bioRxiv Science⌕ Search

Biology subjects

Hahn, A.

Publications and source records attributed to Hahn, A..

At least 37 records · Page 2Linked to original sources

Novel murine model of human astrovirus infection reveals a cardiovascular tropism

Astroviruses are a common cause of gastrointestinal disease in humans and have been recognized to cause fatal cases of encephalitis. A major barrier to the study of human-infecting astroviruses is the lack of an in vivo model, as previous attempts failed to identify a suitable host that supports viral replication. We describe a novel murine model of infection using astrovirus VA1/HMO-C (VA1), an astrovirus with high seroprevalence in humans that is a causative agent of encephalitis. VA1 RNA levels peak in heart tissue at day 7 post-inoculation. The cardiotropism was observed in multiple different murine genetic backgrounds evidenced by high VA1 RNA loads in heart tissue of A/J, C57BL/6, C3H/HeJ, Balb/c, and J:ARC mice. Infectious VA1 particles could be recovered from heart tissue 3 and 5 days post-inoculation. Intracellular viral capsid was present in tissue sections based on immunofluorescent staining and viral RNA was detected in cardiac myocytes, endocardium, and endothelial cells based on fluorescent in situ hybridization and confocal microscopy. Histologically, we identified inflammatory infiltrates consistent with myocarditis in some mice, with viral RNA co-localizing with the infiltrates. These foci contained CD3+ T cells and CD68+ macrophages. Viral RNA levels increased by > 10-fold in heart tissue or serum samples from Rag1 or Stat1 knockout mice, demonstrating the role of both adaptive and innate immunity in the response to VA1 infection. Based on the in vivo tropisms, we also tested cardiac-derived primary cells and determined that VA1 can replicate in human cardiac microvascular and coronary artery endothelial cells, suggesting a novel cardiovascular tropism in human cells. This novel in vivo model of a human-infecting astrovirus enables further characterization of viral pathogenesis and reveals a new cardiovascular tropism of astroviruses. Author SummaryAstroviruses typically cause viral diarrhea in humans but can also cause serious infections of the brain. Previously, the methods available to study how these viruses lead to invasive infections were limited. Here, we describe the first system to study human-infecting astroviruses using mice. We demonstrate that mice are susceptible to astrovirus VA1, a strain that commonly infects humans and has been linked to fatal brain infections. The virus infected heart tissue and was associated with inflammation. When mice with impaired immune systems were infected with VA1, they were found to have higher amounts of virus in their hearts and blood. Linking back to human health, we also found that VA1 can infect cells derived from human blood vessels of the heart. This model will enable us to better understand how astroviruses cause disease and how the immune system responds to infection. Our findings also suggest that astroviruses could be linked to cardiovascular diseases, including in humans. In the future, we can develop interventions that will prevent and treat astrovirus infections in humans.

microbiology↗

e3SIM: epidemiological-ecological-evolutionary simulation framework for genomic epidemiology

Infectious disease dynamics are driven by the complex interplay of epidemiological, ecological, and evolutionary processes. Accurately modeling these interactions is crucial for understanding pathogen spread and informing public health strategies. However, existing simulators often fail to capture the dynamic interplay between these processes, resulting in oversimplified models that do not fully reflect real-world complexities in which the pathogens genetic evolution dynamically influences disease transmission. We introduce the epidemiological-ecological-evolutionary simulator (e3SIM), an open-source framework that concurrently models the transmission dynamics and molecular evolution of pathogens within a host population while integrating environmental factors. Using an agent-based, discrete-generation, forward-in-time approach, e3SIM incorporates compartmental models, host-population contact networks, and quantitative-trait models for pathogens. This integration allows for realistic simulations of disease spread and pathogen evolution. Key features include a modular and scalable design, flexibility in modeling various epidemiological and population-genetic complexities, incorporation of time-varying environmental factors, and a user-friendly graphical interface. We demonstrate e3SIMs capabilities through simulations of realistic outbreak scenarios with SARS-CoV-2 and Mycobacterium tuberculosis, illustrating its flexibility for studying the genomic epidemiology of diverse pathogen types.

bioinformatics↗

MetaPathways v3.5: Modularity and Scalability Improvements for Pathway Inference from Environmental Genomes

Over the past decade MO_SCPLOWETAC_SCPLOWPO_SCPLOWATHWAYSC_SCPLOW has advanced as a modular pipeline for constructing environmental pathway genome databases (ePGDBs), increasing our understanding of microbial metabolism at the individual, population and community levels of biological organization. With this release, we have addressed several user experience issues related to installation, module integration, and database management. With a refactored code base, MO_SCPLOWETAC_SCPLOWPO_SCPLOWATHWAYSC_SCPLOW v3.5 enhances the user experience through streamlined installation via package indexes or containers, refined modules, and interface upgrades. It boasts updated algorithm support for sequence feature prediction, annotation, metabolic inference, and coverage metrics including genome resolved metagenomes. Tested and refined on synthetic datasets, MO_SCPLOWETAC_SCPLOWPO_SCPLOWATHWAYSC_SCPLOW v3.5 demonstrates improved performance and usability; facilitating more in-depth exploration of microbial interactions and metabolic functions in environmental genomes that scales with con-temporary sequencing throughput. Availability and ImplementationMO_SCPLOWETAC_SCPLOWPO_SCPLOWATHWAYSC_SCPLOW v3.5 is available via AO_SCPLOWNACONDAC_SCPLOW, DO_SCPLOWOCKERC_SCPLOW, and AO_SCPLOWPPTAINERC_SCPLOW. The source code is available on BO_SCPLOWITC_SCPLOWBO_SCPLOWUCKETC_SCPLOW:https://bitbucket.org/BCB2/metapathways/ The documentation is available via RO_SCPLOWEADC_SCPLOWTO_SCPLOWHEC_SCPLOWDO_SCPLOWOCSC_SCPLOW:https://metapathways.readthedocs.io Contactshallam@mail.ubc.ca

bioinformatics↗

Connecting the Dots: Approaching a Standardized Nomenclature for Molecular Connectivity Combining Data and Literature

PET-based connectivity computation is a molecular approach that complements fMRI-derived functional connectivity. However, the diversity of methodologies and terms employed in PET connectivity analysis has resulted in ambiguities and confounded interpretations, highlighting the need for a standardized nomenclature. Drawing parallels from other imaging modalities, we propose "molecular connectivity" as an umbrella term to characterize statistical dependencies between PET signals across brain regions at the individual level (within-subject). Like fMRI resting-state functional connectivity, "molecular connectivity" leverages temporal associations in the PET signal to derive brain network associations. Another within-subject approach evaluates regional similarities of tracer kinetics, which are unique in PET imaging, thus referred to as "kinetic connectivity". On the other hand, "molecular covariance" denotes group-level computations of covariance matrices across-subject. Further specification of the terminology can be achieved by including the employed radioligand, such as "metabolic connectivity/covariance" for [18F]FDG as well as "tau/amyloid covariance" for [18F]flutemetamol / [18F]flortaucipir. To augment these distinctions, high-temporal resolution functional [18F]FDG PET scans from 17 healthy participants were analysed with common techniques of molecular connectivity and covariance, allowing for a data-driven support of the above terminology. Our findings demonstrate that temporal band-pass filtering yields structured network organization, whereas other techniques like 3rd order polynomial fitting, spatio-temporal filtering and baseline normalization require further methodological refinement for high-temporal resolution data. Conversely, molecular covariance from across-subject data provided a simple means to estimate brain region interactions through regularized or sparse inverse covariance estimation. A standardized nomenclature in PET-based connectivity research can reduce ambiguity, enhance reproducibility, and facilitate interpretability across radiotracers and imaging modalities. Via a data-driven approach, this work provides a transparent framework for categorizing and comparing PET-derived connectivity and covariance metrics, laying the foundation for future investigations in the field.

neuroscience↗

Optimal filtering strategies for task-specific functional PET imaging

Functional Positron Emission Tomography (fPET) has advanced as an effective tool for investigating dynamic processes in glucose metabolism and neurotransmitter action, offering potential insights into brain function, disease progression, and treatment development. Despite significant methodological advances, extracting stimulation-specific information presents additional challenges in optimizing signal processing across both spatial and temporal domains, which are essential for obtaining clinically relevant insights. This study aims to provide a systematic evaluation of state-of-the-art filtering techniques for fPET imaging. Forty healthy participants underwent a single [18F]FDG PET/MR scan, engaging in the cognitive task Tetris(R). Twenty thereof also underwent a second PET/MR session. Eight filtering techniques, including 3D and 4D Gaussian smoothing, highly constrained backprojection (hypr), iterative hypr (Ihypr4D), two MRI-Markov Random Field (MRI-MRF) filters (L=10 and 14 mm neighborhood) as well as static and dynamic Non-Local Means (sNLM and dNLM respectively) approaches, were applied to fPET data. Test-retest reliability (intraclass correlation coefficient), the identifiability of the task signal (temporal signal-to-noise ratio (tSNR)), spatial task-based activation (group level t-values), and sample size calculations were assessed. Results indicate distinct performance between filtering techniques. Compared to standard 3D Gaussian smoothing, dNLM, sNLM, MRI-MRF L=10 and Ihypr4D filters exhibited superior tSNR, while only dNLM and hypr showed improved test-retest reliability. Spatial task-based activation was enhanced by both NLM filters and MRI-MRF approaches. The dNLM enabled a minimum reduction of 15.4% in required sample size. The study systematically evaluated filtering techniques in fPET data processing, highlighting their strengths and limitations. The dNLM filter emerges as a promising choice, with improved performance across all metrics. However, filter selection should align with specific study objectives, considering factors like processing time and resource constraints.

neuroscience↗

Metabolomic Profiles and Pathways in Osteoarthritic Human Cartilage: A Comparative Analysis with Healthy Cartilage

ObjectiveOsteoarthritis (OA) is a chronic joint disease with heterogenous metabolic pathology. To gain insight into OA-related metabolism, healthy and end-stage osteoarthritic cartilage were compared metabolically to uncover disease-associated profiles, classify OA-specific metabolic endotypes, and identify targets for intervention for the diverse populations of individuals affected by OA. DesignFemoral head cartilage (n=35) from osteoarthritis patients were collected post-total joint arthroplasty. Healthy cartilage (n=11) was obtained from a tissue bank. Metabolites from all cartilage samples were extracted and analyzed using liquid chromatography-mass spectrometry metabolomic profiling. Additionally, cartilage extracts were pooled and underwent fragmentation analysis for biochemical identification of metabolites. ResultsSpecific metabolites and metabolic pathways, including lipid- and amino acid pathways, were differentially regulated between osteoarthritis-derived and healthy cartilage. The detected alterations of amino acids and lipids highlight key differences in bioenergetic resources, matrix homeostasis, and mitochondrial alterations in osteoarthritis-derived cartilage compared to healthy. Moreover, metabolomic profiles of osteoarthritic cartilage separated into four distinct endotypes highlighting the heterogenous nature of OA metabolism and diverse landscape within the joint between patients. ConclusionsThe results of this study demonstrate that human cartilage has distinct metabolomic profiles between healthy and end-stage osteoarthritis patients. By taking a comprehensive approach to assess metabolic differences between healthy and osteoarthritic cartilage, and within osteoarthritic cartilage alone, several metabolic pathways with distinct regulation patterns were detected. Additional investigation may lead to the identification of metabolites that may serve as valuable indicators of disease status or potential therapeutic targets.

biochemistry↗

Active Suppression of the Nigrostriatal Pathway during Optogenetic Stimulation Revealed by Simultaneous fPET/fMRI

The dopaminergic system is a central component of the brains neurobiological framework, governing motor control, reward responses, and playing an essential role in various brain disorders such as Parkinsons disease and schizophrenia. Within this complex network, the nigrostriatal pathway represents a critical circuit for dopamine transmission from the substantia nigra to the striatum, a connection that is vital to understanding many of the disease-related dysfunctions. However, stand-alone functional magnetic resonance imaging (fMRI) is unable to study the intricate interplay between brain activation and its molecular underpinnings. In our study, the simultaneous use of [18F]FDG functional positron emission tomography (fPET)/BOLD-fMRI provided a new insight that allowed us to demonstrate an active suppression of the nigrostriatal activity during optogenetic stimulation via presynaptic autoinhibition. Our in vivo observation emphasizes that the observed BOLD signal depression during neuronal stimulation does not correlate with neuronal inactivity, but results from an active suppression of neuronal firing as shown by the high [18F]FDG signal increase. This result not only illustrates the potential of simultaneous fPET/fMRI to understand the molecular mechanisms of brain function but also provides a new perspective on how neurotransmitters such as dopamine influence hemodynamic responses in the brain.

neuroscience↗

Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET

Functional positron emission tomography (fPET) with [18F]FDG allows one to quantify stimulation-induced dynamics in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires arterial blood sampling, which can cause discomfort for the participant and increases complexity of the experimental protocol. These constraints have limited the widespread applicability of fPET, especially in the clinical routine. Therefore, we introduce a novel approach, which enables the assessment of the dynamics in cerebral glucose metabolism without the need for an input function. MethodsWe tested the validity of a mathematical derivation on the basis of two independent data sets (DS). For DS1, 52 healthy volunteers (23.2 {+/-} 3.3 years, 24 females) completed a visuo-spatial motor coordination task (the video game Tetris(R)) and for DS2, 18 healthy participants (24.2 {+/-} 4.3 years, 8 females) performed an eyes-open/finger tapping task, both during a [18F]FDG fPET scan. Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as the reference standard. Simplified outcome parameters, such as GLM beta values of task effects and percent signal change (%SC) of both parameters were estimated. These were compared for task-relevant brain regions and on a whole-brain level. ResultsIn general, we observed higher agreement with the reference standard for DS1 (radiotracer administration as bolus + constant infusion) compared to DS2 (constant infusion only). Across both data sets, strong correlations were found between regional task-specific beta estimates and CMRGlu (r = 0.763...0.912). Additionally, %SC of beta values exhibited excellent agreement with %SC of CMRGlu (r = 0.909...0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870...0.979) as well as %SC (Dice = 0.932...0.997), respectively. ConclusionTask-specific changes in glucose metabolism can be reliably estimated using %SC of GLM beta values, eliminating the need for any blood sampling. This approach streamlines fPET imaging, albeit with the trade-off of being unable to quantify baseline metabolism. The proposed simplification enhances the applicability of fPET, allowing for widespread employment in research settings and clinical investigations. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/558617v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@77faeaorg.highwire.dtl.DTLVardef@fa3495org.highwire.dtl.DTLVardef@926353org.highwire.dtl.DTLVardef@b70da0_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET framework at a temporal resolution of 3 seconds. Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which depended on the task-positive network metabolic demands. In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing.

neuroscience↗

Phenotypic Plasticity Drives Seasonal Thermal Tolerance in a Baltic Copepod

Seasonal changes in environmental conditions require substantial physiological responses for population persistence. Phenotypic plasticity is a common mechanism to tolerate these changes, but for organisms with short generation times rapid adaptation may also be a contributing factor. Here, we aimed to disentangle the impacts of adaptation from phenotypic plasticity on thermal tolerance of the calanoid copepod Acartia hudsonica collected throughout spring and summer of a single year. We used a common garden (11 {degrees}C and 18 {degrees}C) design to determine the relative impacts of plasticity versus adaptation. Acartia hudsonica were collected from five time points across the season and thermal tolerance was determined using critical thermal maximum (CTmax) followed by additional measurements after one generation of common garden. As sea surface temperature increased through the season, field collected individuals showed corresponding increases in thermal tolerance but decreases in body size. Despite different thermal tolerances of wild collections, common garden animals did not differ in CTmax within thermal treatments. Instead, there was evidence of phenotypic plasticity where higher temperatures were tolerated by the 18 {degrees}C versus the 11 {degrees}C treatment animals across all collections. Acclimation also had significant effects on body size, with higher temperatures resulting in smaller individuals, consistent with the temperature size rule. Therefore, the differences in thermal tolerance and body size observed in field collected A. hudsonica were likely driven by plasticity rather than adaptation. However, the observed decrease in body size suggests that nutrient availability and ecosystem functioning could be impacted if temperatures consistently increase with no change in copepod abundance. This is the first record of A. hudsonica in the Baltic Sea known to the authors. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/551281v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@814a70org.highwire.dtl.DTLVardef@3e17f0org.highwire.dtl.DTLVardef@95cb3corg.highwire.dtl.DTLVardef@51eb1c_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG HighlightsPhenotypic Plasticity Drives Seasonal Thermal Tolerance in a Baltic Copepod Alexandra Hahn, Reid S. Brennan O_LIAcartia hudsonica shows strong seasonality in thermal tolerance. C_LIO_LIThe observed seasonal differences in CTmax are driven by phenotypic plasticity not adaptation. C_LIO_LIBody size in A. hudsonica is negatively correlated to environmental and developmental temperature. C_LIO_LIThis is the first record of A. hudsonica in the Baltic Sea known to the authors. C_LI

ecology↗

Misregulation of mitochondrial 6mA promotes the propagation of mutant mtDNA and causes aging in C. elegans

In virtually all eukaryotes, the mitochondrial genome (mitochondrial DNA, mtDNA) encodes proteins necessary for oxidative phosphorylation (OXPHOS) and the RNA machinery required for their synthesis inside the mitochondria. Appropriate regulation of mtDNA copy number and expression is essential for ensuring the correct stoichiometric formation of OXPHOS complexes assembled from both nuclear- and mtDNA-encoded subunits. The mechanisms of mtDNA regulation are not completely understood but are essential to organismal viability and lifespan. Here, using multiple approaches, we identify the presence of N6-methylation (6mA) on the mtDNA of diverse animal and plant species. Importantly, we also demonstrate that this modification is regulated in C. elegans by the DNA methyltransferase DAMT-1, and DNA demethylase ALKB-1, which localize to mitochondria. Misregulation of mtDNA 6mA through targeted overexpression of these enzymatic activities inappropriately alters mtDNA copy number and expression, impairing OXPHOS function and producing increased oxidative stress, as well as a shortened lifespan. Compounding defects in mtDNA regulation, reductions in mtDNA 6mA methylation promote the propagation of a deleterious mitochondrial genome across generations. Together, these results reveal that mtDNA 6mA is highly conserved among eukaryotes and regulates lifespan by influencing mtDNA copy number, expression, and heritable mutation levels in vivo.

molecular biology↗

Differential Effects of Mutations of Popeye Domain Containing Proteins on Heteromeric Interaction and Membrane Trafficking

BackgroundThe Popeye domain containing (POPDC) genes encode sarcolemma-localised cAMP effector proteins. Mutations in BVES (POPDC1) and POPDC2 have been associated with limb-girdle muscular dystrophy and cardiac arrhythmia. Muscle biopsies of affected patients display impaired membrane trafficking of both POPDC isoforms. MethodsBiopsy material of patients carrying mutations in BVES were immunostained with POPDC antibodies. The interaction of POPDC proteins was investigated by co-precipitation, proximity ligation, bioluminescence resonance energy transfer and bimolecular fluorescence complementation. Site-directed mutagenesis was utilised to map the domains involved in protein interaction. FindingsPatients carrying a novel homozygous variant, BVES (c.547G>T, p.V183F) displayed only a skeletal muscle pathology and a mild impairment of membrane trafficking of both POPDC isoforms. This is in contrast to variants such as BVES p.Q153X or POPDC2 p.W188X, which were associated with a greater impairment of membrane trafficking. Co-transfection analysis in HEK293 cells revealed that POPDC proteins interact with each other through a helix-helix interface located at the C-terminus of the Popeye domain. Site-directed mutagenesis of an array of ultra-conserved hydrophobic residues demonstrated that some of them are required for membrane trafficking of the POPDC1-POPDC2 complex. InterpretationMutations in POPDC proteins that cause an impairment in membrane localisation affect POPDC complex formation while mutations which leave the protein interaction intact likely affect some other essential function of POPDC proteins. FundingThis study was funded by an EPSRC/British Heart Foundation co-funded Imperial Institute of Chemical Biology (ICB) Centre for Doctoral Training (CDT) PhD studentship (EP/S023518/1), a project grant of the British Heart Foundation (PG19/13/34247) and the Deutsche Forschungsgemeinschaft (DE1482/9-1). Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSSeveral biallelic missense and nonsense variants in BVES (POPDC1) have been described and are associated with heart and skeletal muscle disease. Skeletal muscle biopsies of homozygous carriers of these variants display a loss of sarcolemmal localisation of POPDC1 and POPDC2. Added value of this studyWe demonstrate that POPDC1 and POPDC2 form a heteromeric complex and that complex formation is required for plasma membrane trafficking of POPDC proteins. Transfection of different disease variants in HEK293 cells replicates their defective membrane targeting observed in biopsy material. Structural modelling and site-directed mutagenesis identifies an interface of strongly conserved hydrophobic residues in POPDC proteins, which likely mediate the interaction of POPDC proteins. Implications of all the available evidenceThese data provide novel insight into the membrane targeting requirements of POPDC proteins. We recommend testing the membrane targeting properties of any novel variant in POPDC isoforms using a newly developed co-transfection assay in HEK293 cells to characterise its pathogenicity. Our novel insight into the requirement of heterodimerization for proper membrane targeting may also offer novel opportunities to treat patients carrying mutations in POPDC proteins.

genetics↗

Metabolic demands of the posteromedial default mode network are shaped by dorsal attention and frontoparietal control networks

Although BOLD signal decreases in the default mode network (DMN) are commonly observed during attention-demanding tasks, their neurobiological underpinnings are not fully understood. Previous work has shown decreases but also increases in glucose metabolism that match with or dissociate from these BOLD signal decreases, respectively. To resolve this discrepancy, we analyzed functional PET/MRI data from 50 healthy subjects during the performance of the visuo-spatial processing game Tetris(R) and combined this with previously published data sets of working memory as well as visual and motor stimulation. Our findings show that the glucose metabolism of the posteromedial DMN is dependent on the metabolic demands of the correspondingly engaged task-positive brain networks. Specifically, the dorsal attention (involved in Tetris(R)) and frontoparietal networks (engaged during working memory) shape the glucose metabolism of the posteromedial DMN in opposing directions. External attention-demanding tasks lead to a downregulation of the posteromedial DMN with consistent decreases in the BOLD signal and glucose metabolism, whereas working memory is subject to metabolically expensive mechanisms of BOLD signal suppression. We suggest that the former finding is mediated by decreased glutamate signaling, while the latter results from active GABAergic inhibition, regulating the competition between self-generated and task-driven internal demands. The results demonstrate that the DMN relates to cognitive processing in a flexible manner and does not always act as a cohesive task-negative network in isolation.

neuroscience↗

Alteration of myocardial structure and function in RAF1associated Noonan syndrome: Insights from cardiac disease modeling based on patient-derived iPSCs

Noonan syndrome (NS), the most common among the RASopathies, is caused by germline variants in genes encoding components of the RAS-MAPK pathway. Distinct variants, including the recurrent Ser257Leu substitution in RAF1, are associated with severe hypertrophic cardiomyopathy (HCM). Here, we investigated the elusive mechanistic link between NS-associated RAF1S257L and HCM using three-dimensional cardiac bodies and bioartificial cardiac tissues generated from patient-derived induced pluripotent stem cells (iPSCs) harboring the pathogenic RAF1 c.770C>T missense change. We characterize the molecular, structural and functional consequences of aberrant RAF1 -associated signaling on the cardiac models. Ultrastructural assessment of the sarcomere revealed a shortening of the I-bands along the Z disc area in both iPSC-derived RAF1S257L cardiomyocytes, and myocardial tissue biopsies. The disease phenotype was partly reverted by using both MEK inhibition, and a gene-corrected isogenic RAF1L257S cell line. Collectively, our findings uncovered a direct link between a RASopathy gene variant and the abnormal sarcomere structure resulting in a cardiac dysfunction that remarkably recapitulates the human disease. These insights represent a basis to develop future targeted therapeutic approaches.

cell biology↗

Learning induces coordinated neuronal plasticity of metabolic demands and functional brain networks

The neurobiological basis of learning is reflected in adaptations of brain structure, network organization and energy metabolism. However, it is still unknown how different neuroplastic mechanisms act together and if cognitive advancements relate to general or task-specific changes. To address these questions, we tested how hierarchical network interactions contribute to improvements in the performance of a visuo-spatial processing task by employing simultaneous PET/MR neuroimaging before and after a 4-week learning period. We combined functional PET with metabolic connectivity mapping (MCM) to infer directional interactions across brain regions and subsequently performed simulations to disentangle the role of functional network dynamics and glucose metabolism. As a result, learning altered the top-down regulation of the salience network onto the occipital cortex, with increases in MCM at resting-state and decreases during task execution. Accordingly, a higher divergence between resting-state and task-specific effects was associated with better cognitive performance, indicating that these adaptations are complementary and both required for successful skill learning. Simulations further showed that changes at resting-state were dependent on glucose metabolism, whereas those during task performance were driven by functional connectivity between salience and visual networks. Referring to previous work, we suggest that learning establishes a metabolically expensive skill engram at rest, whose retrieval serves for efficient task execution by minimizing prediction errors between neuronal representations of brain regions on different hierarchical levels.

neuroscience↗

SARS-CoV-2 variants B.1.351 and B.1.1.248: Escape from therapeutic antibodies and antibodies induced by infection and vaccination

The global spread of SARS-CoV-2/COVID-19 is devastating health systems and economies worldwide. Recombinant or vaccine-induced neutralizing antibodies are used to combat the COVID-19 pandemic. However, recently emerged SARS-CoV-2 variants B.1.1.7 (UK), B.1.351 (South Africa) and B.1.1.248 (Brazil) harbor mutations in the viral spike (S) protein that may alter virus-host cell interactions and confer resistance to inhibitors and antibodies. Here, using pseudoparticles, we show that entry of UK, South Africa and Brazil variant into human cells is susceptible to blockade by entry inhibitors. In contrast, entry of the South Africa and Brazil variant was partially (Casirivimab) or fully (Bamlanivimab) resistant to antibodies used for COVID-19 treatment and was less efficiently inhibited by serum/plasma from convalescent or BNT162b2 vaccinated individuals. These results suggest that SARS-CoV-2 may escape antibody responses, which has important implications for efforts to contain the pandemic.

molecular biology↗

Serotonin modulates learning content-specific neuroplasticity of functional brain networks

Learning-induced neuroplastic changes, further modulated by content and setting, are mirrored in brain functional connectivity (FC). In animal models, serotonergic agents were shown to facilitate neuroplasticity. This is especially prominent during emotional relearning, such as fear extinction, which may translate to clinical improvements in human patients. To investigate this assumption, 99 healthy subjects underwent six weeks of emotional or non-emotional learning and subsequent relearning. Resting-state functional magnetic resonance imaging was performed before and after the learning phases to investigate changes in FC. During relearning, subjects received either a daily dose of the selective serotonin reuptake inhibitor (SSRI) escitalopram or placebo. Escitalopram intake modulated FC changes in a network comprising Brocas area, the medial prefrontal cortex, the right inferior temporal and left lingual gyrus. More specifically, escitalopram increased the bidirectional connectivity between medial prefrontal cortex and lingual gyrus for non-emotional and additionally the connectivity from medial prefrontal cortex to Brocas area for emotional relearning. The context-dependence of these effects supports the assumption that SSRIs in clinical practice might improve neuroplasticity rather than psychiatric symptoms per se. Correlations with learning behavior further point towards a relationship with extinction processes in relearning. These results demonstrate that escitalopram intake during relearning results in content-dependent network adaptations and support the conclusion that enhanced neuroplasticity might be the major underlying mechanism also in humans. Beyond expanding the complexities of learning, these findings emphasize the influence of external factors on serotonin-facilitated neuroplasticity of the human brain.

neuroscience↗

No metabolic "default mode" of human brain function

The finding of reduced activity in the default mode network (DMN) during externally focused cognitive control has been highly influential to our understanding of human brain function, but deactivations have also prompted major questions of interpretation. Using hybrid functional PET-MR imaging, this study shows that fMRI task activations and deactivations do not reflect antagonistic patterns of synaptic metabolism. FMRI activations were accompanied by concomitant increases in metabolism during cognitive control, but, unlike the BOLD response, metabolism in the core DMN did not change between rest and task. Metabolic increases along the borders of the DMN during task performance further revealed a set of regions that guide engagement and suppression of neighboring networks during cognitive control. Collectively, dissociations between metabolism and BOLD signal specific to the DMN reveal functional heterogeneity in this network and demonstrate that BOLD deactivations during cognitive control should not be interpreted to reflect reduced synaptic activity.

neuroscience↗