Not so fast: Paradoxically increased variability in the glucose tolerance test due to food withdrawal in continuous glucose-monitored mice.

OBJECTIVE: This study was performed to determine the effect of fasting on reproducibility of the glucose tolerance test. Due to individual variation in animal feeding behaviors, fasting animals prior to metabolic and behavioral experiments is widely held to reduce inter-subject variation in glucose and metabolic parameters of preclinical rodent models. Reducing variability is especially important for studies where initial metabolite levels can influence the magnitude of experimental interventions, but fasting also imposes stress that may distort the variables of interest. One such intervention is the glucose tolerance test (GTT) which measures the maximum response and recovery following a bolus of exogenous glucose. We sought to investigate how fasting affects the response of individual mice to a GTT. METHODS: Using simultaneous continuous glucose monitoring (CGM) and indirect calorimetry, we quantified blood glucose, physical activity, body temperature, metabolic rates, and food consumption levels on a minute-to-minute basis in adult male mice for 4 weeks. We tested the effects of a 4-h or 18-h fast on the GTT to examine the effect of food withdrawal in light or dark photoperiods. Studies were also performed with 4-h fasting in additional mice without implanted CGM probes. RESULTS: Contrary to our expectations, a 4-h fast during the light photoperiod promotes a paradoxical increase in inter-animal variation in metabolic rate, physical activity, body temperature, glycemia, and glucose tolerance. This hyperglycemic and hyper-metabolic phenotype promotes increased corticosterone levels and is consistent with a behavioral stress response to food deprivation, even in well-fed mice. We find that mice undergoing an 18-h fast entered torpor, a hibernation-like state. In addition to low body temperature and metabolic rate, torpor is also associated with glucose levels 56 mg/dl lower than those seen in mice with ad libitum access to food. Moreover, the time spent in torpor affects the response to a GTT. CONCLUSION: Our results suggest fasting mice before glucose tolerance testing, and perhaps other experiments, can have the opposite of the intended effect where fasting can increase, rather than decrease, experimental variability.

Indirect Calorimetry to Assess Energy Balance in Mice: Measurement and Data Analysis.

Understanding the factors affecting body weight regulation requires careful measurement of food intake and metabolic rates. Modern indirect calorimetry systems are designed to record these features. Here, we describe our approach for reproducible analysis of energy balance experiments performed using indirect calorimetry. CalR, a free online web tool, calculates both instantaneous and cumulative totals for metabolic variables including food intake, energy expenditure, and energy balance making it an excellent start for analyzing energy balance experiments. Energy balance may be one of the most important metrics that CalR calculates as it provides a clear picture of metabolic trends resulting from experimental interventions. Because of the complexity of indirect calorimetry devices and the frequency of mechanical breakdowns, we place a heavy emphasis on the importance of data refinement and visualization. Plots representing energy intake or energy expenditure versus body mass or physical activity can help to identify a malfunctioning apparatus. We also introduce a critical visualization of experimental quality control: a plot of the change in energy balance versus the change in body mass, which simultaneously represents many of the essential components of indirect calorimetry. These analyses and data visualizations allow the investigator to make inferences about experimental quality control and the validity of experimental results.

Analysis of Thermogenesis Experiments with CalR.

Modern indirect calorimetry systems allow for high-frequency time series measurements of the factors affected by thermogenesis: energy intake and energy expenditure. These indirect calorimetry systems generate a flood of raw data recording oxygen consumption, carbon dioxide production, physical activity, and food intake among other factors. Analysis of these data requires time-consuming manual manipulation for formatting, data cleaning, quality control, and visualization. Beyond data handling, analyses of indirect calorimetry experiments require specialized statistical treatment to account for differential contributions of fat mass and lean mass to metabolic rates.Here we describe how to use the software package CalR version 1.2, to analyze indirect calorimetry data from three examples of thermogenesis, cold exposure, adrenergic agonism, and hyperthyroidism in mice, by providing standardized methods for reproducible research. CalR is a free online tool with an easy-to-use graphical user interface to import data files from the Columbus Instruments' CLAMS, Sable Systems' Promethion, and TSE Systems' PhenoMaster. Once loaded, CalR can quickly visualize experimental results and perform basic statistical analyses. We present a framework that standardizes the data structures and analyses of indirect calorimetry experiments to provide reusable and reproducible methods for the physiological data affecting body weight.