Miracle-dz/UniFAR-FTUs huggingface dataset:
Synaptic Competition Enhances the Discrimination of Interfering Memories

Long-term plasticity is the primary mode of synaptic weight updating. However, other updating modes include modification of synaptic connections across neurons. The synaptic competition found during adult neurogenesis is an example. In this process, adult-born neurons are integrated into the existing neuronal pool by competing with mature neurons for synaptic connections from the entorhinal cortex. Evidence suggests that adult neurogenesis is critical for discriminating similar memories, i.e., memories with considerable interferences. This computational study aims to link synaptic competition with pattern separation. We show that synaptic competition and neuronal maturation are crucial for separating considerably overlapping memory patterns. Furthermore, we demonstrate that a feed-forward neural network trained by a competition-based learning rule can outperform a multi-layer perceptron trained by the backpropagation algorithm, especially when the sample size is small. These results unveil the functional implications and potential applications of synaptic competition in neural computation.
A hybrid structure determination approach to investigate the druggability of the nucleocapsid protein of SARS-CoV-2

The ongoing pandemic caused by SARS-CoV-2 has called for concerted efforts to generate new insights into the biology of betacoronaviruses to inform drug screening and development. Here, we establish a workflow to determine the RNA recognition and druggability of the nucleocapsid N-protein of SARS-CoV-2, a highly abundant protein crucial for the viral life cycle. We use a synergistic method that combines NMR spectroscopy and protein-RNA cross-linking coupled to mass spectrometry to quickly determine the RNA binding of two RNA recognition domains of the N-protein. Finally, we explore the druggability of these domains by performing an NMR fragment screening. This workflow identified small molecule chemotypes that bind to RNA binding interfaces and that have promising properties for further drug development.
Drug resistance-associated mutations in Plasmodium UBP-1 disrupt ubiquitin hydrolysis

Deubiquitinating enzymes function to cleave ubiquitin moieties from modified proteins, serving to maintain the pool of free ubiquitin in the cell while simultaneously impacting the fate and function of a target protein. Like all eukaryotes, Plasmodium parasites rely on the dynamic addition and removal of ubiquitin for their own growth and survival. While humans possess around 100 DUBs, Plasmodium contains ∼20 putative ubiquitin hydrolases, many of which bear little to no resemblance to those of other organisms. In this study, we characterize PfUBP-1, a large ubiquitin hydrolase unique to Plasmodium spp that has been linked to endocytosis and drug resistance. We demonstrate its ubiquitin activity, linkage specificity and assess the repercussions of point mutations associated with drug resistance on catalytic activity and parasite fitness.
Expanding the repertoire of human tandem repeat RNA-binding proteins

Protein regions consisting of arrays of tandem repeats are known to bind other molecular partners, including nucleic acid molecules. Although the interactions between repeat proteins and DNA are already widely explored, studies characterising tandem repeat RNA-binding proteins are lacking. We performed a large-scale analysis of human proteins devoted to expanding the knowledge about tandem repeat proteins experimentally reported as RNA-binding molecules. This work is timely because of the release of a full set of accurate structural models for the human proteome amenable to repeat detection using structural methods. We identified 219 tandem repeat proteins that bind RNA molecules and characterised the overlap between repeat regions and RNA-binding regions as a first step towards assessing their functional relationship. Our results showed that the combination of sequence and structural methods finds more tandem repeat proteins than either method alone. We observed differences in the characteristics of regions predicted as repetitive by sequence-based or structure-based computational methods in terms of their sequence composition, their functions and their protein domains.
Ensemble Machine Learning to “Boost” Ubiquitination-sites Prediction

Ubiquitination-site prediction is an important task because ubiquitination is a critical regulatory function for many biological processes such as proteasome degradation, DNA repair and transcription, signal transduction, endocytoses, and sorting. However, the highly dynamic and reversible nature of ubiquitination makes it difficult to experimentally identify specific ubiquitination sites. In this paper, we explore the possibility of improving the prediction of ubiquitination sites using ensemble machine learning methods including Random Forrest (RF), Adaptive Boosting (ADB), Gradient Boosting (GB), and eXtreme Gradient Boosting (XGB). By doing grid search with the four ensemble methods and six comparison non-ensemble learning methods including Naïve Base (NB), Logistic Regression (LR), Decision Trees (DT), Support Vector Machine (SVM), LASSO, and K-Nearest Neighbor (KNN), we find that all the four ensemble methods significantly outperform one or more non-ensemble methods included in this study. XGB outperforms three out of the six non-ensemble methods that we included; ADB and RF both outperform two of the six non-ensemble methods; GB outperforms one non-ensemble method. Comparing the four ensemble methods among themselves. GB performs the worst; XGB and ADB are very comparable in terms of prediction, but ADB beats XGB by far in terms of both the unit model training time and total running time. Both XGB and ADB tend to do better than RF in terms of prediction, but RF has the shortest unit model training time out of the three. In addition, we notice that ADB tends to outperform XGB when dealing with small-scale datasets, and RF can outperform either ADB or XGB when data are less balanced. Interestingly, we find that SVM, LR, and LASSO, three of the six non-ensemble methods included, perform comparably with all the ensemble methods. Based on this study, ensemble learning is a promising approach to ignificantly improving ubiquitination-site prediction using protein segment data.
ATP hydrolysis tunes specificity of a AAA+ protease

In bacteria, AAA+ proteases such as Lon and ClpXP degrade substrates with exquisite specificity. These machines capture the energy of ATP hydrolysis to power unfolding and degradation of target substrates. Here, we show that a mutation in the ATP binding site of ClpX shifts protease specificity to promote degradation of normally Lon-restricted substrates. However, this ClpX mutant is worse at degrading ClpXP targets, suggesting an optimal balance in substrate preference for a given protease that is surprisingly easy to alter. In vitro, wildtype ClpXP also degrades Lon-restricted substrates more readily when ATP levels are reduced, similar to the shifted specificity of mutant ClpXP, which has altered ATP hydrolysis kinetics. Based on these results, we suggest that rates of ATP hydrolysis not only power substrate unfolding and degradation, but also tune protease specificity. We consider various models for this effect based on emerging structures of AAA+ machines showing conformationally distinct states. Graphical Abstract eTOC AAA+ proteases, such as Lon and ClpXP, select distinct targets for degradation to maintain proteostasis. Mahmoud et al. show that ATP hydrolysis can tune substrate specificity of ClpX, allowing ClpX to degrade Lon-restricted substrates under limiting ATP conditions or in the presence of a ClpX mutant. Highlights A Walker B mutation of the AAA+ protease ClpX alters substrate specificity ClpX mutant degrades new substrates but degrades canonical substrates less well Decreasing ATP levels enhances ClpXP mediated degradation of some classes of substrates ATP-induced changes in conformational states accompany alterations in ClpX specificity
Phenotypic Profiling of Macrocyclic Lactones on Parasitic Schistosoma Flatworms

Macrocyclic lactones are front-line therapies for parasitic roundworm infections; however, there are no comprehensive studies on the activity of this drug class against parasitic flatworms. Ivermectin is well known to be inactive against flatworms. ABSTRACT Macrocyclic lactones are front-line therapies for parasitic roundworm infections; however, there are no comprehensive studies on the activity of this drug class against parasitic flatworms. Ivermectin is well known to be inactive against flatworms. However, the structure-activity relationship of macrocyclic lactones may vary across phyla, and it is entirely possible other members of this drug class do in fact show antiparasitic activity on flatworms. For example, there are several reports hinting at the anti-schistosomal activity of doramectin and moxidectin. To explore this class further, we developed an automated imaging assay combined with measurement of lactate levels from worm media. This assay was applied to the screening of 21 macrocyclic lactones (avermectins, milbemycins, and others such as spinosyns) against adult schistosomes. These in vitro assays identified several macrocyclic lactones (emamectin, milbemycin oxime, and the moxidectin metabolite 23-ketonemadectin) that caused contractile paralysis and lack of lactate production. Several of these were also active against miracidia, which infect the snail intermediate host. Hits prioritized from these in vitro assays were administered to mice harboring patent schistosome infections. However, no reduction in worm burden was observed. Nevertheless, these data show the utility of a multiplexed in vitro screening platform to quantitatively assess drug action and exclude inactive compounds from a chemical series before proceeding to in vivo studies. While the prototypical macrocyclic lactone ivermectin displays minimal activity against adult Schistosoma mansoni, this family of compounds does contain schistocidal compounds which may serve as a starting point for development of new anti-flatworm chemotherapies.
Differential gene expression and mitonuclear incompatibilities in fast- and slow-developing inter-population Tigriopus californicus hybrids

Mitochondrial functions are intimately reliant on proteins and RNAs encoded in both the nuclear and mitochondrial genomes, leading to inter-genomic coevolution within taxa. Hybridization can break apart coevolved mitonuclear genotypes, resulting in decreased mitochondrial performance and reduced fitness. This hybrid breakdown is an important component of outbreeding depression and early-stage reproductive isolation. However, the mechanisms contributing to mitonuclear interactions remain poorly resolved. Here we scored variation in developmental rate (a proxy for fitness) among reciprocal F2 inter-population hybrids of the intertidal copepod Tigriopus californicus, and used RNA sequencing to assess differences in gene expression between fast- and slow-developing hybrids. In total, differences in expression associated with developmental rate were detected for 2,925 genes, whereas only 135 genes were differentially expressed as a result of differences in mitochondrial genotype. Up-regulated expression in fast developers was enriched for genes involved in chitin-based cuticle development, oxidation-reduction processes, hydrogen peroxide catabolic processes and mitochondrial respiratory chain complex I. In contrast, up-regulation in slow developers was enriched for DNA replication, cell division, DNA damage and DNA repair. Eighty-four nuclear-encoded mitochondrial genes were differentially expressed between fast- and slow-developing copepods, including twelve subunits of the electron transport system (ETS) which all had higher expression in fast developers than in slow developers. Nine of these genes were subunits of ETS complex I. Our results emphasize the major roles that mitonuclear interactions within the ETS, particularly in complex I, play in hybrid breakdown, and resolve strong candidate genes for involvement in mitonuclear interactions.
Organization of Upstream ESCRT Machinery at the HIV-1 Budding Site

In the late stages of the HIV-1 life cycle, membrane localization and self-assembly of the Gag polyproteins induce membrane deformation and budding. However, release of the immature virion requires direct interaction between Gag lattice and upstream ESCRT machinery at the budding site, followed by assembly of the downstream ESCRT-III factors, culminating in membrane scission. In this work, using “bottom-up” coarse-grained (CG) molecular dynamics (MD) simulations we investigated the interactions between Gag and different upstream ESCRT components to delineate the molecular organization of proteins at the membrane neck of the HIV-1 budding site. We developed CG models of upstream ESCRT proteins and HIV-1 structural protein Gag based on experimental structural data and extensive all-atom MD simulations. We find that ESCRT-I proteins bound to the immature Gag lattice can recruit multiple copies of ESCRT-II coating the membrane neck. ESCRT-I can effectively oligomerize to higher-order complexes both in absence of ESCRT-II and when multiple copies of ESCRT-II are localized at the bud neck. The ESCRT-I/II supercomplexes observed in our simulations exhibit predominantly extended conformations. Importantly, the ESCRT-I/II supercomplex modulates the membrane mechanical properties at the budding site by decreasing the overall Gaussian curvature of membrane neck. Our findings serve to elucidate a network of interactions between the upstream ESCRT machinery, immature Gag lattice, and membrane bud neck that regulate the protein assemblies and enable bud neck constriction.
Multiscale compression-induced restructuring of stacked lipid bilayers: From buckling delamination to molecular packing

Lipid membranes in nature adapt and reconfigure to changes in composition, temperature, humidity, and mechanics. For instance, the oscillating mechanical forces on lung cells and alveoli influence membrane synthesis and structure during breathing. However, despite advances in the understanding of lipid membrane phase behavior and mechanics of tissue, there is a critical knowledge gap regarding the response of lipid membranes to micromechanical forces. Most studies of lipid membrane mechanics use supported lipid bilayer systems missing the structural complexity of pulmonary lipids in alveolar membranes comprising multi-bilayer interconnected stacks. Here, we elucidate the collective response of the major component of pulmonary lipids to strain in the form of multi-bilayer stacks supported on flexible elastomer substrates. We utilize X-ray diffraction, scanning probe microscopy, confocal microscopy, and molecular dynamics simulation to show that lipid multilayered films both in gel and fluid states evolve structurally and mechanically in response to compression at multiple length scales. Specifically, compression leads to increased disorder of lipid alkyl chains comparable to the effect of cholesterol on gel phases as a direct result of the formation of nanoscale undulations in the lipid multilayers, also inducing buckling delamination and enhancing multi-bilayer alignment. We propose this cooperative short- and long-range reconfiguration of lipid multilayered films under compression constitutes a mechanism to accommodate stress and substrate topography. Our work raises fundamental insights regarding the adaptability of complex lipid membranes to mechanical stimuli. This is critical to several technologies requiring mechanically reconfigurable surfaces such as the development of electronic devices interfacing biological materials.
Decapentaplegic ligand ensures niche space restriction inside and outside of Drosophila testicular niche

Drosophila male germline stem cells (GSCs) reside at the tip of the testis and surround a cluster of niche cells, called the hub. It has been believed that the Decapentaplegic (Dpp) ligand, secreted from the hub, only activates stem cells in close proximity, but not differentiating cells spaced one-cell layer away. However the range of Dpp diffusion is unknown. Here, using genetically encoded nanobodies, called Morphotrap, we physically block Dpp diffusion outside of the niche without interfering with niche-stem cell signaling. Surprisingly, we found that Dpp has an opposite effect on GSCs and on their immediate progenies, such that it promotes self-renewal of GSCs, while ensuring the differentiation of their daughter cells. When the signal from the diffusing fraction of Dpp was specifically blocked, differentiating daughter cells frequently dedifferentiated, suggesting that Dpp ensures asymmetric outcome of stem cells both inside and outside of the niche. We further show that these distinct signaling outcomes are achieved by the same canonical BMP pathway, through the typeI receptor, Thickveins (Tkv), and the downstream effector, Mothers against Dpp (Mad). Given the broad requirement of BMP pathway in many stem cell systems, we propose that such a self-contained behavior of a stem cell ligand may be a common mechanism to ensure special restriction of stem-cell niche.
The EMMA Project

EMMA stands for Electron Model of Muon Accelerator and is expected to demonstrate that a nonscaling FFAG can accelerate a beam quickly with large acceptance in both transverse and longitudinal directions, that is necessary for muon acceleration. We will study resonance crossing and outside bucket acceleration in detail. The concept of EMMA has been considered and designed over the last several years. Recently the project was funded and construction started at the STFC Daresbury Laboratory in April 2007. The first beam should be in the ring in summer 2009. We will discuss its backgrounds and aims, beam dynamics issues, and current hardware status.
Practical scan-length considerations for mapping upper limb movements to the somatosensory/motor cortex at 7T

The relationship between motor cortex (M1) and upper limb movements has been investigated extensively using functional MRI (fMRI). While most research has focused on applications, very few studies have focused on practical aspects related to developing the fMRI protocol. Thus, the effect of scan length on M1 activations during various upper limb movements remains unclear. Scan length constraints are important for conducting motor experiments within a 60- or 90-min scan session. We targeted this gap by studying 7T fMRI activations in a male participant while performing eight different upper limb movements (of the fingers, wrist, and elbow) across 16 task runs (8 with the left arm, 8 with the right arm, 88 mins total fMRI duration). Standard activation analyses were performed (Z>3.1, p<0.01, cluster thresholded) independently for 14 different cases (2 runs through 8 runs, left and right arm) and compared. We found diminishing returns with higher number of runs (activations gradually plateaued with runs). We observed two clusters of movements, one with generally higher activation (more activated voxels and higher Z-stats) and the other with lower activation. To achieve similar statistical power, movements with lower activation required longer scanning (more runs). Based on these observations, we propose a ‘one size does not fit all’ practical protocol within a 60-, 75-, or 90-min scan session, wherein different number of runs are assigned for different movements. Our study could benefit researchers who are designing upper limb fMRI experiments.
Does ivermectin treatment for endemic hookworm infection alter the gut microbiota of endangered Australian sea lion pups?

The gut microbiota is essential for the development and maintenance of the hosts’ immune system, and disturbances can impact host health. This study aimed to determine if topical ivermectin treatment for endemic hookworm (Uncinaria sanguinis) infection in Australian sea lion (Neophoca cinerea) pups causes gut microbial changes. The gut microbiota was characterised for untreated (control) (n=23) and treated (n=23) pups sampled during the 2019 and 2020/21 breeding seasons at Seal Bay, Kangaroo Island. Samples were collected pre- and post-treatment on up to four occasions. The gut microbiota of both untreated (control) and treated pups was dominated by five bacterial phyla, Fusobacteria, Firmicutes, Proteobacteria, Actinobacteria and Bacteroides. There was a significant difference in alpha diversity between treatment groups in 2020/21 (p = 0.008), with greater diversity in treated pups. Modelling the impact of host factors on beta diversity revealed that pup ID accounted for most of the variation with pup ID, age and capture being the only significant contributors to microbial variation (p < 0.05). There were no statistically significant differences in microbial composition between treatment groups in both breeding seasons, indicating that ivermectin treatment did not alter microbial composition. To our knowledge, this is the first study to consider the impact of parasitic treatment on overall diversity and composition of the gut microbiota. Importantly, the lack of compositional changes in the gut microbiota with topical treatment support the utility of topical ivermectin as a safe and minimally invasive management strategy to enhance pup survival in this endangered species. Importance Disturbances to the gut microbiota in early life stages can have life-long impacts on host health. Australian sea lions are endangered and declining, and pups are endemically infected with hookworm (Uncinaria sanguinis) which contributes to pup mortality. Treatment with topical ivermectin has been shown to effectively eliminate hookworm infection and to improve pup health, but the impact on the gut microbiota was previously unknown, representing a key knowledge gap. The results from this study show that topical ivermectin treatment does not alter the gut microbiota of Australian sea lion pups, indicating that it is a safe and minimally invasive treatment that can aid in disease mitigation and conservation of this endangered species.
Intercode hexahedral meshing from Eulerian to Lagrangian simulations

In this chapter, we deal with the problem of mesh conversion for coupling lagrangian and eulerian simulation codes. More speciﬁcally, we focus on hexahedral meshes, which are known as pretty diﬃcult to generate and handle. Starting from an eulerian hexahedral mesh, i.e. a hexahedral mesh where each cell contains several materials, we provide a full-automatic process that generates a lagrangian hexahedral mesh, i.e. a hexahedral mesh where each cell contains a single material. This process is simulation-driven in the meaning that the we guarantee that the generated mesh can be used by a simulation code (minimal quality for individual cells), and we try and preserve the volume and location of each material as best as possible. In other words, the obtained lagrangian mesh ﬁts the input eulerian mesh with high-ﬁdelity. To do it, we interleave several advanced meshing treatments – mesh smoothing, mesh reﬁnement, sheet insertion, discrete material reconstruction, discrepancy computation, in a fully integrated pipeline. Our solution is evaluated on 2D and 3D examples representative of CFD simulation (Computational Fluid Dynamics).