scholarly journals Learning the rules of cell competition without prior scientific knowledge

2021 ◽  
Author(s):  
Christopher Soelistyo ◽  
Giulia Vallardi ◽  
Guillaume Charras ◽  
Alan R Lowe
Keyword(s):  
Cell Fate ◽  
Internal Representation ◽  
Correct Prediction ◽  
Physical Parameters ◽  
Cell Competition ◽  
Normal Behaviour ◽  
Tissue Organization ◽  
Machine Learning Model ◽  
Microscopy Data ◽  
Quality Control Mechanism

Deep learning is now a powerful tool in microscopy data analysis, and is routinely used for image processing applications such as segmentation and denoising. However, it has rarely been used to directly learn mechanistic models of a biological system, owing to the complexity of the internal representations. Here, we develop an end-to-end machine learning model capable of learning the rules of a complex biological phenomenon, cell competition, directly from a large corpus of timelapse microscopy data. Cell competition is a quality control mechanism that eliminates unfit cells from a tissue and during which cell fate is thought to be determined by the local cellular neighborhood over time. To investigate this, we developed a new approach (τ-VAE) by coupling a variational autoencoder to a temporal convolution network to predict the fate of each cell in an epithelium. Using the τ-VAE's latent representation of the local tissue organization and the flow of information in the network, we decode the physical parameters responsible for correct prediction of fate in cell competition. Remarkably, the model autonomously learns that cell density is the single most important factor in predicting cell fate -- a conclusion that has taken over a decade of traditional experimental research to reach. Finally, to test the learned internal representation, we challenge the network with experiments performed in the presence of drugs that block signalling pathways involved in competition. We present a novel discriminator network that, using the predictions of the τ-VAE, can identify conditions which deviate from the normal behaviour, paving the way for automated, mechanism-aware drug screening.

scholarly journals Local cellular neighborhood controls proliferation in cell competition

2017 ◽  
Vol 28 (23) ◽  
pp. 3215-3228 ◽  
Author(s):  
Anna Bove ◽  
Daniel Gradeci ◽  
Yasuyuki Fujita ◽  
Shiladitya Banerjee ◽  
Guillaume Charras ◽  
...  
Keyword(s):  
Single Cell ◽  
Local Density ◽  
Differential Sensitivity ◽  
Cell Type ◽  
Cell Competition ◽  
High Throughput Analysis ◽  
Tissue Organization ◽  
Scale Population ◽  
Quality Control Mechanism

Cell competition is a quality-control mechanism through which tissues eliminate unfit cells. Cell competition can result from short-range biochemical inductions or long-range mechanical cues. However, little is known about how cell-scale interactions give rise to population shifts in tissues, due to the lack of experimental and computational tools to efficiently characterize interactions at the single-cell level. Here, we address these challenges by combining long-term automated microscopy with deep-learning image analysis to decipher how single-cell behavior determines tissue makeup during competition. Using our high-throughput analysis pipeline, we show that competitive interactions between MDCK wild-type cells and cells depleted of the polarity protein scribble are governed by differential sensitivity to local density and the cell type of each cell’s neighbors. We find that local density has a dramatic effect on the rate of division and apoptosis under competitive conditions. Strikingly, our analysis reveals that proliferation of the winner cells is up-regulated in neighborhoods mostly populated by loser cells. These data suggest that tissue-scale population shifts are strongly affected by cellular-scale tissue organization. We present a quantitative mathematical model that demonstrates the effect of neighbor cell–type dependence of apoptosis and division in determining the fitness of competing cell lines.

scholarly journals Design and Development of Lubricating Material Database and Research on Performance Prediction Method of Machine Learning

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Dan Jia ◽  
Haitao Duan ◽  
Shengpeng Zhan ◽  
Yongliang Jin ◽  
Bingxue Cheng ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Performance ◽  
Prediction Method ◽  
Lubricating Oil ◽  
Physical Parameters ◽  
First Principle ◽  
Vast Number ◽  
First Principle Calculation ◽  
Lubricating Material ◽  
Machine Learning Model

AbstractLong developing period and cumbersome evaluation for the lubricating materials performance seriously jeopardize the successful development and application of any database system in tribological field. Such major setback can be solved effectively by implementing approaches with high throughput calculation. However, it often involves with vast number of output files, which are computed on the basis of first principle computation, having different data format from that of their experimental counterparts. Commonly, the input, storage and management of first principle calculation files and their individually test counterparts, implementing fast query and display in the database, adding to the use of physical parameters, as predicted with the performance estimated by first principle approach, may solve such setbacks. Investigation is thus performed for establishing database website specifically for lubricating materials, which satisfies both data: (i) as calculated on the basis of first principles and (ii) as obtained by practical experiment. It further explores preliminarily the likely relationship between calculated physical parameters of lubricating oil and its respectively tribological and anti-oxidative performance as predicted by lubricant machine learning model. Success of the method facilitates in instructing the obtainment of optimal design, preparation and application for any new lubricating material so that accomplishment of high performance is possible.

scholarly journals Active elimination of intestinal cells drives oncogenic growth in organoids

2020 ◽  
Author(s):  
Ana Krotenberg Garcia ◽  
Arianna Fumagalli ◽  
Huy Quang Le ◽  
Owen J. Sansom ◽  
Jacco van Rheenen ◽  
...  
Keyword(s):  
Quality Control ◽  
Cell Death ◽  
Cancer Cells ◽  
Cell Fate ◽  
Crucial Role ◽  
Intestinal Cells ◽  
Dependent Manner ◽  
Wild Type ◽  
Cell Competition ◽  
Type Population

AbstractCompetitive cell-interactions play a crucial role in quality control during development and homeostasis. Here we show that cancer cells use such interactions to actively eliminate wild-type intestine cells in enteroid monolayers and organoids. This apoptosis-dependent process boosts proliferation of intestinal cancer cells. The remaining wild-type population activates markers of primitive epithelia and transits to a fetal-like state. Prevention of this cell fate transition avoids elimination of wild-type cells and, importantly, limits the proliferation of cancer cells. JNK signalling is activated in competing cells and is required for cell fate change and elimination of wild-type cells. Thus, cell competition drives growth of cancer cells by active out-competition of wild-type cells through forced cell death and cell fate change in a JNK dependent manner.

Integrin Structure

2000 ◽  
Vol 28 (4) ◽  
pp. 311-340 ◽  
Author(s):  
M.J. Humphries
Keyword(s):  
Cell Fate ◽  
Molecular Basis ◽  
Tertiary Structure ◽  
Cellular Migration ◽  
Model Studies ◽  
Physical Support ◽  
Tissue Organization ◽  
Wide Range ◽  
Ligand Interactions ◽  
Almost All

The integrins are a family of α,β heterodimeric receptors that mediate dynamic linkages between extracellular adhesion molecules and the intracellular actin cytoskeleton. Integrins are expressed by all multicellular animals, but their diversity varies widely among species; for example, in mammals, 19 α and 8β subunit genes encode polypeptides that combine to form 25 different receptors, whereas the Drosophila and Caenorhabditis genomes encode only five and two integrin a subunits respectively. Thousands of studies over the last two decades have investigated the molecular, cellular and organismal basis of integrin function. Gene deletion has demonstrated essential roles for almost all integrins, with the defects suggesting widespread contributions to both the maintenance of tissue integrity and the promotion of cellular migration. Integrin-ligand interactions are now considered to provide physical support for cells in order to maintain cohesion, to permit the generation of traction forces to enable movement, and to organize signalling complexes to modulate differentiation and cell fate. Animal-model studies have also shown that integrins contribute to the progression of many common diseases, and have implicated them as potential therapeutic targets. The use of anti-integrin monoclonal antibodies and ligand-mimetic peptides has validated this suggestion for inflammatory, neoplastic, traumatic and infectious conditions. Thus, to understand more about the mechanisms underlying tissue organization and cellular trafficking, and to identify approaches for regulating these processes in disease, there is intense interest in determining the molecular basis of integrin function. It is important to state at the outset that the tertiary structure of the integrin dimer is unknown. Our current understanding of the molecular basis of integrin function is therefore compiled from the results of a large number of studies that have employed a wide range of complementary technologies.

scholarly journals Collective MAPK Signaling Dynamics Coordinates Epithelial Homeostasis

2019 ◽  
Author(s):  
Timothy J. Aikin ◽  
Amy F. Peterson ◽  
Michael J. Pokrass ◽  
Helen R. Clark ◽  
Sergi Regot
Keyword(s):  
Cell Fate ◽  
Temporal Patterns ◽  
Mapk Signaling ◽  
Paracrine Signaling ◽  
Cell Behaviors ◽  
Cell Fate Decisions ◽  
Epithelial Tissues ◽  
Mapk Activity ◽  
Signaling Axis ◽  
Quality Control Mechanism

ABSTRACTEpithelial tissues are constantly challenged by individual cell fate decisions while maintaining barrier function. During oncogenesis, mutant and normal cells also differ in their signaling states and cellular behaviors creating competitive interactions that are poorly understood. Here we show that the temporal patterns of MAPK activity are decoded by the ADAM17-EGFR paracrine signaling axis to coordinate migration of neighboring cells and promote extrusion of aberrantly-signaling cells. Concurrently, neighboring cells increase proliferation to maintain cell density while oncogene expressing cells undergo cell cycle arrest. Moreover, the stress MAPK p38 elicits the same paracrine signaling and extrusion response, suggesting that the ADAM17-EGFR pathway constitutes a quality control mechanism to eliminate and replace unfit cells from epithelial tissues. Overall, we show that the temporal patterns of MAPK activity coordinates both single and collective cell behaviors to maintain tissue homeostasis.

scholarly journals Development of a Sensor Node for Remote Monitoring of Plants

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4865 ◽  
Author(s):  
Alexandro Catini ◽  
Leonardo Papale ◽  
Rosamaria Capuano ◽  
Valentina Pasqualetti ◽  
Davide Di Giuseppe ◽  
...  
Keyword(s):  
Plant Stress ◽  
Optimal Solution ◽  
Environmental Parameters ◽  
High Sensitivity ◽  
Sensor Nodes ◽  
Physical Parameters ◽  
Total Volatile ◽  
Stress Monitoring ◽  
Machine Learning Model ◽  
Total Volatile Organic Compounds

The appraisal of stress in plants is of great relevance in agriculture and any time the transport of living plants is involved. Wireless sensor networks (WSNs) are an optimal solution to simultaneously monitor a large number of plants in a mostly automatic way. A number of sensors are readily available to monitor indicators that are likely related to stress. The most common of them include the levels of total volatile compounds and CO2 together with common physical parameters such as temperature, relative humidity, and illumination, which are known to affect plants’ behavior. Recent progress in microsensors and communication technologies, such as the LoRa protocol, makes it possible to design sensor nodes of high sensitivity where power consumption, transmitting distances, and costs are optimized. In this paper, the design of a WSN dedicated to plant stress monitoring is described. The nodes have been tested on European privet (Ligustrum Jonandrum) kept in completely different conditions in order to induce opposite level of stress. The results confirmed the relationship between the release of total Volatile Organic Compounds (VOCs) and the environmental conditions. A machine learning model based on recursive neural networks demonstrates that total VOCs can be estimated from the measure of the environmental parameters.

scholarly journals An Efficient Intestinal Organoid System of Direct Sorting to Evaluate Stem Cell Competition in Vitro

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yuki Fujimichi ◽  
Kensuke Otsuka ◽  
Masanori Tomita ◽  
Toshiyasu Iwasaki
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Fluorescent Protein ◽  
Lineage Tracing ◽  
Cell Competition ◽  
Quality Control Mechanism ◽  
Green Fluorescent ◽  
G Protein Coupled ◽  
Culture Protocol

AbstractStem cell competition could shed light on the tissue-based quality control mechanism that prevents carcinogenesis. To quantitatively evaluate stem cell competition in vitro, we developed a two-color intestinal organoid forming system. First, we improved a protocol of culturing organoids from intestinal leucine-rich-repeat containing G-protein-coupled receptor 5 (Lgr5)- enhanced green fluorescent protein (EGFP)high stem cells directly sorted on Matrigel without embedding. The organoid-forming potential (OFP) was 25% of Lgr5-EGFPhigh cells sorted at one cell per well. Using this culture protocol with lineage tracing, we established a two-color organoid culture system by mixing stem cells expressing different fluorescent colors. To analyze stem cell competition, two-color organoids were formed by mixing X-ray-irradiated and non-irradiated intestinal stem cells. In the two-color organoids, irradiated stem cells exhibited a growth disadvantage, although the OFP of irradiated cells alone did not decrease significantly from that of non-irradiated cells. These results suggest that stem cell competition can be evaluated quantitively in vitro using our new system.

scholarly journals Mitotic spindle (DIS)orientation and DISease: Cause or consequence?

2012 ◽  
Vol 199 (7) ◽  
pp. 1025-1035 ◽  
Author(s):  
Anna Noatynska ◽  
Monica Gotta ◽  
Patrick Meraldi
Keyword(s):  
Cell Proliferation ◽  
Cell Fate ◽  
Mitotic Spindle ◽  
Brain Diseases ◽  
Spindle Orientation ◽  
Cell Fate Determination ◽  
Cellular Functions ◽  
Tissue Organization ◽  
Asymmetric Divisions ◽  
Correct Alignment

Correct alignment of the mitotic spindle during cell division is crucial for cell fate determination, tissue organization, and development. Mutations causing brain diseases and cancer in humans and mice have been associated with spindle orientation defects. These defects are thought to lead to an imbalance between symmetric and asymmetric divisions, causing reduced or excessive cell proliferation. However, most of these disease-linked genes encode proteins that carry out multiple cellular functions. Here, we discuss whether spindle orientation defects are the direct cause for these diseases, or just a correlative side effect.

scholarly journals Histological, immunohistochemical and transcriptomic characterization of human tracheoesophageal fistulas

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242167
Author(s):  
Erwin Brosens ◽  
Janine F. Felix ◽  
Anne Boerema-de Munck ◽  
Elisabeth M. de Jong ◽  
Elisabeth M. Lodder ◽  
...  
Keyword(s):  
Smooth Muscle ◽  
Cell Fate ◽  
Expression Patterns ◽  
Cell Types ◽  
Smooth Muscle Contraction ◽  
Bmp Signaling ◽  
Tissue Type ◽  
Tissue Organization ◽  
Specific Tissue ◽  
Control Samples

Esophageal atresia (EA) and tracheoesophageal fistula (TEF) are relatively frequently occurring foregut malformations. EA/TEF is thought to have a strong genetic component. Not much is known regarding the biological processes disturbed or which cell type is affected in patients. This hampers the detection of the responsible culprits (genetic or environmental) for the origin of these congenital anatomical malformations. Therefore, we examined gene expression patterns in the TEF and compared them to the patterns in esophageal, tracheal and lung control samples. We studied tissue organization and key proteins using immunohistochemistry. There were clear differences between TEF and control samples. Based on the number of differentially expressed genes as well as histological characteristics, TEFs were most similar to normal esophagus. The BMP-signaling pathway, actin cytoskeleton and extracellular matrix pathways are downregulated in TEF. Genes involved in smooth muscle contraction are overexpressed in TEF compared to esophagus as well as trachea. These enriched pathways indicate myofibroblast activated fibrosis. TEF represents a specific tissue type with large contributions of intestinal smooth muscle cells and neurons. All major cell types present in esophagus are present—albeit often structurally disorganized—in TEF, indicating that its etiology should not be sought in cell fate specification.

scholarly journals The Emerging Role of the RBM20 and PTBP1 Ribonucleoproteins in Heart Development and Cardiovascular Diseases

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 402 ◽  
Author(s):  
Stefania Fochi ◽  
Pamela Lorenzi ◽  
Marilisa Galasso ◽  
Chiara Stefani ◽  
Elisabetta Trabetti ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Cell Fate ◽  
Heart Development ◽  
Cardiac Tissue ◽  
Altered Expression ◽  
Tissue Organization ◽  
Polypyrimidine Tract Binding Protein ◽  
Human Genes ◽  
Alternative Splicing Events ◽  
And Function

Alternative splicing is a regulatory mechanism essential for cell differentiation and tissue organization. More than 90% of human genes are regulated by alternative splicing events, which participate in cell fate determination. The general mechanisms of splicing events are well known, whereas only recently have deep-sequencing, high throughput analyses and animal models provided novel information on the network of functionally coordinated, tissue-specific, alternatively spliced exons. Heart development and cardiac tissue differentiation require thoroughly regulated splicing events. The ribonucleoprotein RBM20 is a key regulator of the alternative splicing events required for functional and structural heart properties, such as the expression of TTN isoforms. Recently, the polypyrimidine tract-binding protein PTBP1 has been demonstrated to participate with RBM20 in regulating splicing events. In this review, we summarize the updated knowledge relative to RBM20 and PTBP1 structure and molecular function; their role in alternative splicing mechanisms involved in the heart development and function; RBM20 mutations associated with idiopathic dilated cardiovascular disease (DCM); and the consequences of RBM20-altered expression or dysfunction. Furthermore, we discuss the possible application of targeting RBM20 in new approaches in heart therapies.

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