Enduring effects of perinatal nicotine exposure on murine sleep in adulthood

Vaporized nicotine in utero results in reduced birthweight, increased locomotion, and decreased voluntary exercise, dependent on sex and diet in offspring

Rationale Clinical research has shown that prenatal exposure to nicotine may result in increased obesity risk later in life. Preclinical research has corroborated this finding, but few studies have investigated inhaled nicotine or the interaction with diet on obesity risk. Objective The aim of this study was to investigate the effects of prenatal nicotine exposure on both direct and indirect obesity measures, with both sex and diet as factors. Methods Pregnant rats were exposed to either vehicle or nicotine vapor (24 mg/mL or 59 mg/mL) throughout the entire gestational period. Offspring from each treatment group were given either a normal diet or a high fat diet starting at postnatal day 22. Caloric intake, body weight, spontaneous locomotion, sleep/wake activity, and voluntary exercise were measured throughout adolescence. Pregnancy weight gain and pup birthweights were collected to further measure developmental effects of prenatal nicotine exposure. Results Both maternal weight gain during pregnancy and pup weight at birth were decreased with prenatal nicotine exposure. Early adolescent males showed increased spontaneous activity in the open field following prenatal nicotine exposure compared to vehicle counterparts, particularly those given high-fat diet. Additionally, high dose nicotine prenatal treated males ran significantly less distance on the running wheel in late adolescence compared to vehicle counterparts, in the normal diet group only. Conclusion The results presented here show decreased birthweight, hyperactivity, and decreased voluntary exercise in adolescence following prenatal nicotine exposure in dose, sex, and diet dependent manners, which could lead to increased obesity risk in adulthood.

Early-life nicotine or cotinine exposure produces long-lasting sleep alterations and downregulation of hippocampal corticosteroid receptors in adult mice

Early-life exposure to environmental toxins like tobacco can permanently re-program body structure and function. Here, we investigated the long-term effects on mouse adult sleep phenotype exerted by early-life exposure to nicotine or to its principal metabolite, cotinine. Moreover, we investigated whether these effects occurred together with a reprogramming of the activity of the hippocampus, a key structure to coordinate the hormonal stress response. Adult male mice born from dams subjected to nicotine (NIC), cotinine (COT) or vehicle (CTRL) treatment in drinking water were implanted with electrodes for sleep recordings. NIC and COT mice spent significantly more time awake than CTRL mice at the transition between the rest (light) and the activity (dark) period. NIC and COT mice showed hippocampal glucocorticoid receptor (GR) downregulation compared to CTRL mice, and NIC mice also showed hippocampal mineralocorticoid receptor downregulation. Hippocampal GR expression significantly and inversely correlated with the amount of wakefulness at the light-to-dark transition, while no changes in DNA methylation were found. We demonstrated that early-life exposure to nicotine (and cotinine) concomitantly entails long-lasting reprogramming of hippocampal activity and sleep phenotype suggesting that the adult sleep phenotype may be modulated by events that occurred during that critical period of life.

Peripheral Lipopolyssacharide Rapidly Silences REM-Active LHGABA Neurons

Immune factors (e.g., cytokines, chemokines) can alter the activity of neuronal circuits to promote "sickness behavior," a suite of adaptive actions that organisms exhibit in response to infection/injury in order to maximize their chances of recovery (i.e., return to homeostasis). This includes drastic alterations in sleep/wake states, locomotor activity, and food intake, among other behaviors. Despite the ample evidence highlighting interactions between the brain and systemic immunity, studies on how immune challenges alter the activity of genetically defined cell populations controlling arousal states are scarce. As the lateral hypothalamus (LH) serves a major integrative function in behavioral arousal, food intake, and monitoring and responding to changes in systemic physiology, we investigated how GABAergic neurons within this brain region alter their activity across normal sleep/wake states and in response to a peripheral immune challenge with bacterial endotoxin [lipopolysaccharides (LPS)]. Using fiber photometry (GCaMP6s Ca2+ signal) in tandem with electroencephalogram (EEG)/EMG recordings to determine arousal states, we observed that population activity of GABAergic neurons in the lateral hypothalamus (LHGABA) is highest during rapid-eye-movement sleep (REM), and this activity changes drastically across spontaneous arousal state transitions, with the lowest activity observed during non-REM sleep. Upon intraperitoneal LPS challenge, LHGABA neurons rapidly decrease their activity in tandem with elimination of REM sleep behavior (characteristic of cytokine-induced sickness). Together, these data suggest that peripheral immune challenges can rapidly (in < 40 min) alter subcortical neuronal circuits controlling arousal states. Additionally, we demonstrate that fiber photometry offers a sensitive and cell-type specific tool that can be applied to study the neuronal substrates of sickness behavior.

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice

Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been implemented routinely in neurophysiological analyses. The power of these workflows includes the speed at which they can be deployed, their availability of open-source programming languages, and the objectivity permitted in their data analysis. We used classification-based algorithms, including random forest, gradient boosted machines, support vector machines, and neural networks, to test the hypothesis that the animal genotypes could be separated into their genotype based on interpretation of neurophysiological recordings. We then interrogate the models to identify what were the major features utilized by the algorithms to designate genotype classification. By using raw EEG and respiratory plethysmography data, we were able to predict which recordings came from genotype class with accuracies that were significantly improved relative to the no information rate, although EEG analyses showed more overlap between groups than respiratory plethysmography. In comparison, conventional methods where single features between animal classes were analyzed, differences between the genotypes tested using baseline neurophysiology measurements showed no statistical difference. However, ML/AI workflows successfully were capable of providing successful classification, indicating that interactions between features were different in these genotypes. ML/AI workflows provide new methodologies to interrogate neurophysiology data. However, their implementation must be done with care so as to provide high rigor and reproducibility between laboratories. We provide a series of recommendations on how to report the utilization of ML/AI workflows for the neurophysiology community.NEW & NOTEWORTHY ML/AI classification workflows are capable of providing insight into differences between genotypes for neurophysiology research. Analytical techniques utilized in the neurophysiology community can be augmented by implementing ML/AI workflows. Random forest is a robust classification algorithm for respiratory plethysmography data. Utilization of ML/AI workflows in neurophysiology research requires heightened transparency and improved community research standards.

miR-155 deletion modulates lipopolysaccharide-induced sleep in female mice

Immune signaling is known to regulate sleep. miR-155 is a microRNA that regulates immune responses. We hypothesized that miR-155 would alter sleep regulation. Thus, we investigated the potential effects of miR-155 deletion on sleep-wake behavior in adult female homozygous miR-155 knockout (miR-155^KO) mice and littermate controls (WT). Mice were implanted with biotelemetry units and EEG/EMG biopotentials were recorded continuously for three baseline days. miR-155^KO mice had decreased bouts of NREM and REM sleep compared with WT mice, but no differences were observed in the length of sleep bouts or total time spent in sleep-wake states. Locomotor activity and subcutaneous temperature did not differ between WT and miR-155^KO mice. Following baseline recordings, mice were sleep-deprived during the first six hours of the rest phase (light phase; ZT 0-6) followed by an 18 h recovery period. There were no differences between groups in sleep rebound (% sleep and NREM δ power) after sleep deprivation. Following recovery from sleep deprivation, mice were challenged with a somnogen (viz., lipopolysaccharide (LPS)) one hour prior to the initiation of the dark (active) phase. Biopotentials were continuously recorded for the following 24 h, and miR-155^KO mice displayed increased wakefulness and decreased NREM sleep during the dark phase following LPS injection. Additionally, miR-155^KO mice had reduced EEG slow-wave responses (0.5-4 Hz) compared to WT mice. Together, our findings indicate that miR-155 deletion attenuates the somnogenic and EEG delta-enhancing effects of LPS. Abbreviations: ANOVA: analysis of variance; EEG: electroencephalogram; EMG: electromyogram; h: hour; IL-1: interleukin-1; IL-6: interleukin-6; IP: intra-peritoneal; LPS: lipopolysaccharide; miR/miRNA: microRNA; miR-155^KO: miR-155 knockout; NREM: non-rapid eye movement; REM: rapid eye movement; TNF: tumor necrosis factor; SWS: slow-wave sleep; WT: wild-type.