Metabolic analysis as a driver for discovery, diagnosis, and therapy.

Metabolic anomalies contribute to tissue dysfunction. Current metabolism research spans from organelles to populations, and new technologies can accommodate investigation across these scales. Here, we review recent advancements in metabolic analysis, including small-scale metabolomics techniques amenable to organelles and rare cell types, functional screening to explore how cells respond to metabolic stress, and imaging approaches to non-invasively assess metabolic perturbations in diseases. We discuss how metabolomics provides an informative phenotypic dimension that complements genomic analysis in Mendelian and non-Mendelian disorders. We also outline pressing challenges and how addressing them may further clarify the biochemical basis of human disease.

Allosteric Coupling of Drug Binding and Intracellular Signaling in the A2A Adenosine Receptor.

Signaling across cellular membranes, the 826 human G protein-coupled receptors (GPCRs) govern a wide range of vital physiological processes, making GPCRs prominent drug targets. X-ray crystallography provided GPCR molecular architectures, which also revealed the need for additional structural dynamics data to support drug development. Here, nuclear magnetic resonance (NMR) spectroscopy with the wild-type-like A2A adenosine receptor (A2AAR) in solution provides a comprehensive characterization of signaling-related structural dynamics. All six tryptophan indole and eight glycine backbone 15N-1H NMR signals in A2AAR were individually assigned. These NMR probes provided insight into the role of Asp522.50 as an allosteric link between the orthosteric drug binding site and the intracellular signaling surface, revealing strong interactions with the toggle switch Trp 2466.48, and delineated the structural response to variable efficacy of bound drugs across A2AAR. The present data support GPCR signaling based on dynamic interactions between two semi-independent subdomains connected by an allosteric switch at Asp522.50.

Structural Studies of Amyloid Proteins at the Molecular Level.

Dozens of proteins are known to convert to the aggregated amyloid state. These include fibrils associated with systemic and neurodegenerative diseases and cancer, functional amyloid fibrils in microorganisms and animals, and many denatured proteins. Amyloid fibrils can be much more stable than other protein assemblies. In contrast to globular proteins, a single protein sequence can aggregate into several distinctly different amyloid structures, termed polymorphs, and a given polymorph can reproduce itself by seeding. Amyloid polymorphs may be the molecular basis of prion strains. Whereas the Protein Data Bank contains some 100,000 globular protein and 3,000 membrane protein structures, only a few dozen amyloid protein structures have been determined, and most of these are short segments of full amyloid-forming proteins. Regardless, these amyloid structures illuminate the architecture of the amyloid state, including its stability and its capacity for formation of polymorphs.

Structure of FUS Protein Fibrils and Its Relevance to Self-Assembly and Phase Separation of Low-Complexity Domains.

Polymerization and phase separation of proteins containing low-complexity (LC) domains are important factors in gene expression, mRNA processing and trafficking, and localization of translation. We have used solid-state nuclear magnetic resonance methods to characterize the molecular structure of self-assembling fibrils formed by the LC domain of the fused in sarcoma (FUS) RNA-binding protein. From the 214-residue LC domain of FUS (FUS-LC), a segment of only 57 residues forms the fibril core, while other segments remain dynamically disordered. Unlike pathogenic amyloid fibrils, FUS-LC fibrils lack hydrophobic interactions within the core and are not polymorphic at the molecular structural level. Phosphorylation of core-forming residues by DNA-dependent protein kinase blocks binding of soluble FUS-LC to FUS-LC hydrogels and dissolves phase-separated, liquid-like FUS-LC droplets. These studies offer a structural basis for understanding LC domain self-assembly, phase separation, and regulation by post-translational modification.

Recruitment of trimeric eIF2 by phosphatase non-catalytic subunit PPP1R15B.

Regulated protein phosphorylation controls most cellular processes. The protein phosphatase PP1 is the catalytic subunit of many holoenzymes that dephosphorylate serine/threonine residues. How these enzymes recruit their substrates is largely unknown. Here, we integrated diverse approaches to elucidate how the PP1 non-catalytic subunit PPP1R15B (R15B) captures its full trimeric eIF2 substrate. We found that the substrate-recruitment module of R15B is largely disordered with three short helical elements, H1, H2, and H3. H1 and H2 form a clamp that grasps the substrate in a region remote from the phosphorylated residue. A homozygous N423D variant, adjacent to H1, reducing substrate binding and dephosphorylation was discovered in a rare syndrome with microcephaly, developmental delay, and intellectual disability. These findings explain how R15B captures its 125 kDa substrate by binding the far end of the complex relative to the phosphosite to present it for dephosphorylation by PP1, a paradigm of broad relevance.

Molecular imaging in oncology: Current impact and future directions.

The authors define molecular imaging, according to the Society of Nuclear Medicine and Molecular Imaging, as the visualization, characterization, and measurement of biological processes at the molecular and cellular levels in humans and other living systems. Although practiced for many years clinically in nuclear medicine, expansion to other imaging modalities began roughly 25 years ago and has accelerated since. That acceleration derives from the continual appearance of new and highly relevant animal models of human disease, increasingly sensitive imaging devices, high-throughput methods to discover and optimize affinity agents to key cellular targets, new ways to manipulate genetic material, and expanded use of cloud computing. Greater interest by scientists in allied fields, such as chemistry, biomedical engineering, and immunology, as well as increased attention by the pharmaceutical industry, have likewise contributed to the boom in activity in recent years. Whereas researchers and clinicians have applied molecular imaging to a variety of physiologic processes and disease states, here, the authors focus on oncology, arguably where it has made its greatest impact. The main purpose of imaging in oncology is early detection to enable interception if not prevention of full-blown disease, such as the appearance of metastases. Because biochemical changes occur before changes in anatomy, molecular imaging-particularly when combined with liquid biopsy for screening purposes-promises especially early localization of disease for optimum management. Here, the authors introduce the ways and indications in which molecular imaging can be undertaken, the tools used and under development, and near-term challenges and opportunities in oncology.

Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians.

Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.

A universal allosteric mechanism for G protein activation.

G proteins play a central role in signal transduction and pharmacology. Signaling is initiated by cell-surface receptors, which promote guanosine triphosphate (GTP) binding and dissociation of Gα from the Gßγ subunits. Structural studies have revealed the molecular basis of subunit association with receptors, RGS proteins, and downstream effectors. In contrast, the mechanism of subunit dissociation is poorly understood. We use cell signaling assays, molecular dynamics (MD) simulations, and biochemistry and structural analyses to identify a conserved network of amino acids that dictates subunit release. In the presence of the terminal phosphate of GTP, a glycine forms a polar network with an arginine and glutamate, putting torsional strain on the subunit binding interface. This "G-R-E motif" secures GTP and, through an allosteric link, discharges the Gßγ dimer. Replacement of network residues prevents subunit dissociation regardless of agonist or GTP binding. These findings reveal the molecular basis of the final committed step of G protein activation.

Genetic architecture of brain morphology and overlap with neuropsychiatric traits.

Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.

The Solution Structure of FUS Bound to RNA Reveals a Bipartite Mode of RNA Recognition with Both Sequence and Shape Specificity.

Fused in sarcoma (FUS) is an RNA binding protein involved in regulating many aspects of RNA processing and linked to several neurodegenerative diseases. Transcriptomics studies indicate that FUS binds a large variety of RNA motifs, suggesting that FUS RNA binding might be quite complex. Here, we present solution structures of FUS zinc finger (ZnF) and RNA recognition motif (RRM) domains bound to RNA. These structures show a bipartite binding mode of FUS comprising of sequence-specific recognition of a NGGU motif via the ZnF and an unusual shape recognition of a stem-loop RNA via the RRM. In addition, sequence-independent interactions via the RGG repeats significantly increase binding affinity and promote destabilization of structured RNA conformation, enabling additional binding. We further show that disruption of the RRM and ZnF domains abolishes FUS function in splicing. Altogether, our results rationalize why deciphering the RNA binding mode of FUS has been so challenging.

Multi-axis fields boost SABRE hyperpolarization.

The inherently low signal-to-noise ratio of NMR and MRI is now being addressed by hyperpolarization methods. For example, iridium-based catalysts that reversibly bind both parahydrogen and ligands in solution can hyperpolarize protons (SABRE) or heteronuclei (X-SABRE) on a wide variety of ligands, using a complex interplay of spin dynamics and chemical exchange processes, with common signal enhancements between 103 and 104. This does not approach obvious theoretical limits, and further enhancement would be valuable in many applications (such as imaging mM concentration species in vivo). Most SABRE/X-SABRE implementations require far lower fields (µT-mT) than standard magnetic resonance (>1T), and this gives an additional degree of freedom: the ability to fully modulate fields in three dimensions. However, this has been underexplored because the standard simplifying theoretical assumptions in magnetic resonance need to be revisited. Here, we take a different approach, an evolutionary strategy algorithm for numerical optimization, multi-axis computer-aided heteronuclear transfer enhancement for SABRE (MACHETE-SABRE). We find nonintuitive but highly efficient multiaxial pulse sequences which experimentally can produce a sevenfold improvement in polarization over continuous excitation. This approach optimizes polarization differently than traditional methods, thus gaining extra efficiency.

Observation of magnetic amplification using dark spins.

Quantum amplification enables the enhancement of weak signals and is of great importance for precision measurements, such as biomedical science and tests of fundamental symmetries. Here, we observe a previously unexplored magnetic amplification using dark noble-gas nuclear spins in the absence of pump light. Such dark spins exhibit remarkable coherence lasting up to 6 min and the resilience against the perturbations caused by overlapping alkali-metal gas. We demonstrate that the observed phenomenon, referred to as "dark spin amplification," significantly magnifies magnetic field signals by at least three orders of magnitude. As an immediate application, we showcase an ultrasensitive magnetometer capable of measuring subfemtotesla fields in a single 500-s measurement. Our approach is generic and can be applied to a wide range of noble-gas isotopes, and we discuss promising optimizations that could further improve the current signal amplification up to [Formula: see text] with [Formula: see text]Ne, [Formula: see text] with [Formula: see text]Xe, and [Formula: see text] with [Formula: see text]He. This work unlocks opportunities in precision measurements, including searches for ultralight dark matter with sensitivity well beyond the supernova-observation constraints.

Brain decoding of spontaneous thought: Predictive modeling of self-relevance and valence using personal narratives.

The contents and dynamics of spontaneous thought are important factors for personality traits and mental health. However, assessing spontaneous thoughts is challenging due to their unconstrained nature, and directing participants' attention to report their thoughts may fundamentally alter them. Here, we aimed to decode two key content dimensions of spontaneous thought-self-relevance and valence-directly from brain activity. To train functional MRI-based predictive models, we used individually generated personal stories as stimuli in a story-reading task to mimic narrative-like spontaneous thoughts (n = 49). We then tested these models on multiple test datasets (total n = 199). The default mode, ventral attention, and frontoparietal networks played key roles in the predictions, with the anterior insula and midcingulate cortex contributing to self-relevance prediction and the left temporoparietal junction and dorsomedial prefrontal cortex contributing to valence prediction. Overall, this study presents brain models of internal thoughts and emotions, highlighting the potential for the brain decoding of spontaneous thought.

Genetics of Dilated Cardiomyopathy.

Dilated cardiomyopathy (DCM) is defined as dilation and/or reduced function of one or both ventricles and remains a common disease worldwide. An estimated 40% of cases of familial DCM have an identifiable genetic cause. Accordingly, there is a fast-growing interest in the field of molecular genetics as it pertains to DCM. Many gene mutations have been identified that contribute to phenotypically significant cardiomyopathy. DCM genes can affect a variety of cardiomyocyte functions, and particular genes whose function affects the cell-cell junction and cytoskeleton are associated with increased risk of arrhythmias and sudden cardiac death. Through advancements in next-generation sequencing and cardiac imaging, identification of genetic DCM has improved over the past couple decades, and precision medicine is now at the forefront of treatment for these patients and their families. In addition to standard treatment of heart failure and prevention of arrhythmias and sudden cardiac death, patients with genetic cardiomyopathy stand to benefit from gene mechanism-specific therapies.

An Insulin-Responsive Sensor in the SIRT1 Disordered Region Binds DBC1 and PACS-2 to Control Enzyme Activity.

Current models of SIRT1 enzymatic regulation primarily consider the effects of fluctuating levels of its co-substrate NAD+, which binds to the stably folded catalytic domain. By contrast, the roles of the sizeable disordered N- and C-terminal regions of SIRT1 are largely unexplored. Here we identify an insulin-responsive sensor in the SIRT1 N-terminal region (NTR), comprising an acidic cluster (AC) and a 3-helix bundle (3HB), controlling deacetylase activity. The allosteric assistor DBC1 removes a distal N-terminal shield from the 3-helix bundle, permitting PACS-2 to engage the acidic cluster and the transiently exposed helix 3 of the 3-helix bundle, disrupting its structure and inhibiting catalysis. The SIRT1 activator (STAC) SRT1720 binds and stabilizes the 3-helix bundle, protecting SIRT1 from inhibition by PACS-2. Identification of the SIRT1 insulin-responsive sensor and its engagement by the DBC1 and PACS-2 regulatory hub provides important insight into the roles of disordered regions in enzyme regulation and the mode by which STACs promote metabolic fitness.

Merged magnetic resonance and light sheet microscopy of the whole mouse brain.

We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 µm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 µm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 µm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.

Increased cortical inhibition following brief motor memory reactivation supports reconsolidation and overnight offline learning gains.

Practicing motor skills stabilizes and strengthens motor memories by repeatedly reactivating and reconsolidating them. The conventional view, by which a repetitive practice is required for substantially improving skill performance, has been recently challenged by behavioral experiments, in which even brief reactivations of the motor memory have led to significant improvements in skill performance. However, the mechanisms which facilitate brief reactivation-induced skill improvements remain elusive. While initial memory consolidation has been repeatedly associated with increased neural excitation and disinhibition, reconsolidation has been shown to involve a poorly understood mixture of both excitatory and inhibitory alterations. Here, we followed a 3-d reactivation-reconsolidation framework to examine whether the excitatory/inhibitory mechanisms which underlie brief reactivation and repetitive practice differ. Healthy volunteers practiced a motor sequence learning task using either brief reactivation or repetitive practice and were assessed using ultrahigh field (7T) magnetic resonance spectroscopy at the primary motor cortex (M1). We found that increased inhibition (GABA concentrations) and decreased excitation/inhibition (glutamate/GABA ratios) immediately following the brief reactivation were associated with overnight offline performance gains. These gains were on par with those exhibited following repetitive practice, where no correlations with inhibitory or excitatory changes were observed. Our findings suggest that brief reactivation and repetitive practice depend on fundamentally different neural mechanisms and that early inhibition-and not excitation-is particularly important in supporting the learning gains exhibited by brief reactivation.

Integration of Prior Expectations and Suppression of Prediction Errors During Expectancy-Induced Pain Modulation: The Influence of Anxiety and Pleasantness.

Pain perception arises from the integration of prior expectations with sensory information. Although recent work has demonstrated that treatment expectancy effects (e.g., placebo hypoalgesia) can be explained by a Bayesian integration framework incorporating the precision level of expectations and sensory inputs, the key factor modulating this integration in stimulus expectancy-induced pain modulation remains unclear. In a stimulus expectancy paradigm combining emotion regulation in healthy male and female adults, we found that participants' voluntary reduction in anticipatory anxiety and pleasantness monotonically reduced the magnitude of pain modulation by negative and positive expectations, respectively, indicating a role of emotion. For both types of expectations, Bayesian model comparisons confirmed that an integration model using the respective emotion of expectations and sensory inputs explained stimulus expectancy effects on pain better than using their respective precision. For negative expectations, the role of anxiety is further supported by our fMRI findings that (1) functional coupling within anxiety-processing brain regions (amygdala and anterior cingulate) reflected the integration of expectations with sensory inputs and (2) anxiety appeared to impair the updating of expectations via suppressed prediction error signals in the anterior cingulate, thus perpetuating negative expectancy effects. Regarding positive expectations, their integration with sensory inputs relied on the functional coupling within brain structures processing positive emotion and inhibiting threat responding (medial orbitofrontal cortex and hippocampus). In summary, different from treatment expectancy, pain modulation by stimulus expectancy emanates from emotion-modulated integration of beliefs with sensory evidence and inadequate belief updating.

Diurnal Variation of Brain Activity in the Human Suprachiasmatic Nucleus.

The suprachiasmatic nucleus (SCN) is the central clock for circadian rhythms. Animal studies have revealed daily rhythms in the neuronal activity in the SCN. However, the circadian activity of the human SCN has remained elusive. In this study, to reveal the diurnal variation of the SCN activity in humans, we localized the SCN by employing an areal boundary mapping technique to resting-state functional images and investigated the SCN activity using perfusion imaging. In the first experiment (n = 27, including both sexes), we scanned each participant four times a day, every 6 h. Higher activity was observed at noon, while lower activity was recorded in the early morning. In the second experiment (n = 20, including both sexes), the SCN activity was measured every 30 min for 6 h from midnight to dawn. The results showed that the SCN activity gradually decreased and was not associated with the electroencephalography. Furthermore, the SCN activity was compatible with the rodent SCN activity after switching off the lights. These results suggest that the diurnal variation of the human SCN follows the zeitgeber cycles of nocturnal and diurnal mammals and is modulated by physical lights rather than the local time.

Interaction networks within disease-associated GαS variants characterized by an integrative biophysical approach.

Activation of G proteins through nucleotide exchange initiates intracellular signaling cascades essential for life processes. Under normal conditions, nucleotide exchange is regulated by the formation of G protein-G protein-coupled receptor complexes. Single point mutations in the Gα subunit of G proteins bypass this interaction, leading to loss of function or constitutive gain of function, which is closely linked with the onset of multiple diseases. Despite the recognized significance of Gα mutations in disease pathology, structural information for most variants is lacking, potentially due to inherent protein dynamics that pose challenges for crystallography. To address this, we leveraged an integrative spectroscopic and computational approach to structurally characterize seven of the most frequently observed and clinically relevant mutations in the stimulatory Gα subunit, GαS. A previously proposed allosteric model of Gα activation linked structural changes in the nucleotide-binding pocket with functionally important changes in interactions between switch regions. We investigated this allosteric connection in GαS by integrating data from variable temperature CD spectroscopy, which measured changes in global protein structure and stability, and molecular dynamics simulations, which observed changes in interaction networks between GαS switch regions. Additionally, saturation-transfer difference NMR spectroscopy was applied to observe changes in nucleotide interactions with residues within the nucleotide binding site. These data have enabled testing of predictions regarding how mutations in GαS result in loss or gain of function and evaluation of proposed structural mechanisms. The integration of experimental and computational data allowed us to propose a more nuanced classification of mechanisms underlying GαS gain-of-function and loss-of-function mutations.