In [1]:
import numpy as np
In [2]:
# Conversion factor from CFU on plate to CFU in well, and daily dilution factor during evolution experiment

CFUS_PER_ML_OVER_PLATE = 10**7
DAILY_DILUTION = 500

# Ancestral CFU counts and OD600 in platereader after growing at 30 degrees Celsius
Ancestral_NS001_Plating_Counts = np.array([54, 28, 15, 36, 24, 20, 33, 40, 11, 61, 47, 22, 45,
                                           46, 74, 19, 37, 20, 35, 20, 23, 48, 13, 17, 16, 16,
                                           17, 18, 45, 47, 81, 34, 51, 32, 50, 60, 78, 64, 45,
                                           18, 20, 72, 68])
Ancestral_NS001_OD600s = np.array([0.276, 0.28613, 0.26408, 0.2913, 0.25755, 0.29297, 0.231,
                                   0.16795, 0.16625, 0.20347, 0.19645, 0.15123, 0.18605, 0.2149,
                                   0.15932, 0.18525, 0.15868, 0.18548, 0.15317, 0.16133, 0.18188,
                                   0.17113, 0.1333, 0.14218, 0.16023, 0.18067, 0.17688, 0.2094,
                                   0.21363, 0.18075, 0.1815, 0.14425, 0.15232, 0.17988, 0.17058,
                                   0.16795, 0.15892, 0.17345, 0.13955, 0.15837, 0.14715, 0.14608,
                                   0.1641])
Ancestral_NS001_OD_Blanks = np.array([.0794, .0791, .0869])

# Final Strain CFU counts and OD600 in platereader after growing at 30 degrees Celsius

High1_Plating_Counts = np.array([109, 128, 116, 113, 125, 178, 118, 117])
High1_OD600s = np.array([0.31783, 0.30065, 0.30998, 0.28337,
                         0.31538, 0.333, 0.29463, 0.28297])

HiMid1_Plating_Counts = np.array([136, 126, 203, 174, 225, 130, 223, 128, 144])
HiMid1_OD600s = np.array([0.38885, 0.36762, 0.37105, 0.38145, 0.3728,
                          0.4085, 0.38412, 0.3699, 0.35283])

Mid1_Plating_Counts = np.array([159, 143, 128, 186, 103, 133, 112, 105])
Mid1_OD600s = np.array([0.26927, 0.28328, 0.29468, 0.27982, 0.28565,
                        0.28475, 0.27565, 0.24793])

LoMid1_Plating_Counts = np.array([125, 100, 125, 86, 129, 91, 111, 95])
LoMid1_OD600s = np.array([0.30528, 0.31983, 0.32877, 0.33193, 0.33168,
                          0.31457, 0.32398, 0.3037])

LoMid5_Plating_Counts = np.array([94, 88, 76, 114, 98, 91, 125, 72, 76])
LoMid5_OD600s = np.array([0.34545, 0.33127, 0.32858, 0.37605, 0.34335,
                          0.35247, 0.37815, 0.3294, 0.32993])

Low1_Plating_Counts = np.array([86, 109, 111, 127, 99, 58, 61])
Low1_OD600s = np.array([0.30783, 0.31777, 0.32932, 0.34125,
                        0.33075, 0.30223, 0.3058])

Low5_Plating_Counts = np.array([58, 74, 54, 55, 100, 56, 43, 52])
Low5_OD600s = np.array([0.1811, 0.23818, 0.21805, 0.21475, 0.225,
                        0.1919, 0.1701, 0.19787])

High_to_Mid_OD_Blanks = np.array([0.08205, 0.0804, 0.0784])
LoMid_to_Low_OD_Blanks = np.array([0.0835, 0.08365, 0.081225])
In [3]:
Ancestral_CFU_per_ml_OD600 = (Ancestral_NS001_Plating_Counts
                               / (Ancestral_NS001_OD600s - np.mean(Ancestral_NS001_OD_Blanks))
                               * CFUS_PER_ML_OVER_PLATE)

High1_CFU_per_ml_OD600 = (High1_Plating_Counts
                         / (High1_OD600s - np.mean(High_to_Mid_OD_Blanks))
                         * CFUS_PER_ML_OVER_PLATE)

HiMid1_CFU_per_ml_OD600 = (HiMid1_Plating_Counts
                           / (HiMid1_OD600s - np.mean(High_to_Mid_OD_Blanks))
                           * CFUS_PER_ML_OVER_PLATE)

Mid1_CFU_per_ml_OD600 = (Mid1_Plating_Counts
                         / (Mid1_OD600s - np.mean(High_to_Mid_OD_Blanks))
                         * CFUS_PER_ML_OVER_PLATE)

LoMid1_CFU_per_ml_OD600 = (LoMid1_Plating_Counts
                           / (LoMid1_OD600s - np.mean(LoMid_to_Low_OD_Blanks))
                           * CFUS_PER_ML_OVER_PLATE)

LoMid5_CFU_per_ml_OD600 = (LoMid5_Plating_Counts
                           / (LoMid5_OD600s - np.mean(LoMid_to_Low_OD_Blanks))
                           * CFUS_PER_ML_OVER_PLATE)

Low1_CF_per_ml_OD600 = (Low1_Plating_Counts
                        / (Low1_OD600s - np.mean(LoMid_to_Low_OD_Blanks))
                        * CFUS_PER_ML_OVER_PLATE)

Low5_CF_per_ml_OD600 = (Low5_Plating_Counts
                        / (Low5_OD600s - np.mean(LoMid_to_Low_OD_Blanks))
                        * CFUS_PER_ML_OVER_PLATE)
In [4]:
Ancestral_mean = np.mean(Ancestral_CFU_per_ml_OD600)
Ancestral_std = np.std(Ancestral_CFU_per_ml_OD600)

High1_mean = np.mean(High1_CFU_per_ml_OD600)
High1_std = np.std(High1_CFU_per_ml_OD600)

HiMid1_mean = np.mean(HiMid1_CFU_per_ml_OD600)
HiMid1_std = np.std(HiMid1_CFU_per_ml_OD600)

Mid1_mean = np.mean(Mid1_CFU_per_ml_OD600)
Mid1_std = np.std(Mid1_CFU_per_ml_OD600)

LoMid1_mean = np.mean(LoMid1_CFU_per_ml_OD600)
LoMid1_std = np.std(LoMid1_CFU_per_ml_OD600)

LoMid5_mean = np.mean(LoMid5_CFU_per_ml_OD600)
LoMid5_std = np.std(LoMid5_CFU_per_ml_OD600)

Low1_mean = np.mean(Low1_CF_per_ml_OD600)
Low1_std = np.std(Low1_CF_per_ml_OD600)

Low5_mean = np.mean(Low5_CF_per_ml_OD600)
Low5_std = np.std(Low5_CF_per_ml_OD600)

print("Final CFUs per ml of OD600 culture are estimated at")
print(f"Ancestral: {Ancestral_mean:.2E} +- {Ancestral_std:.2E}")
print(f"High1: {High1_mean:.2E} +- {High1_std:.2E}")
print(f"HiMid1: {HiMid1_mean:.2E} +- {HiMid1_std:.2E}")
print(f"Mid1: {Mid1_mean:.2E} +- {Mid1_std:.2E}")
print(f"LoMid1: {LoMid1_mean:.2E} +- {LoMid1_std:.2E}")
print(f"LoMid5: {LoMid5_mean:.2E} +- {LoMid5_std:.2E}")
print(f"Low1: {Low1_mean:.2E} +- {Low1_std:.2E}")
print(f"Low5: {Low5_mean:.2E} +- {Low5_std:.2E}")

Final CFUs per ml of OD600 culture are estimated at
Ancestral: 4.12E+09 +- 2.65E+09
High1: 5.58E+09 +- 6.68E+08
HiMid1: 5.58E+09 +- 1.35E+09
Mid1: 6.78E+09 +- 1.34E+09
LoMid1: 4.55E+09 +- 6.70E+08
LoMid5: 3.50E+09 +- 4.03E+08
Low1: 3.89E+09 +- 8.36E+08
Low5: 5.05E+09 +- 9.31E+08
In [5]:
TRANSFER_VOLUME = .001
LOWEST_OD600 = .4
HIGHEST_OD600 = .9

Lowest_CFU_at_day_start_estimate = TRANSFER_VOLUME*LOWEST_OD600*(LoMid5_mean - LoMid5_std)
Highest_CFU_at_day_start_estimate = TRANSFER_VOLUME*HIGHEST_OD600*(Mid1_mean + Mid1_std)

print(f"The number of live cells at the start of each day would be"
      f" between roughly {Lowest_CFU_at_day_start_estimate:.2E} and {Highest_CFU_at_day_start_estimate:.2E}.")

The number of live cells at the start of each day would be between roughly 1.24E+06 and 7.31E+06.
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