Limits...
Magnetite-Amyloid-β deteriorates activity and functional organization in an in vitro model for Alzheimer's disease.

Teller S, Tahirbegi IB, Mir M, Samitier J, Soriano J - Sci Rep (2015)

Bottom Line: Recent studies have shown that other agents, in particular magnetite, can also play a pivotal role.Our work suggests that magnetite nanoparticles have a more prominent role in AD than previously thought, and may bring new insights in the understanding of the damaging action of magnetite-amyloid-β complex.Our experimental system also offers new interesting perspectives to explore key biochemical players in neurological disorders through a controlled, model system manner.

View Article: PubMed Central - PubMed

Affiliation: Departament d'Estructura i Constituents de la Matèria, Universitat de Barcelona, Barcelona, E-08028, Spain.

ABSTRACT
The understanding of the key mechanisms behind human brain deterioration in Alzheimer' disease (AD) is a highly active field of research. The most widespread hypothesis considers a cascade of events initiated by amyloid-β peptide fibrils that ultimately lead to the formation of the lethal amyloid plaques. Recent studies have shown that other agents, in particular magnetite, can also play a pivotal role. To shed light on the action of magnetite and amyloid-β in the deterioration of neuronal circuits, we investigated their capacity to alter spontaneous activity patterns in cultured neuronal networks. Using a versatile experimental platform that allows the parallel monitoring of several cultures, the activity in controls was compared with the one in cultures dosed with magnetite, amyloid-β and magnetite-amyloid-β complex. A prominent degradation in spontaneous activity was observed solely when amyloid-β and magnetite acted together. Our work suggests that magnetite nanoparticles have a more prominent role in AD than previously thought, and may bring new insights in the understanding of the damaging action of magnetite-amyloid-β complex. Our experimental system also offers new interesting perspectives to explore key biochemical players in neurological disorders through a controlled, model system manner.

No MeSH data available.


Related in: MedlinePlus

Functional connectivity and damage.(A) Functional networks for control and M-Aβ experiments. Gray links show all functional connections, and color links correspond to the top functional connections (z - score > 1.95, 500 surrogates). The thickness of a link is proportional to its weight. The direction of the links is not shown for clarity. The control network reflects the stability of the network in two consecutive measurements. The M-Aβ network exhibits strong connectivity changes and reorganization of the network moduli, which are color coded according to the hierarchical tree information of Fig. 5. Grey clusters with a square in their center are those that fired independently or that participated equally in different communities. (B) Matrices of weight differences wd of the functional links. The clusters’ index order is the same as in Fig. 5, and corresponds to the unperturbed condition. The square boxes outline the moduli before perturbation. (C) Corresponding distributions of weight differences for the control and M-Aβ experiments. γ indicates the skewness of the distributions. The red vertical line is a guide to the eye to show the symmetry of the distribution in the control case. (D) Comparison of the distributions including all 15 experimental realizations. The M-Aβ distribution is broader and contains both strongly weakened and strongly strengthened functional links.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4660300&req=5

f6: Functional connectivity and damage.(A) Functional networks for control and M-Aβ experiments. Gray links show all functional connections, and color links correspond to the top functional connections (z - score > 1.95, 500 surrogates). The thickness of a link is proportional to its weight. The direction of the links is not shown for clarity. The control network reflects the stability of the network in two consecutive measurements. The M-Aβ network exhibits strong connectivity changes and reorganization of the network moduli, which are color coded according to the hierarchical tree information of Fig. 5. Grey clusters with a square in their center are those that fired independently or that participated equally in different communities. (B) Matrices of weight differences wd of the functional links. The clusters’ index order is the same as in Fig. 5, and corresponds to the unperturbed condition. The square boxes outline the moduli before perturbation. (C) Corresponding distributions of weight differences for the control and M-Aβ experiments. γ indicates the skewness of the distributions. The red vertical line is a guide to the eye to show the symmetry of the distribution in the control case. (D) Comparison of the distributions including all 15 experimental realizations. The M-Aβ distribution is broader and contains both strongly weakened and strongly strengthened functional links.

Mentions: We combined the analysis of the communities’ structure with the functional connectivity of the network to better quantify the changes in the coupling between clusters upon perturbation. As described in Methods, functional maps were obtained by analyzing the time delays in the clusters’ activations. In this construction, the shorter the time delay the stronger the directed functional bond (weight) between clusters. Figure 6A depicts the functional maps for the control and M-Aβ experiments. Two levels of representation are shown. In a first one, all functional connections between clusters are drawn as gray links, effectively shaping a homogeneous area that evinces the widespread clusters’ functional interconnectivity. In a second one, only the top functional connections (z - score > 1.95, 500 surrogates) are shown, with clusters and their connections color coded according to their participation in the above inferred communities. The thicker a connection is, the higher is the weight of the functional bond. For the control case, we observed that the overall structure of the network was well preserved along the two recordings, with small variations in the functional links that reflect the fluctuations observed in the dendrograms. This maintenance of the network features was also observed in the M and Aβ cases (see Supplementary Figure 2). For the M-Aβ case, the rupture of the 3 initial communities into 6 smaller ones was clear, and the clusters that remained in a given community experienced important variations in functional connectivity. However, a number of the strongest links were preserved, hinting at the maintenance of some sort of internal organization in the network. Another example of a M-Aβ perturbation is provided in the Supplementary Figure 2, and corresponds to the data shown in Figs 2A and 3A.


Magnetite-Amyloid-β deteriorates activity and functional organization in an in vitro model for Alzheimer's disease.

Teller S, Tahirbegi IB, Mir M, Samitier J, Soriano J - Sci Rep (2015)

Functional connectivity and damage.(A) Functional networks for control and M-Aβ experiments. Gray links show all functional connections, and color links correspond to the top functional connections (z - score > 1.95, 500 surrogates). The thickness of a link is proportional to its weight. The direction of the links is not shown for clarity. The control network reflects the stability of the network in two consecutive measurements. The M-Aβ network exhibits strong connectivity changes and reorganization of the network moduli, which are color coded according to the hierarchical tree information of Fig. 5. Grey clusters with a square in their center are those that fired independently or that participated equally in different communities. (B) Matrices of weight differences wd of the functional links. The clusters’ index order is the same as in Fig. 5, and corresponds to the unperturbed condition. The square boxes outline the moduli before perturbation. (C) Corresponding distributions of weight differences for the control and M-Aβ experiments. γ indicates the skewness of the distributions. The red vertical line is a guide to the eye to show the symmetry of the distribution in the control case. (D) Comparison of the distributions including all 15 experimental realizations. The M-Aβ distribution is broader and contains both strongly weakened and strongly strengthened functional links.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4660300&req=5

f6: Functional connectivity and damage.(A) Functional networks for control and M-Aβ experiments. Gray links show all functional connections, and color links correspond to the top functional connections (z - score > 1.95, 500 surrogates). The thickness of a link is proportional to its weight. The direction of the links is not shown for clarity. The control network reflects the stability of the network in two consecutive measurements. The M-Aβ network exhibits strong connectivity changes and reorganization of the network moduli, which are color coded according to the hierarchical tree information of Fig. 5. Grey clusters with a square in their center are those that fired independently or that participated equally in different communities. (B) Matrices of weight differences wd of the functional links. The clusters’ index order is the same as in Fig. 5, and corresponds to the unperturbed condition. The square boxes outline the moduli before perturbation. (C) Corresponding distributions of weight differences for the control and M-Aβ experiments. γ indicates the skewness of the distributions. The red vertical line is a guide to the eye to show the symmetry of the distribution in the control case. (D) Comparison of the distributions including all 15 experimental realizations. The M-Aβ distribution is broader and contains both strongly weakened and strongly strengthened functional links.
Mentions: We combined the analysis of the communities’ structure with the functional connectivity of the network to better quantify the changes in the coupling between clusters upon perturbation. As described in Methods, functional maps were obtained by analyzing the time delays in the clusters’ activations. In this construction, the shorter the time delay the stronger the directed functional bond (weight) between clusters. Figure 6A depicts the functional maps for the control and M-Aβ experiments. Two levels of representation are shown. In a first one, all functional connections between clusters are drawn as gray links, effectively shaping a homogeneous area that evinces the widespread clusters’ functional interconnectivity. In a second one, only the top functional connections (z - score > 1.95, 500 surrogates) are shown, with clusters and their connections color coded according to their participation in the above inferred communities. The thicker a connection is, the higher is the weight of the functional bond. For the control case, we observed that the overall structure of the network was well preserved along the two recordings, with small variations in the functional links that reflect the fluctuations observed in the dendrograms. This maintenance of the network features was also observed in the M and Aβ cases (see Supplementary Figure 2). For the M-Aβ case, the rupture of the 3 initial communities into 6 smaller ones was clear, and the clusters that remained in a given community experienced important variations in functional connectivity. However, a number of the strongest links were preserved, hinting at the maintenance of some sort of internal organization in the network. Another example of a M-Aβ perturbation is provided in the Supplementary Figure 2, and corresponds to the data shown in Figs 2A and 3A.

Bottom Line: Recent studies have shown that other agents, in particular magnetite, can also play a pivotal role.Our work suggests that magnetite nanoparticles have a more prominent role in AD than previously thought, and may bring new insights in the understanding of the damaging action of magnetite-amyloid-β complex.Our experimental system also offers new interesting perspectives to explore key biochemical players in neurological disorders through a controlled, model system manner.

View Article: PubMed Central - PubMed

Affiliation: Departament d'Estructura i Constituents de la Matèria, Universitat de Barcelona, Barcelona, E-08028, Spain.

ABSTRACT
The understanding of the key mechanisms behind human brain deterioration in Alzheimer' disease (AD) is a highly active field of research. The most widespread hypothesis considers a cascade of events initiated by amyloid-β peptide fibrils that ultimately lead to the formation of the lethal amyloid plaques. Recent studies have shown that other agents, in particular magnetite, can also play a pivotal role. To shed light on the action of magnetite and amyloid-β in the deterioration of neuronal circuits, we investigated their capacity to alter spontaneous activity patterns in cultured neuronal networks. Using a versatile experimental platform that allows the parallel monitoring of several cultures, the activity in controls was compared with the one in cultures dosed with magnetite, amyloid-β and magnetite-amyloid-β complex. A prominent degradation in spontaneous activity was observed solely when amyloid-β and magnetite acted together. Our work suggests that magnetite nanoparticles have a more prominent role in AD than previously thought, and may bring new insights in the understanding of the damaging action of magnetite-amyloid-β complex. Our experimental system also offers new interesting perspectives to explore key biochemical players in neurological disorders through a controlled, model system manner.

No MeSH data available.


Related in: MedlinePlus