Supplementary Information: Methods
We randomly assigned a total of 1440 female, 3-day old mosquitoes to remain either unmanipulated (negative control, n = 480) or to be injected with either 0.2 µL of sterile LBbroth (positive control, n = 480) or 0.2 µL heat-killed Escherechia coli (200,000 bacteria per dose, n = 480). After being anesthetized on ice and challenged, mosquitoes were distributed into cups (n = 20) and placed into one of 12 reach-in incubators consisting of three temperature treatments (18oC, 26oC, 32oC), two diurnal fluctuation treatments (+0oC and +6oC), and two replicates. This experiment was conducted twice, starting at 6:00 AM and at 6:00 PM, to evaluate the effects of time of day and any interactions between time of day and our temperature treatments on mosquito immune gene expression and daily mortality.
We injected a total of 600 female, 3-day old mosquitoes with 0.2 µL live E. coli (2,000 bacteria per dose). After being anesthetized on ice and infected, mosquitoes were distributed into cups (n = 25) and placed into one of 12 reach-in incubators consisting of three temperature treatments (18oC, 26oC, 32oC), two diurnal fluctuation treatments (+0oC and +6oC), and two replicates. This experiment was conducted starting at 6:00 AM and at 6:00 PM to evaluate the effects of time of day and any interactions between time of day and our temperature treatments on mosquito resistance to bacterial growth and daily mortality.
Parton-Logan Curves for the Diurnal Temperature Fluctuation Treatments
The diurnal temperature model:
The Parton-Logan model, characterized by a sinusoidal progression during the daytime and a decreasing exponential curve during the night is a good representation of both the phase and form of natural diurnal temperature rhythms.
where Tmin and Tmax (oC) are the minimum and maximum daily air temperatures, t (hrs) the time, D (hrs) the day length, p (1.5 hr) the time duration between solar noon and Tmax, trise (hrs) the time of sunrise, tset (hrs) the time of sunset,Tset (oC) the temperature at sunset, N (hrs) the duration of the night, and τ the nocturnal time constant. The following parameters were set at these values for each fluctuation around a mean of 18oC, 26oC, and 32oC:
Tmin = 12oC, 20oC, and 26oCtrise= 6 hrs; 6:00 AM
Tmax = 24oC, 32oC, and 38oCtset = 18 hrs; 6:00 PM
D = 12 hrsp = 1.5 hrs
N = 12 hrsτ = 4
We then programmed the diurnally fluctuating incubators with temperatures generated from the above model across various time points in a 24 hr period of time (plots for the program of each incubator are included below).
Incubator Programs:
Supplementary Information Results:
Table 1Final results from generalized linear model analysis of mosquito mortality from the gene expression assay. Significant effects for each factor are in bold (p < 0.05), and dashes indicate higher order interactions that were eliminated from the full model.
Overall, mosquito death was minimal in the gene assay experiment. However, immune challenging mosquitoes in general did increase the number of dead mosquitoes (unmanipulated vs. injury, p < 0.0001; unmanipulated vs. heat-killed E. coli, p < 0.0001; injury vs. heat-killed E. coli, p = 0.686). Similar to the mortality observed in the mosquito resistance assay, more mosquitoes died when they were challenged with heat-killed E. coli in the morning and placed into a warm environment than mosquitoes challenged in the morning and placed into a cool environment (6:00 AM, 18oC vs. 32oC p = 0.026). Further, the effect of mean ambient temperature on mosquito mortality was no longer significant when mosquitoes were challenged in the evening (Fig SI 1).
Figure SI 1Mosquito mortality due to immune challenge was significantly affected by changes in mean ambient temperature and time of day (6:00 AM, black line; 6:00 PM, red line) challenge was administered.