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Related Concept Videos

Autophagy01:27

Autophagy

Autophagy is a self-digesting process by which a cell protects itself from threats both within and outside the cell, ranging from abnormal proteins to invading bacteria. In this process, obsolete components of the cell and invading microbes are degraded by hydrolytic enzymes active in an acidic environment of the lysosomal lumen.
An autophagic pathway consists of a series of signaling events activated in response to diverse stress and physiological conditions such as food deprivation,...
Delivery Pathways to the Lysosome01:36

Delivery Pathways to the Lysosome

Eukaryotic cells use different mechanisms to eliminate toxic waste obsolete and worn-out substances. Lysosomes play a pivotal role in this, and hence, these substances are carried to the lysosome from other parts of the cell and extracellular space through different pathways. The most elaborately studied pathways to the lysosome are the endocytic pathways.
Endocytosis
In endocytosis, the cell membrane takes up macromolecules and particles from the surrounding medium. Clathrin-mediated...
Autophagic Cell Death01:18

Autophagic Cell Death

Christian de Duve discovered “autophagy,” a process in which cellular components are engulfed by membrane-bound organelles called autophagosomes. The autophagosomes then fuse with lysosomes to digest the enclosed contents. Autophagy is generally activated in cells to prevent cell death. However, cell death is triggered when the damage is beyond repair.
Autophagy and Apoptosis
Autophagy can activate apoptosis. In normal conditions, the autophagy activating protein Beclin-1 and pro-apoptotic...
The Movement of Organelles and Vesicles01:43

The Movement of Organelles and Vesicles

In eukaryotic cells,  cytoskeletal filaments such as actin, microtubules, and intermediate filaments form a mesh-like cytoskeletal network. These filaments serve as tracks for transporting cellular cargo. Specialized motor proteins use the chemical energy stored in adenosine triphosphate (ATP) for this transport. During interphase, microtubules are polarized, with the plus-end towards the cell periphery and the minus-end towards the cell center. Two microtubule-associated motor proteins,...
Intralumenal Vesicles and Multivesicular Bodies01:38

Intralumenal Vesicles and Multivesicular Bodies

Intraluminal vesicles (ILVs) are small vesicles 50-80 nm in diameter formed during the maturation of early endosomes. A specialized endosome containing numerous ILVs is called a multivesicular body (MVB). ILVs contain internalized molecules such as antigens, nucleic acids, proteins, and metabolites. Some of these molecules are released from the MVBs inside exosomes and are transported to other cells. Other MVBs contain molecules that are retained in the ILVs and are later degraded within the...
COP Coated Vesicles00:59

COP Coated Vesicles

Membrane-enclosed structures called vesicles transport proteins and lipids across the cell. The vesicles derive their cargo from the plasma membrane, Golgi, ER, or endosome. Coated vesicles are spherical, protein-coated carriers with a 50–100 nm diameter that mediate bidirectional transport between the ER and the Golgi. The distribution of proteins between the ER and Golgi complex is dynamic and is maintained by different coated vesicles. Their formation is driven by the assembly of different...

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Related Experiment Video

Updated: May 16, 2026

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond
09:00

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Published on: July 27, 2013

Computational model for autophagic vesicle dynamics in single cells.

Katie R Martin1, Dipak Barua, Audra L Kauffman

  • 1Laboratory of Systems Biology, Van Andel Research Institute, Grand Rapids, MI, USA.

Autophagy
|December 1, 2012
PubMed
Summary

We developed a computational model to simulate cellular recycling via macroautophagy (autophagy). This model accurately predicts autophagic vesicle dynamics and can guide future research into this essential biological process.

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Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy
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Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

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Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry
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Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Published on: July 21, 2017

Related Experiment Videos

Last Updated: May 16, 2026

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond
09:00

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Published on: July 27, 2013

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy
09:59

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Published on: May 3, 2013

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry
11:39

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Published on: July 21, 2017

Area of Science:

  • Cell Biology
  • Systems Biology
  • Computational Biology

Background:

  • Macroautophagy (autophagy) is a vital cellular recycling process crucial for maintaining homeostasis and survival under stress.
  • Autophagy involves over 30 proteins acting in four stages and plays a role in disease etiology and treatment.
  • Mathematical and computational models are effective tools for studying complex cellular processes like autophagy.

Purpose of the Study:

  • To develop a computational model simulating autophagic vesicle dynamics in mammalian cells.
  • To validate the model's accuracy against experimental data under various autophagy conditions.
  • To establish a foundation for quantitative characterization of autophagy.

Main Methods:

  • Utilized time-resolved, live-cell microscopy to gather data on autophagic vesicle synthesis and turnover.
  • Developed a stochastically simulated computational model based on experimental knowledge.
  • Tested the model's predictive power through genetic modulation of the autophagic machinery.

Main Results:

  • The computational model accurately reflected experimental data for both basal and chemically-induced autophagy.
  • The model successfully predicted vesicle dynamics following genetic manipulation of autophagy-related proteins.
  • The model generated a novel prediction regarding vesicle size, consistent with existing and new experimental observations.

Conclusions:

  • The developed computational model is a validated and accurate tool for studying autophagic vesicle dynamics.
  • This model serves as a robust foundation for future quantitative analyses of autophagy.
  • The model's predictive capabilities can accelerate hypothesis generation and intervention studies in autophagy research.