Prediction of strain level phage-host interactions across the Escherichia genus using only genomic information.

Predicting bacteriophage infection of specific bacterial strains promises advancements in phage therapy and microbial ecology. Whether the dynamics of well-established phage-host model systems generalize to the wide diversity of microbes is currently unknown. Here we show that we could accurately predict the outcomes of phage-bacteria interactions at the strain level in natural isolates from the genus Escherichia using only genomic data (area under the receiver operating characteristic curve (AUROC) of 86%).

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.

Optogenetic spatial patterning of cooperation in yeast populations.

Microbial communities are shaped by complex metabolic interactions such as cooperation and competition for resources. Methods to control such interactions could lead to major advances in our ability to better engineer microbial consortia for synthetic biology applications. Here, we use optogenetics to control SUC2 invertase production in yeast, thereby shaping spatial assortment of cooperator and cheater cells.

A new look at an old classic: implementation of a SERS-based water hardness titration.

The routine use of SERS as an analytical technique has been hindered by practical considerations among which the irreproducibility of its signals and the lack of robustness of its calibration. In the present work, we examine a strategy to perform quantitative SERS without the need for calibration. The method reinvests a colorimetric volumetric titration procedure to determine water hardness but involves monitoring the progression of the titration through the SERS signal of a complexometric indicator.

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 maximizing 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 and investigate how its performance translates across culture scales.

CyberSco.Py an 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.

Observing Nutrient Gradients, Gene Expression and Growth Variation Using the "Yeast Machine" Microfluidic Device.

The natural environment of microbial cells like bacteria and yeast is often a complex community in which growth and internal organization reflect morphogenetic processes and interactions that are dependent on spatial position and time. While most of research is performed in simple homogeneous environments (, bulk liquid cultures), which cannot capture full spatiotemporal community dynamics, studying biofilms or colonies is complex and usually does not give access to the spatiotemporal dynamics at single cell level. Here, we detail a protocol for generation of a microfluidic device, the "yeast machine", with arrays of long monolayers of yeast colonies to advance the global understanding of how intercellular metabolic interactions affect the internal structure of colonies within defined and customizable spatial dimensions.

Autonomous and Assisted Control for Synthetic Microbiology.

The control of microbes and microbial consortia to achieve specific functions requires synthetic circuits that can reliably cope with internal and external perturbations. Circuits that naturally evolved to regulate biological functions are frequently robust to alterations in their parameters. As the complexity of synthetic circuits increases, synthetic biologists need to implement such robust control "by design".

The Promise of Optogenetics for Bioproduction: Dynamic Control Strategies and Scale-Up Instruments.

Progress in metabolic engineering and synthetic and systems biology has made bioproduction an increasingly attractive and competitive strategy for synthesizing biomolecules, recombinant proteins and biofuels from renewable feedstocks. Yet, due to poor productivity, it remains difficult to make a bioproduction process economically viable at large scale. Achieving dynamic control of cellular processes could lead to even better yields by balancing the two characteristic phases of bioproduction, namely, growth production, which lie at the heart of a trade-off that substantially impacts productivity.

Rational programming of history-dependent logic in cellular populations.

Genetic programs operating in a 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.

Enrichment of persisters enabled by a ß-lactam-induced filamentation method reveals their stochastic single-cell awakening.

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, processes determining phenotypic switches from and to the persister state largely remain elusive.

A microfluidic device for inferring 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 labeled hexose transporters and quantified the spatial correlations with intra-colony growth rates and expression of other genes regulated by glucose availability.

Hyperosmotic Stress Response Memory is Modulated by Gene Positioning in Yeast.

Cellular memory is a critical ability that allows microorganisms to adapt to potentially detrimental environmental fluctuations. In the unicellular eukaryote , cellular memory can take the form of faster or slower responses within the cell population to repeated stresses. Using microfluidics and fluorescence time-lapse microscopy, we studied how yeast responds to short, pulsed hyperosmotic stresses at the single-cell level by analyzing the dynamic behavior of the stress-responsive promoter (pSTL1) fused to a fluorescent reporter.

Identification of individual cells from z-stacks of bright-field microscopy images.

Obtaining single cell data from time-lapse microscopy images is critical for quantitative biology, but bottlenecks in cell identification and segmentation must be overcome. We propose a novel, versatile method that uses machine learning classifiers to identify cell morphologies from z-stack bright-field microscopy images. We show that axial information is enough to successfully classify the pixels of an image, without the need to consider in focus morphological features.

Balancing a genetic toggle switch by real-time feedback control and periodic forcing.

Cybergenetics is a novel field of research aiming at remotely pilot cellular processes in real-time with to leverage the biotechnological potential of synthetic biology. Yet, the control of only a small number of genetic circuits has been tested so far. Here we investigate the control of multistable gene regulatory networks, which are ubiquitously found in nature and play critical roles in cell differentiation and decision-making.

Extracellular Vesicle Production Loaded with Nanoparticles and Drugs in a Trade-off between Loading, Yield and Purity: Towards a Personalized Drug Delivery System.

Extracellular vesicles (EVs) released by cells and circulating in body fluids are recognized as potent vectors of intercellular self-communication. Due to their cellular origin, EVs hold promise as naturally targeted "personalized" drug delivery system insofar as they can be engineered with drugs or theranostic nanoparticles. However, technical hurdles related to their production, drug loading, purification, and characterization restrain the translation of self-derived EVs into a clinical drug delivery system.

Long-term tracking of budding yeast cells in brightfield microscopy: CellStar and the Evaluation Platform.

With the continuous expansion of single cell biology, the observation of the behaviour of individual cells over extended durations and with high accuracy has become a problem of central importance. Surprisingly, even for yeast cells that have relatively regular shapes, no solution has been proposed that reaches the high quality required for long-term experiments for segmentation and tracking (S&T) based on brightfield images. Here, we present , a tool chain designed to achieve good performance in long-term experiments.

Long-range self-organization of cytoskeletal myosin II filament stacks.

Although myosin II filaments are known to exist in non-muscle cells, their dynamics and organization are incompletely understood. Here, we combined structured illumination microscopy with pharmacological and genetic perturbations, to study the process of actomyosin cytoskeleton self-organization into arcs and stress fibres. A striking feature of the myosin II filament organization was their 'registered' alignment into stacks, spanning up to several micrometres in the direction orthogonal to the parallel actin bundles.

Out-of-equilibrium stationary states, percolation, and subcritical instabilities in a fully nonconservative system.

The exploration of the phase diagram of a minimal model for barchan fields leads to the description of three distinct phases for the system: stationary, percolable, and unstable. In the stationary phase the system always reaches an out-of-equilibrium, fluctuating, stationary state, independent of its initial conditions. This state has a large and continuous range of dynamics, from dilute-where dunes do not interact-to dense, where the system exhibits both spatial structuring and collective behavior leading to the selection of a particular size for the dunes.

Age-Related Changes in Locomotor Performance Reveal a Similar Pattern for Caenorhabditis elegans, Mus domesticus, Canis familiaris, Equus caballus, and Homo sapiens.

Locomotion is one of the major physiological functions for most animals. Previous studies have described aging mechanisms linked to locomotor performance among different species. However, the precise dynamics of these age-related changes, and their interactions with development and senescence, are largely unknown.

What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in Yeast.

Significant cell-to-cell heterogeneity is ubiquitously observed in isogenic cell populations. Consequently, parameters of models of intracellular processes, usually fitted to population-averaged data, should rather be fitted to individual cells to obtain a population of models of similar but non-identical individuals. Here, we propose a quantitative modeling framework that attributes specific parameter values to single cells for a standard model of gene expression.

Combining Spinach-tagged RNA and gene localization to image gene expression in live yeast.

Although many factors required for the formation of export-competent mRNPs have been described, an integrative view of the spatiotemporal coordinated cascade leading mRNPs from their site of transcription to their site of nuclear exit, at a single cell level, is still partially missing due to technological limitations. Here we report that the RNA Spinach aptamer is a powerful tool for mRNA imaging in live S. cerevisiae with high spatial-temporal resolution and no perturbation of the mRNA biogenesis properties.

Structured illumination microscopy reveals focal adhesions are composed of linear subunits.

The ability to mechanically interact with the extracellular matrix is a fundamental feature of adherent eukaryotic cells. Cell-matrix adhesion in many cell types is mediated by protein complexes called focal adhesions (FAs). Recent progress in super resolution microscopy revealed FAs possess an internal organization, yet such methods do not enable observation of the formation and dynamics of their internal structure in living cells.

In silico control of biomolecular processes.

By implementing an external feedback loop one can tightly control the expression of a gene over many cell generations with quantitative accuracy. Controlling precisely the level of a protein of interest will be useful to probe quantitatively the dynamical properties of cellular processes and to drive complex, synthetically-engineered networks. In this chapter we describe a platform for real-time closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microfluidics to manipulate the cells environment, and original software for automated imaging, quantification, and model predictive control.