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Proton-powered c-ring rotation in mitochondrial ATP synthase is crucial to convert the transmembrane protonmotive force into torque to drive the synthesis of ATP. Capitalizing on recent cryo-EM structures, we aim at a structural and energetic understanding of how functional directional rotation is achieved. We performed multi-microsecond atomistic simulations to determine the free energy profiles along the c-ring rotation angle before and after the arrival of a new proton. Our results reveal that rotation proceeds by dynamic sliding of the ring over the a-subunit surface, during which interactions with conserved polar residues stabilize distinct intermediates. Ordered water chains line up for a Grotthuss-type proton transfer in one of these intermediates. After proton transfer, a high barrier prevents backward rotation and an overall drop in free energy favors forward rotation, ensuring the directionality of c-ring rotation required for the thermodynamically disfavored ATP synthesis. The essential arginine of the a-subunit stabilizes the rotated configuration through a salt-bridge with the c-ring. Overall, we describe a complete mechanism for the rotation step of the ATP synthase rotor, thereby illuminating a process critical to all life at atomic resolution.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. In other words, any two signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks, and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy for auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
Objects that are congruent with a scene are recognised more efficiently than objects that are incongruent. Further, semantic integration of incongruent objects elicits a stronger N300/N400 EEG component. Yet, the time course and mechanisms of how contextual information supports access to semantic object information is unclear. We used computational modelling and EEG to test how context influences semantic object processing. Using representational similarity analysis, we established that EEG patterns dissociated between objects in congruent or incongruent scenes from around 300 ms. By modelling semantic processing of objects using independently normed properties, we confirm that the onset of semantic processing of both congruent and incongruent objects is similar (∼150 ms). Critically, after ∼275 ms, we discover a difference in the duration of semantic integration, lasting longer for incongruent compared to congruent objects. These results constrain our understanding of how contextual information supports access to semantic object information.
We explore the potential of optically-pumped magnetometers (OPMs) to infer the laminar origins of neural activity non-invasively. OPM sensors can be positioned closer to the scalp than conventional cryogenic MEG sensors, opening an avenue to higher spatial resolution when combined with high-precision forward modelling. By simulating the forward model projection of single dipole sources onto OPM sensor arrays with varying sensor densities and measurement axes, and employing sparse source reconstruction approaches, we find that laminar inference with OPM arrays is possible at relatively low sensor counts at moderate to high signal-to-noise ratios (SNR). We observe improvements in laminar inference with increasing spatial sampling densities and number of measurement axes. Surprisingly, moving sensors closer to the scalp is less advantageous than anticipated - and even detrimental at high SNRs. Biases towards both the superficial and deep surfaces at very low SNRs and a notable bias towards the deep surface when combining empirical Bayesian beamformer (EBB) source reconstruction with a whole-brain analysis pose further challenges. Adequate SNR through appropriate trial numbers and shielding, as well as precise co-registration, is crucial for reliable laminar inference with OPMs.
Sharp wave-ripples (SPW-Rs) are a hippocampal network phenomenon critical for memory consolidation and planning. SPW-Rs have been extensively studied in the adult brain, yet their developmental trajectory is poorly understood. While SPWs have been recorded in rodents shortly after birth, the time point and mechanisms of ripple emergence are still unclear. Here, we combine in vivo electrophysiology with optogenetics and chemogenetics in 4 to 12 days-old mice to address this knowledge gap. We show that ripples are robustly detected and induced by light stimulation of ChR2-transfected CA1 pyramidal neurons only from postnatal day (P) 10 onwards. Leveraging a spiking neural network model, we mechanistically link the maturation of inhibition and ripple emergence. We corroborate these findings by reducing ripple rate upon chemogenetic silencing of CA1 interneurons. Finally, we show that early SPW-Rs elicit a more robust prefrontal cortex response then SPWs lacking ripples. Thus, development of inhibition promotes ripples emergence.
Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. Here, we hypothesized that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Population analysis revealed that neuronal responses converged to a low dimensional subspace for natural but not for synthetic images. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the dominant low dimensional subspace, suggesting an alignment between the attentional and natural stimulus variance. The alignment was pronounced for late evoked responses but not for early transient responses of V1 neurons, supporting the notion that top-down feedback was required. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. brain signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded redundant and synergistic information during auditory prediction error processing. In both tasks, we observed multiple patterns of synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between auditory and frontal regions. Using a brain-constrained neural network, we simulated the spatio-temporal patterns of synergy and redundancy observed in the experimental results and further demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback and feedforward connections. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
Anticipating future events is a key computational task for neuronal networks. Experimental evidence suggests that reliable temporal sequences in neural activity play a functional role in the association and anticipation of events in time. However, how neurons can differentiate and anticipate multiple spike sequences remains largely unknown. We implement a learning rule based on predictive processing, where neurons exclusively fire for the initial, unpredictable inputs in a spiking sequence, leading to an efficient representation with reduced post-synaptic firing. Combining this mechanism with inhibitory feedback leads to sparse firing in the network, enabling neurons to selectively anticipate different sequences in the input. We demonstrate that intermediate levels of inhibition are optimal to decorrelate neuronal activity and to enable the prediction of future inputs. Notably, each sequence is independently encoded in the sparse, anticipatory firing of the network. Overall, our results demonstrate that the interplay of self-supervised predictive learning rules and inhibitory feedback enables fast and efficient classification of different input sequences.
Proton-powered c-ring rotation in mitochondrial ATP synthase is crucial to convert the transmembrane protonmotive force into torque to drive the synthesis of ATP. Capitalizing on recent cryo-EM structures, we aim at a structural and energetic understanding of how functional directional rotation is achieved. We performed multi-microsecond atomistic simulations to determine the free energy profiles along the c-ring rotation angle before and after the arrival of a new proton. Our results reveal that rotation proceeds by dynamic sliding of the ring over the a-subunit surface, during which interactions with conserved polar residues stabilize distinct intermediates. Ordered water chains line up for a Grotthuss-type proton transfer in one of these intermediates. After proton transfer, a high barrier prevents backward rotation and an overall drop in free energy favors forward rotation, ensuring the directionality of c-ring rotation required for the thermodynamically disfavored ATP synthesis. The essential arginine of the a-subunit stabilizes the rotated configuration through a salt-bridge with the c-ring. Overall, we describe a complete mechanism for the rotation step of the ATP synthase rotor, thereby illuminating a process critical to all life at atomic resolution.
The MICOS complex subunit MIC13 is essential for mitochondrial cristae organization. Mutations in MIC13 cause severe mitochondrial hepato-encephalopathy displaying defective cristae morphology and loss of the MIC10-subcomplex. Here we identified SLP2 as a novel interacting partner of MIC13 and decipher a critical role of SLP2 for MICOS assembly at distinct steps. SLP2 provides a large interaction hub for MICOS subunits and loss of SLP2 imparted YME1L-mediated proteolysis of MIC26 and drastic alterations in cristae morphology. We further identified a MIC13-specific role in stabilizing the MIC10-subcomplex via a MIC13-YME1L axis. SLP2 together with the stabilized MIC10-subcomplex promotes efficient assembly of the MIC60-subcomplex forming the MICOS-MIB complex. Consistently, super-resolution nanoscopy showed a dispersed distribution of the MIC60 in cells lacking SLP2 and MIC13. Our study reveals converging and interdependent assembly pathways for the MIC10- and MIC60-subcomplexes which are controlled in two ways, the MIC13-YME1L and the SLP2-YME1L axes, revealing mechanistic insights of these factors in cristae morphogenesis. These results will be helpful in understanding the human pathophysiology linked to mutations in MIC13 or its interaction partners.
Each lifecycle of the Hepatitis C virus (HCV) produces structural and non-structural (NS) proteins in equimolar. Structural proteins were either assembled or degraded by host proteolysis systems, while NS proteins remain inside the host cells and don’t accumulate. Therefore, they must be degraded. Here, NS3 and NS5A half-lives were quantified in the presence of autolysosome and proteasome different modulators. Inhibitors of both systems increased the half-life, while inducers decreased the half-life. Furthermore, polyubiquitination of NS3 and NS5A was observed. Additionally, their intracellular co-localization with autolysosome (LAMP2) and proteasome (PSMB5) was observed, and inhibitors of both systems increased the degree of co-localization. A better understanding of NS protein degradation might help to improve medical interventions during HCV infections in the future.
Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both ≤ 63 μm) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population density and structure, and induced resting egg production. The terminal population size was 28–42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures.
Environmental Implications While microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research.
Candida boidinii NAD+-dependent formate dehydrogenase (CbFDH) has gained significant attention for its potential applications in the production of biofuels and various industrial chemicals from inorganic carbon dioxide. The present study reports the atomic X-ray crystal structures of the wild-type CbFDH at cryogenic and ambient temperatures as well as Val120Thr mutant at cryogenic temperature determined at the Turkish Light Source "Turkish DeLight". The structures reveal new hydrogen bonds between Thr120 and water molecules in the mutant CbFDH's active site, suggesting increased stability of the active site and more efficient electron transfer during the reaction. Further experimental data is needed to test these hypotheses. Collectively, our findings provide invaluable insights into future protein engineering efforts that could potentially enhance the efficiency and effectiveness of CbFDH.
The fundamental structure of cortical networks arises early in development prior to the onset of sensory experience. However, how endogenously generated networks respond to the onset of sensory experience, and how they form mature sensory representations with experience remains unclear. Here we examine this "nature-nurture transform" using in vivo calcium imaging in ferret visual cortex. At eye-opening, visual stimulation evokes robust patterns of cortical activity that are highly variable within and across trials, severely limiting stimulus discriminability. Initial evoked responses are distinct from spontaneous activity of the endogenous network. Visual experience drives the development of low-dimensional, reliable representations aligned with spontaneous activity. A computational model shows that alignment of novel visual inputs and recurrent cortical networks can account for the emergence of reliable visual representations.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
The selective autophagy of mitochondria is linked to mitochondrial quality control and is critical to a healthy organism. Ubiquitylation is sometimes needed for marking damaged mitochondria for disposal but also for governing the expression and turnover of critical regulatory proteins. We have conducted a CRISPR/Cas9 screen of human E3 ubiquitin ligases for influence on mitophagy under both basal cell culture conditions and following acute mitochondrial depolarisation. We identify two Cullin RING ligases, VHL and FBXL4 as the most profound negative regulators of basal mitophagy. Here we show that these converge through control of the mitophagy adaptors BNIP3 and BNIP3L/NIX, but that this is achieved through different mechanisms. FBXL4 suppression of BNIP3 and NIX levels is mediated via direct interaction and protein destabilisation rather than suppression of HIF1α-mediated transcription. Depletion of NIX but not BNIP3 is sufficient to restore mitophagy levels. Our study enables a full understanding of the aetiology of early onset mitochondrial encephalomyopathy that is supported by analysis of a disease associated mutation. We further show that the compound MLN4924, which globally interferes with Cullin RING ligase activity, is a strong inducer of mitophagy which can provide a research tool in this context as well as a candidate therapeutic agent for conditions linked to mitochondrial quality control.
An excess of J/ψ yield at very low transverse momentum (pT<0.3 GeV/c), originating from coherent photoproduction, is observed in peripheral and semicentral hadronic Pb−Pb collisions at a center-of-mass energy per nucleon pair of sNN−−−√=5.02 TeV. The measurement is performed with the ALICE detector via the dimuon decay channel at forward rapidity (2.5<y<4). The nuclear modification factor at very low pT and the coherent photoproduction cross section are measured as a function of centrality down to the 10% most central collisions. These results extend the previous study at sNN−−−√=2.76 TeV, confirming the clear excess over hadronic production in the pT range 0−0.3 GeV/c and the centrality range 70−90%, and establishing an excess with a significance greater than 5σ also in the 50−70% and 30−50% centrality ranges. The results are compared with earlier measurements at sNN−−−√=2.76 TeV and with different theoretical predictions aiming at describing how coherent photoproduction occurs in hadronic interactions with nuclear overlap.
Seed harvesting from wild plant populations is key for ecological restoration, but may threaten the persistence of source populations. Consequently, several countries have set guidelines limiting the proportions of harvestable seeds. Here, we use high-resolution data from 298 plant species to model the demographic consequences of seed harvesting. We find that the current guidelines only protect some species, but are insufficient or overly restrictive for others. We show that the maximum possible fraction of seed harvesting is strongly associated with harvesting frequency and generation time of the target species, ranging from 100% in long-lived species to <1% in the most annuals. Our results provide quantitative basis to guide seed harvesting legislation based on species’ generation time and harvesting regime.
Molecular mechanisms of inorganic-phosphate release from the core and barbed end of actin filaments
(2023)
The release of inorganic phosphate (Pi) from actin filaments constitutes a key step in their regulated turnover, which is fundamental to many cellular functions. However, the molecular mechanisms underlying Pi release from both the core and barbed end of actin filaments remain unclear. Here, we combine cryo-EM with molecular dynamics simulations and in vitro reconstitution to demonstrate how actin releases Pi through a ‘molecular backdoor’. While constantly open at the barbed end, the backdoor is predominantly closed in filament-core subunits and only opens transiently through concerted backbone movements and rotameric rearrangements of residues close to the nucleotide binding pocket. This mechanism explains why Pi escapes rapidly from the filament end and yet slowly from internal actin subunits. In an actin variant associated with nemaline myopathy, the backdoor is predominantly open in filament-core subunits, resulting in greatly accelerated Pi release after polymerization and filaments with drastically shortened ADP-Pi caps. This demonstrates that the Pi release rate from F-actin is controlled by steric hindrance through the backdoor rather than by the disruption of the ionic bond between Pi and Mg2+ at the nucleotide-binding site. Our results provide the molecular basis for Pi release from actin and exemplify how a single, disease-linked point mutation distorts the nucleotide state distribution and atomic structure of the actin filament.
The fundamental structure of cortical networks arises early in development prior to the onset of sensory experience. However, how endogenously generated networks respond to the onset of sensory experience, and how they form mature sensory representations with experience remains unclear. Here we examine this ‘nature-nurture transform’ using in vivo calcium imaging in ferret visual cortex. At eye-opening, visual stimulation evokes robust patterns of cortical activity that are highly variable within and across trials, severely limiting stimulus discriminability. Initial evoked responses are distinct from spontaneous activity of the endogenous network. Visual experience drives the development of low-dimensional, reliable representations aligned with spontaneous activity. A computational model shows that alignment of novel visual inputs and recurrent cortical networks can account for the emergence of reliable visual representations.
SpikeShip: a method for fast, unsupervised discovery of high-dimensional neural spiking patterns
(2023)
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences requires a suitable dissimilarity measure to spiking patterns, which can then be used for clustering and decoding. Here, we present a new dissimilarity measure based on optimal transport theory called SpikeShip, which compares multi-neuron spiking patterns based on all the relative spike-timing relationships among neurons. SpikeShip computes the optimal transport cost to make all the relative spike timing relationships (across neurons) identical between two spiking patterns. We show that this transport cost can be decomposed into a temporal rigid translation term, which captures global latency shifts, and a vector of neuron-specific transport flows, which reflect inter-neuronal spike timing differences. SpikeShip can be effectively computed for high-dimensional neuronal ensembles, has a low (linear) computational cost that has the same order as the spike count, and is sensitive to higher-order correlations. Furthermore SpikeShip is binless, can handle any form of spike time distributions, is not affected by firing rate fluctuations, can detect patterns with a low signal-to-noise ratio, and can be effectively combined with a sliding window approach. We compare the advantages and differences between SpikeShip and other measures like SPIKE and Victor-P urpura distance. We applied SpikeShip to large-scale Neuropixel recordings during spontaneous activity and visual encoding. We show that high-dimensional spiking sequences detected via SpikeShip reliably distinguish between different natural images and different behavioral states. These spiking sequences carried complementary information to conventional firing rate codes. SpikeShip opens new avenues for studying neural coding and memory consolidation by rapid and unsupervised detection of temporal spiking patterns in high-dimensional neural ensembles.
The multistep PROTAC (PROteolysis TArgeting Chimeras) degradation process poses challenges for their rational development, as rate limiting steps determining PROTAC efficiency remain largely unknown. Moreover, the slow throughput of currently used endpoint assays does not allow the comprehensive analysis of larger series of PROTACs. Here we developed cell-based assays using NanoLuciferase and HaloTags, that allow measuring PROTAC induced degradation and ternary complex formation kinetics and stability in cells. Using PROTACs developed for degradation of WDR5, the characterization of the mode of action of these PROTACs in the early degradation cascade revealed a key role of ternary complex formation and stability. Comparing a series of ternary complex crystal structures highlighted the importance of an efficient E3-target interface for ternary complex stability. The developed assays outline a strategy for the rational optimization of PROTACs using a series of live cell assays monitoring key steps of the early PROTAC induced degradation pathway.
Significance The multistep PROTAC induced degradation process of a POI poses a significant challenge for the rational design of these bifunctional small molecules as critical steps that limit PROTAC efficacy cannot be easily assayed at required throughput. In addition, the cellular location of the POI may pose additional challenges as some cellular compartments, such as the nucleus, may not be easily reached by PROTAC molecules and the targeted E3 ligases may not be present in this cellular compartment. We propose therefore a comprehensive assay panel for PROTACs evaluation in cellular environments using a sensor system that allows continuous monitoring of the protein levels of the endogenous POI. We developed a cell line expressing WDR5 from its endogenous locus in fusion with a small sequence tag (HiBIT) that can be reconstituted to functional NanoLuciferase (NLuc). This system allowed continuous monitoring of endogenous WDR5 levels in cells and together with HaloTag system also the continuous monitoring of ternary complex (E3, WDR5 and PROTAC) formation. As this assay can be run at high throughput, we used this versatile system monitoring three diverse chemical series of WDR5 PROTACs that markedly differ in their degradation properties. Monitoring cell penetration, binary complex formation (PROTAC-WDR5 and PROTAC-VHL) as well as ternary complex formation we found that PROTAC efficiency highly correlated with synergy of ternary complex formation in cells. This study represents a first data set on diverse PROTACs studying this property in cellulo and it outlines a strategy for the rational optimization of PROTACs. It also provided kinetic data on ternary complex assembly and dissociation that may serve as a benchmark for future studies utilizing also kinetic properties for PROTAC development. Comparative structural studies revealed larger PROTAC mediated interaction surfaces for PROTACs that efficiently formed ternary complexes highlighting the utility of structure based optimization of PROTAC induced ternary complexes in the development process.
Autophagosome biogenesis requires a localized perturbation of lipid membrane dynamics and a unique protein-lipid conjugate. Autophagy-related (ATG) proteins catalyze this biogenesis on cellular membranes, but the underlying molecular mechanism remains unclear. Focusing on the final step of the protein-lipid conjugation reaction, ATG8/LC3 lipidation, we show how membrane association of the conjugation machinery is organized and fine-tuned at the atomistic level. Amphipathic α-helices in ATG3 proteins (AHATG3) are found to have low hydrophobicity and to be less bulky. Molecular dynamics simulations reveal that AHATG3 regulates the dynamics and accessibility of the thioester bond of the ATG3∼LC3 conjugate to lipids, allowing covalent lipidation of LC3. Live cell imaging shows that the transient membrane association of ATG3 with autophagic membranes is governed by the less bulky- hydrophobic feature of AHATG3. Collectively, the unique properties of AHATG3 facilitate protein- lipid bilayer association leading to the remodeling of the lipid bilayer required for the formation of autophagosomes.
Cyclic di-AMP is the only known essential second messenger in bacteria and archaea, regulating different proteins indispensable for numerous physiological processes. In particular, it controls various potassium and osmolyte transporters involved in osmoregulation. In Bacillus subtilis, the K+/H+ symporter KimA of the KUP family is inactivated by c-di-AMP. KimA sustains survival at potassium limitation at low external pH by mediating K+ ions uptake. However, at elevated intracellular K+ concentrations, further K+ accumulation would be toxic. In this study, we reveal the molecular basis of how c-di-AMP binding inhibits KimA. We report cryo-EM structures of KimA with bound c-di-AMP in detergent solution and reconstituted in amphipols. By combining structural data with functional assays and molecular dynamics simulations we reveal how c-di-AMP modulates transport. We show that an intracellular loop in the transmembrane domain interacts with c-di-AMP bound to the adjacent cytosolic domain. This reduces the mobility of transmembrane helices at the cytosolic side of the K+ binding site and therefore traps KimA in an inward-occluded conformation.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in three common awake marmosets and investigated to what extent event-related-potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy for auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesize that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we show that attention enhances the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Attentional enhancement of stimulus decodability from population responses occurs in low dimensional spaces, as revealed by principal component analysis, suggesting an alignment between the attentional and the natural stimulus variance. Moreover, natural scenes produce stimulus-specific oscillatory responses in V1, whose power undergoes a global shift from low to high frequencies with attention. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.
Glioblastoma is a very aggressive tumor and represents the most common primary brain malignancy. Key characteristics include its high resistance against conventional treatments, such as radio- and chemotherapy and its diffuse tissue infiltration, preventing complete surgical resection. The analysis of migration and invasion processes in a physiological microenvironment allows for enhanced understanding of these processes and can lead to improved therapeutic approaches. Here, we combine two state-of-the-art techniques, adult organotypic brain tissue slice culture (OTC) and light sheet fluorescence microscopy (LSFM) of cleared tissues in a combined method termed OTCxLSFM. Using this methodology, we can show that glioblastoma tissue infiltration can be effectively blocked through treatment with arsenic trioxide, as well as genetic depletion of the tetraspanin, transmembrane receptor CD9. With our analysis-pipeline we gain single-cell level, three-dimensional information, as well as insights into the morphological appearance of the tumor cells.
VASP is a member of the Enabled/VASP protein family that is involved in cortical actin dynamics and may also contribute to the formation of gap junctions. In vessels, gap junctional coupling allows the transfer of signals along the vessel wall and coordinates vascular behavior. Moreover, VASP is reportedly a mediator of NO-induced inhibition of platelet aggregation. Therefore, we hypothesized that VASP exerts also important physiologic functions in arterioles. We examined the spread of vasodilations enabled by gap junctional coupling in endothelial cells as well as NO-induced arteriolar dilations in VASP-deficient mice by intravital microscopy of the microcirculation in a skeletal muscle in anesthetized mice. Conducted dilations were initiated by brief, locally confined stimulation of the arterioles with acetylcholine. The maximal diameters of the arterioles under study ranged from 30 to 40 μm. Brief stimulation with acetylcholine induced a short dilation at the local site that was also observed at remote, upstream sites without an attenuation of the amplitude up to a distance of 1.2 mm in control animals (wild-type). In contrast, remote dilations were reduced in VASP-deficient mice despite a similar local dilation indicating an impairment of conducted dilations. Superfusion of NOdonors induced a concentration-dependent dilation in wild-type mice. However, these dilations were slightly reduced in VASP-deficient animals. In contrast, dilations induced by the endothelial stimulator acetylcholine were fully preserved in VASP-deficient mice. In summary, this study suggests that VASP exerts critical functions in arteriolar diameter control. It is crucial for the conduction of dilator signals along the endothelial cell layer. The impairment possibly reflects a perturbed formation of gap junctions in the endothelial cell membrane. VASP also participates in the full dilatory potential of NOdonors although the effect of its deficiency is only subtle. In contrast, VASP is not required for dilations initiated by endothelial stimulation which are mediated in the murine microcirculation by an EDH-mechanism.
Rhythmic flicker stimulation has gained interest as a treatment for neurodegenerative diseases and a method for frequency tagging neural activity in human EEG/MEG recordings. Yet, little is known about the way in which flicker-induced synchronization propagates across cortical levels and impacts different cell types. Here, we used Neuropixels to simultaneously record from LGN, V1, and CA1 while presenting visual flicker stimuli at different frequencies. LGN neurons showed strong phase locking up to 40Hz, whereas phase locking was substantially weaker in V1 units and absent in CA1 units. Laminar analyses revealed an attenuation of phase locking at 40Hz for each processing stage, with substantially weaker phase locking in the superficial layers of V1. Gamma-rhythmic flicker predominantly entrained fast-spiking interneurons. Optotagging experiments showed that these neurons correspond to either PV+ or narrow-waveform Sst+ neurons. A computational model could explain the observed differences in phase locking based on the neurons’ capacitative low-pass filtering properties. In summary, the propagation of synchronized activity and its effect on distinct cell types strongly depend on its frequency.
Dendritic spines are crucial for excitatory synaptic transmission as the size of a spine head correlates with the strength of its synapse. The distribution of spine head sizes follows a lognormal-like distribution with more small spines than large ones. We analysed the impact of synaptic activity and plasticity on the spine size distribution in adult-born hippocampal granule cells from rats with induced homo- and heterosynaptic long-term plasticity in vivo and CA1 pyramidal cells from Munc-13-1-Munc13-2 knockout mice with completely blocked synaptic transmission. Neither induction of extrinsic synaptic plasticity nor the blockage of presynaptic activity degrades the lognormal-like distribution but changes its mean, variance and skewness. The skewed distribution develops early in the life of the neuron. Our findings and their computational modelling support the idea that intrinsic synaptic plasticity is sufficient for the generation, while a combination of intrinsic and extrinsic synaptic plasticity maintains lognormal like distribution of spines.
The polarization of Λ and Λ¯ hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sNN−−−−√ = 200 GeV. The second harmonic results follow the emission angle dependence as expected due to elliptic flow, similar to that observed in Au+Au collisions. The polarization relative to the third harmonic event plane, measured for the first time, deviates from zero with 4.8σ significance in 20-60\% centrality for 1.1<pT<6.0 GeV/c and exhibits a similar dependence on the emission angle. These results indicate the formation of a complex vortical structure in the system that follows higher harmonic anisotropic flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild pT dependence. While the centrality dependence, except in peripheral collisions, is qualitatively consistent with hydrodynamic model calculations including thermal vorticity and shear contributions, the shape of the pT dependence is very different. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.
Non-coding variations located within regulatory elements may alter gene expression by modifying Transcription Factor (TF) binding sites and thereby lead to functional consequences like various traits or diseases. To understand these molecular mechanisms, different TF models are being used to assess the effect of DNA sequence variations, such as Single Nucleotide Polymorphisms (SNPs). However, few statistical approaches exist to compute statistical significance of results but they often are slow for large sets of SNPs, such as data obtained from a genome-wide association study (GWAS) or allele-specific analysis of chromatin data.
Results We investigate the distribution of maximal differential TF binding scores for general computational models that assess TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo data sets showed that our new approach improves on an existing method in terms of performance and speed. In applications on large sets of eQTL and GWAS SNPs we could illustrate the usefulness of the novel statistic to highlight cell type specific regulators and TF target genes.
Conclusions Our approach allows the evaluation of DNA changes that induce differential TF binding in a fast and accurate manner, permitting computations on large mutation data sets. An implementation of the novel approach is freely available at https://github.com/SchulzLab/SNEEP.
5-iodotubercidin sensitizes cells to RIPK1-dependent necroptosis by interfering with NFκB signaling
(2023)
Receptor-interacting protein kinases (RIPK) −1 and −3 are master regulators of cell fate decisions in response to diverse stimuli and are subjected to multiple checkpoint controls. Earlier studies have established the presence of distinct IKK1/2 and p38/MK2-dependent checkpoints which suppress RIPK1 activation by directly phosphorylating it at different residues. In the present study, we investigated TNF-induced death in MAPK-activated protein kinase 2 (MK2)-deficient cells and show that MK2-deficiency or inactivation predominantly results in necroptotic cell death, even in the absence of caspase inhibition. While MK2-deficient cells can be rescued from necroptosis by RIPK1 inhibitors, RIPK3 inhibition seems to revert the process triggering apoptosis. To understand the mechanism of this necroptosis switch, we screened a 149-compound kinase inhibitor library for compounds which preferentially sensitize MK2-deficient MEFs to TNF-induced cell death. The most potent inhibitor identified was 5-Iodotubericidin, an adenosine analogue acting as adenosine kinase and protein kinase inhibitor. 5-ITu also potentiated LPS-induced necroptosis when combined with MK2 inhibition in RAW264.7 macrophages. Further mechanistic studies revealed that 5-Iodotubericidin induces RIPK1-dependent necroptosis in the absence of MK2 activity by suppressing IKK signaling. The identification of this role for the multitarget kinase inhibitor 5-ITu in TNF-, LPS- and chemotherapeutics-induced necroptosis will have potential implications in RIPK1-targeted therapies.
The production of inclusive, prompt and non-prompt J/ψ was studied for the first time at midrapidity (−1.37<ycms<0.43) in p−Pb collisions at √sNN =8.16 TeV with the ALICE detector at the LHC. The inclusive J/ψ mesons were reconstructed in the dielectron decay channel in the transverse momentum (pT) interval 0<pT<14 GeV/c and the prompt and non-prompt contributions were separated on a statistical basis for pT>2 GeV/c. The study of the J/ψ mesons in the dielectron channel used for the first time in ALICE online single-electron triggers from the Transition Radiation Detector, providing a data sample corresponding to an integrated luminosity of 689±13μb−1. The proton−proton reference cross section for inclusive J/ψ was obtained based on interpolations of measured data at different centre-of-mass energies and a universal function describing the pT-differential J/ψ production cross sections. The pT-differential nuclear modification factors RpPb of inclusive, prompt, and non-prompt J/ψ are consistent with unity and described by theoretical models implementing only nuclear shadowing.
W±-boson production in p–Pb collisions at √sNN = 8.16 TeV and Pb–Pb collisions at √sNN = 5.02 TeV
(2023)
The production of the W± bosons measured in p−Pb collisions at a centre-of-mass energy per nucleon−nucleon collision sNN−−−−√=8.16 TeV and Pb−Pb collisions at √sNN=5.02 TeV with ALICE at the LHC is presented. The W± bosons are measured via their muonic decay channel, with the muon reconstructed in the pseudorapidity region −4<ημlab<−2.5 with transverse momentum pμT>10 GeV/c. While in Pb−Pb collisions the measurements are performed in the forward (2.5<yμcms<4) rapidity region, in p−Pb collisions, where the centre-of-mass frame is boosted with respect to the laboratory frame, the measurements are performed in the backward (−4.46<yμcms<−2.96) and forward (2.03<yμcms<3.53) rapidity regions. The W− and W+ production cross sections, lepton-charge asymmetry, and nuclear modification factors are evaluated as a function of the muon rapidity. In order to study the production as a function of the p−Pb collision centrality, the production cross sections of the W− and W+ bosons are combined and normalised to the average number of binary nucleon−nucleon collision ⟨Ncoll⟩. In Pb−Pb collisions, the same measurements are presented as a function of the collision centrality. Study of the binary scaling of the W±-boson cross sections in p−Pb and Pb−Pb collisions is also reported. The results are compared with perturbative QCD (pQCD) calculations, with and without nuclear modifications of the Parton Distribution Functions (PDFs), as well as with available data at the LHC. Significant deviations from the theory expectations are found in the two collision systems, indicating that the measurements can provide additional constraints for the determination of nuclear PDF (nPDFs) and in particular of the light-quark distributions.
The most precise measurements to date of the 3ΛH lifetime τ and Λ separation energy BΛ are obtained using the data sample of Pb-Pb collisions at √= 5.02 TeV collected by ALICE at the LHC. The 3ΛH is reconsNN structed via its charged two-body mesonic decay channel (3ΛH→ 3He + π− and the charge-conjugate process). The measured values τ=[253±11 (stat.)±6 (syst.)] ps and BΛ=[102±63 (stat.)±67 (syst.)] keV are compatible with predictions from effective field theories and confirm that the 3ΛH structure is consistent with a weakly-bound system.
HER2 belongs to the ErbB sub-family of receptor tyrosine kinases and regulates cellular proliferation and growth. Different from other ErbB receptors, HER2 has no known ligand. Activation occurs through heterodimerization with other ErbB receptors and their cognate ligands. This suggests several possible activation paths of HER2 with ligand-specific, differential response, which so far remained unexplored. Using single-molecule tracking and the diffusion profile of HER2 as a proxy for activity, we measured the activation strength and temporal profile in live cells. We found that HER2 is strongly activated by EGFR-targeting ligands EGF and TGFα, yet with a distinguishable temporal fingerprint. The HER4-targeting ligands EREG and NRGβ1 showed weaker activation of HER2, a preference for EREG, and a delayed response to NRGβ1. Our results indicate a selective ligand response of HER2 that may serve as a regulatory element. Our experimental approach is easily transferable to other membrane receptors targeted by multiple ligands.
The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both ≤ 63 μm) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 particles mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population size and structure and induced resting egg production. The terminal population size was 28–42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures.
Environmental Implications While microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research.
Motivation DNA CpG methylation (CpGm) has proven to be a crucial epigenetic factor in the gene regulatory system. Assessment of DNA CpG methylation values via whole-genome bisulfite sequencing (WGBS) is, however, computationally extremely demanding.
Results We present FAst MEthylation calling (FAME), the first approach to quantify CpGm values directly from bulk or single-cell WGBS reads without intermediate output files. FAME is very fast but as accurate as standard methods, which first produce BS alignment files before computing CpGm values. We present experiments on bulk and single-cell bisulfite datasets in which we show that data analysis can be significantly sped-up and help addressing the current WGBS analysis bottleneck for large-scale datasets without compromising accuracy.
Availability An implementation of FAME is open source and licensed under GPL-3.0 at https://github.com/FischerJo/FAME.
Human behaviour is inextricably linked to the interaction of emotion and cognition. For decades, emotion and cognition were perceived as separable processes, yet with mutual interactions. Recently, this differen-tiation has been challenged by more integrative approaches, but without addressing the exact neurophysiological basis of their interaction. Here, we aimed to uncover neurophysiological mechanisms of emotion-cognition interaction. We used an emotional Flanker task paired with EEG/FEM beamforming in a large cohort (N=121) of healthy human participants, obtaining high temporal and fMRI-equivalent spatial resolution. Spatially, emotion and cognition processing overlapped in the right inferior frontal gyrus (rIFG), specifically in pars triangularis. Temporally, emotion and cognition processing overlapped during the transition from emotional to cognitive processing, with a stronger interaction in β-band power leading to worse behavioral performance. Despite functionally segregated subdivisions in rIFG, frequency-specific information flowed extensively within IFG and top-down to visual areas (V2, Precuneus) – explaining the behavioral interference effect. Thus, for the first time we here show the neural mechanisms of emotion-cognition interaction in space, time, frequency and information transfer with high temporal and spatial resolution, revealing a central role for β-band activity in rIFG. Our results support the idea that rIFG plays a broad role in both inhibitory control and emotional interference inhibition as it is a site of convergence in both processes. Furthermore, our results have potential clinical implications for understanding dysfunctional emotion-cognition interaction and emotional interference inhibition in psychiatric disor-ders, e.g. major depression and substance use disorder, in which patients have difficulties in regulating emotions and executing inhibitory control.
Improved integration of single cell transcriptome data demonstrated on heart failure in mice and men
(2023)
Biomedical research frequently uses murine models to study disease mechanisms. However, the translation of these findings to human disease remains a significant challenge. In order to improve the comparability of mouse and human data, we present a cross-species integration pipeline for single-cell transcriptomic assays.
The pipeline merges expression matrices and assigns clear orthologous relationships. Starting from Ensembl ortholog assignments, we allocated 82% of mouse genes to unique orthologs by using additional publicly available resources such as Uniprot, and NCBI databases. For genes with multiple matches, we employed the Needleman-Wunsch global alignment based on either amino acid or nucleotide sequence to identify the ortholog with the highest degree of similarity.
The workflow was tested for its functionality and efficiency by integrating scRNA-seq datasets from heart failure patients with the corresponding mouse model. We were able to assign unique human orthologs to up to 80% of the mouse genes, utilizing the known 17,492 orthologous pairs. Curiously, the integration process enabled the identification of both common and unique regulatory pathways between species in heart failure.
In conclusion, our pipeline streamlines the integration process, enhances gene nomenclature alignment and simplifies the translation of mouse models to human disease. We have made the OrthoIntegrate R-package accessible on GitHub (https://github.com/MarianoRuzJurado/OrthoIntegrate), which includes the assignment of ortholog definitions for human and mouse, as well as the pipeline for integrating single cells.
Bacterial biosynthetic assembly lines, such as non-ribosomal peptide synthetases (NRPS) and polyketide synthases, are often subject of synthetic biology – because they produce a variety of natural products invaluable for modern pharmacotherapy. Acquiring the ability to engineer these biosynthetic assembly lines allows the production of artificial non-ribosomal peptides (NRP), polyketides, and hybrids thereof with new or improved properties. However, traditional bioengineering approaches have suffered for decades from their very limited applicability and, unlike combinatorial chemistry, are stigmatized as inefficient because they cannot be linked to the high-throughput screening platforms of the pharmaceutical industry. Although combinatorial chemistry can generate new molecules cheaper, faster, and in greater numbers than traditional natural product discovery and bioengineering approaches, it does not meet current medical needs because it covers only a limited biologically relevant chemical space. Hence, methods for high-throughput generation of new natural product-like compound libraries could provide a new avenue towards the identification of new lead compounds. To this end, prior to this work, we introduced an artificial synthetic NRPS type, referred to as type S NRPS, to provide a first-of-its-kind bicombinatorial approach to parallelized high-throughput NRP library generation. However, a bottleneck of these first two generations of type S NRPS was a significant drop in production yields. To address this issue, we applied an iterative optimization process that enabled titer increases of up to 55-fold compared to the non-optimized equivalents, restoring them to wild-type levels and beyond.
The European bison was saved from the brink of extinction due to considerable conservation efforts since the early 20th century. The current global population of > 9,500 individuals is the result of successful ex situ breeding based on a stock of only 12 founders, resulting in an extremely low level of genetic variability. Due to the low allelic diversity, traditional molecular tools, such as microsatellites, fail to provide sufficient resolution for accurate genetic assessments in European bison, let alone from non-invasive samples. Here, we present a SNP panel for accurate high-resolution genotyping of European bison, which is suitable for a wide variety of sample types. The panel accommodates 96 markers allowing for individual and parental assignment, sex determination, breeding line discrimination, and cross-species detection. Two applications were shown to be utilisable in further Bos species with potential conservation significance. The new SNP panel will allow to tackle crucial tasks in European bison conservation, including the genetic monitoring of reintroduced populations, and a molecular assessment of pedigree data documented in the world’s first studbook of a threatened species.
Dendritic spines are considered a morphological proxy for excitatory synapses, rendering them a target of many different lines of research. Over recent years, it has become possible to image simultaneously large numbers of dendritic spines in 3D volumes of neural tissue. In contrast, currently no automated method for spine detection exists that comes close to the detection performance reached by human experts. However, exploiting such datasets requires new tools for the fully automated detection and analysis of large numbers of spines. Here, we developed an efficient analysis pipeline to detect large numbers of dendritic spines in volumetric fluorescence imaging data. The core of our pipeline is a deep convolutional neural network, which was pretrained on a general-purpose image library, and then optimized on the spine detection task. This transfer learning approach is data efficient while achieving a high detection precision. To train and validate the model we generated a labelled dataset using five human expert annotators to account for the variability in human spine detection. The pipeline enables fully automated dendritic spine detection and reaches a near human-level detection performance. Our method for spine detection is fast, accurate and robust, and thus well suited for large-scale datasets with thousands of spines. The code is easily applicable to new datasets, achieving high detection performance, even without any retraining or adjustment of model parameters.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.
In humans, screams have strong amplitude modulations (AM) at 30 to 150 Hz. These AM correspond to the acoustic correlate of perceptual roughness. In bats, distress calls can carry AMs, which elicit heart rate increases in playback experiments. Whether amplitude modulation occurs in fearful vocalisations of other animal species beyond humans and bats remains unknown. Here we analysed the AM pattern of rats’ 22-kHz ultrasonic vocalisations emitted in a fear conditioning task. We found that the number of vocalisations decreases during the presentation of conditioned stimuli. We also observed that AMs do occur in rat 22-kHz vocalisations. AMs are stronger during the presentation of conditioned stimuli, and during escape behaviour compared to freezing. Our results suggest that the presence of AMs in vocalisations emitted could reflect the animal’s internal state of fear related to avoidance behaviour.