Microfabricated polyacrylamide devices for the controlled culture of growing cells and developing organisms

Tracking bacteria at high density with FAST, the Feature-Assisted Segmenter/Tracker

Most bacteria live attached to surfaces in densely-packed communities. While new experimental and imaging techniques are beginning to provide a window on the complex processes that play out in these communities, resolving the behaviour of individual cells through time and space remains a major challenge. Although a number of different software solutions have been developed to track microorganisms, these typically require users either to tune a large number of parameters or to groundtruth a large volume of imaging data to train a deep learning model-both manual processes which can be very time consuming for novel experiments. To overcome these limitations, we have developed FAST, the Feature-Assisted Segmenter/Tracker, which uses unsupervised machine learning to optimise tracking while maintaining ease of use. Our approach, rooted in information theory, largely eliminates the need for users to iteratively adjust parameters manually and make qualitative assessments of the resulting cell trajectories. Instead, FAST measures multiple distinguishing 'features' for each cell and then autonomously quantifies the amount of unique information each feature provides. We then use these measurements to determine how data from different features should be combined to minimize tracking errors. Comparing our algorithm with a naïve approach that uses cell position alone revealed that FAST produced 4 to 10 fold fewer tracking errors. The modular design of FAST combines our novel tracking method with tools for segmentation, extensive data visualisation, lineage assignment, and manual track correction. It is also highly extensible, allowing users to extract custom information from images and seamlessly integrate it into downstream analyses. FAST therefore enables high-throughput, data-rich analyses with minimal user input. It has been released for use either in Matlab or as a compiled stand-alone application, and is available at https://bit.ly/3vovDHn, along with extensive tutorials and detailed documentation.

Depletion attractions drive bacterial capture on both non-fouling and adhesive surfaces, enhancing cell orientation

Depletion attractions, occurring between surfaces immersed in a polymer solution, drive bacteria adhesion to a variety of surfaces. The latter include the surfaces of non-fouling coatings such as hydrated polyethylene glycol (PEG) layers but also, as demonstrated in this work, surfaces that are bacteria-adhesive, such as that of glass. Employing a flagella free E. coli strain, we demonstrate that cell adhesion on glass is enhanced by dissolved polyethylene oxide (PEO), exhibiting a faster rate and greater numbers of captured cells compared with the slower capture of the same cells on glass from a buffer solution. After removal of depletant, any cell retention appears to be governed by the substrate, with cells immediately released from non-fouling PEG surfaces but retained on glass. A distinguishing feature of cells captured by depletion on PEG surfaces is their orientation parallel to the surface and very strong alignment with flow. This suggests that, in the moments of capture, cells are able to rotate as they adhere. By contrast on glass, captured cells are substantially more upright and less aligned by flow. On glass the free polymer exerts forces that slightly tip cells towards the surface. Free polymer also holds cells still on adhesive and non-fouling surfaces alike but, upon removal of free PEO, cells retained on glass tend to be held by one end and exhibit a Brownian type rotational rocking.

Disentangling the fibrous microenvironment: designer culture models for improved drug discovery

INTRODUCTION

Standard high-throughput screening (HTS) assays rarely identify clinically viable 'hits', likely because cells do not experience physiologically realistic culture conditions. The biophysical nature of the extracellular matrix has emerged as a critical driver of cell function and response and recreating these factors could be critically important in streamlining the drug discovery pipeline.

AREAS COVERED

The authors review recent design strategies to understand and manipulate biophysical features of three-dimensional fibrous tissues. The effects of architectural parameters of the extracellular matrix and their resulting mechanical behaviors are deconstructed; and their individual and combined impact on cell behavior is examined. The authors then illustrate the potential impact of these physical features on designing next-generation platforms to identify drugs effective against breast cancer.

EXPERT OPINION

Progression toward increased culture complexity must be balanced against the demanding technical requirements for high-throughput screening; and strategies to identify the minimal set of microenvironmental parameters needed to recreate disease-relevant responses must be specifically tailored to the disease stage and organ system being studied. Although challenging, this can be achieved through integrative and multidisciplinary technologies that span microfabrication, cell biology, and tissue engineering.

Soft-Lithography of Polyacrylamide Hydrogels Using Microstructured Templates: Towards Controlled Cell Populations on Biointerfaces

Polyacrylamide hydrogels are interesting materials for studying cells and cell-material interactions, thanks to the possibility of precisely adjusting their stiffness, shear modulus and porosity during synthesis, and to the feasibility of processing and manufacturing them towards structures and devices with controlled morphology and topography. In this study a novel approach, related to the processing of polyacrylamide hydrogels using soft-lithography and employing microstructured templates, is presented. The main novelty relies on the design and manufacturing processes used for achieving the microstructured templates, which are transferred by soft-lithography, with remarkable level of detail, to the polyacrylamide hydrogels. The conceived process is demonstrated by patterning polyacrylamide substrates with a set of vascular-like and parenchymal-like textures, for controlling cell populations. Final culture of amoeboid cells, whose dynamics is affected by the polyacrylamide patterns, provides a preliminary validation of the described strategy and helps to discuss its potentials.

Hydrogels as artificial matrices for cell seeding in microfluidic devices

Hydrogel-based artificial scaffolds and its incorporation with microfluidic devices play a vital role in shifting in vitro models from two-dimensional (2D) cell culture to in vivo like three-dimensional (3D) cell culture

Human blood platelets contract in perpendicular direction to shear flow

In their physiological environment, blood platelets are permanently exposed to shear forces caused by blood flow. Within this surrounding, they generate contractile forces that eventually lead to a compaction of the blood clot. Here, we present a microfluidic chamber that combines hydrogel-based traction force microscopy with a controlled shear environment, and investigate the force fields platelets generate when exposed to shear flow in a spatio-temporally resolved manner. We find that for shear rates between 14 s-1 to 33 s-1, the general contraction behavior in terms of force distribution and magnitude does not differ from no-flow conditions. The main direction of contraction, however, does respond to the externally applied stress. At high shear stress, we observe an angle of about 90° between flow direction and main contraction axis. We explain this observation by the distribution of the stress acting on the adherent cell: the observed angle provides the most stable situation for the cell experiencing the shear flow, as supported by a finite element method simulation of the stresses along the platelet boundary.

Asymmetric adhesion of rod-shaped bacteria controls microcolony morphogenesis

Surface colonization underpins microbial ecology on terrestrial environments. Although factors that mediate bacteria–substrate adhesion have been extensively studied, their spatiotemporal dynamics during the establishment of microcolonies remains largely unexplored. Here, we use laser ablation and force microscopy to monitor single-cell adhesion during the course of microcolony formation. We find that adhesion forces of the rod-shaped bacteria Escherichia coli and Pseudomonas aeruginosa are polar. This asymmetry induces mechanical tension, and drives daughter cell rearrangements, which eventually determine the shape of the microcolonies. Informed by experimental data, we develop a quantitative model of microcolony morphogenesis that enables the prediction of bacterial adhesion strength from simple time-lapse measurements. Our results demonstrate how patterns of surface colonization derive from the spatial distribution of adhesive factors on the cell envelope.

It is unclear how cell adhesion and elongation coordinate during formation of bacterial microcolonies. Here, Duvernoy et al. monitor microcolony formation in rod-shaped bacteria, and show that patterns of surface colonization derive from the spatial distribution of adhesive factors on the cell envelope.

Microfluidic systems for high-throughput and high-content screening using the nematode Caenorhabditis elegans

In a typical high-throughput drug screening (HTS) process, up to millions of chemical compounds are applied to cells cultured in well plates, aiming to find molecules that exhibit a robust dose-response, as evidenced for example by a fluorescence signal. In high-content screening (HCS), one goes a step further by linking the tested compounds to phenotypic information, obtained, for instance, from microscopic cell images, thereby creating richer data sets that also require more advanced analysis methods. The nematode Caenorhabditis elegans came into the screening picture due to the wide availability of its mutants and human disease models, its relatively easy culture and short life cycle. Being a whole-organism model, it allows drug testing under physiological conditions at multi-tissue levels and provides additional observable phenotypes with respect to cell models, related, for instance, to development, aging, behavior or motility. Worm-based HTS studies in liquid environments on microwell plates have been demonstrated, while microfluidic devices allowed surpassing the performance of plates by enabling more versatile and accurate assays, precise and dynamic dosing of compounds, and readouts down to single-animal resolution. In this review, we discuss microfluidic devices for C. elegans analysis and related studies, published in the period from 2012 to 2017. After an introduction to the different screening approaches, we first focus on microfluidic systems with potential for screening applications. Various enabling technologies, e.g. electrophysiological on-chip recordings or laser axotomy, have been implemented, as well as techniques for reversible worm immobilization and high-resolution imaging, combined with algorithms for automated experimentation and analysis. Several devices for developmental or behavioral assays, and worm sorting based on different phenotypes, have been proposed too. In a subsequent section, we review the application of microfluidic-based systems for medium- and high-throughput screens, including neurobiology and neurodegeneration studies, aging and developmental assays, toxicity and pathogenesis screens, as well as behavioral and motility assays. A thorough analysis of this work reveals a trend towards microfluidic systems more and more capable of offering high-quality analyses of large worm populations, based on multi-phenotypic and/or longitudinal readouts, with clear potential for their application in larger HTS/HCS contexts.

High-throughput screening in the C. elegans nervous system

The nematode Caenorhabditis elegans is widely used as a model organism in the field of neurobiology. The wiring of the C. elegans nervous system has been entirely mapped, and the animal's optical transparency allows for in vivo observation of neuronal activity. The nematode is also small in size, self-fertilizing, and inexpensive to cultivate and maintain, greatly lending to its utility as a whole-animal model for high-throughput screening (HTS) in the nervous system. However, the use of this organism in large-scale screens presents unique technical challenges, including reversible immobilization of the animal, parallel single-animal culture and containment, automation of laser surgery, and high-throughput image acquisition and phenotyping. These obstacles require significant modification of existing techniques and the creation of new C. elegans-based HTS platforms. In this review, we outline these challenges in detail and survey the novel technologies and methods that have been developed to address them.

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domains of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.

Long-term time-lapse microscopy of C. elegans post-embryonic development

We present a microscopy technique that enables long-term time-lapse microscopy at single-cell resolution in moving and feeding Caenorhabditis elegans larvae. Time-lapse microscopy of C. elegans post-embryonic development is challenging, as larvae are highly motile. Moreover, immobilization generally leads to rapid developmental arrest. Instead, we confine larval movement to microchambers that contain bacteria as food, and use fast image acquisition and image analysis to follow the dynamics of cells inside individual larvae, as they move within each microchamber. This allows us to perform fluorescence microscopy of 10-20 animals in parallel with 20 min time resolution. We demonstrate the power of our approach by analysing the dynamics of cell division, cell migration and gene expression over the full ∼48 h of development from larva to adult. Our approach now makes it possible to study the behaviour of individual cells inside the body of a feeding and growing animal.

Microfluidic Approaches for Manipulating, Imaging, and Screening C. elegans

The nematode C. elegans (worm) is a small invertebrate animal widely used in studies related to fundamental biological processes, disease modelling, and drug discovery. Due to their small size and transparent body, these worms are highly suitable for experimental manipulations. In recent years several microfluidic devices and platforms have been developed to accelerate worm handling, phenotypic studies and screens. Here we review major tools and briefly discuss their usage in C. elegans research.

Fitness Trade-Offs in Competence Differentiation of Bacillus subtilis

In the stationary phase, Bacillus subtilis differentiates stochastically and transiently into the state of competence for transformation (K-state). The latter is associated with growth arrest, and it is unclear how the ability to develop competence is stably maintained, despite its cost. To quantify the effect differentiation has on the competitive fitness of B. subtilis, we characterized the competition dynamics between strains with different probabilities of entering the K-state. The relative fitness decreased with increasing differentiation probability both during the stationary phase and during outgrowth. When exposed to antibiotics inhibiting cell wall synthesis, transcription, and translation, cells that differentiated into the K-state showed a selective advantage compared to differentiation-deficient bacteria; this benefit did not require transformation. Although beneficial, the K-state was not induced by sub-MIC concentrations of antibiotics. Increasing the differentiation probability beyond the wt level did not significantly affect the competition dynamics with transient antibiotic exposure. We conclude that the competition dynamics are very sensitive to the fraction of competent cells under benign conditions but less sensitive during antibiotic exposure, supporting the picture of stochastic differentiation as a fitness trade-off.

Single-Cell Analysis of the Dps Response to Oxidative Stress

Microorganisms have developed an elaborate spectrum of mechanisms to respond and adapt to environmental stress conditions. Among these is the expression of dps, coding for the DNA-binding protein from starved cells. Dps becomes the dominant nucleoid-organizing protein in stationary-phase Escherichia coli cells and is required for robust survival under stress conditions, including carbon or nitrogen starvation, oxidative stress, metal exposure, and irradiation. To study the complex regulation of Dps in E. coli, we utilized time-lapse fluorescence microscopy imaging to examine the kinetics, input encoding, and variability of the Dps response in single cells. In the presence of an oxidative stressor, we observed a single pulse of activation of Dps production. Increased concentrations of H2O2 led to increased intensity and duration of the pulse. While lower concentrations of H2O2 robustly activated the Dps response with little effect on the growth rate, higher concentrations of H2O2 resulted in dramatically lower and highly varied growth rates. A comparison of cells exposed to the same concentration of H2O2 revealed that increased levels of Dps expression did not confer a growth advantage, indicating that recovery from stress may rely primarily upon variation in the amount of damage caused to individual cells.

IMPORTANCE

We show for the first time the response of the DNA-binding protein from starved cells (Dps) to oxidative stress in single cells of E. coli Through time-lapse fluorescence microscopy, a single pulse of Dps production is observed in cells exposed to H2O2, with a duration and intensity of induction proportional to the concentration of the applied stress. More intense Dps expression did not provide a growth benefit to the bacteria, suggesting that healing from oxidative stress may largely depend upon the amount of damage in each individual cell.

Microfluidics for High-Throughput Quantitative Studies of Early Development

Developmental biology has traditionally relied on qualitative analyses; recently, however, as in other fields of biology, researchers have become increasingly interested in acquiring quantitative knowledge about embryogenesis. Advances in fluorescence microscopy are enabling high-content imaging in live specimens. At the same time, microfluidics and automation technologies are increasing experimental throughput for studies of multicellular models of development. Furthermore, computer vision methods for processing and analyzing bioimage data are now leading the way toward quantitative biology. Here, we review advances in the areas of fluorescence microscopy, microfluidics, and data analysis that are instrumental to performing high-content, high-throughput studies in biology and specifically in development. We discuss a case study of how these techniques have allowed quantitative analysis and modeling of pattern formation in the Drosophila embryo.

Generation and filtering of gene expression noise by the bacterial cell cycle

Background

Gene expression within cells is known to fluctuate stochastically in time. However, the origins of gene expression noise remain incompletely understood. The bacterial cell cycle has been suggested as one source, involving chromosome replication, exponential volume growth, and various other changes in cellular composition. Elucidating how these factors give rise to expression variations is important to models of cellular homeostasis, fidelity of signal transmission, and cell-fate decisions.

Results

Using single-cell time-lapse microscopy, we measured cellular growth as well as fluctuations in the expression rate of a fluorescent protein and its concentration. We found that, within the population, the mean expression rate doubles throughout the cell cycle with a characteristic cell cycle phase dependent shape which is different for slow and fast growth rates. At low growth rate, we find the mean expression rate was initially flat, and then rose approximately linearly by a factor two until the end of the cell cycle. The mean concentration fluctuated at low amplitude with sinusoidal-like dependence on cell cycle phase. Traces of individual cells were consistent with a sudden two-fold increase in expression rate, together with other non-cell cycle noise. A model was used to relate the findings and to explain the cell cycle-induced variations for different chromosomal positions.

Conclusions

We found that the bacterial cell cycle contribution to expression noise consists of two parts: a deterministic oscillation in synchrony with the cell cycle and a stochastic component caused by variable timing of gene replication. Together, they cause half of the expression rate noise. Concentration fluctuations are partially suppressed by a noise cancelling mechanism that involves the exponential growth of cellular volume. A model explains how the functional form of the concentration oscillations depends on chromosome position.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-016-0231-z) contains supplementary material, which is available to authorized users.