(c) In Matlab, add the HMM-Bayes folder containing the
scripts and the folder containing the tracking data to
the path.
(d) Open the “hmm_skeleton_MultiTrajip_SingleTrajProcess.m” file in Matlab, add the input filename and full
path after XlsReadtraj inside the bracket on line 7, and
save this file, e.g., [Multitrack, sheet] ¼ XlsReadTraj(‘H:
\MATLAB\test.xlsx’).
(e) Execute “hmm_skeleton_MultiTrajip_SingleTrajProcess.
m” by calling the script. This script analyzes each track
and the output plot contains the values of different parameters that best explains the movement of trajectory
being analyzed, which can be used to quantify the type
of movement exhibited by the corresponding RNA
(Fig. 3). The output plot for each track is stored inside
the folder Democode/data as “analysis_output_figure_tracknumber.tif.” Copy the results to a new folder before
starting the analysis for the next cell.
3.6 Summary of
RILPL2-RH1 and SKIP
Tethering Experiments
In cells, precise localization of mRNA is thought to be achieved by
its interaction with specific RBPs. These RBPs exert this effect
mainly by recruiting other cellular factors such as molecular motors
or anchoring proteins that restrict the free diffusion of a transcript
and alter its mobility. Tethering of the RH1 domain of RILPL2
leads to decreased mobility of the reporter RNA (D < 0.01 μm
2 /S)
when compared to a freely diffusing RNA (Fig. 2). In contrast,
tethering of the N-terminal domain of SKIP protein leads to
directed movement of the reporter RNA with an average velocity
of 1.6 μm/S, which is consistent with the previously observed
speed of kinesin-1-based transport (Fig. 3). Thus, tethering of
motor-interacting proteins can alter the mobility of a reporter
RNA and this method could further be extended to evaluate the
effect of distinct RNA-binding proteins on mRNA transport and
localization.
ä
Fig. 2 (continued) luciferase (MCP-GFP-FLuc) plasmid. Bottom panel shows a cumulative probability plot of
particles from the cell shown above undergoing the corresponding displacements. Single (red)- and two
(blue)-component fit is used to calculate displacement coefficients. (b) Top panel shows a representative
image of a cell that is transfected with the MCP-GFP-RILPL2-RH1 plasmid. Bottom panel shows a cumulative
probability plot of particles from the cell shown above undergoing the corresponding displacements. Single
(red)- and two (blue)-component fit is used to calculate displacement coefficients. (c) Quantification of
diffusion coefficients of two RNA populations from cells transfected with either MCP-GFP-FLuc or
MCP-GFP-RILPL2-RH1 plasmids is shown. (d) Fraction of particles showing either fast or slow movement
from cells transfected with either MCP-GFP-FLuc or MCP-GFP-RILPL2-RH1 plasmids is shown
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