Flow cytometry in Probing ROS status

Title:Flow cytometery for Biophyicists

ROS probe H2DCFDA (H2-DCF, DCF)

• The cell-permeant 2’,7’-dichlorodihydrofluorescein diacetate (H2DCFDA) (also known as dichlorofluores cin diacetate) is a chemically reduced form of fluorescein used as an indicator for reactive oxygen species (ROS)
• In cells, for example to detect the generation of reactive oxygen intermediates in neutrophils and macrophages.
• Upon cleavage of the acetate groups by intracellular esterases and oxidation, the nonfluorescent H2DCFDA is converted to the highly fluorescent
• 2’,7’-dichlorofluorescein (DCF). Versions of this indicator that have better cellular retention are available .

Spectrum

#Structure

Readme

• Experiment dated 8.12.2014 performed in BD influx
• Samples three thalassemia major patients (1,2,3) and two thalassemia carrier (4,5)
• The coloumns are FSC(paralell);FSC(perpendicular); SSC; 692_40(488 laser); ROS;Time
• Tube nomenclature— -Tube 0001- unstained whole blood (uwb1)
  • tube 0002- positive cotrol (blood treated with h2o2 and stained with DCFDA)
  • tube 0003-0006 – uwb2-uwb5 (unstained samples)(uwb1,uwb2,uwb3 are thal major) and (uwb4, uwb5 are thal carrier)
  • tube 0007-0011 – SWB1-SWB5 (stained with DCFDA)(SWB1,SWB2,SWB3 are thal major) and (SWB4, SWB5 are thal carrier)
  • tube 0012-0016 – DWB1-DWB5 (treated with chelator and stained with DCFDA)(DWB1,DWB2,DWB3 are thal major) and (DWB4, DWB5 are thal carrier)
  • tube 0017-0021 – UM1-UM5 (incubated with SMF (H+) and unstained)(UM1,UM2,UM3 are thal major) and (UM4, UM5 are thal carrier)
  • tube 0022-0026 – UM1-UM5 (incubated with SMF (H+) and stained with DCFDA)(SM1,SM2,SM3 are thal major) and (SM4, SM5 are thal carrier)
  • tube 0027-0031 – DM1-DM5 (incubated with SMF (H+) and chelator and stained)(DM1,DM2,DM3 are thal major) and (DM4, DM5 are thal carrier)

Links for Doublet discrimination

A classical paper on Doublet discrimination may be seen in (Wersto et al. (2001))

Functions

Function to read from influx.

library(flowCore)
library(flowClust)
library(magrittr)
#https://rdrr.io/github/fribalet/FCSplankton/src/R/core-functions.R

# Function 1: my_influx(fcsfile)
my_influx=function(fcsfile) {
df.fcs<-read.FCS(fcsfile, emptyValue=F)
df=data.frame(df.fcs@exprs)
return(df)
}
# Example 
influx_fcs_file="DB.20141208.A.0003.fcs"
df<-my_influx(influx_fcs_file)
colnames(df)

[1] "pulse.width"   "FSC..Par."     "FSC..Perp."    "SSC"          
[5] "ROS"           "X692.40..488." "TIME"         

# Function 2 :df.singlet(dataframe)
df.singlet=function(df){
# True only for influx setting
attach(df)
ik=which(pulse.width<14000)
df.singlet=data.frame(
pw=pulse.width[ik],
fsc.par=FSC..Par.[ik],
fsc.perp=FSC..Perp.[ik],
ssc=SSC[ik],
ros=ROS[ik])
return(df.singlet)
}
# Example
dfs=df.singlet(df)
attach(dfs)
attach(df)
plot(pulse.width,SSC,pch=16,cex=0.2)
points(pw,ssc,pch=16,cex=0.2,col="red")

Extracting the file list [Tube 7,10,22,25]

pth="./jyotifacs/20141208/"
fnames=list.files(pth)
gnames=""

for (i in fnames){
gnames[i]=paste0(pth,i,sep="")

}
f1=gnames[7]
f2=gnames[10]
f3=gnames[22]
f4=gnames[25]
df1=my_influx(f1)
df2=my_influx(f2)
df3=my_influx(f3)
df4=my_influx(f4)
df1s=df.singlet(df1)
df2s=df.singlet(df2)
df3s=df.singlet(df3)
df4s=df.singlet(df4)

Magnetic field effect

The effect of magnetic field is explored using box-cox transformation.

Histograms using SSC

a1=hist(df1s$ssc,1000)

a2=hist(df2s$ssc,1000)

a3=hist(df3s$ssc,1000)

a4=hist(df4s$ssc,1000)

par(mfrow=c(1,2))
plot(a1$counts[10:180],pch=16,type="l",cex=0.5,col="blue",ylim=c(0,3000),ylab="counts")
points(a3$counts[10:180],pch=16,type="l",cex=0.5,col="red")
plot(a2$counts[10:180],pch=16,type="l",cex=0.5,col="blue",ylab="counts",ylim=c(0,3000))
points(a4$counts[10:180],pch=16,type="l",cex=0.5,col="red")

a1=hist(df1s$ros,1000)

a2=hist(df2s$ros,1000)

a3=hist(df3s$ros,1000)

a4=hist(df4s$ros,1000)

par(mfrow=c(1,2))
plot(a1$counts[10:180],pch=16,type="l",cex=0.5,col="blue",ylim=c(0,3000),ylab="counts")
points(a3$counts[10:180],pch=16,type="l",cex=0.5,col="red")
plot(a2$counts[10:180],pch=16,type="l",cex=0.5,col="blue",ylab="counts",ylim=c(0,3000))
points(a4$counts[10:180],pch=16,type="l",cex=0.5,col="red")

Non singlets

Left panel : 7,22 Right panel:10,25

a1=hist(df1$SSC,1000)

a2=hist(df2$SSC,1000)

a3=hist(df3$SSC,1000)

a4=hist(df4$SSC,1000)

par(mfrow=c(1,2))
plot(a1$counts[10:180],pch=16,type="l",cex=0.5,col="blue",ylim=c(0,6000),ylab="counts")
points(a3$counts[10:180],pch=16,type="l",cex=0.5,col="red")
plot(a2$counts[10:180],pch=16,type="l",cex=0.5,col="blue",ylab="counts",ylim=c(0,6000))
points(a4$counts[10:180],pch=16,type="l",cex=0.5,col="red")