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G protein-coupled receptors (GPCRs) play a crucial role in modulating physiological responses and serve as the main drug target. Specifically, salmeterol and salbutamol which are used for the treatment of pulmonary diseases, exert their effects by activating the GPCR β2-adrenergic receptor (β2AR). In our study, we employed coarse-grained molecular dynamics simulations with the Martini 3 force field to investigate the dynamics of drug molecules in membranes in presence and absence of β2AR. Our simulations reveal that in more than 50% of the flip-flop events the drug molecules use the β2AR surface to permeate the membrane. The pathway along the GPCR surface is significantly more energetically favorable for the drug molecules, which was revealed by umbrella sampling simulations along spontaneous flip-flop pathways. Furthermore, we assessed the behavior of drugs with intracellular targets, such as kinase inhibitors, whose therapeutic efficacy could benefit from this observation. In summary, our results show that β2AR surface interactions can significantly enhance membrane permeation of drugs, emphasizing their potential for consideration in future drug development strategies.
Motivated by the question of the impact of selective advantage in populations with skewed reproduction mechanims, we study a Moran model with selection. We assume that there are two types of individuals, where the reproductive success of one type is larger than the other. The higher reproductive success may stem from either more frequent reproduction, or from larger numbers of offspring, and is encoded in a measure Λ for each of the two types. Our approach consists of constructing a Λ-asymmetric Moran model in which individuals of the two populations compete, rather than considering a Moran model for each population. Under certain conditions, that we call the "partial order of adaptation", we can couple these measures. This allows us to construct the central object of this paper, the Λ−asymmetric ancestral selection graph, leading to a pathwise duality of the forward in time Λ-asymmetric Moran model with its ancestral process. Interestingly, the construction also provides a connection to the theory of optimal transport. We apply the ancestral selection graph in order to obtain scaling limits of the forward and backward processes, and note that the frequency process converges to the solution of an SDE with discontinous paths. Finally, we derive a Griffiths representation for the generator of the SDE and use it to find a semi-explicit formula for the probability of fixation of the less beneficial of the two types.
The ALICE Collaboration reports a differential measurement of inclusive jet suppression using pp and Pb−Pb collision data at a center-of-mass energy per nucleon-nucleon collision sNN−−−√=5.02 TeV. Charged-particle jets are reconstructed using the anti-kT algorithm with resolution parameters R= 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and R= 0.2, 0.4, 0.6 in central (0−10%), semi-central (30−50%), and peripheral (60−80%) Pb−Pb collisions. A novel approach based on machine learning is employed to mitigate the influence of jet background. This enables measurements of inclusive jet suppression in new regions of phase space, including down to the lowest jet pT≥40 GeV/c at R=0.6 in central Pb−Pb collisions. This is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, derived cross section, and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet-quenching models with varying levels of agreement.
The two-particle momentum correlation functions between charm mesons (D∗± and D±) and charged light-flavor mesons (π± and K±) in all charge-combinations are measured for the first time by the ALICE Collaboration in high-multiplicity proton-proton collisions at a center-of-mass energy of s√=13 TeV. For DK and D∗K pairs, the experimental results are in agreement with theoretical predictions of the residual strong interaction based on quantum chromodynamics calculations on the lattice and chiral effective field theory. In the case of Dπ and D∗π pairs, tension between the calculations including strong interactions and the measurement is observed. For all particle pairs, the data can be adequately described by Coulomb interaction only, indicating a shallow interaction between charm and light-flavor mesons. Finally, the scattering lengths governing the residual strong interaction of the Dπ and D∗π systems are determined by fitting the experimental correlation functions with a model that employs a Gaussian potential. The extracted values are small and compatible with zero.
Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.
For genus g=r(r+1)2+1, we prove that via the forgetful map, the universal Prym-Brill-Noether locus Rrg has a unique irreducible component dominating the moduli space Rg of Prym curves.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2024)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
Isothermal titration calorimetry (ITC) is a widely used technique for the characterization of protein-protein and protein-ligand interactions. It provides information on the stoichiometry, affinity, and the thermodynamic driving forces of interactions. This chapter exemplifies the use of ITC to investigate interactions between human autophagy modifiers (LC3/GABARAP proteins) and their interaction partners, the LIR motif containing sequences. The purpose of this report is to present a detailed protocol for the production of LC3/GABARAP-interacting LIR peptides using E. coli expression systems. In addition, we outline the design of ITC experiments using the LC3/GABARAP:peptide interactions as an example. Comprehensive troubleshooting notes are provided to facilitate the adaptation of these protocols to different ligand-receptor systems. The methodology outlined for studying protein-ligand interactions will help to avoid common errors and misinterpretations of experimental results.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
Upon infection, human immunodeficiency virus (HIV-1) releases its cone-shaped capsid into the cytoplasm of infected T-cells and macrophages. As its largest known cargo, the capsid enters the nuclear pore complex (NPC), driven by interactions with numerous FG-repeat nucleoporins (FG-Nups). Whether NPCs structurally adapt to capsid passage and whether capsids are modified during passage remains unknown, however. Here, we combined super-resolution and correlative microscopy with cryo electron tomography and molecular simulations to study nuclear entry of HIV-1 capsids in primary human macrophages. We found that cytosolically bound cyclophilin A is stripped off capsids entering the NPC, and the capsid hexagonal lattice remains largely intact inside and beyond the central channel. Strikingly, the NPC scaffold rings frequently crack during capsid passage, consistent with computer simulations indicating the need for NPC widening. The unique cone shape of the HIV-1 capsid facilitates its entry into NPCs and helps to crack their rings.
Tree-related microhabitats (TreMs) describe the microhabitats that a tree can provide for a multitude of other taxonomic groups and have been proposed as an important indicator for forest biodiversity (Asbeck et al., 2021). So far, the focus of TreM studies has been on temperate forests, although many trees in the tropics harbour exceptionally high numbers of TreMs. In this study, TreMs in the lowland tropical forests of the Choco (Ecuador) and in the mountain tropical forests of Mount Kilimanjaro (Tanzania) were surveyed. Our results extend the existing typology of TreMs of Larrieu et al. (2018) to include tropical forests and enabled a comparison of the relative recordings and diversity of TreMs between tropical and temperate forests. A new TreM form, Root formations, and three new TreM groups, concavities build by fruits or leaves, dendrotelms, and root formations, were established. In total, 15 new TreM types in five different TreM groups were specified. The relative recordings of most TreMs were similar between tropical and temperate forests. However, ivy and lianas, and ferns were more common in the lowland rainforest than in temperate forests, and bark microsoil, limb breakage, and foliose and fruticose lichens in tropical montane forest than in lowland rainforest. Mountain tropical forests hosted the highest diversity for common and dominant TreM types, and lowland tropical forest the highest diversity for rare TreMs. Our extended typology of tree-related microhabitats can support studies of forest-dwelling biodiversity in tropical forests. Specifically, given the ongoing threat to tropical forests, TreMs can serve as an additional tool allowing rapid assessments of biodiversity in these hyperdiverse ecosystems.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
This Letter presents the first measurement of event-by-event fluctuations of the net number (difference between the particle and antiparticle multiplicities) of multistrange hadrons Ξ− and Ξ¯¯¯¯+ and its correlation with the net-kaon number using the data collected by the ALICE Collaboration in pp, p−Pb, and Pb−Pb collisions at a center-of-mass energy per nucleon pair sNN−−−√=5.02 TeV. The statistical hadronization model with a correlation over three units of rapidity between hadrons having the same and opposite strangeness content successfully describes the results. On the other hand, string-fragmentation models that mainly correlate strange hadrons with opposite strange quark content over a small rapidity range fail to describe the data.
he first measurement of 3ΛH and 3Λ¯¯¯¯H¯¯¯¯ differential production with respect to transverse momentum and centrality in Pb−Pb collisions at sNN−−−√=5.02~TeV is presented. The 3ΛH has been reconstructed via its two-charged-body decay channel, i.e., 3ΛH→3He+π−. A Blast-Wave model fit of the pT-differential spectra of all nuclear species measured by the ALICE collaboration suggests that the 3ΛH kinetic freeze-out surface is consistent with that of other nuclei. The ratio between the integrated yields of 3ΛH and 3He is compared to predictions from the statistical hadronisation model and the coalescence model, with the latter being favoured by the presented measurements.
First measurements of hadron(h)−Λ azimuthal angular correlations in p−Pb collisions at sNN−−−√ = 5.02 TeV using the ALICE detector at the LHC are presented. These correlations are used to separate the production of associated Λ baryons into three different kinematic regions, namely those produced in the direction of the trigger particle (near-side), those produced in the opposite direction (away-side), and those whose production is uncorrelated with the jet-axis (underlying event). The per-trigger associated Λ yields in these regions are extracted, along with the near- and away-side azimuthal peak widths, and the results are studied as a function of associated particle pT and event multiplicity. Comparisons with the DPMJET event generator and previous measurements of the ϕ(1020) meson are also made. The final results indicate that strangeness production in the highest multiplicity p−Pb collisions is enhanced relative to low multiplicity collisions in the jet-like regions, as well as the underlying event. The production of Λ relative to charged hadrons is also enhanced in the underlying event when compared to the jet-like regions. Additionally, the results hint that strange quark production in the away-side of the jet is modified by soft interactions with the underlying event.
Upon infection of host cells, Legionella pneumophila releases a multitude of effector enzymes into the cells cytoplasm that hijack a plethora of cellular activities, including the hosts ubiquitination pathways. Effectors belonging to the SidE-family are involved in non-canonical serine phosphoribosyl ubiquitination of host substrate proteins contributing to the formation of a Legionella-containing vacuole that is crucial in the onset of Legionnaires’ disease. This dynamic process is reversed by effectors called Dups that hydrolyse the phosphodiester in the phosphoribosyl ubiquitinated protein. We installed reactive warheads on chemically prepared ribosylated ubiquitin to generate a set of probes targeting these Legionella enzymes. In vitro tests on recombinant DupA revealed that a vinyl sulfonate warhead was most efficient in covalent complex formation. Mutagenesis and x-ray crystallography approaches were used to identify the site of covalent crosslinking to be an allosteric cysteine residue. The subsequent application of this probe highlights the potential to selectively enrich the Dup enzymes from Legionella-infected cell lysates.