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Biological clocks allow organisms to anticipate cycles of feeding, activity, and rest so that metabolic enzymes in mitochondria are ready when needed. Peek et al. ( 10.1126/science.1243417 , published online 19 September; see the Perspective by Rey and Reddy ) describe a mechanism by which the biochemical elements of the circadian clock are linked to such control of mitochondrial metabolism. The clock controls rhythmic transcription of the gene encoding the rate-limiting enzyme required for synthesis of nicotinamide adenine dinucleotide (NAD + ). The concentration of NAD + in mitochondria determines the activity of the deacetylase SIRT3, which then controls acetylation and activity of key metabolic enzymes. NAD+ also influences clock function, and thus appears to be a versatile point at which regulation of oxidative metabolism is coordinated with the daily cycles of energy consumption. The coenzyme nicotinamide adenine dinucleotide mechanistically links the circadian clock to control of energy production by mitochondria. [Also see Perspective by Rey and Reddy ] Circadian clocks are self-sustained cellular oscillators that synchronize oxidative and reductive cycles in anticipation of the solar cycle. We found that the clock transcription feedback loop produces cycles of nicotinamide adenine dinucleotide (NAD + ) biosynthesis, adenosine triphosphate production, and mitochondrial respiration through modulation of mitochondrial protein acetylation to synchronize oxidative metabolic pathways with the 24-hour fasting and feeding cycle. Circadian control of the activity of the NAD + -dependent deacetylase sirtuin 3 (SIRT3) generated rhythms in the acetylation and activity of oxidative enzymes and respiration in isolated mitochondria, and NAD + supplementation restored protein deacetylation and enhanced oxygen consumption in circadian mutant mice. Thus, circadian control of NAD + bioavailability modulates mitochondrial oxidative function and organismal metabolism across the daily cycles of fasting and feeding.

The adipose-derived hormone leptin acts via its receptor (LepRb) in the brain to control energy balance. A potentially unidentified population of GABAergic hypothalamic LepRb neurons plays key roles in the restraint of food intake and body weight by leptin. To identify markers for candidate populations of LepRb neurons in an unbiased manner, we performed single-nucleus RNA-Seq of enriched mouse hypothalamic LepRb cells, identifying several previously unrecognized populations of hypothalamic LepRb neurons. Many of these populations displayed strong conservation across species, including GABAergic Glp1r-expressing LepRb (LepRbGlp1r) neurons, which expressed more Lepr than other LepRb cell populations. Ablating Lepr from LepRbGlp1r cells provoked hyperphagic obesity without impairing energy expenditure. Similarly, improvements in energy balance caused by Lepr reactivation in GABA neurons of otherwise Lepr-null mice required Lepr expression in GABAergic Glp1r-expressing neurons. Furthermore, restoration of Glp1r expression in LepRbGlp1r neurons in otherwise Glp1r-null mice enabled food intake suppression by the GLP1R agonist, liraglutide. Thus, the conserved GABAergic LepRbGlp1r neuron population plays crucial roles in the suppression of food intake by leptin and GLP1R agonists.

The ventromedial hypothalamic nucleus (VMH) controls diverse behaviors and physiologic functions, suggesting the existence of multiple VMH neural subtypes with distinct functions. Combing translating ribosome affinity purification with RNA-sequencing (TRAP-seq) data with single-nucleus RNA-sequencing (snRNA-seq) data, we identified 24 mouse VMH neuron clusters. Further analysis, including snRNA-seq data from macaque tissue, defined a more tractable VMH parceling scheme consisting of six major genetically and anatomically differentiated VMH neuron classes with good cross-species conservation. In addition to two major ventrolateral classes, we identified three distinct classes of dorsomedial VMH neurons. Consistent with previously suggested unique roles for leptin receptor ( Lepr )-expressing VMH neurons, Lepr expression marked a single dorsomedial class. We also identified a class of glutamatergic VMH neurons that resides in the tuberal region, anterolateral to the neuroanatomical core of the VMH. This atlas of conserved VMH neuron populations provides an unbiased starting point for the analysis of VMH circuitry and function.

While Cre-dependent viral systems permit the manipulation of many neuron types, some cell populations cannot be targeted by a single DNA recombinase. Although the combined use of Flp and Cre recombinases can overcome this limitation, insufficient recombinase activity can reduce the efficacy of existing Cre+Flp-dependent viral systems. We developed a sensitive dual recombinase-activated viral approach: tTA-driven Recombinase-Guided Intersectional Targeting (tTARGIT) adeno-associated viruses (AAVs). tTARGIT AAVs utilize a Flp-dependent tetracycline transactivator (tTA) ‘Driver’ AAV and a tetracycline response element-driven, Cre-dependent ‘Payload’ AAV to express the transgene of interest. We employed this system in Slc17a6 FlpO ;Lepr Cre mice to manipulate LepRb neurons of the ventromedial hypothalamus (VMH; LepRb VMH neurons) while omitting neighboring LepRb populations. We defined the circuitry of LepRb VMH neurons and roles for these cells in the control of food intake and energy expenditure. Thus, the tTARGIT system mediates robust recombinase-sensitive transgene expression, permitting the precise manipulation of previously intractable neural populations. The brain contains hundreds of types of neurons, which differ in size, shape and behavior. But neuroscientists often wish to study individual neuronal types in isolation. They are able to do this with the aid of a toolkit made up of two parts: viral vectors and genetically modified mice. Viral vectors are viruses that have been modified so that they are no longer harmful and can instead be used to introduce genetic material into cells on demand. To create a viral vector, the virus’ own genetic material is replaced with a ‘cargo’ gene, such as the gene for a fluorescent protein. The virus is then introduced into a new host such as a mouse. Importantly, the virus only produces the protein encoded by its ‘cargo’ gene if it is inside a cell that also contains one of two specific enzymes. These enzymes are called Cre and Flp. This is where the second part of the toolkit comes in. Mice can be genetically engineered to produce either Cre or Flp exclusively in specific cell types. By introducing a viral vector into mice that produce either Cre or Flp only in one particular type of neuron, researchers can limit the activity of the cargo gene to that neuronal type. But sometimes even this approach is not selective enough. Researchers may wish to limit the activity of the cargo gene to a subpopulation of cells that produce Cre or Flp. Or they may wish to target only Cre- or Flp-producing cells in a small area of the brain, while leaving cells in neighboring areas unaffected. Sabatini et al. have now overcome this limitation by developing and testing a new set of viral vectors that are active only in neurons that produce both Cre and Flp. The vectors are called tTARGIT AAVs and allow researchers to target cells more precisely than was possible with the previous version of the toolkit. Sabatini et al. show tTARGIT AAVs in action by using them to identify a group of neurons that control how much energy mice use and how much food they eat. As well as applying the vectors to their own research on obesity, Sabatini et al. have also made them freely available for other researchers to use in their own projects.

Growing evidence implicates the brain in the regulation of both immediate fuel availability (for example, circulating glucose) and long-term energy stores (that is, adipose tissue mass). Rather than viewing the adipose tissue and glucose control systems separately, we suggest that the brain systems that control them are components of a larger, highly integrated, ‘fuel homeostasis’ control system. This conceptual framework, along with new insights into the organization and function of distinct neuronal systems, provides a context within which to understand how metabolic homeostasis is achieved in both basal and postprandial states. We also review evidence that dysfunction of the central fuel homeostasis system contributes to the close association between obesity and type 2 diabetes, with the goal of identifying more effective treatment options for these common metabolic disorders. Schwartz et al. review mechanisms through which the central nervous system achieves metabolic homeostasis in the basal and postprandial states, and how dysfunction of this integrated central fuel homeostasis control system can contribute to metabolic disease.

Purpose of ReviewWe seek to characterize the impact of bariatric surgery on diabetes mellitus by recalling its history, examining the clinical data, exploring the putative mechanisms of action, and anticipating its future.Recent FindingsResults of clinical trials reveal that bariatric surgery induces remission of diabetes in 33–90% of individuals at 1-year post-treatment versus 0–39% of medically managed. Remission rates decrease over time but remain higher in surgically treated individuals. Investigations have revealed numerous actions of surgery including effects on intestinal physiology, neuronal signaling, incretin hormone secretion, bile acid metabolism, and microbiome changes.SummaryBariatric surgery improves control of diabetes through both weight-dependent and weight-independent actions. These various mechanisms help explain the difference between individuals treated surgically vs. medically. They also explain differing effects of various bariatric surgery procedure types. Understanding how surgery affects diabetes will help optimize utilization of the therapy for both disease prevention and treatment.

Background Severe insulin resistance is an uncommon finding in patients with type 2 diabetes but is often associated with difficult to managing blood glucose. While severe insulin resistance is most frequently seen in the setting of medication side effects or rare genetic conditions, this report of two cases highlights the presence of severe insulin resistance in the setting of severe COVID-19 and explores how this may contribute to the poor prognosis of patients with diabetes who become infected with SARS-CoV-2. Case presentation Here we present the cases of two African-American women with pre-existing type 2 diabetes who developed severe COVID-19 requiring mechanical ventilation and concurrent severe insulin resistance with total daily insulin dose requirements of greater than 5 unit/kg. Both patients received aggressive insulin infusion and subcutaneous insulin therapy to obtain adequate glucose management. As their COVID-19 clinical course improved, their severe insulin resistance improved as well. Conclusions The association between critical illness and hyperglycemia is well documented in the literature, however severe insulin resistance is not commonly identified and may represent a unique clinical feature of the interaction between SARS-CoV-2 infection and type 2 diabetes.

To identify neurons that specifically increase blood glucose from among the diversely functioning cell types in the ventromedial hypothalamic nucleus (VMN), we studied the cholecystokinin receptor B-expressing (CCKBR-expressing) VMN targets of glucose-elevating parabrachial nucleus neurons. Activation of these VMNCCKBR neurons increased blood glucose. Furthermore, although silencing the broader VMN decreased energy expenditure and promoted weight gain without altering blood glucose levels, silencing VMNCCKBR neurons decreased hIepatic glucose production, insulin-independently decreasing blood glucose without altering energy balance. Silencing VMNCCKBR neurons also impaired the counterregulatory response to insulin-induced hypoglycemia and glucoprivation and replicated hypoglycemia-associated autonomic failure. Hence, VMNCCKBR cells represent a specialized subset of VMN cells that function to elevate glucose. These cells not only mediate the allostatic response to hypoglycemia but also modulate the homeostatic setpoint for blood glucose in an insulin-independent manner, consistent with a role for the brain in the insulin-independent control of glucose homeostasis.