TITLE: Chlamydomonas reinhardtii cell motility quantification
AUTHORS: Joao Vitor Molino

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block"><span>This protocols describe the steps required for the motility quantification in </span><span style = "font-style:italic;">Chlamydomonas reinhardtii</span><span>.  </span></div></div>

[STEPS]
?. [Cell preparation]
Culture the cells for 5 days following the growing Chlamydomonas reinhardtii protocol.Prepare a sample of the cells by washing them in the final desired media by centrifugation.  , removal of old media and addition of new media.
Centrifuge: 3000 34, 3 min, 25 10
?. [Glass slide preparation]
In glass slide, attach the Frame-seal Slide chambers, 15x15, 65 μl. Add the sampleSeal the chamber with a cover slip
?. [Imaging]
Set the glass slide in the microscope for image acquisitionRecord sequential images in a fixed interval (e.g. 100 ms per frame) using the desired laser/filter settings.
?. [Cell tracking analysis - imageJ]
Open the image file in imageJAdjust brightness and contrast (Image -> Adjust -> Brightness/Contrast -> auto)Open the Plugins -> Tracking -> TrackMateCheck the image settings (eg. Size and pixels), nextChoose the detector system, nextInput the estimate size of cells and define a threshold, nextAfter detection, choose a range of spots quality, nextSelect a view option, nextSet filter in spots, nextDefine the maximum linking distance between frames, nextSet color for tracks, nextOpen analysis and save the results in a csv file*The analysis files contains information about the tracks, as average speed, max speed, position, etc. ** A video demonstrating the TrackMate workflow can be found here.
?. [Data analysis]
Analyse the data generated. For example, after organizing the data of each test in a excel tab, the R code below demonstrate a possible workflow and analysis to generate a density plot. library(dplyr)library(ggplot2)library(readxl)#set the working directorywd #Get all file names with .xlsx in the working folder.FileNames #load file with resultscc1690_1 cc1690_2 cc1690_3 cc1690 MAW8_1 MAW8_2 MAW8_3 MAW8 GP1_1 GP1_2 GP1_3 GP1 #Take the last 10 seconds of the experimentcc1690  50)MAW8  50)GP1  50)#Add column with Strain informationcc1690_n cc1690 MAW8_n MAW8 GP1_n GP1 #Combine datadf # Convert data to speed um/s (File recorder at 100ms/frame|speed in frames/s)df$speed_r #generates the plotmyplot   geom_density(alpha=0.4) +   scale_fill_manual(limits = c("cc1690",                               "MAW8",                               "GP1"),                    values=c("#1b9e77",                             "#d95f02",                             "#7570b3"))+  theme(text=element_text(size=12,                           #       family="Comic Sans MS"))                          #       family="CM Roman"))                          #       family="mono"))                          #       family="sans"))                          family="serif",                          face="bold"),        plot.background = element_blank(),        panel.grid.major = element_blank(),        panel.grid.minor = element_blank(),        panel.border = element_blank(),        panel.background = element_rect(fill='white', colour='white'),        axis.line = element_line(colour = "black", size = 0.6), #thickness axis        axis.ticks = element_line(size=0.8), #thickness ticks        axis.text.x = element_text(face="bold", colour='black'),        axis.text.y = element_text(face="bold", colour='black'),        legend.key=element_blank())+  labs(x = (expression(paste("Speed (",  #label x axis                             mu, "/", "s",                             ")",                              sep=""))),        y = "Density")  #  Lavel y axis#to save graphggsave(  paste("motility",".png"),  myplot,  width = 6.41,  height = 3.73,  dpi = 1200)