Biology subjects

Hersen, P.

Publications and source records attributed to Hersen, P..

12 recordsLinked to original sources

bioRxiv2025

Morphogen gradients applied basally to human embryonic stem cells to control and dissect tissue patterning

Morphogen gradients are used repeatedly during development to pattern embryonic tissues. Absolute concentrations, duration or even temporal derivative of morphogen concentration have all been proposed to carry positional information. However, establishing the causal relationship between the gradient spatio-temporal profile and resulting cellular diversity and tissue patterning is difficult to address in live embryos because of lack of tools to control those variables. Here, we developed microfluidics devices able to apply spatio-temporally well-defined morphogen landscapes on the basal side of human embryonic stem cells colonies, thus mimicking how BMP4 is delivered to the pluripotent epiblast during mouse gastrulation. Combining live imaging and theoretical modelling, we show that in this configuration the absolute concentration of BMP4 provides positional information and the cell identities emerging during differentiation can vary according to the shape of the gradient. Our toolbox provides a powerful means to dissect the logic of patterning and to engineer tissues precisely.

developmental biology↗

bioRxiv2024

Nonlinear Singular Value Decomposition Beamforming for Ultrasound Imaging of Gas Vesicles

Ultrasound imaging holds significant promise for the observation of molecular and cellular phenomena through the utilization of acoustic contrast agents and acoustic reporter genes. Optimizing imaging methodologies for enhanced detection represents an imperative advancement in this field. Most advanced techniques relying on amplitude modulation scheme such as cross amplitude modulation (xAM) and ultrafast amplitude modulation (uAM) combined with Hadamard encoded multiplane wave transmissions have shown efficacy in capturing acoustic signals of gas vesicles (GVs). Nonetheless, uAM sequence requires odd- or even-element transmissions leading to imprecise amplitude modulation emitting scheme, and the complex multiplane wave transmission scheme inherently yields overlong pulse durations. xAM sequence is limited in terms of field of view and imaging depth. To overcome these limitations, we introduce an innovative ultrafast imaging sequence called nonlinear singular value decomposition (SVD) beamforming. Our method demonstrated a contrast imaging sensitivity comparable to the current gold-standard xAM and uAM, while requiring 4.8 times less pulse transmissions. With similar number of transmit pulses, nonlinear SVD beamforming outperforms xAM and uAM in terms of an improvement in signal-to-background ratio of + 4.78 {+/-} 0.35 dB and + 8.29 {+/-} 3.52 dB respectively. Additionally, our method provides a higher flexibility in terms of the selection of acoustic pressure amplitude compared to the other methods. Furthermore, it shows a significant potential for application in the realm of ultrasound localization microscopy (ULM), where it stands poised to facilitate the more precise extraction of nonlinear signatures originating from contrast agents.

biophysics↗

bioRxiv2024

Optogenetic control of pheromone gradients reveals functional limits of mating behavior in budding yeast

During mating in budding yeast, cells use pheromones to locate each other and fuse. This model system has shaped our current understanding of signal transduction and cell polarization in response to extracellular signals. The cell-population produced extracellular signal landscapes themselves are however less well understood, yet crucial for functionally testing quantitative models of cell polarization and for controlling cell behavior through bioengineering approaches. Here we engineered optogenetic control of pheromone landscapes in mating populations of budding yeast, hijacking the mating-pheromone pathway to achieve spatial control of growth, cell morphology, cell-cell fusion, and distance-dependent gene expression in response to light. Using our tool, we were able to spatially control and shape pheromone gradients, allowing the use of a biophysical model to infer the properties of large-scale gradients generated by mating populations in a single, quantitative experimental setup, predicting that the shape of such gradients depends quantitatively on population parameters. Spatial optogenetic control of diffusible signals and their degradation provides a controllable signaling environment for engineering artificial communication and cell-fate systems in gel-embedded cell populations without the need for physical manipulation.

cell biology↗

bioRxiv2023

Predicting phage-bacteria interactions at the strain level from genomes

Predicting how phages can selectively infect specific bacterial strains holds promise for developing novel approaches to combat bacterial infections and better understanding microbial ecology. Experimental studies on phage-bacteria interactions have been mostly focusing on a few model organisms to understand the molecular mechanisms which makes a particular bacterial strain susceptible to a given phage. However, both bacteria and phages are extremely diverse in natural contexts. How well the concepts learned from well-established experimental models generalize to a broad diversity of what is encountered in the wild is currently unknown. Recent advances in genomics allow to identify traits involved in phage-host specificity, implying that these traits could be utilized for the prediction of such interactions. Here, we show that we could predict outcomes of most phage-bacteria interactions at the strain level in Escherichia natural isolates based solely on genomic data. First, we established a dataset of experimental outcomes of phage-bacteria interactions of 403 natural, phylogenetically diverse, Escherichia strains to 96 bacteriophages matched with fully sequenced and genomically characterized strains and phages. To predict these interactions, we set out to define genomic traits with predictive power. We show that most interactions in our dataset can be explained by adsorption factors as opposed to antiphage systems which play a marginal role. We then trained predictive algorithms to pinpoint which interactions could be accurately predicted and where future research should focus on. Finally, we show the application of such predictions by establishing a pipeline to recommend tailored phage cocktails to target pathogenic strains from their genomes only and show higher efficiency of tailored cocktails on a collection of 100 pathogenic E. coli isolates. Altogether, this work provides quantitative insights into understanding phage-host specificity at the strain level and paves the way for the use of predictive algorithms in phage therapy.

microbiology↗

bioRxiv2023

Optogenetic spatial patterning of cooperation in yeast populations

Microbial communities are a siege of complex metabolic interactions such as cooperation and competition for resources. Methods to control such interactions could lead to major advances in our ability to engineer microbial consortia for bioproduction and synthetic biology applications. Here, we used optogenetics to control invertase production in yeast, thereby creating landscapes of cooperator and cheater cells. Yeast cells behave as cooperators (i.e., transform sucrose into glucose, a public "good") upon blue light illumination or cheaters (i.e., consume glucose produced by cooperators to grow) in the dark. We show that cooperators benefit best from the hexoses they produce when their domain size is constrained between two cut-off length-scales. From an engineering point of view, the system behaves as a band pass filter. The lower limit is the trace of cheaters competition for hexoses, while the upper limit is defined by cooperators competition for sucrose. Hence, cooperation mostly occurs at the frontiers with cheater cells, which not only compete for hexoses but also cooperate passively by letting sucrose reach cooperators. We anticipate that this optogenetic method could be applied to shape metabolic interactions in a variety of microbial ecosystems.

synthetic biology↗

bioRxiv2023

Yeast cell responses and survival during periodic osmotic stress are controlled by glucose availability

Natural environments of living organisms are often dynamic and multifactorial, with multiple parameters fluctuating over time. To better understand how cells respond to dynamically interacting factors, we quantified the effects of dual fluctuations of osmotic stress and glucose deprivation on yeast cells using microfluidics and time-lapse microscopy. Strikingly, we observed that cell proliferation, survival and signaling depend on the phasing of the two periodic stresses. Cells divided faster, survived longer and showed decreased transcriptional response when fluctuations of hyperosmotic stress and glucose deprivation occurred in phase than when the two stresses occurred alternatively. Therefore, glucose availability regulates yeast responses to dynamic osmotic stress, showcasing the key role of metabolic fluctuations in cellular responses to dynamic stress. We also found that mutants with impaired osmotic stress response were better adapted to alternating stresses than wild-type cells, showing that genetic mechanisms of adaptation to a persistent stress factor can be detrimental under dynamically interacting conditions.

systems biology↗

bioRxiv2022

Optogenetic control of beta-carotene bioproduction in yeast across multiple lab-scales

Optogenetics arises as a valuable tool to precisely control genetic circuits in microbial cell factories. Light control holds the promise of optimizing bioproduction methods and maximize yields, but its implementation at different steps of the strain development process and at different culture scales remains challenging. In this study, we aim to control beta-carotene bioproduction using optogenetics in Saccharomyces cerevisiae and investigate how its performance translates across culture scales. We built four lab-scale illumination devices, each handling different culture volumes, and each having specific illumination characteristics and cultivating conditions. We evaluated optogenetic activation and beta-carotene production across devices and optimized them both independently. Then, we combined optogenetic induction and beta-carotene production to make a light-inducible beta-carotene producer strain. This was achieved by placing the transcription of the bifunctional lycopene cyclase / phytoene synthase CrtYB under the control of the pC120 optogenetic promoter regulated by the EL222-VP16 light-activated transcription factor, while other carotenogenic enzymes (CrtI, CrtE, tHMG) were expressed constitutively. We show that illumination, culture volume and shaking impact differently optogenetic activation and beta-carotene production across devices. This enabled us to determine the best culture conditions to maximize light-induced beta-carotene production in each of the devices, reaching a content of up to 880 g/gCDW. Our study exemplifies the stakes of scaling up optogenetics in devices of different lab scales and sheds light on the interplays and potential conflicts between optogenetic control and metabolic pathway efficiency. As a general principle, we propose that it is important to first optimize both components of the system independently, before combining them into optogenetic producing strains to avoid extensive troubleshooting. We anticipate that our results can help designing both strains and devices that could eventually lead to larger scale systems in an effort to bring optogenetics to the industrial scale.

synthetic biology↗

bioRxiv2022

CyberSco.Py: open-source software for event-based, conditional microscopy

Timelapse fluorescence microscopy imaging is routinely used in quantitative cell biology. However, microscopes could become much more powerful investigation systems if they were endowed with simple unsupervised decision-making algorithms to transform them into fully responsive and automated measurement devices. Here, we report CyberSco.Py, Python software for advanced automated timelapse experiments. We provide proof-of-principle of a user-friendly framework that increases the tunability and flexibility when setting up and running fluorescence timelapse microscopy experiments. Importantly, CyberSco.Py combines real-time image analysis with automation capability, which allows users to create conditional, event-based experiments in which the imaging acquisition parameters and the status of various devices can be changed automatically based on the image analysis. We exemplify the relevance of CyberSco.Py to cell biology using several use case experiments with budding yeast. We anticipate that CyberSco.Py could be used to address the growing need for smart microscopy systems to implement more informative quantitative cell biology experiments.

cell biology↗

bioRxiv2019

The memory of hyperosmotic stress response in yeast is modulated by gene-positioning

Cellular memory is a critical ability displayed by microorganisms in order to adapt to potentially detrimental environmental fluctuations. In the unicellular eukaryote S. cerevisiae cellular memory can take the form of a faster or a decreased response following repeated stresses in cell population. Using microfluidics and fluorescence time-lapse microscopy, we studied how yeasts respond to short-pulsed hyperosmotic stresses at the single-cell level by analyzing the dynamical behavior of the stress responsive STL1 promoter fused to a fluorescent reporter. We established that pSTL1 shows variability in its successive activations following two repeated short stresses. Despite this variability, most cells displayed a memory of past stresses through a decreased activity of pSTL1 upon repeated stress. Notably, we showed that genomic location is important for the memory effect since promoter displacement to a pericentromeric chromatin domain leads to a decreased transcriptional strength of pSTL1 and to the loss of memory. This study provides a quantitative description of a cellular memory that includes single-cell variability and points towards the contribution of the chromatin structure in stress memory.

genetics↗

bioRxiv2019

Rational programming of history-dependent logic in cellular populations.

Genetic programs operating in an history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed an automated workflow that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.\n\nOne Sentence SummarySystematic and automated frameworks for implementing robust history-dependent genetic programs in cellular populations.

synthetic biology↗

bioRxiv2019

Isolation of persisters enabled by ss-lactam-induced filamentation reveals their single-cell awakening characteristics

When exposed to lethal doses of antibiotics, bacterial populations are most often not completely eradicated. A small number of phenotypic variants, defined as persisters, are refractory to antibiotics and survive treatment. Despite their involvement in relapsing infections caused by major pathogens, processes determining phenotypic switches from and to the persister state largely remain elusive. This is mainly due to the low frequency of persisters in a population and the lack of reliable persistence markers, both hampering studies of persistence at the single-cell level. Problematically, existing methods to enrich for persisters result in samples with very low persister densities and/or a too high abundance of other cell types. Here we present a novel and highly effective persister isolation method involving cephalexin, an antibiotic that induces extensive filamentation of susceptible cells. We show that antibiotic-tolerant cells can easily be separated by size after a short cephalexin treatment, and that the isolated cells are genuine persisters. We used our isolation method to monitor persister outgrowth at the single-cell level in a microfluidic device, thereby conclusively demonstrating that awakening is a stochastic phenomenon. We anticipate that our novel approach can have far-reaching consequences in the persistence field, by allowing single-cell studies at a much higher throughput than previously reported.

microbiology↗

bioRxiv2019

Emergence of metabolic landscapes in yeast monolayer colonies

Microbial colonies are fascinating structures in which growth and internal organization reflect complex morphogenetic processes. Here, we generated a microfluidics device with arrays of long monolayer yeast colonies to further global understanding of how intercellular metabolic interactions affect the internal structure of colonies within defined boundary conditions. We observed the emergence of stable glucose gradients using fluorescently labelled hexose transporters and quantified the spatial correlations with intracolony growth rates and expression of other genes regulated by glucose availability. These landscapes depended on the external glucose concentration as well as secondary gradients, e.g., amino acid availability. This work demonstrates the regulatory genetic networks governing cellular physiological adaptation are the key to internal structuration of cellular assemblies. This approach could be used in the future to decipher the interplay between long-range metabolic interactions, cellular development and morphogenesis in more complex systems.

biophysics↗