What does indirect calorimetry really tell us?

Highlighting when animals expend excessive energy for travel using Dynamic Body Acceleration

Travel represents a major cost for many animals so there should be selection pressure for it to be efficient – at minimum cost. However, animals sometimes exceed minimum travel costs for reasons that must be correspondingly important. We use Dynamic Body Acceleration (DBA), an acceleration-based metric, as a proxy for movement-based power, in tandem with vertical velocity (rate of change in depth) in a shark (Rhincodon typus) to derive the minimum estimated power required to swim at defined vertical velocities. We show how subtraction of measured DBA from the estimated minimum power for any given vertical velocity provides a “proxy for power above minimum” metric (PPA_min), highlighting when these animals travel above minimum power. We suggest that the adoption of this metric across species has value in identifying where and when animals are subject to compelling conditions that lead them to deviate from ostensibly judicious energy expenditure.

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Plots of vertical speed vs DBA in sharks show swimming with minimum power

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DBA values above this minimum indicate higher speeds or increases in drag

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Linked to space use, this can identify regions and times of excess power use

Methods for the Comprehensive in vivo Analysis of Energy Flux, Fluid Homeostasis, Blood Pressure, and Ventilatory Function in Rodents

Cardiovascular disease represents the leading cause of death in the United States, and metabolic diseases such as obesity represent the primary impediment to improving cardiovascular health. Rodent (mouse and rat) models are widely used to model cardiometabolic disease, and as a result, there is increasing interest in the development of accurate and precise methodologies with sufficiently high resolution to dissect mechanisms controlling cardiometabolic physiology in these small organisms. Further, there is great utility in the development of centralized core facilities furnished with high-throughput equipment configurations and staffed with professional content experts to guide investigators and ensure the rigor and reproducibility of experimental endeavors. Here, we outline the array of specialized equipment and approaches that are employed within the Comprehensive Rodent Metabolic Phenotyping Core (CRMPC) and our collaborating laboratories within the Departments of Physiology, Pediatrics, Microbiology & Immunology, and Biomedical Engineering at the Medical College of Wisconsin (MCW), for the detailed mechanistic dissection of cardiometabolic function in mice and rats. We highlight selected methods for the analysis of body composition and fluid compartmentalization, electrolyte accumulation and flux, energy accumulation and flux, physical activity, ingestive behaviors, ventilatory function, blood pressure, heart rate, autonomic function, and assessment and manipulation of the gut microbiota. Further, we include discussion of the advantages and disadvantages of these approaches for their use with rodent models, and considerations for experimental designs using these methods.

Comprehensive Assessments of Energy Balance in Mice

Increasing evidence supports a major role for the renin-angiotensin system (RAS) in energy balance physiology. The RAS exists as a circulating system but also as a local paracrine/autocrine signaling mechanism in target tissues including the gastrointestinal tract, the brain, the kidney, and distinct adipose beds. Through activation of various receptors in these target tissues, the RAS contributes to the control of food intake behavior, digestive efficiency, spontaneous physical activity, and aerobic and anaerobic resting metabolism. Although the assortment of methodologies available to assess the various aspects of energy balance can be daunting for an investigator new to this area, a relatively straightforward array of entry-level and advanced methodologies can be employed to comprehensively and quantitatively dissect the effects of experimental manipulations on energy homeostasis. Such methodologies and a simple initial workflow for the use of these methods are described in this chapter, including the use of metabolic caging systems, bomb calorimetry, body composition analyzers, respirometry systems, and direct calorimetry systems. Finally, a brief discussion of the statistical analyses of metabolic data is included.

Oxygen consumption rate v. rate of energy utilization of fishes: a comparison and brief history of the two measurements

Accounting for energy use by fishes has been taking place for over 200 years. The original, and continuing gold standard for measuring energy use in terrestrial animals, is to account for the waste heat produced by all reactions of metabolism, a process referred to as direct calorimetry. Direct calorimetry is not easy or convenient in terrestrial animals and is extremely difficult in aquatic animals. Thus, the original and most subsequent measurements of metabolic activity in fishes have been measured via indirect calorimetry. Indirect calorimetry takes advantage of the fact that oxygen is consumed and carbon dioxide is produced during the catabolic conversion of foodstuffs or energy reserves to useful ATP energy. As measuring [CO2 ] in water is more challenging than measuring [O2 ], most indirect calorimetric studies on fishes have used the rate of O2 consumption. To relate measurements of O2 consumption back to actual energy usage requires knowledge of the substrate being oxidized. Many contemporary studies of O2 consumption by fishes do not attempt to relate this measurement back to actual energy usage. Thus, the rate of oxygen consumption (M˙O2 ) has become a measurement in its own right that is not necessarily synonymous with metabolic rate. Because all extant fishes are obligate aerobes (many fishes engage in substantial net anaerobiosis, but all require oxygen to complete their life cycle), this discrepancy does not appear to be of great concern to the fish biology community, and reports of fish oxygen consumption, without being related to energy, have proliferated. Unfortunately, under some circumstances, these measures can be quite different from one another. A review of the methodological history of the two measurements and a look towards the future are included.

Opposing tissue-specific roles of angiotensin in the pathogenesis of obesity, and implications for obesity-related hypertension

Metabolic disease, specifically obesity, has now become the greatest challenge to improving cardiovascular health. The renin-angiotensin system (RAS) exists as both a circulating hormone system and as a local paracrine signaling mechanism within various tissues including the brain, kidney, and adipose, and this system is strongly implicated in cardiovascular health and disease. Growing evidence also implicates the RAS in the control of energy balance, supporting the concept that the RAS may be mechanistically involved in the pathogenesis of obesity and obesity hypertension. Here, we review the involvement of the RAS in the entire spectrum of whole organism energy balance mechanisms, including behaviors (food ingestion and spontaneous physical activity) and biological processes (digestive efficiency and both aerobic and nonaerobic resting metabolic rates). We hypothesize that opposing, tissue-specific effects of the RAS to modulate these various components of energy balance can explain the apparently paradoxical results reported by energy-balance studies that involve stimulating, versus disrupting, the RAS. We propose a model in which such opposing and tissue-specific effects of the RAS can explain the failure of simple, global RAS blockade to result in weight loss in humans, and hypothesize that obesity-mediated uncoupling of endogenous metabolic rate control mechanisms can explain the phenomenon of obesity-related hypertension.

Use of metabolic monitors in a multidisciplinary Intensive Care Unit: A prospective pilot study of 20 patients

Introduction:

Caloric intake of critically ill patients are usually calculated using predictive equations. Recent advances in gas exchange measurements have the potential to estimate energy expenditure at the bedside and at different time periods.

Materials and Methods:

Energy needs of critically ill patients were estimated over a period of 3 months using simplistic formula of 25 kcal/kg/day estimated energy expenditure (EEE), Harris–Benedict equation (HBE) (Basal energy expenditure [BEE]) and M-COVX™ metabolic monitor resting energy expenditure (REE) on day 4 of Intensive Care Unit (ICU) admission. Calculations based on HBE were taken as standard, and percentage errors (PE) were calculated for each patient for values derived from simplistic formula and metabolic monitor. Adequacy of nutritional intake in ICU was also assessed.

Results:

Metabolic monitor could be used in only 20/70 patients. The mean age of patients was 40 years, 65% were males, and average body mass index was 23.69 kg/m². Intermittent intolerance to feeds was reported in 50%. Values of REE and EEE were greater than BEE in 70% of patients. A significant difference was reported in values of PE of ≤20% and ≥30%; P = 0.0003 and 0.0001, respectively estimated using REE and EEE.

Conclusions:

It is not feasible to use metabolic monitors in all patients. Variability in readings is large and further studies are needed to establish the validity of its measurements. Calculations using simplistic formulas are much closer to values obtained using HBE.

Exploration of Energy Metabolism in the Mouse Using Indirect Calorimetry: Measurement of Daily Energy Expenditure (DEE) and Basal Metabolic Rate (BMR)

Current comprehensive mouse metabolic phenotyping involves studying energy balance in cohorts of mice via indirect calorimetry, which determines heat release from changes in respiratory air composition. Here, we describe the measurement of daily energy expenditure (DEE) and basal metabolic rate (BMR) in mice. These well-defined metabolic descriptors serve as meaningful first-line read-outs for metabolic phenotyping and should be reported when exploring energy expenditure in mice. For further guidance, the issue of appropriate sample sizes and the frequency of sampling of metabolic measurements is also discussed.

Mathematical model for the contribution of individual organs to non-zero y-intercepts in single and multi-compartment linear models of whole-body energy expenditure

Mathematical models for the dependence of energy expenditure (EE) on body mass and composition are essential tools in metabolic phenotyping. EE scales over broad ranges of body mass as a non-linear allometric function. When considered within restricted ranges of body mass, however, allometric EE curves exhibit ‘local linearity.’ Indeed, modern EE analysis makes extensive use of linear models. Such models typically involve one or two body mass compartments (e.g., fat free mass and fat mass). Importantly, linear EE models typically involve a non-zero (usually positive) y-intercept term of uncertain origin, a recurring theme in discussions of EE analysis and a source of confounding in traditional ratio-based EE normalization. Emerging linear model approaches quantify whole-body resting EE (REE) in terms of individual organ masses (e.g., liver, kidneys, heart, brain). Proponents of individual organ REE modeling hypothesize that multi-organ linear models may eliminate non-zero y-intercepts. This could have advantages in adjusting REE for body mass and composition. Studies reveal that individual organ REE is an allometric function of total body mass. I exploit first-order Taylor linearization of individual organ REEs to model the manner in which individual organs contribute to whole-body REE and to the non-zero y-intercept in linear REE models. The model predicts that REE analysis at the individual organ-tissue level will not eliminate intercept terms. I demonstrate that the parameters of a linear EE equation can be transformed into the parameters of the underlying ‘latent’ allometric equation. This permits estimates of the allometric scaling of EE in a diverse variety of physiological states that are not represented in the allometric EE literature but are well represented by published linear EE analyses.