 4-Ene-4-ferrocenyl-5,5-bis-(4-hydroxyphenyl)-pentanoate

International audienceThe ferrociphenol family is a group of molecules in which a ferrocenyl moiety is connected to at least one 4-hydroxyphenyl group through a C-C double bond. Among them, ferrocidiphenols in which the double bond is substituted by two gem 4-hydroxyphenyl groups have been largely studied, demonstrating interesting anticancer properties. The fourth available position of the double bond could be substituted by a simple ethyl group (1a) inherited from Tamoxifen, but also by ethyl or methyl acetate, propionate, butanoate, pentanoate (1b-g), hydroxyethyl or hydroxypropyl (1h–i). Ethyl 4-ene-4-ferrocenyl-5,5-bis-(4-hydroxyphenyl)-pentanoate 1e shows an IC50 on the MDA-MB-231 breast cancer cell line very close to that of 1a. These compounds were synthesized in moderate to good yields by McMurry coupling reaction from the corresponding ketones. Ethyl 4-ene-4-ferrocenyl-5,5-bis-(4-hydroxyphenyl)-pentanoate (1e) was fully characterized by 1H NMR (including COSY), 13C NMR (including DEPT135), low resolution mass spectrometry, HRMS, infrared spectroscopy, elemental analysis, and X-ray diffraction (XRD). The data of already published crystal structures of five structurally related ferrocidiphenols are also included for comparison purposes

Smartphone-assisted plasmonic biosensors for rapid on-site detection of foodborne pathogens and allergens

International audienceWe report the design of a smartphone-assisted plasmonic immunosensor and its application to the detection of several food contaminants, namely staphylococcal enterotoxin A (SEA), bovine β-lactoglobulin (BLG), and hen egg white lysozyme (LYSO). Comprehensive characterization of antibodies was performed by ELISA and surface plasmon resonance imaging (SPR-i), demonstrating high affinity and specificity for each target, which supports their potential application in complex food matrices. The immunosensing platform utilizes gold nanoparticle-conjugated antibodies and inexpensive glass slides as single-use chips. Both qualitative visual detection by the naked eye down to around 1 ng of BLG, and quantitative detection with a portable spectrophotometer connectable to a smartphone are demonstrated. This self-contained device may provide a rapid, sensitive, and cost-effective approach to food contaminants analysis, potentially useful for on-site food safety assessment

Façonnage du front d'onde pour l’étude des milieux complexes

International audienceLe façonnage du front d’onde permet de contrôler la propagation de la lumière dans les milieux complexes. Cette approche repose sur l’utilisation de modulateurs spatiaux de lumière, permettant de contrôler le champ optique sur un grand nombre de pixels, et sur des méthodes d’optimisation du champ ou de caractérisation du milieu par des matrices de transmission. Elle ouvre l’accès à de nouvelles applications en imagerie, en télécommunications ou encore en traitement optique de l’information

Hippocampal microstructural changes following electroconvulsive therapy in severe depression

International audienceIntroductionElectroconvulsive therapy (ECT) induces an increase in hippocampal volume presumed to reflect neurogenesis in severely depressed patients. We hypothesized that Neurite Orientation Dispersion and Density Imaging (NODDI) provides in vivo evidence of hippocampal neurogenesis following ECT.MethodsThis prospective longitudinal study included 43 depressed patients treated by ECT. Three sequential evaluations (V1: baseline, V2: at 2 weeks into ECT, V3: 14 days within completing ECT) included a 3T MR-scan with 3D T1-weighted and multi-shell diffusion (b = 200/1500/2500 s/mm2, 30/45/60 directions) sequences and clinical assessment with depression scales. Q-ball, Diffusion Tensor and NODDI models provided the following metrics: axial (AD), radial (RD) and mean diffusivity (MD), fractional anisotropy (FA) and generalized FA (GFA), neurite density index (NDI), isotropic fraction (Fiso), neurite orientation and dispersion index (ODI). FreeSurfer was used to extract whole hippocampal and subfields volumes from T1-weighted images. A linear mixed-effect model assessed the changes over time in hippocampal volumes and mean diffusion metrics, and their relationship with clinical response was analyzed with ANOVA. Bonferroni corrections were applied.Results107 MRI were obtained at V1 (n = 43), V2 (n = 34) and V3 (n = 30) from 43 patients. Mean (± SD) interval between V1-V3 was 70 ± 25 days. Diffusion metrics in the hippocampus were: at V2, a decrease in left GFA, right AD, bilateral Fiso, and a bilateral ODI increase. Additionally, at V3, we observed a left MD decrease, bilateral AD decrease, right NDI increase, and bilateral ODI increase. Notably, NDI and Fiso changes were localized to the dentate gyrus but not to the hippocampal tail. ECT-responders showed a significant right hippocampus volume increase at 2 weeks into ECT.ConclusionAfter ECT, the observed increase in hippocampal volume is accompanied by bilateral changes in NODDI parameters, consistent with hippocampal neuroplasticity

Investigating of the physico-chemistry dhiolated dextran derivatives

International audienceThe study aimed to create redox-responsive dextran carriers for controlled hydrophobic molecule release using glutathione, a natural cellular reducing agent, by modifying dextran with a thiol derivative. Investigating the impact of different hydrophobic length on the molecular self-organization of polysaccharide derivatives into nanoparticles helped to understand their roles in this process. The study demonstrated that thiolated dextran particles can be used as emulsifier and can effectively encapsulated hydrophobic molecules like Nile red dye, with the disulfide linkage being cleaved by glutathione under physiological conditions for rapid release. Additionally, the dextran-based particles were found to be non-toxic to living cells

Programmable metasurfaces for future photonic artificial intelligence

International audiencePhotonic neural networks (PNNs), which share the inherent benefits of photonic systems, such as high parallelism and low power consumption, could challenge traditional digital neural networks in terms of energy efficiency, latency and throughput. However, producing scalable photonic artificial intelligence (AI) solutions remains challenging. To make photonic AI models viable, the scalability problem needs to be solved. Large optical AI models implemented on PNNs are only commercially feasible if the advantages of optical computation outweigh the cost of their input-output overhead. In this Perspective, we discuss how field-programmable metasurface technology may become a key hardware ingredient in achieving scalable photonic AI accelerators and how it can compete with current digital electronic technologies. Programmability or reconfigurability is a pivotal component for PNN hardware, enabling in situ training and accommodating non-stationary use cases that require fine-tuning or transfer learning. Co-integration with electronics, 3D stacking and large-scale manufacturing of metasurfaces would significantly improve PNN scalability and functionalities. Programmable metasurfaces could address some of the current challenges that PNNs face and enable next-generation photonic AI technology