Method to obtain pattern of breathing in senescent mice through unrestrained barometric plethysmography

Document Type

Article

Publication Title

Journal of Visualized Experiments

Abstract

Unrestrained barometric plethysmography (UBP) is a method for quantifying the pattern of breathing in mice, where breathing frequency, tidal volume, and minute ventilation are routinely reported. Moreover, information can be collected regarding the neural output of breathing, including the existence of central apneas and augmented breaths. An important consideration for UBP is obtaining a breathing segment with a minimal impact of anxious or active behaviors, to elucidate the response to breathing challenges. Here, we present a protocol that allows for short, quiet baselines to be obtained in aged mice, comparable to waiting for longer bouts of quiet breathing. The use of shorter time segments is valuable, as some strains of mice may be increasingly excitable or anxious, and longer periods of quiet breathing may not be achieved within a reasonable timeframe. We placed 22 month-old mice in a UBP chamber and compared four 15 s quiet breathing segments between minutes 60–120 to a longer 10 min quiet breathing period that took 2–3 h to acquire. We also obtained counts of central apneas and augmented breaths prior to the quiet breathing segments, following a 30 min familiarization period. We show that 10 min of quiet breathing is comparable to using a much shorter 15 s duration. Additionally, the time leading up to these 15 s quiet breathing segments can be used to gather data regarding apneas of central origin. This protocol allows investigators to collect pattern-of-breathing data in a set amount of time and makes quiet baseline measures feasible for mice that may exhibit increased amounts of excitable behavior. The UBP methodology itself provides a useful and noninvasive way to collect pattern-of-breathing data and allows for mice to be tested over several time points.

DOI

10.3791/59393

Publication Date

4-1-2020

Share

COinS