scholarly journals Cell-cycle-gated feedback control mediates desensitization to interferon stimulation

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Anusorn Mudla ◽  
Yanfei Jiang ◽  
Kei-ichiro Arimoto ◽  
Bingxian Xu ◽  
Adarsh Rajesh ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Regulatory Network ◽  
Feedback Loop ◽  
Single Cells ◽  
Time Lapse ◽  
Feedback Loops ◽  
Type I ◽  
Induction Kinetics ◽  
Treatment Onset ◽  
Fast Acting

Cells use molecular circuits to interpret and respond to extracellular cues, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the type I interferon (IFN)-responsive regulatory network operates in single human cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1/early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback loops, enabling duration-dependent desensitization to repetitive stimulations.

scholarly journals Cell cycle-gated feedback control mediates desensitization to interferon stimulation

2020 ◽  
Author(s):  
Anusorn Mudla ◽  
Yanfei Jiang ◽  
Kei-ichiro Arimoto ◽  
Bingxian Xu ◽  
Adarsh Rajesh ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Feedback Control ◽  
Regulatory Network ◽  
Feedback Loop ◽  
Single Cells ◽  
Time Lapse ◽  
Type I ◽  
Induction Kinetics ◽  
Extracellular Signal ◽  
Treatment Onset

AbstractCells use sophisticated molecular circuits to interpret and respond to extracellular signal factors, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we focus on type I interferon (IFN) signaling in human epithelial cells and combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the IFN-responsive regulatory network operates in single cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on the input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1 and early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback control processes, enabling duration-dependent desensitization to repetitive stimulations. Moreover, our results, highlighting the importance of IFN dynamics, may suggest time-based strategies for enhancing the effectiveness of IFN pretreatment in clinical applications against viruses, such as SARS-CoV-2.

scholarly journals pcnaDeep: A Fast and Robust Single-Cell Tracking Method Using Deep-Learning Mediated Cell Cycle Profiling

2021 ◽  
Author(s):  
Yifan Gui ◽  
Shuang Shuang Xie ◽  
Yanan Wang ◽  
Ping Wang ◽  
Renzhi Yao ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Deep Learning ◽  
Single Cell ◽  
Cell Tracking ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Time Lapse ◽  
Molecular Control ◽  
A Cell ◽  
User Friendly

Motivation: Computational methods that track single-cells and quantify fluorescent biosensors in time-lapse microscopy images have revolutionised our approach in studying the molecular control of cellular decisions. One barrier that limits the adoption of single-cell analysis in biomedical research is the lack of efficient methods to robustly track single-cells over cell division events. Results: Here, we developed an application that automatically tracks and assigns mother-daughter relationships of single-cells. By incorporating cell cycle information from a well-established fluorescent cell cycle reporter, we associate mitosis relationships enabling high fidelity long-term single-cell tracking. This was achieved by integrating a deep-learning based fluorescent PCNA signal instance segmentation module with a cell tracking and cell cycle resolving pipeline. The application offers a user-friendly interface and extensible APIs for customized cell cycle analysis and manual correction for various imaging configurations. Availability and Implementation: pcnaDeep is an open-source Python application under the Apache 2.0 licence. The source code, documentation and tutorials are available at https://github.com/chan-labsite/PCNAdeep.

scholarly journals Long-term live cell cycle imaging of single Cyanidioschyzon merolae cells

PROTOPLASMA ◽  
2021 ◽  
Author(s):  
Takako M. Ichinose ◽  
Atsuko H. Iwane
Keyword(s):  
Cell Cycle ◽  
Environmental Changes ◽  
Single Cells ◽  
Model Organism ◽  
Time Lapse ◽  
Live Cell ◽  
Observation System ◽  
Cyanidioschyzon Merolae ◽  
Morphological Studies

AbstractLive cell imaging by fluorescence microscopy is a useful tool for elucidating the localization and function of proteins and organelles in single cells. Especially, time-lapse analysis observing the same field sequentially can be used to observe cells of many organisms and analyze the dynamics of intracellular molecules. By single-cell analysis, it is possible to elucidate the characteristics and fluctuations of individual cells, which cannot be elucidated from the data obtained by averaging the characteristics of an ensemble of cells. The primitive red alga Cyanidioschyzon merolae has a very simple structure and is considered a useful model organism for studying the mechanism of organelle division, since the division is performed synchronously with the cell cycle. However, C. merolae does not have a rigid cell wall, and environmental changes such as low temperature or high pH cause morphological change and disruption easily. Therefore, morphological studies of C. merolae typically use fixed cells. In this study, we constructed a long-term time-lapse observation system to analyze the dynamics of proteins in living C. merolae cells. From the results, we elucidate the cell division process of single living cells, including the function of intracellular components.

scholarly journals Matrix degradation and cell proliferation are coupled to promote invasion and escape from an engineered human breast microtumor

2021 ◽  
Vol 13 (1) ◽  
pp. 17-29
Author(s):  
Emann M Rabie ◽  
Sherry X Zhang ◽  
Andreas P Kourouklis ◽  
A Nihan Kilinc ◽  
Allison K Simi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Type I ◽  
Matrix Degradation ◽  
Human Breast ◽  
Rate Of Invasion

Abstract Metastasis, the leading cause of mortality in cancer patients, depends upon the ability of cancer cells to invade into the extracellular matrix that surrounds the primary tumor and to escape into the vasculature. To investigate the features of the microenvironment that regulate invasion and escape, we generated solid microtumors of MDA-MB-231 human breast carcinoma cells within gels of type I collagen. The microtumors were formed at defined distances adjacent to an empty cavity, which served as an artificial vessel into which the constituent tumor cells could escape. To define the relative contributions of matrix degradation and cell proliferation on invasion and escape, we used pharmacological approaches to block the activity of matrix metalloproteinases (MMPs) or to arrest the cell cycle. We found that blocking MMP activity prevents both invasion and escape of the breast cancer cells. Surprisingly, blocking proliferation increases the rate of invasion but has no effect on that of escape. We found that arresting the cell cycle increases the expression of MMPs, consistent with the increased rate of invasion. To gain additional insight into the role of cell proliferation in the invasion process, we generated microtumors from cells that express the fluorescent ubiquitination-based cell cycle indicator. We found that the cells that initiate invasions are preferentially quiescent, whereas cell proliferation is associated with the extension of invasions. These data suggest that matrix degradation and cell proliferation are coupled during the invasion and escape of human breast cancer cells and highlight the critical role of matrix proteolysis in governing tumor phenotype.

scholarly journals Stochasticity in Colonial Growth Dynamics of Individual Bacterial Cells

2013 ◽  
Vol 79 (7) ◽  
pp. 2294-2301 ◽  
Author(s):  
Konstantinos P. Koutsoumanis ◽  
Alexandra Lianou
Keyword(s):  
Kinetic Parameters ◽  
Single Cells ◽  
Growth Curves ◽  
Growth Dynamics ◽  
Time Lapse ◽  
Initial Population ◽  
Bacterial Cells ◽  
Stochastic Growth ◽  
Bacterial Populations ◽  
Content Type

ABSTRACTConventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells ofSalmonella entericaserotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time (λ) and maximum specific growth rate (μmax) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size (N0). For bacterial populations withN0of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations.

Sign in / Sign up

Export Citation Format

Share Document