Changes in skeletal muscle and tendon structure and function following genetic inactivation of myostatin in rats

Myostatin is a negative regulator of skeletal muscle and tendon mass. Myostatin deficiency has been well studied in mice, but limited data are available on how myostatin regulates the structure and function of muscles and tendons of larger animals. We hypothesized that, in comparison to wild‐type (MSTN+/+) rats, rats in which zinc finger nucleases were used to genetically inactivate myostatin (MSTNΔ/Δ) would exhibit an increase in muscle mass and total force production, a reduction in specific force, an accumulation of type II fibres and a decrease and stiffening of connective tissue. Overall, the muscle and tendon phenotype of myostatin‐deficient rats was markedly different from that of myostatin‐deficient mice, which have impaired contractility and pathological changes to fibres and their extracellular matrix. Extensor digitorum longus and soleus muscles of MSTNΔ/Δ rats demonstrated 20–33% increases in mass, 35–45% increases in fibre number, 20–57% increases in isometric force and no differences in specific force. The insulin‐like growth factor‐1 pathway was activated to a greater extent in MSTNΔ/Δ muscles, but no substantial differences in atrophy‐related genes were observed. Tendons of MSTNΔ/Δ rats had a 20% reduction in peak strain, with no differences in mass, peak stress or stiffness. The general morphology and gene expression patterns were similar between tendons of both genotypes. This large rodent model of myostatin deficiency did not have the negative consequences to muscle fibres and extracellular matrix observed in mouse models, and suggests that the greatest impact of myostatin in the regulation of muscle mass may not be to induce atrophy directly, but rather to block hypertrophy signalling.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111244/1/tjp6572.pd

Plasma ferritin concentration is positively associated with in vivo fatty acid mobilization and insulin resistance in obese women

High rates of fatty acid (FA) mobilization from adipose tissue are associated with insulin resistance (IR) in obesity. In vitro evidence suggests that iron stimulates lipolysis in adipocytes, but whether iron is related to in vivo FA mobilization is unknown. We hypothesized that plasma ferritin concentration ([ferritin]), a marker of body iron stores, would be positively associated with FA mobilization. We measured [ferritin], the rate of appearance of FA in the systemic circulation (FA Ra; stable isotope dilution), key adipose tissue lipolytic proteins and IR (hyperinsulinaemicâ euglycaemic clamp) in 20 obese, premenopausal women. [Ferritin] was correlated with FA Ra (r = 0.65; P = 0.002) and IR (r = 0.57; P = 0.008); these relationships remained significant after controlling for body mass index and plasma [Câ reactive protein] (a marker of systemic inflammation) in multiple regression analyses. We then stratified subjects into tertiles based on [ferritin] to compare subjects with â Highâ ferritinâ versus â Lowâ ferritinâ . Plasma [hepcidin] was more than fivefold greater (P < 0.05) in the Highâ ferritin versus Lowâ ferritin group, but there was no difference in plasma [Câ reactive protein] between groups, indicating that the large difference in plasma [ferritin] reflects a difference in iron stores, not systemic inflammation. We found that FA Ra, adipose protein abundance of hormoneâ sensitive lipase and adipose triglyceride lipase, and IR were significantly greater in subjects with Highâ ferritin versus Lowâ ferritin (all P < 0.05). These data provide the first evidence linking iron and in vivo FA mobilization and suggest that elevated iron stores might contribute to IR in obesity by increasing systemic FA availability.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146491/1/eph12367_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146491/2/eph12367.pd

Early satellite cell communication creates a permissive environment for long-term muscle growth

Using in vivo muscle stem cell (satellite cell)-specific extracellular vesicle (EV) tracking, satellite cell depletion, in vitro cell culture, and single-cell RNA sequencing, we show satellite cells communicate with other cells in skeletal muscle during mechanical overload. Early satellite cell EV communication primes the muscle milieu for proper long-term extracellular matrix (ECM) deposition and is sufficient to support sustained hypertrophy in adult mice, even in the absence of fusion to muscle fibers. Satellite cells modulate chemokine gene expression across cell types within the first few days of loading, and EV delivery of miR 206 to fibrogenic cells represses Wisp1 expression required for appropriate ECM remodeling. Late-stage communication from myogenic cells during loading is widespread but may be targeted toward endothelial cells. Satellite cells coordinate adaptation by influencing the phenotype of recipient cells, which extends our understanding of their role in muscle adaptation beyond regeneration and myonuclear donation

Shaping Embodied Neural Networks for Adaptive Goal-directed Behavior

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery