Plate <- “A10”

Adapt biosensor IDs in “Defining biosensor subsets”

BS_a <- “BS_AB037” BS_b <- “BS_AB038” BS_c <- “BS_AB039” BS_d <- “BS_AB040”

Cleaning up data

data <- data_raw %>%
  select (time, Well, BS, TF, Nar, Replicate, Abs1:Fluo2) %>%
  rename (OD = Abs1, FL_B = Fluo1, FL_T = Fluo2, Time = time)

data$Nar <- as.factor(data$Nar)
data$Replicate <- as.factor(data$Replicate)

med <- data %>%
  filter (BS == "EZ rich")

data <- data %>%
  mutate(ODc = OD - mean(med$OD), FL_Tc = FL_T - mean(med$FL_T), FL_Bc = FL_B - mean(med$FL_B)) %>%
  mutate (RFU_T = FL_T/OD, RFU_B = FL_B/OD, RFU_Tc = FL_Tc/ODc, RFU_Bc = FL_Bc/ODc)

nomed <- data %>%
  filter (BS != "EZ rich")

Basic plots

All data

Timepoint 30h seems a good timepoint for stationary phase analysis

Only medium

mean(med$OD)
## [1] 0.09915925
mean(med$FL_T)
## [1] 34.43322
mean(med$FL_B)
## [1] 58.22432
grid.arrange(m2, m3, m1, nrow = 2)

One of the replicates is maybe contaminated (OD increases with time). Small increase however that can not be observed in fluorescence values, so probably not an issue.

Without medium

Defining biosensor subsets

control <- nomed %>%
  filter(BS == "Control")
BS_a <- nomed%>%
  filter(BS == "AB037")
BS_b <- nomed %>%
  filter(BS == "AB038")
BS_c <- nomed%>%
  filter(BS == "AB039")
BS_d <- nomed %>%
  filter(BS == "AB040")

Check per biosensor strain

Control

Seems that Nar has effect on growth (also in following graphs) - nicer spreading of results for the bottom measurements compared to the top (RFU_B vs RFU_T): larger dynamic range so trends better visible (for example horizontal trend for exp phase)

Two of the replicates start growing very late > also low FL values.

BS_a

BS_b

BS_c

BS_d

Summary

  • BS_a: no clear repression/activation
  • BS_b: no clear repression/activation
  • BS_c: Repression can be observed
  • BS_d: no clear repression/activation