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Related Concept Videos

Generation of Straight or Branched Actin Filaments01:14

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The straight or branched structure formation of actin filaments is controlled by nucleating proteins such as the formins and Arp2/3 complex. Formin-mediated assembly results in straight filaments, whereas Arp2/3 protein complex-mediated assembly results in branched actin filaments.
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The polymerization of G-actin monomers into filamentous F-actin is a multi-step process. Once the F-actins are formed, they can bundle together in different arrangements to form higher-order networks and regulate cellular functions. Common examples include the formation of lamellipodia and filopodia at the cell's leading edge by actin reorganization in a migrating cell. The microvilli on the brush border epithelial cells are also formed through the F-actin network.
The high-order actin...
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The cytoskeletal architecture can be studied using different microscopic and biochemical techniques. Electron microscopy was instrumental in discovering the cytoskeletal architecture around the 1960s, which allowed obtaining structural information at a high-resolution level. However, the sample preparation procedure often limits this ability in biological samples. Several protocols have been developed over the years to optimize sample preparation. In one of the protocols known as rotary...
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Assembly of Cytoskeletal Filaments01:18

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Cytoskeletal filaments are polymeric forms of smaller protein subunits. However, individual cytoskeletal filaments may easily disassemble or associate with other similar filaments to form rigid structures. Microfilaments, made of actin monomers, rely on actin-binding proteins to form bundles and create networks of individual actin filaments. Microtubules rely on microtubule-associated proteins (MAPs) to form sturdy cylindrical structures. However, the proteins involved in forming complex...
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Actin Filament Depolymerization01:19

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Actin filaments (F-actin) are composed of actin subunits. The dissociation of actin monomers can occur from either end of F-actin. The rate of dissociation is faster from the minus-end or the pointed end, where the actin subunits exist with a bound ADP, together known as ADP-actin. The depolymerization of F-actin is aided by proteins, including the actin-depolymerizing factor (ADF) and cofilin family of proteins, gelsolin, and glia maturation factor (GMF).
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Actin polymerization occurs through the head-to-tail association of binding sites on monomeric actin or G-actin to form filamentous or F-actin. The polymerization can be divided into three phases ̶  nucleation, elongation, and steady-state phase.
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Related Experiment Video

Updated: Sep 17, 2025

Using Microfluidics and Fluorescence Microscopy to Study the Assembly Dynamics of Single Actin Filaments and Bundles
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Tracing Randomly Oriented Filaments in a Simulated Actin Network Tomogram.

Salim Sazzed1, Peter Scheible1, Jing He1

  • 1Department of Computer Science.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
|July 4, 2025
PubMed
Summary
This summary is machine-generated.

We developed a dynamic programming method to trace actin filaments in noisy cryo-electron tomograms. This efficient framework accurately identifies filament segments, improving structural analysis of Dictyostelium discoideum.

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Area of Science:

  • Cell Biology
  • Biophysics
  • Structural Biology

Background:

  • Actin networks in Dictyostelium discoideum filopodia are disordered, making filament identification in cryo-electron tomograms difficult.
  • Existing methods often require assumptions about filament orientation, limiting their applicability.

Purpose of the Study:

  • To develop a computationally efficient framework for tracing arbitrarily oriented actin filaments.
  • To overcome challenges posed by noise and disorder in cryo-electron tomograms.

Main Methods:

  • A dynamic programming-based framework was employed, starting from seed points and accumulating densities along paths.
  • The method considers all possible orientations, accumulating densities within 45° of Cartesian axes.
  • Candidate filament segments (CFSs) were identified, binned, merged based on orientation and distance, and extended to fill gaps.

Main Results:

  • The framework achieved a high precision score of 0.999 on a simulated tomogram.
  • A lower recall score of 0.462 was observed, primarily due to false negatives.
  • The prototype demonstrated proof of concept for tracing actin filaments.

Conclusions:

  • The dynamic programming approach is effective for identifying actin filament segments in challenging tomographic data.
  • Further refinement of the filament merging step is necessary to improve recall and reduce false negatives.
  • This method holds promise for advancing the structural analysis of actin networks.