Host circadian rhythms are disrupted during malaria infection in parasite genotype-specific manners

Infection can dramatically alter behavioural and physiological traits as hosts become sick and subsequently return to health. Such “sickness behaviours” include disrupted circadian rhythms in both locomotor activity and body temperature. Host sickness behaviours vary in pathogen species-specific manners but the influence of pathogen intraspecific variation is rarely studied. We examine how infection with the murine malaria parasite, Plasmodium chabaudi, shapes sickness in terms of parasite genotype-specific effects on host circadian rhythms. We reveal that circadian rhythms in host locomotor activity patterns and body temperature become differentially disrupted and in parasite genotype-specific manners. Locomotor activity and body temperature in combination provide more sensitive measures of health than commonly used virulence metrics for malaria (e.g. anaemia). Moreover, patterns of host disruption cannot be explained simply by variation in replication rate across parasite genotypes or the severity of anaemia each parasite genotype causes. It is well known that disruption to circadian rhythms is associated with non-infectious diseases, including cancer, type 2 diabetes, and obesity. Our results reveal that disruption of host circadian rhythms is a genetically variable virulence trait of pathogens with implications for host health and disease tolerance.


Supplementary Figures
Supplementary Figure S1. Incorporating levels of disruption to locomotor activity (a) and body temperature (b) with parasite genotype-specific effects on host sickness during malaria infection. Disease map of host sickness using the relationship between red blood cell and parasite density for three parasite genotypes (N£15 per genotype: green circles=AJ, orange triangles=AS, blue squares=DK) measured each day post infection (PI) for 14 days. Size of points corresponds to the similarity between a) locomotor activity rhythms and b) body temperature rhythms on each day post infection compared to before infection (higher R 2 /larger points illustrates rhythms that more similar to those before infection). Associated with Figures 2, 4 and 5. Infection segments include "asymptomatic", "moderate", "severe" and "recovery". We collapsed data collected during each 3-day infection segment into one 24-hour period by calculating the average locomotor activity and body temperature for every hour during the circadian cycle, for each mouse (i.e. 24 data points for each mouse per segment comprising of the hourly average over 72 hours of infection).
Time-of-peak; Methods:Data analyses:Genotype-specific effects on host rhythms during infection Using the hourly binned data, we fit sine and cosine terms in a linear mixed effects model to the segment summary data. By finding the maximum of the fitted curve we get an estimate for what time-of-day (ZT) the maximum amount of locomotor activity or body temperature occurs during each infection segment. If neither sine nor cosine term are significant in the model, then the data is not deemed rhythmic and neither time-of-peak nor amplitude are calculated.
Amplitude; Methods:Data analyses:Genotype-specific effects on host rhythms during infection By fitting sine and cosine terms in a linear mixed effects model to the segment summary data, the fitted curve provides estimates for the amplitude of the data (the change between peak and trough) during each infection segment.
Amount of locomotor activity and mean body temperature; Methods:Data analyses:Genotype-specific effects on host rhythms during infection Using the number of activity "bouts" and mean body temperature in 5minute intervals, we take measures of day and night time locomotor activity using the middle 8 hours of night and day (ZT14-22 and ZT2-10), to remove fluctuations caused by lights off/on. This gives us a measure of the actual amount of locomotor activity and body temperature to compare between genotypes (alongside time-of-peak and amplitude).
Change in locomotor activity and body temperature, R 2 ; Methods:Data analyses:Replication rate and anaemia explaining disruption to host rhythms Changes in host rhythms were measured by using daily R 2 values as a metric for rhythm similarity. To do this, locomotor activity and body temperature data were binned every hour for each day post infection. For every mouse, a linear regression was performed using the binned data for each day post infection against that mouse's average rhythm before infection (24 data points; the hourly average over 48-72 hours of monitoring). This resulted in a daily R 2 value which reflects how much host rhythms deviate during infections from their patterns when mice were healthy. R 2 varies between 0 and 1; an R 2 of 1 indicates that the rhythm on that particular day post infection is identical to that observed before infection.
Supplementary  Supplementary Table S5. The relationship between red blood cell and parasite density and locomotor activity and body temperature differs between genotypes. Plotting locomotor activity or body temperature disruption (see Supplementary Table S1: Change in locomotor activity and body temperature, R 2 ) against red blood cell (RBC) or parasite density. Each genotype is compared and parameter estimates, standard errors, t values for each comparison and adjusted p values (corrected for multiple comparisons) are reported. Significant differences between genotypes are highlighted in bold. Associated with Figure 5.