Fluidic Analytics – Understand the Machinery of Life
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Have you ever seen a mouse chowing down on its dinner and wondered how it translates to energy? Well, that’s exactly what is keeping some scientists up at night, and luckily these questions are now becoming easier to answer in quite significant detail.
Over the last couple of decades, several companies have developed ‘metabolic cages’. These devices, whilst costly, can measure a plethora of parameters in individual rodents in vivo, from food and water intake to physical activity and energy expenditure with high degrees of accuracy. Recordings can take place over a period of several days, with many machines capable of measuring each variable every few minutes. Metabolic cages have quickly become valuable tools for studying animal models of obesity, diabetes, and related metabolic syndromes, and the resulting data has become commonplace in journals focused on these diseases.
Metabolism in Numbers
When I first came to analyze my own data, I was baffled by the array of numbers and technical jargon churned out into gigantic spreadsheets (and how they all related to each other). But, as it turns out, understanding those numbers becomes a lot easier when broken down into small chunks. So here are a few tips for untangling the terminology behind the science.
Oxygen Consumption/Carbon Dioxide Production
Let’s start with the most obvious metabolic process: oxygen consumption and carbon dioxide production. Most metabolic cages consist of a leak proof cage which allows very precise sensors to measure the amounts of oxygen and carbon dioxide coming into and leaving the chamber. The differences between what is sent in and what comes out is a result of respiration of the (usually) single animal housed in that cage.
Respiratory Exchange Ratio (RER)
RER is derived by dividing carbon dioxide produced by oxygen consumed. This useful number allows you to determine an animal’s primary fuel source. The oxidation of a single molecule of glucose requires a certain amount of oxygen and produces an equal amount of carbon dioxide. Thus, if an animal is purely using glucose for energy, it will have an RER of 1. On the other hand, if fatty acids are used for fuel, the chemical reaction to oxidize a molecule will differ: a greater amount of oxygen is required, which reduced the RER to around 0.7. If the number is somewhere in the middle, it indicates that the fuel source is mixed. This becomes particularly interesting when a genetically altered model has a different RER to its control while on a high fat diet, indicating a fundamental change in fuel utilization.
Energy expenditure is a further extrapolation of some of the other factors encountered so far. The exact formula used can vary between devices, so if you are running your own experiments, it is important to know how your figures have been derived. Energy expenditure is commonly calculated using oxygen consumption and a number known as the calorific value. Simply put, calorific value is obtained by establishing the amount of energy that is produced by burning a standard quantity of a fuel. One of the most important numbers needed to calculate the calorific value is the RER so be sure you know what that fuel source is!
Importantly, because of how energy expenditure is calculated, some machines may refer to this value as ‘heat’. This can be misleading, as it implies that energy expenditure is a direct measurement of temperature. Temperature probes or telemetry devices are available for just such a measurement, and are often reported, so it is worth making sure you know what is being presented in the article you are reading. If in doubt, check the units on the graph!
Many metabolic cages feature infra-red beams, which are broken when an animal moves across them. Often these are measured in multiple axis, for example along the edges of the cage and up the cage (these are so called ‘rearing’ events). Some more advanced devices may have dedicated exercise areas, such as wheels, which will be able to record the duration and intensity of bouts of exercise. This data is important, because individuals may be lean because they are exercising more – and the opposite could be true in an obesity model.
One additional consideration is the break-down of activity between the light and dark cycles. Physical activity, as well as the other parameters mentioned, are often categorized into these two groups. Since rodents are nocturnal, it would be expected that energy expenditure, oxygen consumption, and particularly physical activity would be higher in the dark cycle compared to the light.
There are increasingly more detailed questions asked of these metabolic-read out machines. Add-ons are now available to test specific hypotheses. For example, additional food or water options could be provided to test food or drink preference. At the more complex end, cages can be fitted with detectors which can receive detailed data from telemetry devices surgically implanted into an animal to measure factors like heart rate or blood pressure. External factors can be altered to see how a mouse responds to being placed into a cold environment. The possibilities are endless!
To Sum Up
So, there we have it—a tour into the world of in vivo measures of energy metabolism. The data that stems from these types of experiments may at first appear confusing (there are many other variables that can be measured within them besides those I have mentioned here). But, hopefully, now that you have a bit of background knowledge, you too will be able to unlock the secrets of this useful new tool, and maybe even start planning experiments yourself!
- Tschöp M et al. (2011) A guide to analysis of mouse energy metabolism. Nature Methods 9:57-63
- Speakman J (2013) Measuring energy metabolism in the mouse- theoretical, practical and analytical considerations. Frontiers in Physiology 4:34