Quantitative characterization of cell behaviors through cell cycle progression via automated cell tracking

Lung extracellular matrix modulates KRT5+ basal cell activity in pulmonary fibrosis

Aberrant expansion of KRT5+ basal cells in the distal lung accompanies progressive alveolar epithelial cell loss and tissue remodelling during fibrogenesis in idiopathic pulmonary fibrosis (IPF). The mechanisms determining activity of KRT5+ cells in IPF have not been delineated. Here, we reveal a potential mechanism by which KRT5+ cells migrate within the fibrotic lung, navigating regional differences in collagen topography. In vitro, KRT5+ cell migratory characteristics and expression of remodelling genes are modulated by extracellular matrix (ECM) composition and organisation. Mass spectrometry- based proteomics revealed compositional differences in ECM components secreted by primary human lung fibroblasts (HLF) from IPF patients compared to controls. Over-expression of ECM glycoprotein, Secreted Protein Acidic and Cysteine Rich (SPARC) in the IPF HLF matrix restricts KRT5+ cell migration in vitro. Together, our findings demonstrate how changes to the ECM in IPF directly influence KRT5+ cell behaviour and function contributing to remodelling events in the fibrotic niche.

Phase intensity nanoscope (PINE) opens long-time investigation windows of living matter

Fundamental to all living organisms and living soft matter are emergent processes in which the reorganization of individual constituents at the nanoscale drives group-level movements and shape changes at the macroscale over time. However, light-induced degradation of fluorophores, photobleaching, is a significant problem in extended bioimaging in life science. Here, we report opening a long-time investigation window by nonbleaching phase intensity nanoscope: PINE. We accomplish phase-intensity separation such that nanoprobe distributions are distinguished by an integrated phase-intensity multilayer thin film (polyvinyl alcohol/liquid crystal). We overcame a physical limit to resolve sub-10 nm cellular architectures, and achieve the first dynamic imaging of nanoscopic reorganization over 250 h using PINE. We discover nanoscopic rearrangements synchronized with the emergence of group-level movements and shape changes at the macroscale according to a set of interaction rules with importance in cellular and soft matter reorganization, self-organization, and pattern formation.

Optoelectronic Trajectory Reconfiguration and Directed Self-Assembly of Self-Propelling Electrically Powered Active Particles

Self-propelling active particles are an exciting and interdisciplinary emerging area of research with projected biomedical and environmental applications. Due to their autonomous motion, control over these active particles that are free to travel along individual trajectories, is challenging. This work uses optically patterned electrodes on a photoconductive substrate using a digital micromirror device (DMD) to dynamically control the region of movement of self-propelling particles (i.e., metallo-dielectric Janus particles (JPs)). This extends previous studies where only a passive micromotor is optoelectronically manipulated with a translocating optical pattern that illuminates the particle. In contrast, the current system uses the optically patterned electrode merely to define the region within which the JPs moved autonomously. Interestingly, the JPs avoid crossing the optical region's edge, which enables constraint of the area of motion and to dynamically shape the JP trajectory. Using the DMD system to simultaneously manipulate several JPs enables to self-assemble the JPs into stable active structures (JPs ring) with precise control over the number of participating JPs and passive particles. Since the optoelectronic system is amenable to closed-loop operation using real-time image analysis, it enables exploitation of these active particles as active microrobots that can be operated in a programmable and parallelized manner.

CoFee-L: A Model of Animal Displacement in Large Groups Combining Cohesion Maintenance, Feeding Area Search and Transient Leadership

Simple Summary

In the current context of climate change and forest cover degradation, the dispersal potential of trees is an issue of great importance. This is particularly the case in the tropics, where trees often need animals to disperse their seeds, as this increases the chances of survival of the progeny and allows migration in the face of climate change. An accurate representation of animal movement is therefore necessary to study the colonization potential of trees in new areas. We have conceived an innovative mathematical model describing the individual movement of gregarious animals, integrating several fundamental features of collective behaviors: cohesion maintenance, feeding area search and leadership. The model was applied to simulate the movements of a wild-ranging troop of primates in a nature reserve. As a result, the model allowed us to simulate the movement of the troop, taking into account the movement and individual characteristics of each member, which is important to consider when the group is composed of many individuals. In the future, this model could be used to improve existing zoochoric seed dispersal models and can be coupled with dynamic vegetation models to predict the shifts of trees species distribution under future climate hypotheses.

Abstract

In the tropics, the conservation of tree species is closely linked to that of animals, as a large proportion of trees are zoochoric and therefore rely on the movement of animals to disperse their seeds in order to increase the chances of the survival of progeny and to allow migration in the face of climate change. Research into the prediction of animal movements is therefore critical but has so far focused only on particular features of collective behavior. In contrast, we included the concepts of cohesion maintenance, feeding area search and transient leadership in a single model, CoFee-L, and tested it to simulate the movement of a wild-ranging troop of primates (Macaca leonina). We analyzed and compared observations and simulations with a statistical physics tool (mean squared displacement) and with histograms and χ² (for the step length and turning angle distributions). CoFee-L allowed us to simulate the physical properties of the troop’s center of mass trajectory as well as the step length and angle distributions of the field data. The parametrization of CoFee-L was rather straightforward, as it was sufficient to fix a set of parameters easily observable in the field and then to adjust the values of four parameters that have biological meaning.

High-Resolution Low-Power Hyperspectral Line-Scan Imaging of Fast Cellular Dynamics Using Azo-Enhanced Raman Scattering Probes

Small-molecule Raman probes for cellular imaging have attracted great attention owing to their sharp peaks that are sensitive to environmental changes. The small cross section of molecular Raman scattering limits dynamic cellular Raman imaging to expensive and complex coherent approaches that acquire single-channel images and lose hyperspectral Raman information. We introduce a new method, dynamic azo-enhanced Raman imaging (DAERI), to couple the new class of azo-enhanced Raman probes with a high-speed line-scan Raman imaging system. DAERI achieved high-resolution low-power imaging of fast cellular dynamics resolved at ∼270 nm along the confocal direction, 75 μW/μm² and 3.5 s/frame. Based on the azo-enhanced Raman probes with characteristic signals 10²-10⁴ stronger than classic Raman labels, DAERI was not restricted to the cellular Raman-silent region as in prior work and enabled multiplex visualization of organelle motions and interactions. We anticipate DAERI to be a powerful tool for future studies in biophysics and cell biology.

FUCCItrack: An all-in-one software for single cell tracking and cell cycle analysis

Beyond the more conventional single-cell segmentation and tracking, single-cell cycle dynamics is gaining a growing interest in the field of cell biology. Thanks to sophisticated systems, such as the fluorescent ubiquitination-based cell cycle indicator (FUCCI), it is now possible to study cell proliferation, migration, changes in nuclear morphology and single cell cycle dynamics, quantitatively and in real time. In this work, we introduce FUCCItrack, an all-in-one, semi-automated software to segment, track and visualize FUCCI modified cell lines. A user-friendly complete graphical user interface is presented to record and quantitatively analyze both collective cell proliferation as well as single cell information, including migration and changes in nuclear or cell morphology as a function of cell cycle. To enable full control over the analysis, FUCCItrack also contains features for identification of errors and manual corrections.

Rab11A regulates dense granule transport and secretion during Toxoplasma gondii invasion of host cells and parasite replication

Toxoplasma gondii possesses an armada of secreted virulent factors that enable parasite invasion and survival into host cells. These factors are contained in specific secretory organelles, the rhoptries, micronemes and dense granules that release their content upon host cell recognition. Dense granules are secreted in a constitutive manner during parasite replication and play a crucial role in modulating host metabolic and immune responses. While the molecular mechanisms triggering rhoptry and microneme release upon host cell adhesion have been well studied, constitutive secretion remains a poorly explored aspect of T. gondii vesicular trafficking. Here, we investigated the role of the small GTPase Rab11A, a known regulator of exocytosis in eukaryotic cells. Our data revealed an essential role of Rab11A in promoting the cytoskeleton driven transport of dense granules and the release of their content into the vacuolar space. Rab11A also regulates transmembrane protein trafficking and localization during parasite replication, indicating a broader role of Rab11A in cargo exocytosis at the plasma membrane. Moreover, we found that Rab11A also regulates extracellular parasite motility and adhesion to host cells. In line with these findings, MIC2 secretion was altered in Rab11A-defective parasites, which also exhibited severe morphological defects. Strikingly, by live imaging we observed a polarized accumulation of Rab11A-positive vesicles and dense granules at the apical pole of extracellular motile and invading parasites suggesting that apically polarized Rab11A-dependent delivery of cargo regulates early secretory events during parasite entry into host cells.

Toxoplasma gondii (T. gondii) is a highly prevalent parasite infecting a wide range of animals as well as humans. T. gondii secretes numerous virulent factors contained in specific organelles, termed the rhoptries, micronemes and dense granules. These factors are released upon host cell recognition and enable parasite invasion and subsequent development into an intracellular vacuole. In particular, dense granules contain critical effectors that modulate intrinsic defenses of infected host cells ensuring parasite survival and dissemination. The mechanisms regulating dense granule secretion have not been elucidated. In this study, we unraveled a novel role for the T. gondii GTPase Rab11A in promoting dense granule transport along the parasite cytoskeleton and their content release into the vacuolar space during parasite replication. We also found that T. gondii Rab11A regulates extracellular parasite motility and adhesion to host cells suggesting a broader role in distinct secretory pathways essential for parasite virulence.

Quantifying Cell Confluency by Plasmonic Nanodot Arrays to Achieve Cultivating Consistency

The determination of cell confluency and subculture timing for cell culture consistency is crucial in the field of cell-based research, but there is no universal standard concerning optimal confluence. In this study, gold nanodot arrays on glass substrates were used as culture substrates, and their spectral shifts of localized surface plasmon resonance (LSPR) were employed to monitor cell growth and quantify cell confluency. Experiments including cell counting, metabolic activity, focal adhesion, and cell cycle were also performed to confirm the cell growth monitoring accuracy of the LSPR signals. The LSPR signal exhibited the same trends like the increase of cell numbers and cell metabolic activity and reached the maximum as the cell growth achieved confluency, suggesting its great capability as an effective indicator to predict suitable subculture timing. The proposed sensing approach is a noninterventional, nondestructive, real-time, and useful tool to help biologists quantify the optimal subculture timing, achieve cell culture consistency, and obtain reproducible experimental results efficiently.

Quantitative assessment of cell contractility using polarized light microscopy

Cell contractility regulates multiple cell behaviors which contribute to both normal and pathological processes. However, measuring cell contractility remains a technical challenge in complex biological samples. The current state of the art technologies employed to measure cell contractility have inherent limitations that greatly limit the experimental conditions under which they can be used. Here, we use quantitative polarization microscopy to extract information about cell contractility. We show that the optical retardance signal measured from the cell body is proportional to cell contractility in 2-dimensional and 3-dimensional platforms, and as such can be used as a straightforward, tractable methodology to assess cell contractility in a variety of systems. This label-free optical method provides a novel and flexible way to assess cellular forces of single cells and monolayers in several cell types, fixed or live, in addition to cells present in situ in mouse tumor tissue samples. This easily implementable and experimentally versatile method will significantly contribute to the cell mechanics field.

Large-scale patterning of single cells and cell clusters in hydrogels

Biophysical properties of the extracellular matrix (ECM) are known to play a significant role in cell behavior. To gain a better understanding of the effects of the biophysical microenvironment on cell behavior, the practical challenge is longitudinally monitoring behavioral variations within a population to make statistically powerful assessments. Population-level measurements mask heterogeneity in cell responses, and large-scale individual cell measurements are often performed in a one-time, snapshot manner after removing cells from their matrix. Here we present an easy and low-cost method for large-scale, longitudinal studies of heterogeneous cell behavior in 3D hydrogel matrices. Using a platform we term "the drop-patterning chip", thousands of cells were simultaneously transferred from microwell arrays and fully embedded, only using the force of gravity, in precise patterns in 3D collagen I or Matrigel. This method allows for throughputs approaching 2D patterning methods that lack phenotypic information on cell-matrix interactions, and does not rely on special equipment and cell treatments that may result in a proximal stiff surface. With a large and yet well-organized group of cells captured in 3D matrices, we demonstrated the capability of locating selected individual cells and monitoring cell division, migration, and proliferation for multiple days.

Segmentation of clustered cells in negative phase contrast images with integrated light intensity and cell shape information

Automated cell segmentation plays a key role in characterisations of cell behaviours for both biology research and clinical practices. Currently, the segmentation of clustered cells still remains as a challenge and is the main reason for false segmentation. In this study, the emphasis was put on the segmentation of clustered cells in negative phase contrast images. A new method was proposed to combine both light intensity and cell shape information through the construction of grey-weighted distance transform (GWDT) within preliminarily segmented areas. With the constructed GWDT, the clustered cells can be detected and then separated with a modified region skeleton-based method. Moreover, a contour expansion operation was applied to get optimised detection of cell boundaries. In this paper, the working principle and detailed procedure of the proposed method are described, followed by the evaluation of the method on clustered cell segmentation. Results show that the proposed method achieves an improved performance in clustered cell segmentation compared with other methods, with 85.8% and 97.16% accuracy rate for clustered cells and all cells, respectively.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.