Development of the brainstem respiratory circuit

Criteria for central respiratory chemoreceptors: experimental evidence supporting current candidate cell groups

An interoceptive homeostatic system monitors levels of CO2/H+ and provides a proportionate drive to respiratory control networks that adjust lung ventilation to maintain physiologically appropriate levels of CO2 and rapidly regulate tissue acid-base balance. It has long been suspected that the sensory cells responsible for the major CNS contribution to this so-called respiratory CO2/H+ chemoreception are located in the brainstem-but there is still substantial debate in the field as to which specific cells subserve the sensory function. Indeed, at the present time, several cell types have been championed as potential respiratory chemoreceptors, including neurons and astrocytes. In this review, we advance a set of criteria that are necessary and sufficient for definitive acceptance of any cell type as a respiratory chemoreceptor. We examine the extant evidence supporting consideration of the different putative chemoreceptor candidate cell types in the context of these criteria and also note for each where the criteria have not yet been fulfilled. By enumerating these specific criteria we hope to provide a useful heuristic that can be employed both to evaluate the various existing respiratory chemoreceptor candidates, and also to focus effort on specific experimental tests that can satisfy the remaining requirements for definitive acceptance.

Glutamatergic cerebellar neurons differentially contribute to the acquisition of motor and social behaviors

Insults to the developing cerebellum can cause motor, language, and social deficits. Here, we investigate whether developmental insults to different cerebellar neurons constrain the ability to acquire cerebellar-dependent behaviors. We perturb cerebellar cortical or nuclei neuron function by eliminating glutamatergic neurotransmission during development, and then we measure motor and social behaviors in early postnatal and adult mice. Altering cortical and nuclei neurons impacts postnatal motor control and social vocalizations. Normalizing neurotransmission in cortical neurons but not nuclei neurons restores social behaviors while the motor deficits remain impaired in adults. In contrast, manipulating only a subset of nuclei neurons leaves social behaviors intact but leads to early motor deficits that are restored by adulthood. Our data uncover that glutamatergic neurotransmission from cerebellar cortical and nuclei neurons differentially control the acquisition of motor and social behaviors, and that the brain can compensate for some but not all perturbations to the developing cerebellum.

mRNA isoform balance in neuronal development and disease

Balanced mRNA isoform diversity and abundance are spatially and temporally regulated throughout cellular differentiation. The proportion of expressed isoforms contributes to cell type specification and determines key properties of the differentiated cells. Neurons are unique cell types with intricate developmental programs, characteristic cellular morphologies, and electrophysiological potential. Neuron-specific gene expression programs establish these distinctive cellular characteristics and drive diversity among neuronal subtypes. Genes with neuron-specific alternative processing are enriched in key neuronal functions, including synaptic proteins, adhesion molecules, and scaffold proteins. Despite the similarity of neuronal gene expression programs, each neuronal subclass can be distinguished by unique alternative mRNA processing events. Alternative processing of developmentally important transcripts alters coding and regulatory information, including interaction domains, transcript stability, subcellular localization, and targeting by RNA binding proteins. Fine-tuning of mRNA processing is essential for neuronal activity and maintenance. Thus, the focus of neuronal RNA biology research is to dissect the transcriptomic mechanisms that underlie neuronal homeostasis, and consequently, predispose neuronal subtypes to disease. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

The integrated brain network that controls respiration

Respiration is a brain function on which our lives essentially depend. Control of respiration ensures that the frequency and depth of breathing adapt continuously to metabolic needs. In addition, the respiratory control network of the brain has to organize muscular synergies that integrate ventilation with posture and body movement. Finally, respiration is coupled to cardiovascular function and emotion. Here, we argue that the brain can handle this all by integrating a brainstem central pattern generator circuit in a larger network that also comprises the cerebellum. Although currently not generally recognized as a respiratory control center, the cerebellum is well known for its coordinating and modulating role in motor behavior, as well as for its role in the autonomic nervous system. In this review, we discuss the role of brain regions involved in the control of respiration, and their anatomical and functional interactions. We discuss how sensory feedback can result in adaptation of respiration, and how these mechanisms can be compromised by various neurological and psychological disorders. Finally, we demonstrate how the respiratory pattern generators are part of a larger and integrated network of respiratory brain regions.

Transcription factors regulating the specification of brainstem respiratory neurons

Breathing (or respiration) is an unconscious and complex motor behavior which neuronal drive emerges from the brainstem. In simplistic terms, respiratory motor activity comprises two phases, inspiration (uptake of oxygen, O2) and expiration (release of carbon dioxide, CO2). Breathing is not rigid, but instead highly adaptable to external and internal physiological demands of the organism. The neurons that generate, monitor, and adjust breathing patterns locate to two major brainstem structures, the pons and medulla oblongata. Extensive research over the last three decades has begun to identify the developmental origins of most brainstem neurons that control different aspects of breathing. This research has also elucidated the transcriptional control that secures the specification of brainstem respiratory neurons. In this review, we aim to summarize our current knowledge on the transcriptional regulation that operates during the specification of respiratory neurons, and we will highlight the cell lineages that contribute to the central respiratory circuit. Lastly, we will discuss on genetic disturbances altering transcription factor regulation and their impact in hypoventilation disorders in humans.

An open-source tool for automated analysis of breathing behaviors in common marmosets and rodents

The respiratory system maintains homeostatic levels of oxygen (O2) and carbon dioxide (CO2) in the body through rapid and efficient regulation of breathing frequency and depth (tidal volume). The commonly used methods of analyzing breathing data in behaving experimental animals are usually subjective, laborious, and time-consuming. To overcome these hurdles, we optimized an analysis toolkit for the unsupervised study of respiratory activities in animal subjects. Using this tool, we analyzed breathing behaviors of the common marmoset (Callithrix jacchus), a New World non-human primate model. Using whole-body plethysmography in room air as well as acute hypoxic (10% O2) and hypercapnic (6% CO2) conditions, we describe breathing behaviors in awake, freely behaving marmosets. Our data indicate that marmosets' exposure to acute hypoxia decreased metabolic rate and increased sigh rate. However, the hypoxic condition did not augment ventilation. Hypercapnia, on the other hand, increased both the frequency and depth (i.e., tidal volume) of breathing.

A critical appraisal of tools for delivery room assessment of the newborn infant

Assessment of an infant's condition in the delivery room represents a prerequisite to adequately initiate medical support. In her seminal paper, Virginia Apgar described five parameters to be used for such an assessment. However, since that time maternal and neonatal care has changed; interventions were improved and infants are even more premature. Nevertheless, the Apgar score is assigned to infants worldwide but there are concerns about low interobserver reliability, especially in preterm infants. Also, resuscitative interventions may preclude the interpretation of the score, which is of concern when used as an outcome parameter in delivery room intervention studies. Within the context of these changes, we performed a critical appraisal on how to assess postnatal condition of the newborn including the clinical parameters of the Apgar score, as well as selected additional parameters and a proposed new scoring system. The development of a new scoring system that guide clinicians in assessing infants and help to decide how to support postnatal adaptation is discussed. IMPACT: This critical paper discusses the reliability of the Apgar score, as well as additional parameters, in order to improve assessment of a newborn's postnatal condition. A revised neonatal scoring system should account for infant maturity and the interventions administered. Delivery room assessment should be directed toward determining how much medical support is needed and how the infant responds to these interventions.

Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution

Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardization of measured breathing in mice across laboratories. These technologies thus allowed for exploration of more precise respiratory pattern changes during the post-natal developmental epoch. Current methods to analyze respiratory behavior utilize plethysmography to acquire standing values of frequency, volume and flow at specific time points in murine maturation. These metrics have historically been independently analyzed as a function of time with no further analysis examining the interplay these variables have with each other and in the context of postnatal maturation or during blood gas homeostasis. We posit that machine learning workflows can provide deeper physiological understanding into the postnatal development of respiration. In this manuscript, we delineate a machine learning workflow based on the R-statistical programming language to examine how variation and relationships of frequency (f) and tidal volume (TV) change with respect to inspiratory and expiratory parameters. Our analytical workflows could successfully predict age and found that the variation and relationships between respiratory metrics are dynamically shifting with age and during hypercapnic breathing. Thus, our work demonstrates the utility of high dimensional analyses to provide reliable class label predictions using non-invasive respiratory metrics. These approaches may be useful in large-scale phenotyping across development and in disease.