TESSARO_NONLOCAL_BACTERIA.sav - Plots

Bacterial biophotons as non-local information carriers: Species-specific spectral characteristics of a stress response.

pacman::p_load(pacman, ggplot2, tidyr, dplyr, haven)

# Read SPSS data
my_data <- haven::read_sav("TESSARO_NONLOCAL_BACTERIA.sav")

# Convert the INJ column to a factor
my_data$INJ <- as.factor(my_data$INJ) 

# Convert columns to factors for ggplot compatibility
my_data$INJ <- as.factor(my_data$INJ) 
my_data$SPEINJ <- as.factor(my_data$SPEINJ)
my_data$SPERE <- as.factor(my_data$SPERE)

# --- Visualisations --- #

#  Baseline vs. Injection
ggplot(my_data, aes(x = INJ, y = WAVG, fill = INJ)) +
  geom_boxplot() +
  facet_wrap(~ CON, scales = "free_y") +
  labs(x = "Injection", y = "Average Biophoton Emission (WAVG)") +
  theme_minimal()

# Species-Specific Differences
ggplot(my_data, aes(x = SPEINJ, y = WAVG, color = SPERE, fill = INJ)) +
  geom_violin() +
  facet_wrap(~ CON, scales = "free") +
  labs(x = "Species Injected", y = "Average Biophoton Emission (WAVG)") +
  theme_minimal()

# Convert necessary columns to factors
my_data$INJ <- as.factor(my_data$INJ) 
my_data$SPEINJ <- as.factor(my_data$SPEINJ)
my_data$SPERE <- as.factor(my_data$SPERE)

#Baseline vs. Injection: Facet by Biophoton Measure
my_data %>%
  select(INJ, CON, WAVG, F1, F2, F3, F4) %>%
  pivot_longer(cols = c(WAVG, F1, F2, F3, F4), names_to = "BM", values_to = "value") %>%
  ggplot(aes(x = INJ, y = value, fill = INJ)) + 
  geom_boxplot() +
  facet_grid(BM ~ CON, scales = "free") + 
  labs(x = "Injection", y = "Biophoton Emission") + 
  theme_minimal()

# Check for columns with overlap
conflicting_cols <- names(which(sapply(my_data, function(x) any(is.factor(x))))) 

# Decide how to resolve conflicts (example: change factors to character types)
for (col in conflicting_cols) {
  my_data[, col] <- as.character(my_data[, col])
} 

my_data %>%
  select(INJ, CON, WAVG, F1, F2, F3, F4) %>%
  pivot_longer(cols = c(WAVG, F1, F2, F3, F4), names_to = "Biophoton_Measure", values_to = "Value") %>%
  ggplot(aes(x = Biophoton_Measure, y = Value)) +
  geom_boxplot() +
  facet_wrap(vars(INJ, CON), scales = "free") +
  theme() 

Data from: Bacterial bio-photons as non-local information carriers: species-specific spectral characteristics of a stress response. Abstract: Studies by Alexander Gurwitsch in the 1920’s with onion root cells revealed the phenomenon of mitogenetic radiation. Subsequent works by Popp, Van Wijk, Quickenden, Tillbury and Trushin have demonstrated a link between Gurwitsch’s mitogenetic radiation and the biophoton, emissions of light correlated with biological processes. The present study seeks to expand upon these works and explore whether biophoton emissions of bacterial cultures is used as an information carrier of environmental stress. Bacterial cultures (Escherichia coli and Serratia marcescens) were incubated for 24 h in 5 mL of Nutrient Broth to stationary phase and cell densities of ~107 cells/mL. Cultures of E. coli were placed upon a photomultiplier tube housed within a dark box. A second bacterial culture, either E. coli or S. marcescens, was placed in an identical dark box at a distance of 5 m and received injections of hydrogen peroxide. Spectral analyses revealed significant differences in peak frequencies of 7.2, 10.1, and 24.9 Hz in the amplitude modulation of the emitted biophoton signal with respect to whether a peroxide injection occurred or not, and whether the species receiving the injection was E. coli or S. marcescens. These and the subsequent results of discriminant functions suggest that bacteria may release biophotons as a non-local communication system in response to stress, and that these biophotons are species specific. Usage notes - TESSARO_NONLOCAL_BACTERIA.sav: SPSS datafile of the extracted raw spectral frequencies and computed bins that were used for subsequent analyses.