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A candidate gene cluster for the bioactive natural product gyrophoric acid in lichen-forming fungi
(2022)
Natural products of lichen-forming fungi are structurally diverse and have a variety of medicinal properties. Despite this, they a have limited implementation in industry, because the corresponding genes remain unknown for most of the natural products. Here we implement a long-read sequencing and bioinformatic approach to identify the biosynthetic gene cluster of the bioactive natural product gyrophoric acid (GA). Using 15 high-quality genomes representing nine GA-producing species of the lichen-forming fungal genus Umbilicaria, we identify the most likely GA cluster and investigate cluster gene organization and composition across the nine species. Our results show that GA clusters are promiscuous within Umbilicaria, with only three genes that are conserved across species, including the PKS gene. In addition, our results suggest that the same cluster codes for different but structurally similar NPs, i.e., GA, umbilicaric acid and hiascic acid, bringing new evidence that lichen metabolite diversity is also generated through regulatory mechanisms at the molecular level. Ours is the first study to identify the most likely GA cluster, and thus provides essential information to open new avenues for biotechnological approaches to producing and modifying GA and similar lichen-derived compounds. We show that bioinformatics approaches are useful in linking genes and potentially associated natural products. Genome analyses help unlocking the pharmaceutical potential of organisms such as lichens, which are biosynthetically diverse but slow growing, and difficult to cultivate due to their symbiotic nature.
The human brain achieves visual object recognition through multiple stages of nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output M/EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
Glutathione (GSH) is the main determinant of intracellular redox potential and participates in multiple cellular signaling pathways. Achieving a detailed understanding of intracellular GSH trafficking and regulation depends on the development of tools to map GSH compartmentalization and intra-organelle fluctuations. Herein, we present a new GSH sensing platform, TRaQ-G, for live-cell imaging. This small-molecule/protein hybrid sensor possesses a unique reactivity turn-on mechanism that ensures that the small molecule is only sensitive to GSH in the desired location. Furthermore, TRaQ-G can be fused to a fluorescent protein of choice to give a ratiometric response. Using TRaQ-G-mGold, we demonstrated that the nuclear and cytosolic GSH pools are independently regulated during cell proliferation. We also used this sensor, in combination with roGFP, to quantify redox potential and GSH concentration simultaneously in the endoplasmic reticulum. Finally, by exchanging the fluorescent protein, we created a near-infrared, targetable and quantitative GSH sensor.
Although new advances in neuroscience allow the study of vocal communication in awake animals, substantial progress in the processing of vocalizations has been made from brains of anaesthetized preparations. Thus, understanding how anaesthetics affect neuronal responses is of paramount importance. Here, we used electrophysiological recordings and computational modelling to study how the auditory cortex of bats responds to vocalizations under anaesthesia and in wakefulness. We found that multifunctional neurons that process echolocation and communication sounds were affected by ketamine anaesthesia in a manner that could not be predicted by known anaesthetic effects. In wakefulness, acoustic contexts (preceding echolocation or communication sequences) led to stimulus-specific suppression of lagging sounds, accentuating neuronal responses to sound transitions. However, under anaesthesia, communication contexts (but not echolocation) led to a global suppression of responses to lagging sounds. Such asymmetric effect was dependent on the frequency composition of the contexts and not on their temporal patterns. We constructed a neuron model that could replicate the data obtained in vivo. In the model, anaesthesia modulates spiking activity in a channel-specific manner, decreasing responses of cortical inputs tuned to high-frequency sounds and increasing adaptation in the respective cortical synapses. Combined, our findings obtained in vivo and in silico reveal that ketamine anaesthesia does not reduce uniformly the neurons’ responsiveness to low and high frequency sounds. This effect depends on combined mechanisms that unbalance cortical inputs and ultimately affect how auditory cortex neurons respond to natural sounds in anaesthetized preparations.
Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, relative duration and relative distance in time of two sequentially-organized events —standard S, with constant duration, and comparison C, varying trial-by-trial— are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer ISI helps counteracting such serial distortion effect only the constant S is in first position, but not if the unpredictable C is in first position. These results suggest the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. We simulated our behavioral results with a Bayesian model and replicated the finding that participants disproportionately expand first-position dynamic (unpredictable) short events. Our results clarify the mechanics generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones.
The neural mechanisms that unfold when humans form a large group defined by an overarching context, such as audiences in theater or sports, are largely unknown and unexplored. This is mainly due to the lack of availability of a scalable system that can record the brain activity from a significantly large portion of such an audience simultaneously. Although the technology for such a system has been readily available for a long time, the high cost as well as the large overhead in human resources and logistic planning have prohibited the development of such a system. However, during the recent years reduction in technology costs and size have led to the emergence of low-cost, consumer-oriented EEG systems, developed primarily for recreational use. Here by combining such a low-cost EEG system with other off-the-shelve hardware and tailor-made software, we develop in the lab and test in a cinema such a scalable EEG hyper-scanning system. The system has a robust and stable performance and achieves accurate unambiguous alignment of the recorded data of the different EEG headsets. These characteristics combined with small preparation time and low-cost make it an ideal candidate for recording large portions of audiences.
Orientation hypercolumns in the visual cortex are delimited by the repeating pinwheel patterns of orientation selective neurons. We design a generative model for visual cortex maps that reproduces such orientation hypercolumns as well as ocular dominance maps while preserving retinotopy. The model uses a neural placement method based on t–distributed stochastic neighbour embedding (t–SNE) to create maps that order common features in the connectivity matrix of the circuit. We find that, in our model, hypercolumns generally appear with fixed cell numbers independently of the overall network size. These results would suggest that existing differences in absolute pinwheel densities are a consequence of variations in neuronal density. Indeed, available measurements in the visual cortex indicate that pinwheels consist of a constant number of ∼30, 000 neurons. Our model is able to reproduce a large number of characteristic properties known for visual cortex maps. We provide the corresponding software in our MAPStoolbox for Matlab.
Difficulty producing intelligible speech is a common and debilitating symptom of Parkinson’s disease (PD). Yet, both the robust evaluation of speech impairments and the identification of the affected brain systems are challenging. We examine the spectral and spatial definitions of the functional neuropathology underlying reduced speech quality in patients with PD using a new approach to characterize speech impairments and a novel brain-imaging marker. We found that the interactive scoring of speech impairments in PD (N=59) is reliable across non-expert raters, and better related to the hallmark motor and cognitive impairments of PD than automatically-extracted acoustical features. By relating these speech impairment ratings to neurophysiological deviations from healthy adults (N=65), we show that articulation impairments in patients with PD are robustly predicted from aberrant activity in the left inferior frontal cortex, and that functional connectivity of this region with somatomotor cortices mediates the influence of cognitive decline on speech deficits.
Targeted protein degradation is a drug modality represented by compounds that recruit a target to an E3 ubiquitin ligase to promote target ubiquitination and proteasomal degradation. Historically, the field distinguishes monovalent degraders from bifunctional degraders (PROTACs) that connect target and ligase via separate binding ligands joined via a linker1–4. Here, we elucidate the mechanism of action of a PROTAC-like degrader of the transcriptional coactivator BRD4, composed of a BRD4 ligand linked to a ligand for the E3 ligase CRL4DCAF15. Using orthogonal CRISPR/Cas9 screens we identify the degrader activity is independent of DCAF15, and relies on a different CRL4 substrate receptor, DCAF16. We demonstrate an intrinsic affinity between BRD4 and DCAF16, which is dependent on the tandem bromodomains of BRD4 and further increased by the degrader without physically engaging DCAF16 in isolation. Structural characterization of the resulting ternary complex reveals both BRD4 bromodomains are bivalently engaged in cis by the degrader and are bound to DCAF16 through several interfacial BRD4-DCAF16 and degrader-DCAF16 contacts. Our findings demonstrate that intramolecularly bridging domains can confer glue-type stabilization of intrinsic target-E3 interactions, and we propose this as a general strategy to modulate the surface topology of target proteins to nucleate co-opting of E3 ligases or other cellular effector proteins for effective proximity-based pharmacology.
Anisotropic flow and flow fluctuations of identified hadrons in Pb–Pb collisions at √sNN = 5.02 TeV
(2022)
The first measurements of elliptic flow of π±, K±, p+p¯¯¯, K0S, Λ+Λ¯¯¯¯, ϕ, Ξ−+Ξ+, and Ω−+Ω+ using multiparticle cumulants in Pb−Pb collisions at sNN−−−√ = 5.02 TeV are presented. Results obtained with two- (v2{2}) and four-particle cumulants (v2{4}) are shown as a function of transverse momentum, pT, for various collision centrality intervals. Combining the data for both v2{2} and v2{4} also allows us to report the first measurements of the mean elliptic flow, elliptic flow fluctuations, and relative elliptic flow fluctuations for various hadron species. These observables probe the event-by-event eccentricity fluctuations in the initial state and the contributions from the dynamic evolution of the expanding quark-gluon plasma. The characteristic features observed in previous pT-differential anisotropic flow measurements for identified hadrons with two-particle correlations, namely the mass ordering at low pT and the approximate scaling with the number of constituent quarks at intermediate pT, are similarly present in the four-particle correlations and the combinations of v2{2} and v2{4}. In addition, a particle species dependence of flow fluctuations is observed that could indicate a significant contribution from final state hadronic interactions. The comparison between experimental measurements and CoLBT model calculations, which combine the various physics processes of hydrodynamics, quark coalescence, and jet fragmentation, illustrates their importance over a wide pT range.
Measurements of elliptic (v2) and triangular (v3) flow coefficients of π±, K±, p+p¯¯¯, K0S, and Λ+Λ¯¯¯¯ obtained with the scalar product method in Xe-Xe collisions at sNN−−−√ = 5.44 TeV are presented. The results are obtained in the rapidity range |y|<0.5 and reported as a function of transverse momentum, pT, for several collision centrality classes. The flow coefficients exhibit a particle mass dependence for pT<3 GeV/c, while a grouping according to particle type (i.e., meson and baryon) is found at intermediate transverse momenta (3< pT <8 GeV/c). The magnitude of the baryon v2 is larger than that of mesons up to pT = 6 GeV/c. The centrality dependence of the shape evolution of the pT-differential v2 is studied for the various hadron species. The v2 coefficients of π±, K±, and p+p¯¯¯ are reproduced by MUSIC hydrodynamic calculations coupled to a hadronic cascade model (UrQMD) for pT<1 GeV/c. A comparison with vn measurements in the corresponding centrality intervals in Pb-Pb collisions at sNN−−−√ = 5.02 TeV yields an enhanced v2 in central collisions and diminished value in semicentral collisions.
The measurement of the azimuthal-correlation function of prompt D mesons with charged particles in pp collisions at s√ = 5.02 TeV and p-Pb collisions at sNN−−−√ = 5.02 TeV with the ALICE detector at the LHC is reported. The D0, D+, and D∗+ mesons, together with their charge conjugates, were reconstructed at midrapidity in the transverse momentum interval 3 < pT < 24 GeV/c and correlated with charged particles having pT > 0.3 GeV/c and pseudorapidity |η|< 0.8. The properties of the correlation peaks appearing in the near- and away-side regions (for Δφ≈ 0 and Δφ≈π, respectively) were extracted via a fit to the azimuthal correlation functions. The shape of the correlation functions and the near- and away-side peak features are found to be consistent in pp and p-Pb collisions, showing no modifications due to nuclear effects within uncertainties. The results are compared with predictions from Monte Carlo simulations performed with the PYTHIA, POWHEG+PYTHIA, HERWIG, and EPOS 3 event generators.
We have investigated the systematic differences introduced when performing a Bayesian-inference analysis of the equation of state of neutron stars employing either variable- or constant-likelihood functions. The former have the advantage that it retains the full information on the distributions of the measurements, making an exhaustive usage of the data. The latter, on the other hand, have the advantage of a much simpler implementation and reduced computational costs. In both approaches, the EOSs have identical priors and have been built using the sound-speed parameterization method so as to satisfy the constraints from X-ray and gravitationalwaves observations, as well as those from Chiral Effective Theory and perturbative QCD. In all cases, the two approaches lead to very similar results and the 90%-confidence levels are essentially overlapping. Some differences do appear, but in regions where the probability density is extremely small and are mostly due to the sharp cutoff set on the binary tidal deformability Λ˜ ≤ 720 employed in the constant-likelihood analysis. Our analysis has also produced two additional results. First, a clear inverse correlation between the normalized central number density of a maximally massive star, nc,TOV/ns, and the radius of a maximally massive star, RTOV. Second, and most importantly, it has confirmed the relation between the chirp mass Mchirp and the binary tidal deformability Λ˜. The importance of this result is that it relates a quantity that is measured very accurately, Mchirp, with a quantity that contains important information on the micro-physics, Λ˜. Hence, once Mchirp is measured in future detections, our relation has the potential of setting tight constraints on Λ˜.
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.
Highlights
HER2 exhibits heterogeneous motion in the plasma membrane
The fraction of immobile HER2 correlates with phosphorylation levels
Diffusion properties serve as proxies for HER2 activation
HER2 exhibits ligand-specific activation strength and temporal profiles
The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown. Here, we generated large stochastic populations of biophysically realistic hippocampal granule cell models comparing those with all 15 ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were more frequent and more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve target excitability.
Hydrogen is a promising fuel in a carbon-neutral economy, and many efforts are currently undertaken to produce hydrogen. One of the challenges is to store and transport the highly explosive gas in a safe and easy way. One option that is intensively analyzed by chemists and biologists is the conversion of hydrogen and CO2 to formic acid, the liquid organic hydrogen carrier. Here, we demonstrate for the first time that a bio-based system, using Acetobacterium woodii as the biocatalyst, allows multiple cycles of bi-directional hydrogenation of CO2 to formic acid in one bioreactor. The process was kept running over 2 weeks producing and oxidizing 330 mM formic acid in total. Unwanted side-product formation of acetic acid was prevented through metabolic engineering of the organism. The demonstrated process design can be considered as a future “bio-battery” for the reversible storage of electrons in the form of H2 in formic acid, a versatile compound.
The NVX-CoV2373-vaccine has recently been licensed, although data on vaccine-induced humoral and cellular immunity towards the parental strain and variants of concern (VOCs) in comparison to dual-dose mRNA-regimens are limited. In this observational study including 66 participants, we show that NVX-CoV2373-induced IgG-levels were lower than after vaccination with BNT162b2 or mRNA-1273 (n=22 each, p=0.006). Regardless of the vaccine and despite different IgG-levels, neutralizing activity towards VOCs was highest for Delta, followed by BA.2 and BA.1. Interestingly, spike-specific CD8 T-cell levels after NVX-CoV2373-vaccination were significantly lower and were detectable in 3/22 (14%) individuals only. In contrast, spike-specific CD4 T-cells were induced in 18/22 (82%) individuals. However, CD4 T-cell levels were lower (p<0.001), had lower CTLA-4 expression (p<0.0001) and comprised less multifunctional cells co-expressing IFNγ, TNFαα and IL-2 (p=0.0007) as compared to mRNA-vaccinated individuals. Unlike neutralizing antibodies, NVX-CoV2373-induced CD4 T cells cross-reacted to all tested VOCs from Alpha to Omicron, which may hold promise to protect from severe disease.
Correlations between mean transverse momentum [pT] and anisotropic flow coefficients v2 or v3 are measured as a function of centrality in Pb−Pb and Xe−Xe collisions at sNN−−−√=5.02 TeV and 5.44 TeV, respectively, with ALICE. In addition, the recently proposed higher-order correlation between [pT], v2, and v3 is measured for the first time, which shows an anticorrelation for the presented centrality ranges. These measurements are compared with hydrodynamic calculations using IP-Glasma and TRENTo initial-state shapes, the former based on the Color Glass Condensate effective theory with gluon saturation, and the latter a parameterized model with nucleons as the relevant degrees of freedom. The data are better described by the IP-Glasma rather than the TRENTo based calculations. In particular, Trajectum and JETSCAPE predictions, both based on the TRENTo initial state model but with different parameter settings, fail to describe the measurements. As the correlations between [pT] and vn are mainly driven by the correlations of the size and the shape of the system in the initial state, these new studies pave a novel way to characterize the initial state and help pin down the uncertainty of the extracted properties of the quark−gluon plasma recreated in relativistic heavy-ion collisions.
Measurements of event-by-event fluctuations of charged-particle multiplicities in Pb-Pb collisions at sNN−−−√ = 2.76 TeV using the ALICE detector at the CERN Large Hadron Collider (LHC) are presented in the pseudorapidity range |η|<0.8 and transverse momentum 0.2<pT<2.0 GeV/c. The amplitude of the fluctuations is expressed in terms of the variance normalized by the mean of the multiplicity distribution. The η and pT dependences of the fluctuations and their evolution with respect to collision centrality are investigated. The multiplicity fluctuations tend to decrease from peripheral to central collisions. The results are compared to those obtained from HIJING and AMPT Monte Carlo event generators as well as to experimental data at lower collision energies. Additionally, the measured multiplicity fluctuations are discussed in the context of the isothermal compressibility of the high-density strongly-interacting system formed in central Pb-Pb collisions.
Recent pT-integrated cross section measurements of the ground-state charm mesons and baryons, D0, D+, D+s, Λ+c, and Ξ0c, are used to evaluate the charm fragmentation fractions and production cross section per unit of rapidity at midrapidity (|y|<0.5), in pp collisions at s√=5.02 TeV at the LHC. The latter is dσcc¯¯¯/dy||y|<0.5 =1165 ±44(stat)+134−101(syst) μb. These measurements were obtained for the first time in hadronic collisions at the LHC including the charm baryon states, recently measured by ALICE at midrapidity. The charm fragmentation fractions differ significantly from the values measured in e+e− and ep collisions, providing evidence of the dependence of the parton-to-hadron fragmentation fractions on the collision system, indicating that the assumption of their universality is not supported by the measured cross sections. An increase of a factor of about 3.3 for the fragmentation fraction for the Λ+c with a significance of 5σ between the values obtained in pp collisions and those obtained in e+e− (ep) collisions is reported. The fragmentation fraction for the Ξ0c was obtained for the first time in any collision system. The measured fragmentation fractions were used to update the cc¯¯ cross sections per unit of rapidity at |y|<0.5 at s√=2.76 and 7 TeV, which are about 40% higher than the previously published results. The data were compared with perturbative-QCD calculations and lie at the upper edge of the theoretical bands.