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Spatio-temporal Dynamics and Mechanisms of Stress Granule Assembly.

Ohshima D, Arimoto-Matsuzaki K, Tomida T, Takekawa M, Ichikawa K - PLoS Comput. Biol. (2015)

Bottom Line: SGs were assembled as a result of applying arsenite to HeLa cells.This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly.Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics.

View Article: PubMed Central - PubMed

Affiliation: Division of Mathematical Oncology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.

ABSTRACT
Stress granules (SGs) are non-membranous cytoplasmic aggregates of mRNAs and related proteins, assembled in response to environmental stresses such as heat shock, hypoxia, endoplasmic reticulum (ER) stress, chemicals (e.g. arsenite), and viral infections. SGs are hypothesized as a loci of mRNA triage and/or maintenance of proper translation capacity ratio to the pool of mRNAs. In brain ischemia, hippocampal CA3 neurons, which are resilient to ischemia, assemble SGs. In contrast, CA1 neurons, which are vulnerable to ischemia, do not assemble SGs. These results suggest a critical role SG plays in regards to cell fate decisions. Thus SG assembly along with its dynamics should determine the cell fate. However, the process that exactly determines the SG assembly dynamics is largely unknown. In this paper, analyses of experimental data and computer simulations were used to approach this problem. SGs were assembled as a result of applying arsenite to HeLa cells. The number of SGs increased after a short latent period, reached a maximum, then decreased during the application of arsenite. At the same time, the size of SGs grew larger and became localized at the perinuclear region. A minimal mathematical model was constructed, and stochastic simulations were run to test the modeling. Since SGs are discrete entities as there are only several tens of them in a cell, commonly used deterministic simulations could not be employed. The stochastic simulations replicated observed dynamics of SG assembly. In addition, these stochastic simulations predicted a gamma distribution relative to the size of SGs. This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly. Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics. Thus our experiments and stochastic simulations presented a possible mechanism regulating SG assembly.

No MeSH data available.


Related in: MedlinePlus

Analysis of the dynamics of SG assembly.(A) Time courses of SG, TIA1, TIA2, and TIA3 are shown. TIA1 decreased monotonically as the increase in the number of SG. TIA2 and TIA3 increased quickly just after the beginning of SS, and soon they decreased. The peak number of TIA2 was small, and that of TIA3 was 9, which was smaller than the peak number of SG. (B) The decrease in the number of SG after the peak was caused by the fusion between SGs. If we aligned the occurrences of fusions (black pulsatile vertical lines) to the time course of the number of SGs (red line), the occurrences of the decrement in the time course and those of fusion events coincided perfectly. Two SGs at 3200 sec (white arrowheads in the bottom left panel) fused together forming one larger SG at 3210 sec (white arrowhead in the bottom right panel). (C) SG distribution at 60 min was changed by the change in pm/pn. Small change in pm/pn changed the SG distribution.
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pcbi.1004326.g006: Analysis of the dynamics of SG assembly.(A) Time courses of SG, TIA1, TIA2, and TIA3 are shown. TIA1 decreased monotonically as the increase in the number of SG. TIA2 and TIA3 increased quickly just after the beginning of SS, and soon they decreased. The peak number of TIA2 was small, and that of TIA3 was 9, which was smaller than the peak number of SG. (B) The decrease in the number of SG after the peak was caused by the fusion between SGs. If we aligned the occurrences of fusions (black pulsatile vertical lines) to the time course of the number of SGs (red line), the occurrences of the decrement in the time course and those of fusion events coincided perfectly. Two SGs at 3200 sec (white arrowheads in the bottom left panel) fused together forming one larger SG at 3210 sec (white arrowhead in the bottom right panel). (C) SG distribution at 60 min was changed by the change in pm/pn. Small change in pm/pn changed the SG distribution.

Mentions: Next we investigated the dynamics of each molecular species in the model. First we analyzed the time course of complexes (Fig 6A). As the increase in the number of SG, TIA1 decreased monotonically. TIA2 and TIA3 increased rapidly just after the start of the simulation, and then decreased monotonically. The peak number of TIA2 and TIA3 was 66 and only 9, respectively in this SS. The small number of TIA3 was expected from Fig 4. This indicates that TIA3 lifetime was relatively short, and quickly made a transition back to TIA2 or forward to TIA*.


Spatio-temporal Dynamics and Mechanisms of Stress Granule Assembly.

Ohshima D, Arimoto-Matsuzaki K, Tomida T, Takekawa M, Ichikawa K - PLoS Comput. Biol. (2015)

Analysis of the dynamics of SG assembly.(A) Time courses of SG, TIA1, TIA2, and TIA3 are shown. TIA1 decreased monotonically as the increase in the number of SG. TIA2 and TIA3 increased quickly just after the beginning of SS, and soon they decreased. The peak number of TIA2 was small, and that of TIA3 was 9, which was smaller than the peak number of SG. (B) The decrease in the number of SG after the peak was caused by the fusion between SGs. If we aligned the occurrences of fusions (black pulsatile vertical lines) to the time course of the number of SGs (red line), the occurrences of the decrement in the time course and those of fusion events coincided perfectly. Two SGs at 3200 sec (white arrowheads in the bottom left panel) fused together forming one larger SG at 3210 sec (white arrowhead in the bottom right panel). (C) SG distribution at 60 min was changed by the change in pm/pn. Small change in pm/pn changed the SG distribution.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482703&req=5

pcbi.1004326.g006: Analysis of the dynamics of SG assembly.(A) Time courses of SG, TIA1, TIA2, and TIA3 are shown. TIA1 decreased monotonically as the increase in the number of SG. TIA2 and TIA3 increased quickly just after the beginning of SS, and soon they decreased. The peak number of TIA2 was small, and that of TIA3 was 9, which was smaller than the peak number of SG. (B) The decrease in the number of SG after the peak was caused by the fusion between SGs. If we aligned the occurrences of fusions (black pulsatile vertical lines) to the time course of the number of SGs (red line), the occurrences of the decrement in the time course and those of fusion events coincided perfectly. Two SGs at 3200 sec (white arrowheads in the bottom left panel) fused together forming one larger SG at 3210 sec (white arrowhead in the bottom right panel). (C) SG distribution at 60 min was changed by the change in pm/pn. Small change in pm/pn changed the SG distribution.
Mentions: Next we investigated the dynamics of each molecular species in the model. First we analyzed the time course of complexes (Fig 6A). As the increase in the number of SG, TIA1 decreased monotonically. TIA2 and TIA3 increased rapidly just after the start of the simulation, and then decreased monotonically. The peak number of TIA2 and TIA3 was 66 and only 9, respectively in this SS. The small number of TIA3 was expected from Fig 4. This indicates that TIA3 lifetime was relatively short, and quickly made a transition back to TIA2 or forward to TIA*.

Bottom Line: SGs were assembled as a result of applying arsenite to HeLa cells.This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly.Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics.

View Article: PubMed Central - PubMed

Affiliation: Division of Mathematical Oncology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.

ABSTRACT
Stress granules (SGs) are non-membranous cytoplasmic aggregates of mRNAs and related proteins, assembled in response to environmental stresses such as heat shock, hypoxia, endoplasmic reticulum (ER) stress, chemicals (e.g. arsenite), and viral infections. SGs are hypothesized as a loci of mRNA triage and/or maintenance of proper translation capacity ratio to the pool of mRNAs. In brain ischemia, hippocampal CA3 neurons, which are resilient to ischemia, assemble SGs. In contrast, CA1 neurons, which are vulnerable to ischemia, do not assemble SGs. These results suggest a critical role SG plays in regards to cell fate decisions. Thus SG assembly along with its dynamics should determine the cell fate. However, the process that exactly determines the SG assembly dynamics is largely unknown. In this paper, analyses of experimental data and computer simulations were used to approach this problem. SGs were assembled as a result of applying arsenite to HeLa cells. The number of SGs increased after a short latent period, reached a maximum, then decreased during the application of arsenite. At the same time, the size of SGs grew larger and became localized at the perinuclear region. A minimal mathematical model was constructed, and stochastic simulations were run to test the modeling. Since SGs are discrete entities as there are only several tens of them in a cell, commonly used deterministic simulations could not be employed. The stochastic simulations replicated observed dynamics of SG assembly. In addition, these stochastic simulations predicted a gamma distribution relative to the size of SGs. This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly. Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics. Thus our experiments and stochastic simulations presented a possible mechanism regulating SG assembly.

No MeSH data available.


Related in: MedlinePlus