Diurnal oscillations in gut bacterial load and composition eclipse seasonal and lifetime dynamics in wild meerkats

Circadian rhythms in gut microbiota composition are crucial for metabolic function, yet the extent to which they govern microbial dynamics compared to seasonal and lifetime processes remains unknown. Here, we investigate gut bacterial dynamics in wild meerkats (Suricata suricatta) over a 20-year period to compare diurnal, seasonal, and lifetime processes in concert, applying ratios of absolute abundance. We found that diurnal oscillations in bacterial load and composition eclipsed seasonal and lifetime dynamics. Diurnal oscillations were characterised by a peak in Clostridium abundance at dawn, were associated with temperature-constrained foraging schedules, and did not decay with age. Some genera exhibited seasonal fluctuations, whilst others developed with age, although we found little support for microbial senescence in very old meerkats. Strong microbial circadian rhythms in this species may reflect the extreme daily temperature fluctuations typical of arid-zone climates. Our findings demonstrate that accounting for circadian rhythms is essential for future gut microbiome research.


Estimating body condition
Individual meerkats are weighed daily by enticing them onto electronic scales using crumbs of hard-boiled egg. Body condition was represented by residuals from a general additive mixed model (GAMM) predicting weight against age and time of day, using all weight data available for individuals included in this study (n = 234,224 weight measurements from 235 meerkats).
Individual ID was included as a random effect. Although age is the major predictor of weight, we included time of day because body mass changes over the day in response to food intake. In almost all cases a weight measurement was taken on the day of sampling, and for a small proportion of samples weight was taken within a 1-3 days of sampling.

Foraging schedule
We reasoned that gut microbiome dynamics is likely to be impacted by daily foraging patterns and therefore aimed to estimate foraging history at the time of sample collection. Meerkats demonstrate relatively predictable daily foraging patterns, with two peaks in foraging intensityone in the morning and a shorter period in the evening before sunset (Fig. 1a;Doolan and MacDonald, 1996;unpublished data Kalahari Meerkat Project). In the summer, when temperatures reach 40°c during the day, meerkats forage early in the morning and again in the evening, and find shade during the day. In the winter, meerkats maintain this foraging pattern in the morning and evening, yet also forage to some extent during the day (Doolan and MacDonald, 1996). In this study, we calculated mean foraging start and end times per month based on longterm observation data (Fig. S7), and assumed meerkats only foraged during these times. Visual inspection of different social group strategies indicated all groups followed similar foraging schedules across the year. Whilst some foraging is likely to occur outside these times in winter, these represent periods of the most intense foraging and therefore may be expected to be reflected in microbiome dynamics if short-term foraging patterns affect the gut microbiome.
From this schedule, we calculated how long each meerkats had been foraging for prior to sample collection. If the sample was collected outside a foraging period (which was a minority of samples), this number was set to zero.

Time spent in the field
We wanted to account for variation in field time to ensure this variable did not bias results.
Meerkats are monitored during their active foraging periods, and therefore fieldwork is carried out at set times throughout the year. We therefore calculated mean morning and afternoon fieldwork return times per month (because fieldwork times shift with season to match meerkat foraging patterns) and estimated the number of hours each sample was carried in the field before being frozen.

Weather data
Hourly and daily weather data dating back to 1997, when the earliest sample was taken, was provided by the South African Weather Service. Weather data was collected from the Van Zyl Rus weather station, approximately 25 km away from the study area. We included daily maximum and minimum temperatures, and the temperature at the time the sample was collected.
Total rainfall from the month prior to sample collection was also calculated. Missing weather data after 2009 (n = 30) was replaced by weather data collected by the Kalahari Research Centre, whilst missing weather data prior to this point (n = 50) was replaced with mean values for that calendar day calculated across 20 years.